DeepDixon synthetic CT for [18F]FET PET/MRI attenuation correction of post-surgery glioma patients with metal implants

PurposeConventional magnetic resonance imaging (MRI) can for glioma assessment be supplemented by positron emission tomography (PET) imaging with radiolabeled amino acids such as O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET), which provides additional information on metabolic properties. In neuro-oncology, patients often undergo brain and skull altering treatment, which is known to challenge MRI-based attenuation correction (MR-AC) methods and thereby impact the simplified semi-quantitative measures such as tumor-to-brain ratio (TBR) used in clinical routine. The aim of the present study was to examine the applicability of our deep learning method, DeepDixon, for MR-AC in [18F]FET PET/MRI scans of a post-surgery glioma cohort with metal implants.MethodsThe MR-AC maps were assessed for all 194 included post-surgery glioma patients (318 studies). The subgroup of 147 patients (222 studies, 200 MBq [18F]FET PET/MRI) with tracer uptake above 1 ml were subsequently reconstructed with DeepDixon, vendor-default atlas-based method, and a low-dose computed tomography (CT) used as reference. The biological tumor volume (BTV) was delineated on each patient by isocontouring tracer uptake above a TBR threshold of 1.6. We evaluated the MR-AC methods using the recommended clinical metrics BTV and mean and maximum TBR on a patient-by-patient basis against the reference with CT-AC.ResultsNinety-seven percent of the studies (310/318) did not have any major artifacts using DeepDixon, which resulted in a Dice coefficient of 0.89/0.83 for tissue/bone, respectively, compared to 0.84/0.57 when using atlas. The average difference between DeepDixon and CT-AC was within 0.2% across all clinical metrics, and no statistically significant difference was found. When using DeepDixon, only 3 out of 222 studies (1%) exceeded our acceptance criteria compared to 72 of the 222 studies (32%) with the atlas method.ConclusionWe evaluated the performance of a state-of-the-art MR-AC method on the largest post-surgical glioma patient cohort to date. We found that DeepDixon could overcome most of the issues arising from irregular anatomy and metal artifacts present in the cohort resulting in clinical metrics within acceptable limits of the reference CT-AC in almost all cases. This is a significant improvement over the vendor-provided atlas method and of particular importance in response assessment

Hybrid 2-[18F] FDG PET/MRI in premanifest Huntington's disease gene-expansion carriers: The significance of partial volume correction.

BackgroundHuntington's disease (HD) is an inherited, progressive neurodegenerative disease that has no cure. Striatal atrophy and hypometabolism has been described in HD as far as 15 years before clinical onset and therefore structural and functional imaging biomarkers are the most applied biomarker modalities which call for these to be exact; however, most studies are not considering the partial volume effect and thereby tend to overestimate metabolic reductions, which may bias imaging outcome measures of interventions.ObjectiveEvaluation of partial volume effects in a cohort of premanifest HD gene-expansion carriers (HDGECs).Methods21 HDGECs and 17 controls had a hybrid 2-[18F]FDG PET/MRI scan performed. Volume measurements and striatal metabolism, both corrected and uncorrected for partial volume effect were correlated to an estimate of disease burden, the CAG age product scaled (CAPS).ResultsWe found significantly reduced striatal metabolism in HDGECs, but not in striatal volume. There was a negative correlation between the CAPS and striatal metabolism, both corrected and uncorrected for the partial volume effect. The partial volume effect was largest in the smallest structures and increased the difference in metabolism between the HDGEC with high and low CAPS scores. Statistical parametric mapping confirmed the results.ConclusionsA hybrid 2-[18F]FDG PET/MRI scan provides simultaneous information on structure and metabolism. Using this approach for the first time on HDGECs, we highlight the importance of partial volume effect correction in order not to underestimate the standardized uptake value and thereby the risk of overestimating the metabolic effect on the striatal structures, which potentially could bias studies determining imaging outcome measures of interventions in HDGECs and probably also symptomatic HD