Subject-Specific Lesion Generation and Pseudo-Healthy Synthesis for Multiple Sclerosis Brain Images

Understanding the intensity characteristics of brain lesions is key for defining image-based biomarkers in neurological studies and for predicting disease burden and outcome. In this work, we present a novel foreground-based generative method for modelling the local lesion characteristics that can both generate synthetic lesions on healthy images and synthesize subject-specific pseudo-healthy images from pathological images. Furthermore, the proposed method can be used as a data augmentation module to generate synthetic images for training brain image segmentation networks. Experiments on multiple sclerosis (MS) brain images acquired on magnetic resonance imaging (MRI) demonstrate that the proposed method can generate highly realistic pseudo-healthy and pseudo-pathological brain images. Data augmentation using the synthetic images improves the brain image segmentation performance compared to traditional data augmentation methods as well as a recent lesion-aware data augmentation technique, CarveMix. The code will be released at https://github.com/dogabasaran/lesion-synthesis.Comment: 13 pages, 6 figures, 2022 MICCAI SASHIMI (Simulation and Synthesis in Medical Imaging) Workshop pape

High prevalence of radiological vertebral fractures in adult patients with Ehlers-Danlos syndrome

Previous studies have reported an increased prevalence of osteoporosis in Ehlers–Danlos syndrome (EDS), but these were limited by a small number of patients and lack of information on fragility fractures. In this cross-sectional study, we evaluated the prevalence of radiological vertebral fractures (by quantitative morphometry) and bone mineral density (BMD, at lumbar spine, total hip and femoral neck by dual-energy X-ray absorptiometry) in 52 consecutive patients with EDS (10 males, 42 females; median age 41 years, range: 21–71; 12 with EDS classic type, 37 with EDS hypermobility type, 1 with classic vascular-like EDS, and 2 without specific classification) and 197 control subjects (163 females and 34 males; median age 49 years, range: 26–83) attending an outpatient bone clinic. EDS patients were also evaluated for back pain by numeric pain rating scale (NRS-11).Vertebral fractures were significantly more prevalent in EDS as compared to the control subjects (38.5% vs. 5.1%; p < 0.001) without significant differences in BMD at either skeletal sites. In EDS patients, the prevalence of vertebral fractures was not significantly (p = 0.72) different between classic and hypermobility types. BMD was not significantly different between fractured and non-fractured EDS patients either at lumbar spine (p = 0.14), total hip (p = 0.08), or femoral neck (p = 0.21). Severe back pain (≥ 7 NRS) was more frequent in EDS patients with vertebral fractures as compared to those without fractures (60% vs. 28%; p = 0.04). In conclusion, this is the first study showing high prevalence of vertebral fractures in a relatively large population of EDS patients. Vertebral fractures were associated with more severe back pain suggesting a potential involvement of skeletal fragility in determining poor quality of life. The lack of correlation between vertebral fractures and BMD is consistent with the hypothesis that bone quality may be impaired in EDS

LesionMix: A Lesion-Level Data Augmentation Method for Medical Image Segmentation

Data augmentation has become a de facto component of deep learning-based medical image segmentation methods. Most data augmentation techniques used in medical imaging focus on spatial and intensity transformations to improve the diversity of training images. They are often designed at the image level, augmenting the full image, and do not pay attention to specific abnormalities within the image. Here, we present LesionMix, a novel and simple lesion-aware data augmentation method. It performs augmentation at the lesion level, increasing the diversity of lesion shape, location, intensity and load distribution, and allowing both lesion populating and inpainting. Experiments on different modalities and different lesion datasets, including four brain MR lesion datasets and one liver CT lesion dataset, demonstrate that LesionMix achieves promising performance in lesion image segmentation, outperforming several recent Mix-based data augmentation methods. The code will be released at https://github.com/dogabasaran/lesionmix.Comment: 13 pages, 5 figures, 4 tables, MICCAI DALI Workshop 202

Improving reproducibility in synchrotron tomography using implementation-adapted filters

For reconstructing large tomographic datasets fast, filtered backprojection-type or Fourier-based algorithms are still the method of choice, as they have been for decades. These robust and computationally efficient algorithms have been integrated in a broad range of software packages. Despite the fact that the underlying mathematical formulas used for image reconstruction are unambiguous, variations in discretisation and interpolation result in quantitative differences between reconstructed images obtained from different software. This hinders reproducibility of experimental results. In this paper, we propose a way to reduce such differences by optimising the filter used in analytical algorithms. These filters can be computed using a wrapper routine around a black-box implementation of a reconstruction algorithm, and lead to quantitatively similar reconstructions. We demonstrate use cases for our approach by computing implementation-adapted filters for several open-source implementations and applying it to simulated phantoms and real-world data acquired at the synchrotron. Our contribution to a reproducible reconstruction step forms a building block towards a fully reproducible synchrotron tomography data processing pipeline.Comment: 30 pages, 7 figure

Olive leaves extract mediated zero-valent iron nanoparticles: synthesis, characterization, and assessment as adsorbent for nickel (II) ions in aqueous medium

Zero-valent iron nanoparticles (NZVI-NPs) possess significantly high surface area and volume ratio, and this unique surface characteristic has enhanced reactivity to their adsorption potential. In this work, a bio-matter (Olive leaves extract) is deployed as a nature-inspired reducing agent for the synthesis of NZVI-NPs. The particle size of NZVINPs has been determined using particle sizer. The NZVI-NPs are characterized using analytical and morphological techniques such as ultraviolet − visible spectroscopy (UV − vis), energy dispersive X-ray spectroscopy (EDS), X-ray diffraction spectroscopy (XRD), scanning electron microscope (SEM), Brunauer–Emmett–Teller (BET), and Fourier transform infrared (FTIR) spectroscopy. The average crystalline size of NZVINPs are around 30–60 nm while maximum adsorption is at 225 nm. XRD spectrum shows two distinctive diffraction peaks at 25.40° and 42.50° corresponding to lattice plane value indexed at (200) and (222) planes of faced centered cubic (FCC). At optimized experimental conditions, NZVI-NPs show 97% removal efficiency of Ni+2 ions from aqueous solution. The equilibrium time has been found to be 55 min and the monolayer maximum adsorption capacity is 139.5 mg/g. Kinetically, Ni+2 ions adsorption has been modelled using various physical isotherms and the data best fitted Freundlich isotherm model and pseudo-first-order kinetic; revealing a maximum adsorption capacity of 139.5 mg/g at 25 ± 3 °C and pH of 6.5. Desorption tests affirm the possibility of recovering reasonable amount of NZVI-NPs after used. The specific surface area of the NZVI-NPs sample measured by BET analysis is 21.9967 m2/g indicating a high adsorption capacity

Influence of vitreoretinal traction localization on horseshoe tear configuration and risk of rhegmatogenous retinal detachment

Purpose. To evaluate the relationship between the shape of horseshoe tear and the localization of vitreoretinal tractions (VRT) using methods of the peripheral vitreoretinal interface visualization and classify horseshoe tears by shape for sur gical planning.Material and methods. We studied horseshoe tears parameters of 52 patients (52 eyes). The localization of VRT was determined by widefield OCT, the horseshoe tear shape was determined as the ratio of length to width of the tear (l/b) by multispectral laser scanning. The ratio of the obtained data was evaluated by the Spearman correlation analysis. We used Ward’s method of hierarchical clustering to classify the horseshoe tears by shape. The obtained data were used to perform YAG-laser excision of the vitreoretinal adhesion zone in patients with rhegmatogenous retinal detachment as part of the combined microinvasive laser-surgical technology.Results. The l/b ratio ranged from 1/4 to 3/1. A strong negative correlation has been revealed between the horseshoe tear shape and the fixation of vitreoretinal tractions (rs -0.95; p &lt;0.05). Horseshoe tears were identified in 4 groups using Ward’s method of clustering. Each group corresponded to a specific localization of VRT. The extension of VRT beyond the tear was associated with a high risk of rhegmatogenous retinal detachment.Conclusion. A significant correlation has been found between the studied factors confirm the possibility of using data on the horseshoe tear shape for an approximate evaluation of vitreoretinal adhesion localization. The obtained data allows to determine the exact VRT excision zone when performing combined laser-surgical technology without the need for preoperative wide-field OCT

Generative Modelling of the Ageing Heart with Cross-Sectional Imaging and Clinical Data

Cardiovascular disease, the leading cause of death globally, is an age-related disease. Understanding the morphological and functional changes of the heart during ageing is a key scientific question, the answer to which will help us define important risk factors of cardiovascular disease and monitor disease progression. In this work, we propose a novel conditional generative model to describe the changes of 3D anatomy of the heart during ageing. The proposed model is flexible and allows integration of multiple clinical factors (e.g. age, gender) into the generating process. We train the model on a large-scale cross-sectional dataset of cardiac anatomies and evaluate on both cross-sectional and longitudinal datasets. The model demonstrates excellent performance in predicting the longitudinal evolution of the ageing heart and modelling its data distribution. The codes are available at https://github.com/MengyunQ/AgeHeart

BIOMEDIATED - TITANIUM NANOCOMPOSITE FOR CORROSION PROTECTION

The present invention relates to a method of inhibiting corrosion of steel in contact with a corrosive solution . The method involves mixing an olive leaf extract titanium nano composite with the corrosive solution . The olive leaf extract titanium nanocomposite may be made by reducing TiC14 with an olive leaf extract , which forms nanoparticles with an average size of 50-100 nm