Purpose: This study aimed to determine whether genetic factors affect the location of dilated perivascular spaces (dPVS) by comparing healthy young twins and non-twin (NT) siblings. Materials and Methods: A total of 700 healthy young adult twins and NT siblings [138 monozygotic (MZ) twin pairs, 79 dizygotic (DZ) twin pairs, and 133 NT sibling pairs] were collected from the Human Connectome Project dataset. dPVS was automatically segmented and normalized to standard space. Then, spatial similarity indices [mean squared error (MSE), structural similarity (SSIM), and dice similarity (DS)] were calculated for dPVS in the basal ganglia (BGdPVS) and white matter (WMdPVS) between paired subjects before and after propensity score matching of dPVS volumes between groups. Within-pair correlations for the regional volumes of dVPS were also assessed using the intraclass correlation coefficient. Results: The spatial similarity of dPVS was significantly higher in MZ twins [higher DS (median, 0.382 and 0.310) and SSIM (0.963 and 0.887) and lower MSE (0.005 and 0.005) for BGdPVS and WMdPVS, respectively] than in DZ twins [DS (0.121 and 0.119), SSIM (0.941 and 0.868), and MSE (0.010 and 0.011)] and NT siblings [DS (0.106 and 0.097), SSIM (0.924 and 0.848), and MSE (0.016 and 0.017)]. No significant difference was found between DZ twins and NT siblings. Similar results were found even after the subjects were matched according to dPVS volume. Regional dPVS volumes were also more correlated within pairs in MZ twins than in DZ twins and NT siblings. Conclusion Our results suggest that genetic factors affect the location of dPVS.

Purpose: This study aimed to determine whether genetic factors affect the location of dilated perivascular spaces (dPVS) by comparing healthy young twins and non-twin (NT) siblings. Materials and Methods: A total of 700 healthy young adult twins and NT siblings [138 monozygotic (MZ) twin pairs, 79 dizygotic (DZ) twin pairs, and 133 NT sibling pairs] were collected from the Human Connectome Project dataset. dPVS was automatically segmented and normalized to standard space. Then, spatial similarity indices [mean squared error (MSE), structural similarity (SSIM), and dice similarity (DS)] were calculated for dPVS in the basal ganglia (BGdPVS) and white matter (WMdPVS) between paired subjects before and after propensity score matching of dPVS volumes between groups. Within-pair correlations for the regional volumes of dVPS were also assessed using the intraclass correlation coefficient. Results: The spatial similarity of dPVS was significantly higher in MZ twins [higher DS (median, 0.382 and 0.310) and SSIM (0.963 and 0.887) and lower MSE (0.005 and 0.005) for BGdPVS and WMdPVS, respectively] than in DZ twins [DS (0.121 and 0.119), SSIM (0.941 and 0.868), and MSE (0.010 and 0.011)] and NT siblings [DS (0.106 and 0.097), SSIM (0.924 and 0.848), and MSE (0.016 and 0.017)]. No significant difference was found between DZ twins and NT siblings. Similar results were found even after the subjects were matched according to dPVS volume. Regional dPVS volumes were also more correlated within pairs in MZ twins than in DZ twins and NT siblings. Conclusion Our results suggest that genetic factors affect the location of dPVS.

Purpose: This study aimed to determine whether genetic factors affect the location of dilated perivascular spaces (dPVS) by comparing healthy young twins and non-twin (NT) siblings. Materials and Methods: A total of 700 healthy young adult twins and NT siblings [138 monozygotic (MZ) twin pairs, 79 dizygotic (DZ) twin pairs, and 133 NT sibling pairs] were collected from the Human Connectome Project dataset. dPVS was automatically segmented and normalized to standard space. Then, spatial similarity indices [mean squared error (MSE), structural similarity (SSIM), and dice similarity (DS)] were calculated for dPVS in the basal ganglia (BGdPVS) and white matter (WMdPVS) between paired subjects before and after propensity score matching of dPVS volumes between groups. Within-pair correlations for the regional volumes of dVPS were also assessed using the intraclass correlation coefficient. Results: The spatial similarity of dPVS was significantly higher in MZ twins [higher DS (median, 0.382 and 0.310) and SSIM (0.963 and 0.887) and lower MSE (0.005 and 0.005) for BGdPVS and WMdPVS, respectively] than in DZ twins [DS (0.121 and 0.119), SSIM (0.941 and 0.868), and MSE (0.010 and 0.011)] and NT siblings [DS (0.106 and 0.097), SSIM (0.924 and 0.848), and MSE (0.016 and 0.017)]. No significant difference was found between DZ twins and NT siblings. Similar results were found even after the subjects were matched according to dPVS volume. Regional dPVS volumes were also more correlated within pairs in MZ twins than in DZ twins and NT siblings. Conclusion Our results suggest that genetic factors affect the location of dPVS.

Purpose: This study aimed to determine whether genetic factors affect the location of dilated perivascular spaces (dPVS) by comparing healthy young twins and non-twin (NT) siblings. Materials and Methods: A total of 700 healthy young adult twins and NT siblings [138 monozygotic (MZ) twin pairs, 79 dizygotic (DZ) twin pairs, and 133 NT sibling pairs] were collected from the Human Connectome Project dataset. dPVS was automatically segmented and normalized to standard space. Then, spatial similarity indices [mean squared error (MSE), structural similarity (SSIM), and dice similarity (DS)] were calculated for dPVS in the basal ganglia (BGdPVS) and white matter (WMdPVS) between paired subjects before and after propensity score matching of dPVS volumes between groups. Within-pair correlations for the regional volumes of dVPS were also assessed using the intraclass correlation coefficient. Results: The spatial similarity of dPVS was significantly higher in MZ twins [higher DS (median, 0.382 and 0.310) and SSIM (0.963 and 0.887) and lower MSE (0.005 and 0.005) for BGdPVS and WMdPVS, respectively] than in DZ twins [DS (0.121 and 0.119), SSIM (0.941 and 0.868), and MSE (0.010 and 0.011)] and NT siblings [DS (0.106 and 0.097), SSIM (0.924 and 0.848), and MSE (0.016 and 0.017)]. No significant difference was found between DZ twins and NT siblings. Similar results were found even after the subjects were matched according to dPVS volume. Regional dPVS volumes were also more correlated within pairs in MZ twins than in DZ twins and NT siblings. Conclusion Our results suggest that genetic factors affect the location of dPVS.

Purpose: This study aimed to determine whether genetic factors affect the location of dilated perivascular spaces (dPVS) by comparing healthy young twins and non-twin (NT) siblings. Materials and Methods: A total of 700 healthy young adult twins and NT siblings [138 monozygotic (MZ) twin pairs, 79 dizygotic (DZ) twin pairs, and 133 NT sibling pairs] were collected from the Human Connectome Project dataset. dPVS was automatically segmented and normalized to standard space. Then, spatial similarity indices [mean squared error (MSE), structural similarity (SSIM), and dice similarity (DS)] were calculated for dPVS in the basal ganglia (BGdPVS) and white matter (WMdPVS) between paired subjects before and after propensity score matching of dPVS volumes between groups. Within-pair correlations for the regional volumes of dVPS were also assessed using the intraclass correlation coefficient. Results: The spatial similarity of dPVS was significantly higher in MZ twins [higher DS (median, 0.382 and 0.310) and SSIM (0.963 and 0.887) and lower MSE (0.005 and 0.005) for BGdPVS and WMdPVS, respectively] than in DZ twins [DS (0.121 and 0.119), SSIM (0.941 and 0.868), and MSE (0.010 and 0.011)] and NT siblings [DS (0.106 and 0.097), SSIM (0.924 and 0.848), and MSE (0.016 and 0.017)]. No significant difference was found between DZ twins and NT siblings. Similar results were found even after the subjects were matched according to dPVS volume. Regional dPVS volumes were also more correlated within pairs in MZ twins than in DZ twins and NT siblings. Conclusion Our results suggest that genetic factors affect the location of dPVS.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Background: Hand hygiene is considered the simplest and most cost-effective method of infection prevention. Regular observation and feedback on hand hygiene compliance are key strategies for its enhancement. This study evaluated the effectiveness of hand hygiene surveillance, including direct observation and feedback, by comprehensively analyzing the reported hand hygiene compliance within the Korean National Healthcare-Associated Infections Surveillance System from 2019 to 2022. Methods: Participating medical institutions included general hospitals and hospitals with infection control departments that consented to participate. Hand hygiene surveillance was conducted using direct observation. Collected data, including healthcare workers, clinical areas, hand hygiene moments, and hand hygiene compliance, were recorded to calculate hand hygiene compliance rates. Additionally, the volume of alcohol-based hand sanitizers used per patient per day was investigated as an indirect indicator of hand hygiene compliance. The study was conducted from July 2019 to December 2022. Results: Hand hygiene compliance increased from 87.2% in Q3 2019 to 89.9% in 2022. Nurses and medical technologists showed the highest compliance rates, whereas doctors showed the lowest compliance rates. Intensive care units excelled in compliance, whereas emergency de partments lagged. Compliance was highest after patient contact and lowest when the patient’s surroundings were touched. Larger hospitals consumed more alcohol-based hand sanitizers than smaller hospitals did. Conclusion This study confirmed an improvement in hand hygiene compliance through sustained surveillance, indicating its contribution not only to preventing infection transfer within healthcare facilities but also to fostering a culture of hand hygiene in the country.

The treatment strategy for postmenopausal symptoms resulting from estrogen deficiency in breast cancer survivors receiving endocrine therapy should differ from that in normal women. Several nonhormonal pharmacological therapies can be used to treat vasomotor symptoms. Cognitive-behavioral therapy can help alleviate psychophysiological symptoms, including depression and sleep disorders.Topical vaginal estrogen and moisturizers may aid in treating genitourinary symptoms. Additionally, chronic conditions must be individually managed. Prevention of osteoporosis should always be included in the management, and physicians should be alert to possible cardiovascular risk and cognitive function changes.

Objectives: Bone mineral density (BMD) is measured in the hip and posteroanterior spine; moreover, according to the 2019 International Society for Clinical Densitometry guidelines, unilateral hip can be used. This study aimed to determine whether there is a difference between the BMD of both the femurs in postmenopausal women. Methods: A total of 343 postmenopausal women were enrolled in this study from January 1, 2010, to December 31, 2019 at a single tertiary hospital. By using the Hologic® Horizon W DXA System, the femur and spine BMD was measured; BMD was recorded in g/cm 2 .Following regions were analyzed in both the femurs: the femur neck, the trochanter area, and total femur. Results: Mean age at imaging was 62 ± 9.7 years, and significant difference in the total BMD of both the femurs (P = 0.003) was observed. In secondary analysis, patients with osteoporosis showed significant contralateral BMD discrepancies in trochanter and total proximal femur BMD (P = 0.041 and P = 0.011, respectively). However, in women with normal BMD, no significant difference between the right and left femur BMD was observed. Furthermore, measurement of solely the unilateral hip can lead to a 16.9% of underdiagnosis in postmenopausal women. Conclusions In conclusion, it is necessary to check BMD in both hips, particularly in patients suspected of osteoporosis.