Stéphane Genaud
email: genaud@unistra.fr

Julien Gossa
email: gossa@unistra.fr

Cost-wait Trade-offs in Client-side Resource Provisioning with Elastic Clouds

Keywords: cloud, provisioning, resource management

Recent Infrastructure-as-a-Service offers, such as Amazon's EC2 cloud, provide virtualized on-demand computing resources on a pay-per-use model. From the user point of view, the cloud provides an inexhaustible supply of resources, which can be dynamically claimed and released. This drastically changes the problem of resource provisioning and job scheduling. This article presents how billing models can be exploited by provisioning strategies to find a trade-off between fast/expensive computations and slow/cheap ones for indepedent sequential jobs. We study a dozen strategies based on classic heuristics for online scheduling and bin-packing problems, with the double objective of minimizing the wait time (and hence the completion time) of jobs and the monetary cost of the rented resources. We simulate these strategies on real grid workloads in two cases. First, we use the workloads as a whole, which is representative of a large community of users sharing some common resources. Second, we use the workloads extracted for each individual user. These lighter workloads correspond to users submitting work independently from others and paying for their own resources. Our findings show that on large workloads, a little budget increase allows to achieve optimal wait time, while trade-off heuristics may be largely beneficial for individual users with lighter workloads.

I. INTRODUCTION

Cloud computing sets a new paradigm for hardware infrastructure management by offering unprecedented possibilities to deploy software in distributed environments. Amazon's EC2 is one of the most well-know solution to provide a utility computing model. Their solution has contributed to popularizing the Infrastructure-as-a-Service (IaaS) paradigm, which enables on-demand provisioning of computational resources, operated by virtual machines (VMs) in cloud providers' data centers. Resources can be reserved on a pay-per-use basis, thereby eliminating capital and maintenance costs for customers. Resource provisioning consists in finding how many VMs are needed, for how long, and the type of hardware configuration fitting the job needs. In this work, we address the problem of resource provisioning on the client side in IaaS clouds. From a technical view point, prior to request a resource, the client must have prepared and transferred a customized VM image at the provider's site. Instances of these VM images can then be started, becoming ready to accept work tasks, and eventually released once they are no longer needed.

Afterwards, the provider invoices the client according to the billing model, the VM type, and the up-time of the VMs.

Clients usually perform the resource provisioning process manually, i.e they decide all by themselves when and what resources should be claimed and released. This might lead to naïve and suboptimal solutions, especially when the number of jobs increases and several resources are proposed at different prices and performance capabilities. A good decision is even harder to make when the billing model is complex and several groups of users are submitting concurrent jobs to the same shared infrastructure. Therefore, a brokering system must be interposed between the clients and the provider of the cloud.

There are two contradictory metrics involved in the evaluation of the choices for a client: the monetary cost of the resources and the completion time of the execution. Generally, meeting short completion time constraints implies to provision powerful and numerous resources, and thus pay a higher price. On the contrary, a low budget implies more tolerance regarding the completion time. When using a cloud infrastructure this choice is typically an online problem, i.e. at the time the job is submitted, it must be decided immediately whether extra resources need to be provisioned or already running instances are sufficient.

Note that we focus here on a specific billing model, based on the main Amazon's pricing model called on-demand, in which users pay by the hour for active VMs. Although per-hour billing is widely spread, some companies propose different billing time units (BTU) or alternative pricing models. For instance, in the reserved model at Amazon, a resource is rented for 1-3 years for a fixed amount of money and in turn has a lower hourly price when used. A third pricing model called spot is based on bidding and requires different techniques to optimize its usage, as studied in [START_REF] Yi | Reducing costs of spot instances via checkpointing in the amazon elastic compute cloud[END_REF]. The on-demand pricing presents two interesting characteristics. First, the cost of deployment is linear only in the BTUs spent, independently of the number of VMs started (modulo the deployment and shutdown overheads). Hence, one VM instance running for two hours costs the same as two instances for one hour. In other words: parallelization is free. Second, BTUs are relatively coarse grain (e.g 1 hour) and each started unit of time is due. As a result, any job whose runtime does not last exactly this time unit leaves idle time on the deployed instances, which can be recycled to run other jobs. Our main investigation in this paper concerns how this remaining time can be reused. Indeed, one may decide to reuse it by delaying the execution of submitted jobs. It enables to lower the cost but involves waiting time for jobs and thus increases the overall completion time. Inversely, one can decide to ignore this reusable time and avoid any wait time by launching new VMs at the cost of extra billed idle time. However, there are intermediate scenarii, where the global price can be reduced while preserving an acceptable wait time. This implies to define strategies where certain jobs are delayed when it is worth, and new instances are deployed when it does not increase the price of the solution.

The paper is organized as follows. Section II explains our assumptions and the problem we address in this paper. In Section III, we present the different strategies, which are evaluated in Section IV. The results are further discussed in Section V. Finally, we present some related work in Section VI and conclude with our future work plans.

II. PROBLEM STATEMENT

A. Assumptions

First, we assume that jobs are independent with known durations. This is for example the case when users submit their jobs through a local resource management system, which requires users to specify a maximum runtime. Second, we consider that tasks are not preemptible, e.g the migration of a running tasks is not possible and jobs can not be suspended to run another one. Third, we assume an online scheduling system: tasks must be dispatched to a resource as soon as they are submitted. Last, the pricing model is a piece-wise linear pricing model, such as on demand instances at Amazon. The billing period is discretized, each started billing time unit (BTU) being fully charged.

B. Problem

Let us introduce the problem on the example of Figure 1. The workload is composed of four job requests according to the chronology indicated on the time-line. The cheapest solution is to provision a single resource and to execute the jobs sequentially in the order they were submitted, as shown on the row labeled 1VM4All. In this case, enqueuing the jobs for execution on a single VM leads to an optimal cost since only the time between the end of J 4 and the end of the second BTU is wasted. An alternative is to reserve simultaneously several resources in order to execute some jobs in parallel, as exemplified on the other rows on Figure 1. These executions will complete earlier but the cost is likely to be higher since the chances to waste the remaining time after the last job's end are greater.

The problem of minimizing the cost is related to the variable-sized bin packing with fixed cost [START_REF] Friesen | Variable sized bin packing[END_REF]. In this problem, we are given a collection of bin sizes and an infinite supply of bins of each size. The objective is to pack a set of items of given sizes by choosing appropriate bins so as to minimize the total size of the packing. This a generalization of the classical bin packing problem where all bins have a size S and every object has a size s i < S. Both problems are NP-hard and many approximation algorithms have been proposed [START_REF] Coffman | Approximation algorithms for bin packing: a survey[END_REF]. In our context, items are jobs and bins are BTUs of VMs. However, the solutions proposed for this problem cannot be used directly. First, many of the approximation algorithms proposed do not apply because of our online constraint. For example, the FitDecrease series of algorithms requires to sort the set of items by size. Second, and most important, the classical bin-packing problem does not take into account the dynamics of the resource provisioning problem. Contrary to a bin, which has a same occupation until new items are packed in it, a VM is, by analogy, continuously filled (or billed) from the time it is started until it is released, whether we assign jobs to it or not. Moreover, as explained in the introduction, our problem has two objectives. Our timing considerations must not be only relative to the number of BTUs spent but also to the completion time of the jobs. Finally, we will resort to adapted versions of the classic bin packing heuristics in the online case to minimize the cost of provisioning.

III. PROVISIONING STRATEGIES

A. Model

As stated previously, we consider an online scheduling system. To model the dynamic state of the system, we essentially need to account at a given instant, for the active VM we have started. We also maintain a queue of jobs assigned to each active VM. The notations used are:

• V : Set of active virtual machines • q v : The job queue of v ∈ V • b v : The boot date of v ∈ V (s) • s v : The shutdown date of v ∈ V (s) • i v :
The date when v ∈ V becomes idle (s) (when q v becomes empty) • J: Set of arriving jobs • r j : The run time of j ∈ J (s) • c(x): Cost of one virtual machine for x seconds of up-time. For EC2: c(x) = pph * x/3600 where 3600 is the BTU and pph is its cost.

B. Common algorithmic phases

The strategies we propose can be expressed through algorithms sharing a common structure. These algorithms have two phases:

1) a deploy phase, invoked at each job submission. It consists in deciding (1) whether or not a new VM must be deployed, and (2) which active VM the job must be mapped to. It is described in Algorithm 1. 2) a release phase, triggered at a parameterized frequency. This release procedure is common to all strategies. It consists in deciding which active VMs must be shutdown and released. Each running VM is examined in turn, and an idle VM is kept running as long as it does not increase the cost. A shutdown occurs when it would incur additional charges.

Algorithm 1 Deploy(j,t) // a new job j is submitted, at date t

C ← ∅ // C is the set of candidate VMs (C ⊂ V ) for v ∈ V do if eligible(v, j) then C ← C ∪ {v} end if end for if C = ∅ then v ← optimum(C) else v ← deploy() // Create and run a new VM V ← V ∪ {v} end if enqueue(q v ,
j) // Map the job to the VM Where:

• eligible(v, j) is true if j can be assigned to q v , • optimum(C) returns the virtual machine to which a job j is to be assigned, • deploy() provisions and starts a new VM and returns its identifier, • enqueue(q v , j) adds the job to the queue of a given VM v. If v is available (i.e q v is empty) the job actually starts immediately on v without being queued.

eligible and optimum allow us to define all our provisioning strategies. eligible filters out the set of active VMs to which a job can be assigned depending on the current state of VMS. If this set is empty, then a new VM is deployed, otherwise optimum selects the VM to assign the job to among the set of candidate VMs. These definitions are summarized in Table I. Figure 1 shows an example use case. One can see that, whatever the strategy is, the VMs are only released at the end of the BTU, even after the execution of J 1 when there is no more job to run.

C. Strategies

We propose four sets of strategies, illustrated on Figure 1: • 1VM4All: The first strategy provisions a single VM and put all the jobs in its queue. It gives a lower bound on cost for the given workload, as idle time is reused at the maximum. • 1VMperJob-based strategies: On the opposite side of the spectrum, we devise three "expensive" strategies. • Relax-based strategies: RelaxFirstFit x, RelaxEarliest-Fit x and RelaxLastestFit x include a bound on the waiting time, which is expressed as a factor x. A new VM is deployed when no active VM can handle the job at constant cost or when the waiting time exceeds x times the runtime of the job. As shown on the example (Relax 0.5), a low value of x leads to a 1VMperJobPluslike behavior. Here, another VM is started for J 4 since using an already deployed VM would either increase the cost or make the execution end after the deadline. On the contrary, a high value of x leads to a Bin-Packing-like behavior, as the same delay is considered acceptable.

The three heuristics only differ in the VM they select.

They respectively select the first VM found, the VM that will be idle first and last.

IV. EVALUATION

To assess the performances of the different strategies, we used four datasets from real production grids publicly available from the Grid Workload Archive [START_REF] Iosup | The grid workloads archive[END_REF]. The main characteristics of the selected datasets are presented in table II: the total numbers of jobs, the number of distinct CPUs used, the number of users and groups, the average interarrival time between jobs, and the average runtime of jobs. All times are in seconds.

LCG is a data storage and computing infrastructure for the high-energy physics community using the Large Hadron Collider at CERN. This production Grid has about 180 sites with around 30,000 CPUs. The traces collected include only high-energy physics (HEP) data processing. Eleven days of activity starting from nov. 20, 2005 were logged. AuverGrid is a multi-site grid, part of the EGEE project. This grid is mainly used for biomedical and HEP applications. The logs account for one year of activity starting from jan. 2006. NorduGrid is a production grid for academic researchers composed of over 75 non-dedicated clusters contributed mostly by academic but also industrial, scientific or private organizations. Applications are from the areas of CAS, chemistry, graphics, biomed, and HEP. The traces used here contain the grid jobs for tree years starting from march 2003. SharcNet is a consortium of Canadian academic institutions who share a network of high performance computers. The traces analyzed were produced for a setup with 10 clusters over one year of activity starting from dec. 2005. They where originally provided by the Parallel Workload Archive and analyzed in [START_REF] Dror | Locality of sampling and diversity in parallel system workloads[END_REF]. The common data we can find in these traces are, for each job, its id, the submission time, the run time, the user id and the group id.

All strategies have been implemented in our own simulator which implements the algorithms described previously. The simulation uses the economic model of Amazon's EC2. The results of the simulations of the different provisioning strategies are plotted in Figure 2 and 3 along two performance metrics, the job average wait time, defined as the total wait time divided by the total number of jobs, and total cost of the resources, defined as the sum of the cost of each provisioned resource.

A. Results on complete traces

First, we make the assumption that each of the four workloads represents the requests from a whole group of users sent to the same submission system in order to mutualize cloud resources. We evaluate the strategies in this context where all requests are concurrent in the access to the resources. The simulations for these complete workloads are presented in Figure 2.

Very similar results are shown by the four workloads LCG, AuverGrid, NorduGrid and Sharcnet. If we compare the strategy 1VM4All designed to minimize the cost, and the set of 1VMperJob-based strategies designed to minimize the waiting time, we see that the average waiting times differ by about 9 to 10 orders of magnitude, while the cost is more or less the same, especially for enhanced versions. 1VMperJob-based strategies perform very well. For a small increase of price compared to 1VM4All the average wait time is reduced to zero. For instance, 1VMperJobPlus increases the price by only 3.5%, 2.5%, 1.1%, and 3.2% respectively on the four workloads. Among 1VMperJob-based strategies, 1VMperJobBest performs slightly better (respectively price increase by 2.7%, 2.2%, 1.0%, and 3.0%).

In other words, we learn from this simulation that there is little room to find a trade-off, as the cost can only be lowered by a few percents compared to the fastest/most expensive strategy. In consequence, "smartest" strategies are of no interest, as it is not possible to perform better than 1VMperJob-based strategies in term of average wait time, while possible price improvements are negligible.

B. Results on individual user traces

Next, we evaluate the strategies on the workloads extracted for each individual user of LCG. Each simulation hence corresponds to the case where a user submits his requests through his own scheduler.

We found that users can be differentiated depending on the margin between the costs resulting from application of the cheapest and the most expensive strategies. This margin represents the room available to find a trade-off. Different margins lead to different winning strategies. To classify the LCG users we looked at this cost margin, defined as the ratio of the cost of 1VMperJobPlus to the cost of 1VM4All. A ratio of 1 means that both strategies produce a solution of equal price, i.e. there is no room for a trade-off. We have plotted in Figure 4 a cumulative distribution of the cost margins. For a sake of illustration, we arbitrarily separate this distribution in four parts, corresponding to different situations. For each situation, we have chosen a representative user workload. The results for these users are shown in Figure 3. • 31% of the user workloads allow no cost margin (ratio=1). The job requests of user 96 in the LCG trace is an example of this situation. In that case, there is no cost difference between the cheapest 1VM4All and the fastest 1VMperJobPlus strategies. Moreover, there is no difference either in term of wait time for most of the users. Actually, this occurs with peculiar workloads having no concurrent jobs, or job runtimes greater than the BTU. This implies that all strategies perform the same. Some rare exceptions show an increase of wait time for 1VM4All or cost for 1VMperJob. In consequence, 1VMperJobPlus should be used for this type of workload. • 24% of the workloads allow a cost margin of up to 10% (ratio=1.1), like for instance LCG's user 155. In that case, the result is very close to our conclusion on For less than 10% of cost increase, the wait time can be reduced to 0 with the 1VMperJobPlus strategy while other strategies are of no use as they imply great increase of wait time for a small cost spare. • 21% of the workloads allow a cost margin of 10 to 40%, like for instance LCG's user 212. In that case, there is room for a trade-off and Bin-Packing based strategies are useful, as they allow to match the price of the 1VM4All strategy, while drastically reducing the wait time. Small differences appear between them: BestFit costs slightly less than WorstFit while having a slight increase of wait time, and FirstFit is in-between. But the most interesting strategies are the Relax-based ones. Indeed, they allow to control the trade-off thanks to their tolerance factor x. When x is low, these strategies behave like 1VMperJobPlus, while they behave like the Bin-Packing based ones with high x. Moreover, moderating x allows to find a trade-off in-between. Unfortunately, this moderation is not easy as we have not been able to find any pattern of its impact among users workload. Similarly, RelaxFirstFit x, RelaxLastestFit x and RelaxEarliestFit x perform slightly differently, but no pattern have been discovered. • Finally, 24% of the workloads allow a cost margin higher than 40%, like for instance LCG's user 10. The same observations apply as previously to these users, except that Bin-Packing based and Relax-based strategies are even more interesting and should be preferred to 1VMperJobPlus.

C. Conclusions

The strategies dynamically provision and release VMs, and we call the number of active VMs at a given instant the diameter of the provisioning. There is a direct relationship between the diameter and the cost margin. On Figure 5 is plotted the maximum diameters for each user's workload on LCG. It can be observed that the cost margin is limited when the provisioning diameter is high. Indeed, no margin exceeds 1.5 when the diameter exceeds 170. This is because large diameters implies the multiplication of the opportunities to reuse idle VMs, and thus very good efficiency of 1VMperJob-based strategies. This explains why there is no room for "smarter" strategies with complete platform workloads, where the diameter is naturally high. Hence, when the number of concurrent jobs is high, the best provisioning strategy is 1VMperJobBest. However, when this number is lower, Bin-Packing-based strategies are efficient as they allow to find a trade-off, and even to match the lowest cost while greatly improving the performances. The differences between each version of one same strategy (i.e. First/Best/Early) are not clear. Except for specific needs, First version can be chosen because of its lowest complexity. Nevertheless, Relax-based strategies are very interesting as they allow to control the trade-off between the 1VMperJob-based and the Bin-Packing-based strategies, and should be used in most cases.

V. DISCUSSION

We have shown that provisioning strategies can be designed regarding the billing models of cloud platforms, leading to different solutions in term of performance and price. However, our study is limited on several aspects.

First, certain technical details have been abstracted from the simulation,like the startup times (deployment, boot) and stop times (shutdown, release) of VM. These details do no impact the relevance of our study, as they are negligible face to the BTU. For example, the time to instantiate and start a VM instance at Amazon's EC2 is 60 to 130 seconds according to a recent study [START_REF] Ostermann | A performance analysis of ec2 cloud computing services for scientific computing[END_REF], while the BTU is 3600 seconds. However, such details have to be taken into account by a real brokering system, and should be handled carefully to optimize the solutions. For instance, if the startup time is greater than the time for one of the active VMs to become idle, then it is better to assign a job to this VM than to deploy a new one. This implies to modify the eligible condition in order to extend the set of candidates to this kind of VMs. Stop time must be handled carefully as well in order to avoid releases just after the BTU, leading to double cost with no performance improvement.

Next, we have considered the same runtimes on the cloud platform as in the workload traces because these last does not include information about the used CPU. However this does not change the conclusions of this study, but only implies that the presented prices and waiting time are not realistic.

Second, our work concerns only the provisioning problem, apart from the job scheduling problem. Indeed, the jobs are considered executed in a FIFO manner accordingly to our assumption of online scheduling. However, the same semionline scheduling as those of batch schedulers such as conservative [START_REF] Lifka | The ANL/IBM SP scheduling system[END_REF], aggressive [START_REF] Mu | Utilization, predictability, workloads, and user runtime estimates in scheduling the IBM SP2 with backfilling[END_REF] or selective back-filling [START_REF] Srinivasan | Selective reservation strategies for backfill job scheduling[END_REF] can be applied to the VM queues. This could improve the overall user experience. Such scheduling might have an impact on the provisioning strategy, for instance they might need a constant over-provisioning. Moreover, the presented provisioning strategies are designed for billing models based on coarse units of time and linear billing.

Finally, we only considered computation time and ondemand basic instances. Our model and strategies could be enhanced to take storage and data transfer costs into account, as well as different types of instance. Indeed, an efficient cloud-resources brokering system should be able to decide the characteristics of the instances to deploy, as well as to choose among the different billing models. Indeed, most of the cloud offers propose several types of instances, different in term of CPU speed, memory and allowed I/O. EC2's billing model is interesting as the cost of one simple-speed instance is the half of the cost of one double-speed instance. Consequently, just as parallelization is free, speed is free too. Thus, our approach can be adapted to find a trade-off between slow/cheap instances fully used and fast/expensive instances leaving more billed idle times.

Ultimately, our approach must be able to handle the decision between different cloud offers, by comparing the price and performances they can provide.

VI. RELATED WORK

We have concentrated in this paper on the decisions a user can make in choosing a satisfactory trade-off between cost and speed to process a set of independent jobs. The need to choose between several scenarii is perfectly exemplified by Deelman et al. [START_REF] Deelman | The cost of doing science on the cloud: the montage example[END_REF]. In this experimental study, users of a scientific application evaluate the benefits and costs of supplementing their in-house computers with cloud resources, taking into account computations and data transfer costs. From a more system oriented point of view, Marshall et al. [START_REF] Marshall | Elastic site: Using clouds to elastically extend site resources[END_REF] propose practical provisioning strategies implemented upon the Nimbus toolkit [START_REF] Keahey | Virtual workspaces: Achieving quality of service and quality of life in the grid[END_REF] in order to provide users with a responsive system. These strategies are designed empirically assuming simple job arrival patterns (one at a time, a stream of requests and a burst of requests). A more general study of scheduling strategies by de Assunc ¸ão et al. [START_REF] De Assunc ¸ão | A cost-benefit analysis of using cloud computing to extend the capacity of clusters[END_REF], based on simulation from real traces, investigates how classic local resource management systems would perform when simultaneously scheduling jobs onto in-house clusters and/or cloud resources. The authors devise several strategies to mix this two types of resources and evaluate their performances depending on the heuristics used for scheduling. This work is the closest to ours, given three main differences: they assume mixed types of resources while we consider cloud-only resources; they test only classical scheduling strategies of local management resource systems (backfilling strategies); Although their objective is to a minimize the cost, the used strategies have no direct impact on the cost. On the contrary, the bin-packing heuristics we have investigated try to minimize the number of time units used.

By contrast, many works address the problem of VMs provisioning on the server side. The objective is to maximize the platform utilization. Some are worth mentioning because they try to improve the users' satisfaction by better serving their requests. Even though the aim is to improve globally the satisfaction, they employ techniques which could be transposed to a client-side approach. Perez et al. [START_REF] Perez | Multi-objective reinforcement learning for responsive grids[END_REF] propose a learning scheme to prioritize the scheduling in presence of mixed workloads (interactive and best-effort jobs), with a bi-objective optimization problem: fairness among users and responsiveness of job requests. A similar goal is targeted by Quiroz et al. in [START_REF] Quiroz | Towards autonomic workload provisioning for enterprise grids and clouds[END_REF], which propose an online clustering approach to detect patterns in the stream of requests. The clustering process periodically outputs a set of VM classes, each related to the required resource configurations and numbers of VMs. For each class, the correlations between the user requirements and the real executions are continuously computed to provide a feedback to the provisioning process, which can adjust the resources to match users requirements.

VII. CONCLUSION AND FUTURE WORK

In this paper, we have shown that the same workloads can lead to different performances and price according to the provisioning strategy with regards to the pay-per-use model. We have proposed and evaluated a dozen strategies based on classic scheduling and bin-packing algorithms. Experiments on real traces show that when the workload is massive, fast and expensive strategies like 1VMperJob are very efficient because of the small price difference compared to the cheapest strategy, while offering the best performances. Moreover we have proposed enhanced alternatives to this strategy, presenting even better results. However, when the workload is lighter or the demand is specific, bin-packing based strategies are interesting. Especially, relax-based ones allow to constraint the waiting time according to the runtime of the job. They allow the user to tune the trade-off between performances and prices according to his specific needs.

The future work is twofold. First, we will investigate how extra scheduling strategies applied to queued waiting jobs can improve the current results, as discussed in Section V. We should also extend the work to consider the choice between different billing models and different types of resources. Second, we will work at giving the user a constant feed-back about the strategies. From a pragmatic point of view, the system should be able to tell the performance improvement per invested dollar for each candidate solution. We will also study how long-term workloads can be analyzed to provide the user with different possible budgets at month or year scale. Two issues might be investigated with this goal. First, the characterization of jobs submission patterns and their relationships with the strategies efficiency; Second, the use of our simulator to assess strategies efficiency without characterizing the job submission pattern. As a bottom line, our main objective is to design a user-side comprehensive and usable brokering system for cloud resources, taking the billing model at the core.

Figure 1 .

 1 Figure 1. Illustration of the provisioning strategies

Figure 2 .

 2 Figure 2. Average Wait Time (s) vs. Cost ($), for each strategy, on complete traces

Figure 4 .

 4 Figure 4. Cumulative distribution of cost margins on user traces

Figure 3 .

 3 Figure 3. Average Wait Time (s) vs. Cost ($), for each strategy, on user's traces

Figure 5 .

 5 Figure 5. Cost margins vs. Provisioning diameter on user traces

  On the example, a new VM is deployed to map the job J 3 because it can not be handled at constant cost otherwise. On the contrary, the execution of J 4 is delayed in order to reuse the idle time of this new VM. BestFit and WorstFit are identical to FirstFit except that they map the job to the VM that leaves the shortest and longest idle time respectively on the VM. Again, the objective is to respectively maximize and minimize the remaining reusable idle time. Fit heuristic selecting the VM which minimizes the waiting time of the job.

	strategy	eligible(v, j) returns true	optimum(C) returns v ∈ C such that ... comment
	1VM4All	always				v = v 0	Slowest/Cheapest
	1VMperJob	never				any
	1VMperJobPlus					any	Fastest/Most expensive
	1VMperJobBest	if qv = ∅				sv is maximum
	1VMperJobWorst					sv is minimum
	FirstFit					any	Regular BinPacking strategies
	BestFit					iv -sv is maximum
	WorstFit	if c(sv -bv) = c(sv -bv + r j )	iv -sv is minimum
	EarliestFit					iv is minimum + wait time optimization
	RelaxFirstFit x					any	Price optimization
	RelaxEarliestFit x if c(sv -bv) = c(sv -bv + r j )	iv is minimum + max wait time constraint
	RelaxLastestFit x	and (iv -t) < (x × rt)		iv is maximum
						Table I
			THE SCHEDULING STRATEGIES WITH THEIR RESPECTIVE PARAMETERS FOR ALGORITHM 1.
	trace	#jobs #CPUs #user/#grp arrival runtime
	LCG	188 041	24 115	216/28	5	8 970
	AuverGrid	347 611	475	405/9	78	25 186
	NorduGrid	78 1370	2 000	387/107	127	89 273
	SharcNet	1 195 242	6 828	412/1	28	31 964
			Table II
		WORKLOAD TRACES
	criteria. It is a

1VMperJob is a reference strategy for the lowest waiting time possible: it deploys a new VM for each new job request whatever the state of the other active VMs. As shown in the example with J 2 , an obvious improvement is to deploy a new VM only if no active VM is currently idle which can be immediately reused at no cost. 1VMperJobPlus implements this by returning the first idle VM found. 1VMperJobBest and 1VMper-JobWorst return the VM that will shutdown the latest and soonest respectively, in order to maximize and minimize the remaining reusable idle time.

• Bin-Packing-based strategies: We have implemented three classic heuristics for the online bin-packing problem

[

1], namely FirstFit, BestFit and WorstFit. In our context, FirstFit scans the list of already deployed VMs and maps the job to the first VM that does not require to prolongate the rent time over a new BTU, i.e we map the job for no extra-cost. If no such already started VM exits, a new VM is deployed. The above strategies have the objective to minimize the number of BTUs. Hence, it tends to minimize the global cost with little consideration to the completion time, which is absent from the original Bin-Packing problem. EarliestFit is a first approach to include this


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Introduction

The term primary open-angle glaucoma (POAG) describes a heterogeneous group of optic neuropathies that lead to optic nerve atrophy and permanent loss of vision. [START_REF]Terminology and guidelines for glaucoma. 3rd ed. Savona: editrice Dogma[END_REF] It is the second most prevalent cause of bilateral blindness in the Western world and affected about 67 million subjects in the year 2000. 2,3 POAG includes various clinical entities, such as ocular hypertension (OH), glaucoma with elevated intraocular pressure (high tension glaucoma HTG-POAG) and normal tension glaucoma (NTG), juvenile open angle glaucoma (JOAG). [START_REF]Terminology and guidelines for glaucoma. 3rd ed. Savona: editrice Dogma[END_REF] Genetic factors play a major role in the aetiology of HTG-POAG. Up to now 14 loci (GLC1A > GLC1N) have been associated with POAG using linkage analysis. [START_REF] Allingham | The genetics of primay open-angle glaucoma: A review[END_REF] Some HTG-POAG families have mutations in the genes associated to GLC1A, GLC1E and GLC1G loci. Mutations in the myocilin gene (MYOC) at locus GLC1A, have been reported in 2-4% of HTG-POAG patients and in up to 33% of JOAG patients. [START_REF] Libby | Complex genetics of glaucoma susceptibility[END_REF][START_REF] Fingert | Analysis of myocilin mutations in 1703 glaucoma patients from five different populations[END_REF] In 2002, the Optineurin gene (OPTN), associated to GLC1E locus was identified. [START_REF] Bruttini | Mutations in the myocilin gene in families with primary open-angle glaucoma and juvenile open-angle glaucoma[END_REF] In the 54 families analysed with adult-onset HTG-POAG and in at least one member with NTG, OPTN mutations have been found in 16.7% of cases. [START_REF] Rezaie | Adult-Onset Primary Open-Angle Glaucoma Caused by Mutations in Optineurin[END_REF] In these families individuals with autosomal dominant NTG were present. In 2005 a new locus on chromosome 5q22 related to HTG-POAG and NTG was identified. [START_REF] Quigley | Number of people with glaucoma worldwide[END_REF] The associated gene, WDR36, was also identified. Sequence variations in the WDR36 gene were identified in approximately 5% of POAG cases. 2 WDR36 is a member of the WD40 repeat protein family. WDR36 sequence variants can lead to an altered cellular phenotype supporting the theory that WDR36 partecipate in polygenic form of glaucoma. [START_REF] Footz | Glaucoma associated WDR36 variants encode functional defects in a yeast model system[END_REF] Interestingly, the T-cell mediated response has been in turn hypothesized to partecipate in optic nerve degeneration. [START_REF] Hauser | Distribution of WDR36 DNA sequence variants in patients with primary open-angle glaucoma[END_REF] The aim of this study was to define the frequency of WDR36 sequence variance in glaucoma Italian families.

4

Methods and Patients

The study was performed in accordance with the tenets of the Declaration of Helsinki. The local ethics committee approved the study. To record the clinical characteristics of the patient, a standard form was provided and written informed consent was obtained from each participant. A visual field was classified as glaucomatous when: 1) three adjacent points depressed by 5 dB, with one of the points depressed by at least 10 dB; 2) two adjacent points depressed by 10 dB;

or 3) a 10 dB difference across the nasal horizontal meridian in two adjacent points. None of the points could be edge points unless immediately above or below the nasal horizontal meridian. 12 In 5 addition, visual field testing was considered reliable only when false-negative responses were less than 30% and fixation losses were less than 20%. 12 The perimetric defect type and stage evaluation were performed using the Brusini's glaucoma staging system. [START_REF] Brusini | Clinical use of a new method for visual field damage classification in glaucoma[END_REF] POAG is characterized by progressive narrowing of the neuroretinal rim. An optic nerve head was classified abnormal when it was present a ONH notch, or a concentric thinning of the neuroretinal rim, or both in combination. [START_REF]Terminology and guidelines for glaucoma[END_REF][START_REF] Tuulonen | Initial glaucomatous optic disk and retinal nerve fiber layer abnormalities and their progression[END_REF] At the end of the examination, glaucomatous patients were catalogued into three groups.

Patients

Molecular analysis

Blood samples were collected from affected and healthy family members (total number of collected samples was 141). Genomic DNA was isolated from the peripheral blood leukocytes by using the QIAamp DNA Blood Kit according to the manufacturer protocol (Qiagen, www.qiagen.com). We used the OD260/280 method on a photometer to determine the appropriate DNA concentration. [START_REF] Monemi | Identification of a novel adult-onset primary openangle glaucoma (POAG) gene on 5q22.1[END_REF] All 23 coding exons and flanking introns of the WDR36 gene were amplified using primers designed on intronic sequences (Table 1

Results

Thirty-four familial cases were enrolled in the study from the 6 eye centers involved in the project. Number of affected members per family varied from 2 to 6 individuals. Analysis of the pedigrees suggested an autosomal dominant inheritance in all families. A total number of 141 subjects underwent to accurate clinical examination. The clinical examination allowed us to define 69 affected individuals (37 females and 32 males). Among the 34 enrolled families, 25 were affected by HTG-POAG, 4 by JOAG and 1 by NTG-POAG. In addition, 4 families presented both JOAG patients and HTG-POAG patients within the same pedigree.

DHPLC mutation analysis of WDR36 gene was performed in the 34 probands of above reported families. In all families mutation in MYOC gene and in OPTN gene were previously excluded [START_REF] Fingert | Analysis of myocilin mutations in 1703 glaucoma patients from five different populations[END_REF] (and personal data). The following intronic variants have been identified: IVS12+190

G>T; IVS13+89G>A; IVS16-30A>G. None of these variants segregate with the disease in the families. The following four already known intronic polymorphisms were found: IVS5+30C>T; IVS12+90 G>T; IVS13+89G>A; IVS16-30A>G. [START_REF] Quigley | Number of people with glaucoma worldwide[END_REF] In addition, a novel polymorphism was found: IVS21-75G>A. This change was present in our population in 13% of patients and 14% of controls.

One proband was found to carry the D658G mutation reported as the more recurrent diseasecausing allele. [START_REF] Quigley | Number of people with glaucoma worldwide[END_REF] The proband, aged 58 years, was affected by HTG-POAG, with an age at diagnosis of 45 years (Fig. 1). He had three sons, one female and two males, aged, 35, 32 and 28 years, respectively. In the sons, ocular hypertension started at 20, at 19 and 27 years, respectively and it was controlled by antihypertensive treatment. Segregation analysis showed that the mutation was inherited only by the youngest son (Fig. 1).

Discussion

The aim of this study was to define the involvement of WDR36 sequence variance in glaucoma Italian families. We previously demonstrated that in the Italian population, about 6% of the familial cases with primary open angle glaucoma has a mutation in MYOC gene. [START_REF] Bruttini | Mutations in the myocilin gene in families with primary open-angle glaucoma and juvenile open-angle glaucoma[END_REF] On the contrary, no mutations were found in OPTN gene. [START_REF] Ariani | Optineurin gene is not involved in the common hightension form of primary open-angle glaucoma[END_REF] Since the WDR36 gene has been recently reported as the third glaucoma-causing gene, we decided to evaluate which fraction of Italian cases is due to this new gene. We did not find any pathogenic mutation in our cohort of patients. We identified only intronic polymorphisms. In one family we identified the D658G mutation, previously reported as the more recurrent disease-causing allele. [START_REF] Ariani | Optineurin gene is not involved in the common hightension form of primary open-angle glaucoma[END_REF] Furthemore, in the four families in which we found JOAG and POAG, we can supposed that glaucoma onset was different among the family members, but the disease was likely the same. The different classification was due to the classification methods, that we use in clinical practice, indeed the main different between POAG and JOAG is the glaucoma onset. [START_REF]Terminology and guidelines for glaucoma. 3rd ed. Savona: editrice Dogma[END_REF] Hauser et al analyzed a large cohort of patients with glaucoma for mutations in WDR36 gene. They found several nonsynonymous single-nucleotide polymorphisms, including those previously described as "disease-causing" and "disease susceptibility," in both patient and control subjects. [START_REF] Hauser | Distribution of WDR36 DNA sequence variants in patients with primary open-angle glaucoma[END_REF] They concluded that abnormalities in WDR36 were not sufficient alone to cause HTG-POAG.

In 2006, Pang et al mapped a new locus for juvenile open angle glaucoma in 5q22.1-q32. [START_REF] Pang | A genome-wide scan maps a novel juvenile-onset primary open angle glaucoma locus to chromosome 5q[END_REF] They described a region of maximum lod score located telomerically with respect to WDR36, by studying a family with 27 members, in which 9 were confirmed JOAG patients. The analysis of the WDR36 coding sequence did not reveal any pathogenic mutation and it definitively excluded the involvement of this gene in generating the phenotype.

In 2008, Pasutto et al recruited 399 patients with glaucoma and 376 healty subjects and investigated the prevalence of WDR36 variants in German populations. [START_REF] Pasutto | Profiling of WDR 36 Missense Variants in German Patients with Glaucoma[END_REF] A total of 44 WDR36 allelic variants were detected but the occurrence of several rare putative disease causing variants in patients with glaucoma suggested to the authors that WDR36 may be a minor disease causing gene in glaucoma at least in the German population.

In Hauser et al. HTG-POAG patients WDR36 sequence variations were associated with a more severe disease phenotype than those without, suggesting that the sequence variants in WDR36 may play a role in disease susceptibility rather than causation. [START_REF] Hauser | Distribution of WDR36 DNA sequence variants in patients with primary open-angle glaucoma[END_REF] POAG is a disease with a complex inheritance that is likely to result from contributions of multiple genes and possibly environmental conditions. Mendelian autosomal dominant and recessive forms of glaucoma are caused by single gene defects but the genetic etiologies results from contributions of multiple genetic factors that independently are able to cause the disease.

Genes that contribute to POAG may not cause clinical evidence of the disease unless they are coupled with other genes or environmental factors. For this reason the identification of any one disease-predisposing factor can be difficult when using traditional linkage approaches. Our findings suggested that WDR36 sequence variance were only rare causes of glaucoma in Italian families with glaucoma. Clearly, investigation of additional families with extensive studies are request to clarify the role of WDR 36 in the pathophysiology of glaucoma. It is very important the identification of susceptibility and glaucoma modifying genes for the complete genetic and molecular understanding of POAG, for this reason the European Glaucoma Society has a project to create an European genetic database to better study the glaucoma phenotypes. [START_REF] Founti | Biobanks and the importance of detailed phenotyping: a case study--the European Glaucoma Society GlaucoGENE project[END_REF] .

Figure legends

Figure1: Segregation analysis of D658G change.

The proband and the youngest son have the same mutation. On the contrary the other two sons do not bear mutation. Symbols, white = unaffected subjects, black = glaucoma, grey = ocular hypertension.

Tables 1 Table 1. Oligonucleotides primers and PCR/DHPLC conditions for WDR36 analysis.

  were classified as POAG when they were 35 years and older and either typical

glaucomatous VF loss or glaucomatous alterations of the ONH. Based on the IOP values the POAG group was divided into two groups: HTG-POAG if an IOP > 21 mmHg and NTG-POAG if IOP < 21 mmHg. If the patients were younger than 35 years and also an IOP > 21 mmHg and either typical glaucomatous VF loss or glaucomatous alterations of the ONH, they were classified as JOAG.

[START_REF]Terminology and guidelines for glaucoma. 3rd ed. Savona: editrice Dogma[END_REF]

  PCR and DHPLC analysis conditions are reported in Table1. Direct sequencing of the purified PCR products was performed in both directions (PE Big dye terminator cycle sequencing kit) on an ABI310 Automated Sequencer and analysed with the Sequencher software .

	). Mutation analysis was performed
	by Denaturing High Performance Liquid Chromatography (DHPLC) using the Transgenomic
	WAVE TM 3500 HT (Transgenomic, San Jose, CA, USA;http://www.transgenomic.com) (Underhill

PA et al Genome

Res 7:996-1005, 1997)

. PCR product were denatured at 95°C, reannealed at 65°C for 10 minutes, and cooled to 4°C to generate heteroduplexes. The optimal column temperature for fragments analysis was calculated using the WaveMaker Software (Transgenomic, San Jose, CA, 6 USA).


MD Hemma Resch

Barbara Brela

Christa Resch-Wolfslehner

MD Clemens Vass
email: clemens.vass@meduniwien.ac.at

Position of retinal blood vessels correlates with retinal nerve fiber layer thickness profiles as measured with GDx VCC and ECC

Keywords: RNFL thickness, blood vessel position, scanning laser polarimetry

Background: Our aim was to evaluate the correlation of the retinal blood vessel position and the retinal nerve fiber layer (RNFL) thickness profile.

Methods: RNFL thickness of 81 healthy subjects was measured using scanning laser polarimetry (SLP). To quantify the retinal blood vessel position we measured on the SLP printout the angle (superior and inferior) between a horizontal line and a line from the optic disc centre to the intersection of the most temporal major retinal blood vessel and the outer margin of the measurement ellipse.

Results:

We report a negative correlation between both the superior and inferior angle and the superotemporal and inferotemporal RNFL thickness, and a positive correlation between both angles and the superonasal and inferonasal RFNL thickness. The steepest slope of the regression line was located in the superotemporal and inferotemporal regions (-0.7 to -1.0 µm/deg). Using this slope the difference in RNFL thickness for the interquartile range of the superior angle was 13 µm.

Conclusion:

RNFL thickness profiles correlate with the location of the main temporal superior and inferior blood vessels. The application of a normative database, taking into account the position of major blood vessels might improve the diagnostic power of RNFL measurement.

Introduction

The GDx (Carl Zeiss Meditec, Dublin, CA, USA) is a scanning laser polarimeter (SLP) that assesses RNFL thickness in the peripapillary retina and discriminates well between normal subjects and glaucoma patients. [START_REF] Weinreb | Association between quantitative nerve fibre layer measurement and visual field loss in glaucoma[END_REF][START_REF] Weinreb | Scanning laser polarimetry to measure the retinal nerve fibre layer of normal and glaucomatous eyes[END_REF][START_REF] Choplin | Differentiating patients with glaucoma from glaucoma suspects and normal subjects by nerve fiber layer assessment with scanning laser polarimetry[END_REF][START_REF] Colen | Prevalence of split nerve fiber layer bundles in healthy eyes imaged with scanning laser polarimetry[END_REF] In healthy eyes, the peripapillary RNFL thickness modulation pattern around the optic disc also referred to as a temporal-superior-nasal-inferior-temporal (TSNIT) graph, was shown to follow a double-hump pattern, with thicker RNFL superiorly and inferiorly and thinner RNFL temporally and nasally. [START_REF] Leung | Comparative study of retinal nerve fiber layer measurement by StratusOCT and GDx VCC: I: correlation analysis in glaucoma[END_REF] Considerable interindividual variability in RNFL thickness values among normal subjects as measured with OCT [START_REF] Ghadiali | An analysis of normal variations in retinal nerve fiber layer thickness profiles measured with optical coherence tomography[END_REF], and some overlap in thickness values between normal subjects and glaucoma patients have been reported in several studies conducted by SLP. [2-4, 7, 8] Various diseases, most notably glaucoma, result in the death of retinal ganglion cells (RGC) and the degeneration of their axons. The loss of RGC axons in turn leads to a thinning of the RNFL. One method for assessing pathological RNFL appearance is by comparing the RNFL to normative values, derived from healthy subjects. These normative values will be more specific when normal physiological differences are taken into account.

Only recently Hood et al have demonstrated qualitatively that the local maxima in the RNFL profile of OCT3 and GDx are associated with blood vessels. [START_REF] Hood | A framework for comparing structural and functional measures of glaucomatous damage[END_REF][START_REF] Hood | Blood vessel contributions to retinal nerve fiber layer thickness profiles measured with optical coherence tomography[END_REF] Statistical analysis concerning the impact of retinal blood vessel position on the total circumpapillary TSNIT profile of RNFL have not yet been published. Understanding the sources of the intersubject variability is central to the understanding and improvement of RNFL thickness-measurements as a test for glaucomatous damage. It was the aim of the present study to examine the influence of the retinal blood vessel position on the RNFL thickness profile around the optic disc as measured with GDx VCC (variable corneal compensation) and ECC (enhanced corneal compensation).

Subjects and Methods

Subjects

The study protocol was approved by the Ethics Committee of the Medical University of Vienna and followed the guidelines of Good Clinical Practice and the Declaration of Helsinki. 83 subjects of both sexes aged between 19 to 71 years (mean 27.27 years ± 9.5) were included.

Inclusion and exclusion criteria

Inclusion criteria were normal ophthalmic findings, especially normal appearance of the optic disc, normal visual fields and IOP and lack of significant retinal disorder. An abnormal visual field was defined as a glaucoma hemifield test outside normal limits and/or a corrected pattern standard deviation with P<0.05. [START_REF] Keltner | Classification of visual field abnormalities in the ocular hypertension treatment study[END_REF] A normal IOP was defined as ≤ 21mmHg. Any of the following excluded a subject from participation in the trial: Evidence of any eye disease except refractive error, history of ocular trauma or intraocular surgery within the last 6 months, ocular inflammation or infection within the last 3 months, astigmatism more than +2.0 diopters and ametropia of more than +/-5.0 diopters.

Experimental Paradigm

Initially a prestudy screening was carried out, where the medical and ocular history was taken. A complete ophthalmological examination was performed, including fundoscopy, visual acuity, measurement of intraocular pressure (IOP) by Goldmann applanation tonometry and standard automated perimetry (SAP).

Subjects eligible for participating in the study according to the inclusion/exclusion criteria were included. One eye was selected randomly for the GDx VCC and ECC measurements.

The study was performed at the Department of Ophthalmology, Allgemeines Krankenhaus, Vienna.

Methods

Automated visual field testing was performed with the Humphrey field analyzer II (program 30-2). Visual field eligibility criteria were less than 33% false-positive responses, less than 33% false-negative responses, and less than 33% fixation losses.

Scanning laser polarimetry GDx VCC was performed using a commercial GDx VCC system Version 5.5.0 (NDB Version 1.05.00, Carl Zeiss Meditec, Dublin, CA, USA). Additionally we used the GDx-ECC method, which provides individualized corneal compensation with enhanced SLP measurement sensitivity. Details of set-up are described elsewhere. [START_REF] Zhou | Individualized compensation of anterior segment birefringence during scanning laser polarimetry[END_REF][START_REF] Weinreb | Glaucoma detection using scanning laser polarimetry with variable corneal polarization compensation[END_REF] Briefly, SLP assesses RNFL thickness in the peripapillary retina by measuring the RNFL birefringence with a near-infrared diode laser. With GDx ECC software, the corneal polarization compensator is automatically adjusted so that the combined retardation magnitude from the cornea and the compensating retarder is approximately 55 nm with a vertical slow axis of polarization. This adjustment bias serves to boost the signal to overcome low sensitivity that can make retardation measurements susceptible to optical and electronic noise. After image acquisition, the bias is subtracted to yield the RNFL retardation values.

In our study, each subject with pupils undilated had scans on the same day performed by an experienced operator. The spherical equivalent refractive error was tested subjectively and entered into the software to allow the GDx VCC and ECC to focus on the retina. All selected images were of high quality (quality scan score of 8 or greater) with a centred optic disc, were well focused and illuminated throughout the image, and were without motion artefacts.

A fixed concentric measurement band with 27 pixels (approximately 2.4 mm) inner and 35 pixels (approximately 3.2 mm) outer diameter was centred on the optic disc, after which the measurements of peripapillary retardation were conducted. Areas of blood vessels are a source of noise and are therefore automatically excluded for analysis by the GDx software. [START_REF] Colen | Prevalence of split nerve fiber layer bundles in healthy eyes imaged with scanning laser polarimetry[END_REF] Retardation was converted to an estimate of RNFL thickness by the software. The GDx data were exported to a personal computer for data analysis.

To examine the retinal blood vessel position we measured the angle between a line through the centre of the optic disc and the most temporal major retinal blood vessel at a particular peripapillary location at 35 pixel distance from the optic disc centre (= outer margin of the measurement band) and between a horizontal line through the optic disc centre. This was performed separately on the GDx printout for the upper and the lower retinal blood vessels using a setsquare. The respective values are referred as superior angle and inferior angle.

All analyses were done for GDx VCC and ECC. The parameters investigated in this study were RNFL thickness values of 64 sectors ("plot") around the optic disc on the measurement band, and the parameters of the GDx standard printout: temporal-superior-nasal-inferiortemporal (TSNIT) average, superior average, inferior average, ellipse standard deviation (TSNIT SD), as well as nerve fiber indicator (NFI) and typical scan score (TSS).

Statistical methods

We calculated linear regression analyses with the superior angle and the inferior angle as independent variables and the RNFL thickness values of 64 sectors "plot" of the TSNITgraph as dependent variables. To depict the slopes of the regression lines of the 64 sectors according to the formula (y=Kx + d) and their significances we plotted a modified TSNIT graph using K-values and the upper and lower limits of the 95% confidence interval (CI) of the K-values. Statistical significance of the slope was reached when the 95% CI did not include zero. While this analysis yields the clinically relevant information about the effect size (= slope) it is not identical with an analysis of the strength of the correlation. We thus additionally checked the significance of Pearson R to test the strength of correlation of the superior or inferior angle with each of those sectors.

To test the linearity of regression we additionally performed a stepwise multiple linear regression analysis using the inferior angle and its square and the superior angle and its square. Statistical analyses were done with the SPSS® software package (SPSS Inc. USA) release No. 16.0.2.

Results

44 female and 37 male subjects were included into the study. Subjects' baseline characteristics, IOP and visual field mean deviation (MD) are given in table 1. We were only able to obtain a sufficient measurement quality of 81 out of 83 patients. Hence all data are from 81 subjects.

There was a significant correlation between the superior angle and the inferior angle (r= 0.344, p= 0.002). The refractive error correlated significantly with the superior angle (r= 0.29, p= 0.01) but not with the inferior angle (r= 0.18, p= 0.112).

TSS VCC and ECC, superior and inferior angle mean values are summarized in table 2. The correlation of GDx VCC and ECC parameters with the superior angle and the inferior angle are shown in table 3. For these parameters the main finding was a significant negative correlation between the superior angle and the superior average of RNFL in GDx VCC and GDx ECC.

The slopes of the regression lines of the superior and the inferior angle with the RNFL thickness values of the 64 sectors around the optic disc are displayed in modified TSNIT graphs (figure 1, 2, 3, 4). These figures clearly demonstrate a statistically significant negative correlation between the superior angle and the temporal superior and temporal inferior RNFL thickness values, and a (less pronounced) positive correlation between the superior angle and the nasal superior and nasal inferior RFNL thickness values, for both GDx VCC and ECC (figure 1,2). The same correlation was found between RNFL thickness values and the inferior angle (figure 3,4).

The steepest slope of the regression line was located in the superotemporal and inferotemporal regions (-0.7 to -1.0 µm/deg). Using this slope the difference in RNFL thickness for the interquartile range of superior angle is 13 µm. For the 10% to 90% range of superior angle (55 to 89 deg) this difference amounts to 34 µm. The maximum R values were found superotemporally for the superior angle and inferotemporally for the inferior angle (-0.497 to -0.627).

Discussion

The RNFL thickness profiles measured with OCT vary across individuals, even when refractive error and scan quality are taken into consideration. [START_REF] Ghadiali | An analysis of normal variations in retinal nerve fiber layer thickness profiles measured with optical coherence tomography[END_REF] This variation in RNFL profiles is large, relative to that found owing to measurement error, [START_REF] Blumenthal | Reproducibility of nerve fiber layer thickness measurements by use of optical coherence tomography[END_REF][START_REF] Paunescu | Reproducibility of nerve fiber thickness, macular thickness, and optical nerve head measurements using StratusOCT[END_REF][START_REF] Budenz | Reproducibility of retinal nerve fiber thickness measurements using the stratus OCT in normal and glaucomatous eyes[END_REF] age, [START_REF] Bowd | Imaging of the optic disc and retinal nerve fiber layer: the effects of age, optic disc area, refractive error, and gender[END_REF][START_REF] Hougaard | Modelling the normal retinal nerve fibre layer thickness as measured by Stratus optical coherence tomography[END_REF] or the size of the optic disc. [START_REF] Bowd | Imaging of the optic disc and retinal nerve fiber layer: the effects of age, optic disc area, refractive error, and gender[END_REF][START_REF] Savini | Correlation between retinal nerve fibre layer thickness and optic nerve head size: an optical coherence tomography study[END_REF] Reference values for RNFL thickness of different ages, ethnic groups, and refractive stages are needed to define normality of RNFL thickness.

In the present study we could find a correspondence between the location of retinal blood vessels and the RNFL thickness around the optic disc (TSNIT graph) as measured with SLP.

We investigated whether the angle of specific retinal blood vessels -the most temporal major retinal blood vessels superiorly and inferiorly -diverging from the optic nerve head has an impact on the RNFL thickness around the TSNIT graph. We report that smaller superior or inferior angles (oblique retinal vessel course) were associated with thicker RNFL in the superotemporal and inferotemporal regions, but thinner RNFL in the superonasal and inferonasal regions. A more oblique course of the most temporal major retinal blood vessels is thus associated with a more oblique location of the arcuate bundles of retinal nerve fibers.

We are the first to demonstrate a statistical correlation of retinal blood vessel position with RNFL distribution around the optic disc using SLP. This is in correspondence with the results of the original article of Hood DC et al, [START_REF] Hood | Blood vessel contributions to retinal nerve fiber layer thickness profiles measured with optical coherence tomography[END_REF] where a correlation was reported between the position of large retinal vessels and the position of RNFL thickness maxima as measured with GDx and OCT. However, this analysis was qualitative not quantitative.

Why should there be an association of retinal blood vessels and the thicker branches of RNFL? It has been established for several organs and also for the retina [START_REF] Stone | Development of retinal vasculature is mediated by hypoxiainduced vascular endothelial growth factor (VEGF) expression by neuroglia[END_REF][START_REF] Stalmans | Arteriolar and venular patterning in retinas of mice selectively expressing VEGF isoforms[END_REF] that axon cues offer guidance for sprouting and developing vasculature. Vasculature may even share common guidance signals with axons. [START_REF] Carmeliet | Common mechanisms of nerve and blood vessel wiring[END_REF][START_REF] Dorrell | Mechanisms of endothelial cell guidance and vascular patterning in the developing mouse retina[END_REF] Considering these findings one should expect some correlation between the location of the superior temporal and inferior temporal arteries and veins, for example, and the distribution of RGC axons (especially at the localization of the temporal arcuate nerve fiber bundles). As a consequence, the location of the blood vessels may help to predict the variation in the profiles of RNFL thickness because they mark regions of increased axonal density.

Our findings may be of relevance for the diagnostic accuracy of RNFL measurements.

Normal eyes with a straight course of RNFL may be more prone to false positive RNFL defects at the temporal superior or inferior regions, right beside the edge of the arcuate RNFL bundles. On the other hand in glaucomatous eyes with an oblique RNFL course a small RNFL bundle defect located temporal superior or inferior might be missed by the GDx. This patient would have started off with high RNFL values in these regions and even after a partial loss of RNFL these values might remain within normal limits. The opposite problem might occur in the nasal superior and nasal inferior sectors. These regions however, are believed to be of less clinical importance for the diagnosis of glaucoma.

In the clinical situation the problem described above is reduced to some extent by interocular comparison. At least in false negative glaucoma patients, asymmetry in the RNFL distribution is displayed. As a high degree of symmetry is expected in normal eyes, asymmetry is a useful clinical sign of early glaucoma. However symmetry is sometimes limited in normal eyes and the disease itself may also be symmetric in some patients.

When interpreting the results of this trial a number of intrinsic limitations have to be discussed. We had the aim to test a simple indicator of the retinal vessel distribution for the postulated effect on the RNFL distribution. While we found that even our simple parameter of retinal vessel location had a significant correlation with the thickness of RNFL over 1/3 to1/2 of the circumference, we did not test the effect of other retinal vessels. We also did not take into account split bundles that might also influence RNFL thickness. [START_REF] Colen | Prevalence of split nerve fiber layer bundles in healthy eyes imaged with scanning laser polarimetry[END_REF] Split bundles primarily occur in the superior region and only rarely in the inferior region. Our data however demonstrate a similar effect of superior temporal and inferior temporal blood vessel location on the RNFL. Split bundles thus do not appear to have greatly influenced our study results.

Furthermore we cannot exclude the possibility that the automatic exclusion of major blood vessel positions from analysis by the GDx software might have influenced our findings.

Another limitation might be the assumption of linear association between blood vessel position and RNFL thickness. To test a possible non-linear relationship we additionally performed a stepwise multiple regression analysis including a quadratic term of the angle. This analysis demonstrated a non-linear relationship for 25% of the plots with significant results. However, the effect of non-linearity was small (data not shown).

For clinical use of our findings an automated analysis of the blood vessel position would be necessary. Since the GDx automatically excludes the major blood vessels from the RNFL measurement, the according data of blood vessel locations should be available also for analyses similar to ours, although the present software does not offer access to these data.

Finally, the axon density seems to be well coupled to the location of the superior and inferior temporal arteries and veins. A better understanding of the relationship between the distribution of the major blood vessels and GDx RNFL thickness helps us to understand interindividual variation. Reduction of interindividual variation in RNFL profiles may lead to an improvement of specificity and sensitivity of RNFL measurements. The application of a normative database, taking into account the position of major blood vessels might therefore improve the diagnostic power of RNFL measurement.

Figure 1 :

 1 Figure 1: Correlation between RNFL as measured with GDx VCC and the superior angle.The slopes of the regression lines (K) together with the limits of the 95% CI of the slopes are plotted against the 64 sectors (plots). Statistical significance of the slope is reached when the 95% CI does not include the zero line. The sections of the TSNIT graph marked with a bold line symbolize significance of Pearson R.

Figure 2 :

 2 Figure 2: Correlation between RNFL as measured with GDx ECC and the superior angle.The slopes of the regression lines (K) together with the limits of the 95% CI of the slopes are plotted against the 64 sectors (plots). Statistical significance of the slope is reached when the 95% CI does not include the zero line. The sections of the TSNIT graph marked with a bold line symbolize significance of Pearson R.

Figure 3 :

 3 Figure 3: Correlation between RNFL as measured with GDx VCC and the inferior angle. The slopes of the regression lines (K) together with the limits of the 95% CI of the slopes are plotted against the 64 sectors (plots). Statistical significance of the slope is reached when the 95% CI does not include the zero line. The sections of the TSNIT graph marked with a bold line symbolize significance of Pearson R. RNFL = retinal nerve fiber layer, VCC = variable corneal compensation, CI = confidence interval

Figure 4 :

 4 Figure 4: Correlation between RNFL as measured with GDx ECC and the inferior angle. The slopes of the regression lines (K) together with the limits of the 95% CI of the slopes are plotted against the 64 sectors (plots). Statistical significance of the slope is reached when the 95% CI does not include the zero line. The sections of the TSNIT graph marked with a bold line symbolize significance of Pearson R. RNFL = retinal nerve fiber layer, ECC = enhanced corneal compensation, CI-confidence interval

Table 1 :

 1 Subjects baseline characteristics, IOP and visual field MD

	Age (years)	27.3 ± 9.5 *
	Sex (female/male)	44/37
	Refractive error (dioptres) -0.23 ± 1.55 *
	IOP (mmHg)	14.8 ± 2.4 *
	MD (dB)	-0.13 ± 0.59 *
	* Results are presented as means ± standard deviation (SD), (n=81).
	IOP = intraocular pressure, MD = mean deviation, dB = decibel

Table 2 :

 2 Mean values of TSS VCC and ECC, superior and inferior angle

		mean values ± SD	interquartile range
	TSS (VCC)	95.05 ± 11.39	95.5 -100.0
	TSS (ECC)	98.65 ± 4.67	100.0 -100.0
	superior angle	72.1 ± 11.08	65.0 -78.5
	inferior angle	77.06 ± 9.96	71.0 -85.0
	TSS = typical scan score, VCC = variable corneal compensation, ECC = enhanced corneal
	compensation, SD = standard deviation

Table 3 :

 3 Correlation of GDx VCC and ECC parameters with the superior angle and the

	inferior angle
		superior angle	inferior angle
		r	significance	r	significance
	GDx ECC NFI	0.287	0.052	0.114	0.396
	TSNIT	-0.066	0.779	-0.038	0.859
	TSNIT SD	0.369	0.224	0.278	0.309
	Average superior	-0.351	0.014	-0.232	0.075
	Average inferior	0.079	0.617	0.011	0.940
	TSS	0.069	0.800	-0.159	0.519
	GDx VCC NFI	0.212	0.129	-0.025	0.845
	TSNIT	-0.348	0.132	0.058	0.781
	TSNIT SD	0.452	0.068	0.132	0.558
	Average superior	-0.317	0.027	-0.173	0.185
	Average inferior	-0.030	0.839	-0.009	0.947
	TSS	0.204	0,060	-0.122	0.213
	VCC = variable corneal compensation, ECC = enhanced corneal compensation, NFI = nerve
	fiber indicator, TSNIT = temporal, superior, nasal, inferior, temporal average, TSNIT SD =
	ellipse standard deviation, TSS = typical scan score

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Competing Interest

None declared.


Sophie Plainer

Elfriede Wenzl

Ali A Saalabian

Christina Wohlfart

Bertram Vidic

Yosuf El-Shabrawi

MD Navid Ardjomand
email: navid.ardjomand@meduni-graz.at

LONG TERM FOLLOW UP WITH I-CARE PHACIC IOLs

Keywords: corneal endothelium, myopia, phakic IOL

Purpose: To evaluate visual quality and postoperative results as well adverse events in myopic patients undergoing I-CARE anterior chamber angle supported phakic intraocular lens (IOL) implantation.

Design

: A retrospective, nonrandomized, case series. Participants: Data of 29 eyes (16 patients) receiving I-CARE phakic IOL for high myopia (-11,66 ± 3,3) was analyzed. Methods: The IOLs were implanted between 2003 and 2006 at the Department of Ophthalmology, Medical University, Graz, Austria. The mean follow up was 51.7 ± 16 months (17 -78 months). Main Outcome Measures: We measured uncorrected visual acuity (UCVA) and bestcorrected visual acuity (BCVA); patients underwent, slit-lamp examination, corneal topography, Scheimpflug imaging and measurement of endothelial cells (EC).

Results: Mean UCVA and BCSVA were 0.63 and 0.94 decimal after one year. Endothelial cell loss was the most serious adverse event observed. Mean EC loss was 2%, 9%, 17%, 21%, 33% and 47% after one (n=17), two (n=20), three (n=17), four (n=17), five (n=12) and six (n=3) years, respectively. Eight IOL explantations were made due to severe EC loss three to six years after implantation.

Other serious complications included one patient with an Urrets-Zavalia Syndrome (1 eye).

Conclusion:

Implantation of the I-CARE phakic-IOL is not a safe method for the correction of high myopia due to a serious endothelial cell loss, that might occur in a high number of patients. Patients with these IOLs should be followed up at least every 6 months and the IOL should be explanted, once the EC count drops to less than 2000 cells/mm 2 .

Introduction

Implantation of phakic intraocular lenses (IOL) for correction of ametropia has gained popularity over the last years, especially in eyes with higher refractive errors, where corneal procedures pose a risk for iatrogenic keratektasia [START_REF] Condon | ESCRS Ridley Medal Lecture: will keratectasia be a major complication for LASIK in the long term?[END_REF][START_REF] Dupps | Biomechanics and wound healing in the cornea[END_REF] .

The first phakic IOLs for the correction of myopia were introduced by Fechner & Worst and George Baikoff almost 20 years ago [START_REF] Fechner | The correction of myopia by lens implantation into phakic eyes[END_REF][START_REF] Fechner | Intraocular lens for the correction of myopia of the phakic eye[END_REF][START_REF] Baikoff | Surgical correction of severe myopia using an anterior chamber implant in the phakic eye. Concept--results[END_REF][START_REF] Baikoff | Phakic anterior chamber intraocular lenses[END_REF] . A high number of different phakic IOLs made of rigid or foldable material have been designed and implanted since then [START_REF] Saxena | Long-term follow-up of endothelial cell change after Artisan phakic intraocular lens implantation[END_REF][START_REF] Perez-Santonja | Surgical correction of severe myopia with an angle-supported phakic intraocular lens[END_REF][START_REF] Espandar | Phakic intraocular lenses[END_REF][START_REF] Kohnen | Evaluation of new phakic intraocular lenses and materials[END_REF] . The advantage of foldable compared to rigid phakic IOLs lies in the possibility to implant the IOL through a smaller incision, which reduces surgical time, has less influence on corneal astigmatism and may be stitchless.

A high number of studies on patients receiving rigid phakic IOLs have been published 8, 9, 11- 14 , but data on the outcome of foldable hydrophilic acrylic phakic IOLs are still rare [START_REF] Gierek-Ciaciura | Correction of high myopia with different phakic anterior chamber intraocular lenses: ICARE anglesupported lens and Verisyse iris-claw lens[END_REF][START_REF] Gierek-Ciaciura | Correction of high myopia with anterior chamber angle-supported phakic intraocular lenses--own results[END_REF][START_REF] Dick | Foldable Artiflex phakic intraocular lens for the correction of myopia: two-year follow-up results of a prospective European multicenter study[END_REF][START_REF] Guell | Evaluation of Verisyse and Artiflex phakic intraocular lenses during accommodation using Visante optical coherence tomography[END_REF] .

The French Society of Ophthalmology (SFO) withdrew all angle-supported phakic IOLs in 2007 due to severe endothelial cell loss two to three years after implantation [START_REF] Espandar | Phakic intraocular lenses[END_REF] .

Two short term studies on the I-CARE lens, a hydrophilic monobloc foldable phakic IOL, have been published, showing good and predictable results [START_REF] Gierek-Ciaciura | Correction of high myopia with different phakic anterior chamber intraocular lenses: ICARE anglesupported lens and Verisyse iris-claw lens[END_REF] . This retrospective study presents for the first time long-term results with foldable I-CARE phakic IOL in patients with high myopia.

Materials and Methods

The I-CARE lens (Corneal, France) is a phakic intraocular lens designed to treat highly shortsighted or hyperopic patients. It is a hydrophilic acrylic monobloc lens with four independent feet. The diameter of the lens' optic is 5.75 mm and it is available with an overall diameter from 12 mm to 13.5 mm. Candidates for implantation were patients without any major systemic diseases, who presented a stable myopia for at least two years, were older 24 years of age and did not show any other ocular co-morbidity but myopia. Ten patients had soft and six patients had rigid gas permeable contact lenses before phakic IOL implantation.

Visual acuity was tested and documented in decimal, but converted in logMar for statistical analysis. Clinical data of the patients are presented in table 1.

Implantation Technique

IOL size and dioptric power of the lens was calculated with a software available on the homepage of the Corneal company (France), which was based on the subjective and cycloplegic refraction and corneal white-to-white measurement (Orbscan II, Bausch&Lomb, USA).

Anterior chamber depth, measured by Orbscan II topography, was at least 3,4 mm as recommended by the company. EC count was at least 2400 cells/mm 2 in all cases and corneal astigmatism was less than 3.0 D in all patients (table 2).

All operations were done in local (n=11) or general anaesthesia (18) by one surgeon (BV).

The selection of anesthesia technique was based on the patients preference and the anesthesiologists recommendation. YAG iridotomy was performed the day before surgery in all cases.

The pupil was constricted with Miochol ® (Novartis, Germany), which was applied through a paracenthesis. Healon GV (Pfizer, USA) was then injected into the anterior chamber and a 3.0 mm corneoscleral tunnel was performed at the 12 o'clock position in all cases. The I-CARE phakic IOL was implanted with the injector and Healon GV was washed out at the end of the operation with a simcoe cannule. Sutures were not used in any patient.

IOL position

IOL rotation was measured using postoperative photography of the patients.

Decentration of the phakic IOL was determined by deviation of the center of the IOL from the center of the pupil 19

Statistical analysis

One-way ANOVA test was used for evaluating significance of difference during the follow up period for visual acuity (converted in log MAR for statistical analysis), refraction, intraocular pressure and endothelial cell count.

Results

Endothelial Cell Loss

There was no statistical significant decrease of the endothelial cell count within the first year, but a significant decrease could be seen after the second post-operative year. The average EC count was 1850 ± 693 cells/mm 2 after five and 1544 ± 136 cells/mm 2 after six years.

Endothelial cell count of less than 2000 cells/mm 2 was seen in five out of 17 eyes, in five out of 12 eyes and in three out of three eyes after four, five and six years, respectively. Exact data is shown in table 3.

IOL explantation

All IOL explantations were done due to a serious endothelial cell loss.

Eight IOLs were explanted within the third and sixth year after implantation and another two patients (two eyes) were scheduled for IOL explantation at the time of mauscript submission.

Exact data of eyes with IOL explantation are shown in table 4.

Visual acuity and refraction

Uncorrected (UCVA) and best corrected spectacle visual acuity (BCSVA) increased significantly after phakic IOL implantation. Best visual acuity was seen two years after implantation and decreased thereafter again, but the decrease between the second and fifth postoperative year was statistically not significant (p=0.50; 2 years vs 5 years) (exact data are shown in table 5).

Spherical equivalent was -0,26 ± 0,6 dpt one month after implantation and remained stable over the entire follow-up period.

Intraocular pressure

Two patients had increase of intraocular pressure (IOP) the day after surgery. IOP could be controlled in one case with a single i.v. application of acetazolamide 500 mg. The second patient developed an Urrets-Zavalia syndrome (Figure 1), but had normal IOP 48 hours after IOL implantation. IOP remained normal in all other patients during the entire follow-up period.

Halos

Halos were reported in six out of 16 patients (37,5%) within the first three postoperativ months. Two of these patients received brimonidine tartrate 0,2% ophthalmic solution for a period of three months. None of the patients reported problems with halos one year after phakic IOL implantation.

Pupil Ovalisation 12 eyes (41.4%) out of 29 showed a mild pupil ovalisation. Severe cases of pupil ovalisation were not seen and no explantations had to be made due to this complication (Figure 2).

Rotation and Decentration

In 17 cases (58.6%) the phakic IOL rotated at least 10°, the average rotation was 33°.

Decentration of the pIOL appeared in 8 eyes (Figure 3).

Discussion

Phakic IOLs have been introduced in the 1980s for the correction of myopia. George Baikoff introduced an angle-supported and Fechner & Worst an iris-claw phakic IOL [START_REF] Fechner | The correction of myopia by lens implantation into phakic eyes[END_REF][START_REF] Fechner | Intraocular lens for the correction of myopia of the phakic eye[END_REF][START_REF] Baikoff | Surgical correction of severe myopia using an anterior chamber implant in the phakic eye. Concept--results[END_REF][START_REF] Baikoff | Phakic anterior chamber intraocular lenses[END_REF] .

Corneal refractive surgery is a limited option, since the treatment of high myopia can result in keratectasia [START_REF] Condon | ESCRS Ridley Medal Lecture: will keratectasia be a major complication for LASIK in the long term?[END_REF][START_REF] Dupps | Biomechanics and wound healing in the cornea[END_REF] .

The first anterior chamber phakic IOLs were made of rigid material. Several foldable anterior chamber phakic IOLs made of acrylic or silicone material were introduced within the last years [START_REF] Espandar | Phakic intraocular lenses[END_REF][START_REF] Gierek-Ciaciura | Correction of high myopia with different phakic anterior chamber intraocular lenses: ICARE anglesupported lens and Verisyse iris-claw lens[END_REF][START_REF] Guell | Evaluation of Verisyse and Artiflex phakic intraocular lenses during accommodation using Visante optical coherence tomography[END_REF][START_REF] Kohnen | AcrySof Phakic Angle-supported Intraocular Lens for the Correction of Moderate-to-High Myopia: One-Year Results of a Multicenter European Study[END_REF] .

Rigid angle supported phakic IOLs have shown good refractive predictability and stable endothelial cell count. However, various serious adverse events including iris ischemia [START_REF] Fellner | Pupil ovalization after phakic intraocular lens implantation is associated with sectorial iris hypoperfusion[END_REF] have also been published. One of the main problems is sizing of the angle-supported phakic IOL [START_REF] Reinstein | Correlation of anterior chamber angle and ciliary sulcus diameters with white-to-white corneal diameter in high myopes using artemis VHF digital ultrasound[END_REF] . In cases of over-sizing, the eye will develop pupil ovalization and iris ischemia due to the pressure on the iris roots and in cases of under-sizing the IOL will rotate or dislocate 11, 21- 23 .

Only few studies report on results of hydrophilic acrylic foldable anterior chamber phakic IOLs [START_REF] Gierek-Ciaciura | Correction of high myopia with different phakic anterior chamber intraocular lenses: ICARE anglesupported lens and Verisyse iris-claw lens[END_REF][START_REF] Coullet | Severe endothelial cell loss following uneventful angle-supported phakic intraocular lens implantation for high myopia[END_REF][START_REF] Piovella | Long-term anterior chamber phakic IOL complications make strict, regular follow-up controls mandatory[END_REF] .

Our retrospective study investigated clinical outcome and complications after implantation of the I-CARE phakic IOL during a follow-up period of up to 6 years.

Corneal EC count was stable over the first 12 months, but a gradual decrease of the cells was observed between the second and 6 th post-operative year. The 6 th follow-up year is limited to three eyes of three patients, but all three eyes had an endothelial cell decrease to less than 2000 cells/mm 2 and the I-CARE IOLs were therefore explanted or scheduled for explantation. 2000 cells/mm 2 seems to be the critical limit to us and eyes with an I-CARE phakic IOL and an endothelial cell decrease to less than 2000 cells/mm 2 should be considered for IOL explantation, since all eyes with a central corneal endothelial cell count of less than 2000 cells/mm 2 seem to be progressive in terms of serious endothelial cell loss.

All anterior chamber phakic IOLs have a potential risk to damage the corneal endothelium.

Alio et al. have shown in a retrospective study, that endothelial cell loss was the second most common reason for explantation of rigid anterior chamber phakic IOLs [START_REF] Alio | Angle-supported anterior chamber phakic intraocular lens explantation causes and outcome[END_REF] . The mean explantation time after implantation was almost 9 years and counted for 24% of explantation reasons. In average, the endothelial cell loss with the latest generation of angle-supported rigid anterior chamber phakic IOLs is about 3 to 4% within the first year and then 1 -2% every year [START_REF] Perez-Santonja | Surgical correction of severe myopia with an angle-supported phakic intraocular lens[END_REF][START_REF] Espandar | Phakic intraocular lenses[END_REF][START_REF] Lovisolo | Phakic intraocular lenses[END_REF] . Two recent studies on foldable material showed similar results. A phase 3 non-randomized multicenter clinical trial showed an endothelial cell loss of 5% with the hydrophobic acrylic Acrysof angle-supported phakic IOL and only 1% cell loss with the foldable silicone iris-claw phakic IOL (Artiflex). However, the follow-up period was only 1 year with the Acrysof and two years with the Artiflex phakic IOL [START_REF] Dick | Foldable Artiflex phakic intraocular lens for the correction of myopia: two-year follow-up results of a prospective European multicenter study[END_REF][START_REF] Kohnen | AcrySof Phakic Angle-supported Intraocular Lens for the Correction of Moderate-to-High Myopia: One-Year Results of a Multicenter European Study[END_REF] . Both lenses are not comparable with the I-CARE phakic IOL since they vary in design and material.

Refractive predictability and stability of the I-CARE phakic IOl was similar to other anterior chamber angle supported phakic IOLs [START_REF] Perez-Santonja | Surgical correction of severe myopia with an angle-supported phakic intraocular lens[END_REF][START_REF] Espandar | Phakic intraocular lenses[END_REF][START_REF] Kohnen | AcrySof Phakic Angle-supported Intraocular Lens for the Correction of Moderate-to-High Myopia: One-Year Results of a Multicenter European Study[END_REF][START_REF] Lovisolo | Phakic intraocular lenses[END_REF] . One patient ended up with a spherical equivalent of -2,0 dpt and a second one with -1,5 dpt. All other patients were within ± 1,0 dpt and the refraction stayed stable over the entire follow up period.

Intraocular pressure did not significantly change after phakic IOL implantation with the exception of two patients developing an intraocular pressure peak of 60 mmHg on the first postoperative day. Whereas the pressure could be managed with acetazolamide in one patient without any long-term complications, the second patient developed an Urrets-Zavalia syndrome with iris ischemia and fixed dilated pupil. This complication is rare after anterior chamber phakic IOL implantation, but has also been described before with other types of phakic IOLs [START_REF] Park | Urrets-Zavalia syndrome following iris-claw phakic intraocular lens implantation[END_REF][START_REF] Yuzbasioglu | Fixed, dilated pupil after phakic intraocular lens implantation[END_REF] .

Halos are a known complication after corneal refractive surgery or phakic IOL implantation, if the patient has a large pupil under mesopic or scotopic conditions. Especially patients with the first generation of phakic IOLs complained about halos at night. The newer models in the late 1990s and beginning of 2000 had better optic edge for reduction of this phenomenon, but patients still described halos in up to 30% [START_REF] Perez-Santonja | Surgical correction of severe myopia with an angle-supported phakic intraocular lens[END_REF] . Six of our patients complained about halos immediately after IOL implantation and two patients were successfully started on brimodine eye drops. Lee JH et al have shown that brimonidine application once a day was sufficient to reduce halos after LASIK [START_REF] Lee | Efficacy of brimonidine tartrate 0.2% ophthalmic solution in reducing halos after laser in situ keratomileusis[END_REF] . There are no studies showing the effect of brimonidine in patients with phakic IOLs, but our two patients reported reduction of halos and the drops were stopped three months after onset. No patient complained about halos 12 months after IOL implantation.

Pupil ovalization is also a known complication of angle-supported phakic IOLs and counts for 10% of phakic IOL explantations [START_REF] Alio | Angle-supported anterior chamber phakic intraocular lens explantation causes and outcome[END_REF] . It is a result of iris ischemia via pressure on the iris roots [START_REF] Fellner | Pupil ovalization after phakic intraocular lens implantation is associated with sectorial iris hypoperfusion[END_REF] . This complication probably happens, when the IOL is over-sized. In contrast to rigid IOLs, which increase the pressure on the iris roots in cases of over-sizing, IOLs made of hydrophilic acrylic material develop a vaulting and decrease the distance to the corneal endothelium. One patient, who had an IOL explantation showed a distance of only 1030 µm from the central anterior surface of the IOL to the central corneal endothelium (Figure 4).

Coullet et al. recently presented three cases of I-CARE oversizing resulting in severe corneal

endothelial cell decrease with one eye undergoing corneal transplantation for corneal decompensation [START_REF] Coullet | Severe endothelial cell loss following uneventful angle-supported phakic intraocular lens implantation for high myopia[END_REF] .

In cases of under-sizing, the IOL will dislocate or rotate. This happened in 17 out of 29 eyes in our study. IOL rotation has been described in up to 50% within the first 24 postoperative months [START_REF] Perez-Santonja | Surgical correction of severe myopia with an angle-supported phakic intraocular lens[END_REF] .

The main problem of anterior chamber phakic IOLs, and especially foldable phakic IOLs, is the importance of exact measurement of the anterior chamber [START_REF] Lovisolo | Phakic intraocular lenses[END_REF] . An estimation from the white-to-white distance of the cornea is not adequate, since it does not represent the real anatomical structures of the internal eye.

Our study shows for the first time the long-term problems with the hydrophilic acrylic phakic IOL I-CARE. The lens is withdrawn from the market, but patients with an I-CARE phakic IOL should be seen at least every 6 months and in cases of endothelial cell decrease to less than 2000 cells/mm 2 IOL explantation should be considered. 1 month (n=21) 0,67±0,2 (0,4 -1,0) 0,88±0,2 (0,5 -1,25) -0,26 ± 0,6 (-1,0 to +1,0)

1 year (n=17) 0,63±0,2 (0,2 -1,25) 0,94±0,16 (0,5 -1,25) -0,50 ± 0,8 (-2,25 to +0,5)

2 years (n=20) 0,70±0,2 (0,5 -1,0) 0,98±0,17 (0,8 -1,25) -0,27 ± 0,7 (-2,0 to +1,0)

3 years (n=17) 0,69±0,2 (0,5 -1,25) 0,95±0,18 (0,8 -1,25) -0,29 ± 0,24 (-0,50 to 0,0) 4 years (n=17) 0,67±0,2 (0,32 -1,0) 0,90±0,20 (0,63 -1,25) -0,40 ± 0,52 (-1,25 to 0,0) 5 years (n=12) 0,59±0,2 (0,32 -1,0) 0,85±0,10 (0,8 -1,0) -0,75 ± 0,9 (-1,5 to 0,0) 6 years (n=3) 0,5±0,2 (0,4 -0,8) 0,80±0,09 (0,8 -1,0) -0,75 ± 0,9 (-1,5 to 0,0)

Table 1: Table 3:

The pre-and postoperative corneal endothelial cell count. p-values are given for comparison with preoperative data.

  Data of 16 patients (29 eyes; 6 female, 10 male), who had I-CARE phakic intraocular lens implantation at the Department of Ophthalmology, Medical University Graz between 2003 and 2006 were analyzed retrospectively. This retrospective case series was approved by the local Ethic committee. Pre-and postoperative clinical examination included slitlamp examination, Goldmann tonometry and corneal topography (Orbscan II, Bausch&Lomb, USA). Additionally endothelial cell (EC) count of the central cornea (Noncon Robo clinical specular microscope, Konan, USA), subjective and cycloplegic refraction and retinoscopy was performed in all patients at all visits. Pentacam imaging (Oculus, Germany) was performed in all patients postoperatively starting from January 2007.

  (y): years; (m): months; (D): diopters; (mm): millimeters; ACD: anterior chamber depth in mm (Orbscan); W -W: Horizontal white to white distance of the cornea (Orbscan).

Table 5 :

 5 UCVA: Uncorrected visual acuity; BCSVA: Bestcorrected spectacle visual acuity; SE: Spherical equivalent of spectacle refraction in dpt; BCSVA preoperative vs BCSVA 1 month: p=0.011; No statistical significant change in terms of BCSVA after 1 month. No statistical significant change in terms of UCVA and SE were seen between the first postoperative month and the 6 th postoperative year.

Figure 1 :

 1 Figure 1: Urrets-Zavalia Syndrome

Figure 2 :

 2 Figure 2: Rotation of the phakic IOL

Table 1 :

 1 Demographic data of the patients

		Mean ± SD
	Age (y)	37,5 ± 5,9 (28 to 53,21)
	Follow up (m)	51,7 ± 16 (17 -78)
	IOL power in (D)	-11,3 ± 2,43 (-16,0 to -7,0)
	IOL length (mm)	12,9 ± 0,40 (12 to 13,5)
	ACD to Epithelium	3,9 ± 0,28 (3,44 to 4,4)
	W -W (mm)	11,85 ± 0,38 (11,10 to 12,70)

Table 2 :

 2 Corneal Astigmatism and phakic IOL distance data.

		Pre-operatively	Post-operatively
	Corneal astigmatism (dpt)	1,26 ± 0,7 (0,2 -2,9); n = 29 1,40 ± 0,58 (0,2 -2,6); n = 24
	Endothelium -IOL (mm)		1,4 ± 0,23 (1,0 -2,0) n= 23
	Crystalline lens -IOL (mm)		1,4 ± 0,29 (1,0 -2,0) n= 23

Table 3 :

 3 Endothelial cell count (ECC) (cells/mm 2 )

		ECC	p
	Preoperative (n=29) 2755 ± 161 (2481 -3300)
	1 year (n=17)	2696 ± 260 (2444 -3194) 0,941
	2 years (n=20)	2503 ± 430 (1111 -3134) 0,016
	3 years (n=19)	2306 ± 582 (751 -3164) 0,004
	4 years (n=17)	2157 ± 574 (1200 -2785) 0,001
	5 years (n=12)	1850 ± 693 (530 -3030) 0,001
	6 years (n=3)	1544 ± 136 (1443 -1700) 0,006

Table 4 :

 4 Endothelial cell count (ECC) (cells/mm 2 ) of eyes with IOL explantation at the time

	of phakic IOL removal
	Patient	ECC	Years after implantation
	1	1324	3 years
	2	751	3 years
	3	1302	4 years
	4	1550	5 years
	5	1098	5 years
	6	1697	5 years
	7	530	5 years
	8	1443	6 years
	9	1490	6 years (scheduled)
	10	1700	6 years (scheduled)

Table 5 :

 5 Visual acuity and refraction

	UCVA	BCSVA	SE
	Preoperative	0.74±0,22 (0,4 -1,25)	-11,66 ± 3,3 (-18,0 to -7,0)