Pulmonary alveolar microlithiasis is rare disease characterized by accumulation of calcium phosphate microlithis in the alveoli. The pathogenesis relates to mutation in the gene SLC34A2 (solute carrier family 34 member 2) located on chromosome 4p15.2, which produces a defective sodium-phosphate cotransporter in alveolar epithelial type-2 cells, making these cells unable to clear phosphorus released during recycling of surfactant [1].
The three smoking-related interstitial lung diseases (ILD) include desquamative interstitial pneumonia (DIP), respiratory bronchiolitis-associated interstitial lung disease (RB-ILD), and pulmonary Langerhans cell histiocytosis (PLCH). They are considered discrete entities, yet it is not unusual to find a mixture of pathologic features rendering the histopathologic diagnosis difficult. It is uncommon to have overlap in the different radiologic findings between these diseases. We present a unique case, in that the extent of DIP and PLCH-like changes were manifested both histologically and on high resolution computed tomography (HRCT) with ground-glass attenuation and upper lobe cystic changes suggestive of both diseases.
Learning Objectives: Human ventilation is a complex dynamical system not easily quantified or visualized with traditional, simple measures. The currently used standard for determining a patient's ability for independent breathing is a single fixed point measurement, the Rapid Shallow Breathing Index (RBSI). The RBSI is a ratio of the instantaneous breathing rate and breath volume that may not capture the subtle aspects of the physiologically challenged patient. Methods: We propose a visualization of the respiratory impedance waveform pattern during a spontaneous breathing trial (SBT) to better capture the complex fluctuations and natural variability exposed during this challenge to a physiological system. The Dynamical Density plot visualization displays the instantaneous rate of change in the impedance waveform as a 3D density histogram. The resulting display reveals breathing patterns that may escape conventional displays. Results: We analyzed 15 patient's SBT from an Emory University medical ICU, and identified 3 pattern categories for these respiration dynamical density plots. The first pattern is a patient at rest supported by a ventilator, the second follows a change from assisted support to spontaneous breathing, or change to assisted breathing after a period of spontaneous breathing, and the third describes the recovery after ventilator support is restored. Conclusions: We observe that 3D density displays of respiratory rate, using dynamical density displays illuminates complex physiological changes consequent to a spontaneous breathing trial, enhancing calculation of the RSBI. We propose bedside display of these data as a test of change, anticipating better clinical decisions and safer care.
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