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Objective: The cerebellum is involved in cognitive processing and emotion control. Cerebellar alterations could explain symptoms of schizophrenia spectrum disorder (SZ) and bipolar disorder (BD). In addition, literature suggests that lithium might influence cerebellar anatomy. Our aim was to study cerebellar anatomy in SZ and BD, and investigate the effect of lithium. Methods: Participants from 7 centers worldwide underwent a 3T MRI. We included 182 patients with SZ, 144 patients with BD, and 322 controls. We automatically segmented the cerebellum using the CERES pipeline. All outputs were visually inspected. Results: Patients with SZ showed a smaller global cerebellar gray matter volume compared to controls, with most of the changes located to the cognitive part of the cerebellum (Crus II and lobule VIIb). This decrease was present in the subgroup of patients with recent‐onset SZ. We did not find any alterations in the cerebellum in patients with BD. However, patients medicated with lithium had a larger size of the anterior cerebellum, compared to patients not treated with lithium. Conclusion: Our multicenter study supports a distinct pattern of cerebellar alterations in SZ and BD. [ABSTRACT FROM AUTHOR]

BackgroundNeuroimaging studies have demonstrated an association between lithium (Li) treatment and brain structure in human subjects. A crucial unresolved question is whether this association reflects direct neurochemical effects of Li or indirect effects secondary to treatment or prevention of episodes of bipolar disorder (BD).MethodTo address this knowledge gap, we compared manually traced hippocampal volumes in 37 BD patients with at least 2 years of Li treatment (Li group), 19 BD patients with <3 months of lifetime Li exposure over 2 years ago (non-Li group) and 50 healthy controls. All BD participants were followed prospectively and had at least 10 years of illness and a minimum of five episodes. We established illness course and long-term treatment response to Li using National Institute of Mental Health (NIMH) life charts.ResultsThe non-Li group had smaller hippocampal volumes than the controls or the Li group (F2,102 = 4.97, p = 0.009). However, the time spent in a mood episode on the current mood stabilizer was more than three times longer in the Li than in the non-Li group (t51 = 2.00, p = 0.05). Even Li-treated patients with BD episodes while on Li had hippocampal volumes comparable to healthy controls and significantly larger than non-Li patients (t43 = 2.62, corrected p = 0.02).ConclusionsOur findings support the neuroprotective effects of Li. The association between Li treatment and hippocampal volume seems to be independent of long-term treatment response and occurred even in subjects with episodes of BD while on Li. Consequently, these effects of Li on brain structure may generalize to patients with neuropsychiatric illnesses other than BD. [ABSTRACT FROM AUTHOR]

Introduction: Minimized perfusion circuits (MPCs), although aiming at minimizing the adverse effects of cardiopulmonary bypass, have not yet gained popularity. This can be attributed to concerns regarding their safety, as well as lack of sufficient evidence of their benefit.Methods: Described is a randomized, multicentre study comparing the MPC - ROCsafeRX to standard cardiopulmonary bypass in patients undergoing elective coronary artery bypass grafting and/ or aortic valve replacement.Results: Five hundred patients were included in the study (252 randomized to the ROCsafeRX group and 248 to standard cardiopulmonary bypass). Both groups were well matched for demographic characteristics and type of surgery. No operative mortality and no device-related complications were encountered.Transfusion requirement (333 ± 603 vs. 587 ± 1010 ml; p=0.001), incidence of atrial fibrillation (16.3% vs. 24.2%; p=0.03) and the incidence of major adverse events (9.1% vs. 16.5%; p=0.02) were all in favour of the MPC group.Conclusion: These results confirm both the safety and efficacy of the ROCsafeRX MPC for a large variety of cardiac patients. Minimized perfusion circuits should, therefore, play a greater role in daily practice so that as many patients as possible can benefit from their advantages. [ABSTRACT FROM PUBLISHER]

OBJECTIVE: Converging evidence suggests that the subgenual cingulate (SGC) is implicated in regulation of mood and in the pathophysiology of mood disorders. Our objective was to carry out the first meta-analysis of SGC volumes in patients with mood disorders. METHODS: We reviewed 10 volumetric magnetic resonance imaging studies of SGC volumes in patients with unipolar depression and bipolar disorders. For meta-analysis, we used standardized differences between means (SDMs) and random effects models. In the search for sources of heterogeneity, we subdivided the studies on the basis of diagnosis and presence of family history. RESULTS: The volumes of left and right SGC in patients with mood disorders were significantly reduced relative to healthy control subjects (SDM -0.38, 95% confidence interval [CI] -0.67 to -0.1 and SDM -0.2, 95% CI -0.4 to -0.007, respectively). There were significant SGC volume reductions in patients with unipolar (left SGC SDM -0.5, 95% CI -0.92 to -0.07; right SGC SDM -0.33, 95% CI -0.64 to -0.02,), but not bipolar, disorder. Patients with a positive family history of mood disorders showed significant left SGC volume decrease (SDM -0.52, 95% CI -0.96 to -0.07), which was not present among subjects without family history of mood disorders. There was no association between age and SGC volumes. CONCLUSION: The available evidence suggests the existence of left and less robust right SGC volumetric reductions in patients with mood disorders, predominantly in those with unipolar depression. The effect size of this difference was moderate and increased in more homogeneous subgroups of patients with a positive family history. The clustering of SGC abnormalities in patients with a family history, their presence early in the illness course and their lack of progression with age make SGC a candidate for a primary vulnerability marker, although studies in unaffected high-risk subjects are missing. [ABSTRACT FROM AUTHOR]

The search for susceptibility genes for bipolar disorder (BD) depends on appropriate definitions of the phenotype. In this paper, we review data on diagnosis and clinical features of BD that could be used in genetic studies to better characterize patients or to define homogeneous subgroups. Clinical symptoms, long-term course, comorbid conditions, and response to prophylactic treatment may define groups associated with more or less specific loci. One such group is characterized by symptoms of psychosis and linkage to 13q and 22q. A second group includes mainly bipolar II patients with comorbid panic disorder, rapid mood switching, and evidence of chromosome 18 linkage. A third group comprises typical BD with an episodic course and favourable response to lithium prophylaxis. Reproducibility of cognitive deficits across studies raises the possibility of using cognitive profiles as endophenotypes of BD, with deficits in verbal explicit memory and executive function commonly reported. Brain imaging provides a more ambiguous data set consistent with heterogeneity of the illness. [ABSTRACT FROM AUTHOR]

Introduction Brain changes in bipolar disorders (BD) may represent inherited risk factors or consequences of the illness (brain plasticity). Neuroanatomical changes, which predispose for BD could aid in early diagnosis, whereas the neuronal sequellae of BD could yield biological outcome measures for prevention and treatment. Methods To separate neuroanatomical changes into those that increase the risk of BD versus those that result from it, we acquired MRI/clinical data from participants at different stages of BD, including: (1) affected and unaffected offspring of bipolar parents ( n = 86); (2) participants with substantial illness burden who had had at least 2 years of current Li treatment ( n = 37) or were Li naive ( n = 19). We also recruited 99 healthy controls matched to the above-mentioned cohorts by age and sex. Results Relative to controls, both the affected and unaffected offpring of bipolar probands showed increased right inferior frontal gyrus (rIFG) volume, but comparable hippocampal volumes and prefrontal N -acetyl aspartate (NAA) levels. Larger rIFG volume was associated with an increased risk of conversion to psychiatric disorders within 4 years following the MRI scanning (hazard ratio = 4.5). In contrast, Li naive patients with substantial illness burden had smaller rIFG, hippocampal volumes and prefrontal NAA levels than controls, who were comparable in these indices to the the Li treated subjects with substantial illness burden. Conclusions Brain structural changes in BD may not be static, but may instead result from an interplay between illness burden and compensatory processes. This illness related brain plasticity may be modulated by lithium treatment. [ABSTRACT FROM AUTHOR]

Introduction: Neuroprotective effects of lithium have been well documented in tissue cultures and animal models. The evidence for lithium related neuroprotection in human subjects is limited and inconsistent, likely due to methodological heterogeneity. Aims: To investigate the effects of lithium on brain chemistry and structure, we recruited bipolar patients selected for substantial illness burden and varied the exposure to lithium by using strict inclusion criteria. Methods: We obtained 1.5T magnetic resonance imaging data from 27 bipolar patients with at least 2 years of ongoing lithium treatment (Li group), 16 subjects with < 3 months lifetime exposure to lithium >2 years ago (non-Li group) and 21 healthy controls. Patient groups had to have at least 10 years of illness and 5 episodes. Results: The non-Li group had significantly lower hippocampal volumes (t=4.68,corrected p<0.05) and prefrontal cortex N-acetyl aspartate (NAA) levels (t=−2.91,corrected p<0.05) than controls, who showed comparable hippocampal volumes and NAA levels to the Li treated subjects. Duration of illness was negatively associated with NAA levels only in the non-Li, but not the Li group. Conclusions: Among patients selected for substantial illness burden, only those with no or minimal lifetime Li exposure had significantly lower prefrontal NAA levels and hippocampal volumes than controls. Patients with at least 2 years of ongoing Li treatment showed no such changes, despite substantial burden of illness. These findings provide indirect support for neuroprotective effects of lithium and negative effects of illness burden on brain chemistry and structure in patients with bipolar disorders. [ABSTRACT FROM AUTHOR]

Objective: As limitations exist across DSM criteria sets for defining and differentiating the bipolar disorders generally and their component bipolar I (BP‐1) and bipolar II (BP‐II) sub‐types, we sought to generate empirically based criteria. Method: We formed an international Task Force (TF) comprising members with bipolar disorder expertise, and who recruited 74 patients with a TF‐diagnosed bipolar I and 104 with a bipolar II condition (with patients responding to definitional queries and symptom questionnaires), while 33 unipolar depressed patients recruited by the first author also completed the symptom questionnaire. A factor analysis sought to determine granular hypo/manic constructs. Results: The bipolar disorder subjects strongly affirmed a new general definition of a bipolar disorder (capturing both manic and hypomanic episodes). While DSM‐5 requires impaired functioning, we established that a high percentage of individuals with a BP‐I or a BP‐II disorder reported improved functioning and therefore modified this criterion. Analyses identified syptoms with differential high rates in individuals with bipolar disorder and its sub‐types (and thus not simply capturing happiness), while a factor analysis generated seven symptom constructs both linked with and differing from DSM‐5 bipolar symptom criteria. Conclusion: This second‐stage report details a new set of criteria for differentiating the bipolar disorders from unipolar depressive conditions, while arguing for BP‐I and BP‐II disorders being differentiated principally by the respective presence or absence of psychotic features. Future studies will evaluate whether further modifications are required and examine for differential treatment benefits for those with a BP‐I versus a BP‐II condition. [ABSTRACT FROM AUTHOR]

Objective: Promptly establishing maintenance therapy could reduce morbidity and mortality in patients with bipolar disorder. Using a machine learning approach, we sought to evaluate whether lithium responsiveness (LR) is predictable using clinical markers. Method: Our data are the largest existing sample of direct interview‐based clinical data from lithium‐treated patients (n = 1266, 34.7% responders), collected across seven sites, internationally. We trained a random forest model to classify LR—as defined by the previously validated Alda scale—against 180 clinical predictors. Results: Under appropriate cross‐validation procedures, LR was predictable in the pooled sample with an area under the receiver operating characteristic curve of 0.80 (95% CI 0.78–0.82) and a Cohen kappa of 0.46 (0.4–0.51). The model demonstrated a particularly low false‐positive rate (specificity 0.91 [0.88–0.92]). Features related to clinical course and the absence of rapid cycling appeared consistently informative. Conclusion: Clinical data can inform out‐of‐sample LR prediction to a potentially clinically relevant degree. Despite the relevance of clinical course and the absence of rapid cycling, there was substantial between‐site heterogeneity with respect to feature importance. Future work must focus on improving classification of true positives, better characterizing between‐ and within‐site heterogeneity, and further testing such models on new external datasets. [ABSTRACT FROM AUTHOR]

Background: Larger grey matter volume of the inferior frontal gyrus (IFG) is among the most replicated biomarkers of genetic risk for bipolar disorders (BD). However, the IFG is a heterogeneous prefrontal region, and volumetric findings can be attributable to changes in cortical thickness (CT), surface area (SA) or gyrification. Here, we investigated the morphometry of IFG in participants at genetic risk for BD. Methods: We quantified the IFG cortical grey matter volume in 29 affected, 32 unaffected relatives of BD probands, and 42 controls. We then examined SA, CT, and cortical folding in subregions of the IFG. Results: We found volumetric group differences in the right IFG, with the largest volumes in unaffected high-risk and smallest in control participants (F 2,192 = 3.07, p = 0.01). The volume alterations were localized to the pars triangularis of the IFG (F 2,97 = 4.05, p = 0.02), with no differences in pars opercularis or pars orbitalis. Pars triangularis volume was highly correlated with its SA [Pearson r (101) = 0.88, p < 0.001], which significantly differed between the groups (F 2,97 = 4.45, p = 0.01). As with volume, the mean SA of the pars triangularis was greater in unaffected (corrected p = 0.02) and affected relatives (corrected p = 0.05) compared with controls. We did not find group differences in pars triangularis CT or gyrification. Conclusions: These findings strengthen prior knowledge about the volumetric findings in this region and provide a new insight into the localization and topology of IFG alterations. The unique nature of rIFG morphology in BD, with larger volume and SA early in the course of illness, could have practical implications for detection of participants at risk for BD. [ABSTRACT FROM AUTHOR]

Objective: Structural MRI (sMRI) increasingly offers insight into abnormalities inherent to schizophrenia. Previous machine learning applications suggest that individual classification is feasible and reliable and, however, is focused on the predictive performance of the clinical status in cross‐sectional designs, which has limited biological perspectives. Moreover, most studies depend on relatively small cohorts or single recruiting site. Finally, no study controlled for disease stage or medication's effect. These elements cast doubt on previous findings' reproducibility. Method: We propose a machine learning algorithm that provides an interpretable brain signature. Using large datasets collected from 4 sites (276 schizophrenia patients, 330 controls), we assessed cross‐site prediction reproducibility and associated predictive signature. For the first time, we evaluated the predictive signature regarding medication and illness duration using an independent dataset of first‐episode patients. Results: Machine learning classifiers based on neuroanatomical features yield significant intersite prediction accuracies (72%) together with an excellent predictive signature stability. This signature provides a neural score significantly correlated with symptom severity and the extent of cognitive impairments. Moreover, this signature demonstrates its efficiency on first‐episode psychosis patients (73% accuracy). Conclusion: These results highlight the existence of a common neuroanatomical signature for schizophrenia, shared by a majority of patients even from an early stage of the disorder. [ABSTRACT FROM AUTHOR]

BackgroundEarly diagnosis of schizophrenia could improve the outcomes and limit the negative effects of untreated illness. Although participants with schizophrenia show aberrant functional connectivity in brain networks, these between-group differences have a limited diagnostic utility. Novel methods of magnetic resonance imaging (MRI) analyses, such as machine learning (ML), may help bring neuroimaging from the bench to the bedside. Here, we used ML to differentiate participants with a first episode of schizophrenia-spectrum disorder (FES) from healthy controls based on resting-state functional connectivity (rsFC).MethodWe acquired resting-state functional MRI data from 63 patients with FES who were individually matched by age and sex to 63 healthy controls. We applied linear kernel support vector machines (SVM) to rsFC within the default mode network, the salience network and the central executive network.ResultsThe SVM applied to the rsFC within the salience network distinguished the FES from the control participants with an accuracy of 73.0% (p = 0.001), specificity of 71.4% and sensitivity of 74.6%. The classification accuracy was not significantly affected by medication dose, or by the presence of psychotic symptoms. The functional connectivity within the default mode or the central executive networks did not yield classification accuracies above chance level.ConclusionsSeed-based functional connectivity maps can be utilized for diagnostic classification, even early in the course of schizophrenia. The classification was probably based on trait rather than state markers, as symptoms or medications were not significantly associated with classification accuracy. Our results support the role of the anterior insula/salience network in the pathophysiology of FES. [ABSTRACT FROM AUTHOR]

Objective: To describe and integrate observations from bipolar patients responsive to lithium stabilization and their children. Method: Selected findings are described from the clinical and biological investigations of adults meeting research criteria for bipolar disorder and for responsiveness to lithium stabilization; and from prospective studies of the children of lithium responders and non-responders. Results: Response to prophylactic lithium identifies a valid subtype of bipolar disorder, however the search for biological markers of lithium response, while promising, has so far remained inconclusive. Adult responders to lithium stabilization exhibit definable clinical features which are also observable in their affected children. In prospective studies the children of bipolar parents develop symptoms earlier than reported previously, with marked differences between the offspring of lithium responders and non-responders. The illness evolves in predictable clinical stages, first from non-specific sleep and anxiety disorders to mood symptoms and then, often starting in adolescence, major depressive and later activated episodes. Conclusion: Investigating and comparing unequivocal responders and non-responders to long-term lithium treatment and their offspring is a fertile research strategy for addressing a multitude of clinical and research questions. [ABSTRACT FROM AUTHOR]

Minimized perfusion circuits (MPC) were found to reduce side effects of standard extracorporeal circulation (ECC). We evaluated the safety and efficacy of the ROCsafe™ MPC for aortic valve and aortic root surgery. One hundred and seventy patients were randomized for surgery using either MPC [n = 85, 30 female/55 male, mean age: 69.8 ± 11.8 years; aortic valve replacement (AVR): n = 40; AVR + coronary artery bypass graft (CABG): n = 31; David operation: n = 3; aortic root replacement (ARR): n = 11] or ECC [n = 85, 29 female/56 male, mean age: 67.7 ± 9.5 years; AVR: n = 39; AVR+CABG: n = 35, David operation: n = 2; ARR: n = 9]. Neurological status, length of ICU stay, C-reactive protein (CRP), blood count, transfusion requirements and bleeding volume were analyzed. The MPC system provided ultrasound-controlled de-airing. A small roller pump and a flexible reservoir were used for left ventricular venting. As a control, we used a standard ECC with cardiotomy suction and hardshell reservoir. Cross-clamp time (MPC: 76.5 ± 29.5; ECC: 79.0 ± 34.0 min) and bypass time (MPC: 103.0 ± 37.9; ECC: 106.9 ± 44.9 min) were comparable between groups. Transfusion requirements (red blood cells: MPC: 1.5 ± 1.5 vs. ECC: 2.2 ± 2.1 units [p = 0.05], frozen plasma: MPC: 1.2 ± 1.8 vs. ECC: 1.9 ± 2.4 units [p = 0.03]), postoperative bleeding (MPC: 521 ± 283 vs. ECC: 615 ± 326 ml/24 h, p = 0.09) were lower using MPC. ICU stay was shorter with MPC (1.6 ± 1.6 days) compared to ECC (2.4 ± 2.8 days, p = 0.001). One stroke occurred in each group. The ROCsafe™ MPC provides safe circulatory support for a wide range of aortic valve surgeries. Transfusion requirements, postoperative bleeding and length of ICU stay were markedly reduced compared to standard extracorporeal perfusion. [ABSTRACT FROM AUTHOR]

Early diagnosis of schizophrenia might reduce the negative impact of the untreated disease. Progressive functional/structural changes were repeatedly detected using classical between-group statistics. However, these findings have been due to their low sensitivity and specificity not clinically useful. Machine learning methods are able to learn from the data and make predictions on the individual level, which might have a diagnostic potential. We performed a classification of patients with the first episode of schizophrenia (FES) and healthy controls (HC) from the resting state functional connectivity (rsFC) and fractional anisotropy (FA) using machine learning on 1:1 age and sex matched samples of 63/63 patients/HC (rsFC) and 77/77 (DTI). Support vector machine distinguished between patients and controls with an accuracy 73.0% (p = 0.001) (rsFC) and 62.34% (p = 0.005) (DTI). These results were not influenced by symptoms or medication. Our work shows that rsFC and FA might be used to classify patients with FES and HC on the individual level. The classification reflects ‘’trait” markers of FES, as the symptoms and medication had no significant effect. Additionally the results of the analysis of rsFC show the significance of anterior insula in the pathophysiology of FES. [ABSTRACT FROM AUTHOR]