Integration of architectural and cytologic driven image algorithms for prostate adenocarcinoma identification

Article type: Research Article

Authors: Hipp, Jason | Monaco, James | Kunju, L. Priya | Cheng, Jerome | Yagi, Yukako | Rodriguez-Canales, Jaime | Emmert-Buck, Michael R. | Hewitt, Stephen | Feldman, Michael D. | Tomaszewski, John E. | Toner, Mehmet | Tompkins, Ronald G. | Flotte, Thomas | Lucas, David | Gilbertson, John R. | Madabhushi, Anant | Balis, Ulysses

Affiliations: Department of Pathology, University of Michigan, M4233A Medical Science I, Catherine MI, USA | Department of Biomedical Engineering, Rutgers The State University of New Jersey, Piscataway, NJ, USA | MGH Pathology Imaging and Communication Technology (PICT) Center, Boston, MA, USA | Laboratory of Pathology, National Institutes of Health, National Cancer Institute, Advanced Technology Center, Gaithersburg, MD, USA | Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA | Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA | Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA | Department of Pathology and Laboratory Medicine, Perlman School of Medicine at the University of Pennsylvania, Division of Surgical Pathology, 6 Founders Hospital of the University of Pennsylvania, Philadelphia, PA, USA | Pathology and Anatomical Sciences, School of Medicine and Biomedical Sciences, SUNY at the University of Buffalo, Buffalo, NY, USA

Note: [] These First authors contributed equally.

Note: [] These First authors contributed equally.

Note: [] Corresponding author: Anant Madabhushi, PhD, Rutgers The State University of New Jersey, Department of Biomedical Engineering, 599 Taylor Road, Piscataway, NJ, USA. Tel.: +1 732 445 4500; Fax: +1 732 445 3753; E-mail: anantm@rci.rutgers.edu These Senior authors contributed equally.

Note: [] Corresponding author: Ulysses J. Balis, MD, Department of Pathology, University of Michigan Health System, M4233A Medical Science I, 1301 Catherine, Ann Arbor, MI 48109-0602, USA. Tel.: +1 734 615 5727; Fax: +1 603 250 3139; E-mail: Ulysses@med.umich.edu These Senior authors contributed equally.

Abstract: Introduction: The advent of digital slides offers new opportunities within the practice of pathology such as the use of image analysis techniques to facilitate computer aided diagnosis (CAD) solutions. Use of CAD holds promise to enable new levels of decision support and allow for additional layers of quality assurance and consistency in rendered diagnoses. However, the development and testing of prostate cancer CAD solutions requires a ground truth map of the cancer to enable the generation of receiver operator characteristic (ROC) curves. This requires a pathologist to annotate, or paint, each of the malignant glands in prostate cancer with an image editor software - a time consuming and exhaustive process. Recently, two CAD algorithms have been described: probabilistic pairwise Markov models (PPMM) and spatially-invariant vector quantization (SIVQ). Briefly, SIVQ operates as a highly sensitive and specific pattern matching algorithm, making it optimal for the identification of any epithelial morphology, whereas PPMM operates as a highly sensitive detector of malignant perturbations in glandular lumenal architecture. Methods: By recapitulating algorithmically how a pathologist reviews prostate tissue sections, we created an algorithmic cascade of PPMM and SIVQ algorithms as previously described by Doyle el al. [1] where PPMM identifies the glands with abnormal lumenal architecture, and this area is then screened by SIVQ to identify the epithelium. Results: The performance of this algorithm cascade was assessed qualitatively (with the use of heatmaps) and quantitatively (with the use of ROC curves) and demonstrates greater performance in the identification of malignant prostatic epithelium. Conclusion: This ability to semi-autonomously paint nearly all the malignant epithelium of prostate cancer has immediate applications to future prostate cancer CAD development as a validated ground truth generator. In addition, such an approach has potential applications as a pre-screening/quality assurance tool.

Keywords: Pathology informatics, whole slide imaging, computer aided diagnosis, SIVQ, PPMM, digital imaging, prostate cancer, cancer

DOI: 10.3233/ACP-2012-0054

Journal: Analytical Cellular Pathology, vol. 35, no. 4, pp. 251-265, 2012