Les nouvelles gamma caméras en cardiologie nucléaire : D-Spect

Over the past few years, advances in nuclear medicine aimed at decreasing both the duration and dosimetry of exams, without decreasing image quality. In this setting, Spectrum Dynamics (D-Spect) is a new generation gamma camera dedicated to cardiac scintigraphy. Its technology includes solid-state detectors based on pixelated semiconductors, region-centric (cardiac area) scanning, high-sensitivity collimators and resolution recovery. An additional particularity is the patient position during scanning. Phantom studies showed an improvement of sensitivity compared to conventional cameras, at the price of a loss in geometric resolution, which is compensated by resolution recovery. Semiconductors detectors provide a better energy resolution than conventional detectors suited to double isotope acquisitions, and a high count rate allowing dynamic acquisitions. Only few clinical studies are available so far, they suggest performances similar to that of conventional cameras obtained with acquisitions duration reduced to few minutes. The next step is to establish a trade-off between acquisition duration and dosimetry reduction.     

Nouvelles caméras cardiaques à semi-conducteur cadmium–zinc–telluride (CZT) et scintigraphies myocardiques au thallium 201

Myocardial perfusion imaging is widely used for management of coronary artery disease. However, it suffers from technical limitations. New cardiac cameras using CZT detectors are now available and increase spatial (×2) and energy (×2) resolutions and photons sensitivity (×5). We describe here the General Electric Discovery NM 530c new camera and summarize the validation studies with technetium agents and with thallium 201, protocols to reduce doses, ultrafast protocols and perspectives offered with this new technology.     

Test Samples for Optimizing STORM Super-Resolution Microscopy

STORM is a recently developed super-resolution microscopy technique with up to 10 times better resolution than standard fluorescence microscopy techniques. However, as the image is acquired in a very different way than normal, by building up an image molecule-by-molecule, there are some significant challenges for users in trying to optimize their image acquisition. In order to aid this process and gain more insight into how STORM works we present the preparation of 3 test samples and the methodology of acquiring and processing STORM super-resolution images with typical resolutions of between 30-50 nm. By combining the test samples with the use of the freely available rainSTORM processing software it is possible to obtain a great deal of information about image quality and resolution. Using these metrics it is then possible to optimize the imaging procedure from the optics, to sample preparation, dye choice, buffer conditions, and image acquisition settings. We also show examples of some common problems that result in poor image quality, such as lateral drift, where the sample moves during image acquisition and density related problems resulting in the ''mislocalization'' phenomenon.     

Les examens cardiaques en tomographie par émission de positons

Cardiac positron emission tomography (PET) is yet considered as a reference imaging technique but remains poorly used in clinical practice. At the present time, the advantages of cardiac PET investigations are far to be evident, when compared with conventional tomoscintigraphy (SPECT), except for perfusion imaging in the obese and for viability assessment in case of very severe cardiac dysfunction. However, this situation might quickly move because of an enhanced availability of PET imaging, dramatic technical progresses and promising new tracers. In particular, the last-generation PET-cameras allow reaching spatial resolutions and detection sensitivities, which are now spectacularly higher than those from conventional SPECT imaging. In addition, the list mode recording allows the subsequent images reconstruction to be synchronized to cardiac cycle but also to respiratory cycle; and the quantifications of myocardial perfusion flow and of coronary flow reserve are now available in clinical routine. Furthermore, new tracers labelled with fluorine-18 are under development, especially for perfusion investigations, and kinetics properties of these new tracers are dramatically enhanced when compared with current perfusion SPECT tracers.     

Introduction to rodent cardiac imaging

Imaging is a noninvasive complement to traditional methods (such as histology) in rodent cardiac studies. Assessments of structure and function are possible with ultrasound, microcomputed tomography (microCT), and magnetic resonance (MR) imaging. Cardiac imaging in the rodent poses a challenge because of the size of the animal and its rapid heart rate. Each aspect in the process of rodent cardiac imaging-animal preparation, choice of anesthetic, selection of gating method, image acquisition, and image interpretation and measurement-requires careful consideration to optimize image quality and to ensure accurate and reproducible data collection. Factors in animal preparation that can affect cardiac imaging are the choice of anesthesia regime (injected or inhaled), intubated or free-breathing animals, physiological monitoring (ECG, respiration, and temperature), and animal restraint. Each will vary depending on the method of imaging and the length of the study. Gating strategies, prospective or retrospective, reduce physiological motion artifacts and isolate specific time points in the cardiac cycle (i.e., end-diastole and end-systole) where measurements are taken. This article includes a simple explanation of the physics of ultrasound, microCT, and MR to describe how images are generated. Subsequent sections provide reviews of animal preparation, image acquisition, and measurement techniques in each modality specific to assessing cardiac functions such as ejection fraction, fractional shortening, stroke volume, cardiac output, and left ventricular mass. The discussion also includes the advantages and disadvantages of the different imaging modalities. With the use of ultrasound, microCT, and MR, it is possible to create 2-, 3-, and 4-dimensional views to characterize the structure and function of the rodent heart.     

MITICS (MALDI Imaging Team Imaging Computing System): a new open source mass spectrometry imaging software

MITICS is a new software developed for MALDI imaging. We tried to render this software compatible with all types of instruments. MITICS is divided in two parts: MITICS control for data acquisition and MITICS Image for data processing and images reconstruction. MITICS control is available for Applied BioSystems MALDI-TOF instruments and MITICS Image for both Applied BioSystems and Bruker Daltonics ones. MITICS Control provides an interface to the user for setting the acquisition parameters for the imaging sequence, namely set instruments acquisition parameters, create the raster of acquisition and control post-acquisition data processing, and provide this settings to the automatic acquisition software of the MALDI instrument. MITICS Image ensures image reconstruction, files are first converted to XML files before being loaded in a database. In MITICS image we have chosen to implement different data representations and calculations for image reconstruction. MITICS Image uses three different representations that have shown to ease extraction of information from the whole data set. It also offers image reconstruction base either on the maximum peak intensity or the peak area. Image reconstruction is possible for single ions but also by summing signals of different ions. MITICS was validated on biological cases.     

Ultrasound-driven cardiac MRI

PurposeOne of the challenges of cardiac MR imaging is the compensation of respiratory motion, which causes the heart and the surrounding tissues to move. Commonly-used methods to overcome this effect, breath-holding and MR navigation, present shortcomings in terms of available acquisition time or need to periodically interrupt the acquisition, respectively. In this work, an implementation of respiratory motion compensation that obtains information from abdominal ultrasound and continuously adapts the imaged slice position in real time is presented.MethodsA custom workflow was developed, comprising an MR-compatible ultrasound acquisition system, a feature-motion-tracking system with polynomial predictive capability, and a custom MR sequence that continuously adapts the position of the acquired slice according to the tracked position. The system was evaluated on a moving phantom by comparing sharpness and image blurring between static and moving conditions, and in vivo by tracking the motion of the blood vessels of the liver to estimate the cardiac motion. Cine images of the heart were acquired during free breathing.ResultsIn vitro, the predictive motion correction yielded significantly better results than non-predictive or non-corrected acquisitions (p ≪ 0.01). In vivo, the predictive correction resulted in an image quality very similar to the breath-hold acquisition, whereas the uncorrected images show noticeable blurring artifacts.ConclusionIn this work, the possibility of using ultrasound navigation with tracking for the real-time adaptation of MR imaging slices was demonstrated. The implemented technique enabled efficient imaging of the heart with resolutions that would not be feasible in a single breath-hold.     

Nouveautés en cardiologie nucléaire : une gamma caméra à semi-conducteurs dédiée à l’imagerie cardiaque

During the last few years, cardiac imaging made important breakthroughs thanks to the development of various techniques allowing the risk stratification of patients with coronary artery disease. The well-established single photon emission computed tomography (SPECT) as a myocardial imaging technique made an important progress with the recent improvement of high-speed volumic acquisition, using dedicated semi-conductor gamma camera. These cameras bring significant improvement to the image quality and the image acquisition time, which is now seven times lower. New type of artefacts is expected because of the geometry of detection, thus studies are still needed to assess the exact performance of this revolutionary technology.     

Multispectral fluorescence and reflectance imaging at the leaf level and its possible applications

Images taken at different spectral bands are increasingly used for characterizing plants and their health status. In contrast to conventional point measurements, imaging detects the distribution and quantity of signals and thus improves the interpretation of fluorescence and reflectance signatures. In multispectral fluorescence and reflectance set-ups, images are separately acquired for the fluorescence in the blue, green, red, and far red, as well as for the reflectance in the green and in the near infrared regions. In addition, 'reference' colour images are taken with an RGB (red, green, blue) camera. Examples of imaging for the detection of photosynthetic activity, UV screening caused by UV-absorbing substances, fruit quality, leaf tissue structure, and disease symptoms are introduced. Subsequently, the different instrumentations used for multispectral fluorescence and reflectance imaging of leaves and fruits are discussed. Various types of irradiation and excitation light sources, detectors, and components for image acquisition and image processing are outlined. The acquired images (or image sequences) can be analysed either directly for each spectral range (wherein they were captured) or after calculating ratios of the different spectral bands. This analysis can be carried out for different regions of interest selected manually or (semi)-automatically. Fluorescence and reflectance imaging in different spectral bands represents a promising tool for non-destructive plant monitoring and a 'road' to a broad range of identification tasks.     

Pattern recognition software and techniques for biological image analysis

The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays.     

Artificial intelligence in image reconstruction: The change is here

Innovations in CT have been impressive among imaging and medical technologies in both the hardware and software domain. The range and speed of CT scanning improved from the introduction of multidetector-row CT scanners with wide-array detectors and faster gantry rotation speeds. To tackle concerns over rising radiation doses from its increasing use and to improve image quality, CT reconstruction techniques evolved from filtered back projection to commercial release of iterative reconstruction techniques, and recently, of deep learning (DL)-based image reconstruction. These newer reconstruction techniques enable improved or retained image quality versus filtered back projection at lower radiation doses. DL can aid in image reconstruction with training data without total reliance on the physical model of the imaging process, unique artifacts of PCD-CT due to charge sharing, K-escape, fluorescence x-ray emission, and pulse pileups can be handled in the data-driven fashion. With sufficiently reconstructed images, a well-designed network can be trained to upgrade image quality over a practical/clinical threshold or define new/killer applications. Besides, the much smaller detector pixel for PCD-CT can lead to huge computational costs with traditional model-based iterative reconstruction methods whereas deep networks can be much faster with training and validation. In this review, we present techniques, applications, uses, and limitations of deep learning-based image reconstruction methods in CT.     

梗阻性低位直肠癌保肛手术可行性探讨

目的：探讨梗阻性低位直肠癌保肛治疗（直肠癌前切除术（dixon手术））的可行性及术后肠瘘的防治。方法：回顾性分析我科2009年1月．2012年1月梗阻性低位直肠癌的保肛治疗（dixon）24例手术患者（梗阻性保肛组）临床资料及非梗阻性低位直肠癌保肛治疗（dixon）的24例患者（非梗阻性保肛组）临床资料,比较梗阻性与非梗阻性低位肠梗阻保肛治疗的临床疗效,分析梗阻性低位肠梗阻保肛治疗的可行性。结果：梗阻性保肛组住院天数：11．9天,非梗阻性肠梗阻保肛组8．7天P〈0．05;梗阻性保肛纽发生肠瘘：4例（16．7％）,非梗阻性肠梗阻保肛组发生肠瘘：1例（4.2％）P〈0．05,经充分引流后肠痿愈合,无1人死亡,两组术后至出院期间死亡人数：0例;梗阻性保肛组肠功能恢复（以排气排便为指标）：5．1天,非梗阻性保肛组肠功能恢复：3．8天,P〈0．05;术后6个月腹泻便秘患者两组相同为24人;术后6个月梗阻性保肛组肿瘤复发6人（25％）,非梗阻性保肛组肿瘤复发5人（20．8％）,P〉0．05。结论：梗阻性低位肠梗阻保肛治疗住院期疗效较非梗阻性保肛组差,中远期疗效无明显差异。梗阻性低位直肠癌可行保肛治疗。     

Biological imaging software tools

Few technologies are more widespread in modern biological laboratories than imaging. Recent advances in optical technologies and instrumentation are providing hitherto unimagined capabilities. Almost all these advances have required the development of software to enable the acquisition, management, analysis and visualization of the imaging data. We review each computational step that biologists encounter when dealing with digital images, the inherent challenges and the overall status of available software for bioimage informatics, focusing on open-source options.     

Workflow and metrics for image quality control in large-scale high-content screens

Automated microscopes have enabled the unprecedented collection of images at a rate that precludes visual inspection. Automated image analysis is required to identify interesting samples and extract quantitative information for high-content screening (HCS). However, researchers are impeded by the lack of metrics and software tools to identify image-based aberrations that pollute data, limiting experiment quality. The authors have developed and validated approaches to identify those image acquisition artifacts that prevent optimal extraction of knowledge from high-content microscopy experiments. They have implemented these as a versatile, open-source toolbox of algorithms and metrics readily usable by biologists to improve data quality in a wide variety of biological experiments.     

Low-light imaging technology in the life sciences

Photon imaging is an increasingly important technique for the measurement and analysis of chemiluminescence and bioluminescence. New high-performance low-light level imaging systems have recently become available for the life science. These systems use advances in camera design and digital image processing and are now being used for a wide range of luminescence applications. They offer good sensitivity for photon detection and large dynamic range, and are suitable for quantitative analysis. This is achieved using a range of software techniques including image arithmetic, histogramming or summing regions of interest, feature extraction and multiple image processing for kinetics or assay screening. Improvements in imageprocessing hardware and software have increased the usefulness of these systems in the biosciences. Low-light imaging is a rapid and non-invasive method for the sensitive detection and analysis of luminescent assays. As such it offers a powerful and sensitive tool for investigating processes, both at the cellular level (luc and lux reporter genes, intracellular signalling) and for measurement of macro samples (immunoassays, gels and blots, tissue sections).     

Interpolated Compressed Sensing for 2D Multiple Slice Fast MR Imaging

Sparse MRI has been introduced to reduce the acquisition time and raw data size by undersampling the k-space data. However, the image quality, particularly the contrast to noise ratio (CNR), decreases with the undersampling rate. In this work, we proposed an interpolated Compressed Sensing (iCS) method to further enhance the imaging speed or reduce data size without significant sacrifice of image quality and CNR for multi-slice two-dimensional sparse MR imaging in humans. This method utilizes the k-space data of the neighboring slice in the multi-slice acquisition. The missing k-space data of a highly undersampled slice are estimated by using the raw data of its neighboring slice multiplied by a weighting function generated from low resolution full k-space reference images. In-vivo MR imaging in human feet has been used to investigate the feasibility and the performance of the proposed iCS method. The results show that by using the proposed iCS reconstruction method, the average image error can be reduced and the average CNR can be improved, compared with the conventional sparse MRI reconstruction at the same undersampling rate.     

Prospective image planning in radiation therapy for optimization of image quality and reduction of patient dose

IntroductionCT simulation data in image-guided radiation therapy (IGRT) provides patient-specific subject contrast. This information can be exploited to establish, a priori, a suitable imaging goal and to select patient-specific imaging acquisition parameters that optimize the similarity between reference and daily set-up images and reduce imaging dose. This study aims to describe and clinically validate a computerized algorithm designed to provide such optimization.Material and methodsAn image planning system (IPS) was developed to assist in planar kV imaging technique selection for radiation therapy. The system's patient-specific image quality and dose reduction capabilities were validated herein. Anthropomorphic phantom and clinical data were acquired. Mutual information (MI) was used to compare simulated and measured images in both phantom and clinical tests. Variations in contrast resolution resulting from imaging panel underexposure, saturation and a contrast plateau were investigated. For evaluation of patient-specific imaging dose reduction, the IPS was used to modify acquisition settings for six patients.ResultsPhantom data confirmed the IPS's predictive capability regarding image contrast. Measured and simulated images showed similar progressions from under-exposure, image quality peak, and loss of contrast due to detector saturation. Clinical data demonstrated that contrast resolution and imaging dose could be prospectively improved without loss of image contrast. The algorithm reduced imaging dose by an average of 47%, and a maximum of 80%.ConclusionsLoss of image contrast resulting from under-exposure or over-exposure, as well as a contrast plateau can be predicted by use of a prospective image planning algorithm. Image acquisition parameters can be predicted that reduce patient dose without loss of useful contrast.     

Cloud-Enabled Microscopy and Droplet Microfluidic Platform for Specific Detection of Escherichia coli in Water

We report an all-in-one platform – ScanDrop – for the rapid and specific capture, detection, and identification of bacteria in drinking water. The ScanDrop platform integrates droplet microfluidics, a portable imaging system, and cloud-based control software and data storage. The cloud-based control software and data storage enables robotic image acquisition, remote image processing, and rapid data sharing. These features form a “cloud” network for water quality monitoring. We have demonstrated the capability of ScanDrop to perform water quality monitoring via the detection of an indicator coliform bacterium, Escherichia coli, in drinking water contaminated with feces. Magnetic beads conjugated with antibodies to E. coli antigen were used to selectively capture and isolate specific bacteria from water samples. The bead-captured bacteria were co-encapsulated in pico-liter droplets with fluorescently-labeled anti-E. coli antibodies, and imaged with an automated custom designed fluorescence microscope. The entire water quality diagnostic process required 8 hours from sample collection to online-accessible results compared with 2–4 days for other currently available standard detection methods.     

A GPU Simulation Tool for Training and Optimisation in 2D Digital X-Ray Imaging

Conventional radiology is performed by means of digital detectors, with various types of technology and different performance in terms of efficiency and image quality. Following the arrival of a new digital detector in a radiology department, all the staff involved should adapt the procedure parameters to the properties of the detector, in order to achieve an optimal result in terms of correct diagnostic information and minimum radiation risks for the patient. The aim of this study was to develop and validate a software capable of simulating a digital X-ray imaging system, using graphics processing unit computing. All radiological image components were implemented in this application: an X-ray tube with primary beam, a virtual patient, noise, scatter radiation, a grid and a digital detector. Three different digital detectors (two digital radiography and a computed radiography systems) were implemented. In order to validate the software, we carried out a quantitative comparison of geometrical and anthropomorphic phantom simulated images with those acquired. In terms of average pixel values, the maximum differences were below 15%, while the noise values were in agreement with a maximum difference of 20%. The relative trends of contrast to noise ratio versus beam energy and intensity were well simulated. Total calculation times were below 3 seconds for clinical images with pixel size of actual dimensions less than 0.2 mm. The application proved to be efficient and realistic. Short calculation times and the accuracy of the results obtained make this software a useful tool for training operators and dose optimisation studies.