<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03754608</url>
  </required_header>
  <id_info>
    <org_study_id>2000023733</org_study_id>
    <nct_id>NCT03754608</nct_id>
  </id_info>
  <brief_title>Validating Imaging Biomarkers of Small Vessel Disease in Diabetic Individuals Using Advanced MRI Techniques.</brief_title>
  <official_title>Validating Imaging Biomarkers of Small Vessel Disease in Diabetic Individuals Using Advanced MRI Techniques.</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Yale University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Yale University</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      To develop a set of biomarkers for imaging of small vessel disease in diabetic individuals&#xD;
      using advanced MRI techniques. With this the investigators want to document progression of&#xD;
      disease both radiologically and clinically.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The investigators will use a paradigm developed at Yale University called Cognitive&#xD;
      Predictive Modelling (CPM) which takes connectivity data and reduces it to two smaller&#xD;
      network which predict higher and lower performance in a particular task for which these&#xD;
      networks have been optimized. Vascular measures will complement this measure.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">November 7, 2018</start_date>
  <completion_date type="Actual">August 31, 2020</completion_date>
  <primary_completion_date type="Actual">August 31, 2020</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Case-Control</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Diagnostic Odds ratio for the MRI vascular cognitive impairment biomarker.</measure>
    <time_frame>2 years</time_frame>
    <description>This will be calculated from the sensitivity and specificity as compared to clinical diagnosis.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Correlation between the biomarker and cognition</measure>
    <time_frame>18 months.</time_frame>
    <description>Assess whether the biomarker can predict the severity of the cognitive performance.</description>
  </secondary_outcome>
  <number_of_groups>2</number_of_groups>
  <enrollment type="Actual">63</enrollment>
  <condition>Small Vessel Disease of Diabetes Mellitus</condition>
  <arm_group>
    <arm_group_label>Diabetics/No cognitive impairment</arm_group_label>
    <description>These are individuals with diabetes who do not have vascular cognitive impairment as determined by VASCOG criteria.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Diabetics with vascular cognitive impairment</arm_group_label>
    <description>These are individuals with diabetes who have vascular cognitive impairment as determined by VASCOG criteria.</description>
  </arm_group>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>MRI including cf-MRI, DTI, ASL and CVR.</intervention_name>
    <description>A paradigm developed at Yale University called Cognitive Predictive Modelling which takes connectivity data and reduces it to two smaller network which predict higher and lower performance in a particular task for which these networks have been optimized. This will be supplemented by MRI vascular measures.</description>
    <arm_group_label>Diabetics with vascular cognitive impairment</arm_group_label>
    <arm_group_label>Diabetics/No cognitive impairment</arm_group_label>
    <other_name>Neuropsychological testing (Cantab), basic laboratory blood tests, small number of CSF</other_name>
  </intervention>
  <biospec_retention>Samples With DNA</biospec_retention>
  <biospec_descr>
    <textblock>
      Blood tests are performed on all participants at three time points. When permission exists we&#xD;
      are banking CSF and blood products.&#xD;
    </textblock>
  </biospec_descr>
  <eligibility>
    <study_pop>
      <textblock>
        Our study population are those with type 2 diabetes in mid-life and old age, who may or may&#xD;
        not have cognitive deficits, whose cognitive deficits (when present) cannot be better&#xD;
        explained by other factors. We exclude those who are unable to have MRI or cognitive&#xD;
        testing due to a variety of reasons.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
        A - Vascular cognitive impairment:&#xD;
&#xD;
          1. Presence of diabetes&#xD;
&#xD;
          2. The International Society of Vascular Behavioral and Cognitive Disorders (VASCOG)&#xD;
             criteria for vascular cognitive impairment&#xD;
&#xD;
          3. Age between 55 and 90 (inclusive)&#xD;
&#xD;
          4. Score on the Montreal Cognitive Assessment (MOCA) 15 to 23&#xD;
&#xD;
          5. Presence of a responsible caregiver who will accompany mild cognitive impaired (MCI)&#xD;
             subjects to all procedures.&#xD;
&#xD;
          6. Evidence of vascular disease&#xD;
&#xD;
          7. The patient should have a capacity to consent.&#xD;
&#xD;
          8. English speakers&#xD;
&#xD;
        B- Cognitively normal elderly Subjects:&#xD;
&#xD;
          1. Presence of diabetes&#xD;
&#xD;
          2. Absence of National Institute on Aging (NIA) - Alzheimer's Association core clinical&#xD;
             criteria for probable Alzheimer's Disease (AD) and VASCOG criteria for vascular&#xD;
             cognitive impairment.&#xD;
&#xD;
          3. Objective memory scores within normal range for age (do not meet MCI Subjects&#xD;
             criterion 2)&#xD;
&#xD;
          4. Age between 55 and 90 (inclusive)&#xD;
&#xD;
          5. English speakers&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          1. Any significant neurologic disease (other than vascular cognitive disease and stroke),&#xD;
             such as Parkinson's disease, brain tumor, seizure disorder, multiple sclerosis, or&#xD;
             history of significant head trauma followed by persistent neurologic deficits.&#xD;
&#xD;
          2. Any significant systemic disease including hepatic failure, heart failure, renal&#xD;
             failure, Chronic obstructive pulmonary disease (COPD), active infection and autoimmune&#xD;
             disease.&#xD;
&#xD;
          3. Any significant systemic illness or unstable medical condition, including:&#xD;
             uncontrolled or insulin-dependent diabetes mellitus, uncorrected hypothyroidism or&#xD;
             hyperthyroidism, or systemic cancer.&#xD;
&#xD;
          4. Investigational agents are prohibited 4 weeks prior to entry and for the duration of&#xD;
             the study. Previous treatment with an investigational small molecule with anti-amyloid&#xD;
             properties or passive immunization against amyloid within 1 year of study entry.&#xD;
             Previous treatment with an active immunization against amyloid.&#xD;
&#xD;
          5. History of schizophrenia or other major psychiatric disorder (DSM IV criteria).&#xD;
&#xD;
          6. History of alcohol or substance abuse or dependence (DSM IV criteria) within the past&#xD;
             2 years.&#xD;
&#xD;
          7. Pregnancy, as determined by screening pregnancy tests for pre-menopausal females&#xD;
&#xD;
          8. Impairment of visual or auditory acuity sufficient to interfere with study procedures.&#xD;
&#xD;
          9. Education level &lt; 6 years.&#xD;
&#xD;
         10. Presence of pacemakers, aneurysm clips, artificial heart valves, ear implants, metal&#xD;
             fragments or foreign objects in the eyes, skin or body. The presence of&#xD;
             claustrophobia, precluding MRI.&#xD;
&#xD;
         11. Drink more than 5 alcoholic drinks per week or any heavy drinking days in the last 30&#xD;
             days&#xD;
&#xD;
         12. Women who are pregnant or nursing, or fail to use one of the following methods of&#xD;
             birth control unless she or partner is surgically sterile or she is postmenopausal&#xD;
             (hormone contraceptives [oral, implant, injection, patch, or ring], contraceptive&#xD;
             sponge, double barrier [diaphragm or condom plus spermicide], or intrauterine device&#xD;
             (IUD)&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>55 Years</minimum_age>
    <maximum_age>90 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Arash Salardini, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Yale University</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Yale University School of Medicine</name>
      <address>
        <city>New Haven</city>
        <state>Connecticut</state>
        <zip>06510</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>April 2021</verification_date>
  <study_first_submitted>October 16, 2018</study_first_submitted>
  <study_first_submitted_qc>November 26, 2018</study_first_submitted_qc>
  <study_first_posted type="Actual">November 27, 2018</study_first_posted>
  <last_update_submitted>April 16, 2021</last_update_submitted>
  <last_update_submitted_qc>April 16, 2021</last_update_submitted_qc>
  <last_update_posted type="Actual">April 19, 2021</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Diabetic Angiopathies</mesh_term>
  </condition_browse>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03754608
org study id: 2000023733
nct id: NCT03754608
lead sponsor: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
To develop a set of biomarkers for imaging of small vessel disease in diabetic individuals
      using advanced MRI techniques. With this the investigators want to document progression of
      disease both radiologically and clinically.
The investigators will use a paradigm developed at Yale University called Cognitive
      Predictive Modelling (CPM) which takes connectivity data and reduces it to two smaller
      network which predict higher and lower performance in a particular task for which these
      networks have been optimized. Vascular measures will complement this measure.
observational model: Case-Control
time perspective: Prospective
measure: Diagnostic Odds ratio for the MRI vascular cognitive impairment biomarker.
time frame: 2 years
description: This will be calculated from the sensitivity and specificity as compared to clinical diagnosis.
measure: Correlation between the biomarker and cognition
time frame: 18 months.
description: Assess whether the biomarker can predict the severity of the cognitive performance.
arm group label: Diabetics/No cognitive impairment
description: These are individuals with diabetes who do not have vascular cognitive impairment as determined by VASCOG criteria.
arm group label: Diabetics with vascular cognitive impairment
description: These are individuals with diabetes who have vascular cognitive impairment as determined by VASCOG criteria.
intervention type: Diagnostic Test
intervention name: MRI including cf-MRI, DTI, ASL and CVR.
description: A paradigm developed at Yale University called Cognitive Predictive Modelling which takes connectivity data and reduces it to two smaller network which predict higher and lower performance in a particular task for which these networks have been optimized. This will be supplemented by MRI vascular measures.
arm group label: Diabetics with vascular cognitive impairment
arm group label: Diabetics/No cognitive impairment
other name: Neuropsychological testing (Cantab), basic laboratory blood tests, small number of CSF
Blood tests are performed on all participants at three time points. When permission exists we
      are banking CSF and blood products.
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 55 Years
maximum age: 90 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Arash Salardini, MD
role: Principal Investigator
affiliation: Yale University
facility: 
country: United States
responsible party type: Sponsor
mesh term: Diabetic Angiopathies