期刊
JOURNAL OF NUCLEAR MEDICINE
卷 61, 期 6, 页码 842-849出版社
SOC NUCLEAR MEDICINE INC
DOI: 10.2967/jnumed.119.234286
关键词
co-clinical trials; triple-negative breast cancer; patient-derived xenografts; quantitative imaging; response to therapy; reproducibility
资金
- National Cancer Institute [U24CA209837, U54CA224083, U54CA199092]
- NIBIB [P41EB025815]
- Siteman Cancer Center Support Grant [P30CA091842]
- Mallinckrodt Institute of Radiology
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 xenografts (PDXs). The inter- and intratumor heterogeneity of PDXs, however, presents several challenges in developing optimal quantitative pipelines to assess response to therapy. The objective of this work was to develop and optimize image metrics for F-18-FDG PET to assess response to combination docetaxel and carboplatin therapy in a co-clinical trial involving triple-negative breast cancer PDXs. We characterized the reproducibility of standardized uptake value (SUV) metrics to assess response to therapy, and we optimized a preclinical PERCIST paradigm to complement clinical standards. Considerations in this effort included variability in tumor growth rate and tumor size, solid tumors versus tumor heterogeneity and a necrotic phenotype, and optimal selection of tumor slices versus whole tumor. Methods: A test-retest protocol was implemented to optimize the reproducibility of F-18-FDG PET SUV thresholds, SUVpeak metrics, and preclinical PERCIST parameters. In assessing response to therapy, F-18-FDG PET imaging was performed at baseline and 4 d after therapy. The reproducibility, accuracy, variability, and performance of imaging metrics to assess response to therapy were determined. We defined an index called the Quantitative Response Assessment Score to integrate parameters of prediction and precision and thus aid in selecting the optimal image metric to assess response to therapy. Results: Our data suggest that a threshold of 25% of SUVmax (SUV25) was highly reproducible (<9% variability). The concordance and reproducibility of preclinical PERCIST were maximized at alpha = 0.7 and beta = 2.8 and exhibited a high correlation with SUV25 measures of tumor uptake, which in turn correlated with the SUV of metabolic tumor. Conclusion: The Quantitative Response Assessment Score favors SUV25 followed by SUVpeak for a sphere with a volume of 14 mm(3) (SUVP14) as optimal metrics of response to therapy. Additional studies are warranted to fully characterize the utility of SUV25 and preclinical PERCIST SUVP14 as image metrics for response to therapy across a wide range of therapeutic regimens and PDX models.
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