Radiation dose reduction in computed tomography: techniques and future perspective

Assessment of bilateral filter on 1/2-dose chest-pelvis CT views

A bilateral filter (BF) is a non-linear filter that has been proved to de-noise images without overrunning edges. Multi-slice computerized tomography (CT) may employ a BF to participate in dose reduction. This paper quantifies the role of the BF in achieving this objective on 1/2-dose CT. Two sets of CT images are acquired for the chest-pelvis at two different radiation doses. The BF was applied on the 1/2-dose CT images by use of various window sizes. Each time, a set of values of the BF range was fixed while the BF domain was modified. The goal was to observe the behavior of the BF on 1/2-dose CT images in comparison with full-dose CT images. The comparison was carried out by use of four co-occurrence matrix descriptors. Additionally, the peak signal-to-noise ratio (PSNR) and the mean square error (MSE) were reported. The study was applied to the sagittal, coronal, and axial CT views. The results showed that the impact of applying a BF varies among different CT views. The BF can retrieve only part of the signal being lost due to reduction of the radiation dose by one half. Yet, the BF improves the appearance of the 1/2-dose chest-pelvis CT examination. Thus, the BF can contribute to a 50% dose reduction. A procedure for employing the BF on CT machines is proposed. The results also showed that texture descriptors are similar to the PSNR and MSE in providing quantities for assessing medical image quality.

Greek dose reference levels in pediatric pelvis computed tomography examinations

The fact that children do undergo computed tomography (CT) examinations similar to those for adults adults has been a research issue, especially since the former are exposed to greater risk levels (developing stochastic late effects, such as cancer) due to their increased radiosensitivity compared to the latter. In a previous research paper (), the values of dose levels were recorded, analyzed, and compared with the reference values for groups of 0, 1, 5 and 10 y-old children for the regions of head, chest, and abdomen. In this paper, the same age group has been considered for measuring dose levels of the pelvic region. Scanning the pelvic region has been one of the most important CT examination procedures, in which unfortunately part of the lower abdomen region is included without adapting any pediatric protocols. Furthermore, the study determines whether the adjustment of the scanning parameters results in any possible reduction in the radiation dose levels to which the patient is being exposed during the examination. The present work also includes the Greek reference levels for the pelvic CT examination for the 5- and 10-y-old children that have been used for comparison against the European ones.

Quando a fase de equilíbrio pode ser suprimida nos exames de tomografia computadorizada de abdome?

OBJETIVO: Avaliar a necessidade de realização da fase de equilíbrio nos exames de tomografia computadorizada de abdome. MATERIAIS E MÉTODOS: Realizou-se estudo retrospectivo, transversal e observacional, avaliando 219 exames consecutivos de tomografia computadorizada de abdome com contraste intravenoso, realizados num período de três meses, com diversas indicações clínicas. Para cada exame foram emitidos dois pareceres, um avaliando o exame sem a fase de equilíbrio (primeira análise) e o outro avaliando todas as fases em conjunto (segunda análise). Ao final de cada avaliação, foi estabelecido se houve mudança nos diagnósticos principais e secundários, entre a primeira e a segunda análise. Foi utilizada a extensão do teste exato de Fisher para avaliar a modificação dos diagnósticos principais (p < 0,05 como significante). RESULTADOS: Entre os 219 casos avaliados, a supressão da fase de equilíbrio provocou alteração no diagnóstico principal em apenas um exame (0,46%; p > 0,999). Com relação aos diagnósticos secundários, cinco exames (2,3%) foram modificados. CONCLUSÃO: Para indicações clínicas como estadiamento tumoral, abdome agudo e pesquisa de coleção abdominal, a fase de equilíbrio não acrescenta contribuição diagnóstica expressiva, podendo ser suprimida dos protocolos de exame.

Improving spatial adaptivity of nonlocal means in low-dosed CT imaging using pointwise fractal dimension

NLMs is a state-of-art image denoising method; however, it sometimes oversmoothes anatomical features in low-dose CT (LDCT) imaging. In this paper, we propose a simple way to improve the spatial adaptivity (SA) of NLMs using pointwise fractal dimension (PWFD). Unlike existing fractal image dimensions that are computed on the whole images or blocks of images, the new PWFD, named pointwise box-counting dimension (PWBCD), is computed for each image pixel. PWBCD uses a fixed size local window centered at the considered image pixel to fit the different local structures of images. Then based on PWBCD, a new method that uses PWBCD to improve SA of NLMs directly is proposed. That is, PWBCD is combined with the weight of the difference between local comparison windows for NLMs. Smoothing results for test images and real sinograms show that PWBCD-NLMs with well-chosen parameters can preserve anatomical features better while suppressing the noises efficiently. In addition, PWBCD-NLMs also has better performance both in visual quality and peak signal to noise ratio (PSNR) than NLMs in LDCT imaging.

Validation of dual-source single-tube reconstruction as a method to obtain half-dose images to evaluate radiation dose and noise reduction: phantom and human assessment using CT colonography and sinogram-affirmed iterative reconstruction (SAFIRE)

OBJECTIVE

To evaluate a method for obtaining half-dose CT images for observer studies evaluating lower-dose CT.

METHODS

Phantoms of varying sizes were scanned at multiple tube potentials using dose-matched dual-source (DS) and single-source (SS) protocols. Images from single-tube reconstruction of DS data were compared with SS images acquired at half-original CTDIvol. Thirty patients underwent supine SS and dose-matched prone DS CT colonography (CTC). Half-dose prone images were reconstructed with sinogram-affirmed iterative reconstruction (SAFIRE). Two radiologists scored image quality on 2-dimensional (2D) and 3D images.

RESULTS

Image noise was similar between half-dose SS images and DS images reconstructed from one tube only with tube potential of 120 kV or more for phantoms 40 cm or smaller (P < 0.05). For both readers, the patients' CTC image quality scores were more than 84% concordant between SS or DS CTC images, and half-dose-prone CTC images with SAFIRE had 84% or more concordance with routine-dose CTC except for 3D image noise.

CONCLUSIONS

In appropriately sized patients, DS acquisition with single-tube reconstruction can create half-dose images, permitting comparison to full-dose images. For CTC, there is comparable image quality for colonic evaluation between full-dose and half-dose images reconstructed with SAFIRE.

Iterative image reconstruction for cerebral perfusion CT using a pre-contrast scan induced edge-preserving prior

Cerebral perfusion x-ray computed tomography (PCT) imaging, which detects and characterizes the ischemic penumbra, and assesses blood-brain barrier permeability with acute stroke or chronic cerebrovascular diseases, has been developed extensively over the past decades. However, due to its sequential scan protocol, the associated radiation dose has raised significant concerns to patients. Therefore, in this study we developed an iterative image reconstruction algorithm based on the maximum a posterior (MAP) principle to yield a clinically acceptable cerebral PCT image with lower milliampere-seconds (mA s). To preserve the edges of the reconstructed image, an edge-preserving prior was designed using a normal-dose pre-contrast unenhanced scan. For simplicity, the present algorithm was termed as 'MAP-ndiNLM'. Evaluations with the digital phantom and the simulated low-dose clinical brain PCT datasets clearly demonstrate that the MAP-ndiNLM method can achieve more significant gains than the existing FBP and MAP-Huber algorithms with better image noise reduction, low-contrast object detection and resolution preservation. More importantly, the MAP-ndiNLM method can yield more accurate kinetic enhanced details and diagnostic hemodynamic parameter maps than the MAP-Huber method.

Diagnosis of hepatocellular carcinoma: newer radiological tools

With the recent dramatic advances in diagnostic modalities, the diagnosis of hepatocellular carcinoma (HCC) is primarily based on imaging. Ultrasound (US) plays a crucial role in HCC surveillance. Dynamic multiphasic multidetector-row CT (MDCT) and magnetic resonance imaging (MRI) are the standard diagnostic methods for the noninvasive diagnosis of HCC, which can be made based on hemodynamic features (arterial enhancement and delayed washout). The technical development of MDCT and MRI has made possible the fast scanning with better image quality and resolution, which enables an accurate CT hemodynamic evaluation of hepatocellular tumor, as well as the application of perfusion CT and MRI in clinical practice. Perfusion CT and MRI can measure perfusion parameters of tumor quantitatively and can be used for treatment response assessment to anti-vascular agents. Besides assessing the hemodynamic or perfusion features of HCC, new advances in MRI can provide a cellular information of HCC. Liver-specific hepatobiliary contrast agents, such as gadoxetic acid, give information regarding hepatocellular function or defect of the lesion, which improves lesion detection and characterization. Diffusion-weighted imaging (DWI) of the liver provides cellular information of HCC and also has broadened its role in lesion detection, lesion characterization, and treatment response assessment to chemotherapeutic agents. In this article, we provide an overview of the state-of-the art imaging techniques of the liver and their clinical role in management of HCC.

Statistical image reconstruction from limited projection data with intensity priors

The radiation dose generated from x-ray computed tomography (CT) scans and its responsibility for increasing the risk of malignancy became a major concern in the medical imaging community. Accordingly, investigating possible approaches for image reconstruction from low-dose imaging protocols, which minimize the patient radiation exposure without affecting image quality, has become an issue of interest. Statistical reconstruction (SR) methods are known to achieve a superior image quality compared with conventional analytical methods. Effective physical noise modeling and possibilities of incorporating priors in the image reconstruction problem are the main advantages of the SR methods. Nevertheless, the high computation cost limits its wide use in clinical scanners. This paper presents a framework for SR in x-ray CT when the angular sampling rate of the projection data is low. The proposed framework is based on the fact that, in many CT imaging applications, some physical and anatomical structures and the corresponding attenuation information of the scanned object can be a priori known. Therefore, the x-ray attenuation distribution in some regions of the object can be expected prior to the reconstruction. Under this assumption, the proposed method is developed by incorporating this prior information into the image reconstruction objective function to suppress streak artifacts. We limit the prior information to only a set of intensity values that represent the average intensity of the normal and expected homogeneous regions within the scanned object. This prior information can be easily computed in several x-ray CT applications. Considering the theory of compressed sensing, the objective function is formulated using the ℓ(1) norm distance between the reconstructed image and the available intensity priors. Experimental comparative studies applied to simulated data and real data are used to evaluate the proposed method. The comparison indicates a significant improvement in image quality when the proposed method is used.

Practical interior tomography with radial Hilbert filtering and a priori knowledge in a small round area

PURPOSES

Interior tomography problem can be solved using the so-called differentiated backprojection-projection onto convex sets (DBP-POCS) method, which requires a priori knowledge within a small area interior to the region of interest (ROI) to be imaged. In theory, the small area wherein the a priori knowledge is required can be in any shape, but most of the existing implementations carry out the Hilbert filtering either horizontally or vertically, leading to a vertical or horizontal strip that may be across a large area in the object. In this work, we implement a practical DBP-POCS method with radial Hilbert filtering and thus the small area with the a priori knowledge can be roughly round (e.g., a sinus or ventricles among other anatomic cavities in human or animal body). We also conduct an experimental evaluation to verify the performance of this practical implementation.

METHODS

We specifically re-derive the reconstruction formula in the DBP-POCS fashion with radial Hilbert filtering to assure that only a small round area with the a priori knowledge be needed (namely radial DBP-POCS method henceforth). The performance of the practical DBP-POCS method with radial Hilbert filtering and a priori knowledge in a small round area is evaluated with projection data of the standard and modified Shepp-Logan phantoms simulated by computer, followed by a verification using real projection data acquired by a computed tomography (CT) scanner.

RESULTS

The preliminary performance study shows that, if a priori knowledge in a small round area is available, the radial DBP-POCS method can solve the interior tomography problem in a more practical way at high accuracy.

CONCLUSIONS

In comparison to the implementations of DBP-POCS method demanding the a priori knowledge in horizontal or vertical strip, the radial DBP-POCS method requires the a priori knowledge within a small round area only. Such a relaxed requirement on the availability of a priori knowledge can be readily met in practice, because a variety of small round areas (e.g., air-filled sinuses or fluid-filled ventricles among other anatomic cavities) exist in human or animal body. Therefore, the radial DBP-POCS method with a priori knowledge in a small round area is more feasible in clinical and preclinical practice.

Porcine ex vivo liver phantom for dynamic contrast-enhanced computed tomography: development and initial results

OBJECTIVES

: To demonstrate the feasibility of developing a fixed, dual-input, biologic liver phantom for dynamic contrast-enhanced computed tomography (CT) imaging and to report initial results of use of the phantom for quantitative CT perfusion imaging.

MATERIALS AND METHODS

: Porcine livers were obtained from completed surgical studies and perfused with saline and fixative. The phantom was placed in a body-shaped, CT-compatible acrylic container and connected to a perfusion circuit fitted with a contrast injection port. Flow-controlled contrast-enhanced imaging experiments were performed using 128-slice and 64-slice dual-source multidetector CT scanners. CT angiography protocols were used to obtain portal venous and hepatic arterial vascular enhancement, reproduced over a period of 4 to 6 months. CT perfusion protocols were used at different input flow rates to correlate input flow with calculated tissue perfusion, to test reproducibility, and to determine the feasibility of simultaneous dual-input liver perfusion. Histologic analysis of the liver phantom was also performed.

RESULTS

: CT angiogram 3-dimensional reconstructions demonstrated homogenous tertiary and quaternary branching of the portal venous system to the periphery of all lobes of the liver as well as enhancement of the hepatic arterial system to all lobes of the liver and gallbladder throughout the study period. For perfusion CT, the correlation between the calculated mean tissue perfusion in a volume of interest and input pump flow rate was excellent (R = 0.996) and color blood flow maps demonstrated variations in regional perfusion in a narrow range. Repeat perfusion CT experiments demonstrated reproducible time-attenuation curves, and dual-input perfusion CT experiments demonstrated that simultaneous dual input liver perfusion is feasible. Histologic analysis demonstrated that the hepatic microvasculature and architecture appeared intact and well preserved at the completion of 4 to 6 months of laboratory experiments and contrast-enhanced imaging.

CONCLUSIONS

: We have demonstrated successful development of a porcine liver phantom using a flow-controlled extracorporeal perfusion circuit. This phantom exhibited reproducible dynamic contrast-enhanced CT of the hepatic arterial and portal venous system over a 4- to 6-month period.

Low-dose computed tomography image restoration using previous normal-dose scan

PURPOSE

In current computed tomography (CT) examinations, the associated x-ray radiation dose is of a significant concern to patients and operators. A simple and cost-effective means to perform the examinations is to lower the milliampere-seconds (mAs) or kVp parameter (or delivering less x-ray energy to the body) as low as reasonably achievable in data acquisition. However, lowering the mAs parameter will unavoidably increase data noise and the noise would propagate into the CT image if no adequate noise control is applied during image reconstruction. Since a normal-dose high diagnostic CT image scanned previously may be available in some clinical applications, such as CT perfusion imaging and CT angiography (CTA), this paper presents an innovative way to utilize the normal-dose scan as a priori information to induce signal restoration of the current low-dose CT image series.

METHODS

Unlike conventional local operations on neighboring image voxels, nonlocal means (NLM) algorithm utilizes the redundancy of information across the whole image. This paper adapts the NLM to utilize the redundancy of information in the previous normal-dose scan and further exploits ways to optimize the nonlocal weights for low-dose image restoration in the NLM framework. The resulting algorithm is called the previous normal-dose scan induced nonlocal means (ndiNLM). Because of the optimized nature of nonlocal weights calculation, the ndiNLM algorithm does not depend heavily on image registration between the current low-dose and the previous normal-dose CT scans. Furthermore, the smoothing parameter involved in the ndiNLM algorithm can be adaptively estimated based on the image noise relationship between the current low-dose and the previous normal-dose scanning protocols.

RESULTS

Qualitative and quantitative evaluations were carried out on a physical phantom as well as clinical abdominal and brain perfusion CT scans in terms of accuracy and resolution properties. The gain by the use of the previous normal-dose scan via the presented ndiNLM algorithm is noticeable as compared to a similar approach without using the previous normal-dose scan.

CONCLUSIONS

For low-dose CT image restoration, the presented ndiNLM method is robust in preserving the spatial resolution and identifying the low-contrast structure. The authors can draw the conclusion that the presented ndiNLM algorithm may be useful for some clinical applications such as in perfusion imaging, radiotherapy, tumor surveillance, etc.

Radiation dose levels for interventional CT procedures

OBJECTIVE

The purpose of this study was to determine typical radiation dose levels to patients undergoing CT-guided interventional procedures.

MATERIALS AND METHODS

A total of 571 patients undergoing CT interventional procedures were included in this retrospective data analysis study. Enrolled patients underwent one of five procedures: cryoablation, aspiration, biopsy, drain, or injection. With each procedure, two scan modes were used, either intermittent (no table increment) or helical mode. Skin dose was estimated from the volumetric CT dose index (CTDI(vol)) and phantom measurements. Effective dose was calculated by multiplying dose-length product (DLP) and conversion factor (k factor) for helical mode, and using Monte Carlo organ dose coefficients for intermittent mode.

RESULTS

The mean (± SD) skin doses were 728 ± 382, 130 ± 104, 128 ± 81, 152 ± 105, and 195 ± 147 mGy, and the mean effective doses were 119.7 ± 50.3, 20.1 ± 11.0, 13.8 ± 9.2, 25.3 ± 15.4, and 9.1 ± 5.5 mSv for each of the five procedures, respectively. The maximum skin dose was 1.95 Gy. The mean effective dose across all procedure types was 24.1 mSv, with 2.3 mSv from intermittent scans and 21.8 mSv from helical scans.

CONCLUSION

Substantial dose differences were observed among the five procedures. The risk of deterministic effects appears to be very low, because the maximum observed skin dose did not exceed the threshold for transient skin erythema (2 Gy). The average risk of stochastic effects was comparable to that of 1-10 abdomen and pelvis CT examinations. Although the intermittent mode can contribute substantially to skin dose, it contributes minimally to the effective dose because of the much shorter scan range used.

Newer CT applications and their alternatives: what is appropriate in children?

Innovations in image acquisition and reconstruction technologies have greatly expanded the range of CT applications available in the routine clinical setting. CT images of sub-millimeter resolution can now be acquired of entire body regions in a few seconds or even sub-second time, allowing depiction of fine anatomical detail uncompromised by motion artifact. With sophisticated visualization software, image data can be processed into multiplanar, volume-rendered, cine and other formats to better display anatomical abnormalities and facilitate newer applications such as CT angiography, enterography, urography, tracheobronchography and cardiac CT. Newer applications including dual-energy material decomposition CT are furthering the transition of CT from a purely morphological to a combined anatomical, functional and metabolic imaging technique. These newer applications have largely been pioneered in adult populations, and heightened concern of the risk of carcinogenesis from ionizing radiation tempers dissemination of their use in children. Similar information can often be gleaned from alternative imaging modalities without ionizing radiation exposure, such as MRI and US, and what is most appropriate in children will depend on relative diagnostic efficacy, cost, availability and local expertise.

Nonconvex prior image constrained compressed sensing (NCPICCS): theory and simulations on perfusion CT

PURPOSE

To present and evaluate a new image reconstruction method for dynamic CT based on a nonconvex prior image constrained compressed sensing (NCPICCS) algorithm. The authors systematically compared the undersampling potential, functional information recovery, and solution convergence speed of four compressed sensing (CS) based image reconstruction methods using perfusion CT data: Standard l1-based CS, nonconvex CS (NCCS), and l1-based and nonconvex CS, including an additional constraint based on a prior image (PICCS and NCPICCS, respectively).

METHODS

The Shepp-Logan phantom was modified such that its uppermost ellipses changed attenuation through time, simulating both an arterial input function (AIF) and a homogeneous tissue perfusion region. Data were simulated with and without Poisson noise added to the projection data and subsequently reconstructed with all four CS-based methods at four levels of undersampling: 20, 12, 6, and 4 projections. Root mean squared (RMS) error of reconstructed images and recovered time attenuation curves (TACs) were assessed as well as convergence speed. The performance of both PICCS and NCPICCS methods were also evaluated using a kidney perfusion animal experiment data set.

RESULTS

All four CS-based methods were able to reconstruct the phantoms with 20 projections, with similar results on the RMS error of the recovered TACs. NCCS allowed accurate reconstructions with as few as 12 projections, PICCS with as few as six projections, and NCPICCS with as few as four projections. These results were consistent for noise-free and noisy data. NCPICCS required the fewest iterations to converge across all simulation conditions, followed by PICCS, NCCS, and then CS. On animal data, at the lowest level of undersampling tested (16 projections), the image quality of NCPICCS was better than PICCS with fewer streaking artifacts, while the TAC accuracy on the selected region of interest was comparable.

CONCLUSIONS

The authors have presented a novel method for image reconstruction using highly undersampled dynamic CT data. The NCPICCS method takes advantage of the information provided by a prior image, as in PICCS, but employs a more general nonconvex sparsity measure [such as the l(p)-norm (0 < p < or = 1)] rather than the conventional convex l1-norm. Despite the lack of guarantees of a globally optimal solution, the proposed nonconvex extension of PICCS consistently allowed for image reconstruction from fewer samples than the analogous l1-based PICCS method. Both nonconvex sparsity measures as well as prior image information (when available) significantly reduced the number of iterations required for convergence, potentially providing computational advantages for practical implementation of CS-based image reconstruction techniques.

Automatic selection of tube potential for radiation dose reduction in CT: a general strategy

PURPOSE

To optimize radiation dose efficiency in CT while maintaining image quality, it is important to select the optimal tube potential. The selection of optimal tube potential, however, is highly dependent on patient size and diagnostic task. The purpose of this work was to develop a general strategy that allows for automatic tube potential selection for each individual patient and each diagnostic task.

METHODS

The authors propose a general strategy that allows automatic adaptation of the tube potential as a function of patient size and diagnostic task, using a novel index of image quality, "iodine contrast to noise ratio with a noise constraint (iCNR_NC)," to characterize the different image quality requirements by various clinical applications. The relative dose factor (RDF) at each tube potential to achieve a target image quality was then determined as a function of patient size and the noise constraint parameter. A workflow was developed to automatically identify the optimal tube potential that is both dose efficient and practically feasible, incorporating patient size and diagnostic task. An experimental study using a series of semianthropomorphic thoracic phantoms was used to demonstrate how the proposed general strategy can be implemented and how the radiation dose reduction achievable by the tube potential selection depends on phantom sizes and noise constraint parameters.

RESULTS

The proposed strategy provides a flexible and quantitative way to select the optimal tube potential based on the patient size and diagnostic task. The noise constraint parameter alpha can be adapted for different clinical applications. For example, alpha = 1 for noncontrast routine exams; alpha = 1.1- 1.25 for contrast-enhanced routine exams; and alpha = 1.5-2.0 for CT angiography. For the five thoracic phantoms in the experiment, when alpha = 1, the optimal tube potentials were 80, 100, 100, 120, 120, respectively. The corresponding RDFs (relative to 120 kV) were 78.0%, 90.9%, 95.2%, 100%, and 100%. When alpha = 1.5, the optimal tube potentials were 80, 80, 80, 100, 100, respectively, with corresponding RDFs of 34.7%, 44.7%, 54.7%, 60.8%, and 89.5%.

CONCLUSIONS

A general strategy to automatically select the most dose efficient tube potential for CT exams was developed that takes into account patient size and diagnostic task. Dependent on the patient size and the selection of noise constraint parameter for different diagnostic tasks, the dose reduction at each tube potential, quantified explicitly with the RDF, varies significantly.