Artificial Intelligence for Radiation Dose Optimization in Pediatric Radiology: A Systematic Review

Radiation dose optimization is particularly important in pediatric radiology, as children are more susceptible to potential harmful effects of ionizing radiation. However, only one narrative review about artificial intelligence (AI) for dose optimization in pediatric computed tomography (CT) has been published yet. The purpose of this systematic review is to answer the question “What are the AI techniques and architectures introduced in pediatric radiology for dose optimization, their specific application areas, and performances?” Literature search with use of electronic databases was conducted on 3 June 2022. Sixteen articles that met selection criteria were included. The included studies showed deep convolutional neural network (CNN) was the most common AI technique and architecture used for dose optimization in pediatric radiology. All but three included studies evaluated AI performance in dose optimization of abdomen, chest, head, neck, and pelvis CT; CT angiography; and dual-energy CT through deep learning image reconstruction. Most studies demonstrated that AI could reduce radiation dose by 36–70% without losing diagnostic information. Despite the dominance of commercially available AI models based on deep CNN with promising outcomes, homegrown models could provide comparable performances. Future exploration of AI value for dose optimization in pediatric radiology is necessary due to small sample sizes and narrow scopes (only three modalities, CT, positron emission tomography/magnetic resonance imaging and mobile radiography, and not all examination types covered) of existing studies

Development of an Online Automatic Computed Radiography Dose Data Mining Program: A Preliminary Study

Recent studies have reported the computed radiography (CR) dose creep problem and therefore the need to have monitoring processes in place in clinical departments. The objective of this study is to provide a better technological solution to implement a regular CR dose monitoring process. An online automatic CR dose data mining program which can be applied to different systems was developed based on freeware and existing softwares in the Picture Archiving and Communication System (PACS) server. The program was tested with 69 CR images. This preliminary study shows that the program addresses the major weaknesses of some existing studies including involvement of manual procedures in the monitoring process and being only applicable to a single manufacturer's CR images. The proposed method provides an efficient and effective solution to implement a CR dose monitoring program regularly in busy clinical departments to regulate the dose creep problem so as to reinforce the As Low As Reasonably Achievable (ALARA) principle

Dual-source CT Angiography in Aortic Stent Grafting: An in vitro Aorta Phantom Study of Image Noise and Radiation Dose

Rationale and Objectives: The aim of the study was to investigate the optimal protocols of dual-source computed tomography (CT) angiographyin aortic stent grafting in terms of image noise and radiation dose, based on an in vitro phantom study. Materials and Methods: A series of helical CT cans were performed on a human aorta phantom using a dual-source CT scannerwith kVp of 100, 120, and 140, corresponding mAs of 180, 150, and 100; slice thickness of 1.0, 1.5, and 2.0 mm; and pitch value of 0.5, 1.0, and 1.5, respectively. Image quality was determined by measuring the standard deviation (SD) on three-dimensional virtual intravascular endoscopy (VIE) images. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured on two dimensional(2D) axial images at superior mesenteric artery (SMA), renal arteries, and aneurysm. Effective dose was determined based on dose-length product.Results: SD measured on VIE images was independent of kVp and pitch values but was determined by the slice thickness (P <.05) at the SMA and renal arteries. SNR and CNR measured on 2D images showed significant differences between variable kVp values and slice thicknesses (P <.05), but were independent of pitch values. The mean estimated effective dose for 120 kVp and 140 kVp protocols were 2.66 ± 0.21 mSv and 2.68 ± 0.18 mSv, respectively. The mean estimated effective dose for 100 kVp protocol was significantly lower (1.97 ± 0.07 mSv, P < .0001). This indicates a reduction of 26.5% radiation dose when the kVp was lowered from 140 to 100. Conclusion: A scanning protocol of 1.5-mm slice thickness, pitch 1.5 with 100 kVp, and 180 mAs is recommended for a dual-source CT angiography in aortic stent grafting as it leads to significant reduction of radiation dose while achieving diagnostic images

Artificial Intelligence (Enhanced Super-Resolution Generative Adversarial Network) for Calcium Deblooming in Coronary Computed Tomography Angiography: A Feasibility Study

Background: The presence of heavy calcification in the coronary artery always presents a challenge for coronary computed tomography angiography (CCTA) in assessing the degree of coronary stenosis due to blooming artifacts associated with calcified plaques. Our study purpose was to use an advanced artificial intelligence (enhanced super-resolution generative adversarial network [ESRGAN]) model to suppress the blooming artifact in CCTA and determine its effect on improving the diagnostic performance of CCTA in calcified plaques. Methods: A total of 184 calcified plaques from 50 patients who underwent both CCTA and invasive coronary angiography (ICA) were analysed with measurements of coronary lumen on the original CCTA, and three sets of ESRGAN-processed images including ESRGAN-high-resolution (ESRGAN-HR), ESRGAN-average and ESRGAN-median with ICA as the reference method for determining sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Results: ESRGAN-processed images improved the specificity and PPV at all three coronary arteries (LAD-left anterior descending, LCx-left circumflex and RCA-right coronary artery) compared to original CCTA with ESRGAN-median resulting in the highest values being 41.0% (95% confidence interval [CI]: 30%, 52.7%) and 26.9% (95% CI: 22.9%, 31.4%) at LAD; 41.7% (95% CI: 22.1%, 63.4%) and 36.4% (95% CI: 28.9%, 44.5%) at LCx; 55% (95% CI: 38.5%, 70.7%) and 47.1% (95% CI: 38.7%, 55.6%) at RCA; while corresponding values for original CCTA were 21.8% (95% CI: 13.2%, 32.6%) and 22.8% (95% CI: 20.8%, 24.9%); 12.5% (95% CI: 2.6%, 32.4%) and 27.6% (95% CI: 24.7%, 30.7%); 17.5% (95% CI: 7.3%, 32.8%) and 32.7% (95% CI: 29.6%, 35.9%) at LAD, LCx and RCA, respectively. There was no significant effect on sensitivity and NPV between the original CCTA and ESRGAN-processed images at all three coronary arteries. The area under the receiver operating characteristic curve was the highest with ESRGAN-median images at the RCA level with values being 0.76 (95% CI: 0.64, 0.89), 0.81 (95% CI: 0.69, 0.93), 0.82 (95% CI: 0.71, 0.94) and 0.86 (95% CI: 0.76, 0.96) corresponding to original CCTA and ESRGAN-HR, average and median images, respectively. Conclusions: This feasibility study shows the potential value of ESRGAN-processed images in improving the diagnostic value of CCTA for patients with calcified plaques

Workplace Violence in Medical Radiation Science: A Systematic Review

Introduction According to World Health Organization (WHO), workplace violence (WPV) is a significant issue in healthcare. However, no systematic review on WPV in medical radiation science (MRS) has been published yet. The purpose of this paper is to systematically review prevalence of WPV in MRS and its risk factors. Methods Electronic scholarly publication databases, namely EBSCOhost/Cumulative Index of Nursing and Allied Health Literature Ultimate, PubMed/Medline, ScienceDirect, Scopus, and Wiley Online Library were used for literature search to identify articles about WPV in MRS published over last 10 years as per preferred reporting items for systematic reviews and meta-analyses guidelines. To facilitate comparisons of the WPV prevalence and relative importance of individual risk factors across the included studies, their reported absolute figures of findings were used to synthesize respective percentages (if not stated). Results Twelve papers met the selection criteria and were included. This review shows that the WPV prevalence were 69.2–100 % (whole career) and 46.1–83.0 % (last 12 months) in diagnostic radiography, 63.0–84.0 % (whole career) in radiation therapy, 57.6 % in medical sonography (last 12 months), and 46.8 % (last 6 months) in nuclear medicine. The identified WPV risk factors included intoxicated patients, staff stress, feeling of inadequacy resulting in self-protection, more vulnerable practitioners (female, <40 years old and <5-year experience), working in radiation therapy treatment room, emergency department, examination room, general radiography, public hospital, and non-examination and waiting areas, long patient waiting time, night shift, overcrowding environment, unable to meet patients'/family members' expectations, miscommunication, patient handling, inadequate staff and security measures, interaction with colleagues, and lone working. Conclusion The WPV risk in diagnostic radiography and radiation therapy appears extremely high as a result of the aforementioned risk factors. Nevertheless, these study findings should be used with caution due to potential non-response bias. Implications for practice A WPV policy should be developed in every clinical workplace. Even if such policy is available, its enforcement including policy awareness boosting, and encouraging incident reporting and support seeking will be essential for reducing WPV. More survey studies based on WHO WPV questionnaire should be conducted for strengthening evidence base

Development of an Online Automatic Diagnostic Reference Levels Management System for Digital Radiography: A Pilot Experience

The diagnostic reference levels (DRLs) concept is a methodology proposed by the International Commission on Radiological Protection (ICRP) for identifying any unusual high patient doses involved in radiological examinations. However, some challenges are anticipated in the DRLs concept including resource demand for running the audit cycle by individual imaging departments and availability of DRLs. The objective of this study was to develop an online automatic DRLs management system for digital radiography (DR) with the aim of addressing the challenges of the DRLs obligation. An online automatic DRLs management system for DR composed of freeware was developed. The system was tested with 75 DR images. This pilot experience shows that the system successfully addresses the challenges in the DRLs management, i.e. resource demand for running the audit cycle by individual imaging departments and availability of DRLs. It can provide at a low cost an efficient and effective solution to the implementation of regular audits of patient doses using DR in busy clinical departments. It can also contribute to the development of DRLs at local and national levels. In this way, any unacceptable radiological practice (examination used unjustified high radiation dose) can be identified

Effects of Image Postprocessing in Digital Radiography to Detect Wooden, Soft Tissue Foreign Bodies

Purpose: To investigate the effects of image postprocessing functions (ie, edge enhancement, noise reduction, and sharpening) that are available on digital radiography systems, including computed radiography (CR) and direct digital radiography (DDR), for detection of wooden, soft tissue foreign bodies. Methods: Dorsoplantar and lateral porcine foot radiographs with 4 lengths of wooden foreign bodies (no foreign bodies, 2 mm, 5 mm, and 10 mm) placed 1 mm (superficial) and 1 cm (deep) below the skin were acquired by CR and DDR systems using 10 exposure factors. Images were postprocessed to produce 960 images, including original CR, original DDR, sharpened CR, sharpened DDR, edge-enhanced DDR, and noised-reduced DDR images. Contrast-to-noise ratios (CNR) were used for objective assessments of foreign body visibility on the images. Six Australian radiologic technologists were recruited to review selected images. Australia allows radiologic technologists to provide initial comments on plain radiographs with the supervision of a radiologist. Technologists rated the visibility of foreign bodies using a 4-point scale to determine diagnostic performances of different image receptor and postprocessing types. Means, standard deviations, analyses of variance, and intraclass correlation coefficients were calculated for statistical analyses. Results: Among the CR and DDR images with and without postprocessing, the edge-enhanced DDR images had the highest overall mean CNR value (3.39, P = .003) and sensitivity (35.13%). The sensitivity of the edge-enhanced DDR images for detecting the 10 mm foreign body was 43.33%. Discussion: Edge-enhanced DDR can be considered an additional tool for suspected wooden, soft tissue foreign body diagnoses in rural areas where digital radiography is the only available imaging modality. This would allow some patients in rural areas to avoid long-distance travel to access sonography or computed tomography to detect foreign bodies, which could minimize emotional, financial, and social costs. Conclusion: This study shows that the image postprocessing function of the DDR system can detect wooden, soft tissue foreign bodies. Edge enhancement, specifically, can improve wooden, soft tissue foreign body detection, especially for large foreign bodies (≥ 10 mm)