WO2018064715A1 - Procédé pour la prédiction ou le diagnostic d'une détérioration cognitive - Google Patents

Procédé pour la prédiction ou le diagnostic d'une détérioration cognitive Download PDF

Info

Publication number
WO2018064715A1
WO2018064715A1 PCT/AU2017/051074 AU2017051074W WO2018064715A1 WO 2018064715 A1 WO2018064715 A1 WO 2018064715A1 AU 2017051074 W AU2017051074 W AU 2017051074W WO 2018064715 A1 WO2018064715 A1 WO 2018064715A1
Authority
WO
WIPO (PCT)
Prior art keywords
qsm
magnetic susceptibility
cognitive
measure
patient
Prior art date
Application number
PCT/AU2017/051074
Other languages
English (en)
Inventor
Scott Jonathan AYTON
Ashley Ian Bush
Amir FAZIOLLHI
Olivier Salvado
Original Assignee
Crc For Mental Health Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from AU2016904000A external-priority patent/AU2016904000A0/en
Application filed by Crc For Mental Health Ltd filed Critical Crc For Mental Health Ltd
Publication of WO2018064715A1 publication Critical patent/WO2018064715A1/fr

Links

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves 
    • A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves  involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0033—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room
    • A61B5/004—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room adapted for image acquisition of a particular organ or body part
    • A61B5/0042—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room adapted for image acquisition of a particular organ or body part for the brain
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/40—Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4058—Detecting, measuring or recording for evaluating the nervous system for evaluating the central nervous system
    • A61B5/4064—Evaluating the brain
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/70—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mental therapies, e.g. psychological therapy or autogenous training
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2576/00—Medical imaging apparatus involving image processing or analysis
    • A61B2576/02—Medical imaging apparatus involving image processing or analysis specially adapted for a particular organ or body part
    • A61B2576/026—Medical imaging apparatus involving image processing or analysis specially adapted for a particular organ or body part for the brain

Definitions

  • the present invention relates to methods for predicting progression of cognitive deterioration relating to the areas of dementias, cognitive disorders and/or affective disorders and/or behavioural dysfunction, Alzheimer's Disease and related dementias in patients with amyloid deposition in the brain by determining a measure of magnetic susceptibility and/or transverse relaxation in brain tissue.
  • the invention is also applicable to monitoring progression of cognitive deterioration and stratifying an individual into one or more classes depending on the diagnosis or prognosis of the cognitive deterioration.
  • AD Alzheimer's disease
  • ⁇ amyloid ⁇
  • AD brain pathology starts developing approximately two decades prior to the onset of cognitive symptoms. Consequently, anti-AD therapies may have the best chance of success when given in this preclinical period.
  • biomarkers that predict cognitive deterioration early.
  • Amyloid PET imaging is the most advanced biomarker of geriatric cognitive deterioration.
  • High ⁇ burden ( ⁇ +) identified by PiB, flutemetamol, or florbetapir radioligands, predicts cognitive decline with an average effect size (difference between slopes) of ⁇ 0.5 on memory composite scores in cognitively normal (CN) subjects over 3+ years.
  • ⁇ imaging is a sensitive predictor (98%) of cognitive decline but studies have shown repeatedly a large prevalence ( ⁇ 20-30%) of cognitive unimpaired people over age 60 with already high ⁇ burden in the brain. It is now clear that other factors are necessary to predict and monitor cognitive decline toward Alzheimer's dementia since ⁇ alone cannot monitor the rate of decline.
  • a test which can provide assistance to clinicians in reaching an early stage prognosis prior to the portrayal of detectable clinical indicators and which would obviate the need for actual confirmatory brain imaging tests would be useful.
  • therapies for neurological disorders undergoing clinical trials there is a social and economic imperative to identify biomarkers and parameters that can detect features of the disease in at-risk individuals in the earliest possible stage, so therapies can be administered at a time when the disease burden is mild and it may prevent or delay functional and irreversible cognitive loss.
  • Measuring cognitive deterioration before the onset of AD may enable early treatment with drugs that would delay disease progression.
  • a method for predicting or diagnosing cognitive deterioration in a patient with amyloid deposition in the brain comprising determining a measure of magnetic susceptibility and/or transverse relaxation in brain tissue for the patient wherein the measure of magnetic susceptibility and/or transverse relaxation is an indication of cognitive deterioration.
  • the measure of magnetic susceptibility and/or transverse relaxation can be performed using any method which can measure magnetic properties of tissues. These may include QSM, T2 * T2, or NMR frequency.
  • the method used to measure magnetic susceptibility is QSM.
  • the method to measure transverse relaxation is T2 * Applicants have demonstrated a QSM value as an alternative/adjunct prognostic for cognitive deterioration. They show that the QSM value in patients with amyloid deposition in the brain can predict the trajectory and rate of cognitive decline in these patients.
  • QSM is a measure of magnetic susceptibility
  • any method available to the skilled addressee for measuring magnetic susceptibility may be used.
  • T2 * which measure the transverse relaxation speed of molecules may be used since molecules such as iron which may be present in tissues will also affect the transverse relaxation of tissue.
  • relaxation maps of tissue such as those obtained from T2 * T2, T1 , or T2' maps may also provide an indication of the presence of molecules such as iron in tissues of patients with amyloid deposition thereby enabling a prediction of cognitive deterioration.
  • the changes in magnetic susceptibility preferably the QSM values can additionally be used in assessing for any changes in cognitive deterioration of a patient. Accordingly, in the monitoring of the magnetic susceptibility or preferably QSM values, it is possible to monitor for the presence of cognitive deterioration over a period of time, or to track cognitive deterioration progression in a patient.
  • a method for monitoring progression of cognitive deterioration in a patient with amyloid deposition in the brain comprising determining a first measure of magnetic susceptibility and/or transverse relaxation from in in the patient at a first time point;
  • the changes in the level of magnetic susceptibility or preferably QSM values and/or transverse relaxation in a patient with amyloid deposition in the brain can also be used to stratify a patient (i.e., sorting a patient with cognitive deterioration into different classes of the condition).
  • a method for stratifying a patient with amyloid deposition in the brain for cognitive deterioration comprising determining a measure of magnetic susceptibility and/or transverse relaxation for the patient;
  • Figure 1 shows the Relationship between QSM and longitudinal cognitive outcomes in ⁇ + subjects. Visual representation of the effect of baseline QSM on longitudinal composites of cognitive performance. For display purposes, ⁇ + subjects were designated to a low or high QSM group, based on the QSM value (0.0064 ppb) that optimally separated HC from diseased participants. DETAILED DESCRIPTION OF THE INVENTION
  • Predicting a rate of cognitive deterioration before the onset of AD may enable early treatment intervention to delay disease progression.
  • Anti-AD therapies given in the pre-clinical period will have the best chance of success.
  • dementia or AD may not fully develop, but the patient displays symptoms of Mild Cognitive Impairment (MCI) or are cognitively normal elders who may eventually experience cognitive deterioration.
  • MCI Mild Cognitive Impairment
  • Monitoring progression and predicting or diagnosing a trajectory of cognitive deterioration will be imperative for managing the cognitive deterioration over time.
  • a method for predicting or diagnosing cognitive deterioration in a patient with amyloid deposition in the brain comprising determining a measure of magnetic susceptibility and/or transverse relaxation in brain tissue for the patient wherein the measure of magnetic susceptibility and/or transverse relaxation is an indication of cognitive deterioration.
  • ⁇ or amyloid alone or any measure of magnetic susceptibility or transverse relaxation alone has been shown to be insufficient as a marker for cognitive deterioration since there exist a large number of cognitively unimpaired people with high ⁇ levels in the brain. Approximately 30% of ⁇ carrying subjects do not have objective cognitive impairment, suggesting that amyloid is not sufficient to precipitate dementia, however amyloid acts in concert with other pathogenic factors to drive disease progression.
  • measures of magnetic susceptibility such as QSM and/or transverse relaxation may also predict the trajectory of cognitive decline in ⁇ carrying subjects depending on a measure of magnetic susceptibility or preferably QSM value and/or transverse relaxation determined.
  • the present invention may also include other ways of measuring magnetic susceptibility and/or transverse relaxation which is one measure of the magnetic properties of a material that may be contributed by iron present in the tissues.
  • Other forms of measure including T2, T2 * or pattern of NMR frequencies can also be used.
  • Magnetic susceptibility is a measure of the magnetic properties of a material including tissue.
  • the susceptibility indicates whether a material is attracted into or repelled out of a magnetic field. It can also be a measure the degree of magnetization of a material in response to an applied magnetic field. Hence, it often reflects iron levels in tissue where iron is the most abundant magnetic material in the tissue.
  • Measuring magnetic susceptibility can be conducted by several methods available to the skilled addressee aiming to measure the magnetic properties of tissue. Methods such as QSM and MRI are the most common methods used. Preferably, QSM is used as it is a superior method for measuring magnetic susceptibility.
  • Transverse relaxation T2 or T2 *
  • T2 * Transverse relaxation
  • the present invention relates to assessing, predicting or diagnosing cognitive deterioration as measured by magnetic susceptibility or preferably QSM and/or transverse relaxation as an indicator of the rate of decline in cognitive capacity.
  • a patient's cognitive capacity declines changes occur which give rise to a variety of symptoms associated with aging, such as forgetfulness, decreased ability to maintain focus, and decreased problem solving capability. Symptoms oftentimes progress into more serious conditions, such as dementia and depression, or even Alzheimer's disease.
  • cognitive deterioration includes mild cognitive impairment (MCI), MCI conversion to Alzheimer's Disease (AD), and AD.
  • MCI mild cognitive impairment
  • AD Alzheimer's Disease
  • the invention also relates broadly to the areas of dementias, cognitive disorders and/or affective disorders and/or behavioural dysfunction, Alzheimer's Disease and related dementias associated with a decline in cognitive function.
  • cognitive deterioration may be used interchangeably with “cognitive decline”.
  • Mild cognitive impairment is an intermediate stage between the expected cognitive decline of normal aging and the more serious decline of dementia. It can involve problems with memory, language, thinking and judgment that are greater than normal age-related changes. Mild cognitive impairment causes cognitive changes that are serious enough to be noticed by the individuals experiencing them or to other people, but the changes are not severe enough to interfere with daily life or independent function. However, underlying what appears to be MCI, there may be a growing incidence of cognitive deterioration that does not manifest until it is too late. Early detection allows for intervention therapies.
  • Alzheimer's Disease and related dementias generally requires an evaluation of medical history and physical examination to determine the extent of cognitive function including neurological, neuropsychological and psychiatric assessment including memory and/or psychological tests, assessment of language impairment and/or other focal cognitive deficits (such as apraxia, acalculia and left-right disorientation), assessment of impaired judgment and general problem-solving difficulties, assessment of personality changes ranging from progressive passivity to marked agitation, as well as various biological, radiological and electrophysiological tests, such as for instance measuring brain volume or activity measurements derived from neuroimaging modalities such as magnetic resonance imaging (MRI) or positron emission tomography (PET) of relevant brain regions.
  • MRI magnetic resonance imaging
  • PET positron emission tomography
  • the cognitive deterioration is determined by Pre-clinical Alzheimer's Cognitive Composite (PACC: MMSE, LMII, Digit Symbol &CVLT-II LDFR), Global Cognition (C10pt: LMII, CVLTFP, Clock), Disease Progression (C2CR: CDRsb and MMSE), or Verbal Episodic Memory (C3VerEM: LMII, CVLTFP, CLVTLDFR).
  • PACC Pre-clinical Alzheimer's Cognitive Composite
  • LMII Digit Symbol &CVLT-II LDFR
  • C10pt LMII, CVLTFP, Clock
  • C2CR CDRsb and MMSE
  • C3VerEM LMII, CVLTFP, CLVTLDFR
  • a risk of cognitive deterioration may be assessed relative to a cognitively normal (CN) patient which will provide a reference level.
  • Patients who are at risk of cognitive deterioration and/or Alzheimer's Disease include those with family histories, genetic vulnerability and deficiency alleles. They may be vulnerable and carry genes which predispose them to a more rapid cognitive deterioration leading to dementia and AD. Being able to determine an onset of rapid decline will enable better management of the cognitive deterioration.
  • CN patient means a subject which has no significant cognitive impairment or impaired activities of daily living. Patients that are suspected of, or are at risk of cognitive deterioration may be compared against a CN patient. This includes patients that are cognitively normal but show changed levels of a marker indicative of a neurological disease such as amyloid loading in the brain (preferably determined by PET imaging). The characteristics of a CN patient may assist in providing a reference level or reference value to which deterioration from normal can be determined.
  • Applicants have demonstrated that a measure of magnetic susceptibility or preferably QSM in patients with amyloid deposition in the brain predicts a propensity for cognitive deterioration and a trajectory of cognitive deterioration in these patients which enables a simple assessment of the risk for cognitive deterioration. This was shown in their observation study of 106 participants who were cognitively appraised over a 6-year period. The study supported that elevated QSM predicted deteriorating cognitive performance in participants with a high amyloid load, whereas low QSM was associated with stable cognitive performance.
  • T2/T2 * transverse relaxation
  • these data support (1 ) the utility of a measure of magnetic susceptibility or preferably QSM and/or transverse relaxation as a prognostic test for cognitive impairment in AD, and (2) a possibility of therapeutically lowering brain iron levels to delay disease progression.
  • QSM provides a contrast mechanism in Magnetic Resonance Imaging (MRI) derived from phase processing of gradient echo acquisition, and is a relatively new MRI technique that has been validated with post mortem studies. It has been used for a number of applications including differentiating calcification from iron, standardized quantitative stratification of cerebral microbleeds, gadolinium quantification in contrast enhanced MRI, and direct monitoring of targeted theranostic drug biodistribution in nanomedicine.
  • MRI Magnetic Resonance Imaging
  • a QSM value may be obtained for patients and individuals that can be used to determine whether there is a change in cognitive deterioration or trajectory of cognitive deterioration. These values may be compared against a reference level such as from a cognitively normal individual or an internal sample taken the same individual. Alternatively, the QSM reference values can derive from diseased participants and heathy controls (HC).
  • HC heathy controls
  • QSM values may be stratified into categories such as, but not limited to high or low QSM values.
  • a positive magnetic susceptibility or high QSM value may be indicative of a high iron loading in the neocortex.
  • a negative magnetic susceptibility or low QSM value may indicate a low iron loading in the neocortex. Consequently, high or elevated QSM values or positive magnetic susceptibility values will indicate a trajectory for deteriorating cognitive performance in participants with an amyloid load, whereas low QSM or negative magnetic susceptibility may be associated with stable cognitive performance in patients with amyloid loading.
  • the magnetic susceptibility or preferably QSM values can assist in assessing cognitive deterioration or a trajectory for cognitive deterioration since a stratified magnetic susceptibility or preferably QSM will allow for a prediction of the severity of deteriorating cognitive performance in participants with amyloid load.
  • severe deterioration may be indicated by high QSM values and manageable deterioration or stable deterioration may be indicated by low QSM values.
  • the magnetic susceptibility or preferably QSM values will also enable a diagnosis of the cognitive deterioration in patients with amyloid loading as being deteriorating or stable cognitive performance.
  • changes in transverse relaxation or T2/T2 * may indicate changes excitability of molecules in the tissues of the brain caused by the presence of other molecules such as but not limited to iron content of the brain.
  • the terms "determining,” “measuring,” “evaluating,” “assessing,” and “assaying,” as used herein, generally refer to any form of measurement. These terms include both quantitative and/or qualitative determinations, which require sample processing and transformation steps of the biological sample. Assessing may be relative or absolute.
  • the measure of magnetic susceptibility or preferably QSM value and/or transverse relaxation is an indication of a rate of cognitive deterioration.
  • diagnosis or “diagnosing” as used herein would be understood by one skilled in the art to refer to the process of attempting to determine or identify a possible disease or disorder, and to the opinion reached by this process.
  • predicts or "predicting” as used herein would be understood by one skilled in the art to refer to the process of anticipating, envisioning or foreseeing an outcome based on results obtained.
  • a “reference value” or “reference level” may be used interchangeably and may be selected from the group comprising an absolute value; a relative value; a value that has an upper and/or lower limit; a range of values; an average value; a median value, a mean value, a shrunken centroid value, or a value as compared to a particular control or baseline value.
  • a predetermined reference value obtained from a known sample prepared in parallel with the biological or test sample in question. It is to be understood that other statistical variables may be used in determining the reference value.
  • a reference value can be based on an individual sample value, such as for example, a value obtained from a sample from the individual with cognitive deterioration, but at an earlier point in time, or a value obtained from a sample from a patient or another patient with the disorder other than the individual being tested, or a "normal" or "healthy” individual, that is an individual not diagnosed with cognitive deterioration otherwise a CN individual.
  • the reference value can be based on a large number of reference samples, such as from AD patients or patients with cognitive deterioration, normal individuals or based on a pool of samples including or excluding the sample to be tested.
  • the "reference level” or “reference value” is typically a predetermined reference level, such as an average of levels obtained from a population that is or isn't afflicted with cognitive deterioration.
  • the predetermined reference level is derived from (e.g., is the mean or median of) levels obtained from an age-matched population.
  • the age-matched population comprises individuals with cognitive deterioration or neurodegenerative disease individuals.
  • a reference level may also be considered as generally a predetermined level considered "normal" for the particular diagnosis (e.g., an average level for age-matched individuals not diagnosed with cognitive deterioration or an average level for age-matched individuals diagnosed with cognitive deterioration other than AD and/or healthy age-matched individuals), although reference levels which are determined contemporaneously (e.g., a reference value that is derived from a pool of samples including the sample being tested) are also contemplated.
  • a reference level may also be a measure of a constant internal control to standardize the measurements to decrease the variability between the tests.
  • the middle frontal white matter region of the brain may be used as a reference region for normalizing QSM regional values. All values would then be relative to the mean susceptibility value of this reference region.
  • Patients who can be tested and/or treated according to any of the methods of the present invention include those who present with cognitive dysfunction with a history of treated depression, cognitive dysfunction with a history of depression, cognitive dysfunction with bipolar disease or schizoaffective disorders, cognitive dysfunction with generalized anxiety disorder, cognitive dysfunction with attention deficit, ADHD disorder or both attention deficit and ADHD disorder, dyslexia, developmental delay, school adjustment reaction, Alzheimer's Disease, amnesic mild cognitive impairment, non-amnesic mild cognitive impairment, cognitive impairment with white matter disease on neuroimaging or by clinical examination, frontotemporal dementia, cognitive disorders in those under 65 years of age, those with serum homocysteine levels of less than 10 nmol/l, and those with high serum transferrin levels (uppermost population quartile).
  • the patient must present with amyloid deposition in the brain.
  • the terms “individual,” “subject,” and “patient,” generally refer to a human subject, unless indicated otherwise, e.g., in the context of a non-human mammal useful in an in vivo model (e.g., for testing drug toxicity), which generally refers to murines, simians, canines, felines, ungulates and the like (e.g., mice, rats, other rodents, rabbits, dogs, cats, swine, cattle, sheep, horses, primates, etc.).
  • a patient can also be confirmed as being positive for amyloid using imaging techniques including, PET and MRI, or with the assistance of diagnostic tools such as PiB when used with PET (otherwise referred to as PiB-PET).
  • the patient positive for amyloid is PiB positive.
  • the patient has a standard uptake value ratio (SUVR) which corresponds with high neocortical amyloid load (PiB positive).
  • SUVR standard uptake value ratio
  • a SUVR can reflect 1.5 as a high level in the brain and below 1 .5 may reflect low levels of neocortical amyloid load in the brain.
  • a skilled person would be able to determine what is considered a high or low level of neocortical amyloid load.
  • a patient can also be confirmed as being positive for a neurological disease by measuring amyloid beta and tau from the CSF.
  • amyloid load or amyloid level often used interchangeably, or presence of amyloid and amyloid fragments, refers to the concentration or level of cerebral amyloid beta ( ⁇ or amyloid- ⁇ ) deposited in the brain, amyloid-beta peptide being the major constituent of (senile) plaques.
  • the present invention relates to predicting cognitive decline in patients with amyloid deposition in the brain. The patients may already show signs of cognitive deterioration correlating with amyloid levels.
  • the patients may have amyloid deposits and be cognitively unimpaired.
  • the methods of the present invention are useful for predicting an outcome for cognitive deterioration.
  • the prognosis may be either deteriorating cognitive performance or stable cognitive performance or somewhere in between.
  • subjects characterised as negative for amyloid neocortical QSM was not a predictive variable in mixed effects models of the same cognitive scales.
  • PiB positive and PiB negative There have been numerous studies that have correlated the PiB radio tracer signal or output with the level of amyloid-beta and this has led to the terminology of PiB positive and PiB negative.
  • the normalisation of the PiB output, or uptake of the tracer occurs to allow inter- and intra-subject comparisons to be made.
  • SVS standard uptake value
  • the normalisation also incorporates standardisation with the (usually) unaffected cerebellum to provide the standard uptake value ratio (SUVR). This has led to the determination of a threshold value to differentiate those with high neocortical load (PiB positive) from those with a low load (PiB negative).
  • the amyloid deposition is determined using PET amyloid imaging.
  • any method available to the skilled addressee may be used to determine amyloid deposition.
  • the patient Once detected, the patient may be stratified as being amyloid positive or amyloid negative or PiB positive or PiB negative. More preferably, the patient has a standard uptake value ratio (SUVR) which corresponds with high neocortical amyloid load (PiB positive).
  • SUVR standard uptake value ratio
  • a SUVR can reflect 1.5 as a high level in the brain and below 1 .5 may reflect low levels of neocortical amyloid load in the brain.
  • a skilled person would be able to determine what is considered a high or low level of neocortical amyloid load.
  • the patient with amyloid deposition is amyloid positive.
  • the patient has a SUVR of >1 .5 as measured using PET amyloid imaging in unit consistent with PiB.
  • the 1.5 threshold can be adapted for other traces like AV-45 to provide the same Amyloid positivity classification.
  • the magnetic susceptibility or preferably QSM and/or transverse relaxation is determined from neocortex of the brain.
  • the magnetic susceptibility or preferably QSM and/or transverse relaxation is determined from multiple regions of the neocortex.
  • magnetic susceptibility or preferably QSM and/or transverse relaxation in the neocortex could be used to predict those amyloid positive subjects who are on the pathway toward disease progression, regardless of diagnosis.
  • the QSM is determined from MRI data. MRI detects the levels of iron through variation in the magnetic susceptibility of the tissue and iron is the strongest biological contributor to this signal.
  • the QSM and/or transverse relaxation is a measure of neocortical iron.
  • Cortical iron accumulation is also a pathological feature of AD (reviewed in Ayton S, Lei P, Bush Al. The Journal of the American Society for Experimental NeuroTherapeutics. Oct 30 2014; 12(1 ): 109-120), and has the potential to propel neurodegeneration though oxidative damage, however the contribution of cortical iron to the development of clinical symptoms has yet to be established. It has recently been shown that elevated levels of CSF ferritin (reporting brain iron levels) predicted poorer cognition, and increased the risk of developing AD in a 7-year prospective study (Ayton S, Faux NG, Bush Al, Nature communications.
  • the QSM and/or transverse relaxation correlates to neocortical iron and may be an indicator of a level of neocortical iron.
  • QSM and/or transverse relaxation does not measure iron directly.
  • QSM measures the magnetic susceptibility of the tissue in which iron is the strongest biological contributor to this signal whereas transverse relaxation measures the speed at which the excited molecules relax. Therefore, these measures merely suggest or correlate to a level of iron in the tissue.
  • an increase in neocortical iron would translate to a difference between the patient and a reference level. This difference assists in predicting or diagnosing cognitive deterioration in patients with amyloid deposition in the brain.
  • diagnostic cut-off In characterising the diagnostic capability of a measure of magnetic susceptibility or preferably QSM values and/or transverse relaxation, one of skill in the art may calculate a diagnostic cut-off.
  • This cut-off may be a value, level or range.
  • the diagnostic cut-off should provide a value level or range that assists in the process of attempting to determine or identify cognitive deterioration or rate of cognitive deterioration.
  • the amyloid positive subjects may be stratified into high and low QSM, based on a QSM value (0.0064 ppb) that optimally separates HC from diseased participants.
  • a nominal cut-off value for the QSM may be determined from relative values obtained from HC or from other diseased individuals.
  • a QSM value from an individual with low iron and/or showing no cognitive deterioration or being cognitively unimpaired may be used to define the cutoff points for QSM.
  • the level of a measure of magnetic susceptibility or preferably QSM value and/or transverse relaxation may be diagnostic for cognitive deterioration if the value is above the diagnostic cut-off.
  • the measure of magnetic susceptibility or preferably QSM value and/or transverse relaxation may be diagnostic for cognitive deterioration if the level is below the diagnostic cut-off.
  • the diagnostic cut-off for measure of magnetic susceptibility or preferably QSM values and/or transverse relaxation can be derived using a number of statistical analysis software programs known to those skilled in the art.
  • the statistical work may be conducted with R (version 3-2-4)22, using packages ggplot223, nlme24, lmerTest25.
  • the conditions necessary to apply the regression models, normal distribution of the residuals, and the absence of multicollinearity may be determined as by the skilled addressee.
  • Minimal models may be obtained via step down regression using Bayesian information criterion (BIC), ensuring that the central hypotheses are maintained. All hypothesis tests may be 2-sided, and significant differences may be inferred when p ⁇ 0.05.
  • BIC Bayesian information criterion
  • measure of magnetic susceptibility or preferably QSM values and/or transverse relaxation in the methods of the present invention could also be used in combination with other methods of clinical assessment of a neurological disease known in the art in providing a prognostic evaluation of the presence of a neurological disease.
  • assessments that include, but are not necessarily limited to, memory and/or psychological tests, assessment of language impairment and/or other focal cognitive deficits (such as apraxia, acalculia and left-right disorientation), assessment of impaired judgment and general problem- solving difficulties, assessment of personality changes ranging from progressive passivity to marked agitation. It would be contemplated that the methods of the present invention could also be used in combination with other methods of clinical assessment of a neurological disease known in the art in providing a prognostic evaluation of the presence of a neurological disease.
  • a difference in a measure of magnetic susceptibility or preferably QSM value and/or transverse relaxation between the patient and the reference level would indicate a change in cognitive deterioration.
  • the degree of change can provide an indication of whether there is increase or decrease risk for cognitive deterioration or the severity of the cognitive deterioration.
  • a small elevation may indicate a small risk whereas a high elevation is likely to indicate greater cognitive deterioration.
  • An increasing elevation between the patient and the reference level will indicate an increased risk for cognitive deterioration.
  • the progression in cognitive deterioration is a change in trajectory of the cognitive deterioration.
  • the changes in the magnetic susceptibility or preferably QSM values and/or transverse relaxation can additionally be used in assessing for any changes in cognitive deterioration of a patient. Accordingly, in the monitoring of the magnetic susceptibility or preferably QSM values and/or transverse relaxation, it is possible to monitor for the presence of cognitive deterioration over a period of time, or to track cognitive deterioration progression in a patient.
  • changes in the level of magnetic susceptibility or preferably QSM values and/or transverse relaxation from a patient can be used to assess cognitive function and cognitive deterioration, to diagnose or aid in the prognosis or diagnosis of cognitive deterioration and/or to monitor progression toward AD in a patient (e.g., tracking progression in a patient and/or tracking the effect of medical or surgical therapy in the patient). For instance if the magnetic susceptibility or preferably QSM value increases over time, the rate at which the cognitive deterioration will occur will increase.
  • a reference level may be the level of magnetic susceptibility or preferably QSM value or transverse relaxation at an earlier time point from the same patient.
  • magnetic susceptibility or preferably QSM values and/or transverse relaxation can also be obtained from a patient at more than one time point.
  • serial sampling would be considered feasible through the methods of the present invention related to monitoring progression of cognitive deterioration in a patient.
  • Serial sampling can be performed on any desired timeline, such as monthly, quarterly (i.e., every three months), semi-annually, annually, biennially, or less frequently.
  • the comparison between the measured levels and predetermined levels may be carried out each time a new sample is measured, or the data relating to levels may be held for less frequent analysis.
  • the difference in magnetic susceptibility or preferably QSM values is an elevation between the first and second time points such that the magnetic susceptibility or preferably QSM value in the second time point is higher than the first time point relative to the reference level thereby indicating an increased progression or trajectory for cognitive deterioration.
  • Applicants have shown that patients with comparatively low QSM value will not deteriorate in the foreseeable future. Conversely, an increase in QSM value predicts a more rapid deterioration. Little change in the QSM value would indicate stability of the cognitive deterioration. This will also be relevant to changes in magnetic susceptibility of the patient where the measure of magnetic susceptibility changes in a positive or negative way. Similarly, if the transverse relaxation is changed, such as if it were to decrease, this may indicate the presence of iron in the tissues.
  • the methods of the invention can additionally be used for monitoring the effect of therapy administered to a mammal, also called therapeutic monitoring, and patient management.
  • Changes in the magnetic susceptibility or preferably QSM values and/or transverse relaxation can be used to evaluate the response of a patient to drug treatment.
  • new treatment regimens can also be developed by examining the magnetic susceptibility or preferably QSM values and/or transverse relaxation in a patient following commencement of treatment.
  • the method of the present invention can thus assist in monitoring a clinical study, for example, for evaluation of a certain therapy for a neurological disease.
  • a chemical compound can be tested for its ability to change the magnetic susceptibility or preferably QSM values and/or transverse relaxation in a patient having cognitive deterioration to levels found in controls or CN patients.
  • a chemical compound can be tested for its ability to maintain the magnetic susceptibility or preferably QSM values and/or transverse relaxation at a level at or near the level seen in controls, HC or CN patients.
  • a method for stratifying a patient with amyloid deposition in the brain for cognitive deterioration comprising
  • determining a measure of magnetic susceptibility and/or transverse relaxation for the patient comparing the measure of magnetic susceptibility and/or transverse relaxation with a reference value previously defined as characteristic for patients diagnosed with a level of cognitive deterioration;
  • the changes in the level of magnetic susceptibility or preferably QSM and/or transverse relaxation in a patient with amyloid deposition in the brain can accordingly be used to stratify a patient (i.e., sorting a patient with cognitive deterioration into different classes of the condition).
  • stratifying of a patient typically refers to sorting of a patient into a different class or strata based on the features characteristic of cognitive deterioration.
  • stratifying patients with cognitive deterioration involves assigning the mammals on the basis of the severity of the deterioration or rate of deterioration. For example a high QSM will identify those patients with amyloid loading that will deteriorate faster than those that have a low QSM which may have a stable deterioration of cognitive deterioration.
  • the assessment in the change of the levels of magnetic susceptibility or preferably QSM and/or transverse relaxation can be used as a manner of identifying a patient that may be at risk of cognitive deterioration. It would be considered that should a patient be identified as being likely to show cognitive deterioration, they may be further considered for potential therapeutic intervention to assess if the predisposition of cognitive deterioration can be arrested or attenuated. The effectiveness of the intervention in the progression or development cognitive deterioration may be made possible through the monitoring for the change in the magnetic susceptibility or preferably QSM values and/or transverse relaxation.
  • Example 1 In vivo mapping of brain iron to predict amyloid-related cognitive decline
  • QSM Quantitative Susceptibility Mapping
  • AIBL Australian Imaging, Biomarkers and Lifestyle
  • MCI Mild Cognitive Impaired
  • HC Healthy Control'
  • Amyloid PET scans were obtained using the 1 1 C-PiB ligand. Image acquisition was for 30 minutes, starting 40 minutes after injection of the radiotracer. PET images were processed using semi-automated region of interest method, as described elsewhere (Villemagne VL, Burnham S, Bourgeat P, et al. Lancet neurology. Apr 2013; 12(4):357-367). Standardised update values (SUV) for 1 1 C-PiB were calculated for all brain regions. A ratio of all regional SUV to the cerebellar cortex SUV was defined as the SUV ratio (SUVR), and a value above 1 .5 designated amyloid positivity (Villemagne VL, Burnham S, Bourgeat P, et al.. Lancet neurology. Apr 2013; 12(4):357-367).
  • SUV ratio SUV ratio
  • T1W anatomical T1 -weighted
  • SWI MRI data were acquired on a 3T Siemens TRIO scanner with a 12-channel head coil.
  • the 3D SWI images used for QSM were acquired with 0.93x0.93mm in-plane resolution and 1 .75mm slice thickness, repetition time/echo time of 27/20msec, flip angle 20° and field of view 240x256, and 80 slices.
  • the magnitude and phase images were stored for each head coil channel.
  • phase offsets between each coil channel were removed by weighting the magnitude of the corresponding channel, and then combined to form a single-phase image.
  • the STI Suite software version 2.2
  • a brain mask was generated from the bias-field corrected magnitude image using FSL's BET with the robust parameter.
  • a Laplacian based method was used to unwrap the phase followed by background field elimination using vSHARP approach.
  • dipole inversion using an iLSQR technique was performed to obtain the QSM image.
  • the middle frontal white matter region was chosen as a reference region for normalizing QSM regional values. All susceptibility values are then relative to the mean susceptibility value of this reference region.
  • QSM values were elevated in amyloid positive subjects in multiple regions of neocortex; an effect that was mediated by diagnostic category, suggesting that QSM is associated more with cognitive performance than amyloid deposition.
  • Neocortical QSM was not associated with longitudinal cognitive performance in amyloid negative participants.
  • Amyloid deposition is evidence for the presence of AD, but the clinical syndrome of AD may take many years to emerge.
  • QSM in the neocortex was tested to predict those amyloid positive subjects who are on the pathway toward disease progression, regardless of diagnosis.
  • linear models of several cognitive composites controlling for age, sex, APOE ⁇ 4, SUVR, years of education, diagnosis
  • higher neocortical QSM was associated with poorer clinical outcomes in amyloid positive subjects over a six-year period (Table 1 ).
  • the amyloid positive subjects were stratified into high and low QSM, based on the QSM value (0.0064 ppb) that optimally separated HC from diseased participants ( Figure 1 ).
  • neocortical QSM was not a predictive variable in mixed effects models of the same cognitive scales (Table 1 ).
  • neocortical QSM predicts the trajectory of cognitive decline in ⁇ + subjects, which, in agreement with previous work on CSF ferritin (Ayton S, Faux NG, Bush Al, Nature communications. 2015;6:6760; S A, Faux NG, Al B. JAMA neurology. 2016;Accepted Sept 9, 2016), supports a pathogenic role of elevated brain-iron in accelerating cognitive impairment.
  • Example 2 Assessing a risk of cognitive deterioration in a patient
  • a patient will be assessed for a level of cognitive ability. This level will set a base for determining whether they will over time deteriorate. They patient may already show signs of cognitive impairment after being initially assessed. The patient is also assessed for amyloid loading before performing QSM in the patient. If the patient is not amyloid positive as assessed using PET amyloid imaging and does not have a SUVR >1 .5, the patient is not progressed.
  • QSM amyloid positive
  • a high or low QSM determines the trajectory for cognitive deterioration.
  • Example 3 Monitoring cognitive deterioration in a patient
  • a patient is tested according to Example 2 at a first time point.
  • a second test is conducted at another time point after the first time point.
  • the difference between the patient QSM is assessed.
  • the difference may then be compared to the difference from the first time point or with a reference level from a CN patient.
  • a degree of deterioration can be determined by assessing the cognitive function with the following statistically-derived composite cognitive scores (as previously described (Burnham SC, Raghavan N, Wilson W, et al. Journal of Alzheimer's disease : JAD. 2015;46(4): 1079-108)) as outcome variables for the analyses: Pre-clinical Alzheimer's Cognitive Composite (PACC: MMSE, LMII, Digit Symbol &CVLT-II LDFR), Global Cognition (C10pt: LMII, CVLTFP, Clock), Disease Progression (C2CR: CDRsb and MMSE), and Verbal Episodic Memory (C3VerEM: LMII, CVLTFP, CLVTLDFR).
  • PACC MMSE
  • LMII Digit Symbol &CVLT-II LDFR
  • C10pt LMII, CVLTFP, Clock
  • C2CR CDRsb and MMSE
  • C3VerEM LMII, CVLTFP, CLVTLDFR
  • QSM Quantitative susceptibility mapping
  • Bartzokis G Tishler TA. MRI evaluation of basal ganglia ferritin iron and neurotoxicity in Alzheimer's and Huntingon's disease. Cell Mol Biol (Noisy-le-grand). Jun 2000;46(4):821 -833. Bartzokis G, Sultzer D, Mintz J, et al. In vivo evaluation of brain iron in Alzheimer's disease and normal subjects using MRI. Biological psychiatry. Apr 1 1994;35(7):480- 487.
  • Alzheimer's & dementia the journal of the Alzheimer's Association. Jan 2014; 10(1 ):e19-26

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Public Health (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Pathology (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Physics & Mathematics (AREA)
  • Epidemiology (AREA)
  • Radiology & Medical Imaging (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • Veterinary Medicine (AREA)
  • Neurology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Primary Health Care (AREA)
  • Biophysics (AREA)
  • Physiology (AREA)
  • Databases & Information Systems (AREA)
  • Psychiatry (AREA)
  • Psychology (AREA)
  • Data Mining & Analysis (AREA)
  • Artificial Intelligence (AREA)
  • Developmental Disabilities (AREA)
  • Hospice & Palliative Care (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
  • Signal Processing (AREA)
  • Social Psychology (AREA)
  • High Energy & Nuclear Physics (AREA)
  • Neurosurgery (AREA)
  • Child & Adolescent Psychology (AREA)

Abstract

La présente invention concerne l'évaluation, la prédiction ou le diagnostic d'une détérioration cognitive chez un patient présentant des dépôts amyloïdes dans le cerveau comme mesuré par susceptibilité magnétique et de préférence en utilisant le QSM et/ou la relaxation transversale en tant qu'indicateur de la vitesse du déclin de la capacité cognitive. Les patients peuvent être stratifiés sur la base de la susceptibilité magnétique de préférence telle que mesurée à l'aide du QSM et/ou de la relaxation transversale qui prédit la trajectoire du déclin cognitif chez des sujets positifs à la protéine amyloïde.
PCT/AU2017/051074 2016-10-03 2017-10-02 Procédé pour la prédiction ou le diagnostic d'une détérioration cognitive WO2018064715A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
AU2016904000A AU2016904000A0 (en) 2016-10-03 Method for predicting or diagnosing cognitive deterioration
AU2016904000 2016-10-03

Publications (1)

Publication Number Publication Date
WO2018064715A1 true WO2018064715A1 (fr) 2018-04-12

Family

ID=61830769

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/AU2017/051074 WO2018064715A1 (fr) 2016-10-03 2017-10-02 Procédé pour la prédiction ou le diagnostic d'une détérioration cognitive

Country Status (1)

Country Link
WO (1) WO2018064715A1 (fr)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112584767A (zh) * 2018-08-21 2021-03-30 皇家飞利浦有限公司 淀粉样蛋白筛查的方法和装置
WO2022034691A1 (fr) * 2020-08-14 2022-02-17 株式会社Splink Programme informatique, dispositif de traitement d'informations, procédé de traitement d'informations, procédé de génération de modèle entraîné et dispositif de sortie d'image de corrélation
RU2819148C1 (ru) * 2023-10-19 2024-05-14 федеральное государственное автономное образовательное учреждение высшего образования "Пермский национальный исследовательский политехнический университет" Способ диагностики болезни альцгеймера

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016154682A1 (fr) * 2015-04-02 2016-10-06 Crc For Mental Health Ltd Procédé pour la prédiction du risque de détérioration cognitive

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016154682A1 (fr) * 2015-04-02 2016-10-06 Crc For Mental Health Ltd Procédé pour la prédiction du risque de détérioration cognitive

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
DAUGHERTY, A.: "Striatal Iron Content Predicts Its Shrinkage and Changes in Verbal Working Memory after Two Years in Healthy Adults", THE JOURNAL OF NEUROSCIENCE, vol. 35, no. 17, 2015, pages 6731 - 6743, XP055475166 *
FAZLOLLAHI, A. ET AL.: "Iron and amyloid depositions are positively related in non- demented individuals", ALZHEIMER'S AND DEMENTIA, vol. 12, no. 7, July 2016 (2016-07-01), pages 542, XP029769675 *
LOU, Z.: "The Correlation of Hippocampal T2-mapping with Neuropsychology Test in Patients with Alzheimer's Disease", PLOS ONE, vol. 8, no. 9, 2013, pages 1 - 7, XP055475161 *
MOON ET AL.: "Patterns of brain iron accumulation in vascular dementia and Alzheimer's dementia using quantitative susceptibility mapping imaging", J ALZH DIS., vol. 51, 30 March 2016 (2016-03-30), pages 737 - 745 *
VAN BURGEN, J. ET AL.: "Iron and Plaques: correlating PIB-PET to quantitative susceptibility mapping in mild cognitive impairment", NEURODEGENERATIVE DISORDERS, vol. 15, no. 1, 2015, pages 931 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112584767A (zh) * 2018-08-21 2021-03-30 皇家飞利浦有限公司 淀粉样蛋白筛查的方法和装置
WO2022034691A1 (fr) * 2020-08-14 2022-02-17 株式会社Splink Programme informatique, dispositif de traitement d'informations, procédé de traitement d'informations, procédé de génération de modèle entraîné et dispositif de sortie d'image de corrélation
US11972564B2 (en) 2020-08-14 2024-04-30 Splink, Inc. Recording medium, information processing device, information processing method, trained model generation method, and correlation image output device
RU2819148C1 (ru) * 2023-10-19 2024-05-14 федеральное государственное автономное образовательное учреждение высшего образования "Пермский национальный исследовательский политехнический университет" Способ диагностики болезни альцгеймера

Similar Documents

Publication Publication Date Title
Sluimer et al. Whole-brain atrophy rate and CSF biomarker levels in MCI and AD: a longitudinal study
Ferman et al. The limbic and neocortical contribution of α-synuclein, tau, and amyloid β to disease duration in dementia with Lewy bodies
Kashihara et al. Neuromelanin magnetic resonance imaging of nigral volume loss in patients with Parkinson’s disease
Müller et al. Diagnostic utility of hippocampal size and mean diffusivity in amnestic MCI
Mak et al. Neuroimaging correlates of cognitive impairment and dementia in Parkinson's disease
Rowe et al. Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging
Dickerson et al. Biomarker-based prediction of progression in MCI: comparison of AD signature and hippocampal volume with spinal fluid amyloid-β and tau
Chiotis et al. Clinical validity of increased cortical uptake of amyloid ligands on PET as a biomarker for Alzheimer's disease in the context of a structured 5-phase development framework
Resnick et al. Changes in Aβ biomarkers and associations with APOE genotype in 2 longitudinal cohorts
US20180284141A1 (en) Method for predicting risk of cognitive deterioration
Pettigrew et al. Cortical thickness in relation to clinical symptom onset in preclinical AD
Del Sole et al. Magnetic resonance imaging and positron emission tomography in the diagnosis of neurodegenerative dementias
Haris et al. T1rho MRI and CSF biomarkers in diagnosis of Alzheimer's disease
Foerster et al. Multimodal MRI as a diagnostic biomarker for amyotrophic lateral sclerosis
Khaleeli et al. Magnetisation transfer ratio in the normal appearing white matter predicts progression of disability over 1 year in early primary progressive multiple sclerosis
Vázquez‐Costa et al. Brain signal intensity changes as biomarkers in amyotrophic lateral sclerosis
Pilotto et al. Developments in the role of transcranial sonography for the differential diagnosis of parkinsonism
Yasuno et al. Use of T1-weighted/T2-weighted magnetic resonance ratio to elucidate changes due to amyloid β accumulation in cognitively normal subjects
Bonilha da Silva et al. Dentate nuclei T2 relaxometry is a reliable neuroimaging marker in Friedreich's ataxia
Reas et al. Microstructural brain changes track cognitive decline in mild cognitive impairment
Liu et al. Motor recovery prediction with clinical assessment and local diffusion homogeneity after acute subcortical infarction
Tu et al. Visual attention performances and related cerebral microstructural integrity among subjects with subjective cognitive decline and mild cognitive impairment
Johnson et al. Altered iron and myelin in premanifest Huntington's Disease more than 20 years before clinical onset: Evidence from the cross-sectional HD Young Adult Study
Zhang et al. Microvascular perfusion based on arterial spin labeled perfusion MRI as a measure of vascular risk in Alzheimer's disease
Mak et al. In vivo coupling of dendritic complexity with presynaptic density in primary tauopathies

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 17857694

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 17857694

Country of ref document: EP

Kind code of ref document: A1