Internal carotid-artery stenosis (ICAS) causes complex and not yet well understood physiological impairments. We present preliminary data from an ongoing clinical study in ICAS patients and healthy, age-matched participants. The major aims were to evaluate the reliability of a multimodal MRI-protocol and investigate physiological changes. For ICAS patients, regionally impaired vascular-reactivity as well as hypo-perfusion were found. In accordance with literature, we did not find ICAS-induced changes in oxygen extraction on group level. The presented preliminary results thus imply successful application of multimodal MRI methods and are highly promising with respect to gaining a deeper insight into ICAS-related physiological changes.
In the ongoing clinical study, 52 subjects (29 healthy: 70.3±4.7y, 13 males; 23 patients: 70.5±6.8y, 15 males, with asymptomatic unilateral high-grade ICAS, NASCET>70%) underwent MRI on a clinical Philips 3T Ingenia MR-Scanner (Philips Healthcare, Best, Netherlands), using a 16ch head/neck-coil for clinical- and 32ch head-coil for functional-imaging. The protocol comprised measurements of CVR, CBF and rOEF (Fig.1). CVR was measured by a breathhold-fMRI scheme16 using single-shot EPI-readout (voxelsize 3x3x3mm3, 38 slices, Multiband/SENSE=2/2, TE=30ms, TR=1200ms, acq.time=5:48min). Processing was implemented using a data-driven approach9. Non-invasive perfusion mapping was performed by pCASL using a segmented 3D GraSE-readout (voxelsize 2.7x2.8x6mm3, 16 slices, TE=7.4ms, TR=4403ms, label duration=1800ms, PLD=2000ms, background suppression, 3 repetitions, including proton-density-weighted M0 normalization, acq.time 5:43min). CBF was calculated following the ISMRM perfusion study group white-paper with λ=0.9ml/g and labeling efficiency α=0.8510. rOEF-mapping (voxelsize 2x2x3mm3, 30 slices) was performed using the multi-parametric qBOLD approach12,13 acquiring a multi-echo GraSE (8 echos, TE1=∆TE=16ms, TR=8971ms, acq.time 2:24min) and multi-GE sequence (12 echoes, TE1=∆TE=5ms, TR=1950ms, α=30°, rapid flyback gradients, acq.time 6:08min) for T2- and T2*-mapping12. rOEF-calculation requires measurement of relative cerebral blood volume (rCBV), obtained by dynamic susceptibility contrast (DSC)11 using a bolus-injection of 15ml Gd-DTPA and single-shot GE-EPI-readout (TE=30ms, TR=1516ms, α=60°, 80 repetitions) after a carotid artery angiography with 17ml Gd-DTPA. Processing was performed with SPM1217 and custom Matlab programs18. For each participant, individual masks of watershed areas were defined for both hemispheres using DSC-based Time-to-Peak (TTP) maps. In selected cases, superselective-pCASL (ss-ASL) of both internal carotid arteries was used to verify individual collateralizations19. Parameter mean values were compared by Bland-Altman plots20.
Figure 2 shows exemplary data from a right-sided ICAS patient. For statistical analysis, low quality parameter maps were excluded according to ratings (SK, CP)22. CVR revealed good symmetry in healthy participants, but showed ipsilateral decreases for ICAS patients (Fig.3). CBF-maps show a similar behavior, demonstrating a clear hypo-perfusion within the affected hemisphere of ICAS patients (Fig.4). Analysis of rOEF maps yielded good symmetry between hemispheres for both healthy participants and in ICAS patients (Fig.5). Thus, our preliminary data demonstrate ICAS induced ipsilateral CVR and CBF decreases while rOEF appear unaffected.
These preliminary results show that breathhold-fMRI and pCASL can detect the expected hemodynamic symmetry in healthy participants. In ICAS patients, breathhold-fMRI and pCASL enable the reliable detection of the expected impairments of CVR and perfusion. With regard to rOEF, there is no easy conclusion: while it appears unchanged on a global scale, single cases seem to show more focal changes, clearly requiring further investigations. In summary, our results show that multimodal MRI can assist in gaining a deeper knowledge on physiological changes induced by cerebrovascular diseases.
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Figure 1: Overview of analyzed modalities and resulting parameters. Breathhold-fMRI (BH-fMRI) for CVR-mapping consists of an EPI time-series with five periods of alternating normal-breathing and 15sec breathhold to induce hypercapnia16. The applied data-driven analysis identifies predefined vascular territories showing the highest correlation between BOLD-signal (blue) and respiratory-response-function (red). Using this, a new regressor is defined and applied to the whole brain, generating correlation-based CVR-maps9. CBF-maps are acquired by pCASL using 3D-GraSE with a normalization image according to recent recommendations10. The multi-parametric qBOLD approach requires DSC-based rCBV-maps and T2- and T2*-quantification to calculate rOEF11,12.