to properly evaluate tumor extension in surrounding tissues of large STS, STS at locations where wide excision is difficult due to proximity of critical tissue structures such as in the head and neck, or an STS within a body cavity. In humans, MRI is the preferred modality for assessment of STS in limbs, delineating muscle groups, and separating tumor from adjacent vascular, muscular, and bony structures, while contrast‐enhanced CT is indicated in cases of (suspected) bone involvement, intra‐abdominal or retroperitoneal tumors, and for screening of pulmonary metastasis (Hanna and Fletcher 1995; López‐Pousa et al. 2016; Fuerst et al. 2017; Spoldi et al. 2017; Ranganathan et al. 2018).
Novel Diagnostic Imaging Techniques
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).
Staging and Grading
STS are histologically distinguished as low (grade I), intermediate (grade II), and high (grade III) grades, based on the degree of tissue differentiation, cellular pleomorphism, cellularity and matrix formation, mitotic index, and the amount of tumor necrosis (Kuntz et al. 1997). Tumor grade is predictive for distant metastasis, local recurrence, and shorter disease‐free intervals. Staging of STS follows a specific TNM staging scheme (Table 4.4) (Dennis et al. 2011; Greene 2002; Kotilingam et al. 2006; MacEwan et al. 2001). Despite the low incidence of lymph node involvement, investigation of draining lymph nodes is advised, including biopsy of suspect lymph nodes (Kuntz et al. 1997; Dennis et al. 2011).
Table 4.4 TNM staging and grading system for soft tissue sarcomas.
Source: Kotilingam et al. 2006; MacEwan et al. 2001; Greene 2002. The American Joint Committee on Cancer.
| T | Primary tumor | |||
| TX | Primary tumor cannot be assessed | |||
| T0 | No evidence of primary tumor | |||
| T1 | Tumor < 5 cm in greatest dimension | |||
| T1a | Superficial tumor | |||
| T1b | Deep tumor | |||
| T2 | Tumor > 5 cm in greatest dimension | |||
| T2a | Superficial tumor | |||
| T2b | Deep tumor | |||
| N | Regional lymph nodes | |||
| NX | Regional lymph nodes cannot be assessed | |||
| N0 | No regional lymph node metastasis | |||
| N1 | Regional lymph node metastasis | |||
| M | Distant metastasis | |||
| MX | Distant metastasis cannot be assessed | |||
| M0 | No distant metastasis | |||
| M1 | Distant metastasis | |||
| G | Histologic grade | |||
| GX | Grade cannot be assessed | |||
| G1 | Low (grade I) | |||
| G2 | Intermediate (grade II) | |||
| G3 | High (grade III) | |||
| Stage | ||||
| I | G1–2 | Any T | N0 | M0 |
| II | G3 | T1a‐b, T2a | N0 | M0 |
| III | G3 | T2b | N0 | M0 |
| IV | Any G | Any T | N1 | Any M |
| Any G | Any T | Any N | Any M | |
Serum VEGF and neutrophil counts are positively correlated, and negative between VEGF and hemoglobin content in dogs with sarcoma (De Quieroz et al. 2013).
In contrary to primary care practices with predominating low‐grade STS (51–84%) (McSporran 2009; Bray et al. 2014), studies from referral practices report high‐grade STS are more
