In vivo comparison of MRI‐based and MRS‐based quantification of adipose tissue fatty acid composition against gas chromatography. Issue 5 (7th May 2020) - Trinh, Lena; Peterson, Pernilla; Leander, Peter; Brorson, Håkan; Månsson, Sven
Abstract : Purpose: To compare MR‐based fatty acid composition (FAC) quantification methods against the gold standard technique, gas chromatography (GC), with comparison of a free and a constrained signal model. The FAC was measured in the healthy and edematous legs of lymphedema patients. Methods: In vivo MRS and MRI data were acquired from 19 patients at 3 T. Biopsies were collected from subcutaneous adipose tissue of both thighs during liposuction. The saturated, monounsaturated, and polyunsaturated fatty acid fractions ( fSFA, fMUFA and fPUFA, respectively) were estimated with the MR‐based methods using two signal models: free and constrained (number of methylene‐interrupted double bonds expressed in number of double bonds, based on GC data). Linear regression, Bland–Altman plots, and correlation coefficients were used to evaluate the MR methods against the GC of the biopsies. Paired t ‐test was used to compare the FAC difference between edematous and healthy legs. Results: The estimated parameters correlated well with the GC data ( rSFA, rMUFA, and rPUFA = 0.82, 0.81 and 0.89, respectively) using the free model MRI‐based approach. In comparison, the MRS‐based method resulted in weaker correlations and larger biases compared with MRI. In both cases, correct estimation of fMUFA and fPUFA fractions were not possible using the constrained model. The difference in FAC of healthy and edematous legs were estimated to 0.008 ( P = .01), −0.009 ( P = .005), and 0.002 ( P = .03) for fSFA, fMUFA, and fPUFA . Conclusion: In this study, MRI‐based FAC quantification was highly correlated, although slightly biased, compared with GC, whereas the MRS‐based approach resulted in weaker correlations. Small but significant differences could be found between the healthy and edematous legs of lymphedema patients using GC analysis.