Healthc Inform Res.  2011 Mar;17(1):51-57. 10.4258/hir.2011.17.1.51.

Statistical 3D Distribution Analysis of Prostate Cancers in Korean Using Digital Processing Techniques

• Pak PJ
• Shin DI
• Cho YM
• Joo SK
• Huh SJ

• KMID: 2166595
• DOI: http://doi.org/10.4258/hir.2011.17.1.51

Abstract

OBJECTIVES
Several researchers have shown that three dimensional (3D) distribution analysis of prostate cancer is helpful when initiating needle biopsy procedures. Knowledge regarding the distribution of prostate cancer could enhance understanding of the pathophysiology involved and improve detection of these malignancies. We propose utilizing digital processing techniques to analyze prostate cancer distribution in a 3D setting.
METHODS
Pre-made radical prostatectomy sample slices were digitized with a resolution of 76 dpi. Slices of each sample were aligned and registered by deformation algorithm and interpolated for analysis of relative distribution statistics. We analyzed 80 samples saved in electronic medical record and compared the detection rate of preoperative needle biopsies and radical prostatectomies using our 3D analysis technique.
RESULTS
The statistical 3D distribution of prostate cancer was evaluated using a 36-sector process. Results were represented in the following two ways: distribution of a single patient, and statistical distribution of prostate cancers of multiple patients. The overall concordance rate was 62.7% between the two methods; therefore a technique is needed which can raise this percentage.
CONCLUSIONS
We suggest using the normalization method to develop a software tool which permits reconstruction of the 3D distribution of prostate cancer from 2D legacy images and reduces the loss of image quality as well. This application will facilitate detection of prostate cancer by aiding in the determination of the most effective clinical position via partial sampling with decreased patient inconvenience.

Keyword

Prostatic Neoplasms; 3D Distribution; Digital Processing; Statistical Analysis

MeSH Terms

Biopsy, Needle
Electronic Health Records
Humans
Prostate
Prostatectomy
Prostatic Neoplasms
Software

Figure

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  Figure 1 The overall processing diagram of the 3D distribution analysis of prostate cancer.

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  Figure 2 Template made from textbook and deformation procedure.

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  Figure 3 Normalization of samples which have different specimen sizes. Sample (A) has less slices for normal. So the thickness is increased to 21 pixels for each slice. (C) Sample has more slices for normal. So the thickness is reduced to 7 pixels for each slice.

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  Figure 4 Definition of 3-dimensional distribution sections.

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  Figure 5 Deformation results.

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  Figure 6 Three-dimensional distribution of prostate cancer using single sample analysis.

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  Figure 7 Three-dimensional distribution of prostate cancer using multi-sample analysis.

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