Nuclear Cerebrospinal Fluid Imaging: Guide to Procedures and Interpretation.

Cerebrospinal fluid (CSF) is an essential component of the central nervous system, and disruption of normal CSF flow from the lateral ventricles to the subarachnoid spaces around the brain and spinal canal can have serious consequences. Nuclear imaging may be useful to help diagnose abnormalities in CSF flow; cisternograms can be used to assess for CSF leaks or normal-pressure hydrocephalus, and shuntograms can be used to evaluate for CSF shunt malfunction. The authors review normal and pathologic findings and pitfalls of cisternography and shuntogram examinations.

Clinical Pilot of a Deep Learning Elastic Registration Algorithm to Improve Misregistration Artifact and Image Quality on Routine Oncologic PET/CT.

Rationale And Objectives: Misregistration artifacts between the PET and attenuation correction CT (CTAC) exams can degrade image quality and cause diagnostic errors. Deep learning (DL)-warped elastic registration methods have been proposed to improve misregistration errors.

Materials And Methods: 30 patients undergoing routine oncologic examination (20 F-FDG PET/CT and 10 Cu-DOTATATE PET/CT) were retrospectively identified and compared using unmodified CTAC, and a DL-augmented spatial transformation CT attenuation map.

Technical note: Can photon-counting CT improve PET/CT's quantitative accuracy?

Background: Linear attenuation coefficients (LACs) in positron emission tomography combined with computed tomography (PET/CT) are derived from CT scans that utilize energy-integrating detectors (EID-CT). These LACs are inaccurate when iodine contrast has been injected. Photon counting detector CT (PCD-CT) may be able to improve the accuracy.