Atherosclerosis is a major contributor to cardiovascular disease, characterized by inflammation and lipid accumulation in arterial walls, leading to plaque formation. Elevated low-density lipoprotein cholesterol is a primary risk factor for atherosclerosis. All-trans retinoic acid (ATRA), a metabolite of vitamin A, has demonstrated anti-inflammatory effects and potential in regulating vascular injury. 9-cisretinoic acid (9cRA) is an active metabolite of vitamin A and activates the retinoid X receptor. This study investigates whether potassium retinoate (PA9RA), a synthetic combination of ATRA and 9cRA, offers superior efficacy in treating atherosclerosis compared to established treatments such as clopidogrel and atorvastatin. Male ApoE -/- mice were fed a Western-type diet and treated with PA9RA, clopidogrel, or atorvastatin for 10 weeks. The body weight, organ weight, serum biochemistry, and histopathology, including atherosclerotic lesion area and liver steatosis were assessed. PA9RA treatment led to a significant reduction in body weight and inguinal fat, with the 45 mg/kg/day dose showing marked efficacy in decreasing atherosclerotic lesion size and ameliorating liver steatosis. Histopathological evaluation revealed decreased foam cell formation and improved liver histology in PA9RA-treated groups compared to controls. Notable side effects included epidermal hyperplasia and gastric hyperplasia at high doses of PA9RA. PA9RA exhibits superior efficacy over clopidogrel and atorvastatin in ameliorating atherosclerosis and fatty liver in ApoE –/–mice. This study highlights PA9RA's potential as a promising therapeutic agent for atherosclerosis. Further research is needed to elucidate its mechanisms of action and assess long-term safety and efficacy.

Purpose: Persistent postoperative stiffness is a common complication after arthroscopic rotator cuff repair (ARCR).We hypothesized that a subacromial steroid injection (SAI) may improve the early outcomes in patients with persistent stiffness without increasing steroid-associated complications. Therefore, we evaluated the effectiveness and safety of SAI in patients with persistent stiffness 3 months after ARCR. Methods: We retrospectively analyzed 300 ARCR cases performed between January 2012 and May 2014, in which repair integrity was confirmed at postoperative 3 months. Patients were divided into SAI and control groups. The SAI group received a single SAI (triamcinolone 40 mg and ropivacaine 52.5 mg) to address postoperative stiffness, with no additional SAI thereafter. The control group did not receive any injections until the final follow-up. Functional and radiological outcomes were compared between the two groups. Results: The mean follow-up period was 18.1±4.7 months (range, 12.1–37.2 months), with no difference between groups (p=0.731). At the time of injection, the range of motion was significantly lower in the SAI (all p＜0.001). However, functional outcomes were comparable between the two groups at 3 months after injection and the final follow-up (all p＞ 0.05). The healing failure rate at the final follow-up also did not differ between the SAI and control groups (14.9% vs. 13.2%, p=0.671). Conclusion This short-term follow-up study suggests that the administration of a single SAI to treat persistent stiffness at 3 months after ARCR may improve functional recovery without increasing the risk of healing failure.

Purpose: The study investigated whether incorporating magnetic resonance imaging (MRI) alongside ultrasonography (US) in the preoperative evaluation is associated with differing survival outcomes between male and female breast cancer patients in a matched analysis. Additionally, clinicopathological prognostic factors were analyzed. Methods: Between January 2005 and December 2020, 93 male and 28,191 female patients who underwent breast surgery were screened. Exact matching analysis was conducted for age, pathologic T and N stages, and molecular subtypes. The clinicopathological characteristics and preoperative imaging methods of the matched cohorts were reviewed. Disease-free survival (DFS) and overall survival (OS) were assessed using Kaplan-Meier analysis, and Cox proportional hazards regression analysis was used to identify prognostic factors. Results: A total of 328 breast cancer patients (61 men and 267 women) were included in the matched analysis. Male patients had worse DFS (10-year DFS, 70.6% vs. 89.2%; P=0.001) and OS (10-year OS, 64.4% vs. 96.3%; P<0.001) than female patients. The pathologic index cancer size (hazard ratio [HR], 2.013; 95% confidence interval [CI], 1.063 to 3.810; P=0.032) was associated with worse DFS, whereas there were no significant factors associated with OS. Adding MRI to US for preoperative evaluation was not associated with DFS (HR, 1.117; 95% CI, 0.223 to 5.583; P=0.893) or OS (HR, 1.529; 95% CI, 0.300 to 7.781; P=0.609) in male patients. Conclusion Adding breast MRI to US in the preoperative evaluation was not associated with survival outcomes in male breast cancer patients, and the pathologic index cancer size was associated with worse DFS.

This guideline outlines the use of 18F-fluoro-2-deoxyglucose positron emission tomography / computed tomography for the diagnosis and management of infectious and inflammatory diseases. It provides detailed recommendations for healthcare providers on patient preparation, imaging procedures, and the interpretation of results. Adapted from international standards and tailored to local clinical practices, the guideline emphasizes safety, quality control, and effective use of the technology in various conditions, including spinal infections, diabetic foot, osteomyelitis, vasculitis, and cardiac inflammation. The aim is to assist nuclear medicine professionals in delivering accurate diagnoses and improving patient outcomes while allowing flexibility to adapt to individual patient needs, technological advancements, and evolving medical knowledge. This document is a comprehensive resource for enhancing the quality and safety of 18F-fluoro-2-deoxyglucose positron emission tomography / computed tomography for the evaluation of infectious and inflammatory diseases.Preamble The Korean Society of Nuclear Medicine (KSNM) was established in 1961 to promote the clinical and technological advancement of nuclear medicine in South Korea, with members that include nuclear medicine physicians and associated scientists. The KSNM regularly formulates and revises procedural guidelines for nuclear medicine examinations to enhance the field and improve the quality of patient care. These guidelines are designed to support healthcare professionals in providing appropriate medical care to patients. However, they are not immutable rules or mandatory requirements for conducting examinations.Therefore, KSNM states that these guidelines should not be used in legal actions challenging a healthcare professional’s medical decisions. The ultimate judgment regarding specific procedures or appropriate measures should be made by nuclear medicine physicians, considering the unique circumstances of each case. Deviation from these guidelines does not imply substandard medical practice. Rather, reasonable judgments differing from the guidelines can be made based on the patient’s condition, available resources, and advancements in knowledge or technology. Due to the diversity and complexity of patients, it is often challenging to predict the most appropriate diagnostic and accurate therapeutic responses. Thus, adherence to these guidelines does not always guarantee an exact diagnosis or successful outcomes.The purpose of this guideline is to assist healthcare providers in making reasonable decisions and conducting effective and safe examinations based on current medical knowledge, available resources, and patient needs when performing 18F-fluoro-2-deoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) examinations for infectious/ inflammatory diseases.

Purpose: Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using highresolution biosignals collected within 4 h of arrival. Materials and Methods: Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices. Results: Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables. Conclusion Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.

This guideline outlines the use of 18F-fluoro-2-deoxyglucose positron emission tomography / computed tomography for the diagnosis and management of infectious and inflammatory diseases. It provides detailed recommendations for healthcare providers on patient preparation, imaging procedures, and the interpretation of results. Adapted from international standards and tailored to local clinical practices, the guideline emphasizes safety, quality control, and effective use of the technology in various conditions, including spinal infections, diabetic foot, osteomyelitis, vasculitis, and cardiac inflammation. The aim is to assist nuclear medicine professionals in delivering accurate diagnoses and improving patient outcomes while allowing flexibility to adapt to individual patient needs, technological advancements, and evolving medical knowledge. This document is a comprehensive resource for enhancing the quality and safety of 18F-fluoro-2-deoxyglucose positron emission tomography / computed tomography for the evaluation of infectious and inflammatory diseases.Preamble The Korean Society of Nuclear Medicine (KSNM) was established in 1961 to promote the clinical and technological advancement of nuclear medicine in South Korea, with members that include nuclear medicine physicians and associated scientists. The KSNM regularly formulates and revises procedural guidelines for nuclear medicine examinations to enhance the field and improve the quality of patient care. These guidelines are designed to support healthcare professionals in providing appropriate medical care to patients. However, they are not immutable rules or mandatory requirements for conducting examinations.Therefore, KSNM states that these guidelines should not be used in legal actions challenging a healthcare professional’s medical decisions. The ultimate judgment regarding specific procedures or appropriate measures should be made by nuclear medicine physicians, considering the unique circumstances of each case. Deviation from these guidelines does not imply substandard medical practice. Rather, reasonable judgments differing from the guidelines can be made based on the patient’s condition, available resources, and advancements in knowledge or technology. Due to the diversity and complexity of patients, it is often challenging to predict the most appropriate diagnostic and accurate therapeutic responses. Thus, adherence to these guidelines does not always guarantee an exact diagnosis or successful outcomes.The purpose of this guideline is to assist healthcare providers in making reasonable decisions and conducting effective and safe examinations based on current medical knowledge, available resources, and patient needs when performing 18F-fluoro-2-deoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) examinations for infectious/ inflammatory diseases.

Atherosclerosis is a major contributor to cardiovascular disease, characterized by inflammation and lipid accumulation in arterial walls, leading to plaque formation. Elevated low-density lipoprotein cholesterol is a primary risk factor for atherosclerosis. All-trans retinoic acid (ATRA), a metabolite of vitamin A, has demonstrated anti-inflammatory effects and potential in regulating vascular injury. 9-cisretinoic acid (9cRA) is an active metabolite of vitamin A and activates the retinoid X receptor. This study investigates whether potassium retinoate (PA9RA), a synthetic combination of ATRA and 9cRA, offers superior efficacy in treating atherosclerosis compared to established treatments such as clopidogrel and atorvastatin. Male ApoE -/- mice were fed a Western-type diet and treated with PA9RA, clopidogrel, or atorvastatin for 10 weeks. The body weight, organ weight, serum biochemistry, and histopathology, including atherosclerotic lesion area and liver steatosis were assessed. PA9RA treatment led to a significant reduction in body weight and inguinal fat, with the 45 mg/kg/day dose showing marked efficacy in decreasing atherosclerotic lesion size and ameliorating liver steatosis. Histopathological evaluation revealed decreased foam cell formation and improved liver histology in PA9RA-treated groups compared to controls. Notable side effects included epidermal hyperplasia and gastric hyperplasia at high doses of PA9RA. PA9RA exhibits superior efficacy over clopidogrel and atorvastatin in ameliorating atherosclerosis and fatty liver in ApoE –/–mice. This study highlights PA9RA's potential as a promising therapeutic agent for atherosclerosis. Further research is needed to elucidate its mechanisms of action and assess long-term safety and efficacy.

Purpose: Persistent postoperative stiffness is a common complication after arthroscopic rotator cuff repair (ARCR).We hypothesized that a subacromial steroid injection (SAI) may improve the early outcomes in patients with persistent stiffness without increasing steroid-associated complications. Therefore, we evaluated the effectiveness and safety of SAI in patients with persistent stiffness 3 months after ARCR. Methods: We retrospectively analyzed 300 ARCR cases performed between January 2012 and May 2014, in which repair integrity was confirmed at postoperative 3 months. Patients were divided into SAI and control groups. The SAI group received a single SAI (triamcinolone 40 mg and ropivacaine 52.5 mg) to address postoperative stiffness, with no additional SAI thereafter. The control group did not receive any injections until the final follow-up. Functional and radiological outcomes were compared between the two groups. Results: The mean follow-up period was 18.1±4.7 months (range, 12.1–37.2 months), with no difference between groups (p=0.731). At the time of injection, the range of motion was significantly lower in the SAI (all p＜0.001). However, functional outcomes were comparable between the two groups at 3 months after injection and the final follow-up (all p＞ 0.05). The healing failure rate at the final follow-up also did not differ between the SAI and control groups (14.9% vs. 13.2%, p=0.671). Conclusion This short-term follow-up study suggests that the administration of a single SAI to treat persistent stiffness at 3 months after ARCR may improve functional recovery without increasing the risk of healing failure.

Purpose: The study investigated whether incorporating magnetic resonance imaging (MRI) alongside ultrasonography (US) in the preoperative evaluation is associated with differing survival outcomes between male and female breast cancer patients in a matched analysis. Additionally, clinicopathological prognostic factors were analyzed. Methods: Between January 2005 and December 2020, 93 male and 28,191 female patients who underwent breast surgery were screened. Exact matching analysis was conducted for age, pathologic T and N stages, and molecular subtypes. The clinicopathological characteristics and preoperative imaging methods of the matched cohorts were reviewed. Disease-free survival (DFS) and overall survival (OS) were assessed using Kaplan-Meier analysis, and Cox proportional hazards regression analysis was used to identify prognostic factors. Results: A total of 328 breast cancer patients (61 men and 267 women) were included in the matched analysis. Male patients had worse DFS (10-year DFS, 70.6% vs. 89.2%; P=0.001) and OS (10-year OS, 64.4% vs. 96.3%; P<0.001) than female patients. The pathologic index cancer size (hazard ratio [HR], 2.013; 95% confidence interval [CI], 1.063 to 3.810; P=0.032) was associated with worse DFS, whereas there were no significant factors associated with OS. Adding MRI to US for preoperative evaluation was not associated with DFS (HR, 1.117; 95% CI, 0.223 to 5.583; P=0.893) or OS (HR, 1.529; 95% CI, 0.300 to 7.781; P=0.609) in male patients. Conclusion Adding breast MRI to US in the preoperative evaluation was not associated with survival outcomes in male breast cancer patients, and the pathologic index cancer size was associated with worse DFS.

Purpose: Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using highresolution biosignals collected within 4 h of arrival. Materials and Methods: Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices. Results: Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables. Conclusion Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.