Publications by authors named "S G Gerard"
Background: Chronic and excessive alcohol consumption is the leading cause of death due to chronic liver disease. Alcohol-related liver disease (ALD) encompasses a broad spectrum of clinical and pathological features, ranging from asymptomatic and reversible pathologies to hepatocellular carcinoma (HCC), a highly prevalent and deadly liver cancer. Indeed, alcohol consumption is one of the main worldwide etiologies of HCC.
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- Four-dimensional computed tomography (4DCT) is crucial for radiation therapy but can suffer from motion artifacts that hinder accurate imaging.
- A deep learning algorithm using a U-net convolutional neural network was created to identify various artifact types in 4DCT images, trained on over 23,000 slices from 98 scans.
- The model outperformed previous methods with a sensitivity of 78%, specificity of 99%, and an ROC AUC of 0.99, showing it can effectively detect multiple artifacts in a single image.
Background: Pulmonary microvasculature alterations are implicated in emphysema pathogenesis, but the association between pulmonary microvascular blood volume (PMBV) and emphysema has not been directly assessed at scale, and prior studies have used non-specific measures of emphysema.
Methods: The Multi-Ethnic Study of Atherosclerosis Lung Study invited participants recruited from the community without renal impairment to undergo contrast-enhanced dual-energy CT. Pulmonary blood volume was calculated by material decomposition; PMBV was defined as blood volume in the peripheral 2 cm of the lung.
Background: Optimal systolic blood pressure (SBP) targets for the treatment of hospitalized acute decompensated heart failure (ADHF) patients are not known.
Objectives: To investigate the association between SBP <130 mmHg at discharge or within 30 days and all-cause mortality or years of life lost (YLL) after ADHF hospitalization.
Methods: We analyzed medical records of 14,611 adults who survived ADHF hospitalization at 17 hospitals (2010-2022) with follow-up until May 2023.
Article Synopsis
- Researchers are investigating how artificial intelligence (AI) can help measure functional small airways disease (fSAD) in chronic obstructive pulmonary disease (COPD) using just one CT scan instead of the two traditionally required.
- They studied over 2,500 participants and found strong correlations between the new AI method and existing measures of lung function, confirming its effectiveness.
- The new AI technique for estimating fSAD proved to be more reliable and repeatable compared to standard methods, suggesting it could enhance clinical assessments of COPD.