Current state of practice regarding digital radiography exposure indicators and deviation indices: Report of AAPM Imaging Physics Committee Task Group 232

Comparison of organ dose from chest radiography with varying beam quality and constant exposure index

The optimum X-ray tube voltage for chest radiographic examinations remains unclear; hence, the tube voltage varies between medical facilities. An exposure index (EI) was proposed to standardize the parameters for radiographic examinations. However, even if identical EI values are used to examine the same person, organ doses may vary due to differences in tube voltages. In this study, the variation in organ doses between different beam qualities under identical EI values for chest radiographic examinations was investigated using Monte Carlo simulations. A focused anti-scatter grid as well as standard and larger physique-type medical internal radiation dose (MIRD) phantoms were studied under tube voltages of 90, 100, 110, and 120 kVp. The organ doses in the MIRD phantom increased as the X-ray tube voltage decreased, even with identical EI values. The absorbed doses in the lungs of standard and large-sized MIRD phantoms at 90 kVp were 23% and 35% higher than those at 120 kVp, respectively. The doses to organs other than the lung at 90 kVp were also higher than those at 120 kVp. From the perspective of reducing radiation doses, a tube voltage of 120 kVp is considered better for chest examinations compared with a tube voltage of 90 kVp under identical EI values.

An Overview of Factors Affecting Exposure Level in Digital Detector Systems and their Relevance in Constructing Exposure Tables in Equine Digital Radiography

The aim of this review is to describe the steps of constructing exposure tables for use of digital detector systems (DRx) in equine practice. Introductory, selected underlying technical aspects of digital radiography are illustrated. Unlike screen-film radiography (SFR), DRx have a uniform signal response of the detector over a large dose range. This enables generation of diagnostic images from exposures that were previously nondiagnostic on SFR, thus reducing retakes. However, with decreasing detector entrance dose, image noise increasingly hampers the image quality. Conversely, unlike the blackening observed on SFR, overexposures can go visibly undetected by the observer. In DRx the numeric exposure indicator value is the only dose-control tool. In digital radiography the challenge is to reduce the dose and reduce the radiation risk to staff whilst maintaining diagnostic image quality. We provide a stepwise method of developing exposure tables as tools for controlling exposure levels. The identified kVp - mAs combinations in the table are derived from the predefined exposure indicator values of the detector system. Further recommendations are given as to how the exposure indicator can be integrated into routine workflow for rechecking the reliability of the formerly identified settings and how these tables might serve a basis for further reduction of the exposure level. Detector quantum efficiency (DQE) is an important parameter of assessing performance of an imaging system. Detectors with higher DQE can generate diagnostic images with a lower dose, thus having a greater potential for dose reduction than detectors with low DQE.

Method of determining technique from weight and height to achieve targeted detector exposures in portable chest and abdominal digital radiography

This study presents a methodology to develop an X-ray technique chart for portable chest and abdomen imaging which utilizes patient data available in the modality worklist (MWL) to reliably achieve a predetermined exposure index (EI) at the detector for any patient size. The method assumes a correlation between the patients' tissue equivalent thickness and the square root of the ratio of the patient's weight to height. To assess variability in detector exposures, the EI statistics for 75 chest examinations and 99 abdominal portable X-ray images acquired with the new technique chart were compared to those from a single portable unit (chest: 3877 images; abdomen: 200 images) using a conventional technique chart with three patient sizes, and to a stationary radiography room utilizing automatic exposure control (AEC) (chest: 360 images; abdomen: 112 images). The results showed that when using the new technique chart on a group of portable units, the variability in EI was significantly reduced (p < 0.01) for both AP chest and AP abdomen images compared to the single portable using a standard technique chart with three patient sizes. The variability in EI for the images acquired with the new chart was comparable to the stationary X-ray room with an AEC system (p > 0.05). This method could be used to streamline the entire imaging chain by automatically selecting an X-ray technique based on patient demographic information contained in the MWL to provide higher quality examinations to clinicians by eliminating outliers. In addition, patient height and weight can be used to estimate the patients' tissue equivalent thickness.

Understanding radiographic decision-making when imaging obese patients: A Think-Aloud study

Introduction

The incidence of obesity has been steadily rising over the last few decades and is having a significant impact upon the health system. In radiography, a particular challenge of imaging obese patients is implementing the as low as reasonably achievable (ALARA) principle when determining radiation dose, and technical and patient‐care adaptations. This study aimed to better understand the decision‐making strategies of experienced radiographers in determining imaging and exposure factor selection in the context of imaging obese patients.

Methods

This study employed a ‘think‐aloud,’ methodology, and eight experienced diagnostic radiographers working in clinical education were recruited to perform routine AP abdominal X‐ray projections on an anthropomorphic phantom. They were asked to simultaneously verbalise emerging thoughts as they considered positioning, exposure selection and image evaluation. This process was repeated with three different phantom sizes, each representing an increased BMI from ‘healthy,’ to, ‘morbidly obese.’ Audio recordings were transcribed and interpreted via Bowman’s (1997) theory of radiographic judgement and decision‐making.

Results

Analysis of interview transcripts identified 12 key concepts considered by experienced radiographers. Differences in radiographic concepts were considered when imaging phantoms of different sizes was demonstrated. A shift from segmental (e.g. positioning) to more environmental factors (e.g. patient comfort) and an increase in the number of verbal considerations with increasing phantom size were identified. The shift in focus of decision‐making stages identified the greater need to consider contextual factors such as patient comfort and repeatability when imaging obese patients.

Conclusion

Experienced radiographers find imaging obese patients challenging and alter their perception of image quality to accommodate for patient presentation. The findings will help inform future research, practice guidelines and learning resources to provide optimal imaging and care for obese patients, especially for student education.

Are the target exposure index and deviation index used efficiently?

INTRODUCTION

Exposure index (EI) is important to evaluate correct exposure in radiography and thus important for image quality. The purpose of this study was to evaluate whether the target exposure index (EI_T) and deviation index (DI) were used efficiently.

METHODS

Radiography departments in Iceland, using <10 years old equipment, were invited to participate. For each x-ray unit, admin users were asked about the use of EI_T and data was gathered on EI_T for five body parts (BP); lumbar spine, chest, hip, knee and hand. For each of the five BP, 100 examinations from the past year were selected randomly (or all, if < 100). The EI from one predefined view was recorded and the corresponding DI calculated.

RESULTS

A total of ten x-ray units, from four manufacturers and located at eight departments, were included in the study. The departments involved are comprised of a university hospital, smaller hospitals, and miscellaneous private departments. Two departments (25%) had not set EI_T, five (62.5%) used default values and only one had revised EI_T values. In four departments (50%) radiographers favored "acceptable EI range" over DI. The mean EI was significantly different (p < 0.05) from the EI_T in the majority of the five BP, in four out of the six departments that had defined EI_T. In total 30% of images from all departments combined had DI outside the range of -3.0 < DI < +3.0. The standard deviation of DI was from 1.4 to 2.7.

CONCLUSION

The study shows that the EI_T and DI are not used efficiently, regardless of equipment vendor or department characteristics.

IMPLICATIONS FOR PRACTICE

Current recommendations on targeting the mean DI of 0 need to be reinforced. Theoretical knowledge and training need to be improved.

Implementing a Novel Through-Glass Chest Radiography Technique for COVID-19 Patients: Image Quality, Radiation Dose Optimization, and Practical Considerations

RATIONALE AND OBJECTIVES

The novel coronavirus (COVID-19) pandemic has presented many logistical challenges, including unprecedented shortages of personal protective equipment (PPE). A technique of obtaining portable chest radiographs (pCXR) through glass doors or windows to minimize technologist-patient contact and conserve PPE has gained popularity, but remains incompletely evaluated in the literature. Our goal was to quickly implement this technique and evaluate image quality and radiation dose.

MATERIALS AND METHODS

An infographic and video were developed to educate nurses and technologists on the through-glass pCXR technique. Imaging parameters were optimized using a phantom and scatter radiation was measured. Three reviewers independently evaluated 100 conventionally obtained and 100 through-glass pCXRs from March 13, 2020 to April 30, 2020 on patients with suspected COVID-19, using criteria for positioning and sharpness/contrast on a 1 (confident criteria not met) to 5 (confident criteria met) scale. Imaging parameters, including deviation index (DI) were recorded for all radiographs.

RESULTS

The through-glass method was rapidly adopted and conserved one isolation gown per interaction. Although there was a statistically significant difference in the positioning (P value 0.018) and sharpness/contrast (P value 0.016), the difference in mean ratings was small: 4.82 vs 4.65 for positioning and 4.67 vs 4.50 (conventional vs modified) for sharpness/contrast. Scatter radiation was measured using a thorax phantom and found to be acceptable for the patient and nearby personnel. Standard deviation was higher for the DI for the through-glass technique (2.8) compared to the conventional technique (1.8), although the means were similar.

CONCLUSION

The through-glass technique was quickly implemented, producing diagnostic quality chest radiographs while conserving PPE and reducing risks to radiology staff. There was more variability with imaging technique and DI using the through-glass technique, likely due to technologist uncertainty regarding technical modifications. Further work to reduce this variation is necessary to optimize quality and dose.

Optimising default radiographic exposure factors using Deviation Index

INTRODUCTION

Radiographers have a duty to ensure that radiation doses to patients are as low as reasonably achievable. With digital technologies, exposure factors which achieve the optimum balance between image noise and patient dose must be sought. In digital radiography, Deviation Index (DI) values provide the radiographer with feedback on the appropriateness of individual exposures but can also be tracked as part of a departmental quality assurance programme.

METHODS

In November 2017, exposure logs were extracted from six digital radiography (DR) x-ray systems, collated and analysed. Five examinations were identified which frequently produced DI values outside the manufacturer's recommended Optimal Range (-3 to +2). Incremental improvements were made to the default exposure settings for these examinations via a cyclical process of modification and re-evaluation. A full data collection exercise was then repeated in April 2019.

RESULTS

At baseline, 10,658 out of 29,637 (36.0%) exposures had DI values outside the manufacturer's recommended Optimal Range, but for some individual examinations the proportion was as high as 547 out of 725 (74.5%). Following multiple optimisation cycles, the overall proportion of examinations outside the Optimal Range had fallen to 7611 out of 26,759 (28.4%). Default milliampere-seconds (mAs) values for these examinations were reduced by between 22% and 50%.

CONCLUSION

A marked reduction in patient doses can be achieved through a departmental programme of DI value monitoring and targeted optimisation of default exposure settings.

IMPLICATIONS FOR PRACTICE

DI values should be routinely monitored as part of routine quality assurance programmes. Radiographers have a responsibility to ensure that they possess a clear understanding of DI values and that appropriate exposure settings are selected for each individual patient.

Calculating the target exposure index using a deep convolutional neural network and a rule base

PURPOSE

The objective of this study is to determine the quality of chest X-ray images using a deep convolutional neural network (DCNN) and a rule base without performing any visual assessment. A method is proposed for determining the minimum diagnosable exposure index (EI) and the target exposure index (EIt).

METHODS

The proposed method involves transfer learning to assess the lung fields, mediastinum, and spine using GoogLeNet, which is a type of DCNN that has been trained using conventional images. Three detectors were created, and the image quality of local regions was rated. Subsequently, the results were used to determine the overall quality of chest X-ray images using a rule-based technique that was in turn based on expert assessment. The minimum EI required for diagnosis was calculated based on the distribution of the EI values, which were classified as either suitable or non-suitable and then used to ascertain the EIt.

RESULTS

The accuracy rate using the DCNN and the rule base was 81%. The minimum EI required for diagnosis was 230, and the EIt was 288.

CONCLUSION

The results indicated that the proposed method using the DCNN and the rule base could discriminate different image qualities without any visual assessment; moreover, it could determine both the minimum EI required for diagnosis and the EIt.

Estimates of Patient Radiation Doses in Digital Radiography Using DICOM Information at a Large Teaching Hospital in Oman

In this study, we sought to estimate the patient radiation doses in the digital radiography X-ray examinations conducted in a large hospital. The patient exposure factors and kerma-area product (PKA) were retrospectively recorded via the Digital Imaging and Communications in Medicine (DICOM) header for 547 patients. The entrance surface air kerma (ESAK) was estimated from the measurements of the X-ray tube output and recorded exposure factors, as well as from the console that displayed PKA as an alternative method. Effective doses were estimated from ESAK and PKA values using the appropriate conversion coefficient. In the chest PA, chest LAT, cervical spine AP, cervical spine LAT, abdomen AP, pelvis AP, lumbar spine AP, and lumbar spine LAT, the median ESAK (mGy) was found to be 0.13, 0.27, 0.35, 0.52, 0.70, 1.06, 2.33, and 4.18 mGy, respectively. Median PKA values were 0.10, 0.26, 0.14, 0.17, 0.77, 0.68, 0.81, and 1.11 Gy cm2, respectively. The estimated effective dose from ESAK and PKA values yielded comparable results. The comparison revealed that the ESAK and PKA values fell far below the reported in the literature. The results showed that the information of the DICOM deader is valuable for dosimetry and optimization.