MRI-based classification of the anatomical variants of the hippocampal head.

PURPOSE: The head of the hippocampus (H) is classically described as having two to four digitations both in ex vivo specimens and in vivo MR coronal images. The aim of this study was to develop and evaluate a new MR-based classification of the anatomical variants of the hippocampal head in a large sample population of healthy subjects. METHODS: MR images of the brain of 238 young healthy subjects (138 men and 100 women; age range 18-39) were analyzed. The head of the H was identified on coronal reformatted 3D T1 weighted MR images. The frequencies were reported for hemisphere and sex. Inter-rater reliability was assessed. RESULTS: Eight variants of the hippocampal head were described. Class 0 (11.4%) indicated a total absence of sulci. This class was further subdivided as follows: 0A (one digitation, 10.1%) and 0B (no digitations or "null variant", 1.3%). Class 1 (25.6%) presented a single sulcus and was further subdivided into four types according to the location and the width of the sulcus [1A (8.8%), 1B (12.8%), 1C (1.3%), and 1D (2.7%)]. Class 2 (63.0%, the most frequent and the classical variant) had two symmetrical sulci and three digitations. Statistically significant differences between the two hemispheres were observed only in women and overall. Differences in prevalence between sexes were not observed. CONCLUSIONS: The large study population allowed the description of a novel morphological classification of the different anatomical variants of normal H in the coronal plane. This classification could reduce the risk of misinterpreting normal anatomical variants as pathological.

Data-driven grading of brain gliomas: a multiparametric MR imaging study.

PURPOSE: To grade brain gliomas by using a data-driven analysis of multiparametric magnetic resonance (MR) imaging, taking into account the heterogeneity of the lesions at MR imaging, and to compare these results with the most widespread current radiologic reporting methods. MATERIALS AND METHODS: One hundred eighteen patients with histologically confirmed brain gliomas were evaluated retrospectively. Conventional and advanced MR sequences (perfusion-weighted imaging, MR spectroscopy, and diffusion-tensor imaging) were performed. Three evaluations were conducted: semiquantitative (based on conventional and advanced sequences with reported cutoffs), qualitative (exclusively based on conventional MR imaging), and quantitative. For quantitative analysis, four volumes of interest were placed: regions with contrast material enhancement, regions with highest and lowest signal intensity on T2-weighted images, and regions of most restricted diffusivity. Statistical analysis included t test, receiver operating characteristic (ROC) analysis, discriminant function analysis (DFA), leave-one-out cross-validation, and Kendall coefficient of concordance. RESULTS: Significant differences were noted in age, relative cerebral blood volume (rCBV) in contrast-enhanced regions (cutoff > 2.59; sensitivity, 80%; specificity, 91%; area under the ROC curve [AUC] = 0.937; P = .0001), areas of lowest signal intensity on T2-weighted images (>2.45, 57%, 97%, 0.852, and P = .0001, respectively), restricted diffusivity regions (>2.61, 54%, 97%, 0.808, and P = .0001, respectively), and choline/creatine ratio in regions with the lowest signal intensity on T2-weighted images (>2.07, 49%, 88%, 0.685, and P = .0007, respectively). DFA that included age; rCBV in contrast-enhanced regions, areas of lowest signal intensity on T2-weighted images, and areas of restricted diffusivity; and choline/creatine ratio in areas with lowest signal intensity on T2-weighted images was used to classify 95% of patients correctly. Quantitative analysis showed a higher concordance with histologic findings than qualitative and semiquantitative methods (P < .0001). CONCLUSION: A quantitative multiparametric MR imaging evaluation that incorporated heterogeneity at MR imaging significantly improved discrimination between low- and high-grade brain gliomas with a very high AUC (ie, 0.95), thus reducing the risk of inappropriate or delayed surgery, respectively.

Modifications of default-mode network connectivity in patients with cerebral glioma.

PURPOSE: The aim of the study was to evaluate connectivity modifications in the Default Mode Network (DMN) in patients with cerebral glioma, and to correlate these modifications to tumor characteristics. METHODS: Twenty-four patients with a left-hemisphere cerebral tumor (14 grade II and 10 grade IV gliomas) and 14 healthy age-matched right-hand volunteers were enrolled in the study. Subjects underwent fMRI while performing language tasks for presurgical mapping. Data was analyzed with independent component analysis in order to identify the DMN. DMN group maps were produced by random-effect analysis (p<0.001, FDR-corrected). An analysis of variance across the three groups (p<0.05) and post-hoc t-test contrasts between pairs of groups were calculated (p<0.05, FDR-corrected). RESULTS: All three groups showed typical DMN areas. However, reduced DMN connectivity was detected in tumor patients with respect to controls. A significantly increased and reduced integration of DMN areas was observed in the hippocampal and prefrontal regions, respectively. Modifications were closely related to tumor grading. Moreover, the DMN lateralized to the hemisphere contralateral to tumor in the low-grade, but not in the high-grade tumor patients. CONCLUSION: Modifications of DMN connectivity were induced by gliomas and differed for high and low grade tumors.