Integration of Node-RADS and Habitat Radiomics for Predicting Occult Nodal Metastasis in Bladder Cancer.

Journal: Annals of surgical oncology

Study type and population

  • Retrospective, single-center study of 84 patients with bladder cancer who underwent pelvic lymphadenectomy.
  • Objective: assess whether CT-based “tumor habitat” radiomics can better predict occult nodal metastasis (ONM) than conventional whole-tumor radiomics, and whether combining habitat features with clinical factors in a nomogram improves prediction.

Methods

  • Imaging and segmentation: preoperative CT tumor volumes were segmented and then partitioned into sub-regions (“habitats”) using a Fuzzy C-Means clustering algorithm based on Hounsfield unit values.
  • Feature extraction: radiomics features were extracted from:
    • the whole tumor, and
    • each sub-region (habitat).
  • Clinical factors: univariate logistic regression identified clinical factors associated with ONM.
  • Predictive models: multiple models were built:
    • whole-tumor radiomics model,
    • single-habitat models,
    • multi-habitat combined model (notably regions 1, 2, and 3 together).
  • Composite nomogram: constructed by integrating:
    • habitat-based radiomics score (radscore) and
    • selected clinical factors.
  • Model evaluation: performance assessed by AUC in training and validation sets. Clinical utility was evaluated with 1000 bootstrap iterations and decision curve analysis.

Key results

  • Whole-tumor radiomics model:
    • AUC 0.735 (training), 0.727 (validation) – moderate performance.
  • Best single-habitat model (region 3):
    • AUC 0.859 (training), 0.788 (validation).
  • Combined multi-habitat model (regions 1, 2, and 3):
    • AUC 0.920 (training), 0.864 (validation) – highest discrimination among radiomics-only models.
  • Integrated clinical–radiomics nomogram:
    • AUC 0.952 (training), 0.742 (validation).
  • Decision curve analysis: suggested potential clinical benefit for using the nomogram in ONM risk stratification.

Oncologic/clinical implications

  • Habitat-based radiomics: which captures intratumoral heterogeneity rather than treating the tumor as a uniform volume, improves prediction of occult nodal metastasis compared with whole-tumor radiomics alone.
  • Combined nomogram: integrating habitat radscore with clinical factors shows promising discrimination and net benefit, but the drop in validation AUC and retrospective, single-cohort design highlight the need for robust external validation before clinical adoption.

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