MR Physics Research Group

MR Physiological Signature and Artificial Intelligence

AI is becoming a revolution in Medical Imaging and aid diagnosis. However oncologists, neurologists, radiologists, medicine specialists in general, need to find the nexus, to fill the gap, between AI and the deep physiological knowledge that they treasure.
Additionally, the MR Physics group wants to contribute to answer an important question for our clinical researchers: to what extent quantitative MR can provide reliable physiological information from the microscopic tissue and even cellular level. 

Deep MR-only Radiotherapy 

In collaboration with the Radiotherapy department and General Electric Healthcare we were granted by EU to develop a technology that eventually could avoid CT scanning for Radiotherapy Planning. 
We will use deep learning for a perfect delineation of the bone and target areas for radiotherapy of head and neck tumours and pelvic tumours.

UTE and ZTE with application in MSK and in Lung free breathing with retrospective gating reconstruction.

UTE and ZTE sequences are capable of providing signal from tissues with really short T2 tissues.
The MR Physics is collaborating in the clinical validation and the technical improvement of these techniques with application in MSK and Lung. 

Hypersense 3DGRASE 

In collaboration with GE Healthcare, the MR physics group has developed a new sequence, Q-3DGRASE (quantitative 3D-GRASE), fully compatible with the GE’s product CUBE. This new development is capable of providing similar T1w, T2w and PD contrasts than CUBE but additionally including T2* contrast.
 Some novel features, different than those in CUBE, as new K-space trajectories, have been implemented to improve the performance of 3DGRASE.

• Vascular Signature Mapping of Brain Tumor Genotypes
  Netherlands Organisation for Scientific Research (NWO)
  Applied and Engineering Sciences (TTW)
  To obtain quantitative vascular physiological biomarkers using MR.
• Multi-coil magnetic resonance guided hyperthermia for precision treatment of advanced head and neck carcinoma”
  Netherlands Cancer Society Grant (KWF) 
  MR Thermometry to monitor  hyperthermia treatment.
• MR Physiological Signature.
  GE Electric Healtcare.
  Quantitative Advanced Biomarkers with MR Fingerprinting.
• Oropharynx Cancer
  Elekta
  MR biomarkers for oropharynx treatment prognosis.
• Deep MR-Only Radiotherapy
  EU EIT Healthcare Grant
• HARPS: Harmonized Acquisition in Resonators using Physiological Signature.
  Erasmus MC MRace Grant.
  To harmonize acquisition in long-term population studies 

• Vascular Signature Mapping of Brain Tumor Genotypes
  Netherlands Organisation for Scientific Research (NWO)
  Applied and Engineering Sciences (TTW)
  To obtain quantitative vascular physiological biomarkers using MR.
• Multi-coil magnetic resonance guided hyperthermia for precision treatment of advanced head and neck carcinoma” Netherlands Cancer Society Grant (KWF) 
  MR Thermometry to monitor  hyperthermia treatment.
• MR Physiological Signature.
  GE Electric Healtcare.
  Quantitative Advanced Biomarkers with MR Fingerprinting.
• Oropharynx Cancer
  Elekta
  MR biomarkers for oropharynx treatment prognosis.
• Deep MR-Only Radiotherapy
  EU EIT Healthcare Grant
• HARPS: Harmonized Acquisition in Resonators using Physiological Signature.
  Erasmus MC MRace Grant.
  To harmonize acquisition in long-term population studies 

• Alexandra Cristobal Huerta, M.Eng. PhD Student
  a.cristobalhuerta@erasmusmc.nl
• Laura Nuñez González. M.Eng. PhD Student
  l.nunezgonzalez@erasmusmc.nl
• Nienke Sijtsema, MSc. PhD Student (50% Radiotherapy)
  n.sijtsema@erasmusmc.nl
• Dorothya Papp. MSc. PhD Student
  d.papp@erasmusmc.nl
• Theresa Feddersen. MSc. PhD Student (50% Radiotherapy)
  t.feddersen@erasmusmc.nl
• Dirk Poot. MSc. PhD. Assistant Professor (50% BIGR)
  d.poot@erasmusmc.nl
• Gyula Kotek. MSc. PhD. Assistant Professor (50% Medical Physics)
  g.kotek@erasmusmc.nl
• Samy Abo Seada, PhD. 
  s.aboseada@erasmusmc.nl