Multi-Parametric Radiomic Model to Predict 1p/19q Co-Deletion in Patients with IDH-1 Mutant Glioma: Added Value to the T2-FLAIR Mismatch Sign

Shingo Kihira; Ahrya Derakhshani; Michael Leung; Keon Mahmoudi; Adam Bauer; Haoyue Zhang; Jennifer Polson; Corey Arnold; Nadejda M. Tsankova; Adilia Hormigo; Banafsheh Salehi; Nancy Pham; Benjamin M. Ellingson; Timothy F. Cloughesy; Kambiz Nael

doi:10.3390/cancers15041037

Cancers (Feb 2023)

Multi-Parametric Radiomic Model to Predict 1p/19q Co-Deletion in Patients with IDH-1 Mutant Glioma: Added Value to the T2-FLAIR Mismatch Sign

Shingo Kihira,
Ahrya Derakhshani,
Michael Leung,
Keon Mahmoudi,
Adam Bauer,
Haoyue Zhang,
Jennifer Polson,
Corey Arnold,
Nadejda M. Tsankova,
Adilia Hormigo,
Banafsheh Salehi,
Nancy Pham,
Benjamin M. Ellingson,
Timothy F. Cloughesy,
Kambiz Nael

Affiliations

Shingo Kihira: Department of Radiological Sciences, David Geffen School of Medicine at University of California Los Angeles, 757 Westwood Plaza, Suite 1621, Los Angeles, CA 90095, USA
Ahrya Derakhshani: Department of Radiological Sciences, David Geffen School of Medicine at University of California Los Angeles, 757 Westwood Plaza, Suite 1621, Los Angeles, CA 90095, USA
Michael Leung: Department of Radiological Sciences, David Geffen School of Medicine at University of California Los Angeles, 757 Westwood Plaza, Suite 1621, Los Angeles, CA 90095, USA
Keon Mahmoudi: Department of Radiological Sciences, David Geffen School of Medicine at University of California Los Angeles, 757 Westwood Plaza, Suite 1621, Los Angeles, CA 90095, USA
Adam Bauer: Department of Radiology, Kaiser Permanente Fontana Medical Center, Fontana, CA 92335, USA
Haoyue Zhang: Department of Bioengineering, University of California Los Angeles, Los Angeles, CA 90095, USA
Jennifer Polson: Department of Bioengineering, University of California Los Angeles, Los Angeles, CA 90095, USA
Corey Arnold: Department of Radiological Sciences, David Geffen School of Medicine at University of California Los Angeles, 757 Westwood Plaza, Suite 1621, Los Angeles, CA 90095, USA
Nadejda M. Tsankova: Department of Pathology and Laboratory Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
Adilia Hormigo: Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
Banafsheh Salehi: Department of Radiological Sciences, David Geffen School of Medicine at University of California Los Angeles, 757 Westwood Plaza, Suite 1621, Los Angeles, CA 90095, USA
Nancy Pham: Department of Radiological Sciences, David Geffen School of Medicine at University of California Los Angeles, 757 Westwood Plaza, Suite 1621, Los Angeles, CA 90095, USA
Benjamin M. Ellingson: Department of Radiological Sciences, David Geffen School of Medicine at University of California Los Angeles, 757 Westwood Plaza, Suite 1621, Los Angeles, CA 90095, USA
Timothy F. Cloughesy: UCLA Brain Tumor Imaging Laboratory, Department of Radiological Sciences, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA 90095, USA
Kambiz Nael: Department of Radiological Sciences, David Geffen School of Medicine at University of California Los Angeles, 757 Westwood Plaza, Suite 1621, Los Angeles, CA 90095, USA

DOI: https://doi.org/10.3390/cancers15041037
Journal volume & issue: Vol. 15, no. 4
p. 1037

Abstract

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Purpose: The T2-FLAIR mismatch sign has shown promise in determining IDH mutant 1p/19q non-co-deleted gliomas with a high specificity and modest sensitivity. To develop a multi-parametric radiomic model using MRI to predict 1p/19q co-deletion status in patients with newly diagnosed IDH1 mutant glioma and to perform a comparative analysis to T2-FLAIR mismatch sign+. Methods: In this retrospective study, patients with diagnosis of IDH1 mutant gliomas with known 1p/19q status who had preoperative MRI were included. T2-FLAIR mismatch was evaluated independently by two board-certified neuroradiologists. Texture features were extracted from glioma segmentation of FLAIR images. eXtremeGradient Boosting (XGboost) classifiers were used for model development. Leave-one-out-cross-validation (LOOCV) and external validation performances were reported for both the training and external validation sets. Results: A total of 103 patients were included for model development and 18 patients for external testing validation. The diagnostic performance (sensitivity/specificity/accuracy) in the determination of the 1p/19q co-deletion status was 59%/83%/67% (training) and 62.5%/70.0%/66.3% (testing) for the T2-FLAIR mismatch sign. This was significantly improved (p = 0.04) using the radiomics model to 77.9%/82.8%/80.3% (training) and 87.5%/89.9%/88.8% (testing), respectively. The addition of radiomics as a computer-assisted tool resulted in significant (p = 0.02) improvement in the performance of the neuroradiologist with 13 additional corrected cases in comparison to just using the T2-FLAIR mismatch sign. Conclusion: The proposed radiomic model provides much needed sensitivity to the highly specific T2-FLAIR mismatch sign in the determination of the 1p/19q non-co-deletion status and improves the overall diagnostic performance of neuroradiologists when used as an assistive tool.

Published in Cancers

ISSN: 2072-6694 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Medicine: Internal medicine: Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Website: https://www.mdpi.com/journal/cancers/

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