Radiographic Image Quality Research Articles

Evaluation of the Diagnostic Quality of Chest Radiographs

Introduction: With the advancement of conventional radiography to digital, digital radiography of the chest is commonly performed these days. The role and importance of diagnostic quality of radiographs are to help the radiologists and the clinicians in the diagnosis of diseases and their management, as well as to prevent the misdiagnosis of any pathology. This study was an attempt to quantify the diagnostic quality of chest radiographs by evaluating the quality of depiction of the anatomical details as well as other technical factors. Method: A total of 450 chest radiographs, produced at Tribhuvan University Teaching Hospital, were selected for study over two months period. Five image quality criteria i.e. anatomical coverage, rotation, adequate penetration, adequate inspiration, and scapula out of lung fields were evaluated and tabulated. Results: Out of the 450 radiographs taken for study, only 22.2% of the radiographs fulfilled all the image quality criteria, the rest 77.8% either lacked one or more of the quality criteria. Conclusion: Many technical factors affect the image quality of digital chest radiographs. However, the radiographer/technologist should always try to maintain adequate image quality of the radiographs.

General Radiography Image Quality Scorecard

Purpose: To describe the Image Quality Audit Framework and highlight the impact of Image Quality Audit.Methods: Radiographers trained in Image Interpretation were recruited to review the radiographic images retrospectively. An Image Quality form was created using “Visual Basic Application” in Microsoft Excel to record the auditors’ findings. There were nine criteria which grade the quality of the images based on technical and clinical aspects. Each criterion consisted of 3-point Likert scale or closed-ended question. The auditors randomly reviewed 5% of the total number of examinations performed by the auditees. The responses were stored, and the programme generated a scorecard automatically. A second auditor was asked to review the images if there is a disagreement between the auditor and auditee in the score achieved.Results: The framework enabled a holistic analysis and accurate identification of radiographer's areas of improvement. Corrective action plans were developed to improve the radiographers’ skill. Continuous active learning was achieved when the auditor and auditee review the results together.Conclusion: A robust clinical audit comprising of both Image Quality and Reject Rate Analysis can improve the quality of images produced. This brings value to the patients by increasing the accuracy of the patient's diagnosis, which allows more targeted treatment. Purpose: To describe the Image Quality Audit Framework and highlight the impact of Image Quality Audit. Methods: Radiographers trained in Image Interpretation were recruited to review the radiographic images retrospectively. An Image Quality form was created using “Visual Basic Application” in Microsoft Excel to record the auditors’ findings. There were nine criteria which grade the quality of the images based on technical and clinical aspects. Each criterion consisted of 3-point Likert scale or closed-ended question. The auditors randomly reviewed 5% of the total number of examinations performed by the auditees. The responses were stored, and the programme generated a scorecard automatically. A second auditor was asked to review the images if there is a disagreement between the auditor and auditee in the score achieved. Results: The framework enabled a holistic analysis and accurate identification of radiographer's areas of improvement. Corrective action plans were developed to improve the radiographers’ skill. Continuous active learning was achieved when the auditor and auditee review the results together. Conclusion: A robust clinical audit comprising of both Image Quality and Reject Rate Analysis can improve the quality of images produced. This brings value to the patients by increasing the accuracy of the patient's diagnosis, which allows more targeted treatment.

Image Quality Control in Lumbar Spine Radiography Using Enhanced U-Net Neural Networks.

PurposeTo standardize the radiography imaging procedure, an image quality control framework using the deep learning technique was developed to segment and evaluate lumbar spine x-ray images according to a defined quality control standard.Materials and MethodsA dataset comprising anteroposterior, lateral, and oblique position lumbar spine x-ray images from 1,389 patients was analyzed in this study. The training set consisted of digital radiography images of 1,070 patients (800, 798, and 623 images of the anteroposterior, lateral, and oblique position, respectively) and the validation set included 319 patients (200, 205, and 156 images of the anteroposterior, lateral, and oblique position, respectively). The quality control standard for lumbar spine x-ray radiography in this study was defined using textbook guidelines of as a reference. An enhanced encoder-decoder fully convolutional network with U-net as the backbone was implemented to segment the anatomical structures in the x-ray images. The segmentations were used to build an automatic assessment method to detect unqualified images. The dice similarity coefficient was used to evaluate segmentation performance.ResultsThe dice similarity coefficient of the anteroposterior position images ranged from 0.82 to 0.96 (mean 0.91 ± 0.06); the dice similarity coefficient of the lateral position images ranged from 0.71 to 0.95 (mean 0.87 ± 0.10); the dice similarity coefficient of the oblique position images ranged from 0.66 to 0.93 (mean 0.80 ± 0.14). The accuracy, sensitivity, and specificity of the assessment method on the validation set were 0.971–0.990 (mean 0.98 ± 0.10), 0.714–0.933 (mean 0.86 ± 0.13), and 0.995–1.000 (mean 0.99 ± 0.12) for the three positions, respectively.ConclusionThis deep learning-based algorithm achieves accurate segmentation of lumbar spine x-ray images. It provides a reliable and efficient method to identify the shape of the lumbar spine while automatically determining the radiographic image quality.

Automated quality assessment of chest radiographs based on deep learning and linear regression cascade algorithms.

Develop and evaluate the performance of deep learning and linear regression cascade algorithms for automated assessment of the image layout and position of chest radiographs. This retrospective study used 10 quantitative indices to capture subjective perceptions of radiologists regarding image layout and position of chest radiographs, including the chest edges, field of view (FOV), clavicles, rotation, scapulae, and symmetry. An automated assessment system was developed using a training dataset consisting of 1025 adult posterior-anterior chest radiographs. The evaluation steps included: (i) use of a CNN framework based on ResNet - 34 to obtain measurement parameters for quantitative indices and (ii) analysis of quantitative indices using a multiple linear regression model to obtain predicted scores for the layout and position of chest radiograph. In the testing dataset (n = 100), the performance of the automated system was evaluated using the intraclass correlation coefficient (ICC), Pearson correlation coefficient (r), mean absolute difference (MAD), and mean absolute percentage error (MAPE). The stepwise regression showed a statistically significant relationship between the 10 quantitative indices and subjective scores (p < 0.05). The deep learning model showed high accuracy in predicting the quantitative indices (ICC = 0.82 to 0.99, r = 0.69 to 0.99, MAD = 0.01 to 2.75). The automatic system provided assessments similar to the mean opinion scores of radiologists regarding image layout (MAPE = 3.05%) and position (MAPE = 5.72%). Ten quantitative indices correlated well with the subjective perceptions of radiologists regarding the image layout and position of chest radiographs. The automated system provided high performance in measuring quantitative indices and assessing image quality. • Objective and reliable assessment for image quality of chest radiographs is important for improving image quality and diagnostic accuracy. • Deep learning can be used for automated measurements of quantitative indices from chest radiographs. • Linear regression can be used for interpretation-based quality assessment of chest radiographs.

Correction of Motion Artifacts in Dark-Field Radiography of the Human Chest.

Dark-field radiography of the human chest is a promising novel imaging technique with the potential of becoming a valuable tool for the early diagnosis of chronic obstructive pulmonary disease and other diseases of the lung. The large field-of-view needed for clinical purposes could recently be achieved by a scanning system. While this approach overcomes the limited availability of large area grating structures, it also results in a prolonged image acquisition time, leading to concomitant motion artifacts caused by intrathoracic movements (e.g. the heartbeat). Here we report on a motion artifact reduction algorithm for a dark-field X-ray scanning system, and its successful evaluation in a simulated chest phantom and human in vivo chest X-ray dark-field data. By partitioning the acquired data into virtual scans with shortened acquisition time, such motion artifacts may be reduced or even fully avoided. Our results demonstrate that motion artifacts (e.g. induced by cardiac motion or diaphragmatic movements) can effectively be reduced, thus significantly improving the image quality of dark-field chest radiographs.

Advances in multiscale image processing and its effects on image quality in skeletal radiography

Multi-frequency processing (MFP) leads to enhanced image quality (IQ) of radiographs. This study is to determine the effect of third generation MFP (M3) on IQ in comparison to standard second-generation MFP (M2). 20 cadavers were examined and post-processing of radiographs was performed with both M2 and M3. Three readers blinded to the MFP used for each image independently compared corresponding image pairs according to overall IQ and depiction of bony structures and soft tissue (+ 2: notably better > 0: equal > − 2: notably worse). A significant deviation of the median grade from grade 0 (equal) (p < 0.01) for each evaluator A, B and C speaks against an equal image quality of M2- and M3-images. M3-images were categorized with better grades (+ 1, + 2) in 87.7% for overall image quality, in 90.4% for soft tissue and 81.8% for bony structures. M3 images showed significant higher averaged SNR and CNR for all investigated lower extremities than that of M2 images (0.031 < p < 0.049). The newest generation of MFP leads to significantly better depiction of anatomical structures and overall image quality than in images processed with the preceding generation of MFP. This provides increased diagnostic accuracy and further decreased radiation exposure.

Evaluation of MR-derived simulated CT-like images and simulated radiographs compared to conventional radiography in patients with shoulder pain: a proof-of-concept study

BackgroundTo evaluate the diagnostic value of MR-derived CT-like images and simulated radiographs compared with conventional radiographs in patients with suspected shoulder pathology.Methods3 T MRI of the shoulder including a 3D T1-weighted gradient echo sequence was performed in 25 patients (mean age 52.4 ± 18 years, 13 women) with suspected shoulder pathology. Subsequently a cone-beam forward projection algorithm was used to obtain intensity-inverted CT-like images and simulated radiographs. Two radiologists evaluated the simulated images separately and independently using the conventional radiographs as the standard of reference, including measurements of the image quality, acromiohumeral distance, critical shoulder angle, degenerative joint changes and the acromial type. Additionally, the CT-like MR images were evaluated for glenoid defects, subcortical cysts and calcifications. Agreement between the MR-derived simulated radiographs and conventional radiographs was calculated using Cohen’s Kappa.ResultsMeasurements on simulated radiographs and conventional radiographs overall showed a substantial to almost perfect inter- and intra-rater agreement (κ = 0.69–1.00 and κ = 0.65–0.85, respectively). Image quality of the simulated radiographs was rated good to excellent (1.6 ± 0.7 and 1.8 ± 0.6, respectively) by the radiologists. A substantial agreement was found regarding diagnostically relevant features, assessed on Y- and anteroposterior projections (κ = 0.84 and κ = 0.69 for the measurement of the CSA; κ = 0.95 and κ = 0.60 for the measurement of the AHD; κ = 0.77 and κ = 0.77 for grading of the Samilson-Prieto classification; κ = 0.83 and κ = 0.67 for the grading of the Bigliani classification, respectively).ConclusionIn this proof-of-concept study, clinically relevant features of the shoulder joint were assessed reliably using MR-derived CT-like images and simulated radiographs with an image quality equivalent to conventional radiographs. MR-derived CT-like images and simulated radiographs may provide useful diagnostic information while reducing the amount of radiation exposure.

THE EFFECT OF EXPOSURE FACTORS ON RADIOGRAPHIC IMAGE QUALITY ON THORAX PHANTOM WITH PA PROJECTION

The posteroanterior projection (PA) chest radiograph is the most frequently performed radiological examination for various purposes of diagnosis. Radiographic examination of the anatomy of the body can provide as much information as possible which can be determined by the Radiologist, which requires good quality radiographic images. To be able to produce radiographs that provide as much information as possible, optimal radiographs are needed. In the radiographic examination, factors that can affect the quality of the photo are needed in order to get good results. These factors include the exposure factor. Exposure factor consists of mains voltage (kV), tube current (mA) and time (s).&#x0D; The objectives to be achieved in this study were to determine the effect of exposure factors on the quality of radiographic images on the use of phantom thorax with PA assessment. The method used in experimental research. This research was conducted at the Laboratory of the Diploma III X-Ray Engineering Study Program, Widya Husada University, Semarang. In several variations of exposure factors, there is no difference in quality both in terms of sharpness and sharpness. The resulting image from each variation is good and informative. So it can be useful that the use of exposure factors is chosen as minimal so that the exposure or dose received is smaller. Image quality analysis should be made with a wider variety of kV and mAs, and using phantom objects other than phantom thorax.

Evaluation of Radiation Dose Reduction and its Effect on Image Quality for Different Flat-Panel Detectors.

Purpose:To evaluate the image quality of semi-anatomical chest radiographs acquired using low radiation doses from seven different flat-panel detector (FPD) systems.Materials and Methods:Radiographs of a semi-anatomical chest phantom were acquired at 70 and 110 kVp using 7 different FPDs from 5 vendors. Radiation doses were measured using a dose-area-product (DAP) meter. To standardize measurements across all FPDs, DAP value of 51.05 μGym2 obtained at 70 kVp and 9.43 μGym2 at 110 kVp was used as reference in this study. Radiation doses were reduced by manually adjusting mAs for both tube potentials in all FPD systems to achieve acceptable image quality. Contrast-to-noise ratio, signal-to-noise ratio and figure of merit (FOM) in lung, heart, and diaphragm for all images were analyzed.Results:In comparison with set standard protocol, radiation dose reduction of 20%, 21%, 21.6%, 59.5%, 60.7%, 62.2%, and 67.6% with optimal image quality was observed in Prognosys Prorad, GE Definium 8000, Siemens Fusion, Fujifilm FGX, Fujifilm FGXR, Philips Digital Diagnost and Siemens Aristos at 70 kVp. At 110 kVp, dose reduction of 15.7% and 34.8% was possible only for Philips Digital Diagnost and Siemens Aristos. FOM was high at 110 kVp even when radiation doses were reduced by a factor 2 when compared to 70 kVp in all digital radiography systems.Conclusion:This study demonstrates the feasibility of using a semi-anatomical chest phantom in the optimization of radiation dose and image quality. The FOM was a good indicator in assessing image quality between different detectors.

A MOSFET-Based Method for Measuring Peak Kilovoltage (kVp) in Diagnostic X-Ray Beams

Peak kilovoltage (kVp) is an X-ray tube parameter that can influence the radiograph image quality and therefore, if the kVp is different from the nominal value, it can provide an unnecessary radiation dose to the patient if the examination has to be repeated. Therefore, some radiation protection institutions and health organizations (ICRP, IAEA) make recommendations to monitor kVp in medical diagnostic X-ray equipment in clinics and hospitals. There are some methods for measuring kVp in diagnostic X-ray beams, and the most common is the well-known two-sensor method, which uses two filters to attenuate the radiation beam, and it is based on the measurement of each identical sensor. The purpose of this article is to present a method for non-invasive measurement of kVp in medical diagnostic X-ray beams using the MOSFET device. Actually, MOSFET is well known as a detector for ionizing radiation dosimetry mainly in radiotherapy beams. Recently, MOSFET has also been used as dosimeter in diagnostic X-ray beams. In this work it will be shown a kVp measurement technique with MOSFET, which does not use the attenuation factor of the radiation filters, but instead takes advantage of the effect of the device package itself, known as the buildup cap effect. The results show that even with damage to the device exposed to radiation, MOSFET can be used as sensor for kVp measurement.

Infracranial radiographic comparison for human identification: A study of image quality and tissue shielding effects.

In this study, we explore how image resolution and tissue shielding can impact correct classification rates (CCRs) of infracranial radiographic comparisons undertaken using small field-of-view radiographs. Thirty-six identification arrays (using clavicles and seventh cervical vertebra) were constructed with each array comprised of five radiographs: one X-ray of a single dry bone (postmortem [PM] skeletal image) and four simulated antemortem [AM] radiographs (radiographs taken pre-skeletization). One AM radiograph in each array represented the ground truth match to the PM radiograph (=25% rate of randomly selecting the correct match). Radiographs were digitally manipulated, so that four varieties of decreasing blur (Gaussian blur=12-0 pr across 24 arrays), and, for PM clavicles, four varieties of decreasing hard tissue shielding (opacity of 40-0% across 12 arrays) existed. Arrays were evaluated, for their correct PM/AM pair, by 8 anthropologists trained in chest radiograph comparison (CXR; either currently or formerly competency certified by the Defense POW/MIA Accounting Agency CXR training program), 28 current American Board of Forensic Anthropology (ABFA) diplomates and 30 novices. Analysts' CCRs substantially improved when Gaussian blur was <10 pr (55% CCR at >10 pr vs. 89% for <10 pr). Tissue shielding effects increased CCRs on average by +10% for each -10% opacity step (between 40-0% opacity). The CXR anthropologists were the most tolerant of the more challenging identification contexts (highest blur and opacity), reconfirming that analyst training and expertise is an important factor, especially when poorer quality radiographic images are the subject of analysis.

A comparative study of promising filter materials for neutron imaging facilities

The effect of sapphire and bismuth single-crystal filters and their combinations on the quality of neutron radiographic images and neutron tomography data has been studied. The parameters of the contrast of the neutron image were analyzed depending on the monocrystalline filters. Neutron transmission spectra were obtained for sapphire and bismuth single crystals. Additionally, the effect of filters on the overall intensity of the thermal neutron beam and the background of gamma-rays was investigated. Based on the obtained data, we assume that a single-crystal sapphire filter can be most effectively used for radiographic and tomographic installations using thermal neutrons.

OPTIMIZACIJA POSEGOV V RADIOLOŠKI TEHNOLOGIJI – SLIKANJE LEDVENE HRBTENICE V SPLOŠNI RADIOLOGIJI

Purpose: Any use of ionizing radiation must be justifi ed and the benefi t must be greater than the harm it causes. Imaging must be performed with the lowest possible dose received by the patient, while maintaining optimal radiographic image quality. Imaging of the lumbar spine is a relatively high dose imaging procedure. This systematic review aims to explore optimisation options to reduce patient exposure, while maintaining radiographic quality during plain lumbar spine imaging. Methods: A systematic review of the literature from the databases Pub Med Central, EBSCOhost including CINAHL, Cochrane Library, Web of Science, Science Direct, DiKUL and Springer Link was conducted. The documents were fully accessible and in the English language. Results: 26 experimental studies were included in the analysis. There are many optimisation methods: changing the tube potential, comparison of diff erent projections, use of shielding, primary beam collimation, increasing the source-to-image receptor distance, compression of the imaged area, using the air gap technique, evaluation of the need for additional projections, and rotating the patient depending on the tube side. On average, the dose is reduced by 44%. Studies that also evaluated the quality of radiographs found all radiographs to be diagnostically acceptable. Conclusion: The results confi rm a reasonable use of methods to optimize radiation exposure and to maintain an optimal image quality of radiographs. A systematic review for each specifi c area in general radiography should be conducted in the future. Keywords: lumbar spine imaging, optimisation, dose reduction, low dose, image quality

RAD_IQ: A free software for characterization of digital X-ray imaging devices based on the novel IEC 62220-1-1:2015 International Standard

Characterization of digital X-ray imaging devices is very important because it can be used to measure and compare the performance of detectors used in Diagnostic Radiology. This characterization is usually made through the calculation of Modulation Transfer Function (MTF), Noise Power Spectrum (NPS) and Detective Quantum Efficiency (DQE). These parameters, especially the DQE, are very important because they quantify the effect of spatial resolution, contrast and noise on Radiographic image quality (IQ). The IEC 62220-1-1:2015 International Standard provides comprehensive guidelines how to capture and analyze X-ray images to characterize digital X-ray detectors. A novel, fast and free MATLAB-based software was developed, named RAD_IQ, to calculate the Signal Transfer Property (STP), perform Noise Component Analysis (NCA), and calculate the parameters MTF, NPS & DQE of X-ray detectors based on the novel IEC 62220-1-1:2015 International Standard for General Radiography and IEC 62220-1-1:2007 for Digital Mammography. Our results were validated against well-established software products used for quantitative image analysis of digital X-ray detectors. The calculated parameters were within 5% difference compared to available software products. The conclusion of our study was that RAD_IQ can be easily used from Medical Physicists, Biomedical Engineers and researchers without any programming experience to characterize the performance of digital X-ray detectors used in Diagnostic Radiology.

Investigation of patch-based modulation transfer function (MTF) prediction framework in radiography

The modulation transfer function (MTF) is a well-established in imaging systems and has played a significant role in assessing the performance of information transfer in accordance with the spatial frequency. Exist methods for measuring MTF require a pinhole, or a slit camera, an edge phantom, etc. These depend on the imaging system and exposure conditions. To overcome these problems, we investigated the proposed patch-based MTF prediction framework using a deep-learning algorithm in radiography. This proposed method directly allows for the predicted MTF from a single image without the need for additional devices and work. We used 800 to 1500 projections for supervised learning and selected many patches, including the edge information from input image for predicting the MTF, for which we used the Kendall's rank correlation. The quantitative evaluation performed included an intensity profile and a root-mean square error. In addition, we implemented the nonblind deblurring process to verify its image performance using the predicted MTF. Our methods successfully predicted the MTF and restored them from the degraded image without such artifacts as the ringing artifact that can occur when using the incorrect blur kernel. Consequently, the simulation and experimental results indicate that the proposed framework is useful to predicting the accurate MTF and is effective in improving radiographic image quality.

Investigating particle track topology for range telescopes in particle radiography using convolutional neural networks

Background Proton computed tomography (pCT) and radiography (pRad) are proposed modalities for improved treatment plan accuracy and in situ treatment validation in proton therapy. The pCT system of the Bergen pCT collaboration is able to handle very high particle intensities by means of track reconstruction. However, incorrectly reconstructed and secondary tracks degrade the image quality. We have investigated whether a convolutional neural network (CNN)-based filter is able to improve the image quality. Material and methods The CNN was trained by simulation and reconstruction of tens of millions of proton and helium tracks. The CNN filter was then compared to simple energy loss threshold methods using the Area Under the Receiver Operating Characteristics curve (AUROC), and by comparing the image quality and Water Equivalent Path Length (WEPL) error of proton and helium radiographs filtered with the same methods. Results The CNN method led to a considerable improvement of the AUROC, from 74.3% to 97.5% with protons and from 94.2% to 99.5% with helium. The CNN filtering reduced the WEPL error in the helium radiograph from 1.03 mm to 0.93 mm while no improvement was seen in the CNN filtered pRads. Conclusion The CNN improved the filtering of proton and helium tracks. Only in the helium radiograph did this lead to improved image quality.

Innovation of Dental X-Ray Holder Using Silicone Rubber Coating in Posterior Dental Periapical Intraoral Examination

The major drawback of the parallel periapical examination technique is that the holder used can damage the oral tissues and cause discomfort to the patient. The objective of this study is to determine the work efficiency and radiographic quality of the innovative dental x-ray holder which has been made by adding synthetic rubber or silicone to the part of the holder that is in direct contact with the patient. This research is an experimental with a post-test only design. The analysis was performed based on filling out the questionnaire on a Likert scale ranging from 1 to 4. With the criteria 1. Disagree, 2. Sometimes, 3. Agree and 4. Strongly Agree. The test was administered by comparing the holder made with the commonly used Aphrodite holder as a control group. There were 16 repetitions of exposure to the cadaveric skull in obtaining research data for each treatment group. The results of statistical work efficiency testing on the control group resulted in a value of B = 0.125 with a significance of 0.071 and an effect of 10.5%. Meanwhile, for testing the quality of radiographic image, the value of B = 0.125 with a significance of 0.014 and an effect of 18.5% was obtained. The innovative dental x-ray holder using a silicone rubber layer is efficient and the resulting radiographic image quality is good when used in the intraoral examination.

التشخيص المبكر لمرض فيروس كورونا (كوفيد-19) عن طريق الأشعة المقطعية

فيروس كورونا هو فيروس يصيب الجهاز التنفسي ويؤدي إلى الالتهاب الرئوي والفشل الكلوي ومشكلات صحية أخرى، هدفت هذه الدراسة إلى أن يكون التشخيص المبكر لفيروس كورونا في أسرع وقت للحفاظ على الخلايا السليمة للمرضى. تم فحص المرضى المصابين بفيروس كورونا الذين تراوحت أعمارهم بين (85-25) عامًا عن طريق الأشعة المقطعية والتحليل المختبري (PCR) والأشعة السينية والتصوير المقطعي بالإصدار البوزيتروني/ التصوير المقطعي المحوسب. يعتبر تشخيص فيروس كورونا بالأشعة المقطعية هي الطريقة الأكثر وضوحًا للتشخيص المبكر لفيروس كورونا؛ نظرًا لإنتاج جودة صورة إشعاعية واضحة وعالية الدقة وثلاثية الأبعاد لصدر المريض في عرضين (عرض أمامي- خلفي anterior-posterior view وعرض جانبي lateral view). بالإضافة إلى ذلك، فإن الأشعة المقطعية تكون أسهل وأرخص ومتوفرة أكثر في المستشفى، كما أنها تستغرق وقتًا أقل لفحص صدر المريض.

European guidelines on radiographic image quality in chiropractic practice \u2013 proposal of a cross-sectional graded classification reporting principle

BackgroundThe Commission of the European Communities (CEC) has published: European Guidelines on Quality Criteria for Diagnostic Radiographic Images. These guidelines are considered a gold standard, recommended for use in quality assurance protocols.The objectives of this study: 1) Propose a graded classification format for Danish chiropractic clinics according to the CEC-quality criteria for diagnostic radiographic images of the lumbar spine. 2) Propose a reporting principle for quality of radiographic images. 3) Document variation in radiation exposure among clinics.MethodsThis is a cross-sectional study of image quality based on random sampling from 148 chiropractic clinics. Clinics were included if using: 1) Digital radiography and 2) The chiropractic picture and archiving system (KirPACS) at the Nordic Institute of Chiropractic and Clinical Biomechanics (NIKKB) in Denmark. A sample of 296 lumbar spine series were randomly collected from KirPACS (January 2018). Two independent observers reviewed 50 lumbar spine series twice with a 4-week interval, testing intra- and inter-observer reproducibility. The same observers then reviewed the remaining 246 radiographic studies. All studies were evaluated using the CEC Quality Criteria. Patient radiation dose values were retrieved from KirPACS (First quarter of 2020).ResultsA reporting and classification principle of diagnostic image quality was used in 148 chiropractic clinics. Compliance with the 22 CEC Quality Criteria had proportions ranging from 0.72–0.96 for 18 criteria, while 4 criteria specifying detail and definition ranged between 0.20–0.66. The proposed rating system (A to E) revealed: 18 A clinics, 28 B clinics, 32 C clinics, 25 D clinics and 45 E clinics (A = highest quality; E = lowest quality). The patient radiation reference dose in Denmark is 7 mGy for the AP/PA lumbar spine. Very few clinics exceed the reference dose value, approximately 50% of clinics were below 5 mGy.ConclusionA reporting principle is proposed for a graded classification format based on the CEC-quality criteria for diagnostic radiographic images of the lumbar spine. The Quality Criteria are for the most part met satisfactorily in 148 Danish chiropractic clinics, but important image details are compromised, in most cases, because of low patient radiation doses. The results of a patient radiation dose survey enabled documentation of variation in radiation exposure among chiropractic clinics.

Radiologia de tecnologia digital aplicada à pintura: avaliação da qualidade de imagens obtidas em sistemas clínicos de radiologia

Introduction: The area’s studies have a great relevance in artwork. Laboratories committed to this purpose are scarce and employ professionals without specific knowledge in handling of ionizing radiation. It is not known to what extent, in Portugal, clinical radiological centers could provide added value to technology of digital radiography applied to painting, in order to expand their business areas and the performance of radiographers, thus enhancing synergies between these two areas. Goals: It was intended to analyse a possible applicability, to painting, of the Digital Radiology systems (CR and DR), used in the clinic settings, through the evaluation of the variable “radiographic image quality”, since the systems Clinical radiological tests, with indirect or direct conversion detectors of different energies and photodetectors of the electrical signal, show significant improvements in imaging patterns. Material and Methods: 21 radiographs were obtained from exposures made over three paintings in three different radiological systems with an emphasis on exposure parameters (potential difference (kV) and current intensity (mAs)). The sample was directed to works that presented different techniques, materials and compositions and selected by a museologist. The quality of the radiographs, operationalized by the analysis’s dimensions used in the evaluation of artworks: preservation of the support; distinction of details; contrast; contour definition; creative and technical process and components / materials. Four observers (2 specialists in medical image and 2 in art), under conditions of independence, evaluated the radiographs acquired according to a 4-point Likert scale. The analysis dimensions were organized into 11 criteria and the conditions for structured observation of the radiographs were standardized for display on a 15.6 ”GeChic 1503H monitor. Results: The most graded images were obtained with the Computerized Radiography (CR) system (mode: 3) given that this technology, in the opinion of the observers, provided a better view of the analysis criteria previously defined. The results were presented using descriptive statistics and discrete categorical variables, grouped into modal classes. Conclusions: Clinical digital radiography, especially Computed Radiography (CR), applied to painting, showed considerable dimensions of image quality and its use can contribute to the conservation, restoration, validation, analytical study, dating and authentication of artworks.