Remote cognitive assessment in severe mental illness: a scoping review.

Many individuals living with severe mental illness, such as schizophrenia, present cognitive deficits and reasoning biases negatively impacting clinical and functional trajectories. Remote cognitive assessment presents many opportunities for advancing research and treatment but has yet to be widely used in psychiatric populations. We conducted a scoping review of remote cognitive assessment in severe mental illness to provide an overview of available measures and guide best practices. Overall, 34 studies (n = 20,813 clinical participants) were reviewed and remote measures, psychometrics, facilitators, barriers, and future directions were synthesized using a logic model. We identified 82 measures assessing cognition in severe mental illness across 11 cognitive domains and four device platforms. Remote measures were generally comparable to traditional versions, though psychometric properties were infrequently reported. Facilitators included standardized procedures and wider recruitment, whereas barriers included imprecise measure adaptations, technology inaccessibility, low patient engagement, and poor digital literacy. Our review identified several remote cognitive measures in psychiatry across all cognitive domains. However, there is a need for more rigorous validation of these measures and consideration of potentially influential factors, such as sex and gender. We provide recommendations for conducting remote cognitive assessment in psychiatry and fostering high-quality research using digital technologies.

Clarifying associations between cortical thickness, subcortical structures, and a comprehensive assessment of clinical insight in enduring schizophrenia.

BACKGROUND: The relationship between poor insight and less favorable outcomes in schizophrenia has promoted research efforts to understand its neurobiological basis. Thus far, research on neural correlates of insight has been constrained by small samples, incomplete insight assessments, and a focus on frontal lobes. The purpose of this study was to examine associations of cortical thickness and subcortical volumes, with a comprehensive assessment of clinical insight, in a large sample of enduring schizophrenia patients. METHODS: Two dimensions of clinical insight previously identified by a factor analysis of 4 insight assessments were used: Awareness of Illness and Need for Treatment (AINT) and Awareness of Symptoms and Consequences (ASC). T1-weighted structural images were acquired on a 3 T MRI scanner for 110 schizophrenia patients and 69 healthy controls. MR images were processed using CIVET (version 2.0) and MAGeT and quality controlled pre and post-processing. Whole-brain and region-of-interest, vertex-wise linear models were applied between cortical thickness, and levels of AINT and ASC. Partial correlations were conducted between volumes of the amygdala, thalamus, striatum, and hippocampus and insight levels. RESULTS: No significant associations between both insight factors and cortical thickness were observed. Moreover, no significant associations emerged between subcortical volumes and both insight factors. CONCLUSIONS: These results do not replicate previous findings obtained with smaller samples using single-item measures of insight into illness, suggesting a limited role of neurobiological factors and a greater role of psychological processes in explaining levels of clinical insight.

Multi-atlas segmentation of the whole hippocampus and subfields using multiple automatically generated templates.

INTRODUCTION: Advances in image segmentation of magnetic resonance images (MRI) have demonstrated that multi-atlas approaches improve segmentation over regular atlas-based approaches. These approaches often rely on a large number of manually segmented atlases (e.g. 30-80) that take significant time and expertise to produce. We present an algorithm, MAGeT-Brain (Multiple Automatically Generated Templates), for the automatic segmentation of the hippocampus that minimises the number of atlases needed whilst still achieving similar agreement to multi-atlas approaches. Thus, our method acts as a reliable multi-atlas approach when using special or hard-to-define atlases that are laborious to construct. METHOD: MAGeT-Brain works by propagating atlas segmentations to a template library, formed from a subset of target images, via transformations estimated by nonlinear image registration. The resulting segmentations are then propagated to each target image and fused using a label fusion method. We conduct two separate Monte Carlo cross-validation experiments comparing MAGeT-Brain and basic multi-atlas whole hippocampal segmentation using differing atlas and template library sizes, and registration and label fusion methods. The first experiment is a 10-fold validation (per parameter setting) over 60 subjects taken from the Alzheimer's Disease Neuroimaging Database (ADNI), and the second is a five-fold validation over 81 subjects having had a first episode of psychosis. In both cases, automated segmentations are compared with manual segmentations following the Pruessner-protocol. Using the best settings found from these experiments, we segment 246 images of the ADNI1:Complete 1Yr 1.5 T dataset and compare these with segmentations from existing automated and semi-automated methods: FSL FIRST, FreeSurfer, MAPER, and SNT. Finally, we conduct a leave-one-out cross-validation of hippocampal subfield segmentation in standard 3T T1-weighted images, using five high-resolution manually segmented atlases (Winterburn et al., 2013). RESULTS: In the ADNI cross-validation, using 9 atlases MAGeT-Brain achieves a mean Dice's Similarity Coefficient (DSC) score of 0.869 with respect to manual whole hippocampus segmentations, and also exhibits significantly lower variability in DSC scores than multi-atlas segmentation. In the younger, psychosis dataset, MAGeT-Brain achieves a mean DSC score of 0.892 and produces volumes which agree with manual segmentation volumes better than those produced by the FreeSurfer and FSL FIRST methods (mean difference in volume: 80 mm(3), 1600 mm(3), and 800 mm(3), respectively). Similarly, in the ADNI1:Complete 1Yr 1.5 T dataset, MAGeT-Brain produces hippocampal segmentations well correlated (r>0.85) with SNT semi-automated reference volumes within disease categories, and shows a conservative bias and a mean difference in volume of 250 mm(3) across the entire dataset, compared with FreeSurfer and FSL FIRST which both overestimate volume differences by 2600 mm(3) and 2800 mm(3) on average, respectively. Finally, MAGeT-Brain segments the CA1, CA4/DG and subiculum subfields on standard 3T T1-weighted resolution images with DSC overlap scores of 0.56, 0.65, and 0.58, respectively, relative to manual segmentations. CONCLUSION: We demonstrate that MAGeT-Brain produces consistent whole hippocampal segmentations using only 9 atlases, or fewer, with various hippocampal definitions, disease populations, and image acquisition types. Additionally, we show that MAGeT-Brain identifies hippocampal subfields in standard 3T T1-weighted images with overlap scores comparable to competing methods.

Utilization of the ferrous sulfate (Fricke) dosimeter for evaluating the radioprotective potential of cystamine: experiment and Monte Carlo simulation.

Cystamine, an organic disulfide (RSSR), is among the best of the known radiation-protective compounds and has been used to protect normal tissues in clinical radiation therapy. Recently, it has also proved to be beneficial in the treatment of disorders of the central nervous system in animal models. However, the underlying mechanism of its action at the chemical level is not yet well understood. The present study aims at using the ferrous sulfate (Fricke) dosimeter to quantitatively evaluate, both experimentally and theoretically, the radioprotective potential of this compound. The well-known radiolysis of the Fricke dosimeter by (60)Co γ rays or fast electrons, based on the oxidation of ferrous ions to ferric ions by the oxidizing species (•)OH, HO(2)(•), and H(2)O(2) produced in the radiolytic decomposition of water, forms the basis for our method. The presence of cystamine in Fricke dosimeter solutions during irradiation prevents the radiolytic oxidation of Fe(2+) and leads to decreased ferric yields (or G values). The observed decrease in G(Fe(3+)) increases upon increasing the concentration of the disulfide compound over the range 0-0.1 M under both aerated and deaerated conditions. To help assess the basic radiation-protective mechanism of this compound, a full Monte Carlo computer code is developed to simulate in complete detail the radiation-induced chemistry of the studied Fricke/cystamine solutions. Benefiting from the fact that cystamine is reasonably well characterized in terms of radiation chemistry, this computer model proposes reaction mechanisms and incorporates specific reactions describing the radiolysis of cystamine in aerated and deaerated Fricke solutions that lead to the observable quantitative chemical yields. Results clearly indicate that the protective effect of cystamine originates from its radical-capturing ability, which allows this compound to act by competing with the ferrous ions for the various free radicals--especially (•)OH radicals and H(•) atoms--formed during irradiation of the surrounding water. Most interestingly, our simulation modeling also shows that the predominant pathway in the oxidation of cystamine by (•)OH radicals involves an electron-transfer mechanism, yielding RSSR(•+) and OH(-). A very good agreement is found between calculated G(Fe(3+)) values and experiment. This study concludes that Monte Carlo simulations represent a very efficient method for understanding indirect radiation damage at the molecular level.

Neural markers of remission in first-episode schizophrenia: a volumetric neuroimaging study of the hippocampus and amygdala.

OBJECTIVE: The temporolimbic region has been implicated in the pathophysiology in schizophrenia. More specifically, significantly smaller hippocampal volumes but not amygdala volumes have been identified at onset in first-episode schizophrenia (FES) patients. However, volumetric differences (namely, in the hippocampus) exhibit an ambiguous relationship with long-term outcome. So, we examined the relationship between hippocampus and amygdala volumes and early remission status. METHODS: We compared hippocampus and amygdala volumes between 40 non-remitted and 17 remitted FES patients and 57 healthy controls. Amygdala and hippocampus were manually traced with the hippocampus additionally segmented into three parts: body, head, and tail. Remission was defined as mild or less on both positive and negative symptoms over a period of 6 consecutive months as per the 2005 Remission in Schizophrenia Working Group criteria. RESULTS: A significant [group x structure x side] interaction revealed outcome groups differed in hippocampus tail volumes; significantly on the left (non-remitted=694+/-175 mm(3); remitted=855+/-133 mm(3); p=0.001) with a trend difference on the right (non-remitted=723+/-162 mm(3); remitted=833+/-126 mm(3); p=0.023). Groups did not differ in body, head, or amygdala volumes bi-laterally. CONCLUSIONS: A smaller hippocampal tail volume may represent a neural marker in FES patients who do not achieve early remission after the first 6 months of treatment. The early identification of patients with poor outcome with respect to the hippocampus tail may encourage the search for new, more target-specific, medications in hope of improving outcome and moving us towards a better understanding of the pathophysiology of schizophrenia.

Assessment of single and bound features in a working memory task in schizophrenia.

If disturbance of binding in long term memory is well established in schizophrenia, data concerning working memory maintenance are less clear. Feature binding in working memory was investigated in 19 patients with schizophrenia and 19 healthy controls. Binding was assessed by comparing two conditions in which participants had to retain four letters and four spatial locations. These features were presented either bound or separate. Results showed that both groups had better performances for bound than separate features, despite the fact that patients performed significantly worse than controls. When maintenance for isolated features was assessed, patients were severely disturbed for spatial locations but not for letters. Such a result suggests that reduced working memory performance in patients with schizophrenia for bound features is probably a consequence of a spatial deficit rather than a specific deficit of the binding process. Thus, not all form of binding are disturbed in schizophrenia.