Brain Imaging in Schizophrenia

Specific Substantial Dysconnectivity in Schizophrenia: A Transdiagnostic Multimodal Meta-analysis of Resting-State Functional and Structural Magnetic Resonance Imaging Studies

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

CLINICAL PERFORMANCE OF RB82 MYOCARDIAL PERFUSION PET AND TC-99M SPECT IN PATIENTS WITH EXTREME OBESITY (BMI ≥ 40)

Unprecedented 4D spatiotemporal infant regional cerebral blood flow framework and region-specific physiology–function coupling across infancy were elucidated, highlighting strong physiology–function coupling specifically at the default-mode network to meet extraneuronal metabolic demand for network emergence.

Functional Connectivity of the Striatum in Schizophrenia and Psychotic Bipolar Disorder

ObjectiveDeep learning approaches have attracted attention for improving the scoring accuracy in computed tomography-less single photon emission computed tomography (SPECT). In this study, we proposed a novel deep learning approach referring to positron emission tomography (PET). The aims of this study were to analyze the agreement of representative voxel values and perfusion scores of SPECT-to-PET translation model-generated SPECT (SPECTSPT) against PET in 17 segments according to the American Heart Association (AHA).MethodsThis retrospective study evaluated the patient-to-patient stress, resting SPECT, and PET datasets of 71 patients. The SPECTSPT generation model was trained (stress: 979 image pairs, rest: 987 image pairs) and validated (stress: 421 image pairs, rest: 425 image pairs) using 31 cases of SPECT and PET image pairs using an image-to-image translation network. Forty of 71 cases of left ventricular base-to-apex short-axis images were translated to SPECTSPT in the stress and resting state (stress: 1830 images, rest: 1856 images). Representative voxel values of SPECT and SPECTSPT in the 17 AHA segments against PET were compared. The stress, resting, and difference scores of 40 cases of SPECT and SPECTSPT were also compared in each of the 17 segments.ResultsFor AHA 17-segment-wise analysis, stressed SPECT but not SPECTSPT voxel values showed significant error from PET at basal anterior regions (segments #1, #6), and at mid inferoseptal regions (segments #8, #9, and #10). SPECT, but not SPECTSPT, voxel values at resting state showed significant error at basal anterior regions (segments #1, #2, and #6), and at mid inferior regions (segments #8, #9, and #11). Significant SPECT overscoring was observed against PET in basal-to-apical inferior regions (segments #4, #10, and #15) during stress. No significant overscoring was observed in SPECTSPT at stress, and only moderate over and underscoring in the basal inferior region (segment #4) was found in the resting and difference states.ConclusionsOur PET-supervised deep learning model is a new approach to correct well-known inferior wall attenuation in SPECT myocardial perfusion imaging. As standalone SPECT systems are used worldwide, the SPECTSPT generation model may be applied as a low-cost and practical clinical tool that provides powerful auxiliary information for the diagnosis of myocardial blood flow.

Noninvasive imaging in the evaluation of a wide variety of cardiovascular diseases has gained an increasing role in the diagnostic strategy in current cardiology practice [1][2][3][4].This holds in particular for patients with myocardial ischaemia due to coronary artery disease (CAD) [5][6][7].Of the present imaging modalities, single-photon emission computed tomography (SPECT), positron emission tomography (PET) and cardiac magnetic resonance (CMR) have attained a major position when it comes to myocardial perfusion imaging [8][9][10][11][12].In the May 2012 issue of the Journal of the American College of Cardiology (JACC), Jaarsma et al. [13] from Maastricht University Medical Center evaluated the diagnostic accuracy of SPECT, PET and CMR for the diagnosis of obstructive CAD.Studies published between 1990 and 2010 identified by PubMed search and citation tracking were examined.A study was included if a perfusion imaging modality was used as a diagnostic test for the detection of obstructive CAD and coronary angiography as the reference standard (50 % diameter luminal stenosis).Out of a total of 3635 studies, 166 articles (including 17,901 patients) met the inclusion criteria: 114 SPECT, 37 CMR, and 15 PET studies.There were insufficient publications on perfusion echocardiography and computed tomography to include these modalities in the study.Patient-based analysis per imaging modality demonstrated pooled sensitivities of 88 % for SPECT, 84 % for PET , and 89 % for CMR; pooled specificities were 61 %, 81 %, and 76 %, respectively.The authors concluded that SPECT, PET, and CMR all yielded high sensitivities, whereas a broad range of specificities were observed.CMR and especially PET showed a significantly higher diagnostic accuracy than SPECT.However, SPECT is more widely available, less expensive, and most extensively validated.In addition, the use of attenuation programs improved the specificity of SPECT.CMR may provide a valid alternative without ionising radiation to the nuclear imaging methods.The authors suggested that referring physicians should consider these findings in the context of local expertise and internal logistics.The authors should be complimented for performing this impressive research.It is the first meta-analysis that has directly compared the three most commonly used techniques for myocardial perfusion imaging, i.e.SPECT, PET, and CMR.The present study emphasises that, from a clinical perspective, each of the studied imaging modalities is in principle suited for detection of abnormalities in myocardial perfusion imaging [14].As always, selective use is mostly dependent on the institutional availability of the imaging device(s), familiarity with the technique, and the individual expert knowledge of the treating physician [15].

The single photon emission computed tomography (SPECT) radiotracer [123I]iomazenil is used to assess benzodiazepine receptor binding parameters. These measurements are relative indices of benzodiazepine receptor concentration (B'max). To evaluate the ability of such indices in accurately accessing the B'max the authors compared them with absolute values of B'max, measured using positron emission tomography (PET). The authors performed SPECT, PET, and magnetic resonance imaging (MRI) studies on a group composed of seven subjects. For SPECT studies, the authors administered a single injection of [123I]iomazenil and estimated the total and specific distribution volumes (DV(T SPECT), DV(S SPECT)) and the binding potential (BP) using unconstrained (BP(SPECT)) and constrained (BP(C SPECT)) compartmental models. For PET studies, the authors used a multiinjection approach with [11C]flumazenil and unlabeled flumazenil to estimate absolute values of receptor concentration, B'max, and some other binding parameters. The authors studied the correlation of different binding parameters with B'max. To study the robustness of the binding parameter measurements at the pixel level, the authors applied a wavelet-based filter to improve signal-to-noise ratio of time-concentration curves, and the calculated kinetic parameters were used to build up parametric images. For PET data, the B'max and the DV(PET) were highly correlated (r = 0.988). This confirms that it is possible to use the DV(PET) to access benzodiazepine receptor density. For SPECT data, the correlation between DV(SPECT) estimated using a two- and three-compartment model was also high (r = 0.999). The DV(T SPECT) and BP(C SPECT) parameters estimated with a constrained three-compartment model or the DV(T''SPECT) parameter estimated with a two-compartment model were also highly correlated to the B'max parameter estimated with PET. Finally, the robustness of the binding parameters allowed the authors to build pixel-by-pixel parametric images using SPECT data.

Positron emission tomography (PET) and single photon emission computed tomography (SPECT) brain imaging are widely used as diagnostic tools for suspected dementia but no studies have directly compared participant views of the two procedures. We used a range of methods to explore preferences for PET and SPECT. Patients and controls (and accompanying carers) completed questionnaires immediately after undergoing PET and SPECT brain scans. Pulse rate data were collected during each scan. Scan attributes were prioritized using a card sorting exercise; carers and controls additionally answered willingness to pay (WTP) questions. Few differences were found either between the scans or groups of participants, although carers marginally preferred SPECT. Diagnostic accuracy was prioritized over other scan characteristics. Mean heart rate during both scans was lower than baseline heart rate measured at home (p < 0.001). Most participants viewed PET and SPECT scans as roughly equivalent and did not have a preference for either scan. Carer preference for SPECT is likely to reflect their desire to be with the patient (routine practice for SPECT but not for PET), suggesting that they should be able to accompany vulnerable patients throughout imaging procedures wherever possible. Pulse rate data indicated that brain imaging was no more stressful than a home visit (HV) from a researcher. The data do not support the anecdotal view that PET is a more burdensome procedure and the use of PET or SPECT scans in dementia should be based on diagnostic accuracy of the technique.

Phase I Study of Noninvasive Imaging of Adenovirus-mediated Gene Expression in the Human Prostate

CLR1404 is a theranostic molecular agent that can be radiolabeled with 124I (CLR 124) for positron emission tomography (PET) imaging, or 131I (CLR 131) for single-photon emission computed tomography (SPECT) imaging and targeted radionuclide therapy. This pilot study evaluated a pretreatment dosimetry methodology in a triple-negative breast cancer patient who was uniquely enrolled in both a CLR 124 PET imaging clinical trial and a CLR 131 therapeutic dose escalation clinical trial. Three-dimensional PET/CT images were acquired at 1, 3, 24, 48, and 120 h postinjection of 178 MBq CLR 124. One month later, pretherapy 2D whole-body planar images were acquired at 0.25, 5, 24, 48, and 144 h postinjection of 370 MBq CLR 131. Following the therapeutic administration of 1990 MBq CLR 131, 3D SPECT/CT images were acquired at 74, 147, 334, and 505 h postinjection. The therapeutic CLR 131 voxel-level absorbed dose was estimated from PET (RAPID PET) and SPECT (RAPID SPECT) images using a Geant4-based Monte Carlo dosimetry platform called RAPID (Radiopharmaceutical Assessment Platform for Internal Dosimetry), and region of interest (ROI) mean doses were also estimated using the OLINDA/EXM software based on PET (OLINDA PET), SPECT (OLINDA SPECT), and planar (OLINDA planar) images. The RAPID PET and OLINDA PET tracer-predicted ROI mean doses correlated well (m ≥ 0.631, R2 ≥ 0.694, p ≤ 0.01) with both the RAPID SPECT and OLINDA SPECT therapeutic mean doses. The 2D planar images did not have any significant correlations. The ROI mean doses differed by -4% to -43% between RAPID and OLINDA/EXM, and by -19% to 29% between PET and SPECT. The 3D dose distributions and dose volume histograms calculated with RAPID were similar for the PET/CT and SPECT/CT. This pilot study demonstrated that CLR 124 pretreatment PET images can be used to predict CLR 131 3D therapeutic dosimetry better than CLR 131 2D planar images. In addition, unlike OLINDA/EXM, Monte Carlo dosimetry methods were capable of accurately predicting dose heterogeneity, which is important for predicting dose-response relationships and clinical outcomes.

Single-photon emission computed tomography (SPECT) and positron emission tomography (PET) are non-invasive nuclear medicine techniques that can identify areas of abnormal myocardial perfusion. We assessed the prevalence of cardiovascular risk factors in patients with suspected coronary artery disease (CAD) undergoing SPECT or PET stress myocardial perfusion imaging (MPI). Based on significant risk factors associated with an abnormal MPI, we developed a nomogram for each cohort as a pretest that would be helpful in decision-making for clinicians. A total of 6,854 patients with suspected CAD who underwent stress myocardial perfusion imaging by SPECT or PET/CT was studied. As part of the baseline examination, clinical teams collected information on traditional cardiovascular risk factors: age, gender, body mass index, angina, dyspnea, diabetes, hypertension, hyperlipidemia, family history of CAD, and smoking. The prevalence of cardiovascular risk factors was different in the two cohorts of patients undergoing SPECT (n = 4,397) or PET (n = 2,457) myocardial perfusion imaging. A statistical significance was observed in both cohorts for age, gender, and diabetes. At multivariable analysis, only age and male gender were significant covariates in both cohorts. The risk of abnormal myocardial perfusion imaging related to age was greater in patients undergoing PET (odds ratio 4% vs. 1% per year). In contrast, male gender odds ratio was slightly higher for SPECT compared to PET (2.52 vs. 2.06). In the SPECT cohort, smoking increased the risk of abnormal perfusion of 24%. Among patients undergoing PET, diabetes and hypertension increased the risk of abnormal perfusion by 63% and 37%, respectively. For each cohort, we obtained a nomogram by significant risk factors at multivariable logistic regression. The area under the receiver operating characteristic curve associated with the nomogram was 0.67 for SPECT and 0.73 for the PET model. Patients with suspected CAD belonging to two different cohorts undergoing SPECT or PET stress myocardial perfusion imaging can have different cardiovascular risk factors associated with a higher risk of an abnormal MPI study. As crude variables, age, gender, and diabetes were significant for both cohorts. Net of the effect of other covariates, age and gender were the only risk factors in common between the two cohorts. Furthermore, smoking and type of stress test were significant for the SPECT cohort, where as diabetes and hypertension were significant for the PET cohort. Nomograms obtained by significant risk factors for the two cohorts can be used by clinicians to evaluate the risk of an abnormal study.

Hybrid PET-MRI Applications in Movement Disorders.

Radioembolization (RE) with 90Y microspheres has been recognized as an emerging treatment strategy for patients with liver tumors either primary or secondary. New tools for complex patient dosimetry, based on real absorbed dose distribution to the normal liver and tumor are under development by our research group at the Champalimaud Centre for the Unknown (CCU), Champalimaud Foundation (CF). Furthermore, we have been using the gamma-index quantitative approach to evaluate the degree of agreement between reference and target voxel-based dose distributions. In this research work, we quantitatively investigated the correlation between dose distributions calculated based on pre-treatment/reference Technetium-99m Macroaggregated Albumin (99mTc-MAA) Single Photon Emission Computed Tomography (SPECT) and post-treatment/target Yttrium-90 (90Y) Positron Emission Tomography (PET) images, to evaluate the predictive power of 99mTc-MAA SPECT maps in comparison with post-radioembolization 90Y PET maps. Voxel-based dose distributions were retrospectively calculated based on a total of 13 treatments from 10 patients submitted to RE with 90Y glass microspheres at CCU-CF. The dose distributions (reference and target) were co-registered to the same matrix resolution and a region extraction algorithm was applied to the entire data for each treatment so that only the liver was considered as the region of interest (ROI). In addition, each slice was normalized to the pixel with the maximum intensity value and a dose threshold was applied to the background level. The gamma-index test was then applied to all reference and target pairs of slices from each treatment image series (99mTc-MAA SPECT and 90Y PET), using the dose-difference (DD) and distance-to-agreement (DTA) tolerances. The computation based on 1766 dose maps (slices) included in this work, showed that the mean percentage of voxels passing gamma-index, for each patient, varies from 17% to 48%. Considering all the patients, the median of this variability is 35% and the mean value is 33% with a standard deviation of 10% In conclusion, the application of gamma-index tests to our data, with the tolerances considered (DD = 10% and DTA = 5mm), reveals good correlation between pre-treatment 99mTc-MAA SPECT dose maps and post-treatment 90Y PET dose maps in one third of the voxels analyzed. Considering that the deposition of the microspheres (glass and MAA) and the dose maps are heterogeneous, these preliminary results are encouraging and led us to further consider the application of this gamma-index quantitative approach together with dose-volume histograms to investigate the additional predictive power of 99mTc-MAA SPECT maps in comparison with post-therapy 90Y PET maps.

Objective To provide a new approach to further elucidate the underlying pathogenesis of major depressive disorder by using resting-state functional connectivity strengths(FCS) in unmedicated patients with major depressive disorder(MDD). Methods Thirty-three unmedicated patients with MDD and thirty-three normal controls underwent the resting-state functional magnetic resonance imaging(rs-fMRI).After preprocessing of rs-fMRI, the whole brain FCS values were constructed. Two-sample t-test was used to compare the FCS values of both groups to locate the regions with significant change. And correlation analysis was performed between the FCS values extracted from significantly different brain regions and Hamilton Depression Scale (HAMD24) scores. Results One sample t test had shown that high FCS values brain areas (hubs) of MDD patients and normal controls were mainly located in the default mode network (the prefrontal cortex, anterior cingulate gyrus, posterior cingulate gyrus, precuneus/cuneus, angular gyrus) and parietal cortex, lateral temporal cortex as well as occipital cortex. In comparison to the normal controls, the MDD patients had FCS values significantly decreased in the bilateral posterior cerebellar lobe (right posterior cerebellar t=-4.57, P<0.05; left posterior cerebellar t=-3.40,P<0.05), and FCS values increased in the right superior temporal gyrus (t=3.71,P<0.05) and left anterior insular lobe (t=3.91, P<0.05). There were no significant correlations between the HAMD24 scores and the FCS values in right/left posterior cerebellar (r=0.081, P=0.654; r=-0.028, P=0.877), right superior temporal gyrus (r=0.211, P=0.239) and left anterior insular lobe (r=-0.017,P=0.924). Conclusions These findings suggest abnormal functional connectivity in the bilateral posterior cerebellar lobe, right temporal lobe and left insular lobe in MDD. The FCS analysis may be used as a new research method to explore the pathogenesis of MDD. Key words: Depressive disorder; Resting state; Functional connectivity strengths