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* Context.--Pancreatic ductal adenocarcinoma has some of the worst prognostic outcomes among various cancer types. Detection of histologic patterns of pancreatic tumors is essential to predict prognosis and decide the treatment for patients. This histologic classification can have a large degree of variability even among expert pathologists. Objective.--To detect aggressive adenocarcinoma and less aggressive pancreatic tumors from nonneoplasm cases using a graph convolutional network-based deep learning model. Design.--Our model uses a convolutional neural network to extract detailed information from every small region in a whole slide image. Then, we use a graph architecture to aggregate the extracted features from these regions and their positional information to capture the whole slide-level structure and make the final prediction. Results.--We evaluated our model on an independent test set and achieved an F1 score of 0.85 for detecting neoplastic cells and ductal adenocarcinoma, significantly outperforming other baseline methods. Conclusions.--If validated in prospective studies, this approach has a great potential to assist pathologists in identifying adenocarcinoma and other types of pancreatic tumors in clinical settings. doi: 10.5858/arpa.2022-0035-OA, Pancreatic ductal adenocarcinoma (PDAC) is an aggressive type of cancer derived from the epithelial cells that make up the ducts of the pancreas. PDAC ranks firmly first among all cancer [...]

The goal of this study was to evaluate the magnitude and origin of scattered radiation in a small-animal PET scanner and to assess the impact of these findings on noise equivalent count rate (NECR) measurements, a metric often used to optimize scanner acquisition parameters and to compare one scanner with another. The scatter fraction (SF) was measured for line sources in air and line sources placed within a mouse-sized phantom (25 mm [phi] x 70 mm) and a rat-sized phantom (60 mm [phi] x 150 mm) on the microPET II small-animal PET scanner. Measurements were performed for lower energy thresholds ranging from 150-450 keV and a fixed upper energy threshold of 750 keV. Four different methods were compared for estimating the SF. Significant scatter fractions were measured with just the line source in the field of view, with the spatial distribution of these events consistent with scatter from the gantry and room environment. For mouse imaging, this component dominates over object scatter, and the measured SF is strongly method dependent. The environmental SF rapidly increases as the lower energy threshold decreases and can be more than 30% for an open energy window of 150-750 keV. The object SF originating from the mouse phantom is about 3-4 % and does not change significantly as the lower energy threshold increases. The object SF for the rat phantom ranges from 10 to 35% for different energy windows and increases as the lower energy threshold decreases. Because the measured SF is highly dependent on the method, and there is as yet no agreed upon standard for animal PET, care must be exercised when comparing NECR for small objects between different scanners. Differences may be methodological rather than reflecting any relevant difference in the performance of the scanner. Furthermore, these results have implications for scatter correction methods when the majority of the detected scatter does not arise from the object itself. Index Terms--MicroPET, positron emission tomography (PET), scatter fraction, small-animal imaging.

Digital image processing is now commonplace in radiology, nuclear medicine and sonography. This article outlines underlying principles and concepts of digital image processing. After completing this article, readers should be able to: * List the limitations of film-based imaging. * Identify major components of a digital imaging system. * Describe the history and application areas of digital image processing. * Discuss image representation and the fundamentals of digital image processing. * Outline digital image processing techniques and processing operations used in selected imaging modalities. * Explain the basic concepts and visualization tools used in 3-D and virtual reality imaging. * Recognize medical imaging informatics as a new area of specialization for radiologic technologists. This article is a Directed Reading. See the quiz at conclusion., Digital image processing is formally defined as 'subjecting numerical representations of objects to a series of operations in order to obtain a desired result.' (1) More simply put, digital image [...]

Patients with myocardial infarction caused by atherosclerosis are increasing and it is imperative to diagnose this in the early stage using Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). These techniques provide information on the shape of the artery and the diameter of the lumen and in early stage atherosclerosis this is of little use and to detect this automated method

A new system is proposed for tracking sensitive areas in the retina for computer-assisted laser treatment of choroidal neovascularization (CNV). The system consists of a fundus camera using red-free illumination mode interfaced to a computer that allows real-time capturing of video input. The first image acquired is used as the reference image and utilized by the treatment physician for treatment planning. A grid of seed contours over the whole image is initiated and allowed to deform by splitting and/or merging according to preset criteria until the whole vessel tree is demarcated. Then, the image is filtered using a one-dimensional Gaussian filter in two perpendicular directions to extract the core areas of such vessels. Faster segmentation can be obtained for subsequent images by automatic registration to compensate for eye movement and saccades. An efficient registration technique is developed whereby some landmarks are detected in the reference frame then tracked in the subsequent frames. Using the relation between these two sets of corresponding points, an optimal transformation can be obtained. The implementation details of proposed strategy are presented and the obtained results indicate that it is suitable for real-time location determination and tracking of treatment positions. Index Terms--Contour detection, feature extraction, image registration, retinal tracking.

A prototype monopole-transceiver microwave imaging system has been implemented, and initial single and multitarget imaging experiments involving biologically relevant property distributions have been conducted to evaluate its performance relative to a previously developed waveguide system. A new, simplified, but more effective calibration procedure has also been devised and tested. Results show that the calibration procedure leads to improvements which are independent of the type of radiator used. Specifically, data-model match is found to increase by 0.4 dB in magnitude and 4 [degrees] in phase for the monopoles and by 0.6 dB in magnitude and 7[degrees] in phase for the waveguides (on average) on a per measurement basis when the new calibration procedure is employed. Enhancements are also found in the reconstructed images obtained with the monopole system relative to waveguides. Improvements are observed in: 1) the recovered object shape: 2) the uniformity of the background; 3) edge detection; and 4) target property value recovery. Analyses of reconstructed images also suggest that there is a systematic decrease of approximately 10% in the reconstruction errors for the monopole system over its waveguide counterpart in single-target experiments and as much as a 20% decrease in multitarget cases. Results indicate that these enhancements stem from a better data-model match for the monopoles relative to waveguides which is consistent across the type of calibration procedure used. Comparisons of computations and measurements show an average improvement in data-model match of approximately 0.25 dB in magnitude and near 7[degrees] in phase in favor of the monopoles in this regard. Beyond this apparent imaging performance enhancement, the monopole system offers economy-of-space and low construction-cost considerations along with computational advantages (as described herein) which make it a compelling choice as a radiator/receiver element around which to construct a clinically viable near-field microwave imaging system.

Positron emission tomography (PET) with the glucose analog [18F] fluorodeoxyglucose is proving to be useful in cancer diagnosis and treatment. However, as in all nuclear medicine imaging technologies, lesion detection with PET is often hindered by limited spatial resolution and low signal-to-noise ratios. Under such conditions, conventional diagnosis by visual inspection usually becomes difficult and potentially inaccurate. In this paper, we propose use of computer-aided lesion detection methods for PET imaging by applying a maximum likelihood ratio test and a composite hypothesis test, assuming that the mean positron emission rate is deterministic or random, respectively. In our approach, different statistical models characterizing the mean positron emission rate, the raw sinogram data and the filtered backprojection (FBP) reconstructed image are used to derive the test criteria. Three methods to estimate the unknown parameters of the test functions from observations are presented. The performance of one of the proposed methods is evaluated and compared with both simulated and experimental phantom data. In the preliminary trials, the methods detect correctly (with a high probability > 0.9) lesions of diameter [greater than or equal to] 15mm with lesion-to-background contrast 1.1:1. Under the same conditions, the test lesion could not be detected by visual inspection alone in the images reconstructed by either the FBP or the maximum likelihood iterative algorithms. The methods may also be used for the objective assessment of the quality of images reconstructed from different algorithms.

A technique has been devised for independently determining the energy and spatial resolution components of the point-spread functions of electronically collimated (Compton scatter) imaging devices using a Monte Carlo method. Monte Carlo runs are performed for the device being examined, and detailed records of exact energy loss and spatial coordinates of each interaction for each particle in the simulation are made. Taking resolution parameters from the known performance of the detectors, measured data is simulated by sampling from Gaussian distributions (for both energy and position) about the exact interaction energy and position in both detectors, for each Monte Carlo history. By back-projecting cones on an event-by-event basis and calculating the closest approach of the cone to the known source point using the simulated measurement data for one of the energy and position variables and the exact interaction data for the rest of the variables, the effect of the variable in question on the point spread can be isolated. In this paper we present the calculations of the contribution to the point-spread function of the energy and spatial resolution in each detector for various source positions for a representative Compton camera configuration. Index Terms - Compton scatter camera, Monte Carlo, resolution.

Digital x-ray imaging detectors designed for soft x-rays (1 to 50 keV) are significant for medical mammography, dental radiography, microradiography, and microtomography. Detector designs involve either direct absorption of x-rays in solid state devices or thin scintillator screens optically coupled to solid state sensors. Well designed scintillator systems produce 10 or more electrons per detected x-ray and, used with charge coupled devices (CCD), detect 100,000 x-rays per pixel before saturation. However, if the scintillator is directly coupled to the detector, radiation can penetrate to the semiconductor detector with a small number of events producing large charge and noise. We have investigated the degradation of image noise by these direct absorption events using numerical models for a laboratory detector system consisting of a 60 [[micro]meter] CsI scintillator optically coupled to a scientific CCD. Monte Carlo methods were used to estimate the charge deposition signal and noise for both the CsI and the semiconductor. Without a fiber optic coupler, direct absorptions dominate the signal and increase the signal variance by a factor of about 30 at energies above 10 keV. With a 3 mm fiber optic coupler, no significant degradation is observed for input energies below 45 keV.

Using Monte Carlo simulation, we investigate algorithms to identify and correct for detector Compton scatter in hypothetical PET modules with 3x3x30 mm BGO crystals coupled to individual photosensors. Rather than assume a particular design, we study three classes of detectors: (1) with energy resolution limited by counting statistics, (2) with energy resolution limited by electronic noise, and (3) with depth of interaction (DOI) measurement capability. For the first two classes, selecting the channel with the highest signal as the crystal of interaction yields a 22-25% misidentification fraction (MIF) for all reasonable noise fwhm to signal (N/S) ratios (i.e. < 0.5 at 511 keV). Algorithms that attempt to correctly position events that undergo forward Compton scatter using only energy information can reduce the MIF to 12%, and can be easily realized with counting statistics limited detectors but can only be achieved with very low noise values for noise limited detectors. When using position of interaction to identify forward scatter, a MIF of 12% can be obtained if the detector has good energy and position resolution.

Performance measurements of the General Electric ADVANCE Positron Emission Tomograph operating with the septa retracted (3D mode) were made. All reconstructions were performed with the GE ADVANCE 3D package. Performance tests were carried out with: the NEMA phantoms; a 3D Hoffman phantom; a Data Spectrum torso phantom with lung and cardiac inserts; and the 'Utah' 3D evaluation phantom. Data collected included: transaxial and axial resolution, uniformity, recovery coefficients, count rate performance, dead time accuracy, and effect of scatter correction.