Evaluation of brain MRI scans with the help of artificial intelligence

Greece is just one example of a population where the proportion of the elderly is increasing, and with it the incidence of neurodegenerative diseases. Of these, Alzheimer’s disease is Most popular, which accounts for 70% of cases of neurodegenerative diseases in Greece. According to estimates published by the Alzheimer’s Association of Greece, there are currently 197,000 people suffering from the disease. This number is expected to rise to 354,000 in 2050.

Dr. Andreas Papadopoulosfirst, physician and science coordinator at Iatropolis Medical Group, a leading provider of diagnostic services near Athens, Greece, explains the important role of early diagnosis: “The likelihood of developing Alzheimer’s disease may indicate is 1% to 2% at age 65. But then it doubles every five years. Existing drugs cannot reverse the degenerative process; they can only slow it down. This is why it is so important to get the right diagnosis in the early stages – when mild cognitive disturbances first appear – and filter out Alzheimer’s patients.2. ”

Diseases such as Alzheimer’s or other neurodegenerative diseases are characterized by a very slow progression, which makes it difficult to recognize and quantify pathological changes on brain MRI images in the early stages. When evaluating scans, some radiologists describe the process as one of “guess,” since visual changes in the brain’s highly complex anatomical structure are not always present. can be seen well with the human eye. This is where technical innovations such as artificial intelligence can aid in the interpretation of clinical images.

One of such tools is AI-Rad Companion Brain MR3. Part of the family of AI-based, decision support solutions for imaging, AI-Rad Companion Brain MR is brain volumetric software that provides automated volumetric quantification of other brain segments together. “It can segment them from each other: it isolates the hippocampus and lobes of the brain and quantifies white matter and gray matter volume for each individual segment.” Dr. Papadopoulos said. In total, it has the ability to segment, measure, and highlight more than 40 brain regions.

Calculating volumetric properties manually can be an extremely time-consuming and labor-intensive task. “More importantly, it also involves a level of precision that humans simply cannot achieve.” Dr. Papadopoulos said. Papadopoulos has always been an early adopter and has welcomed technological innovations in imaging throughout his career. This AI-powered tool means he can now also compare quantifiers with normative data from a healthy population. And it’s not all about automation: the software displays the data in a structured report and generates a marked deviation map based on the user’s settings. This allows the user to also monitor volume changes manually with all key data prepared automatically in advance.

The opportunity to more accurately observe and evaluate volumetric changes in the brain encouraged Papadopoulos, considering how important it is to detect neurodegenerative diseases early. “In the early stages, the change in volume is small,” he explains. In the hippocampus, for example, there is a volume reduction of 10% to 15% that is difficult to detect with the naked eye. But the objective calculations provided by the system can prove a big help. ”

The aim of AI is to significantly reduce the burden on physicians and ultimately save time when optimally embedded in the workflow. An extremely valuable role for this particular AI-powered post-processing tool is that it can visualize deviations of various structures that might otherwise be difficult to discern with the naked eye. Papadopoulos has found that the biggest advantage in his work is “the objective framework that the AI-Rad Companion Brain MR provides on which he can base his subjective assessment during the test.”

Companion AI-Rad4 from Siemens Healthineers assist clinicians in their day-to-day diagnostic decision making. To maintain a continuous stream of value, our AI-powered tools include regular software updates and upgrades that are deployed to customers via the cloud. Customers can decide whether they want to integrate a fully cloud-based approach into their work environment to take advantage of all the benefits of the cloud, or a hybrid approach that allows them to process data. image data in their own hospital IT settings.

The upcoming software version of AI-Rad Companion Brain MR will contain new algorithms capable of segmenting, quantifying, and visualizing white matter (WMH) intensities. Together with the McDonald criteria, the WHM report supports the assessment of multiple sclerosis (MS).

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