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 in Children with Low-Radiation Chest CT Using Adaptive Statistical Iterative Reconstruction and Model-Based Iterative Reconstruction

Objective

To evaluate noise reduction and image quality improvement in low-radiation dose chest CT images in children using adaptive statistical iterative reconstruction (ASIR) and a full model-based iterative reconstruction (MBIR) algorithm.

Methods

Forty-five children (age ranging from 28 days to 6 years, median of 1.8 years) who received low-dose chest CT scans were included. Age-dependent noise index (NI) was used for acquisition. Images were retrospectively reconstructed using three methods: MBIR, 60% of ASIR and 40% of conventional filtered back-projection (FBP), and FBP. The subjective quality of the images was independently evaluated by two radiologists. Objective noises in the left ventricle (LV), muscle, fat, descending aorta and lung field at the layer with the largest cross-section area of LV were measured, with the region of interest about one fourth to half of the area of descending aorta. Optimized signal-to-noise ratio (SNR) was calculated.

Result

In terms of subjective quality, MBIR images were significantly better than ASIR and FBP in image noise and visibility of tiny structures, but blurred edges were observed. In terms of objective noise, MBIR and ASIR reconstruction decreased the image noise by 55.2% and 31.8%, respectively, for LV compared with FBP. Similarly, MBIR and ASIR reconstruction increased the SNR by 124.0% and 46.2%, respectively, compared with FBP.

Conclusion

Compared with FBP and ASIR, overall image quality and noise reduction were significantly improved by MBIR. MBIR image could reconstruct eligible chest CT images in children with lower radiation dose.     

Bone-induced streak artifact suppression in sparse-view CT image reconstruction

ABSTRACT: BACKGROUND: In sparse-view CT imaging, strong streak artifacts may appear around bony structures and they often compromise the image readability. Compressed sensing (CS) or total variation (TV) minimization-based image reconstruction method has reduced the streak artifacts to a great extent, but, sparse-view CT imaging still suffers from residual streak artifacts. We introduce a new bone-induced streak artifact reduction method in the CS-based image reconstruction. METHODS: We firstly identify the high-intensity bony regions from the image reconstructed by the filtered backprojection (FBP) method, and we calculate the sinogram stemming from the bony regions only. Then, we subtract the calculated sinogram, which stands for the bony regions, from the measured sinogram before performing the CS-based image reconstruction. The image reconstructed from the subtracted sinogram will stand for the soft tissues with little streak artifacts on it. To restore the original image intensity in the bony regions, we add the bony region image, which has been identified from the FBP image, to the soft tissue image to form a combined image. Then, we perform the CS-based image reconstruction again on the measured sinogram using the combined image as the initial condition of the iteration. For experimental validation of the proposed method, we take images of a contrast phantom and a rat using a micro-CT and we evaluate the reconstructed images based on two figures of merit, relative mean square error and total variation caused by the streak artifacts. RESULTS: The images reconstructed by the proposed method have been found to have smaller streak artifacts than the ones reconstructed by the original CS-based method when visually inspected. The quantitative image evaluation studies have also shown that the proposed method outperforms the conventional CS-based method. CONCLUSIONS: The proposed method can effectively suppress streak artifacts stemming from bony structures in sparse-view CT imaging.     

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.     

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.     

Reduced Radiation Exposure for Face Transplant Surgical Planning Computed Tomography Angiography

Objective

To test the hypothesis that wide area detector face transplant surgical planning CT angiograms with simulated lower radiation dose and iterative reconstruction (AIDR3D) are comparable in image quality to those with standard tube current and filtered back projection (FBP) reconstruction.

Materials and Methods

The sinograms from 320-detector row CT angiography of four clinical candidates for face transplantation were processed utilizing standard FBP, FBP with simulated 75, 62, and 50% tube current, and AIDR3D with corresponding dose reduction. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured at muscle, fat, artery, and vein. Image quality for each reconstruction strategy was assessed by two independent readers using a 4-point scale.

Results

Compared to FBP, the median SNR and CNR for AIDR3D images were higher at all sites for all 4 different tube currents. The AIDR3D with simulated 50% tube current achieved comparable SNR and CNR to FBP with standard dose (median muscle SNR: 5.77 vs. 6.23; fat SNR: 6.40 vs. 5.75; artery SNR: 43.8 vs. 45.0; vein SNR: 54.9 vs. 55.7; artery CNR: 38.1 vs. 38.6; vein CNR: 49.0 vs. 48.7; all p-values >0.19). The interobserver agreement in the image quality score was good (weighted κ = 0.7). The overall score and the scores for smaller arteries were significantly lower when FBP with 50% dose reduction was used. The AIDR3D reconstruction images with 4 different simulated doses achieved a mean score ranging from 3.68 to 3.82 that were comparable to the scores from images reconstructed using FBP with original dose (3.68–3.77).

Conclusions

Simulated radiation dose reduction applied to clinical CT angiography for face transplant planning suggests that AIDR3D allows for a 50% reduction in radiation dose, as compared to FBP, while preserving image quality.     

Noise properties of reconstructed images in a kilo-voltage on-board imaging system with iterative reconstruction techniques: A phantom study

X-ray computed tomography (CT) images obtained with a kilo-voltage (kV) on-board imaging (OBI) system improve the accuracy of patient setup and treatment planning. The use of iterative reconstruction techniques (IRTs) for CT imaging can also reduce radiation dose compared to analytic reconstruction techniques. Despite these improvements, the image quality varies with IRTs, and the noise structure of reconstructed images can be distorted by IRTs. In this study, the noise properties and spatial resolution of the images reconstructed by IRTs were evaluated in terms of conventional noise metrics, high-order statistics, noise spectral density (NSD) and modulation transfer function (MTF) at different radiation doses. A kV OBI system mounted on a Varian Trilogy machine and a CATPHAN600 phantom were used to obtain projections, and the projections were reconstructed by Feldkamp (FDK), algebraic reconstruction technique (ART), maximum-likelihood expectation–maximization (MLEM) and total variation (TV) minimization algorithms. The reconstructed images were compared according to mean, standard deviation, skewness, kurtosis, NSD and MTF at different radiation doses. The results demonstrated that the noise properties and spatial resolution of reconstructed images depend on the type of IRT and the radiation dose. The noise structures are altered by IRTs and can be characterized by high-order statistics and NSD, as well as conventional noise metrics. In conclusion, high-order statistics and NSD should be considered in order to provide detailed information for the images reconstructed by IRTs. Also, trade-off among noise properties, spatial resolution and contrast is important to optimize image quality obtained using IRTs.     

CT iterative reconstruction in image space: A phantom study

Although iterative reconstruction is widely applied in SPECT/PET, its introduction in clinical CT is quite recent, in the past the demand for extensive computer power and long image reconstruction times have stopped the diffusion of this technique. Recently Iterative Reconstruction in Image Space (IRIS) has been introduced on Siemens top CT scanners. This recon method works on image data area, reducing the time-consuming loops on raw data and noise removal is obtained in subsequent iterative steps with a smoothing process. We evaluated image noise, low contrast resolution, CT number linearity and accuracy, transverse and z-axis spatial resolution using some dedicated phantoms in single, dual source and cardiac mode. We reconstructed images with a traditional filtered back-projection algorithm and with IRIS. The iterative procedure preserves spatial resolution, CT number accuracy and linearity moreover decreases image noise. These preliminary results support the idea that dose reduction with preserved image quality is possible with IRIS, even if studies on patients are necessary to confirm these data.     

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.     

Whole-Organ CT Perfusion of the Pancreas: Impact of Iterative Reconstruction on Image Quality,Perfusion Parameters and Radiation Dose in 256-Slice CT-Preliminary Findings

Background

This study was performed to assess whether iterative reconstruction can reduce radiation dose while maintaining acceptable image quality, and to investigate whether perfusion parameters vary from conventional filtered back projection (FBP) at the low-tube-voltage (80-kVp) during whole-pancreas perfusion examination using a 256-slice CT.

Methods

76 patients with known or suspected pancreatic mass underwent whole-pancreas perfusion by a 256-slice CT. High- and low-tube-voltage CT images were acquired. 120-kVp image data (protocol A) and 80-kVp image data (protocol B) were reconstructed with conventional FBP, and 80-kVp image data were reconstructed with iDose⁴ (protocol C) iterative reconstruction. The image noise; contrast-to-noise ratio (CNR) relative to muscle for the pancreas, liver, and aorta; and radiation dose of each protocol were assessed quantitatively. Overall image quality was assessed qualitatively. Among 76 patients, 23 were eventually proven to have a normal pancreas. Perfusion parameters of normal pancreas in each protocol including blood volume, blood flow, and permeability-surface area product were measured.

Results

In the quantitative study, protocol C reduced image noise by 36.8% compared to protocol B (P<0.001). Protocol C yielded significantly higher CNR relative to muscle for the aorta, pancreas and liver compared to protocol B (P<0.001), and offered no significant difference compared to protocol A. In the qualitative study, protocols C and A gained similar scores and protocol B gained the lowest score for overall image quality (P<0.001). Mean effective doses were 23.37 mSv for protocol A and 10.81 mSv for protocols B and C. There were no significant differences in the normal pancreas perfusion values among three different protocols.

Conclusion

Low-tube-voltage and iDose⁴ iterative reconstruction can dramatically decrease the radiation dose with acceptable image quality during whole-pancreas CT perfusion and have no significant impact on the perfusion parameters of normal pancreas compared to the conventional FBP reconstruction using a 256-slice CT scanner.     

Optimization of SPECT-CT Hybrid Imaging Using Iterative Image Reconstruction for Low-Dose CT: A Phantom Study

Background

Hybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT) or positron emission tomography (PET) with computed tomography (CT). Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR) on the image quality of the low-dose CT images.

Methodology/Principal Findings

Examinations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU) values reconstructed by ASIR were correlated to the FBP HU values(R² ≥ 0.88) and the contrast-to-noise ratio (CNR) was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04). In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001).

Conclusion/Significance

In general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality.     

Generating and using patient-specific whole-body models for organ dose estimates in CT with increased accuracy: Feasibility and validation

The estimation of patient dose using Monte Carlo (MC) simulations based on the available patient CT images is limited to the length of the scan. Software tools for dose estimation based on standard computational phantoms overcome this problem; however, they are limited with respect to taking individual patient anatomy into account. The purpose of this study was to generate whole-body patient models in order to take scattered radiation and over-scanning effects into account. Thorax examinations were performed on three physical anthropomorphic phantoms at tube voltages of 80 kV and 120 kV; absorbed dose was measured using thermoluminescence dosimeters (TLD). Whole-body voxel models were built as a combination of the acquired CT images appended by data taken from widely used anthropomorphic voxel phantoms. MC simulations were performed both for the CT image volumes alone and for the whole-body models. Measured and calculated dose distributions were compared for each TLD chip position; additionally, organ doses were determined.MC simulations based only on CT data underestimated dose by 8%–15% on average depending on patient size with highest underestimation values of 37% for the adult phantom at the caudal border of the image volume. The use of whole-body models substantially reduced these errors; measured and simulated results consistently agreed to better than 10%.This study demonstrates that combined whole-body models can provide three-dimensional dose distributions with improved accuracy. Using the presented concept should be of high interest for research studies which demand high accuracy, e.g. for dose optimization efforts.     

Development of a 3D optical scanner for evaluating patient-specific dose distributions

PurposeThis paper describes the hardware and software characteristics of a 3D optical scanner (P3DS) developed in-house. The P3DS consists of an LED light source, diffuse screen, step motor, CCD camera, and scanner management software with 3D reconstructed software.Materials and methodWe performed optical simulation, 2D and 3D reconstruction image testing, and pre-clinical testing for the P3DS. We developed the optical scanner with three key characteristics in mind. First, we developed a continuous scanning method to expand possible clinical applications. Second, we manufactured a collimator to improve image quality by reducing scattering from the light source. Third, we developed an optical scanner with changeable camera positioning to enable acquisition of optimal images according to the size of the gel dosimeter.ResultsWe confirmed ray-tracing in P3DS with optic simulation and found that 2D projection and 3D reconstructed images were qualitatively similar to the phantom images. For pre-clinical tests, the dose distribution and profile showed good agreement among RTP, optical CT, and external beam radiotherapy film data for the axial and coronal views. The P3DS has shown that it can scan and reconstruct for evaluation of the gel dosimeter within 1 min. We confirmed that the P3DS system is a useful tool for the measurement of 3D dose distributions for 3D radiation therapy QA. Further experiments are needed to investigate quantitative analysis for 3D dose distribution.     

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.     

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.     

Feasibility Study of Using Gemstone Spectral Imaging (GSI) and Adaptive Statistical Iterative Reconstruction (ASIR) for Reducing Radiation and Iodine Contrast Dose in Abdominal CT Patients with High BMI Values

Purpose

To prospectively investigate the effect of using Gemstone Spectral Imaging (GSI) and adaptive statistical iterative reconstruction (ASIR) for reducing radiation and iodine contrast dose in abdominal CT patients with high BMI values.

Materials and Methods

26 patients (weight > 65kg and BMI ≥ 22) underwent abdominal CT using GSI mode with 300mgI/kg contrast material as study group (group A). Another 21 patients (weight ≤ 65kg and BMI ≥ 22) were scanned with a conventional 120 kVp tube voltage for noise index (NI) of 11 with 450mgI/kg contrast material as control group (group B). GSI images were reconstructed at 60keV with 50%ASIR and the conventional 120kVp images were reconstructed with FBP reconstruction. The CT values, standard deviation (SD), signal-noise-ratio (SNR), contrast-noise-ratio (CNR) of 26 landmarks were quantitatively measured and image quality qualitatively assessed using statistical analysis.

Results

As for the quantitative analysis, the difference of CNR between groups A and B was all significant except for the mesenteric vein. The SNR in group A was higher than B except the mesenteric artery and splenic artery. As for the qualitative analysis, all images had diagnostic quality and the agreement for image quality assessment between the reviewers was substantial (kappa = 0.684). CT dose index (CTDI) values for non-enhanced, arterial phase and portal phase in group A were decreased by 49.04%, 40.51% and 40.54% compared with group B (P = 0.000), respectively. The total dose and the injection rate for the contrast material were reduced by 14.40% and 14.95% in A compared with B.

Conclusion

The use of GSI and ASIR provides similar enhancement in vessels and image quality with reduced radiation dose and contrast dose, compared with the use of conventional scan protocol.     

应用反向滤过及迭代重建方法评估标准放射剂量与低剂量颈椎 CT图像质量的对比研究

目的：利用反向滤过重建（filtered back-projection,FBP）及迭代重建（iterative reconstruction,IR）方法评估标准剂量及低剂量 对颈椎CT 图像质量的影响。方法：40 例受检对象行颈椎CT 检查,将其随机分为两组：标准剂量组（SD,120 kVp, 275 mAs）及低 剂量组（LD,120 kVp,150 mAs）,随机选择管电流值,所有数据均行FBP 及IR 重建。测量C3 C4 及C6 C7 椎间盘水平椎间盘、脊 神经、脊髓、韧带以及周围软组织的图像噪声值（Image noise,IN）,信噪比（signal-to-noise,SNR）及对比信噪比（contrast-to-noise, CNR）。结果：在测量的各椎间盘水平,迭代重建的信噪比及对比噪声比要明显高于反向滤过重建方法,并有效的降低了图像噪 声。低剂量迭代重建图像与标准剂量反向滤过图像相比无明显统计学意义。排除剂量及扫描层面的影响,椎间盘、脊神经及韧带 的图像质量,迭代重建评分要明显高于反向滤过重建,结果具有统计学差异;而低剂量迭代重建图像质量评分与标准剂量反向滤 过重建相比无明显差异。软组织及椎体的图像质量,迭代重建图像质量评分要低于反向滤过重建方法,结果具有统计学差异;而 低剂量迭代重建图像质量评分与标准剂量反向滤过重建相比无明显差异。整体病例图像质量评分,迭代重建方法要高于反向滤 过重建方法,低剂量迭代重建方法要高于标准剂量反向滤过重建方法。结论：应用低剂量扫描方式以及迭代重建方法进行颈椎 CT 检查可以为临床提供较好的图像质量,对于椎间盘、脊神经、脊髓显示较好,对于周围软组织以及椎体来说,图像质量相对较 差,同时可以降低大约40%的放射剂量。     

应用反向滤过及迭代重建方法评估标准放射剂量与低剂量颈椎CT图像质量的对比研究

目的：利用反向滤过重建（filtered back-projecfion,FBP）及迭代重建（iterative reconstruction,IR）方法评估标准剂量及低剂量对颈椎CT图像质量的影响。方法：40例受检对象行颈椎CT检查,将其随机分为两组：标准剂量组（SD,120kVp,275mAs）及低剂量组（LD,120kVp,150mAs）,随机选择管电流值,所有数据均行FBP及IR重建。测量C3C4及C6C7椎间盘水平椎间盘、脊神经、脊髓、韧带以及周围软组织的图像噪声值（Imagenoise,IN）,信噪比（signal—to—noise,SNR）及对比信噪比（contrast—to—noise,CNR）。结果：在测量的各椎间盘水平,迭代重建的信噪比及对比噪声比要明显高于反向滤过重建方法,并有效的降低了图像噪声。低剂量迭代重建图像与标准剂量反向滤过图像相比无明显统计学意义。排除剂量及扫描层面的影响,椎间盘、脊神经及韧带的图像质量,迭代重建评分要明显高于反向滤过重建,结果具有统计学差异;而低剂量迭代重建图像质量评分与标准剂量反向滤过重建相比无明显差异。软组织及椎体的图像质量,迭代重建图像质量评分要低于反向滤过重建方法,结果具有统计学差异;而低剂量迭代重建图像质量评分与标准剂量反向滤过重建相比无明显差异。整体病例图像质量评分,迭代重建方法要高于反向滤过重建方法,低剂量迭代重建方法要高于标准剂量反向滤过重建方法。结论：应用低剂量扫描方式以及迭代重建方法进行颈椎CT检查可以为I临床提供较好的图像质量,对于椎间盘、脊神经、脊髓显示较好,对于周围软组织以及椎体来说,图像质量相对较差,同时可以降低大约40％的放射剂量。     

A Novel Iterative CT Reconstruction Approach Based on FBP Algorithm

The Filtered Back-Projection (FBP) algorithm and its modified versions are the most important techniques for CT (Computerized tomography) reconstruction, however, it may produce aliasing degradation in the reconstructed images due to projection discretization. The general iterative reconstruction (IR) algorithms suffer from their heavy calculation burden and other drawbacks. In this paper, an iterative FBP approach is proposed to reduce the aliasing degradation. In the approach, the image reconstructed by FBP algorithm is treated as the intermediate image and projected along the original projection directions to produce the reprojection data. The difference between the original and reprojection data is filtered by a special digital filter, and then is reconstructed by FBP to produce a correction term. The correction term is added to the intermediate image to update it. This procedure can be performed iteratively to improve the reconstruction performance gradually until certain stopping criterion is satisfied. Some simulations and tests on real data show the proposed approach is better than FBP algorithm or some IR algorithms in term of some general image criteria. The calculation burden is several times that of FBP, which is much less than that of general IR algorithms and acceptable in the most situations. Therefore, the proposed algorithm has the potential applications in practical CT systems.     

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.