Masaki Katsura

Model-based iterative reconstruction technique for ultralow-dose chest CT: comparison of pulmonary nodule detectability with the adaptive statistical iterative reconstruction technique.

PurposeThe purpose of this study was to evaluate whether model-based iterative reconstruction (MBIR) enables dose reduction over adaptive iterative reconstruction (ASIR) while maintaining diagnostic performance. MethodsIn this institutional review board–approved and Health Insurance Portability and Accountability Act–compliant study, 59 patients (mean [SD] age, 64.7 [13.4] years) gave informed consent to undergo reference-, low-, and ultralow-dose chest computed tomography (CT) with 64-row multidetector CT. The reference- and low-dose CT involved the use of automatic tube current modulation with fixed noise indices (31.5 and 70.44 at 0.625 mm, respectively) and were reconstructed with 50% ASIR-filtered back projection blending. The ultralow-dose CT was acquired with a fixed tube current-time product of 5 mA s and reconstructed with MBIR. Two radiologists evaluated 2.5- and 0.625-mm-slice–thick axial images from low-dose ASIR and ultralow-dose MBIR, recorded the pattern of each nodule candidate, and assigned each a confidence score. A reference standard was established by a consensus panel of 2 different radiologists, who identified 84 noncalcified nodules with diameters of 4 mm or greater on reference-dose ASIR (ground-glass opacity, n = 18; partly solid, n = 11; solid, n = 55). Sensitivity in nodule detection was assessed using the McNemar test. Jackknife alternative free-response receiver operating characteristic (JAFROC) analysis was applied to assess the results including confidence scores. ResultsCompared with the low-dose CT, a 78.1% decrease in dose-length product was seen with the ultralow-dose CT. No significant differences were observed between the low-dose ASIR and the ultralow-dose MBIR for overall nodule detection in sensitivity (P = 0.48–0.69) or the JAFROC analysis (P = 0.57). Likewise, no significant differences were seen for ground-glass opacity, partly solid, or solid nodule detection in sensitivity (P = 0.08–0.65) or the JAFROC analysis (P = 0.21–0.90). ConclusionsModel-based iterative reconstruction enables nearly an 80% reduction in radiation dose for chest CT from a low-dose level to an ultralow-dose level, without affecting nodule detectability.

Model-based iterative reconstruction for reduction of radiation dose in abdominopelvic CT: comparison to adaptive statistical iterative reconstruction

PurposeTo evaluate dose reduction and image quality of abdominopelvic computed tomography (CT) reconstructed with model-based iterative reconstruction (MBIR) compared to adaptive statistical iterative reconstruction (ASIR).Materials and methodsIn this prospective study, 85 patients underwent referential-, low-, and ultralow-dose unenhanced abdominopelvic CT. Images were reconstructed with ASIR for low-dose (L-ASIR) and ultralow-dose CT (UL-ASIR), and with MBIR for ultralow-dose CT (UL-MBIR). Image noise was measured in the abdominal aorta and iliopsoas muscle. Subjective image analyses and a lesion detection study (adrenal nodules) were conducted by two blinded radiologists. A reference standard was established by a consensus panel of two different radiologists using referential-dose CT reconstructed with filtered back projection.ResultsCompared to low-dose CT, there was a 63% decrease in dose-length product with ultralow-dose CT. UL-MBIR had significantly lower image noise than L-ASIR and UL-ASIR (all p<0.01). UL-MBIR was significantly better for subjective image noise and streak artifacts than L-ASIR and UL-ASIR (all p<0.01). There were no significant differences between UL-MBIR and L-ASIR in diagnostic acceptability (p>0.65), or diagnostic performance for adrenal nodules (p>0.87).ConclusionMBIR significantly improves image noise and streak artifacts compared to ASIR, and can achieve radiation dose reduction without severely compromising image quality.

Reduced Frontal Glutamate + Glutamine and N-Acetylaspartate Levels in Patients With Chronic Schizophrenia but not in Those at Clinical High Risk for Psychosis or With First-Episode Schizophrenia

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.

Diminished Medial Prefrontal Activity behind Autistic Social Judgments of Incongruent Information

Individuals with autism spectrum disorders (ASD) tend to make inadequate social judgments, particularly when the nonverbal and verbal emotional expressions of other people are incongruent. Although previous behavioral studies have suggested that ASD individuals have difficulty in using nonverbal cues when presented with incongruent verbal-nonverbal information, the neural mechanisms underlying this symptom of ASD remain unclear. In the present functional magnetic resonance imaging study, we compared brain activity in 15 non-medicated adult males with high-functioning ASD to that of 17 age-, parental-background-, socioeconomic-, and intelligence-quotient-matched typically-developed (TD) male participants. Brain activity was measured while each participant made friend or foe judgments of realistic movies in which professional actors spoke with conflicting nonverbal facial expressions and voice prosody. We found that the ASD group made significantly less judgments primarily based on the nonverbal information than the TD group, and they exhibited significantly less brain activity in the right inferior frontal gyrus, bilateral anterior insula, anterior cingulate cortex/ventral medial prefrontal cortex (ACC/vmPFC), and dorsal medial prefrontal cortex (dmPFC) than the TD group. Among these five regions, the ACC/vmPFC and dmPFC were most involved in nonverbal-information-biased judgments in the TD group. Furthermore, the degree of decrease of the brain activity in these two brain regions predicted the severity of autistic communication deficits. The findings indicate that diminished activity in the ACC/vmPFC and dmPFC underlies the impaired abilities of individuals with ASD to use nonverbal content when making judgments regarding other people based on incongruent social information.

Localized gray matter volume reductions in the pars triangularis of the inferior frontal gyrus in individuals at clinical high-risk for psychosis and first episode for schizophrenia

Recent studies have suggested an important role for Brocas region and its right hemisphere counterpart in the pathophysiology of schizophrenia, owing to its roles in language and interpersonal information processing. Brocas region consists of the pars opercularis (PO) and the pars triangularis (PT). Neuroimaging studies have suggested that they have differential functional roles in healthy individuals and contribute differentially to the pathogenesis of schizophrenic symptoms. However, volume changes in these regions in subjects with ultra-high risk for psychosis (UHR) or first-episode schizophrenia (FES) have not been clarified. In the present 3 Tesla magnetic resonance imaging study, we separately measured the gray matter volumes of the PO and PT using a reliable manual-tracing volumetry in 80 participants (20 with UHR, 20 with FES, and 40 matched controls). The controls constituted two groups: the first group was matched for age, sex, parental socioeconomic background, and intelligence quotient to UHR (n=20); the second was matched for those to FES (n=20). Compared with matched controls, the volume of the bilateral PT, but not that of the PO, was significantly reduced in the subjects with UHR and FES. The reduced right PT volume, which showed the largest effect size among regions-of-interest in the both UHR and FES groups, correlated with the severity of the positive symptoms also in the both groups. These results suggest that localized gray matter volume reductions of the bilateral PT represent a vulnerability to schizophrenia in contrast to the PO volume, which was previously found to be reduced in patients with chronic schizophrenia. The right PT might preferentially contribute to the pathogenesis of psychotic symptoms.

Comparison of pure and hybrid iterative reconstruction techniques with conventional filtered back projection: image quality assessment in the cervicothoracic region.

OBJECTIVES To evaluate the impact on image quality of three different image reconstruction techniques in the cervicothoracic region: model-based iterative reconstruction (MBIR), adaptive statistical iterative reconstruction (ASIR), and filtered back projection (FBP). METHODS Forty-four patients underwent unenhanced standard-of-care clinical computed tomography (CT) examinations which included the cervicothoracic region with a 64-row multidetector CT scanner. Images were reconstructed with FBP, 50% ASIR-FBP blending (ASIR50), and MBIR. Two radiologists assessed the cervicothoracic region in a blinded manner for streak artifacts, pixilated blotchy appearances, critical reproduction of visually sharp anatomical structures (thyroid gland, common carotid artery, and esophagus), and overall diagnostic acceptability. Objective image noise was measured in the internal jugular vein. Data were analyzed using the sign test and pair-wise Students t-test. RESULTS MBIR images had significant lower quantitative image noise (8.88 ± 1.32) compared to ASIR images (18.63 ± 4.19, P<0.01) and FBP images (26.52 ± 5.8, P<0.01). Significant improvements in streak artifacts of the cervicothoracic region were observed with the use of MBIR (P<0.001 each for MBIR vs. the other two image data sets for both readers), while no significant difference was observed between ASIR and FBP (P>0.9 for ASIR vs. FBP for both readers). MBIR images were all diagnostically acceptable. Unique features of MBIR images included pixilated blotchy appearances, which did not adversely affect diagnostic acceptability. CONCLUSIONS MBIR significantly improves image noise and streak artifacts of the cervicothoracic region over ASIR and FBP. MBIR is expected to enhance the value of CT examinations for areas where image noise and streak artifacts are problematic.

Effects of rTMS of Pre-Supplementary Motor Area on Fronto Basal Ganglia Network Activity during Stop-Signal Task

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 rTMS-induced modulation of brain activity in pre-SMA, STR, and GPi during SST. Moreover, by examining the effects of the rTMS on resting-state 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.

Absence of age-related prefrontal NAA change in adults with autism spectrum disorders.

Atypical trajectory of brain growth in autism spectrum disorders (ASDs) has been recognized as a potential etiology of an atypical course of behavioral development. Numerous neuroimaging studies have focused on childhood to investigate atypical age-related change of brain structure and function, because it is a period of neuron and synapse maturation. Recent studies, however, have shown that the atypical age-related structural change of autistic brain expands beyond childhood and constitutes neural underpinnings for lifelong difficulty to behavioral adaptation. Thus, we examined effects of aging on neurochemical aspects of brain maturation using 3-T proton magnetic resonance spectroscopy (1H-MRS) with single voxel in the medial prefrontal cortex (PFC) in 24 adult men with non-medicated high-functioning ASDs and 25 age-, IQ- and parental-socioeconomic-background-matched men with typical development (TD). Multivariate analyses of covariance demonstrated significantly high N-acetylaspartate (NAA) level in the ASD subjects compared with the TD subjects (F=4.83, P=0.033). The low NAA level showed a significant positive correlation with advanced age in the TD group (r=−0.618, P=0.001), but was not evident among the ASD individuals (r=0.258, P=0.223). Fisher’s r-to-z transformation showed a significant difference in the correlations between the ASD and TD groups (Z=−3.23, P=0.001), which indicated that the age–NAA relationship was significantly specific to people with TD. The current 1H-MRS study provided new evidence that atypical age-related change of neurochemical aspects of brain maturation in ASD individuals expands beyond childhood and persists during adulthood.

Prediction of subsequent recognition performance using brain activity in the medial temporal lobe.

Application of multivoxel pattern analysis (MVPA) to functional magnetic resonance imaging (fMRI) data enables reconstruction and classification of cognitive status from brain activity. However, previous studies using MVPA have extracted information about cognitive status that is experienced simultaneously with fMRI scanning, but not one that will be observed after the scanning. In this study, by focusing on activity in the medial temporal lobe (MTL), we demonstrate that MVPA on fMRI data is capable of predicting subsequent recognition performance. In this experiment, six runs of fMRI signals were acquired during encoding of phonogram stimuli. In the analysis, using data acquired in runs 1-3, we first conducted MVPA-based voxel-wise search for the clusters in the MTL whose signals contained the most information about subsequent recognition performance. Next, using the fMRI signals acquired in runs 1-3 from the selected clusters, we trained a classifier function in MVPA. Finally, the trained classifier function was applied to fMRI signals acquired in runs 4-6. Consequently, we succeeded in predicting the subsequent recognition performance for stimuli studied in runs 4-6 with significant accuracy. This accurate prediction suggests that MVPA can extract information that is associated not only with concurrent cognitive status, but also with behavior in the near future.

Network structure underlying resolution of conflicting non-verbal and verbal social information

Social judgments often require resolution of incongruity in communication contents. Although previous studies revealed that such conflict resolution recruits brain regions including the medial prefrontal cortex (mPFC) and posterior inferior frontal gyrus (pIFG), functional relationships and networks among these regions remain unclear. In this functional magnetic resonance imaging study, we investigated the functional dissociation and networks by measuring human brain activity during resolving incongruity between verbal and non-verbal emotional contents. First, we found that the conflict resolutions biased by the non-verbal contents activated the posterior dorsal mPFC (post-dmPFC), bilateral anterior insula (AI) and right dorsal pIFG, whereas the resolutions biased by the verbal contents activated the bilateral ventral pIFG. In contrast, the anterior dmPFC (ant-dmPFC), bilateral superior temporal sulcus and fusiform gyrus were commonly involved in both of the resolutions. Second, we found that the post-dmPFC and right ventral pIFG were hub regions in networks underlying the non-verbal- and verbal-content-biased resolutions, respectively. Finally, we revealed that these resolution-type-specific networks were bridged by the ant-dmPFC, which was recruited for the conflict resolutions earlier than the two hub regions. These findings suggest that, in social conflict resolutions, the ant-dmPFC selectively recruits one of the resolution-type-specific networks through its interaction with resolution-type-specific hub regions.