Shun Zhang

Diffusion kurtosis imaging can efficiently assess the glioma grade and cellular proliferation

Conventional diffusion imaging techniques are not sufficiently accurate for evaluating glioma grade and cellular proliferation, which are critical for guiding glioma treatment. Diffusion kurtosis imaging (DKI), an advanced non-Gaussian diffusion imaging technique, has shown potential in grading glioma; however, its applications in this tumor have not been fully elucidated. In this study, DKI and diffusion weighted imaging (DWI) were performed on 74 consecutive patients with histopathologically confirmed glioma. The kurtosis and conventional diffusion metric values of the tumor were semi-automatically obtained. The relationships of these metrics with the glioma grade and Ki-67 expression were evaluated. The diagnostic efficiency of these metrics in grading was further compared. It was demonstrated that compared with the conventional diffusion metrics, the kurtosis metrics were more promising imaging markers in distinguishing high-grade from low-grade gliomas and distinguishing among grade II, III and IV gliomas; the kurtosis metrics also showed great potential in the prediction of Ki-67 expression. To our best knowledge, we are the first to reveal the ability of DKI to assess the cellular proliferation of gliomas, and to employ the semi-automatic method for the accurate measurement of gliomas. These results could have a significant impact on the diagnosis and subsequent therapy of glioma.

Intravoxel incoherent motion diffusion-weighted imaging analysis of diffusion and microperfusion in grading gliomas and comparison with arterial spin labeling for evaluation of tumor perfusion.

To determine the utility of intravoxel incoherent motion (IVIM) imaging in grading gliomas and compare IVIM perfusion metrics with arterial spin labeling (ASL)‐derived cerebral blood flow (CBF).

In vivo quantitative whole-brain diffusion tensor imaging analysis of APP/PS1 transgenic mice using voxel-based and atlas-based methods

IntroductionDiffusion tensor imaging (DTI) has been applied to characterize the pathological features of Alzheimers disease (AD) in a mouse model, although little is known about whether these features are structure specific. Voxel-based analysis (VBA) and atlas-based analysis (ABA) are good complementary tools for whole-brain DTI analysis. The purpose of this study was to identify the spatial localization of disease-related pathology in an AD mouse model.MethodsVBA and ABA quantification were used for the whole-brain DTI analysis of nine APP/PS1 mice and wild-type (WT) controls. Multiple scalar measurements, including fractional anisotropy (FA), trace, axial diffusivity (DA), and radial diffusivity (DR), were investigated to capture the various types of pathology. The accuracy of the image transformation applied for VBA and ABA was evaluated by comparing manual and atlas-based structure delineation using kappa statistics. Following the MR examination, the brains of the animals were analyzed for microscopy.ResultsExtensive anatomical alterations were identified in APP/PS1 mice, in both the gray matter areas (neocortex, hippocampus, caudate putamen, thalamus, hypothalamus, claustrum, amygdala, and piriform cortex) and the white matter areas (corpus callosum/external capsule, cingulum, septum, internal capsule, fimbria, and optic tract), evidenced by an increase in FA or DA, or both, compared to WT mice (pu2009<u20090.05, corrected). The average kappa value between manual and atlas-based structure delineation was approximately 0.8, and there was no significant difference between APP/PS1 and WT mice (pu2009>u20090.05). The histopathological changes in the gray matter areas were confirmed by microscopy studies. DTI did, however, demonstrate significant changes in white matter areas, where the difference was not apparent by qualitative observation of a single-slice histological specimen.ConclusionThis study demonstrated the structure-specific nature of pathological changes in APP/PS1 mouse, and also showed the feasibility of applying whole-brain analysis methods to the investigation of an AD mouse model.

Voxel-Based Diffusion Tensor Imaging of an APP/PS1 Mouse Model of Alzheimer's Disease

Increasing evidence has demonstrated that white matter (WM) disruptions, due to the injury of the axon and myelin, play an important role in the pathogenesis of Alzheimer’s disease (AD). Diffusion tensor imaging (DTI) is a sensitive modality to evaluate the WM integrity in both AD patients and animal models. In this study, an advanced DTI modality, employing a 7.0-T magnetic resonance imaging system, was used to analyze WM changes across the whole brain of an amyloid precursor protein/presenilin 1 (APP/PS1) mouse model. A voxel-based analysis was used to compare the quantitative DTI parameters automatically in both APP/PS1 mice (nu2009=u20099) and wild-type (WT) controls (nu2009=u20099). After DTI examination, the ultrastructure analysis was compared with DTI findings. Compared with WT controls, gray matter (GM) areas in APP/PS1 mice such as the cingulate cortex and the striatum showed significant fractional anisotropy (FA) and axial diffusivity (DA) increase, while the thalamus only showed a significant FA increase (pu2009<u20090.01). Similarly, a significant mean diffusivity, DA, and radial diffusivity increase was observed in the bilateral neocortex (pu2009<u20090.01). The left hippocampus only showed significant FA increase in APP/PS1 mice (pu2009<u20090.01). The changes in WM regions were detected in the forceps minor of the corpus callosum, the anterior part of the anterior commissure, and the internal capsule, with a significant FA or DA increase (pu2009<u20090.01). Abnormalities derived from diffusion measurements were in-line with the ultrastructure findings, including extensive pathological damage of the neurons, neutrophils, and vessels. In conclusion, voxel-based diffusion tensor imaging can detect diffusion alterations not only in GM but also in WM areas in AD models, reflecting the extensive pathological changes of AD.

Altered Intranetwork and Internetwork Functional Connectivity in Type 2 Diabetes Mellitus With and Without Cognitive Impairment

Type 2 diabetes mellitus (T2DM) is associated with cognitive impairment. We investigated whether alterations of intranetwork and internetwork functional connectivity with T2DM progression exist, by using resting-state functional MRI. MRI data were analysed from 19 T2DM patients with normal cognition (DMCN) and 19 T2DM patients with cognitive impairment (DMCI), 19 healthy controls (HC). Functional connectivity among 36 previously well-defined brain regions which consisted of 5 resting-state network (RSN) systems [default mode network (DMN), dorsal attention network (DAN), control network (CON), salience network (SAL) and sensorimotor network (SMN)] was investigated at 3 levels (integrity, network and connectivity). Impaired intranetwork and internetwork connectivity were found in T2DM, especially in DMCI, on the basis of the three levels of analysis. The bilateral posterior cerebellum, the right insula, the DMN and the CON were mainly involved in these changes. The functional connectivity strength of specific brain architectures in T2DM was found to be associated with haemoglobin A1c (HbA1c), cognitive score and illness duration. These network alterations in intergroup differences, which were associated with brain functional impairment due to T2DM, indicate that network organizations might be potential biomarkers for predicting the clinical progression, evaluating the cognitive impairment, and further understanding the pathophysiology of T2DM.

Brain white matter plasticity and functional reorganization underlying the central pathogenesis of trigeminal neuralgia

Peripheral nerve damage does not fully explain the pathogenesis of trigeminal neuralgia (TN). Central nervous system changes can follow trigeminal nerve dysfunction. We hypothesized that brain white matter and functional connectivity changes in TN patients were involved in pain perception, modulation, the cognitive-affective system, and motor function; moreover, changes in functional reorganization were correlated with white matter alterations. Twenty left TN patients and twenty-two healthy controls were studied. Diffusion kurtosis imaging was analyzed to extract diffusion and kurtosis parameters, and functional connectivity density (FCD) mapping was used to explore the functional reorganization in the brain. In the patient group, we found lower axial kurtosis and higher axial diffusivity in tracts participated in sensory, cognitive-affective, and modulatory aspects of pain, such as the corticospinal tract, superior longitudinal fasciculus, anterior thalamic radiation, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, cingulated gyrus, forceps major and uncinate fasciculus. Patients exhibited complex FCD reorganization of hippocampus, striatum, thalamus, precentral gyrus, precuneus, prefrontal cortex and inferior parietal lobule in multiple modulatory networks that played crucial roles in pain perception, modulation, cognitive-affective system, and motor function. Further, the correlated structural-functional changes may be responsible for the persistence of long-term recurrent pain and sensory-related dysfunction in TN.

The temporal evolution of diffusional kurtosis imaging in an experimental middle cerebral artery occlusion (MCAO) model.

PURPOSEnDiffusional kurtosis imaging (DKI), as a non-Gaussian diffusion model, has been applied in human and animal studies of ischemic stroke. This study aimed to intensively characterize the temporal evolution of DKI-derived variables in an experimental middle cerebral artery occlusion (MCAO) model, and to explore its potential application in ischemic stroke.nnnMATERIALS AND METHODSnEleven MCAO rats and ten control rats underwent DKI and diffusion weighted imaging (DWI) scans, at different time points of 0.5, 2, 6, 12, 24 and 72h after operation respectively. The infarct area in DKI- and DWI-derived variables was compared among different time points, and between different groups [INFARCTION, MIRROR, CONTROL-R (right side of the control group, the same side as in the infarction group), CONTROL-L (left side of the control group)] using repeated measures analysis of variance (ANOVA). The percent changes from normal to that in ischemic tissues and histology were also evaluated.nnnRESULTSnIn the infarct region, from 0.5 to 72h, MK, K∥, K⊥ demonstrated irregular high signal, whereas relative homogeneous low signals were revealed by MD, D∥, D⊥ and ADC. Compared with the MIRROR and CONTROL-R group, MK, K∥, K⊥ in the infarcted area increased aggressively which peaked at 12h and gradually decreased; MD, D∥, D⊥ and ADC decreased gradually until 12h and then began to increase gradually; FA decreased rapidly from 0.5 to 72h. MD, D∥ and ADC were significantly different between Mirror and CONTROL-L group (P<0.05).nnnCONCLUSIONnDKI can provide more detailed information to describe ischemic lesion, and has great potential application in ischemic stroke.

Monoclonal Antibody–Conjugated Superparamagnetic Iron Oxide Nanoparticles for Imaging of Epidermal Growth Factor Receptor–Targeted Cells and Gliomas

The objective of this study was to successfully synthesize epidermal growth factor receptor monoclonal antibody-conjugated superparamagnetic iron oxide nanoparticles (EGFRmAb-SPIONs) and explore their biocompatibility and potential applications as a targeted magnetic resonance imaging (MRI) contrast agent for the EGFR-specific detection of brain glioma in vivo. After conjugation of EGFRmAb with SPIONs, the magnetic characteristics of EGFRmAb-SPIONs were investigated. Thereafter, the targeting abilities of EGFRmAb-SPIONs with MRI were qualitatively and quantitatively assessed in EGFR-positive C6 glioma cells in vitro and in a Wistar rat model bearing C6 glioma in vivo. Furthermore, the preliminary biocompatibility and toxicity of EGFRmAb-SPIONs were evaluated in normal rats through hematology assays and histopathologic analyses. Statistical analysis was performed using one-way analysis of variance and Student t-test, with a significance level of p < .05. From the results of EGFRmAb-SPION characterizations, the average particle size was 10.21 nm and the hydrodynamic diameter was 161.5 ± 2.12 nm. The saturation magnetization was 55 emu/g·Fe, and T2 relaxivity was 92.73 s-1mM-1 in distilled water. The preferential accumulation of the EGFRmAb-SPIONs within glioma and subsequent MRI contrast enhancement were demonstrated both in vitro in C6 cells and in vivo in rats bearing C6 glioma. After intravenous administration of EGFRmAb-SPIONs, T2-weighted MRI of the rat model with brain glioma exhibited an apparent hypointense region within glioma from 2 to 48 hours. The maximal image contrast was reached at 24 hours, where the signal intensity decreased and the R2 value increased by 30% compared to baseline. However, T2-weighted imaging of the rat model administered with SPIONs showed no visible signal changes within the tumor over the same time period. Moreover, no evident toxicities in vitro and in vivo with EGFRmAb-SPIONs were clearly identified based on the laboratory examinations. EGFRmAb-SPIONs could potentially be employed as a targeted contrast agent in the molecule-specific diagnosis of brain glioma in MRI.The objective of this study was to successfully synthesize epidermal growth factor receptor monoclonal antibody–conjugated superparamagnetic iron oxide nanoparticles (EGFRmAb-SPIONs) and explore their biocompatibility and potential applications as a targeted magnetic resonance imaging (MRI) contrast agent for the EGFR-specific detection of brain glioma in vivo. After conjugation of EGFRmAb with SPIONs, the magnetic characteristics of EGFRmAb-SPIONs were investigated. Thereafter, the targeting abilities of EGFRmAb-SPIONs with MRI were qualitatively and quantitatively assessed in EGFR-positive C6 glioma cells in vitro and in a Wistar rat model bearing C6 glioma in vivo. Furthermore, the preliminary biocompatibility and toxicity of EGFRmAb-SPIONs were evaluated in normal rats through hematology assays and histopathologic analyses. Statistical analysis was performed using one-way analysis of variance and Student t-test, with a significance level of p < .05. From the results of EGFRmAb-SPION characterizations, the average particle size was 10.21 nm and the hydrodynamic diameter was 161.5 ± 2.12 nm. The saturation magnetization was 55 emu/g·Fe, and T2 relaxivity was 92.73 s−1mM−1 in distilled water. The preferential accumulation of the EGFRmAb-SPIONs within glioma and subsequent MRI contrast enhancement were demonstrated both in vitro in C6 cells and in vivo in rats bearing C6 glioma. After intravenous administration of EGFRmAb-SPIONs, T2-weighted MRI of the rat model with brain glioma exhibited an apparent hypointense region within glioma from 2 to 48 hours. The maximal image contrast was reached at 24 hours, where the signal intensity decreased and the R2 value increased by 30% compared to baseline. However, T2-weighted imaging of the rat model administered with SPIONs showed no visible signal changes within the tumor over the same time period. Moreover, no evident toxicities in vitro and in vivo with EGFRmAb-SPIONs were clearly identified based on the laboratory examinations. EGFRmAb-SPIONs could potentially be employed as a targeted contrast agent in the molecule-specific diagnosis of brain glioma in MRI.

Comparative study of DSC-PWI and 3D-ASL in ischemic stroke patients

The purpose of this study was to quantitatively analyze the relationship between three dimensional arterial spin labeling (3D-ASL) and dynamic susceptibility contrast-enhanced perfusion weighted imaging (DSC-PWI) in ischemic stroke patients. Thirty patients with ischemic stroke were included in this study. All subjects underwent routine magnetic resonance imaging scanning, diffusion weighted imaging (DWI), magnetic resonance angiography (MRA), 3D-ASL and DSC-PWI on a 3.0T MR scanner. Regions of interest (ROIs) were drawn on the cerebral blood flow (CBF) maps (derived from ASL) and multi-parametric DSC perfusion maps, and then, the absolute and relative values of ASL-CBF, DSC-derived CBF, and DSC-derived mean transit time (MTT) were calculated. The relationships between ASL and DSC parameters were analyzed using Pearson’s correlation analysis. Receiver operative characteristic (ROC) curves were performed to define the thresholds of relative value of ASL-CBF (rASL) that could best predict DSC-CBF reduction and MTT prolongation. Relative ASL better correlated with CBF and MTT in the anterior circulation with the Pearson correlation coefficients (R) values being 0.611 (P<0.001) and–0.610 (P<0.001) respectively. ROC curves demonstrated that when rASL ≤0.585, the sensitivity, specificity and accuracy for predicting ROIs with rCBF<0.9 were 92.3%, 63.6% and 76.6% respectively. When rASL ≤0.952, the sensitivity, specificity and accuracy for predicting ROIs rMTT>1.0 were 75.7%, 89.2% and 87.8% respectively. ASL-CBF map has better linear correlations with DSC-derived parameters (DSC-CBF and MTT) in anterior circulation in ischemic stroke patients. Additionally, when rASL is lower than 0.585, it could predict DSC-CBF decrease with moderate accuracy. If rASL values range from 0.585 to 0.952, we just speculate the prolonged MTT.The purpose of this study was to quantitatively analyze the relationship between three dimensional arterial spin labeling (3D-ASL) and dynamic susceptibility contrast-enhanced perfusion weighted imaging (DSC-PWI) in ischemic stroke patients. Thirty patients with ischemic stroke were included in this study. All subjects underwent routine magnetic resonance imaging scanning, diffusion weighted imaging (DWI), magnetic resonance angiography (MRA), 3D-ASL and DSC-PWI on a 3.0T MR scanner. Regions of interest (ROIs) were drawn on the cerebral blood flow (CBF) maps (derived from ASL) and multi-parametric DSC perfusion maps, and then, the absolute and relative values of ASL-CBF, DSC-derived CBF, and DSC-derived mean transit time (MTT) were calculated. The relationships between ASL and DSC parameters were analyzed using Pearson’s correlation analysis. Receiver operative characteristic (ROC) curves were performed to define the thresholds of relative value of ASL-CBF (rASL) that could best predict DSC-CBF reduction and MTT prolongation. Relative ASL better correlated with CBF and MTT in the anterior circulation with the Pearson correlation coefficients (R) values being 0.611 (P<0.001) and–0.610 (P<0.001) respectively. ROC curves demonstrated that when rASL ≤0.585, the sensitivity, specificity and accuracy for predicting ROIs with rCBF<0.9 were 92.3%, 63.6% and 76.6% respectively. When rASL ≤0.952, the sensitivity, specificity and accuracy for predicting ROIs rMTT>1.0 were 75.7%, 89.2% and 87.8% respectively. ASL-CBF map has better linear correlations with DSC-derived parameters (DSC-CBF and MTT) in anterior circulation in ischemic stroke patients. Additionally, when rASL is lower than 0.585, it could predict DSC-CBF decrease with moderate accuracy. If rASL values range from 0.585 to 0.952, we just speculate the prolonged MTT.

Radiomics based on multicontrast MRI can precisely differentiate among glioma subtypes and predict tumour-proliferative behaviour

PurposeTo explore the feasibility and diagnostic performance of radiomics based on anatomical, diffusion and perfusion MRI in differentiating among glioma subtypes and predicting tumour proliferation.Methods220 pathology-confirmed gliomas and ten contrasts were included in the retrospective analysis. After being registered to T2FLAIR images and resampling to 1 mm3 isotropically, 431 radiomics features were extracted from each contrast map within a semi-automatic defined tumour volume. For single-contrast and the combination of all contrasts, correlations between the radiomics features and pathological biomarkers were revealed by partial correlation analysis, and multivariate models were built to identify the best predictive models with adjusted 0.632+ bootstrap AUC.ResultsIn univariate analysis, both non-wavelet and wavelet radiomics features were correlated significantly with tumour grade and the Ki-67 labelling index. The max R was 0.557 (pxa0=xa02.04E-14) in T1C for tumour grade and 0.395 (pxa0=xa02.33E-07) in ADC for Ki-67. In the multivariate analysis, the combination of all-contrast radiomics features had the highest AUCs in both differentiating among glioma subtypes and predicting proliferation compared with those in single-contrast images. For low-/high-grade gliomas, the best AUC was 0.911. In differentiating among glioma subtypes, the best AUC was 0.896 for grades II–III, 0.997 for grades II–IV, and 0.881 for grades III–IV. In predicting proliferation levels, multicontrast features led to an AUC of 0.936.ConclusionMulticontrast radiomics supplies complementary information on both geometric characters and molecular biological traits, which correlated significantly with tumour grade and proliferation. Combining all-contrast radiomics models might precisely predict glioma biological behaviour, which may be attributed to presurgical personal diagnosis.Key Points• Multicontrast MRI radiomics features are significantly correlated with tumour grade and Ki-67 LI.• Multimodality MRI provides independent but supplemental information in assessing glioma pathological behaviour.• Combined multicontrast MRI radiomics can precisely predict glioma subtypes and proliferation levels.