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Proceedings Paper

Development and proof-of-concept of three-dimensional lung histology volumes
Author(s): Lindsay Mathew; Mostafa Alabousi; Andrew Wheatley; Usaf Aladl; Deborah Slipetz; James C. Hogg; Aaron Fenster; Grace Parraga
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Paper Abstract

Most medical imaging is inherently three-dimensional (3D) but for validation of pathological findings, histopathology is commonly used and typically histopathology images are acquired as twodimensional slices with quantitative analysis performed in a single dimension. Histopathology is invasive, labour-intensive, and the analysis cannot be performed in real time, yet it remains the gold standard for the pathological diagnosis and validation of clinical or radiological diagnoses of disease. A major goal worldwide is to improve medical imaging resolution, sensitivity and specificity to better guide therapy and biopsy and to one day delay or replace biopsy. A key limitation however is the lack of tools to directly compare 3D macroscopic imaging acquired in patients with histopathology findings, typically provided in a single dimension (1D) or in two dimensions (2D). To directly address this, we developed methods for 2D histology slice visualization/registration to generate 3D volumes and quantified tissue components in the 3D volume for direct comparison to volumetric micro-CT and clinical CT. We used the elastase-instilled mouse emphysema lung model to evaluate our methods with murine lungs sectioned (5 μm thickness/10 μm gap) and digitized with 2μm in-plane resolution. 3D volumes were generated for wildtype and elastase mouse lung sections after semi-automated registration of all tissue slices. The 1D mean linear intercept (Lm) for wildtype (WT) (47.1 μm ± 9.8 μm) and elastase mouse lung (64.5 μm ± 14.0 μm) was significantly different (p<.001). We also generated 3D measurements based on tissue and airspace morphometry from the 3D volumes and all of these were significantly different (p<.0001) when comparing elastase and WT mouse lung. The ratio of the airspace-to-lung volume for the entire lung volume was also significantly and strongly correlated with Lm.

Paper Details

Date Published: 16 April 2012
PDF: 6 pages
Proc. SPIE 8317, Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging, 83171N (16 April 2012); doi: 10.1117/12.912620
Show Author Affiliations
Lindsay Mathew, Imaging Research Labs., Robarts Research Institute (Canada)
Mostafa Alabousi, Imaging Research Labs., Robarts Research Institute (Canada)
Andrew Wheatley, Imaging Research Labs., Robarts Research Institute (Canada)
Usaf Aladl, Imaging Research Labs., Robarts Research Institute (Canada)
Deborah Slipetz, Merck Research Labs. (United States)
James C. Hogg, The James Hogg Research Ctr., Univ. of British Columbia (Canada)
St. Paul's Hospital (Canada)
Aaron Fenster, Imaging Research Labs., Robarts Research Institute (Canada)
Grace Parraga, Imaging Research Labs., Robarts Research Institute (Canada)


Published in SPIE Proceedings Vol. 8317:
Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging
Robert C. Molthen; John B. Weaver, Editor(s)

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