{
  "abstract": "Current prostate cancer (PCa) assessment uses clinical findings, prostate-specific antigen (PSA), and multiparametric magnetic resonance imaging (mp-MRI), while transrectal ultrasound (TRUS) mainly provides real-time biopsy guidance. We developed zone-specific TRUS radiomics models for patient-level and planned needle-level PCa prediction. This retrospective single-center study included 247 biopsy-naive men undergoing freehand transperineal 10-core systematic biopsy from August 2023 to April 2024. Each patient contributed two transition zone (TZ) cores and eight peripheral zone (PZ) cores. A blinded sonographer delineated whole-zone and pre-firing needle-target regions of interest (ROIs), visually matched to post-firing images acquired seconds later. From each ROI, 513 radiomic features were extracted, sparsely selected, and classified with a two-layer RNN. Models were evaluated using an 80:20 split. A patient or core was positive when pathology showed Gleason score (GS) ≥6. The cohort included 116 patients with PCa and 131 with benign findings; 545 of 2,470 cores were positive. Without PSA, the combined TZ + PZ patient-level model had the highest patient-level area under the receiver operating characteristic curve (AUC) (0.828), whereas needle-level AUCs were 0.699, 0.698, and 0.680 for TZ, PZ, and TZ + PZ models. With PSA, the combined patient-level model reached an AUC of 0.876, and the needle-level TZ + PSA model reached 0.826. The findings support further investigation of zone-specific TRUS radiomics, particularly for patient-level prediction. Needle-level results are exploratory and do not establish real-time biopsy guidance. External validation, confidence intervals, comparator models, prospective registration, and patient-grouped evaluation are required before clinical use.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Ultrasound, Huashan Hospital, Fudan University, Shanghai, China.",
    "Department of Urology, Huashan Hospital, Fudan University, Shanghai, China.",
    "Department of Electronic Engineering, College of Biomedical Engineering, Fudan University, Shanghai, China."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Jizhao Chen"
    },
    {
      "affs": [
        1
      ],
      "name": "Guanxiong Ding"
    },
    {
      "affs": [
        2
      ],
      "name": "Guoqing Wu"
    },
    {
      "affs": [
        0
      ],
      "name": "Weibin Zhang",
      "orcid": "0000-0003-3999-4260"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/62nxg15yt5dmn.bib",
  "cited_by": 0,
  "doi": "10.21037/tau-2026-0354",
  "fulltext_url": "https://europepmc.org/articles/PMC13741066",
  "id": "62nxg15yt5dmn",
  "issns": [
    "2223-4691"
  ],
  "landing_url": "https://europepmc.org/article/MED/42997186",
  "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": "W7223787984",
  "pdf_url": "https://europepmc.org/articles/PMC13741066?pdf=render",
  "pmcid": "PMC13741066",
  "pmid": "42997186",
  "published": "2026-09-29",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/62nxg15yt5dmn.ris",
  "sources": [
    {
      "first_seen": "2026-11-09T15:20:41Z",
      "native_id": "MED:42997186",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42997186"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2741|Radiomics and Machine Learning in Medical Imaging",
      "subfield": "imaging"
    }
  ],
  "title": "Development and internal validation of transrectal ultrasound radiomics models for patient- and needle-level prostate cancer prediction in biopsy-naive men.",
  "title_text": "Development and internal validation of transrectal ultrasound radiomics models for patient- and needle-level prostate cancer prediction in biopsy-naive men.",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T15:20:41Z",
  "url": "https://research.draconitic.com/paper/62nxg15yt5dmn",
  "venue": "Translational andrology and urology",
  "versions": []
}