Relative delays in blood-oxygen-level-dependent (BOLD) signal oscillations can be used to assess cerebral perfusion without using contrast agents. However, little is currently known about the utility of this method in detecting clinically relevant perfusion changes over time. We investigated the relationship between longitudinal BOLD delay changes, vessel recanalization, and reperfusion in 15 acute stroke patients with vessel occlusion examined within 24 h of symptom onset (D0) and one day later (D1). We created BOLD delay maps using time shift analysis of resting-state functional MRI data and quantified perfusion lesion volume changes (using the D1/D0 volume ratio) and severity changes (using a linear mixed model) over time. Between baseline and follow-up, BOLD delay lesions shrank (median D1/D0 ratio = 0.2, IQR = 0.03–0.7) and BOLD delay severity decreased (b = −4.4 s) in patients with recanalization, whereas they grew (median D1/D0 ratio = 1.47, IQR = 1.1–1.7) and became more severe (b = 4.3 s) in patients with persistent vessel occlusion. Clinically relevant changes in cerebral perfusion in early stroke can be detected using BOLD delay, making this non-invasive method a promising option for detecting tissue at risk of infarction and monitoring stroke patients following recanalization therapy.
Macaque monkeys are a model of human color vision. To facilitate linking physiology in monkeys with psychophysics in humans, we directly compared colordetection thresholds in humans and rhesus monkeys. Colors were defined by an equiluminant plane of coneopponent color space. All subjects were tested on an identical apparatus with a four-alternative forced-choice task. Targets were 28 square, centered 28 from fixation, embedded in luminance noise. Across all subjects, the change in detection thresholds from initial testing to plateau performance (''learning'') was similar for þL À M (red) colors and þM À L (bluish-green) colors. But the extent of learning was higher for þS (lavender) than for ÀS (yellow-lime); moreover, at plateau performance, the cone contrast at the detection threshold was higher for þS than for ÀS. These asymmetries may reflect differences in retinal circuitry for S-ON and S-OFF. At plateau performance, the two species also had similar detection thresholds for all colors, although monkeys had shorter reaction times than humans and slightly lower thresholds for colors that modulated L/M cones. We discuss whether these observations, together with previous work showing that monkeys have lower spatial acuity than humans, could be accounted for by selective pressures driving higher chromatic sensitivity at the cost of spatial acuity amongst monkeys, specifically for the more recently evolved L À M mechanism.
Despite the potential of deep learning (DL)-based methods in substituting CT-based PET attenuation and scatter correction for CT-free PET imaging, a critical bottleneck is their limited capability in handling large heterogeneity of tracers and scanners of PET imaging. This study employs a simple way to integrate domain knowledge in DL for CT-free PET imaging. In contrast to conventional direct DL methods, we simplify the complex problem by a domain decomposition so that the learning of anatomy-dependent attenuation correction can be achieved robustly in a low-frequency domain while the original anatomy-independent high-frequency texture can be preserved during the processing. Even with the training from one tracer on one scanner, the effectiveness and robustness of our proposed approach are confirmed in tests of various external imaging tracers on different scanners. The robust, generalizable, and transparent DL development may enhance the potential of clinical translation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.