Unlocking the Future of Alzheimer's Care

Sep 21, 2023

Insights from leading clinicians on digital health technologies in 2023

2023 has been an exciting year for developments in the care of patients with Alzheimer’s disease (AD). With Leqembi obtaining market approval in the US, and other drugs in the development pipeline, there is hope for people with AD that effective treatments may soon be available to them. Significant challenges remain, however, specifically pertaining to the diagnosis, maintenance, and monitoring of people with AD. Technological advances have helped to fill in these gaps to an extent, but there is still work to be done in order to provide optimal care for people with AD. 

We asked three leading clinicians; Dr. Ana Franceschi (Zucker School of Medicine at Hofstra/Northwell, NY, USA), Dr. Giovanni Frisoni (University of Geneva, Switzerland), and Dr. Marwan Sabbagh (Barrow Neurological Institute, AZ, USA), about their thoughts on some of the most pressing challenges clinicians face in the care of AD today, and what potential they see for digital health technologies in alleviating some of those issues in the future. 

The need for timely diagnosis and access to care

With disease-modifying treatments (DMTs) becoming available, there is an increased urgency for a timely differential diagnosis to identify candidate patients for treatment. Dr. Sabbagh explains: “The biggest challenges that neurologists face in the dementia space are establishing workflows to screen patients suited for treatment with anti-amyloid monoclonal antibodies (mABs). This concept is so new and begins the transformation of AD to chronic disease.” Dr. Frisoni continues, stating that “this includes the challenges of providing fair, safe and sustainable access to mABs”. To find and reach the right patients at the right time and to provide optimal, equitable care to all patients with AD, a transformation of the current workflow is of vital importance. This includes finding optimal biomarkers for early diagnosis, addressing potential risk factors and co-pathologies, as well as ensuring access to care in more rural areas.

Dr. Sabbagh, Dr. Frisoni and Dr. Franceschi recognized the potential for digital health technologies to contribute to optimizations of the care pathway. Dr. Frisoni describes that “digital solutions for optimizing and harmonizing history taking and cognitive assessment, for improving readouts of MR and PET imaging markers, as well as for ARIA screening, have the potential to help our systems adapt to these new challenges.” AI-related quantification in neuroimaging aims to optimize and harmonize workflow and interpretation, improve readouts from images, and help to identify early markers of disease activity, thereby securing optimally-timed care for AD patients. Dr. Sabbagh further expresses the urgency of implementing such changes and potential technologies to the workflow: “The process of reengineering the care pathway from a diagnostic to a therapeutic pathway needs to take place immediately so that our healthcare systems are ready as soon as possible to provide optimal care to our patients.”

Dealing with increased numbers of scans

While the approval of a drug for AD brings immense excitement, it also brings fresh logistical challenges for our healthcare systems. “From a neuroimaging perspective, and in light of the recent regulatory approval of mABs, there is concern about the potential influx of a large number of scans, both structural (MRI for safety monitoring) and molecular/functional (amyloid PET for detection of cortical beta-amyloid burden; tau-PET for risk stratification; FDG-PET for neurodegeneration). We need to be ready with appropriately trained neuroradiologists and nuclear medicine physicians, in order to treat AD patients in an effective, timely, and compassionate manner” says Dr. Franceschi.

As the population ages, an increasing number of individuals will require screening for AD. Meanwhile, the Leqembi label recommends at least 3 safety MRIs in the first year, prior to the 5th, 7th, and 14th infusions. It is anticipated that between these two factors, there will be a sharp increase in the number of AD-related MRIs conducted per year. This places an enormous strain on our already overloaded healthcare systems. 

“Using digital technology for the monitoring of amyloid-related imaging abnormalities (ARIA) and to improve readouts of MR and PET imaging can facilitate faster and more detailed assessments” describes Dr. Frisoni. Dr. Franceschi continues “Digital health technologies, and in particular computer-aided detection of ARIA, AI-related MRI brain quantification, and (semi)quantitative PET analyses have the potential to serve as invaluable tools in clinical practice, particularly by assisting novice readers and trainees, thereby building reader confidence.”

ARIA detection

The vital need for reliable, objective detection of ARIA was addressed by all three experts. These side effects can be subtle and difficult to detect. Dr. Frisoni addresses the importance of ARIA reading to guarantee safe usage of mABs, and believes that AI technology for ARIA quantification can support more accurate and detailed assessments in clinical routine. Dr. Franceschi highlights how such technology could reduce the gap between experts and novice readers. Dr. Sabbagh believes that such a tool is especially important for the detection of edema (ARIA-E), as in his experience, those are the side effects most missed in readings without software assistance. He believes that if such a tool would be able to identify the severity of the ARIA, it has the potential to greatly improve clinical decision-making. The need for ARIA assessment also has a significant contribution to the increased burden on health care practitioners and in particular radiology, as described by Dr. Franceschi. All three experts recognize that AI tools for ARIA detection have the potential to reduce the workload of clinicians, and should be well integrated in the clinical workflow. 

In summary, the prospect of having DMTs available for AD has highlighted the need to revolutionize the care pathway, in particular in relation to diagnosis and access to care, safety monitoring and the corresponding increased workflow for healthcare practitioners.  Digital health technologies, with a central role for AI-driven image quantification, can fill this gap, by making it easier to identify and monitor markers of disease and potential side effects, supporting HCPs with optimal clinical decision-making in a time-efficient way. Integration of such solutions to optimize diagnostic and monitoring workflow, might as such greatly improve outcomes for people with AD.