Jian Guo1,2, Zheng Li1,2, Xiaoxia Qu1,2, Junfang Xian1,2. 1. Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, PR China. 2. Clinical Center for Eye Tumors, Capital Medical University, Beijing, PR China.
Abstract
BACKGROUND: It is essential to distinguish malignant from benign epithelial neoplasms in the lacrimal gland for different treatment options and prognosis. PURPOSE: To retrospectively assess the performance of magnetic resonance imaging (MRI)-based radiomics features in the differentiation of benign and malignant epithelial neoplasms in the lacrimal gland. MATERIAL AND METHODS: Seventy-six consecutive patients with histopathology-proven epithelial neoplasms of the lacrimal gland were enrolled in the study, including 41 benign and 35 malignant neoplasms. Radiomics features were extracted from T2-weighted and post-contrast T1-weighted imaging. The least absolute shrinkage and selection operator method was used to select imaging features and reduce data dimension to discriminate malignant from benign neoplasms in the lacrimal gland. Diagnostic performance of the radiomics model was assessed by receive operation characteristic (ROC) curve and compared with that of radiologists. RESULTS: Four quantitative image features including inverse difference moment normalized (IDMN), mean deviation (MD), standard deviation (SD), and long-run emphasis (LRE) were selected to distinguish malignant from benign epithelial neoplasms in the lacrimal gland. Area under the curve (AUC) of these four features were 0.88, 086, 0.88, and 0.86, respectively, with 0.93 for the combination model. The model identified malignant epithelial neoplasms from benign group with 89% sensitivity, 93% specificity, and 89% accuracy. There was a significant difference in the diagnostic performance of radiomics model and the radiologists, with AUC of 0.70 for radiologists. The diagnostic performance of radiomics is superior to that of radiologists. CONCLUSION: MRI-based radiomics analysis has potential for differentiation of benign and malignant epithelial neoplasms in the lacrimal gland.
BACKGROUND: It is essential to distinguish malignant from benign epithelial neoplasms in the lacrimal gland for different treatment options and prognosis. PURPOSE: To retrospectively assess the performance of magnetic resonance imaging (MRI)-based radiomics features in the differentiation of benign and malignant epithelial neoplasms in the lacrimal gland. MATERIAL AND METHODS: Seventy-six consecutive patients with histopathology-proven epithelial neoplasms of the lacrimal gland were enrolled in the study, including 41 benign and 35 malignant neoplasms. Radiomics features were extracted from T2-weighted and post-contrast T1-weighted imaging. The least absolute shrinkage and selection operator method was used to select imaging features and reduce data dimension to discriminate malignant from benign neoplasms in the lacrimal gland. Diagnostic performance of the radiomics model was assessed by receive operation characteristic (ROC) curve and compared with that of radiologists. RESULTS: Four quantitative image features including inverse difference moment normalized (IDMN), mean deviation (MD), standard deviation (SD), and long-run emphasis (LRE) were selected to distinguish malignant from benign epithelial neoplasms in the lacrimal gland. Area under the curve (AUC) of these four features were 0.88, 086, 0.88, and 0.86, respectively, with 0.93 for the combination model. The model identified malignant epithelial neoplasms from benign group with 89% sensitivity, 93% specificity, and 89% accuracy. There was a significant difference in the diagnostic performance of radiomics model and the radiologists, with AUC of 0.70 for radiologists. The diagnostic performance of radiomics is superior to that of radiologists. CONCLUSION: MRI-based radiomics analysis has potential for differentiation of benign and malignant epithelial neoplasms in the lacrimal gland.
Entities:
Keywords:
Magnetic resonance imaging; lacrimal gland; neoplasms; radiomics