修车大队一品楼qm论坛51一品茶楼论坛,栖凤楼品茶全国楼凤app软件 ,栖凤阁全国论坛入口,广州百花丛bhc论坛杭州百花坊妃子阁

Characterizing spatiotemporal information loss in sparse-sampling-based dynamic MRI for monitoring respiration-induced tumor motion in radiotherapy

DOI:10.1118/1.4948684 期刊:Medical Physics 出版年份:2016 更新时间:2025-09-23 15:22:29
摘要: Purpose: Sparse-sampling and reconstruction techniques represent an attractive strategy to achieve faster image acquisition speeds, while maintaining adequate spatial resolution and signal-to-noise ratio in rapid magnetic resonance imaging (MRI). The authors investigate the use of one such sequence, broad-use linear acquisition speed-up technique (k-t BLAST) in monitoring tumor motion for thoracic and abdominal radiotherapy and examine the potential trade-off between increased sparsification (to increase imaging speed) and the potential loss of 'true' information due to greater reliance on a priori information. Methods: Lung tumor motion trajectories in the superior–inferior direction, previously recorded from ten lung cancer patients, were replayed using a motion phantom module driven by an MRI-compatible motion platform. Eppendorf test tubes filled with water which serve as fiducial markers were placed in the phantom. The modeled rigid and deformable motions were collected in a coronal image slice using balanced fast field echo in conjunction with k-t BLAST. Root mean square (RMS) error was used as a metric of spatial accuracy as measured trajectories were compared to input data. The loss of spatial information was characterized for progressively increasing acceleration factor from 1 to 16; the resultant sampling frequency was increased approximately from 2.5 to 19 Hz when the principal direction of the motion was set along frequency encoding direction. In addition to the phantom study, respiration-induced tumor motions were captured from two patients (kidney tumor and lung tumor) at 13 Hz over 49 s to demonstrate the impact of high speed motion monitoring over multiple breathing cycles. For each subject, the authors compared the tumor centroid trajectory as well as the deformable motion during free breathing. Results: In the rigid and deformable phantom studies, the RMS error of target tracking at the acquisition speed of 19 Hz was approximately 0.3–0.4 mm, which was smaller than the reconstructed pixel resolution of 0.67 mm. In the patient study, the dynamic 2D MRI enabled the monitoring of cycle-to-cycle respiratory variability present in the tumor position. It was seen that the range of centroid motion as well as the area covered due to target motion during each individual respiratory cycle was underestimated compared to the entire motion range observed over multiple breathing cycles. Conclusions: The authors’ initial results demonstrate that sparse-sampling- and reconstruction-based dynamic MRI can be used to achieve adequate image acquisition speeds without significant information loss for the task of radiotherapy guidance. Such monitoring can yield spatial and temporal information superior to conventional offline and online motion capture methods used in thoracic and abdominal radiotherapy.
作者: Tatsuya J. Arai,Joris Nofiele,Ananth J. Madhuranthakam,Qing Yuan,Ivan Pedrosa,Rajiv Chopra,Amit Sawant
AI智能分析
纠错
研究概述 实验方案 设备清单

To investigate the use of k-t BLAST in monitoring tumor motion for radiotherapy and examine the trade-off between increased sparsification and potential loss of information.

Sparse-sampling-based dynamic MRI with k-t BLAST can achieve high acquisition speeds (up to 20 Hz) with minimal information loss (RMS error <1 mm), making it suitable for radiotherapy guidance. It enables monitoring of respiratory variability over multiple cycles, complementing 4DCT by providing better temporal resolution and soft-tissue contrast. Future work should focus on 3D dynamic imaging and multimodality integration.

The study is limited to 2D imaging in a single coronal plane, not capturing motion in other directions. MRI cannot measure electron density for dose calculation. Memory constraints of the MRI scanner limit the number of images acquired, and reconstruction time is significant. The deformable phantom may not fully mimic biological tissue properties.

SCI高频之选
查看全部>
  • AQ6370D
    AQ6370D
    463

    型号:AQ6370D

    厂家:Yokogawa

    智能分析: Yokogawa AQ6370D是一款性能卓越的光谱分析仪,适用于光通信领域以及光放大器(EDFA)的测量和评估。其高波长分辨率、精准度和宽动态范围使其成为实验室和工业环境中的理想选择。虽然设备体积较大且预热时间较长,但其丰富的接口和出色的显示屏设计弥补了这些不足,整体是一款值得推荐的光谱分析仪。
    获取实验方案
  • ZEISS EVO Family

    型号:ZEISS EVO Family

    厂家:Carl Zeiss Microscopy GmbH

    智能分析: ZEISS EVO系列是一款高性能??榛璧缱酉晕⒕?,适用于材料科学、生命科学及工业质量控制等领域。其先进的技术特性包括高分辨率、广泛加速电压范围和集成EDS系统。该产品操作直观,支持多用户环境,适合科学研究和工业应用。然而,价格信息缺失以及潜在的维护成本可能是其需要注意的方面。总体而言,ZEISS EVO系列表现优秀,值得推荐给专业用户。
    获取实验方案
  • Crossbeam Family

    型号:Crossbeam Family350/550

    厂家:Carl Zeiss Microscopy GmbH

    智能分析: ZEISS Crossbeam系列是蔡司公司推出的一款高端光电分析设备,结合了场发射扫描电子显微镜(FE-SEM)和聚焦离子束(FIB)的功能,适用于材料科学、纳米技术和半导体行业等多个领域。其高分辨率成像能力和自动化样品制备功能使其成为高通量分析的理想选择。此外,该设备支持多种检测器,具备强大的多功能性,是高精度研究和工业应用的利器。然而,由于其高端定位,设备成本较高且操作需要专业技能。总体而言,该设备表现卓越,为科学研究和工业应用提供了先进的解决方案。
    获取实验方案
  • Axio Observer

    型号:Axio Observer

    厂家:Carl Zeiss Microscopy GmbH

    智能分析: Axio Observer是一款专为金相学研究设计的倒置显微镜系统,以其高效的设计和蔡司知名的光学技术为特色。它能够快速、灵活地分析大量样品,并支持自动化操作,适用于多种应用场景,包括晶粒尺寸分析、非金属夹杂物检测等。然而,其重量较大且光源寿命较短,可能对使用者提出了额外的维护和空间管理需求。总体而言,这款产品在性能和可靠性方面表现出色,特别适合专业实验室使用。
    获取实验方案
  • ZEISS LSM 990 Spectral Multiplex

    型号:ZEISS LSM 990 Spectral Multiplex

    厂家:Carl Zeiss Microscopy GmbH

    智能分析: ZEISS LSM 990 Spectral Multiplex是一款定位于高端科研机构的光谱成像系统,具有卓越的光谱分辨率和自动化功能,适用于复杂的生物、医学及材料科学实验。其高效的荧光标签分离能力和多功能自动化设计为用户提供了强大的实验支持。然而,高昂的价格和一定的学习曲线可能对中小型实验室构成挑战。总体而言,这是一款性能优越、适应性强的高端实验设备。
    获取实验方案
  • ZEISS Sigma 300 with RISE

    型号:ZEISS Sigma 300 with RISE

    厂家:Carl Zeiss Microscopy GmbH

    智能分析: ZEISS Sigma 300 with RISE是蔡司公司推出的一款高端光谱分析仪,集成了拉曼成像和扫描电子显微镜技术,能够提供高质量的化学和结构分析。其功能强大,支持多领域应用,但设备价格较高且操作学习曲线可能较陡。适用于科研机构和高端实验室,是材料科学和生命科学领域的理想选择。
    获取实验方案
立即咨询

加载中....

论文纠错

您正在对论文“Characterizing spatiotemporal information loss in sparse-sampling-based dynamic MRI for monitoring respiration-induced tumor motion in radiotherapy”进行纠错

纠错内容

联系方式(选填)

设备询价

称呼

电话

+86

单位名称

用途

期望交货周期

产品预约

称呼

电话

+86

单位名称

用途

期望交货周期