Accelerated Body Composition Analysis in Whole-body MRI Using CycleGAN-based T2-HASTE Synthesis From Fast Whole-body Localizers.

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Abstract

To evaluate whether CycleGAN-based synthesis of T2-HASTE images from routinely acquired fast whole-body localizer (FWBL) can support accelerated body composition analysis (BCA) by preserving sufficient information for an established T2-HASTE-based BCA pipeline to generate measurements comparable to those derived from reference T2-HASTE images. This retrospective single-center proof-of-concept study included 468 patients (53% female, mean age 51±18 y) who underwent WB-MRI with FWBL and T2-HASTE between March 2012 and December 2025, 431 (92%) of whom were examined from 2023 onward. A CycleGAN model was trained to generate synthetic T2-HASTE images from registered FWBL and T2-HASTE images. Fully automated MRI-based BCA was conducted on synthetic and reference T2-HASTE images using a fixed pretrained BCA model, focusing on 5 key segmentation compartments: subcutaneous adipose tissue (SAT), muscle, abdominal cavity, thoracic cavity, and bone, with subsequent region-specific volumetric analyses of SAT, muscle, and bone in the thoracic, abdominal, and whole-body regions. Derived BCA markers included the Sarcopenia Index (muscle-to-bone ratio) and the muscle-to-SAT ratio. Agreement was assessed using Bland-Altman analysis, including mean bias expressed in absolute units and as a percentage of the mean reference volume, median absolute percentage error, Pearson correlation, and weighted Cohen kappa for tertile-based stratification. Segmentation overlap was evaluated using Sørensen-Dice similarity coefficients. In addition, a qualitative reader evaluation was performed by 4 radiologists across 30 cases. Mean percentage bias across the thoracic, abdominal, and whole-body regions was -0.05%, 3.51%, and 2.91% for muscle, -0.19%, -1.21%, and 0.71% for SAT, and -7.10%, -8.86%, and -6.30% for bone, respectively. Median absolute percentage error remained low for muscle (2.96% to 3.52%) and SAT (2.03% to 3.71%), whereas bone showed the highest relative error (5.93% to 8.26%). Tertile-based stratification agreement was high, particularly for the muscle-to-SAT ratio, with unchanged tertile assignment in 89.4% of thoracic, 93.6% of abdominal, and 95.7% of whole-body analyses (κ=0.92, 0.95, and 0.97, respectively). For the Sarcopenia Index, unchanged tertile assignment was 68.1%, 80.9%, and 87.2%, respectively (κ=0.76, 0.86, and 0.90). Segmentation overlap was high across the main compartments, with mean Sørensen-Dice coefficients of 0.90 for SAT, 0.87 for muscle, 0.94 for the abdominal cavity, and 0.91 for the thoracic cavity, whereas bone showed lower overlap (0.76). Qualitative evaluation showed positive ratings for both synthetic image utility and segmentation plausibility, with the synthetic T2 representation rated as providing added value over FWBL for coarse body composition assessment on a 5-point Likert scale, where 1 indicated strong disagreement, and 5 indicated strong agreement (mean: 4.52, median: 5). Combining FWBL MRI with CycleGAN-based image synthesis yielded BCA measurements that closely matched those from reference T2-HASTE images and largely preserved body composition stratification. These findings demonstrate the feasibility of deriving quantitative BCA information from routinely acquired WB-MRI localizer data and support further investigation of accelerated MRI-based BCA approaches using simplified acquisitions.

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