Glandular object based tumor morphometry in H&E biopsy samples for prostate cancer prognosis

Stephen I. Fogarasi, Faisal M. Khan, Ho Yuen H. Pang, Ricardo Mesa-Tejada, Michael J. Donovan, Gerardo Fernandez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

Morphological and architectural characteristics of primary prostate tissue compartments, such as epithelial nuclei (EN) and cytoplasm, provide critical information for cancer diagnosis, prognosis and therapeutic response prediction. The subjective and variable Gleason grade assessed by expert pathologists in Hematoxylin and Eosin (H&E) stained specimens has been the standard for prostate cancer diagnosis and prognosis. We propose a novel morphometric, glandular object-oriented image analysis approach for the robust quantification of H&E prostate biopsy images. We demonstrate the utility of features extracted through the proposed method in predicting disease progression post treatment in a multi-institution cohort of 1027 patients. The biopsy based features were univariately predictive for clinical response post therapy; with concordance indexes (CI) ≤ 0.4 or ≥ 0.6. In multivariate analysis, a glandular object feature quantifying tumor epithelial cells not directly associated with an intact tumor gland was selected in a model incorporating preoperative clinical data, protein biomarker and morphological imaging features. The model achieved a CI of 0.73 in validation, which was significantly higher than a CI of 0.69 for the standard multivariate model based solely on clinical features currently used in clinical practice. This work presents one of the first demonstrations of glandular object based morphological features in the H&E stained biopsy specimen to predict disease progression post primary treatment. Additionally, it is the largest scale study of the efficacy and robustness of the proposed features in prostate cancer prognosis.

Original languageEnglish
Title of host publicationMedical Imaging 2011
Subtitle of host publicationComputer-Aided Diagnosis
DOIs
StatePublished - 2011
Externally publishedYes
EventMedical Imaging 2011: Computer-Aided Diagnosis - Lake Buena Vista, FL, United States
Duration: 15 Feb 201117 Feb 2011

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7963
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2011: Computer-Aided Diagnosis
Country/TerritoryUnited States
CityLake Buena Vista, FL
Period15/02/1117/02/11

Keywords

  • Gleason
  • H&E
  • gland classification
  • gland segmentation
  • prognosis
  • prostate biopsy

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