Abstract
Numerous recent works highlight the limited utility of established tumor cell lines in recapitulating the heterogeneity of tumors in patients. More realistic preclinical cancer models are thought to be provided by transplantable, patient-derived tumor xenografts (PDX). Inter- and intra-tumor heterogeneity of PDX, however, present several challenges in developing optimal quantitative pipelines to assess response to therapy. The objective of this work was to develop and optimize image metrics of FDG-PET to assess response to combination docetaxel/carboplatin therapy in a co-clinical trial involving triple negative breast cancer (TNBC) PDX. We characterize the reproducibility of SUV metrics to assess response to therapy and optimize a preclinical PERCIST (µPERCIST) paradigm to complement clinical standards. Considerations in this effort included variability in tumor growth rate and tumor size; solid tumor vs. tumor heterogeneity and necrotic phenotype; and optimal selection of tumor slice versus whole tumor. A test-retest protocol was implemented to optimize the reproducibility of FDG-PET SUV thresholds, SUVpeak metrics, and µPERCIST parameters. In assessing response to therapy, FDG-PET imaging was performed at baseline and +4 days following therapy. The reproducibility, accuracy, variability, and performance of imaging metrics to assess response to therapy were determined. We defined an index—“Quantitative Response Assessment Score (QRAS)”—to integrate parameters of prediction and precision, and thus aid in selecting optimal image metrics of response to therapy. Our data suggests that a threshold value of 25% (SUV25) of SUVmax was highly reproducible (<9% variability). Concordance and reproducibility of µPERCIST were maximized at α=0.7 and β=2.8 and exhibited high correlation to SUV25 measures of tumor uptake. QRAS scores favor SUV25 followed by SUVP14 as optimal metrics of response to therapy. Additional studies are warranted to fully characterize the utility of SUV25 and µPERCIST SUVP14 as image metrics of response to therapy across a wide range of therapeutic regiments and PDX models.
- Animal Imaging
- Image Processing
- Oncology: Breast
- PET/CT
- FDG-PET
- co-clinical imaging
- patient-derived tumor xenografts (PDX)
- quantitative imaging
- triple negative breast cancer
- Copyright © 2019 by the Society of Nuclear Medicine and Molecular Imaging, Inc.