Iterative reconstruction improves image quality and reduces radiation dose in trauma protocols; A human cadaver study

Background Radiation-related cancer risk is an object of concern in CT of trauma patients, as these represent a young population. Different radiation reducing methods, including iterative reconstruction (IR), and spilt bolus techniques have been introduced in the recent years in different large scale trauma centers. Purpose To compare image quality in human cadaver exposed to thoracoabdominal computed tomography using IR and standard filtered back-projection (FBP) at different dose levels. Material and methods Ten cadavers were scanned at full dose and a dose reduction in CTDIvol of 5 mGy (low dose 1) and 7.5 mGy (low dose 2) on a Siemens Definition Flash 128-slice computed tomography scanner. Low dose images were reconstructed with FBP and Sinogram affirmed iterative reconstruction (SAFIRE) level 2 and 4. Quantitative image quality was analyzed by comparison of contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR). Qualitative image quality was evaluated by use of visual grading regression (VGR) by four radiologists. Results Readers preferred SAFIRE reconstructed images over FBP at a dose reduction of 40% (low dose 1) and 56% (low dose 2), with significant difference in overall impression of image quality. CNR and SNR showed significant improvement for images reconstructed with SAFIRE 2 and 4 compared to FBP at both low dose levels. Conclusions Iterative image reconstruction, SAFIRE 2 and 4, resulted in equal or improved image quality at a dose reduction of up to 56% compared to full dose FBP and may be used a strong radiation reduction tool in the young trauma population.

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Quantitative evaluation of deep convolutional neural network-based image denoising for low-dose computed tomography

Visual Computing for Industry Biomedicine and Art ◽

10.1186/s42492-021-00087-9 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Keisuke Usui ◽

Koichi Ogawa ◽

Masami Goto ◽

Yasuaki Sakano ◽

Shinsuke Kyougoku ◽

...

Keyword(s):

Computed Tomography ◽

Image Quality ◽

Dose Reduction ◽

Image Denoising ◽

Low Dose ◽

Radiation Risk ◽

Natural Image ◽

Denoising Method ◽

Low Dose Ct ◽

Dose Levels

AbstractTo minimize radiation risk, dose reduction is important in the diagnostic and therapeutic applications of computed tomography (CT). However, image noise degrades image quality owing to the reduced X-ray dose and a possible unacceptably reduced diagnostic performance. Deep learning approaches with convolutional neural networks (CNNs) have been proposed for natural image denoising; however, these approaches might introduce image blurring or loss of original gradients. The aim of this study was to compare the dose-dependent properties of a CNN-based denoising method for low-dose CT with those of other noise-reduction methods on unique CT noise-simulation images. To simulate a low-dose CT image, a Poisson noise distribution was introduced to normal-dose images while convoluting the CT unit-specific modulation transfer function. An abdominal CT of 100 images obtained from a public database was adopted, and simulated dose-reduction images were created from the original dose at equal 10-step dose-reduction intervals with a final dose of 1/100. These images were denoised using the denoising network structure of CNN (DnCNN) as the general CNN model and for transfer learning. To evaluate the image quality, image similarities determined by the structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) were calculated for the denoised images. Significantly better denoising, in terms of SSIM and PSNR, was achieved by the DnCNN than by other image denoising methods, especially at the ultra-low-dose levels used to generate the 10% and 5% dose-equivalent images. Moreover, the developed CNN model can eliminate noise and maintain image sharpness at these dose levels and improve SSIM by approximately 10% from that of the original method. In contrast, under small dose-reduction conditions, this model also led to excessive smoothing of the images. In quantitative evaluations, the CNN denoising method improved the low-dose CT and prevented over-smoothing by tailoring the CNN model.

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CT pulmonary angiography: dose reduction via a next generation iterative reconstruction algorithm

Acta Radiologica ◽

10.1177/0284185118784976 ◽

2018 ◽

Vol 60 (4) ◽

pp. 478-487 ◽

Cited By ~ 7

Author(s):

Andreas Sauter ◽

Thomas Koehler ◽

Bernhard Brendel ◽

Juliane Aichele ◽

Jan Neumann ◽

...

Keyword(s):

Image Quality ◽

Dose Reduction ◽

Iterative Reconstruction ◽

Low Dose ◽

Reconstruction Algorithm ◽

Pulmonary Angiography ◽

Reconstruction Algorithms ◽

Iterative Reconstruction Algorithm ◽

Dose Levels ◽

Rule Out

Background Computed tomography pulmonary angiography (CTPA) is the standard imaging modality for detection or rule out of pulmonary embolism (PE); however, radiation exposure is a serious concern. With iterative reconstruction algorithms a distinct dose reduction could be achievable. Purpose To evaluate a next generation iterative reconstruction algorithm for detection or rule-out of PE in simulated low-dose CTPA. Material and Methods Low-dose CT datasets with 50%, 25%, and 12.5% of the original tube current were simulated based on CTPA examinations of 92 patients with suspected PE. All datasets were reconstructed with two reconstruction algorithms: standard filtered back-projection (FBP) and iterative model reconstruction (IMR). In total, 736 CTPA datasets were evaluated by three blinded radiologists regarding image quality, diagnostic confidence, and detectability of PE. Furthermore, contrast-to-noise ratio (CNR) was calculated. Results Images reconstructed with IMR showed better detectability of PE than images reconstructed with FBP, especially at lower dose levels. With IMR, sensitivity was over 95% for central and segmental PE down to a dose level of 25%. Significantly higher subjective image quality was shown at lower dose levels (25% and 12.5%) for IMR images whereas it was higher for FBP images at higher dose levels. FBP was rated as showing less artificial image appearance. CNR was significantly higher with IMR at all dose levels. Conclusion By using IMR, a dose reduction of up to 50% while maintaining satisfactory image quality seems feasible in standard clinical situations, resulting in a mean effective dose of 1.38 mSv for CTPA.

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Ultra-Low-Dose CT of the Thorax Using Iterative Reconstruction: Evaluation of Image Quality and Radiation Dose Reduction

American Journal of Roentgenology ◽

10.2214/ajr.14.13629 ◽

2015 ◽

Vol 204 (6) ◽

pp. 1197-1202 ◽

Cited By ~ 61

Author(s):

Yookyung Kim ◽

Yoon Kyung Kim ◽

Bo Eun Lee ◽

Seok Jeong Lee ◽

Yon Ju Ryu ◽

...

Keyword(s):

Image Quality ◽

Radiation Dose ◽

Dose Reduction ◽

Iterative Reconstruction ◽

Low Dose ◽

Radiation Dose Reduction ◽

Low Dose Ct

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Low Dose Computed Tomography in Diagnosis of Ureteric Calculus in Obese Patients

Journal of Nobel Medical College ◽

10.3126/jonmc.v9i1.29464 ◽

2020 ◽

Vol 9 (1) ◽

pp. 27-31

Author(s):

Mahesh Gautam ◽

Aziz Ullah ◽

Manish Raj Pathak

Keyword(s):

Computed Tomography ◽

Image Quality ◽

Radiation Dose ◽

Iterative Reconstruction ◽

Low Dose ◽

Standard Dose ◽

Reconstruction Technique ◽

Obese Patients ◽

Low Dose Computed Tomography ◽

Effective Radiation

Background: Standard dose computed tomography is standard imaging modality in diagnosis of urolithiasis. The introduction of low dose techniques results in decrease radiation dose without significant change in image quality. However, the image quality of low dose computed tomography is affected by skin fold thickness and subcutaneous abdominal adipose tissue. The aim of this study to evaluate stone location, size, and density using low dose computed tomography compared with standard dose computed tomography in obese population. Material and Methods: This non-randomized non-inferiority trial includes 120 patient having BMI≥25kg/m2 with acute ureteric colic. The low dose and standard dose computed tomography were performed accordingly. Effective radiation doses were calculated from dose-length product obtained from scan report using conversion factor of 0.015. The images were reconstructed using iterative reconstruction algorithm. Effective dose, number and size of stone, Hounsfield Unit value of stone and image quality was assessed. Results: Stones were located in 69 (57.5%) in right and 51 (42.5%) in left ureter. There was no statistical difference in mean diameter, number and density of stones in low dose as compared with standard dose. The radiation dose was significantly lower with low dose. (3.68 mSv) The delineation of the ureter, outline of the stones and image quality in low dose was overall sufficient for diagnosis. No images of low dose scan were subjectively rated as non-diagnostics. Conclusion: Low dose computed tomography with iterative reconstruction technique is as effective as standard dose in diagnosis of ureteric stones in obese patients with lower effective radiation dose.

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Influence of a novel deep-learning based reconstruction software on the objective and subjective image quality in low-dose abdominal computed tomography

British Journal of Radiology ◽

10.1259/bjr.20200677 ◽

2021 ◽

Vol 94 (1117) ◽

pp. 20200677

Author(s):

Andrea Steuwe ◽

Marie Weber ◽

Oliver Thomas Bethge ◽

Christin Rademacher ◽

Matthias Boschheidgen ◽

...

Keyword(s):

Deep Learning ◽

Image Quality ◽

Dose Reduction ◽

Low Dose ◽

Ct Images ◽

Image Noise ◽

The Novel ◽

Subjective Image Quality ◽

Image Information ◽

Noise Ratio

Objectives: Modern reconstruction and post-processing software aims at reducing image noise in CT images, potentially allowing for a reduction of the employed radiation exposure. This study aimed at assessing the influence of a novel deep-learning based software on the subjective and objective image quality compared to two traditional methods [filtered back-projection (FBP), iterative reconstruction (IR)]. Methods: In this institutional review board-approved retrospective study, abdominal low-dose CT images of 27 patients (mean age 38 ± 12 years, volumetric CT dose index 2.9 ± 1.8 mGy) were reconstructed with IR, FBP and, furthermore, post-processed using a novel software. For the three reconstructions, qualitative and quantitative image quality was evaluated by means of CT numbers, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in six different ROIs. Additionally, the reconstructions were compared using SNR, peak SNR, root mean square error and mean absolute error to assess structural differences. Results: On average, CT numbers varied within 1 Hounsfield unit (HU) for the three assessed methods in the assessed ROIs. In soft tissue, image noise was up to 42% lower compared to FBP and up to 27% lower to IR when applying the novel software. Consequently, SNR and CNR were highest with the novel software. For both IR and the novel software, subjective image quality was equal but higher than the image quality of FBP-images. Conclusion: The assessed software reduces image noise while maintaining image information, even in comparison to IR, allowing for a potential dose reduction of approximately 20% in abdominal CT imaging. Advances in knowledge: The assessed software reduces image noise by up to 27% compared to IR and 48% compared to FBP while maintaining the image information. The reduced image noise allows for a potential dose reduction of approximately 20% in abdominal imaging.

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Phantom Study on Dose Reduction Using Iterative Reconstruction in Low-dose Computed Tomography for Lung Cancer Screening

Japanese Journal of Radiological Technology ◽

10.6009/jjrt.2015_jsrt_71.12.1201 ◽

2015 ◽

Vol 71 (12) ◽

pp. 1201-1208 ◽

Cited By ~ 3

Author(s):

Kaori Minehiro ◽

Tadanori Takata ◽

Hiroyuki Hayashi ◽

Keita Sakuda ◽

Haruka Nunome ◽

...

Keyword(s):

Computed Tomography ◽

Lung Cancer ◽

Cancer Screening ◽

Dose Reduction ◽

Iterative Reconstruction ◽

Low Dose ◽

Lung Cancer Screening ◽

Phantom Study ◽

Low Dose Computed Tomography

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An open label, prospective, multicenter, non-interventional study of iodixanol 270 mg I/mL for use in individuals undergoing computed tomography angiography in real-world clinical practice

Acta Radiologica ◽

10.1177/0284185118774917 ◽

2018 ◽

Vol 60 (2) ◽

pp. 177-185

Author(s):

Xiangying Du ◽

Bin Lu ◽

Daoyu Hu ◽

Bin Song ◽

Kuncheng Li

Keyword(s):

Computed Tomography ◽

Image Quality ◽

Radiation Dose ◽

Iterative Reconstruction ◽

Computed Tomography Angiography ◽

Pulmonary Arteries ◽

Open Label ◽

Tube Voltage ◽

Effective Radiation Dose ◽

Noise Ratio

Background Concern about radiation exposure is leading to an increasing interest in low-concentration contrast medium administration. Purpose To evaluate the image quality and safety profile after administration of iodixanol 270 mg I/mL at 100-kVp tube voltage with iterative reconstruction in subjects undergoing computed tomography angiography (CTA). Material and Methods Patients who completed CTA examination using iodixanol 270 mg I/mL and 100-kVp tube voltage along with iterative reconstruction for coronary, aortic, head and neck, renal, or pulmonary arteries were included. Image quality was qualitatively and quantitatively evaluated. Incidence of adverse events (AEs) and adverse drug reactions (ADRs) within seven days and radiation dose were also analyzed. Results A total of 4513 individuals in 42 centers in China were enrolled, among which 4367 were included in efficacy analysis. The mean image quality score was 4.8 ± 0.45 across all arteries (all above 4.6) and 99.7% of the individuals’ images were classified as evaluable. The CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in the regions of interest (ROIs) were 431.79 ± 99.018, 18.29 ± 11.947, and 28.21 ± 19.535 HU, respectively. Of all the participants, 68 (1.5%) and 65 (1.4%) experienced AEs and ADRs, respectively. No serious AEs or AEs leading to discontinuation occurred. The average effective radiation dose was 3.13 ± 2.550 mSv. Conclusion Iodixanol 270 mg I/mL in combination with 100-kVp tube voltage and iterative reconstruction could be safely applied in CTA and yield high-quality and evaluable images with reduced radiation dose.

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