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The device quantifies dynamic stiffness of the palpable prostate surface and was tested in vivo on 12 men scheduled for radical prostatectomy. Patients with asymmetric disease were selected to provide variation across the palpation surface. Measurements use oscillating pressure on a flexible probe and track probe displacement to derive dynamic stiffness and incidentally static stiffness. Tissue was then histologically labeled per palpation point as cancerous or not, enabling modulus and dynamic property estimation and ANN classification.",{"@graph":69,"@context":114},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/mechanical-mapping-of-the-prostate-in-vivo-using-dynamic-instrumented-palpation-towards-an-in-vivo-strategy-for-cancer-assessment/377938/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/mechanical-mapping-of-the-prostate-in-vivo-using-dynamic-instrumented-palpation-towards-an-in-vivo-strategy-for-cancer-assessment/377938.png","ImageObject",300,407,{"name":92,"@type":93},"Mia  ","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-26","2026-09-24",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108],{"name":109,"@type":110,"acceptedAnswer":111},"What classification performance did the study report using an Artificial Neural Network?","Question",{"text":112,"@type":113},"Using limited generated features, an ANN achieved sensitivity of 97%, negative predictive value of 86%, positive predictive value of 67%, and accuracy of 70%, with relatively poor specificity (30%).","Answer","https://schema.org",{"og:url":83,"og:type":116,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":118,"canonical":83},"index,follow",{"doc_id":120,"site_id":62},377938,1790493058,{"code":4,"msg":5,"data":123},{"doc_id":120,"user_id":124,"nickname":92,"user_avatar":125,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":126,"file_id":127,"file_url":128,"file_type":129,"file_size":130,"view_count":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":131,"language":132,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":133,"faqs":134,"seo_title":135,"seo_description":67,"update_tm":136,"read_time":137},687207024478,"https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd","Original Article  \nMechanical mapping of the prostate in vivo using Dynamic Instrumented Palpation; towards an in vivo strategy for cancer assessment  \nRobert L Reuben 1, Steven J Hammer 1, Olufemi Johnson 1, Daniel W Good2,3, Javier Palacio-Torralba 1, Antonio Candito 1, Yuhang Chen 1, Simon Phipps2,3, Will Shu 1 and S Alan McNeill2,3  \nGraphical abstract  \nProc IMechE Part H: J Engineering in Medicine 2023, Vol. 237(5) 571–584 􀀂 IMechE 2023  \nArticle reuse guidelines: [sagepub.com/journals-permissions](sagepub.com/journals-permissions)[ ](sagepub.com/journals-permissions)[DOI: 10.1177/09544119231154305](DOI: 10.1177/09544119231154305)[ ](DOI: 10.1177/09544119231154305)[journals.sagepub.com/home/pih](journals.sagepub.com/home/pih)  \nAbstract  \nA calibrated palpation sensor has been developed for making instrumented Digital Rectal Examinations (iDREs) with a view to assessing patients for prostate cancer. The instrument measures the dynamic stiffness of the palpable surface of the prostate, and has been trialled on 12 patients in vivo. The patients had been diagnosed with prostate cancer and were scheduled for radical prostatectomy. As far as possible, patients with asymmetric disease were chosen so as to give a variation in gland condition over the palpable surface. The device works by applying an oscillating pressure (force) to a flexible probe whose displacement into the tissue is also measured in order to yield a dynamic stiffness, the static stiffness being incidentally measured at the mean oscillatory force. The device was deployed mounted on the  \n1 Institute for Mechanical, Process and Energy Engineering, School of Engineering and Physical Sciences, Heriot Watt University, Edinburgh, UK 2Department of Urology, Western General Hospital, Edinburgh, UK  \n3Edinburgh Urological Cancer Group, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK  \nCorresponding author:  \nRobert L Reuben, Institute for Mechanical, Process and Energy Engineering, School of Engineering and Physical Sciences, Heriot Watt University, Nasmyth Building, Edinburgh EH14 4AS, UK.  \nEmail: [r.reuben@hw.ac.uk](r.reuben@hw.ac.uk)  \nindex finger of a urologist and measurements taken at 12–16 positions on each patient using light and firm pressure and palpation frequencies of 1 or 5Hz. In parallel, conventional DRE assessments were made by a consultant urologist for cancer. After in vivo measurement, the glands were removed and examined histologically with each palpation point being classified as cancerous (C) or not (NC). The work has established the first measurements of static modulus of living prostate tissue to be: 26.8 (13.3) kPa for tissue affected by prostate cancer (C classification), and 24.8kPa (11.9) for tissue unaffected by cancer (NC classification), values quoted as median (interquartile range). The dynamic properties were characterised by: dynamic modulus, 5.15kPa (4.86) for the C classification and 4.61kPa (3.08) for the NC classification and the time lag between force and displacement at 5Hz palpation frequency, 0.0175s (0.0078) for the C classification and 0.0186s (0.0397) for the NC classification, values again quoted as median (interquartile range). With the limited set of features that could be generated, an Artificial Neural Network (ANN) classification yielded a sensitivity of 97%, negative predictive value of 86%, positive predictive value of 67% and accuracy of 70% but with relatively poor specificity (30%). Besides extending the feature set, there are a number of changes in probe design, probing strategy and in mechanics analysis, which are expected to improve the diagnostic capabilities of the method.  \nKeywords  \nProstate cancer diagnosis, dynamic stiffness, relaxation time, elastic modulus, in vivo  \nDate received: 13 February 2019; accepted: 10 January 2023  \nBackground  \nCurrently, a blood test (for prostate specific antigen, PSA) and/or examination of the prostate by digital rectal examination","cbCaipFzz1q8m7Iu","https://ap.wps.com/l/cbCaipFzz1q8m7Iu","pdf",2462125,14,"English","# Abstract\n# Background\n## Current diagnostic workflow\n## Need to distinguish indolent vs aggressive disease\n## Mechanical assessment and elastography","[{\"question\":\"What classification performance did the study report using an Artificial Neural Network?\",\"answer\":\"Using limited generated features, an ANN achieved sensitivity of 97%, negative predictive value of 86%, positive predictive value of 67%, and accuracy of 70%, with relatively poor specificity (30%).\"}]","Mechanical mapping of the prostate in vivo using Dynamic Instrumented Palpation - towards an in vivo strategy for cancer assessment | PDF",1790227726,35]