已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Respiratory-Correlated 4-Dimensional Magnetic Resonance Fingerprinting for Liver Cancer Radiation Therapy Motion Management

医学 磁共振成像 核医学 成像体模 核磁共振 标准差 相关性 物理 放射科 数学 统计 几何学
作者
Chenyang Liu,Li Tian,Peng Cao,Edward S. Hui,Yat-Lam Wong,Zuojun Wang,Haonan Xiao,Shaohua Zhi,Ta Zhou,Wen Li,Saikit Lam,Andy Lai-Yin Cheung,Victor Ho-Fun Lee,Michael Ying,Jing Cai
出处
期刊:International Journal of Radiation Oncology Biology Physics [Elsevier BV]
卷期号:117 (2): 493-504 被引量:14
标识
DOI:10.1016/j.ijrobp.2023.04.015
摘要

Purpose The objective of this study was to develop a respiratory-correlated (RC) 4-dimensional (4D) imaging technique based on magnetic resonance fingerprinting (MRF) (RC-4DMRF) for liver tumor motion management in radiation therapy. Methods and Materials Thirteen patients with liver cancer were prospectively enrolled in this study. k-space MRF signals of the liver were acquired during free-breathing using the fast acquisition with steady-state precession sequence on a 3T scanner. The signals were binned into 8 respiratory phases based on respiratory surrogates, and interphase displacement vector fields were estimated using a phase-specific low-rank optimization method. Hereafter, the tissue property maps, including T1 and T2 relaxation times, and proton density, were reconstructed using a pyramid motion-compensated method that alternatively optimized interphase displacement vector fields and subspace images. To evaluate the efficacy of RC-4DMRF, amplitude motion differences and Pearson correlation coefficients were determined to assess measurement agreement in tumor motion between RC-4DMRF and cine magnetic resonance imaging (MRI); mean absolute percentage errors of the RC-4DMRF–derived tissue maps were calculated to reveal tissue quantification accuracy using digital human phantom; and tumor-to-liver contrast-to-noise ratio of RC-4DMRF images was compared with that of planning CT and contrast-enhanced MRI (CE-MRI) images. A paired Student t test was used for statistical significance analysis with a P value threshold of .05. Results RC-4DMRF achieved excellent agreement in motion measurement with cine MRI, yielding the mean (± standard deviation) Pearson correlation coefficients of 0.95 ± 0.05 and 0.93 ± 0.09 and amplitude motion differences of 1.48 ± 1.06 mm and 0.81 ± 0.64 mm in the superior-inferior and anterior-posterior directions, respectively. Moreover, RC-4DMRF achieved high accuracy in tissue property quantification, with mean absolute percentage errors of 8.8%, 9.6%, and 5.0% for T1, T2, and proton density, respectively. Notably, the tumor contrast-to-noise ratio in RC-4DMRI–derived T1 maps (6.41 ± 3.37) was found to be the highest among all tissue property maps, approximately equal to that of CE-MRI (6.96 ± 1.01, P = .862), and substantially higher than that of planning CT (2.91 ± 1.97, P = .048). Conclusions RC-4DMRF demonstrated high accuracy in respiratory motion measurement and tissue properties quantification, potentially facilitating tumor motion management in liver radiation therapy. The objective of this study was to develop a respiratory-correlated (RC) 4-dimensional (4D) imaging technique based on magnetic resonance fingerprinting (MRF) (RC-4DMRF) for liver tumor motion management in radiation therapy. Thirteen patients with liver cancer were prospectively enrolled in this study. k-space MRF signals of the liver were acquired during free-breathing using the fast acquisition with steady-state precession sequence on a 3T scanner. The signals were binned into 8 respiratory phases based on respiratory surrogates, and interphase displacement vector fields were estimated using a phase-specific low-rank optimization method. Hereafter, the tissue property maps, including T1 and T2 relaxation times, and proton density, were reconstructed using a pyramid motion-compensated method that alternatively optimized interphase displacement vector fields and subspace images. To evaluate the efficacy of RC-4DMRF, amplitude motion differences and Pearson correlation coefficients were determined to assess measurement agreement in tumor motion between RC-4DMRF and cine magnetic resonance imaging (MRI); mean absolute percentage errors of the RC-4DMRF–derived tissue maps were calculated to reveal tissue quantification accuracy using digital human phantom; and tumor-to-liver contrast-to-noise ratio of RC-4DMRF images was compared with that of planning CT and contrast-enhanced MRI (CE-MRI) images. A paired Student t test was used for statistical significance analysis with a P value threshold of .05. RC-4DMRF achieved excellent agreement in motion measurement with cine MRI, yielding the mean (± standard deviation) Pearson correlation coefficients of 0.95 ± 0.05 and 0.93 ± 0.09 and amplitude motion differences of 1.48 ± 1.06 mm and 0.81 ± 0.64 mm in the superior-inferior and anterior-posterior directions, respectively. Moreover, RC-4DMRF achieved high accuracy in tissue property quantification, with mean absolute percentage errors of 8.8%, 9.6%, and 5.0% for T1, T2, and proton density, respectively. Notably, the tumor contrast-to-noise ratio in RC-4DMRI–derived T1 maps (6.41 ± 3.37) was found to be the highest among all tissue property maps, approximately equal to that of CE-MRI (6.96 ± 1.01, P = .862), and substantially higher than that of planning CT (2.91 ± 1.97, P = .048). RC-4DMRF demonstrated high accuracy in respiratory motion measurement and tissue properties quantification, potentially facilitating tumor motion management in liver radiation therapy.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研发布了新的文献求助10
刚刚
领导范儿应助XX采纳,获得10
2秒前
旺仔发布了新的文献求助10
2秒前
Linkkk完成签到 ,获得积分10
5秒前
赘婿应助light采纳,获得10
6秒前
9秒前
9秒前
无花果应助一天一苹果采纳,获得30
11秒前
CK完成签到 ,获得积分20
11秒前
欢呼河马完成签到,获得积分10
12秒前
12秒前
Sledge应助cc采纳,获得10
13秒前
XX发布了新的文献求助10
14秒前
NexusExplorer应助从容的凌文采纳,获得10
14秒前
14秒前
123完成签到,获得积分10
14秒前
16秒前
赵乂发布了新的文献求助10
18秒前
sci求您疼我完成签到,获得积分10
20秒前
华仔应助碧蓝念烟采纳,获得10
21秒前
敏感思远发布了新的文献求助30
21秒前
shanfeng完成签到 ,获得积分10
21秒前
22秒前
22秒前
Vesper发布了新的文献求助10
22秒前
科研完成签到,获得积分10
24秒前
斯文败类应助赵乂采纳,获得10
25秒前
26秒前
28秒前
28秒前
wbh发布了新的文献求助10
28秒前
夏兰关注了科研通微信公众号
28秒前
ding应助科研采纳,获得10
29秒前
29秒前
天才蹦蹦man赞赞完成签到,获得积分20
30秒前
32秒前
huajuan2002发布了新的文献求助10
34秒前
GGGGA发布了新的文献求助10
35秒前
是个宝耶完成签到 ,获得积分10
37秒前
Zhengkeke发布了新的文献求助10
38秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Autoparametric Resonance in Mechanical Systems 1000
基于锂离子电池正极材料回收的绿色溶剂开发及工程化应用研究 800
Social Psychology 600
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 600
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7644994
求助须知:如何正确求助?哪些是违规求助? 9217663
关于积分的说明 19776377
捐赠科研通 7210009
什么是DOI,文献DOI怎么找? 3276802
关于科研通互助平台的介绍 2438416
邀请新用户注册赠送积分活动 2274806