Registration of 3D Fetal Brain US and MRI

We propose a novel method for registration of 3D fetal brain ultrasound and a reconstructed magnetic resonance fetal brain volumes. The reconstructed MR volume is first segmented using a probabilistic atlas and an ultrasound-like image volume is simulated from the segmentation of the MR image. This ultrasound-like image volume is then affinely aligned with real ultrasound volumes of 27 fetal brains using a robust block-matching approach which can deal with intensity artefacts and missing features in ultrasound images. We show that this approach results in good overlap of four small structures. The average of the co-aligned US images shows good correlation with anatomy of the fetal brain as seen in the MR reconstruction

Partial Volume Segmentation of Brain MRI Scans of any Resolution and Contrast

Partial voluming (PV) is arguably the last crucial unsolved problem in Bayesian segmentation of brain MRI with probabilistic atlases. PV occurs when voxels contain multiple tissue classes, giving rise to image intensities that may not be representative of any one of the underlying classes. PV is particularly problematic for segmentation when there is a large resolution gap between the atlas and the test scan, e.g., when segmenting clinical scans with thick slices, or when using a high-resolution atlas. In this work, we present PV-SynthSeg, a convolutional neural network (CNN) that tackles this problem by directly learning a mapping between (possibly multi-modal) low resolution (LR) scans and underlying high resolution (HR) segmentations. PV-SynthSeg simulates LR images from HR label maps with a generative model of PV, and can be trained to segment scans of any desired target contrast and resolution, even for previously unseen modalities where neither images nor segmentations are available at training. PV-SynthSeg does not require any preprocessing, and runs in seconds. We demonstrate the accuracy and flexibility of the method with extensive experiments on three datasets and 2,680 scans. The code is available at https://github.com/BBillot/SynthSeg.Comment: accepted for MICCAI 202

Widespread extrahippocampal NAA/(Cr+Cho) abnormalities in TLE with and without mesial temporal sclerosis

MR spectroscopy has demonstrated extrahippocampal NAA/(Cr+Cho) reductions in medial temporal lobe epilepsy with (TLE-MTS) and without (TLE-no) mesial temporal sclerosis. Because of the limited brain coverage of those previous studies, it was, however, not possible to assess differences in the distribution and extent of these abnormalities between TLE-MTS and TLE-no. This study used a 3D whole brain echoplanar spectroscopic imaging (EPSI) sequence to address the following questions: (1) Do TLE-MTS and TLE-no differ regarding severity and distribution of extrahippocampal NAA/(Cr+Cho) reductions? (2) Do extrahippocampal NAA/(Cr+Cho) reductions provide additional information for focus lateralization? Forty-three subjects (12 TLE-MTS, 13 TLE-no, 18 controls) were studied with 3D EPSI. Statistical parametric mapping (SPM2) was used to identify regions of significantly decreased NAA/(Cr+Cho) in TLE groups and in individual patients. TLE-MTS and TLE-no had widespread extrahippocampal NAA/(Cr+Cho) reductions. NAA/(Cr+Cho) reductions had a bilateral fronto-temporal distribution in TLE-MTS and a more diffuse, less well defined distribution in TLE-no. Extrahippocampal NAA/(Cr+Cho) decreases in the single subject analysis showed a large inter-individual variability and did not provide additional focus lateralizing information. Extrahippocampal NAA/(Cr+Cho) reductions in TLE-MTS and TLE-no are neither focal nor homogeneous. This reduces their value for focus lateralization and suggests a heterogeneous etiology of extrahippocampal spectroscopic metabolic abnormalities in TLE

Automated ventricular systems segmentation in brain CT images by combining low-level segmentation and high-level template matching

<p>Abstract</p> <p>Background</p> <p>Accurate analysis of CT brain scans is vital for diagnosis and treatment of Traumatic Brain Injuries (TBI). Automatic processing of these CT brain scans could speed up the decision making process, lower the cost of healthcare, and reduce the chance of human error. In this paper, we focus on automatic processing of CT brain images to segment and identify the ventricular systems. The segmentation of ventricles provides quantitative measures on the changes of ventricles in the brain that form vital diagnosis information.</p> <p>Methods</p> <p>First all CT slices are aligned by detecting the ideal midlines in all images. The initial estimation of the ideal midline of the brain is found based on skull symmetry and then the initial estimate is further refined using detected anatomical features. Then a two-step method is used for ventricle segmentation. First a low-level segmentation on each pixel is applied on the CT images. For this step, both Iterated Conditional Mode (ICM) and Maximum A Posteriori Spatial Probability (MASP) are evaluated and compared. The second step applies template matching algorithm to identify objects in the initial low-level segmentation as ventricles. Experiments for ventricle segmentation are conducted using a relatively large CT dataset containing mild and severe TBI cases.</p> <p>Results</p> <p>Experiments show that the acceptable rate of the ideal midline detection is over 95%. Two measurements are defined to evaluate ventricle recognition results. The first measure is a sensitivity-like measure and the second is a false positive-like measure. For the first measurement, the rate is 100% indicating that all ventricles are identified in all slices. The false positives-like measurement is 8.59%. We also point out the similarities and differences between ICM and MASP algorithms through both mathematically relationships and segmentation results on CT images.</p> <p>Conclusion</p> <p>The experiments show the reliability of the proposed algorithms. The novelty of the proposed method lies in its incorporation of anatomical features for ideal midline detection and the two-step ventricle segmentation method. Our method offers the following improvements over existing approaches: accurate detection of the ideal midline and accurate recognition of ventricles using both anatomical features and spatial templates derived from Magnetic Resonance Images.</p

Quantifying resilience of humans and other animals

All life requires the capacity to recover from challenges that are as inevitable as they are unpredictable. Understanding this resilience is essential for managing the health of humans and their livestock. It has long been difficult to quantify resilience directly, forcing practitioners to rely on indirect static indicators of health. However, measurements from wearable electronics and other sources now allow us to analyze the dynamics of physiology and behavior with unsurpassed resolution. The resulting flood of data coincides with the emergence of novel analytical tools for estimating resilience from the pattern of micro-recoveries observed in natural time series. Such dynamic indicators of resilience (DIORs) may be used to monitor the risk of systemic failure across systems ranging from organs to entire organisms. These tools invite a fundamental rethink of our approach to the adaptive management of health and resilience

Concordance and Discordance Between Brain Perfusion and Atrophy in Frontotemporal Dementia

The aim of this study was to determine if a dissociation between reduced cerebral perfusion and gray matter (GM) atrophy exists in frontotemporal dementia (FTD). The study included 28 patients with FTD and 29 cognitive normal (CN) subjects. All subjects had MRI at 1.5 T, including T1-weighted structural and arterial spin labeling (ASL) perfusion imaging. Non-parametric concordance/discordance tests revealed that GM atrophy without hypoperfusion occurs in the premotor cortex in FTD whereas concordant GM atrophy and hypoperfusion changes are found in the right prefrontal cortex and bilateral medial frontal lobe. The results suggest that damage of brain function in FTD, assessed by ASL perfusion, can vary regionally despite widespread atrophy. Detection of discordance between brain perfusion and structure in FTD might aid diagnosis and staging of the disease

Deletion at ITPR1 Underlies Ataxia in Mice and Spinocerebellar Ataxia 15 in Humans

We observed a severe autosomal recessive movement disorder in mice used within our laboratory. We pursued a series of experiments to define the genetic lesion underlying this disorder and to identify a cognate disease in humans with mutation at the same locus. Through linkage and sequence analysis we show here that this disorder is caused by a homozygous in-frame 18-bp deletion in Itpr1 (Itpr1Δ18/Δ18), encoding inositol 1,4,5-triphosphate receptor 1. A previously reported spontaneous Itpr1 mutation in mice causes a phenotype identical to that observed here. In both models in-frame deletion within Itpr1 leads to a decrease in the normally high level of Itpr1 expression in cerebellar Purkinje cells. Spinocerebellar ataxia 15 (SCA15), a human autosomal dominant disorder, maps to the genomic region containing ITPR1; however, to date no causal mutations had been identified. Because ataxia is a prominent feature in Itpr1 mutant mice, we performed a series of experiments to test the hypothesis that mutation at ITPR1 may be the cause of SCA15. We show here that heterozygous deletion of the 5′ part of the ITPR1 gene, encompassing exons 1–10, 1–40, and 1–44 in three studied families, underlies SCA15 in humans

Frequency of KCNC3 DNA Variants as Causes of Spinocerebellar Ataxia 13 (SCA13)

Gain-of function or dominant-negative mutations in the voltage-gated potassium channel KCNC3 (Kv3.3) were recently identified as a cause of autosomal dominant spinocerebellar ataxia. Our objective was to describe the frequency of mutations associated with KCNC3 in a large cohort of index patients with sporadic or familial ataxia presenting to three US ataxia clinics at academic medical centers.DNA sequence analysis of the coding region of the KCNC3 gene was performed in 327 index cases with ataxia. Analysis of channel function was performed by expression of DNA variants in Xenopus oocytes.Sequence analysis revealed two non-synonymous substitutions in exon 2 and five intronic changes, which were not predicted to alter splicing. We identified another pedigree with the p.Arg423His mutation in the highly conserved S4 domain of this channel. This family had an early-onset of disease and associated seizures in one individual. The second coding change, p.Gly263Asp, subtly altered biophysical properties of the channel, but was unlikely to be disease-associated as it occurred in an individual with an expansion of the CAG repeat in the CACNA1A calcium channel.Mutations in KCNC3 are a rare cause of spinocerebellar ataxia with a frequency of less than 1%. The p.Arg423His mutation is recurrent in different populations and associated with early onset. In contrast to previous p.Arg423His mutation carriers, we now observed seizures and mild mental retardation in one individual. This study confirms the wide phenotypic spectrum in SCA13