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dc.contributor.authorKepner, Gordon R.
dc.contributor.authorKepner, Jeremy
dc.date.accessioned2012-03-14T15:24:44Z
dc.date.available2012-03-14T15:24:44Z
dc.date.issued2010-06
dc.date.submitted2009-12
dc.identifier.issn1742-4682
dc.identifier.urihttp://hdl.handle.net/1721.1/69651
dc.description.abstractBackground Analyze an approach to distributing transperineal prostate biopsy cores that yields data on the volume of a tumor that might be present when the biopsy is negative, and also increases detection efficiency. Methods Basic principles of sampling and probability theory are employed to analyze a transperineal biopsy pattern that uses evenly-spaced parallel cores in order to extract quantitative data on the volume of a small spherical tumor that could potentially be present, even though the biopsy did not detect it, i.e., negative biopsy. Results This approach to distributing biopsy cores provides data for the upper limit on the volume of a small, spherical tumor that might be present, and the probability of smaller volumes, when biopsies are negative and provides a quantitative basis for evaluating the effectiveness of different core spacing distances. Conclusions Distributing transperineal biopsy cores so they are evenly spaced provides a means to calculate the probability that a tumor of given volume could be present when the biopsy is negative, and can improve detection efficiency.en_US
dc.language.isoen_US
dc.publisherBioMed Central Ltd.en_US
dc.relation.isversionofhttp://dx.doi.org/10.1186/1742-4682-7-23en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en_US
dc.sourceBioMed Centralen_US
dc.titleTransperineal prostate biopsy: analysis of a uniform core sampling pattern that yields data on tumor volume limits in negative biopsiesen_US
dc.typeArticleen_US
dc.identifier.citationKepner, Gordon R., and Jeremy V. Kepner. “Transperineal Prostate Biopsy: Analysis of a Uniform Core Sampling Pattern That Yields Data on Tumor Volume Limits in Negative Biopsies.” Theoretical Biology and Medical Modelling 7.23 (2010): 1-13.en_US
dc.contributor.departmentLincoln Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.approverKepner, Jeremy
dc.contributor.mitauthorKepner, Jeremy
dc.relation.journalTheoretical Biology and Medical Modellingen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsKepner, Gordon R; Kepner, Jeremy Ven
mit.licensePUBLISHER_CCen_US


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