Objective assessment of low-contrast computed tomography images with iterative reconstruction

ObjectiveThis study aims to assess low-contrast image quality using a low-contrast object specific contrast-to-noise ratio (CNR_LO) analysis for iterative reconstruction (IR) computed tomography (CT) images.MethodsA phantom composed of low-contrast rods placed in a uniform material was used in this study. Images were reconstructed using filtered back projection (FBP) and IR (Adaptive Iterative Dose Reduction 3D). Scans were performed at six dose levels: 1.0, 1.8, 3.1, 4.6, 7.1 and 13.3 mGy. Objective image quality was assessed by comparing CNR_LO with CNR using a human observer test.ResultsCompared with FBP, IR yielded increased CNR at the same dose levels. The results of CNR_LO and observer tests showed similarities or only marginal differences between FBP and IR at the same dose levels. The coefficient of determination for CNR_LO was significantly better (R² = 0.86) than that of CNR (R² = 0.47).ConclusionFor IR, CNR_LO could potentially serve as an objective index reflective of a human observer assessment. The results of CNR_LO test indicated that the IR algorithm was not superior to FBP in terms of low-contrast detectability at the same radiation doses.     

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

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

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

PurposeTo 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.MethodsInvestigations 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 (CTDI_vol, 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.ResultsFor 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.ConclusionIn abdominal CT, switching from FBP to IR algorithms offers limited possibilities for achieving significant dose reductions while ensuring a constant objective LCD.     

Impact of iterative reconstructions on image quality and detectability of focal liver lesions in low-energy monochromatic images

PurposeTo assess the impact of iterative reconstructions on image quality and detectability of focal liver lesions in low-energy monochromatic images from a Fast kV-Switching Dual Energy CT (KVSCT) platform.MethodsAcquisitions on an image-quality phantom were performed using a KVSCT for three dose levels (CTDI_vol:12.72/10.76/8.79 mGy). Raw data were reconstructed for five energy levels (40/50/60/70/80 keV) using Filtered Back Projection (FBP) and four levels of ASIR (ASIR30/ASIR50/ASIR70/ASIR100). Noise power spectrum (NPS) and task-based transfer function (TTF) were measured before computing a Detectability index (d′) to model the detection task of liver metastasis (LM) and hepatocellular carcinoma (HCC) as function of keV.ResultsFrom 40 to 70 keV, noise-magnitude was reduced on average by −68% ± 1% with FBP; −61% ± 3% with ASIR50 and −52% ± 6% with ASIR100. The mean spatial frequency of the NPS decreased when the energy level decreased and the iterative level increased. TTF values at 50% decreased as the energy level increased and as the percentage of ASIR increased. The detectability of both lesions increased with increasing dose level and percentage of ASIR. For the LM, d′ peaked at 70 keV for all reconstruction types, except for ASIR70 at 12.72 mGy and ASIR100, where d' peaked at 50 keV. For HCC, d’ peaked at 60 keV for FBP and ASIR30 but peaked at 50 keV for ASIR50, ASIR70 and ASIR100.ConclusionsUsing percentage of ASIR above 50% at low-energy monochromatic images could limit the increase of noise-magnitude, benefit from spatial resolution improvement and hence enhance detectability of subtle low contrast focal liver lesions such as HCC.     

Objective criteria for acceptability and constancy tests of digital subtraction angiography

PurposeDemonstrate an objective procedure to quantify image quality in digital subtraction angiography (DSA) and suggest thresholds for acceptability and constancy tests.MethodsSeries of images were obtained in a DSA system simulating a small (paediatric) and a large patient using the dynamic phantom described in the IEC and DIN standards for acceptance tests of DSA equipment. Image quality was quantified using measurements of contrast-to-noise ratio (CNR). Overall scores combining the CNR of 10–100 mg/ml Iodine at a vascular diameter of 1–4 mm in a homogeneous background were defined. Phantom entrance surface air kerma (K_a,e) was measured with an ionisation chamber.ResultsThe visibility of a low-contrast vessel in DSA images has been identified with a CNR value of 0.50 ± 0.03. Despite using 14 times more K_a,e (8.85 vs 0.63 mGy/image), the protocol for large patients showed a decrease in the overall score CNR_sum of 67% (4.21 ± 0.06 vs 2.10 ± 0.05). The uncertainty in the results of the objective method was below 5%.ConclusionObjective evaluation of DSA images using CNR is feasible with dedicated phantom measurements. An objective methodology has been suggested for acceptance tests compliant with the IEC/DIN standards. The defined overall scores can serve to fix a reproducible baseline for constancy tests, as well as to study the device stability within one acquisition series and compare different imaging protocols. This work provides aspects that have not been included in the recent European guidelines on Criteria for Acceptability of Medical Radiological Equipment.     

Dual-energy contrast-enhanced digital mammography: Glandular dose estimation using a Monte Carlo code and voxel phantom

PurposeTo estimate the mean glandular dose of contrast enhanced digital mammography, using the EGSnrc Monte Carlo code and female adult voxel phantom.MethodsAutomatic exposure control of full field digital mammography system was used for the selection of the X-ray spectrum and the exposure settings for dual energy imaging. Measurements of the air-kerma and of the half value layers were performed and a Monte Carlo simulation of the digital mammography system was used to compute the mean glandular dose, for breast phantoms of various thicknesses, glandularities and for different X-ray spectra (low and high energy).ResultsFor breast phantoms of 2.0–8.0 cm thick and 0.1–100% glandular fraction, CC view acquisition, from AEC settings, can result in a mean glandular dose of 0.450 ± 0.022 mGy −2.575 ± 0.033 mGy for low energy images and 0.061 ± 0.021 mGy – 0.232 ± 0.033 mGy for high energy images. In MLO view acquisition mean glandular dose values ranged between 0.488 ± 0.007 mGy – 2.080 ± 0.021 mGy for low energy images and 0.065 ± 0.012 mGy – 0.215 ± 0.010 mGy for high energy images.ConclusionThe low kV part of contrast enhanced digital mammography is the main contributor to total mean glandular breast dose. The results of this study can be used to provide an estimated mean glandular dose for individual cases.     

CT dose reduction using Automatic Exposure Control and iterative reconstruction: A chest paediatric phantoms study

PurposeTo evaluate the impact of Automatic Exposure Control (AEC) on radiation dose and image quality in paediatric chest scans (MDCT), with or without iterative reconstruction (IR).MethodsThree anthropomorphic phantoms representing children aged one, five and 10-year-old were explored using AEC system (CARE Dose 4D) with five modulation strength options. For each phantom, six acquisitions were carried out: one with fixed mAs (without AEC) and five each with different modulation strength. Raw data were reconstructed with Filtered Back Projection (FBP) and with two distinct levels of IR using soft and strong kernels. Dose reduction and image quality indices (Noise, SNR, CNR) were measured in lung and soft tissues. Noise Power Spectrum (NPS) was evaluated with a Catphan 600 phantom.ResultsThe use of AEC produced a significant dose reduction (p < 0.01) for all anthropomorphic sizes employed. According to the modulation strength applied, dose delivered was reduced from 43% to 91%. This pattern led to significantly increased noise (p < 0.01) and reduced SNR and CNR (p < 0.01). However, IR was able to improve these indices. The use of AEC/IR preserved image quality indices with a lower dose delivered. Doses were reduced from 39% to 58% for the one-year-old phantom, from 46% to 63% for the five-year-old phantom, and from 58% to 74% for the 10-year-old phantom. In addition, AEC/IR changed the patterns of NPS curves in amplitude and in spatial frequency.ConclusionsIn chest paediatric MDCT, the use of AEC with IR allows one to obtain a significant dose reduction while maintaining constant image quality indices.     

Preserving image texture while reducing radiation dose with a deep learning image reconstruction algorithm in chest CT: A phantom study

PurposeTo assess whether a deep learning image reconstruction algorithm (TrueFidelity) can preserve the image texture of conventional filtered back projection (FBP) at reduced dose levels attained by ASIR-V in chest CT.MethodsPhantom images were acquired using a clinical chest protocol (7.6 mGy) and two levels of dose reduction (60% and 80%). Images were reconstructed with FBP, ASIR-V (50% and 100% blending) and TrueFidelity (low (DL-L), medium (DL-M) and high (DL-H) strength). Noise (SD), noise power spectrum (NPS) and task-based transfer function (TTF) were calculated. Noise texture was quantitatively compared by computing root-mean-square deviations (RMSD) of NPS with respect to FBP. Four experienced readers performed a contrast-detail evaluation. The dose reducing potential of TrueFidelity compared to ASIR-V was assessed by fitting SD and contrast-detail as a function of dose.ResultsDL-M and DL-H reduced noise and NPS area compared to FBP and 50% ASIR-V, at all dose levels. At 7.6 mGy, NPS of ASIR-V 50/100% was shifted towards lower frequencies (f_peak = 0.22/0.13 mm⁻¹, RMSD = 0.14/0.38), with respect to FBP (f_peak = 0.30 mm⁻¹). Marginal difference was observed for TrueFidelity: f_peak = 0.33/0.30/0.30 mm⁻¹ and RMSD = 0.03/0.04/0.07 for L/M/H strength. Values of TTF_50% were independent of DL strength and higher compared to FBP and ASIR-V, at all dose and contrast levels. Contrast-detail was highest for DL-H at all doses. Compared to 50% ASIR-V, DL-H had an estimated dose reducing potential of 50% on average, without impairing noise, texture and detectability.ConclusionsTrueFidelity preserves the image texture of FBP, while outperforming ASIR-V in terms of noise, spatial resolution and detectability at lower doses.     

Geometric and dosimetric accuracy and imaging dose of the real-time tumour tracking system of a gimbal mounted linac

PurposeTo suggest a comprehensive testing scheme to evaluate the geometric and dosimetric accuracy and the imaging dose of the VERO dynamic tumour tracking (DTT) for its clinical implementation.MethodsGeometric accuracy was evaluated for gantry 0° and 90° in terms of prediction (E_P), mechanical (E_M) and tracking (E_T) errors for sinusoidal patterns with 10 and 20 mm amplitudes, 2–6 s periods and phase shift up to 1 s and for 3 patient patterns. The automatic 4D model update was investigated simulating changes in the breathing pattern during treatment.Dosimetric accuracy was evaluated with gafchromic films irradiated in static and moving phantom with and without DTT. The entrance skin dose (ESD) was assessed using a solid state detector and gafchromic films.ResultsThe RMS of E_P, E_M, and E_T were up to 0.8, 0.5 and 0.9 mm for all non phased-shifted motion patterns while for the phased-shifted ones, E_P and E_T increased to 2.2 and 2.6 mm. Up to 4 updates are necessary to restore a good correlation model, according to type of change.For 100 kVp and 1 mA s X-ray beam, the ESD per portal due to 20 s fluoroscopy was 16.6 mGy, while treatment verification at a frequency of 1 Hz contributed with 4.2 mGy/min.ConclusionsThe proposed testing scheme highlighted that the VERO DTT system tracks a moving target with high accuracy. The automatic update of the 4D model is a powerful tool to guarantee the accuracy of tracking without increasing the imaging dose.     

Automatic exposure control at single- and dual-heartbeat CTCA on a 320-MDCT volume scanner: Effect of heart rate,exposure phase window setting,and reconstruction algorithm

PurposeTo investigate whether electrocardiogram (ECG)-gated single- and dual-heartbeat computed tomography coronary angiography (CTCA) with automatic exposure control (AEC) yields images with uniform image noise at reduced radiation doses.Materials and methodsUsing an anthropomorphic chest CT phantom we performed prospectively ECG-gated single- and dual-heartbeat CTCA on a second-generation 320-multidetector CT volume scanner. The exposure phase window was set at 75%, 70–80%, 40–80%, and 0–100% and the heart rate at 60 or 80 or corr80 bpm; images were reconstructed with filtered back projection (FBP) or iterative reconstruction (IR, adaptive iterative dose reduction 3D). We applied AEC and set the image noise level to 20 or 25 HU. For each technique we determined the image noise and the radiation dose to the phantom center.ResultsWith half-scan reconstruction at 60 bpm, a 70–80% phase window- and a 20-HU standard deviation (SD) setting, the imagenoise level and -variation along the z axis manifested similar curves with FBP and IR. With half-scan reconstruction, the radiation dose to the phantom center with 70–80% phase window was 18.89 and 12.34 mGy for FBP and 4.61 and 3.10 mGy for IR at an SD setting SD of 20 and 25 HU, respectively. At 80 bpm with two-segment reconstruction the dose was approximately twice that of 60 bpm at both SD settings. However, increasing radiation dose at corr80 bpm was suppressed to 1.39 times compared to 60 bpm.ConclusionAEC at ECG-gated single- and dual-heartbeat CTCA controls the image noise at different radiation dose.     

Objective assessment of low contrast detectability in computed tomography with Channelized Hotelling Observer

PurposeIterative 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 methodsA 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 CTDI_vol 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.ResultsFor the same CTDI_vol 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.ConclusionThe 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.     

Determination of radiation dose and low-dose protocol for digital chest tomosynthesis using radiophotoluminescent (RPL) glass dosimeters

PurposeThis study aimed to determine a low-dose protocol for digital chest tomosynthesis (DTS).MethodsFive simulated nodules with a CT number of approximately 100 HU with size diameter of 3, 5, 8, 10, and 12 mm were inserted into an anthropomorphic chest phantom (N1 Lungman model), and then scanned by DTS system (Definium 8000) with varying tube voltage, copper filter thickness, and dose ratio. Three radiophotoluminescent (RPL) glass dosimeters, type GD-352 M with a dimension of 1.5 × 12 mm, were used to measure the entrance surface air kerma (ESAK) in each protocol. The effective dose (ED) was calculated using the recorded total dose-area-product (DAP). The signal-to-noise ratio (SNR) was determined for qualitative image quality evaluation. The image criteria and nodule detection capability were scored by two experienced radiologists. The selected low-dose protocol was further applied in a clinical study with 30 pulmonary nodule follow-up patients.ResultsThe average ESAK obtained from the standard default protocol was 1.68 ± 0.15 mGy, while an ESAK of 0.47 ± 0.02 mGy was found for a low-dose protocol. The EDs for the default and low-dose protocols were 313.98 ± 0.72 µSv and 100.55 ± 0.28 µSv, respectively. There were small non-significant differences in the image criteria and nodule detection scoring between the low-dose and default protocols interpreted by two radiologists. The effective dose of 98.87 ± 0.08 µSv was obtained in clinical study after applying the low-dose protocol.ConclusionsThe low-dose protocol obtained in this study can substantially reduce radiation dose while preserving an acceptable image quality compared to the standard protocol.     

Fetal radiation dose in three common CT examinations during pregnancy – Monte Carlo study

PurposeTo determine fetal doses in different stages of pregnancy in three common computed tomography (CT) examinations: pulmonary CT angiography, abdomino-pelvic and trauma scan with Monte Carlo (MC) simulations.MethodsAn adult female anthropomorphic phantom was scanned with a 64-slice CT using pulmonary angiography, abdomino-pelvic and trauma CT scan protocols. Three different sized gelatin boluses placed on the phantom’s abdomen simulated different stages of pregnancy. Intrauterine dose was used as a surrogate to a dose absorbed to the fetus. MC simulations were performed to estimate uterine doses. The simulation dose levels were calibrated with volumetric CT dose index (CTDI_vol) measurements and MC simulations in a cylindrical CTDI body phantom and compared with ten point doses measured with metal-oxide-semiconductor field-effect-transistor dosimeters. Intrauterine volumes and uterine walls were segmented and the respective dose volume histograms were calculated.ResultsThe mean intrauterine doses in different stages of pregnancy varied from 0.04 to 1.04 mGy, from 4.8 to 5.8 mGy, and from 9.8 to 12.6 mGy in the CT scans for pulmonary angiography, abdomino-pelvic and trauma CT scans, respectively. MC simulations showed good correlation with the MOSFET measurement at the measured locations.ConclusionsThe three studied examinations provided highly varying fetal doses increasing from sub-mGy level in pulmonary CT angiography to notably higher levels in abdomino-pelvic and trauma scans where the fetus is in the primary exposure range. Volumetric dose distribution offered by MC simulations in an appropriate anthropomorphic phantom provides a comprehensive dose assessment when applied in adjunct to point-dose measurements.     

Dosimetric and radiation cancer risk evaluation of high resolution thorax CT during COVID-19 outbreak

PurposeThe aim of this work was to evaluate the dosimetric impact of high-resolution thorax CT during COVID-19 outbreak in the University Hospital of Parma. In two months we have performed a huge number of thorax CT scans collecting effective and equivalent organ doses and evaluating also the lifetime attributable risk (LAR) of lung and other major cancers.Materials and MethodFrom February 24th to April 28th, 3224 high-resolution thorax CT were acquired. For all patients we have examined the volumetric computed tomography dose index (CTDIvol), the dose length product (DLP), the size-specific dose estimate (SSDE) and effective dose (E₁₀₃) using a dose tracking software (Radimetrics Bayer HealthCare). From the equivalent dose to organs for each patient, LAR for lung and major cancers were estimated following the method proposed in BEIR VII which considers age and sex differences.ResultsStudy population included 3224 patients, 1843 male and 1381 female, with an average age of 67 years. The average CTDIvol, SSDE and DLP, and E₁₀₃ were 6.8 mGy, 8.7 mGy, 239 mGy·cm and 4.4 mSv respectively. The average LAR of all solid cancers was 2.1 cases per 10,000 patients, while the average LAR of leukemia was 0.2 cases per 10,000 patients. For both male and female the organ with a major cancer risk was lung.ConclusionsDespite the impressive increment in thoracic CT examinations due to COVID-19 outbreak, the high resolution low dose protocol used in our hospital guaranteed low doses and very low risk estimation in terms of LAR.     

A single phantom,a single statistical method for low-contrast detectability assessment

PurposeThe assessment of low-contrast-details is a part of the quality control (QC) program in digital radiology. It generally consists of evaluating the threshold contrast (Cth) detectability details for different-sized inserts, appropriately located in dedicated QC test tools. This work aims to propose a simplified method, based on a statistical model approach for threshold contrast estimation, suitable for different modalities in digital radiology.MethodsA home-made low-contrast phantom, made of a central aluminium insert with a step-wedge, was assembled and tested. The reliability and robustness of the method were investigated for Mammography, Digital Radiography, Fluoroscopy and Angiography. Images were analysed using our dedicated software developed on Matlab®. The Cth is expressed in the same unit (mmAl) for all studied modalities.ResultsThis method allows the collection of Cth information from different modalities and equipment by different vendors, and it could be used to define typical values. Results are summarized in detail. For 0.5 diameter detail, Cth results are in the range of: 0.018–0.023 mmAl for 2D mammography and 0.26–0.34 mmAl DR images. For angiographic images, for 2.5 mm diameter detail, the Cth s median values are 0.55, 0.4, 0.06, 0.12 mmAl for low dose fluoroscopy, coronary fluorography, cerebral and abdominal DSA, respectively.ConclusionsThe statistical method proposed in this study gives a simple approach for Low-Contrast-Details assessment, and the typical values proposed can be implemented in a QA program for digital radiology modalities.     

Validation of low-dose lung cancer PET-CT protocol and PET image improvement using machine learning

PurposeTo conduct a simplified lesion-detection task of a low-dose (LD) PET-CT protocol for frequent lung screening using 30% of the effective PETCT dose and to investigate the feasibility of increasing clinical value of low-statistics scans using machine learning.MethodsWe acquired 33 SD PET images, of which 13 had actual LD (ALD) PET, and simulated LD (SLD) PET images at seven different count levels from the SD PET scans. We employed image quality transfer (IQT), a machine learning algorithm that performs patch-regression to map parameters from low-quality to high-quality images. At each count level, patches extracted from 23 pairs of SD/SLD PET images were used to train three IQT models – global linear, single tree, and random forest regressions with cubic patch sizes of 3 and 5 voxels. The models were then used to estimate SD images from LD images at each count level for 10 unseen subjects. Lesion-detection task was carried out on matched lesion-present and lesion-absent images.ResultsLD PET-CT protocol yielded lesion detectability with sensitivity of 0.98 and specificity of 1. Random forest algorithm with cubic patch size of 5 allowed further 11.7% reduction in the effective PETCT dose without compromising lesion detectability, but underestimated SUV by 30%.ConclusionLD PET-CT protocol was validated for lesion detection using ALD PET scans. Substantial image quality improvement or additional dose reduction while preserving clinical values can be achieved using machine learning methods though SUV quantification may be biased and adjustment of our research protocol is required for clinical use.     

Optimization of image quality and accuracy of low iodine concentration quantification as function of kVp pairs for abdominal imaging using dual-source CT: A phantom study

PurposeTo determine the suitable kVp pair for optimal image quality of the virtual monochromatic images (VMIs) and iodine quantification accuracy at low concentration, using a third generation dual-source CT (DSCT).Materials and methodsMulti-energy CT phantoms with and without body rings were scanned with a DSCT using four kVp pairs (tube “A”/“B” voltage): 100/Sn150, 90/Sn150, 80/Sn150 and 70/Sn150 kVp. The reference mAs was adjusted to obtain a CTDI_vol close to 11 mGy. HU values accuracy (RMSD_HU), noise (SD) and contrast-to-noise ratio (CNR) of iodine inserts of 0.5, 1, 2 and 5 mg/mL concentrations were assessed on VMIs at 40/50/60/70 keV. Iodine quantification accuracy was assessed using the RMSD_iodine and iodine bias (IB_iodine).ResultsThe RMSD_HU decreased when the tube “A” voltage increased. The mean noise value increased significantly with tube “A” voltage (p < 0.001) but decreased between 80/Sn150 and 90/Sn150 kVp for the small phantom (1.1 ± 0.1%; p = 0.047). The CNR significantly decreased with tube “A” voltage (p < 0.001), except between 80/Sn150 and 90/Sn150 kVp for all inserts and between 90/Sn150 kVp and 100/Sn150 kVp for the 1.0 and 0.5 mg/mL inserts in the large phantom. In the small phantom, no significant difference was found between 80/Sn150 kVp and 90/Sn150 kVp for all inserts and between 80/Sn150, 90/Sn150 and 100/Sn150 kVp for the 1 and 0.5 mg/mL inserts. The RMSD_iodine and IB_iodine decreased as the tube “A” voltage of the kVp pair increased.ConclusionThe kVp pair of 70/Sn150 led to better image quality in VMIs and sufficient iodine accuracy.     

Enhancement of soft-tissue contrast in cone-beam CT using an anti-scatter grid with a sparse sampling approach

PurposeAnti-scatter grids suppress the scatter substantially thus improving image contrast in radiography. However, its active use in cone-beam CT for the purpose of improving contrast-to-noise ratio (CNR) has not been successful mainly due to the increased noise related to Poisson statistics of photons. This paper proposes a sparse-view scanning approach to address the above issue.MethodCompared to the conventional cone-beam CT imaging framework, the proposed method reduces the number of projections and increases exposure in each projection to enhance image quality without an additional cost of radiation dose to patients. For image reconstruction from sparse-view data, an adaptive-steepest-descent projection-onto-convex-sets (ASD POCS) algorithm regularized by total-variation (TV) minimization was adopted. Contrast and CNR with various scattering conditions were evaluated in projection domain by a simulation study using GATE. Then we evaluated contrast, resolution, and image uniformity in CT image domain with Catphan phantom. A head phantom with soft-tissue structures was also employed for demonstrating a realistic application. A virtual grid-based estimation and reduction of scatter has also been implemented for comparison with the real anti-scatter grid.ResultsIn the projection domain evaluation, contrast and CNR enhancement was observed when using an anti-scatter grid compared to the virtual grid. In the CT image domain, the proposed method produced substantially higher contrast and CNR of the low-contrast structures with much improved image uniformity.ConclusionWe have shown that the proposed method can provide high-quality CBCT images particularly with an increased contrast of soft-tissue at a neutral dose for image-guidance.     

Dose profiles for lung and breast regions at prospective and retrospective CT coronary angiography using optically stimulated luminescence dosimeters on a 64-detector CT scanner

PurposeThe purpose of our study was to acquire dose profiles at critical organs of lung and breast regions using optically stimulated luminescence (OSL) dosimeters; assess the actual radiation dose delivered at retrospective and prospective computed tomography coronary angiography (CTCA).Materials and methodsUsing a chest CT phantom we applied a prospectively-gated step-and-shoot- and a retrospectively-gated helical mode on a 64-detector row CT scanner. Retrospective scan mode was used with and without electrocardiogram (ECG) based tube current modulation. OSL dosimeters were used to measure dose profiles. In the both scan modes we acquired dose profiles and determined the mean and maximum dose in left lung and in left breast regions.ResultsIn prospective mode, the mean dose was 21.53 mGy in left lung- and 23.59 mGy in left breast region. With respect to the retrospective mode, the mean dose with tube current modulation was 38.63 mGy for left lung- and 46.02 mGy for left breast region, i.e. 0.56 and 0.55 times lower than the mean dose without modulation.ConclusionThe OSL dosimeter is useful for measurement of the actual radiation dose along z-axis at lung and breast regions in the prospective and the retrospective CTCA.