Computed Tomography Technology-and Dose-in the 21st Century

Survey of CT radiation doses and iodinated contrast medium administration: an international multicentric study

OBJECTIVE

To assess the relationship between intravenous iodinated contrast media (ICM) administration usage and radiation doses for contrast-enhanced (CE) CT of head, chest, and abdomen-pelvis (AP) in international, multicenter settings.

METHODS

Our international (n = 16 countries), multicenter (n = 43 sites), and cross-sectional (ConRad) study had two parts. Part 1: Redcap survey with questions on information related to CT and ICM manufacturer/brand and respective protocols. Part 2: Information on 3,258 patients (18-96 years; M:F 1654:1604) who underwent CECT for a routine head (n = 456), chest (n = 528), AP (n = 599), head CT angiography (n = 539), pulmonary embolism (n = 599), and liver CT examinations (n = 537) at 43 sites across five continents. The following information was recorded: hospital name, patient age, gender, body mass index [BMI], clinical indications, scan parameters (number of scan phases, kV), IV-contrast information (concentration, volume, flow rate, and delay), and dose indices (CTDIvol and DLP).

RESULTS

Most routine chest (58.4%) and AP (68.7%) CECT exams were performed with 2-4 scan phases with fixed scan delay (chest 71.4%; AP 79.8%, liver CECT 50.7%) following ICM administration. Most sites did not change kV across different patients and scan phases; most CECT protocols were performed at 120-140 kV (83%, 1979/2685). There were no significant differences between radiation doses for non-contrast (CTDIvol 24 [16-30] mGy; DLP 633 [414-702] mGy·cm) and post-contrast phases (22 [19-27] mGy; 648 [392-694] mGy·cm) (p = 0.142). Sites that used bolus tracking for chest and AP CECT had lower CTDIvol than sites with fixed scan delays (p < 0.001). There was no correlation between BMI and CTDIvol (r2 ≤ - 0.1 to 0.1, p = 0.931).

CONCLUSION

Our study demonstrates up to ten-fold variability in ICM injection protocols and radiation doses across different CT protocols. The study emphasizes the need for optimizing CT scanning and contrast protocols to reduce unnecessary contrast and radiation exposure to patients.

CLINICAL RELEVANCE STATEMENT

The wide variability and lack of standardization of ICM media and radiation doses in CT protocols suggest the need for education and optimization of contrast usage and scan factors for optimizing image quality in CECT.

KEY POINTS

There is a lack of patient-centric CT protocol optimization taking into consideration mainly patients' size. There is a lack of correlation between ICM volume and CT radiation dose across CT protocol. A ten-fold variation in iodine-load for the same CT protocol in sites suggests a lack of standardization.

Awareness and preparedness level of medical workers for radiation and nuclear emergency response

Radiological science and nuclear technology have made great strides in the twenty-first century, with wide-ranging applications in various fields, including energy, medicine, and industry. However, those developments have been accompanied by the inherent risks of exposure to nuclear radiation, which is a source of concern owing to its potentially adverse effects on human health and safety and which is of particular relevance to medical personnel who may be exposed to certain cancers associated with low-dose radiation in their working environment. While medical radiation workers have seen a decrease in their occupational exposure since the 1950s thanks to improved measures for radiation protection, a concerning lack of understanding and awareness persists among medical professionals regarding these potential hazards and the required safety precautions. This issue is further compounded by insufficient capabilities in emergency response. This highlights the urgent need to strengthen radiation safety education and training to ensure the well-being of medical staff who play a critical role in radiological and nuclear emergencies. This review examines the health hazards of nuclear radiation to healthcare workers and the awareness and willingness and education of healthcare workers on radiation protection, calling for improved training programs and emergency response skills to mitigate the risks of radiation exposure in the occupational environment, providing a catalyst for future enhancement of radiation safety protocols and fostering of a culture of safety in the medical community.

Quantitative analysis of aortic Na[18F]F uptake in macrocalcifications and microcalcifications in PET/CT scans

BACKGROUND

Currently, computed tomography (CT) is used for risk profiling of (asymptomatic) individuals by calculating coronary artery calcium scores. Although this score is a strong predictor of major adverse cardiovascular events, this method has limitations. Sodium [18F]fluoride (Na[18F]F) positron emission tomography (PET) has shown promise as an early marker for atherosclerotic progression. However, evidence on Na[18F]F as a marker for high-risk plaques is limited, particularly on its presentation in clinical PET/CT. Besides, the relationship between microcalcifications visualized by Na[18F]F PET and macrocalcifications detectable on CT is unknown.

PURPOSE

To establish a match/mismatch score in the aorta between macrocalcified plaque content on CT and microcalcification Na[18F]F PET uptake.

METHODS

Na[18F]F-PET/CT scans acquired in our centre in 2019-2020 were retrospectively collected. The aorta of each low-dose CT was manually segmented. Background measurements were placed in the superior vena cava. The vertebrae were automatically segmented using an open-source convolutional neural network, dilated with 10 mm, and subtracted from the aortic mask. Per patient, calcium and Na[18F]F-hotspot masks were retrieved using an in-house developed algorithm. Three match/mismatch analyses were performed: a population analysis, a per slice analysis, and an overlap score. To generate a population image of calcium and Na[18F]F hotspot distribution, all aortic masks were aligned. Then, a heatmap of calcium HU and Na[18F]F-uptake on the surface was obtained by outward projection of HU and uptake values from the centerline. In each slice of the aortic wall of each patient, the calcium mass score and target-to-bloodpool ratios (TBR) were calculated within the calcium masks, in the aortic wall except the calcium masks, and in the aortic wall in slices without calcium. For the overlap score, three volumes were identified in the calcium and Na[18F]F masks: volume of PET (PET+/CT-), volume of CT (PET-/CT+), and overlapping volumes (PET+/CT+). A Spearman's correlation analysis with Bonferroni correction was performed on the population image, assessing the correlation between all HU and Na[18F]F vertex values. In the per slice analysis, a paired Wilcoxon signed-rank test was used to compare TBR values within each slice, while an ANOVA with post-hoc Kruskal-Wallis test was employed to compare TBR values between slices. p-values < 0.05 were considered significant.

RESULTS

In total, 186 Na[18F]F-PET/CT scans were included. A moderate positive exponential correlation was observed between total aortic calcium mass and total aortic TBR (r = 0.68, p < 0.001). A strong positive correlation (r = 0.77, p < 0.0001) was observed between CT values and Na[18F]F values on the population image. Significantly higher TBR values were found outside calcium masks than inside calcium masks (p < 0.0001). TBR values in slices where no calcium was present, were significantly lower compared with outside calcium and inside calcium (both p < 0.0001). On average, only 3.7% of the mask volumes were overlapping.

CONCLUSIONS

Na[18F]F-uptake in the aorta behaves similarly to macrocalcification detectable on CT. Na[18F]F-uptake values are also moderately correlated to calcium mass scores (match). Higher uptake values were found just outside macrocalcification masks instead of inside the macrocalcification masks (mismatch). Also, only a small percentage of the Na[18F]F-uptake volumes overlapped with the calcium volumes (mismatch).

Deep learning-based scan range optimization can reduce radiation exposure in coronary CT angiography

OBJECTIVES

Cardiac computed tomography (CT) is essential in diagnosing coronary heart disease. However, a disadvantage is the associated radiation exposure to the patient which depends in part on the scan range. This study aimed to develop a deep neural network to optimize the delimitation of scan ranges in CT localizers to reduce the radiation dose.

METHODS

On a retrospective training cohort of 1507 CT localizers randomly selected from calcium scoring and angiography scans and acquired between 2010 and 2017, optimized scan ranges were delimited by two radiologists in consensus. A neural network was trained to reproduce the scan ranges and was tested on two randomly selected and independent validation cohorts: an internal cohort of 233 CT localizers (January 2018-June 2020) and an external cohort from a nearby hospital of 298 CT localizers (July 2020-December 2020). Localizers where a bypass surgery was visible were excluded. The effective radiation dose to the patient was simulated using a Monte Carlo simulation. Scan ranges of radiographers, radiologists, and the network were compared using an equivalence test; likewise, the reduction in effective dose was tested using a superior test.

RESULTS

The network replicated the radiologists' scan ranges with a Dice score of 96.5 ± 0.02 (p < 0.001, indicating equivalence). The generated scan ranges resulted in an effective dose reduction of 10.0% (p = 0.002) in the internal cohort and 12.6% (p < 0.001) in the external cohort compared to the scan ranges delimited by radiographers in clinical routine.

CONCLUSIONS

Automatic delimitation of the scan range can result in a radiation dose reduction to the patient.

CLINICAL RELEVANCE STATEMENT

Fully automated delimitation of the scan range using a deep neural network enables a significant reduction in radiation exposure during CT coronary angiography compared to manual examination planning. It can also reduce the workload of the radiographers.

KEY POINTS

• Scan range delimitation for coronary computed tomography angiography could be performed with high accuracy by a deep neural network. • Automated scan ranges showed a high agreement of 96.5% with the scan ranges of radiologists. • Using a Monte Carlo simulation, automated scan ranges reduced the effective dose to the patient by up to 12.6% (0.9 mSv) compared to the scan ranges of radiographers in clinical routine.

Artificial Intelligence in CT and MR Imaging for Oncological Applications

Cancer care increasingly relies on imaging for patient management. The two most common cross-sectional imaging modalities in oncology are computed tomography (CT) and magnetic resonance imaging (MRI), which provide high-resolution anatomic and physiological imaging. Herewith is a summary of recent applications of rapidly advancing artificial intelligence (AI) in CT and MRI oncological imaging that addresses the benefits and challenges of the resultant opportunities with examples. Major challenges remain, such as how best to integrate AI developments into clinical radiology practice, the vigorous assessment of quantitative CT and MR imaging data accuracy, and reliability for clinical utility and research integrity in oncology. Such challenges necessitate an evaluation of the robustness of imaging biomarkers to be included in AI developments, a culture of data sharing, and the cooperation of knowledgeable academics with vendor scientists and companies operating in radiology and oncology fields. Herein, we will illustrate a few challenges and solutions of these efforts using novel methods for synthesizing different contrast modality images, auto-segmentation, and image reconstruction with examples from lung CT as well as abdome, pelvis, and head and neck MRI. The imaging community must embrace the need for quantitative CT and MRI metrics beyond lesion size measurement. AI methods for the extraction and longitudinal tracking of imaging metrics from registered lesions and understanding the tumor environment will be invaluable for interpreting disease status and treatment efficacy. This is an exciting time to work together to move the imaging field forward with narrow AI-specific tasks. New AI developments using CT and MRI datasets will be used to improve the personalized management of cancer patients.

Photon-counting detector CT and energy-integrating detector CT for trabecular bone microstructure analysis of cubic specimens from human radius

Background

As bone microstructure is known to impact bone strength, the aim of this in vitro study was to evaluate if the emerging photon-counting detector computed tomography (PCD-CT) technique may be used for measurements of trabecular bone structures like thickness, separation, nodes, spacing and bone volume fraction.

Methods

Fourteen cubic sections of human radius were scanned with two multislice CT devices, one PCD-CT and one energy-integrating detector CT (EID-CT), using micro-CT as a reference standard. The protocols for PCD-CT and EID-CT were those recommended for inner- and middle-ear structures, although at higher mAs values: PCD-CT at 450 mAs and EID-CT at 600 (dose equivalent to PCD-CT) and 1000 mAs. Average measurements of the five bone parameters as well as dispersion measurements of thickness, separation and spacing were calculated using a three-dimensional automated region growing (ARG) algorithm. Spearman correlations with micro-CT were computed.

Results

Correlations with micro-CT, for PCD-CT and EID-CT, ranged from 0.64 to 0.98 for all parameters except for dispersion of thickness, which did not show a significant correlation (p = 0.078 to 0.892). PCD-CT had seven of the eight parameters with correlations ρ > 0.7 and three ρ > 0.9. The dose-equivalent EID-CT instead had four parameters with correlations ρ > 0.7 and only one ρ > 0.9.

Conclusions

In this in vitro study of radius specimens, strong correlations were found between trabecular bone structure parameters computed from PCD-CT data when compared to micro-CT. This suggests that PCD-CT might be useful for analysing bone microstructure in the peripheral human skeleton.

Radiation concerns in frequent flyer patients: Should imaging history influence decisions about recurrent imaging?

Radiation risks from diagnostic imaging have captured the attention of patients and medical practitioners alike, yet it remains unclear how these considerations can best be incorporated into clinical decision making. This manuscript presents a framework to consider these issues in a potentially at-risk population, the so called "frequent flyer" patients undergoing a large amount of recurrent imaging over time. Radiation risks from the low-dose exposures of diagnostic imaging are briefly reviewed, as applied to recurrent exposures. Some scenarios are then explored in which it may be helpful to incorporate knowledge of a patient's imaging history. There is no simple or uniformly applicable approach to these challenging and often nuanced clinical decisions. The complexity and variability of the underlying disease states and trajectories argues against alerting mechanisms based on a simple cumulative dose threshold. Awareness of imaging history may instead be beneficial in encouraging physicians and patients to take the long view, and to identify those populations of frequent flyers that might benefit from alternative imaging strategies.

Technological developments of X-ray computed tomography over half a century: User's influence on protocol optimization

Since the introduction of Computed Tomography (CT), technological improvements have been impressive. At the same time, the number of adjustable acquisition and reconstruction parameters has increased substantially. Overall, these developments led to improved image quality at a reduced radiation dose. However, many parameters are interrelated and part of automated algorithms. This makes it more complicated to adjust them individually and more difficult to comprehend their influence on CT protocol adjustments. Moreover, the user's influence in adapting protocol parameters is sometimes limited by the manufacturer's policy or the user's knowledge. As a consequence, optimization can be a challenge. A literature search in Embase, Medline, Cochrane, and Web of Science was performed. The literature was reviewed with the objective to collect information regarding technological developments in CT over the past five decades and the role of the associated acquisition and reconstruction parameters in the optimization process.

Cumulative Doses of Ionizing Radiation From Computed Tomography: A Population-Based Study

OBJECTIVE

To assess cumulative radiation doses from computed tomography (CT), patient characteristics, and clinical indications for CT in a population-based sample.

PATIENTS AND METHODS

A cohort study using medical records linkage through the Rochester Epidemiology Project was conducted to ascertain all CT examinations in Olmsted County, Minnesota, performed between January 1, 2004, and December 31, 2013, among all adults who were alive for 3 or more years after the end of follow-up (to exclude exposures preceding death). Ten-year cumulative effective ionizing radiation doses were estimated on the basis of typical doses per CT modality. Among patients with high doses (≥100 mSv/10 years), CT scans were reviewed for clinical setting, indications, and results.

RESULTS

Of 54,447 adults (median age, 44.0 years at inclusion), 26,377 (48.4%) underwent at least one CT. Ten-year radiation doses from CT were 0.1 to 9.9 mSv in 15.8% of the population (8593 patients), 10 to 24.9 mSv in 16.9% (9502), 25 to 99.9 mSv in 13.8% (7492), and 100 mSv or greater in 1.9% (1041). Computed tomography of the abdomen and pelvis accounted for 67.2% of the estimated dose. In multivariable models, doses differed 1.21-fold to 2.16-fold between extreme categories of age, body mass index, education level, smoking status, and by race. Of 600 CTs in 200 patients with high doses, 70.5% were obtained for restaging of solid cancers and lymphoma, abdominal pain, infection, kidney stones, follow-up of nodules or masses, and chest pain/evaluation for pulmonary embolism.

CONCLUSION

Exposure to ionizing radiation from CT occurred disproportionally in specific subgroups of the population. A limited number of clinical indications contributed the majority of radiation among adults with high doses.

Projection X-ray Imaging: Radiography, Mammography, Fluoroscopy

Recent advances in digital detector technology for medical radiography and fluoroscopy have resulted in improved workflow efficiency, operational flexibility, image quality, and diagnostic accuracy. This is attributed to the implementation of portable flat-panel x-ray detector devices able to provide real-time readout, processing, and display of medical images. As a result, digital radiography flat-panel detectors are rapidly replacing computed radiography passive detectors for projection imaging exams and image intensifier detectors for dynamic fluoroscopy exams. Advanced exam capabilities now include digital tomosynthesis and dual-energy radiography; the former is based on rapid acquisition of multiple angle-dependent image projections to synthesize tomographic slabs at selectable depths within the patient, and the latter is based on rapid back-to-back acquisition of the same anatomy at low and high x-ray energies to generate separate soft tissue and bone images. In both situations, superimposition of anatomy is reduced or eliminated, with the possibility of enhanced diagnostic confidence. Increased x-ray absorption efficiency and lower electronic noise of digital radiography detectors compared to computed radiography detectors enable equal image quality at lower patient dose; however, because of a disconnect between image appearance and radiation dose, lower patient dose is not always achieved. Education, training, and implementation of standards such as the International Electrotechnical Commission 62494-1 Digital Radiography Exposure Index are needed to ensure image quality at the lowest appropriate radiation dose. The National Council on Radiation Protection and Measurements can contribute to radiation responsibility in medical imaging by providing guidance on use of digital radiography, including recommendations for acquisition protocols and exposure index standards, for development of radiographic exam diagnostic reference levels, and for oversight of retake and reject analysis.