ArticleMagnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine2026
CT- and MR Imaging-based Radiomics Approach to Differentiating Ovarian Mature and Immature Teratomas: Can MR Imaging-based Radiomics Predict the Histological Grade of Immature Teratomas?
Article in Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeThis study aimed to evaluate CT- and MRI-based radiomic features of ovarian mature and immature teratomas (MTs and ITs) and to investigate the differences between low- and high-grade ITs.
methodsA total of 41 patients aged ≤ 30 years with histopathologically confirmed ovarian MT and 23 patients with ovarian IT who underwent preoperative MRI were included. Among them, 51 (31 MTs and 20 ITs) underwent preoperative CT. We investigated the differences in visual findings by radiologists and radiomics analysis not only between MTs and ITs but also between low- (grade 1) and high-grade (grades 2-3) ITs.
resultsMultiple CT and MRI findings, along with radiomic features, showed significant differences between MTs and ITs (P < 0.05). Although the maximum diameter of nodular fat was greater in low-grade ITs than in high-grade ITs (P < 0.05), no other visual CT or MRI findings showed significant differences between low- and high-grade ITs. In contrast, several MRI-based radiomic features derived from fat-suppressed T1-weighted images, along with selected CT-based radiomic features, showed significant differences between low- and high-grade ITs (P < 0.05).
conclusionVisual assessments by radiologists and radiomics analysis effectively distinguished MTs from ITs. However, differentiating between low- and high-grade ITs using visual assessment alone was difficult. Radiomics analysis-particularly MRI-based features from fat-suppressed T1-weighted images-showed potential as a noninvasive approach for grading ITs, although further validation is required.
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