Volumetric brain MRI signatures of heart failure with preserved ejection fraction in the setting of dementia

Heart failure with preserved ejection fraction (HFpEF) is an important, emerging risk factor for dementia, but it is not clear whether HFpEF contributes to a specific pattern of neuroanatomical changes in dementia. A major challenge to studying this is the relative paucity of datasets of patients with dementia, with/without HFpEF, and relevant neuroimaging. We sought to demonstrate the feasibility of using modern data mining tools to create and analyze clinical imaging datasets and identify the neuroanatomical signature of HFpEF-associated dementia. We leveraged the bioinformatics tools at Vanderbilt University Medical Center to identify patients with a diagnosis of dementia with and without comorbid HFpEF using the electronic health record. We identified high resolution, clinically-acquired neuroimaging data on 30 dementia patients with HFpEF (age 76.9 ± 8.12 years, 61% female) as well as 301 age- and sex-matched patients with dementia but without HFpEF to serve as comparators (age 76.2 ± 8.52 years, 60% female). We used automated image processing pipelines to parcellate the brain into 132 structures and quantify their volume. We found six regions with significant atrophy associated with HFpEF: accumbens area, amygdala, posterior insula, anterior orbital gyrus, angular gyrus, and cerebellar white matter. There were no regions with atrophy inversely associated with HFpEF. Patients with dementia and HFpEF have a distinct neuroimaging signature compared to patients with dementia only. Five of the six regions identified in are in the temporo-parietal region of the brain. Future studies should investigate mechanisms of injury associated with cerebrovascular disease leading to subsequent brain atrophy.

In subjects with chronic low back pain, does neuropathia exclusively correlated to neuronal compression? A correlation study of PainDETECT questionnaire and corresponding MRI and X-ray findings

INTRODUCTION

Understanding the complex nature of low back pain (LBP) is crucial for effective management. The PainDETECT questionnaire is a tool that distinguishes between neuropathic (NeP), nociceptive (NoP), and ambiguous pain. This study aimed to investigate the relationship between pain classification and lumbar intervertebral degenerative parameters obtained from imaging.

METHODS

A cohort study was conducted involving 279 patients, aged 18 years and above, who completed PainDETECT questionnaires and underwent lumbar MRI and/or X-ray scans.

RESULTS

The study included 102 patients with NoP, 78 with ambiguous pain, and 99 with NeP. The NeP group had lower mean age (58.21 vs. 53.63, p < 0.05) and higher mean numerical rating scale score (7.9 vs. 5.9, p < 0.001) compared to the NoP group. A negative correlation was found between PainDETECT scores and pelvic incidence (τ = - 0.177, p = 0.043). The NeP group exhibited significantly higher severity of foraminal stenosis (U = 18.962, p = 0.002), spinal stenosis (U = 14.481, p = 0.005), and Pfirrmann grade (U = 14.221, p = 0.028) compared to the NoP group. A higher proportion of NeP patients had intervertebral disk bulge (96% vs. 78% vs. 78%, p = 0.002) and high-intensity zones (51% vs. 41% vs. 19%, p < 0.001) compared to those with NoP and ambiguous pain.

CONCLUSION

NeP, as determined by the PainDETECT questionnaire, is associated with more severe neural compression, increased presence of discogenic disease and inflammatory disk severity, and decreased pelvic incidence. This pioneering study establishes a connection between pathological findings and pain categorization, providing clinicians with valuable guidance for formulating tailored management plans and reducing the need for unnecessary pharmacotherapy, imaging, and non-targeted surgical interventions.

Spotlight on porphyrins: Classifications, mechanisms and medical applications

Photodynamic therapy (PDT) and sonodynamic therapy (SDT) are non-invasive treatment methods with obvious inhibitory effect on tumors and have few side effects, which have been widely concerned and explored by researchers. Sensitizer is the main factor in determining the therapeutic effect of PDT and SDT. Porphyrins, a group of organic compounds widespread in nature, can be activated by light or ultrasound and produce reactive oxygen species. Therefore, porphyrins as sensitizers in PDT have been widely explored and investigated for many years. Herein, we summarize the classical porphyrin compounds and their applications and mechanisms in PDT and SDT. The application of porphyrin in clinical diagnosis and imaging is also discussed. In conclusion, porphyrins have good application prospects in disease treatment as an important part of PDT or SDT, and in clinical diagnosis and imaging.

Putting the Cart Before the Horse? Developing a Blended Anatomy Curriculum Supplemented by Cadaveric Anatomy

Cadaveric anatomy is frequently described as the gold standard for anatomy education. Increasingly and especially following the COVID-19 pandemic, there is acceptance that a blended approach for anatomy curriculum delivery is optimal for learners.Setting up a new UK Medical School in 2019 necessitated building a new cadaveric anatomy facility. To enable anatomy curriculum delivery during the construction period (2019-2021), a technology-enhanced learning (TEL) anatomy curriculum was developed, as well as an anatomy laboratory suitable for TEL. Development of a TEL anatomy curriculum with the later inclusion of cadaveric anatomy is unusual since the typical model is to supplement cadaveric anatomy with TEL approaches.TEL solutions that provide digital visualisation of anatomy may support learners by reducing cognitive load. Examples include using colour and/or translucency features to highlight and signpost pertinent anatomy and constructing virtual anatomical models in real time, rather than dissection. Radiology and portable ultrasound provide clinically contextualised visualisations of anatomy; the latter offers a haptic learning experience too. A TEL anatomy laboratory can provide interactive learning experiences for engagement and outreach activities for young school children, where cadaveric anatomy is not suitable.

A difficult-to-diagnose pericardial fistula

Pericardial fistula is a rare complication. Generally, the diagnosis can be confirmed by imaging examination, but our patient was an exception. We present a 71-year-old female patient that complained of remnant gastric cancer for five months and dyspnea for seven days; the dyspnea became aggravated during the last two days. After admission, emergency thoracic computed tomography and echocardiography showed pericardial effusion, and pericardiocentesis was performed. After conventional treatment, the pericardial effusion was unchanged and no cancer cells were found in the pericardial drainage. However, the color changed from turbid to golden yellow and, finally, to green. After 20 days of repeated laboratory, imaging, and gastrointestinal contrast examinations, no cause was found. Moreover, a clinical diagnosis could not be obtained following numerous comprehensive clinical analyses. Given the color change of the pericardial drainage, we strongly suspected pericardial fistula, but the imaging examinations were negative. Finally, a methylene blue test confirmed the existence of a pericardial fistula. When the color of the pericardial effusion changes, the existence of a pericardial fistula must be considered in advance, and other methods should be evaluated if imaging cannot assist in the diagnosis.

UK reporting radiographers' perceptions of AI in radiographic image interpretation - Current perspectives and future developments

INTRODUCTION

Radiographer reporting is accepted practice in the UK. With a national shortage of radiographers and radiologists, artificial intelligence (AI) support in reporting may help minimise the backlog of unreported images. Modern AI is not well understood by human end-users. This may have ethical implications and impact human trust in these systems, due to over- and under-reliance. This study investigates the perceptions of reporting radiographers about AI, gathers information to explain how they may interact with AI in future and identifies features perceived as necessary for appropriate trust in these systems.

METHODS

A Qualtrics® survey was designed and piloted by a team of UK AI expert radiographers. This paper reports the third part of the survey, open to reporting radiographers only.

RESULTS

86 responses were received. Respondents were confident in how an AI reached its decision (n = 53, 62%). Less than a third of respondents would be confident communicating the AI decision to stakeholders. Affirmation from AI would improve confidence (n = 49, 57%) and disagreement would make respondents seek a second opinion (n = 60, 70%). There is a moderate trust level in AI for image interpretation. System performance data and AI visual explanations would increase trust.

CONCLUSIONS

Responses indicate that AI will have a strong impact on reporting radiographers' decision making in the future. Respondents are confident in how an AI makes decisions but less confident explaining this to others. Trust levels could be improved with explainable AI solutions.

IMPLICATIONS FOR PRACTICE

This survey clarifies UK reporting radiographers' perceptions of AI, used for image interpretation, highlighting key issues with AI integration.

In vivo detection of the lumbar intraforaminal ligaments by MRI

PURPOSE

Intraforaminal ligaments (IFL) are of great interest to anatomists and clinicians to fully understand the detailed anatomy of the neuroforamina and to diagnose unclear radicular symptoms. Studies published until now have described radiological imaging of the IFLs using magnetic resonance imaging (MRI) on donor bodies. In the present study, we investigated the detectability of lumbar IFLs in vivo in adults using the high spatial resolution of the constructive interference in steady state (CISS) sequence.

METHODS

A total of 14 patients were studied using a 1.5 T MRI scanner. The lumbar spine was imaged using the parasagittal CISS sequence, and the detectability of the IFLs was assessed for each lumbar level. All image datasets were analyzed by a radiologist, an orthopedic surgeon, and an anatomist. Interrater reliability was expressed as Fleiss' Kappa. Using a single data set, a three-dimensional (3D) model was created to map the location of the IFLs within the intervertebral foramen (IF) and the immediate surrounding vessels.

RESULTS

Overall, the radiologist was able to detect IFLs in 60% of all imaged IFs, the orthopedic surgeon in 62%, and the anatomist in 66%. Fleiss' Kappa for the various segments varies from 0.71 for L4/5 up to 0.90 for L3/4.

CONCLUSION

Lumbar IFLs were successfully detected in vivo in every patient. The detection frequency varied from 42-86% per IF. We demonstrated reproducible imaging of the IFLs on MRI, with good interrater reliability. The present study was a launching point for further clinical studies investigating the potential impact of altered IFLs on radicular pain.

Lesion symptom mapping of domain-specific cognitive impairments using routine imaging in stroke

INTRODUCTION

This large-scale lesion-symptom mapping study investigates the necessary neuro-anatomical substrates of 5 cognitive domains frequently affected post stroke: Language, Attention, Praxis, Number, and Memory. This study aims to demonstrate the validity of using routine clinical brain imaging and standard bedside cognitive screening data from a large, real-world patient cohort for lesion-symptom mapping.

PATIENTS AND METHODS

Behavioural cognitive screening data from the Oxford Cognitive Screen and routine clinical neuroimaging from 573 acute patients was used in voxel-based lesion-symptom mapping analyses. Patients were classed as impaired or not on each of the subtests within 5 cognitive domains.

RESULTS

Distinct patterns of lesion damage were associated with different domains. Language functions were associated with damage to left hemisphere fronto-temporal areas. Visuo-spatial functions were associated with damage to posterior occipital areas (Visual Field) and the right temporo-parietal region (Visual Neglect). Different memory impairments were linked to distinct voxel clusters within the left insular and opercular cortices. Deficits which were not associated with localised voxels (e.g. executive function, praxis) represent distributed, bilateral functions.

DISCUSSION

The standardised, brief Oxford Cognitive Screen was able to reliably differentiate distinct neural correlates critically involved in supporting domain-specific cognitive abilities.

CONCLUSION

By demonstrating and replicating known brain anatomy correlates within real-life clinical cohorts using routinely collected scans and standard bedside screens, we open up VLSM techniques to a wealth of clinically relevant studies which can capitalise on using existing clinical data.

Medical imaging clinical trials unit: A professional need

PURPOSE

To design and describe a management and control tool and the human resources needed to efficiently manage the imaging process within clinical trials for a better quality of care for the patient.

METHODS

A unit was created to efficiently organise the participation of our Medical Imaging Department in clinical trials. This entity was defined and monitored using a customized, flexible and modular software package that provides the necessary information to execute and monitor requests (appointments, protocols, reports, complaints, billing). Various indicators of activity and professional satisfaction were parameterised.

RESULTS

From 2016 to 2020, 367 trials were participated and monitored, 50% of all the hospital clinical trials. The budget of the Medical Imaging Department grew by 47% in this period. The coordination with other departments and principal investigators improved, as shown by surveys (62% fluid and 38% very fluid), with a high perception of collaboration (86%).

CONCLUSIONS

The implementation of a Medical Imaging Clinical Trials Unit involve identifying the tasks, personnel, organisational needs, workflow, monitoring and invoicing. The creation of this Unit has improved the control and traceability of clinical trials within the Department.

Morphometric measurements can improve prediction of progressive vertebral deformity following vertebral damage

PURPOSE

A damaged vertebral body can exhibit accelerated 'creep' under constant load, leading to progressive vertebral deformity. However, the risk of this happening is not easy to predict in clinical practice. The present cadaveric study aimed to identify morphometric measurements in a damaged vertebral body that can predict a susceptibility to accelerated creep.

METHODS

A total of 27 vertebral trabeculae samples cored from five cadaveric spines (3 male, 2 female, aged 36 to 73 (mean 57) years) were mechanically tested to establish the relationship between bone damage and residual strain. Compression testing of 28 human spinal motion segments (three vertebrae and intervening soft tissues) dissected from 14 cadaveric spines (10 male, 4 female, aged 67 to 92 (mean 80) years) showed how the rate of creep of a damaged vertebral body increases with increasing "damage intensity" in its trabecular bone. Damage intensity was calculated from vertebral body residual strain following initial compressive overload using the relationship established in the compression test of trabecular bone samples.

RESULTS

Calculations from trabecular bone samples showed a strong nonlinear relationship between residual strain and trabecular bone damage intensity (R² = 0.78, P < 0.001). In damaged vertebral bodies, damage intensity was then related to vertebral creep rate (R² = 0.39, P = 0.001). This procedure enabled accelerated vertebral body creep to be predicted from morphological changes (residual strains) in the damaged vertebra.

CONCLUSION

These findings suggest that morphometric measurements obtained from fractured vertebrae can be used to quantify vertebral damage and hence to predict progressive vertebral deformity.

COVID19-CT-dataset: an open-access chest CT image repository of 1000+ patients with confirmed COVID-19 diagnosis

OBJECTIVES

The ongoing Coronavirus disease 2019 (COVID-19) pandemic has drastically impacted the global health and economy. Computed tomography (CT) is the prime imaging modality for diagnosis of lung infections in COVID-19 patients. Data-driven and Artificial intelligence (AI)-powered solutions for automatic processing of CT images predominantly rely on large-scale, heterogeneous datasets. Owing to privacy and data availability issues, open-access and publicly available COVID-19 CT datasets are difficult to obtain, thus limiting the development of AI-enabled automatic diagnostic solutions. To tackle this problem, large CT image datasets encompassing diverse patterns of lung infections are in high demand.

DATA DESCRIPTION

In the present study, we provide an open-source repository containing 1000+ CT images of COVID-19 lung infections established by a team of board-certified radiologists. CT images were acquired from two main general university hospitals in Mashhad, Iran from March 2020 until January 2021. COVID-19 infections were ratified with matching tests including Reverse transcription polymerase chain reaction (RT-PCR) and accompanying clinical symptoms. All data are 16-bit grayscale images composed of 512 × 512 pixels and are stored in DICOM standard. Patient privacy is preserved by removing all patient-specific information from image headers. Subsequently, all images corresponding to each patient are compressed and stored in RAR format.

Virtual brain grafting: Enabling whole brain parcellation in the presence of large lesions

Brain atlases and templates are at the heart of neuroimaging analyses, for which they facilitate multimodal registration, enable group comparisons and provide anatomical reference. However, as atlas-based approaches rely on correspondence mapping between images they perform poorly in the presence of structural pathology. Whilst several strategies exist to overcome this problem, their performance is often dependent on the type, size and homogeneity of any lesions present. We therefore propose a new solution, referred to as Virtual Brain Grafting (VBG), which is a fully-automated, open-source workflow to reliably parcellate magnetic resonance imaging (MRI) datasets in the presence of a broad spectrum of focal brain pathologies, including large, bilateral, intra- and extra-axial, heterogeneous lesions with and without mass effect. The core of the VBG approach is the generation of a lesion-free T1-weighted image, which enables further image processing operations that would otherwise fail. Here we validated our solution based on Freesurfer recon-all parcellation in a group of 10 patients with heterogeneous gliomatous lesions, and a realistic synthetic cohort of glioma patients (n = 100) derived from healthy control data and patient data. We demonstrate that VBG outperforms a non-VBG approach assessed qualitatively by expert neuroradiologists and Mann-Whitney U tests to compare corresponding parcellations (real patients U(6,6) = 33, z = 2.738, P < .010, synthetic-patients U(48,48) = 2076, z = 7.336, P < .001). Results were also quantitatively evaluated by comparing mean dice scores from the synthetic-patients using one-way ANOVA (unilateral VBG = 0.894, bilateral VBG = 0.903, and non-VBG = 0.617, P < .001). Additionally, we used linear regression to show the influence of lesion volume, lesion overlap with, and distance from the Freesurfer volumes of interest, on labeling accuracy. VBG may benefit the neuroimaging community by enabling automated state-of-the-art MRI analyses in clinical populations using methods such as FreeSurfer, CAT12, SPM, Connectome Workbench, as well as structural and functional connectomics. To fully maximize its availability, VBG is provided as open software under a Mozilla 2.0 license (https://github.com/KUL-Radneuron/KUL_VBG).

Declining interest in clinical imaging during the COVID-19 pandemic: An analysis of Google Trends data

OBJECTIVE

Current evidence suggests a decrease in elective diagnostic imaging procedures during the COVID-19 pandemic with potentially severe long-term consequences. The aim of this study was to quantify recent trends in public interest and related online search behavior for a range of imaging modalities, and "nowcast" future scenarios with respect to imaging use.

METHODS

We used Google Trends, a publicly available database to access search query data in systematic and quantitative fashion, to search for key terms related to clinical imaging. We queried the search volume for multiple imaging modalities, identified the most common terms, extracted data for the United States over the time range from August 1, 2016 to August 1, 2020. Results were given in relative terms, using the Google metric 'search volume index'.

RESULTS

We report a decrease in public interest across all imaging modalities since March 2020 with a subsequent slow increase starting in May 2020. Mean relative search volume (RSV) has changed by -19.4%, -38.3%, and -51.0% for the search terms "Computed tomography", "Magnetic resonance imaging", and "Mammography", respectively, and comparing the two months prior to and following March 1, 2020. RSV has since steadily recuperated reaching all-year highs.

CONCLUSION

Decrease in public interest coupled with delays and deferrals of diagnostic imaging will likely result in a high demand for healthcare in the coming months. To respond to this challenge, measures such as risk-stratification algorithms must be developed to allocate resources and avoid the risk of overstraining the healthcare system.

Nanomaterials innovation as an enabler for effective cancer interventions

Nanomedicines have been developing very rapidly and have started to play a significant role in several cancer therapeutic modalities. Early on, the nanomedicine field focused on optimizing pharmacokinetics, toxicity, and/or biodistribution of an agent through nanoparticle formulation. In other cases, where materials science is employed more decisively, nanomedicine can include the creation of new agents that take advantage of nanoscale materials properties to enhance treatment efficacy through unique mode of action, molecular targeting, or controlled drug release. Both current and future nanomedicines will seek to contribute to the therapeutic and diagnostic landscape through creative leveraging of mechanical, electrical, optical, magnetic, and biological nanomaterial properties. In this work, we discuss how by modulating these material properties, one can design more diverse and more effective cancer interventions. We focus on six areas in cancer management, including in vitro diagnostics, clinical imaging, theranostics, combination therapy, immunotherapy, and gene therapy.

A review of visual ethnography: Radiography viewed through a different lens

INTRODUCTION

The objective of this article is to provide a short review of the research methodology 'visual ethnography'.

METHOD

The review article will provide a summary of the foundations of visual ethnography, outline the key debates and refer to some of the main authors working in this field.

RESULTS

Visual Ethnography is both a methodology and a method of research. It should be selected for research in radiography when research questions seek to focus upon aspects or elements of a culture. A research plan that is designed using a visual ethnographic approach should be flexible and take into account the requirements of the researcher and research participants. Visual methods of research include the use of various images, for example, photographs, collage, film or drawings. Visual methods are commonly employed together with interviews, conversations and observation. The approach enables researchers to generate new and unique insights into cultures.

CONCLUSION

This review of visual ethnography provides background information that informs an introduction to the methodology. It demonstrates a methodology with the potential to explore culture and expand knowledge of radiography practice.

IMPLICATIONS FOR PRACTICE

The authors suggest that for future studies visual ethnography is a methodology that can expand the paradigm of radiography research.

Ligamental compartments and their relation to the passing spinal nerves are detectable with MRI inside the lumbar neural foramina

PURPOSE

Intraforaminal ligaments (IFL) in lumbar neural foramina (NF) and their relation to the lumbar spinal nerves (SN) are addressed.

METHOD

Giemsa- and PAS-stained plastinated body slices of 15 lumbar spines were made and compared to MRI and CT data acquired of the same fresh specimens. We dissected one fixed lumbar spine to discuss our results with previous literature. Macroscopic pathophysiological changes and operational interventions at these lumbar spines were excluded.

RESULTS

In the NF, thin medial IFL touch the SN. As a second compartment, intermedial vertical IFL are seen. A third lateral horizontal compartment of IFL is formed by thick cranial and caudal ligaments. Ligaments of the second and third compartments have no direct contact with the SN. From medial to lateral, the IFL thicken. All compartments are 3D reconstructed. If compartments of the IFL have no direct contact with the SN seen in the slices, a connection was noticed after dissection.

CONCLUSION

Manual dissection seems to be inappropriate for a detailed study of the IFL. The lateral and intermedial compartments being free of the SN may transmit power and protect the SN, while the thin medial IFL may lead the SN passing the NF under physiological conditions. We conclude from the close topographical relation that the IFL may be relevant in foraminal stenosis. Any herniation in the NF presses IFL to the SN. Therefore, we think the IFL themselves could cause neurogenic claudication in case of their non-physiological turnover. Visualisation of IFL seems to be possible by using MRI. These slides can be retrieved under Electronic Supplementary Material.

Clinical imaging of hypoxia: Current status and future directions

Tissue hypoxia is a key feature of many important causes of morbidity and mortality. In pathologies such as stroke, peripheral vascular disease and ischaemic heart disease, hypoxia is largely a consequence of low blood flow induced ischaemia, hence perfusion imaging is often used as a surrogate for hypoxia to guide clinical diagnosis and treatment. Importantly, ischaemia and hypoxia are not synonymous conditions as it is not universally true that well perfused tissues are normoxic or that poorly perfused tissues are hypoxic. In pathologies such as cancer, for instance, perfusion imaging and oxygen concentration are less well correlated, and oxygen concentration is independently correlated to radiotherapy response and overall treatment outcomes. In addition, the progression of many diseases is intricately related to maladaptive responses to the hypoxia itself. Thus there is potentially great clinical and scientific utility in direct measurements of tissue oxygenation. Despite this, imaging assessment of hypoxia in patients is rarely performed in clinical settings. This review summarises some of the current methods used to clinically evaluate hypoxia, the barriers to the routine use of these methods and the newer agents and techniques being explored for the assessment of hypoxia in pathological processes.

Multimodal imaging-based therapeutic fingerprints for optimizing personalized interventions: Application to neurodegeneration

Personalized Medicine (PM) seeks to assist the patients according to their specific treatment needs and potential intervention responses. However, in the neurological context, this approach is limited by crucial methodological challenges, such as the requirement for an understanding of the causal disease mechanisms and the inability to predict the brain's response to therapeutic interventions. Here, we introduce and validate the concept of the personalized Therapeutic Intervention Fingerprint (pTIF), which predicts the effectiveness of potential interventions for controlling a patient's disease evolution. Each subject's pTIF can be inferred from multimodal longitudinal imaging (e.g. amyloid-β, metabolic and tau PET; vascular, functional and structural MRI). We studied an aging population (N = 331) comprising cognitively normal and neurodegenerative patients, longitudinally scanned using six different neuroimaging modalities. We found that the resulting pTIF vastly outperforms cognitive and clinical evaluations on predicting individual variability in gene expression (GE) profiles. Furthermore, after regrouping the patients according to their predicted primary single-target interventions, we observed that these pTIF-based subgroups present distinctively altered molecular pathway signatures, supporting the across-population identification of dissimilar pathological stages, in active correspondence with different therapeutic needs. The results further evidence the imprecision of using broad clinical categories for understanding individual molecular alterations and selecting appropriate therapeutic needs. To our knowledge, this is the first study highlighting the direct link between multifactorial brain dynamics, predicted treatment responses, and molecular alterations at the patient level. Inspired by the principles of PM, the proposed pTIF framework is a promising step towards biomarker-driven assisted therapeutic interventions, with additional important implications for selective enrollment of patients in clinical trials.

Importance of Consistent Datasets in Musculoskeletal Modelling: A Study of the Hand and Wrist

Hand musculoskeletal models provide a valuable insight into the loads withstood by the upper limb; however, their development remains challenging because there are few datasets describing both the musculoskeletal geometry and muscle morphology from the elbow to the finger tips. Clinical imaging, optical motion capture and microscopy were used to create a dataset from a single specimen. Subsequently, a musculoskeletal model of the wrist was developed based on these data to estimate muscle tensions and to demonstrate the potential of the provided parameters. Tendon excursions and moment arms predicted by this model were in agreement with previously reported experimental data. When simulating a flexion–extension motion, muscle forces reached 90 N among extensors and a co-contraction of flexors, amounting to 62.6 N, was estimated by the model. Two alternative musculoskeletal models were also created based on anatomical data available in the literature to illustrate the effect of combining incomplete datasets. Compared to the initial model, the intensities and load sharing of the muscles estimated by the two alternative models differed by up to 180% for a single muscle. This confirms the importance of using a single source of anatomical data when developing such models.

Clinical Evaluation of Bone Strength and Fracture Risk

PURPOSE OF REVIEW

This paper seeks to evaluate and compare recent advances in the clinical assessment of the changes in bone mechanical properties that take place as a result of osteoporosis and other metabolic bone diseases and their treatments.

RECENT FINDINGS

In addition to the standard of DXA-based areal bone mineral density (aBMD), a variety of methods, including imaging-based structural measurements, finite element analysis (FEA)-based techniques, and alternate methods including ultrasound, bone biopsy, reference point indentation, and statistical shape and density modeling, have been developed which allow for reliable prediction of bone strength and fracture risk. These methods have also shown promise in the evaluation of treatment-induced changes in bone mechanical properties. Continued technological advances allowing for increasingly high-resolution imaging with low radiation dose, together with the expanding adoption of DXA-based predictions of bone structure and mechanics, as well as the increasing awareness of the importance of bone material properties in determining whole-bone mechanics, lead us to anticipate substantial future advances in this field.

Advanced alveolar echinococcosis disease associated with Budd-Chiari syndrome

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Alveolar echinococcosis is an emerging community problem.

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Advanced disease may be presented with end stage liver disease and Budd–Chiari syndrome.

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Living donor liver transplantation may be a treatment option. However, outcomes may be poor.

Introduction

Alveolar echinococceal disease of the liver is rare. Echinococcus multilocularis is responsible for the development of the related clinical conditions. Advanced disease may result with serious complications such as end stage liver disease and Budd–Chiari syndrome.

Presentation of case

In this presentation, a 28 years-old woman who was a case with advanced alveolar echinococcosis complicated with a Budd–Chiari syndrome and was performed successful living donor liver transplantation, has been demonstrated with clinical and radiological images.

Discussion

Initially there may be no clinical evidence of the disease in humans for years. Severity and fatality are the significant characteristics of the natural history. Extension to the surrounding tissues and metastasis of the parasitic mass may be observed. Prevention is essential in disease control. Serologic assay may identify the parasite. However, early diagnosis is rare. Staging is based on radiologic imaging. Some patients with advanced disease may require surgery. Hepatic resection and liver transplantation are accepted procedures in selected patients.

Conclusion

The importance of early diagnosis to prevent advanced complications such as development of Budd–Chiari syndrome and metastasis has been underlined.

The rise of large-scale imaging studies in psychiatry

From the initial arguments over whether 12 to 20 subjects were sufficient for an fMRI study, sample sizes in psychiatric neuroimaging studies have expanded into the tens of thousands. These large-scale imaging studies fall into several categories, each of which has specific advantages and challenges. The different study types can be grouped based on their level of control: meta-analyses, at one extreme of the spectrum, control nothing about the imaging protocol or subject selection criteria in the datasets they include, On the other hand, planned multi-site mega studies pour intense efforts into strictly having the same protocols. However, there are several other combinations possible, each of which is best used to address certain questions. The growing investment of all these studies is delivering on the promises of neuroimaging for psychiatry, and holds incredible potential for impact at the level of the individual patient. However, to realize this potential requires both standardized data-sharing efforts, so that there is more staying power in the datasets for re-use and new applications, as well as training the next generation of neuropsychiatric researchers in "Big Data" techniques in addition to traditional experimental methods. The increased access to thousands of datasets along with the needed informatics demands a new emphasis on integrative scientific methods.