Premium
Biexponential T 1ρ relaxation mapping of human knee cartilage in vivo at 3 T
Author(s) -
Sharafi Azadeh,
Xia Ding,
Chang Gregory,
Regatte Ravinder R.
Publication year - 2017
Publication title -
nmr in biomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 114
eISSN - 1099-1492
pISSN - 0952-3480
DOI - 10.1002/nbm.3760
Subject(s) - repeatability , cartilage , relaxation (psychology) , t2 relaxation , osteoarthritis , nuclear medicine , coefficient of variation , chemistry , in vivo , nuclear magnetic resonance , statistical parametric mapping , magnetic resonance imaging , anatomy , pathology , medicine , physics , radiology , chromatography , alternative medicine , microbiology and biotechnology , biology
The purpose of this study was to demonstrate the feasibility of biexponential T 1ρ relaxation mapping of human knee cartilage in vivo . A three‐dimensional, customized, turbo‐flash sequence was used to acquire T 1ρ ‐weighted images from healthy volunteers employing a standard 3‐T MRI clinical scanner. A series of T 1ρ ‐weighted images was fitted using monoexponential and biexponential models with two‐ and four‐parametric non‐linear approaches, respectively. Non‐parametric Kruskal–Wallis and Mann–Whitney U ‐statistical tests were used to evaluate the regional relaxation and gender differences, respectively, with a level of significance of P = 0.05. Biexponential relaxations were detected in the cartilage of all volunteers. The short and long relaxation components of T 1ρ were estimated to be 6.9 and 51.0 ms, respectively. Similarly, the fractions of short and long T 1ρ were 37.6% and 62.4%, respectively. The monoexponential relaxation of T 1ρ was 32.6 ms. The experiments showed good repeatability with a coefficient of variation (CV) of less than 20%. A biexponential relaxation model showed a better fit than a monoexponential model to the T 1ρ relaxation decay in knee cartilage. Biexponential T 1ρ components could potentially be used to increase the specificity to detect early osteoarthritis by the measurement of different water compartments and their fractions.