# Comparison of quantitative imaging analysis methods to evaluate murine [18F]FLT PET therapy response studies

## TL;DR

This study compares different methods to analyze FLT PET imaging in mice to evaluate how well they can track cancer treatment responses.

## Contribution

The study identifies optimal semi-quantitative FLT PET metrics for harmonizing preclinical imaging studies.

## Key findings

- SUVbw(max) and SUVbw(mean-50%) showed the strongest ability to differentiate between treatment and control groups.
- Standardized imaging protocols can harmonize FLT PET metrics across preclinical studies.
- Larger animal cohorts are needed for robust statistical power in FLT PET studies.

## Abstract

Positron Emission Tomography (PET) imaging using 3’-deoxy-3’-[F-18] fluorothymidine (FLT) is a valuable non-invasive marker of tumor proliferation. However, variability in imaging protocols and quantitative analysis techniques hampers comparability across preclinical chemotherapy response studies.

To address this issue in preclinical studies, we evaluated two key areas: (1) imaging standardization (2) semi-quantitative analyses, including Standard Uptake Value (SUV) SUV(max) and SUV(mean), and percent injected (%ID)/g. Using standardized methods of animal handling, image acquisition, image reconstruction and analyses, we assessed multiple FLT uptake metrics in three responsive Patient-Derived Xenograft (PDX) models treated with temozolomide/berzosertib or cisplatin/berzosertib. Metrics included: %ID, SUVbw(max), SUVbw(mean) with a Region of Interest (ROI) threshold of 50% of the maximum value [SUVbw(mean-50%)], and the ratios tumor-to-tissue and tumor-to-liver. Statistical comparisons were made using Brown-Forsythe and Kruskal-Wallis ANOVA and unpaired two tailed t-test to assess cohort differences.

Across models and timepoints, no statistical difference among analysis techniques were observed except for one outlier at day 3 in one vehicle cohort, likely due to variability in the normalization parameter. SUVbw(max) and SUVbw(mean-50%) showed the strongest ability to differentiate between vehicle and treated cohorts.

Semi-quantitative FLT PET metrics can be harmonized across preclinical studies, with caveats in understanding the normalization parameters, with SUV-based metrics preferred and that larger numbers of animals per cohort will be required to power (≥0.8) robust conclusions. These findings support FLT PET standardization in translational imaging.

The online version contains supplementary material available at 10.1186/s12967-025-07475-2.