Optimization of CT pulmonary angiography for pulmonary embolism using task-based image quality assessment and diagnostic reference levels: A multicentric study.

PURPOSE: To establish size-specific diagnostic reference levels (DRLs) for pulmonary embolism (PE) based on patient CT examinations performed on 74 CT devices. To assess task-based image quality (IQ) for each device and to investigate the variability of dose and IQ across different CTs. To propose a dose/IQ optimization. METHODS: 1051 CT pulmonary angiography dose data were collected. DRLs were calculated as the 75th percentile of CT dose index (CTDI) for two patient categories based on the thoracic perimeters. IQ was assessed with two thoracic phantom sizes using local acquisition parameters and three other dose levels. The area under the ROC curve (AUC) of a 2 mm low perfused vessel was assessed with a non-prewhitening with eye-filter model observer. The optimal IQ-dose point was mathematically assessed from the relationship between IQ and dose. RESULTS: The DRLs of CTDIvol were 6.4 mGy and 10 mGy for the two patient categories. 75th percentiles of phantom CTDIvol were 6.3 mGy and 10 mGy for the two phantom sizes with inter-quartile AUC values of 0.047 and 0.066, respectively. After the optimization, 75th percentiles of phantom CTDIvol decreased to 5.9 mGy and 7.55 mGy and the interquartile AUC values were reduced to 0.025 and 0.057 for the two phantom sizes. CONCLUSION: DRLs for PE were proposed as a function of patient thoracic perimeters. This study highlights the variability in terms of dose and IQ. An optimization process can be started individually and lead to a harmonization of practice throughout multiple CT sites.

Gated cardiac CT in infants: What can we expect from deep learning image reconstruction algorithm?

BACKGROUND: ECG-gated cardiac CT is now widely used in infants with congenital heart disease (CHD). Deep Learning Image Reconstruction (DLIR) could improve image quality while minimizing the radiation dose. OBJECTIVES: To define the potential dose reduction using DLIR with an anthropomorphic phantom. METHOD: An anthropomorphic pediatric phantom was scanned with an ECG-gated cardiac CT at four dose levels. Images were reconstructed with an iterative and a deep-learning reconstruction algorithm (ASIR-V and DLIR). Detectability of high-contrast vessels were computed using a mathematical observer. Discrimination between two vessels was assessed by measuring the CT spatial resolution. The potential dose reduction while keeping a similar level of image quality was assessed. RESULTS: DLIR-H enhances detectability by 2.4% and discrimination performances by 20.9% in comparison with ASIR-V 50. To maintain a similar level of detection, the dose could be reduced by 64% using high-strength DLIR in comparison with ASIR-V50. CONCLUSION: DLIR offers the potential for a substantial dose reduction while preserving image quality compared to ASIR-V.

Chances and challenges of photon-counting CT in musculoskeletal imaging.

In musculoskeletal imaging, CT is used in a wide range of indications, either alone or in a synergistic approach with MRI. While MRI is the preferred modality for the assessment of soft tissues and bone marrow, CT excels in the imaging of high-contrast structures, such as mineralized tissue. Additionally, the introduction of dual-energy CT in clinical practice two decades ago opened the door for spectral imaging applications. Recently, the advent of photon-counting detectors (PCDs) has further advanced the potential of CT, at least in theory. Compared to conventional energy-integrating detectors (EIDs), PCDs provide superior spatial resolution, reduced noise, and intrinsic spectral imaging capabilities. This review briefly describes the technical advantages of PCDs. For each technical feature, the corresponding applications in musculoskeletal imaging will be discussed, including high-spatial resolution imaging for the assessment of bone and crystal deposits, low-dose applications such as whole-body CT, as well as spectral imaging applications including the characterization of crystal deposits and imaging of metal hardware. Finally, we will highlight the potential of PCD-CT in emerging applications, underscoring the need for further preclinical and clinical validation to unleash its full clinical potential.

Photon-Counting Detector CT for Liver Lesion Detection-Optimal Virtual Monoenergetic Energy for Different Simulated Patient Sizes and Radiation Doses.

OBJECTIVES: The aim of this study was to evaluate the optimal energy level of virtual monoenergetic images (VMIs) from photon-counting detector computed tomography (CT) for the detection of liver lesions as a function of phantom size and radiation dose. MATERIALS AND METHODS: An anthropomorphic abdominal phantom with liver parenchyma and lesions was imaged on a dual-source photon-counting detector CT at 120 kVp. Five hypoattenuating lesions with a lesion-to-background contrast difference of -30 HU and -45 HU and 3 hyperattenuating lesions with +30 HU and +90 HU were used. The lesion diameter was 5-10 mm. Rings of fat-equivalent material were added to emulate medium- or large-sized patients. The medium size was imaged at a volume CT dose index of 5, 2.5, and 1.25 mGy and the large size at 5 and 2.5 mGy, respectively. Each setup was imaged 10 times. For each setup, VMIs from 40 to 80 keV at 5 keV increments were reconstructed with quantum iterative reconstruction at a strength level of 4 (QIR-4). Lesion detectability was measured as area under the receiver operating curve (AUC) using a channelized Hotelling model observer with 10 dense differences of Gaussian channels. RESULTS: Overall, highest detectability was found at 65 and 70 keV for both hypoattenuating and hyperattenuating lesions in the medium and large phantom independent of radiation dose (AUC range, 0.91-1.0 for the medium and 0.94-0.99 for the large phantom, respectively). The lowest detectability was found at 40 keV irrespective of the radiation dose and phantom size (AUC range, 0.78-0.99). A more pronounced reduction in detectability was apparent at 40-50 keV as compared with 65-75 keV when radiation dose was decreased. At equal radiation dose, detection as a function of VMI energy differed stronger for the large size as compared with the medium-sized phantom (12% vs 6%). CONCLUSIONS: Detectability of hypoattenuating and hyperattenuating liver lesions differed between VMI energies for different phantom sizes and radiation doses. Virtual monoenergetic images at 65 and 70 keV yielded highest detectability independent of phantom size and radiation dose.

Brain image quality according to beam collimation width and image reconstruction algorithm: A phantom study.

PURPOSE: To compare quantitatively and qualitatively brain image quality acquired in helical and axial modes on two wide collimation CT systems according to the dose level and algorithm used. METHODS: Acquisitions were performed on an image quality and an anthropomorphic phantoms at three dose levels (CTDIvol: 45/35/25 mGy) on two wide collimation CT systems (GE Healthcare and Canon Medical Systems) in axial and helical modes. Raw data were reconstructed using iterative reconstruction (IR) and deep-learning image reconstruction (DLR) algorithms. The noise power spectrum (NPS) was computed on both phantoms and the task-based transfer function (TTF) on the image quality phantom. The subjective quality of images from an anthropomorphic brain phantom was evaluated by two radiologists including overall image quality. RESULTS: For the GE system, noise magnitude and noise texture (average NPS spatial frequency) were lower with DLR than with IR. For the Canon system, noise magnitude values were lower with DLR than with IR for similar noise texture but the opposite was true for spatial resolution. For both CT systems, noise magnitude was lower with the axial mode than with the helical mode for similar noise texture and spatial resolution. Radiologists rated the overall quality of all brain images as "satisfactory for clinical use", whatever the dose level, algorithm or acquisition mode. CONCLUSIONS: Using 16-cm axial acquisition reduces image noise without changing the spatial resolution and image texture compared to helical acquisitions. Axial acquisition can be used in clinical routine for brain CT examinations with an explored length of less than 16 cm.

Clinical commissioning of the first point-of-care spectral photon-counting CT for the upper extremities.

BACKGROUND: Acceptance testing and quality assurance (QA) of computed tomography (CT) scans are of great importance to ensure the appropriate performance of the systems. However, current standards and guidelines do not include a dedicated QA program for spectral photon-counting CT (SPCCT), nor adapted tolerance levels. PURPOSE: To evaluate the technical performance, in terms of image quality and radiation dose, of the first point-of-care SPCCT for the upper extremities (MARS Extremity 5X120, MARS Bioimaging Ltd., Christchurch, New Zealand) and to establish a comprehensive QA program. METHODS: The specific dimensions of the scanner with a 125 mm diameter gantry and a small voxel size of 0.1 × 0.1 × 0.1 mm3 require the use of suitable phantoms and evaluation techniques. Indicators such as CT number accuracy, image noise, uniformity, and slice thickness were assessed to characterize the image quality. The in-plane and longitudinal spatial resolutions were evaluated by means of the modulation transfer function (MTF). Noise power spectra (NPS) were calculated to further evaluate the image noise. Material identification capabilities were assessed using clinically relevant high-Z materials (iodine, gold, gadolinium, and calcium). A 100-mm diameter CTDI-like phantom was used to measure the dose indices. A complete radiation survey was carried out to measure the radiation exposure at different points around the scanner. RESULTS: The proposed QA program is based on international and local recommendations as well as practical experience. It includes standardised CT tests and SPCCT-specific methods. Additional methodologies to further assess the system performance are also presented. Tolerance levels are discussed and revised when appropriate. Both in-plane and longitudinal high spatial resolutions were evidenced by the MTF measurements with 1.8 lp· mm-1 and 5.0 lp· mm-1 at 10%, respectively. The calculated effective slice thickness ranged between 0.15 and 0.16 mm for the five energy bins and for a reconstructed voxel size of 0.1 × 0.1 × 0.1 mm3 . Reference values of the linear attenuation coefficient of water have been calculated and used to assess the CT number uniformity of water. Evaluation of the CT number accuracy and stability of various clinically relevant materials showed excellent spectral correlation and linearity between HU values and concentrations (r2 > 0.99). The NPS showed less noise correlation between slices than within transverse slice, as well as a systematic increase at low spatial frequencies. The volume CT dose index (CTDI v o l $_{vol}$ ) for a custom-made 100 mm diameter phantom was 9.32 mGy. Radiation measurements around the scanner showed that it is completely shielded except for the access port, and that no additional protective measures are necessary for the patient. CONCLUSIONS: A routine QA framework for SPCCT systems has been proposed. Image quality and radiation dose were assessed using newly designed phantoms, relevant metrics, and automated algorithms. Baseline values were established and tolerance levels discussed for the MARS SPCCT scanner based on collected data and international recommendations.

Photon-Counting Detector CT With Quantum Iterative Reconstruction: Impact on Liver Lesion Detection and Radiation Dose Reduction.

OBJECTIVES: To assess image noise, diagnostic performance, and potential for radiation dose reduction of photon-counting detector (PCD) computed tomography (CT) with quantum iterative reconstruction (QIR) in the detection of hypoattenuating and hyperattenuating focal liver lesions compared with energy-integrating detector (EID) CT. MATERIALS AND METHODS: A medium-sized anthropomorphic abdominal phantom with liver parenchyma and lesions (diameter, 5-10 mm; hypoattenuating and hyperattenuating from -30 HU to +90 HU at 120 kVp) was used. The phantom was imaged on ( a ) a third-generation dual-source EID-CT (SOMATOM Force, Siemens Healthineers) in the dual-energy mode at 100 and 150 kVp with tin filtration and ( b ) a clinical dual-source PCD-CT at 120 kVp (NAEOTOM Alpha, Siemens). Scans were repeated 10 times for each of 3 different radiation doses of 5, 2.5, and 1.25 mGy. Datasets were reconstructed as virtual monoenergetic images (VMIs) at 60 keV for both scanners and as linear-blended images (LBIs) for EID-CT. For PCD-CT, VMIs were reconstructed with different strength levels of QIR (QIR 1-4) and without QIR (QIR-off). For EID-CT, VMIs and LBIs were reconstructed using advanced modeled iterative reconstruction at a strength level of 3. Noise power spectrum was measured to compare image noise magnitude and texture. A channelized Hotelling model observer was used to assess diagnostic accuracy for lesion detection. The potential for radiation dose reduction using PCD-CT was estimated for the QIR strength level with the highest area under the curve compared with EID-CT for each radiation dose. RESULTS: Image noise decreased with increasing QIR level at all radiation doses. Using QIR-4, noise reduction was 41%, 45%, and 59% compared with EID-CT VMIs and 12%, 18%, and 33% compared with EID-CT LBIs at 5, 2.5, and 1.25 mGy, respectively. The peak spatial frequency shifted slightly to lower frequencies at higher QIR levels. Lesion detection accuracy increased at higher QIR levels and was higher for PCD-CT compared with EID-CT VMIs. The improvement in detection with PCD-CT was strongest at the lowest radiation dose, with an area under the receiver operating curve of 0.917 for QIR-4 versus 0.677 for EID-CT VMIs for hyperattenuating lesions, and 0.900 for QIR-4 versus 0.726 for EID-CT VMIs for hypoattenuating lesions. Compared with EID-CT LBIs, detection was higher for QIR 1-4 at 2.5 mGy and for QIR 2-4 at 1.25 mGy (eg, 0.900 for QIR-4 compared with 0.854 for EID-CT LBIs at 1.25 mGy). Radiation dose reduction potential of PCD-CT with QIR-4 was 54% at 5 mGy compared with VMIs and 39% at 2.5 mGy compared with LBIs. CONCLUSIONS: Compared with EID-CT, PCD-CT with QIR substantially improved focal liver lesion detection, especially at low radiation dose. This enables substantial radiation dose reduction while maintaining diagnostic accuracy.

Phantom task-based image quality assessment of three generations of rapid kV-switching dual-energy CT systems on virtual monoenergetic images.

PURPOSE: To compare the spectral performance of three rapid kV switching dual-energy CT (DECT) systems on virtual monoenergetic images (VMIs) at low-energy levels on abdominal imaging. METHODS: A multi-energy phantom was scanned on three DECT systems equipped with three different gemstone spectral imaging (GSI) platforms: GSI (1st generation, GSI-1st), GSI-Pro (2nd generation, GSI-2nd ), and GSI-Xtream (3rd generation, GSI-3rd). Acquisitions on the phantom were performed with a CTDIvol close to 11mGy. For all platforms, raw data were reconstructed using filtered-back projection (FBP) and a hybrid iterative reconstruction algorithm (ASIR-V at 50%; AV50). A deep-learning image reconstruction (DLR) algorithm (TrueFidelity) was used only for the GSI-3rd. Noise power spectrum (NPS) and task-based transfer function (TTF) were evaluated from 40 to 80 keV of VMIs. A detectability index (d') was computed to assess the detection of two contrast-enhanced lesions according to the keV level used. RESULTS: For all GSI platforms, the noise magnitude decreased from 40 to 70 keV, and using AV50 compared to FBP. The average NPS spatial frequency (fav ) and spatial resolution (TTF50% ) were similar from 40 to 70 keV and decreased with AV50 compared to FBP. Compared to AV50, using DLR reduced the noise magnitude (-27% ± 3%) and improved fav values (10% ± 0%) and altering spatial resolution (2% ± 5%). For the two lesions, d' values peaked at 70 keV for GSI-1st and GSI-2nd platforms and at 40/50 keV for GSI-3rd, for all reconstruction algorithms. The highest d' values were found for the GSI-3rd with DLR. CONCLUSION: Differences in image quality were found between the GSI platforms for VMIs at low keV. The new DLR algorithm on the GSI-3rd platform reduced noise and improved spatial resolution and detectability without changing the noise texture for VMIs at low keV. The choice of the best energy level in VMIs depends on the platform and the reconstruction algorithm.

Assessment of task-based image quality for abdominal CT protocols linked with national diagnostic reference levels.

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.

Performance of Spectral Photon-Counting Coronary CT Angiography and Comparison with Energy-Integrating-Detector CT: Objective Assessment with Model Observer.

AIMS: To evaluate spectral photon-counting CT's (SPCCT) objective image quality characteristics in vitro, compared with standard-of-care energy-integrating-detector (EID) CT. METHODS: We scanned a thorax phantom with a coronary artery module at 10 mGy on a prototype SPCCT and a clinical dual-layer EID-CT under various conditions of simulated patient size (small, medium, and large). We used filtered back-projection with a soft-tissue kernel. We assessed noise and contrast-dependent spatial resolution with noise power spectra (NPS) and target transfer functions (TTF), respectively. Detectability indices (d') of simulated non-calcified and lipid-rich atherosclerotic plaques were computed using the non-pre-whitening with eye filter model observer. RESULTS: SPCCT provided lower noise magnitude (9-38% lower NPS amplitude) and higher noise frequency peaks (sharper noise texture). Furthermore, SPCCT provided consistently higher spatial resolution (30-33% better TTF10). In the detectability analysis, SPCCT outperformed EID-CT in all investigated conditions, providing superior d'. SPCCT reached almost perfect detectability (AUC ≈ 95%) for simulated 0.5-mm-thick non-calcified plaques (for large-sized patients), whereas EID-CT had lower d' (AUC ≈ 75%). For lipid-rich atherosclerotic plaques, SPCCT achieved 85% AUC vs. 77.5% with EID-CT. CONCLUSIONS: SPCCT outperformed EID-CT in detecting simulated coronary atherosclerosis and might enhance diagnostic accuracy by providing lower noise magnitude, markedly improved spatial resolution, and superior lipid core detectability.

ANNUAL EXPOSURE OF THE SWISS POPULATION FROM MEDICAL IMAGING IN 2018.

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.

Task-based characterization of a deep learning image reconstruction and comparison with filtered back-projection and a partial model-based iterative reconstruction in abdominal CT: A phantom study.

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.

Channelized Hotelling observer correlation with human observers for low-contrast detection in liver CT images.

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.

Clinical Utility of Multi-Energy Spectral Photon-Counting Computed Tomography in Crystal Arthritis.

OBJECTIVE: To determine whether novel multi-energy spectral photon-counting computed tomography (SPCCT) imaging can detect and differentiate between monosodium urate (MSU), calcium pyrophosphate (CPP), and hydroxyapatite (HA) crystal deposits ex vivo. METHODS: A finger with a subcutaneous gouty tophus and a calcified knee meniscus excised at the time of surgery were obtained. The finger was imaged using plain x-ray, dual-energy CT (DECT), and multi-energy SPCCT. Plain x-ray and multi-energy SPCCT images of the meniscus were acquired. For validation purposes, samples of the crystals were obtained from the tophus and meniscus, and examined by polarized light microscopy and/or x-ray diffraction. As further validation, synthetic crystal suspensions of MSU, CPP, and HA were scanned using multi-energy SPCCT. RESULTS: Plain x-ray of the gouty finger revealed bone erosions with overhanging edges. DECT and multi-energy SPCCT both showed MSU crystal deposits; SPCCT was able to show finer detail. Plain x-ray of the calcified meniscus showed chondrocalcinosis consistent with CPP, while SPCCT showed and differentiated CPP and HA. CONCLUSION: Multi-energy SPCCT can not only detect, differentiate, and quantify MSU crystal deposits in a gouty finger ex vivo, but also specifically detect, identify, and quantify CPP within an osteoarthritic meniscus, and distinguish them from HA crystal deposits. There is potential for multi-energy SPCCT to become useful in the diagnosis of crystal arthropathies.

Task-based quantification of image quality using a model observer in abdominal CT: a multicentre study.

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.

Effects of various generations of iterative CT reconstruction algorithms on low-contrast detectability as a function of the effective abdominal diameter: A quantitative task-based phantom study.

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.

Objective comparison of high-contrast spatial resolution and low-contrast detectability for various clinical protocols on multiple CT scanners.

PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Assessment of low contrast detection in CT using model observers: Developing a clinically-relevant tool for characterising adaptive statistical and model-based iterative reconstruction.

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 8mm at contrast levels of 10 and 20HU at 120kVp was used. Images of the phantom were acquired at CTDIvol of 0.8, 3.6, 8.2 and 14.5mGy, 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.