Abstract Nationwide surveys on radiation dose to the population from medical imaging are recommended in order to follow trends in population exposure. The goal of the 2018 survey was to investigate the current exposure. The invoice coding information was collected in five university hospitals and large clinics. To improve the estimation of the effective dose delivered in computed tomography (CT), we collected dose data from different Dose Archiving Communication Systems. On average, we found that 1.2 radiological examinations per year and per inhabitant were performed. Dental radiography was the most frequent examination (48% of all the X-ray examinations), followed by conventional radiography (36%) and CT (11%). The average annual effective dose was estimated to be 1.48 mSv per inhabitant, with CT representing 64% of that dose. Our results show that the exposure of the Swiss population from medical imaging has remained stable since 2013, despite a 15% increase in the number of CT examinations.

To assess task-based image quality for two abdominal protocols on various CT scanners. To establish a relationship between diagnostic reference levels (DRLs) and task-based image quality. A protocol for the detection of focal liver lesions was used to scan an anthropomorphic abdominal phantom containing 8- and 5-mm low-contrast (20 HU) spheres at five CTDIvol levels (4, 8, 12, 16, and 20 mGy) on 12 CTs. Another phantom with high-contrast calcium targets (200 HU) was scanned at 2, 4, 6, 10, and 15 mGy using a renal stones protocol on the same CTs. To assess the detectability, a channelized Hotelling observer was used for low-contrast targets and a non-prewhitening observer with an eye filter was used for high contrast targets. The area under the ROC curve and signal to noise ratio were used as figures of merit. For the detection of 8-mm spheres, the image quality reached a high level (mean AUC over all CTs higher than 0.95) at 11 mGy. For the detection of 5-mm spheres, the AUC never reached a high level of image quality. Variability between CTs was found, especially at low dose levels. For the search of renal stones, the AUC was nearly maximal even for the lowest dose level. Comparable task-based image quality cannot be reached at the same dose level on all CT scanners. This variability implies the need for scanner-specific dose optimization. • There is an image quality variability for subtle low-contrast lesion detection in the clinically used dose range. • Diagnostic reference levels were linked with task-based image quality metrics. • There is a need for specific dose optimization for each CT scanner and clinical protocol.

The study was conducted to calibrate and characterise the response of the Timepix3 photon-counting hybrid pixel detector. The study was conducted to calibrate and characterise the response of the Timepix3 photon-counting hybrid pixel detector. The goal was also to determine the impact of the angular variation of the detector to the source, of temperature change, and of ambient or strobe light on the on the detector response (measured fluence and energy spectrum). The impacts were studied using X-ray fluorescence lines, as well as Am-241 and Fe-55 radioactive sources. Angular variation measurements indicated angular dependence. This dependency increased with the angle and increased with lower energies. A decrease in fluence of up to 98.4% was recorded for Fe-55 (5.89 keV) and 43.1% for Am-241 (59.56 keV) at an angle of 90 degrees. Temperature measurements showed a 4% decrease of photon count when increasing the temperature from 10 degrees C to 36 degrees C. Energy spectra were shifted to lower energies when the temperature increased. Measurements with variable light intensities showed no variations in terms of fluence or energy spectra. However, if it was a strobe light, the fluence was overestimated by 10% and the spectral shape presented an additional artefactual peak around 3 keV. To restrict the variability of the detector response and avoid a time-consuming calculation of the error factor, due to the detector's temperature variation, we showed that it is necessary to keep the measurement temperature as close as possible to the temperature at which the calibration was performed. We also discovered the necessity of focusing on other relevant parameters such as the effect of the ambient light level or the angle of incidence of the X-ray beam impinging the detector on the detector response. This enabled us to propose a set of correction factors that can be used for other applications.

The standard Fourier metrics used for assessing image quality in computed tomography (CT) use a planar (2D) formulation of the noise equivalent quanta (NEQ) without a specific concept to manage the influence of longitudinal resolution variations, thus create a bias in the comparison of image quality for different reconstructed slice thicknesses. For this work, we designed a ‘slice NEQ’ that takes the longitudinal resolution into account and provides a volumetric indication of the scanner imaging performance. We also developed a specific formulation for the system DQE at the CT isocentre. A cylindrical water phantom with three different inserts for three contrast levels (−100, 120 and 1000 HU) was used for the task-based transfer functions (TTF) and noise power spectra (NPS) measurements. The longitudinal TTF was measured using the point source of the Catphan® 600 phantom. Images of the phantoms were acquired on two scanners (GE Discovery 750 HD and Siemens SOMATOM Force) and reconstructed using different slice thicknesses between 1 and 5 mm and algorithms (FBP for both systems, ASIR 50 and ASIR-V 50 for the GE). The slice NEQ correctly compared the imaging performance for different longitudinal resolutions whereas the 2D NEQ increased proportionally with the reconstructed slice thickness. The system DQE peaked at 0.70 (at 0.1 mm−1) for the Siemens and at 0.50 (at 0.1 mm−1) for the GE for FBP reconstructions. The validity of these Fourier-based metrics was restricted to a limited range of contrast due to nonlinearities introduced when dealing with iterative reconstructions (IR).

Background We assessed and compared image quality obtained with clinical 18 F-FDG whole-body oncologic PET protocols used in three different, state-of-the-art digital PET/CT and two conventional PMT-based PET/CT devices. Our goal was to evaluate an improved trade-off between administered activity (patient dose exposure/signal-to-noise ratio) and acquisition time (patient comfort) while preserving diagnostic information achievable with the recently introduced digital detector technology compared to previous analogue PET technology. Methods We performed list-mode (LM) PET acquisitions using a NEMA/IEC NU2 phantom, with activity concentrations of 5 kBq/mL and 25 kBq/mL for the background (9.5 L) and sphere inserts, respectively. For each device, reconstructions were obtained varying the image statistics (10, 30, 60, 90, 120, 180, and 300 s from LM data) and the number of iterations (range 1 to 10) in addition to the employed local clinical protocol setup. We measured for each reconstructed dataset: the quantitative cross-calibration, the image noise on the uniform background assessed by the coefficient of variation (COV), and the recovery coefficients (RCs) evaluated in the hot spheres. Additionally, we compared the characteristic time-activity-product (TAP) that is the product of scan time per bed position × mass-activity administered (in min·MBq/kg) across datasets. Results Good system cross-calibration was obtained for all tested datasets with < 6% deviation from the expected value was observed. For all clinical protocol settings, image noise was compatible with clinical interpretation (COV < 15%). Digital PET showed an improved background signal-to-noise ratio as compared to conventional PMT-based PET. RCs were comparable between digital and PMT-based PET datasets. Compared to PMT-based PET, digital systems provided comparable image quality with lower TAP (from ~ 40% less and up to 70% less). Conclusions This study compared the achievable clinical image quality in three state-of-the-art digital PET/CT devices (from different vendors) as well as in two conventional PMT-based PET. Reported results show that a comparable image quality is achievable with a TAP reduction of ~ 40% in digital PET. This could lead to a significant reduction of the administered mass-activity and/or scan time with direct benefits in terms of dose exposure and patient comfort.

PurposeWe aimed to thoroughly characterize image quality of a novel deep learning image reconstruction (DLIR), and investigate its potential for dose reduction in abdominal CT in comparison with filtered back-projection (FBP) and a partial model-based iterative reconstruction (ASiR-V).MethodsWe scanned a phantom at three dose levels: regular (7 mGy), low (3 mGy) and ultra-low (1 mGy). Images were reconstructed using DLIR (low, medium and high levels) and ASiR-V (0% = FBP, 50% and 100%). Noise and contrast-dependent spatial resolution were characterized by computing noise power spectra and target transfer functions, respectively. Detectability indexes of simulated acute appendicitis or colonic diverticulitis (low contrast), and calcium-containing urinary stones (high contrast) (|ΔHU| = 50 and 500, respectively) were calculated using the nonprewhitening with eye filter model observer.ResultsAt all dose levels, increasing DLIR and ASiR-V levels both markedly decreased noise magnitude compared with FBP, with DLIR low and medium maintaining noise texture overall. For both low- and high-contrast spatial resolution, DLIR not only maintained, but even slightly enhanced spatial resolution in comparison with FBP across all dose levels. Conversely, increasing ASiR-V impaired low-contrast spatial resolution compared with FBP. Overall, DLIR outperformed ASiR-V in all simulated clinical scenarios. For both low- and high-contrast diagnostic tasks, increasing DLIR substantially enhanced detectability at any dose and contrast levels for any simulated lesion size.ConclusionsUnlike ASiR-V, DLIR substantially reduces noise while maintaining noise texture and slightly enhancing spatial resolution overall. DLIR outperforms ASiR-V by enabling higher detectability of both low- and high-contrast simulated abdominal lesions across all investigated dose levels.

Purpose: Visual search using volumetric images is becoming the standard in medical imaging. However, we do not fully understand how eye movement strategies mediate diagnostic performance. A recent study on computed tomography (CT) images showed that the search strategies of radiologists could be classified based on saccade amplitudes and cross-quadrant eye movements [eye movement index (EMI)] into two categories: drillers and scanners. Approach: We investigate how the number of times a radiologist scrolls in a given direction during analysis of the images (number of courses) could add a supplementary variable to use to characterize search strategies. We used a set of 15 normal liver CT images in which we inserted 1 to 5 hypodense metastases of two different signal contrast amplitudes. Twenty radiologists were asked to search for the metastases while their eye-gaze was recorded by an eye-tracker device (EyeLink1000, SR Research Ltd., Mississauga, Ontario, Canada). Results: We found that categorizing radiologists based on the number of courses (rather than EMI) could better predict differences in decision times, percentage of image covered, and search error rates. Radiologists with a larger number of courses covered more volume in more time, found more metastases, and made fewer search errors than those with a lower number of courses. Our results suggest that the traditional definition of drillers and scanners could be expanded to include scrolling behavior. Drillers could be defined as scrolling back and forth through the image stack, each time exploring a different area on each image (low EMI and high number of courses). Scanners could be defined as scrolling progressively through the stack of images and focusing on different areas within each image slice (high EMI and low number of courses). Conclusions: Together, our results further enhance the understanding of how radiologists investigate three-dimensional volumes and may improve how to teach effective reading strategies to radiology residents.

Objectives: The aim of this study was to establish diagnostic reference levels (DRLs) in the field of dental maxillofacial and ear-nose-throat (ENT) practices using cone beam CT (CBCT) in Switzerland. Methods: A questionnaire was sent to owners of CBCTs in Switzerland; to a total of 612 institutions. The answers were analyzed for each indication, provided that enough data were available. The DRLs were defined as the 75th percentile of air kerma product distribution (PKA). Results: 227 answers were collected (38% of all centers). Third quartile of PKA values were obtained for five dental indications: 662 mGy cm² for wisdom tooth, 683 mGy cm² for single tooth implant treatment, 542 mGy cm² for tooth position anomalies, 569 mGy cm² for pathological dentoalveolar modifications, and 639 mGy cm² for endodontics. The standard field of view (FOV) size of 5 cm in diameter x 5 cm in height was proposed. Conclusions: Large ranges of FOV and PKA were found for a given indication, demonstrating the importance of establishing DRLs as well as FOV recommendations in view of optimizing the present practice. For now, only DRLs for dental and maxillofacial could be defined; because of a lack of ENT data, no DRL values for ENT practices could be derived from this survey.

We used the Timepix3 hybrid pixel detector technology in order to determine the exposure of medical personnel to ionizing radiation in an interventional radiology room. We measured the energy spectra of the scattered radiation generated by the patient during X-ray image-guided interventional procedures. We performed measurements at different positions and heights within the theatre. We first observed a difference in fluence for each staff member. As expected, we found that the person closest to the X-ray tube is the most exposed while the least exposed staff member is positioned at the patient's feet. Additionally, we observed a shift in energy from head to toe for practitioners, clearly indicating a non-homogenous energy exposure. The photon counting Timepix3 detector provides a new tool for radiation field characterisation that is easier-to-use and more compact than conventional X-ray spectrometers. The spectral information is particularly valuable for optimising the use of radiation protection gear and improving dosimetry surveillance programs. We also found the device very useful for training purposes to provide awareness and understanding about radiation protection principles among interventional radiology staff.

A rigorous 2D analysis of signal and noise transfer applied to reconstructed planes in digital breast tomosynthesis (DBT) is necessary for system characterization and optimization. This work proposes a method for assessing technical image quality and system detective quantum efficiency (DQEsys) for reconstructed planes in DBT. Measurements of 2D in-plane modulation transfer function (MTF) and noise power spectrum (NPS) were made on five DBT systems using different acquisition parameters, reconstruction algorithms and plane spacing. This work develops the noise equivalent quanta (NEQ), DQEsys and detectability index (d’) calculated using a non-prewhitening model observer with eye filter (NPWE) for reconstructed DBT planes. The images required for this implementation were acquired using a homogeneous test object of thickness 40 mm poly(methyl) methacrylate plus 0.5 mm Al; 2D MTF was calculated from an Al disc of thickness 0.2 mm and diameter 50 mm positioned within the phantom. The radiant contrast of the MTF disc and the air kerma at the system input were used as normalization factors. The NPWE detectability index was then compared to the in-plane contrast-detail (c-d) threshold measured using the CDMAM phantom. The MTF and NPS measured on the different systems showed a strong anisotropy, consistent with the cascaded models developed in the literature for DBT. Detectability indices calculated from the measured MTF and NPS successfully predicted changes in c-d detectability for details between 0.1 mm and 2.0 mm, for DBT plane spacings between 0.5 mm and 10 mm, and for air kerma values at the system input between 157 µGy and 1170 μGy. The linear Pearson correlation between the detectability index and threshold gold thickness of the CDMAM phantom was −0.996. The method implements a parametric means of assessing the technical image quality of reconstructed DBT planes, providing valuable information for optimization of DBT systems.

The standard approach to signal difference-to-noise ratio (SDNR) analysis requires a region of interest (ROI) positioned within the object to measure signal-difference, restricting this metric to flat-topped objects with large, sharply delineated areas. This work develops a generalized expression for SDNR (SDNRg) calculated from a ROI encompassing the object. Signal power, defined as the deviation of pixel values from the mean background due to the object, is used instead of signal-difference. Comparison was first made by simulating ideal flat-topped discs with sharp edges and diameters between 1 and 80 pixels, into a uniformly noisy background using a known signal-difference. For discs covering more than 20 pixels, SDNRg and standard SDNR (SDNRst) were within 3%, while for discs of less than 20 pixels, SDNRg was within 26% of the truth compared to 58% for SDNRst. Generalized and standard SDNR were compared for radiography images of three different phantoms with microcalcification-like objects (MTM-100 phantom), hemispheric objects of different thicknesses with a Gaussian intensity distribution and mammography quality control (QC) images. Applied to Gaussian details, SDNRg was between 20% and 45% higher than SDNRst, depending on object thickness, while for the QC images, SDNRg was with 1.7% of the standard SDNR. Compared to the standard SDNR, SDNRg is applicable to non-uniform signals, where an explicit contrast measurement is not suitable, and has improved accuracy when assessing SDNR of small objects.

Task-based image quality procedures in CT that substitute a human observer with a model observer usually use single-slice images with uniform backgrounds from homogeneous phantoms. However, anatomical structures and inhomogeneities in organs generate noise that can affect the detection performance of human observers. The purpose of this work was to assess the impact of background type, uniform or liver, and the viewing modality, single- or multislice, on the detection performance of human and model observers. We collected abdominal CT scans from patients and homogeneous phantom scans in which we digitally inserted low-contrast signals that mimicked a liver lesion. We ran a rating experiment with the two background conditions with three signal sizes and three human observers presenting images in two reading modalities: single- and multislice. In addition, channelized Hotelling observers (CHO) for single- and multislice detection were implemented and evaluated according to their degree of correlation with the human observer performance. For human observers, there was a small but significant improvement in performance with multislice compared to the single-slice viewing mode. Our data did not reveal a significant difference between uniform and anatomical backgrounds. Model observers demonstrated a good correlation with human observers for both viewing modalities. Human observers have very similar performances in both multi- and single-slice viewing mode. It is therefore preferable to use single-slice CHO as this model is computationally more tractable than multislice CHO. However, using images from a homogeneous phantom can result in overestimating image quality as CHO performance tends to be higher in uniform than anatomical backgrounds, while human observers have similar detection performances.

Our objectives were first to determine the optimal coronary computed tomography angiography (CTA) protocol for the quantification and detection of simulated coronary artery cross-sectional area (CSA) differences in vitro, and secondly to quantitatively compare the performance of the optimized CTA protocol with a previously validated radial coronary cardiovascular magnetic resonance (CMR) technique. 256-multidetector CTA and radial coronary CMR were used to obtain images of a custom in vitro resolution phantom simulating a range of physiological responses of coronary arteries to stress. CSAs were automatically quantified and compared with known nominal values to determine the accuracy, precision, signal-to-noise ratio (SNR), and circularity of CSA measurements, as well as the limit of detection (LOD) of CSA differences. Various iodine concentrations, radiation dose levels, tube potentials, and iterative image reconstruction algorithms (ASiR-V) were investigated to determine the optimal CTA protocol. The performance of the optimized CTA protocol was then compared with a radial coronary CMR method previously developed for endothelial function assessment under both static and moving conditions. The iodine concentration, dose level, tube potential, and reconstruction algorithm all had significant effects (all p <  0.001) on the accuracy, precision, LOD, SNR, and circularity of CSA measurements with CTA. The best precision, LOD, SNR, and circularity with CTA were achieved with 6% iodine, 20 mGy, 100 kVp, and 90% ASiR-V. Compared with the optimized CTA protocol under static conditions, radial coronary CMR was less accurate (− 0.91 ± 0.13 mm2 vs. -0.35 ± 0.04 mm2, p <  0.001), but more precise (0.08 ± 0.02 mm2 vs. 0.21 ± 0.02 mm2, p <  0.001), and enabled the detection of significantly smaller CSA differences (0.16 ± 0.06 mm2 vs. 0.52 ± 0.04 mm2; p <  0.001; corresponding to CSA percentage differences of 2.3 ± 0.8% vs. 7.4 ± 0.6% for a 3-mm baseline diameter). The same results held true under moving conditions as CSA measurements with CMR were less affected by motion. Radial coronary CMR was more precise and outperformed CTA for the specific task of detecting small CSA differences in vitro, and was able to reliably identify CSA changes an order of magnitude smaller than those reported for healthy physiological vasomotor responses of proximal coronary arteries. However, CTA yielded more accurate CSA measurements, which may prove useful in other clinical scenarios, such as coronary artery stenosis assessment.

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Purpose: To investigate how various generations of iterative reconstruction (IR) algorithms impact low-contrast detectability (LCD) in abdominal computed tomography (CT) for different patient effective diameters, using a quantitative task-based approach. Methods: Investigations were performed using an anthropomorphic abdominal phantom with two optional additional rings to simulate varying patient effective diameters (25, 30, and 35 cm), and containing multiple spherical targets (5, 6, and 8 mm in diameter) with a 20-HU contrast difference. The phantom was scanned using routine abdominal protocols (CTDIvol, 5.9-16 mGy) on four CT systems from two manufacturers. Images were reconstructed using both filtered back-projection (FBP) and various IR algorithms: ASiR 50%, SAFIRE 3 (both statistical IRs), ASiR-V 50%, ADMIRE 3 (both partial model-based IRs), or Veo (full model-based IR). Section thickness/interval was 2/1 mm or 2.5/1.25 mm, except 0.625/0.625 mm for Veo. We assessed LCD using a channelized Hotelling observer with 10 dense differences of Gaussian channels, with the area under the receiver operating characteristic curve (AUC) as a figure of merit. Results: For the smallest phantom (25-cm diameter) and smallest lesion size (5-mm diameter), AUC for FBP and the various IR algorithms did not significantly differ for any of the tested CT systems. For the largest phantom (35-cm diameter), Veo yielded the highest AUC improvement (8.5%). Statistical and partial model-based IR algorithms did not significantly improve LCD. Conclusion: In abdominal CT, switching from FBP to IR algorithms offers limited possibilities for achieving significant dose reductions while ensuring a constant objective LCD.

Purpose: We aimed to determine the in-vitro diagnostic performance of multi-energy spectral photon-counting CT (SPCCT) in crystal-related arthropathies. Methods: Four crystal types (monosodium urate, MSU; calcium pyrophosphate, CPP; octacalcium phosphate, OCP; and calcium hydroxyapatite, CHA) were synthesized and blended with agar at the following concentrations: 240, 88, 46, and 72 mg/mL, respectively. Crystal suspensions were scanned on a pre-clinical SPCCT system at 80 kVp using the following four energy thresholds: 20, 30, 40, and 50 keV. Differences in linear attenuation coefficients between the various crystal suspensions were compared using the receiver operating characteristic (ROC) paradigm. Areas under the ROC curves (AUC), sensitivities, specificities, and diagnostic accuracies were calculated. Crystal differentiation was considered successful if AUC>0.95. Results: For each paired comparison of crystal suspensions, AUCs were significantly higher in the first energy range (20-30 keV). In the first energy range, MSU was confidently differentiated from CPP (sensitivity, 0.978; specificity, 0.990; accuracy, 0.984) and CHA (sensitivity, 0.957; specificity, 0.970; accuracy, 0.964), while only moderately distinguished from OCP (sensitivity, 0.663; specificity, 0.714; accuracy, 0.688). CPP was confidently differentiated from OCP (sensitivity, 0.950; specificity, 0.954; accuracy, 0.952), while only moderately from CHA (sensitivity, 0.564; specificity, 0.885; accuracy, 0.727). OCP was accurately differentiated from CHA (sensitivity, 0.898; specificity, 0.917; accuracy, 0.907). Conclusions: Multi-energy SPCCT can accurately differentiate MSU from CPP and CHA, CPP from OCP, and OCP from CHA in vitro. The distinction between MSU and OCP, and CPP and CHA is more challenging.

statistical significant (p > 0.05).However, the contrast in the breast between the s-s films (0.87 ± 0.29) and d-s films (1.17 ± 0.35) were statistically significant (p < 0.01).In addition, the contrast in the breast between the d-s films (1.17 ± 0.35) and d-s films with adjusted tube voltage (0.96 ± 0.28) were also statistically significant (p < 0.01).The tube voltage for s-s film and d-s film with adjusted tube voltage was increased from 26.3 ± 0.15 kV to 27.2 kV ± 0.16 kV to adjusted optimized tube voltage.Conclusions.To adjust contrast in the breast of the d-s film was same as s-s film, tube voltage should be increased 1 kV.Therefore, the similar contrast image in the breast was obtained by using d-s film.