Purpose: Selecting the better techniques to harbor optimal motion management, either a stereotactic linear accelerator delivery using TrueBeam (TBX) or magnetic resonance–guided gated delivery using MRIdian (MRG), is time-consuming and costly. To address this challenge, we aimed to develop a decision-supporting algorithm based on a combination of deep learning-generated dose distributions and clinical data. Materials and Methods: We retrospectively analyzed 65 patients with liver or pancreatic cancer who underwent both TBX and MRG simulations and planning process. We trained three-dimensional U-Net deep learning models to predict dose distributions and generated dose volume histograms (DVHs) for each system. We integrated predicted DVH metrics into a Bayesian network (BN) model incorporating clinical data. Results: The MRG prediction model outperformed the TBX model, demonstrating statistically significant superiorities in predicting normalized dose to the planning target volume (PTV) and liver. We developed a final BN prediction model integrating the predictive DVH metrics with patient factors like age, PTV size, and tumor location. This BN model an area under the receiver operating characteristic curve index of 83.56%. The decision tree derived from the BN model showed that the tumor location (abutting vs. apart of PTV to hollow viscus organs) was the most important factor to determine TBX or MRG. It provided a potential framework for selecting the optimal radiation therapy (RT) system based on individual patient characteristics. Conclusion We demonstrated a decision-supporting algorithm for selecting optimal RT plans in upper gastrointestinal cancers, incorporating both deep learning-based dose prediction and BN-based treatment selection. This approach might streamline the decision-making process, saving resources and improving treatment outcomes for patients undergoing RT.

Background: With growing elderly populations, management of patients with acute stroke is increasingly important. In South Korea, the Acute Stroke Quality Assessment Program (ASQAP) has contributed to improving the quality of stroke care and practice behavior in healthcare institutions. While the mortality of hemorrhagic stroke remains high, there are only a few assessment indices associated with hemorrhagic stroke. Considering the need to develop assessment indices to improve the actual quality of care in the field of acute stroke treatment, this study aims to investigate the current status of human resources and practices related to the treatment of patients with acute stroke through a nationwide survey. Methods: For the healthcare institutions included in the Ninth ASQAP of the Health Insurance Review and Assessment Service (HIRA), data from January 2022 to December 2022 were collected through a survey on the current status and practice of healthcare providers related to the treatment of patients with acute stroke. The questionnaire consisted of 19 items, including six items on healthcare providers involved in stroke care and 10 items on the care of patients with acute stroke. Results: In the treatment of patients with hemorrhagic stroke among patients with acute stroke, neurosurgeons were the most common providers. The contribution of neurosurgeons in the treatment of ischemic stroke has also been found to be equivalent to that of neurologists. However, a number of institutions were found to be devoid of healthcare providers who perform definitive treatments, such as intra-arterial thrombectomy for patients with ischemic stroke or cerebral aneurysm clipping for subarachnoid hemorrhage. The intensity of the workload of healthcare providers involved in the care of patients with acute stroke, especially those involved in definitive treatment, was also found to be quite high. Conclusion Currently, there are almost no assessment indices specific to hemorrhagic stroke in the ASQAP for acute stroke. Furthermore, it does not reflect the reality of the healthcare providers and practices that provide definitive treatment for acute stroke. The findings of this study suggest the need for the development of appropriate assessment indices that reflect the realities of acute stroke care.

Background: With growing elderly populations, management of patients with acute stroke is increasingly important. In South Korea, the Acute Stroke Quality Assessment Program (ASQAP) has contributed to improving the quality of stroke care and practice behavior in healthcare institutions. While the mortality of hemorrhagic stroke remains high, there are only a few assessment indices associated with hemorrhagic stroke. Considering the need to develop assessment indices to improve the actual quality of care in the field of acute stroke treatment, this study aims to investigate the current status of human resources and practices related to the treatment of patients with acute stroke through a nationwide survey. Methods: For the healthcare institutions included in the Ninth ASQAP of the Health Insurance Review and Assessment Service (HIRA), data from January 2022 to December 2022 were collected through a survey on the current status and practice of healthcare providers related to the treatment of patients with acute stroke. The questionnaire consisted of 19 items, including six items on healthcare providers involved in stroke care and 10 items on the care of patients with acute stroke. Results: In the treatment of patients with hemorrhagic stroke among patients with acute stroke, neurosurgeons were the most common providers. The contribution of neurosurgeons in the treatment of ischemic stroke has also been found to be equivalent to that of neurologists. However, a number of institutions were found to be devoid of healthcare providers who perform definitive treatments, such as intra-arterial thrombectomy for patients with ischemic stroke or cerebral aneurysm clipping for subarachnoid hemorrhage. The intensity of the workload of healthcare providers involved in the care of patients with acute stroke, especially those involved in definitive treatment, was also found to be quite high. Conclusion Currently, there are almost no assessment indices specific to hemorrhagic stroke in the ASQAP for acute stroke. Furthermore, it does not reflect the reality of the healthcare providers and practices that provide definitive treatment for acute stroke. The findings of this study suggest the need for the development of appropriate assessment indices that reflect the realities of acute stroke care.

Purpose: Selecting the better techniques to harbor optimal motion management, either a stereotactic linear accelerator delivery using TrueBeam (TBX) or magnetic resonance–guided gated delivery using MRIdian (MRG), is time-consuming and costly. To address this challenge, we aimed to develop a decision-supporting algorithm based on a combination of deep learning-generated dose distributions and clinical data. Materials and Methods: We retrospectively analyzed 65 patients with liver or pancreatic cancer who underwent both TBX and MRG simulations and planning process. We trained three-dimensional U-Net deep learning models to predict dose distributions and generated dose volume histograms (DVHs) for each system. We integrated predicted DVH metrics into a Bayesian network (BN) model incorporating clinical data. Results: The MRG prediction model outperformed the TBX model, demonstrating statistically significant superiorities in predicting normalized dose to the planning target volume (PTV) and liver. We developed a final BN prediction model integrating the predictive DVH metrics with patient factors like age, PTV size, and tumor location. This BN model an area under the receiver operating characteristic curve index of 83.56%. The decision tree derived from the BN model showed that the tumor location (abutting vs. apart of PTV to hollow viscus organs) was the most important factor to determine TBX or MRG. It provided a potential framework for selecting the optimal radiation therapy (RT) system based on individual patient characteristics. Conclusion We demonstrated a decision-supporting algorithm for selecting optimal RT plans in upper gastrointestinal cancers, incorporating both deep learning-based dose prediction and BN-based treatment selection. This approach might streamline the decision-making process, saving resources and improving treatment outcomes for patients undergoing RT.

Background: With growing elderly populations, management of patients with acute stroke is increasingly important. In South Korea, the Acute Stroke Quality Assessment Program (ASQAP) has contributed to improving the quality of stroke care and practice behavior in healthcare institutions. While the mortality of hemorrhagic stroke remains high, there are only a few assessment indices associated with hemorrhagic stroke. Considering the need to develop assessment indices to improve the actual quality of care in the field of acute stroke treatment, this study aims to investigate the current status of human resources and practices related to the treatment of patients with acute stroke through a nationwide survey. Methods: For the healthcare institutions included in the Ninth ASQAP of the Health Insurance Review and Assessment Service (HIRA), data from January 2022 to December 2022 were collected through a survey on the current status and practice of healthcare providers related to the treatment of patients with acute stroke. The questionnaire consisted of 19 items, including six items on healthcare providers involved in stroke care and 10 items on the care of patients with acute stroke. Results: In the treatment of patients with hemorrhagic stroke among patients with acute stroke, neurosurgeons were the most common providers. The contribution of neurosurgeons in the treatment of ischemic stroke has also been found to be equivalent to that of neurologists. However, a number of institutions were found to be devoid of healthcare providers who perform definitive treatments, such as intra-arterial thrombectomy for patients with ischemic stroke or cerebral aneurysm clipping for subarachnoid hemorrhage. The intensity of the workload of healthcare providers involved in the care of patients with acute stroke, especially those involved in definitive treatment, was also found to be quite high. Conclusion Currently, there are almost no assessment indices specific to hemorrhagic stroke in the ASQAP for acute stroke. Furthermore, it does not reflect the reality of the healthcare providers and practices that provide definitive treatment for acute stroke. The findings of this study suggest the need for the development of appropriate assessment indices that reflect the realities of acute stroke care.

Purpose: Selecting the better techniques to harbor optimal motion management, either a stereotactic linear accelerator delivery using TrueBeam (TBX) or magnetic resonance–guided gated delivery using MRIdian (MRG), is time-consuming and costly. To address this challenge, we aimed to develop a decision-supporting algorithm based on a combination of deep learning-generated dose distributions and clinical data. Materials and Methods: We retrospectively analyzed 65 patients with liver or pancreatic cancer who underwent both TBX and MRG simulations and planning process. We trained three-dimensional U-Net deep learning models to predict dose distributions and generated dose volume histograms (DVHs) for each system. We integrated predicted DVH metrics into a Bayesian network (BN) model incorporating clinical data. Results: The MRG prediction model outperformed the TBX model, demonstrating statistically significant superiorities in predicting normalized dose to the planning target volume (PTV) and liver. We developed a final BN prediction model integrating the predictive DVH metrics with patient factors like age, PTV size, and tumor location. This BN model an area under the receiver operating characteristic curve index of 83.56%. The decision tree derived from the BN model showed that the tumor location (abutting vs. apart of PTV to hollow viscus organs) was the most important factor to determine TBX or MRG. It provided a potential framework for selecting the optimal radiation therapy (RT) system based on individual patient characteristics. Conclusion We demonstrated a decision-supporting algorithm for selecting optimal RT plans in upper gastrointestinal cancers, incorporating both deep learning-based dose prediction and BN-based treatment selection. This approach might streamline the decision-making process, saving resources and improving treatment outcomes for patients undergoing RT.

Background: With growing elderly populations, management of patients with acute stroke is increasingly important. In South Korea, the Acute Stroke Quality Assessment Program (ASQAP) has contributed to improving the quality of stroke care and practice behavior in healthcare institutions. While the mortality of hemorrhagic stroke remains high, there are only a few assessment indices associated with hemorrhagic stroke. Considering the need to develop assessment indices to improve the actual quality of care in the field of acute stroke treatment, this study aims to investigate the current status of human resources and practices related to the treatment of patients with acute stroke through a nationwide survey. Methods: For the healthcare institutions included in the Ninth ASQAP of the Health Insurance Review and Assessment Service (HIRA), data from January 2022 to December 2022 were collected through a survey on the current status and practice of healthcare providers related to the treatment of patients with acute stroke. The questionnaire consisted of 19 items, including six items on healthcare providers involved in stroke care and 10 items on the care of patients with acute stroke. Results: In the treatment of patients with hemorrhagic stroke among patients with acute stroke, neurosurgeons were the most common providers. The contribution of neurosurgeons in the treatment of ischemic stroke has also been found to be equivalent to that of neurologists. However, a number of institutions were found to be devoid of healthcare providers who perform definitive treatments, such as intra-arterial thrombectomy for patients with ischemic stroke or cerebral aneurysm clipping for subarachnoid hemorrhage. The intensity of the workload of healthcare providers involved in the care of patients with acute stroke, especially those involved in definitive treatment, was also found to be quite high. Conclusion Currently, there are almost no assessment indices specific to hemorrhagic stroke in the ASQAP for acute stroke. Furthermore, it does not reflect the reality of the healthcare providers and practices that provide definitive treatment for acute stroke. The findings of this study suggest the need for the development of appropriate assessment indices that reflect the realities of acute stroke care.

Objective: Spinal stenosis is a prevalent condition; however, the optimal surgical treatment for central lumbar stenosis remains controversial. This study compared the clinical outcomes and radiological parameters of 3 surgical methods: unilateral laminectomy bilateral decompression with unilateral biportal endoscopy (ULBD-UBE), conventional subtotal laminectomy (STL), and minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF). Methods: This retrospective study included 86 patients, divided into ULBD-UBE (n=34), STL (n=24), and MIS-TLIF (n=28) groups. We evaluated demographics and perioperative factors and assessed clinical outcomes using the visual analogue scale (VAS), Oswestry Disability Index (ODI), and neurogenic intermittent claudication (NIC). Radiological parameters assessed included lumbar lordosis, L4S1 Cobb angle (L4S1), T12S1 Cobb angle (T12S1), increased cross-sectional dural area (CSA), dynamic angulation (DA), dynamic slip (DS), and development of postoperative instability. Results: The ULBD-UBE group showed a significantly shorter hospital stay duration and operation time and reduced blood loss than the other groups (p<0.001). ULBD-UBE group showed a trend towards greater VAS and ODI improvement at 1 month and postoperative NIC symptom relief. Radiologically, MIS-TLIF group exhibited lower postoperative DA and DS (p<0.001), indicating higher postoperative stability. Postoperative instability was lower in the ULBD-UBE group (2.9%) than in the STL group (16.7%) and similar to the MIS-TLIF group (0.0%) (p=0.028). The CSA was highest in the MIS-TLIF group (295.5%) compared to that in the other groups (ULBD-UBE, 216.3%; STL, 245.2%) (p<0.001). Conclusion Compared to other procedures, ULBD-UBE is a safe, effective, and viable surgical procedure for treating lumbar central stenosis.

Objective: We aimed to investigate the incidence of delayed-onset neurological deficits (DONDs), DOND-related reoperation rates following adult spinal deformity (ASD) surgery, and efficacy of transverse process hooks (TPHs) at the uppermost instrumented vertebra (UIV) compared to pedicle screws (PSs). Methods: We included 90 consecutive patients who underwent instrumented fusion from the sacrum to the distal thoracic spine for ASD, with a minimum follow-up of 24 months. Clinical and radiological outcomes were compared between 33 patients in the TPH group and 57 patients in the PS group, using the Scoliosis Research Society-22 Outcomes questionnaire (SRS-22), Medical Outcomes Study Questionnaire Short-Form 36 (SF-36), and various spinal sagittal parameters. Results: While absent in the TPH group, myelopathy occurred in 15.8% of the PS group, wherein 15 patients underwent reoperation. The change in the proximal junctional angle, from the pre- to postoperative assessment, was lower in the TPH group than in the PS group (0.2 vs. 6.6, p=0.002). Postoperative facet degeneration in the PS group progressed more significantly than in the TPH group (0.5 vs. 0.1, p=0.002). Surgical outcomes were comparable for both groups, except for the back visual analogue scale (3.5 vs. 4.1, p=0.010) and SRS-22 domains, including pain and satisfaction (3.3 vs. 2.9, p=0.033; 3.7 vs. 3.3, p=0.041). No intergroup difference was observed in SF-36. Conclusion Using TPHs at the UIV level can prevent DOND, and thereby prevent postoperative myelopathy that necessitates reoperation; thus, TPHs is preferable over PSs in ASD surgery.

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.