Could Phosphorous MR Spectroscopy Help Predict the Severity of Vasospasm? A Pilot Study.

One of the main causes of the dismal prognosis in patients who survive the initial bleeding after aneurysmal subarachnoidal hemorrhage is the delayed cerebral ischaemia caused by vasospasm. Studies suggest that cerebral magnesium and pH may potentially play a role in the pathophysiology of this adverse event. Using phosphorous magnetic resonance spectrocopy (31P-MRS), we calculated the cerebral magnesium (Mg) and pH levels in 13 patients who suffered from aSAH. The values between the group that developed clinically significant vasospasm (n = 7) and the group that did not (n = 6) were compared. The results of this study show significantly lower cerebral Mg levels (p = 0.019) and higher pH levels (p < 0.001) in the cumulative group (all brain voxels together) in patients who developed clinically significant vasospasm. Further clinical studies on a larger group of carefully selected patients are needed in order to predict clinically significant vasospasm.

A deep learning pipeline for the automated segmentation of posterior limb of internal capsule in preterm neonates.

Segmentation of specific brain tissue from MRI volumes is of great significance for brain disease diagnosis, progression assessment, and monitoring of neurological conditions. Manual segmentation is time-consuming, laborious, and subjective, which significantly amplifies the need for automated processes. Over the last decades, the active development in the field of deep learning, especially convolutional neural networks (CNNs), and the associated performance improvements have increased the demand for the application of CNN-based methods to provide consistent measurements and quantitative analyses. In this paper, we present an efficient deep learning approach for the segmentation of brain tissue. More specifically, we address the problem of segmentation of the posterior limb of the internal capsule (PLIC) in preterm neonates. To this end, we propose a CNN-based pipeline comprised of slice-selection modules and a multi-view segmentation model, which exploits the 3D information contained in the MRI volumes to improve segmentation performance. One special feature of the proposed method is its ability to identify one desired slice out of the whole image volume, which is relevant for pediatricians in terms of prognosis. To increase computational efficiency, we apply a strategy that automatically reduces the information contained in the MRI volumes to its relevant parts. Finally, we conduct an expert rating alongside standard evaluation metrics, such as dice score, to evaluate the performance of the proposed framework. We demonstrate the benefit of the multi-view technique by comparing it with its single-view counterparts, which reveals that the proposed method strikes a good balance between exploiting the available image information and reducing the required computing power compared to 3D segmentation networks. Standard evaluation metrics as, well as expert-based assessment, confirm the good performance of the proposed framework, with the latter being more relevant in terms of clinical applicability. We demonstrate that the proposed deep learning pipeline can compete with the experts in terms of accuracy. To prove the generalisability of the proposed method, we additionally assess our deep learning pipeline to data from the Developing Human Connectome Project (dHCP).

Accelerating and improving radiochromic film calibration by utilizing the dose ratio in photon and proton beams.

PURPOSE: Radiochromic films are versatile 2D dosimeters with high-resolution and near tissue equivalence. To assure high precision and accuracy, a time-consuming calibration process is required. To improve the time efficiency, a novel calibration method utilizing the ratio of the same dose profile measured at different monitor units (MUs) is introduced and tested in a proton and photon beam. METHODS: The calibration procedure employs the dose ratio of film measurements of the same relative profile for different absolute dose values. Hence, the ratio of the dose is constant at any point of the profile, but the ratio of the net optical densities is not constant. The key idea of the method is to optimize the calibration function until the ratio of the calculated doses is constant. The proposed method was tested in the dose range between 0.25-12 and 1-6 Gy in a proton and photon beam, respectively. A radial symmetric profile and a rectangular profile were created, both having a central plateau region of about 3 cm diameter and a dose falloff of about 1.5 cm at larger distances. The dose falloff region was used as input for the optimization method and the central plateau region served as dose reference points. Only the plateau region of the highest dose entered the optimization as an additional objective. The measured data were randomly split into differently sized training and test sets. The optimization was repeated 1000 times with random start value initialization using the same start values for the standard and the gradient method. Finally, a proton plan with four dose levels was created, which were separated spatially, to test the possibility of a full calibration within a single measurement. RESULTS: Parameter estimation was possible with as low as one dose ratio used for optimization in both the photon and the proton case, yet exhibiting a high sensitivity on the dose level. The root mean squared deviation (RMSD) of the dose was less than 1% when the dose ratio was in the order of 20, whereas the median RMSD of all optimizations was 1.7%. Using four dose levels for optimization resulted in a median RMSD of 1% when randomly selecting the dose levels. Having at least one dose ratio of about 20 included in the optimization considerably improved the RMSD of the calibration function. Using six or eight dose levels reduced the sensitivity on the dose level selection and the median RMSD was 0.8%. A full calibration was possible in a single measurement having four dose levels in one plan but spatially separated. CONCLUSIONS: The number of measurements required to obtain an EBT3 film calibration function could be reduced using the proposed dose ratio method while maintaining the same accuracy as with the standard method.

Novel microscope-based visual display and nasopharyngeal registration for auditory brainstem implantation: a feasibility study in an ex vivo model.

PURPOSE: An auditory brainstem implant (ABI) represents an alternative for patients with profound hearing loss who are constrained from receiving a cochlear implant. The positioning of the ABI electrode influences the patient's auditory capacity and, therefore, quality of life and is challenging even with available intraoperative electrophysiological monitoring. This work aims to provide and assess the feasibility of visual-spatial assistance for ABI positioning. METHODS: The pose of the forceps instrument that grasps the electrode was electromagnetically navigated and interactively projected in the eyepieces of a surgical microscope with respect to a target point. Intraoperative navigation was established with an experimental technique for automated nasopharyngeal patient registration. Two ABI procedures were completed in a human specimen head. RESULTS: An intraoperative usability study demonstrated lower localization error when using the proposed visual display versus standard cross-sectional views. The postoperative evaluations of the preclinical study showed that the center of the electrode was misplaced to the planned position by 1.58 mm and 3.16 mm for the left and the right ear procedure, respectively. CONCLUSION: The results indicate the potential to enhance intraoperative feedback during ABI positioning with the presented system. Further improvements consider estimating the pose of the electrode itself to allow for better orientation during placement.

Brain Energy Metabolism in Two States of Mind Measured by Phosphorous Magnetic Resonance Spectroscopy.

Introduction: Various functional neuroimaging studies help to better understand the changes in brain activity during meditation. The purpose of this study was to investigate how brain energy metabolism changes during focused attention meditation (FAM) state, measured by phosphorous magnetic resonance spectroscopy (31P-MRS). Methods: 31P-MRS imaging was carried out in 27 participants after 7 weeks of FAM training. Metabolite ratios and the absolute values of metabolites were assessed after meditation training in two MRI measurements, by comparing effects in a FAM state with those in a distinct focused attention awake state during a backwards counting task. Results: The results showed decreased phosphocreatine/ATP (PCr/ATP), PCr/ inorganic phosphate (Pi), and intracellular pH values in the entire brain, but especially in basal ganglia, frontal lobes, and occipital lobes, and increased Pi/ATP ratio, cerebral Mg, and Pi absolute values were found in the same areas during FAM compared to the control focused attention awake state. Conclusions: Changes in the temporal areas and basal ganglia may be interpreted as a higher energetic state induced by meditation, whereas the frontal and occipital areas showed changes that may be related to a down-regulation in ATP turnover, energy state, and oxidative capacity.

Phosphorous Magnetic Resonance Spectroscopy and Molecular Markers in IDH1 Wild Type Glioblastoma.

The World Health Organisation's (WHO) classification of brain tumors requires consideration of both histological appearance and molecular characteristics. Possible differences in brain energy metabolism could be important in designing future therapeutic strategies. Forty-three patients with primary, isocitrate dehydrogenase 1 (IDH1) wild type glioblastomas (GBMs) were included in this study. Pre-operative standard MRI was obtained with additional phosphorous magnetic resonance spectroscopy (31-P-MRS) imaging. Following microsurgical resection of the tumors, biopsy specimens underwent neuropathological diagnostics including standard molecular diagnosis. The spectroscopy results were correlated with epidermal growth factor (EGFR) and O6-Methylguanine-DNA methyltransferase (MGMT) status. EGFR amplified tumors had significantly lower phosphocreatine (PCr) to adenosine triphosphate (ATP)-PCr/ATP and PCr to inorganic phosphate (Pi)-PCr/Pi ratios, and higher Pi/ATP and phosphomonoesters (PME) to phosphodiesters (PDE)-PME/PDE ratio than those without the amplification. Patients with MGMT-methylated tumors had significantly higher cerebral magnesium (Mg) values and PME/PDE ratio, while their PCr/ATP and PCr/Pi ratios were lower than in patients without the methylation. In survival analysis, not-EGFR-amplified, MGMT-methylated GBMs showed the longest survival. This group had lower PCr/Pi ratio when compared to MGMT-methylated, EGFR-amplified group. PCr/Pi ratio was lower also when compared to the MGMT-unmethylated, EGFR not-amplified group, while PCr/ATP ratio was lower than all other examined groups. Differences in energy metabolism in various molecular subtypes of wild-type-GBMs could be important information in future precision medicine approach.

Automated fiducial marker detection and localization in volumetric computed tomography images: a three-step hybrid approach with deep learning.

Purpose: Automating fiducial detection and localization in the patient's pre-operative images can lead to better registration accuracy, reduced human errors, and shorter intervention time. Most current approaches are optimized for a single marker type, mainly spherical adhesive markers. A fully automated algorithm is proposed and evaluated for screw and spherical titanium fiducials, typically used in high-accurate frameless surgical navigation. Approach: The algorithm builds on previous approaches with morphological functions and pose estimation algorithms. A 3D convolutional neural network (CNN) is proposed for the fiducial classification task and evaluated for both traditional closed-set and emerging open-set classifiers. A proposed digital ground-truth experiment, with cone-beam computed tomography (CBCT) imaging software, is performed to determine the localization accuracy of the algorithm. The localized fiducial positions in the CBCT images by the presented algorithm were compared to the actual known positions in the virtual phantom models. The difference represents the fiducial localization error (FLE). Results: A total of 241 screws, 151 spherical fiducials, and 1550 other structures are identified with the best true positive rate 95.9% for screw and 99.3% for spherical fiducials at 8.7% and 3.4% false positive rate, respectively. The best achieved FLE mean and its standard deviation for a screw and spherical marker are 58 (14) and 14 ( 6 ) µ m , respectively. Conclusions: Accurate marker detection and localization were achieved, with spherical fiducials being superior to screws. Large marker volume and smaller voxel size yield significantly smaller FLEs. Attenuating noise by mesh smoothing has a minor effect on FLE. Future work will focus on expanding the CNN for image segmentation.

Visual display for surgical targeting: concepts and usability study.

PURPOSE: Interactive image-guided surgery technologies enable accurate target localization while preserving critical nearby structures in many surgical interventions. Current state-of-the-art interfaces largely employ traditional anatomical cross-sectional views or augmented reality environments to present the actual spatial location of the surgical instrument in preoperatively acquired images. This work proposes an alternative, simple, minimalistic visual interface intended to assist during real-time surgical target localization. METHODS: The estimated 3D pose of the interventional instruments and their positional uncertainty are intuitively presented in a visual interface with respect to the target point. A usability study with multidisciplinary participants evaluates the proposed interface projected in surgical microscope oculars against cross-sectional views. The latter was presented on a screen both stand-alone and combined with the proposed interface. The instruments were electromagnetically navigated in phantoms. RESULTS: The usability study demonstrated that the participants were able to detect invisible targets marked in phantom imagery with significant enhancements for localization accuracy and duration time. Clinically experienced users reached the targets with shorter trajectories. The stand-alone and multi-modal versions of the proposed interface outperformed cross-sectional views-only navigation in both quantitative and qualitative evaluations. CONCLUSION: The results and participants' feedback indicate potential to accurately navigate users toward the target with less distraction and workload. An ongoing study evaluates the proposed system in a preclinical setting for auditory brainstem implantation.