[{"innerBlocks":[],"name":"core\/freeform","postId":3535,"blockType":{"name":"core\/freeform","keywords":[],"attributes":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"providesContext":[],"usesContext":[],"selectors":[],"supports":{"className":false,"customClassName":false,"reusable":false},"styles":[],"variations":[],"apiVersion":3,"title":"Classic","description":"Use the classic WordPress editor.","category":"text"},"originalContent":"The global fight against rare genetic diseases has a new tool in its arsenal for early diagnoses of these dreaded conditions\u2014facial recognition software.

Researchers at the National Human Genome Research Institute have successfully leveraged the software to help diagnose DiGeorge syndrome, a rare genetic disease that afflicts African, Asian and Latin American children. The technology has also been used for diagnosing Down syndrome.

According to Maximilian Muenke, MD, chief of the Medical Genetics Branch at NHGRI, facial features are crucial to the diagnosis of such diseases. However, Muenke contends that the appearance of individuals with the diseases can vary widely in diverse populations, making it difficult for clinicians to diagnose.

However, Muenke\u2019s colleague Marius George Linguraru, an investigator at the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children\u2019s National Health System in Washington, developed facial recognition software that is very accurate in diagnosing DiGeorge syndrome and Down syndrome using photographs of patients from different ethnic groups.

\u201cFacial landmark\u201d detection is the key, says Muenke. The software measures facial features such as \u201cdistances between eyes, distances between the lips, and whether the eyes slant upwards or downwards,\u201d he adds.

Results of a study<\/a>, published last week in the American Journal of Medical Genetics<\/i> by Muenke and his colleagues, showed that researchers using the facial recognition software made correct diagnoses more than 96 percent of the time for DiGeorge syndrome\u2014also known as velocardiofacial syndrome, which can cause heart defects, poor immune system function, a cleft palate, and low levels of calcium in the blood.

Also See<\/b>: NIH putting in place global rare diseases repository<\/a>

The effort is part of NHGRI\u2019s Atlas of Human Malformations in Diverse Populations, a website launched last September to serve as an online resource for clinicians looking to diagnose different inherited diseases through photographs of people with syndromic disorders and the molecular diagnoses gathered from around the world, including Asia, the Indian subcontinent, the Middle East, South America and sub-Saharan Africa.

Muenke, who is co-creator of the atlas, notes that the only previously available diagnostic atlas featured photos of patients of northern European descent, which was very limiting in terms of geographic value. \u201cWe were leaving out the majority of the world\u2019s population,\u201d he says.

\u201cHuman malformation syndromes appear different in different parts of the world,\" said Paul Kruszka, MD, a medical geneticist in NHGRI\u2019s Medical Genetics Branch. \u201cEven experienced clinicians have difficulty diagnosing genetic syndromes in non-European populations.\u201d

DiGeorge syndrome and Down syndrome have now been added to the electronic atlas, which shows the pattern of malformations that are consistent with these syndromes, according to Muenke. Providers with limited resources or access to genetic specialists are able to use the atlas and the facial recognition software for early diagnoses of these rare diseases that often go undiagnosed, he says.

\u201cWe take photos of every syndrome that we can get our hands on,\u201d Muenke adds. At the same time, he relates that there is no identifying personal information on the atlas website.

Going forward, Muenke says researchers plan to study Noonan syndrome and Williams syndrome, which are also rare genetic disorders. Nonetheless, he hastens to add that \u201cthe trained clinician is always better than the software,\u201d and in those areas of the world that have shortages of trained clinicians, then \u201cthe software is so much better\u201d for making diagnoses in those populations.","saveContent":"The global fight against rare genetic diseases has a new tool in its arsenal for early diagnoses of these dreaded conditions\u2014facial recognition software.

Researchers at the National Human Genome Research Institute have successfully leveraged the software to help diagnose DiGeorge syndrome, a rare genetic disease that afflicts African, Asian and Latin American children. The technology has also been used for diagnosing Down syndrome.

According to Maximilian Muenke, MD, chief of the Medical Genetics Branch at NHGRI, facial features are crucial to the diagnosis of such diseases. However, Muenke contends that the appearance of individuals with the diseases can vary widely in diverse populations, making it difficult for clinicians to diagnose.

However, Muenke\u2019s colleague Marius George Linguraru, an investigator at the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children\u2019s National Health System in Washington, developed facial recognition software that is very accurate in diagnosing DiGeorge syndrome and Down syndrome using photographs of patients from different ethnic groups.

\u201cFacial landmark\u201d detection is the key, says Muenke. The software measures facial features such as \u201cdistances between eyes, distances between the lips, and whether the eyes slant upwards or downwards,\u201d he adds.

Results of a study<\/a>, published last week in the American Journal of Medical Genetics<\/i> by Muenke and his colleagues, showed that researchers using the facial recognition software made correct diagnoses more than 96 percent of the time for DiGeorge syndrome\u2014also known as velocardiofacial syndrome, which can cause heart defects, poor immune system function, a cleft palate, and low levels of calcium in the blood.

Also See<\/b>: NIH putting in place global rare diseases repository<\/a>

The effort is part of NHGRI\u2019s Atlas of Human Malformations in Diverse Populations, a website launched last September to serve as an online resource for clinicians looking to diagnose different inherited diseases through photographs of people with syndromic disorders and the molecular diagnoses gathered from around the world, including Asia, the Indian subcontinent, the Middle East, South America and sub-Saharan Africa.

Muenke, who is co-creator of the atlas, notes that the only previously available diagnostic atlas featured photos of patients of northern European descent, which was very limiting in terms of geographic value. \u201cWe were leaving out the majority of the world\u2019s population,\u201d he says.

\u201cHuman malformation syndromes appear different in different parts of the world,\" said Paul Kruszka, MD, a medical geneticist in NHGRI\u2019s Medical Genetics Branch. \u201cEven experienced clinicians have difficulty diagnosing genetic syndromes in non-European populations.\u201d

DiGeorge syndrome and Down syndrome have now been added to the electronic atlas, which shows the pattern of malformations that are consistent with these syndromes, according to Muenke. Providers with limited resources or access to genetic specialists are able to use the atlas and the facial recognition software for early diagnoses of these rare diseases that often go undiagnosed, he says.

\u201cWe take photos of every syndrome that we can get our hands on,\u201d Muenke adds. At the same time, he relates that there is no identifying personal information on the atlas website.

Going forward, Muenke says researchers plan to study Noonan syndrome and Williams syndrome, which are also rare genetic disorders. Nonetheless, he hastens to add that \u201cthe trained clinician is always better than the software,\u201d and in those areas of the world that have shortages of trained clinicians, then \u201cthe software is so much better\u201d for making diagnoses in those populations.","order":0,"get_parent":{},"attributes":[],"attributesType":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"dynamicContent":""}]

NIH leverages facial recognition software to diagnose rare genetic diseases

More for you