Segmentation of Juxtapleural Pulmonary Nodules Using a Robust Surface Estimate

An algorithm was developed to segment solid pulmonary nodules attached to the chest wall in computed tomography scans. The pleural surface was estimated and used to segment the nodule from the chest wall. To estimate the surface, a robust approach was used to identify points that lie on the pleural surface but not on the nodule. A 3D surface was estimated from the identified surface points. The segmentation performance of the algorithm was evaluated on a database of 150 solid juxtapleural pulmonary nodules. Segmented images were rated on a scale of 1 to 4 based on visual inspection, with 3 and 4 considered acceptable. This algorithm offers a large improvement in the success rate of juxtapleural nodule segmentation, successfully segmenting 98.0% of nodules compared to 81.3% for a previously published plane-fitting algorithm, which will provide for the development of more robust automated nodule measurement methods

AI-Enabled CT Cardiac Chamber Volumetry Predicts Atrial Fibrillation and Stroke Comparable to MRI

BackgroundAI-CAC provides more actionable information than the Agatston coronary artery calcium (CAC) score. We have recently shown in the MESA (Multi-Ethnic Study of Atherosclerosis) that AI-CAC automated left atrial (LA) volumetry enabled prediction of atrial fibrillation (AF) as early as 1 year.ObjectivesIn this study, the authors evaluated the performance of AI-CAC LA volumetry versus LA measured by human experts using cardiac magnetic resonance imaging (CMRI) for predicting incident AF and stroke and compared them with Cohorts for Heart and Aging Research in Genomic Epidemiology model for atrial fibrillation (CHARGE-AF) risk score, Agatston score, and N-terminal pro b-type natriuretic peptide (NT-proBNP).MethodsWe used 15-year outcomes data from 3,552 asymptomatic individuals (52.2% women, age 61.7 ± 10.2 years) who underwent both CAC scans and CMRI in the MESA baseline examination. CMRI LA volume was previously measured by human experts. Data on NT-proBNP, CHARGE-AF risk score, and the Agatston score were obtained from MESA. Discrimination was assessed using the time-dependent area under the curve.ResultsOver 15 years follow-up, 562 cases of AF and 140 cases of stroke accrued. The area under the curve for AI-CAC versus CMRI volumetry for AF (0.802 vs 0.798) and stroke (0.762 vs 0.751) were not significantly different. AI-CAC LA significantly improved the continuous net reclassification index for prediction of 5-year AF when added to CHARGE-AF risk score (0.23), NT-proBNP (0.37, 0.37), and Agatston score (0.44) (P for all <0.0001).ConclusionsAI-CAC automated LA volumetry and CMRI LA volume measured by human experts similarly predicted incident AF and stroke over 15 years. Further studies to investigate the clinical utility of AI-CAC for AF and stroke prediction are warranted

Emphysema Predicts Hospitalisation and Incident Airflow Obstruction among Older Smokers: A Prospective Cohort Study

Background Emphysema on CT is common in older smokers. We hypothesised that emphysema on CT predicts acute episodes of care for chronic lower respiratory disease among older smokers. Materials and Methods Participants in a lung cancer screening study age ≥60 years were recruited into a prospective cohort study in 2001–02. Two radiologists independently visually assessed the severity of emphysema as absent, mild, moderate or severe. Percent emphysema was defined as the proportion of voxels ≤ −910 Hounsfield Units. Participants completed a median of 5 visits over a median of 6 years of follow-up. The primary outcome was hospitalization, emergency room or urgent office visit for chronic lower respiratory disease. Spirometry was performed following ATS/ERS guidelines. Airflow obstruction was defined as FEV1/FVC ratio <0.70 and FEV1<80% predicted. Results Of 521 participants, 4% had moderate or severe emphysema, which was associated with acute episodes of care (rate ratio 1.89; 95% CI: 1.01–3.52) adjusting for age, sex and race/ethnicity, as was percent emphysema, with similar associations for hospitalisation. Emphysema on visual assessment also predicted incident airflow obstruction (HR 5.14; 95% CI 2.19–21.1). Conclusion Visually assessed emphysema and percent emphysema on CT predicted acute episodes of care for chronic lower respiratory disease, with the former predicting incident airflow obstruction among older smokers

The Association of Organizational Readiness With Lung Cancer Screening Utilization.

INTRODUCTION: Lung cancer screening is widely underutilized. Organizational factors, such as readiness for change and belief in the value of change (change valence), may contribute to underutilization. The aim of this study was to evaluate the association between healthcare organizations preparedness and lung cancer screening utilization. METHODS: Investigators cross-sectionally surveyed clinicians, staff, and leaders at10 Veterans Affairs from November 2018 to February 2021 to assess organizational readiness to implement change. In 2022, investigators used simple and multivariable linear regression to evaluate the associations between facility-level organizational readiness to implement change and change valence with lung cancer screening utilization. Organizational readiness to implement change and change valence were calculated from individual surveys. The primary outcome was the proportion of eligible Veterans screened using low-dose computed tomography. Secondary analyses assessed scores by healthcare role. RESULTS: The overall response rate was 27.4% (n=1,049), with 956 complete surveys analyzed: median age of 49 years, 70.3% female, 67.6% White, 34.6% clinicians, 61.1% staff, and 4.3% leaders. For each 1-point increase in median organizational readiness to implement change and change valence, there was an associated 8.4-percentage point (95% CI=0.2, 16.6) and a 6.3-percentage point increase in utilization (95% CI= -3.9, 16.5), respectively. Higher clinician and staff median scores were associated with increased utilization, whereas leader scores were associated with decreased utilization after adjusting for other roles. CONCLUSIONS: Healthcare organizations with higher readiness and change valence utilized more lung cancer screening. These results are hypothesis generating. Future interventions to increase organizations preparedness, especially among clinicians and staff, may increase lung cancer screening utilization

Artificial intelligence applied to coronary artery calcium scans (AI-CAC) significantly improves cardiovascular events prediction

Coronary artery calcium (CAC) scans contain valuable information beyond the Agatston Score which is currently reported for predicting coronary heart disease (CHD) only. We examined whether new artificial intelligence (AI) applied to CAC scans can predict non-CHD events, including heart failure, atrial fibrillation, and stroke. We applied AI-enabled automated cardiac chambers volumetry and calcified plaque characterization to CAC scans (AI-CAC) of 5830 asymptomatic individuals (52.2% women, age 61.7 ± 10.2 years) in the multi-ethnic study of atherosclerosis during 15 years of follow-up, 1773 CVD events accrued. The AUC at 1-, 5-, 10-, and 15-year follow-up for AI-CAC vs. Agatston score was (0.784 vs. 0.701), (0.771 vs. 0.709), (0.789 vs. 0.712) and (0.816 vs. 0.729) (p &lt; 0.0001 for all), respectively. AI-CAC plaque characteristics, including number, location, density, plus number of vessels, significantly improved CHD prediction in the CAC 1-100 cohort vs. Agatston Score. AI-CAC significantly improved the Agatston score for predicting all CVD events

Volumetric Measurements of Lung Nodules with Multi-Detector Row CT: Effect of Changes in Lung Volume

OBJECTIVE: To evaluate how changes in lung volume affect volumetric measurements of lung nodules using a multi-detector row CT. MATERIALS AND METHODS: Ten subjects with asthma or chronic bronchitis who had one or more lung nodules were included. For each subject, two sets of CT images were obtained at inspiration and at expiration. A total of 33 nodules (23 nodules > or =3 mm) were identified and their volume measured using a semiautomatic volume measurement program. Differences between nodule volume on inspiration and expiration were compared using the paired t-test. Percent differences, between on inspiration and expiration, in nodule attenuation, total lung volume, whole lung attenuation, and regional lung attenuation, were computed and compared with percent difference in nodule volume determined by linear correlation analysis. RESULTS: The difference in nodule volume observed between inspiration and expiration was significant (p or =3 mm. The volume of nodules was measured to be larger on expiration CT than on inspiration CT (28 out of 33 nodules; 19 out of 23 nodules > or =3 mm). A statistically significant correlation was found between the percent difference of lung nodule volume and lung volume or regional lung attenuation (p or =3 mm. CONCLUSION: Volumetric measurements of pulmonary nodules were significantly affected by changes in lung volume. The variability in this respiration-related measurement should be considered to determine whether growth has occurred in a lung nodule.Supported by in part NIH NHLBI, RO1 HL 69149 and by a grant from Electronics and Telecommunications Research Institute

From the International Association for the Study of Lung Cancer Early Detection and Screening Committee: Terminology Issues in Screening and Early Detection of Lung Cancer-International Association for the Study of Lung Cancer Early Detection and Screening Committee Expert Group Recommendations.

IntroductionTo facilitate global implementation of lung cancer (LC) screening and early detection in a quality assured and consistent manner, common terminology is needed. Researchers and clinicians within different specialties may use the same terms but with different meanings or different terms for the same intended meanings.MethodsThe Diagnostics Working Group of the International Association for the Study of Lung Cancer Early Detection and Screening Committee has analyzed and discussed relevant terms used on a regular basis and suggests recommendations for consensus definitions of terminology applicable in this setting. We explored how to reach consensus to define relevant and unambiguous terminology for use by health care providers, researchers, patients, screening participants, and family.ResultsTerms and definitions for epidemiologic and health-economical purposes included the following: standardized incidence and mortality rates, LC-specific survival, long-term survival and cure rates, overdiagnosis, overtreatment, and undertreatment. Terms and definitions for defining screening findings included the following: positive, false-positive, negative, false-negative, and indeterminate findings and additional and incidental findings. Terms and definitions for describing parameters in screening programs included the following: opportunistic versus programmatic screening, screening rounds, interval or interim diagnoses, and invasive and minimally invasive procedures. Terms and definitions for shared decision-making included the following: LC screening-possible harms and risks and LC risk and modifiers prior and posterior to a measure.ConclusionsA common set of terminology with standard definitions is recommended for describing clinical LC screening programs, the discussion about effectiveness and outcomes, or the clinical setting. The use of the terms should be clearly defined and explained

The Lung Image Database Consortium (LIDC) Data Collection Process for Nodule Detection and Annotation

RATIONALE AND OBJECTIVES: The Lung Image Database Consortium (LIDC) is developing a publicly available database of thoracic computed tomography (CT) scans as a medical imaging research resource to promote the development of computer-aided detection or characterization of pulmonary nodules. To obtain the best estimate of the location and spatial extent of lung nodules, expert thoracic radiologists reviewed and annotated each scan. Because a consensus panel approach was neither feasible nor desirable, a unique two-phase, multicenter data collection process was developed to allow multiple radiologists at different centers to asynchronously review and annotate each CT scan. This data collection process was also intended to capture the variability among readers.MATERIALS AND METHODS: Four radiologists reviewed each scan using the following process. In the first or "blinded" phase, each radiologist reviewed the CT scan independently. In the second or "unblinded" review phase, results from all four blinded reviews were compiled and presented to each radiologist for a second review, allowing the radiologists to review their own annotations together with the annotations of the other radiologists. The results of each radiologist's unblinded review were compiled to form the final unblinded review. An XML-based message system was developed to communicate the results of each reading.RESULTS: This two-phase data collection process was designed, tested, and implemented across the LIDC. More than 500 CT scans have been read and annotated using this method by four expert readers; these scans either are currently publicly available at http://ncia.nci.nih.gov or will be in the near future.CONCLUSIONS: A unique data collection process was developed, tested, and implemented that allowed multiple readers at distributed sites to asynchronously review CT scans multiple times. This process captured the opinions of each reader regarding the location and spatial extent of lung nodules