A diffusion-compensated model for the analysis of DCE-MRI data: theory, simulations and experimental results

Fluckiger, Jacob U.; Loveless, Mary E.; Barnes, Stephanie L.; Lepage, Martin; Yankeelov, Thomas E.

doi:10.1088/0031-9155/58/6/1983

Cited by 25 publications

(63 citation statements)

References 29 publications

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“…In general the tumor vasculature, even in the well perfused region, is chaotic and poorly functional [40] and regions of hypoxia can co-exist with vasculature within the volume of an MRI voxel (390 μm × 390 μm × 1000 μm in this case). Similarly, agents that are non-specific for hypoxia also accumulate in hypoxic or necrotic regions by passive diffusion and demonstrate enhanced retention [41]. Indeed, GdDTPA (non-hypoxia specific clinical contrast agent) based pharmacokinetic parameters have been shown to correlate with hypoxia [42].…”

Section: Discussionmentioning

confidence: 99%

GdDO3NI, a nitroimidazole-based T 1 MRI contrast agent for imaging tumor hypoxia in vivo

et al. 2013

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Tumor hypoxia is known to affect sensitivity to radiotherapy and promote development of metastases. Therefore the ability to image tumor hypoxia in vivo could provide useful prognostic information and help tailor therapy. We previously demonstrated in vitro evidence for selective accumulation of GdDO3NI (GdDOTA monoamide conjugate of 2-nitroimidazole), a magnetic resonance imaging (MRI) T1 shortening agent, in hypoxic cells grown in tissue culture. We now report in vivo evidence for accumulation of GdDO3NI, in hypoxic tumor tissue in vivo. Our data show that GdDO3NI accumulated significantly (p<0.05) in the central, poorly perfused regions of rat prostate adenocarcinoma AT1 tumors (3-fold higher concentration than control agent) and showed better clearance from well-perfused regions and completely clearance from the surrounding muscle tissue. Inductively coupled plasma mass spectroscopy (ICP-MS) confirmed that more GdDO3NI was retained in the central region compared to either the periphery or the control agent. These results show the utility of GdDO3NI to image tumor hypoxia and highlight the potential of GdDO3NI for application to image guided interventions for radiation or hypoxia activated chemo therapy.

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Section: Discussionmentioning

confidence: 99%

GdDO3NI, a nitroimidazole-based T 1 MRI contrast agent for imaging tumor hypoxia in vivo

et al. 2013

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“…Inter-voxel contrast agent diffusion has been the subject of simulation and experimental research that modifies the Tofts pharmacokinetic model [12,13]. Simulation of diffusion characteristics and contrast agent diffusion's associated effect on capillary permeability has also been the subject of research [14].…”

Section: Introductionmentioning

confidence: 99%

A Metric for Reducing False Positives in the Computer-Aided Detection of Breast Cancer from Dynamic Contrast-Enhanced Magnetic Resonance Imaging Based Screening Examinations of High-Risk Women

et al. 2015

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Magnetic resonance imaging (MRI)-enabled cancer screening has been shown to be a highly sensitive method for the early detection of breast cancer. Computer-aided detection systems have the potential to improve the screening process by standardizing radiologists to a high level of diagnostic accuracy. This retrospective study was approved by the institutional review board of Sunnybrook Health Sciences Centre. This study compares the performance of a proposed method for computer-aided detection (based on the second-order spatial derivative of the relative signal intensity) with the signal enhancement ratio (SER) on MRI-based breast screening examinations. Comparison is performed using receiver operating characteristic (ROC) curve analysis as well as free-response receiver operating characteristic (FROC) curve analysis. A modified computer-aided detection system combining the proposed approach with the SER method is also presented. The proposed method provides improvements in the rates of false positive markings over the SER method in the detection of breast cancer (as assessed by FROC analysis). The modified computer-aided detection system that incorporates both the proposed method and the SER method yields ROC results equal to that produced by SER while simultaneously providing improvements over the SER method in terms of false positives per noncancerous exam. The proposed method for identifying malignancies outperforms the SER method in terms of false positives on a challenging dataset containing many small lesions and may play a useful role in breast cancer screening by MRI as part of a computer-aided detection system.

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“…The diffusion‐corrected model improves on the Tofts model by including a diffusion term when calculating the changes in concentration as a function of time . In this study, because IAs are surrounded by the pial surface of the cerebral cortex, remote from white matter, we are able to reduce the computational complexity by approximating the diffusion rate ( D ) to be uniform in the extravascular space as follows:

C_{D C} (normalt) = k^{t r a n s} {true \int}_{0}^{t} e^{- k_{e p} (t - τ)} C_{p} (τ) d τ + v_{p} C_{p} (t) + {true \int}_{0}^{t} \underset{N}{true \sum} \frac{bold-italicD}{{bold-italica}^{2}} (\frac{{bold-italicC}_{bold-italicN} (bold-italicτ)}{{bold-italicv}_{e N}} - \frac{{bold-italicC}_{bold-italici} (bold-italicτ)}{{bold-italicv}_{e i}}) d τ

where C DC is the diffusion‐compensated tracer concentration, a is the in‐plane voxel length, D is the voxel‐specific diffusion constant, and C is the measured concentration.…”

Section: Methodsmentioning

confidence: 99%

“…Previous work by Fluckiger and Pellerin demonstrated that estimating kinetic parameters in the presence of passive contrast diffusion improved physiologic representation and reduced the likelihood of returning unphysical v e values. We apply a diffusion‐compensated Tofts model (DC‐Tofts) to analyze contrast kinetics at the surface of an IA wall.…”

Section: Introductionmentioning

confidence: 99%

Diffusion‐compensated tofts model suggests contrast leakage through aneurysm wall

Cantrell

Vakil

Jeong

et al. 2017

Magnetic Resonance in Med

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Purpose The purpose of this study was to investigate the diffusional transport of contrast agent and its effects on kinetic modeling of Dynamic Contrast Enhanced (DCE) images. Methods We performed simulations of our diffusion-compensated model and compared these results to human intracranial aneurysms (IAs). We derive an easy to use parameterization of diffusional effects that can provide an accurate estimate of diffusion corrected contrast agent leakage rates (ktrans). Finally, we performed re-analysis of an existing dataset to determine if diffusion-corrected kinetic parameters improve the identification of high-risk IAs, thereby providing a new MRI-based imaging metric of IA stability based on wall integrity. Results Probability distributions of simulated vs. measured data show contrast leakage away from the aneurysm wall. Parameterization of diffusional effects on ktrans showed high correlation with long-chain methods in both surrounding tissue and near the aneurysm wall (r2 = 0.91 and r2=0.90 respectively). Finally, size, ktrans, and (ktrans−ktransDC) showed significant univariate relationships with rupture risk (p<0.05). Conclusions We report the first evidence of diffusion-compensated permeability-modeling in intracranial aneurysms and propose a parameterization of diffusional effects on ktrans. Furthermore, a comparison of measured against simulated data suggests contrast leakage occurs across the aneurysm wall.

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A diffusion-compensated model for the analysis of DCE-MRI data: theory, simulations and experimental results

Cited by 25 publications

References 29 publications

GdDO3NI, a nitroimidazole-based T 1 MRI contrast agent for imaging tumor hypoxia in vivo

GdDO3NI, a nitroimidazole-based T 1 MRI contrast agent for imaging tumor hypoxia in vivo

A Metric for Reducing False Positives in the Computer-Aided Detection of Breast Cancer from Dynamic Contrast-Enhanced Magnetic Resonance Imaging Based Screening Examinations of High-Risk Women

Diffusion‐compensated tofts model suggests contrast leakage through aneurysm wall

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