AI Transformers for Radiation Dose Reduction in Serial Whole-Body PET Scans.

Purpose: To develop a deep learning approach that enables ultra-low-dose, 1% of the standard clinical dosage (3 MBq/kg), ultrafast whole-body PET reconstruction in cancer imaging.

Materials And Methods: In this Health Insurance Portability and Accountability Act-compliant study, serial fluorine 18-labeled fluorodeoxyglucose PET/MRI scans of pediatric patients with lymphoma were retrospectively collected from two cross-continental medical centers between July 2015 and March 2020. Global similarity between baseline and follow-up scans was used to develop Masked-LMCTrans, a longitudinal multimodality coattentional convolutional neural network (CNN) transformer that provides interaction and joint reasoning between serial PET/MRI scans from the same patient.

Predicting FDG-PET Images From Multi-Contrast MRI Using Deep Learning in Patients With Brain Neoplasms.

Background: F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is valuable for determining presence of viable tumor, but is limited by geographical restrictions, radiation exposure, and high cost.

Purpose: To generate diagnostic-quality PET equivalent imaging for patients with brain neoplasms by deep learning with multi-contrast MRI.

Study Type: Retrospective.

Comparison of whole-body DW-MRI with 2-[F]FDG PET for staging and treatment monitoring of children with Langerhans cell histiocytosis.

Purpose: To assess and compare the diagnostic accuracy of whole-body (WB) DW-MRI with 2-[F]FDG PET for staging and treatment monitoring of children with Langerhans cell histiocytosis (LCH).

Methods: Twenty-three children with LCH underwent 2-[F]FDG PET and WB DW-MRI at baseline. Two nuclear medicine physicians and two radiologists independently assessed presence/absence of tumors in 8 anatomical areas.

One-stop local and whole-body staging of children with cancer.

Accurate staging and re-staging of cancer in children is crucial for patient management. Currently, children with a newly diagnosed cancer must undergo a series of imaging tests, which are stressful, time-consuming, partially redundant, expensive, and can require repetitive anesthesia. New approaches for pediatric cancer staging can evaluate the primary tumor and metastases in a single session.