{
  "abstract": "Objective: To evaluate the real-world diagnostic performance of PI-RADS for detecting clinically significant prostate cancer (csPCa) across large-scale worldwide cohorts.\n\nMaterials and methods: This multicenter observational study included 20,429 patients from nine Chinese institutions and a published worldwide meta-analysis dataset comprising 13,330 patients for comparison. All PI-RADS assessments were extracted from original MRI reports produced by clinical radiologists as part of standard diagnostic workflows. Summary receiver operating characteristic curves were constructed using a bivariate random-effects model, and center-level areas under the curve (AUCs) were pooled via random-effects meta-analysis. Subgroup analyses were conducted.\n\nResults: PI-RADS exhibited overall discriminatory performance for csPCa across nine Chinese cohorts comparable to the META results from 70 studies, though significant inter-center variation was observed. Using a PI-RADS ≥ 3 threshold, pooled sensitivity was 92.6% and specificity was 51.5%. At a PI-RADS ≥ 4 threshold, pooled specificity improved to 78.1%, with a sensitivity of 81.5%. The overall diagnostic performance was consistent across thresholds: The summary ROC (SROC) AUC was 0.903 for PI-RADS ≥ 3 and 0.826 for PI-RADS ≥ 4 in detecting csPCa at the meta-analysis level. Subgroup analyses indicated better performance among older patients (≥ 70 years) and those with higher PSA levels (> 20 ng/mL). PI-RADS v2.1 outperformed v2 or earlier versions in most clinical scenarios.\n\nConclusions: This large-scale real-world study provides critical multicenter evidence supporting the use of PI-RADS in clinical practice worldwide, while also revealing substantial variability in scoring and diagnostic performance across institutions. The findings offer an evidence-based overview of PI-RADS implementation in China and worldwide, highlighting both its utility and inconsistencies.\n\nKey Points: Question What are the real-world PI-RADS diagnostic performance benchmarks for clinically significant prostate cancer detection across diverse Chinese multicenter institutions versus global data?\n\nFindings PI-RADS demonstrated good overall performance (SROC AUC 0.903 at a threshold of ≥ 3), with superior discriminatory ability in older patients, higher PSA levels, and v2.1 users.\n\nCritical relevance statement This article critically assesses substantial inter-institutional heterogeneity in PI-RADS performance, highlighting that pooled estimates should not replace local calibration and that regionally adapted implementation strategies are essential for advancing clinical radiology practice.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 14,
  "authors": [
    {
      "name": "Jie Bao"
    },
    {
      "name": "Mulin Su"
    },
    {
      "name": "Huijuan Tu"
    },
    {
      "name": "Litao Zhao"
    },
    {
      "name": "Yanting Ji"
    },
    {
      "name": "Pengfei Jin"
    },
    {
      "name": "Libiao Ji"
    },
    {
      "name": "Yueting Su"
    },
    {
      "name": "Hailin Shen"
    },
    {
      "name": "Ximing Wang"
    },
    {
      "name": "Xiaoying Wang"
    },
    {
      "name": "Zhen Li"
    },
    {
      "name": "Chunhong Hu"
    },
    {
      "name": "Yudong Zhang",
      "orcid": "0000-0002-2811-7513"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/545qj3g9ttgch.bib",
  "cited_by": 0,
  "doi": "10.1186/s13244-026-02460-9",
  "fulltext_url": "https://doi.org/10.1186/s13244-026-02460-9",
  "id": "545qj3g9ttgch",
  "issns": [
    "1869-4101"
  ],
  "landing_url": "https://link.springer.com/article/10.1186/s13244-026-02460-9",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Original Article"
    ],
    [
      "lcc",
      "R895-920"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://link.springer.com/content/pdf/10.1186/s13244-026-02460-9.pdf",
  "pmcid": "PMC13737363",
  "pmid": "42980945",
  "published": "2026-11-04",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/545qj3g9ttgch.ris",
  "sources": [
    {
      "first_seen": "2026-11-05T00:21:14Z",
      "native_id": "10.1186/s13244-026-02460-9",
      "source": "crossref",
      "url": "https://link.springer.com/article/10.1186/s13244-026-02460-9"
    },
    {
      "first_seen": "2026-11-08T14:20:59Z",
      "native_id": "0a005fd034304c328b502a00f785209e",
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      "url": "https://doi.org/10.1186/s13244-026-02460-9"
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    {
      "first_seen": "2026-11-09T12:22:34Z",
      "native_id": "PMC13737363",
      "source": "pmc",
      "url": "https://doi.org/10.1186/s13244-026-02460-9"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "issn:1869-4101",
      "subfield": "imaging"
    }
  ],
  "title": "Diagnostic performance benchmarks of MRI for prostate cancer: a large-scale cohort study of 33,759 patients",
  "title_text": "Diagnostic performance benchmarks of MRI for prostate cancer: a large-scale cohort study of 33,759 patients",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T14:21:18Z",
  "url": "https://research.draconitic.com/paper/545qj3g9ttgch",
  "venue": "Insights into Imaging",
  "versions": []
}