Evidence map›Paper›PMID 40664867›Full record

ArticleEuropean radiology2026

Magnetic resonance fingerprinting for the whole knee articular cartilage assessment using automated pipeline.

Diana Sitarcikova, Veronika Janacova, Malina Gologan, Barbara Hristoska, Martijn A Cloos, Pavol Szomolanyi, Siegfried Trattnig, Vladimir Juras

Abstract read
In one paragraph

Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Diana SitarcikovaDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria. diana.sitarcikova@meduniwien.ac.at.ORCID http://orcid.org/0000-0002-8464-801X
Veronika JanacovaDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.
Malina GologanDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.
Barbara HristoskaDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.
Martijn A CloosDonders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
Pavol SzomolanyiDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.
Siegfried TrattnigDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.
Vladimir JurasDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.

Funding

Austrian Science Fund KLI917
6 · The paper itself

Abstract

objectivesTo evaluate the feasibility of a prototype MRF sequence in an automated pipeline for T2 extraction of knee cartilage, and to compare it to the same procedure with a conventional T2 mapping sequence. MATERIALS AND

methodsSeventeen healthy volunteers and twenty patients with a focal cartilage damage ICRS grade I-III diagnosed via morphological MRI underwent knee MRI examination, including a prototype MRF sequence, a conventional multi-slice multi-echo (MSME) T2 mapping sequence and double-echo steady-state sequence (DESS). Automated cartilage segmentation with a subsequent automated pipeline for T2 extraction from both T2 maps was performed. The methods were compared via correlation analysis. Test-retest analysis was performed on 5 healthy volunteers and evaluated with the intra-class correlation coefficient (ICC). Additionally, the National Institute of Standards and Technology (NIST) phantom was scanned to compare the methods.

resultsOn average, the MSME method yielded T2 values 12.4 ms higher than MRF in the phantom and 17.3 ms and 16.3 ms higher in healthy volunteers and patients, respectively. The T2 values correlated very strongly in phantom (r = 0.998, p < 0.001) and in pooled in vivo analysis (r = 0.819, p < 0.001 and r = 0.865, p < 0.001 in volunteer and patient group, respectively), but moderately to strongly in global regions (femoral, patellar and tibial). The reliability of the pipeline was excellent for both methods (ICC from 0.823 to 0.958 for MRF and ICC from 0.863 to 0.932 for MSME).

conclusionsMRF T2 mapping in the knee cartilage in combination with automatic segmentation is feasible and reliable. KEY POINTS: Question Quantitative MRI suffers from long acquisition and post-processing times, reducing its feasibility for routine clinical use in knee articular cartilage applications. Findings T2 mapping via MR fingerprinting in combination with automatic segmentation and T2 extraction procedure in knee articular cartilage performs reliably and time-efficiently. Clinical relevance The proposed combination of methods is suitable for further investigation and characterization of cartilage disorders. The improved time efficiency and high accuracy, together with the elimination of the need for manual input, represent a significant advancement toward clinical translation.

Indexed as

Cartilage, ArticularImage Interpretation, Computer-AssistedKnee JointMagnetic Resonance ImagingOsteoarthritis, KneeAdultCase-Control StudiesFeasibility StudiesFemaleHealthy VolunteersHumansMalePhantoms, ImagingProspective StudiesReproducibility of ResultsTime FactorsCartilageMagnetic resonance fingerprintingRelaxometrySegmentationT2 mapping

Identifiers

PMID40664867
PMCPMC12711938

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