Jian Guo1, Zhenyu Liu2, Chen Shen3, Zheng Li1, Fei Yan1, Jie Tian4,5, Junfang Xian6. 1. Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No. 1 of Dongjiaominxiang, Dongcheng District, Beijing, 100730, China. 2. CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China. 3. School of Life Science and Technology, Xidian University, Xi'an, Shanxi, 710126, China. 4. CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China. jie.tian@ia.ac.cn. 5. University of Chinese Academy of Sciences, Beijing, 100049, China. jie.tian@ia.ac.cn. 6. Department of Radiology, Beijing Tongren Hospital, Capital Medical University, No. 1 of Dongjiaominxiang, Dongcheng District, Beijing, 100730, China. cjr.xianjunfang@vip.163.com.
Abstract
OBJECTIVES: To assess the value of the MR-based radiomics signature in differentiating ocular adnexal lymphoma (OAL) and idiopathic orbital inflammation (IOI). METHODS: One hundred fifty-seven patients with pathology-proven OAL (84 patients) and IOI (73 patients) were divided into primary and validation cohorts. Eight hundred six radiomics features were extracted from morphological MR images. The least absolute shrinkage and selection operator (LASSO) procedure and linear combination were used to select features and build radiomics signature for discriminating OAL from IOI. Discriminating performance was assessed by the area under the receiver-operating characteristic curve (AUC). The predictive results were compared with the assessment of radiologists by chi-square test. RESULTS: Five radiomics features were included in the radiomics signature, which differentiated OAL from IOI with an AUC of 0.74 and 0.73 in the primary and validation cohorts respectively. There was a significant difference between the classification results of the radiomics signature and those of a radiology resident (p < 0.05), although there was no significant difference between the results of the radiomics signature and those of a more experienced radiologist (p > 0.05). CONCLUSIONS: Radiomics features have the potential to differentiate OAL from IOI. KEY POINTS: • Clinical and imaging findings of OAL and IOI often overlap, which makes diagnosis difficult. • Radiomics features can potentially differentiate OAL from IOI non invasively. • The radiomics signature discriminates OAL from IOI at the same level as an experienced radiologist.
OBJECTIVES: To assess the value of the MR-based radiomics signature in differentiating ocular adnexal lymphoma (OAL) and idiopathic orbital inflammation (IOI). METHODS: One hundred fifty-seven patients with pathology-proven OAL (84 patients) and IOI (73 patients) were divided into primary and validation cohorts. Eight hundred six radiomics features were extracted from morphological MR images. The least absolute shrinkage and selection operator (LASSO) procedure and linear combination were used to select features and build radiomics signature for discriminating OAL from IOI. Discriminating performance was assessed by the area under the receiver-operating characteristic curve (AUC). The predictive results were compared with the assessment of radiologists by chi-square test. RESULTS: Five radiomics features were included in the radiomics signature, which differentiated OAL from IOI with an AUC of 0.74 and 0.73 in the primary and validation cohorts respectively. There was a significant difference between the classification results of the radiomics signature and those of a radiology resident (p < 0.05), although there was no significant difference between the results of the radiomics signature and those of a more experienced radiologist (p > 0.05). CONCLUSIONS: Radiomics features have the potential to differentiate OAL from IOI. KEY POINTS: • Clinical and imaging findings of OAL and IOI often overlap, which makes diagnosis difficult. • Radiomics features can potentially differentiate OAL from IOI non invasively. • The radiomics signature discriminates OAL from IOI at the same level as an experienced radiologist.
Entities:
Keywords:
Inflammation; Lymphoma; Magnetic resonance imaging (MRI); Orbital neoplasms; Radiomics
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