Functional 4-D clustering for characterizing intratumor heterogeneity in dynamic imaging: evaluation in FDG PET as a prognostic biomarker for breast cancer.
Breast cancer
Dynamic PET
Imaging markers
Intratumor heterogeneity
Journal
European journal of nuclear medicine and molecular imaging
ISSN: 1619-7089
Titre abrégé: Eur J Nucl Med Mol Imaging
Pays: Germany
ID NLM: 101140988
Informations de publication
Date de publication:
11 2021
11 2021
Historique:
received:
12
11
2020
accepted:
14
02
2021
pubmed:
8
3
2021
medline:
21
10
2021
entrez:
7
3
2021
Statut:
ppublish
Résumé
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. 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. 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. 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.
Identifiants
pubmed: 33677641
doi: 10.1007/s00259-021-05265-8
pii: 10.1007/s00259-021-05265-8
pmc: PMC8421450
mid: NIHMS1701449
doi:
Substances chimiques
Biomarkers
0
Fluorodeoxyglucose F18
0Z5B2CJX4D
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
3990-4001Subventions
Organisme : NCI NIH HHS
ID : R01 CA223816
Pays : United States
Organisme : NIBIB NIH HHS
ID : T32 EB009384
Pays : United States
Organisme : NCI NIH HHS
ID : R50 CA211270
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA197000
Pays : United States
Organisme : NCI NIH HHS
ID : R33 CA225310
Pays : United States
Organisme : NIH HHS
ID : S10 OD023495
Pays : United States
Commentaires et corrections
Type : ErratumIn
Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.
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