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At the MFI Laboratory, we develop and use a variety of magnetic resonance (MR) sequences that facilitate non-invasive acquisition of physiological data of the mother and her fetus. We then apply these techniques to understand how maternal lifestyle choices and gestational disorders alter maternal and fetal physiology, fetal development and consequently, postnatal health.
Through an international collaboration, we are creating an artificial intelligence algorithm that identifies patterns and predicts disease severity and progression in pregnant women with COVID-19.
Automatic Fetal Image Segmentation and Classification
We are using machine learning approaches along with image processing techniques to develop novel algorithms for segmentation and disease classification of the placenta, fetus, and fetal organs from MR images. These will permit earlier and more accurate disease detection and facilitate interventions.
Imaging Fetal Glucose Metabolism
We are developing a novel MRI technique that will non-invasively assess glucose metabolism in fetal organs. This technique, called Chemical Exchange Saturation Transfer (glucoCEST), creates image contrast by exploiting magnetization transfer between glucose and surrounding water. This method will facilitate early diagnosis and treatment of fetal metabolic disorders and intra-uterine growth restriction.
Fetal Phantom Synthesis
We are synthesizing 3D phantoms of the human fetus for magnetic resonance testing. This phantom will enable us to optimize various MR sequences as well as motion correction algorithms.
Amniotic Fluid MR Spectroscopy
Amniotic fluid (AF) contains nutrients and hormones that support fetal growth as well as markers of fetal organ development. We are developing an in-vivo Magnetic Resonance Spectroscopy (MRS) technique to non-invasively evaluate AF chemical content as it changes throughout pregnancy. This method will allow us to evaluate fetal lung and kidney maturity, thereby replacing amniocentesis—a highly invasive and risky procedure.
Maternal-Fetal Cardiovascular Imaging
We are applying phase-contrast MRI and MR-oximetry to evaluate blood flow and oxygen delivery to the materno-fetal unit. This approach is currently used in understanding how cardiovascular physiology is altered due to exercise and nutrient intake during pregnancy.
Smart Surveillance of Brain Tumours
Clinical surveillance of brain tumours is typically a manual task aimed at assessing tumour growth and transformation. We are working closely with neurosurgeons and radiologists to develop an algorithm that automatically carries out tumour grading from non-contrast enhanced 3D MRIs.