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.     

Quantifying near metal visibility using dual energy computed tomography and iterative metal artifact reduction in a fracture phantom

PurposeTo quantitatively assess CT image quality and fracture visibility using virtual monochromatic imaging and iterative metal artifact reduction (iMAR) in a femoral bone fracture phantom with different fixation implants.MethodsA custom made phantom was scanned at 120-kVp and 140-kVp single-energy and 100/150-kVp dual-energy. Three stainless steel and two titanium implants with different thicknesses were placed on the phantom containing simulated one and two mm fractures. Single-energy CT images were reconstructed with and without iMAR, while DECT images were reconstructed at monochromatic energies between 70 and 190 keV. Non-metal scans were used as a reference. A Fourier power spectrum method and fracture model were used to analyze several anatomical areas.ResultsCT-value deviations of titanium implants were much lower compared to stainless steel implants. These deviations decreased for both DECT and iMAR. Fracture visibility, measured with the fracture model, improved the most when DECT was used while artifact reduction benefitted more from iMAR. The optimal monochromatic energy for metal artifact reduction, based on CT-value deviation, varied for each metal between 130 and 150 keV. The fracture model provided a signal-to-noise ratio for the near metal fracture visibility, providing the optimal keV.ConclusioniMAR and high keV monochromatic images extracted from DECT both reduce metal artifacts caused by different metal fixation implants. Quantitative femoral phantom results show that DECT is superior to iMAR regarding fracture visualization adjacent to metal fixation implants. The introduction of new artifacts when using iMAR impedes its value in near metal fixation implant imaging.     

Spectral CT Imaging of Laryngeal and Hypopharyngeal Squamous Cell Carcinoma: Evaluation of Image Quality and Status of Lymph Nodes

Purpose

The purpose of this study was to evaluate image quality and status of lymph nodes in laryngeal and hypopharyngeal squamous cell carcinoma (SCC) patients using spectral CT imaging.

Materials and Methods

Thirty-eight patients with laryngeal and hypopharyngeal SCCs were scanned with spectral CT mode in venous phase. The conventional 140-kVp polychromatic images and one hundred and one sets of monochromatic images were generated ranging from 40 keV to 140 keV. The mean optimal keV was calculated on the monochromatic images. The image quality of the mean optimal keV monochromatic images and polychromatic images was compared with two different methods including a quantitative analysis method and a qualitative analysis method. The HU curve slope (λ_HU) in the target lymph nodes and the primary lesion was calculated respectively. The ratio of λ_HU was studied between metastatic and non-metastatic lymph nodes group.

Results

A total of 38 primary lesions were included. The mean optimal keV was obtained at 55±1.77 keV on the monochromatic images. The image quality evaluated by two different methods including a quantitative analysis method and a qualitative analysis method was obviously increased on monochromatic images than polychromatic images (p<0.05). The ratio of λ_HU between metastatic and non-metastatic lymph nodes was significantly different in the venous phase images (p<0.05).

Conclusion

The monochromatic images obtained with spectral CT can be used to improve the image quality of laryngeal and hypopharyngeal SCC and the N-staging accuracy. The quantitative ratio of λ_HU may be helpful for differentiating between metastatic and non-metastatic cervical lymph nodes.     

Simultaneous achievement of accurate CT number and image quality improvement for myocardial perfusion CT at 320-MDCT volume scanning

PurposeTo investigate differences in image-to-image variations between full- and half-scan reconstruction on myocardial CT perfusion (CTP) study.MethodsUsing a cardiac phantom we performed ECG-gated myocardial CTP on a second-generation 320-multidetector CT volume scanner. The heart rate was set at 60 bpm; once per second for a total of 24 s were performed. CT images were acquired at 80- and 120 kVp and subjected to full- and half-scan reconstruction. On images acquired at the same slice level we then measured image-to-image variations, coefficients of variance (CV), and image noise.ResultsThe image-to-image variations with full- and half-scan reconstruction were 1.3 HU vs. 27.2 HU at 80 kVp (p < 0.001) and 0.70 HU vs. 9.3 HU at 120 kVp (p < 0.001) even though the mean HU value was almost the same for both reconstruction methods. The CV of 80- and 120-kVp images of the left ventricular cavity decreased by 0.16% and 0.17%, respectively, with full-scan reconstruction; with half-scan reconstruction it decreased by 3.34% and 2.30%, respectively. Compared with half-scan reconstruction, the image noise was reduced by 27.2% at 80 kVp and by 28.0% at 120 kVp with full-scan reconstruction.ConclusionMyocardial CTP with full-scan reconstruction substantially decreased image-to-image variations and provided accurate CT attenuation.     

Dual Energy CT Angiography of Peripheral Arterial Disease: Feasibility of Using Lower Contrast Medium Volume

ObjectiveOne of the main drawbacks associated with Dual Energy Computed Tomography Angiography (DECTA) is the risk of developing contrast medium-induced nephropathy (CIN). The aim of the present study was firstly, to design an optimal CT imaging protocol by determining the feasibility of using a reduced contrast medium volume in peripheral arterial DECTA, and secondly, to compare the results with those obtained from using routine contrast medium volume.MethodsThirty four patients underwent DECTA for the diagnosis of peripheral arterial disease. They were randomly divided into two groups: Group 1 (routine contrast volume group) with n = 17, injection rate 4–5 ml/s, and 1.5 ml/kg of contrast medium, and Group 2 ((low contrast volume group), with n = 17, injection rate 4–5ml/s, and contrast medium volume 0.75 ml/kg. A fast kilovoltage—switching 64-slice CT scanner in the dual-energy mode was employed for the study. A total of 6 datasets of monochromatic images at 50, 55, 60, 65, 70 and 75 keV levels were reconstructed with adaptive statistical iterative reconstruction (ASIR) at 50%. A 4-point scale was the tool for qualitative analysis of results. The two groups were compared and assessed quantitatively for image quality on the basis of signal-to-noise ratio (SNR) and contrast-to-noise-ratio (CNR). Radiation and contrast medium doses were also compared.ResultsThe overall mean CT attenuation and mean noise for all lower extremity body parts was significantly lower for the low volume contrast group (p<0.001), and varied significantly between groups (p = 0.001), body parts (p<0.001) and keVs (p<0.001). The interaction between group body parts was significant with CT attenuation and CNR (p = 0.002 and 0.003 respectively), and marginally significant with SNR (p = 0.047), with minimal changes noticed between the two groups. Group 2 (low contrast volume group) displayed the lowest image noise between 65 and 70 keV, recorded the highest SNR and CNR at 65 keV, and produced significantly lower results with respect to contrast medium volume and duration of contrast injection (p<0.001). The effect of radiation dose was not statistically significant between the two groups.ConclusionsDECTA images created at 65 keV and 50% ASIR with low contrast medium volume protocol, yielded results that were comparable to routine contrast medium volume, with acceptable diagnostic images produced during the evaluation of peripheral arteries.     

Monte Carlo evaluation of glandular dose in cone-beam X-ray computed tomography dedicated to the breast: Homogeneous and heterogeneous breast models

PurposeIn cone-beam computed tomography dedicated to the breast (BCT), the mean glandular dose (MGD) is the dose metric of reference, evaluated from the measured air kerma by means of normalized glandular dose coefficients (DgN_CT). This work aimed at computing, for a simple breast model, a set of DgN_CT values for monoenergetic and polyenergetic X-ray beams, and at validating the results vs. those for patient specific digital phantoms from BCT scans.MethodsWe developed a Monte Carlo code for calculation of monoenergetic DgN_CT coefficients (energy range 4.25–82.25 keV). The pendant breast was modelled as a cylinder of a homogeneous mixture of adipose and glandular tissue with glandular fractions by mass of 0.1%, 14.3%, 25%, 50% or 100%, enveloped by a 1.45 mm-thick skin layer. The breast diameter ranged between 8 cm and 18 cm. Then, polyenergetic DgN_CT coefficients were analytically derived for 49-kVp W-anode spectra (half value layer 1.25–1.50 mm Al), as in a commercial BCT scanner. We compared the homogeneous models to 20 digital phantoms produced from classified 3D breast images.ResultsPolyenergetic DgN_CT resulted 13% lower than most recent published data. The comparison vs. patient specific breast phantoms showed that the homogeneous cylindrical model leads to a DgN_CT percentage difference between −15% and +27%, with an average overestimation of 8%.ConclusionsA dataset of monoenergetic and polyenergetic DgN_CT coefficients for BCT was provided. Patient specific breast models showed a different volume distribution of glandular dose and determined a DgN_CT 8% lower, on average, than homogeneous breast model.     

Low-tube-voltage selection for non-contrast-enhanced CT: Comparison of the radiation dose in pediatric and adult phantoms

PurposeWe used pediatric and adult anthropomorphic phantoms to compare the radiation dose of low- and standard tube voltage chest and abdominal non-contrast-enhanced computed tomography (CT) scans. We also discuss the optimal low tube voltage for non-contrast-enhanced CT.MethodsUsing a female adult- and three differently-sized pediatric anthropomorphic phantoms we acquired chest and abdominal non-contrast-enhanced scans on a 320-multidetector CT volume scanner. The tube voltage was set at 80-, 100-, and 120 kVp. The tube current was automatically assigned on the CT scanner in response to the set image noise level. On each phantom and at each tube voltage we measured the surface and center dose using high-sensitivity metal-oxide-semiconductor field-effect transistor detectors.ResultsThe mean surface dose of chest and abdominal CT scans in 5-year olds was 4.4 and 5.3 mGy at 80 kVp, 4.5 and 5.4 mGy at 100 kV, and 4.0 and 5.0 mGy at 120 kVp, respectively. These values were similar in our 3-pediatric phantoms (p > 0.05). The mean surface dose in the adult phantom increased from 14.7 to 19.4 mGy for chest- and from 18.7 to 24.8 mGy for abdominal CT as the tube voltage decreased from 120 to 80 kVp (p < 0.01).ConclusionCompared to adults, the surface and center dose for pediatric patients is almost the same despite a decrease in the tube voltage and the low tube voltage technique can be used for non-contrast-enhanced chest- and abdominal scanning.     

Elimination of biological and physical artifacts in abdomen and brain computed tomography procedures using filtering techniques

IntroductionMedical images are usually affected by biological and physical artifacts or noise, which reduces image quality and hence poses difficulties in visual analysis, interpretation and thus requires higher doses and increased radiographs repetition rate.ObjectivesThis study aims at assessing image quality during CT abdomen and brain examinations using filtering techniques as well as estimating the radiogenic risk associated with CT abdomen and brain examinations.Materials and MethodsThe data were collected from the Radiology Department at Royal Care International (RCI) Hospital, Khartoum, Sudan. The study included 100 abdominal CT images and 100 brain CT images selected from adult patients. Filters applied are namely: Mean filter, Gaussian filter, Median filter and Minimum filter. In this study, image quality after denoising is measured based on the Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and the Structural Similarity Index Metric (SSIM).ResultsThe results show that the images quality parameters become higher after applications of filters. Median filter showed improved image quality as interpreted by the measured parameters: PSNR and SSIM, and it is thus considered as a better filter for removing the noise from all other applied filters.DiscussionThe noise removed by the different filters applied to the CT images resulted in enhancing high quality images thereby effectively revealing the important details of the images without increasing the patients’ risks from higher doses.ConclusionsFiltering and image reconstruction techniques not only reduce the dose and thus the radiation risks, but also enhances high quality imaging which allows better diagnosis.     

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.     

Improvement of image quality for pancreatic cancer using deep learning-generated virtual monochromatic images: Comparison with single-energy computed tomography

PurposeTo construct a deep convolutional neural network that generates virtual monochromatic images (VMIs) from single-energy computed tomography (SECT) images for improved pancreatic cancer imaging quality.Materials and methodsFifty patients with pancreatic cancer underwent a dual-energy CT simulation and VMIs at 77 and 60 keV were reconstructed. A 2D deep densely connected convolutional neural network was modeled to learn the relationship between the VMIs at 77 (input) and 60 keV (ground-truth). Subsequently, VMIs were generated for 20 patients from SECT images using the trained deep learning model.ResultsThe contrast-to-noise ratio was significantly improved (p < 0.001) in the generated VMIs (4.1 ± 1.8) compared to the SECT images (2.8 ± 1.1). The mean overall image quality (4.1 ± 0.6) and tumor enhancement (3.6 ± 0.6) in the generated VMIs assessed on a five-point scale were significantly higher (p < 0.001) than that in the SECT images (3.2 ± 0.4 and 2.8 ± 0.4 for overall image quality and tumor enhancement, respectively).ConclusionsThe quality of the SECT image was significantly improved both objectively and subjectively using the proposed deep learning model for pancreatic tumors in radiotherapy.     

A novel fast kilovoltage switching dual-energy CT with deep learning: Accuracy of CT number on virtual monochromatic imaging and iodine quantification

PurposeA novel fast kilovoltage switching dual-energy CT with deep learning [Deep learning based-spectral CT (DL-Spectral CT)], which generates a complete sinogram for each kilovolt using deep learning views that complement the measured views at each energy, was commercialized in 2020. The purpose of this study was to evaluate the accuracy of CT numbers in virtual monochromatic images (VMIs) and iodine quantifications at various radiation doses using DL-Spectral CT.Materials and methodsTwo multi-energy phantoms (large and small) using several rods representing different materials (iodine, calcium, blood, and adipose) were scanned by DL-Spectral CT at varying radiation doses. Images were reconstructed using three reconstruction parameters (body, lung, bone). The absolute percentage errors (APEs) for CT numbers on VMIs at 50, 70, and 100 keV and iodine quantification were compared among different radiation dose protocols.ResultsThe APEs of the CT numbers on VMIs were <15% in both the large and small phantoms, except at the minimum dose in the large phantom. There were no significant differences among radiation dose protocols in computed tomography dose index volumes of 12.3 mGy or larger. The accuracy of iodine quantification provided by the body parameter was significantly better than those obtained with the lung and bone parameters. Increasing the radiation dose did not always improve the accuracy of iodine quantification, regardless of the reconstruction parameter and phantom size.ConclusionThe accuracy of iodine quantification and CT numbers on VMIs in DL-Spectral CT was not affected by the radiation dose, except for an extremely low radiation dose for body size.     

Spectral CT Imaging in Patients with Budd-Chiari Syndrome: Investigation of Image Quality

To assess the image quality of monochromatic imaging from spectral CT in patients with Budd-Chiari syndrome (BCS), fifty patients with BCS underwent spectral CT to generate conventional 140 kVp polychromatic images (group A) and monochromatic images, with energy levels from 40 to 80, 40 + 70, and 50 + 70 keV fusion images (group B) during the portal venous phase (PVP) and the hepatic venous phase (HVP). Two-sample t tests compared vessel-to-liver contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) for the portal vein (PV), hepatic vein (HV), inferior vena cava. Readers’ subjective evaluations of the image quality were recorded. The highest SNR values in group B were distributed at 50 keV; the highest CNR values in group B were distributed at 40 keV. The higher CNR values and SNR values were obtained though PVP of PV (SNR 18.39 ± 6.13 vs. 10.56 ± 3.31, CNR 7.81 ± 3.40 vs. 3.58 ± 1.31) and HVP of HV (3.89 ± 2.08 vs. 1.27 ± 1.55) in the group B; the lower image noise for group B was at 70 keV and 50 + 70 keV (15.54 ± 8.39 vs. 18.40 ± 4.97, P = 0.0004 and 18.97 ± 7.61 vs. 18.40 ± 4.97, P = 0.0691); the results show that the 50 + 70 keV fusion image quality was better than that in group A. Monochromatic energy levels of 40–70, 40 + 70, and 50 + 70 keV fusion image can increase vascular contrast and that will be helpful for the diagnosis of BCS, we select the 50 + 70 keV fusion image to acquire the best BCS images.     

宝石能谱CT GSI成像和常规成像在上腹部应用价值的对比研究

目的:探讨宝石能谱CT GSI扫描模式在上腹部检查中降低辐射剂量和优化图像质量的可行性及应用价值。方法:选择2016年9月至2016年12月期间我院40例拟行上腹部三期增强的患者,根据扫描模式将患者分为A组和B组,每组20例。A组患者采用宝石能谱CT常规扫描模式行螺旋扫描,管电压120 Kvp及自动毫安管电流,确定NI值为10。B组患者采用GSI模式行三期增强扫描收集门脉期图像。回顾性自适应统计迭代重建(ASIR)70kev单能量图像,应用ASIR Review工具收集0到100%ASIR的CT值、噪声值,计算图像信号噪声比(SNR)。记录各组剂量报告中CT剂量容积指数(CTDI vol)及剂量长度乘积(DLP),并计算有效剂量(ED),采用图像质量主观评分对图像进行评价。结果:B组CT值、噪声值及SNR均高于A组(P0.05),B组CTDIvol、DLP和ED均显著低于A组(P0.05);随着ASIR升高,SNR升高,但是图像质量主观评分先升高后降低。当ASIR为50%时,图像质量最高,不同ASIR的CT值、噪声值之间的差异无统计学意义(P0.05)。结论:宝石能谱CT GSI扫描模式的效果明显优于螺旋扫描,同时在降低图像噪声的前提下选择50%ASIR,可保障图像质量。     

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.     

Ultra-low dose whole-body CT for attenuation correction in a dual tracer PET/CT protocol for multiple myeloma

PurposeTo investigate within phantoms the minimum CT dose allowed for accurate attenuation correction of PET data and to quantify the effective dose reduction when a CT for this purpose is incorporated in the clinical setting.MethodsThe NEMA image quality phantom was scanned within a large parallelepiped container. Twenty-one different CT images were acquired to correct attenuation of PET raw data. Radiation dose and image quality were evaluated.Thirty-one patients with proven multiple myeloma who underwent a dual tracer PET/CT scan were retrospectively reviewed. ¹⁸F-fluorodeoxyglucose PET/CT included a diagnostic whole-body low dose CT (WBLDCT: 120 kV-80mAs) and ¹¹C-Methionine PET/CT included a whole-body ultra-low dose CT (WBULDCT) for attenuation correction (100 kV-40mAs). Effective dose and image quality were analysed.ResultsOnly the two lowest radiation dose conditions (80 kV-20mAs and 80 kV-10mAs) produced artifacts in CT images that degraded corrected PET images. For all the other conditions (CTDI_vol ≥ 0.43 mGy), PET contrast recovery coefficients varied less than ± 1.2%.Patients received a median dose of 6.4 mSv from diagnostic CT and 2.1 mSv from the attenuation correction CT. Despite the worse image quality of this CT, 94.8% of bone lesions were identifiable.ConclusionPhantom experiments showed that an ultra-low dose CT can be implemented in PET/CT procedures without any noticeable degradation in the attenuation corrected PET scan. The replacement of the standard CT for this ultra-low dose CT in clinical PET/CT scans involves a significant radiation dose reduction.     

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.     

Evaluation of a Learning-based Deformable Registration Method on Abdominal CT Images

BackgroundReliable image comparisons, based on fast and accurate deformable registration methods, are recognized as key steps in the diagnosis and follow-up of cancer as well as for radiation therapy planning or surgery. In the particular case of abdominal images, the images to compare often differ widely from each other due to organ deformation, patient motion, movements of gastrointestinal tract or breathing. As a consequence, there is a need for registration methods that can cope with both local and global large and highly non-linear deformations.MethodDeformable registration of medical images traditionally relies on the iterative minimization of a cost function involving a large number of parameters. For complex deformations and large datasets, this process is computationally very demanding, leading to processing times that are incompatible with the clinical routine workflow. Moreover, the highly non-convex nature of these optimization problems leads to a high risk of convergence toward local minima. Recently, deep learning approaches using Convolutional Neural Networks (CNN) have led to major breakthroughs by providing computationally fast unsupervised methods for the registration of 2D and 3D images within seconds. Among all the proposed approaches, the VoxelMorph learning-based framework pioneered to learn in an unsupervised way the complex mapping, parameterized using a CNN, between every couple of 2D or 3D pairs of images and the corresponding deformation field by minimizing a standard intensity-based similarity metrics over the whole learning database. Voxelmorph has so far only been evaluated on brain images. The present study proposes to evaluate this method in the context of inter-subject registration of abdominal CT images, which present a greater challenge in terms of registration than brain images, due to greater anatomical variability and significant organ deformations.ResultsThe performances of VoxelMorph were compared with the current top-performing non-learning-based deformable registration method “Symmetric Normalization” (SyN), implemented in ANTs, on two representative databases: LiTS and 3D-IRCADb-01. Three different experiments were carried out on 2D or 3D data, the atlas-based or pairwise registration, using two different similarity metrics, namely (MSE and CC). Accuracy of the registration was measured by the Dice score, which quantifies the volume overlap for the selected anatomical region.All the three experiments exhibit that the two deformable registration methods significantly outperform the affine registration and that VoxelMorph accuracy is comparable or even better than the reference non-learning based registration method ANTs (SyN), with a drastically reduced computation time.ConclusionBy substituting a time consuming optimization problem, VoxelMorph has made an outstanding achievement in learning-based registration algorithm, where a registration function is trained and thus, able to perform deformable registration almost accurately on abdominal images, while reducing the computation time from minutes to seconds and from seconds to milliseconds in comparison to ANTs (SyN) on a CPU.     

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

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

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

PurposeTo investigate how various generations of iterative reconstruction (IR) algorithms impact low-contrast detectability (LCD) in abdominal computed tomography (CT) for different patient effective diameters, using a quantitative task-based approach.MethodsInvestigations were performed using an anthropomorphic abdominal phantom with two optional additional rings to simulate varying patient effective diameters (25, 30, and 35 cm), and containing multiple spherical targets (5, 6, and 8 mm in diameter) with a 20-HU contrast difference. The phantom was scanned using routine abdominal protocols (CTDI_vol, 5.9–16 mGy) on four CT systems from two manufacturers. Images were reconstructed using both filtered back-projection (FBP) and various IR algorithms: ASiR 50%, SAFIRE 3 (both statistical IRs), ASiR-V 50%, ADMIRE 3 (both partial model-based IRs), or Veo (full model-based IR). Section thickness/interval was 2/1 mm or 2.5/1.25 mm, except 0.625/0.625 mm for Veo. We assessed LCD using a channelized Hotelling observer with 10 dense differences of Gaussian channels, with the area under the receiver operating characteristic curve (AUC) as a figure of merit.ResultsFor the smallest phantom (25-cm diameter) and smallest lesion size (5-mm diameter), AUC for FBP and the various IR algorithms did not significantly differ for any of the tested CT systems. For the largest phantom (35-cm diameter), Veo yielded the highest AUC improvement (8.5%). Statistical and partial model-based IR algorithms did not significantly improve LCD.ConclusionIn abdominal CT, switching from FBP to IR algorithms offers limited possibilities for achieving significant dose reductions while ensuring a constant objective LCD.     

Evaluation of a cycle-generative adversarial network-based cone-beam CT to synthetic CT conversion algorithm for adaptive radiation therapy

PurposeImage-guided radiation therapy could benefit from implementing adaptive radiation therapy (ART) techniques. A cycle-generative adversarial network (cycle-GAN)-based cone-beam computed tomography (CBCT)-to-synthetic CT (sCT) conversion algorithm was evaluated regarding image quality, image segmentation and dosimetric accuracy for head and neck (H&N), thoracic and pelvic body regions.MethodsUsing a cycle-GAN, three body site-specific models were priorly trained with independent paired CT and CBCT datasets of a kV imaging system (XVI, Elekta). sCT were generated based on first-fraction CBCT for 15 patients of each body region. Mean errors (ME) and mean absolute errors (MAE) were analyzed for the sCT. On the sCT, manually delineated structures were compared to deformed structures from the planning CT (pCT) and evaluated with standard segmentation metrics. Treatment plans were recalculated on sCT. A comparison of clinically relevant dose-volume parameters (D₉₈, D₅₀ and D₂ of the target volume) and 3D-gamma (3%/3mm) analysis were performed.ResultsThe mean ME and MAE were 1.4, 29.6, 5.4 Hounsfield units (HU) and 77.2, 94.2, 41.8 HU for H&N, thoracic and pelvic region, respectively. Dice similarity coefficients varied between 66.7 ± 8.3% (seminal vesicles) and 94.9 ± 2.0% (lungs). Maximum mean surface distances were 6.3 mm (heart), followed by 3.5 mm (brainstem). The mean dosimetric differences of the target volumes did not exceed 1.7%. Mean 3D gamma pass rates greater than 97.8% were achieved in all cases.ConclusionsThe presented method generates sCT images with a quality close to pCT and yielded clinically acceptable dosimetric deviations. Thus, an important prerequisite towards clinical implementation of CBCT-based ART is fulfilled.