Pulmonary Emphysema Regional Distribution and Extent Assessed by Chest Computed Tomography Is Associated With Pulmonary Function Impairment in Patients With COPD.

Objective: This study aimed to evaluate how emphysema extent and its regional distribution quantified by chest CT are associated with clinical and functional severity in patients with chronic obstructive pulmonary disease (COPD). Methods/Design: Patients with a post-bronchodilator forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) < 0.70, without any other obstructive airway disease, who presented radiological evidence of emphysema on visual CT inspection were retrospectively enrolled. A Quantitative Lung Imaging (QUALI) system automatically quantified the volume of pulmonary emphysema and adjusted this volume to the measured (EmphCTLV) or predicted total lung volume (TLV) (EmphPLV) and assessed its regional distribution based on an artificial neural network (ANN) trained for this purpose. Additionally, the percentage of lung volume occupied by low-attenuation areas (LAA) was computed by dividing the total volume of regions with attenuation lower or equal to -950 Hounsfield units (HU) by the predicted [LAA (%PLV)] or measured CT lung volume [LAA (%CTLV)]. The LAA was then compared with the QUALI emphysema estimations. The association between emphysema extension and its regional distribution with pulmonary function impairment was then assessed. Results: In this study, 86 patients fulfilled the inclusion criteria. Both EmphCTLV and EmphPLV were significantly lower than the LAA indices independently of emphysema severity. CT-derived TLV significantly increased with emphysema severity (from 6,143 ± 1,295 up to 7,659 ± 1,264 ml from mild to very severe emphysema, p < 0.005) and thus, both EmphCTLV and LAA significantly underestimated emphysema extent when compared with those values adjusted to the predicted lung volume. All CT-derived emphysema indices presented moderate to strong correlations with residual volume (RV) (with correlations ranging from 0.61 to 0.66), total lung capacity (TLC) (from 0.51 to 0.59), and FEV1 (~0.6) and diffusing capacity for carbon monoxide DLCO (~0.6). The values of FEV1 and DLCO were significantly lower, and RV (p < 0.001) and TLC (p < 0.001) were significantly higher with the increasing emphysema extent and when emphysematous areas homogeneously affected the lungs. Conclusions: Emphysema volume must be referred to the predicted and not to the measured lung volume when assessing the CT-derived emphysema extension. Pulmonary function impairment was greater in patients with higher emphysema volumes and with a more homogeneous emphysema distribution. Further studies are still necessary to assess the significance of CTpLV in the clinical and research fields.

Estimating COVID-19 Pneumonia Extent and Severity From Chest Computed Tomography.

BACKGROUND: COVID-19 pneumonia extension is assessed by computed tomography (CT) with the ratio between the volume of abnormal pulmonary opacities (PO) and CT-estimated lung volume (CTLV). CT-estimated lung weight (CTLW) also correlates with pneumonia severity. However, both CTLV and CTLW depend on demographic and anthropometric variables. PURPOSES: To estimate the extent and severity of COVID-19 pneumonia adjusting the volume and weight of abnormal PO to the predicted CTLV (pCTLV) and CTLW (pCTLW), respectively, and to evaluate their possible association with clinical and radiological outcomes. METHODS: Chest CT from 103 COVID-19 and 86 healthy subjects were examined retrospectively. In controls, predictive equations for estimating pCTLV and pCTLW were assessed. COVID-19 pneumonia extent and severity were then defined as the ratio between the volume and the weight of abnormal PO expressed as a percentage of the pCTLV and pCTLW, respectively. A ROC analysis was used to test differential diagnosis ability of the proposed method in COVID-19 and controls. The degree of pneumonia extent and severity was assessed with Z-scores relative to the average volume and weight of PO in controls. Accordingly, COVID-19 patients were classified as with limited, moderate and diffuse pneumonia extent and as with mild, moderate and severe pneumonia severity. RESULTS: In controls, CTLV could be predicted by sex and height (adjusted R 2 = 0.57; P < 0.001) while CTLW by age, sex, and height (adjusted R 2 = 0.6; P < 0.001). The cutoff of 20% (AUC = 0.91, 95%CI 0.88-0.93) for pneumonia extent and of 50% (AUC = 0.91, 95%CI 0.89-0.92) for pneumonia severity were obtained. Pneumonia extent were better correlated when expressed as a percentage of the pCTLV and pCTLW (r = 0.85, P < 0.001), respectively. COVID-19 patients with diffuse and severe pneumonia at admission presented significantly higher CRP concentration, intra-hospital mortality, ICU stay and ventilatory support necessity, than those with moderate and limited/mild pneumonia. Moreover, pneumonia severity, but not extent, was positively and moderately correlated with age (r = 0.46) and CRP concentration (r = 0.44). CONCLUSION: The proposed estimation of COVID-19 pneumonia extent and severity might be useful for clinical and radiological patient stratification.

COVID-19 Chest Computed Tomography to Stratify Severity and Disease Extension by Artificial Neural Network Computer-Aided Diagnosis.

Purpose: This work aims to develop a computer-aided diagnosis (CAD) to quantify the extent of pulmonary involvement (PI) in COVID-19 as well as the radiological patterns referred to as lung opacities in chest computer tomography (CT). Methods: One hundred thirty subjects with COVID-19 pneumonia who underwent chest CT at hospital admission were retrospectively studied (141 sets of CT scan images). Eighty-eight healthy individuals without radiological evidence of acute lung disease served as controls. Two radiologists selected up to four regions of interest (ROI) per patient (totaling 1,475 ROIs) visually regarded as well-aerated regions (472), ground-glass opacity (GGO, 413), crazy paving and linear opacities (CP/LO, 340), and consolidation (250). After balancing with 250 ROIs for each class, the density quantiles (2.5, 25, 50, 75, and 97.5%) of 1,000 ROIs were used to train (700), validate (150), and test (150 ROIs) an artificial neural network (ANN) classifier (60 neurons in a single-hidden-layer architecture). Pulmonary involvement was defined as the sum of GGO, CP/LO, and consolidation volumes divided by total lung volume (TLV), and the cutoff of normality between controls and COVID-19 patients was determined with a receiver operator characteristic (ROC) curve. The severity of pulmonary involvement in COVID-19 patients was also assessed by calculating Z scores relative to the average volume of parenchymal opacities in controls. Thus, COVID-19 cases were classified as mild (

Automatic Quantification of Interstitial Lung Disease From Chest Computed Tomography in Systemic Sclerosis.

Background: Interstitial lung disease (ILD) is a common complication in patients with systemic sclerosis (SSc), and its diagnosis contributes to early treatment decisions. Purposes: To quantify ILD associated with SSc (SSc-ILD) from chest CT images using an automatic quantification method based on the computation of the weight of interstitial lung opacities. Methods: Ninety-four patients with SSc underwent CT, forced vital capacity (FVC), and carbon monoxide diffusion capacity (DLCO) tests. Seventy-three healthy individuals without radiological evidence of lung disease served as controls. After lung and airway segmentation, the ratio between the weight of interstitial opacities [densities between -500 and +50 Hounsfield units (HU)] and the total lung weight (densities between -1,000 and +50 HU) was used as an ILD indicator (ILD[%] = 100 × [LW(-500 to +50HU)/LW(-1, 000 to +50HU)]). The cutoff of normality between controls and SSc was determined with a receiver operator characteristic curve. The severity of pulmonary involvement in SSc patients was also assessed by calculating Z scores of ILD relative to the average interstitial opacities in controls. Accordingly, SSc-ILD was classified as SSc Limited-ILD (Z score < 3) and SSc Extensive-ILD (Z score ≥ 3 or FVC < 70%). Results: Seventy-eight (83%) SSc patients were classified as presenting SSc-ILD (optimal ILD threshold of 23.4%, 0.83 sensitivity, 0.92 specificity, and 0.94 area under the receiver operator characteristic curve, 95% CI from 0.89 to 0.96, 0.93 positive predictive value, and 0.81 negative predictive value, p < 0.001) and exhibited radiological attenuations compatible with interstitial pneumonia dispersed in the lung parenchyma. Thirty-six (38%) patients were classified as SSc Extensive-ILD (ILD threshold ≥ 29.6% equivalent to a Z score ≥ 3) and 42 (45%) as SSc Limited-ILD. Eighteen (50%) patients with SSc Extensive-ILD presented FVC < 70%, being only five patients classified exclusively based on FVC. SSc Extensive-ILD also presented lower DLCO (57.9 ± 17.9% vs. 73.7 ± 19.8%; p < 0.001) and total lung volume (2,916 ± 674 vs. 4,286 ± 1,136, p < 0.001) compared with SSc Limited-ILD. Conclusion: The proposed method seems to provide an alternative to identify and quantify the extension of ILD in patients with SSc, mitigating the subjectivity of semiquantitative analyzes based on visual scores.

Pulmonary Densitovolumetry Using Computed Tomography in Patients with Nontuberculous Mycobacteria: Correlation with Pulmonary Function Tests.

BACKGROUND: Since nontuberculous mycobacterial pulmonary disease (NTM-PD) is a condition with increasing morbidity, a more detailed knowledge of radiological aspects and pulmonary function plays a relevant role in the diagnosis and appropriate therapeutic management of these patients. OBJECTIVES: The purpose of this study was to evaluate changes in lung parenchyma through computed tomography (CT) densitometry and, secondarily, to analyze its correlation with pulmonary function testing (PFT) in patients with NTM-PD. METHODS: This is a cross-sectional study in which 31 patients with NTM-PD and 27 controls matched by sex, age, and body mass index underwent CT pulmonary densitovolumetry and pulmonary function tests including spirometry and body plethysmograph. RESULTS: Based on the total lung volume (TLV) and total lung mass (TLM) measurements, the cumulative mass ratios were calculated for 3% (M3), 15% (M15), 85% (M85), and 97% (M97) of the TLV. We also calculated the complement, which is represented by TLM (100%) minus the mass of 15% (C85) or 3% (C97) of the TLV. Patients with NTM-PD presented lower values of M3 and M15 than controls, with greater significant differences in the apical third and middle third measurements. Compared to controls, patients with NTM-PD showed higher values of C85 and C97, although significant differences were observed only in the basal third measurements. There were negative correlations of total lung capacity with M3 and M15 in the middle third and apical third measurements. There were positive correlations of residual volume and airway resistance with M3 at the apical third measurement. CONCLUSIONS: Patients with NTM-PD show reduced lung mass and increased lung mass in the apical and basal regions of the lungs, respectively. Furthermore, there is a relationship between lung mass measurements and pulmonary function parameters.

Association of respiratory integer and fractional-order models with structural abnormalities in silicosis.

BACKGROUND AND OBJECTIVE: Integer and fractional-order models have emerged as powerful methods for obtaining information regarding the anatomical or pathophysiological changes that occur during respiratory diseases. However, the precise interpretation of the model parameters in light of the lung structural changes is not known. This study analyzed the associations of the integer and fractional-order models with structural changes obtained using multidetector computed tomography densitometry (MDCT) and pulmonary function analysis. METHODS: Integer and fractional-order models were adjusted to data obtained using the forced oscillation technique (FOT). The results obtained in controls (n = 20) were compared with those obtained in patients with silicosis (n = 32), who were submitted to spirometry, body plethysmograph, FOT, diffusing capacity of the lungs for carbon monoxide (DLCO), and MDCT. The diagnostic accuracy was also investigated using ROC analysis. RESULTS: The observed changes in the integer and fractional-order models were consistent with the pathophysiology of silicosis. The integer-order model showed association only between inertance and the non-aerated compartment (R = -0.69). This parameter also presented the highest associations with spirometry (R = 0.81), plethysmography (-0.61) and pulmonary diffusion (R = 0.53). Considering the fractional-order model, the increase in the poorly aerated and non-aerated regions presented direct correlations with the fractional inertance (R = 0.48), respiratory damping (R = 0.37) and hysteresivity (R = 0.54) and inverse associations with its fractional exponent (R = -0.62) and elastance (-0.35). Significant associations were also observed with spirometry (R = 0.63), plethysmography (0.37) and pulmonary diffusion (R = 0.51). Receiver operator characteristic analysis showed a higher accuracy in the FrOr model (0.908) than the eRIC model (0.789). CONCLUSIONS: Our study has shown clear associations of the integer and fractional-order parameters with anatomical changes obtained via MDCT and pulmonary function measurements. These findings help to elucidate the physiological interpretation of the integer and fractional-order parameters and provide evidence that these parameters are reflective of the abnormal changes in silicosis. We also observed that the fractional-order model showed smaller curve-fitting errors, which resulted in a higher diagnostic accuracy than that of the eRIC model. Taken together, these results provide strong motivation for further studies exploring the clinical and scientific use of these models in respiratory medicine.

Computed tomography trachea volumetry in patients with scleroderma: Association with clinical and functional findings.

BACKGROUND: In scleroderma, excessive collagen production can alter tracheal geometry, and computed tomography (CT) volumetry of this structure may aid in detecting possible abnormalities. The objectives of this study were to quantify the morphological abnormalities in the tracheas of ​​patients with scleroderma and to correlate these findings with data on clinical and pulmonary function. METHODS: This was a cross-sectional study in which 28 adults with scleroderma and 27 controls matched by age, gender and body mass index underwent chest CT with posterior segmentation and skeletonization of the images. In addition, all participants underwent pulmonary function tests and clinical evaluation, including the modified Rodnan skin score (mRSS). RESULTS: Most patients (71.4%) had interstitial lung disease on CT. Compared to controls, patients with scleroderma showed higher values ​​in the parameters measured by CT trachea volumetry, including area, eccentricity, major diameter, minor diameter, and tortuosity. The tracheal area and equivalent diameter were negatively correlated with the ratio between forced expiratory flow and forced inspiratory flow at 50% of forced vital capacity (FEF50%/FIF50%) (r = -0.44, p = 0.03 and r = -0.46, p = 0.02, respectively). The tracheal tortuosity was negatively correlated with peak expiratory flow (r = -0.51, p = 0.008). The mRSS showed a positive correlation with eccentricity (r = 0.62, p < 0.001) and tracheal tortuosity (r = 0.51, p = 0.007), while the presence of anti-topoisomerase I antibody (ATA) showed a positive correlation with tracheal tortuosity (r = 0.45, p = 0.03). CONCLUSIONS: In a sample composed predominantly of scleroderma patients with associated interstitial lung disease, there were abnormalities in tracheal geometry, including greater eccentricity, diameter and tortuosity. In these patients, abnormalities in the geometry of the trachea were associated with functional markers of obstruction. In addition, tracheal tortuosity was correlated with cutaneous involvement and the presence of ATA.

The Role of Multidetector Computed Tomography and the Forced Oscillation Technique in Assessing Lung Damage in Adults With Cystic Fibrosis.

BACKGROUND: With increased survival rates and the consequent emergence of an adult population with cystic fibrosis (CF), developing novel tools for periodic evaluations of these patients has become a new challenge. Thus, we sought to determine the contribution of lung-volume quantification using multidetector computed tomography (CT) in adults with CF and to investigate the association between structural changes and functional abnormalities. METHODS: This was a cross-sectional study in which 21 adults with CF and 22 control subjects underwent lung-volume quantification using multidetector CT. Voxel densities were divided into 4 bands: -1,000 to -900 Hounsfield units (HU) (hyperaerated region), -900 to -500 HU (normally aerated region), -500 to -100 HU (poorly aerated region), and -100 to 100 HU (non-aerated region). In addition, all participants performed pulmonary function tests including spirometry, body plethysmography, diffusion capacity for carbon monoxide, and the forced oscillation technique. RESULTS: Adults with CF had more non-aerated regions and poorly aerated regions with lung-volume quantification using multidetector CT than controls. Despite these abnormalities, total lung volume measured by lung-volume quantification using multidetector CT did not differ between subjects and controls. Total lung capacity (TLC) measured by body plethysmography correlated with both total lung volume (rs = 0.71, P < .001) and total air volume (rs = 0.71, P < .001) as measured with lung-volume quantification using multidetector CT. While the hyperaerated regions correlated with the functional markers of gas retention in the lungs (increased residual volume (RV) and RV/TLC ratio), the poorly aerated regions correlated with the resistive parameters measured by the forced oscillation technique (increased intercept resistance and mean resistance). We also observed a correlation between normally aerated regions and highest pulmonary diffusion values (rs = 0.68, P < .001). CONCLUSIONS: In adults with CF, lung-volume quantification using multidetector CT can destimate the lung volumes of compartments with different densities and determine the aerated and non-aerated contents of the lungs; furthermore, lung-volume quantification using multidetector CT is clearly related to pulmonary function parameters.

Computed tomography airway lumen volumetry in patients with acromegaly: Association with growth hormone levels and lung function.

INTRODUCTION: The segmentation and skeletonisation of images via computed tomography (CT) airway lumen volumetry provide a new perspective regarding the incorporation of this technique in medical practice. Our aim was to quantify morphological changes in the large airways of patients with acromegaly through CT and, secondarily, to correlate these findings with hormone levels and pulmonary function testing (PFT) parameters. METHODS: This was a cross-sectional study in which 28 non-smoker patients with acromegaly and 15 control subjects underwent CT analysis of airway lumen volumetry with subsequent image segmentation and skeletonisation. Moreover, all participants were subjected to PFT. RESULTS: Compared with the controls, patients with acromegaly presented higher diameters in the trachea, right main bronchus and left main bronchus. The patients with acromegaly also showed a higher tracheal sinuosity index (the deviation of a line from the shortest path, calculated by dividing total length by shortest possible path) than the controls [1.06 (1.02-1.09) vs. 1.03 (1.02-1.04), P = 0.04], and tracheal stenosis was observed in 25% of these individuals. The tracheal area was correlated with the levels of growth hormone (rs  = 0.45, P = 0.02) and insulin-like growth factor type I (rs  = 0.38, P = 0.04). The ratio between the forced expiratory flow and forced inspiratory flow at 50% of the forced vital capacity was correlated with the tracheal area (rs  = 0.36, P = 0.02) and Δ tracheal diameters (rs  = 0.58, P < 0.0001). CONCLUSION: Patients with acromegaly exhibit tracheobronchomegaly and tracheal sinuosity/stenosis. Moreover, there are associations between the results of CT airway lumen volumetry, hormone levels and functional parameters of large airway obstruction.