UNASSIGNED: In this paper, we introduce a novel method for determining 3D deformations of the human tibialis anterior (TA) muscle during dynamic movements using 3D ultrasound.
UNASSIGNED: An existing automated 3D ultrasound system is used for data acquisition, which consists of three moveable axes, along which the probe can move. While the subjects perform continuous plantar- and dorsiflexion movements in two different controlled velocities, the ultrasound probe sweeps cyclically from the ankle to the knee along the anterior shin. The ankle joint angle can be determined using reflective motion capture markers. Since we considered the movement direction of the foot, i.e., active or passive TA, four conditions occur: slow active, slow passive, fast active, fast passive. By employing an algorithm which defines ankle joint angle intervals, i.e., intervals of range of motion (ROM), 3D images of the volumes during movement can be reconstructed.
UNASSIGNED: We found constant muscle volumes between different muscle lengths, i.e., ROM intervals. The results show an increase in mean cross-sectional area (CSA) for TA muscle shortening. Furthermore, a shift in maximum CSA towards the proximal side of the muscle could be observed for muscle shortening. We found significantly different maximum CSA values between the fast active and all other conditions, which might be caused by higher muscle activation due to the faster velocity.
UNASSIGNED: In summary, we present a method for determining muscle volume deformation during dynamic contraction using ultrasound, which will enable future empirical studies and 3D computational models of skeletal muscles.

BACKGROUND: Frontonasal dysplasia (FND) is a rare congenital anomaly resulting from the underdevelopment of the frontonasal process, and it can be syndromic or nonsyndromic. The typical features of FND include a deformed nose and ocular hypertelorism, which are sometimes associated with cleft lip and/or palate. Only approximately 10 cases of prenatally diagnosed nonsyndromic FND have been reported in the past 30 years.
METHODS: A 33-year-old woman (G2P1) was referred to our center at 20 gestational weeks for bilateral hydrocephaly. We detected typical features of FND, including severe hypertelorism, median nasal bifidity, a minor cleft lip, and multiple limb anomalies using three-dimensional (3D) ultrasound. A hypoplastic corpus callosum, unilateral microtia, and a ventricular septal defect were also detected. Genetic testing, including karyotype analysis, copy number variation (CNV) analysis, trio-whole exome sequencing (trio-WES), and trio-whole-gene sequencing (trio-WGS), was performed; however, we did not find any de novo gene variants in the fetus as compared to the parents. Postmortem examination confirmed the prenatal diagnosis of FND.
CONCLUSIONS: The present case expands the wide phenotypic spectrum of prenatal FND patients. 3D ultrasound is a useful tool for detecting facial and limb deformities.

BACKGROUND: Three-dimensional (3D) ultrasound (US) imaging has shown promise in non-invasive monitoring of changes in the lateral brain ventricles of neonates suffering from intraventricular hemorrhaging. Due to the poorly defined anatomical boundaries and low signal-to-noise ratio, fully supervised methods for segmentation of the lateral ventricles in 3D US images require a large dataset of annotated images by trained physicians, which is tedious, time-consuming, and expensive. Training fully supervised segmentation methods on a small dataset may lead to overfitting and hence reduce its generalizability. Semi-supervised learning (SSL) methods for 3D US segmentation may be able to address these challenges but most existing SSL methods have been developed for magnetic resonance or computed tomography (CT) images.
OBJECTIVE: To develop a fast, lightweight, and accurate SSL method, specifically for 3D US images, that will use unlabeled data towards improving segmentation performance.
METHODS: We propose an SSL framework that leverages the shape-encoding ability of an autoencoder network to enforce complex shape and size constraints on a 3D U-Net segmentation model. The autoencoder created pseudo-labels, based on the 3D U-Net predicted segmentations, that enforces shape constraints. An adversarial discriminator network then determined whether images came from the labeled or unlabeled data distributions. We used 887 3D US images, of which 87 had manually annotated labels and 800 images were unlabeled. Training/validation/testing sets of 25/12/50, 25/12/25 and 50/12/25 images were used for model experimentation. The Dice similarity coefficient (DSC), mean absolute surface distance (MAD), and absolute volumetric difference (VD) were used as metrics for comparing to other benchmarks. The baseline benchmark was the fully supervised vanilla 3D U-Net while dual task consistency, shape-aware semi-supervised network, correlation-aware mutual learning, and 3D U-Net Ensemble models were used as state-of-the-art benchmarks with DSC, MAD, and VD as comparison metrics. The Wilcoxon signed-rank test was used to test statistical significance between algorithms for DSC and VD with the threshold being p < 0.05 and corrected to p < 0.01 using the Bonferroni correction. The random-access memory (RAM) trace and number of trainable parameters were used to compare the computing efficiency between models.
RESULTS: Relative to the baseline 3D U-Net model, our shape-encoding SSL method reported a mean DSC improvement of 6.5%, 7.7%, and 4.1% with a 95% confidence interval of 4.2%, 5.7%, and 2.1% using image data splits of 25/12/50, 25/12/25, and 50/12/25, respectively. Our method only used a 1GB increase in RAM compared to the baseline 3D U-Net and required less than half the RAM and trainable parameters compared to the 3D U-Net ensemble method.
CONCLUSIONS: Based on our extensive literature survey, this is one of the first reported works to propose an SSL method designed for segmenting organs in 3D US images and specifically one that incorporates unlabeled data for segmenting neonatal cerebral lateral ventricles. When compared to the state-of-the-art SSL and fully supervised learning methods, our method yielded the highest DSC and lowest VD while being computationally efficient.

BACKGROUND: Histopathological analysis often shows close resection margins after surgical removal of tongue squamous cell carcinoma (TSCC). This study aimed to investigate the agreement between intraoperative 3D ultrasound (US) margin assessment and postoperative histopathology of resected TSCC.
METHODS: In this study, ten patients were prospectively included. Three fiducial cannulas were inserted into the specimen. To acquire a motorized 3D US volume, the resected specimen was submerged in saline, after which images were acquired while the probe moved over the specimen. The US volumes were annotated twice: (1) automatically and (2) manually, with the automatic segmentation as initialization. After standardized histopathological processing, all hematoxylin-eosin whole slide images (WSI) were included for analysis. Corresponding US images were found based on the known WSI spacing and fiducials. Blinded observers measured the tumor thickness and the margin in the caudal, deep, and cranial directions on every slide. The anterior and posterior margin was measured per specimen.
RESULTS: The mean difference in all measurements between manually segmented US and histopathology was 2.34 (SD: ±3.34) mm, and Spearman\'s rank correlation coefficient was 0.733 (p < 0.001). The smallest mean difference was in the tumor thickness with 0.80 (SD: ±2.44) mm and a correlation of 0.836 (p < 0.001). Limitations were observed in the caudal region, where no correlation was found.
CONCLUSIONS: This study shows that 3D US and histopathology have a moderate to strong statistically significant correlation (r = 0.733; p < 0.001) and a mean difference between the modalities of 2.3 mm (95%CI: -4.2; 8.9). Future research should focus on patient outcomes regarding resection margins.

OBJECTIVE: Transoral robotic surgery (TORS) is a challenging procedure due to its small workspace and complex anatomy. Ultrasound (US) image guidance has the potential to improve surgical outcomes, but an appropriate method for US probe manipulation has not been defined. This study evaluates using an additional robotic (4th) arm on the da Vinci Surgical System to perform extracorporeal US scanning for image guidance in TORS.
METHODS: A stereoscopic imaging system and da Vinci-compatible US probe attachment were developed to enable control of the extracorporeal US probe from the surgeon console. The prototype was compared to freehand US by nine operators in three tasks on a healthy volunteer: (1) identification of the common carotid artery, (2) carotid artery scanning, and (3) identification of the submandibular gland. Operator workload and user experience were evaluated using a questionnaire.
RESULTS: The robotic US tasks took longer than freehand US tasks (2.09x longer; p = 0.001 ) and had higher operator workload (2.12x higher; p = 0.004 ). However, operator-rated performance was closer (avg robotic/avg freehand = 0.66; p = 0.017 ), and scanning performance measured by MRI-US average Hausdorff distance provided no statistically significant difference.
CONCLUSIONS: Extracorporeal US scanning for intraoperative US image guidance is a convenient approach for providing the surgeon direct control over the US image plane during TORS, with little modification to the existing operating room workflow. Although more time-consuming and higher operator workload, several methods have been identified to address these limitations.

暂无摘要。

OBJECTIVE: To assess embryonic genital tubercle using transvaginal three-dimensional (3D) ultrasound at 8-10+6 weeks of gestation.
METHODS: One-hundred and two transvaginal 3D ultrasound scans were performed for first-trimester dating at 8-10+6 weeks of gestation. The genital tubercle angle (GTA) and genital tubercle length (GTL) were measured with a mid-sagittal view of the embryo using the 3D ultrasound multiplanar mode. Intra- and inter-observer agreements regarding GTA and GTL were also assessed with Bland-Altman plots and intra- and inter-correlation coefficients.
RESULTS: There were no significant differences in GTA between male and female embryos at 8, 9, 10 weeks, or 8-10+6 weeks of gestation, respectively. There were also no significant differences in GTL between male and female embryos at 8, 9, 10 weeks, or 8-10+6 weeks of gestation, respectively. However, GTL increased linearly with advancing gestation (r=0.8276, p<0.00001). Mean GTL (SD) values at 8, 9, and 10 weeks were 0.833 mm (0.274), 1.623 mm (0.262), and 2.152 mm (0.420), respectively (p<0.001). Intra- and inter-reproducibilities of GTA and GTL were excellent. The intra- and inter-correlation coefficients of GTA and GTL were 0.964 and 0.995, and 0.996 and 0.9933, respectively.
CONCLUSIONS: The genital tubercle could be identified using transvaginal 3D ultrasound at 8-10+6 weeks of gestation. However, sex differentiation could not be performed at this age. The genital tubercle linearly developed with advancing gestation during the mid-first trimester of pregnancy.

BACKGROUND: Stroke is the second leading cause of death across the globe. Early screening and risk detection could provide early intervention and possibly prevent its incidence. Imaging modalities, including 1D-Transcranial Doppler Ultrasound (1D-TCD) or Transcranial Color-code sonography (TCCS), could only provide low spatial resolution or 2D image information, respectively. Notably, 3D imaging modalities including CT have high radiation exposure, whereas MRI is expensive and cannot be adopted in patients with implanted devices. This study proposes an alternative imaging solution for reconstructing 3D Doppler ultrasound geared towards providing a screening tool for the 3D vessel structure of the brain.
METHODS: The system comprises an ultrasound phased array attached to a servo motor, which can rotate 180˚ at a speed of 2˚/s. We extracted the color Doppler ROI from the image before reconstructing it into a 3D view using a customized pixel-based algorithm. Different vascular diameters, flow velocity, and depth were tested using a vascular phantom with a pumped flow to confirm the system for imaging blood flow. These variables were set to mimic the vessel diameter, flow speed, and depth of the Circle of Willis (CoW) during a transcranial screening.
CONCLUSIONS: The lower values of absolute error and ratio were found in the larger vascular channels, and vessel diameter overrepresentation was observed. Under different flow velocities, such diameter overrepresentation in the reconstructed flow did not change much; however, it did change with different depths. Meanwhile, the setting of the velocity scale and the color gain affected the dimension of reconstructed objectives. Moreover, we presented a 3D image of CoW from a subject to demonstrate its potential. The findings of this work can provide a good reference for further studies on the reconstruction of the CoW or other blood vessels using Doppler imaging.

暂无摘要。

Background: Accurate prenatal diagnosis of cleft lip and palate is essential to discuss severity prediction, perform appropriate parental counseling, and, at last, establish long-term treatment planning. The aim of this systematic review was to analyze the accuracy of various imaging techniques for the prenatal diagnosis of cleft lip and palate, assess the pregnancy phase for orofacial clefts diagnosis, and study the different cleft types in terms of diagnostic methods, timing, and predictability. Methods: A search of the PubMed, EMBASE, Scopus, and Web of Science databases was conducted to identify potentially relevant studies published until January 2024. The quality of the selected articles was assessed using the Newcastle-Ottawa scale for methodological quality assessment of cohort studies and the QUADAS-2 scale for diagnostic test studies. Results: A total of 18 studies met the eligibility criteria and were included in the review. The findings of this review indicate that the majority of studies showed improved diagnostic accuracy when supplementary techniques, such as 3D ultrasound or magnetic resonance imaging, were added to 2D ultrasound. Conclusions: The implementation of magnetic resonance imaging as a standard procedure could significantly improve the precision of diagnosing cleft lip and palate. Therefore, the diagnostic technique used will play a crucial role in the accuracy of the diagnosis.