{
  "abstract": "Nasopharyngeal carcinoma (NPC), a head and neck malignancy, is highly sensitive to radiation. Accordingly, radiotherapy has long been the primary curative modality for patients with non-metastatic NPC. Although intensity-modulated radiotherapy has significantly improved target conformality and normal tissue protection, local recurrence, distant metastasis, and late toxicity remain important issues in long-term management. To achieve a balance between tumor control and normal tissue protection, the continuous integration of multi-source information throughout the treatment workflow is critical. Radiomics has the potential to quantify spatial heterogeneity that may not be fully captured by conventional visual assessment. In this review, radiomics-driven multimodal integration refers to the task-specific combination of imaging-derived phenotypes with complementary clinical variables, Epstein–Barr virus DNA (EBV-DNA), hematological biomarkers, dose distributions, pathological features, molecular data, longitudinal imaging, or treatment-delivery information for defined radiotherapy decisions. This review focuses on the clinical timeline of precision radiotherapy for NPC and provides an overview of radiomics-driven multimodal integration studies. It discusses the current applications and limitations of this framework in pretreatment risk stratification and treatment selection, target volume and organ-at-risk definition during radiotherapy planning, on-treatment monitoring and adaptive radiotherapy, toxicity prediction and normal-tissue protection, and post-treatment recurrence assessment and re-irradiation decision-making. This synthesis of current evidence, clinical barriers, and methodological considerations may inform future validation and implementation of radiomics-driven multimodal integration in NPC precision radiotherapy.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": "Review",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "name": "Yuhan Ma"
    },
    {
      "name": "Yuxin Xie"
    },
    {
      "name": "Qitao Gou"
    },
    {
      "name": "Nianyong Chen"
    },
    {
      "name": "Qiheng Gou"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5djmeah9003ny.bib",
  "cited_by": 0,
  "doi": "10.3389/fonc.2026.1902266",
  "fulltext_url": null,
  "id": "5djmeah9003ny",
  "issns": [
    "2234-943X"
  ],
  "landing_url": "https://www.frontiersin.org/articles/10.3389/fonc.2026.1902266",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "feed-journal",
      "medicine/oncology"
    ]
  ],
  "openalex": null,
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-04",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/5djmeah9003ny.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T12:20:54Z",
      "native_id": "10.3389/fonc.2026.1902266",
      "source": "feed-frontiers",
      "url": "https://www.frontiersin.org/articles/10.3389/fonc.2026.1902266"
    },
    {
      "first_seen": "2026-11-04T12:21:46Z",
      "native_id": "10.3389/fonc.2026.1902266",
      "source": "crossref",
      "url": "https://www.frontiersin.org/articles/10.3389/fonc.2026.1902266/full"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "feed-journal:medicine/oncology",
      "subfield": "oncology"
    }
  ],
  "title": "Radiomics-driven multimodal integration in precision radiotherapy for nasopharyngeal carcinoma— current evidence, clinical barriers, and future directions",
  "title_text": "Radiomics-driven multimodal integration in precision radiotherapy for nasopharyngeal carcinoma— current evidence, clinical barriers, and future directions",
  "type": "peer-reviewed",
  "updated_at": "2026-11-06T00:21:26Z",
  "url": "https://research.draconitic.com/paper/5djmeah9003ny",
  "venue": "Frontiers in Oncology",
  "versions": []
}