Impact of disease-modifying therapy on [99mTc]Tc-DPD SPECT/CT markers in transthyretin cardiac amyloidosis enabled by artificial intelligence.
Journal:
European journal of nuclear medicine and molecular imaging
Published Date:
Nov 29, 2025
Abstract
PURPOSE: Transthyretin cardiac amyloidosis (ATTR-CM) is a progressive, underdiagnosed disease with high morbidity and mortality. While disease-modifying therapies (DMTs) slow progression, early treatment response markers remain scarce. This study assessed AI-quantified thoracic [99mTc]Tc-DPD SPECT/CT markers as potential non-invasive biomarkers for monitoring therapeutic efficacy. METHODS: This longitudinal study included ATTR-CM patients receiving DMTs (transthyretin stabilizers, RNA interference, or antisense oligonucleotides). [99mTc]Tc-DPD SPECT/CT scans were acquired at baseline and after treatment (median interval 9 months, IQR 7-10). AI-driven segmentation and quantification extracted 26 markers (SUV metrics, retention index, amyloid-affected volume, and amyloid activity). Functional, clinical, and blood parameters, as well as clinical outcomes, were evaluated for their association with changes in imaging markers. RESULTS: In 45 patients (37 ATTRwt-CM, 8 ATTRv-CM), 65% (17/26) of AI-extracted SPECT/CT markers significantly decreased after treatment (all p < 0.001), including SUVmax reductions in the left ventricle (18.6 to 14.1) and myocardium (19.5 to 15.5). None of the markers significantly increased (p > 0.05). Six of the imaging markers, most notably SUVpeak (p = 0.007) of the myocardium and amyloid activity of the left ventricle (p = 0.009), were associated with reductions in NT-proBNP. Lower values for three markers, including amyloid activity of the myocardium, retention index, and SUVmean of the left atrium (all p = 0.016), were associated with improved NYHA class. An increase in amyloid-affected volume of the right ventricle (HR 3.19, 95% CI [1.29; 7.86], p = 0.005) and a decrease in right ventricular SUVmean (adjHR 0.15 95% CI [0.02;1.10], logrank p = 0.030) were associated with death or heart failure-associated hospitalization before and after multivariate adjustment. AI-driven analysis extracted imaging markers substantially faster and eliminated inter-rater variability. CONCLUSION: AI-driven [99mTc]Tc-DPD SPECT/CT analysis effectively detects treatment-induced reductions in cardiac amyloid burden, offering a non-invasive biomarker for early response assessment in ATTR-CM. AI-enabled imaging markers enhance reproducibility and efficiency, providing valuable support for personalized treatment strategies as new therapeutic options for ATTR-CM become available.
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