Evidence map›Paper›PMID 41314377›Full record

ArticleJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology2026

Artificial intelligence-driven longitudinal quantification of technetium pyrophosphate uptake in cardiac amyloidosis: Correlation with multimodality imaging and outcomes.

Robert Jh Miller, Aakash Shanbhag, Karan Shahi, Debra Bosley, Lyndsay Litwin, James A White, Victor Jimenez-Zepeda, Damini Dey, Daniel S Berman, Nowell M Fine and 1 more

Abstract read
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In one paragraph

Article in Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Robert Jh MillerDepartment of Cardiac Sciences, University of Calgary, Calgary AB, Canada. Electronic address: Robert.miller@ahs.ca.
Aakash ShanbhagDepartments 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.
Karan ShahiDepartment of Cardiac Sciences, University of Calgary, Calgary AB, Canada.
Debra BosleyDepartment of Cardiac Sciences, University of Calgary, Calgary AB, Canada.
Lyndsay LitwinDepartment of Cardiac Sciences, University of Calgary, Calgary AB, Canada.
James A WhiteDepartment of Cardiac Sciences, University of Calgary, Calgary AB, Canada.
Victor Jimenez-ZepedaDepartment of Cardiac Sciences, University of Calgary, Calgary AB, Canada.
Damini DeyDepartments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Daniel S BermanDepartments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Nowell M FineDepartment of Cardiac Sciences, University of Calgary, Calgary AB, Canada.
Piotr J SlomkaDepartments of Medicine (Division of Artificial Intelligence in Medicine), Imaging and Biomedical Sciences Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Funding

Patient-specific Outcome Prediction from Cardiovascular Multimodality Imaging by Artificial IntelligenceR35HL161195 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI Piotr J Slomka · 2022 to 2026
$5.0M
NHLBI NIH HHS R35 HL161195
6 · The paper itself

Abstract

backgroundTransthyretin 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 (

methodsWe included patients with a diagnosis of ATTR-CM and at least two

resultsIn total, 85 patients were included, with a median population age of 79 years (interquartile range [IQR]: 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: 1400 to 1387, P = 0.005), and extracellular volume (median: 50 to 49, P = 0.035) during a median time of 369 days (IQR: 365-516) between scans. There was a modest correlation between change in CPA and 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 an increased risk (adjusted hazard ratio: 2.31 per standard deviation increase, 95% confidence interval: 1.28-4.17, P = 0.005).

conclusionsSerial

Indexed as

Amyloid Neuropathies, FamilialAmyloidosisArtificial IntelligenceCardiomyopathiesMultimodal ImagingTechnetium Tc 99m PyrophosphateAgedAged, 80 and overEchocardiographyFemaleHumansLongitudinal StudiesMaleTechnetium Tc 99m PyrophosphateBiomarkerCardiac amyloidosisDiagnostic accuracyQuantificationTechnetium pyrophosphate

Identifiers

PMID41314377
PMCPMC13016408

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.