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Introduction: Early lung cancer screening (LCS) through low-dose CT (LDCT) is crucial but underused due to various barriers, including incomplete or inaccurate patient smoking data in the electronic health record and limited time for shared decision-making. The objective of this trial is to investigate a patient-centred intervention, MyLungHealth, delivered through the patient portal. The intervention is designed to improve LCS rates through increased identification of eligible patients and informed decision-making.

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Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radiation exposure and the need for specialized personnel. This study aims to develop an artificial intelligence (AI) method to automatically detect CAC from non-gated, freely-breathing, low-dose CT images obtained from positron emission tomography/computed tomography scans.

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Lung Cancer Screening With Low-Dose CT: A Systematic Review.

Cureus

December 2024

Family Health Unit New Directions, Unidade Local de Saúde do Alto Ave, Vizela, PRT.

Lung cancer is highly prevalent worldwide and is the leading cause of cancer-related death in Portugal. There is increasing evidence that low-dose computed tomography (LDCT) screening reduces mortality; however, few countries have implemented screening strategies. This review aims to gather the best evidence to assess the relevance of implementing lung cancer screening.

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Aim: To assess transmural remission in patients with Crohn's disease using low-dose small bowel computed tomography (CT) perfusion scans.

Materials And Methods: Forty six patients were divided into active and remission phases based on Crohn's Disease Activity Index (CDAI) and C-reactive protein (CRP). Dual-source CT enterography with low-dose perfusion scans was conducted to generate perfusion parameter maps, including blood flow (BF), blood volume (BV), time to peak (TTP), mean transit time (MTT), and permeability of surface (PS).

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Hypothesis: To evaluate how comorbidities affect mortality benefits of lung cancer screening (LCS) with low-dose computed-tomography (LDCT).

Methods: We developed a comorbidity index (PLCO-ci) using LCS-eligible participants' data from the Prostate Lung Colorectal and Ovarian (PLCO) trial (training set) and the National Lung Screening Trial (NLST) (validation set). PLCO-ci predicts 5-year non-lung cancer (LC) mortality using a regularized Cox model; with performance evaluated by the area under the ROC curve (ROC).

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