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Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography

AIM: The current proof-of-concept study investigates the value of radiomic features from normal 13N-ammonia positron emission tomography (PET) myocardial retention images to identify patients with reduced global myocardial flow reserve (MFR). METHODS: Data from 100 patients with normal retention 13N...

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Autores principales: Degtiarova, Ganna, Garefa, Chrysoula, Boehm, Reto, Ciancone, Domenico, Sepulcri, Daniel, Gebhard, Catherine, Giannopoulos, Andreas A., Pazhenkottil, Aju P., Kaufmann, Philipp A., Buechel, Ronny R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10371953/
https://www.ncbi.nlm.nih.gov/pubmed/36600174
http://dx.doi.org/10.1007/s12350-022-03179-y
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author Degtiarova, Ganna
Garefa, Chrysoula
Boehm, Reto
Ciancone, Domenico
Sepulcri, Daniel
Gebhard, Catherine
Giannopoulos, Andreas A.
Pazhenkottil, Aju P.
Kaufmann, Philipp A.
Buechel, Ronny R.
author_facet Degtiarova, Ganna
Garefa, Chrysoula
Boehm, Reto
Ciancone, Domenico
Sepulcri, Daniel
Gebhard, Catherine
Giannopoulos, Andreas A.
Pazhenkottil, Aju P.
Kaufmann, Philipp A.
Buechel, Ronny R.
author_sort Degtiarova, Ganna
collection PubMed
description AIM: The current proof-of-concept study investigates the value of radiomic features from normal 13N-ammonia positron emission tomography (PET) myocardial retention images to identify patients with reduced global myocardial flow reserve (MFR). METHODS: Data from 100 patients with normal retention 13N-ammonia PET scans were divided into two groups, according to global MFR (i.e., < 2 and ≥ 2), as derived from quantitative PET analysis. We extracted radiomic features from retention images at each of five different gray-level (GL) discretization (8, 16, 32, 64, and 128 bins). Outcome independent and dependent feature selection and subsequent univariate and multivariate analyses was performed to identify image features predicting reduced global MFR. RESULTS: A total of 475 radiomic features were extracted per patient. Outcome independent and dependent feature selection resulted in a remainder of 35 features. Discretization at 16 bins (GL16) yielded the highest number of significant predictors of reduced MFR and was chosen for the final analysis. GLRLM_GLNU was the most robust parameter and at a cut-off of 948 yielded an accuracy, sensitivity, specificity, negative and positive predictive value of 67%, 74%, 58%, 64%, and 69%, respectively, to detect diffusely impaired myocardial perfusion. CONCLUSION: A single radiomic feature (GLRLM_GLNU) extracted from visually normal 13N-ammonia PET retention images independently predicts reduced global MFR with moderate accuracy. This concept could potentially be applied to other myocardial perfusion imaging modalities based purely on relative distribution patterns to allow for better detection of diffuse disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12350-022-03179-y.
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spelling pubmed-103719532023-07-28 Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography Degtiarova, Ganna Garefa, Chrysoula Boehm, Reto Ciancone, Domenico Sepulcri, Daniel Gebhard, Catherine Giannopoulos, Andreas A. Pazhenkottil, Aju P. Kaufmann, Philipp A. Buechel, Ronny R. J Nucl Cardiol Original Article AIM: The current proof-of-concept study investigates the value of radiomic features from normal 13N-ammonia positron emission tomography (PET) myocardial retention images to identify patients with reduced global myocardial flow reserve (MFR). METHODS: Data from 100 patients with normal retention 13N-ammonia PET scans were divided into two groups, according to global MFR (i.e., < 2 and ≥ 2), as derived from quantitative PET analysis. We extracted radiomic features from retention images at each of five different gray-level (GL) discretization (8, 16, 32, 64, and 128 bins). Outcome independent and dependent feature selection and subsequent univariate and multivariate analyses was performed to identify image features predicting reduced global MFR. RESULTS: A total of 475 radiomic features were extracted per patient. Outcome independent and dependent feature selection resulted in a remainder of 35 features. Discretization at 16 bins (GL16) yielded the highest number of significant predictors of reduced MFR and was chosen for the final analysis. GLRLM_GLNU was the most robust parameter and at a cut-off of 948 yielded an accuracy, sensitivity, specificity, negative and positive predictive value of 67%, 74%, 58%, 64%, and 69%, respectively, to detect diffusely impaired myocardial perfusion. CONCLUSION: A single radiomic feature (GLRLM_GLNU) extracted from visually normal 13N-ammonia PET retention images independently predicts reduced global MFR with moderate accuracy. This concept could potentially be applied to other myocardial perfusion imaging modalities based purely on relative distribution patterns to allow for better detection of diffuse disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12350-022-03179-y. Springer International Publishing 2023-01-05 2023 /pmc/articles/PMC10371953/ /pubmed/36600174 http://dx.doi.org/10.1007/s12350-022-03179-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Degtiarova, Ganna
Garefa, Chrysoula
Boehm, Reto
Ciancone, Domenico
Sepulcri, Daniel
Gebhard, Catherine
Giannopoulos, Andreas A.
Pazhenkottil, Aju P.
Kaufmann, Philipp A.
Buechel, Ronny R.
Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography
title Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography
title_full Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography
title_fullStr Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography
title_full_unstemmed Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography
title_short Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography
title_sort radiomics for the detection of diffusely impaired myocardial perfusion: a proof-of-concept study using 13n-ammonia positron emission tomography
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10371953/
https://www.ncbi.nlm.nih.gov/pubmed/36600174
http://dx.doi.org/10.1007/s12350-022-03179-y
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