Thaiss, W.M.* ; Gatidis, S.* ; Sartorius, T. ; Machann, J. ; Peter, A. ; Eigentler, T.K.* ; Nikolaou, K.* ; Pichler, B.J.* ; Kneilling, M.*
Noninvasive, longitudinal imaging-based analysis of body adipose tissue and water composition in a melanoma mouse model and in immune checkpoint inhibitor-treated metastatic melanoma patients.
Background As cancer cachexia (CC) is associated with cancer progression, early identification would be beneficial. The aim of this study was to establish a workflow for automated MRI-based segmentation of visceral (VAT) and subcutaneous adipose tissue (SCAT) and lean tissue water (LTW) in a B16 melanoma animal model, monitor diseases progression and transfer the protocol to human melanoma patients for therapy assessment. Methods For in vivo monitoring of CC B16 melanoma-bearing and healthy mice underwent longitudinal three-point DIXON MRI (days 3, 12, 17 after subcutaneous tumor inoculation). In a prospective clinical study, 18 metastatic melanoma patients underwent MRI before, 2 and 12 weeks after onset of checkpoint inhibitor therapy (CIT; n = 16). We employed an in-house MATLAB script for automated whole-body segmentation for detection of VAT, SCAT and LTW. Results B16 mice exhibited a CC phenotype and developed a reduced VAT volume compared to baseline (B16 - 249.8 mu l, - 25%; controls + 85.3 mu l, + 10%, p = 0.003) and to healthy controls. LTW was increased in controls compared to melanoma mice. Five melanoma patients responded to CIT, 7 progressed, and 6 displayed a mixed response. Responding patients exhibited a very limited variability in VAT and SCAT in contrast to others. Interestingly, the LTW was decreased in CIT responding patients (- 3.02% +/- 2.67%; p = 0.0034) but increased in patients with progressive disease (+ 1.97% +/- 2.19%) and mixed response (+ 4.59% +/- 3.71%). Conclusion MRI-based segmentation of fat and water contents adds essential additional information for monitoring the development of CC in mice and metastatic melanoma patients during CIT or other treatment approaches.
FörderungenWerner Siemens-Foundation (Zug, Switzerland) Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, Germany's Excellence Strategy -EXC) Faculty of Medicine of the Eberhard Karls Universitat Tubingen Projekt DEAL