On two methods of statistical image analysis

Statistical Parametric Mapping of Hypoxic Tissue Identified by [18F]Fluoromisonidazole and Positron Emission Tomography Following Acute Ischemic Stroke

Statistical parametric mapping (SPM) quantification and analysis has been successfully applied to functional imaging studies of partial epilepsy syndromes in adults. The present study evaluated whether localisation of the epileptogenic zone (determined by SPM) improves upon visually examined single-photon emission tomography (SPET) imaging in presurgical assessment of children with temporal lobe epilepsy (TLE) and frontal lobe epilepsy (FLE). The patient sample consisted of 24 children (15 males) aged 2.1-17.8 years (9.8+/-4.3 years; mean+/-SD) with intractable TLE or FLE. SPET imaging was acquired routinely in presurgical evaluation. All patient images were transformed into the standard stereotactic space of the adult SPM SPET template prior to SPM statistical analysis. Individual patient images were contrasted with an adult control group of 22 healthy adult females. Resultant statistical parametric maps were rendered over the SPM canonical magnetic resonance imaging (MRI). Two corresponding sets of ictal and interictal SPM and SPET images were then generated for each patient. Experienced clinicians independently reviewed the image sets, blinded to clinical details. Concordance of the reports between SPM and SPET images, syndrome classification and MRI abnormality was studied. A fair level of inter-rater reliability (kappa=0.73) was evident for SPM localisation. SPM was concordant with SPET in 71% of all patients, the majority of the discordance being from the FLE group. SPM and SPET localisation were concordant with epilepsy syndrome in 80% of the TLE cases. Concordant localisation to syndrome was worse for both SPM (33%) and SPET (44%) in the FLE group. Data from a small sample of patients with varied focal structural pathologies suggested that SPM performed poorly relative to SPET in these cases. Concordance of SPM and SPET with syndrome was lower in patients younger than 6 years than in those aged 6 years and above. SPM is effective in localising the potential epileptogenic zone but does not provide additional benefit beyond SPET in presurgical assessment of children with intractable epilepsy. The impact of different pathologies on the efficacy of SPM warrants further study.

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Objective To investigate the value of statistical parametric mapping (SPM) analysis of 18F-fluorodeoxyglucose (FDG) PET imaging in the differential diagnosis of Parkinsonism in single-case level. Methods SPM software was used to retrospectively analyze the 18F-FDG PET images of 160 patients (104 males, 56 females, age: 30-82 years) who were suspected with Parkinsonism at baseline and were clinical confirmed by follow-up from April 2010 to December 2017. 18F-FDG PET images of patients was compared with those of age-matched healthy controls in single-case level using two-sample t test in SPM software to obtain the imaging diagnosis. By comparing imaging diagnosis with the final clinical diagnosis, the diagnostic accuracy of SPM in the overall cohort as well as the early subcohort (duration of disease less than 2 years (56 males, 22 females, age: 50-82 years)) were calculated respectively. Results Among 160 patients with Parkinsonism, 146(91.2%) had the same 18F-FDG PET diagnosis as their final clinical diagnosis. The diagnostic sensitivity for Parkinson′s disease (PD), multiple system atrophy (MSA), progressive supranuclear palsy (PSP) and cortical basal ganglia degeneration (CBD) were 93.5%(86/92), 92.3%(24/26), 84.0%(21/25) and 15/17, respectively. The specificity were 95.6%(65/68), 95.5%(128/134), 96.3%(130/135) and 100%(143/143), respectively. In the early subcohort, the analysis also achieved similar differential diagnosis effectiveness(92.3%). Conclusion The single-case 18F-FDG PET imaging SPM analysis can be helpful in the early differential diagnosis of Parkinsonism effectively. Key words: Parkinsonian disorders; Positron-emission tomography; Diagnosis, differential; Deoxyglucose

Effects of attenuation correction and reconstruction method on PET activation studies

Positron emission tomography (PET) can be used to locate epileptic foci in patients with mesial temporal lobe epilepsy (MTLE) by measuring multiple parameters of the brain. We investigated a series of patients with MTLE using PET measurements of three parameters: the cerebral blood flow measured with [15 O] H2O, the uptake of [18F] fluorodeoxyglucose (FDG), an index of the cerebral metabolism rate of glucose, and the distribution volume (DV) of [11C] flumazenil (FMZ), an index of the binding potential of central benzodiazepine receptor. We compared predictive values obtained from two methods: a voxel-based statistical analysis using statistical parametric mapping (SPM) and an asymmetry index obtained by placing regions of interest (ROIs) on PET images. Preoperative PET data of 11 patients with surgically confirmed MTLE were retrospectively examined. In the voxel-based analysis, the PET data were analyzed using SPM99 by statistically comparing the voxel values of PET parameters between individual patients and the mean values of 12 normal volunteers. Voxels with values significantly lower than the normal control values were mapped on a standard brain atlas. In the ROI-based analysis, the asymmetry index was calculated to depict ROIs with abnormally decreased values when compared with the contralateral side. (1) Statistical parametric mapping and ROI analyses of the FDG uptake correctly determined epileptic temporal lobe in 73% and 82%, respectively. (2) The decreased DV of FMZ depicted by SPM revealed the mesial temporal pathology in 91%. Positron emission tomography measurement of FDG uptake was most sensitive in detecting the side of the epileptic focus. On the other hand, SPM analysis of the DV of FMZ was the most sensitive method for delineating the actual epileptic focus.

Recent developments in Statistical Parametric Mapping (SPM) for continuum data (e.g. kinematic time series) have been adopted by the biomechanics research community with great interest. The Python/MATLAB package spm1d developed by T. Pataky has introduced SPM into the biomechanical literature, adapted originally from neuroimaging. The package already allows many of the statistical analyses common in biomechanics from a frequentist perspective. In this paper, we propose an application of Bayesian analogs of SPM based on Bayes factors and posterior probability with default priors using the BayesFactor package in R. Results are provided for two typical designs (two-sample and paired sample t-tests) and compared to classical SPM results, but more complex standard designs are possible in both classical and Bayesian frameworks. The advantages of Bayesian analyses in general and specifically for SPM are discussed. Scripts of the analyses are available as supplementary materials.

Quantitative Comparison of Functional Magnetic Resonance Imaging with Positron Emission Tomography Using a Force-Related Paradigm

Inappropriate intracranial hemodynamics in the natural course of MELAS

Neuroimaging is crucial in the presurgical evaluation of patients with medically refractory epilepsy. To improve the moderate sensitivity of [(18) F]fluorodeoxyglucose-positron emission tomography ((18) F-FDG-PET), our aim was to evaluate the usefulness of statistical parametric mapping (SPM) to localize the seizure-onset zone (SOZ) in PET studies deemed normal by visual assessment. Fifty-five patients with medically refractory epilepsy whose (18) F-FDG-PET was visually evaluated as normal were retrospectively included. Twenty of these patients had undergone surgical intervention. PET images were analyzed by SPM8 using a corrected p-value of p < 0.05 and three uncorrected p-values of p < 0.0001, p < 0.001, and p < 0.005, matched with minimum cluster sizes of k > 0, k > 20, k > 100, and k > 200, respectively. The SPM-identified potential seizure zone (SZ) was compared to the SOZ, which was determined by consensus during patient management meetings in the epilepsy unit, taking into account presurgical tests. Studies in which the SPM-identified potential SZ was concordant with the SOZ were considered "correctly localizing." The SPM threshold combination with the least restrictive p-value and greatest minimum cluster size achieved the highest rate of correctly localizing studies. When p < 0.005/k > 200 was used, 40% (22/55) of studies were correctly localizing, and the concordance obtained in the surgically intervened subgroup was substantial (к = 0.607, 95% confidence interval [CI] 0.258-0.957), which was comparable to the concordance obtained by magnetic resonance imaging (MRI) (к = 0.783, 95% CI 0.509-1.000). SPM offers improved SOZ localization in (18) F-FDG-PET studies that are negative on visual assessment. For this purpose, statistical parametric maps could be thresholded with liberal p-values and restrictive cluster sizes.

Objectives: To test the applicability of an automated method of magnetic resonance image analysis (voxel based morphometry) to detect presence and severity of regional grey matter density reduction—a proxy of...

Hallucinations are considered one of the primary symptoms of psychosis; however, their neural basis remains unclear. Voxel-based morphometry (VBM)1 studies have associated hallucinations with gray matter (GM) volume reduction in the superior temporal gyrus in schizophrenia.2 Although hallucinations are associated with brain connectivity,3 few studies have investigated their relationship with white matter (WM) volume. Moreover, these studies have shown inconsistent results.4, 5 The chronicity of illness and long-term medications for schizophrenia may limit the interpretation of previous findings.2 Thus, hallucination studies in clinical high risk for psychosis (CHR) and first-episode psychosis (FEP) are required, with minimal effects of chronicity of illness and medication. However, no VBM study has examined the relationship between hallucinations and WM volume in CHR and FEP. Therefore, we aimed to investigate the regional GM and WM volumes associated with hallucinations in CHR and FEP. We enrolled 57 individuals with CHR, 50 individuals with FEP, and 33 healthy controls (HCs). The Comprehensive Assessment of At-Risk Mental States-Japanese version6 was used to confirm whether ultra-high risk criteria7 were met. Table S1 summarizes the demographic and clinical data of the patients. Hallucination severity was assessed using the Positive and Negative Syndrome Scale (PANSS)8 P3 score. Fig. S1 shows the distribution of the severity of hallucinations. Some of those with a PANSS P3 score of 3 or higher were classified as having CHR because of the low frequency and duration of hallucinations. Magnetic resonance imaging (MRI) data were acquired with a 1.5-T Philips scanner. We examined the association of GM and WM volume with hallucination severity in the group that combined patients with CHR and FEP (CHR/FEP combined group) and performed group comparisons of GM and WM volume between the CHR/FEP combined and HC groups. Age, sex, and intracranial volume were entered as nuisance covariates for each analysis. VBM analysis was conducted using DARTEL9 in SPM12 (https://www.fil.ion.ucl.ac.uk/spm/software/spm12/) with standard smoothing of 8-mm full width at half maximum (FWHM). The initial statistical threshold was set at P < 0.001, uncorrected at the voxel level. The extent threshold for cluster size was set based on the expected number of voxels per cluster provided by SPM. Familywise error (FWE) correction at the cluster level (P < 0.05) was applied to identify significant clusters. Appendix S1 provides detailed information on these methods. This study was performed in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Tohoku University Graduate School of Medicine and Tohoku University Hospital. Written informed consent was obtained from participants aged 18 years or older and from the parents of those under 18 years of age, with written assent from the participants. The anonymity of participants was preserved. WM volume was not significantly correlated with hallucination severity in the CHR/FEP combined group after FWE correction at the cluster level. Reanalysis with 15-mm or 20-mm FWHM filtering did not show significant associations. Additionally, there was no significant difference in the GM and WM volumes between the CHR/FEP combined and HC groups. No regional GM volume abnormalities were significantly correlated with hallucination severity in the CHR/FEP combined group. Appendix S1, Figs. S2–S5, and Tables S2–S5 provide uncorrected results and detailed information regarding these results. To the best of our knowledge, this is the first VBM study to investigate WM volume related to hallucinations in CHR and FEP. We found no significant correlation between WM volume and hallucination severity. In contrast to previous studies in schizophrenia,2, 4, 5 this study examined the brain volume association of hallucinations in CHR and FEP. CHR and FEP are heterogeneous groups in the early stages of mental illness and do not necessarily convert to schizophrenia. Our results indicate that brain disturbances involved in hallucinations in CHR and FEP may be more subtle and/or inconsistent with those in schizophrenia. Diffusion tensor imaging, a neuroimaging method applied to CHR,10 may be suitable for examining structural abnormalities in the development of hallucinations. This study has some limitations. First, information regarding hallucinations is not detailed. Second, the cross-sectional design limited the interpretation of our findings. Third, we used an MRI scanner with a lower field strength than that of recent studies.4 Fourth, there were significant age differences between the groups. Fifth, automatic quality assurance for MRI scans was not performed. In conclusion, advanced neuroimaging studies are needed to reveal the mechanism of hallucinations. This work was supported by JSPS KAKENHI (grant number 18K07586). We thank the participants, staff of the SAFE clinic, and radiological technologists. The authors declare no conflicts of interest. Appendix S1. Supporting information Figure S1. Distribution of hallucination severity. CHR, clinical high risk for psychosis; FEP, first-episode psychosis; PANSS, Positive and Negative Syndrome Scale. Figure S2. Brain regions with lower gray matter volume in the CHR/FEP group compared to the HC group. Statistical threshold was set at P < 0.001, uncorrected at the voxel level. The threshold extent for cluster size was set to k = 117 based on the expected number of voxels per cluster provided by SPM. The full width at half maximum was set to 8-mm. CHR, clinical high risk for psychosis; FEP, first-episode psychosis; HC, healthy controls; SPM, Statistical Parametric Mapping Figure S3. Brain regions with lower white matter volume in the CHR/FEP group compared to the HC group. Statistical threshold was set at P < 0.001, uncorrected at the voxel level. The threshold extent for cluster size was set to k = 129 based on the expected number of voxels per cluster provided by SPM. The full width at half maximum was set to 8-mm. CHR, clinical high risk for psychosis; FEP, first-episode psychosis; HC, healthy controls; SPM, Statistical Parametric Mapping Figure S4. Positive correlation between gray matter volume and hallucination severity in the patients at clinical high risk for psychosis. Statistical threshold was set at P < 0.001, uncorrected at the voxel level. The threshold extent for cluster size was set to k = 101 based on the expected number of voxels per cluster provided by the SPM. The full width at half maximum was set to 8-mm. SPM, Statistical Parametric Mapping Figure S5. Negative correlation between white matter volume and hallucination severity in the patients at clinical high risk for psychosis. Statistical threshold was set at P < 0.001, uncorrected at the voxel level. The threshold extent for cluster size was set to k = 121 based on the expected number of voxels per cluster provided by the SPM. The full width at half maximum was set to 8-mm. SPM, Statistical Parametric Mapping Table S1. Demographic and clinical characteristics of the participants. †Educational level, CP-equivalent dose on MRI scan, PANSS positive, PANSS negative, PANSS general, PANSS total, PANSS P3: hallucinatory behavior, and days from enrollment to MRI scan were analyzed using the t-test. Age and intracranial volume were analyzed using one-way analysis of variance. Sex and antipsychotic use were analyzed using the chi-squared test. Significant results are shown in bold. CHR, clinical high risk for psychosis; CP-equivalent, chlorpromazine equivalent; FEP, first-episode psychosis; HC, healthy controls; PANSS, Positive and Negative Syndrome Scale. Table S2. Between-group comparison of regional gray matter volume. CHR/FEP < HC (extent threshold: 117 voxels). † Uncorrected p-value at voxel level. ‡ familywise error-corrected p-value at the cluster level. k, cluster size at P < 0.001 (uncorrected); CHR, clinical high risk for psychosis; FEP, first-episode psychosis; HC, healthy controls; L/R, left/right hemisphere; MNI, Montreal Neurological Institute. The extent threshold for cluster size was set based on the expected number of voxels per cluster provided by the SPM. The full width at half maximum was set to 8-mm. Table S3. Between group comparison of regional white matter volume. CHR/FEP < HC (extent threshold: 129 voxels). † Uncorrected P-value at voxel level. ‡ familywise error-corrected p-value at the cluster level. k, cluster size at P < 0.001 (uncorrected); CHR, clinical high risk for psychosis; FEP, first-episode psychosis; HC, healthy controls; L/R, left/right hemisphere; MNI, Montreal Neurological Institute. The extent threshold for cluster size was set based on the expected number of voxels per cluster provided by the SPM. The full width at half maximum was set to 8-mm. Table S4. Correlation between gray matter volume and hallucination severity in the patients with CHR. Positive correlation (extent threshold: 101 voxels). † Uncorrected p-value at voxel level. ‡ familywise error-corrected p-value at the cluster level. k, cluster size at P < 0.001 (uncorrected); CHR, clinical high risk for psychosis; L/R, left/right hemisphere; MNI, Montreal Neurological Institute. The extent threshold for cluster size was set based on the expected number of voxels per cluster provided by the SPM. The full width at half maximum was set to 8-mm. Table S5. Correlation between white matter volume and hallucination severity in the patients with CHR. Negative correlation (extent threshold: 121 voxels). † Uncorrected p-value at voxel level. ‡ familywise error-corrected p-value at the cluster level. k, cluster size at P < 0.001 (uncorrected); CHR, clinical high risk for psychosis; L/R, left/right hemisphere; MNI, Montreal Neurological Institute. The extent threshold for cluster size was set based on the expected number of voxels per cluster provided by the SPM. The full width at half maximum was set to 8-mm. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Imaging of Eating Disorders: Multiple Techniques to Demonstrate the Dynamic Brain

Testing anatomically specified hypotheses in functional imaging using cytoarchitectonic maps

We develop and apply an analytic method to predict peak counts in weak-lensing surveys. It is based on the theory of Gaussian random fields and suitable to quantify the level of spurious detections caused by chance projections of large-scale structures as well as the shape and shot noise contributed by the background galaxies. We compare our method to peak counts obtained from numerical ray-tracing simulations and find good agreement at the expected level. The number of peak detections depends substantially on the shape and size of the filter applied to the gravitational shear field. Our main results are that weak-lensing peak counts are dominated by spurious detections up to signal-to-noise ratios of 3--5 and that most filters yield only a few detections per square degree above this level, while a filter optimised for suppressing large-scale structure noise returns up to an order of magnitude more.