This 11th edition of the book Modern Nutrition in Health and Disease, featuring the work of more than 190 expert authors and divided into five parts, fully explains and encapsulates the fundamentals of nutrition and its role in contemporary society, from mastering the basic science of nutrient metabolism and function to applying nutritional concepts to combat human disease. Part I comprehensively covers specific dietary components, including major dietary constituents, minerals, vitamins and other Other CABI sites 

Modern Nutrition in Health and Disease

We present VoxelMorph, a fast learning-based framework for deformable, pairwise medical image registration. Traditional registration methods optimize an objective function for each pair of images, which can be time-consuming for large datasets or rich deformation models. In contrast to this approach, and building on recent learning-based methods, we formulate registration as a function that maps an input image pair to a deformation field that aligns these images. We parameterize the function via a convolutional neural network (CNN), and optimize the parameters of the neural network on a set of images. Given a new pair of scans, VoxelMorph rapidly computes a deformation field by directly evaluating the function. In this work, we explore two different training strategies. In the first (unsupervised) setting, we train the model to maximize standard image matching objective functions that are based on the image intensities. In the second setting, we leverage auxiliary segmentations available in the training data. We demonstrate that the unsupervised model's accuracy is comparable to state-of-the-art methods, while operating orders of magnitude faster. We also show that VoxelMorph trained with auxiliary data improves registration accuracy at test time, and evaluate the effect of training set size on registration. Our method promises to speed up medical image analysis and processing pipelines, while facilitating novel directions in learning-based registration and its applications. Our code is freely available at this http URL.

/pdf/voxelmorph-a-learning-framework-for-deformable-medical-image-4slzlz3vmh.pdf

VoxelMorph: A Learning Framework for Deformable Medical Image Registration

In this chapter, you will see how the simplex method simplifies when it is applied to a class of optimization problems that are known as “network flow models.” You will also see that if a network flow model has “integer-valued data,” the simplex method finds an optimal solution that is integer-valued.

Flows in Networks

Epilepsy in adults

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(14)60456-6.pdf

Epilepsy: new advances

Acquired copper deficiency has been recognised as a rare cause of anaemia and neutropenia for over half a century. Copper deficiency myelopathy (CDM) was only described within the last decade, and represents a treatable cause of non-compressive myelopathy which closely mimics subacute combined degeneration due to vitamin B12 deficiency. Here, 55 case reports from the literature are reviewed regarding their demographics, aetiology, haematological and biochemical parameters, spinal imaging, treatment and outcome. The pathophysiology of disorders of copper metabolism is discussed. CDM most frequently presented in the fifth and sixth decades and was more common in women (F:M = 3.6:1). Risk factors included previous upper gastrointestinal surgery, zinc overload and malabsorption syndromes, all of which impair copper absorption in the upper gastrointestinal tract. No aetiology was established in 20% of cases. High zinc levels were detected in some cases not considered to have primary zinc overload, and in this situation the contribution of zinc to the copper deficiency state remained unclear. Cytopenias were found in 78%, particularly anaemia, and a myelodysplastic syndrome may have been falsely diagnosed in the past. Spinal MRI was abnormal in 47% and usually showed high T2 signal in the posterior cervical and thoracic cord. In a clinically compatible case, CDM may be suggested by the presence of one or more risk factors and/or cytopenias. Low serum copper and caeruloplasmin levels confirmed the diagnosis and, in contrast to Wilson’s disease, urinary copper levels were typically low. Treatment comprised copper supplementation and modification of any risk factors, and led to haematological normalisation and neurological improvement or stabilisation. Since any neurological recovery was partial and case numbers of CDM will continue to rise with the growing use of bariatric gastrointestinal surgery, clinical vigilance will remain the key to minimising neurological sequelae. Recommendations for treatment and prevention are made.

/pdf/copper-deficiency-myelopathy-5ax869bd7q.pdf

Copper deficiency myelopathy

Most medical image registration algorithms suffer from a directionality bias that has been shown to largely impact subsequent analyses. Several approaches have been proposed in the literature to address this bias in the context of nonlinear registration, but little work has been done for global registration. We propose a symmetric approach based on a block-matching technique and least-trimmed square regression. The proposed method is suitable for multimodal registration and is robust to outliers in the input images. The symmetric framework is compared with the original asymmetric block-matching technique and is shown to outperform it in terms of accuracy and robustness. The methodology presented in this article has been made available to the community as part of the NiftyReg open-source package.

https://www.spiedigitallibrary.org/journals/Journal-of-Medical-Imaging/volume-1/issue-2/024003/Global-image-registration-using-a-symmetric-block-matching-approach/10.1117/1.JMI.1.2.024003.pdf

Global image registration using a symmetric block-matching approach

Brain imaging has a crucial role in the presurgical assessment of patients with epilepsy. Structural imaging reveals most cerebral lesions underlying focal epilepsy. Advances in MRI acquisitions including diffusion-weighted imaging, post-acquisition image processing techniques, and quantification of imaging data are increasing the accuracy of lesion detection. Functional MRI can be used to identify areas of the cortex that are essential for language, motor function, and memory, and tractography can reveal white matter tracts that are vital for these functions, thus reducing the risk of epilepsy surgery causing new morbidities. PET, SPECT, simultaneous EEG and functional MRI, and electrical and magnetic source imaging can be used to infer the localisation of epileptic foci and assist in the design of intracranial EEG recording strategies. Progress in semi-automated methods to register imaging data into a common space is enabling the creation of multimodal three-dimensional patient-specific datasets. These techniques show promise for the demonstration of the complex relations between normal and abnormal structural and functional data and could be used to direct precise intracranial navigation and surgery for individual patients.

/pdf/brain-imaging-in-the-assessment-for-epilepsy-surgery-8hu7qwjmf6.pdf

Brain imaging in the assessment for epilepsy surgery

Diffusion magnetic resonance imaging is a quantitative imaging technique that measures the underlying molecular diffusion of protons. Diffusion-weighted imaging (DWI) quantifies the apparent diffusion coefficient (ADC) which was first used to detect early ischemic stroke. However this does not take account of the directional dependence of diffusion seen in biological systems (anisotropy).Diffusion tensor imaging (DTI) provides a mathematical model of diffusion anisotropy and is widely used. Parameters, including fractional anisotropy (FA), mean diffusivity (MD), parallel and perpendicular diffusivity can be derived to provide sensitive, but non-specific, measures of altered tissue structure. They are typically assessed in clinical studies by voxel-based or region-of-interest based analyses.The increasing recognition of the limitations of the diffusion tensor model has led to more complex multi-compartment models such as CHARMED, AxCaliber or NODDI being developed to estimate microstructural parameters including axonal diameter, axonal density and fiber orientations. However these are not yet in routine clinical use due to lengthy acquisition times.In this review, I discuss how molecular diffusion may be measured using diffusion MRI, the biological and physical bases for the parameters derived from DWI and DTI, how these are used in clinical studies and the prospect of more complex tissue models providing helpful micro-structural information.

/pdf/the-physical-and-biological-basis-of-quantitative-parameters-1dvuozjx78.pdf

Gavin P. Winston

Papers

Copper deficiency myelopathy

Global image registration using a symmetric block-matching approach

Brain imaging in the assessment for epilepsy surgery

The physical and biological basis of quantitative parameters derived from diffusion MRI

Advanced diffusion imaging sequences could aid assessing patients with focal cortical dysplasia and epilepsy