Objectives: This study aimed to explore factors influencing satisfaction with medical services among medically underserved populations at the free medical clinic, providing data to improve free medical services for these populations. Methods: We employed a descriptive correlational study design involving 112 individuals (aged 19 years and older) from medically underserved populations who visited the clinic. Data were collected through face-to-face surveys from September to October 2023, and statistical analyses (t-tests, analysis of variance, Pearson correlation, and hierarchical multiple regression) were used to identify key predictors of satisfaction. Results: Perceived support from healthcare providers emerged as the strongest predictor ofsatisfaction with medical services, demonstrating a significant positive association. While socialsupport was positively correlated with perceived support from healthcare providers, it did not independently predict satisfaction. Conclusion These findings underscore the importance of healthcare provider and social supportin increasing satisfaction with medical services among medically underserved populations.Developing tailored healthcare programs and specialized healthcare provider training are essential strategies to improve healthcare access and outcomes for these vulnerable groups.

Purpose: This study aimed to present a novel method for estimating the effective atomic number(Zeff ) using dual-energy computed tomography (DECT) designed to improve accuracy andstreamline clinical workflows by reducing computational complexity. Methods: The proposed model leverages the DECT-derived mass attenuation coefficients without detailed compositional analysis. By incorporating additional parameters into the conventional Rutherford model, such as exponential and trigonometric functions, the model effectively capturescomplex variations in attenuation, enabling precise Zeff estimation. Model fitting was performedusing dual-energy data and evaluated using the percentage difference in error rates. Results: Compared with the Rutherford model, which recorded a maximum error rate of 0.55%, the proposed model demonstrated a significantly lower maximum error rate of 0.15%, highlightingits precision. Zeff estimates for various materials closely matched the reference values, confirmingthe improved accuracy of the model. Conclusions The proposed DECT-based model provides a practical and efficient approach to Zeff estimation, with potential applications in radiation oncology, particularly for accurate stopping power ratio calculations in proton and heavy ion therapies.

Objectives: This study aimed to explore factors influencing satisfaction with medical services among medically underserved populations at the free medical clinic, providing data to improve free medical services for these populations. Methods: We employed a descriptive correlational study design involving 112 individuals (aged 19 years and older) from medically underserved populations who visited the clinic. Data were collected through face-to-face surveys from September to October 2023, and statistical analyses (t-tests, analysis of variance, Pearson correlation, and hierarchical multiple regression) were used to identify key predictors of satisfaction. Results: Perceived support from healthcare providers emerged as the strongest predictor ofsatisfaction with medical services, demonstrating a significant positive association. While socialsupport was positively correlated with perceived support from healthcare providers, it did not independently predict satisfaction. Conclusion These findings underscore the importance of healthcare provider and social supportin increasing satisfaction with medical services among medically underserved populations.Developing tailored healthcare programs and specialized healthcare provider training are essential strategies to improve healthcare access and outcomes for these vulnerable groups.

Purpose: This study aimed to present a novel method for estimating the effective atomic number(Zeff ) using dual-energy computed tomography (DECT) designed to improve accuracy andstreamline clinical workflows by reducing computational complexity. Methods: The proposed model leverages the DECT-derived mass attenuation coefficients without detailed compositional analysis. By incorporating additional parameters into the conventional Rutherford model, such as exponential and trigonometric functions, the model effectively capturescomplex variations in attenuation, enabling precise Zeff estimation. Model fitting was performedusing dual-energy data and evaluated using the percentage difference in error rates. Results: Compared with the Rutherford model, which recorded a maximum error rate of 0.55%, the proposed model demonstrated a significantly lower maximum error rate of 0.15%, highlightingits precision. Zeff estimates for various materials closely matched the reference values, confirmingthe improved accuracy of the model. Conclusions The proposed DECT-based model provides a practical and efficient approach to Zeff estimation, with potential applications in radiation oncology, particularly for accurate stopping power ratio calculations in proton and heavy ion therapies.

Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.

Background and Objectives: Cigarette smoking is a major risk factor for atherosclerosis.Nicotine, a crucial constituent of tobacco, contributes to atherosclerosis development and progression. However, evidence of the association between nicotine and neointima formation is limited. We aimed to evaluate whether nicotine enhances neointimal hyperplasia in the native epicardial coronary arteries of pigs after percutaneous coronary intervention (PCI) with drug-eluting stents (DES). Methods: After coronary angiography (CAG) and quantitative coronary angiography (QCA), we implanted 20 DES into 20 pigs allocated to 2 groups: no-nicotine (n=10) and nicotine (n=10) groups. Post-PCI CAG and QCA were performed immediately. Follow-up CAG, QCA, optical coherence tomography (OCT), and histopathological analyses were performed 2 months post-PCI. Results: Despite intergroup similarities in the baseline QCA findings, OCT analysis showed that the nicotine group had a smaller mean stent and lumen areas, a larger mean neointimal area, greater percent area stenosis, and higher peri-strut fibrin and inflammation scores than the no-nicotine group. In immunofluorescence analysis, the nicotine group displayed higher expression of CD68 and α-smooth muscle actin but lower CD31 expression than the no-nicotine group. Conclusions Nicotine inhibited re-endothelialization and promoted inflammation and NIH after PCI with DES in a porcine model.

Vaccine-induced hypermetabolic lymph nodes have been clinically observed following coronavirus disease 2019 (COVID-19) mRNA vaccination. Specifically, the booster dose of the mRNA vaccines, produced by Pfizer and Moderna, has been linked to a relatively high incidence of lymphadenopathy. We present the case of a kidney transplant recipient who developed an enlarged abdominal mass after receiving a booster dose of the COVID-19 mRNA vaccine. This mass occupied the retroperitoneal space, infiltrated the psoas muscle, and resulted in ureteric compression and hydronephrosis. Percutaneous drainage and analysis of the perirenal fluid revealed the presence of lymphatic fluid. In summary, lymphadenopathy is a recognized adverse reaction to the Pfizer and Moderna vaccines. Patients with compromised immune systems should be informed about the incidence and potential severity of lymphadenopathy following booster vaccination.

Purpose: Cancer poses a significant global health challenge, demanding precise genomic testing for individualized treatment strategies. Targeted-panel sequencing (TPS) has improved personalized oncology but often lacks comprehensive coverage of crucial cancer alterations. Whole-genome sequencing (WGS) addresses this gap, offering extensive genomic testing. This study demonstrates the medical potential of WGS. Materials and Methods: This study evaluates target-enhanced WGS (TE-WGS), a clinical-grade WGS method sequencing both cancer and matched normal tissues. Forty-nine patients with various solid cancer types underwent both TE-WGS and TruSight Oncology 500 (TSO500), one of the mainstream TPS approaches. Results: TE-WGS detected all variants reported by TSO500 (100%, 498/498). A high correlation in variant allele fractions was observed between TE-WGS and TSO500 (r=0.978). Notably, 223 variants (44.8%) within the common set were discerned exclusively by TE-WGS in peripheral blood, suggesting their germline origin. Conversely, the remaining subset of 275 variants (55.2%) were not detected in peripheral blood using the TE-WGS, signifying them as bona fide somatic variants. Further, TE-WGS provided accurate copy number profiles, fusion genes, microsatellite instability, and homologous recombination deficiency scores, which were essential for clinical decision-making. Conclusion TE-WGS is a comprehensive approach in personalized oncology, matching TSO500’s key biomarker detection capabilities. It uniquely identifies germline variants and genomic instability markers, offering additional clinical actions. Its adaptability and cost-effectiveness underscore its clinical utility, making TE-WGS a valuable tool in personalized cancer treatment.

Purpose: Recent development in perioperative treatment of resectable non–small cell lung cancer (NSCLC) have changed the landscape of early lung cancer management. The ADAURA trial has demonstrated the efficacy of adjuvant osimertinib treatment in resectable NSCLC patients; however, studies are required to show which subgroup of patients are at a high risk of relapse and require adjuvant epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor treatment. This study evaluated risk factors for postoperative relapse among patients who underwent complete resection. Materials and Methods: Data were obtained from the Korean Association for Lung Cancer Registry (KALC-R), a database created using a retrospective sampling survey by the Korean Central Cancer Registry (KCCR) and the Lung Cancer Registration Committee. Results: A total of 3,176 patients who underwent curative resection was evaluated. The mean observation time was approximately 35.4 months. Among stage I to IIIA NSCLC patients, the EGFR-mutant subgroup included 867 patients, and 75.2%, 11.2%, and 11.8% were classified as stage I, stage II, and stage III, respectively. Within the EGFR-mutant subgroup, 44 (5.1%) and 121 (14.0%) patients showed early and late recurrence, respectively. Multivariate analysis on association with postoperative relapse among the EGFR-mutant subgroup showed that age, pathologic N and TNM stages, pleural invasion status, and surgery type were independent significant factors. Conclusion Among the population that underwent complete resection for early NSCLC with EGFR mutation, patients with advanced stage, pleural invasion, or limited resection are more likely to show postoperative relapse.