The accuracy of existing PET/MR attenuation correction (AC) has been limited by a lack of correlation between MR signal and tissue electron density. Based on our finding that longitudinal relaxation rate, or R 1 , is associated with CT Hounsfield unit in bone and soft tissues in the brain, we propose a deep learning T 1-enhanced selection of linear attenuation coefficients (DL-TESLA) method to incorporate quantitative R 1 for PET/MR AC and evaluate its accuracy and longitudinal test-retest repeatability in brain PET/MR imaging. Methods: DL-TESLA uses a 3D residual UNet (ResUNet) for pseudo-CT (pCT) estimation. With a total of 174 participants, we compared PET AC accuracy of DL-TESLA to 3 other methods adopting similar 3D ResUNet structures but using UTE R * 2 , or Dixon, or T 1-MPRAGE as input. With images from 23 additional participants repeatedly scanned, the test-retest differences and within-subject coefficient of variation of standardized uptake value ratios (SUVR) were compared between PET images reconstructed using either DL-TESLA or CT for AC. Results: DL-TESLA had (1) significantly lower mean absolute error in pCT, (2) the highest Dice coefficients in both bone and air, (3) significantly lower PET relative absolute error in whole brain and various brain regions, (4) the highest percentage of voxels with a PET relative error within both ±3% and ±5%, (5) similar to CT testretest differences in SUVRs from the cerebrum and mean cortical (MC) region, and (6) similar to CT within-subject coefficient of variation in cerebrum and MC. Conclusion: DL-TESLA demonstrates excellent PET/MR AC accuracy and testretest repeatability.

Background and Purpose: Chronic hypoxia-ischemia is a putative mechanism underlying the development of white matter hyperintensities (WMH) and microstructural disruption in cerebral small vessel disease. WMH fall primarily within deep white matter (WM) watershed regions. We hypothesized that elevated oxygen extraction fraction (OEF), a signature of hypoxia-ischemia, would be detected in the watershed where WMH density is highest. We further hypothesized that OEF would be elevated in regions immediately surrounding WMH, at the leading edge of growth. Methods: In this cross-sectional study conducted from 2016 to 2019 at an academic medical center in St Louis, MO, participants (age >50) with a range of cerebrovascular risk factors underwent brain magnetic resonance imaging using pseudocontinuous arterial spin labeling, asymmetric spin echo, fluid-attenuated inversion recovery and diffusion tensor imaging to measure cerebral blood flow (CBF), OEF, WMH, and WM integrity, respectively. We defined the physiologic watershed as a region where CBF was below the 10th percentile of mean WM CBF in a young healthy cohort. We conducted linear regression to evaluate the relationship between CBF and OEF with structural and microstructural WM injury defined by fluid-attenuated inversion recovery WMH and diffusion tensor imaging, respectively. We conducted ANOVA to determine if OEF was increased in proximity to WMH lesions. Results: In a cohort of 42 participants (age 50–80), the physiologic watershed region spatially overlapped with regions of highest WMH lesion density. As CBF decreased and OEF increased, WMH density increased. Elevated watershed OEF was associated with greater WMH burden and microstructural disruption, after adjusting for vascular risk factors. In contrast, WM and watershed CBF were not associated with WMH burden or microstructural disruption. Moreover, OEF progressively increased while CBF decreased, in concentric contours approaching WMH lesions. Conclusions: Chronic hypoxia-ischemia in the watershed region may contribute to cerebral small vessel disease pathogenesis and development of WMH. Watershed OEF may hold promise as an imaging biomarker to identify individuals at risk for cerebral small vessel disease progression.

Positron emission tomography and magnetic resonance imaging (PET/MRI) scanners cannot be qualified in the manner adopted for hybrid PET and computed tomography (CT) devices. The main hurdle with qualification in PET/MRI is that attenuation correction (AC) cannot be adequately measured in conventional PET phantoms due to the difficulty in converting the MRI images of the physical structures (e.g., plastic) into electron density maps. Over the last decade, a plethora of novel MR-based algorithms have been developed to more accurately derive the attenuation properties of the human head, including the skull. Although very promising, none of these techniques has yet emerged as an optimal and universally adopted strategy for AC in PET/MRI.In this work, we propose a path for PET/MRI qualification for multicenter brain imaging studies. Specifically, our solution is to separate the head attenuation correction from the other factors that affect PET data quantification and use a patient as a phantom to assess the former. The emission data collected on the integrated PET/MRI scanner to be qualified should be reconstructed using both MR-and CT-based AC methods and whole-brain qualitative and quantitative (both voxelwise and regional) analyses should be performed. The MR-based approach will be considered satisfactory if the PET quantification bias is within the acceptance criteria specified herein. We have implemented this approach successfully across two PET/MRI scanner manufacturers at two sites.

Background: Individuals with sickle cell anemia have heightened risk of stroke and cognitive dysfunction. Given its high prevalence globally, whether sickle cell trait (SCT) is a risk factor for neurological injury has been of interest; however, data have been limited. We hypothesized that young, healthy adults with SCT would show normal cerebrovascular structure and hemodynamic function. Methods: As a case-control study, young adults with (N=25, cases) and without SCT (N=24, controls) underwent brain magnetic resonance imaging to quantify brain volume, microstructural integrity (fractional anisotropy), silent cerebral infarcts (SCI), intracranial stenosis, and aneurysms. Pseudocontinuous arterial spin labeling and asymmetric spin echo sequences measured cerebral blood flow and oxygen extraction fraction, respectively, from which cerebral metabolic oxygen demand was calculated. Imaging metrics were compared between SCT cases and controls. SCI volume was correlated with baseline characteristics. Results: Compared with controls, adults with SCT demonstrated similar normalized brain volumes (SCT 0.80 versus control 0.81, P =0.41), white matter fractional anisotropy (SCT 0.41 versus control 0.43, P =0.37), cerebral blood flow (SCT 62.04 versus control, 61.16 mL/min/100 g, P =0.67), oxygen extraction fraction (SCT 0.27 versus control 0.27, P =0.31), and cerebral metabolic oxygen demand (SCT 2.71 versus control 2.70 mL/min/100 g, P =0.96). One per cohort had an intracranial aneurysm. None had intracranial stenosis. The SCT cases and controls showed similar prevalence and volume of SCIs; however, in the subset of participants with SCIs, the SCT cases had greater SCI volume versus controls (0.29 versus 0.07 mL, P =0.008). Of baseline characteristics, creatinine was mildly elevated in the SCT cohort (0.9 versus 0.8 mg/dL, P =0.053) and correlated with SCI volume (ρ=0.49, P =0.032). In the SCT cohort, SCI distribution was similar to that of young adults with sickle cell anemia. Conclusions: Adults with SCT showed normal cerebrovascular structure and hemodynamic function. These findings suggest that healthy individuals with SCT are unlikely to be at increased risk for early or accelerated ischemic brain injury.

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