Publications by authors named "Joana Sofia F Pinto"
Article Synopsis
- Background: The study investigates how CT scans are used to measure the extent and severity of COVID-19 pneumonia by comparing abnormal lung opacities to estimated lung volume and weight, noting that these measurements can be influenced by demographic factors.
- Purposes: Researchers aimed to refine pneumonia assessments in COVID-19 by adjusting CT scan results to a predicted lung volume and weight, and to explore their relationships with patient outcomes.
- Results: Predictive factors like sex, age, and height helped estimate lung metrics in healthy individuals, while significant thresholds for pneumonia extent and severity were established; patients exhibiting severe pneumonia faced higher risks of complications such as mortality and ICU admission.
This work aims to develop a computer-aided diagnosis (CAD) to quantify the extent of pulmonary involvement (PI) in COVID-19 as well as the radiological patterns referred to as lung opacities in chest computer tomography (CT). One hundred thirty subjects with COVID-19 pneumonia who underwent chest CT at hospital admission were retrospectively studied (141 sets of CT scan images). Eighty-eight healthy individuals without radiological evidence of acute lung disease served as controls.
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