Combined ultrasound and clinical characteristics to predict the treatment time of 90Sr radioisotope applicator therapy for pathologic scars
10.3760/cma.j.cn131148-20240205-00088
- VernacularTitle:超声与临床特征联合预测 90Sr敷贴治疗病理性瘢痕起效时间
- Author:
Yanjing CHEN
1
;
Yongshuai QI
;
Zhouyue JIANG
;
Yanyan ZHANG
;
Ting LANG
;
Yue LIN
;
Min CHANG
;
Yingjia LI
Author Information
1. 南方医科大学南方医院超声医学科，广州 510515
- Keywords:
Ultrasonography;
Strontium 90 radioisotope applicator therapy;
Pathological scars;
Treatment time
- From:
Chinese Journal of Ultrasonography
2024;33(7):603-608
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To combine ultrasound and clinical characteristics for predicting the treatment time of strontium 90( 90Sr) radioisotope applicator therapy for pathological scars when the therapeutic effect meets the clinical effective criteria. Methods:From September 2022 to October 2023, 48 patients (90 lesions) with pathological scars who underwent 90Sr radioisotope applicator therapy at the Department of Nuclear Medicine, Nanfang Hospital, Southern Medical University were prospectively collected. The clinically effective criteria of 90Sr radioisotope applicator therapy for pathological scars were defined as a reduction of the superficial height of the scar higher than 50%. All lesions were divided into short period treatment group (2 months, 38 lesions) and long period treatment group (>2 months, 52 lesions) according to the duration of treatment when the therapeutic effect met the clinical criteria. Univariate comparative analyses of ultrasound and clinical characteristics between the two groups were performed. The statistically significant variates were used to build a multivariate logistic regression model for analyzing the independent predictors of the treatment time of 90Sr radioisotope applicator therapy for pathological scars. Results:Family history, blood flow signal, disease duration, age, and scar Young′s modulus were independent predictors of the effective treatment time of 90Sr radioisotope applicator therapy for pathological scars (all P<0.05). By using the selected variables, a predictive model was developed, area under the ROC curve (AUC) were 0.886 (95% CI=0.817-0.955, P<0.001), and the calibration curve showed that the model was well calibrated(χ 2=5.668, P=0.684). Conclusions:The multivariate logistic regression model with family history, blood flow signal, disease duration, age, and scar Young′s modulus could be used to predict the treatment time of 90Sr radioisotope applicator therapy for pathologic scars, which can help to guide the design of treatment plan, reduce unnecessary radiation damage, and improve patient compliance.
