Analysis of sagittal profile of spine using 3D ultrasound imaging: a phantom study and preliminary subject test

Three-dimensional ultrasonography could be a potential non-ionizing tool to evaluate vertebral rotation of subjects with adolescent idiopathic scoliosis

Background

Three-dimensional (3D) ultrasonography is nonionizing and has been demonstrated to be a reliable tool for scoliosis assessment, including coronal and sagittal curvatures. It shows a great potential for axial vertebral rotation (AVR) evaluation, yet its validity and reliability need to be further demonstrated.

Materials and Methods

Twenty patients with adolescent idiopathic scoliosis (AIS) (coronal Cobb: 26.6 ± 9.1°) received 3D ultrasound scan for twice, 10 were scanned by the same operator, and the other 10 by different operators. EOS Bi-planar x-rays and 3D scan were conducted on another 29 patients on the same day. Two experienced 3D ultrasonographic researchers, with different experiences on AVR measurement, evaluated the 3D ultrasonographic AVR of the 29 patients (55 curves; coronal Cobb angle: 26.9 ± 11.3°). The gold standard AVR was determined from the 3D reconstruction of coronal and sagittal EOS radiographs. Intra-class correlation coefficients (ICCs), mean absolute difference (MAD), standard error measurements (SEM), and Bland-Altman's bias were reported to evaluate the intra-operator and inter-operator/rater reliabilities of 3D ultrasonography. The reliability of 3D ultrasonographic AVR measurements was further validated using inter-method with that of EOS.

Results

ICCs for intra-operator and inter-operator/rater reliability assessment were all greater than 0.95. MAD, SEM, and bias for the 3D ultrasonographic AVRs were no more than 2.2°, 2.0°, and 0.5°, respectively. AVRs between both modalities were strongly correlated (R 2 = 0.901) and not significantly different (p = 0.205). Bland-Altman plot also shows that the bias was less than 1°, with no proportional bias between the difference and mean of expected and radiographic Cobb angles.

Conclusion

This study demonstrates that 3D ultrasonography is valid and reliable to evaluate AVR in AIS patients. 3D ultrasonography can be a potential tool for screening and following up subjects with AIS and evaluating the effectiveness of nonsurgical treatments.

Sagittal Spinal Alignment in People with Chronic Spinal Cord Injury and Normal Individual: A Comparison Study Using 3D Ultrasound Imaging

The aim of this study was to compare the sagittal spinal alignment of people with chronic spinal cord injury (SCI) with normal individuals and to determine whether transcutaneous electrical spinal cord stimulation (TSCS) could cause a change in the thoracic kyphosis (TK) and lumbar lordosis (LL) to re-establish normal sagittal spinal alignment. A case series study was conducted, wherein twelve individuals with SCI and ten neurologically intact subjects were scanned using 3D ultrasonography. In addition, three people with SCI having complete tetraplegia participated further to receive a 12-week treatment (TSCS with task-specific rehabilitation) after evaluation of sagittal spinal profile. Pre- and post-assessments were conducted to evaluate the differences in sagittal spinal alignment. The results showed that the TK and LL values for a person with SCI in a dependent seated posture were greater than those of normal subjects for: standing (by TK: 6.8° ± 1.6°; LL: 21.2° ± 1.9°), sitting straight (by TK: 10.0° ± 4.0°; LL: 1.7° ± 2.6°), and relaxed sitting (by TK: 3.9° ± 0.3°; LL: 7.7° ± 1.4°), respectively, indicating an increased risk for spinal deformity. In addition, TK decreased by 10.3° ± 2.3° after the TSCS treatment, showing a reversible change. These results suggest that the TSCS treatment could be used to restore normal sagittal spinal alignment for individuals with chronic SCI.

Endocrine Tumor Classification via Machine-Learning-Based Elastography: A Systematic Scoping Review

Elastography complements traditional medical imaging modalities by mapping tissue stiffness to identify tumors in the endocrine system, and machine learning models can further improve diagnostic accuracy and reliability. Our objective in this review was to summarize the applications and performance of machine-learning-based elastography on the classification of endocrine tumors. Two authors independently searched electronic databases, including PubMed, Scopus, Web of Science, IEEEXpress, CINAHL, and EMBASE. Eleven (n = 11) articles were eligible for the review, of which eight (n = 8) focused on thyroid tumors and three (n = 3) considered pancreatic tumors. In all thyroid studies, the researchers used shear-wave ultrasound elastography, whereas the pancreas researchers applied strain elastography with endoscopy. Traditional machine learning approaches or the deep feature extractors were used to extract the predetermined features, followed by classifiers. The applied deep learning approaches included the convolutional neural network (CNN) and multilayer perceptron (MLP). Some researchers considered the mixed or sequential training of B-mode and elastographic ultrasound data or fusing data from different image segmentation techniques in machine learning models. All reviewed methods achieved an accuracy of ≥80%, but only three were ≥90% accurate. The most accurate thyroid classification (94.70%) was achieved by applying sequential training CNN; the most accurate pancreas classification (98.26%) was achieved using a CNN-long short-term memory (LSTM) model integrating elastography with B-mode and Doppler images.

Physical Fitness of Chinese Primary School Students across the Coronavirus (COVID-19) Outbreak: A Retrospective Repeated Cross-Sectional Study

Social distancing measures against COVID-19 imposed restrictions on students that may have affected their physical health and fitness. The objective of this study was to investigate the change in physical fitness of primary school students across the coronavirus outbreaks from 2019 to 2021. This was a retrospective repeated cross-sectional study. We obtained the annual physical and fitness assessment data measured every November for all students at the same primary school in Guangzhou, China. There was a total of 6371 observations in the dataset for three years. The physical fitness of the students was evaluated with an overall physical fitness score, body mass index (BMI), lung vital capacity, physical flexibility (via a sit-and-reach test) and sports task performances (sprint, shuttle run, rope-jumping, and sit-up). Generalised estimating equations were used to determine any significant changes from 2019 to 2021, adjusted for confounders. After the COVID-19 outbreak in 2021, there was a significant elevation in BMI of 0.64 kg/m2 in 2020 and 0.39 kg/m2 in 2021 (p < 0.001). The overall physical fitness score was significantly increased by 2.1 and 4.1 points, respectively, in 2020 and 2021 (p < 0.001). Lung vital capacity and rope-jumping performance were significantly improved in both 2020 and 2021 compared with 2019, and sit-up performance was marginally significantly improved in 2020 and significantly improved in 2021. However, students demonstrated poorer flexibility and sprint and shuttle run performance in 2021 compared with 2019. A health promotion programme during and after COVID-19, including online physical education classes, television broadcasts, and a rope-jumping campaign, could account for these positive outcomes, along with the ease of administering rope-jumping and sit-ups at home.