Pe d i a t r i c I m a g i n g • O r i g i n a l R e s e a r c h Khawaja et al. Radiation Dose in Pediatric CT
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Pediatric Imaging Original Research
Simplifying Size-Specific Radiation Dose Estimates in Pediatric CT Ranish Deedar Ali Khawaja1 Sarabjeet Singh1 Beth Vettiyil1 Ruth Lim 2 Michael Gee1 Sjirk Westra2 Mannudeep K. Kalra1 Khawaja RDA, Singh S, Vettiyl B, et al.
Keywords: body diameter, body weight, pediatric CT, size-specific dose estimate DOI:10.2214/AJR.13.12191 Received November 5, 2013; accepted after revision April 25, 2014. 1 Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 25 New Chardon St, 4th Fl, Boston, MA 02114. Address correspondence to R. D. A. Khawaja ([email protected]). 2 Division of Pediatric Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
AJR 2015; 204:167–176 0361–803X/15/2041–167 © American Roentgen Ray Society
OBJECTIVE. Size-specific dose estimates (SSDEs) require manual measurement of torso diameters for individual patients—anteroposterior (hereafter, DAP), lateral (hereafter, DLAT), and effective (hereafter, DE)—which can be tedious in clinical settings. We aimed to determine whether body weight can be used as a surrogate for measuring diameter in children. MATERIALS AND METHODS. DAP and DLAT were measured in 522 consecutive CT examinations (chest, 187 and abdomen–pelvis, 335) performed in 483 (± SD) children (13 ± 7 years). Effective diameter (DE1) was calculated as the square root of the product of DAP and DLAT. A second measurement of effective diameter (DE2) was obtained using automated software. Correlation coefficients between patient body weight, age, and diameter were measured in addition to 95% prediction interval analysis for diameters corresponding to body weight. RESULTS. Median body weight was 51 kg, and mean DAP, DLAT, DE1, and DE2 were 207.1 ± 50.8 mm, 289.8 ± 72.6 mm, 243.3 ± 62.0 mm, and 233.6 ± 55.4 mm, respectively. Overall body weight had a strong correlation with diameter (0.88, 0.85, 0.86, and 0.93 respectively; all p < 0.0001). SSDE measured using body weight was statistically not different than SSDE measured using effective diameters (p = 0.9). Children weighing less than 27 kg and between 46 and 100 kg had statistically significant correlations with torso diameters, whereas only anteroposterior and effective diameters were correlated with children weighing between 27 and 45 kg. Children less than 4 years old had strong correlation with all diameters. Adolescents (15–18 years) did not have statistically significant correlation with any of the diameters. CONCLUSION. Body weight, instead of body diameter, can be used as a surrogate to estimate size-specific dose in children, making dose estimation clinically simpler and more rapid.
T
he risks associated with radiation dose are one of the major concerns for CT as an imaging modality. Presently, all CT scanners are required to report radiation dose as two values: volume CT dose index (CTDIvol) and dose-length product (DLP). CTDIvol is an index of average scanner output and is measured in milliGrays, whereas DLP is the product of CTDIvol and scanning length measured in centimeters (mGy × cm) [1]. CTDIvol is a standardized measurement in homogeneous phantoms with a diameter of either 16 or 32 cm that has been adopted by the Center for Devices in Radiologic Health of the Food and Drug Administration as well as included in the Code of Federal Regulations. However, CTDIvol and DLP do not indicate exact patient absorbed dose and underestimate the dose of smaller pediatric patients [2–4].
To refine CTDIvol on the basis of patient size, the American Association of Physicists in Medicine (AAPM) task group 204 has introduced the concept of size-specific dose estimates (SSDEs), which is derived from CTDIvol and measured patient diameters using look-up tables for conversion factors [5]. This method requires manual or automatic measurement of one or more cross-sectional diameters of patients on transverse CT images or localizers [6]. The practical limitations of this technique are the difficulty and interobserver variability in selecting the horizontal skin-to-skin diameters at the midslice location and that the anatomic level of the patient’s maximum diameter may not be included in reconstructed CT images or localizers. Hence, the purpose of our study was to determine whether body weight can be used as a surrogate for measuring patient diameters in pediatric CT exami-
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Khawaja et al. Fig. 1—Measurement of patient diameters. A, Lateral CT planning radiograph in 12-year-old boy shows anteroposterior diameter (line) at midscan location (17 cm). Asterisk indicates midpoint of midslice diameter. B, Posteroanterior CT planning radiograph in 12-yearold boy shows lateral diameter (line) at midscan location (30 cm). Effective diameter is measured by square root of product of anteroposterior and lateral diameters (23 cm in this case). Asterisk indicates midpoint of midslice diameter.
A
B
nations to simplify the calculation of size-specific radiation dose estimates.
about the patients’ weights just before CT. Children were grouped into five subgroups according to their body weight: W1, ≤ 10 kg (n = 20); W2, ≤ 27 kg (n = 102); W3, ≤ 47 kg (n = 93); W4, ≤ 101 kg (n = 292); and W5, ≥ 101 kg (n = 15). We adopted these weight subgroups from previously published work on pediatric CT protocols based on body weight [7].
into a Microsoft Excel 2010 spreadsheet for further analysis. Automated measurements—A second effective diameter (hereafter referred to as DE2) measurement was obtained from a web-based dose-monitoring software program (eXposure, Radimetrics). This software automatically estimates body diameters
Body Diameter Measurements
TABLE 1: Conversion Factors as Function of Body Weight of Child Based on Use of 32-cm-Diameter Phantom for Volume CT Dose Index (CTDIvol)
Materials and Methods Patient Selection This retrospective clinical study was performed with approval from the hospital’s institutional review board and in compliance with HIPAA guidelines. Written informed consent was waived in accordance with hospital policies for this clinical study. Consecutive pediatric patients (1 day–18 years) undergoing chest and abdomen and pelvis CT examinations from January 1, 2011, to January 31, 2013, were included in this study. A PACS workstation (Impax ES, AGFA Technical Imaging Systems) was used for retrieving transverse CT images and localizers for 522 CT examinations in 483 pediatric patients (294 boys and 228 girls; mean age [± SD], 13 ± 7 years). All chest CT (n = 187) and abdominal or abdominal and pelvic CT (n = 335) studies with or without IV contrast administration, regardless of routine or emergent clinical indications, were included. The scanning range for chest CT included the top of the lungs to the adrenals and the scanning range for abdomen and pelvis CT extended from the lung bases to the symphysis pubis. Pediatric CT performed for the head or extremity, CT angiography, or combined PET/CT examinations were excluded from this study. Age subgroups—Age was categorized into four subgroups: A1, 0 to < 5years (n = 70); A2, 5 to < 10 years (n = 78); A3, 10 to < 15years (n = 125); and A4, 15 to < 19 years (n = 249). Body weight subgroups—In accordance with our institutional practice, the body weight of all children was recorded on the CT user interface just before scanning and archived in the PACS. Children were either weighed on a digital weighing scale in the CT suite or the parents were asked
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Manual measurements—Although the AAPM Report 204 suggests performing body measurements on either CT images or localizers; we choose to measure body diameters on localizers because maximum skin-to-skin diameter is often not included in transverse CT images. Maximum skin-to-skin lateral (hereafter referred to as DLAT) body diameters and anteroposterior diameters (hereafter referred to as DAP) were measured in centimeters on anteroposterior and lateral localizer images, respectively. Two study investigators performed diameter measurements manually with electronic calipers available on the PACS. The midslice level (median image of craniocaudal scanning length) was chosen on the localizer image for the measurement as suggested by AAPM Report 204 (Fig. 1). DLAT was defined as the horizontal (left-to-right or right-to-left) skin-to-skin diameter at the midslice level for the thorax (chest CT) and abdomen (abdominal CT). DAP was defined as anteroposterior skin-to-skin diameter on the lateral localizer at the midslice level. Effective diameter (hereafter referred to as DE1) was calculated as the square root of the product of DAP and DLAT. Effective diameter was defined as the diameter of the circle with area equivalent to the cross-section of the patient at that particular z-axis level. Another measurement was obtained by summing DAP and DLAT (DAP + DLAT). All of these four diameter measurements (DAP, DLAT, DE1, and DAP + LAT) were entered
Body Weight Groups (kg)
Conversion Factors
3–4
2.47
5–6
2.37
7–9
2.20
10–13
2.12
14–20
1.92
21–28
1.88
29–33
1.85
34–42
1.72
43–48
1.66
49–51
1.54
52–55
1.5
56–57
1.4
58–75
1.32
76–85
1.25
86–88
1.22
89–99
1.07
100 or above
0.94
Note—To obtain size-specific dose estimate from body weight, find conversion factor from this table and multiply by CTDIvol (32 cm).
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Radiation Dose in Pediatric CT for all patients at the midslice level on transverse CT images in accordance with AAPM report 204. The software enables real-time tracking and recording of all patient demographics, including name; age; sex; body weight; and scanner details, such as manufacturer, model number, and scanning parameters, including tube current, tube voltage, helical pitch, table speed, reconstructed slice thickness, and slice interval. These scanning parameters were set on the basis of standard departmental pediatric CT protocols that are based on patient weight and clinical indication. Automatic tube current modulation used for lowering radiation doses was also recorded with all modulated tube current values. Radiation dose descriptors, including CTDIvol (along with phantom size), DLP, SSDE, estimated effective doses in accordance with ICRP 60 and ICRP 103, and organ doses (in milliSieverts) were also calculated and recorded with this software. Because we followed the AAPM Task Group guidelines, we used only integer values for CTDIvol above 5 mGy and up to one decimal point for values up to 5 mGy. This report was the result of a confluence of consistent findings from four independent research groups across the United States. It proposed estimating patient dose with the use of patient size–dependent factors and CTDIvol before CT, called SSDE. To make this method simple, two tables were generated, one each for 16- and 32-cm diameter body dosimetry phantoms with four different input variables (DAP, DLAT, DAP + LAT, and DE1) to estimate size-dependent conversion factors. The document states that the resultant SSDE is reasonably accurate, with 10–20% variability. How-
ever, this variability was found to be acceptable provided that the method for calculating SSDE is simple and efficient.
Size-Specific Dose Estimate Calculations To consider body weight as a surrogate for effective diameter in measuring the SSDE, we calculated the following four SSDE measurements: SSDE measured by the automatic software (hereafter referred to as SSDEauto), SSDE measured using automatic effective diameter DE2 with conversion factors from AAPM Report 204 and CTDIvol of 32 cm (hereafter referred to as SSDEE2), SSDE measured using manually measured effective diameter DE1 (hereafter referred to as SSDEE1), and SSDE measured using body weight for children (hereafter referred to as SSDEBW). SSDEauto was automatically retrieved from the software. SSDEE1 and SSDEE2 were measured using the same method as described in AAPM Report 204—that is, to use effective diameters and multiply the respective conversion factors with the CTDIvol (32 cm). SSDEBW was measured by multiplying the conversion factors (as tabulated in Table 1) with the CTDIvol (32 cm) for the respective body weight of the child.
Statistical Analysis Statistical analyses were conducted by using SPSS, version 18.0, statistical software. We estimated descriptive statistics including means, SDs, and ranges. Average body weight, age, dose indexes (CTDIvol and SSDE), and body diameters (DAP, DLAT, DAP + DLAT, DE1, and DE2) were recorded for each patient per CT examination. Body weight variability was assessed
by measuring the SD for each age and body weight subgroup. The association between body weight, age, dose indexes, and body diameter measurements was calculated with Pearson correlation coefficients (r) for the following: correlation of means for each of the four body diameters and body weight, age, and sex; correlation between manual effective diameter (from localizer images) and software estimated automatic effective diameter (from transverse CT images); correlation of mean body weights and mean diameters (DAP, DLAT, DAP + LAT, DE1, and DE2), both overall and across body weight subgroups; correlation of mean age and mean diameters, both overall and across age subgroups; and correlation of dose indexes (CTDIvol and SSDE) and mean body weight, age, and body diameters. Mean body weight for each age subgroup was also correlated for age-for-body weight analyses. The ANOVA and regression analysis were used to evaluate differences in correlations between body weight subgroups, patient age groups, and patient sex. Linear regression models were used to assess the dependence of CTDIvol and SSDE on patient size. Linear regression models were also used to estimate the relationship of effective diameter (independent variable) with patient body weight (dependent variable). The 95% prediction intervals for all measured body diameters (DAP, DLAT, DE1, and DE2) corresponding to patient weight were plotted in addition to half width 95% calibration interval as a percentage of the DE2 estimate derived from patient body weight. Values for p of 0.05 or less were considered to indicate a significant difference.
TABLE 2: Summary of Body Weight and Maximum Skin-to-Skin Diameter for 522 CT Examinations Mean Body Weight (kg)
Parameter
Skin-to-Skin Body Diameter (cm)
Overall (n = 522)
Boys (n = 294)
Girls (n = 228)
Anteroposterior (n = 522)
49.7 ± 25.7
63.5 ± 21.6
45.6 ± 22.9
20.8 ± 25.7
6.9 ± 1.8
7.3 ± 1.8
6.4 ± 1.8
12.2 ± 1.4
Manual Effective Diameter (n = 522)
Automatic Effective Diameter (n = 522)
29.1 ± 7.2
24.6 ± 6.0
23.4 ± 5.6
16.0 ± 2.1
13.9 ± 1.52
13.1 ± 1.4
Lateral (n = 522)
Body weight subgroups Overall W1: < 9 kg (n = 20) W 2: 10–26 kg (n = 102)
18.4 ± 4.8
18.7 ± 3.8
18.1 ± 5.6
15.5 ± 2.2
21.9 ± 3.0
18.5 ± 2.3
17.1 ± 2.1
W 3: 27–45 kg (n = 93)
36.6 ± 6.0
36.7 ± 5.9
36.4 ± 6.1
18.3 ± 2.1
26.2 ± 2.9
21.6 ± 3.2
20.6 ± 20.8
W4: 46–100 kg (n = 292)
64.1 ± 12.3
66.5 ± 12.1
61.1 ± 11.8
23.3 ± 3.3
32.6 ± 5.1
27.4 ± 4.1
25.9 ± 3.5
W 5: ≥ 101 kg (n = 15)
122.8 ± 13.9
127.7 ± 12.1
109.2 ± 7.5
33.2 ± 3.4
46.1 ± 3.4
39.1 ± 2.6
36.3 ± 3.2
49.7 ± 25.7
63.5 ± 21.6
45.6 ± 22.9
20.8 ± 25.7
29.1 ± 7.2
24.6 ± 6.0
23.4 ± 5.6
14.1 ± 8.6
16.3 ± 10.9
11.8 ± 3.9
14.5 ± 3.4
20.1 ± 4.8
17.2 ± 3.9
15.4 ± 3.2
Age subgroups Overall A1: 1 d–4 y (n = 70) A 2: 5–9 y (n = 78)
6.7 ± 1.3
24.7 ± 10.5
28.5 ± 7.4
16.7 ± 2.5
24.2 ± 4.2
20.1 ± 2.9
19.3 ± 2.2
A 3: 10–14 y (n = 125)
49.6 ± 14.8
51.6 ± 14.3
47.6 ± 15.4
20.6 ± 3.4
29.2 ± 5.2
24.3 ± 4.5
23.7 ± 3.6
A 4: 15–18 y (n = 249)
67.2 ± 19.9
70.6 ± 21.2
62.1 ± 16.7
23.8 ± 4.3
33.1 ± 6.1
28.0 ± 5.1
26.3 ± 4.7
Note—Data are mean ± SD.
AJR:204, January 2015 169
50 ± 26 kg (range, 3–145 kg; median, 51 kg). Khawaja et al. Overall, boys were significantly heavier than girls (63 ± 22 kg vs 46 ± 23 kg; p < 0.001). The highest variability in body weight was found in children weighing less than 101 kg (± 13.9 kg) and lowest in those 0–9 kg (± 1.8 kg). In terms of age groups, the highest variability in body weight was found in children more than 15 years old (± 19.9 kg) and the lowest was seen in children 5–9 years old (± 1.3 kg). Mean overall DAP, DLAT, DE1, and DE2 were 21 ± 26, 29 ± 7, 25 ± 6, and 23 ± 6 cm, respectively. Mean body weight and body diameters across body weight and age subgroups are shown in Table 2.
160
160
140
140
120
120
100 80 60
100 80 60
40
40
20
20
0
0
5
10
15
20
25
(all, p < 0.001). Correlations of coefficients (r) for diameters were DAP–DLAT, 0.88; DAP– DE1, 0.97; DAP–DE2, 0.91; DLAT–DE1, 0.95; and DLAT–DE2, 0.88. DE2 correlated strongly with DE1 (r = 0.90; p < 0.001), with a mean difference of 4%. Manual measurement of effective diameter (DE1) was on average larger than the automatically measured DE2 by 4%. We found the highest correlation value between combined DAP + LAT and DE1 (r = 0.99) than either of them correlated alone. Across body weight subgroups—All body weight–diameter correlations are shown in Table 3. Overall, across body weight subgroups, the highest correlation was found with DE2 (0.93), and the correlations between mean body weights and mean body diameters were statistically significant (p < 0.001). Children who weighed less than 27
Correlation Coefficients Across body diameters—All diameters were strongly correlated across each other
Body Weight (kg)
Body Weight (kg)
Body Weight and Body Diameters Across Subgroups Children 15 years or older were the largest age group in our study sample (48%, n = 249/522). Mean overall body weight was
30
35
40
0
45
0
10
20
Midslice Anteroposterior Diameter (cm)
30
40
50
60
Midslice Lateral Diameter (cm)
A
B
160
160
140
140
120
120 Body Weight (kg)
Body Weight (kg)
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Results CT Scanners and Dose Metrics Pediatric CT examinations were performed on four different CT scanners: LightSpeed Ultra (n = 13) (GE Healthcare), Definition Flash (n = 26) (Siemens Healthcare), LightSpeed Pro 16 (n = 59) (GE Healthcare), LightSpeed VCT (n = 136) (GE Healthcare), and Discovery 750 HD (n = 288) (GE Healthcare). Mean CTDIvol at 32 cm, CTDIvol at 16 cm, DLP at 32 cm, DLP at 16 cm, and SSDE were 4.4 ± 4.0 mGy, 8 ± 8 mGy, 225 ± 219 mGy × cm, 450 ± 438 mGy × cm, 7 ± 6 mSv, and 7 ± 4 mGy, respectively.
100 80 60
100 80 60
40
40
20
20
0
0
5
10
15
20
25
30
35
40
45
Midslice Manual Effective Diameter (cm)
0
0
5
10
15
20
25
30
35
40
45
Midslice Automatic Effective Diameter (cm)
C
D
Fig. 2—Patient body weight across each diameter. A–D, Scatterplots show weight for anteroposterior diameter (A), lateral diameter (B), manual effective diameter (C), and automatic effective diameter (D).Correlation values were 0.88, 0.85, 0.87, and 0.93, respectively (all p < 0.0001). For correlations specific to individual weight subgroups, please refer to Results section. Red lines indicate polynomial trendline. Blue lines indicate linear trendline.
170
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weight correlation was strong (r = 0.79; p < 0.001). Across all age subgroups, the highest positive correlation was found with DE2 (0.73). However, correlation values for all other manually measured diameters were also statistically significant (p < 0.001). Children who were less than 4 years old and between 10 and 14 years old had a statistically significant correlation value across all body measurements (all, p < 0.01) (Table 3). With the exception of DAP (p = 0.2), all body measurements had significant correlation for the age group of 5–9 years (all p < 0.05). None
20
20
18
18
16
16
14
14
12
12 Age (y)
Age (y)
kg and between 46 and 100 kg had statistically significant correlation values across all diameters (all, p < 0.01) (Table 3). The body weight of children who weighed 27–45 kg correlated well with DAP (p = 0.006) and DE2 (p < 0.001) but was found statistically insignificant for DLAT (p = 0.06) and DE1 (p = 0.2). With the exception of DE2 (p = 0.003), none of the body measurements were significantly correlated with children who weighed less than 101 kg (Fig. 2). Across age subgroups—All age–diameter correlations are shown in Table 3. Age–body
10
8
6
6
4
4
2
2 0
5
10
15
20
25
30
35
40
0
45
of the body measurements were significantly correlated in children who were older than 15 years (all p > 0.05) (Fig. 3). The average body weight for each age subgroup (A1–A4) was correlated with diameter to perform age-for-weight analyses. The highest positive correlation was found between DE2 and average body weight for children less than 4 years old (r = 0.96; p < 0.001) and between 10 and 14 years old (r = 0.90; p < 0.001). For children 5–9 years old, DLAT had the highest positive correlation (0.84) with average body weight. However, for chil-
10
8
0
0
10
Midslice Anteroposterior Effective Diameter (cm)
20
30
30
35
45
Midslice Lateral Diameter (cm)
A
B
20 20
18
18
16
16
14
14
12
Age (y)
Age (y)
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Radiation Dose in Pediatric CT
10 8
12 10 8
6
6
4
4
2
2
0
0
5
10
15
20
25
30
35
40
0
45
0
5
10
15
20
25
30
35
40
Midslice Automatic Effective Diameter (cm)
Midslice Manual Effective Diameter (cm)
C
D
Fig. 3—Patient age across each diameter. A–D, Scatterplots show patient age for anteroposterior diameter (A), lateral diameter (B), manual effective diameter (C), and automatic effective diameter (D). Correlation values were 0.69, 0.68, 0.67, and 0.73, respectively (all p < 0.0001). For correlations specific to individual age subgroups, please refer to Results section. Red lines indicate polynomial trendline. Blue lines indicate linear trendline.
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Khawaja et al. dren more than 14 years old, DLAT had the lowest positive correlation coefficient value (0.74) with average body weight (Table 3). Across volume CT dose index and size-specific dose estimate—Both the effective body diameter (DE2) and weight correlated strongly with SSDE (r = 0.49 and 0.52, respectively, p < 0.001). Body weight–CTDIvol at 32 cm had a higher correlation value (r = 0.57) compared with body weight–CTDIvol at 16 cm (r = 0.50) (p < 0.001 for both). Patient diameter (DE2) had statistically significant correlations with CTDIvol (r = 0.87; p < 0.001) (Fig. 4). Correlation values for age–SSDE and age–CTDIvol analyses were 0.42 and 0.49 (p < 0.05), respectively. Table 4 summarizes CTDIvol (for both phantom 16 cm and 32 cm) and SSDE across patient weight and age subgroups. Prediction Analysis Figure 5A shows the 95% prediction interval for automatically measured effective diameter (DE2) corresponding to weight, and Figure 5B shows half width of the 95% calibration interval for diameter as a percentage of diameter estimate versus weight. Figure 6 shows normal plot diagrams for body weight and 95% prediction intervals for manually measured body diameters corresponding to weight. On the basis of our linear regression analysis on manually measured diameters, we have developed a spreadsheet data entry program (Microsoft Office Excel 2003) that can be used to predict the effective diameter (y) from patient’s known body weight (x). The program can be requested free of charge by contacting us. SSDE Calculations The means (± SDs) of different SSDE measurements were as follows: SSDEauto (6.8 ± 4.4 mGy), SSDEBW (6.7 ± 4.7 mGy), SSDEE1 (6.7 ± 4.7 mGy), and SSDEE2 (6.2 ± 4.6 mGy). The correlation between SSDEauto and SSDEBW was 0.92 (p < 0.001), whereas the correlations for SSDEauto and SSDEE1 and SSDEE2 were 0.92 and 0.95, respectively (p < 0.001). There were no statistical differences in the four SSDE measurements (p = 0.9). Discussion We found that in children of diverse body measurements (weight range, 3–145 kg; effective diameter range, 10–41 cm), the body weight measurements correlated strongly with diameters (correlation coefficients range, 0.83– 0.93; p < 0.05). SSDE measured using body weight of children can be measured with good correlation with SSDE measured using effective
172
TABLE 3: Summary of Pearson Correlation Coefficient Values for Body Weight, Age, and Diameter Subgroups Diameter Parameter
Anteroposterior
Lateral
Manual Effective Diameter
Automatic Effective Diameter
0.88
0.85
0.87
0.93
Body weight subgroups Overall W1: < 9 kg
0.51
0.66
0.69
0.83
W 2: 10–26 kg
0.45
0.41
0.45
0.64
W 3: 27–45 kg
0.28
0.19a
0.11a
0.55
W4: 46–100 kg
0.61
0.56
0.61
0.61
W 5: ≥ 101 kg
0.50a
0.09a
0.45a
0.71
0.69
0.68
0.67
0.73
Age subgroups Overall A1: 1 d–4 y
0.56
0.63
0.53
0.50
A 2: 5–9 y
0.14a
0.34
0.25
0.27
A 3: 10–14 y
0.24
0.30
0.23
0.30
A 4: 15–18 y
0.07a
0.10a
0.05a
0.07a
A1: 1 d–4 y
0.87
0.82
0.88
0.96
Age for body weight analysis A 2: 5–9 y
0.65
0.84
0.79
0.72
A 3: 10–14 y
0.73
0.67
0.67
0.90
A 4: 15–18 y
0.78
0.74
0.77
0.77
aNot statistically significant.
TABLE 4: Summary of Pearson Correlation Coefficient Values for Volume CT Dose Index (CTDIvol) With Phantom Sizes of 16 and 32 cm and Size-Specific Dose Estimates (SSDEs) Across Body Weight and Age Subgroups SSDE–CTDIvol Parameter
16 cm
32 cm
Body weight subgroups Overall
0.87
0.87
W1: < 9 kg
0.99
0.99
W 2: 10–26 kg
0.96
0.96
W 3: 27–45 kg
0.97
0.97
W4: 46–100 kg
0.84
0.84
W 5: ≥ 101 kg
0.93
0.93
0.87
0.87
A1: 1 d–4 y
0.94
0.94
A 2: 5–9 y
0.97
0.97
A 3: 10–14 y
0.95
0.95
A 4: 15–18 y
0.84
0.84
Age subgroups Overall
Note—All correlations were statistically significant with p < 0.0001.
AJR:204, January 2015
40
30
30
CTDIvol 32 cm (mGy)
CTDIvol 32 cm (mGy)
40
20
10
20
10
0
0 0
20
40
60
80
100
120
100
140
150
200
250
300
350
400
Midslice Automatic Effective Diameter (mm)
Body Weight (kg)
A
B 35
40
30
25 SSDE (mGy)
CTDIvol 32 cm (mGy)
30
20
20 15 10
10
5 0 5
0
10
0
15
0
20
40
Age (y)
60
80
100
120
140
Body Weight (kg)
C
D
35
35
30
30
25
25
SSDE (mGy)
SSDE (mGy)
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Radiation Dose in Pediatric CT
20 15
20 15
10
10
5
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0
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Midslice Automatic Effective Diameter (mm)
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Fig. 4—Volume CT dose index (CTDIvol) and size-specific dose estimate (SSDE). A–C, Scatterplots show CTDIvol (32 cm) for body weight (A), automatic effective diameter (B), and age (C). Correlation values for CTDIvol were 0.7, 0.57, and 0.49, respectively. D–F, Scatterplots show SSDE for body weight (A), automatic effective diameter (B), and age (C). Correlation values for SSDE were 0.52, 0.49, and 0.42, respectively..
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Khawaja et al. 30
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Fig. 5—Graphs for measured effective diameter. A, Scatterplot diagram shows linear regression line and 95% prediction interval for two variables (automatically measured effective diameter and patient body weight). This diagram shows patient with body weight of 50 kg and 95% predicted effective diameter (mean prediction interval, 189–272 mm). This may be interpreted that we are 95% sure that average body weight for given effective diameter values is within that interval. This plot helps predict diameter of child with given body weight or vice versa with 95% probability. For any given value of effective diameter, interval estimate of dependent variable of body weight can be estimated using this prediction interval. B, Graph shows margin of error or (half width) of 95% calibration CI for automatically measured effective diameter as percentage of diameter estimate derived from patient body weight. Plot shows 95% CIs using independently measured body weight of children in our study sample. This may be interpreted as when body weight of child approaches from 20 kg to 100 kg, 95% margin of error of effective diameter becomes small or, in other words, has smaller 95% CI.
diameters using the method recommended in AAPM Report 204. There were no statistical differences among all four SSDE measurements (p = 0.9). Children weighing less than 27 kg and 46–100 kg had the best correlation with all body diameters (DAP, DLAT, DE1, and DE2). For children weighing 27–45 kg and above 100 kg, only a few body diameters were strongly correlated. According to age, adolescents (15– 18 years) consistently did not have any statistically significant correlations with age and body diameters. This group represented 48% of our study sample. We have also noted that the correlation values for age–diameter relationship were significant but not as high as for the weight relationship. For example, the highest correlation value across overall mean body weight versus DE2 was 0.93 compared with the highest correlation value across overall mean age versus DE2 was 0.73. Hence, with increasing age of a child from 1 day to 18 years, the corresponding correlation values decreased up to a point at which it became insignificant for adolescents and yet still significant for children less than 15 years old. One may also argue for the use of body mass index (BMI), requiring both body weight and height, instead of body weight alone because it may have significantly higher correlation with diameters. BMI could not be used in this study because patient height was not routinely recorded and therefore could not be analyzed in a retrospective fashion. However, for clinical practicality, the need for only a single patient parameter, such as weight is advanta-
174
geous, provided that there are strong correlations to body diameter as shown in our results. We also noted a statistically significant correlation between manually (DE1) and automatically measured effective (DE2) diameters (r = 0.9, p < 0.001). Both DE1 and DE2 had statistically significant correlation with overall body weight (0.87 and 0.93, respectively; p < 0.001). Efforts of the AAPM to refine CTDIvol as SSDE with patient diameter are fairly accurate, with 10–20% variability [8]. In clinical practice, however, measurement of body diameters is a cumbersome process that has prompted a need for a simpler more rapid method that could be used as a surrogate for body diameter in the calculation of accurate SSDEs. Patient weight is an easily and routinely obtained measurement, and our study results from 522 CT examinations show that body weight has excellent potential for providing a simple surrogate to patient diameter measurements for calculating patient SSDEs. If body diameters are to be used, the effective diameter (DE2), calculated by one specific automated software program, first needs to be validated. Only then can it be recommended to estimate SSDE on the basis of the conversion factors provided in AAPM Report 204. Prior studies have shown that CTDIvol can substantially underestimate radiation dose to small subjects and overestimate it for larger patients [3, 4]. These inaccuracies motivated the AAPM to develop correction factors for CTDIvol in pediatric patients, based on effec-
tive diameter as well as anteroposterior or lateral diameters [6]. In clinical practice, however, measurement of body diameters is a complicated and time-consuming process that has prompted a need for a simplified measurement that could be used as a surrogate while at the same time, provide accurate SSDEs. As previously shown, body weight significantly correlated with diameters of smaller and younger children. As shown in Figure 5A, the weight of a child can be used to determine the 95% prediction interval of the effective diameter with significant correlation values. Brady et al. [8] implemented and compared five methodologies used to calculate SSDE in the AAPM report in 186 retrospectively reviewed patients from 1 month to 28 years old. They reported that SSDE calculated with a combination of DAP and DLAT diameters leads to less calculated SSDE variability compared with either diameter measurement used individually. They concluded that no SSDE correction was required on body weight less than 36 kg when the phantom size of 16 cm was used and on body weight greater than 100 kg when the phantom size of 32 was used. However, CTDIvol values for patients weighing 36–100 kg or greater than 140 kg required SSDE correction. In comparison with these reported results, our study supports that body weights in patients who weigh less than 27 kg (the lighter weight pediatric cohort in our study, n = 122) were strongly correlated with all measured diameters and hence unlikely to require
AJR:204, January 2015
SSDE correction (correlations between SSDE and CTDIvol in this weight range was 0.96– 0.99, p < 0.0001). However, our results differ in two aspects. First, patients weighing 46– 100 kg (n = 292, 36% more CT examinations than in the Brady et al. study sample) similar to the lighter weight group, showed statistically strong correlations with all diameter measurements and hence would be less likely to require SSDE correction (correlation between SSDE and CTDIvol was 0.84, p < 0.0001). Second, children weighing 100 kg or less (with a maximum weight of 145 kg) were only correlated well with effective diameter (DE2) and not with other diameters. However the correlation between SSDE and CTDIvol in this weight subgroup was statistically significant (0.93, p < 0.0001) and these patients would be less likely to require SSDE correction, supporting the study by Brady et al. Hence, diameters (DAP, DLAT, DLAT+AP, DE1, and DE2) were highly correlated with body weight for most of our study sample (79%, 414/522), specifically
those weighing less than 27 kg and between 46 and 100 kg. Children weighing 27–45 kg and more than 100 kg correlated only with DAP and DE1, and DE2 diameters, respectively. The latter group (> 100 kg) represented only 20% of our study sample. Irrespective of the body weight subgroup, patient weight was strongly related to automatically measured effective diameter (DE2). The latter may be used in the clinical setting (provided it is validated) to estimate SSDE on the basis of conversion factors provided in the AAPM report [5]. Although the primary objective of our study was to determine the correlation between weight and diameter, we additionally studied whether patient age can be another possible surrogate. This idea emerged from the AAPM report, which recommended the use of the patient’s age when body diameter is not known [5, 9]. Patient age is another easily obtainable demographic in cases when the body weight is unknown or cannot be measured. On the basis of our study, most body diameters were strong-
120 Body Weight (kg)
20 Normal Scores
y = 4.5466x – 43.5
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40
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–30 –40 –40
ly correlated across all age groups except adolescents more than 15 years old. This observation may be explained by maximum variability in body weight of children in that age subgroup. Given the wide variation in body dimensions in adolescents as noted in our study, we believe that SSDE in this age group should not be estimated using patient age for patients more than 15 years old. For younger children, our findings support the AAPM report in that in cases of unknown body diameter and weight, a patient’s age can be used to determine age-specific conversion factors [5]. Both SSDE and CTDIvol correlated strongly with patient size (body diameters and body weight) in our pediatric cohort. Christner et al. [6] reported results from linear regression for patient size with CTDIvol and SSDE for adult patients. Their study concluded that CTDIvol increased linearly with patient size, whereas SSDE was independent of size. Likewise, we too noticed that CTDIvol had a higher correlation coefficient than did
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Radiation Dose in Pediatric CT
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Fig. 6—Scatterplot diagrams for normal and manually measured body diameters. A, Scatterplot diagram shows normal plot for body weight. Red line indicates linear trendline. B–D, Scatterplot diagrams show 95% prediction interval for manually measured anteroposterior diameter (B), lateral diameter (C), and manual effective diameter (D). × indicates body weight, red indicates fit of body weight, and line indicates linear fit of body weight.
AJR:204, January 2015 175
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Khawaja et al. SSDE with the effective diameter (DE2) of a child (0.87 vs 0.49, respectively (Fig. 4). Our study has some limitations. Our study sample included a heterogeneous set of CT studies that included both chest and abdominopelvic imaging. These two types of imaging were not analyzed separately. There was no specific rationale for this methodology. We believed body weight might be as effective as a surrogate in the chest as well as abdomen. Another limitation is the retrospective nature of this study. A possible confounding variable from this study design is the interprovider variability in scanning protocol. More than 30 different CT technologists practice at our institution. Multiple factors influence the scanning range or length that is selected for scanning. In very young patients, technologists have a tendency to image lower into the abdomen than with older patients. Also, we did not standardize the CT examinations to select the midslice level as exactly midway between two anatomic landmarks but have simply chosen midway between the first slice and last slice. Additionally, our findings may not be desired by a selected few institutions and hospitals that have automatic software that determines the body measurements directly. Implementation of dose reduction methods for each pediatric CT examination requires a balance between radiation dose and image quality. To achieve this univer-
176
sally, the pediatric radiology community requires a user-friendly computational tool to estimate radiation dose during CT examinations [10]. With the increased need for more accurate dose monitoring, the best surrogates for patient size are being sought. Patient body weight was highly correlated with body diameters in children under 15 years old. Patient body weight, an easily obtained measurement, may serve as an important surrogate in providing a fast and simple way for pediatric SSDE. Future research is necessary to confirm this recommendation. Acknowledgment We thank Mark G. Vangel, statistician and assistant professor in the Department of Radiology at Harvard Medical School, for his kind suggestions and guidance in the statistical input. References 1. Shope TB, Gagne RM, Johnson GC. A method for describing the doses delivered by transmission x-ray computed tomography. Med Phys 1981; 8:488–495 2. McCollough CH, Leng S, Yu L, Cody DD, Boone JM, McNitt-Gray MF. CT dose index and patient dose: they are not the same thing. Radiology 2011; 259:311–316 3. Brenner DJ, McCollough C, Orton CG. Is it time to retire the CTDI for CT quality assurance and
dose optimization? Med Phys 2006; 33:1189–1190 4. Hurwitz LM, Yoshizumi TT, Goodman PC, et al. Effective dose determination using an anthropomorphic phantom and metal oxide semiconductor field effect transistor technology for clinical adult body multi detector array computed tomography protocols. J Comput Assist Tomogr 2007; 31:544–549 5. American Association of Physicists in Medicine website. Size-specific dose estimates (SSDE) in pediatric and adult CT examinations (Report 204). www.aapm.org/pubs/reports/rpt_204.pdf. Published 2011. Accessed September 8, 2014 6. Christner JA, Braun NN, Jacobsen MC, Carter RE, Kofler JM, McCollough CH. Size-specific dose estimates for adult patients at CT of the torso. Radiology 2012; 265:841–847 7. Singh S, Kalra MK, Moore MA, et al. Dose reduction and compliance with pediatric CT protocols adapted to patient size, clinical indication, and number of prior studies. Radiology 2009; 252:200–208 8. Brady SL, Kaufman RA. Investigation of American Association of Physicists in Medicine Report 204 size-specific dose estimates for pediatric CT implementation. Radiology 2012; 265:832–840 9. Strauss KJ, Goske MJ, Frush DP, Butler PF, Morrison G. Image Gently Vendor Summit: working together for better estimates of pediatric radiation dose from CT. AJR 2009; 192:1169–1175 10. Hopkins KL, Pettersson DR, Koudelka CW, et al. Size-appropriate radiation doses in pediatric body CT: a study of regional community adoption in the United States. Pediatr Radiol 2013; 43:1128–1135
AJR:204, January 2015
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Pediatric Imaging Original Research
Simplifying Size-Specific Radiation Dose Estimates in Pediatric CT Ranish Deedar Ali Khawaja1 Sarabjeet Singh1 Beth Vettiyil1 Ruth Lim 2 Michael Gee1 Sjirk Westra2 Mannudeep K. Kalra1 Khawaja RDA, Singh S, Vettiyl B, et al.
Keywords: body diameter, body weight, pediatric CT, size-specific dose estimate DOI:10.2214/AJR.13.12191 Received November 5, 2013; accepted after revision April 25, 2014. 1 Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 25 New Chardon St, 4th Fl, Boston, MA 02114. Address correspondence to R. D. A. Khawaja ([email protected]). 2 Division of Pediatric Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
AJR 2015; 204:167–176 0361–803X/15/2041–167 © American Roentgen Ray Society
OBJECTIVE. Size-specific dose estimates (SSDEs) require manual measurement of torso diameters for individual patients—anteroposterior (hereafter, DAP), lateral (hereafter, DLAT), and effective (hereafter, DE)—which can be tedious in clinical settings. We aimed to determine whether body weight can be used as a surrogate for measuring diameter in children. MATERIALS AND METHODS. DAP and DLAT were measured in 522 consecutive CT examinations (chest, 187 and abdomen–pelvis, 335) performed in 483 (± SD) children (13 ± 7 years). Effective diameter (DE1) was calculated as the square root of the product of DAP and DLAT. A second measurement of effective diameter (DE2) was obtained using automated software. Correlation coefficients between patient body weight, age, and diameter were measured in addition to 95% prediction interval analysis for diameters corresponding to body weight. RESULTS. Median body weight was 51 kg, and mean DAP, DLAT, DE1, and DE2 were 207.1 ± 50.8 mm, 289.8 ± 72.6 mm, 243.3 ± 62.0 mm, and 233.6 ± 55.4 mm, respectively. Overall body weight had a strong correlation with diameter (0.88, 0.85, 0.86, and 0.93 respectively; all p < 0.0001). SSDE measured using body weight was statistically not different than SSDE measured using effective diameters (p = 0.9). Children weighing less than 27 kg and between 46 and 100 kg had statistically significant correlations with torso diameters, whereas only anteroposterior and effective diameters were correlated with children weighing between 27 and 45 kg. Children less than 4 years old had strong correlation with all diameters. Adolescents (15–18 years) did not have statistically significant correlation with any of the diameters. CONCLUSION. Body weight, instead of body diameter, can be used as a surrogate to estimate size-specific dose in children, making dose estimation clinically simpler and more rapid.
T
he risks associated with radiation dose are one of the major concerns for CT as an imaging modality. Presently, all CT scanners are required to report radiation dose as two values: volume CT dose index (CTDIvol) and dose-length product (DLP). CTDIvol is an index of average scanner output and is measured in milliGrays, whereas DLP is the product of CTDIvol and scanning length measured in centimeters (mGy × cm) [1]. CTDIvol is a standardized measurement in homogeneous phantoms with a diameter of either 16 or 32 cm that has been adopted by the Center for Devices in Radiologic Health of the Food and Drug Administration as well as included in the Code of Federal Regulations. However, CTDIvol and DLP do not indicate exact patient absorbed dose and underestimate the dose of smaller pediatric patients [2–4].
To refine CTDIvol on the basis of patient size, the American Association of Physicists in Medicine (AAPM) task group 204 has introduced the concept of size-specific dose estimates (SSDEs), which is derived from CTDIvol and measured patient diameters using look-up tables for conversion factors [5]. This method requires manual or automatic measurement of one or more cross-sectional diameters of patients on transverse CT images or localizers [6]. The practical limitations of this technique are the difficulty and interobserver variability in selecting the horizontal skin-to-skin diameters at the midslice location and that the anatomic level of the patient’s maximum diameter may not be included in reconstructed CT images or localizers. Hence, the purpose of our study was to determine whether body weight can be used as a surrogate for measuring patient diameters in pediatric CT exami-
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Khawaja et al. Fig. 1—Measurement of patient diameters. A, Lateral CT planning radiograph in 12-year-old boy shows anteroposterior diameter (line) at midscan location (17 cm). Asterisk indicates midpoint of midslice diameter. B, Posteroanterior CT planning radiograph in 12-yearold boy shows lateral diameter (line) at midscan location (30 cm). Effective diameter is measured by square root of product of anteroposterior and lateral diameters (23 cm in this case). Asterisk indicates midpoint of midslice diameter.
A
B
nations to simplify the calculation of size-specific radiation dose estimates.
about the patients’ weights just before CT. Children were grouped into five subgroups according to their body weight: W1, ≤ 10 kg (n = 20); W2, ≤ 27 kg (n = 102); W3, ≤ 47 kg (n = 93); W4, ≤ 101 kg (n = 292); and W5, ≥ 101 kg (n = 15). We adopted these weight subgroups from previously published work on pediatric CT protocols based on body weight [7].
into a Microsoft Excel 2010 spreadsheet for further analysis. Automated measurements—A second effective diameter (hereafter referred to as DE2) measurement was obtained from a web-based dose-monitoring software program (eXposure, Radimetrics). This software automatically estimates body diameters
Body Diameter Measurements
TABLE 1: Conversion Factors as Function of Body Weight of Child Based on Use of 32-cm-Diameter Phantom for Volume CT Dose Index (CTDIvol)
Materials and Methods Patient Selection This retrospective clinical study was performed with approval from the hospital’s institutional review board and in compliance with HIPAA guidelines. Written informed consent was waived in accordance with hospital policies for this clinical study. Consecutive pediatric patients (1 day–18 years) undergoing chest and abdomen and pelvis CT examinations from January 1, 2011, to January 31, 2013, were included in this study. A PACS workstation (Impax ES, AGFA Technical Imaging Systems) was used for retrieving transverse CT images and localizers for 522 CT examinations in 483 pediatric patients (294 boys and 228 girls; mean age [± SD], 13 ± 7 years). All chest CT (n = 187) and abdominal or abdominal and pelvic CT (n = 335) studies with or without IV contrast administration, regardless of routine or emergent clinical indications, were included. The scanning range for chest CT included the top of the lungs to the adrenals and the scanning range for abdomen and pelvis CT extended from the lung bases to the symphysis pubis. Pediatric CT performed for the head or extremity, CT angiography, or combined PET/CT examinations were excluded from this study. Age subgroups—Age was categorized into four subgroups: A1, 0 to < 5years (n = 70); A2, 5 to < 10 years (n = 78); A3, 10 to < 15years (n = 125); and A4, 15 to < 19 years (n = 249). Body weight subgroups—In accordance with our institutional practice, the body weight of all children was recorded on the CT user interface just before scanning and archived in the PACS. Children were either weighed on a digital weighing scale in the CT suite or the parents were asked
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Manual measurements—Although the AAPM Report 204 suggests performing body measurements on either CT images or localizers; we choose to measure body diameters on localizers because maximum skin-to-skin diameter is often not included in transverse CT images. Maximum skin-to-skin lateral (hereafter referred to as DLAT) body diameters and anteroposterior diameters (hereafter referred to as DAP) were measured in centimeters on anteroposterior and lateral localizer images, respectively. Two study investigators performed diameter measurements manually with electronic calipers available on the PACS. The midslice level (median image of craniocaudal scanning length) was chosen on the localizer image for the measurement as suggested by AAPM Report 204 (Fig. 1). DLAT was defined as the horizontal (left-to-right or right-to-left) skin-to-skin diameter at the midslice level for the thorax (chest CT) and abdomen (abdominal CT). DAP was defined as anteroposterior skin-to-skin diameter on the lateral localizer at the midslice level. Effective diameter (hereafter referred to as DE1) was calculated as the square root of the product of DAP and DLAT. Effective diameter was defined as the diameter of the circle with area equivalent to the cross-section of the patient at that particular z-axis level. Another measurement was obtained by summing DAP and DLAT (DAP + DLAT). All of these four diameter measurements (DAP, DLAT, DE1, and DAP + LAT) were entered
Body Weight Groups (kg)
Conversion Factors
3–4
2.47
5–6
2.37
7–9
2.20
10–13
2.12
14–20
1.92
21–28
1.88
29–33
1.85
34–42
1.72
43–48
1.66
49–51
1.54
52–55
1.5
56–57
1.4
58–75
1.32
76–85
1.25
86–88
1.22
89–99
1.07
100 or above
0.94
Note—To obtain size-specific dose estimate from body weight, find conversion factor from this table and multiply by CTDIvol (32 cm).
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Radiation Dose in Pediatric CT for all patients at the midslice level on transverse CT images in accordance with AAPM report 204. The software enables real-time tracking and recording of all patient demographics, including name; age; sex; body weight; and scanner details, such as manufacturer, model number, and scanning parameters, including tube current, tube voltage, helical pitch, table speed, reconstructed slice thickness, and slice interval. These scanning parameters were set on the basis of standard departmental pediatric CT protocols that are based on patient weight and clinical indication. Automatic tube current modulation used for lowering radiation doses was also recorded with all modulated tube current values. Radiation dose descriptors, including CTDIvol (along with phantom size), DLP, SSDE, estimated effective doses in accordance with ICRP 60 and ICRP 103, and organ doses (in milliSieverts) were also calculated and recorded with this software. Because we followed the AAPM Task Group guidelines, we used only integer values for CTDIvol above 5 mGy and up to one decimal point for values up to 5 mGy. This report was the result of a confluence of consistent findings from four independent research groups across the United States. It proposed estimating patient dose with the use of patient size–dependent factors and CTDIvol before CT, called SSDE. To make this method simple, two tables were generated, one each for 16- and 32-cm diameter body dosimetry phantoms with four different input variables (DAP, DLAT, DAP + LAT, and DE1) to estimate size-dependent conversion factors. The document states that the resultant SSDE is reasonably accurate, with 10–20% variability. How-
ever, this variability was found to be acceptable provided that the method for calculating SSDE is simple and efficient.
Size-Specific Dose Estimate Calculations To consider body weight as a surrogate for effective diameter in measuring the SSDE, we calculated the following four SSDE measurements: SSDE measured by the automatic software (hereafter referred to as SSDEauto), SSDE measured using automatic effective diameter DE2 with conversion factors from AAPM Report 204 and CTDIvol of 32 cm (hereafter referred to as SSDEE2), SSDE measured using manually measured effective diameter DE1 (hereafter referred to as SSDEE1), and SSDE measured using body weight for children (hereafter referred to as SSDEBW). SSDEauto was automatically retrieved from the software. SSDEE1 and SSDEE2 were measured using the same method as described in AAPM Report 204—that is, to use effective diameters and multiply the respective conversion factors with the CTDIvol (32 cm). SSDEBW was measured by multiplying the conversion factors (as tabulated in Table 1) with the CTDIvol (32 cm) for the respective body weight of the child.
Statistical Analysis Statistical analyses were conducted by using SPSS, version 18.0, statistical software. We estimated descriptive statistics including means, SDs, and ranges. Average body weight, age, dose indexes (CTDIvol and SSDE), and body diameters (DAP, DLAT, DAP + DLAT, DE1, and DE2) were recorded for each patient per CT examination. Body weight variability was assessed
by measuring the SD for each age and body weight subgroup. The association between body weight, age, dose indexes, and body diameter measurements was calculated with Pearson correlation coefficients (r) for the following: correlation of means for each of the four body diameters and body weight, age, and sex; correlation between manual effective diameter (from localizer images) and software estimated automatic effective diameter (from transverse CT images); correlation of mean body weights and mean diameters (DAP, DLAT, DAP + LAT, DE1, and DE2), both overall and across body weight subgroups; correlation of mean age and mean diameters, both overall and across age subgroups; and correlation of dose indexes (CTDIvol and SSDE) and mean body weight, age, and body diameters. Mean body weight for each age subgroup was also correlated for age-for-body weight analyses. The ANOVA and regression analysis were used to evaluate differences in correlations between body weight subgroups, patient age groups, and patient sex. Linear regression models were used to assess the dependence of CTDIvol and SSDE on patient size. Linear regression models were also used to estimate the relationship of effective diameter (independent variable) with patient body weight (dependent variable). The 95% prediction intervals for all measured body diameters (DAP, DLAT, DE1, and DE2) corresponding to patient weight were plotted in addition to half width 95% calibration interval as a percentage of the DE2 estimate derived from patient body weight. Values for p of 0.05 or less were considered to indicate a significant difference.
TABLE 2: Summary of Body Weight and Maximum Skin-to-Skin Diameter for 522 CT Examinations Mean Body Weight (kg)
Parameter
Skin-to-Skin Body Diameter (cm)
Overall (n = 522)
Boys (n = 294)
Girls (n = 228)
Anteroposterior (n = 522)
49.7 ± 25.7
63.5 ± 21.6
45.6 ± 22.9
20.8 ± 25.7
6.9 ± 1.8
7.3 ± 1.8
6.4 ± 1.8
12.2 ± 1.4
Manual Effective Diameter (n = 522)
Automatic Effective Diameter (n = 522)
29.1 ± 7.2
24.6 ± 6.0
23.4 ± 5.6
16.0 ± 2.1
13.9 ± 1.52
13.1 ± 1.4
Lateral (n = 522)
Body weight subgroups Overall W1: < 9 kg (n = 20) W 2: 10–26 kg (n = 102)
18.4 ± 4.8
18.7 ± 3.8
18.1 ± 5.6
15.5 ± 2.2
21.9 ± 3.0
18.5 ± 2.3
17.1 ± 2.1
W 3: 27–45 kg (n = 93)
36.6 ± 6.0
36.7 ± 5.9
36.4 ± 6.1
18.3 ± 2.1
26.2 ± 2.9
21.6 ± 3.2
20.6 ± 20.8
W4: 46–100 kg (n = 292)
64.1 ± 12.3
66.5 ± 12.1
61.1 ± 11.8
23.3 ± 3.3
32.6 ± 5.1
27.4 ± 4.1
25.9 ± 3.5
W 5: ≥ 101 kg (n = 15)
122.8 ± 13.9
127.7 ± 12.1
109.2 ± 7.5
33.2 ± 3.4
46.1 ± 3.4
39.1 ± 2.6
36.3 ± 3.2
49.7 ± 25.7
63.5 ± 21.6
45.6 ± 22.9
20.8 ± 25.7
29.1 ± 7.2
24.6 ± 6.0
23.4 ± 5.6
14.1 ± 8.6
16.3 ± 10.9
11.8 ± 3.9
14.5 ± 3.4
20.1 ± 4.8
17.2 ± 3.9
15.4 ± 3.2
Age subgroups Overall A1: 1 d–4 y (n = 70) A 2: 5–9 y (n = 78)
6.7 ± 1.3
24.7 ± 10.5
28.5 ± 7.4
16.7 ± 2.5
24.2 ± 4.2
20.1 ± 2.9
19.3 ± 2.2
A 3: 10–14 y (n = 125)
49.6 ± 14.8
51.6 ± 14.3
47.6 ± 15.4
20.6 ± 3.4
29.2 ± 5.2
24.3 ± 4.5
23.7 ± 3.6
A 4: 15–18 y (n = 249)
67.2 ± 19.9
70.6 ± 21.2
62.1 ± 16.7
23.8 ± 4.3
33.1 ± 6.1
28.0 ± 5.1
26.3 ± 4.7
Note—Data are mean ± SD.
AJR:204, January 2015 169
50 ± 26 kg (range, 3–145 kg; median, 51 kg). Khawaja et al. Overall, boys were significantly heavier than girls (63 ± 22 kg vs 46 ± 23 kg; p < 0.001). The highest variability in body weight was found in children weighing less than 101 kg (± 13.9 kg) and lowest in those 0–9 kg (± 1.8 kg). In terms of age groups, the highest variability in body weight was found in children more than 15 years old (± 19.9 kg) and the lowest was seen in children 5–9 years old (± 1.3 kg). Mean overall DAP, DLAT, DE1, and DE2 were 21 ± 26, 29 ± 7, 25 ± 6, and 23 ± 6 cm, respectively. Mean body weight and body diameters across body weight and age subgroups are shown in Table 2.
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120
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100 80 60
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20
0
0
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(all, p < 0.001). Correlations of coefficients (r) for diameters were DAP–DLAT, 0.88; DAP– DE1, 0.97; DAP–DE2, 0.91; DLAT–DE1, 0.95; and DLAT–DE2, 0.88. DE2 correlated strongly with DE1 (r = 0.90; p < 0.001), with a mean difference of 4%. Manual measurement of effective diameter (DE1) was on average larger than the automatically measured DE2 by 4%. We found the highest correlation value between combined DAP + LAT and DE1 (r = 0.99) than either of them correlated alone. Across body weight subgroups—All body weight–diameter correlations are shown in Table 3. Overall, across body weight subgroups, the highest correlation was found with DE2 (0.93), and the correlations between mean body weights and mean body diameters were statistically significant (p < 0.001). Children who weighed less than 27
Correlation Coefficients Across body diameters—All diameters were strongly correlated across each other
Body Weight (kg)
Body Weight (kg)
Body Weight and Body Diameters Across Subgroups Children 15 years or older were the largest age group in our study sample (48%, n = 249/522). Mean overall body weight was
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Results CT Scanners and Dose Metrics Pediatric CT examinations were performed on four different CT scanners: LightSpeed Ultra (n = 13) (GE Healthcare), Definition Flash (n = 26) (Siemens Healthcare), LightSpeed Pro 16 (n = 59) (GE Healthcare), LightSpeed VCT (n = 136) (GE Healthcare), and Discovery 750 HD (n = 288) (GE Healthcare). Mean CTDIvol at 32 cm, CTDIvol at 16 cm, DLP at 32 cm, DLP at 16 cm, and SSDE were 4.4 ± 4.0 mGy, 8 ± 8 mGy, 225 ± 219 mGy × cm, 450 ± 438 mGy × cm, 7 ± 6 mSv, and 7 ± 4 mGy, respectively.
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Fig. 2—Patient body weight across each diameter. A–D, Scatterplots show weight for anteroposterior diameter (A), lateral diameter (B), manual effective diameter (C), and automatic effective diameter (D).Correlation values were 0.88, 0.85, 0.87, and 0.93, respectively (all p < 0.0001). For correlations specific to individual weight subgroups, please refer to Results section. Red lines indicate polynomial trendline. Blue lines indicate linear trendline.
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weight correlation was strong (r = 0.79; p < 0.001). Across all age subgroups, the highest positive correlation was found with DE2 (0.73). However, correlation values for all other manually measured diameters were also statistically significant (p < 0.001). Children who were less than 4 years old and between 10 and 14 years old had a statistically significant correlation value across all body measurements (all, p < 0.01) (Table 3). With the exception of DAP (p = 0.2), all body measurements had significant correlation for the age group of 5–9 years (all p < 0.05). None
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kg and between 46 and 100 kg had statistically significant correlation values across all diameters (all, p < 0.01) (Table 3). The body weight of children who weighed 27–45 kg correlated well with DAP (p = 0.006) and DE2 (p < 0.001) but was found statistically insignificant for DLAT (p = 0.06) and DE1 (p = 0.2). With the exception of DE2 (p = 0.003), none of the body measurements were significantly correlated with children who weighed less than 101 kg (Fig. 2). Across age subgroups—All age–diameter correlations are shown in Table 3. Age–body
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of the body measurements were significantly correlated in children who were older than 15 years (all p > 0.05) (Fig. 3). The average body weight for each age subgroup (A1–A4) was correlated with diameter to perform age-for-weight analyses. The highest positive correlation was found between DE2 and average body weight for children less than 4 years old (r = 0.96; p < 0.001) and between 10 and 14 years old (r = 0.90; p < 0.001). For children 5–9 years old, DLAT had the highest positive correlation (0.84) with average body weight. However, for chil-
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Radiation Dose in Pediatric CT
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Fig. 3—Patient age across each diameter. A–D, Scatterplots show patient age for anteroposterior diameter (A), lateral diameter (B), manual effective diameter (C), and automatic effective diameter (D). Correlation values were 0.69, 0.68, 0.67, and 0.73, respectively (all p < 0.0001). For correlations specific to individual age subgroups, please refer to Results section. Red lines indicate polynomial trendline. Blue lines indicate linear trendline.
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Khawaja et al. dren more than 14 years old, DLAT had the lowest positive correlation coefficient value (0.74) with average body weight (Table 3). Across volume CT dose index and size-specific dose estimate—Both the effective body diameter (DE2) and weight correlated strongly with SSDE (r = 0.49 and 0.52, respectively, p < 0.001). Body weight–CTDIvol at 32 cm had a higher correlation value (r = 0.57) compared with body weight–CTDIvol at 16 cm (r = 0.50) (p < 0.001 for both). Patient diameter (DE2) had statistically significant correlations with CTDIvol (r = 0.87; p < 0.001) (Fig. 4). Correlation values for age–SSDE and age–CTDIvol analyses were 0.42 and 0.49 (p < 0.05), respectively. Table 4 summarizes CTDIvol (for both phantom 16 cm and 32 cm) and SSDE across patient weight and age subgroups. Prediction Analysis Figure 5A shows the 95% prediction interval for automatically measured effective diameter (DE2) corresponding to weight, and Figure 5B shows half width of the 95% calibration interval for diameter as a percentage of diameter estimate versus weight. Figure 6 shows normal plot diagrams for body weight and 95% prediction intervals for manually measured body diameters corresponding to weight. On the basis of our linear regression analysis on manually measured diameters, we have developed a spreadsheet data entry program (Microsoft Office Excel 2003) that can be used to predict the effective diameter (y) from patient’s known body weight (x). The program can be requested free of charge by contacting us. SSDE Calculations The means (± SDs) of different SSDE measurements were as follows: SSDEauto (6.8 ± 4.4 mGy), SSDEBW (6.7 ± 4.7 mGy), SSDEE1 (6.7 ± 4.7 mGy), and SSDEE2 (6.2 ± 4.6 mGy). The correlation between SSDEauto and SSDEBW was 0.92 (p < 0.001), whereas the correlations for SSDEauto and SSDEE1 and SSDEE2 were 0.92 and 0.95, respectively (p < 0.001). There were no statistical differences in the four SSDE measurements (p = 0.9). Discussion We found that in children of diverse body measurements (weight range, 3–145 kg; effective diameter range, 10–41 cm), the body weight measurements correlated strongly with diameters (correlation coefficients range, 0.83– 0.93; p < 0.05). SSDE measured using body weight of children can be measured with good correlation with SSDE measured using effective
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TABLE 3: Summary of Pearson Correlation Coefficient Values for Body Weight, Age, and Diameter Subgroups Diameter Parameter
Anteroposterior
Lateral
Manual Effective Diameter
Automatic Effective Diameter
0.88
0.85
0.87
0.93
Body weight subgroups Overall W1: < 9 kg
0.51
0.66
0.69
0.83
W 2: 10–26 kg
0.45
0.41
0.45
0.64
W 3: 27–45 kg
0.28
0.19a
0.11a
0.55
W4: 46–100 kg
0.61
0.56
0.61
0.61
W 5: ≥ 101 kg
0.50a
0.09a
0.45a
0.71
0.69
0.68
0.67
0.73
Age subgroups Overall A1: 1 d–4 y
0.56
0.63
0.53
0.50
A 2: 5–9 y
0.14a
0.34
0.25
0.27
A 3: 10–14 y
0.24
0.30
0.23
0.30
A 4: 15–18 y
0.07a
0.10a
0.05a
0.07a
A1: 1 d–4 y
0.87
0.82
0.88
0.96
Age for body weight analysis A 2: 5–9 y
0.65
0.84
0.79
0.72
A 3: 10–14 y
0.73
0.67
0.67
0.90
A 4: 15–18 y
0.78
0.74
0.77
0.77
aNot statistically significant.
TABLE 4: Summary of Pearson Correlation Coefficient Values for Volume CT Dose Index (CTDIvol) With Phantom Sizes of 16 and 32 cm and Size-Specific Dose Estimates (SSDEs) Across Body Weight and Age Subgroups SSDE–CTDIvol Parameter
16 cm
32 cm
Body weight subgroups Overall
0.87
0.87
W1: < 9 kg
0.99
0.99
W 2: 10–26 kg
0.96
0.96
W 3: 27–45 kg
0.97
0.97
W4: 46–100 kg
0.84
0.84
W 5: ≥ 101 kg
0.93
0.93
0.87
0.87
A1: 1 d–4 y
0.94
0.94
A 2: 5–9 y
0.97
0.97
A 3: 10–14 y
0.95
0.95
A 4: 15–18 y
0.84
0.84
Age subgroups Overall
Note—All correlations were statistically significant with p < 0.0001.
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Radiation Dose in Pediatric CT
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Fig. 4—Volume CT dose index (CTDIvol) and size-specific dose estimate (SSDE). A–C, Scatterplots show CTDIvol (32 cm) for body weight (A), automatic effective diameter (B), and age (C). Correlation values for CTDIvol were 0.7, 0.57, and 0.49, respectively. D–F, Scatterplots show SSDE for body weight (A), automatic effective diameter (B), and age (C). Correlation values for SSDE were 0.52, 0.49, and 0.42, respectively..
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Fig. 5—Graphs for measured effective diameter. A, Scatterplot diagram shows linear regression line and 95% prediction interval for two variables (automatically measured effective diameter and patient body weight). This diagram shows patient with body weight of 50 kg and 95% predicted effective diameter (mean prediction interval, 189–272 mm). This may be interpreted that we are 95% sure that average body weight for given effective diameter values is within that interval. This plot helps predict diameter of child with given body weight or vice versa with 95% probability. For any given value of effective diameter, interval estimate of dependent variable of body weight can be estimated using this prediction interval. B, Graph shows margin of error or (half width) of 95% calibration CI for automatically measured effective diameter as percentage of diameter estimate derived from patient body weight. Plot shows 95% CIs using independently measured body weight of children in our study sample. This may be interpreted as when body weight of child approaches from 20 kg to 100 kg, 95% margin of error of effective diameter becomes small or, in other words, has smaller 95% CI.
diameters using the method recommended in AAPM Report 204. There were no statistical differences among all four SSDE measurements (p = 0.9). Children weighing less than 27 kg and 46–100 kg had the best correlation with all body diameters (DAP, DLAT, DE1, and DE2). For children weighing 27–45 kg and above 100 kg, only a few body diameters were strongly correlated. According to age, adolescents (15– 18 years) consistently did not have any statistically significant correlations with age and body diameters. This group represented 48% of our study sample. We have also noted that the correlation values for age–diameter relationship were significant but not as high as for the weight relationship. For example, the highest correlation value across overall mean body weight versus DE2 was 0.93 compared with the highest correlation value across overall mean age versus DE2 was 0.73. Hence, with increasing age of a child from 1 day to 18 years, the corresponding correlation values decreased up to a point at which it became insignificant for adolescents and yet still significant for children less than 15 years old. One may also argue for the use of body mass index (BMI), requiring both body weight and height, instead of body weight alone because it may have significantly higher correlation with diameters. BMI could not be used in this study because patient height was not routinely recorded and therefore could not be analyzed in a retrospective fashion. However, for clinical practicality, the need for only a single patient parameter, such as weight is advanta-
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geous, provided that there are strong correlations to body diameter as shown in our results. We also noted a statistically significant correlation between manually (DE1) and automatically measured effective (DE2) diameters (r = 0.9, p < 0.001). Both DE1 and DE2 had statistically significant correlation with overall body weight (0.87 and 0.93, respectively; p < 0.001). Efforts of the AAPM to refine CTDIvol as SSDE with patient diameter are fairly accurate, with 10–20% variability [8]. In clinical practice, however, measurement of body diameters is a cumbersome process that has prompted a need for a simpler more rapid method that could be used as a surrogate for body diameter in the calculation of accurate SSDEs. Patient weight is an easily and routinely obtained measurement, and our study results from 522 CT examinations show that body weight has excellent potential for providing a simple surrogate to patient diameter measurements for calculating patient SSDEs. If body diameters are to be used, the effective diameter (DE2), calculated by one specific automated software program, first needs to be validated. Only then can it be recommended to estimate SSDE on the basis of the conversion factors provided in AAPM Report 204. Prior studies have shown that CTDIvol can substantially underestimate radiation dose to small subjects and overestimate it for larger patients [3, 4]. These inaccuracies motivated the AAPM to develop correction factors for CTDIvol in pediatric patients, based on effec-
tive diameter as well as anteroposterior or lateral diameters [6]. In clinical practice, however, measurement of body diameters is a complicated and time-consuming process that has prompted a need for a simplified measurement that could be used as a surrogate while at the same time, provide accurate SSDEs. As previously shown, body weight significantly correlated with diameters of smaller and younger children. As shown in Figure 5A, the weight of a child can be used to determine the 95% prediction interval of the effective diameter with significant correlation values. Brady et al. [8] implemented and compared five methodologies used to calculate SSDE in the AAPM report in 186 retrospectively reviewed patients from 1 month to 28 years old. They reported that SSDE calculated with a combination of DAP and DLAT diameters leads to less calculated SSDE variability compared with either diameter measurement used individually. They concluded that no SSDE correction was required on body weight less than 36 kg when the phantom size of 16 cm was used and on body weight greater than 100 kg when the phantom size of 32 was used. However, CTDIvol values for patients weighing 36–100 kg or greater than 140 kg required SSDE correction. In comparison with these reported results, our study supports that body weights in patients who weigh less than 27 kg (the lighter weight pediatric cohort in our study, n = 122) were strongly correlated with all measured diameters and hence unlikely to require
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SSDE correction (correlations between SSDE and CTDIvol in this weight range was 0.96– 0.99, p < 0.0001). However, our results differ in two aspects. First, patients weighing 46– 100 kg (n = 292, 36% more CT examinations than in the Brady et al. study sample) similar to the lighter weight group, showed statistically strong correlations with all diameter measurements and hence would be less likely to require SSDE correction (correlation between SSDE and CTDIvol was 0.84, p < 0.0001). Second, children weighing 100 kg or less (with a maximum weight of 145 kg) were only correlated well with effective diameter (DE2) and not with other diameters. However the correlation between SSDE and CTDIvol in this weight subgroup was statistically significant (0.93, p < 0.0001) and these patients would be less likely to require SSDE correction, supporting the study by Brady et al. Hence, diameters (DAP, DLAT, DLAT+AP, DE1, and DE2) were highly correlated with body weight for most of our study sample (79%, 414/522), specifically
those weighing less than 27 kg and between 46 and 100 kg. Children weighing 27–45 kg and more than 100 kg correlated only with DAP and DE1, and DE2 diameters, respectively. The latter group (> 100 kg) represented only 20% of our study sample. Irrespective of the body weight subgroup, patient weight was strongly related to automatically measured effective diameter (DE2). The latter may be used in the clinical setting (provided it is validated) to estimate SSDE on the basis of conversion factors provided in the AAPM report [5]. Although the primary objective of our study was to determine the correlation between weight and diameter, we additionally studied whether patient age can be another possible surrogate. This idea emerged from the AAPM report, which recommended the use of the patient’s age when body diameter is not known [5, 9]. Patient age is another easily obtainable demographic in cases when the body weight is unknown or cannot be measured. On the basis of our study, most body diameters were strong-
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ly correlated across all age groups except adolescents more than 15 years old. This observation may be explained by maximum variability in body weight of children in that age subgroup. Given the wide variation in body dimensions in adolescents as noted in our study, we believe that SSDE in this age group should not be estimated using patient age for patients more than 15 years old. For younger children, our findings support the AAPM report in that in cases of unknown body diameter and weight, a patient’s age can be used to determine age-specific conversion factors [5]. Both SSDE and CTDIvol correlated strongly with patient size (body diameters and body weight) in our pediatric cohort. Christner et al. [6] reported results from linear regression for patient size with CTDIvol and SSDE for adult patients. Their study concluded that CTDIvol increased linearly with patient size, whereas SSDE was independent of size. Likewise, we too noticed that CTDIvol had a higher correlation coefficient than did
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Radiation Dose in Pediatric CT
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Khawaja et al. SSDE with the effective diameter (DE2) of a child (0.87 vs 0.49, respectively (Fig. 4). Our study has some limitations. Our study sample included a heterogeneous set of CT studies that included both chest and abdominopelvic imaging. These two types of imaging were not analyzed separately. There was no specific rationale for this methodology. We believed body weight might be as effective as a surrogate in the chest as well as abdomen. Another limitation is the retrospective nature of this study. A possible confounding variable from this study design is the interprovider variability in scanning protocol. More than 30 different CT technologists practice at our institution. Multiple factors influence the scanning range or length that is selected for scanning. In very young patients, technologists have a tendency to image lower into the abdomen than with older patients. Also, we did not standardize the CT examinations to select the midslice level as exactly midway between two anatomic landmarks but have simply chosen midway between the first slice and last slice. Additionally, our findings may not be desired by a selected few institutions and hospitals that have automatic software that determines the body measurements directly. Implementation of dose reduction methods for each pediatric CT examination requires a balance between radiation dose and image quality. To achieve this univer-
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sally, the pediatric radiology community requires a user-friendly computational tool to estimate radiation dose during CT examinations [10]. With the increased need for more accurate dose monitoring, the best surrogates for patient size are being sought. Patient body weight was highly correlated with body diameters in children under 15 years old. Patient body weight, an easily obtained measurement, may serve as an important surrogate in providing a fast and simple way for pediatric SSDE. Future research is necessary to confirm this recommendation. Acknowledgment We thank Mark G. Vangel, statistician and assistant professor in the Department of Radiology at Harvard Medical School, for his kind suggestions and guidance in the statistical input. References 1. Shope TB, Gagne RM, Johnson GC. A method for describing the doses delivered by transmission x-ray computed tomography. Med Phys 1981; 8:488–495 2. McCollough CH, Leng S, Yu L, Cody DD, Boone JM, McNitt-Gray MF. CT dose index and patient dose: they are not the same thing. Radiology 2011; 259:311–316 3. Brenner DJ, McCollough C, Orton CG. Is it time to retire the CTDI for CT quality assurance and
dose optimization? Med Phys 2006; 33:1189–1190 4. Hurwitz LM, Yoshizumi TT, Goodman PC, et al. Effective dose determination using an anthropomorphic phantom and metal oxide semiconductor field effect transistor technology for clinical adult body multi detector array computed tomography protocols. J Comput Assist Tomogr 2007; 31:544–549 5. American Association of Physicists in Medicine website. Size-specific dose estimates (SSDE) in pediatric and adult CT examinations (Report 204). www.aapm.org/pubs/reports/rpt_204.pdf. Published 2011. Accessed September 8, 2014 6. Christner JA, Braun NN, Jacobsen MC, Carter RE, Kofler JM, McCollough CH. Size-specific dose estimates for adult patients at CT of the torso. Radiology 2012; 265:841–847 7. Singh S, Kalra MK, Moore MA, et al. Dose reduction and compliance with pediatric CT protocols adapted to patient size, clinical indication, and number of prior studies. Radiology 2009; 252:200–208 8. Brady SL, Kaufman RA. Investigation of American Association of Physicists in Medicine Report 204 size-specific dose estimates for pediatric CT implementation. Radiology 2012; 265:832–840 9. Strauss KJ, Goske MJ, Frush DP, Butler PF, Morrison G. Image Gently Vendor Summit: working together for better estimates of pediatric radiation dose from CT. AJR 2009; 192:1169–1175 10. Hopkins KL, Pettersson DR, Koudelka CW, et al. Size-appropriate radiation doses in pediatric body CT: a study of regional community adoption in the United States. Pediatr Radiol 2013; 43:1128–1135
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