Mariana Fernández-Olalla

María Martínez-Jauregui

Francisco Guil

Alfonso San

Miguel -Ayanz

W Lutz

Provision of artificial warrens as a means to enhance native wild rabbit populations: what type of warren and where should they be sited?

Keywords: Habitat management, Mediterranean ecosystems, Oryctolagus cuniculus, Risk of predation, Shelter

In Spain, wild rabbits are essential for some highly endangered species, and, therefore, many actions have been undertaken to increase their populations. In the present study, artificial warrens are provided as a means to increase shelter for native wild rabbit populations in a given area. We evaluate the use of three types of warrens by rabbits and the effect on that use of five habitat characteristics at two spatial scales (500×500-m grids and 25-m plots). To evaluate that use, we identified pre-established signs at the entrances to each warren, and based on this, we calculated occupancy rate and activity. Our results indicate that rabbit abundance within a grid is the only variable which simultaneously explains both the greater occupancy and the higher activity in the artificial warrens located in that grid. Some 73.2% of the grids showed signs of rabbit use at the time of the evaluation. However, the pre-existing rabbit populations within the grids were not quantified and, hence, we cannot state that the warrens contributed to an increase in the rabbit abundance. Regarding the habitat, our results reveal that warrens should be situated in grids with food coverage of less than 50%, while the use of each individual refuge is greater where food availability in the immediate surroundings is at least 20% and shelter at least 50%. The tube warrens showed significantly greater rabbit use than the other types while there was little difference between the stone and pallet warrens in terms of use.

Introduction

The wild rabbit (Oryctolagus cuniculus) is native to the Iberian Peninsula, where its populations have thrived successfully since the Palaeolithic period (Branco et al. 2002). However, in recent decades, they have dramatically declined in large areas, mainly due to myxomatosis and rabbit haemorrhagic disease (Delibes-Mateos et al. 2009). A sharp population decrease of 71% from 1973 to 1993 has been documented (Virgós et al. 2007). The conservation of this species is of great relevance for the Mediterranean region: it is considered both a keystone species and an ecosystem engineer in southern Europe (Delibes-Mateos et al. 2008a;Gálvez-Bravo et al. 2009). Additionally, the rabbit is an important small game species in Spain, and the profit obtained from hunting can contribute significantly to the economy in rural areas (Delibes-Mateos et al. 2008b).

Over the last few years, many strategies have been developed to increase wild rabbit populations in Spain, often with the final aim of recovering the populations of Iberian lynx (Lynx pardinus), Spanish imperial eagle (Aquila adalberti) or cinereous vulture (Aegypius monachus) within the framework of projects supported by LIFE funds (European Commission LIFE-Projects). Current work centres around drawing conclusions from the valuable initiatives undertaken to date in order to develop appropriate conservation strategies and optimise the existing funds.

Apart from the release of animals, in the form of either restocking or translocation, the most widespread strategies for the recovery of rabbit populations involve habitat management. Basically, these techniques consist of improving the carrying capacity of a habitat, by increasing the availability of food, shelter or both (Cabezas and Moreno 2007;Delibes-Mateos et al. 2009).

Natural shelter can be easily increased by building artificial warrens. These warrens provide safe places where rabbits can breed and find refuge from predators, since predation could prevent the recovery of rabbit populations in Mediterranean ecosystems, especially in places where rabbits are at low densities (the predator-pit hypothesis, Pech et al. 1992;Palomares et al. 1996;Delibes-Mateos et al. 2009).

Although the installation of artificial warrens is a commonly used strategy in Spain in both protected zones and hunting areas, little is known about how the characteristics of the location and the type of warren affect the extent of utilisation by wild rabbits.

In this paper, we study the installation of artificial warrens as a stand-alone measure to boost native rabbit populations. The degree of use of the artificial warrens by the rabbits was estimated via latrine counts at warrens entrances and was analysed through the variables "occupancy and activity". We had four specific objectives: (1) to estimate the amount of use of the warrens by the rabbits; (2) to identify the better locations at larger spatial scales; (3) to determine which type of artificial warren should be installed and finally, (4) to decide where to place each artificial warren at smaller spatial scales. That way, we expect to provide the managers with a simple protocol of how to undertake this strategy.

Materials and methods

Study area

The study was carried out on 14 private estates located in the provinces of Toledo (4), Cáceres (1), Badajoz (2), Ciudad Real (1) and Albacete (6) in central Spain (Fig. 1). All the estates were included in LIFE-projects to enhance their rabbit populations and, therefore, to ensure the conservation of the endangered species present there. In terms of the criteria, which most affect wild rabbit abundance and population trends (natural and management factors) all the estates can be considered relatively homogeneous (Delibes-Mateos et al. 2009).

Type of artificial warrens

No rabbits were released into the artificial warrens. Figure 2 shows sketches of each type of warren. The distribution of all three types of warren according to estate and region is shown in Table 1. The warrens were built between 2002 and 2006 and were located in areas where remnant wild rabbit low-density populations existed. Once the experimental sites on the estates had been chosen, all of the artificial warrens within each individual estate were established simultaneously. The warrens were located in places of similar characteristics to those where, according to previous studies (Palomares 2003;Gea-Izquierdo et al. 2005), rabbits would locate their natural warrens. Three types of warren were chosen for the following reasons: (1) stone warrens are widespread and have been used in the Spanish countryside for many years; (2) pallet warrens are inexpensive, easy to install and biodegradable and (3) tube warrens are those which are most similar to the natural warrens described by Kolb (1985) and may therefore be preferred by rabbits.

The number of warrens built differed from one estate to another, and the total number was 525 (207 stone, 198 pallet and 120 tube warrens; Table 1).

-Stone warrens. These were built using stone material obtained from the estates. They had a circular form (approximately 5 m in diameter) and between six and ten entrances. First, the base stones were set starting from the centre, leaving galleries and holes between them, and finally the entire structure was covered with another layer of stones. -Pallet warrens. Each warren consisted of a minimum of four wooden pallets similar to those used for transportation. The sides and top were subsequently covered with stones, leaving four to eight holes as entrances. -Tube warrens. A complete description of this type of warren can be found in González and San Miguel ( 2004). These warrens were made of concrete tubes (15 cm in diameter and 1 m in length) connected by central PVC bottomless chambers simulating a labyrinth.

The whole structure was placed underground (approximately 1 m depth) and was subsequently covered with sand. All tube warrens studied had four entrances.

A tube warren costs around 250 €, a stone warren 240 € and a pallet warren 180 € (CBD-Habitat Foundation unpublished data), although the final price of establishing a warren on an estate could vary widely, depending on material transport costs.

Data collection

Data were collected during February and March of 2007. Two spatial scales were established in order to obtain as much information as possible about where to locate a set of artificial warrens and where to place each individual warren. Every set of artificial warrens on each estate was divided into 500×500-m grids (according to the UTM coordinate system). Although the grids in each estate were fairly homogeneous, we also characterised the microhabitat around each warren to assess whether small differences in habitat characteristics affected the level of warren use. We defined circular plots with a 25-m radius around the central point of every artificial warren.

In each grid, we estimated rabbit abundance using a relative abundance index (RAI). It was measured through latrine counts made walking along fixed transects which crossed each grid. This method provides a good indirect measure of rabbit abundance in this type of large-scale studies (Palomares 2001). The index was expressed as the number of latrines per kilometre, and we used it to correct for the different rabbit abundances in each grid.

The type of artificial warren was defined as a categorical variable with three levels: stone, pallet and tube. Each artificial warren was evaluated through its entrances. The entrances were given a "score" according to pre-established rabbit activity signs (Table 2), as described by Muñoz (2005). On the basis of the scores, we obtained the dependent variables for the statistical analyses. We calcu-lated the "average warren activity" variable, which was the average score for the entrances to a given warren and the "average grid activity", which was the average score for all the warrens located in a grid. As these two activities had many zero values, each variable was redefined into two, as proposed by Fletcher et al. (2005). On the basis of the average warren activity, we defined warren occupancy (O w ) as a binary variable describing whether the average activity was zero (not occupied) or one (occupied). The warren activity (A w ) included only positive values of average warren activity. In the same manner, we determined grid occupancy (O g ) and grid activity (A g ).

Finally, four environmental variables (soil, suitable food, suitable shelter and water sources) were measured at microand macrohabitat scales, whereas topography was measured only at microhabitat level, since the topography of each of the grids was similar and fairly flat. Table 2 includes a description of these variables.

Statistical analysis

Two analyses of variables at macrohabitat scale and two analyses of the variables at microhabitat scale were performed. We used "R.2.8.0" software (R Development Core Team 2008) for the analysis.

In the macrohabitat analyses, the individual grid was the experimental unit. To evaluate factors influencing grid occupancy, we used a generalised linear mixed model with a log-link function and a binomial distribution (Crawley 2007). RAI, number of years since warrens construction and number of artificial warrens per grid were included as covariates. Fixed factors were soil, shelter, food, water sources and their first-order interaction. Regions were introduced as a random factor (Analysis MAC1). Additionally, we fitted a general linear mixed model to determine whether any natural characteristic of a grid entails higher levels of activity in the warrens located within it. The response variable was log (A g ). The covariates, fixed and random factors were the same as in the previous model (Analysis MAC2).

In the microhabitat analysis, the individual artificial warren was the experimental unit. Similarly, a generalised linear mixed model was fitted for the response variable O w . We included type of warren, topography, soil, shelter, food and water, as fixed factors taking into account their firstorder interaction. Regions and grids within regions were included as random factors (Analysis MIC1). A general linear mixed model was also carried out for the response variable log (A w ), using the same fixed and random factors as in the previous model (Analysis MIC2).

The generalised linear mixed models were fitted using the Laplace approximation, and the general linear mixed models were fitted using the maximum likelihood method (Crawley 2007). In all cases, the models were simplified by removing non-significant factors (α=5%) after checking that the simplification did not significantly change the model. Once we had determined the significant factors in each model, we subsequently aggregated the nonsignificant levels of each factor to obtain the "minimal adequate model", using a stepwise a posteriori procedure. If two levels of a factor did not differ significantly and did not improve the fit of the model, they were grouped together (Crawley 2007). Model comparisons were carried out using likelihood criteria.

Results

Data were collected from 98 grids. In 72 of the grids (73.47%), the artificial warrens showed signs of rabbit use at the time the data were collected. The 26 remaining grids showed no rabbit use in any artificial warrens, although 15 of them have rabbit populations currently. The fact that the artificial warrens in a given grid are not used by rabbits may be due to other factors and not to the absence of rabbits in that grid. We found an average of 3.16 latrines/km (range, 0.00-14.80; SE, 3.89) in grids where the warrens showed no sign of use and an average of 13.49 latrines/km (range, 0.00-90.00; SE, 14.67) in grids where warrens had been used by rabbits.

In Appendix 1, we have included models MAC1, MAC2, MIC1 and MIC2 after the simplification of nonsignificant factors but before the simplification of nonsignificant levels of the factor, to fit the minimal adequate models in each case. To facilitate the interpretation of the results, only the results of the minimal adequate model are referred to in the text. The first-order interactions of fixed effects were not significant in any of the models.

In MAC1, the only significant variable was rabbit RAI ( p=0.0021), showing a positive relationship with warren occupancy in each grid. The same relationship ( p=0.0225) was observed in MAC2, which also revealed that warrens located in soft soils grids ( p<0.001) and with medium to high levels of food (coverage >20%; p=0.0111) had significantly higher rabbit activity.

We found that the inclusion of grids nested in regions significantly improved the models, both in the case of MIC1 ( p < 0.001) and MIC 2 ( p < 0.001). The only significant effect in MIC 1 was the type of warren. Tube warrens showed the highest occupancy rates (occupancy rate=0.6743), differing significantly from the other two types (occupancy rate=0.5388; p<0.001). Significant factors in MIC2 were type of warren, food and shelter. Topography was found to be not significant at 5% (see Appendix 1), but its elimination brought about significant changes to the model, hence it was retained (Likelihood ratio test=10.84 model without/with factor topography, p=0.0283). The minimal adequate model for MIC2 showed that the tube warrens were those with the highest activity levels, again differing from the other two ( p<0.001) that did not differ between them. The warrens surrounded by medium to high levels of food and high levels of shelter were significantly ( p<0.001) more used by rabbits than those with low level of food coverage and low to medium levels of shelter, respectively. The sign of the coefficients estimated in MIC2 for topography levels suggested that locations at the foot of hillsides could show lower rabbit activity (negative sign). We repeated the last model but grouping topography levels (foot hillside versus the others). This did not lead to significant changes in the model (Likelihood ratio test= 0.7365 model grouped/non-grouped topography levels, p= 0.8646) and furthermore, the new two-level factor was found to be significant ( p=0.0017), indicating that warrens located at the foot of the hillsides showed lower degrees of activity. Water sources and soil type had no significant effect either in MIC 1 or in MIC 2.

Discussion

In this study, we used a scale beyond that of the estate (region) which could be particularly useful for endangered species management, since their territories extend beyond the limits defined by these private properties. However, at such a large-scale and without previous information about good management practices regarding artificial warrens, it was far out of our reach to cover every possible environmental situation with a suitable experimental design. Besides, our results should be interpreted with caution, since the effect of building artificial warrens on wild rabbit densities has not been quantified. It would be necessary to deal with this topic in depth in further studies. That is why our contribution could be regarded as a first step in a suitable direction since it has been able to satisfactorily fulfil its specific objectives.

The first question was to ascertain whether artificial warrens were significantly used by sparse wild rabbit populations. The answer is positive since, in spite of the abovementioned limitations, a high percentage of those warrens were used by wild rabbits. Our results also indicate that at larger scales, rabbit abundance within a grid is a fundamental variable to explain the degree of rabbit use of the artificial warrens located in that grid, even though it showed large standard deviations between the grids (Fa et al. 1999;Calvete et al. 2004). The warrens situated in areas with greater rabbit abundance show higher rates of occupancy and activity. We suggest two possible reasons for this: (1) the requirement of a previous minimal rabbit population in the area where the artificial warrens were placed in order to serve as a founding population and (2) higher refuge availability resulting in higher rabbit population densities (Catalán et al. 2008), since this minimises the impact of predation and provides better breeding areas. The first practical conclusion which can be drawn is that, where possible, artificial warrens should be sited in areas with existing rabbit populations, although low, but as large as possible. However, it is remarkable that half of the grids where rabbits did not use warrens did have, indeed, wild rabbit populations. We found that other macrohabitat variables, such as soil type and food coverage, also affect that use.

Previous studies demonstrated that wild rabbit distribution and their overall abundance are related to soil type and climate at large scales and to the availability of food and shelter at smaller scales (Fa et al. 1999). What is more, Cabezas and Moreno (2007) found that food availability was the prime factor regulating rabbit densities and that this factor, together with the availability of shelter, was a fundamental factor in the success or failure of rabbit translocation initiatives. Our results also reveal a relationship between higher rabbit activity in the artificial warrens and food coverage at grid scale and with food coverage and shelter at smaller scales. However, we expected to find higher levels of use in artificial warrens located on soils where rabbits could not dig their own warrens (Gea-Izquierdo et al. 2005;Williams et al. 2007). On the contrary, our results indicate that artificial warrens in soft soil grids were more used by the species. This may be related to the fact that it is precisely in these areas of diggable soils where stable populations of wild rabbit could have remained and, therefore, significantly use more the artificial warrens. The effect of soil type in warren level of activity in grids can be, thereby, an indirect effect related to higher rabbit abundance, as well as could happen with food coverage at grid scale.

Regarding the habitat surrounding each individual warren, our results indicate that rabbits select warrens surrounded by food coverage of at least 20% and shelter coverage of at least 50%. The fact that the most used warrens were surrounded by a mix of food and shelter coverage fits in with the ecotone preference theory. Rabbits usually select ecotones between pasturelands and scrublands because they can obtain both shelter and food in these environments (Rogers and Myers 1979), although Lombardi et al. (2003) also found a higher incidence of predation and disease in these areas. The artificial warrens with low to medium shelter coverage are less used by the rabbit, probably because the species would not even be able to colonise the warrens due to the high risk of predation or because, even if they were able to settle in the warrens, they could not satisfy their needs outside without being preyed upon. Strategies that minimise predation risk are crucial to a prey species like the wild rabbit, particularly when population levels are low (Palomares et al. 1996).

Only artificial warrens located at the foot of hillsides are less used by rabbits, probably because they are more susceptible to flooding than warrens in the other locations. It has been shown that the worst places for wild rabbits to breed are those susceptible to floods (Palomares 2003); thus, they conspicuously avoid these areas (Lombardi et al. 2007). Although none of the artificial warrens was found flooded at the time that data were collected, our experience indicates that the sites at the foot of hillsides are very prone to flooding, particularly if they are placed on plastic/impermeable soils (CBD-Foundation, unpublished data).

Finally, wild rabbits seem to prefer tube warrens: they showed higher rates of occupancy and activity. Of the three types of warrens studied, this is the only underground type and, apparently, the one which most resembles the natural warrens so this result was to be expected. It is also very safe, as concrete tubes are impregnable to predators and the rabbits are able to create new galleries from the intermediate PVC bottomless chambers in the warren. The main disadvantage of this type of warren is that it is more susceptible to flooding than the other types (CBD-Habitat Foundation, unpublished data), so the location should be carefully chosen.

In conclusion, the artificial warrens have been widely used by sparse wild rabbit populations. Warrens should be located in areas with a minimum pre-existing rabbit population, soft soils and adequate food coverage. When choosing the location for each individual warren, the availability of food and shelter should be taken into consideration (food coverage>20% and shelter 20-50%); however, the presence of water sources does not seem to be necessary. We also recommend avoiding areas at the foot of hillsides and other places where flooding is possible. Considering the figures we deal with in this study, we have not found a relationship between the number of warrens per grid and warren use. We have identified, therefore, a number of management guidelines applicable to large-scale future initiatives involving artificial warrens. That way we would like to contribute to provide what many investigators and managers often miss: detailed advice on methodologies to recover wild rabbit populations, especially where needed for endangered predators conservation (Delibes-Mateos et al. 2008c).

Fig. 1

 1 Fig. 1 Location of estates and regions in the study area. Extremadura = estates 1-3; Sierra Morena = estates 4-10; Montes de Toledo = estates 11-14

Table 2

 2 Habitat variables (above) and activity levels for artificial warren entrance evaluation (below)

		Variable/level	Description
	Habitat variables	Soil	Binary variable indicating whether rabbits were able to dig
			the predominant soil in each plot. Level 0=hard soil
			(tertiary alluviums, such as the raña formations, slate based
			soils and quartzite based soils), 1=soft soil (quaternary
			alluviums, arkose and granitic soils)
		Suitable food (subsequently	Categorical variable whose levels (high, medium and low)
		referred to as "Food")	depended on the percentage of cover that was suitable for
			feeding (>50%, 50-20% and <20%, respectively).
		Suitable shelter (subsequently	Categorical variable with three levels (high, medium and low),
		referred to as "Shelter")	similarly to levels defined for the food variable
		Water sources	Binary variable describing the presence or absence of water
			sources in the plot (gullies, streams, ponds or artificial
			drinking sources)
		Topography	Categorical variable describing the location of the artificial
			warren as top, hillside, foot (lower part of the hillside),
			valley bottom or flat
	Activity levels at entrances	0	No activity. No signs of use are present. No faeces and no
			marking. Existence of spider webs
		1	Low activity. Not sure if rabbits use the entrance. Some old
			faeces (brown, absence of green mucous covering and black)
			or badly preserved
		2	Medium activity. Some droppings, fresh (greenish, presence of
			mucous covering) or almost fresh (black, consistent). Never
			more than 15. There are diggings nearby
		3	High activity. Many fresh or almost fresh faeces
			(approximately 15-40), though no large latrines.
		4	Maximum activity. Many fresh or almost fresh faeces (>40);
			well marked passage.

Eur J Wildl Res (2010) 56:829-837

Acknowledgements This study was carried out in the framework of the LIFE 2003/NAT/E/0050 and LIFE 2002/NAT/E/8617 projects. The artificial warrens were built by people of CBD-Habitat foundation. We are indebted to R. Higuero, A. Arredondo, L. Bolonio, M. Mata and J.F. Leiva for their help with fieldwork. The Environmental Spanish Ministry and the Royal Spanish Federation of Hunting also participated in the projects, as well as the Organismo Autónomo de Espacios Naturales of the regional government of Castilla-La Mancha and the Dirección General de Medio Ambiente of the regional government of Extremadura. We would like to thank to Víctor Díez, Nacho Mosqueda, Antonio Aranda, Ramón Pintado and Javier Caldera, to the estate owners as well as those people from the CBD-Habitat foundation who lent their assistance, especially J. Oria, S. Agudín, F. Silvestre, J. Inogés and J. Muñoz-Igualada. The authors would also like to express sincere thanks to Mar Celada, who translated the manuscript, to R. Perea and C. Herruzo for their useful comments on earlier drafts and to two anonymous referees and to W. Lutz for their helpful suggestions.

Appendix 1

Table 3 Dependence of grid occupancy (MAC 1), grid activity (MAC2), warrens occupancy (MIC1) and warren activity (MIC2) on the predictor variables. Models are included after the removal of non-significant factors (top). None of the first-order interaction was significant. Generalised linear mixed models (MAC 1 and MIC 1) were fitted using Laplace approximation and general linear mixed models (MAC 2 and MIC 2) using maximum likelihood criteria.


MD Georg Widhalm

PhD Martin Krssak

MD Georgi Minchev

Adelheid Woehrer

MD Tatjana Traub-Weidinger

MD Thomas Czech

MD Susanne Asenbaum

MD Christine Marosi

MD Engelbert Knosp

MD Johannes A Hainfellner

MD Adelheid Wöhrer

MD Daniela Prayer

MD Stefan Wolfsberger
email: stefan.wolfsberger@meduniwien.ac.at

T Tesla

Value of 1H-Magnetic Resonance Spectroscopy Chemical Shift Imaging (CSI) for Detection of Anaplastic Foci in Diffusely Infiltrating Gliomas with Non-Significant Contrast-Enhancement

Keywords:

published or not. The documents may come   L'archive ouverte pluridisciplinaire

INTRODUCTION

Standard neuroradiological imaging of diffusely infiltrating gliomas (DIG) by magnetic resonance imaging (MRI) is frequently not able to visualize the most malignant areas within these potentially heterogenous tumors.[1-4] However, intraoperative identification of anaplastic foci is essential, because only representative histology indicates which postoperative therapy is adequate.

In DIG with non-significant contrast-enhancement (CE), positron emission tomography (PET) represents a clinically useful method for the preoperative detection of malignant areas. For this purpose, the metabolic information of amino-acid tracers, e.g. ¹¹C-methionine-PET (MET-PET) or 18 F-fluoroethyl-L-tyrosine-PET (FET-PET), is frequently used.[5-10] In case of MET-PET, histological analysis confirmed that voxels with maximum tracer uptake (=PET max ) represent the most malignant tumor areas. [8,9,11,12] Therefore, neuronavigation based on MET-PET data coregistered with anatomic images is a powerful tool in glioma surgery: [13,14] In cases of biopsy, the accurate targeting of the most malignant tumor area indicated by PET max is supported; in cases of tumor resection, reliable removal of the most malignant tumor areas is warranted. Further, MET-PET imaging is useful for postoperative follow-up of low-grade gliomas: In these patients, PET facilitates early recognition of tumor progression and recurrence.[9,15] Altogether, MET-PET plays an important role in preoperative planning, intraoperative multimodal neuronavigation and postoperative follow-up of glioma patients. However, PET exposes the patient to radiation exposure and is only available in highly specialized neurooncological centers. Thus, an alternative diagnostic tool is of interest: 5/28 Multivoxel proton magnetic resonance spectroscopy (MRS), termed chemical shift imaging (CSI), has recently emerged as a promising non-invasive metabolic imaging technique. CSI can be performed in the frame of standard MRI with short acquisition time and is thus a widely available investigational tool. Like PET, CSI allows intratumoral detection of most malignant areas by examination of the spatial distribution of metabolites in DIG. Typically, CSI metabolic profile of gliomas includes: Increase of choline (Cho), due to increased cell membrane turnover, a reduction or loss of N-acetyl-L-aspartate (NAA), as a consequence of impairment of neuronal function, a frequently encountered reduction of creatine (Cr), a marker for tissue energy metabolism due to a hypermetabolic state, and the common presence of lipide and lactate due to tissue necrosis and change to anaerobic metabolism. [START_REF] Hattingen | Prognostic value of choline and creatine in WHO grade II gliomas[END_REF][START_REF] Isobe | Quantification of cerebral metabolites in glioma patients with proton MR spectroscopy using T2 relaxation time correction[END_REF][START_REF] Negendank | Proton magnetic resonance spectroscopy in patients with glial tumors: a multicenter study[END_REF][START_REF] Sibtain | The clinical value of proton magnetic resonance spectroscopy in adult brain tumours[END_REF][START_REF] Stadlbauer | Preoperative grading of gliomas by using metabolite quantification with high-spatial-resolution proton MR spectroscopic imaging[END_REF] For identification of the most malignant intratumoral areas within gliomas, the clinical use of the metabolite ratios Cho/Cr [START_REF] Negendank | Proton magnetic resonance spectroscopy in patients with glial tumors: a multicenter study[END_REF][START_REF] Croteau | Correlation between magnetic resonance spectroscopy imaging and image-guided biopsies: semiquantitative and qualitative histopathological analyses of patients with untreated glioma[END_REF][START_REF] Fayed | Contrast/Noise ratio on conventional MRI and choline/creatine ratio on proton MRI spectroscopy accurately discriminate low-grade from high-grade cerebral gliomas[END_REF][START_REF] Guillevin | Proton magnetic resonance spectroscopy predicts proliferative activity in diffuse low-grade gliomas[END_REF][START_REF] Jeun | Assessment of malignancy in gliomas by 3T 1H MR spectroscopy[END_REF][START_REF] Law | Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging[END_REF][START_REF] Shimizu | Noninvasive evaluation of malignancy of brain tumors with proton MR spectroscopy[END_REF][START_REF] Tamiya | Proton magnetic resonance spectroscopy reflects cellular proliferative activity in astrocytomas[END_REF][START_REF] Toyooka | Tissue characterization of glioma by proton magnetic resonance spectroscopy and perfusion-weighted magnetic resonance imaging: glioma grading and histological correlation[END_REF] and

Cho/NAA[10, [START_REF] Negendank | Proton magnetic resonance spectroscopy in patients with glial tumors: a multicenter study[END_REF][START_REF] Croteau | Correlation between magnetic resonance spectroscopy imaging and image-guided biopsies: semiquantitative and qualitative histopathological analyses of patients with untreated glioma[END_REF][START_REF] Fayed | Contrast/Noise ratio on conventional MRI and choline/creatine ratio on proton MRI spectroscopy accurately discriminate low-grade from high-grade cerebral gliomas[END_REF][START_REF] Guillevin | Proton magnetic resonance spectroscopy predicts proliferative activity in diffuse low-grade gliomas[END_REF][START_REF] Law | Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging[END_REF][START_REF] Shimizu | Noninvasive evaluation of malignancy of brain tumors with proton MR spectroscopy[END_REF] has been established.

To analyze the ability of this new metabolic imaging technique to detect anaplastic foci in DIG with non-significant CE, we determined the maximum intratumoral ratios of CSI metabolites (=CSI max ), performed a topographic correlation of CSI max with MET-PET and assessed histological criteria of anaplasia as well as cell proliferation rate in tumor samples inside and outside of CSI max .

METHODS

The

6/28

All patients underwent MRI, CSI and MET-PET investigations within two weeks before the neurosurgical procedure. After topographic correlation of CSI and MET-PET data, 6/38 patients had to be excluded for the following reasons: In 3 patients, PET max was too close to the skull which did not allow a reliable CSI analysis due to bone artifacts; in 3 further patients, the CSI slice was outside of PET max as CSI examinations were performed without knowledge of MET-PET results.

MET-PET investigations

Patients received 800-850 MBq ¹¹C-methionine after fasting for 4 hours. PET images were then obtained from a dedicated full-ring GE Advance PET scanner (General Electric Medical Systems, Milwaukee, Wisconsin, USA). For detailed description of radiotracer production, data acquisition and reconstruction see. [START_REF] Potzi | 11C] methionine and [18F] fluorodeoxyglucose PET in the follow-up of glioblastoma multiforme[END_REF] The scanner produces 35 slices with a slice thickness of 4.25 mm in a field of view of 14.875 cm.

The spatial resolution of the scanner in axial direction is 4.0 mm and in tangential direction 3.8 mm. Image reconstruction was done by filtered back projection using a Hanning Filter with a cutoff value of 6.2 mm and a 256x256 matrix.

7/28

For the semiquantitative evaluation of tracer accumulation in tumor tissue the standardized uptake value (SUV) and the calculated ratio tumor/contralateral normal tissue (T/N ratio) were used. SUV was defined as radioactive concentration (MBq/g)/injected dose (MBq)*body weight (g). For quantification, a circular region of interest (ROI) was drawn over the tumor lesion with knowledge of tumor localization from structural imaging and clinical data and covering the hottest pixel of the lesion. Afterwards this ROI was mirrored contralaterally to the non-affected hemisphere. Maximal SUVs of these ROIs and T/N ratios were calculated.

PET max definition

To define a threshold for pathologic tracer uptake in PET, a T/N ratio was considered as normal below 1.15 or as non-specific (1.15 to <1.5). A T/N ratio >1.5 was regarded as pathologic. Areas with highest pathologic T/N ratios, reflecting most intense tracer uptake, were defined as PET max .

MRI/CSI investigations

Our routine MRI protocol for brain tumors consisted of axial fluid-attenuated-inversion-recovery sequences, diffusion-weighted images, axial, coronal T1-and T2-weighted sequences, and contrast-enhanced axial, coronal and sagittal T1-weighted sequences. All gliomas were classified by a neuroradiologist (D.P.) according to the pattern of CE: Only patients with none or unspecific (defined as "patchy" and "faint") CE were included in the study cohort of the initial 38 cases.

Patients with unequivocal (defined as "nodular" or "ring-like") CE as a target for tissue sampling

were not part of this study.

8/28

With the CSI software integrated in our routine clinical 3 Tesla (T) MRI scanner (Tim Trio, Siemens, Erlangen, Germany), single slice (2D) CSI examination could be performed in the course of the same examination as morphologic MRI.

The protocol for CSI consisted of a T2-weighted turbo spin echo sequence and a contrast-

enhanced

3

. The total acquisition time was less than 7 minutes.

Maps of the metabolic ratios Cho/total NAA (=NAA and N-acetylaspartylglutamate) and Cho/Cr were produced using the spectroscopy application within the spectrometer operating system (SyngoMR VB13 and VB15, Siemens, Erlangen, Germany). After zero filling, phasing, filtering (Hanning Filter, 400 ms) of the data, polynomial baseline correction was applied and line fit in the frequency domain was used to obtain Cho, Cr and total NAA signal intensity (area under the peak).

Metabolic ratio maps were created within the VOI using the numerical value interpolation as implemented by the manufacturer.

The CSI postprocessing software uses a rainbow-type color lookup-table whereby blue-greenyellow-red correspond to values from zero to maximum (see figure 1).

9/28 CSI max definition

A threshold of CSI ratio is needed to define pathological areas. Therefore, we tested various ratios in pilot CSI examinations preceding our study: We compared tumor areas with the contralateral tumor-free white matter. Both, for Cho/Cr and Cho/NAA, a ratio of ≥1.0 proved suitable as cut-off for specific color-coded visualization of the tumor area. Using this method, normal brain was not visualized. The area with the highest pathologic CSI ratios within a given tumor, reflecting the most abnormal metabolite ratio, was defined as CSI max (Cho/Cr max or Cho/NAA max ; figure 1d).

PET / CSI co-registration (figure 2)

Due to lack of spatial information, it is impossible to perform registration of a single slice of CSI metabolic map with an anatomic MR image stack that is routinely used for intraoperative navigation. To enable registration additional anatomic information is needed. Therefore, similarily to Stadlbauer, [START_REF] Stadlbauer | Integration of biochemical images of a tumor into frameless stereotaxy achieved using a magnetic resonance imaging/magnetic resonance spectroscopy hybrid data set[END_REF] we performed the following workaround: T2-weighted TSE MR images (15 slices, 2 mm slice thickness) centred around CSI FOV position were obtained. This image stack had FOV identical with CSI FOV (16 x 16 cm) and the matrix resolution identical with the resolution of standard CSI metabolic map (256 x 256). This data set provided the geometrical basis for the data integration into the navigation system. The CSI metabolic maps were projected on five central image slices from this T2-weighted stack, which were interposed between ten empty slices containing only geometric information from the T2-weighted images, five on top and five below the CSI map projections. The central five identical CSI slices of 2 mm thickness represent the real CSI slice acquisition dimension of 1 cm. This MRI/MRS hybrid data set was called "CSI sandwich".

10/28

Prior to surgery, the T2-weighted anatomic dataset was co-registered to the standard T1-weighted contrast-enhanced MR images using the semi-automated registration algorithm of the navigation software (Stealth Station Cranial Mach 5; Medtronic, USA). The system creates a registration matrix file for the T2-weighted anatomic image stack that was manually copied to the folder of the CSI sandwich dataset. This workaround resulted in a co-registration of the T1-weighted anatomic MR image data and the CSI slice.

Topographic correlation of CSI max and PET max

The navigation software provides a rainbow-type color lookup table which converts the grey scale values of the PET and CSI data to a black-red-yellow-green-blue-purple-white color scale 1 .

Prior to topographic correlation of CSI max and PET max we used the following windowing adjustments as standard in the navigation system: For removal of background tracer-uptake of normal brain in PET, the level slider was set to maximum and the width was increased from zero to just before the first background uptake of normal brain appeared. For CSI we used maximum level and width as standard.

After image fusion with contrast-enhanced MRI, the degree of overlap of CSI max and PET max areas visualized by this method was estimated semiquantitatively by visual impression by two authors (SW, GW) as follows: (1) Cho/Cr max and PET max and, (2) Cho/NAA max and PET max , and (3) Cho/Cr max and Cho/NAA max (table 1). The degree of overlap of the maxima of CSI and PET was categorized as follows:

(1) overlap ≥ 50%; (2) overlap < 50%; (3) distant (no overlap).

1 Notably, the navigation software color scale is in the opposite direction to the MRI software color scale: CSI max appears in red on the MRI software (see figures 1 and 5c) and in white on the navigation software (see all other figures).

11/28

The center of the CSI and PET areas was regarded as area of maximum metabolism and therefore used as target point for intraoperative tissue sampling with the aid of neuronavigational guidance.

Tissue sampling

Intraoperative navigation was performed with the co-registered CSI/PET/MRI data set. To minimize the effects of potential brain shift in our study, we used either conventional stereotactic biopsy through a burr hole (n=5 of 32 cases, table 1) or a technique very similar to a frameless stereotactic biopsy (n=27 of 32 cases): To minimize CSF loss, the patient positioning was selected with the craniotomy at its highest level. Immediately after dural opening, navigation accuracy was verified on surface veins successfully in all patients. Subsequently, the targets inside of CSI max and/or PET max were approached through a small corticotomy using a stereotactic biopsy needle tracked by the navigation system. Sampling of the target area was deliberately performed before tumor resection to ensure a minimal interference with the brain shift that would render the navigation-guided tissue sampling inaccurate.

Intraoperative tissue sampling was performed as follows:

(1) If Cho/Cr max and Cho/NAA max overlap was ≥50%, one tissue sample was taken from this area defined as CSI max .

(2) If Cho/Cr max and Cho/NAA max did not show significant overlap (<50%) specimens were collected from the area of higher metabolite ratio (defined as CSI max ).

(3) If CSI max and PET max showed overlap ≥50%, one tissue sample was taken from this area.

(4) If CSI max and PET max showed overlap <50%, separate specimens were taken from both areas.

12/28

(5) If PET was negative or showed only unspecific tracer uptake, specimens were taken from CSI max .

To additionally determine the ability of the metabolic imaging methods to detect anaplastic foci, intratumoral tissue samples outside of CSI max and/or PET max were collected as well by using the stereotactic biopsy needle for histopathological correlation purposes. In case of a glioma resection, additionally multiple tissue specimens were collected during tumor removal from intratumoral areas located definitely outside of CSI max and/or PET max , as shown by the navigation system.

Neuropathology

Histopathological tumor typing was performed by the local neuropathology according to the WHO 2007 criteria. [START_REF] Louis | WHO Classifcation of tumours of the central nervous system[END_REF] In each case, all tumor specimens were systematically analysed by one author (J.A.H) for anaplastic tissue areas (defined as areas with presence of mitotic figures, necrosis, microvascular proliferation, increased cell density and nuclear pleomorphism) for statistical analysis and to avoid under-grading. For histopathological diagnoses see table 1.

Additionally, tumor cell proliferation was assessed immunohistochemically using the MIB-1 antibody (anti-Ki-67, 1:50; DAKO). MIB-1 binding was apparent as nuclear staining. In each specimen, a total of 500 tumor cell nuclei were evaluated in "hot spots" i.e. fields showing the highest density of Ki-67 immunopositive cells by one author (A.W.), who was unaware of clinical patient characteristics. The fraction of immunolabeled tumor cell nuclei was expressed as percentage (MIB-1 labeling index (LI)).

13/28

If more than one sample of CSI max , PET max , and the tumor area outside of CSI max and/or PET max was available, the sample with the most anaplastic histopathologic criteria as described above and with the maximum MIB-1 LI was selected for statistical analysis.

Statistical analysis

For statistical analyses SPSS® version 16.0 software (SPSS Inc., Chicago, Illinois, USA) was used. The presence of histopathologic criteria of anaplasia inside versus outside of CSI max and PET max were compared using the Chi-square test. MIB-1 LI values showed a right-skewed distribution. Thus, for comparison of cell proliferation rates in different areas of a given tumor a non-parametric test (Wilcoxon rank-sum test for paired data) was applied. Values are given as mean and standard deviation. A P-value of <0.05 was considered significant.

RESULTS

Intratumoral metabolite ratios (table 1)

CSI ratios were pathologic (≥1.0) in all patients: Cho/Cr ratio was 2.7 ± 1.6 (range 1.2 -9.4), Cho/NAA ratio was 4.4 ± 3.7 (range 1.2 -14.8).

MET-PET demonstrated pathologic (T/N ≥ 1.5) tracer uptake in 21/32 patients: In these cases PET T/N ratio was 2.2 ± 0.7 (range 1.5 -3.8). However, normal (T/N < 1.2) or non-specific (T/N 1.2 -1.4) tracer uptake was encountered in 7 and 4 of 32 patients, respectively.

14/28

Topographic correlation

CSI versus PET (figure 3, table 1)

Topographic correlation was possible in 21 patients with pathological CSI ratios (ratios ≥1) and unequivocal pathological MET-PET T/N ratios (ratio ≥ 1.5). A ≥50% overlap of CSI (Cho/Cr max and Cho/NAA max ) and PET max was found in 18/21 cases and an overlap of <50% was present in 3/21 patients.

Due to the lack of a pathological PET T/N ratio (ratio <1.5), correlation was not possible in 11/32 cases: in 7/11 patients with normal T/N ratio, CSI ratios were pathologic and histopathological examination revealed a glioma WHO grade II in 5 and grade III in 2 patients, respectively. In the remaining 4/11 patients with non-specific tracer uptake, pathological CSI ratios were detected as well (WHO grade II in 2 and grade III in 2 patients, respectively).

CSI: Cho/Cr versus Cho/NAA (figure 4, table 1)

An overlap of Cho/Cr max and Cho/NAA max was found ≥50% in 24/32 and <50% in 8/32 cases, respectively. Of the cases with <50% overlap, 6/8 cases exhibited a peculiar pattern with a central Cho/NAA maximum and satellite-like surrounding Cho/Cr maxima.

Histopathologic criteria (table 2)

Of the 32 patients with DIG, tissue samples inside and outside of the CSI max and PET max of a given tumor were available in 25 and 17 cases, respectively. In the remaining patients, biopsies were taken only from the site of the metabolic maximum and thus had to be excluded from this analysis.

15/28

For the histopathologic criteria of anaplasia (mitotic figures, necrosis, microvascular proliferation, increased cell density and nuclear pleomorphism), mitotic figures were significantly more frequently present within CSI and PET maxima as compared to peripheral tumor regions. Further, microvasular proliferation was significantly more frequently encountered inside PET max and nuclear pleomorphism inside CSI max as compared to peripheral tumor areas.

For both CSI and PET, the proliferation rate assessed by MIB-1 LI was significantly higher inside the maximum metabolite ratio area than outside. In the cases with negative or non-specific PET tracer uptake, CSI max still exhibited a significantly higher proliferation rate than in the surrounding tumor areas (10.8% inside CSI max versus 5.2% outside CSI max , p=0.011).

DISCUSSION

CSI is a metabolic imaging technique that is widely available and does not expose the patient to radiation exposure. In this study, we investigated the clinical usability of CSI for detection of anaplastic foci in DIG with non-significant CE and performed correlation with MET-PET. We found pathologic CSI ratios in all patients, whereas MET-PET was pathologic in only 21/32 patients. The CSI max and MET-PET max showed significant topographic overlap (≥50%) in the majority of cases (18/21 patients).

Previous studies have shown that MET-PET max represents areas of highest malignancy within DIG.[8,9,11,12] Consequently, we used MET-PET max as reference for topographic correlation with CSI max in our study.

16/28

A topographic correlation of the maxima of CSI and PET in DIG has been observed in single cases. [START_REF] Go | Contribution of magnetic resonance spectroscopic imaging and L-[1-11C]tyrosine positron emission tomography to localization of cerebral gliomas for biopsy[END_REF][START_REF] Luyten | Metabolic imaging of patients with intracranial tumors: H-1 MR spectroscopic imaging and PET[END_REF] A systematic topographic analysis has been performed in only two previous small exploratory studies: Go analysed three patients with DIG using multivoxel MRS and L-1-11 Ctyrosine-PET. [START_REF] Go | Localised proton spectroscopy and spectroscopic imaging in cerebral gliomas, with comparison to positron emission tomography[END_REF] In 2/3 patients the choline MRS and tyrosine PET maxima showed significant topographic correlation, only partial overlap was observed in the third patient. The number of patients in our series without pathological MET-PET seems high compared to other studies. One possible explanation is the relatively high cutoff value in our series: Whereas other studies used lower cutoffs (between 1.2 and 1.5), [6,7,12,[START_REF] Herholz | 11C-methionine PET for differential diagnosis of low-grade gliomas[END_REF][START_REF] Kracht | Delineation of brain tumor extent with [11C]L-methionine positron emission tomography: local comparison with stereotactic histopathology[END_REF] we defined a rather high cutoff of T/N ratio ≥1.5 as pathologic for the following reasons: According to our experience, gliomas with T/N ratios between 1.15 and <1.5 often demonstrate diffuse tracer uptake without distinct focal maximum. This situation does not allow a reasonable topographic correlation with CSI max as we observed in all 4 patients with T/N ratio between 1.2 and 1.4. In contrast, a distinct focal maximum of MET-PET was detected in all patients with a T/N ratio ≥1.5, which does permit topographic correlation with CSI max .

18/28

Cutoff values for pathologic CSI ratios have not been consensually defined in the literature so far.

Therefore, we empirically defined CSI ratios of ≥1.0 as pathologic (see Methods). Thereby, we achieved specific color-coded visualization of distinct intratumoral CSI maxima, whereas regions in the normal brain were not visualized (figure 5c). According to this cutoff definition, all patients in our series had clearly pathologic maxima of CSI.

Herminghaus reported a significant correlation of total choline concentration with MIB-1 LI in neuroepithelial tumors using single voxel MRS, which was proposed as a preoperative tool for tumor grading. [39] Due to potential intratumoral heterogeneity, however, single voxel MRS may miss small anaplastic foci.

To determine the ability of CSI to detect such anaplastic foci, we assessed the WHO criteria of anaplasia as well as the cell proliferation rate measured by MIB-1 LI in tumor samples inside and outside of CSI max : A significantly higher MIB-1 LI, presence of mitotic figures and nuclear pleomorphism was encountered inside the CSI max (see table 2). As CSI max and PET max showed significant topographic correlation in the majority of patients, MIB-1 LI, presence of mitotic figures and microvascular proliferation was significantly higher in the area of maximum PET tracer uptake as well. It is of note that even in cases with negative or non-specific PET tracer uptake, CSI was able to depict tumor areas of increased proliferation rate.

Current Limits of CSI

The low spatial resolution of CSI of 1 cm is an inherent limitation for detection of intratumoral anaplastic foci. Compared to the higher resolution of PET (0.4 cm), however, our data demonstrate 19/28 that CSI visualization of intumoral "hotspots" correlates with PET max topographically and may be of additional value in cases of negative or non-specific tracer-uptake in PET scan.

The largest diameter of the suspected glioma on T2-weighted images was our key criterion for selection of the single CSI slice, without knowledge of MET-PET findings. Such an approach may miss PET max . Indeed, co-registration of CSI max and PET max revealed a PET max outside of the selected CSI slice in 3/38 patients.

Reliable detection of the metabolically active tumor areas may be achieved by three-dimensional CSI. [START_REF] Mcknight | Correlation of magnetic resonance spectroscopic and growth characteristics within Grades II and III gliomas[END_REF][START_REF] Nelson | Serial evaluation of patients with brain tumors using volume MRI and 3D 1H MRSI[END_REF] Alternatively, multi-slice CSI could solve the problem. This method uses parallel contiguous CSI slices covering the majority of the tumor volume. We are currently testing the reliability of multi-slice CSI at our center. shows significant topographic correlation with PET max in the majority of our glioma patients.

Further, CSI max corresponds to regions with increased proliferative activity within these tumors.

Therefore, the intraoperative use of CSI data by multimodal neuronavigation may increase the reliability of detection of malignant areas in DIG with non-significant CE and consequently optimize allocation of patients to adjuvant treatments. Step 1 -Image registration of T2-weighted anatomic dataset (co-planar to CSI stack) to the standard T1-weighted contrast-enhanced MR images.

REFERENCE LIST

Step 2 -Manual copying of the resulting registration matrix file from the T2-weighted anatomic image stack to the folder of the CSI sandwich dataset on the navigation system.

Step 3 -For intraoperative application, the resulting registered morphologic T1-weighted and metabolic CSI image datasets are loaded into the navigation system. processing depicts a central CSI max . d: Focused CSI max (Cho/NAA) after windowing at the navigation workstation. e -f: Tissue sample from CSI max . e: HE depicts prominent anaplasia of the astrocytic tumor part with brisk mitotic activity (magnification x200). f: MIB-1 labeling index of the Ki-67 antigen > 40% (magnification x400). g-h: Tissue sample from outside of CSI max . g: HE depicts a low- grade tumor area; h: MIB-1 labeling index of the Ki-67 antigen <9%.

  study cohort comprises a consecutive series of 38 patients with DIG with non-significant CE treated at the Department of Neurosurgery of the Medical University of Vienna between July 2007 and November 2009. This study was approved by the ethics committee of the Medical University of Vienna.

  resonance-spectra from fronto-parietal brain region including the tumor lesion.(b) Maps of the metabolic ratios Cho/NAA are produced using the spectroscopy application within the spectrometer operating system. After zero filling, phasing, filtering of the data, polynomial baseline correction was applied and line fit in the frequency domain was used to obtain Cho and NAA signal intensity.(c) Metabolic ratio maps were created within the VOI using the numerical value interpolation as implemented by the manufacturer. Lower limit of the color map (blue) corresponds to a value of Cho/NAA 0.39 in this patient.(d) Rescaling of color map according to the predefined pathologic CSI ratio of ≥1: The blue color code now corresponds to the CSI min of 1.00. The red color code visualizes the tumor area with the highest Cho/NAA CSI ratio (CSI max = 1.96 in this patient).

Figure 2 -

 2 Figure 2 -Methods -Registration of single-slice CSI on morphologic MRI data for intraoperative navigation:

Figure 3 -

 3 Figure 3 -Topographic correlation of MET-PET and CSI maxima: a -c: Right parietal oligodendroglioma WHO grade III (case 22). a: PET max , b: CSI Cho/Cr max , c: PET/CSI co-registration resulting in >50% maxima overlap. d -f: Left precentral oligodendroglioma WHO grade II (case 25). d: PET max , e: CSI Cho/NAA max , f: PET/CSI co-registration resulting in <50% maxima overlap.

Figure 4 -

 4 Figure 4 -Topographic correlation of CSI Cho/Cr and CSI Cho/NAA maxima: a -c: Left frontal oligodendroglioma WHO grade III (case 30). a: Cho/NAA max , b: Cho/Cr max , c: Cho/NAA and Cho/Cr co-registration resulting in >50% maxima overlap. d -f: Right insular oligoastrocytoma WHO grade III (case 19). d: Cho/NAA max , e: Cho/Cr max , f: Cho/NAA and Cho/Cr co-registration resulting in <50% maxima overlap. Note the central Cho/NAA maximum and satellite-like surrounding Cho/Cr maxima.

Figure 5 -

 5 Figure 5 -Non-specific MET-PET tracer uptake with CSI max in a left precentral oligoastrocytoma WHO grade III (case 16): a: T1-weighted contrast-enhanced MRI: Note the non-enhancing left precentral lesion, b: MET-PET without distinct focal maximum, c: Complete single-slice CSI (Cho/NAA) as derived from MR post-

  Low or absent levels of NAA, however, are typically encountered in WHO grade IV gliomas which were not the primary pathology of interest in the present study. We therefore assessed the ratios multiple satellite-like Cho/Cr maxima. This characteristic pattern has not been described so far. It remains to be shown whether the center and the satellites are histologically different. Future studies could also clarify whether this peculiar Cho/NAA-Cho/Cr pattern is specific to gliomas with oligodendroglioma component, as observed in 5/6 of our cases.

	patients (3 oligodendrogliomas, 2 oligoastrocytomas and 1 astrocytoma) had a central Cho/NAA
	Stadlbauer reported ≥50% overlap of maxima of CSI (Cho/total NAA) and FET-PET in 11/15 patients and <50% overlap in 4/15 patients.[10] His study design differed from ours by the use of a 1.5 T maximum surrounded by In our series, pathological CSI ratios were detectable even in patients without pathological MET-
	MRI, FET as PET tracer, inclusion of glioblastomas, biopsy only, the use of Cho/total NAA CSI ratio PET (11/32 cases, figure 5). In 4/11 of these patients histological examination revealed an
	for topographical correlation with PET only. anaplastic glioma. Floeth reported glioma patients with pathologic single voxel spectroscopy but
	no pathological FET-PET.[5] Nelson reported that MRS was more reliable in tumor identification
	than	18
	Cho/Cr[18,21-28]	and/or	Cho/NAA[10,18,21-23,25,26]	derived	from	direct	output	of	the
	commercially available MRI software package that are most commonly reported in the literature.
	Topographic correlation of the maxima of both ratios revealed a high degree of overlap (≥50%) in
	most cases (24/32 patients). The remaining 8/32 patients showed an overlap of <50%: Six of these
				17/28

Despite of methodological differences, the results of all three CSI-PET correlation studies, including our own study, are similar and indicate that CSI maxima represent metabolically active areas in DIG.

For the detection of metabolically active areas in gliomas by changes in metabolites on MRS, different methods have been described: The calculation of relative metabolite levels in relation to normal brain tissue (such as the Cho-to-NAA index, CNI) has certain advantages, such as the generation of stable measures of Cho abnormality in voxels that have very low or absent NAA.

[START_REF] Mcknight | Correlation of magnetic resonance spectroscopic and growth characteristics within Grades II and III gliomas[END_REF]

F-fluorodeoxyglucose-PET in 12/38 cases.

[START_REF] Nelson | Serial evaluation of patients with brain tumors using volume MRI and 3D 1H MRSI[END_REF]

These three independent observations indicate that MRS may visualize metabolically active areas within DIG more sensitively than PET.

Table 1 -

 1 1. Barker FG, 2nd, Chang SM, Huhn SL, Davis RL, Gutin PH, McDermott MW, et al. Age and the risk of anaplasia in magnetic resonance-nonenhancing supratentorial cerebral tumors. Cancer Patient Characteristics

	1997;80(5):936-41.
	2. Ginsberg LE, Fuller GN, Hashmi M, Leeds NE, Schomer DF. The significance of lack of MR
	contrast	enhancement	of	supratentorial	brain	tumors	in	adults:	histopathological
	evaluation of a series. Surg.Neurol. 1998;49(4):436-440.
	3. Kondziolka D, Lunsford LD, Martinez AJ. Unreliability of contemporary neurodiagnostic imaging
	in	evaluating	suspected	adult	supratentorial	(low-grade)	astrocytoma.	J.Neurosurg.
	1993;79(4):533-536.
	4. Pallud J, Capelle L, Taillandier L, Fontaine D, Mandonnet E, Guillevin R, et al. Prognostic
	Significance of Imaging Contrast Enhancement for WHO grade II Gliomas. Neuro.Oncol.
	2008.
	5. Floeth FW, Pauleit D, Wittsack HJ, Langen KJ, Reifenberger G, Hamacher K, et al. Multimodal
	metabolic	imaging		of		cerebral	gliomas:	positron	emission	tomography	with
	[18F]fluoroethyl-L-tyrosine		and	magnetic	resonance	spectroscopy.	J.Neurosurg.
	2005;102(2):318-327.
	6. Gumprecht H, Grosu AL, Souvatsoglou M, Dzewas B, Weber WA, Lumenta CB. 11C-Methionine
	positron emission tomography for preoperative evaluation	of	suggestive low-grade
	gliomas. Zentralbl.Neurochir. 2007;68(1):19-23.
	8. Roessler K, Gatterbauer B, Becherer A, Paul M, Kletter K, Prayer D, et al. Surgical target selection
	in	cerebral	glioma		surgery:		linking	methionine	(MET)	PET	image	fusion	and
	neuronavigation. Minim.Invasive.Neurosurg. 2007;50(5):273-280.
	9. Singhal T, Narayanan TK, Jain V, Mukherjee J, Mantil J. 11C-L-methionine positron emission
	tomography	in	the	clinical	management	of	cerebral	gliomas.	Mol.Imaging	Biol.
	2008;10(1):1-18.
	10. Stadlbauer A, Prante O, Nimsky C, Salomonowitz E, Buchfelder M, Kuwert T, et al. Metabolic
	imaging of cerebral gliomas: spatial correlation of changes in O-(2-18F-fluoroethyl)-L-
	tyrosine	PET	and	proton	magnetic	resonance	spectroscopic	imaging.	J.Nucl.Med.
	2008;49(5):721-729.
	11. Goldman S, Levivier M, Pirotte B, Brucher JM, Wikler D, Damhaut P, et al. Regional methionine
	and glucose uptake in high-grade gliomas: a comparative study on PET-guided stereotactic
	biopsy. J.Nucl.Med. 1997;38(9):1459-1462.
	12. Sadeghi N, Salmon I, Decaestecker C, Levivier M, Metens T, Wikler D, et al. Stereotactic
	comparison among cerebral blood volume, methionine uptake, and histopathology in brain
	glioma. AJNR Am.J.Neuroradiol. 2007;28(3):455-461.
	13. Pirotte B, Goldman S, Dewitte O, Massager N, Wikler D, Lefranc F, et al. Integrated positron
	emission tomography and magnetic resonance imaging-guided resection of brain tumors: a
	report of 103 consecutive procedures. J Neurosurg 2006;104(2):238-53.

7. Hatakeyama T, Kawai N, Nishiyama Y, Yamamoto Y, Sasakawa Y, Ichikawa T, et al. (11)Cmethionine (MET) and (18)F-fluorothymidine (FLT) PET in patients with newly diagnosed glioma. Eur.J.Nucl.Med.Mol.Imaging 2008.

Table 2 -

 2 Histopathologic Criteria

	27/28

ACKNOWLEDGMENTS

We thank Dr. Harald Heinzl, Department of Medical Computer Sciences, for statistical advice, Brigitte Dobsak for drawing the illustration and Irene Leisser& Gerda Ricken for technical assistance with preparation of tissue specimens.

Competing Interest: None declared Funding: None declared

The Corresponding Author has the right to grant on behalf of all authors, and does grant on behalf of all authors, an exclusive licence (or non-exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article (if accepted) to be published in Journal of Neurology, Neurosurgery & Psychiatry editions and any other BMJPGL products to exploit all subsidiary rights, as set out in our licence (http://jnnp.bmjjournals.com/ifora/licence.pdf).