Insa Schiffmann
email: i.schiffmann@uke.de

Magalie Freund

Eik Vettorazzi

Jan-Patrick Stellmann

Susanne Heyer-Borchelt

Marie D'hooghe

Vivien Häussler

Anne Christin Rahn

Christoph Heesen

Vivien Häußler

Assessing the

Keywords: Clinicaltrials.gov NCT03872583. Registered on 13 March 2019 Multiple sclerosis, Evidence-based patient information, Magnetic resonance imaging, Risk knowledge, Disease-specific knowledge, Autonomy preferences, Shared decision-making, Randomized controlled trial, Process evaluation Melsbroek, Belgium

Background

Multiple sclerosis (MS) is a chronic demyelinating disease mainly affecting young adults; in Germany, more than 200,000 people are afflicted by MS [START_REF] Petersen | Epidemiology of multiple sclerosis in Germany: regional differences and drug prescription in the claims data of the statutory health insurance[END_REF]. Magnetic resonance imaging (MRI) plays a major role in the diagnosis [START_REF] Thompson | Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria[END_REF], predicting the prognosis [START_REF] Kaunzner | MRI in the assessment and monitoring of multiple sclerosis: an update on best practice[END_REF] and controlling treatment effectiveness during the course of the disease [START_REF] Río | Short-term suboptimal response criteria for predicting longterm non-response to first-line disease modifying therapies in multiple sclerosis: a systematic review and meta-analysis[END_REF]. Especially at the beginning of the disease, pwMS may have several MRIs within 12 months, and even in the absence of clinical disease activity, annual MRI monitoring has been suggested (Magnetic Resonance Imaging in MS (MAGNIMS)-Network) [START_REF] Filippi | MRI criteria for the diagnosis of multiple sclerosis: MAGNIMS consensus guidelines[END_REF]. While the number and location of MS lesions in MRI after the first clinical event has a limited predictive value for the progression in the following 7 or 20 years [START_REF] Fisniku | Disability and T2 MRI lesions: a 20-year follow-up of patients with relapse onset of multiple sclerosis[END_REF], lesion load during the course of the disease is virtually unrelated to clinical appearance of a patient. This discrepancy is called the "clinico-radiological paradox" [START_REF] Chard | Resolving the clinico-radiological paradox in multiple sclerosis[END_REF]. There is no international consensus about handling the occurrence of new MS lesions when assessing treatment effectiveness. For example, while there is evidence that the appearance of more than 3 new T2 lesions predicts treatment failure in pwMS treated with beta-interferons [START_REF] Río | Short-term suboptimal response criteria for predicting longterm non-response to first-line disease modifying therapies in multiple sclerosis: a systematic review and meta-analysis[END_REF], many neurologists follow the "no evidence of disease activity" (NEDA) concept and may change treatment even after the appearance of a single new silent T2 lesion [START_REF] Stangel | Towards the implementation of 'no evidence of disease activity' in multiple sclerosis treatment the multiple sclerlosis[END_REF].

Therefore, oftentimes, when MRI results are discussed in the context of initiation or change of a diseasemodifying drug (DMD), there is no clear medically superior option. These so-called preference-sensitive decisions are predestined for a shared decision-making (SDM) approach, in which physician and patient discuss options together. A prerequisite for SDM is a sufficient disease-specific knowledge. In pwMS, however, this knowledge has proven to be only moderate with around 60% of correctly answered questions in MS-specific [START_REF] Heesen | Risk knowledge in relapsing multiple sclerosis (RIKNO 1.0)--development of an outcome instrument for educational interventions[END_REF][START_REF] Giordano | The Multiple Sclerosis Knowledge Questionnaire: a self-administered instrument for recently diagnosed patients[END_REF] and MRI-specific knowledge questionnaires [START_REF] Brand | Magnetic resonance imaging in multiple sclerosis-patients' experiences, information interests and responses to an education programme[END_REF]. Apart from being a necessity for medical decisionmaking, a high disease-specific knowledge can also influence patients' emotions: For example, a low disease-specific knowledge was associated with greater levels of fear in patients with chronic obstructive pulmonary disease [START_REF] Zhang | Disease knowledge level is a noteworthy risk factor of anxiety and depression in patients with chronic obstructive pulmonary disease: a cross-sectional study[END_REF], and patient education has also been shown to decrease anxiety before medical procedures, e.g. in the perioperative setting [START_REF] Bailey | Strategies for decreasing patient anxiety in the perioperative setting[END_REF]. Therefore, increasing MRI knowledge in pwMS might not only lead to a better understanding of their disease and increase shared decision-making, it may also decrease anxiety concerning MRI.

To our knowledge, evidence-based and patientfriendly information on MRI in MS is currently not available, hindering patient participation. We have therefore developed an online patient education tool on MRI in MS called "Understanding MRI in MS" (UMIMS). This randomized controlled trial (RCT) aims to assess the effect of this online education tool on knowledge about and emotions towards MRI in n = 120 pwMS.

Aims and objective

We hypothesize that access to an online education tool about MRI in MS will lead to an increase in MRIspecific knowledge in pwMS. Increased knowledge will be accompanied by a decrease of fear of MRI and increased feeling of competence during patient-physician encounters. The intervention will enhance patient empowerment and increase patients' desire for participation in MRI-related decisions. Finally, it will increase SDM when considering MRI-activity-based treatment changes or decisions about subsequent MRIs during clinical interactions. At large, this study is guided by the principles of evidence-based medicine (EBM) [START_REF] Sackett | Evidence based medicine: what it is and what it isn't[END_REF] and evidencebased patient information (EBPI) [START_REF] Bunge | What constitutes evidence-based patient information? Overview of discussed criteria[END_REF] and the Medical Research Council (MRC) framework for developing and evaluating complex interventions [START_REF] Craig | Developing and evaluating complex interventions: the new Medical Research Council guidance[END_REF].

Methods

Design

The UMIMS trial will be carried out as a double-blind, superiority randomized controlled trial. Following the MRC guidelines for the development and evaluation of complex interventions [START_REF] Craig | Developing and evaluating complex interventions: the new Medical Research Council guidance[END_REF], the website and the outcome measures used in the RCT were pre-tested in a feasibility study with n = 79 participants recruited via the website of the German MS society. In detail, the feasibility study tested if patients had technical issues accessing or using the website, asked how much time patients spent on it and if patients found the content understandable, interesting and relevant. Furthermore, the main study will be accompanied by a process evaluation [START_REF] Craig | Developing and evaluating complex interventions: the new Medical Research Council guidance[END_REF].

Study setting

To ensure a more diverse patient population, the study will be conducted in 5 German clinics specialized in MS care (3 university clinics, and 2 private practices) throughout Germany.

Eligibility criteria

PwMS are eligible to participate if they are older than 18 years and have been diagnosed with a relapsingremitting MS (RRMS) according to the McDonald criteria [START_REF] Thompson | Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria[END_REF] within the previous 10 years and have an active disease course (i.e. treatment change or new T2 lesion within the previous year) or a clinically isolated syndrome (CIS) with at least one MS-typical T2 lesion.

In order to realistically assess whether the education tool changes the attitude towards MRI, patients can only be included if they are scheduled to receive an MRI within 2 weeks to 6 months following randomization.

Because the study will use the internet for information provision and data collection, only patients with access to the internet will be included.

Patient exclusion criteria

We assume that MRI results have the greatest impact on people with active RRMS or suspected MS (e.g. resulting in treatment initiation or confirmation of diagnosis) and therefore decided to exclude patients with (even active) secondary-progressive or primary-progressive MS from participation. Additionally, severe cognitive deficit or major psychiatric illness affecting information uptake, any suspected central nervous system disease other than MS, contraindications for MRI and pregnancy are reasons for exclusion.

Interventions

Intervention group (IG)

After answering the baseline questionnaires and randomization, patients in the intervention group will receive access to the newly developed, evidence-based, online education tool "Understanding MRI in MS" (UMIMS). The tool was developed based on previous research [START_REF] Brand | Magnetic resonance imaging in multiple sclerosis-patients' experiences, information interests and responses to an education programme[END_REF] and the input of pwMS, MRI experts and expert patients. It consists of 3 sections:

1 "About MRI" (MRI education) 2 "Learning to read" (interactive MRI training with real MRI images) 3 Training (MRI quiz) "About MRI" covers topics, which emerged during the interviews with pwMS and/or were deemed relevant by the expert patients, MRI experts or the research team. Expert patients are defined as people affected by an illness, that, among other characteristics, have both personal and experiental experiences with the disease, are knowledgeable in symptoms and treatment of it and have active roles or even hold responsibilities in selfhelp organizations (e.g. as board members) [START_REF] Cordier | The expert patient: towards a novel definition[END_REF]. It includes evidence-based information on the importance of MRI for prognosis (e.g. impact of number and location of MS lesions), diagnosis (e.g. explanation of the McDonald criteria) and treatment control in MS (i.e. definition of non-responders), the MRI procedure (e.g. duration and scanning procedure), contrast agents (i.e. use and risks of gadolinium), basic neuroanatomy, lesion knowledge (i.e. configuration and types of MS lesions) and MRI sequences. Easy-to-understand figures, videos and explanations of technical terms simplify the learning process. All evidence sources are cited. In "Learning to read", users are presented with 3 different doctor's letters, which are translated into layman's terms and 7 original MRI images with a step-by-step explanation for interpretation of the results. In the "Training" section, patients can test their acquired knowledge in a quiz.

Control group (CG)

After answering the baseline questionnaires and randomization, patients in the control group will receive access to a newly created website providing standard information on MRI in the same design as the UMIMS website. The standard information consists of the content that was freely available on the websites of several European as well as major English-speaking MS self-help organizations (Germany, France, Belgium, Netherlands, Great Britain, Canada, Australia, USA; time of access: September 2018). All topics that were permanently hosted on the websites were included; single articles, which were only available via a separate search were not included. The topics are as follows: importance of MRI for diagnosis (i.e. short explanation of the McDonald criteria) and treatment control in MS (i.e. that MR images are used for decision-making after treatment initiation), MRI procedure (i.e. duration, contraindications for MRI scans and basic procedure of the scan) and contrast agents (i.e. what contrast agents are used for).

Outcomes

For a list of the major endpoints of the UMIMS trial, see Table 1.

Primary endpoint

The primary endpoint is MRI-risk knowledge measured by the MRI-risk knowledge questionnaire 2.0 (MRI-RIKNO) [START_REF] Brand | Magnetic resonance imaging in multiple sclerosis-patients' experiences, information interests and responses to an education programme[END_REF]. It comprises n = 14 mainly multiple-choice items (maximum score of n = 22) concerning the meaning of MRI for diagnosis, prognosis and treatment control. It aims to assess pwMS' basic understanding (e.g. basic neuroanatomy, recognizing lesions on MR images, procedure of the scan) as well as knowledge on relevant features of MRI results in MS (e.g. meaning of new lesions in an MRI for prognosis or use of contrast agents). MRI-risk knowledge will be assessed twice during the trial: t 0 (allocation) and t 1 (after a 2-week access to the intervention or control website). The primary endpoint is change of MRI-RIKNO score from baseline to t 1 . The study is powered to detect a 10% difference in the proportion of correct answers.

Secondary endpoints

Emotions and attitude towards MRI will be assessed using the validated questionnaire "MRI-emotions and attitude" (MRI-EMA) at t 0 , t 1 and t 2 [START_REF] Engels | Emotions towards magnetic resonance imaging in people with multiple sclerosis[END_REF]. Autonomy preferences will be assessed using the Control Preference Scale (CPS) [START_REF] Degner | The control preferences scale[END_REF] (moderate internal consistency and good convergent validity [START_REF] Las Cuevas | Validity of the Control Preferences Scale in patients with emotional disorders[END_REF]) before and after the (control) intervention (at t 0 and t 1 ) as well as after the patient-physician encounter (t 2 ). Perceived involvement in decisional encounters concerning MRI results and their consequences will be evaluated with the Multifocal Approach to Sharing in Shared Decision Making (MAPPIN'SDM; inter-rater-reliabilities in the observer scales and internal consistencies high to excellent) evaluation [START_REF] Kasper | MAPPIN'SDMthe multifocal approach to sharing in shared decision making[END_REF]; applying a newly developed short version. For a subgroup of n = 5 participants of each group, who have specifically consented to it, the encounter will be audiotaped and the degree of SDM will be assessed via an external rater using the MAPP IN'SDM. Decisions on future MRIs and treatment changes as well as acceptance of the intervention will be assessed from patients using a standardized questionnaire immediately (t 2 ) and 6 months after the patient-physician encounter (t 3 ) (for both the intervention group (IG) and control group (CG)). Quality of life (QoL) will be assessed using the subscales fatigue, cognition, visual impairment, communication and mood of the HAmburg QUAlity of life questionnaire in MS (HAQUAMS) [START_REF] Gold | Disease specific quality of life instruments in multiple sclerosis: validation of the Hamburg Quality of Life Questionnaire in Multiple Sclerosis (HAQUAMS)[END_REF] (internal consistency and retest coefficients high). Tertiary outcomes (control and safety parameters)

Anxiety and depression will be assessed as a control parameter using the Hospital Anxiety and Depression Scale (HADS) [START_REF] Zigmond | The hospital anxiety and depression scale[END_REF] will be assessed as a control parameter. Occurrence of relapses will be evaluated at baseline (t 0 ), after patient-physician encounter (t 2 ) and at the 6month follow-up (t 3 ) (for both the IG and CG) using a standardized questionnaire.

Participant timeline

For a presentation of the flow of the UMIMS trial, see Fig. 1.

Baseline data

After inclusion and random allocation to either the IG or CG, all patients will answer baseline questionnaires that assess demographic and clinical data, MRI knowledge (using the MRI-RIKNO), emotions and attitude towards MRI (using the MRI-EMA), autonomy preferences (using the CPS), numeracy and general internet use. Patients in the IG will receive an access code to the education tool UMIMS, and patients in the CG will receive a similar access code to the control website. The study nurse or other medical personnel will schedule the MRI appointment and the subsequent patient-physician encounter.

Post-MRI patient-physician encounter

Next, patients receive a 2-week access to either UMIMS or the control website; at the end of this period, the primary and several secondary endpoints are assessed. The MRI takes place in a 2-week to 6-month window after randomization. Participants then return to the study centre to discuss their MRI results. SDM concerning decisions based on MRI findings will be assessed via the MAPPIN'SDM questionnaire [START_REF] Kasper | MAPPIN'SDMthe multifocal approach to sharing in shared decision making[END_REF] and the actual decisions will be noted. All participants will be asked whether they agree to be audiotaped during the patientphysician encounter. The aim is to externally evaluate the SDM process in a subgroup of at least n = 5 patients from both groups. Both, physicians and patients, will answer questions for the process evaluation.

Follow-up

Six months after the patient-physician encounter, participants will be called to assess if the MRI-based decisions have led to any behavioural action, i.e. a new MRI or treatment change. Patients will be asked for their assumed group allocation. Unblinding might occur, if participants suspect to be in the control group due to the limited amount of information on the control website.

Sample size

The primary endpoint of the UMIMS trial is the difference of change in MRI-specific risk knowledge between baseline and t 1 between IG and CG. The sample size calculation is based on data from prior studies comparing n = 120 pwMS with and n = 497 pwMS without access to the educational program [START_REF] Engels | Emotions towards magnetic resonance imaging in people with multiple sclerosis[END_REF]. PwMS with access to the education program answered 75% of the MRI-RIKNO questionnaire correctly (16.3 out of 22 possible points, standard deviation (SD) ± 3.0), while participants without access answered 65% of questions correctly (14.5 of 22 possible points, SD ± 3.0). In order to detect this difference with a power of 90% and a significance level of alpha = 0.05, n = 49 patients in each group will be needed. Assuming a dropout rate of 20%, n = 11 additional participants will be needed, accounting for a total of n = 120 participants. In most of our previous trials on EBPIs, loss to follow-up was less than 10%. Therefore, 20% seems a realistic and conservative assumption.

Recruitment, screening, allocation and blinding Recruitment

Consecutive patients will be recruited by treating physicians in the 5 participating centres.

Screening

To minimize selection bias during the enrollment period, physicians are asked to consider every patient they see in a patient-physician encounter for the study. Eligible patients will be invited to participate and receive information about the study. Informed consent will be obtained by treating physicians from patients fulfilling the inclusion criteria after they have had enough time to read the study information and ask questions; participants then receive a pseudonym. Suitable patients, who are not willing to participate in the study, will be asked for the reason.

Allocation

Permuted-block randomization will be computer generated and performed by a statistician not involved in the conduct of the study; the randomization list is stored in a separate location not accessible to personnel responsible for the trial, and recruitment of new patients for randomization will be communicated via telephone. In a previous study, analysis of covariance did not reveal an influence of sociodemographic variables on MRI knowledge; therefore, no stratification will take place except for study site. Study materials, including the randomly assigned logins to the intervention or control website, will be provided by a member of the research team that is not involved in any outcome assessment or the analysis of the study.

Blinding

In the consent form, patients will be informed, that 2 different types of information will be tested. Blinding is achieved by providing a control group website featuring standard information on MRI in MS but following the same graphical format as the active intervention. Physicians and study nurses at the recruiting centres as well as 2 external raters for SDM during the patient-physician encounter will be blinded.

Relevant concomitant care Physician encounters

Patients are free to consult a physician and receive treatment for e.g. relapses at any point of the study. Any physician encounter will be documented.

Technical support

An employee that is not involved in the analysis of the study will answer any e-mails from participants reporting e.g. technical problems concerning the website. During this contact, content of the website (e.g. if a participant does not understand a certain figure and asks for an explanation) will not be discussed.

Criteria for discontinuation

Adverse events

The intervention website contains complex medical information, which has the potential to overwhelm participants. Additionally, it provides information on the prognostic value of MRI and participants may learn that they fulfil negative prognostic criteria. However, our previous work has shown that pwMS understand complex medical information and are able to cope with negative information [START_REF] Kopke | Information provision for people with multiple sclerosis[END_REF]. We do not foresee any other harm of the intervention. As relevant adverse events are unlikely, a data monitoring committee does not exist, no interim analyses are planned and no stopping rules will be applied. Nevertheless, safety measures are applied as tertiary endpoints to control for anxiety and depression.

There is no anticipated harm and compensation for trial participation and no systematic post-trial care.

Patient withdrawal and non-adherence

At any point, patients in both groups can quit the study.

Patients who withdraw from the study will be asked whether they agree to continue to fill in a limited set of questionnaires related to the primary study outcome.

The data of non-adherent participants (e.g. with missing questionnaires) will be included in the intention-to-treat analysis.

Strategies to improve adherence

If appropriate, patients will be asked to fill in a questionnaire in the outpatient clinic directly after an encounter. When questionnaires have to be answered independently of an appointment, patients will be contacted by e-mail by a member of the coordinating centre in Hamburg and asked to complete the questionnaires within a specified time period. Patients that miss the completion will again be reminded by e-mail and telephone. If patients miss the physician appointment to discuss their MRI results, they will be contacted by the study nurse to arrange a new appointment.

To ensure the use of the education website, a study nurse will call the participants in the control and intervention group shortly after inclusion and encourage them to use the education tool. Additionally, participants will receive biweekly e-mail reminders concerning the tool.

Data collection methods

Data will be collected at 4 time points using paperpencil questionnaires (see Table 1). Follow-up data will be collected by telephone using trained and blinded interviewers after 6 months. Paper-based data is stored securely and pseudonymized at the coordinating centre. Data will be digitalized and evaluated for plausibility and quality (e.g. double data entry) by two employees of the coordinating centre independent from the study. Data will then be stored on secured servers at the coordinating centre and access will be granted to members of the trial team and the statistician after completion of the trial. Additional data management procedures (e.g. storage duration) can be found in the study protocol submitted to the Hamburg Chamber of Physicians (approval number: PV5722) as well as the patient consent form.

Study supervision

Day-to-day delivery and conduct of the trial is performed by the coordinating researcher and a study nurse of the coordinating centre (Trial Management Group (TMG)). Treating physicians at the respective participating centres are responsible for recruitment of participants and obtaining written consent. The principle investigator, coordinating researcher and a study nurse monitor and supervise the trial, meet every 3 months to discuss its progress and update relevant parties (i.e. sponsors, trial registry, participants), i.e. take over the responsibilities of the Trial Steering Committee (TSC). Due to the low-risk intervention, an independent TSC, Data Monitoring Committee (DMC) or meeting of a Stakeholder and Public Involvement Group (SPIG) were not deemed necessary.

Statistical methods

Continuous data will be described using means and standard deviations (SDs) and compared using Student's t test. Categorical data will be presented using contingency tables and raw percentages and will be compared using Fisher's exact test.

The primary endpoint, change in MRI-RIKNO from t 0 to t 1 , will be analysed using an ANCOVA model with adjustment for baseline. Secondary endpoints will be analysed accordingly depending on the scale of measurement either by ANCOVA models for continuous endpoints or (ordinal) logistic regression models for dichotomous or ordinal endpoints.

It is planned to perform subgroup analysis of the 2 groups of patients included in the trial: first, those with an RRMS diagnosis of less than 10 years and active disease, and second, those with suspected MS. We will report causes for study withdrawal for each patient to clarify whether there are any differences between the intervention and control groups.

All data will be analysed on an intention-to-treat as well as per-protocol basis. In addition, sensitivity analyses will be performed to evaluate the robustness of study results and to explore different imputation techniques. Altman [START_REF] Altman | Missing outcomes in randomized trials: addressing the dilemma[END_REF] addressed that there is no ideal method to address missing data. Therefore, different common imputation techniques [START_REF] Alshurafa | Inconsistent definitions for intention-to-treat in relation to missing outcome data: systematic review of the methods literature[END_REF] will be applied and reported with as well as without imputation techniques as suggested by Altman [START_REF] Altman | Missing outcomes in randomized trials: addressing the dilemma[END_REF]. Best-and worst-case scenarios for dichotomous outcomes and multiple imputation techniques will be conducted in the sensitivity analysis [START_REF] Thabane | A tutorial on sensitivity analyses in clinical trials: the what, why, when and how[END_REF].

Process evaluation

This RCT will be accompanied by a process evaluation to measure the intervention's fidelity and determine reasons for an (in)effective study outcome, following the guidelines of the MRC [START_REF] Craig | Developing and evaluating complex interventions: the new Medical Research Council guidance[END_REF][START_REF] Linnan | Process evaluation for public health interventions and research[END_REF]. The process evaluation will be used to investigate study processes related to participants, physicians and the context and setting of the study. The framework of the process evaluation is based on a previous study including a process evaluation [START_REF] Rahn | Evaluatorblinded trial evaluating nurse-led immunotherapy DEcision Coaching In persons with relapsing-remitting Multiple Sclerosis (DECIMS) and accompanying process evaluation: study protocol for a cluster randomised controlled trial[END_REF] as well as guidelines by Moore et al. [START_REF] Moore | Process evaluation of complex interventions: a summary of Medical Research Council guidance[END_REF].

In this process evaluation, quantitative elements will be used to explore expected and unexpected events arising from the intervention. The overall aim is to uncover barriers and facilitators for reaching study goals and to explore mechanisms that lead to explanations for failure or success of the intervention.

In detail, the objectives are to:

1 Explore the reaction of individuals (such as userfriendliness of, hours spent on and feelings evoked by the website) 2 Detect barriers and facilitators for the intervention's delivery (such as technical problems with the website) and for the dose received by participants (such as disease-related or internet-related problems participants may experience) 3 Find barriers and facilitators of study termination, participation and retention 4 Analyse reasons why study elements work or do not work out as planned 5 Reveal contamination of the intervention and control groups (such as the use of other information materials other than those provided during the trial) 6 Identify unintended consequences of the study (such as depression and anxiety)

All questionnaires have been constructed by the research team and were tailored specially to the study. The content of this process evaluation refers to both IG and CG. There will be one separate questionnaire for the IG evaluating the different chapters of the intervention website in detail in order to collect data for the website's improvement.

Domains covered by the process evaluation

Following the MRC framework [START_REF] Moore | Process evaluation of complex interventions: a summary of Medical Research Council guidance[END_REF], the following domains will be covered by the process evaluation:

1 Implementation: fidelity, dose, reach (as no adaptations will be made to the study throughout the trial, the domain "Adaptations" is not covered) 2 Mechanisms of impact 3 Context.

Implementation: fidelity

Measuring to which extent the intervention is actually delivered as planned is difficult. There is still ongoing research on how to best collect data on fidelity [START_REF] Linnan | Process evaluation for public health interventions and research[END_REF]. Considering that the intervention is an online resource, the quality of the intervention will remain stable; therefore, mostly the received dose will vary. Fidelity could however be breached, if physicians talk about the meaning of the participant's MRI throughout the study. Whether this is the case is assessed after the patient-physician encounter. Additionally, it is recorded if participants of the IG and CG really visited the respective website. Additionally, we will ask participants in the follow-up questionnaire (t 3 ) and physicians after the patient-physicianencounter (t 2 ) if they have been unblinded during the study.

Implementation: dose

The dose of an intervention can be subcategorized into: Dose delivered, i.e. the amount or number of intended units of each intervention or component delivered or provided by interventionists, and Dose received, i.e. the extent to which participants actively engage with, interact with, are receptive to and/or use materials or recommended resources; this can include "initial use" and "continued use". The collection of data on the initial and continued use of the study materials, and information on what barriers and facilitators hinder or serve to maintain the implementation, can be used to interpret study outcomes.

In this trial, the dose delivered is the same for all participants, because the intervention is a website and therefore available at all times.

Concerning the dose received, the following aspects will be captured:

1 The use of the website (number of logins, duration of use, visited chapters) 2 Reasons for amount/lack of usage 3 Expenditure of the study.

Implementation: reach

The reach describes the proportion of the intended audience that participates in the intervention; it can be measured by attendance and includes documentation of barriers to participation. Demographic data is collected for all participants to properly describe the study population. In participants, reasons for participation as well as early exit will be registered (t 0 ). PwMS who qualify for the study, but do not want to participate, will be asked for the main reason why (t -1 ).

Mechanism of impact

The domain Mechanism of impact covers the participants' responses to, and interactions with, the intervention, mediators and unanticipated consequences. Overall, it examines how the intervention triggers change. For the evaluation, questionnaires with Likert scales, multiple choice and open questions will be used in IG and CG.

First, the satisfaction with the educational tool as well as relevance, importance of topics, understandability and handling of the website will be assessed. Participants of the IG will additionally answer a short questionnaire concerning the content of the intervention website. Secondly, barriers and promoting factors for the usage of the website (e.g. age, internet access and skills, amount of free time) will be assessed.

Thirdly, several of the primary and secondary outcomes (e.g. change in MRI-risk knowledge (subjective and objective) and attitude towards MRI) of the trial will be analysed to estimate how participants interacted with the website.

To monitor unintended consequences, threat by MS, change in quality of life, depression and anxiety or patient-physician-relationship/communication will be measured.

Context

Overall, 5 different MS centres are participating study centres; 3 of them are university hospitals, and 2 private practices. Depending on size and location, there is a variation in terms of the number of potential participants, practice hours, clinical focus of each clinic and access to an MRI. Therefore, there might be a difference in e.g. the number in prescribed MRIs or length of the waiting periods for patients.

As access to the internet may also vary in urban versus rural areas, internet availability and skills are assessed. Further, participants might also find information on MRI in MS on other platforms e.g. websites, blogs, magazines, books (…). Participants will therefore be asked, if they searched for additional information and what they found. Questions concerning contextual factors will be in the form of multiple choice and open questions (t 0 , t 1 , t 2 ).

Data analysis (process evaluation)

Data analysis of the process evaluation will follow descriptively (see above) and via SPSS (International Business Machines Corporation (IBM), Armonk, United States of America) or R (R Development Core Team) will be used. In case of a failed trial or inconclusive findings, it will be considered to use the quantitative data to determine questions for qualitative interviews.

Summary process evaluation

The applied framework of Moore et al. [START_REF] Moore | Process evaluation of complex interventions: a summary of Medical Research Council guidance[END_REF] facilitates systematically appraising, analysing and retrieving relevant aspects of this complex intervention. The questionnaires are designed to permit an elaborate and more precise interpretation of the study results.

Discussion

PwMS, while being constantly confronted with MRI results, possess a poor knowledge on the meaning of MRI in MS. They often do not feel competent to discuss their MRI results with their physician and receiving results may cause a relevant amount of fear [START_REF] Engels | Emotions towards magnetic resonance imaging in people with multiple sclerosis[END_REF]. At the same time, pwMS consider MRI to be very important and desire MRI education. The UMIMS trial is the first RCT to assess the effect of an MRI education in pwMS. It aims to prove that access to an education tool on MRI in MS will increase pwMS' knowledge on this complex topic, facilitate communication with their physician and enhance SDM when discussing decisions involving MRI results. If the trial proves to be effective, the website is an easily accessible tool, which can be maintained and made available nationwide at a low cost.

Trial status

The RCT is registered at clinicaltrials.gov (identifier NCT0387258). Recruitment has started in 15 March 2019 and is ongoing (estimated recruitment end 31 March 2021). Protocol version 2.0, date: 30 August 2020.

Fig. 1

 1 Fig. 1 RCT design

Table 1

 1 Major endpoints

	Instrument	Measurement time point
		Enrollment	Allocation	Post-allocation
		t -1	t 0	t 1	t 2	t 3
	Eligibility screen	x				s
	Informed consent	x
	Allocation	x
	Sociodemographic data	x	x
	PDDS		x
	MS-related data and resource use		x
	MRI-RIKNO		x a	x
	Subjective knowledge		x	x
	MRI-EMA		x	x	x
	CPS		x	x	x
	Numeracy		x
	Threat by MS		x	x
	HADS		x	x
	Process evaluation			x	x (patient and physician)	x
	MAPPIN'SDM				x (patient and physician)
	MAPPIN'SDM audio (n = 5 CG/IG)				x (external rater)
	Treatment/MRI decision				x	x

t 1 2 weeks after allocation and access to the intervention/control website, t 2 immediately after patient-physician encounter, t 3 6 months after patient-physician encounter, CG control group, CPS Control Preference Scale, HADS Hospital Anxiety and Depression Scale, IG intervention group, MAPPIN'SDM Multifocal Approach to Sharing in Shared Decision Making, MRI-EMA magnetic resonance imaging-emotions and attitude questionnaire, MRI-RIKNO magnetic resonance imaging-risk knowledge questionnaire, PDDS patient-determined disease steps a Primary endpoint

Acknowledgements

We would like to acknowledge the contributions of Katharina Engels, Dr. Jutta Scheiderbauer, Prof. Dr. Carsten Lukas and Prof. Dr. Declan Chard to the work leading to this trial.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Funding

The study is funded by Sanofi-Genzyme. The sponsor did not and will not have any influence on the study design, collection, management, analysis or interpretation of data, writing of the report and the decision to submit the report for publication. Open Access funding enabled and organized by Projekt DEAL.

Ethics approval and consent to participate

Ethical approval has been obtained from the ethical committee of Hamburg Chamber of Physicians (approval number: PV5722) as well as local committees at each centre location. Protocol amendments, if necessary, will be reported to the sponsor, communicated to participating centres and sent to the leading ethics committee at the Hamburg Chamber of Physicians. Upon acceptance, clinical trial registry will be adapted. Deviations from the protocol will be documented using a breach report form. Written informed consent will be obtained from all study participants. On the consent form, participants will be asked if they agree to use of their data should they choose to withdraw from the trial. Participants will also be asked for permission for the research team to share relevant data with people from the universities taking part in the research or from regulatory authorities, where relevant. This trial does not involve collecting biological specimens for storage.

Consent for publication

Results of the trial will be submitted for publication in a scientific journal, reported to the sponsor as well as the trial registry and distributed among pwMS via the newsletter of the MS dayclinic of the University Medical Centre Hamburg-Eppendorf.

Competing interests

Insa Schiffmann has received travel grants from Sanofi-Genzyme. Magalie Freund has nothing to declare. Eik Vettorazzi has nothing to declare. Anne Rahn was supported by a research grant from the National MS Society, USA (grant no. G-1508-06034). Jan-Patrick Stellmann received research funding from Deutsche Forschungsgemeinschaft and reports grants from Biogen and Genzyme. Susanne Heyer-Borchelt has nothing to declare. Marie D'Hooge has nothing to declare for this study. Vivien Häußler has nothing to declare. Christoph Heesen received speaker honoraria and grants from Biogen, Genzyme, Merck, Novartis and Roche.

Author details 1

Institute of Neuroimmunology and Multiple Sclerosis (INIMS), University

Medical Centre Hamburg-Eppendorf (UKE), Hamburg, Germany. 2 Department of Neurology, University Medical Centre Hamburg-Eppendorf (UKE), Hamburg, Germany. 3 Department of Medical Biometry and Epidemiology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany. 4 APHM, Hopital de la Timone, CEMEREM, Marseille, France. 5 Aix Marseille Université, CNRS, CRMBM, UMR 7339, Marseille, France. 6 Centre for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium. 7 National MS Centre Melsbroek,

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Sina C Rosenkranz

Barbara Kaulen

Hanna G Zimmermann

Ava K Bittner

Michael Dorr

Jan-Patrick Stellmann

Validation of Computer-Adaptive Contrast Sensitivity as a Tool to Assess Visual Impairment in Multiple Sclerosis Patients

Keywords: qCSF, AULCSF, precision, repeatability, discrimination, multiple sclerosis, vision

Validation of qCSF in MS CSF acuity measured with the qCSF (0.18 vs. 0.11 and 0.17, respectively). Even better repeatability (MAP = 0.19) was demonstrated by a CSF-derived feature that was inspired by low-contrast acuity charts, i.e., the highest spatial frequency at 25% contrast. When compared to healthy controls, the MS patients showed reduced CSF (average AULCSF 1.21 vs. 1.42, p < 0.01).

Conclusion:

High precision, usability, repeatability, and discrimination support the qCSF as a tool to assess contrast vision in pwMS.

Background: Impairment of visual function is one of the major symptoms of people with multiple sclerosis (pwMS). A multitude of disease effects including inflammation and neurodegeneration lead to structural impairment in the visual system. However, the gold standard of disability quantification, the expanded disability status scale (EDSS), relies on visual assessment charts. A more comprehensive assessment of visual function is the full contrast sensitivity function (CSF), but most tools are time consuming and not feasible in clinical routine. The quantitative CSF (qCSF) test is a computerized test to assess the full CSF. We have already shown a better correlation with visual quality of life (QoL) than for classical high and low contrast charts in multiple sclerosis (MS).

Objective: To study the precision, test duration, and repeatability of the qCSF in pwMS. In order to evaluate the discrimination ability, we compared the data of pwMS to healthy controls.

Methods: We recruited two independent cohorts of MS patients. Within the precision cohort (n = 54), we analyzed the benefit of running 50 instead of 25 qCSF trials. The repeatability cohort (n = 44) was assessed by high contrast vision charts and qCSF assessments twice and we computed repeatability metrics. For the discrimination ability we used the data from all pwMS without any previous optic neuritis and compared the area under the log CSF (AULCSF) to an age-matched healthy control data set.

Results: We identified 25 trials of the qCSF algorithm as a sufficient amount for a precise estimate of the CSF. The median test duration for one eye was 185 s (range 129-373 s). The AULCSF had better test-retest repeatability (Mean Average Precision, MAP) than visual acuity measured by standard high contrast visual acuity charts or

INTRODUCTION

Visual impairment can be one of the major symptoms in multiple sclerosis (MS) patients. Because vision is rated as one of the three most important bodily functions by MS patients, its impairment has a high impact on quality of life (QoL; [START_REF] Balcer | Vision and vision-related outcome measures in multiple sclerosis[END_REF][START_REF] Heesen | Perceptions on the value of bodily functions in multiple sclerosis[END_REF]. Structural pathological changes in the retina are caused not only by acute optic neuritis, but also as the consequence of chronic inflammation, demyelination, and progressive neurodegeneration [START_REF] Talman | Longitudinal study of vision and retinal nerve fiber layer thickness in MS[END_REF]. Key pathological features observed in the retinas of MS patients are decreased thickness of the retinal nerve fiber layer (RNFL), ganglion cell layer, and inner plexiform layer [START_REF] Balcer | Vision and vision-related outcome measures in multiple sclerosis[END_REF][START_REF] Martinez-Lapiscina | Retinal thickness measured with optical coherence tomography and risk of disability worsening in multiple sclerosis: a cohort study[END_REF][START_REF] Petzold | Retinal layer segmentation in multiple sclerosis: a systematic review and meta-analysis[END_REF]. However, vision outcomes are not yet routinely implemented as a disease monitoring tool in clinical care or clinical trials for MS. This is mainly due to the fact that the available tests either do not sufficiently represent the pathological changes in the central nervous system or are too time-consuming to incorporate into routine clinical practice.

Currently, visual impairment in clinical practice is usually assessed by the Snellen chart, which records high-contrast visual acuity (HCVA) [START_REF] Gilbert | The illumination of the Snellen chart[END_REF]. For example, the gold standard for MS disability quantification, the expanded disability status scale (EDSS), relies on HCVA to estimate its visual functioning score. In MS patients, however, low-contrast visual acuity (LCVA) seems to better correlate with the alterations of retinal morphology [START_REF] Schinzel | Relations of low contrast visual acuity, quality of life and multiple sclerosis functional composite: a cross-sectional analysis[END_REF] and cognitive function [START_REF] Wieder | Low contrast visual acuity testing is associated with cognitive performance in multiple sclerosis: a cross-sectional pilot study[END_REF]. LCVA is usually assessed by the low-contrast Sloan letter charts, but the evidence supporting this method is controversial as association with vision-related QoL in MS patients is inconsistent [START_REF] Mowry | Vision related quality of life in multiple sclerosis: correlation with new measures of low and high contrast letter acuity[END_REF]Stellmann et al., 2015b;[START_REF] Sabadia | 20/40 or better visual acuity after optic neuritis: not as good as we once thought?[END_REF]. Sloan LCVA charts usually measure at selected contrast levels [for example 1.25% or 2.5% [START_REF] Balcer | Low-contrast acuity measures visual improvement in phase 3 trial of natalizumab in relapsing MS[END_REF][START_REF] Balcer | Validity of low-contrast letter acuity as a visual performance outcome measure for multiple sclerosis[END_REF]] whereas the affected contrast sensitivity changes on an individual basis for different letter sizes. Consequently, contrast sensitivity should be assessed across a range of different letter sizes or spatial frequencies [START_REF] Balcer | Validity of low-contrast letter acuity as a visual performance outcome measure for multiple sclerosis[END_REF], but the most established tools to measure the full contrast sensitivity function (CSF) are time-consuming, unreliable, and not feasible in routine clinical practice [START_REF] Kalia | Development of pattern vision following early and extended blindness[END_REF]. The quantitative CSF (qCSF, previously also termed quick CSF) test is a computerized test that uses a Bayesian adaptive method to assess the full CSF, which implicitly includes LCVA and HCVA, quickly but precisely [START_REF] Lesmes | Bayesian adaptive estimation of the contrast sensitivity function: the quick CSF method[END_REF][START_REF] Dorr | Rapid and reliable assessment of the contrast sensitivity function on an iPad[END_REF].

We recently showed that qCSF could be a useful tool for the assessment of visual function in MS patients as it correlated best with vision-related QoL measured by the National Eye Institute Visual Functioning Questionnaire (NEI-VFQ) (Stellmann et al., 2015b), whereas VA with Sloan charts was not significantly associated with the NEI-VFQ administered to MS patients. However, to establish the qCSF as a diagnostic tool in routine clinical care and research, further validation is necessary in the intended patient population. Here, we studied two independent consecutive MS cohorts in order to (i) optimize the precision and usability and (ii) evaluate repeatability and discrimination of the qCSF in MS patients.

MATERIALS AND METHODS

Patient Cohorts

Between August 2014 until November 2016 we included consecutive patients with a clinically isolated syndrome highly suggestive for MS or patients with a definite MS diagnosis according to the revised McDonald criteria [START_REF] Polman | Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria[END_REF] for two independent cohorts: (i) n = 54 in the precision cohort; and (ii) n = 44 in the repeatability cohort. Within the precision cohort, we aimed to compare the precision of two different test settings for the qCSF device, namely 25 vs. 50 qCSF trials. The repeatability cohort performed two consecutive qCSF assessments at a single visit to determine within-session variability with the previously established number of trials, and an additional HCVA assessment, which was chosen as the most commonly used standard clinical visual outcome measure. We assessed the typical median test duration for the qCSF method in the repeatability cohort. The cohorts were recruited sequentially without any overlap in the recruitment periods; thus, no patient was included in both cohorts. For an evaluation of the ability of the qCSF to discriminate between normal vision and abnormal vision in MS, we pooled the patients with a RRMS disease course and without any current or previous optic neuritis of both cohorts (n = 13 patients, 40 measurements) and compared them to a published normative dataset of 61 age-matched healthy controls (186 measurements because some subjects were tested repeatedly at two visits about a week apart) [START_REF] Lesmes | Distinguishing the contribution of precision and repeatability to vision testing[END_REF]. The diagnosis of an acute optic neuritis was assessed by an Ophthalmologist and Neurologist. Historical optic neuritis was assessed with clinical history. Previous optic neuritis was excluded to focus on the neurodegenerative changes rather than previous inflammatory damage. All participants with MS were recruited at the MS outpatient clinic, University Medical Centre Hamburg-Eppendorf, and the healthy controls were recruited and tested at the Nova Southeastern University, College of Optometry. All subjects gave their written informed consent prior to any testing. The local ethics committees approved the studies (Ethics Committee of the Board of Physicians in the State of Hamburg, PV4455 for both MS cohorts and the Institutional Review Board at the Nova Southeastern University in Fort Lauderdale, Florida for the healthy controls).

Data Acquisition

All tests were performed in the same room, under the same daylight illumination, and in the same order for both MS cohorts; the same stipulations applied for the normal healthy controls tested at a different site. Each eye was assessed separately and measured with best habitual correction (e.g., glasses or contact lenses). For the precision analysis, the repeatability and the analysis of the time duration we treated within-subject eyes as independent measurements, for the discrimination analysis we averaged the available measurements per subject. To assess the full CSF, for each of the 25 trials, the qCSF device (Manifold Contrast Vision Meter, Adaptive Sensory Technology) presented three bandpass-filtered Sloan letters of varying size and contrast on a 46-inch computer screen at a viewing distance of 4.5 m (for details see [START_REF] Lesmes | Bayesian adaptive estimation of the contrast sensitivity function: the quick CSF method[END_REF][START_REF] Dorr | Rapid and reliable assessment of the contrast sensitivity function on an iPad[END_REF]. The letters were presented until the patient gave a response; hence the test duration depended on the individual being tested. Based on the participant's responses, the method chose the most informative combination of size and contrast for the next trial. Test duration for the qCSF was calculated by the file timestamps of subsequent tested eyes. This estimation includes changing the eye patch, any break (rest period) requested by the subject, and re-entering test details. For the precision cohort we ran the qCSF with 50 instead of 25 trials. For the repeatability cohort, the HCVA at 5 m (VA 500) was additionally determined with standard Snellen charts presenting nine lines with 1 to 10 letters. The smallest line with less than two mistakes was defined VA500 (possible values in LogMAR: -0.1, 0, 0.2, 0.3, 0.5, 0.6, 0.7, 0.85, and 1). For all MS subjects, the clinical neurological status was assessed by trained neurologists with the EDSS including its functional system subscore for vision [START_REF] Kurtzke | Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS)[END_REF]. [For correlations of area under the log CSF (AULCSF) and CSF acuity to VA500 see Supplementary Figures 1A,B, for correlations of AULCSF with EDSS and disease duration see Supplementary Figures 2A,B].

Contrast Sensitivity Function Outcomes

The shape of the CSF can be modeled with four parameters: (i) peak spatial frequency, (ii) peak contrast sensitivity, (iii) bandwidth, and (iv) a low-frequency truncation parameter [START_REF] Lesmes | Bayesian adaptive estimation of the contrast sensitivity function: the quick CSF method[END_REF]. The qCSF provides not only scalar estimates of these parameters, but their full joint posterior distribution. However, to simplify statistics and facilitate comparison with the point estimates of existing charts, here we calculated and report several scalar features of the CSF: (i) the AULCSF in the range from 1.5 to 18 cycles per degree; (ii) the CSF acuity, the spatial frequency for which sensitivity reaches zero (i.e., 100% contrast is required for recognition); and (iii) a "low-contrast CSF acuity" as an approximate equivalent of low-contrast acuity charts. Because of the different stimuli (bandpass-filtered vs. unfiltered letters) and the different contrast definitions (Michelson vs. Weber contrast), contrast values (typically 1.25% or 2.5% for LCVA charts) are not directly comparable, so we varied the threshold to 2.5% and in 5% steps from 5 to 50%. In our repeatability cohort, best repeatability precision was obtained with the spatial frequency for which sensitivity reached 0.6 (=log10(4), i.e., 25% contrast required for recognition), and we will thus refer to this parameter as "CS4."

Data Analysis

Because the ground truth of the actual CSF of an observer is unknown, we estimated the accuracy by calculating the convergence in the precision cohort by running the qCSF for 50 trials. We also calculated the difference of the CSF estimates after 25 and 50 trials (mean bias and mean absolute bias). For calculating the within-visit test-retest repeatability we used the Bland-Altman coefficient of repeatability (COR) [START_REF] Bland | Statistical methods for assessing agreement between two methods of clinical measurement[END_REF]. However, standard vision charts have a limited number of values and low discriminant abilities for the continuum of visual functioning. From a conceptual point of view, this leads to a risk of artificially high repeatability at the cost of low sensitivity to detect subtle differences, and restricts the use of COR for comparison of quantized tests (e.g., vision charts) and continuous outcomes, such as AULCSF. In recent work, we therefore have developed a new metric that penalizes test quantization, namely, Mean Average Precision (MAP) [START_REF] Dorr | New precision metrics for contrast sensitivity testing[END_REF]. This metric assesses how uniquely an individual is identified by their test and repeated test pair: Repeated tests from the same subject should yield the same result, whereas different subjects should typically yield different results. MAP ranks all retests by their similarity to the first subject's test and an average rank precision over all participants can be computed. A MAP score of 1.0 indicates high precision and resolution, whereas the MAP score approaches zero for a poor test. For the discrimination between healthy controls and MS patients, we calculate a between-group t-test on the AULCSF summary statistic.

RESULTS

Quantitative CSF Precision and Number of Trials

We have already shown that 25 trials of the qCSF algorithm are sufficient for a good estimate of the CSF in MS patients (Stellmann et al., 2015b). However, greater precision may be obtained by running the adaptive Bayesian procedure for more trials. In the precision cohort, we analyzed the difference of the estimated CSF between 25 and 50 trials by calculating the convergence. Descriptive statistics for the precision cohort are summarized in Table 1.

Two of the 54 included subjects with MS were measured monocularly only because they had no remaining vision in one of their eyes. One measurement in one subject had to be excluded due to technical problems. This resulted in a total of 105 qCSF measurements. Figure 1A shows the convergence of the AULCSF estimate over the time course of 50 trials (internal variability, not variability across measurements). For many patients, the first incorrect response leads to a drop in the AULCSF estimate, which then recovers after the first 5-10 trials. After 25-30 trials, the mean AULCSF estimate and the credible interval width have mostly converged with a small but statistically significant difference between the AULCSF estimate after 25 and after 50 trials (Figure 1B); (for 105 measurements mean = -0.02 log10 units, SD = 0.049; 95% CI (-0.03, -0.01), one-sample t-test t (104) = -4.34, p < 0.001). In line with previous work and the negligible benefit above 25 trials compared to the cost of additional test time, we performed subsequent testing and analyses with 25 trials.

Quantitative CSF Repeatability

Next, we assessed the individual within-visit reliability of two repeated tests in the repeatability cohort of MS patients. We included 44 subjects with one who was measured in one eye only. This resulted in 87 pairs of test and retest measurements; one eye was excluded from the CS4 calculation because its contrast sensitivity was too low (no stimulus size could be recognized at 25% contrast). Table 2 shows the baseline descriptive statistics of this cohort. Numerically, AULCSF had the highest ("least repeatable") COR in comparison to VA500 based on standard charts, CSF acuity, and CS4 (0.23 vs. 0.08, 0.14, 0.13, respectively, Figure 2A; for Bland-Altman plots, see Supplementary Figures 3A-D). However, the test score ranges are not directly comparable and paper charts strongly quantize results (see Supplementary Figure 3D), i.e., lack resolution. Using the novel metric MAP that penalizes coarse quantization, the AULCSF, high-contrast CSF acuity and low-contrast CS4 had better repeatability and precision (higher MAP values) than VA500 (0.18, 0.17, 0.19. vs. 0.11, respectively, Figure 2B).

Quantitative qCSF Test Duration

Test duration is an important factor for clinical usability. We looked at the duration between subsequent tests of 25 trials each for alternating eyes in the repeatability cohort (43 patients, the patient with only one measured eye was excluded). As the data were not normally distributed, we fit a mixture of two Gaussian distributions (mean 172 and 219 s; standard deviation 17 and 10 s, respectively). Median test duration per eye including all preparation, such as changing the eye patch and a break between eyes, was 185 s (5th and 95th percentiles were 154 and 260 s, respectively, Figure 3).

Discriminative Power of the qCSF in MS

We further investigated whether the qCSF could serve as a diagnostic instrument in MS and could discriminate these patients from healthy controls. For this aim, we pooled all qCSF measurements from both MS cohorts (precision and repeatability cohort), excluded all patients with a previous optic neuritis or an unknown visual symptom history and compared them to a normative data set of age-matched healthy normal controls (n = 186 measurements from 61 subjects, age range 20-59 years). On average, MS subjects (mean EDSS 2.65; SD 1.62) had reduced CSF results when compared to healthy controls (mean AULCSF after averaging measurements per subject 1.21 vs. 1.42, 95% CI of group differences (0.12, 0.3), Welch's t (36.28) = 4.77, p < 0.001).

The most pronounced difference is seen on the top left side of the curve indicating a larger gap of performance for large and medium-sized letters at low contrast (Figure 4).

DISCUSSION

Precise, reliable assessment of visual function is an important part of disability quantification in MS [START_REF] Balcer | Vision and vision-related outcome measures in multiple sclerosis[END_REF][START_REF] Heesen | Perceptions on the value of bodily functions in multiple sclerosis[END_REF]. However, currently available tools have several limitations and their impact on clinical decisions is probably negligible. Here, we provide important feasibility and reliability information about a new outcome to assess visual impairment in MS. The qCSF method shows higher precision than the current standard of care (VA500) without major burden to the patient or clinician. The qCSF has previously been compared to standard vision outcomes in MS patients, namely HCVA and LCVA, and already has demonstrated higher correlation with visual quality of life from the MS patient's perspective than HCVA or LCVA (Stellmann et al., 2015b).

In a first consecutive cohort, we aimed to define a reliable trade-off between duration and precision of the qCSF computeradaptive algorithm. Conceptually, precision of an estimate increases as a function of time as the impact of outliers and lapses decreases with the number of trials. However, long test duration directly reduces the feasibility and acceptance in clinical care and trials. For example, longer walking tests of 2 or 6 min for several years already have been considered to replace the MS standard of a timed 25 foot walk (which usually takes less than 1 min), but implementation of such outcomes is still rare [START_REF] Gijbels | Which walking capacity tests to use in multiple sclerosis? A multicentre study providing the basis for a core set[END_REF]Stellmann et al., 2015a). We found that 25 trials were sufficient for a reliable convergence of the algorithm, and a longer test duration did not change the estimate of the AULCSF substantially. This is in line with a previous study that showed that 25 trials of the qCSF were enough to demonstrate loss of visual function in diabetic subjects with and without retinopathy compared to healthy controls [START_REF] Joltikov | Multidimensional functional and structural evaluation reveals neuroretinal impairment in early diabetic retinopathy[END_REF]. However, longer test durations might still be necessary if other, potentially noisier features than the summary statistic AULCSF were of interest.

The second aim of our study was to evaluate the repeatability performance of the qCSF method in MS patients. First, we found that the visual function estimate did not differ substantially between two separate assessments in each individual, i.e., we found high stability of the method or high intra-individual reliability. This held true for both the evaluated parameters of the qCSF and for visual acuity VA500. However, care must be taken not to confound the commonly reported COR as a tool to compare tests with different outputs. The smaller range and the strong quantization of VA500 scores led to a seemingly excellent COR. However, repeatability (or precision) is only a necessary but not sufficient condition for the more important quality of a biomarker, which is the sensitivity to detect changes in the underlying signal. In the absence of a ground truth of visual change, we hypothesize that different individuals differ in their visual function, and the MAP metric quantifies the discriminant ability of a test for each individual in comparison to the whole group. Here, in a reversal of the ranking based on the COR, the summary statistic AULCSF provided higher discriminant ability than VA500 and CSF acuity.

Similar to low-contrast Sloan VA charts, we further calculated the cut-off frequency for stimuli presented at 25% contrast (CS4), and found that this parameter was even more precise than the AULCSF. In principle, the combination of several parameters, or the distributions thereof, might provide even further precision gains. This also demonstrated the advantage of estimating the full CSF versus paper charts that are limited to a fixed contrast level (HCVA or LCVA) or fixed spatial frequency (e.g., Pelli-Robson CS chart) [START_REF] Pelli | Measuring contrast sensitivity[END_REF]. In addition to the summary statistic AULCSF, we were able to calculate cut-off frequencies for a large number of contrast levels, in order to select the parameter with the highest test-retest precision. In general, different ocular or neurological pathologies might affect vision differently at different stages, and the most informative part of the CSF may therefore differ across individuals or diseases. For example, low vision patients may experience floor effects at low contrast levels, which was the case for one MS patient at our 25% contrast criterion. Testing the entire CSF thus solves the conundrum of knowing where to test in advance.

Furthermore, we also assessed typical test duration. With an average of about 3 min, results are in agreement with previous qCSF data from healthy controls [START_REF] Dorr | Evaluation of the precision of contrast sensitivity function assessment on a tablet device[END_REF]. Taken together with the comparable COR [START_REF] Lesmes | Distinguishing the contribution of precision and repeatability to vision testing[END_REF], this implies that mildly to moderately impaired MS patients do not need specialized test protocols because they are as fast and precise, albeit at a lower performance level, than healthy controls. Notably, the test duration for the qCSF in our study seems comparable to Sloan charts in previous studies. The literature reports a test duration of 10-15 min for a complete monocular and binocular testing at two contrast levels for the Sloan charts [START_REF] Balcer | Validity of low-contrast letter acuity as a visual performance outcome measure for multiple sclerosis[END_REF].

The descriptive analysis comparing average CSF estimates from MS and healthy controls indicates a worse performance over the complete frequency range with marked impairment of sensitivity to lower contrast levels. This finding in our study is consistent with reports for Sloan charts, that provide best discriminant abilities for MS with 1.25 and 2.5% low contrast VA charts. While 0.6% seems to be biased by a floor effect, 5% charts are already limited by a raising ceiling effect [START_REF] Balcer | Validity of low-contrast letter acuity as a visual performance outcome measure for multiple sclerosis[END_REF]. The qCSF approach avoids test restrictions at selected contrast levels, which may differ with disease progression, or spatial frequencies as the full CSF is estimated. The current main outcome, AULCSF, might thus be sensitive to differentiate patients from healthy controls as subtle differences over the complete CSF might sum up to a significant difference of the AULCSF. However, a sufficiently powered future head-tohead comparison of matched individuals tested under the same conditions might reveal even more discriminatory features of the CSF. Moreover, to establish qCSF as a diagnostic tool for MS, prospective studies are needed to determine sensitivity for change over time and define meaningful clinically relevant cut-offs.

The main limitation of the current study was the lack of comparison with Sloan VA charts in MS patients. However, we aimed to keep the burden for recruited patients low and decided to contrast our findings only with the clinical and EDSS standard, which is HCVA with a Snellen chart. Interestingly, repeatability data for Sloan charts in MS patients have not been previously published, although a good intra-rater agreement has been reported (ICC 0.86-0.95) [START_REF] Balcer | Self-reported visual dysfunction in multiple sclerosis: results from the 25-item National Eye Institute Visual Function Questionnaire (Vfq-25)[END_REF]. It should also be noted that the data from healthy controls were collected in a different clinic under slightly different conditions, at a viewing distance of 400 vs. 450 cm. However, these subtle factors likely did not substantially affect the rather large (qualitative) difference in qCSF on average that we observed between MS and healthy controls.

Taken together, qCSF provides excellent test characteristics and has already been linked to visual quality of life in MS. Our findings indicate that the further evaluation of the qCSF method in longitudinal studies as an outcome measure for MS seems promising. These studies should also include comparisons to the Sloan VA charts.

  deviation; EDSS = Expanded Disability Status Scale; CIS = Clinically isolated syndrome; RRMS = Relapsing remitting MS; SPMS = Secondary progressive MS; PPMS = Primary progressive MS.

FIGURE 1 |

 1 FIGURE 1 | Precision of AULCSF estimate over time. (A) AULCSF estimates for each eye (gray lines) (n = 105 measurements) and their mean over all measurements (solid black line). The dashed black lines show the mean lower and upper ends of the 68.3% credible interval estimates averaged across all measurements and are therefore indicative of the internal measurement variability (not of variability across measurements). (B) Distribution of differences between AULCSF estimates after 25 and 50 trials (n = 105 measurements). The y-axis shows the absolute number of measurements within each bin of differences. AULCSF = area under the log CSF.

FIGURE 3 |

 3 FIGURE 3 | Histogram of test durations per eye including all preparations. Shown here is the distribution of qCSF test duration per eye (n = 86 measurements) including all preparations. The raw data were best fit by a mixture of two Gaussian distributions with means of 172 and 219 s, respectively. The overall median test duration per eye is 185 s.

FIGURE 4 |

 4 FIGURE 4 | Quantitative contrast sensitivity function (qCSF)-examination in MS patients compared to age-matched healthy controls (HC). Curves show mean contrast sensitivity function (CSF) in MS patients (n = 13, based on patient-specific averages of a total of 40 measurements) and HC (n = 61, 186 measurements) ± SEM, x-axis represents logarithmic spatial frequencies, i.e., decreasing size of the letters; y-axis represents logarithmic sensitivity to decreasing contrast.

TABLE 1 |

 1 Baseline characteristics of the precision cohort.

Frontiers in Neuroscience | www.frontiersin.org

February 2021 | Volume 15 | Article 591302

ACKNOWLEDGMENTS

We thank all study nurses from the MS outpatient clinic for their excellent assistance.

DATA AVAILABILITY STATEMENT

The raw data of all MS patients supporting the conclusions of this article will be made available by the authors, without undue reservation.

ETHICS STATEMENT

The studies involving human participants were reviewed and approved by Ethics Committee of the Board of Physicians in the State of Hamburg and the Institutional Review Board at the Nova Southeastern University in Fort Lauderdale, Florida. The patients/participants provided their written informed consent to participate in this study.

AUTHOR CONTRIBUTIONS

J-PS conducted and designed the experiments. AKB designed the study involving healthy controls. SCR, MD, and J-PS analyzed the data and wrote the manuscript. BK analyzed the data. HZ and AKB supervised the study and wrote the manuscript. All authors contributed to the article and approved the submitted version.

SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnins. 2021.591302/full#supplementary-material Conflict of Interest: MD holds equity in and employment by Adaptive Sensory Technology and holds patents related to the qCSF. The qCSF device was provided to INIMS free of charge; no further compensation was granted. HZ received research grants from Novartis and speaking honoraria from Bayer Healthcare, unrelated to this study.

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.