利用超声放射组学推进辐射阴道毒性评估:幻影验证和临床试验研究。

Medical physics Pub Date : 2025-05-08 DOI:10.1002/mp.17864
Jing Wang, Joseph Shelton, Boran Zhou, Deborah C Marshall, Himanshu Joshi, Emi J Yoshida, Xiaofeng Yang, Tian Liu
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引用次数: 0

摘要

背景:放疗引起的长期毒性,如阴道狭窄,严重影响妇科(GYN)恶性肿瘤盆腔放疗(RT)患者的生活质量。然而,目前评估这些毒性的方法依赖于主观体检和患者报告的症状,导致分级不一致和管理不理想。目的:本初步研究探讨基于超声的放射组学,特别是灰度共生矩阵(GLCM)纹理指标,作为评估长期辐射引起的阴道毒性的客观定量生物标志物的潜力。方法:采用两期研究。首先,进行了一项模拟研究,以确定具有低变异系数(COV)的GLCM纹理特征的鲁棒性。结果:17个GLCM特征具有鲁棒性(COV)。结论:该模拟研究和初步研究表明,超声GLCM特征可以作为可靠的定量生物标志物,用于评估接受骨盆放疗的女性妇科癌症患者的辐射诱导阴道毒性。在临床实践中实施这些生物标志物可以提高毒性评估的客观性,从而使分级更加一致,并为患者提供更好的随访护理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancing the evaluation of radiation-induced vaginal toxicity using ultrasound radiomics: Phantom validation and pilot clinical study.

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.

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