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.     

Brain PET imaging optimization with time of flight and point spread function modelling

PurposeTo assess the influence of reconstruction algorithms and parameters on the PET image quality of brain phantoms in order to optimize reconstruction for clinical PET brain studies in a new generation PET/CT.MethodsThe 3D Hoffman phantom that simulates ¹⁸F-fluorodeoxyglucose (FDG) distribution was imaged in a Siemens Biograph mCT TrueV PET/CT with Time of Flight (TOF) and Point Spread Function (PSF) modelling. Contrast-to-Noise Ratio (CNR), contrast and noise were studied for different reconstruction models: OSEM, OSEM + TOF, OSEM + PSF and OSEM + PSF + TOF.The 2D multi-compartment Hoffman phantom was filled to simulate 4 different tracers' spatial distribution: FDG, ¹¹C-flumazenil (FMZ), ¹¹C-Methionine (MET) and 6-¹⁸F-fluoro-l-dopa (FDOPA). The best algorithm for each tracer was selected by visual inspection. The maximization of CNR determined the optimal parameters for each reconstruction.ResultsIn the 3D Hoffman phantom, both noise and contrast increased with increasing number of iterations and decreased with increasing FWHM. OSEM + PSF + TOF reconstruction was generally superior to other reconstruction models. Visual analysis of the 2D Hoffman brain phantom suggested that OSEM + PSF + TOF is the optimum algorithm for tracers with focal uptake, such as MET or FDOPA, and OSEM + TOF for tracers with diffuse cortical uptake (i.e. FDG and FMZ). Optimization of CNR demonstrated that OSEM + TOF reconstruction must be performed with 2 iterations and a filter FWHM of 3 mm, and OSEM + PSF + TOF reconstruction with 4 iterations and 1 mm FWHM filter.ConclusionsOptimization of reconstruction algorithm and parameters has been performed to take particular advantage of the last generation PET scanner, recommending specific settings for different brain PET radiotracers.     

An iterative deconvolution algorithm for image recovery in clinical CT: A phantom study

PurposeTo study the feasibility of using an iterative reconstruction algorithm to improve previously reconstructed CT images which are judged to be non-diagnostic on clinical review. A novel rapidly converging, iterative algorithm (RSEMD) to reduce noise as compared with standard filtered back-projection algorithm has been developed.Materials and methodsThe RSEMD method was tested on in-silico, Catphan^®500, and anthropomorphic 4D XCAT phantoms. The method was applied to noisy CT images previously reconstructed with FBP to determine improvements in SNR and CNR. To test the potential improvement in clinically relevant CT images, 4D XCAT phantom images were used to simulate a small, low contrast lesion placed in the liver.ResultsIn all of the phantom studies the images proved to have higher resolution and lower noise as compared with images reconstructed by conventional FBP. In general, the values of SNR and CNR reached a plateau at around 20 iterations with an improvement factor of about 1.5 for in noisy CT images. Improvements in lesion conspicuity after the application of RSEMD have also been demonstrated. The results obtained with the RSEMD method are in agreement with other iterative algorithms employed either in image space or with hybrid reconstruction algorithms.ConclusionsIn this proof of concept work, a rapidly converging, iterative deconvolution algorithm with a novel resolution subsets-based approach that operates on DICOM CT images has been demonstrated. The RSEMD method can be applied to sub-optimal routine-dose clinical CT images to improve image quality to potentially diagnostically acceptable levels.     

Image quality for radiotherapy CT simulators with different scanner bore size

PurposeWe compare image quality parameters derived from phantom images taken on three commercially available radiotherapy CT simulators. To make an unbiased evaluation, we assured images were obtained with the same surface dose measured using XR-QA2 model GafChromic™ film placed at the imaging phantom surface for all three CT-simulators.MethodsRadiotherapy CT simulators GE LS 16, Philips Brilliance Big Bore, and Toshiba Aquilion LB were compared in terms of spatial resolution, low contrast detectability, image uniformity, and contrast to noise ratio using CATPHAN-504 phantom, scanned with Head and Pelvis protocols. Dose was measured at phantom surface, with CT scans repeated until doses on all scanners were within 2%.ResultsIn terms of spatial resolution, the GE simulator appears slightly better, while Philips CT images are superior in terms of SNR for both scanning protocols. The CNR results show that Philips CT images appear to be better, except for high Z material, while Toshiba appears to fit in between the two simulators.ConclusionsWhile the image quality parameters for three RT CT simulators show comparable results, the scanner bore size is of vital importance in various radiotherapy applications. Since the image quality is a function of a large number of confounding parameters, any loss in image quality due to scanner bore size could be compensated by the appropriate choice of scanning parameters, including the exposure and by balancing between the additional imaging dose to the patient and high image quality required in highly conformal RT techniques.     

Automatic exposure control at MDCT based on the contrast-to-noise ratio: Theoretical background and phantom study

PurposeTo develop a new automatic exposure control (AEC) technique based on the contrast-to-noise ratio (CNR) and provide constant lesion detectability.MethodsLesion detectability is affected by factors such as image noise, lesion contrast, and lesion size. We performed ROC analysis to assess the relationship between the optimum CNR and the lesion diameter at various levels of lesion contrast. We then developed a CNR-based AEC algorithm based on lesion detectability. Using CNR- based AEC algorithm, we performed visual evaluation of low-contrast detectability by 5 radiologists on a low-contrast module of the Catphan phantom, a contrast-difference level of 1.0% (difference in the CT number = 10 HU), and objects 3.0–9.0 mm in diameter.ResultsOn step-and-shoot scans the mean detection fraction with CNR-based AEC remained almost constant from 88 to 99 % regardless of the lesion size. We observed the same trend on helical scans, the mean detection fraction with CNR-based AEC exhibited a high score from 91 to 100%. Although CNR-based AEC maintains higher CNR for smaller size or lower contrast lesion, radiation dose on 3 mm lesion resulted in about 13 times larger than that of 9 mm lesion size. CTDI_vol for the CNR-based AEC technique changed dramatically with the SD_Z from 7.5 to 100.0 mGy for step-and-shoot scans and from 9.1 to 121.5 mGy for helical scans.ConclusionsFrom the viewpoint of ROC analysis-based CNR for lesion detection, CNR-based AEC potentially provide image quality advantages for clinical implementation.     

Influence of Sinogram Affirmed Iterative Reconstruction of CT Data on Image Noise Characteristics and Low-Contrast Detectability: An Objective Approach

Objectives

To utilize a novel objective approach combining a software phantom and an image quality metric to systematically evaluate the influence of sinogram affirmed iterative reconstruction (SAFIRE) of multidetector computed tomography (MDCT) data on image noise characteristics and low-contrast detectability (LCD).

Materials and Methods

A low-contrast and a high-contrast phantom were examined on a 128-slice scanner at different dose levels. The datasets were reconstructed using filtered back projection (FBP) and SAFIRE and virtual low-contrast lesions (-20HU) were inserted. LCD was evaluated using the multiscale structural similarity index (MS-SIM*). Image noise texture and spatial resolution were objectively evaluated.

Results

The use of SAFIRE led to an improvement of LCD for all dose levels and lesions sizes. The relative improvement of LCD was inversely related to the dose level, declining from 208%(±37%), 259%(±30%) and 309%(±35%) at 25mAs to 106%(±6%), 119%(±9%) and 123%(±8%) at 200mAs for SAFIRE filter strengths of 1, 3 and 5 (p<0.05). SAFIRE reached at least the LCD of FBP at a relative dose of 50%. There was no statistically significant difference in spatial resolution. The use of SAFIRE led to coarser image noise granularity.

Conclusion

A novel objective approach combining a software phantom and the MS-SSIM* image quality metric was used to analyze the detectability of virtual low-contrast lesions against the background of image noise as created using SAFIRE in comparison to filtered back-projection. We found, that image noise characteristics using SAFIRE at 50% dose were comparable to the use of FBP at 100% dose with respect to lesion detectability. The unfamiliar imaging appearance of iteratively reconstructed datasets may in part be explained by a different, coarser noise characteristic as demonstrated by a granulometric analysis.     

Toward standardized quantitative image quality (IQ) assessment in computed tomography (CT): A comprehensive framework for automated and comparative IQ analysis based on ICRU Report 87

PurposeBased on the guidelines from “Report 87: Radiation Dose and Image-quality Assessment in Computed Tomography” of the International Commission on Radiation Units and Measurements (ICRU), a software framework for automated quantitative image quality analysis was developed and its usability for a variety of scientific questions demonstrated.MethodsThe extendable framework currently implements the calculation of the recommended Fourier image quality (IQ) metrics modulation transfer function (MTF) and noise-power spectrum (NPS), and additional IQ quantities such as noise magnitude, CT number accuracy, uniformity across the field-of-view, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of simulated lesions for a commercially available cone-beam phantom. Sample image data were acquired with different scan and reconstruction settings on CT systems from different manufacturers.ResultsSpatial resolution is analyzed in terms of edge-spread function, line-spread-function, and MTF. 3D NPS is calculated according to ICRU Report 87, and condensed to 2D and radially averaged 1D representations. Noise magnitude, CT numbers, and uniformity of these quantities are assessed on large samples of ROIs. Low-contrast resolution (CNR, SNR) is quantitatively evaluated as a function of lesion contrast and diameter. Simultaneous automated processing of several image datasets allows for straightforward comparative assessment.ConclusionsThe presented framework enables systematic, reproducible, automated and time-efficient quantitative IQ analysis. Consistent application of the ICRU guidelines facilitates standardization of quantitative assessment not only for routine quality assurance, but for a number of research questions, e.g. the comparison of different scanner models or acquisition protocols, and the evaluation of new technology or reconstruction methods.     

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.     

The effect of tube focal spot size and acquisition mode on task-based image quality performance of a GE revolution HD dual energy CT scanner

PurposeTo assess the task-based performance of images obtained under different focal spot size and acquisition mode on a dual-energy CT scanner.MethodsAxial CT image series of the Catphan phantom were obtained using a tube focus at different sizes. Acquisitions were performed in standard single-energy, high resolution (HR) and dual-energy modes. Images were reconstructed using conventional and high definition (HD) kernels. Task-based transfer function at the 50% level (TTF_50%) for teflon, delrin, low density polyethylene (LDPE) and acrylic, as well as image noise and noise texture, were assessed across all focal spots and acquisition modes using Noise Power Spectrum (NPS) analysis. A non-prewhitening mathematical observer model was used to calculate detectability index ($d_{\mathit{NPW}}^{\prime }$).ResultsTTF_50% degraded with increasing focal spot size. TTF_50% ranged from 0.67 mm⁻¹ for teflon to 0.25 mm⁻¹ for acrylic. For standard kernel, image noise and NPS-determined average spatial frequency were 8.3 HU and 0.29 mm⁻¹, respectively in single-energy, 12.0 HU and 0.37 mm⁻¹ in HR, and 7.9 HU and 0.26 mm⁻¹ in dual-energy mode. For standard kernel, $d_{\mathit{NPW}}^{\prime }$ was 61 in single-energy and HR mode and reduced to 56 in dual-energy mode.ConclusionsThe task-based image quality assessment metrics have shown that spatial resolution is higher for higher image contrast materials and detectability is higher in the standard single-energy mode compared to HR and dual-energy mode. The results of the current study provide CT operators the required knowledge to characterize their CT system towards the optimization of its clinical performance.     

Technical Note: Quality assessment of virtual monochromatic spectral images on a dual energy CT scanner

PurposeTo assess the quality of images obtained on a dual energy computed tomography (CT) scanner.MethodsImage quality was assessed on a 64 detector-row fast kVp-switching dual energy CT scanner (Revolution GSI, GE Medical Systems). The Catphan phantom and a low contrast resolution phantom were employed. Acquisitions were performed at eight different radiation dose levels that ranged from 9 mGy to 32 mGy. Virtual monochromatic spectral images (VMI) were reconstructed in the 40–140 keV range using all available kernels and iterative reconstruction (IR) at four different blending levels. Modulation Transfer Function (MTF) curves, image noise, image contrast, noise power spectrum and contrast to noise ratio were assessed.ResultsIn-plane spatial resolution at the 10% of the MTF curve was 0.60 mm⁻¹. In-plane spatial resolution was not modified with VMI energy and IR blending level. Image noise was reduced from 16.6 at 9 mGy to 6.7 at 32 mGy, while peak frequency remained within 0.14 ± 0.01 mm⁻¹. Image noise was reduced from 14.3 at IR 10% to 11.5 at IR 50% at a constant peak frequency. The lowest image noise and maximum peak frequency were recorded at 70 keV.ConclusionsOur results have shown how objective image quality is varied when different levels of radiation dose and different settings in IR are applied. These results provide CT operators an in depth understanding of the imaging performance characteristics in dual energy CT.     

Effective dose and image quality for intraoperative imaging with a cone-beam CT and a mobile multi-slice CT in spinal surgery: A phantom study

PurposeTo compare the effective dose (ED) and image quality (IQ) of O-arm cone-beam CT (Medtronic, Minneapolis, MN, USA) and Airo multi-slice CT (Brainlab AG, Munich, Germany) for intraoperative-CT (i-CT) in spinal surgery.MethodsThe manufacturer-defined protocols available in the O-arm and Airo systems for three-dimensional lumbar spine imaging were compared.Organ dose was measured both with thermo-luminescent dosimeters and GafChromic films in the Alderson Radiation Therapy anthropomorphic phantom.A subjective analysis was performed by neurosurgeons to compare the clinical IQ of the anthropomorphic phantom images acquired with the different i-CT systems and imaging protocols.Image uniformity, noise, contrast-to-noise-ratio (CNR), and spatial resolution were additionally assessed with the Catphan 504 phantom.ResultsO-arm i-CT caused 56% larger ED than Airo due to the high definition (HD) imaging protocol.The noise was larger for O-arm images leading to a lower CNR than that measured for Airo. Moreover, scattering and beam hardening effects were observed in the O-arm images. Better spatial resolution was measured for the O-arm system (9 lp/cm) than for Airo (4 lp/cm).For all the investigated protocols, O-arm was found to be better for identifying anatomical features important for accurate pedicle screw positioning.ConclusionsAccording to phantom measurements, the HD protocol of O-arm offered better clinical IQ than Airo but larger ED. The larger noise of O-arm images did not compromise the clinical IQ while the superior spatial resolution of this system allowed a better visibility of anatomical features important for pedicle screw positioning in the lumbar region.     

Analyse comparative de 3 logiciels de reconstruction itérative de tomoscintigraphie monophotonique myocardique

ObjectiveThis study makes a comparative analysis of the quality reconstruction of three software: 2D ordered subset expectation maximisation (2D OSEM), 3D ordered subsets expectation maximisation (Flash 3D) and Wallis.Patients and methodsThe data from myocardial scintigraphy acquisitions of 50 patients (38 men and 12 women; average age 61 ± 9 years) were successively reconstructed using three myocardial perfusion SPECT algorithms (Flash 3D, OSEM 2D and Wallis). Different combinations of iterations and subsets were considered. For Wallis, only the cut-off frequency was considered. The image's quality was assessed by determining the maximum contrast and the signal to noise ratio.ResultsThe Wallis software provided a higher signal to noise ratio compared to Flash 3D and OSEM 2D at stress and rest. The Wallis signal to noise ratio increased by a factor 1.93 (P = 0.0010) and 2.28 at stress (P = 0.0009); 1.50 (P = 0.0011) and 2.84 at rest (P = 0.0024) compared to respectively Flash 3D and OSEM 2D. Flash 3D provided better signal to noise ratio than OSEM 2D at stress and at rest. The difference in medians and interquartile ranges of the signal-to-noise ratio in post-stress were 22 % and 54 %, respectively between Flash 3D and OSEM 2D. At rest, the difference between the two methods in signal to noise ratio was 32 % ± 0.,29.ConclusionWallis algorithm was improve image quality with better signal to noise ratio compared to the reference method of Siemens Flash 3D. For both Flash 3D and OSEM 2D methods, the combination with 8 subsets and 12 iterations provided the best contrast and signal to noise ratio.     

The use of noise equivalent count rate and the NEMA phantom for PET image quality evaluation

PET image quality is directly associated with two important parameters among others: count-rate performance and image signal-to-noise ratio (SNR). The framework of noise equivalent count rate (NECR) was developed back in the 1990s and has been widely used since then to evaluate count-rate performance for PET systems. The concept of NECR is not entirely straightforward, however, and among the issues requiring clarification are its original definition, its relationship to image quality, and its consistency among different derivation methods. In particular, we try to answer whether a higher NECR measurement using a standard NEMA phantom actually corresponds to better imaging performance. The paper includes the following topics: 1) revisiting the original analytical model for NECR derivation; 2) validating three methods for NECR calculation based on the NEMA phantom/standard; and 3) studying the spatial dependence of NECR and quantitative relationship between NECR and image SNR.     

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.     

Bayesian penalized-likelihood reconstruction algorithm suppresses edge artifacts in PET reconstruction based on point-spread-function

PurposeThe Bayesian penalized-likelihood reconstruction algorithm (BPL), Q.Clear, uses relative difference penalty as a regularization function to control image noise and the degree of edge-preservation in PET images. The present study aimed to determine the effects of suppression on edge artifacts due to point-spread-function (PSF) correction using a Q.Clear.MethodsSpheres of a cylindrical phantom contained a background of 5.3 kBq/mL of [¹⁸F]FDG and sphere-to-background ratios (SBR) of 16, 8, 4 and 2. The background also contained water and spheres containing 21.2 kBq/mL of [¹⁸F]FDG as non-background. All data were acquired using a Discovery PET/CT 710 and were reconstructed using three-dimensional ordered-subset expectation maximization with time-of-flight (TOF) and PSF correction (3D-OSEM), and Q.Clear with TOF (BPL). We investigated β-values of 200–800 using BPL. The PET images were analyzed using visual assessment and profile curves, edge variability and contrast recovery coefficients were measured.ResultsThe 38- and 27-mm spheres were surrounded by higher radioactivity concentration when reconstructed with 3D-OSEM as opposed to BPL, which suppressed edge artifacts. Images of 10-mm spheres had sharper overshoot at high SBR and non-background when reconstructed with BPL. Although contrast recovery coefficients of 10-mm spheres in BPL decreased as a function of increasing β, higher penalty parameter decreased the overshoot.ConclusionsBPL is a feasible method for the suppression of edge artifacts of PSF correction, although this depends on SBR and sphere size. Overshoot associated with BPL caused overestimation in small spheres at high SBR. Higher penalty parameter in BPL can suppress overshoot more effectively.     

Imaging performance of phase-contrast breast computed tomography with synchrotron radiation and a CdTe photon-counting detector

PurposeWithin the SYRMA-CT collaboration based at the ELETTRA synchrotron radiation (SR) facility the authors investigated the imaging performance of the phase-contrast computed tomography (CT) system dedicated to monochromatic in vivo 3D imaging of the female breast, for breast cancer diagnosis.MethodsTest objects were imaged at 38 keV using monochromatic SR and a high-resolution CdTe photon-counting detector. Signal and noise performance were evaluated using modulation transfer function (MTF) and noise power spectrum. The analysis was performed on the images obtained with the application of a phase retrieval algorithm as well as on those obtained without phase retrieval. The contrast to noise ratio (CNR) and the capability of detecting test microcalcification clusters and soft masses were investigated.ResultsFor a voxel size of (60 μm)³, images without phase retrieval showed higher spatial resolution (6.7 mm⁻¹ at 10% MTF) than corresponding images with phase retrieval (2.5 mm⁻¹). Phase retrieval produced a reduction of the noise level and an increase of the CNR by more than one order of magnitude, compared to raw phase-contrast images. Microcalcifications with a diameter down to 130 μm could be detected in both types of images.ConclusionsThe investigation on test objects indicates that breast CT with a monochromatic SR source is technically feasible in terms of spatial resolution, image noise and contrast, for in vivo 3D imaging with a dose comparable to that of two-view mammography. Images obtained with the phase retrieval algorithm showed the best performance in the trade-off between spatial resolution and image noise.     

The effect of scatter correction and radius of rotation on semiquantitative measurements in SPECT 123I-FP-CIT imaging. A phantom study

PurposeThe high energy emissions of ¹²³I and the suboptimal radius of rotation affect the semiquantitative measurements performed during ¹²³I-FP-CIT tomographic imaging. An in-house extra low cost striatum phantom with brain and striatum compartments was constructed and was used to study the effects of Triple Energy Window scatter correction (TEW-SC) and radius of rotation on the Specific Binding Ratio (SBR) measurements.Materials and methodsThe phantom compartments were filled with radioactive ¹²³I solutions with varying concentrations, in a series of experiments. Tomographic images were acquired at six different radii of rotation, with and without TEW-SC and the SBRs were calculated using appropriate regions of interest, as in clinical imaging.ResultsSBRs decreased with increasing radius of rotation in both non-SC and TEW-SC images, the decrease being more pronounced in the latter. The application of TEW-SC increases SBR values by 40% on average. A maximum %Recovery of 42.7% of the true SBR value was achieved in the non-SC images, which increased to 64.6% after TEW-SC. Appropriate correction factors (CF) were calculated in order to make the SBR values independent on the radius of rotation, which could be used to correct SBR values obtained from tomographic acquisitions with suboptimal radius of rotation.ConclusionThe use of appropriate CF can provide more consistent SBR values and a more meaningful comparison between SBRs calculated from images acquired at different radii of rotation.     

Evaluation of a commercial Model Based Iterative reconstruction algorithm in computed tomography

IntroductionIterative reconstruction algorithms have been introduced in clinical practice to obtain dose reduction without compromising the diagnostic performance.PurposeTo investigate the commercial Model Based IMR algorithm by means of patient dose and image quality, with standard Fourier and alternative metrics.Materials and methodsA Catphan phantom, a commercial density phantom and a cylindrical water filled phantom were scanned both varying CTDI_vol and reconstruction thickness. Images were then reconstructed with Filtered Back Projection and both statistical (iDose) and Model Based (IMR) Iterative reconstruction algorithms.Spatial resolution was evaluated with Modulation Transfer Function and Target Transfer Function. Noise reduction was investigated with Standard Deviation. Furthermore, its behaviour was analysed with 3D and 2D Noise Power Spectrum. Blur and Low Contrast Detectability were investigated.Patient dose indexes were collected and analysed.ResultsAll results, related to image quality, have been compared to FBP standard reconstructions.Model Based IMR significantly improves Modulation Transfer Function with an increase between 12% and 64%. Target Transfer Function curves confirm this trend for high density objects, while Blur presents a sharpness reduction for low density details.Model Based IMR underlines a noise reduction between 44% and 66% and a variation in noise power spectrum behaviour. Low Contrast Detectability curves underline an averaged improvement of 35–45%; these results are compatible with an achievable reduction of 50% of CTDI_vol.A dose reduction between 25% and 35% is confirmed by median values of CTDI_vol.ConclusionIMR produces an improvement in image quality and dose reduction.     

Effect of diagnostic cone-beam computed tomography protocols on image quality,patient dose,and lesion detection

ObjectiveTo evaluate the effect of cone-beam computed tomography (CBCT) image acquisition protocols on image quality, lesion detection, delineation, and patient dose.Methods100-patients and a CTDI phantom combined with an electron density phantom were examined using four different CBCT-image acquisition protocols during image-guided transarterial chemoembolization (TACE). Protocol-1 (time: 6 s, tube rotation: 360°), protocol-2 (5 s, 300°), protocol-3 (4 s, 240°) and protocol-4 (3 s, 180°) were used. The protocols were first investigated using a phantom. The protocols that were found to be clinically appropriate in terms of image quality and radiation dose were then assessed on patients. A higher radiation dose and/or a poor image quality were inappropriate for the patient imaging. Patient dose (patient-entrance dose and dose-area product), image quality (Hounsfield Unit, noise, signal-to-noise ratio and contrast-to-noise ratio), and lesion delineation (tumor-liver contrast) were assessed and compared using appropriate statistical tests. Lesion detectability, sensitivity, and predictive values were estimated for CBCT-image data using pre-treatment patient magnetic resonance imaging.ResultsThe estimated patient dose showed no statistical significance (p > 0.05) between protocols-2 and -3; the assessed image quality between these protocols manifested insignificant difference (p > 0.05). Two other phantom protocols were not considered for patient imaging due to significantly higher dose (protocols-1) and poor image quality (protocol-4). Lesion delineation and detection were insignificant (p > 0.05) between protocols-2 and -3. Lesion sensitivities generated were 81–89% (protocol-2) and 81–85% (protocol-3) for different lesion types.ConclusionData acquisition using protocols-2 and -3 provided good image quality, lesion detection and delineation with acceptable patient dose during CBCT-imaging mainly due to similar frame numbers acquired.