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.

Background/Aims: Combi-elastography is a B-mode ultrasound-based method in which two elastography modalities are utilized simultaneously to assess metabolic dysfunction-associated steatotic liver disease (MASLD). However, the performance of combi-elastography for diagnosing metabolic dysfunction-associated steatohepatitis (MASH) and determining fibrosis severity is unclear. This study compared the diagnostic performances of combi-elastography and vibrationcontrolled transient elastography (VCTE) for identifying hepatic steatosis, fibrosis, and high-risk MASH. Methods: Participants who underwent combi-elastography, VCTE, and liver biopsy were selected from a prospective cohort of patients with clinically suspected MASLD. Combi-elastographyrelated parameters were acquired, and their performances were evaluated using area under the receiver-operating characteristic curve (AUROC) analysis. Results: A total of 212 participants were included. The diagnostic performance for hepatic steatosis of the attenuation coefficient adjusted by covariates from combi-elastography was comparable to that of the controlled attenuation parameter measured by VCTE (AUROC, 0.85 vs 0.85; p=0.925). The performance of the combi-elastography-derived fibrosis index adjusted by covariates for diagnosing significant fibrosis was comparable to that of liver stiffness measured by VCTE (AUROC, 0.77 vs 0.80; p=0.573). The activity index from combi-elastography adjusted by covariates was equivalent to the FibroScan-aspartate aminotransferase score in diagnosing high-risk MASH among participants with MASLD (AUROC, 0.72 vs 0.74; p=0.792). Conclusions The performance of combi-elastography is similar to that of VCTE when evaluating histology of MASLD.

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.

Background/Aims: Combi-elastography is a B-mode ultrasound-based method in which two elastography modalities are utilized simultaneously to assess metabolic dysfunction-associated steatotic liver disease (MASLD). However, the performance of combi-elastography for diagnosing metabolic dysfunction-associated steatohepatitis (MASH) and determining fibrosis severity is unclear. This study compared the diagnostic performances of combi-elastography and vibrationcontrolled transient elastography (VCTE) for identifying hepatic steatosis, fibrosis, and high-risk MASH. Methods: Participants who underwent combi-elastography, VCTE, and liver biopsy were selected from a prospective cohort of patients with clinically suspected MASLD. Combi-elastographyrelated parameters were acquired, and their performances were evaluated using area under the receiver-operating characteristic curve (AUROC) analysis. Results: A total of 212 participants were included. The diagnostic performance for hepatic steatosis of the attenuation coefficient adjusted by covariates from combi-elastography was comparable to that of the controlled attenuation parameter measured by VCTE (AUROC, 0.85 vs 0.85; p=0.925). The performance of the combi-elastography-derived fibrosis index adjusted by covariates for diagnosing significant fibrosis was comparable to that of liver stiffness measured by VCTE (AUROC, 0.77 vs 0.80; p=0.573). The activity index from combi-elastography adjusted by covariates was equivalent to the FibroScan-aspartate aminotransferase score in diagnosing high-risk MASH among participants with MASLD (AUROC, 0.72 vs 0.74; p=0.792). Conclusions The performance of combi-elastography is similar to that of VCTE when evaluating histology of MASLD.

Background/Aims: Combi-elastography is a B-mode ultrasound-based method in which two elastography modalities are utilized simultaneously to assess metabolic dysfunction-associated steatotic liver disease (MASLD). However, the performance of combi-elastography for diagnosing metabolic dysfunction-associated steatohepatitis (MASH) and determining fibrosis severity is unclear. This study compared the diagnostic performances of combi-elastography and vibrationcontrolled transient elastography (VCTE) for identifying hepatic steatosis, fibrosis, and high-risk MASH. Methods: Participants who underwent combi-elastography, VCTE, and liver biopsy were selected from a prospective cohort of patients with clinically suspected MASLD. Combi-elastographyrelated parameters were acquired, and their performances were evaluated using area under the receiver-operating characteristic curve (AUROC) analysis. Results: A total of 212 participants were included. The diagnostic performance for hepatic steatosis of the attenuation coefficient adjusted by covariates from combi-elastography was comparable to that of the controlled attenuation parameter measured by VCTE (AUROC, 0.85 vs 0.85; p=0.925). The performance of the combi-elastography-derived fibrosis index adjusted by covariates for diagnosing significant fibrosis was comparable to that of liver stiffness measured by VCTE (AUROC, 0.77 vs 0.80; p=0.573). The activity index from combi-elastography adjusted by covariates was equivalent to the FibroScan-aspartate aminotransferase score in diagnosing high-risk MASH among participants with MASLD (AUROC, 0.72 vs 0.74; p=0.792). Conclusions The performance of combi-elastography is similar to that of VCTE when evaluating histology of MASLD.

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.

Background/Aims: Combi-elastography is a B-mode ultrasound-based method in which two elastography modalities are utilized simultaneously to assess metabolic dysfunction-associated steatotic liver disease (MASLD). However, the performance of combi-elastography for diagnosing metabolic dysfunction-associated steatohepatitis (MASH) and determining fibrosis severity is unclear. This study compared the diagnostic performances of combi-elastography and vibrationcontrolled transient elastography (VCTE) for identifying hepatic steatosis, fibrosis, and high-risk MASH. Methods: Participants who underwent combi-elastography, VCTE, and liver biopsy were selected from a prospective cohort of patients with clinically suspected MASLD. Combi-elastographyrelated parameters were acquired, and their performances were evaluated using area under the receiver-operating characteristic curve (AUROC) analysis. Results: A total of 212 participants were included. The diagnostic performance for hepatic steatosis of the attenuation coefficient adjusted by covariates from combi-elastography was comparable to that of the controlled attenuation parameter measured by VCTE (AUROC, 0.85 vs 0.85; p=0.925). The performance of the combi-elastography-derived fibrosis index adjusted by covariates for diagnosing significant fibrosis was comparable to that of liver stiffness measured by VCTE (AUROC, 0.77 vs 0.80; p=0.573). The activity index from combi-elastography adjusted by covariates was equivalent to the FibroScan-aspartate aminotransferase score in diagnosing high-risk MASH among participants with MASLD (AUROC, 0.72 vs 0.74; p=0.792). Conclusions The performance of combi-elastography is similar to that of VCTE when evaluating histology of MASLD.

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: The role of allogeneic stem cell transplantation (alloSCT) in multiple myeloma (MM) treatment remains controversial. We conducted a retrospective, multicenter, nationwide study in Korea to evaluate the outcomes of alloSCT in Asian patients with MM. Materials and Methods: Overall, 109 patients with MM who underwent alloSCT between 2003 and 2020 were included in this study. Data were collected from the Korean Multiple Myeloma Working Party Registry. Results: The overall response rate and stringent complete response plus complete response (CR) rates were 67.0 and 46.8%, respectively, after alloSCT. At a median follow-up of 32.5 months, the 3-year probability of progression-free survival (PFS) and overall survival (OS) rates were 69.3% and 71.8%, respectively. The 3-year probabilities of OS rates in the upfront alloSCT, tandem auto-alloSCT, and later alloSCT groups were 75.0%, 88.9%, and 61.1%, respectively. Patients who achieved CR before or after alloSCT had significantly longer OS (89.8 vs. 18 months and 89.8 vs. 15.2 months, respectively). Even though patients who did not achieve CR prior to alloSCT, those who achieve CR after alloSCT had improved PFS and OS compared to those who had no achievement of CR both prior and after alloSCT. Patients who underwent alloSCT with 1-2 prior treatment lines had improved PFS (22.4 vs. 4.5 months) and OS (45.6 vs. 15.3 months) compared to those with three or more prior treatment lines. Conclusion AlloSCT may be a promising therapeutic option especially for younger, chemosensitive patients with earlier implementation from relapse.