Decrease In Image Quality Research Articles

Virtual camera-based analysis of photosensor characterization methods

Digital cameras are widely used in artificial intelligent systems: machine vision, pattern recognition, automatic defect detection, etc. The quality of these systems is defined in significant degree by the registered images signal-to-noise ratio. Digital camera noise, conditions of shooting, low-light illumination decrease image quality. But information about camera noise allows to significantly improve it. However, noise characteristics are often absent in the instructions even for scientific digital cameras. There are various methods of photosensor noise measurement. They have different accuracy, speed of implementation and processing time. Therefore, the choice of the optimal method for measuring noise is of great interest. The paper presents the virtual camera-based analysis of methods of photosensor characterization. This technique determines the maximum and possible accuracy of the methods. Three methods of photosensor noise characterization are considered: the EMVA (European machine vision association) standard 1288, automatic segmentation of a non-uniform target (ASNT), and automatic segmentation of a striped target (ASST). The method's accuracy and processing time were estimated.

Evaluation of Eye Lens Dose Reduction Technics in Head CT

The purpose of this study is to find the best protocol to reduce the X-ray dose to the eye lens during head diagnostic computed tomography (CT) without decreasing image quality in the organs of interest according to the type of scanner. The lens of the eye is one of radiosensitive tissues in the body. Radiation induced cataract has been demonstrated among staff involved in interventional procedures using X-rays. This study compares the absorbed dose and image quality of several dose reduction technics to the eye lens during head CT exam namely bismuth shielding, organ-based dose modulation, tube current modulation, tube voltage modulation and the combination of a number of these techniques. Compared to the reference scan (Fixed tube current without bismuth shielding), the dose to the eye lens was reduced by 29.91% with bismuth shield, 14.55% with tube current modulation, 37.76% with tube current modulation and bismuth shield. The combination of organ-based dose modulation with tube voltage modulation reduced the dose by 44.93% that of tube current modulation with tube voltage modulation reduced by 19.03% and that of tube current modulation with tube voltage modulation and shield by 46.73%.
 The combination of organ-based dose with tube voltage modulation provided superior image quality than that of tube current modulation with tube voltage modulation and shield while similarly reducing dose to the eye lens.

Deep learning for automated left ventricular outflow tract diameter measurements in 2D echocardiography

Abstract Background Left ventricular outflow tract diameter (LVOTd) is routinely measured to calculate stroke volume and estimate aortic valve area by the continuity equation. Despite LVOTd being regularly measured clinically, significant inter- and intraobserver variability is evident. This variability is highly impactful on both aortic stenosis evaluation and cardiac output calculation due to the squaring of the LVOT radius. Purpose We aimed to investigate if LVOTd measurements from clinical echocardiographic examinations could be used in a deep learning (DL) model to automatically perform LVOTd measurements with equivalent accuracy and improved consistency compared to current practice. Methods Data was collected from clinical echocardiographic examinations performed on 656 consecutive patients admitted to the cardiac catheterization laboratory at a university hospital in January – December 2018. Parasternal views with cardiologist annotated LVOTd coordinates were assessed for 1314 echocardiographic still images. The quality of the still image and annotated LVOT ground truth were individually graded as high, medium and low by experienced cardiologists to establish a rigorous training basis. Spatial geometry data was preserved for each still image in order to distinguish between different degrees of image zoom. Data was randomly split into training, validation and testing sets (68%, 17%, 15%). A fully convolutional network based on the Resnet50 architecture was used with a custom loss function with heatmap regression. Image augmentations were added to extend the dataset. Results When including echocardiographic images of any quality (n=1314) in the model training and inference, the median absolute difference between cardiologist LVOTd and DL LVOTd was 0.97 mm (95% Confidence interval (CI) 0.79–1.14). Using only high and medium quality still images and ground truth (n=869) in the training and inference, median absolute difference decreased to 0.81 mm (95% CI 0.60–0.96). Adding image augmentations to this dataset further improved the model, resulting in a median LVOTd absolute difference of 0.66 mm (95% CI 0.51–0.78). The LVOTd error in inference increased with decreasing image quality, as shown in Figure 1, with two predictions (0.9%) failing completely. Conclusion Deep learning models are capable of measuring LVOTd with comparable accuracy to cardiologists when trained on clinical data. Data quality affects both training and inference. Even with a slightly lower accuracy when used on lower quality echocardiographic images, DL-assisted LVOT measurement has a clear potential to increase repeatability and consistency of LVOTd measurements. Funding Acknowledgement Type of funding sources: Public Institution(s). Main funding source(s): Research Council of Norway (Norges forskningsråd) Figure 1

Simulating dose reduction for myocardial perfusion SPECT using a Poisson resampling method.

The purpose of this study was to determine the lowest Tl-201 dose that does not reduce the image quality of myocardial perfusion SPECT (MPS) by Poisson resampling simulation. One hundred and twelve consecutive MPS data from patients with suspected or known coronary artery disease were collected retrospectively. Stress and rest MPS data were resampled using the Poisson method with 33%, 50%, 67%, and 100% count settings. Two nuclear medicine physicians assessed the image quality of reconstructed data visually by giving grades from - 2 to + 2. The summed stress score (SSS), summed rest score (SRS), and summed difference score (SDS) were obtained on the workstation. Image quality grades and semi-quantitative scores were then compared among these resampled images. The proportions of "adequate" image quality were 0.48, 0.75, 0.92, and 0.96 for the groups of images with 33%, 50%, 67%, and 100% data, respectively. The quality of the resampled images was significantly degraded at 50% and 33% count settings, while the image quality was not different between 67 and 100% count settings. We also found that high body mass index further decreased image quality at 33% count setting. Among the semi-quantitative parameters, SSS and SRS showed a tendency to increase with a decline in count. Based on the simulation results, Tl-201 dose for MPS can be reduced to 74MBq without significant loss of image quality. However, the SSS and SRS can be changed significantly, and it needs to be further verified under the different conditions.

Inpainting-filtering for metal artifact reduction (IMIF-MAR) in computed tomography.

The reduction of metal artifacts remains a challenge in computed tomography because they decrease image quality, and consequently might affect the medical diagnosis. The objective of this study is to present a novel method to correct metal artifacts based solely on the CT-slices. The proposed method consists of four steps. First, metal implants in the original CT-slice are segmented using an entropy based method, producing a metal image. Second, a prior image is acquired using three transformations: Gaussian filter, Parisotto and Schoenlieb inpainting method with the Mumford-Shah image model and L0 Gradient Minimization method (L0GM). Next, based on the projections from the original CT-slice, prior image and metal image, the sinogram is corrected in the traces affected by metal in the process called normalization and denormalization. Finally, the reconstructed image is obtained by FBP and a Nonlocal Means (NLM) filtering. The efficacy of the algorithm is evaluated by comparing five image quality metrics of the images and by inspecting regions of interest (ROI). Phantom data as well as clinical datasets are included. The proposed method is compared with three established metal artifact reduction (MAR) methods. The results from a phantom and clinical dataset show the visible reduction of artifacts. The conclusion is that IMIF-MAR method can reduce streak metal artifacts effectively and avoid new artifacts around metal implants, while preserving the anatomical structures. Considering both clinical and phantom studies, the proposed MAR algorithm improves the quality of clinical images affected by metal artifacts, and could be integrated in clinical setting.

Influence of heart rate and coronary artery calcification on image quality and diagnostic performance of coronary CT angiography: comparison between 96-row detector dual source CT and 256-row multidetector CT.

CT-derived fractional flow reserve (FFRCT) and diagnostic accuracy rely on good image quality during coronary CT angiography (CCTA). To investigate whether heart rate (HR) and coronary artery calcium (CAC) score decrease image quality and diagnostic performance of two advanced CT scanners including 96-row detector dual source CT (DSCT) and 256-row multidetector CT (MDCT). First, 79 patients who underwent CCTA (42 with DSCT and 37 with MDCT) and invasive coronary angiography (ICA) are enrolled. Next, coronary segments with excellent image quality are evaluated and the percentage is calculated. Then, diagnostic accuracy in detecting significant diameter stenosis is presented with ICA as the reference standard. Compared with the DSCT, the percentage of coronary segments with excellent image quality is lower (P = 0.010) while diagnostic accuracy on per-segment level is improved (P = 0.037) using MDCT. CAC score≥400 is the only independent factor influencing the percentage of coronary segments with excellent image quality [odds ratio (OR): DSCT, 3.096 and MDCT, 1.982] and segmental diagnostic accuracy (OR: DSCT, 2.630 and MDCT, 2.336) for both scanners. HR≥70 bpm (OR: 5.506) is the independent factor influencing the percentage of coronary segments with excellent image quality with MDCT. During CCTA, CAC score≥400 still decreases the proportion of coronary segments with excellent image quality and diagnostic accuracy with advanced CT scanners. HR≥70 bpm is another factor causing image quality decreasing with MDCT.

Image quality of bedside chest radiographs in intensive care beds with integrated detector tray: A phantom study

IntroductionVendors offer intensive care beds with integrated detector trays for bedside radiography, promoting better ergonomics and patient comfort. However, no documentation of the effects on diagnostic image quality has been located. This study examines measured and subjective image quality of supine bedside chest radiographs with and without use of such a detector tray. MethodsA contrast-detail phantom (CDRAD 2.0) was exposed using standard supine chest exposure parameters. Plexiglass plates of 16 and 21 cm were placed in front to simulate patient attenuation for standard and adipose patients. Exposures were repeated with the detector placed in tray and directly in bed. Images were analysed using dedicated software giving a figure-of-merit IQFinv. Results were compared using ANOVA. Then an anthropomorphic chest phantom (Lungman) was exposed using the same parameters, and the same placements of the detector. Exposures were done with and without extra conformal tissue to simulate varying patient sizes, and with and without added typical intensive care equipment. Images were analysed by two radiologists using a three-point scale, on five image quality criteria. Radiologist also stated whether the images were sufficient for diagnosis. Results were compared using Visual Grading Characteristics, using dedicated software, resulting in Areas Under the Curve (AUC-VGC) for each combination and criteria. Inter- and intra-rater reliability were assessed with kappa statistics. Composite Visual Grading Analysis (VGAS) scores were calculated for each image. Both IQFinv and were normalized and compared. ResultsFor all criteria both IQFinv and AUC-VGC was significantly better when exposing the detector directly in bed, than with the detector placed in the tray across all exposures. When stratified into thin and adipose patients, IQFinv decreased significantly for thin patients, while VGAS-scores did not. For adipose patients, both figures were significantly lower with the detector in the tray. ConclusionUse of detector tray for bedside chest imaging decreases image quality. Implications for practiceRadiographers should critically evaluate image quality and experimentally determine optimal exposure factors, when taking equipment with integrated trays into use.

Deep learning improves contrast in low-fluence photoacoustic imaging.

Low fluence illumination sources can facilitate clinical transition of photoacoustic imaging because they are rugged, portable, affordable, and safe. However, these sources also decrease image quality due to their low fluence. Here, we propose a denoising method using a multi-level wavelet-convolutional neural network to map low fluence illumination source images to its corresponding high fluence excitation map. Quantitative and qualitative results show a significant potential to remove the background noise and preserve the structures of target. Substantial improvements up to 2.20, 2.25, and 4.3-fold for PSNR, SSIM, and CNR metrics were observed, respectively. We also observed enhanced contrast (up to 1.76-fold) in an in vivo application using our proposed methods. We suggest that this tool can improve the value of such sources in photoacoustic imaging.

Controlling propagation of spatial coherence for enhanced imaging through scattering media

It is known that a spatially partially coherent light field produces better imaging contrast compared to a spatially coherent field and that the contrast increases as the spatial coherence length of the field becomes smaller. The transverse spatial coherence length of most spatially partially coherent fields increases upon propagation. As a result, the field produces progressively decreasing image quality at subsequent transverse planes. By controlling the propagation of spatial coherence, we demonstrate enhanced image quality at different transverse planes along the propagation direction through a scattering medium. Using a source with propagation-invariant spatial coherence function, we report experimental observations of imaging different transverse planes with equal contrast over a significant distance. Furthermore, we generate a spatially partially coherent source that can be tailored to have minimum-possible transverse coherence area at the plane of the object to be imaged, and using this source, we demonstrate imaging spatially separated transverse planes with maximum possible image contrast.

Production and clinical evaluation of breast lesion skin markers for automated three-dimensional ultrasonography of the breast: a pilot study

ObjectivesAutomated ultrasound of the breast has the advantage to have the whole breast scanned by technicians. Consequently, feedback to the radiologist about concurrent focal abnormalities (e.g., palpable lesions) is lost. To enable marking of patient- or physician-reported focal abnormalities, we aimed to develop skin markers that can be used without disturbing the interpretability of the image.MethodsDisk-shaped markers were casted out of silicone. In this IRB-approved prospective study, 16 patients were included with a mean age of 57 (39–85). In all patients, the same volume was imaged twice using an automated breast ultrasound system, once with and once without a marker in place. Nine radiologists from two medical centers filled scoring forms regarding image quality, image interpretation, and confidence in providing a diagnosis based on the images.ResultsMarker adhesion was sufficient for automated scanning. Observer scores showed a significant shift in scores from excellent to good regarding diagnostic yield/image quality (χ2, 15.99, p < 0.01), and image noise (χ2, 21.20, p < 0.01) due to marker presence. In 93% of cases, the median score of observers “agree” with the statement that marker-induced noise did not influence image interpretability. Marker presence did not interfere with confidence in diagnosis (χ2, 6.00, p = 0.20).ConclusionInexpensive, easy producible skin markers can be used for accurate lesion marking in automated ultrasound examinations of the breast while image interpretability is preserved. Any marker-induced noise and decreased image quality did not affect confidence in providing a diagnosis.Key Points• The use of a skin marker enables the reporting radiologist to identify a location which a patient is concerned about.• The developed skin marker can be used for accurate breast lesion marking in ultrasound examinations.

Scaled projected-directions methods with application to transmission tomography

Statistical image reconstruction in X-ray computed tomography yields large-scale regularized linear least-squares problems with nonnegativity bounds, where the memory footprint of the operator is a concern. Discretizing images in cylindrical coordinates results in significant memory savings, and allows parallel operator–vector products without on-the-fly computation of the operator, without necessarily decreasing image quality. However, it deteriorates the conditioning of the operator. We improve the Hessian conditioning by way of a block-circulant scaling operator and we propose a strategy to handle nondiagonal scaling in the context of projected-directions methods for bound-constrained problems. We describe our implementation of the scaling strategy using two algorithms: TRON, a trust-region method with exact second derivatives, and L-BFGS-B, a linesearch method with a limited-memory quasi-Newton Hessian approximation. We compare our approach with one where a change of variable is made in the problem. On two reconstruction problems, our approach converges faster than the change of variable approach, and achieves much tighter accuracy in terms of optimality residual than a first-order method.

Development of a zoomorphic test specimen for constancy testing on digital X-ray systems in veterinary radiology

BackgroundTechnical failures and incorrect usage of digital X-ray systems may lead to a decreasing image quality, artefacts and a higher dose exposure of staff and patients. Although there are no regulations regarding constancy testing in veterinary radiology all operators are required to avoid unnecessary exposure. The aim of this study was to develop a reasonably inexpensive zoomorphic 3D-printed test specimen for constancy testing that allows the detection of changing image quality by visual analysis.Primarily, a calibration curve of the attenuation factor of the 3D-printing material (ZP150) was determined. MATLAB converted every pixel value of a thorax X-ray image of a Beagle dog into an equivalent thickness of printing material. The thickness distribution was printed using a 3D-printer. This printed test specimen was additionally provided with five thin aluminium discs to simulate lung nodules.To evaluate the usability for constancy testing 12 X-ray images of the test specimen were made. Two images (reference and control) were taken with the minimum dose in order to obtain images suitable for diagnosis purposes. Eight images were taken with a dose differing 30–140% from the reference dose by varying current–time product (mAs) or tube voltage (kVp). Two images were taken with the same parameters as the reference image but edited with different image processing. Six veterinarians (general practitioners) evaluated ten chosen structures in the X-ray images in a Visual Grading Analysis and scored the image quality of these structures for every image in comparison to the reference image. A Visual Grading Analysis Score was calculated and statistically analysed.ResultsA higher current–time product led to a negligibly better evaluation of the X-ray image. The lower the current–time product the worse the X-ray images were scored. Likewise, both increasing and decreasing of the tube voltage led to lower scores.ConclusionsA zoomorphic test specimen can be used for constancy testing of digital X-ray systems in veterinary medicine. Especially a lower dose can be recognised due to deviation in the image quality when compared to the reference image. The 3D-printed test specimen is less expensive than test equipment used in human medicine.

Survey Results Regarding Uptake and Impact of Synthetic Digital Mammography With Tomosynthesis in the Screening Setting

Synthesized digital mammography (SM) was developed to replace digital mammography (DM) in digital breast tomosynthesis (DBT) imaging to reduce radiation dose. This survey assessed utilization and attitudes regarding SM in DBT screening. The study was institutional review board exempt. An online survey was sent to members of the Society of Breast Imaging in June 2018. Questions included practice information, utilization of DBT and SM, perception of change in recall rates (RRs) and cancer detection rates (CDRs) with SM–DBT versus DM–DBT, and attitudes regarding SM versus DM in DBT screening. χ2 Tests were used to compare response frequencies across groups. In all, 312 of 2,600 Society of Breast Imaging members responded to the survey (12%). Of respondents, 96% reported DBT capability, and 83% reported SM capability. Of those without SM, the most cited reasons were cost or administration and image quality concerns (both 32%). In addition, 40% reported combined SM and DM use in DBT screens, and 52% reported SM use without DM in the majority of DBT screens. The overall satisfaction with SM was 3.4 of 5 (1-5 scale). Most cited SM advantages were decreased dose (85%) and increased lesion conspicuity (27%). The most cited SM disadvantages were calcification characterization (61%) and decreased image quality (31%). Most respondents were unsure if CDRs changed (44%) and RR changed (30%) with few reporting adverse outcomes (6% RR increase, 1% CDR decrease). Most radiologists screening with DBT have SM, but only one-half have replaced DM with SM. Despite few reported adverse screening outcomes with SM–DBT, radiologists have concerns about image quality, specifically calcification characterization.

Clinical impact of a new cone beam CT angiography respiratory motion artifact reduction algorithm during hepatic intra-arterial interventions.

To assess the impact of recently developed respiratory motion correction software on contrast-enhanced cone beam CT angiography (CBCT-a) for intraprocedural image guidance during intra-arterial liver-directed therapy. From 2015 to 2017, two groups of patients who underwent intra-arterial liver-directed therapy with (breathing, n = 30) or without (still, n = 30) significant respiratory motion artifacts were retrospectively included. All CBCT-a were processed with and without dedicated respiratory motion correction software. Four readers independently assessed the following in both reconstructions (motion correction ON and OFF): (1) overall image quality on a 0-to-5 point scale, and (2) presence of relevant peri-procedural information on tumor and vasculature (overall vessel geometry, visibility of extrahepatic vessels, target tumor conspicuity, visibility of tumor feeders). Motion correction increased the average image quality in the breathing group from 2.0 ± 0.9 to 2.9 ± 1.0 (p < 0.01). The visibility of vessel geometry, extrahepatic vessels, and tumor feeders was significantly improved for all readers, and tumor conspicuity was improved for three readers. The average image quality was not significantly different between reconstructions in the still group (motion correction ON and OFF), for any of the readers (4.0 ± 0.6 vs 4.2 ± 0.6; p = 0.12). There was no change in the visibility of vessel geometry, extrahepatic vessels, tumor feeders, or tumor conspicuity for the four readers using the respiratory motion correction software in this group. Using the dedicated respiratory motion correction software during intra-arterial liver-directed procedures increases the visualization of relevant peri-procedural information and image quality in CBCT-a corrupted by respiratory motion artifacts without affecting these elements in still CBCT-a. • The use of respiratory motion correction software could reduce the need for cone beam CT angiography acquisition retake. • Motion correction software significantly increases the visibility of vessel geometry, extrahepatic vessels, and tumor feeders, as well as tumor conspicuity in cone beam CT angiography corrupted by respiratory motion artifacts. • The use of respiratory motion correction software on cone beam CT angiography uncorrupted by respiratory motion artifact does not result in decreased image quality.

Quantitative analysis of effects of the grid specifications on the quality of digital radiography images.

A grid is one of the key components of a digital radiography (DR) system because it removes scattered radiation, which arises when X-rays penetrate an object and improves diagnostic accuracy by enhancing image quality. With the widespread use of DR systems, demand for grids with high precision has simultaneously increased. Because unsuitable grids may decrease image quality and lead to misdiagnosis, using optimised grids for DR systems is critical. In this study, we aimed to analyse the quality of X-ray images acquired using grids with different specifications and proposed standardised criteria for grid use on the basis of our results. We measured modulation transfer function (MTF), normalised noise power spectrum (NNPS) and detective quantum efficiency (DQE) using grids with different ratios (10:1, 12:1 and 15:1) with or without implementing poly methyl methacrylate (PMMA) phantoms (0-20cm). Pixel pitch of the detector used in this experiment was 143μm. Based on this, a grid with a line frequency of 85 line pairs/cm was selected to prevent distortion caused by implementing unoptimised grids. As a result, the NNPS was found to increase when using the grid, and the difference in MTF and DQE was only measured when the scattered X-ray was generated by stacking the PMMA phantom. However, grids showed a positive effect MTF and DQE when the PMMA phantom was implemented. Specifically, MTF and DQE improved with increase in grid ratio. Thus, it is desirable to use a high-ratio grid to improve image quality.

Ultralow Dose Dynamic Expiratory Computed Tomography for Evaluation of Tracheomalacia.

The aim of this study was to determine the average effective radiation dose and feasibility of ultralow dose dynamic expiratory computed tomography (CT) for evaluation of tracheomalacia (ULD) and to evaluate factors that impact image quality. This is a retrospective study of 64 consecutive patients from September to October 2016 for the evaluation of tracheomalacia. All studies were performed with routine inspiration chest CT followed by ULD z(kilovoltage peak (kVp) 80, 100, or 120 and fixed milliamperage 10) or typical dose CT (TD) (kVp 100 or 120 with automated milliamperage) dynamic expiration CT. Image quality was considered diagnostic if the trachea area could be accurately measured for tracheomalacia assessment, and diagnostic studies were graded fair, good, or excellent. Scan length, image quality, and effective radiation dose were compared for ULD versus TD and ULD at 100 kVp versus ULD at 80 kVp. For ULD studies, patient factors were compared across image quality. The ULD had a mean effective radiation dose of 0.08 mSv, with all studies of diagnostic image quality. The ULD showed 95% reduction in effective radiation dose (P < 0.001), 14% significant reduction in scan length (P = 0.029), and qualitatively decreased image quality compared w2 ith TD (P < 0.001). The ULD at 100 kVp had significantly better image quality compared with ULD at 80 kVp (P = 0.041) with higher effective radiation dose (0.09 vs 0.05 mSv) (P < 0.001). Body mass index significantly impacted image quality for all ULD studies but not for ULD at 80 or 100 kVp. For evaluation of tracheomalacia, ULD showed low effective radiation dose less than 0.1 mSv and maintained diagnostic image quality.

Improved Wavelet Threshold for Image De-noising.

With the development of communication technology and network technology, as well as the rising popularity of digital electronic products, an image has become an important carrier of access to outside information. However, images are vulnerable to noise interference during collection, transmission and storage, thereby decreasing image quality. Therefore, image noise reduction processing is necessary to obtain higher-quality images. For the characteristics of its multi-analysis, relativity removal, low entropy, and flexible bases, the wavelet transform has become a powerful tool in the field of image de-noising. The wavelet transform in application mathematics has a rapid development. De-noising methods based on wavelet transform is proposed and achieved with good results, but shortcomings still remain. Traditional threshold functions have some deficiencies in image de-noising. A hard threshold function is discontinuous, whereas a soft threshold function causes constant deviation. To address these shortcomings, a method for removing image noise is proposed in this paper. First, the method decomposes the noise image to determine the wavelet coefficients. Second, the wavelet coefficient is applied on the high-frequency part of the threshold processing by using the improved threshold function. Finally, the de-noised images are obtained to rebuild the images in accordance with the estimation in the wavelet-based conditions. Experiment results show that this method, discussed in this paper, is better than traditional hard threshold de-noising and soft threshold de-noising methods, in terms of objective effects and subjective visual effects.

Quantitatively detecting postictal hypoperfusion in patients with focal epilepsy using CT perfusion: Determining cross-modality comparisons and electrode artifacts

BackgroundWe previously showed that CT perfusion (CTP) and arterial spin labelled (ASL) MRI can localize the seizure onset zone in humans via postictal perfusion patterns. As a step towards improving the feasibility/ease of collecting postictal CBF data, we determined whether EEG electrodes need to be removed for CTP data collection and whether a cross-modality comparison between baseline ASL and postictal CTP data is possible. New methodFive patients with epilepsy underwent postictal CTP scanning. Three patients had an interictal ASL scan; one patient had both an ASL and CTP interictal scan. Postictal CTP maps were quantitatively compared to 1) ASL maps averaged from 100 healthy controls, 2) each patient’s baseline ASL map and 3) each patient’s baseline CTP map. To assess for electrode artifacts, a phantom and one patient underwent CTP scanning with EEG electrodes in place. The acquired scans were assessed for artifacts and for postictal hypoperfusion. ResultsFocal postictal hypoperfusion was observable only in intra-modality comparisons (CTP to CTP) and not in cross-modality comparisons (CTP to ASL). EEG electrodes produced streaking artifact that decreased image quality and precluded quantitative analysis. Comparison with existing methods(s)An intra-modality comparison of baseline CTP to postictal CTP was the only comparison method that showed localized hypoperfusion. ConclusionsQuantitative comparison between postictal CTP and baseline ASL scans is not feasible. Postictal hypoperfusion can be detected by CTP only when two CTP scans are collected and when metallic EEG electrodes are removed.

Assessing a novel point-of-care ultrasound training program for rural healthcare providers in Kenya

BackgroundA novel point-of-care ultrasound (PoCUS) training program was developed to train rural healthcare providers in Kenya on the Focused Assessment with Sonography for Trauma (FAST), thoracic ultrasound, basic echocardiography, and focused obstetric ultrasonography. The program includes a multimedia manual, pre-course testing, 1-day hands-on training, post-testing, 3-month post-course evaluation, and scheduled refresher training. This study evaluates the impact of the course on PoCUS knowledge and skills. Competency results were compared based on number of previous training/refresher sessions and time elapsed since prior training.MethodsTrainees were evaluated using a computer-based, 30 question, multiple-choice test, a standardized observed structured clinical exam (OSCE), and a survey on their ultrasound use over the previous 3 months.ResultsThirty-three trainees were evaluated at 21 different facilities. All trainees completed the written exam, and 32 completed the OSCE. Nine trainees out of 33 (27.3%) passed the written test. Trainees with two or more prior training sessions had statistically significant increases in their written test scores, while those with only one prior training session maintained their test scores. Time elapsed since last training was not associated with statistically significant differences in mean written test scores. Mean image quality scores (95% confidence interval) were 2.65 (2.37–2.93) for FAST, 2.41 (2.03–2.78) for thoracic, 2.22 (1.89–2.55) for cardiac, and 2.95 (2.67–3.24) for obstetric exams. There was a trend towards increased mean image quality scores with increases in the number of prior training sessions, and a trend towards decreased image quality with increased time elapsed since previous training. Forty percent of trainees reported performing more than 20 scans in the previous 3 months, while 22% reported less than 10 scans in the previous 3 months. Second and third trimester focused obstetric ultrasound was the most frequently performed scan type. Frequency of scanning was positively correlated with written test scores and image quality scores.ConclusionThis novel training program has the potential to improve PoCUS knowledge and skills amongst rural healthcare providers in Kenya. There is an ongoing need to increase refresher/re-training opportunities and to enhance frequency of scanning in order to improve PoCUS competency.

Modified ultrasound despeckling assessment index for the Field II simulated cyst image

Various methods have been proposed to reduce speckle noise, which decreases image quality in ultrasound images. The Field II simulated cyst image consists of three classes and is used to compare a proposed despeckle filter with other well-known filters. The ultrasound despeckling assessment index (USDSAI) is a metric used to evaluate the proposed despeckling filters for the cyst image. This metric should be used when different regions are properly defined. In this study, the authors first analysed the performance of USDSAI for the cyst image. Then, the authors modified the USDSAI by proposing a new metric for the background class of the cyst image and evaluated its performance. The results show that the authors' proposed metric has better performance than USDSAI.