Autoimmune encephalitis: what the radiologist needs to know.

Autoimmune encephalitis is a relatively novel nosological entity characterized by an immune-mediated damage of the central nervous system. While originally described as a paraneoplastic inflammatory phenomenon affecting limbic structures, numerous instances of non-paraneoplastic pathogenesis, as well as extra-limbic involvement, have been characterized. Given the wide spectrum of insidious clinical presentations ranging from cognitive impairment to psychiatric symptoms or seizures, it is crucial to raise awareness about this disease category. In fact, an early diagnosis can be dramatically beneficial for the prognosis both to achieve an early therapeutic intervention and to detect a potential underlying malignancy. In this scenario, the radiologist can be the first to pose the hypothesis of autoimmune encephalitis and refer the patient to a comprehensive diagnostic work-up - including clinical, serological, and neurophysiological assessments.In this article, we illustrate the main radiological characteristics of autoimmune encephalitis and its subtypes, including the typical limbic presentation, the features of extra-limbic involvement, and also peculiar imaging findings. In addition, we review the most relevant alternative diagnoses that should be considered, ranging from other encephalitides to neoplasms, vascular conditions, and post-seizure alterations. Finally, we discuss the most appropriate imaging diagnostic work-up, also proposing a suggested MRI protocol.

Cortically constrained shape recognition: Automated white matter tract segmentation validated in the pediatric brain.

BACKGROUND AND PURPOSE: Manual segmentation of white matter (WM) bundles requires extensive training and is prohibitively labor-intensive for large-scale studies. Automated segmentation methods are necessary in order to eliminate operator dependency and to enable reproducible studies. Significant changes in the WM landscape throughout childhood require flexible methods to capture the variance across the span of brain development. METHODS: Here, we describe a novel automated segmentation tool called Cortically Constrained Shape Recognition (CCSR), which combines two complementary approaches: (1) anatomical connectivity priors based on FreeSurfer-derived regions of interest and (2) shape priors based on 3-dimensional streamline bundle atlases applied using RecoBundles. We tested the performance and repeatability of this approach by comparing volume and diffusion metrics of the main language WM tracts that were both manually and automatically segmented in a pediatric cohort acquired at the UCSF Dyslexia Center (n = 59; 25 females; average age: 11 ± 2; range: 7-14). RESULTS: The CCSR approach showed high agreement with the expert manual segmentations: across all tracts, the spatial overlap between tract volumes showed an average Dice Similarity Coefficient (DSC) of 0.76, and the fractional anisotropy (FA) on average had a Lin's Concordance Correlation Coefficient (CCC) of 0.81. The CCSR's repeatability in a subset of this cohort achieved a DSC of 0.92 on average across all tracts. CONCLUSION: This novel automated segmentation approach is a promising tool for reproducible large-scale tractography analyses in pediatric populations and particularly for the quantitative assessment of structural connections underlying various clinical presentations in neurodevelopmental disorders.

fMRI-Targeted High-Angular Resolution Diffusion MR Tractography to Identify Functional Language Tracts in Healthy Controls and Glioma Patients.

BACKGROUND: MR Tractography enables non-invasive preoperative depiction of language subcortical tracts, which is crucial for the presurgical work-up of brain tumors; however, it cannot evaluate the exact function of the fibers. PURPOSE: A systematic pipeline was developed to combine tractography reconstruction of language fiber bundles, based on anatomical landmarks (Anatomical-T), with language fMRI cortical activations. A fMRI-targeted Tractography (fMRI-T) was thus obtained, depicting the subsets of the anatomical tracts whose endpoints are located inside a fMRI activation. We hypothesized that fMRI-T could provide additional functional information regarding the subcortical structures, better reflecting the eloquent white matter structures identified intraoperatively. METHODS: Both Anatomical-T and fMRI-T of language fiber tracts were performed on 16 controls and preoperatively on 16 patients with left-hemisphere brain tumors, using a q-ball residual bootstrap algorithm based on High Angular Resolution Diffusion Imaging (HARDI) datasets (b = 3000 s/mm2; 60 directions); fMRI ROIs were obtained using picture naming, verbal fluency, and auditory verb generation tasks. In healthy controls, normalized MNI atlases of fMRI-T and Anatomical-T were obtained. In patients, the surgical resection of the tumor was pursued by identifying eloquent structures with intraoperative direct electrical stimulation mapping and extending surgery to the functional boundaries. Post-surgical MRI allowed to identify Anatomical-T and fMRI-T non-eloquent portions removed during the procedure. RESULTS: MNI Atlases showed that fMRI-T is a subset of Anatomical-T, and that different task-specific fMRI-T involve both shared subsets and task-specific subsets - e.g., verbal fluency fMRI-T strongly involves dorsal frontal tracts, consistently with the phonogical-articulatory features of this task. A quantitative analysis in patients revealed that Anatomical-T removed portions of AF-SLF and IFOF were significantly greater than verbal fluency fMRI-T ones, suggesting that fMRI-T is a more specific approach. In addition, qualitative analyses showed that fMRI-T AF-SLF and IFOF predict the exact functional limits of resection with increased specificity when compared to Anatomical-T counterparts, especially the superior frontal portion of IFOF, in a subcohort of patients. CONCLUSION: These results suggest that performing fMRI-T in addition to the 'classic' Anatomical-T may be useful in a preoperative setting to identify the 'high-risk subsets' that should be spared during the surgical procedure.

Language outcomes after resection of dominant inferior parietal lobule gliomas.

OBJECTIVE The dominant inferior parietal lobule (IPL) contains cortical and subcortical regions essential for language. Although resection of IPL tumors could result in language deficits, little is known about the likelihood of postoperative language morbidity or the risk factors predisposing to this outcome. METHODS The authors retrospectively examined a series of patients who underwent resections of gliomas from the dominant IPL. Postoperative language outcomes were characterized across the patient population. To identify factors associated with postoperative language morbidity, the authors then compared features between those patients who experienced postoperative deficits and those who experienced no postoperative language dysfunction. RESULTS Twenty-four patients were identified for analysis. Long-term language deficits occurred in 29.2% of patients (7 of 24): 3 of these patients had experienced preoperative language deficits, whereas new long-term language deficits occurred in 4 patients (16.7%; 4 of 24). Of those patients who exhibited preoperative language deficits, 62.5% (5 of 8) experienced long-term resolution of their language deficits with surgical treatment. All patients underwent intraoperative brain mapping by direct electrical stimulation. Awake, intraoperative cortical language mapping was performed on 17 patients (70.8%). Positive cortical language sites were identified in 23.5% of these patients (4 of 17). Awake, intraoperative subcortical language mapping was performed in 8 patients (33.3%). Positive subcortical language sites were identified in 62.5% of these patients (5 of 8). Patients with positive cortical language sites exhibited a higher rate of long-term language deficits (3 of 4, 75%), compared with those who did not (1 of 13, 7.7%; p = 0.02). Although patients with positive subcortical language sites exhibited a higher rate of long-term language deficits than those who exhibited only negative sites (40.0% vs 0.0%, respectively), this difference was not statistically significant (p = 0.46). Additionally, patients with long-term language deficits were older than those without deficits (p < 0.05). CONCLUSIONS In a small number of patients with preoperative language deficits, IPL glioma resection resulted in improved language function. However, in patients with intact preoperative language function, resection of IPL gliomas may result in new language deficits, especially if the tumors are diffuse, high-grade lesions. Thus, language-dominant IPL glioma resection is not risk-free, yet it is safe and its morbidity can be reduced by the use of cortical and subcortical stimulation mapping.

Neurite Orientation Dispersion and Density Imaging Color Maps to Characterize Brain Diffusion in Neurologic Disorders.

PURPOSE: Neurite orientation dispersion and density imaging (NODDI) has recently been developed to overcome diffusion technique limitations in modeling biological systems. This manuscript reports a preliminary investigation into the use of a single color-coded map to represent NODDI-derived information. MATERIALS AND METHODS: An optimized diffusion-weighted imaging protocol was acquired in several clinical neurological contexts including demyelinating disease, neoplastic process, stroke, and toxic/metabolic disease. The NODDI model was fitted to the diffusion datasets. NODDI is based on a three-compartment diffusion model and provides maps that quantify the contributions to the total diffusion signal in each voxel. The NODDI compartment maps were combined into a single 4-dimensional volume visualized as RGB image (red for anisotropic Gaussian diffusion, green for non-Gaussian anisotropic diffusion, and blue for isotropic Gaussian diffusion), in which the relative contributions of the different microstructural compartments can be easily appreciated. RESULTS: The NODDI color maps better describe the heterogeneity of neoplastic as well inflammatory lesions by identifying different tissue components within areas apparently homogeneous on conventional imaging. Moreover, NODDI color maps seem to be useful for identifying vasogenic edema differently from tumor-infiltrated edema. In multiple sclerosis, the NODDI color maps enable a visual assessment of the underlying microstructural changes, possibly highlighting an increased inflammatory component, within lesions and potentially in normal-appearing white matter. CONCLUSION: The NODDI color maps could make this technique valuable in a clinical setting, providing comprehensive and accessible information in normal and pathological brain tissues in different neurological pathologies.

Identifying preoperative language tracts and predicting postoperative functional recovery using HARDI q-ball fiber tractography in patients with gliomas.

OBJECT Diffusion MRI has uniquely enabled in vivo delineation of white matter tracts, which has been applied to the segmentation of eloquent pathways for intraoperative mapping. The last decade has also seen the development from earlier diffusion tensor models to higher-order models, which take advantage of high angular resolution diffusion-weighted imaging (HARDI) techniques. However, these advanced methods have not been widely implemented for routine preoperative and intraoperative mapping. The authors report on the application of residual bootstrap q-ball fiber tracking for routine mapping of potentially functional language pathways, the development of a system for rating tract injury to evaluate the impact on clinically assessed language function, and initial results predicting long-term language deficits following glioma resection. METHODS The authors have developed methods for the segmentation of 8 putative language pathways including dorsal phonological pathways and ventral semantic streams using residual bootstrap q-ball fiber tracking. Furthermore, they have implemented clinically feasible preoperative acquisition and processing of HARDI data to delineate these pathways for neurosurgical application. They have also developed a rating scale based on the altered fiber tract density to estimate the degree of pathway injury, applying these ratings to a subset of 35 patients with pre- and postoperative fiber tracking. The relationships between specific pathways and clinical language deficits were assessed to determine which pathways are predictive of long-term language deficits following surgery. RESULTS This tracking methodology has been routinely implemented for preoperative mapping in patients with brain gliomas who have undergone awake brain tumor resection at the University of California, San Francisco (more than 300 patients to date). In this particular study the authors investigated the white matter structure status and language correlation in a subcohort of 35 subjects both pre- and postsurgery. The rating scales developed for fiber pathway damage were found to be highly reproducible and provided significant correlations with language performance. Preservation of the left arcuate fasciculus (AF) and the temporoparietal component of the superior longitudinal fasciculus (SLF-tp) was consistent in all patients without language deficits (p < 0.001) at the long-term follow-up. Furthermore, in patients with short-term language deficits, the AF and/or SLF-tp were affected, and damage to these 2 pathways was predictive of a long-term language deficit (p = 0.005). CONCLUSIONS The authors demonstrated the successful application of q-ball tracking in presurgical planning for language pathways in brain tumor patients and in assessing white matter tract integrity postoperatively to predict long-term language dysfunction. These initial results predicting long-term language deficits following tumor resection indicate that postoperative injury to dorsal language pathways may be prognostic for long-term clinical language deficits. Study results suggest the importance of dorsal stream tract preservation to reduce language deficits in patients undergoing glioma resection, as well as the potential prognostic value of assessing postoperative injury to dorsal language pathways to predict long-term clinical language deficits.

Neural stem cell engraftment and myelination in the human brain.

Pelizaeus-Merzbacher disease (PMD) is a rare leukodystrophy caused by mutation of the proteolipid protein 1 gene. Defective oligodendrocytes in PMD fail to myelinate axons, causing global neurological dysfunction. Human central nervous system stem cells (HuCNS-SCs) can develop into oligodendrocytes and confer structurally normal myelin when transplanted into a hypomyelinating mouse model. A 1-year, open-label phase-1 study was undertaken to evaluate safety and to detect evidence of myelin formation after HuCNS-SC transplantation. Allogeneic HuCNS-SCs were surgically implanted into the frontal lobe white matter in four male subjects with an early-onset severe form of PMD. Immunosuppression was administered for 9 months. Serial neurological evaluations, developmental assessments, and cranial magnetic resonance imaging (MRI) and MR spectroscopy, including high-angular resolution diffusion tensor imaging (DTI), were performed at baseline and after transplantation. The neurosurgical procedure, immunosuppression regimen, and HuCNS-SC transplantation were well tolerated. Modest gains in neurological function were observed in three of the four subjects. No clinical or radiological adverse effects were directly attributed to the donor cells. Reduced T1 and T2 relaxation times were observed in the regions of transplantation 9 months after the procedure in the three subjects. Normalized DTI showed increasing fractional anisotropy and reduced radial diffusivity, consistent with myelination, in the region of transplantation compared to control white matter regions remote to the transplant sites. These phase 1 findings indicate a favorable safety profile for HuCNS-SCs in subjects with PMD. The MRI results suggest durable cell engraftment and donor-derived myelin in the transplanted host white matter.