Artificial Intelligence may Aid in Alzheimer's Diagnosis

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 disease," 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 cognitive impairment 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 learning methods 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.

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 mild cognitive impairment (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 machine learning 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."

"Application of Machine Learning to Arterial Spin Labeling in Mild Cognitive Impairment and Alzheimer Disease." Collaborating with Dr. Meije Wink were Lyduine E. Collij, B.Sc., Fiona Heeman, B.Sc., Joost P. A. Kuijer, Ph.D., Rik Ossenkoppele, Ph.D., Marije R. Benedictus, Ph.D., Christiane Möller, Ph.D., Sander C. J. Verfaillie, M.Sc., Ernesto J. Sanz-Arigita, Ph.D., Bart N. M. van Berckel, Prof. M.D., Ph.D., Wiesje M. van der Flier, Prof. Ph.D., Philip Scheltens, Prof. M.D., Ph.D., and Frederik Barkhof, Prof. M.D., Ph.D.

Radiology is edited by Herbert Y. Kressel, M.D., Harvard Medical School, Boston, Mass., and owned and published by the Radiological Society of North America, Inc.

RSNA is an association of more than 54,000 radiologists, radiation oncologists, medical physicists and related scientists promoting excellence in patient care and health care delivery through education, research and technologic innovation. The Society is based in Oak Brook, Ill.

Most Popular Now

AI Harnesses Tumor Genetics to Predict T…

In a groundbreaking study published on January 18, 2024, in Cancer Discovery, scientists at University of California San Diego School of Medicine leveraged a machine learning algorithm to tackle one...

Northern Care Alliance Deploys Digital P…

The trust's Oldham laboratory has completed technical go-live, with its Salford site also set to follow. Collectively the laboratories provide a wide range of general and specialist pathology services that...

American College of Radiology Releases J…

The American College of Radiology® (ACR®), working in close collaboration with four other radiology societies from around the world, have issued a joint statement on the development and use of...

Autonomous Synthesis Robot Uses AI to Sp…

Chemists of the University of Amsterdam (UvA) have developed an autonomous chemical synthesis robot with an integrated AI-driven machine learning unit. Dubbed 'RoboChem', the benchtop device can outperform a human...

AI in Personalized Cancer Medicine: New …

The application of AI in precision oncology has so far been largely confined to the development of new drugs and had only limited impact on the personalisation of therapies. New...

AI can Predict Brain Cancer Patients…

Artificial Intelligence (AI) can predict whether adult patients with brain cancer will survive more than eight months after receiving radiotherapy treatment. The use of the AI to successfully predict patient outcomes...

Paper Calls for Patient-First Regulation…

Ever wonder if the latest and greatest artificial intelligence (AI) tool you read about in the morning paper is going to save your life? A new study published in JAMA...

Max Planck Institute for Informatics and…

The Max Planck Institute for Informatics and Google deepen their strategic research partnership. With additional financial support from the U.S. IT company, the "Saarbrücken Research Center for Visual Computing, Interaction...

JMIR Medical Informatics Invites Submiss…

JMIR Publications has announced a new section titled, "AI Language Models in Health Care" in JMIR Medical Informatics. This leading peer-reviewed journal is indexed in PubMed and has a unique...

DMEA nova Award: Wanted - Visionary Solu…

9 - 11 April 2024, Berlin, Germany. The DMEA nova Award is being presented at DMEA 2024 for the first time. The award honours a digital health startup for an outstanding...

Could ChatGPT Help or Hurt Scientific Re…

Since its introduction to the public in November 2022, ChatGPT, an artificial intelligence system, has substantially grown in use, creating written stories, graphics, art and more with just a short...

Evaluating the Performance of AI-Based L…

A new study evaluates an artificial intelligence (AI)-based algorithm for autocontouring prior to radiotherapy in head and neck cancer. Manual contouring to pinpoint the area of treatment requires significant time...