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    • 专利摘要:
    A method of establishing a brain status indication parameter indicative of a brain disorder is disclosed. The method comprising the steps: - determining a brain energy metabolism indicator of at least a part of the brain of a subject, - determining a skull energy metabolism indicator of at least a part of the skull of said subject, - establishing the brain status indication parameter by at least relating said brain energy metabolism indicator to said skull energy metabolism indicator. Also disclosed are a system for establishing such brain status indication parameter, a computer program, and methods for treating a disease.
    公开号:DK201870707A1
    申请号:DKP201870707
    申请日:2018-10-31
    公开日:2020-06-08
    发明作者:Antonsen Segtnan Eivind
    申请人:Synaptic Aps；
    IPC主号:
    专利说明:

    METHOD OF ESTABLISHING A BRAIN STATUS INDICATION PARAMETER AND SYSTEM THEREFOR
    FIELD OF INVENTION
    The invention relates to a method for establishing a brain status indication parameter, particularly a brain status indication parameter indicative of brain disorders relating to diaschisis. The invention further relates to a system for establishing such brain status indication parameter, a computer program, and methods for treating a disease.
    BACKGROUND OF THE INVENTION
    The use of imaging techniques as input for diagnosing brain disorders has become extremely common. Nevertheless, such images are typically evaluated with respect to a specific area of the brain which is suspected to be affected. Also, the evaluation leading to the diagnosis may typically be done by the medical practitioner, leading to an inherently subjective nature of the findings which forms the basis for making the diagnosis.
    Thus, it continues to be a challenge to arrive at more accurate diagnoses.
    An object of the present invention is to solve the above challenges.
    SUMMARY
    The invention relates to a method of establishing a brain status indication parameter indicative of a brain disorder, the method comprising the steps:
    - determining a brain energy metabolism indicator of at least a part of the brain of a subject,
    - determining a skull energy metabolism indicator of at least a part of the skull of said subject,
    - establishing the brain status indication parameter by at least relating said brain energy metabolism indicator to said skull energy metabolism indicator.
    DK 2018 70707 A1
    One advantage of the invention is that a likelihood of presence of a brain disorder may be established with a higher accuracy than previously known methods. By relating the brain energy metabolism indicator with the skull energy metabolism indicator, an indication of the status of the brain is obtained as the brain status indication parameter. The brain status indication parameter may therefore be a highly valuable input for a medical practitioner in the process of diagnosing a subject.
    Particularly, by including the relation between the skull energy metabolism indicator and the brain energy metabolism indicator, variations between different subjects with respect to the energy metabolism in the brain can be at least partly accounted for to obtain a more accurate brain status indication parameter.
    Surprisingly, the present inventor discovered that by relating said brain energy metabolism indicator to said skull energy metabolism indicator an unprecedented accuracy with respect to the brain status indication parameter, even across different types of etiology in brain disorders. In advantageous embodiments the relation between said brain energy metabolism indicator and said skull energy metabolism is a ratio.
    A significant advantage of the invention is that deviations from subject to subject are countered by using the relation between the brain energy metabolism indicator and the skull energy metabolism indicator. In other words, using the mentioned relation helps to make the values comparable in the sense that deviation from normal values can be detected. Previous measurements for the same subject could in theory be comparable, but can in practice not be relied upon, since such only exists for exceptionally few subjects, and further since even minor changes in equipment and their settings may lead to different absolute values, and thus remove the comparability. The present inventor discovered that by using the skull values of the same subject a suitable reference value was obtained, i.e. by comparing the energy metabolism value of the brain or part thereof to the energy metabolism value of the skull or part thereof, the variations between subjects could be at least partly accounted for.
    DK 2018 70707 A1
    Even in cases when images of the brain do not provide any conclusive input to the medical practitioner, the brain status indication parameter of the present invention may still provide an indication of presence of a brain disorder, possibly even an indication specific type of brain disorder.
    Advantageously, by providing the medical practitioner with a parameter of diagnostic relevance in the form of the brain status indication parameter, a more accurate and fast diagnosis is facilitated, which again facilitates a more accurate and fast treatment. Therefore, a significant advantage of the present invention may be that it facilitates increased change of successful treatment, including higher change of survival, more effective mitigation of adverse effects of the disease or condition, mitigated side effects etc.
    In the present context, the term “brain” refers to the whole brain, i.e. including the cerebrum and the cerebellum, unless otherwise specifically stated.
    In the present context the term “brain energy metabolism indicator” refers to an indicator of the brain energy metabolism. It is noted that “energy metabolism” and “glucose metabolism” is used interchangeably herein. Particularly, it is noted that the brain energy metabolism indicator is related to at least a part of the brain. Thus, the brain energy metabolism indicator may be determined on the basis of a part of the brain in some embodiments, and on the basis of the whole brain in some other embodiments. Examples of parts of the brain for this purpose include the cerebrum, or part thereof such as the left or right hemisphere of the cerebrum, or another part of the cerebrum, the cerebellum, or part thereof such as the left or right hemisphere of the cerebellum, or another part of the cerebellum, the left or right hemisphere of the whole brain, or another part of the brain. It is also noted that the brain energy metabolism indicator includes both direct indicators, such as FDG-PET, and more indirect indicators showing e.g. neural activity or blood flow, which is associated with energy metabolism. The cerebellum comprises two hemispheres, a right hemisphere and a left
    DK 2018 70707 A1 hemisphere. Similarly, the cerebrum comprises two hemispheres, a right hemisphere and a left hemisphere. When referring to e.g. the left hemisphere of the brain, the left hemisphere of the cerebrum and of the cerebellum is meant, unless otherwise specifically stated.
    In the present context the term “skull energy metabolism indicator” refers to an indicator of the skull energy metabolism. It is noted that “energy metabolism” and “glucose metabolism” is used interchangeably herein. Particularly, it is noted that the skull energy metabolism indicator is related to at least a part of the skull. Thus, the skull energy metabolism indicator may be determined on the basis of a part of the skull in some embodiments, and on the basis of the whole skull in some other embodiments. It is also noted that the skull energy metabolism indicator includes both direct indicators, such as FDG-PET, and more indirect indicators showing e.g. blood flow, which is associated with energy metabolism.
    In the context of the present invention, the term “brain disorder indication parameter” is used as a parameter indicating the status of the brain and may indicate the likelihood of existence of a brain disorder and/or the type(s) of brain disorder(s) for the subject in question. In some embodiments, especially in simpler implementations, the brain disorder indication parameter is a number or value, typically between two predefined end point values. In some embodiments, especially in more refined implementations, the brain disorder indication parameter may comprise a set of number or values, each of which may indicate e.g. a likelihood of a certain type of brain disorder. It is noted that brain disorder indication parameter serves as an intermediate finding of diagnostic relevance in the sense that it does not replace a diagnosis but can be used as input by a medical practitioner in order to arrive at such diagnosis.
    In the present context the term “relating” may refer to various forms of correlating or comparing, i.e. a relation between said brain energy metabolism indicator to said skull energy metabolism indicator. In advantageous embodiments, the relating comprises at least finding the ratio between the two.
    DK 2018 70707 A1
    In the present context the term “brain disorder” is understood to broadly cover abnormalities related to the brain. It is noted that it may cover both causes (e.g. brain cancer) and resulting conditions (diaschisis). Thus, the various brain disorders mentioned herein may in some cases be somewhat overlapping. Examples of brain disorders include Alzheimer’s disease, Parkinson’s disease, Mild cognitive impairment (MCI), Glioma, Traumatic brain injury, Apoplexy, Neurosurgery and probable Drug side effects to the bram parenchyma.
    In the present context, the term “brain status establishment system” is understood as a system adapted to record measurements from subjects and establish a brain status indication parameter for each subject. In some embodiments, the system may further be configured to arrive at a diagnosis using at least the bram status indication parameter in the sense that a recommended treatment can readily be applied.
    According to an advantageous embodiment of the invention said relating involves calculating a ratio between the brain energy metabolism indicator and the skull energy metabolism indicator, or vice versa.
    An advantage of the above embodiment may be that variations between different subjects with respect to the energy metabolism in the brain can be at least partly accounted for to obtain more accurate brain status indication parameter. Particularly, by using the ratio between the brain energy metabolism indicator and the skull energy metabolism indicator (or vice versa) a more accurate measure with respect to brain disorder may be obtained, which is much less vulnerable for variations between subjects. This in turn supports the decision making of the medical practitioner to arrive at correct diagnosis and treatment adapted and tailored for the specific subject.
    According to an alternative embodiment, the relating may be in the form:
    Skull - brain ratio = Sk^erf
    DK 2018 70707 A1
    Here, i denotes the i’th part of the skull, j denotes the j’th part of the brain, a and b denote exponents, where a and b have opposite signs, i.e. a is positive and b is negative or vice versa.
    It is noted that this embodiment includes the ratio between the two values when a and b are unity values of opposite signs.
    According to an alternative embodiment, the relating may be in the form:
    Skull - brain ratio = kQ(Ski 4- k1)<l(Hzj + fc2)h
    Here, i denotes the i’th part of the skull, j denotes the j’th part of the brain, a and b denote exponents, where a and b have opposite signs, i.e. a is positive and b is negative or vice versa. Further, Ao, k and ki are constant values.
    It is noted that when k = ki = 0, the relation reduces to the above described relation.
    According to an advantageous embodiment of the invention said relating comprises calculating a ratio between the brain energy metabolism indicator and the skull energy metabolism indicator.
    According to an advantageous embodiment of the invention said part of the brain comprises at least the left hemisphere of cerebellum.
    Using the left hemisphere of the cerebellum in determining of the brain energy metabolism indicator, or when determining at one or more further brain energy metabolism indicators in determining of the brain energy metabolism indicator and/or at least one of the one or more further brain energy metabolism indicators.
    According to an advantageous embodiment of the invention said part of the brain comprises at least the right hemisphere of cerebellum.
    DK 2018 70707 A1
    According to an advantageous embodiment of the invention said part of the brain comprises at least the left hemisphere of cerebrum.
    According to an advantageous embodiment of the invention said part of the brain comprises at least the right hemisphere of cerebrum.
    According to an advantageous embodiment of the invention the brain energy metabolism indicator of the brain of the subject is determined.
    Thus, in the above embodiment of the brain energy metabolism indicator the whole brain is determined. In other words, the step of determining brain energy metabolism indicator of at least a part of the brain of said subject consists of determining brain energy metabolism indicator of the whole brain of said subject.
    According to an advantageous embodiment of the invention the part of the brain comprises at least the 50 percent most active nerve fibers.
    According to an advantageous embodiment of the invention the method comprises establishing a degree of symmetry between at least a part of the right hemisphere of the brain and a corresponding part of the left hemisphere of the brain.
    An advantage of the above embodiment may be that a very high accuracy brain status indication parameter may be obtained.
    It is noted that a healthy brain normally exhibits a high degree of symmetry and that deviating from such high degree of symmetry indicates presence of a brain disorder.
    According to an advantageous embodiment of the invention the degree of symmetry comprises a ratio between at least a part of the right hemisphere of the brain and a corresponding part of the left hemisphere of the brain.
    DK 2018 70707 A1
    According to an advantageous embodiment of the invention the degree of symmetry comprises a ratio between the right hemisphere of the cerebrum and the left hemisphere of the cerebrum.
    According to an advantageous embodiment of the invention the degree of symmetry comprises a ratio between the right hemisphere of the cerebellum and the left hemisphere of the cerebellum.
    According to an advantageous embodiment of the invention the degree of symmetry comprises a ratio between the right hemisphere of the cerebrum and the left hemisphere of the cerebrum, and a ratio between the right hemisphere of the cerebellum and the left hemisphere of the cerebellum.
    According to an advantageous embodiment of the invention the degree of symmetry comprises a ratio between the right hemisphere of the brain and the left hemisphere of the brain.
    According to an advantageous embodiment of the invention said brain energy metabolism indicator is determined from a brain energy metabolism indicator distribution.
    According to an advantageous embodiment of the invention said skull energy metabolism indicator is determined from a skull energy metabolism indicator distribution.
    In an embodiment the brain energy metabolism indicator is determined from a brain energy metabolism indicator distribution and the skull energy metabolism indicator is determined from a skull energy metabolism indicator distribution indicator.
    DK 2018 70707 A1
    According to an advantageous embodiment of the invention a segmentation on the brain energy metabolism indicator distribution is performed to obtain a brain energy metabolism indicator in one or more parts of the brain.
    According to an advantageous embodiment of the invention the method comprises a correction ratio for segmentation errors by relating at least one hemisphere of the skull to the contralateral hemisphere of the skull.
    According to an advantageous embodiment of the invention said correction for segmentation errors comprises a ratio between the right hemisphere of the skull and the left hemisphere of the skull.
    According to an advantageous embodiment of the invention the method further comprises the step of determining one or more further brain energy metabolism indicators of at least a part of the brain of the subject.
    As an example, said brain energy metabolism indicator and said one or more further brain energy metabolism indicators may be obtained from segmentation of a brain energy metabolism indicator distribution, e.g. in the form of one or more brain energy metabolism indicator images.
    According to an advantageous embodiment of the invention the method further comprises the step of determining one or more further skull energy metabolism indicators of at least a part of the skull of the subject.
    As an example, said skull energy metabolism indicator and said one or more further skull energy metabolism indicators may be obtained from segmentation of a skull energy metabolism indicator distribution, e.g. in the form of one or more skull energy metabolism indicator images.
    DK 2018 70707 A1
    According to an advantageous embodiment of the invention the method comprises a further step of relating said brain energy metabolism indicator or one of said further brain energy metabolism indicators to said skull energy metabolism indicator or one of said further skull energy metabolism indicators, wherein at least one of said further brain energy metabolism indicators or one of said further skull energy metabolism indicators is used.
    For example, one or more brain energy metabolism indicator(s) related to the cerebrum or part thereof and/or one or more brain energy metabolism indicator(s) related to the cerebellum or part thereof may be used.
    According to an advantageous embodiment of the invention the energy metabolism indicator is determined by a neuroimaging technique, such as a functional Magnetic Resonance Imaging (fMRI) based technique, a Computed Tomography (CT) Scan based technique, a Positron Emission Tomography (PET) based technique, a Magnetoencephalography (MEG) or Electroencephalography (EEG) based technique, a Single-Photon Emission Computed Tomography (SPECT) based technique, or an ultrasound (US) based technique.
    The above techniques are suitable for use in establishing the energy metabolism indicator, e.g. via an energy metabolism indicator distribution. An advantage of using an energy metabolism indicator distribution technique is that segmentation of the brain into subparts may be relatively easy.
    According to an advantageous embodiment of the invention the energy metabolism indicator is determined by a Positron Emission Tomography (PET) based technique.
    An advantage of the above embodiment may be that a relatively direct indication of the energy metabolism may be obtained, e.g. by using a Positron Emission Tomography (PET) based technique with a tracer, such as fludeoxyglucose (FDG).
    DK 2018 70707 A1
    According to an advantageous embodiment of the invention the energy metabolism indicator is determined by a magnetic resonance imaging (MRI) based technique, such as a functional Magnetic Resonance Imaging (fMRI) based technique.
    An advantage of the above embodiment may be that the energy metabolism may be determined from the indication provided by the MRI-based technique, such as fMRIbased technique.
    According to an advantageous embodiment of the invention a tracer, such as a radioactive tracer, is used in determination of the energy metabolism indicator.
    According to an advantageous embodiment of the invention the energy metabolism indicator is determined by a Positron Emission Tomography (PET) based technique with fludeoxyglucose (FDG) as a tracer.
    According to an advantageous embodiment of the invention the brain status indication parameter gives an indication of a presence of the brain disorder or not.
    According to an advantageous embodiment of the invention the brain status indication parameter gives an indication of a probability of presence of the brain disorder.
    According to an advantageous embodiment of the invention the brain status indication parameter gives an indication of a type of the brain disorder.
    According to an advantageous embodiment of the invention the brain disorder is selected from diaschisis; brain tumor, such as Glioma; Mild Cognitive Impairment (MCI); and Alzheimer's disease (AD).
    According to an advantageous embodiment of the invention the brain disorder comprises diaschisis.
    DK 2018 70707 A1
    The present invention may provide a very accurate brain status indication parameter with respect to diaschisis.
    According to an advantageous embodiment of the invention the brain comprises brain tumor, such as Glioma.
    According to an advantageous embodiment of the invention the brain disorder comprises Mild Cognitive Impairment (MCI).
    According to an advantageous embodiment of the invention the brain disorder comprises Alzheimer's disease (AD).
    According to an embodiment of the invention, the brain status indication parameter indicative comprises an expression of cerebral function. The cerebral function may appear that a ratio of the energy metabolism indicator of the cerebrum to the whole brain.
    According to an embodiment of the invention, the brain status indication parameter indicative comprises an expression of cerebral function, and the relation between said brain energy metabolism indicator to said skull energy metabolism indicator.
    According to an embodiment of the invention, the brain status indication parameter indicative comprises an expression of the degree of symmetry between at least a part of the right hemisphere of the brain and a corresponding part of the left hemisphere of the brain, and the relation between said brain energy metabolism indicator to said skull energy metabolism indicator.
    According to an embodiment of the invention, the brain status indication parameter indicative comprises an expression of cerebral function, an expression of the degree of symmetry between at least a part of the right hemisphere of the brain, and the relation
    DK 2018 70707 A1 between said brain energy metabolism indicator to said skull energy metabolism indicator.
    According to an advantageous embodiment of the invention the step of establishing the brain status indication parameter is carried out by a computer.
    The invention further relates to a brain status establishment system for establishing a brain status indication parameter indicative of a brain disorder, the system comprising:
    - a brain scanning device configured to
    - determine a brain energy metabolism indicator of at least a part of the brain of a subject,
    - determine a skull energy metabolism indicator of at least a part of the skull of said subject,
    - a computer device configured to establishing the brain status indication parameter by at least relating said brain energy metabolism indicator to said skull energy metabolism indicator.
    According to an embodiment of the invention, the brain status establishment system according to the invention or any of its embodiments is configured to operate in accordance with the method of establishing a brain status indication parameter according to the invention or any of its embodiments.
    The brain scanning device may a neuroimaging scanner, such as a functional Magnetic Resonance Imaging (fMRI) scanner, a Computed Tomography (CT) scanner, a Positron Emission Tomography (PET) scanner, a Magnetoencephalography (MEG) or Electroencephalography (EEG) scanner, a Single-Photon Emission Computed Tomography (SPECT) scanner, or an ultrasound (US) scanner, or any other scanner capable of measuring energy metabolism or an indicator thereof in the brain and skull.
    DK 2018 70707 A1
    The invention further relates to a computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the steps of the method of any of the preceding claims.
    The invention further relates to a method of treating a disease comprising performing the method according to any of the preceding claims before administering a drug or performing surgery.
    The invention further relates to a method of treating a disease comprising performing 10 the method according to any of the preceding claims before performing physical exercise.
    DK 2018 70707 A1
    FIGURES
    The invention will now be described with reference to the figures where
    Figure 1A illustrates a method of establishing a brain status indication parameter according to an embodiment of the invention,
    Figure 1B illustrates a method of establishing a brain status indication parameter according to an embodiment of the invention,
    Figure 2 illustrates a brain status establishment system according to an embodiment of the invention,
    Figure 3 illustrates a segmentation step according to an embodiment of the invention,
    Figures 4A-4B illustrate a trans-axial view of an energy metabolism indicator distribution image according to an embodiment of the invention,
    Figures 5A-5B illustrate a trans axial view of an energy metabolism indicator distribution image according to an embodiment of the invention,
    Figure 6A illustrates a coronal view of an energy metabolism indicator distribution image according to an embodiment of the invention, and
    Figure 6B illustrates a sagittal view of an energy metabolism indicator distribution image according to an embodiment of the invention.
    DK 2018 70707 A1
    DETAILED DESCRIPTION
    Referring to figure 1A, a method of establishing a brain status indication parameter BSI according to an embodiment of the invention is described.
    The brain status indication parameter BSI provides an indicative of a brain disorder, for example as a likelihood of a brain disorder being present, or as a likelihood of at least one or a group of brain disorders being present, or as a likelihood of one or more specific brain disorders being present.
    First, a brain energy metabolism indicator BEM of at least a part of the brain BR of a subject is determined DBI. This may be done by a variety of different techniques, which may provide a more or less direct indication of the energy metabolism.
    Then, a skull energy metabolism indicator SEM of at least a part of the skull SK of a subject is determined DSI. This may typically be done by a similar technique as for the brain energy metabolism indicator BEM. In embodiments, the steps of determining a brain energy metabolism indicator BEM and establishing the brain status indication parameter BSI are executed as a single step in the sense that the brain energy metabolism indicator and the skull energy metabolism indicator are obtained from the same image(s) and subsequently segmented into the brain energy metabolism indicator of at least a part of the brain and the skull energy metabolism indicator of at least a part of the skull. This is illustrated in more detail in figure 1B and figure 3.
    Then, the brain status indication parameter BSI established. This involves at least relating said brain energy metabolism indicator to said skull energy metabolism indicator. This relation may comprise e.g. comparing or forming a ratio between the brain energy metabolism indicator and the skull energy metabolism indicator. When using the ratio, this may be the ratio between the brain energy metabolism indicator and the skull energy metabolism indicator, or vice versa.
    DK 2018 70707 A1
    In some embodiments, this ratio forms part of a single number, or a set of numbers, for example in the sense that it is a factor and/or term in an equation forming basis for calculating the number(s).
    Turning to figure 1B, a method of establishing a brain status indication parameter BSI according to an embodiment of the invention is described.
    First, in a measuring step MES, one or more images of an energy metabolism indicator is recorded. The one or more images are then segmented in a segmentation step SEG. First, the brain part(s) of the image(s) are separated to form basis for determining DBI the brain energy metabolism indicator BEM. Then, the skull part(s) of the image(s) are separated to form basis for determining DSI the skull energy metabolism indicator SEM.
    It is noted that the segmentation step SEG may divide the brain into smaller segments, e.g. right and left hemisphere, cerebrum and cerebellum, or right and left hemispheres of both the cerebrum and cerebellum. Smaller segments may also be applied.
    In figure 1B, the brain energy metabolism indicator determining step DBI is shown before the skull energy metabolism indicator determining step DSI. However, in other embodiments, they may e.g. be performed in the opposite order, partly overlapping or concurrently executed.
    Then, a step of demining further parameter(s) DFP is executed according to figure 1B. In this step, one or more further parameters may be determined, e.g. from one or more distributions of energy metabolisms of the brain and/or skull forming basis for the brain energy metabolism indicator determination step DBI and/or the skull energy metabolism indicator determination step DSI. These one or more further parameter(s) may include parameters indicative of symmetry aspects of the brain or part thereof, of the cerebral function etc. In some embodiments, this step may be omitted.
    DK 2018 70707 A1
    Then, a diagnosis establishing step EDI follows. This step comprises at least relating said brain energy metabolism indicator BEM to said skull energy metabolism indicator SEM.
    In embodiments comprising a step of demining further parameter(s) DFP, the diagnosis establishing step EDI may further comprise calculations based also on such one or more further parameter(s).
    When the method also is directed to treatment of any brain disorder(s) resulting from the diagnosis establishing step EDI, the method comprises a treatment step TRT.
    This step may comprise administration of an effective amount of one or more active pharmaceutical ingredients (i.e. one or more drugs) and/or performing surgery.
    In some embodiments, the treatment step TRT may comprise performing physical exercises.
    Turning to figure 2, a brain status establishment system BSS for establishing a brain status indication parameter BSI indicative of a brain disorder. The system (BSS) comprises a brain scanning device BSD and a computer device CD.
    The brain scanning device BSD is configured to determine a brain energy metabolism indicator BEM of at least a part of the brain BR of a subject SUB, and to determine a skull energy metabolism indicator SEM of at least a part of the skull (SK) of said subject SUB. In figure 2, the brain scanning device BSD is illustrated as a positron emission tomography (PET) scanner but may be any other scanner capable of measuring energy metabolism or an indicator thereof in the brain and skull.
    The computer device CD is configured to establish the brain status indication parameter BSI by at least relating said brain energy metabolism indicator BEM to said skull energy metabolism indicator SEM. When further parameter(s) are determined,
    DK 2018 70707 A1 as described in relation to figure 1B, such further parameter(s) may form part of the basis for the establishing of the brain status indication parameter BSI by the computer device CD.
    Referring now to figure 3, the segmentation step SEG is illustrated according to an embodiment of the invention. First, one or more image(s) of an energy metabolism indicator is recorded, as e.g. illustrated in figure 2. As can be seen, the image(s), shown to the upper left, covers both the brain and the skull. Then, the image(s) is segmented, i.e. broken down into at least a skull part and a brain part. In figure 3, the brain part is further segmented into a left hemisphere of cerebrum LCE, a right hemisphere of cerebrum RCE, a left hemisphere of cerebellum LCB, and a right hemisphere of cerebellum RCB.
    In some further embodiments, the brain and/or the skull is further segmented, e.g. into rather small parts, such as a plurality of square fields. By utilizing computerized segmentation, such fields may be rather small, e.g. giving a resolution of tens or hundreds of fields for each direction in the image. It is noted that such deep segmentation is especially advantageous when advanced computerized processing is available, e.g. using machine learning-based methods, such as deep learning-based methods.
    Referring now to figures 4A-4B, 5A-5B, and 6A-6B, an energy metabolism indicator distribution image is illustrated according to an embodiment of the invention. The images shown in figures 4A-4B, 5A-5B, and 6A-6B, is recorded by a Positron Emission Tomography (PET) based technique with fludeoxyglucose (FDG) as a tracer. It is noted that other energy metabolism indicator recording techniques are also usable within the scope of the invention. Figures 4A-B, 5A-B, and 6A-B are images of the same subject having been diagnosed with brain cancer. The location of the brain tumor is more easily seen in figure 4A, in the upper center part of the image, corresponding to a location in the left part of the cerebrum.
    DK 2018 70707 A1
    Figures 4A and 4B show areas segmented in the cerebrum and the skull, respectively, where the energy metabolism indicator distribution exceeds a certain threshold. Figures 4A and 4B are identical, except that figure 4B shows segmentation only for the left hemisphere whereas figure 4A shows this for both left and right hemispheres. Also, as it can be seen from figure 4A in particular, the corresponding emphasized areas are partitioned into left and right hemispheres, both for the skull and the cerebrum.
    Figures 5A and 5B show views somewhat similar to figures 4A and 4B, but in a transaxial plane through the cerebellum, thus showing segmented areas for the cerebellum and the skull in figure 5B, but only for the skull in figure 5A.
    Figure 6A shows a coronal view of the cerebrum and the skull, with only the left hemisphere being segmented.
    Figure 6B shows a sagittal view of the skull and the cerebrum and the cerebellum, with segmented regions.
    These images illustrate the complexity of performing a subjective analysis based on a perceived normality or abnormality, even when comparing with another image representing a healthy subject. In contrast, the present invention provides an objective, reliable and reproducible output.
    DK 2018 70707 A1
    EXAMPLES
    FDG-PET images of 47 subjects (37 patients and 10 control subjects) were obtained.
    From these images, total energy metabolism values were calculated. These values are 5 given in tables 1-2.
    Table 1. Total energy metabolism values after segmentation.
    SubjectNo.DiagnosisSk_WhSk_LSk_RBr_WhCe_Wh1NL290141149230720852NL384195189425639203NL383192190308528094NL19088102225020655NL326164162351531976NL378181197608356657NL417207210449340758NL396205191457040859NL3471771713860349710NL3381701684614424811AD2221141082496228212AD19699973345306213AD195951003411309214AD17986923369304015AD14875732068187716AD2511301214495410617AD2391171223019274218AD18491922372214919AD2301131173479317120AD3181591593836348021AD186959136443334
    DK 2018 70707 A1
    22AD17186862529229823AD2821391433274295224AD2961501461983176325AD2601321293328300626MCI18992972752248127MCI2261191074375403328MCI2591301294623421029MCI2991521472012179730MCI3531731804464410431MCI2271111163846352332MCI2121121003194296933MCI2201121093505318734Glioma197101962595235835Glioma2591301282436224736Glioma2681311373079282337Glioma3661811854091376338Glioma2181091091853172139Glioma5082402682878258540Glioma2041031012254202041Glioma16586791981184042Glioma2761301462844254943Glioma3061551511993181844Glioma3161601562681241345Glioma5702952753952353646Glioma4842292553013274547Glioma30615614925222282
    Table 1. Total energy metabolism for the brain or skull part in question. Sk_Wh denotes whole skull, Sk_L denotes left hemisphere of skull, Sk_R detotes right hemisphere of skull, Br_Wh denotes whole brain, Ce_Wh denotes whole Cerebrum.
    DK 2018 70707 A1
    NL signifies a control subject. AD signifies a subject diagnosed with Alzheimer’s
    Disease. MCI signifies Mild Cognitive Impairment.
    Table 2. Total energy metabolism values after segmentation.
    SubjectNo.DiagnosisCe_LCe_RCb_WhCb_LCb_R1NL103010552221071152NL196619543351571793NL144313662761391374NL901116418590955NL163515623191821376NL280928564182191997NL201320624192112088NL213919474842302549NL1792170636318018310NL2155209336619017611AD110611762141249012AD1490157228313814513AD1471162231815916014AD1730131032915517415AD78610911911286216AD1913219338821117717AD1477126527716011718AD943120622412410019AD1775139730816814020AD1538194235620115621AD1668166531117713422AD132297623112810323AD13371615323163160
    DK 2018 70707 A1
    24AD90286122010911125AD1351165532118413726MCI1324115727113813327MCI2025200734216617628MCI2095211541321719629MCI9198792149711830MCI2034206936019416631MCI1754177032315217132MCI1439153022511910533MCI1631155631920211634Glioma1100125823711412435Glioma12251023189969336Glioma1328149525612313337Glioma1524223932820012838Glioma6671054132844839Glioma1130145429315214140Glioma67513442341548041Glioma1166674141548742Glioma152510252948121343Glioma9508681751106644Glioma106613472688818145Glioma1375216141629012646Glioma101517312681808747Glioma11581124240115125
    Table 2. Total energy metabolism for the brain or skull part in question. Ce_L denotes left hemisphere of Cerebrum, Ce_R denotes right hemisphere of Cerebrum, Cb_Wh denotes whole Cerebellum, Cb_L denotes left hemisphere of Cerebellum, Cb_R denotes right hemisphere of Cerebellum. NL. Signifies a control subject. AD signifies 5 a subject diagnosed with Alzheimer’s Disease. MCI signifies Mild Cognitive Impairment.
    DK 2018 70707 A1
    These values may possibly be corrected using comparison of energy metabolism in the left and right hemispheres of the skull.
    Further values are calculated based on the measured energy metabolism values or corrected values obtained therefrom. The following equations have been written and standardized so that the results, in normal controls, equal to one.
    Cerebral Function (CF) = KCF
    Cerebral Symmetry I (CeSI) = KCeSI CeL — CeR
    In—7---Cerebellar Symmetry I (CbSI) = KcbsI
    CeWh
    Brwh . CbL-CbR ln—ch---cuWh
    Cerebral Symmetry II (CeSII) = KCeSII
    Min(CeL, CeR~)
    Max(CeL, CeR~)
    Min(CbL,CbR)
    Cerebellar Symmetry II (CbSII) = Kcbsn Max(-Cb cb
    Skull — cerebellar ratio (SV I) = KSVI
    Skwh
    Cbwh
    Skull — cerebral ratio (SVII) = KSVII
    Skwb
    CeWh
    Here, Min(X, T) is the minimum value of X and Y, and Max(X, T) is the maximum value of X and Y.
    Constants (K) in each equation are as follows:
    KCeSI = KcbSI = -0.33
    KCeSII = 1.08
    KCbSII = Ksvi = 1.11
    Kcf = 1.12
    Ksvii = 10
    These above constants are set to give unity values (i.e. values of 1) for healthy control subjects.
    DK 2018 70707 A1
    The above defined values (CF, CeS I, CbS I, CeS II, CbS II, SV I, SV II) are calculated to see if a value below or above 1 was obtained. Simplified values TCF, TCeS I, TCbS I, TCeS II, TCbS II, TSV I, and TSV II were then obtained as 1 (binary true) when the 5 corresponding equation gave a result above 1, and 0 (binary false) when the corresponding equation gave a result not above 1.
    Then, a brain function score was defined as follows:
    BFS = 4CF + 4Max(CeSI, CbSI) + 4Max(CeSII,SVI) + Max(CbSII,SVII) - 3
    The obtained values are listed in table 3.
    No.DiagnosisBFS1NL102NL93NL104NL105NL106NL97NL108NL99NL1010NL1011AD512AD613AD614AD615AD116AD117AD118AD1
    DK 2018 70707 A1
    19AD120AD121AD522AD123AD624AD625AD126MCI627MCI528MCI1029MCI1030MCI931MCI1032MCI1033MCI934Glioma135Glioma1036Glioma1037Glioma538Glioma639Glioma640Glioma241Glioma542Glioma643Glioma1044Glioma645Glioma646Glioma647Glioma10
    Table 3. Brain function score (BFS) for subjects 1-47 are listed.
    DK 2018 70707 A1
    Theoretically, the above function may give values between -3 and 10; however, in a living brain, all the numbers in Table 3 can hardly equal to zero. For example, a clinically impaired brain should the value of about 1, whereas a clinically healthy brain 5 gets the maximum values. Minus numbers are left for brain death, comatose state, severe encephalopathies, or very severely impaired brain conditions.
    Table 3 shows BFS values for each patient. One may easily distinguish the difference between disease groups. Results show the status of the brain with only one number 10 which makes it easy to understand how good the patient's condition is.
    A more advanced approach is obtained by using the following equation:
    ψ„ = (KlnCeF)'“(K„n 20^')Α“(Κ(„η 20c“')i“'(KiVn CeSII)’ (K„n CbSl/)Λν”(K„n SW)”(K„IIn svn)lM
    For the purpose of this example, the above equation is executed as Vh-^6 and i/jext, using the constants defined in table 4.
    Table 4. Constants
    ConstantsVhΨ2 V>4 V'öΨ extCoefficientsKi1111111Ku2222222Km2222222K[v 0.960.960.960.960.960.960.96Kv 1111111Kvi0.90.90.90.90.90.90.9Kyii1111111Expo*i35003500-800-8000-50000Λί105026020190
    DK 2018 70707 A1
    Λϋ0840-250-350-500/- iv1500150015001500000λν 1001002002004000-2000/vi-150200001500014000/vH-100200-600-101500010000
    Table 4. Constants including coefficients and exponents for use in calculation of ipn
    It is noted that the above constants listed in table 4, i.e. K( vii and vii are constants in nth equation. A set of equations may be written in this form with altered constants differentiating various diseases.
    Using this, ψ-^-ψβ andψext are calculated. Typically, either very high numbers above 100000 or numbers very close to zero are obtained. For the purpose of the present example, a threshold value of 100000 is used to signify “large numbers”, whereas numbers below 10000 signifies a “small number”. Intermediate numbers signify uncertainty with respect to the result, whereas extreme numbers (very high, very low) signifies a higher degree of certainty.
    Finally, the below list of questions was used to determine an indication of the diagnosis:
    1) Is ψ6 a large number If yes, the brain status indication parameter indicates glioma.
    2) If question 1) is no, is ψ5 a large number, and is i/jext a small number If yes, the brain status indication parameter indicates glioma.
    3) If question 2) is no, are all of 1/^, ip2, and i/>3 large numbers If yes, the brain status indication parameter indicates normal condition.
    4) If question 3) is no, is i/>4 a small number and ψ5 a large number If yes, the brain status indication parameter indicates glioma.
    5) If question 4) is no, is at least five of i/^, ip2, ^3^4, V^s, ^6, and ipext large numbers If yes, the brain status indication parameter indicates glioma.
    DK 2018 70707 A1
    6) If question 5) is no, is ipext a large number, and is BFS at least 8 If yes, the brain status indication parameter indicates MCI.
    7) If question 6) is no, the brain status indication parameter indicates Alzheimer’s disease.
    Evaluating the above described method, the following results were obtained:
    First, it was evaluated how accurate the above described method was when differentiating diseased from healthy, the results are indicated in table 5.
    Disease +Disease -TotalsTest +36036Test -11011Totals371047
    Table 5. Here, ’’Test +’’ indicates a positive result for a brain condition from the brain status indication parameter, “Test indicates a negative result, “Disease +’’ indicates subject having a brain disorder, and “Disease indicates subject within brain disorder.
    As can be seen from table 5, only 1 out of 47 was wrongly indicated to have a disease by the brain status indication parameter.
    When differentiating Alzheimer's disease (AD) from MCI, the results are indicated in table 6.
    ADMCITotalsPredicted AD15217Predicted MCI055Totals15722
    Table 6. ”AD” indicates subjects with AD. “MCI” indicates subjects with MCI.
    From table 6, the following was concluded:
    DK 2018 70707 A1
    Sensitivity = 100%
    Specificity = 71.4%
    Positive predictive values (PPV) = 88.2%
    Negative predictive values (NPV) = 100%
    Accuracy = 90.9%
    When differentiating AD from Glioma, the results are indicated in table 7.
    ADGliomaTotalsPredicted AD15116Predicted Glioma01313Totals151429
    Table 7
    From table 7, the following was concluded:
    Sensitivity = 100%
    Specificity = 92.8%
    PPV = 93.7%
    NPV = 100%
    Accuracy = 96.5%
    When differentiating Glioma from MCI, the results are indicated in table 8.
    GliomaMCITotalsPredicted Glioma13013Predicted MCI055Totals13518
    Table 8.
    From table 8, the following was concluded:
    Sensitivity = 100%
    Specificity = 100%
    DK 2018 70707 A1
    PPV = 100%
    NPV = 100%
    Accuracy = 100%
    A total summation of results with respect to accuracy are indicated in table 9.
    DiseaseNLADMCIGliomaTotalsPredictedNL1001011AD0152118MCI00505Glioma0001313Totals101581447
    Table 9. ”NL” indicates a control subject without a brain disorder.
    As can be seen from table 9, the overall accuracy obtained was 91.48%.
    Therefore, it was concluded that the presently described the brain status indication parameter according to the present invention results in a very accurate indication of brain disorders, both with respect to the presence of a brain disorder and with respect to the specific brain disorder.
    DK 2018 70707 A1
    FIGURE REFERENCES
    BR. Brain
    SK. Skull
    LCE. Left hemisphere of cerebrum
    RCE. Right hemisphere of cerebrum
    LCB. Left hemisphere of cerebellum
    RCB. Right hemisphere of cerebellum
    BSI. Brain status indication parameter
    BEM. Brain energy metabolism indicator
    SEM. Skull energy metabolism indicator
    SEG. Segmentation step
    DBI. Determining brain energy metabolism indicator step
    DSI. Determining skull energy metabolism indicator step
    EBI. Establish brain status indication parameter
    MES. Measuring step
    DFP. Demining further parameter(s) step
    EDI. Establish diagnosis step
    TRT. Treatment step
    BSD. Brain scanning device
    SUB. Subject
    CD. Computer device
    BSS. Brain status establishment system
    权利要求:
    Claims (46)
    [1] 1. A method of establishing a brain status indication parameter indicative of a brain disorder, the method comprising the steps:
    - determining a brain energy metabolism indicator of at least a part of the brain of a subject,
    - determining a skull energy metabolism indicator of at least a part of the skull of said subject,
    - establishing the brain status indication parameter by at least relating said brain energy metabolism indicator to said skull energy metabolism indicator.
    [2] 2. The method according to claim 1, wherein said relating involves calculating a ratio between the brain energy metabolism indicator and the skull energy metabolism indicator, or vice versa.
    [3] 3. The method according to claim 1 or 2, wherein said relating comprises calculating a ratio between the brain energy metabolism indicator and the skull energy metabolism indicator.
    [4] 4. The method according to any of claims 1-3, wherein said part of the brain comprises at least the left hemisphere of cerebellum.
    [5] 5. The method according to any of claims 1-5, wherein said part of the brain comprises at least the right hemisphere of cerebellum.
    [6] 6. The method according to any of claims 1-5, wherein said part of the brain comprises at least the left hemisphere of cerebrum.
    DK 2018 70707 A1
    [7] 7. The method according to any of claims 1-6, wherein said part of the brain comprises at least the right hemisphere of cerebrum.
    [8] 8. The method according to any of claims 1-7, wherein the brain energy metabolism indicator of the brain of the subject is determined.
    [9] 9. The method according to any of claims 1-8, wherein the part of the brain comprises at least the 50 percent most active nerve fibers.
    [10] 10. The method according to any of claims 1-9, wherein the method comprises establishing a degree of symmetry between at least a part of the right hemisphere of the brain and a corresponding part of the left hemisphere of the brain.
    [11] 11. The method according to any of claims 1-10, wherein the degree of symmetry comprises a ratio between at least a part of the right hemisphere of the brain and a corresponding part of the left hemisphere of the brain.
    [12] 12. The method according to any of claims 1-11, wherein the degree of symmetry comprises a ratio between the right hemisphere of the cerebrum and the left hemisphere of the cerebrum.
    [13] 13. The method according to any of claims 1-12, wherein the degree of symmetry comprises a ratio between the right hemisphere of the cerebellum and the left hemisphere of the cerebellum.
    [14] 14. The method according to any of claims 1-13, wherein the degree of symmetry comprises a ratio between the right hemisphere of the cerebrum and the left hemisphere of the cerebrum, and a ratio between the right hemisphere of the cerebellum and the left hemisphere of the cerebellum.
    DK 2018 70707 A1
    [15] 15. The method according to any of claims 1-14, wherein the degree of symmetry comprises a ratio between the right hemisphere of the brain and the left hemisphere of the brain.
    [16] 16. The method according to any of claims 1-15, wherein said brain energy metabolism indicator is determined from a brain energy metabolism indicator distribution.
    [17] 17. The method according to any of claims 1-16, wherein said skull energy metabolism indicator is determined from a skull energy metabolism indicator distribution.
    [18] 18. The method according to any of claims 1-17, wherein a segmentation on the brain energy metabolism indicator distribution is performed to obtain a brain energy metabolism indicator in one or more parts of the brain.
    [19] 19. The method according to any of claims 1-18, wherein the method comprises a correction ratio for segmentation errors by relating at least one hemisphere of the skull to the contralateral hemisphere of the skull.
    [20] 20. The method according to any of claims 1-19, wherein said correction for segmentation errors comprises a ratio between the right hemisphere of the skull and the left hemisphere of the skull.
    [21] 21. The method according to any of claims 1-20, wherein the method further comprises the step of determining one or more further brain energy metabolism indicators of at least a part of the brain of the subject.
    [22] 22. The method according to any of claims 1-21, wherein the method further comprises the step of determining one or more further skull energy metabolism indicators of at least a part of the skull of the subject.
    DK 2018 70707 A1
    [23] 23. The method according to any of claims 1-22, wherein the method comprises a further step of relating said brain energy metabolism indicator or one of said further brain energy metabolism indicators to said skull energy metabolism indicator or one of said further skull energy metabolism indicators, wherein at least one of said further brain energy metabolism indicators or one of said further skull energy metabolism indicators is used.
    [24] 24. The method according to any of claims 1-23, wherein the energy metabolism indicator is determined by a neuroimaging technique, such as a functional Magnetic Resonance Imaging (fMRI) based technique, a Computed Tomography (CT) Scan based technique, a Positron Emission Tomography (PET) based technique, a Magnetoencephalography (MEG) or Electroencephalography (EEG) based technique, a Single-photon emission computed tomography (SPECT) based technique, or an ultrasound-based technique.
    [25] 25. The method according to any of claims 1-24, wherein the energy metabolism indicator is determined by a Positron Emission Tomography (PET) based technique.
    [26] 26. The method according to any of claims 1-24, wherein the energy metabolism indicator is determined by a magnetic resonance imaging (MRI) based technique, such as a functional Magnetic Resonance Imaging (fMRI) based technique.
    [27] 27. The method according to any of claims 1-26, wherein a tracer, such as a radioactive tracer, is used in determination of the energy metabolism indicator.
    [28] 28. The method according to any of claims 1-27, wherein the energy metabolism indicator is determined by a Positron Emission Tomography (PET) based technique with fludeoxyglucose (FDG) as a tracer.
    [29] 29. The method according to any of claims 1-28, wherein the brain status indication parameter gives an indication of a presence of the brain disorder or not.
    DK 2018 70707 A1
    [30] 30. The method according to any of claims 1-29, wherein the brain status indication parameter gives an indication of a probability of presence of the brain disorder.
    [31] 31. The method according to any of claims 1-30, wherein the brain status indication parameter gives an indication of a type of the brain disorder.
    [32] 32. The method according to any of claims 1-31, wherein the brain disorder is selected from diaschisis; brain tumor, such as Glioma; Mild Cognitive Impairment (MCI); and Alzheimer's disease (AD).
    [33] 33. The method according to any of claims 1-32, wherein the brain disorder comprises diaschisis.
    [34] 34. The method according to any of claims 1-33, wherein the brain disorder comprises brain tumor, such as Glioma.
    [35] 35. The method according to any of claims 1-34, wherein the brain disorder comprises Mild Cognitive Impairment (MCI).
    [36] 36. The method according to any of claims 1-35, wherein the brain disorder comprises Alzheimer's disease (AD).
    [37] 37. The method according to any of claims 1-36, wherein the brain status indication parameter indicative comprises an expression of cerebral function. The cerebral function may appear that a ratio of the energy metabolism indicator of the cerebrum to the whole brain.
    [38] 38. The method according to any of claims 1-37, wherein the brain status indication parameter indicative comprises an expression of cerebral function, and the relation
    DK 2018 70707 A1 between said brain energy metabolism indicator to said skull energy metabolism indicator.
    [39] 39. The method according to any of claims 1-38, wherein the brain status indication parameter indicative comprises an expression of the degree of symmetry between at least a part of the right hemisphere of the brain and a corresponding part of the left hemisphere of the brain, and the relation between said brain energy metabolism indicator to said skull energy metabolism indicator.
    [40] 40. The method according to any of claims 1-39, wherein the brain status indication parameter indicative comprises an expression of cerebral function, an expression of the degree of symmetry between at least a part of the right hemisphere of the brain, and the relation between said brain energy metabolism indicator to said skull energy metabolism indicator.
    [41] 41. The method according to any of claims 1-36, wherein the step of establishing the brain status indication parameter is carried out by a computer.
    [42] 42. A brain status establishment system (BSS) for establishing a brain status indication parameter (BSI) indicative of a brain disorder, the system (BSS) comprising:
    - a brain scanning device (BSD) configured to
    - determine a brain energy metabolism indicator (BEM) of at least a part of the brain (BR) of a subject (SUB),
    - determine a skull energy metabolism indicator (SEM) of at least a part of the skull (SK) of said subject (SUB),
    - a computer device (CD) configured to establishing the brain status indication parameter (BSI) by at least relating said brain energy metabolism indicator (BEM) to said skull energy metabolism indicator (SEM).
    DK 2018 70707 A1
    [43] 43. The brain status establishment system (BSS) according to claim 42, wherein the brain status establishment system (BSS) is configured to operate in accordance with the method of any of claims 1-41.
    5
    [44] 44. A computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the steps of the method of any of claims 1-41.
    [45] 45. A method of treating a disease comprising performing the method according to 10 any of claims 1-41 before administering a drug or performing surgery.
    [46] 46. A method of treating a disease comprising performing the method according to any of claims 1-41before performing physical exercise.
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    同族专利:
    公开号 | 公开日
    DK180231B1|2020-08-28|
    EP3873339A1|2021-09-08|
    US20210393224A1|2021-12-23|
    CN113226168A|2021-08-06|
    CA3118046A1|2020-05-07|
    WO2020088730A1|2020-05-07|
    JP2022509347A|2022-01-20|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    US20050215889A1|2004-03-29|2005-09-29|The Board of Supervisory of Louisiana State University|Methods for using pet measured metabolism to determine cognitive impairment|
    US8379957B2|2006-01-12|2013-02-19|Siemens Corporation|System and method for segmentation of anatomical structures in MRI volumes using graph cuts|
    WO2008107809A2|2007-03-06|2008-09-12|Koninklijke Philips Electronics, N.V.|Automated diagnosis and alignment supplemented with pet/mr flow estimation|
    法律状态:
    2020-06-08| PAT| Application published|Effective date: 20200501 |
    2020-08-28| PME| Patent granted|Effective date: 20200828 |
    优先权:
    申请号 | 申请日 | 专利标题
    DKPA201870707A|DK180231B1|2018-10-31|2018-10-31|Method of establishing a brain status indication parameter and system therefor|DKPA201870707A| DK180231B1|2018-10-31|2018-10-31|Method of establishing a brain status indication parameter and system therefor|
    JP2021547641A| JP2022509347A|2018-10-31|2019-10-30|A method for establishing brain condition indicator parameters and a system for establishing brain condition indicator parameters|
    US17/289,610| US20210393224A1|2018-10-31|2019-10-30|Method of establishing a brain status indication parameter and system therefor|
    CN201980081179.9A| CN113226168A|2018-10-31|2019-10-30|Method and system for establishing brain state index|
    EP19797560.0A| EP3873339A1|2018-10-31|2019-10-30|Method of establishing a brain status indication parameter and system therefor|
    CA3118046A| CA3118046A1|2018-10-31|2019-10-30|Method of establishing a brain status indication parameter and system therefor|
    PCT/DK2019/050327| WO2020088730A1|2018-10-31|2019-10-30|Method of establishing a brain status indication parameter and system therefor|
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