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Each year about a third of elderly aged 65 or older experience a fall. Many of these falls may have been avoided if fall risk assessment and prevention tools where available in a daily living situation. We identify what kind of information is relevant for doing fall risk assessment and prevention using wearable sensors in a daily living environment by investigating current research, distinguishing between prospective and context-aware fall risk assessment and prevention. Based on our findings, we propose a fall risk awareness protocol as a fall prevention tool integrating both wearables and ambient sensing technology into a single platform., (Copyright © 2016. Published by Elsevier Inc.)

Conventional microscopic techniques, to study embryonic development, require large numbers of embryos and are invasive, making follow-up impossible. We explored the use of in vivo MRI to study embryonic development, in general, and cardiovascular development in particular, over time. Wild-type quail embryos (n = 11) were imaged at embryonic days 3, 5, 7, 9, and 11, covering the main time course of embryonic heart development. On each imaging day cardiac morphology was evaluated and embryonic length was measured. MRI-embryos as well as control embryos (n = 11) were sacrificed at day 11 and scored for external malformations, while embryonic wet weight and stage were determined. In addition, venous clipped embryos (n = 4), known to develop cardiovascular malformations, were scanned at regular intervals and sacrificed at day 9 for histological analysis ex vivo. We were able to follow heart development of individual quail embryos inside their shell non-invasively over time, with sufficient detail to study cardiac morphology in vivo. We did not find any adverse effect of the repeated MRI examinations on morphology, length, or weight. Prenatally diagnosed malformations, like ventricular septal defects and aortic arch interruptions were confirmed by histology. In conclusion, micro-MRI can be used to evaluate in vivo early embryonic development and to diagnose cardiovascular malformations prenatally.

Objective: In this paper, we present an autonomous virtual mobile robot (AVMR) for three-dimensional (3D) exploration of unknown tubular-like structures in 3D images., Methods and Materials: The trajectory planning for 3D central navigation is achieved by combining two neuro-fuzzy controllers, and is based on 3D sensory information; a Hough transform is used to locally fit a cylinder during the exploration, estimating the local radius of the tube. Nonholonomic constraints are applied to assure a smooth, continuous and unique final path. When applied to 3D medical images, the AVMR operates as a virtual endoscope, directly providing anatomical measurements of the organ. After a thorough validation on challenging synthetic environments, we applied our method to eight micro-CT datasets of cochleae., Results: Validation on synthetic environments proved the robustness of our method, and highlighted key parameters for the design of the AVMR. When applied to the micro-CT datasets, the AVMR automatically estimated length and radius of the cochleae: results were compared to manual delineations, proving the accuracy of our approach., Conclusions: The AVMR presents several advantages when used as a virtual endoscope: the nonholonomic constraint guarantees a unique and smooth central path, which can be reliably used both for qualitative and quantitative investigation of 3D medical datasets. Results on the micro-CT cochleae are a significant step towards the validation of more clinical computed tomography (CT) studies.

In this work, we aimed at correlating focal atrophy in periventricular structures with cognitive function, in the spectrum from healthy subjects to severe Alzheimer disease: 28 subjects with normal cognition and 84 patients presenting various degrees of cognitive impairment were included in the study. The cognitive level of each subject was assessed with the Mini-Mental State Examination (MMSE). Atrophy in periventricular structures was inferred by modeling and analyzing local shape variations of brain ventricles: for a given subject, we distinguished between the severity of atrophy, estimated as local enlargement (in mm) of the ventricular surface relative to an average normal subject, and the extent of atrophy, defined as the percentage of the ventricular surface (global or per anatomical region) significantly different from an average control. Linear regression across subjects was performed to evaluate the correlation between atrophy and MMSE score. The severity of atrophy showed good correlation with MMSE score in the left thalamus, the left temporal horn, the left corona radiata, and the right caudate nuclei. The extent of atrophy showed no significant correlations. In conclusion, the MMSE scores correlate with localized depth of atrophy in well-defined periventricular structures.

The aim of this work was to identify ventricular shape-based biomarkers in MR images to discriminate between patients with Alzheimer's disease (AD) and healthy elderly. Clinical MR images were collected for 58 patients and 28 age-matched healthy controls. After normalizing all the images the ventricular cerebrospinal fluid was semiautomatically extracted for each subject and an innovative technique for fully automatic shape modeling was applied to generate comparable meshes of all ventricles. The search for potential biomarkers was carried out with repeated permutation tests: results highlighted well-defined areas of the ventricular surface being discriminating features for AD: the left inferior medial temporal horn, the right medial temporal horn (superior and inferior), and the areas close to the left anterior part of the corpus callosum and the head of the right caudate nucleus. The biomarkers were then used as features to build an intelligent machine for AD detection: a Support Vector Machine was trained on AD and healthy subjects and subsequently tested with leave-1-out experiments and validation tests on previously unseen cases. The results showed a sensitivity of 76% for AD, with an overall accuracy of 84%, proving that suitable biomarkers for AD can be detected in clinical MR images., ((c) 2008 Wiley-Liss, Inc.)

Background and Purpose: Previous studies have shown involvement of both gray matter (GM) and white matter (WM) in mild cognitive impairment (MCI) and Alzheimer disease (AD). In this study, we assessed the lobar distribution of the GM and WM pathology over the brain and the association of lobar distribution with global cognitive decline., Materials and Methods: Fifty-five patients with AD, 19 patients with MCI, and 43 subjects with normal cognitive function participated in this study. GM and WM were segmented on dual fast spin-echo and fluid-attenuated inversion recovery MR images. A custom template representing anatomic areas was applied. Magnetization transfer imaging (MTI) peak height and mean magnetization transfer ratio (MTR) provided measures for structural brain damage., Results: Both mean MTR and MTI peak height showed that patients with AD had more structural brain damage in the GM of all lobes compared with controls. Patients with MCI had lower GM peak height compared with controls for the temporal and frontal lobe. WM peak height was lower for all lobes investigated for patients with both AD and MCI. WM mean MTR was lower in the frontal, parietal, and temporal lobes for patients with AD compared with controls. Age and both temporal GM peak height and mean MTR were the only parameters that predicted cognition., Conclusion: This study shows that in addition to more focal GM MTI changes in the temporal and frontal lobes, widespread WM changes are present in the earliest stages of AD. This might point to an important role for WM pathology in the earliest stage of AD.

Purpose: To assess whether magnetization transfer imaging (MTI) parameters change in correspondence with clinical changes in NPSLE patients., Materials and Methods: Nineteen female patients (mean age=37.5 years, range=19-64) underwent MTI on at least two separate occasions (mean time between scans=25.4 months, range=5.4-52.3 months). Twenty-four pairs of scans of 19 patients were available. Each patient's clinical course was classified as improved, stable, or deteriorated. Whole-brain magnetization transfer ratio (MTR) histograms were generated. The peak height of these histograms was used as an estimate of parenchymal integrity. Based on the change in clinical status, paired examinations were grouped and tested for significant differences between the first and second examinations using paired-samples t-tests., Results: Four patients clinically deteriorated, all patients showed a significant peak height decrease (mean decrease=8.6%, P=0.02), and in 14 patients with stable disease the peak height did not change significantly (mean increase=0.4%). Six patients clinically improved, and all showed a significant relative peak height increase (mean increase=12.0%, P=0.02)., Conclusion: The peak height of whole-brain MTR histograms corresponds to changes in the clinical status of individual NPSLE patients. This suggests that MTI can be a valuable tool in the clinical assessment of such patients., (Copyright (c) 2006 Wiley-Liss, Inc.)

The brain ventricles are surrounded by gray and white matter structures that are often affected in dementia in general and Alzheimer's disease (AD) in particular. Any change of volume or shape occurring in these structures must affect the volume and shape of the ventricles. It is well known that ventricular volume is significantly higher in AD patients compared to age-matched healthy subjects. However, the large overlap between the two volume distributions makes the measurement unsuitable as a biomarker of the disease. The purpose of this work was to assess whether local shape differences of the ventricles can be detected when comparing AD patients and controls. In this work, we captured the ventricle's shape and shape variations of 29 AD subjects and 25 age-matched controls, using a fully automatic shape modeling technique. By applying permutation tests on every single node of a mesh representation of the shapes, we identified local areas with significant differences. About 22% of an average surface of the ventricles presented significant difference (P < 0.05) ( approximately 14% of the left against approximately 7% of the right side). We found out that in patients with Alzheimer disease, not only the lateral horns were significantly affected, but also the areas adjacent to the anterior corpus callosum, the splenium of the corpus callosum, the amygdala, the thalamus, the tale of the caudate nuclei (especially the left one), and the head of the left caudate nucleus.

Background and Purpose: Quantitative MR imaging techniques such as magnetization transfer imaging (MTI), diffusion-weighted imaging (DWI), and MR spectroscopy are promising diagnostic tools for use with patients with diffuse brain diseases such as neuropsychiatric systemic lupus erythematosus (NPSLE). Such patients are often on corticosteroid (CS) treatment. Presently, it is unknown whether CSs per se influence quantitative MR imaging measurements. The aim of this study was to evaluate the effect of low-dose oral CSs on MTI, DWI, and MR spectroscopy parameters of the brain., Methods: Twenty-seven rheumatoid arthritis (RA) patients with and without CS medication and 15 healthy controls were subjected to conventional MR imaging, whole-brain MTI and DWI, and single-voxel MR spectroscopy. Oral CSs were used by 13 of the RA patients. Univariate analyses with age as a covariate were performed on MTI, DWI, and MR spectroscopy parameters between RA patients with and without CSs and healthy controls. Pearson correlations were calculated between all imaging parameters and duration of disease, duration of CS use, and CS dosage., Results: No significant differences between the groups of subjects or significant correlations with clinical parameters were found for MTI, DWI and MR spectroscopy parameters., Conclusion: In this study, we found no evidence for an effect of low-dose oral CSs on whole-brain MTI and DWI histogram parameters and single-voxel MR spectroscopy measurements of the brain. The results of this study demonstrate that it is unlikely that MTI, DWI, and MR spectroscopy parameters reported in NPSLE studies are confounded by low-dose oral CS.

In this paper, we present a new framework for shape modelling and analysis: we suggest to look at the problem from a pattern recognition point of view, and claim that under this prospective several advantages are achieved. The modelling of a surface with a point distribution model is seen as an unsupervised clustering problem, and tackled by using growing cell structures. The adaptation of a model to new shapes is studied as a classification task, and provides a straightforward solution to the point correspondence problem in active shape modelling. The method is illustrated and tested in 3D synthetic datasets and applied to the modelling of brain ventricles in an elderly population.