[经皮介入射频热融合 L5/S1 节段的多约束最佳穿刺路径规划算法]。

H Liu, Z Su, C Huang, L Zhao, Y Chen, Y Zhou, H Lü, Q Feng
{"title":"[经皮介入射频热融合 L5/S1 节段的多约束最佳穿刺路径规划算法]。","authors":"H Liu, Z Su, C Huang, L Zhao, Y Chen, Y Zhou, H Lü, Q Feng","doi":"10.12122/j.issn.1673-4254.2024.09.19","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To minimize variations in treatment outcomes of L5/S1 percutaneous intervertebral radiofrequency thermocoagulation (PIRFT) arising from physician proficiency and achieve precise quantitative risk assessment of the puncture paths.</p><p><strong>Methods: </strong>We used a self-developed deep neural network DWT-UNet for automatic segmentation of the magnetic resonance (MR) images of the L5/S1 segments into 7 key structures: L5, S1, Ilium, Disc, N5, Dura mater, and Skin, based on which a needle insertion path planning environment was modeled. Six hard constraints and 6 soft constraints were proposed based on clinical criteria for needle insertion, and the physician's experience was quantified into weights using the analytic hierarchy process and incorporated into the risk function for needle insertion paths to enhance individual case adaptability. By leveraging the proposed skin entry point sampling sub-algorithm and Kambin's triangle projection area sub-algorithm in conjunction with the analytic hierarchy process, and employing various technologies such as ray tracing, CPU multi-threading, and GPU parallel computing, a puncture path was calculated that not only met clinical hard constraints but also optimized the overall soft constraints.</p><p><strong>Results: </strong>A surgical team conducted a subjective evaluation of the 21 needle puncture paths planned by the algorithm, and all the paths met the clinical requirements, with 95.24% of them rated excellent or good. Compared with the physician's planning results, the plans generated by the algorithm showed inferior D<sub>Ilium</sub>, D<sub>S1</sub>, and Depth (<i>P</i> < 0.05) but much better D<sub>Dura</sub>, D<sub>L5</sub>, D<sub>N5</sub>, and A<sub>Kambin</sub> (<i>P</i> < 0.05). In the 21 cases, the planning time of the algorithm averaged 7.97±3.73 s, much shorter than that by the physicians (typically beyond 10 min).</p><p><strong>Conclusion: </strong>The multi-constraint optimal puncture path planning algorithm offers an efficient automated solution for PIRFT of the L5/S1 segments with great potentials for clinical application.</p>","PeriodicalId":18962,"journal":{"name":"Nan fang yi ke da xue xue bao = Journal of Southern Medical University","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[A multi-constraint optimal puncture path planning algorithm for percutaneous interventional radiofrequency thermal fusion of the L5/S1 segments].\",\"authors\":\"H Liu, Z Su, C Huang, L Zhao, Y Chen, Y Zhou, H Lü, Q Feng\",\"doi\":\"10.12122/j.issn.1673-4254.2024.09.19\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To minimize variations in treatment outcomes of L5/S1 percutaneous intervertebral radiofrequency thermocoagulation (PIRFT) arising from physician proficiency and achieve precise quantitative risk assessment of the puncture paths.</p><p><strong>Methods: </strong>We used a self-developed deep neural network DWT-UNet for automatic segmentation of the magnetic resonance (MR) images of the L5/S1 segments into 7 key structures: L5, S1, Ilium, Disc, N5, Dura mater, and Skin, based on which a needle insertion path planning environment was modeled. Six hard constraints and 6 soft constraints were proposed based on clinical criteria for needle insertion, and the physician's experience was quantified into weights using the analytic hierarchy process and incorporated into the risk function for needle insertion paths to enhance individual case adaptability. By leveraging the proposed skin entry point sampling sub-algorithm and Kambin's triangle projection area sub-algorithm in conjunction with the analytic hierarchy process, and employing various technologies such as ray tracing, CPU multi-threading, and GPU parallel computing, a puncture path was calculated that not only met clinical hard constraints but also optimized the overall soft constraints.</p><p><strong>Results: </strong>A surgical team conducted a subjective evaluation of the 21 needle puncture paths planned by the algorithm, and all the paths met the clinical requirements, with 95.24% of them rated excellent or good. Compared with the physician's planning results, the plans generated by the algorithm showed inferior D<sub>Ilium</sub>, D<sub>S1</sub>, and Depth (<i>P</i> < 0.05) but much better D<sub>Dura</sub>, D<sub>L5</sub>, D<sub>N5</sub>, and A<sub>Kambin</sub> (<i>P</i> < 0.05). In the 21 cases, the planning time of the algorithm averaged 7.97±3.73 s, much shorter than that by the physicians (typically beyond 10 min).</p><p><strong>Conclusion: </strong>The multi-constraint optimal puncture path planning algorithm offers an efficient automated solution for PIRFT of the L5/S1 segments with great potentials for clinical application.</p>\",\"PeriodicalId\":18962,\"journal\":{\"name\":\"Nan fang yi ke da xue xue bao = Journal of Southern Medical University\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nan fang yi ke da xue xue bao = Journal of Southern Medical University\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12122/j.issn.1673-4254.2024.09.19\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nan fang yi ke da xue xue bao = Journal of Southern Medical University","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12122/j.issn.1673-4254.2024.09.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

摘要

目的:尽量减少因医生操作熟练程度而导致的L5/S1经皮椎间射频热凝术(PIRFT)治疗效果的差异,实现穿刺路径的精确定量风险评估:我们使用自主研发的深度神经网络 DWT-UNet 将 L5/S1 节段的磁共振(MR)图像自动分割为 7 个关键结构:L5、S1、髂骨、椎间盘、N5、硬脑膜和皮肤,并在此基础上建立了针插入路径规划环境模型。根据穿刺针插入的临床标准,提出了 6 个硬约束和 6 个软约束,并使用层次分析法将医生的经验量化为权重,纳入穿刺针插入路径的风险函数,以提高个案适应性。通过利用提出的皮肤进针点取样子算法和 Kambin 三角形投影面积子算法,结合层次分析法,并采用光线追踪、CPU 多线程和 GPU 并行计算等多种技术,计算出的穿刺路径不仅满足了临床硬约束,还优化了整体软约束:手术团队对算法规划的 21 条穿刺针路径进行了主观评价,所有路径均符合临床要求,其中 95.24% 的路径被评为优或良。与医生的计划结果相比,算法生成的计划显示 DIlium、DS1 和 Depth 较差(P < 0.05),但 DDura、DL5、DN5 和 AKambin 好得多(P < 0.05)。在 21 个病例中,该算法的规划时间平均为(7.97±3.73)秒,比医生的规划时间(通常超过 10 分钟)短得多:多约束最佳穿刺路径规划算法为 L5/S1 节段的 PIRFT 提供了一种高效的自动化解决方案,具有巨大的临床应用潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
[A multi-constraint optimal puncture path planning algorithm for percutaneous interventional radiofrequency thermal fusion of the L5/S1 segments].

Objective: To minimize variations in treatment outcomes of L5/S1 percutaneous intervertebral radiofrequency thermocoagulation (PIRFT) arising from physician proficiency and achieve precise quantitative risk assessment of the puncture paths.

Methods: We used a self-developed deep neural network DWT-UNet for automatic segmentation of the magnetic resonance (MR) images of the L5/S1 segments into 7 key structures: L5, S1, Ilium, Disc, N5, Dura mater, and Skin, based on which a needle insertion path planning environment was modeled. Six hard constraints and 6 soft constraints were proposed based on clinical criteria for needle insertion, and the physician's experience was quantified into weights using the analytic hierarchy process and incorporated into the risk function for needle insertion paths to enhance individual case adaptability. By leveraging the proposed skin entry point sampling sub-algorithm and Kambin's triangle projection area sub-algorithm in conjunction with the analytic hierarchy process, and employing various technologies such as ray tracing, CPU multi-threading, and GPU parallel computing, a puncture path was calculated that not only met clinical hard constraints but also optimized the overall soft constraints.

Results: A surgical team conducted a subjective evaluation of the 21 needle puncture paths planned by the algorithm, and all the paths met the clinical requirements, with 95.24% of them rated excellent or good. Compared with the physician's planning results, the plans generated by the algorithm showed inferior DIlium, DS1, and Depth (P < 0.05) but much better DDura, DL5, DN5, and AKambin (P < 0.05). In the 21 cases, the planning time of the algorithm averaged 7.97±3.73 s, much shorter than that by the physicians (typically beyond 10 min).

Conclusion: The multi-constraint optimal puncture path planning algorithm offers an efficient automated solution for PIRFT of the L5/S1 segments with great potentials for clinical application.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
1.50
自引率
0.00%
发文量
208
期刊最新文献
[HNRNPA1 gene is highly expressed in colorectal cancer: its prognostic implications and potential as a therapeutic target]. [Lycium barbarum glycopeptide reduces bone loss caused by exosomes derived from human gingival fibroblasts with radiation exposure]. [A deep learning model based on magnetic resonance imaging and clinical feature fusion for predicting preoperative cytokeratin 19 status in hepatocellular carcinoma]. [A lung sound classification model with a spatial and channel reconstruction convolutional module]. [A multi-constraint optimal puncture path planning algorithm for percutaneous interventional radiofrequency thermal fusion of the L5/S1 segments].
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1