Early biomarkers of extracapsular extension of prostate cancer using MRI-derived semantic features

Bibliographic Details
Main Author: Guerra, Adalgisa
Publication Date: 2022
Other Authors: Alves, Filipe Caseiro, Maes, Kris, Joniau, Steven, Cassis, João, Maio, Rui, Cravo, Marília, Mouriño, Helena
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/147232
Summary: Funding This work is supported by a PhD student scholarship (Adalgisa Guerra) it was granted as a scientifc project by Hospital da Luz (ID LH.INV.F2019027). Helena Mouriño was supported by CEAUL (funded by FCT, Portugal, through the project UIDB/00006/2020).
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spelling Early biomarkers of extracapsular extension of prostate cancer using MRI-derived semantic featuresCapsular contactExtracapsular extensionMagnetic resonance imagingProstate cancerRadical prostatectomySematic featuresStagingRadiological and Ultrasound TechnologyOncologyRadiology Nuclear Medicine and imagingSDG 3 - Good Health and Well-beingFunding This work is supported by a PhD student scholarship (Adalgisa Guerra) it was granted as a scientifc project by Hospital da Luz (ID LH.INV.F2019027). Helena Mouriño was supported by CEAUL (funded by FCT, Portugal, through the project UIDB/00006/2020).BACKGROUND: To construct a model based on magnetic resonance imaging (MRI) features and histological and clinical variables for the prediction of pathology-detected extracapsular extension (pECE) in patients with prostate cancer (PCa). METHODS: We performed a prospective 3 T MRI study comparing the clinical and MRI data on pECE obtained from patients treated using robotic-assisted radical prostatectomy (RARP) at our institution. The covariates under consideration were prostate-specific antigen (PSA) levels, the patient's age, prostate volume, and MRI interpretative features for predicting pECE based on the Prostate Imaging-Reporting and Data System (PI-RADS) version 2.0 (v2), as well as tumor capsular contact length (TCCL), length of the index lesion, and prostate biopsy Gleason score (GS). Univariable and multivariable logistic regression models were applied to explore the statistical associations and construct the model. We also recruited an additional set of participants-which included 59 patients from external institutions-to validate the model. RESULTS: The study participants included 184 patients who had undergone RARP at our institution, 26% of whom were pECE+ (i.e., pECE positive). Significant predictors of pECE+ were TCCL, capsular disruption, measurable ECE on MRI, and a GS of ≥7(4 + 3) on a prostate biopsy. The strongest predictor of pECE+ is measurable ECE on MRI, and in its absence, a combination of TCCL and prostate biopsy GS was significantly effective for detecting the patient's risk of being pECE+. Our predictive model showed a satisfactory performance at distinguishing between patients with pECE+ and patients with pECE-, with an area under the ROC curve (AUC) of 0.90 (86.0-95.8%), high sensitivity (86%), and moderate specificity (70%). CONCLUSIONS: Our predictive model, based on consistent MRI features (i.e., measurable ECE and TCCL) and a prostate biopsy GS, has satisfactory performance and sufficiently high sensitivity for predicting pECE+. Hence, the model could be a valuable tool for surgeons planning preoperative nerve sparing, as it would reduce positive surgical margins.NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)RUNGuerra, AdalgisaAlves, Filipe CaseiroMaes, KrisJoniau, StevenCassis, JoãoMaio, RuiCravo, MaríliaMouriño, Helena2023-01-09T22:16:22Z2022-12-232022-12-23T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/147232eng1470-7330PURE: 49448615https://doi.org/10.1186/s40644-022-00509-8info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T18:07:52Zoai:run.unl.pt:10362/147232Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:38:23.976775Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Early biomarkers of extracapsular extension of prostate cancer using MRI-derived semantic features
title Early biomarkers of extracapsular extension of prostate cancer using MRI-derived semantic features
spellingShingle Early biomarkers of extracapsular extension of prostate cancer using MRI-derived semantic features
Guerra, Adalgisa
Capsular contact
Extracapsular extension
Magnetic resonance imaging
Prostate cancer
Radical prostatectomy
Sematic features
Staging
Radiological and Ultrasound Technology
Oncology
Radiology Nuclear Medicine and imaging
SDG 3 - Good Health and Well-being
title_short Early biomarkers of extracapsular extension of prostate cancer using MRI-derived semantic features
title_full Early biomarkers of extracapsular extension of prostate cancer using MRI-derived semantic features
title_fullStr Early biomarkers of extracapsular extension of prostate cancer using MRI-derived semantic features
title_full_unstemmed Early biomarkers of extracapsular extension of prostate cancer using MRI-derived semantic features
title_sort Early biomarkers of extracapsular extension of prostate cancer using MRI-derived semantic features
author Guerra, Adalgisa
author_facet Guerra, Adalgisa
Alves, Filipe Caseiro
Maes, Kris
Joniau, Steven
Cassis, João
Maio, Rui
Cravo, Marília
Mouriño, Helena
author_role author
author2 Alves, Filipe Caseiro
Maes, Kris
Joniau, Steven
Cassis, João
Maio, Rui
Cravo, Marília
Mouriño, Helena
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
RUN
dc.contributor.author.fl_str_mv Guerra, Adalgisa
Alves, Filipe Caseiro
Maes, Kris
Joniau, Steven
Cassis, João
Maio, Rui
Cravo, Marília
Mouriño, Helena
dc.subject.por.fl_str_mv Capsular contact
Extracapsular extension
Magnetic resonance imaging
Prostate cancer
Radical prostatectomy
Sematic features
Staging
Radiological and Ultrasound Technology
Oncology
Radiology Nuclear Medicine and imaging
SDG 3 - Good Health and Well-being
topic Capsular contact
Extracapsular extension
Magnetic resonance imaging
Prostate cancer
Radical prostatectomy
Sematic features
Staging
Radiological and Ultrasound Technology
Oncology
Radiology Nuclear Medicine and imaging
SDG 3 - Good Health and Well-being
description Funding This work is supported by a PhD student scholarship (Adalgisa Guerra) it was granted as a scientifc project by Hospital da Luz (ID LH.INV.F2019027). Helena Mouriño was supported by CEAUL (funded by FCT, Portugal, through the project UIDB/00006/2020).
publishDate 2022
dc.date.none.fl_str_mv 2022-12-23
2022-12-23T00:00:00Z
2023-01-09T22:16:22Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/147232
url http://hdl.handle.net/10362/147232
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1470-7330
PURE: 49448615
https://doi.org/10.1186/s40644-022-00509-8
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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