medical dementia Diagnosis is classified according to clinical symptoms, areas of brain degeneration and atrophy, and pathological features , including: Alzheimer’s disease (accounting for 50% to 60%), vascular dementia (accounting for 20%), and frontotemporal dementia Syndrome (accounting for 10%), dementia with Lewy bodies (accounting for 10%). Each of these diseases has specific clinical presentations, areas of brain atrophy, and pathological slide features.
15 to 20 years before a person develops dementia, the brain actually begins to change , and there may be no obvious symptoms during this period. Once symptoms appear, it is difficult to repair. “Age” is the biggest risk factor for dementia, but this does not mean that young people will not suffer from dementia!
Dementia is a cluster of symptoms, not a specific diagnosis of a disease. In Taiwan, there are about 350,000 people with dementia. It is estimated that there are about 700,000 patients with so-called pre-dementia, that is, patients with “mild cognitive impairment”. However, the mild symptoms are easily ignored, and it is often too late to go to the hospital for examination until the symptoms are severe.
Today, with the advancement of medicine, we still have nothing to do with dementia. There is no effective treatment. We can only detect and prevent it early. However, at present, there is still no clinical examination that can detect these recessive dementia patients in advance, so the goals of early diagnosis and early treatment cannot be achieved.
What are the tools for diagnosing dementia?
Common clinical tools for diagnosing dementia include:
One: Scale. One is
the rapid screening scale, which takes about seven or eight minutes to answer . This method is suitable for a large number of screening tests. The disadvantage is that the accuracy is low, and false negatives or false positives are prone to occur, such as people with insufficient literacy or poor Chinese proficiency. , there will be difficulties in reading the scale, not only the answering speed is slow, but also there may be misunderstandings in interpreting the narrative, which eventually leads to too low scores.
The other is a long-term structured interview scale . Although it is more accurate than the rapid screening test, it still has the disadvantages of being too time-consuming or subjective.
Two: blood test . Thyroid function, kidney function, liver function, electrolytes, syphilis, folic acid, vitamin B12, etc. If the above inspection items are abnormal, it will also cause cognitive dysfunction .
Three: Image. Magnetic resonance imaging (MRI) is used to look at the brain to rule out stroke, brain tumors, or structural abnormalities of the brain, which may also cause dementia symptoms.
Dementia will only be diagnosed if the results of the scale show that cognitive function is significantly reduced, and abnormalities in blood tests and brain imaging are ruled out.
Among them, the most commonly used clinical tools for diagnosing dementia include Clinical Dementia Rating (CDR), Montreal Cognitive Assessment (MOCA), and Mini-Mental State Examination (Mini-Mental State Examination). , MMSE), and neuropsychological examination, etc. However, these are all used to assess the severity of “current” cognitive degeneration, and cannot be used to predict the risk of dementia or the progression of the disease , and to propose preventive measures for high-risk groups of dementia.
Now there is an innovative technology to detect brain age, called “axonal brain age” magnetic resonance imaging examination. To solve the above shortcomings, just scan 15 to 25 minutes of MRI, artificial intelligence (AI) can analyze your brain health and predict your future dementia risk, the advantages are objective, accurate, sensitive, no radiation, no harm, especially the early prediction of the risk of dementia before symptoms appear.
Brain age, also known as brain age, brain age. Just like skin age and bone age, brain age even reveals your overall health status, which is broader and deeper than you think. This kind of examination is to evaluate whether a person’s cranial nerves have degenerated more severely than normal people of the same age by analyzing the “nerve fiber bundles” of the “white matter” of the brain. It can predict the risk of dementia and effectively intervene before symptoms appear .
What are the nerve fiber bundles in the brain? Think of it as the wires of the brain, transmitting signals, and these signals are transmitted in different forms to form different cognitive functions of the human brain. The outer layer of nerve fiber bundles is covered with myelin, which is like a membrane. When the myelin sheath is healthy, the brain nerve fiber bundles are complete, and the signals are naturally transmitted quickly, efficiently and accurately.
When we move and speak, we switch within milliseconds, so of course the signal transmission must be fast enough to cope with our daily life. However, as we get older, the brain nerve bundles will be damaged and become unhealthy , which will affect our health . If the speed of signal conduction is slow, our movements will become sluggish , and daily functions cannot be carried out smoothly, such as memory loss, poor concentration, and slow reaction speed. Severe degeneration of brain nerve structure will lead to dementia , while mild cases will not.
Brain age degeneration over the age of five has a potential risk of dementia
For the prediction of brain age on the market, most of them use relatively large changes in the brain, such as the atrophy of the volume of gray matter and white matter . Previous studies have shown that changes in the microstructure of white matter tract bundles, such as the integrity of the bundles, are more sensitive to the aging process.
The new technology “Brain Age Prediction (BAP)” is to use the image data of “water molecule diffusion technology” to observe the structural changes of the white matter of the brain, and then use a large amount of brain image data to build the brain through machine learning training. age prediction model. The brain age calculated in this way focuses on the degeneration of brain neural connections, which is more relevant to the degeneration of clinical symptoms or cognitive functions than gray matter.
If the brain age degenerates over five years old, it is a potential risk group for dementia. It is recommended to follow up regularly ; if the degeneration is over 10 years old, it means obvious aging, and mild cognitive function may occur in the next 2 to 3 years 10 years later, the risk of dementia will increase by two to three times; a new study in the Journal of Alzheimer’s Disease pointed out that if the brain age is degenerated over 9 years old, it is very likely to be dementia within two years . The suspected dementia in the “Clinical Dementia Rating Scale (CDR)” has changed to mild dementia. However, if the regression is less than 3.22 years old, there is a chance to reverse from suspected dementia to normal cognition.
In other words, brain age difference can predict the risk of mild cognitive impairment in the future for people with normal cognition ; at the same time, it can also predict the risk of dementia early, adjust life style early, reverse brain age and stay away from dementia.
This technology has been certified by the US FDA. Using diffusion magnetic resonance imaging (dMRI) and artificial intelligence (AI), it can analyze the health status of brain nerve fiber bundles. The core technology has been transferred from National Taiwan University School of Medicine for nearly 20 years. The academic research results, in addition to assisting in the diagnosis of various brain diseases or mental disorders, have been verified by clinical data research, and can be used as an objective judgment of pre-dementia, prediction of cognitive degradation speed, and evaluation of preventive intervention effects.
It is generally believed that memory or judgment has significantly deteriorated, and a family history of dementia is a high-risk group for dementia. But in fact, those who have any of the following conditions belong to the high-risk group :