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In human STS, specific MRI features or combinations of MRI data in multivariable algorithms have been increasingly investigated to build “radiomics” models to predict tumor grade and to assess the integrity of the pseudocapsule. Three‐dimensional imaging features from fat‐suppressed T2‐weighted imaging could be used as candidate biomarkers for preoperative prediction of histopathological grades of soft tissue sarcomas noninvasively (Liu et al. 2008). Accuracy levels of such “radiomics” models currently reach up to 88% (Chhabra et al. 2018; Corino et al. 2018). These findings might have implications for veterinary patients although they have not been reported to our knowledge.

Optical coherence tomography (OCT) is a medical imaging technique that uses light to capture micrometer‐resolution, three‐dimensional images from within optical scattering media (e.g. biological tissue). Following the generation of an initial set of OCT images correlated with standard hematoxylin and eosin‐stained histopathology, over 760 images were subsequently used for automated analysis. Using texture‐based image processing metrics, OCT images of sarcoma, muscle, and adipose tissue were all found to be statistically different from one another. This demonstrates the potential use of intraoperative OCT, along with an automated tissue differentiation algorithm, as a guidance tool for soft tissue sarcoma margin delineation in the operating room (Mesa et al. 2017).

Fluorescence‐based imaging is another technique for real‐time intraoperative tumor margin assessment in excision of STS. Fluorescence‐based imaging techniques use fluorescent agents that are preferentially activated by tumor cells, which can subsequently be measured after excitation by an appropriate wavelength of light (Bartholf DeWitt et al. 2016).