Development of a novel mobile application to assist in the diagnosis of Fetal Alcohol Syndrome (FAS)
Development of a novel mobile application to assist in the diagnosis of Fetal Alcohol Syndrome (FAS)
批准号:
9905934
负责人:
Ganz Chockalingam
金额:
$22.5万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-20 至 2020-05-31
关键词:
3-DimensionalAffectAgreementAutomobile DrivingBackCellular PhoneCharacteristicsChargeChildClinicalConfidence IntervalsConfusionConsensusConsultationsDataDevelopmentDiagnosisDiagnosticDiagnostic ProcedureElementsEquationEthnic groupEvaluationExpert OpinionFaceFeedbackFetal Alcohol ExposureFetal Alcohol Spectrum DisorderFetal Alcohol SyndromeFissuralHealth PersonnelHealth ProfessionalImageIndividualLengthLicensingLip structureManualsMeasurementMeasuresMethodologyMobile Health ApplicationPatientsPerformancePhenotypePhysiciansPopulationPositioning AttributeProcessPublic HealthRaceReportingSamplingSecureSeriesServicesSex DifferencesShapesSideStructureSurveysTabletsTechnical ExpertiseTechnologyTestingThinnessThree-Dimensional ImageValidationValidity and Reliabilityanimationbaseclinical Diagnosisclinically relevantcloud basedcommercializationcostexperiencefallsfetal diagnosisheuristicsimaging modalitymobile applicationnovelpediatricianprototypeskillstool
中文摘要
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英文摘要
Project Summary/Abstract. Fetal alcohol spectrum disorder (FASD) is a major public health issue resulting
from prenatal alcohol exposure (PAE), impacting between 1-5% of the US population and perhaps more than
630,000 children globally each year. When assessing for FASD the following facial features must to be evaluated
as part of the diagnostic process: palpebral fissure length (PFL), thinness of the upper vermillion, and the
smoothness of the philtrum. PFL is typically assessed with a metric ruler or photometrically, while the lip and
philtrum are evaluated against a series of five Likert scale photos. Each of these assessments has
methodological problems often resulting in unreliable application of specific diagnostic criteria. There is also a
reluctance on the part of health care providers to diagnose FASD because they don’t feel confident in their skills,
resulting in under- or misdiagnosis. Furthermore, the number of affected individuals is far greater than the
capacity of diagnosticians, especially when considering the global impact of PAE. Some of the issues involved
in the diagnosis of FASD could be remedied by simple-to-use mobile apps that would take much of the
guesswork or heuristic elements out of the diagnostic equation, provide evaluation based upon expert opinion,
and can be used by health care providers globally. Several aims of this project revolve around replacing the
standard Likert scale lip-philtrum guide with an animation, morphing from a full to a thin upper lip on a continuous
slider scale that the user controls while examining a subject. A similar morphing tool is proposed for the
assessment of the philtrum. This would eliminate much of the confusion that exists between the rankings required
for a fetal alcohol syndrome (FAS) or partial FAS (pFAS) diagnosis. The 5-point Likert scale doesn’t provide
enough guidance and agreement even among experts is often mediocre. Rather than having a scale with only
five demarcations, where really only the demarcation between a Rank 3 and 4 matters for a diagnosis, the apps
allow for a more accurate assessment by providing a continuous distribution removing all ambiguity.
Dysmorphologists who are expert at diagnosing FAS will determine the demarcation points for an upper lip and
a smooth philtrum compatible with a diagnosis of FAS or pFAS for use in the app. Bias in the current diagnostic
methods will also be assessed. PFL is an extremely difficult measurement even for experts, and it is proposed
that using a smartphone camera with 3D capability would provide a more accurate way to assess this cardinal
feature. These apps could be used by health care providers anywhere in the world to receive expert opinion
feedback almost instantly to assist them in making a difficult yet critically important clinical diagnosis. We are in
a unique position to accomplish these endeavors, as we have both the clinical and technical expertise to develop
the apps, and access to data to validate the findings. Given the scope of the problem and the lack of access to
expert diagnosticians, these mobile health applications should overcome at least some of the issues involved in
the diagnosis of FASD.
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