E2607. Volumetry as a Biomarker in Soft Tissue Sarcoma Imaging: An Evidence-Based Overview
  1. Ananya Singh; University of Miami
  2. Rania Anan; Mansoura University
  3. Wenli Cai; Harvard Medical School; Massachusetts General Hospital
  4. Saumya Tripathi; Batumi Shota Rustaveli State University
  5. Francis Hornicek; University of Miami, Miller School of Medicine
Current limitations of response assessment criteria’s for soft tissue sarcoma include RECIST (limited reliability in nonspherical and necrotic tumors), PET-CT (costs, false positive for inflammations & failure to detect small lesions), and overall and progression-free survival (confounded by deaths or other illness). Purpose to discuss principles involved in volumetric estimation of soft tissue sarcoma, highlight recent advances in volumetric estimations of tumors with evidence-based support, and highlight recent advances in volumetric estimations of other pathophysiological processes with evidence-based support.

Educational Goals / Teaching Points
Volumetry has evolved from quantification of total tumor burden to estimation of various differential tumor components such as vascularity, necrosis and viable tumor portion in treated cases. Split tumor estimates and quantification of differential sarcoma tumor tissue characteristics on MRI correlates well with viable tumor tissue estimates by histopathology and may also aid in preoperative planning tumor resections based on tumor margin viable tumor scores. This exhibit reviews these emerging trends in soft tissue sarcoma volumetry with evidence-based support.

Key Anatomic/Physiologic Issues and Imaging Findings/Techniques
Principles, background and prerequisites would highlight limitations of RECIST criteria for assessment of tumor response to therapy, will emphasize reasons and need for more reproducible and efficient quantitative imaging MRI based methods. Emerging concepts in soft tissue sarcoma Imaging: Advantages, Limitations: This section would focus on emerging role of 3D volumetry, artificial intelligence and computer-aided detection methods which use MRI datasets with effective processing to generate total and fractional tumor components volume burden. Evidence-based tumor component quantification: Differentiation of necrosis from tumor tissue- The results of a pilot study will be highlighted where a prospective study correlates computer-aided detection volumetry of viable tumor components of preoperative soft tissue sarcoma MRI with histopathology viable tumor scores given by pathologists on reviewing post operative specimens. Pearson correlation and Bland-Altman statistics would be used. Emerging concepts: tumor necrosis vs. soft tissue quantification by computer-aided automations. This section would further elaborate the future potential on such image post processing techniques.

The estimated percentage of MRI-based enhancing tumor volume of soft tissue sarcomas on dynamic acquisition shows excellent correlation with percentage of tumor viability reported on the excised tumor pathology in our study. The best correlation of MRI-based viable tumor volume was observed in tumors greater than 5 cm in diameter and in tumors of relatively homogenous lipoid variety. Heterogeneity in tumors, mixed inflammation on pathology, pleomorphism and tumors of non-myxo-lipoid and spindle cell variety were found in cases where larger differences between MRI and pathology necrosis were observed. These findings may warrant further validation on a larger cohort.