The clinical significance of modifying X-ray tube current-time product based on prior image deviation index for digital radiography

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.

Diagnostic radiography students' experiences of a practical method demonstrating the effect of milliampere-second in digital X-ray imaging systems

BACKGROUND

The effect of exposure technique factors varies between analogue and digital X-ray imaging systems (DR). Understanding these variations is paramount to optimising radiation protection, yet radiographers are unclear about these effects. A practical method to demonstrate milliampere second (mAs) effect in DR was developed to assist diagnostic radiography students in understanding exposure technique factors in DR.

OBJECTIVES

To explore second-year diagnostic radiography students' experiences of a practical method to demonstrate the effect of mAs in DR.

METHODS

A qualitative research approach employing an open-ended questionnaire explored second-year diagnostic radiography students' experiences of the practical method demonstrating the effect of mAs in DR. Twenty students participated in the study, and the data collected underwent thematic analysis.

RESULTS

Students appreciated working in small groups and provided suggestions to improve the practical method's instruction sheet. Most students' predicted outcome differed from the actual outcome of the demonstration. Seeing and documenting the effect of mAs in DR not only enhanced students' understanding of it but showed the implications of increasing mAs on image quality and radiation exposure.

CONCLUSION

Students found that the practical method enhanced their understanding of mAs and exposure technique factors in DR. Additionally, the practical method highlighted exposure creep in DR and radiographers' role in protecting patients from overexposure to ionising radiation in the digital era.

Proper Management of the Clinical Exposure Index Based on Body Thickness Using Dose Optimization Tools in Digital Chest Radiography: A Phantom Study

In radiography, the exposure index (EI), as per the International Electrotechnical Commission standard, depends on the incident beam quality and exposure dose to the digital radiography system. Today automatic exposure control (AEC) systems are commonly employed to obtain the optimal image quality. An AEC system can maintain a constant incident exposure dose on the image receptor regardless of the patient thickness. In this study, we investigated the relationship between body thickness, entrance surface dose (ESD), EI, and the exposure indicator (S value) with the aim of using EI as the dose optimization tool in digital chest radiography (posterior-anterior and lateral projection). The exposure condition from the Korean national survey for determining diagnostic reference levels and two digital radiography systems (photostimulable phosphor plate and indirect flat panel detector) were used. As a result, ESD increased as the phantom became thicker with constant exposure indicator, which indicates similar settings to an AEC system, but the EI indicated comparatively constant values without following the tendency of ESD. Therefore, body thickness should be considered under the AEC system for introducing EI as the dose optimization tool in digital chest radiography.

USE OF CLINICAL EXPOSURE INDEX AND DEVIATION INDEX BASED ON NATIONAL DIAGNOSTIC REFERENCE LEVEL AS DOSE-OPTIMIZATION TOOLS FOR GENERAL RADIOGRAPHY IN KOREA

The International Electrotechnical Commission introduced the concepts of exposure index (EI), target exposure index (EIT) and deviation index (DI) to manage and optimize patient dose in real time. In this study, we have proposed an appropriate method for setting the EIT based on the Korean national diagnostic reference levels (DRLs). Furthermore, we evaluated the use of clinical EI, EIT and DI as tools for patient dose optimization in clinical environments by observing the changes in DI with those in EIT. According to the Korean national exposure conditions, we conducted experiments on three representative radiographic examinations (chest posterior-anterior, lateral and abdomen anterior-posterior) of clinical environments. As the exposure conditions and DRLs varied, the clinical EI, EIT and DI also varied. These results reveal that the clinical EI, EIT and DI can be used as tools for optimizing the patient dose if EIT is periodically and properly updated.

Development of an application to visualise the spread of scattered radiation in radiography using augmented reality

As radiation is widely used in medical institutions, the lack of radiation protection education for health workers increases the risk of radiation exposure. The purpose of this study is to develop an application for radiation medical personnel that visualises the distribution of scattered radiation by using augmented reality (AR). The irradiation conditions for mobile chest and pelvic radiography were simulated using Monte Carlo simulations (Particle and Heavy Ion Transport code System). Monte Carlo results were verified using physical measurements. The behaviour of scattered radiation was displayed three-dimensionally in virtual reality using ParaView. Subsequently, an application to visualise scattered rays was developed in Unity for tablet devices. An application with a sense of reality was developed by visualising the scattered radiation distribution of a mobile imaging in a real space in AR in a three-dimensional size, which is close to the actual size. The radiation dose could be estimated at any position and the behaviour of scattered radiation became easier to understand.

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.