Optimized prostate biopsy via a statistical atlas of cancer spatial distribution

Dinggang Shen; Zhiqiang Lao; Jianchao Zeng; Wei Zhang; Isabel A. Sesterhenn; Leon Sun; Judd W. Moul; Edward H. Herskovits; Gabor Fichtinger; Christos Davatzikos

doi:10.1016/j.media.2003.11.002

Optimized prostate biopsy via a statistical atlas of cancer spatial distribution

Dinggang Shen, Zhiqiang Lao, Jianchao Zeng, Wei Zhang, Isabel A. Sesterhenn, Leon Sun, Judd W. Moul, Edward H. Herskovits, Gabor Fichtinger, Christos Davatzikos

Research output: Contribution to journal › Article › peer-review

67 Citations (Scopus)

Abstract

A methodology is presented for constructing a statistical atlas of spatial distribution of prostate cancer from a large patient cohort, and it is used for optimizing needle biopsy. An adaptive-focus deformable model is used for the spatial normalization and registration of 100 prostate histological samples, which were provided by the Center for Prostate Disease Research of the US Department of Defense, resulting in a statistical atlas of spatial distribution of prostate cancer. Based on this atlas, a statistical predictive model was developed to optimize the needle biopsy sites, by maximizing the probability of detecting cancer. Experimental results using cross-validation show that the proposed method can detect cancer with a 99% success rate using seven needles, in these samples.

Original language	English
Pages (from-to)	139-150
Number of pages	12
Journal	Medical Image Analysis
Volume	8
Issue number	2
DOIs	https://doi.org/10.1016/j.media.2003.11.002
Publication status	Published - 2004 Jun
Externally published	Yes

Keywords

Deformable registration
Image normalization
Image warping
Needle biopsy
Prostate cancer
Statistical atlas

ASJC Scopus subject areas

Radiological and Ultrasound Technology
Radiology Nuclear Medicine and imaging
Computer Vision and Pattern Recognition
Health Informatics
Computer Graphics and Computer-Aided Design

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.media.2003.11.002

Cite this

@article{307f4f11906a4c97a76a78bb67d0b37b,

title = "Optimized prostate biopsy via a statistical atlas of cancer spatial distribution",

abstract = "A methodology is presented for constructing a statistical atlas of spatial distribution of prostate cancer from a large patient cohort, and it is used for optimizing needle biopsy. An adaptive-focus deformable model is used for the spatial normalization and registration of 100 prostate histological samples, which were provided by the Center for Prostate Disease Research of the US Department of Defense, resulting in a statistical atlas of spatial distribution of prostate cancer. Based on this atlas, a statistical predictive model was developed to optimize the needle biopsy sites, by maximizing the probability of detecting cancer. Experimental results using cross-validation show that the proposed method can detect cancer with a 99% success rate using seven needles, in these samples.",

keywords = "Deformable registration, Image normalization, Image warping, Needle biopsy, Prostate cancer, Statistical atlas",

author = "Dinggang Shen and Zhiqiang Lao and Jianchao Zeng and Wei Zhang and Sesterhenn, {Isabel A.} and Leon Sun and Moul, {Judd W.} and Herskovits, {Edward H.} and Gabor Fichtinger and Christos Davatzikos",

note = "Funding Information: This work was supported in part by a grant from the National Science Foundation to the Engineering Research Center for Computer Integrated Surgical Systems and Technology. J. Zeng was supported in part by The Whitaker Foundation. ",

year = "2004",

month = jun,

doi = "10.1016/j.media.2003.11.002",

language = "English",

volume = "8",

pages = "139--150",

journal = "Medical Image Analysis",

issn = "1361-8415",

publisher = "Elsevier",

number = "2",

}

TY - JOUR

T1 - Optimized prostate biopsy via a statistical atlas of cancer spatial distribution

AU - Shen, Dinggang

AU - Lao, Zhiqiang

AU - Zeng, Jianchao

AU - Zhang, Wei

AU - Sesterhenn, Isabel A.

AU - Sun, Leon

AU - Moul, Judd W.

AU - Herskovits, Edward H.

AU - Fichtinger, Gabor

AU - Davatzikos, Christos

N1 - Funding Information: This work was supported in part by a grant from the National Science Foundation to the Engineering Research Center for Computer Integrated Surgical Systems and Technology. J. Zeng was supported in part by The Whitaker Foundation.

PY - 2004/6

Y1 - 2004/6

N2 - A methodology is presented for constructing a statistical atlas of spatial distribution of prostate cancer from a large patient cohort, and it is used for optimizing needle biopsy. An adaptive-focus deformable model is used for the spatial normalization and registration of 100 prostate histological samples, which were provided by the Center for Prostate Disease Research of the US Department of Defense, resulting in a statistical atlas of spatial distribution of prostate cancer. Based on this atlas, a statistical predictive model was developed to optimize the needle biopsy sites, by maximizing the probability of detecting cancer. Experimental results using cross-validation show that the proposed method can detect cancer with a 99% success rate using seven needles, in these samples.

AB - A methodology is presented for constructing a statistical atlas of spatial distribution of prostate cancer from a large patient cohort, and it is used for optimizing needle biopsy. An adaptive-focus deformable model is used for the spatial normalization and registration of 100 prostate histological samples, which were provided by the Center for Prostate Disease Research of the US Department of Defense, resulting in a statistical atlas of spatial distribution of prostate cancer. Based on this atlas, a statistical predictive model was developed to optimize the needle biopsy sites, by maximizing the probability of detecting cancer. Experimental results using cross-validation show that the proposed method can detect cancer with a 99% success rate using seven needles, in these samples.

KW - Deformable registration

KW - Image normalization

KW - Image warping

KW - Needle biopsy

KW - Prostate cancer

KW - Statistical atlas

UR - http://www.scopus.com/inward/record.url?scp=11144356849&partnerID=8YFLogxK

U2 - 10.1016/j.media.2003.11.002

DO - 10.1016/j.media.2003.11.002

M3 - Article

C2 - 15063863

AN - SCOPUS:11144356849

SN - 1361-8415

VL - 8

SP - 139

EP - 150

JO - Medical Image Analysis

JF - Medical Image Analysis

IS - 2

ER -

Optimized prostate biopsy via a statistical atlas of cancer spatial distribution

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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