Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

Purpose: To evaluate the compatibility and usability of test results obtained from the IDRA and Keratograph 5M in clinical settings by comparing their performance in patients with dry eye disease. Methods: From December 27 to 30, 2022, a study was conducted on 30 patients diagnosed with dry eye utilizing both the Keratograph 5M and IDRA devices. The parameters compared and analyzed included lipid layer thickness, tear meniscus height, tear film break-up time, and meibography. A paired t-test was used for statistical comparison. The lipid layer thickness in the Keratograph 5M was graded on a scale from 0 to 4 based on thickness. Results: No significant differences were found between the two devices in tear film break-up time, tear meniscus height, and meibography (p = 0.148, 0.072, 0.124, respectively). However, the tear lipid layer thickness measured by IDRA showed a proportional relationship with the grade assigned by the Keratograph 5M (Kendall R = 0.217, p = 0.037; Spearman R = 0.260, p = 0.045). Conclusions The IDRA device offers the advantage of performing multiple dry eye tests; simultaneously, thereby saving time compared to the Keratograph 5M. Both devices can be used compatibly with IDRA particularly advantageous for providing a numerical value for tear lipid layer thickness which enhances the convenience of dry eye diagnosis and treatment.

Background: This study aimed to determine whether a shorter high-dose rifampicin regimen is non-inferior to the standard 6-month tuberculosis regimen. Methods: This multicenter, randomized, open-label, non-inferiority trial enrolled participants with respiratory specimen positivity by Xpert MTB/RIF assay or Mycobacterium tuberculosis culture without rifampicin-resistance. Participants were randomized at 1:1 to the investigational or control group. The investigational group received high-dose rifampicin (30 mg/kg/day), isoniazid, and pyrazinamide until culture conversion, followed by high-dose rifampicin and isoniazid for 12 weeks. The control group received the standard 6-month regimen. The primary outcome was the rate of unfavorable outcomes at 18 months post-randomization. The non-inferiority margin was set at <6% difference in unfavorable outcomes rates. The study is registered with ClinicalTrials.gov (NCT04485156) Results: Between 4 November 2020 and 3 January 2022, 76 participants were enrolled. Of these, 58 were included in the modified intention-to-treat analysis. Unfavorable outcomes occurred in 10 (31.3%) of 32 in the control group and 10 (38.5%) of 26 in the investigational group. The difference was 7.2% (95% confidence interval, ∞ to 31.9%), failing to prove non-inferiority. Serious adverse events and grade 3 or higher adverse events did not differ between the groups. Conclusion The shorter high-dose rifampicin regimen failed to demonstrate non-inferiority but had an acceptable safety profile.

Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: Cognitive behavioral therapy (CBT) has long been recognized as an effective treatment for depression and suicidality.Virtual reality (VR) technology is widely used for cognitive training for conditions such as anxiety disorder and post-traumatic stress disorder, but little research has considered VR-based CBT for depressive symptoms and suicidality. We tested the effectiveness and safety of a VR-based CBT program for depressive disorders. Materials and Methods: We recruited 57 participants from May 2022 through February 2023 using online advertisements. This multi-center, assessor-blinded, randomized, controlled exploratory trial used two groups: VR treatment group and treat as usual (TAU) group. VR treatment group received a VR mental health training/education program. TAU group received standard pharmacotherapy. Assessments were conducted at baseline, immediately after the 6-week treatment period, and 4 weeks after the end of the treatment period in each group. Results: Depression scores decreased significantly over time in both VR treatment and TAU groups, with no differences between the two groups. The suicidality score decreased significantly only in VR group. No group differences were found in the remission or response rate for depression, perceived stress, or clinical severity. No adverse events or motion sickness occurred during the VR treatment program. Conclusion VR CBT treatment for major depressive disorder has the potential to be equivalent to the gold-standard pharmacotherapy in reducing depressive symptoms, suicidality, and related clinical symptoms, with no difference in improvement found in this study. Thus, VR-based CBT might be an effective alternative to pharmacotherapy for depressive disorders.

Background: This study aimed to determine whether a shorter high-dose rifampicin regimen is non-inferior to the standard 6-month tuberculosis regimen. Methods: This multicenter, randomized, open-label, non-inferiority trial enrolled participants with respiratory specimen positivity by Xpert MTB/RIF assay or Mycobacterium tuberculosis culture without rifampicin-resistance. Participants were randomized at 1:1 to the investigational or control group. The investigational group received high-dose rifampicin (30 mg/kg/day), isoniazid, and pyrazinamide until culture conversion, followed by high-dose rifampicin and isoniazid for 12 weeks. The control group received the standard 6-month regimen. The primary outcome was the rate of unfavorable outcomes at 18 months post-randomization. The non-inferiority margin was set at <6% difference in unfavorable outcomes rates. The study is registered with ClinicalTrials.gov (NCT04485156) Results: Between 4 November 2020 and 3 January 2022, 76 participants were enrolled. Of these, 58 were included in the modified intention-to-treat analysis. Unfavorable outcomes occurred in 10 (31.3%) of 32 in the control group and 10 (38.5%) of 26 in the investigational group. The difference was 7.2% (95% confidence interval, ∞ to 31.9%), failing to prove non-inferiority. Serious adverse events and grade 3 or higher adverse events did not differ between the groups. Conclusion The shorter high-dose rifampicin regimen failed to demonstrate non-inferiority but had an acceptable safety profile.

Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: Cognitive behavioral therapy (CBT) has long been recognized as an effective treatment for depression and suicidality.Virtual reality (VR) technology is widely used for cognitive training for conditions such as anxiety disorder and post-traumatic stress disorder, but little research has considered VR-based CBT for depressive symptoms and suicidality. We tested the effectiveness and safety of a VR-based CBT program for depressive disorders. Materials and Methods: We recruited 57 participants from May 2022 through February 2023 using online advertisements. This multi-center, assessor-blinded, randomized, controlled exploratory trial used two groups: VR treatment group and treat as usual (TAU) group. VR treatment group received a VR mental health training/education program. TAU group received standard pharmacotherapy. Assessments were conducted at baseline, immediately after the 6-week treatment period, and 4 weeks after the end of the treatment period in each group. Results: Depression scores decreased significantly over time in both VR treatment and TAU groups, with no differences between the two groups. The suicidality score decreased significantly only in VR group. No group differences were found in the remission or response rate for depression, perceived stress, or clinical severity. No adverse events or motion sickness occurred during the VR treatment program. Conclusion VR CBT treatment for major depressive disorder has the potential to be equivalent to the gold-standard pharmacotherapy in reducing depressive symptoms, suicidality, and related clinical symptoms, with no difference in improvement found in this study. Thus, VR-based CBT might be an effective alternative to pharmacotherapy for depressive disorders.

Background and Objectives: Obstructive sleep apnea (OSA) has been associated with an increased risk of cancer in various organs. OSA is also linked to chronic inflammation in the biliary tract and pancreas, a well-established risk factor for carcinogenesis in these organs. However, its relationship with biliary tract and pancreatic cancers remains unclear and has been rarely investigated. Therefore, we aimed to evaluate whether OSA serves as an independent risk factor for these malignancies by analyzing a nationwide healthcare claims database in South Korea. Methods: A retrospective cohort study was conducted using the Korean National Health Insurance Service (KNHIS) database. Adults aged ≥20 years who were newly diagnosed with OSA (ICD-10: G47.30) between 2007 and 2014 were identified and propensity score-matched (1:5) with controls based on age, sex, and comorbidities. Individuals with pre-existing cancer diagnoses were excluded. The primary endpoints were the incidence of overall cancer, biliary tract cancer (C23–C24), and pancreatic cancer (C25). Cox proportional hazards regression models were used to calculate hazard ratios (HRs), adjusting for demographic and clinical factors. Results: A total of 1,191,444 individuals were included, comprising 198,574 patients diagnosed with OSA and 992,870 matched controls. OSA was associated with an increased overall cancer incidence (HR, 1.132; 95% confidence interval [CI], 1.097–1.169); however, it was not significantly associated with pancreatic cancer (HR, 0.941; 95% CI, 0.823–1.072) or biliary tract cancer (HR, 0.931; 95% CI, 0.751–1.142). Subgroup analyses stratified by sex and age revealed no statistically significant associations across these groups. Conclusion Our findings do not support OSA as an independent risk factor for biliary tract or pancreatic cancers.

Background: and Purpose Previous research on patients with acute ischemic stroke (AIS) has shown a 0.5% incidence of major gastrointestinal bleeding (GIB) requiring blood transfusion during hospitalization. The existing literature has insufficiently explored the long-term incidence in this population despite the decremental impact of GIB on stroke outcomes. Methods: We analyzed the data from a cohort of patients with AIS admitted to 14 hospitals as part of a nationwide multicenter prospective stroke registry between 2011 and 2013. These patients were followed up for up to 6 years. The occurrence of major GIB events, defined as GIB necessitating at least two units of blood transfusion, was tracked using the National Health Insurance Service claims data. Results: Among 10,818 patients with AIS (male, 59%; mean age, 68±13 years), 947 (8.8%) experienced 1,224 episodes of major GIB over a median follow-up duration of 3.1 years. Remarkably, 20% of 947 patients experienced multiple episodes of major GIB. The incidence peaked in the first month after AIS, reaching 19.2 per 100 person-years, and gradually decreased to approximately one-sixth of this rate by the 2nd year with subsequent stabilization. Multivariable analysis identified the following predictors of major GIB: anemia, estimated glomerular filtration rate <60 mL/min/1.73 m2 , and a 3-month modified Rankin Scale score of ≥4. Conclusion Patients with AIS are susceptible to major GIB, particularly in the first month after the onset of AIS, with the risk decreasing thereafter. Implementing preventive strategies may be important, especially for patients with anemia and impaired renal function at stroke onset and those with a disabling stroke.