Multimodal Machine Learning Characterization of Solid Tumors

Description:

This research study wants to develop advanced imaging methods to more accurately characterize prostate cancer or solid tumor aggressiveness. This observational study involves \[18F\]DCFPyL positron emission tomography and magnetic resonance imaging (PET/MRI)

Sponsor:

Massachusetts General Hospital

Contacts:

Ciprian Catana, MD, Ph.D (PRINCIPAL_INVESTIGATOR)

DCFPyL

Isotope(s):
Target(s):
  • PSMA
Ligand Class: Small Molecules
Inclusion
  • Must have primary prostate cancer (e.g. adenocarcinoma of prostate) and deemed a candidate for radical prostatectomy as part of standard clinical care for Cohort A.
  • estimated or measured glomerular filtration rate (GFR) ≥ 60 mL/min/1.73 m2 for repeated administrations.
Exclusion
  • Reduced renal function as determined by creatinine or GFR values defined above obtained within 30 days prior to registration
  • Research-related radiation exposure exceeding current Massachusetts General Hospital (MGH) Radiology Department guidelines (i.e. 50 millisievert in the prior 12 months)
  • Body weight of \> 300 lbs (weight limit of the MRI table)