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The technique of colour EM that was recently developed enabled localisation of specific macromolecules/proteins of interest by the targeted deposition of diaminobenzidine (DAB) conjugated to lanthanide chelates. By acquiring lanthanide elemental maps by energy-filtered transmission electron microscopy (EFTEM) and overlaying them in pseudo-colour over the conventional greyscale TEM image, a colour EM image is generated. This provides a powerful tool for visualising subcellular component/s, by the ability to clearly distinguish them from the general staining of the endogenous cellular material. Previously, the lanthanide elemental maps were acquired at the high-loss M4,5 edge (excitation of 3d electrons), where the characteristic signal is extremely low and required considerably long exposures. In this paper, we explore the possibility of acquiring the elemental maps of lanthanides at their N4,5 edge (excitation of 4d electrons), which occurring at a much lower energy-loss regime, thereby contains significantly greater total characteristic signal owing to the higher inelastic scattering cross-sections at the N4,5 edge. Acquiring EFTEM lanthanide elemental maps at the N4,5 edge instead of the M4,5 edge, provides ∼4× increase in signal-to-noise and ∼2× increase in resolution. However, the interpretation of the lanthanide maps acquired at the N4,5 edge by the traditional 3-window method, is complicated due to the broad shape of the edge profile and the lower signal-above-background ratio. Most of these problems can be circumvented by the acquisition of elemental maps with the more sophisticated technique of EFTEM Spectrum Imaging (EFTEM SI). Here, we also report the chemical synthesis of novel second-generation DAB lanthanide metal chelate conjugates that contain 2 lanthanide ions per DAB molecule in comparison with 0.5 lanthanide ion per DAB in the first generation. Thereby, fourfold more Ln3+ per oxidised DAB would be deposited providing significant amplification of signal. This paper applies the colour EM technique at the intermediate-loss energy-loss regime to three different cellular targets, namely using mitochondrial matrix-directed APEX2, histone H2B-Nucleosome and EdU-DNA. All the examples shown in the paper are single colour EM images only.

ObjectiveTo identify research works that exemplify recent developments in the field of sensors, signals, and imaging informatics.MethodA broad literature search was conducted using PubMed and Web of Science, supplemented with individual papers that were nominated by section editors. A predefined query made from a combination of Medical Subject Heading (MeSH) terms and keywords were used to search both sources. Section editors then filtered the entire set of retrieved papers with each paper having been reviewed by two section editors. Papers were assessed on a three-point Likert scale by two section editors, rated from 0 (do not include) to 2 (should be included). Only papers with a combined score of 2 or above were considered.ResultsA search for papers was executed at the start of January 2019, resulting in a combined set of 1,459 records published in 2018 in 119 unique journals. Section editors jointly filtered the list of candidates down to 14 nominations. The 14 candidate best papers were then ranked by a group of eight external reviewers. Four papers, representing different international groups and journals, were selected as the best papers by consensus of the International Medical Informatics Association (IMIA) Yearbook editorial board.ConclusionsThe fields of sensors, signals, and imaging informatics have rapidly evolved with the application of novel artificial intelligence/machine learning techniques. Studies have been able to discover hidden patterns and integrate different types of data towards improving diagnostic accuracy and patient outcomes. However, the quality of papers varied widely without clear reporting standards for these types of models. Nevertheless, a number of papers have demonstrated useful techniques to improve the generalizability, interpretability, and reproducibility of increasingly sophisticated models.

Objective: To summarize significant contributions to sensor, signal, and imaging informatics published in 2016. Methods: We conducted an extensive search using PubMed® and Web of Science® to identify the scientific contributions published in 2016 that addressed sensors, signals, and imaging in medical informatics. The three section editors selected 15 candidate best papers by consensus. Each candidate article was reviewed by the section editors and at least two other external reviewers. The final selection of the six best papers was conducted by the editorial board of the Yearbook. Results: The selected papers of 2016 demonstrate the important scientific advances in management and analysis of sensor, signal, and imaging information. Conclusion: The growing volume of signal and imaging data provides exciting new challenges and opportunities for research in medical informatics. Evolving technologies provide faster and more effective approaches for pattern recognition and diagnostic evaluation. The papers selected here offer a small glimpse of the high-quality scientific work published in 2016 in the domain of sensor, signal, and imaging informatics.

This paper presents a set of validation procedures for nonrigid registration of functional EPI to anatomical M~ brain images. Although various registration techniques have been developed and validated for high-resolution anatomical MRI images, due to a lack of quantitative and qualitative validation procedures, the use of nonrigid registration between functional EPI and anatomical MRI images has not yet been deployed in neuroimaging studies. In this paper, the performance of a robust formulation of a nonrigid registration technique is evaluated in a quantitative manner based on simulated data and is further evaluated in a quantitative and qualitative manner based on in vivo data as compared to the commonly used rigid and affine registration techniques in the neuroimaging software packages. The nonrigid registration technique is formulated as a second-order constrained optimization problem using a free-form deformation model and mutual information similarity measure. Bound constraints, resolution level and cross-validation issues have been discussed to show the degree of accuracy and effectiveness of the nonrigid registration technique. The analyses performed reveal that the nonrigid approach provides a more accurate registration, in particular when the functional regions of interest lie in regions distorted by susceptibility artifacts. [ABSTRACT FROM AUTHOR]

With the development of medical imaging modalities and image processing algorithms, there arises a need for methods of their comprehensive quantitative evaluation. In particular, this concerns the algorithms for vessel tracking and segmentation in magnetic resonance angiography images. The problem can be approached by using synthetic images, where true geometry of vessels is known. This paper presents a framework for computer modeling of MRA imaging and the results of its validation. A new model incorporates blood flow simulation within MR signal computation kernel. The proposed solution is unique, especially with respect to the interface between flow and image formation processes. Furthermore it utilizes the concept of particle tracing. The particles reflect the flow of fluid they are immersed in and they are assigned magnetization vectors with temporal evolution controlled by MR physics. Such an approach ensures flexibility as the designed simulator is able to reconstruct flow profiles of any type. The proposed model is validated in a series of experiments with physical and digital flow phantoms. The synthesized 3D images contain various features (including artifacts) characteristic for the time-of-flight protocol and exhibit remarkable correlation with the data acquired in a real MR scanner. The obtained results support the primary goal of the conducted research, i.e. establishing a reference technique for a quantified validation of MR angiography image processing algorithms. [ABSTRACT FROM AUTHOR]

With great potential for assisting radiological image interpretation and decision making, content-based image retrieval in the medical domain has become a hot topic in recent years. Many methods to enhance the performance of content-based medical image retrieval have been proposed, among which the relevance feedback (RF) scheme is one of the most promising. Given user feedback information, RF algorithms interactively learn a user’s preferences to bridge the “semantic gap” between low-level computerized visual features and high-level human semantic perception and thus improve retrieval performance. However, most existing RF algorithms perform in the original high-dimensional feature space and ignore the manifold structure of the low-level visual features of images. In this paper, we propose a new method, termed dual-force ISOMAP (DFISOMAP), for content-based medical image retrieval. Under the assumption that medical images lie on a low-dimensional manifold embedded in a high-dimensional ambient space, DFISOMAP operates in the following three stages. First, the geometric structure of positive examples in the learned low-dimensional embedding is preserved according to the isometric feature mapping (ISOMAP) criterion. To precisely model the geometric structure, a reconstruction error constraint is also added. Second, the average distance between positive and negative examples is maximized to separate them; this margin maximization acts as a force that pushes negative examples far away from positive examples. Finally, the similarity propagation technique is utilized to provide negative examples with another force that will pull them back into the negative sample set. We evaluate the proposed method on a subset of the IRMA medical image dataset with a RF-based medical image retrieval framework. Experimental results show that DFISOMAP outperforms popular approaches for content-based medical image retrieval in terms of accuracy and stability. [ABSTRACT FROM AUTHOR]

In recent years, active microwave breast imaging is increasingly being viewed as a promising complementary imaging modality for cancer detection. In this paper, we present a novel deformable reflector microwave tomography technique for noninvasive characterization of the breast tissue. In contrast to conventional multitransceiver designs, the proposed technique utilizes a continuously deformable reflector with metallic coating to acquire field measurements for imaging. Computational feasibility of the proposed technique to image heterogeneous dielectric tissue property is evaluated using simplified 2-D breast models. The robustness of the deformable reflector-based tomography technique in imaging the spatial distribution of the tissue dielectric property in the presence of measurement noise is investigated using first-order Tikhonov regularization. Preliminary results obtained for the 2-D breast models appear promising and indicate further investigation of the new microwave tomography technique for breast imaging. [ABSTRACT FROM AUTHOR]

This paper describes a 3D reconstruction methodology used for anatomical structures conformed by soft and hard tissues. This technique uses biomedical images as input in applications where a further Finite Element Method (FEM) bioengineering modeling is required. A biomedical image processing software in DICOM (Digital Imaging Standard for Medical Images) was developed using C language. This software provides the cloud of points of the anatomic structure in order to reconstruct and optimize the surfaces which finally form a solid which can be exported to the software ANSYS 10.0®. Geometric modeling software as ProENGINEER WILDFIRE 3.0® and GID 8.0® were also used in the modeling process. Anatomical structures like jaw, temporal bone and some dental pieces were successfully reconstructed maintaining their anatomical characteristics and obtaining geometric models that allowed biomechanical simulations by FEM. The method proposed improved the ability to geometrically model in an accurate way the structures studied. Furthermore, this application enabled to perform a biomedical application without simplifications as ambition of cancellous bone and inadequate allocation of mandibular properties which could affect the final results of the FEM predictions. Although the validation of the results was conducted on orthodontic device, the developed methodology could be applied to the evaluation of other problems involving different anatomical structures. [ABSTRACT FROM AUTHOR]

In this paper, the current published knowledge about smart and adaptive engineering systems in medicine is reviewed. The achievements of frontier research in this particular field within medical engineering are described. A multi-disciplinary approach to the applications of adaptive systems is observed from the literature surveyed. The three modalities of diagnosis, imaging and therapy are considered to be an appropriate classification method for the analysis of smart systems being applied to specified medical sub-disciplines. It is expected that future research in biomedicine should identify subject areas where more advanced intelligent systems could be applied than is currently evident. The literature provides evidence of hybridisation of different types of adaptive and smart systems with applications in different areas of medical specifications. [Copyright &y& Elsevier]

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

Purpose : To enable high spatial and temporal breast imaging resolution via combined use of high field MRI, array coils, and forced current excitation (FCE) multi channel transmit. Materials and Methods : A unilateral 16-channel receive array insert was designed for use in a transmit volume coil optimized for quadrature operation with dual-transmit RF shimming at 7T. Signal-to-noise ratio (SNR) maps, g-factor maps, and high spatial and temporal resolution in vivo images were acquired to demonstrate the utility of the coil architecture. Results : The dual-transmit FCE coil provided homogeneous excitation and the array provided an increase in average SNR of 3.3 times (max 10.8, min 1.5) compared to the volume coil in transmit/receive mode. High resolution accelerated in vivo breast imaging demonstrated the ability to achieve isotropic spatial resolution of 0.5 mm within clinically relevant 90 s scan times, as well as the ability to perform 1.0 mm isotropic resolution imaging, 7 s per dynamics, with the use of bidirectional SENSE acceleration of up to R = 9. Conclusion : The FCE design of the transmit coil easily accommodates the addition of a sixteen channel array coil. The improved spatial and temporal resolution provided by the high-field array coil with FCE dual-channel transmit will ultimately be beneficial in lesion detection and characterization. [ABSTRACT FROM AUTHOR]

Purpose: To suppress the noise, by sacrificing some of the signal homogeneity for numerical stability, in uniform T1 weighted (T1w) images obtained with the magnetization prepared 2 rapid gradient echoes sequence (MP2RAGE) and to compare the clinical utility of these robust T1w images against the uniform T1w images. Materials and Methods: 8 healthy subjects (29.0±4.1 years; 6 Male), who provided written consent, underwent two scan sessions within a 24 hour period on a 7T head-only scanner. The uniform and robust T1w image volumes were calculated inline on the scanner. Two experienced radiologists qualitatively rated the images for: general image quality; 7T specific artefacts; and, local structure definition. Voxel-based and volume-based morphometry packages were used to compare the segmentation quality between the uniform and robust images. Statistical differences were evaluated by using a positive sided Wilcoxon rank test. Results: The robust image suppresses background noise inside and outside the skull. The inhomogeneity introduced was ranked as mild. The robust image was significantly ranked higher than the uniform image for both observers (observer 1/2, p-value = 0.0006/0.0004). In particular, an improved delineation of the pituitary gland, cerebellar lobes was observed in the robust versus uniform T1w image. The reproducibility of the segmentation results between repeat scans improved (p-value = 0.0004) from an average volumetric difference across structures of ≈6.6% to ≈2.4% for the uniform image and robust T1w image respectively. Conclusions: The robust T1w image enables MP2RAGE to produce, clinically familiar T1w images, in addition to T1 maps, which can be readily used in uniform morphometry packages. [ABSTRACT FROM AUTHOR]

Glandular epithelial cells differentiate into complex multicellular or acinar structures, when embedded in three-dimensional (3D) extracellular matrix. The spectrum of different multicellular morphologies formed in 3D is a sensitive indicator for the differentiation potential of normal, non-transformed cells compared to different stages of malignant progression. In addition, single cells or cell aggregates may actively invade the matrix, utilizing epithelial, mesenchymal or mixed modes of motility. Dynamic phenotypic changes involved in 3D tumor cell invasion are sensitive to specific small-molecule inhibitors that target the actin cytoskeleton. We have used a panel of inhibitors to demonstrate the power of automated image analysis as a phenotypic or morphometric readout in cell-based assays. We introduce a streamlined stand-alone software solution that supports large-scale high-content screens, based on complex and organotypic cultures. AMIDA (Automated Morphometric Image Data Analysis) allows quantitative measurements of large numbers of images and structures, with a multitude of different spheroid shapes, sizes, and textures. AMIDA supports an automated workflow, and can be combined with quality control and statistical tools for data interpretation and visualization. We have used a representative panel of 12 prostate and breast cancer lines that display a broad spectrum of different spheroid morphologies and modes of invasion, challenged by a library of 19 direct or indirect modulators of the actin cytoskeleton which induce systematic changes in spheroid morphology and differentiation versus invasion. These results were independently validated by 2D proliferation, apoptosis and cell motility assays. We identified three drugs that primarily attenuated the invasion and formation of invasive processes in 3D, without affecting proliferation or apoptosis. Two of these compounds block Rac signalling, one affects cellular cAMP/cGMP accumulation. Our approach supports the growing needs for user-friendly, straightforward solutions that facilitate large-scale, cell-based 3D assays in basic research, drug discovery, and target validation. [ABSTRACT FROM AUTHOR]

Diffuse multi-spectral imaging has been evaluated as a potential non-invasive marker of tumor response. Multi-spectral images of Kaposi sarcoma skin lesions were taken over the course of treatment, and blood volume and oxygenation concentration maps were obtained through principal component analysis (PCA) of the data. These images were compared with clinical and pathological responses determined by conventional means. We demonstrate that cutaneous lesions have increased blood volume concentration and that changes in this parameter are a reliable indicator of treatment efficacy, differentiating responders and non-responders. Blood volume decreased by at least 20% in all lesions that responded by clinical criteria and increased in the two lesions that did not respond clinically. Responses as assessed by multi-spectral imaging also generally correlated with overall patient clinical response assessment, were often detectable earlier in the course of therapy, and are less subject to observer variability than conventional clinical assessment. Tissue oxygenation was more variable, with lesions often showing decreased oxygenation in the center surrounded by a zone of increased oxygenation. This technique could potentially be a clinically useful supplement to existing response assessment in KS, providing an early, quantitative, and non-invasive marker of treatment effect. [ABSTRACT FROM AUTHOR]

Medical imaging plays an important role in patients' care and is continuously being used in managing health and disease. To obtain the maximum benefit from this rapidly developing technology, further research is needed. Ideally, this research should be done in a patient-safe and environment-friendly manner; for example, on phantoms. The goal of this work was to develop a protocol and manufacture a multimodal liver phantom that is suitable for ultrasound, computed tomography, and magnetic resonance imaging modalities. The proposed phantom consists of three types of mimicked soft tissues: liver parenchyma, tumors, and portal veins, that are made of six ingredients: candle gel, sephadex®, agarose, glycerol, distilled water, and silicone string. The entire procedure is advantageous, since preparation of the phantom is simple, rather cost-effective, and reasonably quick – it takes around 2 days. Besides, most of the phantom's parts can be reused to manufacture a new phantom. Comparison of ultrasound images of real patient's liver and the developed phantom shows that the phantom's liver tissue and its structures are well simulated. [ABSTRACT FROM AUTHOR]

Background: Non-invasive imaging biomarkers of cellular proliferation hold great promise for quantifying response to personalized medicine in oncology. An emerging approach to assess tumor proliferation utilizes the positron emission tomography (PET) tracer 3’-deoxy-3’[18F]-fluorothymidine, [18F]-FLT. Though several studies have associated serial changes in [18F]-FLT-PET with elements of therapeutic response, the degree to which [18F]-FLT-PET quantitatively reflects proliferative index has been continuously debated for more that a decade. The goal of this study was to elucidate quantitative relationships between [18F]-FLT-PET and cellular metrics of proliferation in treatment naïve human cell line xenografts commonly employed in cancer research. Methods and Findings: [18F]-FLT-PET was conducted in human cancer xenograft-bearing mice. Quantitative relationships between PET, thymidine kinase 1 (TK1) protein levels and immunostaining for proliferation markers (Ki67, TK1, PCNA) were evaluated using imaging-matched tumor specimens. Overall, we determined that [18F]-FLT-PET reflects TK1 protein levels, yet the cell cycle specificity of TK1 expression and the extent to which tumors utilize thymidine salvage for DNA synthesis decouple [18F]-FLT-PET data from standard estimates of proliferative index. Conclusions: Our findings illustrate that [18F]-FLT-PET reflects tumor proliferation as a function of thymidine salvage pathway utilization. Unlike more general proliferation markers, such as Ki67, [18F]-FLT PET reflects proliferative indices to variable and potentially unreliable extents. [18F]-FLT-PET cannot discriminate moderately proliferative, thymidine salvage-driven tumors from those of high proliferative index that rely primarily upon de novo thymidine synthesis. Accordingly, the magnitude of [18F]-FLT uptake should not be considered a surrogate of proliferative index. These data rationalize the diversity of [18F]-FLT-PET correlative results previously reported and suggest future best-practices when [18F]-FLT-PET is employed in oncology. [ABSTRACT FROM AUTHOR]