Radiomics for the noninvasive prediction of the BRAF mutation status in patients with melanoma brain metastases

Meissner, Anna-Katharina, Gutsche, Robin, Galldiks, Norbert, Kocher, Martin, Juenger, Stephanie T., Eich, Marie-Lisa, Montesinos-Rongen, Manuel, Brunn, Anna, Deckert, Martina, Wendl, Christina, Dietmaier, Wolfgang, Goldbrunner, Roland, Ruge, Maximilian, I, Mauch, Cornelia, Schmidt, Nils-Ole, Proescholdt, Martin, Grau, Stefan and Lohmann, Philipp . Radiomics for the noninvasive prediction of the BRAF mutation status in patients with melanoma brain metastases. Neuro-Oncology. CARY: OXFORD UNIV PRESS INC. ISSN 1523-5866

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DOI:10.1093/neuonc/noab294

Abstract

Background The BRAF V600E mutation is present in approximately 50% of patients with melanoma brain metastases and an important prerequisite for response to targeted therapies, particularly BRAF inhibitors. As heterogeneity in terms of BRAF mutation status may occur in melanoma patients, a wild-type extracranial primary tumor does not necessarily rule out a targetable mutation in brain metastases using BRAF inhibitors. We evaluated the potential of MRI radiomics for a noninvasive prediction of the intracranial BRAF mutation status. Methods Fifty-nine patients with melanoma brain metastases from two university brain tumor centers (group 1, 45 patients; group 2, 14 patients) underwent tumor resection with subsequent genetic analysis of the intracranial BRAF mutation status. Preoperative contrast-enhanced MRI was manually segmented and analyzed. Group 1 was used for model training and validation, group 2 for model testing. After radiomics feature extraction, a test-retest analysis was performed to identify robust features prior to feature selection. Finally, the best performing radiomics model was applied to the test data. Diagnostic performances were evaluated using receiver operating characteristic (ROC) analyses. Results Twenty-two of 45 patients (49%) in group 1, and 8 of 14 patients (57%) in group 2 had an intracranial BRAF V600E mutation. A linear support vector machine classifier using a six-parameter radiomics signature yielded an area under the ROC curve of 0.92 (sensitivity, 83%; specificity, 88%) in the test data. Conclusions The developed radiomics classifier allows a noninvasive prediction of the intracranial BRAF V600E mutation status in patients with melanoma brain metastases with high diagnostic performance.

Item Type:

Journal Article

Creators:

Creators	Email	ORCID	ORCID Put Code
Meissner, Anna-Katharina	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Gutsche, Robin	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Galldiks, Norbert	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Kocher, Martin	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Juenger, Stephanie T.	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Eich, Marie-Lisa	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Montesinos-Rongen, Manuel	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Brunn, Anna	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Deckert, Martina	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Wendl, Christina	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Dietmaier, Wolfgang	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Goldbrunner, Roland	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Ruge, Maximilian, I	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Mauch, Cornelia	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Schmidt, Nils-Ole	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Proescholdt, Martin	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Grau, Stefan	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Lohmann, Philipp	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED