Pituitary adenylate cyclase-activating polypeptide-38 (PACAP38) and vasoactive intestinal polypeptide are structurally and functionally closely related but show differences in migraine-inducing properties. Mechanisms responsible for the difference in migraine induction are unknown. Here, for the first time, we present a head-to-head comparison study of the immediate and long-lasting observations of the migraine-inducing, arterial, physiological and biochemical responses comparing PACAP38 and vasoactive intestinal polypeptide. In a double-blind crossover study 24 female migraine patients without aura were randomly allocated to intravenous infusion of PACAP38 (10 pmol/kg/min) or vasoactive intestinal polypeptide (8 pmol/kg/min) over 20 min. We recorded incidence of migraine during and after infusion (0-24 h). Magnetic resonance angiography of selected extra- and intracranial arteries, blood samples (plasma PACAP38 and vasoactive intestinal polypeptide and serum tryptase), and vital signs (blood pressure, heart rate, respiratory frequency, and end-tidal pressure of CO2) was recorded before and up to 5 h after infusion. Twenty-two patients [mean age 24 years (range 19-36)] completed the study on both days. Sixteen patients (73%) reported migraine-like attacks after PACAP38 and four after vasoactive intestinal polypeptide (18%) infusion (P = 0.002). Three of four patients, who reported migraine-like attacks after vasoactive intestinal polypeptide, also reported attacks after PACAP38. Both peptides induced marked dilatation of the extracranial (P < 0.05), but not intracranial arteries (P > 0.05). PACAP38-induced vasodilatation was longer lasting (>2 h), whereas vasoactive intestinal polypeptide-induced dilatation was normalized after 2 h. We recorded elevated plasma PACAP38 at 1 h after the start of PACAP38 infusion only in those patients who later reported migraine attacks. Blood levels of vasoactive intestinal polypeptide and tryptase were unchanged after PACAP38 infusion. In conclusion, PACAP38-induced migraine was associated with sustained dilatation of extracranial arteries and elevated plasma PACAP38 before onset of migraine-like attacks. PACAP38 has a much higher affinity for the PAC1 receptor and we therefore suggest that migraine induction by PACAP38 may be because of activation of the PAC1 receptor, which may be a future anti-migraine drug target.

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Migraine with aura is prevalent in high-altitude populations suggesting an association between migraine aura and hypoxia. We investigated whether experimental hypoxia triggers migraine and aura attacks in patients suffering from migraine with aura. We also investigated the metabolic and vascular response to hypoxia. In a randomized double-blind crossover study design, 15 migraine with aura patients were exposed to 180 min of normobaric hypoxia (capillary oxygen saturation 70-75%) or sham on two separate days and 14 healthy controls were exposed to hypoxia. Glutamate and lactate concentrations in the visual cortex were measured by proton magnetic resonance spectroscopy. The circumference of cranial arteries was measured by 3 T high-resolution magnetic resonance angiography. Hypoxia induced migraine-like attacks in eight patients compared to one patient after sham (P = 0.039), aura in three and possible aura in 4 of 15 patients. Hypoxia did not change glutamate concentration in the visual cortex compared to sham, but increased lactate concentration (P = 0.028) and circumference of the cranial arteries (P < 0.05). We found no difference in the metabolic or vascular responses to hypoxia between migraine patients and controls. In conclusion, hypoxia induced migraine-like attacks with and without aura and dilated the cranial arteries in patients with migraine with aura. Hypoxia-induced attacks were not associated with altered concentration of glutamate or other metabolites. The present study suggests that hypoxia may provoke migraine headache and aura symptoms in some patients. The mechanisms behind the migraine-inducing effect of hypoxia should be further investigated.

The accurate assessment of the presence and extent of vascular disease, and planning of vascular interventions based on MRA requires the determination of vessel dimensions. The current standard is based on measuring vessel diameters on maximum intensity projections (MIPs) using calipers. In order to increase the accuracy and reproducibility of the method, automated analysis of the 3D MR data is required. A novel method for automatically determining the trajectory of the vessel of interest, the luminal boundaries, and subsequent the vessel dimensions is presented. The automated segmentation in 3D uses deformable models, combined with knowledge of the acquisition protocol. The trajectory determination was tested on 20 in vivo studies of the abdomen and legs. In 93% the detected trajectory followed the vessel. Determination of the vessel morphology along a vessel segment is important in grading the presence and extent of possible vascular stenoses. Until recently, most examinations of vascular stenoses were carried out using x-ray angiography (XA). This technology has been regarded as the gold standard in the evaluation of stenoses. However, several problems are associated with this imaging modality. First, since XA is a projection technique, overprojection of vessels can occur even if the view angle is set optimally. Second, an ionizing nephrotoxic contrast agent has to be administered by means of a catheter, a technique that is associated with a definite (although relatively small) morbidity and mortality risk. Finally, the patient and the personnel of the catheterization laboratory are exposed to x-ray radiation.Magnetic resonance angiography (MRA), on the other hand, is a technique that produces three-dimensional (3D) images. Consequently, there is no risk of overprojection of vessels. MRA can be applied without the use of a contrast agent, although the signal-to-noise ratio (SNR) increases if a contrast agent is used. This contrast agent is normally administered intravenously, which presents minimal risks to the patient (1,2).MRA data sets are generally evaluated on 2D maximum intensity projections (MIP); however, it is known that this leads to underestimation of the vessel width, and a decreased SNR. The interpretation is carried out by either visual inspection or by caliper measurements (3-7).To improve the conventional analysis of MRA, it would be desirable to obtain quantitative morphological information directly from the 3D images and not from the projections. To accomplish this, accurate 3D segmentation tools are required.Vessel segmentation of 3D images has been investigated by many researchers (8 -16). However, the majority of this research focused on enhancing the 3D visualization of the vascular structures in the image, and not on accurate quantification of these structures.In this work a novel approach for quantitative vessel analysis of MRA images is introduced and validated. The approach uses knowledge about the image acquisition procedure to accurately determine the vessel boundaries. The techniq...

Purpose: To develop and validate an automated segmentation technique for the detection of the lumen and outer wall boundaries in MR vessel wall studies of the common carotid artery. Materials and Methods:A new segmentation method was developed using a three-dimensional (3D) deformable vessel model requiring only one single user interaction by combining 3D MR angiography (MRA) and 2D vessel wall images. This vessel model is a 3D cylindrical Non-Uniform Rational B-Spline (NURBS) surface which can be deformed to fit the underlying image data. Image data of 45 subjects was used to validate the method by comparing manual and automatic segmentations. Vessel wall thickness and volume measurements obtained by both methods were compared.Results: Substantial agreement was observed between manual and automatic segmentation; over 85% of the vessel wall contours were segmented successfully. The interclass correlation was 0.690 for the vessel wall thickness and 0.793 for the vessel wall volume. Compared with manual image analysis, the automated method demonstrated improved interobserver agreement and inter-scan reproducibility. Additionally, the proposed automated image analysis approach was substantially faster. ATHEROSCLEROSIS IS A progressive disease which, at an early stage, is characterized by vessel wall thickening causing outward remodeling, then narrowing of the lumen, and at a later stage by the formation of plaque lesions inside the vessel wall (1). In patients with unstable plaques, the thin fibrous cap can rupture causing the plaque contents to enter the vessel lumen causing a stroke. Therefore, accurate assessment of the vessel wall dimensions and composition of the vessel wall is essential for identifying patients at risk. The 3.0 Tesla (T) MRI offers high-resolution noninvasive imaging of the vessel wall of the carotid artery. For quantitative assessment of the vessel wall morphology and plaque composition, contours describing the boundaries of the vessel wall are needed (2). Vessel wall thickness measurements have been shown to correlate well with ultrasound (US) intima media thickness measurements (IMT) (3-5). IMT has emerged as a marker for cardiovascular disease and has been used as an endpoint in clinical trials assessing the effect of pharmacological treatment of systemic atherosclerosis (6,7). In turn, MRI is also used in clinical trials (8,9), but compared with US, it offers the advantage that it can provide a 3D image of the vascular structure instead of a 2D image that is dependent on the angle of insonation (5). Other advantages of MRI over US are lower measurement variability (5), enabling smaller sample sizes and potentially shorter study duration in clinical trials. ConclusionCurrently, quantitative assessment of the vessel wall dimensions is based on manual tracing of the lumen and outer wall boundaries, which is timeconsuming and subject to inter-and intra-observer variation. Consequently, computerized segmentation