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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
- Source :
-
Neuroradiology . Mar2024, Vol. 66 Issue 3, p333-341. 9p. - Publication Year :
- 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 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MAGNETIC resonance imaging
*GLIOMAS
*DIFFERENTIAL diagnosis
*QUANTITATIVE research
*MANN Whitney U Test
*COMPARATIVE studies
*DESCRIPTIVE statistics
*RESEARCH funding
*COMPUTER-assisted image analysis (Medicine)
*ARTIFICIAL neural networks
*SENSITIVITY & specificity (Statistics)
*RECEIVER operating characteristic curves
*EVALUATION
Subjects
Details
- Language :
- English
- ISSN :
- 00283940
- Volume :
- 66
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Neuroradiology
- Publication Type :
- Academic Journal
- Accession number :
- 175359646
- Full Text :
- https://doi.org/10.1007/s00234-024-03288-0