Radiomics-based Prediction Model of Tumor Spread Through Air Space in Lung Adenocarcinoma

Study Overview
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Brief Summary
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Spread through air space (STAS) has been reported as a negative prognostic factor in patients with lung cancer undergone sublobar resection. Its preoperative assessment could thus be useful to customize surgical treatment. Radiomics has been recently proposed to predict STAS in patients with lung adenocarcinoma. However, all the studies have strictly selected both imaging and patients, leading to results hardly applicable to daily clinical practice. The aim of this study is to test a radiomics-based prediction model of STAS in practice-based dataset and verify its validity and translational potentials. Radiological and clinical data from 100 consecutive patients with resected lung adenocarcinoma were retrospectively collected for the training section. As in common clinical practice, preoperative CT images were acquired independently by different physicians and from different hospitals. Therefore, our dataset presents high variance in model and manufacture of scanner, acquisition and reconstruction protocol, endovenous contrast phase and pixel size. To test the effect of normalization in highly varying data, preoperative CT images and tumor region of interest were preprocessed with four different pipelines. Features were extracted using pyradiomics and selected considering both separation power and robustness within pipelines. After that, a radiomics-based prediction model of STAS were created using the most significant associated features. This model were than validated in a group of 50 patients prospectively enrolled as external validation group to test its efficacy in STAS prediction.

Official Title
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Could Radiomics Predict Tumor Spread Through Air Space in Lung Adenocarcinoma in All Computed Tomography Settings?

Conditions
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Lung Adenocarcinoma

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients with suspected or cito-histologically proven lung adenocarcinoma undergoing lung cancer surgery; Available preoperative CT images Age older than 18 years Exclusion Criteria: Chest wall infiltration Induction radio or chemotherapy Incomplete surgical resection

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Lung adenocarcinoma<br>Imaging from patients with surgically treated lung adenocarcinoma were collected and processed for the construction of the radiomics-based prediction model | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Sensitivity | Testing the sensitivity of Radiomics to predict STAS using the area under receiver operating characteristic curve | 24 hour before operation | 
| Specificity | Testing the specificity of Radiomics to predict STAS using the area under receiver operating characteristic curve | 24 hour before operation | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Spread Through Air Space; Radiomics