Artificial Intelligence-Driven Longitudinal Quantification of Technetium Pyrophosphate Uptake in Cardiac Amyloidosis: Correlation with Multimodality Imaging and Outcomes.
Authors
Affiliations (4)
Affiliations (4)
- Department of Cardiac Sciences, University of Calgary, Calgary AB, Canada. Electronic address: [email protected].
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA; Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA.
- Department of Cardiac Sciences, University of Calgary, Calgary AB, Canada.
- Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Abstract
Transthyretin cardiac amyloidosis (ATTR-CM) is an increasingly recognized cause of heart failure (HF) in older adults. Several therapies for ATTR-CM are now available, with more currently in development. As such, there is an increasing need for methods to assess response to therapy. We evaluated the associations between serial 99m-Technetium pyrophosphate (<sup>99m</sup>Tc-PYP) deep learning measurements with changes in other imaging parameters and clinical outcomes. We included patients with a diagnosis of ATTR-CM and at least two <sup>99m</sup>Tc-PYP studies followed through the Amyloidosis Program of Calgary. Patients underwent laboratory testing, echocardiography, and cardiovascular magnetic resonance (CMR) unless contraindications were present. <sup>99m</sup>Tc-PYP images were quantified using our previously developed deep learning methodology including assessment of cardiac pyrophosphate activity (CPA) and volume of involvement (VOI). In total 85 patients were included, with median population age 79 (interquartile range 72 - 84) and 76 (89%) male patients. In patients on therapy, there was a reduction in VOI (median 100 to 51, p<0.001), CPA (median 165 to 81, p<0.001), native T1 (median 1399 to 1380, p=0.029), and extracellular volume (median 52 to 50, p=0.031) during a median time of 369 days (interquartile range 365 - 516) between scans. There was a modest correlation between change in CPA with change in native T1 (ρ=0.376, p=0.009). After adjusting for age, treatment, and CPA at follow-up, an increase in CPA during follow-up was also associated with increased risk (adjusted HR 2.31 per SD increase, 95% CI 1.28 - 4.17, p=0.005). Serial <sup>99m</sup>Tc-PYP quantitation has modest correlations with other measures of disease burden including native T1. Changes in these measures were associated with risk of cardiovascular death or HF hospitalization, suggesting that the serial measurements may be clinically meaningful surrogate endpoints.