Hybrid of glioma growth model and deformable image registration for longitudinal brain MRIs synthesis.

IF 1.9 4区 数学 Q2 BIOLOGY
Fulian Zhong, Yujian Liu, Jianquan Zhong, Ling He, Zhonglan Tang, Jing Zhang
{"title":"Hybrid of glioma growth model and deformable image registration for longitudinal brain MRIs synthesis.","authors":"Fulian Zhong, Yujian Liu, Jianquan Zhong, Ling He, Zhonglan Tang, Jing Zhang","doi":"10.1016/j.jtbi.2025.112147","DOIUrl":null,"url":null,"abstract":"<p><p>Modeling and visualization of glioma growth could assist in cancer diagnosis, tumor progression prediction, and clinical treatment outcome improvement. However, most studies either failed to make patient-specific predictions or could only display information about tumor size and shape, lacking the capability to characterize the impact of tumor growth on surrounding tissues. In this study, a method (HybrSyn) combining tumor growth model and deformable image registration technique for synthesizing MRIs at arbitrary time point after the detection time has been proposed. Through the tumor growth model, tumor growth process for consecutive time point has been predicted according to the characteristics of tumor cell diffusion and proliferation within the brain. The glioma deformable image registration model was employed to obtain the deformation fields between the tumors at detection time and simulations at subsequent time points. These fields were then mapped to the patient's initial MRI scans to generate the synthetic MRIs corresponding to that time points. To validate the HybrSyn, various experiments were conducted on the BraTS19 and the internal dataset collected from Zigong First People's Hospital. The quantitative results demonstrated a structural similarity of 80.93% between the synthesized MRIs and the patients' MRI scans. The qualitative results indicated that the HybrSyn could effectively capture changes during tumor progression and provide a global view. From the clinical point of view, synthesized longitudinal brain MRIs could potentially aid in presenting the impact of glioma growth on surrounding functional areas, and identifying target regions for personalized treatment planning.</p>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":" ","pages":"112147"},"PeriodicalIF":1.9000,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Theoretical Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.jtbi.2025.112147","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Modeling and visualization of glioma growth could assist in cancer diagnosis, tumor progression prediction, and clinical treatment outcome improvement. However, most studies either failed to make patient-specific predictions or could only display information about tumor size and shape, lacking the capability to characterize the impact of tumor growth on surrounding tissues. In this study, a method (HybrSyn) combining tumor growth model and deformable image registration technique for synthesizing MRIs at arbitrary time point after the detection time has been proposed. Through the tumor growth model, tumor growth process for consecutive time point has been predicted according to the characteristics of tumor cell diffusion and proliferation within the brain. The glioma deformable image registration model was employed to obtain the deformation fields between the tumors at detection time and simulations at subsequent time points. These fields were then mapped to the patient's initial MRI scans to generate the synthetic MRIs corresponding to that time points. To validate the HybrSyn, various experiments were conducted on the BraTS19 and the internal dataset collected from Zigong First People's Hospital. The quantitative results demonstrated a structural similarity of 80.93% between the synthesized MRIs and the patients' MRI scans. The qualitative results indicated that the HybrSyn could effectively capture changes during tumor progression and provide a global view. From the clinical point of view, synthesized longitudinal brain MRIs could potentially aid in presenting the impact of glioma growth on surrounding functional areas, and identifying target regions for personalized treatment planning.

脑胶质瘤生长模型与形变图像配准的混合合成。
胶质瘤生长的建模和可视化有助于肿瘤诊断、肿瘤进展预测和临床治疗结果的改善。然而,大多数研究要么无法对患者进行特异性预测,要么只能显示肿瘤大小和形状的信息,缺乏表征肿瘤生长对周围组织影响的能力。本研究提出了一种结合肿瘤生长模型和可变形图像配准技术合成检测时间后任意时间点mri的方法(HybrSyn)。通过肿瘤生长模型,根据肿瘤细胞在脑内扩散和增殖的特点,预测连续时间点的肿瘤生长过程。采用胶质瘤可变形图像配准模型,获得肿瘤在检测时刻与后续时间点模拟之间的变形场。然后将这些磁场映射到患者最初的核磁共振扫描上,生成与该时间点对应的合成核磁共振成像。为了验证HybrSyn,我们在BraTS19和自贡市第一人民医院的内部数据集上进行了各种实验。定量结果表明,合成MRI与患者MRI扫描的结构相似性为80.93%。定性结果表明,HybrSyn可以有效地捕捉肿瘤进展过程中的变化,并提供全局视图。从临床角度来看,综合脑纵向mri可能有助于呈现胶质瘤生长对周围功能区域的影响,并确定个性化治疗计划的目标区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
4.20
自引率
5.00%
发文量
218
审稿时长
51 days
期刊介绍: The Journal of Theoretical Biology is the leading forum for theoretical perspectives that give insight into biological processes. It covers a very wide range of topics and is of interest to biologists in many areas of research, including: • Brain and Neuroscience • Cancer Growth and Treatment • Cell Biology • Developmental Biology • Ecology • Evolution • Immunology, • Infectious and non-infectious Diseases, • Mathematical, Computational, Biophysical and Statistical Modeling • Microbiology, Molecular Biology, and Biochemistry • Networks and Complex Systems • Physiology • Pharmacodynamics • Animal Behavior and Game Theory Acceptable papers are those that bear significant importance on the biology per se being presented, and not on the mathematical analysis. Papers that include some data or experimental material bearing on theory will be considered, including those that contain comparative study, statistical data analysis, mathematical proof, computer simulations, experiments, field observations, or even philosophical arguments, which are all methods to support or reject theoretical ideas. However, there should be a concerted effort to make papers intelligible to biologists in the chosen field.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信