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Updated: Oct 11, 2025
A Mouse Model of Incompletely Resected Soft Tissue Sarcoma for Testing Neoadjuvant Therapies
Published on: July 28, 2020
Natural speed of growth of untreated soft-tissue sarcomas: A dimension-based imaging analysis
Amandine Crombé1, David Fadli2, Paolo Spinnato3
1Department of Oncologic Imaging, Bergonié Institut, Regional Comprehensive Cancer Center of Bordeaux, F-33076 Bordeaux, France; University of Bordeaux, F-33000 Bordeaux, France; Models in Oncology (MONC) Team, INRIA Bordeaux Sud-Ouest, CNRS, UMR 5251, F-33405 Talence, France.
Purpose:
The interval from first symptoms to diagnosis, staging and referral to reference center can last months for soft-tissue sarcoma (STS) patients. Meanwhile, patients can undergo different imaging that capture the 'natural' tumor changes, before medical intervention. Aim was to depict these 'natural' dimensional variations and to correlate them with patients' outcome.
Methods:
Single-center retrospective study including all consecutive adults with newly-diagnosed STS, ≥2 pre-treatment imaging (CT-scan or MRI) on the tumor (Exam-0 and Exam-1), and managed in reference center between 2007 and 2018. Longest diameter (LD) and volume were calculated on both examinations to obtain the naïve dimensional growth before any intervention. SARCULATOR nomogram was applied on data at Exam-0 and Exam-1. Correlations with overall, metastatic and local relapse-free survivals (OS, MFS and LFS), and with pre-treatment pathological features were performed.
Results:
137 patients were included (median age: 65 years). Average naïve growth was +39.4% in LD and +503% in volume during an average Exam-0-to-Exam-1 interval of 130 days. The 10-year distant metastasis and OS predictions were different at Exam-0 and Exam-1 (P < 0.0001 for both). All the changes in radiological measurements significantly correlated with pre-treatment number of mitosis, grade and complex genomic (P-value range: <0.0001-0.0481). Multivariate Cox modeling identified the relative change in LD/month and absolute change in LD/month as independent predictors for OS and LFS, respectively (P = 0.0003 and 0.0001, respectively).
Conclusion:
When available, the natural speed of growth on pre-treatment imaging should be evaluated to improve the estimation of pre-treatment histological grade and patients' OS and LFS.
