Projected cancer risks from computed tomographic scans performed in the United States in 2007

PECARN prediction rule for cervical spine imaging of children presenting to the emergency department with blunt trauma: a multicentre prospective observational study

BACKGROUND

Cervical spine injuries in children are uncommon but potentially devastating; however, indiscriminate neck imaging after trauma unnecessarily exposes children to ionising radiation. The aim of this study was to derive and validate a paediatric clinical prediction rule that can be incorporated into an algorithm to guide radiographic screening for cervical spine injury among children in the emergency department.

METHODS

In this prospective observational cohort study, we screened children aged 0-17 years presenting with known or suspected blunt trauma at 18 specialised children's emergency departments in hospitals in the USA affiliated with the Pediatric Emergency Care Applied Research Network (PECARN). Injured children were eligible for enrolment into derivation or validation cohorts by fulfilling one of the following criteria: transported from the scene of injury to the emergency department by emergency medical services; evaluated by a trauma team; and undergone neck imaging for concern for cervical spine injury either at or before arriving at the PECARN-affiliated emergency department. Children presenting with solely penetrating trauma were excluded. Before viewing an enrolled child's neck imaging results, the attending emergency department clinician completed a clinical examination and prospectively documented cervical spine injury risk factors in an electronic questionnaire. Cervical spine injuries were determined by imaging reports and telephone follow-up with guardians within 21-28 days of the emergency room encounter, and cervical spine injury was confirmed by a paediatric neurosurgeon. Factors associated with a high risk of cervical spine injury (>10%) were identified by bivariable Poisson regression with robust error estimates, and factors associated with non-negligible risk were identified by classification and regression tree (CART) analysis. Variables were combined in the cervical spine injury prediction rule. The primary outcome of interest was cervical spine injury within 28 days of initial trauma warranting inpatient observation or surgical intervention. Rule performance measures were calculated for both derivation and validation cohorts. A clinical care algorithm for determining which risk factors warrant radiographic screening for cervical spine injury after blunt trauma was applied to the study population to estimate the potential effect on reducing CT and x-ray use in the paediatric emergency department. This study is registered with ClinicalTrials.gov, NCT05049330.

FINDINGS

Nine emergency departments participated in the derivation cohort, and nine participated in the validation cohort. In total, 22 430 children presenting with known or suspected blunt trauma were enrolled (11 857 children in the derivation cohort; 10 573 in the validation cohort). 433 (1·9%) of the total population had confirmed cervical spine injuries. The following factors were associated with a high risk of cervical spine injury: altered mental status (Glasgow Coma Scale [GCS] score of 3-8 or unresponsive on the Alert, Verbal, Pain, Unresponsive scale [AVPU] of consciousness); abnormal airway, breathing, or circulation findings; and focal neurological deficits including paresthesia, numbness, or weakness. Of 928 in the derivation cohort presenting with at least one of these risk factors, 118 (12·7%) had cervical spine injury (risk ratio 8·9 [95% CI 7·1-11·2]). The following factors were associated with non-negligible risk of cervical spine injury by CART analysis: neck pain; altered mental status (GCS score of 9-14; verbal or pain on the AVPU; or other signs of altered mental status); substantial head injury; substantial torso injury; and midline neck tenderness. The high-risk and CART-derived factors combined and applied to the validation cohort performed with 94·3% (95% CI 90·7-97·9) sensitivity, 60·4% (59·4-61·3) specificity, and 99·9% (99·8-100·0) negative predictive value. Had the algorithm been applied to all participants to guide the use of imaging, we estimated the number of children having CT might have decreased from 3856 (17·2%) to 1549 (6·9%) of 22 430 children without increasing the number of children getting plain x-rays.

INTERPRETATION

Incorporated into a clinical algorithm, the cervical spine injury prediction rule showed strong potential for aiding clinicians in determining which children arriving in the emergency department after blunt trauma should undergo radiographic neck imaging for potential cervical spine injury. Implementation of the clinical algorithm could decrease use of unnecessary radiographic testing in the emergency department and eliminate high-risk radiation exposure. Future work should validate the prediction rule and care algorithm in more general settings such as community emergency departments.

FUNDING

The Eunice Kennedy Shriver National Institute of Child Health and Human Development and the Health Resources and Services Administration of the US Department of Health and Human Services in the Maternal and Child Health Bureau under the Emergency Medical Services for Children programme.

Parallel processing model for low-dose computed tomography image denoising

Low-dose computed tomography (LDCT) has gained increasing attention owing to its crucial role in reducing radiation exposure in patients. However, LDCT-reconstructed images often suffer from significant noise and artifacts, negatively impacting the radiologists' ability to accurately diagnose. To address this issue, many studies have focused on denoising LDCT images using deep learning (DL) methods. However, these DL-based denoising methods have been hindered by the highly variable feature distribution of LDCT data from different imaging sources, which adversely affects the performance of current denoising models. In this study, we propose a parallel processing model, the multi-encoder deep feature transformation network (MDFTN), which is designed to enhance the performance of LDCT imaging for multisource data. Unlike traditional network structures, which rely on continual learning to process multitask data, the approach can simultaneously handle LDCT images within a unified framework from various imaging sources. The proposed MDFTN consists of multiple encoders and decoders along with a deep feature transformation module (DFTM). During forward propagation in network training, each encoder extracts diverse features from its respective data source in parallel and the DFTM compresses these features into a shared feature space. Subsequently, each decoder performs an inverse operation for multisource loss estimation. Through collaborative training, the proposed MDFTN leverages the complementary advantages of multisource data distribution to enhance its adaptability and generalization. Numerous experiments were conducted on two public datasets and one local dataset, which demonstrated that the proposed network model can simultaneously process multisource data while effectively suppressing noise and preserving fine structures. The source code is available at https://github.com/123456789ey/MDFTN .

Emergency Department Evaluation of Young Infants With Head Injury

OBJECTIVES

We compared the emergency department (ED) evaluation and outcomes of young head-injured infants to older children.

METHODS

Using the Pediatric Health Information Systems database, we performed a retrospective, cross-sectional analysis of children <2 years old with isolated head injuries (International Classification of Diseases, 10th Revision, diagnoses) at one of 47 EDs from 2015 to 2019. Our primary outcome was utilization of diagnostic cranial imaging. Secondary outcomes were diagnosis of traumatic brain injury (TBI), clinically important TBI, and mortality. We compared outcomes between the youngest infants (<3 months old) and children 3 to 24 months old.

RESULTS

We identified 112 885 ED visits for children <2 years old with isolated head injuries. A total of 62 129 (55%) were by males, and 10 325 (9.1%) were by infants <3 months of age. Compared with older children (12-23 months old), the youngest infants were more likely to: Undergo any diagnostic cranial imaging (50.3% vs 18.3%; difference 31.9%, 95% confidence interval [CI] 35.0-28.9%), be diagnosed with a TBI (17.5% vs 2.7%; difference 14.8%, 95% CI 16.4%-13.2%) or clinically important TBI (4.6% vs 0.5%; difference 4.1%, 95% CI 3.8%-4.5%), and to die (0.3% vs 0.1%; difference 0.2%, 95% CI 0.3%-0.1%). Among those undergoing computed tomography or MRI, TBIs were significantly more common in the youngest infants (26.4% vs 8.8%, difference 17.6%, 95% CI 16.3%-19.0%).

CONCLUSIONS

The youngest infants with head injuries are significantly more likely to undergo cranial imaging, be diagnosed with brain injuries, and die, highlighting the need for a specialized approach for this vulnerable population.

Radiation Therapy Technology Advances and Mitigation of Subsequent Neoplasms in Childhood Cancer Survivors

PURPOSE

In this Pediatric Normal Tissue Effects in the Clinic (PENTEC) vision paper, challenges and opportunities in the assessment of subsequent neoplasms (SNs) from radiation therapy (RT) are presented and discussed in the context of technology advancement.

METHODS AND MATERIALS

The paper discusses the current knowledge of SN risks associated with historic, contemporary, and future RT technologies. Opportunities for research and SN mitigation strategies in pediatric patients with cancer are reviewed.

RESULTS

Present experience with radiation carcinogenesis is from populations exposed during widely different scenarios. Knowledge gaps exist within clinical cohorts and follow-up; dose-response and volume effects; dose-rate and fractionation effects; radiation quality and proton/particle therapy; age considerations; susceptibility of specific tissues; and risks related to genetic predisposition. The biological mechanisms associated with local and patient-level risks are largely unknown.

CONCLUSIONS

Future cancer care is expected to involve several available RT technologies, necessitating evidence and strategies to assess the performance of competing treatments. It is essential to maximize the utilization of existing follow-up while planning for prospective data collection, including standardized registration of individual treatment information with linkage across patient databases.

Texture-preserving low dose CT image denoising using Pearson divergence

Objective.The mean squared error (MSE), also known asL2loss, has been widely used as a loss function to optimize image denoising models due to its strong performance as a mean estimator of the Gaussian noise model. Recently, various low-dose computed tomography (LDCT) image denoising methods using deep learning combined with the MSE loss have been developed; however, this approach has been observed to suffer from the regression-to-the-mean problem, leading to over-smoothed edges and degradation of texture in the image.Approach.To overcome this issue, we propose a stochastic function in the loss function to improve the texture of the denoised CT images, rather than relying on complicated networks or feature space losses. The proposed loss function includes the MSE loss to learn the mean distribution and the Pearson divergence loss to learn feature textures. Specifically, the Pearson divergence loss is computed in an image space to measure the distance between two intensity measures of denoised low-dose and normal-dose CT images. The evaluation of the proposed model employs a novel approach of multi-metric quantitative analysis utilizing relative texture feature distance.Results.Our experimental results show that the proposed Pearson divergence loss leads to a significant improvement in texture compared to the conventional MSE loss and generative adversarial network (GAN), both qualitatively and quantitatively.Significance.Achieving consistent texture preservation in LDCT is a challenge in conventional GAN-type methods due to adversarial aspects aimed at minimizing noise while preserving texture. By incorporating the Pearson regularizer in the loss function, we can easily achieve a balance between two conflicting properties. Consistent high-quality CT images can significantly help clinicians in diagnoses and supporting researchers in the development of AI-diagnostic models.

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.

The paediatric polytrauma CT-indication (PePCI)-score-Development of a prognostic model to reduce unnecessary CT scans in paediatric trauma patients

BACKGROUND

Whole-Body CT (WBCT) is frequently used in emergency situations for promptly diagnosing paediatric polytrauma patients, given the challenges associated with obtaining precise details about the mechanism and progression of trauma. However, WBCT does not lead to reduced mortality in paediatric patients, but is associated with high radiation exposure. We therefore wanted to develop a screening tool for CT demand-driven emergency room (ER)-trauma diagnostic to reduce radiation exposure in paediatric patients.

METHODS

A retrospective study in a Level I trauma centre in Germany was performed. Data from 344 paediatric emergency patients with critical mechanism of injury who were pre-announced by the ambulance for the trauma room were collected. Patients' symptoms, clinical examination, extended Focused Assessment with Sonography for Trauma (eFAST), routinely, laboratory tests and blood gas and - when obtained - WBCT images were analysed. To identify potential predictors of severe injuries (ISS > 23), 300 of the 344 cases with complete data were subjected to regression analyses model.

RESULTS

Multiple regression analysis identified cGCS, base excess (BE), medically abnormal results from eFAST screening, initial unconsciousness, and injuries involving three or more body regions as significant predictors for a screening tool for decision-making to perform WBCT or selective CT. The developed Paediatric polytrauma CT-Indication (PePCI)-Score was divided into three risk categories and achieved a sensitivity of 87 % and a specificity of 71 % when comparing the low and medium risk groups with the high risk group. Comparing only the low-risk group with the high-risk group for the decision to perform WBCT, 32/35 (91 %) of patients with an ISS >23 were correctly identified, as were 124/137 (91 %) with lower ISS scores.

CONCLUSION

With the newly developed PePCI-Score, the frequency of WBCT in a paediatric emergency patients collective can be significantly reduced according to our data. After prospective validation, the initial assessment of paediatric trauma patients in the future could be made not only by the mechanism of injury, but also by the new PePCI-Score, deriving on clinical findings after thorough clinical assessment and the discretion of the trauma team.

Measurement and Application of Incidentally Detected Coronary Calcium: JACC Review Topic of the Week

Coronary artery calcium (CAC) scoring is a powerful tool for atherosclerotic cardiovascular disease risk stratification. The nongated, noncontrast chest computed tomography scan (NCCT) has emerged as a source of CAC characterization with tremendous potential due to the high volume of NCCT scans. Application of incidental CAC characterization from NCCT has raised questions around score accuracy, standardization of methodology including the possibility of deep learning to automate the process, and the risk stratification potential of an NCCT-derived score. In this review, the authors aim to summarize the role of NCCT-derived CAC in preventive cardiovascular health today as well as explore future avenues for eventual clinical applicability in specific patient populations and broader health systems.

Establishment and utilisation of national diagnostic reference level for adult computed tomography examinations in Ghana

The International Atomic Energy Agency, as part of the new regional project (RAF/9/059), recommend the establishment of diagnostic reference levels (DRLs) in Africa. In response to this recommendation, this project was designed to establish and utilise national DRLs of routine computed tomography (CT) examinations. These were done by estimating CT dose index and dose length product (DLP) from a minimum of 20 patient dose report of the most frequently used procedures using 75th percentile distribution of the median values. In all, 22 centres that formed 54% of all CT equipment in the country took part in this study. Additionally, a total of 2156 adult patients dose report were randomly selected, with a percentage distribution of 60, 12, 21 and 7% for head, chest, abdomen-pelvis and lumber spine, respectively. The established DRL for volume CT dose index were 60.0, 15.7, 20.5 and 23.8 mGy for head, chest, abdomen-pelvis and lumber spine, respectively. While the established DRL for DLP were 962.9, 1102.8, 1393.5 and 824.6 mGy-cm for head, chest, abdomen-pelvis, and lumber spine, respectively. These preliminary results were comparable with data from 16 other African countries, European Commission and the International Commission on Radiological Protection. Hence, this study would serve as a baseline for the establishment of a more generalised regional and national adult DRLs for Africa and other developing countries.

Fully automated deep learning system for osteoporosis screening using chest computed tomography images

Background

Osteoporosis, a disease stemming from bone metabolism irregularities, affects approximately 200 million people worldwide. Timely detection of osteoporosis is pivotal in grappling with this public health challenge. Deep learning (DL), emerging as a promising methodology in the field of medical imaging, holds considerable potential for the assessment of bone mineral density (BMD). This study aimed to propose an automated DL framework for BMD assessment that integrates localization, segmentation, and ternary classification using various dominant convolutional neural networks (CNNs).

Methods

In this retrospective study, a cohort of 2,274 patients underwent chest computed tomography (CT) was enrolled from January 2022 to June 2023 for the development of the integrated DL system. The study unfolded in 2 phases. Initially, 1,025 patients were selected based on specific criteria to develop an automated segmentation model, utilizing 2 VB-Net networks. Subsequently, a distinct cohort of 902 patients was employed for the development and testing of classification models for BMD assessment. Then, 3 distinct DL network architectures, specifically DenseNet, ResNet-18, and ResNet-50, were applied to formulate the 3-classification BMD assessment model. The performance of both phases was evaluated using an independent test set consisting of 347 individuals. Segmentation performance was evaluated using the Dice similarity coefficient; classification performance was appraised using the receiver operating characteristic (ROC) curve. Furthermore, metrics such as the area under the curve (AUC), accuracy, and precision were meticulously calculated.

Results

In the first stage, the automatic segmentation model demonstrated excellent segmentation performance, with mean Dice surpassing 0.93 in the independent test set. In the second stage, both the DenseNet and ResNet-18 demonstrated excellent diagnostic performance in detecting bone status. For osteoporosis, and osteopenia, the AUCs were as follows: DenseNet achieved 0.94 [95% confidence interval (CI): 0.91-0.97], and 0.91 (95% CI: 0.87-0.94), respectively; ResNet-18 attained 0.96 (95% CI: 0.92-0.98), and 0.91 (95% CI: 0.87-0.94), respectively. However, the ResNet-50 model exhibited suboptimal diagnostic performance for osteopenia, with an AUC value of only 0.76 (95% CI: 0.69-0.80). Alterations in tube voltage had a more pronounced impact on the performance of the DenseNet. In the independent test set with tube voltage at 100 kVp images, the accuracy and precision of DenseNet decreased on average by approximately 14.29% and 18.82%, respectively, whereas the accuracy and precision of ResNet-18 decreased by about 8.33% and 7.14%, respectively.

Conclusions

The state-of-the-art DL framework model offers an effective and efficient approach for opportunistic osteoporosis screening using chest CT, without incurring additional costs or radiation exposure.

Developmental cervical spinal canal size: population reference range

Background

The developmental size of the cervical spinal canal varies considerably. Neural compression and injury are more likely with a developmentally small spinal canal. This study was designed to develop a population reference range for developmental cervical spinal canal size for the Hong Kong population.

Methods

Prospective study of 522 ambulatory patients (256 males, 266 females, mean age 55±18 years; range, 20-89 years) who underwent computed tomography (CT) neck examinations. Using a manually operated segmentation program, spinal canal, and vertebral body cross-sectional area (CSA), anteroposterior (AP) sagittal diameter, and width were measured at each level from C3-C7. Patient height and weight were measured.

Results

Considerable variation in spinal canal size existed with, for example, a 164-168% variation exists for males and females between the largest and smallest spinal canal CSA at C5. All spinal canal measurements increased slightly with height (r=0.25-0.36, P<0.001), while vertebral body AP sagittal diameter increased with age (r=0.48-0.51, P<0.001). All spinal canal measurements were larger (<0.0001) in males. Although spinal canal CSA was larger in males (at C5, males 276.0±41.5 mm2; females 252.6±38.4 mm2), relative to vertebral body CSA, spinal canal CSA was larger in females. Arbitrary population thresholds indicating the smallest 25% spinal canal CSA and AP sagittal diameter as well as other parameters were defined.

Conclusions

There is a large variation in developmental cervical spinal canal size within the Hong Kong population. A reference range of developmental spinal canal size was developed which will enable an objective assessment of an individual's cervical spinal canal size relative to the wider population.

Sparse-view cone-beam computed tomography iterative reconstruction based on new multi-gradient direction total variation

AIM

The accurate reconstruction of cone-beam computed tomography (CBCT) from sparse projections is one of the most important areas for study. The compressed sensing theory has been widely employed in the sparse reconstruction of CBCT. However, the total variation (TV) approach solely uses information from the i-coordinate, j-coordinate, and k-coordinate gradients to reconstruct the CBCT image.

MATERIALS AND METHODS

It is well recognized that the CBCT image can be reconstructed more accurately with more gradient information from different directions. Thus, this study introduces a novel approach, named the new multi-gradient direction total variation minimization method. The method uses gradient information from the ij-coordinate, ik-coordinate, and jk-coordinate directions to reconstruct CBCT images, which incorporates nine different types of gradient information from nine directions.

RESULTS

This study assessed the efficacy of the proposed methodology using under-sampled projections from four different experiments, including two digital phantoms, one patient's head dataset, and one physical phantom dataset. The results indicated that the proposed method achieved the lowest RMSE index and the highest SSIM index. Meanwhile, we compared the voxel intensity curves of the reconstructed images to assess the edge structure preservation. Among the various methods compared, the curves generated by the proposed method exhibited the highest level of consistency with the gold standard image curves.

CONCLUSION

In summary, the proposed method showed significant potential in enhancing the quality and accuracy of CBCT image reconstruction.

Ten-Year Trend in Advanced Imaging Utilization for Suspected Pulmonary Embolism in Pregnancy

PURPOSE

Advanced imaging is essential to diagnose pulmonary embolism (PE) in pregnancy, but there are associated maternal and fetal radiation risks. The purpose of this study was to evaluate the 10-year trend in advanced imaging utilization for the evaluation of suspected PE in pregnancy.

METHODS

The authors evaluated pregnant women with advanced imaging using CT pulmonary angiography (CTPA) or lung scintigraphy (LS) for evaluation of suspected PE presenting to two tertiary hospitals from 2007 to 2016. The rate of imaging was evaluated relative to positive PE rate and local pregnancy rate. positive PE was defined as a new acute PE finding on any advanced imaging within 3 days of first advanced imaging test. Local pregnancy rates were defined per 1,000 pregnancies in the county serviced by both hospitals. Chi-square testing was used to evaluate statistical significance (P < .05) in the utilization trend of advanced imaging and relative to local pregnancy rates and evaluations positive for PE.

RESULTS

A total of 707 pregnant patients were identified, of whom 92.5% (n = 654) underwent CTPA and 7.5% (n = 53) underwent LS. Regression analysis showed an average increase of 5.2 advanced imaging studies per year (P < .001), with 61 and 105 studies performed in 2007 and 2016, respectively. Additionally, there was an average increase of 0.08 (P < .001) advanced imaging studies per 1,000 local pregnancies per year, doubling from 0.7 in 2007 to 1.4 in 2016 (P < .001). Finally, there was a decrease of 0.004 (P = .009) in advanced imaging positive for PE, from 3% (2 of 61) in 2007 to 0% (0 of 100) in 2016.

CONCLUSIONS

Advanced imaging utilization increased by 72% over the 10-year window, driven by higher use of CTPA. Although the detection rate of PE on advanced imaging has decreased, the utilization rate among pregnant patients doubled during this period. These results highlight the need to consider the radiation risks and costs of advanced imaging in specific patient populations.

Predicting mortality from AI cardiac volumes mass and coronary calcium on chest computed tomography

Chest computed tomography is one of the most common diagnostic tests, with 15 million scans performed annually in the United States. Coronary calcium can be visualized on these scans, but other measures of cardiac risk such as atrial and ventricular volumes have classically required administration of contrast. Here we show that a fully automated pipeline, incorporating two artificial intelligence models, automatically quantifies coronary calcium, left atrial volume, left ventricular mass, and other cardiac chamber volumes in 29,687 patients from three cohorts. The model processes chamber volumes and coronary artery calcium with an end-to-end time of ~18 s, while failing to segment only 0.1% of cases. Coronary calcium, left atrial volume, and left ventricular mass index are independently associated with all-cause and cardiovascular mortality and significantly improve risk classification compared to identification of abnormalities by a radiologist. This automated approach can be integrated into clinical workflows to improve identification of abnormalities and risk stratification, allowing physicians to improve clinical decision-making.

COVID-19 and cancer risk arising from ionizing radiation exposure through CT scans: a cross-sectional study

BACKGROUND

The surge in the utilization of CT scans for COVID-19 diagnosis and monitoring during the pandemic is undeniable. This increase has brought to the forefront concerns about the potential long-term health consequences, especially radiation-induced cancer risk. This study aimed to quantify the potential cancer risk associated with CT scans performed for COVID-19 detection.

METHODS

In this cross-sectional study data from a total of 561 patients, who were referred to the radiology center at Imam Hossein Hospital in Shahroud, was collected. CT scan reports were categorized into three groups based on the radiologist's interpretation. The BEIR VII model was employed to estimate the risk of radiation-induced cancer.

RESULTS

Among the 561 patients, 299 (53.3%) were males and the average age of the patients was 49.61 ± 18.73 years. Of the CT scans, 408 (72.7%) were reported as normal. The average age of patients with normal, abnormal, and potentially abnormal CT scans was 47.57 ± 19.06, 54.80 ± 16.70, and 58.14 ± 16.60 years, respectively (p-value < 0.001). The average effective dose was 1.89 ± 0.21 mSv, with 1.76 ± 0.11 mSv for males and 2.05 ± 0.29 mSv for females (p-value < 0.001). The average risk of lung cancer was 3.84 ± 1.19 and 9.73 ± 3.27 cases per 100,000 patients for males and females, respectively. The average LAR for all cancer types was 10.30 ± 6.03 cases per 100,000 patients.

CONCLUSIONS

This study highlights the critical issue of increased CT scan usage for COVID-19 diagnosis and the potential long-term consequences, especially the risk of cancer incidence. Healthcare policies should be prepared to address this potential rise in cancer incidence and the utilization of CT scans should be restricted to cases where laboratory tests are not readily available or when clinical symptoms are severe.

Comparison of dose length product and image quality of a biphasic whole-body polytrauma CT protocol with and without the automatic tube voltage selection

BACKGROUND AND AIMS

A significant source of man-made radiation is now linked to medical devices especially X-ray imaging based ones like CT scans which expose the body to cumulative ionizing radiation and thus attendant cancer risks. The aim of this study was to determine whether using a combination of Automatic Tube Current Modulation (ATCM) and Automatic Tube Voltage Selection (ATVS) during two-phase whole-body CT (2PWBCT) examinations would reduce the radiation dose while preserving the image quality.

PATIENTS AND METHODS

This was a prospective, observational, single-centre study of 127 adult patients who had undergone the 2PWBCT polytraumatic protocol. All were examined on a Somatom Drive scanner (Siemens). The patients were divided into two groups: ATCM only (42 patients) and ATCM +ATVS (85 patients). Patients' arm positions during examination and the examination dose length product (DLP) values were recorded, as well the standard deviations (SD) of the density in reference areas on CT scans for the image quality assessment. The DLP values and image quality in the groups were compared using ANOVA.

RESULTS

Mean Total DLP (in mGy*cm): ATCM only: 3337 +/-797, ATCM+ATVS: 3402 +/-830; P=0.674. No effect of arm position (P=0.586). Mean density SD values in reference areas (in HU) in ATCM only: 49 +/-45, 15 +/-6, 9 +/-2, 12 +/-4, 10 +/-3, in ATCM+ATVS: 48 +/-45, 17 +/-6, 11 +/-3, 15 +/-6, 12 +/-4. SD values was higher in ATCM+ATVS group (P<0.001).

CONCLUSION

Combination of ATVS and ATCM in polytraumatic 2PWBCT leads to no significant radiation load reduction compared with ATCM only but does lead to a slight degradation of image quality. The radiation load is significantly reduced if the patient has their arms behind the head when scanning, regardless of the activation of ATVS.

Direct estimation of the noise power spectrum from patient data to generate synthesized CT noise for denoising network training

BACKGROUND

Developing a deep-learning network for denoising low-dose CT (LDCT) images necessitates paired computed tomography (CT) images acquired at different dose levels. However, it is challenging to obtain these images from the same patient.

PURPOSE

In this study, we introduce a novel approach to generate CT images at different dose levels.

METHODS

Our method involves the direct estimation of the quantum noise power spectrum (NPS) from patient CT images without the need for prior information. By modeling the anatomical NPS using a power-law function and estimating the quantum NPS from the measured NPS after removing the anatomical NPS, we create synthesized quantum noise by applying the estimated quantum NPS as a filter to random noise. By adding synthesized noise to CT images, synthesized CT images can be generated as if these are obtained at a lower dose. This leads to the generation of paired images at different dose levels for training denoising networks.

RESULTS

The proposed method accurately estimates the reference quantum NPS. The denoising network trained with paired data generated using synthesized quantum noise achieves denoising performance comparable to networks trained using Mayo Clinic data, as justified by the mean-squared-error (MSE), structural similarity index (SSIM)and peak signal-to-noise ratio (PSNR) scores.

CONCLUSIONS

This approach offers a promising solution for LDCT image denoising network development without the need for multiple scans of the same patient at different doses.

CT acquisition parameter selection in the real world: impacts on radiation dose and variation amongst 155 institutions

OBJECTIVE

Quantify the relationship between CT acquisition parameters and radiation dose, how often parameters are adjusted in real-world practice, and their degree of contribution to real-world dose distribution. Identify discrepancies between parameters that are impactful in theory and impactful in practice.

METHODS

This study analyses 1.3 million consecutive adult routine abdomen exams performed between November 2015 and Jan 2021 included in the University of California, San Francisco International CT Dose Registry of 155 institutions. We calculated geometric standard deviation (gSD) for five parameters (kV, mAs, spiral pitch, number of phases, scan length) to assess variation in practice. A Gaussian mixed regression model was performed to predict the radiation dose-length product (DLP) using the parameters. Three conceptualizations of "impact" were computed for each parameter. To reflect the theoretical impact, we predict the increase in DLP per 10% (and 15%) increase in the parameter. To reflect the real-world practical impact, we predict the increase in DLP per gSD increase in the parameter.

RESULTS

Among studied examinations, mAs, number of phases, and scan length were frequently manipulated (gSD 1.52-1.70); kV was rarely manipulated (gSD 1.07). Theoretically, kV is the most impactful parameter (29% increase in DLP per 10% increase in kV, versus 5-9% increase for other parameters). In real-world practice, kV is less impactful; for each gSD increase in kV, the DLP increases by 20%, versus 22-69% for other parameters.

CONCLUSION

Despite the potential impact of kV on radiation dose, this parameter is rarely manipulated in common practice and this potential remains untapped.

CLINICAL RELEVANCE STATEMENT

CT beam energy (kV) modulation has the potential to strongly reduce radiation over-dosage to the patient, theoretically more so than similar degrees of modulation in other CT acquisition parameters. Despite this, beam energy modulation rarely occurs in practice, leaving its potential untapped.

KEY POINTS

• The relationship between CT acquisition parameter selection and radiation dose roughly coincided with established theoretical understanding. • CT acquisition parameters differ from each other in frequency and magnitude of manipulation, with beam energy (kV) being rarely manipulated. • Beam energy (kV) has the potential to substantially impact radiation dose, but because it is rarely manipulated, it is the least impactful CT acquisition parameter affecting radiation dose in practice.

Optimizing lung biopsy procedures:Comparative analysis of diagnostic efficacy and safety in experimental low-dose, conventional low-dose, and standard-dose CT-guided approaches

PURPOSE

Lung cancer is a major cause of cancer-related deaths, emphasizing the importance of early diagnosis. CT-guided percutaneous lung biopsy(CT-PLB) is a valuable method for diagnosing lung lesions, but multiple scans can elevate radiation exposure. This study aims to compare diagnostic efficacy and safety across different CT-PLB protocols.

METHODS

273 consecutive patients who underwent CT-PLB between June 2018 and February 2021 were enrolled, and were divided into standard-dose, conventional low-dose, and experimental low-dose groups. The study mainly evaluated technical success, diagnostic efficacy, radiation dose, complications, and image quality.

RESULTS

93 patients were assigned to standard-dose group, 85 to conventional low-dose group, and 95 to experimental low-dose group. Technical success rates in these groups were 97.9%, 100%, and 97.9%, respectively. Procedure-related complications rates were similar across the groups(pneumothorax:p=0.71, hemorrhage:p=0.59). Sensitivity, specificity, and overall diagnostic accuracy were comparable among three groups(p=0.59,1.0,0.65), with respective values of 90.5%, 100%, and 93.2% in standard-dose group, 88.1%, 100%, and 90.5% in conventional low-dose group, and 91.9%, 100%, and 93.4% in experimental low-dose group. The effective dose (ED) in the experimental low-dose group was significantly lower compared to both the standard-dose and conventional low-dose CT-PLB groups[ED: 1.49(1.0∼1.97) mSv vs 5.42(3.92∼6.91) mSv vs 3.15(2.52∼4.22) mSv, p<0.001].

CONCLUSIONS

This study has developed a standardized six-step procedure for CT-PLB using experimental low-dose settings. It can achieve comparable diagnostic efficacy to conventional low-dose and standard-dose CT-PLB protocols while substantially reducing radiation exposure. These findings indicate that the experimental low-dose protocol could serve as a safe and effective alternative for CT-PLB.

Influence of spectral shaping and tube voltage modulation in ultralow-dose computed tomography of the abdomen

PURPOSE

Unenhanced abdominal CT constitutes the diagnostic standard of care in suspected urolithiasis. Aiming to identify potential for radiation dose reduction in this frequent imaging task, this experimental study compares the effect of spectral shaping and tube voltage modulation on image quality.

METHODS

Using a third-generation dual-source CT, eight cadaveric specimens were scanned with varying tube voltage settings with and without tin filter application (Sn 150, Sn 100, 120, 100, and 80 kVp) at three dose levels (3 mGy: standard; 1 mGy: low; 0.5 mGy: ultralow). Image quality was assessed quantitatively by calculation of signal-to-noise ratios (SNR) for various tissues (spleen, kidney, trabecular bone, fat) and subjectively by three independent radiologists based on a seven-point rating scale (7 = excellent; 1 = very poor).

RESULTS

Irrespective of dose level, Sn 100 kVp resulted in the highest SNR of all tube voltage settings. In direct comparison to Sn 150 kVp, superior SNR was ascertained for spleen (p ≤ 0.004) and kidney tissue (p ≤ 0.009). In ultralow-dose scans, subjective image quality of Sn 100 kVp (median score 3; interquartile range 3-3) was higher compared with conventional imaging at 120 kVp (2; 2-2), 100 kVp (1; 1-2), and 80 kVp (1; 1-1) (all p < 0.001). Indicated by an intraclass correlation coefficient of 0.945 (95% confidence interval: 0.927-0.960), interrater reliability was excellent.

CONCLUSIONS

In abdominal CT with maximised dose reduction, tin prefiltration at 100 kVp allows for superior image quality over Sn 150 kVp and conventional imaging without spectral shaping.

Radiation reduction for interventional radiology imaging: a video frame interpolation solution

PURPOSE

The aim of this study was to diminish radiation exposure in interventional radiology (IR) imaging while maintaining image quality. This was achieved by decreasing the acquisition frame rate and employing a deep neural network to interpolate the reduced frames.

METHODS

This retrospective study involved the analysis of 1634 IR sequences from 167 pediatric patients (March 2014 to January 2022). The dataset underwent a random split into training and validation subsets (at a 9:1 ratio) for model training and evaluation. Our approach proficiently synthesized absent frames in simulated low-frame-rate sequences by excluding intermediate frames from the validation subset. Accuracy assessments encompassed both objective experiments and subjective evaluations conducted by nine radiologists.

RESULTS

The deep learning model adeptly interpolated the eliminated frames within IR sequences, demonstrating encouraging peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) results. The average PSNR values for angiographic, subtraction, and fluoroscopic modes were 44.94 dB, 34.84 dB, and 33.82 dB, respectively, while the corresponding SSIM values were 0.9840, 0.9194, and 0.7752. Subjective experiments conducted with experienced interventional radiologists revealed minimal discernible differences between interpolated and authentic sequences.

CONCLUSION

Our method, which interpolates low-frame-rate IR sequences, has shown the capability to produce high-quality IR images. Additionally, the model exhibits potential for reducing the frame rate during IR image acquisition, consequently mitigating radiation exposure.

CRITICAL RELEVANCE STATEMENT

This study presents a critical advancement in clinical radiology by demonstrating the effectiveness of a deep neural network in reducing radiation exposure during pediatric interventional radiology while maintaining image quality, offering a potential solution to enhance patient safety.

KEY POINTS

• Reducing radiation: cutting IR image to reduce radiation. • Accurate frame interpolation: our model effectively interpolates missing frames. • High visual quality in terms of PSNR and SSIM, making IR procedures safer without sacrificing quality.

Customised weight-based volume contrast media protocol for multiphase abdominal computed tomography

INTRODUCTION

Multiphase computed tomography (CT) using fixed volume contrast media may lead to high radiation exposure and toxicity in patients with low body weight. We evaluated a customised weight-based protocol for multiphase CT in terms of radiation exposure, image quality and cost savings.

METHODS

A total of 224 patients were recruited. An optimised CT protocol was applied using 100 kV and 1 mL/kg of contrast media dosing. The image quality and radiation dose exposure of this CT protocol were compared to those of a standard 120 kV, 80 mL fixed volume protocol. The radiation dose information and CT Hounsfield units were recorded. The signal-to-noise ratio, contrast-to-noise ratio (CNR) and figure of merit (FOM) were used as comparison metrics. The images were assessed for contrast opacification and visual quality by two radiologists. The renal function, contrast media volume and cost were also evaluated.

RESULTS

The median effective dose was lowered by 16% in the optimised protocol, while the arterial phase images achieved significantly higher CNR and FOM. The radiologists' evaluation showed more than 97% absolute agreement with no significant differences in image quality. No significant differences were found in the pre- and post-CT estimated glomerular filtration rate. However, contrast media usage was significantly reduced by 1,680 mL, with an overall cost savings of USD 421 in the optimised protocol.

CONCLUSION

The optimised weight-based protocol is cost-efficient and lowers radiation dose while maintaining overall contrast enhancement and image quality.

Towards safer imaging: A comparative study of deep learning-based denoising and iterative reconstruction in intraindividual low-dose CT scans using an in-vivo large animal model

PURPOSE

Computed tomography (CT) scans are a significant source of medically induced radiation exposure. Novel deep learning-based denoising (DLD) algorithms have been shown to enable diagnostic image quality at lower radiation doses than iterative reconstruction (IR) methods. However, most comparative studies employ low-dose simulations due to ethical constraints. We used real intraindividual animal scans to investigate the dose-reduction capabilities of a DLD algorithm in comparison to IR.

MATERIALS AND METHODS

Fourteen veterinarian-sedated alive pigs underwent 2 CT scans on the same 3rd generation dual-source scanner with two months between each scan. Four additional scans ensued each time, with mAs reduced to 50 %, 25 %, 10 %, and 5 %. All scans were reconstructed ADMIRE levels 2 (IR2) and a novel DLD algorithm, resulting in 280 datasets. Objective image quality (CT numbers stability, noise, and contrast-to-noise ratio) was measured via consistent regions of interest. Three radiologists independently rated all possible dataset combinations per time point for subjective image quality (-1 = inferior, 0 = equal, 1 = superior). The points were averaged for a semiquantitative score, and inter-rater agreement was measured using Spearman's correlation coefficient and adequately corrected mixed-effects modeling analyzed objective and subjective image quality.

RESULTS

Neither dose-reduction nor reconstruction method negatively impacted CT number stability (p > 0.999). In objective image quality assessment, the lowest radiation dose achievable by DLD when comparing noise (p = 0.544) and CNR (p = 0.115) to 100 % IR2 was 25 %. Overall, inter-rater agreement of the subjective image quality ratings was strong (r ≥ 0.69, mean 0.93 ± 0.05, 95 % CI 0.92-0.94; each p < 0.001), and subjective assessments corroborated that DLD at 25 % radiation dose was comparable to 100 % IR2 in image quality, sharpness, and contrast (p ≥ 0.281).

CONCLUSIONS

The DLD algorithm can achieve image quality comparable to the standard IR method but with a significant dose reduction of up to 75%. This suggests a promising avenue for lowering patient radiation exposure without sacrificing diagnostic quality.

Improving the Safety of Computed Tomography Through Automated Quality Measurement: A Radiologist Reader Study of Radiation Dose, Image Noise, and Image Quality

OBJECTIVES

The Centers for Medicare and Medicaid Services funded the development of a computed tomography (CT) quality measure for use in pay-for-performance programs, which balances automated assessments of radiation dose with image quality to incentivize dose reduction without compromising the diagnostic utility of the tests. However, no existing quantitative method for assessing CT image quality has been validated against radiologists' image quality assessments on a large number of CT examinations. Thus to develop an automated measure of image quality, we tested the relationship between radiologists' subjective ratings of image quality with measurements of radiation dose and image noise.

MATERIALS AND METHODS

Board-certified, posttraining, clinically active radiologists rated the image quality of 200 diagnostic CT examinations from a set of 734, representing 14 CT categories. Examinations with significant distractions, motion, or artifact were excluded. Radiologists rated diagnostic image quality as excellent, adequate, marginally acceptable, or poor; the latter 2 were considered unacceptable for rendering diagnoses. We quantified the relationship between ratings and image noise and radiation dose, by category, by analyzing the odds of an acceptable rating per standard deviation (SD) increase in noise or geometric SD (gSD) in dose.

RESULTS

One hundred twenty-five radiologists contributed 24,800 ratings. Most (89%) were acceptable. The odds of an examination being rated acceptable statistically significantly increased per gSD increase in dose and decreased per SD increase in noise for most categories, including routine dose head, chest, and abdomen-pelvis, which together comprise 60% of examinations performed in routine practice. For routine dose abdomen-pelvis, the most common category, each gSD increase in dose raised the odds of an acceptable rating (2.33; 95% confidence interval, 1.98-3.24), whereas each SD increase in noise decreased the odds (0.90; 0.79-0.99). For only 2 CT categories, high-dose head and neck/cervical spine, neither dose nor noise was associated with ratings.

CONCLUSIONS

Radiation dose and image noise correlate with radiologists' image quality assessments for most CT categories, making them suitable as automated metrics in quality programs incentivizing reduction of excessive radiation doses.

Artificial Intelligence in Coronary Artery Calcium Scoring Detection and Quantification

Coronary artery calcium (CAC) is a marker of coronary atherosclerosis, and the presence and severity of CAC have been shown to be powerful predictors of future cardiovascular events. Due to its value in risk discrimination and reclassification beyond traditional risk factors, CAC has been supported by recent guidelines, particularly for the purposes of informing shared decision-making regarding the use of preventive therapies. In addition to dedicated ECG-gated CAC scans, the presence and severity of CAC can also be accurately estimated on non-contrast chest computed tomography scans performed for other clinical indications. However, the presence of such "incidental" CAC is rarely reported. Advances in artificial intelligence have now enabled automatic CAC scoring for both cardiac and non-cardiac CT scans. Various AI approaches, from rule-based models to machine learning algorithms and deep learning, have been applied to automate CAC scoring. Convolutional neural networks, a deep learning technique, have had the most successful approach, with high agreement with manual scoring demonstrated in multiple studies. Such automated CAC measurements may enable wider and more accurate detection of CAC from non-gated CT studies, thus improving the efficiency of healthcare systems to identify and treat previously undiagnosed coronary artery disease.

Knowledge and Perception of Radiation Risk From Computed Tomography Scans Among Patients Attending an Emergency Department

To evaluate the level of knowledge about radiation dose and possible risks related to computed tomography (CT) scans among patients visiting emergency departments (EDs), a survey was conducted over a two-month period. A total of 357 adult patients (44% men and 56% women) presenting for diagnostic imaging in the ED answered a survey consisting of 15 questions. The survey included questions about the participants' demographics and knowledge of radiation. Most of the respondents (58.5%) reported that the physician did not explain the potential risk of radiation before the procedure. In addition, more than half of the respondents (58.1%) expressed feeling anxious about the potential risk of radiation. Most respondents (84.9%) stated that the potential radiation risk did not affect their decision to proceed with the procedure. Overall, the findings highlight a lack of information about radiation and its potential risks provided to patients prior to the diagnostic procedure. Increasing awareness and understanding of the risks associated with these imaging modalities should be considered essential in modern communities. Efforts should be made to ensure that patients undergoing diagnostic imaging are aware of the radiation risks they may encounter.

Medical Malpractice and Diagnostic Radiology: Challenges and Opportunities

Medicolegal challenges in radiology are broad and impact both radiologists and patients. Radiologists may be affected directly by malpractice litigation or indirectly due to defensive imaging ordering practices. Patients also could be harmed physically, emotionally, or financially by unnecessary tests or procedures. As technology advances, the incorporation of artificial intelligence into medicine will bring with it new medicolegal challenges and opportunities. This article reviews the current and emerging direct and indirect effects of medical malpractice on radiologists and summarizes evidence-based solutions.

Imaging Wisely Campaign: Initiative to Reduce Imaging for Low Back Pain Across a Large Safety Net System

OBJECTIVES

Low back pain is a common clinical presentation that often results in expensive and unnecessary imaging that may lead to undue patient harm, including unnecessary procedures. We present an initiative in a safety net system to reduce imaging for low back pain.

METHODS

This quality improvement study was conducted across 70 ambulatory clinics and 11 teaching hospitals. Three electronic health record changes, using the concept of a nudge, were introduced into orders for lumbar radiography (x-ray), lumbar CT, and lumbar MRI. The primary outcome was the number of orders per 1,000 patient-days or encounters for each imaging test in the inpatient, ambulatory, and emergency department (ED) settings. Variation across facilities was assessed, along with selected indications.

RESULTS

Across all clinical environments, there were statistically significant decreases in level differences pre- and postintervention for lumbar x-ray (-52.9% for inpatient encounters, P < .001; -23.7% for ambulatory encounters, P < .001; and -17.3% for ED only encounters, P < .01). There was no decrease in ordering of lumbar CTs in the inpatient and ambulatory settings, although there was an increase in lumbar CTs in ED-only encounters. There was no difference in lumbar MRI ordering. Variation was seen across all hospitals and clinics.

DISCUSSION

Our intervention successfully decreased lumbar radiography across all clinical settings, with a reduction in lumbar CTs in the inpatient and ambulatory settings. There were no changes for lumbar MRI orders.

AntiHalluciNet: A Potential Auditing Tool of the Behavior of Deep Learning Denoising Models in Low-Dose Computed Tomography

Gaining the ability to audit the behavior of deep learning (DL) denoising models is of crucial importance to prevent potential hallucinations and adversarial clinical consequences. We present a preliminary version of AntiHalluciNet, which is designed to predict spurious structural components embedded in the residual noise from DL denoising models in low-dose CT and assess its feasibility for auditing the behavior of DL denoising models. We created a paired set of structure-embedded and pure noise images and trained AntiHalluciNet to predict spurious structures in the structure-embedded noise images. The performance of AntiHalluciNet was evaluated by using a newly devised residual structure index (RSI), which represents the prediction confidence based on the presence of structural components in the residual noise image. We also evaluated whether AntiHalluciNet could assess the image fidelity of a denoised image by using only a noise component instead of measuring the SSIM, which requires both reference and test images. Then, we explored the potential of AntiHalluciNet for auditing the behavior of DL denoising models. AntiHalluciNet was applied to three DL denoising models (two pre-trained models, RED-CNN and CTformer, and a commercial software, ClariCT.AI [version 1.2.3]), and whether AntiHalluciNet could discriminate between the noise purity performances of DL denoising models was assessed. AntiHalluciNet demonstrated an excellent performance in predicting the presence of structural components. The RSI values for the structural-embedded and pure noise images measured using the 50% low-dose dataset were 0.57 ± 31 and 0.02 ± 0.02, respectively, showing a substantial difference with a p-value < 0.0001. The AntiHalluciNet-derived RSI could differentiate between the quality of the degraded denoised images, with measurement values of 0.27, 0.41, 0.48, and 0.52 for the 25%, 50%, 75%, and 100% mixing rates of the degradation component, which showed a higher differentiation potential compared with the SSIM values of 0.9603, 0.9579, 0.9490, and 0.9333. The RSI measurements from the residual images of the three DL denoising models showed a distinct distribution, being 0.28 ± 0.06, 0.21 ± 0.06, and 0.15 ± 0.03 for RED-CNN, CTformer, and ClariCT.AI, respectively. AntiHalluciNet has the potential to predict the structural components embedded in the residual noise from DL denoising models in low-dose CT. With AntiHalluciNet, it is feasible to audit the performance and behavior of DL denoising models in clinical environments where only residual noise images are available.

Significance of S100B Protein as a Rapid Diagnostic Tool in Emergency Departments for Traumatic Brain Injury Patients

Traumatic brain injuries (TBIs) are not only the leading cause of death among people below 44 years of age, but also one of the biggest diagnostic challenges in the emergency set up. We believe that the use of serum biomarkers in diagnosis can help to improve patient care in TBI. One of them is the S100B protein, which is currently proposed as a promising diagnostic tool for TBI and its consequences. In our study, we analyzed serum biomarker S100B in 136 patients admitted to the Emergency Department of the Regional Specialist Hospital in Olsztyn. Participants were divided into three groups: patients with head trauma and alcohol intoxication, patients with head trauma with no alcohol intoxication and a control group of patients with no trauma or with injury in locations other than the head. In our study, as compared to the control group, patients with TBI had a significantly higher S100B level (both with and without intoxication). Moreover, in both groups, the mean S100B protein level was significantly higher in patients with pathological changes in CT. According to our study results, the S100B protein is a promising diagnostic tool, and we propose including its evaluation in routine regimens in patients with TBI.

Evaluating the Necessity and Radiation Risk of Brain CT Scans Requested by the Trauma Emergency Department

Background

Numerous Computed Tomography (CT) scan requests for trauma patients have raised serious concern about the impacts of radiation such as radiation-induced cancers.

Objective

This study aimed to evaluate the necessity rate of requested head CT scans for traumatic patients and to ultimately estimate the risk of radiation-induced brain cancer.

Material and Methods

In this retrospective analytical study, traumatic patients, who had undergone a head CT scan in a two-month period from August 23 to October 22, 2018, were considered as the study population. Two radiologists reviewed each patient individually to evaluate the rate of normal and abnormal cases. Dose length product in milligrays (mGy) was utilized to calculate the effective dose (ED) in millisieverts (mSv), resulting in an assessment of the risk of radiation-induced brain cancer using ICRP 103.

Results

Among 523 scans, 460 patients (88%) received normal reviews, while only 47 patients (9%) had findings related to their current trauma. The mean effective dose value was 1.05±0.36 mSv. Risk of the radiation induced brain cancer was calculated to be 0.037 and 0.030 new cancer cases in 10000 males and females per Gy, respectively.

Conclusion

Final results demonstrated that a significant number of traumatic patients undergoing a CT scan are in fact, healthy. Such reckless usage of CT and consequently the excess exposure could result in a dramatic rise in cancer rates. The need to limit unnecessary CT scan usage and keeping the radiation given to patients as low as reasonably achievable (ALARA) when collecting essential diagnostic data is more critical than ever.

Diagnostic Yield, Radiation Exposure, and the Role of Clinical Decision Rules to Limit Computed Tomographic Pulmonary Angiography-Associated Complications

OBJECTIVES

Computed tomographic pulmonary angiography (CT-PA) is associated with significant cost, contrast, and radiation exposure. Clinical decision rules (CDRs) reduce the need for diagnostic imaging; however, their utility in the medical intensive care unit (MICU) remains unknown. We explored the diagnostic yield and complications associated with CT-PA (radiation exposure and contrast-induced acute kidney injury [AKI]) while investigating the efficacy of CDRs to reduce unnecessary testing.

METHODS

All CT-PAs performed in an academic MICU for 4 years were retrospectively reviewed. The Wells and revised Geneva scores (CDRs) and radiation dose per CT-PA were calculated, and the incidence of post-CT-PA AKI was recorded.

RESULTS

A total of 439 studies were analyzed; the diagnostic yield was 11% (48 PEs). Positive CT-PAs were associated with a higher Wells score (5.8 versus 3.2, P < 0.001), but similar revised Geneva scores (6.4 versus 6.0, P = 0.32). A Wells score of ≥4 had a positive likelihood ratio of 2.1 with a negative predictive value of 98.2. More than half (88.9%) of patients with a Wells score of ≤4 developed an AKI, with 55.6% of those having recovery of renal function.

CONCLUSIONS

There is overutilization of CT-PA in the MICU. The Wells score retains its negative predictive value in critically ill adult patients and may aid to limit radiation exposure and contrast-induced AKI in MICU.

Evaluating Surgical Cervical Arthrodesis With a Novel MRI Grading Score

STUDY DESIGN

This was a single-institution retrospective study.

OBJECTIVE

Evaluate a magnetic resonance imaging (MRI)-scoring system to differentiate arthrodesis from pseudoarthrosis following anterior cervical discectomy and fusion.

SUMMARY OF BACKGROUND DATA

Diagnostic workup following fusion surgery often includes MRI to evaluate neural structures and computed tomography (CT) and/or dynamic x-rays to evaluate instrumentation and arthrodesis. The use of MRI alone for these evaluations would protect patients from harmful CT and x-ray ionizing radiation.

METHODS

Neurosurgical attending evaluated CTs for arthrodesis or pseudoarthrosis. Blinded neuroradiology attending and neurosurgery senior resident evaluated independent T1 and T2 region of interest (ROI) signal intensity over instrumented disk space. Cerebral spinal fluid (CSF) at the cisterna magnum and distal adjacent uninstrumented vertebral body (VB) were also calculated. ROI interspace /ROI CSF and ROI interspace /ROI VB quotients were used to create T1- and T2-interspace interbody scores (IIS).

RESULTS

Study population (n=64 patients, 50% female) with a mean age of 51.72 years and 109 instrumented levels with 45 fused levels (41.3%) were included. T1-weighted MRI, median T1-IIS CSF for arthrodesis was 176.20 versus 130.92 for pseudoarthrosis ( P <0.0001), T1-IIS VB for arthrodesis was 68.52 and pseudoarthrosis was 52.71 ( P <0.0001). T2-weighted MRI, median T2-IIS CSF for arthrodesis was 27.72 and 14.21 for pseudoarthrosis ( P <0.0001), while T2-IIS VB for arthrodesis was 67.90 and 41.02 for pseudoarthrosis ( P <0.0001). The greatest univariable discriminative capability for arthrodesis via AUROC was T1-IIS VB (0.7743).

CONCLUSION

We describe a novel MRI scoring system that may help determine arthrodesis versus pseudoarthrosis following anterior cervical discectomy and fusion. Postoperative symptomatic patients may only require MRI, which would protect patients from ionizing radiation.

LEVEL OF EVIDENCE

Level IV.

Cardiac coronary tomography angiography (CCTA) use across geographical regions in the USA and the UK: a cross-sectional study

Objective

Increased use of CT imaging has been identified as a key component of unsustainable rising healthcare costs in the USA and globally. Understanding evidence and its relation to imaging coverage policies can help identify patterns of variation to better inform high value care initiatives. This cross-sectional study evaluates regional differences in US utilisation of cardiac coronary tomography angiography (CCTA) and compares use in the USA and England.

Design

We determined differences in CCTA order rates by US Medicare region and compared order rates in the US and England, compared CT scanner prevalence in the USA and UK, and reviewed the CCTA coverage policies for each region.

Setting

The US and the UK.

Participants

Medicare Coverage Database; Medicare 2018 Part B data; National Health Services 2018 data.

Interventions

CCTA orders, CT scanner prevalence.

Main outcome measures

CCTA orders per beneficiary, CT scanner prevalence, CCTA policy variation.

Results

We found that CCTA coverage policies are more permissive in the UK compared with the USA. However, CT scanner prevalence per beneficiary is four times greater in the USA than the UK. There was significant variation in number of CCTA ordered per 100 000 beneficiaries between regions in England and the USA, ranging from 74 to 313 in the US and 57-317 in England.

Conclusions

There is significant geographical variation in use of CCTA in both the USA and England, although overall use does not differ significantly between both countries. Similarities in order rates, despite a much higher CT scanner density in the USA, may be related to more permissive guidelines around use of CCTA in the UK. Variation in both countries may also reflect the lack of high-quality clinical outcomes data for use of CCTA, underscoring opportunities for more evidence and evidence-based policy to promote appropriate use of CCTA imaging.

MRI-based torsion measurement of the lower limb is a reliable and valid alternative for CT measurement: a prospective study

PURPOSE

The aim of this study was to compare MRI-based torsion measurements of the lower limb to a well-established CT-based assessment in a prospective inter- and intraindividual approach.

METHODS

A total of 26 patients (age 28.8 years ± 11.0) were enrolled beginning in January 2021 until August 2022. Inclusion criteria were the clinical indication for torsion measurement of the lower limb. CT and MRI imaging were performed with a standard operating procedure, to ensure that all patients were examined in a standardized position. The examinations were planned on a coronal scout view based on prominent anatomical landmarks. Femoral and tibial torsion were measured individually. Torsion measurements were analysed twice: immediately after examination and after 3 weeks. Subsequently, intra-rater and parallel test reliability was calculated accordingly.

RESULTS

High significant results for CT and MRI measurements for both tibia (MRI: r = 0.961; p ≤ 0.001; CT: r = 0.963; p ≤ 0.001) and femur (MRI: r = 0.980; p ≤ 0.001; CT: r = 0.979; p ≤ 0.001) were obtained by calculated intra-rater reliability, showing that measurements were highly consistent for MRI and CT, respectively. Parallel test reliability for time point 1 as well as time point 2 was also highly significant and ranged from r = 0.947 to r = 0.972 (all with p ≤ 0.001, respectively) for both tibia and femur, showing a high concordance between the two measurements.

CONCLUSION

Measurement of tibial as well as femoral torsion was comparable for CT and MRI measurement. Therefore, this study supports MRI measurement as an equivalent alternative for CT measurement concerning torsional malalignment to reduce exposure to radiation.

LEVEL OF EVIDENCE

Level II.

Use of CT, ED presentation and hospitalisations 12 months before and after a diagnosis of cancer in Western Australia: a population-based retrospective cohort study

OBJECTIVE

To examine the use of CT, emergency department (ED)-presentation and hospitalisation and in 12 months before and after a diagnosis of cancer.

DESIGN

Population-based retrospective cohort study.

SETTING

West Australian linked administrative records at individual level.

PARTICIPANTS

104 009 adults newly diagnosed with cancer in 2004-2014.

MAIN OUTCOME MEASURES

CT use, ED presentations, hospitalisations.

RESULTS

As compared with the rates in the 12th month before diagnosis, the rate of CT scans started to increase from 2 months before diagnosis with an increase in both ED presentations and hospitalisation from 1 month before the diagnosis. These rates peaked in the month of diagnosis for CT scans (477 (95% CI 471 to 482) per 1000 patients), and for hospitalisations (910 (95% CI 902 to 919) per 1000 patients), and the month prior to diagnosis for ED (181 (95% CI 178 to 184) per 1000 patients) then rapidly reduced after diagnosis but remained high for the next 12 months. While the patterns of the health services used were similar between 2004 and 2014, the rate of the health services used during after diagnosis was higher in 2014 versus 2004 except for CT use in patients with lymphohaematopoietic cancer with a significant reduction.

CONCLUSION

Our results showed an increase in demand for health services from 2 months before diagnosis of cancer. Increasing use of health services during and post cancer diagnosis may warrant further investigation to identify factors driving this change.

The effect of contact radiation shielding on breast dose during CT abdomen-pelvis: a phantom study

This study aims to investigate if contact shielding reduces breast radiation dose during computed tomography (CT) abdomen-pelvis examinations using automatic tube current modulation to protect one of the four most radiosensitive organs during CT examinations. Dose measurements were taken with and without contact shielding across the anterior and lateral aspects of the breasts and with and without organ dose modulation (ODM) to quantify achievable dose reductions. Although there are no statistically significant findings, when comparing with and without shielding, the mean breast surface dose was reduced by 0.01 μSv without ODM (1.92-1.91 μSv, p = 0.49) and increased by 0.03 μSv with ODM (1.53-1.56 μSv, p = 0.44). Comparing with and without ODM, the mean breast surface dose was reduced by 0.35 μSv with shielding (1.91-1.56 μSv, p = 0.24) and by 0.39 μSv without shielding (1.92-1.53 μSv, p = 0.17). The addition of contact shielding does not provide significant breast surface radiation dose reduction during CT abdomen-pelvis.

Revolutionizing pediatric neuroimaging: the era of CT, MRI, and beyond

PURPOSE

To review the evolution of cross-sectional imaging in pediatric neuroradiology from early developments to current advancements and future directions.

METHODS

Information was obtained through a PubMed literature search as well as referenced online resources and personal experience from radiologists currently practicing pediatric neuroimaging and those who experienced the era of nascent cross-sectional imaging.

RESULTS

The advent of computed tomography (CT) and magnetic resonance imaging (MRI) in the 1970s and 1980s brought about a revolutionary shift in the field of medical imaging, neurosurgical and neurological diagnosis. These cross-sectional imaging techniques ushered in a new era by enabling the visualization of soft tissue structures within the brain and spine. Advancements in these imaging modalities have continued at a remarkable pace, now providing not only high high-resolution and 3-dimensional anatomical imaging, but also functional assessment. With each stride forward, CT and MRI have provided clinicians with invaluable insights, improving the accuracy and precision of diagnoses, facilitating the identification of optimal surgical targets, and guiding the selection of appropriate treatment strategies.

CONCLUSION

This article traces the origins and early developments of CT and MRI, chronicling their journey from pioneering technologies to their current indispensable status in clinical applications and exciting possibilities that lie ahead in the realm of medical imaging and neurologic diagnosis.

Looking for appropriateness in follow-up CT of oncologic patients: Results from a cross-sectional study

PURPOSE

The objective of this study was to assess the inappropriateness rate of oncological follow-up CT examinations.

METHODS

Out of 7.000 oncology patients referred for follow-up CT examinations between March and October 2022, a random sample of 10 % was included. Radiology residents assessed the appropriateness using the Italian Society of Medical Oncology (AIOM) guidelines, supervised by senior radiologists. Association between inappropriateness and clinical variables was investigated and variables influencing inappropriateness were analyzed through a binary logistic regression.

RESULTS

Three-hundred-eighty-eight examinations (56.1 %) were consistent with AIOM guidelines. An additional 100 (14.5  %) examinations did not follow the recommended schedule but were nevertheless considered appropriate because of suspected recurrence/progression (10.7 %) or adverse event requiring imaging assessment (3.8 %). Two-hundred-four (29.4 %) examinations were rated as inappropriate. Inappropriateness causes were as follows: CT not included in the relevant guideline (n = 47); CT extended to additional anatomical regions (n = 59); CT requested at a shorter time-interval (n = 98). No statistically significant difference was found in age, sex, scan region, and primary cancer between appropriate and inappropriate examinations. The only variable significantly associated with inappropriateness was being referred by a specific hospital unit named "unit 2" in the study (p = 0.009), which was demonstrated to be the only appropriateness independent predictor (OR 1.952).

CONCLUSION

This study shows that majority of oncological patients referred for follow-up CT follows standard guidelines. However, a non-negligible proportion was rated as inappropriate, mainly due to the shorter time-interval. No clinical variable was associated with inappropriateness, except for referral by a specific hospital unit.

Increasing use of computed tomography scans in the North Denmark Region raises patient safety concern

PURPOSE

Use of computed tomography (CT) scans raises safety concern as lifetime cumulative ionising radiation exposure is associated with risk of developing malignancies. This study aimed to investigate use of abdominal CT scans in the Danish health care sector.

METHODS

Data on abdominal CT scans performed annually in the North Denmark Region between 2005 and 2018 were extracted from the regional registry with emphasis on patients with a medical history of a repeated abdominal CT scan within 28 days. An audit of the medical files was subsequently conducted in 100 randomly selected patient cases to evaluate clinical information being provided, in addition to justification for a repeated abdominal CT scan, and finally if other radiology modalities could have been applied.

RESULTS

Number of annually performed abdominal CT scans in this demographically stable regional population increased by a factor 4.3 from 15 in 2005 to 65 in 2018 per 1,000 inhabitants. The audit revealed that 31% of the secondabdominal CT scans within a 28 days period were categorized as either doubtful whether justified or not justified. Moreover, 20% of theCT scans were considered replaceable by ultrasonography.

CONCLUSIONS

Annual performance of abdominal CT scans increased fourfold during the 14 years period. This tendency is probably attributable to changes in the Danish health care sector by which CT scan examination are used more frequently aiming at more accelerated patient investigation flow in conjunction with shorter length of hospitalization stay. Alertness is strongly warranted towards the associated risk of cancer due to life-time cumulative ionising radiation exposure by this strategy.

Computed Tomography of the Head : A Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose

In 1971, the first computed tomography (CT) scan was performed on a patient's brain. Clinical CT systems were introduced in 1974 and dedicated to head imaging only. New technological developments, broader availability, and the clinical success of CT led to a steady growth in examination numbers. Most frequent indications for non-contrast CT (NCCT) of the head include the assessment of ischemia and stroke, intracranial hemorrhage and trauma, while CT angiography (CTA) has become the standard for first-line cerebrovascular evaluation; however, resulting improvements in patient management and clinical outcomes come at the cost of radiation exposure, increasing the risk for secondary morbidity. Therefore, radiation dose optimization should always be part of technical advancements in CT imaging but how can the dose be optimized? What dose reduction can be achieved without compromising diagnostic value, and what is the potential of the upcoming technologies artificial intelligence and photon counting CT? In this article, we look for answers to these questions by reviewing dose reduction techniques with respect to the major clinical indications of NCCT and CTA of the head, including a brief perspective on what to expect from current and future developments in CT technology with respect to radiation dose optimization.

CDDnet: Cross-domain denoising network for low-dose CT image via local and global information alignment

The domain shift problem has emerged as a challenge in cross-domain low-dose CT (LDCT) image denoising task, where the acquisition of a sufficient number of medical images from multiple sources may be constrained by privacy concerns. In this study, we propose a novel cross-domain denoising network (CDDnet) that incorporates both local and global information of CT images. To address the local component, a local information alignment module has been proposed to regularize the similarity between extracted target and source features from selected patches. To align the general information of the semantic structure from a global perspective, an autoencoder is adopted to learn the latent correlation between the source label and the estimated target label generated by the pre-trained denoiser. Experimental results demonstrate that our proposed CDDnet effectively alleviates the domain shift problem, outperforming other deep learning-based and domain adaptation-based methods under cross-domain scenarios.

Red flags to screen for vertebral fracture in people presenting with low back pain

BACKGROUND

Low back pain is a common presentation across different healthcare settings. Clinicians need to confidently be able to screen and identify people presenting with low back pain with a high suspicion of serious or specific pathology (e.g. vertebral fracture). Patients identified with an increased likelihood of having a serious pathology will likely require additional investigations and specific treatment. Guidelines recommend a thorough history and clinical assessment to screen for serious pathology as a cause of low back pain. However, the diagnostic accuracy of recommended red flags (e.g. older age, trauma, corticosteroid use) remains unclear, particularly those used to screen for vertebral fracture.

OBJECTIVES

To assess the diagnostic accuracy of red flags used to screen for vertebral fracture in people presenting with low back pain. Where possible, we reported results of red flags separately for different types of vertebral fracture (i.e. acute osteoporotic vertebral compression fracture, vertebral traumatic fracture, vertebral stress fracture, unspecified vertebral fracture).

SEARCH METHODS

We used standard, extensive Cochrane search methods. The latest search date was 26 July 2022.

SELECTION CRITERIA

We considered primary diagnostic studies if they compared results of history taking or physical examination (or both) findings (index test) with a reference standard test (e.g. X-ray, magnetic resonance imaging (MRI), computed tomography (CT), single-photon emission computerised tomography (SPECT)) for the identification of vertebral fracture in people presenting with low back pain. We included index tests that were presented individually or as part of a combination of tests.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted data for diagnostic two-by-two tables from the publications or reconstructed them using information from relevant parameters to calculate sensitivity, specificity, and positive (+LR) and negative (-LR) likelihood ratios with 95% confidence intervals (CIs). We extracted aspects of study design, characteristics of the population, index test, reference standard, and type of vertebral fracture. Meta-analysis was not possible due to heterogeneity of studies and index tests, therefore the analysis was descriptive. We calculated sensitivity, specificity, and LRs for each test and used these as an indication of clinical usefulness. Two review authors independently conducted risk of bias and applicability assessment using the QUADAS-2 tool.

MAIN RESULTS

This review is an update of a previous Cochrane Review of red flags to screen for vertebral fracture in people with low back pain. We included 14 studies in this review, six based in primary care, five in secondary care, and three in tertiary care. Four studies reported on 'osteoporotic vertebral fractures', two studies reported on 'vertebral compression fracture', one study reported on 'osteoporotic and traumatic vertebral fracture', two studies reported on 'vertebral stress fracture', and five studies reported on 'unspecified vertebral fracture'. Risk of bias was only rated as low in one study for the domains reference standard and flow and timing. The domain patient selection had three studies and the domain index test had six studies rated at low risk of bias. Meta-analysis was not possible due to heterogeneity of the data. Results from single studies suggest only a small number of the red flags investigated may be informative. In the primary healthcare setting, results from single studies suggest 'trauma' demonstrated informative +LRs (range: 1.93 to 12.85) for 'unspecified vertebral fracture' and 'osteoporotic vertebral fracture' (+LR: 6.42, 95% CI 2.94 to 14.02). Results from single studies suggest 'older age' demonstrated informative +LRs for studies in primary care for 'unspecified vertebral fracture' (older age greater than 70 years: 11.19, 95% CI 5.33 to 23.51). Results from single studies suggest 'corticosteroid use' may be an informative red flag in primary care for 'unspecified vertebral fracture' (+LR range: 3.97, 95% CI 0.20 to 79.15 to 48.50, 95% CI 11.48 to 204.98) and 'osteoporotic vertebral fracture' (+LR: 2.46, 95% CI 1.13 to 5.34); however, diagnostic values varied and CIs were imprecise. Results from a single study suggest red flags as part of a combination of index tests such as 'older age and female gender' in primary care demonstrated informative +LRs for 'unspecified vertebral fracture' (16.17, 95% CI 4.47 to 58.43). In the secondary healthcare setting, results from a single study suggest 'trauma' demonstrated informative +LRs for 'unspecified vertebral fracture' (+LR: 2.18, 95% CI 1.86 to 2.54) and 'older age' demonstrated informative +LRs for 'osteoporotic vertebral fracture' (older age greater than 75 years: 2.51, 95% CI 1.48 to 4.27). Results from a single study suggest red flags as part of a combination of index tests such as 'older age and trauma' in secondary care demonstrated informative +LRs for 'unspecified vertebral fracture' (+LR: 4.35, 95% CI 2.92 to 6.48). Results from a single study suggest when '4 of 5 tests' were positive in secondary care, they demonstrated informative +LRs for 'osteoporotic vertebral fracture' (+LR: 9.62, 95% CI 5.88 to 15.73). In the tertiary care setting, results from a single study suggest 'presence of contusion/abrasion' was informative for 'vertebral compression fracture' (+LR: 31.09, 95% CI 18.25 to 52.96).

AUTHORS' CONCLUSIONS

The available evidence suggests that only a few red flags are potentially useful in guiding clinical decisions to further investigate people suspected to have a vertebral fracture. Most red flags were not useful as screening tools to identify vertebral fracture in people with low back pain. In primary care, 'older age' was informative for 'unspecified vertebral fracture', and 'trauma' and 'corticosteroid use' were both informative for 'unspecified vertebral fracture' and 'osteoporotic vertebral fracture'. In secondary care, 'older age' was informative for 'osteoporotic vertebral fracture' and 'trauma' was informative for 'unspecified vertebral fracture'. In tertiary care, 'presence of contusion/abrasion' was informative for 'vertebral compression fracture'. Combinations of red flags were also informative and may be more useful than individual tests alone. Unfortunately, the challenge to provide clear guidance on which red flags should be used routinely in clinical practice remains. Further research with primary studies is needed to improve and consolidate our current recommendations for screening for vertebral fractures to guide clinical care.

How Real Are Computed Tomography Low Dose Simulations? An Investigational In-Vivo Large Animal Study

OBJECTIVES

CT low-dose simulation methods have gained significant traction in protocol development, as they lack the risk of increased patient exposure. However, in-vivo validations of low-dose simulations are as uncommon as prospective low-dose image acquisition itself. Therefore, we investigated the extent to which simulated low-dose CT datasets resemble their real-dose counterparts.

MATERIALS AND METHODS

Fourteen veterinarian-sedated alive pigs underwent three CT scans on the same third generation dual-source scanner with 2 months between each scan. At each time, three additional scans ensued, with mAs reduced to 50%, 25%, and 10%. All scans were reconstructed using wFBP and ADMIRE levels 1-5. Matching low-dose datasets were generated from the 100% scans using reconstruction-based and DICOM-based simulations. Objective image quality (CT numbers stability, noise, and signal-to-noise ratio) was measured via consistent regions of interest. Three radiologists independently rated all possible dataset combinations per time point for subjective image quality (-1=inferior, 0=equal, 1=superior). The points were averaged for a semiquantitative score, and inter-rater-agreement was measured using Spearman's correlation coefficient. A structural similarity index (SSIM) analyzed the voxel-wise similarity of the volumes. Adequately corrected mixed-effects analysis compared objective and subjective image quality. Multiple linear regression with three-way interactions measured the contribution of dose, reconstruction mode, simulation method, and rater to subjective image quality.

RESULTS

There were no significant differences between objective and subjective image quality of reconstruction-based and DICOM-based simulation on all dose levels (p≥0.137). However, both simulation methods produced significantly lower objective image quality than real-dose images below 25% mAs due to noise overestimation (p<0.001; SSIM≤89±3). Overall, inter-rater-agreement was strong (r≥0.68, mean 0.93±0.05, 95% CI 0.92-0.94; each p<0.001). In regression analysis, significant decreases in subjective image quality were observed for lower radiation doses (b ≤ -0.387, 95%CI -0.399 to -0.358; p<0.001) but not for reconstruction modes, simulation methods, raters, or three-way interactions (p≥0.103).

CONCLUSION

Simulated low-dose CT datasets are subjectively and objectively indistinguishable from their real-dose counterparts down to 25% mAs, making them an invaluable tool for efficient low-dose protocol development.

Imaging surveillance in multiple endocrine neoplasia type 1: Ten years of experience with somatostatin receptor positron emission tomography

Guidelines for multiple endocrine neoplasia type 1 (MEN1) recommend intensive imaging surveillance without specifying a superior regimen, including the role of somatostatin receptor imaging (SRI) with positron emission tomography (PET). The primary outcomes were to: (1) Assess change in treatment of duodenal-pancreatic neuroendocrine neoplasms (DP-NENs), bronchopulmonary NENs, and thymic tumors attributed to use of SRI PET/computed tomography (CT) and (2) estimate radiation from imaging and risk of cancer death attributed to imaging radiation. This was a retrospective single center study, including all MEN1 patients, who had had at least one SRI PET/CT. A total of 60 patients, median age 42 (range 21-54) years, median follow-up 6 (range 1-10) years were included. Of 470 cross sectional scans (MRI, CT, SRI PET/CT), 209 were SRI PET/CT. The additional information from SRI PET had implications in 1/14 surgical interventions and 2/12 medical interventions. The estimated median radiation dose per patient was 104 (range 51-468) mSv of which PET contributed with 13 (range 5-55) mSv and CT with 91 mSv (range 46-413 mSv), corresponding to an estimated increased median risk of cancer death of 0.5% during 6 years follow-up. SRI PET had a significant impact on 3/26 decisions to intervene in 60 MEN1 patients followed for a median of 6 years with SRI PET/CT as the most frequently used modality. The surveillance program showed a high radiation dose. Multi-modality imaging strategies designed to minimize radiation exposure should be considered. Based on our findings, SRI-PET combined with CT cannot be recommended for routine surveillance in MEN1 patients.

Assessment of Effectiveness and Adverse Effect of New Combination Chemotherapy (irinotecan, cisplatin, and dexamethasone) in Relapse and Refractory Hodgkin Lymphoma

Background: Chemotherapy with Adriamycin, Bleomycin, Vinblastine, and Dacarbazine (ABVD regimen) cannot cure all patients with Hodgkin lymphoma. In this study, we evaluated the efficacy and adverse effect of a new regimen consist Irinotecan, Cisplatin, and Dexamethasone (ICD) in relapsed and refractory Hodgkin lymphoma as the second to fifth line of treatment. Materials and Methods: We performed a retrospective study in 26 relapsed or refractory patients with Hodgkin lymphoma receiving at least the first-line chemotherapy regimen (ABVD) and (ICD) as salvage therapy in Thaleghany Hospital from 2012 to 2018. This regimen consisted of Irinotecan 65mg/m2 D1, D8, Cisplatin 30mg/m2 D1, D8, and dexamethasone 40mg D1, 2, 8, and 9 was administered every 3 weeks for 6 cycles.  Treatment was discontinued in cases of disease progression or severe toxicity. Response to treatment was evaluated after two cycles. Patients with complete and partial remission were candidates for high-dose chemotherapy and autologous stem cell transplantation. Twenty-four patients were enrolled in the study. The mean age of 22 patients was 31.5 (19-67) years. Seven patients (29.1%) were in the first recurrence, and 17 (70.8%) were in the second or subsequent recurrence. Results: According to this study, three patients (12.5%) had complete response, 13 (45%) had partial response, four (16.6%) had stable disease, and four (16.6%) had progressive disease. Nine patients (37.5%) received high-dose chemotherapy and autologous stem cell support after ICD regimen. None of the cycles of chemotherapy were delayed due to treatment-related adverse event. Overall survival after six months in all patients was 91%, and mortality rate was 8.3% at the end of the study. Conclusion: The goal of salvage chemotherapy in relapsed or refractory Hodgkin Lymphoma is achieving CR or PR preparation patients for stabilization with BMT. Thus, we recommend ICD as one of the most effective protocols with overall response rate of 66% in this population.