To compare image quality and radiation dose using Adaptive Statistical Iterative Reconstruction (ASiR) and Filtered Back Projection (FBP) in patients weighing ≥ 91 kg.
In this Institution Review Board-approved retrospective study, single-phase contrast-enhanced abdominopelvic CT examinations of 100 adults weighing ≥ 91 kg (mean body weight: 107.6 ± 17.4 kg range: 91-181.9 kg) with (1) ASiR and (2) FBP were reviewed by two readers in a blinded fashion for subjective measures of image quality (using a subjective standardized numerical scale and objective noise) and for radiation exposure. Imaging parameters and radiation dose results of the two techniques were compared within weight and BMI sub-categories.
All examinations were found to be of adequate quality. Both subjective (mean = 1.4 ± 0.5 vs. 1.6 ± 0.6, P < 0.05) and objective noise (13.0 ± 3.2 vs.19.5 ± 5.7, P < 0.0001) were lower with ASiR. Average radiation dose reduction of 31.5 % was achieved using ASiR (mean CTDIvol. ASiR: 13.5 ± 7.3 mGy; FBP: 19.7 ± 9.0 mGy, P < 0.0001). Other measures of image quality were comparable between the two techniques. Trends for all parameters were similar in patients across weight and BMI sub-categories.
In obese individuals, abdominal CT images reconstructed using ASiR provide diagnostic images with reduced image noise at lower radiation dose.
• CT images in obese adults are noisy, even with high radiation dose. • Newer iterative reconstruction techniques have theoretical advantages in obese patients. • Adaptive statistical iterative reconstruction should reduce image noise and radiation dose. • This has been proven in abdominopelvic CT images of obese patients.
"The conventional CT image reconstruction algorithm, FBP, reflects a trade-off between sharpness and image noise that limits the reduction of the radiation dose to maintain the diagnostic image quality.  ASIR is a newer image reconstruction algorithm that reduces image noise by applying iterations between the raw data and image space, generating images of higher quality and greater structural detail at lower radiation doses than FBP,  helping to improve image quality and reduce radiation dose., , , – Iterative reconstruction algorithms could effectively reduce radiation doses for chest CT: one study showed a 27% radiation dose reduction using 30% ASIR , and another reported that higher ASIR levels (100%) could reduce radiation doses even further (76%). "
[Show abstract][Hide abstract] ABSTRACT: To reduce radiation dose while maintaining image quality in low-dose chest computed tomography (CT) by combining adaptive statistical iterative reconstruction (ASIR) and automatic tube current modulation (ATCM).
Patients undergoing cancer screening (n = 200) were subjected to 64-slice multidetector chest CT scanning with ASIR and ATCM. Patients were divided into groups 1, 2, 3, and 4 (n = 50 each), with a noise index (NI) of 15, 20, 30, and 40, respectively. Each image set was reconstructed with 4 ASIR levels (0% ASIR, 30% ASIR, 50% ASIR, and 80% ASIR) in each group. Two radiologists assessed subjective image noise, image artifacts, and visibility of the anatomical structures. Objective image noise and signal-to-noise ratio (SNR) were measured, and effective dose (ED) was recorded.
Increased NI was associated with increased subjective and objective image noise results (P<0.001), and SNR decreased with increasing NI (P<0.001). These values improved with increased ASIR levels (P<0.001). Images from all 4 groups were clinically diagnosable. Images with NI = 30 and 50% ASIR had average subjective image noise scores and nearly average anatomical structure visibility scores, with a mean objective image noise of 23.42 HU. The EDs for groups 1, 2, 3 and 4 were 2.79±1.17, 1.69±0.59, 0.74±0.29, and 0.37±0.22 mSv, respectively. Compared to group 1 (NI = 15), the ED reductions were 39.43%, 73.48%, and 86.74% for groups 2, 3, and 4, respectively.
Using NI = 30 with 50% ASIR in the chest CT protocol, we obtained average or above-average image quality but a reduced ED.
PLoS ONE 04/2014; 9(4):e92414. DOI:10.1371/journal.pone.0092414 · 3.23 Impact Factor
"The overall image quality was graded using a 5-point scale in which a score of 5 indicated excellent; a score of 4, better than average; a score of 3, average; a score of 2, worse than average; and a score of 1, unacceptable diagnostic image quality (25). The image noise was graded according to the presence and amount of mottle or graininess in the images with use of a 5-point scale in which a score of 1 indicated unacceptable noise; a score of 2, above-average increased noise; a score of 3, average noise in an acceptable image; a score of 4, less than average noise; and a score of 5, minimum or no image noise. "
[Show abstract][Hide abstract] ABSTRACT: To evaluate the impact of the adaptive iterative dose reduction (AIDR) three-dimensional (3D) algorithm in CT on noise reduction and the image quality compared to the filtered back projection (FBP) algorithm and to compare the effectiveness of AIDR 3D on noise reduction according to the body habitus using phantoms with different sizes.
Three different-sized phantoms with diameters of 24 cm, 30 cm, and 40 cm were built up using the American College of Radiology CT accreditation phantom and layers of pork belly fat. Each phantom was scanned eight times using different mAs. Images were reconstructed using the FBP and three different strengths of the AIDR 3D. The image noise, the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) of the phantom were assessed. Two radiologists assessed the image quality of the 4 image sets in consensus. The effectiveness of AIDR 3D on noise reduction compared with FBP were also compared according to the phantom sizes.
Adaptive iterative dose reduction 3D significantly reduced the image noise compared with FBP and enhanced the SNR and CNR (p < 0.05) with improved image quality (p < 0.05). When a stronger reconstruction algorithm was used, greater increase of SNR and CNR as well as noise reduction was achieved (p < 0.05). The noise reduction effect of AIDR 3D was significantly greater in the 40-cm phantom than in the 24-cm or 30-cm phantoms (p < 0.05).
The AIDR 3D algorithm is effective to reduce the image noise as well as to improve the image-quality parameters compared by FBP algorithm, and its effectiveness may increase as the phantom size increases.
Korean journal of radiology: official journal of the Korean Radiological Society 03/2014; 15(2):195-204. DOI:10.3348/kjr.2014.15.2.195 · 1.57 Impact Factor
"In the past two years, several studies have examined the effects on patient dose and image noise of various iterative reconstruction methods. All showed significant reductions in radiation dose (up to 40% -50% in so me cases)  . A study which was analysed in the algorithm SAFIRE body scans (abdomen), showed a dose reduction by 50% wh ile preserving image quality. "
[Show abstract][Hide abstract] ABSTRACT: With this review article, we intend to demonstrate the importance of Computerized Tomography (CT) in healthcare quality and safety. The concept of safety in CT is wider than for general healthcare. Safe healthcare provided using CT must include diagnostic image quality and reliability, as this is the only way to ensure diagnostic accuracy. The images must be acquired with the most adequate protocols available and with the lowest achievable radiation dose. In this article we will focus primarily on the concepts of dose, since this variable strongly affects the image quality and the consequent diagnostic accuracy. In methodological terms, 73 papers and 6 catalogues issued by the manufacturers of CT equipment, that included the keywords low dose, ultra-low dose and dose reduction were analysed. After review of these articles we found that about 82% are chest exams, namely the lungs. The remaining were subdivided mainly by studies of the sinuses, heart and bone segments. After this review we selected the only 10 articles that present the keywords and simultaneously quantify the dose reduction. Given the lack of precision associated with these terms, introduced mainly by commercial catalogues of different equipment brands, we intend to demonstrate that the concepts low dose and ultra-low dose are wrapped in unclear marketing strategies, without a strict and unambiguous definition of what is the effective dose. We propose that these concepts should be clearly defined and a precise indication of the effective dose reduction value should be compared to the default value (standard diagnostic dose) by exam region. Therefore, it is demonstrated that there is no concrete definition of what low dose or ultra-low dose are. These slogans cannot be used until they are not holistically defined, as well as the correspondent dose reduction value.
Keywords: Dose, Low-Dose, Ultra-Low-Dose, Computed Tomography, Image Quality
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