Jacob Andriessen wins ENEN2+ B.Sc. competition

Congratulations to DCU School of Physical Sciences student, Jacob Andriessen – who recently won the ENEN2+ B.Sc. competition, for his research investigating the use of 3D printed phantoms in Parkinson’s disease. 

Jacob’s research was carried out as part of his undergraduate fourth-year project, under the supervision of Prof. Jean Paul Mosnier from the School of Physical Sciences, DCU and by Maria Dooley and Luke Noonan from the Mater Misericordiae University Hospital.

The European Nuclear Education Network (ENEN), funded by the European Union, is the largest Education and Training project in the field of nuclear and applications, e.g. Medical Physics.

Here is Jacob’s description of his work:                                                                                                               

My project investigated the development and evaluation of a low-cost, anatomically accurate 3D-printed phantom for quality assurance (QA) in nuclear medicine imaging, specifically for Dopamine Transporter (DAT) scans used in the differential diagnosis of Parkinson’s disease. 

Phantoms are ground truth tools of accurate known dimensions meant to simulate a patient in a scan for the purposes of quality assurance of medical imaging equipment. Recognizing the limitations of commercially available phantoms— namely high cost and lack of anatomical accuracy—the study focused on replicating the section of the brain associated with Parkinson's, the Basal Ganglia, using anonymised patient MRI data and open-source software to create a 3D model. The model was validated by a specialist consultant radiologist, and two 3D printing techniques were compared: Fused Deposition Modelling (FDM) and Stereolithography (SLA). A ballistic gel-filled FDM head was used to simulate soft tissue attenuation, and imaging was performed using PETCT and SPECT-CT under clinical conditions. 

The SLA phantom showed accurate anatomical replication and successful integration with dedicated clinical software. The success of the phantom validated the research as a low cost, scalable workflow for producing custom phantoms suitable for QA, imaging optimisation, training, and further research.