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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: OBJECTIVE, METHODS, RESULTS. Meshes: Adult, Cohort Studies, Exercise Test, Female, Forced Expiratory Volume, Forecasting, Humans, Linear Models, Lung Neoplasms, Lung Volume Measurements, Lymphangioleiomyomatosis, Middle Aged, Oxygen Consumption, Physical Exertion, Prognosis, Pulmonary Diffusing Capacity, Pulmonary Gas Exchange, Pulmonary Ventilation, Radiographic Image Enhancement, Residual Volume, Spirometry, Tomography, X-Ray Computed, Vital Capacity.
user
Does quantitative CT predict the severity of physiologic dysfunction in patients with lymphangioleiomyomatosis? Context: To assess quantitative high-resolution CT (quantitative CT) as a diagnostic and prognostic tool in pulmonary lymphangioleiomyomatosis. Spirometry, lung volumes, diffusing capacity, exercise physiology, and expiratory high-resolution CT (HRCT) examinations were performed on a cohort of ten patients with the diagnosis of lymphangioleiomyomatosis (LAM) referred to a tertiary care center. HRCT examinations were also done on ten normal control subjects. A thresholding technique was used to quantitatively assess the amount of abnormal cystic parenchyma present on each of the two images obtained for each subject with LAM and for each normal control subject. This numeric index of cystic parenchyma, the quantitative CT index, was then examined (1) as a diagnostic measure to distinguish the subjects with LAM from the normal control subjects and (2) as a prognostic measure to assess disease severity in the subjects with LAM. Linear regression of the quantitative CT index against physiologic indexes of pulmonary function and exercise performance was analyzed to determine the relationship between this radiologic assessment of disease severity and functional impairment. The quantitative CT index was significantly greater for the LAM patients, 37.2 +/- 6.9 (SEM), compared with the control group, 0.8 +/- 0.2 (p = 0.0001). Linear regression analysis demonstrated significant linear correlation between the quantitative CT index and measures of airflow (FEV1, r = -0.90, p = 0.0005), air trapping (residual volume, r = 0.70, p = 0.02), diffusing capacity (diffusing capacity for carbon monoxide, r = -0.76, p = 0.01), gas exchange (alveolar to arterial oxygen gradient) at rest, r = 0.69, p = 0.007, and at maximum exercise, r = 0.79, p = 0.007) and exercise performance (maximum workload, r = -0.84, p = 0.002), and oxygen utilization (oxygen utilization at maximum exercise, r = -0.76, p = 0.01).
assistant
Quantitative CT techniques can distinguish subjects with LAM from normal controls. Further, the quantitative CT index correlates well with physiologic measurements of airflow, lung volumes, diffusing capacity, and exercise performance and, thus, may provide a useful measure of disease severity. Final Decision: yes