Concussion, BrainNCT05993351
Objective Concussion Assessment Using MRI and Metabolomics
An observational study of Concussion, Brain, run by St. Joseph's Healthcare Hamilton at 1 site in Canada.
Trial summary
Mild traumatic brain injury (mTBI), also referred to as concussions, affect millions of people around the world and can cause harmful long term effects. Unfortunately, concussions can be hard to diagnose and many people have lasting post-concussion symptoms such as headaches, difficulty concentrating, and light… Read more about this study
- Who is it for?
- Ages 9 to 50 yearsHealthy volunteers can take part
- Conditions the study is for
- Concussion, Brain
- What is being tested?
- Magnetic resonance imaging (MRI), Urine and saliva samples and Questionnaires
- Type of treatment
- Injection or infusion, Lifestyle or therapy programme
- How many people
- 100 participants
- Where
- 1 siteCanada
- Study dates
- 11 Aug 2023to 15 Dec 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 9 to 50 years
- All sexes
- Healthy volunteers accepted
- Child, Adult
Study population: Participants for this prospective observational cohort will include 50 individuals who have recently sustained a concussion within the last 2 weeks. Participants will primarily be recruited based on their involvement in collision or contact sport, causing sport-related concussions. Fifty healthy control participants will be recruited with the intention to have age, sex and athletic status matching to the concussion participants.
Who may be able to join
- Aged between 9-50
- Recently sustained a concussion (within the last 2 weeks)
Who cannot join
- Aged 8 and younger or 51 and older
- Unable to provide consent (e.g., poor English language skills, etc.)
- History of liver or kidney disease
- MRI contraindications:
- Pacemaker
- Stent
Show all 14Show fewer
- Joint prothesis
- Implanted devices
- Claustrophobia
- Pregnant
- Permanent piercings
- Chronic/abusive use of alcohol and/or illicit drugs
- Previous stroke or moderate/severe traumatic brain injury, subarachnoid hemorrhage, or intracranial hemorrhage
- Healthy control participants must not have a concussion history or recently sustained a concussion
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Ethan Danielli, PhD contact
Canada1 site, 1 recruiting
- Recruiting
Imaging Research Center at St. Joseph's Healthcare Hamilton
Hamilton, Ontario, L8N 4A6
Michael D Noseworthy, PhD, PEng, (905) 522-1155, nosewor@mcmaster.ca
Ethan Danielli, PhD, ethan.danielli@uhn.ca
About this study
Official title: Correlating Advanced MRI Techniques With Neuropsychological Analysis and Immunosensing Assays for Assessment of Sport-related Mild Traumatic Brain Injuries (mTBI)
Mild traumatic brain injury (mTBI), also referred to as concussions, affect millions of people around the world and can cause harmful long term effects. Unfortunately, concussions can be hard to diagnose and many people have lasting post-concussion symptoms such as headaches, difficulty concentrating, and light sensitivity. Recent studies have shown that advanced magnetic resonance imaging (MRI) techniques can identify subtle brain changes caused by a concussion. This study aims to track concussions over time measuring MRI brain scans and post-concussion symptoms to gain a better understand how the brain is affected in comparison to symptoms.
Read the detailed description
Mild traumatic brain injuries (mTBI) are a major health concern due to the risk of short and long-term complications. In order to understand the effects of an TBI (also referred to as a concussion), studies have examined the physiological and cognitive impact of concussions on the brains of youth and collegiate athletes. Based on athletic-exposure (AE), the most concussions in the National Collegiate Athletics Association (NCAA) occur in Men's wrestling, Men's and Women's ice hockey, Men's football, and Women's soccer (Zuckerman et al. 2015). It has been estimated that 300 000 sport-related concussions (SRC) occur annually in the United States among youth and collegiate athletes (Coronado et al. 2015; Gessel et al. 2007; Langlois et al. 2006; Thurman et al. 1998). However, a SRC estimate would likely be grossly underestimated due to underreporting and failure to seek medical treatment (Karlin 2011; Kaut et al. 2003; Kerr et al. 2016; McCrea et al. 2004; Roozenbeek et al. 2013). In reality, the number of annual SRC could be as high as 1.6 to 3.8 million occurrences (Langlois et al. 2006).
Brain injuries are classified as mild, moderate or severe based on patient reported symptoms, cognitive impairment and structural damage visualized using medical imaging (Bodin et al. 2012; DeCuypere and Kilmo 2012; DeMatteo et al. 2010; Roozenbeek et al. 2013). A major challenge facing mTBI diagnosis has been standardizing assessment, predicting prognosis, and clearing people to return to work or sport. In order to more accurately diagnose and treat patients, healthcare providers require a better understanding of how to brain is affected acutely, and the timeline for when it returns to a pre-concussion state. Recent technological innovations show promise to supplement the current behavioural and psychological assessments. Current concussion and mTBI diagnosis are often based on tests that assess a patient's sensory feedback, mental cognition, motor control, and post-concussion symptoms (Bodin et al. 2012; DeCuypere and Klimo 2012).
To supplement symptom tracking, magnetic resonance imaging (MRI) has been shown in research to be an invaluable concussion tool. The health of brain white matter can be predicted based on the relativistic shape of the myelin surrounding axons and the diffusivity of water along the length of the axons by using a MRI technique called diffusion tensor imaging (DTI)(Asken et al. 2018; Jonkman et al. 2015). In addition, the function of brain grey matter can be assessed using functional magnetic resonance imaging (fMRI) by measuring the paramagnetic differences between oxygenated and deoxygenated blood, based on the Blood-Oxygen Level Dependent (BOLD) signal (Horn et al. 2014; Liu et al. 2018; Ogawa et al. 1990). Activated brain regions have a greater BOLD signal due to magnetic field inhomogeneities caused by changes in blood volume, blood flow, and local metabolism (Ogawa et al. 1990). An fMRI can be used to analyze brain resting state activation patterns, a primary connective system is the Default Mode Network (DMN)(Mak et al. 2017). The DMN has been shown to have decreased activity following a mTBI (Bonnelle et al. 2011; Zhou et al. 2012).
A serious issue surrounding head injuries is the need for a method to diagnose athletes immediately following the injury. The growing interest in using metabolomics for the discovery of clinically relevant biomarkers associated with mild traumatic brain injury (mTBI) could be a solution. However, most studies to date have relied exclusively on blood specimens and/or targeted metabolite panels involving small cohorts of patients without adequate replication, and validation of aberrant metabolic changes in circulation to independent MRI-based brain imaging (Fiandaca et al. 2018; Orešič et al. 2016). We propose to include an analysis of fasting saliva and urine specimens from mTBI patients for comprehensive metabolite profiling using high throughput multi-segment injection-capillary electrophoresis-mass spectrometry technology (DiBattista et al. 2019; Yamamoto et al. 2019), which allows for rapid non-targeted analysis of polar/hydrophilic metabolites, as well as non-polar/ionic lipids with stringent quality control (Azab et al. 2019).
This study aims to track concussion recovery over 6-months using clinical standards of concussion symptoms and objective MRI and metabolomics metrics. Concussion participants will complete three study visits: acutely within 2-weeks of a concussion, 3-month follow-up and 6-month follow-up. Participants will be recruited from St. Joseph's Healthcare Hamilton and local athletic organizations. The study protocol will be identical for all three study visits. Participants will complete the Post-Concussion Symptom Scale (PCSS) and Depression Anxiety Stress Scale (DASS-42) to measure the presence and self-reported severity of common post-concussion symptoms. The MRI data will be used to measure brain function (resting state fMRI) and microstructural properties (diffusion tenor imaging), while the metabolomics will measure if metabolites have abnormal presence or concentration post-concussion based on urine and saliva samples. These quantitative methods will be compared to the subjective concussion symptom scores to identify if brain and physiological abnormalities persist past symptom resolution, and if certain brain regions are more frequently affected by concussion. It is hypothesized that across all three time points that brain function will have decreased BOLD signal fractal complexity and network connectivity (representative of concussion-related injuries), and white matter damage will be present based on the primary DTI metric of fractional anisotropy. It is also hypothesized that post-concussion symptoms will be self-reported as resolved or almost resolved by the 3-month follow-up study visit.
- Conditions
- Concussion, Brain
- Being tested
- Magnetic resonance imaging (MRI), Urine and saliva samples, Questionnaires
- Keywords
- functional magnetic resonance imaging, diffusion tensor imaging, symptom tracking, sport-related concussions
- Medical subject headings
- Brain Concussion
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Magnetic resonance imaging (MRI)Diagnostic test
All participants will have 3 MRI scanning sessions to track brain health over time following the same protocol each time. The MRI sessions will occur acutely (<2 weeks post-concussion), 3-months and 6-months post-concussion. A series of MRI scans will be acquired including T1, T2, T2-FLAIR, SWI, ASL, rsfMRI, and DTI scans to characterize structural, microstructural, functional and tissue perfusion changes within the brain over time.
Urine and saliva samplesDiagnostic test
At each study visit all participants will be asked to provide small urine and saliva samples for a metabolomic analysis using a high throughput multi-segment injection-capillary electrophoresis-mass spectrometry technology. This will allow for rapid non-targeted analysis of polar/hydrophilic metabolites, as well as non-polar/ionic lipids with stringent quality control.
QuestionnairesBehavioural
The Post-Concussion Symptom Scale (PCSS) and the Depression Anxiety Stress Scale (DASS-42) will be used to assess the self-reported presence and severity of known concussion-related symptoms.
| Study group | Role | What they receive |
|---|---|---|
| Concussion | Individuals who have recently sustained a concussion within the past 2-weeks. Receives: Diagnostic Test: Magnetic resonance imaging (MRI); Diagnostic Test: Urine and saliva samples; Behavioral: Questionnaires | |
| Healthy Control | Individuals who have limited to no concussion history, and have not recently sustained a concussion. Receives: Diagnostic Test: Magnetic resonance imaging (MRI); Diagnostic Test: Urine and saliva samples; Behavioral: Questionnaires |
What is being measured
The primary outcome is the main question the study is designed to answer.
Functional brain characteristics
Brain function will be examined based on the network connectivity and fractal complexity of the rsfMRI BOLD signal. This will be measured across known brain networks (e.g., Default Mode Network) and specific regions-of-interest (e.g., insula).
Measured: 45-minute MRI sessions acutely, 3-months and 6-months post-concussion
Microstructural brain characteristics
Microstructural brain changes will be examined based on diffusion tensor imaging (DTI) metrics of fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. This will be measured within specific regions-of-interest (e.g., insula).
Measured: 45-minute MRI sessions acutely, 3-months and 6-months post-concussion
Post-concussion symptoms
Tracking of self-reported post-concussion symptoms using PCSS and DASS-42 questionnaires
Measured: Acutely, 3-months and 6-months post-concussion
Secondary outcomes (1)
Metabolomics
High throughput multi-segment injection-capillary electrophoresis-mass spectrometry technology will be used to analyze the urine and saliva samples to identify if any polar or non-polar metabolites are abnormal post-concussion, and that may indicate physiological markers for future assessment and treatment options.
Measured: Acutely, 3-months and 6-months post-concussion
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Aug 2023
- Study start11 Aug 2023
- Primary completion15 Dec 2026 (estimated)
- Study completion15 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (26)Papers the sponsor has linked to this study.
- Other trials for Concussion, BrainStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- St. Joseph's Healthcare Hamilton
- Sponsor type
- University, hospital or other
- Collaborators
- McMaster University
- Responsible party
- Principal investigator, Michael Noseworthy PhD, St. Joseph's Healthcare Hamilton
- Investigators
- Michael D Noseworthy, PhD, PEng, Principal investigator, McMaster UniversityDinesh A Kumbhare, MD, PhD, Principal investigator, University Health Network, Toronto
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05993351
- Sponsor's protocol ID
- Concussion MRI & recovery
- Status last verified
- Nov 2024
- First submitted
- 12 Aug 2023
- Last updated
- 15 May 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: Study data may be shared upon request to the research team.
Publications
Asken BM, DeKosky ST, Clugston JR, Jaffee MS, Bauer RM. Diffusion tensor imaging (DTI) findings in adult civilian, military, and sport-related mild traumatic brain injury (mTBI): a systematic critical review. Brain Imaging Behav. 2018 Apr;12(2):585-612. doi: 10.1007/s11682-017-9708-9.
PubMed 28337734Azab S, Ly R, Britz-McKibbin P. Robust Method for High-Throughput Screening of Fatty Acids by Multisegment Injection-Nonaqueous Capillary Electrophoresis-Mass Spectrometry with Stringent Quality Control. Anal Chem. 2019 Feb 5;91(3):2329-2336. doi: 10.1021/acs.analchem.8b05054. Epub 2019 Jan 7.
PubMed 30570251Bodin, D., Yeates, K. O., & Klamar, K. (2012). Definition and Classification of Concussion. In J. N. Apps & K. D. Walter (Eds.), Pediatric and Adolescent Concussion (pp. 9-19). New York, NY: Springer New York. https://doi.org/10.1007/978-0-387-89545-1_2
Bonnelle V, Leech R, Kinnunen KM, Ham TE, Beckmann CF, De Boissezon X, Greenwood RJ, Sharp DJ. Default mode network connectivity predicts sustained attention deficits after traumatic brain injury. J Neurosci. 2011 Sep 21;31(38):13442-51. doi: 10.1523/JNEUROSCI.1163-11.2011.
PubMed 21940437Coronado VG, Haileyesus T, Cheng TA, Bell JM, Haarbauer-Krupa J, Lionbarger MR, Flores-Herrera J, McGuire LC, Gilchrist J. Trends in Sports- and Recreation-Related Traumatic Brain Injuries Treated in US Emergency Departments: The National Electronic Injury Surveillance System-All Injury Program (NEISS-AIP) 2001-2012. J Head Trauma Rehabil. 2015 May-Jun;30(3):185-97. doi: 10.1097/HTR.0000000000000156.
PubMed 25955705Decuypere M, Klimo P Jr. Spectrum of traumatic brain injury from mild to severe. Surg Clin North Am. 2012 Aug;92(4):939-57, ix. doi: 10.1016/j.suc.2012.04.005. Epub 2012 Jun 5.
PubMed 22850156Dematteo CA, Hanna SE, Mahoney WJ, Hollenberg RD, Scott LA, Law MC, Newman A, Lin CY, Xu L. "My child doesn't have a brain injury, he only has a concussion". Pediatrics. 2010 Feb;125(2):327-34. doi: 10.1542/peds.2008-2720. Epub 2010 Jan 18.
PubMed 20083526DiBattista A, McIntosh N, Lamoureux M, Al-Dirbashi OY, Chakraborty P, Britz-McKibbin P. Metabolic Signatures of Cystic Fibrosis Identified in Dried Blood Spots For Newborn Screening Without Carrier Identification. J Proteome Res. 2019 Mar 1;18(3):841-854. doi: 10.1021/acs.jproteome.8b00351. Epub 2019 Jan 7.
PubMed 30507207Fiandaca MS, Mapstone M, Mahmoodi A, Gross T, Macciardi F, Cheema AK, Merchant-Borna K, Bazarian J, Federoff HJ. Plasma metabolomic biomarkers accurately classify acute mild traumatic brain injury from controls. PLoS One. 2018 Apr 20;13(4):e0195318. doi: 10.1371/journal.pone.0195318. eCollection 2018.
PubMed 29677216Gessel LM, Fields SK, Collins CL, Dick RW, Comstock RD. Concussions among United States high school and collegiate athletes. J Athl Train. 2007 Oct-Dec;42(4):495-503.
PubMed 18174937Horn A, Ostwald D, Reisert M, Blankenburg F. The structural-functional connectome and the default mode network of the human brain. Neuroimage. 2014 Nov 15;102 Pt 1:142-51. doi: 10.1016/j.neuroimage.2013.09.069. Epub 2013 Oct 4.
PubMed 24099851Jonkman LE, Rosenthal DM, Sormani MP, Miles L, Herbert J, Grossman RI, Inglese M. Gray Matter Correlates of Cognitive Performance Differ between Relapsing-Remitting and Primary-Progressive Multiple Sclerosis. PLoS One. 2015 Oct 20;10(10):e0129380. doi: 10.1371/journal.pone.0129380. eCollection 2015.
PubMed 26485710Karlin AM. Concussion in the pediatric and adolescent population: "different population, different concerns". PM R. 2011 Oct;3(10 Suppl 2):S369-79. doi: 10.1016/j.pmrj.2011.07.015.
PubMed 22035679Kaut KP, DePompei R, Kerr J, Congeni J. Reports of head injury and symptom knowledge among college athletes: implications for assessment and educational intervention. Clin J Sport Med. 2003 Jul;13(4):213-21. doi: 10.1097/00042752-200307000-00004.
PubMed 12855923Kerr ZY, Register-Mihalik JK, Kroshus E, Baugh CM, Marshall SW. Motivations Associated With Nondisclosure of Self-Reported Concussions in Former Collegiate Athletes. Am J Sports Med. 2016 Jan;44(1):220-5. doi: 10.1177/0363546515612082. Epub 2015 Nov 18.
PubMed 26582799
Study at a glance
From the registry record, last updated by the sponsor on 15 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Correlating Advanced MRI Techniques With Neuropsychological Analysis and Immunosensing Assays for Assessment of Sport-related Mild Traumatic Brain Injuries (mTBI)
- ClinicalTrials.gov ID
- NCT05993351
- Acronym / sponsor ID
- Concussion MRI & recovery
- Conditions
- Concussion, Brain
- Keywords
- functional magnetic resonance imaging, diffusion tensor imaging, symptom tracking, sport-related concussions
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- St. Joseph's Healthcare HamiltonUniversity, hospital or other
- Collaborators
- McMaster University
- Study start
- 11 Aug 2023 (actual)
- Primary completion
- 15 Dec 2026 (estimated)
- Study completion
- 15 Dec 2026 (estimated)
- First posted
- 15 Aug 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Mild traumatic brain injury (mTBI), also referred to as concussions, affect millions of people around the world and can cause harmful long term effects. Unfortunately, concussions can be hard to diagnose and many people have lasting post-concussion symptoms such as headaches, difficulty concentrating, and light sensitivity. Recent studies have shown that advanced magnetic resonance imaging (MRI) techniques can identify subtle brain changes caused by a concussion. This study aims to track concussions over time measuring MRI brain scans and post-concussion symptoms to gain a better understand how the brain is affected in comparison to symptoms.
Detailed description
Mild traumatic brain injuries (mTBI) are a major health concern due to the risk of short and long-term complications. In order to understand the effects of an TBI (also referred to as a concussion), studies have examined the physiological and cognitive impact of concussions on the brains of youth and collegiate athletes. Based on athletic-exposure (AE), the most concussions in the National Collegiate Athletics Association (NCAA) occur in Men's wrestling, Men's and Women's ice hockey, Men's football, and Women's soccer (Zuckerman et al. 2015). It has been estimated that 300 000 sport-related concussions (SRC) occur annually in the United States among youth and collegiate athletes (Coronado et al. 2015; Gessel et al. 2007; Langlois et al. 2006; Thurman et al. 1998). However, a SRC estimate would likely be grossly underestimated due to underreporting and failure to seek medical treatment (Karlin 2011; Kaut et al. 2003; Kerr et al. 2016; McCrea et al. 2004; Roozenbeek et al. 2013). In reality, the number of annual SRC could be as high as 1.6 to 3.8 million occurrences (Langlois et al. 2006).
Brain injuries are classified as mild, moderate or severe based on patient reported symptoms, cognitive impairment and structural damage visualized using medical imaging (Bodin et al. 2012; DeCuypere and Kilmo 2012; DeMatteo et al. 2010; Roozenbeek et al. 2013). A major challenge facing mTBI diagnosis has been standardizing assessment, predicting prognosis, and clearing people to return to work or sport. In order to more accurately diagnose and treat patients, healthcare providers require a better understanding of how to brain is affected acutely, and the timeline for when it returns to a pre-concussion state. Recent technological innovations show promise to supplement the current behavioural and psychological assessments. Current concussion and mTBI diagnosis are often based on tests that assess a patient's sensory feedback, mental cognition, motor control, and post-concussion symptoms (Bodin et al. 2012; DeCuypere and Klimo 2012).
To supplement symptom tracking, magnetic resonance imaging (MRI) has been shown in research to be an invaluable concussion tool. The health of brain white matter can be predicted based on the relativistic shape of the myelin surrounding axons and the diffusivity of water along the length of the axons by using a MRI technique called diffusion tensor imaging (DTI)(Asken et al. 2018; Jonkman et al. 2015). In addition, the function of brain grey matter can be assessed using functional magnetic resonance imaging (fMRI) by measuring the paramagnetic differences between oxygenated and deoxygenated blood, based on the Blood-Oxygen Level Dependent (BOLD) signal (Horn et al. 2014; Liu et al. 2018; Ogawa et al. 1990). Activated brain regions have a greater BOLD signal due to magnetic field inhomogeneities caused by changes in blood volume, blood flow, and local metabolism (Ogawa et al. 1990). An fMRI can be used to analyze brain resting state activation patterns, a primary connective system is the Default Mode Network (DMN)(Mak et al. 2017). The DMN has been shown to have decreased activity following a mTBI (Bonnelle et al. 2011; Zhou et al. 2012).
A serious issue surrounding head injuries is the need for a method to diagnose athletes immediately following the injury. The growing interest in using metabolomics for the discovery of clinically relevant biomarkers associated with mild traumatic brain injury (mTBI) could be a solution. However, most studies to date have relied exclusively on blood specimens and/or targeted metabolite panels involving small cohorts of patients without adequate replication, and validation of aberrant metabolic changes in circulation to independent MRI-based brain imaging (Fiandaca et al. 2018; Orešič et al. 2016). We propose to include an analysis of fasting saliva and urine specimens from mTBI patients for comprehensive metabolite profiling using high throughput multi-segment injection-capillary electrophoresis-mass spectrometry technology (DiBattista et al. 2019; Yamamoto et al. 2019), which allows for rapid non-targeted analysis of polar/hydrophilic metabolites, as well as non-polar/ionic lipids with stringent quality control (Azab et al. 2019).
This study aims to track concussion recovery over 6-months using clinical standards of concussion symptoms and objective MRI and metabolomics metrics. Concussion participants will complete three study visits: acutely within 2-weeks of a concussion, 3-month follow-up and 6-month follow-up. Participants will be recruited from St. Joseph's Healthcare Hamilton and local athletic organizations. The study protocol will be identical for all three study visits. Participants will complete the Post-Concussion Symptom Scale (PCSS) and Depression Anxiety Stress Scale (DASS-42) to measure the presence and self-reported severity of common post-concussion symptoms. The MRI data will be used to measure brain function (resting state fMRI) and microstructural properties (diffusion tenor imaging), while the metabolomics will measure if metabolites have abnormal presence or concentration post-concussion based on urine and saliva samples. These quantitative methods will be compared to the subjective concussion symptom scores to identify if brain and physiological abnormalities persist past symptom resolution, and if certain brain regions are more frequently affected by concussion. It is hypothesized that across all three time points that brain function will have decreased BOLD signal fractal complexity and network connectivity (representative of concussion-related injuries), and white matter damage will be present based on the primary DTI metric of fractional anisotropy. It is also hypothesized that post-concussion symptoms will be self-reported as resolved or almost resolved by the 3-month follow-up study visit.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Concussion | – | Diagnostic Test: Magnetic resonance imaging (MRI), Diagnostic Test: Urine and saliva samples, Behavioral: QuestionnairesIndividuals who have recently sustained a concussion within the past 2-weeks. |
| Healthy Control | – | Diagnostic Test: Magnetic resonance imaging (MRI), Diagnostic Test: Urine and saliva samples, Behavioral: QuestionnairesIndividuals who have limited to no concussion history, and have not recently sustained a concussion. |
Who may qualify
- Ages
- 9 to 50 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult
- Study population
- Participants for this prospective observational cohort will include 50 individuals who have recently sustained a concussion within the last 2 weeks. Participants will primarily be recruited based on their involvement in collision or contact sport, causing sport-related concussions. Fifty healthy control participants will be recruited with the intention to have age, sex and athletic status matching to the concussion participants.
Key inclusion criteria (2 listed)
- Aged between 9-50
- Recently sustained a concussion (within the last 2 weeks)
Key exclusion criteria (14 listed)
- Aged 8 and younger or 51 and older
- Unable to provide consent (e.g., poor English language skills, etc.)
- History of liver or kidney disease
- MRI contraindications:
- Chronic/abusive use of alcohol and/or illicit drugs
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Magnetic resonance imaging (MRI)All participants will have 3 MRI scanning sessions to track brain health over time following the same protocol each time. The MRI sessions will occur acutely (<2 weeks post-concussion), 3-months and 6-months post-concussion. A series of MRI scans will be acquired including T1, T2, T2-FLAIR, SWI, ASL, rsfMRI, and DTI scans to characterize structural, microstructural, functional and tissue perfusion changes within the brain over time. | Diagnostic test | Concussion, Healthy Control |
| Urine and saliva samplesAt each study visit all participants will be asked to provide small urine and saliva samples for a metabolomic analysis using a high throughput multi-segment injection-capillary electrophoresis-mass spectrometry technology. This will allow for rapid non-targeted analysis of polar/hydrophilic metabolites, as well as non-polar/ionic lipids with stringent quality control. | Diagnostic test | Concussion, Healthy Control |
| QuestionnairesThe Post-Concussion Symptom Scale (PCSS) and the Depression Anxiety Stress Scale (DASS-42) will be used to assess the self-reported presence and severity of known concussion-related symptoms. | Behavioural | Concussion, Healthy Control |
Primary outcome
Functional brain characteristics
Time frame: 45-minute MRI sessions acutely, 3-months and 6-months post-concussion
Brain function will be examined based on the network connectivity and fractal complexity of the rsfMRI BOLD signal. This will be measured across known brain networks (e.g., Default Mode Network) and specific regions-of-interest (e.g., insula).
Microstructural brain characteristics
Time frame: 45-minute MRI sessions acutely, 3-months and 6-months post-concussion
Microstructural brain changes will be examined based on diffusion tensor imaging (DTI) metrics of fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. This will be measured within specific regions-of-interest (e.g., insula).
Post-concussion symptoms
Time frame: Acutely, 3-months and 6-months post-concussion
Tracking of self-reported post-concussion symptoms using PCSS and DASS-42 questionnaires
1 secondary outcome
Metabolomics
Time frame: Acutely, 3-months and 6-months post-concussion
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 May 2025.
- Background: PubMed 28337734Asken BM, DeKosky ST, Clugston JR, Jaffee MS, Bauer RM. Diffusion tensor imaging (DTI) findings in adult civilian, military, and sport-related mild traumatic brain injury (mTBI): a systematic critical review. Brain Imaging Behav. 2018 Apr;12(2):585-612. doi: 10.1007/s11682-017-9708-9.
- Background: PubMed 30570251Azab S, Ly R, Britz-McKibbin P. Robust Method for High-Throughput Screening of Fatty Acids by Multisegment Injection-Nonaqueous Capillary Electrophoresis-Mass Spectrometry with Stringent Quality Control. Anal Chem. 2019 Feb 5;91(3):2329-2336. doi: 10.1021/acs.analchem.8b05054. Epub 2019 Jan 7.
- BackgroundBodin, D., Yeates, K. O., & Klamar, K. (2012). Definition and Classification of Concussion. In J. N. Apps & K. D. Walter (Eds.), Pediatric and Adolescent Concussion (pp. 9-19). New York, NY: Springer New York. https://doi.org/10.1007/978-0-387-89545-1_2
- Background: PubMed 21940437Bonnelle V, Leech R, Kinnunen KM, Ham TE, Beckmann CF, De Boissezon X, Greenwood RJ, Sharp DJ. Default mode network connectivity predicts sustained attention deficits after traumatic brain injury. J Neurosci. 2011 Sep 21;31(38):13442-51. doi: 10.1523/JNEUROSCI.1163-11.2011.
- Background: PubMed 25955705Coronado VG, Haileyesus T, Cheng TA, Bell JM, Haarbauer-Krupa J, Lionbarger MR, Flores-Herrera J, McGuire LC, Gilchrist J. Trends in Sports- and Recreation-Related Traumatic Brain Injuries Treated in US Emergency Departments: The National Electronic Injury Surveillance System-All Injury Program (NEISS-AIP) 2001-2012. J Head Trauma Rehabil. 2015 May-Jun;30(3):185-97. doi: 10.1097/HTR.0000000000000156.
- Background: PubMed 22850156Decuypere M, Klimo P Jr. Spectrum of traumatic brain injury from mild to severe. Surg Clin North Am. 2012 Aug;92(4):939-57, ix. doi: 10.1016/j.suc.2012.04.005. Epub 2012 Jun 5.
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- Individual participant dataSharing planned: Undecided. Study data may be shared upon request to the research team.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Ethan Danielli, PhD contact
Michael D Noseworthy, PhD, PEng principal investigator
McMaster University
Dinesh A Kumbhare, MD, PhD principal investigator
University Health Network, Toronto
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Concussion, Brain, run by St. Joseph's Healthcare Hamilton at 1 site in Canada.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 14 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 15 May 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Canada. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Michael D Noseworthy, PhD, PEng (905.525.9140 ext. 23727, nosewor@mcmaster.ca), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Functional brain characteristics (time frame: 45-minute MRI sessions acutely, 3-months and 6-months post-concussion). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05993351, which also lists 26 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 May 2025.