Background
In glioblastoma (GBM), promoter methylation of the DNA repair gene O‐methylguanine‐DNA methyltransferase (MGMT) is associated with beneficial chemotherapy.
Purpose/Hypothesis
To analyze ...radiomics features for utilizing the full potential of medical imaging as biomarkers of MGMT promoter methylation.
Study Type
Retrospective.
Population/Subjects
In all, 98 GBM patients with known MGMT (48 methylated and 50 unmethylated tumors).
Field Strength/Sequence
3.0T magnetic resonance (MR) images, containing T1‐weighted image (T1WI), T2‐weighted image (T2WI), and enhanced T1WI.
Assessment
A region of interest (ROI) of the tumor was delineated. A total of 1665 radiomics features were extracted and quantized, and were reduced using least absolute shrinkage and selection operator (LASSO) regularization.
Statistical Testing
After the support vector machine construction, accuracy, sensitivity, and specificity were computed for different sequences. An independent validation cohort containing 20 GBM patients was utilized to further evaluate the radiomics model performance.
Results
Radiomics features of T1WI reached an accuracy of 67.54%. Enhanced T1WI features reached an accuracy of 82.01%, while T2WI reached an accuracy of 69.25%. The best classification system for predicting MGMT promoter methylation status originated from the combination of 36 T1WI, T2WI, and enhanced T1WI images features, with an accuracy of 86.59%. Further validation on the independent cohort of 20 patients produced similar results, with an accuracy of 80%.
Data Conclusion
Our results provide further evidence that radiomics MR features could predict MGMT methylation status in preoperative GBM. Multiple imaging modalities together can yield putative noninvasive biomarkers for the identification of MGMT.
Level of Evidence: 4
Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1380–1387.
Multimodal neuroimaging features provide opportunities for accurate classification and personalized treatment options in the psychiatric domain. This study aimed to investigate whether brain features ...predict responses to the overall treatment of schizophrenia at the end of the first or a single hospitalization. Structural and functional magnetic resonance imaging (MRI) data from two independent samples (N = 85 and 63, separately) of schizophrenia patients at baseline were included. After treatment, patients were classified as responders and non‐responders. Radiomics features of gray matter morphology and functional connectivity were extracted using Least Absolute Shrinkage and Selection Operator. Support vector machine was used to explore the predictive performance. Prediction models were based on structural features (cortical thickness, surface area, gray matter regional volume, mean curvature, metric distortion, and sulcal depth), functional features (functional connectivity), and combined features. There were 12 features after dimensionality reduction. The structural features involved the right precuneus, cuneus, and inferior parietal lobule. The functional features predominately included inter‐hemispheric connectivity. We observed a prediction accuracy of 80.38% (sensitivity: 87.28%; specificity 82.47%) for the model using functional features, and 69.68% (sensitivity: 83.96%; specificity: 72.41%) for the one using structural features. Our model combining both structural and functional features achieved a higher accuracy of 85.03%, with 92.04% responder and 80.23% non‐responders to the overall treatment to be correctly predicted. These results highlight the power of structural and functional MRI‐derived radiomics features to predict early response to treatment in schizophrenia. Prediction models of the very early treatment response in schizophrenia could augment effective therapeutic strategies.
By radiomics strategy, we established prediction models based on structural features and functional features extracted from multi‐modal magnetic resonance imaging (MRI) data of 148 schizophrenia patients collected from two independent samples. The model combining both structural and functional features achieved a prediction accuracy of 85.03% to the overall treatment response. Our results highlight the capability of structural and functional MRI‐derived radiomics features to predict early responses to the treatment in schizophrenia.
Neuroimaging- and machine-learning-based brain-age prediction of schizophrenia is well established. However, the diagnostic significance and the effect of early medication on first-episode ...schizophrenia remains unclear.
To explore whether predicted brain age can be used as a biomarker for schizophrenia diagnosis, and the relationship between clinical characteristics and brain-predicted age difference (PAD), and the effects of early medication on predicted brain age.
The predicted model was built on 523 diffusion tensor imaging magnetic resonance imaging scans from healthy controls. First, the brain-PAD of 60 patients with first-episode schizophrenia, 60 healthy controls and 21 follow-up patients from the principal data-set and 40 pairs of individuals in the replication data-set were calculated. Next, the brain-PAD between groups were compared and the correlations between brain-PAD and clinical measurements were analysed.
The patients showed a significant increase in brain-PAD compared with healthy controls. After early medication, the brain-PAD of patients decreased significantly compared with baseline (P < 0.001). The fractional anisotropy value of 31/33 white matter tract features, which related to the brain-PAD scores, had significantly statistical differences before and after measurements (P < 0.05, false discovery rate corrected). Correlation analysis showed that the age gap was negatively associated with the positive score on the Positive and Negative Syndrome Scale in the principal data-set (r = -0.326, P = 0.014).
The brain age of patients with first-episode schizophrenia may be older than their chronological age. Early medication holds promise for improving the patient's brain ageing. Neuroimaging-based brain-age prediction can provide novel insights into the understanding of schizophrenia.
Attempts to determine why some patients respond to electroconvulsive therapy (ECT) are valuable in schizophrenia. Schizophrenia is associated with aberrant dynamic functional architecture, which ...might impact the efficacy of ECT. We aimed to explore the relationship between pre‐treatment temporal variability and ECT acute efficacy. Forty‐eight patients with schizophrenia and 30 healthy controls underwent functional magnetic resonance imaging to examine whether patterns of temporary variability of functional architecture differ between high responders (HR) and low responders (LR) at baseline. Compared with LR, HR exhibited significantly abnormal temporal variability in right inferior front gyrus (IFGtriang.R), left temporal pole (TPOsup.L) and right middle temporal gyrus (MTG.R). In the pooled patient group, ∆PANSS was correlated with the temporal variability of these regions. Patients with schizophrenia with a distinct dynamic functional architecture appear to reveal differential response to ECT. Our findings provide not only an understanding of the neural functional architecture patterns that are found in schizophrenia but also the possibility of using these measures as moderators for ECT selection.
Compared with low responders, high responders exhibited significantly abnormal temporal variability in right inferior front gyrus, left temporal pole and right middle temporal gyrus. Patients with schizophrenia with a distinct dynamic functional architecture appear to reveal differential response to electroconvulsive therapy.
•PCNSL demonstrated lower rCBF, higher Ktrans and Ve compared with HGG and metastasis.•Both Ktrans and rCBF had good diagnostic performance for discriminating PCNSL.•The combination of rCBF and ...Ktrans has the best diagnostic ability for PCNSL.
Conventional magnetic resonance imaging (MRI) is sometimes difficult to distinguish primary central nervous system lymphoma (PCNSL) from other malignant brain tumors effectively. The study aimed to evaluate the diagnostic performance of arterial spin labeling (ASL) and dynamic contrast-enhanced (DCE)-derived permeability parameters to differentiate PCNSL from high-grade glioma (HGG) and brain metastasis.
Eight patients with PCNSL, twenty one patients with HGG and six brain metastasis underwent preoperative 3.0-T MR imaging including conventional, ASL and DCE. Quantitative parameters including relative cerebral blood flow (rCBF), extravascular extracellular volume fraction (Ve) and the volume transfer constant (Ktrans) among PCNSL, HGG and metastasis were compared with a one-way analysis of variance. In addition, the area under the receiver-operating characteristic (ROC) curve (AUC) was constructed to evaluate the differentiation diagnostic performance of each parameter and the combination.
The PCNSL demonstrated significantly lower rCBF, higher Ktrans and Ve compared with HGG and metastasis. For the ROC analyses, both Ktrans and rCBF had good diagnostic performance for discriminating PCNSL from HGG and metastasis, with the AUC of 0.880 and 0.889. With the combination of rCBF and Ktrans, the diagnostic ability for PCNSL was improved with AUC of 0.986.
rCBF and Ktrans are useful parameters for differentiating PCNSL from HGG and brain metastasis. The combination of rCBF and Ktrans further helps to improve the diagnostic performance of PCNSL.
A novel hierarchically ZIF-67 derived Co3O4/carbon aerogel (CA) composite has been successfully synthesized by an in situ deposition and calcination method. The unique 3D nanoarchitecture provides an ...effective pathway for the rapid transport of electrons and ions. As a result, the ZIF-67 derived Co3O4/CA composite electrode exhibits a high specific capacitance of 298.8 F g−1 at 0.5 A g−1, excellent rate capability and outstanding cycling stability (82% retention after 1000 cycles). These results suggest that such a composite electrode possesses great potential for electrochemical supercapacitor applications.
We aimed to evaluate the functional network properties in first-episode schizophrenia (SZ) patients at baseline and after 4-months treatment with second-generation antipsychotic drugs.
Resting-state ...functional magnetic resonance imaging and graph theory approaches were utilized to evaluate the functional integration and segregation of brain networks in 36 first-episode patients (20 male/16 female) with SZ and 36 age and sex matched healthy controls (20 male/16 female).
Compared with healthy controls, SZ at baseline showed lower clustering coefficient (Cp) and local network efficiency (Eloc), and this abnormal pattern was modulated with treatment of antipsychotic drugs at follow-up. Longitudinally, the increase of Cp was associated with the improvement of negative symptom. We found that the strength of functional connectivity between brain regions were significantly increased in three connections after treatment, mainly involving the frontal, parietal and occipital lobes.
The current study suggested that antipsychotic drugs could modulate the faulty local clustering of the functional connectome in SZ. Furthermore, Cp, the parameter that reflects local clustering of topological organization, demonstrated the potential to be a connectome-based biomarker of treatment response to second-generation antipsychotics in patients with SZ.
Summary
Background
Disturbances in emotion regulation are the hallmarks of major depressive disorder (MDD). The incapacity to control negative emotion in patients has been associated with abnormal ...hyperactivation of the limbic system and hypoactivation of the frontal cortex. The amygdala and orbital frontal cortex (OFC) are two critical regions of the emotion regulation neural systems.
Methods
This study investigated the anatomical basis of abnormal emotion regulation by tracking the fiber tracts connecting the amygdala and OFC. In addition, using dynamic casual modeling on resting‐state fMRI data of 20 MDD patients and equivalent controls, we investigated the exact neural mechanism through which abnormal communications between these two nodes were mediated in MDD.
Key Results
The results revealed disrupted white matter integrity of fiber tracts in MDD, suggesting that functional abnormalities were accompanied by underlying anatomical basis. We also detected a failure of inhibition of the OFC on the activity of the amygdala in MDD, suggesting dysconnectivity was mediated through “top‐down” influences from the frontal cortex to the amygdala. Following 8 weeks of antidepressant treatment, the patients showed significant clinical improvement and normalization of the abnormal OFC‐amygdala structural and effective connectivity in the left hemisphere.
Conclusions & Inferences
Our findings suggest that pathways connecting these two nodes may be core targets of the antidepressant treatment. In particular, it raised the intriguing question: Does the reversal of structural markers of connectivity reflect a response to antidepressant medication or activity‐dependent myelination following a therapeutic restoration of effective connectivity?
Purpose
Premature ejaculation (PE) is one of the most common sexual dysfunctions in men. However, there has been little research evaluating alterations in brain structure related to PE. We aimed to ...investigate the characteristics of nonmedicated PE patients in terms of brain morphometry.
Materials and Methods
The sample consisted with 32 medication‐naïve adult men with clinical diagnosed PE and matched 31 healthy controls. All participants received diagnostic interviews and 3.0 Tesla MRI scans. Automatic segmentation processing of MRI structure images was performed using FreeSurfer software and cerebral cortical thickness between groups was compared.
Results
The PE group had thicker cortex in widespread regions, including the frontal, parietal and occipital lobe, and limbic system, compared with the healthy control group (P < 0.05). Moreover, the duration is negatively correlated with the mean cortical thickness of the right medial orbitofrontal cortex, right precentral gyrus and left superior frontal cortex (R2 = 0.29, P < 0.003; R2 = 0.163, P < 0.04; R2 = 0.2, P < 0.02), while the Premature Ejaculation Diagnostic Tool score is negatively correlated with the mean cortical thickness of the left caudal middle frontal cortex (R2 = 0.33, P < 0.005).
Conclusion
The result highlights the structural features of PE and suggests the relationship with the severity of impairment is related to the severity of anatomic abnormality with the relevant brain region. These results support the value of imaging measures as markers for understanding the physiopathology of PE.
Level of Evidence: 1
Technical Efficacy: Stage 3
J. Magn. Reson. Imaging 2018;47:656–662.
To investigate the ability of amide proton transfer (APT) weighted magnetic resonance imaging (MRI), arterial spin labeling (ASL), diffusion weighted imaging (DWI) and the combination for ...differentiating high-grade gliomas (HGGs) from low-grade gliomas (LGGs).
Twenty-seven patients including nine LGGs and eighteen HGGs underwent conventional, APT, ASL and DWI MRI with a 3.0-T MR scanner. Histogram analyses was performed and quantitative parameters including mean apparent diffusion coefficient (ADC mean), 20th-percentile ADC (ADC 20th), mean APT (APT mean), 90th-percentile APT (APT 90th), relative mean cerebral blood flow (rCBF mean) and relative 90th-percentile CBF (rCBF 90th) were compared between HGGs and LGGs. The diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis of each parameter and their combination. Correlations were analyzed among the MRI parameters and Ki-67.
The APT values were significantly higher in the HGGs compared to the LGGs (p < 0.005), whereas ADC values were significantly lower in HGGs than LGGs (P < 0.0001). The ADC 20th and APT mean had higher discrimination abilities compared with other single parameters, with the area under the ROC curve (AUC) of 0.877 and 0.840. Adding ADC parameter, the discrimination ability of APT and rCBF significantly improved. The ADC was negatively correlated with the APT and rCBF value, respectively, while APT value was positively correlated with rCBF value. Significant correlations between ADC values and Ki-67 were also observed.
APT and DWI are valuable in differentiating HGGs from LGGs. The combination of APT, DWI and ASL imaging could improve the ability for discriminating HGGs from LGGs.
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