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

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 detecti...

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Autores principales: Pak, Pil June, Shin, Dong Ik, Cho, Young Mi, Joo, Se Kyeong, Huh, Soo Jin
Formato: Texto
Lenguaje:English
Publicado: Korean Society of Medical Informatics 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3092994/
https://www.ncbi.nlm.nih.gov/pubmed/21818457
http://dx.doi.org/10.4258/hir.2011.17.1.51
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author Pak, Pil June
Shin, Dong Ik
Cho, Young Mi
Joo, Se Kyeong
Huh, Soo Jin
author_facet Pak, Pil June
Shin, Dong Ik
Cho, Young Mi
Joo, Se Kyeong
Huh, Soo Jin
author_sort Pak, Pil June
collection PubMed
description 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.
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spelling pubmed-30929942011-07-13 Statistical 3D Distribution Analysis of Prostate Cancers in Korean Using Digital Processing Techniques Pak, Pil June Shin, Dong Ik Cho, Young Mi Joo, Se Kyeong Huh, Soo Jin Healthc Inform Res Original Article 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. Korean Society of Medical Informatics 2011-03 2011-03-31 /pmc/articles/PMC3092994/ /pubmed/21818457 http://dx.doi.org/10.4258/hir.2011.17.1.51 Text en © 2011 The Korean Society of Medical Informatics http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Pak, Pil June
Shin, Dong Ik
Cho, Young Mi
Joo, Se Kyeong
Huh, Soo Jin
Statistical 3D Distribution Analysis of Prostate Cancers in Korean Using Digital Processing Techniques
title Statistical 3D Distribution Analysis of Prostate Cancers in Korean Using Digital Processing Techniques
title_full Statistical 3D Distribution Analysis of Prostate Cancers in Korean Using Digital Processing Techniques
title_fullStr Statistical 3D Distribution Analysis of Prostate Cancers in Korean Using Digital Processing Techniques
title_full_unstemmed Statistical 3D Distribution Analysis of Prostate Cancers in Korean Using Digital Processing Techniques
title_short Statistical 3D Distribution Analysis of Prostate Cancers in Korean Using Digital Processing Techniques
title_sort statistical 3d distribution analysis of prostate cancers in korean using digital processing techniques
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3092994/
https://www.ncbi.nlm.nih.gov/pubmed/21818457
http://dx.doi.org/10.4258/hir.2011.17.1.51
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