A cystic and bullous lung disease associated with a PIK3CA-related overgrowth syndrome.

A bullous and cystic lung disease diagnosed in the context of a clinically and genetically diagnosed PROS https://bit.ly/48GnoJy.

Sarcoidosis-Associated Pulmonary Hypertension.

Sarcoidosis-associated pulmonary hypertension (SAPH) is a very severe complication of the disease, largely impacting its morbidity and being one of its strongest predictors of mortality. With the recent modifications of the hemodynamic definition of pulmonary hypertension (mean arterial pulmonary pressure >20 instead of <25 mmHg,) its prevalence is presently not precisely known, but it affects from 3 to 20% of sarcoid patients; mostly, although not exclusively, those with an advanced, fibrotic pulmonary disease. Its gold-standard diagnostic tool remains right heart catheterization (RHC). The decision to perform it relies on an expert decision after a non-invasive work-up, in which echocardiography remains the screening tool of choice. The mechanisms underlying SAPH, very often entangled, are crucial to define, as appropriate and personalized therapeutic strategies will aim at targeting the most significant ones. There are no recommendations so far as to the indications and modalities of the medical treatment of SAPH, which is based upon the opinion of a multidisciplinary team of sarcoidosis, pulmonary hypertension and sometimes lung transplant experts.

High-Risk Sarcoidosis: A Focus on Pulmonary, Cardiac, Hepatic and Renal Advanced Diseases, as Well as on Calcium Metabolism Abnormalities.

Although sarcoidosis is generally regarded as a benign condition, approximately 20-30% of patients will develop a chronic and progressive disease. Advanced pulmonary fibrotic sarcoidosis and cardiac involvement are the main contributors to sarcoidosis morbidity and mortality, with failure of the liver and/or kidneys representing additional life-threatening situations. In this review, we discuss diagnosis and treatment of each of these complications and highlight how the integration of clinical, pathological and radiological features may help predict the development of such high-risk situations in sarcoid patients.

An adjudication algorithm for respiratory-related hospitalisation in idiopathic pulmonary fibrosis.

Background: There is no standard definition of respiratory-related hospitalisation, a common end-point in idiopathic pulmonary fibrosis (IPF) clinical trials. As diverse aetiologies and complicating comorbidities can present similarly, external adjudication is sometimes employed to achieve standardisation of these events. Methods: An algorithm for respiratory-related hospitalisation was developed through a literature review of IPF clinical trials with respiratory-related hospitalisation as an end-point. Experts reviewed the algorithm until a consensus was reached. The algorithm was validated using data from the phase 3 ISABELA trials (clinicaltrials.gov identifiers NCT03711162 and NCT03733444), by assessing concordance between nonadjudicated, investigator-defined, respiratory-related hospitalisations and those defined by the adjudication committee using the algorithm. Results: The algorithm classifies respiratory-related hospitalisation according to cause: extraparenchymal (worsening respiratory symptoms due to left heart failure, volume overload, pulmonary embolism, pneumothorax or trauma); other (respiratory tract infection, right heart failure or exacerbation of COPD); "definite" acute exacerbation of IPF (AEIPF) (worsening respiratory symptoms within 1 month, with radiological or histological evidence of diffuse alveolar damage); or "suspected" AEIPF (as for "definite" AEIPF, but with no radiological or histological evidence of diffuse alveolar damage). Exacerbations ("definite" or "suspected") with identified triggers (infective, post-procedural or traumatic, drug toxicity- or aspiration-related) are classed as "known AEIPF"; "idiopathic AEIPF" refers to exacerbations with no identified trigger. In the ISABELA programme, there was 94% concordance between investigator- and adjudication committee-determined causes of respiratory-related hospitalisation. Conclusion: The algorithm could help to ensure consistency in the reporting of respiratory-related hospitalisation in IPF trials, optimising its utility as an end-point.

U-net convolutional neural network applied to progressive fibrotic interstitial lung disease: Is progression at CT scan associated with a clinical outcome?

BACKGROUND: Computational advances in artificial intelligence have led to the recent emergence of U-Net convolutional neural networks (CNNs) applied to medical imaging. Our objectives were to assess the progression of fibrotic interstitial lung disease (ILD) using routine CT scans processed by a U-Net CNN developed by our research team, and to identify a progression threshold indicative of poor prognosis. METHODS: CT scans and clinical history of 32 patients with idiopathic fibrotic ILDs were retrospectively reviewed. Successive CT scans were processed by the U-Net CNN and ILD quantification was obtained. Correlation between ILD and FVC changes was assessed. ROC curve was used to define a threshold of ILD progression rate (PR) to predict poor prognostic (mortality or lung transplantation). The PR threshold was used to compare the cohort survival with Kaplan Mayer curves and log-rank test. RESULTS: The follow-up was 3.8 ± 1.5 years encompassing 105 CT scans, with 3.3 ± 1.1 CT scans per patient. A significant correlation between ILD and FVC changes was obtained (p = 0.004, ρ = -0.30 [95% CI: -0.16 to -0.45]). Sixteen patients (50%) experienced unfavorable outcome including 13 deaths and 3 lung transplantations. ROC curve analysis showed an aera under curve of 0.83 (p < 0.001), with an optimal cut-off PR value of 4%/year. Patients exhibiting a PR ≥ 4%/year during the first two years had a poorer prognosis (p = 0.001). CONCLUSIONS: Applying a U-Net CNN to routine CT scan allowed identifying patients with a rapid progression and unfavorable outcome.