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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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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. |
format | Online Article Text |
id | pubmed-10000720 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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