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Ultrasound radiomics features predicting the dosimetry for focused ultrasound surgery of benign breast tumor: A retrospective study
Purpose: To investigate the correlation between pre-ablation ultrasound radiomics features and the sonication energy for focused ultrasound surgery (FUS) of benign breast tumors. Method: 53 benign breast tumors of 28 patients treated by ultrasound-guided focused ultrasound surgery (USgFUS) were incl...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9479455/ https://www.ncbi.nlm.nih.gov/pubmed/36118892 http://dx.doi.org/10.3389/fgene.2022.969409 |
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author | Liang, Mengdi Zhang, Cai Xia, Tiansong Chen, Rui Wang, Xinyang Weng, Miaomiao Xie, Hui Chen, Lin Liu, Xiaoan Wang, Shui |
author_facet | Liang, Mengdi Zhang, Cai Xia, Tiansong Chen, Rui Wang, Xinyang Weng, Miaomiao Xie, Hui Chen, Lin Liu, Xiaoan Wang, Shui |
author_sort | Liang, Mengdi |
collection | PubMed |
description | Purpose: To investigate the correlation between pre-ablation ultrasound radiomics features and the sonication energy for focused ultrasound surgery (FUS) of benign breast tumors. Method: 53 benign breast tumors of 28 patients treated by ultrasound-guided focused ultrasound surgery (USgFUS) were included in this study. The sonication energy per unit volume of each tumor was calculated. Three-quarter point was chosen as the cut-off to divide the 53 included tumors into high sonication energy (HSE, n = 14) and low sonication energy (LSE, n = 39) groups. For each tumor, the region of interest (ROI) of both the tumor itself (tROI) and the near field tissue (nfROI) were delineated and analyzed separately using ImageJ software. Pearson correlation coefficient and multiple linear regression analysis were used for radiomics feature selection. To explore the diagnostic performance of different ultrasound radiomics features, a receiver operating characteristic (ROC) curve analysis was performed. Results: In total of 68 radiomics features were extracted from pre-ablation ultrasound images of each tumor. Of all radiomics features, BX in tROI (p < 0.001), BX (p = 0.001) and Circ (p = 0.019) in nfROI were independently predictive features of sonication energy per unit volume. The ROC curves showed that the area under the curve (AUC) values of BX in tROI, BX, and Circ in nfROI were 0.797, 0.787 and 0.822, respectively. Conclusion: This study provided three radiomics features of pre-ablation ultrasound image as predictors of sonication dose for FUS in benign breast tumors. Further clinical trials are needed to confirm the predictive effect of these radiomics features. |
format | Online Article Text |
id | pubmed-9479455 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94794552022-09-17 Ultrasound radiomics features predicting the dosimetry for focused ultrasound surgery of benign breast tumor: A retrospective study Liang, Mengdi Zhang, Cai Xia, Tiansong Chen, Rui Wang, Xinyang Weng, Miaomiao Xie, Hui Chen, Lin Liu, Xiaoan Wang, Shui Front Genet Genetics Purpose: To investigate the correlation between pre-ablation ultrasound radiomics features and the sonication energy for focused ultrasound surgery (FUS) of benign breast tumors. Method: 53 benign breast tumors of 28 patients treated by ultrasound-guided focused ultrasound surgery (USgFUS) were included in this study. The sonication energy per unit volume of each tumor was calculated. Three-quarter point was chosen as the cut-off to divide the 53 included tumors into high sonication energy (HSE, n = 14) and low sonication energy (LSE, n = 39) groups. For each tumor, the region of interest (ROI) of both the tumor itself (tROI) and the near field tissue (nfROI) were delineated and analyzed separately using ImageJ software. Pearson correlation coefficient and multiple linear regression analysis were used for radiomics feature selection. To explore the diagnostic performance of different ultrasound radiomics features, a receiver operating characteristic (ROC) curve analysis was performed. Results: In total of 68 radiomics features were extracted from pre-ablation ultrasound images of each tumor. Of all radiomics features, BX in tROI (p < 0.001), BX (p = 0.001) and Circ (p = 0.019) in nfROI were independently predictive features of sonication energy per unit volume. The ROC curves showed that the area under the curve (AUC) values of BX in tROI, BX, and Circ in nfROI were 0.797, 0.787 and 0.822, respectively. Conclusion: This study provided three radiomics features of pre-ablation ultrasound image as predictors of sonication dose for FUS in benign breast tumors. Further clinical trials are needed to confirm the predictive effect of these radiomics features. Frontiers Media S.A. 2022-09-06 /pmc/articles/PMC9479455/ /pubmed/36118892 http://dx.doi.org/10.3389/fgene.2022.969409 Text en Copyright © 2022 Liang, Zhang, Xia, Chen, Wang, Weng, Xie, Chen, Liu and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Liang, Mengdi Zhang, Cai Xia, Tiansong Chen, Rui Wang, Xinyang Weng, Miaomiao Xie, Hui Chen, Lin Liu, Xiaoan Wang, Shui Ultrasound radiomics features predicting the dosimetry for focused ultrasound surgery of benign breast tumor: A retrospective study |
title | Ultrasound radiomics features predicting the dosimetry for focused ultrasound surgery of benign breast tumor: A retrospective study |
title_full | Ultrasound radiomics features predicting the dosimetry for focused ultrasound surgery of benign breast tumor: A retrospective study |
title_fullStr | Ultrasound radiomics features predicting the dosimetry for focused ultrasound surgery of benign breast tumor: A retrospective study |
title_full_unstemmed | Ultrasound radiomics features predicting the dosimetry for focused ultrasound surgery of benign breast tumor: A retrospective study |
title_short | Ultrasound radiomics features predicting the dosimetry for focused ultrasound surgery of benign breast tumor: A retrospective study |
title_sort | ultrasound radiomics features predicting the dosimetry for focused ultrasound surgery of benign breast tumor: a retrospective study |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9479455/ https://www.ncbi.nlm.nih.gov/pubmed/36118892 http://dx.doi.org/10.3389/fgene.2022.969409 |
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