Charles G Cantrell1, Parmede Vakil1,2, Sameer A Ansari3, and Timothy J Carroll1,3
1Biomedical Engineering, Northwestern, Chicago, IL, United States, 2College of Medicine, University of Illinois, Chicago, IL, United States, 3Radiology, Northwestern, Chicago, IL, United States
Synopsis
We report the first evidence of diffusion corrected DCE-MRI modeled contrast permeability in intracranial aneurysms and show the diffusion model more accurately represents physiology than previous methods. Permeability metrics, as measured in 23 patients, demonstrate a statistically significant trend with rupture risk as defined by anatomic imaging and clinical risk factors. Introduction
Intracranial aneurysms (IA) affect
2-6% of the population [1]. Rupture of IA carries a mortality rate of 50%
and devastates the lives of many otherwise young healthy people who survive
rupture. Unruptued IAs are often discovered incidentally and, given the inherent
risks associated with surgical clipping or coiling, treatment remains
controversial. The search for a “smoking
gun” biomarker that predicts IA rupture conducted over the last fifteen years has, to date, been unsuccessful. The purpose of this study was to quantify IA wall
permeability (k
trans,v
L)
to contrast agent utilizing a diffusion corrected Tofts’ model [2]. While previous
work has shown k
trans
to be associated with wall thinning and IA rupture risk, as defined by various
anatomic, imaging and clinical risk factors, it employed a Tofts’ based
permeability model [3]. For aneurysmal
modelling, a diffusion model [4] more accurately represents physiology and
provides better resolution for determining wall thickness and potential bleb
formation zones.
Methods
We
employ a finite element model (FEM), to quantify leakage and compare to more
traditional Tofts modeling. The FEM model improves on the permeability limited
modified Tofts model by allowing contrast to flow from regions of high
concentration towards low concentrations: $$ \frac{dC(t)}{dt}= k^{trans}C_{p}(t)-k^{trans}\frac{C_{p}(t)}{v_{l}}+\sum_N(\frac{D_i+D_N}{2})\frac{1}{a^2}(\frac{C_N(t)}{v_{lN}}-\frac{C_i(t)}{v_{li}})+v_pC_p(t) $$ K
trans and v
L
were evaluated as markers of rupture risk by comparing against established
clinical (symptomatic lesions) and anatomic (size, location, morphology,
multiplicity) risk metrics and evaluated against values obtained through
utilization of the permeability limited Tofts’ Model. One patient opted out of surgical
intervention and was imaged 18 months after initial evaluation.
Patient Studies
Twenty-seven symptomatic, unruptured IAs in 23
patients (M/F, 10/13, <age> = 60.7 ± 12.3) were imaged with DCE-MRI, and
wall permeability parameters (k
trans,
v
L) were calculated in regions adjacent to the aneurysm wall. K
trans and v
L
were calculated using both a Tofts’ permeability model as described in [2] and
a finite-element diffusion model. Correlation and mean values where compared to
test the hypothesis that FEM analysis corrects for parenchymal diffusion of the
contrast agent. Statistical significance was defined at the 5% level.
Results
All IAs had a pronounced increase in wall
permeability compared to the paired healthy MCA (p<0.001). Regression
analysis demonstrated a significant trend toward increased k
trans
with increasing aneurysm size (p<0.05).
Diffusion corrected k
trans and v
l values correlate
strongly with the Tofts’ Model (p<.001) (Figure 1a-b). Diffusion corrected values showed greater
permeability distinction between aneurysm wall and healthy vessel (p<.001)
(Figure 1d)
Conclusions
We report the first evidence of diffusion corrected
DCE-MRI modeled contrast permeability in IAs. We found contrast agent
permeability across the aneurysm wall correlated significantly with both
aneurysm size as well as size-independent anatomic risk factors. Moreover, we note the diffusion correction
shows greater distinction between permeable regions (i.e. leaky aneurysmal
wall) and healthy tissue which can been seen in figure (1d). Additionally we see, in figure (1a-c),
distinct regions of faster leakage even within a single aneurysm. Intuitively this makes sense, as we know
physiologically aneurysms can be non-uniform.
Not all aneurysms show a great discrepancy between model methods,
however. Figure 2 shows a 61 year old
male who decided to forgo surgical intervention. For this anecdotal case, both methods
provided similar results that lined up exceptionally well with future bleb
formation.
Acknowledgements
NIH/NIBIB T32
EB005170, NIH/NHLBI R01 HL088437, AHA 14PRE20380810References
[1] Weir, JNS 2002 [2] Vakil,
AJNR 2014, [3] Tofts, JMRI, 1999, [4] Fluckiger, Phys Med Bio, 2013