The evaluation of prostate cancer histology following hormonal therapy often represents a diagnostic problem for the pathologist. Previous studies have shown that an inference or Bayesian belief network (BBN) offers a descriptive classifier useful for the accurate analysis of morphological changes i
Investigating FTIR based histopathology for the diagnosis of prostate cancer
β Scribed by Matthew J. Baker; Ehsan Gazi; Michael D. Brown; Jonathan H. Shanks; Noel W. Clarke; Peter Gardner
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 497 KB
- Volume
- 2
- Category
- Article
- ISSN
- 1864-063X
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β¦ Synopsis
Abstract
Prostate cancer is the most common gender specific cancer. The current gold standard for diagnosis, histopathology, is subjective and limited by variation between different pathologists. The diagnostic problems associated with the correct grading and staging of prostate cancer (CaP) has led to an interest in the development of spectroscopic based diagnostic techniques. FTIR microspectroscopy used in combination with a Principal Component Discriminant Function Analysis (PCβDFA) was applied to investigate FTIR based histopathology for the diagnosis of CaP. In this paper we report the results of a large patient study in which FTIR has been proven to grade CaP tissue specimens to a high degree of sensitivity and specificity. (Β© 2009 WILEYβVCH Verlag GmbH & Co. KGaA, Weinheim)
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