Background: and Purpose: Given the irreversible nature of dementia, this study examined the effects of a 20-week exercise-based dementia prevention program in community-dwelling older adults, focusing on prior exercise experience and program adherence. Methods: In this exploratory, non-randomized trial, 55 older adults (65–79 years) were allocated to an intervention (n=26) or control (n=29) group, and blinding was not feasible.The intervention comprised supervised rhythmic aerobic exercise with cognitive-motor components performed three times per week. Cognition was the primary outcome, and secondary outcomes included physical fitness, blood pressure, and blood biomarkers.Subgroup analyses classified participants by prior exercise experience and intervention exposure: G1 and G2 comprised control subgroups with no intervention exposure, whereas G3 and G4 comprised intervention-exposed subgroups stratified by adherence. Results: No significant group-by-time interactions were observed for cognitive outcomes.Participants with prior exercise experience and low adherence (G2) showed significant improvement on the Korean Mini-Mental State Examination (β=1.66, p=0.024) despite declines in physical fitness, whereas higher adherence in G3–G4 was associated with stable or favorable physical performance, with G4 showing a positive trend in the 30-second sit-tostand test. Systolic blood pressure decreased significantly in G2–G4. Conclusions Although overall cognitive gains were modest and not group specific, prior exercise experience and sustained adherence were associated with favorable changes in physical fitness and vascular outcomes, suggesting that tailored multicomponent exercise programs and long-term engagement may help promote cognitive health in older adults.

Background: and Purpose: Tailored physical exercise interventions have the potential to promote cognitive health in older adults and offer significant advantages for those more vulnerable to decline. The specific relationship between physical fitness and cognition among the elderly has not been clearly established. The purpose of this investigation was to assess the relationship between physical fitness and cognitive function in older Korean adults. Methods: Eighty-four community-dwelling older adults (mean age: 70.7±5.3 years; 81.0% female) completed a standardized physical fitness battery assessing handgrip strength, sit-and-reach, 30-second sit-to-stand, 2-minute stationary march, 3-m sit-walk-and-return, figure-8-walk, and T-wall response time. Cognitive function was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Descriptive statistics, partial correlation analyses, and stepwise multiple linear regression were conducted. Results: Slower T-wall response time was significantly correlated with lower RBANS total index, immediate memory, and delayed memory scores. In regression models, slower T-wall response time was independently associated with lower RBANS total index (β=−0.234, p=0.026) and delayed memory scores (β=−0.295, p=0.029). The regression model for immediate memory was not statistically significant overall; therefore, no predictive conclusion was drawn for this domain. Higher education showed a significant positive association with cognitive performance. Conclusions Coordination, as measured by T-wall response time, emerged as the only physical fitness component consistently associated with cognitive performance in older adults. Coordination-related fitness may be an important correlate of cognitive function in older adults and a promising target for future exercise interventions.

Objective: This study aimed to assess the association between exposure to gadolinium-based contrast agents (GBCAs) and the risk of parkinsonism according to the GBCA type. Materials and Methods: Individuals aged ≥40 years who underwent first-ever magnetic resonance imaging (MRI) examinations between 2011 and 2014 were identified from the Korean nationwide population-based health insurance claims database and followed up until 2022. Individuals were divided into those who underwent at least one GBCA-enhanced MRI, and those who underwent only non-enhanced MRI. GBCA-exposed individuals were further categorized into those exposed only to linear or macrocyclic GBCAs, after excluding those exposed to both types. The primary event of interest was allcause parkinsonism. Secondary events included all-cause parkinsonism requiring medication, Parkinson’s disease (PD), atypical parkinsonism, and secondary parkinsonism. Hazard ratios (HRs) were estimated using multivariable Cox proportional hazard regression models for exposure to linear and macrocyclic GBCAs, with the non-enhanced MRI group serving as a reference. The models were adjusted for age, sex, smoking status, alcohol consumption, regular exercise, body mass index, estimated glomerular filtration rate, and comorbidities. Subgroup analyses were performed according to age, sex, renal function, and history of cancer. Results: A total of 222,977 individuals were included in this study. Among them, 92,230, 48,335, and 82,412 individuals underwent non-enhanced, linear GBCA-enhanced, and macrocyclic GBCA-enhanced MRI, respectively. Exposure to linear GBCAs slightly increased the risk of all-cause parkinsonism (adjusted HR, 1.13 [97.5% confidence interval, 1.08–1.19]), while exposure to macrocyclic GBCAs did not increase the risk (adjusted HR, 1.00 [97.5% confidence interval, 0.95–1.05]).The results were similar for all-cause parkinsonism requiring medication, PD, and secondary parkinsonism, whereas no significant association was observed for atypical parkinsonism. Conclusion Exposure to linear GBCAs may slightly increase the risk of parkinsonism in adults, whereas exposure to macrocyclic GBCAs may not. Caution should be exercised when using linear GBCAs until further evidence emerges.

Purpose: To evaluate the feasibility and utility of deep learning-based computer-aided diagnosis (DL-CAD) for the detection of pulmonary nodules on coronary artery calcium (CAC)-scoring computed tomography (CT). Materials and Methods: This retrospective study included 273 patients (aged 63.9±13.2 years; 129 men) who underwent CACscoring CT. A DL-CAD system based on thin-section images was used for pulmonary nodule detection, and two independent junior readers reviewed the standard CAC-scoring CT scans with and without referencing DL-CAD results. A reference standard was established through the consensus of two experienced radiologists. Sensitivity, positive predictive value, and F1-score were assessed on a per-nodule and per-patient basis. The patients’ medical records were monitored until November 2023. Results: A total of 269 nodules were identified in 129 patients. With DL-CAD assistance, the readers’ sensitivity significantly improved (65% vs. 80% for reader 1; 82% vs. 86% for reader 2; all p<0.001), without a notable increase in the number of false-positives per case (0.11 vs. 0.13, p=0.078 for reader 1; 0.11 vs. 0.11, p>0.999 for reader 2). Per-patient analysis also enhanced sensitivity with DL-CAD assistance (73% vs. 84%, p<0.001 for reader 1; 89% vs. 91%, p=0.250 for reader 2). During follow-up, lung cancer was diagnosed in four patients (1.5%). Among them, two had lesions detected on CAC-scoring CT, both of which were successfully identified by DL-CAD. Conclusion DL-CAD based on thin-section images can assist less experienced readers in detecting pulmonary nodules on CACscoring CT scans, improving detection sensitivity without significantly increasing false-positives.

Background: and Purpose We aimed to determine the proportion of Korean patients with early Alzheimer’s disease (AD) who are eligible to receive lecanemab based on the United States Appropriate Use Recommendations (US AUR), and also identify the barriers to this treatment. Methods: We retrospectively enrolled 6,132 patients with amnestic mild cognitive impairment or mild amnestic dementia at 13 hospitals from June 2023 to May 2024. Among them, 2,058 patients underwent amyloid positron emission tomography (PET) and 1,199 (58.3%) of these patients were amyloid-positive on PET. We excluded 732 patients who did not undergo brain magnetic resonance imaging between June 2023 and May 2024. Finally, 467 patients were included in the present study. Results: When applying the criteria of the US AUR, approximately 50% of patients with early AD were eligible to receive lecanemab treatment. Among the 467 included patients, 36.8% did not meet the inclusion criterion of a Mini-Mental State Examination (MMSE) score of ≥22. Conclusions Eligibility for lecanemab treatment was not restricted to Korean patients with early AD except for those with an MMSE score of ≥22. The MMSE criteria should therefore be reconsidered in areas with a higher proportion of older people, who tend to have lower levels of education.

Objectives: This study examined the symptoms and emotions expressed by older adults with cancer and their caregivers in South Korean online cancer communities. It aimed to identify narrative patterns and provide insights to inform personalized care strategies. Methods: We analyzed 6,908 user-generated posts collected from major online cancer communities in South Korea. Keyword frequency analysis, term frequency-inverse document frequency, 2-gram analysis, and latent Dirichlet allocation-based topic modeling were applied to explore language patterns. Sentiment analysis identified 12 emotional categories, and Pearson correlation coefficients were calculated to examine associations between symptoms and emotional expressions. All data were cleaned and standardized prior to analysis. Results: Many users expressed anxiety (20.63%) and depression (19.59%), frequently associated with chemotherapy and sleep disturbances. Among reported symptoms, sleep problems carried the highest negative sentiment (79.81%), underscoring their profound impact on well-being. Topic modeling consistently revealed seven recurring themes, including treatment decision-making, symptom management, and concerns about family, demonstrating the layered and personalized experiences of older cancer patients and their caregivers. Conclusions This study explored treatment-related and symptom-related difficulties faced by older adults with cancer. Many reported significant emotional strain, especially anxiety, depression, and sleep disturbances. These findings highlight the necessity for supportive strategies addressing both psychological and physical aspects of care. Future research could investigate the utility of large language models in analyzing these narratives, provided the data is ethically managed and appropriate for such use.

Purpose: To evaluate the feasibility and utility of deep learning-based computer-aided diagnosis (DL-CAD) for the detection of pulmonary nodules on coronary artery calcium (CAC)-scoring computed tomography (CT). Materials and Methods: This retrospective study included 273 patients (aged 63.9±13.2 years; 129 men) who underwent CACscoring CT. A DL-CAD system based on thin-section images was used for pulmonary nodule detection, and two independent junior readers reviewed the standard CAC-scoring CT scans with and without referencing DL-CAD results. A reference standard was established through the consensus of two experienced radiologists. Sensitivity, positive predictive value, and F1-score were assessed on a per-nodule and per-patient basis. The patients’ medical records were monitored until November 2023. Results: A total of 269 nodules were identified in 129 patients. With DL-CAD assistance, the readers’ sensitivity significantly improved (65% vs. 80% for reader 1; 82% vs. 86% for reader 2; all p<0.001), without a notable increase in the number of false-positives per case (0.11 vs. 0.13, p=0.078 for reader 1; 0.11 vs. 0.11, p>0.999 for reader 2). Per-patient analysis also enhanced sensitivity with DL-CAD assistance (73% vs. 84%, p<0.001 for reader 1; 89% vs. 91%, p=0.250 for reader 2). During follow-up, lung cancer was diagnosed in four patients (1.5%). Among them, two had lesions detected on CAC-scoring CT, both of which were successfully identified by DL-CAD. Conclusion DL-CAD based on thin-section images can assist less experienced readers in detecting pulmonary nodules on CACscoring CT scans, improving detection sensitivity without significantly increasing false-positives.

Objectives: This study examined the symptoms and emotions expressed by older adults with cancer and their caregivers in South Korean online cancer communities. It aimed to identify narrative patterns and provide insights to inform personalized care strategies. Methods: We analyzed 6,908 user-generated posts collected from major online cancer communities in South Korea. Keyword frequency analysis, term frequency-inverse document frequency, 2-gram analysis, and latent Dirichlet allocation-based topic modeling were applied to explore language patterns. Sentiment analysis identified 12 emotional categories, and Pearson correlation coefficients were calculated to examine associations between symptoms and emotional expressions. All data were cleaned and standardized prior to analysis. Results: Many users expressed anxiety (20.63%) and depression (19.59%), frequently associated with chemotherapy and sleep disturbances. Among reported symptoms, sleep problems carried the highest negative sentiment (79.81%), underscoring their profound impact on well-being. Topic modeling consistently revealed seven recurring themes, including treatment decision-making, symptom management, and concerns about family, demonstrating the layered and personalized experiences of older cancer patients and their caregivers. Conclusions This study explored treatment-related and symptom-related difficulties faced by older adults with cancer. Many reported significant emotional strain, especially anxiety, depression, and sleep disturbances. These findings highlight the necessity for supportive strategies addressing both psychological and physical aspects of care. Future research could investigate the utility of large language models in analyzing these narratives, provided the data is ethically managed and appropriate for such use.

Background: and Purpose We aimed to determine the proportion of Korean patients with early Alzheimer’s disease (AD) who are eligible to receive lecanemab based on the United States Appropriate Use Recommendations (US AUR), and also identify the barriers to this treatment. Methods: We retrospectively enrolled 6,132 patients with amnestic mild cognitive impairment or mild amnestic dementia at 13 hospitals from June 2023 to May 2024. Among them, 2,058 patients underwent amyloid positron emission tomography (PET) and 1,199 (58.3%) of these patients were amyloid-positive on PET. We excluded 732 patients who did not undergo brain magnetic resonance imaging between June 2023 and May 2024. Finally, 467 patients were included in the present study. Results: When applying the criteria of the US AUR, approximately 50% of patients with early AD were eligible to receive lecanemab treatment. Among the 467 included patients, 36.8% did not meet the inclusion criterion of a Mini-Mental State Examination (MMSE) score of ≥22. Conclusions Eligibility for lecanemab treatment was not restricted to Korean patients with early AD except for those with an MMSE score of ≥22. The MMSE criteria should therefore be reconsidered in areas with a higher proportion of older people, who tend to have lower levels of education.

Purpose: To evaluate the feasibility and utility of deep learning-based computer-aided diagnosis (DL-CAD) for the detection of pulmonary nodules on coronary artery calcium (CAC)-scoring computed tomography (CT). Materials and Methods: This retrospective study included 273 patients (aged 63.9±13.2 years; 129 men) who underwent CACscoring CT. A DL-CAD system based on thin-section images was used for pulmonary nodule detection, and two independent junior readers reviewed the standard CAC-scoring CT scans with and without referencing DL-CAD results. A reference standard was established through the consensus of two experienced radiologists. Sensitivity, positive predictive value, and F1-score were assessed on a per-nodule and per-patient basis. The patients’ medical records were monitored until November 2023. Results: A total of 269 nodules were identified in 129 patients. With DL-CAD assistance, the readers’ sensitivity significantly improved (65% vs. 80% for reader 1; 82% vs. 86% for reader 2; all p<0.001), without a notable increase in the number of false-positives per case (0.11 vs. 0.13, p=0.078 for reader 1; 0.11 vs. 0.11, p>0.999 for reader 2). Per-patient analysis also enhanced sensitivity with DL-CAD assistance (73% vs. 84%, p<0.001 for reader 1; 89% vs. 91%, p=0.250 for reader 2). During follow-up, lung cancer was diagnosed in four patients (1.5%). Among them, two had lesions detected on CAC-scoring CT, both of which were successfully identified by DL-CAD. Conclusion DL-CAD based on thin-section images can assist less experienced readers in detecting pulmonary nodules on CACscoring CT scans, improving detection sensitivity without significantly increasing false-positives.