Spiral CT evaluation of pulmonary emphysema using a low-dose technique
Abstract
PURPOSE: To evaluate the diagnostic accuracy and clinical acceptability of low-dose spiral CT for determining pulmonary volumes and emphysema extension in patients with pulmonary emphysema, in comparison with studies based on spiral CT at conventional dose.
MATERIALS AND METHODS: We prospectively evaluated eighteen patients, current or former smokers, with a clinical diagnosis of chronic obstructive pulmonary disease. All the patients underwent: HRCT with three scans at predetermined levels; quantitative spiral CT, with two inspiratory scans, one conventional scan at 240 mA, and the second one a low-dose scan at 80 mA. We used the following parameters: 120 kV, rotation time 0.8", scan time less than 20" (single inspiratory breath-hold), layer thickness 7.5 mm, pitch 6 (high speed), interpolation algorithm at 180 degrees. A 3D reconstruction was performed, with segmentation of the lungs and automatic quantification of pulmonary volumes. We compared the volumes of absolute and percent emphysema and the ratings of the dose delivered to the patient (CTDIw and DLP) obtained with the two spiral CT scans with each other and with the respiratory function tests.
RESULTS: The average total lung capacity (TLC) obtained by conventional-dose spiral CT (CTs1) was 6889.4 cc (SD +/-1813.2), and the capacity with low-dose spiral CT (CTs2) was 6929.4 cc (SD +/-1811.6). The percentage of emphysema was 39.7% (range: 2.2-63.5%; SD: +/-19.9) for the CTs1 and 41.1% (range: 2.1-66.4%; SD: +/-20).…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence.
Read the paper
Related studies
- In silico toxicology protocols
- QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
- Quantum Informed Machine-Learning Potentials for Molecular Dynamics Simulations of CO2's Chemisorption and Diffusion in Mg-MOF-74
- In-silico strategies in nano-drug design: Bridging nanomaterials and pharmacological applications
- mRNA codon optimization with quantum computers
- The computational power of the human brain
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.