{"doi":"10.1002/jor.70094","title":"Detecting Collagen Fiber Architecture after Destabilization of the Medial Meniscus Surgery Using High‐Resolution Diffusion Tensor Imaging","abstract":"Diffusion tensor imaging (DTI) has exhibited remarkable success in probing the tissue microstructure of connective tissues. How the different DTI metrics correlate to molecular and structural changes in osteoarthritis (OA) has not been thoroughly investigated. The potential of DTI to evaluate the 3D collagen fiber network in osteoarthritic cartilage remains largely unexplored. This study aims to assess tissue microstructure and 3D collagen fiber alterations following destabilization of the medial meniscus (DMM) surgery in rats using high-resolution DTI. MRI scans were conducted on 8 DMM and 8 SHAM knee joints. A 3D diffusion-weighted spin-echo pulse sequence, incorporating undersampling in both phase dimensions, was employed at 9.4 T. The fractional anisotropy (FA) values were significantly decreased in femoral cartilage in the DMM group, while the mean diffusivity (MD) and radial diffusivity (RD) values in both femoral and tibial cartilage were significantly increased. Regional analysis of femoral cartilage revealed that these differences were more pronounced in the anterior and central areas. Tractography provided evidence of disrupted 3D collagen fiber architecture in the DMM group. Simulations were conducted in the extra-collagen space with and without collagen dispersion/disruption, and with and without glycosaminoglycans (GAG), to interpret the DTI results. The simulations revealed that the loss of GAG primarily led to increased MD, while collagen dispersion/disruption predominantly resulted in decreased FA. Imaging and simulation findings were supported by changes on histology. High-resolution DTI enables visualization of 3D collagen fiber architecture and detection of changes in cartilage tissue integrity, which are crucial for understanding cartilage degradation in OA.","journal":"Journal of Orthopaedic Research®","year":2025,"id":587630,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9595,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1483944,"name":"J. Chen","orcid":"0000-0002-4853-5341","position":1,"is_corresponding":false},{"id":1503670,"name":"Benjamin Sylvanus","orcid":null,"position":2,"is_corresponding":false},{"id":1484313,"name":"Zhuoheng Liu","orcid":null,"position":3,"is_corresponding":false},{"id":970416,"name":"Xinyue Han","orcid":"0000-0002-8082-0863","position":4,"is_corresponding":false},{"id":678125,"name":"Mingquan Lin","orcid":"0000-0003-0862-6588","position":5,"is_corresponding":false},{"id":35644,"name":"Fang Liu","orcid":"0000-0002-8325-1213","position":6,"is_corresponding":false},{"id":270689,"name":"Hong‐Hsi Lee","orcid":"0000-0002-3663-6559","position":7,"is_corresponding":false},{"id":619070,"name":"Nian Wang","orcid":"0000-0001-9185-4199","position":8,"is_corresponding":false},{"id":1503669,"name":"Nataliya Tod","orcid":null,"position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-19T02:59:39.958043Z","pmid":"41475693","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}