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Reply to: Comparing the Variability Between Measurements for Sarcopenia Using Magnetic Resonance Imaging and Computed Tomography Imaging

2016; Elsevier BV; Volume: 16; Issue: 9 Linguagem: Inglês

10.1111/ajt.13860

1600-6143

Jeroen L.A. van Vugt, Stef Levolger, Herold J. Metselaar, Jan N.M. IJzermans,

Body Composition Measurement Techniques

We appreciate the interest of Tandon and colleagues in our recently published article (1.van Vugt JL Levolger S de Bruin RW van Rosmalen J Metselaar HJ IJzermans JN Systematic review and meta-analysis of the impact of computed tomography assessed skeletal muscle mass on outcome in patients awaiting or undergoing liver transplantation.Am J Transplant. 2016; Google Scholar). Their valuable results suggest that computed tomography (CT) and magnetic resonance imaging (MRI) are highly comparable imaging modalities to assess cross-sectional parameters of body composition that could be used interchangeably. However, we would like to add some remarks regarding their results. Although the Bland Altman plot depicts a mean difference of 2.1 cm² in cross-sectional skeletal muscle area between CT and MRI, there are some significant outliers up to around 35 cm², mostly favoring CT. These disagreements are remarkable and should be discussed in more detail. Since there is a time interval between CT and MRI, one could wonder whether these disagreements occurred, for instance, in patients with a longer time interval between CT and MRI during which muscle wasting or gaining may have occurred. Recently, we performed a study on the comparability of multiple software programs to assess parameters of body composition (i.e. skeletal muscle, and subcutaneous and visceral adipose tissue) on CT (2.Abstracts of the 8th International Conference on CachexiaSarcopenia and Muscle Wasting. Paris, Paris, France2015: 398-509Google Scholar). We observed intraclass coefficient correlations (ICCs) comparable to those of Tandon and colleagues. Excellent ICCs, however, represent a high correlation between the value of the surface (cm²) only. This could, however, be accompanied by systematically excluding skeletal muscle tissue or, vice versa, including incorrectly annotated skeletal muscle tissue. Therefore, we recommend adding the Jaccard index (J), also known as the Jaccard similarity coefficient, which was first described by Paul Jaccard in 1901 (3.Jaccard P Étude comparative de la distribution florale dans une portion des alpes et des jura.Bulletin de la Société Vaudoise des Sciences Naturelles. 1901; 37: 547-579Google Scholar). The Jaccard index measures the similarity between sample sets and is defined as the size of the intersection divided by the size of the union of sample sets: J(A,B)=|A∩B||A∪B|, where A and B are annotated skeletal muscle areas on CT and MRI, respectively. Attracted by the promising data of Tandon and colleagues, we are looking forward to the final results. We want to emphasize the need for larger and well-defined studies comparing CT and MRI in order to establish the most appropriate clinical approach and are open to cooperation on this topic. The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation