We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




Earlier Alzheimer's Diagnosis Using Automated MRI Technique

By MedImaging staff writers
Posted on 28 Jul 2008
Print article
Image: Color-enhanced coronal MRI image of the brain, showing the regions of the brain most severely affected in Alzheimer’s disease (Photo courtesy of Living Art Enterprises).
Image: Color-enhanced coronal MRI image of the brain, showing the regions of the brain most severely affected in Alzheimer’s disease (Photo courtesy of Living Art Enterprises).
An automated system for measuring brain tissue combined with magnetic resonance imaging (MRI) can help clinicians more effectively diagnose Alzheimer's disease (AD) at an earlier stage, according to new research.

In AD, nerve cell death and tissue loss cause all areas of the brain, particularly the hippocampus region, to shrink. Utilizing MRI with high spatial resolution allows radiologists to visualize slight anatomic changes in the brain that signal atrophy, or shrinkage. But the conventional practice for measuring brain tissue volume with MRI, called segmentation, is a complicated, lengthy process, according to the researchers, who published their study in the July 2008, issue of the journal Radiology.

"Visually evaluating the atrophy of the hippocampus is not only difficult and prone to subjectivity, it is time-consuming,” explained the study's lead author, Olivier Colliot, Ph.D, from the Cognitive Neuroscience and Brain Imaging Laboratory (Paris, France). "As a result, it hasn't become part of clinical routine.”

In the study, the researchers used an automated segmentation process with computer software developed in their laboratory by Marie Chupin, Ph.D., to measure the volume of the hippocampus in 25 patients with Alzheimer's disease, 24 patients with mild cognitive impairment, and 25 healthy older adults. The MRI volume measurements were then compared with those reported in studies of similar patient groups using the visual, or manual, segmentation method.

The researchers found a significant reduction in hippocampal volume in both the AD and cognitively impaired patients when compared to the healthy adults. Alzheimer's patients and those with mild cognitive impairment had a median volume loss in the hippocampus of 32% and 19%, respectively. Studies utilizing manual segmentation methods have reported similar results. "The performance of automated segmentation is not only similar to that of the manual method, it is much faster,” Dr. Colliot said. "It can be performed within a few minutes versus an hour.”

One of the goals of modern neuroimaging is to help in the early and accurate diagnosis of Alzheimer's disease, which can be challenging. When the disease is diagnosed early, drug treatment can help improve or stabilize patient symptoms. "Combined with other clinical and neuropsychological evaluations, automated segmentation of the hippocampus on MR images can contribute to a more accurate diagnosis of Alzheimer's disease,” Dr. Colliot said.


Related Links:
Cognitive Neuroscience and Brain Imaging Laboratory
Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
New
Ultrasound Table
Ergonomic Advantage (EA) Line
Silver Member
Mobile X-Ray Barrier
Lead Acrylic Mobile X-Ray Barriers
New
Digital Radiography Generator
meX+20BT lite

Print article
Radcal

Channels

Nuclear Medicine

view channel
Image: The new SPECT/CT technique demonstrated impressive biomarker identification (Journal of Nuclear Medicine: doi.org/10.2967/jnumed.123.267189)

New SPECT/CT Technique Could Change Imaging Practices and Increase Patient Access

The development of lead-212 (212Pb)-PSMA–based targeted alpha therapy (TAT) is garnering significant interest in treating patients with metastatic castration-resistant prostate cancer. The imaging of 212Pb,... Read more

General/Advanced Imaging

view channel
Image: The Tyche machine-learning model could help capture crucial information. (Photo courtesy of 123RF)

New AI Method Captures Uncertainty in Medical Images

In the field of biomedicine, segmentation is the process of annotating pixels from an important structure in medical images, such as organs or cells. Artificial Intelligence (AI) models are utilized to... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.