Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition - MSK: Everything, Everywhere, and All at Once

MSK: Everything, Everywhere, and All at Once

Power Pitch

Musculoskeletal

Monday, 11 May 2026

Power Pitch Theatre 1

13:50 - 15:26

Moderators: Dilbag Singh & Matthew Birkbeck

Session Number: 351-02

No CME/CE Credit

Similar Sessions

Latest developments in MSK imaging, from muscle to joint and bone and back.

13:50		351-02-001. Detection of Spontaneous Muscular Contractions at Rest: A Comparison of DW-MRI to Clinically Established Methods Martin Schwartz, Petros Martirosian, Julia Wittlinger, Thorsten Feiweier, Günter Steidle, Bin Yang, Ludger Schöls, Fritz Schick University Hospital of Tuebingen, Tuebingen, Germany Impact: Demonstrating a high agreement with clinically established techniques supports DW-MRI as a non-invasive method with the ability to overcome limitations of ultrasound and needle electromyography.
13:52		351-02-002. Enhancing Supraspinatus Visualization Using Deep Learning-Reconstructed TSE MRI: A Qualitative and Quantitative Analysis Wanqing Gong, Wei Chen, Zhenmeng Sun, Xiaoqian Tian, Kun Liu, Tingting Zhang Yichang Central People’s Hospital, Yichang, China Impact: By enabling faster scan times, high-resolution image, and superior image quality in supraspinatus TSE MRI, deep learning reconstruction permits more accurate detection of abnormalities, boosting diagnostic confidence and patient throughput.
13:54		351-02-003. Fat-suppressed quantitative CEST imaging in skeletal muscle using a 3D Dixon-CEST sequence Valentin Henriet, Marc Lapert, Benjamin Marty, Pierre-Yves Baudin, Harmen Reyngoudt Institute of Myology, Paris, France Impact: Combining 3-point-Dixon processing with 3D-CEST imaging enables accurate fat suppression and reliable CEST-based metabolic quantification. This approach improves Cr-CEST contrast and allows for accurate B0-mapping and FF quantification. This technic aims to improve quantification of muscle metabolism in neuromuscular diseases.
13:56		351-02-004. Clinical Impact of MR Neurography on Surgical Decision-Making Across Diverse Peripheral Neuropathies Yenpo Lin, Johnny Chuieng-Yi Lu Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan Impact: MR neurography (MRN) may serve as a valuable tool for integration into clinical decision-making, particularly in complex or postoperative peripheral nerve cases.
13:58		351-02-005. Is 2-minute Simultaneous CT-like Bone-weighted Imaging and UTE-T2* Quantification Clinically Possible? Hung Do, Mitsuhiro Bekku, Mark Golden, Shinichi Kitane, Mitsuhiro Uike, Ryohei Takayanagi, Kensuke Shinoda, Hiroshi Takai, Dawn Berkeley, Brian Tymkiw, Wissam Alghuraibawi, Shelton Caruthers, Mo Kadbi Canon Medical Systems USA, Cleveland, United States of America Impact: mecho-UTE enables bone-weighted imaging without risk of radiation exposure and provides accurate T2* quantification of short-T2 tissues, which are invisible in both MRI and CT. A rapid 2-minute mecho-UTE could feasibly be added to routine clinical protocols.
14:00		351-02-006. Data-Driven MRI Analysis Reveals Response Phenotypes in Soft Tissue Sarcomas During Neoadjuvant Radiation Therapy Balazs Bogner, Alexander Runkel, Marco Reisert, Elena Fritsch, Thierno Diallo, Pia Jungmann, Fabian Bamberg, Matthias Jung University Medical Center Freiburg — Department of Diagnostic and Interventional Radiology, Freiburg, Germany Impact: Data-driven mpMRI clustering objectively stratifies STS patients into biologically distinct response phenotypes independent of tumor size, providing a framework for non-invasive treatment monitoring that could guide personalized therapy decisions beyond conventional imaging criteria.
14:02		351-02-007. Direct Correlation of Advanced DWI Modeling of Soft Tissue Sarcoma and Quantitative Histopathological Features jinge li, Kai Zhang, yifeng zhu, Wenjia Wang, Shaowu Wang The Second Affiliated Hospital of Dalian Medical University, Dalian, China Impact: Using image–pathology co-registration, this study revealed direct correlations between advanced DWI parameters and quantitative histopathologic composition in STS and highlighted their potential for differentiating histological origins, offering new imaging biomarkers for histological characterization and tumor microenvironment assessment.
14:04		351-02-008. Temporal Synchronous and Lagged Coupling of Hip and Knee Cartilage: A Longitudinal Compositional Study Rupsa Bhattacharjee, Zehra Akkaya, Yurui Qian, Misung Han, Richard Souza, Sharmila Majumdar Indian Institute of Technology, Madras, Chennai, India Impact: This study demonstrates temporally lagged coupling between hip and knee cartilage compositional changes, independent of baseline knee-morphology. These findings suggest early biochemical propagation of degeneration within the same limb, emphasizing the importance of multi-joint imaging biomarkers in longitudinal OA monitoring.
14:06		351-02-009. Ultrashort Echo Time magnetization transfer imaging for Assessing Tibial Cortical Collagen Structure in T1DM Rabbits. Minzhi Pei, Chuanyun Jiang, Weiyin Vivian Liu, Kejun Wang, Yufan Gao, Liang Li, Yunfei Zha Renmin Hospital of Wuhan University, Wuhan, China Impact: Our findings demonstrate the UTE-MT-derived MTR serves as a non-invasive biomarker, providing in vivo quantitative evidence that links cortical collagen degradation to impaired bone quality in T1DM.
14:08		351-02-010. CAIPIRINHA & Compressed Sensing with Deep Learning Reconstruction for Slice Encoding for Metal Artifact Reduction (SEMAC) Constantin von Deuster, Thomas Yu, Jeanette Deck, Marcel Dominik Nickel, Mathias Nittka, Dominik Paul, Daniel Nanz, Reto Sutter Balgrist Campus AG, Zurich, Switzerland Impact: Deep learning image reconstruction of SEMAC data that is both incoherently and coherently undersampled allows a further reduction in acquisition time by ~40% compared to conventional coherent undersampling while preserving image quality. This reduces motion sensitivity of long SEMAC scans.
14:10		351-02-011. Radiomics analysis of clinical knee MRI associates with radiographic and symptomatic PTOA 10 years after ACL reconstruction Kihwan Kim, Urmika Gosh, Sameed Khan, Richard Lartey, Brendan Eck, Mei Li, Mingrui Yang, Jeehun Kim, Carl Winalski, Faysal Althahawi, Nancy Obuchowski, Morgan Jones, Laura Huston, Kevin Harkins, Michael Knopp, Christopher Kaeding, Kurt Spindler, Xiaojuan Li Cleveland Clinic, Cleveland, United States of America Impact: This study demonstrates that radiomic analysis of clinical knee MRI can predict post-traumatic osteoarthritis development, offering a practical and scalable approach for early detection and risk stratification in patients after ACL reconstruction.
14:12		351-02-012. Impact of Deep Resolve Boost reconstruction on image quality of lumbar spine imaging at 0.55T Virginie Kreutzinger, Katharina Ziegeler, Pan Su, Marcel Dominik Nickel, Sharmila Majumdar, Daehyun Yoon Technical University Munich, Munich, Germany Impact: Deep Resolve Boost (DRB) reconstruction of 0.55T lumbar spine images yields higher image quality, better visualization of anatomic detail and tissue texture appearance, higher diagnostic confidence and similar inter reader agreement compared to original images (without DRB).
14:14		351-02-013. Multi-Vendor Multi-Site Prospective Evaluation of SuperMAP Deep-Learning Reconstruction for Accelerated T1ρ and T2 Mappings Xinyan Jian, Zhiyuan Zhang, Jeehun Kim, Ruiying Liu, Koushani Chakrabarty, Richard Lartey, Carl Winalski, Mingrui Yang, Qi Peng, Michael Samaan, Peter Hardy, Jing Liu, Thomas Link, Lei (Leslie) Ying, Xiaojuan Li Cleveland Clinic, Cleveland, United States of America Impact: SuperMAP enables fast, reliable, and quantitative MRI, achieving accuracy comparable to CS with significantly shorter reconstruction time. This efficiency supports scalable multi-site and multi-vendor T1ρ and T2 mapping for early osteoarthritis detection and longitudinal monitoring.
14:16		351-02-014. Tricomponent analysis of the spine via interleaved dual-echo UTE imaging Soo Hyun Shin, Xing Lu, James Lo, Jiaji Wang, Jiayang Wu, Arya Suprana, Eric Chang, Jiang Du, Monica Guma, Yajun Ma University of California, Berkeley, United States of America Impact: Water and fat are key non-mineral determinants of vertebral fracture risk. Our tricomponent approach simultaneously quantifies different pools of water and fat. This method shows potential in improving the assessment of bone quality and prediction of vertebral fracture risk.
14:18		351-02-015. Lumbar MRI Radiomics for Non-invasive ISS/R-ISS Stratification in Newly Diagnosed Multiple Myeloma: A Two-Center Study Hao Wenhan, Fei Zheng, Xinyi Gou, Ping Yin, Sicong Wang, Zhang Chuanchen, Hong Nan Peking University People's Hospital, Beijing, China Impact: Radiomics from routine lumbar MRI—combining whole-lumbar T1WI with single-vertebra T2FS—enables non-invasiveISS/R-ISS risk stratification in newly diagnosed multiple myeloma, offering clinic-comparable performance for ISS and practical utility where bone marrow genetics are unavailable.
14:20		351-02-016. Patellofemoral Cartilage Integrity after Patellar Stabilization with or without Trochleoplasty: a T1ρ and T2 Mapping Study Georg Feuerriegel, Jakob Ackermann, Manuel Waltenspül, Thaddäus Muri, Tom Hilbert, Constantin von Deuster, Daniel Nanz, Reto Sutter, Sandro Fucentese, Gabriele Bonanno Balgrist University Hospital, Zurich, Switzerland Impact: Quantitative T2 and T1ρ mapping provides sensitive biomarkers for long-term cartilage health after patellar stabilization surgery. Relaxation time changes correlated with cartilage degeneration from conventional imaging and poorer patient-reported outcomes.
14:22		351-02-017. Cartilage UTE-T2* Predicts Long-term Clinical Outcomes After Arthroscopic Partial Meniscectomy Ashley Williams, Constance Chu Stanford Medicine, Stanford, United States of America Impact: Non-invasive MRI UTE-T2* of cartilage adjacent to torn menisci predicted long-term clinical outcomes after surgical treatment of degenerative meniscal tears suggesting a potential role in guiding clinical management of early osteoarthritis (OA) patients.
14:24		351-02-018. Deep Learning Framework Integrating Multi-B-Value DWI and MRI for Automated Classification of Solitary Spinal Lesions Jun Xu, Wenjia Wang, Ning Lang Peking University Third Hospital, Beijing, China Impact: The DL framework integrating mb-DWI, conventional MRI, and clinical features enables automated SSLs classification with attending-level accuracy, enhancing performance, especially for juniors. Mb-DWI improves the model's ability to capture multi-dimensional data, surpassing single-sequence models in detecting aggressive end malignant lesions.