Visualization of Cranial Nerves Using High-Definition Fiber Tractography

Brain tissue microstructure in a prospective, longitudinal, population-based cohort of preterm and term-born young adults

BACKGROUND

Fifteen million infants annually are born prematurely, placing them at high risk for life-long adverse neurodevelopmental outcomes. Whether brain tissue abnormalities that accompany preterm birth persist into young adulthood and are associated with long-term cognitive or psychiatric outcomes is not known.

METHODS

From infancy into young adulthood, we followed a population-based sample of consecutively identified preterm infants and their matched term controls. The preterm group was born at an average gestational age of 31.5 ± 2.6 weeks. We obtained Diffusion Tensor Imaging scans and assessed cognitive and psychiatric outcomes in young adulthood, at a mean age of 19 (range 17.6-20.8) years. Usable data were acquired from 180 participants (89 preterm, 91 term).

RESULTS

Preterm birth was associated with lower fractional anisotropy (FA) and higher average diffusion coefficient (ADC) values in deep white matter tracts of the internal capsule, cerebral peduncles, inferior frontal-occipital fasciculus, sagittal stratum and splenium of the corpus callosum, as well as in grey matter of the caudate, putamen and thalamus. A younger gestational age at birth accentuated these tissue abnormalities. Perinatal characteristics, including lower 5-min APGAR score, history of bronchopulmonary dysplasia, more days of oxygen supplementation and multiple births all increased ADC values in deep white matter tracts and grey matter throughout the brain. Preterm individuals had significantly lower full-scale IQ and more frequent lifetime psychiatric disorders. Those with psychiatric illnesses had significantly higher ADC and lower FA values throughout the deep posterior white matter.

CONCLUSIONS

Abnormalities in brain tissue microstructure associated with preterm birth persist into young adulthood and likely represent disordered myelination and accompanying axonal pathology. These disturbances are associated with a higher likelihood of developing a psychiatric disorder by young adulthood. Brain tissue disturbances were accentuated in those born at younger gestational ages and in those with a history of perinatal complications associated with infection and inflammation.

Assessing Visual Pathway White Matter Degeneration in Primary Open-Angle Glaucoma Using Multiple MRI Morphology and Diffusion Metrics

BACKGROUND

Primary open-angle glaucoma (POAG), a leading cause of irreversible blindness, is associated with neurodegeneration in the visual pathway, but the underlying pathophysiology remains incompletely resolved.

PURPOSE

To characterize macro- and microstructural white matter abnormalities in optic tract (OT) and optic radiation (OR) of POAG.

STUDY TYPE

Prospective.

POPULATIONS

A total of 34 POAG patients (21 males, 13 females) and 25 healthy controls (HCs) (16 males, nine females).

FIELD STRENGTH/SEQUENCE

3 T; multiband spin-echo echo planar diffusion spectrum imaging (DSI).

ASSESSMENT

We compared multiple morphology metrics, including volume, area, length, and shape metrics, as well as diffusion metrics such as diffusion tensor imaging (fractional anisotropy [FA], mean diffusivity, radial diffusivity, and axial diffusivity), mean apparent propagator (mean squared displacement, q-space inverse variance, return-to-origin probability, return-to-axis probabilities [RTAP] and return-to-plane probabilities, non-Gaussianity, perpendicular non-Gaussianity, parallel non-Gaussianity), and neurite orientation dispersion and density imaging (intracellular volume fraction, orientation dispersion index [ODI], and isotropic volume fraction of the OT and OR).

STATISTICAL TESTS

Statistical comparisons and classifications employed linear mixed model and logistic regression. Diagnostic performance was assessed using area under the receiver operating characteristic curve (AUC). P-value <0.05 was statistically significant.

RESULTS

Morphology analysis in POAG revealed a lower span in the OR (29.43 ± 2.30 vs. 30.59 ± 2.01, 3.8%) and OT (19.73 ± 2.21 vs. 20.68 ± 1.37, 4.6%), and a higher curl (3.03 ± 0.22 vs. 2.90 ± 0.16, 4.5%) in OT. Diffusion metrics revealed lower mean FA (OR: 0.328 ± 0.03 vs. 0.340 ± 0.018, 3.5%; OT: 0.255 ± 0.022 vs. 0.268 ± 0.018, 4.9%) and lower mean RTAP (OR: 5.919 ± 0.529 vs. 6.216 ± 0.489, 4.8%; OT: 4.089 ± 0.402 vs. 4.280 ± 0.353, 4.5%), with higher mean ODI in the OT (0.448 ± 0.029 vs. 0.433 ± 0.025, 3.5%). Combined models, incorporating these MRI metrics, effectively discriminated POAG from HCs, achieving AUCs of 0.84 for OR and 0.83 for OT.

DATA CONCLUSIONS

DSI-derived morphology and diffusion metrics demonstrated macro- and micro abnormalities in the visual pathway, providing insights into POAG-related neurodegeneration.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 3.

Preoperative Vascular and Cranial Nerve Imaging in Skull Base Tumors

Skull base tumors such as meningiomas and schwannomas are often pathologically benign. However, surgery for these tumors poses significant challenges because of their proximity to critical structures such as the brainstem, cerebral arteries, veins, and cranial nerves. These structures are compressed or encased by the tumor as they grow, increasing the risk of unintended injury to these structures, which can potentially lead to severe neurological deficits. Preoperative imaging is crucial for assessing the tumor size, location, and its relationship with adjacent vital structures. This study reviews advanced imaging techniques that allow detailed visualization of vascular structures and cranial nerves. Contrast-enhanced computed tomography and digital subtraction angiography are optimal for evaluating vascular structures, whereas magnetic resonance imaging (MRI) with high-resolution T2-weighted images and diffusion tensor imaging are optimal for evaluating cranial nerves. These methods help surgeons plan tumor resection strategies, including surgical approaches, more precisely. An accurate preoperative assessment can contribute to safe tumor resection and preserve neurological function. Additionally, we report the MRI contrast defect sign in skull base meningiomas, which suggests cranial nerve penetration through the tumor. This is an essential finding for inferring the course of cranial nerves completely encased within the tumor. These preoperative imaging techniques have the potential to improve the outcomes of patients with skull base tumors. Furthermore, this study highlights the importance of multimodal imaging approaches and discusses future directions for imaging technology that could further develop preoperative surgical simulations and improve the quality of complex skull base tumor surgeries.

Tractography-Based Automated Identification of Retinogeniculate Visual Pathway With Novel Microstructure-Informed Supervised Contrastive Learning

The retinogeniculate visual pathway (RGVP) is responsible for carrying visual information from the retina to the lateral geniculate nucleus. Identification and visualization of the RGVP are important in studying the anatomy of the visual system and can inform the treatment of related brain diseases. Diffusion MRI (dMRI) tractography is an advanced imaging method that uniquely enables in vivo mapping of the 3D trajectory of the RGVP. Currently, identification of the RGVP from tractography data relies on expert (manual) selection of tractography streamlines, which is time-consuming, has high clinical and expert labor costs, and is affected by inter-observer variability. In this paper, we present a novel deep learning framework, DeepRGVP, to enable fast and accurate identification of the RGVP from dMRI tractography data. We design a novel microstructure-informed supervised contrastive learning method that leverages both streamline label and tissue microstructure information to determine positive and negative pairs. We propose a new streamline-level data augmentation method to address highly imbalanced training data, where the number of RGVP streamlines is much lower than that of non-RGVP streamlines. In the experiments, we perform comparisons with several state-of-the-art deep learning methods that were designed for tractography parcellation. Furthermore, to assess the generalizability of the proposed RGVP method, we apply our method to dMRI tractography data from neurosurgical patients with pituitary tumors. In comparison with the state-of-the-art methods, we show superior RGVP identification results using DeepRGVP with significantly higher accuracy and F1 scores. In the patient data experiment, we show DeepRGVP can successfully identify RGVPs despite the effect of lesions affecting the RGVPs. Overall, our study shows the high potential of using deep learning to automatically identify the RGVP.

A novel 3D multimodal fusion imaging surgical guidance in microvascular decompression for primary trigeminal neuralgia and hemifacial spasm

BACKGROUND

Neurovascular compression (NVC) is a primary etiology of trigeminal neuralgia (TN) and hemifacial spasm (HFS). Despite Magnetic Resonance Tomographic Angiography (MRTA) being a useful tool for 3D multimodal fusion imaging (MFI) in microvascular decompression (MVD) surgery planning, it may not visualize smaller arterial vessels and veins effectively. We validate a novel computed tomography angiography and venography (CTA/V) - diffusion tensor tractography (DTT) -3D-MFI to enhance the MVD surgical guidance.

METHODS

In this prospective study, 80 patients with unilateral primary TN or HFS who underwent MVD surgery were included. Imaging was conducted using CTA/V-DTT-3D-MFI compared with CT-MRTA-3D-MFI in predicting the responsible vessel and assessing the severity of NVC. Surgical outcomes were subsequently analyzed. Neurosurgery residents were provided with questionnaires to evaluate and compare the two approaches.

RESULTS

CTA/V-DTT-3D-MFI significantly improved accuracy in identifying the responsible vessel (kappa = 0.954) and NVC (kappa = 0.969) compared to CT-MRTA-3D-MFI, aligning well with surgical findings. CTA/V-DTT-3D-MFI also exhibited higher sensitivity in identifying responsible vessels (98.0%) and NVC (98.7%) than CT-MRTA-3D-MFI. Additionally, CTA/V-DTT-3D-MFI showed fewer complications, shorter operation times, and lower recurrence after one year (all p < 0.05). Resident neurosurgeons emphasized that CTA/V-DTT-3D-MFI greatly assisted in formulating precise surgical strategies for more accurate identification and protection of responsible vessels and nerves (all p < 0.001).

CONCLUSION

CTA/V-DTT-3D-MFI enhances MVD surgery guidance, improving accuracy in identifying responsible vessels and NVC for better outcomes. This advanced imaging plays a crucial role in safer and more effective MVD surgery, as well as in training neurosurgeons.

Facial Nerve Tractography Using Diffusion MRI: A Comparison of Acquisition b -Values and Single- and Multifiber Tracking Strategies

HYPOTHESIS

This study investigates the impact of different diffusion magnetic imaging (dMRI) acquisition settings and mathematical fiber models on tractography performance for depicting cranial nerve (CN) VII in healthy young adults.

BACKGROUND

The aim of this study is to optimize visualization of CN VII for preoperative assessment in surgeries near the nerve in the cerebellopontine angle, reducing surgery-associated complications. The study analyzes 100 CN VII in dMRI images from the Human Connectome Project, using three separate sets with different b values ( b = 1,000 s/mm 2 , b =2,000 s/mm 2 , b =3,000 s/mm 2 ) and four different tractography methods, resulting in 1,200 tractographies analyzed.

RESULTS

The results show that multifiber and free water (FW) compartment models produce significantly more streamlines than single-fiber tractography. The addition of an FW compartment significantly increases the mean streamline fractional anisotropy (FA). Expert quality ratings showed that the highest rated tractography was the 1 tensor (1T) method without FW at b values of 1,000 s/mm2.

CONCLUSIONS

In this young and healthy cohort, best tractography results are obtained by using a 1T model without a FW compartment in b =1,000 diffusion MR images. The FW compartment increased the contrast between streamlines and cerebrospinal fluid (higher mean streamline FA). This finding may help ongoing research to improve CN VII tractography results in tumor cases where the nerve is often stretched and thinned by the tumor.

Comparative study of CTA/CTV and MRTA for preoperative simulation of microvascular decompression in neurovascular compression syndromes

Neurovascular compression syndrome (NVCS), characterized by cranial nerve compression due to adjacent blood vessels at the root entry zone, frequently presents as trigeminal neuralgia (TN), hemifacial spasm (HFS), or glossopharyngeal neuralgia (GN). Despite its prevalence in NVCS assessment, Magnetic Resonance Tomographic Angiography (MRTA)'s limited sensitivity to small vessels and veins poses challenges. This study aims to refine vessel localization and surgical planning for NVCS patients using a novel 3D multimodal fusion imaging (MFI) technique incorporating computed tomography angiography and venography (CTA/CTV). A retrospective analysis was conducted on 76 patients who underwent MVD surgery and were diagnosed with single-site primary TN, HFS, or GN. Imaging was obtained from MRTA and CTA/CTV sequences, followed by image processing and 3D-MFI using FastSurfer and 3DSlicer. The CTA/CTV-3D-MFI showed higher sensitivity than MRTA-3D-MFI in predicting responsible vessels (98.6% vs. 94.6%) and NVC severity (98.6% vs. 90.8%). Kappa coefficients revealed strong agreement with MRTA-3D-MFI (0.855 for vessels, 0.835 for NVC severity) and excellent agreement with CTA/CTV-3D-MFI (0.951 for vessels, 0.952 for NVC). Resident neurosurgeons significantly preferred CTA/CTV-3D-MFI due to its better correlation with surgical reality, clearer depiction of surgical anatomy, and optimized visualization of approaches (p < 0.001). Implementing CTA/CTV-3D-MFI significantly enhanced diagnostic accuracy and surgical planning for NVCS, outperforming MRTA-3D-MFI in identifying responsible vessels and assessing NVC severity. This innovative imaging modality can potentially improve outcomes by guiding safer and more targeted surgeries, particularly in cases where MRTA may not adequately visualize crucial neurovascular structures.

Tractography-based automated identification of the retinogeniculate visual pathway with novel microstructure-informed supervised contrastive learning

The retinogeniculate visual pathway (RGVP) is responsible for carrying visual information from the retina to the lateral geniculate nucleus. Identification and visualization of the RGVP are important in studying the anatomy of the visual system and can inform the treatment of related brain diseases. Diffusion MRI (dMRI) tractography is an advanced imaging method that uniquely enables in vivo mapping of the 3D trajectory of the RGVP. Currently, identification of the RGVP from tractography data relies on expert (manual) selection of tractography streamlines, which is time-consuming, has high clinical and expert labor costs, and is affected by inter-observer variability. In this paper, we present a novel deep learning framework, DeepRGVP , to enable fast and accurate identification of the RGVP from dMRI tractography data. We design a novel microstructure-informed supervised contrastive learning method that leverages both streamline label and tissue microstructure information to determine positive and negative pairs. We propose a simple and successful streamline-level data augmentation method to address highly imbalanced training data, where the number of RGVP streamlines is much lower than that of non-RGVP streamlines. We perform comparisons with several state-of-the-art deep learning methods that were designed for tractography parcellation, and we show superior RGVP identification results using DeepRGVP. In addition, we demonstrate a good generalizability of DeepRGVP to dMRI tractography data from neurosurgical patients with pituitary tumors and we show DeepRGVP can successfully identify RGVPs despite the effect of lesions affecting the RGVPs. Overall, our study shows the high potential of using deep learning to automatically identify the RGVP.

Diffusion MRI of the facial-vestibulocochlear nerve complex: a prospective clinical validation study

OBJECTIVES

Surgical planning of vestibular schwannoma surgery would benefit greatly from a robust method of delineating the facial-vestibulocochlear nerve complex with respect to the tumour. This study aimed to optimise a multi-shell readout-segmented diffusion-weighted imaging (rs-DWI) protocol and develop a novel post-processing pipeline to delineate the facial-vestibulocochlear complex within the skull base region, evaluating its accuracy intraoperatively using neuronavigation and tracked electrophysiological recordings.

METHODS

In a prospective study of five healthy volunteers and five patients who underwent vestibular schwannoma surgery, rs-DWI was performed and colour tissue maps (CTM) and probabilistic tractography of the cranial nerves were generated. In patients, the average symmetric surface distance (ASSD) and 95% Hausdorff distance (HD-95) were calculated with reference to the neuroradiologist-approved facial nerve segmentation. The accuracy of patient results was assessed intraoperatively using neuronavigation and tracked electrophysiological recordings.

RESULTS

Using CTM alone, the facial-vestibulocochlear complex of healthy volunteer subjects was visualised on 9/10 sides. CTM were generated in all 5 patients with vestibular schwannoma enabling the facial nerve to be accurately identified preoperatively. The mean ASSD between the annotators' two segmentations was 1.11 mm (SD 0.40) and the mean HD-95 was 4.62 mm (SD 1.78). The median distance from the nerve segmentation to a positive stimulation point was 1.21 mm (IQR 0.81-3.27 mm) and 2.03 mm (IQR 0.99-3.84 mm) for the two annotators, respectively.

CONCLUSIONS

rs-DWI may be used to acquire dMRI data of the cranial nerves within the posterior fossa.

CLINICAL RELEVANCE STATEMENT

Readout-segmented diffusion-weighted imaging and colour tissue mapping provide 1-2 mm spatially accurate imaging of the facial-vestibulocochlear nerve complex, enabling accurate preoperative localisation of the facial nerve. This study evaluated the technique in 5 healthy volunteers and 5 patients with vestibular schwannoma.

KEY POINTS

• Readout-segmented diffusion-weighted imaging (rs-DWI) with colour tissue mapping (CTM) visualised the facial-vestibulocochlear nerve complex on 9/10 sides in 5 healthy volunteer subjects. • Using rs-DWI and CTM, the facial nerve was visualised in all 5 patients with vestibular schwannoma and within 1.21-2.03 mm of the nerve's true intraoperative location. • Reproducible results were obtained on different scanners.

3D color multimodality fusion imaging as an augmented reality educational and surgical planning tool for extracerebral tumors

Extracerebral tumors often occur on the surface of the brain or at the skull base. It is important to identify the peritumoral sulci, gyri, and nerve fibers. Preoperative visualization of three-dimensional (3D) multimodal fusion imaging (MFI) is crucial for surgery. However, the traditional 3D-MFI brain models are homochromatic and do not allow easy identification of anatomical functional areas. In this study, 33 patients with extracerebral tumors without peritumoral edema were retrospectively recruited. They underwent 3D T1-weighted MRI, diffusion tensor imaging (DTI), and CT angiography (CTA) sequence scans. 3DSlicer, Freesurfer, and BrainSuite were used to explore 3D-color-MFI and preoperative planning. To determine the effectiveness of 3D-color-MFI as an augmented reality (AR) teaching tool for neurosurgeons and as a patient education and communication tool, questionnaires were administered to 15 neurosurgery residents and all patients, respectively. For neurosurgical residents, 3D-color-MFI provided a better understanding of surgical anatomy and more efficient techniques for removing extracerebral tumors than traditional 3D-MFI (P < 0.001). For patients, the use of 3D-color MFI can significantly improve their understanding of the surgical approach and risks (P < 0.005). 3D-color-MFI is a promising AR tool for extracerebral tumors and is more useful for learning surgical anatomy, developing surgical strategies, and improving communication with patients.

Methods of diffusion MRI tractography for localization of the anterior optic pathway: A systematic review of validated methods

The anterior optic pathway (AOP) is a system of three structures (optic nerves, optic chiasma, and optic tracts) that convey visual stimuli from the retina to the lateral geniculate nuclei. A successful reconstruction of the AOP using tractography could be helpful in several clinical scenarios, from presurgical planning and neuronavigation of sellar and parasellar surgery to monitoring the stage of fiber degeneration both in acute (e.g., traumatic optic neuropathy) or chronic conditions that affect AOP structures (e.g., amblyopia, glaucoma, demyelinating disorders or genetic optic nerve atrophies). However, its peculiar anatomy and course, as well as its surroundings, pose a serious challenge to obtaining successful tractographic reconstructions. Several AOP tractography strategies have been adopted but no standard procedure has been agreed upon. We performed a systematic review of the literature according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) 2020 guidelines in order to find the combinations of acquisition and reconstruction parameters that have been performed previously and have provided the highest rate of successful reconstruction of the AOP, in order to promote their routine implementation in clinical practice. For this purpose, we reviewed data regarding how the process of anatomical validation of the tractographies was performed. The Cochrane Handbook for Systematic Reviews of Interventions was used to assess the risk of bias and thus the study quality We identified thirty-nine studies that met our inclusion criteria, and only five were considered at low risk of bias and achieved over 80% of successful reconstructions. We found a high degree of heterogeneity in the acquisition and analysis parameters used to perform AOP tractography and different combinations of them can achieve satisfactory levels of anterior optic tractographic reconstruction both in real-life research and clinical scenarios. One thousand s/mm2 was the most frequently used b value, while both deterministic and probabilistic tractography algorithms performed morphological reconstruction of the tract satisfactorily, although probabilistic algorithms estimated a more realistic percentage of crossing fibers (45.6%) in healthy subjects. A wide heterogeneity was also found regarding the method used to assess the anatomical fidelity of the AOP reconstructions. Three main strategies can be found: direct visual direct visual assessment of the tractography superimposed to a conventional MR image, surgical evaluation, and computational methods. Because the latter is less dependent on a priori knowledge of the anatomy by the operator, computational methods of validation of the anatomy should be considered whenever possible.

The use of diffusion magnetic resonance imaging tractography in supporting anatomical conflict between an uncal protrusion and the oculomotor nerve: A case report of isolated inferior rectus palsy

Background

Isolated inferior rectus muscle palsy is a rare entity and even more rarely induced by an anatomical conflict. We report here a clinical case of third cranial nerve (CN III) compression in its cisternal segment by an idiopathic uncal protrusion in a patient presenting an isolated inferior rectus muscle palsy.

Case Description

We report a case of an anatomical conflict between the uncus and the CN III in the form of a protrusion and highly asymmetrical proximity of the uncus and asymmetrically thinned nerve diameter deviated from its straight cisternal trajectory on the ipsilateral side were supported by an altered diffusion tractography along the concerned CN III. Clinical description, review of the literature, and image analysis were done including CN III fiber reconstruction using a fused image from diffusion tensor imaging images, constructive interference in steady state, and T2-fluid-attenuated inversion recovery images on a dedicated software (BrainLAB AG).

Conclusion

This case illustrates the importance of anatomical-clinical correlation in cases of CN deficits and supports the use of new neuroradiologically based interrogation methods such as CN diffusion tractography to support anatomical CN conflicts.

CNTSeg: A multimodal deep-learning-based network for cranial nerves tract segmentation

The segmentation of cranial nerves (CNs) tracts based on diffusion magnetic resonance imaging (dMRI) provides a valuable quantitative tool for the analysis of the morphology and course of individual CNs. Tractography-based approaches can describe and analyze the anatomical area of CNs by selecting the reference streamlines in combination with ROIs-based (regions-of-interests) or clustering-based. However, due to the slender structure of CNs and the complex anatomical environment, single-modality data based on dMRI cannot provide a complete and accurate description, resulting in low accuracy or even failure of current algorithms in performing individualized CNs segmentation. In this work, we propose a novel multimodal deep-learning-based multi-class network for automated cranial nerves tract segmentation without using tractography, ROI placement or clustering, called CNTSeg. Specifically, we introduced T1w images, fractional anisotropy (FA) images, and fiber orientation distribution function (fODF) peaks into the training data set, and design the back-end fusion module which uses the complementary information of the interphase feature fusion to improve the segmentation performance. CNTSeg has achieved the segmentation of 5 pairs of CNs (i.e. optic nerve CN II, oculomotor nerve CN III, trigeminal nerve CN V, and facial-vestibulocochlear nerve CN VII/VIII). Extensive comparisons and ablation experiments show promising results and are anatomically convincing even for difficult tracts. The code will be openly available at https://github.com/IPIS-XieLei/CNTSeg.

Visualization of human optic nerve by diffusion tensor mapping and degree of neuropathy

Diffusion-weighted magnetic resonance imaging of the human optic nerve and tract is technically difficult because of its small size, the inherent strong signal generated by the surrounding fat and the cerebrospinal fluid, and due to eddy current-induced distortions and subject movement artifacts. The effects of the bone canal through which the optic nerve passes, and the proximity of blood vessels, muscles and tendons are generally unknown. Also, the limited technical capabilities of the scanners and the minimization of acquisition times result in poor quality diffusion-weighted images. It is challenging for current tractography methods to accurately track optic pathway fibers that correspond to known anatomy. Despite these technical limitations and low image resolution, here we show how to visualize the optic nerve and tract and quantify nerve atrophy. Our visualization method based on the analysis of the diffusion tensor shows marked differences between a healthy male subject and a male subject with progressive optic nerve neuropathy. These differences coincide with diffusion scalar metrics and are not visible on standard morphological images. A quantification of the degree of optic nerve atrophy in a systematic way is provided and it is tested on 9 subjects from the Human Connectome Project.

Association fiber tracts related to Broca’s area: A comparative study based on diffusion spectrum imaging and fiber dissection

Broca’s area, made up of Brodmann areas (BA) 44 and 45 in the ventrolateral frontal region, is associated with language production and articulation. A comprehensive network analysis of Broca’s area is necessary for understanding language function, which is still lacking. In this study, we attempted to investigate the association fiber tracts related to Broca’s area using both diffusion spectrum imaging (DSI) and postmortem fiber dissection. DSI was performed on 10 healthy subjects and an atlas comprising the average data of 842 healthy subjects from the Human Connectome Project. Fiber dissection was implemented in 10 cerebral hemispheres of cadaver donors. The following five association fiber tracts related to Broca’s area were identified: first, the distinct fasciculus of the inferior fronto-occipital fasciculus (IFOF), from Broca’s area (BA44, BA45) and pars orbitalis (BA47) to the parietal and occipital lobes; second, the ventral superior longitudinal fasciculus (SLF-III), from the supramarginal gyrus (BA40) to the ventral precentral gyrus (PreG, BA6) and posterior Broca’s area (BA44); third, the arcuate fascicle (AF), from the superior, middle, and inferior temporal gyrus (BA20, BA21, BA22) to Broca’s area (BA44, BA45) and ventral PreG; fourth, the frontal aslant tract (FAT), from Broca’s area (BA44, BA45) to the lateral superior frontal gyrus (SFG), medial SFG, and supplementary motor area (BA6, BA8, BA9); and fifth, the frontal longitudinal fasciculus (FLF), a novel intralobar frontal association fiber tract, from the anterior part of the middle frontal gyrus (MFG, BA46) and Broca’s area (BA45) to the caudal MFG (BA8), caudal SFG, and dorsal PreG (BA6). Moreover, compared with the left FAT, the right FAT covered almost the entire inferior frontal gyrus (BA44, BA45, BA47). The cross validation between DSI and fiber dissection revealed a good consistence in the association fiber tracts of Broca’s area. Combining DSI and fiber dissection, this study first identified five association fiber tracts related to Broca’s area and characterized their structure and anatomy comprehensively. The frameworks provided key elements for functional research in Broca’s area.

Decoding psychosis: from national genome project to national brain project

The mind has puzzled humans for centuries, and its disorders, such as psychoses, have caused tremendous difficulties. However, relatively recent biotechnological breakthroughs, such as DNA technology and neuroimaging, have empowered scientists to explore the more fundamental aspects of psychosis. From searching for psychosis-causing genes to imaging the depths of the brain, scientists worldwide seek novel methods to understand the mind and the causes of its disorders. This article will briefly review the history of understanding and managing psychosis and the main findings of modern genetic research and then attempt to stimulate thought for decoding the biological mechanisms of psychosis in the present era of brain science.

Using tissue microstructure and multimodal MRI to parse the phenotypic heterogeneity and cellular basis of autism spectrum disorder

BACKGROUND

Identifying the brain bases for phenotypic heterogeneity in Autism Spectrum Disorder (ASD) will advance understanding of its pathogenesis and improve its clinical management.

METHODS

We compared Diffusion Tensor Imaging (DTI) indices and connectome measures between 77 ASD and 88 Typically Developing (TD) control participants. We also assessed voxel-wise associations of DTI indices with measures of regional cerebral blood flow (rCBF) and N-acetylaspartate (NAA) to understand how tissue microstructure associates with cellular metabolism and neuronal density, respectively.

RESULTS

Autism Spectrum Disorder participants had significantly lower fractional anisotropy (FA) and higher diffusivity values in deep white matter tracts, likely representing ether reduced myelination by oligodendrocytes or a reduced density of myelinated axons. Greater abnormalities in these measures and regions were associated with higher ASD symptom scores. Participant age, sex and IQ significantly moderated these group differences. Path analyses showed that reduced NAA levels accounted significantly for higher diffusivity and higher rCBF values in ASD compared with TD participants.

CONCLUSIONS

Reduced neuronal density (reduced NAA) likely underlies abnormalities in DTI indices of white matter microstructure in ASD, which in turn are major determinants of elevated blood flow. Together, these findings suggest the presence of reduced axonal density and axonal pathology in ASD white matter. Greater pathology in turn accounts for more severe symptoms, lower intellectual ability, and reduced global efficiency for measures of white matter connectivity in ASD.

Combined [18F]FDG-PET with MRI structural patterns in predicting post-surgical seizure outcomes in temporal lobe epilepsy patients

OBJECTIVES

To integrate the glucose metabolism measured using [¹⁸F]FDG PET/CT and anatomical features measured using MRI to forecast the post-surgical seizure outcomes of intractable temporal lobe epilepsy.

METHODS

This retrospective study enrolled 63 patients with drug-resistant temporal lobe epilepsy. Z-transform of the patients' PET images based on comparison with a database of healthy controls, cortical thickness, and quantitative anisotropy (QA) of the diffusion spectrum imaging concordant/non-concordant with cortical resection was adopted to quantify their predictive values for the post-surgical seizure outcomes.

RESULTS

The PET hypometabolism region was concordant with the surgical field in 47 of the 63 patients. Forty-two patients were seizure-free post-surgery. The sensitivity and specificity of PET in predicting seizure freedom were 89.4% and 68.8%, respectively. Complete resection of foci with overlapped PET, cortical thickness, and QA abnormalities resulted in Engel I in 27 patients, which was a good predictor of seizure freedom with an odds ratio (OR) of 19.57 (95% CI 2.38-161.25, p = 0.006). Hypometabolism involved in multiple lobes (OR = 7.18, 95% CI 1.02-50.75, p = 0.048) and foci of hypometabolism with QA/cortical thickness abnormalities outside surgical field (OR = 14.72, 95% CI 2.13-101.56, p = 0.006) were two major predictors of Engel III/IV outcomes. ORs of QA to predict Engel I and seizure recurrence were 14.64 (95% CI 2.90-73.80, p = 0.001) and 12.01 (95% CI 2.91-49.65, p = 0.001), respectively.

CONCLUSION

Combined PET and structural pattern is helpful to predict the post-surgical seizure outcomes and worse outcomes of Engel III/IV. This might decrease unnecessary surgical injuries to patients who are potentially not amenable to surgery.

KEY POINTS

• A combined metabolic and structural pattern is helpful to predict the post-surgical seizure outcomes. • Favorable post-surgical seizure outcome was most likely reached in patients whose hypometabolism overlapped with the structural changes. • Hypometabolism in multiple lobes and QA or cortical thickness abnormalities outside the surgical field were predictors of worse seizure outcomes of Engel III/IV.

Automation of Cranial Nerve Tractography by Filtering Tractograms for Skull Base Surgery

Fiber tractography enables the in vivo reconstruction of white matter fibers in 3 dimensions using data collected by diffusion tensor imaging, thereby helping to understand functional neuroanatomy. In a pre-operative context, it provides essential information on the trajectory of fiber bundles of medical interest, such as cranial nerves. However, the optimization of tractography parameters is a time-consuming process and requires expert neuroanatomical knowledge, making the use of tractography difficult in clinical routine. Tractogram filtering is a method used to isolate the most relevant fibers. In this work, we propose to use filtering as a post-processing of tractography to avoid the manual optimization of tracking parameters and therefore making a step forward automation of tractography. To question the feasibility of automated tractography of cranial nerves, we perform an analysis of main cranial nerves on a series of patients with skull base tumors. A quantitative evaluation of the filtering performance of two state-of-the-art and a new entropy-based methods is carried out on the basis of reference tractograms produced by experts. Our approach proves to be more stable in the selection of the optimal filtering threshold and turns out to be interesting in terms of computational time complexity.

Automatic oculomotor nerve identification based on data‐driven fiber clustering

The oculomotor nerve (OCN) is the main motor nerve innervating eye muscles and can be involved in multiple flammatory, compressive, or pathologies. The diffusion magnetic resonance imaging (dMRI) tractography is now widely used to describe the trajectory of the OCN. However, the complex cranial structure leads to difficulties in fiber orientation distribution (FOD) modeling, fiber tracking, and region of interest (ROI) selection. Currently, the identification of OCN relies on expert manual operation, resulting in challenges, such as the carries high clinical, time‐consuming, and labor costs. Thus, we propose a method that can automatically identify OCN from dMRI tractography. First, we choose the multi‐shell multi‐tissue constraint spherical deconvolution (MSMT‐CSD) FOD estimation model and deterministic tractography to describe the 3D trajectory of the OCN. Then, we rely on the well‐established computational pipeline and anatomical expertise to create a data‐driven OCN tractography atlas from 40 HCP data. We identify six clusters belonging to the OCN from the atlas, including the structures of three kinds of positional relationships (pass between, pass through, and go around) with the red nuclei and two kinds of positional relationships with medial longitudinal fasciculus. Finally, we apply the proposed OCN atlas to identify the OCN automatically from 40 new HCP subjects and two patients with brainstem cavernous malformation. In terms of spatial overlap and visualization, experiment results show that the automatically and manually identified OCN fibers are consistent. Our proposed OCN atlas provides an effective tool for identifying OCN by avoiding the traditional selection strategy of ROIs.

Trigeminal Nerve White Matter Fiber Abnormalities in Primary Trigeminal Neuralgia: A Diffusion Spectrum Imaging Study

OBJECTIVE

Diffusion spectrum imaging (DSI) was used to quantitatively study the changes in the trigeminal cistern segment in patients with trigeminal neuralgia (TN) and to further explore the value of acquiring DSI data from patients with TN.

METHODS

To achieve high-resolution fiber tracking, 60 patients with TN and 35 healthy controls (HCs) were scanned with conventional magnetic resonance imaging (MRI) and DSI. The patients and the members of the control group were compared within and between groups. The correlations between quantitative parameters of DSI and the visual analog scale (VAS), and symptom duration and responsible vessel types were analyzed.

RESULTS

Compared with unaffected side of patients in the TN group, the affected side showed significantly decreased quantitative anisotropy (QA) (p < 0.001), fractional anisotropy (FA) (p = 0.001), and general FA (GFA) (p < 0.001). The unaffected side exhibited significantly decreased QA (p + 0.001), FA (p = 0.001), and GFA (p < 0.001) and significantly increased axial diffusivity (AD) (p = 0.036) compared with the affected side of patients in the TN group and the average values of HCs. There were significantly decreased QA (p = 0.046) and FA (p = 0.008) between the unaffected side of patients and the average values of HCs. GFA can evidently distinguish arteries, veins, and features of unaffected side in TN patients.

CONCLUSION

Using high-resolution fiber tracking technology, DSI can provide quantitative information that can be used to detect the integrity of trigeminal white matter in patients with TN and can improve the understanding of the disease mechanism.

The trajectory of the medial longitudinal fasciculus in the human brain: A diffusion imaging-based tractography study

The aim of this study is to investigate the trajectory of medial longitudinal fasciculus (MLF) and explore its anatomical relationship with the oculomotor nerve using tractography technique. The MLF and oculomotor nerve were reconstructed at the same time with preset three region of interests (ROIs): one set at the area of rostral midbrain, one placed on the MLF area at the upper pons, and one placed at the cisternal part of the oculomotor nerve. This mapping protocol was tested in an HCP‐1065 template, 35 health subjects from Massachusetts General Hospital (MGH), 20 healthy adults and 6 brainstem cavernous malformation (BCM) patients with generalized q‐sampling imaging (GQI)‐based tractography. Finally, the 200 μm brainstem template from Center for In Vivo Microscopy, Duke University (Duke CIVM), was used to validate the trajectory of reconstructed MLF. The MLF and oculomotor nerve were reconstructed in the HCP‐1065 template, 35 MGH health subjects, 20 healthy adults and 6 BCM patients. The MLF was in conjunction with the ipsilateral mesencephalic part of the oculomotor nerve. The displacement of MLF was identified in all BCM patients. Decreased QA, RDI and FA were found in the MLF of lesion side, indicating axonal loss and/or edema of displaced MLF. The reconstructed MLF in Duke CIVM brainstem 200 μm template corresponded well with histological anatomy. The MLF and oculomotor nerve were visualized accurately with our protocol using GQI‐based fiber tracking. This GQI‐based tractography is an important tool in the reconstruction and evaluation of MLF.

Automated facial-vestibulocochlear nerve complex identification based on data-driven tractography clustering

Small size and intricate anatomical environment are the main difficulties facing tractography of the facial-vestibulocochlear nerve complex (FVN), and lead to challenges in fiber orientation distribution (FOD) modeling, fiber tracking, region-of-interest selection, and fiber filtering. Experts need rich experience in anatomy and tractography, as well as substantial labor costs, to identify the FVN. Thus, we present a pipeline to identify the FVN automatically, in what we believe is the first study of the automated identification of the FVN. First, we created an FVN template. Forty high-resolution multishell data were used to perform data-driven fiber clustering based on the multishell multitissue constraint spherical deconvolution FOD model and deterministic tractography. We selected the brainstem and cerebellum (BS-CB) region as the seed region and removed the fibers that reach other brain regions. We then performed spectral fiber clustering twice. The first clustering was to create a BS-CB atlas and separate the fibers that pass through the cerebellopontine angle, and the other one was to extract the FVN. Second, we registered the subject-specific fibers in the space of the FVN template and assigned each fiber to the closest cluster to identify the FVN automatically by spectral embedding. We applied the proposed method to different acquirement sites, including two different healthy datasets and two tumor patient datasets. Experimental results showed that our automatic identification results have ideal colocalization with expert manual identification in terms of spatial overlap and visualization. Importantly, we successfully applied our method to tumor patient data. The FVNs identified by the proposed method were in agreement with intraoperative findings.

Correlation between Cranial Nerve Microstructural Characteristics and Vestibular Schwannoma Tumor Volume

BACKGROUND AND PURPOSE

Vestibular schwannomas are common cerebellopontine angle tumors arising from the vestibulocochlear nerve and can result in cranial nerve dysfunction. Conventional MR imaging does not provide information that could correlate with cranial nerve compression symptoms of hearing loss or imbalance. We used multitensor tractography to evaluate the relationship between the WM microstructural properties of cranial nerves and tumor volume in a cohort of patients with vestibular schwannomas.

MATERIALS AND METHODS

A retrospective study was performed in 258 patients with vestibular schwannomas treated at the Gamma Knife clinic at Toronto Western Hospital between 2014 and 2018. 3T MR images were analyzed in 160 surgically naïve patients with unilateral vestibular schwannomas. Multitensor tractography was used to extract DTI-derived metrics (fractional anisotropy and radial, axial, and mean diffusivities of the bilateral facial and vestibulocochlear nerves [cranial nerves VII/VIII]). ROIs were placed in the transition between cisternal and intracanalicular segments, and images were analyzed using the eXtended Streamline Tractography reconstruction method. Diffusion metrics were correlated with 3D tumor volume derived from the Gamma Knife clinic.

RESULTS

DTI analyses revealed significantly higher fractional anisotropy values and a reduction in axial diffusivity, radial diffusivity, and mean diffusivity (all P < .001) within the affected cranial nerves VII and VIII compared with unaffected side. All specific diffusivities (axial, radial, and mean diffusivity) demonstrated an inverse correlation with tumor volume (axial, radial, and mean diffusivity, P < .01).

CONCLUSIONS

Multitensor tractography allows the quantification of cranial nerve VII and VIII WM microstructural alterations in patients with vestibular schwannomas. Our findings support the hypothesis that tumor volume may cause microstructural alterations of the affected cranial nerves VII and VIII. This type of advanced imaging may represent a possible avenue to correlate diffusivities with cranial nerve function.

Radiofrequency thermocoagulation of trigeminal nerve assisted by nerve bundle extraction and image fusion based on hamilton-jacobi equation

BACKGROUND AND OBJECTIVE

Radiofrequency thermocoagulation is an effective method for treating classic trigeminal neuralgia. However, the accurate positioning of thermocoagulation is difficult. The purpose of this study was to design an optimal strategy for performing adjuvant surgery.

METHODS

A total of 60 patients with trigeminal neuralgia were divided into two groups. One group received conventional computed tomography (CT) guided treatment (CT group). In the other group, neural fiber bundles were firstly extracted based on the Hamilton-Jacobi equation. Then, the MRI, CT, and fiber bundle images were fused to visualize the relationship among semilunar ganglion, trigeminal nerve, and puncture needle (fusion group).

RESULTS

Trigeminal fiber bundles were extracted quickly by the contour tracking method, and different types of image fusion were realized for radiofrequency surgery navigation. In the fusion group, 13.3% of patients could not reach semilunar ganglion, and 76.9% of the remaining cases reached the ideal damage area. In the CT group, the preoperative design shows that 26.7% of patients may have puncture difficulty, and 54.5% of remaining cases reached the ideal damage area.

CONCLUSION

The technique of neural bundle extraction and image fusion based on the Hamilton-Jacobi equation can be used to plan the personalized puncture path targeting the semilunar ganglion.

A high-resolution interactive atlas of the human brainstem using magnetic resonance imaging

Conventional atlases of the human brainstem are limited by the inflexible, sparsely-sampled, two-dimensional nature of histology, or the low spatial resolution of conventional magnetic resonance imaging (MRI). Postmortem high-resolution MRI circumvents the challenges associated with both modalities. A single human brainstem specimen extending from the rostral diencephalon through the caudal medulla was prepared for imaging after the brain was removed from a 65-year-old male within 24 h of death. The specimen was formalin-fixed for two weeks, then rehydrated and placed in a custom-made MRI compatible tube and immersed in liquid fluorocarbon. MRI was performed in a 7-Tesla scanner with 120 unique diffusion directions. Acquisition time for anatomic and diffusion images were 14 h and 208 h, respectively. Segmentation was performed manually. Deterministic fiber tractography was done using strategically chosen regions of interest and avoidance, with manual editing using expert knowledge of human neuroanatomy. Anatomic and diffusion images were rendered with isotropic resolutions of 50 μm and 200 μm, respectively. Ninety different structures were segmented and labeled, and 11 different fiber bundles were rendered with tractography. The complete atlas is available online for interactive use at https://www.civmvoxport.vm.duke.edu/voxbase/login.php?return_url=%2Fvoxbase%2F. This atlas presents multiple contrasting datasets and selected tract reconstruction with unprecedented resolution for MR imaging of the human brainstem. There are immediate applications in neuroanatomical education, with the potential to serve future applications for neuroanatomical research and enhanced neurosurgical planning through "safe" zones of entry into the human brainstem.

Comparison of multiple tractography methods for reconstruction of the retinogeniculate visual pathway using diffusion MRI

The retinogeniculate visual pathway (RGVP) conveys visual information from the retina to the lateral geniculate nucleus. The RGVP has four subdivisions, including two decussating and two nondecussating pathways that cannot be identified on conventional structural magnetic resonance imaging (MRI). Diffusion MRI tractography has the potential to trace these subdivisions and is increasingly used to study the RGVP. However, it is not yet known which fiber tracking strategy is most suitable for RGVP reconstruction. In this study, four tractography methods are compared, including constrained spherical deconvolution (CSD) based probabilistic (iFOD1) and deterministic (SD-Stream) methods, and multi-fiber (UKF-2T) and single-fiber (UKF-1T) unscented Kalman filter (UKF) methods. Experiments use diffusion MRI data from 57 subjects in the Human Connectome Project. The RGVP is identified using regions of interest created by two clinical experts. Quantitative anatomical measurements and expert anatomical judgment are used to assess the advantages and limitations of the four tractography methods. Overall, we conclude that UKF-2T and iFOD1 produce the best RGVP reconstruction results. The iFOD1 method can better quantitatively estimate the percentage of decussating fibers, while the UKF-2T method produces reconstructed RGVPs that are judged to better correspond to the known anatomy and have the highest spatial overlap across subjects. Overall, we find that it is challenging for current tractography methods to both accurately track RGVP fibers that correspond to known anatomy and produce an approximately correct percentage of decussating fibers. We suggest that future algorithm development for RGVP tractography should take consideration of both of these two points.

Three-dimensional (3D) Printed Vestibular Schwannoma for Facial Nerve Tractography Validation

OBJECTIVES

Predicting the course of cranial nerve (CN) VII in the cerebellopontine angle (CPA) on preoperative imaging for vestibular schwannoma (VS) may help guide surgical resection and reduce complications. Diffusion MRI based tractography has been used to identify cranial nerve trajectory, but intraoperative validation of this novel approach is challenging. Currently, validation is based on operative report descriptions of the course of cranial nerves, but yields a simplified picture of the three-dimensional (3D) course of CN VII. In this study, we investigate the accuracy of tractography with detailed patient-specific 3D-printed VS tumors.

DESIGN

Retrospective case review.

SETTING

Tertiary referral center.

PARTICIPANTS

Twenty adult VS surgical candidates.

MAIN OUTCOME MEASURES

We compared tractography with intraoperative 3D course of CN VII. The surgeons were blinded to tractography and drew the intraoperative course of the CN VII on a patient specific 3D-printed tumor model for detailed comparison with tractography.

RESULTS

Of 20 patients, one was excluded due to subtotal removal and inability to assess CN VII course. In the remaining 19 patients, 84% (16/19) tractography was successful. In 94% of tumors with tractography (15/16), the intraoperative description of CN VII course matched the tractography finding. The maximum distance, however, between tractography and intraoperative course of CN VII was 3.7 mm ± 4.2 mm.

CONCLUSION

This study presents a novel approach to CN VII tractography validation in VS. Although descriptions of CN VII intraoperatively match tractography, caution is warranted as quantitative measures suggest a clinically significant distance between tractography and CN VII course.

Quantitative visual pathway abnormalities predict visual field defects in patients with pituitary adenomas: a diffusion spectrum imaging study

OBJECTIVES

This study was to investigate clinical applicability of diffusion spectrum imaging (DSI) for quantitative detection of visual pathway abnormalities to predict the degree of visual field defects (VFD) in patients with pituitary adenomas.

METHODS

Sixty-five patients with pituitary adenomas and 33 healthy controls underwent conventional MRI and DSI scanning that allowed high-angular-resolution fiber tracking. Optic chiasmal compression and VFD were confirmed in all patients via radiological and neuro-ophthalmological examinations. Quantitative assessments of chiasmal lift, VFD, and DSI parameters from the optic nerve, optic tract, and optic radiation were performed. Group comparisons and correlation analyses were conducted in patients and controls. Using the 5-fold cross-validation method, the support vector machine classifiers were constructed to predict the degree of visual defects.

RESULTS

The mean values of quantitative anisotropy and generalized fractional anisotropy in optic nerve and optic tract showed significant differences between patients and controls (p < 0.05). These parameters were also significantly correlated with the chiasmal lift distance and degree of visual defects (p < 0.05). All patients were divided into mild (n = 42) and severe (n = 23) VFD groups, using the mean deviation value of -8 dB as the threshold. The classifiers achieved an accuracy of 0.83, sensitivity of 0.78, and specificity of 0.86 to discriminate patients with mild and severe visual defects.

CONCLUSIONS

Using high-angular-resolution fiber tracking, DSI may provide quantitative information to detect visual pathway abnormalities and be a potential diagnostic tool for determining the degree of visual field defects in pituitary adenomas.

KEY POINTS

• Abnormal QA and GFA values of optic nerve and optic tract in adenoma patients • Close relationship between DSI parameters and VFD degree in adenoma patients • The classifiers achieved an accuracy of 0.83, sensitivity of 0.78, and specificity of 0.86 to discriminate patients with mild and severe VFD.

Reliability of Preoperative Prediction of the Location of the Facial Nerve Using Diffusion Tensor Imaging-Fiber Tracking in Vestibular Schwannoma: A Systematic Review and Meta-Analysis

The popularization and application of microscopy, the in-depth study of the microanatomy of the cerebellopontine angle, and the application of intraoperative electrophysiological monitoring technology to preserve facial nerve function have laid a solid foundation for the modern era of neurosurgery. The preoperative prediction of the location of the facial nerve is a long-desired goal of neurosurgeons. The advances in neuroimaging seem to be making this goal a reality. Many studies investigating the reliability of the preoperative prediction of the location of the facial nerve using diffusion tensor imaging-fiber tracking in vestibular schwannoma have been reported in the last 20 years. The PubMed, Embase, and Cochrane databases were searched for articles published before March 30, 2020. A comprehensive review of published studies was carried out in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Authors performed a systematic review and meta-analysis of the reported data to assess the reliability of the preoperative prediction of the location of the facial nerve using diffusion tensor imaging-fiber tracking in vestibular schwannoma. The data were analyzed using a fixed-effects model. The estimated overall intraoperative verification concordance rate was 89.05% (95% confidence interval 85.06%-92.58%). Preoperatively predicting the location of the facial nerve using diffusion tensor imaging-fiber tracking in vestibular schwannoma is reliable, but the extent to which it contributes to long-term facial nerve function is still unclear. To further verify these results, studies with larger sample sizes are needed in the future, especially prospective randomized controlled trials focusing on the long-term functional preservation of the facial nerve.

Creation of a novel trigeminal tractography atlas for automated trigeminal nerve identification

Diffusion MRI (dMRI) tractography has been successfully used to study the trigeminal nerves (TGNs) in many clinical and research applications. Currently, identification of the TGN in tractography data requires expert nerve selection using manually drawn regions of interest (ROIs), which is prone to inter-observer variability, time-consuming and carries high clinical and labor costs. To overcome these issues, we propose to create a novel anatomically curated TGN tractography atlas that enables automated identification of the TGN from dMRI tractography. In this paper, we first illustrate the creation of a trigeminal tractography atlas. Leveraging a well-established computational pipeline and expert neuroanatomical knowledge, we generate a data-driven TGN fiber clustering atlas using tractography data from 50 subjects from the Human Connectome Project. Then, we demonstrate the application of the proposed atlas for automated TGN identification in new subjects, without relying on expert ROI placement. Quantitative and visual experiments are performed with comparison to expert TGN identification using dMRI data from two different acquisition sites. We show highly comparable results between the automatically and manually identified TGNs in terms of spatial overlap and visualization, while our proposed method has several advantages. First, our method performs automated TGN identification, and thus it provides an efficient tool to reduce expert labor costs and inter-operator bias relative to expert manual selection. Second, our method is robust to potential imaging artifacts and/or noise that can prevent successful manual ROI placement for TGN selection and hence yields a higher successful TGN identification rate.

Endoscopic Endonasal Petrosectomy: Anatomical Investigation, Limitations, and Surgical Relevance

BACKGROUND

The endoscopic endonasal approach (EEA) was recently added to the neurosurgical armamentarium as an alternative approach to the petrous apex (PA) region. However, the maximal extension, anatomical landmarks, and indications of this procedure remain to be established.

OBJECTIVE

To investigate the limitations and suggest a classification of PA lesions for endoscopic petrosectomy.

METHODS

Five anatomical specimens were dissected with EEA to the PA. Anatomical landmarks for the surgical steps and maximal limits were noted. Pre- and postprocedural computed tomographic scan and image-guidance were used. Relevant surgical cases were reviewed and presented.

RESULTS

We defined 3 types of petrosectomy: medial, inferior, and inferomedial. Medial petrosectomy was limited within the paraclival internal carotid artery (ICA) anteriorly, lacerum ICA inferiorly, abducens nerve superiorly, and petrous ICA laterally. Among those, abducens nerve and petrous ICA are surgical limits. Full skeletonization of the paraclival ICA and removal of the lingual process are essential for better access to the medial aspect of PA. Inferior petrosectomy was defined by the lacerum foramen synchondrosis anteriorly, jugular foramen inferiorly, internal acoustic canal posteriorly, and PA superolaterally. Those are surgical limits except for the foramen lacerum synchondrosis. The connective tissue at the pterygosphenoidal fissure was a key landmark for the sublacerum approach. Clinical cases in 3 types of PA lesions were presented.

CONCLUSION

The EEA provides access to the medial and inferior aspects of the PA. Several technical maneuvers, including paraclival and lacerum ICA skeletonization, sublacerum approach, and lingual process removal, are key to maximize PA drilling.

Prediction of trigeminal nerve position based on the main feeding artery in petroclival meningioma

The trigeminal nerve is often displaced by petroclival meningioma (PCM) compression, making it difficult to locate during PCM surgery. This study investigated whether the deviated position of the trigeminal nerve could be easily predicted using the main tumor feeding artery. We retrospectively examined 32 patients who underwent surgery for primary PCM. The deviation of the trigeminal nerve was classified as either Type 1 (displacement toward the back of the cerebellar tentorium), Type 2 (toward the back of the superior petrosal sinus), Type 3 (toward the back of the petrous apex dura), Type 4 (toward the inferior aspect of the tumor), or Type 5 (toward the surface of the brain stem). The main feeding artery was determined by preoperative angiography. The trigeminal nerve was classified as Type 2 in 60% of cases where the proximal tentorial artery (TA) was the main feeding vessel. The nerve was Type 5 where the distal portion of the TA was the main feeding vessel (60% of the cases). The nerves were Type 3 and Type 4 where the proximal inferior lateral trunk (ILT) (60%) and distal ILT (75%), respectively, were the main feeding vessels. In 66.7% of the cases where the dorsal meningeal artery was the main feeding vessel, the nerve was Type 3. Type 1 classification applied in all cases where the ascending pharyngeal artery was the main feeding artery. The main feeding artery can be used to predict trigeminal nerve transposition during PCM surgery.

Full tractography for detecting the position of cranial nerves in preoperative planning for skull base surgery: technical note

OBJECTIVE

Diffusion imaging tractography has allowed the in vivo description of brain white matter. One of its applications is preoperative planning for brain tumor resection. Due to a limited spatial and angular resolution, it is difficult for fiber tracking to delineate fiber crossing areas and small-scale structures, in particular brainstem tracts and cranial nerves. New methods are being developed but these involve extensive multistep tractography pipelines including the patient-specific design of multiple regions of interest (ROIs). The authors propose a new practical full tractography method that could be implemented in routine presurgical planning for skull base surgery.

METHODS

A Philips MRI machine provided diffusion-weighted and anatomical sequences for 2 healthy volunteers and 2 skull base tumor patients. Tractography of the full brainstem, the cerebellum, and cranial nerves was performed using the software DSI Studio, generalized-q-sampling reconstruction, orientation distribution function (ODF) of fibers, and a quantitative anisotropy-based generalized deterministic algorithm. No ROI or extensive manual filtering of spurious fibers was used. Tractography rendering was displayed in a tridimensional space with directional color code. This approach was also tested on diffusion data from the Human Connectome Project (HCP) database.

RESULTS

The brainstem, the cerebellum, and the cisternal segments of most cranial nerves were depicted in all participants. In cases of skull base tumors, the tridimensional rendering permitted the visualization of the whole anatomical environment and cranial nerve displacement, thus helping the surgical strategy.

CONCLUSIONS

As opposed to classical ROI-based methods, this novel full tractography approach could enable routine enhanced surgical planning or brain imaging for skull base tumors.

Tractography in Neurosurgery: A Systematic Review of Current Applications

The ability to visualize the brain's fiber connections noninvasively in vivo is relatively young compared with other possibilities of functional magnetic resonance imaging. Although many studies showed tractography to be of promising value for neurosurgical care, the implications remain inconclusive. An overview of current applications is presented in this systematic review. A search was conducted for (("tractography" or "fiber tracking" or "fibre tracking") and "neurosurgery") that produced 751 results. We identified 260 relevant articles and added 20 more from other sources. Most publications concerned surgical planning for resection of tumors (n = 193) and vascular lesions (n = 15). Preoperative use of transcranial magnetic stimulation was discussed in 22 of these articles. Tractography in skull base surgery presents a special challenge (n = 29). Fewer publications evaluated traumatic brain injury (TBI) (n = 25) and spontaneous intracranial bleeding (n = 22). Twenty-three articles focused on tractography in pediatric neurosurgery. Most authors found tractography to be a valuable addition in neurosurgical care. The accuracy of the technique has increased over time. There are articles suggesting that tractography improves patient outcome after tumor resection. However, no reliable biomarkers have yet been described. The better rehabilitation potential after TBI and spontaneous intracranial bleeding compared with brain tumors offers an insight into the process of neurorehabilitation. Tractography and diffusion measurements in some studies showed a correlation with patient outcome that might help uncover the neuroanatomical principles of rehabilitation itself. Alternative corticofugal and cortico-cortical networks have been implicated in motor recovery after ischemic stroke, suggesting more complex mechanisms in neurorehabilitation that go beyond current models. Hence tractography may potentially be able to predict clinical deficits and rehabilitation potential, as well as finding possible explanations for neurologic disorders in retrospect. However, large variations of the results indicate a lack of data to establish robust diagnostical concepts at this point. Therefore, in vivo tractography should still be interpreted with caution and by experienced surgeons.

Identifying and characterizing projections from the subthalamic nucleus to the cerebellum in humans

A connection between the subthalamic nucleus (STN) and the cerebellum which has been shown to exist in non-human primates, was recently identified in humans. However, its anatomical features, network properties and function have yet to be elucidated in humans. In the present study, we quantified the STN-cerebellum pathway in humans and explored its function based on structural observations. Anatomical features and asymmetry index (AI) were explored using high definition fiber tractography data of 30 individuals from the Massachusetts General Hospital - Human Connectome Project adult diffusion database. Pearson's correlation analysis was performed to determine the interrelationship between the subdivisions of the STN-cerebellum and the global cortical-STN connections. The pathway was visualized bilaterally in all the subjects. Typically, after setting out from the STN, the STN-cerebellum projections incorporated into the nearby corticopontine tracts, passing through the cerebral peduncle, mediated by the pontine nucleus and then connecting in two opposite directions to join the bilateral middle cerebellar peduncle. On the group averaged level, 78.03% and 62.54% of fibers from the right and left STN respectively, distributed to Crus I in the cerebellum, part of the remaining fibers projected to Crus II, with most of the fibers crossing contralaterally. According to the AI evaluation, 60% of the participants were right STN dominant, 23% were left STN dominant, and 17% were relatively symmetric. Pearson's correlation analysis further indicated that the number of pathways from mesial Brodmann area 8 to the STN (hyperdirect pathway associated with decision making) was positively correlated with the number of fibers from the right STN to Crus I. The insertion and termination, the right-side dominance, and the positive correlation with the hyperdirect pathway all suggest that the STN-cerebellum pathway might be involved in decision-making processes.

Anatomical assessment of trigeminal nerve tractography using diffusion MRI: A comparison of acquisition b-values and single- and multi-fiber tracking strategies

BACKGROUND

The trigeminal nerve (TGN) is the largest cranial nerve and can be involved in multiple inflammatory, compressive, ischemic or other pathologies. Currently, imaging-based approaches to identify the TGN mostly rely on T2-weighted magnetic resonance imaging (MRI), which provides localization of the cisternal portion of the TGN where the contrast between nerve and cerebrospinal fluid (CSF) is high enough to allow differentiation. The course of the TGN within the brainstem as well as anterior to the cisternal portion, however, is more difficult to display on traditional imaging sequences. An advanced imaging technique, diffusion MRI (dMRI), enables tracking of the trajectory of TGN fibers and has the potential to visualize anatomical regions of the TGN not seen on T2-weighted imaging. This may allow a more comprehensive assessment of the nerve in the context of pathology. To date, most work in TGN tracking has used clinical dMRI acquisitions with a b-value of 1000 s/mm2 and conventional diffusion tensor MRI (DTI) tractography methods. Though higher b-value acquisitions and multi-tensor tractography methods are known to be beneficial for tracking brain white matter fiber tracts, there have been no studies conducted to evaluate the performance of these advanced approaches on nerve tracking of the TGN, in particular on tracking different anatomical regions of the TGN.

OBJECTIVE

We compare TGN tracking performance using dMRI data with different b-values, in combination with both single- and multi-tensor tractography methods. Our goal is to assess the advantages and limitations of these different strategies for identifying the anatomical regions of the TGN.

METHODS

We proposed seven anatomical rating criteria including true and false positive structures, and we performed an expert rating study of over 1000 TGN visualizations, as follows. We tracked the TGN using high-quality dMRI data from 100 healthy adult subjects from the Human Connectome Project (HCP). TGN tracking performance was compared across dMRI acquisitions with b = 1000 s/mm2, b = 2000 s/mm2 and b = 3000 s/mm2, using single-tensor (1T) and two-tensor (2T) unscented Kalman filter (UKF) tractography. This resulted in a total of six tracking strategies. The TGN was identified using an anatomical region-of-interest (ROI) selection approach. First, in a subset of the dataset we identified ROIs that provided good TGN tracking performance across all tracking strategies. Using these ROIs, the TGN was then tracked in all subjects using the six tracking strategies. An expert rater (GX) visually assessed and scored each TGN based on seven anatomical judgment criteria. These criteria included the presence of multiple expected anatomical segments of the TGN (true positive structures), specifically branch-like structures, cisternal portion, mesencephalic trigeminal tract, and spinal cord tract of the TGN. False positive criteria included the presence of any fibers entering the temporal lobe, the inferior cerebellar peduncle, or the middle cerebellar peduncle. Expert rating scores were analyzed to compare TGN tracking performance across the six tracking strategies. Intra- and inter-rater validation was performed to assess the reliability of the expert TGN rating result.

RESULTS

The TGN was selected using two anatomical ROIs (Meckel's Cave and cisternal portion of the TGN). The two-tensor tractography method had significantly better performance on identifying true positive structures, while generating more false positive streamlines in comparison to the single-tensor tractography method. TGN tracking performance was significantly different across the three b-values for almost all structures studied. Tracking performance was reported in terms of the percentage of subjects achieving each anatomical rating criterion. Tracking of the cisternal portion and branching structure of the TGN was generally successful, with the highest performance of over 98% using two-tensor tractography and b = 1000 or b = 2000. However, tracking the smaller mesencephalic and spinal cord tracts of the TGN was quite challenging (highest performance of 37.5% and 57.07%, using two-tensor tractography with b = 1000 and b = 2000, respectively). False positive connections to the temporal lobe (over 38% of subjects for all strategies) and cerebellar peduncles (100% of subjects for all strategies) were prevalent. High joint probability of agreement was obtained in the inter-rater (on average 83%) and intra-rater validation (on average 90%), showing a highly reliable expert rating result.

CONCLUSIONS

Overall, the results of the study suggest that researchers and clinicians may benefit from tailoring their acquisition and tracking methodology to the specific anatomical portion of the TGN that is of the greatest interest. For example, tracking of branching structures and TGN-T2 overlap can be best achieved with a two-tensor model and an acquisition using b = 1000 or b = 2000. In general, b = 1000 and b = 2000 acquisitions provided the best-rated tracking results. Further research is needed to improve both sensitivity and specificity of the depiction of the TGN anatomy using dMRI.

Projections of Brodmann Area 6 to the Pyramidal Tract in Humans: Quantifications Using High Angular Resolution Data

Primate studies indicate that the pyramidal tract (PyT) could originate from Brodmann area (BA) 6. However, in humans, the accurate origin of PyT from BA 6 is still uncertain owing to difficulties in visualizing anatomical features such as the fanning shape at the corona radiata and multiple crossings at the semioval centrum. High angular-resolution diffusion imaging (HARDI) could reliably replicate these anatomical features. We explored the origin of the human PyT from BA 6 using HARDI. With HARDI data of 30 adults from the Massachusetts General Hospital-Human Connectome Project (MGH-HCP) database and the HCP 1021 template (average of 1021 HCP diffusion data), we visualized the PyT at the 30-averaged group level and the 1021 large-sample level and validated the observations in each of the individuals. Endpoints of the fibers within each subregion were quantified. PyT fibers originating from the BA 6 were consistently visualized in all images. Specifically, the bilateral supplementary motor area (SMA) and dorsal premotor area (dPMA) were consistently found to contribute to the PyT. PyT fibers from BA 6 and those from BA 4 exhibited a twisting topology. The PyT contains fibers originating from the SMA and dPMA in BA 6. Infarction of these regions or aging would result in incomplete provision of information to the PyT and concomitant decreases in motor planning and coordination abilities.

Differences between generalized Q-sampling imaging and diffusion tensor imaging in visualization of crossing neural fibers in the brain

Purpose

The aim of this study was to discuss the advantages of GQI reconstruction in the imaging of nerve fibers at crossing regions. Compared with DTI, the paper also discussed the advantages of GQI in imaging principles.

Methods

3-T MRI data from five normal participants were reconstructed using GQI and DTI. After adjusting the parameters, we compared the differences in reconstructed nerve fibers at the crossing regions between the two methods. To complete this study, we chose four obvious examples (the optic nerve, the Superior cerebellar peduncles, the intersection of the pyramidal tract, the corpus callosum and the arcuate fibers and the intersection of the supplementary motor area (SMA) and the anterior part of arcuate fasciculus) to illustrate.

Results

By reconstructing nerve fibers in three regions, we can find that crossing-area images of nerve fibers significantly differed between DTI and GQI reconstruction. Although crossing fibers could be clearly and completely visualized after GQI reconstruction, they showed artifacts, incompleteness, deletions, and fractures after DTI reconstruction. After GQI reconstruction, we can find that there were two or more nerve fibers in each voxel. However, only one nerve fiber was present in each voxel after DTI reconstruction.

Conclusion

The imaging of crossing fibers is more complete, consistent, and accurate when they are reconstructed by GQI than when they are reconstructed by DTI.

Super-resolution Diffusion Tensor Imaging for Delineating the Facial Nerve in Patients with Vestibular Schwannoma

Objectives  Predicting the course of cranial nerves (CNs) VII and VIII in the cerebellopontine angle on preoperative imaging for vestibular schwannoma (VS) may help guide surgical resection and reduce complications. Diffusion magnetic resonance imaging dMRI is commonly used for this purpose, but is limited by its resolution. We investigate the use of super-resolution reconstruction (SRR), where several different dMRIs are combined into one dataset. We hypothesize that SRR improves the visualization of the CN VII and VIII. Design  Retrospective case review. Setting  Tertiary referral center. SRR was performed on the basis of axial and parasagittal single-shot epiplanar diffusion tensor imaging on a 3.0-tesla MRI scanner. Participants  Seventeen adult patients with suspected neoplasms of the lateral skull base. Main Outcome Measures  We assessed separability of the two distinct nerves on fractional anisotropy (FA) maps, the tractography of the nerves through the cerebrospinal fluid (CSF), and FA in the CSF as a measure of noise. Results  SRR increases separability of the CN VII and VIII (16/17 vs. 0/17, p  = 0.008). Mean FA of CSF surrounding the nerves is significantly lower in SRRs (0.07 ± 0.02 vs. 0.13 ± 0.03 [axial images]/0.14 ± 0.05 [parasagittal images], p  = 0.00003/ p  = 0.00005). Combined scanning times (parasagittal and axial) used for SRR were shorter (8 minute 25 seconds) than a comparable high-resolution scan (15 minute 17 seconds). Conclusion  SRR improves the resolution of CN VII and VIII. The technique can be readily applied in the clinical setting, improving surgical counseling and planning in patients with VS.

Clinical Applications for Diffusion MRI and Tractography of Cranial Nerves Within the Posterior Fossa: A Systematic Review

Objective: This paper presents a systematic review of diffusion MRI (dMRI) and tractography of cranial nerves within the posterior fossa. We assess the effectiveness of the diffusion imaging methods used and examine their clinical applications. Methods: The Pubmed, Web of Science and EMBASE databases were searched from January 1st 1997 to December 11th 2017 to identify relevant publications. Any study reporting the use of diffusion imaging and/or tractography in patients with confirmed cranial nerve pathology was eligible for selection. Study quality was assessed using the Methodological Index for Non-Randomized Studies (MINORS) tool. Results: We included 41 studies comprising 16 studies of patients with trigeminal neuralgia (TN), 22 studies of patients with a posterior fossa tumor and three studies of patients with other pathologies. Most acquisition protocols used single-shot echo planar imaging (88%) with a single b-value of 1,000 s/mm2 (78%) but there was significant variation in the number of gradient directions, in-plane resolution, and slice thickness between studies. dMRI of the trigeminal nerve generated interpretable data in all cases. Analysis of diffusivity measurements found significantly lower fractional anisotropy (FA) values within the root entry zone of nerves affected by TN and FA values were significantly lower in patients with multiple sclerosis. Diffusivity values within the trigeminal nerve correlate with the effectiveness of surgical treatment and there is some evidence that pre-operative measurements may be predictive of treatment outcome. Fiber tractography was performed in 30 studies (73%). Most studies evaluating fiber tractography involved patients with a vestibular schwannoma (82%) and focused on generating tractography of the facial nerve to assist with surgical planning. Deterministic tractography using diffusion tensor imaging was performed in 93% of cases but the reported success rate and accuracy of generating fiber tracts from the acquired diffusion data varied considerably. Conclusions: dMRI has the potential to inform our understanding of the microstructural changes that occur within the cranial nerves in various pathologies. Cranial nerve tractography is a promising technique but new avenues of using dMRI should be explored to optimize and improve its reliability.

Tractography for Surgical Neuro-Oncology Planning: Towards a Gold Standard

Magnetic resonance imaging tractography permits in vivo visualization of white matter structures. Aside from its academic value, tractography has been proven particularly useful to neurosurgeons for preoperative planning. Preoperative tractography permits both qualitative and quantitative analyses of tumor effects upon surrounding white matter, allowing the surgeon to specifically tailor their operative approach. Despite its benefits, there is controversy pertaining to methodology, implementation, and interpretation of results in this context. High-definition fiber tractography (HDFT) is one of several non-tensor tractography approaches permitting visualization of crossing white matter trajectories at high resolutions, dispensing with the well-known shortcomings of diffusion tensor imaging (DTI) tractography. In this article, we provide an overview of the advantages of HDFT in a neurosurgical context, derived from our considerable experience implementing the technique for academic and clinical purposes. We highlight nuances of qualitative and quantitative approaches to using HDFT for brain tumor surgery planning, and integration of tractography with complementary operative adjuncts, and consider areas requiring further research.

Usefulness of Preoperative Simulation in Skull Base Approach: A Case Report

Skull base approach is a neurosurgical challenge requiring dexterity of the operating surgeon for good postoperative outcome. In addition to the experience of the operating surgeon, adequate preoperative information of the tumor is necessary to ensure better outcome. In clinoid meningioma, it is sometimes difficult to determine its relationship with the surrounding structure and the feeding artery. Previously, preoperative simulation has been utilized to determine the intracranial course of the compressed nerves in relation to the petroclival meningioma. We report a case of clinoid meningioma where preoperative fusion of three dimensional computed tomography angiography (3D-CTA) and 3T-fast imaging employing steady-state acquisition (FIESTA) images was useful in determining the exact location of the feeding artery to devascularize the tumor and aid in surgery. Preoperative simulation with three-dimensional digital subtraction angiography (3D-DSA) and 3T-FIESTA fusion images can be a useful adjunct tool to supplement surgery and to train neurosurgical trainees.

Using Three-Dimensional Printing to Create Individualized Cranial Nerve Models for Skull Base Tumor Surgery

OBJECTIVE

Using three-dimensional (3D) printing to create individualized patient models of the skull base, the optic chiasm and facial nerve can be previsualized to help identify and protect these structures during tumor removal surgery.

METHODS

Preoperative imaging data for 2 cases of sellar tumor and 1 case of acoustic neuroma were obtained. Based on these data, the cranial nerves were visualized using 3D T1-weighted turbo field echo sequence and diffusion tensor imaging-based fiber tracking. Mimics software was used to create 3D reconstructions of the skull base regions surrounding the tumors, and 3D solid models were printed for use in simulation of the basic surgical steps.

RESULTS

The 3D printed personalized skull base tumor solid models contained information regarding the skull, brain tissue, blood vessels, cranial nerves, tumors, and other associated structures. The sphenoid sinus anatomy, saddle area, and cerebellopontine angle region could be visually displayed, and the spatial relationship between the tumor and the cranial nerves and important blood vessels was clearly defined. The models allowed for simulation of the operation, prediction of operative details, and verification of accuracy of cranial nerve reconstruction during the operation. Questionnaire assessment showed that neurosurgeons highly valued the accuracy and usefulness of these skull base tumor models.

CONCLUSIONS

3D printed models of skull base tumors and nearby cranial nerves, by allowing for the surgical procedure to be simulated beforehand, facilitate preoperative planning and help prevent cranial nerve injury.

A Quantitative Tractography Study Into the Connectivity, Segmentation and Laterality of the Human Inferior Longitudinal Fasciculus

The human inferior longitudinal fasciculus (ILF) is a ventral, temporo-occipital association tract. Though described in early neuroanatomical works, its existence was later questioned. Application of in vivo tractography to the neuroanatomical study of the ILF has generally confirmed its existence, however, consensus is lacking regarding its subdivision, laterality and connectivity. Further, there is a paucity of detailed neuroanatomic data pertaining to the exact anatomy of the ILF. Generalized Q-Sampling imaging (GQI) is a non-tensor tractographic modality permitting high resolution imaging of white-matter structures. As it is a non-tensor modality, it permits visualization of crossing fibers and accurate delineation of close-proximity fiber-systems. We applied deterministic GQI tractography to data from 30 healthy subjects and a large-volume, averaged diffusion atlas, to delineate ILF anatomy. Post-mortem white matter dissection was also carried out in three cadaveric specimens for further validation. The ILF was found in all 60 hemispheres. At its occipital extremity, ILF fascicles demonstrated a bifurcated, ventral-dorsal morphological termination pattern, which we used to further subdivide the bundle for detailed analysis. These divisions were consistent across the subject set and within the atlas. We applied quantitative techniques to study connectivity strength of the ILF at its anterior and posterior extremities. Overall, both morphological divisions, and the un-separated ILF, demonstrated strong leftward-lateralized connectivity patterns. Leftward-lateralization was also found for ILF volumes across the subject set. Due to connective and volumetric leftward-dominance and ventral location, we postulate the ILFs role in the semantic system. Further, our results are in agreement with functional and lesion-based postulations pertaining to the ILFs role in facial recognition.