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MR histology reveals tissue features beneath heterogeneous MRI signal in genetically engineered mouse models of sarcoma

To identify significant relationships between quantitative cytometric tissue features and quantitative MR (qMRI) intratumorally in preclinical undifferentiated pleomorphic sarcomas (UPS). In a prospective study of genetically engineered mouse models of UPS, we registered imaging libraries consisting...

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Published in:Frontiers in oncology 2024-05, Vol.14, p.1287479-1287479
Main Authors: Blocker, Stephanie J, Mowery, Yvonne M, Everitt, Jeffrey I, Cook, James, Cofer, Gary Price, Qi, Yi, Bassil, Alex M, Xu, Eric S, Kirsch, David G, Badea, Cristian T, Johnson, G Allan
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container_title Frontiers in oncology
container_volume 14
creator Blocker, Stephanie J
Mowery, Yvonne M
Everitt, Jeffrey I
Cook, James
Cofer, Gary Price
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Bassil, Alex M
Xu, Eric S
Kirsch, David G
Badea, Cristian T
Johnson, G Allan
description To identify significant relationships between quantitative cytometric tissue features and quantitative MR (qMRI) intratumorally in preclinical undifferentiated pleomorphic sarcomas (UPS). In a prospective study of genetically engineered mouse models of UPS, we registered imaging libraries consisting of matched multi-contrast MRI, three-dimensional (3D) multi-contrast high-resolution MR histology (MRH), and two-dimensional (2D) tissue slides. From digitized histology we generated quantitative cytometric feature maps from whole-slide automated nuclear segmentation. We automatically segmented intratumoral regions of distinct qMRI values and measured corresponding cytometric features. Linear regression analysis was performed to compare intratumoral qMRI and tissue cytometric features, and results were corrected for multiple comparisons. Linear correlations between qMRI and cytometric features with p values of
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Six features demonstrated significant linear relationships with T2*, and fifteen features correlated significantly with T2*. In both cases, nuclear Haralick texture features were the most prevalent type of feature correlated with T2*. A small group of nuclear topology features also correlated with one or both T2* contrasts, and positive trends were seen between T2* and nuclear size metrics. Registered multi-parametric imaging datasets can identify quantitative tissue features which contribute to UPS MR signal. 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subjects histology
image registration
MRI
multi-modal
Oncology
preclinical
sarcoma
title MR histology reveals tissue features beneath heterogeneous MRI signal in genetically engineered mouse models of sarcoma
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