{
  "abstract": "Purpose\n\nThis study aims to assess the computed tomography (CT) features of transcription factor E3 gene fusion renal cell carcinoma (TFE3-RCC) and develop a radiomics-based model for preoperative discrimination between TFE3-RCCs and clear cell renal cell carcinomas (ccRCCs).Methods\n\nA total of 34 pathologically confirmed TFE3-RCC and 98 ccRCC cases with preoperative renal CT were enrolled. Subjective image analysis was performed to determine the CT parameters that can distinguish TFE3-RCCs from ccRCCs. A random forest classifier was evaluated through 5-fold cross-validation to establish the radiomics model. Diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis.Results\n\nPatients with TFE3-RCC were significantly younger (36.2 ± 14.4 vs. 56.8 ± 13.5 years, P < 0.001). Ten of the 34 TFE3-RCCs had calcification, whereas only four in the ccRCC group did (29.4% vs. 4.1%, P < 0.001). Additionally, the TOC enhancement ratio in the corticomedullary phase were significantly lower in the TFE3-RCC group compared with the ccRCC group (0.61 ± 0.11 vs. 0.90 ± 0.13, p < 0.001). The random forest classifier achieved stable performance with robust cross-validation metrics (AUC = 0.82 ± 0.17, accuracy = 85% ± 13%).Conclusion\n\nThe CT radiomics model exhibits favorable diagnostic performance for noninvasively differentiating TFE3-RCC from ccRCC, supporting its potential utility in preoperative personalized management of renal masses.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Radiology, Peking University First Hospital, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China.",
    "Beijing Smart Tree Medical Technology Co., Ltd, 24, Huangsi Avenue, Xicheng District, Beijing, 100035, China.",
    "Department of Urology, Peking University First Hospital, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China.",
    "Institute of Urology, Beijing Key Laboratory of Urogenital Diseases (Male) Molecular Diagnosis and Treatment Center, Peking University, National Urological Cancer Center, No. 8 Xishiku Street., Xicheng District, Beijing, 100034, China.",
    "Department of Radiology, Peking University First Hospital, No. 8 Xishiku Street, Xicheng District, Beijing, 100034, China. cjr.wangxiaoying@vip.163.com."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Yi Liu"
    },
    {
      "affs": [
        0
      ],
      "name": "Kexin Wang"
    },
    {
      "affs": [
        1
      ],
      "name": "Yaofeng Zhang"
    },
    {
      "affs": [
        1
      ],
      "name": "Jiangtao Liu"
    },
    {
      "affs": [
        1
      ],
      "name": "Zuqiang Xi"
    },
    {
      "affs": [
        1
      ],
      "name": "Xiangpeng Wang"
    },
    {
      "affs": [
        2,
        3
      ],
      "name": "Yanfei Yu"
    },
    {
      "affs": [
        4
      ],
      "name": "Xiaoying Wang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9yfjwhwwjp9ct.bib",
  "cited_by": 0,
  "doi": "10.1186/s12885-026-16463-8",
  "fulltext_url": "https://europepmc.org/articles/PMC13678919",
  "id": "9yfjwhwwjp9ct",
  "issns": [
    "1471-2407"
  ],
  "landing_url": "https://europepmc.org/article/MED/42894154",
  "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": [
    [
      "lcc",
      "RC254-282"
    ],
    [
      "openalex",
      "2741|Radiomics and Machine Learning in Medical Imaging"
    ]
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  "openalex": "W7170095416",
  "pdf_url": "https://europepmc.org/articles/PMC13678919?pdf=render",
  "pmcid": "PMC13678919",
  "pmid": "42894154",
  "published": "2026-07-01",
  "publisher": "BMC",
  "ris": "https://research.draconitic.com/paper/9yfjwhwwjp9ct.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:42Z",
      "native_id": "MED:42894154",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42894154"
    },
    {
      "first_seen": "2026-10-30T13:46:06Z",
      "native_id": "d42e6d00be9740aab06023987b826aec",
      "source": "doaj",
      "url": "https://doi.org/10.1186/s12885-026-16463-8"
    }
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  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2741|Radiomics and Machine Learning in Medical Imaging",
      "subfield": "imaging"
    }
  ],
  "title": "Differentiating Xp11.2/TFE3 translocation renal cell carcinoma from clear cell carcinoma: performance of a radiomics model.",
  "title_text": "Differentiating Xp11.2/TFE3 translocation renal cell carcinoma from clear cell carcinoma: performance of a radiomics model.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:46:06Z",
  "url": "https://research.draconitic.com/paper/9yfjwhwwjp9ct",
  "venue": "BMC cancer",
  "versions": []
}