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Jeganathan, Jelliffe

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Jeganathan

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Jelliffe

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Jeganathan, Jelliffe
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    Low-cost three-dimensional printed phantom for neuraxial anesthesia training: Development and comparison to a commercial model
    (Public Library of Science, 2018) Mashari, Azad; Montealegre-Gallegos, Mario; Jeganathan, Jelliffe; Yeh, Lu; Qua Hiansen, Joshua; Meineri, Massimiliano; Mahmood, Feroze; Matyal, Robina
    Neuraxial anesthesia (spinal and epidural anesthesia) procedures have significant learning curves and have been traditionally taught at the bed side, exposing patients to the increased risk associated with procedures done by novices. Simulation based medical education allows trainees to repeatedly practice and hone their skills prior to patient interaction. Wide-spread adoption of simulation-based medical education for procedural teaching has been slow due to the expense and limited variety of commercially available phantoms. Free/Libre/open-source (FLOS) software and desktop 3D printing technologies has enabled the fabrication of low-cost, patient-specific medical phantoms. However, few studies have evaluated the performance of these devices compared to commercially available phantoms. This paper describes the fabrication of a low-cost 3D printed neuraxial phantom based on computed tomorography (CT) scan data, and expert validation data comparing this phantom to a commercially available model. Methods: Anonymized CT DICOM data was segmented to create a 3D model of the lumbar spine. The 3D model was modified, placed inside a digitally designed housing unit and fabricated on a desktop 3D printer using polylactic acid (PLA) filament. The model was filled with an echogenic solution of gelatin with psyllium fiber. Twenty-two staff anesthesiologists performed a spinal and epidural on the 3D printed simulator and a commercially available Simulab phantom. Participants evaluated the tactile and ultrasound imaging fidelity of both phantoms via Likert-scale questionnaire. Results: The 3D printed neuraxial phantom cost $13 to print and required 25 hours of non-supervised printing and 2 hours of assembly time. The 3D printed phantom was found to be less realistic to surface palpation than the Simulab phantom due to fragility of the silicone but had significantly better fidelity for loss of resistance, dural puncture and ultrasound imaging than the Simulab phantom. Conclusion: Low-cost neuraxial phantoms with fidelity comparable to commercial models can be produced using CT data and low-cost infrastructure consisting of FLOS software and desktop 3D printers.
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    Artificial Intelligence in Mitral Valve Analysis
    (Medknow Publications & Media Pvt Ltd, 2017) Jeganathan, Jelliffe; Knio, Ziyad; Amador, Yannis; Hai, Ting; Khamooshian, Arash; Matyal, Robina; Khabbaz, Kamal; Mahmood, Feroze
    Background: Echocardiographic analysis of mitral valve (MV) has become essential for diagnosis and management of patients with MV disease. Currently, the various software used for MV analysis require manual input and are prone to interobserver variability in the measurements. Aim: The aim of this study is to determine the interobserver variability in an automated software that uses artificial intelligence for MV analysis. Settings and Design: Retrospective analysis of intraoperative three-dimensional transesophageal echocardiography data acquired from four patients with normal MV undergoing coronary artery bypass graft surgery in a tertiary hospital. Materials and Methods: Echocardiographic data were analyzed using the eSie Valve Software (Siemens Healthcare, Mountain View, CA, USA). Three examiners analyzed three end-systolic (ES) frames from each of the four patients. A total of 36 ES frames were analyzed and included in the study. Statistical Analysis: A multiple mixed-effects ANOVA model was constructed to determine if the examiner, the patient, and the loop had a significant effect on the average value of each parameter. A Bonferroni correction was used to correct for multiple comparisons, and P = 0.0083 was considered to be significant. Results: Examiners did not have an effect on any of the six parameters tested. Patient and loop had an effect on the average parameter value for each of the six parameters as expected (P < 0.0083 for both). Conclusion: We were able to conclude that using automated analysis, it is possible to obtain results with good reproducibility, which only requires minimal user intervention.
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    Making three-dimensional echocardiography more tangible: a workflow for three-dimensional printing with echocardiographic data
    (Bioscientifica Ltd, 2016) Mashari, Azad; Montealegre-Gallegos, Mario; Knio, Ziyad; Yeh, Lu; Jeganathan, Jelliffe; Matyal, Robina; Khabbaz, Kamal; Mahmood, Feroze
    Three-dimensional (3D) printing is a rapidly evolving technology with several potential applications in the diagnosis and management of cardiac disease. Recently, 3D printing (i.e. rapid prototyping) derived from 3D transesophageal echocardiography (TEE) has become possible. Due to the multiple steps involved and the specific equipment required for each step, it might be difficult to start implementing echocardiography-derived 3D printing in a clinical setting. In this review, we provide an overview of this process, including its logistics and organization of tools and materials, 3D TEE image acquisition strategies, data export, format conversion, segmentation, and printing. Generation of patient-specific models of cardiac anatomy from echocardiographic data is a feasible, practical application of 3D printing technology.