Genetic Testing Goes Beyond Imaging and Histological Evaluation in Pleuroparenchymal Fibroelastosis.

BACKGROUND: Lung biopsy remains the gold standard in the diagnosis of fibrotic interstitial lung disease (F-ILD), but there is a growing appreciation of the role of pathogenic gene variants in telomere and surfactant protein genes, especially in familial pulmonary fibrosis (FPF). Pleuroparenchymal fibroelastosis (PPFE) is a rare disease that can coexist with different patterns of F-ILD, including FPF. It can be progressive and often leads to respiratory failure and death. This study tested the hypothesis that genetic testing goes beyond radiological and histological findings in PPFE and other F-ILD further informing clinical decision-making for patients and affected family members by identifying pathological gene variants in telomere and surfactant protein genes. METHODS: This is a retrospective review of 70 patients with F-ILD in the setting of FPF or premature lung fibrosis. Six out of 70 patients were diagnosed with PPFE based on radiological or histological characteristics. All patients underwent telomere length evaluation in peripheral blood by Flow-FISH or genetic testing using a customized exome-based panel that included telomere and surfactant protein genes associated with lung fibrosis. RESULTS: Herein, we identified six individuals where radiographic or histopathological analyses of PPFE were linked with telomere biology disorders (TBD) or variants in surfactant protein genes. Each case involved individuals with either personal early-onset lung fibrosis or a family history of the disease. Assessments of telomere length and genetic testing offered insights beyond traditional radiological and histopathological evaluations. CONCLUSION: Detecting anomalies in TBD-related or surfactant protein genes can significantly refine the diagnosis and treatment strategies for individuals with PPFE and other F-ILD.

The role of PET scan in monitoring the progression of fibrosing mediastinitis.

We present the case of a 31-year-old man who presented with acute chest pain. Computed tomography scan showed a mediastinal mass engulfing right main-stem bronchus and another mass surrounding descending aorta. Positron emission tomography (PET) scan showed high mass metabolic activity. Histopathological evaluation revealed fibroinflammatory scarring. He was diagnosed with idiopathic fibrosing mediastinitis, started on prednisone and tamoxifen treatment, and monitored with serial PET scans. Nine months after treatment initiation, paraaortic abnormality had resolved and mediastinal mass had regressed.

Respiratory rate variability in sleeping adults without obstructive sleep apnea.

Characterizing respiratory rate variability (RRV) in humans during sleep is challenging, since it requires the analysis of respiratory signals over a period of several hours. These signals are easily distorted by movement and volitional inputs. We applied the method of spectral analysis to the nasal pressure transducer signal in 38 adults with no obstructive sleep apnea, defined by an apnea-hypopnea index <5, who underwent all-night polysomnography (PSG). Our aim was to detect and quantitate RRV during the various sleep stages, including wakefulness. The nasal pressure transducer signal was acquired at 100 Hz and consecutive frequency spectra were generated for the length of the PSG with the Fast Fourier Transform. For each spectrum, we computed the amplitude ratio of the first harmonic peak to the zero frequency peak (H1/DC), and defined as RRV as (100 - H1/DC) %. RRV was greater during wakefulness compared to any sleep stage, including rapid-eye-movement. Furthermore, RRV correlated with the depth of sleep, being lowest during N3. Patients spent most their sleep time supine, but we found no correlation between RRV and body position. There was a correlation between respiratory rate and sleep stage, being greater in wakefulness than in any sleep stage. We conclude that RRV varies according to sleep stage. Moreover, spectral analysis of nasal pressure signal appears to provide a valid measure of RRV during sleep. It remains to be seen if the method can differentiate normal from pathological sleep patterns.