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Open Access 15-01-2024 | Astrocytoma | Diagnostic Neuroradiology

Comparison of diagnostic performance of radiologist- and AI-based assessments of T2-FLAIR mismatch sign and quantitative assessment using synthetic MRI in the differential diagnosis between astrocytoma, IDH-mutant and oligodendroglioma, IDH-mutant and 1p/19q-codeleted

Authors: Kazufumi Kikuchi, Osamu Togao, Koji Yamashita, Daichi Momosaka, Yoshitomo Kikuchi, Daisuke Kuga, Sangatsuda Yuhei, Yutaka Fujioka, Fumiya Narutomi, Makoto Obara, Koji Yoshimoto, Kousei Ishigami

Published in: Neuroradiology | Issue 3/2024

Abstract

Purpose

This study aimed to compare assessments by radiologists, artificial intelligence (AI), and quantitative measurement using synthetic MRI (SyMRI) for differential diagnosis between astrocytoma, IDH-mutant and oligodendroglioma, and IDH-mutant and 1p/19q-codeleted and to identify the superior method.

Methods

Thirty-three cases (men, 14; women, 19) comprising 19 astrocytomas and 14 oligodendrogliomas were evaluated. Four radiologists independently evaluated the presence of the T2-FLAIR mismatch sign. A 3D convolutional neural network (CNN) model was trained using 50 patients outside the test group (28 astrocytomas and 22 oligodendrogliomas) and transferred to evaluate the T2-FLAIR mismatch lesions in the test group. If the CNN labeled more than 50% of the T2-prolonged lesion area, the result was considered positive. The T1/T2-relaxation times and proton density (PD) derived from SyMRI were measured in both gliomas. Each quantitative parameter (T1, T2, and PD) was compared between gliomas using the Mann–Whitney U-test. Receiver-operating characteristic analysis was used to evaluate the diagnostic performance.

Results

The mean sensitivity, specificity, and area under the curve (AUC) of radiologists vs. AI were 76.3% vs. 94.7%; 100% vs. 92.9%; and 0.880 vs. 0.938, respectively. The two types of diffuse gliomas could be differentiated using a cutoff value of 2290/128 ms for a combined 90^th percentile of T1 and 10^th percentile of T2 relaxation times with 94.4/100% sensitivity/specificity with an AUC of 0.981.

Conclusion

Compared to the radiologists’ assessment using the T2-FLAIR mismatch sign, the AI and the SyMRI assessments increased both sensitivity and objectivity, resulting in improved diagnostic performance in differentiating gliomas.

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WHO Classification of Tumours Editorial Board (2022) Central nervous system tumours: WHO classification of tumours. WHO classification of tumours

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Title: Comparison of diagnostic performance of radiologist- and AI-based assessments of T2-FLAIR mismatch sign and quantitative assessment using synthetic MRI in the differential diagnosis between astrocytoma, IDH-mutant and oligodendroglioma, IDH-mutant and 1p/19q-codeleted
Authors: Kazufumi Kikuchi
Osamu Togao
Koji Yamashita
Daichi Momosaka
Yoshitomo Kikuchi
Daisuke Kuga
Sangatsuda Yuhei
Yutaka Fujioka
Fumiya Narutomi
Makoto Obara
Koji Yoshimoto
Kousei Ishigami
Publication date: 15-01-2024
Publisher: Springer Berlin Heidelberg
Keywords: Astrocytoma
Astrocytoma
Astrocytoma
Artificial Intelligence
Oligodendroglioma
Glioma
Glioma
Glioma
Published in: Neuroradiology / Issue 3/2024
Print ISSN: 0028-3940
Electronic ISSN: 1432-1920
DOI: https://doi.org/10.1007/s00234-024-03288-0

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Comparison of diagnostic performance of radiologist- and AI-based assessments of T2-FLAIR mismatch sign and quantitative assessment using synthetic MRI in the differential diagnosis between astrocytoma, IDH-mutant and oligodendroglioma, IDH-mutant and 1p/19q-codeleted

Abstract

Purpose

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusion

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