Accepted Manuscript Title: Single Extracorporeal Shock-wave Lithotripsy for proximal ureter stones: Can CT Texture Analysis technique help predict the therapeutic effect? Authors: Yang Xun, Jiali Li, Yudi Geng, Zheng Liu, Xiao Yu, Xiang Wang, Fan Xiao, Zhen Li, Cong Li, Shaogang Wang PII: DOI: Reference:
S0720-048X(18)30293-6 https://doi.org/10.1016/j.ejrad.2018.08.018 EURR 8282
To appear in:
European Journal of Radiology
Received date: Revised date: Accepted date:
11-7-2018 13-8-2018 21-8-2018
Please cite this article as: Xun Y, Li J, Geng Y, Liu Z, Xiao Y, Wang X, Xiao F, Li Z, Li C, Wang S, Single Extracorporeal Shock-wave Lithotripsy for proximal ureter stones: Can CT Texture Analysis technique help predict the therapeutic effect?, European Journal of Radiology (2018), https://doi.org/10.1016/j.ejrad.2018.08.018 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Title Single Extracorporeal Shock-wave Lithotripsy for proximal ureter stones: Can CT Texture Analysis technique help predict the therapeutic effect?
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Author names and affiliations Yang Xuna#, Jiali Lib#, Yudi Gengc, Zheng Liua, Xiao Yua, Xiang Wanga, Fan Xiaoa, Zhen Lib,
#Co-first
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Cong Lia*, Shaogang Wanga authorship: Two authors contributed equally to this work
of Urology, Tongji Hospital, Tongji Medical College, Huazhong University
N
aDepartment
author:Cong Li
U
*Correspondence
M
bDepartment
A
of Science and Technology, No. 1095 Jiefang Avenue, Wuhan, Hubei, 430030, China. of Radiology, Tongji Hospital, Tongji Medical College, Huazhong
ED
University of Science and Technology, No. 1095 Jiefang Avenue, Wuhan, Hubei, 430030, China.
PT
cReproductive
medicine center, Tongji Hospital, Tongji Medical College, Huazhong
CC E
University of Science and Technology, No. 1095 Jiefang Avenue, Wuhan, Hubei, 430030, China.
A
Correspondence information *
Correspondence: Cong Li, Department of Urology, Tongji Hospital, Tongji Medical
College, Huazhong University of Science and Technology, No.1095 Jiefang Avenue, Wuhan, China. Tel. +86 027 8366 3460. E-mail address: [email protected]
Cong Li will handle correspondence at all stages of refereeing and publication, also post-publication.
Highlights 1, As a quantitative analysis method, computed tomography texture
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SC R
analysis (CTTA) may be helpful in selecting appropriate extracorporeal shock-wave lithotripsy (ESWL) patients.
2, Moreover, CTTA may be more helpful in selecting appropriate ESWL
3, Especially, patients with high kurtosis and low mean HU values may
N
U
patients compared with previous methods (such as mean HU).
Abstract
PT
ED
M
A
simultaneously achieve an optimal therapeutic effect.
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Purpose: To explore whether the computed tomography texture analysis (CTTA) technique can help predict the curative effects of a single
A
extracorporeal shock-wave lithotripsy (ESWL) for proximal ureteral stones. Materials and Methods: In all, 100 patients with proximal ureteral stone underwent non-enhanced multi-detector computed tomography (MDCT) before ESWL. The patients were divided into success and failure groups. Success of ESWL was defined as the patients being stone-free or having
residual stone fragments of ≤2 mm. Traditional characteristics, such as stone size, body mass index (BMI), and skin-to-stone distance (SSD), and CTTA metrics, such as the mean Hounsfield unit (HU) density, entropy, kurtosis, and skewness, were analyzed and compared between two groups by univariate
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and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curves were generated to determine Youden index-based cutoff values.
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Result: Failure of stone removal was observed in 36 patients (36%). Stone height, stone cross-sectional diameter, largest cross-sectional area, stone
U
volume, stone density (mean HU), and CTTA metrics (kurtosis and entropy)
N
were the significant independent predictors of ESWL success on univariate
A
analysis (p0, and kurtosis>−0.95 were significant predictors of ESWL success, with the odds ratios (ORs) of 0.253, 0.175, and 4.724, respectively (Table 3, p−0.95 (Table 4, p857 subgroup, the OR for kurtosis>−0.95 was much higher than that in the other subgroup.
Patients were then stratified into four risk categories: mean HU>857 and
A
kurtosis≤-0.95, mean HU≤857 and kurtosis≤−0.95, mean HU>857 and kurtosis>−0.95, mean HU≤857 and kurtosis>−0.95. The corresponding ESWL success rates were 28.6%, 62.1%, 71.4%, and 81.4%, respectively (Fig 4). Patients who had both mean HU≤857 and kurtosis>−0.95 were 4.2 times more
likely to have a successful ESWL than the others (OR 4.2, 95% CI 1.67–10.68, p=0.002). 4 Discussion The treatment of proximal urinary tract stones has been controversial for a
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long time. With technological progress in uroscopy, the retrograde intrarenal surgery (RIRS) technique, in particular, is currently considered an effective and
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safe procedure. With a satisfactory stone-free rate (SFR), safety, and
non-invasion, the major restriction of ESWL is the inaccuracy in predicting the
U
curative effect[6, 17].
N
According to the multivariate analysis, we found no significant differences in
A
SSD, BMI, and stone characteristics between ESWL success and failure
M
groups. Ahmed R. El-Nahas[1] et al reported similar results suggesting that
ED
SSD and stone volume cannot predict ESWL success rates; however, the study conducted by Timothy Y[10] et al and Hwang[18] et al demonstrated the
PT
contradictory results.
CC E
The mean HU was found to be an independent predictor of ESWL success in our research, similar to that in most previous studies. Joseph[19] and Wiesenthal JD[20] reported that mean HU can be used to predict the success
A
rate of ESWL, although the range of cutoff values in the two studies was different. Nevertheless, Cui H[21] and El-Nahas[1] demonstrated that mean HU cannot predict the curative effect of ESWL. The abovementioned contrary results reveal that the mean HU may not be stable and has some limitations in
predicting ESWL success. Possible reasons for this are as follows: first, the measurement result of mean HU is easily affected by the machine or scanning parameters[22] and second, mean HU could not reflect the distribution situation of high-density and low-density components in stones. We strongly
IP T
believe that the distribution of low-density components may be the key to ESWL success and our results supported this hypothesis. Skewness, entropy,
SC R
and kurtosis can reflect the heterogeneity of stones from different
perspectives[11]， which is equivalent to the distribution of different density
U
components in stones. Thus, to overcome the limitations of mean HU, CTTA
N
was introduced in this study.
A
Entropy represents the irregularity of pixel intensities. A study by Cui H[23] et
M
al showed that stones with higher entropy values required more ESWL shock
ED
waves. However, there was no such difference in our research. Skewness reflects the histogram asymmetry[24]. Negative skewness indicates that the
PT
tail on the left of the histogram is longer than that on the right, while positive
CC E
skewness indicates an opposite curve. In the present study, the results of multivariate analysis showed that skewness of the ESWL success group was negative and significantly lower than that of the ESWL failure group. We
A
assume that the group with negative skewness reflects a high-density component of calculus, resulting in a decreased density in rest of the portion, while mean HU is controlled. The success of ESWL mainly depends on the large proportion of low-density components of calculus, rather than the small
proportion of high-density components. Multivariate logistic regression analysis also showed that kurtosis was an independent predictor of ESWL success. Kurtosis reflects the peakedness of the histogram. A negative kurtosis indicates that the histogram is flatter than a
IP T
Gaussian (normal) distribution, whereas a positive kurtosis indicates the opposite status. This study showed that stones with kurtosis values greater
SC R
than −0.95 were more likely to successfully be fragmented by ESWL than
others. Some in vitro studies had results similar to ours. Cui H[23] et al
U
indicated that more negative kurtosis values were associated with greater
N
ESWL success rate. A convincing explanation for this is that when mean HU of
A
two groups is controlled, the calculus with higher kurtosis values indicates
M
greater heterogeneity of density components, which may lead to easy
ED
fragmentation”
In summary, multivariate logistic regression analysis showed that mean HU,
PT
skewness, and kurtosis can be used to predict the success of ESWL.
CC E
Considering that mean HU is the most commonly used clinical parameter, subgroup analysis was conducted according to the cutoff value (HU = 857) of mean HU, which was determined by the Youden index. Subgroup analysis
A
showed that kurtosis was the only independent predictor in both subgroups, and the OR was larger in the high-HU group. This may signify that kurtosis has better discrimination for ESWL success in a harder calculus. To determine the predictive effect of kurtosis value combined with mean HU,
patients were divided into four risk categories based on kurtosis and mean HU and the success rate of ESWL for each category was calculated and compared. The results showed that ESWL success rate of “mean HU −0.95” group was the highest, when compared with the other three
IP T
groups (p
S0720-048X(18)30293-6 https://doi.org/10.1016/j.ejrad.2018.08.018 EURR 8282
To appear in:
European Journal of Radiology
Received date: Revised date: Accepted date:
11-7-2018 13-8-2018 21-8-2018
Please cite this article as: Xun Y, Li J, Geng Y, Liu Z, Xiao Y, Wang X, Xiao F, Li Z, Li C, Wang S, Single Extracorporeal Shock-wave Lithotripsy for proximal ureter stones: Can CT Texture Analysis technique help predict the therapeutic effect?, European Journal of Radiology (2018), https://doi.org/10.1016/j.ejrad.2018.08.018 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Title Single Extracorporeal Shock-wave Lithotripsy for proximal ureter stones: Can CT Texture Analysis technique help predict the therapeutic effect?
IP T
Author names and affiliations Yang Xuna#, Jiali Lib#, Yudi Gengc, Zheng Liua, Xiao Yua, Xiang Wanga, Fan Xiaoa, Zhen Lib,
#Co-first
SC R
Cong Lia*, Shaogang Wanga authorship: Two authors contributed equally to this work
of Urology, Tongji Hospital, Tongji Medical College, Huazhong University
N
aDepartment
author:Cong Li
U
*Correspondence
M
bDepartment
A
of Science and Technology, No. 1095 Jiefang Avenue, Wuhan, Hubei, 430030, China. of Radiology, Tongji Hospital, Tongji Medical College, Huazhong
ED
University of Science and Technology, No. 1095 Jiefang Avenue, Wuhan, Hubei, 430030, China.
PT
cReproductive
medicine center, Tongji Hospital, Tongji Medical College, Huazhong
CC E
University of Science and Technology, No. 1095 Jiefang Avenue, Wuhan, Hubei, 430030, China.
A
Correspondence information *
Correspondence: Cong Li, Department of Urology, Tongji Hospital, Tongji Medical
College, Huazhong University of Science and Technology, No.1095 Jiefang Avenue, Wuhan, China. Tel. +86 027 8366 3460. E-mail address: [email protected]
Cong Li will handle correspondence at all stages of refereeing and publication, also post-publication.
Highlights 1, As a quantitative analysis method, computed tomography texture
IP T
SC R
analysis (CTTA) may be helpful in selecting appropriate extracorporeal shock-wave lithotripsy (ESWL) patients.
2, Moreover, CTTA may be more helpful in selecting appropriate ESWL
3, Especially, patients with high kurtosis and low mean HU values may
N
U
patients compared with previous methods (such as mean HU).
Abstract
PT
ED
M
A
simultaneously achieve an optimal therapeutic effect.
CC E
Purpose: To explore whether the computed tomography texture analysis (CTTA) technique can help predict the curative effects of a single
A
extracorporeal shock-wave lithotripsy (ESWL) for proximal ureteral stones. Materials and Methods: In all, 100 patients with proximal ureteral stone underwent non-enhanced multi-detector computed tomography (MDCT) before ESWL. The patients were divided into success and failure groups. Success of ESWL was defined as the patients being stone-free or having
residual stone fragments of ≤2 mm. Traditional characteristics, such as stone size, body mass index (BMI), and skin-to-stone distance (SSD), and CTTA metrics, such as the mean Hounsfield unit (HU) density, entropy, kurtosis, and skewness, were analyzed and compared between two groups by univariate
IP T
and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curves were generated to determine Youden index-based cutoff values.
SC R
Result: Failure of stone removal was observed in 36 patients (36%). Stone height, stone cross-sectional diameter, largest cross-sectional area, stone
U
volume, stone density (mean HU), and CTTA metrics (kurtosis and entropy)
N
were the significant independent predictors of ESWL success on univariate
A
analysis (p0, and kurtosis>−0.95 were significant predictors of ESWL success, with the odds ratios (ORs) of 0.253, 0.175, and 4.724, respectively (Table 3, p−0.95 (Table 4, p857 subgroup, the OR for kurtosis>−0.95 was much higher than that in the other subgroup.
Patients were then stratified into four risk categories: mean HU>857 and
A
kurtosis≤-0.95, mean HU≤857 and kurtosis≤−0.95, mean HU>857 and kurtosis>−0.95, mean HU≤857 and kurtosis>−0.95. The corresponding ESWL success rates were 28.6%, 62.1%, 71.4%, and 81.4%, respectively (Fig 4). Patients who had both mean HU≤857 and kurtosis>−0.95 were 4.2 times more
likely to have a successful ESWL than the others (OR 4.2, 95% CI 1.67–10.68, p=0.002). 4 Discussion The treatment of proximal urinary tract stones has been controversial for a
IP T
long time. With technological progress in uroscopy, the retrograde intrarenal surgery (RIRS) technique, in particular, is currently considered an effective and
SC R
safe procedure. With a satisfactory stone-free rate (SFR), safety, and
non-invasion, the major restriction of ESWL is the inaccuracy in predicting the
U
curative effect[6, 17].
N
According to the multivariate analysis, we found no significant differences in
A
SSD, BMI, and stone characteristics between ESWL success and failure
M
groups. Ahmed R. El-Nahas[1] et al reported similar results suggesting that
ED
SSD and stone volume cannot predict ESWL success rates; however, the study conducted by Timothy Y[10] et al and Hwang[18] et al demonstrated the
PT
contradictory results.
CC E
The mean HU was found to be an independent predictor of ESWL success in our research, similar to that in most previous studies. Joseph[19] and Wiesenthal JD[20] reported that mean HU can be used to predict the success
A
rate of ESWL, although the range of cutoff values in the two studies was different. Nevertheless, Cui H[21] and El-Nahas[1] demonstrated that mean HU cannot predict the curative effect of ESWL. The abovementioned contrary results reveal that the mean HU may not be stable and has some limitations in
predicting ESWL success. Possible reasons for this are as follows: first, the measurement result of mean HU is easily affected by the machine or scanning parameters[22] and second, mean HU could not reflect the distribution situation of high-density and low-density components in stones. We strongly
IP T
believe that the distribution of low-density components may be the key to ESWL success and our results supported this hypothesis. Skewness, entropy,
SC R
and kurtosis can reflect the heterogeneity of stones from different
perspectives[11]， which is equivalent to the distribution of different density
U
components in stones. Thus, to overcome the limitations of mean HU, CTTA
N
was introduced in this study.
A
Entropy represents the irregularity of pixel intensities. A study by Cui H[23] et
M
al showed that stones with higher entropy values required more ESWL shock
ED
waves. However, there was no such difference in our research. Skewness reflects the histogram asymmetry[24]. Negative skewness indicates that the
PT
tail on the left of the histogram is longer than that on the right, while positive
CC E
skewness indicates an opposite curve. In the present study, the results of multivariate analysis showed that skewness of the ESWL success group was negative and significantly lower than that of the ESWL failure group. We
A
assume that the group with negative skewness reflects a high-density component of calculus, resulting in a decreased density in rest of the portion, while mean HU is controlled. The success of ESWL mainly depends on the large proportion of low-density components of calculus, rather than the small
proportion of high-density components. Multivariate logistic regression analysis also showed that kurtosis was an independent predictor of ESWL success. Kurtosis reflects the peakedness of the histogram. A negative kurtosis indicates that the histogram is flatter than a
IP T
Gaussian (normal) distribution, whereas a positive kurtosis indicates the opposite status. This study showed that stones with kurtosis values greater
SC R
than −0.95 were more likely to successfully be fragmented by ESWL than
others. Some in vitro studies had results similar to ours. Cui H[23] et al
U
indicated that more negative kurtosis values were associated with greater
N
ESWL success rate. A convincing explanation for this is that when mean HU of
A
two groups is controlled, the calculus with higher kurtosis values indicates
M
greater heterogeneity of density components, which may lead to easy
ED
fragmentation”
In summary, multivariate logistic regression analysis showed that mean HU,
PT
skewness, and kurtosis can be used to predict the success of ESWL.
CC E
Considering that mean HU is the most commonly used clinical parameter, subgroup analysis was conducted according to the cutoff value (HU = 857) of mean HU, which was determined by the Youden index. Subgroup analysis
A
showed that kurtosis was the only independent predictor in both subgroups, and the OR was larger in the high-HU group. This may signify that kurtosis has better discrimination for ESWL success in a harder calculus. To determine the predictive effect of kurtosis value combined with mean HU,
patients were divided into four risk categories based on kurtosis and mean HU and the success rate of ESWL for each category was calculated and compared. The results showed that ESWL success rate of “mean HU −0.95” group was the highest, when compared with the other three
IP T
groups (p
