Less qualitative multiparametric magnetic resonance imaging in prostate cancer can underestimate extraprostatic extension in higher grade tumors

被引:0
作者
Schmit, Stephen [1 ,2 ]
Allu, Sai [1 ]
Tanzer, Joshua Ray [1 ]
Ortiz, Rebecca [1 ]
Pareek, Gyan [1 ]
Hyams, Elias [1 ]
机构
[1] Brown Univ, Minimally Invas Urol Inst, Div Urol, Warren Alpert Med Sch,Miriam Hosp, Providence, RI USA
[2] Brown Univ, Warren Alpert Med Sch, 222 Richmond St, Providence, RI 02903 USA
来源
INTERNATIONAL BRAZ J UROL | 2024年 / 50卷 / 01期
关键词
Prostatic Neoplasms; Multiparametric Magnetic Resonance Imaging; Prostatectomy; FUSION; RISK;
D O I
10.1590/S1677-5538.IBJU.2023.032
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Background: Multiparametric magnetic resonance imaging (mpMRI) is increasingly used for risk stratification and preoperative staging of prostate cancer. It remains unclear how Grade Group (GG) interacts with the ability of mpMRI to determine the presence of extraprostatic extension (EPE) on surgical pathology. Methods: A retrospective review of a robotic assisted laparoscopic radical prostatectomy (RALP) database from 2016-2020 was performed. Radiology mpMRI reports by multiple attending radiologists and without clear standardization or quality control were retrospectively assessed for EPE findings and compared with surgical pathology reports. The data were stratified by biopsy -based GG and a multivariable cluster analysis was performed to incorporate additional preoperative variables (age at diagnosis, PSA, etc.). Hazard ratios were calculated to determine how mpMRI findings and radiographic EPE relate to positive surgical margins. Results: Two hundred and eighty nine patients underwent at least one mpMRI prior to RALP. Preoperative mpMRI demonstrated sensitivity of 39.3% and specificity of 88.8% for pathological EPE and had a negative predictive value (NPV) of 49.5%, and positive predictive value (PPV) of 84.0%. Stratification of NPV by GG yielded the following values: GG 1-5 (49.5%), GG 3-5 (40.8%), GG 4-5 (43.4%), and GG 5 (30.4%). Additionally, positive EPE on preoperative mpMRI was associated with a significantly decreased risk of positive surgical margins (RR: 0.655; 95% CI: 0.557-0.771). Conclusions: NPV of prostate mpMRI for EPE may be decreased for higher grade tumors. A detailed reference reading and image quality optimization may improve performance. However, urologists should exercise caution in nerve sparing approaches in these patients.
引用
收藏
页码:37 / 45
页数:9
相关论文
共 22 条
  • [1] Impact of preoperative prostate magnetic resonance imaging on the surgical management of high-risk prostate cancer
    Baack Kukreja, Janet
    Bathala, Tharakeswara K.
    Reichard, Chad A.
    Troncoso, Patricia
    Delacroix, Scott
    Davies, Benjamin
    Eggener, Scott
    Smaldone, Marc
    Minhaj Siddiqui, Mohummad
    Tollefson, Matthew
    Chapin, Brian F.
    [J]. PROSTATE CANCER AND PROSTATIC DISEASES, 2020, 23 (01) : 172 - 178
  • [2] MRI grading for the prediction of prostate cancer aggressiveness
    Boschheidgen, M.
    Schimmoeller, L.
    Arsov, C.
    Ziayee, F.
    Morawitz, J.
    Valentin, B.
    Radke, K. L.
    Giessing, M.
    Esposito, I
    Albers, P.
    Antoch, G.
    Ullrich, T.
    [J]. EUROPEAN RADIOLOGY, 2022, 32 (04) : 2351 - 2359
  • [3] Brown H., 1999, Applied mixed models in medicine
  • [4] MRI-based nomograms and radiomics in presurgical prediction of extraprostatic extension in prostate cancer: a systematic review
    Calimano-Ramirez, Luis F. F.
    Virarkar, Mayur K. K.
    Hernandez, Mauricio
    Ozdemir, Savas
    Kumar, Sindhu
    Gopireddy, Dheeraj R. R.
    Lall, Chandana
    Balaji, K. C.
    Mete, Mutlu
    Gumus, Kazim Z. Z.
    [J]. ABDOMINAL RADIOLOGY, 2023, 48 (07) : 2379 - 2400
  • [5] Preoperative Risk-Stratification of High-Risk Prostate Cancer: A Multicenter Analysis
    Chys, Brecht
    Devos, Gaetan
    Everaerts, Wouter
    Albersen, Maarten
    Moris, Lisa
    Claessens, Frank
    De Meerleer, Gert
    Haustermans, Karin
    Briganti, Alberto
    Chlosta, Piotr
    Gontero, Paolo
    Graefen, Markus
    Gratzke, Christian
    Karnes, R. Jeffrey
    Kneitz, Burkhard
    Marchioro, Giansilvio
    Salas, Rafael Sanchez
    Spahn, Martin
    Tombal, Bertrand
    Van Der Poel, Henk
    Walz, Jochen
    Van Poppel, Hendrik
    Joniau, Steven
    [J]. FRONTIERS IN ONCOLOGY, 2020, 10
  • [6] MR Imaging-Transrectal US Fusion for Targeted Prostate Biopsies: Implications for Diagnosis and Clinical Management
    Costa, Daniel N.
    Pedrosa, Ivan
    Donato, Francisco, Jr.
    Roehrborn, Claus G.
    Rofsky, Neil M.
    [J]. RADIOGRAPHICS, 2015, 35 (03) : 696 - 708
  • [7] The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma Definition of Grading Patterns and Proposal for a New Grading System
    Epstein, Jonathan I.
    Egevad, Lars
    Amin, Mahul B.
    Delahunt, Brett
    Srigley, John R.
    Humphrey, Peter A.
    [J]. AMERICAN JOURNAL OF SURGICAL PATHOLOGY, 2016, 40 (02) : 244 - 252
  • [8] kamila: Clustering Mixed-Type Data in R and Hadoop
    Foss, Alexander H.
    Markatou, Marianthi
    [J]. JOURNAL OF STATISTICAL SOFTWARE, 2018, 83 (13): : 1 - 44
  • [9] Prostate Imaging Quality (PI-QUAL): A New Quality Control Scoring System for Multiparametric Magnetic Resonance Imaging of the Prostate from the PRECISION trial
    Giganti, Francesco
    Allen, Clare
    Emberton, Mark
    Moore, Caroline M.
    Kasivisvanathan, Veeru
    [J]. EUROPEAN UROLOGY ONCOLOGY, 2020, 3 (05): : 615 - 619
  • [10] Gilberto GM, 2023, INT BRAZ J UROL, V49, P334, DOI [10.1590/S1677-5538.IBJU.2023.0054, 10.1590/s1677-5538.ibju.2023.0054]