a multifactorial model combining radiomics with frozen section analysis is a potential biomarker for assessing Spread Through Air Space during surgery, which can provide decision-making support to therapeutic planning for early-stage lung adenocarcinomas.
Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma and is also a risk factor for recurrence and worse prognosis of lung adenocarcinoma. Its preoperative assessment could thus be useful to customize surgical treatment. Radiomics and frozen section haave been recently proposed to predict STAS in patients with lung adenocarcinoma. Radiomics-based Prediction Model is highly sensitive but not specific for STAS detection. While, frozen section is highly specific but not sensitive for STAS detection in early lung adenocarcinomas. Therefore, the proposed project aims to develop and validate a multifactorial model combining radiomics with frozen section analysis to assesse Spread Through Air Space during surgery, which can provide decision-making support to therapeutic planning for early-stage lung adenocarcinomas.
Study Type
OBSERVATIONAL
Enrollment
900
The high-throughput extraction of large amounts of quantitative image features from medical images
Sensitivity
Testing the sensitivity of Radiomics to predict STAS using the area under receiver operating characteristic curve
Time frame: 24 hour before operation
Specificity
Testing the specificity of Radiomics to predict STAS using the area under receiver operating characteristic curve
Time frame: 24 hour before operation
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