News | June 26, 2007

Philips Tests MRI/PET Diagnostic Solution for Neurodegenerative Diseases

June 27, 2007 - The University Medical Center Hamburg-Eppendorf (UKE) and Royal Philips Electronics have developed a computer aided diagnosis system for neurodegenerative diseases to support clinicians in diagnosing the onset and type of disease as early as possible, and the tool is set to undergo clinical evaluation at UKE to fine-tune the its ability to detect and differentiate the three most common types of neurodegenerative disease – Alzheimer’s Disease, Lewy-body Dementia and Frontotemporal Dementia.

The software tool developed by Philips Research and UKE overlays anatomical images of the brain obtained from MRI scans with PET scans that display brain activity – specifically the uptake of glucose that fuels brain activity. By using advanced image processing and computer learning techniques in combination with a database of reference brain-scans, the system then analyses the images automatically and displays anomalous brain patterns. Based on these patterns, it then suggests a diagnosis. As a result, the system will help less experienced doctors to achieve the same diagnostic accuracy as highly trained specialists.

The clinical evaluation that is about to start will run the computer aided diagnostic system alongside UKE’s existing dementia diagnosis procedures with the aim of fine-tuning the system’s ability to detect and differentiate the three most common types of neurodegenerative disease – Alzheimer’s Disease, Lewy-body Dementia and Frontotemporal Dementia.

The hope is that such a system will ultimately mean a better quality of life for patients by enabling earlier prescription of drugs that delay progression of the disease, and hence delay the worst effects of dementia. It will also provide pharmaceutical companies and clinicians with a valuable tool for the development and testing of new, potentially curative drugs for neurodegenerative diseases such as Alzheimer’s.

“In the not too distant future there is going to be much greater demand for the accurate early diagnosis of neurodegenerative disease and not everyone will have access to the clinical expertise of a university hospital to obtain it,” said Dr. Ralph Buchert of the Department of Nuclear Medicine at UKE. “The availability of an automated system will help less experienced physicians to achieve the same high level of accuracy in their diagnoses.”

For more information: www.medical.philips.com

Related Content

Artificial Intelligence Performs As Well As Experienced Radiologists in Detecting Prostate Cancer
News | Artificial Intelligence | April 18, 2019
University of California Los Angeles (UCLA) researchers have developed a new artificial intelligence (AI) system to...
A smart algorithm has been trained on a neural network to recognize the appearance of breast cancer in MR images

A smart algorithm has been trained on a neural network to recognize the appearance of breast cancer in MR images. The algorithm, described at the SBI/ACR Breast Imaging Symposium, used “Deep Learning,“ a form of machine learning, which is a type of artificial intelligence. Graphic courtesy of Sarah Eskreis-Winkler, M.D.

Feature | Artificial Intelligence | April 12, 2019 | By Greg Freiherr
The use of smart algorithms has the potential to make healthcare more efficient.
Videos | RSNA | April 03, 2019
ITN Editor Dave Fornell takes a tour of some of the most interesting new medical imaging technologies displa
NIH Study of Brain Energy Patterns Provides New Insights into Alcohol Effects

NIH scientists present a new method for combining measures of brain activity (left) and glucose consumption (right) to study regional specialization and to better understand the effects of alcohol on the human brain. Image courtesy of Ehsan Shokri-Kojori, Ph.D., of NIAAA.

News | Neuro Imaging | March 22, 2019
March 22, 2019 — Assessing the patterns of energy use and neuronal activity simultaneously in the human brain improve
Book Chapter Reports on Fonar Upright MRI for Hydrocephalus Imaging

Rotary misalignment of atlas (C1) and axis (C2). Image courtesy of Scott Rosa, DC, BCAO.

News | Magnetic Resonance Imaging (MRI) | March 20, 2019
Fonar Corp. reported publication of a chapter where the physician-author-researchers utilized the Fonar Upright Multi-...
PET Scans Show Biomarkers Could Spare Some Breast Cancer Patients from Chemotherapy
News | PET Imaging | March 18, 2019
A new study positron emission tomography (PET) scans has identified a biomarker that may accurately predict which...