Dataset Information

Clustering analysis of HRCT parameters measured using a texture-based automated system: relationship with clinical outcomes of IPF.

ABSTRACT:

Purpose

The extent of honeycombing and reticulation predict the clinical prognosis of IPF. Emphysema, consolidation, and ground glass opacity are visible in HRCT scans. To date, there have been few comprehensive studies that have used these parameters. We conducted automated quantitative analysis to identify predictive parameters for clinical outcomes and then grouped the subjects accordingly.

Methods

CT images were obtained while patients held their breath at full inspiration. Parameters were analyzed using an automated lung texture quantification system. Cluster analysis was conducted on 159 IPF patients and clinical profiles were compared between clusters in terms of survival.

Results

Kaplan-Meier analysis revealed that survival rates declined as fibrosis, reticulation, honeycombing, consolidation, and emphysema scores increased. Cox regression analysis revealed that reticulation had the most significant impact on survival rate, followed by honeycombing, consolidation, and emphysema scores. Hierarchical and K-means cluster analyses revealed 3 clusters. Cluster 1 (n = 126) with the lowest values for all parameters had the longest survival duration, and relatively-well preserved FVC and DLCO. Cluster 2 (n = 15) with high reticulation and consolidation scores had the lowest FVC and DLCO values with a predominance of female, while cluster 3 (n = 18) with high honeycombing and emphysema scores predominantly consisted of male smokers. Kaplan-Meier analysis revealed that cluster 2 had the lowest survival rate, followed by cluster 3 and cluster 1.

Conclusion

Automated quantitative CT analysis provides valuable information for predicting clinical outcomes, and clustering based on these parameters may help identify the high-risk group for management.

SUBMITTER: Lee JU

PROVIDER: S-EPMC11290077 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

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Publications

Clustering analysis of HRCT parameters measured using a texture-based automated system: relationship with clinical outcomes of IPF.

Lee Jong-Uk JU Park Jong-Sook JS Seo Eunjeong E Kim Jin Seol JS Lee Hae Ung HU Chang Yongjin Y Park Jai Seong JS Park Choon-Sik CS

BMC pulmonary medicine 20240730 1

<h4>Purpose</h4>The extent of honeycombing and reticulation predict the clinical prognosis of IPF. Emphysema, consolidation, and ground glass opacity are visible in HRCT scans. To date, there have been few comprehensive studies that have used these parameters. We conducted automated quantitative analysis to identify predictive parameters for clinical outcomes and then grouped the subjects accordingly.<h4>Methods</h4>CT images were obtained while patients held their breath at full inspiration. Pa ...[more]

PMID: 39080584

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Project description:Brown RH, Henderson RJ, Sugar EA, Holbrook JT, Wise RA, on behalf of the American Lung Association Airways Clinical Research Centers. Reproducibility of airway luminal size in asthma measured by HRCT. J Appl Physiol 123: 876-883, 2017. First published July 13, 2017; doi:10.1152/japplphysiol.00307.2017.-High-resolution CT (HRCT) is a well-established imaging technology used to measure lung and airway morphology in vivo. However, there is a surprising lack of studies examining HRCT reproducibility. The CPAP Trial was a multicenter, randomized, three-parallel-arm, sham-controlled 12-wk clinical trial to assess the use of a nocturnal continuous positive airway pressure (CPAP) device on airway reactivity to methacholine. The lack of a treatment effect of CPAP on clinical or HRCT measures provided an opportunity for the current analysis. We assessed the reproducibility of HRCT imaging over 12 wk. Intraclass correlation coefficients (ICCs) were calculated for individual airway segments, individual lung lobes, both lungs, and air trapping. The ICC [95% confidence interval (CI)] for airway luminal size at total lung capacity ranged from 0.95 (0.91, 0.97) to 0.47 (0.27, 0.69). The ICC (95% CI) for airway luminal size at functional residual capacity ranged from 0.91 (0.85, 0.95) to 0.32 (0.11, 0.65). The ICC measurements for airway distensibility index and wall thickness were lower, ranging from poor (0.08) to moderate (0.63) agreement. The ICC for air trapping at functional residual capacity was 0.89 (0.81, 0.94) and varied only modestly by lobe from 0.76 (0.61, 0.87) to 0.95 (0.92, 0.97). In stable well-controlled asthmatic subjects, it is possible to reproducibly image unstimulated airway luminal areas over time, by region, and by size at total lung capacity throughout the lungs. Therefore, any changes in luminal size on repeat CT imaging are more likely due to changes in disease state and less likely due to normal variability.NEW & NOTEWORTHY There is a surprising lack of studies examining the reproducibility of high-resolution CT in asthma. The current study examined reproducibility of airway measurements. In stable well-controlled asthmatic subjects, it is possible to reproducibly image airway luminal areas over time, by region, and by size at total lung capacity throughout the lungs. Therefore, any changes in luminal size on repeat CT imaging are more likely due to changes in disease state and less likely due to normal variability.

Project description:BackgroundAs automated echocardiographic analysis is increasingly utilized, continued evaluation within hospital settings is important to further understand its potential value. The importance of cardiac involvement in patients hospitalized with COVID-19 provides an opportunity to evaluate the feasibility and clinical relevance of automated analysis applied to limited echocardiograms.MethodsIn this multisite US cohort, the feasibility of automated AI analysis was evaluated on 558 limited echocardiograms in patients hospitalized with COVID-19. Reliability of automated assessment of left ventricular (LV) volumes, ejection fraction (EF), and LV longitudinal strain (LS) was assessed against clinically obtained measures and echocardiographic findings. Automated measures were evaluated against patient outcomes using ROC analysis, survival modeling, and logistic regression for the outcomes of 30-day mortality and in-hospital sequelae.ResultsFeasibility of automated analysis for both LVEF and LS was 87.5% (488/558 patients). AI analysis was performed with biplane method in 300 (61.5%) and single plane apical 4- or 2-chamber analysis in 136 (27.9%) and 52 (10.7%) studies, respectively. Clinical LVEF was assessed using visual estimation in 192 (39.3%), biplane in 163 (33.4%), and single plane or linear methods in 104 (21.2%) of the 488 studies; 29 (5.9%) studies did not have clinically reported LVEF. LV LS was clinically reported in 80 (16.4%). Consistency between automated and clinical values demonstrated Pearson's R, root mean square error (RMSE) and intraclass correlation coefficient (ICC) of 0.61, 11.3% and 0.72, respectively, for LVEF; 0.73, 3.9% and 0.74, respectively for LS; 0.76, 24.4ml and 0.87, respectively, for end-diastolic volume; and 0.82, 12.8 ml, and 0.91, respectively, for end-systolic volume. Abnormal automated measures of LVEF and LS were associated with LV wall motion abnormalities, left atrial enlargement, and right ventricular dysfunction. Automated analysis was associated with outcomes, including survival.ConclusionAutomated analysis was highly feasible on limited echocardiograms using abbreviated protocols, consistent with equivalent clinically obtained metrics, and associated with echocardiographic abnormalities and patient outcomes.

Dataset Information

Clustering analysis of HRCT parameters measured using a texture-based automated system: relationship with clinical outcomes of IPF.

Purpose

Methods

Results

Conclusion

Publications

Clustering analysis of HRCT parameters measured using a texture-based automated system: relationship with clinical outcomes of IPF.

Similar Datasets

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