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Internship: Deep lEarning tooLs for selectIve iNtErnal rAdiation ThErapy of hepatic tumours (DELINEATE) – registration of the baseline ceMRI-SPECT/CT-PET/CT images

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Internship: Deep lEarning tooLs for selectIve iNtErnal rAdiation ThErapy of hepatic tumours (DELINEATE) – registration of the baseline ceMRI-SPECT/CT-PET/CT images

Where: Imagerie et Vision Artificielle (ImViA) laboratory, Dijon, France
Specific unit: Functional and Molecular Imaging, Medical Image Processing (IFTIM), Dijon, France – https://imvia.u-bourgogne.fr/en/laboratory/iftim-team 
Duration of the internship: six months 
Stipend: about 590 € per month
Team: Jean-Louis Alberini, MD, PhD; Arnaud Boucher, PhD; Olivier Chevallier, MD; Sarah Leclerc, PhD; Fabrice Meriaudeau, PhD; Tien-Phong Pham, PhD student; Romain Popoff, PhD; Benoît Presles, PhD; Jean-Marc Vrigneaud, PhD

Project description
Liver cancer is the sixth most common cancer in the world but is the second most frequent cause of cancer death in men and the sixth leading cause of cancer death in women. Among the different types of liver cancer, hepatocellular carcinoma (HCC) can be treated by selective internal radiation therapy (SIRT), which consists in injecting selectively into the hepatic arteries yttrium-90 (90Y) β-radiation emitter microspheres. Prior to 90Y bead injection, several examinations must be performed. First, a baseline contrast­enhanced magnetic resonance imaging (ceMRI) scan is acquired to visualise the tumour, and a hepatic angiography is acquired to identify the extrahepatic vessels that must be prophylactically embolized to preserve healthy organs. Then, a simulation of the treatment is performed by injecting Technetium-99m macroaggregated albumin (99mTc-MAA) as a surrogate for 90Y particles. A pre-treatment dosimetry is performed by acquiring a single-photon emission computed tomography (SPECT/CT) scan which allows to obtain the 99mTc-MAA distribution of activity and to calculate the 90Y activity to prescribe. Once calculated, the appropriate amount of 90Y microspheres is injected into the patient and a positron emission tomography (PET/CT) scan is acquired to ensure the proper 90Y distribution and calculate 90Y post-treatment dosimetry. To be able to calculate proper dosimetry, it is necessary to perform registrations beforehand.
The aim of this internship is to perform
– a first registration between the baseline ceMRI and SPECT/CT images (pre-treatment dosimetry),
– and a second registration between the baseline ceMRI and the PET/CT images (post-treatment dosimetry).
The objective of this work is to validate and optimise on the dataset that was recently gathered at the university hospital centre (CHU) and the cancer research centre Georges-François Leclerc (CGFL) of Dijon, France, existing approaches already implemented in software packages such as NiftyReg (http://cmictig.cs.ucl.ac.uk/wiki/index.php/NiftyReg) or elastix (https://elastix.lumc.nl). Deep learning approaches might also be considered.
The student will work in close relation with the medical teams of the CHU and the CGFL.

Person specification
Candidates must be engineering or master students in a relevant area such as computer science, biomedical engineering or applied mathematics.

Application
Applications (including a CV and covering letter outlining your motivation for the position) should be sent to Benoît Presles (benoit.presles@u-bourgogne.fr).

Closing date: 30 November 2021

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