医学
无线电技术
神经组阅片室
可解释性
胶质瘤
放射科
人工智能
机器学习
神经学
计算机科学
精神科
癌症研究
作者
Yae Won Park,Jihwan Eom,Dain Kim,Sung Soo Ahn,Eui Hyun Kim,Seok‐Gu Kang,Jong Hee Chang,Se Hoon Kim,Seung‐Koo Lee
出处
期刊:European Radiology
[Springer Science+Business Media]
日期:2022-02-09
卷期号:32 (7): 4500-4509
被引量:31
标识
DOI:10.1007/s00330-022-08575-z
摘要
To develop a fully automatic radiomics model to differentiate adult pilocytic astrocytomas (PA) from high-grade gliomas (HGGs).This retrospective study included 302 adult patients with PA (n = 62) or HGG (n = 240). The patients were randomly divided into training (n = 211) and test (n = 91) sets. Clinical data were obtained, and radiomic features (n = 372) were extracted from multiparametric MRI with automatic tumour segmentation. After feature selection with F-score, a Light Gradient Boosting Machine classifier with subsampling was trained to develop three models: (1) clinical model, (2) radiomics model, and (3) combined clinical and radiomics model. Human performance was also assessed. The performance of the classifier was validated in the test set. SHapley Additive exPlanations (SHAP) was applied to explore the interpretability of the model.A total of 15 radiomic features were selected. In the test set, the combined clinical and radiomics model (area under the curve [AUC], 0.93) showed a significantly higher performance than the clinical model (AUC, 0.79, p = 0.037) and had a similar performance to the radiomics model (AUC, 0.92, p = 0.828). The combined clinical and radiomics model also showed a significantly higher performance than humans (AUC, 0.76-0.81, p < 0.05). The model explanation by SHAP suggested that lower intratumoural heterogeneity from T2-weighted images was highly associated with PA diagnosis.The fully automatic combined clinical and radiomics model may be helpful for differentiating adult PAs from HGGs.• Differentiating adult PAs from HGGs is challenging because PAs may manifest a large spectrum of imaging presentations, often including aggressive imaging features. • The fully automatic combined clinical and radiomics model showed a significantly higher performance than the clinical model or humans. • The model explanation by SHAP suggested that second-order features from T2-weighted imaging were important in diagnosis and might reflect the underlying pathophysiology that PAs have lesser tissue heterogeneity than HGGs.
科研通智能强力驱动
Strongly Powered by AbleSci AI