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α- and β-Genotyping of Thalassemia Patients Based on a Multimodal Liver MRI Radiomics Model: A Preliminary Study in Two Centers

Background: So far, there is no non-invasive method that can popularize the genetic testing of thalassemia (TM) patients on a large scale. The purpose of the study was to investigate the value of predicting the α- and β- genotypes of TM patients based on a liver MRI radiomics model. Methods: Radiomi...

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Autores principales: Xu, Fengming, Feng, Qing, Yi, Jixing, Tang, Cheng, Lin, Huashan, Liang, Bumin, Luo, Chaotian, Guan, Kaiming, Li, Tao, Peng, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10000720/
https://www.ncbi.nlm.nih.gov/pubmed/36900102
http://dx.doi.org/10.3390/diagnostics13050958
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author Xu, Fengming
Feng, Qing
Yi, Jixing
Tang, Cheng
Lin, Huashan
Liang, Bumin
Luo, Chaotian
Guan, Kaiming
Li, Tao
Peng, Peng
author_facet Xu, Fengming
Feng, Qing
Yi, Jixing
Tang, Cheng
Lin, Huashan
Liang, Bumin
Luo, Chaotian
Guan, Kaiming
Li, Tao
Peng, Peng
author_sort Xu, Fengming
collection PubMed
description Background: So far, there is no non-invasive method that can popularize the genetic testing of thalassemia (TM) patients on a large scale. The purpose of the study was to investigate the value of predicting the α- and β- genotypes of TM patients based on a liver MRI radiomics model. Methods: Radiomics features of liver MRI image data and clinical data of 175 TM patients were extracted using Analysis Kinetics (AK) software. The radiomics model with optimal predictive performance was combined with the clinical model to construct a joint model. The predictive performance of the model was evaluated in terms of AUC, accuracy, sensitivity, and specificity. Results: The T2 model showed the best predictive performance: the AUC, accuracy, sensitivity, and specificity of the validation group were 0.88, 0.865, 0.875, and 0.833, respectively. The joint model constructed from T2 image features and clinical features showed higher predictive performance: the AUC, accuracy, sensitivity, and specificity of the validation group were 0.91, 0.846, 0.9, and 0.667, respectively. Conclusion: The liver MRI radiomics model is feasible and reliable for predicting α- and β-genotypes in TM patients.
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spelling pubmed-100007202023-03-11 α- and β-Genotyping of Thalassemia Patients Based on a Multimodal Liver MRI Radiomics Model: A Preliminary Study in Two Centers Xu, Fengming Feng, Qing Yi, Jixing Tang, Cheng Lin, Huashan Liang, Bumin Luo, Chaotian Guan, Kaiming Li, Tao Peng, Peng Diagnostics (Basel) Article Background: So far, there is no non-invasive method that can popularize the genetic testing of thalassemia (TM) patients on a large scale. The purpose of the study was to investigate the value of predicting the α- and β- genotypes of TM patients based on a liver MRI radiomics model. Methods: Radiomics features of liver MRI image data and clinical data of 175 TM patients were extracted using Analysis Kinetics (AK) software. The radiomics model with optimal predictive performance was combined with the clinical model to construct a joint model. The predictive performance of the model was evaluated in terms of AUC, accuracy, sensitivity, and specificity. Results: The T2 model showed the best predictive performance: the AUC, accuracy, sensitivity, and specificity of the validation group were 0.88, 0.865, 0.875, and 0.833, respectively. The joint model constructed from T2 image features and clinical features showed higher predictive performance: the AUC, accuracy, sensitivity, and specificity of the validation group were 0.91, 0.846, 0.9, and 0.667, respectively. Conclusion: The liver MRI radiomics model is feasible and reliable for predicting α- and β-genotypes in TM patients. MDPI 2023-03-03 /pmc/articles/PMC10000720/ /pubmed/36900102 http://dx.doi.org/10.3390/diagnostics13050958 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xu, Fengming
Feng, Qing
Yi, Jixing
Tang, Cheng
Lin, Huashan
Liang, Bumin
Luo, Chaotian
Guan, Kaiming
Li, Tao
Peng, Peng
α- and β-Genotyping of Thalassemia Patients Based on a Multimodal Liver MRI Radiomics Model: A Preliminary Study in Two Centers
title α- and β-Genotyping of Thalassemia Patients Based on a Multimodal Liver MRI Radiomics Model: A Preliminary Study in Two Centers
title_full α- and β-Genotyping of Thalassemia Patients Based on a Multimodal Liver MRI Radiomics Model: A Preliminary Study in Two Centers
title_fullStr α- and β-Genotyping of Thalassemia Patients Based on a Multimodal Liver MRI Radiomics Model: A Preliminary Study in Two Centers
title_full_unstemmed α- and β-Genotyping of Thalassemia Patients Based on a Multimodal Liver MRI Radiomics Model: A Preliminary Study in Two Centers
title_short α- and β-Genotyping of Thalassemia Patients Based on a Multimodal Liver MRI Radiomics Model: A Preliminary Study in Two Centers
title_sort α- and β-genotyping of thalassemia patients based on a multimodal liver mri radiomics model: a preliminary study in two centers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10000720/
https://www.ncbi.nlm.nih.gov/pubmed/36900102
http://dx.doi.org/10.3390/diagnostics13050958
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