Predictive value of radiomics based on laparoscopic ultrasound imaging in microvascular invasion of hepatocellular carcinoma
10.3760/cma.j.cn131148-20240328-00186
- VernacularTitle:基于腹腔镜超声影像组学模型术中预测肝细胞性肝癌微血管浸润的价值
- Author:
Tongtong GUO
1
;
Hongchang LUO
;
Hanzhang WANG
;
Xiaojing LIN
;
Shu ZHU
;
Dan WANG
;
Wanguang ZHANG
Author Information
1. 华中科技大学同济医学院附属同济医院超声影像科，武汉 430030
- Keywords:
Ultrasonography;
Laparoscopic ultrasound;
Hepatocellular carcinoma;
Microvascular invasion;
Radiomics
- From:
Chinese Journal of Ultrasonography
2024;33(9):807-814
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct a predictive model of radiomics based on laparoscopic grayscale ultrasound features and investigate its value in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC) during laparoscopic liver resection.Methods:A total of 74 patients (74 lesions)with HCC confirmed by postoperative pathology, who underwent a laparoscopic ultrasonography during laparoscopic hepatectomy were prospectively enrolled in Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology from March 2022 to August 2023. The general clinical information of the patients was recorded, and the features were extracted and screened from tumor regions in gray-scale ultrasound images, and eventually the radiomics prediction models were constructed, respectively. Pathological results were used as gold standard to compare the effectiveness of different models in predicting MVI.Results:In the 74 HCC lesions, 12 lesions were MVI positive.The MVI imaging prediction model of HCC lesions was constructed from the screened clinical features, laparoscopic gray scale ultrasound image features, as well as combined screened clinical features, respectively. The obtained data sets were randomly divided into 5 parts (4 parts with 15 lesions, 1 part with 14 lesions), and the effectiveness of the model was trained and tested by the method of 5 folds interaction validation. The performance of support vector machine(SVM) radiomics model based on the characteristics of laparoscopic gray scale ultrasound in predicting the MVI of HCC was the best. Compared with clinical model and combined Adaboost model, the SVM, radiomics model had higher area under ROC curve (0.836 vs 0.696, 0.804), accuracy (0.852 vs 0.687, 0.838), sensitivity (0.900 vs 0.900, 0.833) and specificity (0.837 vs 0.644, 0.838). Conclusions:The radiomics model based on the characteristics of laparoscopic gray-scale ultrasound is an innovative potential approach to predict the MVI status of HCC lesions during laparoscopic hepatectomy.
