Factors Affecting Image Quality Research Articles

An Image-Based Sensor System for Low-Cost Airborne Particle Detection in Citizen Science Air Quality Monitoring.

Air pollution poses significant public health risks, necessitating accurate and efficient monitoring of particulate matter (PM). These organic compounds may be released from natural sources like trees and vegetation, as well as from anthropogenic, or human-made sources including industrial activities and motor vehicle emissions. Therefore, measuring PM concentrations is paramount to understanding people's exposure levels to pollutants. This paper introduces a novel image processing technique utilizing photographs/pictures of Do-it-Yourself (DiY) sensors for the detection and quantification of PM10 particles, enhancing community involvement and data collection accuracy in Citizen Science (CS) projects. A synthetic data generation algorithm was developed to overcome the challenge of data scarcity commonly associated with citizen-based data collection to validate the image processing technique. This algorithm generates images by precisely defining parameters such as image resolution, image dimension, and PM airborne particle density. To ensure these synthetic images mimic real-world conditions, variations like Gaussian noise, focus blur, and white balance adjustments and combinations were introduced, simulating the environmental and technical factors affecting image quality in typical smartphone digital cameras. The detection algorithm for PM10 particles demonstrates robust performance across varying levels of noise, maintaining effectiveness in realistic mobile imaging conditions. Therefore, the methodology retains sufficient accuracy, suggesting its practical applicability for environmental monitoring in diverse real-world conditions using mobile devices.

NoiseNet, a fully automatic noise assessment tool that can identify non-diagnostic CCTA examinations

Image noise and vascular attenuation are important factors affecting image quality and diagnostic accuracy of coronary computed tomography angiography (CCTA). The aim of this study was to develop an algorithm that automatically performs noise and attenuation measurements in CCTA and to evaluate the ability of the algorithm to identify non-diagnostic examinations. The algorithm, “NoiseNet”, was trained and tested on 244 CCTA studies from the Swedish CArdioPulmonary BioImage Study. The model is a 3D U-Net that automatically segments the aortic root and measures attenuation (Hounsfield Units, HU), noise (standard deviation of HU, HUsd) and signal-to-noise ratio (SNR, HU/HUsd) in the aortic lumen, close to the left coronary ostium. NoiseNet was then applied to 529 CCTA studies previously categorized into three subgroups: fully diagnostic, diagnostic with excluded parts and non-diagnostic. There was excellent correlation between NoiseNet and manual measurements of noise (r = 0.948; p < 0.001) and SNR (r = 0.948; <0.001). There was a significant difference in noise levels between the image quality subgroups: fully diagnostic 33.1 (29.8–37.9); diagnostic with excluded parts 36.1 (31.5–40.3) and non-diagnostic 42.1 (35.2–47.7; p < 0.001). Corresponding values for SNR were 16.1 (14.0–18.0); 14.0 (12.4–16.2) and 11.1 (9.6–14.0; p < 0.001). ROC analysis for prediction of a non-diagnostic study showed an AUC for noise of 0.73 (CI 0.64–0.83) and for SNR of 0.80 (CI 0.71–0.89). In conclusion, NoiseNet can perform noise and SNR measurements with high accuracy. Noise and SNR impact image quality and automatic measurements may be used to identify CCTA studies with low image quality.

Quantifying cerebral microbleeds using quantitative susceptibility mapping from magnetization-prepared rapid gradient-echo.

T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) is commonly included in brain studies for structural imaging using magnitude images; however, its phase images can provide an opportunity to assess microbleed burden using quantitative susceptibility mapping (QSM). This potential application for MPRAGE-based QSM was evaluated using in vivo and simulated measurements. Possible factors affecting image quality were also explored. Detection sensitivity was evaluated against standard multiecho gradient echo (MEGE) QSM using 3-T in vivo data of 15 subjects with a combined total of 108 confirmed microbleeds. The two methods were compared based on the microbleed size and susceptibility measurements. In addition, simulations explored the detection sensitivity of MPRAGE-QSM at different representative magnetic field strengths and echo times using microbleeds of different size, susceptibility, and location. Results showed that in vivo microbleeds appeared to be smaller (× 0.54) and of higher mean susceptibility (× 1.9) on MPRAGE-QSM than on MEGE-QSM, but total susceptibility estimates were in closer agreement (slope: 0.97, r2: 0.94), and detection sensitivity was comparable. In simulations, QSM at 1.5 T had a low contrast-to-noise ratio that obscured the detection of many microbleeds. Signal-to-noise ratio (SNR) levels at 3 T and above resulted in better contrast and increased detection. The detection rates for microbleeds of minimum one-voxel diameter and 0.4-ppm susceptibility were 0.55, 0.80, and 0.88 at SNR levels of 1.5, 3, and 7 T, respectively. Size and total susceptibility estimates were more consistent than mean susceptibility estimates, which showed size-dependent underestimation. MPRAGE-QSM provides an opportunity to detect and quantify the size and susceptibility of microbleeds of at least one-voxel diameter at B0of 3 T or higher with no additional time cost, when standard T2*-weighted images are not available or have inadequate spatial resolution. The total susceptibility measure is more robust against sequence variations and might allow combining data from different protocols.

Numerical Simulation of Neural Network Based on Adaptive Optics for Correcting Phase Distortion in Astronomical Observations

Adaptive optics revolutionizes telescopic resolution but faces cost, complexity, and calibration hurdles. Neural network adaptive optics (NNAO) offers promise by using neural networks to tailor corrections to telescopes and atmospheric conditions, by passing calibration and sensors. This MATLAB-based study examines NNAO's impact on astronomical image quality, revealing it as a cost-efficient solution that enhances adaptive optics in astronomy. The numerical simulation results were encouraging, with a compensation rate exceeding 50% due to favorable monitoring conditions. The results indicate that the dominant factor affecting image quality is the variance of wavefront aberrations. The Strehl ratio (SR) decreases from an average of 0.548 for a variance of 0.2 to 0.020 for a variance of 0.6, while the mean squared error (MSE) increases from an average of 0.613 to 5.414. However, the effect on peak signal-to-noise ratio (PSNR) is inconclusive. Furthermore, it was found that increasing the number of neurons and training ratio does not significantly impact the results obtained, but it noticeably affects the computational time required.

Design and dynamic analysis of supporting mechanism for large scale space deployable membrane sunshield

AbstractStray light from the sun is one of the most significant factors affecting image quality for the optical system of a spacecraft. This paper proposes a method to design a deployable supporting mechanism for the sunshield based on origami. Firstly, a new type of space mechanism with single-closed loop was proposed according to thick-panel origami, and its mobility was analysed by using the screw theory. In order to design a deployable structure with high controllability, the tetrahedral constraint was introduced to reduce the degree of freedom (DOF), and a corresponding deployable unit named tetrahedral deployable unit (TDU) was obtained. Secondly, the process to constructing a large space deployable mechanism with infinite number of units was explained based on the characteristics of motion and planar mosaic array, and kinematics analysis and folding ratio of supporting mechanism were conducted. A physical prototype was constructed to demonstrate the mobility and deployment of the supporting mechanism. Finally, based on the Lagrange method, a dynamic model of supporting mechanism was established, and the influence of the torsion spring parameters on the deployment process was analysed.

To Assess the Factors Effecting Image Quality in Magnetic Resonance Imaging at 1.5T

Background: Good image quality is essential for accurate diagnosis in magnetic resonance imaging (MRI) examinations. This study aimed to investigate how image quality can be improved by implementing improvement strategies on factors that effects the MRI parameters instead of relying solely on conventional techniques. Method: This research employs a Comparative study design to compare the image quality in routine brain Magnetic Resonance Imaging (MRI) scans at 1.5T before and after implementing image quality improvement strategies. The study involved 37 individuals participant’s data (20 females and 17 males) aged 15-70 years who underwent MRI scans. Participants with any systemic disease, acute trauma, pregnancy and participants with absolute contraindications were excluded from the study. Result: The study found that several factors can effects MRI image quality and can be improved by implementing improvement strategies on these factors by manual adjustments. By identifying factors affecting image quality and evaluating improvement strategies, we seek to optimize MRI protocols and enhance the diagnostic utility of routine brain imaging. For instance, increasing the number of Excitation (NEX) values improved image quality. By increasing the echo time (TE) value a 50% images shows improvement in image quality. The volume of shimming showed better image quality than the other two modes (difficult mode and auto mode). Decreasing the flip angle and voxel size also improved image quality Conclusion: In conclusion, image quality can be improved by implementing improvement strategies on factors that effects the MRI parameters in comparison with the conventional techniques.

Physical Image Quality Metrics for the Characterization of X-ray Systems Used in Fluoroscopy-Guided Pediatric Cardiac Interventional Procedures: A Systematic Review.

Pediatric interventional cardiology procedures are essential in diagnosing and treating congenital heart disease in children; however, they raise concerns about potential radiation exposure. Managing radiation doses and assessing image quality in angiographs becomes imperative for safe and effective interventions. This systematic review aims to comprehensively analyze the current understanding of physical image quality metrics relevant for characterizing X-ray systems used in fluoroscopy-guided pediatric cardiac interventional procedures, considering the main factors reported in the literature that influence this outcome. A search in Scopus and Web of Science, using relevant keywords and inclusion/exclusion criteria, yielded 14 relevant articles published between 2000 and 2022. The physical image quality metrics reported were noise, signal-to-noise ratio, contrast, contrast-to-noise ratio, and high-contrast spatial resolution. Various factors influencing image quality were investigated, such as polymethyl methacrylate thickness (often used to simulate water equivalent tissue thickness), operation mode, anti-scatter grid presence, and tube voltage. Objective evaluations using these metrics ensured impartial assessments for main factors affecting image quality, improving the characterization of fluoroscopic X-ray systems, and aiding informed decision making to safeguard pediatric patients during procedures.

P-373 Low-Dose Vaginal Misoprostol Application Before Office Hysteroscopy

Abstract Study question In gynecological interventional procedures what should be the minimum misoprostol dose for achieving cervical maturation? Summary answer 50mcgr vaginal misoprostol before office hysteroscopy; decreases the VAS score, bleeding and the total procedure time. What is known already Misoprostol has been on the World Health Organization (WHO) essential drugs list since 2005 due to its uterotonic effect.FIGO (The International Federation of Gynecology and Obstetrics) published a posology table in 2017 that does not cause side effects in off-label use of misoprostol in the obstetric field.There are many publications that misoprostol facilitates interventional gynecologic procedures by allowing cervical maturation . However, no guidelines have yet been published on the dose and route of administration Study design, size, duration This Prospective Randomized Clinical Research was approved by Ankara City Hospital Clinical Research Ethics and Academic committee . Then, 100 women who underwent office hysteroscopy in Ankara City Hospital Gynecology and Obstetrics Clinic gynecology-infertility outpatient clinic between 01/12/2021-01/05/2022 were included in the study after their informed consent was obtained. Participants/materials, setting, methods 50 women who self-administered 50 mcg vaginal misoprostol the night before the office hysteroscopy procedure and 50 women who did not administer the drug were compared. The primary outcome of the study was the duration of the procedure, with the pain score during the procedure used being the (VAS) score system. The secondary outcome was procedure and drug-related side effects Statistical evaluation of the data was performed using the SPSS for Windows version 20.0 Main results and the role of chance In the medicated group the mean of VAS scores during and after the procedure, and the transition and the total time of the procedure were significantly lower than non-medicated group. Limitations, reasons for caution In Turkey, there is only one misoprostol product (CYTOTEC Ali Raif İlaç Sanayi A.Ş) with the 200 mcg posology Off label use of misoporostol in obstetrics is legal since 2021 but not for gynecological practice. We do not have country guidelines on misoprostol posology in obstetrics and gynecology usage also Wider implications of the findings In gynecological interventional procedures especially before office hysteroscopy, it is important to apply a minimum dose of misoprostol for cervical maturation due to its bleeding-increasing effect in patients whith endometrial polyps or hyperplasia .Because bleeding is the most important factor affecting image quality and procedure efficacy during hysteroscopy. Trial registration number E2-21-1068 dated 24.11.2021

Validation of a sonographic checklist for the detection of histologic placenta accreta spectrum

To standardize research terminology and reduce unanticipated placenta accreta spectrum (PAS), the European Working Group for Abnormally Invasive Placenta (EW-AIP) developed a consensus checklist for reporting PAS suspected on antenatal ultrasound. The diagnostic accuracy of the EW-AIP checklist has not been assessed. To test the performance of the EW-AIP sonographic checklist in predicting histologic PAS. This is a multi-site, blinded, retrospective review of transabdominal ultrasound studies performed between 26-32 weeks gestation for subjects with histologic PAS between 2016-2020. We matched a 1:1 control cohort of subjects without histologic PAS. To reduce reader bias, we matched the control cohort for known risk factors including previa, number of prior cesarean deliveries, prior dilation and curettage (D&C), in vitro fertilization (IVF), and clinical factors affecting image quality including multiple gestation, body mass index (BMI) and gestational age at the ultrasound. Nine sonologists from 5 referral centers, blinded to the histologic outcomes, interpreted the randomized ultrasound studies using the EW-AIP checklist. The primary outcome was the sensitivity and specificity of the checklist to predict PAS. Two separate sensitivity analyses were performed: 1) we excluded subjects with mild disease (i.e. only assessed subjects with histologic increta and percreta); 2) we excluded interpretations from the 2 most junior sonologists. 78 subjects were included (39 PAS, 39 matched control). Clinical risk factors and image quality markers were statistically similar between cohorts. The checklist sensitivity (95% Confidence Interval, CI) was 76.6% (63.4%-90.6%) and specificity (95% CI) was 92.0% (63.4%-99.9%), with a positive and negative likelihood ratio of 9.6 and 0.3, respectively. When we excluded subjects with mild PAS disease, the sensitivity (95% CI) increased to 84.7% (73.6%-96.4%) and specificity was unchanged at 92.0% (83.2%-99.9%). Sensitivity and specificity were unchanged when the interpretations from the 2 most junior sonologists were excluded. The 2016 EW-AIP checklist for interpreting PAS has a reasonable performance in detecting and excluding histologic placenta accreta spectrum.

New challenges and opportunities for low-field MRI

In this manuscript we deal with recent advances in low-field Magnetic Resonance Imaging (MRI). The development of low-cost MRI solutions allowing portability and trustable diagnosis is a hot topic worldwide by these days. We analyze basic technical issues of recent examples of fixed-field instruments operating at low-field. Then we discuss pros and cons of the pre-polarized approach, from both physical and technical perspectives. Permanent magnet and electromagnet technology are confronted. Finally, magnetic field-cycling is introduced as an alternative MRI technique, where field-dependent experiments can be exploded for the development of new contrast mechanisms that are not feasible for fixed-field MRI instruments. As field cycled machines usually deals with switched currents in electromagnets, magnetic field instability and inhomogeneity are the main limiting factors affecting image quality. We finalize this manuscript discussing how it turns possible to overcome these limitations, thus opening new possibilities for the development of cost effective MRI technology.

Performance Evaluation of Indian Food Image Classification system using Transfer Learning with MobileNetV3

Food image classification and recognition is an emerging research area due to its growing importance in the medical and health industries. As India is growing digitally rapidly, an automated Indian food image classification system will help in the development of diet tracking, calorie estimation, and many other health and food consumption-related applications. In recent years many deep learning techniques evolved. Deep learning is a robust and low-cost method for extracting information from food images, though, challenges lie in extracting information from real-world food images due to various factors affecting image quality such as photos from different angles and positions, several objects appearing in the photo, etc. We used Non-Standard dataset for Indian Food images of 13 different classes consist more than 3500 images. In this paper, we use CNN as our base model to build our system, which gives an accuracy of 47% of the system. After that, we deployed the transfer learning technique with MobileNetV3 for improvement in accuracy, which resulted in an improvement in accuracy of up to 90%.

Advanced pediatric neuroimaging.

Advanced magnetic resonance neuroimaging techniques play an important adjunct role to conventional MRI sequences for better depiction and characterization of a variety of brain disorders. In this article we briefly review the basic principles and clinical utility of a select number of these techniques, including clinical functional MRI for presurgical planning, clinical diffusion tensor imaging and related techniques, dynamic susceptibility contrast perfusion imaging using gadolinium injection, and arterial spin labeling perfusion imaging. The article focuses on general principles of clinical MRI acquisition protocols, relevant factors affecting image quality, and a general framework for obtaining images for each of these techniques. We also present relevant advances for acquiring these types of imaging sequences in a clinical setting.

CSDM: A Cross-Scale Decomposition Method for Low-Light Image Enhancement

Inadequate lighting condition is one of the main factors affecting image quality. For high-quality image display and vision applications, low-light image enhancement is an extremely challenging task. However, most existing methods are difficult to remove heavy noise in the low-light enhancement process effectively. To solve this problem, this paper presents a novel cross-scale decomposition method (CSDM) for low-light image enhancement. The main idea is to capture the small-scale texture and heavy noise, and preserve the large-scale structure by designing a Gaussian regularization based on a cross-scale relative relationship. An optimization objective function is established to transform image decomposition, low-light enhancement and noise suppression into a unified optimization framework. The framework uses sequential decomposition to estimate texture and structure layers. Firstly, the structure layer of the image is estimated, and an illumination prior is introduced to improve the contrast. Then the texture layer is estimated, and a low-rank prior is applied to eliminate noise. Finally, the structure and texture layers are combined to obtain a final enhanced image. Experiment results on public datasets and an industrial site demonstrate that the advantages of our method from both qualitative and quantitative perspectives.

Validation of a dedicated positron emission tomography scanner for imaging of the distal limb of standing horses.

A positron emission tomography (PET) scanner, with an openable ring of detectors, was specifically designed to image the distal limb of standing horses. The goals of this prospective, preclinical, experimental, methods comparison study were to validate the safety of the scanner, assess image quality, and optimize scanning protocols. Six research horses were imaged three times (twice standing, once anesthetized) and six horses in active race training were imaged once under standing sedation. Multiple scans of both front fetlocks were obtained with different scan durations and axial fields of view. A total of 94 fetlock scans were attempted and 90 provided images of diagnostic value. Radiotracer uptake was the main factor affecting image quality, while motion did not represent a major issue. Scan duration and field of view also affected image quality. Eight specific lesions were identified on PET images from anesthetized horses and were all also independently recognized on the PET images obtained on standing horses. Maximal standardized uptake values (SUVmax) had good repeatability for the assessment of specific lesions among different scans. Three feet and six carpi were also successfully imaged. This study validated the safety and practicality of a PET scanner specifically designed to image the distal limb in standing horses. Proper preparation of horses, similar to bone scintigraphy, is important for image quality. A 4-min scan with 12cm field of view was considered optimal for clinical fetlock imaging. Evaluation of a larger clinical population is the next step for further assessment of the clinical utility of PET imaging in horses.

Anterior segment imaging using a simple universal smartphone attachment for patients

ABSTRACT To assess the utility of a universal smartphone attachment to capture images of the anterior segment of the eye, we conducted a retrospective analysis of 344 images captured using a smartphone by the patients to identify factors affecting image quality, such as lack of perspective, lack of focus, improper illumination, and resolution. Based on this analysis, a universal smartphone attachment named GrabiTMLite and a protocol for anterior segment imaging were designed and validated in the first prospective arm of 60 patients. These images were then compared with the same eyes imaged on the gold standard slit-lamp photography. In the second prospective arm, nine patients were trained to use the GrabiTM Lite with the imaging protocol, and the images were assessed for utility in arriving at a diagnosis. A total of 178 images were analyzed using a questionnaire by masked observers. The images were evaluated based on their quality and suitability in clinical decision-making, risk stratification for triage for referral to a tertiary eye care centre. The quality of 344 images captured by patients using only their smartphone was rated as good 24 (7%), average 209 (60.8%), and poor in 111 (32.2%). Of these, 55 (16%) images were deemed suitable for clinical decision-making, and 224 (65.6%) images were adequate for risk stratification. Lack of perspective, focus, illumination, and resolution were seen in 167 (51.2%), 284 (87.1%), 226 (69.3%), and 126 (38.7%) images, respectively. These metrics improved in the next iteration of 178 images captured by patients using Grabi Lite + imaging protocol to good 103 (57%), average 58 (32.6%), and bad 17 (19.6%) (p < .001 using chi-square test). Images deemed suitable for clinical decision-making, and risk stratification for triage also improved to 80 (45%), 158 (88.8%) (p < .001 using chi-square test), respectively. Adherence to protocol was seen in 98 (55.5%) images, of which all were suitable for risk stratification, while of these images, 66 (67.3%) were eligible for clinical decision making. In comparison with slit-lamp photography, out of 120 responses by masked observers to images captured by GrabiTM Lite with the imaging protocol, 63 (52.85%) were suitable for clinical decision-making, and 68 (57%) were graded to be between 70 and 99% of the quality of the slit lamp photographs. The GrabiTM lite with imaging protocol training is an effective tool to improve anterior segment imaging, potentially allowing smartphone use for teleconsultations. This device may serve as a universal solution for all smartphones with the patient as the user and is of value in the future of tele-ophthalmology.

Factors Affecting Image Quality For Optimal Radiodiagnosis

Factors Affecting Image Quality For Optimal Radiodiagnosis

Radiation Risks of Kidney during Abdominal CT Procedures in Morocco: A Multicentre Study

This study aimed to estimate renal effective dose during abdominal CT scans in order to assess the renal risks of cancer and heredity per procedure in Moroccan hospitals. It’s consisted of examining a total of 120 patients referred to three radiology departments for an abdominal CT scan at the rate of 40 per hospital. The data that collected for this diagnostic exam included scanner acquisition parameters, number of series, use of the contrast medium, and rotation time as well as slice thickness, the displayed CT dose index (CTDIvol) and the Dose Length Product (DLP). Renal dose, effective dose and biological risks were estimated using the International Commission on Radiological Protection (ICRP) conversion factor. The patients included in this study were an average age of the (46.49 ± 14.16) years and an average weight of (73.34 ± 7.58) kg. For the mean effective dose (E) and average kidney dose (DK) received per patient during an abdominal CT scan, it were respectively of (6.67 ± 2.73) and (18.26 ± 7.74) mSv. The distribution of these values according to the hospital variable shows a difference in mean effective dose of the order of 0.26, 0.38 and 1.45 mSv and a difference in the mean renal dose of the order of 8.76, 4.94 and 0.48 mSv respectively for H1, H2 and H3. The induction cancer risk of abdominal and kidney per 105 procedures was respectively of 3 and 10. The kidney cancer risk by procedure is two to three times more likely than abdominal. For hereditary risk of abdominal and renal exposure per 106 procedures, it is 14 and 21 respectively. The renal stochastic effect by procedure is also two to three times more likely than that of the abdomen. Our values are relatively higher than those of published in some previous studies. Cancer risk and heredity estimation highlights the need to limit radiation dose. This first ever survey confirmed the need to improved training of health professionals involved in computed tomography on factors affecting image quality, doses and protocols optimization.

Factors Affecting Image Quality and Lesion Evaluability in Breast Diffusion-weighted MRI: Observations from the ECOG-ACRIN Cancer Research Group Multisite Trial (A6702).

The A6702 multisite trial confirmed that apparent diffusion coefficient (ADC) measures can improve breast MRI accuracy and reduce unnecessary biopsies, but also found that technical issues rendered many lesions non-evaluable on diffusion-weighted imaging (DWI). This secondary analysis investigated factors affecting lesion evaluability and impact on diagnostic performance. The A6702 protocol was IRB-approved at 10 institutions; participants provided informed consent. In total, 103 women with 142 MRI-detected breast lesions (BI-RADS assessment category 3, 4, or 5) completed the study. DWI was acquired at 1.5T and 3T using a four b-value, echo-planar imaging sequence. Scans were reviewed for multiple quality factors (artifacts, signal-to-noise, misregistration, and fat suppression); lesions were considered non-evaluable if there was low confidence in ADC measurement. Associations of lesion evaluability with imaging and lesion characteristics were determined. Areas under the receiver operating characteristic curves (AUCs) were compared using bootstrapping. Thirty percent (42/142) of lesions were non-evaluable on DWI; 23% (32/142) with image quality issues, 7% (10/142) with conspicuity and/or localization issues. Misregistration was the only factor associated with non-evaluability (P = 0.001). Smaller (≤10 mm) lesions were more commonly non-evaluable than larger lesions (p <0.03), though not significant after multiplicity correction. The AUC for differentiating benign and malignant lesions increased after excluding non-evaluable lesions, from 0.61 (95% CI: 0.50-0.71) to 0.75 (95% CI: 0.65-0.84). Image quality remains a technical challenge in breast DWI, particularly for smaller lesions. Protocol optimization and advanced acquisition and post-processing techniques would help to improve clinical utility.

Is Bigger Really Better? Comparison of Ultraportable Handheld Ultrasound with Standard Point-of-Care Ultrasound for Evaluating Safe Site Identification and Image Quality prior to Pleurocentesis

Background: Pleural effusions remain a common medical problem which often requires diagnostic pleurocentesis to determine the underlying cause. Pleurocentesis is a frequently performed procedure worldwide with improved safety using ultrasound (US) technology. Objectives: This prospective, single-center study evaluated the use of an ultraportable handheld (UPHH) US compared with standard point-of-care (SPOC) US in determining a safe site for pleurocentesis. In addition, US image quality and factors impacting on image quality were assessed using both UPHH and SPOC US. Methods: Paired US assessments were performed by thoracic physicians using UPHH and SPOC US on patients with unilateral pleural effusions to determine a safe site for pleurocentesis (defined as >2 cm of pleural fluid, >2 cm from a solid organ/diaphragm, and <7 cm chest wall depth). Distance measurements for key structures and image quality scores (using a 5-point Likert rating scale) were obtained at the time of US assessment. Factors affecting image quality were analyzed using univariate analysis. Results: In 52 of the 54 included patients (96.3%), UPHH US was able to identify a safe site for pleurocentesis. Distance measurements between UPHH and SPOC US were not statistically different (all <0.5 cm with values of p > 0.05), but image quality was reduced in UPHH compared with SPOC US by 1 point on a 5-point Likert rating scale (p < 0.002). Increasing body mass index was associated with a reduction in image quality in both UPHH and SPOC US (all p < 0.01). Conclusions: Although image quality was lower in UPHH than SPOC US, a safe site was found in 96.3% of patients, which suggests that UPHH US may be a useful tool for diagnostic pleuro­centesis when SPOC US is not available (http://www.anzctr.org.au/, Australia New Zealand Clinical Trials Registry, No. ACTRN12618001592235).

A Comparison of MRI Radiographers' Knowledge in Saudi Arabia and the Republic of Ireland in Relation to Image Quality Management, for Abdomen and Pelvic MRI Examinations

PurposeThe purpose of this article was to qualitatively compare current MRI radiographers’ knowledge from Saudi Arabia and the Republic of Ireland in relation to MR image quality for abdominal and pelvic MRI examinations. Methods and materialsSemistructured interviews were designed to investigate the professional role of radiographers towards image quality management, personal development in MRI, and training in relation to image quality improvement. Public, private, military, and academic hospitals in the Western region of the Kingdom of Saudi Arabia participated, as did a range of public and private Irish centres. Clinical specialist radiographers (CSRs)/supervisors, and MR radiographers working in MR completed the interviews. These were recorded, coded, and transcribed. ResultsSixty-one MR radiographers and CSRs/supervisors within 11 MRI departments in the Kingdom of Saudi Arabia and 11 MRI departments in the Republic of Ireland participated in this study. Three themes resulted by using a qualitative data analysis program called NVivo: (1) health care professional and the cultural attitudes with regards to the scope of professional roles, (2) factors affecting image quality, and (3) departmental policy. Participants' knowledge of image quality varied and challenges to achieving optimal quality levels were noted. Differences in clinical practice between countries were identified, as was the impact of clinical experience and levels of education. ConclusionDifferences in attitude and clinical practice between Saudi and Irish radiographers and CSRs/supervisors working in MRI departments were identified. There is a need for further training and subsequent assessment of professional skills, including developing postgraduate opportunities, particularly for Saudi radiographers, to support radiographers in the routine management of MR image quality.