guest ::
| Home > Publications database > Diagnostic accuracy of multiparametric MRI for detecting unconventional prostate cancer histology: a systematic review and meta-analysis. > print |
| Home > Publications database > Diagnostic accuracy of multiparametric MRI for detecting unconventional prostate cancer histology: a systematic review and meta-analysis. > print |
| 001 | 300739 | ||
| 005 | 20251218151529.0 | ||
| 024 | 7 | _ | |a pmid:40307530 |2 pmid |
| 024 | 7 | _ | |a 0938-7994 |2 ISSN |
| 024 | 7 | _ | |a 1432-1084 |2 ISSN |
| 024 | 7 | _ | |a 1613-3749 |2 ISSN |
| 024 | 7 | _ | |a 1613-3757 |2 ISSN |
| 024 | 7 | _ | |a (ISSN |2 ISSN |
| 024 | 7 | _ | |a DES |2 ISSN |
| 024 | 7 | _ | |a SUPPLEMENTS) |2 ISSN |
| 024 | 7 | _ | |a 10.1007/s00330-025-11603-3 |2 doi |
| 024 | 7 | _ | |a altmetric:177040985 |2 altmetric |
| 037 | _ | _ | |a DKFZ-2025-00899 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Carletti, Filippo |b 0 |
| 245 | _ | _ | |a Diagnostic accuracy of multiparametric MRI for detecting unconventional prostate cancer histology: a systematic review and meta-analysis. |
| 260 | _ | _ | |a Heidelberg |c 2026 |b Springer |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1766067265_2624437 |2 PUB:(DE-HGF) |x Review Article |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 500 | _ | _ | |a 2026 Jan;36(1):17-29 / Epub 2025 Apr 30 |
| 520 | _ | _ | |a Accurate detection of unconventional histologies (UH) in prostate cancer (PCa) is crucial for treatment planning and prognosis. This systematic review and meta-analysis aimed to evaluate the accuracy of multiparametric magnetic resonance imaging (mpMRI) in detecting UH on prostatectomy, particularly cribriform architecture (CA) and intraductal carcinoma (IDC-P), in patients with localized PCa.A literature search was conducted in major databases for studies published after 2000. Seventeen articles fulfilled the inclusion criteria and were eligible for qualitative analysis. Five studies met the inclusion criteria for meta-analysis.The pooled sensitivity and specificity of mpMRI (Prostate Imaging Reporting and Data System (PI-RADS) cutoff 3) to detect cribriform architecture were 0.91 and 0.29. The proportion of cribriform lesions increased with higher PI-RADS scores (23.2% for PI-RADS 1-2 to 66.7% for PI-RADS 5). For intraductal carcinoma (IDC-P), two studies found that IDC-P lesions were visible on mpMRI and had lower apparent diffusion coefficient (ADC) values compared to acinar prostate cancer. Four studies evaluating combined CA/IDC-P found sensitivities ranging from 33 to 100%. Lower ADC values were associated with CA/IDC-P in some studies, but not in others. Overall, mpMRI demonstrated promising sensitivity but moderate specificity in detecting these aggressive histological variants, with continued challenges in accurate sampling and characterization of mpMRI.mpMRI shows high sensitivity but moderate specificity in detecting cribriform architecture in PCa, especially for high PI-RADS scores. These findings support the use of mpMRI for UH detection, but caution is advised in clinical interpretation. Larger prospective studies are needed to validate these results before routine clinical application. We studied how effective MRI is at identifying different UH of PCa, such as cribriform architecture and intraductal carcinoma. MRI is accurate at detecting these cancers when they are present, but it also produces a significant number of false positives. More research is needed to standardize imaging protocols and histological definition and ensure an accurate diagnosis.Question The accurate detection of unconventional histologies in prostate cancer, particularly cribriform architecture and intraductal carcinoma, is challenging but crucial for treatment planning and prognosis. Findings mpMRI shows high sensitivity (91%) but low specificity (29%) for detecting cribriform architecture, with detection rates increasing proportionally with higher PI-RADS scores. Clinical relevance mpMRI can effectively detect aggressive unconventional histologies in prostate cancer, though its moderate specificity suggests the need for careful interpretation. This aids in risk stratification and treatment planning, potentially improving patient outcomes. |
| 536 | _ | _ | |a 899 - ohne Topic (POF4-899) |0 G:(DE-HGF)POF4-899 |c POF4-899 |f POF IV |x 0 |
| 588 | _ | _ | |a Dataset connected to DataCite, PubMed, , Journals: inrepo02.dkfz.de |
| 700 | 1 | _ | |a Maggi, Martina |b 1 |
| 700 | 1 | _ | |a Fazekas, Tamas |b 2 |
| 700 | 1 | _ | |a Rajwa, Pawel |b 3 |
| 700 | 1 | _ | |a Nicoletti, Rossella |b 4 |
| 700 | 1 | _ | |a Olivier, Jonathan |b 5 |
| 700 | 1 | _ | |a Preisser, Felix |b 6 |
| 700 | 1 | _ | |a Soeterik, Timo F W |b 7 |
| 700 | 1 | _ | |a Giganti, Francesco |b 8 |
| 700 | 1 | _ | |a Martini, Alberto |b 9 |
| 700 | 1 | _ | |a Heidegger, Isabel |b 10 |
| 700 | 1 | _ | |a Kasivisvanathan, Veeru |b 11 |
| 700 | 1 | _ | |a Pradère, Benjamin |b 12 |
| 700 | 1 | _ | |a Ploussard, Guillaume |b 13 |
| 700 | 1 | _ | |a Hadaschik, Boris |0 P:(DE-HGF)0 |b 14 |
| 700 | 1 | _ | |a Moro, Fabrizio Dal |b 15 |
| 700 | 1 | _ | |a van den Bergh, Roderick C N |b 16 |
| 700 | 1 | _ | |a Marra, Giancarlo |b 17 |
| 700 | 1 | _ | |a Gandaglia, Giorgio |b 18 |
| 700 | 1 | _ | |a Zattoni, Fabio |0 0000-0002-4178-373X |b 19 |
| 700 | 1 | _ | |a Kesch, Claudia |0 P:(DE-HGF)0 |b 20 |
| 700 | 1 | _ | |a Party, EAU-YAU Prostate Cancer Working |b 21 |e Collaboration Author |
| 773 | _ | _ | |a 10.1007/s00330-025-11603-3 |0 PERI:(DE-600)1472718-3 |n 1 |p 17-29 |t European radiology |v 36 |y 2026 |x 0938-7994 |
| 909 | C | O | |p VDB |o oai:inrepo02.dkfz.de:300739 |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 14 |6 P:(DE-HGF)0 |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 20 |6 P:(DE-HGF)0 |
| 913 | 1 | _ | |a DE-HGF |b Programmungebundene Forschung |l ohne Programm |1 G:(DE-HGF)POF4-890 |0 G:(DE-HGF)POF4-899 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-800 |4 G:(DE-HGF)POF |v ohne Topic |x 0 |
| 914 | 1 | _ | |y 2025 |
| 915 | _ | _ | |a DEAL Springer |0 StatID:(DE-HGF)3002 |2 StatID |d 2024-12-28 |w ger |
| 915 | _ | _ | |a DEAL Springer |0 StatID:(DE-HGF)3002 |2 StatID |d 2024-12-28 |w ger |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2024-12-28 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2024-12-28 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2024-12-28 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2024-12-28 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1110 |2 StatID |b Current Contents - Clinical Medicine |d 2024-12-28 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2024-12-28 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2024-12-28 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b EUR RADIOL : 2022 |d 2024-12-28 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2024-12-28 |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2024-12-28 |
| 915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b EUR RADIOL : 2022 |d 2024-12-28 |
| 920 | 1 | _ | |0 I:(DE-He78)ED01-20160331 |k ED01 |l DKTK Koordinierungsstelle Essen/Düsseldorf |x 0 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-He78)ED01-20160331 |
| 980 | _ | _ | |a UNRESTRICTED |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|