TY - JOUR
T1 - Advancing the evaluation of radiation-induced vaginal toxicity using ultrasound radiomics
T2 - Phantom validation and pilot clinical study
AU - Wang, Jing
AU - Shelton, Joseph
AU - Zhou, Boran
AU - Marshall, Deborah C.
AU - Joshi, Himanshu
AU - Yoshida, Emi J.
AU - Yang, Xiaofeng
AU - Liu, Tian
N1 - Publisher Copyright:
© 2025 American Association of Physicists in Medicine.
PY - 2025/7
Y1 - 2025/7
N2 - Background: Radiation-induced long-term toxicities, such as vaginal stenosis, severely impact the quality of life for patients undergoing pelvic radiotherapy (RT) for gynecologic (GYN) malignancies. However, current methods for assessing these toxicities rely on subjective physical examinations and patient-reported symptoms, leading to inconsistencies in grading and suboptimal management. Purpose: This pilot study investigates the potential of ultrasound-based radiomics, specifically gray level co-occurrence matrix (GLCM) texture metrics, as objective and quantitative biomarkers for evaluating long-term radiation-induced vaginal toxicity. Methods: A two-phase study was conducted. First, a phantom study was performed to identify robust GLCM texture features with low variability [coefficient of variance (COV) < 10%] across ultrasound brightness settings. In a subsequent clinical pilot study, 22 female participants were recruited: 10 had received pelvic radiotherapy (RT) with follow-up times ranging from 8 to 23 months, while 12 served as non-RT controls. All participants underwent transvaginal ultrasound imaging, and GLCM texture features were extracted for analysis. A Mann–Whitney U test was used to assess between-group differences of distribution, with a p value < 0.05 identified as statistically significance. Cohen's d values were calculated to quantify effect sizes, with a value of greater than 0.8 indicating large effects. Results: Seventeen GLCM features demonstrated robustness (COVs < 10%) across brightness settings in the phantom study, including two with COVs < 1%, 10 with COVs between 1% and 5%, and five with COVs between 5% and 10%. In the clinical study, four texture features showed significant differences between the treated group and controls (p < 0.05). Specifically, the treated group exhibited a 15.5% increase in correlation (p = 0.03), a 35.8% decrease in contrast (p = 0.03), a 10.1% decrease in difference entropy (p = 0.04), and a 17.9% decrease in dissimilarity (p = 0.07). Conclusion: This phantom and pilot study demonstrated that ultrasound GLCM features can serve as reliable quantitative biomarkers for assessing radiation-induced vaginal toxicity in female patients receiving pelvic RT for GYN cancers. Implementing these biomarkers in clinical practice could enhance the objectivity of toxicity evaluations, leading to more consistent grading and better-informed follow-up care for patients.
AB - Background: Radiation-induced long-term toxicities, such as vaginal stenosis, severely impact the quality of life for patients undergoing pelvic radiotherapy (RT) for gynecologic (GYN) malignancies. However, current methods for assessing these toxicities rely on subjective physical examinations and patient-reported symptoms, leading to inconsistencies in grading and suboptimal management. Purpose: This pilot study investigates the potential of ultrasound-based radiomics, specifically gray level co-occurrence matrix (GLCM) texture metrics, as objective and quantitative biomarkers for evaluating long-term radiation-induced vaginal toxicity. Methods: A two-phase study was conducted. First, a phantom study was performed to identify robust GLCM texture features with low variability [coefficient of variance (COV) < 10%] across ultrasound brightness settings. In a subsequent clinical pilot study, 22 female participants were recruited: 10 had received pelvic radiotherapy (RT) with follow-up times ranging from 8 to 23 months, while 12 served as non-RT controls. All participants underwent transvaginal ultrasound imaging, and GLCM texture features were extracted for analysis. A Mann–Whitney U test was used to assess between-group differences of distribution, with a p value < 0.05 identified as statistically significance. Cohen's d values were calculated to quantify effect sizes, with a value of greater than 0.8 indicating large effects. Results: Seventeen GLCM features demonstrated robustness (COVs < 10%) across brightness settings in the phantom study, including two with COVs < 1%, 10 with COVs between 1% and 5%, and five with COVs between 5% and 10%. In the clinical study, four texture features showed significant differences between the treated group and controls (p < 0.05). Specifically, the treated group exhibited a 15.5% increase in correlation (p = 0.03), a 35.8% decrease in contrast (p = 0.03), a 10.1% decrease in difference entropy (p = 0.04), and a 17.9% decrease in dissimilarity (p = 0.07). Conclusion: This phantom and pilot study demonstrated that ultrasound GLCM features can serve as reliable quantitative biomarkers for assessing radiation-induced vaginal toxicity in female patients receiving pelvic RT for GYN cancers. Implementing these biomarkers in clinical practice could enhance the objectivity of toxicity evaluations, leading to more consistent grading and better-informed follow-up care for patients.
KW - radiomics
KW - radiotherapy (RT)
KW - transvaginal ultrasound
KW - vaginal toxicity
UR - https://www.scopus.com/pages/publications/105004707563
U2 - 10.1002/mp.17864
DO - 10.1002/mp.17864
M3 - Article
AN - SCOPUS:105004707563
SN - 0094-2405
VL - 52
JO - Medical Physics
JF - Medical Physics
IS - 7
M1 - e17864
ER -