Publications by authors named "G Hunninghake"
This retrospective study developed an automated algorithm for 3D segmentation of adipose tissue and paravertebral muscle on chest CT using artificial intelligence (AI) and assessed its feasibility. The study included patients from the Boston Lung Cancer Study (2000-2011). For adipose tissue quantification, 77 patients were included, while 245 were used for muscle quantification.
View Article and Find Full Text PDFObjectives: To explore the association between the extent of CT abnormalities by quantitative imaging analysis (QIA) and clinical/physiological disease parameters in patients with antisynthetase syndrome associated interstitial lung disease (ARS-ILD).
Methods: We analysed 20 patients with antisynthetase antibodies and active ILD enrolled in the Abatacept in Myositis-Associated Interstitial Lung Disease study. High-resolution chest CT was obtained at weeks 0, 24 and 48 and QIA scored the extent of ground glass (quantitative score for ground glass), fibrosis (quantitative score for lung fibrosis, QLF) and total ILD (quantitative ILD, QILD).
Rationale: Rheumatoid arthritis (RA) has been implicated in interstitial lung disease (ILD) as majority of studies have been comprised of patients with known RA. However, it remains unclear whether an underlying risk for RA in combination with genetic risk for pulmonary fibrosis is associated with radiological markers of early lung injury and fibrosis in broader population samples.
Objective: Determine whether genetic and serological biomarkers of RA risk in combination with the (rs35705950) risk allele (T) are associated with interstitial lung abnormalities (ILA) on computed tomography (CT) scans.
Article Synopsis
- Researchers are developing automated models using machine learning to predict interstitial lung abnormalities (ILAs) in CT scans, as current methods rely heavily on manual assessments, which can be less efficient.
- The study analyzed 1,382 CT scans from the Boston Lung Cancer Study, with radiologists serving as a reference point to identify ILAs; the scans were categorized into three groups: ILA present, indeterminate, and no ILA.
- Various machine learning classifiers were tested for accuracy, revealing that certain models performed better in identifying ILAs, highlighting the potential for automated methods to improve clinical decision-making in lung health.
Objective: The 6-min walk test (6MWT) is a simple test widely used to assess sub-maximal exercise capacity in chronic respiratory diseases. We explored the relationship of 6-min walk distance (6MWD) with measurements of physiological, clinical, radiographic measures in patients with myositis-associated interstitial lung disease (MA-ILD).
Method: We analyzed data from the Abatacept in Myositis Associated Interstitial lung disease (Attack My-ILD) study, a 48-week multicentre randomized trial of patients with anti-synthetase antibodies and active MA-ILD.