Local heterogeneity of normal lung parenchyma and small airways disease are associated with COPD severity and progression.

BACKGROUND: Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline. METHODS: PRM metrics of normal lung (PRMNorm) and functional SAD (PRMfSAD) were generated from CT scans collected as part of the COPDGene study (n = 8956). Volume density (V) and Euler-Poincaré Characteristic (χ) image maps, measures of the extent and coalescence of pocket formations (i.e., topologies), respectively, were determined for both PRMNorm and PRMfSAD. Association with COPD severity, emphysema, and spirometric measures were assessed via multivariable regression models. Readouts were evaluated as inputs for predicting FEV1 decline using a machine learning model. RESULTS: Multivariable cross-sectional analysis of COPD subjects showed that V and χ measures for PRMfSAD and PRMNorm were independently associated with the amount of emphysema. Readouts χfSAD (ß of 0.106, p < 0.001) and VfSAD (ß of 0.065, p = 0.004) were also independently associated with FEV1% predicted. The machine learning model using PRM topologies as inputs predicted FEV1 decline over five years with an AUC of 0.69. CONCLUSIONS: We demonstrated that V and χ of fSAD and Norm have independent value when associated with lung function and emphysema. In addition, we demonstrated that these readouts are predictive of spirometric decline when used as inputs in a ML model. Our topological PRM approach using PRMfSAD and PRMNorm may show promise as an early indicator of emphysema onset and COPD progression.

Parametric Response Mapping as an Imaging Biomarker in Lung Transplant Recipients.

RATIONALE: The predominant cause of chronic lung allograft failure is small airway obstruction arising from bronchiolitis obliterans. However, clinical methodologies for evaluating presence and degree of small airway disease are lacking. OBJECTIVES: To determine if parametric response mapping (PRM), a novel computed tomography voxel-wise methodology, can offer insight into chronic allograft failure phenotypes and provide prognostic information following spirometric decline. METHODS: PRM-based computed tomography metrics quantifying functional small airways disease (PRMfSAD) and parenchymal disease (PRMPD) were compared between bilateral lung transplant recipients with irreversible spirometric decline and control subjects matched by time post-transplant (n = 22). PRMfSAD at spirometric decline was evaluated as a prognostic marker for mortality in a cohort study via multivariable restricted mean models (n = 52). MEASUREMENTS AND MAIN RESULTS: Patients presenting with an isolated decline in FEV1 (FEV1 First) had significantly higher PRMfSAD than control subjects (28% vs. 15%; P = 0.005), whereas patients with concurrent decline in FEV1 and FVC had significantly higher PRMPD than control subjects (39% vs. 20%; P = 0.02). Over 8.3 years of follow-up, FEV1 First patients with PRMfSAD greater than or equal to 30% at spirometric decline lived on average 2.6 years less than those with PRMfSAD less than 30% (P = 0.004). In this group, PRMfSAD greater than or equal to 30% was the strongest predictor of survival in a multivariable model including bronchiolitis obliterans syndrome grade and baseline FEV1% predicted (P = 0.04). CONCLUSIONS: PRM is a novel imaging tool for lung transplant recipients presenting with spirometric decline. Quantifying underlying small airway obstruction via PRMfSAD helps further stratify the risk of death in patients with diverse spirometric decline patterns.

Quantitative CT of Normal Lung Parenchyma and Small Airways Disease Topologies are Associated With COPD Severity and Progression.

Objectives: Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients, and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline. Materials and Methods: PRM metrics of normal lung (PRMNorm) and functional SAD (PRMfSAD) were generated from CT scans collected as part of the COPDGene study (n=8956). Volume density (V) and Euler-Poincaré Characteristic (χ) image maps, measures of the extent and coalescence of pocket formations (i.e., topologies), respectively, were determined for both PRMNorm and PRMfSAD. Association with COPD severity, emphysema, and spirometric measures were assessed via multivariable regression models. Readouts were evaluated as inputs for predicting FEV1 decline using a machine learning model. Results: Multivariable cross-sectional analysis of COPD subjects showed that V and χ measures for PRMfSAD and PRMNorm were independently associated with the amount of emphysema. Readouts χfSAD (ß of 0.106, p<0.001) and VfSAD (ß of 0.065, p=0.004) were also independently associated with FEV1% predicted. The machine learning model using PRM topologies as inputs predicted FEV1 decline over five years with an AUC of 0.69. Conclusions: We demonstrated that V and χ of fSAD and Norm have independent value when associated with lung function and emphysema. In addition, we demonstrated that these readouts are predictive of spirometric decline when used as inputs in a ML model. Our topological PRM approach using PRMfSAD and PRMNorm may show promise as an early indicator of emphysema onset and COPD progression.

Distinguishing Adenocarcinomas from Granulomas in the CT scan of the chest: performance degradation evaluation in the automatic segmentation framework.

OBJECTIVE: The most common histopathologic malignant and benign nodules are Adenocarcinoma and Granuloma, respectively, which have different standards of care. In this paper, we propose an automatic framework for the diagnosis of the Adenocarcinomas and the Granulomas in the CT scans of the chest from a private dataset. We use the radiomic features of the nodules and the attached vessel tortuosity for the diagnosis. The private dataset includes 22 CTs for each nodule type, i.e., adenocarcinoma and granuloma. The dataset contains the CTs of the non-smoker patients who are between 30 and 60 years old. To automatically segment the delineated nodule area and the attached vessels area, we apply a morphological-based approach. For distinguishing the malignancy of the segmented nodule, two texture features of the nodule, the curvature Mean and the number of the attached vessels are extracted. RESULTS: We compare our framework with the state-of-the-art feature selection methods for differentiating Adenocarcinomas from Granulomas. These methods employ only the shape features of the nodule, the texture features of the nodule, or the torsion features of the attached vessels along with the radiomic features of the nodule. The accuracy of our framework is improved by considering the four selected features.

Warfarin-induced diffuse alveolar hemorrhage: Case report and a review of the literature.

Diffuse alveolar hemorrhage (DAH) refers to the intra-alveolar accumulation of blood originating from the pulmonary microvasculature. This life-threatening condition is a medical emergency as patients often develop acute respiratory failure requiring invasive mechanical ventilation. This mandates for an early diagnosis with prompt and aggressive management strategies. A host of clinical disorders are known to cause DAH; however, warfarin-induced alveolar hemorrhage is a distinct clinical rarity. A search of the literature reveals few reports documenting this entity. A 27-year-old male presented with complaints of recent-onset hemoptysis and dyspnea. One month back, he was diagnosed with lower-limb deep-venous thrombosis and pulmonary embolism. He had been taking oral anticoagulants irregularly since then without monitoring of prothrombin time. Chest radiograph, done on presentation, revealed bilateral upper-lobe infiltrates, whereas computed tomography of the chest was suggestive of bilateral upper-lobe ground-glass opacities. Serial bronchoscopic alveolar lavage yielded samples which became progressively bloodier, whereas cytological evaluation of the sample revealed numerous alveolar macrophages with intracytoplasmic hemosiderin. A diagnosis of DAH due to warfarin was made, and the patient was administered Vitamin K followed by infusion of fresh frozen plasma. There was a marked clinical recovery, and the patient has been asymptomatic since then.

Pleuroparenchymal fibroelastosis (PPFE) associated with giant cell arteritis: A coincidence or a novel phenotype?

Pleuroparenchymal fibroelastosis (PPFE) is a rare interstitial lung disease characterized by the fibrotic thickening of subpleural and parenchymal areas of the upper lobes. It may be both idiopathic or secondary to infections, interstitial lung diseases and/or drug exposure. Often PPFE patients report recurrent lower respiratory tract infections, suggesting that repeated inflammatory alterations induced by pulmonary infections may contribute to the development/progression of PPFE. Here, we report for the first time the case of a patient affected by Giant cell Arteritis with histologically proven PPFE. The lung involvement in GCA is rare and interstitial lung diseases are usually reported as an uncommon clinical manifestation of GCA. Our patient is probably the first case presenting PPFE associated with GCA and we wonder if this is a real associative disease or a coincidence perhaps, secondary to drug effects.