Ex Vivo MR Histology and Cytometric Feature Mapping Connect Three-dimensional in Vivo MR Images to Two-dimensional Histopathologic Images of Murine Sarcomas.

Blocker, Stephanie J

Cook, James

Mowery, Yvonne M

Everitt, Jeffrey I

Qi, Yi

Hornburg, Kathryn J

Cofer, Gary P

Zapata, Fernando

Bassil, Alex M

Badea, Cristian T

Kirsch, David G

Johnson, G Allan

2021-06-21T20:49:53Z

2021-06-21T20:49:53Z

2021-05

2021-06-21T20:49:52Z

Purpose To establish a platform for quantitative tissue-based interpretation of cytoarchitecture features from tumor MRI measurements. Materials and Methods In a pilot preclinical study, multicontrast in vivo MRI of murine soft-tissue sarcomas in 10 mice, followed by ex vivo MRI of fixed tissues (termed MR histology), was performed. Paraffin-embedded limb cross-sections were stained with hematoxylin-eosin, digitized, and registered with MRI. Registration was assessed by using binarized tumor maps and Dice similarity coefficients (DSCs). Quantitative cytometric feature maps from histologic slides were derived by using nuclear segmentation and compared with registered MRI, including apparent diffusion coefficients and transverse relaxation times as affected by magnetic field heterogeneity (T2* maps). Cytometric features were compared with each MR image individually by using simple linear regression analysis to identify the features of interest, and the goodness of fit was assessed on the basis of R² values. Results Registration of MR images to histopathologic slide images resulted in mean DSCs of 0.912 for ex vivo MR histology and 0.881 for in vivo MRI. Triplicate repeats showed high registration repeatability (mean DSC, >0.9). Whole-slide nuclear segmentations were automated to detect nuclei on histopathologic slides (DSC = 0.8), and feature maps were generated for correlative analysis with MR images. Notable trends were observed between cell density and in vivo apparent diffusion coefficients (best line fit: R² = 0.96, P < .001). Multiple cytoarchitectural features exhibited linear relationships with in vivo T2* maps, including nuclear circularity (best line fit: R² = 0.99, P < .001) and variance in nuclear circularity (best line fit: R² = 0.98, P < .001). Conclusion An infrastructure for registering and quantitatively comparing in vivo tumor MRI with traditional histologic analysis was successfully implemented in a preclinical pilot study of soft-tissue sarcomas. Keywords: MRI, Pathology, Animal Studies, Tissue Characterization Supplemental material is available for this article. © RSNA, 2021.

2638-616X

2638-616X

https://hdl.handle.net/10161/23389

eng

Radiological Society of North America (RSNA)

Radiology. Imaging cancer

10.1148/rycan.2021200103

Animal Studies

MRI

Pathology

Tissue Characterization

Ex Vivo MR Histology and Cytometric Feature Mapping Connect Three-dimensional in Vivo MR Images to Two-dimensional Histopathologic Images of Murine Sarcomas.

Journal article

Blocker, Stephanie J|0000-0002-6665-7844

Mowery, Yvonne M|0000-0002-9839-2414

Everitt, Jeffrey I|0000-0003-0273-6284

Hornburg, Kathryn J|0000-0003-3851-8297

Badea, Cristian T|0000-0002-1850-2522

Johnson, G Allan|0000-0002-7606-5447

e200103

3

School of Medicine

Physics

Biomedical Engineering

Duke Cancer Institute

Radiology

Duke

Trinity College of Arts & Sciences

Pratt School of Engineering

Institutes and Centers

Clinical Science Departments

Radiation Oncology

Head and Neck Surgery & Communication Sciences

Pathology

Published

3