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

Bisdas

Magnetic Resonance Imaging

et al. 2011

113

130

Tracer kinetic methods employed for quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) share common roots with earlier tracer studies involving arterial-venous sampling and other dynamic imaging modalities. This article reviews the essential foundation concepts and principles in tracer kinetics that are relevant to DCE MRI, including the notions of impulse response and convolution, which are central to the analysis of DCE MRI data. We further examine the formulation and solutions of various compartmental models frequently used in the literature. Topics of recent interest in the processing of DCE MRI data, such as the account of water exchange and the use of reference tissue methods to obviate the measurement of an arterial input, are also discussed. Although the primary focus of this review is on the tracer models and methods for T 1 -weighted DCE MRI, some of these concepts and methods are also applicable for analysis of dynamic susceptibility contrastenhanced MRI data.

Section: Reference Region (Rr) Methodsmentioning

confidence: 99%

Fundamentals of tracer kinetics for dynamic contrast‐enhanced MRI

Bisdas

Magnetic Resonance Imaging

et al. 2011

113

130

“…This linearity can be assumed to be valid for other scanners and scan protocols. Differences in the choice of time points in the acquisition protocol can infl uence the accuracy with which model parameters are determined and may lead to a bias ( 35,36 ). Changes in injection protocol may have a similar effect (36)(37)(38), even though the AIF is explicitly taken into account in the analysis.…”

Section: Roi Analysis Parametersmentioning

confidence: 99%

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

Korporaal

Berg²,

Jeukens³

et al. 2010

Radiology

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

“…The main rationale of our approach was to avoid unreliability and inaccuracy of the PK‐model‐based method. It has been established that wide variability in estimating arterial input function leads to substantial deviations in calculating TP and BV parameters 45, 46. Moreover, PK modeling is significantly influenced by B 1 field inhomogeneity.…”

Section: Discussionmentioning

confidence: 99%

Spatiotemporal heterogeneity of tumor vasculature during tumor growth and antiangiogenic treatment: MRI assessment using permeability and blood volume parameters

et al. 2018

Tumor heterogeneity is an important concept when assessing intratumoral variety in vascular phenotypes and responses to antiangiogenic treatment. This study explored spatiotemporal heterogeneity of vascular alterations in C6 glioma mice during tumor growth and antiangiogenic treatment on serial MR examinations (days 0, 4, and 7 from initiation of vehicle or multireceptor tyrosine kinase inhibitor administration). Transvascular permeability (TP) was quantified on dynamic‐contrast‐enhanced MRI (DCE‐MRI) using extravascular extracellular agent (Gd‐DOTA); blood volume (BV) was estimated using intravascular T2 agent (SPION). With regard to region‐dependent variability in vascular phenotypes, the control group demonstrated higher TP in the tumor center than in the periphery, and greater BV in the tumor periphery than in the center. This distribution pattern became more apparent with tumor growth. Antiangiogenic treatment effect was regionally heterogeneous: in the tumor center, treatment significantly suppressed the increase in TP and decrease in BV (ie, typical temporal change in the control group); in the tumor periphery, treatment‐induced vascular alterations were insignificant and BV remained high. On histopathological examination, the control group showed greater CD31, VEGFR2, Ki67, and NG2 expression in the tumor periphery than in the center. After treatment, CD31 and Ki67 expression was significantly suppressed only in the tumor center, whereas VEGFR2 and α‐caspase 3 expression was decreased and NG2 expression was increased in the entire tumor. These results demonstrate that MRI can reliably depict spatial heterogeneity in tumor vascular phenotypes and antiangiogenic treatment effects. Preserved angiogenic activity (high BV on MRI and high CD31) and proliferation (high Ki67) in the tumor periphery after treatment may provide insights into the mechanism of tumor resistance to antiangiogenic treatment.