Patient radiation dose from x-ray guided endovascular aneurysm repair: a Monte Carlo approach using voxel phantoms and detailed exposure information

Use of ionizing radiation in a Norwegian cohort of children with congenital heart disease: imaging frequency and radiation dose for the Health Effects of Cardiac Fluoroscopy and Modern Radiotherapy in Pediatrics (HARMONIC) study

BACKGROUND

The European-funded Health Effects of Cardiac Fluoroscopy and Modern Radiotherapy in Pediatrics (HARMONIC) project is a multicenter cohort study assessing the long-term effects of ionizing radiation in patients with congenital heart disease. Knowledge is lacking regarding the use of ionizing radiation from sources other than cardiac catheterization in this cohort.

OBJECTIVE

This study aims to assess imaging frequency and radiation dose (excluding cardiac catheterization) to patients from a single center participating in the Norwegian HARMONIC project.

MATERIALS AND METHODS

Between 2000 and 2020, we recruited 3,609 patients treated for congenital heart disease (age < 18 years), with 33,768 examinations categorized by modality and body region. Data were retrieved from the radiology information system. Effective doses were estimated using International Commission on Radiological Protection Publication 60 conversion factors, and the analysis was stratified into six age categories: newborn; 1 year, 5 years, 10 years, 15 years, and late adolescence.

RESULTS

The examination distribution was as follows: 91.0% conventional radiography, 4.0% computed tomography (CT), 3.6% diagnostic fluoroscopy, 1.2% nuclear medicine, and 0.3% noncardiac intervention. In the newborn to 15 years age categories, 4-12% had ≥ ten conventional radiography studies, 1-8% underwent CT, and 0.3-2.5% received nuclear medicine examinations. The median effective dose ranged from 0.008-0.02 mSv and from 0.76-3.47 mSv for thoracic conventional radiography and thoracic CT, respectively. The total effective dose burden from thoracic conventional radiography ranged between 28-65% of the dose burden from thoracic CT in various age categories (40% for all ages combined). The median effective dose for nuclear medicine lung perfusion was 0.6-0.86 mSv and for gastrointestinal fluoroscopy 0.17-0.27 mSv. Because of their low frequency, these procedures contributed less to the total effective dose than thoracic radiography.

CONCLUSION

This study shows that CT made the largest contribution to the radiation dose from imaging (excluding cardiac intervention). However, although the dose per conventional radiograph was low, the large number of examinations resulted in a substantial total effective dose. Therefore, it is important to consider the frequency of conventional radiography while calculating cumulative dose for individuals. The findings of this study will help the HARMONIC project to improve risk assessment by minimizing the uncertainty associated with cumulative dose calculations.

A radiomics model for predicting the outcome of endovascular abdominal aortic aneurysm repair based on machine learning

OBJECTIVE

This study aimed to develop a radiomics model to predict the outcome of endovascular aneurysm repair (EVAR) for abdominal aortic aneurysm (AAA), based on machine learning (ML) algorithms.

METHODS

We retrospectively reviewed 711 patients with infra-renal AAA who underwent elective EVAR procedures between January 2016 and December 2019 at our single center. The radiomics features of AAA were extracted using Pyradiomics. Pearson correlation analysis, analysis of variance (ANOVA), least absolute shrinkage, and selection operator (LASSO) regression were applied to determine the predictors for EVAR-related severe adverse events (SAEs). Eighty percent of patients were classified as the training set and the remaining 20 percent of patients were classified as the test set. The selected features were used to build a radiomics model in training set using different ML algorithms. The performance of each model was assessed using the area under the curve (AUC) from the receiver operating characteristic (ROC) curve in the test set.

RESULTS

A total of 493 patients were enrolled in this study, the mean follow-up time was 32 months. During the follow-up, 156 (31.6%) patients experienced EVAR-related SAEs. A total of 1223 radiomics features were extracted from each patient, of which 30 radiomics features were finally identified. The quantitative performance assessment and the ROC curves indicated that the logistics regression (LR) model had better predictive value than others, with accuracy, 0.86; AUC, 0.93; and F1 score, 0.91. The Rad-score waterfall plot showed that the overall amount of error was small both in the training set and in the test set. Calibration curve showed that the calibration degree of the training set and the test set were good (p > 0.05). Decision curve analysis (threshold 0.32) demonstrated that the model had good clinical applicability.

CONCLUSION

Our radiomics model could be used as an efficient and adjunctive tool to predict the outcome after EVAR.

BMI-Based organ doses in endovascular aneurysm repair interventions utilising Monte Carlo simulation

In this study, the effect of body-mass-index (BMI) on organ doses (ODs) during infrarenal endovascular-aneurysm-repair (EVAR) procedures was evaluated. Patient- and intra-operative data from fifty-nine EVAR procedures were inserted into VirtualDose-IR software to calculate ODs. For overweight, obesity class-I and obesity class-II, ODs were up to 147%, 412% and 775% higher than those for normal weight-patients, respectively. A large variation was observed in ODs published in literature mainly due to the differences in the software and the technical parameters used for the calculations.

Risk of various cancers in adults with abdominal aortic aneurysms

BACKGROUND

The cause of death for patients with an abdominal aortic aneurysm (AAA) can be related to the AAA itself. However, cancer-related mortality could also be a contributing factor. In the present study, we examined the hypothesis that an association exists between AAAs and certain cancers.

METHODS

Information from 2009 to 2015 was extracted from the Korean National Health Insurance Service database. We included 14,920 participants with a new diagnosis of an AAA. Propensity score matching by age and sex with disease-free patients was used to select the control group of 44,760 participants. The primary end point of the present study was a new diagnosis of various cancers.

RESULTS

The hazard ratio (HR) for cancer incidence was higher in the AAA group than in the control group for hepatoma, pancreatic cancer, and lung cancer (HR, 1.376, 1.429, and 1.394, respectively). In the case of leukemia, the HR for cancer occurrence was not significantly higher in the AAA group than in the control group. However, when stratified by surgery, the HR was significantly higher for the surgical group (HR, 3.355), especially for endovascular aneurysm repair (HR, 3.864).

CONCLUSIONS

We found that AAAs are associated with an increased risk of cancer, in particular, hepatoma, pancreatic cancer, and lung cancer, even after adjusting for several comorbidities. Thus, continued follow-up is necessary for patients with an AAA to permit the early detection of the signs and symptoms of cancer.

Development and Comparison of Multimodal Models for Preoperative Prediction of Outcomes After Endovascular Aneurysm Repair

Objective

The aim of this study was to develop and compare multimodal models for predicting outcomes after endovascular abdominal aortic aneurysm repair (EVAR) based on morphological, deep learning (DL), and radiomic features.

Methods

We retrospectively reviewed 979 patients (January 2010—December 2019) with infrarenal abdominal aortic aneurysms (AAAs) who underwent elective EVAR procedures. A total of 486 patients (January 2010–December 2015) were used for morphological feature model development and optimization. Univariable and multivariable analyses were conducted to determine significant morphological features of EVAR-related severe adverse events (SAEs) and to build a morphological feature model based on different machine learning algorithms. Subsequently, to develop the morphological feature model more easily and better compare with other modal models, 340 patients of AAA with intraluminal thrombosis (ILT) were used for automatic segmentation of ILT based on deep convolutional neural networks (DCNNs). Notably, 493 patients (January 2016–December 2019) were used for the development and comparison of multimodal models (optimized morphological feature, DL, and radiomic models). Of note, 80% of patients were classified as the training set and 20% of patients were classified as the test set. The area under the curve (AUC) was used to evaluate the predictive abilities of different modal models.

Results

The mean age of the patients was 69.9 years, the mean follow-up was 54 months, and 307 (31.4%) patients experienced SAEs. Statistical analysis revealed that short neck, angulated neck, conical neck, ILT, ILT percentage ≥51.6%, luminal calcification, double iliac sign, and common iliac artery index ≥1.255 were associated with SAEs. The morphological feature model based on the support vector machine had a better predictive performance with an AUC of 0.76, an accuracy of 0.76, and an F1 score of 0.82. Our DCNN model achieved a mean intersection over union score of more than 90.78% for the segmentation of ILT and AAA aortic lumen. The multimodal model result showed that the radiomic model based on logistics regression had better predictive performance (AUC 0.93, accuracy 0.86, and F1 score 0.91) than the optimized morphological feature model (AUC 0.62, accuracy 0.69, and F1 score 0.81) and the DL model (AUC 0.82, accuracy 0.85, and F1 score 0.89).

Conclusion

The radiomic model has better predictive performance for patient status after EVAR. The morphological feature model and DL model have their own advantages and could also be used to predict outcomes after EVAR.

Potential risks of cardiovascular and cerebrovascular disease and cancer due to cumulative doses received from diagnostic CT scans?

Potential risks from radiation exposure on the development of cardiovascular and cerebrovascular disease are indicated by epidemiological studies. Medical exposures give the largest dose to the population from artificial sources, with cumulative doses from multiple CT scans being significant. Data on doses from scans performed on 12 CT scanners in three hospitals over a period of 5½ years, derived using Radimetrics^TMsoftware, have been reviewed for 105 757 patients. Data have been downloaded for heart, brain, thyroid, and effective doses, and cumulative doses analysed using Excel^TMspreadsheets. 2.4% of patients having body CT scans received cumulative doses to the heart over 100 mSv, 9% of whom were under 50 years. 9.6% of patients having head CT scans received cumulative doses to the brain over 100 mSv with 0.08% over 500 mSv from whom 41% were under 50 years, but only 1.3% of patients scanned had thyroid/carotid artery doses over 100 mSv. An approximate evaluation of potential risks from exposures of the heart above 100 mSv and brain over 500 mSv for patients under 60 years would suggest that at most only one patient would demonstrate any excess risk from vascular disease resulting from the exposures. 0.67% of patients scanned received effective doses over 100 mSv, in line with results from European studies, with 8.4% being under 50 years. The application of age and sex specific risk coefficients relating to excess cancer incidence suggests that two or three patients with effective doses over 100 mSv and five patients with effective doses between 50 and 100 mSv, from those examined, might develop cancer as a result of exposure. However, this will be an overestimate, since it does not take patients' health into account. Exposure management software can aid in evaluating cumulative doses and identifying individual patients receiving substantial doses from repetitive imaging.

Neutron Radiobiology and Dosimetry

As the U.S. prepares for the possibility of a radiological or nuclear incident, or anticipated lunar and Mars missions, the exposure of individuals to neutron radiation must be considered. More information is needed on how to determine the neutron dose to better estimate the true biological effects of neutrons and mixed-field (i.e., neutron and photon) radiation exposures. While exposure to gamma-ray radiation will cause significant health issues, the addition of neutrons will likely exacerbate the biological effects already anticipated after radiation exposure. To begin to understand the issues and knowledge gaps in these areas, the National Institute of Allergy and Infectious Diseases (NIAID), Radiation Nuclear Countermeasures Program (RNCP), Department of Defense (DoD), Defense Threat Reduction Agency (DTRA), and National Aeronautics and Space Administration (NASA) formed an inter-agency working group to host a Neutron Radiobiology and Dosimetry Workshop on March 7, 2019 in Rockville, MD. Stakeholder interests were clearly positioned, given the differences in the missions of each agency. An overview of neutron dosimetry and neutron radiobiology was included, as well as a historical overview of neutron exposure research. In addition, current research in the fields of biodosimetry and diagnostics, medical countermeasures (MCMs) and treatment, long-term health effects, and computational studies were presented and discussed.

A novel personalized dosimetry method for endovascular aneurysm repair (EVAR) procedures

OBJECTIVE

To estimate radiation doses for the primarily irradiated organs/tissues of patients subjected to standard endovascular aneurysm repair (EVAR) procedures using a novel personalized dosimetry method.

METHODS

Dosimetric and anthropometric data were collected prospectively for eight patients who underwent standard EVAR procedures. Patient-specific Monte Carlo simulations were performed to estimate organ/tissue doses from each of the fluoroscopic and digital subtraction angiography acquisitions involved in EVAR. Individual-specific cumulative absorbed doses were estimated for the skin, spinal bone marrow, heart, kidneys, liver, colon, bladder, pancreas, stomach, and spleen and compared to corresponding values estimated through a commercially available dosimetric software package that employs standardized phantoms.

RESULTS

The highest organ/tissue radiation doses from EVAR were found for the skin, spinal bone marrow, kidneys, and spleen as 192.4 mGy, 96.7 mGy, 72.9 mGy, and 33.6 mGy respectively, while the doses to the heart, liver, colon, bladder, pancreas, and stomach were 6.3 mGy, 14.4 mGy, 18.4 mGy, 14.8 mGy, 21.6 mGy, and 11.2 mGy respectively. Corresponding dose values using standardized phantoms were found to differ up to 151%.

CONCLUSION

Considerable radiation doses may be received by primarily exposed organs/tissues during standard EVAR. The specific size/anatomy of the patient and the variation in exposure parameters/beam angulation between different projections commonly involved in EVAR procedures should be taken into account if reliable organ dose data are to be derived.

KEY POINTS

• A novel patient-specific dosimetry method was utilized to estimate radiation doses to the primarily irradiated organs/tissues of patients subjected to standard endovascular aneurysm repair procedures. • The use of standardized mathematical anthropomorphic phantoms to derive organ dose from fluoroscopically guided procedures may result in considerable inaccuracies due to differences in the assumed organ position/volume/shape compared to patients.

Conversion factors for effective dose and organ doses with the air Kerma area product in hysterosalpingography

Histerosalpingography (HSG) remains the dominant diagnostic tool for investigation of infertility in women. Conversion factors used to estimate effective (E) and organ doses (H_T) from air Kerma area product (KAP) are needed to estimate patient doses in HSG, performed with state-of-the-art fluoroscopic X-ray systems with digital detectors. In this study, estimates of E and H_T for six critical organs/tissues, were derived on an individual basis in 120 HSG procedures and in 1410 irradiation events, performed on two X-ray systems from information available through the radiation dose structured report using Monte Carlo methods. Mean values of E and H_ovaries were1.0 ± 0.9 mSv and 5.6 ± 5.4 mGy. E/KAP conversion factors of 0.13; 0.18; 0.28 and 0.35 mSv Gy^-1cm^-2 were established for irradiation events with a Cu filtration of 0.0; 0.1; 0.4 and 0.9 mm. A high agreement was obtained between E estimated through Monte Carlo methods and E/KAP conversion factors accounting separately for the different modes of fluoroscopy and the radiography component of HSG, with a systematic error of 0 mSv and lower/upper limits of agreement of -0.6 and 0.5 mSv. On the contrary, the use of a single coefficient of conversion did not provide accurate estimates of E, showing a bias of -0.4 mSv and lower and upper limits of agreement of -1.9 and 1.2 mSv. An algorithm for the estimation of effective and organ doses from KAP has been established in HSG procedures depending on the Cu filtration in the X-ray irradiation events.