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Graduate Seminar Series: Clinical Stream – Craig Macsemchuk

April 12, 2023 @ 12:30 pm - 1:00 pm EDT

Graduate Seminar Series: Clinical Stream
Graduate Seminar Series for the Institute of Biomedical Engineering (BME). This day is for clinical stream presenters.
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Presentation Title: A Magnetic Resonance Imaging Guided High Intensity Focused Ultrasound Platform for Fetal Interventions
Abstract:
Background:
Congenital abnormalities cause 20% of all perinatal deaths in North America, where some
require fetal intervention to improve outcomes . Due to routine ultrasound imaging during
pregnancy, most fetal anomalies are detected before birth; however, many are progressive before
birth, leading to fetal death . All current options for fetal therapy involve entering the
amniotic sac for surgical procedures, which carry a significant risk of premature birth due to
membrane rupture . Ultrasound energy creates no incision and is non-ionizing, therefore, it
reduces the risk of infection and does not damage adjacent non-targeted tissues. These attributes
make it an ideal modality for fetal surgical interventions. Magnetic resonance-guided high
intensity focused ultrasound (MRgHIFU) is a non-invasive therapy modality that is clinically
approved in Canada to treat uterine fibroids, bone metastasis and essential tremor. All currently
available MRgHIFU devices generate ultrasound energy from a transducer integrated into a
purpose-built MRI table. This ultrasound energy source transmits upward, focusing into the
patient, and creating a thermal lesion as small as a grain of rice (8x2x2mm). This focal point can
be mechanically and electronically steered to cover a large treatment volume. However, in these
approved devices, the ultrasound energy sources are situated so they cannot accommodate a
pregnant mother and therefore are not conducive to an ergonomically feasible or safe treatment
of fetuses. A pregnant mother cannot lay on her stomach in a prone position. Such is the rational
for developing an MRgHIFU robot that brings the ultrasound energy source to the pregnant
mother inside an MRI scanner in such a way that she can lay on her back in a supine position.
Objective and Hypothesis:
The objective of this project is to design and build an MRgHIFU robot for fetal interventions
that can accommodate a pregnant mother. My hypothesis is that robotic positioning of
ultrasound energy will demonstrate that MRIgHIFU is safe, effective, and feasible for treating
congenital fetal defects.
Methods:
I will achieve my objective by: 1) Designing and developing an MRgHIFU platform for fetal
applications. This will incorporate MRgHIFU infrastructure in our laboratory at SickKids and
create an MRgHIFU robot that brings the ultrasound transducer to the patient to accommodate
prenatal interventions. 2) Assessing the workspace range and targeting accuracy of the produced
MRgHIFU robot in phantoms to ensure it performs appropriately for fetal interventions.
3) Demonstrating the safety and efficacy of the produced robot by ablating multiple targets in
our lab’s established pregnant rabbit model . This will consist of an MRgHIFU survival study
in a pregnant rabbit model targeting placental and fetal lung, kidney, liver, and heart tissues.
Significance of the research:
Developing an MRIgHIFU robot for fetal therapies is critical for making it available to pregnant
patients. Our lab’s partnership with Profound Medical, a HIFU device company with experience
releasing multiple clinical devices, will allow the developed robot to become accessible to
patients in the future. The availability of MRIgHIFU in a clinical setting can decrease the risk of
complications in fetal therapies, lead to better patient outcomes, shorter patient recovery times
and also reduce the average healthcare cost attributed to fetal surgery.
Supervisor Name: James Drake
Year of Study: 2
Program of Study: MASc
Zoom link: https://us02web.zoom.us/j/89610372821?pwd=azd4SCtYVWtreVovaGNPV1c2NGY2Zz09
Meeting ID: 896 1037 2821
Password: 483329
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Date:
April 12, 2023
Time:
12:30 pm - 1:00 pm EDT
Event Category:

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