PET-Based Personalized Management in Clinical Oncology: An Unavoidable Path for the Foreseeable Future

It is imperative that the thrust of clinical practice in the ensuing years would be to develop personalized management model for various disorders. PET-computed tomography (PET-CT) based molecular functional imaging has been increasingly utilized for assessment of tumor and other nonmalignant disorders and has the ability to explore disease phenotype on an individual basis and address critical clinical decision making questions related to practice of personalized medicine. Hence, it is essential to make a concerted systematic effort to explore and define the appropriate place of PET-CT in personalized clinical practice in each of malignancies, which would strengthen the concept further. The potential advantages of PET based disease management can be classified into broad categories: (1) Traditional: which includes assessment of disease extent such as initial disease staging and restaging, treatment response evaluation particularly early in the course and thus PET-CT response adaptive decision for continuing the same regimen or switching to salvage schedules; there has been continuous addition of newer application of PET based disease restaging in oncological parlance (eg, Richter transformation); (2) Recent and emerging developments: this includes exploring tumor biology with FDG and non-FDG PET tracers. The potential of multitracer PET imaging (particularly new and novel tracers, eg, 68Ga-DOTA-TOC/NOC/TATE in NET, 68Ga-PSMA and 18F-fluorocholine in prostate carcinoma, 18F-fluoroestradiol in breast carcinoma) has provided a scientific basis to stratify and select appropriate targeted therapies (both radionuclide and nonradionuclide treatment), a major boost for individualized disease management in clinical oncology. Integrating the molecular level information obtained from PET with structural imaging further individualizing treatment plan in radiation oncology, precision of interventions and biopsies of a particular lesion and forecasting disease prognosis.