Connectomic Analysis in Dementia With Lewy Bodies: A Potential Diagnostic Imaging Biomarker
Conditions: Dementia With Lewy Bodies
Sponsor: HealthPartners Institute

 
 
Connectomic Analysis in Dementia with Lewy Bodies: A 
Potential Diagnostic Imaging Biomarker 
Short Title: DLB rsfMRI 
  
Protocol Number: Version 5 
National Clinical Trial (NCT) Identified Number: NCT 04773041 
Principal Investigator: Bhavani Kashyap, MBBS, PhD 
Sponsor: HealthPartners Neuroscience Research 
Institutional Review Board Number: 21-037 
Funded by: Department Donations Raised by Regions Hospital Foundation 
 

 
CONFIDENTIALITY STATEMENT 
 
This document is confidential communication. Acceptance of this document constitutes agreement by the 
recipient that no unpublished information contained herein will be published or disclosed without prior 
approval of the Principal Investigator or other participating study leadership and as consistent with the 
terms of the award. 
 
 

A# 21-037 DLB-rsfMRI 
 
Version 5.0  
 
 
May 18, 2023 
 
 
Table of Contents 
1 
PROTOCOL SUMMARY ............................................................................................................................... 1 
1.1 
Synopsis ................................................................................................................................................ 1 
2 
INTRODUCTION ............................................................................................................................................ 2 
2.1 
Background & Study Rationale .......................................................................................................... 2 
2.2 
Risk/Benefit Assessment .................................................................................................................... 5 
2.2.1 
Known Potential Risks ..................................................................................................... 5 
2.2.2 
Known Potential Benefits ................................................................................................ 5 
2.2.3 
Assessment of Potential Risks and Benefits ................................................................ 5 
3 
OBJECTIVES AND ENDPOINTS ................................................................................................................ 6 
4 
STUDY DESIGN ............................................................................................................................................. 6 
4.1 
Overall Design ...................................................................................................................................... 6 
4.2 
Overview – study procedures/data collection .................................................................................. 7 
4.3 
End-of-Study Definition ....................................................................................................................... 7 
5 
STUDY POPULATION .................................................................................................................................. 7 
5.1 
Inclusion Criteria .................................................................................................................................. 7 
5.2 
Exclusion Criteria ................................................................................................................................. 7 
5.3 
Lifestyle Considerations ...................................................................................................................... 8 
5.4 
Screen Failures .................................................................................................................................... 8 
5.5 
Strategies for Recruitment and Retention ........................................................................................ 8 
5.6 
Participant Withdrwal .......................................................................................................................... 8 
5.6.1 
Reasons for participant withdrwal .................................................................................. 8 
5.6.2 
Handling of participant withdrwals ................................................................................. 9 
6 
STUDY Schedule ........................................................................................................................................... 9 
6.1 
Screening .............................................................................................................................................. 9 
6.1.1 
Screening/consent visit (Visit 1) (day 0) ....................................................................... 9 
6.2 
Cognitive visit (Visit 2) (Within 3 weeks of visit 1) ......................................................................... 10 
6.3 
Imaging visit (Visit 3 – at NSC) (Within 3 weeks of visit 2) .......................................................... 10 
6.4 
Optional Results Review visit (after visit 3 – at NSC/VIRTUAL) ................................................. 10 
7 
STUDY ASSESSMENTS AND PROCEDURES ..................................................................................... 10 
7.1 
Study assessments for enrolled patients ....................................................................................... 10 
7.1.1 
Demographics and medical history ............................................................................. 10 
7.1.2 
MMSE (Mini-mental status examination) .................................................................... 10 
7.1.3 
Neuropsychological assessments ............................................................................... 10 
7.1.4 
MRI Imaging .................................................................................................................... 11 
7.1.5 
connectomic Analysis .................................................................................................... 12 
7.2 
ADNI DAtabase .................................................................................................................................. 12 
7.3 
Unanticipated Problems .................................................................................................................... 12 
7.3.1 
Definition of Unanticipated Problems .......................................................................... 12 
7.3.2 
Unanticipated Problems Reporting .............................................................................. 13 
7.3.3 
Reporting Unanticipated Problems to Participants ................................................... 13 
8 
STATISTICAL CONSIDERATIONS .................................................................................................. 13 
8.1 
StatisticaL ANALYSIS PLAN ........................................................................................................... 13 
8.2 
Power analysis or Statement of Precision ..................................................................................... 14 
9 
SUPPORTING DOCUMENTATION AND OPERATIONAL CONSIDERATIONS ............. 15 
9.1 
Regulatory, Ethical, and Study Oversight Considerations ........................................................... 15 

A# 21-037 DLB-rsfMRI 
 
Version 5.0  
 
 
May 18, 2023 
 
 
9.1.1 
Informed Consent Process ........................................................................................... 15 
9.1.2 
Confidentiality and Privacy ........................................................................................... 15 
9.1.3 
Key Roles and Study Governance .............................................................................. 16 
9.1.4 
Safety Oversight ............................................................................................................. 16 
9.1.5 
Clinical Monitoring .......................................................................................................... 17 
9.1.6 
Quality Assurance and Quality Control ....................................................................... 17 
9.1.7 
Data Handling and Record Keeping ............................................................................ 17 
9.1.8 
Protocol Deviations ........................................................................................................ 17 
9.1.9 
Publication and Data Sharing Policy ........................................................................... 17 
9.1.10 
Conflict of Interest Policy .............................................................................................. 18 
9.2 
Additional Considerations ................................................................................................................. 18 
10 
REFERENCES .......................................................................................................................................... 19 
11 
APPENDIX .................................................................................................................................................. 22 
11.1 
Schedule of Visits .............................................................................................................................. 22 
 

 
 
 
 
 
 
1 
1 
PROTOCOL SUMMARY 
1.1 
SYNOPSIS  
 
Title: 
Connectomic Analysis in Dementia with Lewy Bodies: A Potential Diagnostic 
Imaging Biomarker 
IRB Number: 
A#_21-037_______ 
Study Description: 
This is a cross-sectional study in patients with Lewy Body Dementia (DLB) with 
two comparison groups (AD and cognitively normal controls) drawn from a 
publicly available database called ADNI-2/3.  We intend to study dysfunctional 
large scale brain networks (LSBNs) in DLB by comparing resting state 
functional MRI (rs-fMRI) imaging data. We propose using a novel cloud-based 
automated imaging software processing program that identifies abnormal 
brain networks or connectomes using rs-fMRI and data from the Human 
Connectome Project (HCP).  
Specific Aims: 
 
Specific Aim #1: Evaluate the role of rs-fMRI and connectomic analysis as a 
diagnostic imaging biomarker for LSBN deterioration in DLB by comparing a 
clinic population of DLB patients with pre-existing data from an ADNI 2/3 
cohort of CN and MCI/mild AD subjects  
Specific Aim #2: Correlate cross-sectional dysfunction between LSBN 
parcellations with specific neuropsychological abnormalities in DLB patients   
Outcomes: 
Aim 1 Outcomes: Functional connectivity (FC) scores between pairs of LSBN 
parcellations. 
Aim 2 Outcomes: Functional connectivity (FC) scores between pairs of LSBN 
parcellations vs Neurophsychological test scores 
Study Population: 
Inclusions: 1) Age 40- 90 years, 2) Established DLB diagnosis (McKeith Criteria 
2017), 3) MMSE>15  
Exclusions: 1) Other forms of dementia including, but not limited to 
Alzheimer’s dementia, frontotemporal dementia, vascular dementia, 
NPH, etc, 2) Inability to tolerate brain fMRI, 3) Risk of brain fMRI due to 
implants or metal.   
Sample Size: We plan to enroll 19 DLB patients.  38 AD and 38 CN age and 
sex-matched subjects will be selected from the ADNI-2/3 database.  
Description of 
Sites/Facilities 
Enrolling  
Participants: 
 
Participants will be enrolled at HealthPartners Neuroscience Center, located 
at 295 Phalen Blvd., St. Paul, MN 55130. 
 
Study Duration: 
The duration of this study is 1.5 years.  
 
Participant Duration: 
Participants should take about 3 hours - total time for all the visits, that may 
be conducted within 6 weeks 
 
 
 

 
 
 
 
 
 
2 
2 
 
INTRODUCTION 
2.1 
BACKGROUND & STUDY RATIONALE 
  
Dementia with Lewy bodies (DLB) is a common neurodegenerative condition characterized by 
parkinsonism, hallucinations, and cognitive fluctuations. This disease represents the second most 
common cause of dementia, affecting 
1.4 
million 
individuals 
(www.lbda.org). In comparison to 
Alzheimer’s disease (AD), DLB is a 
more rapid dementia that not only 
results 
in 
progressive 
cognitive 
decline, but also leads to a variety of 
non-cognitive symptoms that include 
motoric 
impairment, 
REM 
sleep 
behavioral disorder, psychosis, and 
autonomic dysfunction.  Disease 
progression is predicated on the 
propagation 
of 
alpha-synuclein 
aggregates from peripheral nervous 
system locations such as the olfactory 
cortex and enteric nervous system to 
central nervous system structures 
that include the brainstem and 
temporal cortex, thus resulting in 
progressive deterioration of LSBNs (H 
Braak J Neurol 200).   
Detection rates of DLB in clinical 
practice are suboptimal (Jones & 
O'brien, 2014). To facilitate the diagnosis of this relatively common dementia, revised criteria have been 
developed based on core clinical features, supportive clinical features, and indicative biomarkers (table 
1) (McKeith et al., 2017).  The diagnosis of probable DLB (greatest degree of certainty in the absence of 
confirmatory brain pathology) can be made when a patient has either 2 core clinical features or one 
clinical feature accompanied by one indicative biomarker.  In contrast to most other neurological 
diseases, the indicative biomarkers in DLB measure indirect effects of the disease: reduced dopamine 
transporter update on a DaT scan indicates parkinsonism, abnormal cardiac uptake on a 123iodine-MIBG 
myocardial scintigraphy suggests autonomic dysfunction, and tonic contractions during REM sleep during 
polysomnography supports REM sleep behavioral disorder.  Limitations of these tests include a lack of 
specificity for this diagnosis (findings can be seen in Parkinson’s disease or multiple system atrophy), 
relatively higher costs, and lack of insurance coverage as in the case of the DaT scan.   
 
Further complicating matters, there are no universal imaging tools that directly show the impact of DLB 
on the CNS.  Structural brain MRI is relatively less helpful for diagnostic classification, described as a 
“supportive biomarker” meaning that it has a less critical role in determining diagnosis. MRI will support 
a DLB diagnosis when there is an absence of medial temporal lobe atrophy, commonly found in 
Alzheimer’s disease.  However, the sensitivity and specificity of this diagnostic test is suboptimal: a 
Table 1: Criteria for Dementia with Lewy Bodies 

 
 
 
 
 
 
3 
multisite study with autopsy confirmation showed that MRI was 64% sensitive and 68% specific for 
differentiating DLB from AD.  Fluorodeoxyglucose positive emission tomography (FDG-PET), a functional 
biomarker that has been used to support a DLB diagnosis, shows occipital hypometabolism with relatively 
sparing of the posterior cingulate although these findings likewise lack sensitivity (83%) and specificity for 
DLB (80%) (Minoshima et al., 2001; Yamamoto et al., 2007). 
 
The role of brain rs-fMRI, an imaging tool that maps interactions between brain regions during a resting 
state and produces a blood-oxygen-level-dependent signal, has been only preliminarily evaluated in 
patients with DLB. Currently, there is no defined pattern of LSBN deterioration in this condition.  Certain 
investigations have failed to demonstrate characteristic differences between connectivity in DLB versus 
AD whereas others have demonstrated subtle difference (eg. increased precuneus-medial frontal 
connectivity (Galvin, Price, Yan, Morris, & Sheline, 2011). A study consisting of 18 DLB, 18 AD, and 15 CN 
subjects showed that posterior cingulate cortex connectivity was lower in AD than in DLB (Franciotti et 
al., 2013).  Another study evaluated rs-fMRI functional connectivity in 15 DLB, 13, AD, and 40 controls, 
showing that functional connectivity was lower in DLB in the default mode, salience, and executive 
networks compared to the other groups (Lowther, O’Brien, Firbank, & Blamire, 2014) whereas a second 
study failed to show significant differences in LSBN connectivity between AD and DLB (Schumacher et al., 
2018).   
 
The core symptoms of DLB (hallucinations, cognitive fluctuations, parkinsonism, and REM sleep behavioral 
disorder) may offer clues to the specific LSBNs impacted by this disease.  To our knowledge, few studies 
have evaluated the networks responsible for these symptoms and then attempted to leverage findings 
for diagnostic purposes.  The locus coeruleus, a brainstem structure containing abundant noradrenergic 
neurons with ascending pathways throughout the central nervous system, has been found to exhibit cell 
loss in post-mortem analysis of DLB patients (Del Tredici & Braak, 2013) and may be responsible for the 
characteristic cognitive fluctuations (O’Dowd et al., 2019).  fMRI studies have further shown that patients 
with disorders of consciousness exhibit compromise of those connections between the locus coeruleus, 
intralaminar nucleus of the thalamus, and nucleus basalis of Meynert (Edlow, Claassen, Schiff, & Greer, 
2020).  It has also been demonstrated that neuronal loss and Lewy bodies in the nucleus basalis of 
Meynert are correlated with the reduction of choline acetyltransferase levels in DLB (Lippa, Smith, & 
Perry, 1999).  Thus, we suspect that the locus coerulus and its ascending projections play a significant role 
in the arousal disturbances and cognitive fluctuations in DLB.  Parkinsonism results from disruption of 
connections between the substantia nigra and basal ganglia structures (Young & Penney, 1984).  
Furthermore, findings of attention/executive dysfunction in DLB correlate with the basal ganglia, 
particularly the left caudate nucleus (Botzung, Philippi, Noblet, de Sousa, & Blanc, 2019).   Finally, 
hallucinations in Lewy body are thought to involve dysfunction in a variety of brain areas.  A systemic 
literature search of 56 neuroimaging studies in PD and DLB with visual hallucinations were reviewed—the 
main structural neuroimaging results showed grey matter loss in the frontal areas whereas functional 
investigations revealed parietal and temporal hypometabolism in PD with hallucinations (Pezzoli, Cagnin, 
Bandmann, & Venneri, 2017).  Disrupted functional connectivity was also detected in the fronto-parietal 
regions through fMRI studies. One structure, the inferior longitudinal fasciculus (ILF), which connects the 
occipital lobe with the temporal lobe, has been found to be dysfunctional in DLB (Kantarci et al., 2010).  
We suspect that brain regions within this pathway may be compromised in DLB patients with visual 
hallucinations.  Preliminary work from our group has shown from that area PH, a region located within 
the anterioinferior lateral occipital lobe and lateral to the occipitotemporal sulcus, is associated with visual 
hallucinations in schizophrenia and has white matter connections within the ILF.  This area is a higher-
level perception region of the visual system that acts as a hub of ventral stream input, integrating “place-
specific” information, while showing little to no activity to objects or faces (Baker, Burks, Briggs, Milton, 

 
 
 
 
 
 
4 
et al., 2018).  There are connections to other brain regions including area or hub FST, which is involved in 
integrating information related to detail, motion, and form. Thus, our study will focus on pairwise 
functional connectivity between the seven parcellations listed in Table 2.    
 
Table 2. Parcellations of Interest for Each DLB Core Symptom and Associated LSBN  
DLB Core Symptom 
Associated Large Scale Brain 
Network 
Parcellations of Interest 
Cognitive fluctuations 
Ascending 
brainstem 
norepinephrine tracts 
Locus coeruleus, basal nucleus of Meynert, 
intralaminar nucleus of thalamus (Edlow et 
al., 2020) 
Visual hallucinations 
Inferior longitudinal fasciculus 
Areas PH and FST (Pezzoli et al., 2017) 
Parkinsonism 
Ascending 
brainstem 
dopamine tracts 
Substantia nigra, caudate nucleus (Young & 
Penney, 1984) 
 
One potential challenge for functional imaging to this point is that brain parcellations (or distinct brain 
partitions) have been based on outdated models such as the Broadmann map from the 19th century (Zilles, 
2018). In 2009, the Human Connectome Project (HCP) began one of the most ambitious neuroscientific 
initiatives to map the brain (Fox, 2018; Glasser et al., 2016). This project identified 379 functional areas of 
the brain and discovered 97 new regions that had never been previously described.  This data has provided 
neuroscientists for the first time in history the ability to view the brain not merely as a structural entity, 
but as an individualized network system.  
 
 
Figure 1: Infinitome Program – Removed for CT.GoV version 
 
Omniscient, a for-profit, Sydney, Australia-based company, created the cloud-based software Infinitome, 
a program that utilizes data from the HCP together with machine learning to analyze diffusion tensor and 
resting-state fMRI imaging data from remote sites (Figure 1).  The foundation for this imaging tool is based 
upon the HCP atlas, which has also informed prior publications from our group, including the Connectomic 
Atlas of the Human Cerebrum (Baker, Burks, Briggs, Conner, et al., 2018).  The Infinitome program creates 
a subject specific version of the Human Connectome Project Multimodal Parcellation (HCP-MMP1) atlas 
using diffusion tractography.  Analytics are performed on both diffusion tensor imaging and rs-fMRI.  
Outlier detection using a tangent space connectivity matrix is performed by comparing results with a 
subset of 300 normal HCP subject fMRI samples to determine the range of normal correlations for each 
regions of interest in a LSBN.  Abnormal connectivity is determined as a 3-sigma outlier for that 
correlation.  The imaging protocol for rs-fMRI is limited to 15 minutes, enabling each study to be readily 
added on to structural MRI sequences.  The program also provides automated image processing and 
analysis, thus simplifying the process of accessing imaging data and incorporating rs-fMRI into routine 
practice.  By providing support for fMRI processing through a cloud-based server and incorporating normal 
control data from the HCP, this program addresses the challenges associated with the analysis and 
interpretation of rs-fMRI data. Thus, it has the potential to simplify the incorporation of rs-fMRI into 
clinical trials as a biomarker for neurodegeneration of vulnerable networks in DLB.   Preliminary work has 
shown that connectomic analysis in AD subjects using this software is feasible and can detect functional 
anomalies involving regions of interest described by the HCP (Ren et al., 2020). Results from this proposal 

 
 
 
 
 
 
5 
will be applicable to both clinical practice and research where a diagnostic biomarker may impact either 
medical decision-making or enrollment into a clinical trial.   
 
2.2 
RISK/BENEFIT ASSESSMENT  
2.2.1 KNOWN POTENTIAL RISKS  
 
Study has no Intervention.  
Imaging 
Structural MRI is a routine diagnostic procedure at HealthPartners, and the resting state portion merely 
requires 15 minutes of scan time.   The patient may experience claustrophobia with the narrow imaging 
space, and hearing loud noises while inside the machine. A MRI scan does not involve radiation like 
conventional X-rays.  Instead, images are generated using a magnetic field and radio signals.  Because an 
MRI scanner uses strong magnets, subjects will be screened by the NSC Imaging staff – as for a routine 
MRI.  People with artificial heart valve, metal plate, pin, or other metallic objects in their body (including 
gun shot or shrapnel) will not be eligible for this study. 
 
Cogntive Assesments  
The questions on these assessments may make participants feel uncomfortable because some parts may 
be easy to answer, while some parts may be difficult or tiring. It may also cause individuals to feel 
uncomfortable or upset. 
 
Loss of Confidentiality 
There may be a slight possibility of breach of confidential information that was collected. However, the 
following procedures will be implemented to reduce this risk: 
• 
Data collection and reporting tools will be developed and stored internally. 
• 
Data collected and stored electronically will remain confidential and secure (e.g. secured server 
and password protected files [REDCap]).  
• 
Study binders will be stored in a locked file cabinet within a locked office. 
• 
After the study is closed, all subject identifiers will be destroyed. 
 
2.2.2 KNOWN POTENTIAL BENEFITS  
 
No known direct benefits. 
 
With minimal risk beyond what is typically encountered in the standard evaluation of dementia, research 
participants will have the opportunity to review novel rs-fMRI brain imaging that depicts the human 
connectome as large scale brain networks. 
 
By employing a novel and innovative cloud-based program that is based on machine learning and HCP 
data, this study will serve to develop rs-fMRI as a diagnostic biomarker for DLB.  
 
2.2.3 ASSESSMENT OF POTENTIAL RISKS AND BENEFITS  
 

 
 
 
 
 
 
6 
We believe the potential risks to the participants in this study are minimal. A significant portion of the 
study population will come from rs-fMRI from the publically accessible ADNI 2/3 database, thus reducing 
the number of study subjects undergoing study procedures for this project. 
 
The following measures will be taken to protect providers and patients from the risk of breach of 
confidentiality:  
• 
A unique study ID code unrelated to the medical record number or other study subject-specific 
information will be assigned to each patient and used to link data from various sources and 
needed for analysis.  The study number will be used on the RedCap database and Infinitome 
Program.  All imaging data uploaded from the NSC research site will be de-identified and uploaded 
to the Infinitome cloud-based server.   
• 
Infinitome program uses an industrial grade cyber security that is superior to what is offered at 
the leading medical device companies.  No personal health information is stored on servers and 
only de-identified scans are stored on a dedicated edge node on encrypted MinIO instances.  
Patient data is only accessed through authenticated calls form Kubernetes pods contained in the 
VPC.  The web service requires user authentication.  Only the data related to a specific facility can 
be retrieved through authenticated calls and are restricted to their use. 
 
3 
OBJECTIVES AND ENDPOINTS  
 
Aim 1: Evaluate the role of rs-fMRI and connectomic analysis as a biomarker of disease in DLB using 
data from an ADNI-2/3 population of MCI and mild AD subjects and a clinic population 
of DLB subjects  
Functional connectivity (FC) scores between pairs of LSBN parcellations  
• 
Primary pairs of interest (see background for justification of these choices):   
o 
Locus coeruleus v. Basal nucleus of Meynert  
o 
Locus coeruleus v. Intralaminar nucleus of thalamus  
o 
Basal nucleus of Meynert v. Intralaminar nucleus of thalamus  
o 
PH v. FST  
o 
Substantia nigra v. Caudate nucleus  
• 
Exploratory pairs: Other 15 combinations of the pre-specified parcellations, other pairs of 
parcellations found to be anomalies by Infinitome program  
Aim 2: Correlate cross-sectional and longitudinal dysfunction between LSBN parcellations with 
specific neuropsychological abnormalities in DLB Patients  
Functional connectivity (FC) scores between pairs of LSBN parcellations (same primary pairs of interest 
as Aim 1).  
Scores on neuropsychological tests: WMS-R Logical Memory Story A, Boston Naming Test Short, 
Category Fluency, WMS-R Digit Span Forward and Backward, ANART, RAVLT, Trails A/B, WMS-R Digit 
Symbol, Clock Drawing, NPI-Q, FAQ, ADAS-Cog 13  
 
4 
STUDY DESIGN 
 
4.1 
OVERALL DESIGN 
 
This is a cross-sectional study in patients with DLB with two comparison groups. The study includes 
analyzing resting state-functional MRI (rs-fMRI) imaging data in CN and AD subjects from the ADNI 2/3 
database and in DLB subjects recruited from a multidisciplinary dementia clinic 

 
 
 
 
 
 
7 
 
Specific Aim #1: Evaluate the role of rs-fMRI and connectomic analysis as a diagnostic imaging biomarker 
for LSBN deterioration in DLB by comparing a clinic population of DLB patients with pre-existing data from 
an ADNI 2/3 cohort of CN and mild AD subjects  
 
Specific Aim #2: Correlate cross-sectional dysfunction between LSBN parcellations with specific 
neuropsychological abnormalities in DLB patients . 
 
 
4.2 
OVERVIEW – STUDY PROCEDURES/DATA COLLECTION 
 
Data will be obtained for cognivite measures and imaging data (rs-fMRI, DTI, T1) from ADNI 2/3 data 
base cohort subjects with AD diagnosis, CN and DLB subjects recruited from a multidisciplinary dementia 
clinic. See the section # for detailed study procedures/data collection. Cognitive tests were selected so 
as to be harmonized with those used with the ADNI-2/3 database. 
 
This research investigation will take place at the Center for Memory and Aging at the HealthPartners 
Neuroscience Center (multidisciplinary dementia clinic).  Potential candidates will also be referred to our 
site through the Park Nicollet Neurology Clinic.   
 
4.3 
END-OF-STUDY DEFINITION 
 
A participant is considered to have completed the study if he or she has completed study visits and 
assessments.  
 
5 
STUDY POPULATION 
For ADNI 2/3 data, we will include CN and AD subjects who have undergone rs-fMRI images (with DTI 
and T1 images) and have cognitive/function testing data available. Below we describe the study 
population regarding clinic recruitment.  
5.1 
INCLUSION CRITERIA 
 
In order to be eligible to participate in this study, an individual must meet all of the following criteria: 
• 
Age 40- 90 years 
• 
Established DLB diagnosis (McKeith et al. 2017) 
• 
MMSE>15  
5.2 
EXCLUSION CRITERIA 
 
An individual who meets any of the following criteria will be excluded from participation in this study: 
• 
Other forms of dementia including, but not limited to Alzheimer’s dementia, frontotemporal 
dementia, vascular dementia, NPH, etc, 
• 
Inability to tolerate brain fMRI 
• 
Risk of brain fMRI due to implants or metal.  
 

 
 
 
 
 
 
8 
5.3 
LIFESTYLE CONSIDERATIONS 
 
NA 
 
5.4 
SCREEN FAILURES 
 
Pre-screening Phone Call: All potential participants will undergo a pre-screening phone or a video call to 
determine whether they meet the inclusion/exclusion criteria. Patients will be considered ineligible if they 
do not meet one or more of the inclusion/exclusion criteria during pre-screening. We will collect 
information on why participants are ineligible or decide not to move forward with the trial. 
 
Screen failures are defined as participants who are considered eligible during the pre-screening phone 
call, but it was subsequently determined that they do not meet one or more of the inclusion/exclusion 
criteria. We will collect information on why participants screen fail or decide not to move forward with 
the trial.  
 
5.5 
STRATEGIES FOR RECRUITMENT AND RETENTION 
 
Recruitment: For Alzheimer’s Disease Neuroimaging Initiative (ADNI), analysis will be based on data 
available from the database. As such there are no recruitment or retention activities. rs-fMRI data as well 
as variables listed in Table 3 & 4 will be downloaded from ADNI-2/3 for age/sex-matched mild AD (with 
supportive biomarkers) and age/sex-matched CN patients. 
 
Clinic Population: Potential DLB subjects will be referred to the study coordinator by clinicians in the 
neurology departments of HealthPartners and Park Nicollet.  Participants with clinic visits will meet with 
research staff. Other patients will be mailed/e-mailed a letter and flyer/brochure.  An informed consent 
form will be provided to those individuals expressing interest in the study.  A video or phone encounter 
will be arranged to provide additional details of the study and informed consent. This study will be listed 
as one of the regional DLB investigations on the Alzheimer’s Association Trial Match website.  All referrals 
will be directed to study staff who will contact interested participants by phone.  Participation will include 
one virtual visit and two in-person visits at HealthPartners Neuroscience Center. 
To reach our target enrollment, we anticipate that we will need to screen 40 people, of those 19 
individuals will sign the informed consent.  
 
Remuneration: Participants will be provided gift cards totaling $100 per subject for completing certain 
visits of the research study. The gift cards will be provided at the end of the study for completing the 
cognitive and imaging visits. 
 
 
5.6 
PARTICIPANT WITHDRWAL 
 
5.6.1 REASONS FOR PARTICIPANT WITHDRWAL 
Participants are free to withdraw from participation in the study at any time upon request. 

 
 
 
 
 
 
9 
An investigator may withdraw a participant from the study if: 
• 
Any medical condition, event or situation occurs such that continued participation in the study 
would not be in the best interest of the subject. 
• 
The participant meets an exclusion criterion (either newly developed or not previously 
recognized) that precludes further study participation.   
• 
Significant study procedure non-compliance  
• 
Lost-to-follow up; unable to contact subject 
5.6.2 HANDLING OF PARTICIPANT WITHDRWALS 
The reason for participant discontinuation or withdrawal from the study will be recorded on the relevant 
eCRF. Subjects  who  sign  the  informed  consent  form and undergo only cognitive measures, and not 
imaging will not have completed participation and may be replaced.  
A participant will be considered lost to follow-up if he or she fails to attend any scheduled study visit and 
study staff are unable to contact the participant after at least 5 attempts. 
The following actions must be taken if a participant fails to attend any required study visit: 
• 
Study  staff  will attempt  to  contact  the  participant,   reschedule  the  missed  visit,   counsel  
the  participant  on  the  importance  of  maintaining  the  assigned  visit  schedule  and  
ascertain  if the participant wishes to and/or should continue in the study.  
• 
Before a  participant  is  deemed  lost  to  follow-up,  the  investigator  or  designee  will make 
every effort  to  regain  contact  with  the  participant  (where  possible,  telephone  calls  or  e-
mail –  if  no  answer  leave  a  voicemail  on  the  first  and  last  attempt).  These  contact  
attempts  will be documented. 
• 
Should  the  participant  continue  to  be  unreachable,  he  or  she  will  be  considered  to  have  
withdrawn from the study with a primary reason of lost to follow-up. 
 
6 
STUDY SCHEDULE 
 
The sections below are only for recruitment of DLB patients for clinic. See Section 11.1 for schedule. 
6.1 
SCREENING 
 
6.1.1 SCREENING/CONSENT VISIT (VISIT 1) (DAY 0) 
• 
This visit may be a telephone/video visit 
• 
Review, obtain and document consent from subject and caregiver (e-consent) 
• 
Adminster MMSE 
• 
Review medical history, demorgraphics to determine eligibility to participate 
• 
Review history regarding any contraindications for MRI imaging 
• 
Schedule study visits for individuals who are eligible and available for the duration of the study 

 
 
 
 
 
 
10 
• 
A total time of 40 minutes is anticipated for this visit 
 
6.2 
COGNITIVE VISIT (VISIT 2) (WITHIN 3 WEEKS OF VISIT 1) 
• 
Verify inclusion/exclusion criteria 
• 
Neuropsychological battery as mentioned in Section 7. 
• 
Schedule Imaging visit if not scheduled 
• 
This visit may be combined with imaging visit, but imaging can be performed only after cognitive 
assessments 
• 
This visit is at the clinic (HealthPartners Neuroscience Center [NSC]), is about 60 minutes. 
6.3 
IMAGING VISIT (VISIT 3 – AT NSC) (WITHIN 3 WEEKS OF VISIT 2) 
 
• 
Verify inclusion/exclusion criteria 
• 
Subject will undergo MRI imaging as mentioned in Section 7. 
• 
This visit may be combined with cogntive visit, but imaging can be performed only after 
cognitive assessments 
• 
This visit is at the clinic (NSC), is about 50 minutes. 
6.4 
OPTIONAL RESULTS REVIEW VISIT (AFTER VISIT 3 – AT NSC/VIRTUAL) 
 
An optional 30 minute visit may be scheduled to share the brain imaging results with with the subject and 
the caregiver by the PI.  The participant can decide whether or not they would like to attend this visit, 
which can either be virtual or at NSC.  
 
Participants will be asked to adhere to study visits and to complete study assessments. Participants will 
remain active unless withdrawn from the study. These will be documented in the relevant CRF. 
 
7 
STUDY ASSESSMENTS AND PROCEDURES 
 
7.1 
STUDY ASSESSMENTS FOR ENROLLED PATIENTS 
7.1.1 DEMOGRAPHICS AND MEDICAL HISTORY 
 
Demographic information will be collected, including: gender, age, race, ethnicity, height, weight, BMI, 
education, dementia diagnosis, co-morbidities (such as Diabetes, Hypertension) and e-mail address for 
consent. 
7.1.2 MMSE (MINI-MENTAL STATUS EXAMINATION) 
Originally developed in 1976 by Folstein, the MMSE is a paper-based test commonly used in clinical and 
research settings (Folstein, Folstein, & McHugh, 1975). A 30 point cognitive screening tool that assesses 
orientation, working memory, short term memory, visuospatial construction, and language.  
 
7.1.3 NEUROPSYCHOLOGICAL ASSESSMENTS 

 
 
 
 
 
 
11 
 
All enrolled subjects will undergo the following cognitive scales.  These will be adminstered by the 
research staff trained in these assessments using instructions specific for tests under the guidance/ 
supervision of the study neuropsychologist. Cognitive tests (validated) were selected so as to be 
harmonized with those used with the ADNI-2/3 database.  Testing will take between 45-60 min. The 
following battery will be administered:  
 
Table 3. Neuropsychological Battery (Visit 2) 
 
Cognitive Test/Scale 
Domain 
References 
WMS R Logical Memory Story A 
Story Memory/Delay 
(Wechsler, 1987) 
ADAS-COG-13 Number Cancellation 
Visual Attention 
(Rosen, Mohs, & Davis, 1984) 
ADAS-COG—13 Praxis 
Visuoconstruction 
(Rosen et al., 1984) 
Boston Naming Test (Odd items) 
Naming 
(Kaplan, Goodglass, & 
Weintraub, 1983) 
Verbal Fluency 
Verbal Fluency 
(Butters, Granholm, Salmon, 
Grant, & Wolfe, 1987) 
WMS R Digit span F and B 
Auditory Attention  
(Wechsler, 1987) 
ANART 
Pre-morbid function 
(Nelson & O'Connell, 1978) 
RAVLT 
List Learning/Memory/Recog 
(Rey, 1964; Rosenberg, Ryan, 
& Prifitera, 1984) 
Trails A/B 
Attention/Executive 
Function 
(Reitan, 1958) 
Clock Drawing 
Clock Draw 
(Goodglass & Kaplan, 1983) 
NPI-Q 
Neuropsychiatric Symptom  
(Kaufer et al., 2000) 
FAQ 
Functional assessment 
(Pfeffer, Kurosaki, Harrah Jr, 
Chance, & Filos, 1982) 
ADAS-Cog-13=Alzheimer’s Disease Assessment Scale-cognitive subscale 13; WMS R=Weschler Memory Scale-
Revised; ANART=American National Adult Reading Test; RAVLT: Rey Auditory Verbal Learning Test; Rey O 
Copy: Rey Osterrieth Figure Copy; NPI-Q: Neuropsychiatric Inventory Questionnaire; FAQ: Functional 
Assessment Questionnaire  
7.1.4 MRI IMAGING 
Subjects will undergo MRI imaging at HealthPartners Neuroscience Center. Subjects will be screened for 
any contraindications for MRI. Subjects will undergo a protocol based on recommendation by 
Omniscent (o8t MR Acquisition Recommendations). We anticipate 15 minutes of scan run time using a 
3T Siemens Skyra scanner and the following images will be obtained. 
1) High-resolution multi-scan directional diffusion scan, which is most similar to a diffusion tensor 
image (DTI) acquisition - Specifically, diffusion weighted imaging with the following acquisition 
parameters will be used: 2 mm x 2 mm x 2 mm voxels, FOV = 25.6 cm, matrix = 128 mm x 128 
mm, slice thickness = 2.0 mm, one non-zero b-value of b = 1000, 40 directions, and gap = 0.0 
mm.  

 
 
 
 
 
 
12 
2) EPI BOLD rs-fMRI - A resting-state fMRI as a T2-star EPI sequence, with 3 x 3 x 3-mm voxels, 128 
volumes/run, a TE = 27ms, a TR = 2.8s, a field of view – 256mm, a flip angle = 90°  
3) Anatomical Scan –T1 Weighting 
All images will be de-identified and uploaded to the infintome cloud-based server to be analyzed. 
Internal guidelines/best practices based on infinitome user manual will be developed for transfer, 
obtaining accounts, uploading of raw images and downloading of analyzed data.  
 
7.1.5 CONNECTOMIC ANALYSIS 
All subject images will be processed using the infitiome tool. This tool creates a machine learning-based, 
subject specific version of the Human Connectome Project-Multimodal Parcellation (HCP-MMP1) atlas 
based upon diffusion tractography structural connectivity. This will be used to conduct a connectomic 
analysis to identify large scale brain networks.  
 
7.2 
ADNI DATABASE 
A data use agreement with ADNI will be completed prior to downloading the data for analysis from the 
ADNI database (ADNI Database). A user login – for research staff will be used for downloading the data. 
 
All necessary ADNI data for MCI, mild AD patients, and cognitively normal (CN) will be downloaded to a 
local secure server for further analysis.  
 
Data will be obtained regarding demographics, medical history, cognitive assessments (as mentioned in 
earler sections), MMSE for eligibility, biomarkers and imaging ( as mentioned in the previous section). The 
imaging data will be uploaded and processed with the Infinitome software as stated in the previous 
sections.   
 
7.3 
UNANTICIPATED PROBLEMS 
 
7.3.1 DEFINITION OF UNANTICIPATED PROBLEMS 
 
This protocol uses the definition of Unanticipated Problems as defined by the Office for Human Research 
Protections (OHRP). OHRP considers unanticipated problems involving risks to participants or others to 
include, in general, any incident, experience, or outcome that meets all of the following criteria: 
 
1. Unexpected in terms of nature, severity, or frequency given (a) the research procedures that are 
described in the protocol-related documents, such as the IRB-approved research protocol and 
informed consent document; and (b) the characteristics of the participant population being 
studied; 
2. Related or possibly related to participation in the research (“possibly related” means there is a 
reasonable possibility that the incident, experience, or outcome may have been caused by the 
procedures involved in the research); and 

 
 
 
 
 
 
13 
3. Suggests that the research places participants or others at a greater risk of harm (including 
physical, psychological, economic, or social harm) than was previously known or recognized. 
 
7.3.2 UNANTICIPATED PROBLEMS REPORTING  
 
The PI will report unanticipated problems (UPs) to the reviewing IRB. The UP report will include the 
following information: 
 
• 
Protocol identifying information: protocol title and number, PI’s name, and the IRB project 
number 
• 
A detailed description of the event, incident, experience, or outcome  
• 
An explanation of the basis for determining that the event, incident, experience, or outcome 
represents an UP 
• 
A description of any changes to the protocol or other corrective actions that have been taken or 
are proposed in response to the UP 
 
To satisfy the requirement for prompt reporting, UPs will be reported using the following timeline:   
 
• 
UPs will be reported to the IRB as soon as possible, but no later than 10 working days after the 
investigator first learns of the event 
 
7.3.3 REPORTING UNANTICIPATED PROBLEMS TO PARTICIPANTS  
 
Following IRB review of any unanticipated problems, the PI will follow the IRB’s recommended actions. 
This may include, but is not limited to, modifying the informed consent document or process, re-
consenting current participants, providing information to past or current participants (e.g. whenever the 
information may relate to the participant’s willingness to continue participants), and modifications to the 
protocol/research plan. 
 
8 
STATISTICAL CONSIDERATIONS 
8.1 
STATISTICAL ANALYSIS PLAN 
 
Preliminary data analysis: One-way ANOVA will be used to compare demographic and baseline clinical 
characteristics across groups. **no missing data expected, SAS, p-value 
Aim 1 Analysis: For the between-group analysis of functional connectivity, general linear model 
multivariate analysis of variance will be used with FC values between pairs of LSBN parcellations as 
dependent variables and group (DLB, AD, and CN) as a factor variable. Bonferroni post hoc test will be 
used to correct for multiple comparisons. The primary pairs of interest (see Table 4) based on available 
literature (see background and Table 2) will be analyzed first. Other combinations of these seven 
parcellations will be analyzed secondarily. If additional, unexpected anomalies are present between 
groups, we will test them in an exploratory fashion to advance this novel field of study.  

 
 
 
 
 
 
14 
Aim 2 Analysis: Pearson correlation analyses will be performed between functional connectivity values 
and neuropsychological test scores to evaluate the relationship between connectivity strengths and the 
clinical phenotype of DLB. Similar to Aim 1, we will focus on pre-specified pairs of interest, but will 
explore others if they present themselves in the functional connectivity analysis. 
 
 
Table 4: Data Variables  
Population Descriptors: age, sex, race, ethnicity, education, measures of baseline cognition (e.g. 
MoCA) 
Aim 1: Evaluate the role of rs-fMRI and connectomic analysis as a biomarker of disease in DLB using 
data from an ADNI-2/3 population of MCI and mild AD subjects and a clinic population of DLB 
subjects 
Group variable: DLB, AD, or CN 
Dependent variables: Functional connectivity (FC) scores between pairs of LSBN parcellations 
• 
Primary pairs of interest (see background for justification of these choices):  
o Locus coeruleus v. Basal nucleus of Meynert 
o Locus coeruleus v. Intralaminar nucleus of thalamus 
o Basal nucleus of Meynert v. Intralaminar nucleus of thalamus 
o PH v. FST 
o Substantia nigra v. Caudate nucleus 
• 
Exploratory pairs: Other 15 combinations of the pre-specified parcellations, other pairs of 
parcellations found to be anomalies by Infinitome program 
Aim 2: Correlate cross-sectional dysfunction between LSBN parcellations with specific 
neuropsychological abnormalities in DLB Patients 
Functional connectivity (FC) scores between pairs of LSBN parcellations (same primary pairs of interest 
as Aim 1). 
Scores on neuropsychological tests: WMS-R Logical Memory Story A, Boston Naming Test Short, 
Category Fluency, WMS-R Digit Span Forward and Backward, ANART, RAVLT, Trails A/B, WMS-R Digit 
Symbol, Clock Drawing, NPI-Q, FAQ, ADAS-Cog 13 
 
8.2 
POWER ANALYSIS OR STATEMENT OF PRECISION 
In a one-way ANOVA, sample sizes of 19 DLB, 38 AD, and 38 CN achieve 80% power to detect differences 
among the means versus the alternative of equal means using an F test with a 0.01 significance level and 
assuming a common standard deviation within a group of 0.05. This is true for any set of group means 
with a standard deviation greater than or equal to 0.02, which we anticipate being able to achieve based 
on previous research. All significant brain connection couples in Franciotti’s work had standard 
deviations of the group means greater than 0.06. 
For post-hoc tests, group sample sizes of 19 DLB, 38 AD, and 38 CN patients achieve 81% power to reject 
the null hypothesis of equal means when the population mean difference is 0.05 with a standard 
deviation for both groups of 0.05 and with a significance level (alpha) of 0.010 using a two-sided two-
sample equal-variance t-test. 

 
 
 
 
 
 
15 
 
9 
SUPPORTING DOCUMENTATION AND OPERATIONAL CONSIDERATIONS 
 
 
9.1 
REGULATORY, ETHICAL, AND STUDY OVERSIGHT CONSIDERATIONS 
 
9.1.1 INFORMED CONSENT PROCESS 
 
ADNI: We are requesting a waiver of written informed consent for all ADNI data for the following reasons: 
1) The data is retrospective and will be downloaded from a database, 2) There is no additional data 
collection, and 3) It would be impractical to consent patients (due to large numbers) if written informed 
consent of patients were required. A data use agreement with ADNI will be completed prior to 
downloading the data for analysis from the ADNI database.   
 
Clinic: All research study staff will maintain certification in human subject’s protection. All study 
investigators and staff will take an active role in developing procedures to protect against or minimize 
potential risks to the safety and well-being of enrolled participants. Potential research subjects will be 
informed that participation in this study is voluntary and will not be discriminated against if they choose 
not to participate. Written informed or electronic consent and assent will be obtained from participants, 
and family member/caregivers or legally authorized representatives (LAR). Participants will be asked to 
describe in their own words the study’s expectations. Subjects will be informed that they can withdraw 
from the study at any time and will be given a copy of the consent form. Subjects will have written 
assurance that while de-identified individual subject data may be available to other researchers for 
research purposes, or used to improve the software program, only a summary of the results will ever be 
published or otherwise publicly released. Subjects will be assured that participation in the study will be 
strictly confidential, that any identifying information will be available to the study staff only, and that no 
identifying information concerning the data and results will be made known. 
 
Potential research subjects will be informed that participation in this study is voluntary and that their 
decision to participate will not reflect upon their relationships with the Center for Memory and Aging, 
Regions Hospital, or HealthPartners. Subjects will be informed that they can withdraw from the study at 
any time and will be given a copy of the consent form.   
 
With the electronic consent via REDCap the patient/caregiver providing consent will be able to review the 
consent form themselves and sign electronically with a stylus, touch screen, or cursor using a signature 
field in REDCap. After the individual has received the link and can view the consent form, the research 
staff member will go through the consent form with the individual as would be typical in person. Following 
the consent conversation, the staff member will sign and e-mail the consent and HIPPA electronically to 
the patient. The patient will electronically sign, certify, and submit the consent and HIPPA in REDCap. A 
fully executed PDF copy of the consent and HIPPA will be provided electronically to the patient for their 
records as well as saved via the auto-archiver function in REDCap. 
 
9.1.2 CONFIDENTIALITY AND PRIVACY  
 
Participant confidentiality and privacy is strictly held in trust by the participating investigators, their staff, 
the safety and oversight monitor(s), and the sponsor(s). This confidentiality is extended to the data being 
collected as part of this study. Data that could be used to identify a specific study participant will be held 

 
 
 
 
 
 
16 
in strict confidence within the research team. No personally-identifiable information from the study will 
be released to any unauthorized third party without prior written approval of the sponsor/funding agency.  
 
All research activities will be conducted in as private a setting as possible. 
 
All study regulatory binders will be stored in a locked file cabinet within a secure office. The internal study 
monitor, representatives of the IRB, or regulatory agencies, may inspect all documents and records 
required to be maintained by the investigator, for the participants in this study. The clinical study site will 
permit access to such records. 
 
The study participant’s contact information will be securely stored at the clinical site for internal use 
during the study. At the end of the study, all records will continue to be kept in a secure location for as 
long a period as dictated by the reviewing IRB, Institutional policies, or sponsor/funding agency 
requirements. 
 
A unique study ID code unrelated to the medical record number or other study subject-specific 
information will be assigned to each patient and used to link data from various sources and needed for 
analysis.  The study number will be used on the RedCap database and Infinitome Program.  All imaging 
data uploaded from the NSC research site will be de-identified and uploaded to the Infinitome cloud-
based server.   
 
Infinitome program uses an industrial grade cyber security that is superior to what is offered at the leading 
medical device companies.  No personal health information is stored on servers and only de-identified 
scans are stored on a dedicated edge node on encrypted MinIO instances.  Patient data is only accessed 
through authenticated calls form Kubernetes pods contained in the VPC.  The web service requires user 
authentication.  Only the data related to a specific facility can be retrieved through authenticated calls 
and are restricted to their use 
 
The PI will ensure all mechanisms used to share data will include proper plans and safeguards for the 
protection of privacy, confidentiality, and security for data dissemination and reuse (e.g., all data will be 
thoroughly de-identified and will not be traceable to a specific study participant). Plans for archiving and 
long-term preservation of the data will be implemented, as appropriate.  
 
 
9.1.3 KEY ROLES AND STUDY GOVERNANCE 
 
Principal Investigator 
Michael Rosenbloom, MD 
HealthPartners Neuroscience Center 
295 Phalen Blvd. St. Paul, MN 55130 
 
 
 
9.1.4 SAFETY OVERSIGHT 
 
There is no Data Safety Monitoring Board for this study, as there is no intervention and has minimal risks 
 

 
 
 
 
 
 
17 
9.1.5 CLINICAL MONITORING 
 
N/A, refer to next section. 
 
9.1.6 QUALITY ASSURANCE AND QUALITY CONTROL 
 
Study staff will perform internal quality management of study conduct, data collection, documentation 
and completion. 
 
Quality control (QC) procedures will be implemented as follows: 
 
Informed consent --- Study staff will review both the documentation of the consenting process and 10% 
of the completed consent documents. Feedback will be provided to study staff to ensure proper 
consenting procedures are followed. 
 
Protocol Deviations – The study team will review documented protocol deviations on an ongoing basis 
and will implement corrective actions when the quantity or nature of deviations are deemed to be at a 
level of concern. 
 
Should independent monitoring become necessary, the PI will provide direct access to all study related 
sites, source data/documents, and reports for the purpose of monitoring and auditing by the 
sponsor/funding agency, and inspection by local and regulatory authorities. 
 
9.1.7 DATA HANDLING AND RECORD KEEPING  
 
9.1.7.1 DATA COLLECTION AND MANAGEMENT RESPONSIBILITIES  
 
Data collection will be the responsibility of the research study staff under the supervision of the PI. The PI 
will be responsible for ensuring the accuracy, completeness, legibility, and timeliness of the data reported. 
 
Data collection/reporting tools will be developed internally (i.e. CRFs or eCRFs (RedCap Database) and 
source documents).  Data collected and stored electronically will remain confidential and secure (e.g. 
secured server, encrypted data, password protected file). 
9.1.7.2 STUDY RECORDS RETENTION  
 
Investigator records will be retained in accordance with regulatory, organizational and sponsor or grantor 
requirements.  All records will be maintained securely with limited access. Disposal of investigator records 
will be done in such a manner that no identifying information can be linked to research data. 
 
9.1.8 PROTOCOL DEVIATIONS   
 
This protocol defines a protocol deviation as any noncompliance with the study protocol. The 
noncompliance may be either on the part of the participant, the investigator, or the study site staff. As a 
result of deviations, corrective actions will be developed by the site and implemented promptly.  
 
9.1.9 PUBLICATION AND DATA SHARING POLICY  

 
 
 
 
 
 
18 
 
This study will be registered at ClinicalTrials.gov, and results information from this study will be submitted 
to ClinicalTrials.gov. In addition, every attempt will be made to publish results in peer-reviewed journals. 
 
Data from the de-identifed images may be utilized by Omniscent for improvement of Infinitome program 
and potential future imaging research studies.  
 
9.1.10 CONFLICT OF INTEREST POLICY 
 
The study leadership in conjunction with HealthPartners Institute has established policies and procedures 
for all study group members to disclose all conflicts of interest and will establish a mechanism for the 
management of all reported dualities of interest. 
 
9.2 
ADDITIONAL CONSIDERATIONS 
 
N/A 
 
 
 
 

 
 
 
 
 
 
19 
 
10 REFERENCES 
 
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Connectomic Atlas of the Human Cerebrum—Chapter 6: The Temporal Lobe. Operative Neurosurgery, 
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Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). Mini-mental state: A practical method for grading the 
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network is not hypoactive in dementia with fluctuating cognition: an Alzheimer disease/dementia with 
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22 
11 APPENDIX 
11.1 SCHEDULE OF VISITS 
 
Procedure 
Screen/Consent 
Cognitive 
Imaging 
Results Review 
 
Visit 1 
Visit 2 
Visit 3 (Within 3 
weeks of visit 2) 
Optional (After 
Visit 3) 
 
Telephone/Video 
At NSC 
At NSC 
At NSC or Virtual 
E-consent 
X 
 
 
 
Medical History 
X 
 
 
 
Demographics 
X 
 
 
 
MRI Contraindications 
X 
 
X 
 
Inclusion/Exclusion 
Criteria 
X 
X 
X 
 
MMSE 
X 
 
 
 
Cognitive Tests 
 
X 
 
 
MRI Imaging 
 
 
X 
 
Brain Imaging Results 
 
 
 
X 
 

DLB-rsfMRI 
 
A21-037 
06 FEB 2024 
 
PI: Bhavani Kashyap 
 
Updated A Priori SAP 
06 FEB 2024 
 
 

DLB-rsfMRI 
 
A21-037 
06 FEB 2024 
 
PI: Bhavani Kashyap 
Aim 1 
 
Our primary aim was to evaluate the role of rs-fMRI and connectomic analysis as a diagnosƟc 
imaging biomarker of disease for LSBN deterioraƟon in DLB by comparing a clinical populaƟon of 
DLB paƟents with the ADNI 2/3 cohort of CN and AD/CI subjects. Speciﬁcally, we compared FC 
scores of prespeciﬁed parcellaƟon pairs between the three groups using a one-way ANOVA. Eight 
parcellaƟon pairs were chosen as the primary pairs, and twenty-two as the exploratory pairs.  
 
Aim 2 
Our secondary aim (aim 2) was to correlate cross-sectional dysfunction between LSBN 
parcellations with specific neuropsychological abnormalities in DLB patients. To accomplish this, 
we performed a two-stage analysis. First, we compared cognitive test scores between groups to 
understand which successfully distinguished between the cohorts. When possible, test scores 
were normed, i.e., converted to a Z- or T-score adjusted for age, sex, and years of education.  
Primary Comparisons/A Priori Hypotheses: 
1) ADAS Number Cancellation Targets will be lower in DLB patients 
2) Trails B time will be higher in DLB patients 
3) Clock Drawing Tests will be lower in DLB patients 
4) ADAS construction praxis score will be lower in DLB patients 
5) Category Fluency Animals will be lower in AD patients 
6) RAVLT recognition will be lower in AD patients 
 
The remaining comparisons were exploratory: Trails A Ɵme, RAVLT immediate recall, RAVLT delayed recall, 
FuncƟonal AcƟviƟes QuesƟonnaire (FAQ), Logical Memory Immediate, and Logical Memory Delayed. Digit 
Span Forward, Digit Span Backward, and Boston Naming Test were either missing or highly incomplete in 
ADNI controls; therefore, they were described in the DLB cohort only. 
 

DLB-rsfMRI 
 
A21-037 
06 FEB 2024 
 
PI: Bhavani Kashyap 
In the second part of the Aim 2 analysis, we correlated test scores with FC scores from the 
primary parcellaƟon group in Aim 1, within diagnosis (DLB, CN, or AD/CI) and compared these 
correlaƟons across diagnosis group. As above, we prespeciﬁed 4 hypotheses to test and consider 
the remaining correlaƟons to be exploratory. Because of the high volume of staƟsƟcal tests 
performed in the exploratory analysis, we used the Holm correcƟon to adjust the p-values in the 
exploratory correlaƟons only.  
 
Primary/ A Priori Hypotheses: 
1) Caudate R / Substantia Nigra R and the Clock Drawing Test will be diﬀerently correlated for DLB patients 
vs other groups. 
2) Caudate R/ Substantia Nigra R and the ADAS Number Cancellation Targets will be diﬀerently correlated 
for DLB patients vs other groups. 
3) FST R/PH Rand the ADAS construction praxis will be diﬀerently correlated for DLB patients vs other 
groups. 
4) FST R / PH R and the Clock Drawing Test will be diﬀerently correlated for DLB patients vs other groups. 
 
With respect to the exploratory correlaƟons, we used a signiﬁcance threshold of p < 0.15, which is an 
accepted approach for detecƟng eﬀects in emerging research areas where it’s preferable to err on the 
side of idenƟfying novel eﬀects versus failing to reject a null hypothesis when it is false (Type II error).