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Études médicales de premier cycle - EMPC

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Nombre de bourses offertes à la Faculté de médecine

372 135

Somme qui a été remise en bourses à l’automne 2023 aux étudiants en médecine de la première à la quatrième année

198

Nombre de récipiendaires à l’automne 2023

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Plusieurs bourses en cours d’études viendront à échéance le 30 septembre. La date de clôture pour les bourses du premier terme est le 31 octobre, alors que les bourses du deuxième terme viendront à échéance le 28 février ou le 31 mars. Il est recommandé de vérifier la liste des bourses disponibles régulièrement au cas où il y aurait eu des ajouts.

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Bourses offertes à la Faculté de médecine

Nous remercions tous les donateurs de leurs contributions. Leur soutien aidera nos étudiants, la prochaine génération de médecins, à bâtir un monde plus sain. Grâce à eux, il nous est possible de proposer plusieurs bourses à la Faculté de médecine.

Objectif du fonds

Offrir une bourse à des étudiantes et étudiants dans le programme de MD qui travaillent sur un projet au Département de radiologie pendant l’été.

Admissibilité

La personne candidate doit:

être citoyenne canadienne, résidente permanente, personne à statut protégé/réfugié ou étudiante internationale;
être inscrite à temps plein au premier cycle à la Faculté de médecine de l’Université d’Ottawa; et
avoir l’intention de participer à un projet de recherche d’été (exigeant un minimum de 8 semaines de travail à 37,5 heures par semaine) au Département de radiologie.

Note : L’horaire de travail sera décidé par la personne récipiendaire, le chercheur ou la chercheuse et le Département.

Valeur de la bourse : 4 000 $ (allouée en trois paiements : 1 000 $ au début du placement, 1 500 $ à la moitié du placement, et 1 500 $ à la fin du placement)

Nombre de bourses : 3

Fréquence d’attribution : Annuelle

Échéance des demandes : 31 mars

Demande:

La demande doit être soumise par l’entremise de Bourses en ligne, accessible une fois connecté au portail uoZone, et doit comprendre:

le Curriculum vitae sur Bourses en ligne;
une copie non-officielle du relevé de notes de la personne candidate;
le formulaire de demande étudiante dans lequel la personne candidate doit détailler sa motivation pour participer à cette opportunité, ses intérêts de recherche et son classement des propositions de recherche en fonction de son propre intérêt.

Propositions de recherche du Département d’imagerie médicale pour 2024 :

Note : les descriptifs sont disponibles en anglais seulement.

Description:

On March 11, 2020 the WHO declared the COVID-19 outbreak a global pandemic. As a result, BC screening in Ontario was halted between March 13, 2020-June 4, 2020. At TOH, we have seen a surge in the number of BCs diagnosed in the first two-years post pandemic (37% increase) with more late-stage BC at diagnosis (43% increase) which equates to lower overall survival (1–7) . Modelling predicts that this surge will continue over the coming years with cumulative excess cancer deaths from BC continuing to rise beyond 2030 (8). Understanding the delayed impacts of the COVID-19 pandemic on BC diagnosis at TOH is integral to inform the necessary changes to existing infrastructure and resources available to accommodate this surge.

Hypothesis:

There continues to be an increase in symptomatic and later stage breast cancers at diagnosis at TOH in the fourth-year post pandemic.

Specific Objective(s):

To determine the incidence of symptomatic breast cancers and the stage at BC diagnosis at TOH over a one-year period (fourth year (Y4) post pandemic).
Compare this data with existing data for a pre-COVID cohort and post-COVID Y1-Y3 to determine the ongoing impacts of the pandemic on BC outcomes at our hospital.

Brief Methods:

A retrospective review of all biopsy-proven BCs at our institution over a one-year period will be conducted (June 1, 2023-May 31 2024 – post-pandemic Y4). Patient age, presentation (screen detected versus symptomatic) and cancer stage will be collected. Comparison will be made to an existing data set for a pre-COVID cohort and post-COVID Y1-3.

Student skills required:

Basic excel skills, an understanding of the scientific method, ability to conduct a literature review and an interest in publication.

Potential skills developed:

Opportunity to work with staff radiologists, to gain a better understanding of the OBSP and to learn the process of data collection, manuscript creation and publication of scientific journal articles.

Timeline:

Data collection completed by Aug 2024, Data analysis/manuscript preparation Fall 2024.

Benefit to researcher/professor:

To teach students about breast imaging and screening programs and the importance of detection and diagnosis of early-stage breast cancers. To inspire trainees to pursue academic medicine and contribute to the scientific body of knowledge.

Matching funding:

References:

Joensuu H, Asola R, Holli K, Kumpulainen E, Nikkanen V, Parvinen LM. Delayed diagnosis and large size of breast cancer after a false negative mammogram. Eur J Cancer. 1994 Jan;30(9):1299–302.
Montella M, Crispo A, DʼAiuto G, De Marco M, de Bellis G, Fabbrocini G, et al. Determinant factors for diagnostic delay in operable breast cancer patients: Eur J Cancer Prev. 2001 Feb;10(1):53–9.
Ojala K, Meretoja TJ, Mattson J, Salminen-Peltola P, Leutola S, Berggren M, et al. The quality of preoperative diagnostics and surgery and their impact on delays in breast cancer treatment – A population based study. The Breast. 2016 Apr;26:80–6.
Richards M, Westcombe A, Love S, Littlejohns P, Ramirez A. Influence of delay on survival in patients with breast cancer: a systematic review. The Lancet. 1999 Apr;353(9159):1119–26.
Dinmohamed AG, Cellamare M, Visser O, de Munck L, Elferink MAG, Westenend PJ, et al. The impact of the temporary suspension of national cancer screening programmes due to the COVID-19 epidemic on the diagnosis of breast and colorectal cancer in the Netherlands. J Hematol OncolJ Hematol Oncol. 2020 Dec;13(1):147.
Seely JM, Scaranelo AM, Yong-Hing C, Appavoo S, Flegg C, Kulkarni S, et al. COVID-19: Safe Guidelines for Breast Imaging During the Pandemic. Can Assoc Radiol J. 2020 Nov;71(4):459–69.
Sud A, Jones ME, Broggio J, Loveday C, Torr B, Garrett A, et al. Collateral damage: the impact on outcomes from cancer surgery of the COVID-19 pandemic. Ann Oncol. 2020 Aug;31(8):1065–74.
Yong JH, Mainprize JG, Yaffe MJ, Ruan Y, Poirier AE, Coldman A, et al. The impact of episodic screening interruption: COVID-19 and population-based cancer screening in Canada. J Med Screen. 2021 Jun;28(2):100–7.

Description:

Risk assessment is a key tool for personalized screening and early detection of breast cancer. In recent work¹, the MIT (Massachusetts Institute of Technology) team developed deep learning models that assess cancer risk from full-resolution screening mammograms and found them to be significantly more accurate than the Tyrer-Cuzick model, identified in the top risk decile by the Hybrid DL model were at 3.8x higher risk than the average woman compared to 1.9x by the Tyrer-Cuzick model. Since this publication, the MIT team has significantly improved the model and extended it to jointly predict the risk of future cancer at one to five years away from the mammogram². Moreover, they have also developed a new model for risk-based screening recommendations and found it to outperform traditional age-based screening guidelines in retrospective simulations.

Purpose and objectives:

The primary aim of this study is the measure the discriminative performance of the developed risk models on the Ontario Breast Screening Program (OBSP) screening population.

Our secondary aim is to quantify the performance of learned personalized screening recommendations in retrospective analysis. This study will be a retrospective chart review analyzing the charts and mammograms of any female patient who had a screening mammogram from 1/1/2012 to 12/31/2016.

Hypothesis:

Women with the top risk decile by the Hybrid DL model will have a higher cancer detection rate than women in the lower risk decile, thus better predicting breast cancer development and risk assessment than currently exists in the OBSP.

Specific Objective(s):

We will evaluate all women diagnosed with breast cancer within the OBSP program within 2012-2016 to determine how well the Hybrid DL model performed in prediction of breast cancer.

Brief Methods: Analyses of results

To measure the accuracy of each risk model, we will measure the concordance index of the predictions with the provided outcomes on the retrospective data as well at the ROC AUCs at one to five years from the time of the mammogram. To measure the simulated performance of risk-based screening, we will measure relative screening volume under simulated screening guidelines as well as shifts in diagnosis time. We will assess confidence intervals using a clustered-bootstrap procedure. To facilitate this work, we will collect the risk assessment and outcomes for each anonymized patient ID, and this data will be sent to MIT to complete the analysis. Note, no images or identifiable information will be sent to MIT.

MIT will analyze the data as follows:

Data Collection and Computer Setup
Hampton Park TOH team will prepare the dataset as well as a computing environment.
Analysis of Risk models on Screening Cohort
Using on premise computing at Hampton Park TOH and a virtual private network, the MIT team will process data and compute risk assessments. Given the risk assessments and outcomes, the MIT team will evaluate the performance of different image based risk models.
Analysis of Screening guidelines on Screening Cohort
MIT team will compute simulated impact of risk-based screening for different risk models on screening cohort.

Student skills required:

The student will be required to review patients in EPIC, have Excel and Word skills, be able to review using PACS, and collaborate with the research staff to complete tasks. Prior research collaboration and skills would be an asset.

Potential skills developed:

The student would learn about the imaging for cancer detection, the performance indicators for high quality work in breast imaging, the importance of Artificial intelligence in Radiology, as well as joining a collaborative team of researchers dedicated to early detection of breast cancer.

Timeline:

The project would begin May 1, 2024, and completed by August 31, 2024, with the possibility of data analysis continuing into the fall.

Benefit to researcher/professor:

I am interested in mentoring a medical student who is interested in research in Radiology and Breast Imaging, and to collaborate with them on a project that may improve the quality of breast cancer risk assessment and allow greater access to early detection of breast cancer.

Matching funding:

References:

Yala A, Lehman C, Schuster T, Portnoi T, Barzilay R. A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction. Radiology. 2019;292:60-66. doi: 10.1148/radiol.2019182716
Yala A, Mikhael PG, Strand F, Lin G, Satuluru S, Kim T, Banerjee I, Gichoya J, Trivedi H, Lehman CD, et al. Multi-Institutional Validation of a Mammography-Based Breast Cancer Risk Model. J Clin Oncol. 2022;40:1732-1740. doi: 10.1200/jco.21.01337

Description:

Whole body MRI is a promising biomarker for the diagnosis and treatment follow-up of patients with neuromuscular diseases (NMD), including OPMD. Our neuromuscular imaging research group has a standing NMD research grant and institutional REB approval to study MRI as a biomarker for patients with OPMD. We currently employ a dedicated protocol to assess NMD, including STIR and DWI sequences (intended to assess active myopathy), as well as DIXON sequences (to assess trophism and muscle fat fraction, which are markers of disease chronicity). The ADC (Apparent diffusion coefficient) is derived from the DWI sequence and measures the magnitude of diffusion of water molecules within the tissues. It has been shown that DWI imaging can be helpful in muscle disorders comprising inflammation and myopathies. The correlation between DWI, ADC and STIR in the context of OPMD remains undetermined. This project intends to add to the field by studying these correlations.

Hypothesis:

Patients with active NMD present direct correlation between the signal intensity of muscles in STIR and DWI, with decrease in the ADC.

Specific Objective(s):

Determine the feasibility of co-registration of regions of interest (ROIs) between the different sequences of the NMD whole-body MRI protocol.
Correlate the results of STIR, DWI, ADC and clinical parameters in patients with OPMD

Brief Methods:

We will co-register the whole-body DWI and ADC imaging data to the in/out phase DIXON gradient echo data.
The ROIs derived from existing fat-fraction analysis will be evaluated on the ADC maps to derive quantitative diffusion values for each of the muscles.
The diffusion outcomes will be compared to the fat-fraction and clinical parameters in patients with OPMD.
Likewise, the STIR and DWI images of the whole muscles will be assessed subjectively semi-quantitatively and the result compared to the ADC and clinical parameters.

Student skills required:

High interest in MRI and research in diagnostic imaging.
Ability to work in a multidisciplinary team.
Fluency in imaging and data processing skills are highly valued for this project.

Potential skills developed:

The research will be performed at the Department of Medical Imaging and at the NeuroMuscular Centre at Ottawa Hospital, where the student will receive training in research and analytic methods, preparation of scientific manuscripts, and detailed career mentoring on clinical research, perform data analysis and present data (written and oral). Specific skills to be gained with this project include: anatomical knowledge of muscles, clinical knowledge on NMD, MRI science and clinical applications, use of computational tools for muscle segmentation, data extraction and complex data processing.

Timeline:

Introduction to NMD MRI and muscle segmentation (~1 week);
ROI co-registration pipeline development (~1 week);
Data extraction and preparation (~2 weeks);
Datasheet preparation for quantitative analysis and semi-quantitative analysis/reading (~1 week);
Data analysis and interpretation (~ 2 weeks). Abstract, presentation and manuscript preparation will follow.

Benefit to researcher/professor:

The neuromuscular imaging research group has different ongoing projects with radiology residents and students. The possibility of having a dedicated medical student to conduct and help with this project will foster the development of our future clinical and research protocols to advance in the mission of using MRI as a meaningful biomarker for neuromuscular and muscular disorders.

Matching funding:

References:

Melkus G, Sampaio ML, Smith IC, Rakhra KS, Bourque PR, Breiner A, Zwicker J, Lochmüller H, Brais B, Warman-Chardon J. Quantitative vs qualitative muscle MRI: Imaging biomarker in patients with Oculopharyngeal Muscular Dystrophy (OPMD). Neuromuscul Disord. 2023 Jan;33(1):24-31. doi: 10.1016/j.nmd.2022.09.010. Epub 2022 Oct 2. PMID: 36462961.
Warman Chardon J, Straub V. The Role of Muscle Imaging in the Diagnosis and Assessment of Children with Genetic Muscle Disease. Neuropediatrics 2017;48:233-241.
Dahlqvist JR, Widholm P, Leinhard OD, Vissing J. MRI in Neuromuscular Diseases: An Emerging Diagnostic Tool and Biomarker for Prognosis and Efficacy. Ann Neurol 2020;88:669-681.
Alonso-Jimenez A, Kroon R, Alejaldre-Monforte A, et al. Muscle MRI in a large cohort of patients with oculopharyngeal muscular dystrophy. Journal of neurology, neurosurgery, and psychiatry 2019;90:576-585.
Michoux, N.F., Ceranka, J.W., Vandemeulebroucke, J. et al. Repeatability and reproducibility of ADC measurements: a prospective multicenter whole-body-MRI study. Eur Radiol 31, 4514–4527 (2021). https://doi.org/10.1007/s00330-020-07522-0
Yanagisawa O, Shimao D, Maruyama K, Nielsen M, Irie T, Niitsu M. Diffusion-weighted magnetic resonance imaging of human skeletal muscles: gender-, age- and muscle-related differences in apparent diffusion coefficient. Magn Reson Imaging. 2009 Jan;27(1):69-78. doi: 10.1016/j.mri.2008.05.011. Epub 2008 Jul 22. PMID: 18650046.
Fischmann A, Hafner P, Fasler S, et al. Quantitative MRI can detect subclinical disease progression in muscular dystrophy. Journal of neurology 2012;259:1648-1654.
Lassche S, Küsters B, Heerschap A, et al. Correlation Between Quantitative MRI and Muscle Histopathology in Muscle Biopsies from Healthy Controls and Patients with IBM, FSHD and OPMD. Journal of neuromuscular diseases 2020;7:495-504.
Schlaffke L, Rehmann R, Rohm M, et al. Multi-center evaluation of stability and reproducibility of quantitative MRI measures in healthy calf muscles. NMR in biomedicine 2019;32:e4119.

Description:

Magnetic resonance spectroscopy (MRS) has emerged as a non-invasive tool to detect 2-hydroxyglutarate (2-HG), a biomarker of IDH mutation¹. Additional metabolites such as myoinostol cystathionine, glycine and glutamine have been recently found in specific subtypes of gliomas with MRS². MR perfusion is an established technique which allows measurement of the cerebral blood volume (rCBV), a biomarker of angiogenesis, which is seen with high grade gliomas³.

Hypothesis:

In addition to conventional MRI, MRS and MR perfusion might help in improving the accuracy of preoperative MRI in determining glioma subtype and grade.

Specific Objective(s):

To assess the diagnostic accuracy of MRS and MR perfusion in the preoperative identification of the molecular status and grading of gliomas

Brief Methods:

Each patient will undergo a preoperative MRI exam including MR perfusion and MRS. MRS data will be processed using the LC model to quantify the presence of different tumor metabolites. MR perfusion data will be processed using a commercial software (Olea) to derive the tumor cerebral blood volume. Following surgery, the tumor will be graded using histopathology +/- DNA sequencing. Differences in the imaging parameters between different glioma subtypes will be assessed using a non parametric test. A receiver operating curve will be performed for each parameter to assess its diagnostic accuracy in identifying a tumor subtype.

Student skills required:

The student should be familiar with computers in general, particularly with the Excel software. He/she is expected to learn how to process MRI data using image processing softwares. Programming skills are not required.

Potential skills developed:

The student will learn about neuroimaging and will be able to recognize different MR images. He/she will also learn about image processing of MR data. He/she will be working in the MR physics lab at the Ottawa General Hospital under the supervision of a neuroradiologist, neuroradiology fellow and a MR physicist.

Timeline:

The student will be expected to work during the summer starting in May or early June. It is estimated that it will take 10 weeks to complete the data analysis and to a draft an abstract.

Benefit to researcher/professor:

I have supervised medical students in the past and have found it rewarding. Their curiosity, ability to learn fast and high motivation can really help advance the project.

Matching funding:

Yes

References:

Branzoli F, Di Stefano AL, Capelle L, Ottolenghi C, Valabrègue R, Deelchand DK, Bielle F, Villa C, Baussart B, Lehéricy S, Sanson M, Marjanska M. Highly specific determination of IDH status using edited in vivo magnetic resonance spectroscopy. Neuro Oncol. 2018 Jun 18;20(7):907-916.
Keunen O, Niclou SP. Is there a prominent role for MR spectroscopy in the clinical management of brain tumors? Neuro Oncol. 2020 Jul 7;22(7):903-904. doi: 10.1093/neuonc/noaa098. PMID: 32291457; PMCID: PMC7339882.
Zakhari N, Taccone MS, Torres CH, Chakraborty S, Sinclair J, Woulfe J, Jansen GH, Cron GO, Thornhill RE, McInnes MDF, Nguyen TB. Prospective comparative diagnostic accuracy evaluation of dynamic contrast-enhanced (DCE) vs. dynamic susceptibility contrast (DSC) MR perfusion in differentiating tumor recurrence from radiation necrosis in treated high-grade gliomas. J Magn Reson Imaging. 2019 Aug;50(2):573-582. doi: 10.1002/jmri.26621. Epub 2019 Jan 5. PMID: 30614146.

Description:

Our study explores the clinical utility of neck Computed Tomography Angiography (CTA) in cases of blunt cervical trauma, assaults, and strangulation. Blunt cervical trauma, especially from assaults and strangulation, can lead to the rare yet severe condition known as blunt cerebrovascular injury (BCVI), which may result in complications like stroke, disability, and death.

Hypothesis:

The hypothesis is that neck CTA is valuable in identifying BCVI in cases of blunt cervical trauma, assaults, and strangulation, and that its improved indication, performance, and accuracy can lead to better patient outcomes.

Specific Objectives:

Investigate the clinical utility of neck CTA in these cases.
Assess neck CTA's ability to identify BCVI in such scenarios.
Evaluate the relationship between trauma severity and CTA yield.

Brief Methods:

Retrospective cohort study covering cases of 10 years involving patients with blunt cervical trauma who underwent neck CTA. Data will be collected from CTA images, reports, and clinical presentations. Statistical analysis will include descriptive statistics, correlation analysis, and multivariate logistic regression.

Student skills required:

Skills in data collection and data analysis.
Collaborative skills and the ability to work with medical records and imaging software will be beneficial.

Potential skills developed:

Working on this research project will provide students with valuable experience in clinical research, data analysis, and evidence-based medicine. They will gain expertise in interpreting medical records and radiological images, contributing to evidence-based guidelines, and understanding the practical implications of research in a clinical setting. The research environment will involve collaboration with medical professionals and access to medical databases and imaging systems.

Timeline:

8 to 12 weeks.

Benefit to researcher/professor:

This project provides an opportunity to enhance patient care by offering evidence-based recommendations for neck CTA use in blunt cervical trauma, assaults, and strangulation cases. Additionally, it may lead to publications, collaborations, and clinical guideline development, further enhancing the researcher's academic and professional profile.

Matching funding:

Yes

References:

Harper, P. R., Jacobson, L. E., Sheff, Z., Williams, J. M., & Rodgers, R. B. (2022). Routine CTA screening identifies blunt cerebrovascular injuries missed by clinical risk factors. Trauma Surgery and Acute Care Open, 7(1). https://doi.org/10.1136/tsaco 2022-000924
Fietz, D. (2021). Non-fatal strangulation and the gold coast forensic medicine clinical and legal experience. Pathology, 53. https://doi.org/10.1016/j.pathol.2021.05.035
Black, J. A., Abraham, P. J., Abraham, M. N., Cox, D. B., Griffin, R. L., Holcomb, J. B., Hu, P. J., Kerby, J. D., Liptrap, E. J., Thaci, B., Harrigan, M. R., & Jansen, J. O. (2021). Universal screening for blunt cerebrovascular injury. Journal of Trauma and Acute Care Surgery, 90(2). https://doi.org/10.1097/TA.0000000000003010
Wynn, M. S., Kesler, K. K., Bertroche, E., Pugely, A. J., & Igram, C. (2021). Patient specific predictive factors of vertebral artery injury following blunt cervical spine trauma. Clinical Neurology and Neurosurgery, 210. https://doi.org/10.1016/j.clineuro.2021.106988
Schellenberg, M., Inaba, K., Warriner, Z., Alfson, D., Roman, J., van Velsen, V., Lam, L., & Demetriades, D. (2019). Near hangings: Epidemiology, injuries, and investigations. Journal of Trauma and Acute Care Surgery, 86(3). https://doi.org/10.1097/TA.0000000000002134
Lockwood, M. M., Smith, G. A., Tanenbaum, J., Lubelski, D., Seicean, A., Pace, J., Benzel, E. C., Mroz, T. E., & Steinmetz, M. P. (2016). Screening via CT angiogram after traumatic cervical spine fractures: Narrowing imaging to improve cost effectiveness. Experience of a Level I trauma center. Journal of Neurosurgery: Spine, 24(3). https://doi.org/10.3171/2015.6.SPINE15140

Description:

Carotid atherosclerotic disease constitutes a major health problem and is an established risk factor of ischemic stroke. Presently risk stratification of patients based on the degree of carotid artery stenosis is used to guide management. However increasingly evidence has shown that plaque characteristics such as plaque composition, and surface morphology (i.e. Ulceration, surface irregularity, calcification, Lipid rich necrotic core (LR-NC) and intraplaque hemorrhage) play an important role in the occurrence of symptoms. The aim of this study is to evaluate carotid plaque characteristics with CT angiography in ischemic stroke patients. Most plaque characteristics studies are performed using MR but not on CTA that all patients with suspected stroke undergo on admission.

Hypothesis:

We will test the hypothesis that the characteristics of carotid plaque are additional predictors of ischemic strokes in cases with no significant stenosis.

Specific Objective:

Density measurement and surfacecharacteristics assessment of carotid plaque with comparison with a control group.

Brief Methods:

Ischemic stroke patients at TOH from the past 5 years with confirmed thrombus will be evaluated for the presence of atherosclerotic plaque, degree of stenosis, the presence of plaque ulceration and other characteristics. Plaque volume and plaque component proportions of LR-NC, and calcification will be measured. Exclusion criteria includes patients with >70% stenosis and patients with cardiac risk factors (i.e. atrial fibrillation). The uninvolved side will be used as control.

Student skills required:

Searching and using PACS and training will be given for image analysis using Aquarius platform.

Potential skills developed:

You will be involved in searching PACS and our database of acute stroke patients, creating list of study patients and gathering clinical data, outcome data; help processing CT angiogram for density analysis of carotid plaques; and some preliminary analysis. You will also be able to understand the care pathway for acute stroke patients.

Timeline:

1 year

Benefit to researcher/professor:

mage processing and measurement help. Also, an opportunity to mentor students interested in Radiology.

Matching funding:

Yes, partial funding possible.

Faire une demande de bourses d’études

Étapes à suivre

Questionnaire financier

Dates importantes

Bourses offertes à la Faculté de médecine

Propositions de recherche du Département d’imagerie médicale pour 2024 :

Ongoing impact of the COVID-19 pandemic on breast cancer (BC) method of detection and stage at diagnosis at The Ottawa Hospital (TOH) arrow_drop_down

Description:

Hypothesis:

Specific Objective(s):

Brief Methods:

Student skills required:

Potential skills developed:

Timeline:

Benefit to researcher/professor:

Matching funding:

References:

Using Mammographic Images in Conjunction with Other Risk Factors to determine the Risk of Breast Cancer arrow_drop_down

Description:

Purpose and objectives:

Hypothesis:

Specific Objective(s):

Brief Methods: Analyses of results

Student skills required:

Potential skills developed:

Timeline:

Benefit to researcher/professor:

Matching funding:

References:

Evaluation of whole-body diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) in muscles of patients with OPMD (oculopharyngeal muscle dystrophy) arrow_drop_down

Description:

Hypothesis:

Specific Objective(s):

Brief Methods:

Student skills required:

Potential skills developed:

Timeline:

Benefit to researcher/professor:

Matching funding:

References:

Magnetic resonance spectroscopy and MR perfusion as a non-invasive tool to diagnose and monitor gliomas arrow_drop_down

Description:

Hypothesis:

Specific Objective(s):

Brief Methods:

Student skills required:

Potential skills developed:

Timeline:

Benefit to researcher/professor:

Matching funding:

References:

Value of CT neck angiography in the assessment of blunt cerebrovascular injury (BCVI) in the setting of Blunt Cervical Trauma, Assaults and Strangulation arrow_drop_down

Description:

Hypothesis:

Specific Objectives:

Brief Methods:

Student skills required:

Potential skills developed:

Timeline:

Benefit to researcher/professor:

Matching funding:

References:

Carotid plaque assessment by CT in stroke patients with no significant stenosis arrow_drop_down

Description:

Hypothesis:

Specific Objective:

Brief Methods:

Student skills required:

Potential skills developed:

Timeline:

Benefit to researcher/professor:

Matching funding:

Fonds de conférences médicales étudiantes de la Société d’Esculape arrow_drop_down

Bourse Amanda Kelsall arrow_drop_down

Bourse commémorative Antonio (Tony) Tavares arrow_drop_down

Bourse d’études de la famille Aubert-Gravelle arrow_drop_down

Bourse d'échange Canada-Afrique arrow_drop_down

Bourse de la famille Caron-Deschamps pour les étudiants de la Faculté de médecine arrow_drop_down

Admissibilité