The Sensitivity and Specificity of Multiparametric Magnetic Resonance Imaging and Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography for Predicting Seminal Vesicle Invasion in Clinically Significant Prostate Cancer: A Multicenter Retrospective Study
The presence of seminal vesicle invasion (SVI) in prostate cancer (PCa) is associated with poorer postoperative outcomes. This study evaluates the predictive value of magnetic resonance imaging (MRI) and prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT...
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| Veröffentlicht in: | Journal of clinical medicine 2024-08, Vol.13 (15), p.4424 |
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| creator | Sitharthan, Darshan Kang, Song Treacy, Patrick-Julien Bird, Jacob Alexander, Kate Karunaratne, Sascha Leslie, Scott Chan, Lewis Steffens, Daniel Thanigasalam, Ruban |
| description | The presence of seminal vesicle invasion (SVI) in prostate cancer (PCa) is associated with poorer postoperative outcomes. This study evaluates the predictive value of magnetic resonance imaging (MRI) and prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) for SVI in PCa.
This cohort study included consecutive robotic prostatectomy patients for PCa at three Australian tertiary referral centres between April 2016 and September 2022. MRI and PSMA PET/CT results, clinicopathological variables, including age, BMI, prostate-specific antigen (PSA), PSA density, DRE, Biopsy Gleason score, Positive biopsy cores, PIRADS v2.1 score, MRI volume and MRI lesion size were extracted. The sensitivity, specificity, and accuracy of MRI and PSMA PET/CT for predicting SVI were compared with the histopathological results by receiver operating characteristic (ROC) analysis. Subgroup univariate and multivariate analysis was performed.
Of the 528 patients identified, 86 had SVI on final pathology. MRI had a low sensitivity of 0.162 (95% CI: 0.088-0.261) and a high specificity of 0.963 (95% CI: 0.940-0.979). The PSMA PET/CT had a low sensitivity of 0.439 (95% CI: 0.294-0591) and a high specificity of 0.933 (95% CI: 0.849-0.969). When MRI and PSMA PET/CT were used in combination, the sensitivity and specificity improved to 0.514 (95%CI: 0.356-0.670) and 0.880 (95% CI: 0.813-0.931). The multivariate regression showed a higher biopsy Gleason score (
= 0.033), higher PSA (
< 0.001), older age (
= 0.001), and right base lesions (
= 0.003) to be predictors of SVI.
MRI and PSMA PET/CT independently underpredicted SVI. The sensitivity and AUC improved when they were used in combination. Multiple clinicopathological factors were associated with SVI on multivariate regression and predictive models incorporating this information may improve oncological outcomes. |
| doi_str_mv | 10.3390/jcm13154424 |
| format | Article |
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This cohort study included consecutive robotic prostatectomy patients for PCa at three Australian tertiary referral centres between April 2016 and September 2022. MRI and PSMA PET/CT results, clinicopathological variables, including age, BMI, prostate-specific antigen (PSA), PSA density, DRE, Biopsy Gleason score, Positive biopsy cores, PIRADS v2.1 score, MRI volume and MRI lesion size were extracted. The sensitivity, specificity, and accuracy of MRI and PSMA PET/CT for predicting SVI were compared with the histopathological results by receiver operating characteristic (ROC) analysis. Subgroup univariate and multivariate analysis was performed.
Of the 528 patients identified, 86 had SVI on final pathology. MRI had a low sensitivity of 0.162 (95% CI: 0.088-0.261) and a high specificity of 0.963 (95% CI: 0.940-0.979). The PSMA PET/CT had a low sensitivity of 0.439 (95% CI: 0.294-0591) and a high specificity of 0.933 (95% CI: 0.849-0.969). When MRI and PSMA PET/CT were used in combination, the sensitivity and specificity improved to 0.514 (95%CI: 0.356-0.670) and 0.880 (95% CI: 0.813-0.931). The multivariate regression showed a higher biopsy Gleason score (
= 0.033), higher PSA (
< 0.001), older age (
= 0.001), and right base lesions (
= 0.003) to be predictors of SVI.
MRI and PSMA PET/CT independently underpredicted SVI. The sensitivity and AUC improved when they were used in combination. Multiple clinicopathological factors were associated with SVI on multivariate regression and predictive models incorporating this information may improve oncological outcomes.</description><identifier>ISSN: 2077-0383</identifier><identifier>EISSN: 2077-0383</identifier><identifier>DOI: 10.3390/jcm13154424</identifier><identifier>PMID: 39124692</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Accuracy ; Antigens ; Biopsy ; Cancer ; Cancer therapies ; Clinical outcomes ; CT imaging ; Development and progression ; Diagnosis ; Electronic health records ; Health aspects ; Histopathology ; Magnetic resonance imaging ; Medical prognosis ; Medical records ; Medical research ; Medicine, Experimental ; Metastasis ; Oncology, Experimental ; Pathology ; Patients ; PET imaging ; Physiological aspects ; Prostate cancer ; Seminal vesicles ; Testing ; Tomography ; Tumor antigens</subject><ispartof>Journal of clinical medicine, 2024-08, Vol.13 (15), p.4424</ispartof><rights>COPYRIGHT 2024 MDPI AG</rights><rights>2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c309t-6f07f5a980e313f8eacf6f83453dee2e14ce9487dd906584de4e179f2070987e3</cites><orcidid>0000-0001-9848-969X ; 0000-0002-7163-097X ; 0000-0001-7518-0307 ; 0000-0002-9715-860X ; 0000-0001-6631-1117 ; 0009-0000-5786-1387</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39124692$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sitharthan, Darshan</creatorcontrib><creatorcontrib>Kang, Song</creatorcontrib><creatorcontrib>Treacy, Patrick-Julien</creatorcontrib><creatorcontrib>Bird, Jacob</creatorcontrib><creatorcontrib>Alexander, Kate</creatorcontrib><creatorcontrib>Karunaratne, Sascha</creatorcontrib><creatorcontrib>Leslie, Scott</creatorcontrib><creatorcontrib>Chan, Lewis</creatorcontrib><creatorcontrib>Steffens, Daniel</creatorcontrib><creatorcontrib>Thanigasalam, Ruban</creatorcontrib><title>The Sensitivity and Specificity of Multiparametric Magnetic Resonance Imaging and Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography for Predicting Seminal Vesicle Invasion in Clinically Significant Prostate Cancer: A Multicenter Retrospective Study</title><title>Journal of clinical medicine</title><addtitle>J Clin Med</addtitle><description>The presence of seminal vesicle invasion (SVI) in prostate cancer (PCa) is associated with poorer postoperative outcomes. This study evaluates the predictive value of magnetic resonance imaging (MRI) and prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) for SVI in PCa.
This cohort study included consecutive robotic prostatectomy patients for PCa at three Australian tertiary referral centres between April 2016 and September 2022. MRI and PSMA PET/CT results, clinicopathological variables, including age, BMI, prostate-specific antigen (PSA), PSA density, DRE, Biopsy Gleason score, Positive biopsy cores, PIRADS v2.1 score, MRI volume and MRI lesion size were extracted. The sensitivity, specificity, and accuracy of MRI and PSMA PET/CT for predicting SVI were compared with the histopathological results by receiver operating characteristic (ROC) analysis. Subgroup univariate and multivariate analysis was performed.
Of the 528 patients identified, 86 had SVI on final pathology. MRI had a low sensitivity of 0.162 (95% CI: 0.088-0.261) and a high specificity of 0.963 (95% CI: 0.940-0.979). The PSMA PET/CT had a low sensitivity of 0.439 (95% CI: 0.294-0591) and a high specificity of 0.933 (95% CI: 0.849-0.969). When MRI and PSMA PET/CT were used in combination, the sensitivity and specificity improved to 0.514 (95%CI: 0.356-0.670) and 0.880 (95% CI: 0.813-0.931). The multivariate regression showed a higher biopsy Gleason score (
= 0.033), higher PSA (
< 0.001), older age (
= 0.001), and right base lesions (
= 0.003) to be predictors of SVI.
MRI and PSMA PET/CT independently underpredicted SVI. The sensitivity and AUC improved when they were used in combination. Multiple clinicopathological factors were associated with SVI on multivariate regression and predictive models incorporating this information may improve oncological outcomes.</description><subject>Accuracy</subject><subject>Antigens</subject><subject>Biopsy</subject><subject>Cancer</subject><subject>Cancer therapies</subject><subject>Clinical outcomes</subject><subject>CT imaging</subject><subject>Development and progression</subject><subject>Diagnosis</subject><subject>Electronic health records</subject><subject>Health aspects</subject><subject>Histopathology</subject><subject>Magnetic resonance imaging</subject><subject>Medical prognosis</subject><subject>Medical records</subject><subject>Medical research</subject><subject>Medicine, Experimental</subject><subject>Metastasis</subject><subject>Oncology, Experimental</subject><subject>Pathology</subject><subject>Patients</subject><subject>PET imaging</subject><subject>Physiological aspects</subject><subject>Prostate cancer</subject><subject>Seminal vesicles</subject><subject>Testing</subject><subject>Tomography</subject><subject>Tumor antigens</subject><issn>2077-0383</issn><issn>2077-0383</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNptUsFu1DAQDQhEq9ITNw7IEhcktK0dOxuH22pVoFJXVOzCNXKdceoqsYPtVNq_Z7LblgVhHzy23rx58zxZ9obRM84ren6ne8ZZIUQunmfHOS3LGeWSvziIj7LTGO8oLilFzspX2RGvWC7mVX787O3mFsgaXLTJ3tu0Jco1ZD2Atsbq6e4NWY1dsoMKqocUrCYr1TpIGHyH6J1yGshlr1rr2l32dfAxqQSzRxqygv4mKAdk4ZJtwZFrj_WCd-SitzFaDDa-921Qw-32fOn7YUzQHLwR4wPyQmN1msqsobdOdeQnRKs7LO_u1Y7GOrLsrLNadd2WrG3rJgHKpSdVZDkJDp_IYt-XBpcgYCuoJ6JgtAENSWOzfZ29NKqLcPpwnmQ_Pl9sll9nV9--XC4XVzPNaZVmc0NLU6hKUuCMGwlKm7mRXBS8AciBCQ2VkGXTVHReSNGAAFZWBv-HVrIEfpJ92PMOwf8aIaYaTdHQdeiYH2ONVVgui3nOEPr-H-idHwM6sUPRKi85lX9Qreqgts74FJSeSOuFpKJgrCpLRJ39B4W7QXO1d2Asvv-V8HGfoNGpGMDUQ7C9Ctua0XoaxvpgGBH97kHqeNND84R9HD3-G-q43wI</recordid><startdate>20240801</startdate><enddate>20240801</enddate><creator>Sitharthan, Darshan</creator><creator>Kang, Song</creator><creator>Treacy, Patrick-Julien</creator><creator>Bird, Jacob</creator><creator>Alexander, Kate</creator><creator>Karunaratne, Sascha</creator><creator>Leslie, Scott</creator><creator>Chan, Lewis</creator><creator>Steffens, Daniel</creator><creator>Thanigasalam, Ruban</creator><general>MDPI AG</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-9848-969X</orcidid><orcidid>https://orcid.org/0000-0002-7163-097X</orcidid><orcidid>https://orcid.org/0000-0001-7518-0307</orcidid><orcidid>https://orcid.org/0000-0002-9715-860X</orcidid><orcidid>https://orcid.org/0000-0001-6631-1117</orcidid><orcidid>https://orcid.org/0009-0000-5786-1387</orcidid></search><sort><creationdate>20240801</creationdate><title>The Sensitivity and Specificity of Multiparametric Magnetic Resonance Imaging and Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography for Predicting Seminal Vesicle Invasion in Clinically Significant Prostate Cancer: A Multicenter Retrospective Study</title><author>Sitharthan, Darshan ; 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This study evaluates the predictive value of magnetic resonance imaging (MRI) and prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) for SVI in PCa.
This cohort study included consecutive robotic prostatectomy patients for PCa at three Australian tertiary referral centres between April 2016 and September 2022. MRI and PSMA PET/CT results, clinicopathological variables, including age, BMI, prostate-specific antigen (PSA), PSA density, DRE, Biopsy Gleason score, Positive biopsy cores, PIRADS v2.1 score, MRI volume and MRI lesion size were extracted. The sensitivity, specificity, and accuracy of MRI and PSMA PET/CT for predicting SVI were compared with the histopathological results by receiver operating characteristic (ROC) analysis. Subgroup univariate and multivariate analysis was performed.
Of the 528 patients identified, 86 had SVI on final pathology. MRI had a low sensitivity of 0.162 (95% CI: 0.088-0.261) and a high specificity of 0.963 (95% CI: 0.940-0.979). The PSMA PET/CT had a low sensitivity of 0.439 (95% CI: 0.294-0591) and a high specificity of 0.933 (95% CI: 0.849-0.969). When MRI and PSMA PET/CT were used in combination, the sensitivity and specificity improved to 0.514 (95%CI: 0.356-0.670) and 0.880 (95% CI: 0.813-0.931). The multivariate regression showed a higher biopsy Gleason score (
= 0.033), higher PSA (
< 0.001), older age (
= 0.001), and right base lesions (
= 0.003) to be predictors of SVI.
MRI and PSMA PET/CT independently underpredicted SVI. The sensitivity and AUC improved when they were used in combination. Multiple clinicopathological factors were associated with SVI on multivariate regression and predictive models incorporating this information may improve oncological outcomes.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>39124692</pmid><doi>10.3390/jcm13154424</doi><orcidid>https://orcid.org/0000-0001-9848-969X</orcidid><orcidid>https://orcid.org/0000-0002-7163-097X</orcidid><orcidid>https://orcid.org/0000-0001-7518-0307</orcidid><orcidid>https://orcid.org/0000-0002-9715-860X</orcidid><orcidid>https://orcid.org/0000-0001-6631-1117</orcidid><orcidid>https://orcid.org/0009-0000-5786-1387</orcidid><oa>free_for_read</oa></addata></record> |
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| source | PubMed Central Open Access; MDPI - Multidisciplinary Digital Publishing Institute; EZB-FREE-00999 freely available EZB journals; PubMed Central |
| subjects | Accuracy Antigens Biopsy Cancer Cancer therapies Clinical outcomes CT imaging Development and progression Diagnosis Electronic health records Health aspects Histopathology Magnetic resonance imaging Medical prognosis Medical records Medical research Medicine, Experimental Metastasis Oncology, Experimental Pathology Patients PET imaging Physiological aspects Prostate cancer Seminal vesicles Testing Tomography Tumor antigens |
| title | The Sensitivity and Specificity of Multiparametric Magnetic Resonance Imaging and Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography for Predicting Seminal Vesicle Invasion in Clinically Significant Prostate Cancer: A Multicenter Retrospective Study |
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