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Ultrasound probe calibration is crucial for precise spatial mapping in ultrasound-guided surgical navigation and free-hand 3D ultrasound imaging as it establishes the rigid-body transformation between the ultrasound image plane and an external tracking sensor. However, the existing methods often rely on manual feature point selection and exhibit limited robustness to outliers, resulting in reduced accuracy, reproducibility, and efficiency. To address these limitations, we propose a fully automated calibration framework that leverages the geometric priors of an N-wire phantom to achieve reliable recognition. The method incorporates a robust feature point extraction algorithm and integrates a hybrid outlier rejection strategy based on the Random Sample Consensus (RANSAC) algorithm. The experimental evaluations demonstrate sub-millimeter accuracy (<0.6 mm) across varying imaging depths, with the calibration process completed in under two minutes and exhibiting high repeatability. These results suggest that the proposed framework provides a robust, accurate, and time-efficient solution for ultrasound probe calibration, with strong potential for clinical integration.

Spinal flexibility is an essential parameter for clinical decision making on the patients with adolescent idiopathic scoliosis (AIS). Various methods are proposed to assess spinal flexibility, but which assessment method is more effective to predict the effect of orthotic treatment is unclear. To investigate an effective assessment method of spinal flexibility to predict the initial in-orthosis correction, among the supine, prone, sitting with lateral bending and prone with lateral bending positions. Thirty-five patients with AIS (mean Cobb angle: 28° ± 7°; mean age: 12 ± 2 years; Risser sign: 0-2) were recruited. Before orthosis fitting, spinal flexibility was assessed by an ultrasound system in 4 positions (apart from standing) including supine, prone, sitting with lateral bending and prone with lateral bending. After orthosis fitting, the initial in-orthosis correction was routinely assessed by whole spine standing radiograph. Comparisons and correlation analyses were performed between the spinal flexibility in the 4 positions and the initial in-orthosis correction. The mean in-orthosis correction was 41% while the mean curve correction (spinal flexibility) in the 4 studied positions were 40% (supine), 42% (prone), 127% (prone with lateral bending) and 143% (sitting with lateral bending). The correlation coefficients between initial in-orthosis correction and curve correction (spinal flexibility) in the 4 studied positions were r = 0.66 (supine), r = 0.75 (prone), r = 0.03 (prone with lateral bending) and r = 0.04 (sitting with lateral bending). The spinal flexibility in the prone position is the closest to and most correlated with the initial in-orthosis correction among the 4 studied positions. Thus, the prone position could be an effective method to predict the initial effect of orthotic treatment on the patients with AIS.

Background A global diaphragm thickness measurement technique was developed for the zone of apposition (ZOA) using an image edge identification approach. The method was assessed in terms of its repeatability and reliability when applied in patients with critical illness. Methods Diaphragm thickness measurements were conducted by experienced ultrasound examiners in 60 critically ill adult patients. The performance of continuous global diaphragm thickness measurements was compared to traditional localized diaphragm thickness measurements with regard to intra-observer and inter-observer consistency. Results End-expiratory diaphragm thickness was measured to assess consistency. For the traditional local diaphragm thickness measurements, the intraclass correlation coefficients (ICC) were 0.882 for intra-observer and 0.848 for inter-observer assessments ( p  < 0.001). The global diaphragm thickness measurements yielded ICC values of 0.968 and 0.955 for intra-observer and inter-observer assessments, respectively ( p  < 0.001). These findings indicated good reliability for the conventional method and excellent reliability for the global measurement method. The maximum observed variability was 16.5% with the traditional method and 3.9% with the continuous measurement approach. When using a 10% decrease in diaphragm thickness as the threshold for clinically relevant diaphragmatic atrophy, 16.7% of measurements obtained through the traditional method exceeded this error margin, whereas all measurements acquired through the continuous method remained within the acceptable range. Conclusions Compared to traditional localized diaphragm thickness ultrasonography, the continuous approach demonstrated superior repeatability and reliability. This newly developed methodology may enhance the precision of diaphragm thickness evaluations within the ZOA in patients with critical illness.

Background: Corneal fluorescein staining is a key biomarker in evaluating dry eye disease. However, subjective scales of corneal fluorescein staining are lacking in consistency and increase the difficulties of an accurate diagnosis for clinicians. This study aimed to propose an automatic machine learning-based method for corneal fluorescein staining evaluation by utilizing prior information about the spatial connection and distribution of the staining region. Methods: We proposed an end-to-end automatic machine learning-based classification model that consists of staining region identification, feature signature construction, and machine learning-based classification, which fully scrutinizes the multiscale topological features together with conventional texture and morphological features. The proposed model was evaluated using retrospective data from Beijing Tongren Hospital. Two masked ophthalmologists scored images independently using the Sjögren’s International Collaborative Clinical Alliance Ocular Staining Score scale. Results: A total of 382 images were enrolled in the study. A signature with six topological features, two textural features, and two morphological features was constructed after feature extraction and selection. Support vector machines showed the best classification performance (accuracy: 82.67%, area under the curve: 96.59%) with the designed signature. Meanwhile, topological features contributed more to the classification, compared with other features. According to the distribution and correlation with features and scores, topological features performed better than others. Conclusions: An automatic machine learning-based method was advanced for corneal fluorescein staining evaluation. The topological features in presenting the spatial connectivity and distribution of staining regions are essential for an efficient corneal fluorescein staining evaluation. This result implies the clinical application of topological features in dry-eye diagnosis and therapeutic effect evaluation.

Applying ultrasound for scoliosis assessment has been an attractive topic over the past decade. This study proposed a new fast 3-D ultrasound projection imaging method to evaluate the spine deformity. A narrow-band rendering method was used to generate the coronal images based on B-mode images and their corresponding positional data. The non-planar reslicing method, which followed the natural spine curve, was used to project the complete spine data into the coronal image. The repeatability of the new method was tested. A comparison experiment on the reconstructed images and the processing time between the conventional 3-D rendering method and the developed projection imaging method was also performed among 70 patients with scoliosis. The intra- and inter-operator tests results demonstrated very good repeatability (ICC ≥ 0.90). The mean processing times for the developed projection method and conventional rendering method were 15.07 ± 0.03 s and 130.31 ± 35.07 s, respectively. The angle measurement results showed a high correlation (y = 0.984x, r = 0.954) between the images obtained using the two methods. The above results indicated that the developed projection imaging method could greatly decrease the processing time while preserving the comparative image quality. It can be expected that this novel method may help to provide fast 3-D ultrasound diagnosis of scoliosis in clinics.

This study proposed a new automatic measurement method of spinal curvature on ultrasound coronal images in adolescent idiopathic scoliosis (AIS). After preprocessing of Gaussian enhancement, the symmetric information of the image was extracted using the phase congruency. Then bony features were segmented from the soft tissues and background using the greyscale polarity. The morphological methods of image erosion and top-bottom-hat transformation, and geometric moment were utilized to identify the spinous column profile from the transverse processes. Finally, the spine deformity curve was obtained using robust regression. In-vivo experiments based on AIS patients were performed to evaluate the performance of the developed method. The comparison results revealed there was a significant correlation (y=0.81x, r=0.86) and good agreement between the new automatic method and the manual measurement method. It can be expected that this novel method may help to provide effective and objective deformity assessment method during the ultrasound scanning for AIS patients.

The objective is to evaluate the feasibility of utilizing ultrasound images in identifying critical prognostic biomarkers for HER2-positive breast cancer (HER2 + BC). This study enrolled 512 female patients diagnosed with HER2-positive breast cancer through pathological validation at our institution from January 2016 to December 2021. Five distinct deep convolutional neural networks (DCNNs) and a deep ensemble (DE) approach were trained to classify axillary lymph node involvement (ALNM), lymphovascular invasion (LVI), and histological grade (HG). The efficacy of the models was evaluated based on accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), receiver operating characteristic (ROC) curves, areas under the ROC curve (AUCs), and heat maps. DeLong test was applied to compare differences in AUC among different models. The deep ensemble approach, as the most effective model, demonstrated AUCs and accuracy of 0.869 (95% CI: 0.802–0.936) and 69.7% in LVI, 0.973 (95% CI: 0.949–0.998) and 73.8% in HG, thus providing superior classification performance in the context of imbalanced data (p < 0.05 by the DeLong test). On ALNM, AUC and accuracy were 0.780 (95% CI: 0.688–0.873) and 77.5%, which were comparable to other single models. The pretreatment US-based DE model could hold promise as a clinical guidance for predicting pathological characteristics of patients with HER2-positive breast cancer, thereby providing benefit of facilitating timely adjustments in treatment strategies.

Skeletal muscles are essential to the gender-specific characteristics of human movements. Sonomyography, a new signal for quantifying muscle activation, is of great benefit to understand muscle function through monitoring the real-time muscle architectural changes. The purpose of this pilot study was to investigate gender differences in the architectural changes of gastronomies muscle and tendon by using sonomyography during performing two-legged calf raising exercises. A motion analysis system was developed to extract sonomyography from ultrasound images together with kinematic and kinetic measurements. Tiny fascicle length changes among seven male subjects were observed at the initial part of calf raising, whereas the fascicle of seven female subjects shortened immediately. This result suggested that men would generate higher mechanical power output of plantar flexors to regulate their heavier body mass. In addition, the larger regression coefficient between the fascicle length and muscle force for the male subjects implied that higher muscle stiffness for the men was required in demand of maintaining their heavier body economically. The findings from the current study suggested that the body mass might play a factor in the gender difference in structural changes of muscle and tendon during motion. The sonomyography may provide valuable information in the understanding of the gender difference in human movements.

Background Radiographic evaluation for patients with scoliosis using Cobb method is the current gold standard, but radiography has radiation hazards. Several groups have recently demonstrated the feasibility of using 3D ultrasound for the evaluation of scoliosis. Ultrasound imaging is radiation-free, comparatively more accessible, and inexpensive. However, a reliable and valid 3D ultrasound system ready for clinical scoliosis assessment has not yet been reported. Scolioscan is a newly developed system targeted for scoliosis assessment in clinics by using coronal images of spine generated by a 3D ultrasound volume projection imaging method. The aim of this study is to test the reliability of spine deformity measurement of Scolioscan and its validity compared to the gold standard Cobb angle measurements from radiography in adolescent idiopathic scoliosis (AIS) patients. Methods Prospective study divided into two stages: 1) Investigation of intra- and inter- reliability between two operators for acquiring images using Scolioscan and among three raters for measuring spinal curves from those images; 2) Correlation between the Cobb angle obtained from radiography by a medical doctor and the spine curve angle obtained using Scolioscan (Scolioscan angle). The raters for ultrasound images and the doctors for evaluating radiographic images were mutually blinded. The two stages of tests involved 20 (80 % females, total of 26 angles, age of 16.4 ± 2.7 years, and Cobb angle of 27.6 ± 11.8°) and 49 (69 % female, 73 angles, 15.8 ± 2.7 years and 24.8 ± 9.7°) AIS patients, respectively. Intra-class correlation coefficients (ICC) and Bland-Altman plots and root-mean-square differences (RMS) were employed to determine correlations, which interpreted based on defined criteria. Results We demonstrated a very good intra-rater and intra-operator reliability for Scolioscan angle measurement with ICC larger than 0.94 and 0.88, respectively. Very good inter-rater and inter-operator reliability was also demonstrated, with both ICC larger than 0.87. For the thoracic deformity measurement, the RMS were 2.5 and 3.3° in the intra- and inter-operator tests, and 1.5 and 3.6° in the intra- and inter-rater tests, respectively. The RMS differences were 3.1, 3.1, 1.6, 3.7° in the intra- and inter-operator and intra- and inter-rater tests, respectively, for the lumbar angle measurement. Moderate to strong correlations (R 2  > 0.72) were observed between the Scolioscan angles and Cobb angles for both the thoracic and lumbar regions. It was noted that the Scolioscan angle slightly underestimated the spinal deformity in comparison with Cobb angle, and an overall regression equation y = 1.1797x (R 2  = 0.76) could be used to translate the Scolioscan angle (x) to Cobb angle (y) for this group of patients. The RMS difference between Scolioscan angle and Cobb angle was 4.7 and 6.2°, with and without the correlation using the overall regression equation. Conclusions We showed that Scolioscan is reliable for measuring coronal deformity for patients with AIS and appears promising in screening large numbers of patients, for progress monitoring, and evaluation of treatment outcomes. Due to it being radiation-free and relatively low-cost, Scolioscan has potential to be widely implemented and may contribute to reducing radiation dose during serial monitoring.

One of the most frequent malignancies in the head and neck is nasopharyngeal carcinoma (NPC). MicroRNAs, a kind of tiny noncoding RNA molecule, have been used as negative regulators in different types of cancer therapy in recent decades by downregulating their targets. Recent research suggests that microRNAs play an important role in cancer’s epithelial-to-mesenchymal transition (EMT), supporting or inhibiting EMT development. The epithelial-to-mesenchymal transition (EMT) is linked to a variety of cancer-related activities, including growth, metastasis, and invasion. Previous research has linked EMT to cancer stem-like characteristics as well as treatment resistance. Moreover, since microRNAs (miRNAs) are important regulators of the EMT phenotype, certain miRNAs have an effect on cancer stemness and treatment resistance. As a result, both fundamental research and clinical therapy benefit from knowing the connection between EMT-associated miRNAs and cancer stemness/drug resistance. As a result, we looked at the different functions that EMT-associated miRNAs (miR-137) play in the stem-like characteristics of malignant cells in this article. Then we looked at how EMT-associated miRNAs interact with nasopharyngeal cancer’s drug-resistant complex signaling pathways. Using qRT-PCR, we evaluated the performance of several micro RNAs with the proposed miR-137 for inhibiting invasion, metastasis, and the EMT process. In conclusion, our findings showed that miR-137 acted as a tumor suppressor gene in controlling NPC EMT and metastasis and that it may be a new therapeutic strategy and prognosis marker for the disease.