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

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

研究成果: ジャーナルへの寄稿学術誌査読

抄録

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 90th percentile of T1 and 10th 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.

本文言語英語
ページ(範囲)333-341
ページ数9
ジャーナルNeuroradiology
66
3
DOI
出版ステータス出版済み - 3月 2024

!!!All Science Journal Classification (ASJC) codes

  • 放射線学、核医学およびイメージング
  • 臨床神経学
  • 循環器および心血管医学

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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」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

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