Purpose: This study evaluated volumetric analysis using automatic whole-brain segmentation as a potential tool to enhance diagnostic accuracy alongside traditional magnetic resonance imaging (MRI) markers in the diagnosis of idiopathic normal pressure hydrocephalus (INPH). Materials and Methods: Twenty-six patients diagnosed with INPH exhibited progressive symptoms, including gait dysfunction and cognitive impairment, confirmed by MRI evidence of enlarged ventricles and normal cerebrospinal fluid pressure. Automatic segmentation was performed on sagittal T1-weighted volumetric images using LesionQuant. Age- and sex-matched groups with Alzheimer’s disease (AD) and normal control (NC) groups were included. Multinomial logistic regression was applied to predict diagnoses (NC, INPH, or AD) based on volumetric parameters. Results: Compared to the AD and NC groups, enlarged inferior lateral ventricles were observed in the INPH group. The inferior lateral ventricle volume showed a positive linear correlation with the Evans’ index (R2 = 0.639) and a negative linear correlation with the callosal angle (R2 = 0.482). High classification accuracy was achieved, with 87.5% of NC cases, 88.5% of INPH cases, and 76% of AD cases correctly identified. Conclusion Automated volumetric markers appear valuable for diagnosing INPH and distinguishing it from other neurodegenerative diseases.

Purpose: This study evaluated volumetric analysis using automatic whole-brain segmentation as a potential tool to enhance diagnostic accuracy alongside traditional magnetic resonance imaging (MRI) markers in the diagnosis of idiopathic normal pressure hydrocephalus (INPH). Materials and Methods: Twenty-six patients diagnosed with INPH exhibited progressive symptoms, including gait dysfunction and cognitive impairment, confirmed by MRI evidence of enlarged ventricles and normal cerebrospinal fluid pressure. Automatic segmentation was performed on sagittal T1-weighted volumetric images using LesionQuant. Age- and sex-matched groups with Alzheimer’s disease (AD) and normal control (NC) groups were included. Multinomial logistic regression was applied to predict diagnoses (NC, INPH, or AD) based on volumetric parameters. Results: Compared to the AD and NC groups, enlarged inferior lateral ventricles were observed in the INPH group. The inferior lateral ventricle volume showed a positive linear correlation with the Evans’ index (R2 = 0.639) and a negative linear correlation with the callosal angle (R2 = 0.482). High classification accuracy was achieved, with 87.5% of NC cases, 88.5% of INPH cases, and 76% of AD cases correctly identified. Conclusion Automated volumetric markers appear valuable for diagnosing INPH and distinguishing it from other neurodegenerative diseases.

Purpose: This study evaluated volumetric analysis using automatic whole-brain segmentation as a potential tool to enhance diagnostic accuracy alongside traditional magnetic resonance imaging (MRI) markers in the diagnosis of idiopathic normal pressure hydrocephalus (INPH). Materials and Methods: Twenty-six patients diagnosed with INPH exhibited progressive symptoms, including gait dysfunction and cognitive impairment, confirmed by MRI evidence of enlarged ventricles and normal cerebrospinal fluid pressure. Automatic segmentation was performed on sagittal T1-weighted volumetric images using LesionQuant. Age- and sex-matched groups with Alzheimer’s disease (AD) and normal control (NC) groups were included. Multinomial logistic regression was applied to predict diagnoses (NC, INPH, or AD) based on volumetric parameters. Results: Compared to the AD and NC groups, enlarged inferior lateral ventricles were observed in the INPH group. The inferior lateral ventricle volume showed a positive linear correlation with the Evans’ index (R2 = 0.639) and a negative linear correlation with the callosal angle (R2 = 0.482). High classification accuracy was achieved, with 87.5% of NC cases, 88.5% of INPH cases, and 76% of AD cases correctly identified. Conclusion Automated volumetric markers appear valuable for diagnosing INPH and distinguishing it from other neurodegenerative diseases.

Objectives: Insulin degludec (IDeg)/insulin aspart (IAsp; IDegAsp) is a co-formulation of 70% IDeg and 30% IAsp. According to several randomized controlled trials, IDegAsp is effective and safe for patients with type 2 diabetes mellitus (T2DM). A subgroup analysis of the ARISE study was conducted to explore the safety and efficacy of IDegAsp among Malaysian patients with T2DM in real-world settings. Methodology: ARISE, an open-label, multicenter, non-interventional, prospective study was conducted between August 2019 and December 2020. Adult Malaysian patients with T2DM who were enrolled from 14 sites received IDegAsp as per the local label for 26 weeks. The primary endpoint was change in glycated hemoglobin (HbA1c) levels from baseline to end of study (EOS). Results: Of the 182 patients included in the full analysis set, 159 (87.4%) completed the study. From baseline to EOS, HbA1c (estimated difference [ED]: –1.3% [95% CI: –1.61 to –0.90]) and fasting plasma glucose levels (ED: –1.8 mmol/L [95% CI: –2.49 to –1.13]) were significantly reduced (p<0.0001). The patient-reported reduced hypoglycemic episodes (overall and nocturnal) during treatment. Overall, 37 adverse events were observed in 23 (12.6%) patients. Conclusion Switching or initiating IDegAsp treatment resulted in significant improvements in glycemic control and a reduction in hypoglycemic episodes.

Gastric cancer is one of the most common cancers in Korea and the world. Since 2004, this is the 4th gastric cancer guideline published in Korea which is the revised version of previous evidence-based approach in 2018. Current guideline is a collaborative work of the interdisciplinary working group including experts in the field of gastric surgery, gastroenterology, endoscopy, medical oncology, abdominal radiology, pathology, nuclear medicine, radiation oncology and guideline development methodology. Total of 33 key questions were updated or proposed after a collaborative review by the working group and 40 statements were developed according to the systematic review using the MEDLINE, Embase, Cochrane Library and KoreaMed database. The level of evidence and the grading of recommendations were categorized according to the Grading of Recommendations, Assessment, Development and Evaluation proposition. Evidence level, benefit, harm, and clinical applicability was considered as the significant factors for recommendation. The working group reviewed recommendations and discussed for consensus. In the earlier part, general consideration discusses screening, diagnosis and staging of endoscopy, pathology, radiology, and nuclear medicine. Flowchart is depicted with statements which is supported by meta-analysis and references. Since clinical trial and systematic review was not suitable for postoperative oncologic and nutritional follow-up, working group agreed to conduct a nationwide survey investigating the clinical practice of all tertiary or general hospitals in Korea. The purpose of this survey was to provide baseline information on follow up. Herein we present a multidisciplinary-evidence based gastric cancer guideline.

Background: As the number of large-scale studies involving multiple organizations producing data has steadily increased, an integrated system for a common interoperable format is needed. In response to the coronavirus disease 2019 (COVID-19) pandemic, a number of global efforts are underway to develop vaccines and therapeutics. We are therefore observing an explosion in the proliferation of COVID-19 data, and interoperability is highly requested in multiple institutions participating simultaneously in COVID-19 pandemic research. Results: In this study, a laboratory information management system (LIMS) approach has been adopted to systemically manage various COVID-19 non-clinical trial data, including mortality, clinical signs, body weight, body temperature, organ weights, viral titer (viral replication and viral RNA), and multiorgan histopathology, from multiple institutions based on a web interface. The main aim of the implemented system is to integrate, standardize, and organize data collected from laboratories in multiple institutes for COVID-19 non-clinical efficacy testings. Six animal biosafety level 3 institutions proved the feasibility of our system. Substantial benefits were shown by maximizing collaborative high-quality non-clinical research. Conclusions This LIMS platform can be used for future outbreaks, leading to accelerated medical product development through the systematic management of extensive data from non-clinical animal studies.

Background and Objectives: We investigated whether extra-pulmonary vein (PV) ablation targeting a high maximal slope of the action potential duration restitution curve (Smax) improves the rhythm outcome of persistent atrial fibrillation (PeAF) ablation. Methods: In this open-label, multi-center, randomized, and controlled trial, 178 PeAF patients were randomized with 1:1 ratio to computational modeling-guided virtual Smax ablation (V-Smax) or empirical ablation (E-ABL) groups. Smax maps were generated by computational modeling based on atrial substrate maps acquired during clinical procedures in sinus rhythm. Smax maps were generated during the clinical PV isolation (PVI). The V-Smax group underwent an additional extra-PV ablation after PVI targeting the virtual high Smax sites. Results: After a mean follow-up period of 12.3±5.2 months, the clinical recurrence rates (25.6% vs. 23.9% in the V-Smax and the E-ABL group, p=0.880) or recurrence appearing as atrial tachycardia (11.1% vs. 5.7%, p=0.169) did not differ between the 2 groups. The postablation cardioversion rate was higher in the V-Smax group than E-ABL group (14.4% vs. 5.7%, p=0.027). Among antiarrhythmic drug-free patients (n=129), the AF freedom rate was 78.7% in the V-Smax group and 80.9% in the E-ABL group (p=0.776). The total procedure time was longer in the V-Smax group (p=0.008), but no significant difference was found in the major complication rates (p=0.497) between the groups. Conclusions Unlike a dominant frequency ablation, the computational modeling-guided V-Smax ablation did not improve the rhythm outcome of the PeAF ablation and had a longer procedure time.