Axonal conduction velocity, which ensures efficient function of the brain network, is related to axon diameter. Noninvasive, in vivo axon diameter estimates can be made with diffusion magnetic resonance imaging, but the technique requires three-dimensional (3D) validation. Here, high-resolution, 3D synchrotron X-ray nano-holotomography images of white matter samples from the corpus callosum of a monkey brain reveal that blood vessels, cells, and vacuoles affect axonal diameter and trajectory. Within single axons, we find that the variation in diameter and conduction velocity correlates with the mean diameter, contesting the value of precise diameter determination in larger axons. These complex 3D axon morphologies drive previously reported 2D trends in axon diameter and g-ratio. Furthermore, we find that these morphologies bias the estimates of axon diameter with diffusion magnetic resonance imaging and, ultimately, impact the investigation and formulation of the axon structure–function relationship.

Radiotherapy (RT) based on magnetic resonance imaging (MRI) as the only modality, so-called MRI-only RT, would remove the systematic registration error between MR and computed tomography (CT), and provide co-registered MRI for assessment of treatment response and adaptive RT. Electron densities, however, need to be assigned to the MRI images for dose calculation and patient setup based on digitally reconstructed radiographs (DRRs). Here, we investigate the geometric and dosimetric performance for a number of popular voxel-based methods to generate a so-called pseudo CT (pCT). Five patients receiving cranial irradiation, each containing a co-registered MRI and CT scan, were included. An ultra short echo time MRI sequence for bone visualization was used. Six methods were investigated for three popular types of voxel-based approaches; (1) threshold-based segmentation, (2) Bayesian segmentation and (3) statistical regression. Each approach contained two methods. Approach 1 used bulk density assignment of MRI voxels into air, soft tissue and bone based on logical masks and the transverse relaxation time T2 of the bone. Approach 2 used similar bulk density assignments with Bayesian statistics including or excluding additional spatial information. Approach 3 used a statistical regression correlating MRI voxels with their corresponding CT voxels. A similar photon and proton treatment plan was generated for a target positioned between the nasal cavity and the brainstem for all patients. The CT agreement with the pCT of each method was quantified and compared with the other methods geometrically and dosimetrically using both a number of reported metrics and introducing some novel metrics. The best geometrical agreement with CT was obtained with the statistical regression methods which performed significantly better than the threshold and Bayesian segmentation methods (excluding spatial information). All methods agreed significantly better with CT than a reference water MRI comparison. The mean dosimetric deviation for photons and protons compared to the CT was about 2% and highest in the gradient dose region of the brainstem. Both the threshold based method and the statistical regression methods showed the highest dosimetrical agreement.Generation of pCTs using statistical regression seems to be the most promising candidate for MRI-only RT of the brain. Further, the total amount of different tissues needs to be taken into account for dosimetric considerations regardless of their correct geometrical position.

No abstract

Understanding the human inner ear anatomy and its internal structures is paramount to advance hearing implant technology. While the emergence of imaging devices allowed researchers to improve understanding of intracochlear structures, the difficulties to collect appropriate data has resulted in studies conducted with few samples. To assist the cochlear research community, a large collection of human temporal bone images is being made available. This data descriptor, therefore, describes a rich set of image volumes acquired using cone beam computed tomography and micro-CT modalities, accompanied by manual delineations of the cochlea and sub-compartments, a statistical shape model encoding its anatomical variability, and data for electrode insertion and electrical simulations. This data makes an important asset for future studies in need of high-resolution data and related statistical data objects of the cochlea used to leverage scientific hypotheses. It is of relevance to anatomists, audiologists, computer scientists in the different domains of image analysis, computer simulations, imaging formation, and for biomedical engineers designing new strategies for cochlear implantations, electrode design, and others.

The paper presents the process of building and using the SDM of the cochlea. Compared to current best practice, we demonstrate competitive performance and some useful properties of our method.

Recent developments in computational modeling of cochlear implantation are promising to study in-silico the performance of the implant before surgery. However, creating a complete computational model of the patient's anatomy while including an external device geometry remains challenging. To address such a challenge, we propose an automatic framework for the generation of patient-specific meshes for finite element modeling of the implanted cochlea. First, a statistical shape model is constructed from highresolution anatomical µCT images. Then, by fitting the statistical model to a patient's CT image, an accurate model of the patient-specific cochlea anatomy is obtained. An algorithm based on the parallel transport frame is employed to perform the virtual insertion of the cochlear implant. Our automatic framework also incorporates the surrounding bone and nerve fibers and assigns constitutive parameters to all components of the finite element model. This model can then be used to study in-silico the e↵ects of the electrical stimulation of the cochlear implant. Results are shown on a total of 25 models of patients. In all cases, a final mesh suitable for finite element 1 This a pre-print version. The final document is available at http://www.springerlink.com simulations was obtained, in an average time of 94 seconds. The framework has proven to be fast and robust, and is promising for a detailed prognosis of the cochlear implantation surgery.

Super resolution (SR) imaging is currently conducted using fragile ultrasound contrast agents. This precludes using the full acoustic pressure range, and the distribution of bubbles has to be sparse for them to be isolated for SR imaging. Images have to be acquired over minutes to accumulate enough positions for visualizing the vasculature. A new method for SUper Resolution imaging using the Erythrocytes (SURE) as targets is introduced, which makes it possible to maximize the emitted pressure for good signal-to-noise ratios. The abundant number of erythrocyte targets make acquisition fast, and the SURE images can be acquired in seconds. A Verasonics Vantage 256 scanner was used in combination with a GE L8-18iD linear array probe operated at 10 MHz for a wavelength of 150 µm. A 12 emissions synthetic aperture ultrasound sequence was employed to scan the kidney of a Sprague-Dawley rat for 24 seconds to visualize its vasculature. An ex vivo micro-CT image using the contrast agent Microfil was also acquired at a voxel size of 22.6 µm for validating the SURE images. The SURE image revealed vessels with a size down to 29 µm, five times smaller than the ultrasound wavelength, and the dense grid of vessels in the full kidney was reliably shown for scan times between 1 to 24 seconds. Visually the SURE images revealed the same vasculature as the micro-CT images. SURE images are acquired in seconds rather than minutes without contrast injection for easy clinical use, and they can be measured at full regulatory levels for pressure, intensity, and probe temperature.

Axonal conduction velocity, which ensures efficient function of the brain network, is related to axon diameter. Non-invasive, in vivo axon diameter estimates can be made with diffusion magnetic resonance imaging, but the technique requires 3D validation. Here, high resolution, 3D synchrotron X-ray Nano-Holotomography images of white matter samples from the corpus callosum of a monkey brain reveal that blood vessels, cells and vacuoles affect axonal diameter and trajectory. Within single axons, we find that the variance in diameter and conduction velocity correlates with the mean diameter, contesting the value of precise diameter determination in larger axons. These complex 3D axon morphologies drive previously reported 2D trends in axon diameter and g-ratio. Furthermore, we find that these morphologies bias the estimates of axon diameter with diffusion magnetic resonance imaging and, ultimately, impact the investigation and formulation of the axon structure-function relationship. 4 acquired diffusion signal 15 . However, diffusion MRI-based AD estimates 14,16,17 are larger than those obtained by histology 15,18 . A potential cause is inaccurate modeling of the WM compartments, including the century old representation of myelinated axons as cylinders. A validation of the 3D WM anatomy could thus improve diffusion MRI-based AD estimations 17 and shed light on the validity of enforcing a cylindrical geometry and constant g-ratio in axonal structure-function relations. Recent 3D electron microscopy (EM) studies on axon morphology of the mouse reveal, in high resolution, non-uniform ADs and trajectories 19,20 . However, axons are only tracked for up to 20 µm, a fraction of their length in MRI voxels. Here, we characterize the long-range micro-morphologies of axons against the backdrop of the complex 3D WM environment consisting of blood vessels, cells and vacuoles. With synchrotron X-ray Nano-Holotomography (XNH), we acquire MRI measurements of the WM from the same monkey brain as in Alexander et al. (2010) 14 and Dyrby et al. (2013) 21 , in which the MRIderived AD estimates were larger than those estimated by histology. The 3D WM environment is mapped at a voxel size of 75 nm and volume of approximately 150 ⨉ 150 ⨉ 150 µm 3 . By combining adjacent XNH volumes, we extract axons >660 µm in length and show that AD, axon trajectory and g-ratio depend on the local microstructural environment. The 3D measurements shed light on the interpretation of 2D measurements, highlighting the importance of the third dimension for a robust description of single-axon structure and function. Lastly, by performing Monte Carlo (MC) diffusion simulations on axonal substrates with morphological features deriving from the XNH-segmented axons, we show that geometrical deviations from cylinders cause an overestimation of AD with diffusion MRI.