Anatomic abnormalities of hippocampal subfields in never-treated and antipsychotic-treated patients with long-term schizophrenia

A longitudinal study of hippocampal subfield volumes and hippocampal glutamate levels in antipsychotic-naïve first episode psychosis patients

BACKGROUND

Previous studies have implicated hippocampal abnormalities in the neuropathology of psychosis spectrum disorders. Reduced hippocampal volume has been reported across all illness stages, and this atrophy has been hypothesized to be the result of glutamatergic excess. To test this hypothesis, we measured hippocampal subfield volumes and hippocampal glutamate levels in antipsychotic naïve first episode psychosis patients (FEP) and the progression of volume decline and changes in glutamate levels over a 16-week antipsychotic drug (APD) trial. We aimed to determine if subfield volumes at baseline were associated with glutamate levels, and if baseline glutamate levels were predictive of change in subfield volumes over time.

METHODS

We enrolled ninety-three medication-naïve FEP participants and 80 matched healthy controls (HC). T1 and T2 weighted images and magnetic resonance spectroscopy (MRS) data from a voxel prescribed in the left hippocampus were collected from participants at baseline and after 6 and 16 weeks of APD treatment. Hippocampal subfield volumes were assessed using FreeSurfer 7.1.1., while glutamate levels were quantified using jMRUI version 6.0. Data were analyzed using linear mixed models.

RESULTS

We found regional subfield volume deficits in the CA1, and presubiculum in FEP at baseline, that further expanded to include the molecular and granule cell layer of the dentate gyrus (GC/ML/DG) and CA4 by week 16. Baseline hippocampal glutamate levels in FEP were not significantly different than those of HC, and there was no effect of treatment on glutamate. Glutamate levels were not related to initial subfield volumes or volume changes over 16 weeks.

CONCLUSION

We report a progressive loss of hippocampal subfield volumes over a period of 16 weeks after initiation of treatment, suggestive of early progression in neuropathology. Our results do not suggest a role for glutamate as a driving factor. This study underscores the need to further research the mechanism(s) underlying this phenomenon as it has implications for early intervention to preserve cognitive decline in FEP participants.

Neuroimage Analysis Methods and Artificial Intelligence Techniques for Reliable Biomarkers and Accurate Diagnosis of Schizophrenia: Achievements Made by Chinese Scholars Around the Past Decade

BACKGROUND AND HYPOTHESIS

Schizophrenia (SZ) is characterized by significant cognitive and behavioral disruptions. Neuroimaging techniques, particularly magnetic resonance imaging (MRI), have been widely utilized to investigate biomarkers of SZ, distinguish SZ from healthy conditions or other mental disorders, and explore biotypes within SZ or across SZ and other mental disorders, which aim to promote the accurate diagnosis of SZ. In China, research on SZ using MRI has grown considerably in recent years.

STUDY DESIGN

The article reviews advanced neuroimaging and artificial intelligence (AI) methods using single-modal or multimodal MRI to reveal the mechanism of SZ and promote accurate diagnosis of SZ, with a particular emphasis on the achievements made by Chinese scholars around the past decade.

STUDY RESULTS

Our article focuses on the methods for capturing subtle brain functional and structural properties from the high-dimensional MRI data, the multimodal fusion and feature selection methods for obtaining important and sparse neuroimaging features, the supervised statistical analysis and classification for distinguishing disorders, and the unsupervised clustering and semi-supervised learning methods for identifying neuroimage-based biotypes. Crucially, our article highlights the characteristics of each method and underscores the interconnections among various approaches regarding biomarker extraction and neuroimage-based diagnosis, which is beneficial not only for comprehending SZ but also for exploring other mental disorders.

CONCLUSIONS

We offer a valuable review of advanced neuroimage analysis and AI methods primarily focused on SZ research by Chinese scholars, aiming to promote the diagnosis, treatment, and prevention of SZ, as well as other mental disorders, both within China and internationally.

Neurostructural, Neurofunctional, and Clinical Features of Chronic, Untreated Schizophrenia: A Narrative Review

Studies of individuals with chronic, untreated schizophrenia (CUS) can provide important insights into the natural course of schizophrenia and how antipsychotic pharmacotherapy affects neurobiological aspects of illness course and progression. We systematically review 17 studies on the neuroimaging, cognitive, and epidemiological aspects of CUS individuals. These studies were conducted at the Shanghai Mental Health Center, Institute of Mental Health at Peking University, and Huaxi MR Research Center between 2013 and 2021. CUS is associated with cognitive impairment, severe symptoms, and specific demographic characteristics and is different significantly from those observed in antipsychotic-treated individuals. Furthermore, CUS individuals have neurostructural and neurofunctional alterations in frontal and temporal regions, corpus callosum, subcortical, and visual processing areas, as well as default-mode and somatomotor networks. As the disease progresses, significant structural deteriorations occur, such as accelerated cortical thinning in frontal and temporal lobes, greater reduction in fractional anisotropy in the genu of corpus callosum, and decline in nodal metrics of gray mater network in thalamus, correlating with worsening cognitive deficits and clinical outcomes. In addition, striatal hypertrophy also occurs, independent of antipsychotic treatment. Contrasting with the negative neurostructural and neurofunctional effects of short-term antipsychotic treatment, long-term therapy frequently results in significant improvements. It notably enhances white matter integrity and the functions of key subcortical regions such as the amygdala, hippocampus, and striatum, potentially improving cognitive functions. This narrative review highlights the progressive neurobiological sequelae of CUS, the importance of early detection, and long-term treatment of schizophrenia, particularly because treatment may attenuate neurobiological deterioration and improve clinical outcomes.

Structural alteration of hippocampal subfields in type 2 diabetes mellitus patients with dyslipidemia

OBJECTIVE

To explore alterations in hippocampal subfield volumes in type 2 diabetes mellitus (T2DM) patients with dyslipidemia using hippocampal subfield segmentation.

METHODS

A total of 99 T2DM patients were prospectively recruited and divided into two groups based on the presence or absence of dyslipidemia: the T2DM dyslipidemia group and the T2DM normal lipidemia group. Additionally, 57 healthy volunteers were recruited as the healthy control (HC) group. General clinical data and cognitive psychological scale scores were collected. Subgroup analyses of T2DM patients were conducted based on the presence or absence of mild cognitive impairment (MCI). Hippocampal subfield volumes were analyzed using a general linear model with post-hoc Bonferroni correction. Significant differential hippocampal subfields were further analyzed in subgroups using the general linear model with post-hoc Bonferroni tests. Partial correlation analyses were performed to assess correlations between subfield-specific volumes and lipid and glucose metabolism indicators, as well as cognitive psychological scale scores. P-values from partial correlation analyses were corrected using the false discovery rate (FDR).

RESULTS

Volumes of the bilateral hippocampal tail, left presubiculum_body, and right subiculum_body were significantly reduced in the T2DM dyslipidemia group compared to both the HC group and the T2DM normal lipidemia group. Post-hoc analyses revealed that the T2DM dyslipidemia group had the smallest hippocampal subfield volumes. Further subgroup analysis showed that T2DM dyslipidemia patients with MCI exhibited the most pronounced volume reductions in the bilateral hippocampal tail and right subiculum_body. After FDR correction, partial correlation analysis indicated that, in the T2DM dyslipidemia group, the left hippocampal tail volume was positively correlated with the Montreal Cognitive Assessment score. In the T2DM dyslipidemia without MCI group, the volume of the right subiculum_body was negatively correlated with fasting insulin levels and the insulin resistance index, but positively correlated with total cholesterol and low-density lipoprotein cholesterol levels. In T2DM patients with normal lipidemia without MCI, the volume of the right subiculum_body was positively correlated with TC levels.

CONCLUSION

T2DM patients with dyslipidemia, especially those with MCI, exhibit significant atrophy in hippocampal subfield volumes, with correlations observed between lipid levels and hippocampal subfield volume changes. These findings suggest that lipid alterations may play an essential role in hippocampal structural abnormalities and cognitive impairment in T2DM patients. This study provides new insights into the neuropathophysiological mechanisms underlying brain alterations and cognitive decline in T2DM.

Altered Volumes of the Amygdala and Hippocampus in the Brain of Suicidal Patients with First Episode Schizophrenia

Suicide remains a significant cause of premature death in schizophrenia patients. Structural alterations in the brain and neurobiological mechanisms behind suicidal behavior (SB) in first-episode schizophrenia (FES) have received increasing attention. The amygdala and hippocampus regulate behaviors such as risk-taking, impulsivity, and emotional processing. Abnormalities in these regions have been linked with suicidal ideation, behavior, and psychotic symptoms. However, the association remains unclear. The study included 20 FES patients with current SB, 51 FES patients without SB, and 42 healthy controls. All patients were subjected to clinical evaluations to assess psychotic symptoms and suicidal ideation and behavior, both current and lifetime. T1-weighted magnetic resonance imaging scans were processed through two web-based automatic analysis tools, MRICloud, and volBrain. Bilateral amygdala volumes were found to be significantly lower in the patient groups, while schizophrenia and suicidal ideation had opposite effects on amygdala volumes. Hippocampal subfields such as the right Cornu Amnonis (CA) fields varied according to the clinical status of the patients, including the severity of suicidal ideation and behavior. These findings support not only the involvement of the amygdala and hippocampus in SB and schizophrenia but also their roles in the discrimination of SB in patients with schizophrenia.

The associations of peripheral interleukin alterations and hippocampal subfield volume deficits in schizophrenia

The hippocampus is one of the brain regions most vulnerable to inflammatory insults, and the relationships between peripheral inflammation and hippocampal subfields in patients with schizophrenia remain unclear. In this study, forty-six stably medicated patients with schizophrenia and 48 demographically matched healthy controls (HCs) were recruited. The serum levels of IL - 1β, IL-6, IL-10, and IL-12p70 were measured, and 3D high-resolution T1-weighted magnetic resonance imaging was performed. The IL levels and hippocampal subfield volumes were both compared between patients and HCs. The associations of altered IL levels with hippocampal subfield volumes were assessed in patients. Patients with schizophrenia demonstrated higher serum levels of IL-6 and IL-10 but lower levels of IL-12p70 than HCs. In patients, the levels of IL-6 were positively correlated with the volumes of the left granule cell layer of the dentate gyrus (GCL) and cornu Ammonis (CA) 4, while the levels of IL-10 were negatively correlated with the volumes of those subfields. IL-6 and IL-10 might have antagonistic roles in atrophy of the left GCL and CA4. This suggests a complexity of peripheral cytokine dysregulation and the potential for its selective effects on hippocampal substructures, which might be related to the pathophysiology of schizophrenia.

Hippocampal subfields in remitted schizophrenia

BACKGROUND

Current evidence of volume changes in hippocampal subdivisions in schizophrenia remains inconsistent, and few studies have investigated the relationship between regional hippocampal volumes and symptom remission.

METHODS

In this cross-sectional study, we recruited 31 patients with schizophrenia and 31 healthy controls (HCs). Symptomatic remission in schizophrenia was determined according to Remission in Schizophrenia Working Group criteria. The volumes of hippocampal longitudinal subregions and transverse subfields were measured using manual and automatic techniques, respectively. Between-group regional hippocampal volume differences were analyzed using multivariate analysis of covariance followed by univariate analysis of covariance.

RESULTS

Compared with the HCs, the patients with schizophrenia had smaller bilateral heads and tails along the longitudinal axis; they also had reduced volumes of the bilateral CA1, CA3, CA4, GC-ML-DG, molecular layer, tail, left subiculum, left HATA, and right parasubiculum along the transverse axis in the hippocampus (all corrected p < 0.05). Furthermore, compared with the HCs and patients with remitted schizophrenia, the patients with nonremitted schizophrenia had smaller bilateral hippocampal tail subfields (corrected p < 0.05).

CONCLUSION

Our results indicated that the pathophysiology and symptomatic remission of schizophrenia are related to changes in the volumes of hippocampal subdivisions. These volume changes might be clinically relevant as biomarkers for schizophrenia identification and treatment.

The cortical hypogyrification pattern in antipsychotic-naive first-episode schizophrenia

Schizophrenia is thought to be a neurodevelopmental disease with high genetic heritability, and evidence from neuroimaging studies has consistently shown widespread cortical local gyrification index (LGI) alterations; however, genes accounting for LGI alterations in schizophrenia remain unknown. The present study examined the LGI alterations in first-episode antipsychotic-naive schizophrenia compared with controls (235 patients and 214 controls); transcription-neuroimaging association analysis was used to evaluate the relationship between LGI deficits and specific risk genes. The expression profiles of 232 schizophrenia risk genes were extracted from six donated normal brains from the Allen Human Brain Atlas database. The correlation between LGI alterations and clinical symptoms was also tested. We found lower LGI values involved in frontotemporal regions and limbic systems. Nonparametric correlation analysis showed that 83 risk genes correlated with the hypogyrification pattern in schizophrenia. These identified risk genes were functionally enriched for the development of the central nervous system. The LGI in the left superior temporal gyrus was negatively associated with Positive and Negative Syndrome Scale negative symptoms. In summary, the present study provides a set of risk genes possibly related to the hypogyrification pattern in antipsychotic-naive first-episode schizophrenia, which could help to unveil the neurobiological underpinnings of cortical impairments in early-stage schizophrenia.

The effect of initial antipsychotic treatment on hippocampal and amygdalar volume in first-episode schizophrenia is influenced by age

BACKGROUND

Antipsychotic treatment has been shown to yield hippocampal and amygdalar volumetric changes in first-episode schizophrenia (FES). However, whether antipsychotic induced volumetric changes interact with age remains unclear.

METHODS

The current study includes data from 120 medication naïve FES patients and 110 matched healthy controls (HC). Patients underwent MRI scans before (T1) and after (T2) antipsychotic treatment. HCs underwent MRI scans at baseline only. The hippocampus and amygdala were segmented via Freesurfer 7. General linear models were conducted to investigate the effect of age by diagnosis interaction on baseline volume. Linear mixed models (LMM) were used to detect the effect of age on volumetric changes from pre to post treatment in FES.

RESULTS

GLM revealed a trending effect (F = 3.758, p = 0.054) of age by diagnosis interaction on the baseline volume of the left (whole) hippocampus, with older FES patients showing smaller hippocampal volumes, relative to HC, when controlled sex, education years, and ICV. LMM showed a significant age by time-point interaction effect (F = 4.194, estimate effect = -1.964, p = 0.043) on left hippocampal volume in all FES and significant time effect(F = 6.608,T1-T2(estimate effect) = 62.486, p = 0.011), whereby younger patients showed greater hippocampal volumetric decreases following treatment. At the subfield level, a significant time effect emerged in left molecular_layer_HP (F = 4.509,T1-T2(estimate effect) = 12.424, p = 0.032, FDR corrected) and left cornu ammonis(CA)4 (F = 4.800,T1-T2(estimate effect) = 7.527, p = 0.046, FDR corrected), implying volumetric reduction after treatment in these subfields.

CONCLUSIONS

Our findings suggest that age plays an important role in the neuroplastic mechanisms of initial antipsychotics on the hippocampus and amygdala of schizophrenia.

Oxidative stress impairs cognitive function by affecting hippocampal fimbria volume in drug-naïve, first-episode schizophrenia

Objective

The aim of the present study was to explore influencing factors of cognitive impairments and their interrelationships in drug-naïve, first-episode schizophrenia (SCZ).

Methods

Patients with drug naïve, first episode SCZ and healthy controls (HCs) were enrolled. Cognitive function was assessed by the MATRICS Consensus Cognitive Battery (MCCB). Serum levels of oxidative stress indices, including folate, superoxide dismutase (SOD), uric acid (UA) and homocysteine (Hcy), were determined after an overnight fast. Hippocampal subfield volumes were measured using FreeSurfer. Mediation models were conducted using the SPSS PROCESS v3.4 macro. A false discovery rate (FDR) correction was applied for multiple comparisons.

Results

Sixty-seven patients with SCZ and 65 HCs were enrolled in our study. The patient group had significantly lower serum levels of folate and SOD and higher serum levels of HCY compared with the HCs (all p < 0.05). The patient group had a significantly smaller volume of the whole hippocampus than the HC group (p < 0.05). We also found significant volume differences between the two groups in the following subfields: CA1, molecular layer, GC-ML-DG and fimbria (all p < 0.05, uncorrected). The partial correlation analysis controlling for age and sex showed that the fimbria volume in the patient group was significantly positively associated with NAB scores (r = 0.382, pFDR = 0.024); serum levels of SOD in the patient group showed a significantly positive correlation with fimbria volume (r = 0.360, pFDR = 0.036). Mediation analyses controlling for age and sex showed that the serum levels of SOD in patients with SCZ had significant indirect effects on the NAB scores which were mediated by the fimbria volume [indirect effect = 0.0565, 95% CI from the bootstrap test excluding zero (0.0066 to 0.0891)].

Conclusion

Oxidative stress, a reduction in hippocampal subfield volumes and cognitive impairments occur in early SCZ. Oxidative stress impairs cognitive function by affecting hippocampal subfield volumes.

Clinical MRI morphological analysis of functional seizures compared to seizure-naïve and psychiatric controls

PURPOSE

Functional seizures (FS), also known as psychogenic nonepileptic seizures (PNES), are physical manifestations of acute or chronic psychological distress. Functional and structural neuroimaging have identified objective signs of this disorder. We evaluated whether magnetic resonance imaging (MRI) morphometry differed between patients with FS and clinically relevant comparison populations.

METHODS

Quality-screened clinical-grade MRIs were acquired from 666 patients from 2006 to 2020. Morphometric features were quantified with FreeSurfer v6. Mixed-effects linear regression compared the volume, thickness, and surface area within 201 regions-of-interest for 90 patients with FS, compared to seizure-naïve patients with depression (n = 243), anxiety (n = 68), and obsessive-compulsive disorder (OCD, n = 41), respectively, and to other seizure-naïve controls with similar quality MRIs, accounting for the influence of multiple confounds including depression and anxiety based on chart review. These comparison populations were obtained through review of clinical records plus research studies obtained on similar scanners.

RESULTS

After Bonferroni-Holm correction, patients with FS compared with seizure-naïve controls exhibited thinner bilateral superior temporal cortex (left 0.053 mm, p = 0.014; right 0.071 mm, p = 0.00006), thicker left lateral occipital cortex (0.052 mm, p = 0.0035), and greater left cerebellar white-matter volume (1085 mm³, p = 0.0065). These findings were not accounted for by lower MRI quality in patients with FS.

CONCLUSIONS

These results reinforce prior indications of structural neuroimaging correlates of FS and, in particular, distinguish brain morphology in FS from that in depression, anxiety, and OCD. Future work may entail comparisons with other psychiatric disorders including bipolar and schizophrenia, as well as exploration of brain structural heterogeneity within FS.

Effects of Antipsychotic Medications and Illness Duration on Brain Features That Distinguish Schizophrenia Patients

BACKGROUND AND HYPOTHESIS

Previous studies have reported effects of antipsychotic treatment and illness duration on brain features. This study used a machine learning approach to examine whether these factors in aggregate impacted the utility of MRI features for differentiating individual schizophrenia patients from healthy controls.

STUDY DESIGN

This case-control study used patients with never-treated first-episode schizophrenia (FES, n = 179) and long-term ill schizophrenia (LTSZ, n = 30), with follow-up of the FES group after treatment (n = 71), a group of patients who had received long-term antipsychotic treatment (n = 93) and age and sex-matched healthy controls (n = 373) for each patient group. A multiple kernel learning classifier combining both structural and functional brain features was used to discriminate individual patients from controls.

STUDY RESULTS

MRI features differentiated untreated FES (0.73) and LTSZ (0.83) patients from healthy controls with moderate accuracy, but accuracy was significantly higher in antipsychotic-treated FES (0.94) and LTSZ (0.98) patients. Treatment was associated with significantly increased accuracy of case identification in both early course and long-term ill patients (both p < .001). Effects of illness duration, examined separately in treated and untreated patients, were less robust.

CONCLUSIONS

Our results demonstrate that initiation of antipsychotic treatment alters brain features in ways that further distinguish individual schizophrenia patients from healthy individuals, and have a modest effect of illness duration. Intrinsic illness-related brain alterations in untreated patients, regardless of illness duration, are not sufficiently robust for accurate identification of schizophrenia patients.

The effect of first- and second-generation antipsychotics on brain morphology in schizophrenia: A systematic review of longitudinal magnetic resonance studies with a randomized allocation to treatment arms

Schizophrenia manifests as loss of brain volume in specific areas in a progressive nature and an important question concerns whether long-term treatment with medications contributes to this. The aim of the current PRISMA systematic review was to search for prospective studies involving randomization to treatment. PROSPERO ID: CRD42020197874. The MEDLINE/PUBMED was searched and it returned 2638 articles; 3 were fulfilling the inclusion criteria. A fourth was published later; they included 359 subjects, of whom 86 were healthy controls, while the rest were first-episode patients, with 91 under olanzapine, 93 under haloperidol, 48 under risperidone, 5 under paliperidone, 6 under ziprasidone, and 30 under placebo. Probably one-third of patients were suffering from a psychotic disorder other than schizophrenia. The consideration of their results suggested that there is no significant difference between these medications concerning their effects on brain structure and also in comparison to healthy subjects. There does not seem to be any strong support to the opinion that medications that treat psychosis cause loss of brain volume in patients with schizophrenia. On the contrary, the data might imply the possible presence of a protective effect for D2, 5-HT2, and NE alpha-2 antagonists (previously called SGAs). However, the literature is limited and focused research in large study samples is essential to clarify the issue, since important numerical differences do exist. The possibility of the results and their heterogeneity to be artifacts secondary to a modification of magnetic resonance imaging (MRI) signal by antipsychotics should not be easily rejected until relevant data are available.

Association Between Hippocampal Subfields and Clinical Symptoms of First-Episode and Drug Naive Schizophrenia Patients During 12 Weeks of Risperidone Treatment

Small hippocampal size may be implicated in the pathogenesis and psychopathology of schizophrenia (SCZ). However, does the volume of hippocampal subfields in SCZ patients affect response to antipsychotic treatment? In this study, we used risperidone to treat first-episode drug naïve (FEDN) SCZ patients for 12 weeks, and then explored the relationship between baseline hippocampal subfield volumes, as well as any changes in these hippocampal subfield volumes during treatment, and improvement in their psychopathological symptoms. By adopting a state-of the-art automated algorithm, the hippocampal subfields were segmented in 43 FEDN SCZ inpatients at baseline and after 12 weeks of risperidone monotherapy, as well as in 30 matched healthy controls. We adopted the Positive and Negative Syndrome Scale (PANSS) to assess psychopathological symptoms in patients at baseline and at post-treatment. Before treatment, SCZ patients had no significant differences in total or subfield hippocampal volumes compared with healthy volunteers. However, we found a significant correlation between a smaller left CA1 at baseline and a lower PANSS total score and general psychopathology sub-score at post-treatment (both p < 0.05). Furthermore, the left CA1 at baseline was significantly smaller in responders, who had >50% improvement in PANSS total score, than in non-responders (p < 0.05). Our results suggest that smaller left CA1 volume may be a predicator for improvement in psychotic symptoms of FEDN SCZ patients.

Alterations in hippocampal subfield and amygdala subregion volumes in posttraumatic subjects with and without posttraumatic stress disorder

The hippocampus and amygdala are important structures in the posttraumatic stress disorder (PTSD); however, the exact relationship between these structures and stress or PTSD remains unclear. Moreover, they consist of several functionally distinct subfields/subregions that may serve different roles in the neuropathophysiology of PTSD. Here we present a subregional profile of the hippocampus and amygdala in 145 survivors of a major earthquake and 56 non‐traumatized healthy controls (HCs). We found that the bilateral hippocampus and left amygdala were significantly smaller in survivors than in HCs, and there was no difference between survivors with (n = 69) and without PTSD (trauma‐exposed controls [TCs], n = 76). Analyses revealed similar results in most subfields/subregions, except that the right hippocampal body (in a head‐body‐tail segmentation scheme), right presubiculum, and left amygdala medial nuclei (Me) were significantly larger in PTSD patients than in TCs but smaller than in HCs. Larger hippocampal body were associated with the time since trauma in PTSD patients. The volume of the right cortical nucleus (Co) was negatively correlated with the severity of symptoms in the PTSD group but positively correlated with the same measurement in the TC group. This correlation between symptom severity and Co volume was significantly different between the PTSD and TCs. Together, we demonstrated that generalized smaller volumes in the hippocampus and amygdala were more likely to be trauma‐related than PTSD‐specific, and their subfields/subregions were distinctively affected. Notably, larger left Me, right hippocampal body and presubiculum were PTSD‐specific; these could be preexisting factors for PTSD or reflect rapid posttraumatic reshaping.

The Effects of Antipsychotic Treatment on the Brain of Patients With First-Episode Schizophrenia: A Selective Review of Longitudinal MRI Studies

A large number of neuroimaging studies have detected brain abnormalities in first-episode schizophrenia both before and after treatment, but it remains unclear how these abnormalities reflect the effects of antipsychotic treatment on the brain. To summarize the findings in this regard and provide potential directions for future work, we reviewed longitudinal structural and functional imaging studies in patients with first-episode schizophrenia before and after antipsychotic treatment. A total of 36 neuroimaging studies was included, involving 21 structural imaging studies and 15 functional imaging studies. Both anatomical and functional brain changes in patients after treatment were consistently observed in the frontal and temporal lobes, basal ganglia, limbic system and several key components within the default mode network (DMN). Alterations in these regions were affected by factors such as antipsychotic type, course of treatment, and duration of untreated psychosis (DUP). Over all we showed that: (a) The striatum and DMN were core target regions of treatment in schizophrenia, and their changes were related to different antipsychotics; (b) The gray matter of frontal and temporal lobes tended to reduce after long-term treatment; and (c) Longer DUP was accompanied with faster hippocampal atrophy after initial treatment, which was also associated with poorer outcome. These findings are in accordance with previous notions but should be interpreted with caution. Future studies are needed to clarify the effects of different antipsychotics in multiple conditions and to identify imaging or other biomarkers that may predict antipsychotic treatment response. With such progress, it may help choose effective pharmacological interventional strategies for individuals experiencing recent-onset schizophrenia.

Reduced Hippocampal Subfield Volume in Schizophrenia and Clinical High-Risk State for Psychosis

Magnetic resonance imaging (MRI) studies in schizophrenia demonstrated volume reduction in hippocampal subfields divided on the basis of specific cytoarchitecture and function. However, it remains unclear whether this abnormality exists prior to the onset of psychosis and differs across illness stages. MRI (3 T) scans were obtained from 77 patients with schizophrenia, including 24 recent-onset and 40 chronic patients, 51 individuals with an at-risk mental state (ARMS) (of whom 5 subsequently developed psychosis within the follow-up period), and 87 healthy controls. Using FreeSurfer software, hippocampal subfield volumes were measured and compared across the groups. Both schizophrenia and ARMS groups exhibited significantly smaller volumes for the bilateral Cornu Ammonis 1 area, left hippocampal tail, and right molecular layer of the hippocampus than the healthy control group. Within the schizophrenia group, chronic patients exhibited a significantly smaller volume for the left hippocampal tail than recent-onset patients. The left hippocampal tail volume was positively correlated with onset age, and negatively correlated with duration of psychosis and duration of medication in the schizophrenia group. Reduced hippocampal subfield volumes observed in both schizophrenia and ARMS groups may represent a common biotype associated with psychosis vulnerability. Volumetric changes of the left hippocampal tail may also suggest ongoing atrophy after the onset of schizophrenia.

Differentiating patients with schizophrenia from healthy controls by hippocampal subfields using radiomics

BACKGROUND

Accurately diagnosing schizophrenia is still challenging due to the lack of validated biomarkers. Here, we aimed to investigate whether radiomic features in bilateral hippocampal subfields from magnetic resonance images (MRIs) can differentiate patients with schizophrenia from healthy controls (HCs).

METHODS

A total of 152 participants with MRI (86 schizophrenia and 66 HCs) were allocated to training (n = 106) and test (n = 46) sets. Radiomic features (n = 642) from the bilateral hippocampal subfields processed with automatic segmentation techniques were extracted from T1-weighted MRIs. After feature selection, various combinations of classifiers (logistic regression, extra-trees, AdaBoost, XGBoost, or support vector machine) and subsampling were trained. The performance of the classifier was validated in the test set by determining the area under the curve (AUC). Furthermore, the association between selected radiomic features and clinical symptoms in schizophrenia was assessed.

RESULTS

Thirty radiomic features were identified to differentiate participants with schizophrenia from HCs. In the training set, the AUC exhibited poor to good performance (range: 0.683-0.861). The best performing radiomics model in the test set was achieved by the mutual information feature selection and logistic regression with an AUC, accuracy, sensitivity, and specificity of 0.821 (95% confidence interval 0.681-0.961), 82.1%, 76.9%, and 70%, respectively. Greater maximum values in the left cornu ammonis 1-3 subfield were associated with a higher severity of positive symptoms and general psychopathology in participants with schizophrenia.

CONCLUSION

Radiomic features from hippocampal subfields may be useful biomarkers for identifying schizophrenia.