Spatial resolution enhancement using deep learning improves chest disease diagnosis based on thick slice CT.

CT is crucial for diagnosing chest diseases, with image quality affected by spatial resolution. Thick-slice CT remains prevalent in practice due to cost considerations, yet its coarse spatial resolution may hinder accurate diagnoses. Our multicenter study develops a deep learning synthetic model with Convolutional-Transformer hybrid encoder-decoder architecture for generating thin-slice CT from thick-slice CT on a single center (1576 participants) and access the synthetic CT on three cross-regional centers (1228 participants).

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 Classification of Usual Interstitial Pneumonia Predicts Outcomes.

Computed tomography (CT) enables noninvasive diagnosis of usual interstitial pneumonia (UIP), but enhanced image analyses are needed to overcome the limitations of visual assessment. 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. We trained an MIL algorithm using a pooled dataset ( = 2,143) and tested it in three independent populations: data from a prior publication ( = 127), a single-institution clinical cohort ( = 239), and a national registry of patients with pulmonary fibrosis ( = 979).

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.

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.

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.

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

Relatives of patients with familial interstitial pneumonia (FIP) are at increased risk for pulmonary fibrosis and develop preclinical pulmonary fibrosis (PrePF). We defined the incidence and progression of new-onset PrePF and its relationship to survival among first-degree relatives of families with FIP. 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.

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.

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.

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.

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.

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 LPA receptor antagonist - in patients with IPF.

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.

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).

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.

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.

Evaluating topic model interpretability from a primary care physician perspective.

Background And Objective: Probabilistic topic models provide an unsupervised method for analyzing unstructured text. These models discover semantically coherent combinations of words (topics) that could be integrated in a clinical automatic summarization system for primary care physicians performing chart review. However, the human interpretability of topics discovered from clinical reports is unknown.

RadPath: A Web-based System for Integrating and Correlating Radiology and Pathology Findings During Cancer Diagnosis.

Rationale And Objectives: The current paradigm of cancer diagnosis involves uncoordinated communication of findings from radiology and pathology to downstream physicians. Discordance between these findings can require additional time from downstream users to resolve, or given incorrect resolution, may adversely impact treatment decisions. To mitigate this problem, we developed a web-based system, called RadPath, for correlating and integrating radiology and pathology reporting.