BerlinIn the fight against Alzheimer's disease, early detection is particularly important. If the still incurable dementia is diagnosed early, it can at least slow down the course with medications.
"If we diagnose Alzheimer's disease only when clear symptoms emerge, the loss of brain volume is so great that it is usually too late for effective surgery," explains Jae Ho Sohn.
Together with his team from the University of California at San Francisco, the doctor developed a new tool for early diagnosis of Alzheimer's disease: an adaptive algorithm that reliably predicts dementia years before a doctor's diagnosis.
The researchers focused their development on subtle metabolic changes in the brain caused by the onset of the disease. Such changes can be visualized using an imaging technique known as positron emission tomography (PET).
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However, traces in the early stages of the disease are so weak that they are hardly recognizable even for experienced doctors. "It is easier for humans to find disease-specific biomarkers," explains Sohn. "But metabolic changes are much thinner processes."
Researchers trained their artificial intelligence using Alzheimer's Disease Neuroimaging Initiative (ADNI) data. Among other things, this data collection contains thousands of PET images of Alzheimer's patients in the early stages of the disease. Ninety percent of these records, the researchers used to train the algorithm, the remaining 10 percent to control success.
For the final test, IA had to finally analyze 40 images that had not been presented to date. The result describes the child as follows: "The algorithm was able to reliably detect any case, which later came to the onset of Alzheimer's disease".
In addition to the 100 percent success rate, doctors have impressed above all the very early identification of cases. On average, the system recognized the symptoms more than six years before the actual diagnosis of the disease. "We were very happy with this result," says Son. However, the doctor also knows that the test series was still relatively small and further tests must confirm the result.
However, he sees in his algorithm the potential for an important tool in the treatment of Alzheimer's: "If we can detect the disease first, it will give researchers the opportunity to find better ways to slow down or even stop the disease process ".