Abstract
BackgroundAs 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.MethodsFor 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.ResultsB16 mice exhibited a CC phenotype and developed a reduced VAT volume compared to baseline (B16 − 249.8 µl, − 25%; controls + 85.3 µl, + 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%).ConclusionMRI-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.
Highlights
Cancer cachexia (CC) as an epiphenomenon associated with cancer and other chronic diseases is defined by an involuntary loss of muscle and fat mass [1]
We noninvasively investigated changes in glucose metabolism in vivo in primary and secondary lymphatic organs of immune checkpoint inhibitor-treated experimental mice as well as metastatic melanoma patients and identified differential signatures enabling us to differentiate between responders and nonresponders [25]
In animal studies as well as patient examinations, adipose tissue compartments (subcutaneous (SCAT) and visceral adipose tissue (VAT)) as well as the lean tissue water compartment (LTW)) were automatically segmented on the fat images using an active contour-based approach as previously described by Wuerslin et al [27]. This method is based on the use of active contours to detect the boundary between subcutaneous adipose tissue (SCAT) and the underlying musculature/fascia
Summary
Cancer cachexia (CC) as an epiphenomenon associated with cancer and other chronic diseases is defined by an involuntary loss of muscle and fat mass [1]. It can be associated with a variety of diseases, such as chronic heart failure, chronic kidney disease, and cancer. 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. 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
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