Background: Many COVID-19 patients rapidly progress to respiratory failure with a broad range of severities. Identification of high-risk cases is critical for early intervention. Objective: The aim of this study is to develop deep learning models that can rapidly identify high-risk COVID-19 patients based on computed tomography (CT) images and clinical data. Methods: We analyzed 297 COVID-19 patients from five hospitals in Daegu, South Korea. A mixed artificial convolutional neural network (ACNN) model, combining an artificial neural network for clinical data and a convolutional neural network for 3D CT imaging data, was developed to classify these cases as either high risk of severe progression (ie, event) or low risk (ie, event-free). Results: Using the mixed ACNN model, we were able to obtain high classification performance using novel coronavirus pneumonia lesion images (ie, 93.9% accuracy, 80.8% sensitivity, 96.9% specificity, and 0.916 area under the curve [AUC] score) and lung segmentation images (ie, 94.3% accuracy, 74.7% sensitivity, 95.9% specificity, and 0.928 AUC score) for event versus event-free groups. Conclusions: Our study successfully differentiated high-risk cases among COVID-19 patients using imaging and clinical features. The developed model can be used as a predictive tool for interventions in aggressive therapies.

Park B, et al. Korean J Radiol. 2020 Jul;21:e130. https://doi.org/10.3348/kjr.2020.0567

Purpose: To identify effective factors predicting extraprostatic extension (EPE) in patients with prostate cancer (PCa). Methods: This retrospective cohort study recruited 898 consecutive patients with PCa treated with robot-assisted laparoscopic radical prostatectomy. The patients were divided into EPE and non-EPE groups based on the analysis of whole-mount histopathologic sections. Histopathological analysis (ISUP biopsy grade group) and magnetic resonance imaging (MRI) (PI-RADS v2.1 scores [1–5] and the Mehralivand EPE grade [0–3]) were used to assess the prediction of EPE. We also assessed the clinical usefulness of the prediction model based on decision-curve analysis. Results: Of 800 included patients, 235 (29.3%) had EPE, and 565 patients (70.7%) did not (non-EPE). Multivariable logistic regression analysis showed that the biopsy ISUP grade, PI-RADS v2.1 score, and Mehralivand EPE grade were independent risk factors for EPE. In the regression assessment of the models, the best discrimination (area under the curve of 0.879) was obtained using the basic model (age, serum PSA, prostate volume at MRI, positive biopsy core, clinical T stage, and D’Amico risk group) and Mehralivand EPE grade 3. Decision-curve analysis showed that combining Mehralivand EPE grade 3 with the basic model resulted in superior net benefits for predicting EPE. Conclusion: Mehralivand EPE grades and PI-RADS v2.1 scores, in addition to basic clinical and demographic information, are potentially useful for predicting EPE in patients with PCa.

Background: Patients with bronchiectasis commonly experience disease exacerbations, which cause significant morbidity and mortality. However, data regarding the clinical features of bronchiectasis patients hospitalized with hemoptysis are scarce. Methods: We retrospectively collected the data of patients with bronchiectasis-associated hospitalization at a tertiary referral center in Korea, and classified them into the hemoptysis and infective exacerbation (IE) groups. The presence of hemoptysis was defined as a volume of expectorated blood larger than 10 mL per 24 hours. The clinical, radiological, and laboratory parameters were compared between the two groups. Results: Patients were classified into the hemoptysis [267 (54.5%)] and IE [223 (45.5%)] groups. Among the 44 patients of the hemoptysis group, 37 (84.1%) presented with hemoptysis than with IE at the recurrent episode. The hemoptysis group had a significantly lower 30-day mortality than that of the IE group. Previous pulmonary tuberculosis (TB), mycetoma, and bronchial artery hypertrophy were independently associated with the hemoptysis group. In contrast, male sex, poor performance status, colonization of Pseudomonas aeruginosa, ≥3 involved lobes, cystic bronchiectasis, and emphysema were inversely associated with the hemoptysis group. The absence of hemoptysis was one of the independent predictors of 30-day mortality in patients with bronchiectasis-associated hospitalization. Conclusions: In Korea, bronchiectasis patients hospitalized with hemoptysis exhibit a distinct phenotype, and are more likely to have previous pulmonary TB, mycetoma, and bronchial artery hypertrophy. Hemoptysis is associated with a lower risk of short-term mortality compared to IE in bronchiectasis-associated hospitalization.

Lee J, et al. J Korean Med Sci. 2024 Nov;40:e35. https://doi.org/10.3346/jkms.2025.40.e35

Purpose: This study aimed to investigate the impact of FDG PET/CT timing for biopsy site selection in patients with stage IV lung cancer regarding complications and diagnostic yield. Methods: This retrospective analysis was performed on 1297 patients (924 men and 373 women with a mean age of 71.4 ± 10.2 years) who underwent percutaneous needle biopsy (PNB) for stage IV lung cancer diagnosis in two hospitals. Data collected included the patient’s characteristics, order date of the biopsy and PET/CT exams, biopsy target site (lung or non-lung), guidance modality, complications, sample adequacy, and diagnostic success. Based on the order date of the PNB and PET/CT exams, patients were categorized into upfront and delayed PET/CT groups. Results: PNB for non-lung targets resulted in significantly lower rates of minor (8.1% vs. 16.2%), major (0.2% vs. 3.4%), and overall complications (8.3% vs. 19.6%) compared to PNB for lung targets (p < 0.001 for all types of complications). Compared to the delayed PET/CT group, the upfront PET/CT group exhibited a lower probability of lung target selection of PNB (53.9% vs. 67.1%, p < 0.001), including a reduced incidence of major complications (1.0% vs. 2.9%, p = 0.031). Moreover, there was no significant difference in the occurrence of minor and total complications between the two groups. Upfront PET/CT and delayed PET/CT groups showed no significant difference regarding sample adequacy and diagnostic success. Conclusions: Upfront PET/CT may have an impact on the selection of the biopsy site for patients with advanced lung cancer, which could result in a lower rate of major complications with no change in the diagnostic yield. Upfront PET/CT demonstrates potential clinical implications for enhancing the safety of lung cancer diagnosis in clinical practice.