Kobe University · Graduate School of Medicine / Faculty of Medicine

Research keywordsdiagnostic radiology・placenta accreta・renal tumor imaging・hepatic fibrosis・magnetic resonance・FDG PET

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• 深層学習モデルを用いた脳出血分類AIに対する有用性の検討2025 · (公社)日本診療放射線技師会, 2025年09月, JART: 日本診療放射線技師会誌, 72(9) (9), 1014 - 1014, 日本語
• 腎腫瘍のFDG-PET所見-WHO分類第5版(2022)に基づいて2025 · (一社)日本核医学会, 2025年, 核医学, 62(1) (1), 101 - 101, 日本語
• 【悪性リンパ腫の画像診断:間違えやすい疾患との鑑別のポイント】婦人科領域2024 · 金原出版(株), 2024年07月, 臨床放射線, 69(4) (4), 495 - 500, 日本語
• Mri-based diagnostic model integrating clinical features for placenta accreta spectrum in non-previa placenta.2022 · OBJECTIVES: To identify clinical and MRI features useful for diagnosing placenta accreta spectrum (PAS) in non-previa placenta and to develop diagnostic models integrating these features. METHODS: This retrospective study included 101 pregnant women with non-previa placenta who underwent MRI between January 2022 and June 2024. Nineteen were confirmed as PAS. Clinical variables and 11 MRI findings were evaluated using intraoperative or pathological results as the reference standard. Diagnostic performance was assessed using univariable analysis and repeated cross-validation of a random forest (RF) model, with ROC analysis used to assess discriminative performance. RESULTS: Hormone replacement cycle-frozen embryo transfer (HRC-FET) (sensitivity 0.89, specificity 0.63) and abnormal placental bed vascularization (sensitivity 0.63, specificity 0.90) showed the strongest univariable performance. The RF model using six variables with acceptable interobserver agreement achieved an AUC of 0.88, sensitivity 0.92, specificity 0.79, demonstrating higher discriminative performance than individual predictors. Feature importance analysis highlighted HRC-FET and abnormal placental bed vascularization as the most influential factors. CONCLUSIONS: Integrating clinical and MRI features improves PAS diagnosis in non-previa placenta. The RF model demonstrated a more balanced diagnostic profile than individual predictors in this exploratory cohort and may aid preoperative risk assessment. HRC-FET and abnormal placental bed vascularization were key contributors, supporting their relevance for risk stratification.

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