Unsupervised deconvolution of dynamic imaging reveals intratumor vascular heterogeneity
This work addresses the challenge of improving vascular phenotyping in tumors for medical imaging and oncology, representing an incremental advance in computational methods for dynamic imaging analysis.
The researchers tackled the problem of resolving intratumor vascular heterogeneity in dynamic imaging by developing an unsupervised computational method called tissue-specific compartment modeling (TSCM), which successfully revealed characteristic vascular heterogeneity and therapeutic responses in breast cancers that were previously undetectable.
Intratumor heterogeneity is often manifested by vascular compartments with distinct pharmacokinetics that cannot be resolved directly by in vivo dynamic imaging. We developed tissue-specific compartment modeling (TSCM), an unsupervised computational method of deconvolving dynamic imaging series from heterogeneous tumors that can improve vascular phenotyping in many biological contexts. Applying TSCM to dynamic contrast-enhanced MRI of breast cancers revealed characteristic intratumor vascular heterogeneity and therapeutic responses that were otherwise undetectable.