Four dimensional magnetic resonance imaging with retrospective <i>k</i>‐space reordering: A feasibility study

Liu, Yilin; Yin, Fang‐Fang; Chen, Nan‐kuei; Matsuda, Chu; Cai, Jing

doi:10.1118/1.4905044

Cited by 39 publications

(43 citation statements)

References 28 publications

(30 reference statements)

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“…However, further development of image quality and decreasing the required scanning time could be desirable and promising for our future research. The image quality improvement could be achieved via many approaches, 31 including hardware upgrades and software developments. Shortening the required scanning time would be achieved by a more comprehensive sorting technique, taking amplitude sorting or other sorting method into consideration.…”

Section: Discussionmentioning

confidence: 99%

T2‐weighted four dimensional magnetic resonance imaging with result‐driven phase sorting

et al. 2015

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Purpose: T2-weighted MRI provides excellent tumor-to-tissue contrast for target volume delineation in radiation therapy treatment planning. This study aims at developing a novel T2-weighted retrospective four dimensional magnetic resonance imaging (4D-MRI) phase sorting technique for imaging organ/tumor respiratory motion. Methods: A 2D fast T2-weighted half-Fourier acquisition single-shot turbo spin-echo MR sequence was used for image acquisition of 4D-MRI, with a frame rate of 2-3 frames/s. Respiratory motion was measured using an external breathing monitoring device. A phase sorting method was developed to sort the images by their corresponding respiratory phases. Besides, a result-driven strategy was applied to effectively utilize redundant images in the case when multiple images were allocated to a bin. This strategy, selecting the image with minimal amplitude error, will generate the most representative 4D-MRI. Since we are using a different image acquisition mode for 4D imaging (the sequential image acquisition scheme) with the conventionally used cine or helical image acquisition scheme, the 4D dataset sufficient condition was not obviously and directly predictable. An important challenge of the proposed technique was to determine the number of repeated scans (N R ) required to obtain sufficient phase information at each slice position. To tackle this challenge, the authors first conducted computer simulations using real-time position management respiratory signals of the 29 cancer patients under an IRB-approved retrospective study to derive the relationships between N R and the following factors: number of slices (N S ), number of 4D-MRI respiratory bins (N B ), and starting phase at image acquisition (P 0 ). To validate the authors' technique, 4D-MRI acquisition and reconstruction were simulated on a 4D digital extended cardiac-torso (XCAT) human phantom using simulation derived parameters. Twelve healthy volunteers were involved in an IRB-approved study to investigate the feasibility of this technique. Results: 4D data acquisition completeness (C p ) increases as NR increases in an inverse-exponential fashion (C p = 100 − 99 × exp(−0.18 × N R ), when N B = 6, fitted using 29 patients' data). The N R required for 4D-MRI reconstruction (defined as achieving 95% completeness, C p = 95%, N R = N R,95 ) is proportional to N B (N R,95 ∼ 2.86 × N B , r = 1.0), but independent of N S and P 0 . Simulated XCAT 4D-MRI showed a clear pattern of respiratory motion. Tumor motion trajectories measured on 4D-MRI were comparable to the average input signal, with a mean relative amplitude error of 2.7% ± 2.9%. Reconstructed 4D-MRI for healthy volunteers illustrated clear respiratory motion on three orthogonal planes, with minimal image artifacts. The artifacts were presumably caused by breathing irregularity and incompleteness of data acquisition (95% acquired only). The mean relative amplitude error between critical structure trajectory and average breathing curve for 12 healthy volunteers is 2.5 ± 0.3 mm in superior-...

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Section: Discussionmentioning

confidence: 99%

T2‐weighted four dimensional magnetic resonance imaging with result‐driven phase sorting

et al. 2015

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“…Despite the wide use of prospective and retrospective sorting techniques in MRI, especially in 4D‐MRI, dynamic enhanced contrast (DCE)‐MRI, and cardiac imaging, to our best knowledge there is no study yet to apply the sorting technique on DWI. This study is the first to demonstrate the feasibility of 4D‐DWI using a retrospective sorting method.…”

Section: Discussionmentioning

confidence: 99%

“…Retrospective 4D‐MRI continuously acquires images at all respiratory phases and all slice locations, then retrospectively sorts them by respiratory phases calculated from synchronized motion signal . Cai et al.…”

Section: Introductionmentioning

confidence: 99%

Four‐dimensional diffusion‐weighted MR imaging (4D‐DWI): a feasibility study

et al. 2017

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Purpose: Diffusion-weighted Magnetic Resonance Imaging (DWI) has been shown to be a powerful tool for cancer detection with high tumor-to-tissue contrast. This study aims to investigate the feasibility of developing a four-dimensional DWI technique (4D-DWI) for imaging respiratory motion for radiation therapy applications. Materials/Methods: Image acquisition was performed by repeatedly imaging a volume of interest (VOI) using an interleaved multislice single-shot echo-planar imaging (EPI) 2D-DWI sequence in the axial plane. Each 2D-DWI image was acquired with an intermediately low b-value (b = 500 s/mm2) and with diffusion-encoding gradients in x, y, and z diffusion directions. Respiratory motion was simultaneously recorded using a respiratory bellow, and the synchronized respiratory signal was used to retrospectively sort the 2D images to generate 4D-DWI. Cine MRI using steady-state free precession was also acquired as a motion reference. As a preliminary feasibility study, this technique was implemented on a 4D digital human phantom (XCAT) with a simulated pancreas tumor. The respiretory motion of the phantom was controlled by regular sinusoidal motion profile. 4D-DWI tumor motion trajectories were extracted and compared with the input breathing curve. The mean absolute amplitude differences (D) were calculated in superior-inferior (SI) direction and anterior-posterior (AP) direction. The technique was then evaluated on two healthy volunteers. Finally, the effects of 4D-DWI on apparent diffusion coefficient (ADC) measurements were investigated for hypothetical heterogeneous tumors via simulations. Results: Tumor trajectories extracted from XCAT 4D-DWI were consistent with the input signal: the average D value was 1.9 mm (SI) and 0.4 mm (AP). The average D value was 2.6 mm (SI) and 1.7 mm (AP) for the two healthy volunteers. Conclusion: A 4D-DWI technique has been developed and evaluated on digital phantom and human subjects. 4D-DWI can lead to more accurate respiratory motion measurement. This has a great potential to improve the visualization and delineation of cancer tumors for radiotherapy.

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“…The results demonstrated the feasibility of a novel retrospective 4D-MRI technique that uses body area as a respiratory surrogate. The XCAT phantom has been further applied to investigate other strategies for 4D MRI to improve temporal/spatial resolution 98, 99 .…”

Section: Radiation Therapymentioning

confidence: 99%

Application of the 4-D XCAT Phantoms in Biomedical Imaging and Beyond

Segars

Tsui

Cai

et al. 2018

IEEE Trans. Med. Imaging

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The four dimensional (4D) eXtended CArdiac-Torso (XCAT) series of phantoms was developed to provide accurate computerized models of the human anatomy and physiology. The XCAT series encompasses a vast population of phantoms of varying ages from newborn to adult, each including parameterized models for the cardiac and respiratory motions. With great flexibility in the XCAT’s design, any number of body sizes, different anatomies, cardiac or respiratory motions or patterns, patient positions and orientations, and spatial resolutions can be simulated. As such, the XCAT phantoms are gaining a wide use in biomedical imaging research. There they can provide a virtual patient base from which to quantitatively evaluate and improve imaging instrumentation, data acquisition, techniques and image reconstruction and processing methods which can lead to improved image quality and more accurate clinical diagnoses. The phantoms have also found great use in radiation dosimetry, radiation therapy, medical device design, and even the security and defense industry. This review paper highlights some specific areas in which the XCAT phantoms have found use within biomedical imaging and other fields. From these examples, we illustrate the increasingly important role that computerized phantoms and computer simulation are playing in the research community.

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Four dimensional magnetic resonance imaging with retrospective k‐space reordering: A feasibility study

Cited by 39 publications

References 28 publications

T2‐weighted four dimensional magnetic resonance imaging with result‐driven phase sorting

T2‐weighted four dimensional magnetic resonance imaging with result‐driven phase sorting

Four‐dimensional diffusion‐weighted MR imaging (4D‐DWI): a feasibility study

Application of the 4-D XCAT Phantoms in Biomedical Imaging and Beyond

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