In the complex world of pediatric care, diagnosing rare diseases can often feel like searching for a needle in a haystack. With thousands of rare conditions and overlapping symptoms, pediatricians face immense challenges in identifying these elusive disorders early. In Europe, the average time from symptom onset to first medical contact was approximately 5 months, while the average time from first medical contact to confirmed diagnosis was 4.3 years. 

Advancements in technology, particularly in the field of artificial intelligence (AI), are offering new hope. Among these, Face2Gene, an AI-powered application that analyses facial features to assist in the identification of rare genetic conditions is gaining recognition in the medical community, with several recent scientific studies highlighting its effectiveness.  

Below, we explore two studies that emphasize the value of Face2Gene in pediatric care: 

 

THE APPROACH TO A CHILD WITH DYSMORPHIC FEATURES: WHAT THE PEDIATRICIAN SHOULD KNOW 

Ciancia, S.; Madeo, S.F.; et al. The Approach to a Child with Dysmorphic Features: What the Pediatrician Should Know. Children2024, 11, 578. https://doi.org/10.3390/children11050578 

Pediatricians often encounter children with unique physical features, some of which may be indicative of underlying genetic conditions. Recognizing these dysmorphic features—subtle abnormalities in facial or bodily structure—is crucial for early diagnosis and intervention. A recent article published in Children 2024, titled “The Approach to a Child with Dysmorphic Features: What the Pediatrician Should Know,” provides a comprehensive guide for pediatricians on how to approach and assess children presenting with dysmorphic features. 

This article highlights the increasing role of technology in the assessment of dysmorphic features. Tools like Face2Gene use facial recognition software to compare a child’s features with a database of known genetic conditions. This can provide pediatricians with a list of potential diagnoses, which can be further explored through genetic testing. Such tools enhance diagnostic accuracy and can be particularly helpful in complex cases where multiple syndromes may be considered. 

The authors outline several key steps that pediatricians should follow when evaluating a child with dysmorphic features: 

 

  1. Detailed Medical and Family History: A thorough history is essential, including information on prenatal development, birth history, and any family history of genetic conditions or birth defects. This information can provide vital clues and help narrow down potential diagnoses. 
  2. Comprehensive Physical Examination: Pediatricians should conduct a meticulous physical examination, focusing on both major and minor anomalies. This includes measuring the child’s head circumference, assessing facial proportions, and examining the limbs and torso for any abnormalities. Using standardized growth charts and reference images can aid in identifying deviations from typical development. 
  3. Photographic Documentation: High-quality photographs of the child’s face, profile, and full body are invaluable for comparison with known syndromes. These images can be used for consultation with specialists or for further analysis using tools like Face2Gene, an AI-powered application that assists in diagnosing genetic conditions based on facial features. 
  4. Genetic Testing and Referral: If dysmorphic features suggest a genetic condition, pediatricians should consider genetic testing, such as chromosomal microarray analysis or whole-exome sequencing. Additionally, referral to a geneticist or a multidisciplinary clinic specializing in dysmorphology is recommended for further evaluation and diagnosis. 

 

A COST-EFFICIENT ALGORITHM FOR DIAGNOSING CHILDREN WITH DYSMORPHIC FEATURES 

Levkova, M., Stoyanova, M., Hachmeriyan, M. et al. A cost-efficient algorithm for diagnosing children with dysmorphic features. Egypt J Med Hum Genet 25, 76 (2024). https://doi.org/10.1186/s43042-024-00545-y 

 

Diagnosing children with dysmorphic features—subtle physical anomalies that often indicate underlying genetic conditions—can be a complex and resource-intensive process. However, a recent study published in the Egyptian Journal of Human Genetics titled “A Cost-Efficient Algorithm for Diagnosing Children with Dysmorphic Features” presents a promising approach that combines advanced technology with a streamlined diagnostic process. This approach aims to improve diagnostic accuracy while reducing costs, making it a valuable tool for clinicians, especially in resource-limited settings. 

Dysmorphic features, which include atypical facial structures, unusual growth patterns, or abnormal limb proportions, are often the first visible signs of a genetic syndrome. However, the sheer number of potential syndromes—many of which have overlapping features—makes diagnosis challenging. Traditional diagnostic methods often involve extensive and expensive genetic testing, which can be time-consuming and inaccessible for many families. 

The study introduces a protocol designed to address these challenges by prioritizing the most likely diagnoses based on initial assessments and utilizing advanced facial analysis technology to guide further testing.  

The proposed workflow integrates several key components: 

  1. Initial Clinical Assessment: The process begins with a detailed clinical evaluation by a pediatrician, focusing on the identification of major and minor dysmorphic features. This step is crucial in narrowing down the possible conditions and guiding the subsequent use of technology. 
  2. Facial Analysis with AI Tools: The algorithm incorporates AI-powered tools like Face2Gene to analyze the child’s facial features. This step reduces the need for broad-spectrum genetic testing by suggesting the most probable conditions. 
  3. Targeted Genetic Testing: Based on the results from the facial analysis, the article suggests specific genetic tests that are most likely to confirm the  diagnosis. By focusing on targeted tests rather than broad panels, this approach significantly reduces costs while maintaining diagnostic accuracy.
  4. Multidisciplinary Review: The final step involves a review by a multidisciplinary team, including geneticists, pediatricians, and other specialists, to confirm the diagnosis and develop a management plan. This collaborative approach ensures that all aspects of the child’s health are considered in the diagnosis and subsequent care.
    Advantages of this approach are: 
  • Reduced Costs 
  • Faster Diagnosis 
  • Accessibility 
  • Improved Diagnostic Accuracy 

 

The study presents several case examples where this approach has been successfully implemented, demonstrating its effectiveness in clinical practice. In one case, a child with non-specific dysmorphic features was quickly diagnosed with a rare genetic condition allowing for timely treatment and management. 

 

 You can check out the more scientific articles about Face2Gene here.

Face2Gene User Community Includes Users From:

  • Using Face2Gene to reference all my department’s cases, share information with my colleagues and quickly look up relevant information in the London Medical Databases Online saves me hours of work every week and allows me to focus on my patients.

    Dr. Ibrahim Akalin

    Assoc. Prof. Ibrahim Akalin, MD, Medical Geneticist from the Istanbul Medeniyet University, Istanbul, Turkey

  • FDNA’s game-changing technology introduces an objective computer-aided dimension to the “art of dysmorphology”, transforming the analysis into an evidence-based science.

    Dr. Michael R. Hayden

    Chairman of FDNA’s Scientific Advisory Board & Steering Committee and Editor in Chief of Clinical Genetics

  • FDNA is developing technology that has the potential to help so many physicians and families by bringing them closer to a diagnosis- there are literally millions of individuals with unusual features around the world that lack a diagnosis and therefore lack information on natural history, recurrence risk and prevention of known complications.

    Dr. Judith G. Hall

    Professor Emerita of Pediatrics & Medical Genetics UBC & Children's and Women's Health Centre of BC

  • FDNA has been “right on the money”, providing me with relevant, accurate and insightful information for differential diagnoses.

    Dr. Cynthia J.R. Curry

    Professor of Pediatrics UCSF, Adjunct Professor of Pediatrics Stanford

  • I am excited to be a part of the FDNA community, promoting broad information sharing with my peers to amplify the scientific and clinical value of our community’s accumulated knowledge for the purpose of efficiently diagnosing individuals with rare genetic disorders.

    Dr. Karen W. Gripp

    Chief, Division of Medical Genetics A.I. duPont Hospital for Children

  • FDNA's idea of incorporating several dysmorphology resources (OMIM, GeneReviews), supported by their visual analytic technology, will be able to improve researching of genetic syndromes - all within a single mobile app.

    Dr. Chad Haldeman-Englert

    Assistant Professor Pediatrics at Mission Fullerton Genetics

  • Given the advancement of visual analytical technology, it’s about time Dysmorphology is supported with computational capabilities and moving this to mobile support, is simply the next logical step.

    Dr. Chanika Phornphutkul

    Associate Professor of Pediatrics Director, Division of Human Genetics Department of Pediatrics Warren Alpert Medical School of Brown University

  • Having an archive of cases easily accessible from my mobile device anytime and anywhere is a long-time unmet need.

    Dr. Lynne Bird

    Rady Children's Specialists of San Diego

  • FDNA's solution is a huge leap forward for dysmorphology. It saves me significant time when I’m evaluating patients in my clinic and provides me with insightful tools that help me generate a differential diagnosis.

    Dr. David A. Chitayat

    Head of the Prenatal Diagnosis and Medical Genetics Program at Mount Sinai Hospital, Toronto

  • Shortly after learning about Face2Gene, I’ve started to incorporate this amazing tool into my workflow. Soon enough, Face2Gene’s analysis flushed out references that I would not have considered for several of my patients, which turned out to be their correct diagnosis

    Dr. Zvi U. Borochowitz

    Chairman (Retired) of The Simon Winter Institute for Human Genetics at Bnai-Zion Medical Center, Technion-Rappaport Faculty of Medicine

  • The Unknown Forum from Face2Gene is a great community platform for exchanging opinions regarding undiagnosed cases. It is straightforward to use and safe for exchange of medical data, thanks to the efforts of its developers and to the involvement of geneticists worldwide.

    Dr. Oana Moldovan

    Clinical Geneticist at the Hospital Santa Maria, CHLN, Lisbon, Portugal