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Barth, M.

Publications and source records attributed to Barth, M..

At least 19 recordsLinked to original sources

A geometric anthropomorphic phantom for quantitative susceptibility mapping: accuracy and repeatability

Quantitative Susceptibility Mapping (QSM) relies on a tissue's underlying macroscopic geometry to lead to measurable orientation-dependent field perturbations. To understand and assess QSM error in vivo, anthropomorphic phantoms provide a useful model that mimic the electromagnetic properties and morphology of underlying tissue. Herein, we designed and manufactured an MRI compatible anthropomorphic phantom with cylindrical and spheroid compartments containing realistic susceptibilities to mimic hemorrhages, calcifications, and blood vessels. We estimated accuracy ({epsilon}, bias, RMSE) and repeatability (RC) of MEDI-susceptibility measurements within ROIs. We evaluated voxel-based agreement to validate susceptibility mapping under different acquisition conditions (3T versus 7T) and reconstruction algorithms (COSMOS versus MEDI). Reliable MEDI-based susceptibility measurements were obtained from ellipsoids but not from straws. The ellipsoids (|{epsilon}| = 0.007 to 0.083 ppm at 3T; 0.050 to 0.118 ppm at 7T) were more accurate than the straws (|{epsilon}| = 0.084 to 0.190 ppm at 3T; 0.105 to 0.160 ppm at 7T). The repeatability coefficient across all 6 ROIs (RC = 0.652 ppm at 3T; 0.459 ppm at 7T) was substantially larger than across the 4 ellipsoid ROIs only (RC' = 0.168 ppm at 3T; 0.141 ppm at 7T). The accuracy at 3T (bias = -0.002 ppm, RMSE = 0.082 ppm) was better than the accuracy at 7T (bias = -0.056 ppm, RMSE = 0.092 ppm). Using voxels from the 4 ellipsoid ROIs, we observed excellent agreement between COSMOS and MEDI susceptibility maps at 3T, with linear regression of y=1.00x-0.01 (r=0.99). We observed some underestimation of MEDI susceptibility maps relative to COSMOS at 7T, with linear regression and y=0.93x-0.04 (r=0.99). The results imply that QSM reconstructions are reliable with 3T scanners but can be challenging with 7T scanners at high magnetic susceptibilities.

biophysics↗

Automated Segmentation of Prostatic Gold Fiducial Markers for MR-Only Radiotherapy Planning Using Multi-Modal Consensus Deep Learning

PurposeTo develop and evaluate a multi-model consensus deep learning approach for automated gold fiducial marker (FM) segmentation in T1-weighted prostate MRI. Materials and MethodsIn this retrospective study, T1-weighted MRI and CT-derived reference standard segmentations were collected from 127 prostate cancer patients (all male; mean age, 70 years {+/-} 7 [standard deviation]; age range, 50-88 years; collected between October 2020 and January 2026) who each had three implanted gold FMs. A 3D U-Net was trained on 93 subjects using four random seeds to produce an ensemble. At inference, marker-class probability maps were averaged across models and the top three connected components selected. Performance was evaluated on 34 temporally held-out subjects (9 tuning, 25 test) using marker-level sensitivity and precision with exact (Clopper-Pearson) 95% confidence intervals (CIs). A model count ablation study was performed. The pipeline was deployed for on-scanner processing on Siemens MRI systems via the OpenRecon framework and as a browser-based application using WebAssembly, executing entirely client-side. ResultsThe four-model consensus achieved 96% (70 of 73) sensitivity and 95% (70 of 74) precision on 25 test subjects, with 29 of 34 (85%) subjects achieving perfect marker detection. Single models had a mean sensitivity of 84% (SD, 9%), improving to 96% with four-model consensus (SD, <1%). ConclusionMulti-model consensus deep learning substantially improved FM segmentation reliability over individual models, achieving high sensitivity and precision using only routinely acquired T1-weighted MRI.

bioinformatics↗

Mitochondrial protein import stress causes progressive neurodegeneration opposed by PERK - eIF2α signalling

Mitochondrial dysfunction and impairments of the mitochondrial protein import system are often linked to neurodegenerative disease, but whether import stress per se causes neurodegeneration has not been tested. Here, we adapted the yeast clogger system to Drosophila motoneurons to block TOM-TIM23-mediated import with temporal control. Sustained import stress converts somatic mitochondria into donut-shaped structures, depletes functional mitochondria from synaptic terminals, and causes progressive neurodegeneration with impaired neurotransmitter release and locomotor dysfunction. This neurodegeneration is mechanistically distinct from mitochondrial absence, as miro mutant neurons that completely lack presynaptic mitochondria do not degenerate. Import-stressed motoneurons activate multiple protective programmes, including chaperone remodelling, metabolic repression, and translational control through the eIF2 kinase PERK. Both pharmacological PERK inhibition and reversal of translational attenuation via ISRIB accelerate neurodegeneration, whereas PERK overexpression alone is sufficient to cause it, defining a protective range of eIF2-dependent translational control. The observation that PERK inhibition is protective in protein misfolding models but detrimental during import stress shows that the nature of mitochondrial dysfunction determines the molecular consequence of translational control in neurodegeneration.

neuroscience↗

Ultra-high field fMRI reveals functional patterns consistent with columnar organisation in human somatosensory cortex

In animal models, the primary somatosensory cortex (S1) exhibits columnar organisation, where vertically arranged neurons share functional properties. In humans, however, the thinness and folding of S1 have limited non-invasive investigations of such columnar structures. In this study, we aimed to identify columns in human S1 by delivering alternating bursts of 3 Hz and 30 Hz fingertip vibration while acquiring functional MRI time series at 7 Tesla. Using cortical surface modelling, we identified functional patterns in S1 that showed higher reliability, stronger differential responses, and greater statistical sensitivity than those observed in a frontal cortex control region (p = .001-.012 for reliability; p < .001 for differential signal; p = .004-.011 for sensitivity). Laminar analyses revealed depth-consistent frequency preferences in approximately 20-45% of S1 nodes, a pattern compatible with vertically organised functional structure. Although the relative signal difference between 3 Hz and 30 Hz was small (0.14% signal change), frequency tuning was reliably observed. Taken together, these findings reveal functional patterns in human S1 consistent with aspects of columnar-like organisation, providing non-invasive evidence of fine-scale functional architecture. TeaserfMRI reveals highly reliable but modestly selective responses in human S1, consistent with column-like functional organisation.

neuroscience↗

T1-weighted fMRI in mouse visual cortex using an Iron Oxide Nanoparticle contrast agent and Ultrashort Echo Time (UTE) imaging at 9.4 T

PurposeThis study aims to investigate the feasibility of using T1-weighted fMRI with an iron oxide nanoparticle contrast agent and Ultrashort Echo Time (UTE) imaging at 9.4T to measure functional hyperaemia in the mouse visual cortex. The goal is to capture positive signal changes in both the parenchyma and pial surface, and to test whether surface vessels respond during neuronal activation. MethodsThe study involved scanning of nine mice after administration of iron oxide-based superparamagnetic contrast agent (Molday ION) via the tail vein. Two functional imaging experiments were conducted: one to investigate the effect of echo time on the functional response, and another to characterize the impact of higher resolution on UTE functional contrast. Regions of interest (ROIs) were defined in the parenchyma and pial surface of the visual cortex. ResultsThe administration of the contrast agent produced a bright-blood signal in the vasculature in structural MRI when using a UTE acquisition. Positive signal changes were observed at the shortest echo time (0.164 ms) in both the parenchyma (0.2% {+/-} 0.08) and pial surface (0.2% {+/-} 0.1 %), providing evidence that UTE fMRI experiments can detect changes in both pial and parenchymal vessels. Measurements using longer echo times ([&ge;]1 ms) showed negative signal changes. Higher spatial resolution resulted in increased percent signal change at the pial surface, suggesting less partial volume effects and better delineation of surface vessels. ConclusionThe findings demonstrate that T1-weighted fMRI with UTE imaging and iron oxide nanoparticles captures positive signal changes across all vascular compartments, providing additional insights into the involvement of surface vessels during functional hyperemia.

neuroscience↗

VesselBoost: A Python Toolbox for Small Blood Vessel Segmentation in Human Magnetic Resonance Angiography Data

Magnetic resonance angiography (MRA) performed at ultra-high magnetic field provides a unique opportunity to study the arteries of the living human brain at the mesoscopic level. From this, we can gain new insights into the brains blood supply and vascular disease affecting small vessels. However, for quantitative characterization and precise representation of human angioarchitecture to, for example, inform blood-flow simulations, detailed segmentations of the smallest vessels are required. Given the success of deep learning-based methods in many segmentation tasks, we here explore their application to high-resolution MRA data, and address the difficulty of obtaining large data sets of correctly and comprehensively labelled data. We introduce VesselBoost, a vessel segmentation package, which utilizes deep learning and imperfect training labels for accurate vasculature segmentation. Combined with an innovative data augmentation technique, which leverages the resemblance of vascular structures, VesselBoost enables detailed vascular segmentations.

neuroscience↗

Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subjects sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1{+/-}6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44[&le;]r[&le;]0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21[&ge;]r[&ge;]-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20[&ge;]r[&ge;]-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39[&le;]r[&le;]0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22[&ge;]r[&ge;]-0.25). Linear mixture of sex and age explained 26{+/-}10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33{+/-}11% when body height was added into the mixture model. Age itself explained only 2{+/-}2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.

neuroscience↗

Guidelines for QSM phantom production and evaluation ofcandidate phantom materials

PurposeTo measure magnetic susceptibility ({chi}) with Quantitative Susceptibility Mapping (QSM) and evaluate its repeatability using four phantom doping materials relevant to QSM applications. MethodsA cylindrical phantom was constructed containing vials of agarose gel doped with two paramagnetic materials (ferritin, USPIO) and two diamagnetic materials (CaCl2, CaCO3) at five concentrations each. Single orientation QSM measurements (MEDI+0) were carried out on the phantom at 3T and 7T. We measured molar susceptibility ({chi}mol) from QSM and evaluated the test-retest repeatability of {chi} using the standard error of the measurement (SEM). We evaluated material lifespan by conducting a t-test of {chi}mol at various timepoints. Results{chi}mol (ppm{middle dot}L{middle dot}mmol-1) were measured as 1.67 {+/-} 0.24 and 0.74 {+/-} 0.09 (USPIO: 3T and 7T, respectively), 10-2x(8.13 {+/-} 1.35; 8.13 {+/-} 1.19) (Ferritin: 3T; 7T), 10-4x(-2.68 {+/-} 0.24; -2.71 {+/-} 0.37) (CaCl2: 3T; 7T), and 10-5x(-9.52 {+/-} 1.44; -9.53 {+/-} 1.18) (CaCO3: 3T; 7T). The USPIO SEM (1.5 {+/-} 2.0; 5.1 {+/-} 2.0 ppb at 3T; 7T) was greater than the ferritin SEM (1.2 {+/-} 1.0; 2.2 {+/-} 1.3 ppb at 3T; 7T). The CaCl2 SEM (7.5 {+/-} 5.5; 1.2 {+/-} 0.6 ppb at 3T; 7T) was greater than the CaCO3 SEM (1.2 {+/-} 0.6; 0.9 {+/-} 0.7 ppb at 3T; 7T). We observed no significant changes in molar susceptibility for ferritin and CaCO3 over the measured timeframes (24 months and 15 months, respectively). ConclusionWe recommend using ferritin and CaCO3 in the construction of susceptibility phantoms, removing later echo times for CaCO3 QSM reconstructions.

biophysics↗

The quest for improved biohydrogen formation: are heat shocks the solution?

BackgroundThe integration of anaerobic digestion into bio-based industries can create synergies, which help to make anaerobic digestion self-sustaining. Two-stage digesters with separate acidification stages allow to produce green hydrogen and short-chain fatty acids, which are promising industrial products. Heat shocks can be used to foster the production of these products. However, the practical applicability is oft not addressed sufficiently. The here presented work aims to close this gap. MethodsBatch experiments were conducted in 5 litre double-walled tank reactors incubated at 37 {degrees}C. Short microwave heat shocks of 25 min duration and exposure times of 5 - 10 min at 80 {degrees}C were performed and compared to oven heat shocks. Pairwise experimental group differences for gas production and chemical parameters were determined using ANOVA and post-hoc tests. High-throughput 16S rRNA gene amplicon sequencing was performed to analyse taxonomic profiles. ResultsHeat shocking the entire seed sludge, the highest hydrogen productivity was observed at a substrate load of 50 g/l with 1.09 mol H2/mol hexose. With 1.01 mol H2/mol hexose, microwave assisted treatment was not significantly different from oven-based treatments. The study emphasised the better repeatability of heat shocks with microwave-assisted experiments, showing low variation coefficients averaging 29 %. Microwave pre-treatment indicates a high predictability and a stronger microbiome shift to Clostridia than the oven. The pre-treatment of heat shocks supported the formation of butyric acid up to 10.8 g/l in average and a peak of 24.01 g/l at a butyric/acetic acid ratio of 2.0. ConclusionResults show the suitability to heat shock the entire seed sludge rather than just a small inoculum, which makes the process more relevant for industrial application. A microwave-based treatment has proven to be a promising alternative to oven-based treatments, which ultimately might facilitate the implementation into industrial systems. The approach becomes economically sustainable with high-temperature heat pumps with a coefficient of performance (COP) of 4.3.

bioengineering↗

Deep-Learning-Enabled Differentiation between Intraprostatic Gold Fiducial Markers and Calcification in Quantitative Susceptibility Mapping

PurposeInterest is growing in MR-only radiotherapy (RT) planning for prostate cancer (PCa) due to the potential reductions in cost and patient exposure to radiation, and a more streamlined work-flow and patient imaging pathway. However, in MRI, the gold fiducial markers (FMs) used for target localization appear as signal voids, complicating differentiation from other void sources such as calcifications and bleeds. This work investigates using Quantitative Susceptibility Mapping (QSM), an MRI phase post-processing technique, to aid in the differentiation task. It also presents deep learning models that capture nuanced information and automate the segmentation task, facilitating a streamlined approach to MR-only RT. MethodsCT and MRI, including GRE and T1-weighted imaging, were acquired from 26 PCa patients, each with three implanted gold FMs. GRE data were post-processed into QSM, T 2*, and R2* maps using QSMxTs body imaging pipeline. Statistical analyses were conducted to investigate the quantitative differentiation of FMs and calcification in each contrast. 3D U-Nets were developed using fastMONAI to automate the segmentation task using various combinations of MR-derived contrasts, with a model trained on CT used as a baseline. Models were evaluated using precision and recall calculated using a leave-one-out cross-validation scheme. ResultsSignificant differences were observed between FM and calcification regions in CT, QSM and T 2*, though overlap was observed in QSM and T 2*. The baseline CT U-Net achieved an FM-level precision of {approx} 98% and perfect recall. The best-performing QSM-based model achieved precision and recall of 80% and 90%, respectively, while conventional MRI had values below 70% and 80%, respectively. The QSM-based model produced segmentations with good agreement with the ground truth, including a challenging FM that coincided with a bleed. ConclusionThe model performance highlights the value of using QSM over indirect measures in MRI, such as signal voids in magnitude-based contrasts. The results also indicate that a U-Net can capture more information about the presentation of FMs and other sources than would be possible using susceptibility quantification alone, which may be less reliable due to the diverse presentation of sources across a patient population. In our study, QSM was a reliable discriminator of FMs and other sources in the prostate, facilitating an accurate and streamlined approach to MR-only RT.

pathology↗

HumanBrainAtlas: an in vivo MRI dataset for detailed segmentations

We introduce HumanBrainAtlas, an initiative to construct a highly detailed, open-access atlas of the living human brain that combines high-resolution in vivo MR imaging and detailed segmentations previously possible only in histological preparations. Here, we present and evaluate the first step of this initiative: a comprehensive dataset of two healthy male volunteers reconstructed to a 0.25 mm3 isotropic resolution for T1w, T2w and DWI contrasts. Multiple high-resolution acquisitions were collected for each contrast and each participant, followed by averaging using symmetric group-wise normalisation (Advanced Normalisation Tools). The resulting image quality permits structural parcellations rivalling histology-based atlases, while maintaining the advantages of in vivo MRI. For example, components of the thalamus, hypothalamus, and hippocampus - difficult or often impossible to identify using standard MRI protocols, can be identified within the present data. Our data are virtually distortion free, fully 3D, and compatible with existing in vivo Neuroimaging analysis tools. The dataset is suitable for teaching and is publicly available via our website (www.hba.neura.edu.au), which also provides data processing scripts. Instead of focusing on coordinates in an averaged brain space, our approach focuses on providing an example segmentation at great detail in the high quality individual brain, this serves as an illustration on what features contrasts and relations can be used to interpret MRI datasets, in research, clinical and education settings.

neuroscience↗

Molecular evolution of classic Hodgkin lymphoma revealed through whole genome sequencing of Hodgkin and Reed Sternberg cells

The rarity of malignant Hodgkin and Reed Sternberg (HRS) cells within a classic Hodgkin lymphoma (cHL) biopsy limits the ability to study the genomics of cHL. To circumvent this, our group has previously optimized fluorescence-activated cell sorting to purify HRS cells. Here we leveraged this method to report the first whole genome sequencing landscape of HRS cells and reconstruct the chronology and likely etiology of pathogenic events prior to the clinical diagnosis of cHL. We identified alterations in driver genes not previously described in cHL, a high activity of the APOBEC mutational signature, and the presence complex structural variants including chromothripsis. We found that the high ploidy observed in cHL is often acquired through multiple, independent large chromosomal gain events including whole genome duplication. The first of these likely occurs several years prior to the diagnosis of cHL, and the last gains typically occur very close to the time of diagnosis. Evolutionary timing analyses revealed that driver mutations in B2M, BCL7A, GNA13, and PTPN1, and the onset of AID driven mutagenesis usually preceded large chromosomal gains. The study provides the first temporal reconstruction of cHL pathogenesis and suggests a relatively long time course between the first pathogenic event and the clinical diagnosis.

cancer biology↗

Modelling the depth-dependent VASO and BOLD responses in human primary visual cortex

Functional magnetic resonance imaging (fMRI) using a blood-oxygenation-level-dependent (BOLD) contrast is a common method for studying human brain function non-invasively. Gradient-echo (GRE) BOLD is highly sensitive to the blood oxygenation change in blood vessels; however, the spatial signal specificity can be degraded due to signal leakage from activated lower layers to superficial layers in depth-dependent (also called laminar or layer-specific) fMRI. Alternatively, physiological variables such as cerebral blood volume using the VAscular-Space-Occupancy (VASO) contrast have shown higher spatial specificity compared to BOLD. To better understand the physiological mechanisms such as blood volume and oxygenation changes and to interpret the measured depth-dependent responses, models are needed which reflect vascular properties at this scale. For this purpose, we extended and modified the "cortical vascular model" previously developed to predict layer-specific BOLD signal changes in human primary visual cortex to also predict a layer-specific VASO response. To evaluate the model, we compared the predictions with experimental results of simultaneous VASO and BOLD measurements in a group of healthy participants. Fitting the model to our experimental data provided an estimate of CBV change in different vascular compartments upon neural activity. We found that stimulus-evoked CBV change mainly occurs in small arterioles, capillaries and intracortical arteries, and that the contribution from venules and ICVs is small. Our results confirm that VASO is less susceptible to large vessel effects compared to BOLD, as blood volume changes in intracortical arteries did not substantially affect the resulting depth-dependent VASO profiles, whereas depth-dependent BOLD profiles showed a bias towards signal contributions from intracortical veins.

neuroscience↗

QSMxT: Robust Masking and Artefact Reduction for Quantitative Susceptibility Mapping

PurposeQuantitative Susceptibility Mapping (QSM) is a post-processing technique applied to gradient-echo phase data. QSM algorithms require a signal mask to delineate regions with reliable phase signal for subsequent susceptibility estimation. Existing masking techniques used in QSM have limitations that introduce artefacts, exclude anatomical detail, and rely on parameter tuning and anatomical priors that narrow their application. Here, a robust masking and reconstruction procedure is presented to overcome these limitations and enable automated QSM processing for a wide range of use-cases implemented in an open-source software framework: QSMxT. MethodsA robust masking technique that automatically separates reliable from less reliable phase regions was developed and combined with a two-pass reconstruction procedure that operates on the separated sources before combination, extracting more information while reducing the influence of artefacts. ResultCompared with standard masking and reconstruction procedures, the two-pass inversion reduces streaking artefacts caused by unreliable phase and high dynamic ranges of susceptibility sources. QSMxT is robust across a range of datasets at 3 T in healthy volunteers and phantoms, at 7 T in tumour patients, and in the QSM challenge 2.0 simulated brain dataset, with significant artefact and error reductions, greater anatomical detail, and minimal parameter tuning. ConclusionQSMxT generates masks for QSM that separate reliable from less reliable phase regions, enables a more accurate QSM reconstruction that mitigates artefacts, operates without anatomical priors, and requires minimal parameter tuning. QSMxT makes QSM processing more accessible, reliable and reproducible.

neuroscience↗

LAG3 is not expressed in human and murine neurons and does not modulate α-synucleinopathies

While the initial pathology of Parkinsons disease and other -synucleinopathies is often confined to circumscribed brain regions, it can spread and progressively affect adjacent and distant brain locales. This process may be controlled by cellular receptors of -synuclein fibrils, one of which was proposed to be the LAG3 immune checkpoint molecule. Here, we analyzed the expression pattern of LAG3 in human and mouse brains. Using a variety of methods and model systems, we found no evidence for LAG3 expression by neurons. While we confirmed that LAG3 interacts with -synuclein fibrils, the specificity of this interaction appears limited. Moreover, overexpression of LAG3 in cultured human neural cells did not cause any worsening of -synuclein pathology ex vivo. The overall survival of A53T -synuclein transgenic mice was unaffected by LAG3 depletion and the seeded induction of -synuclein lesions in hippocampal slice cultures was unaffected by LAG3 knockout. These data suggest that the proposed role of LAG3 in the spreading of -synucleinopathies is not universally valid.

neuroscience↗

Assembly defects of the human tRNA splicing endonuclease contribute to impaired pre-tRNA processing in pontocerebellar hypoplasia

Introns of human transfer RNA precursors (pre-tRNAs) are excised by the tRNA splicing endonuclease TSEN in complex with the RNA kinase CLP1. Mutations in TSEN/CLP1 occur in patients with pontocerebellar hypoplasia (PCH), however, their role in the disease is unclear. Here, we show that intron excision is catalyzed by tetrameric TSEN assembled from inactive heterodimers independently of CLP1. Splice site recognition involves the mature domain and the anticodon-intron base pair of pre-tRNAs. The 2.1-[A] resolution X-ray crystal structure of a TSEN15-34 heterodimer and differential scanning fluorimetry analyses show that PCH mutations cause thermal destabilization. While endonuclease activity in recombinant mutant TSEN is unaltered, we observe assembly defects and reduced pre-tRNA cleavage activity resulting in an imbalanced pre-tRNA pool in PCH patient-derived fibroblasts. Our work defines the molecular principles of intron excision in humans and provides evidence that modulation of TSEN stability may contribute to PCH phenotypes.

biochemistry↗

Longitudinal Automatic Segmentation of Hippocampal Subfields (LASHiS) using Multi-Contrast MRI

The volumetric and morphometric examination of hippocampus formation subfields in a longitudinal manner using in vivo MRI could lead to more sensitive biomarkers for neuropsychiatric disorders and diseases including Alzheimers disease, as the anatomical subregions are functionally specialised. Longitudinal processing allows for increased sensitivity due to reduced confounds of inter-subject variability and higher effect-sensitivity than cross-sectional designs. We examined the performance of a new longitudinal pipeline (Longitudinal Automatic Segmentation of Hippocampus Subfields [LASHiS]) against three freely available, published approaches. LASHiS automatically segments hippocampus formation subfields by propagating labels from cross-sectionally labelled time point scans using joint-label fusion to a non-linearly realigned single subject template, where image segmentation occurs free of bias to any individual time point. Our pipeline measures tissue characteristics available in in vivo high-resolution MRI scans, at both clinical (3 Tesla) and ultra-high field strength (7 Tesla) and differs from previous longitudinal segmentation pipelines in that it leverages multi-contrast information in the segmentation process. LASHiS produces robust and reliable automatic multi-contrast segmentations of hippocampus formation subfields, as measured by higher volume similarity coefficients and Dice coefficients for test-retest reliability and robust longitudinal Bayesian Linear Mixed Effects results at 7 T, while showing sound results at 3 T. All code for this project including the automatic pipeline is available at https://github.com/CAIsr/LASHiS

neuroscience↗

Non-Linear Realignment Improves Hippocampus Subfield Segmentation

Participant movement can deleteriously affect MR image quality. Further, for the visualization and segmentation of small anatomical structures, there is a need to improve image quality, specifically signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), by acquiring multiple anatomical scans consecutively. We aimed to ameliorate movement artefacts and increase SNR in a high-resolution turbo spin-echo (TSE) sequence acquired thrice using non-linear realignment in order to improve segmentation consistency of the hippocampus subfields. We assessed the method in young healthy participants, Motor Neurone Disease patients, and age matched controls. Results show improved image segmentation of the hippocampus subfields when comparing template-based segmentations with individual segmentations with Dice overlaps N=51; ps < 0.001 (Friedmans test) and higher sharpness ps < 0.001 in non-linearly realigned scans as compared to linearly, and arithmetically averaged scans.

neuroscience↗