PAE planning: Radiation exposure and image quality of CT and CBCT

PURPOSE

To determine accurate organ doses, effective doses, and image quality of computed tomography (CT) compared with cone beam CT (CBCT) for correct identification of prostatic arteries.

METHOD

A dual-energy CT scanner and a flat-panel angiography system were used. Dose measurements (gallbladder (g), intestine (i), bladder (b), prostate (p), testes (t), active bone marrow of pelvis (bmp) and femura (bmf)) were performed using an anthropomorphic phantom with 65 thermoluminescent dosimeters in the pelvis and abdomen region. For the calculation of the contrast-to-noise ratio (CNR) of the pelvic arteries, a patient whose weight and height were almost identical to those of the phantom was selected for each examination type.

RESULTS

The effective dose of CT was 2.7 mSv and that of CBCT was 21.8 mSv. Phantom organ doses were lower for CT than for CBCT in all organs except the testes (g: 1.2 mGy vs. 3.3 mGy, i: 5.8 mGy vs. 23.9 mGy, b: 6.9 mGy vs. 19.4 mGy, p: 6.4 mGy vs. 13.2 mGy, t: 4.7 mGy vs. 2.4 mGy, bmp: 5.1 mGy vs. 18.2 mGy, bmf: 3.3 mGy vs. 6.6 mGy). For human pelvic arteries, the CNR of CT was better than that of CBCT, with the exception of one prostate artery that showed stenosis on CT. Evaluation by experienced radiologists also confirmed the better detectability of prostate arteries on CT examination.

CONCLUSIONS

In our study preprocedural CT had lower organ doses and better image quality comparedd with CBCT and should be considered for the correct identification of prostatic arteries.

Predicting disease-related MRI patterns of multiple sclerosis through GAN-based image editing

INTRODUCTION

Multiple sclerosis (MS) is a complex neurodegenerative disorder that affects the brain and spinal cord. In this study, we applied a deep learning-based approach using the StyleGAN model to explore patterns related to MS and predict disease progression in magnetic resonance images (MRI).

METHODS

We trained the StyleGAN model unsupervised using T1-weighted GRE MR images and diffusion-based ADC maps of MS patients and healthy controls. We then used the trained model to resample MR images from real input data and modified them by manipulations in the latent space to simulate MS progression. We analyzed the resulting simulation-related patterns mimicking disease progression by comparing the intensity profiles of the original and manipulated images and determined the brain parenchymal fraction (BPF).

RESULTS

Our results show that MS progression can be simulated by manipulating MR images in the latent space, as evidenced by brain volume loss on both T1-weighted and ADC maps and increasing lesion extent on ADC maps.

CONCLUSION

Overall, this study demonstrates the potential of the StyleGAN model in medical imaging to study image markers and to shed more light on the relationship between brain atrophy and MS progression through corresponding manipulations in the latent space.

Perfusion and T2 Relaxation Time as Predictors of Severity and Outcome in Sepsis-Associated Acute Kidney Injury: A Preclinical MRI Study

BACKGROUND

Preventing sepsis-associated acute kidney injury (S-AKI) can be challenging because it develops rapidly and is often asymptomatic. Probability assessment of disease progression for therapeutic follow-up and outcome are important to intervene and prevent further damage.

PURPOSE

To establish a noninvasive multiparametric MRI (mpMRI) tool, including T1 , T2 , and perfusion mapping, for probability assessment of the outcome of S-AKI.

STUDY TYPE

Preclinical randomized prospective study.

ANIMAL MODEL

One hundred and forty adult female SD rats (65 control and 75 sepsis).

FIELD STRENGTH/SEQUENCE

9.4T; T1 and perfusion map (FAIR-EPI) and T2 map (multiecho RARE).

ASSESSMENT

Experiment 1: To identify renal injury in relation to sepsis severity, serum creatinine levels were determined (31 control and 35 sepsis). Experiment 2: Animals underwent mpMRI (T1 , T2 , perfusion) 18 hours postsepsis. A subgroup of animals was immediately sacrificed for histology examination (nine control and seven sepsis). Result of mpMRI in follow-up subgroup (25 control and 33 sepsis) was used to predict survival outcomes at 96 hours.

STATISTICAL TESTS

Mann-Whitney U test, Spearman/Pearson correlation (r), P < 0.05 was considered statistically significant.

RESULTS

Severely ill septic animals exhibited significantly increased serum creatinine levels compared to controls (70 ± 30 vs. 34 ± 9 μmol/L, P < 0.0001). Cortical perfusion (480 ± 80 vs. 330 ± 140 mL/100 g tissue/min, P < 0.005), and cortical and medullary T2 relaxation time constants were significantly reduced compared to controls (41 ± 4 vs. 37 ± 5 msec in cortex, P < 0.05, 52 ± 7 vs. 45 ± 6 msec in medulla, P < 0.05). The combination of cortical T2 relaxation time constants and perfusion results at 18 hours could predict survival outcomes at 96 hours with high sensitivity (80%) and specificity (73%) (area under curve of ROC = 0.8, Jmax  = 0.52).

DATA CONCLUSION

This preclinical study suggests combined T2 relaxation time and perfusion mapping as first line diagnostic tool for treatment planning.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 2.

Variability and magnitude of brain glutamate levels in schizophrenia: a meta and mega-analysis

Glutamatergic dysfunction is implicated in schizophrenia pathoaetiology, but this may vary in extent between patients. It is unclear whether inter-individual variability in glutamate is greater in schizophrenia than the general population. We conducted meta-analyses to assess (1) variability of glutamate measures in patients relative to controls (log coefficient of variation ratio: CVR); (2) standardised mean differences (SMD) using Hedges g; (3) modal distribution of individual-level glutamate data (Hartigan's unimodality dip test). MEDLINE and EMBASE databases were searched from inception to September 2022 for proton magnetic resonance spectroscopy (1H-MRS) studies reporting glutamate, glutamine or Glx in schizophrenia. 123 studies reporting on 8256 patients and 7532 controls were included. Compared with controls, patients demonstrated greater variability in glutamatergic metabolites in the medial frontal cortex (MFC, glutamate: CVR = 0.15, p < 0.001; glutamine: CVR = 0.15, p = 0.003; Glx: CVR = 0.11, p = 0.002), dorsolateral prefrontal cortex (glutamine: CVR = 0.14, p = 0.05; Glx: CVR = 0.25, p < 0.001) and thalamus (glutamate: CVR = 0.16, p = 0.008; Glx: CVR = 0.19, p = 0.008). Studies in younger, more symptomatic patients were associated with greater variability in the basal ganglia (BG glutamate with age: z = -0.03, p = 0.003, symptoms: z = 0.007, p = 0.02) and temporal lobe (glutamate with age: z = -0.03, p = 0.02), while studies with older, more symptomatic patients associated with greater variability in MFC (glutamate with age: z = 0.01, p = 0.02, glutamine with symptoms: z = 0.01, p = 0.02). For individual patient data, most studies showed a unimodal distribution of glutamatergic metabolites. Meta-analysis of mean differences found lower MFC glutamate (g = -0.15, p = 0.03), higher thalamic glutamine (g = 0.53, p < 0.001) and higher BG Glx in patients relative to controls (g = 0.28, p < 0.001). Proportion of males was negatively associated with MFC glutamate (z = -0.02, p < 0.001) and frontal white matter Glx (z = -0.03, p = 0.02) in patients relative to controls. Patient PANSS total score was positively associated with glutamate SMD in BG (z = 0.01, p = 0.01) and temporal lobe (z = 0.05, p = 0.008). Further research into the mechanisms underlying greater glutamatergic metabolite variability in schizophrenia and their clinical consequences may inform the identification of patient subgroups for future treatment strategies.

Age-related differences of cerebellar cortex and nuclei: MRI findings in healthy controls and its application to spinocerebellar ataxia (SCA6) patients

Understanding cerebellar alterations due to healthy aging provides a reference point against which pathological findings in late-onset disease, for example spinocerebellar ataxia type 6 (SCA6), can be contrasted. In the present study, we investigated the impact of aging on the cerebellar nuclei and cerebellar cortex in 109 healthy controls (age range: 16 - 78 years) using 3 Tesla magnetic resonance imaging (MRI). Findings were compared with 25 SCA6 patients (age range: 38 - 78 years). A subset of 16 SCA6 (included: 14) patients and 50 controls (included: 45) received an additional MRI scan at 7 Tesla and were re-scanned after one year. MRI included T1-weighted, T2-weighted FLAIR, and multi-echo T2*-weighted imaging. The T2*-weighted phase images were converted to quantitative susceptibility maps (QSM). Since the cerebellar nuclei are characterized by elevated iron content with respect to their surroundings, two independent raters manually outlined them on the susceptibility maps. T1-weighted images acquired at 3T were utilized to automatically identify the cerebellar gray matter (GM) volume. Linear correlations revealed significant atrophy of the cerebellum due to tissue loss of cerebellar cortical GM in healthy controls with increasing age. Reduction of the cerebellar GM was substantially stronger in SCA6 patients. The volume of the dentate nuclei did not exhibit a significant relationship with age, at least in the age range between 18 and 78 years, whereas mean susceptibilities of the dentate nuclei increased with age. As previously shown, the dentate nuclei volumes were smaller and magnetic susceptibilities were lower in SCA6 patients compared to age- and sex-matched controls. The significant dentate volume loss in SCA6 patients could also be confirmed with 7T MRI. Linear mixed effects models and individual paired t-tests accounting for multiple comparisons revealed no statistical significant change in volume and susceptibility of the dentate nuclei after one year in neither patients nor controls. Importantly, dentate volumes were more sensitive to differentiate between SCA6 (Cohen's d = 3.02) and matched controls than the cerebellar cortex volume (d = 2.04). In addition to age-related decline of the cerebellar cortex and atrophy in SCA6 patients, age-related increase of susceptibility of the dentate nuclei was found in controls, whereas dentate volume and susceptibility was significantly decreased in SCA6 patients. Because no significant changes of any of these parameters was found at follow-up, these measures do not allow to monitor disease progression at short intervals.

High-resolution CINE imaging of active guided knee motion using continuously acquired golden-angle radial MRI and rotary sensor information

To explore and extend on dynamic imaging of joint motion, an MRI-safe device guiding knee motion with an attached rotary encoder was used in MRI measurements of multiple knee flexion-extension cycles using radial gradient echo imaging with the golden-angle as azimuthal angle increment. Reproducibility of knee motion was investigated. Real-time and CINE mode anatomical images were reconstructed for different knee flexion angles by synchronizing the encoder information with the MRI data, and performing flexion angle selective gating across multiple motion cycles. When investigating the influence of the rotation angle window width on reconstructed CINE images, it was found that angle windows between 0.5° and 3° exhibited acceptable image sharpness without suffering from significant motion-induced blurring. Furthermore, due to flexible retrospective image reconstruction afforded by the radial golden-angle imaging, the number of motion cycles included in the reconstruction could be retrospectively reduced to investigate the corresponding influence of acquisition time on image quality. Finally, motion reproducibility between motion cycles and accuracy of the flexion angle selective gating were sufficient to acquire whole-knee 3D dynamic imaging with a retrospectively gated 3D cone UTE sequence.

Magnetic susceptibility anisotropy in normal appearing white matter in multiple sclerosis from single-orientation acquisition

•

Orientation dependence of QSM is studied in a large cohort of MS patients.

•

Apparent magnetic susceptibility anisotropy (MSA) obtained from single-orientation QSM.

•

Apparent MSA found decreased in optic radiation (OR) of MS patients.

•

Apparent MSA decreases with lesion load in OR and with disease duration in splenium.

•

Negative apparent MSA observed in SLF indicates limitations of the proposed method.

Quantitative susceptibility mapping (QSM) has been successfully applied to study changes in deep grey matter nuclei as well as in lesional tissue, but its application to white matter has been complicated by the observed orientation dependence of gradient echo signal. The anisotropic susceptibility tensor is thought to be at the origin of this orientation dependence, and magnetic susceptibility anisotropy (MSA) derived from this tensor has been proposed as a marker of the state and integrity of the myelin sheath and may therefore be of particular interest for the study of demyelinating pathologies such as multiple sclerosis (MS). Reconstruction of the susceptibility tensor, however, requires repeated measurements with multiple head orientations, rendering the approach impractical for clinical applications.

In this study, we combined single-orientation QSM with fibre orientation information to assess apparent MSA in three white matter tracts, i.e., optic radiation (OR), splenium of the corpus callosum (SCC), and superior longitudinal fascicle (SLF), in two cohorts of 64 healthy controls and 89 MS patients. The apparent MSA showed a significant decrease in optic radiation in the MS cohort compared with healthy controls. It decreased in the MS cohort with increasing lesion load in OR and with disease duration in the splenium. All of this suggests demyelination in normal appearing white matter. However, the apparent MSA observed in the SLF pointed to potential systematic issues that require further exploration to realize the full potential of the presented approach. Despite the limitations of such single-orientation ROI-specific estimation, we believe that our clinically feasible approach to study degenerative changes in WM is worthy of further investigation.

CAN THE SIZE-SPECIFIC DOSE ESTIMATE BE DERIVED FROM THE BODY MASS INDEX? A FEASIBILITY STUDY

Size-specific dose estimate ($\mathbf{SSDE}$) index appears to be more suitable than the commonly used volume computed tomography dose index ($\mathbf{C}{\mathbf{TDI}}_{\mathbf{vol}}$) to estimate the dose delivered to the patient during a computed tomography (CT) scan. We evaluated whether an ${\mathbf{SSDE}}_{\mathbf{BMI}}$ can be determined from the patient's body mass index ($\mathbf{BMI}$) with sufficient reliability in the case that a $\mathbf{SSDE}$ is not given by the CT scanner. For each of the three most used examination types, CT examinations of 50 female and 50 male patients were analyzed. The $\mathbf{SSDE}$ values automatically provided by the scanner were compared with ${\mathbf{SSDE}}_{\mathbf{BMI}}$ determined from $\mathbf{C}{\mathbf{TDI}}_{\mathbf{vol}}$ and $\mathbf{BMI}$. A good accordance of ${\mathbf{SSDE}}_{\mathbf{BMI}}$ and $\mathbf{SSDE}$ was found for the chest and abdominal regions. A low correlation was observed for the head region. The presented method is a simple and practically useful surrogate approach for the chest and abdominal regions but not for the head.

Neurometabolic patterns of an "at risk for mental disorders" syndrome involve abnormalities in the thalamus and anterior midcingulate cortex

BACKGROUND

The ultra-high risk (UHR) paradigm allows the investigation of individuals at increased risk of developing psychotic or other mental disorders with the aim of making prevention and early intervention as specific as possible in terms of the individual outcome.

METHODS

Single-session ¹H-/³¹P-Chemical Shift Imaging of thalamus, prefrontal (DLPFC) and anterior midcingulate (aMCC) cortices was applied to 69 UHR patients for psychosis and 61 matched healthy controls. N-acetylaspartate (NAA), glutamate/glutamine complex (Glx), energy (PCr, ATP) and phospholipid metabolites were assessed, analysed by ANOVA (or ANCOVA [with covariates]) and correlated with symptomatology (SCL-90R).

RESULTS

The thalamus showed decreased NAA, inversely correlated with self-rated aggressiveness, as well as increased PCr, and altered phospholipid breakdown. While the aMCC showed a pattern of NAA decrease and PCr increase, the DLPFC showed PCr increase only in the close-to-psychosis patient subgroup. There were no specific findings in transition patients.

CONCLUSION

The results do not support the notion of a specific pre-psychotic neurometabolic pattern, but likely reflect correlates of an "at risk for mental disorders syndrome". This includes disturbed neuronal (mitochondrial) metabolism in the thalamus and aMCC, with emphasis on left-sided structures, and altered PL remodeling across structures.

A novel multipurpose device for guided knee motion and loading during dynamic magnetic resonance imaging

INTRODUCTION

This work aimed to develop a novel multipurpose device for guided knee flexion-extension, both passively using a motorized pneumatic system and actively (muscle-driven) with the joint unloaded or loaded during dynamic MRI. Secondary objectives were to characterize the participant experience during device use, and present preliminary dynamic MRI data to demonstrate the different device capabilities.

MATERIAL AND METHODS

Self-reported outcomes were used to characterize the pain, physical exertion and discomfort levels experienced by 10 healthy male participants during four different active knee motion and loading protocols using the novel device. Knee angular data were recorded during the protocols to determine the maximum knee range of motion achievable. Dynamic MRI was acquired for three healthy volunteers during passive, unloaded knee motion using 2D Cartesian TSE, 2D radial GRE and 3D UTE sequences; and during active, unloaded and loaded knee motion using 2D radial GRE imaging. Because of the different MRI sequences used, spatial resolution was inherently lower for active knee motion than for passive motion acquisitions.

RESULTS

Depending on the protocol, some participants reported slight pain, mild discomfort and varying levels of physical exertion. On average, participants achieved ∼40° of knee flexion; loaded conditions can create knee moments up to 27Nm. High quality imaging data were obtained during different motion and loading conditions. Dynamic 3D data allowed to retrospectively extract arbitrarily oriented slices.

CONCLUSION

A novel multipurpose device for guided, physiologically relevant knee motion and loading during dynamic MRI was developed. Device use was well tolerated and suitable for acquiring high quality images during different motion and loading conditions. Different bone positions between loaded and unloaded conditions were likely due to out-of-plane motion, particularly because image registration was not performed. Ultimately, this device could be used to advance our understanding of physiological and pathological joint mechanics.

Quantitative susceptibility mapping reveals alterations of dentate nuclei in common types of degenerative cerebellar ataxias

The cerebellar nuclei are a brain region with high iron content. Surprisingly, little is known about iron content in the cerebellar nuclei and its possible contribution to pathology in cerebellar ataxias, with the only exception of Friedreich’s ataxia. In the present exploratory cross-sectional study, quantitative susceptibility mapping was used to investigate volume, iron concentration and total iron content of the dentate nuclei in common types of hereditary and non-hereditary degenerative ataxias. Seventy-nine patients with spinocerebellar ataxias of types 1, 2, 3 and 6; 15 patients with Friedreich’s ataxia; 18 patients with multiple system atrophy, cerebellar type and 111 healthy controls were also included. All underwent 3 T MRI and clinical assessments. For each specific ataxia subtype, voxel-based and volumes-of-interest-based group analyses were performed in comparison with a corresponding age- and sex-matched control group, both for volume, magnetic susceptiblity (indicating iron concentration) and susceptibility mass (indicating total iron content) of the dentate nuclei. Spinocerebellar ataxia of type 1 and multiple system atrophy, cerebellar type patients showed higher susceptibilities in large parts of the dentate nucleus but unaltered susceptibility masses compared with controls. Friedreich’s ataxia patients and, only on a trend level, spinocerebellar ataxia of type 2 patients showed higher susceptibilities in more circumscribed parts of the dentate. In contrast, spinocerebellar ataxia of type 6 patients revealed lower susceptibilities and susceptibility masses compared with controls throughout the dentate nucleus. Spinocerebellar ataxia of type 3 patients showed no significant changes in susceptibility and susceptibility mass. Lower volume of the dentate nuclei was found to varying degrees in all ataxia types. It was most pronounced in spinocerebellar ataxia of type 6 patients and least prominent in spinocerebellar ataxia of type 3 patients. The findings show that alterations in susceptibility revealed by quantitative susceptibility mapping are common in the dentate nuclei in different types of cerebellar ataxias. The most striking changes in susceptibility were found in spinocerebellar ataxia of type 1, multiple system atrophy, cerebellar type and spinocerebellar ataxia of type 6. Because iron content is known to be high in glial cells but not in neurons of the cerebellar nuclei, the higher susceptibility in spinocerebellar ataxia of type 1 and multiple system atrophy, cerebellar type may be explained by a reduction of neurons (increase in iron concentration) and/or an increase in iron-rich glial cells, e.g. microgliosis. Hypomyelination also leads to higher susceptibility and could also contribute. The lower susceptibility in SCA6 suggests a loss of iron-rich glial cells. Quantitative susceptibility maps warrant future studies of iron content and iron-rich cells in ataxias to gain a more comprehensive understanding of the pathogenesis of these diseases.

In vitro measurements of radiation exposure with different modalities (computed tomography, cone beam computed tomography) for imaging the petrous bone with a pediatric anthropomorphic phantom

BACKGROUND

Various imaging modalities, such as multi-detector computed tomography (CT) and cone beam CT are commonly used in infants for the diagnosis of hearing loss and surgical planning of implantation hearing aid devices, with differing results.

OBJECTIVE

We compared three different imaging modalities available in our institution, including a high-class CT scanner, a mid-class CT scanner and an angiography system with a cone beam CT option, for image quality and radiation exposure in a phantom study.

MATERIALS AND METHODS

While scanning an anthropomorphic phantom imitating a 1-year-old child with vendor-provided routine protocols, organ doses, surface doses and effective doses were determined for these three modalities with thermoluminescent dosimeters. The image quality was evaluated using the signal difference to noise ratio (SDNR) and the spatial resolution of a line-pair insert in the phantom head. The dose efficiency, defined as the ratio of SDNR and effective dose, was also compared.

RESULTS

The organ and surface doses were lowest with the high-class CT protocol, but the image quality was the worst. Image quality was best with the cone beam CT protocol, which, however, had the highest radiation exposure in this study, whereas the mid-class CT was in between.

CONCLUSION

Based on our results, high-end CT should be used for surgical planning because it has the lowest dose, while the image quality is still sufficient for this purpose. However, if highest image quality is needed and required, e.g., by ENT surgeons, the other modalities should be considered.

Pulmonary Arteriovenous Pressure Gradient and Time-Averaged Mean Velocity of Small Pulmonary Arteries Can Serve as Sensitive Biomarkers in the Diagnosis of Pulmonary Arterial Hypertension: A Preclinical Study by 4D-Flow MRI

(1) Background: Pulmonary arterial hypertension (PAH) is a serious condition that is associated with many cardiopulmonary diseases. Invasive right heart catheterization (RHC) is currently the only method for the definitive diagnosis and follow-up of PAH. In this study, we sought a non-invasive hemodynamic biomarker for the diagnosis of PAH. (2) Methods: We applied prospectively respiratory and cardiac gated 4D-flow MRI at a 9.4T preclinical scanner on three different groups of Sprague Dawley rats: baseline (n = 11), moderate PAH (n = 8), and severe PAH (n = 8). The pressure gradients as well as the velocity values were analyzed from 4D-flow data and correlated with lung histology. (3) Results: The pressure gradient between the pulmonary artery and vein on the unilateral side as well as the time-averaged mean velocity values of the small pulmonary arteries were capable of distinguishing not only between baseline and severe PAH, but also between the moderate and severe stages of the disease. (4) Conclusions: The current preclinical study suggests the pulmonary arteriovenous pressure gradient and the time-averaged mean velocity as potential biomarkers to diagnose PAH.

Magnetic Resonance Imaging-based biomechanical simulation of cartilage: A systematic review

MRI-based mathematical and computational modeling studies can contribute to a better understanding of the mechanisms governing cartilage's mechanical performance and cartilage disease. In addition, distinct modeling of cartilage is needed to optimize artificial cartilage production. These studies have opened up the prospect of further deepening our understanding of cartilage function. Furthermore, these studies reveal the initiation of an engineering-level approach to how cartilage disease affects material properties and cartilage function. Aimed at researchers in the field of MRI-based cartilage simulation, research articles pertinent to MRI-based cartilage modeling were identified, reviewed, and summarized systematically. Various MRI applications for cartilage modeling are highlighted, and the limitations of different constitutive models used are addressed. In addition, the clinical application of simulations and studied diseases are discussed. The paper's quality, based on the developed questionnaire, was assessed, and out of 79 reviewed papers, 34 papers were determined as high-quality. Due to the lack of the best constitutive models for various clinical conditions, researchers may consider the effect of constitutive material models on the cartilage disease simulation. In the future, research groups may incorporate various aspects of machine learning into constitutive models and MRI data extraction to further refine the study methodology. Moreover, researchers should strive for further reproducibility and rigorous model validation and verification, such as gait analysis.

Hepatectomy-Induced Alterations in Hepatic Perfusion and Function - Toward Multi-Scale Computational Modeling for a Better Prediction of Post-hepatectomy Liver Function

Liver resection causes marked perfusion alterations in the liver remnant both on the organ scale (vascular anatomy) and on the microscale (sinusoidal blood flow on tissue level). These changes in perfusion affect hepatic functions via direct alterations in blood supply and drainage, followed by indirect changes of biomechanical tissue properties and cellular function. Changes in blood flow impose compression, tension and shear forces on the liver tissue. These forces are perceived by mechanosensors on parenchymal and non-parenchymal cells of the liver and regulate cell-cell and cell-matrix interactions as well as cellular signaling and metabolism. These interactions are key players in tissue growth and remodeling, a prerequisite to restore tissue function after PHx. Their dysregulation is associated with metabolic impairment of the liver eventually leading to liver failure, a serious post-hepatectomy complication with high morbidity and mortality. Though certain links are known, the overall functional change after liver surgery is not understood due to complex feedback loops, non-linearities, spatial heterogeneities and different time-scales of events. Computational modeling is a unique approach to gain a better understanding of complex biomedical systems. This approach allows (i) integration of heterogeneous data and knowledge on multiple scales into a consistent view of how perfusion is related to hepatic function; (ii) testing and generating hypotheses based on predictive models, which must be validated experimentally and clinically. In the long term, computational modeling will (iii) support surgical planning by predicting surgery-induced perfusion perturbations and their functional (metabolic) consequences; and thereby (iv) allow minimizing surgical risks for the individual patient. Here, we review the alterations of hepatic perfusion, biomechanical properties and function associated with hepatectomy. Specifically, we provide an overview over the clinical problem, preoperative diagnostics, functional imaging approaches, experimental approaches in animal models, mechanoperception in the liver and impact on cellular metabolism, omics approaches with a focus on transcriptomics, data integration and uncertainty analysis, and computational modeling on multiple scales. Finally, we provide a perspective on how multi-scale computational models, which couple perfusion changes to hepatic function, could become part of clinical workflows to predict and optimize patient outcome after complex liver surgery.

Application of Magnetic Resonance Imaging in Liver Biomechanics: A Systematic Review

MRI-based biomechanical studies can provide a deep understanding of the mechanisms governing liver function, its mechanical performance but also liver diseases. In addition, comprehensive modeling of the liver can help improve liver disease treatment. Furthermore, such studies demonstrate the beginning of an engineering-level approach to how the liver disease affects material properties and liver function. Aimed at researchers in the field of MRI-based liver simulation, research articles pertinent to MRI-based liver modeling were identified, reviewed, and summarized systematically. Various MRI applications for liver biomechanics are highlighted, and the limitations of different viscoelastic models used in magnetic resonance elastography are addressed. The clinical application of the simulations and the diseases studied are also discussed. Based on the developed questionnaire, the papers' quality was assessed, and of the 46 reviewed papers, 32 papers were determined to be of high-quality. Due to the lack of the suitable material models for different liver diseases studied by magnetic resonance elastography, researchers may consider the effect of liver diseases on constitutive models. In the future, research groups may incorporate various aspects of machine learning (ML) into constitutive models and MRI data extraction to further refine the study methodology. Moreover, researchers should strive for further reproducibility and rigorous model validation and verification.

High-resolution MRI of the human palatine tonsil and its schematic anatomic 3D reconstruction

The palatine tonsils form an important part of the human immune system. Together with the other lymphoid tonsils of Waldeyer's tonsillar ring, they act as the first line of defense against ingested or inhaled pathogens. Although histologically stained sections of the palatine tonsil are widely available, they represent the tissue only in two dimensions and do not provide reference to three‐dimensional space. Such a representation of a tonsillar specimen based on imaging data as a 3D anatomical reconstruction is lacking both in scientific publications and especially in textbooks. As a first step in this direction, the objective of the present work was to image a resected tonsil specimen with high spatial resolution in a 9.4 T small‐bore pre‐clinical MRI and to combine these data with data from the completely sectioned and H&E stained same palatine tonsil. Based on the information from both image modalities, a 3D anatomical sketch was drawn by a scientific graphic artist. In perspective, such studies could help to overcome the difficulty of capturing the spatial extent and arrangement of anatomical structures from 2D images and to establish a link between three‐dimensional anatomical preparations and two‐dimensional sections or illustrations, as they have been found so far in common textbooks and anatomical atlases.

Optimized gradient spoiling of UTE VFA-AFI sequences for robust T1 estimation with B1-field correction

Quantifying T₁ relaxation times is a challenge because inhomogeneities of the B₁ field have to be corrected to obtain proper values. It is a particular challenge in tissues with short T₂^⁎ values, for which conventional MRI techniques do not provide sufficient signal. Recently, a B₁-field correction technique called AFI (Actual Flip angle Imaging) has been introduced that can be combined with UTE (ultra-short echo-time) sequences, which have much shorter echo times compared to conventional MRI techniques, allowing quantification of signal in short T₂^⁎ tissues. A disadvantage of AFI is that it requires very long relaxation delays between repetitions to minimize the influence of imperfect spoiling of transverse magnetization on signal behavior. In this work, we propose a novel spoiling scheme for the AFI sequence that efficiently provides accurate B₁ correction maps with strongly reduced acquisition time. We validated the method with both phantom and preliminary in vivo results.

Classification of first-episode psychosis using cortical thickness: A large multicenter MRI study

Machine learning classifications of first-episode psychosis (FEP) using neuroimaging have predominantly analyzed brain volumes. Some studies examined cortical thickness, but most of them have used parcellation approaches with data from single sites, which limits claims of generalizability. To address these limitations, we conducted a large-scale, multi-site analysis of cortical thickness comparing parcellations and vertex-wise approaches. By leveraging the multi-site nature of the study, we further investigated how different demographical and site-dependent variables affected predictions. Finally, we assessed relationships between predictions and clinical variables. 428 subjects (147 females, mean age 27.14) with FEP and 448 (230 females, mean age 27.06) healthy controls were enrolled in 8 centers by the ClassiFEP group. All subjects underwent a structural MRI and were clinically assessed. Cortical thickness parcellation (68 areas) and full cortical maps (20,484 vertices) were extracted. Linear Support Vector Machine was used for classification within a repeated nested cross-validation framework. Vertex-wise thickness maps outperformed parcellation-based methods with a balanced accuracy of 66.2% and an Area Under the Curve of 72%. By stratifying our sample for MRI scanner, we increased generalizability across sites. Temporal brain areas resulted as the most influential in the classification. The predictive decision scores significantly correlated with age at onset, duration of treatment, and positive symptoms. In conclusion, although far from the threshold of clinical relevance, temporal cortical thickness proved to classify between FEP subjects and healthy individuals. The assessment of site-dependent variables permitted an increase in the across-site generalizability, thus attempting to address an important machine learning limitation.

Association of Age, Antipsychotic Medication, and Symptom Severity in Schizophrenia With Proton Magnetic Resonance Spectroscopy Brain Glutamate Level: A Mega-analysis of Individual Participant-Level Data

Importance

Proton magnetic resonance spectroscopy (1H-MRS) studies indicate that altered brain glutamatergic function may be associated with the pathophysiology of schizophrenia and the response to antipsychotic treatment. However, the association of altered glutamatergic function with clinical and demographic factors is unclear.

Objective

To assess the associations of age, symptom severity, level of functioning, and antipsychotic treatment with brain glutamatergic metabolites.

Data Sources

The MEDLINE database was searched to identify journal articles published between January 1, 1980, and June 3, 2020, using the following search terms: MRS or magnetic resonance spectroscopy and (1) schizophrenia or (2) psychosis or (3) UHR or (4) ARMS or (5) ultra-high risk or (6) clinical high risk or (7) genetic high risk or (8) prodrome* or (9) schizoaffective. Authors of 114 1H-MRS studies measuring glutamate (Glu) levels in patients with schizophrenia were contacted between January 2014 and June 2020 and asked to provide individual participant data.

Study Selection

In total, 45 1H-MRS studies contributed data.

Data Extraction and Synthesis

Associations of Glu, Glu plus glutamine (Glx), or total creatine plus phosphocreatine levels with age, antipsychotic medication dose, symptom severity, and functioning were assessed using linear mixed models, with study as a random factor.

Main Outcomes and Measures

Glu, Glx, and Cr values in the medial frontal cortex (MFC) and medial temporal lobe (MTL).

Results

In total, 42 studies were included, with data for 1251 patients with schizophrenia (mean [SD] age, 30.3 [10.4] years) and 1197 healthy volunteers (mean [SD] age, 27.5 [8.8] years). The MFC Glu (F1,1211.9 = 4.311, P = .04) and Glx (F1,1079.2 = 5.287, P = .02) levels were lower in patients than in healthy volunteers, and although creatine levels appeared lower in patients, the difference was not significant (F1,1395.9 = 3.622, P = .06). In both patients and volunteers, the MFC Glu level was negatively associated with age (Glu to Cr ratio, F1,1522.4 = 47.533, P < .001; cerebrospinal fluid-corrected Glu, F1,1216.7 = 5.610, P = .02), showing a 0.2-unit reduction per decade. In patients, antipsychotic dose (in chlorpromazine equivalents) was negatively associated with MFC Glu (estimate, 0.10 reduction per 100 mg; SE, 0.03) and MFC Glx (estimate, -0.11; SE, 0.04) levels. The MFC Glu to Cr ratio was positively associated with total symptom severity (estimate, 0.01 per 10 points; SE, 0.005) and positive symptom severity (estimate, 0.04; SE, 0.02) and was negatively associated with level of global functioning (estimate, 0.04; SE, 0.01). In the MTL, the Glx to Cr ratio was positively associated with total symptom severity (estimate, 0.06; SE, 0.03), negative symptoms (estimate, 0.2; SE, 0.07), and worse Clinical Global Impression score (estimate, 0.2 per point; SE, 0.06). The MFC creatine level increased with age (estimate, 0.2; SE, 0.05) but was not associated with either symptom severity or antipsychotic medication dose.

Conclusions and Relevance

Findings from this mega-analysis suggest that lower brain Glu levels in patients with schizophrenia may be associated with antipsychotic medication exposure rather than with greater age-related decline. Higher brain Glu levels may act as a biomarker of illness severity in schizophrenia.

Interrelations between dopamine and serotonin producing sites and regions of the default mode network

Recent functional magnetic resonance imaging (fMRI) studies showed that blood oxygenation level-dependent (BOLD) signal fluctuations in the default mode network (DMN) are functionally tightly connected to those in monoaminergic nuclei, producing dopamine (DA), and serotonin (5-HT) transmitters, in the midbrain/brainstem. We combined accelerated fMRI acquisition with spectral Granger causality and coherence analysis to investigate causal relationships between these areas. Both methods independently lead to similar results and confirm the existence of a top-down information flow in the resting-state condition, where activity in core DMN areas influences activity in the neuromodulatory centers producing DA/5-HT. We found that latencies range from milliseconds to seconds with high inter-subject variability, likely attributable to the resting condition. Our novel findings provide new insights into the functional organization of the human brain.

Alterations of neurometabolism in the dorsolateral prefrontal cortex and thalamus in transition to psychosis patients change under treatment as usual - A two years follow-up 1H/31P-MR-spectroscopy study

BACKGROUND

The ultra-high risk (UHR) paradigm allows early contact with patients developing acute psychosis and the study of treatment effects on the underlying pathology.

METHODS

29 patients with first acute psychosis according to CAARMS criteria (transition patients, TP) (T0) and thereof 22 patients after two-year follow-up (mean 788 d) (T1) underwent ¹H-/³¹P-MR spectroscopy of the prefrontal (DLPFC) and anterior midcingulate (aMCC) cortices and the thalamus. N-acetylaspartate (NAA), glutamate (Glu, Glx), energy (PCr, ATP) and phospholipid metabolites (PME, PDE) were compared to 27 healthy controls by ANCOVA and correlated with patients' symptom ratings (BPRS-E, SCL-90R). For longitudinal analysis, linear mixed model (LMM) and ANCOVA for repeated measures were used.

RESULTS

DLPFC: In patients, NAA and PME were decreased bilaterally and Glu on the left side at T0. Left-sided Glu and NAA (trend) and bilateral Glx increased during follow-up. Thalamus: In TP, bilateral NAA, left-sided Glu and right-sided Glx were decreased at T0; bilateral NAA and left-sided Glx increased during follow-up. aMCC: In TP, bilateral NAA, right-sided Glu, and bilateral PME and PDE were decreased, while left-sided PCr was increased at T0. No changes were observed during follow-up.

CONCLUSION

Regardless of the long-term diagnosis, the psychotic state of illness includes disturbed neuronal function in the DLPFC, thalamus and aMCC. Treatment-as-usual (TAU), including antipsychotic/antidepressant medication and supportive psychotherapy, had an effect on the thalamo-frontal area but not or less pronounced on the neurometabolic deficits of the aMCC.

Investigation of Deep-Learning-Driven Identification of Multiple Sclerosis Patients Based on Susceptibility-Weighted Images Using Relevance Analysis

The diagnosis of multiple sclerosis (MS) is usually based on clinical symptoms and signs of damage to the central nervous system, which is assessed using magnetic resonance imaging. The correct interpretation of these data requires excellent clinical expertise and experience. Deep neural networks aim to assist clinicians in identifying MS using imaging data. However, before such networks can be integrated into clinical workflow, it is crucial to understand their classification strategy. In this study, we propose to use a convolutional neural network to identify MS patients in combination with attribution algorithms to investigate the classification decisions. The network was trained using images acquired with susceptibility-weighted imaging (SWI), which is known to be sensitive to the presence of paramagnetic iron components and is routinely applied in imaging protocols for MS patients. Different attribution algorithms were used to the trained network resulting in heatmaps visualizing the contribution of each input voxel to the classification decision. Based on the quantitative image perturbation method, we selected DeepLIFT heatmaps for further investigation. Single-subject analysis revealed veins and adjacent voxels as signs for MS, while the population-based study revealed relevant brain areas common to most subjects in a class. This pattern was found to be stable across different echo times and also for a multi-echo trained network. Intensity analysis of the relevant voxels revealed a group difference, which was found to be primarily based on the T1w magnitude images, which are part of the SWI calculation. This difference was not observed in the phase mask data.

Experience-dependent structural plasticity in the adult brain: How the learning brain grows

Volumetric magnetic resonance imaging studies have shown that intense learning can be associated with grey matter volume increases in the adult brain. The underlying mechanisms are poorly understood. Here we used monocular deprivation in rats to analyze the mechanisms underlying use-dependent grey matter increases. Optometry for quantification of visual acuity was combined with volumetric magnetic resonance imaging and microscopic techniques in longitudinal and cross-sectional studies. We found an increased spatial vision of the open eye which was associated with a transient increase in the volumes of the contralateral visual and lateral entorhinal cortex. In these brain areas dendrites of neurons elongated, and there was a strong increase in the number of spines, the targets of synapses, which was followed by spine maturation and partial pruning. Astrocytes displayed a transient pronounced swelling and underwent a reorganization of their processes. The use-dependent increase in grey matter corresponded predominantly to the swelling of the astrocytes. Experience-dependent increase in brain grey matter volume indicates a gain of structure plasticity with both synaptic and astrocyte remodeling.

Superficial white matter imaging: Contrast mechanisms and whole-brain in vivo mapping

Superficial white matter (SWM) contains the most cortico-cortical white matter connections in the human brain encompassing the short U-shaped association fibers. Despite its importance for brain connectivity, very little is known about SWM in humans, mainly due to the lack of noninvasive imaging methods. Here, we lay the groundwork for systematic in vivo SWM mapping using ultrahigh resolution 7 T magnetic resonance imaging. Using biophysical modeling informed by quantitative ion beam microscopy on postmortem brain tissue, we demonstrate that MR contrast in SWM is driven by iron and can be linked to the microscopic iron distribution. Higher SWM iron concentrations were observed in U-fiber-rich frontal, temporal, and parietal areas, potentially reflecting high fiber density or late myelination in these areas. Our SWM mapping approach provides the foundation for systematic studies of interindividual differences, plasticity, and pathologies of this crucial structure for cortico-cortical connectivity in humans.

Energy Expenditure of Dynamic Submaximal Human Plantarflexion Movements: Model Prediction and Validation by in-vivo Magnetic Resonance Spectroscopy

To understand the organization and efficiency of biological movement, it is important to evaluate the energy requirements on the level of individual muscles. To this end, predicting energy expenditure with musculoskeletal models in forward-dynamic computer simulations is currently the most promising approach. However, it is challenging to validate muscle models in-vivo in humans, because access to the energy expenditure of single muscles is difficult. Previous approaches focused on whole body energy expenditure, e.g., oxygen consumption (VO2), or on thermal measurements of individual muscles by tracking blood flow and heat release (through measurements of the skin temperature). This study proposes to validate models of muscular energy expenditure by using functional phosphorus magnetic resonance spectroscopy (³¹P-MRS). ³¹P-MRS allows to measure phosphocreatine (PCr) concentration which changes in relation to energy expenditure. In the first 25 s of an exercise, PCr breakdown rate reflects ATP hydrolysis, and is therefore a direct measure of muscular enthalpy rate. This method was applied to the gastrocnemius medialis muscle of one healthy subject during repetitive dynamic plantarflexion movements at submaximal contraction, i.e., 20% of the maximum plantarflexion force using a MR compatible ergometer. Furthermore, muscle activity was measured by surface electromyography (EMG). A model (provided as open source) that combines previous models for muscle contraction dynamics and energy expenditure was used to reproduce the experiment in simulation. All parameters (e.g., muscle length and volume, pennation angle) in the model were determined from magnetic resonance imaging or literature (e.g., fiber composition), leaving no free parameters to fit the experimental data. Model prediction and experimental data on the energy supply rates are in good agreement with the validation phase (<25 s) of the dynamic movements. After 25 s, the experimental data differs from the model prediction as the change in PCr does not reflect all metabolic contributions to the energy expenditure anymore and therefore underestimates the energy consumption. This shows that this new approach allows to validate models of muscular energy expenditure in dynamic movements in vivo.

Immersion of Achilles tendon in phosphate-buffered saline influences T1 and T2 * relaxation times: An ex vivo study

Robust mapping of relaxation parameters in ex vivo tissues is based on hydration and therefore requires control of the tissue treatment to ensure tissue integrity and consistent measurement conditions over long periods of time. One way to maintain the hydration of ex vivo tendon tissue is to immerse the samples in a buffer solution. To this end, various buffer solutions have been proposed; however, many appear to influence the tissue relaxation times, especially with prolonged exposure. In this work, ovine Achilles tendon tissue was used as a model to investigate the effect of immersion in phosphate-buffered saline (PBS) and the effects on the T₁ and T₂^* relaxation times. Ex vivo samples were measured at 0 (baseline), 30 and 67 hours after immersion in PBS. Ultrashort echo time (UTE) imaging was performed using variable flip angle and echo train-shifted multi-echo imaging for T₁ and T₂^* estimation, respectively. Compared with baseline, both T₁ and T₂^* relaxation time constants increased significantly after 30 hours of immersion. T₂^* continued to show a significant increase between 30 and 67 hours. Both T₁ and T₂^* tended to approach saturation at 67 hours. These results exemplify the relevance of stringently controlled tissue preparation and preservation techniques, both before and during MRI experiments.

A virtual “Werkstatt” for digitization in the sciences

Data is central in almost all scientific disciplines nowadays. Furthermore, intelligent systems have developed rapidly in recent years, so that in many disciplines the expectation is emerging that with the help of intelligent systems, significant challenges can be overcome and science can be done in completely new ways. In order for this to succeed, however, first, fundamental research in computer science is still required, and, second, generic tools must be developed on which specialized solutions can be built. In this paper, we introduce a recently started collaborative project funded by the Carl Zeiss Foundation, a virtual manufactory for digitization in the sciences, the “Werkstatt”, which is being established at the Michael Stifel Center Jena (MSCJ) for data-driven and simulation science to address fundamental questions in computer science and applications. The Werkstatt focuses on three key areas, which include generic tools for machine learning, knowledge generation using machine learning processes, and semantic methods for the data life cycle, as well as the application of these topics in different disciplines. Core and pilot projects address the key aspects of the topics and form the basis for sustainable work in the Werkstatt.

Characterization of Iron Accumulation in Deep Gray Matter in Myotonic Dystrophy Type 1 and 2 Using Quantitative Susceptibility Mapping and R2* Relaxometry: A Magnetic Resonance Imaging Study at 3 Tesla

Quantitative mapping of the magnetic susceptibility and the effective transverse relaxation rate (R2^*) are suitable to assess the iron content in distinct brain regions. In this prospective, explorative study the iron accumulation in deep gray matter nuclei (DGM) in myotonic dystrophy type 1 (DM1) and 2 (DM2) and its clinical and neuro-cognitive relevance using susceptibility and R2^* mapping was examined. Twelve classical DM1, four childhood-onset DM1 (DM1_c.o.), twelve DM2 patients and twenty-nine matched healthy controls underwent MRI at 3 Tesla, neurological and neuro-cognitive tests. Susceptibility, R2^* and volumes were determined for eleven DGM structures and compared between patients and controls. Twelve classical DM1, four childhood-onset DM1, and 12 DM2 patients as well as 29 matched healthy controls underwent MRI at 3 Tesla, and neurological and neuro-cognitive tests. Susceptibility, R2^* and volumes were determined for 11 DGM structures and compared between patients and controls. Iron accumulation in DGM reflected by R2^* or susceptibility was found in the putamen and accumbens of DM1 and in DM2, but was more widespread in DM1 (caudate, pallidum, hippocampus, subthalamic nucleus, thalamus, and substantia nigra). Opposed changes of R2^* or susceptibility were detected in caudate, putamen and accumbens in the childhood-onset DM1 patients compared to classical DM1. R2^* or susceptibility alterations in DGM were significantly associated with clinical symptoms including muscular weakness (DM1), daytime sleepiness (DM1), depression (DM2), and with specific cognitive deficits in DM1 and DM2.

Segmentation and visualization of the human cranial bone by T2* approximation using ultra-short echo time (UTE) magnetic resonance imaging

Segmentation of the human cranial bone from MRI data is challenging, because compact bone is characterized by very short transverse relaxation times and typically produces no signal when using conventional magnetic resonance imaging (MRI) sequences. In this work, we propose a fully automated segmentation algorithm, which uses dual-echo, ultra-short echo-time (UTE) MRI data. The segmentation was initialized by interval thresholding of approximated T₂* relaxation time maps in the range of 1ms<T₂*<3ms. This parameter range was derived from a manual region-of-interest analysis of high resolution data of the cranial layers, resulting in average T₂* relaxation times of 1.7±0.3ms in the lamina externa, 2.5±0.3ms in the diploe and 1.7±0.2ms in the lamina interna. Segmentations were performed based on data of 8 healthy volunteers that were acquired with different acquisition parameters and spatial resolutions to test the stability of the algorithm. Comparison with computed tomography data demonstrated close agreement with the segmented UTE MRI data. Visualization of the segmented cranial bone was performed by volumetric rendering and by using the approximated T₂* values for color coding, clearly visualizing the cranial sutures as well as their intersections.

A new framework for assessing subject-specific whole brain circulation and perfusion using MRI-based measurements and a multi-scale continuous flow model

A large variety of severe medical conditions involve alterations in microvascular circulation. Hence, measurements or simulation of circulation and perfusion has considerable clinical value and can be used for diagnostics, evaluation of treatment efficacy, and for surgical planning. However, the accuracy of traditional tracer kinetic one-compartment models is limited due to scale dependency. As a remedy, we propose a scale invariant mathematical framework for simulating whole brain perfusion. The suggested framework is based on a segmentation of anatomical geometry down to imaging voxel resolution. Large vessels in the arterial and venous network are identified from time-of-flight (ToF) and quantitative susceptibility mapping (QSM). Macro-scale flow in the large-vessel-network is accurately modelled using the Hagen-Poiseuille equation, whereas capillary flow is treated as two-compartment porous media flow. Macro-scale flow is coupled with micro-scale flow by a spatially distributing support function in the terminal endings. Perfusion is defined as the transition of fluid from the arterial to the venous compartment. We demonstrate a whole brain simulation of tracer propagation on a realistic geometric model of the human brain, where the model comprises distinct areas of grey and white matter, as well as large vessels in the arterial and venous vascular network. Our proposed framework is an accurate and viable alternative to traditional compartment models, with high relevance for simulation of brain perfusion and also for restoration of field parameters in clinical brain perfusion applications.

An accurate simulation of blood-flow in the human brain can be used for improved diagnostics and assignment of personalized treatment regimes. However, current algorithms are limited to simulation of blood flow within tumours only, and in terms of parameter estimation, traditional compartment models have limited accuracy due to lack of spatial connectivity within the models. As a remedy, we propose a data-driven computational fluid dynamics model where the geometric domains for simulation are defined from state-of-the art MR acquisitions enabling a segmentation of large arteries and veins. In the capillary tissue we apply a two-compartment porous media model, where the perfusion is pressure-driven and is defined as the transition of blood from arterial to venous side. In addition, we propose a model for dealing with the intermediate scale problem where the vessels are undetectable and the flow does not adhere to requirements of porous media flow. For this scale, we propose a support function distributing the fluid in a nearby region around the vessel terminals. Combining these elements, we have developed a novel full human brain blood-flow simulator.

The relationship between heart rate and functional connectivity of brain regions involved in autonomic control

The peripheral autonomic nervous system (ANS) adjusts the heart rate (HR) to intrinsic and extrinsic demands. It is controlled by a group of functionally connected brain regions assembling the so-called central autonomic network (CAN). More specifically, forebrain cortical regions, limbic and brainstem structures within the CAN have been identified as important components of circuits involved in HR regulation. The present study aimed to investigate whether functional connectivity (FC) between these regions varies in subjects with different heart rates. Thus, 84 healthy subjects were separated according to their HR in slow, medium and fast. We observed a direct association between HR and FC in CAN regions, where stronger FC was related to slower HR. This relationship, however, is non-linear, follows an exponential course and is not restricted to CAN areas only. The network-based analysis (NBS) using time series from 262 independent anatomical ROIs revealed significantly increased functional connectivity in subjects with slow HR compared to subjects with fast HR mainly in regions being part of the salience network, but also of the default-mode network. We additionally simulated the effect of aliasing on the functional connectivity using several TRs and heart rates to exclude the possibility that FC differences might be due to different aliasing effects in the data. The result of the simulation indicated that aliasing cannot explain our findings. Thus, present results imply a functionally meaningful coupling between FC and HR that need to be accounted for in future studies. Moreover, given the established link between HR and emotional, cognitive and social processes, present findings may also be considered to explain individual differences in brain activation or connectivity when using corresponding paradigms in the MR scanner to investigate such processes.

Establishment and effects of allograft and synthetic bone graft substitute treatment of a critical size metaphyseal bone defect model in the sheep femur

Assessment of bone graft material efficacy is difficult in humans, since invasive methods like staged CT scans or biopsies are ethically unjustifiable. Therefore, we developed a novel large animal model for the verification of a potential transformation of synthetic bone graft substitutes into vital bone. The model combines multiple imaging methods with corresponding histology in standardized critical sized cancellous bone defect. Cylindrical bone voids (10 ml) were created in the medial femoral condyles of both hind legs (first surgery at right hind leg, second surgery 3 months later at left hind leg) in three merino‐wool sheep and either (i) left empty, filled with (ii) cancellous allograft bone or (iii) a synthetic, gentamicin eluting bone graft substitute. All samples were analysed with radiographs, MRI, μCT, DEXA and histology after sacrifice at 6 months. Unfilled defects only showed ingrowth of fibrous tissue, whereas good integration of the cancellous graft was seen in the allograft group. The bone graft substitute showed centripetal biodegradation and new trabecular bone formation in the periphery of the void as early as 3 months. μCT gave excellent insight into the structural changes within the defects, particularly progressive allograft incorporation and the bone graft substitute biodegradation process. MRI completed the picture by clearly visualizing soft tissue ingrowth into unfilled bone voids and presence of fluid collections. Histology was essential for verification of trabecular bone and osteoid formation. Conventional radiographs and DEXA could not differentiate details of the ongoing transformation process. This model appears well suited for detailed in vivo and ex vivo evaluation of bone graft substitute behaviour within large bone defects.

Analysis of intensity normalization for optimal segmentation performance of a fully convolutional neural network

INTRODUCTION

Convolutional neural networks have begun to surpass classical statistical- and atlas based machine learning techniques in medical image segmentation in recent years, proving to be superior in performance and speed. However, a major challenge that the community faces are mismatch between variability within training and evaluation datasets and therefore a dependency on proper data pre-processing. Intensity normalization is a widely applied technique for reducing the variance of the data for which there are several methods available ranging from uniformity transformation to histogram equalization. The current study analyses the influence of intensity normalization on cerebellum segmentation performance of a convolutional neural network (CNN).

METHOD

The study included three population samples with a total number of 218 datasets, all including a T1w MRI data set acquired at 3T and a ground truth segmentation delineating the cerebellum. A 12 layer deep 3D fully convolutional neural network was trained using 150 datasets from one of the population samples. Four different intensity normalization methods were separately applied to pre-process the data, and the CNN was correspondingly trained four times with respect to the different normalization techniques. A quantitative analysis of the segmentation performance, assessed via the Sørensen-Dice similarity coefficient (DSC) of all four CNNs, was performed to investigate the intensity sensitivity of the CNNs. Additionally, the optimal network performance was determined by identifying the best parameter set for intensity normalization.

RESULTS

All four normalization methods led to excellent (mean DSC score=0.96) segmentation results when evaluated using known data; however, the segmentation performance differed depending on the applied intensity normalization method when testing with formerly unseen data, in which case the histogram equalization methods outperformed the unit distribution methods. A detailed, systematic analysis of intensity manipulations revealed, that the distribution of input intensities clearly affected the segmentation performance and that for each input dataset a linear intensity modification (shifting and scaling) existed leading to optimal segmentation results. This was further proven by an optimization analysis to find the optimal adjustment for an individual input evaluation sample within each normalization configuration.

DISCUSSION

The findings suggest that proper preparation of the evaluation data is more crucial than the exact choice of normalization method to prepare the training data. The histogram equalization methods tested in this study were found to perform this task best, although leaving room for further improvements, as shown by the optimization analysis.

The Use of Physiological Signals in Brainstem/Midbrain fMRI

Brainstem and midbrain nuclei are closely linked to cognitive performance and autonomic function. To advance the localization in this area, precise functional imaging is fundamental. In this study, we used a sophisticated fMRI technique as well as physiological recordings to investigate the involvement of brainstem/midbrain nuclei in cognitive control during a Stroop task. The temporal signal-to-noise ratio (tSNR) increased due to physiological noise correction (PNC) especially in regions adjacent to arteries and cerebrospinal fluid. Within the brainstem/cerebellum template an average tSNR of 68 ± 16 was achieved after the simultaneous application of a high-resolution fMRI, specialized co-registration, and PNC. The analysis of PNC data revealed an activation of the substantia nigra in the Stroop interference contrast whereas no significant results were obtained in the midbrain or brainstem when analyzing uncorrected data. Additionally, we found that pupil size indicated the level of cognitive effort. The Stroop interference effect on pupillary responses was correlated to the effect on reaction times (R 2 = 0.464, p < 0.05). When Stroop stimuli were modulated by pupillary responses, we observed a significant activation of the LC in the Stroop interference contrast. Thus, we demonstrated the beneficial effect of PNC on data quality and statistical results when analyzing neuronal responses to a cognitive task. Parametric modulation of task events with pupillary responses improved the model of LC BOLD activations in the Stroop interference contrast.

Disturbed glutathione antioxidative defense is associated with structural brain changes in neuroleptic-naïve first-episode psychosis patients

BACKGROUND

Oxidative stress and impaired antioxidant defense are reported in schizophrenia and are thought to be associated with disturbed neurodevelopment, brain structural alterations, glutamatergic imbalance, negative symptomatology, and cognitive impairment. To test some of these assumptions we investigated the glutathione (GSH) antioxidant defense system (AODS) and brain structural abnormalities in drug-naïve individuals with first acute episode of psychosis (FEP).

METHOD

The study involved 27 drug-naïve FEP patients and 31 healthy controls (HC). GSH AODS markers and TBARS (thiobarbituric acid reactive substances) were measured in blood plasma and erythrocytes. High-resolution T₁-weighted 3T MRI were acquired from all subjects. To investigate brain structural abnormalities and effects of illness on interactions between GSH metabolites or enzyme activities and local grey matter density, voxel-based morphometry (VBM) with the computational anatomy toolbox (CAT12) was used. Symptomatology was assessed using the Positive and Negative Syndrome Scale (PANSS) and the Symptom Checklist 1990 revised (SCL-90-R).

RESULTS

(i) In FEP patients, glutathione reductase activity (GSR) was lower than in the HC group. GSR activity in plasma was inversely correlated with SCL-90-R scores of depression and PANSS scores of the negative symptom subscale. (ii) A reduction of GM was observed in left inferior frontal, bilateral temporal, as well as parietal cortices of FEP patients. (iii) Interaction analyses revealed an influence of illness on GSR/GM associations in the left orbitofrontal cortex (BA 47).

CONCLUSION

Our findings support the notion of altered GSH antioxidative defense in untreated acute psychosis as a potential pathomechanism for localized brain structural abnormalities. This pathology relates to a key brain region of social cognition, affective motivation control and decision making, and is clinically accompanied by depressive and negative symptoms.

Comparison of metabolic adaptations between endurance- and sprint-trained athletes after an exhaustive exercise in two different calf muscles using a multi-slice 31 P-MR spectroscopic sequence

Measurements of exercise-induced metabolic changes, such as oxygen consumption, carbon dioxide exhalation or lactate concentration, are important indicators for assessing the current performance level of athletes in training science. With exercise-limiting metabolic processes occurring in loaded muscles, ³¹ P-MRS represents a particularly powerful modality to identify and analyze corresponding training-induced alterations. Against this background, the current study aimed to analyze metabolic adaptations after an exhaustive exercise in two calf muscles (m. soleus - SOL - and m. gastrocnemius medialis - GM) of sprinters and endurance athletes by using localized dynamic ³¹ P-MRS. In addition, the respiratory parameters VO₂ and VCO₂ , as well as blood lactate concentrations, were monitored simultaneously to assess the effects of local metabolic adjustments in the loaded muscles on global physiological parameters. Besides noting obvious differences between the SOL and the GM muscles, we were also able to identify distinct physiological strategies in dealing with the exhaustive exercise by recruiting two athlete groups with opposing metabolic profiles. Endurance athletes tended to use the aerobic pathway in the metabolism of glucose, whereas sprinters produced a significantly higher peak concentration of lactate. These global findings go along with locally measured differences, especially in the main performer GM, with sprinters revealing a higher degree of acidification at the end of exercise (pH 6.29 ± 0.20 vs. 6.57 ± 0.21). Endurance athletes were able to partially recover their PCr stores during the exhaustive exercise and seemed to distribute their metabolic activity more consistently over both investigated muscles. In contrast, sprinters mainly stressed Type II muscle fibers, which corresponds more to their training orientation preferring the glycolytic energy supply pathway. In conclusion, we were able to analyze the relation between specific local metabolic processes in loaded muscles and typical global adaptation parameters, conventionally used to monitor the training status of athletes, in two cohorts with different sports orientations.

Prefrontal glutamatergic emotion regulation is disturbed in cluster B and C personality disorders - A combined 1H/31P-MR spectroscopic study

BACKGROUND

Personality disorders (PD) belong to the most common and most serious mental disorders as regards social dysfunction, inability to work, occurrence of comorbidity and suicidal risk. PDs also crucially influence the incidence, clinical course and treatment response of mental disorders with high suicidal risk, such as depression or substance abuse. One key issue of PD concerns the regulation of emotions.

METHODS

Both ¹H-/³¹P-Chemical Shift Imaging (CSI) was applied in a single session to assess neurochemical markers of glutamate function (NAA, Glu) and local energy metabolism (PCr, ATP) in two patient cohorts encompassing 22 cluster B (CB) and 21 cluster C (CC) PD patients, whereby 10 patients of each group were on low-dose antidepressants, and in 60 healthy controls (HC). Non-parametric statistical tests and correlation analyses were performed to assess disease effects on the metabolites and their relation to symptomatology as assessed by SCL-90R self-ratings.

RESULTS

Overall comparison including Bonferroni correction revealed significant differences of Glu across all groups in the dorsolateral prefrontal cortex (DLPFC). The following uncorrected results of pairwise tests were obtained: (i) Glu was bilaterally increased in the DLPFC in CB patients, whereas it was - together with NAA - bilaterally decreased in the DLPFC in CC patients and accompanied by increased PCr in the left DLPFC. (ii) NAA and Glu, accompanied by increased PCr, were significantly decreased in the dorsomedial prefrontal cortex (DMPFC) in CC patients. (iii) NAA was decreased in the right anterior cingulate cortex (ACC) in CB patients, and in the left ACC in CC patients with PCr being increased bilaterally. (iv) No associations were observed between metabolites and psychopathology measures.

CONCLUSION

The observations in the DLPFC may reflect a neurobiochemical correlate of disturbed cognitive control function in CB and CC PD. While the alterations in CB patients suggest increased basal activity, the observed patterns in CC patients likely reflect decreased or inhibited activity. The alterations of NAA and Glu levels in the ACC and DMPFC indirectly support the assumption of disturbed neuronal function in regions involved in social cognition and mentalizing abilities in both CB and CC PD. Further studies should include the investigation of metabolites of neuronal inhibition (GABA) and the examination of treatment effects.

Vascular and Tissue Changes of Magnetic Susceptibility in the Mouse Brain After Transient Cerebral Ischemia

Quantitative susceptibility mapping (QSM) has been recently introduced as a novel MRI post-processing technique of gradient recalled echo (GRE) data. QSM is useful in depicting both brain anatomy and for detecting abnormalities. Its utility in the context of ischemic stroke has, however, not been extensively characterized so far. In this study, we explored the potential of QSM to characterize vascular and tissue changes in the transient middle cerebral artery occlusion (tMCAO) mouse model of cerebral ischemia. We acquired GRE data of mice brains at different time points after tMCAO, from which we computed QSM and MR frequency maps, and compared these maps with diffusion imaging and multi-slice multi-echo imaging data acquired in the same animals. Prominent vessels with increased magnetic susceptibility were visible surrounding the lesion on both frequency and magnetic susceptibility maps at all time points (mostly visible at > 12 h after reperfusion). Immunohistochemistry revealed the presence of compressed capillaries and dilated larger vessels, suggesting that the appearance of prominent vessels after reestablishment of reperfusion may serve compensatory purposes. In addition, on both contrast maps, tissue regions of decreased magnetic susceptibility were observed at 24 and 48 h after reperfusion that were distinctly different from the lesions seen on maps of the apparent diffusion coefficient and T₂ relaxation time constant. Since QSM can be extracted as an add-on from GRE data and thus requires no additional acquisition time in the course of acute stroke MRI examination, it may provide unique and complementary information during the course of acute stroke MRI examinations.

Computational Modeling in Liver Surgery

The need for extended liver resection is increasing due to the growing incidence of liver tumors in aging societies. Individualized surgical planning is the key for identifying the optimal resection strategy and to minimize the risk of postoperative liver failure and tumor recurrence. Current computational tools provide virtual planning of liver resection by taking into account the spatial relationship between the tumor and the hepatic vascular trees, as well as the size of the future liver remnant. However, size and function of the liver are not necessarily equivalent. Hence, determining the future liver volume might misestimate the future liver function, especially in cases of hepatic comorbidities such as hepatic steatosis. A systems medicine approach could be applied, including biological, medical, and surgical aspects, by integrating all available anatomical and functional information of the individual patient. Such an approach holds promise for better prediction of postoperative liver function and hence improved risk assessment. This review provides an overview of mathematical models related to the liver and its function and explores their potential relevance for computational liver surgery. We first summarize key facts of hepatic anatomy, physiology, and pathology relevant for hepatic surgery, followed by a description of the computational tools currently used in liver surgical planning. Then we present selected state-of-the-art computational liver models potentially useful to support liver surgery. Finally, we discuss the main challenges that will need to be addressed when developing advanced computational planning tools in the context of liver surgery.

Diffusion tensor imaging of cingulum bundle and corpus callosum in schizophrenia vs. bipolar disorder

Both schizophrenia and bipolar disorder show abnormalities of white matter, as seen in diffusion tensor imaging (DTI) analyses of major brain fibre bundles. While studies in each of the two conditions have indicated possible overlap in anatomical location, there are few direct comparisons between the disorders. Also, it is unclear whether phenotypically similar subgroups (e.g. patients with bipolar disorder and psychotic features) might share white matter pathologies or be rather similar. Using region-of-interest (ROI) analysis of white matter with diffusion tensor imaging (DTI) at 3 T, we analysed fractional anisotropy (FA), radial diffusivity (RD), and apparent diffusion coefficient (ADC) of the corpus callosum and cingulum bundle in 33 schizophrenia patients, 17 euthymic (previously psychotic) bipolar disorder patients, and 36 healthy controls. ANOVA analysis showed significant main effects of group for RD and ADC (both elevated in schizophrenia). Across the corpus callosum ROIs, there was not group effect on FA, but for RD (elevated in schizophrenia, lower in bipolar disorder) and ADC (higher in schizophrenia, intermediate in bipolar disorder). Our findings show similarities and difference (some gradual) across regions of the two major fibre tracts implicated in these disorders, which would be consistent with a neurobiological overlap of similar clinical phenotypes.

GlucoCEST magnetic resonance imaging in vivo may be diagnostic of acute renal allograft rejection

Acute cellular renal allograft rejection (AR) frequently occurs after kidney transplantations. It is a sterile T-cell mediated inflammation leading to increased local glucose metabolism. Here we demonstrate in an allogeneic model of Brown Norway rat kidneys transplanted into uninephrectomized Lewis rats the successful implementation of the recently developed glucose chemical exchange saturation transfer (glucoCEST) magnetic resonance imaging. This technique is a novel method to assess and differentiate AR. Renal allografts undergoing AR showed significantly increased glucoCEST contrast ratios of cortex to medulla of 1.61 compared to healthy controls (1.02), syngeneic Lewis kidney to Lewis rat transplants without rejection (0.92), kidneys with ischemia reperfusion injury (0.99) and kidneys affected by cyclosporine A toxicity (1.10). Receiver operating characteristic curve analysis showed an area under the curve value of 0.92, and the glucoCEST contrast ratio predicted AR with a sensitivity of 100% and a specificity of 69% at a threshold level over 1.08. In defined animal models of kidney injuries, the glucoCEST contrast ratios of cortex to medulla correlated positively with mRNA expression levels of T-cell markers (CD3, CD4, CD8a/b), but did not correlate to impaired renal perfusion. Thus, the glucoCEST parameter may be valuable for the assessment and follow up treatment of AR.

Combined spiroergometry and 31 P-MRS of human calf muscle during high-intensity exercise

Simultaneous measurements of pulmonary oxygen consumption (VO₂ ), carbon dioxide exhalation (VCO₂ ) and phosphorus magnetic resonance spectroscopy (³¹ P-MRS) are valuable in physiological studies to evaluate muscle metabolism during specific loads. Therefore, the aim of this study was to adapt a commercially available spirometric device to enable measurements of VO₂ and VCO₂ whilst simultaneously performing ³¹ P-MRS at 3 T. Volunteers performed intense plantar flexion of their right calf muscle inside the MR scanner against a pneumatic MR-compatible pedal ergometer. The use of a non-magnetic pneumotachograph and extension of the sampling line from 3 m to 5 m to place the spirometric device outside the MR scanner room did not affect adversely the measurements of VO₂ and VCO₂ . Response and delay times increased, on average, by at most 0.05 s and 0.79 s, respectively. Overall, we were able to demonstrate a feasible ventilation response (VO₂ = 1.05 ± 0.31 L/min; VCO₂ = 1.11 ± 0.33 L/min) during the exercise of a single calf muscle, as well as a good correlation between local energy metabolism and muscular acidification (τ_{PCr fast} and pH; R² = 0.73, p < 0.005) and global respiration (τ_{PCr fast} and VO₂ ; R²  = 0.55, p = 0.01). This provides improved insights into aerobic and anaerobic energy supply during strong muscular performances.