Search

Objectives 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. Methods 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. Results 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. Conclusions 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. Key Points • 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.

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.

Purpose We 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). Methods We 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. Results At 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. Conclusions Unlike 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.

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 (SDNR g ) 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, SDNR g and standard SDNR (SDNR st ) were within 3%, while for discs of less than 20 pixels, SDNR g was within 26% of the truth compared to 58% for SDNR st . 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, SDNR g was between 20% and 45% higher than SDNR st , depending on object thickness, while for the QC images, SDNR g was with 1.7% of the standard SDNR. Compared to the standard SDNR, SDNR g is applicable to non-uniform signals, where an explicit contrast measurement is not suitable, and has improved accuracy when assessing SDNR of small objects.

Background We assessed and compared image quality obtained with clinical 18F-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 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.

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.

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 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).

To investigate the impact of a partial model-based iterative reconstruction (ASiR-V) on image quality in thoracic oncologic multidetector computed tomography (MDCT), using human and mathematical model observers. Twenty cancer patients examined with regular-dose thoracic-abdominal-pelvic MDCT were retrospectively included. Thoracic images reconstructed using a sharp kernel and filtered back-projection (reference) or ASiR-V (0–100%, 20% increments; follow-up) were analysed by three thoracic radiologists. Advanced quantitative physical metrics, including detectability indexes of simulated 4-mm-diameter solid non-calcified nodules and ground-glass opacities, were computed at regular and reduced doses using a custom-designed phantom. All three radiologists preferred higher ASiR-V levels (best = 80%). Increasing ASiR-V substantially decreased noise magnitude, with slight changes in noise texture. For high-contrast objects, changing the ASiR-V level had no major effect on spatial resolution; whereas for lower-contrast objects, increasing ASiR-V substantially decreased spatial resolution, more markedly at reduced dose. For both high- and lower-contrast pulmonary lesions, detectability remained excellent, regardless of ASiR-V and dose levels, and increased significantly with increasing ASiR-V levels (all p

Objective We investigated the variability in diagnostic information inherent in computed tomography (CT) images acquired at 68 different CT units, with the selected acquisition protocols aiming to answer the same clinical question. Methods An anthropomorphic abdominal phantom with two optional rings was scanned on 68 CT systems from 62 centres using the local clinical acquisition parameters of the portal venous phase for the detection of focal liver lesions. Low-contrast detectability (LCD) was assessed objectively with channelised Hotelling observer (CHO) using the receiver operating characteristic (ROC) paradigm. For each lesion size, the area under the ROC curve (AUC) was calculated and considered as a figure of merit. The volume computed tomography dose index (CTDIvol) was used to indicate radiation dose exposure. Results The median CTDIvol used was 5.8 mGy, 10.5 mGy and 16.3 mGy for the small, medium and large phantoms, respectively. The median AUC obtained from clinical CT protocols was 0.96, 0.90 and 0.83 for the small, medium and large phantoms, respectively. Conclusions Our study used a model observer to highlight the difference in image quality levels when dealing with the same clinical question. This difference was important and increased with growing phantom size, which generated large variations in patient exposure. In the end, a standardisation initiative may be launched to ensure comparable diagnostic information for well-defined clinical questions. The image quality requirements, related to the clinical question to be answered, should be the starting point of patient dose optimisation. Key Points • Model observers enable to assess image quality objectively based on clinical tasks. • Objective image quality assessment should always include several patient sizes. • Clinical diagnostic image quality should be the starting point for patient dose optimisation. • Dose optimisation by applying DRLs only is insufficient for ensuring clinical requirements.

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.

We sought to compare objectively computed tomography (CT) scanner performance for three clinically relevant protocols using a task-based image quality assessment method in order to assess the potential for radiation dose reduction. Four CT scanners released between 2003 and 2007 by different manufacturers were compared with four CT scanners released between 2012 and 2014 by the same manufacturers using ideal linear model observers (MO): prewhitening (PW) MO and channelized Hotelling (CHO) MO with Laguerre-Gauss channels for high-contrast spatial resolution and low-contrast detectability (LCD) performance, respectively. High-contrast spatial resolution was assessed using a custom-made phantom that enabled the computation of the target transfer function (TTF) and noise power spectrum (NPS). Low-contrast detectability was assessed using a commercially available anthropomorphic abdominal phantom providing equivalent diameters of 24, 29.6, and 34.6 cm. Three protocols were reviewed: a head (trauma) and an abdominal (urinary stones) protocol were applied to assess high-contrast spatial resolution performance; and another abdominal (focal liver lesions) protocol was applied for LCD. The liver protocol was tested using fixed and modulated tube currents. The PW MO was proposed for assessing high-contrast detectability performance of the various CT scanners. Compared with older generation CT scanners, three newer systems displayed significant improvements in high-contrast detectability over that of their predecessors. A fourth, newer system had lower performance. The CHO MO was appropriate for assessing LCD performance and revealed that an excellent level of image quality could be obtained with newer scanners at significantly lower dose levels. This study shows that MO can objectively benchmark CT scanners using a task-based image quality method, thus helping to estimate the potential for further dose reductions offered by the latest systems. Such an approach may be useful for adequately and quantitatively comparing clinically relevant image quality among various scanners.

Rationale and Objectives To compare adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) algorithms for reduced-dose computed tomography (CT). Materials and Methods Forty-four young oncology patients (mean age 30 ± 9 years) were included. After routine thoraco-abdominal CT (dose 100%, average CTDIvol 9.1 ± 2.4 mGy, range 4.4–16.9 mGy), follow-up CT was acquired at 50% (average CTDIvol 4.5 ± 1.2 mGy, range 2.2–8.4 mGy) in 29 patients additionally at 20% dose (average CTDIvol 1.9 ± 0.5 mGy, range 0.9–3.4 mGy). Each reduced-dose CT was reconstructed using both ASIR and MBIR. Four radiologists (two juniors and two seniors) blinded to dose and technique read each set of CT images regarding objective and subjective image qualities (high- or low-contrast structures), subjective noise or pixilated appearance, diagnostic confidence, and lesion detection. Results At all dose levels, objective image noise was significantly lower with MBIR than with ASIR (P

Aim To outline the importance of continuous monitoring of quantitative positron emission tomography (PET) data in multicentre trials to minimize quantitative bias in longitudinal intra-patient PET studies in light of the multicentre SAKK 56/07 experience in quantification and monitoring 18 F-FDG PET/CT data. Patients and methods We collected 64 uniform phantom 18 F-FDG PET acquisitions periodically at the enrolling centres (12 European institutions). A core-laboratory analysed them for standard uptake value (SUV) accuracy (desired 1.00 ± 10%) and acceptable image noise was defined by a coefficient of variation (COV) less than 15%. In total, 151 patients 18 F-FDG PET acquisitions (baseline and follow-up) were also collected and analysed to verify longitudinal coherence of main acquisition/reconstruction parameters (DICOM tags verification) and patient preparation, in particular the uptake time (desired uptake time [UT] = 60 ± 10 min). Results Uniform phantom PET acquisition satisfied the inclusion criteria in 58/64 (89%) examinations. All PET scanner exhibited comparable SUV quantification, but we found large dispersion in terms of noise, with COV ranging 3–15%. Only 1 phantom PET acquisition was out of range with COV = 21.5%. Patient data exhibited important variation in uptake time with UT = 65 ± 10 min (mean ± SD), with only 111/151 (74%) patients’ examinations satisfying inclusion criteria while 26% were out of range. Conclusions Regular monitoring of PET data in multicentre trials is capital to ensure longitudinal intra-patient PET data consistence and minimize quantitative bias while it helps to spread the culture of quality in participating centre. Recent EARL (EANM Research Ltd) standardization and unification of procedures is a welcome step in this direction.

Purpose This study aims to assess CT image quality in a way that would meet specific requirements of clinical practice. Physics metrics like Fourier transform derived metrics were traditionally employed for that. However, assessment methods through a detection task have also developed quite extensively lately, and we chose here to rely on this modality for image quality assessment. Our goal was to develop a tool adapted for a fast and reliable CT image quality assessment in order to pave the way for new CT benchmarking techniques in a clinical context. Additionally, we also used this method to estimate the benefits brought by some IR algorithms. Materials and methods A modified QRM chest phantom containing spheres of 5 and 8 mm at contrast levels of 10 and 20 HU at 120 kVp was used. Images of the phantom were acquired at CTDI vol of 0.8, 3.6, 8.2 and 14.5 mGy, before being reconstructed using FBP, ASIR 40 and MBIR on a GE HD 750 CT scanner. They were then assessed by eight human observers undergoing a 4-AFC test. After that, these data were compared with the results obtained from two different model observers (NPWE and CHO with DDoG channels). The study investigated the effects of the acquisition conditions as well as reconstruction methods. Results NPWE and CHO models both gave coherent results and approximated human observer results well. Moreover, the reconstruction technique used to retrieve the images had a clear impact on the PC values. Both models suggest that switching from FBP to ASIR 40 and particularly to MBIR produces an increase of the low contrast detection, provided a minimum level of exposure is reached. Conclusion Our work shows that both CHO with DDoG channels and NPWE models both approximate the trend of humans performing a detection task. Both models also suggest that the use of MBIR goes along with an increase of the PCs, indicating that further dose reduction is still possible when using those techniques. Eventually, the CHO model associated to the protocol we described in this study happened to be an efficient way to assess CT images in a clinical environment. In the future, this simple method could represent a sound basis to benchmark clinical practice and CT devices.

Background We assessed and compared image quality obtained with clinical 18F-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

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.

In 2013, a nationwide investigation was conducted in Switzerland to establish the population's exposure from medical X rays. A hybrid approach was used combining the Raddose database accessible on-line by the participating practices and the Swiss medical tariffication system for hospitals. This study revealed that the average annual number of examinations is 1.2 per inhabitant, and the associated annual effective dose is 1.4 mSv. It also showed that computed tomography is the most irradiating modality and that it delivers 70 % of the total dose. The annual effective dose per inhabitant registered a 17 % increase in 5 y and is comparable with what was recently reported in neighbouring countries.

Aim. Similar to PET, absolute quantitative imaging is becoming available in commercial SPECT/CT devices. This study’s goal was to assess quantitative accuracy of activity recovery as a function of image reconstruction parameters and count statistics in a variety of phantoms. Materials and Methods. We performed quantitative Tc99m-SPECT/CT acquisitions (Siemens Symbia Intevo, Erlangen, Germany) of a uniform cylindrical, NEMA/IEC, and an anthropomorphic abdominal phantom. Background activity concentrations tested ranged: 2–80 kBq/mL. SPECT acquisitions used 120 projections (20 s/projection). Reconstructions were performed with the proprietary iterative conjugate gradient algorithm. NEMA phantom reconstructions were obtained as a function of the iteration number (range: 4–48). Recovery coefficients, hot contrast, relative lung error (NEMA phantom), and image noise were assessed. Results. In all cases, absolute activity and activity concentration were measured within 10% of the expected value. Recovery coefficients and hot contrast in hot inserts did not vary appreciably with count statistics. RC converged at 16 iterations for insert size > 22 mm. Relative lung errors were comparable to PET levels indicating the efficient integration of attenuation and scatter corrections with adequate detector modeling. Conclusions. The tested device provided accurate activity recovery within 10% of correct values; these performances are comparable to current generation PET/CT systems.

Purpose Iterative algorithms introduce new challenges in the field of image quality assessment. The purpose of this study is to use a mathematical model to evaluate objectively the low contrast detectability in CT. Materials and methods A QRM 401 phantom containing 5 and 8 mm diameter spheres with a contrast level of 10 and 20 HU was used. The images were acquired at 120 kV with CTDIvol equal to 5, 10, 15, 20 mGy and reconstructed using the filtered back-projection (FBP), adaptive statistical iterative reconstruction 50% (ASIR 50%) and model-based iterative reconstruction (MBIR) algorithms. The model observer used is the Channelized Hotelling Observer (CHO). The channels are dense difference of Gaussian channels (D-DOG). The CHO performances were compared to the outcomes of six human observers having performed four alternative forced choice (4-AFC) tests. Results For the same CTDIvol level and according to CHO model, the MBIR algorithm gives the higher detectability index. The outcomes of human observers and results of CHO are highly correlated whatever the dose levels, the signals considered and the algorithms used when some noise is added to the CHO model. The Pearson coefficient between the human observers and the CHO is 0.93 for FBP and 0.98 for MBIR. Conclusion The human observers' performances can be predicted by the CHO model. This opens the way for proposing, in parallel to the standard dose report, the level of low contrast detectability expected. The introduction of iterative reconstruction requires such an approach to ensure that dose reduction does not impair diagnostics.

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°. Temperature measurements showed a 4% decrease of photon count when increasing the temperature from 10 °C to 36 °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.

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.

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.

Definition of new national diagnostic reference levels (DRLs) for volume computed tomography dose index (CTDI vol ) and dose length product (DLP) for neuro-paediatric CT examinations depending on the medical indication. Paediatric cranial CT data sets acquired between January 2013 and December 2016 were retrospectively collected between July 2016 and March 2017 from eight of the largest university and cantonal hospitals that perform most of the neuro-paediatric CTs in Switzerland. A consensus review of CTDI vol and DLP was undertaken for three defined anatomical regions: brain, facial bone, and petrous bone, each with and without contrast medium application. All indications for cranial CT imaging in paediatrics were assigned to one of these three regions. Descriptive statistical analysis of the distribution of the median values for CTDI vol and DLP yielded values in the minimum, maximum, 25th percentile (1st quartile), median (2nd quartile), and 75th percentile (3rd quartile). New DRLs for neuro-paediatric CT examinations in Switzerland were based on the 75th percentiles of the distributions of the median values of all eight centres. Where appropriate, values were rounded such that the DRLs increase or at least remain constant as the age of the patient increases. Our results revealed DRLs for CTDI vol and DLP up to 20% lower than the DRLs used so far in Switzerland and elsewhere in Europe. This study provides Swiss neuro-paediatric CT DRL values to establish optimum conditions for paediatric cranial CT examinations. Periodic national updates of DRLs, following international comparisons, are essential.

This study compared different acquisition protocols performance to detect small liver metastases (

The purpose was to compare the image quality and patient dose between 4- and 16-row MDCT units and to evaluate the dispersion of the dose delivered for common clinical examinations. Four 4- and 16-row MDCT units were used in the study. Image noise levels from images of a CatPhan phantom were compared for all units using a given CTDI(vol) of 15.0+/-1.0 mGy. Standard acquisition protocols from ten centres, shifted from 4- to 16-row MDCT (plus one additional centre for 16-row MDCT), were compared for cerebral angiography and standard chest and abdomen examinations. In addition, the protocols used with 16-row MDCT units for diagnosis of the unstable shoulder and for cardiac examinations were also compared. The introduction of 16-MSCT units did not reduce the performance of the detectors. Concerning the acquisition protocols, a wide range in practice was observed for standard examinations; DLP varied from 800 to 5,120 mGy x cm, 130 to 860 mGy x cm, 410 to 1,790 mGy x cm and 850 to 2,500 mGy x cm for cerebral angiography, standard chest, standard abdomen and heart examinations, respectively. The introduction of 16-row MDCT did not, on average, increase the patient dose for standard chest and abdominal examinations. However, a significant dose increase has been observed for cerebral angiography. There is a wide dispersion in the doses delivered, especially for cardiac imaging.

The purpose of this paper is to compare the influence of detector collimation on the signal-to-noise ratio (SNR) for a 5.0 mm reconstructed slice thickness for four multi-detector row CT (MDCT) units. SNRs were measured on Catphan test phantom images from four MDCT units: a GE LightSpeed QX/I, a Marconi MX 8000, a Toshiba Aquilion and a Siemens Volume Zoom. Five-millimetre-thick reconstructed slices were obtained from acquisitions performed using detector collimations of 2.0-2.5 mm and 5.0 mm, 120 kV, a 360 degrees tube rotation time of 0.5 s, a wide range of mA and pitch values in the range of 0.75-0.85 and 1.25-1.5. For each set of acquisition parameters, a Wiener spectrum was also calculated. Statistical differences in SNR for the different acquisition parameters were evaluated using a Student's t-test (P0.05). The influence of detector collimation on the SNR for a 5.0-mm reconstructed slice thickness is different for different MDCT scanners. At pitch values lower than unity, the use of a small detector collimation to produce 5.0-mm thick slices is beneficial for one unit and detrimental for another. At pitch values higher than unity, using a small detector collimation is beneficial for two units. One manufacturer uses different reconstruction filters when switching from a 2.5- to a 5.0-mm detector collimation. For a comparable reconstructed slice thickness, using a smaller detector collimation does not always reduce image noise. Thus, the impact of the detector collimation on image noise should be determined by standard deviation calculations, and also by assessing the power spectra of the noise.

BACKGROUND: Radiation dose exposure is of particular concern in children due to the possible harmful effects of ionizing radiation. The adaptive statistical iterative reconstruction (ASIR) method is a promising new technique that reduces image noise and produces better overall image quality compared with routine-dose contrast-enhanced methods. OBJECTIVE: To assess the benefits of ASIR on the diagnostic image quality in paediatric cardiac CT examinations. MATERIALS AND METHODS: Four paediatric radiologists based at two major hospitals evaluated ten low-dose paediatric cardiac examinations (80 kVp, CTDI(vol) 4.8-7.9 mGy, DLP 37.1-178.9 mGy·cm). The average age of the cohort studied was 2.6 years (range 1 day to 7 years). Acquisitions were performed on a 64-MDCT scanner. All images were reconstructed at various ASIR percentages (0-100%). For each examination, radiologists scored 19 anatomical structures using the relative visual grading analysis method. To estimate the potential for dose reduction, acquisitions were also performed on a Catphan phantom and a paediatric phantom. RESULTS: The best image quality for all clinical images was obtained with 20% and 40% ASIR (p

When performing CT examinations on pregnant patients, great effort should be dedicated towards optimising the exposure of the mother and the conceptus. For this purpose, many radiology departments use high-Z garments to be wrapped around the patient's lower abdomen for out-of-plane organ shielding to protect the fetus. To assess their current protection efficiency, we performed a literature review and compared the efficiencies mentioned in the literature to Monte-Carlo calculations of CT protocols for which the overall scan length was reduced. We found 11 relevant articles, all of them reporting uterus exposure due to CT imaging performed for exclusion of pulmonary embolism, one of the leading causes of peripartum deaths in western countries. Uterus doses ranged between 60 and 660 µGy per examination, and relative dose reductions to the uterus due to high-Z garments were between 20 and 56%. Calculations showed that reducing the scan length by one to three centimetres could potentially reduce uterus dose up to 24% for chest imaging, and even 47% for upper abdominal imaging. These dose reductions were in the order of those achieved by high-Z garments. However, using the latter may negatively influence the diagnostic image quality and even interfere with the automatic exposure control system thus increasing patient dose if positioned in the primary beam, for example in the overranging length in helical acquisition. We conclude that efforts should be concentrated on positioning the patient correctly in the gantry and optimising protocol parameters, rather than using high-Z garments for out-of-plane uterus shielding.

Computed tomography (CT) is a modality of choice for the study of the musculoskeletal system for various indications including the study of bone, calcifications, internal derangements of joints (with CT arthrography), as well as periprosthetic complications. However, CT remains intrinsically limited by the fact that it exposes patients to ionizing radiation. Scanning protocols need to be optimized to achieve diagnostic image quality at the lowest radiation dose possible. In this optimization process, the radiologist needs to be familiar with the parameters used to quantify radiation dose and image quality. CT imaging of the musculoskeletal system has certain specificities including the focus on high-contrast objects (i.e., in CT of bone or CT arthrography). These characteristics need to be taken into account when defining a strategy to optimize dose and when choosing the best combination of scanning parameters. In the first part of this review, we present the parameters used for the evaluation and quantification of radiation dose and image quality. In the second part, we discuss different strategies to optimize radiation dose and image quality of CT, with a focus on the musculoskeletal system and the use of novel iterative reconstruction techniques.

Fluoroscopically guided procedures might be highly irradiating for patients, possibly leading to skin injuries. In such a context, every effort should be done to lower patient exposure as much as possible. Moreover, patient dose reduction does not only benefit to the patient but also allows reducing staff exposure. In this framework, Philips Healthcare recently introduced a system upgrade for their angiography units, called 'AlluraClarity'. The authors performed air kerma rate measurements for all available fluoroscopy modes and air kerma per frame measurements for the digital subtraction angiography protocols, along with subjective spatial resolution and low-contrast detectability assessments using a standard QA phantom. Air kerma reductions ranging from 25.5 to 84.4 % were found, with no significant change in image quality when switching from a standard operating mode to an upgraded version. These results are confirmed by the comparison of actual patient exposures for similar procedures.

Purpose: Signal detection on 3D medical images depends on many factors, such as foveal and peripheral vision, the type of signal, and background complexity, and the speed at which the frames are displayed. In this paper, the authors focus on the speed with which radiologists and naive observers search through medical images. Prior to the study, the authors asked the radiologists to estimate the speed at which they scrolled through CT sets. They gave a subjective estimate of 5 frames per second (fps). The aim of this paper is to measure and analyze the speed with which humans scroll through image stacks, showing a method to visually display the behavior of observers as the search is made as well as measuring the accuracy of the decisions. This information will be useful in the development of model observers, mathematical algorithms that can be used to evaluate diagnostic imaging systems. Methods: The authors performed a series of 3D 4-alternative forced-choice lung nodule detection tasks on volumetric stacks of chest CT images iteratively reconstructed in lung algorithm. The strategy used by three radiologists and three naive observers was assessed using an eye-tracker in order to establish where their gaze was fixed during the experiment and to verify that when a decision was made, a correct answer was not due only to chance. In a first set of experiments, the observers were restricted to read the images at three fixed speeds of image scrolling and were allowed to see each alternative once. In the second set of experiments, the subjects were allowed to scroll through the image stacks at will with no time or gaze limits. In both static-speed and free-scrolling conditions, the four image stacks were displayed simultaneously. All trials were shown at two different image contrasts. Results: The authors were able to determine a histogram of scrolling speeds in frames per second. The scrolling speed of the naive observers and the radiologists at the moment the signal was detected was measured at 25–30 fps. For the task chosen, the performance of the observers was not affected by the contrast or experience of the observer. However, the naive observers exhibited a different pattern of scrolling than the radiologists, which included a tendency toward higher number of direction changes and number of slices viewed. Conclusions: The authors have determined a distribution of speeds for volumetric detection tasks. The speed at detection was higher than that subjectively estimated by the radiologists before the experiment. The speed information that was measured will be useful in the development of 3D model observers, especially anthropomorphic model observers which try to mimic human behavior.

The number of fluoroscopy-guided procedures in cardiology is increasing over time and it is appropriate to wonder whether technological progress or change of techniques is influencing patient exposure. The aim of this study is to examine whether patient dose has been decreasing over the years. Patient dose data of more than 7700 procedures were collected from two cardiology centres. A steady increase in the patient dose over the years was observed in both the centres for the two cardiological procedures included in this study. Significant increase in dose was also observed after the installation of a flat-panel detector. The increasing use of radial access may lead to an increase in the patient exposure. The monitoring of dose data over time showed a considerable increase in the patient exposure over time. Actions have to be taken towards dose reduction in both the centres.

This work aims at establishing a set of diagnostic reference levels (DRLs) for various types of examinations performed in diagnostic and interventional radiology. The average doses for 257 types of radiological examinations were established during the 1998 nationwide survey on the exposure of the Swiss population by radiodiagnostics. They were calculated using appropriate dosimetric models and average technical parameters. The DRLs were derived from the average doses using a multiplying factor of 1.5. The DRLs obtained were rounded and compared to the data reported in the literature. The results are in most cases comparable to the DRLs determined by the 3rd-quartile method. These discrepancies registered in some cases, particularly for complex examinations, can be explained by significant differences in the protocols and/or the technical parameters used. A set of DRLs is proposed for a large number of examinations to be used in Switzerland as temporary values until a national dosimetric database is set up.

A wide variation in patient exposure has been observed in interventional radiology and cardiology. The purpose of this study was to investigate the patient dose from fluoroscopy-guided procedures performed in non-academic centres when compared with academic centres. Four procedures (coronary angiography, percutaneous coronary intervention, angiography of the lower limbs and percutaneous transluminal angioplasty of the lower limbs) were evaluated. Data on the dose-area product, fluoroscopy time and number of images for 1000 procedures were obtained from 23 non-academic centres and compared with data from 5 academic centres. No differences were found for cardiology procedures performed in non-academic centres versus academic ones. However, significantly lower doses were delivered to patients for procedures of the lower limbs when they were performed in non-academic centres. This may be due to more complex procedures performed in the academic centres. Comparison between the centres showed a great variation in the patient dose for these lower limb procedures.

The age of the patient is of prime importance when assessing the radiological risk to patients due to medical X-ray exposures and the total detriment to the population due to radiodiagnostics. In order to take into account the age-specific radiosensitivity, three age groups are considered: children, adults and the elderly. In this work, the relative number of examinations carried out on paediatric and geriatric patients is established, compared with adult patients, for radiodiagnostics as a whole, for dental and medical radiology, for 8 radiological modalities as well as for 40 types of X-ray examinations. The relative numbers of X-ray examinations are determined based on the corresponding age distributions of patients and that of the general population. Two broad groups of X-ray examinations may be defined. Group A comprises conventional radiography, fluoroscopy and computed tomography; for this group a paediatric patient undergoes half the number of examinations as that of an adult, and a geriatric patient undergoes 2.5 times more. Group B comprises angiography and interventional procedures; for this group a paediatric patient undergoes a one-fourth of the number of examinations carried out on an adult, and a geriatric patient undergoes five times more.

This work proposes a method for assessing the detective quantum efficiency (DQE) of radiographic imaging systems that include both the x-ray detector and the antiscatter device. Cascaded linear analysis of the antiscatter device efficiency (DQEASD) with the x-ray detector DQE is used to develop a metric of system efficiency (DQEsys); the new metric is then related to the existing system efficiency parameters of effective DQE (eDQE) and generalized DQE (gDQE). The effect of scatter on signal transfer was modelled through its point spread function (PSF), leading to an x-ray beam transfer function (BTF) that multiplies with the classical presampling modulation transfer function (MTF) to give the system MTF. Expressions are then derived for the influence of scattered radiation on signal-difference to noise ratio (SDNR) and contrast-detail (c-d) detectability. The DQEsys metric was tested using two digital mammography systems, for eight x-ray beams (four with and four without scatter), matched in terms of effective energy. The model was validated through measurements of contrast, SDNR and MTF for poly(methyl)methacrylate thicknesses covering the range of scatter fractions expected in mammography. The metric also successfully predicted changes in c-d detectability for different scatter conditions. Scatter fractions for the four beams with scatter were established with the beam stop method using an extrapolation function derived from the scatter PSF, and validated through Monte Carlo (MC) simulations. Low-frequency drop of the MTF from scatter was compared to both theory and MC calculations. DQEsys successfully quantified the influence of the grid on SDNR and accurately gave the break-even object thickness at which system efficiency was improved by the grid. The DQEsys metric is proposed as an extension of current detector characterization methods to include a performance evaluation in the presence of scattered radiation, with an antiscatter device in place. ispartof: Physics in Medicine and Biology vol:62 issue:14 pages:5691-5722 ispartof: location:England status: published

Image quality assessment is crucial for the optimization of computed tomography (CT) protocols. Human and mathematical model observers are increasingly used for the detection of low contrast signal in abdominal CT, but are frequently limited to the use of a single image slice. Another limitation is that most of them only consider the detection of a signal embedded in a uniform background phantom. The purpose of this paper was to test if human observer performance is significantly different in CT images read in single or multiple slice modes and if these differences are the same for anatomical and uniform clinical images. We investigated detection performance and scrolling trends of human observers of a simulated liver lesion embedded in anatomical and uniform CT backgrounds. Results show that observers don’t take significantly benefit of additional information provided in multi-slice reading mode. Regarding the background, performances are moderately higher for uniform than for anatomical images. Our results suggest that for low contrast detection in abdominal CT, the use of multi-slice model observers would probably only add a marginal benefit. On the other hand, the quality of a CT image is more accurately estimated with clinical anatomical backgrounds.

Major technological advances in CT enable the acquisition of high quality images while minimizing patient exposure. The goal of this study was to objectively compare two generations of iterative reconstruction (IR) algorithms for the detection of low contrast structures. An abdominal phantom (QRM, Germany), containing 8, 6 and 5mm-diameter spheres (with a nominal contrast of 20HU) was scanned using our standard clinical noise index settings on a GE CT: “Discovery 750 HD”. Two additional rings (2.5 and 5 cm) were also added to the phantom. Images were reconstructed using FBP, ASIR-50%, and VEO (full statistical Model Based Iterative Reconstruction, MBIR). The reconstructed slice thickness was 2.5 mm except 0.625 mm for VEO reconstructions. NPS was calculated to highlight the potential noise reduction of each IR algorithm. To assess LCD (low Contrast Detectability), a Channelized Hotelling Observer (CHO) with 10 DDoG channels was used with the area under the curve (AUC) as a figure of merit. Spheres contrast was also measured. ASIR-50% allowed a noise reduction by a factor two when compared to FBP without an improvement of the LCD. VEO allowed an additional noise reduction with a thinner slice thickness compared to ASIR-50% but with a major improvement of the LCD especially for the large-sized phantom and small lesions. Contrast decreased up to 10% with the phantom size increase for FBP and ASIR-50% and remained constant with VEO. VEO is particularly interesting for LCD when dealing with large patients and small lesion sizes and when the detection task is difficult.

Since January 2008-de facto 2012-medical physics experts (MPEs) are, by law, to be involved in the optimisation process of radiological diagnostic procedures in Switzerland. Computed tomography, fluoroscopy and nuclear medicine imaging units have been assessed for patient exposure and image quality. Large spreads in clinical practice have been observed. For example, the number of scans per abdominal CT examination went from 1 to 9. Fluoroscopy units showed, for the same device settings, dose rate variations up to a factor of 3 to 7. Quantitative image quality for positron emission tomography (PET)/CT examinations varied significantly depending on the local image reconstruction algorithms. Future work will be focused on promoting team cooperation between MPEs, radiologists and radiographers and on implementing task-oriented objective image quality indicators.

The purpose of this article is to assess the effect of the adaptive statistical iterative reconstruction (ASIR) technique on image quality in hip MDCT arthrography and to evaluate its potential for reducing radiation dose.Thirty-seven patients examined with hip MDCT arthrography were prospectively randomized into three different protocols: one with a regular dose (volume CT dose index [CTDIvol], 38.4 mGy) and two with a reduced dose (CTDIvol, 24.6 or 15.4 mGy). Images were reconstructed using filtered back projection (FBP) and four increasing percentages of ASIR (30%, 50%, 70%, and 90%). Image noise and contrast-to-noise ratio (CNR) were measured. Two musculoskeletal radiologists independently evaluated several anatomic structures and image quality parameters using a 4-point scale. They also jointly assessed acetabular labrum tears and articular cartilage lesions.With decreasing radiation dose level, image noise statistically significantly increased (p=0.0009) and CNR statistically significantly decreased (p=0.001). We also found a statistically significant reduction in noise (p=0.0001) and increase in CNR (p≤0.003) with increasing percentage of ASIR; in addition, we noted statistically significant increases in image quality scores for the labrum and cartilage, subchondral bone, overall diagnostic quality (up to 50% ASIR), and subjective noise (p≤0.04), and statistically significant reductions for the trabecular bone and muscles (p≤0.03). Regardless of the radiation dose level, there were no statistically significant differences in the detection and characterization of labral tears (n=24; p=1) and cartilage lesions (n=40; p≥0.89) depending on the ASIR percentage.The use of up to 50% ASIR in hip MDCT arthrography helps to reduce radiation dose by approximately 35-60%, while maintaining diagnostic image quality comparable to that of a regular-dose protocol using FBP.

Given the adverse impact of image noise on the perception of important clinical details in digital mammography, routine quality control measurements should include an evaluation of noise. The European Guidelines, for example, employ a second-order polynomial fit of pixel variance as a function of detector air kerma (DAK) to decompose noise into quantum, electronic and fixed pattern (FP) components and assess the DAK range where quantum noise dominates. This work examines the robustness of the polynomial method against an explicit noise decomposition method. The two methods were applied to variance and noise power spectrum (NPS) data from six digital mammography units. Twenty homogeneously exposed images were acquired with PMMA blocks for target DAKs ranging from 6.25 to 1600 µGy. Both methods were explored for the effects of data weighting and squared fit coefficients during the curve fitting, the influence of the additional filter material (2 mm Al versus 40 mm PMMA) and noise de-trending. Finally, spatial stationarity of noise was assessed.Data weighting improved noise model fitting over large DAK ranges, especially at low detector exposures. The polynomial and explicit decompositions generally agreed for quantum and electronic noise but FP noise fraction was consistently underestimated by the polynomial method. Noise decomposition as a function of position in the image showed limited noise stationarity, especially for FP noise; thus the position of the region of interest (ROI) used for noise decomposition may influence fractional noise composition. The ROI area and position used in the Guidelines offer an acceptable estimation of noise components. While there are limitations to the polynomial model, when used with care and with appropriate data weighting, the method offers a simple and robust means of examining the detector noise components as a function of detector exposure.

The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.