Identifying subgroups of eating behavior traits unrelated to obesity using functional connectivity and feature representation learning.

Eating behavior is highly heterogeneous across individuals and cannot be fully explained using only the degree of obesity. We utilized unsupervised machine learning and functional connectivity measures to explore the heterogeneity of eating behaviors measured by a self-assessment instrument using 424 healthy adults (mean ± standard deviation [SD] age = 47.07 ± 18.89 years; 67% female). We generated low-dimensional representations of functional connectivity using resting-state functional magnetic resonance imaging and estimated latent features using the feature representation capabilities of an autoencoder by nonlinearly compressing the functional connectivity information. The clustering approaches applied to latent features identified three distinct subgroups. The subgroups exhibited different levels of hunger traits, while their body mass indices were comparable. The results were replicated in an independent dataset consisting of 212 participants (mean ± SD age = 38.97 ± 19.80 years; 35% female). The model interpretation technique of integrated gradients revealed that the between-group differences in the integrated gradient maps were associated with functional reorganization in heteromodal association and limbic cortices and reward-related subcortical structures such as the accumbens, amygdala, and caudate. The cognitive decoding analysis revealed that these systems are associated with reward- and emotion-related systems. Our findings provide insights into the macroscopic brain organization of eating behavior-related subgroups independent of obesity.

Effectiveness of COVID-19 Vaccines Over Time Against Clinical and Radiologic Outcomes Related to Severe SARS-CoV-2 Infection.

Background The impact of waning vaccine effectiveness on the severity of COVID-19-related findings discovered with radiologic examinations remains underexplored. Purpose To evaluate the effectiveness of vaccines over time against severe clinical and radiologic outcomes related to SARS-CoV-2 infections. Materials and Methods This multicenter retrospective study included patients in the Korean Imaging Cohort of COVID-19 database who were hospitalized for COVID-19 between June 2021 and December 2022. Patients who had received at least one dose of a SARS-CoV-2 vaccine were categorized based on the time elapsed between diagnosis and their last vaccination. Adjusted multivariable logistic regression analysis was used to estimate vaccine effectiveness against a composite of severe clinical outcomes (invasive ventilation, extracorporeal membrane oxygenation, or in-hospital death) and severe radiologic pneumonia (≥25% of lung involvement), and odds ratios (ORs) were compared between patients vaccinated within 90 days of diagnosis and those vaccinated more than 90 days before diagnosis. Results Of 4196 patients with COVID-19 (mean age, 66 years ± 17 [SD]; 2132 [51%] women, 2064 [49%] men), the ratio of severe pneumonia since their most recent vaccination was as follows: 90 days or less, 18% (277 of 1527); between 91 and 120 days, 22% (172 of 783); between 121 and 180 days, 27% (274 of 1032); between 181 and 240 days, 32% (159 of 496); and more than 240 days, 31% (110 of 358). Patients vaccinated more than 240 days before diagnosis showed increased odds of severe clinical outcomes compared with patients vaccinated within 90 days (OR = 1.94 [95% CI: 1.16, 3.24]; P = .01). Similarly, patients vaccinated more than 240 days before diagnosis showed increased odds of severe pneumonia on chest radiographs compared with patients vaccinated within 90 days (OR = 1.65 [95% CI: 1.13, 2.40]; P = .009). No difference in odds of severe clinical outcomes (P = .13 to P = .68) or severe pneumonia (P = .15 to P = .86) were observed between patients vaccinated 91-240 days before diagnosis and those vaccinated within 90 days of diagnosis. Conclusion Vaccine effectiveness against severe clinical outcomes and severe pneumonia related to SARS-CoV-2 infection gradually declined, with increased odds of both observed in patients vaccinated more than 240 days before diagnosis. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Wells in this issue.

Chronic Lung Injury after COVID-19 Pneumonia: Clinical, Radiologic, and Histopathologic Perspectives.

With the COVID-19 pandemic having lasted more than 3 years, concerns are growing about prolonged symptoms and respiratory complications in COVID-19 survivors, collectively termed post-COVID-19 condition (PCC). Up to 50% of patients have residual symptoms and physiologic impairment, particularly dyspnea and reduced diffusion capacity. Studies have also shown that 24%-54% of patients hospitalized during the 1st year of the pandemic exhibit radiologic abnormalities, such as ground-glass opacity, reticular opacity, bronchial dilatation, and air trapping, when imaged more than 1 year after infection. In patients with persistent respiratory symptoms but normal results at chest CT, dual-energy contrast-enhanced CT, xenon 129 MRI, and low-field-strength MRI were reported to show abnormal ventilation and/or perfusion, suggesting that some lung injury may not be detectable with standard CT. Histologic patterns in post-COVID-19 lung disease include fibrosis, organizing pneumonia, and vascular abnormality, indicating that different pathologic mechanisms may contribute to PCC. Therefore, a comprehensive imaging approach is necessary to evaluate and diagnose patients with persistent post-COVID-19 symptoms. This review will focus on the long-term findings of clinical and radiologic abnormalities and describe histopathologic perspectives. It also addresses advanced imaging techniques and deep learning approaches that can be applied to COVID-19 survivors. This field remains an active area of research, and further follow-up studies are warranted for a better understanding of the chronic stage of the disease and developing a multidisciplinary approach for patient management.

Transcriptomic Expression of T2-Inflammation Genes in Peripheral Blood Mononuclear Cells and Longitudinal Clinical Outcomes in Asthma: Insights from the COREA Study.

BACKGROUND: Gene expression can provide distinct information compared to clinical biomarkers in the context of longitudinal clinical outcomes in asthma patients. OBJECTIVE: This study examined the association between the gene expression levels of upstream (IL-25, IL-33, and TSLP) and downstream cytokines (IL-5, IL-4, and IL-13) in the T2 inflammatory pathway with a 12-month follow-up of exacerbation, lung function, and steroid use. METHODS: Transcriptomic sequencing analysis was performed on peripheral blood mononuclear cells from 279 adult asthmatics. Survival analysis and linear mixed-effect models were used to investigate potential differences between the high-level and low-level gene expression groups and the clinical outcomes. Analysis was performed separately for the upstream, downstream, and all 6 cytokines. RESULTS: In general, T2 inflammatory cytokine gene expression showed a weak correlation with blood eosinophil counts (all r < 0.1) and clinical outcomes. Among moderate-to-severe eosinophilic asthma (MSEA) patients, individuals with elevated levels of downstream cytokines were at increased risk of time-to-first exacerbation (p = 0.044) and a greater increase of inhaled corticosteroid use over time (p = 0.002) compared to those with lower gene expression. There was no association between baseline T2 inflammatory cytokine gene expression and the longitudinal changes in lung function over time among MSEA patients. CONCLUSION: These findings suggest that, among MSEA patients, the gene expression levels of downstream cytokines in the T2 inflammatory pathway may serve as indicators for endotyping asthma.

Validation of the Utility of the Genetically Shared Regions of Chromosomes (GD-ICS) Measuring Method in Identifying Complicated Genetic Relatedness.

BACKGROUND: Relatives share more genomic regions than unrelated individuals, with closer relatives sharing more regions. This concept, paired with the increased availability of high-throughput single nucleotide polymorphism (SNP) genotyping technologies, has made it feasible to measure the shared chromosomal regions between individuals to assess their level of relation to each other. However, such techniques have remained in the conceptual rather than practical stages in terms of applying measures or indices. Recently, we developed an index called "genetic distance-based index of chromosomal sharing (GD-ICS)" utilizing large-scale SNP data from Korean family samples and demonstrated its potential for practical applications in kinship determination. In the current study, we present validation results from various real cases demonstrating the utility of this method in resolving complex familial relationships where information obtained from traditional short tandem repeats (STRs) or lineage markers is inconclusive. METHODS: We obtained large-scale SNP data through microarray analysis from Korean individuals involving 13 kinship cases and calculated GD-ICS values using the method described in our previous study. Based on the GD-ICS reference constructed for Korean families, each disputed kinship was evaluated and validated using a combination of traditional STRs and lineage markers. RESULTS: The cases comprised those A) that were found to be inconclusive using the traditional approach, B) for which it was difficult to apply traditional testing methods, and C) that were more conclusively resolved using the GD-ICS method. This method has overcome the limitations faced by traditional STRs in kinship testing, particularly in a paternity case with STR mutational events and in confirming distant kinship where the individual of interest is unavailable for testing. It has also been demonstrated to be effective in identifying various relationships without specific presumptions and in confirming a lack of genetic relatedness between individuals. CONCLUSION: This method has been proven effective in identifying familial relationships across diverse complex and practical scenarios. It is not only useful when traditional testing methods fail to provide conclusive results, but it also enhances the resolution of challenging kinship cases, which suggests its applicability in various types of practical casework.

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.

Current and Emerging Knowledge in COVID-19.

COVID-19 has emerged as a pandemic leading to a global public health crisis of unprecedented morbidity. A comprehensive insight into the imaging of COVID-19 has enabled early diagnosis, stratification of disease severity, and identification of potential sequelae. The evolution of COVID-19 can be divided into early infectious, pulmonary, and hyperinflammatory phases. Clinical features, imaging features, and management are different among the three phases. In the early stage, peripheral ground-glass opacities are predominant CT findings, and therapy directly targeting SARS-CoV-2 is effective. In the later stage, organizing pneumonia or diffuse alveolar damage pattern are predominant CT findings and anti-inflammatory therapies are more beneficial. The risk of severe disease or hospitalization is lower in breakthrough or Omicron variant infection compared with nonimmunized or Delta variant infections. The protection rates of the fourth dose of mRNA vaccination were 34% and 67% against overall infection and hospitalizations for severe illness, respectively. After acute COVID-19 pneumonia, most residual CT abnormalities gradually decreased in extent, but they may remain as linear or multifocal reticular or cystic lesions. Advanced insights into the pathophysiologic and imaging features of COVID-19 along with vaccine benefits have improved patient care, but emerging knowledge of post-COVID-19 condition, or long COVID, also presents radiology with new challenges.

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.

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.

Tracking antigen-specific TCR clonotypes in SARS-CoV-2 infection reveals distinct severity trajectories.

Despite the importance of antigen-specific T cells in infectious disease, characterizing and tracking clonally amplified T cells during the progression of a patient's symptoms remain unclear. Here, we performed a longitudinal, in-depth single-cell multiomics analysis of samples from asymptomatic, mild, usual severe, and delayed severe patients of SARS-CoV-2 infection. Our in-depth analysis revealed that hyperactive or improper T-cell responses were more aggressive in delayed severe patients. Interestingly, tracking of antigen-specific T-cell receptor (TCR) clonotypes along the developmental trajectory indicated an attenuation in functional T cells upon severity. In addition, increased glycolysis and interleukin-6 signaling in the cytotoxic T cells were markedly distinct in delayed severe patients compared to usual severe patients, particularly in the middle and late stages of infection. Tracking B-cell receptor clonotypes also revealed distinct transitions and somatic hypermutations within B cells across different levels of disease severity. Our results suggest that single-cell TCR clonotype tracking can distinguish the severity of patients through immunological hallmarks, leading to a better understanding of the severity differences in and improving the management of infectious diseases by analyzing the dynamics of immune responses over time.

APP96-110 Elicits Neuroprotective Effects Following Ischemic Insult in Animal Models.

Competitive amyloidogenic pathways play an important role in many neurological diseases such as the onset of various degenerative diseases and ischemic stroke. Overexpression of amyloid precursor protein (APP) and amyloid-beta is modulated via the amyloidogenic pathway, which plays a crucial role in neuroinflammation. During ischemic conditions, the activity of the anti-inflammatory non-amyloidogenic pathway decreases, thus increasing the activity of amyloidogenic pathway. The soluble alpha form of APP (sAPPα), formed via the non-amyloidogenic pathway, exhibits neuroprotective effects against neurological diseases. sAPPα is thought to have a modulatory effect on several cell survival pathways, including its ability to inhibit the phosphoinositide 3-kinases (PI3K) pathway, thereby inhibiting the inflammatory response. The APP derivative, APP96-110, could act as a functional substitute for native sAPPα. Herein, we investigated whether APP96-110 has neuroprotective effects against neuroinflammation and damage following cerebral ischemic stroke. Treatment with diluted APP96-110 (0.005 mg/kg) in mice after 30 min of transient middle cerebral artery occlusion (tMCAO) showed improved motor function and reduced expression of the inflammatory marker CD86. APP96-110 decreased the infarct size and induced an anti-inflammatory response by inhibiting the PI3K pathway. These results suggest that the treatment of APP96-110 is efficacious in reducing neuroinflammation and infarct size in ischemic stroke.

Agmatine-IRF2BP2 interaction induces M2 phenotype of microglia by increasing IRF2-KLF4 signaling.

BACKGROUND: Following central nervous system (CNS) injury, the investigation for neuroinflammation is vital because of its pleiotropic role in both acute injury and long-term recovery. Agmatine (Agm) is well known for its neuroprotective effects and anti-neuroinflammatory properties. However, Agm's mechanism for neuroprotection is still unclear. We screened target proteins that bind to Agm using a protein microarray; the results showed that Agm strongly binds to interferon regulatory factor 2 binding protein (IRF2BP2), which partakes in the inflammatory response. Based on these prior data, we attempted to elucidate the mechanism by which the combination of Agm and IRF2BP2 induces a neuroprotective phenotype of microglia. METHODS: To confirm the relationship between Agm and IRF2BP2 in neuroinflammation, we used microglia cell-line (BV2) and treated with lipopolysaccharide from Escherichia coli 0111:B4 (LPS; 20 ng/mL, 24 h) and interleukin (IL)-4 (20 ng/mL, 24 h). Although Agm bound to IRF2BP2, it failed to enhance IRF2BP2 expression in BV2. Therefore, we shifted our focus onto interferon regulatory factor 2 (IRF2), which is a transcription factor and interacts with IRF2BP2. RESULTS: IRF2 was highly expressed in BV2 after LPS treatment but not after IL-4 treatment. When Agm bound to IRF2BP2 following Agm treatment, the free IRF2 translocated to the nucleus of BV2. The translocated IRF2 activated the transcription of Kruppel-like factor 4 (KLF4), causing KLF4 to be induced in BV2. The expression of KLF4 increased the CD206-positive cells in BV2. CONCLUSIONS: Taken together, unbound IRF2, resulting from the competitive binding of Agm to IRF2BP2, may provide neuroprotection against neuroinflammation via an anti-inflammatory mechanism of microglia involving the expression of KLF4.

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.

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.

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.

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.].

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.

Diagnosis-informed connectivity subtyping discovers subgroups of autism with reproducible symptom profiles.

Clinical heterogeneity has been one of the main barriers to develop effective biomarkers and therapeutic strategies in autism spectrum disorder (ASD). Recognizing this challenge, much effort has been made in recent neuroimaging studies to find biologically more homogeneous subgroups (called 'neurosubtypes') in autism. However, most approaches have rarely evaluated how much the employed features in subtyping represent the core anomalies of ASD, obscuring its utility in actual clinical diagnosis. To address this, we combined two data-driven methods, 'connectome-based gradient' and 'functional random forest', collectively allowing to discover reproducible neurosubtypes based on resting-state functional connectivity profiles that are specific to ASD. Indeed, the former technique provides the features (as input for subtyping) that effectively summarize whole-brain connectome variations in both normal and ASD conditions, while the latter leverages a supervised random forest algorithm to inform diagnostic labels to clustering, which makes neurosubtyping driven by the features of ASD core anomalies. Applying this framework to the open-sharing Autism Brain Imaging Data Exchange repository data (discovery, n = 103/108 for ASD/typically developing [TD]; replication, n = 44/42 for ASD/TD), we found three dominant subtypes of functional gradients in ASD and three subtypes in TD. The subtypes in ASD revealed distinct connectome profiles in multiple brain areas, which are associated with different Neurosynth-derived cognitive functions previously implicated in autism studies. Moreover, these subtypes showed different symptom severity, which degree co-varies with the extent of functional gradient changes observed across the groups. The subtypes in the discovery and replication datasets showed similar symptom profiles in social interaction and communication domains, confirming a largely reproducible brain-behavior relationship. Finally, the connectome gradients in ASD subtypes present both common and distinct patterns compared to those in TD, reflecting their potential overlap and divergence in terms of developmental mechanisms involved in the manifestation of large-scale functional networks. Our study demonstrated a potential of the diagnosis-informed subtyping approach in developing a clinically useful brain-based classification system for future ASD research.

Imaging and Clinical Features of COVID-19 Breakthrough Infections: A Multicenter Study.

Background Since vaccines against COVID-19 became available, rare breakthrough infections have been reported despite their high efficacies. Purpose To evaluate the clinical and imaging characteristics of patients with COVID-19 breakthrough infections and compare them with those of unvaccinated patients with COVID-19. Materials and Methods In this retrospective multicenter cohort study, the authors analyzed patient (aged ≥18 years) data from three centers that were registered in an open data repository for COVID-19 between June and August 2021. Hospitalized patients with baseline chest radiographs were divided into three groups according to their vaccination status. Differences between clinical and imaging features were analyzed using the Pearson χ2 test, Fisher exact test, and analysis of variance. Univariable and multivariable logistic regression analyses were used to evaluate associations between clinical factors, including vaccination status and clinical outcomes. Results Of the 761 hospitalized patients with COVID-19, the mean age was 47 years and 385 (51%) were women; 47 patients (6%) were fully vaccinated (breakthrough infection), 127 (17%) were partially vaccinated, and 587 (77%) were unvaccinated. Of the 761 patients, 412 (54%) underwent chest CT during hospitalization. Among the patients who underwent CT, the proportions without pneumonia were 22% of unvaccinated patients (71 of 326), 30% of partially vaccinated patients (19 of 64), and 59% of fully vaccinated patients (13 of 22) (P < .001). Fully vaccinated status was associated with a lower risk of requiring supplemental oxygen (odds ratio [OR], 0.24 [95% CI: 0.09, 0.64; P = .005]) and lower risk of intensive care unit admission (OR, 0.08 [95% CI: 0.09, 0.78; P = .02]) compared with unvaccinated status. Conclusion Patients with COVID-19 breakthrough infections had a significantly higher proportion of CT scans without pneumonia compared with unvaccinated patients. Vaccinated patients with breakthrough infections had a lower likelihood of requiring supplemental oxygen and intensive care unit admission. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Schiebler and Bluemke in this issue.