{
  "abstract": "Multiparametric magnetic resonance imaging (mpMRI) is increasingly recognized as an important diagnostic modality in the evaluation of prostate cancer. This analysis sought to investigate whether simple, ratio-normalized quantitative magnetic resonance imaging (MRI) biomarkers obtained from routine mpMRI of the prostate provide incremental diagnostic value beyond the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) for the detection of clinically significant prostate cancer (csPCa). In this retrospective single-center study, 129 men underwent pre-biopsy 3-Tesla mpMRI followed by MRI/ultrasound fusion-guided biopsy. Quantitative first-order imaging features representing the three principal imaging domains underlying PI-RADS were derived from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging and normalized to intra-patient reference tissue. The analyses were performed on a lesion-specific basis and stratified by anatomical zone. Zone-specific logistic regression models were constructed to assess the incremental diagnostic value of quantitative biomarkers beyond PI-RADS v2.1. In the peripheral zone (PZ; 99 lesions), PI-RADS alone exhibited moderate discrimination for csPCa [area under the curve (AUC) =0.723]. An integrative model combining PI-RADS with prostate-specific antigen density (PSAD) and quantitative MRI-derived ratios from DWI, T2WI, and DCE significantly improved discrimination [AUC =0.901, 95% confidence interval (CI): 0.839-0.964]. After bootstrap-based optimism correction, the AUC decreased to 0.879. In the transition zone (TZ; 30 lesions), univariable analyses revealed no consistent differences in quantitative parameters between clinically significant and non-clinically significant lesions. PI-RADS alone yielded an AUC of 0.670, while ratio-based quantitative parameters did not provide meaningful incremental diagnostic value beyond PI-RADS v2.1. Simple, ratio-normalized quantitative MRI parameters integrated with PI-RADS and PSAD showed potential incremental value for detecting csPCa in the PZ. Conversely, these parameters demonstrated no statistically significant incremental diagnostic value beyond PI-RADS in the TZ in this limited cohort. These findings support a zone-aware, pragmatic approach to the quantitative augmentation of PI-RADS using routinely available MRI metrics.",
  "abstract_shown": true,
  "affiliations": [
    "Institute for Radiology, Caritas Hospital St. Josef, Regensburg, Germany.",
    "Department of Urology, Caritas Hospital St. Josef, University of Regensburg, Regensburg, Germany.",
    "Institute for Radiology, University Hospital Regensburg, Regensburg, Germany.",
    "Institute for Pathology, University of Regensburg, Regensburg, Germany."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 12,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Christoph Niessen"
    },
    {
      "affs": [
        1
      ],
      "name": "Maximilian Haas"
    },
    {
      "affs": [
        1
      ],
      "name": "Maximilian Burger"
    },
    {
      "affs": [
        1
      ],
      "name": "Simon Udo Engelmann"
    },
    {
      "affs": [
        1
      ],
      "name": "Christoph Eckl"
    },
    {
      "affs": [
        1
      ],
      "name": "Elena Vogel"
    },
    {
      "affs": [
        1
      ],
      "name": "Marco Julius Schnabel"
    },
    {
      "affs": [
        2
      ],
      "name": "Christian Stroszczynski"
    },
    {
      "affs": [
        3
      ],
      "name": "Florian Weber"
    },
    {
      "affs": [
        1
      ],
      "name": "Sarah Lena Haas"
    },
    {
      "affs": [
        1
      ],
      "name": "Roman Mayr"
    },
    {
      "affs": [
        1
      ],
      "name": "Christoph Pickl"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8qgsp6jqhk8r1.bib",
  "cited_by": 0,
  "doi": "10.21037/qims-2026-1006",
  "fulltext_url": "https://europepmc.org/articles/PMC13743309",
  "id": "8qgsp6jqhk8r1",
  "issns": [
    "2223-4292",
    "2223-4306"
  ],
  "landing_url": "https://europepmc.org/article/MED/42997770",
  "language": "eng",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2741|Radiomics and Machine Learning in Medical Imaging"
    ]
  ],
  "openalex": "W7223204256",
  "pdf_url": "https://europepmc.org/articles/PMC13743309?pdf=render",
  "pmcid": "PMC13743309",
  "pmid": "42997770",
  "published": "2026-10-16",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/8qgsp6jqhk8r1.ris",
  "sources": [
    {
      "first_seen": "2026-11-09T15:20:41Z",
      "native_id": "MED:42997770",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42997770"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2741|Radiomics and Machine Learning in Medical Imaging",
      "subfield": "imaging"
    }
  ],
  "title": "Radiomics-augmented lesion characterization on prostate multiparametric magnetic resonance imaging: first-order features and ratio metrics may improve diagnostic performance in prostate cancer.",
  "title_text": "Radiomics-augmented lesion characterization on prostate multiparametric magnetic resonance imaging: first-order features and ratio metrics may improve diagnostic performance in prostate cancer.",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T15:20:41Z",
  "url": "https://research.draconitic.com/paper/8qgsp6jqhk8r1",
  "venue": "Quantitative imaging in medicine and surgery",
  "versions": []
}