Evidence map›Paper›PMID 37458906›Full record

ArticleLa Radiologia medica2023

Radiomics of spinal muscles: toward a radiological biomarker for allograft rejection in lung transplant.

Chiara Giraudo, Antonella Modugno, Giacomo Negro, Andrea Dell'Amore, Diego Cecchin, Raffaella Motta, Elisabetta Balestro, Annalisa Boscolo, Fiorella Calabrese, Eleonora Faccioli and 4 more

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Article in La Radiologia medica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

14 authors.

Chiara GiraudoUnit of Advanced Clinical and Translational Imaging, Department of Medicine - DIMED, University of Padova, Padua, Italy. chiara.giraudo@unipd.it.ORCID http://orcid.org/0000-0003-0924-5883
Antonella ModugnoUnit of Advanced Clinical and Translational Imaging, Department of Medicine - DIMED, University of Padova, Padua, Italy.
Giacomo NegroUnit of Advanced Clinical and Translational Imaging, Department of Medicine - DIMED, University of Padova, Padua, Italy.
Andrea Dell'AmoreThoracic Surgery Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padua, Italy.
Diego CecchinNuclear Medicine Unit, Department of Medicine - DIMED, University of Padova, Padua, Italy.
Raffaella MottaUnit of Advanced Clinical and Translational Imaging, Department of Medicine - DIMED, University of Padova, Padua, Italy.
Elisabetta BalestroRespiratory Disease Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padua, Italy.
Annalisa BoscoloAnesthesiology and Intensive Care Unit, Department of Medicine-DIMED, University of Padova, Padua, Italy.
Fiorella CalabresePathological Anatomy Section, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padua, Italy.
Eleonora FaccioliThoracic Surgery Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padua, Italy.
Paolo NavalesiAnesthesiology and Intensive Care Unit, Department of Medicine-DIMED, University of Padova, Padua, Italy.
Andrea VianelloRespiratory Pathophysiology Division, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padua, Italy.
Federico ReaThoracic Surgery Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padua, Italy.
Roberto StramareUnit of Advanced Clinical and Translational Imaging, Department of Medicine - DIMED, University of Padova, Padua, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo assess the role of muscle composition and radiomics in predicting allograft rejection in lung transplant. MATERIAL AND

methodsThe last available HRCT before surgery of lung transplant candidates referring to our tertiary center from January 2010 to February 2020 was retrospectively examined. Only scans with B30 kernel reconstructions and 1 mm slice thickness were included. One radiologist segmented the spinal muscles of each patient at the level of the 11th dorsal vertebra by an open-source software. The same software was used to extract Hu values and 72 radiomic features of first and second order. Factor analysis was applied to select highly correlating features and then their prognostic value for allograft rejection was investigated by logistic regression analysis (level of significance p < 0.05). In case of significant results, the diagnostic value of the model was computed by ROC curves.

resultsOverall 200 patients had a HRCT prior to the transplant but only 97 matched the inclusion criteria (29 women; mean age 50.4 ± 13 years old). Twenty-one patients showed allograft rejection. The following features were selected by the factor analysis: cluster prominence, Imc2, gray level non-uniformity normalized, median, kurtosis, gray level non-uniformity, and inverse variance. The radiomic-based model including also Hu demonstrated that only the feature Imc2 acts as a predictor of allograft rejection (p = 0.021). The model showed 76.6% accuracy and the Imc2 value of 0.19 demonstrated 81% sensitivity and 64.5% specificity in predicting lung transplant rejection.

conclusionThe radiomic feature Imc2 demonstrated to be a predictor of allograft rejection in lung transplant.

Indexed as

Lung TransplantationSpineAdultAllograftsBiomarkersFemaleHumansMiddle AgedMusclesRetrospective StudiesBiomarkersComputed tomographyLung transplantMuscle compositionRadiomics

Identifiers

PMID37458906
PMCPMC10474186

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