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Job Record #16801
TitleComputational modeling of microspheres in liver tumors
CategoryJob in Academia
EmployerUniversity of Twente
InternationalYes, international applications are welcome
Closure Date* None *
Each year, over 1.5 million people worldwide develop primary or secondary (metastatic) liver cancer. Liver 
tumours are characterised by their limited treatment options and the relatively high 1-year mortality. 
Selective Internal Radiation Therapy (SIRT), also called radioembolization, is a treatment option for 
patients suffering from liver tumours that do not benefit from conventional therapy such as surgery or 
chemotherapy. During the treatment, radioactive microspheres are injected into the liver artery that 
supplies the tumour, where they lodge in and around the tumour and deliver a high local radiation dose. Up 
to now over 150.000 patients have been treated with SIRT worldwide. However, the outcomes vary greatly 
between individuals, resulting in an extremely broad survival distribution. It is not well known what factors 
give rise to these mixed outcomes. The very nature of the technique, in which the distribution of 
microspheres is dependent on blood flow and the structure of the tumour blood vessels, gives rise to a 
non- controlled dynamic process that will differ per procedure, per medical practitioner, per patient and 
even to some extent over time..

Research rationale and the project consortium

A crucial aspect to obtain an optimal treatment result is an effective distribution of the microspheres in the 
vascular network of the liver. An optimal distribution means that lodged microspheres in the vascular 
network of the liver are distributed such that as much as possible tumour tissue will receive the aimed 
dose while sparing the healthy tissue. There are several parameters that possibly affect these distributions 
including microsphere density: total number of administered microspheres, injection velocity and catheter 
tip location. However, to what extent these factors affect the distribution is still unknown. Having a better 
understanding of the effect of these parameters will allow for a further optimisation of this treatment.

Computational modeling has evolved as a useful tool that can help in understanding optimal distri- bution 
of microspheres, among other aspects. In this project, funded by the Netherlands Organisation for 
Scientific Research (NWO) we will develop a particle transport model within the lattice Boltzmann 
framework to study the optimal microsphere distribution. The methodology will be developed within the 
LBM framework. The PhD candidate will actively collaborate with two other PhD students in this project 
involved in experimental and clinical aspects. Collaboration and exchange with hospitals like the Radboud 
University Medical Center, Nijmegen and the Physics of Fluids group at the University of Twente will form 
regular part of the activities of the PhD candidate.

Your doctoral advisor will be Assistant Professor Dr. Kartik Jain. The project will run for four years leading 
to a PhD degree from the University of Twente, The Netherlands. Salary and other benefits including 
holiday allowance, vacation days and end of year bonus are in accordance with the Collective Labour 
Agreement of Dutch Universities.

Qualifications of the Applicant

You are excited by the idea of impacting patient’s lives using mathematics and computers as languages 
that form a bridge to medicine. You are keen to have exposure to state of the art research facilities in 
hospitals and labs as well as large computational resources. You are curious to learn various cultures, and 
envision yourself working in a highly international environment. You hold a master’s degree in engineering, 
physics, or similar. The application must include a detailed CV with names and contact details of 2-3 
references, a motivation letter and transcripts of bachelors and masters studies.

PLEASE APPLY ONLINE AT:!/2020-134/phd-position-computational-modeling-of-
Contact Information:
Please mention the CFD Jobs Database, record #16801 when responding to this ad.
NameKartik Jain
Email ApplicationYes
Record Data:
Last Modified15:27:24, Wednesday, December 23, 2020

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