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Accelerating t 1ρ cartilage imaging using compressed sensing with iterative locally adapted support detection and JSENSE
Author(s) -
Zhou Yihang,
Pandit Prachi,
Pedoia Valentina,
Rivoire Julien,
Wang Yanhua,
Liang Dong,
Li Xiaojuan,
Ying Leslie
Publication year - 2016
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.25773
Subject(s) - compressed sensing , computer science , cartilage , translation (biology) , iterative reconstruction , artificial intelligence , computer vision , reproducibility , pattern recognition (psychology) , process (computing) , biomedical engineering , mathematics , medicine , chemistry , biochemistry , statistics , messenger rna , gene , anatomy , operating system
Purpose To accelerate T 1ρ quantification in cartilage imaging using combined compressed sensing with iterative locally adaptive support detection and JSENSE. Methods To reconstruct T 1ρ images from accelerated acquisition at different time of spin‐lock (TSLs), we propose an approach to combine an advanced compressed sensing (CS) based reconstruction technique, LAISD (locally adaptive iterative support detection), and an advanced parallel imaging technique, JSENSE. Specifically, the reconstruction process alternates iteratively among local support detection in the domain of principal component analysis, compressed sensing reconstruction of the image sequence, and sensitivity estimation with JSENSE. T 1ρ quantification results from accelerated scans using the proposed method are evaluated using in vivo knee cartilage data from bilateral scans of three healthy volunteers. Results T 1ρ maps obtained from accelerated scans (acceleration factors of 3 and 3.5) using the proposed method showed results comparable to conventional full scans. The T 1ρ errors in all compartments are below 1%, which is well below the in vivo reproducibility of cartilage T 1ρ reported from previous studies. Conclusion The proposed method can significantly accelerate the acquisition process of T 1ρ quantification on human cartilage imaging without sacrificing accuracy, which will greatly facilitate the clinical translation of quantitative cartilage MRI. Magn Reson Med 75:1617–1629, 2016. © 2015 Wiley Periodicals, Inc.