Simulation of scanner- and patient-specific low-dose CT imaging from existing CT images

Naziroglu, Robiel E.; Ravesteijn, Vincent F. van; Vliet, Lucas J. van; Streekstra, Geert J.; Vos, Frans M.

doi:10.1016/j.ejmp.2017.02.009

Cited by 11 publications

(4 citation statements)

References 34 publications

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“…The major number of investigations are retrospective studies, where the amount of radiation exposure reduction cannot be generalized because of the missing ground truth. However, when comparing our study to the work of others, which used simulation tools (24)(25)(26), our results suffer from a 5-s delay between the two consecutive scans. As a result, we observe a difference in contrast due to the physiology in liver lesions.…”

Section: Discussionmentioning

confidence: 78%

Evaluation of an iterative model-based CT reconstruction algorithm by intra-patient comparison of standard and ultra-low-dose examinations

et al. 2018

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Background The explosive growth of computer tomography (CT) has led to a growing public health concern about patient and population radiation dose. A recently introduced technique for dose reduction, which can be combined with tube-current modulation, over-beam reduction, and organ-specific dose reduction, is iterative reconstruction (IR). Purpose To evaluate the quality, at different radiation dose levels, of three reconstruction algorithms for diagnostics of patients with proven liver metastases under tumor follow-up. Material and Methods A total of 40 thorax-abdomen-pelvis CT examinations acquired from 20 patients in a tumor follow-up were included. All patients were imaged using the standard-dose and a specific low-dose CT protocol. Reconstructed slices were generated by using three different reconstruction algorithms: a classical filtered back projection (FBP); a first-generation iterative noise-reduction algorithm (iDose4); and a next generation model-based IR algorithm (IMR). Results The overall detection of liver lesions tended to be higher with the IMR algorithm than with FBP or iDose4. The IMR dataset at standard dose yielded the highest overall detectability, while the low-dose FBP dataset showed the lowest detectability. For the low-dose protocols, a significantly improved detectability of the liver lesion can be reported compared to FBP or iDose ( P = 0.01). The radiation dose decreased by an approximate factor of 5 between the standard-dose and the low-dose protocol. Conclusion The latest generation of IR algorithms significantly improved the diagnostic image quality and provided virtually noise-free images for ultra-low-dose CT imaging.

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Section: Discussionmentioning

confidence: 78%

Evaluation of an iterative model-based CT reconstruction algorithm by intra-patient comparison of standard and ultra-low-dose examinations

et al. 2018

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“… 76 , 77 Thus various groups have proposed low-dose simulations using reconstructed CT images. The methods involve adding Gaussian 76 , 77 or a combination of Gaussian and Poisson noise 78 on the sinogram of the forward projection of the CT image. Although there has been limited validation of the appearance of lung nodules against simulated low dose simulation, 79 there has been no validation on the efficacy of these methods on the appearance of airways.…”

Section: Discussionmentioning

confidence: 99%

Reproducibility of an airway tapering measurement in computed tomography with application to bronchiectasis

et al. 2019

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Purpose: This paper proposes a pipeline to acquire a scalar tapering measurement from the carina to the most distal point of an individual airway visible on CT. We show the applicability of using tapering measurements on clinically acquired data by quantifying the reproducibility of the tapering measure. Methods: We generate a spline from the centreline of an airway to measure the area and arclength at contiguous intervals. The tapering measurement is the gradient of the linear regression between area in log space and arclength. The reproducibility of the measure was assessed by analysing different radiation doses, voxel sizes and reconstruction kernel on single timepoint and longitudinal CT scans and by evaluating the effct of airway bifurcations. Results: Using 74 airways from 10 CT scans, we show a statistical difference, p = 3.4 × 10 −4 in tapering between healthy airways (n = 35) and those affected by bronchiectasis (n = 39). The difference between the mean of the two populations was 0.011mm −1 and the difference between the medians of the two populations was 0.006mm −1 . The tapering measurement retained a 95% confidence interval of ±0.005mm −1 in a simulated 25 mAs scan and retained a 95% confidence of ±0.005mm −1 on simulated CTs up to 1.5 times the original voxel size. Conclusion: We have established an estimate of the precision of the tapering measurement and estimated the effect on precision of simulated voxel size and CT scan dose. We recommend that the scanner calibration be undertaken with the phantoms as described, on the specific CT scanner, radiation dose and reconstruction algorithm that is to be used in any quantitative studies.Our code is available at https://github.com/quan14/AirwayTaperingInCT

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“…However, nonlocal noise properties in reconstructed CT images (Massoumzadeh et al 2009) make it very difficult to simulate noise directly in the image domain. In the absence of raw projection data, an alternative way can be to generate a virtual sinogram from a high-dose CT image (Naziroglu et al 2017, Takenaga et al 2016 and model dose reduction in the sinogram domain.…”

Section: Introductionmentioning

confidence: 99%

Low-dose x-ray CT simulation from an available higher-dose scan

Elhamiasl¹

2020

Phys. Med. Biol.

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In CT-imaging an optimal compromise between the radiation burden and the image quality for the imaging task is needed. Lower-dose CT is desirable, however, lowering the dose results in a lower signal-to-noise ratio and therefore in a reduced image quality. In this research, we aim to develop a tool to simulate lower-dose scans from an existing standard-dose scan. The main application of this tool is to determine the lowest possible radiation dose that still produces sufficient clinical information. The X-ray tube current reduction is modeled by estimating the noise equivalent number of photons in the high exposure scan and applying a thinning technique to reduce that number. The proposed method accounts for the bowtie filter, for the electronic system noise, for the noise correlation between neighboring detector elements, for the beam hardening effect, and for the non-linear smoothing filter in very low dose scans. Several phantom studies with different acquisition protocols were performed to evaluate the accuracy of the proposed framework. The results demonstrate a close agreement between the noise magnitude and texture of the measured and the simulated lowerdose scans. For instance, the standard deviation of noise in the simulation of lowerdose scans with 90% tube current reduction matches the reconstructions from the real scans with less than 1% and 3% error for sequential and helical scans, respectively. The noise texture was also assessed by analyzing the noise power spectrum of the simulated lower-dose images which matches those from the real scans. Furthermore, the relation between the measured and predicted noise in projection domain is very close to the line of identity which confirms the accuracy of the model.

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Simulation of scanner- and patient-specific low-dose CT imaging from existing CT images

Cited by 11 publications

References 34 publications

Evaluation of an iterative model-based CT reconstruction algorithm by intra-patient comparison of standard and ultra-low-dose examinations

Evaluation of an iterative model-based CT reconstruction algorithm by intra-patient comparison of standard and ultra-low-dose examinations

Reproducibility of an airway tapering measurement in computed tomography with application to bronchiectasis

Low-dose x-ray CT simulation from an available higher-dose scan

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