Prediction of Metastasis in Small Pulmonary Oligonodules Detected in Breast Cancer Patients at Baseline CT
Huei‐Yi Tsai, Min‐Fang Chao, Tzu‐Hsueh Tsai, Shen‐Liang Shih, Fang‐Ming Chen, Ming‐Feng Hou, Ming‐Yii Huang, Jui‐Sheng Hsu

TL;DR
This study identifies factors that help predict if small lung nodules in breast cancer patients are metastases.
Contribution
The study provides new risk stratification criteria for metastasis prediction in small pulmonary nodules in breast cancer patients.
Findings
Nodules ≥ 6 mm, lymphadenopathy, advanced clinical stages, and triple-negative subtype are independent predictors of metastasis.
Nodule size ≥ 6 mm has a positive likelihood ratio of 3.74 for metastasis prediction.
Features like shape, margin, and location of nodules are not associated with metastasis.
Abstract
It is challenging for radiologists to diagnose pulmonary metastases when they encounter only a few (n ≤ 5) small pulmonary nodules (< 10 mm) on staging CT in breast cancer patients. We conducted this study to assess clinical and imaging features related to metastasis for better risk stratification. Retrospective analysis of 249 pulmonary nodules present at the baseline CTs of 194 patients diagnosed with breast cancer between 2014 and 2021 was performed. The evaluated features included nodular characteristics, perifissural nodules, associated imaging findings, clinical stage, and breast cancer subtype. Nodules with interval change were determined to be metastases. A large proportion of the patients had single nodule (78.9%) presence, and most of the nodules were less than 6 mm (86.3%). Among the 249 nodules, 63 (25.3%) nodules were in metastases. The independent predictors were nodule ≥…
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Taxonomy
TopicsLung Cancer Diagnosis and Treatment · Medical Imaging and Pathology Studies · Medical Imaging Techniques and Applications
