Greece is just one example of a population where the proportion of older people is expanding and with it the incidence of neurodegenerative diseases. Of these, Alzheimer’s disease is the most common, accounting for 70% of cases of neurodegenerative diseases in Greece. According to estimates published by the Greek Alzheimer’s Society, 197,000 people are currently suffering from the disease. That number is expected to increase to 354,000 by 2050.
Dr. Andreas Papadopoulos1a physician and scientific coordinator at Iatropolis Medical Group, a leading diagnostic provider near Athens, Greece, explains the key role of early diagnosis: “The likelihood of developing Alzheimer’s can be only 1% to 2% in 65. But then it doubles, every five years Existing drugs can’t reverse the course of degeneration, they can only slow it down, so it’s crucial to make the correct diagnosis in the early stages — when the first mild cognitive disorder appears. – and filter Alzheimer’s patients.2. ”
Diseases such as Alzheimer’s or other neurodegenerative pathologies typically have a very slow progression, making it difficult to recognize and quantify pathological changes in brain MRI images at an early stage. When evaluating scans, some radiologists describe the process as an “estimate,” as visual changes in the highly complex anatomy of the brain are not always possible to observe well with the human eye. This is where technical innovations like artificial intelligence can offer support in the interpretation of clinical images.
One such tool is the AI-Rad Companion Brain MR3. Part of a family of AI-based imaging decision support solutions, AI-Rad Companion Brain MR is a brain volumetric software that provides automatic volumetric quantification of different brain segments. “It is able to segment them with each other: it isolates the hippocampus and the lobes of the brain and quantifies the volumes of white matter and gray matter for each segment individually.” says Dr. Papadopoulos. In total, it has the ability to segment, measure volumes, and highlight more than 40 brain regions.
Manually calculating volumetric properties can be an extremely laborious and time-consuming task. “More importantly, it also involves an accurate degree of observation that humans are simply not able to achieve.” says Dr. Papadopoulos. Papadopoulos has always been one of the first adopters and has embraced technological innovations in imaging throughout his career. This AI-driven tool means you can now also compare quantifications with normative data from a healthy population. And it’s not just about automation – the software displays the data in a structured report and generates a prominent map of deviations based on user settings. This allows the user to also control volumetric changes manually with all key data automatically prepared in advance.
Opportunities for more accurate observation and assessment of volumetric changes in the brain encourage Papadopoulos when considering the importance of early detection of neurodegenerative diseases. He explains: “In the early stages, the volumetric changes are small. In the hippocampus, for example, there is a reduction in volume from 10% to 15%, which is very difficult for the eye to detect. But the objective calculations provided by the system could be very helpful. “
The goal of AI is to relieve physicians of a considerable burden and ultimately save time when it is optimally integrated into the workflow. An extremely valuable role for this AI-driven post-processing tool is that it can visualize a deviation from different structures that can be difficult to identify with the naked eye. Papadopoulos already acknowledges that the biggest advantage of his work is “the objective framework provided by AI-Rad Companion Brain MR on which he can base his subjective assessment during an examination.”
AI-Rad Companion4 of Siemens Healthineers supports physicians in their daily diagnostic decision-making routine. To maintain a continuous value stream, our AI-based tools include periodic updates and software updates that are deployed to customers through the cloud. Customers can decide whether to integrate a fully cloud-based approach into their work environment to take full advantage of the cloud or a hybrid approach that allows them to process image data within their own in-hospital computing configuration.
The next version of the AI-Rad Companion Brain MR software will contain new algorithms capable of segmenting, quantifying, and visualizing white matter hyperintensities (WMH). Along with McDonald’s criteria, WHM notification helps assess multiple sclerosis (MS).