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- All Subjects: Imaging
- Creators: Stabenfeldt, Sarah
- Creators: Frakes, David
- Status: Published
Methods: A virtual, 3D library of clinically-defined normal hearts was compiled from reconstructed CT and MR scans. Non-invasive imaging parameters and patient characteristics were collected and subjected to backward elimination linear regression to define a model relating patient parameters to the total cardiac volume. This regression model was then used to retrospectively accept or reject an ‘ideal’ donor graft from the library for 3 patients that had undergone heart transplantation. Oversized and undersized grafts were also transplanted to qualitatively analyze virtual transplantation specificity.
Results: The backward elimination approach of the data for the 20 patients rejected the factors of BMI, BSA, sex and both end-systolic and end-diastolic left ventricular measurements from echocardiography. Height and weight were included in the linear regression model yielding an adjusted R-squared of 82.5%. Height and weight showed statistical significance with p-values of 0.005 and 0.02 respectively. The final equation for the linear regression model was TCV = -169.320+ 2.874h + 3.578w ± 73 (h=height, w=weight, TCV= total cardiac volume).
Discussion: With the current regression model, height and weight significantly correlate to total cardiac volume. This regression model and virtual normal heart library provide for the possibility of virtual transplant and size-matching for transplantation. The study and regression model is, however, limited due to a small sample size. Additionally, the lack of volumetric resolution from the MR datasets is a potentially limiting factor. Despite these limitations the virtual library has the potential to be a critical tool for clinical care that will continue to grow as normal hearts are added to the virtual library.
Polymeric nanoparticles (NP) consisting of Poly Lactic-co-lactic acid - methyl polyethylene glycol (PLLA-mPEG) or Poly Lactic-co-Glycolic Acid (PLGA) are an emerging field of study for therapeutic and diagnostic applications. NPs have a variety of tunable physical characteristics like size, morphology, and surface topography. They can be loaded with therapeutic and/or diagnostic agents, either on the surface or within the core. NP size is an important characteristic as it directly impacts clearance and where the particles can travel and bind in the body. To that end, the typical target size for NPs is 30-200 nm for the majority of applications. Fabricating NPs using the typical techniques such as drop emulsion, microfluidics, or traditional nanoprecipitation can be expensive and may not yield the appropriate particle size. Therefore, a need has emerged for low-cost fabrication methods that allow customization of NP physical characteristics with high reproducibility. In this study we manufactured a low-cost (<$210), open-source syringe pump that can be used in nanoprecipitation. A design of experiments was utilized to find the relationship between the independent variables: polymer concentration (mg/mL), agitation rate of aqueous solution (rpm), and injection rate of the polymer solution (mL/min) and the dependent variables: size (nm), zeta potential, and polydispersity index (PDI). The quarter factorial design consisted of 4 experiments, each of which was manufactured in batches of three. Each sample of each batch was measured three times via dynamic light scattering. The particles were made with PLLA-mPEG dissolved in a 50% dichloromethane and 50% acetone solution. The polymer solution was dispensed into the aqueous solution containing 0.3% polyvinyl alcohol (PVA). Data suggests that none of the factors had a statistically significant effect on NP size. However, all interactions and relationships showed that there was a negative correlation between the above defined input parameters and the NP size. The NP sizes ranged from 276.144 ± 14.710 nm at the largest to 185.611 ± 15.634 nm at the smallest. In conclusion, the low-cost syringe pump nanoprecipitation method can achieve small sizes like the ones reported with drop emulsion or microfluidics. While there are trends suggesting predictable tuning of physical characteristics, significant control over the customization has not yet been achieved.