Evidence map›Paper›PMID 39410653›Full record

ReviewDiagnostics (Basel, Switzerland)2024

Novel Insights into Non-Invasive Diagnostic Techniques for Cardiac Amyloidosis: A Critical Review.

Marco Maria Dicorato, Paolo Basile, Giuseppe Muscogiuri, Maria Cristina Carella, Maria Ludovica Naccarati, Ilaria Dentamaro, Marco Guglielmo, Andrea Baggiano, Saima Mushtaq, Laura Fusini and 4 more

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. Review
  8. Review
  9. DIRECT MEDICAL IMAGE TO SIMULATION USING AUTO-SEGMENTATION AND POINT CLOUD-BASED CFD.Advances in computational science and engineering · 2025
    Article
  10. 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

14 authors.

Marco Maria DicoratoInterdisciplinary Department of Medicine, University of Bari "Aldo Moro", Polyclinic University Hospital, 70124 Bari, Italy.ORCID 0009-0008-4865-2522
Paolo BasileInterdisciplinary Department of Medicine, University of Bari "Aldo Moro", Polyclinic University Hospital, 70124 Bari, Italy.ORCID 0000-0002-2327-7585
Giuseppe MuscogiuriDepartment of Radiology, IRCCS Istituto Auxologico Italiano, San Luca Hospital, 20149 Milan, Italy.
Maria Cristina CarellaInterdisciplinary Department of Medicine, University of Bari "Aldo Moro", Polyclinic University Hospital, 70124 Bari, Italy.ORCID 0000-0002-5094-2237
Maria Ludovica NaccaratiInterdisciplinary Department of Medicine, University of Bari "Aldo Moro", Polyclinic University Hospital, 70124 Bari, Italy.
Ilaria DentamaroInterdisciplinary Department of Medicine, University of Bari "Aldo Moro", Polyclinic University Hospital, 70124 Bari, Italy.
Marco GuglielmoDepartment of Cardiology, Division of Heart and Lungs, Utrecht University, Utrecht University Medical Center, 3584 Utrecht, The Netherlands.ORCID 0000-0003-1718-9949
Andrea BaggianoDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy.ORCID 0000-0002-8261-4529
Saima MushtaqDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy.
Laura FusiniDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy.ORCID 0000-0003-0309-6231
Gianluca PontoneDepartment of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino, IRCCS, 20138 Milan, Italy.
Cinzia ForleoInterdisciplinary Department of Medicine, University of Bari "Aldo Moro", Polyclinic University Hospital, 70124 Bari, Italy.ORCID 0000-0002-9452-4037
Marco Matteo CicconeInterdisciplinary Department of Medicine, University of Bari "Aldo Moro", Polyclinic University Hospital, 70124 Bari, Italy.
Andrea Igoren GuaricciInterdisciplinary Department of Medicine, University of Bari "Aldo Moro", Polyclinic University Hospital, 70124 Bari, Italy.ORCID 0000-0001-7133-4401

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiac amyloidosis (CA) is a cardiac storage disease caused by the progressive extracellular deposition of misfolded proteins in the myocardium. Despite the increasing interest in this pathology, it remains an underdiagnosed condition. Non-invasive diagnostic techniques play a central role in the suspicion and detection of CA, also thanks to the continuous scientific and technological advances in these tools. The 12-lead electrocardiography is an inexpensive and reproducible test with a diagnostic accuracy that, in some cases, exceeds that of imaging techniques, as recent studies have shown. Echocardiography is the first-line imaging modality, although none of its parameters are pathognomonic. According to the 2023 ESC Guidelines, a left ventricular wall thickness ≥ 12 mm is mandatory for the suspicion of CA, making this technique crucial. Cardiac magnetic resonance provides high-resolution images associated with tissue characterization. The use of contrast and non-contrast sequences enhances the diagnostic power of this imaging modality. Nuclear imaging techniques, including bone scintigraphy and positron emission tomography, allow the detection of amyloid deposition in the heart, and their role is also central in assessing the prognosis and response to therapy. The role of computed tomography was recently evaluated by several studies, above in population affected by aortic stenosis undergoing transcatheter aortic valve replacement, with promising results. Finally, machine learning and artificial intelligence-derived algorithms are gaining ground in this scenario and provide the basis for future research. Understanding the new insights into non-invasive diagnostic techniques is critical to better diagnose and manage patients with CA and improve their survival.

Indexed as

artificial intelligencecardiac amyloidosiscardiac imaging techniquescardiomyopathiesechocardiographymagnetic resonance imagingradionuclide imaging

Identifiers

PMID39410653
PMCPMC11475987

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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.