Magnetic Resonance Imaging and the Prediction of Outcome in First-Episode Schizophrenia: A Review of Current Evidence and Directions for Future Research

Dazzan, Paola; Arango, Celso; Fleischacker, W. Wolfgang; Galderisi, Silvana; Glenthøj, Birte; Leucht, S.; Meyer‐Lindenberg, Andreas; Kahn, René S.; Rujescu, Dan; Sommer, Iris E.; Winter, Inge; McGuire, Philip

doi:10.1093/schbul/sbv024

Cited by 92 publications

(57 citation statements)

References 50 publications

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“…Some of these neuroanatomical abnormalities are already evident in the so‐called at‐risk mental state (ARMS) for psychosis (Dazzan et al., ), including GM volume reductions of prefrontal (Cannon, ; Smieskova et al., ), temporal (Fusar‐Poli et al., ; Smieskova et al., ) and cingulate cortices (Fusar‐Poli, McGuire, et al., ; Fusar‐Poli et al., ; Smieskova et al., ), parahippocampal gyrus and hippocampus (Fusar‐Poli, McGuire, et al., ; Thermenos et al., ), insula and caudate (Smieskova et al., ).…”

Section: Introductionmentioning

confidence: 99%

No associations between medial temporal lobe volumes and verbal learning/memory in emerging psychosis

Egloff

Lenz

Studerus

et al. 2019

Eur J of Neuroscience

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Grey matter (GM) volume alterations have been repeatedly demonstrated in patients with first episode psychosis (FEP). Some of these neuroanatomical abnormalities are already evident in the at‐risk mental state (ARMS) for psychosis. Not only GM alterations but also neurocognitive impairments predate the onset of frank psychosis with verbal learning and memory (VLM) being among the most impaired domains. Yet, their interconnection with alterations in GM volumes remains ambiguous. Thus, we evaluated associations of different subcortical GM volumes in the medial temporal lobe with VLM performance in antipsychotic‐naïve ARMS and FEP patients. Data from 59 ARMS and 31 FEP patients, collected within the prospective Früherkennung von Psychosen study, were analysed. Structural T1‐weighted images were acquired using a 3 Tesla magnetic resonance imaging scanner. VLM was assessed using the California Verbal Learning Test and its factors Attention Span, Learning Efficiency, Delayed Memory and Inaccurate Memory. FEP patients showed significantly enlarged volumes of hippocampus, pallidum, putamen and thalamus compared to ARMS patients. A significant negative association between amygdala and pallidum volume and Attention Span was found in ARMS and FEP patients combined, which however did not withstand correction for multiple testing. Although we found significant between‐group differences in subcortical volumes and VLM is among the most impaired cognitive domains in emerging psychosis, we could not demonstrate an association between low performance and subcortical GM volumes alterations in antipsychotic‐naïve patients. Hence, deficits in this domain do not appear to stem from alterations in subcortical structures.

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Section: Introductionmentioning

confidence: 99%

No associations between medial temporal lobe volumes and verbal learning/memory in emerging psychosis

Egloff

Lenz

Studerus

et al. 2019

Eur J of Neuroscience

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“…Predictive biomarkers are widely used to influence the treatment selection for a variety of diseases, namely cancer, but even in the assessment of experimental thermal pain (Wager et al, 2013). Dazzan et al concluded that alterations of gray and white matter identified on structural neuroimaging, predominantly distributed in the medial temporal and prefrontal cortices, are potential neuroanatomical markers for the prediction of poor symptomatic and functional outcome (Dazzan et al, 2015). There have also been studies that identified correlations between structural features and antipsychotic treatment response from the perspectives of both volume and morphology, involving asymmetry and hypogyria (Altamura et al, 2017;Dusi et al, 2017;Francis et al, 2018;Fung et al, 2014;Hutcheson, Clark, Bolding, White, & Lahti, 2014;Molina, Taboada, Aragues, Hernandez, & Sanz-Fuentenebro, 2014;Morch-Johnsen et al, 2015;Palaniyappan et al, 2013;Premkumar et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Prediction of early response to overall treatment for schizophrenia: A functional magnetic resonance imaging study

et al. 2019

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Introduction Treatment response at an early stage of schizophrenia is of considerable value with regard to future management of the disorder; however, there are currently no biomarkers that can inform physicians about the likelihood of response. Objects We aim to develop and validate regional brain activity derived from functional magnetic resonance imaging (fMRI) as a potential signature to predict early treatment response in schizophrenia. Methods Amplitude of low‐frequency fluctuation (ALFF) was measured at the start of the first/single episode resulting in hospitalization. Inpatients were included in a principal dataset ( n = 79) and a replication dataset ( n = 44). Two groups of healthy controls ( n = 87; n = 106) were also recruited for each dataset. The clinical response was assessed at discharge from the hospital. The predictive capacity of normalized ALFF in patients by healthy controls, ALFF ratio , was evaluated based on diagnostic tests and clinical correlates. Results In the principal dataset, responders exhibited increased baseline ALFF in the left postcentral gyrus/inferior parietal lobule relative to non‐responders. ALFF ratio of responders before treatment was significantly higher than that of non‐responders ( p < 0.001). The area under the receiver operating characteristic curve was 0.746 for baseline ALFF ratio to distinguish responders from non‐responders, and the sensitivity, specificity, and accuracy were 72.7%, 68.6%, and 70.9%, respectively. Similar results were found in the independent replication dataset. Conclusions Baseline regional activity of the brain seems to be predictive of early response to treatment for schizophrenia. This study shows that psycho‐neuroimaging holds promise for influencing the clinical treatment and management of schizophrenia.

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“…Finding predictors of response to antipsychotic drug treatment is of critical importance to improving outcomes for psychotic disorders [1,2]. A priori identification of patients who are not likely to respond to a specific treatment strategy could reduce the number and length of ineffective treatment trials.…”

Section: Introductionmentioning

confidence: 99%

Structural similarity networks predict clinical outcome in early-phase psychosis

Homan

DeRosse

Szeszko

et al. 2019

Neuropsychopharmacol.

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Despite recent advances, there is still a major need for prediction of treatment success in schizophrenia, a condition long considered a disorder of dysconnectivity in the brain. Graph theory provides a means to characterize the connectivity in both healthy and abnormal brains. We calculated structural similarity networks in each participant and hypothesized that the "hubness", i.e., the number of edges connecting a node to the rest of the network, would be associated with clinical outcome. This prospective controlled study took place at an academic research center and included 82 early-phase psychosis patients (23 females; mean age [SD] = 21.6 [5.5] years) and 58 healthy controls. Medications were administered in a double-blind randomized manner, and patients were scanned at baseline prior to treatment with second-generation antipsychotics. Symptoms were assessed with the Brief Psychiatric Rating Scale at baseline and over the course of 12 weeks. Nodal degree of structural similarity networks was computed for each subject and entered as a predictor of individual treatment response into a partial least squares (PLS) regression. The model fit was significant in a permutation test with 1000 permutations (P = 0.006), and the first two PLS regression components explained 29% (95% CI: 27; 30) of the variance in treatment response after cross-validation. Nodes loading strongly on the first PLS component were primarily located in the orbito-and prefrontal cortex, whereas nodes loading strongly on the second PLS component were primarily located in the superior temporal, precentral, and middle cingulate cortex. These data suggest a link between brain network morphology and clinical outcome in early-phase psychosis.Neuropsychopharmacology (2019) 44:915-922; https://doi.Structural similarity networks predict clinical outcome in early-phase. . . P Homan et al. Neuropsychopharmacology (2019) 44:915 -922 1234567890();,:

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Magnetic Resonance Imaging and the Prediction of Outcome in First-Episode Schizophrenia: A Review of Current Evidence and Directions for Future Research

Cited by 92 publications

References 50 publications

No associations between medial temporal lobe volumes and verbal learning/memory in emerging psychosis

No associations between medial temporal lobe volumes and verbal learning/memory in emerging psychosis

Prediction of early response to overall treatment for schizophrenia: A functional magnetic resonance imaging study

Structural similarity networks predict clinical outcome in early-phase psychosis

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