Jérémy Lecoeur

Feng Wang

Min Li

Chen

Rui Li

Malcolm J Avison

Benoît M Dawant

Automated longitudinal registration of high resolution structural MRI brain sub-volumes in non-human primates

Keywords: Rigid registration, longitudinal studies, MRI, attenuation artifacts in MR, primates

Accurate anatomic co-registration is a prerequisite for identifying structural and functional changes in longitudinal studies of brain plasticity. Current MRI methods permit collection of brain images across multiple scales, ranging from whole brain at relatively low resolution (≥ 1mm), to local brain areas at the level of cortical layers and columns (∼100 um) in the same session, allowing detection of subtle structural changes on a similar spatial scale. To measure these changes reliably, high resolution structural and functional images of local brain regions must be registered accurately across imaging sessions. The present study describes a robust fully automated strategy for the registration of high resolution structural images of brain sub-volumes to lower resolution whole brain images collected within a session, and the registration of partially overlapping high resolution MRI subvolumes (slabs) across imaging sessions. In high field (9.4 T) reduced field-of-view high resolution structural imaging studies using a surface coil in an anesthetized non-human primate model, this fully automated coregistration pipeline was robust in the face of significant inhomogeneities in image intensity and tissue contrast arising from the spatially inhomogeneous transmit and receive properties of the surface coil, achieving a registration accuracy of 30 ± 15 micrometers between sessions.

Introduction

There is compelling evidence that plastic changes of the brain are a key etiologic factor in the emergence of a broad range of neurological, psychiatric and behavioral disorders. The development of successful therapies to remediate these pathological plastic changes requires, among other things, the availability of robust quantitative measures of plasticity that can link the spatio-temporal trajectories of cellular and molecular events in vitro to Central Nervous System (CNS) remodeling in vivo in animals, and ultimately in humans. The enhancement of existing and the development of new MRI methods for measuring CNS plasticity, together with tools that allow the MRI observations in animal models to be linked back to molecular and cellular events on the one hand, and to plastic changes in the human CNS on the other, will provide a methodological bridge across scales and species. Central to the success of such an enterprise is the ability to achieve stable, unbiased and, ideally, fully automated coregistration of structural images collected from the same subject longitudinally over time. The fidelity of this coregistration ultimately constrains the sensitivity with which MRI can detect changes in local structure and/or function associated with normal and pathological brain remodeling in vivo. Currently, high resolution (≤ 100 µm) imaging of the whole brain in vivo requires an impractically long time. Rather, a sub-volume is imaged, whose position is prescribed using a lower resolution larger field of view images for guidance. The challenge in longitudinal studies is to achieve accurate coregistration of the sub-volumes across imaging sessions that may be separated by days to years.

A large body of work dealing with the longitudinal registration of both human and animal head scans has been published over the years and a complete review of these methods (see for instance [START_REF] Pluim | Mutual-Information-Based Registration of Medical Images: A survey[END_REF]) is beyond the scope of this article. However, these methods are generally applied to whole brain images or to slabs covering an entire cross-section of the head [START_REF] Baker | Distribution of activity across the monkey cerebral cortical surface, thalamus and midbrain during rapid, visually guided saccades[END_REF]; [START_REF] Schweizer | Finger representations in human primary somatosensory cortex as revealed by high-resolution functional MRI of tactile stimulation[END_REF]; [START_REF] Sydekum | Functional reorganization in rat somatosensory cortex assessed by fMRI: Elastic image registration based on structural landmarks in fMRI images and application to spinal cord injured rats[END_REF]). In the present work we address a more general problem, that of coregistering very high resolution images of local brain areas collected from the same subject over times. These high resolution image sets generally comprise sub-volumes (or slabs) within a larger volume of brain imaged at lower spatial resolution.

In current practice, the position of a slab is prescribed manually with the help of a user interface provided by the scanner manufacturer, using the lower resolution larger field of view images for guidance. This is a somewhat unreliable process and its accuracy largely depends on the skills of the operator. In general, however, the slabs acquired during different sessions, possibly separated by long periods of time, will not cover exactly the same brain volume nor are they acquired with exactly the same orientation. It is therefore necessary for high resolution sub-volumes to be registered retrospectively. Currently, there is no automatic method for the coregistration of overlapping but non-identical slabs acquired in different sessions. Manual coregistration introduces another source of inaccuracy and is subject to examiners experience. Thus, the goal of the present study was to develop and assess the performance of an accurate, reliable, and automated process for coregistering MRI scans acquired longitudinally from the same subject across multiple imaging sessions. In particular, we sought to achieve high fidelity coregistration of very high resolution structural image sets providing partial brain coverage(referred to here as "slabs") acquired using surface transceiver coils whose image intensities are spatially inhomogeneous. In the present study, these slabs are centered on the somato-sensory cortex, a region of the cortex corresponding to the areas 1, 2 and 3 of Brodmann's nomenclature [START_REF] Brodmann | Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues[END_REF]) and responsible for the sense of fine touch and proprioception of hand and face [START_REF] Penfield | Secondary Sensory and Motor Representation[END_REF]). Figure 1 illustrates the typical position, orientation, and coverage of a slab. The unique nature of our data set and the accuracy requirements for our long term goals necessitated the development of a new registration procedure, which is described and evaluated in this article.

Images and acquisition protocol

MR images were acquired across multiple sessions separated by weeks to months from five male squirrel monkeys aged 4 -5 years, and weighing 800 -1100 g under an IACUC approved protoco on a 9.4 T varian scannerl. The animals were scanned under anesthesia to reduce artifacts caused by intra-session motion. Anesthesia was induced with ketamine (10 -30 mg/kg) and atropine (0.03 -0.08 mg/kg) and maintained by isoflurane (0.75 -2%) with a NO 2 /O 2 ratio of 7/3. Two data sets were acquired during each session: (1) a lower resolution 3D head scan covering a larger part of the brain, which is referred to as a partial head scan, that was used to guide positioning of the high-resolution sub-volume; (2) an oblique high resolution scan, covering a smaller volume of the cortex, referred to going forward, as a "slab".

Low-resolution whole-head scans

Low-resolution whole-head images were acquired with the same 3 cm surface coil used to acquire the slabs.A surface coil was used so that the robustness of the registration in the face of large variations in tissue contrast and signal-to-noise ratio arising from the spatial inhomogeneity of transmit B1 and receiver sensitivity could be determined. The slab and the lowresolution whole-head images were acquired within the same session, and neither the animal nor the coil was repositioned during the session. The low-resolution whole-head scans were collected using a 3D FLASH sequence (nominal flip angle = 15 degrees; TR/TE = 5/2.39 milliseconds; FoV = 64×64×64 mm 3 ; 128×128 × 128 isotropic voxels; voxel dimension 0.5 × 0.5 × 0.5 mm 3 ). As shown in Figure 2, these images provide whole brain coverage, but show significant signal attenuation as one moves away from the surface coil. The large intensity modulation makes it difficult to adjust the contrast to permit the visualization of anatomical details in both high intensity and low intensity regions.

Figure 2: Low-resolution whole-head MRI scans. Because the signal drops off rapidly with distance from the coil, the contrast needs to be adjusted to permit visualization. Bottom row: two views with contrast adjusted in order to show details in regions of low intensity. Top row: Same images with contrast adjusted to show details in regions of high intensity. When the contrast is adjusted for high intensity regions, the rest of the head is not visible. When it is adjusted for low intensity regions, the area close to the coil is saturated.

Slabs

Each slab, comprising a stack of contiguous thin 2D images oriented obliquely with respect to the scanner frame of reference, was positioned using anatomic landmarks present in the low-resolution whole-head image. High resolution slabs were collected using a multislice 2D FLASH sequence (nominal flip angle 25 degrees; TR/TE = 400/16 ms; FoV = 36 x 36 mm 2 ; 512 × 512 in plane voxels; in-plane pixel resolution is 68.35 × 68.35 µm2; 16 contiguous slices, thickness 0.5 mm; slab thickness 8 mm). Figure 3 shows a typical high resolution slab in three orthogonal directions.

Methodology

In this work, we assume that geometric distortion is minimal. With the high bandwidth acquisition sequences we use, this assumption is reasonable. Based on this assumption, all the transformations needed to register the various scans are rigidbody transformations, i.e., they only involve a translation vector [t x , t y , t z ] and a rotation matrix R(ϕ, θ, ψ).

Direct slab to slab registration

The easiest approach to compute the rigid-body parameters would be to register slabs acquired during different sessions to each other directly with a standard intensity-based algorithm. Our in-house implementation of such an algorithm, which we call AMIR, computes the transformation that maximizes the Normalized Mutual Information (NMI), introduced by [START_REF] Studholme | An overlap invariant entropy measure of 3D medical image alignment[END_REF], between the image volumes. Mutual Information (MI) [START_REF] Collignon | Automated multimodality image registration based on information theory[END_REF]; [START_REF] Viola | Alignment by maximization of mutual information[END_REF] and NMI have been used extensively as similarity measures for the registration of single and multi-modality images since the validation study conducted by Fitzpatrick and colleagues Fitzpatrick and West (1998). NMI has been documented as being more robust than MI for partially overlapping volumes by [START_REF] Studholme | An overlap invariant entropy measure of 3D medical image alignment[END_REF]. NMI is defined as:

N MI(A; B) = H(A) + H(B) H(A, B) (1)
where H(A) is the marginal entropy of image A, H(B) is the marginal entropy of image B and H(A, B) is the joint entropy of image A and B, introduced by [START_REF] Shannon | A mathematical theory of communication[END_REF].The marginal entropy of an image is computed from its intensity probability density function as:

H(A) = - i∈A p(i) log p(i) ( 2
)
where i is an intensity and p(i) is the probability of observing intensity i in the image. The intensity probability density function is estimated from the normalized intensity histogram. Similarly, the joint entropy of two images is computed as:

H(A, B) = - i∈A j∈B p(i, j) log p(i, j) (3)
where p(i, j) is the joint probability density function estimated from the normalized joint intensity histogram. Intensity histograms were built with 128 intensity bins. This direct approach did not produce reliable results. Experiments performed to determine the cause of the failure and discussed in the Results section revealed that it is related to the approachs small capture range and imperfect overlap of the data (between 67 and 86 %). The following sections describe the solution that has been developed to address this problem.

Slab to low-resolution whole-head scan registration

Since the animal is anesthetized and their heads are immobilized during acquisition, motion between the slab and the lowresolution whole-head scan can be assumed to be minimal. The transformation that registers these scans can thus be computed analytically using image coordinates and scanning information retrieved from the image headers (Euler angles used to acquire the scan and center of the volume). In principle, this approach should lead to an accurate registration but we have observed a small residual error, which we attribute to the hardware. To correct for this residual error, we used our in-house implementation of an intensity-based registration algorithm, AMIR, where intensity histograms were again built with 128 intensity bins. The easiest approach to register the inter-session partial 3D head scans is to apply an intensity based registration algorithm to these image volumes. However, as discussed previously these images are affected by signal drop-off with increasing distance from the transceiver coil. This signal attenuation presents a challenge for intensity-based registration methods and, as shown in the results section, registration of the unprocessed volumes led to poor results. Methods have been proposed in the literature to correct for intensity variation (see for instance [START_REF] Dawant | Correction of intensity variations in MR images for computer-aided tissues classification[END_REF]; [START_REF] Ashburner | MRI sensitivity correction and tissue classification[END_REF]; [START_REF] Sled | A nonparametric method for automatic correction of intensity nonuniformity in MRI data[END_REF][START_REF] Van Leemput | Automated model-based tissue classification of MR images of the brain[END_REF]; [START_REF] Shattuck | Magnetic resonance image tissue classification using a partial volume model[END_REF]). However, these methods were developed and are typically used for whole human head images acquired at 1.5 or 3 T.

Low-resolution whole-head scan co-registration

Rather than attempting to develop an intensity correction algorithm for the type of images used in the study, we opted to work with the gradient images. This approach helps to mitigate the spatial variations in signal amplitude and tissue contrast that result from the inhomogeneous transmit/receive characteristics of the surface coil, and to the extent that it is successful in the setting of spatial inhomogeneities in signal amplitude and tissue contrast weighting associated with surface coils, will perform well in applications using volume transceiver coils. Others like [START_REF] Pluim | Image Registration by Maximization of Combined Mutual Information and Gradient Information[END_REF]; [START_REF] Shams | Gradient Intensity-Based Registration of Multi-Modal Images of the Brain[END_REF] and [START_REF] Liu | Multi-modal Medical Image Registration Based on Adaptive Combination of Intensity and Gradient Field Mutual Information[END_REF] have proposed to combine gradient and intensity images for intensity-based registration. In the present study, however, working with the gradient images alone led to accurate results for two reasons. First, sulci are clearly visible in the images and their edges provide strong registration features. Second, the rapid intensity drop-off visible in the images is reduced in the gradient image. Figure 4 shows illustrative examples of gradient magnitude images (the gradient images were computed with a standard 3D Sobel operator [START_REF] Sobel | An Isotropic 3x3x3 Volume Gradient Operator[END_REF]) as implemented in ITK by [START_REF] Ibanez | The ITK Software Guide[END_REF]).

The bottom panel of Figure 5 shows the normalized intensity profiles in the original and in the gradient magnitude images along the red line shown on the top panel. The procedure that was followed was thus to first compute the gradient magnitude of both images and then to register these with the same intensity-based registration algorithm that is used to register the slabs to their corresponding partial head volume. NMI was also used as the similarity measure measure as, contrary to sum square difference or normalized cross correlation, NMI retains inhomogeneity in contrast. The intensity histograms were built with 128 bins.

Final refinement

Even though both the slab to low-resolution whole-head scan and the low-resolution whole-head scan to low-resolution whole-head scan registration steps produced results that are visually correct,, the overall slab to slab registration obtained using the low-resolution whole-head images was poor. This is due to the difference in spatial resolution between the volumes. Indeed, the in-plane resolution of the partial head volumes is almost ten times lower than the resolution of the slabs. Slab to low-resolution whole-head or low-resolution whole-head to low-resolution whole-head registrations may appear accurate when evaluated with the low-resolution whole-head data, but not when slabs are compared. Nonetheless, the transformation obtained with the process described so far was sufficient to permit a final intensity-based registration of the slabs. Again, NMI was used as the similarity measure and the intensity histograms were built with 128 intensity bins.

Overall registration procedure

Evaluation of accuracy

Assessing the accuracy of automatic registration algorithms is a difficult task. When a ground truth transformation is known, the estimated transformation can be compared to it. In this study, a validation procedure based on visible landmarks was used because there is no known ground truth. The small dark points visible in the image shown on Figure 7 are trans-cortical vessels. Because these vessels have high conspicuity, are focal and are typically seen throughout the entire image, they form a good set of landmark points to evaluate our approach. The procedure that was used to create the set of landmarks for each monkey was as follows. First, vessel cross-sections were manually defined by the first author on all the slices of the second slab. Next, 50 of these cross-sections were randomly selected and circles were placed around these selected cross sections.

Figure 7 shows one slice on which selected cross-sections have been encircled. Finally, the same cross sections were localized by the first author in the volume obtained after registering slab 1 to slab 2 and circles were placed around the selected cross sections, using triangulation with anatomical landmarks such as sulcal boundaries, large veins, etc. to confirm the correspondence of individual vessels cross-sections. These transcortical vessels are normal to the local cortical curvature and help constrain the registration as a tilt in the slice orientation would likely make the corresponding vessels of the two sides of the images go in opposite directions. For each monkey, this resulted in pairs of images in which 50 homologous cross-sections were labeled. Two raters were then asked to localize the center of the selected cross-sections. These raters were provided with a printout of each slice of each volume on which cross-sections were selected and they picked the center of these cross-sections using a visualization tool, developed in house, that allow them to see the same slice as the annotated printout. To evaluate intra-rater variability, these two raters were asked to repeat the experiment at a 4 week interval. The homolgous point registration error (HPRE) is defined as the distance between the centers of two homologous cross-sections. The intra-rater variability is defined as the distance between the centers of the same cross section selected by a rater the first and the second time. The inter-rater variability is defined as the distance between the center of the same cross-section selected by rater 1 and rater 2.

Results

Direct slab-to-slab registration

Figure 8, for two different monkeys, results obtained when attempting to register directly slabs acquired during two differ-ent sessions. Each row in this figure shows one slice in the first slab on the left panel and the corresponding slice in the second slab on the right panel. The middle panel shows the same slice in the volume obtained after registering the first slab to the second one. As can be seen, differences in the position of the slab during acquisition led to substantial differences between the images. In particular, some sulci can be seen in one image and different sulci in the other image. Because sulci are strong features in these images, the lack of correspondence between these makes the registration difficult. As shown in Figure 8, on the middle image of the top row, the registration is misled by the incorrect correspondence of two different sulci. This incorrect correspondence is driving the whole registration process to the wrong solution. Using two images registered with the method described in this article, we investigated the capture range of the AMIR algorithm for high-resolution brain sub-volumes, to better understand the reason of its failure. Starting from these two registered images, we applied a transformation (rotation and/or translation) to one of them (image A) and used AMIR to try to register it to the other image (image B), hence producing a third image (image A') which should be similar to image B. To evaluate the accuracy of this direct registration, we used a regularly spaced point grid on each image. This grid is the same for image A and B and was transformed with the matrix that change image A into image A'. We then computed the distance between each of these points in A' and their homologous point in A and used the mean distance as a decision criterion. If this mean distance is smaller than 50 µm, the registration is considered a success and a failure otherwise. This experiment was repeated 10000 times on the five sets of monkey images for different rotation angles, rotation axes, translation distances and translation directions. We chose a range of ±5 degrees for rotations and ±2 mm for translation as they are the ranges of rotations and trans-lations observed in usual acquisitions. In this experiment, X is the phase encoding direction, Y is the read out direction and Z is the stacking direction of slices. Table 1 shows the results of this experiment for rotation angles randomly chosen in the ± 5 degrees range: rotations about the X or Y axis leads to a mis-registration while rotations about Z-axis are not a problem. Table 2 shows the results of this experiment for translation distances randomly chosen in the ± 2 mm range: translation along the Z axis leads to mis-registration whereas translations along X or Y axes are handled quite easily.

Although testing for rotations and translations provide a good idea of the capture range, in usual conditions of acquisitions, rotations and translations occur together. In order to test the capture range in a realistic manner, we designed a slightly different experiment, applying 3 rotations (in the ± 5 degrees range) and 3 translations (in the ± 2 mm range) to image A, again 10000 times and using the same success criterion. In these usual conditions of acquisitions, the direct slab to slab registration is unlikely to succeed, as the success rate is only 0.17. The capture range of AMIR for such images is not sufficient to permit a direct slab to slab registration. This very small capture range is due to the highly non-isotropic nature of the image voxels combined with an imperfect overlap of the data.

Slab-to-low-resolution whole-head registration

A representative example of slab-to-low-resolution wholehead registration using only information derived from the image headers is shown in the left panels of Figure 9.Although the global orientation and position of the slab is correct, the sulci and the surface of the cortex are misplaced. However, because the transformation computed with the header information is close to the correct transformation, an additional intensitybased registration permits the accurate registration of the slab with its corresponding partial head volume. Results obtained after this step are shown on the right panels of Figure 9.

Low-resolution whole-head scans coregistration

The NMI can be viewed as a measure of the spread of the joint intensity histograms. The top panels of figure 10 show the joint intensity histogram of the original images (left panel) and of the gradient magnitude images (right panel) when the images are registered. These figures show that the joint histogram of the original image is more diffuse than that of the gradient magnitude image. This, in turn, suggests that the NMI will be less sensitive to misalignment in the parent images than the Sobel-filtered gradient magnitude images. The bottom panel confirms this. It shows the value of the NMI as a function of misalignment for the original images (dotted lines) and the gradient magnitude images (solid lines). For illustration purposes, a simple rotation around one axis is used to produce the misalignment. It is clear from this figure that the NMI has a peak that is much more pronounced at registration for the gradient magnitude images than for the original images. This facilitates the convergence to a local maximum, and explains why we have obtained better results with the gradient images than with the original images.

Final refinement

Figure 11 shows the effect of the last slab-to-slab intensitybased registration algorithm. The panel on the left (Fig 11A) is one slice in the reference slab (slab 2). The middle panel (Fig 11B) is the corresponding slice in the volume obtained by registering slab 1 to slab 2 after step 3 (see Figure 6). The right panel (Fig 11C) is the corresponding slice in the volume obtained after the final registration step. After step 3, a registration error on the order of 3 voxels (∼ 200 micrometers) can be observed, but after step 4, visual inspection suggests that registration accuracy is significantly better.

Quantitative evaluation of the complete process

Table 3 summarizes the registration errors as well as the inter-and intra-rater variability for the 5 data sets included in this study. The average registration error was 30.3 ±16.3µm (0.443 voxels). Mean intra-and rater-variability were both ∼ 28 ± 15 µm .

Discussion

To the best of our knowledge, this is the first automatic registration method proposed for the longitudinal registration of small brain sub-volumes, especially at a spatial resolution of less than 100 µm. An analysis of the problem indicated that a simple slab-to-slab approach does not work because of the limited capture range which does not accomodate the range of rota-tions and translations offsets between slabs acquired in different sessions.We therefore developed and implemented the modified acquisition and coregistration pipeline that provides highly accurate session to session coregistration of brain sub-volumes.

A low-resolution whole-head volume could be acquired with the same surface coil used for the acquisition of the slab. Using a volume head coil to acquire the whole head volumes would greatly reduce the intensity and tissue contrast variations, reducing the challenges of coregistration. However spatial inhomogeneities in the transmit and receive modes increase with increasing B0 field strength, and a goal of the present study was an automated coregistration approach that would remain robust in the face of even severe inhomogeneities. For this reason, we have used a surface coil transceiver for all imaging, to specifically challenge this aspect of the pipelines performance. As expected, severe intensity attenuation artefacts in these images proved to be a challenging confound for their direct registration. Furthermore, incorporation of intensity correction algorithms developed for human images acquired at lower field strength did not produce convincing results. In contrast, we found that registering gradient magnitude images, which exhibit less fall-off in intensity with distance from the transceiver coil, was an effective strategy. We notea number of edge operators that may be better than the simple Sobel operator under noisy conditions have been proposed, including for example, Deriche [START_REF] Deriche | Using Canny's criteria to derive a recursively implemented optimal edge detector[END_REF]) or Shen-Castan filter [START_REF] Shen | An optimal linear operator for edge detection[END_REF]) and Difference of Gaussians [START_REF] Marr | Theory of edge detection[END_REF]. However, the results we have obtained show that the choice of operator is not critical. Finally, scanner imperfection and differences in spatial resolution between the slabs and the low-resolution whole-head images required several final small adjustments following which we achieved an overall registration accuracy of 30.3 ± 16.3 µm (∼ 0.4 voxels).

The slab to low resolution whole head scan registration step is similar to the slice-to-volume or stack-to-volume registration problems found in cardiac MRI [START_REF] Chandler | Correction of misaligned slices in multi-slice MR cardiac examinations by using slice-to-volume registration[END_REF]) or MR fetal motion correction [START_REF] Gholipour | Robust Super-Resolution Volume Reconstruction From Slice Acquisitions: Application to Fetal Brain MRI[END_REF]; [START_REF] Kim | Intersection Based Motion Correction of Multislice MRI for 3-D in Utero Fetal Brain Image Formation[END_REF]).In our case, there is an additional challenge: the resolution of the slab and the whole head images is very different. Furthermore, in the cardiac and fetal imaging studies, several slices are commonly used to reconstruct a volume, while in the present study we use the volume as an intermediate step to register two slabs. Ultrasound stitching faces a similar partial overlap problem as the one being addressed here [START_REF] Gooding | Investigation into the Fusion of Multiple 4-D Fetal Echocardiography Images to Improve Image Quality[END_REF]. However the method used by Gooding and colleagues is not fully automated and relies on a first manual approximation of the correct alignment. In designing our coregistration tool, we sought a completely automated approach to avoid the problem of reproducibility associated with human intervention.

Registration of the somatosensory cortex has been performed previously in humans and rats, but mostly they rely on full head 3D MRI scans. No studies so far have developed an automatic method with a focus on coregistration of high resolution partial brain volume. For example, [START_REF] Schweizer | Finger representations in human primary somatosensory cortex as revealed by high-resolution functional MRI of tactile stimulation[END_REF] used the FSL registration tool [START_REF] Jenkinson | A global optimization method for robust affine registration of brain images[END_REF]) with rigid body transformation and sinc interpolation with good results in humans, but on our slabs, this led to unsatisfactory results. Oth-Table 3: Registration error, inter-and intra-variability of the raters. All measures are expressed in micrometers. For each case, Mean, standard-deviation (SD), maximum and median (Med) are given. ers, like [START_REF] Sydekum | Functional reorganization in rat somatosensory cortex assessed by fMRI: Elastic image registration based on structural landmarks in fMRI images and application to spinal cord injured rats[END_REF], sought to coregister functional maps using the native functional Echo Planar Images (EPI) to compute the registration. We suspect that the registration of functional EPI should be performed using the transformation computed for anatomical images acquired during the same session as the EPI. Indeed, the anatomical images have a higher resolution; hence, structures and textures are sharper and allow a better registration. Moreover, the anatomical images are not subject to distortions which can arise as a result of static magnetic field inhomogeneities and the low pixel bandwidth of EPI images.

Assessing the accuracy of registration methods requires a ground truth or surrogate thereof. For rigid body transformations used in this work, this typically means being able to localize homologous points in the images and computing the distance between these points after registration. We called the distance between these points after registration the Homologous Point Registration Error (HPRE) . Even if the transformation computed to register the images was perfect, the HPRE would typically not be zero because homologous points cannot be localized with infinite precision. The error made while localizing the homologous points is referred to as the Target Localization Error (TLE) [START_REF] Maurer | Registration of Head Volume Images Using Implantable Fiducial markers[END_REF]). Ideal points used to assess registration errors are thus points that can be localized easily and accurately. Our results have shown that the transcortical vessels visible in the images are good target candidates that can be localized with sub-voxel accuracy. However, these are not perfect. Indeed, vessels are tubular structures and not points. Using the center of their cross-sections is thus ambiguous. It is possible to conceive a scenario in which our approach would not be able to detect a registration error. Indeed, if all vessels were perfectly perpendicular to the imaging plane, we could not detect a translation error. However, this scenario is highly unlikely because the vessels are not all oriented in the same direction. Even if one vessel was perpendicular to the imaging plane, a translational error would result in a target registration error for the other vessel cross-sections. Our results indicate that the registration accuracy we have achieved is as good as we can measure it, i.e., the target registration error is on the order of the target localization error.

Conclusions

This study describes and characterizes the performance of an acquisition and processing pipeline for fully automatic registration of longitudinal high resolution MRI brain sub-volumes. The method has been applied successfully for retrospective coregistration across sessions.

In principle, this approach can be extended to allow coregistration of high resolution fMRI images. However, functional images are generally more prone to geometric distortion and additional non-rigid registration approaches will need to be incorporated.

The ultimate objective of the work is to assess brain plasticity. To that end, fMRI images acquired in the same orientation as the slabs and covering the same space will need to be registered to each other. Geometric distortions present in EPI will need to be taken into account in the process.

Finally, we note that the approach described generalize across scales and can be used for highly accurate inter-session coregistration in high resolution imaging studies of human brain anatomy. This method makes no assumption about monkey-specific features and should transfer easily to other species. In high field MR imaging, such as 7 T for humans, the acquisition time becomes prohibitive for a whole head MRI scan. Multi-slice sub-volumes acquisition of the region of interest is a good way to acquire very high resolution data in a convenient time, and with the help of the method described in this article, accurate registration of such slabs is achievable.

Figure 1 :

 1 Figure 1: 3D rendering of brain (white), eyes (cyan), brain stem and spine (yellow) and slab (red).

Figure 3 :

 3 Figure 3: Three orthogonal views of a high resolution slab.

Figure 4 :

 4 Figure 4: Representative low-resolution whole-head gradient magnitude images obtained with a 3D Sobel operator.

Figure 6

 6 Figure 6 summarizes the various steps involved in the procedure we have developed. The first transformation is the concatenation of the transformations computed with the scanner information and with the intensity-based registration of a slab with its corresponding partial head volume. The second transformation is estimated by the intensity-based registration of the gradient magnitude images. T3 is obtained with scanner information and with the intensity-based registration. The last transformation (T4) is estimated by the intensity-based registration of the slabs.

Figure 5 :

 5 Figure 5: Top panel, original and gradient magnitude for one low-resolution whole-head image. Bottom panel, normalized intensity profiles along the red line shown on the top panel images. Solid blue: normalized intensity profile for the original low-resolution whole-head scan. Dotted red: normalized intensity profile for the gradient magnitude image.

Figure 6 :

 6 Figure 6: Overall process used to register slabs acquired during two imaging sessions. All four transformations are computed with an intensity based registration algorithm with NMI as the similarity measure. Transformations 1 and 3 (T1 and T3) use header information retrieved from the scanner for initialization. T2 is computed on the gradient magnitude image of the low-resolution whole head scan. T4 is a simple rigid body transformation as the combination of T1, T2 and T3 is sufficient to bring the images within the capture range of the intensity-based registration.

Figure 7 :

 7 Figure 7: Example of a printout used for the selection of vessels' center.

Figure 8 :

 8 Figure 8: Direct slab-to-slab registration is not accurate. Rows show examples of poor slab registration for two different monkeys. Left panels: slice from first slab. Right panels: corresponding slice of second slab. Middle panels: first slab registered to second slab. Lines in the middle panel are the contours of the second slab projected onto the registered first slab. Top row: registration error is about 75 voxels. Bottom: registration error is about 35 voxels.

Figure 9 :

 9 Figure 9: Registration of a slab with its corresponding partial head image. Left column with scanner-derived information only; Right column after an additional intensity-based step. The top row shows the slab image, the bottom row the partial head image. Contours have been drawn on the top images and copied on the bottom ones.

Figure 10 :

 10 Figure 10: Left: Normalized joint histogram of partial 3D images after registration computed with gradient images Right: Normalized joint histogram of the gradient images. Bottom: NMI of gradient images and original images versus rotation. The joint histogram of the gradient image spreads less than the other one, showing a better correspondence of the voxels intensities. The NMI function of the gradient image is sharper and allows a better registration.

Figure 11 :

 11 Figure 11: Effect of the final AMIR step. A: Reference Slab (slab 2) with vessels (typical diameter ∼ 100 µm) highlighted.; B: Slab 1 registered to slab 2 with contours of slab 2's vessels projected onto it before step 4. C: Slab 1 registered to slab 2 after step 4.

Table 1 :

 1 Success rate of direct slab to slab registration for different rotations in the ± 5 degrees range.

	Rotation axes	x	y	z	xy	xz	yz	xyz
	Sucess rate	0.44	0.42	0.95	0.38	0.36	0.35	0.28

Table 2 :

 2 Success rate of direct slab to slab registration for different translations in the ± 2 mm range.

	Translation axes	x	y	z	xy	xz	yz	xyz
	Sucess rate	0.97	0.96	0.54	0.95	0.48	0.47	0.46

Acknowledgements

This work was supported in part by in part by NIH Grant R01DA028303 from the National Institute on Drug Abuse. The content is solely the responsibility of the authors and does not necessarily represent the official views of these institutions.


MSc Mia Birkhøj Kjaerstad

Flemming Nielsen

Lene Nøhr-Jensen

Stine Zwisler

Kim Brøsen

Helle Raun Andersen

Mia Birkhøj Kjaerstad

& Helle

Raun Andersen

Systemic uptake of miconazole during vaginal suppository use and effect on CYP1A2

Keywords: miconazole, antifungal, CYP1A2, CYP3A4, vaginal uptake

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Miconazole (Figure 1) is a pharmaceutical antifungal. It inhibits the fungal enzyme lanosterol 14-α-demethylase (CYP51) which regulates ergosterol synthesis essential for formation of the fungal cell membrane. Miconazole is used for the treatment of oral candidiasis in infants and vaginal mycoses in pregnant women and may reach the systemic circulation of the child and foetus if it is able to cross the mucous membrane and the placental barrier. However, the systemic bioavailability of miconazole following absorption via the vagina and the gut were reported to be low, 1.4% and 27%, respectively [START_REF] Boelaert | Miconazole plasma levels in healthy subjects and in patients with impaired renal function[END_REF][START_REF] Daneshmend | Clinical pharmacokinetics of systemic antifungal drugs[END_REF][START_REF] Daneshmend | Systemic absorption of miconazole from the vagina[END_REF], and oral and vaginal absorbed miconazole were eliminated with half lives between 2 and 57 hours [START_REF] Daneshmend | Systemic absorption of miconazole from the vagina[END_REF][START_REF] Mannisto | Impairing effect of food on ketoconazole absorption[END_REF][START_REF] Stevens | Miconazole in coccidioidomycosis. II. Therapeutic and pharmacologic studies in man[END_REF]. Nevertheless, drug interactions between oral gel or vaginal used miconazole and the anticoagulant warfarin have been reported indicating a systemic concentration high enough to affect biotransformation [START_REF] Murty | Miconazole-warfarin interaction: increased INR[END_REF][START_REF] Pemberton | Miconazole oral gel and drug interactions[END_REF].

In a panel of in vitro test systems, miconazole showed potential to disrupt the endocrine system by several mechanisms [START_REF] Kjaerstad | Endocrine disrupting effects in vitro of conazole antifungals used as pesticides and pharmaceuticals[END_REF]. Miconazole inhibited testosterone biosynthesis and the oestrogen synthesizing enzyme aromatase (CYP19) and it was a weak oestrogen receptor antagonist. In other experimental test systems, miconazole had unspecific effects on the humane cytochrome P450 (CYP) system and has been reported to inhibit CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP17, CYP19, and CYP51 activities [START_REF] Ayub | Inhibition of testicular 17 alpha-hydroxylase and 17,20-lyase but not 3 beta-hydroxysteroid dehydrogenase-isomerase or 17 betahydroxysteroid oxidoreductase by ketoconazole and other imidazole drugs[END_REF][START_REF] Ayub | Inhibition of human adrenal steroidogenic enzymes in vitro by imidazole drugs including ketoconazole[END_REF][START_REF] Mason | Imidazole antimycotics: selective inhibitors of steroid aromatization and progesterone hydroxylation[END_REF][START_REF] Trosken | Inhibition of human CYP19 by azoles used as antifungal agents and aromatase inhibitors, using a new LC-MS/MS method for the analysis of estradiol product formation[END_REF][START_REF] Trosken | Comparison of lanosterol-14 alpha-demethylase (CYP51) of human and Candida albicans for inhibition by different antifungal azoles[END_REF][START_REF] Zhang | Inhibition of cytochromes P450 by antifungal imidazole derivatives[END_REF]. Though, the inhibitory potency of miconazole differed among different CYPs. CYP17 and CYP19 are involved in steroid synthesis whereas CYP1A2 and CYP3A4 are major drug metabolizing enzymes but they are also involved in oestrogen metabolism [START_REF] Shou | Role of human hepatic cytochrome P450 1A2 and 3A4 in the metabolic activation of estrone[END_REF][START_REF] Yamazaki | Roles of cytochromes P450 1A2 and 3A4 in the oxidation of estradiol and estrone in human liver microsomes[END_REF]. Disturbance of these enzymatic pathways may affect homeostasis. The developing foetal and infantile endocrine and reproductive systems are particularly susceptible to endocrine disrupting substances [START_REF] Grandjean | The faroes statement: human health effects of developmental exposure to chemicals in our environment[END_REF][START_REF] Skakkebaek | Testicular dysgenesis syndrome: an increasingly common developmental disorder with environmental aspects[END_REF][START_REF] Swan | Decrease in anogenital distance among male infants with prenatal phthalate exposure[END_REF]. Other conazoles which like miconazole, have been reported to inhibit CYP19 and testosterone synthesis in vitro, have been shown to disturb steroid synthesis in rat foetuses after prenatal exposure [START_REF] Taxvig | Endocrine-disrupting activities in vivo of the fungicides tebuconazole and epoxiconazole[END_REF][START_REF] Vinggaard | Prochloraz: an imidazole fungicide with multiple mechanisms of action[END_REF].

Consequently there is a concern that miconazole after ordinary use orally or in the vagina could result in systemic concentrations high enough to disturb the endocrine balance of the infant, the pregnant woman, or the foetus.

The primary aim of this study was therefore to investigate whether the ordinary use of vaginal suppository containing 1200 mg of miconazole resulted in a systemic absorption.

The secondary aim was then to investigate if the systemic concentration of miconazole was high enough to affect enzyme activities associated with CYP1A2 and CYP3A4.

Materials and Methods

Subjects

Twenty healthy female subjects were recruited in the period of May to August 2008. The participants were mainly students at the University of Southern Denmark or staff at Odense University Hospital. Characteristics of the study subjects are shown in Table 1. After oral and written information about the study and their rights, 30 subjects gave their written consent and a written authority giving relevant personnel from the GCP-Unit and the Danish Medicines Agency access to documents and data of importance for the study. Out of these 30, four subjects regretted their enrolment and withdrew their consent. Four individuals were excluded due to use of medication, and two were excluded since their electrocardiogram (ECG) revealed irregularities. Hence, twenty subjects completed the study.

Inclusion and exclusion criteria

Inclusion criteria were healthy non-pregnant (evaluated by no detection of human chorionic gonadotrophin in a urine sample) and non-breastfeeding women aged between 18 and 45 years. They were ascertained to be in good health based on clinical examination including blood pressure, medical history, and evaluation of a standard 12-lead ECG done by the physician responsible for the study. Subjects with a daily alcohol or medical use including oral contraceptives or known allergy to miconazole, caffeine, quinidine, sodium methyl 4hydroxybenzoate (E219), or sodium propyl 4-hydroxybenzoate (E217) were excluded.

Smokers were not excluded since smoking is known to have an inducing effect on CYP1A2, not an inhibitory effect, and since the subjects were their own controls and exclusion of smokers might hamper the recruitment of subjects.

Ethics

The study was approved by The Regional Scientific Ethical Committee for Southern Denmark (record no: S-20080022), the Danish Medicines Agency (record no: 2612-3691), and the Danish Data Protection Agency (record no: 2008-41-2011). The study was performed according to the Helsinki-II-Declaration and in accordance with guidelines of Good Clinical Practice (ICH-GCP) as monitored by the GCP-Unit, Odense University Hospital (record no: 07.035).

Study design and procedures

Initially, all participants answered a questionnaire regarding vegetable and fruit intake, smoking status, job function, and use of antifungals in the homes including personal hygiene products such as shampoo or cream.

For each subject the study lasted 11 days (Figure 2). It was a two-period study with a washout period of 2 days before each caffeine and quinidine administration period and of 5 days after insertion of the miconazole containing vaginal suppository.

The subjects were asked to abstain from ingesting quinine, quinidine, and methylxanthine containing food and beverages (specific items were pointed out) as well as alcohol and medication, from 48 hours before caffeine and quinidine administration and until the last blood sampling at day 8. To avoid pregnancy in the study period the subjects were asked to use condom when having intercourse from the time of pregnancy test until the insertion of the vaginal suppository. Thereafter sexual absence was required until the end of trial at day 11.

Each subject ingested 200 mg of caffeine (batch-nr. 2151631) and 200 mg of quinidine (batch-nr. 51313011), both supplied by the Central Pharmacy, Odense University Hospital (Denmark), at 11pm on day 3. Previous studies indicate that simultaneously administrations of low doses of these two compounds do not influence the outcome of their respective metabolic ratios [START_REF] Christensen | The Karolinska cocktail for phenotyping of five human cytochrome P450 enzymes[END_REF][START_REF] Damkier | Quinidine as a probe for CYP3A4 activity: intrasubject variability and lack of correlation with probe-based assays for CYP1A2, CYP2C9, CYP2C19, and CYP2D6[END_REF][START_REF] Frye | Validation of the five-drug "Pittsburgh cocktail" approach for assessment of selective regulation of drug-metabolizing enzymes[END_REF]. Morning urine was collected after a minimum of three hours.

Ten ml of the urine was poured into a conical tube containing 300 µl 1 M hydrochloric acid (HCl) for the CYP1A2 activity analysis. Forty ml was transferred into each of two sterile empty test-tubes for the miconazole analysis. The urine samples were brought to the laboratory and stored at -20 ºC until analysis. At 9-10 hours after quinidine administration, blood samples (5×10 ml) were collected by vein puncture at the laboratory for the CYP3A4 activity and miconazole analysis. Blood sampling was done by either the technician or the physician involved in the study. Twenty ml was collected in heparin tubes and 30 ml in dry tubes. All blood samples were centrifuged for 10 minutes at 3500 rpm and plasma and serum were transferred to sterile cryogenic vials and kept frozen at -20 o C until analysis.

On day 6 at 11 pm the vaginal suppository was inserted and the volunteers were instructed to lie down afterwards for the night. Twenty-four hours later caffeine and quinidine were administered again for the evaluation of CYP1A2 and CYP3A4 activity after miconazole exposure. The urine and blood sampling procedures were repeated.

The time schedule was chosen based on the findings of [START_REF] Daneshmend | Systemic absorption of miconazole from the vagina[END_REF] [START_REF] Daneshmend | Systemic absorption of miconazole from the vagina[END_REF] which showed a continuous maximally miconazole concentration in plasma from 6 to 48 hours after insertion of a 1200 mg miconazole containing suppository combined with knowledge from caffeine [START_REF] Rost | Accelerated caffeine metabolism after omeprazole treatment is indicated by urinary metabolite ratios: coincidence with plasma clearance and breath test[END_REF] and quinidine [START_REF] Damkier | Quinidine as a probe for CYP3A4 activity: intrasubject variability and lack of correlation with probe-based assays for CYP1A2, CYP2C9, CYP2C19, and CYP2D6[END_REF] kinetic studies.

Determination of miconazole in serum

The serum concentration of miconazole was quantified by liquid chromatography coupled to a Thermo TSQ Quantum Ultra triple quadrupole mass spectrometer (LC-HESI-MS/MS system from Thermo Scientific, Waltham, MA). Extraction procedure: A volume of 250 µl of the serum sample, 60 µl 0.2 M sodium hydroxide and 50 µl of internal standard (0.5 ng/ml tebuconazole in ethanol) was briefly vortex mixed in a 10 ml centrifugation tube.

Hereafter 1 ml tert-butyl methylether was added and the samples were mixed horizontally for 20 minutes at 200 rpm followed by 15 minutes centrifugation at 3000 g. The supernatant was transferred to a new extraction tube. The extraction procedure was repeated. The two supernatants were combined and evaporated to accurate dryness at 40 °C under a gentle stream of nitrogen. The dried extract was dissolved in 125 µl acetonitrile (ACN) followed by 125 µl buffer solution (2 mM ammonium acetate and 2 mM acetic acid, pH 4.6). The sample was centrifuged for 10 minutes at 3000 g, transferred to a 300 µl sample vial, and injected (30 µl) onto the analytical system.

The separation was performed on a Phenomenex C12 MAX-RP column (4 μm, 150 x 2 mm) kept at 20 °C using a two solvent gradient system: (2 mM ammonium acetate and 2 mM acetic acid), pH 4.6 : ACN (95:5) (A) and (5:95) (B). The gradient profile was: 0 to 4.37 min: 40 % to 100 %B; 4.38 to 10.00 min: 100 % B; 10.01 to 11.50 min: 100 % to 40% B; 11.51 to 15.00 min: 40% B. The flow rate was 0.3 ml/min. The MS/MS-system was operated with positive polarity in SRM mode with a scan width of 0.2 m/z and a scan time of 0.250 sec. The spray voltage was 3500 V, the vaporizer temperature 350 C, the sheath gas pressure 60 AU, the aux gas pressure 45 AU and the capillary temperature 315 C.

Miconazole was quantified with a parent mass of 416.86 m/z fragmented to a product mass of 160.95 m/z, and was detected at a retention time of 8.66 minutes. Tebuconazole was quantified with a parent mass of 308.1 m/z to the product masses of 124.8 and 70.0 m/z and was detected at a retention time of 5.91 minutes.

Quantitation of miconazole was based on calibration curves obtained after addition of known concentrations of the compound to blank serum and water samples and then extracted and analyzed as described above. The recovery of the extraction method was > 90 %. The linearity was investigated in a range from 0.1 -50.0 ng/ml (R 2 > 0.98). The interday repeatability (n=3) was < 11 %. The accuracy for the quality control samples spiked to a concentration of 5 ng/ml was -4 %. The limit of determination (LOQ) for miconazole was 0.10 ng/ml and the limit of detection (LOD) was 0.05 ng/ml.

Determination of CYP1A2 activity

Four metabolites of caffeine: 5-acetylamino-6-formylamino-3-methyluracil (AFMU), 1methyluric acid (1MU), 1-methylxanthine (1MX), and 1,7-dimethyluric acid (17DMU) were determined in morning urine samples conserved with 1M HCl by high-performance liquid chromatography with UV detection [START_REF] Rasmussen | Determination of urinary metabolites of caffeine for the assessment of cytochrome P4501A2, xanthine oxidase, and Nacetyltransferase activity in humans[END_REF]. The CYP1A2 activity was estimated by the caffeine metabolic ratio (CMR) = (AFMU+1MU+1MX)/17DMU.

Determination of CYP3A4 activity

Quinidine and 3-hydroxy-quinidine in plasma samples collected 9-10 hours after ingestion of 200 mg quinidine were analyzed using high-performance liquid chromatography as described previously [START_REF] Nielsen | Determination of quinidine, dihydroquinidine, (3S)-3-hydroxyquinidine and quinidine N-oxide in plasma and urine by high-performance liquid chromatography[END_REF]. The CYP3A4 activity was estimated by the quinidine metabolic ratio (QMR) = 3-hydroxy-quinidine/quinidine as suggested by [START_REF] Damkier | Quinidine as a probe for CYP3A4 activity: intrasubject variability and lack of correlation with probe-based assays for CYP1A2, CYP2C9, CYP2C19, and CYP2D6[END_REF].

Data analysis

The mean miconazole absorption was tested by a paired t-test comparing the mean miconazole concentrations in serum 34 h after and before the start of miconazole exposure.

The differences in metabolic ratios are expressed as the relative differences e.g. (CMR after -CMR before )/CMR before . The mean relative differences in CMR and QMR during and before exposure to miconazole were analysed by one-sample t-tests comparing the relative differences to zero. The assumptions of normal distribution were considered fulfilled after evaluation by Q-Q plot (not shown) of the differences. The variations were roughly constant along the x-axis. Relative difference (Bland Altman) plots of CMR and QMR were used as supplements to analyse the deviation between the metabolic ratios during and before exposure to miconazole.

The association between the relative difference in CMR or QMR and the miconazole concentration in serum was examined by linear regression. P-values <0.05 were considered statistically significant. The statistical analyses were performed using Stata/SE 9.0 for Windows (Texas, USA). Sample size calculations were based on the primary outcome, absorption of miconazole. As the background concentration of miconazole was zero and the LOQ = 0.10 µg/L we consider a concentration of at least 1 µg/L as an indication of absorption. Twenty women were considered suitable to detect miconazole in serum and would give a power >90% at a significance level of 5 %.

Results

Subjects

No subjects had adverse drug reactions. Seventeen subjects had one or more side effects.

The side effects occurring were expected: head ache, trouble sleeping, diarrhea, palpitations, and vaginal itching/discomfort. All side effects were followed up and all subjects were well again after the study. Three subjects had no side effects.

Miconazole

The mean serum concentrations of absorbed miconazole in the 20 women after 34 hours use of a vaginal suppository containing 1200 mg miconazol was 12.9 ± 5.6 µg/L (mean±SD) (range: 3.5-24.6 µg/L) (Figure 3). Background serum concentrations of miconazole were below the limit of detection. The absorption of miconazole was not associated with information on menstruation during the study, age, or BMI (data not shown). The miconazole concentration in the urine samples was very high due to leakage from the vagina and therefore the urine concentration could not be used as indication of the absorbed concentration of miconazole.

CYP1A2 and CYP3A4 activity

During the chromatographic detection of caffeine and metabolites, interference from the urine sample hindered the separation of AFMU in six samples. Consequently, only 14 out of 20 subjects were included in the calculations of CYP1A2 activity. One subject had trouble swallowing the quinidine capsule and therefore 19 out of 20 subjects were included in the CYP3A4 activity determination. The urine sampling time after caffeine administration differed between the two administrations with more than one hour for five subjects, while for the rest of the subjects the difference was close to zero. Data of CMR are presented as scatter plot showing the relative difference of CMR between the two exposure-periods against the average of CMR of the two periods (Figure 4a). The mean relative CMR difference (the horizontal full line) was shifted a bit below zero, but this was not statistically significant (Table 2). One subject had high CMRs compared to the other subjects and a relatively large change in CMR (the dot furthest to the right).

QMR data are presented in Figure 4b. The mean relative QMR difference (the horizontal full line) was shifted a bit above zero, but this was not statistically significant (Table 2).

One subject (not the same having high CMRs above) had a relatively large change in quinidine metabolism.

The associations between the relative difference in CMR or QMR and serum miconazole concentrations are shown in Figure 5. A low non-statistically significant decrease (p=0. [START_REF] Kharasch | Assessment of cytochrome P450 3A4 activity during the menstrual cycle using alfentanil as a noninvasive probe[END_REF] in relative CMR difference with increased concentration of miconazole in serum was indicated. There was no concentration dependent association (p=0.89) between QMR and miconazole.

Discussion

In this study we demonstrated that the use of a 1200 mg miconazole containing vaginal suppository resulted in a mean serum concentration of miconazole of 12.9 ± 5.6 µg/L (n=20) after 34 hours use. No substantial mean differences in CYP1A2 and CYP3A4 activities were observed after exposure to miconazole (exposure range: 3.5-24.6 µg/L serum). However, a weak negative and none-statistically significant association between the serum concentrations of miconazole and the relative difference in CMR was seen, indicating inhibition of CYP1A2. Due to considerable interindividual variations in the metabolic ratios and in the absorbed miconazole concentration only marked effects on enzyme activities can be detected in this study. Post hoc calculations using the standard deviation obtained from this study show that a true relative difference of at least 0.2 could be demonstrated for both CMR (n=14) and QMR (n=19) activities at a significance level of 5 % and with a power of 80%. The association should therefore be interpreted with caution.

The large variation in serum miconazole absorption between subjects is in accordance with a previous study (mean serum concentration: 10.4±4.2 µg/L, n=11) [START_REF] Daneshmend | Systemic absorption of miconazole from the vagina[END_REF]. The reason for this variation is not clarified but might be due to differences in vaginal environment and physical activity. In our study, neither menstruation during the study nor the duration of vaginal miconazole leakage (subjective evaluation of vaginal discharge) seemed to influence the systemic concentration of miconazole. The subjects were not examined for vaginal infections but a damaged mucous membrane could probably absorb more miconazole, similar to when slightly damaged skin increased the penetration of pesticides in an in vitro skin model [START_REF] Nielsen | Percutaneous penetration through slightly damaged skin[END_REF]. Also, genetic variations in the biotransformation of miconazole could play a role [START_REF] Duret | Ketoconazole and miconazole are antagonists of the human glucocorticoid receptor: consequences on the expression and function of the constitutive androstane receptor and the pregnane X receptor[END_REF]. Other formulations of vaginal miconazole, i.e., vaginal cream are not expected to give higher or lower systemic levels as the application is repeated every day for two weeks resulting in a similar total local dose as with the suppository.

The mean CMR (CYP1A2 activity) estimated before the exposure to miconazole was 4.3±1.5. This was very similar to the values obtained in two other studies with nonsmoking Caucasian women not using oral contraceptives [START_REF] Rasmussen | Determination of urinary metabolites of caffeine for the assessment of cytochrome P4501A2, xanthine oxidase, and Nacetyltransferase activity in humans[END_REF][START_REF] Rasmussen | The interindividual differences in the 3-demthylation of caffeine alias CYP1A2 is determined by both genetic and environmental factors[END_REF]. In a study with Faroese residents the overall mean (not adjusted for confounders such as gender, smoking, oral contraceptives) was 7.8±5.8 (n=307) [START_REF] Petersen | Caffeine N3-demethylation (CYP1A2) in a population with an increased exposure to polychlorinated biphenyls[END_REF] which was statistically significant different from a Danish twin study with a mean value of 5.9±3.4 (n=378) [START_REF] Rasmussen | The interindividual differences in the 3-demthylation of caffeine alias CYP1A2 is determined by both genetic and environmental factors[END_REF] indicating that either genetic or environmental factors or both should be considered when measuring and comparing CYP1A2 activity.

None of the women in our study used oral contraceptives or other medical products. All women were Caucasian except one whose genetic background was unknown. This woman smoked occasionally and she was the only smoker included in the determination of CYP1A2 activity. No obvious deviation from the results of the other women was observed for this subject. Intraindividual variability may derive from difference in morning urine sampling time before and during miconazole exposure as the time interval differed with up to four hours. It could also be speculated that the menstrual cycle could influence the activities of the enzymes and add to the variability, though studies investigating the effect of the menstrual cycle on CYP1A2 and CYP3A4 activities did not report such an effect [START_REF] Kashuba | Quantitation of threemonth intraindividual variability and influence of sex and menstrual cycle phase on CYP1A2, N-acetyltransferase-2, and xanthine oxidase activity determined with caffeine phenotyping[END_REF][START_REF] Kharasch | Assessment of cytochrome P450 3A4 activity during the menstrual cycle using alfentanil as a noninvasive probe[END_REF][START_REF] Zaigler | Variation of CYP1A2-dependent caffeine metabolism during menstrual cycle in healthy women[END_REF].

The mean CYP3A4 activity (based on QMR) was not affected by exposure to miconazole.

The wide interindividual variability was in accordance with other studies determining CYP3A4 based on the urinary 6β-hydroxycortisol/cortisol ratio or formation clearance of 3hydroxyquinidine [START_REF] Damkier | Quinidine as a probe for CYP3A4 activity: intrasubject variability and lack of correlation with probe-based assays for CYP1A2, CYP2C9, CYP2C19, and CYP2D6[END_REF][START_REF] Petersen | Polychlorinated biphenyl (PCB) induction of CYP3A4 enzyme activity in healthy Faroese adults[END_REF]. One woman had a decreased CYP3A4 activity during the use of the miconazole vaginal suppository, but it was not the woman with the highest concentration of absorbed miconazole. The cause has not been identified, as the subjects were instructed to refrain from known CYP3A4 inhibitors. Miconazole and quinidine are both known inhibitors of P-glycoprotein and also likely substrates for this efflux transporter [START_REF] Chang | Rapid identification of P-glycoprotein substrates and inhibitors[END_REF][START_REF] Elsby | Validation and application of Caco-2 assays for the in vitro evaluation of development candidate drugs as substrates or inhibitors of P-glycoprotein to support regulatory submissions[END_REF][START_REF] Fromm | Inhibition of P-glycoprotein-mediated drug transport: A unifying mechanism to explain the interaction between digoxin and quinidine [seecomments[END_REF][START_REF] Sakaeda | Effect of micafungin on cytochrome P450 3A4 and multidrug resistance protein 1 activities, and its comparison with azole antifungal drugs[END_REF]. Intake of quinidine during miconazole exposure could be speculated to reduce the hepatic elimination of miconazole causing an elevation of the systemic concentration of miconazole. By inhibiting P-glycoprotein, miconazole use during pregnancy might also increase the placental transfer of other exogenous compounds that are P-glycoprotein substrates. In placenta, P-glycoprotein is expressed both at the membrane facing maternal circulation and at the membrane facing fetal circulation [START_REF] Vahakangas | Drug transporters in the human bloodplacental barrier[END_REF]. If not metabolized in placenta, miconazole concentration may increase in this tissue when pregnant women are in treatment with miconazole.

Miconazole has been reported to inhibit several CYP-enzymes in human liver or lymphoblast microsomes in vitro, including CYP1A2 and CYP3A4, with an inhibition constant (K i ) of 3.2 and 0.028 µM [START_REF] Zhang | Inhibition of cytochromes P450 by antifungal imidazole derivatives[END_REF] and a half maximal inhibitory concentration (IC 50 ) of 2.9 and 0.074 µM [START_REF] Niwa | Effect of antifungal drugs on cytochrome P450 (CYP) 2C9, CYP2C19, and CYP3A4 activities in human liver microsomes[END_REF][START_REF] Niwa | Effect of antifungal drugs on cytochrome P450 (CYP) 1A2, CYP2D6, and CYP2E1 activities in human liver microsomes[END_REF], respectively. This indicates, that miconazole in the mean absorbed concentration of 12.9 µg/L serum corresponding to 0.03 µM could have an effect on the enzymes in vivo also.

Miconazole is used for treatment of vaginal mycoses, also in pregnant women, and of oral candidiasis in infants as these treatments are regarded effective and safe in regard to a claimed negligible absorption [START_REF] Daneshmend | Clinical pharmacokinetics of systemic antifungal drugs[END_REF][START_REF] Daneshmend | Systemic absorption of miconazole from the vagina[END_REF]. The mean serum miconazole concentration of 12.9µg/L was indeed low but maintained for several days [START_REF] Daneshmend | Systemic absorption of miconazole from the vagina[END_REF]. The measured biological effect in individuals using the miconazole containing suppository was negligible. However, orally administered miconazole has in vivo been reported to interact with the CYP2C9 substrate warfarin [START_REF] Ariyaratnam | Potentiation of warfarin anticoagulant activity by miconazole oral gel[END_REF][START_REF] O'reilly | Mechanisms of the stereoselective interaction between miconazole and racemic warfarin in human subjects[END_REF][START_REF] Pemberton | Miconazole oral gel and drug interactions[END_REF][START_REF] Silingardi | Miconazole oral gel potentiates warfarin anticoagulant activity[END_REF]. Hence, if miconazole is present in a sufficient systemic concentration, a biological effect in vivo of miconazole is possible. Therefore the potential adverse effects on the developing foetus and infant after miconazole exposure should be investigated further in vivo. Furthermore, it should be investigated if miconazole is transferred to the foetus or if miconazole concentration is increased in the placenta with the possibility to disturb development of the foetus or the placental function, respectively.

In conclusion, miconazole is absorbed via the vaginal mucosa to the systemic circulation in measurable concentrations. Our data indicate a concentration dependent inhibition of CYP1A2, but the effect is negligible compared to the variation in the activity of CYP1A2 and regarded to be of no clinical significance for the women. However, further studies on the ability of miconazole to be transferred across the placenta or to interfere with the placental function are warranted to secure safe use during pregnancy. Note: Miconazole before exposure was below the limit of detection. The t-test was performed on the difference (after-before)

Fig. 1 Fig. 2 Time schedule of the trial Fig. 3 Fig. 4 Fig. 5

 12345 Fig. 1Chemical structure of miconazole, a pharmaceutical imidazole fungicide

Table 1 -

 1 Characteristics of the study subjects

	Characteristic
	No. of subjects completing the study	20
	Age, years	26 (23-43)
	Weight, kg	65 (52-95)
	Height, cm	169 (158-180)
	BMI, kg/m 2	22.2 (18.5-31.0)
	Race and nationality	16 Caucasian -Danish
		3 Caucasian -Norwegian
		1 unknown -Danish
	Work	14 students
		5 hospital workers
		1 maternity leave
	No. of subjects menstruating during study	9
	Contraceptives	3 none
		10 condom
		7 intrauterine device made of cupper
	Non-smokers	18
	For continuous variables, data represent median (range)

Table 2 -

 2 Serum concentration of miconazole and the caffeine (CMR) and quinidine (QMR) metabolic ratio in women before and 34 h after start exposure to miconazole

		Mean±SD	Range	95% confidence interval	t-test (p-value)
	Miconazole (µg/L; n=20)	12.9±5.6	3.6-24.6	10.3-15.5	<0.0001
	CMR before (n=14)	4.3±1.5	2.4-8.7	3.4-5.2
	CMR after	3.9±0.9	2.4-6.4	3.4-4.5
	Relative CMR difference -0.035±0.24 -0.34-0.41	-0.17-0.11	0.60
	QMR before (n=19)	0.18±0.05	0.09-0.27	0.15-0.20
	QMR after	0.18±0.06	0.07-0.32	0.15-0.21
	Relative QMR difference	0.024±0.25 -0.63-0.43	-0.098-0.15	0.68

Acknowledgements

This work was supported by Clinical Pharmacology and the Department of Environmental Medicine at the University of Southern Denmark and with grants from Hartmann Fonden (no. A1461), Beckett Fonden (no. 80530), and Kong Christian den tiendes Fond (no.

75/2008).

We are indebted to Vibeke Kvist Pedersen and Stine Rosendahl for excellent technical assistance.

Conflict of Interest Statement

The authors declare that there are no conflicts of interest.

Miconazole

Cl