Deep Learning-Accelerated Prostate MRI: Improving Speed, Accuracy, and Sustainability

作者：Philipp Reschke, Vitali Koch, Leon D. Gruenewald, Ahmed Ait Bachir, Jennifer Gotta, Christian Booz, Mohamed Alaa Alrahmoun, Ralph Strecker, Dominik Nickel, Tommaso D’Angelo, Daniel Dahm, P Konrad, Levent A Solim, Maximilian Holzer, Saber Al-Saleh, Jan‐Erik Scholtz, Christof M. Sommer, Renate Hammerstingl, Katrin Eichler, Thomas J. Vogl, David M. Leistner, Sebastian M Haberkorn, Scherwin Mahmoudi · 发表于：Academic Radiology · 年份：2025 · DOI：10.1016/j.acra.2025.06.022 · 被引用次数：4 · 研究领域：Prostate Cancer Diagnosis and Treatment、Radiomics and Machine Learning in Medical Imaging、MRI in cancer diagnosis

RATIONALE AND OBJECTIVES: This study aims to evaluate the effectiveness of a deep learning (DL)-enhanced four-fold parallel acquisition technique (P4) in improving prostate MR image quality while optimizing scan efficiency compared to the traditional two-fold parallel acquisition technique (P2). MATERIALS AND METHODS: Patients undergoing prostate MRI with DL-enhanced acquisitions were analyzed from January 2024 to July 2024. The participants prospectively received T2-weighted sequences in all imaging planes using both P2 and P4. Three independent readers assessed image quality, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR). Significant differences in contrast and gray-level properties between P2 and P4 were identified through radiomics analysis (p <.05). RESULTS: A total of 51 participants (mean age 69.4 years ± 10.5 years) underwent P2 and P4 imaging. P4 demonstrated higher CNR and SNR values compared to P2 (p <.001). P4 was consistently rated superior to P2, demonstrating enhanced image quality and greater diagnostic precision across all evaluated categories (p <.001). Furthermore, radiomics analysis confirmed that P4 significantly altered structural and textural differentiation in comparison to P2. The P4 protocol reduced T2w scan times by 50.8%, from 11:48 min to 5:48 min (p <.001). CONCLUSION: In conclusion, P4 imaging enhances diagnostic quality and reduces scan times, improving workflow efficiency, and potentially contributing to a more patient-centered an...