Spatial resolution compensation by adjusting the reconstruction kernels for iterative reconstruction images of computed tomography

PurposeHybrid iterative reconstruction (IR) is useful to reduce noise in computed tomography (CT) images. However, it often decreases the spatial resolution. The ability of high spatial resolution kernels (harder kernels) to compensate for the decrease in the spatial resolution of hybrid IRs was investigated.MethodsAn elliptic cylindrical phantom simulating an adult abdomen was used. Two types of rod-shaped objects with ~330 and ~130 HU were inserted to simulate contrasts of arteries in CT angiography. Two multi-slice CT systems were used to scan the phantoms with 120 kVp and scan doses of 20 and 10 mGy. The task transfer functions (TTFs) were measured from the circular edges of the rod images. The noise power spectrum (NPS) was measured from the images of the water-only section. The CT images were reconstructed using a filtered back projection (FBP) with baseline kernels and two levels of hybrid IRs with harder kernels. The profiles of the clinical images across the aortic dissection flaps were measured to evaluate actual spatial resolutions.ResultsThe TTF degradation of each hybrid IR was recovered by the harder kernels, whereas the noise reduction effect was retained, for both the 20 and 10 mGy. The profiles of the dissection flaps for the FBP were maintained by using the harder kernels. Even with the best combination of hybrid IR and harder kernel, the noise level at 10 mGy was not reduced to the level of FBP at 20 mGy, suggesting no capability of a 50% dose reduction while maintaining noise.     

Image quality comparison of a nonlinear image-based noise reduction technique with a hybrid-type iterative reconstruction for pediatric computed tomography

PurposeTo compare computed tomography (CT) image properties between a vendor-independent image-based noise reduction technique, Image-space Noise Reduction (iNoir) and a hybrid-type iterative reconstruction technique, Adaptive Statistical Iterative Reconstruction (ASIR).MethodsA cylindrical water phantom, corresponding to pediatric body size, containing soft-tissue-equivalent rod and 12-mg iodine/ml rod was scanned at size-specific dose estimates of 8.4 and 16.7 mGy. For assessments of image quality and noise texture change, task-based system performance function (SPF) and peak frequency difference (PFD) were compared, respectively, among filtered back projection (FBP), IR image with 50%-blending rate (50%ASIR), 100%ASIR, 50%iNoir, and 100%iNoir. Human observer test for pediatric CT images was performed by radiologists.ResultsFor the soft-tissue contrast, SPF² of 100%iNoir was the highest. The average SPF² between 0.1 and 0.5 cycles/mm for 100%iNoir increased by approximately 70% compared with FBP, while ASIR indicted slight increases in the frequency region of >0.2 cycles/mm. For the iodine contrast, 100%iNoir indicated highest values at the spatial frequencies corresponding pediatric artery diameters. The PFDs of iNoir were negligible and lower than that of ASIR. The results of human observer test supported results of SPF² and PFD.ConclusionsCompared with ASIR, iNoir provided better image quality for pediatric abdominal CT without compromising noise texture change.     

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.     

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.     

Object shape dependency of in-plane resolution for iterative reconstruction of computed tomography

The present study aimed to investigate whether the in-plane resolution property of iterative reconstruction (IR) of computed tomography (CT) data is object shape-dependent by testing columnar shapes with diameters of 3, 7, and 10 cm (circular edge method) and a cubic shape with 5-cm side lengths (linear edge method). For each shape, objects were constructed of acrylic (contrast in Hounsfield units [ΔHU] = 120) as well as a soft tissue equivalent material (ΔHU = 50). For each shape, we measured the modulation transfer functions (MTFs) of IR and filtered back projection (FBP) using two multi-slice CT scanners at scan doses of 5 and 10 mGy. In addition, we evaluated a thin metal wire using the conventional method at 10 mGy. For FBP images, the MTF results of the tested objects and the wire method showed substantial agreement, thus demonstrating the validity of our analysis technique. For IR images, the MTF results of different shapes were nearly identical for each object contrast and dose combination, and we did not observe shape-dependent effects of the resolution properties of either tested IR. We conclude that both the circular edge method and linear edge method are equally useful for evaluating the resolution properties of IRs.     

A newly-developed metal artifact reduction algorithm improves the visibility of oral cavity lesions on 320-MDCT volume scans

PurposeTo investigate whether a newly-developed single-energy metal artifact reduction (SEMAR) algorithm applied to images acquired on a 320-MDCT volume scanner reduces image artifacts from dental metal.MethodsWe inserted the lower right teeth covered with a dental metal alloy and crown in a skull phantom and performed single-volume scanning on a second-generation 320-MDCT scanner. A 12-mm diameter spherical lesion was placed either close to or far from the dental metal. The tube voltage and current were 120 kVp and 80 or 155 mA, respectively. Images were reconstructed with filtered back projection (FBP) or iterative reconstruction (IR), with or without SEMAR. We calculated the signal-to-artifact ratios (SAR) to quantify the visibility of the lesion. Two radiologists inspected 96 images (48 with lesion and 48 without) for the presence or absence of the lesion using a 5-point ordinal scale (1 = definitely absent to 5 = definitely present).ResultsOn images reconstructed with FPB and IR with SEMAR, streak artifacts from the dental metal were reduced substantially compared to images without SEMAR. At 155 mA with the lesion near the dental metal, the SARs were better on FBP and IR images (FBP: 1.7 and 0.5 with and without SEMAR, respectively; IR: 1.6 and 0.9 with and without SEMAR, respectively). The observer visual scores improved with SEMAR (FBP: 4.2 and 3.2 with and without SEMAR, respectively; IR: 4.2 and 3.0).ConclusionThe SEMAR algorithm reduces dental metal artifacts and improves lesion detectability and image quality in patients with oral cavity lesions.     

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.     

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.     

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.     

Algorithm-based artifact reduction in patients with arms-down positioning in computed tomography

PurposeArm-artifact, a type of streak artifact frequently observed in computed tomography (CT) images obtained at arms-down positioning in polytrauma patients, is known to degrade image quality. This study aimed to develop a novel arm-artifact reduction algorithm (AAR) applied to projection data.MethodsA phantom resembling an adult abdomen with two arms was scanned using a 16-row CT scanner. The projection data were processed by AAR, and CT images were reconstructed. The artifact reduction for the same phantom was compared with that achieved by two latest iterative reconstruction (IR) techniques (IR1 and IR2) using a normalized artifact index (nAI) at two locations (ventral and dorsal side). Image blurring as a processing side effect was compared with IR2 of the model-based IR using a plastic needle phantom. Additionally, the projection data of two clinical cases were processed using AAR, and the image noise was evaluated.ResultsAAR and IR2 significantly reduced nAI by 87.5% and 74.0%, respectively at the ventral side and 84.2% and 69.6%, respectively, at the dorsal side compared with each filtered back projection (P < 0.01), whereas IR1 did not. The proposed algorithm mostly maintained the original spatial resolution, compared with IR2, which yielded apparent image blurring. The image noise in the clinical cases was also reduced significantly (P < 0.01).ConclusionsAAR was more effective and superior than the latest IR techniques and is expected to improve the image quality of polytrauma CT imaging with arms-down positioning.     

Experimental implementation of a polyenergetic statistical reconstruction algorithm for a commercial fan-beam CT scanner

PurposeTo present a framework for characterizing the data needed to implement a polyenergetic model-based statistical reconstruction algorithm, Alternating Minimization (AM), on a commercial fan-beam CT scanner and a novel method for assessing the accuracy of the commissioned data model.MethodsThe X-ray spectra for three tube potentials on the Philips Brilliance CT scanner were estimated by fitting a semi-empirical X-ray spectrum model to transmission measurements. Spectral variations due to the bowtie filter were computationally modeled. Eight homogeneous cylinders of PMMA, Teflon and water with varying diameters were scanned at each energy. Central-axis scatter was measured for each cylinder using a beam-stop technique. AM reconstruction with a single-basis object-model matched to the scanned cylinder's composition allows assessment of the accuracy of the AM algorithm's polyenergetic data model. Filtered-backprojection (FBP) was also performed to compare consistency metrics such as uniformity and object-size dependence.ResultsThe spectrum model fit measured transmission curves with residual root-mean-square-error of 1.20%–1.34% for the three scanning energies. The estimated spectrum and scatter data supported polyenergetic AM reconstruction of the test cylinders to within 0.5% of expected in the matched object-model reconstruction test. In comparison to FBP, polyenergetic AM exhibited better uniformity and less object-size dependence.ConclusionsReconstruction using a matched object-model illustrate that the polyenergetic AM algorithm's data model was commissioned to within 0.5% of an expected ground truth. These results support ongoing and future research with polyenergetic AM reconstruction of commercial fan-beam CT data for quantitative CT applications.     

Utility of fast non-local means (FNLM) filter for detection of pulmonary nodules in chest CT for pediatric patient

PurposeThis study was aimed to evaluate the utility based on imaging quality of the fast non-local means (FNLM) filter in diagnosing lung nodules in pediatric chest computed tomography (CT).MethodsWe retrospectively reviewed the chest CT reconstructed with both filtered back projection (FBP) and iterative reconstruction (IR) in pediatric patients with metastatic lung nodules. After applying FNLM filter with six h values (0.0001, 0.001, 0.01, 0.1, 1, and 10) to the FBP images, eight sets of images including FBP, IR, and FNLM were analyzed. The image quality of the lung nodules was evaluated objectively for coefficient of variation (COV), contrast to noise ratio (CNR), and point spread function (PSF), and subjectively for noise, sharpness, artifacts, and diagnostic acceptability.ResultsThe COV was lowest in IR images and decreased according to increasing h values and highest with FBP images (P < 0.001). The CNR was highest with IR images, increased according to increasing h values and lowest with FBP images (P < 0.001). The PSF was lower only in FNLM filter with h value of 0.0001 or 0.001 than in IR images (P < 0.001). In subjective analysis, only images of FNLM filter with h value of 0.0001 or 0.001 rarely showed unacceptable quality and had comparable results with IR images. There were less artifacts in FNLM images with h value of 0.0001 compared with IR images (p < 0.001).ConclusionFNLM filter with h values of 0.0001 allows comparable image quality with less artifacts compared with IR in diagnosing metastatic lung nodules in pediatric chest CT.     

Evaluating the usefulness of the direct density reconstruction algorithm for intensity modulated and passively scattered proton therapy: Validation using an anthropomorphic phantom

PurposeAccurate calculation of the proton beam range inside a patient is an important topic in proton therapy. In recent times, a computed tomography (CT) image reconstruction algorithm was developed for treatment planning to reduce the impact of the variation of the CT number with changes in imaging conditions. In this study, we investigated the usefulness of this new reconstruction algorithm (DirectDensity™: DD) in proton therapy based on its comparison with filtered back projection (FBP).MethodsWe evaluated the effects of variations in the X-ray tube potential and target size on the FBP- and DD-image values and investigated the usefulness of the DD algorithm based on the range variations and dosimetric quantity variations.ResultsFor X-ray tube potential variations, the range variation in the case of FBP was up to 12.5 mm (20.8%), whereas that of DD was up to 3.3 mm (5.6%). Meanwhile, for target size variations, the range variation in the case of FBP was up to 2.2 mm (2.5%), whereas that of DD was up to 0.9 mm (1.4%). Moreover, the variations observed in the case of DD were smaller than those of FBP for all dosimetric quantities.ConclusionThe dose distributions obtained using DD were more robust against variations in the CT imaging conditions (X-ray tube potential and target size) than those obtained using FBP, and the range variations were often less than the dose calculation grid (2 mm). Therefore, the DD algorithm is effective in a robust workflow and reduces uncertainty in range calculations.     

Deep learning-based reconstruction in ultra-high-resolution computed tomography: Can image noise caused by high definition detector and the miniaturization of matrix element size be improved?

PurposeThis study aimed to assess the noise characteristics of ultra-high-resolution computed tomography (UHRCT) with deep learning-based reconstruction (DLR).MethodsTwo different diameters of water phantom were scanned with three different resolution acquisition modes. Images were reconstructed by filtered back projection (FBP), hybrid iterative reconstruction (hybrid-IR), and DLR. Image noise analysis was performed with noise magnitude, peak frequency (f_p) of the noise power spectrum (NPS), and the square root of the area under the curve (√AUC_NPS) for the NPS curve.ResultsThe noise magnitude was up to 3.30 times higher for the FBP acquired in SHR mode than that for the NR mode.The f_p values of the FBP were 0.20–0.21, 0.34–0.36, and 0.34–0.37 cycles/mm for normal resolution (NR), high resolution (HR), and super high resolution (SHR) mode, respectively. The f_p of hybrid-IR was 0.16–0.19, 0.21–0.26, and 0.23–0.26 cycles/mm for NR, HR, and SHR mode, respectively. The f_p of DLR was 0.21–0.32 and 0.22–0.33 cycles/mm for HR and SHR mode, respectively.√AUC_NPS showed that the highest value in FBP images of the SHR mode was up to 1.89 times that of the NR mode. DLR in the HR and SHR modes showed high noise reduction while suppressing f_p shift with respect to FBP.ConclusionsThe new DLR algorithm could be a solution to the noise increase due to the high-definition detector elements and the small reconstruction matrix element size.     

Performance comparison of two resolution modeling PET reconstruction algorithms in terms of physical figures of merit used in quantitative imaging

PurposeResolution modeling (RM) of PET systems has been introduced in iterative reconstruction algorithms for oncologic PET. The RM recovers the loss of resolution and reduces the associated partial volume effect. While these methods improved the observer performance, particularly in the detection of small and faint lesions, their impact on quantification accuracy still requires thorough investigation. The aim of this study was to characterize the performances of the RM algorithms under controlled conditions simulating a typical ¹⁸F-FDG oncologic study, using an anthropomorphic phantom and selected physical figures of merit, used for image quantification.MethodsMeasurements were performed on Biograph HiREZ (B_HiREZ) and Discovery 710 (D_710) PET/CT scanners and reconstructions were performed using the standard iterative reconstructions and the RM algorithms associated to each scanner: TrueX and SharpIR, respectively.ResultsRM determined a significant improvement in contrast recovery for small targets (≤17 mm diameter) only for the D_710 scanner. The maximum standardized uptake value (SUV_max) increased when RM was applied using both scanners. The SUV_max of small targets was on average lower with the B_HiREZ than with the D_710. Sharp IR improved the accuracy of SUV_max determination, whilst TrueX showed an overestimation of SUV_max for sphere dimensions greater than 22 mm. The goodness of fit of adaptive threshold algorithms worsened significantly when RM algorithms were employed for both scanners.ConclusionsDifferences in general quantitative performance were observed for the PET scanners analyzed. Segmentation of PET images using adaptive threshold algorithms should not be undertaken in conjunction with RM reconstructions.     

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.     

Image quality characteristics for virtual monoenergetic images using dual-layer spectral detector CT: Comparison with conventional tube-voltage images

PurposeTo investigate the image quality characteristics for virtual monoenergetic images compared with conventional tube-voltage image with dual-layer spectral CT (DLCT).MethodsHelical scans were performed using a first-generation DLCT scanner, two different sizes of acrylic cylindrical phantoms, and a Catphan phantom. Three different iodine concentrations were inserted into the phantom center. The single-tube voltage for obtaining virtual monoenergetic images was set to 120 or 140 kVp. Conventional 120- and 140-kVp images and virtual monoenergetic images (40–200-keV images) were reconstructed from slice thicknesses of 1.0 mm. The CT number and image noise were measured for each iodine concentration and water on the 120-kVp images and virtual monoenergetic images. The noise power spectrum (NPS) was also calculated.ResultsThe iodine CT numbers for the iodinated enhancing materials were similar regardless of phantom size and acquisition method. Compared with the iodine CT numbers of the conventional 120-kVp images, those for the monoenergetic 40-, 50-, and 60-keV images increased by approximately 3.0-, 1.9-, and 1.3-fold, respectively. The image noise values for each virtual monoenergetic image were similar (for example, 24.6 HU at 40 keV and 23.3 HU at 200 keV obtained at 120 kVp and 30-cm phantom size). The NPS curves of the 70-keV and 120-kVp images for a 1.0-mm slice thickness over the entire frequency range were similar.ConclusionVirtual monoenergetic images represent stable image noise over the entire energy spectrum and improved the contrast-to-noise ratio than conventional tube voltage using the dual-layer spectral detector CT.     

Dose calculation validation of a convolution algorithm in a solid water phantom

PurposeThe dose calculated using a convolution algorithm should be validated in a simple homogeneous water-equivalent phantom before clinical use. The dose calculation accuracy within a solid water phantom was investigated.MethodsThe specific Gamma knife design requires a dose rate calibration within a spherical solid water phantom. The TMR10 algorithm, which approximates the phantom material as liquid water, correctly computes the absolute dose in water. The convolution algorithm, which considers electron density miscalculates the dose in water as the phantom Hounsfield units were converted into higher electron density when the original CT calibration curve was used. To address this issue, the electron density of liquid water was affected by modifying the CT calibration curve. The absolute dose calculated using the convolution algorithm was compared with that computed by the TMR10. The measured depth dose profiles were also compared to those computed by the convolution and TMR10 algorithms. A patient treatment was recalculated in the solid-water phantom and the delivery quality assurance was checked.ResultsThe convolution algorithm and the TMR10 calculate an absolute dose within 1% when using the modified CT calibration curve. The dose depth profile calculated using the convolution algorithms was superimposed on the TMR10 and measured dose profiles when the modified CT calibration curve was applied. The Gamma index was better than 93%.ConclusionsDose calculation algorithms, which consider electron density, require a CT calibration curve adapted to the phantom material to correctly compute the dose in water.     

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.     

自由呼吸状态下冠状动脉CT血管成像的可行性研究

目的:探讨自由呼吸状态下冠状动脉CT血管成像(Coronary CT Angiography, CCTA)的可行性。方法:收集187例疑似冠心病患者,所有患者均行CCTA检查,其中108例采用传统屏气法扫描,79例采用自由呼吸法扫描。扫描采用前门控预估法(Auto Gating)测得冠脉扫描期相,设置扫描范围和参数(准直宽度256×0.625、224×0.625、192×0.625,球管转速0.28 s,kV100,智能管电流,噪声指数25)。对比剂浓度为370 mg I/m L,注药量为0.86 m L/kg,注药时间维持12 s。由2名高年资放射科医师对冠状动脉图像采用5分法评分。测量升主动脉根部(冠状动脉左主干开口水平)和胸壁肌肉的CT值及标准差,计算图像的信噪比和对比噪声比。结果:自由呼吸状态下右冠状动脉(Right coronary artery, RCA)、左前降支(Left ascending artery, LAD)、左旋支(Left circumflex artery, LCx)的优良血管率分别为46.5%(87/187)、51.9%(97/187)及48.7%(91/187);屏气状态下RCA、LAD、LCx的优良血管率分别为32.6%(61/187)、36.4%(68/187)及36.9%(69/187),两组之间无统计学差异(Fisher值分别为6.94、1.54、0.81,P均0.05)。采用自由呼吸和屏气状态下CCTA检查的主动脉CT值、噪声、SNR和CNR均无统计学差异(P均0.05)。结论:采用超宽探测器CT,自由呼吸法CCTA可完全取代传统屏气法CCTA检查,从而降低受检者的配合难度,提高工作效率。