Artificial intelligence may aid in Alzheimer's diagnosis

July 6, 2016
The classifiers can be represented as discrimination maps, where a red color indicates that the intensity at that location contributes to the likelihood of the images belonging to the more advanced stage, and a blue color to the likelihood of belonging to the less advanced stage. Weights are shown inside the mask that resulted in the highest accuracies for each classification: A: Alzheimer's disease (AD) vs. subjective cognitive decline (SCD); B: AD vs. mild cognitive impairment (MCI); C: MCI vs. SCD. Credit: Radiological Society of North America

Machine learning is a type of artificial intelligence that allows computer programs to learn when exposed to new data without being programmed. Now, researchers in The Netherlands have coupled machine learning methods with a special MRI technique that measures the perfusion, or tissue absorption rate, of blood throughout the brain to detect early forms of dementia, such as mild cognitive impairment (MCI), according to a new study published online in the journal Radiology.

"MRI can help with the diagnosis of Alzheimer's ," said principal investigator Alle Meije Wink, Ph.D., from the VU University Medical Centre in Amsterdam. "However, the early diagnosis of Alzheimer's disease is problematic."

Scientists have long known that Alzheimer's disease is a gradual process and that the brain undergoes functional changes before the structural changes associated with the disease show up on imaging results. Physicians have no definitive way of identifying who has early dementia or which cases of mild will progress to Alzheimer's disease.

"With standard diagnostic MRI, we can see advanced Alzheimer's disease, such as atrophy of the hippocampus," Dr. Meije Wink said. "But at that point, the brain tissue is gone and there's no way to restore it. It would be helpful to detect and diagnose the disease before it's too late."

For the new study, the researchers applied machine to special type of MRI called arterial spin labeling (ASL) imaging. ASL MRI is used to create images called perfusion maps, which show how much blood is delivered to various regions of the brain.

The automated machine learning program is taught to recognize patterns in these maps to distinguish among patients with varying levels of cognitive impairment and predict the stage of Alzheimer's disease in new (unseen) cases.

Discrimination maps for classifying MCI subgroups, inside the masks that resulted in the highest accuracies. A: between patients with MCI that converted to AD (MCIc) and subjects with SCD; B: between MCIc and patients with MCI that remained stable (MCIs). Credit: Radiological Society of North America

The study included 260 of 311 participants from the Alzheimer Center of the VU University Medical Center dementia cohort who underwent ASL MRI between October 2010 and November 2012.

The study group included 100 patients diagnosed with probable Alzheimer's disease, 60 patients with (MCI) and 100 patients with subjective cognitive decline (SCD), and 26 healthy controls.

SCD and MCI are considered to be early stages of the dementia process and are diagnosed based on the severity of cognitive symptoms, including memory loss and thought- and decision-making problems.

The automated system was able to distinguish effectively among participants with Alzheimer's disease, MCI and SCD. Using classifiers based on the automated machine learning training, the researchers were then able to predict the Alzheimer's diagnosis or progression of single patients with a high degree of accuracy, ranging from 82 percent to 90 percent.

"ASL is a promising alternative functional biomarker for the early diagnosis of Alzheimer's disease," Dr. Meije Wink said.

He added that the application of automated methods would be useful as a potential screening tool.

"ASL MRI can identify brain changes that appear early in disease process, when there's a window of opportunity for intervention," Dr. Meije Wink said. "If the disease process from SCD to MCI to Alzheimer's disease could be intercepted or slowed, this technique could play a role in screening."

Explore further: Study shows effectiveness of brief, simple test to screen for cognitive impairment in Alzheimer's disease

More information: "Application of Machine Learning to Arterial Spin Labeling in Mild Cognitive Impairment and Alzheimer Disease" Radiology, 2016.

Related Stories

Study shows effectiveness of brief, simple test to screen for cognitive impairment in Alzheimer's disease

July 5, 2016
For the first time, researchers have determined that a brief, simple number naming test can differentiate between cognitively healthy elderly individuals and cognitively impaired people with Alzheimer's disease (AD), including ...

MRI technique detects evidence of cognitive decline before symptoms appear

October 7, 2014
A magnetic resonance imaging (MRI) technique can detect signs of cognitive decline in the brain even before symptoms appear, according to a new study published online in the journal Radiology. The technique has the potential ...

Team develops blood test that detects early Alzheimer's disease

June 8, 2016
A research team, led by Dr. Robert Nagele from Rowan University School of Osteopathic Medicine and Durin Technologies, Inc., has announced the development of a blood test that leverages the body's immune response system to ...

Changes in blood flow to the brain may be early feature of Alzheimer's disease

June 22, 2016
A new study has shown that changes in blood flow to different brain areas may be one of the earliest changes in the brain linked to Alzheimer's disease. The research is published today in the journal Nature Communications.

Current screening methods miss worrisome number of persons with mild cognitive impairment

May 24, 2016
Mild cognitive impairment (MCI) is a slight but noticeable and measurable decline in cognitive abilities, such as remembering names or a list of items. While changes may not be severe enough to disrupt daily life, a clinical ...

Recommended for you

Thinking 'out-of-the-box' may build a better brain and prevent dementia

September 25, 2017
More than 5 million Americans today are affected by Alzheimer's disease (AD). If nothing is done to stop this upward trajectory, there will be more than 16 million people with AD in the United States and more than 60 million ...

Multi-gene test predicts Alzheimer's better than APOE E4 alone

September 22, 2017
A new test that combines the effects of more than two dozen genetic variants, most associated by themselves with only a small risk of Alzheimer's disease, does a better job of predicting which cognitively normal older adults ...

Personality changes don't precede clinical onset of Alzheimer's, study shows

September 21, 2017
For years, scientists and physicians have been debating whether personality and behavior changes might appear prior to the onset of Alzheimer's disease and related dementias.

Newly ID'd role of major Alzheimer's gene suggests possible therapeutic target

September 20, 2017
Nearly a quarter century ago, a genetic variant known as ApoE4 was identified as a major risk factor for Alzheimer's disease—one that increases a person's chances of developing the neurodegenerative disease by up to 12 ...

Is the Alzheimer's gene the ring leader or the sidekick?

September 15, 2017
The notorious genetic marker of Alzheimer's disease and other forms of dementia, ApoE4, may not be a lone wolf.

Potential noninvasive test for Alzheimer's disease

September 6, 2017
In the largest and most conclusive study of its kind, researchers have analysed blood samples to create a novel and non-invasive way of helping to diagnose Alzheimer's disease and distinguishing between different types of ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.