Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Liang, Mengdi, Zhang, Cai, Xia, Tiansong, Chen, Rui, Wang, Xinyang, Weng, Miaomiao, Xie, Hui, Chen, Lin, Liu, Xiaoan, Wang, Shui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
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
_version_ 1784790794780016640
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
work_keys_str_mv AT liangmengdi ultrasoundradiomicsfeaturespredictingthedosimetryforfocusedultrasoundsurgeryofbenignbreasttumoraretrospectivestudy
AT zhangcai ultrasoundradiomicsfeaturespredictingthedosimetryforfocusedultrasoundsurgeryofbenignbreasttumoraretrospectivestudy
AT xiatiansong ultrasoundradiomicsfeaturespredictingthedosimetryforfocusedultrasoundsurgeryofbenignbreasttumoraretrospectivestudy
AT chenrui ultrasoundradiomicsfeaturespredictingthedosimetryforfocusedultrasoundsurgeryofbenignbreasttumoraretrospectivestudy
AT wangxinyang ultrasoundradiomicsfeaturespredictingthedosimetryforfocusedultrasoundsurgeryofbenignbreasttumoraretrospectivestudy
AT wengmiaomiao ultrasoundradiomicsfeaturespredictingthedosimetryforfocusedultrasoundsurgeryofbenignbreasttumoraretrospectivestudy
AT xiehui ultrasoundradiomicsfeaturespredictingthedosimetryforfocusedultrasoundsurgeryofbenignbreasttumoraretrospectivestudy
AT chenlin ultrasoundradiomicsfeaturespredictingthedosimetryforfocusedultrasoundsurgeryofbenignbreasttumoraretrospectivestudy
AT liuxiaoan ultrasoundradiomicsfeaturespredictingthedosimetryforfocusedultrasoundsurgeryofbenignbreasttumoraretrospectivestudy
AT wangshui ultrasoundradiomicsfeaturespredictingthedosimetryforfocusedultrasoundsurgeryofbenignbreasttumoraretrospectivestudy