{
  "abstract": "ObjectivesTo determine how clinically anchored MRI representations behave from supportive internal testing through locked institutional transfer and limited target-site adaptation for prediction of substantial lymphovascular space invasion (LVSI) in endometrial cancer.\n\nMaterials and MethodsThis retrospective two-center study included 206 women undergoing preoperative 3-T MRI between March 2016 and March 2023. Hospital A provided training (n = 117) and supportive internal testing (n = 13); Hospital B provided strict external testing (n = 76; 12 positive). Age and CA125 formed the clinical baseline and were included in every imaging model. In 200 repeated stratified two-fold Hospital B splits, each patient was evaluated outside the adaptation half. Models remained locked; adaptation changed only the threshold or applied no-empirical-Bayes (no-EB) ComBat before threshold selection.\n\nResultsDenseNet121, U-NEXtractor, and fusion U-NEXtractor achieved internal AUC 1.000 but strict external AUCs of 0.685, 0.671, and 0.669, respectively. At development-locked thresholds, sensitivities were 0.167, 0.583, and 0.417. Threshold adaptation increased median sensitivity to 0.833 for all three, with specificities of 0.625, 0.500, and 0.500. No-EB ComBat changed median AUC by -0.007, -0.007, and -0.014, respectively, versus strict transfer. U-NEXtractor prediction ranking was most stable (median Spearman {rho}, 0.999), whereas fusion did not improve transportability. Empirical-Bayes ComBat lacked complete repeated-split coverage.\n\nConclusionStrong internal performance did not establish transportability. Limited target-site threshold adaptation recovered operating sensitivity without improving discrimination; feature harmonization produced no consistent AUC gain and affected representations differently.",
  "abstract_shown": true,
  "affiliations": [
    "McGill University"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "D. A. Di Giovanni"
    },
    {
      "name": "A. Takada"
    },
    {
      "name": "T. Horikoshi"
    },
    {
      "name": "T. Tsuboyama"
    },
    {
      "name": "H. Yokota"
    },
    {
      "name": "R. Zakarian"
    },
    {
      "name": "Y. Matsumoto"
    },
    {
      "name": "M. Vallieres"
    },
    {
      "name": "C. Reinhold"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dkxade2g5r0dp.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.07.14.26358100",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.07.14.26358100v2.full",
  "id": "dkxade2g5r0dp",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.07.14.26358100v2",
  "language": null,
  "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": [
    [
      "medrxiv",
      "radiology and imaging"
    ],
    [
      "openalex",
      "2729|Endometrial and Cervical Cancer Treatments"
    ]
  ],
  "openalex": "W7169000524",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.07.14.26358100v2.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-07-14",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/dkxade2g5r0dp.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:44Z",
      "native_id": "10.64898/2026.07.14.26358100",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.07.14.26358100v2"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:radiology and imaging",
      "subfield": "imaging"
    }
  ],
  "title": "Limited-site adaptation reveals representation-specific MRI transportability for lymphovascular invasion in endometrial cancer",
  "title_text": "Limited-site adaptation reveals representation-specific MRI transportability for lymphovascular invasion in endometrial cancer",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:44Z",
  "url": "https://research.draconitic.com/paper/dkxade2g5r0dp",
  "venue": "medRxiv",
  "versions": []
}