Objective: : Hemifacial spasm (HFS) is treated by a surgical procedure called microvascular decompression (MVD). However, HFS re-appearing phenomenon after surgery, presenting as early recurrence, is experienced by some patients after MVD. Dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) and two analytical methods : receiver operating characteristic (ROC) curve and machine learning, were used to predict early recurrence in this study. Methods: : This study enrolled 60 patients who underwent MVD for HFS. They were divided into two groups : group A consisted of 32 patients who had early recurrence and group B consisted of 28 patients who had no early recurrence of HFS. DSC perfusion MRI was undergone by all patients before the surgery to obtain the several parameters. ROC curve and machine learning methods were used to predict early recurrence using these parameters. Results: : Group A had significantly lower relative cerebral blood flow than group B in most of the selected brain regions, as shown by the region-of-interest-based analysis. By combining three extraction fraction (EF) values at middle temporal gyrus, posterior cingulate, and brainstem, with age, using naive Bayes machine learning method, the best prediction model for early recurrence was obtained. This model had an area under the curve value of 0.845. Conclusion : By combining EF values with age or sex using machine learning methods, DSC perfusion MRI can be used to predict early recurrence before MVD surgery. This may help neurosurgeons to identify patients who are at risk of HFS recurrence and provide appropriate postoperative care.

Objective: : Hemifacial spasm (HFS) is treated by a surgical procedure called microvascular decompression (MVD). However, HFS re-appearing phenomenon after surgery, presenting as early recurrence, is experienced by some patients after MVD. Dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) and two analytical methods : receiver operating characteristic (ROC) curve and machine learning, were used to predict early recurrence in this study. Methods: : This study enrolled 60 patients who underwent MVD for HFS. They were divided into two groups : group A consisted of 32 patients who had early recurrence and group B consisted of 28 patients who had no early recurrence of HFS. DSC perfusion MRI was undergone by all patients before the surgery to obtain the several parameters. ROC curve and machine learning methods were used to predict early recurrence using these parameters. Results: : Group A had significantly lower relative cerebral blood flow than group B in most of the selected brain regions, as shown by the region-of-interest-based analysis. By combining three extraction fraction (EF) values at middle temporal gyrus, posterior cingulate, and brainstem, with age, using naive Bayes machine learning method, the best prediction model for early recurrence was obtained. This model had an area under the curve value of 0.845. Conclusion : By combining EF values with age or sex using machine learning methods, DSC perfusion MRI can be used to predict early recurrence before MVD surgery. This may help neurosurgeons to identify patients who are at risk of HFS recurrence and provide appropriate postoperative care.

Objective: : Hemifacial spasm (HFS) is treated by a surgical procedure called microvascular decompression (MVD). However, HFS re-appearing phenomenon after surgery, presenting as early recurrence, is experienced by some patients after MVD. Dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) and two analytical methods : receiver operating characteristic (ROC) curve and machine learning, were used to predict early recurrence in this study. Methods: : This study enrolled 60 patients who underwent MVD for HFS. They were divided into two groups : group A consisted of 32 patients who had early recurrence and group B consisted of 28 patients who had no early recurrence of HFS. DSC perfusion MRI was undergone by all patients before the surgery to obtain the several parameters. ROC curve and machine learning methods were used to predict early recurrence using these parameters. Results: : Group A had significantly lower relative cerebral blood flow than group B in most of the selected brain regions, as shown by the region-of-interest-based analysis. By combining three extraction fraction (EF) values at middle temporal gyrus, posterior cingulate, and brainstem, with age, using naive Bayes machine learning method, the best prediction model for early recurrence was obtained. This model had an area under the curve value of 0.845. Conclusion : By combining EF values with age or sex using machine learning methods, DSC perfusion MRI can be used to predict early recurrence before MVD surgery. This may help neurosurgeons to identify patients who are at risk of HFS recurrence and provide appropriate postoperative care.

Objective: : Hemifacial spasm (HFS) is treated by a surgical procedure called microvascular decompression (MVD). However, HFS re-appearing phenomenon after surgery, presenting as early recurrence, is experienced by some patients after MVD. Dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) and two analytical methods : receiver operating characteristic (ROC) curve and machine learning, were used to predict early recurrence in this study. Methods: : This study enrolled 60 patients who underwent MVD for HFS. They were divided into two groups : group A consisted of 32 patients who had early recurrence and group B consisted of 28 patients who had no early recurrence of HFS. DSC perfusion MRI was undergone by all patients before the surgery to obtain the several parameters. ROC curve and machine learning methods were used to predict early recurrence using these parameters. Results: : Group A had significantly lower relative cerebral blood flow than group B in most of the selected brain regions, as shown by the region-of-interest-based analysis. By combining three extraction fraction (EF) values at middle temporal gyrus, posterior cingulate, and brainstem, with age, using naive Bayes machine learning method, the best prediction model for early recurrence was obtained. This model had an area under the curve value of 0.845. Conclusion : By combining EF values with age or sex using machine learning methods, DSC perfusion MRI can be used to predict early recurrence before MVD surgery. This may help neurosurgeons to identify patients who are at risk of HFS recurrence and provide appropriate postoperative care.

Background: The rapid economic development of South Korea provides a unique model to study changes in the clinical characteristics, treatment approaches, and clinical outcomes of patients with rheumatic mitral stenosis (MS) relative to socioeconomic growth. Methods: From the Multicenter mitrAl STEnosis with Rheumatic etiology (MASTER) registry, 2,337 patients diagnosed with moderate or severe rheumatic MS between January 2001 and December 2020 were analyzed. Patients were grouped into consecutive 5-year intervals based on their year of diagnosis. Clinical characteristics, echocardiographic data, and clinical outcomes were assessed. Results: Over 20 years, the severity of mitral stenosis increased from 79.1% to 90.2%; similarly, the average age at diagnosis increased from 54.3 to 63.0 years (all P < 0.001). Comorbidities such as hypertension and atrial fibrillation increased (6.3% to 29.5% and 41.4% to 46.9%, respectively; all P for trend < 0.05). The rate of mitral intervention within five years after diagnosis increased from 31.2% to 47.4% (P for trend < 0.001). However, clinical outcomes of rheumatic mitral stenosis deteriorated over time in the composite outcomes (log-rank test, P < 0.001). Conversely, the incidence of stroke remained stable (60.6–73.7%; P < 0.001), which might be attributed to the increased use of anticoagulation therapy. Conclusion This study observed an increase in patient age, comorbidities, and valve disease severity as the country transitioned from a developing to developed status. Despite a rise in mitral valve interventions, clinical outcomes deteriorated over 20 years, highlighting the need for modified treatment approaches to improve patient outcomes.

Coronavirus disease 2019 (COVID-19) vaccination may non-specifically alter the host immune system. This study aimed to evaluate the effect of COVID-19 vaccination on hepatitis B surface Ag (HBsAg) titer and host immunity in chronic hepatitis B (CHB) patients. Consecutive 2,797 CHB patients who had serial HBsAg measurements during antiviral treatment were included in this study. Changes in the HBsAg levels after COVID-19 vaccination were analyzed. The dynamics of NK cells following COVID-19 vaccination were also examined using serial blood samples collected prospectively from 25 healthy volunteers. Vaccinated CHB patients (n=2,329) had significantly lower HBsAg levels 1–30 days post-vaccination compared to baseline (median, −21.4 IU/ml from baseline), but the levels reverted to baseline by 91–180 days (median, −3.8 IU/ml). The velocity of the HBsAg decline was transiently accelerated within 30 days after vaccination (median velocity: −0.06, −0.39, and −0.04 log 10 IU/ml/year in pre-vaccination period, days 1–30, and days 31–90, respectively). In contrast, unvaccinated patients (n=468) had no change in HBsAg levels. Flow cytometric analysis showed that the frequency of NK cells expressing NKG2A, an NK inhibitory receptor, significantly decreased within 7 days after the first dose of COVID-19 vaccine (median, −13.1% from baseline; p<0.001). The decrease in the frequency of NKG2A + NK cells was observed in the CD56dimCD16+ NK cell population regardless of type of COVID-19 vaccine. COVID-19 vaccination leads to a rapid, transient decline in HBsAg titer and a decrease in the frequency of NKG2A + NK cells.

Background: We evaluated the achievement of low-density lipoprotein cholesterol (LDL-C) targets in patients with type 2 diabetes mellitus (T2DM) according to up-to-date Korean Diabetes Association (KDA), European Society of Cardiology (ESC)/European Atherosclerosis Society (EAS), and American Diabetes Association (ADA) guidelines. Methods: This retrospective cohort study collected electronic medical record data from patients with T2DM (≥20 years) managed by endocrinologists from 15 hospitals in Korea (January to December 2019). Patients were categorized according to guidelines to assess LDL-C target achievement. KDA (2019): Very High-I (atherosclerotic cardiovascular disease [ASCVD]) <70 mg/dL; Very High-II (target organ damage [TOD], or cardiovascular risk factors [CVRFs]) <70 mg/dL; high (others) <100 mg/dL. ESC/EAS (2019): Very High-I (ASCVD): <55 mg/dL; Very High-II (TOD or ≥3-CVRF) <55 mg/dL; high (diabetes ≥10 years without TOD plus any CVRF) <70 mg/dL; moderate (diabetes <10 years without CVRF) <100 mg/dL. ADA (2019): Very High-I (ASCVD); Very High-II (age ≥40+ TOD, or any CVRF), for high intensity statin or statin combined with ezetimibe. Results: Among 2,000 T2DM patients (mean age 62.6 years; male 55.9%; mean glycosylated hemoglobin 7.2%) ASCVD prevalence was 24.7%. Of 1,455 (72.8%) patients treated with statins, 73.9% received monotherapy. According to KDA guidelines, LDL-C target achievement rates were 55.2% in Very High-I and 34.9% in Very High-II patients. With ESC/EAS guidelines, target attainment rates were 26.6% in Very High-I, 15.7% in Very High-II, and 25.9% in high risk patients. Based on ADA guidelines, most patients (78.9%) were very-high risk; however, only 15.5% received high-intensity statin or combination therapy. Conclusion According to current dyslipidemia management guidelines, LDL-C goal achievement remains suboptimal in Korean patients with T2DM.

Diploic arteriovenous fistulas (AVFs) or intraosseous dural AVFs are rare arteriovenous shunts. A diploic AVF is formed between a meningeal artery and an intraosseous diploic vein or the transosseous emissary vein, and the nidus is located exclusively within the bone. Currently, endovascular embolization with a transvenous approach is considered the treatment of choice for most dural AVFs. However, in the absence of an accessible venous channel, an alternate treatment approach should be considered. Herein, we report a case of a diploic AVF that was treated using embolization with transosseous direct cannulation.

Purpose: The aim of this study is to evaluate the safety and efficacy of ex vivo activated and expanded natural killer (NK) cell therapy (SNK01) plus pembrolizumab in a randomized phase I/IIa clinical trial. Materials and Methods: Overall, 18 patients with advanced non–small cell lung cancer (NSCLC) and a programmed death ligand 1 tumor proportion score of 1% or greater who had a history of failed frontline platinum-based therapy were randomized (2:1) to receive pembrolizumab every 3 weeks +/– 6 weekly infusions of SNK01 at either 2×109 or 4×109 cells per infusion (pembrolizumab monotherapy vs. SNK01 combination). The primary endpoint was safety, whereas the secondary endpoints were the objective response rate (ORR), progression-free survival (PFS), overall survival, and quality of life. Results: Since no dose-limiting toxicity was observed, the maximum tolerated dose was determined as SNK01 4×109 cells/dose. The safety data did not show any new safety signals when SNK01 was combined with pembrolizumab. The ORR and the 1-year survival rate in the NK combination group were higher than those in patients who underwent pembrolizumab monotherapy (ORR, 41.7% vs. 0%; 1-year survival rate, 66.7% vs. 50.0%). Furthermore, the median PFS was higher in the SNK01 combination group (6.2 months vs. 1.6 months, p=0.001). Conclusion Based on the findings of this study, the NK cell combination therapy may consider as a safe treatment method for stage IV NSCLC patients who had a history of failed platinum-based therapy without an increase in adverse events.

Objective: : Preoperative prediction of the arachnoid membrane descent in pituitary surgery is useful for achieving gross total removal and avoiding cerebrospinal fluid leakage resulting from tearing of the arachnoid membrane in the chiasmatic cistern. In this study, we analyzed the patterns of arachnoid membrane descent during or after pituitary tumor surgery and identified the factors related to this descent. Methods: : Analysis was restricted to pituitary macroadenomas not extending into the third ventricle or over the internal carotid artery. To minimize confounding factors, patients who underwent revision surgery, those who had a torn arachnoid during operation or small medial diaphragma sellae (DS) opening, and subtotal resections were excluded. We enrolled 41 consecutive patients in this retrospective analysis. The degree of arachnoid descent was categorized using intraoperative videos. Preoperative magnetic resonance findings, including tumor height, suprasellar extension, and variables including DS area and medial opening size, tumor composition, and displacement of the pituitary stalk and gland were evaluated to determine their correlations with arachnoid membrane descent. Results: : Arachnoid membrane descent was significantly correlated with DS area and medial opening size. Based on T2-weighted images (T2WI) magnetic resonance (MR) images, tumor composition was significantly associated with arachnoid membrane descent. Other factors were not significantly correlated with arachnoid membrane descent. Conclusion : T2WI of tumor composition and preoperative MR imaging of DS area and medial opening provided valuable information regarding arachnoid membrane descent. These parameters may serve as fundamental measures to facilitate complete resection of pituitary macroadenomas.