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3D Technology Uses Children’s Faces to Help Diagnose Rare Diseases

March 27, 2019 By Tierney King

A new project hopes to help with clinical diagnosing, drug treatment monitoring, and clinical trials by using 3D facial image visualization and analysis methods.

The project, called Cliniface, is led by research fellow Dr. Richard Palmer, from the Discipline of Spatial Sciences at Curtin’s School of Earth and Planetary Sciences. Dr. Palmer said 63,000 children in Western Australian alone were affected by rare diseases; providing an early and accurate diagnosis is an unmet need, he says.

“The shape and growth of the face is a window into a person’s health, and this technology is especially suited to younger patients where conditions can be discovered through tell-tale variations in the development of facial features,” Dr. Palmer said. “This technology unobtrusively takes highly accurate measurements from a 3D image of a face and analyzes them in seconds to help detect latent medical issues. Assessing whether a face has grown in a way that might be due to an underlying rare condition in childhood is when this tool is most useful, meaning it speeds up the diagnosis and resulting medical intervention.”

These 3D facial images explore different features of the facial surface to visualize, identify, and communicate cues of syndromic or surgical relevance.

Helping with the project, Cliniface’s project manager Dr. Petra Helmholz, said they are hopeful these 3D facial images of Indigenous children and newborns may provide a more efficient diagnosis of rare diseases. In turn, this could help save numerous lives and better care to those who are diagnosed too late or aren’t diagnosed at all.

“The project has already attracted considerable interest from clinicians and institutes in Australia and overseas including in the US, Europe and India,” said Dr. Helmholz. “The latest version of the Cliniface application was recently released and includes new facial measurements that allows clinicians to generate PDF reports for clinicians highlighting which facial traits of potential medical relevance have been detected.”

The application is free and open source, and can be used for both Windows and Linux.

Analysis of facial measurements Credit: Cliniface

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