Rationale and Objectives
The aim of this study was to evaluate the feasibility of quantitative analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data in the detection of bowel inflammation in patients with Crohn’s disease.
Materials and Methods
Eleven patients who underwent magnetic resonance enterography for known or suspected Crohn’s disease and had colonoscopy or surgery within 4 weeks of imaging were included in this study. DCE-MRI data were acquired using a 1.5-T scanner with temporal resolution of 5 to 12 seconds for approximately 5 to 7 minutes. A two-compartment pharmacokinetic model was used to analyze the data to obtain the volume transfer constant ( K trans ) and the extravascular extracellular space ( v e ). Additionally, semiquantitative parameters were derived using an empirical mathematical model to fit the contrast concentration curves. Endoscopic, surgical, and pathologic results were compared to the MRI data. Receiver-operating characteristic analysis was performed to compare the diagnostic accuracy of the parameters in the task of distinguishing normal tissue from inflammation.
Results
A total of 51 bowel segments (19 with inflammation, 32 normal) were included in the analyses. Inflamed bowel segments had faster K trans values, larger v e values, increased contrast uptake, larger initial areas under the contrast concentration curve, and steeper initial enhancement slopes than normal bowel segments ( P < .05). The areas under the receiver-operating characteristic curve for these parameters ranged from 0.70 to 0.86.
Conclusion
These preliminary results demonstrate that the quantitative analysis of DCE-MRI data is possible for the assessment of bowel inflammation in patients with Crohn’s disease. Future studies need be performed on larger numbers of patients to correlate the severity and type of inflammation with kinetic parameters.
Crohn’s disease is a chronic inflammatory disease of unknown origin affecting the entire gastrointestinal tract, with a remitting and relapsing course. Cross-sectional imaging techniques are commonly used during the course of the disease for the determination of its extent and severity, detection of complications, and planning of therapy . Traditionally, computed tomography has been the predominant cross-sectional imaging technique in patients with Crohn’s disease because of its proven efficacy in the evaluation of intestinal diseases and extraintestinal complications . Recently, magnetic resonance (MR) imaging (MRI) has emerged as a valuable tool in the detection of bowel abnormalities and evaluation of disease activity in Crohn’s disease .
MRI has several advantages compared to computed tomography, including a lack of ionizing radiation, superior contrast resolution of soft tissue, and the ability to perform real-time and functional imaging. In addition to fast T2-weighted sequences, dynamic contrast-enhanced (DCE) T1-weighted gradient-echo sequences are also routinely performed to evaluate bowel inflammation . MRI strongly correlates with conventional enteroclysis in the detection of individual lesions of small intestinal Crohn’s disease and provides additional information from the mesenteries . Gadolinium enhancement of inflamed bowel wall segments in Crohn’s disease has been described as a sensitive measurement for the detection of inflammation . Several studies have also suggested a correlation between clinical disease activity and the enhancement level of the bowel wall . In these studies, the enhancement pattern of the bowel has been assessed either qualitatively or semiquantitatively . To our knowledge, a pharmacokinetic model to quantitatively analyze DCE-MRI data has not previously been applied to bowel inflammation. In other organs, the quantitative analysis of DCE-MRI data is a widely accepted reliable technique for monitoring the effects of antiangiogenic cancer drugs and allows for a more robust and reproducible analysis of tissue enhancement . This noninvasive method can be potentially applied to the gastrointestinal tract to provide quantification of bowel wall perfusion and permeability, which can be used to localize inflamed bowel segments, monitor disease activity, and evaluate the response to treatment without exposing patients to ionizing radiation. A variety of research and clinical scoring tools have been used to address these issues, such as the Crohn’s disease activity index, biologic indices, and endoscopic and imaging studies. However, there remains no established reference standard that accurately provides all this information.
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Materials and methods
Patients
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MRI Protocol
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Quantitative Pharmacokinetic Model Analysis of DCE-MRI Data
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dC(t)dt=Ktrans×[Cp(t)−C(t)/ve], d
C
(
t
)
d
t
=
K
trans
×
[
C
p
(
t
)
−
C
(
t
)
/
v
e
]
,
where K trans (min −1 ) is the volume transfer constant between intravascular extracellular space and EES, v e is the volume of EES per unit volume of tissue, and C p ( t ) is the arterial input function. The contrast concentration curves as function of time were converted from the signal intensity curves for each region of interest (ROI) using an approximation formula published previously, with muscle as a reference tissue and longitudinal relaxivity of r 1 = 4.5 mmol/L −1 · s −1 for gadolinium diethylenetriamine penta-acetic acid at 1.5 T . Subsequently, the arterial input function was obtained from the ROI of aortic contrast concentration, C a ( t ), for each patient using C p ( t ) = C a ( t )/(1 − hematocrit), with hematocrit = 0.45, to correct for hematocrit.
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Model Free Empirical Mathematical Analysis
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C(t)=A×(1−e−αt)q×e−βt, C
(
t
)
=
A
×
(
1
−
e
−
α
t
)
q
×
e
−
β
t
,
where A is the upper limit of the tracer concentration, α is the rate of contrast uptake (min −1 ), β is the rate of contrast washout (min −1 ) (with β > 0 indicating that the curve exhibits washout rather than plateau or persistent contrast uptake), and q is related to the slope of early uptake. Prior studies have shown that the EMM provides an accurate fit to DCE-MRI kinetic data acquired from breast lesions .
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Semiquantitative Analysis Parameters
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IAUC
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IAUC=∫0τA×(1−e−αt)q×e−βtdt. IAUC
=
∫
0
τ
A
×
(
1
−
e
−
α
t
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q
×
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−
β
t
d
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A value of τ = 1 minute was selected for this study.
Slopeini S
l
o
p
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i
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i
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slopeini=A×(1−e−α)q×e−β. s
l
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p
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i
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i
=
A
×
(
1
−
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q
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.
Tpeak T
p
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a
k
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Tpeak=1αlog(1+qαβ). T
peak
=
1
α
log
(
1
+
q
α
β
)
.
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Data Analysis and Statistical Evaluation
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Results
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Table 1
Summary of Kinetic Parameters Calculated from the TCM, the EMM, and Semiquantitative Parameters for Normal ( n = 32) and Abnormal ( n = 19) Bowel Segments
Parameter Normal Abnormal_P_ TCM_K_ trans 0.49 ± 0.36 0.81 ± 0.60 .05 ∗ v e 0.25 ± 0.12 0.36 ± 0.12 .001 ∗ R 2 0.76 ± 0.13 0.80 ± 0.18 .46 EMM_A_ 1.69 ± 1.18 3.21 ± 1.45 .004 ∗ q 2.5 ± 2.1 1.59 ± 1.27 .07 α 3.51 ± 2.90 3.33 ± 2.49 .81 β 0.034 ± 0.080 0.026 ± 0.120 .77R 2 0.80 ± 0.12 0.89 ± 0.12 .02 ∗ Semiquantitative analysis IAUC 0.85 ± 0.59 1.70 ± 0.74 .0002 ∗ T peak 3.0 ± 1.7 3.9 ± 2.8 .18 slope ini 1.32 ± 0.87 2.56 ± 1.27 .001 ∗
A , contrast uptake; α, rate of contrast uptake; β, rate of contrast washout; EMM, empirical mathematical model; IAUC, initial area under the curve; K trans , volume transfer constant; q , related to the slope of early uptake; slope ini , initial slope of enhancement; TCM, two-compartment model; T peak , time to peak enhancement; v e , extravascular extracellular space volume.
Data are expressed as mean ± standard deviation for all cases.
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Discussion
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