Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition • 09-14 May 2026

Digital Poster

Quantitative Outcome Measures in MSK MRI

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Quantitative Outcome Measures in MSK MRI
Digital Poster
Musculoskeletal
Wednesday, 13 May 2026
Digital Posters Row G
16:55 - 17:50
Session Number: 566-06
No CME/CE Credit
Novel quantitative outcome measures in musculoskeletal MRI

  Figure 566-06-001.  Preliminary Study on Analyzing Inflammatory Activity in axSpA Using DCE-MRI-Based Multiparametric Radiomics Models
Jinru Lin, Yun Su, Yiming Nurabdulla, Shuntao Wang, Jun Jing, Jun Peng, Zehong Yang
Shenshan Medical Center, Memorial Hospital of Sun Yat-Sen University, Shanwei, China
Impact: This study introduces a quantitative imaging framework that enhances diagnostic precision and clinical decision-making for axSpA. It may guide personalized monitoring of inflammatory activity and stimulate further research into radiomics-based assessment of musculoskeletal inflammation.
  Figure 566-06-002.  Accelerating T1ρ Knee Mapping via Jointly Learning Sampling and Deep Quantitative MRI
Dilbag Singh, Ravinder Regatte, Marcelo Zibetti
NYU Grossman School of Medicine, New York, United States of America
Impact: Joint learning enabled faster, model-consistent T1ρ mapping with improved fidelity from undersampled data, enhancing early OA detection. Direct mapping with machine-designed sampling patterns outperformed manual designs, advancing quantitative MRI toward practical deployment in musculoskeletal imaging.
  Figure 566-06-003.  Foot Perfusion Mapping Using 3D Stack-of-Spirals FLASH-based Velocity-Selective ASL: Development and Comparison with pCASL
Qingle Kong, Yang Chen, Pengcheng Wang, Jiayu Xiao, Tyler Liang, Miguel Manzur, David Armstrong, Zhaoyang Fan
University of Southern California, Los Angeles, United States of America
Impact: The VSASL technique shows strong promise for noninvasive quantification of microvascular perfusion in the foot, enabling improved ischemia evaluation and potential clinical translation.
  Figure 566-06-004.  Longitudinally monitoring non-enzymatic crosslinking of collagen in bovine tendon via UTE quantitative MT (UTE-qMT) imaging
Soo Hyun Shin, Qingbo Tang, Saeed Jerban, Yajun Ma, Eric Chang, Jiang Du
University of California, Berkeley, United States of America
Impact: We demonstrate that collagen crosslinking via advanced glycation endproducts in tendon can be monitored via UTE-qMT MRI. This technique may advance our understanding of the pathology of diabetic tendinopathy and expedite the development of targeted novel treatments.
  Figure 566-06-005.  Sex-Specific Alterations in Thigh Muscle Quality in Individuals with Knee Osteoarthritis
Francesca Belibi, Yael Vainberg, McKenzie White, Anthony Gatti, Garry Gold, Feliks Kogan, Ananya Goyal
Stanford University, Stanford, United States of America
Impact: This study gives us insight into the ways OA may affect muscle quality differently by sex, allowing for more targeted muscle strengthening that could lead to better prevention and alleviation of OA symptoms.
  Figure 566-06-006.  Quantitative muscle assessment in Parsonage-Turner Syndrome: A Prospective, Longitudinal Study
Ek Tan, Yenpo Lin, Tim Li, Gracyn Campbell, Michelle Akerman, Shayna Turbin, Carlo Milani, Kiril Kiprovski, Jospeh Feinberg, Darryl Sneag
Hospital for Special Surgery, New York, United States of America
Impact: Muscle qMRI objectively characterizes muscle quality changes in PTS and can provide confirmatory evidence for muscle denervation to supplement the diagnosis of PTS. Muscle T2 can help inform PTS patients’ recovery of muscle strength.
  Figure 566-06-007.  Quantitative Assessment of Intramuscular Fibrosis Using UTE MRI in Sarcopenia and muscle aging
Meeghage Randika Perera, Dimitri Martel, Valentina Mazzoli
New York University Grossman School of Medicine, New York, United States of America
Impact: This study aims to overcome current limitations in early sarcopenia diagnosis by developing UTE MRI–based tools to quantify muscle fibrosis, a key feature of the disease, and to evaluate its role in disease progression.
  Figure 566-06-008.  Evaluation of Arterial Spin Labeling Imaging Methods for Jaw Muscle Perfusion Imaging
Estephan Filho, Sara Duffy, Alexander Hagstrom, Xiufeng Li
University of Minnesota, Minneapolis, United States of America
Impact: Reliable and robust ASL imaging of jaw muscle is critical for the investigation of the pathophysiological mechanisms of temporomandibular disorders (TMDs) and to get insights into the potential jaw muscle metabolic dysfunction and its relation to chronic TMD pain.
  Figure 566-06-009.  Comprehensive Deep-Learning-Based Assessment of Quantitative Magnetic Resonance Imaging in patients with Dystrophinopathies
Dianzhe Tian, Xiaohong Huang, Xinying Huang, Bo Hou, Francesco Santini, Jinxia ZHU, xiaoming Liu, Tom Hilbert, Tobias Kober, Yi Dai, Fengdan Wang
Peking Union Medical College Hospital, Beijing, China
Impact: Deep-learning-based qMRI provides a noninvasive and reproducible method for comprehensive muscle evaluation. It integrates multiple quantitative parameters. Offering an objective biomarker for disease staging, treatment monitoring, and personalized assessment in dystrophinopathies.
  Figure 566-06-010.  Automated Quadriceps Segmentation and Torque Prediction from Multi-Vendor MRI: Cross-Sectional Area vs. Radiomics
Ozkan Cigdem, Eros Montin, Salim Bin Ghouth, Akshay Chaudhari, Donnie Cameron, Luigi Ferrucci, Garry Gold, Cem Deniz, Valentina Mazzoli
Center for Advanced Imaging Innovation and Research (CAI²R), New York University Grossman School of Medicine, New York, United States of America
Impact: An automated pipeline converts routine Dixon MRI into useful strength indicators, providing quadriceps muscle segmentations across three MR vendors. Beyond CSA, radiomics captures compositional cues that improve muscle strength estimation, particularly in heterogeneous cohorts.
  Figure 566-06-011.  Determining the Repeatability and Precision of qDESS for Quantifying Muscle-Water T2 of Skeletal Muscle in FSHD
Gabriel Rossetto, David Higgins, Kieren Hollingsworth
Newcastle University, Newcastle upon Tyne, United Kingdom
Impact: The 3D qDESS method produces robust and accurate $T_2$ maps of the lower limb with substantially shorter acquisition times than the MESE sequence, making it a viable tool for FSHD clinical trials.
  Figure 566-06-012.  Quantitative MRI of avascular necrosis: comparison between a piglet model and children with Legg-Calvé-Perthes disease
Casey Johnson, Erick Buko, Ashton Amann, Nicole Nelson, Suhail Parvaze Pathan, Alexandra Armstrong, Susan Novotny, Jennifer Laine, Ferenc Tóth
Impact: Our study directly compared quantitative MRI measures in children with LCPD and in a preclinical model used to inform pathogenesis and treatment this condition. We identified specific similarities and differences between species that have important implications for future study.
  Figure 566-06-013.  Radiomics-Integrated Dual-Encoder Attention Network for Automatic Thigh Muscle Segmentation in MRI
Eun-Gyu Ha, Hyung Jun Park, Dong-Hyun Kim
Yonsei University, Seoul, Korea, Republic of
Impact: Integrating radiomics features with deep learning improved segmentation robustness and stability. This approach may facilitate more reliable and reproducible quantitative muscle analysis, contributing to objective assessment of neuromuscular disorders in both research and clinical applications.
  Figure 566-06-014.  Proton Density Fat Fraction in Bone Marrow and Muscle: Repeatability and Reproducibility Across Field Strength and Protocol
Utsav Shrestha, Felix Schön, Jiayi Tang, Ali Pirasteh, Scott Reeder, Diego Hernando
University of Wisconsin - Madison, Madison, United States of America
Impact: Establishing PDFF as a reliable biomarker in skeletal muscle and bone marrow is necessary to enable widespread adoption. High performance repeatability and reproducibility is essential for multi-center studies and to accelerate its adoption as a robust biomarker in clinical practice.
  Figure 566-06-015.  Quantitative MRI Assessment of Vertebral Marrow Fat Remodeling Across Aging in Women Using mDIXON-Quant
Ningna Li, Yunping Yi, Suyun Luo, Shuqin Zhou, Jun Peng, Siwei Zhang
Traditional Chinese Medicine Hospital of Guangdong Province, Guangzhou, China
Impact: mDIXON-Quant enables rapid 3D assessment of vertebral marrow fat remodeling across aging, providing a radiation-free biomarker for early metabolic bone quality evaluation in women beyond conventional BMD.

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