Digital Pathology

Methodology to study the three-dimensional spatial distribution of prostate cancer and their dependence on clinical parameters

[+] Author Affiliations
Kristians Diaz Rojas, Benjamin Castaneda

Pontificia Universidad Católica del Perú, Department of Engineering, Section in Electrical and Electronic, Laboratory Medical Images, Av. Universitaria 1801, San Miguel Lima 32, Perú

Maria L. Montero

Pontificia Universidad Católica del Perú, Department of Science, Section of Mathematics, Laboratory Statistics, Av. Universitaria 1801, San Miguel Lima 32, Perú

Jorge Yao

University of Rochester Medical Center, Department of Pathology and Laboratory Medicine, 601 Elmwood Avenue, Box 648, Rochester, New York 14642, United States

Edward Messing, Anees Fazili, Jean Joseph

University of Rochester Medical Center, Department of Urology, 601 Elmwood Avenue, Box 648, Rochester, New York 14642, United States

Yangming Ou

Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts 02129, United States

Deborah J. Rubens

University of Rochester Medical Center, Department of Imaging Sciences, 601 Elmwood Avenue, Box 648, Rochester, New York 14642, United States

Kevin J. Parker

University of Rochester, Department of Electrical and Computer Engineering, Hopeman Engineering Building 203, Box 270126, Rochester, New York 14627, United States

Christos Davatzikos

University of Pennsylvania, Departments of Radiology and Electrical and Computer Engineering, 3600 Market Street, Suite 380, Philadelphia, Pennsylvania 19104, United States

J. Med. Imag. 2(3), 037502 (Jul 29, 2015). doi:10.1117/1.JMI.2.3.037502
History: Received March 2, 2015; Accepted June 29, 2015
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Abstract.  A methodology to study the relationship between clinical variables [e.g., prostate specific antigen (PSA) or Gleason score] and cancer spatial distribution is described. Three-dimensional (3-D) models of 216 glands are reconstructed from digital images of whole mount histopathological slices. The models are deformed into one prostate model selected as an atlas using a combination of rigid, affine, and B-spline deformable registration techniques. Spatial cancer distribution is assessed by counting the number of tumor occurrences among all glands in a given position of the 3-D registered atlas. Finally, a difference between proportions is used to compare different spatial distributions. As a proof of concept, we compare spatial distributions from patients with PSA greater and less than 5ng/ml and from patients older and younger than 60 years. Results suggest that prostate cancer has a significant difference in the right zone of the prostate between populations with PSA greater and less than 5ng/ml. Age does not have any impact in the spatial distribution of the disease. The proposed methodology can help to comprehend prostate cancer by understanding its spatial distribution and how it changes according to clinical parameters. Finally, this methodology can be easily adapted to other organs and pathologies.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Kristians Diaz Rojas ; Maria L. Montero ; Jorge Yao ; Edward Messing ; Anees Fazili, et al.
"Methodology to study the three-dimensional spatial distribution of prostate cancer and their dependence on clinical parameters", J. Med. Imag. 2(3), 037502 (Jul 29, 2015). ; http://dx.doi.org/10.1117/1.JMI.2.3.037502


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