MRI Habitat Radiomics for Predicting Lymph Node Metastasis in Triple-Negate Breast Cancer

125 patient records from a retrospective study of triple-negative breast cancer patients who underwent preoperative multiparametric MRI. The dataset likely contains radiomics features extracted from whole tumors and intratumoral habitat subregions, used to build predictive models for axillary lymph node metastasis. The data was authored by Bo Xie and uploaded to figshare in May 2026.

Use Cases

• Developing predictive models for lymph node metastasis based on habitat radiomics features.
• Comparing the performance of clinical, conventional radiomics, and habitat radiomics models.
• Applying SHAP analysis for model interpretation to identify key predictors like axillary lymph node length.
• Evaluating model performance using AUC, calibration curves, and decision curve analysis.

Strengths

• Includes data from 125 patients with pathologically confirmed triple-negative breast cancer.
• Features were extracted from both whole tumors and habitat subregions identified via unsupervised clustering.
• Model performance was validated, with the combined model achieving an AUC of 0.81 in the test set.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is 2.5 MB, indicating a relatively small scale.

Provenance

Source

figshare

Collection Method

Retrospective study; tumors were manually segmented from preoperative mpMRI scans.

Freshness

Last updated 2026-05-18 04:17:05; freshness should be verified.