Browsing by Subject "prenatal testing"

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    Creation of a Novel 3D-Printed Amniocentesis Simulation Model and Impact on Resident Confidence
    (European Society of medicine, 2024-08-31) Pape, Kelsey J.; Wilson, Ashtin; Cronin, Nichole; Parmenter, Jacob; Ellis, Nick; Rouse, Caroline E.; Shanks, Anthony L.
    Background: Non-invasive prenatal screening has decreased opportunities for diagnostic antenatal procedures during residency training. Commercially available models are often cost prohibitive while homemade models can be low fidelity and non-reusable. Objective: To create a training tool with realistic anatomy, tissue-specific tactile sensation, and cost-effective assembly for amniocentesis procedural technique practice and evaluate its impact on trainee confidence with performance. Study Design: Collaborating with biomedical engineering students, our team defined several characteristics to achieve a high-fidelity model: compatible with ultrasound, anatomically accurate, demonstrate tactile realism, endure repeat use, and be cost-effective. A 3-D printed model was created that satisfied fidelity guidelines after rigorous materials and imaging testing. Results: We implemented the model in the observed structured clinical exam for Obstetrics and Gynecology residents in which trainees (PGY2-4) performed an amniocentesis after guided practice with Maternal-Fetal Medicine faculty. Residents were given pre and post-simulation Likert scale surveys regarding confidence and satisfaction with the model. Descriptive analyses and paired t-test were used for analysis. 19 residents completed both pre and post surveys. Mean resident confidence in performing an amniocentesis increased from 1.6 to 3.2 (p<0.001, scale 1-5) after the practice session. Most residents (89.5%) strongly agreed that the model was easy to use and would use it to practice independently. Conclusion: This novel 3-D printed, ultrasound compatible, anatomically accurate, and cost-effective amniocentesis model provides high-fidelity procedural practice and improved trainee confidence. Models such as these have the potential to greatly impact skill development for rare procedures. Future directions include modifying this model for additional fetal procedures, such as cordocentesis.
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    Reliable detection of subchromosomal deletions and duplications using cell-based noninvasive prenatal testing
    (Wiley, 2018-10-25) Vossaert, Liesbeth; Wang, Qun; Salman, Roseen; Zhuo, Xinming; Qu, Chunjing; Henke, David; Seubert, Ron; Chow, Jennifer; U'ren, Lance; Enright, Brennan; Stilwell, Jackie; Kaldjian, Eric; Yang, Yaping; Shaw, Chad; Levy, Brynn; Wapner, Ronald; Breman, Amy; Veyver, Ignatia Van den; Beaudet, Arthur; Medical and Molecular Genetics, School of Medicine
    Objective To gather additional data on the ability to detect subchromosomal abnormalities of various sizes in single fetal cells isolated from maternal blood, using low-coverage shotgun next-generation sequencing for cell-based noninvasive prenatal testing (NIPT). Method Fetal trophoblasts were recovered from approximately 30 mL of maternal blood using maternal white blood cell depletion, density-based cell separation, immunofluorescence staining, and high-resolution scanning. These trophoblastic cells were picked as single cells and underwent whole genome amplification for subsequent genome-wide copy number analysis and genotyping to confirm the fetal origin of the cells. Results Applying our fetal cell isolation method to a series of 125 maternal blood samples, we detected on average 4.17 putative fetal cells/sample. The series included 15 cases with clinically diagnosed fetal aneuploidies and five cases with subchromosomal abnormalities. This method was capable of detecting findings that were 1 to 2 Mb in size, and all were concordant with the microarray or karyotype data obtained on a fetal sample. A minority of fetal cells showed evidence of genome degradation likely related to apoptosis. Conclusion We demonstrate that this cell-based NIPT method has the capacity to reliably diagnose fetal chromosomal abnormalities down to 1 to 2 Mb in size.