Dose and perceived image quality in chest radiography

Acquisition parameters influence AI recognition of race in chest x-rays and mitigating these factors reduces underdiagnosis bias

A core motivation for the use of artificial intelligence (AI) in medicine is to reduce existing healthcare disparities. Yet, recent studies have demonstrated two distinct findings: (1) AI models can show performance biases in underserved populations, and (2) these same models can be directly trained to recognize patient demographics, such as predicting self-reported race from medical images alone. Here, we investigate how these findings may be related, with an end goal of reducing a previously identified underdiagnosis bias. Using two popular chest x-ray datasets, we first demonstrate that technical parameters related to image acquisition and processing influence AI models trained to predict patient race, where these results partly reflect underlying biases in the original clinical datasets. We then find that mitigating the observed differences through a demographics-independent calibration strategy reduces the previously identified bias. While many factors likely contribute to AI bias and demographics prediction, these results highlight the importance of carefully considering data acquisition and processing parameters in AI development and healthcare equity more broadly.

Automated Quality Control Solution for Radiographic Imaging of Lung Diseases

Background/Objectives: Radiography is an essential and low-cost diagnostic method in pulmonary medicine that is used for the early detection and monitoring of lung diseases. An adequate and consistent image quality (IQ) is crucial to ensure accurate diagnosis and effective patient management. This pilot study evaluates the feasibility and effectiveness of the International Atomic Energy Agency (IAEA)'s remote and automated quality control (QC) methodology, which has been tested in multiple imaging centers. Methods: The data, collected between April and December 2022, included 47 longitudinal data sets from 22 digital radiographic units. Participants submitted metadata on the radiography setup, exposure parameters, and imaging modes. The database comprised 968 exposures, each representing multiple image quality parameters and metadata of image acquisition parameters. Python scripts were developed to collate, analyze, and visualize image quality data. Results: The pilot survey identified several critical issues affecting the future implementation of the IAEA method, as follows: (1) difficulty in accessing raw images due to manufacturer restrictions, (2) variability in IQ parameters even among identical X-ray systems and image acquisitions, (3) inconsistencies in phantom construction affecting IQ values, (4) vendor-dependent DICOM tag reporting, and (5) large variability in SNR values compared to other IQ metrics, making SNR less reliable for image quality assessment. Conclusions: Cross-comparisons among radiography systems must be taken with cautious because of the dependence on phantom construction and acquisition mode variations. Awareness of these factors will generate reliable and standardized quality control programs, which are crucial for accurate and fair evaluations, especially in high-frequency chest imaging.

Optimization of Fast Non-Local Means Noise Reduction Algorithm Parameter in Computed Tomographic Phantom Images Using 3D Printing Technology

Noise in computed tomography (CT) is inevitably generated, which lowers the accuracy of disease diagnosis. The non-local means approach, a software technique for reducing noise, is widely used in medical imaging. In this study, we propose a noise reduction algorithm based on fast non-local means (FNLMs) and apply it to CT images of a phantom created using 3D printing technology. The self-produced phantom was manufactured using filaments with similar density to human brain tissues. To quantitatively evaluate image quality, the contrast-to-noise ratio (CNR), coefficient of variation (COV), and normalized noise power spectrum (NNPS) were calculated. The results demonstrate that the optimized smoothing factors of FNLMs are 0.08, 0.16, 0.22, 0.25, and 0.32 at 0.001, 0.005, 0.01, 0.05, and 0.1 of noise intensities, respectively. In addition, we compared the optimized FNLMs with noisy, local filters and total variation algorithms. As a result, FNLMs showed superior performance compared to various denoising techniques. Particularly, comparing the optimized FNLMs to the noisy images, the CNR improved by 6.53 to 16.34 times, COV improved by 6.55 to 18.28 times, and the NNPS improved by 10-2 mm2 on average. In conclusion, our approach shows significant potential in enhancing CT image quality with anthropomorphic phantoms, thus addressing the noise issue and improving diagnostic accuracy.

Artificial Intelligence Applied to Chest X-ray: A Reliable Tool to Assess the Differential Diagnosis of Lung Pneumonia in the Emergency Department

BACKGROUND

Considering the large number of patients with pulmonary symptoms admitted to the emergency department daily, it is essential to diagnose them correctly. It is necessary to quickly solve the differential diagnosis between COVID-19 and typical bacterial pneumonia to address them with the best management possible. In this setting, an artificial intelligence (AI) system can help radiologists detect pneumonia more quickly.

METHODS

We aimed to test the diagnostic performance of an AI system in detecting COVID-19 pneumonia and typical bacterial pneumonia in patients who underwent a chest X-ray (CXR) and were admitted to the emergency department. The final dataset was composed of three sub-datasets: the first included all patients positive for COVID-19 pneumonia (n = 1140, namely "COVID-19+"), the second one included all patients with typical bacterial pneumonia (n = 500, "pneumonia+"), and the third one was composed of healthy subjects (n = 1000). Two radiologists were blinded to demographic, clinical, and laboratory data. The developed AI system was used to evaluate all CXRs randomly and was asked to classify them into three classes. Cohen's κ was used for interrater reliability analysis. The AI system's diagnostic accuracy was evaluated using a confusion matrix, and 95%CIs were reported as appropriate.

RESULTS

The interrater reliability analysis between the most experienced radiologist and the AI system reported an almost perfect agreement for COVID-19+ (κ = 0.822) and pneumonia+ (κ = 0.913). We found 96% sensitivity (95% CIs = 94.9-96.9) and 79.8% specificity (76.4-82.9) for the radiologist and 94.7% sensitivity (93.4-95.8) and 80.2% specificity (76.9-83.2) for the AI system in the detection of COVID-19+. Moreover, we found 97.9% sensitivity (98-99.3) and 88% specificity (83.5-91.7) for the radiologist and 97.5% sensitivity (96.5-98.3) and 83.9% specificity (79-87.9) for the AI system in the detection of pneumonia+ patients. Finally, the AI system reached an accuracy of 93.8%, with a misclassification rate of 6.2% and weighted-F1 of 93.8% in detecting COVID+, pneumonia+, and healthy subjects.

CONCLUSIONS

The AI system demonstrated excellent diagnostic performance in identifying COVID-19 and typical bacterial pneumonia in CXRs acquired in the emergency setting.

Effect of Contrast Level and Image Format on a Deep Learning Algorithm for the Detection of Pneumothorax with Chest Radiography

Under the black-box nature in the deep learning model, it is uncertain how the change in contrast level and format affects the performance. We aimed to investigate the effect of contrast level and image format on the effectiveness of deep learning for diagnosing pneumothorax on chest radiographs. We collected 3316 images (1016 pneumothorax and 2300 normal images), and all images were set to the standard contrast level (100%) and stored in the Digital Imaging and Communication in Medicine and Joint Photographic Experts Group (JPEG) formats. Data were randomly separated into 80% of training and 20% of test sets, and the contrast of images in the test set was changed to 5 levels (50%, 75%, 100%, 125%, and 150%). We trained the model to detect pneumothorax using ResNet-50 with 100% level images and tested with 5-level images in the two formats. While comparing the overall performance between each contrast level in the two formats, the area under the receiver-operating characteristic curve (AUC) was significantly different (all p < 0.001) except between 125 and 150% in JPEG format (p = 0.382). When comparing the two formats at same contrast levels, AUC was significantly different (all p < 0.001) except 50% and 100% (p = 0.079 and p = 0.082, respectively). The contrast level and format of medical images could influence the performance of the deep learning model. It is required to train with various contrast levels and formats of image, and further image processing for improvement and maintenance of the performance.

EFFECT OF PELVIC LEAD SHIELD ON ORGAN DOSES IN POSTERO-ANTERIOR CHEST RADIOGRAPHY

Lead shields are commonly used in X-ray imaging to protect radiosensitive organs and to minimise patient's radiation dose. However, they might also complicate or interfere with the examination, and even decrease the diagnostic value if they are positioned incorrectly. In this study, the radiation dose effect of waist half-apron lead shield was examined via Monte Carlo simulations of postero-anterior (PA) chest radiography examinations using a female anthropomorphic phantom. Relevant organs for dose determination were lungs, breasts, liver, kidneys and uterus. The organ dose reductions varied depending on shield position and organ but were negligible for properly positioned shields. The shield that had the largest effective dose reduction (9%) was partly positioned inside the field of view, which should not be done in practice. Dose reduction was practically 0% for properly positioned shields. Therefore, the use of lead shield in the pelvic region during chest PA examinations should be discontinued.

Impact of flexible noise control (FNC) image processing parameters on portable chest radiography

There is a lack of understanding in the performance of flexible noise control (FNC) processing, which is used in digital radiography on a scanner vendor and has four parameters each involving multiple options. The aim of this study was to investigate the impact of FNC on portable chest imaging. An anthropomorphic chest phantom was imaged using a clinical chest program with 85 kV and five radiation dose levels at 40″ source-to-image distance with software-based scatter reduction method. All images were processed without and with FNC. Noise analysis was performed in two regions of interest (ROI) on subtracted noise-only images, and line profiles were generated through a lung-rib interface. In addition, noise power spectra (NPS) analysis was performed in solid water phantoms of 10 and 20 cm thicknesses, using the same acquisition program and a range of dose levels. Last, feedback on retrospectively deidentified, reprocessed, and randomized clinical images from 20 portable chest exams was gathered from two thoracic radiologists. Noise reduction performances of FNC were demonstrated, with the level depending on specific FNC parameters, dose levels, ROI placement, and phantom sizes. Higher frequency textural patterns were revealed through the NPS analysis, which varied based on FNC parameters, dose levels, and phantom sizes. Overall, the vendor default parameter FGA0.5 yielded the highest noise reduction and textural artifacts. Radiologist feedback showed consistent preference of no FNC due to the presence of textural artifacts in the FNC-processed images. An algorithm improvement to avoid introducing artifacts would be desired.

Relationship between the visual evaluation of pathology visibility and the physical measure of low contrast detail detectability in neonatal chest radiography

INTRODUCTION

The detectability of low contrast detail (LCD) is a method used to assess image quality (IQ) in neonatal radiography; however, there is a lack of data on the relationship between LCD detectability and visual IQ. The study aims at investigating the relationship between the LCD detectability and visual IQ and pathology visibility (PV).

METHODS

Several acquisition parameters were employed to obtain a group of images from a neonatal Gammex chest phantom. Three observers applied relative visual grading analysis (VGA) for assessing the IQ and PV. A simulated pneumothorax visibility (PNV) and simulated hyaline membrane disease visibility (HMV) represented PV. Next, a CDRAD 2.0 phantom was radiographed utilising the same acquisition protocols, and several paired images were obtained. With the use of CDRAD analyser software, the detectability of LCD was assessed and expressed by an image quality figure inverse (IQFi_inv) metric. The correlation between the IQF_inv and each of IQ, PNV and HMV was examined.

RESULTS

The physical measure (IQF_inv) and the visual assessment of IQ were shown to be strongly correlated (r = 0.95; p < 0.001). Using Pearson's correlation, the IQF_inv, PNV, and HMV were found to be strongly correlated (r = 0.94; p < 0.001) and (r = 0.92; p < 0.001), correspondingly.

CONCLUSION

Results of the study show that physical measures of LCD detectability utilising the CDRAD 2.0 phantom is strongly corelated with visual IQ and PV (PNV and HMV) and can be used to evaluate IQ when undertaking neonatal chest radiography (CXR).

IMPLICATIONS FOR PRACTICE

This study establishes the feasibility of utilising the physical measure (IQF_inv) and the CDRAD 2.0 phantom in routine quality assurance and neonatal CXR optimisation studies.

Systematic Review of Artificial Intelligence in Acute Respiratory Distress Syndrome for COVID-19 Lung Patients: A Biomedical Imaging Perspective

SARS-CoV-2 has infected over ∼165 million people worldwide causing Acute Respiratory Distress Syndrome (ARDS) and has killed ∼3.4 million people. Artificial Intelligence (AI) has shown to benefit in the biomedical image such as X-ray/Computed Tomography in diagnosis of ARDS, but there are limited AI-based systematic reviews (aiSR). The purpose of this study is to understand the Risk-of-Bias (RoB) in a non-randomized AI trial for handling ARDS using novel AtheroPoint-AI-Bias (AP(ai)Bias). Our hypothesis for acceptance of a study to be in low RoB must have a mean score of 80% in a study. Using the PRISMA model, 42 best AI studies were analyzed to understand the RoB. Using the AP(ai)Bias paradigm, the top 19 studies were then chosen using the raw-cutoff of 1.9. This was obtained using the intersection of the cumulative plot of "mean score vs. study" and score distribution. Finally, these studies were benchmarked against ROBINS-I and PROBAST paradigm. Our observation showed that AP(ai)Bias, ROBINS-I, and PROBAST had only 32%, 16%, and 26% studies, respectively in low-moderate RoB (cutoff>2.5), however none of them met the RoB hypothesis. Further, the aiSR analysis recommends six primary and six secondary recommendations for the non-randomized AI for ARDS. The primary recommendations for improvement in AI-based ARDS design inclusive of (i) comorbidity, (ii) inter-and intra-observer variability studies, (iii) large data size, (iv) clinical validation, (v) granularity of COVID-19 risk, and (vi) cross-modality scientific validation. The AI is an important component for diagnosis of ARDS and the recommendations must be followed to lower the RoB.

Exploring the reliability of the exposure index with a range of kV and mAs values: An experimental study

INTRODUCTION

The exposure index (EI) is a numerical post-exposure tool that provides feedback to diagnostic radiographers undertaking digital X-ray examinations. The EI seeks to provide an indicator of the quantity of incident ionising radiation imparted on an image receptor. However, any large increase to X-ray intensity could interfere with the calculation of the EI. The aim of this paper was to evaluate detector overexposure by increasing X-ray beam intensity and quantifying the resultant effect on the EI.

METHODS

A porcine hip was purchased and exposed with varying tube potentials (50 to 110 kVp) and tube current-time products (5 to 100 mAs). Entrance surface dose (ESD) and EI values were determined for each exposure. For each acquisition parameter, two dose readings were collected. Linear regression was utilised to ascertain the relationship between the EI and varying tube exposures.

RESULTS

Tube exposures between 50 and 80 kVp demonstrated strong positive linear correlation coefficients (r = 0.993, p <0.001; r = 0.999, p <0.001; r = 0.983, p <0.001; r = 0.925, p <0.001) between ESD and EI. However, upon increasing tube exposures (90 to 110 kVp), interference with the EI calculation was demonstrated, which impacted both linearity, strength and direction of correlation (90 kVp r = 0.083, p = .248; 100 kVp r = -0.066, p = .479; 110 kVp r = -0.110, p = .601). Consequently, the use of higher tube exposures demonstrated variability with the EI by not demonstrating an expected positive linear relationship, which remained the initial expectation in this study.

CONCLUSION

The EI value is generally associated with providing reliable feedback to radiographers, yet this paper identifies some unexpected findings at high tube exposures (90 to 110 kVp). In short, this experiment provides insight that the EI value demonstrates inconsistent values within certain energy ranges.

IMPLICATIONS FOR PRACTICE

The findings have implications because it identifies variability of EI values at higher tube exposures. EI values may, therefore, not be helpful in providing meaningful feedback to radiographers when making changes to exposure factors.

Correlation of Oxygenation and Radiographic Assessment of Lung Edema (RALE) Score to Lung Ultrasound Score (LUS) in Acute Respiratory Distress Syndrome (ARDS) Patients in the Intensive Care Unit

Background

Lung ultrasound score (LUS) as well as radiographic assessment of lung edema (RALE) score as calculated from chest radiography (CXR) have been applied to assess Acute Respiratory Distress Syndrome (ARDS) severity. CXRs, which are frequently performed in ARDS patients, pose a greater risk of radiation exposure to patients and health care staff.

Aims and objectives

The aim of the study was to evaluate if LUS had a better correlation to oxygenation (PaO₂/FiO₂) compared with the RALE score in ARDS patients. We also aimed to analyse if there was a correlation between RALE score and LUS. We wanted to determine the LUS and RALE score cut-off, which could predict a prolonged length of intensive care unit (ICU) stay (≥10 days) and survival.

Methods

Thirty-seven patients aged above 18 years with ARDS as per Berlin definition and admitted to the ICU were included in the study. It was a retrospective study done over a period of 11 months. On the day of admission to ICU, the global and basal LUS, global and basal RALE score, and PaO₂ /FiO₂ were recorded. Outcome and days of ICU stay were noted.

Results

Global LUS score and PaO₂/FiO₂ showed the best negative correlation (r = –0.491), which was significant (p = 0.002), followed by global RALE score and PaO₂/FiO₂ (r = –0.422, p = 0.009). Basal LUS and PaO₂/FiO₂ also had moderate negative correlation (r = –0.334, p = 0.043) followed by basal RALE score and PaO₂/FiO₂ (r = –0.34, p = 0.039). Global RALE score and global LUS did not show a significant correlation. Similarly, there was no significant correlation between basal RALE score and basal LUS. Global and basal LUS as well as global and basal RALE score were not beneficial in predicting either a prolonged length of ICU stay or survival as the area under curve was low.

Conclusion

In ARDS patients, global LUS had the best correlation to oxygenation (PaO₂/FiO₂), followed by global RALE score. Basal LUS and basal RALE score also had moderate correlation to oxygenation. However, there was no significant correlation between global LUS and global RALE score as well as between basal LUS and basal RALE score. Global and basal LUS as well as global and basal RALE scores were not able to predict a prolonged ICU stay or survival in ARDS patients.

ESTIMATION OF ENTRANCE SURFACE AIR KERMA IN DIGITAL RADIOGRAPHIC EXAMINATIONS

PURPOSE

Contribution of radiation doses from medical X-ray examination to collective dose is significant. Unusually, high doses may increase the risk of stochastic effects of radiations. Therefore, radiation dose assessment was performed in 241 digital X-ray examinations in the study and was compared with published dose reference levels (DRLs).

METHODS

Entrance surface air kerma (ESAK) was calculated in chest PA, cervical AP/Lat, abdomen AP, lumbar AP/Lat and pelvis AP digital radiographic examinations (119 male and 122 female) following the International Atomic Energy Agency recommended protocol. Initially, 270 digital examinations were selected, reject analysis was performed and final 241 examinations were enrolled in the study for dose calculations. The exposure parameters and X-ray tube output were used for dose calculations. Effective doses were estimated with the help of conversion coefficients from ICRP 103.

RESULTS

Median ESAK (mGy) and associated effective doses obtained were cervical spine AP (1.30 mGy, 0.045 mSv), cervical spine Lat (0.25 mGy, 0.005 mSv), chest PA (0.11 mGy, 0.014 mSv), abdomen AP (0.90 mGy, 0.118 mSv), lumbar spine AP (1.52 mGy, 0.177 mSv), lumbar spine Lat (7.76 mGy, 0.209 mSv) and pelvis AP (0.82 mGy, 0.081 mSv). Results were compared with the studies of UK, Oman, India and Canada.

CONCLUSION

The calculated ESAK and effective dose values were less than or close to previously published literature except for cervical spine AP and lumbar spine Lat. The results reinforce the need for radiation protection optimization, improving examination techniques and appropriate use of automatic exposure control in digital radiography. ESAK values reported in this study could further contribute to establishing local DRLs, regional DRLs and national DRLs.

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.

Radiation dose reduction and improvement of image quality in digital chest radiography by new spatial noise reduction algorithm

Purpose

To evaluate the image quality of low-dose chest digital radiographic images obtained with a new spatial noise reduction algorithm, compared to a conventional de-noising technique.

Materials and methods

In 69 patients, the dose reduction protocol was divided into A, B, and C test groups– 60% (n = 22), 50% (n = 23), and 40% (n = 24) of the baseline dose. In each patient, baseline dose radiographs were obtained with conventional image processing while low-dose images were acquired with new image processing. A set of baseline and low-dose radiographic images per patient was evaluated and scored on a 5-point scale over seven anatomical landmarks (radiolucency of unobscured lung, pulmonary vascularity, trachea, edge of rib, heart border, intervertebral disc space, and pulmonary vessels in the retrocardiac area) and three representative abnormal findings (nodule, consolidation, and interstitial marking) by two thoracic radiologists. A comparison of paired baseline and low-dose images was statistically analyzed using a non-inferiority test based on the paired t-test or the Wilcoxon signed-rank test.

Results

In A, B, and C test groups, the mean dose reduction rate of the baseline radiation dose was 63.4%, 53.9%, and 47.8%, respectively. In all test groups, the upper limit of the 95% confidence interval was less than the non-inferiority margin of 0.5 every seven anatomical landmarks and three representative abnormal findings, which suggested that the image quality of the low-dose image was not inferior to that of the baseline dose image even if the maximum average dose reduction rate was reduced to 47.8% of the baseline dose.

Conclusion

In our study, an image processing technique integrating a new noise reduction algorithm achieved dose reductions of approximately half without compromising image quality for abnormal lung findings and anatomical landmarks seen on chest radiographs. This feature-preserving, noise reduction algorithm adopted in the proposed engine enables a lower radiation dose boundary for the sake of patient’s and radiography technologist’s radiation safety in routine clinical practice, in compliance with regulatory guidelines.

OPTIMIZING IMAGE QUALITY, RADIATION DOSAGE TO THE PATIENT AND TO THE DETECTOR IN PEDIATRIC CHEST RADIOGRAPHY: A PHANTOM STUDY OF A PORTABLE DIGITAL RADIOGRAPHY SYSTEM

The present work aimed to optimize exposure settings in pediatric digital chest radiography (DR) with regard to image quality and radiation dosage. A pediatric phantom was imaged with a portable DR unit to examine different exposure settings (range: 75-109 kVp; 0.3-1.28 mAs) for patients of 10-20 kg. Fourteen experienced radiologists compared the structural image quality of the images with a reference image (85 kVp/1.28 mAs). A multiple-reader multiple-case analysis of the radiologists' interpretations was performed. Effective dose was computed and standardized exposure indices (EIs) were extracted for the different exposure settings. For the lowest tube voltage setting (75 kVp/1.28 mAs), radiation dosage could be reduced with 35% relative the reference settings without compromising image quality (p > 0.05). EI was within recommendations (250 ± 100). Lower tube voltage in pediatric DR permitted a dose reduction at maintained quality for the physical aspects and diagnostic performance. Other weight-classes should be examined and adjusted accordingly.

Image Quality Assessment of the Digital Radiography Units in Tabriz, Iran: A Phantom Study

Creating a high-quality image with the low patient dose is one of the most important goals in medical X-ray imaging. In this study, the image quality parameters of the digital radiographic units in Tabriz city were considered and compared with the international protocols. The image quality parameters were measured at 11 high workload digital radiography (DR) imaging centers in Tabriz city, and the results were compared to DINN 6868/58 standards. All centers equipped with the direct DR units passed the spatial resolution, low contrast detectability, contrast dynamic range, and noise tests, while the computed radiography (CR) units only could pass the two last tests. The highest spatial resolution was observed 3.2 lp/mm in the DR unit while the lowest one was 1.8 lp/mm in the CR unit. The highest noise was measured to be 0.03 OD that was observed in the DR unit. The most difference between the nominal and measured peak kilovoltage and mAs was 3.1% and 6.8%, respectively. The entrance surface air kerma in all units was obtained <0.63 mGy. The measured half-value layer range was between 2.4 and 3.54 mmAl. The physical parameters of image quality such as spatial resolution, contrast, and noise are robustness quantitative parameters for the assessment of the image quality performance of the units. Therefore, measurement and control of these parameters using two-dimensional phantoms are very critical.

Daily routine versus on-demand chest radiograph policy and practice in adult ICU patients- clinicians' perspective

Background

Chest radiographs are taken daily as a part of routine investigations in Intensive care unit (ICU) patients. They are less effective and unlikely to alter the management of the majority of these patients compared to the radiographs obtained when indicated. According to the American College of Radiology (ACR) Appropriateness criteria, only selective ordering of chest radiographs is recommended, including elderly or high risk patients. The aim of this study was to identify and assess the clinician’s perspective in abandoning the current practice of daily routine chest radiograph and replacing with the on-demand radiograph in Saudi hospitals.

Methods

This was a cross-sectional study. A valid self-administered questionnaire was distributed to all clinical staff members working in ICUs in the major tertiary hospitals in Saudi Arabia. The study population was primarily the ICU intensivists (physicians), nurses and respiratory therapists (RT). The data collected were statistically processed using SPSS version 20.0; descriptive and inferential analyses were done.

Results

Out of 730 questionnaires sent, we received only 495 completed questionnaires with a response rate of 67.8%. Majority of them (n = 351) are working at academic hospitals. About half of the respondents (n = 247) are working in an open-format ICUs. Findings showed that the daily routine chest X-ray was performed in almost 96.8% of ICUs patients, which the majority of the clinical staff members (73%) thought that this current daily routine CXR protocol in the ICUs should be replaced with the on-demand CXR policy. Interestingly, the differences in demographic and work-related characteristics had no significant impact on the clinician’s view and supported moving to on-demand CXR policy and practice.

Conclusions

The daily routine CXR is still a common practice in most of the Saudi hospitals ICUs although enough empirical evidence shows that it can be avoided. We observed that intensivists support the change of the current practice and recommend an on-demand CXR policy likely to be followed in intensive care management.

Electronic supplementary material

The online version of this article (10.1186/s12880-018-0248-6) contains supplementary material, which is available to authorized users.

PATIENT RADIATION DOSE FROM CHEST X-RAY EXAMINATIONS IN THE WEST BANK-PALESTINE

Radiation doses to patients resulting from chest X-ray examinations were evaluated in four medical centers in the West Bank and East Jerusalem-Palestine. Absorbed organ and effective doses were calculated for a total of 428 adult male and female patients by using commercially available Monte Carlo based softwares; CALDOSE-X5 and PCXMC-2.0, and hermaphrodite mathematical adult phantoms. Patients were selected randomly from medical records in the time period from November 2014 to February 2015. A database of surveyed patients and exposure factors has been established and includes: patient's height, weight, age, gender, X-ray tube voltage, electric current (mAs), examination projection (anterior posterior (AP), posterior anterior (PA), lateral), X-ray tube filtration thickness in each X-ray equipment, anode angle, focus to skin distance and X-ray beam size. The average absorbed doses in the whole body from different projections were: 0.06, 0.07 and 0.11 mGy from AP, PA and lateral projections, respectively. The average effective dose for all surveyed patients was 0.14 mSv for all chest X-ray examinations and projections in the four investigated medical centers. The effect of projection geometry was also investigated. The average effective doses for AP, PA and lateral projections were 0.14, 0.07 and 0.22 mSv, respectively. The collective effective dose estimated for the exposed population was ~60 man-mSv.

Incident air kerma to absorbed organ dose conversion factors for breast and lung in PA thorax radiography: The effect of patient thickness and radiation quality

PURPOSE

Converting the measurable quantities to patient organ doses in projection radiography is usually based on a standard-sized patient model and a specific radiation quality, which are likely to differ from the real situation. Large inaccuracies can therefore be obtained in organ doses, because organ doses are dependent on the exposure parameters, exposure geometry and patient anatomy. In this study, the effect of radiation quality and patient thickness on the organ dose conversion factors were determined.

METHODS

In this study, the posterior-anterior projection radiograph of the thorax was selected in order to determine the effect of radiation quality (tube voltages of 70-130kV and total filtrations of 3mmAl to 4mmAl+0.2 mmCu) and patient thickness (anterior-posterior thicknesses of 19.4-30.8cm) on the breast and lung dose conversion factors. For this purpose, Monte Carlo simulation programs ImpactMC and PCXMC were used with computed tomography examination data of adult male and female patients and mathematical hermaphrodite phantoms, respectively.

RESULTS

Compared to the reference beam quality and patient thickness, the relative variation range in organ dose conversion factors was up to 74% for different radiation qualities and 122% for different patient thicknesses.

CONCLUSIONS

Conversion factors should only be used with comprehensive understanding of the exposure conditions, considering the exposure parameters, exposure geometry and patient anatomy they are valid for. This study demonstrates that patient thickness-specific and radiation quality-specific conversion factors are needed in projection radiography.

Knowing the Enemy: Health Care Provider Knowledge of Computed Tomography Radiation Dose and Associated Risks

BACKGROUND

There is ionizing radiation and associated risk from many medical imaging examinations, especially computed tomography (CT). Unfortunately, health care providers often have limited knowledge regarding radiation dose levels and potential risk.

RESEARCH OBJECTIVES

To assess knowledge of dose levels and risk among referring physicians, imaging technologists, and radiologists in Saskatoon, Saskatchewan, and to identify potential differences between and within those groups.

MATERIALS AND METHODS

A survey was designed and administered to health care professionals.

RESULTS

A total of 308 of 328 surveys were completed (91% response rate). Overall 73% of physicians, 97% of radiologists, and 76% of technologists correctly believed that there is a risk for cancer from an abdomen-pelvic CT scan. Although only 18% of physicians, 28% of radiologists, and 22% of technologists selected the most appropriate estimate of abdominal-pelvic CT dose in terms of chest x-ray equivalents, this is similar to other reported studies. Physicians and technologists who use CT were more likely to select the correct dose than those who do not. Most respondents (91% of physicians, 100% of radiologists, and 100% of technologists) felt that pregnant patients should always be informed about radiation dose as a risk. Although frequency of discussing risk decreased with increasing patient age, technologists were more likely to discuss risk at any age. A total of 93% of respondents expressed interest in receiving dose feedback from medical imaging procedures.

CONCLUSIONS

Radiologists and technologists generally showed better knowledge than referring physicians. Among physicians and technologists, knowledge was better in those who use CT than those who do not.

Change in Image Quality According to the 3D Locations of a CBCT Phantom

A patient's position changes in every CBCT scan despite patient alignment protocols. However, there have been studies to determine image quality differences when an object is located at the center of the field of view (FOV). To evaluate changes in the image quality of the CBCT scan according to different object positions, the image quality indexes of the Alphard 3030 (Alphard Roentgen Ind., Ltd., Kyoto, Japan) and the Rayscan Symphony (RAY Ind., Ltd., Suwon, Korea) were measured using the Quart DVT_AP phantom at the center of the FOV and 6 peripheral positions under four types of exposure conditions. Anterior, posterior, right, left, upper, and lower positions 1 cm offset from the center of the FOV were used for the peripheral positions. We evaluated and compared the voxel size, homogeneity, contrast to noise ratio (CNR), and the 10% point of the modulation transfer function (MTF10%) of the center and periphery. Because the voxel size, which is determined by the Nyquist frequency, was within tolerance, other image quality indexes were not influenced by the voxel size. For the CNR, homogeneity, and MTF10%, there were peripheral positions which showed considerable differences with statistical significance. The average difference between the center and periphery was up to 31.27% (CNR), 70.49% (homogeneity), and 13.64% (MTF10%). Homogeneity was under tolerance at some of the peripheral locations. Because the CNR, homogeneity, and MTF10% were significantly affected by positional changes of the phantom, an object's position can influence the interpretation of follow up CBCT images. Therefore, efforts to locate the object in the same position are important.

Patient and staff dosimetry during radiographic procedures in an intensive care unit

The performance of radiography in the Intensive Care Unit (ICU) may be associated with a certain level of radiation exposure for staff and patients in the unit. Little evidence on exposure levels is available in the literature. However, healthcare professionals in the ICUs at our centre tend to leave the room during radiographic examinations, potentially compromising patient care. The objectives of this study were to quantify dose levels within the ICU and to evaluate the performance of ICU x-ray studies according to patient dose measurements. This study was conducted in the 18-bed ICU of a third-level hospital. The scattering radiation due to mobile x-ray examinations was measured by using four personal thermoluminiscent dosimeters (TLDs). The dose area product (DAP) was measured at each examination using a transmission chamber installed on the diaphragm of the x-ray equipment. Based on the TLD readings and taking account of the error margin, the annual dose to patients and staff was less than 0.6 mSv. The value given by the DAP meter for chest x-rays was 94  ±  17 mGy cm(2); this value is well below the lower limit recommended by different agencies and committees. Exposure levels were found to be extremely low and pose no apparent risk to staff or to those in beds adjacent to the patients undergoing x-ray examinations, which were correctly performed in the unit.

Correlation of clinical and physical-technical image quality in chest CT: a human cadaver study applied on iterative reconstruction

Background

The first aim of this study was to evaluate the correlation between clinical and physical-technical image quality applied to different strengths of iterative reconstruction in chest CT images using Thiel cadaver acquisitions and Catphan images. The second aim was to determine the potential dose reduction of iterative reconstruction compared to conventional filtered back projection based on different clinical and physical-technical image quality parameters.

Methods

Clinical image quality was assessed using three Thiel embalmed human cadavers. A Catphan phantom was used to assess physical-technical image quality parameters such as noise, contrast-detail and contrast-to-noise ratio (CNR).

Both Catphan and chest Thiel CT images were acquired on a multislice CT scanner at 120 kVp and 0.9 pitch. Six different refmAs settings were applied (12, 30, 60, 90, 120 and 150refmAs) and each scan was reconstructed using filtered back projection (FBP) and iterative reconstruction (SAFIRE) algorithms (1,3 and 5 strengths) using a sharp kernel, resulting in 24 image series. Four radiologists assessed the clinical image quality, using a visual grading analysis (VGA) technique based on the European Quality Criteria for Chest CT.

Results

Correlation coefficients between clinical and physical-technical image quality varied from 0.88 to 0.92, depending on the selected physical-technical parameter. Depending on the strength of SAFIRE, the potential dose reduction based on noise, CNR and the inverse image quality figure (IQF_inv) varied from 14.0 to 67.8 %, 16.0 to 71.5 % and 22.7 to 50.6 % respectively. Potential dose reduction based on clinical image quality varied from 27 to 37.4 %, depending on the strength of SAFIRE.

Conclusion

Our results demonstrate that noise assessments in a uniform phantom overestimate the potential dose reduction for the SAFIRE IR algorithm. Since the IQF_inv based dose reduction is quite consistent with the clinical based dose reduction, an optimised contrast-detail phantom could improve the use of contrast-detail analysis for image quality assessment in chest CT imaging. In conclusion, one should be cautious to evaluate the performance of CT equipment taking into account only physical-technical parameters as noise and CNR, as this might give an incomplete representation of the actual clinical image quality performance.

Automated characterization of perceptual quality of clinical chest radiographs: validation and calibration to observer preference

PURPOSE

The authors previously proposed an image-based technique [Y. Lin et al. Med. Phys. 39, 7019-7031 (2012)] to assess the perceptual quality of clinical chest radiographs. In this study, an observer study was designed and conducted to validate the output of the program against rankings by expert radiologists and to establish the ranges of the output values that reflect the acceptable image appearance so the program output can be used for image quality optimization and tracking.

METHODS

Using an IRB-approved protocol, 2500 clinical chest radiographs (PA/AP) were collected from our clinical operation. The images were processed through our perceptual quality assessment program to measure their appearance in terms of ten metrics of perceptual image quality: lung gray level, lung detail, lung noise, rib-lung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm-lung contrast, and subdiaphragm area. From the results, for each targeted appearance attribute/metric, 18 images were selected such that the images presented a relatively constant appearance with respect to all metrics except the targeted one. The images were then incorporated into a graphical user interface, which displayed them into three panels of six in a random order. Using a DICOM calibrated diagnostic display workstation and under low ambient lighting conditions, each of five participating attending chest radiologists was tasked to spatially order the images based only on the targeted appearance attribute regardless of the other qualities. Once ordered, the observer also indicated the range of image appearances that he/she considered clinically acceptable. The observer data were analyzed in terms of the correlations between the observer and algorithmic rankings and interobserver variability. An observer-averaged acceptable image appearance was also statistically derived for each quality attribute based on the collected individual acceptable ranges.

RESULTS

The observer study indicated that, for each image quality attribute, the averaged observer ranking strongly correlated with the algorithmic ranking (linear correlation coefficient R > 0.92), with highest correlation (R = 1) for lung gray level and the lowest (R = 0.92) for mediastinum noise. There was a strong concordance between the observers in terms of their rankings (i.e., Kendall's tau agreement > 0.84). The observers also generally indicated similar tolerance and preference levels in terms of acceptable ranges, as 85% of the values were close to the overall tolerance or preference levels and the differences were smaller than 0.15.

CONCLUSIONS

The observer study indicates that the previously proposed technique provides a robust reflection of the perceptual image quality in clinical images. The results established the range of algorithmic outputs for each metric that can be used to quantitatively assess and qualify the appearance quality of clinical chest radiographs.

[Detection of lung nodules. New opportunities in chest radiography]

BACKGROUND

Chest radiography still represents the most commonly performed X-ray examination because it is readily available, requires low radiation doses and is relatively inexpensive. However, as previously published, many initially undetected lung nodules are retrospectively visible in chest radiographs.

STANDARD RADIOLOGICAL METHODS

The great improvements in detector technology with the increasing dose efficiency and improved contrast resolution provide a better image quality and reduced dose needs.

METHODICAL INNOVATIONS

The dual energy acquisition technique and advanced image processing methods (e.g. digital bone subtraction and temporal subtraction) reduce the anatomical background noise by reduction of overlapping structures in chest radiography. Computer-aided detection (CAD) schemes increase the awareness of radiologists for suspicious areas.

RESULTS

The advanced image processing methods show clear improvements for the detection of pulmonary lung nodules in chest radiography and strengthen the role of this method in comparison to 3D acquisition techniques, such as computed tomography (CT).

ASSESSMENT

Many of these methods will probably be integrated into standard clinical treatment in the near future. Digital software solutions offer advantages as they can be easily incorporated into radiology departments and are often more affordable as compared to hardware solutions.

Optimization of dual-energy subtraction chest radiography by use of a direct-conversion flat-panel detector system

We aimed to optimize the exposure conditions in the acquisition of soft-tissue images using dual-energy subtraction chest radiography with a direct-conversion flat-panel detector system. Two separate chest images were acquired at high- and low-energy exposures with standard or thick chest phantoms. The high-energy exposure was fixed at 120 kVp with the use of an auto-exposure control technique. For the low-energy exposure, the tube voltages and entrance surface doses ranged 40-80 kVp and 20-100 % of the dose required for high-energy exposure, respectively. Further, a repetitive processing algorithm was used for reduction of the image noise generated by the subtraction process. Seven radiology technicians ranked soft-tissue images, and these results were analyzed using the normalized-rank method. Images acquired at 60 kVp were of acceptable quality regardless of the entrance surface dose and phantom size. Using a repetitive processing algorithm, the minimum acceptable doses were reduced from 75 to 40 % for the standard phantom and to 50 % for the thick phantom. We determined that the optimum low-energy exposure was 60 kVp at 50 % of the dose required for the high-energy exposure. This allowed the simultaneous acquisition of standard radiographs and soft-tissue images at 1.5 times the dose required for a standard radiograph, which is significantly lower than the values reported previously.

Retrospective evaluation of exposure index (EI) values from plain radiographs reveals important considerations for quality improvement

INTRODUCTION

Following X-ray exposure, radiographers receive immediate feedback on detector exposure in the form of the exposure index (EI).

PURPOSE

To identify whether radiographers are meeting manufacturer-recommended EI (MREI) ranges for routine chest, abdomen and pelvis X-ray examinations under a variety of conditions and to examine factors affecting the EI.

METHODS

Data on 5000 adult X-ray examinations including the following variables were collected: examination parameters, EI values, patient gender, date of birth, date and time of examination, grid usage and the presence of implant or prosthesis. Descriptive statistics were used to summarize each data set and the Mann-Whitney U test was used to determine significant differences, with P < 0.05 indicating significance for all tests.

RESULTS

Most examinations demonstrated EI values that were outside the MREI ranges, with significantly higher median EI values recorded for female patient radiographs than those for male patients for all manufacturers, indicating higher detector exposures for all units except for Philips digital radiography (DR), where increased EI values indicate lower exposure (P = 0.01). Median EI values for out of hours radiography were also significantly higher compared with normal working hours for all technologies (P ≤ 0.02). Significantly higher median EI values were demonstrated for Philips DR chest X-rays without as compared to those with the employment of a grid (P = 0.03), while significantly lower median EI values were recorded for Carestream Health computed radiography (CR) chest X-rays when an implant or prosthesis was present (P = 0.02).

CONCLUSIONS

Non-adherence to MREIs has been demonstrated with EI value discrepancies being dependent on patient gender, time/day of exposure, grid usage and the presence of an implant or prosthesis. Retrospective evaluation of EI databases is a valuable tool to assess the need of quality improvement in routine DR.

[Dose reduction and adequate image quality in digital radiography: a contradiction?]

CLINICAL/METHODICAL ISSUE

Dose reduction and adequate image quality in digital radiography - a contradiction?

STANDARD RADIOLOGICAL METHODS

Digital radiography has already replaced traditional screen-film systems.

METHODICAL INNOVATIONS

Substantial improvements in both dose efficiency and spatial resolution demonstrate the rapid developments in digital radiography.

PERFORMANCE

Needle-detector systems have shown up to a 50% dose reduction compared to traditional screen-film systems. There is also a dose reduction capability of up to 50% comparing direct radiography (DR) systems to computed radiography (CR) systems for chest X-rays. However, despite the most recent achievements of CR technology, the dose efficiency of DR systems (caesium iodide flat-panel detector) is unparalleled.

ACHIEVEMENTS

The progress in detector technology has contributed to dose reduction and improved image quality, while saving time and providing a higher examination rate.

PRACTICAL RECOMMENDATIONS

The use of dose indicators and longitudinal dose control are important to avoid substantial accidental dose increase. The dose applied to patients should fall markedly below the defined diagnostic reference levels within the European Union. Regular quality control, as well as continuous education and training of medical and technical personnel, contribute to ensure that the ALARA (as low as reasonably achievable) principle is consistently followed.

Routine chest x-rays in intensive care units: a systematic review and meta-analysis

Introduction

Chest x-rays (CXRs) are the most frequent radiological tests performed in the intensive care unit (ICU). However, the utility of performing daily routine CXRs is unclear.

Methods

We searched Medline and Embase (1948 to March 2011) for randomized and quasi-randomized controlled trials (RCTs) and before-after observational studies comparing a strategy of routine CXRs to a more restrictive approach with CXRs performed to investigate clinical changes among critically ill adults or children. In duplicate, we extracted data on the CXR strategy, study quality and clinical outcomes (ICU and hospital mortality; duration of mechanical ventilation and ICU and hospital stay).

Results

Nine studies (39,358 CXRs; 9,611 patients) were included in the meta-analysis. Three trials (N = 870) of moderate to good quality provided information on the safety of a restrictive routine CXR strategy; only one trial systematically assessed for missed findings. Pooled data from trials showed no evidence of effect of a restrictive approach on ICU mortality (risk ratio [RR] 1.04, 95% confidence interval [CI] 0.84 to 1.28, P = 0.72; two trials, N = 776), hospital mortality (RR 0.98, 95% CI 0.68 to 1.41, P = 0.91; two trials, N = 259), ICU length of stay (weighted mean difference [WMD] -0.86 days, 95% CI -2.38 to 0.66 days, P = 0.27; three trials, N = 870), hospital length of stay (WMD -2.50 days, 95% CI -6.62 to 1.61 days, P = 0.23; two trials, N = 259), or duration of mechanical ventilation (WMD -0.30 days, 95% CI -1.48 to 0.89 days, P = 0.62; three trials, N = 705). Adding data from six observational studies, one of which systematically screened for missed findings, gave similar results.

Conclusions

This meta-analysis did not detect any harm associated with a restrictive chest radiograph strategy. However, confidence intervals were wide and harm was not rigorously assessed. Therefore, the safety of abandoning routine CXRs in patients admitted to the ICU remains uncertain.

Use of a digitally reconstructed radiograph-based computer simulation for the optimisation of chest radiographic techniques for computed radiography imaging systems

OBJECTIVES

The purpose of this study was to derive an optimum radiographic technique for computed radiography (CR) chest imaging using a digitally reconstructed radiograph computer simulator. The simulator is capable of producing CR chest radiographs of adults with various tube potentials, receptor doses and scatter rejection.

METHODS

Four experienced image evaluators graded images of average and obese adult patients at different potentials (average-sized, n=50; obese, n=20), receptor doses (n=10) and scatter rejection techniques (average-sized, n=20; obese, n=20). The quality of the images was evaluated using visually graded analysis. The influence of rib contrast was also assessed.

RESULTS

For average-sized patients, image quality improved when tube potential was reduced compared with the reference (102 kVp). No scatter rejection was indicated. For obese patients, it has been shown that an antiscatter grid is indicated, and should be used in conjunction with as low a tube potential as possible (while allowing exposure times <20 ms). It is also possible to reduce receptor air kerma by 50% without adversely influencing image quality. Rib contrast did not interfere at any tube potential.

CONCLUSIONS

A virtual clinical trial has been performed with simulated chest CR images. Results indicate that low tube potentials (<102 kVp) are optimal for average and obese adults, the former acquired without scatter rejection, the latter with an anti-scatter grid. Lower receptor (and therefore patient doses) than those used clinically are possible while maintaining adequate image quality.

Radiation exposure during nasojejunal intubation for MRI enteroclysis

BACKGROUND

Patients with Crohn's disease are often investigated using MRI enteroclysis which may provide better visual quality than MRI enterography, but exposes patients to radiation. Only few data exist of the radiation dose used in fluoroscopy prior to MRI enteroclysis.

SUBJECTS AND METHODS

During the 12-month study period, all 95 patients (40 men) undergoing MRI enteroclysis with nasojejunal intubation using fluoroscopy for suspicion or evaluation of Crohn's disease were included. Average age at the time of MRI was 40.1 years (range 17-79). Conversion factors from dose-area product to effective dose were determined with a Monte Carlo-based software PCXMC. The conversion factors were determined for a standard-sized adult phantom for posterior-anterior and right-posterior-oblique projections.

RESULTS

The average total time of fluoroscopy was 3 min 17 s (range 0 min 7 s to 31 min). The average effective dose of ionizing radiation was 0.21 mSv (range 0.01-2.67). The average dose is equivalent to 10 PA chest x-rays. Standard deviation was 0.41 mSv. The highest effective dose of a single patient was 2.67 mSv. In comparison, a standard abdominal CT scan causes an effective dose of 12 mSv.

CONCLUSIONS

The effective dose of ionizing radiation with nasojejunal intubation is relatively small in the majority of patients. When repeated imaging is necessary, it seems advisable to consider imaging techniques, which do not subject patients to ionizing radiation. Also if a previous nasojejunal intubation has been difficult, a different imaging technique is recommended.

Optimization of the radiological protection of patients undergoing digital radiography

Because of a much higher dynamic range of flat panel detectors, patient dose can vary without change of image quality being perceived by radiologists. This condition makes optimization (OT) of radiation protection undergoing digital radiography (DR) more complex, while a chance to reduced patient dose also exists. In this study, we evaluated the difference of patient radiation and image rejection before and after OT to identify if it is necessary to carry out an OT procedure in a routine task with DR. The study consisted of a measurement of the dose area product (DAP) and entrance surface dose (ESD) received by a reference group of patients for eight common radiographic procedures using the DR system before and after OT. Meanwhile image rejection data during two 2-month periods were collected and sorted according to reason. For every radiographic procedure, t tests showed significant difference in average ESD and DAP before and after OT (p < 0.005). The ESDs from most examinations before OT were three times higher than that after OT. For DAPs, the difference is more significant. Image rejection rate after OT is significantly lower than that before OT (χ (2) = 36.5, p < 0.005). The substantial reductions of dose after OT resulted from appropriate mAs and exposure field. For DR patient dose, less than recommended diagnostic reference level can meet quality criteria and clinic diagnosis.

Diagnostic value of routine chest radiography in febrile, neutropenic children for early detection of pneumonia and mould infections

BACKGROUND

Despite recent studies failing to demonstrate the value of routine chest radiography (CXR) in the initial evaluation of the febrile neutropenic patient with cancer, this screening test is advocated by some experts. We evaluated the benefits of CXR for early diagnosis of pulmonary infection at St. Jude Children's Research Hospital (SJCRH) with emphasis on early recognition of mould infections.

PATIENTS AND METHODS

We reviewed the courses of 200 consecutive febrile neutropenic pediatric patients to determine if routine CXR at initial evaluation was useful in the identification of clinically occult pneumonia. We also reviewed all cases of proven or probable mould infections from the opening of SJCRH in 1962 until 1998 when routine CXR was no longer practiced in our institution to identify cases that were first recognized by routine CXR.

RESULTS

Of 200 febrile neutropenic patients, pulmonary abnormalities consistent with pneumonia were detected by routine CXR in only five patients without pulmonary signs or symptoms. In only one case was a change in management considered. Of the 70 patients with pulmonary mould infection identified from 1962 to 1998, routine CXR was performed in 45 patients at the onset of a febrile, neutropenic episode in which a mould infection was diagnosed. Routine CXR was pivotal in the recognition of the mould infection in only two cases over this 36-year period.

CONCLUSION

CXR is warranted in the evaluation of the newly febrile neutropenic pediatric oncology patient only when respiratory signs or symptoms are present.

Correlation of contrast-detail analysis and clinical image quality assessment in chest radiography with a human cadaver study

PURPOSE

To determine the correlation between the clinical and physical image quality of chest images by using cadavers embalmed with the Thiel technique and a contrast-detail phantom.

MATERIALS AND METHODS

The use of human cadavers fulfilled the requirements of the institutional ethics committee. Clinical image quality was assessed by using three human cadavers embalmed with the Thiel technique, which results in excellent preservation of the flexibility and plasticity of organs and tissues. As a result, lungs can be inflated during image acquisition to simulate the pulmonary anatomy seen on a chest radiograph. Both contrast-detail phantom images and chest images of the Thiel-embalmed bodies were acquired with an amorphous silicon flat-panel detector. Tube voltage (70, 81, 90, 100, 113, 125 kVp), copper filtration (0.1, 0.2, 0.3 mm Cu), and exposure settings (200, 280, 400, 560, 800 speed class) were altered to simulate different quality levels. Four experienced radiologists assessed the image quality by using a visual grading analysis (VGA) technique based on European Quality Criteria for Chest Radiology. The phantom images were scored manually and automatically with use of dedicated software, both resulting in an inverse image quality figure (IQF). Spearman rank correlations between inverse IQFs and VGA scores were calculated.

RESULTS

A statistically significant correlation (r = 0.80, P < .01) was observed between the VGA scores and the manually obtained inverse IQFs. Comparison of the VGA scores and the automated evaluated phantom images showed an even better correlation (r = 0.92, P < .001).

CONCLUSION

The results support the value of contrast-detail phantom analysis for evaluating clinical image quality in chest radiography.