Looking for Students in Engineering, Science or Health Science
Two opportunities are available to students
First Research Opportunity
Through Prof. Linda McLean’s NSERC Discovery Grant and equipment recently purchased through the NSERC RTI program, we have begun an exciting new direction of research based on our capacity to investigate mechanical tissue properties in-vivo using ultrasound Shear Wave Elastography (SWE). This capacity has catalyzed a new collaboration with Obstetricians and Gynaecologists at the Ottawa Hospital, who are interested in being able to determine the state of degeneration of uterine fibroid masses as a means of determining the best approach to management (ie. medical or surgical) and, when appropriate, the best surgical approach to use. This work is in the early stages. An important first step is to validate our in-vivo method of determining the stiffness characteristics of healthy uterine tissue and uterine fibroid masses against the mechanical properties of these tissues ex-vivo.
For this validation, we will work collaboratively with our medical partners. In women who are scheduled for complete or partial hysterectomy, we will image the uterus using SWE to determine the stiffness characteristics of regions of healthy tissue as well as select uterine fibroid masses. We will then receive samples of healthy uterine tissue and uterine fibroid masses from these same regions after the tissues have been surgically removed. We will test the mechanical properties of these tissues using cyclic uniaxial tension. We will plot the estimates of tissue stiffness from SWE against the stiffness measured ex-vivo to determine the strength of the association between the two approaches.
Student Role
Under Prof. McLean’s direct mentorship the student will be trained on tissue mechanical testing and will develop and test methods to secure the tissue samples using 3D print technology. The student will then first perform validation tests using animal tissues to ensure that all methods are feasible. The student will then assist with data collection on the tissue samples generated through the protocol described above and will generate a validation model as an MSc thesis.
Please contact professors Catherine Mavriplis and Linda McLean : Catherine.Mavriplis@uottawa.ca; Linda.Mclean@uottawa.ca
Second Research Opportunity
Through Prof. Linda McLean’s NSERC Discovery Grant program, we have been building a software, UROKIN, that uses semi-automated segmentation of 2D ultrasound video to evaluate urethral kinematics associated with pelvic floor muscle function in women. This semi-automated process is very time and labour intensive – as it still requires frame-by-frame user input to identify or verify landmarks of interest. We aim to make this process more efficient through two separate and concurrent approaches. First we plan to continue to optimize the automated software to reduce the need for user input. Second, we plan to complete an evaluation of the power spectral density curves computed for a series of different relevant landmarks and during three distinct tasks- voluntary contraction, coughing, and Valsalva maneuver. Through acquiring a new data set from 10 women who perform three repetitions of a voluntary pelvic floor muscle contraction, a cough and a bearing down maneuver, and through using our semi-automated software, we will analyze each frame of each video to generate relevant kinematic curves. We will then compute the power spectrum of each curve to determine the maximum frequency seen in the signal, which will, in turn, be used to determine what the minimum frame rate should be based on the Nyquist Theorem. Based on our experience using our semi-automated software to date, we anticipate that the maximum frequency in the different curves will be approximately 4 Hz and as such we will be able to reduce or image processing to roughly 8 frames per second, cutting data processing time by a factor of three without sacrificing relevant kinematic information. If our hypothesis is correct, then we will add an algorithm to our program that will down-sample the video data accordingly.
Student Role
Under Prof. McLean’s direct mentorship, one MSc student will assist with data collection and then lead the image processing and analysis. In particular, the student will compute kinematic curves (ie. acceleration, velocity and displacement of each relevant landmark), compute the associated power spectra, and determine the Nyquist rate. This rate will, in turn, be integrated as the frame rate used by the UROKIN software.
Please contact professors Catherine Mavriplis and Linda McLean : Catherine.Mavriplis@uottawa.ca; Linda.Mclean@uottawa.ca
