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Noninvasive molecular diagnosis of craniopharyngioma with MRI-based radiomics approach
Xi Chen1, Yusheng Tong2, Zhifeng Shi2
1Department of Electronic Engineering, Fudan University, Shanghai, China.
Background:
Frequent somatic mutations of BRAF and CTNNB1 were identified in both histological subtypes of craniopharyngioma (adamantinomatous and papillary) which shed light on target therapy to cure this oncogenic disease. The aim of this study was to investigate the noninvasive MRI-based radiomics diagnosis to detect BRAF and CTNNB1 mutations in craniopharyngioma patients.
Methods:
Forty-four patients pathologically diagnosed as adamantinomatous craniopharyngioma (ACP) or papillary craniopharyngioma (PCP) were retrospectively studied. High-throughput features were extracted from manually segmented tumors in MR images of each case. The modifications-robustness in region of interests and Random Forest-based feature selection methods were adopted to select the most significant features. Random forest classifier with 10-fold cross-validation was applied to build our radiomics model.
Results:
Four features were selected to make pathological diagnosis between ACP and PCP with area under the receiver operating characteristic curve (AUC) of 0.89, accurancy (ACC) of 0.86, sensitivity (SENS) of 0.89 and specificity (SPEC) of 0.85. The other two features were applied to estimate BRAF V600E mutation with AUC of 0.91, ACC of 0.93, SENS of 0.83 and SPEC of 0.97. Accurate predication of CTNNB1 mutation by three selected features was realized with AUC of 0.93, ACC of 0.86, SENS of 0.86 and SPEC of 0.86.
Conclusions:
We developed a reliable MRI-based radiomics approach to perform pathological and molecular diagnosis in craniopharyngioma patients with considerably accurate prediction, which could offer potential guidance for clinical decision-making.
Insights
This study presents a novel MRI-based radiomics approach for diagnosing craniopharyngioma subtypes and detecting BRAF and CTNNB1 mutations, offering accurate noninvasive predictions for better patient management.
Area of Science:
- Oncology
- Radiology
- Medical Imaging
Background:
- Craniopharyngiomas exhibit frequent BRAF and CTNNB1 mutations, crucial for targeted therapies.
- Histological subtypes include adamantinomatous (ACP) and papillary (PCP) craniopharyngioma.
- Noninvasive diagnostic methods are needed to guide treatment decisions.
Purpose of the Study:
- To develop and validate an MRI-based radiomics model for diagnosing craniopharyngioma subtypes.
- To assess the model's ability to predict BRAF and CTNNB1 mutations noninvasively.
- To provide a tool for accurate pathological and molecular diagnosis in craniopharyngioma patients.
Main Methods:
- Retrospective analysis of 44 craniopharyngioma patients (ACP and PCP).
- Extraction of high-throughput radiomic features from segmented MR images.
- Application of Random Forest for feature selection and classification with 10-fold cross-validation.
Main Results:
- Radiomics model accurately distinguished between ACP and PCP (AUC 0.89).
- BRAF V600E mutation prediction achieved high accuracy (AUC 0.91).
- CTNNB1 mutation prediction demonstrated strong performance (AUC 0.93).
Conclusions:
- An MRI-based radiomics approach provides reliable pathological and molecular diagnosis for craniopharyngioma.
- This noninvasive method shows potential for guiding clinical decision-making.
- Accurate prediction of mutations and subtypes can personalize treatment strategies.
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