image: Figure 1. Cerebral metabolic patterns of Alzheimer's Disease (AD, top row), Limbic-Predominant Age-Related TDP-43 Encephalopathy (LATE, middle row), and Dementia with Lewy Bodies (DLB, bottom row). The non-AD group was comprised of patients with LATE and DLB cerebral metabolic patterns. After 1 year of anti-amyloid therapy, the AD group's MoCA significantly increased by 1.75 0.96 points (p=0.035) while the non-AD group's MoCA significantly decreased by 5.00 2.71 points (p=0.035). There is a significant difference in the change in MoCA scores between AD and non-AD groups (p = 0.01).
Credit: Image courtesy of SNMMI.
Los Angeles -- A specific pattern of brain metabolism visualized with PET imaging can predict which patients are most likely to benefit from Alzheimer's disease therapy. In a retrospective study of patients who received Alzheimer's treatments, those with the identified pattern experienced stabilized cognitive performance, while patients with other patterns had significant cognitive decline. This study was presented at the Society of Nuclear Medicine and Molecular Imaging (SNMMI) 2026 Annual Meeting, where it received top recognition as the Abstract of the Year.
Each year, SNMMI chooses an abstract that best exemplifies the most promising advances in the field of nuclear medicine and molecular imaging. This year, the SNMMI Henry N. Wagner, Jr., Abstract of the Year was chosen from nearly 1,500 abstracts submitted to the meeting and voted on by reviewers and the society leadership.
The hallmark of Alzheimer's disease is amyloid plaques that accumulate in the brain. Two anti-amyloid therapies that target these plaques were recently approved by the U.S. Food and Drug Administration (FDA). While these treatments have been effective on the whole, there remains substantial variability in individual success rates.
"Numerous large-scale prior studies have shown that many people who meet the requirements for the clinical diagnosis of Alzheimer's disease as the patients for whom anti-amyloid therapies are currently being prescribed do are actually found to have other diagnoses underlying their cognitive impairment after autopsy or long-term follow-up," said Amanda Rose Nguyen, DO, MS, a clinical fellow in nuclear medicine at the David Geffen School of Medicine at the University of California, Los Angeles. "This could account for the variability in the success rates of these therapies."
Knowing the 18F-FDG PET scans can diagnose Alzheimer's disease with high accuracy even in its earliest stages, researchers assessed the relationship of brain metabolic data from PET scans to prescription practices and clinical outcomes in patients receiving anti-amyloid therapy.
The study examined a consecutive series of 124 patients whose cases were reviewed by a university committee for consideration of receiving amyloid immunotherapy. Brain 18F-FDG PET data, treatment decisions, and clinical outcomes were analyzed for all patients who underwent treatment for at least one year with respect to cognitive assessment scores before and after treatment. Brain metabolism patterns on PET were categorized as being consistent or not consistent with Alzheimer's disease, and the corresponding subsequent changes in cognitive assessment scores were calculated.
The brain metabolism patterns were representative of Alzheimer's disease, Lewy body disease, Limbic-predominant Age-related TDP-43 Encephalopathy-type pathology, or frontotemporal lobar degeneration. Those with Alzheimer's disease metabolism patterns experienced an increase in their cognitive performance scores, while all other subjects suffered significant cognitive decline as measured by their cognitive assessments.
"This work demonstrates that 18F-FDG PET is an important tool in the diagnosis of dementia," said Nguyen. "Armed with powerful brain metabolic data, physicians can provide more personalized care, prescribing anti-amyloid therapy to individuals who are most likely to benefit from it, and conversely sparing others from ineffective treatments, potential harmful adverse effects, and unnecessary expense."
Nguyen anticipates larger, higher-powered analyses from an expanded sample by year-end, which will better define the predictive value and potential role of brain metabolism patterns. In the meantime, she recommends that physicians gather comprehensive neuroimaging data on an individual patient basis to help guide treatment decisions.
Abstract 262363. "Relationship between Prospective Assessment of Regional Cerebral Metabolism and Subsequent Response to Amyloid-Directed Therapy for Cognitive Decline," Amanda Rose Nguyen and Daniel H. Silverman, University of California, Los Angeles.
Link to Abstract
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All 2026 SNMMI Annual Meeting abstracts can be found online.
About the Society of Nuclear Medicine and Molecular Imaging
The Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and medical organization dedicated to advancing nuclear medicine and molecular imaging vital elements of precision medicine that allow diagnosis and treatment to be tailored to individual patients in order to achieve the best possible outcomes.
SNMMI's members set the standard for molecular imaging and nuclear medicine practice by creating guidelines, sharing information through journals and meetings and leading advocacy on key issues that affect molecular imaging and therapy research and practice. For more information, visit www.snmmi.org.