[944] Quantification of Cancer in Prostate Needle Biopsies: AMACR and Digital Image Analysis

V Parimi, LJ Eisengart, XJ Yang. Northwestern University, Chicago, IL

Background: Triple immunohistochemical (IHC) stains have been a valuable aid in accurate identification of prostate carcinoma. However, accurate quantification of minuscule areas of prostate carcinoma in biopsy specimens can often be a clinical challenge. Here we assessed the diagnostic and quantitative use of digital image analysis on triple IHC stained prostate needle biopsies.
Design: Twelveprostate needle biopsy sections composed of 75 needle cores with known amounts of adenocarcinoma were stained with triple-antibody cocktail (P504S + 34βE12 + p63). Slides were digitally scanned with the APERIO digital image analyzer and evaluated with the GENIE pattern and color recognition program algorithm. A slide with known areas of adenocarcinoma, high grade prostatic intraepithelial neoplasia (PIN), benign glands and stroma was used for defining areas of interest was used as a training set for the algorithm program. Sensitivity and specificity for digital recognition was set to 90% and 93%, respectively, due to practical considerations.
Results: Among 75 needle biopsy cores, 19 (25.33%) contained adenocarcinoma by histology and triple stain. Digital image analysis recognized adenocarcinoma in 95% of these needle biopsies. The average area of the needle biopsy was 7.63 sq-mm. Overall; the average area of tumor was 0.196 sq-mm. The smallest area of tumor recognized by the program was 0.0022 sq-mm (0.0363% of the core) and the largest was 0.62 sq-mm (8.17% of the core). False positives resulted from areas of high grade PIN with patchy basal cells. The false negative was caused by uneven AMACR staining in one area of adenocarcinoma. Digital recognition of areas of interest was improved by three successive algorithm trainings.
Conclusions: IHC triple staining is a well known technique used to increase accuracy in the diagnosis of prostate carcinoma. Digital image analysis in concert with IHC provides the opportunity for accurate quantitative analysis of small foci of tumor. Future automated digital scanning and innovative pattern and color recognition technologies may open avenues for classifying a variety of prostate lesions.
Category: Genitourinary (including renal tumors)

Tuesday, March 23, 2010 1:00 PM

Poster Session IV # 113, Tuesday Afternoon

 

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