580766
research-article2015
UIXXXX10.1177/0161734615580766Ultrasonic ImagingZandieh et al.
Article
Acoustic Structure Quantification Analysis of the Thyroid in Patients with Diffuse Autoimmune Thyroid Disease
Ultrasonic Imaging 1–11 © The Author(s) 2015 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0161734615580766 ultrasonicimaging.sagepub.com
Shahin Zandieh1, Reinhard Bernt1, Jochen Zwerina2, Joerg Haller1, Peter Knoll3, Orang Seyeddain4, and Siroos Mirzaei3
Abstract The aim of this study was to assess whether acoustic structure quantification (ASQ) can differentiate normal from pathological thyroid parenchyma in patients with diffuse autoimmune thyroid disease (AITD). We evaluated 83 subjects (72 [87%] women and 11 [13%] men) aged 19 to 94 years with a mean age of 53 years. We performed a prospective study (from March 2011 to November 2014) that included 43 (52%) patients with chronic autoimmune thyroiditis (CAT), 22 (26%) patients with Graves’ disease (GD), and 18 (22%) healthy volunteers. The ASQ values were significantly lower in normal subjects than in subjects with CAT and GD (p < 0.001). In contrast, the differences between the GD and the CAT patients (p = 0.23) were not statistically significant. The optimal cutoff ASQ value for which the sum of sensitivity and specificity was the highest for the prediction of diffuse thyroid pathology was 103 (95% confidence interval = [0.79, 0.95]). At this cutoff value, the sensitivity was 83% and the specificity was 89%. Our findings suggest that ASQ is a useful method for the assessment of the thyroid in patients with AITD. Keywords thyroid, ultrasound, autoimmune thyroid disease, tissue characterization, instrumentation
Introduction Chronic autoimmune thyroiditis (CAT) and Graves’ disease (GD) are the most common types of autoimmune thyroid disease (AITD), a common autoimmune disorder affecting mostly middle-aged women. About 2% to 4% of women and up to 1% of men are affected worldwide, 1Institute
of Radiology and Nuclear Medicine, Hanusch Hospital, Teaching Hospital of Medical University of Vienna, Austria 2Ludwig Boltzmann Institute of Osteology at the Hanusch Hospital of WGKK; Department of Internal Medicine, Hanusch Hospital, Teaching Hospital of Medical University of Vienna, Austria 3Institute of Nuclear Medicine with PET-Center, Wilhelminen Hospital, Teaching Hospital of Medical University of Vienna, Austria, Austria 4Department of Ophthalmology, Paracelsus Medical University of Salzburg, Austria Corresponding Author: Shahin Zandieh, Department of Radiology and Nuclear Medicine, Hanusch Hospital, Teaching Hospital of Medical University of Vienna, Heinrich-Collin-Strasse 30, Vienna 1140, Austria. Email: [email protected] Downloaded from uix.sagepub.com at UNIV OF OTTAWA LIBRARY on August 5, 2015
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and the prevalence rate increases with age.1 CAT is one of the most frequent causes of hypothyroidism2 and mostly affects people above the age of 50.3,4 In contrast, GD mainly affects younger individuals.5 In a previous study, thyroid sonography (ultrasound [US]) was shown to be of considerable value in establishing the absence of AITD) because it ruled out AITD in 88% of cases using an US examination alone.6 In most previous studies that used an US examination to diagnose AITD, the results varied considerably with diagnostic sensitivities ranging from 19% to 95%.6-10 Kim et al. showed the efficacy of an experienced radiologist using real-time thyroid US to identify asymptomatic diffuse thyroid disease. In their study, the sensitivity and the specificity in the diagnosis of asymptomatic diffuse thyroid disease were 87.7% and 92.1%, respectively.11 Over the last decade, methods that quantify changes in ultrasonic texture have focused on the non-invasive tissue classification of parenchymal organs through the use of different mathematical procedures.12-14 In the literature, a couple of studies have been reported on elastography and acoustic radiation force impulse (ARFI) elastography for thyroid assessment. These elastography techniques can assess the rigidity of tissue, but no information is given about the heterogeneity of the thyroid structure.12-14 US is an established method for the surveillance of patients with thyroid disease. Physical changes in the thyroid structure caused by nodules and fibrosis can be detected by grayscale US, but this appraisal is subjective and operator dependent. The assessment of stages and monitoring of disease progress quantitatively within routine US examinations may potentially optimize the therapeutic options. Acoustic structure quantification (ASQ) is a novel imaging technique that analyzes the statistical information of the acquired echo signals. The analysis of the speckled pattern in a certain region of interest (ROI) makes tissue differentiation possible. ASQ software has been used to analyze the level of fibrosis in the liver using statistical information of the acquired US echo signals. A couple of studies have evaluated the liver fibrosis in patients with chronic liver diseases using this technique.15,16 In the present study, we assessed whether an ASQ technique would be useful in the evaluation of AITD.
Materials and Method Study Subjects Consecutive patients with clinical symptoms or signs of CAT or GD were referred to the Nuclear Medicine Department of the Hanusch Hospital between March of 2011 and November of 2014. In addition, 18 healthy volunteers (medical students, nurses, and medical doctors from our hospital who did not have any known thyroid pathology) were examined. Two experienced radiologists who had no knowledge of the clinical or the laboratory data examined all subjects independently. All patients had been diagnosed with CAT or GD within the last 12 months in the Department of Nuclear Medicine of Hanusch Hospital. Written informed consent was obtained from all patients and volunteers who agreed to participate in our study, which was approved by our ethics committee. The serum levels of thyroid antibody were obtained from the medical records after the US examinations were performed. The diagnosis of CAT was based on the presence of high titers of antithyroid antibodies (antiTPO and/or anti-Tg) and a diffuse hypoechogenicity or heterogeneity of thyroid parenchyma at US. The diagnosis of GD was based on the following criteria: thyrotoxicosis at the beginning confirmed by a suppressed thyroid stimulating hormone (TSH), elevated FT4 and FT3 levels, and the presence of TSH receptor antibodies. All healthy volunteers had normal serum TSH values and negative thyroid antibodies.
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Brightness Modulation US examinations were performed with a Toshiba Aplio XG scanner (Toshiba Medical Systems, Tokyo, Japan) using a 2- to 6-MHz convex probe. Patients were examined in the supine position. The insonating frequency of the sector scanner was 4.7 MHz. The Toshiba unit incorporates a real-time scanner and a range-gated pulse Doppler velocity meter. The wall filter was set as low as possible, and the real-time brightness modulation (B-mode) was used to locate the thyroid and to evaluate the echogenicity. The echogenicity was described as isoechoic, hypoechoic, or hyperechoic in reference to the echogenicity of the strap muscles and submandibular glands. The echotexture was described as homogeneous or heterogeneous. No patients were in remission, and all patients were treated at the time of the ASQ measurement.
Color Imaging Color Doppler (CD) flow imaging was used to assess the vascularity of the thyroid. The CD settings used remained constant for all patients. The total gain was the only setting that the operator could modify. The CD pattern was defined as normal (type I), or markedly increased (type II). The thyroid volume was calculated as the sum of the volumes of both lobes and of that of the isthmus. The volumes of each lobe and of the isthmus were calculated using the rotation ellipsoid model formula17: VLobe (mL) = π/6 × Width (cm) × Depth (cm) × Length (cm). The interobserver agreement between the two radiologists was assessed by using kappa statistics.
ASQ The image analysis of speckle patterns has been used to identify tissue characteristics associated with autoimmune thyroiditis because of the pattern changes according to the structural characteristics of the medium. One of these analytical methods, the probability density function (PDF) of the echo amplitude of a speckle pattern, is reported to be approximated using a function called the Rayleigh distribution. The principles of the ASQ method are as follows: when echo signals are generated from very small, dense scatters that are beyond the limit of spatial resolution, the pattern of the US image is constructed based on the interference of the sound waves (speckle noise). In that case, the PDF of the echo amplitude can be approximated using the Rayleigh distribution function. The results for a thyroid parenchymal alteration are significantly less similar to the Rayleigh distribution. Once the examiner sets a ROI (hereafter referred to as a large ROI) on the image, several hundred small ROIs (hereafter small ROIs) are automatically set to calculate the PDF (Figure 1). Multiple results for small ROIs in a large ROI are displayed as occurrence frequency polygons (Figure 2). Normal tissue parenchyma is composed primarily of various structures that are smaller than the wavelength of the typical US pulse used in clinical examinations. Tissues containing fibrotic structures can easily be detected by an US because their dimensions are larger than the US wavelength. ASQ measures the difference between the theoretical echo amplitude distribution and the real measurements obtained in a patient’s ROI using the adjusted chi-square test as statistical tool.18 The difference between these is depicted as frequency polygons, and the first-order statistics of these frequency polygons are shown as an average and a standard deviation (Figure 3). An improved analysis is obtained for the ASQ by using the raw data before any post-processing. This offers two presentation modes. One is a statistical graph that maps the distribution curve
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Figure 1. Schematic of region of interests used for statistical analysis of the radiofrequency signal with the acoustic structure quantification method and the frequency polygons. The PDF (green line) measured in a ROI is displayed against the theoretical speckle generated using Rayleigh distribution (red line). PDF = probability density function; ROI = region of interest. Note: Figure is available in full color in the online version at http://uix.sagepub.com/
Figure 2. The difference between the PDF and the theoretical speckle is shown as the occurrence in the frequency polygons (red line). PDF = probability density function. Note: Figure is available in full color in the online version at http://uix.sagepub.com/
of the probability of parenchymal structures, which reflects the US beam, or the “homogeneity” or “smoothness” of the tissue. The other display is a Doppler-like image with colors that are associated with the different values superimposed over the grayscale sonogram (Figure 4). The ASQ measurements in the present study were performed with a Toshiba Aplio XG scanner using a 2- to 6-MHz convex probe. The ASQ measurements for each patient were performed within an ROI drawn manually on the thyroid (Figure 3). The ROI with a set size of 1 × 1.5 cm were positioned in the saved grayscale image. All of the images were analyzed using the ASQ analysis software. The ROI actually consists of several hundred small ROIs used to calculate multiple square centimeter (intensity or amplitude) values; these calculations were done with the ASQ analysis software.19 The time intervals between the diagnoses of thyroid disease and the ASQ measurements ranged from 2 to 12 months.
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Figure 3. ASQ measurement of the thyroid lobe. The difference between the PDF and the theoretical speckle is shown as the occurrence in the frequency polygons (red line). ASQ = acoustic structure quantification; PDF = probability density function; ROI = region of interest. Note: Figure is available in full color in the online version at http://uix.sagepub.com/
Figure 4. The image shows the colored ASQ values. ASQ = acoustic structure quantification. Note: Figure is available in full color in the online version at http://uix.sagepub.com/
Statistical Analysis The data obtained from patients were collected in a Microsoft Excel file (Microsoft Office 2013, Microsoft) and analyzed statistically using SPSS (Version 20, IBM) and ACOMED Statistic (Version 1, ACOMED) programs. In addition, a Mann–Whitney U test was used to compare the median ASQ values of the three different groups, and the results are presented as a boxplot. The diagnostic performance of the ASQ was assessed using receiver operating characteristic (ROC)
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curves that were constructed for the prediction of thyroid tissue changes. The optimal cutoff values were chosen to maximize the sum of sensitivity and specificity; the 95% confidence intervals (CIs) were calculated for each of the estimates of sensitivity and specificity.
Results We evaluated 83 subjects (72 [87%] women and 11 [13%] men) aged 19 to 94 years with a mean age of 53 years. The study was performed prospectively (from March 2011 to November 2014) and included 43 (52%) patients with CAT, 22 (26%) patients with GD, and 18 (22%) healthy volunteers. The 43 patients diagnosed with CAT included 36 (84%) women and 7 (16%) men with a mean age of 60 years. The thyroid volume was decreased in 13 (30%) patients, increased in 2 (5%), and normal in 28 (65%) patients. The ASQ values were lower in healthy subjects (median: 97) than in subjects diagnosed with CAT disease (median: 112) (p < 0.001). The thyroid was hypoechoic in 25 (58%) of the 43 patients. Heterogeneity of the thyroid parenchyma was seen in 16 (37%) of the patients. In the group with CAT, the CD pattern was of type I in 38 (88%) and of type II in 3 (7%) of the patients. The 22 patients diagnosed with GD had a mean age of 47 years and included 20 (91%) women and 2 (9%) men. Five (23%) patients showed increased thyroid volume, whereas 17 (77%) had a normal thyroid volume. The ASQ values were lower in healthy subjects (median: 97) than in subjects diagnosed with GD disease (median: 117; p < 0.001). The echogenicity was decreased in 7 (32%) patients. The thyroid appeared heterogeneous in 13 (59%) patients. The CD pattern was of type II in 12 (54%) and of type I in 10 (46%). The CD patterns and the thyroid volumes were significantly different in the CAT and in GD cases (p < 0.001). The ASQ values in healthy volunteers and in patients diagnosed with CAT and GD are presented in Figures 5 to 8. There was no statistically significant difference between the ASQ values in the GD (median: 117) and in the CAT (median: 112) patients (p = 0.23). The optimal cutoff ASQ value for which the sum of sensitivity and specificity was the highest for the prediction of diffuse thyroid pathology was 103 (95% CI = [0.79, 0.95]). For this cutoff value, ASQ had a sensitivity of 83% and a specificity of 89%. To obtain a sensitivity >90% in predicting diffuse thyroid pathology, the best ASQ cutoff was 98 (95% CI = [0.79, 0.95]; 91% sensitivity, 56% specificity; Figure 9).20 The sensitivity and the specificity of the presence of hypoechogenicity for identifying AITD were 56% and 99%, respectively. When used in combination, the ASQ measurements and the presence of hypoechogenicity of the thyroid showed a sensitivity and specificity of 91% and 99%, respectively, in the diagnosis of CAT. There was full agreement between the two observers regarding the US diagnosis of AITD in 86% of the 83 patients. The interobserver agreement was good (with a kappa index of 0.70). There were disagreements between the two radiologists’ interpretations in 12 cases.
Discussion US has developed rapidly in recent years and now plays a critical role in the diagnosis of thyroid diseases.21 Several US parameters contribute to the diagnosis of CAT using both grayscale imaging (glandular volume, echotexture, and echogenicity) and CD; however, the interpretation of these qualitative findings depends highly on the expertise of the sonographer. The novelty of the ASQ technique is that it is based on the raw grayscale data and is operator independent. The raw data are collected before the application of the scan converter and the lateral filter. Downloaded from uix.sagepub.com at UNIV OF OTTAWA LIBRARY on August 5, 2015
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Figure 5. Boxplot graphics of thyroid ASQ values assessed using acoustic structure quantification in healthy subjects versus patients with thyroid pathology. The ASQ values were lower in normal subjects (median: 97) than in subjects diagnosed with CAT disease (median: 112; p < 0.001). The ASQ values were lower in normal subjects (median: 97) than in subjects diagnosed with GD disease (median: 117; p < 0.001). ASQ = acoustic structure quantification; CAT = chronic autoimmune thyroiditis; GD = Graves’ disease.
The diagnosis of CAT can be made at any thyroid function state, but it is not typically characterized by a painful thyroid enlargement or biochemical or clinical signs of inflammation. Vascularization can be increased, normal, or decreased in CAT patients. In a CAT patient, a thyroid nuclear scan generally shows only a slight reduction or focal change in iodine or technetium uptake. The ASQ is easy to perform and requires no more than 2 to 3 minutes. In this study, we obtained significantly higher ASQ values in the CAT patients than in the healthy control group. In most CAT patients, the echogenicity of the parenchyma is decreased. This decrease in echogenicity is believed to result from the reduction of the colloid/cellular interfaces, which are responsible for the normal echogenicity of the gland and from the lymphocytic infiltration of the thyroid tissue. The ASQ values were significantly higher in patients diagnosed with GD than in the control group. This may also be explained by the reduced colloid content and lymphocytic infiltration that are characteristic of GD, in addition to the increased intrathyroidal blood flow.22 At the time of the US examination, the radiologists often do not have the results of the thyroid laboratory tests. In such cases, an ASQ value above 98 should alert the radiologist of the presence of AITD. The ASQ measurement provides a quantification of thyroid parenchymal changes in AITD.
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Figure 6. Scatter diagram for ASQ value and age. Each point represents the ASQ value and age of one of the 83 patients aged 19 to 94 years. ASQ = acoustic structure quantification; CAT = chronic autoimmune thyroiditis; GD = Graves’ disease.
Figure 7. The colored ASQ values of (a) CAT, (b) GD, and (b) healthy patients. ASQ = acoustic structure quantification; CAT = chronic autoimmune thyroiditis; GD = Graves’ disease. Note: Figure is available in full color in the online version at http://uix.sagepub.com/
To identify AITD, the hypoechogenicity sensitivity and specificity were 56% and 99%, respectively. In the diagnosis of AITD, the combination of the ASQ measurements and the presence of thyroid hypoechogenicity showed a sensitivity and specificity of 91% and 99%, respectively. To identify GD, the sensitivity and specificity of the CD type II pattern were 55% and 99%, respectively, and when these measures were combined with the ASQ measurements, the sensitivity and specificity were 90% and 99%, respectively. The CD patterns and thyroid volumes were significantly different in the CAT and GD cases (p < 0.001). These parameters combined with the ASQ measurements could be useful for differentiating GD patients from CAT patients. We believe that a combination of a high ASQ score and presence of hypoechogenicity has a higher diagnostic accuracy in identifying AITD than the mere presence of hypoechogenicity. To the best of our knowledge, this is the first study to use the ASQ technique for the quantification of AITD.
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Figure 8. The PDF function of (a) CAT, (b) GD, and (c) healthy patients. PDF = probability density function; CAT = chronic autoimmune thyroiditis; GD = Graves’ disease; ASQ = acoustic structure quantification. Note: Figure is available in full color in the online version at http://uix.sagepub.com/
Figure 9. The ROC curve of the ASQ values assessed using acoustic structure quantification in healthy subjects and inpatients with thyroid pathology. ROC = receiver operating characteristic; ASQ = acoustic structure quantification.
One limitation of our study is that we did not apply the ASQ to other types of thyroiditis. Another limitation of this study is that the estimates of sensitivity and specificity for the optimal cutoff ASQ value were biased high because they were estimated based on the same data used to determine the optimal cutoff point. In addition, the ROIs were measured with a spacer manually, and thus small differences cannot be excluded. Moreover, the inclusion of areas rich in vessels could lead to unreliable results related to the vacuum effect of the vessels. Our experience with ASQ shows encouraging results in the diagnosis of patients with AITD. Use of the software during routine US examinations of patients with AITD makes it possible to Downloaded from uix.sagepub.com at UNIV OF OTTAWA LIBRARY on August 5, 2015
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combine ultrasonography with a quantitative evaluation of AITD. We believe that a combined analysis of the parameters provided by the software, together with the possibility of positioning an automatic ROI in the parametric map and algorithm for the automatic removal of small vessels in the ROI, could improve the diagnostic ability of this technique in the future. Thus, we have planned further studies with a larger inpatient AITD population under therapy to evaluate this technique for monitoring and optimizing the therapy. Larger and possibly multicenter studies would help us clearly define the place of this technique in the diagnosis of AITD. The population size is defined using the following formula: SampleSize=
( z score )2 × SD × (1 − SD ) , ( margin of error )2
with 95% CI, 0.5 SD, and a margin of error (CI) of ±9%.
Conclusion ASQ appears to be a useful method for the evaluation of CAT and GD with high specificity for cutoff values (>103). Thyroid US is an inherent part of routine examinations for clinical routine inpatients with thyroid diseases. Therefore, further improvements of this method are necessary. More studies are needed to determine which ASQ parameters are relevant for monitoring the parenchymal changes in inpatients with AITD. The ROI should be set automatically by the software to eliminate the interobserver variability. In addition, another algorithm is necessary to exclude small vessels from the analysis. Authors’ Note The authors agree that the material presented in this paper has not been published before, nor has it been submitted for publication to another scientific journal or considered for publication elsewhere. I attest that this work has been approved by all co-authors.
Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.
References 1. Canaris GJ, Manowitz NR, Mayor G, Ridgway EC. The Colorado thyroid disease prevalence study. Arch Intern Med. 2000;160(4):526-34. 2. Hollowell JG, Staehling NW, Flanders WD, Hannon WH, Gunter EW, Spencer CA, et al. Serum TSH, T(4), and thyroid antibodies in the United States population (1988 to 1994): National Health and Nutrition Examination Survey (NHANES III). J Clin Endocrinol Metab. 2002;87(2):489-99. 3. Slatosky J, Shipton B, Wahba H. Thyroiditis: differential diagnosis and management. Am Fam Physician. 2000;61(4):1047-52.1054. 4. Barbesino G, Chiovato L. The genetics of Hashimoto’s disease. Endocrinol Metab Clin North Am. 2000;29(2):357-74. 5. Jemeson JL, Weetman AP. Disorders of the thyroid gland. In: E Braunwald E, Fauci A, eds. Harrison’s Principles of Internal Medicine. 15th ed., Vol. 2. New York: McGraw-Hill; 2001. p. 2060. 6. Pedersen OM, Aardal NP, Larssen TB, Varhaug JE, Myking O, Vik-Mo H. The value of ultrasonography in predicting autoimmune thyroid disease. Thyroid. 2000;10(3):251-9.
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7. Gutekunst R, Hafermann W, Mansky T, Scriba PC. Ultrasonography related to clinical and laboratory findings in lymphocytic thyroiditis. Acta Endocrinol. 1989;121(1):129-35. 8. Marcocci C, Vitti P, Cetani F, Catalano F, Concetti R, Pinchera A. Thyroid ultrasonography helps to identify patients with diffuse lymphocytic thyroiditis who are prone to develop hypothyroidism. J Clin Endocrinol Metab. 1991;72(1):209-13. 9. Adams H, Jones MC, Othman S, Lazarus JH, Parkes AB, Hall R, et al. The sonographic appearances in postpartum thyroiditis. Clin Radiol. 1992;45(5):311-5. 10. Vitti P, Rago T, Mancusi F, Pallini S, Tonacchera M, Santini F, et al. Thyroid hypoechogenic pattern at ultrasonography as a tool for predicting recurrence of hyperthyroidism after medical treatment in patients with Graves’ disease. Acta Endocrinol. 1992;126(2):128-31. 11. Kim DW, Eun CK, In HS, Kim MH, Jung SJ, Bae SK. Sonographic differentiation of asymptomatic diffuse thyroid disease from normal thyroid: a prospective study. AJNR Am J Neuroradiol. 2010;31(10):1956-60. 12. Sporea I, Vlad M, Bota S, Sirli RL, Popescu A, Danila M, et al. Thyroid stiffness assessment by acoustic radiation force impulse elastography (ARFI). Ultraschall Med. 2011;32(3):281-5. 13. Ruchala M, Szczepanek-Parulska E, Zybek A, Moczko J, Czarnywojtek A, Kaminski G, et al. The role of sonoelastography in acute, subacute and chronic thyroiditis: a novel application of the method. Eur J Endocrinol. 2012;166(3):425-32. 14. Ciledag N, Arda K, Aribas BK, Aktas E, Köse SK. The utility of ultrasound elastography and MicroPure imaging in the differentiation of benign and malignant thyroid nodules. AJR Am J Roentgenol. 2012;198(3):W244-9. 15. Ricci P, Marigliano C, Cantisani V, Porfiri A, Marcantonio A, Lodise P, et al. Ultrasound evaluation of liver fibrosis: preliminary experience with acoustic structure quantification (ASQ) software. La radiologia medica. 2013;118(6), 995-1010. 16. Krämer C, Jaspers N, Nierhoff D, Kuhr K, Bowe A, Goeser T, et al. Acoustic structure quantification ultrasound software proves imprecise in assessing liver fibrosis or cirrhosis in parenchymal liver diseases. Ultrasound Med Biol. 2014;40(12), 2811-8. 17. Knudsen N, Bols B, Bülow I, Jørgensen T, Perrild H, Ovesen L, et al. Validation of ultrasonography of the thyroid gland for epidemiological purposes. Thyroid. 1999;9(11):1069-74. 18. Yamada H, Ebara M, Yamaguchi T, Okabe S, Fukuda H, Yoshikawa M, et al. A pilot approach for quantitative assessment of liver fibrosis using ultrasound: preliminary results in 79 cases. J Hepatol. 2006; 44(1):68-75. 19. Kuroda H, Kakisaka K, Kamiyama N, Oikawa T, Onodera M, Sawara K, et al. Non-invasive determination of hepatic steatosis by acoustic structure quantification from ultrasound echo amplitude. World J Gastroenterol. 2012;7;18(29):3889-95. 20. Hanley JA, Mcneil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 1982; 143(1):29-36. 21. Shung KK. Diagnostic ultrasound: past, present, and future. J Med Biol Eng. 2011;31(6):371-4. 22. Li Volsi V, ed. Surgical Pathology of the Thyroid. Philadelphia, PA: W.B. Saunders; 1990. p. 82.
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research-article2015
UIXXXX10.1177/0161734615580766Ultrasonic ImagingZandieh et al.
Article
Acoustic Structure Quantification Analysis of the Thyroid in Patients with Diffuse Autoimmune Thyroid Disease
Ultrasonic Imaging 1–11 © The Author(s) 2015 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0161734615580766 ultrasonicimaging.sagepub.com
Shahin Zandieh1, Reinhard Bernt1, Jochen Zwerina2, Joerg Haller1, Peter Knoll3, Orang Seyeddain4, and Siroos Mirzaei3
Abstract The aim of this study was to assess whether acoustic structure quantification (ASQ) can differentiate normal from pathological thyroid parenchyma in patients with diffuse autoimmune thyroid disease (AITD). We evaluated 83 subjects (72 [87%] women and 11 [13%] men) aged 19 to 94 years with a mean age of 53 years. We performed a prospective study (from March 2011 to November 2014) that included 43 (52%) patients with chronic autoimmune thyroiditis (CAT), 22 (26%) patients with Graves’ disease (GD), and 18 (22%) healthy volunteers. The ASQ values were significantly lower in normal subjects than in subjects with CAT and GD (p < 0.001). In contrast, the differences between the GD and the CAT patients (p = 0.23) were not statistically significant. The optimal cutoff ASQ value for which the sum of sensitivity and specificity was the highest for the prediction of diffuse thyroid pathology was 103 (95% confidence interval = [0.79, 0.95]). At this cutoff value, the sensitivity was 83% and the specificity was 89%. Our findings suggest that ASQ is a useful method for the assessment of the thyroid in patients with AITD. Keywords thyroid, ultrasound, autoimmune thyroid disease, tissue characterization, instrumentation
Introduction Chronic autoimmune thyroiditis (CAT) and Graves’ disease (GD) are the most common types of autoimmune thyroid disease (AITD), a common autoimmune disorder affecting mostly middle-aged women. About 2% to 4% of women and up to 1% of men are affected worldwide, 1Institute
of Radiology and Nuclear Medicine, Hanusch Hospital, Teaching Hospital of Medical University of Vienna, Austria 2Ludwig Boltzmann Institute of Osteology at the Hanusch Hospital of WGKK; Department of Internal Medicine, Hanusch Hospital, Teaching Hospital of Medical University of Vienna, Austria 3Institute of Nuclear Medicine with PET-Center, Wilhelminen Hospital, Teaching Hospital of Medical University of Vienna, Austria, Austria 4Department of Ophthalmology, Paracelsus Medical University of Salzburg, Austria Corresponding Author: Shahin Zandieh, Department of Radiology and Nuclear Medicine, Hanusch Hospital, Teaching Hospital of Medical University of Vienna, Heinrich-Collin-Strasse 30, Vienna 1140, Austria. Email: [email protected] Downloaded from uix.sagepub.com at UNIV OF OTTAWA LIBRARY on August 5, 2015
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and the prevalence rate increases with age.1 CAT is one of the most frequent causes of hypothyroidism2 and mostly affects people above the age of 50.3,4 In contrast, GD mainly affects younger individuals.5 In a previous study, thyroid sonography (ultrasound [US]) was shown to be of considerable value in establishing the absence of AITD) because it ruled out AITD in 88% of cases using an US examination alone.6 In most previous studies that used an US examination to diagnose AITD, the results varied considerably with diagnostic sensitivities ranging from 19% to 95%.6-10 Kim et al. showed the efficacy of an experienced radiologist using real-time thyroid US to identify asymptomatic diffuse thyroid disease. In their study, the sensitivity and the specificity in the diagnosis of asymptomatic diffuse thyroid disease were 87.7% and 92.1%, respectively.11 Over the last decade, methods that quantify changes in ultrasonic texture have focused on the non-invasive tissue classification of parenchymal organs through the use of different mathematical procedures.12-14 In the literature, a couple of studies have been reported on elastography and acoustic radiation force impulse (ARFI) elastography for thyroid assessment. These elastography techniques can assess the rigidity of tissue, but no information is given about the heterogeneity of the thyroid structure.12-14 US is an established method for the surveillance of patients with thyroid disease. Physical changes in the thyroid structure caused by nodules and fibrosis can be detected by grayscale US, but this appraisal is subjective and operator dependent. The assessment of stages and monitoring of disease progress quantitatively within routine US examinations may potentially optimize the therapeutic options. Acoustic structure quantification (ASQ) is a novel imaging technique that analyzes the statistical information of the acquired echo signals. The analysis of the speckled pattern in a certain region of interest (ROI) makes tissue differentiation possible. ASQ software has been used to analyze the level of fibrosis in the liver using statistical information of the acquired US echo signals. A couple of studies have evaluated the liver fibrosis in patients with chronic liver diseases using this technique.15,16 In the present study, we assessed whether an ASQ technique would be useful in the evaluation of AITD.
Materials and Method Study Subjects Consecutive patients with clinical symptoms or signs of CAT or GD were referred to the Nuclear Medicine Department of the Hanusch Hospital between March of 2011 and November of 2014. In addition, 18 healthy volunteers (medical students, nurses, and medical doctors from our hospital who did not have any known thyroid pathology) were examined. Two experienced radiologists who had no knowledge of the clinical or the laboratory data examined all subjects independently. All patients had been diagnosed with CAT or GD within the last 12 months in the Department of Nuclear Medicine of Hanusch Hospital. Written informed consent was obtained from all patients and volunteers who agreed to participate in our study, which was approved by our ethics committee. The serum levels of thyroid antibody were obtained from the medical records after the US examinations were performed. The diagnosis of CAT was based on the presence of high titers of antithyroid antibodies (antiTPO and/or anti-Tg) and a diffuse hypoechogenicity or heterogeneity of thyroid parenchyma at US. The diagnosis of GD was based on the following criteria: thyrotoxicosis at the beginning confirmed by a suppressed thyroid stimulating hormone (TSH), elevated FT4 and FT3 levels, and the presence of TSH receptor antibodies. All healthy volunteers had normal serum TSH values and negative thyroid antibodies.
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Brightness Modulation US examinations were performed with a Toshiba Aplio XG scanner (Toshiba Medical Systems, Tokyo, Japan) using a 2- to 6-MHz convex probe. Patients were examined in the supine position. The insonating frequency of the sector scanner was 4.7 MHz. The Toshiba unit incorporates a real-time scanner and a range-gated pulse Doppler velocity meter. The wall filter was set as low as possible, and the real-time brightness modulation (B-mode) was used to locate the thyroid and to evaluate the echogenicity. The echogenicity was described as isoechoic, hypoechoic, or hyperechoic in reference to the echogenicity of the strap muscles and submandibular glands. The echotexture was described as homogeneous or heterogeneous. No patients were in remission, and all patients were treated at the time of the ASQ measurement.
Color Imaging Color Doppler (CD) flow imaging was used to assess the vascularity of the thyroid. The CD settings used remained constant for all patients. The total gain was the only setting that the operator could modify. The CD pattern was defined as normal (type I), or markedly increased (type II). The thyroid volume was calculated as the sum of the volumes of both lobes and of that of the isthmus. The volumes of each lobe and of the isthmus were calculated using the rotation ellipsoid model formula17: VLobe (mL) = π/6 × Width (cm) × Depth (cm) × Length (cm). The interobserver agreement between the two radiologists was assessed by using kappa statistics.
ASQ The image analysis of speckle patterns has been used to identify tissue characteristics associated with autoimmune thyroiditis because of the pattern changes according to the structural characteristics of the medium. One of these analytical methods, the probability density function (PDF) of the echo amplitude of a speckle pattern, is reported to be approximated using a function called the Rayleigh distribution. The principles of the ASQ method are as follows: when echo signals are generated from very small, dense scatters that are beyond the limit of spatial resolution, the pattern of the US image is constructed based on the interference of the sound waves (speckle noise). In that case, the PDF of the echo amplitude can be approximated using the Rayleigh distribution function. The results for a thyroid parenchymal alteration are significantly less similar to the Rayleigh distribution. Once the examiner sets a ROI (hereafter referred to as a large ROI) on the image, several hundred small ROIs (hereafter small ROIs) are automatically set to calculate the PDF (Figure 1). Multiple results for small ROIs in a large ROI are displayed as occurrence frequency polygons (Figure 2). Normal tissue parenchyma is composed primarily of various structures that are smaller than the wavelength of the typical US pulse used in clinical examinations. Tissues containing fibrotic structures can easily be detected by an US because their dimensions are larger than the US wavelength. ASQ measures the difference between the theoretical echo amplitude distribution and the real measurements obtained in a patient’s ROI using the adjusted chi-square test as statistical tool.18 The difference between these is depicted as frequency polygons, and the first-order statistics of these frequency polygons are shown as an average and a standard deviation (Figure 3). An improved analysis is obtained for the ASQ by using the raw data before any post-processing. This offers two presentation modes. One is a statistical graph that maps the distribution curve
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Figure 1. Schematic of region of interests used for statistical analysis of the radiofrequency signal with the acoustic structure quantification method and the frequency polygons. The PDF (green line) measured in a ROI is displayed against the theoretical speckle generated using Rayleigh distribution (red line). PDF = probability density function; ROI = region of interest. Note: Figure is available in full color in the online version at http://uix.sagepub.com/
Figure 2. The difference between the PDF and the theoretical speckle is shown as the occurrence in the frequency polygons (red line). PDF = probability density function. Note: Figure is available in full color in the online version at http://uix.sagepub.com/
of the probability of parenchymal structures, which reflects the US beam, or the “homogeneity” or “smoothness” of the tissue. The other display is a Doppler-like image with colors that are associated with the different values superimposed over the grayscale sonogram (Figure 4). The ASQ measurements in the present study were performed with a Toshiba Aplio XG scanner using a 2- to 6-MHz convex probe. The ASQ measurements for each patient were performed within an ROI drawn manually on the thyroid (Figure 3). The ROI with a set size of 1 × 1.5 cm were positioned in the saved grayscale image. All of the images were analyzed using the ASQ analysis software. The ROI actually consists of several hundred small ROIs used to calculate multiple square centimeter (intensity or amplitude) values; these calculations were done with the ASQ analysis software.19 The time intervals between the diagnoses of thyroid disease and the ASQ measurements ranged from 2 to 12 months.
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Figure 3. ASQ measurement of the thyroid lobe. The difference between the PDF and the theoretical speckle is shown as the occurrence in the frequency polygons (red line). ASQ = acoustic structure quantification; PDF = probability density function; ROI = region of interest. Note: Figure is available in full color in the online version at http://uix.sagepub.com/
Figure 4. The image shows the colored ASQ values. ASQ = acoustic structure quantification. Note: Figure is available in full color in the online version at http://uix.sagepub.com/
Statistical Analysis The data obtained from patients were collected in a Microsoft Excel file (Microsoft Office 2013, Microsoft) and analyzed statistically using SPSS (Version 20, IBM) and ACOMED Statistic (Version 1, ACOMED) programs. In addition, a Mann–Whitney U test was used to compare the median ASQ values of the three different groups, and the results are presented as a boxplot. The diagnostic performance of the ASQ was assessed using receiver operating characteristic (ROC)
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curves that were constructed for the prediction of thyroid tissue changes. The optimal cutoff values were chosen to maximize the sum of sensitivity and specificity; the 95% confidence intervals (CIs) were calculated for each of the estimates of sensitivity and specificity.
Results We evaluated 83 subjects (72 [87%] women and 11 [13%] men) aged 19 to 94 years with a mean age of 53 years. The study was performed prospectively (from March 2011 to November 2014) and included 43 (52%) patients with CAT, 22 (26%) patients with GD, and 18 (22%) healthy volunteers. The 43 patients diagnosed with CAT included 36 (84%) women and 7 (16%) men with a mean age of 60 years. The thyroid volume was decreased in 13 (30%) patients, increased in 2 (5%), and normal in 28 (65%) patients. The ASQ values were lower in healthy subjects (median: 97) than in subjects diagnosed with CAT disease (median: 112) (p < 0.001). The thyroid was hypoechoic in 25 (58%) of the 43 patients. Heterogeneity of the thyroid parenchyma was seen in 16 (37%) of the patients. In the group with CAT, the CD pattern was of type I in 38 (88%) and of type II in 3 (7%) of the patients. The 22 patients diagnosed with GD had a mean age of 47 years and included 20 (91%) women and 2 (9%) men. Five (23%) patients showed increased thyroid volume, whereas 17 (77%) had a normal thyroid volume. The ASQ values were lower in healthy subjects (median: 97) than in subjects diagnosed with GD disease (median: 117; p < 0.001). The echogenicity was decreased in 7 (32%) patients. The thyroid appeared heterogeneous in 13 (59%) patients. The CD pattern was of type II in 12 (54%) and of type I in 10 (46%). The CD patterns and the thyroid volumes were significantly different in the CAT and in GD cases (p < 0.001). The ASQ values in healthy volunteers and in patients diagnosed with CAT and GD are presented in Figures 5 to 8. There was no statistically significant difference between the ASQ values in the GD (median: 117) and in the CAT (median: 112) patients (p = 0.23). The optimal cutoff ASQ value for which the sum of sensitivity and specificity was the highest for the prediction of diffuse thyroid pathology was 103 (95% CI = [0.79, 0.95]). For this cutoff value, ASQ had a sensitivity of 83% and a specificity of 89%. To obtain a sensitivity >90% in predicting diffuse thyroid pathology, the best ASQ cutoff was 98 (95% CI = [0.79, 0.95]; 91% sensitivity, 56% specificity; Figure 9).20 The sensitivity and the specificity of the presence of hypoechogenicity for identifying AITD were 56% and 99%, respectively. When used in combination, the ASQ measurements and the presence of hypoechogenicity of the thyroid showed a sensitivity and specificity of 91% and 99%, respectively, in the diagnosis of CAT. There was full agreement between the two observers regarding the US diagnosis of AITD in 86% of the 83 patients. The interobserver agreement was good (with a kappa index of 0.70). There were disagreements between the two radiologists’ interpretations in 12 cases.
Discussion US has developed rapidly in recent years and now plays a critical role in the diagnosis of thyroid diseases.21 Several US parameters contribute to the diagnosis of CAT using both grayscale imaging (glandular volume, echotexture, and echogenicity) and CD; however, the interpretation of these qualitative findings depends highly on the expertise of the sonographer. The novelty of the ASQ technique is that it is based on the raw grayscale data and is operator independent. The raw data are collected before the application of the scan converter and the lateral filter. Downloaded from uix.sagepub.com at UNIV OF OTTAWA LIBRARY on August 5, 2015
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Figure 5. Boxplot graphics of thyroid ASQ values assessed using acoustic structure quantification in healthy subjects versus patients with thyroid pathology. The ASQ values were lower in normal subjects (median: 97) than in subjects diagnosed with CAT disease (median: 112; p < 0.001). The ASQ values were lower in normal subjects (median: 97) than in subjects diagnosed with GD disease (median: 117; p < 0.001). ASQ = acoustic structure quantification; CAT = chronic autoimmune thyroiditis; GD = Graves’ disease.
The diagnosis of CAT can be made at any thyroid function state, but it is not typically characterized by a painful thyroid enlargement or biochemical or clinical signs of inflammation. Vascularization can be increased, normal, or decreased in CAT patients. In a CAT patient, a thyroid nuclear scan generally shows only a slight reduction or focal change in iodine or technetium uptake. The ASQ is easy to perform and requires no more than 2 to 3 minutes. In this study, we obtained significantly higher ASQ values in the CAT patients than in the healthy control group. In most CAT patients, the echogenicity of the parenchyma is decreased. This decrease in echogenicity is believed to result from the reduction of the colloid/cellular interfaces, which are responsible for the normal echogenicity of the gland and from the lymphocytic infiltration of the thyroid tissue. The ASQ values were significantly higher in patients diagnosed with GD than in the control group. This may also be explained by the reduced colloid content and lymphocytic infiltration that are characteristic of GD, in addition to the increased intrathyroidal blood flow.22 At the time of the US examination, the radiologists often do not have the results of the thyroid laboratory tests. In such cases, an ASQ value above 98 should alert the radiologist of the presence of AITD. The ASQ measurement provides a quantification of thyroid parenchymal changes in AITD.
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Figure 6. Scatter diagram for ASQ value and age. Each point represents the ASQ value and age of one of the 83 patients aged 19 to 94 years. ASQ = acoustic structure quantification; CAT = chronic autoimmune thyroiditis; GD = Graves’ disease.
Figure 7. The colored ASQ values of (a) CAT, (b) GD, and (b) healthy patients. ASQ = acoustic structure quantification; CAT = chronic autoimmune thyroiditis; GD = Graves’ disease. Note: Figure is available in full color in the online version at http://uix.sagepub.com/
To identify AITD, the hypoechogenicity sensitivity and specificity were 56% and 99%, respectively. In the diagnosis of AITD, the combination of the ASQ measurements and the presence of thyroid hypoechogenicity showed a sensitivity and specificity of 91% and 99%, respectively. To identify GD, the sensitivity and specificity of the CD type II pattern were 55% and 99%, respectively, and when these measures were combined with the ASQ measurements, the sensitivity and specificity were 90% and 99%, respectively. The CD patterns and thyroid volumes were significantly different in the CAT and GD cases (p < 0.001). These parameters combined with the ASQ measurements could be useful for differentiating GD patients from CAT patients. We believe that a combination of a high ASQ score and presence of hypoechogenicity has a higher diagnostic accuracy in identifying AITD than the mere presence of hypoechogenicity. To the best of our knowledge, this is the first study to use the ASQ technique for the quantification of AITD.
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Figure 8. The PDF function of (a) CAT, (b) GD, and (c) healthy patients. PDF = probability density function; CAT = chronic autoimmune thyroiditis; GD = Graves’ disease; ASQ = acoustic structure quantification. Note: Figure is available in full color in the online version at http://uix.sagepub.com/
Figure 9. The ROC curve of the ASQ values assessed using acoustic structure quantification in healthy subjects and inpatients with thyroid pathology. ROC = receiver operating characteristic; ASQ = acoustic structure quantification.
One limitation of our study is that we did not apply the ASQ to other types of thyroiditis. Another limitation of this study is that the estimates of sensitivity and specificity for the optimal cutoff ASQ value were biased high because they were estimated based on the same data used to determine the optimal cutoff point. In addition, the ROIs were measured with a spacer manually, and thus small differences cannot be excluded. Moreover, the inclusion of areas rich in vessels could lead to unreliable results related to the vacuum effect of the vessels. Our experience with ASQ shows encouraging results in the diagnosis of patients with AITD. Use of the software during routine US examinations of patients with AITD makes it possible to Downloaded from uix.sagepub.com at UNIV OF OTTAWA LIBRARY on August 5, 2015
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combine ultrasonography with a quantitative evaluation of AITD. We believe that a combined analysis of the parameters provided by the software, together with the possibility of positioning an automatic ROI in the parametric map and algorithm for the automatic removal of small vessels in the ROI, could improve the diagnostic ability of this technique in the future. Thus, we have planned further studies with a larger inpatient AITD population under therapy to evaluate this technique for monitoring and optimizing the therapy. Larger and possibly multicenter studies would help us clearly define the place of this technique in the diagnosis of AITD. The population size is defined using the following formula: SampleSize=
( z score )2 × SD × (1 − SD ) , ( margin of error )2
with 95% CI, 0.5 SD, and a margin of error (CI) of ±9%.
Conclusion ASQ appears to be a useful method for the evaluation of CAT and GD with high specificity for cutoff values (>103). Thyroid US is an inherent part of routine examinations for clinical routine inpatients with thyroid diseases. Therefore, further improvements of this method are necessary. More studies are needed to determine which ASQ parameters are relevant for monitoring the parenchymal changes in inpatients with AITD. The ROI should be set automatically by the software to eliminate the interobserver variability. In addition, another algorithm is necessary to exclude small vessels from the analysis. Authors’ Note The authors agree that the material presented in this paper has not been published before, nor has it been submitted for publication to another scientific journal or considered for publication elsewhere. I attest that this work has been approved by all co-authors.
Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.
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