Advanced imaging techniques in the diagnosis of Atypical Teratoid Rhabdoid Tumor in pediatric patients

Atypical Teratoid Rhabdoid Tumor (AT/RT) is a highly invasive malignant embryonal tumor that is characterized by its low survival rate among pediatric patients. AT/RT spreads through the cerebral spinal fluid (CSF) and white matter tracts (WMTs) to other parts along the brain. Due to its rarity, AT/RT affects only a small number of pediatric patients, therefore studies on the tumor have been limited. While standard Magnetic Resonance Imaging (MRI) techniques offer valuable insight to characterize and detect AT/RT, incorporating advancing imaging techniques such as Diffusion Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI), MR Spectroscopy (MRS), and Perfusion Weighted Imaging (PWI) significantly improves diagnostic accuracy, facilitates early detection of tumor spread, and overcomes the limitations of standard imaging techniques. This paper examines and provides clinical recommendations on how advanced imaging techniques can be used with standard imaging techniques to diagnose AT/RT and identify recurrence in pediatric patients. Additionally, this paper proposes that artificial intelligence (AI) powered Machine Language algorithms be used to statistically recreate DWI, DTI and PWI from conventional MRI scans for use in resource-constrained healthcare settings so as to diagnose AT/RT as well as to distinguish between AT/RT and other brain tumors. It also proposes creation of synthetic pediatric MRI images from adult MRI counterparts so as to expand pediatric MRI image database paucity. Genetic and epigenetic approaches to further improve detection and treatment of AT/RT are also discussed.