Maternal physical activity and sitting time and its association with placental morphology and blood flow during gestation: Findings from the Queensland Family Cohort study.

OBJECTIVES: Antenatal exercise is associated with placental morphological alterations, however research in this area is limited. Given the emphasis on the beneficial effects of antenatal exercise, it is important to understand its effect on placental function and the relationship to foetal development. The aim of this study was to investigate the association between physical activity, sitting time, and placental outcomes measured during gestation. DESIGN: Prospective cohort study. METHODS: Pregnant women in the Queensland Family Cohort study self-reported physical activity at 24 and 36 weeks of gestation (n = 203) and were categorised into physical activity volume groups of nil-low (0-<500 metabolic equivalent of task·minutes/week), moderate (500-<1000 metabolic equivalent of task·minutes/week), or high-volume activity (≥1000 metabolic equivalent of task·minutes/week). Participants reported average daily sitting time, whereby excessive sitting time was considered as ≥8h/day. Placental stiffness, thickness, and uteroplacental blood flow resistance were measured by ultrasound imaging at each timepoint. RESULTS: Physical activity volume was not associated with changes to placental morphometrics or uteroplacental blood flow resistance at 24 or 36 weeks of gestation. Excessive sitting time at 36 weeks was associated with greater placental stiffness (p = 0.046), and a lower umbilical artery pulsatility index (p = 0.001). CONCLUSIONS: Placental tissue stiffness and umbilical artery resistance were altered in late gestation with higher maternal sitting time but not with physical activity volume. Overall, excessive sitting time may be a risk for suboptimal placental function and could be an important focus for antenatal care.

Automatic GAN-based MRI volume synthesis from US volumes: a proof of concept investigation.

Usually, a baseline image, either through magnetic resonance imaging (MRI) or computed tomography (CT), is captured as a reference before medical procedures such as respiratory interventions like Thoracentesis. In these procedures, ultrasound (US) imaging is often employed for guiding needle placement during Thoracentesis or providing image guidance in MISS procedures within the thoracic region. Following the procedure, a post-procedure image is acquired to monitor and evaluate the patient's progress. Currently, there are no real-time guidance and tracking capabilities that allow a surgeon to perform their procedure using the familiarity of the reference imaging modality. In this work, we propose a real-time volumetric indirect registration using a deep learning approach where the fusion of multi-imaging modalities will allow for guidance and tracking of surgical procedures using US while displaying the resultant changes in a clinically friendly reference imaging modality (MRI). The deep learning method employs a series of generative adversarial networks (GANs), specifically CycleGAN, to conduct an unsupervised image-to-image translation. This process produces spatially aligned US and MRI volumes corresponding to their respective input volumes (MRI and US) of the thoracic spine anatomical region. In this preliminary proof-of-concept study, the focus was on the T9 vertebrae. A clinical expert performs anatomical validation of randomly selected real and generated volumes of the T9 thoracic vertebrae and gives a score of 0 (conclusive anatomical structures present) or 1 (inconclusive anatomical structures present) to each volume to check if the volumes are anatomically accurate. The Dice and Overlap metrics show how accurate the shape of T9 is when compared to real volumes and how consistent the shape of T9 is when compared to other generated volumes. The average Dice, Overlap and Accuracy to clearly label all the anatomical structures of the T9 vertebrae are approximately 80% across the board.

Automatic deep learning-based pleural effusion segmentation in lung ultrasound images.

BACKGROUND: Point-of-care lung ultrasound (LUS) allows real-time patient scanning to help diagnose pleural effusion (PE) and plan further investigation and treatment. LUS typically requires training and experience from the clinician to accurately interpret the images. To address this limitation, we previously demonstrated a deep-learning model capable of detecting the presence of PE on LUS at an accuracy greater than 90%, when compared to an experienced LUS operator. METHODS: This follow-up study aimed to develop a deep-learning model to provide segmentations for PE in LUS. Three thousand and forty-one LUS images from twenty-four patients diagnosed with PE were selected for this study. Two LUS experts provided the ground truth for training by reviewing and segmenting the images. The algorithm was then trained using ten-fold cross-validation. Once training was completed, the algorithm segmented a separate subset of patients. RESULTS: Comparing the segmentations, we demonstrated an average Dice Similarity Coefficient (DSC) of 0.70 between the algorithm and experts. In contrast, an average DSC of 0.61 was observed between the experts. CONCLUSION: In summary, we showed that the trained algorithm achieved a comparable average DSC at PE segmentation. This represents a promising step toward developing a computational tool for accurately augmenting PE diagnosis and treatment.

Deep learning-based ultrasound transducer induced CT metal artifact reduction using generative adversarial networks for ultrasound-guided cardiac radioablation.

In US-guided cardiac radioablation, a possible workflow includes simultaneous US and planning CT acquisitions, which can result in US transducer-induced metal artifacts on the planning CT scans. To reduce the impact of these artifacts, a metal artifact reduction (MAR) algorithm has been developed based on a deep learning Generative Adversarial Network called Cycle-MAR, and compared with iMAR (Siemens), O-MAR (Philips) and MDT (ReVision Radiology), and CCS-MAR (Combined Clustered Scan-based MAR). Cycle-MAR was trained with a supervised learning scheme using sets of paired clinical CT scans with and without simulated artifacts. It was then evaluated on CT scans with real artifacts of an anthropomorphic phantom, and on sets of clinical CT scans with simulated artifacts which were not used for Cycle-MAR training. Image quality metrics and HU value-based analysis were used to evaluate the performance of Cycle-MAR compared to the other algorithms. The proposed Cycle-MAR network effectively reduces the negative impact of the metal artifacts. For example, the calculated HU value improvement percentage for the cardiac structures in the clinical CT scans was 59.58%, 62.22%, and 72.84% after MDT, CCS-MAR, and Cycle-MAR application, respectively. The application of MAR algorithms reduces the impact of US transducer-induced metal artifacts on CT scans. In comparison to iMAR, O-MAR, MDT, and CCS-MAR, the application of developed Cycle-MAR network on CT scans performs better in reducing these metal artifacts.

Genomic and Phenotypic Biomarkers for Precision Medicine Guidance in Advanced Prostate Cancer.

OPINION STATEMENT: Prostate cancer (PCa) is the second most diagnosed malignant neoplasm and is one of the leading causes of cancer-related death in men worldwide. Despite significant advances in screening and treatment of PCa, given the heterogeneity of this disease, optimal personalized therapeutic strategies remain limited. However, emerging predictive and prognostic biomarkers based on individual patient profiles in combination with computer-assisted diagnostics have the potential to guide precision medicine, where patients may benefit from therapeutic approaches optimally suited to their disease. Also, the integration of genotypic and phenotypic diagnostic methods is supporting better informed treatment decisions. Focusing on advanced PCa, this review discusses polygenic risk scores for screening of PCa and common genomic aberrations in androgen receptor (AR), PTEN-PI3K-AKT, and DNA damage response (DDR) pathways, considering clinical implications for diagnosis, prognosis, and treatment prediction. Furthermore, we evaluate liquid biopsy, protein biomarkers such as serum testosterone levels, SLFN11 expression, total alkaline phosphatase (tALP), neutrophil-to-lymphocyte ratio (NLR), tissue biopsy, and advanced imaging tools, summarizing current phenotypic biomarkers and envisaging more effective utilization of diagnostic and prognostic biomarkers in advanced PCa. We conclude that prognostic and treatment predictive biomarker discovery can improve the management of patients, especially in metastatic stages of advanced PCa. This will result in decreased mortality and enhanced quality of life and help design a personalized treatment regimen.

Fluoroscopically guided vascular and cardiac transcatheter procedures: a comparison of occupational and patient dose by anatomical region.

X-ray guided procedures are being performed by an increasing variety of medical specialties. Due to improvements in vascular transcatheter therapies, there is an increasing overlap of imaged anatomy between medical specialties. There is concern that non-radiology fluoroscopic operators may not have sufficient training to be well informed of the potential implications of radiation exposure and mitigation strategies to reduce dose. This was a prospective, observational, single center study to compare occupational and patient dose levels when imaging different anatomical regions during fluoroscopically guided cardiac and endovascular procedures. Occupational radiation dose was measured at the level of the temple of 24 cardiologists and 3 vascular surgeons (n = 1369), 32 scrub nurses (n = 1307) and 35 circulating nurses (n = 885). The patient dose was recorded for procedures (n = 1792) performed in three angiography suites. Abdominal imaging during endovascular aneurysm repair (EVAR) procedures was associated with a comparatively high average patient, operator and scrub nurse dose despite additional table-mounted lead shields. Air kerma was relatively high for procedures performed in the chest, and chest + pelvis. Higher dose area product and staff eye dose were recorded during procedures of the chest + pelvis due to the use of digital subtraction angiography to evaluate access route prior to/during transaortic valve implantation. Scrub nurses were exposed to higher average radiation levels than the operator during some procedures. Staff should be cognizant of the potentially higher radiation burden to patients and exposed personnel during EVAR procedures and cardiac procedures using digital subtraction angiography.

One step surgical scene restoration for robot assisted minimally invasive surgery.

Minimally invasive surgery (MIS) offers several advantages to patients including minimum blood loss and quick recovery time. However, lack of tactile or haptic feedback and poor visualization of the surgical site often result in some unintentional tissue damage. Visualization aspects further limits the collection of imaged frame contextual details, therefore the utility of computational methods such as tracking of tissue and tools, scene segmentation, and depth estimation are of paramount interest. Here, we discuss an online preprocessing framework that overcomes routinely encountered visualization challenges associated with the MIS. We resolve three pivotal surgical scene reconstruction tasks in a single step; namely, (i) denoise, (ii) deblur, and (iii) color correction. Our proposed method provides a latent clean and sharp image in the standard RGB color space from its noisy, blurred, and raw inputs in a single preprocessing step (end-to-end in one step). The proposed approach is compared against current state-of-the-art methods that perform each of the image restoration tasks separately. Results from knee arthroscopy show that our method outperforms existing solutions in tackling high-level vision tasks at a significantly reduced computation time.

MRI-based mechanical analysis of carotid atherosclerotic plaque using a material-property-mapping approach: A material-property-mapping method for plaque stress analysis.

BACKGROUND AND OBJECTIVE: Atherosclerosis is a major underlying cause of cardiovascular conditions. In order to understand the biomechanics involved in the generation and rupture of atherosclerotic plaques, numerical analysis methods have been widely used. However, several factors limit the practical use of this information in a clinical setting. One of the key challenges in finite element analysis (FEA) is the reconstruction of the structure and the generation of a mesh. The complexity of the shapes associated with carotid plaques, including multiple components, makes the generation of meshes for biomechanical computation a difficult and in some cases, an impossible task. To address these challenges, in this study, we propose a novel material-property-mapping method for carotid atherosclerotic plaque stress analysis that aims to simplify the process. METHODS: The different carotid plaque components were identified and segmented using magnetic resonance imaging (MRI). For the mapping method, this information was used in conjunction with an in-house code, which provided the coordinates for each pixel/voxel and tissue type within a predetermined region of interest. These coordinates were utilized to assign specific material properties to each element in the volume mesh which provides a region of transition. The proposed method was subsequently compared to the traditional method, which involves creating a composed mesh for the arterial wall and plaque components, based on its location and size. RESULTS: The comparison between the proposed material-property-mapping method and the traditional method was performed in 2D, 3D structural-only, and fluid-structure interaction (FSI) simulations in terms of stress, wall shear stress (WSS), time-averaged WSS (TAWSS), and oscillatory shear index (OSI). The stress contours from both methods were found to be similar, although the proposed method tended to produce lower local maximum stress values. The WSS contours were also in agreement between the two methods. The velocity contours generated by the proposed method were verified against phase-contrast magnetic resonance imaging (MRI) measurements, for a higher level of confidence. CONCLUSION: This study shows that a material-property-mapping method can effectively be used for analyzing the biomechanics of carotid plaques in a patient-specific manner. This approach has the potential to streamline the process of creating volume meshes for complex biological structures, such as carotid plaques, and to provide a more efficient and less labor-intensive method.

A comparison of patient dose and occupational eye dose to the operator and nursing staff during transcatheter cardiac and endovascular procedures.

The number and complexity of transcatheter procedures continue to increase, raising concerns regarding radiation exposure to patients and staff. Procedures such as transaortic valve implantations (TAVI) have led to cardiologists adopting higher dose techniques, such as digital subtraction angiography (DSA). This study compared the estimated patient and occupational eye dose during coronary angiography (CA), percutaneous coronary intervention (PCI), TAVI workups (TWU), TAVI, endovascular aneurysm repairs (EVAR), and other peripheral diagnostic (VD) and interventional (VI) vascular procedures. A quantitative analysis was performed on patient dose during 299 endovascular and 1498 cardiac procedures. Occupational dose was measured for the cardiologists (n = 24), vascular surgeons (n = 3), scrub (n = 32) and circulator nurses (n = 35). TAVI and EVAR were associated with the highest average dose for all staff, and significantly higher patient dose area product, probably attributable to the use of DSA. Scrub nurses were exposed to higher average doses than the operator and scout nurse during CA, VD and VI. Circulating nurses had the highest average levels of exposure during TAVI. This study has demonstrated that EVAR and TAVI have similar levels of occupational and patient dose, with a notable increase in circulator dose during TAVI. The use of DSA during cardiac procedures is associated with an increase in patient and staff dose, and cardiologists should evaluate whether DSA is necessary. Scrub nurses may be exposed to higher levels of occupational dose than the operator.

Absorbed dose calculation for a realistic CT-derived mouse phantom irradiated with a standard Cs-137 cell irradiator using a Monte Carlo method.

Computed tomography (CT) derived Monte Carlo (MC) phantoms allow dose determination within small animal models that is not feasible with in-vivo dosimetry. The aim of this study was to develop a CT-derived MC phantom generated from a mouse with a xenograft tumour that could then be used to calculate both the dose heterogeneity in the tumour volume and out of field scattered dose for pre-clinical small animal irradiation experiments. A BEAMnrc Monte-Carlo model has been built of our irradiation system that comprises a lead collimator with a 1 cm diameter aperture fitted to a Cs-137 gamma irradiator. The MC model of the irradiation system was validated by comparing the calculated dose results with dosimetric film measurement in a polymethyl methacrylate (PMMA) phantom using a 1D gamma-index analysis. Dose distributions in the MC mouse phantom were calculated and visualized on the CT-image data. Dose volume histograms (DVHs) were generated for the tumour and organs at risk (OARs). The effect of the xenographic tumour volume on the scattered out of field dose was also investigated. The defined gamma index analysis criteria were met, indicating that our MC simulation is a valid model for MC mouse phantom dose calculations. MC dose calculations showed a maximum out of field dose to the mouse of 7% of Dmax. Absorbed dose to the tumour varies in the range 60%-100% of Dmax. DVH analysis demonstrated that tumour received an inhomogeneous dose of 12 Gy-20 Gy (for 20 Gy prescribed dose) while out of field doses to all OARs were minimized (1.29 Gy-1.38 Gy). Variation of the xenographic tumour volume exhibited no significant effect on the out of field scattered dose to OARs. The CT derived MC mouse model presented here is a useful tool for tumour dose verifications as well as investigating the doses to normal tissue (in out of field) for preclinical radiobiological research.

Assessment of thoracic spinal curvatures in static postures using spatially tracked 3D ultrasound volumes: a proof-of-concept study.

The assessment of spinal posture is a difficult endeavour given the lack of identifiable bony landmarks for placement of skin markers. Moreover, potentially significant soft tissue artefacts along the spine further affect the accuracy of marker-based approaches. The objective of this proof-of-concept study was to develop an experimental framework to assess spinal postures by using three-dimensional (3D) ultrasound (US) imaging. A phantom spine model immersed in water was scanned using 3D US in a neutral and two curved postures mimicking a forward flexion in the sagittal plane while the US probe was localised by three electromagnetic tracking sensors attached to the probe head. The obtained anatomical 'coarse' registrations were further refined using an automatic registration algorithm and validated by an experienced sonographer. Spinal landmarks were selected in the US images and validated against magnetic resonance imaging data of the same phantom through image registration. Their position was then related to the location of the tracking sensors identified in the acquired US volumes, enabling the localisation of landmarks in the global coordinate system of the tracking device. Results of this study show that localised 3D US enables US-based anatomical reconstructions comparable to clinical standards and the identification of spinal landmarks in different postures of the spine. The accuracy in sensor identification was 0.49 mm on average while the intra- and inter-observer reliability in sensor identification was strongly correlated with a maximum deviation of 0.8 mm. Mapping of landmarks had a small relative distance error of 0.21 mm (SD = ± 0.16) on average. This study implies that localised 3D US holds the potential for the assessment of full spinal posture by accurately and non-invasively localising vertebrae in space.

Shear wave velocity measurement of the placenta is not limited by placental location.

INTRODUCTION: Ultrasound elastography shows diagnostic promise via the non-invasive determination of placental elastic properties. A limitation is a potential for inadequate measurements from posterior placentae. This study aimed to analyse placental position's influence on measures of shear wave elastography (SWV). METHODS: SWV elastography measurements were obtained via ultrasound at 24, 28 and 36 weeks gestation from 238 pregnancies. . The placental position was labelled as either anterior, posterior or fundal/lateral. Average SWV measurements (m/s) and the corresponding standard deviations (SD) were used for data analysis. RESULTS: There was a statistically significant difference between SWV recorded from anterior (1.33 ± 0.19)m/s and posterior (1.39 ± 0.18)m/s placentae (p < 0.001). However, the average sampling depth between these groups was significantly different (3.98 cm vs. 5.38 cm, p < 0.001). There was no statistically significant difference between SWV when measurements were compared at similar depths, regardless of placental location. The addition of placental position to a previously developed mixed-effects model confirmed placental position did not result in improved SWV measurements. In this model, sampling depth remained the best predictor for SWV. CONCLUSIONS: This study showed that placental position does not influence the accuracy or reliability of SWV.

Differences in Carotid Artery Geometry and Flow Caused by Body Postural Changes and Physical Exercise.

Different body postures and physical exercises may lead to changes in arterial geometry and hemodynamics, which may be associated with the distribution of atherosclerosis lesions. This study was aimed at investigating potential geometric and hemodynamic changes of the carotid bifurcation in different body postures and after high-intensity interval training (HIIT) workouts. Three-dimensional vascular ultrasound (3DVUS) and Doppler ultrasound images were acquired for 21 healthy participants (aged 29 ± 6 y, 14 men and 7 women) in different body postures (sitting and three sleeping postures [supine, left lateral and right lateral]) and after physical exercises. The common carotid artery (CCA) and internal carotid artery (ICA) diameters of the left carotid artery were found to increase significantly from supine to left lateral (both p <0.05). CCA diameters (p < 0.05) and ICA/CCA diameter ratio (p < 0.01) of the left carotid artery changed significantly from supine to sitting. Significant differences in CCA peak systolic velocity (CCA PSV, p < 0.001), CCA end-diastolic velocity (CCA EDV, p < 0.001), CCA pulsatility index (CCA PI, p < 0.001) and maximum velocity-based wall shear stress at the CCA (WSS(max) at the CCA, p < 0.001) were identified in different postures. After physical exercises, significant increases were observed in the CCA diameter (p < 0.001), CCA PSV (p < 0.001), ICA PSV (p < 0.05), WSS(max) at the CCA (p < 0.001) and WSS(max) at the ICA (p < 0.05), as were significantly lower values of the CCA EDV (p < 0.01) and ICA/CCA PSV ratio (p < 0.05). Side-to-side differences were also detected in different postural change scenarios and after physical exercise; more significant differences were found to occur only in the left-sided carotid artery. Significant differences were identified under postural change and after physical exercise among healthy adults, suggesting that daily activity has an effect on the carotid bifurcation. These changes may be associated with formation and development of carotid atherosclerosis. Moreover, these side differences might be severe for patients and worth further attention in clinical practice.

Variability of Biceps Muscle Stiffness Measured Using Shear Wave Elastography at Different Anatomical Locations With Different Ultrasound Machines.

Shear wave elastography is an emerging diagnostic tool used to assess for changes in the stiffness of muscle. Each region of the muscle may have a different stiffness; therefore, the anatomical region should be carefully selected. Machine vendors each have unique methods for calculating the returned stiffness values and, consequently, a high level of agreement in measurement between machines (quantified using the intraclass correlation coefficient [ICC] and Bland-Altman analysis) will allow research findings to be translated to the clinic. This study assessed three locations within the biceps muscle (50% and 75% of the distance between the acromioclavicular joint and antecubital fossa, and superior to distal myotendinous junction [MTJ]) of 32 healthy volunteers with two different machines, the Canon Aplio i600 and SuperSonic Imagine Aixplorer (SSI), to compare the reported shear wave velocities and the variability by coefficient of variation (CV) and ICC. There was no difference in the CV between machines, but a significant difference in the CV at muscle regions, with the 75% location having a 40.2% reduction in CV. The 75% location had the highest ICC values with good posterior mean ICCs of 0.84 on the Canon and 0.83 on the SSI. The 50% and MTJ locations had poor ICC values. The 75% location provided the lowest CV and highest ICC and should be used for future stiffness assessments.

Combined clustered scan-based metal artifact reduction algorithm (CCS-MAR) for ultrasound-guided cardiac radioablation.

Cardiac radioablation is a promising treatment for cardiac arrhythmias, but accurate dose delivery can be affected by heart motion. For this reason, real-time cardiac motion monitoring during radioablation is of paramount importance. Real-time ultrasound (US) guidance can be a solution. The US-guided cardiac radioablation workflow can be simplified by the simultaneous US and planning computed tomography (CT) acquisition, which can result in US transducer-induced metal artifacts on the planning CT scans. To reduce the impact of these artifacts, a new metal artifact reduction (MAR) algorithm (named: Combined Clustered Scan-based MAR [CCS-MAR]) has been developed and compared with iMAR (Siemens), O-MAR (Philips) and MDT (ReVision Radiology) algorithms. CCS-MAR is a fully automated sinogram inpainting-based MAR algorithm, which uses a two-stage correction process based on a normalized MAR method. The second stage aims to correct errors remaining from the first stage to create an artifact-free combined clustered scan for the process of metal artifact reduction. To evaluate the robustness of CCS-MAR, conventional CT scans and/or dual-energy CT scans from three anthropomorphic phantoms and transducers with different sizes were used. The performance of CCS-MAR for metal artifact reduction was compared with other algorithms through visual comparison, image quality metrics analysis, and HU value restoration evaluation. The results of this study show that CCS-MAR effectively reduced the US transducer-induced metal artifacts and that it improved HU value accuracy more or comparably to other MAR algorithms. These promising results justify future research into US transducer-induced metal artifact reduction for the US-guided cardiac radioablation purposes.

Automatic deep learning-based consolidation/collapse classification in lung ultrasound images for COVID-19 induced pneumonia.

Our automated deep learning-based approach identifies consolidation/collapse in LUS images to aid in the identification of late stages of COVID-19 induced pneumonia, where consolidation/collapse is one of the possible associated pathologies. A common challenge in training such models is that annotating each frame of an ultrasound video requires high labelling effort. This effort in practice becomes prohibitive for large ultrasound datasets. To understand the impact of various degrees of labelling precision, we compare labelling strategies to train fully supervised models (frame-based method, higher labelling effort) and inaccurately supervised models (video-based methods, lower labelling effort), both of which yield binary predictions for LUS videos on a frame-by-frame level. We moreover introduce a novel sampled quaternary method which randomly samples only 10% of the LUS video frames and subsequently assigns (ordinal) categorical labels to all frames in the video based on the fraction of positively annotated samples. This method outperformed the inaccurately supervised video-based method and more surprisingly, the supervised frame-based approach with respect to metrics such as precision-recall area under curve (PR-AUC) and F1 score, despite being a form of inaccurate learning. We argue that our video-based method is more robust with respect to label noise and mitigates overfitting in a manner similar to label smoothing. The algorithm was trained using a ten-fold cross validation, which resulted in a PR-AUC score of 73% and an accuracy of 89%. While the efficacy of our classifier using the sampled quaternary method significantly lowers the labelling effort, it must be verified on a larger consolidation/collapse dataset, our proposed classifier using the sampled quaternary video-based method is clinically comparable with trained experts' performance.

Impact of dose reducing software on patient and staff temple dose during fluoroscopically guided pacemaker insertion, closure devices implantation and coronary angiography procedures.

The aim of this study is to investigate the effectiveness of dose reducing software (ClarityIQ) on patient and staff dose during fluoroscopically guided cardiac procedures. Dose measurements were collected in a room without dose reducing software (n = 157) and compared with similar procedures performed in two rooms with the software (n = 1141). Procedures included diagnostic coronary angiography, percutaneous coronary intervention, deployment of cardiac closure devices (for occlusion of atrial septal defect, patent foramen ovale, and atrial appendage) and insertion of permanent pacemakers. The dose reducing software was found to be effective in reducing patient and staff dose by approximately 50%. This study has added to the limited literature reporting on the capability of dose reducing software to decrease radiation exposure during the implantation of cardiac closure devices, as well as demonstrating a reduction in dose to the cardiologist and nursing staff. Administrators should ensure timely upgrades to angiographic equipment to safeguard patients and staff against the potentially adverse effects of radiation exposure. Regardless of the use of dose reducing software, the mean occupational dose during closure devices was in descending order scout > scrub > cardiologist. Scrub nurse dose was found to be higher than the cardiologist during closure devices (0.98/0.26 µSv) and diagnostic coronary angiograms (1.51/0.82 µSv). Nursing staff should be aware that their levels of radiation dose during some cardiac procedures may come close to or even exceed that of the cardiologist.

Ultrasound elastography in the assessment of post-stroke muscle stiffness: a systematic review.

BACKGROUND: Post-stroke muscle stiffness is a major challenge in the rehabilitation of stroke survivors, with no gold standard in clinical assessment. Muscle stiffness is typically evaluated by the Modified Ashworth Scale or the Tardieu Scale; however, these can have low reliability and sensitivity. Ultrasound elastography is an advanced imaging technology that can quantitatively measure the stiffness of a tissue and has been shown to have good construct validity when compared to clinically assessed muscle stiffness and functional motor recovery. OBJECTIVE: The purpose of this article is to systematically review the literature regarding the change in muscle stiffness as measured by ultrasound elastography in stroke survivors. METHODS: Scopus, PubMed, Embase, CINAHL, MEDLINE and Cochrane Library were searched for relevant studies that assessed the change in stiffness of post-stroke muscle stiffness measured by ultrasound elastography following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. RESULTS: In total, 29 articles were identified, using either strain elastography and shear wave elastography to measure the stiffness of muscles in stroke survivors, most frequently in the biceps and medial gastrocnemius muscles. The stiffness was typically higher in the paretic compared to the non-paretic or healthy control. Other variations that increased the stiffness include increasing the joint angle and introducing a passive stretch or muscle activation. The paretic muscle has also been assessed pre- and post-treatment demonstrating a decrease in stiffness. CONCLUSION: Ultrasound elastography is a promising imaging technology for determining the muscle stiffness in stroke survivors with need for a standardized imaging protocol.

Relationship between placental elastography, maternal pre-pregnancy body mass index and gestational weight gain.

INTRODUCTION: Maternal obesity is a significant risk factor for poor pregnancy outcomes. Obesity is linked to abnormalities in placental tissue at term. The purpose of this study was to correlate changes in placental stiffness, measured via ultrasound elastography, with maternal pre-pregnancy body mass index and gestational weight gain. METHODS: Body Mass Index and gestation weight gain data was collected from 238 women. Elastography measurements were obtained via ultrasound at 24-, 28- and 36-weeks' gestation. An analysis using a linear mixed regression model assessed for the statistical significance of pre-pregnancy BMI, pregnancy weight gain and placental SWV (Shear Wave Velocity). RESULTS: Pre-pregnancy weight status has a significant impact on placental tissue stiffness detectable via ultrasound elastography. Placental tissue stiffness was highest in obese women, followed by overweight women. Obese women, on average, had a MeanSWV 0.11 m/s (95% CI (0.061-0.15) m/s, p < 0.001) above the healthy group throughout the 3rd trimester. Weight gain during pregnancy had a small impact on placental stiffness at the end of pregnancy. MeanSWV was 0.06 m/s (95% CI (0.03-0.10) m/s, p < 0.001) higher in the excessive weight gain group. DISCUSSION: Structural changes of the placenta detected via ultrasound elastography techniques are not exclusive to placental dysfunction conditions (pre-eclampsia and growth restriction) but are also associated with maternal obesity.

Ultrasound Imaging Offers Promising Alternative to Create 3-D Models for Personalised Auricular Implants.

Three-dimensional imaging and advanced manufacturing are being applied in health care research to create novel diagnostic and surgical planning methods, as well as personalised treatments and implants. For ear reconstruction, where a cartilage-shaped implant is embedded underneath the skin to re-create shape and form, volumetric imaging and segmentation processing to capture patient anatomy are particularly challenging. Here, we introduce 3-D ultrasound (US) as an available option for imaging the external ear and underlying auricular cartilage structure, and compare it with computed tomography (CT) and magnetic resonance imaging (MRI) against micro-CT (µCT) as a high-resolution reference (gold standard). US images were segmented to create 3-D models of the auricular cartilage and compared against models generated from µCT to assess accuracy. We found that CT was significantly less accurate than the other methods (root mean square [RMS]: 1.30 ± 0.5 mm) and had the least contrast between tissues. There was no significant difference between MRI (RMS: 0.69 ± 0.2 mm) and US (0.55 ± 0.1 mm). US was also the least expensive imaging method at half the cost of MRI. These results unveil a novel use of ultrasound imaging that has not been presented before, as well as support its more widespread use in biofabrication as a low-cost imaging technique to create patient-specific 3D models and implants.