Evidence map›Paper›PMID 39463855›Full record

ArticleJournal of healthcare informatics research2024

A Methodology to Measure Glucose Metabolism by Quantitative Analysis of PET Images.

Patrizia Vizza, Elena Succurro, Giuseppe Pozzi, Pietro Hiram Guzzi, Giuseppe Lucio Cascini, Giuseppe Tradigo, Pierangelo Veltri

Abstract read
In one paragraph

Article in Journal of healthcare informatics research, 2024. 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. Review
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

7 authors.

Patrizia VizzaDepartment of Medical and Surgery Sciences, Magna Græcia University, Catanzaro, 88100 Italy.
Elena SuccurroDepartment of Medical and Surgery Sciences, Magna Græcia University, Catanzaro, 88100 Italy.
Giuseppe PozziDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, 20133 Italy.
Pietro Hiram GuzziDepartment of Medical and Surgery Sciences, Magna Græcia University, Catanzaro, 88100 Italy.
Giuseppe Lucio CasciniDepartment of Clinical and Experimental Medicine, Magna Græcia University, Catanzaro, 88100 Italy.
Giuseppe TradigoDepartment of Theoretical and Applied Sciences, University e-Campus, Novedrate, 22060 Italy.
Pierangelo VeltriDIMES Department, University of Calabria, Rende, 87036 Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Positron emission tomography (PET) with F-18 fluorodeoxyglucose (FDG) tracer is the standard clinical technique to measure myocardial and vessel metabolism and viability and to investigate the metabolic syndrome associated with cardiovascular diseases. The quantitative analysis of PET images allows one to study the cardiovascular physiological processes, by extracting quantitative parameters from the analysis of the tracer kinetic. Here, we propose a new methodology to quantify and evaluate the evolution of glucose metabolism inside the myocardium and the large vascular structures over time. We merge and analyze PET and CT cardiac images, extracting different volumes of interest (VOI) and performing quantitative measurements. To validate it, we apply the methodology to merge images of the aorta vessel for patients affected by metabolic syndrome. The application of the proposed approach to the use case reveals a correlation between administered drugs and metabolic syndrome, measuring the glucose metabolic rate (MRGlu) in both the myocardium and aorta. The proposed methodology can be used to evaluate some cardiovascular risk indexes of diabetic patients, too. The proposed methodology can also be deployed to analyze other application domains.

Indexed as

Glucose metabolic rate (MRGlu)Large vessel structurePET imageQuantitative analysisVolume of interest (VOI)

Identifiers

PMID39463855
PMCPMC11499506

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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.