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Which DIY Tissue Substitute is Best for Creation of an Ultrasoundable Task Trainer (1090-004193) (Developmental Research Projects: Virtual (By Invitation Only))
Start time: Tuesday, February 2, 2021, 2:00 PM End time: Tuesday, February 2, 2021, 3:00 PM Session Type: Research Study Development and Presentation Program Abstracts Cost: $0.00
Content Category: Researcher
Hypothesis:
There are multiple materials that have been suggested in the literature and online to use for creating a task trainer with simulated tissue that is able to be ultrasounded such as silicone mold, PVC polymers, and gelatin. The authors are not aware of any study that has compared the fidelity and capabilities of these, which would benefit any simulation center that builds their own models that require ultrasound capabilities. The hypothesis is that a ballistic gel model will outperform other simulated tissue models in regards to 'realism' and 'depth of penetration with identifiable structures'. Our research questions are as follows: 1) Which commercially available material to simulate tissue provides the highest fidelity ('realism') appearance of image obtained by ultrasound for a DIY task trainer; and 2) Is there a difference in depth of ultrasound penetration based on which commercially available material is used to simulate tissue for a DIY task trainer.
Methods:
This is a prospective, experimental study to compare the following commercially available materials that are commonly referenced in literature and online to use in building a ultrasound capable tissue simulator: 1) silicone mold; 2) ballistic gel; 3) PVC polymer 4) gelatin (with or without fiber additive); 5) agar; 6) precooked processed meat; 7) tofu. Following IRB review a model will be created with each of the tissue material listed above that has the following: a) fluid filled long thin balloon at an angle of approximately 45 degrees from 0 cm to 10 cm; and b) uncooked spaghetti noodle at an angle of approximately 45 degrees from 0 cm to 10 cm. Attending and resident physicians will be asked to ultrasound each model and rate them on image similarity to clinical practice and on depth they are able to ultrasound. Statistical analysis will then be performed on those results.
Anticipated Results:
We anticipate collecting likert scale ordinal data associated with research question 1 and continuous data with research question 2. We will use descriptive statistics such as ranges, means, and counts on all data. We will also use inferential statistics such as chi square and Mood's Median test to evaluate for significance of differences noted.