{
  "abstract": "Background: Pretreatment computed tomography (CT) describes tumor characteristics in patients receiving transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC), but whether measuring more tumors improves mortality predictions in a new cohort remains unclear. We assessed the added value of different lesion-selection scopes beyond shared clinical predictors. Methods: We compared a model using five clinical variables with models adding CT measurements from the largest, two largest, or all retained annotated tumors. All models used the same regularized discrete-time survival estimator. Evaluation used repeated nested cross-validation in 228 WAW-TACE patients and frozen external application in 69 HCC-TACE-Seg patients, with 15 deaths by day 365. We assessed first-year probability error, discrimination, and calibration, followed by local recalibration using small external samples. Results: Internally, adding CT-derived lesion features did not establish an improvement in prediction accuracy. Externally, the all-lesion model had the highest discrimination point estimates, but its advantage over the clinical-only model was uncertain. Its mortality probabilities were less accurate than those of the clinical-only model, with calibration estimates consistent with overly extreme predicted risks. Local recalibration reduced its median held-out prediction error at day 365, but the median adjusted error remained higher than that of the adjusted clinical model. Simple tumor-burden predictors also did not improve external probability accuracy over the clinical baseline. Conclusions: In these cohorts, measurements from more annotated tumors did not yield more reliable first-year mortality probabilities. Comparisons of clinical-imaging models should evaluate external probability accuracy and calibration alongside patient ranking.",
  "abstract_shown": true,
  "affiliations": [
    "University of Texas at Austin"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "name": "Z. Xu"
    },
    {
      "name": "A. Melek"
    },
    {
      "name": "E. Castillo"
    },
    {
      "affs": [
        0
      ],
      "name": "H. Wang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/33cesbryd99q4.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.28.26366759",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.10.28.26366759v1.full",
  "id": "33cesbryd99q4",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.10.28.26366759v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "radiology and imaging"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.10.28.26366759v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-28",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/33cesbryd99q4.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:22:07Z",
      "native_id": "10.64898/2026.10.28.26366759",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.10.28.26366759v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:radiology and imaging",
      "subfield": "imaging"
    }
  ],
  "title": "Lesion selection and external evaluation of clinical-imaging survival models after transarterial chemoembolization for hepatocellular carcinoma",
  "title_text": "Lesion selection and external evaluation of clinical-imaging survival models after transarterial chemoembolization for hepatocellular carcinoma",
  "type": "preprint",
  "updated_at": "2026-10-31T00:20:43Z",
  "url": "https://research.draconitic.com/paper/33cesbryd99q4",
  "venue": "medRxiv",
  "versions": []
}