Arterial enhancing local tumor progression detection on CT images using convolutional neural network after hepatocellular carcinoma ablation: a preliminary study

To evaluate the performance of a deep convolutional neural network (DCNN) in detecting local tumor progression (LTP) after tumor ablation for hepatocellular carcinoma (HCC) on follow-up arterial phase CT images. The DCNN model utilizes three-dimensional (3D) patches extracted from three-channel CT imaging to detect LTP. We built a pipeline to automatically produce a bounding box localization of pathological regions using a 3D-CNN trained for classification. The performance metrics of the 3D-CNN prediction were analyzed in terms of accuracy, sensitivity, specificity, positive predictive value (PPV), area under the receiver operating characteristic curve (AUC), and average precision. We included 34 patients with 49 LTP lesions and randomly selected 40 patients without LTP. A total of 74 patients were randomly divided into three sets: training (n = 48; LTP: no LTP = 21:27), validation (n = 10; 5:5), and test (n = 16; 8:8). When used with the test set (160 LTP positive patches, 640 LTP negative patches), our proposed 3D-CNN classifier demonstrated an accuracy of 97.59%, sensitivity of 96.88%, specificity of 97.65%, and PPV of 91.18%. The AUC and precision-recall curves showed high average precision values of 0.992 and 0.96, respectively. LTP detection on follow-up CT images after tumor ablation for HCC using a DCNN demonstrated high accuracy and incorporated multichannel registration.ope

The Pattern of Use, Effectiveness, and Safety of Gadoteric Acid (Clariscan) in Patients Undergoing Contrast-Enhanced Magnetic Resonance Imaging: A Prospective, Multicenter, Observational Study

Objective: Contrast-enhanced MR (CE-MR) imaging is often required to improve lesion detection and characterization and to increase diagnostic confidence. This study aimed to evaluate the safety and effectiveness, as well as the use pattern, of the macrocyclic gadolinium-based contrast agent Clariscan in real-world clinical practice in Korea. Materials and methods: This was a prospective, multicenter, observational study of patients undergoing CE-MR as part of routine clinical care at 6 university hospitals in Korea. Effectiveness was evaluated by determining diagnostic confidence and image quality; safety evaluation included the adverse event (AE) expression rate. Subgroup analyses were conducted by body regions of diagnosis (musculoskeletal, nervous system, others) and in pediatric patients (aged ≤7 years). Results: From October 2019 to September 2020, 1,376 subjects were included in the study. The mean volume of Clariscan used was 0.26 mL/kg (0.13 mmol/kg). In the overall study population and in each subgroup, diagnostic confidence increased after contrast enhancement with Clariscan. Overall, image quality was excellent in 72.5% of subjects and good-to-adequate in 27.2%. Clariscan was well tolerated (14 AEs occurred in 10 subjects); all AEs were of mild severity. Subgroup analyses showed that the mean dose of Clariscan used was ≥0.1 mmol/kg for nervous system-related diagnoses (e.g., brain) and ≤0.1 mmol/kg for musculoskeletal and pediatric-related diagnoses. All musculoskeletal and pediatric examinations were provided with a smaller package of 5 mL Clariscan. By body region of MR examination, the most common region was the nervous system in 69.0%, musculoskeletal system in 13.6%, and reproductive system in 4.9%. Conclusions: This study confirmed the use pattern of Clariscan and its excellent effectiveness and safety in the real-world clinical environment in Korea. The small-dose package indicated the possibility of increasing the convenience and efficiency of drug use.ope

Temporal Trends in Cervical Spine Curvature of South Korean Adults Assessed by Deep Learning System Segmentation, 2006-2018

Importance: The loss of the physiologic cervical lordotic curve is a common degenerative disorder known to be associated with abnormal spinal alignment. However, the changing trends among sex and age groups has not yet been well established. Objective: To analyze the temporal trends in cervical curvature across sex and age groups using an automated deep learning system (DLS). Design, setting, and participants: A retrospective cross-sectional study was conducted using lateral cervical radiographs of 13 691 individuals from January 1, 2006, to December 31, 2018. The degree of anterior vertical curvature was approximated by a DLS approach and convexity measurement method. This population-based study used the Yonsei University College of Medicine Severance Hospital, Seoul, South Korea, cohort database to identify 13 691 consecutive adults (≥18 years of age) who underwent standing lateral radiography in inpatient and outpatient settings. Main outcomes and measures: The prevalence of kyphotic and straight cervical curve as well as the trends of degree of cervical curvature in 2006 to 2018 among sex and age groups were determined. The DLS performance was validated with quantitative metrics and compared with interobserver and intraobserver variations. Results: Automatic cervical spine segmentation was identified from lateral radiographs of 13 691 individuals (mean [SD] age, 49.9 [15.3] years; 8051 women [58.8%]). From 2006 to 2018, the decrease in the lordotic curve was significant across both sexes and age groups younger than 70 years, with the decrease more pronounced in women and successively younger generations (female, -0.05; 95% CI, -0.06 to -0.04; 18-29 years of age, -0.06; 95% CI, -0.08 to -0.04; 30-39 years of age, -0.06; 95% CI, -0.08 to -0.04; and 40-49 years of age, -0.05; 95% CI, -0.06 to -0.03; all P < .001). The prevalence of straight and kyphotic curvature had a significant increasing trend for both sexes and young generations, in which individuals 18 to 29 years of age generally had the highest prevalence rates during the study cycle (in 2018, kyphosis, 16.7%; 95% CI, 10.8%-22.5%; straight, 45.5%; 95% CI, 37.7%-53.3%). Similar trends were observed with longitudinal analysis of repeated measures of individuals, with more pronounced decreases in lordotic curvature observed among women and young adults. Conclusions and relevance: This study suggests a significant, increasing loss of normal cervical lordotic curvature for both sexes and young adults that is greater in progressively younger cohorts and women. Further research is necessary to evaluate associations between neck pain and loss of cervical curvature and address the need for active promotion and practical interventions aimed at neck posture correction.ope

우리나라의 에너지 부문 민간 R&D 스톡 추계

학위논문 (석사)-- 서울대학교 대학원 사회과학대학 경제학부, 2017. 8. 김소영.본 논문은 2004년부터 2014년 기간의 우리나라 에너지 부문의 민간 R&D 투자를 에너지 자원 8대부문으로 나누어 추계하고, 이를 바탕으로 2009년부터 2020년 기간의 R&D 스톡을 추계한 결과를 수록하였다. 우리나라의 에너지 부문 민간 R&D 명목 투자는 2014년 기준 약 1.2조원으로 추계되었고, 명목 스톡은 2014년 기준 약 3.8조원, 2015년 기준 약 4.2조원, 2016년 기준 약 4.8조원으로 추계되었다. 또한 2009년~2020년 기간의 실질 스톡 연평균 성장률은 약 8% 정도로 2020년 기준 실질 스톡은 약 6.1조원 추계되었다. 우리나라 민간의 전산업 R&D 투자 집약도가 2014년 기준 2.54%인 것을 감안할 때, 에너지 부문의 R&D 투자 집약도(매출 대비 R&D 투자)는 2004년~2014년 기간 동안 1.1%~1.3%에서 횡보하는 수준으로 에너지 산업의 R&D 투자가 매출에서 차지하는 비중이 타 산업에 비해 낮은 수준이라고 평가할 수 있다. 효율적인 R&D 투자를 위해서는 과거부터 현재까지의 정확한 투자(flow) 현황 통계와 투자가 누적되어 현재까지 어느 정도 수준(stock)에 있는지에 대한 적절한 분석이 선행되어야 하므로 본 논문의 연구 결과가 정부 및 민간에서 향후 에너지부문 R&D 투자 계획을 세우는 데에 기여할 수 있을 것이다.제 1 장 서 론 1 제 1 절 연구의 배경 1 제 2 절 연구의 내용 3 제 2 장 본 론 4 제 1 절 에너지 부문 민간 R&D 투자 추계 4 제 2 절 에너지 부문 민간 R&D 스톡 추계 18 제 3 절 R&D 스톡조정모형 28 제 3 장 결 론 32 참고문헌 33 Abstract 35Maste

Patient-Specific Phantomless Estimation of Bone Mineral Density and Its Effects on Finite Element Analysis Results: A Feasibility Study

Objectives: This study proposes a regression model for the phantomless Hounsfield units (HU) to bone mineral density (BMD) conversion including patient physical factors and analyzes the accuracy of the estimated BMD values. Methods: The HU values, BMDs, circumferences of the body, and cross-sectional areas of bone were measured from 39 quantitative computed tomography images of L2 vertebrae and hips. Then, the phantomless HU-to-BMD conversion was derived using a multiple linear regression model. For the statistical analysis, the correlation between the estimated BMD values and the reference BMD values was evaluated using Pearson's correlation test. Voxelwise BMD and finite element analysis (FEA) results were analyzed in terms of root-mean-square error (RMSE) and strain energy density, respectively. Results: The HU values and circumferences were statistically significant (p < 0.05) for the lumbar spine, whereas only the HU values were statistically significant (p < 0.05) for the proximal femur. The BMD values estimated using the proposed HU-to-BMD conversion were significantly correlated with those measured using the reference phantom: Pearson's correlation coefficients of 0.998 and 0.984 for the lumbar spine and proximal femur, respectively. The RMSEs of the estimated BMD values for the lumbar spine and hip were 4.26 ± 0.60 (mg/cc) and 8.35 ± 0.57 (mg/cc), respectively. The errors of total strain energy were 1.06% and 0.91%, respectively. Conclusions: The proposed phantomless HU-to-BMD conversion demonstrates the potential of precisely estimating BMD values from CT images without the reference phantom and being utilized as a viable tool for FEA-based quantitative assessment using routine CT images.ope

Deep learning based sarcopenia prediction from shear-wave ultrasonographic elastography and gray scale ultrasonography of rectus femoris muscle

We aim to evaluate the performance of a deep convolutional neural network (DCNN) in predicting the presence or absence of sarcopenia using shear-wave elastography (SWE) and gray-scale ultrasonography (GSU) of rectus femoris muscle as an imaging biomarker. This retrospective study included 160 pair sets of GSU and SWE images (n = 160) from December 2018 and July 2019. Two radiologists scored the echogenicity of muscle on GSU (4-point score). Among them, 141 patients underwent CT and their L3 skeletal muscle index (SMI) were measured to categorize the presence or absence of sarcopenia. For DCNN, we used three CNN architectures (VGG19, ResNet-50, DenseNet 121). The accuracies of DCNNs for sarcopenia classification were 70.0-80.0% (based on SWE) and 65.0-75.0% (based on GSU). The DCNN application to SWE images highlights the utility of deep-learning base SWE for sarcopenia prediction. DCNN application to SWE images might be a potentially useful biomarker to predict sarcopenic status.ope

Learning Radiologist’s Step-by-Step Skill for Cervical Spinal Injury Examination: Line Drawing, Prevertebral Soft Tissue Thickness Measurement, and Swelling Detection

Radiologists examine lateral view radiographs of the cervical spine to determine the presence of cervical spinal injury. In this paper, we demonstrate that an artificial intelligence neural network can learn the steps employed by a radiologist when examining these radiographs for possible injury. We deconstructed the decision-making strategy into three steps: line drawing, prevertebral soft tissue thickness (PSTT) measurement, and swelling detection. After training neural networks to be guided by the radiologist's intermediate labels, the networks successfully performed comparable line drawings to those of the radiologists, and subsequent PSTT measurement and swelling detection were successful. Quantitative comparison of PSTT measurements between our proposed method and radiologists showed a high correlation (r = 0.8663, p <; 0.05, and intraclass correlation coefficient = 0.9283 at the C2 level; r = 0.7720, p <; 0.05, and intraclass correlation coefficient = 0.8667 at the C6 level). Using the radiologist's diagnosis as the reference point, the sensitivity, specificity, and accuracy of swelling detection by our proposed method were 100%, 98.37%, and 98.48, respectively. We conclude that our neural networks successfully learned the sequence of skills used by radiologists when interpreting radiographs for injury of the cervical spine.ope

The effects of posterior cruciate ligament deficiency on posterolateral corner structures under gait- and squat-loading conditions: A computational knee model

OBJECTIVES: The aim of the current study was to analyse the effects of posterior cruciate ligament (PCL) deficiency on forces of the posterolateral corner structure and on tibiofemoral (TF) and patellofemoral (PF) contact force under dynamic-loading conditions. METHODS: A subject-specific knee model was validated using a passive flexion experiment, electromyography data, muscle activation, and previous experimental studies. The simulation was performed on the musculoskeletal models with and without PCL deficiency using a novel force-dependent kinematics method under gait- and squat-loading conditions, followed by probabilistic analysis for material uncertain to be considered. RESULTS: Comparison of predicted passive flexion, posterior drawer kinematics and muscle activation with experimental measurements showed good agreement. Forces of the posterolateral corner structure, and TF and PF contact forces increased with PCL deficiency under gait- and squat-loading conditions. The rate of increase in PF contact force was the greatest during the squat-loading condition. The TF contact forces increased on both medial and lateral compartments during gait-loading conditions. However, during the squat-loading condition, the medial TF contact force tended to increase, while the lateral TF contact forces decreased. The posterolateral corner structure, which showed the greatest increase in force with deficiency of PCL under both gait- and squat-loading conditions, was the popliteus tendon (PT). CONCLUSION: PCL deficiency is a factor affecting the variability of force on the PT in dynamic-loading conditions, and it could lead to degeneration of the PF joint.Cite this article: K-T. Kang, Y-G. Koh, M. Jung, J-H. Nam, J. Son, Y.H. Lee, S-J. Kim, S-H. Kim. The effects of posterior cruciate ligament deficiency on posterolateral corner structures under gait- and squat-loading conditions: A computational knee model. Bone Joint Res 2017;6:31-42. DOI: 10.1302/2046-3758.61.BJR-2016-0184.R1.ope

In Vivo Evaluation of the Subject-Specific Finite Element Model for Knee Joint Cartilage Contact Area

In this paper, we present a new validation method for subject-specific finite element (FE) modeling of the knee joint based on in vivo computed tomography (CT) and magnetic resonance imaging (MRI) data. Previously, several FE models have been developed for estimating the mechanical response of joint structures, where direct or indirect in vivo measurement is difficult or impossible. More recently, studies using MRI have provided clear visualization of the motion and deformation of the articular cartilage within the tibiofemoral (TF) joint space. Two methods have been introduced to validate in vivo subject-specific models: alignment of supine MRI with X-ray images and weight-bearing MRI. The size of the contact area between the femur and tibia was determined by computing the area of femoral cartilage that intersected the tibial cartilage. The result showed good agreement between non-weight bearing image aligned with X-ray and weight-bearing MRI images. This study may help to better define the relative importance of modeling validations for the development of subject-specific models.ope

An anatomical and radiological study of the tectorial membrane and its clinical implications

The radiological image of an intact tectorial membrane (TM) became an important favorable prognostic factor for craniovertebral instability. This study visualized the fascial layers of the TM and adjacent connective tissues with clinical significance by micro-CT and histological analysis. The TM firmly attached to the bony surface of the clivus, traversed the atlantoaxial joint posteriorly, and was inserted to the body of the axis showing wide distribution on the craniovertebral junction. The supradental space between the clivus, dens of the axis, anterior atlantooccipital membrane, and the TM contained profound venous networks within the adipose tissues. At the body of the axis, the compact TM layer is gradually divided into multiple layers and the deeper TM layers reached the axis while the superficial layer continued to the posterior longitudinal ligament of the lower vertebrae. The consistent presence of the fat pad and venous plexus in the supradental space and firm stabilization of the TM on the craniovertebral junction was demonstrated by high-resolution radiologic images and histological analysis. The evaluation of the TM integrity is a promising diagnostic factor for traumatic craniovertebral dislocation.ope