Spatial Characterization of Tumor Perfusion Properties from 3D DCE-US Perfusion Maps are Early Predictors of Cancer Treatment Response.

Abstract:

:There is a need for noninvasive repeatable biomarkers to detect early cancer treatment response and spare non-responders unnecessary morbidities and costs. Here, we introduce three-dimensional (3D) dynamic contrast enhanced ultrasound (DCE-US) perfusion map characterization as inexpensive, bedside and longitudinal indicator of tumor perfusion for prediction of vascular changes and therapy response. More specifically, we developed computational tools to generate perfusion maps in 3D of tumor blood flow, and identified repeatable quantitative features to use in machine-learning models to capture subtle multi-parametric perfusion properties, including heterogeneity. Models were developed and trained in mice data and tested in a separate mouse cohort, as well as early validation clinical data consisting of patients receiving therapy for liver metastases. Models had excellent (ROC-AUC > 0.9) prediction of response in pre-clinical data, as well as proof-of-concept clinical data. Significant correlations with histological assessments of tumor vasculature were noted (Spearman R > 0.70) in pre-clinical data. Our approach can identify responders based on early perfusion changes, using perfusion properties correlated to gold-standard vascular properties.

journal_name

Sci Rep

journal_title

Scientific reports

authors

El Kaffas A,Hoogi A,Zhou J,Durot I,Wang H,Rosenberg J,Tseng A,Sagreiya H,Akhbardeh A,Rubin DL,Kamaya A,Hristov D,Willmann JK

doi

10.1038/s41598-020-63810-1

subject

Has Abstract

pub_date

2020-04-24 00:00:00

pages

6996

issue

1

issn

2045-2322

pii

10.1038/s41598-020-63810-1

journal_volume

10

pub_type

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