EP4146050A1

EP4146050A1 - Means and methods for assessing low contrast vision

Info

Publication number: EP4146050A1
Application number: EP21724280.9A
Authority: EP
Inventors: Timothy KILCHENMANN; Michael Lindemann; Joerg Sprengel; Mattia ZANON
Original assignee: F Hoffmann La Roche AG
Current assignee: F Hoffmann La Roche AG
Priority date: 2020-05-08
Filing date: 2021-05-07
Publication date: 2023-03-15
Also published as: WO2021224441A1

Abstract

The present invention relates to the field of diagnostics. Specifically, it relates to a method for assessing contrast vision capabilities in a subject comprising the steps of determining at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from said subject, comparing the determined at least one contrast vision parameter to a reference, and assessing the contrast vision capabilities of the subject based on said comparison. The present invention also relates to a method of assessing multiple sclerosis (MS) in a subject comprising assessing contrast vision capabilities according to the method of the invention and the further step of assessing MS based on the contrast vision capabilities of the subject. Yet, the invention contemplates a device and a system for carrying out the aforementioned methods and the use of such device or system for assessing contrast vision capabilities or MS in the subject.

Description

Means and methods for assessing low contrast vision

Multiple sclerosis (MS) is a severe neurodegenerative disease which at present cannot be cured. Affected by this disease are approximately 2 to 3 million individuals worldwide. It is the most common disease of the central nervous system (CNS) that causes prolonged and severe disability in young adults. There is evidence supporting the concept that a B- and T cell- mediated inflammatory process against self-molecules within the white matter of the brain and spinal cord causes the disease. However, its etiology is still not well understood. It has been found that myelin-reactive T cells are present in both MS patients and healthy individuals. Accordingly, the primary abnormality in MS may involve more likely an impaired regulatory mechanisms leading to an enhanced T cell activation status and less stringent activation requirements. The pathogenesis of MS includes activation of encephalitogenic, i.e. autoimmune myelin-specific T cells outside the CNS, followed by an opening of the blood-brain barrier, T cell and macrophage infiltration, microglia activation and demyelination. The latter causes irreversible neuronal damage (see, e.g., Aktas 2005, Neuron 46, 421-432, Zamvil 2003, Neuron 38:685-688). It was shown more recently that besides T cells, B lymphocytes (expressing CD20 molecule) may play a central role in MS and influence the underlying pathophysiology through at least four specific functions:

1. Antigen presentation: B cells can present self neuroantigens to T cells and activate them.

2. Cytokine production: B cells in patients with MS produce abnormal proinflammatory cytokines, which can activate T cells and other immune cells.

3. Autoantibody production: B cells produce autoantibodies that may cause tissue damage and activate macrophages and natural killer (NK) cells.

4. Follicle-like aggregate formation: B cells are present in ectopic lymphoid follicle-like aggregates, linked to microglia activation, local inflammation, and neuronal loss in the nearby cortex.

Although there is sound knowledge about the mechanisms responsible for the encephalitogenicity, far less is known regarding the control mechanisms for regulating harmful lymphocyte responses into and within the CNS in a subject.

MS diagnosis is based at present on clinical investigations by a medical practitioner. Such investigations involve testing of the capabilities of a patient for certain physical activities. Several tests have been developed and are routinely applied by medical practitioners. These tests aim at assessing walking, balance, and other motoric or sensoric abilities. Contrast sensitivity is affected in patients with MS due to optic neuritis at a rather early onset of the disease (Balcer 2017). Examples of currently applied tests for contrast vision capabilities used in MS diagnosis are Pelli-Robson contrast sensitivity and Sloan LCLA charts. These tests require the presence of a medical practitioner for evaluation and assessment purposes and are currently performed ambulant at doctor^'s offices or hospitals. Recently, there have been reports of letter based tests such as Pelli-Robson and Sloan LCLA for smart devices such as iPads (Lin 2015).

Further, diagnostic tools are used in MS diagnosis. Such tools include neuroimaging, analysis of cerebrospinal fluid and evoked potentials. Magnetic resonance imaging (MRI) of the brain and spinal cord can visualize demyelination (lesions or plaques). Contrast agents containing gadolinium can be administered intravenously to mark active plaques and, differentiate acute inflammation from the existence of older lesions which are not associated with symptoms at the moment of the evaluation. The analysis of cerebrospinal fluid obtained from a lumbar puncture can provide evidence of chronic inflammation of the central nervous system. The cerebrospinal fluid can be analyzed for oligoclonal immunoglobulin bands, which are an inflammation marker present in 75-85% of people with MS (Link 2006, J Neuroimmunol. 180 (1-2): 17-28). However, none of the aforementioned techniques is specific to MS. Therefore, ascertainment of diagnosis may require repetition of clinical and MRI investigations to demonstrate dissemination in space and in time of the disease which is a prerequisite to MS diagnosis.

There are several treatments approved by regulatory agencies for relap sing-remitting multiple sclerosis which shall modify the course of the disease. These treatments include interferon beta- la, interferon beta- lb, glatiramer acetate, mitoxantrone, natalizumab, fmgolimod, teriflunomide, dimethyl fumarate, alemtuzumab, and daclizumab. The interferons and glatiramer acetate are first-line treatments that reduce relapses by approximately 30% (see, e.g., Tsang 2011, Australian family physician 40 (12): 948-55). Natalizumab reduces the relapse rate more than the interferons, however, due to issues of adverse effects it is a second-line agent reserved for those who do not respond to other treatments or patients with severe disease (see, e.g., Tsang 2011, loc. cit.). Treatment of clinically isolated syndrome (CIS) with interferons decreases the chance of progressing to clinically definite MS (Compston 2008, Lancet 372(9648): 1502-17). Efficacy of interferons and glatiramer acetate in children has been estimated to be roughly equivalent to that of adults (Johnston 2012, Drugs 72 (9): 1195-211).

Recently, new monoclonal antibodies such as ocrelizumab, alemtuzumab and daclizumab have shown potential as therapeutics for MS. The anti-CD20 B-cell targeting monoclonal antibody ocrelizumab has shown beneficial effects in both relapsing and primary progressive forms of MS in one phase 2 and 3 phase III trials (NCT00676715, NCT01247324, NCT01412333, NCT01194570).

MS is a clinically heterogeneous inflammatory disease of the CNS. Therefore, diagnostic tools are needed that allow a reliable diagnosis and identification of the present disease status and can, thus, aid an accurate treatment, in particular, for those patients suffering for progressing forms of MS.

The technical problem underlying the present invention may be seen in the provision of means and methods complying with the aforementioned needs. The technical problem is solved by the embodiments characterized in the claims and described herein below.

The present invention, thus, relates to a method for assessing contrast vision capabilities in a subject comprising the steps of: a) determining at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from said subject; b) comparing the determined at least one contrast vision parameter to a reference; and c) assessing the contrast vision capabilities of the subject based on said comparison.

The method is, typically, a computer implemented method, i.e. the steps a) to c) are carried out in an automated manner, typically, by use of a data processing device. Details are also found herein below and in the accompanying Examples.

In some embodiments, the method may also comprise prior to step (a) the step of obtaining from the subject using a mobile device a dataset of measurements of non-cognitive contrast vision capabilities from said subject during predetermined activity performed by the subject or during a predetermined time window. However, typically the method is an ex vivo method carried out on an existing dataset of measurements from a subject which does not require any physical interaction with the said subject.

The method as referred to in accordance with the present invention includes a method which essentially consists of the aforementioned steps or a method which may include additional steps.

As used in the following, the terms “have”, “comprise” or “include” or any arbitrary grammatical variations thereof are used in a non-exclusive way. Thus, these terms may both refer to a situation in which, besides the feature introduced by these terms, no further features are present in the entity described in this context and to a situation in which one or more further features are present. As an example, the expressions “A has B”, “A comprises B” and “A includes B” may both refer to a situation in which, besides B, no other element is present in A (i.e. a situation in which A solely and exclusively consists of B) and to a situation in which, besides B, one or more further elements are present in entity A, such as element C, elements C and D or even further elements.

Further, it shall be noted that the terms “at least one”, “one or more” or similar expressions indicating that a feature or element may be present once or more than once typically will be used only once when introducing the respective feature or element. In the following, in most cases, when referring to the respective feature or element, the expressions “at least one” or “one or more” will not be repeated, non-withstanding the fact that the respective feature or element may be present once or more than once. Further, as used in the following, the terms "particularly", "more particularly", "specifically", "more specifically", “typically”, and “more typically” or similar terms are used in conjunction with additional / alternative features, without restricting alternative possibilities. Thus, features introduced by these terms are additional / alternative features and are not intended to restrict the scope of the claims in any way. The invention may, as the skilled person will recognize, be performed by using alternative features. Similarly, features introduced by "in an embodiment of the invention" or similar expressions are intended to be additional / alternative features, without any restriction regarding alternative embodiments of the invention, without any restrictions regarding the scope of the invention and without any restriction regarding the possibility of combining the features introduced in such way with other additional / alternative or non-additional / alternative features of the invention.

The method may be carried out on the mobile device by the subject once the dataset of measurements of non-cognitive contrast vision capabilities has been acquired. Thus, the mobile device and the device acquiring the dataset may be physically identical, i.e. the same device. Such a mobile device shall have a data acquisition unit which typically comprises means for data acquisition, i.e. means which detect or measure either quantitatively or qualitatively physical and/or chemical parameters and transform them into electronic signals transmitted to the evaluation unit in the mobile device used for carrying out the method according to the invention. The data acquisition unit comprises means for data acquisition, i.e. means which detect or measure either quantitatively or qualitatively physical and/or chemical parameters and transform them into electronic signals transmitted to the device being remote from the mobile device and used for carrying out the method according to the invention. Typically, said means for data acquisition comprise at least one sensor. It will be understood that more than one sensor can be used in the mobile device, i.e. at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine or at least ten or even more different sensors. Typical sensors used as means for data acquisition are sensors such as gyroscope, magnetometer, accelerometer, proximity sensors, thermometer, humidity sensors, pedometer, heart rate detectors, fingerprint detectors, touch sensors, voice recorders, light sensors, pressure sensors, location data detectors, cameras, sweat analysis sensors and the like. The evaluation unit typically comprises a processor and a database as well as software which is tangibly embedded to said device and, when running on said device, carries out the method of the invention. More typically, such a mobile device may also comprise a user interface, such as a screen, which allows for providing the result of the analysis carried out by the evaluation unit to a user. Alternatively, it may be carried out on a device being remote with respect to the mobile device that has been used to acquire the said dataset. In this case, the mobile device shall merely comprise means for data acquisition, i.e. means which detect or measure either quantitatively or qualitatively physical and/or chemical parameters and transform them into electronic signals transmitted to the device being remote from the mobile device and used for carrying out the method according to the invention. Typically, said means for data acquisition comprise at least one sensor. It will be understood that more than one sensor can be used in the mobile device, i.e. at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine or at least ten or even more different sensors. Typical sensors used as means for data acquisition are sensors such as gyroscope, magnetometer, accelerometer, proximity sensors, thermometer, humidity sensors, pedometer, heart rate detectors, fingerprint detectors, touch sensors, voice recorders, light sensors, pressure sensors, location data detectors, cameras, sweat analysis sensors, GPS, and the like. Thus, the mobile device and the device used for carrying out the method of the invention may be physically different devices. In this case, the mobile device may correspond with the device used for carrying out the method of the present invention by any means for data transmission. Such data transmission may be achieved by a permanent or temporary physical connection, such as coaxial, fiber, fiber-optic or twisted-pair, 10 BASE-T cables. Typically, however, it may be achieved by a temporary or permanent wireless connection using, e.g., radio waves, such as Wi-Fi, LTE, LTE-advanced or Bluetooth. Accordingly, for carrying out the method of the present invention, the only requirement is the presence of a dataset of measurements obtained from a subject using a mobile device. The said dataset may also be transmitted or stored from the acquiring mobile device on a permanent or temporary memory device which subsequently can be used to transfer the data to the device used for carrying out the method of the present invention. The remote device which carries out the method of the invention in this setup typically comprises a processor and a database as well as software which is tangibly embedded to said device and, when running on said device, carries out the method of the invention. More typically, the said device may also comprise a user interface, such as a screen, which allows for providing the result of the analysis carried out by the evaluation unit to a user.

Typically, the mobile device may also determine environmental parameters which may affect the measurements of non-cognitive contrast vision capabilities to be carried out. For example, environmental light may be measured by sensor equipment in the mobile device and the device may show instructions in the display to position the mobile device with respect to the environmental light such that the method can be performed under optimal conditions. Moreover, gyroscope, accelerometer and other sensor equipment may be used to determine an optimal position for carrying out the measurements of non-cognitive contrast vision capabilities as well. Again, instructions for optimal positioning of the mobile device may be shown on the display.

The term “assessing” as used herein refers to assessing whether a subject suffers from an impairment of contrast vision capabilities, or not, or whether said contrast vision capabilities worsens or improves over time or dependent on a certain stimulation, or not. Accordingly, assessing as used herein includes identifying an impairment of contrast vision capabilities, identifying improvement or worsening of the said contrast vision capabilities, monitoring contrast vision capabilities, determining efficacy of a therapy of impaired contrast vision capabilities, and/or diagnosing impaired contrast vision capabilities. Typically, the term may also encompass the stratification of subjects for or during re-myelination therapies. Moreover, the assessing may also relate to predicting relapse events in disease and, in particular, in MS. As will be understood by those skilled in the art, such an assessment, although preferred to be, may usually not be correct for 100% of the investigated subjects. The term, however, requires that a statistically significant portion of subjects can be correctly assessed. Whether a portion is statistically significant can be determined without further ado by the person skilled in the art using various well known statistic evaluation tools, e.g., determination of confidence intervals, p-value determination, Student^'s t-test, Mann-Whitney test, etc.. Details may be found in Dowdy and Wearden, Statistics for Research, John Wiley & Sons, New York 1983. Typically envisaged confidence intervals are at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95%. The p-values are, typically, 0.2, 0.1, 0.05. Thus, the method of the present invention, typically, aids the assessment of contrast vision impairment by providing a means for evaluating a dataset of measurements of non-cognitive contrast vision capabilities.

The term “contrast vision capabilities” as used herein refers to the ability of the subject to visually recognize an object or its representation in an image or display from the background. The contrast is determined by the difference in color and brightness of an object versus other objects and/or background within a certain field of view. The visual system is more sensitive to contrast than to absolute luminance. The contrast vision capabilities also referred to as visual acuity capabilities may be affected by any impairment of a component of the visual system. This includes the eyes, the optic nerves as well as the visual brain comprising parts of the midbrain as well as the visual cortex. Impairments may arise from damage, lesions or inflammation of said tissues or organs, e.g., caused by macular degeneration, diabetes, cancer, stroke or multiple sclerosis (MS).

The term “non-cognitive contrast vision capabilities” refers to contrast vision capabilities which do not require involvement of the higher cognitive functions of the brain. In particular, non- cognitive contrast vision capabilities do not involve association capabilities in relation to an object or features thereof. Typically, an object to be recognized at different levels of contrast is a symbol having no cultural meaning for the subject to be tested. For example, if a letter or number is displayed to subject, higher cognitive functions will associate features to the letter or number. Thus, even when the letter or number cannot be properly recognized by the vision capabilities, the higher brain functions may correctly construct an imaginary image of the letter or number based on even a limited amount of features. In accordance with the present invention, it is envisaged to measure pivotally those contrast vision capabilities the deficiency of which is not compensated by such higher cognitive functions such as association. This can be typically achieved by presenting as symbol to the subject that has no cultural or other meaning to the subject and the features of which can be recognized solely using the aforementioned non- cognitive contrast vision capabilities depending on the contrast viz-a-viz a given background.

The term “subject” as used herein relates to animals and, typically, to mammals. In particular, the subject is a primate and, most typically, a human. The subject in accordance with the present invention shall suffer from or shall be suspected to suffer from impaired contrast vision capabilities. As discussed elsewhere herein, contrast vision capabilities may become affected in neurodegenerative disorders and, in particular, in MS. Thus, the subject in accordance with the present invention is, typically, a subject suffering from or suspected to suffer from MS.

The term “contrast vision parameter” as used herein refers to a parameter which is indicative for the capability of a subject to carry out a certain activity during the measurement involving contrast vision capabilities.

The term “at least one” means that one or more contrast vision parameter may be determined in accordance with the invention, i.e. at least two, at least three, at least four or even more different performance parameters. Thus, there is no upper limit for the number of different contrast vision parameter which can be determined in accordance with the method of the present invention.

Typically, the parameter(s) are selected from datasets of measurements of non-cognitive contrast vision capabilities and comprise optical recognition, typically, at varying levels of contrast, of a symbol or one or more features thereof, wherein said recognition does not require involvement of cognitive capabilities of the subject. The symbol is, typically, a Landolt ring. However, other symbols the recognition of which does not involve cognitive capabilities may also be used in the measurements. Typically, such symbols are not and are not related to letters, numbers or any other symbols which have a meaning associated thereto and which could be also recognized by higher cognitive functions of the brain.

Typically, the contrast vision parameter may be the accuracy or speed with which a symbol or one or more features thereof is optically recognized on a screen displaying said symbol with a predetermined contrast level viz-a-viz a background. For example, the contrast vision parameter may be determined from a dataset of measurements of contrast vision capabilities wherein said measurements comprise displaying to the subject to be tested on a display a symbol the recognition of which does not require cognitive capabilities such as a Landolt ring at varying levels of contrast. During the measurements, the subject must indicate the position of the opening of the displayed Landolt ring. The measurements comprise, inter alia, data which allow for determining the accuracy of the indication made by the subject and/or the speed for performing said task. The contrast vision parameter may be the accuracy, the speed or any parameter derived from one or both of said values.

The term “dataset of measurements” refers to the entirety of data which has been acquired by the mobile device from a subject during measurements of non-cognitive contrast vision capabilities from said subject or to a subset of data. The dataset according to the method of the present invention may be derived from a contrast vison test performed by a subject to be tested. The subject may carry out a computer implemented test for visual acuity. In said test, a symbol shall be displayed to the subject on a display. The symbol of features thereof shall be recognized by the subject which to this end shall generate a predefined input signal once the symbol or one or more features thereof have been recognized. Time and accuracy data, e.g., the position of certain predetermined features of the symbol or the position of the symbol on the display will be recorded and compiled as a dataset of measurements of non-cognitive contrast vision capabilities from said subject provided for evaluation by the method of the present invention. As discussed above, care should be taken by selecting a symbol which requires non-cognitive contrast vision capabilities for recognition. Further details are found in the accompanying Examples, below.

Determining at least one contrast vision parameter can be achieved either by deriving a desired measured value from the dataset as the performance parameter directly. Alternatively, the parameter may integrate one or more measured values from the dataset and, thus, may be a derived from the dataset by mathematical operations such as calculations. Typically, the performance parameter is derived from the dataset by an automated algorithm, e.g., by a computer program which automatically derives the performance parameter from the dataset of measurements when tangibly embedded on a data processing device feed by the said dataset. The term “reference” as used herein refers to a discriminator which allows for assessing contrast vision capabilities based on the determined at least one contrast vision parameter. Such a discriminator may be a value for the contrast vision parameter which is indicative for subjects with normal (i.e. healthy or physiological) contrast vision or for subjects with impaired (i.e. pathological) contrast vision.

Such a value may be derived from one or more contrast vision parameters of subjects known to have impaired contrast vision capabilities. Typically, the average or median of the parameter may be used as a discriminator in such a case. If the determined contrast vision parameter from the subject is identical to the reference or above a threshold derived from the reference, the subject can be identified as exhibiting impaired contrast vision capabilities in such a case. If the determined contrast vision parameter differs from the reference and, in particular, is below the said threshold, the subject shall be identified as not exhibiting impaired contrast vision capabilities.

Similarly, a value may be derived from one or more contrast vision parameters of subjects known not to have impaired contrast vision capabilities. Typically, the average or median of the parameter may be used as a discriminator in such a case. If the determined contrast vision parameter from the subject is identical to the reference or below a threshold derived from the reference, the subject can be identified as not exhibiting impaired contrast vision capabilities in such a case. If the determined performance parameter differs from the reference and, in particular, is above the said threshold, the subject shall be identified as exhibiting impaired contrast vision capabilities.

As an alternative, the reference may be a previously determined contrast vision parameter from a dataset of measurements which has been obtained from the same subject prior to the actual dataset. In such a case, a determined contrast vision parameter determined from the actual dataset which differs with respect to the previously determined parameter shall be indicative for either an improvement or worsening depending on the previous status of the contrast vision capabilities and the kind of activity represented by the contrast vision parameter. The skilled person knows based on the kind of activity and previous parameter how the said parameter can be used as a reference.

Comparing the determined at least one contrast vision parameter to a reference can be achieved by an automated comparison algorithm implemented on a data processing device such as a computer. Compared to each other are the values of a determined contrast vision parameter and a reference for said determined parameter as specified elsewhere herein in detail. As a result of the comparison, it can be assessed whether the determined contrast vision parameter is identical or differs from or is in a certain relation to the reference (e.g., is larger or lower than the reference). Based on said assessment, the subject can be identified as exhibiting impaired contrast vision capabilities (“rule-in”), or not (“rule-out”). For the assessment, the kind of reference will be taken into account as described elsewhere in connection with suitable references according to the invention.

Moreover, by determining the degree of difference between a determined contrast vision parameter and a reference, a quantitative assessment of contrast vision capabilities in a subject shall be possible. It is to be understood that an improvement, worsening or unchanged condition can be determined by comparing an actually determined contrast vision parameter to an earlier determined one used as a reference. Based on quantitative differences in the value of the said contrast vision parameter the improvement, worsening or unchanged condition can be determined and, optionally, also quantified. If other references, such as references from subjects exhibiting impaired contrast vision capabilities are used, it will be understood that the quantitative differences are meaningful if a certain stage of impairment can be allocated to the reference collective. Relative to this stage of impairment, worsening, improvement or unchanged condition can be determined in such a case and, optionally, also quantified.

The assessment made by the method of the present invention is indicated to the subject or to another person, such as a medical practitioner. Typically, this is achieved by displaying the diagnosis on a display of the mobile device or the evaluation device. Alternatively, a recommendation for a therapy, such as a drug treatment, or for a certain life style, e.g. rehabilitation measures, is provided automatically to the subject or other person. To this end, the established assessment is compared to recommendations allocated to different assessments in a database. Once the established assessment matches one of the stored and allocated assessments, a suitable recommendation can be identified due to the allocation of the recommendation to the stored assessment matching the established assessment. Accordingly, it is, typically, envisaged that the recommendations and assessments are present in form of a relational database. However, other arrangements which allow for the identification of suitable recommendations are also possible and known to the skilled artisan.

Moreover, the one or more contrast vision parameter may also be stored on the mobile device or indicated to the subject, typically, in real time. The stored contrast vision parameters may be assembled into a time course or similar evaluation measures. Such evaluated contrast vision parameters may be provided to the subject as a feedback for the contrast vision capabilities investigated in accordance with the method of the invention. Typically, such a feedback can be provided in electronic format on a suitable display of the mobile device and can be linked to a recommendation for a therapy as specified above or rehabilitation measures.

Further, the evaluated contrast vision parameters may also be provided to medical practitioners in doctor^'s offices or hospitals as well as to other health care providers, such as, developers of diagnostic tests or drug developers in the context of clinical trials, health insurance providers or other stakeholders of the public or private health care system.

Typically, the method of the present invention for assessing contrast vision capabilities in a subject may be carried out as follows:

First, at least one contrast vision parameter is determined from an existing dataset of measurements of non-cognitive contrast vision capabilities obtained from said subject using a mobile device. Said dataset may be transmitted from the mobile device to an evaluating device, such as a computer, or may be processed in the mobile device in order to derive the at least one contrast vision parameter from the dataset.

Second, the determined at least one contrast vision parameter is compared to a reference by, e.g., using a computer-implemented comparison algorithm carried out by the data processor of the mobile device or by the evaluating device, e.g., the computer. The result of the comparison is assessed with respect to the reference used in the comparison and based on the said comparison the contrast vision capabilities in the subject will be assessed, e.g., the subject will be identified as having impaired contrast vision capabilities, or not.

Third, the said assessment, e.g., the identification of the subject as having impaired contrast vision capabilities, or not, is indicated to the subject or to another person, such as a medical practitioner, on a suitable display such as a screen connected or implemented in the mobile device or the evaluation device.

Alternatively, a recommendation for a therapy, such as a drug treatment, or for a certain life style, is provided automatically to the subject or other person. To this end, the established assessment is compared to recommendations allocated to different assessments in a database. Once the established assessment matches one of the stored and allocated assessments, a suitable recommendation can be identified due to the allocation of the recommendation to the stored assessment matching the established assessment. Particular envisaged in accordance with the present invention is a recommendation for a re-myelination therapy. Yet as an alternative or in addition, the at least one contrast vision parameter underlying the assessment will be stored on the mobile device. Typically, it shall be evaluated together with other stored contrast vision parameters by suitable evaluation tools, such as time course assembling algorithms, implemented on the mobile device which can assist electronically rehabilitation or therapy recommendation as specified elsewhere herein.

The invention, in light of the above, also specifically contemplates a method for assessing contrast vision capabilities in a subject comprising the steps of: a) obtaining from said subject using a mobile device a dataset of measurements of non-cognitive contrast vision capabilities from the subject; b) determining at least one contrast vision parameter determined from a dataset of measurements of non-cognitive contrast vision capabilities obtained from said subject using a mobile device; c) comparing the determined at least one contrast vision parameter to a reference; and d) assessing the contrast vision capabilities in the subject based on the comparison carried out in step c).

Advantageously, it has been found in the studies underlying the present invention that contrast vision parameters obtained from datasets of measurements of non-cognitive contrast vision capabilities can be used as digital biomarkers for identifying impaired contrast vision capabilities. An impairment of the contrast vision capabilities occurs during the early onset of MS due to inflammation of the optic nerves. It has been found in accordance with the present invention that contrast vision capabilities can be measured gradually using a mobile device. The mobile device shall carry out a computer-implemented version of the Landolt test using different types of Landolt rings presented to the patient in different forms with varying levels of contrast. Using this automated version, it is possible to identify even minor changes in contrast vision capabilities. Moreover, the patient may carry out the test thanks to the mobile device at any time and in any place. There is no need for consultation of a medical practitioner in a doctor's office or hospital ambulance for performing the measurement. Further, it has been found that it is advantageous to use a symbol, such as a Landolt ring, which does not elicit cognitive associations by higher brain functions which may compensate for the impaired function of the optic nerves due to MS. Thereby, the method of the present invention is robust with respect to false negative testing which may occur in other tests due to compensation by the brain. Thanks to the present invention, the life conditions of MS patients, in particular, at early stages, can be adjusted more precisely to the actual disease status due to the use of actual determined performance parameters by the method of the invention. Thereby, drug treatments, such as re-myelination therapies, can be selected that are more efficient or dosage regimens can be adapted to the current status of the patient. It is to be understood that the method of the invention is, typically, a data evaluation method which requires an existing dataset of activity measurements from a subject.

Accordingly, the method of the present invention may be used for: assessing the disease condition comprising, inter alia, assessing relapse events in MS patients; monitoring patients, in particular, in a real life, daily situation and on large scale; supporting patients with life style and/or therapy recommendations; investigating drug efficacy, e.g. also during clinical trials; facilitating and/or aiding therapeutic decision making, in particular with respect to re- myelination therapies; supporting hospital managements; supporting rehabilitation measure management; improving the disease condition as a rehabilitation instrument stimulating higher density cognitive, motoric and walking activity supporting health insurances assessments and management; and/or supporting decisions in public health management.

In addition to its application in MS management, the method of the present invention can, in principle, be used for assessing contrast vision capabilities. Impaired contrast vision capabilities may also result from other diseases or conditions such as cancer, stroke, damage or injury. The method of the present invention can, thus, also aid diagnostic tasks when investigating such disease or conditions and provide an aid for therapeutic recommendations.

The definitions and explanations of the terms made above apply mutatis mutandis for the following embodiments except as specified otherwise.

In an embodiment of the method of the invention, said measurements of non-cognitive contrast vision capabilities comprise optical recognition of a symbol or one or more features thereof, wherein said recognition does not require involvement of cognitive capabilities of the subject. Typically, said measurement of optical recognition of a symbol or one or more features thereof is carried out at varying levels of contrast. Typically, said symbol is a Landolt ring. In yet an embodiment of the method of the invention, said measurements are carried out using a mobile device. Typically, said mobile device is comprised in a smartphone or tablet computer.

In an embodiment of the method of the invention, said method is computer-implemented.

In yet an embodiment of the method of the invention, the reference is at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from said subject wherein said dataset has been obtained prior to the dataset of step a).

In another embodiment of the method of the invention, the reference is at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from at least one subject known to have normal or impaired contrast vision capabilities.

The present invention relates to a method of assessing multiple sclerosis (MS) in a subject comprising assessing contrast vision capabilities according to the aforementioned method of the invention and the further step of assessing MS based on the contrast vision capabilities of the subject.

The term “multiple sclerosis (MS)” as used herein relates to disease of the central nervous system (CNS) that typically causes prolonged and severe disability in a subject suffering therefrom. There are four standardized subtype definitions of MS which are also encompassed by the term as used in accordance with the present invention: relapsing-remitting, secondary progressive, primary progressive and progressive relapsing. The relapsing forms of MS encompass relapsing-remitting and secondary progressive MS with superimposed relapses. The relapsing-remitting subtype is characterized by unpredictable relapses followed by periods of months to years of remission with no new signs of clinical disease activity. Deficits suffered during attacks (active status) may either resolve or leave sequelae. This describes the initial course of 85 to 90% of subjects suffering from MS. Secondary progressive MS describes those with initial relapsing-remitting MS, who then begin to have progressive neurological decline between acute attacks without any definite periods of remission. Occasional relapses and minor remissions may appear. The median time between disease onset and conversion from relapsing remitting to secondary progressive MS is about 19 years. The primary progressive subtype describes about 10 to 15% of subjects who never have remission after their initial MS symptoms. It is characterized by progressive of disability from onset, with no, or only occasional and minor, remissions and improvements. The age of onset for the primary progressive subtype is later than other subtypes. Progressive relapsing MS describes those subjects who, from onset, have a steady neurological decline but also suffer clear superimposed attacks. It is now accepted that this latter progressive relapsing phenotype is a variant of primary progressive MS (PPMS) and diagnosis of PPMS according to McDonald 2010 criteria includes the progressive relapsing variant.

Symptoms associated with MS include changes in sensation (hypoesthesia and par-aesthesia), muscle weakness, muscle spasms, difficulty in moving, difficulties with co-ordination and balance (ataxia), problems in speech (dysarthria) or swallowing (dysphagia), visual problems (nystagmus, optic neuritis and reduced visual acuity, or diplopia), fatigue, acute or chronic pain, bladder, sexual and bowel difficulties. Cognitive impairment of varying degrees as well as emotional symptoms of depression or unstable mood are also frequent symptoms. The main clinical measure of disability progression and symptom severity is the Expanded Disability Status Scale (EDSS). Further symptoms of MS are well known in the art and are described in the standard text books of medicine and neurology.

The term “progressing MS” as used herein refers to a condition, where the disease and/or one or more of its symptoms get worse over time. Typically, the progression is accompanied by the appearance of active statuses. The said progression may occur in all subtypes of the disease. However, typically “progressing MS” shall be determined in accordance with the present invention in subjects suffering from relapsing-remitting MS.

In an embodiment of said method of the invention, said assessing MS comprises diagnosing and/or predicting relapse events, transient daily fluctuations, recommending re-myelination therapies.

The present invention also encompasses a method for determining efficacy of a therapy against MS comprising the steps of the method of the invention (i.e. the method for assessing MS) and the further step of determining a therapy response if improvement of the contrast vision capabilities occur in the subject upon therapy or determining a failure of response if worsening of contrast vision capabilities occur in the subject upon therapy or if the contrast vision capabilities remain unchanged.

The term “a therapy against a MS” as used herein refers to all kinds of medical treatments, including drug-based therapies, respiratory support and the like. The term also encompasses, life-style recommendations and rehabilitation measures. Typically, the method encompasses recommendation of a drug-based therapy and, in particular, a therapy with a drug known to be useful for the treatment of MS. Such drug may be a therapy applying an anti-CD20 antibody and, more typically, Ocrelizumab (Hutas 2008). Moreover, the aforementioned method may comprise in yet an embodiment the additional step of applying the recommended therapy to the subject.

Moreover, encompassed in accordance with the present invention is a method for determining efficacy of a therapy against MS comprising the steps of the aforementioned method of the invention (i.e. the method for assessing MS) and the further step of determining a therapy response if improvement of contrast vision capabilities occur in the subject upon therapy or determining a failure of response if worsening of contrast vision capabilities occur in the subject upon therapy or if contrast vision capabilities remain unchanged.

The term “improvement” as referred to in accordance with the present invention relates to any improvement of the overall disease condition or of individual symptoms thereof and, in particular, the contrast vision capabilities. Likewise, a “worsening” means any worsening of the overall disease condition or individual symptoms thereof and, in particular, the contrast vision capabilities. Since, MS as a progressing disease is associated typically with a worsening of the overall disease condition and symptoms thereof, the worsening referred to in connection with the aforementioned method is an unexpected or untypical worsening which goes beyond the normal course of the disease. Unchanged MS means that the overall disease condition and the symptoms accompanying it are within the normal course of the disease.

Moreover, the present invention pertains to a method of monitoring MS in a subject comprising determining whether said disease improves, worsens or remains unchanged in a subject by carrying out the steps of the method of the invention (i.e. the method of assessing MS) at least two times during a predefined monitoring period. If the contrast vision capabilities improve, the disease improves, if the contrast vision capabilities worsen, the disease worsens and if the contrast vision capabilities remain unchanged, the disease does as well.

The present invention relates to a mobile device comprising a processor, at least one sensor and a database as well as software which is tangibly embedded to said device and, when running on said device, carries out the method of the invention.

The term “mobile device” as used herein refers to any portable device which comprises at least a sensor and data-recording equipment suitable for obtaining the dataset of the above measurements. This may also require a data processor and storage unit as well as a display for electronically simulating a test for non-cognitive contrast vision capabilities on the mobile device. The data processor may comprise a Central Processing Unit (CPU) and/or one or more Graphics Processing Units (GPUs) and/or one or more Application Specific Integrated Circuits (ASICs) and/or one or more Tensor Processing Units (TPUs) and/or one or more field- programmable gate arrays (FPGAs) or the like. Moreover, from the activity of the subject data shall be recorded and compiled to a dataset which is to be evaluated by the method of the present invention either on the mobile device itself or on a second device. Depending on the specific setup envisaged, it may be necessary that the mobile device comprises data transmission equipment in order to transfer the acquired dataset from the mobile device to further device. Particular well suited as mobile devices according to the present invention are smartphones, portable multimedia devices or tablet computers. Alternatively, portable sensors with data recording and processing equipment may be used. Further, depending on the kind of activity test to be performed, the mobile device shall be adapted to display instructions for the subject regarding the activity to be carried out for the test. Particular envisaged activities to be carried out by the subject are described elsewhere herein and encompass the tests for non-cognitive contrast vision capabilities as described in this specification.

The present invention contemplates a system comprising a mobile device comprising at least one sensor and a remote device comprising a processor and a database as well as software which is tangibly embedded to said device and, when running on said device, carries out the method of the invention, wherein said mobile device and said remote device are operatively linked to each other.

Under “operatively linked to each other” it is to be understood that the devices are connect as to allow data transfer from one device to the other device. Typically, it is envisaged that at least the mobile device which acquires data from the subject is connect to the remote device carrying out the steps of the methods of the invention such that the acquired data can be transmitted for processing to the remote device. However, the remote device may also transmit data to the mobile device such as signals controlling or supervising its proper function. The connection between the mobile device and the remote device may be achieved by a permanent or temporary physical connection, such as coaxial, fiber, fiber-optic or twisted-pair, 10 BASE-T cables. Alternatively, it may be achieved by a temporary or permanent wireless connection using, e.g., radio waves, such as Wi-Fi, LTE, LTE-advanced or Bluetooth. Further details may be found elsewhere in this specification. For data acquisition, the mobile device may comprise a user interface such as screen or other equipment for data acquisition. Typically, the activity measurements can be performed on a screen comprised by a mobile device, wherein it will be understood that the said screen may have different sizes including, e.g., a 5.1 inch screen.

Yet, the invention relates to the use of the mobile device or the system of the invention for assessing contrast vision capabilities in a subject using at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from said subject.

Moreover, the invention relates to the use of the mobile device or the system of the invention for assessing MS in a subject using at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from said subject.

The present invention also contemplates the use of the mobile device or the system according to the present invention for monitoring patients, in particular, in a real life, daily situation and on large scale. Encompassed by the present invention is furthermore the use of the mobile device or the system according to the present invention for supporting patients with life style and/or therapy recommendations. Yet, it will be understood that the present invention contemplates the use of the mobile device or the system according to the present invention for investigating drug safety and efficacy, e.g. also during clinical trials. Further, the present invention contemplates the use of the mobile device or the system according to the present invention for facilitating and/or aiding therapeutic decision making. Furthermore, the present invention provides for the use of the mobile device or the system according to the present invention for improving the disease condition as a rehabilitation instrument, and for supporting hospital management, rehabilitation measure management, health insurances assessments and management and/or supporting decisions in public health management.

The present invention also, in principle, contemplates a computer program, computer program product or computer readable storage medium having tangibly embedded said computer program, wherein the computer program comprises instructions when run on a data processing device or computer carry out the method of the present invention as specified above. Specifically, the present disclosure further encompasses:

A computer or computer network comprising at least one processor, wherein the processor is adapted to perform the method according to one of the embodiments described in this description, a computer loadable data structure that is adapted to perform the method according to one of the embodiments described in this description while the data structure is being executed on a computer, a computer script, wherein the computer program is adapted to perform the method according to one of the embodiments described in this description while the program is being executed on a computer, a computer program comprising program means for performing the method according to one of the embodiments described in this description while the computer program is being executed on a computer or on a computer network, a computer program comprising program means according to the preceding embodiment, wherein the program means are stored on a storage medium readable to a computer, a storage medium, wherein a data structure is stored on the storage medium and wherein the data structure is adapted to perform the method according to one of the embodiments described in this description after having been loaded into a main and/or working storage of a computer or of a computer network, a computer program product having program code means, wherein the program code means can be stored or are stored on a storage medium, for performing the method according to one of the embodiments described in this description, if the program code means are executed on a computer or on a computer network, a data stream signal, typically encrypted, comprising a dataset measurements of non- cognitive contrast vision capabilities obtained from the subject using a mobile, and a data stream signal, typically encrypted, comprising the at least one contrast vision parameter derived from the dataset of measurements of non-cognitive contrast vision capabilities obtained from the subject using a mobile.

The present invention, further, relates to a method for determining at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from said subject using a mobile device a) deriving at least one contrast vision parameter from a dataset of non-cognitive contrast vision capabilities from said subject using a mobile device; and b) comparing the determined at least one contrast vision parameter to a reference, wherein, typically, said at least one contrast vision parameter can aid assessment of contrast vision capabilities in said subject. In the following, further particular embodiments of the invention are listed:

Embodiment 1 : A method for assessing contrast vision capabilities in a subject comprising the steps of: a) determining at least one contrast vision parameter from a dataset of measurements of non- cognitive contrast vision capabilities from said subject; b) comparing the determined at least one contrast vision parameter to a reference; and c) assessing the contrast vision capabilities of the subject based on said comparison.

Embodiment 2: The method of embodiment 1, wherein the said measurements of non-cognitive contrast vision capabilities comprise optical recognition of a symbol or one or more features thereof, wherein said recognition does not require involvement of cognitive capabilities of the subject.

Embodiment 3 : The method of embodiment 2, wherein said measurement of optical recognition of a symbol or one or more features thereof is carried out at varying levels of contrast.

Embodiment 4: The method of embodiment 2 or 3, wherein said symbol is a Landolt ring.

Embodiment 5: The method of any one of embodiments 1 to 4, wherein said measurements are carried out using a mobile device.

Embodiment 6: The method of embodiment 5, wherein said mobile device is comprised in a smartphone or tablet computer.

Embodiment 7: The method of any one of embodiments 1 to 6, wherein said method is computer-implemented.

Embodiment 8: The method of any one of embodiments 1 to 7, wherein the reference is at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from said subject wherein said dataset has been obtained prior to the dataset of step a).

Embodiment 9: The method of any one of embodiments 1 to 7, wherein the reference is at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from at least one subject known to have normal or impaired contrast vision capabilities. Embodiment 10: A method of assessing multiple sclerosis (MS) in a subject comprising assessing contrast vision capabilities according to the method of any one of embodiments 1 to 9 and the further step of assessing MS based on the contrast vision capabilities of the subject.

Embodiment 11: The method of embodiment 10, wherein said assessing MS comprises diagnosing and/or predicting relapse events, transient daily fluctuations, recommending re- myelination therapies.

Embodiment 12: A mobile device comprising a processor, at least one sensor and a database as well as software which is tangibly embedded to said device and, when running on said device, carries out the method of any one of embodiments 1 to 9.

Embodiment 13: A system comprising a mobile device comprising at least one sensor and a remote device comprising a processor and a database as well as software which is tangibly embedded to said device and, when running on said device, carries out the method of any one of embodiments 1 to 9, wherein said mobile device and said remote device are operatively linked to each other.

Embodiment 14: Use of the mobile device according to embodiment 12 or the system of claim 13 for assessing contrast vision capabilities in a subject using at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from said subject.

Embodiment 15: Use of the mobile device according to embodiment 12 or the system of claim 13 for assessing MS in a subject using at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from said subject.

All references cited throughout this specification are herewith incorporated by reference with respect to their entire disclosure content and with respect to the specific disclosure contents mentioned in the specification. FIGURES:

Figure 1 shows a view of a display of a smart phone display having implemented the contrast vision test according to the invention. Instructions are given to the patient how to carry the test for the left eye (A) to (C).

Figure 2 shows Landolt rings at a given contrast viz-a-viz the display background. The position of the opening at different positions in A) and B) in the Landolt ring needs to be recognized and indicated on the display by touching.

EXAMPLES:

The following Examples merely illustrate the invention. Whatsoever, they shall not be construed in a way as to limit the scope of the invention.

Example 1: Results from the prospective pilot study (FLOODLIGHT) to evaluate contrast vision capabilities with the use of digital technology in patients with multiple sclerosis

A study population was selected by using the following inclusion and exclusion criteria:

Key inclusion criteria:

• Signed informed consent form

• Able to comply with the study protocol, in the investigator’s judgment

• Age 18 - 55 years, inclusive

• Have a definite diagnosis of MS, confirmed as per the revised McDonald 2010 criteria

• EDSS score of 0.0 to 5.5, inclusive

• Weight: 45 -110 kg

• For women of childbearing potential: Agreement to use an acceptable birth control method during the study period

Key exclusion criteria:

• Severely ill and unstable patients as per investigator’s discretion

• Change in dosing regimen or switch of disease modifying therapy (DMT) in the last 12 weeks prior to enrollment

• Pregnant or lactating, or intending to become pregnant during the study It is a primary objective of this study to show adherence to smartphone and smartwatch-based assessments quantified as compliance level (%) and to obtain feedback from patients and healthy controls on the smartphone and smartwatch schedule of assessments and the impact on their daily activities using a satisfaction questionnaire. Furthermore, additional objectives are addressed, in particular, the association between assessments conducted using the Floodlight Test and conventional MS clinical outcomes was determined, it was established if Floodlight measures can be used as a marker for disease activity/progression and are associated with changes in MRI and clinical outcomes over time and it was determined if the Floodlight Test Battery can differentiate between patients with and without MS, and between phenotypes in patients with MS.

In addition to the active tests and passive monitoring, the following assessments were performed at each scheduled clinic visit:

Oral Version of SDMT

Fatigue Scale for Motor and Cognitive Functions (FSMC)

Timed 25-Foot Walk Test (T25-FW)

Berg Balance Scale (BBS)

9-Hole Peg Test (9HPT)

Patient Health Questionnaire (PHQ-9)

Patients with MS only:

Brain MRI (MSmetrix)

Expanded Disability Status Scale (EDSS)

Patient Determined Disease Steps (PDDS)

Pen and paper version of MSIS-29

While performing in-clinic tests, patients and healthy controls were asked to carry/wear smartphone and smartwatch to collect sensor data along with in-clinic measures.

In summary, the results of the study showed that patients are highly engaged with the smartphone- and smartwatch-based assessments. Moreover, there is a correlation between tests and in-clinic clinical outcome measures recorded at baseline which suggests that the smartphone-based Floodlight Test Battery shall become a powerful tool to continuously monitor MS in a real-world scenario. Further, the smartphone-based measurement of contrast vision capabilities such as smart phone-based measurements of contrast vision using Landolt ring tests will be used to show correlations with MS. Cited References

Aktas 2005, Neuron 46, 421-432.

Zamvil 2003, Neuron 38:685-688.

Kurtzke 1983, Neurology. 33 (11): 1444-52. doi:10.1212/WNL.33.11.1444. PMID 6685237.

Collins 2016, Multiple Sclerosis. 22 (10): 1349-58. doi : 10.1177/1352458515616205. PMC 5015760. PMID 26564998.

Breiman 2001, Machine Learning 45(1): 5-32 doi: 10.1023/A: 1010933404324 Balcer 2017, Mul. Scler. 23(5): 737-747.

Lin 2015, J Parkinsons Dis 5(1): 125-130.

Link 2006, J Neuroimmunol. 180 (1-2): 17-28.

Tsang 2011, Australian family physician 40 (12): 948-55.

Compston 2008, Lancet 372(9648): 1502-17.

Johnston 2012, Drugs 72 (9): 1195-211.

Hutas 2008, Current opinion in investigational drugs 9 (11): 1206-15.

Claims

1. A method for assessing contrast vision capabilities in a subject comprising the steps of: a) determining at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from said subject; b) comparing the determined at least one contrast vision parameter to a reference; and c) assessing the contrast vision capabilities of the subject based on said comparison.

2. The method of claim 1, wherein the said measurements of non-cognitive contrast vision capabilities comprise optical recognition of a symbol or one or more features thereof, wherein said recognition does not require involvement of cognitive capabilities of the subject.

3. The method of claim 2, wherein said measurement of optical recognition of a symbol or one or more features thereof is carried out at varying levels of contrast.

4. The method of claim 2 or 3, wherein said symbol is a Landolt ring.

5. The method of any one of claims 1 to 4, wherein said measurements are carried out using a mobile device.

6. The method of claim 5, wherein said mobile device is comprised in a smartphone or tablet computer.

7. The method of any one of claims 1 to 6, wherein said method is computer-implemented.

8. The method of any one of claims 1 to 7, wherein the reference is at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from said subject wherein said dataset has been obtained prior to the dataset of step a).

9. The method of any one of claims 1 to 7, wherein the reference is at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from at least one subject known to have normal or impaired contrast vision capabilities.

10. A method of assessing multiple sclerosis (MS) in a subject comprising assessing contrast vision capabilities according to the method of any one of claims 1 to 9 and the further step of assessing MS based on the contrast vision capabilities of the subject.

11. The method of claim 10, wherein said assessing MS comprises diagnosing and/or predicting relapse events, transient daily fluctuations, recommending re-myelination therapies.

12. A mobile device comprising a processor, at least one sensor and a database as well as software which is tangibly embedded to said device and, when running on said device, carries out the method of any one of claims 1 to 9.

13. A system comprising a mobile device comprising at least one sensor and a remote device comprising a processor and a database as well as software which is tangibly embedded to said device and, when running on said device, carries out the method of any one of claims 1 to 9, wherein said mobile device and said remote device are operatively linked to each other.

14. Use of the mobile device according to claim 12 or the system of claim 13 for assessing contrast vision capabilities in a subject using at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from said subject.

15. Use of the mobile device according to claim 12 or the system of claim 13 for assessing MS in a subject using at least one contrast vision parameter from a dataset of measurements of non-cognitive contrast vision capabilities from said subject.