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

Digital Poster

Cartilage 2026

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Cartilage 2026
Digital Poster
Musculoskeletal
Wednesday, 13 May 2026
Digital Posters Row D
09:15 - 10:10
Session Number: 563-02
No CME/CE Credit
Similar Sessions
Technical advancements for structural imaging and quantitative analysis of articular cartilage
  Figure 563-02-001.  Normative T1 and T2 Relaxation Time Values of Healthy Knee Cartilage in a Single-Age, Population-Based Cohort
Samu Majabacka, Egor Panfilov, Antti Kemppainen, Mika Nevalainen, Victor Casula, Miika T Nieminen
University of Oulu, Oulu, Finland
Impact: MRF-derived T1 and T2 mapping of knee cartilage established normative reference values for young adults with radiologically healthy knees. Compartment- and depth-specific values provide a benchmark for studying early cartilage degeneration and evaluating preventive interventions for osteoarthritis.
  Figure 563-02-002.  Longitudinal quantitative MRI of cartilage degeneration in ACL-reconstructed patients using ultrashort echo time adiabatic T1
Dina Moazamian, Jiayang Wu, Mohamad Amin Cheraghi, Hamidreza Shaterian Mohammadi, Bhavsimran Malhi, Jiyo Athertya, Mahyar Daskareh, Yajun Ma, Susan Bukata, Eric Chang, Saeed Jerban, Christine Chung, Jiang Du
University of California, Berkeley, United States of America
Impact: This study demonstrates that UTE Adiabatic T1ρ MRI can sensitively detect early cartilage degeneration after ACL reconstruction, enabling clinicians to monitor osteoarthritis risk non-invasively and inspiring further research into early therapeutic interventions and quantitative imaging biomarkers for joint health.
  Figure 563-02-003.  In vivo MR elastography reveals cartilage stiffness changes linked to altered gait patterns post-ACL surgery
Emily Miller, Timothy Lowe, Hongtian Zhu, Stéphane Avril, Corey Neu
Impact: Our findings enable MRI-based early detection of cartilage stiffness changes post-ACL injury, offering clinicians a tool to predict osteoarthritis onset.
  Figure 563-02-004.  Prediction of Cartilage Proteoglycan Content from MR Fingerprinting Using Deep Kernel Learning Gaussian Processes (DKL-GP)
Wajiha Bano, Ajinkya Gorad, Ville Kantola, Olli Nykänen, Mikko Nissi, Miika T Nieminen, Simo Särkkä
Aalto University, Espoo, Finland
Impact: Deep Kernel Learning Gaussian Processes (DKL-GP) offer accurate predictions of histological tissue properties from MR Fingerprinting (MRF) data. The work demonstrates the value of combining deep learning with probabilistic modeling for tissue characterization from fast quantitative MRI.
  Figure 563-02-005.  Texture Cluster Analysis Of Knee Cartilage T2 Maps
Veronika Janacova, Diana Sitarcikova, Pavol Szomolanyi, Barbara Hristoska, Malina Gologan, Siegfried Trattnig, Vladimir Juras
Medical University of Vienna, Vienna, Austria
Impact: GLCM texture clusters differ not only between patients and healthy controls but also align spatially with lesion locations. Clusters provide an intuitive visual representation that is easier to interpret in clinical practice than numerical feature values from the entire ROI.
  Figure 563-02-006.  Quantitative Susceptibility Mapping Reveals Layer-Specific Biomechanical Response in Knee Cartilage to Mechanical Loading
Jia Chen, Hanqi Wang, Yong Lu
Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Impact: Our findings demonstrate unique spatiotemporal susceptibility patterns in knee cartilage collagen following mechanical loading.The observed temporal differences in medial versus lateral susceptibility changes may provide new insights for early osteoarthritis diagnosis.
  Figure 563-02-007.  Healthy knee cartilage T2 mapping assessed with GRAPPATINI and multi-echo spin-echo (MESE) at 3T
Bénédicte Delattre, Tom Hilbert, Halah Kutaish, Lindsey Crowe, Pierre-Alexandre Poletti, Jacques Menetrey, Didier Hannouche, Philippe Tscholl, Sana Boudabbous
Geneva University Hospital, Geneva, Switzerland
Impact: Quantitative cartilage MRI is faster, more reliable, and clinically feasible with accelerated GRAPPATINI compared to conventional multi-echo spin-echo sequence.
  Figure 563-02-008.  Longitudinal Quantitative MRI of Meniscal Degeneration in ACLR Patients Using 3D UTE-MT and UTE-Adiab-T1ρ Imaging
Jiayang Wu, Dina Moazamian, Mohamad Amin Cheraghi, Hamidreza Shaterian Mohammadi, Bhavsimran Malhi Malhi, Jiyo Athertya, Mahyar Daskareh, Yajun Ma, Eric Chang, Saeed Jerban, Christine Chung, Susan Bukata, Jiang Du
The First Affiliated Hospital of Jinan University, Guangzhou, China
Impact: This study highlights UTE-Adiab-T1ρ and UTE-MMF as key tools for early, non-invasive detection of meniscal degeneration post-ACLR, offering a promising approach to predict and mitigate OA.
  Figure 563-02-009.  Feasibility and Repeatability of UTE-Adiabatic-T1ρ for whole-knee assessment
Hector Lise de Moura, Mahesh Keerthivasan, Marcelo Zibetti, Ravinder Regatte
NYU Grossman School of Medicine, New York, United States of America
Impact: Adiabatic T₁ρ mapping using UTE at 3T enables robust, repeatable, and field-insensitive tissue quantification. Optimized TAN-based spin-lock pulses may enhance the sensitivity for early musculoskeletal degeneration detection, advancing clinical diagnostics and research in tissue relaxation imaging.
  Figure 563-02-010.  HRDNet: Hybrid ResNeXt–Dense Network for Quantitative T1ρ Mapping from Undersampled k-Space
Dilbag Singh, Ravinder Regatte, Marcelo Zibetti
NYU Grossman School of Medicine, New York, United States of America
Impact: HRDNet directly estimates T1ρ maps from accelerated, undersampled multi-coil k-space, improving fidelity and precision over common deep-learning baselines. Therefore, it advances translation toward routine clinical assessment of early osteoarthritis, moving quantitative knee MRI toward everyday practice.
  Figure 563-02-011.  Highly efficient simultaneous 3D joint T1-T2 mapping of the knee at 0.55T: Comparison of Cartesian and radial strategies.
Dabne Barrera, Dongyue Si, Nicolas Garrido, Felipe Ercoli, Carlos Castillo-Passi, Rene Botnar, Claudia Prieto
Pontificia Universidad Católica de Chile, Santiago, Chile
Impact: This work demonstrates the potential of low-field MRI for rapid quantitative cartilage assessment, achieving simultaneous 3D T1 and T2 mapping of the knee in under 4 minutes with two different acquisition strategies based on Cartesian and radial imaging.
  Figure 563-02-012.  Quantitative MRI Characterization of Osteochondritis Dissecans Lesion Development in a Piglet Model
Erick Buko, Callista Hohenhaus, Alexandra Armstrong, Casey Johnson, Ferenc Tóth
University of Minnesota, Minneapolis, United States of America
Impact: Quantitative MRI captures multiple changes during the temporal evolution of OCD lesions, with T2 and T2* detecting early injury, fat fraction demonstrating delayed marrow remodeling, and DESS depicting late morphological disruption, thus providing noninvasive methods to monitor OCD lesion development.
  Figure 563-02-013.  Does T₂ Fitting Model Impact Repeatability and Longitudinal Cartilage Repair Assessment?
Laura Carretero-Gómez, maggie fung, Tim Sprenger, Marco Barbieri, Bruno Astuto, Elena Rodríguez, Juan Manuel López-Alcorocho, Isabel Guillén, Eugenia Sánchez Lacalle, Norberto Malpica, Florian Wiesinger, Mario Padrón
GE HealthCare, Madrid, Spain
Impact: This study aims to improve qMRI interpretation in cartilage repair by clarifying how T₂ fitting models influence repeatability and longitudinal trends, supporting development of robust imaging biomarkers and integration with clinical outcomes for better patient monitoring.

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