Evidence map›Paper›PMID 40108628›Full record

ArticleOrphanet journal of rare diseases2025

Texture analysis of cardiovascular MRI native T1 mapping in patients with Duchenne muscular dystrophy.

Mary Luz Mojica-Pisciotti, Tomáš Holeček, Věra Feitová, Lukáš Opatřil, Roman Panovský

Abstract read
In one paragraph

Article in Orphanet journal of rare diseases, 2025. 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

5 authors.

Mary Luz Mojica-PisciottiInternational Clinical Research Center, St. Anne's University Hospital, Pekařská 53, 60200, Brno, Czech Republic.ORCID http://orcid.org/0000-0002-9827-1006
Tomáš HolečekInternational Clinical Research Center and Department of Medical Imaging, St. Anne's University Hospital, Faculty of Medicine, Masaryk University, Pekařská 53, Brno, 602 00, Czech Republic. tomas.holecek@fnusa.cz.ORCID http://orcid.org/0000-0001-8805-668X
Věra FeitováInternational Clinical Research Center and Department of Medical Imaging, St. Anne's University Hospital, Pekařská 53, 60200, Brno, Czech Republic.ORCID http://orcid.org/0000-0002-6789-6687
Lukáš OpatřilInternational Clinical Research Center and 1st Department of Internal Medicine/Cardioangiology, St. Anne's University Hospital, and Faculty of Medicine, Masaryk University, Pekařská 53, 60200, Brno, Czech Republic.ORCID http://orcid.org/0000-0002-5504-7370
Roman PanovskýInternational Clinical Research Center and 1st Department of Internal Medicine/Cardioangiology, St. Anne's University Hospital, and Faculty of Medicine, Masaryk University, Pekařská 53, 60200, Brno, Czech Republic.ORCID http://orcid.org/0000-0001-8489-132X

Funding

Lékařská fakulta, Masarykova univerzita MUNI/A/1624/2023Programme EXCELES LX22NPO5104
6 · The paper itself

Abstract

backgroundDuchenne muscular dystrophy (DMD) patients are monitored periodically for cardiac involvement, including cardiac MRI with gadolinium-based contrast agents (GBCA). Texture analysis (TA) offers an alternative approach to assess late gadolinium enhancement (LGE) without relying on GBCA administration, impacting DMD patients' care. The study aimed to evaluate the prognostic value of selected TA features in the LGE assessment of DMD patients.

resultsWe developed a pipeline to extract TA features of native T1 parametric mapping and evaluated their prognostic value in assessing LGE in DMD patients. For this evaluation, five independent TA features were selected using Boruta to identify relevant features based on their importance, least absolute shrinkage and selection operator (LASSO) to reduce the number of features, and hierarchical clustering to target multicollinearity and identify independent features. Afterward, logistic regression was used to determine the features with better discrimination ability. The independent feature inverse difference moment normalized (IDMN), which measures the pixel values homogeneity in the myocardium, achieved the highest accuracy in classifying LGE (0.857 (0.572-0.982)) and also was significantly associated with changes in the likelihood of LGE in a subgroup of patients with three yearly examinations (estimate: 23.35 (8.7), p-value = 0.008). Data are presented as mean (SD) or median (IQR) for normally and non-normally distributed continuous variables and numbers (percentages) for categorical ones. Variables were compared with the Welch t-test, Wilcoxon rank-sum, and Chi-square tests. A P-value < 0.05 was considered statistically significant.

conclusionIDMN leverages the information native T1 parametric mapping provides, as it can detect changes in the pixel values of LGE images of DMD patients that may reflect myocardial alterations, serving as a supporting tool to reduce GBCA use in their cardiac MRI examinations.

Indexed as

Magnetic Resonance ImagingMuscular Dystrophy, DuchenneAdolescentChildContrast MediaGadoliniumHumansMaleContrast MediaGadoliniumCardiac MRIDuchenne muscular dystrophyRadiomicsTexture analysis

Identifiers

PMID40108628
PMCPMC11924673

What OpenQuestion holds

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LicenceCC BY
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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.