Size and shape matter: The impact of voxel geometry on the identification of small nuclei

Microstructural imaging of brain changes in schizophrenia via quantitative T1 (qT1): a preliminary comparison of two acquisition protocols

Schizophrenia spectrum disorders (SSD) are a complex group of illnesses, and their pathophysiology remains unclear. Recent developments in neuroimaging techniques provided useful quantitative measures, such as quantitative T1 mapping (qT1) that is susceptible to tissue-level, microscopic changes. However, it is important to identify the most sensitive, accurate, and reliable imaging protocol, given the complex nature of SSD. We compared structural brain changes in a pilot sample of 15 SSD patients and 7 healthy controls, cross-sectionally, and using two different qT1 mapping protocols. Our findings showed a global elevation in qT1 values in SSD patients, that was statistically significant in the lateral ventricles, thalamus, caudate, and hippocampus (p < 0.01). Moreover, the two acquisition protocols were differently modulated by demographic factors, such as age, sex, and education, which further illustrates the importance of protocol selection. In conclusion, this investigation revealed microstructural tissue changes in subcortical regions in SSD patients, providing further insights into the pathophysiology of the illness.

Multiscale Analysis of Alzheimer's Disease Using Feature Fusion in Cognitive and Sensory Brain Regions

Introduction

This research is focused on early detection of Alzheimer's disease (AD) using a multiscale feature fusion framework, combining biomarkers from memory, vision, and speech regions extracted from magnetic resonance imaging and positron emission tomography images.

Methods

Using 2D gray level co-occurrence matrix (2D-GLCM) texture features, volume, standardized uptake value ratios (SUVR), and obesity from different neuroimaging modalities, the study applies various classifiers, demonstrating a feature importance analysis in each region of interest. The research employs four classifiers, namely linear support vector machine, linear discriminant analysis, logistic regression (LR), and logistic regression with stochastic gradient descent (LRSGD) classifiers, to determine feature importance, leading to subsequent validation using a probabilistic neural network classifier.

Results

The research highlights the critical role of brain texture features, particularly in memory regions, for AD detection. Significant sex-specific differences are observed, with males showing significance in texture features in memory regions, volume in vision regions, and SUVR in speech regions, while females exhibit significance in texture features in memory and speech regions, and SUVR in vision regions. Additionally, the study analyzes how obesity affects features used in AD prediction models, clarifying its effects on speech and vision regions, particularly brain volume.

Conclusion

The findings contribute valuable insights into the effectiveness of feature fusion, sex-specific differences, and the impact of obesity on AD-related biomarkers, paving the way for future research in early AD detection strategies and cognitive impairment classification.

Portable, low-field magnetic resonance imaging for evaluation of Alzheimer's disease

Portable, low-field magnetic resonance imaging (LF-MRI) of the brain may facilitate point-of-care assessment of patients with Alzheimer's disease (AD) in settings where conventional MRI cannot. However, image quality is limited by a lower signal-to-noise ratio. Here, we optimize LF-MRI acquisition and develop a freely available machine learning pipeline to quantify brain morphometry and white matter hyperintensities (WMH). We validate the pipeline and apply it to outpatients presenting with mild cognitive impairment or dementia due to AD. We find hippocampal volumes from ≤ 3 mm isotropic LF-MRI scans have agreement with conventional MRI and are more accurate than anisotropic counterparts. We also show WMH volume has agreement between manual segmentation and the automated pipeline. The increased availability and reduced cost of LF-MRI, in combination with our machine learning pipeline, has the potential to increase access to neuroimaging for dementia.

A roadmap towards standardized neuroimaging approaches for human thalamic nuclei

The thalamus has a key role in mediating cortical-subcortical interactions but is often neglected in neuroimaging studies, which mostly focus on changes in cortical structure and activity. One of the main reasons for the thalamus being overlooked is that the delineation of individual thalamic nuclei via neuroimaging remains controversial. Indeed, neuroimaging atlases vary substantially regarding which thalamic nuclei are included and how their delineations were established. Here, we review current and emerging methods for thalamic nuclei segmentation in neuroimaging data and consider the limitations of existing techniques in terms of their research and clinical applicability. We address these challenges by proposing a roadmap to improve thalamic nuclei segmentation in human neuroimaging and, in turn, harmonize research approaches and advance clinical applications. We believe that a collective effort is required to achieve this. We hope that this will ultimately lead to the thalamic nuclei being regarded as key brain regions in their own right and not (as often currently assumed) as simply a gateway between cortical and subcortical regions.

Leveraging ultra-high field (7T) MRI in psychiatric research

Non-invasive brain imaging has played a critical role in establishing our understanding of the neural properties that contribute to the emergence of psychiatric disorders. However, characterizing core neurobiological mechanisms of psychiatric symptomatology requires greater structural, functional, and neurochemical specificity than is typically obtainable with standard field strength MRI acquisitions (e.g., 3T). Ultra-high field (UHF) imaging at 7 Tesla (7T) provides the opportunity to identify neurobiological systems that confer risk, determine etiology, and characterize disease progression and treatment outcomes of major mental illnesses. Increases in scanner availability, regulatory approval, and sequence availability have made the application of UHF to clinical cohorts more feasible than ever before, yet the application of UHF approaches to the study of mental health remains nascent. In this technical review, we describe core neuroimaging methodologies which benefit from UHF acquisition, including high resolution structural and functional imaging, single (1H) and multi-nuclear (e.g., 31P) MR spectroscopy, and quantitative MR techniques for assessing brain tissue iron and myelin. We discuss advantages provided by 7T MRI, including higher signal- and contrast-to-noise ratio, enhanced spatial resolution, increased test-retest reliability, and molecular and neurochemical specificity, and how these have begun to uncover mechanisms of psychiatric disorders. Finally, we consider current limitations of UHF in its application to clinical cohorts, and point to ongoing work that aims to overcome technical hurdles through the continued development of UHF hardware, software, and protocols.

Structural covariance, topological organization, and volumetric features of amygdala subnuclei in posttraumatic stress disorder

The amygdala is divided into functional subnuclei which have been challenging to investigate due to functional magnetic resonance imaging (MRI) limitations in mapping small neural structures. Hence their role in the neurobiology of posttraumatic stress disorder (PTSD) remains poorly understood. Examination of covariance of structural MRI measures could be an alternate approach to circumvent this issue. T1-weighted anatomical scans from a 3 T scanner from non-trauma-exposed controls (NEC; n = 71, 75 % female) and PTSD participants (n = 67, 69 % female) were parcellated into 105 brain regions. Pearson's r partial correlations were computed for three and nine bilateral amygdala subnuclei and every other brain region, corrected for age, sex, and total brain volume. Pairwise correlation comparisons were performed to examine subnuclei covariance profiles between-groups. Graph theory was employed to investigate subnuclei network topology. Volumetric measures were compared to investigate structural changes. We found differences between amygdala subnuclei in covariance with the hippocampus for both groups, and additionally with temporal brain regions for the PTSD group. Network topology demonstrated the importance of the right basal nucleus in facilitating network communication only in PTSD. There were no between-group differences for any of the three structural metrics. These findings are in line with previous work that has failed to find structural differences for amygdala subnuclei between PTSD and controls. However, differences between amygdala subnuclei covariance profiles observed in our study highlight the need to investigate amygdala subnuclei functional connectivity in PTSD using higher field strength fMRI for better spatial resolution.

Impact of Deep Learning Denoising Algorithm on Diffusion Tensor Imaging of the Growth Plate on Different Spatial Resolutions

To assess the impact of a deep learning (DL) denoising reconstruction algorithm applied to identical patient scans acquired with two different voxel dimensions, representing distinct spatial resolutions, this IRB-approved prospective study was conducted at a tertiary pediatric center in compliance with the Health Insurance Portability and Accountability Act. A General Electric Signa Premier unit (GE Medical Systems, Milwaukee, WI) was employed to acquire two DTI (diffusion tensor imaging) sequences of the left knee on each child at 3T: an in-plane 2.0 × 2.0 mm2 with section thickness of 3.0 mm and a 2 mm3 isovolumetric voxel; neither had an intersection gap. For image acquisition, a multi-band DTI with a fat-suppressed single-shot spin-echo echo-planar sequence (20 non-collinear directions; b-values of 0 and 600 s/mm2) was utilized. The MR vendor-provided a commercially available DL model which was applied with 75% noise reduction settings to the same subject DTI sequences at different spatial resolutions. We compared DTI tract metrics from both DL-reconstructed scans and non-denoised scans for the femur and tibia at each spatial resolution. Differences were evaluated using Wilcoxon-signed ranked test and Bland-Altman plots. When comparing DL versus non-denoised diffusion metrics in femur and tibia using the 2 mm × 2 mm × 3 mm voxel dimension, there were no significant differences between tract count (p = 0.1, p = 0.14) tract volume (p = 0.1, p = 0.29) or tibial tract length (p = 0.16); femur tract length exhibited a significant difference (p < 0.01). All diffusion metrics (tract count, volume, length, and fractional anisotropy (FA)) derived from the DL-reconstructed scans, were significantly different from the non-denoised scan DTI metrics in both the femur and tibial physes using the 2 mm3 voxel size (p < 0.001). DL reconstruction resulted in a significant decrease in femorotibial FA for both voxel dimensions (p < 0.01). Leveraging denoising algorithms could address the drawbacks of lower signal-to-noise ratios (SNRs) associated with smaller voxel volumes and capitalize on their better spatial resolutions, allowing for more accurate quantification of diffusion metrics.

Functional Magnetic Resonance Imaging of the Amygdala and Subregions at 3 Tesla: A Scoping Review

The amygdalae are a pair of small brain structures, each of which is composed of three main subregions and whose function is implicated in neuropsychiatric conditions. Functional Magnetic Resonance Imaging (fMRI) has been utilized extensively in investigation of amygdala activation and functional connectivity (FC) with most clinical research sites now utilizing 3 Tesla (3T) MR systems. However, accurate imaging and analysis remains challenging not just due to the small size of the amygdala, but also its location deep in the temporal lobe. Selection of imaging parameters can significantly impact data quality with implications for the accuracy of study results and validity of conclusions. Wide variation exists in acquisition protocols with spatial resolution of some protocols suboptimal for accurate assessment of the amygdala as a whole, and for measuring activation and FC of the three main subregions, each of which contains multiple nuclei with specialized roles. The primary objective of this scoping review is to provide a broad overview of 3T fMRI protocols in use to image the activation and FC of the amygdala with particular reference to spatial resolution. The secondary objective is to provide context for a discussion culminating in recommendations for a standardized protocol for imaging activation of the amygdala and its subregions. As the advantages of big data and protocol harmonization in imaging become more apparent so, too, do the disadvantages of data heterogeneity. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Isotropic 3D compressed sensing (CS) based sequence is comparable to 2D-LGE in left ventricular scar quantification in different disease entities

The goal of this study was to evaluate a three-dimensional compressed sensing (3D-CS) LGE prototype sequence for the detection and quantification of myocardial fibrosis in patients with chronic myocardial infarction (CMI) and myocarditis (MYC) compared with a 2D-LGE standard. Patients with left-ventricular LGE due to CMI (n = 33) or MYC (n = 20) were prospectively recruited. 2D-LGE and 3D-CS images were acquired in random order at 1.5 Tesla. 3D-CS short axis (SAX) images were reconstructed corresponding to 2D SAX images. LGE was quantitatively assessed on patient and segment level using semi-automated threshold methods. Image quality (4-point scoring system), Contrast-ratio (CR) and acquisition times were compared. There was no significant difference between 2D and 3D sequences regarding global LGE (%) (CMI [2D-LGE: 11.4 ± 7.5; 3D-LGE: 11.5 ± 8.5; p = 0.99]; MYC [2D-LGE: 27.0 ± 15.7; 3D-LGE: 26.2 ± 13.1; p = 0.70]) and segmental LGE-extent (p = 0.63). 3D-CS identified papillary infarction in 5 cases which was not present in 2D images. 2D-LGE acquisition time was shorter (2D: median: 06:59 min [IQR: 05:51-08:18]; 3D: 14:48 min [12:45-16:57]). 3D-CS obtained better quality scores (2D: 2.06 ± 0.56 vs. 3D: 2.29 ± 0.61). CR did not differ (p = 0.63) between basal and apical regions in 3D-CS images but decreased significantly in 2D apical images (CR basal: 2D: 0.77 ± 0.11, 3D: 0.59 ± 0.10; CR apical: 2D: 0.64 ± 0.17, 3D: 0.53 ± 0.11). 3D-LGE shows high congruency with standard LGE and allows better identification of small lesions. However, the current 3D-CS LGE sequence did not provide PSIR reconstruction and acquisition time was longer.

Through Thick and Thin: Baseline Cortical Volume and Thickness Predict Performance and Response to Transcranial Direct Current Stimulation in Primary Progressive Aphasia

Objectives

We hypothesized that measures of cortical thickness and volume in language areas would correlate with response to treatment with high-definition transcranial direct current stimulation (HD-tDCS) in persons with primary progressive aphasia (PPA).

Materials and Methods

In a blinded, within-group crossover study, PPA patients (N = 12) underwent a 2-week intervention HD-tDCS paired with constraint-induced language therapy (CILT). Multi-level linear regression (backward-fitted models) were performed to assess cortical measures as predictors of tDCS-induced naming improvements, measured by the Western Aphasia Battery-naming subtest, from baseline to immediately after and 6 weeks post-intervention.

Results

Greater baseline thickness of the pars opercularis significantly predicted naming gains (p = 0.03) immediately following intervention, while greater thickness of the middle temporal gyrus (MTG) and lower thickness of the superior temporal gyrus (STG) significantly predicted 6-week naming gains (p's < 0.02). Thickness did not predict naming gains in sham. Volume did not predict immediate gains for active stimulation. Greater volume of the pars triangularis and MTG, but lower STG volume significantly predicted 6-week naming gains in active stimulation. Greater pars orbitalis and MTG volume, and lower STG volume predicted immediate naming gains in sham (p's < 0.05). Volume did not predict 6-week naming gains in sham.

Conclusion

Cortical thickness and volume were predictive of tDCS-induced naming improvement in PPA patients. The finding that frontal thickness predicted immediate active tDCS-induced naming gains while temporal areas predicted naming changes at 6-week suggests that a broader network of regions may be important for long-term maintenance of treatment gains. The finding that volume predicted immediate naming performance in the sham condition may reflect the benefits of behavioral speech language therapy and neural correlates of its short-lived treatment gains. Collectively, thickness and volume were predictive of treatment gains in the active condition but not sham, suggesting that pairing HD-tDCS with CILT may be important for maintaining treatment effects.

Assessment of Bone Microarchitecture in Fresh Cadaveric Human Femurs: What Could Be the Clinical Relevance of Ultra-High Field MRI

MRI could be applied for bone microarchitecture assessment; however, this technique is still suffering from low resolution compared to the trabecular dimension. A clear comparative analysis between MRI and X-ray microcomputed tomography (μCT) regarding microarchitecture metrics is still lacking. In this study, we performed a comparative analysis between μCT and 7T MRI with the aim of assessing the image resolution effect on the accuracy of microarchitecture metrics. We also addressed the issue of air bubble artifacts in cadaveric bones. Three fresh cadaveric femur heads were scanned using 7T MRI and µCT at high resolution (0.051 mm). Samples were submitted to a vacuum procedure combined with vibration to reduce the volume of air bubbles. Trabecular interconnectivity, a new metric, and conventional histomorphometric parameters were quantified using MR images and compared to those derived from µCT at full resolution and downsized resolutions (0.102 and 0.153 mm). Correlations between bone morphology and mineral density (BMD) were evaluated. Air bubbles were reduced by 99.8% in 30 min, leaving partial volume effects as the only source of bias. Morphological parameters quantified with 7T MRI were not statistically different (p > 0.01) to those computed from μCT images, with error up to 8% for both bone volume fraction and trabecular spacing. No linear correlation was found between BMD and all morphological parameters except trabecular interconnectivity (R2 = 0.69 for 7T MRI-BMD). These results strongly suggest that 7T MRI could be of interest for in vivo bone microarchitecture assessment, providing additional information about bone health and quality.

Charting human subcortical maturation across the adult lifespan with in vivo 7 T MRI

The human subcortex comprises hundreds of unique structures. Subcortical functioning is crucial for behavior, and disrupted function is observed in common neurodegenerative diseases. Despite their importance, human subcortical structures continue to be difficult to study in vivo. Here we provide a detailed account of 17 prominent subcortical structures and ventricles, describing their approximate iron and myelin contents, morphometry, and their age-related changes across the normal adult lifespan. The results provide compelling insights into the heterogeneity and intricate age-related alterations of these structures. They also show that the locations of many structures shift across the lifespan, which is of direct relevance for the use of standard magnetic resonance imaging atlases. The results further our understanding of subcortical morphometry and neuroimaging properties, and of normal aging processes which ultimately can improve our understanding of neurodegeneration.

An isotropic EPI database and analytical pipelines for rat brain resting-state fMRI

Resting-state functional magnetic resonance imaging (fMRI) has drastically expanded the scope of brain research by advancing our knowledge about the topologies, dynamics, and interspecies translatability of functional brain networks. Several databases have been developed and shared in accordance with recent key initiatives in the rodent fMRI community to enhance the transparency, reproducibility, and interpretability of data acquired at various sites. Despite these pioneering efforts, one notable challenge preventing efficient standardization in the field is the customary choice of anisotropic echo planar imaging (EPI) schemes with limited spatial coverage. Imaging with anisotropic resolution and/or reduced brain coverage has significant shortcomings including reduced registration accuracy and increased deviation in brain feature detection. Here we proposed a high-spatial-resolution (0.4 mm), isotropic, whole-brain EPI protocol for the rat brain using a horizontal slicing scheme that can maintain a functionally relevant repetition time (TR), avoid high gradient duty cycles, and offer unequivocal whole-brain coverage. Using this protocol, we acquired resting-state EPI fMRI data from 87 healthy rats under the widely used dexmedetomidine sedation supplemented with low-dose isoflurane on a 9.4 T MRI system. We developed an EPI template that closely approximates the Paxinos and Watson's rat brain coordinate system and demonstrated its ability to improve the accuracy of group-level approaches and streamline fMRI data pre-processing. Using this database, we employed a multi-scale dictionary-learning approach to identify reliable spatiotemporal features representing rat brain intrinsic activity. Subsequently, we performed k-means clustering on those features to obtain spatially discrete, functional regions of interest (ROIs). Using Euclidean-based hierarchical clustering and modularity-based partitioning, we identified the topological organizations of the rat brain. Additionally, the identified group-level FC network appeared robust across strains and sexes. The "triple-network" commonly adapted in human fMRI were resembled in the rat brain. Through this work, we disseminate raw and pre-processed isotropic EPI data, a rat brain EPI template, as well as identified functional ROIs and networks in standardized rat brain coordinates. We also make our analytical pipelines and scripts publicly available, with the hope of facilitating rat brain resting-state fMRI study standardization.

Manual delineation approaches for direct imaging of the subcortex

The growing interest in the human subcortex is accompanied by an increasing number of parcellation procedures to identify deep brain structures in magnetic resonance imaging (MRI) contrasts. Manual procedures continue to form the gold standard for parcellating brain structures and is used for the validation of automated approaches. Performing manual parcellations is a tedious process which requires a systematic and reproducible approach. For this purpose, we created a series of protocols for the anatomical delineation of 21 individual subcortical structures. The intelligibility of the protocols was assessed by calculating Dice similarity coefficients for ten healthy volunteers. In addition, dilated Dice coefficients showed that manual parcellations created using these protocols can provide high-quality training data for automated algorithms. Here, we share the protocols, together with three example MRI datasets and the created manual delineations. The protocols can be applied to create high-quality training data for automated parcellation procedures, as well as for further validation of existing procedures and are shared without restrictions with the research community.

Variability in subthalamic nucleus targeting for deep brain stimulation with 3 and 7 Tesla magnetic resonance imaging

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective surgical treatment for Parkinson's disease (PD). Side-effects may, however, be induced when the DBS lead is placed suboptimally. Currently, lower field magnetic resonance imaging (MRI) at 1.5 or 3 Tesla (T) is used for targeting. Ultra-high-field MRI (7 T and above) can obtain superior anatomical information and might therefore be better suited for targeting. This study aims to test whether optimized 7 T imaging protocols result in less variable targeting of the STN for DBS compared to clinically utilized 3 T images. Three DBS-experienced neurosurgeons determined the optimal STN DBS target site on three repetitions of 3 T-T2, 7 T-T2*, 7 T-R2* and 7 T-QSM images for five PD patients. The distance in millimetres between the three repetitive coordinates was used as an index of targeting variability and was compared between field strength, MRI contrast and repetition with a Bayesian ANOVA. Further, the target coordinates were registered to MNI space, and anatomical coordinates were compared between field strength, MRI contrast and repetition using a Bayesian ANOVA. The results indicate that the neurosurgeons are stable in selecting the DBS target site across MRI field strength, MRI contrast and repetitions. The analysis of the coordinates in MNI space however revealed that the actual selected location of the electrode is seemingly more ventral when using the 3 T scan compared to the 7 T scans.

Subthalamic and Pallidal Stimulations in Patients with Parkinson's Disease: Common and Dissociable Connections

OBJECTIVE

The subthalamic nucleus (STN) and internal globus pallidus (GPi) are the most effective targets in deep brain stimulation (DBS) for Parkinson's disease (PD). However, the common and specific effects on brain connectivity of stimulating the 2 nuclei remain unclear.

METHODS

Patients with PD receiving STN-DBS (n = 27, 6 women, mean age 64.8 years) or GPi-DBS (n = 28, 13 women, mean age 64.6 years) were recruited for resting-state functional magnetic resonance imaging to assess the effects of STN-DBS and GPi-DBS on brain functional dynamics.

RESULTS

The functional connectivity both between the somatosensory-motor cortices and thalamus, and between the somatosensory-motor cortices and cerebellum decreased in the DBS-on state compared with the off state (p < 0.05). The changes in thalamocortical connectivity correlated with DBS-induced motor improvement (p < 0.05) and were negatively correlated with the normalized intersection volume of tissues activated at both DBS targets (p < 0.05). STN-DBS modulated functional connectivity among a wider range of brain areas than GPi-DBS (p = 0.009). Notably, only STN-DBS affected connectivity between the postcentral gyrus and cerebellar vermis (p < 0.001) and between the somatomotor and visual networks (p < 0.001).

INTERPRETATION

Our findings highlight common alterations in the motor pathway and its relationship with the motor improvement induced by both STN- and GPi-DBS. The effects on cortico-cerebellar and somatomotor-visual functional connectivity differed between groups, suggesting differentiated neural modulation of the 2 target sites. Our results provide mechanistic insight and yield the potential to refine target selection strategies for focal brain stimulation in PD. ANN NEUROL 2021.

Cortical and subcortical contributions to interference resolution and inhibition - An fMRI ALE meta-analysis

Interacting with our environment requires the selection of appropriate responses and the inhibition of others. Such effortful inhibition is achieved by a number of interference resolution and global inhibition processes. This meta-analysis including 57 studies and 73 contrasts revisits the overlap and differences in brain areas supporting interference resolution and global inhibition in cortical and subcortical brain areas. Activation likelihood estimation was used to discern the brain regions subserving each type of cognitive control. Individual contrast analysis revealed a common activation of the bilateral insula and supplementary motor areas. Subtraction analyses demonstrated the voxel-wise differences in recruitment in a number of areas including the precuneus in the interference tasks and the frontal pole and dorsal striatum in the inhibition tasks. Our results display a surprising lack of subcortical involvement within these types of cognitive control, a finding that is likely to reflect a systematic gap in the field of functional neuroimaging.

A new 2D-3D registration gold-standard dataset for the hip joint based on uncertainty modeling

Purpose

Estimation of the accuracy of 2D‐3D registration is paramount for a correct evaluation of its outcome in both research and clinical studies. Publicly available datasets with standardized evaluation methodology are necessary for validation and comparison of 2D‐3D registration techniques. Given the large use of 2D‐3D registration in biomechanics, we introduced the first gold standard validation dataset for computed tomography (CT)‐to‐x‐ray registration of the hip joint, based on fluoroscopic images with large rotation angles. As the ground truth computed with fiducial markers is affected by localization errors in the image datasets, we proposed a new methodology based on uncertainty propagation to estimate the accuracy of a gold standard dataset.

Methods

The gold standard dataset included a 3D CT scan of a female hip phantom and 19 2D fluoroscopic images acquired at different views and voltages. The ground truth transformations were estimated based on the corresponding pairs of extracted 2D and 3D fiducial locations. These were assumed to be corrupted by Gaussian noise, without any restrictions of isotropy. We devised the multiple projective points criterion (MPPC) that jointly optimizes the transformations and the noisy 3D fiducial locations for all views. The accuracy of the transformations obtained with the MPPC was assessed in both synthetic and real experiments using different formulations of the target registration error (TRE), including a novel formulation of the TRE (uTRE) derived from the uncertainty analysis of the MPPC.

Results

The proposed MPPC method was statistically more accurate compared to the validation methods for 2D‐3D registration that did not optimize the 3D fiducial positions or wrongly assumed the isotropy of the noise. The reported results were comparable to previous published works of gold standard datasets. However, a formulation of the TRE commonly found in these gold standard datasets was found to significantly miscalculate the true TRE computed in synthetic experiments with known ground truths. In contrast, the uncertainty‐based uTRE was statistically closer to the true TRE.

Conclusions

We proposed a new gold standard dataset for the validation of CT‐to‐X‐ray registration of the hip joint. The gold standard transformations were derived from a novel method modeling the uncertainty in extracted 2D and 3D fiducials. Results showed that considering possible noise anisotropy and including corrupted 3D fiducials in the optimization resulted in improved accuracy of the gold standard. A new uncertainty‐based formulation of the TRE also appeared as a good alternative to the unknown true TRE that has been replaced in previous works by an alternative TRE not fully reflecting the gold standard accuracy.

Significant increases of the amygdala between immediate and late postpartum: Pronounced effects within the superficial subregion

Research exploring the underlying neuroanatomical correlates of early motherhood seems to suggest that the period after giving birth is marked by tissue increases in the mother's brain. While some studies point to the amygdala as one of the areas undergoing postpartum changes, existing analyses did not discriminate between the different subregions of this functionally heterogeneous structure. Thus, to further extend this understudied field of research and to better understand the potential role of the amygdala when transitioning to motherhood, we applied an advanced region-of-interest technique that enabled us to analyze the amygdala as a whole as well as its different subareas, specifically the left and right centromedian (CM), laterobasal (LB), and superficial (SF) regions. Comparing the brains of 14 healthy women between immediate postpartum (within 1-2 days of childbirth) and late postpartum (at 4-6 weeks after childbirth), we revealed increases of the amygdala. However, effects manifested differentially across subareas, with particularly strong effects for the SF region, moderate effects for the CM region, and no effects for the LB region. These findings might reflect region-specific adaptations of the mother's brain tuning into the distinct and ever-changing needs of a newborn, either as a cause for it or as a consequence thereof.

Globus Pallidus Internus (GPi) Deep Brain Stimulation for Parkinson's Disease: Expert Review and Commentary

INTRODUCTION

The globus pallidus internus (GPi) region has evolved as a potential target for deep brain stimulation (DBS) in Parkinson's disease (PD). DBS of the GPi (GPi DBS) is an established, safe and effective method for addressing many of the motor symptoms associated with advanced PD. It is important that clinicians fully understand this target when considering GPi DBS for individual patients.

METHODS

The literature on GPi DBS in PD has been comprehensively reviewed, including the anatomy, physiology and potential pitfalls that may be encountered during surgical targeting and post-operative management. Here, we review and address the implications of lead location on GPi DBS outcomes. Additionally, we provide a summary of randomized controlled clinical trials conducted on DBS in PD, together with expert commentary on potential applications of the GPi as target. Finally, we highlight future technologies that will likely impact GPi DBS, including closed-loop adaptive approaches (e.g. sensing-stimulating capabilities), advanced methods for image-based targeting and advances in DBS programming, including directional leads and pulse shaping.

RESULTS

There are important disease characteristics and factors to consider prior to selecting the GPi as the DBS target of PD surgery. Prior to and during implantation of the leads it is critical to consider the neuroanatomy, which can be defined through the combination of image-based targeting and intraoperative microelectrode recording strategies. There is an increasing body of literature on GPi DBS in patients with PD suggesting both short- and long-term benefits. Understanding the GPi target can be useful in choosing between the subthalamic (STN), GPi and ventralis intermedius nucleus as lead locations to address the motor symptoms and complications of PD.

CONCLUSION

GPi DBS can be effectively used in select cases of PD. As the ongoing DBS target debate continues (GPi vs. STN as DBS target), clinicians should keep in mind that GPi DBS has been shown to be an effective treatment strategy for a variety of symptoms, including bradykinesia, rigidity and tremor control. GPi DBS also has an important, direct anti-dyskinetic effect. GPi DBS is easier to program in the outpatient setting and will allow for more flexibility in medication adjustments (e.g. levodopa). Emerging technologies, including GPi closed-loop systems, advanced tractography-based targeting and enhanced programming strategies, will likely be future areas of GPi DBS expansion. We conclude that although the GPi as DBS target may not be appropriate for all PD patients, it has specific clinical advantages.

Comparison of electrodiagnosis, neurosonography and MR neurography in localization of ulnar neuropathy at the elbow

INTRODUCTION

In patients with ulnar neuropathy at the elbow (UNE) the precise determination of the site of lesion is important for subsequent differential diagnostic considerations and therapeutic management. Due to a paucity of comparable data, to better define the role of different diagnostic tests, we performed the first prospective study comparing the diagnostic accuracy of short segment nerve stimulation, nerve ultrasonography, MR neurography (MRN), and diffusion tensor imaging (DTI) in patients with UNE.

METHODS

UNE was clinically diagnosed in 17 patients with 18 affected elbows. For all 18 affected elbows in patients and 20 elbows in 10 healthy volunteers, measurements of all different diagnostic tests were performed at six anatomical positions across the elbow with measuring points from distal (D4) to proximal (P6) in relation to the medial epicondyle (P0). Additional qualitative assessment regarding structural changes of surrounding nerve anatomy was conducted.

RESULTS

The difference between affected arms of patients and healthy control arms were most frequently the largest at measure intervals D2 to P0 and P0 to P2 for electrophysiological testing, or measure points P0 and P2 for all other devices, respectively. At both levels P0 and at P2, T2 contrast-to-noise ratio (CNR) of MRN and mean diffusivity (MD) of DTI-based MRN showed best accuracies.

DISCUSSION

This study revealed differences in diagnostic performance of tests concerning a specific location of UNE, with better results for T2 contrast to noise ratio (CNR) in MRN and mean diffusivity of DTI-based MRN. Additional testing with MRN and nerve ultrasonography is recommended to uncover anatomical changes.

Optimisation of T2 and T2* sequences in MRI for better quantification of iron on transfused dependent sickle cell patients

This work aimed to investigate the effect of different shim techniques, voxel sizes, and repetition time (TR) on using theT2 and T2* sequences to determine their optimum settings to investigate the quantification of iron in transfused dependent sickle cell patients. The effect of each of these parameters was investigated on phantoms of different Gadolinium (Gd) concentrations, on 10 volunteers and 25 patients using a1 5T MRI Philips scanner. No significant difference between the three shim techniques was noticed in either T2 or T2* sequence measurements. Pixel sizes of 1 × 1 and 2 × 2 mm provided optimum results for T2 measurements. At 1 × 1 mm pixel size the T2* measurements experienced less error in measurements than the size of 2.5 × 2.5 mm used in the literature. Even though the slice thickness variation did not provide any changes in T2 measurements, the 12 mm provided optimum T2* measurements. TR variation did not yield significant changes on either T2 or T2* measurements. These results indicate that both T2 and T2* sequences can be further improved by providing more reliable measurements and reducing acquisition time.

Survey of MRI Usefulness for the Clinical Assessment of Bone Microstructure

Bone microarchitecture has been shown to provide useful information regarding the evaluation of skeleton quality with an added value to areal bone mineral density, which can be used for the diagnosis of several bone diseases. Bone mineral density estimated from dual-energy X-ray absorptiometry (DXA) has shown to be a limited tool to identify patients' risk stratification and therapy delivery. Magnetic resonance imaging (MRI) has been proposed as another technique to assess bone quality and fracture risk by evaluating the bone structure and microarchitecture. To date, MRI is the only completely non-invasive and non-ionizing imaging modality that can assess both cortical and trabecular bone in vivo. In this review article, we reported a survey regarding the clinically relevant information MRI could provide for the assessment of the inner trabecular morphology of different bone segments. The last section will be devoted to the upcoming MRI applications (MR spectroscopy and chemical shift encoding MRI, solid state MRI and quantitative susceptibility mapping), which could provide additional biomarkers for the assessment of bone microarchitecture.

7-T MRI for brain virtual autopsy: a proof of concept in comparison to 3-T MRI and CT

The detection and assessment of cerebral lesions and traumatic brain injuries are of particular interest in forensic investigations in order to differentiate between natural and traumatic deaths and to reconstruct the course of events in case of traumatic deaths. For this purpose, computed tomography (CT) and magnetic resonance imaging (MRI) are applied to supplement autopsy (traumatic death) or to supplant autopsy (natural deaths). This approach is termed “virtual autopsy.” The value of this approach increases as more microlesions and traumatic brain injuries are detected and assessed. Focusing on these findings, this article describes the examination of two decedents using CT, 3-T, and 7-T MRI. The main question asked was whether there is a benefit in using 7-T over 3-T MRI. To answer this question, the 3-T and 7-T images were graded regarding the detectability and the assessability of coup/contrecoup injuries and microlesions using 3-point Likert scales. While CT missed these findings, they were detectable on 3-T and 7-T MRI. However, the 3-T images appeared blurry in direct comparison with the 7-T images; thus, the detectability and assessability of small findings were hampered on 3-T MRI. The potential benefit of 7-T over 3-T MRI is discussed.

Imaging of the human subthalamic nucleus

The human subthalamic nucleus (STN) is a small lens shaped iron rich nucleus, which has gained substantial interest as a target for deep brain stimulation surgery for a variety of movement disorders. The internal anatomy of the human STN has not been fully elucidated, and an intensive debate, discussing the level of overlap between putative limbic, associative, and motor zones within the STN is still ongoing. In this chapter, we have summarized anatomical information obtained using different neuroimaging modalities focusing on the anatomy of the STN. Additionally, we have highlighted a number of major challenges faced when using magnetic resonance imaging (MRI) approaches for the visualization of small iron rich deep brain structures such as the STN. In vivo MRI and postmortem microscopy efforts provide valuable complementary information on the internal structure of the STN, although the results are not always fully aligned. Finally, we provide an outlook on future efforts that could contribute to the development of an integrative research approach that will help with the reconciliation of seemingly divergent results across research approaches.

3 versus 7 Tesla magnetic resonance imaging for parcellations of subcortical brain structures in clinical settings

7 Tesla (7T) magnetic resonance imaging holds great promise for improved visualization of the human brain for clinical purposes. To assess whether 7T is superior regarding localization procedures of small brain structures, we compared manual parcellations of the red nucleus, subthalamic nucleus, substantia nigra, globus pallidus interna and externa. These parcellations were created on a commonly used clinical anisotropic clinical 3T with an optimized isotropic (o)3T and standard 7T scan. The clinical 3T MRI scans did not allow delineation of an anatomically plausible structure due to its limited spatial resolution. o3T and 7T parcellations were directly compared. We found that 7T outperformed the o3T MRI as reflected by higher Dice scores, which were used as a measurement of interrater agreement for manual parcellations on quantitative susceptibility maps. This increase in agreement was associated with higher contrast to noise ratios for smaller structures, but not for the larger globus pallidus segments. Additionally, control-analyses were performed to account for potential biases in manual parcellations by assessing semi-automatic parcellations. These results showed a higher consistency for structure volumes for 7T compared to optimized 3T which illustrates the importance of the use of isotropic voxels for 3D visualization of the surgical target area. Together these results indicate that 7T outperforms c3T as well as o3T given the constraints of a clinical setting.

Methodological Considerations for Neuroimaging in Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson's Disease Patients

Deep brain stimulation (DBS) of the subthalamic nucleus is a neurosurgical intervention for Parkinson's disease patients who no longer appropriately respond to drug treatments. A small fraction of patients will fail to respond to DBS, develop psychiatric and cognitive side-effects, or incur surgery-related complications such as infections and hemorrhagic events. In these cases, DBS may require recalibration, reimplantation, or removal. These negative responses to treatment can partly be attributed to suboptimal pre-operative planning procedures via direct targeting through low-field and low-resolution magnetic resonance imaging (MRI). One solution for increasing the success and efficacy of DBS is to optimize preoperative planning procedures via sophisticated neuroimaging techniques such as high-resolution MRI and higher field strengths to improve visualization of DBS targets and vasculature. We discuss targeting approaches, MRI acquisition, parameters, and post-acquisition analyses. Additionally, we highlight a number of approaches including the use of ultra-high field (UHF) MRI to overcome limitations of standard settings. There is a trade-off between spatial resolution, motion artifacts, and acquisition time, which could potentially be dissolved through the use of UHF-MRI. Image registration, correction, and post-processing techniques may require combined expertise of traditional radiologists, clinicians, and fundamental researchers. The optimization of pre-operative planning with MRI can therefore be best achieved through direct collaboration between researchers and clinicians.

Fabrication and validation of reference structures for the localization of subdural standard- and micro-electrodes in MRI

OBJECTIVE

Report simple reference structure fabrication and validate the precise localization of subdural micro- and standard electrodes in magnetic resonance imaging (MRI) in phantom experiments.

APPROACH

Electrode contacts with diameters of 0.3 mm and 4 mm are localized in 1.5 T MRI using reference structures made of silicone and iron oxide nanoparticle doping. The precision of the localization procedure was assessed for several standard MRI sequences and implant orientations in phantom experiments and compared to common clinical localization procedures.

MAIN RESULTS

A localization precision of 0.41 ± 0.20 mm could be achieved for both electrode diameters compared to 1.46 ± 0.69 mm that was achieved for 4 mm standard electrode contacts localized using a common clinical standard method. The new reference structures are intrinsically bio-compatible, and they can be detected with currently available feature detection software so that a clinical implementation of this technology should be feasible.

SIGNIFICANCE

Neuropathologies are increasingly diagnosed and treated with subdural electrodes, where the exact localization of the electrode contacts with respect to the patient's cortical anatomy is a prerequisite for the procedure. Post-implantation electrode localization using MRI may be advantageous compared to the common alternative of CT-MRI image co-registration, as it avoids systematic localization errors associated with the co-registration itself, as well as brain shift and implant movement. Additionally, MRI provides superior soft tissue contrast for the identification of brain lesions without exposing the patient to ionizing radiation. Recent studies show that smaller electrodes and high-density electrode grids are ideal for clinical and research purposes, but the localization of these devices in MRI has not been demonstrated.