Fast Field Echo imaging: An overview and contrast calculations

Meulen, P. van der; Groen, J.P.; Tinus, A.M.C.; Bruntink, G.

doi:10.1016/0730-725x(88)90472-9

Cited by 119 publications

(53 citation statements)

References 7 publications

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“…Non-ideal slice select profile may also be part of the reason for the observed signal difference (13). The effect of non-ideal slice select profile on the signal curves could be seen from Fig.…”

Section: Resultsmentioning

confidence: 86%

Signal formation in echo-shifted sequences

Chung

Duerk

1999

Magn. Reson. Med.

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Section: Resultsmentioning

confidence: 86%

Signal formation in echo-shifted sequences

Chung

Duerk

1999

Magn. Reson. Med.

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“…Those voxels are represented by a linear combination of both air and fluid classes and are underestimated in pseudo-CT. This effect has been previously described and is largely due to CSF flow effects 56 and a signal loss of a long T1 tissue acquired with a short repetition time MR sequence. 25 An approach to reduce this clustering error is to use the RF spoiling technique in the UTE-mDixon acquisition.…”

Section: Discussionmentioning

confidence: 97%

Generation of brain pseudo‐CTs using an undersampled, single‐acquisition UTE‐mDixon pulse sequence and unsupervised clustering

Stehning

et al. 2015

Medical Physics

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Purpose: MR-based pseudo-CT has an important role in MR-based radiation therapy planning and PET attenuation correction. The purpose of this study is to establish a clinically feasible approach, including image acquisition, correction, and CT formation, for pseudo-CT generation of the brain using a single-acquisition, undersampled ultrashort echo time (UTE)-mDixon pulse sequence. Methods: Nine patients were recruited for this study. For each patient, a 190-s, undersampled, single acquisition UTE-mDixon sequence of the brain was acquired (TE = 0.1, 1.5, and 2.8 ms). A novel method of retrospective trajectory correction of the free induction decay (FID) signal was performed based on point-spread functions of three external MR markers. Two-point Dixon images were reconstructed using the first and second echo data (TE = 1.5 and 2.8 ms). R2 * images (1/T2 * ) were then estimated and were used to provide bone information. Three image features, i.e., Dixon-fat, Dixon-water, and R2 * , were used for unsupervised clustering. Five tissue clusters, i.e., air, brain, fat, fluid, and bone, were estimated using the fuzzy c-means (FCM) algorithm. A two-step, automatic tissue-assignment approach was proposed and designed according to the prior information of the given feature space. Pseudo-CTs were generated by a voxelwise linear combination of the membership functions of the FCM. A low-dose CT was acquired for each patient and was used as the gold standard for comparison. Results: The contrast and sharpness of the FID images were improved after trajectory correction was applied. The mean of the estimated trajectory delay was 0.774 µs (max: 1.350 µs; min: 0.180 µs). The FCM-estimated centroids of different tissue types showed a distinguishable pattern for different tissues, and significant differences were found between the centroid locations of different tissue types. Pseudo-CT can provide additional skull detail and has low bias and absolute error of estimated CT numbers of voxels (−22 ± 29 HU and 130 ± 16 HU) when compared to low-dose CT. Conclusions: The MR features generated by the proposed acquisition, correction, and processing methods may provide representative clustering information and could thus be used for clinical pseudo-CT generation. C 2015 American Association of Physicists in Medicine.

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“…The echo time was chosen 16.1 ms for which water and fat protons have opposed phases. The FFE sequence was an RF spoiled gradient e c ho sequence, which improves the T 1 image contrast Van der Meulen et al 1988. For the motion studies, signal acquisition was triggered on the respiration cycle using a respiration monitor with sensor Type MR 10, Graseby Medical Ltd, Watford, England in combination with the scanners triggering device.…”

Section: Methodsmentioning

confidence: 99%

Magnetic resonance imaging in radiotherapy treatment planning

Moerland¹

1997

Medical Physics

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The aim of this study is to investigate the capabilities of magnetic resonance imaging (MRI) in radiotherapy treatment planning (RTP) and to explore the MR image distortions and how these distortions can be reduced or, if necessary, corrected in order to integrate MRI into RTP in a reliable manner. Image distortions and the efficacy of correction methods were evaluated in phantom, volunteer, and patient studies. From the measurement, analysis, and correction of machine‐related geometric distortions in MRI, it was concluded that MR image corrections are necessary in applications which require mm accuracy and that correction methods, based on 3D maps of static field inhomogeneity and gradient nonlinearity, are feasible in clinical practice. From the measurement and numerical analysis of object‐related geometric distortions, it was concluded that these distortions can be reduced to the order of the pixel size by imaging at 0.5 T and using gradients on the order of 3 mT normalm−1. Furthermore, in a study on volunteers, fast MRI scan techniques were used to measure the respiration induced kidney movement and in a study on patients with prostate cancer, the value of MRI for the evaluation of brachytherapy was demonstrated. The MR image artifacts induced by the I‐125 seeds were used to evaluate the dose distributions and dose volume histograms of permanent prostate implants.

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Fast Field Echo imaging: An overview and contrast calculations

Cited by 119 publications

References 7 publications

Signal formation in echo-shifted sequences

Signal formation in echo-shifted sequences

Generation of brain pseudo‐CTs using an undersampled, single‐acquisition UTE‐mDixon pulse sequence and unsupervised clustering

Magnetic resonance imaging in radiotherapy treatment planning

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