Dataset Information

CT-Based Commercial Software Applications: Improving Patient Care Through Accurate COPD Subtyping.

ABSTRACT: Chronic obstructive pulmonary disease (COPD) is heterogenous in its clinical manifestations and disease progression. Patients often have disease courses that are difficult to predict with readily available data, such as lung function testing. The ability to better classify COPD into well-defined groups will allow researchers and clinicians to tailor novel therapies, monitor their effects, and improve patient-centered outcomes. Different modalities of assessing these COPD phenotypes are actively being studied, and an area of great promise includes the use of quantitative computed tomography (QCT) techniques focused on key features such as airway anatomy, lung density, and vascular morphology. Over the last few decades, companies around the world have commercialized automated CT software packages that have proven immensely useful in these endeavors. This article reviews the key features of several commercial platforms, including the technologies they are based on, the metrics they can generate, and their clinical correlations and applications. While such tools are increasingly being used in research and clinical settings, they have yet to be consistently adopted for diagnostic work-up and treatment planning, and their full potential remains to be explored.

SUBMITTER: Wang JM

PROVIDER: S-EPMC9056100 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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CT-Based Commercial Software Applications: Improving Patient Care Through Accurate COPD Subtyping.

Wang Jennifer M JM Ram Sundaresh S Labaki Wassim W WW Han MeiLan K MK Galbán Craig J CJ

International journal of chronic obstructive pulmonary disease 20220426

Chronic obstructive pulmonary disease (COPD) is heterogenous in its clinical manifestations and disease progression. Patients often have disease courses that are difficult to predict with readily available data, such as lung function testing. The ability to better classify COPD into well-defined groups will allow researchers and clinicians to tailor novel therapies, monitor their effects, and improve patient-centered outcomes. Different modalities of assessing these COPD phenotypes are actively ...[more]

PMID: 35502294

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Project description:BackgroundMultiple studies have identified COPD subtypes by using visual or quantitative evaluation of CT images. However, there has been no systematic assessment of a combined visual and quantitative CT imaging classification. We integrated visually defined patterns of emphysema with quantitative imaging features and spirometry data to produce a set of 10 nonoverlapping CT imaging subtypes, and we assessed differences between subtypes in demographic features, physiological characteristics, longitudinal disease progression, and mortality.MethodsWe evaluated 9,080 current and former smokers in the COPDGene study who had available volumetric inspiratory and expiratory CT images obtained using a standardized imaging protocol. We defined 10 discrete, nonoverlapping CT imaging subtypes: no CT imaging abnormality, paraseptal emphysema (PSE), bronchial disease, small airway disease, mild emphysema, upper lobe predominant centrilobular emphysema (CLE), lower lobe predominant CLE, diffuse CLE, visual without quantitative emphysema, and quantitative without visual emphysema. Baseline and 5-year longitudinal characteristics and mortality were compared across these CT imaging subtypes.ResultsThe overall mortality differed significantly between groups (P < .01) and was highest in the 3 moderate to severe CLE groups. Subjects having quantitative but not visual emphysema and subjects with visual but not quantitative emphysema were unique groups with mild COPD, at risk for progression, and with likely different underlying mechanisms. Subjects with PSE and/or moderate to severe CLE had substantial progression of emphysema over 5 years compared with findings in subjects with no CT imaging abnormality (P < .01).ConclusionsThe combination of visual and quantitative CT imaging features reflects different underlying pathological processes in the heterogeneous COPD syndrome and provides a useful approach to reclassify types of COPD.Trial registryClinicalTrials.gov; No.: NCT00608764; URL: www.clinicaltrials.gov.

Project description:PurposeTo describe demographic and clinical characteristics of chronic obstructive pulmonary disease patients managed in US primary care.MethodsThis was an observational registry study using data from the Chronic Obstructive Pulmonary Disease (COPD) Optimum Patient Care DARTNet Research Database from which the Advancing the Patient Experience COPD registry is derived. Registry patients were aged ≥35 years at diagnosis. Electronic health record data were collected from both registries, supplemented with patient-reported information/outcomes from the Advancing the Patient Experience registry from 5 primary care groups in Texas, Ohio, Colorado, New York, and North Carolina (June 2019 through November 2020).ResultsOf 17,192 patients included, 1,354 were also in the Advancing the Patient Experience registry. Patients were predominantly female (56%; 9,689/17,192), White (64%; 9,732/15,225), current/ex-smokers (80%; 13,784/17,192), and overweight/obese (69%; 11,628/16,849). The most commonly prescribed maintenance treatments were inhaled corticosteroid with a long-acting β2-agonist (30%) and inhaled corticosteroid with a long-acting muscarinic antagonist (27%). Although 3% (565/17,192) of patitents were untreated, 9% (1,587/17,192) were on short-acting bronchodilator monotherapy, and 4% (756/17,192) were on inhaled corticosteroid monotherapy. Despite treatment, 38% (6,579/17,192) of patients experienced 1 or more exacerbations in the last 12 months. These findings were mirrored in the Advancing Patient Experience registry with many patients reporting high or very high impact of disease on their health (43%; 580/1,322), a breathlessness score 2 or more (45%; 588/1,315), and 1 or more exacerbation in the last 12 months (50%; 646/1,294).ConclusionsOur findings highlight the high exacerbation, symptom, and treatment burdens experienced by COPD patients managed in US primary care, and the need for more real-life effectiveness trials to support decision making at the primary care level.

Dataset Information

CT-Based Commercial Software Applications: Improving Patient Care Through Accurate COPD Subtyping.

Publications

CT-Based Commercial Software Applications: Improving Patient Care Through Accurate COPD Subtyping.

Similar Datasets

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