Deep Learning Classification of Usual Interstitial Pneumonia Predicts Outcomes.

Rationale: Computed tomography (CT) enables noninvasive diagnosis of usual interstitial pneumonia (UIP), but enhanced image analyses are needed to overcome the limitations of visual assessment. Objectives: Apply multiple instance learning (MIL) to develop an explainable deep learning algorithm for prediction of UIP from CT and validate its performance in independent cohorts. Methods: We trained an MIL algorithm using a pooled dataset (n = 2,143) and tested it in three independent populations: data from a prior publication (n = 127), a single-institution clinical cohort (n = 239), and a national registry of patients with pulmonary fibrosis (n = 979). We tested UIP classification performance using receiver operating characteristic analysis, with histologic UIP as ground truth. Cox proportional hazards and linear mixed-effects models were used to examine associations between MIL predictions and survival or longitudinal FVC. Measurements and Main Results: In two cohorts with biopsy data, MIL improved accuracy for histologic UIP (area under the curve, 0.77 [n = 127] and 0.79 [n = 239]) compared with visual assessment (area under the curve, 0.65 and 0.71). In cohorts with survival data, MIL-UIP classifications were significant for mortality (n = 239, mortality to April 2021: unadjusted hazard ratio, 3.1; 95% confidence interval [CI], 1.96-4.91; P < 0.001; and n = 979, mortality to July 2022: unadjusted hazard ratio, 3.64; 95% CI, 2.66-4.97; P < 0.001). Individuals classified as UIP positive by the algorithm had a significantly greater annual decline in FVC than those classified as UIP negative (-88 ml/yr vs. -45 ml/yr; n = 979; P < 0.01), adjusting for extent of lung fibrosis. Conclusions: Computerized assessment using MIL identifies clinically significant features of UIP on CT. Such a method could improve confidence in radiologic assessment of patients with interstitial lung disease, potentially enabling earlier and more precise diagnosis.

Deep Learning Assessment of Progression of Emphysema and Fibrotic Interstitial Lung Abnormality.

Rationale: Although studies have evaluated emphysema and fibrotic interstitial lung abnormality individually, less is known about their combined progression. Objectives: To define clinically meaningful progression of fibrotic interstitial lung abnormality in smokers without interstitial lung disease and evaluate the effects of fibrosis and emphysema progression on mortality. Methods: Emphysema and pulmonary fibrosis were assessed on the basis of baseline and 5-year follow-up computed tomography scans of 4,450 smokers in the COPDGene Study using deep learning algorithms. Emphysema was classified as absent, trace, mild, moderate, confluent, or advanced destructive. Fibrosis was expressed as a percentage of lung volume. Emphysema progression was defined as an increase by at least one grade. A hybrid distribution and anchor-based method was used to determine the minimal clinically important difference in fibrosis. The relationship between progression and mortality was evaluated using multivariable shared frailty models using an age timescale. Measurements and Main Results: The minimal clinically important difference for fibrosis was 0.58%. On the basis of this threshold, 2,822 (63%) had progression of neither emphysema nor fibrosis, 841 (19%) had emphysema progression alone, 512 (12%) had fibrosis progression alone, and 275 (6.2%) had progression of both. Compared with nonprogressors, hazard ratios for mortality were 1.42 (95% confidence interval, 1.11-1.82) in emphysema progressors, 1.49 (1.14-1.94) in fibrosis progressors, and 2.18 (1.58-3.02) in those with progression of both emphysema and fibrosis. Conclusions: In smokers without known interstitial lung disease, small changes in fibrosis may be clinically significant, and combined progression of emphysema and fibrosis is associated with increased mortality.

Incidence and Progression of Fibrotic Lung Disease in an At-Risk Cohort.

Rationale: Relatives of patients with familial interstitial pneumonia (FIP) are at increased risk for pulmonary fibrosis and develop preclinical pulmonary fibrosis (PrePF). Objectives: We defined the incidence and progression of new-onset PrePF and its relationship to survival among first-degree relatives of families with FIP. Methods: This is a cohort study of family members with FIP who were initially screened with a health questionnaire and chest high-resolution computed tomography (HRCT) scan, and approximately 4 years later, the evaluation was repeated. A total of 493 asymptomatic first-degree relatives of patients with FIP were evaluated at baseline, and 296 (60%) of the original subjects participated in the subsequent evaluation. Measurements and Main Results: The median interval between HRCTs was 3.9 years (interquartile range, 3.5-4.4 yr). A total of 252 subjects who agreed to repeat evaluation were originally determined not to have PrePF at baseline; 16 developed PrePF. A conservative estimate of the annual incidence of PrePF is 1,023 per 100,000 person-years (95% confidence interval, 511-1,831 per 100,000 person-years). Of 44 subjects with PrePF at baseline, 38.4% subjects had worsening dyspnea compared with 15.4% of those without PrePF (P = 0.002). Usual interstitial pneumonia by HRCT (P < 0.0002) and baseline quantitative fibrosis score (P < 0.001) are also associated with worsening dyspnea. PrePF at the initial screen is associated with decreased survival (P < 0.001). Conclusions: The incidence of PrePF in this at-risk population is at least 100-fold higher than that reported for sporadic idiopathic pulmonary fibrosis (IPF). Although PrePF and IPF represent distinct entities, our study demonstrates that PrePF, like IPF, is progressive and associated with decreased survival.

Emphysema Progression at CT by Deep Learning Predicts Functional Impairment and Mortality: Results from the COPDGene Study.

Background Visual assessment remains the standard for evaluating emphysema at CT; however, it is time consuming, is subjective, requires training, and is affected by variability that may limit sensitivity to longitudinal change. Purpose To evaluate the clinical and imaging significance of increasing emphysema severity as graded by a deep learning algorithm on sequential CT scans in cigarette smokers. Materials and Methods A secondary analysis of the prospective Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study participants was performed and included baseline and 5-year follow-up CT scans from 2007 to 2017. Emphysema was classified automatically according to the Fleischner emphysema grading system at baseline and 5-year follow-up using a deep learning model. Baseline and change in clinical and imaging parameters at 5-year follow-up were compared in participants whose emphysema progressed versus those who did not. Kaplan-Meier analysis and multivariable Cox regression were used to assess the relationship between emphysema score progression and mortality. Results A total of 5056 participants (mean age, 60 years ± 9 [SD]; 2566 men) were evaluated. At 5-year follow-up, 1293 of the 5056 participants (26%) had emphysema progression according to the Fleischner grading system. This group demonstrated progressive airflow obstruction (forced expiratory volume in 1 second [percent predicted]: -3.4 vs -1.8), a greater decline in 6-minute walk distance (-177 m vs -124 m), and greater progression in quantitative emphysema extent (adjusted lung density: -1.4 g/L vs 0.5 g/L; percentage of lung voxels with CT attenuation less than -950 HU: 0.6 vs 0.2) than those with nonprogressive emphysema (P < .001 for each). Multivariable Cox regression analysis showed a higher mortality rate in the group with emphysema progression, with an estimated hazard ratio of 1.5 (95% CI: 1.2, 1.8; P < .001). Conclusion An increase in Fleischner emphysema grade on sequential CT scans using an automated deep learning algorithm was associated with increased functional impairment and increased risk of mortality. ClinicalTrials.gov registration no. NCT00608764 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Grenier in this issue.

Quantitative imaging analysis detects subtle airway abnormalities in symptomatic military deployers.

BACKGROUND: Exposure to inhalational hazards during post-9/11 deployment to Southwest Asia and Afghanistan puts military personnel at risk for respiratory symptoms and disease. Pulmonary function and qualitative chest high resolution computed tomography (HRCT) are often normal in "deployers" with persistent respiratory symptoms. We explored the utility of quantitative HRCT imaging markers of large and small airways abnormalities, including airway wall thickness, emphysema, and air trapping, in symptomatic deployers with clinically-confirmed lung disease compared to controls. METHODS: Chest HRCT images from 45 healthy controls and 82 symptomatic deployers with asthma, distal lung disease or both were analyzed using Thirona Lung quantification software to calculate airway wall thickness (by Pi10), emphysema (by percentage of lung volume with attenuation < -950 Hounsfield units [LAA%-950]), and three parameters of air trapping (expiratory/inspiratory total lung volume and mean lung density ratios, and LAA%-856). SAS v.9.4 was used to compare demographic and clinical characteristics between deployers and controls using Chi-Square, Fisher Exact or t-tests. Linear regression was used to assess relationships between pulmonary function and quantitative imaging findings. RESULTS: Gender and smoking status were not statistically significantly different between groups, but deployers were significantly younger than controls (42 vs 58 years, p < 0.0001), had higher body mass index (31 vs 28 kg/m2, p = 0.01), and had fewer total smoking pack-years (8 vs. 26, p = 0.007). Spirometric measures were not statistically significantly different between groups. Pi10 and LAA%-950 were significantly elevated in deployers compared to controls in unadjusted analyses, with the emphysema measure remaining significantly higher in deployers after adjustment for age, sex, smoking, BMI, and expiratory total lung volume. Air trapping parameters were more common in control images, likely due to differences in age and smoking between groups. Among deployers, LAA%-950 and Pi10 were significantly correlated with spirometric markers of obstruction based on ratio of forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) and/or percent predicted FEV1. CONCLUSIONS: Quantitative chest HRCT imaging analysis identifies emphysema in deployers with asthma and distal lung disease, and may be useful in detecting and monitoring deployment-related lung disease in a population where spirometry is typically normal.

Visual Emphysema at Chest CT in GOLD Stage 0 Cigarette Smokers Predicts Disease Progression: Results from the COPDGene Study.

Background The clinical significance of visually evident emphysema on CT images in individuals without spirometric evidence of chronic obstructive pulmonary disease (COPD) by current diagnostic criteria is, to the knowledge of the authors, unknown. Purpose To evaluate whether participants with visually evident emphysema at CT were more likely to have progressive disease and increased mortality at 5 years compared with those without visual emphysema. Materials and Methods This secondary analysis of the prospective Genetic Epidemiology of COPD study evaluated current or former smokers enrolled between 2008 and 2011 who did not meet current criteria for COPD (defined as Global Initiative for Obstructive Lung Disease stage 0). Statistical analysis was performed by using linear mixed models to estimate mean physiologic, imaging, and clinical outcomes for those with and without visual emphysema. Hazard ratios for mortality were calculated by using Cox regression models with emphysema as the main predictor. Results Of the 4095 participants, 48.3% (1979 participants; 1096 men and 883 women; mean age, 57 years ± 8 [standard deviation]) had trace or greater visual emphysema at CT and 51.7% (2116 participants; 1068 men and 1048 women; mean age, 56 years ± 8) had no emphysema at CT. At 5 years, participants with visual emphysema at CT demonstrated progressive airflow obstruction with lower values of ratio of forced expiratory volume in 1 second (FEV1)-to-functional vital capacity (FVC) ratio (-1.7 vs -0.7) and greater progression in quantitative emphysema measured by 15th percentile lung density (-3.3 vs -0.3 HU), adjusted lung density (-3.1 vs -0.2 g/L), and percentage of lung voxels with CT attenuation less than -950 HU (0.17 vs -0.20) than participants without emphysema (P < .001 for each). The rate of quantitative emphysema progression increased with greater grades of emphysema severity within the emphysema group. Conclusion The presence of visual emphysema at CT in current and former Global Initiative for Obstructive Lung Disease stage 0 smokers predicted structural and physiologic disease progression. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Grenier in this issue.

Pictorial Review of Fibrotic Interstitial Lung Disease on High-Resolution CT Scan and Updated Classification.

TOPIC IMPORTANCE: Given the recently expanded approval of antifibrotics for various fibrotic interstitial lung diseases (ILDs), early and correct recognition of these diseases is imperative for physicians. Because high-resolution chest CT scan forms the backbone of diagnosis for ILD, this review will discuss evidence-based imaging findings of key fibrotic ILDs and an approach for differentiating these diseases. REVIEW FINDINGS: (1) Imaging findings of nonspecific interstitial pneumonia may evolve over time and become indistinguishable from usual interstitial pneumonia. Therefore, if remote imaging can be reviewed, this would increase the likelihood of an accurate imaging diagnosis, particularly if findings appear to represent a usual interstitial pneumonia pattern on the recent examination. (2) Given the difficulty and lack of objectivity in classifying patients with hypersensitivity pneumonitis into acute, subacute, and chronic categories and that prognosis depends primarily on presence or absence of fibrosis, the new set of guidelines released in 2020 categorizes patients with hypersensitivity pneumonitis as either nonfibrotic (purely inflammatory) or fibrotic (either purely fibrotic or mixed fibrotic/inflammatory) based on imaging and/or histologic findings, and the prior temporal terms are no longer used. (3) Interstitial lung abnormalities are incidental CT scan findings that may suggest early ILD in patients without clinical suspicion for ILD. Patients with high-risk features should undergo clinical evaluation for ILD and be actively monitored for disease progression. SUMMARY: Fibrotic ILD on high-resolution chest CT scan is a complex topic, but with use of an evidence-based analysis and algorithm as provided in this article, the probability of a correct imaging diagnosis increases.

Subsolid Nodules: Significance and Current Understanding.

Subsolid nodules are heterogeneously appearing and behaving entities, commonly encountered incidentally and in high-risk populations. Accurate characterization of subsolid nodules, and application of evolving surveillance guidelines, facilitates evidence-based and multidisciplinary patient-centered management.

Deep Learning-based Fibrosis Extent on Computed Tomography Predicts Outcome of Fibrosing Interstitial Lung Disease Independent of Visually Assessed Computed Tomography Pattern.

Rationale: Radiologic pattern has been shown to predict survival in patients with fibrosing interstitial lung disease. The additional prognostic value of fibrosis extent by quantitative computed tomography (CT) is unknown. Objectives: We hypothesized that fibrosis extent provides information beyond visually assessed CT pattern that is useful for outcome prediction. Methods: We performed a retrospective analysis of chest CT, demographics, longitudinal pulmonary function, and transplantation-free survival among participants in the Pulmonary Fibrosis Foundation Patient Registry. CT pattern was classified visually according to the 2018 usual interstitial pneumonia criteria. Extent of fibrosis was objectively quantified using data-driven textural analysis. We used Kaplan-Meier plots and Cox proportional hazards and linear mixed-effects models to evaluate the relationships between CT-derived metrics and outcomes. Results: Visual assessment and quantitative analysis were performed on 979 enrollment CT scans. Linear mixed-effect modeling showed that greater baseline fibrosis extent was significantly associated with the annual rate of decline in forced vital capacity. In multivariable models that included CT pattern and fibrosis extent, quantitative fibrosis extent was strongly associated with transplantation-free survival independent of CT pattern (hazard ratio, 1.04; 95% confidence interval, 1.04-1.05; P < 0.001; C statistic = 0.73). Conclusions: The extent of lung fibrosis by quantitative CT is a strong predictor of physiologic progression and survival, independent of visually assessed CT pattern.

Findings on High Resolution Computed Tomography in Symptomatic Veterans with Deployment-Related Lung Disease.

PURPOSE: Military deployment to dusty, austere environments in Southwest Asia and Afghanistan is associated with symptomatic airways diseases including asthma and bronchiolitis. The utility of chest high-resolution computed tomographic (HRCT) imaging in lung disease diagnosis in this population is poorly understood. We investigated visual assessment of HRCT for identifying deployment-related lung disease compared with healthy controls. MATERIALS AND METHODS: Chest HRCT images from 46 healthy controls and 45 symptomatic deployed military personnel with clinically confirmed asthma and/or biopsy-confirmed distal lung disease were scored by 3 independent thoracic radiologists. We compared demographic and clinical characteristics and frequency of imaging findings between deployers and controls, and between deployers with asthma and those with biopsy-confirmed distal lung disease, using χ2, Fisher exact or t tests, and logistic regression where appropriate. We also analyzed inter-rater agreement for imaging findings. RESULTS: Expiratory air trapping was the only chest CT imaging finding that was significantly more frequent in deployers compared with controls. None of the 24 deployers with biopsy-confirmed bronchiolitis and/or granulomatous pneumonitis had HRCT findings of inspiratory mosaic attenuation or centrilobular nodularity. Only 2 of 21 with biopsy-proven emphysema had emphysema on HRCT. CONCLUSIONS: Compared with surgical lung biopsy, visual assessment of HRCT showed few abnormalities in this small cohort of previously deployed symptomatic veterans with normal or near-normal spirometry.

Interstitial Lung Abnormality-Why Should I Care and What Should I Do About It?

Interstitial lung abnormalities (ILAs) are specific computed tomography (CT) findings that are potentially compatible with interstitial lung disease (ILD) in patients without clinical suspicion for disease. ILAs are associated with adverse clinical outcomes including increased mortality, imaging progression and lung function decline, and increased lung injury risk with lung cancer therapies. It is expected that identification of ILAs will increase with implementation of lung cancer screening and diagnostic CT imaging for workup of other pathologies. As such, radiologists will play a critical role in the diagnosis and management of ILAs.

The disconnect between visual assessment of air trapping and lung physiology for assessment of small airway disease in scleroderma-related interstitial lung disease: An observation from the Scleroderma Lung Study II Cohort.

Objective: To explore the presence of small airway disease (SAD) and emphysema in scleroderma-related interstitial lung disease (SSc-ILD) and to evaluate the physiologic and clinical correlates of SAD in SSc-ILD. Methods: Thoracic high-resolution computed tomography (HRCT) images obtained from the Scleroderma Lung Study II (SLSII) participants were reviewed by a group of thoracic radiologists. The presence of SAD was assessed by visual assessment for air trapping. HRCT scans were also evaluated for the presence of emphysema. The association of the presence of air trapping and emphysema with physiological measures of airway disease and clinical variables was evaluated. Results: A total of 155 baseline HRCT scans were reviewed. For assessment of air trapping, images needed to be adequate end-expiratory examinations, leaving 123 scans. Air trapping was seen in 13/123 (10.6%) of the SSc-ILD cohort and was independent of smoking history, asthma or the presence of gastroesophageal reflux. Air trapping on HRCT was not associated with physiologic evidence of SAD. We also identified 8/155 (5.2%) patients with emphysema on HRCT, which was independent of SAD and found mostly in prior smokers. Conclusion: We report the first study of air trapping on standardized, high-quality HRCT images as a reflection of SAD in a relatively large, well characterized SSc-ILD cohort. The presence of SAD in non-smoking SSc-ILD patients supports that SSc may cause not only restrictive lung disease (SSc-ILD), but also, to a lesser extent, obstructive disease. Physiologic measures alone may be inadequate to detect airway disease in patients with SSc-ILD.

Imaging of the rare cystic lung diseases.

When discussing cystic lung diseases, a certain group of diseases tends to receive the majority of attention. Other less frequently discussed cystic lung diseases are also important causes of morbidity in patients. Etiologies include genetic syndromes, lymphoproliferative diseases, infections, exogenous exposures, and a developmental abnormality. This review article focuses on the clinical and imaging features of these other cystic lung diseases.

Semiquantitative Chest Computed Tomography Assessment Identifies Expiratory Central Airway Collapse in Symptomatic Military Personnel Deployed to Iraq and Afghanistan.

PURPOSE: We noted incidental findings on chest computed tomography (CT) imaging of expiratory central airway collapse (ECAC) in dyspneic patients after military deployment to southwest Asia (mainly Iraq and Afghanistan). We developed a standardized chest CT protocol with dynamic expiration to enhance diagnostic reliability and investigated demographic, clinical, and deployment characteristics possibly associated with ECAC. MATERIALS AND METHODS: We calculated ECAC in 62 consecutive post-9/11 deployers with dyspnea who underwent multi-detector chest CT acquisition. ECAC was defined as ≥70% reduction in the cross-sectional tracheal area at dynamic expiration. We compared demographics (age, smoking, body mass index), comorbid conditions (gastroesophageal reflux, obstructive sleep apnea [OSA]), and clinical findings (air trapping, forced expiratory volume in 1 second percent predicted) in deployers with and without ECAC. We examined associations between ECAC and forced expiratory volume in 1 second percent predicted, air trapping, OSA, deployment duration, and blast exposure. RESULTS: Among 62 consecutive deployers with persistent dyspnea, 37% had ECAC. Three had severe (>85%) collapse. Those with ECAC were older (mean age 46 vs. 40 y, P=0.02), but no other demographic or clinical characteristics were statistically different among the groups. Although not statistically significant, ECAC odds were 1.5 times higher (95% confidence interval: 0.9, 2.5) for each additional year of southwest Asia deployment. Deployers with ECAC had 1.6 times greater odds (95% confidence interval: 0.5, 4.8) of OSA. CONCLUSIONS: Findings suggest that ECAC is common in symptomatic southwest Asia deployers. Chest high-resolution CT with dynamic expiration may provide an insight into the causes of dyspnea in this population, although risk factors for ECAC remain to be determined. A standardized semiquantitative approach to CT-based assessment of ECAC should improve reliable diagnosis in dyspneic patients.

The value of imaging and clinical outcomes in a phase II clinical trial of a lysophosphatidic acid receptor antagonist in idiopathic pulmonary fibrosis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive fibrotic lung disease characterized by worsening dyspnea and lung function and has a median survival of 2-3 years. Forced vital capacity (FVC) is the primary endpoint used most commonly in IPF clinical trials as it is the best surrogate for mortality. This study assessed quantitative scores from high-resolution computed tomography (HRCT) developed by machine learning as a secondary efficacy endpoint in a 26-week phase II study of BMS-986020 - an LPA1 receptor antagonist - in patients with IPF. METHODS: HRCT scans from 96% (137/142) of randomized subjects were utilized. Quantitative lung fibrosis (QLF) scores were calculated from the HRCT images. QLF improvement was defined as ⩾2% reduction in QLF score from baseline to week 26. RESULTS: In the placebo arm, 5% of patients demonstrated an improvement in QLF score at week 26 compared with 15% and 27% of patients in the BMS-986020 600 mg once daily (QD) and twice daily (BID) arms, respectively [versus placebo: p = 0.08 (600 mg QD); p = 0.0098 (600 mg BID)]. Significant correlations were found between changes in QLF and changes in percent predicted FVC, diffusing capacity for carbon monoxide (DLCO), and shortness of breath at week 26 (ρ = -0.41, ρ = -0.22, and ρ = 0.27, respectively; all p < 0.01). CONCLUSIONS: This study demonstrated the utility of quantitative HRCT as an efficacy endpoint for IPF in a double-blind, placebo-controlled clinical trial setting.The reviews of this paper are available via the supplemental material section.

Comparison of CT Lung Density Measurements between Standard Full-Dose and Reduced-Dose Protocols.

PURPOSE: To evaluate the reproducibility and predicted clinical outcomes of CT-based quantitative lung density measurements using standard fixed-dose (FD) and reduced-dose (RD) scans. MATERIALS AND METHODS: In this retrospective analysis of prospectively acquired data, 1205 participants (mean age, 65 years ± 9 [standard deviation]; 618 men) enrolled in the COPDGene study who underwent FD and RD CT image acquisition protocols between November 2014 and July 2017 were included. Of these, the RD scans of 640 participants were also reconstructed using iterative reconstruction (IR). Median filtering was applied to the RD scans (RD-MF) to investigate an alternative noise reduction strategy. CT attenuation at the 15th percentile of the lung CT histogram (Perc15) was computed for all image types (FD, RD, RD-MF, and RD-IR). Reproducibility coefficients were calculated to quantify the measurement differences between FD and RD scans. The ability of Perc15 to predict chronic obstructive pulmonary disease (COPD) diagnosis and exacerbation frequency was investigated using receiver operating characteristic analysis. RESULTS: The Perc15 reproducibility coefficients with and without volume adjustment were as follows: RD, 29.43 HU ± 0.62 versus 32.81 HU ± 1.70; RD-MF, 7.42 HU ± 0.42 versus 19.40 HU ± 2.65; and RD-IR, 7.10 HU ± 0.52 versus 22.46 HU ± 3.91. Receiver operating characteristic curve analysis indicated that Perc15 on volume-adjusted FD and RD scans were both predictive for COPD diagnosis (area under the receiver operating characteristic curve [AUC]: FD, 0.724 ± 0.045; RD, 0.739 ± 0.045) and for having one or more exacerbation per year (AUCs: FD, 0.593 ± 0.068; RD, 0.589 ± 0.066). Similar trends were observed when volume adjustment was not applied. CONCLUSION: A combination of volume adjustment and noise reduction filtering improved the reproducibility of lung density measurements computed using serial FD and RD CT scans.Supplemental material is available for this article.© RSNA, 2021.

Performance of pulmonary artery dimensions measured on high-resolution computed tomography scan for identifying pulmonary hypertension.

BACKGROUND: On high-resolution computed tomography (HRCT), pulmonary artery (PA) dimensions may hint at the presence of pulmonary hypertension. We aimed to determine how accurately various measures of the PA, as viewed on HRCT, predict right heart catheterisation (RHC)-confirmed pulmonary hypertension. METHODS: We retrospectively reviewed patients who had HRCT and RHC between 2010 and 2018. Analyses considered respiratory cycle, pulmonary hypertension diagnostic criteria, time between HRCT and RHC, and subgroup analysis in interstitial lung disease (ILD) and chronic obstructive pulmonary disease (COPD). RESULTS: Of 620 patients, 375 had pulmonary hypertension. For pulmonary hypertension (defined as mean PA pressure (mPAP) ≥25 mmHg) and from HRCT performed within 60 days of RHC, main PA diameter (MPAD) ≥29 mm had a sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 88%, 42%, 0.70 and 0.70, respectively, while ratio of the diameter of the PA to the diameter of the ascending aorta (PA:Ao) ≥1.0 showed 53%, 85%, 0.84 and 0.54, respectively. In general, results were similar when the interval between HRCT and RHC varied from 7 to 60 days and when measured on expiratory images. In ILD, the sensitivity of MPAD was higher; in COPD, the specificity of PA:Ao was higher. There was moderately positive correlation between mPAP and inspiratory MPAD, PA:Ao, right PA diameter (RPAD), left PA diameter (LPAD) and (RPAD+LPAD)/2 (r=0.48, 0.51, 0.34, 0.34 and 0.36, respectively), whereas there was weak negative correlation between mPAP and PA angle (r= -0.24). CONCLUSIONS: Findings on HRCT may assist in the diagnosis of RHC-confirmed pulmonary hypertension. MPAD ≥29 mm had high sensitivity and PA:Ao ≥1.0 had high specificity. Compared with the entire cohort, MPAD had greater sensitivity in ILD and PA:Ao had higher specificity in COPD.

The Use of the Net Promoter Score (NPS) in an Outpatient Allergy and Pulmonary Clinic: An Innovative Look into Using Tablet-Based Tool vs Traditional Survey Method.

INTRODUCTION: Patient satisfaction has become an essential metric in addition to the type of care they receive. Phone calls, emails, and text to patients after their healthcare visit are the typical way of obtaining the data reflecting patient satisfaction. The purpose of this retrospective quality improvement study is to compare the traditional post-outpatient clinic survey method with an onsite concise two-question survey using a tablet method immediately after the patient visit using Net Promoter Score (NPS) questions. METHODS: Data were collected retrospectively from February to August 2018 from an outpatient subspecialty clinic in southern California using an existing database from two different sources: the traditional method (TM) and the tablet-based tool (TBT), using NPS. The TM data were obtained from a third-party company using two questions via phone, email, and text collected 2-4 weeks after the patient's visit. The TBT has only two questions that were given to patients upon their visit check-out. These two questions assessed both provider and clinic's performance using the NPS method. RESULTS: In total, there were 1708 patients seen from February to August 2018. In the TM, the total outgoing messages during this period were 580 (34.0%) with 156 responses (27%). In the TBT, 648 out of 1708 (37.9%) surveys were collected with a 100% response rate. The NPS score showed that 99.2% of the providers were promoters. The NPS score for the clinic was 96% which reflects a promoter score. CONCLUSION: Our results indicate that when using the TBT immediately after their visit to the clinic, a higher response rate was noted. In addition, both methods had similar outcomes in terms of patient satisfaction NPS scores. Future prospective studies with a larger sample size are warranted to evaluate the effectiveness of the TBT tool in assessing patient satisfaction.