Skip to main navigation Skip to search Skip to main content

Functional 4-D clustering for characterizing intratumor heterogeneity in dynamic imaging: evaluation in FDG PET as a prognostic biomarker for breast cancer

  • Rhea Chitalia
  • , Varsha Viswanath
  • , Austin R. Pantel
  • , Lanell M. Peterson
  • , Aimilia Gastounioti
  • , Eric A. Cohen
  • , Mark Muzi
  • , Joel Karp
  • , David A. Mankoff
  • , Despina Kontos

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: Probe-based dynamic (4-D) imaging modalities capture breast intratumor heterogeneity both spatially and kinetically. Characterizing heterogeneity through tumor sub-populations with distinct functional behavior may elucidate tumor biology to improve targeted therapy specificity and enable precision clinical decision making. Methods: We propose an unsupervised clustering algorithm for 4-D imaging that integrates Markov-Random Field (MRF) image segmentation with time-series analysis to characterize kinetic intratumor heterogeneity. We applied this to dynamic FDG PET scans by identifying distinct time-activity curve (TAC) profiles with spatial proximity constraints. We first evaluated algorithm performance using simulated dynamic data. We then applied our algorithm to a dataset of 50 women with locally advanced breast cancer imaged by dynamic FDG PET prior to treatment and followed to monitor for disease recurrence. A functional tumor heterogeneity (FTH) signature was then extracted from functionally distinct sub-regions within each tumor. Cross-validated time-to-event analysis was performed to assess the prognostic value of FTH signatures compared to established histopathological and kinetic prognostic markers. Results: Adding FTH signatures to a baseline model of known predictors of disease recurrence and established FDG PET uptake and kinetic markers improved the concordance statistic (C-statistic) from 0.59 to 0.74 (p = 0.005). Unsupervised hierarchical clustering of the FTH signatures identified two significant (p < 0.001) phenotypes of tumor heterogeneity corresponding to high and low FTH. Distributions of FDG flux, or Ki, were significantly different (p = 0.04) across the two phenotypes. Conclusions: Our findings suggest that imaging markers of FTH add independent value beyond standard PET imaging metrics in predicting recurrence-free survival in breast cancer and thus merit further study.

Original languageEnglish
Pages (from-to)3990-4001
Number of pages12
JournalEuropean Journal of Nuclear Medicine and Molecular Imaging
Volume48
Issue number12
DOIs
StatePublished - Nov 2021

Keywords

  • Breast cancer
  • Dynamic PET
  • Imaging markers
  • Intratumor heterogeneity

Fingerprint

Dive into the research topics of 'Functional 4-D clustering for characterizing intratumor heterogeneity in dynamic imaging: evaluation in FDG PET as a prognostic biomarker for breast cancer'. Together they form a unique fingerprint.

Cite this