Clinical and Imaging Characteristics of SARS-CoV-2 Breakthrough Infection in Hospitalized Immunocompromised Patients.

OBJECTIVE: To evaluate the clinical and imaging characteristics of SARS-CoV-2 breakthrough infection in hospitalized immunocompromised patients in comparison with immunocompetent patients. MATERIALS AND METHODS: This retrospective study analyzed consecutive adult patients hospitalized for COVID-19 who received at least one dose of the SARS-CoV-2 vaccine at two academic medical centers between June 2021 and December 2022. Immunocompromised patients (with active solid organ cancer, active hematologic cancer, active immune-mediated inflammatory disease, status post solid organ transplantation, or acquired immune deficiency syndrome) were compared with immunocompetent patients. Multivariable logistic regression analysis was performed to evaluate the effect of immune status on severe clinical outcomes (in-hospital death, mechanical ventilation, or intensive care unit admission), severe radiologic pneumonia (≥ 25% of lung involvement), and typical CT pneumonia. RESULTS: Of 2218 patients (mean age, 69.5 ± 16.1 years), 274 (12.4%), and 1944 (87.6%) were immunocompromised an immunocompetent, respectively. Patients with active solid organ cancer and patients status post solid organ transplantation had significantly higher risks for severe clinical outcomes (adjusted odds ratio = 1.58 [95% confidence interval {CI}, 1.01-2.47], P = 0.042; and 3.12 [95% CI, 1.47-6.60], P = 0.003, respectively). Patient status post solid organ transplantation and patients with active hematologic cancer were associated with increased risks for severe pneumonia based on chest radiographs (2.96 [95% CI, 1.54-5.67], P = 0.001; and 2.87 [95% CI, 1.50-5.49], P = 0.001, respectively) and for typical CT pneumonia (9.03 [95% CI, 2.49-32.66], P < 0.001; and 4.18 [95% CI, 1.70-10.25], P = 0.002, respectively). CONCLUSION: Immunocompromised patients with COVID-19 breakthrough infection showed an increased risk of severe clinical outcome, severe pneumonia based on chest radiographs, and typical CT pneumonia. In particular, patients status post solid organ transplantation was specifically found to be associated with a higher risk of all three outcomes than hospitalized immunocompetent patients.

Coronary Artery Calcification on Low-Dose Lung Cancer Screening CT in South Korea: Visual and Artificial Intelligence-Based Assessment and Association With Cardiovascular Events.

BACKGROUND. Coronary artery calcification (CAC) on lung cancer screening low-dose chest CT (LDCT) is a cardiovascular risk marker. South Korea was the first Asian country to initiate a national LDCT lung cancer screening program, although CAC-related outcomes are poorly explored. OBJECTIVE. The purpose of this article is to evaluate CAC prevalence and severity using visual analysis and artificial intelligence (AI) methods and to characterize CAC's association with major adverse cardiovascular events (MACEs) in patients undergoing LDCT in Korea's national lung cancer screening program. METHODS. This retrospective study included 1002 patients (mean age, 62.4 ± 5.4 [SD] years; 994 men, eight women) who underwent LDCT at two Korean medical centers between April 2017 and May 2023 as part of Korea's national lung cancer screening program. Two radiologists independently assessed CAC presence and severity using visual analysis, consulting a third radiologist to resolve differences. Two AI software applications were also used to assess CAC presence and severity. MACE occurrences were identified by EMR review. RESULTS. Interreader agreement for CAC presence and severity, expressed as kappa, was 0.793 and 0.671, respectively. CAC prevalence was 53.4% by consensus visual assessment, 60.1% by AI software I, and 56.6% by AI software II. CAC severity was mild, moderate, and severe by consensus visual analysis in 28.0%, 10.3%, and 15.1%; by AI software I in 39.9%, 14.0%, and 6.2%; and by AI software II in 34.9%, 14.3%, and 7.3%. MACEs occurred in 36 of 625 (5.6%) patients with follow-up after LDCT (median, 1108 days). MACE incidence in patients with no, mild, moderate, and severe CAC for consensus visual analysis was 1.1%, 5.0%, 2.9%, and 8.6%, respectively (p < .001); for AI software I, it was 1.3%, 3.0%, 7.9%, and 11.3% (p < .001); and for AI software II, it was 1.2%, 3.4%, 7.7%, and 9.6% (p < .001). CONCLUSION. For Korea's national lung cancer screening program, MACE occurrence increased significantly with increasing CAC severity, whether assessed by visual analysis or AI software. The study is limited by the large sex imbalance for Korea's national lung cancer screening program. CLINICAL IMPACT. The findings provide reference data for health care practitioners engaged in developing and overseeing national lung cancer screening programs, highlighting the importance of routine CAC evaluation.

Altered brain morphology and functional connectivity in postmenopausal women: automatic segmentation of whole-brain and thalamic subnuclei and resting-state fMRI.

The transition to menopause is associated with various physiological changes, including alterations in brain structure and function. However, menopause-related structural and functional changes are poorly understood. The purpose of this study was not only to compare the brain volume changes between premenopausal and postmenopausal women, but also to evaluate the functional connectivity between the targeted brain regions associated with structural atrophy in postmenopausal women. Each 21 premenopausal and postmenopausal women underwent magnetic resonance imaging (MRI). T1-weighted MRI and resting-state functional MRI data were used to compare the brain volume and seed-based functional connectivity, respectively. In statistical analysis, multivariate analysis of variance, with age and whole brain volume as covariates, was used to evaluate surface areas and subcortical volumes between the two groups. Postmenopausal women showed significantly smaller cortical surface, especially in the left medial orbitofrontal cortex (mOFC), right superior temporal cortex, and right lateral orbitofrontal cortex, compared to premenopausal women (p < 0.05, Bonferroni-corrected) as well as significantly decreased functional connectivity between the left mOFC and the right thalamus was observed (p < 0.005, Monte-Carlo corrected). Although postmenopausal women did not show volume atrophy in the right thalamus, the volume of the right pulvinar anterior, which is one of the distinguished thalamic subnuclei, was significantly decreased (p < 0.05, Bonferroni-corrected). Taken together, our findings suggest that diminished brain volume and functional connectivity may be linked to menopause-related symptoms caused by the lower sex hormone levels.

Cardiac Magnetic Resonance Imaging Findings and Clinical Features of COVID-19 Vaccine-Associated Myocarditis, Compared With Those of Other Types of Myocarditis.

BACKGROUND: To compare the clinical and cardiac magnetic resonance (CMR) imaging findings of coronavirus disease 2019 (COVID-19) vaccine-associated myocarditis (VAM) with those of other types of myocarditis. METHODS: From January 2020 to March 2022, a total of 39 patients diagnosed with myocarditis via CMR according to the Modified Lake Louise criteria were included in the present study. The patients were classified into two groups based on their vaccination status: COVID-19 VAM and other types of myocarditis not associated with COVID-19 vaccination. Clinical outcomes, including the development of clinically significant arrhythmias, sudden cardiac arrest, and death, and CMR imaging features were compared between COVID-19 VAM and other types of myocarditis. RESULTS: Of the 39 included patients (mean age, 39 years ± 16.4 [standard deviation]; 23 men), 23 (59%) had COVID-19 VAM and 16 (41%) had other types of myocarditis. The occurrence of clinical adverse events did not differ significantly between the two groups. As per the CMR imaging findings, the presence and dominant pattern of late gadolinium enhancement did not differ significantly between the two groups. The presence of high native T1 or T2 values was not significantly different between the two groups. Although the native T1 and T2 values tended to be lower in COVID-19 VAM than in other types of myocarditis, there were no statistically significant differences between the native T1 and T2 values in the two groups. CONCLUSION: The present study demonstrated that the CMR imaging findings and clinical outcomes of COVID-19 VAM did not differ significantly from those of other types of myocarditis during hospitalization.

Pretreatment Interstitial Lung Abnormalities Detected on Abdominal Computed Tomography Scans in Prostate Cancer Patients.

OBJECTIVE: Prostate cancer and interstitial lung abnormality (ILA) share similar risk factor, which is men and older age. The purpose of this study was to investigate the prevalence of pretreatment ILA among prostate cancer patients who underwent abdominal computed tomography (CT) within 1 year at their first visit to the urology department. In addition, we aimed to assess the association between pretreatment ILA and long-term survival in prostate cancer patients. METHODS: This study was conducted in patients who had a first visit for prostate cancer at urology department between 2005 and 2016 and underwent an abdominal CT within 1 year. A thoracic radiologist evaluated the presence of ILA through inspecting the lung base scanned on an abdominal CT. The association between pretreatment ILA and survival was assessed using Kaplan-Meier analysis with log-rank test. Specific survival rates at 12, 36, and 60 months according to the presence of ILA were evaluated using z -test. Cox regression analysis was used to assess the risk factors of mortality. RESULTS: A total of 173 patients were included (mean age, 70.23 ± 7.98 years). Pretreatment ILA was observed in 10.4% of patients. Patients with ILA were more likely to be older and current smokers. Pretreatment ILA was associated with poor survival ( P < 0.001). Age ≥70 years (hazards ratio [HR], 1.98; 95% confidence interval [CI], 1.24-3.16; P = 0.004), metastatic stage (HR, 2.26; 95% CI, 1.36-3.74; P = 0.002), and ILA (HR, 1.96; 95% CI, 1.06-3.60; P = 0.031) were the independent risk factors of mortality. An ILA (HR, 3.94; 95% CI, 1.78-8.72; P = 0.001) was the only independent risk factor of mortality in localized stage prostate cancer patients. CONCLUSIONS: This study provides important insights into the unexplored effect of pretreatment ILA in prostate cancer patients. Pretreatment ILAs were observed considerably in the lung bases scanned on the abdominal CT scans among prostate cancer patients. Furthermore, pretreatment ILAs were the risk factor of mortality. Therefore, lung bases should be routinely inspected in the abdominal CT scans of prostate cancer patients. This result may help clinicians in establishing personalized management strategy of prostate cancer patients.

Development and Validation of a Robust and Interpretable Early Triaging Support System for Patients Hospitalized With COVID-19: Predictive Algorithm Modeling and Interpretation Study.

BACKGROUND: Robust and accurate prediction of severity for patients with COVID-19 is crucial for patient triaging decisions. Many proposed models were prone to either high bias risk or low-to-moderate discrimination. Some also suffered from a lack of clinical interpretability and were developed based on early pandemic period data. Hence, there has been a compelling need for advancements in prediction models for better clinical applicability. OBJECTIVE: The primary objective of this study was to develop and validate a machine learning-based Robust and Interpretable Early Triaging Support (RIETS) system that predicts severity progression (involving any of the following events: intensive care unit admission, in-hospital death, mechanical ventilation required, or extracorporeal membrane oxygenation required) within 15 days upon hospitalization based on routinely available clinical and laboratory biomarkers. METHODS: We included data from 5945 hospitalized patients with COVID-19 from 19 hospitals in South Korea collected between January 2020 and August 2022. For model development and external validation, the whole data set was partitioned into 2 independent cohorts by stratified random cluster sampling according to hospital type (general and tertiary care) and geographical location (metropolitan and nonmetropolitan). Machine learning models were trained and internally validated through a cross-validation technique on the development cohort. They were externally validated using a bootstrapped sampling technique on the external validation cohort. The best-performing model was selected primarily based on the area under the receiver operating characteristic curve (AUROC), and its robustness was evaluated using bias risk assessment. For model interpretability, we used Shapley and patient clustering methods. RESULTS: Our final model, RIETS, was developed based on a deep neural network of 11 clinical and laboratory biomarkers that are readily available within the first day of hospitalization. The features predictive of severity included lactate dehydrogenase, age, absolute lymphocyte count, dyspnea, respiratory rate, diabetes mellitus, c-reactive protein, absolute neutrophil count, platelet count, white blood cell count, and saturation of peripheral oxygen. RIETS demonstrated excellent discrimination (AUROC=0.937; 95% CI 0.935-0.938) with high calibration (integrated calibration index=0.041), satisfied all the criteria of low bias risk in a risk assessment tool, and provided detailed interpretations of model parameters and patient clusters. In addition, RIETS showed potential for transportability across variant periods with its sustainable prediction on Omicron cases (AUROC=0.903, 95% CI 0.897-0.910). CONCLUSIONS: RIETS was developed and validated to assist early triaging by promptly predicting the severity of hospitalized patients with COVID-19. Its high performance with low bias risk ensures considerably reliable prediction. The use of a nationwide multicenter cohort in the model development and validation implicates generalizability. The use of routinely collected features may enable wide adaptability. Interpretations of model parameters and patients can promote clinical applicability. Together, we anticipate that RIETS will facilitate the patient triaging workflow and efficient resource allocation when incorporated into a routine clinical practice.

Erratum: Correction of Affiliations in the Article "Establishment of a Nationwide Korean Imaging Cohort of Coronavirus Disease 2019".

This corrects the article on p. e413 in vol. 35, PMID: 33258333.

Correction: Deep Learning With Chest Radiographs for Making Prognoses in Patients With COVID-19: Retrospective Cohort Study.

[This corrects the article DOI: 10.2196/42717.].

Comparison of Clinical Outcomes and Imaging Features in Hospitalized Patients with SARS-CoV-2 Omicron Subvariants.

Background Differences in the clinical and radiological characteristics of SARS-CoV-2 Omicron subvariants have not been well studied. Purpose To compare clinical disease severity and radiologically severe pneumonia in patients with COVID-19 hospitalized during a period of either Omicron BA.1/BA.2 or Omicron BA.5 subvariant predominance. Materials and Methods This multicenter retrospective study, included patients registered in the Korean Imaging Cohort of COVID-19 database who were hospitalized for COVID-19 between January and December 2022. Publicly available relative variant genome frequency data were used to determine the dominant periods of Omicron BA.1/BA.2 subvariants (January 17 to June 20, 2022) and the Omicron BA.5 subvariant (July 4 to December 5, 2022). Clinical outcomes and imaging pneumonia outcomes based on chest radiography and CT were compared among predominant subvariants using multivariable analyses adjusted for covariates. Results Of 1916 confirmed patients with COVID-19 (mean age, 72 years ± 16 [SD]; 1019 males), 1269 were registered during the Omicron BA.1/BA.2 subvariant dominant period and 647 during the Omicron BA.5 subvariant dominant period. Patients in the BA.5 group showed lower odds of high-flow O2 requirement (adjusted odds ratio [OR], 0.75 [95% CI: 0.57, 0.99]; P = .04), mechanical ventilation (adjusted OR, 0.49 [95% CI: 0.34, 0.72]; P < .001]), and death (adjusted OR, 0.47 [95% CI: 0.33, 0.68]; P <.001) than those in the BA.1/BA.2 group. Additionally, the BA.5 group had lower odds of severe pneumonia on chest radiographs (adjusted OR, 0.68 [95% CI: 0.53, 0.88]; P = .004) and higher odds of atypical pattern pneumonia on CT images (adjusted OR, 1.81 [95% CI: 1.26, 2.58]; P = .001) than the BA.1/BA.2 group. Conclusions Patients hospitalized during the period of Omicron BA.5 subvariant predominance had lower odds of clinical and pneumonia severity than those hospitalized during the period of Omicron BA.1/BA.2 predominance, even after adjusting for covariates. See also the editorial by Hammer in this issue.

Survival impact of fibrotic interstitial lung abnormalities in resected stage IA non-small cell lung cancer.

OBJECTIVES: To assess the association between fibrotic interstitial lung abnormalities (ILAs) and long-term survival in patients with resected Stage IA non-small cell lung cancer (NSCLC). METHODS: Data of patients who underwent curative resection of pathological Stage IA NSCLC between 2010 and 2015 were retrospectively analysed. ILAs were evaluated using pre-operative high-resolution CT scans. The association between ILAs and cause-specific mortality was assessed via Kaplan-Meier analysis and the log-rank test. Cox proportional hazards regression was performed to determine the risk factors for cause-specific death. RESULTS: Overall, 228 patients were identified (63.27 ± 8.54 years, 133 men [58.3%]). ILAs were detected in 24 patients (10.53%). Fibrotic ILAs were observed in 16 patients (7.02%), and there was a significantly higher cause-specific mortality rate among patients with fibrotic ILAs compared with patients with no ILAs (p < 0.001). Patients with fibrotic ILAs had a significantly higher cause-specific mortality rate than patients without ILAs at 5 post-operative years (survival rate: 61.88% vs 93.03%, p < 0.001). The presence of afibrotic ILA was an independent risk factor for cause-specific death (adjusted hazard ratio = 3.22; 95% confidence interval: 1.10, 9.44; p = 0.033). CONCLUSION: The presence of afibrotic ILA was a risk factor for cause-specific death in patients with resected Stage IA NSCLC. Radiologists and clinicians should be familiar with the relatively new concept of ILAs and understand the close association between ILA status and long-term survival in resected Stage IA NSCLC. Patients presenting fibrotic ILAs should receive appropriate surveillance and management to optimise prognosis. ADVANCES IN KNOWLEDGE: Fibrotic ILAs are important findings implicated inthe long-term survival of patients with resected Stage IA NSCLC. Specific management is required for this group.

Effect of Interstitial Lung Abnormality on Concurrent Chemoradiotherapy-treated Stage III Non-small Cell Lung Cancer Patients.

BACKGROUND/AIM: Pre-treatment interstitial lung abnormality (ILA) is associated with post-cancer treatment adverse events and high mortality rate in lung cancer patients. This study aimed to assess whether ILA affects the survival and development of symptomatic radiation pneumonitis (RP) in unresectable stage III non-small cell lung cancer (NSCLC) patients who had undergone definitive concurrent chemoradiotherapy (CCRT). PATIENTS AND METHODS: Data of stage III NSCLC patients who underwent definitive CCRT between January 2010 and November 2017 were retrospectively collected. Univariate and multivariate regression analyses were performed to evaluate the risk factors for symptomatic RP. The association between pre-treatment ILA and survival was assessed using Kaplan-Meier analysis with log-rank test and Cox proportional hazards regression. RESULTS: This study included 201 patients (188 men) of a mean age of 64.7±7.3 years. Pre-treatment ILA and fibrotic ILA were observed in 21.9% and 12.9% of the patients, respectively. Symptomatic RP (grade ≥2) occurred in 13.5% of the patients. Fibrotic ILA was a significant risk factor for grade ≥2 RP and grade ≥3 RP (p=0.004 and 0.033, respectively). The survival rate was significantly poorer in patients with fibrotic ILA than in those without ILA. Cox proportional hazards regression revealed that fibrotic ILA was an independent risk factor for mortality (p<0.001). CONCLUSION: Pre-treatment fibrotic ILA is significantly associated with symptomatic RP and poor survival in unresectable stage III NSCLC patients who have undergone definitive CCRT. CCRT should be cautiously performed in patients presenting pre-treatment fibrotic ILA to prevent adverse outcomes.

Increased Hippocampal-Inferior Temporal Gyrus White Matter Connectivity following Donepezil Treatment in Patients with Early Alzheimer's Disease: A Diffusion Tensor Probabilistic Tractography Study.

The incidence of Alzheimer's disease (AD) has been increasing each year, and a defective hippocampus has been primarily associated with an early stage of AD. However, the effect of donepezil treatment on hippocampus-related networks is unknown. Thus, in the current study, we evaluated the hippocampal white matter (WM) connectivity in patients with early-stage AD before and after donepezil treatment using probabilistic tractography, and we further determined the WM integrity and changes in brain volume. Ten patients with early-stage AD (mean age = 72.4 ± 7.9 years; seven females and three males) and nine healthy controls (HC; mean age = 70.7 ± 3.5 years; six females and three males) underwent a magnetic resonance (MR) examination. After performing the first MR examination, the patients received donepezil treatment for 6 months. The brain volumes and diffusion tensor imaging scalars of 11 regions of interest (the superior/middle/inferior frontal gyrus, the superior/middle/inferior temporal gyrus, the amygdala, the caudate nucleus, the hippocampus, the putamen, and the thalamus) were measured using MR imaging and DTI, respectively. Seed-based structural connectivity analyses were focused on the hippocampus. The patients with early AD had a lower hippocampal volume and WM connectivity with the superior frontal gyrus and higher mean diffusivity (MD) and radial diffusivity (RD) in the amygdala than HC (p < 0.05, Bonferroni-corrected). However, brain areas with a higher (or lower) brain volume and WM connectivity were not observed in the HC compared with the patients with early AD. After six months of donepezil treatment, the patients with early AD showed increased hippocampal-inferior temporal gyrus (ITG) WM connectivity (p < 0.05, Bonferroni-corrected).

Deep Learning With Chest Radiographs for Making Prognoses in Patients With COVID-19: Retrospective Cohort Study.

BACKGROUND: An artificial intelligence (AI) model using chest radiography (CXR) may provide good performance in making prognoses for COVID-19. OBJECTIVE: We aimed to develop and validate a prediction model using CXR based on an AI model and clinical variables to predict clinical outcomes in patients with COVID-19. METHODS: This retrospective longitudinal study included patients hospitalized for COVID-19 at multiple COVID-19 medical centers between February 2020 and October 2020. Patients at Boramae Medical Center were randomly classified into training, validation, and internal testing sets (at a ratio of 8:1:1, respectively). An AI model using initial CXR images as input, a logistic regression model using clinical information, and a combined model using the output of the AI model (as CXR score) and clinical information were developed and trained to predict hospital length of stay (LOS) ≤2 weeks, need for oxygen supplementation, and acute respiratory distress syndrome (ARDS). The models were externally validated in the Korean Imaging Cohort of COVID-19 data set for discrimination and calibration. RESULTS: The AI model using CXR and the logistic regression model using clinical variables were suboptimal to predict hospital LOS ≤2 weeks or the need for oxygen supplementation but performed acceptably in the prediction of ARDS (AI model area under the curve [AUC] 0.782, 95% CI 0.720-0.845; logistic regression model AUC 0.878, 95% CI 0.838-0.919). The combined model performed better in predicting the need for oxygen supplementation (AUC 0.704, 95% CI 0.646-0.762) and ARDS (AUC 0.890, 95% CI 0.853-0.928) compared to the CXR score alone. Both the AI and combined models showed good calibration for predicting ARDS (P=.079 and P=.859). CONCLUSIONS: The combined prediction model, comprising the CXR score and clinical information, was externally validated as having acceptable performance in predicting severe illness and excellent performance in predicting ARDS in patients with COVID-19.

Comparison of Coronary Computed Tomography Angiography Image Quality With High-concentration and Low-concentration Contrast Agents: The Randomized CONCENTRATE Trial.

PURPOSE: To confirm that the image quality of coronary computed tomography (CT) angiography with a low tube voltage (80 to 100 kVp), iterative reconstruction, and low-concentration contrast agents (iodixanol 270 to 320 mgI/mL) was not inferior to that with conventional high tube voltage (120 kVp) and high-concentration contrast agent (iopamidol 370 mgI/mL). MATERIALS AND METHODS: This prospective, multicenter, noninferiority, randomized trial enrolled a total of 318 patients from 8 clinical sites. All patients were randomly assigned 1: 1: 1 for each contrast medium of 270, 320, and 370 mgI/mL. CT scans were taken with a standard protocol in the high-concentration group (370 mgI/mL) and with 20 kVp lower protocol in the low-concentration group (270 or 320 mgI/mL). Image quality and radiation dose were compared between the groups. Image quality was evaluated with a score of 1 to 4 as subject image quality. RESULTS: The mean HU, signal-to-noise ratio, and contrast-to-noise ratio of the 3 groups were significantly different (all P<0.0001). The signal-to-noise ratio and contrast-to-noise ratio of the low-concentration groups were significantly lower than those of the high-concentration group (P<0.05). However, the image quality scores were not significantly different among the 3 groups (P=0.745). The dose length product and effective dose of the high-concentration group were significantly higher than those of the low-concentration group (P<0.0001 and 0.003, respectively). CONCLUSIONS: The CT protocol with iterative reconstruction and lower tube voltage for low-concentration contrast agents significantly reduced the effective radiation dose (mean: 3.7±2.7 to 4.1±3.1 mSv) while keeping the subjective image quality as good as the standard protocol (mean: 5.7±3.4 mSv).

Clinicoradiological Features of Pulmonary Cryptococcosis in Immunocompetent Patients.

Purpose: To assess the clinicoradiological features of pulmonary cryptococcosis in immunocompetent patients. Materials and Methods: This retrospective study included immunocompetent patients who had been diagnosed with pulmonary cryptococcosis on the histopathologic exam and underwent chest CT between January 2008 and November 2019. Imaging features were divided into major imaging patterns, distributions, and ancillary imaging findings. Univariable analysis was performed to evaluate clinicoradiological features according to the presence of serum cryptococcal antigen. Results: Thirty-one patients were evaluated (mean age: 60 years, range: 19-78 years). A single nodular lesion confined to a single lobe was the most common imaging pattern (14/31, 45.2%). Serum cryptococcal antigen tests were performed in 19 patients (19/31, 61.3%). The presence of serum cryptococcal antigen was observed in six patients (6/19, 31.6%), all of whom showed a consolidation-dominant pattern. The presence of serum cryptococcal antigen was significantly associated with the consolidation-dominant pattern compared to those associated with a nodule-dominant pattern (p = 0.011). Conclusion: A combination of CT findings of consolidation and a positive serum cryptococcal antigen test may be helpful for diagnosing pulmonary cryptococcosis in immunocompetent patients.

Prognostic significance of location index in resected T1-sized early-stage non-small cell lung cancer.

BACKGROUND: While the central location is a known adverse prognostic factor in lung cancer, a precise definition of central lung cancer has not yet emerged. PURPOSE: To determine the prognostic significance of central lung cancer (defined by location index) in resected T1-sized early-stage non-small cell lung cancer (NSCLC). MATERIAL AND METHODS: Patients with resected T1-sized early-stage NSCLC between 2010 and 2015 at a single tertiary cancer center were retrospectively reviewed. Central lung cancer was defined by a location index of the second tertile or less. Kaplan-Meier analysis with log-rank test and multivariable Cox regression analysis were performed to analyze the relationship between central lung cancer and the prognosis of relapse-free survival (RFS) and overall survival (OS). Inter-observer agreement was assessed using Cohen's kappa value and intraclass correlation coefficient (ICC). RESULTS: Overall, 289 patients (169 men; median age 65 years; interquartile range 58-70 years) were evaluated. Central lung cancer (defined by location index) was adversely associated with RFS (P = 0.005) and OS (P = 0.01). Multivariable Cox regression analysis showed that central lung cancer was independently associated with poor RFS (adjusted hazard ratio 1.91; 95% confidence interval [CI] 1.12-3.24; P = 0.017) and OS (adjusted hazard ratio 1.69; 95% CI 1.04-2.74; P = 0.033). Location index demonstrated excellent inter-observer agreement (Cohen's kappa value 0.88; 95% CI 0.82-0.93) with a high ICC (0.98; 95% CI 0.97-0.98). CONCLUSION: Central lung cancer defined by a location index of the second tertile or lower is an independent adverse prognostic factor in resected T1-sized early-stage NSCLC.

Association between myocardial ischemia and plaque characteristics in chronic total occlusion.

BACKGROUND: Myocardial ischemia varies in chronic total occlusion (CTO) despite the occluded artery. We analyzed whether it is associated with the plaque characteristics of the occluded segment. METHODS: We retrospectively enrolled 100 patients with CTO who underwent myocardial perfusion single-photon emission computed tomography (SPECT) and coronary computed tomography angiography (CCTA) within 2 months. CTO-related ischemia was classified as moderate to severe (summed difference score [SDS] of the CTO territory ≥ 5) or mild or none (SDS < 5) on SPECT. Using CCTA, the atherosclerotic plaques of the occluded segment were subdivided into low-density (- 100-30 HU), intermediate-density (31-350 HU), and high-density (351-1000 HU) plaques. The plaque composition was compared according to the severity of CTO-related ischemia. RESULTS: Moderate-to-severe CTO-related ischemia (n = 23) showed significantly higher proportion of intermediate-density plaques (72.4% vs. 64.0%), intermediate/low-density (7.10 vs. 3.65) and intermediate-to-high/low-density (7.78 vs. 3.80) plaque ratios, frequent shorter occlusion (30% vs. 6%), and lower volume (26.5 mm3 vs. 58.8 mm3) and proportion (11.4% vs. 20.8%) of low-density plaques. Multivariable analysis revealed significant associations between higher proportion of intermediate-density plaques and moderate-to-severe CTO-related ischemia, independent of occlusion length. CONCLUSION: Higher proportion of intermediate-density plaques in the occluded segment was associated with the moderate-to-severe CTO-related ischemia.

Prevalence and Long-term Outcomes of CT Interstitial Lung Abnormalities in a Health Screening Cohort.

Background The association between interstitial lung abnormalities (ILAs) and long-term outcomes has not been reported in Asian health screening populations. Purpose To investigate ILA prevalence in an Asian health screening cohort and determine rates and risks for ILA progression, lung cancer development, and mortality within the 10-year follow-up. Materials and Methods This observational, retrospective multicenter study included patients aged 50 years or older who underwent chest CT at three health screening centers over a 4-year period (2007-2010). ILA status was classified as none, equivocal ILA, and ILA (nonfibrotic or fibrotic). Progression was evaluated from baseline to the last follow-up CT examination, when available. The log-rank test was performed to compare mortality rates over time between ILA statuses. Multivariable Cox proportional hazards models were used to assess factors associated with hazards of ILA progression, lung cancer development, and mortality. Results Of the 2765 included patients (mean age, 59 years ± 7 [SD]; 2068 men), 94 (3%) had a finding of ILA (35 nonfibrotic and 59 fibrotic ILA) and 119 (4%) had equivocal ILA. The median time for CT follow-up and the entire observation was 8 and 12 years, respectively. ILA progression was observed in 80% (48 of 60) of patients with ILA over 8 years. Those with fibrotic and nonfibrotic ILA had a higher mortality rate than those without ILA (P < .001 and P = .01, respectively) over 12 years. Fibrotic ILA was independently associated with ILA progression (hazard ratio [HR], 10.3; 95% CI: 6.4, 16.4; P < .001), lung cancer development (HR, 4.4; 95% CI: 2.1, 9.1; P < .001), disease-specific mortality (HR, 6.7; 95% CI: 3.7, 12.2; P < .001), and all-cause mortality (HR, 2.5; 95% CI: 1.6, 3.8; P < .001) compared with no ILA. Conclusion The prevalence of interstitial lung abnormalities (ILAs) in an Asian health screening cohort was approximately 3%, and fibrotic ILA was an independent risk factor for ILA progression, lung cancer development, and mortality. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Hatabu and Hata in this issue.

SARS-CoV-2 Variants Infection in Relationship to Imaging-based Pneumonia and Clinical Outcomes.

Background Few reports have evaluated the effect of the SARS-CoV-2 variant and vaccination on the clinical and imaging features of COVID-19. Purpose To evaluate and compare the effect of vaccination and variant prevalence on the clinical and imaging features of infections by the SARS-CoV-2. Materials and Methods Consecutive adults hospitalized for confirmed COVID-19 at three centers (two academic medical centers and one community hospital) and registered in a nationwide open data repository for COVID-19 between August 2021 and March 2022 were retrospectively included. All patients had available chest radiographs or CT images. Patients were divided into two groups according to predominant variant type over the study period. Differences between clinical and imaging features were analyzed with use of the Pearson χ2 test, Fisher exact test, or the independent t test. Multivariable logistic regression analyses were used to evaluate the effect of variant predominance and vaccination status on imaging features of pneumonia and clinical severity. Results Of the 2180 patients (mean age, 57 years ± 21; 1171 women), 1022 patients (47%) were treated during the Delta variant predominant period and 1158 (53%) during the Omicron period. The Omicron variant prevalence was associated with lower pneumonia severity based on CT scores (odds ratio [OR], 0.71 [95% CI: 0.51, 0.99; P = .04]) and lower clinical severity based on intensive care unit (ICU) admission or in-hospital death (OR, 0.43 [95% CI: 0.24, 0.77; P = .004]) than the Delta variant prevalence. Vaccination was associated with the lowest odds of severe pneumonia based on CT scores (OR, 0.05 [95% CI: 0.03, 0.13; P < .001]) and clinical severity based on ICU admission or in-hospital death (OR, 0.15 [95% CI: 0.07, 0.31; P < .001]) relative to no vaccination. Conclusion The SARS-CoV-2 Omicron variant prevalence and vaccination were associated with better clinical outcomes and lower severe pneumonia risk relative to Delta variant prevalence. © RSNA, 2022 Supplemental material is available for this article. See also the editorial by Little in this issue.

A Radiomics Approach on Chest CT Distinguishes Primary Lung Cancer from Solitary Lung Metastasis in Colorectal Cancer Patients.

PURPOSE: This study utilized a radiomics approach combined with a machine learning algorithm to distinguish primary lung cancer (LC) from solitary lung metastasis (LM) in colorectal cancer (CRC) patients with a solitary pulmonary nodule (SPN). MATERIALS AND METHODS: In a retrospective study, 239 patients who underwent chest computerized tomography (CT) at three different institutions between 2011 and 2019 and were diagnosed as primary LC or solitary LM were included. The data from the first institution were divided into training and internal testing datasets. The data from the second and third institutions were used as an external testing dataset. Radiomic features were extracted from the intra and perinodular regions of interest (ROI). After a feature selection process, Support vector machine (SVM) was used to train models for classifying between LC and LM. The performances of the SVM classifiers were evaluated with both the internal and external testing datasets. The performances of the model were compared to those of two radiologists who reviewed the CT images of the testing datasets for the binary prediction of LC versus LM. RESULTS: The SVM classifier trained with the radiomic features from the intranodular ROI and achieved the sensitivity/specificity of 0.545/0.828 in the internal test dataset, and 0.833/0.964 in the external test dataset, respectively. The SVM classifier trained with the combined radiomic features from the intra- and perinodular ROIs achieved the sensitivity/specificity of 0.545/0.966 in the internal test dataset, and 0.833/1.000 in the external test data set, respectively. Two radiologists demonstrated the sensitivity/specificity of 0.545/0.966 and 0.636/0.828 in the internal test dataset, and 0.917/0.929 and 0.833/0.929 in the external test dataset, which were comparable to the performance of the model trained with the combined radiomics features. CONCLUSION: Our results suggested that the machine learning classifiers trained using radiomics features of SPN in CRC patients can be used to distinguish the primary LC and the solitary LM with a similar level of performance to radiologists.