Diagnosis of ulnar nerve entrapment anterior to the medial epicondyle by ultrasound elastography and diffusion tensor imaging with fiber tractography: a case report

Ulnar/cubital tunnel syndrome is the second most common compressive neuropathy of the upper limb. Permanent location of the ulnar nerve anterior to the medial epicondyle is extremely rare, with only five cases reported in the literature. Using ultrasound elastography and diffusion tensor imaging with fiber tractography, we diagnosed a case in which ulnar nerve entrapment was associated with anterior nerve location. Surgical release confirmed the diagnosis and the patient was symptom free 3 months after surgery.

Breast Tumour Classification Using Ultrasound Elastography with Machine Learning: A Systematic Scoping Review

Ultrasound elastography can quantify stiffness distribution of tissue lesions and complements conventional B-mode ultrasound for breast cancer screening. Recently, the development of computer-aided diagnosis has improved the reliability of the system, whilst the inception of machine learning, such as deep learning, has further extended its power by facilitating automated segmentation and tumour classification. The objective of this review was to summarize application of the machine learning model to ultrasound elastography systems for breast tumour classification. Review databases included PubMed, Web of Science, CINAHL, and EMBASE. Thirteen (n = 13) articles were eligible for review. Shear-wave elastography was investigated in six articles, whereas seven studies focused on strain elastography (5 freehand and 2 Acoustic Radiation Force). Traditional computer vision workflow was common in strain elastography with separated image segmentation, feature extraction, and classifier functions using different algorithm-based methods, neural networks or support vector machines (SVM). Shear-wave elastography often adopts the deep learning model, convolutional neural network (CNN), that integrates functional tasks. All of the reviewed articles achieved sensitivity ³ 80%, while only half of them attained acceptable specificity ³ 95%. Deep learning models did not necessarily perform better than traditional computer vision workflow. Nevertheless, there were inconsistencies and insufficiencies in reporting and calculation, such as the testing dataset, cross-validation, and methods to avoid overfitting. Most of the studies did not report loss or hyperparameters. Future studies may consider using the deep network with an attention layer to locate the targeted object automatically and online training to facilitate efficient re-training for sequential data.

Mechanical Deformation of Peripapillary Retina in Response to Acute Intraocular Pressure Elevation

Elevated intraocular pressure (IOP) may cause mechanical injuries to the optic nerve head (ONH) and the peripapillary tissues in glaucoma. Previous studies have reported the mechanical deformation of the ONH and the peripapillary sclera (PPS) at elevated IOP. The deformation of the peripapillary retina (PPR) has not been well-characterized. Here we applied high-frequency ultrasound elastography to map and quantify PPR deformation, and compared PPR, PPS and ONH deformation in the same eye. Whole globe inflation was performed in ten human donor eyes. High-frequency ultrasound scans of the posterior eye were acquired while IOP was raised from 5 to 30 mmHg. A correlation-based ultrasound speckle tracking algorithm was used to compute pressure-induced displacements within the scanned tissue cross-sections. Radial, tangential, and shear strains were calculated for the PPR, PPS, and ONH regions. In PPR, shear was significantly larger in magnitude than radial and tangential strains. Strain maps showed localized high shear and high tangential strains in PPR. In comparison to PPS and ONH, PPR had greater shear and a similar level of tangential strain. Surprisingly, PPR radial compression was minimal and significantly smaller than that in PPS. These results provide new insights into PPR deformation in response of IOP elevation, suggesting that shear rather than compression was likely the primary mode of IOP-induced mechanical insult in PPR. High shear, especially localized high shear, may contribute to the mechanical damage of this tissue in glaucoma.

Regional pleural strain measurements during mechanical ventilation using ultrasound elastography: A randomised, crossover, proof of concept physiologic study

Background Mechanical ventilation is a common therapy in operating rooms and intensive care units. When ill-adapted, it can lead to ventilator-induced lung injury (VILI), which is associated with poor outcomes. Excessive regional pulmonary strain is thought to be a major mechanism responsible for VILI. Scarce bedside methods exist to measure regional pulmonary strain. We propose a novel way to measure regional pleural strain using ultrasound elastography. Research Question The objective of this study was to assess the feasibility and reliability of pleural strain measurement by ultrasound elastography and to determine if elastography parameters would correlate with varying tidal volumes. Study Design and Methods A single-blind randomized crossover proof of concept study was conducted July to October 2017 at a tertiary care referral center. Ten patients requiring general anesthesia for elective surgery were recruited. After induction, patients were received tidal volumes of 6, 8, 10 and 12 mL.kg-1 in random order, while pleural ultrasound cineloops were acquired at 4 standardized locations. Ultrasound radiofrequency speckle tracking allowed computing various pleural translation, strain and shear components. These were screened to identify those with the best dose-response with tidal volumes using linear mixed effect models. Goodness-of-fit was assessed by the coefficient of determination. Intraobserver, interobserver and test-retest reliability were calculated using intraclass correlation coefficients. Results Analysis was possible in 90.7% of ultrasound cineloops. Lateral absolute shear, lateral absolute strain and Von Mises strain varied significantly with tidal volume and offered the best dose-responses and data modelling fits. Point estimates for intraobserver reliability measures were excellent for all 3 parameters (0.94, 0.94 and 0.93, respectively). Point estimates for interobserver (0.84, 0.83 and 0.77, respectively) and test-retest (0.85, 0.82 and 0.76, respectively) reliability measures were good. Interpretation Strain imaging is feasible and reproducible, and may eventually guide mechanical ventilation strategies in larger cohorts of patients.

Ultrasound for the Diagnosis of Biliary Atresia: From Conventional Ultrasound to Artificial Intelligence

Biliary atresia is an aggressive liver disease of infancy and can cause death without timely surgical intervention. Early diagnosis of biliary atresia is critical to the recovery of bile drainage and long-term transplant-free survival. Ultrasound is recommended as the initial imaging strategy for the diagnosis of biliary atresia. Numerous ultrasound features have been proved helpful for the diagnosis of biliary atresia. In recent years, with the help of new technologies such as elastography ultrasound, contrast-enhanced ultrasound and artificial intelligence, the diagnostic performance of ultrasound has been significantly improved. In this review, various ultrasound features in the diagnosis of biliary atresia are summarized. A diagnostic decision flow chart for biliary atresia is proposed on the basis of the hybrid technologies, combining conventional ultrasound, elastography and contrast-enhanced ultrasound. In addition, the application of artificial intelligence in the diagnosis of biliary atresia with ultrasound images is also introduced.