T1 measurement of flowing blood and arterial input function determination for quantitative 3D T1‐weighted DCE‐MRI

Cheng, Hai‐Ling Margaret

doi:10.1002/jmri.20898

Cited by 73 publications

(78 citation statements)

References 20 publications

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“…The size of this component is approximately 0.02 min ) ( 3-5,32 ). These differences in absolute K trans may be owing to differences in imaging protocol and problems with absolute quantifi cation (12)(13)(14)(15).…”

Section: Roi Analysis Parametersmentioning

confidence: 99%

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Dynamic Contrast-enhanced CT for Prostate Cancer: Relationship between Image Noise, Voxel Size, and Repeatability

Korporaal

Berg²,

Jeukens³

et al. 2010

Radiology

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Purpose:To evaluate the relationship between image noise, voxel size, and voxel-wise repeatability of a dynamic contrast agent-enhanced (DCE) computed tomographic (CT) examination for prostate cancer. Materials and Methods:This prospective study was approved by the local research ethics committee, and all patients gave written informed consent. Twenty-nine patients (mean age, 69.1 years; range, 56-80 years) with biopsy-proved prostate cancer underwent two DCE CT examinations within 1 week prior to radiation therapy. Parameter maps of transfer constant ( K trans ), the fraction of blood plasma (v p ) , the fraction of extravascular extracellular space (v e ) , and the fl ux rate constant between the extravascular extracellular space and plasma ( k ep ) were calculated at 15 different image resolutions, with kernel sizes ranging from 0.002 to 2.57 cm 3 . Statistical analysis to quantify the voxel-wise repeatability was performed by using a Bland-Altman analysis on all tracer kinetic model parameter maps of each patient. From this analysis, the within-voxel standard deviation (wSD) was calculated as a function of spatial resolution. Results:A kernel size in the range of 0. Conclusion:There is a high voxel-wise repeatability of the DCE CT imaging technique for prostate cancer for kernel sizes as small as 0.1 cm 3 . With the relationship between kernel size, image noise and voxel-wise repeatability, it becomes possible to estimate for alternative DCE CT protocols (eg, those with a reduced radiation dose) at what kernel size a suffi cient repeatability can be obtained.q RSNA, 2010

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Section: Roi Analysis Parametersmentioning

confidence: 99%

“…However, quantifi cation of DCE MR imaging data is diffi cult because of the complex relation between the signal intensity and the concentration of the contrast agent in tissue ( 12 ). In particular, the determination of the arterial input function (AIF) required for tracer kinetic modeling can be unreliable (13)(14)(15).…”

mentioning

confidence: 99%

Dynamic Contrast-enhanced CT for Prostate Cancer: Relationship between Image Noise, Voxel Size, and Repeatability

Korporaal

Berg²,

Jeukens³

et al. 2010

Radiology

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“…Even when rapid sampling is achieved, the measured blood concentration during the initial bolus is not necessarily accurate. The reason is that in addition to inflow (9) and partial volume (10) that affect the entire AIF time course, the initial bolus is further affected by saturation effects and is more sensitive to mis-sampling. Finally, it should be recognized that regardless of how accurately an AIF measurement is made, DCE-MRI quantification will be significantly influenced by the delay and dispersion the AIF undergoes when it reaches the local tissue region of interest (11), and by the mean capillary transit time for the contrast agent to pass through the vascular bed.…”

mentioning

confidence: 99%

Investigation and optimization of parameter accuracy in dynamic contrast‐enhanced MRI

Cheng

2008

Magnetic Resonance Imaging

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Purpose: To present a modified pharmacokinetic model for improved parameter accuracy and to investigate the influence of an inaccurate arterial input function (AIF) on dynamic contrast-enhanced (DCE)-MRI parameter estimates of the transfer constant (K trans ), blood volume (v p ), and interstitial volume (v e ). Materials and Methods:Tissue uptake curves were simulated over a large range of physiological values and analyzed for different AIF measurement errors and temporal resolutions. The AIF measurement was assumed to be inaccurate in the bolus amplitude (rapid sampling) or susceptible to unknown temporal offsets (slow sampling with biexponential decay fit). Results:The modified model adequately reduces errors in parameter estimates arising from transit time effects. An error in the AIF bolus amplitude results in an inversely proportional error in K trans and v p ; v e remains robust. More consistent error in K trans (Ϸ20% underestimation) was obtained using a biexponential AIF, at the expense of severely underestimating v p . Conclusion:While an accurate, high temporal resolution AIF is essential for estimating v p , a biexponential AIF acquired at low temporal resolution (Ͻ20 seconds) provides robust estimates of v e and results in a K trans underestimation comparable to that from a 25% error in the initial AIF bolus amplitude. DYNAMIC CONTRAST-ENHANCED (DCE)-MRI for characterizing tissue uptake of a contrast agent is an established method for assessing microcirculation physiology. It is relevant in studying a wide range of diseases and conditions, including cancer (1), ischemia (2), and inflammation (3). Quantitative parameters directly related to underlying physiological properties, such as vessel permeability, perfusion, and blood volume, may be obtained by applying a pharmacokinetic model to the DCE-MRI data (4). This physiology-based information is beneficial in a number of ways, from improving cancer diagnostic sensitivity and specificity to elucidating microvascular changes that accompany novel anticancer therapies. However, the degree to which measured parameters represent true physiology is influenced by a number of factors, and accurate DCE-MRI quantification remains challenging (5).A problematic but necessary requirement for quantitative DCE-MRI is measurement of the arterial input function (AIF), or contrast agent concentration time course in the blood pool. The simplest approach is to use a standard AIF (6), but this may differ from the individual's input function, and large errors in pharmacokinetic parameter estimates have been reported (7). The ideal approach is to obtain individual measurements. This, however, is beset by a number of challenges. One challenge is achieving a high temporal resolution (1 second) to capture rapid changes during the initial bolus passage, which is believed to be essential for reliable DCE-MRI quantification (8). Despite the availability of faster scanners and parallel imaging, a lower temporal resolution is often used due to competing demands for high spatial res...

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“…Numerous methods exist for the implementation of each of the above steps: T1 and M 0 maps can be acquired with several techniques; [3][4][5][6] different mathematical models can be used to analyze the dynamic data; [7][8][9][10][11][12][13][14] and finally, various pulse sequences differing in sampling strategies and acquisition parameters have been developed to sample the signal in k-space. [15][16][17][18] The vast majority of preclinical sampling strategies used for DCE-MRI acquire a limited number of relatively thick slices.…”

Section: Introductionmentioning

confidence: 99%

A comparison of radial keyhole strategies for high spatial and temporal resolution 4D contrast-enhanced MRI in small animal tumor models

et al. 2013

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Purpose: Dynamic contrast-enhanced (DCE) MRI has been widely used as a quantitative imaging method for monitoring tumor response to therapy. The simultaneous challenges of increasing temporal and spatial resolution in a setting where the signal from the much smaller voxel is weaker have made this MR technique difficult to implement in small-animal imaging. Existing protocols employed in preclinical DCE-MRI acquire a limited number of slices resulting in potentially lost information in the third dimension. This study describes and compares a family of four-dimensional (3D spatial + time), projection acquisition, radial keyhole-sampling strategies that support high spatial and temporal resolution. Methods: The 4D method is based on a RF-spoiled, steady-state, gradient-recalled sequence with minimal echo time. An interleaved 3D radial trajectory with a quasi-uniform distribution of points in k-space was used for sampling temporally resolved datasets. These volumes were reconstructed with three different k-space filters encompassing a range of possible radial keyhole strategies. The effect of k-space filtering on spatial and temporal resolution was studied in a 5 mM CuSO 4 phantom consisting of a meshgrid with 350-μm spacing and in 12 tumors from three cell lines (HT-29, LoVo, MX-1) and a primary mouse sarcoma model (three tumors/group). The time-to-peak signal intensity was used to assess the effect of the reconstruction filters on temporal resolution. As a measure of heterogeneity in the third dimension, the authors analyzed the spatial distribution of the rate of transport (K trans ) of the contrast agent across the endothelium barrier for several different types of tumors. Results: Four-dimensional radial keyhole imaging does not degrade the system spatial resolution. Phantom studies indicate there is a maximum 40% decrease in signal-to-noise ratio as compared to a fully sampled dataset. T1 measurements obtained with the interleaved radial technique do not differ significantly from those made with a conventional Cartesian spin-echo sequence. A bin-by-bin comparison of the distribution of the time-to-peak parameter shows that 4D radial keyhole reconstruction does not cause significant temporal blurring when a temporal resolution of 9.9 s is used for the subsamples of the keyhole data. In vivo studies reveal substantial tumor heterogeneity in the third spatial dimension that may be missed with lower resolution imaging protocols. Conclusions: Volumetric keyhole imaging with projection acquisition provides a means to increase spatiotemporal resolution and coverage over that provided by existing 2D Cartesian protocols. Furthermore, there is no difference in temporal resolution between the higher spatial resolution keyhole reconstruction and the undersampled projection data. The technique allows one to measure complex heterogeneity of kinetic parameters with isotropic, microscopic spatial resolution.

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T₁ measurement of flowing blood and arterial input function determination for quantitative 3D T₁‐weighted DCE‐MRI

Cited by 73 publications

References 20 publications

Dynamic Contrast-enhanced CT for Prostate Cancer: Relationship between Image Noise, Voxel Size, and Repeatability

Dynamic Contrast-enhanced CT for Prostate Cancer: Relationship between Image Noise, Voxel Size, and Repeatability

Investigation and optimization of parameter accuracy in dynamic contrast‐enhanced MRI

A comparison of radial keyhole strategies for high spatial and temporal resolution 4D contrast-enhanced MRI in small animal tumor models

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