Baseline white matter function predicts short-term treatment response in first-episode schizophrenia.

BACKGROUND AND PURPOSE: The detection and characterization of functional activities in the gray matter of schizophrenia (SZ) have been widely explored. However, the relationship between resting-state functional signals in the white matter of first-episode SZ and short-term treatment response remains unclear. METHODS: Thirty-six patients with first-episode SZ and 44 matched healthy controls were recruited in this study. Patients were classified as nonresponders and responders based on response to antipsychotic medication during a single hospitalization. The fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and functional connectivity (FC) of white matter were calculated. The relationships between functional changes and clinical features were analyzed. In addition, voxel-based morphometry was performed to analyze the white matter volume. RESULTS: One-way analysis of variance showed significant differences of fALFF and ReHo in the left posterior thalamic radiation and left cingulum (hippocampus) in the patient group, and the areas were regarded as seeds. The FC was calculated between seeds and other white matter networks. Compared with responders, nonresponders showed significantly increased FC between the left cingulum (hippocampus) and left posterior thalamic radiation, splenium of corpus callosum, and left tapetum, and were associated with the changes of clinical assessment. However, there was no difference in white matter volume between groups. CONCLUSION: Our work provides a novel insight that psycho-neuroimaging-based white matter function holds promise for influencing the clinical diagnosis and treatment of SZ.

Differentiation of Neoplastic and Non-neoplastic Intracranial Enhancement Lesions Using Three-Dimensional Pseudo-Continuous Arterial Spin Labeling.

Background and Purpose: It is sometimes difficult to effectively distinguish non-neoplastic from neoplastic intracranial enhancement lesions using conventional magnetic resonance imaging (MRI). This study aimed to evaluate the diagnostic performance of three-dimensional pseudo-continuous arterial spin labeling (3D-pCASL) to differentiate non-neoplastic from neoplastic enhancement lesions intracranially. Materials and Methods: This prospective study included thirty-five patients with high-grade gliomas (HGG), twelve patients with brain metastasis, and fifteen non-neoplastic patients who underwent conventional, contrast enhancement and 3D-pCASL imaging at 3.0-T MR; all lesions were significantly enhanced. Quantitative parameters including cerebral blood flow (CBF) and relative cerebral blood flow (rCBF) were compared between neoplastic and non-neoplastic using Student's t-test. In addition, the area under the receiver operating characteristic (ROC) curve (AUC) was measured to assess the differentiation diagnostic performance of each parameter. Results: The non-neoplastic group demonstrated significantly lower rCBF values of lesions and perilesional edema compared with the neoplastic group. For the ROC analysis, both relative cerebral blood flow of lesion (rCBF-L) and relative cerebral blood flow of perilesional edema (rCBF-PE) had good diagnostic performance for discriminating non-neoplastic from neoplastic lesions, with an AUC of 0.994 and 0.846, respectively. Conclusion: 3D-pCASL may contribute to differentiation of non-neoplastic from neoplastic lesions.

Grading of Glioma: combined diagnostic value of amide proton transfer weighted, arterial spin labeling and diffusion weighted magnetic resonance imaging.

BACKGROUND: 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). METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Learning curve of double-guidewire technique by trainees during hands-on endoscopic retrograde cholangiopancreatography training.

BACKGROUND AND AIMS: Double-guidewire technique (DWT) has been successfully performed by experts in difficult biliary cannulation as an advanced technique. This study aimed to define the learning curve and safety of DWT by trainees during hands-on endoscopic retrograde cholangiopancreatography (ERCP) training. METHODS: Patients were eligible for inclusion in the study if the biliary cannulation was difficult and the pancreatic duct was inadvertently cannulated. DWT was performed by two trainees randomly under trainers' guidance. The primary outcome was the success rate of DWT biliary cannulation of trainees. Cumulative sum analysis was used to generate visual learning curves. RESULTS: A total of 60 patients with difficult cannulation were enrolled. The main indications for ERCP were common bile duct stones (65%) and biliary stricture (31.7%). The learning curve analysis showed that to achieve a 70% rate of successful DWT, 12 procedures were needed for trainee A and 15 for trainee B. Higher targeted success rate of DWT could be achieved if the number of DWT procedures increased. Compared with the early stage of learning DWT (case 1 to 15 for each trainee), trainees had significantly higher DWT success rate in the late stage (36.7% [11/30] vs 80% [24/30], P = 0.001). The final success rate of cannulation was 98.3% (59/60). The overall rate of post-ERCP pancreatitis and adverse events was 6.7% (4/60) and 8.3% (5/60), respectively. CONCLUSIONS: Double-guidewire technique was safely performed by two novel trainees during hands-on ERCP training. Fifteen procedures may be enough for trainees to achieve the competency of performing DWT. (Clinicaltrials.gov number: NCT03707613).

MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma.

OBJECTIVES: To establish and validate a radiomics nomogram for prediction of induction chemotherapy (IC) response and survival in nasopharyngeal carcinoma (NPC) patients. METHODS: One hundred twenty-three NPC patients (100 in training and 23 in validation cohort) with multi-MR images were enrolled. A radiomics nomogram was established by integrating the clinical data and radiomics signature generated by support vector machine. RESULTS: The radiomics signature consisting of 19 selected features from the joint T1-weighted (T1-WI), T2-weighted (T2-WI), and contrast-enhanced T1-weighted MRI images (T1-C) showed good prognostic performance in terms of evaluating IC response in two cohorts. The radiomics nomogram established by integrating the radiomics signature with clinical data outperformed clinical nomogram alone (C-index in validation cohort, 0.863 vs 0.549; p < 0.01). Decision curve analysis demonstrated the clinical utility of the radiomics nomogram. Survival analysis showed that IC responders had significant better PFS (progression-free survival) than non-responders (3-year PFS 84.81% vs 39.75%, p < 0.001). Low-risk groups defined by radiomics signature had significant better PFS than high-risk groups (3-year PFS 76.24% vs 48.04%, p < 0.05). CONCLUSIONS: Multiparametric MRI-based radiomics could be helpful for personalized risk stratification and treatment in NPC patients receiving IC. KEY POINTS: • MRI Radiomics can predict IC response and survival in non-endemic NPC. • Radiomics signature in combination with clinical data showed excellent predictive performance. • Radiomics signature could separate patients into two groups with different prognosis.

Clear cell renal cell carcinoma: Machine learning-based computed tomography radiomics analysis for the prediction of WHO/ISUP grade.

PURPOSE: To evaluate the performance of machine learning (ML)-based computed tomography (CT) radiomics analysis for discriminating between low grade (WHO/ISUP I-II) and high grade (WHO/ISUP III-IV) clear cell renal cell carcinomas (ccRCCs). METHODS: A total of 164 low grade and 107 high grade ccRCCs were retrospectively analyzed in this study. Radiomic features were extracted from corticomedullary phase (CMP) and nephrographic phase (NP) CT images. Intraclass correlation coefficient (ICC) was calculated to quantify the feature's reproducibility. The training and validation cohort consisted of 163 and 108 cases. Least absolute shrinkage and selection operator (LASSO) regression method was used for feature selection. The machine learning (ML) classifiers were k-NearestNeighbor (KNN), Logistic Regression (LR), multilayer perceptron (MLP), Random Forest (RF), and support vector machine (SVM). The performance of classifiers was mainly evaluated and compared by certain metrics. RESULTS: Seven CMP features (ICC range, 0.990-0.999) and seven NP features (ICC range, 0.931-0.999) were selected. The accuracy of CMP, NP and the combination of CMP and NP ranged from 82.2%-85.9 %, 82.8%-94.5 % and 86.5%-90.8 % in the training cohort, and 90.7%-95.4%, 77.8%-79.6 % and 91.7%-93.5 % in the validation cohort. The AUC of CMP, NP and the combination of CMP and NP ranged from 0.901 to 0.938, 0.912 to 0.976, 0.948 to 0.968 in the training cohort, and 0.957 to 0.974, 0.856 to 0.875, 0.960 to 0.978 in the validation cohort. CONCLUSIONS: ML-based CT radiomics analysis can be used to predict the WHO/ISUP grade of ccRCCs preoperatively.

Primary central nervous system small lymphocytic lymphoma in the bilateral ventricles: two case reports.

BACKGROUND: Primary central nervous system (CNS) small lymphocytic lymphoma (SLL), as a type of low-grade lymphoma, is extremely rare. The diagnosis of CNS SLL is challenging due to its variable clinical and radiological features, which may overlap with those of diffuse large B-cell lymphoma (DLBCL). Primary CNS SLL differs from DLBCL in that it has an indolent clinical course and a good prognosis. Thus, it is important to distinguish SLL from DLBCL. By reviewing the literature, only two cases of low-grade SLL, primarily located in the CNS and involving the brain parenchyma and dura, have been reported. To our knowledge, primary CNS SLL in the bilateral ventricles has never been reported. Interestingly, the two cases in our report are identical in terms of the clinical presentations, magnetic resonance imaging (MRI) features, pathological results and prognoses. CASE PRESENTATION: Both patients presented with headaches. MRI suggested solid lesions located in the bilateral ventricles that were isointense on T1-weighted images and hypointense on T2-weighted images. After the injection of contrast agent (gadolinium, Gd), the intraventricular lesions were homogeneously enhanced and hyperperfused. CSF cytology revealed malignant cells. Brain biopsy revealed diffuse proliferation of small lymphocytes with positive labelling of B-cell immunomarkers. The primary origin in the CNS was confirmed with no evidence of systemic lymphoma. Two patients were given high doses of methotrexate-based chemotherapy and were free from symptoms and progression for more than 1-year of follow-up. CONCLUSIONS: The presence of homogeneously enhanced intraventricular MRI lesions should raise the suspicion of primary CNS SLL.

Isocitrate dehydrogenase1 mutation reduces the pericyte coverage of microvessels in astrocytic tumours.

INTRODUCTION: Tumour-associated angiogenesis is associated with the malignancy and poor prognosis of glioma. Isocitrate dehydrogenase (IDH) mutations are present in the majority of lower-grade (WHO grade II and III) and secondary glioblastomas, but their roles in tumour angiogenesis remain unclear. METHODS: Using magnetic resonance imaging (MRI), the cerebral blood flow (CBF) of IDH-mutated glioma was measured and compared with the IDH-wildtype glioma. The densities of microvessels in IDH-mutated and wildtype astrocytoma and glioblastoma were assessed by immunohistochemical (IHC) staining with CD34, and the pericytes were labelled with α-smooth muscle antigen (α-SMA), neural-glial antigen 2 (NG2) and PDGF receptor-ß (PDGFR-ß), respectively. Furthermore, glia-specific mutant IDH1 knock-in mice were generated to evaluate the roles of mutant IDH1 on brain vascular architectures. The transcriptions of the angiogenesis-related genes were assessed in TCGA datasets, including ANGPT1, PDGFB and VEGFA. The expressions of these genes were further determined by western blot in U87-MG cells expressing a mutant IDH1 or treated with 2-HG. RESULTS: The MRI results indicated that CBF was reduced in the IDH-mutated gliomas. The IHC staining showed that the pericyte coverages of microvessels were significantly decreased, but the microvessel densities (MVDs) were only slightly decreased in IDH-mutated glioma. The mutant IDH1 knock-in also impeded the pericyte coverage of brain microvessels in mice. Moreover, the TCGA database showed the mRNA levels of angiogenesis factors, including ANGPT1, PDGFB and VEGFA, were downregulated, and their promoters were also highly hyper-methylated in IDH-mutated gliomas. In addition, both mutant IDH1 and D-2-HG could downregulate the expression of these genes in U87-MG cells. CONCLUSIONS: Our results suggested that IDH mutations could reduce the pericyte coverage of microvessels in astrocytic tumours by inhibiting the expression of angiogenesis factors. As vascular pericytes play an essential role in maintaining functional blood vessels to support tumour growth, our findings imply a potential avenue of therapeutic strategy for IDH-mutated gliomas.

Differentiation of primary central nervous system lymphoma from high-grade glioma and brain metastasis using arterial spin labeling and dynamic contrast-enhanced magnetic resonance imaging.

BACKGROUND AND PURPOSE: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Noninvasively evaluating the grading and IDH1 mutation status of diffuse gliomas by three-dimensional pseudo-continuous arterial spin labeling and diffusion-weighted imaging.

PURPOSE: To noninvasively evaluate the value of three-dimensional pseudo-continuous arterial spin labeling (3D pCASL) and diffusion-weighted imaging (DWI) in diffuse gliomas grading as well as isocitrate dehydrogenase (IDH) 1 mutation status. METHODS: Fifty-six patients with pathologically confirmed diffuse gliomas with preoperative 3D pCASL and DWI were enrolled in this study. The Student's t test and Mann-Whitney U test were used to evaluate differences in parameters of DWI and 3D pCASL between low and high grade as well as between mutant and wild-type IDH1 diffuse gliomas; receiver operator characteristic (ROC) analysis was used to assess the diagnostic performance. Subsequently, a multivariate stepwise logistic regression analysis was used to identify the independent parameters. Besides, Kruskal-Wallis H test was used to examine the differences among grades II, III, and IV diffuse gliomas. RESULTS: All parameters but CBFmean showed significant differences between low- and high-grade diffuse gliomas. In ROC analysis, the AUC of CBFmax, rCBFmean, rCBFmax, ADCmean, and ADCmin were 0.701, 0.730, 0.746, 0.810, and 0.856 respectively. Only the value of ADCmin was identified as the independent parameter in the differentiation of low- from high-grade diffuse gliomas. All parameters but CBFmean showed significant differences among the three grades. And the values of CBFmean, CBFmax, rCBFmean, and ADCmean showed significant differences between mutant and wild-type IDH1 in grade II-III astrocytoma. CONCLUSION: Both 3D pCASL and DWI could be useful tools for distinguishing low- from high-grade diffuse gliomas and have the potential to differentiate different IDH1 mutation statuses of astrocytoma.

Radiomics signature: A potential biomarker for the prediction of MGMT promoter methylation in glioblastoma.

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 (T1 WI), T2 -weighted image (T2 WI), and enhanced T1 WI. 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 T1 WI reached an accuracy of 67.54%. Enhanced T1 WI features reached an accuracy of 82.01%, while T2 WI reached an accuracy of 69.25%. The best classification system for predicting MGMT promoter methylation status originated from the combination of 36 T1 WI, T2 WI, and enhanced T1 WI 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.