Artifacts caused by metallic implants appear as dark and bright streaks at computed tomography (CT), which severely degrade the image quality and decrease the diagnostic value of the examination. When x-rays pass through a metal object, depending on its size and composition, different physical effects negatively affect the measurements in the detector, most notably the effects of photon starvation and beam hardening. To improve image quality and recover information about underlying structures, several artifact reduction methods have been introduced in modern CT systems. Projection-based metal artifact reduction (MAR) algorithms act in projection space and replace corrupted projections caused by metal with interpolation from neighboring uncorrupted projections. MAR algorithms primarily suppress artifacts that are due to photon starvation. The dual-energy CT technique is characterized by data acquisition at two different energy spectra. Dual-energy CT provides synthesized virtual monochromatic images at different photon energy (kiloelectron volt) levels, and virtual monochromatic images obtained at high kiloelectron volt levels are known to reduce the effects of beam hardening. In clinical practice, although MAR algorithms can be applied after image acquisition, the decision whether to apply dual-energy CT for the patient usually needs to be made before image acquisition. Radiologists should be more familiar with the clinical and technical features of each method and should be able to choose the optimal method according to the clinical situation. RSNA, 2018.

• Model-based iterative reconstruction (MBIR) creates high-quality low-dose CT images. • MBIR significantly improves image noise and artefacts over adaptive statistical iterative techniques. • MBIR shows greater potential than ASIR for diagnostically acceptable low-dose CT. • The prolonged processing time of MBIR may currently limit its routine use in clinical practice.

Stop-signal task (SST) has been a key paradigm for probing human brain mechanisms underlying response inhibition, and the inhibition observed in SST is now considered to largely depend on a fronto basal ganglia network consisting mainly of right inferior frontal cortex, pre-supplementary motor area (pre-SMA), and basal ganglia, including subthalamic nucleus, striatum (STR), and globus pallidus pars interna (GPi). However, causal relationships between these frontal regions and basal ganglia are not fully understood in humans. Here, we partly examined these causal links by measuring human fMRI activity during SST before and after excitatory/inhibitory repetitive transcranial magnetic stimulation (rTMS) of pre-SMA. We first confirmed that the behavioral performance of SST was improved by excitatory rTMS and impaired by inhibitory rTMS. Afterward, we found that these behavioral changes were well predicted by rTMSinduced modulation of brain activity in pre-SMA, STR, and GPi during SST. Moreover, by examining the effects of the rTMS on restingstate functional connectivity between these three regions, we showed that the magnetic stimulation of pre-SMA significantly affected intrinsic connectivity between pre-SMA and STR, and between STR and GPi. Furthermore, the magnitudes of changes in resting-state connectivity were also correlated with the behavioral changes seen in SST. These results suggest a causal relationship between pre-SMA and GPi via STR during response inhibition, and add direct evidence that the fronto basal ganglia network for response inhibition consists of multiple top-down regulation pathways in humans.

Changes in brain pathology as schizophrenia progresses have been repeatedly suggested by previous studies. Meta-analyses of previous proton magnetic resonance spectroscopy ((1)H MRS) studies at each clinical stage of schizophrenia indicate that the abnormalities of N-acetylaspartate (NAA) and glutamatergic metabolites change progressively. However, to our knowledge, no single study has addressed the possible differences in (1)H MRS abnormalities in subjects at 3 different stages of disease, including those at ultrahigh risk for psychosis (UHR), with first-episode schizophrenia (FES), and with chronic schizophrenia (ChSz). In the current study, 24 patients with UHR, 19 FES, 25 ChSz, and their demographically matched 3 independent control groups (n = 26/19/28 for the UHR, FES, and ChSz control groups, respectively) underwent (1)H MRS in a 3-Tesla scanner to examine metabolites in medial prefrontal cortex. The analysis revealed significant decreases in the medial prefrontal NAA and glutamate + glutamine (Glx) levels, specifically in the ChSz group as indexed by a significant interaction between stage (UHR/FES/ChSz) and clinical status (patients/controls) (P = .008). Furthermore, the specificity of NAA and Glx reductions compared with the other metabolites in the patients with ChSz was also supported by a significant interaction between the clinical status and types of metabolites that only occurred at the ChSz stage (P = .001 for NAA, P = .004 for Glx). The present study demonstrates significant differences in (1)H MRS abnormalities at different stages of schizophrenia, which potentially correspond to changes in glutamatergic neurotransmission, plasticity, and/or excitotoxicity and regional neuronal integrity with relevance for the progression of schizophrenia.