Three-dimensional (3D) photogrammetry in association with Cliniface—an open-source software for facial analysis—could have a role in the diagnosis of hereditary angioedema (HAE), according to a study published in PLOS Digital Health.

The authors of the study anticipate multiple benefits for the application of quantitative 3D facial imaging in analyzing the physiognomy of people with HAE, including raising the index of suspicion of HAE and assisting in early detection and diagnosis, identifying early objective prodromal signs of an imminent HAE episode, and improving treatment outcomes and quality of life of patients.

3D facial data of people living with HAE could be integrated into a knowledge base and correlated with clinical data and patient-centric metrics, involving all stakeholders involved in care delivery. Moreover, it can be combined with other parameters (eg, patient-reported outcome and experience measures) to establish potential digital biomarkers for the disease.

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“This blueprint for hereditary angioedema may have far-reaching consequences beyond disease diagnosis to benefit all the stakeholders in the healthcare arena including research and new drug development,” the study’s authors said.

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This study also highlighted several new opportunities for 3D facial analysis to provide value to patients with HAE and clinicians. For instance, 3D facial scans capturing the neck of the patient may provide objective detection of unique or shared subtle subclinical alterations that might correlate with facial and laryngeal manifestations.

Expanding the scope of Cliniface to include 3D scans of a patient’s abdomen, which would be feasible with current 3D imaging hardware and measurement tools provided by the software, would allow healthcare providers to obtain objective reproducible measurements of swelling to support pain scores, as well as other symptoms, thereby creating a more comprehensive picture of the disease. This would improve the knowledge on HAE, paving the path to better treatment.

Furthermore, objective 3D facial data can aid in the process of creating personalized facial devices to improve patients’ quality of life.


Jamuar S, Palmer R, Dawkins H, Lee D-W, Helmholz P, Baynam G. 3D facial analysis for rare disease diagnosis and treatment monitoring: proof-of-concept plan for hereditary angioedema. PLOS Digit Health. 2023;2(3):e0000090. doi:10.1371/journal.pdig.0000090