A contrast-enhanced CT-based radiomic nomogram for the differential diagnosis of intravenous leiomyomatosis and uterine leiomyoma

Jiang Shao; Chaonan Wang; Keqiang Shu; Yan Zhou; Ninghai Cheng; Zhichao Lai; Kang Li; Leyin Xu; Junye Chen; Fenghe Du; Xiaoxi Yu; Zhan Zhu; Jiaxian Wang; Yuyao Feng; Yixuan Yang; Xiaolong Liu; Jinghui Yuan; Bao Liu

doi:10.3389/fonc.2023.1239124

A contrast-enhanced CT-based radiomic nomogram for the differential diagnosis of intravenous leiomyomatosis and uterine leiomyoma

Front Oncol. 2023 Aug 23:13:1239124. doi: 10.3389/fonc.2023.1239124. eCollection 2023.

Authors

Jiang Shao¹, Chaonan Wang^{1

2}, Keqiang Shu¹, Yan Zhou^{1

3}, Ninghai Cheng⁴, Zhichao Lai¹, Kang Li¹, Leyin Xu¹, Junye Chen^{1

5}, Fenghe Du^{1

6}, Xiaoxi Yu^{1

3}, Zhan Zhu^{1

3}, Jiaxian Wang^{1

3}, Yuyao Feng¹, Yixuan Yang^{1

3}, Xiaolong Liu¹, Jinghui Yuan¹, Bao Liu¹

Affiliations

¹ Department of Vascular Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Science, Beijing, China.
² Plastic Surgery Hospital, Chinese Academy of Medical Science, Peking Union Medical College, Beijing, China.
³ Eight-year Program of Clinical Medicine, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
⁴ National Clinical Research Center for Obstetric & Gynecologic Diseases, Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
⁵ State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Department of Pathophysiology, Peking Union Medical College, Beijing, China.
⁶ Peking Union Medical College, MD Program, Beijing, China.

Abstract

Objective: Uterine intravenous leiomyomatosis (IVL) is a rare and unique leiomyoma that is difficult to surgery due to its ability to extend into intra- and extra-uterine vasculature. And it is difficult to differentiate from uterine leiomyoma (LM) by conventional CT scanning, which results in a large number of missed diagnoses. This study aimed to evaluate the utility of a contrast-enhanced CT-based radiomic nomogram for preoperative differentiation of IVL and LM.

Methods: 124 patients (37 IVL and 87 LM) were retrospectively enrolled in the study. Radiomic features were extracted from contrast-enhanced CT before surgery. Clinical, radiomic, and combined models were developed using LightGBM (Light Gradient Boosting Machine) algorithm to differentiate IVL and LM. The clinical and radiomic signatures were integrated into a nomogram. The diagnostic performance of the models was evaluated using the area under the curve (AUC) and decision curve analysis (DCA).

Results: Clinical factors, such as symptoms, menopausal status, age, and selected imaging features, were found to have significant correlations with the differential diagnosis of IVL and LM. A total of 108 radiomic features were extracted from contrast-enhanced CT images and selected for analysis. 29 radiomics features were selected to establish the Rad-score. A clinical model was developed to discriminate IVL and LM (AUC=0.826). Radiomic models were used to effectively differentiate IVL and LM (AUC=0.980). This radiological nomogram combined the Rad-score with independent clinical factors showed better differentiation efficiency than the clinical model (AUC=0.985, p=0.046).

Conclusion: This study provides evidence for the utility of a radiomic nomogram integrating clinical and radiomic signatures for differentiating IVL and LM with improved diagnostic accuracy. The nomogram may be useful in clinical decision-making and provide recommendations for clinical treatment.

Keywords: contrast-enhanced CT; intravenous leiomyomatosis; nomogram; preoperative differential; radiomics.

Grants and funding

This study received funding from the National High Level Hospital Clinical Research Funding (2022-PUMCH-A-078), National Natural Science Foundation of China (NO. 82070498), Non-profit Central Research Institute Fund of Chinese Academy of Medical Science (no. 2022-I2M-C&T-A-002), Beijing Science and Technology Innovation Foundation for University or College students (no:2023zglc06082) and Fundamental Research Funds for the Central Universities (no. 3332020009).