Objective: This study aimed to evaluate the feasibility, safety, and oncologic outcomes of irreversible electroporation (IRE) using a clustered electrode in patients with locally advanced pancreatic cancer (LAPC). Materials and Methods: In this single-center prospective cohort study, 13 patients with LAPC (median age, 60 years; range, 48–78 years) underwent clustered electrode IRE between September 2022 and September 2024. Patient characteristics, procedural details, and clinical outcomes were recorded. Endpoints included technical success, procedure-related complications, overall survival (OS), and progression-free survival (PFS). Results: Tumors were located in the pancreatic head in four patients (30.8%) and in the body/tail in nine (69.2%). The median tumor size was 2.4 cm (1.5–4.0 cm), and vascular invasion was present in all patients. Technical success was achieved in all patients. Intraoperative IRE was performed in 11 (84.6%) patients, and 2 (15.4%) patients underwent percutaneous IRE. Gastrointestinal bleeding events as major complications occurred in two patients (15.4%) and, both were successfully controlled by embolization. No 60-day mortality was observed. At a median follow-up of 24.5 months (range, 9.9–33.4 months) after IRE, median OS and PFS from IRE were 20.1 and 14.5 months, respectively. Conclusion IRE using clustered electrodes for LAPC appears to be a feasible therapeutic approach, offering reliable technical success and acceptable safety. Survival outcomes are encouraging; however, larger, controlled studies are required.

Subarachnoid hemorrhage (SAH) is a stroke subtype with high mortality and poor functional outcomes. Prompt occlusion of a ruptured aneurysm at an early stage is crucial to prevent rebleeding, which can result in even higher mortality and more severe disabilities. The most critical initial decision in SAH management is the choice of treatment method with surgical clipping or endovascular coiling. We aimed to develop an evidence-based clinical guideline to select the optimal initial treatment in patients with SAH. We developed this guideline based on evidence from systematic reviews and meta-analyses via a de novo process. A systematic literature review was conducted across four databases (MEDLINE, Embase, Cochrane, and KoreaMed) to answer two population, intervention, comparison, outcome questions comparing clipping and coiling. The risk of bias was assessed using ROB 2.0 and the Newcastle-Ottawa Scale. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagrams and meta-analyses were generated for functional outcome and mortality. We included six randomized control trials (RCTs) and 58 observational studies. Meta-analysis of RCTs showed that coiling improved functional outcomes compared to clipping (odds ratio [OR], 0.91; 95% confidence interval [CI], 0.86–0.97). No significant mortality difference was observed in RCTs (OR, 1.38; 95% CI, 0.91–2.09), but non-RCTs favored clipping for reduced mortality (OR, 0.77; 95% CI, 0.69–0.86). However, it is difficult to generalize these findings to all clinical situations, as patients with SAH have a highly variable clinical course. Final treatment decision should be tailored to the individual patient’s status, including aneurysm location, morphology, and the expertise available at the treatment center. Such decisions are best made by specialists such as a board-certified physician and should be explained to the patient and their caregivers, along with the rationale for selecting the most appropriate treatment at the given hospital. Korea has many certified endovascular neurosurgeons, cerebrovascular surgeons, and certified cerebrovascular centers. Proper selection of the most suitable treatment method by certified physicians and centers would greatly benefit patient outcomes and healthcare professionals.

Accurate and early identification of stroke and large vessel occlusion (LVO) in emergency settings is essential for improving patient outcomes and ensuring the efficient allocation of medical resources. This clinical practice guideline systematically reviews domestic and international literature and conducts meta-analyses to evaluate the utility and diagnostic accuracy of stroke assessment tools used in prehospital emergency medical services (EMS). We developed a guideline based on evidence from systematic reviews and meta-analyses via a de novo process. A systematic literature review was conducted to evaluate the usefulness of diagnostic EMS assessment tools for diagnosing stroke and LVO. Overall, 70 non-randomized control studies were selected for this study. A meta-analysis was conducted with a subgroup analysis to distinguish between patients with stroke and those with LVO. EMS tools demonstrated high sensitivity but low specificity for diagnosing stroke. In the prehospital setting, using validated EMS stroke assessment tools is recommended for the early identification of stroke and LVO. Upon hospital arrival, stroke specialists should conduct further evaluation and triage to confirm the diagnosis and guide appropriate management. Delays in diagnosing LVO are frequently unacceptable. While experts advocate for the use of EMS assessment tools to facilitate early identification of LVO, these tools alone lack adequate sensitivity. Therefore, further diagnostic evaluations and consultation with stroke specialists upon hospital arrival are recommended.

The mothership (MS) model, where patients are directly transferred to a thrombectomy-capable center, and the drip-and-ship (DS) model, where thrombolysis is initiated at the nearest primary stroke center before transfer for thrombectomy, are the primary transport modes for patients with stroke. We aimed to establish guidelines for selecting the appropriate transfer strategy based on emergent large vessel occlusion (LVO). We developed this guideline based on evidence from systematic reviews and meta-analyses via a de novo process. A systematic literature review was conducted across four databases (MEDLINE, Embase, Cochrane, and KoreaMed) to answer three Population, Intervention, Comparison, and Outcome questions comparing MS and DS models. The risk of bias was assessed using the Newcastle-Ottawa Scale. Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagrams and meta-analyses were generated for functional outcomes, mortality, and successful recanalization. Twenty-six non-randomized controlled studies showed that the MS model improved good functional outcomes by approximately 14% compared with the DS model (odds ratio [OR], 1.14; 95% confidence interval [CI], 1.00–1.30). Fifteen studies reported that mortality in the MS and DS models showed no significant differences (OR, 0.97; 95% CI, 0.84–1.11). Twenty-four studies revealed no significant difference in successful recanalization between the MS and DS models (OR, 0.87; 95% CI, 0.68–1.10). The MS model should be considered first to improve the functional outcome of patients with LVO. However, if thrombectomy cannot be performed immediately after thrombolysis, or if a thrombectomy-enabled hospital is not nearby, the DS model should be considered by stroke specialists depending on transportation time and regional factors. We suggest a mixed approach with the DS model based on specific circumstances or regions to ensure the optimum treatment of patients with acute ischemic stroke (AIS). Appropriate transport for patients with LVO improves the prognosis of AIS.

Purpose: The aim of this study is to compare the detection ability of quality of life (QoL) changes and responsiveness of the KOrean QUality of life in Stomach cancer patients Study group (KOQUSS)-40 and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ). Materials and Methods: A multicenter prospective observational study was conducted to evaluate QoL changes after various gastrectomies between January 2021 and April 2022. Participants were instructed to complete the KOQUSS-40 and EORTC QLQ-C30/STO22 preoperatively and at 1, 3, 6, and 12 months postoperatively. QoL changes over time and QoL responsiveness were assessed for each questionnaire. Results: Data from 491 patients who underwent curative gastrectomy for gastric cancer at 22 institutions were analyzed. The summary scores of the KOQUSS-40 and EORTC QLQ-STO22 showed significant differences between the total and proximal gastrectomy groups (p=0.044 and p=0.038, respectively), but no difference was observed for the EORTC QLQ-C30. Dysphagia on the KOQUSS-40 was significantly different between the total and proximal gastrectomy groups (p=0.031); however, dysphagia on the EORTC QLQ-STO22 did not differ. The responsiveness of the KOQUSS-40 was similar to that of the EORTC QLQ in patients who experienced ≥ 10% body weight loss, but approximately 10% less in patients receiving adjuvant chemotherapy than the EORTC QLQ. Conclusion KOQUSS-40 has several advantages over EORTC QLQ-C30/STO22 when comparing QoL between the total and proximal gastrectomy groups. The findings provide information for researchers investigating the QoL of patients who have undergone curative gastrectomy for gastric cancer.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.