Predictive value of 18F-FDG PET/CT radiomics for BCL-2/IgH fusion gene expression status in follicular lymphoma
10.3760/cma.j.cn321828-20240109-00011
- VernacularTitle:18F－FDG PET/CT影像组学对滤泡性淋巴瘤BCL－2/IgH融合基因表达状态的预测价值
- Author:
Xiaohe GAO
1
;
Yanmei LI
;
Jie CHEN
;
Jian SUN
;
Zeying WEN
Author Information
1. 河南中医药大学第一临床医学院，郑州 450046
- Keywords:
Lymphoma, follicular;
Genes, bcl-2;
Genes, immunoglobulin heavy chain;
Radiomics;
Positron-emission tomography;
Tomography, X-ray computed;
Fluorodeoxygluco
- From:
Chinese Journal of Nuclear Medicine and Molecular Imaging
2024;44(10):577-582
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the clinical application value of 18F-FDG PET/CT radiomics in predicting B-cell lymphoma-2 (BCL-2)/immunoglobulin heavy chain (IgH) fusion gene expression status in follicular lymphoma (FL) patients. Methods:A retrospective analysis was conducted on the clinical and imaging data of 90 FL patients (46 males and 44 females, age (48.7±10.5) years) who underwent 18F-FDG PET/CT examinations at Henan Cancer Hospital from January 2016 to August 2023. According to the expression status, patients were divided into positive group and negative group. Patients were randomly divided into training set ( n=62) and validation set ( n=28) at a ratio of 7∶3. PET and CT radiomics features were extracted by LIFEx 7.3.11 software. After using least absolute shrinkage and selection operator (LASSO) regression and ten-fold cross-validation for feature selection, PET and CT radiomics models were constructed. Univariate and multivariate analyses were used to select important clinical features and construct clinical model. Finally, a combined model was established by combining the radiomics features with clinical features. ROC curve and AUC were used to evaluate the predictive performance of models, and Delong test was used to compare the differences in AUCs. Results:After features selection, a total of 3 PET radiomics features, 3 CT radiomics features and 2 clinical features were selected for the construction of radiomics model and clinical model respectively. Multivariate analysis of clinical data showed that pathological grade (odds ratio ( OR)=0.201, 95% CI: 0.052-0.699, P=0.014) and maximum diameter of the maximum lesion (D max) ( OR=1.033, 95% CI: 1.009-1.065, P=0.017) were associated with BCL-2/IgH expression status. In the training set, the AUCs of clinical model, PET radiomics model, CT radiomics model and combined model were 0.84, 0.80, 0.80 and 0.91 respectively. In the validation set, the AUCs of the four models were 0.55, 0.61, 0.66 and 0.71 respectively. The combined model exhibited a trend toward higher in AUC than other three models in both the training and validation sets ( z values: 0.50-1.71, P values: 0.087-0.620). Conclusion:It is valuable to predict BCL-2/IgH fusion gene expression status based on PET/CT radiomics combined with clinical features.
