FASD Diagnostic Telemedicine Resource

NIH RePORTER · NIH · U24 · $370,438 · view on reporter.nih.gov ↗

Abstract

Project Summary Prenatal alcohol exposure is estimated to impact 1-5% of children in the US alone. Yet, many individuals who have been exposed prenatally to alcohol and suffer from fetal alcohol spectrum disorders (FASD) fail to be recognized. This failure is due, in large part, to a paucity of specialized clinics and expert dysmorphologists who are trained to identify FASD. Access to appropriate diagnostic expertise is particularly limited in remote areas. Unfortunately, if individuals with FASD are not recognized and diagnosed, they do not receive critically needed services nor can they access potential interventions early in life, when intervention is most likely to be effective. The CIFASD5 Diagnostic-Telemedicine Resource (DTR) will ensure consistent and accurate assessment of the physical characteristics of FASD across the CIFASD research sites. In addition, the DTR will address the critical need for increased diagnostic capacity through training of non-expert practitioners across CIFASD5 sites using telemedicine-based methods. In the previous CIFASD4 iteration, telemedicine approaches were tested for this purpose in a small sample of clinicians and found to be an effective method for training and monitoring of new examiners. In CIFASD5, this method will be extended to multiple sites and be employed in the evaluation of over 1,800 children and adults. However, telemedicine alone is insufficient to expand capacity and ensure consistency and accuracy of diagnosis. To that end, several novel eHealth tools have been developed to assist in the detection of physical features associated with prenatal alcohol exposure. These tools hold promise in providing simple and efficient ways to screen and identify FASD. These include MorpheusQ, a smart-phone based app that automates facial feature detection; Face-to-Gene, a 2D facial image diagnostic aid used by clinical geneticists to screen for potential syndromes; and 3D facial image signatures. These tools are scalable and have the potential to improve screening and diagnosis across the globe, even in remote areas, such as in Alaska. However, the diagnostic accuracy of these tools needs to be systematically compared to standardized dysmorphological exams. It is essential to determine whether eHealth tools can effectively replace and/or improve traditional exams before they are widely implemented.

Key facts

NIH application ID
10470671
Project number
2U24AA014815-19
Recipient
UNIVERSITY OF CALIFORNIA, SAN DIEGO
Principal Investigator
Miguel del Campo Casanelles
Activity code
U24
Funding institute
NIH
Fiscal year
2022
Award amount
$370,438
Award type
2
Project period
2022-09-15 → 2027-04-30