Aortic Annulus Detection Based on Deep Learning for Transcatheter Aortic Valve Replacement Using Cardiac Computed Tomography.

BACKGROUND: To propose a deep learning architecture for automatically detecting the complex structure of the aortic annulus plane using cardiac computed tomography (CT) for transcatheter aortic valve replacement (TAVR). METHODS: This study retrospectively reviewed consecutive patients who underwent TAVR between January 2017 and July 2020 at a tertiary medical center. Annulus Detection Permuted AdaIN network (ADPANet) based on a three-dimensional (3D) U-net architecture was developed to detect and localize the aortic annulus plane using cardiac CT. Patients (N = 72) who underwent TAVR between January 2017 and July 2020 at a tertiary medical center were enrolled. Ground truth using a limited dataset was delineated manually by three cardiac radiologists. Training, tuning, and testing sets (70:10:20) were used to build the deep learning model. The performance of ADPANet for detecting the aortic annulus plane was analyzed using the root mean square error (RMSE) and dice similarity coefficient (DSC). RESULTS: In this study, the total dataset consisted of 72 selected scans from patients who underwent TAVR. The RMSE and DSC values for the aortic annulus plane using ADPANet were 55.078 ± 35.794 and 0.496 ± 0.217, respectively. CONCLUSION: Our deep learning framework was feasible to detect the 3D complex structure of the aortic annulus plane using cardiac CT for TAVR. The performance of our algorithms was higher than other convolutional neural networks.

Identifying fragile calcifications of the aortic valve in transcatheter aortic valve replacement: iodine concentration of aortic valvular calcification by spectral CT.

OBJECTIVE: To demonstrate the relationship between spectral computed tomography (CT) measured iodine concentration and strength of aortic valvular calcification (AVC) in patients with aortic valve stenosis (AVS). METHODS: A retrospective study was performed on patients who underwent transcatheter aortic valve replacement (TAVR) for symptomatic AVS and underwent both pre and postprocedural electrocardiogram gated CT scans using a spectral CT system. Preprocedural CT was used to evaluate the volume and iodine concentration (IC) in the AVC. Postprocedural CT data were used to calculate the volume reduction percentage (VRP) of AVC. Multiple linear regression analysis was used to identify the independent variables related to the VRP in AVCs. RESULTS: A total of 94 AVCs were selected from 22 patients. The mean volume and IC of the AVCs before TAVR were 0.37 mL ± 0.15 mL and 7 mg/mL ± 10.5 mg/mL, respectively. After TAVR, a median VRP of all 94 AVCs was 18.5%. Multiple linear regression analysis showed that the IC was independently associated with the VRP (coefficient = 1.64, p < 0.001). When an optimal IC cutoff point was set at 4 mg/mL in the assessment of a fragile AVC which showed the VRP was > 18.5%, the sensitivity was 63%; specificity, 91%; positive predictive value, 88%; and negative predictive value, 71%. CONCLUSIONS: When using spectral CT to prepare the TAVR, measuring the IC of the AVC may be useful to assess the probability of AVC deformity after TAVR. KEY POINTS: • A dual-layer detector-based spectral CT enables quantifying iodine of contrast media in the aortic valve calcification (AVC) on contrast-enhanced CT images. • The AVC including iodine of contrast media on contrast-enhanced CT image may have loose compositions, associated with the deformity of AVC after TAVR. • Measuring the iodine concentration in AVC may have the potential to assess the probability of AVC deformity, which may be associated with the outcome and complications after TAVR.2.

Risk factors of postoperative complications following total knee arthroplasty in Korea: A nationwide retrospective cohort study.

BACKGROUND: The number of patients undergoing total knee arthroplasty (TKA) is gradually increasing and there is also increase in postoperative complications. The patient's demographic, socio-economic factors, hospital and clinical factors are all factors that can influence postoperative complications. The purpose of this study was to determine the risk factors associated with complications following TKA in a large national cohort. METHODS: Among patients diagnosed with primary knee arthrosis, a total of 560,954 patients older than 50 years who underwent TKA from January 1, 2005 to December 31, 2018 were included in the study. The risk of postoperative complications (surgical site infection, sepsis, cardiovascular complications, respiratory complications, pulmonary embolism, stroke, acute renal failure, periprosthetic joint infection, and periprosthetic fracture) were assessed with eight independent variables: gender, age, place of residence, household income, hospital bed size, procedure type (unilateral or bilateral, primary or revision TKA), length of stay (LOS), use of transfusion. Multivariable Cox Proportional Hazard model analysis was used. The significant predictors for complications (P < .05) were as follows. RESULTS: Surgical site infection: male, procedure type (bilateral, revision), LOS (≥35 days), transfusion. Sepsis: male, household income, procedure type (bilateral, revision), LOS (≥35 days), transfusion. Cardiovascular complications: male, age, household income, procedure type (bilateral, revision), LOS (≥35 days), transfusion. Respiratory complications: male, household income, procedure type (bilateral, revision), LOS (≥35 days), transfusion. Pulmonary embolism: male, household income, procedure type (bilateral, revision), LOS (≥35 days), transfusion. Stroke: male, age, procedure type (bilateral, revision), LOS (≥35 days), transfusion. Acute renal failure: male, household income, procedure type (bilateral, revision), LOS (≥35 days), transfusion. Periprosthetic joint infection: male, household income, procedure type (bilateral, revision), LOS (≥35 days), transfusion. Periprosthetic fracture: male, procedure type (bilateral, revision), LOS (≥35 days), transfusion. CONCLUSION: In summary, male, procedure type (bilateral, revision), LOS (≥35 days), and use of transfusion were shown to be risk factors of postoperative complications following TKA.

Analysis of the relationships among perceived service encounter quality, service value, satisfaction and behavioral intention for physical therapy patients.

[Purpose] The purpose of this study was to investigate the relationships among perceived service encounter quality, service value, patient satisfaction, and behavioral intention in physical therapy patients. [Subjects and Methods] This study surveyed 335 patients who received physical therapy treatment at five medical institutions in Jeonju-si, Republic of Korea. This study conducted path analysis on the collected data using Smart PLS 2.0 M3. [Results] The analysis of this study showed that service encounter quality had significantly positive relationship with service value, patient satisfaction, and behavioral intention. Service value had significantly positive relationship with patient satisfaction and behavioral intention. Patient satisfaction had significantly positive relationship with behavioral intention. [Conclusion] Improving the perceived quality of service encounters for physical therapy patients increases service value and patient satisfaction, and positively influences behavioral intention.

Effect of sleep posture on neck muscle activity.

[Purpose] This study investigated the effect of sleep posture on neck muscle activity. [Subjects and Methods] The study recruited 20 healthy subjects, who were positioned in three supine sleeping positions: both hands at sides, both hands on the chest, and dominant hand on the forehead. The activities of the scalene and upper trapezius muscles bilaterally were measured by surface electromyography. [Results] The upper trapezius and scalene muscle activity on the right side was significantly greater in the supine with dominant hand on the forehead position than in the other positions. [Conclusion] Sleep posture is important and prevent neck and shoulder musculoskeletal pain.

Relationship between Bone Mineral Density and Spinal Muscle Area in Magnetic Resonance Imaging.

BACKGROUND: Bone mineral density (BMD) is known to have a positive correlation with lean body mass. Several studies have also reported the positive correlation between muscle power and BMD. From this point of view, we hypothesized BMD of lumbar spine to have a positive correlation with muscle mass. METHODS: Seventy-nine female patients aged between 60 and 75 years old and who underwent magnetic resonance imaging (MRI) and BMD studies were included. Muscle mass in spine MRI was defined by the sum of the average muscle area of three axial images for each disc level. Lumbosacral muscle is the sum of paraspinal muscle and psoas muscle. RESULTS: In correlation analysis, paraspinal muscle mass showed positive correlation with BMD of lumbar spine. Lumbosacral muscle mass showed positive correlation with BMD of trochanteric area of the femur. However, BMD of other area showed no significant correlation with muscle mass. CONCLUSIONS: Therefore, postmenopausal women older than 60 years with a well developed spine muscle mass, have a high BMD.