Computed tomography--an increasing source of radiation exposure

Age-Dependent Differences in Blood Levels of Glial Fibrillary Acidic Protein but Not Ubiquitin Carboxy-Terminal Hydrolase L1 in Children

OBJECTIVES

Despite the growing evidence of the clinical utility of blood-brain biomarkers in adults with traumatic brain injury (TBI), less is known about the performance of these biomarkers in children. We characterize age-dependent differences in levels of ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) and glial fibrillary acidic protein (GFAP) in children without TBI.

METHODS

Plasma biobank specimens from children and adolescents aged 0-<19 years without TBI were obtained, and UCH-L1 and GFAP levels were quantified. The relationship between age and biomarker expression was determined using previously defined aged epochs (<3.5 years, 3.5 years to <11 years, 11 years and older), then biomarker levels were compared with established thresholds for ruling out the need for a head CT in adults with a mild TBI (mTBI) (UCH-L1 400 pg/mL, GFAP 35 pg/mL).

RESULTS

The age range of the 366 control patients was 3 months-18 years. There was a significant negative association between age and GFAP but not UCH-L1. Only 1.4% of samples exceeded the UCH-L1 cutoff; however, 20% of samples exceeded the GFAP cutoff and 100% children younger than 3.5 years had values that exceeded the cutoff.

DISCUSSION

Age seems to modify physiologic plasma GFAP levels. Diagnostic cutoffs for TBI based on GFAP but not UCH-L1 and may need to be adjusted in children younger than 11 years.

Optical frequency domain imaging (OFDI) represents a novel technique for the diagnosis of giant cell arteritis

BACKGROUND/OBJECTIVES

Giant cell arteritis (GCA) is an inflammatory vascular disease in which prompt and accurate diagnosis is critical. The efficacy of temporal artery biopsy (TAB) is limited by 'skip' lesions and a delay in histological analysis. This first-in-man ex-vivo study aims to assess the accuracy of optical frequency domain imaging (OFDI) in diagnosing GCA.

SUBJECTS/METHODS

29 TAB samples of patients with suspected GCA were submerged in 0.9% sodium chloride and an OFDI catheter was passed through the lumen to create cross-sectional images prior to histological analysis. The specimens were then preserved in formalin for histological examination. Mean intimal thickness (MIT) on OFDI was measured, and the presence of both multinucleate giant cells (MNGCs) and fragmentation of the internal elastic lamina (FIEL) was assessed and compared with histology, used as the diagnostic gold standard.

RESULTS

MIT in patients with/without histological evidence of GCA was 0.425 mm (±0.43) and 0.13 mm (±0.06) respectively compared with 0.215 mm (±0.09) and 0.135 mm (±0.07) on OFDI. MIT measured by OFDI was significantly higher in patients with histologically diagnosed arteritis compared to those without (p = 0.0195). For detecting FIEL and MNGCs, OFDI had a sensitivity of 75% and 28.6% and a specificity of 100% and 77.3% respectively. Applying diagnostic criteria of MIT > 0.20 mm, or the presence of MNGCs or FIEL, the sensitivity of detecting histological arteritis using OFDI was 91.4% and the specificity 94.1%.

CONCLUSIONS

OFDI provided rapid imaging of TAB specimens achieving a diagnostic accuracy comparable to histological examination. In-vivo imaging may allow imaging of a longer arterial section.

Changes in femoral anteversion after intramedullary nailing for pediatric femoral shaft fracture: a multicenter study

BACKGROUND

The rotational change after using a flexible intramedullary (IM) nail for femoral shaft fractures has been a concern for many surgeons. Recently, a statistical shape model (SSM) was developed for the three-dimensional reconstruction of the femur from two-dimensional plain radiographs. In this study, we measured postoperative femoral anteversion (FAV) in patients diagnosed with femoral shaft fractures who were treated with flexible IM nails and investigated age-related changes in FAV using the SSM.

METHODS

This study used radiographic data collected from six regional tertiary centers specializing in pediatric trauma in South Korea. Patients diagnosed with femoral shaft fractures between September 2002 and June 2020 and patients aged < 18 years with at least two anteroposterior (AP) and lateral (LAT) femur plain radiographs obtained at least three months apart were included. A linear mixed model (LMM) was used for statistical analysis.

RESULTS

Overall, 72 patients were included in the study. The average patient age was 7.6 years and the average follow-up duration was 6.8 years. The average FAV of immediate postoperative images was 27.5 ± 11.5°. Out of 72 patients, 52 patients (72.2%) showed immediate postoperative FAV greater than 20°. The average FAV in patients with initial FAV > 20° was 32.74°, and the LMM showed that FAV decreased by 2.5° (p = 0.0001) with each 1-year increase from the time of initial trauma.

CONCLUSIONS

This study explored changes in FAV after femoral shaft fracture using a newly developed technology that allows 3D reconstruction from uncalibrated 2D images. There was a pattern of change on the rotation of the femur after initial fixation, with a 2.5° decrease of FAV per year.

Utility of Torso Imaging for Elderly Patients Sustaining Ground-Level Falls

INTRODUCTION

Computed tomography (CT) of the torso has become increasingly common for assessment of fall patients in the emergency department. Some data suggest that older adults (≥65) may benefit from torso imaging more than younger patients. We sought to evaluate the usage and utility of CT imaging for elderly patients presenting after ground-level falls (GLFs) from 1 meter or less at our level 1 trauma center.

METHODS

Patients ≥18 presenting with GLF in 2015-2019 were included. Data were obtained through chart and trauma registry review. Descriptive statistics were used to summarize the use of CT imaging for patients younger than versus older than 65 y old. Three multivariate logistic regression models with age as a continuous, binary (<65 versus ≥65), or categorical (in multiples of 5) variable were used to investigate whether age is associated with an increased identification of traumatic injury not previously suspected or known based on physical exam (PE) or plain radiograph after GLF.

RESULTS

A total of 522 patients <65 and 673 patients ≥65 y old were included. Older patients were significantly more likely to receive screening chest radiograph, screening pelvic radiograph, brain CT, and neck CT (all P < 0.001), but not torso (chest, abdomen, and pelvis) CT (P = 0.144). On multivariate logistic regression, age was not significantly associated with an increased odds of identification of traumatic injury after torso CT (continuous: adjusted odds ratio [aOR] = 1.01, 95% confidence interval [CI] = 0.99-1.03, P = 0.379; binary: aOR = 0.86, 95% CI = 0.46-1.58, P = 0.619; categorical: aOR = 1.03, 95% CI = 0.94-1.14, P = 0.453). A positive PE was the only variable associated with significantly increased odds of having an abnormal torso CT scan in all models. Only two patients ≥65 y old had injuries identified on torso CT in the context of a negative PE and negative screening imaging.

CONCLUSIONS

The rate of torso injury identification in patients sustaining GLF is not associated with age, but is strongly associated with positive PE findings. In the subset of elderly GLF patients without positive torso PE findings, more conservative use of CT imaging could decrease health-care utilization costs without compromising patient care.

The Florida Geriatric Head Trauma CT Clinical Decision Rule

BACKGROUND

Several clinical decision rules have been devised to guide head computed tomography (CT) use in patients with minor head injuries, but none have been validated in patients 65 years or older. We aimed to derive and validate a head injury clinical decision rule for older adults.

METHODS

We conducted a secondary analysis of an existing dataset of consecutive emergency department (ED) patients >65 years old with blunt head trauma. The main predictive outcomes were significant intracranial injury and Need for Neurosurgical Intervention on CT. The secondary outcomes also considered in the model development and validation were All Injuries and All Intracranial Injuries. Predictor variables were identified using multiple variable logistic regression, and clinical decision rule models were developed in a split-sample derivation cohort and then tested in an independent validation cohort.

RESULTS

Of 5776 patients, 233 (4.0%) had significant intracranial injury and an additional 104 (1.8%) met CT criteria for Need for Neurosurgical Intervention. The best performing model, the Florida Geriatric Head Trauma CT Clinical Decision Rule, assigns points based on several clinical variables. If the points totaled 25 or more, a CT scan is indicated. The included predictors were arrival via Emergency Medical Services (+30 points), Glasgow Coma Scale (GCS) <15 (+20 points), GCS <14 (+50 points), antiplatelet medications (+17 points), loss of consciousness (+16 points), signs of basilar skull fracture (+50 points), and headache (+20 points). Utilizing this clinical decision rule in the validation cohort, a point total ≥25 had a sensitivity and specificity of 100.0% (95% CI: 96.0-100) and 12.3% (95% CI: 10.9-13.8), respectively, for significant intracranial injury and Need for Neurosurgical Intervention.

CONCLUSIONS

The Florida Geriatric Head Trauma CT Clinical Decision Rule has the potential to reduce unnecessary CT scans in older adults, without compromising safe emergency medicine practice.

Evaluation of low-dose pediatric chest CT examination using in-house developed various age-size pediatric chest phantoms

PURPOSE

This study aims to develop Various Age-size Pediatric Chest Phantoms (VAPC) to evaluate low-dose protocol that approximates clinical conditions achieved by low organ-specific doses and optimal image quality among the challenges of pediatric size variations.

METHODS

Three original pediatric data aged 1, 4, and 7 years were used as a reference for developing VAPC phantoms. Six protocols, namely standard dose (STD) and low dose (low mA and low kV) reconstructed using Filtered Back Projection (FBP) and iterative reconstruction (IR) algorithms, were investigated. This study directly measured the lungs, heart, and spinal cord dose using LD-V1 film. Linearity, Modulation Transfer Function (MTF), Contrast to Noise Ratio (CNR), and Noise Power Spectrum (NPS) were evaluated to assess the CT image quality of the VAPC phantom.

RESULTS

This study found that the mean organ-specific dose was higher than CTDIvol. A Comparison of mean lung doses showed VAPC phantom 1 (y.o.) received 74.8% and 137.2% more doses than 4 (y.o.) and 7 (y.o.), respectively. Low kV produces a lower organ dose than low mA. The linearity of CT numbers is not biased at low doses. Differences in age measures significantly influenced organ-specific dose, MTF, CNR, and NPS.

CONCLUSION

Smaller pediatrics are still exposed to higher doses at low-dose examinations, whereas larger pediatrics have lower contrast resolution and increased image noise. CT number linearity is unbiased. The combination of low kV with FBP produces higher spatial resolution, while low mA with IR effectively reduces noise to detect low-contrast objects better.

Effectiveness of contrast-enhanced duplex ultrasound for detecting renal artery stenosis: A systematic review

PURPOSE

Contrast-enhanced duplex ultrasound (CEUS) might be a useful tool to diagnosing renal artery stenosis (RAS). We amalgamated and reviewed the evidence assessing the diagnostic accuracy of CEUS on detecting RAS compared to angiography.

METHODS

This preregistered systematic review included studies that compared the presence of RAS via CEUS with angiography. Sources were searched in November 2022 and included Scopus, EMBASE, MEDLINE, CINAHL, and Academic Search Premier (n = 1717). The Quality Assessment of Diagnostic Studies 2 tool assessed study quality. Results are presented narratively.

RESULTS

The studies included (n = 11) had a total of 447 unique participants (193 females) and average age of 56 ± 9 years. Five of eleven studies investigated CEUS using SonoVue contrast agent and reported an average accuracy (91% ± 2%), sensitivity (91% ± 3%), specificity (90% ± 5%), negative predictive value (86% ± 6%), and positive predictive value (94% ± 1%) with all values >80%. The accuracy of CEUS using other types of contrast agent (n = 6), including Levovsit (n = 3/6), Definity (n = 1/6), perfienapent emulsion (n = 1/6), and perfluorocarbon-exposed sonicated dextrose albumin (n = 1/6) was mixed. These studies detected an average accuracy of 91 ± 11% (n = 2/3% > 80%), sensitivity of 98% ± 4%, (n = 3/3% > 80%), and specificity of 86% ± 10% (n = 2/3% > 80%). Included studies had generally low risk of bias and applicability concerns except for unclear flow and timing (n = 7/11) and applicability of patient selection (n = 4/11).

CONCLUSION

Despite being limited by the heterogeneity of included studies, our review indicates a high overall diagnostic accuracy for CEUS to detect RAS compared to angiography, with the largest evidence-base for SonoVue contrast. Radiologists and hospital decision makers should consider CEUS as an acceptable alternative to angiography.

Improving Automated Hemorrhage Detection at Sparse-View CT via U-Net-based Artifact Reduction

Purpose To explore the potential benefits of deep learning-based artifact reduction in sparse-view cranial CT scans and its impact on automated hemorrhage detection. Materials and Methods In this retrospective study, a U-Net was trained for artifact reduction on simulated sparse-view cranial CT scans in 3000 patients, obtained from a public dataset and reconstructed with varying sparse-view levels. Additionally, EfficientNet-B2 was trained on full-view CT data from 17 545 patients for automated hemorrhage detection. Detection performance was evaluated using the area under the receiver operating characteristic curve (AUC), with differences assessed using the DeLong test, along with confusion matrices. A total variation (TV) postprocessing approach, commonly applied to sparse-view CT, served as the basis for comparison. A Bonferroni-corrected significance level of .001/6 = .00017 was used to accommodate for multiple hypotheses testing. Results Images with U-Net postprocessing were better than unprocessed and TV-processed images with respect to image quality and automated hemorrhage detection. With U-Net postprocessing, the number of views could be reduced from 4096 (AUC: 0.97 [95% CI: 0.97, 0.98]) to 512 (0.97 [95% CI: 0.97, 0.98], P < .00017) and to 256 views (0.97 [95% CI: 0.96, 0.97], P < .00017) with a minimal decrease in hemorrhage detection performance. This was accompanied by mean structural similarity index measure increases of 0.0210 (95% CI: 0.0210, 0.0211) and 0.0560 (95% CI: 0.0559, 0.0560) relative to unprocessed images. Conclusion U-Net-based artifact reduction substantially enhanced automated hemorrhage detection in sparse-view cranial CT scans. Keywords: CT, Head/Neck, Hemorrhage, Diagnosis, Supervised Learning Supplemental material is available for this article. © RSNA, 2024.

A Narrative Review on Financial Challenges and Health Care Costs Associated with Traumatic Brain Injury in the United States

BACKGROUND

Traumatic brain injury (TBI) is a highly prevalent and potentially severe medical condition. Challenges regarding TBI management are related to accurate diagnostics, defining its severity, and establishing prompt interventions to affect outcomes. Among the health care components in the TBI handling strategy is intracranial pressure (ICP) monitoring, which is fundamental to therapy decisions. However, ICP monitoring is an Achilles tendon, imposing a significant financial burden on health care systems, particularly in middle and low-income communities. This article arises from the understanding from the authors that there is insufficient scientific evidence about the potential economic impacts from the use of noninvasive technologies in the monitoring of TBI. Based on personal experience, as well as from reading other, clinically focused studies, the thesis is that the use of such technologies could greatly affect the health care system and this article seeks to address this lack of literature, show ways in which such systems could be evaluated, and show estimations of possible results from these investigations.

OBJECTIVE

This review primarily investigates the economic burden of TBI and whether new technologies are suitable to reduce its health care costs without compromising the quality of care, according to the levels of evidence available. The objective is to stimulate more research and attention in the area.

METHODS

For this narrative review, a PubMed search was conducted for articles discussing TBI health care costs, as well as monitoring technologies (tomography, magnetic resonance imaging, optic nerve sheath diameter, transcranial Doppler, pupillometry, and noninvasive ICP waveform) and their application in managing TBI. Strategies were first evaluated from a medical noninferiority perspective before calculating the average savings of each selected strategy. All applicable studies were analyzed for quality using the Consolidated Health Economic Evaluation Reporting Standards 2022 Statement117 and this article was written to conform as much as possible with it.

RESULTS

The review included 109 references and showed a consistent potential in noninvasive technologies to reduce costs and maintain or improve the quality of care.

CONCLUSIONS

TBI prevalence has increased with a disproportionate health care burden in the last decades. Noninvasive monitoring techniques seem to be effective in reducing TBI health care costs, with few limitations, especially the need for more supporting scientific evidence. The undeniable clinical and financial potential of these techniques is compelling to further investigate their role in TBI management, as well as the creation of more comprehensive monitoring models to the understanding of complex phenomena occurring in the injured brain.

Optimizing Advanced Imaging of the Pediatric Patient in the Emergency Department: Technical Report

Advanced diagnostic imaging modalities, including ultrasonography, computed tomography, and magnetic resonance imaging, are key components in the evaluation and management of pediatric patients presenting to the emergency department. Advances in imaging technology have led to the availability of faster and more accurate tools to improve patient care. Notwithstanding these advances, it is important for physicians, physician assistants, and nurse practitioners to understand the risks and limitations associated with advanced imaging in children and to limit imaging studies that are considered low value, when possible. This technical report provides a summary of imaging strategies for specific conditions where advanced imaging is commonly considered in the emergency department. As an accompaniment to the policy statement, this document provides resources and strategies to optimize advanced imaging, including clinical decision support mechanisms, teleradiology, shared decision-making, and rationale for deferred imaging for patients who will be transferred for definitive care.

Optimizing Advanced Imaging of the Pediatric Patient in the Emergency Department: Technical Report

Advanced diagnostic imaging modalities, including ultrasonography, computed tomography, and magnetic resonance imaging (MRI), are key components in the evaluation and management of pediatric patients presenting to the emergency department. Advances in imaging technology have led to the availability of faster and more accurate tools to improve patient care. Notwithstanding these advances, it is important for physicians, physician assistants, and nurse practitioners to understand the risks and limitations associated with advanced imaging in children and to limit imaging studies that are considered low value, when possible. This technical report provides a summary of imaging strategies for specific conditions where advanced imaging is commonly considered in the emergency department. As an accompaniment to the policy statement, this document provides resources and strategies to optimize advanced imaging, including clinical decision support mechanisms, teleradiology, shared decision-making, and rationale for deferred imaging for patients who will be transferred for definitive care.

DistilIQA: Distilling Vision Transformers for no-reference perceptual CT image quality assessment

No-reference image quality assessment (IQA) is a critical step in medical image analysis, with the objective of predicting perceptual image quality without the need for a pristine reference image. The application of no-reference IQA to CT scans is valuable in providing an automated and objective approach to assessing scan quality, optimizing radiation dose, and improving overall healthcare efficiency. In this paper, we introduce DistilIQA, a novel distilled Vision Transformer network designed for no-reference CT image quality assessment. DistilIQA integrates convolutional operations and multi-head self-attention mechanisms by incorporating a powerful convolutional stem at the beginning of the traditional ViT network. Additionally, we present a two-step distillation methodology aimed at improving network performance and efficiency. In the initial step, a "teacher ensemble network" is constructed by training five vision Transformer networks using a five-fold division schema. In the second step, a "student network", comprising of a single Vision Transformer, is trained using the original labeled dataset and the predictions generated by the teacher network as new labels. DistilIQA is evaluated in the task of quality score prediction from low-dose chest CT scans obtained from the LDCT and Projection data of the Cancer Imaging Archive, along with low-dose abdominal CT images from the LDCTIQAC2023 Grand Challenge. Our results demonstrate DistilIQA's remarkable performance in both benchmarks, surpassing the capabilities of various CNNs and Transformer architectures. Moreover, our comprehensive experimental analysis demonstrates the effectiveness of incorporating convolutional operations within the ViT architecture and highlights the advantages of our distillation methodology.

Image reconstruction method for incomplete CT projection based on self-guided image filtering

In some fields of medical diagnosis or industrial nondestructive testing, it is difficult to obtain complete computed tomography (CT) data due to the limitation of radiation dose or other factors. Therefore, image reconstruction of incomplete projection data is the focus of this paper. In this paper, a new image reconstruction model based on self-guided image filtering (SGIF) term is proposed for few-view and segmental limited-angle (SLA) CT reconstruction. Then the alternating direction method (ADM) is used to solve this model. For simplicity, we call it ADM-SGIF method. The key idea of ADM-SGIF method is to use the reconstructed image itself as a reference and utilize its structural features to guide CT reconstruction. This method can effectively preserve image structures and remove shading artifacts. To validate the effectiveness of the proposed reconstruction method, we conduct digital phantom and real CT data experiments. The results indicate that ADM-SGIF method outperforms competing methods, including total variation (TV), relative total variation (RTV), and L0-norm minimization solved by ADM (ADM-L0) methods, in both subjective and objective evaluations.

Comparison of lung ultrasound assisted by artificial intelligence to radiology examination in pneumothorax

BACKGROUND

Lung ultrasound can evaluate for pneumothorax but the accuracy of diagnosis depends on experience among physicians. This study aimed to investigate the sensitivity and specificity of intelligent lung ultrasound in comparison with chest x-ray, employing chest computed tomography (CT) as the gold standard for diagnosis of pneumothorax in critical ill patients.

METHODS

This prospective, observational study included 75 dyspnea patients admitted to the Intensive Care Unit of the Fourth Affiliated Hospital of Soochow University from January 2021 to April 2023. Lung ultrasound images were collected using BLUE-plus protocol and analyzed by artificial intelligence software to identify the pleural line, with CT results serving as the gold standard for diagnosis. Pneumothorax was diagnosed based on either the disappearance of pleural slip sign or identification of lung point. Additionally, chest x-ray images and diagnostic results were also obtained during the same period for comparison.

RESULTS

The sensitivity and specificity of intelligent lung ultrasound in diagnosing pneumothorax were 79.4% and 85.4%, respectively. The sensitivity and specificity of x-ray diagnosis were 82.4% and 80.5%. Additionally, the diagnostic time for lung ultrasound was significantly shorter than that for x-ray examination.

CONCLUSION

Intelligent lung ultrasound has diagnostic efficiency comparable to that of x-ray examination but offers advantages in terms of speed.

Identifying skull fractures after head trauma in infants with ultrasonography: is that possible?

Management of pediatric head trauma requires a delicate balance between accuracy and safety, with a dual emphasis on prompt diagnosis while minimizing radiation exposure. Ultrasonography (US) shows promise in this regard. A case study involving a 10-month-old infant with acute right parietal swelling revealed the utility of US in detecting a corresponding hypoechoic lesion, along with an underlying suspected fracture line of the vault and subdural hematoma. Subsequent CT confirmed the fracture, while MRI confirmed the subdural hematoma. At one-month follow-up, MRI demonstrated hematoma reabsorption, while US revealed a bone callus in its advanced phase. Although US is not yet standard practice for pediatric head trauma, its ability to detect fractures in infants suggests its potential role: when a fracture is evident on US, it may serve as an indication to perform neuroimaging. Potentially, adoption of US could contribute to mitigation of children's exposure to ionizing radiation.

Advanced Imaging Techniques for Complex Endovascular Aortic Repair: Pre-Operative, Intra-Operative and Post-Operative Advancements

OBJECTIVES

Endovascular aortic repair requires extensive preoperative, intraoperative, and postoperative imaging for planning, surveillance, and detection of endo-leaks. There have been many advancements in imaging modalities to achieve this purpose. This review discussed different imaging modalities used at different stages of treatment of complex endovascular aortic repair.

METHODS

We conducted a literature review of all the imaging modalities utilized in endovascular aortic repair by searching various databases.

RESULTS

Pre-operative techniques include analysis of images obtained via modified central line using analysis software and intravascular ultrasound. Fusion imaging, CO2 angiography, intravascular ultrasound, and Fiber Optic RealShape technology have been crucial in obtaining real-time imaging for the detection of endo-leaks during operative procedures. Conventional imaging modalities like CT Angiography and MR Angiography are still employed for post-operative surveillance along with computational fluid dynamics and contrast-enhanced ultrasound. The advancements in artificial intelligence have been the breakthrough in developing robust imaging applications.

CONCLUSIONS

This review explains the advantages, disadvantages, and side-effect profile of the abovementioned imaging modalities.

Racial difference in receiving computed tomography for head injury patients in emergency departments

STUDY OBJECTIVE

Prior studies have suggested potential racial differences in receiving imaging tests in emergency departments (EDs), but the results remain inconclusive. In addition, most prior studies may only have limited racial groups for minority patients. This study aimed to investigate racial differences in head computed tomography (CT) administration rates in EDs among patients with head injuries.

METHODS

Patients with head injuries who visited EDs were examined. The primary outcome was patients receiving head CT during ED visits, and the primary exposure was patient race/ethnicity, including Asian, Hispanic, Non-Hispanic Black (Black), and Non-Hispanic White (White). Multivariable logistic regression analyses were performed using the National Hospital Ambulatory Medical Care Survey database, adjusting for patients and hospital characteristics.

RESULTS

Among 6130 patients, 51.9% received a head CT scan. Asian head injury patients were more likely to receive head CT than White patients (59.1% versus 54.0%, difference 5.1%, p < 0.001). This difference persisted in adjusted results (odds ratio, 1.52; 95% CI, 1.06-2.16, p = 0.022). In contrast, Black and Hispanic patients have no significant difference in receiving head CT than White patients after the adjustment.

CONCLUSIONS

Asian head injury patients were more likely to receive head CT than White patients. This difference may be attributed to the limited English proficiency among Asian individuals and the fact that there is a wide variety of different languages spoken by Asian patients. Future studies should examine rates of receiving other diagnostic imaging modalities among different racial groups and possible interventions to address this difference.

Current Applications and Future Directions of Circulating Tumor Cells in Colorectal Cancer Recurrence

The ability to predict or detect colorectal cancer (CRC) recurrence early after surgery enables physicians to apply appropriate treatment plans and different follow-up strategies to improve patient survival. Overall, 30-50% of CRC patients experience cancer recurrence after radical surgery, but current surveillance tools have limitations in the precise and early detection of cancer recurrence. Circulating tumor cells (CTCs) are cancer cells that detach from the primary tumor and enter the bloodstream. These can provide real-time information on disease status. CTCs might become novel markers for predicting CRC recurrence and, more importantly, for making decisions about additional adjuvant chemotherapy. In this review, the clinical application of CTCs as a therapeutic marker for stage II CRC is described. It then discusses the utility of CTCs for monitoring cancer recurrence in advanced rectal cancer patients who undergo neoadjuvant chemoradiotherapy. Finally, it discusses the roles of CTC subtypes and CTCs combined with clinicopathological factors in establishing a multimarker model for predicting CRC recurrence.

Time trend analysis of Injury Severity score of adult trauma patients with emergent CT examination

PURPOSE

Controversy exists about whole-body computed tomography (CT) as a primary screening modality for suspected multiple trauma patients. Therefore, the aim of this study was to analyze time trends of CT examinations for trauma patients in relation to the Injury Severity Score (ISS).

METHODS

We retrospectively analyzed 561 adult trauma patients (mean age = 54 years) who were admitted to the trauma room of our hospital, immediately followed by a CT examination, in 2009, 2013 und 2017. Review of electronic patient charts was performed to determine the cause of injury. ISS was either calculated upon hospital charts and CT imaging reports or documented in the TraumaRegister DGU® for trauma patients with ICU treatment or ISS ≥ 16.

RESULTS

An increasing number of CT examinations of acute trauma patients were performed at our hospital with 117 patients in 2009 compared to 192 in 2013 and 252 in 2017. Their mean age increased (50 years in 2009, 54 in 2013 and 55 in 2017;p = 0.046), whereas their mean ISS decreased over time (15.2 in 2009 compared to 12.1 in 2013 and 10.6 in 2017;p = 0.001), especially in women (15.1 in 2009, 11.8 in 2013 and 7.4 in 2017;p = 0.001 both), younger age groups (18 to 24 years:15.6 in 2009, 6.5 in 2013 and 8.9 in 2017; p = 0.033 and 25 to 49 years:15.0 in 2009, 11.2 in 2013 and 8.3 in 2017;p = 0.001) as well as motor vehicle collision (MVC) victims (16.2 in 2009, 11.8 in 2013 and 6.1 in 2017; p < 0.001). Trauma patients with a high ISS were especially more likely of older age (OR 1.02,p < 0.001) and with the type of incident being a fall (< 3 m: OR3.84,p < 0.001;>3 m: OR6.22,p < 0.001) compared to MVC.

CONCLUSION

Previous studies suggesting a benefit of primary whole-body CT for trauma patients might not reflect the current patient population with decreasing ISS. Especially females, younger age groups and MVC patients might benefit from stricter selection criteria for receiving whole-body CT. Our results also emphasize the importance of prevention of fall or tumble for elderly people.

T1-mapping characterization of two tumor types

T1 mapping is a quantitative method to characterize tissues with magnetic resonance imaging in a quick and efficient manner. It utilizes the relaxation rate of protons to depict the underlying structures within the imaging frame. While T1-mapping techniques are used with some frequency in areas such as cardiac imaging, their application for understanding malignancies and identifying tumor structures has yet to be thoroughly investigated. Utilizing a saturation recovery method to acquire T1 maps for two different tumor models has revealed that longitudinal relaxation mapping is sensitive enough to distinguish between normal and malignant tissue. This is seen even with decreased signal/noise ratios using small voxel sizes to obtain high-resolution images. In both tumor models, it was revealed that relaxation mapping recorded significantly different relaxation values between regions encapsulating the tumor, muscle, kidney, or spleen, as well as between the cell lines themselves. This indicates a potential future application of relaxation mapping as a method to fingerprint various stages of tumor development and may prove a useful measure to identify micro-metastases.

Pediatric Carotid Injury after Blunt Trauma and the Necessity of CT and CTA-A Narrative Literature Review

Background: Blunt carotid injury (BCI) in pediatric trauma is quite rare. Due to the low number of cases, only a few reports and studies have been conducted on this topic. This review will discuss how frequent BCI/blunt cerebrovascular injury (BCVI) on pediatric patients after blunt trauma is, what routine diagnostics looks like, if a computed tomography (CT)/computed tomography angiography (CTA) scan on pediatric patients after blunt trauma is always necessary and if there are any negative health effects. Methods: This narrative literature review includes reviews, systematic reviews, case reports and original studies in the English language between 1999 and 2020 that deal with pediatric blunt trauma and the diagnostics of BCI and BCVI. Furthermore, publications on the risk of radiation exposure for children were included in this study. For literature research, Medline (PubMed) and the Cochrane library were used. Results: Pediatric BCI/BCVI shows an overall incidence between 0.03 and 0.5% of confirmed BCI/BCVI cases due to pediatric blunt trauma. In total, 1.1-3.5% of pediatric blunt trauma patients underwent CTA to detect BCI/BCVI. Only 0.17-1.2% of all CTA scans show a positive diagnosis for BCI/BCVI. In children, the median volume CT dose index on a non-contrast head CT is 33 milligrays (mGy), whereas a computed tomography angiography needs at least 138 mGy. A cumulative dose of about 50 mGy almost triples the risk of leukemia, and a cumulative dose of about 60 mGy triples the risk of brain cancer. Conclusions: Given that a BCI/BCVI could have extensive neurological consequences for children, it is necessary to evaluate routine pediatric diagnostics after blunt trauma. CT and CTA are mostly used in routine BCI/BCVI diagnostics. However, since radiation exposure in children should be as low as reasonably achievable, it should be asked if other diagnostic methods could be used to identify risk groups. Trauma guidelines and clinical scores like the McGovern score are established BCI/BCVI screening options, as well as duplex ultrasound.

Importance of repeated computed tomography on pediatric traumatic acute posterior fossa subdural hematoma: A case study

Traumatic acute posterior fossa subdural hematoma (PFSDH) is a rare and potentially fatal condition in which the progressed hematoma compresses the brainstem or causes secondary hydrocephalus. Hence, vigilant monitoring of clinical and radiological findings is crucial to detect the typical sudden deterioration, which can occur in the early stages. However, managing pediatric PFSDHs poses additional challenges due to risks associated with radiation exposure from repeat computed tomography (CT) examinations, potentially impeding crucial diagnostic insights. Here, we present a rare pediatric case of fatal acute traumatic PFSDH. Despite undergoing a timely initial CT scan that indicated the presence of PFSDH, the patient experienced sudden deterioration 15 h later and eventually died. No follow-up CT examinations were conducted during this critical period. This case underscores the challenges in managing pediatric PFSDHs, particularly concerning the benefits of repeated CT examinations in initially stable patients.

Lung Ultrasonography Accuracy for Diagnosis of Adult Pneumonia: Systematic Review and Meta-Analysis

BACKGROUND

Pneumonia is a ubiquitous health condition with severe outcomes. The advancement of ultrasonography techniques allows its application in evaluating pulmonary diseases, providing safer and accessible bedside therapeutic decisions compared to chest X-ray and chest computed tomography (CT) scan. Because of its aforementioned benefits, we aimed to confirm the diagnostic accuracy of lung ultrasound (LUS) for pneumonia in adults.

METHODS

A systematic literature search was performed of Medline, Cochrane and Crossref, independently by two authors. The selection of studies proceeded based on specific inclusion and exclusion criteria without restrictions to particular study designs, language or publication dates and was followed by data extraction. The gold standard reference in the included studies was chest X-ray/CT scan or both.

RESULTS

Twenty-nine (29) studies containing 6702 participants were included in our meta-analysis. Pooled sensitivity, specificity and PPV were 92% (95% CI: 91-93%), 94% (95% CI: 94 to 95%) and 93% (95% CI: 89 to 96%), respectively. Pooled positive and negative likelihood ratios were 16 (95% CI: 14 to 19) and 0.08 (95% CI: 0.07 to 0.09). The area under the ROC curve of LUS was 0. 9712.

CONCLUSIONS

LUS has high diagnostic accuracy in adult pneumonia. Its contribution could form an optimistic clue in future updates considering this condition.

Predictors of Clinically Important Neuroimaging Findings in Children Presenting Pediatric Emergency Department

OBJECTIVE

The aim of the study is to evaluate predictors of clinically important neuroimaging results, that is, computed tomography and magnetic resonance imaging in children in an academic pediatric emergency department (PED) from 2015 to 2019.

METHODS

This study was conducted in an academic PED. The patient's demographic and clinical characteristics of PED visits and neuroimaging findings requested at the PED were recorded for January 1, 2015, to December 31, 2019. In addition, descriptive statistics and logistic regression analyses were conducted. We described and determined the predictors of clinically important neuroimaging findings in children.

RESULTS

Clinically important neuroimaging findings were detected in patients with blurred vision ( P = 0.001), ataxia ( P = 0.003), unilateral weakness ( P = 0.004), and altered level of consciousness ( P = 0.026). Clinically important neuroimaging was found 9.4 times higher in patients with altered level of consciousness, 7.4 times higher in patients with focal weakness, 4.6 times higher in patients with blurred vision, and 3.5 times more in patients presenting with ataxia.

CONCLUSIONS

Advanced neuroimaging, especially for selected patients in PED, can improve the quality of health care for patients. On the other hand, irrelevant neuroimaging findings can lead physicians away from prompt diagnosis and accurate management. According to our study, advanced neuroimaging can be performed in the early period for both diagnosis and early treatment, especially in selected patients with ataxia, blurred vision, altered consciousness, and unilateral weakness. In other cases, clinicians may find more supporting evidence.

Subjective and objective image quality of low-dose CT images processed using a self-supervised denoising algorithm

This study aimed to assess the subjective and objective image quality of low-dose computed tomography (CT) images processed using a self-supervised denoising algorithm with deep learning. We trained the self-supervised denoising model using low-dose CT images of 40 patients and applied this model to CT images of another 30 patients. Image quality, in terms of noise and edge sharpness, was rated on a 5-point scale by two radiologists. The coefficient of variation, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were calculated. The values for the self-supervised denoising model were compared with those for the original low-dose CT images and CT images processed using other conventional denoising algorithms (non-local means, block-matching and 3D filtering, and total variation minimization-based algorithms). The mean (standard deviation) scores of local and overall noise levels for the self-supervised denoising algorithm were 3.90 (0.40) and 3.93 (0.51), respectively, outperforming the original image and other algorithms. Similarly, the mean scores of local and overall edge sharpness for the self-supervised denoising algorithm were 3.90 (0.40) and 3.75 (0.47), respectively, surpassing the scores of the original image and other algorithms. The CNR and SNR for the self-supervised denoising algorithm were higher than those for the original images but slightly lower than those for the other algorithms. Our findings indicate the potential clinical applicability of the self-supervised denoising algorithm for low-dose CT images in clinical settings.

Understanding the factors that influence CT utilization for mild traumatic brain injury in a low resource setting - a qualitative study using the Theoretical Domains Framework

Introduction

In low resource settings (LRS), utilization of Computed Tomography scan (CTS) for mild traumatic brain injuries (mTBIs) presents unique challenges and considerations given the limited infrastructure, financial resources, and trained personnel. The Theoretical Domains Framework (TDF) offers a comprehensive theoretical lens to explore factors influencing the decision-making to order CTS for mTBI by imaging referrers (IRs).

Objectives

The primary objective was to explore IRs' beliefs about factors influencing CT utilization in mTBIs using TDF in Uganda.Differences in the factors influencing CTS ordering behavior across specialties, levels of experience, and hospital category were also explored.

Materials and Methods

In-depth semi-structured interviews guided by TDF were conducted among purposively selected IRs from 6 tertiary public and private hospitals with functional CTS services. A thematic analysis was performed with codes and emerging themes developed based on the TDF.

Results

Eleven IRs including medical officers, non-neurosurgeon specialists and neurosurgeons aged on average 42 years (SD+/-12.3 years) participated.Identified factors within skills domain involved IRs' clinical assessment and decision-making abilities, while beliefs about capabilities and consequences encompassed their confidence in diagnostic abilities and perceptions of CTS risks and benefits. The environmental context and resources domain addressed the availability of CT scanners and financial constraints. The knowledge domain elicited IRs' understanding of clinical guidelines and evidence-based practices while social influences considered peer influence and institutional culture. For memory, attention & decision processes domain, IRs adherence to guidelines and intentions to order CT scans were cited.

Conclusion

Using TDF, IRs identified several factors believed to influence decision making to order CTS in mTBI in a LRS. The findings can inform stakeholders to develop targeted strategies and evidence-based interventions to optimize CT utilization in mTBI such as; educational programs, workflow modifications, decision support tools, and infrastructure improvements, among others.

Unsupervised low-dose CT denoising using bidirectional contrastive network

BACKGROUND AND OBJECTIVE

Low-dose computed tomography (LDCT) scans significantly reduce radiation exposure, but introduce higher levels of noise and artifacts that compromise image quality and diagnostic accuracy. Supervised learning methods have proven effective in denoising LDCT images, but are hampered by the need for large, paired datasets, which pose significant challenges in data acquisition. This study aims to develop a robust unsupervised LDCT denoising method that overcomes the reliance on paired LDCT and normal-dose CT (NDCT) samples, paving the way for more accessible and practical denoising techniques.

METHODS

We propose a novel unsupervised network model, Bidirectional Contrastive Unsupervised Denoising (BCUD), for LDCT denoising. This model innovatively combines a bidirectional network structure with contrastive learning theory to map the precise mutual correspondence between the noisy LDCT image domain and the clean NDCT image domain. Specifically, we employ dual encoders and discriminators for domain-specific data generation, and use unique projection heads for each domain to adaptively learn customized embedded representations. We then align corresponding features across domains within the learned embedding spaces to achieve effective noise reduction. This approach fundamentally improves the model's ability to match features in latent space, thereby improving noise reduction while preserving fine image detail.

RESULTS

Through extensive experimental validation on the AAPM-Mayo public dataset and real-world clinical datasets, the proposed BCUD method demonstrated superior performance. It achieved a peak signal-to-noise ratio (PSNR) of 31.387 dB, a structural similarity index measure (SSIM) of 0.886, an information fidelity criterion (IFC) of 2.305, and a visual information fidelity (VIF) of 0.373. Notably, subjective evaluation by radiologists resulted in a mean score of 4.23, highlighting its advantages over existing methods in terms of clinical applicability.

CONCLUSIONS

This paper presents an innovative unsupervised LDCT denoising method using a bidirectional contrastive network, which greatly improves clinical applicability by eliminating the need for perfectly matched image pairs. The method sets a new benchmark in unsupervised LDCT image denoising, excelling in noise reduction and preservation of fine structural details.

Diagnostic performance and image quality of an image-based denoising algorithm applied to radiation dose-reduced CT in diagnosing acute appendicitis

PURPOSE

To evaluate diagnostic performance and image quality of ultralow-dose CT (ULDCT) in diagnosing acute appendicitis with an image-based deep-learning denoising algorithm (IDLDA).

METHODS

This retrospective multicenter study included 180 patients (mean ± standard deviation, 29 ± 9 years; 91 female) who underwent contrast-enhanced 2-mSv CT for suspected appendicitis from February 2014 to August 2016. We simulated ULDCT from 2-mSv CT, reducing the dose by at least 50%. Then we applied an IDLDA on ULDCT to produce denoised ULDCT (D-ULDCT). Six radiologists with different experience levels (three board-certified radiologists and three residents) independently reviewed the ULDCT and D-ULDCT. They rated the likelihood of appendicitis and subjective image qualities (subjective image noise, diagnostic acceptability, and artificial sensation). One radiologist measured image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). We used the receiver operating characteristic (ROC) analyses, Wilcoxon's signed-rank tests, and paired t-tests.

RESULTS

The area under the ROC curves (AUC) for diagnosing appendicitis ranged 0.90-0.97 for ULDCT and 0.94-0.97 for D-ULDCT. The AUCs of two residents were significantly higher on D-ULDCT (AUC difference = 0.06 [95% confidence interval, 0.01-0.11; p = .022] and 0.05 [0.00-0.10; p = .046], respectively). D-ULDCT provided better subjective image noise and diagnostic acceptability to all six readers. However, the response of board-certified radiologists and residents differed in artificial sensation (all p ≤ .003). D-ULDCT showed significantly lower image noise, higher SNR, and higher CNR (all p < .001).

CONCLUSION

An IDLDA can provide better ULDCT image quality and enhance diagnostic performance for less-experienced radiologists.

Effects of long-term X-ray exposure on CBC among radiological department staff in Sulaimani city

Objectives

Ionizing rays used in radiology devices are believed to affect the body tissues of radiology department employees. This study was aimed at comparing the effects of long-term exposure to X-rays on the blood cells of staff working in the radiology departments of several hospitals in the Sulaimani City/Kurdistan region government.

Methods

This cross-sectional study was conducted from 2021 to 2022 on 250 employees-including radiologists, radiographers, and other medical staff such as physicians or nurses-in the radiology departments of hospitals in the city of Sulaimani, Kurdistan region government. Data were collected with a questionnaire completed by the participants after verbal consent was provided. Blood samples were collected from 250 radiology staff and sent to a laboratory for measurement of blood parameters. The collected data were analyzed in SPSS version 26 software, and relationships in the data were investigated with descriptive statistical tests, Student's t test, and ANOVA.

Results

Most male participants were radiographers with a diploma degree. A statistically significant difference in RBC, HCT %, MCV, and PCT blood parameters was observed between sexes. Moreover, statistically significant differences were observed in RDW-CV and RDW-SD between occupational groups; in mean WBC and lymphocytes among staff who were current, never, or former smokers; and in mean WBC among employees who were current, never, or former drinkers (p < 0.01).

Conclusion

Blood parameters such as RDW-CV and RDW-SD were concluded to be affected by job type and X-ray exposure duration.

Brain tumor detection with integrating traditional and computational intelligence approaches across diverse imaging modalities - Challenges and future directions

Brain tumor segmentation and classification play a crucial role in the diagnosis and treatment planning of brain tumors. Accurate and efficient methods for identifying tumor regions and classifying different tumor types are essential for guiding medical interventions. This study comprehensively reviews brain tumor segmentation and classification techniques, exploring various approaches based on image processing, machine learning, and deep learning. Furthermore, our study aims to review existing methodologies, discuss their advantages and limitations, and highlight recent advancements in this field. The impact of existing segmentation and classification techniques for automated brain tumor detection is also critically examined using various open-source datasets of Magnetic Resonance Images (MRI) of different modalities. Moreover, our proposed study highlights the challenges related to segmentation and classification techniques and datasets having various MRI modalities to enable researchers to develop innovative and robust solutions for automated brain tumor detection. The results of this study contribute to the development of automated and robust solutions for analyzing brain tumors, ultimately aiding medical professionals in making informed decisions and providing better patient care.

A multipurpose, adolescent idiopathic scoliosis-specific, short MRI protocol: A feasibility study in volunteers

INTRODUCTION

Visualization of scoliosis typically requires ionizing radiation (radiography and CT) to visualize bony anatomy. MRI is often additionally performed to screen for neural axis abnormalities. We propose a 14-minutes radiation-free scoliosis-specific MRI protocol, which combines MRI and MRI-based synthetic CT images to visualize soft and osseous structures in one examination. We assess the ability of the protocol to visualize landmarks needed to detect 3D patho-anatomical changes, screen for neural axis abnormalities, and perform surgical planning and navigation.

METHODS

18 adult volunteers were scanned on 1.5 T MR-scanner using 3D T2-weighted and synthetic CT sequences. A predefined checklist of relevant landmarks was used for the parameter assessment by three readers. Parameters included Cobb angles, rotation, torsion, segmental height, area and centroids of Nucleus Pulposus and Intervertebral Disc. Precision, reliability and agreement between the readers measurements were evaluated.

RESULTS

91 % of Likert-based questions scored ≥ 4, indicating moderate to high confidence. Precision of 3D dot positioning was 1.0 mm. Precision of angle measurement was 0.6° (ICC 0.98). Precision of vertebral and IVD height measurements was 0.4 mm (ICC 0.99). Precision of area measurement for NP was 8 mm2 (ICC 0.55) and for IVD 18 mm2 (ICC 0.62) for IVD. Precision of centroid measurement for NP was 1.3 mm (ICC 0.88-0.92) and for IVD 1.1 mm (ICC 0.88-91).

CONCLUSIONS

The proposed MRI protocol with synthetic CT reconstructions, has high precision, reliability and agreement between the readers for multiple scoliosis-specific measurements. It can be used to study scoliosis etiopathogenesis and to assess 3D spinal morphology.

Appropriateness and imaging outcomes of ultrasound, CT, and MR in the emergency department: a retrospective analysis from an urban academic center

PURPOSE

To evaluate the appropriateness and outcomes of ultrasound (US), computed tomography (CT), and magnetic resonance (MR) orders in the ED.

METHODS

We retrospectively reviewed consecutive US, CT, and MR orders for adult ED patients at a tertiary care urban academic center from January to March 2019. The American College of Radiology Appropriateness Criteria (ACRAC) guidelines were primarily used to classify imaging orders as "appropriate" or "inappropriate". Two radiologists in consensus judged specific clinical scenarios that were unavailable in the ACRAC. Final imaging reports were compared with the initial clinical suspicion for imaging and categorized into "normal", "compatible with initial diagnosis", "alternative diagnosis", or "inconclusive". The sample was powered to show a prevalence of inappropriate orders of 30% with a margin of error of 5%.

RESULTS

The rate of inappropriate orders was 59.4% for US, 29.1% for CT, and 33.3% for MR. The most commonly imaged systems for each modality were neuro (130/330) and gastrointestinal (95/330) for CT, genitourinary (132/330) and gastrointestinal (121/330) for US, neuro (273/330) and gastrointestinal (37/330) for MR. Compared to inappropriately ordered tests, the final reports of appropriate orders were nearly three times more likely to demonstrate findings compatible with the initial diagnosis for all modalities: US (45.5 vs. 14.3%, p < 0.001), CT (46.6 vs. 14.6%, p < 0.001), and MR (56.3 vs. 21.8%, p < 0.001). Inappropriate orders were more likely to show no abnormalities compared to appropriate orders: US (65.8 vs. 38.8%, p < 0.001), CT (62.5 vs. 34.2%, p < 0.001), and MR (61.8 vs. 38.7%, p < 0.001).

CONCLUSION

The prevalence of inappropriate imaging orders in the ED was 59.4% for US, 29.1% for CT, and 33.3% for MR. Appropriately ordered imaging was three times more likely to yield findings compatible with the initial diagnosis across all modalities.

Detection of urinary tract stones on submillisievert abdominopelvic CT imaging with deep-learning image reconstruction algorithm (DLIR)

PURPOSE

Urolithiasis is a chronic condition that leads to repeated CT scans throughout the patient's life. The goal was to assess the diagnostic performance and image quality of submillisievert abdominopelvic computed tomography (CT) using deep learning-based image reconstruction (DLIR) in urolithiasis.

METHODS

57 patients with suspected urolithiasis underwent both non-contrast low-dose (LD) and ULD abdominopelvic CT. Raw image data of ULD CT were reconstructed using hybrid iterative reconstruction (ASIR-V 70%) and high-strength-level DLIR (DLIR-H). The performance of ULD CT for the detection of urinary stones was assessed by two readers and compared with LD CT with ASIR-V 70% as a reference standard. Image quality was assessed subjectively and objectively.

RESULTS

266 stones were detected in 38 patients. Mean effective dose was 0.59 mSv for ULD CT and 1.96 mSv for LD CT. For diagnostic performance, sensitivity and specificity were 89% and 94%, respectively, for ULDCT with DLIR-H. There was an almost perfect intra-observer concordance on ULD CT with DLIR-H versus LDCT with ASIR-V 70% (ICC = 0.90 and 0.90 for the two readers). Image noise was significantly lower and signal-to-noise ratio significantly higher with DLIR-H compared to ASIR-V 70%. Subjective image quality was also significantly better with ULDCT with DLIR-H.

CONCLUSION

ULD CT with Deep Learning Image Reconstruction maintains a good diagnostic performance in urolithiasis, with better image quality than hybrid iterative reconstruction and a significant radiation dose reduction.

Radiation protection in CT-guided interventions: does real-time dose visualisation lead to a reduction in radiation dose to participating radiologists? A single-centre evaluation

AIM

To evaluate if real-time dose visualisation during computed tomography (CT)-guided interventions leads to a reduction in radiation dose to participating radiologists.

MATERIALS AND METHODS

The individual radiation dose radiologists are exposed to during CT interventions was measured using dedicated dosimeters (RaySafe i2-system, Unfors RaySafe GmbH, Billdal, Sweden) worn over the usual radiation protective apron. Initially, only the total radiation dose was measured, without visualisation (control group). In the following study period, the radiation dose was shown to participants on a live screen in real-time (experimental group). In both groups, the dose was recorded in 1-second intervals. The results collected were evaluated by comparison using descriptive statistics and mixed-effect models. In particular, the variables experience, gender, role, and position during the intervention were analysed.

RESULTS

In total, 517 measurements of 304 interventions (n=249 with and n=268 without live screen) performed by 29 radiologists acting as interventionalists or assistants were analysed. All CT-guided interventions were performed percutaneously, the majority of which (n=280) were microwave ablations (MWA). Radiation doses in the group without visualisation were comparable with usual dose rates for the corresponding intervention type. The mean total radiation dose was reduced by 58.1% (11.6 versus 4.86 μSv) in the experimental group (p=0.034). The highest reduction of 78.5% (15.55 versus 3.35 μSv) was observed in radiologists with the role of assistant (p=0.002). Sub-analysis showed significant dose reduction (p<0.0001) for the use of live screen in general; considering all variables, the role "assistant" alone had a statistically significant influence (p=0.002).

CONCLUSION

The real-time visualisation of active radiation dose during CT interventions leads to a relevant reduction in radiation dose to participating radiologists.

Capturing anatomy in computed tomography scans for genital pathology

PURPOSE

In this cross-sectional study, we aimed to characterize how frequently the anatomy of interest (AOI) was excluded when evaluating genital pathology using the current CT pelvis protocol recommended by the American College of Radiology and evaluate how AOI exclusion affects patient management.

METHODS

We retrospectively reviewed medical records, using diagnosis and CPT codes, of patients admitted with genital pathology who obtained a CT scan at our institution from July 1, 2020-April 30, 2023. Baseline patient demographics were included. Data about each index CT scan (scan obtained at our institution) were recorded and assessed for exclusion of the AOI. Statistical analysis was performed to determine the rate of AOI exclusion and to compare patient management between patients with AOI excluded versus those without AOI exclusion.

RESULTS

113 presentations for genital pathology included an index CT scan and were included for analysis. Patients were primarily men (98%) with a mean age of 53.1 years (SD 13.9). The most common diagnoses were Fournier's gangrene (35%), scrotal abscess (22%) and unspecified infection (19%). 26/113 scans (23%) did not capture the entire AOI. When the AOI was missed during the index scan, there was a higher rate of obtaining additional scans (38% vs. 21%), but a similar rate of intervention (77% vs. 63%) when compared to index scans that captured the entire AOI. 35 scans (31%) had protocol-extending instructions; index scans that captured the entire AOI were more likely to have specific protocol-extending instructions (38% vs. 8% p < 0.01).

CONCLUSIONS

Creating a specific CT protocol for genital pathology could decrease the amount of inappropriate irradiation and improve AOI capture rates without relying on specific request for protocol deviation.

A Primer for Utilizing Deep Learning and Abdominal MRI Imaging Features to Monitor Autosomal Dominant Polycystic Kidney Disease Progression

Abdominal imaging of autosomal dominant polycystic kidney disease (ADPKD) has historically focused on detecting complications such as cyst rupture, cyst infection, obstructing renal calculi, and pyelonephritis; discriminating complex cysts from renal cell carcinoma; and identifying sources of abdominal pain. Many imaging features of ADPKD are incompletely evaluated or not deemed to be clinically significant, and because of this, treatment options are limited. However, total kidney volume (TKV) measurement has become important for assessing the risk of disease progression (i.e., Mayo Imaging Classification) and predicting tolvaptan treatment's efficacy. Deep learning for segmenting the kidneys has improved these measurements' speed, accuracy, and reproducibility. Deep learning models can also segment other organs and tissues, extracting additional biomarkers to characterize the extent to which extrarenal manifestations complicate ADPKD. In this concept paper, we demonstrate how deep learning may be applied to measure the TKV and how it can be extended to measure additional features of this disease.

Global Trends in Kidney Stone Awareness: A Time Series Analysis from 2004-2023

BACKGROUND

Despite the prevalence and incidence of kidney stones progressively increasing worldwide, public awareness of this condition remains unclear. Understanding trends of awareness can assist healthcare professionals and policymakers in planning and implementing targeted health interventions. This study investigated online search interest in "kidney stone" by analyzing Google Trends, focusing on stationarity of the trends and predicting future trends.

METHODS

We performed time series analysis on worldwide Google monthly search data from January 2004 to November 2023. The Augmented Dickey-Fuller (ADF) test was used to assess the stationarity of the data, with a p-value below 0.05 indicating stationarity. Time series forecasting was performed using the autoregressive integrated moving average to predict future trends.

RESULTS

The highest search interest for "kidney stone" (score 100) was in August 2022, while the lowest was in December 2007 (score 36). As of November 2023, search interest remained high, at 92. The ADF test was significant (p = 0.023), confirming data stationarity. The time series forecasting projected continued high public interest, likely reflecting ongoing concern and awareness. Notably, diverse regions such as Iran, the Philippines, Ecuador, the United States, and Nepal showed significant interest, suggesting widespread awareness of nephrolithiasis.

CONCLUSION

This study highlighted that "kidney stone" is a consistently relevant health issue globally. The increase and stationarity of search trends, the forecasted sustained interest, and diverse regional interest emphasize the need for collaborative research and educational initiatives. This study's analysis serves as a valuable tool for shaping future healthcare policies and research directions in addressing nephrolithiasis related health challenges.

Implementation of lung ultrasonography by general practitioners for lower respiratory tract infections: a feasibility study

OBJECTIVE

To evaluate the feasibility of lung ultrasonography (LUS) performed by novice users' general practitioners (GPs) in diagnosing lower respiratory tract infections (LRTIs) in primary health care settings.

DESIGN

A prospective interventional multicenter study (December 2019-March 2020).

SETTINGS AND SUBJECTS

Patients aged >3 months, suspected of having LRTI consulting in three different general practices (GPs) (rural, semirural and urban) in France.

MAIN OUTCOME MEASURES

Feasibility of LUS by GPs was assessed by (1) the proportion of patients where LUS was not performed, (2) technical breakdowns, (3) interpretability of images by GPs, (4) examination duration and (5) patient perception and acceptability.

RESULTS

A total of 151 patients were recruited, and GPs performed LUS for 111 (73.5%) patients (LUS group). In 99.1% (n = 110) of cases, GPs indicated that they were able to interpret images. The median [IQR] exam duration was 4 [3-5] minutes. LRTI was diagnosed in 70.3% and 60% of patients in the LUS and no-LUS groups, respectively (p = .43). After LUS, GPs changed their diagnosis from 'other' to 'LRTI' in six cases (+5.4%, p < .001), prescribed antibiotics for five patients (+4.5%, p = .164) and complementary chest imaging for 10 patients (+9%, p < .001). Patient stress was reported in 1.8% of cases, 81.7% of patients declared that they better understood the diagnosis, and 82% of patients thought that the GP diagnosis was more reliable after LUS.

CONCLUSIONS

LUS by GPs using handheld devices is a feasible diagnostic tool in primary health care for LRTI symptoms, demonstrating both effectiveness and positive patient reception.

TRIAL REGISTRATION NUMBER

Clinicaltrial.gov: NCT04602234, 20/10/2020.

Medical radiation exposure in inflammatory bowel disease: an updated meta-analysis

BACKGROUND

There have been previous studies and earlier systematic review on the relationship between inflammatory bowel disease (IBD) and radiation exposure. With the diversification of current test methods, this study intended to conduct a meta-analysis to evaluate the IBD radiation exposure in recent years.

METHODS

Three databases (PUBMED, EMBASE, and MEDICINE) for relevant literature up to May 1, 2023 were searched. The statistical data meeting requirements were collated and extracted.

RESULTS

20 papers were enrolled. The overall high radiation exposure rate was 15% (95% CI = [12%, 19%]) for CD and 5% (95% CI = [3%, 7%]) for UC. The pooled result found that high radiation exposure rate was 3.44 times higher in CD than in UC (OR = 3.44, 95% CI = [2.35, 5.02]). Moreover, the average radiation exposure level in CD was 12.77 mSv higher than that in UC (WMD = 12.77, 95% CI = [9.93, 15.62] mSv). Furthermore, radiation exposure level of CD after 2012 was higher than those before 2012 (26.42 ± 39.61vs. 23.76 ± 38.46 mSv, P = 0.016), while UC did not show similar result (11.99 ± 27.66 vs. 10.01 ± 30.76 mSv, P = 0.1). Through subgroup analysis, it was found that disease duration (WMD = 2.75, 95% CI = [0.10, 5.40] mSv), complications (OR = 5.09, 95% CI = [1.50, 17.29]), and surgical history (OR = 5.46, 95% CI = [1.51, 19.69]) significantly increased the proportion of high radiation exposure.

CONCLUSION

This study found that radiation exposure level of IBD patients was high, which revealed the radiation risk in the process of diagnosis and treatment of IBD patients. In the future, longer follow-up and prospective studies are needed to reveal the relationship between high radiation exposure and solid tumorigenesis.

Abdominal image quality and dose reduction with energy-integrating or photon-counting detectors dual-source CT: A phantom study

PURPOSE

The purpose of this study was to assess image-quality and dose reduction potential using a photon-counting computed tomography (PCCT) system by comparison with two different dual-source CT (DSCT) systems using two phantoms.

MATERIALS AND METHODS

Acquisitions on phantoms were performed using two DSCT systems (DSCT1 [Somatom Force] and DSCT2 [Somatom Pro.Pulse]) and one PCCT system (Naeotom Alpha) at four dose levels (13/6/3.4/1.8 mGy). Noise power spectrum (NPS) and task-based transfer function (TTF) were computed to assess noise magnitude and noise texture and spatial resolution (f50), respectively. Detectability indexes (d') were computed to model the detection of abdominal lesions: one unenhanced high-contrast task, one contrast-enhanced high-contrast task and one unenhanced low-contrast task. Image quality was subjectively assessed on an anthropomorphic phantom by two radiologists.

RESULTS

For all dose levels, noise magnitude values were lower with PCCT than with DSCTs. For all CT systems, similar noise texture values were found at 13 and 6 mGy, but the greatest noise texture values were found for DSCT2 and the lowest for PCCT at 3.4 and 1.8 mGy. For high-contrast inserts, similar or lower f50 values were found with PCCT than with DSCT1 and the opposite pattern was found for the low-contrast insert. For the three simulated lesions, d' values were greater with PCCT than with DSCTs. Abdominal images were rated satisfactory for clinical use by the radiologists for all dose levels with PCCT and for 13 and 6 mGy with DSCTs.

CONCLUSION

By comparison with DSCTs, PCCT reduces image-noise and improves detectability of simulated abdominal lesions without altering the spatial resolution and image texture. Image-quality obtained with PCCT seem to indicate greater potential for dose optimization than those obtained with DSCTs.

Patient-derived PixelPrint phantoms for evaluating clinical imaging performance of a deep learning CT reconstruction algorithm

Objective. Deep learning reconstruction (DLR) algorithms exhibit object-dependent resolution and noise performance. Thus, traditional geometric CT phantoms cannot fully capture the clinical imaging performance of DLR. This study uses a patient-derived 3D-printed PixelPrint lung phantom to evaluate a commercial DLR algorithm across a wide range of radiation dose levels.Method. The lung phantom used in this study is based on a patient chest CT scan containing ground glass opacities and was fabricated using PixelPrint 3D-printing technology. The phantom was placed inside two different size extension rings to mimic a small- and medium-sized patient and was scanned on a conventional CT scanner at exposures between 0.5 and 20 mGy. Each scan was reconstructed using filtered back projection (FBP), iterative reconstruction, and DLR at five levels of denoising. Image noise, contrast to noise ratio (CNR), root mean squared error, structural similarity index (SSIM), and multi-scale SSIM (MS SSIM) were calculated for each image.Results.DLR demonstrated superior performance compared to FBP and iterative reconstruction for all measured metrics in both phantom sizes, with better performance for more aggressive denoising levels. DLR was estimated to reduce dose by 25%-83% in the small phantom and by 50%-83% in the medium phantom without decreasing image quality for any of the metrics measured in this study. These dose reduction estimates are more conservative compared to the estimates obtained when only considering noise and CNR.Conclusion. DLR has the capability of producing diagnostic image quality at up to 83% lower radiation dose, which can improve the clinical utility and viability of lower dose CT scans. Furthermore, the PixelPrint phantom used in this study offers an improved testing environment with more realistic tissue structures compared to traditional CT phantoms, allowing for structure-based image quality evaluation beyond noise and contrast-based assessments.

TEAM participation in the irradiation of IROC phantoms for cooperative group clinical trials

The participation of radiation oncology team members in the irradiation of Imaging and Radiation Oncology Core (IROC) phantom for cooperative group clinical trials is essential to comply with the latest quality management philosophy. Medical dosimetrists are expected to develop treatment plans for the irradiation of IROC phantoms. For advanced treatment techniques, such as three-dimensional conformal radiation therapy (3DCRT), intensity-modulated radiation therapy (IMRT), and volumetric-modulated arc therapy (VMAT), the irradiation of the IROC phantoms serves as quality audit. If successful, the irradiation processes demonstrate that the institution has the knowledge of the protocol, and has the appropriate equipment to comply with the protocol requirements. This article describes three IROC phantoms used for credentialing external beam photon beam therapy, delivered using conventional medical linear accelerators, to the medical dosimetry community. Guidance and strategies for the development of treatment plans are discussed. Our institutional irradiation of the three IROC phantoms, delivered using the Truebeam medical linear accelerator, resulted in consistent dose accuracy to within ±1%. The participation of the team members may reduce the overall published failing rate stated to be about one-third of all participating institutions.

Which is a real valuable screening tool for lung cancer and measure thoracic diseases, chest radiography or low-dose computed tomography?: A review on the current status of Japan and other countries

Chest radiography (CR) has been used as a screening tool for lung cancer and the use of low-dose computed tomography (LDCT) is not recommended in Japan. We need to reconsider whether CR really contributes to the early detection of lung cancer. In addition, we have not well discussed about other major thoracic disease detection by CR and LDCT compared with lung cancer despite of its high frequency. We review the usefulness of CR and LDCT as veridical screening tools for lung cancer and other thoracic diseases. In the case of lung cancer, many studies showed that LDCT has capability of early detection and improving outcomes compared with CR. Recent large randomized trial also supports former results. In the case of chronic obstructive pulmonary disease (COPD), LDCT contributes to early detection and leads to the implementation of smoking cessation treatments. In the case of pulmonary infections, LDCT can reveal tiny inflammatory changes that are not observed on CR, though many of these cases improve spontaneously. Therefore, LDCT screening for pulmonary infections may be less useful. CR screening is more suitable for the detection of pulmonary infections. In the case of cardiovascular disease (CVD), CR may be a better screening tool for detecting cardiomegaly, whereas LDCT may be a more useful tool for detecting vascular changes. Therefore, the current status of thoracic disease screening is that LDCT may be a better screening tool for detecting lung cancer, COPD, and vascular changes. CR may be a suitable screening tool for pulmonary infections and cardiomegaly.

PECARN prediction rules for CT imaging of children presenting to the emergency department with blunt abdominal or minor head trauma: a multicentre prospective validation study

BACKGROUND

The intra-abdominal injury and traumatic brain injury prediction rules derived by the Pediatric Emergency Care Applied Research Network (PECARN) were designed to reduce inappropriate use of CT in children with abdominal and head trauma, respectively. We aimed to validate these prediction rules for children presenting to emergency departments with blunt abdominal or minor head trauma.

METHODS

For this prospective validation study, we enrolled children and adolescents younger than 18 years presenting to six emergency departments in Sacramento (CA), Dallas (TX), Houston (TX), San Diego (CA), Los Angeles (CA), and Oakland (CA), USA between Dec 27, 2016, and Sept 1, 2021. We excluded patients who were pregnant or had pre-existing neurological disorders preventing examination, penetrating trauma, injuries more than 24 h before arrival, CT or MRI before transfer, or high suspicion of non-accidental trauma. Children presenting with blunt abdominal trauma were enrolled into an abdominal trauma cohort, and children with minor head trauma were enrolled into one of two age-segregated minor head trauma cohorts (younger than 2 years vs aged 2 years and older). Enrolled children were clinically examined in the emergency department, and CT scans were obtained at the attending clinician's discretion. All enrolled children were evaluated against the variables of the pertinent PECARN prediction rule before CT results were seen. The primary outcome of interest in the abdominal trauma cohort was intra-abdominal injury undergoing acute intervention (therapeutic laparotomy, angiographic embolisation, blood transfusion, intravenous fluid for ≥2 days for pancreatic or gastrointestinal injuries, or death from intra-abdominal injury). In the age-segregated minor head trauma cohorts, the primary outcome of interest was clinically important traumatic brain injury (neurosurgery, intubation for >24 h for traumatic brain injury, or hospital admission ≥2 nights for ongoing symptoms and CT-confirmed traumatic brain injury; or death from traumatic brain injury).

FINDINGS

7542 children with blunt abdominal trauma and 19 999 children with minor head trauma were enrolled. The intra-abdominal injury rule had a sensitivity of 100·0% (95% CI 98·0-100·0; correct test for 145 of 145 patients with intra-abdominal injury undergoing acute intervention) and a negative predictive value (NPV) of 100·0% (95% CI 99·9-100·0; correct test for 3488 of 3488 patients without intra-abdominal injuries undergoing acute intervention). The traumatic brain injury rule for children younger than 2 years had a sensitivity of 100·0% (93·1-100·0; 42 of 42) for clinically important traumatic brain injuries and an NPV of 100·0%; 99·9-100·0; 2940 of 2940), whereas the traumatic brain injury rule for children aged 2 years and older had a sensitivity of 98·8% (95·8-99·9; 168 of 170) and an NPV of 100·0% (99·9-100·0; 6015 of 6017). The two children who were misclassified by the traumatic brain injury rule were admitted to hospital for observation but did not need neurosurgery.

INTERPRETATION

The PECARN intra-abdominal injury and traumatic brain injury rules were validated with a high degree of accuracy. Their implementation in paediatric emergency departments can therefore be considered a safe strategy to minimise inappropriate CT use in children needing high-quality care for abdominal or head trauma.

FUNDING

The Eunice Kennedy Shriver National Institute of Child Health and Human Development.

FSformer: A combined frequency separation network and transformer for LDCT denoising

Low-dose computed tomography (LDCT) has been widely concerned in the field of medical imaging because of its low radiation hazard to humans. However, under low-dose radiation scenarios, a large amount of noise/artifacts are present in the reconstructed image, which reduces the clarity of the image and is not conducive to diagnosis. To improve the LDCT image quality, we proposed a combined frequency separation network and Transformer (FSformer) for LDCT denoising. Firstly, FSformer decomposes the LDCT images into low-frequency images and multi-layer high-frequency images by frequency separation blocks. Then, the low-frequency components are fused with the high-frequency components of different layers to remove the noise in the high-frequency components with the help of the potential texture of low-frequency parts. Next, the estimated noise images can be obtained by using Transformer stage in the frequency aggregation denoising block. Finally, they are fed into the reconstruction prediction block to obtain improved quality images. In addition, a compound loss function with frequency loss and Charbonnier loss is used to guide the training of the network. The performance of FSformer has been validated and evaluated on AAPM Mayo dataset, real Piglet dataset and clinical dataset. Compared with previous representative models in different architectures, FSformer achieves the optimal metrics with PSNR of 33.7714 dB and SSIM of 0.9254 on Mayo dataset, the testing time is 1.825 s. The experimental results show that FSformer is a state-of-the-art (SOTA) model with noise/artifact suppression and texture/organization preservation. Moreover, the model has certain robustness and can effectively improve LDCT image quality.

Novel Deep Learning Denoising Enhances Image Quality and Lowers Radiation Exposure in Interventional Bronchial Artery Embolization Cone Beam CT

OBJECTIVES

In interventional bronchial artery embolization (BAE), periprocedural cone beam CT (CBCT) improves guiding and localization. However, a trade-off exists between 6-second runs (high radiation dose and motion artifacts, but low noise) and 3-second runs (vice versa). This study aimed to determine the efficacy of an advanced deep learning denoising (DLD) technique in mitigating the trade-offs related to radiation dose and image quality during interventional BAE CBCT.

MATERIALS AND METHODS

This study included BMI-matched patients undergoing 6-second and 3-second BAE CBCT scans. The dose-area product values (DAP) were obtained. All datasets were reconstructed using standard weighted filtered back projection (OR) and a novel DLD software. Objective image metrics were derived from place-consistent regions of interest, including CT numbers of the Aorta and lung, noise, and contrast-to-noise ratio. Three blinded radiologists performed subjective assessments regarding image quality, sharpness, contrast, and motion artifacts on all dataset combinations in a forced-choice setup (-1 = inferior, 0 = equal; 1 = superior). The points were averaged per item for a total score. Statistical analysis ensued using a properly corrected mixed-effects model with post hoc pairwise comparisons.

RESULTS

Sixty patients were assessed in 30 matched pairs (age 64 ± 15 years; 10 female). The mean DAP for the 6 s and 3 s runs was 2199 ± 185 µGym² and 1227 ± 90 µGym², respectively. Neither low-dose imaging nor the reconstruction method introduced a significant HU shift (p ≥ 0.127). The 3 s-DLD presented the least noise and superior contrast-to-noise ratio (CNR) (p < 0.001). While subjective evaluation revealed no noticeable distinction between 6 s-DLD and 3 s-DLD in terms of quality (p ≥ 0.996), both outperformed the OR variants (p < 0.001). The 3 s datasets exhibited fewer motion artifacts than the 6 s datasets (p < 0.001).

CONCLUSIONS

DLD effectively mitigates the trade-off between radiation dose, image noise, and motion artifact burden in regular reconstructed BAE CBCT by enabling diagnostic scans with low radiation exposure and inherently low motion artifact burden at short examination times.

The Adelaide Facial Bone Rule: A simple prediction model and clinical guideline for the presence of facial fractures using CT brain scans in victims of minor trauma

BACKGROUND

Facial fractures bleed, resulting in high-density fluid in the sinuses (haemosinus) on computed tomography (CT) scans. A CT brain scan includes most maxillary sinuses in the scan field, which should allow detection of haemosinus as an indirect indicator of a facial fracture without the need for an additional CT facial bone scan, yet no robust evidence for this exists in the literature. The aim of this study was to determine whether the presence of haemosinus on a CT brain scan, alone or in combination with other clinical information, can predict the presence of facial fractures.

METHODS

1231 adult patients, who had both brain and facial CT scans performed on the same day, were selected from a seven year period. Patients were eligible if scans were requested for trauma. Brain and facial scans were reviewed separately for the presence of facial fractures, haemosinus, emphysema and intra-cranial haemorrhage. Prediction modelling was used to assess whether findings from brain scans could be used to identify patients requiring further CT scanning.

FINDINGS

The full prediction model included four predictors and showed excellent discrimination (AUROC 0.982; 95 % CI 0.971 - 0.993). A simplified model, more suitable for clinical implementation, used only facial fractures and haemosinus as predictors. This model showed only marginally poorer discrimination (AUROC 0.964; 95 % CI 0.945 - 0.983) and excellent performance on other measures.

CONCLUSION

Based on the excellent performance of the simplified prediction model, we present the Adelaide Facial Bone Rule: The absence of blood in the sinuses or facial fractures on a CT brain scan means a CT facial bone scan does not need to be routinely performed in the setting of clinically-determined minor trauma.

CT Imaging Computed Tomography/Computed Tomography Angiography/Perfusion in Acute Ischemic Stroke and Vasospasm

Computed tomography (CT), CT angiography (CTA), and CT perfusion (CTP) play crucial roles in the comprehensive evaluation and management of acute ischemic stroke, aneurysmal subarachnoid hemorrhage (SAH), and vasospasm. CTP provides functional data about cerebral blood flow, allowing radiologists, neurointerventionalists, and stroke neurologists to more accurately delineate the volume of core infarct and ischemic penumbra allowing for patient-specific treatment decisions to be made. CTA and CTP are used in tandem to evaluate for vasospasm associated with aneurysmal SAH and can help provide an insight into the physiologic impact of angiographic vasospasm, better triaging patients for medical and interventional treatment.

Optimization of CT pulmonary angiography for pulmonary embolism using task-based image quality assessment and diagnostic reference levels: A multicentric study

PURPOSE

To establish size-specific diagnostic reference levels (DRLs) for pulmonary embolism (PE) based on patient CT examinations performed on 74 CT devices. To assess task-based image quality (IQ) for each device and to investigate the variability of dose and IQ across different CTs. To propose a dose/IQ optimization.

METHODS

1051 CT pulmonary angiography dose data were collected. DRLs were calculated as the 75th percentile of CT dose index (CTDI) for two patient categories based on the thoracic perimeters. IQ was assessed with two thoracic phantom sizes using local acquisition parameters and three other dose levels. The area under the ROC curve (AUC) of a 2 mm low perfused vessel was assessed with a non-prewhitening with eye-filter model observer. The optimal IQ-dose point was mathematically assessed from the relationship between IQ and dose.

RESULTS

The DRLs of CTDIvol were 6.4 mGy and 10 mGy for the two patient categories. 75th percentiles of phantom CTDIvol were 6.3 mGy and 10 mGy for the two phantom sizes with inter-quartile AUC values of 0.047 and 0.066, respectively. After the optimization, 75th percentiles of phantom CTDIvol decreased to 5.9 mGy and 7.55 mGy and the interquartile AUC values were reduced to 0.025 and 0.057 for the two phantom sizes.

CONCLUSION

DRLs for PE were proposed as a function of patient thoracic perimeters. This study highlights the variability in terms of dose and IQ. An optimization process can be started individually and lead to a harmonization of practice throughout multiple CT sites.