Towards Patient Specific Mitral Valve Modelling via Dynamic 3D Transesophageal Echocardiography

Mitral valve disease is a common pathologic problem occurring increasingly in an aging population, and many patients suffering from mitral valve disease require surgical intervention. Planning an interventional approach from diagnostic imaging alone remains a significant clinical challenge. Transesophageal echocardiography (TEE) is the primary imaging modality used diagnostically, it has limitations in image quality and field-of-view. Recently, developments have been made towards modelling patient-specific deformable mitral valves from TEE imaging, however, a major barrier to producing accurate valve models is the need to derive the leaflet geometry through segmentation of diagnostic TEE imaging. This work explores the development of volume compounding and automated image analysis to more accurately and quickly capture the relevant valve geometry needed to produce patient-specific mitral valve models. Volume compounding enables multiple ultrasound acquisitions from different orientations and locations to be aligned and blended to form a single volume with improved resolution and field-of-view. A series of overlapping transgastric views are acquired that are then registered together with the standard en-face image and are combined using a blending function. The resulting compounded ultrasound volumes allow the visualization of a wider range of anatomical features within the left heart, enhancing the capabilities of a standard TEE probe. In this thesis, I first describe a semi-automatic segmentation algorithm based on active contours designed to produce segmentations from end-diastole suitable for deriving 3D printable molds. Subsequently I describe the development of DeepMitral, a fully automatic segmentation pipeline which leverages deep learning to produce very accurate segmentations with a runtime of less than ten seconds. DeepMitral is the first reported method using convolutional neural networks (CNNs) on 3D TEE for mitral valve segmentations. The results demonstrate very accurate leaflet segmentations, and a reduction in the time and complexity to produce a patient-specific mitral valve replica. Finally, a real-time annulus tracking system using CNNs to predict the annulus coordinates in the spatial frequency domain was developed. This method facilitates the use of mitral annulus tracking in real-time guidance systems, and further simplifies mitral valve modelling through the automatic detection of the annulus, which is a key structure for valve quantification, and reproducing accurate leaflet dynamics

Multi-View 3D Transesophageal Echocardiography Registration and Volume Compounding for Mitral Valve Procedure Planning

Three-dimensional ultrasound mosaicing can increase image quality and expand the field of view. However, limited work has been done applying these compounded approaches for cardiac procedures focused on the mitral valve. For procedures targeting the mitral valve, transesophageal echocardiography (TEE) is the primary imaging modality used as it provides clear 3D images of the valve and surrounding tissues. However, TEE suffers from image artefacts and signal dropout, particularly for structures lying below the valve, including chordae tendineae, making it necessary to acquire alternative echo views to visualize these structures. Due to the limited field of view obtainable, the entire ventricle cannot be directly visualized in sufficient detail from a single image acquisition in 3D. We propose applying an image compounding technique to TEE volumes acquired from a mid-esophageal position and several transgastric positions in order to reconstruct a high-detail volume of the mitral valve and sub-valvular structures. This compounding technique utilizes both fully and semi-simultaneous group-wise registration to align the multiple 3D volumes, followed by a weighted intensity compounding step based on the monogenic signal. This compounding technique is validated using images acquired from two excised porcine mitral valve units and three patient data sets. We demonstrate that this compounding technique accurately captures the physical structures present, including the mitral valve, chordae tendineae and papillary muscles. The chordae length measurement error between the compounded ultrasound and ground-truth CT for two porcine valves is reported as 0.7 ± 0.6 mm and 0.6 ± 0.6 mm

Effects of Mindfulness-Based Interventions on Fatigue in Cancer Survivors: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

This systematic review and meta-analysis was designed to determine the efficacy of mindfulness-based interventions (MBIs) in improving fatigue-related outcomes in adult cancer survivors. Randomized controlled trials (RCTs) were identified from PubMed, MEDLINE, PsycINFO, CINAHL, Web of Science, and EMBASE databases and reference lists of included studies. Separate random-effects meta-analyses were conducted for fatigue and vitality/vigor. Twenty-three studies reporting on 21 RCTs (N=2,239) met inclusion criteria. MBIs significantly reduced fatigue compared to controls at post-intervention (g=0.60, 95% CI [0.36, 0.83]) and first follow-up (g=0.42, 95% CI [0.20, 0.64]). Likewise, MBIs significantly improved vitality/vigor at post-intervention (g=0.39, 95% CI [0.25, 0.52]) and first follow-up (g=0.35, 95% CI [0.03, 0.67]). The evidence grade was low due to risk of bias, substantial heterogeneity, and publication bias among studies. MBIs show promise in improving fatigue and vitality/vigor in cancer survivors. More rigorous trials are needed to address current gaps in the evidence base

International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways.

Primary biliary cirrhosis (PBC) is a classical autoimmune liver disease for which effective immunomodulatory therapy is lacking. Here we perform meta-analyses of discovery data sets from genome-wide association studies of European subjects (n=2,764 cases and 10,475 controls) followed by validation genotyping in an independent cohort (n=3,716 cases and 4,261 controls). We discover and validate six previously unknown risk loci for PBC (Pcombined<5 × 10(-8)) and used pathway analysis to identify JAK-STAT/IL12/IL27 signalling and cytokine-cytokine pathways, for which relevant therapies exist

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Multi-View 3D Transesophageal Echocardiography Registration and Volume Compounding for Mitral Valve Procedure Planning

Three-dimensional ultrasound mosaicing can increase image quality and expand the field of view. However, limited work has been done applying these compounded approaches for cardiac procedures focused on the mitral valve. For procedures targeting the mitral valve, transesophageal echocardiography (TEE) is the primary imaging modality used as it provides clear 3D images of the valve and surrounding tissues. However, TEE suffers from image artefacts and signal dropout, particularly for structures lying below the valve, including chordae tendineae, making it necessary to acquire alternative echo views to visualize these structures. Due to the limited field of view obtainable, the entire ventricle cannot be directly visualized in sufficient detail from a single image acquisition in 3D. We propose applying an image compounding technique to TEE volumes acquired from a mid-esophageal position and several transgastric positions in order to reconstruct a high-detail volume of the mitral valve and sub-valvular structures. This compounding technique utilizes both fully and semi-simultaneous group-wise registration to align the multiple 3D volumes, followed by a weighted intensity compounding step based on the monogenic signal. This compounding technique is validated using images acquired from two excised porcine mitral valve units and three patient data sets. We demonstrate that this compounding technique accurately captures the physical structures present, including the mitral valve, chordae tendineae and papillary muscles. The chordae length measurement error between the compounded ultrasound and ground-truth CT for two porcine valves is reported as 0.7 &plusmn; 0.6 mm and 0.6 &plusmn; 0.6 mm

Multi-view 3D echocardiography volume compounding for mitral valve procedure planning

© 2020 SPIE. Echocardiography is widely used for obtaining images of the heart for both preoperative diagnostic and intraoperative purposes. For procedures targeting the mitral valve, transesophageal echocardiography (TEE) is the primary imaging modality used as it provides clear 3D images of the valve and surrounding tissues. However, TEE suffers from image artifacts and signal dropout, particularly for structures lying below the valve including chordae tendineae. In order to see these structures, alternative echo views are required. However due to the limited field of view obtainable, the entire ventricle cannot be directly visualized in sufficient detail from a single image acquisition in 3D. This results in a large learning curve for interpreting these images as the multiple views must be reconciled mentally by a clinician. We propose applying an image compounding technique to TEE images acquired from a mid-esophageal position and a number of transgastric positions in order to reconstruct a high-detail image of the mitral valve and sub-valvular structures. This compounding technique utilizes a semi-simultaneous group-wise registration to align the multiple 3D volumes, followed by a weighted intensity compounding step. This compounding technique is validated using images acquired of a custom silicone phantom, excised porcine mitral valve units, and two patient data sets. We demonstrate that this compounding technique accurately captures the physical structures present, including the mitral valve, chordae tendineae and papillary muscles

Accuracy assessment for the co-registration between optical and VIVE head-mounted display tracking

© 2019, CARS. Purpose: We report on the development and accuracy assessment of a hybrid tracking system that integrates optical spatial tracking into a video pass-through head-mounted display. Methods: The hybrid system uses a dual-tracked co-calibration apparatus to provide a co-registration between the origins of an optical dynamic reference frame and the VIVE Pro controller through a point-based registration. This registration provides the location of optically tracked tools with respect to the VIVE controller’s origin and thus the VIVE’s tracking system. Results: The positional accuracy was assessed using a CNC machine to collect a grid of points with 25 samples per location. The positional trueness and precision for the hybrid tracking system were 0.48mm and 0.23mm, respectively. The rotational accuracy was assessed through inserting a stylus tracked by all three systems into a hemispherical phantom with cylindrical openings at known angles and collecting 25 samples per cylinder for each system. The rotational trueness and precision for the hybrid tracking system were 0. 64 ∘ and 0. 05 ∘, respectively. The difference in position and rotational trueness between the OTS and the hybrid tracking system was 0.27mm and 0. 04 ∘, respectively. Conclusions: We developed a hybrid tracking system that allows the pose of optically tracked surgical instruments to be known within a first-person HMD visualization system, achieving submillimeter accuracy. This research validated the positional and rotational accuracy of the hybrid tracking system and subsequently the optical tracking and VIVE tracking systems. This work provides a method to determine the position of an optically tracked surgical tool with a surgically acceptable accuracy within a low-cost commercial-grade video pass-through HMD. The hybrid tracking system provides the foundation for the continued development of virtual reality or augmented virtuality surgical navigation systems for training or practicing surgical techniques

Restructuring Wildland Fire Management for an Army Training and Testing Center in Cheatgrass-Dominated Landscapes

Maintaining flexibility for military training, while protecting life, facilities, and natural resources can present labyrinthine tradeoffs for managers facing wildfire threats. This is especially true at Dugway Proving Ground, where wildfire can convert sagebrush into cheatgrass-dominated landscapes. To maintain flexibility for military training while limiting ignitions, we developed a new fire danger announcement system using the Energy Release Component (ERC) from three on-installation RAWS, and wind speed using 25 Dugway meteorological stations. Fire danger categories were created using local meteorological records, fire history, and fuel models. These categories are Dugway-specific as they categorize fire danger according to firefighting resources, and provide precautions for training activities. This system provides flexibility for military trainers; areas exhibiting lower fire danger can remain open to a wider range of training activities. To prioritize pre-suppression actions, we employed a values-at-risk approach using vulnerability assessments. Stakeholder interviews identified resources and assessed their value to produce a ranking thereof. Stakeholders included military trainers, the fire department, natural resources, and others. Each resource was assigned a sensitivity ranking, which was then combined with an exposure ranking based on fire frequency, cheatgrass, and ignition sources. This composite produced a vulnerability map, allowing for the design and prioritization of fuelbreaks. We also include various strategies both for fuelbreak installation using of native species, as well as strategies for postfire restoration