Comparison of extramedullary versus intramedullary referencing for tibial component alignment in total ankle arthroplasty.

BACKGROUND: The majority of total ankle arthroplasty (TAA) systems use extramedullary alignment guides for tibial component placement. However, at least 1 system offers intramedullary referencing. In total knee arthroplasty, studies suggest that tibial component placement is more accurate with intramedullary referencing. The purpose of this study was to compare the accuracy of extramedullary referencing with intramedullary referencing for tibial component placement in total ankle arthroplasty. METHODS: The coronal and sagittal tibial component alignment was evaluated on the postoperative weight-bearing anteroposterior (AP) and lateral radiographs of 236 consecutive fixed-bearing TAAs. Radiographs were measured blindly by 2 investigators. The postoperative alignment of the prosthesis was compared with the surgeon's intended alignment in both planes. The accuracy of tibial component alignment was compared between the extramedullary and intramedullary referencing techniques using unpaired t tests. Interrater and intrarater reliabilities were assessed with intraclass correlation coefficients (ICCs). RESULTS: Eighty-three tibial components placed with an extramedullary referencing technique were compared with 153 implants placed with an intramedullary referencing technique. The accuracy of the extramedullary referencing was within a mean of 1.5 ± 1.4 degrees and 4.1 ± 2.9 degrees in the coronal and sagittal planes, respectively. The accuracy of intramedullary referencing was within a mean of 1.4 ± 1.1 degrees and 2.5 ± 1.8 degrees in the coronal and sagittal planes, respectively. There was a significant difference (P < .001) between the 2 techniques with respect to the sagittal plane alignment. Interrater ICCs for coronal and sagittal alignment were high (0.81 and 0.94, respectively). Intrarater ICCs for coronal and sagittal alignment were high for both investigators. CONCLUSIONS: Initial sagittal plane tibial component alignment was notably more accurate when intramedullary referencing was used. Further studies are needed to determine the effect of this difference on clinical outcomes and long-term survivability of the implants. LEVEL OF EVIDENCE: Level III, retrospective comparative study.

A COMPARISON OF MARKET CLEARING TOOLS IN ELECTRICITY SYSTEMS

To maintain a strict balance between demand and supply in the US power systems, the Independent System Operators (ISOs) schedule power plants and determine electricity prices using a market clearing model. This model determines for each time period and power plant, the times of startup, shutdown, the amount of power production, and the provisioning of spinning and non-spinning power generation reserves, etc. Such a deterministic optimization model takes as input the characteristics of all the generating units such as their power generation installed capacity, ramp rates, minimum up and down time requirements, and marginal costs for production, as well as the forecast of intermittent energy such as wind and solar, along with the minimum reserve requirement of the whole system. This reserve requirement is determined based on the likelihood of outages on the supply side and on the levels of error forecasts in demand and intermittent generation. With increased installed capacity of intermittent renewable energy, determining the appropriate level of reserve requirements has become harder. Stochastic market clearing models have been proposed as an alternative to deterministic market clearing models. Rather than using a fixed reserve targets as an input, stochastic market clearing models take different scenarios of wind power into consideration and determine reserves schedule as output. Using a scaled version of the power generation system of PJM, a regional transmission organization (RTO) that coordinates the movement of wholesale electricity in all or parts of 13 states and the District of Columbia, and wind scenarios generated from BPA (Bonneville Power Administration) data, this paper explores a comparison of the performance between a stochastic and deterministic model in market clearing. The two models are compared in their ability to contribute to the affordability, reliability and sustainability of the electricity system, measured in terms of total operational costs, load shedding and air emissions. The process of building the models and running for tests indicate that a fair comparison is difficult to obtain due to the multi-dimensional performance metrics considered here, and the difficulty in setting up the parameters of the models in a way that does not advantage or disadvantage one modeling framework. Along these lines, this study explores the effect that model assumptions such as reserve requirements, value of lost load (VOLL) and wind spillage costs have on the comparison of the performance of stochastic vs deterministic market clearing models.

Preoperative pain level and patient expectation predict hospital length of stay after total hip arthroplasty.

The purpose of this study was to identify preoperative predictors of length of stay after primary total hip arthroplasty in a patient population reflecting current trends toward shorter hospitalization and using readily obtainable factors that do not require scoring systems. A retrospective review of 112 consecutive patients was performed. High preoperative pain level and patient expectation of discharge to extended care facilities (ECFs) were the only significant multivariable predictors of hospitalization extending beyond 2 days (P=0.001 and P<0.001 respectively). Patient expectation remained significant after adjusting for Medicare's 3-day requirement for discharge to ECFs (P<0.001). The study was adequately powered to analyze the variables in the multivariable logistic regression model, which had a concordance index of 0.857.

Preoperative predictors of extended hospital length of stay following total knee arthroplasty.

The purpose of this study was to identify the preoperative predictors of hospital length of stay after primary total knee arthroplasty in a patient population reflecting current trends toward shorter hospitalization and using readily obtainable factors that do not require scoring systems. A single-center, multi-surgeon retrospective chart review of two hundred and sixty consecutive patients who underwent primary total knee arthroplasty was performed. The mean length of stay was 3.0 days. Among the different variables studied, increasing comorbidities, lack of adequate assistance at home, and bilateral surgery were the only multivariable significant predictors of longer length of stay. The study was adequately powered for statistical analyses and the concordance index of the multivariable logistic regression model was 0.815.

A Tissue-Engineered Microvascular System to Evaluate Vascular Progenitor Cells for Angiogenic Therapies

The ability of tissue engineered constructs to replace diseased or damaged organs is limited without the incorporation of a functional vascular system. To design microvasculature that recapitulates the vascular niche functions for each tissue in the body, we investigated the following hypotheses: (1) cocultures of human umbilical cord blood-derived endothelial progenitor cells (hCB-EPCs) with mural cells can produce the microenvironmental cues necessary to support physiological microvessel formation in vitro; (2) poly(ethylene glycol) (PEG) hydrogel systems can support 3D microvessel formation by hCB-EPCs in coculture with mural cells; (3) mesenchymal cells, derived from either umbilical cord blood (MPCs) or bone marrow (MSCs), can serve as mural cells upon coculture with hCB-EPCs. Coculture ratios between 0.2 (16,000 cells/cm2) and 0.6 (48,000 cells/cm2) of hCB-EPCs plated upon 3.3 µg/ml of fibronectin-coated tissue culture plastic with (80,000 cells/cm2) of human aortic smooth muscle cells (SMCs), results in robust microvessel structures observable for several weeks in vitro. Endothelial basal media (EBM-2, Lonza) with 9% v/v fetal bovine serum (FBS) could support viability of both hCB-EPCs and SMCs. Coculture spatial arrangement of hCB-EPCs and SMCs significantly affected network formation with mixed systems showing greater connectivity and increased solution levels of angiogenic cytokines than lamellar systems. We extended this model into a 3D system by encapsulation of a 1 to 1 ratio of hCB-EPC and SMCs (30,000 cells/µl) within hydrogels of PEG-conjugated RGDS adhesive peptide (3.5 mM) and PEG-conjugated protease sensitive peptide (6 mM). Robust hCB-EPC microvessels formed within the gel with invasion up to 150 µm depths and parameters of total tubule length (12 mm/mm2), branch points (127/mm2), and average tubule thickness (27 µm). 3D hCB-EPC microvessels showed quiescence of hCB-EPCs (<1% proliferating cells), lumen formation, expression of EC proteins connexin 32 and VE-cadherin, eNOS, basement membrane formation by collagen IV and laminin, and perivascular investment of PDGFR-β+/α-SMA+ cells. MPCs present in <15% of isolations displayed >98% expression for mural markers PDGFR-β, α-SMA, NG2 and supported hCB-EPC by day 14 of coculture with total tubule lengths near 12 mm/mm2. hCB-EPCs cocultured with MSCs underwent cell loss by day 10 with a 4-fold reduction in CD31/PECAM+ cells, in comparison to controls of hCB-EPCs in SMC coculture. Changing the coculture media to endothelial growth media (EBM-2 + 2% v/v FBS + EGM-2 supplement containing VEGF, FGF-2, EGF, hydrocortisone, IGF-1, ascorbic acid, and heparin), promoted stable hCB-EPC network formation in MSC cocultures over 2 weeks in vitro, with total segment length per image area of 9 mm/mm2. Taken together, these findings demonstrate a tissue engineered system that can be utilized to evaluate vascular progenitor cells for angiogenic therapies.

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Design of Latent Thermal Energy Storage Systems

This dissertation documents the results of a theoretical and numerical study of time dependent storage of energy by melting a phase change material. The heating is provided along invading lines, which change from single-line invasion to tree-shaped invasion. Chapter 2 identifies the special design feature of distributing energy storage in time-dependent fashion on a territory, when the energy flows by fluid flow from a concentrated source to points (users) distributed equidistantly on the area. The challenge in this chapter is to determine the architecture of distributed energy storage. The chief conclusion is that the finite amount of storage material should be distributed proportionally with the distribution of the flow rate of heating agent arriving on the area. The total time needed by the source stream to ‘invade’ the area is cumulative (the sum of the storage times required at each storage site), and depends on the energy distribution paths and the sequence in which the users are served by the source stream. Chapter 3 shows theoretically that the melting process consists of two phases: “invasion” thermal diffusion along the invading line, which is followed by “consolidation” as heat diffuses perpendicularly to the invading line. This chapter also reports the duration of both phases and the evolution of the melt layer around the invading line during the two-dimensional and three-dimensional invasion. It also shows that the amount of melted material increases in time according to a curve shaped as an S. These theoretical predictions are validated by means of numerical simulations in chapter 4. This chapter also shows that the heat transfer rate density increases (i.e., the S curve becomes steeper) as the complexity and number of degrees of freedom of the structure are increased, in accord with the constructal law. The optimal geometric features of the tree structure are detailed in this chapter. Chapter 5 documents a numerical study of time-dependent melting where the heat transfer is convection dominated, unlike in chapter 3 and 4 where the melting is ruled by pure conduction. In accord with constructal design, the search is for effective heat-flow architectures. The volume-constrained improvement of the designs for heat flow begins with assuming the simplest structure, where a single line serves as heat source. Next, the heat source is endowed with freedom to change its shape as it grows. The objective of the numerical simulations is to discover the geometric features that lead to the fastest melting process. The results show that the heat transfer rate density increases as the complexity and number of degrees of freedom of the structure are increased. Furthermore, the angles between heat invasion lines have a minor effect on the global performance compared to other degrees of freedom: number of branching levels, stem length, and branch lengths. The effect of natural convection in the melt zone is documented.

The Barriers to the Integration of the Uterine Balloon Tamponade into South Africa and Ghana's Health Systems for the Management of Postpartum Hemorrhage

Background

Postpartum hemorrhage is the most significant contributor to maternal mortality globally, claiming 140,000 lives annually. Postpartum hemorrhage is a leading cause of maternal death in South Africa, with the literature indicating that 80 percent of the postpartum hemorrhage deaths in South Africa are avoidable. Ghana, as of 2010, witnesses 2700 maternal deaths annually, primarily because of poor quality of care in health facilities and services being difficult to access. As per WHO recommendations, uterotonics are integral to treating postpartum hemorrhage as soon as it is diagnosed. In case of persistent bleeding or limited availability of uterotonics, the uterine balloon tamponade (UBT) can be used as a second line of defense. If both these measures are unable to counter the bleeding, providers must perform surgical interventions. Literature on the UBT, as one tool in the protocol to address postpartum hemorrhage, has shown it to have success rates ranging from 60 to 100 percent. Despite the potential to lower the number of postpartum hemorrhage deaths in South Africa and Ghana, the UBT has not been incorporated widely in South Africa and Ghana. The aim of this study is to describe the barriers involved with integrating the UBT into South Africa and Ghana’s health systems to address postpartum hemorrhage.

Methods

The study took place in multiple sites in South Africa (Cape Town, Johannesburg, Durban and Mpumalanga) and in Accra, Ghana. South Africa and Ghana were selected because postpartum hemorrhage contributes greatly to their maternal mortality numbers and there is potential in both countries to lower those rates through greater use of the UBT. A total of 25 participants were interviewed through purposive sampling, snowball sampling and participant referrals, and included various categories of stakeholders integral to the integration process of a medical device. Individual in-depth interviews were used for data collection, with interview questions being tailored to each stakeholder category. The focus of the interviews was on the protocol used to counter postpartum hemorrhage, the frequency with which the UBT is used as part of the protocol, and the process of integrating it into the South Africa and Ghana’s health systems. The data collected were coded using NVivo and analyzed using content analysis.

Results

The barriers to integration of the uterine balloon tamponade to address postpartum hemorrhage in South Africa and Ghana were evident on the political, economic and health delivery levels. The results indicated that the barriers to integration in South Africa included the low recognition of postpartum hemorrhage as a problem, the lack of clarity surrounding the role of the Medicines Control Council as a regulatory body for medical devices, and low awareness of the UBT as an intervention to control postpartum hemorrhage. The barriers in Ghana were the cash constraints experienced by the Ghana Health Services to fund medical devices, a heavy reliance on donors for funding, and the lack of consistent knowledge on processes involving clinical trials for new medical devices in Ghana.

Conclusion

Existing literature on methods to counter postpartum hemorrhage to reduce maternal mortality has focused on and emphasized the efficacy of the UBT. Despite overwhelming evidence supporting the use of the UBT, many health systems across the world, particularly low-income countries, do not have access to the device owing to numerous barriers in integrating the device into obstetric care. This study illustrates the need to focus on incorporating the UBT into health systems for greater availability to health workers and its use as standard of care. Ultimately, this study can be used as a stepping-stone for more research on this subject, providing evidence to influence policymakers to integrate the UBT into their protocols for postpartum hemorrhage response.