Radiation Dose Reduction Potential Research Articles

Magnified x ray ghost imaging with tapered polycapillary optics free of the penumbra effect.

X ray ghost imaging (XGI) offers both radiation dose-reduction potential and cost-effective benefits owing to the utilization of a single-pixel detector. Most XGI schemes with laboratory x ray sources require a mechanically moving mask for either structured illumination or structured detection. In either configuration, however, its resolution remains limited by the source size and the unit size of the mask. Upon propagation, the details of the object can actually be magnified by the divergence of x rays, but at the same time, the penumbra effect produced by the finite source size is dramatically intensified, which ultimately leads to a degradation of image quality in XGI. To address these limitations, this work proposes a magnified XGI scheme using structured detection equipped with tapered polycapillary optics, which can efficiently suppress the object's penumbra as well as resolve the magnified details of the object. In general, the resolution of this scheme is no longer affected by the source size but by the microcapillary size of polycapillary. Our work fundamentally achieves cancellation of penumbra effect-induced aberration, thus paving the way for high-resolution magnified XGI.

Investigating the Small Pixel Effect in Ultra-High Resolution Photon-Counting CT of the Lung.

The aim of this study was to investigate potential benefits of ultra-high resolution (UHR) over standard resolution scan mode in ultra-low dose photon-counting detector CT (PCD-CT) of the lung. Six cadaveric specimens were examined with 5 dose settings using tin prefiltration, each in UHR (120 × 0.2 mm) and standard mode (144 × 0.4 mm), on a first-generation PCD-CT scanner. Image quality was evaluated quantitatively by noise comparisons in the trachea and both main bronchi. In addition, 16 readers (14 radiologists and 2 internal medicine physicians) independently completed a browser-based pairwise forced-choice comparison task for assessment of subjective image quality. The Kendall rank coefficient ( W ) was calculated to assess interrater agreement, and Pearson's correlation coefficient ( r ) was used to analyze the relationship between noise measurements and image quality rankings. Across all dose levels, image noise in UHR mode was lower than in standard mode for scan protocols matched by CTDI vol ( P < 0.001). UHR examinations exhibited noise levels comparable to the next higher dose setting in standard mode ( P ≥ 0.275). Subjective ranking of protocols based on 5760 pairwise tests showed high interrater agreement ( W = 0.99; P ≤ 0.001) with UHR images being preferred by readers in the majority of comparisons. Irrespective of scan mode, a substantial indirect correlation was observed between image noise and subjective image quality ranking ( r = -0.97; P ≤ 0.001). In PCD-CT of the lung, UHR scan mode reduces image noise considerably over standard resolution acquisition. Originating from the smaller detector element size in fan direction, the small pixel effect allows for superior image quality in ultra-low dose examinations with considerable potential for radiation dose reduction.

Radiation dose optimization for photon-counting CT coronary artery calcium scoring for different patient sizes: a dynamic phantom study

PurposeTo systematically assess the radiation dose reduction potential of coronary artery calcium (CAC) assessments with photon-counting computed tomography (PCCT) by changing the tube potential for different patient sizes with a dynamic phantom.MethodsA hollow artery, containing three calcifications of different densities, was translated at velocities corresponding to 0, < 60, 60–75, and > 75 beats per minute within an anthropomorphic phantom. Extension rings were used to simulate average- and large -sized patients. PCCT scans were made with the reference clinical protocol (tube potential of 120 kilovolt (kV)), and with 70, 90, Sn100, Sn140, and 140 kV at identical image quality levels. All acquisitions were reconstructed at a virtual monoenergetic energy level of 70 keV. For each calcification, Agatston scores and contrast-to-noise ratios (CNR) were determined, and compared to the reference with Wilcoxon signed-rank tests, with p < 0.05 indicating significant differences.ResultsA decrease in radiation dose (22%) was achieved at Sn100 kV for the average-sized phantom. For the large phantom, Sn100 and Sn140 kV resulted in a decrease in radiation doses of 19% and 3%, respectively. Irrespective of CAC density, Sn100 and 140 kVp did not result in significantly different CNR. Only at Sn100 kV were there no significant differences in Agatston scores for all CAC densities, heart rates, and phantom sizes.ConclusionPCCT at tube voltage of 100 kV with added tin filtration and reconstructed at 70 keV enables a ≥ 19% dose reduction compared to 120 kV, independent of phantom size, CAC density, and heart rate.Key Points• Photon-counting CT allows for reduced radiation dose acquisitions (up to 19%) for coronary calcium assessment by reducing tube voltage while reconstructing at a normal monoE level of 70 keV.• Tube voltage reduction is possible for medium and large patient sizes, without affecting the Agatston score outcome.

Detectability of Small Low-Attenuation Lesions With Deep Learning CT Image Reconstruction: A 24-Reader Phantom Study.

BACKGROUND. Iterative reconstruction (IR) techniques are susceptible to contrast-dependent spatial resolution, limiting overall radiation dose reduction potential. Deep learning image reconstruction (DLIR) may mitigate this limitation. OBJECTIVE. The purpose of our study was to evaluate low-contrast detectability performance and radiation-saving potential of a DLIR algorithm in comparison with filtered back projection (FBP) and IR using a human multireader noninferiority study design and task-based observer modeling. METHODS. A dual-phantom construct, consisting of a low-contrast detectability module (21 low-contrast hypoattenuating objects in seven sizes [2.4-10.0 mm] and three contrast levels [-15, -10, -5 HU] embedded within liver-equivalent background) and a phantom, was imaged at five radiation exposures (CTDIvol range, 1.4-14.0 mGy; size-specific dose estimate, 2.5-25.0 mGy; 90%-, 70%-, 50%-, and 30%-reduced radiation levels and full radiation level) using an MDCT scanner. Images were reconstructed using FBP, hybrid IR (ASiR-V), and DLIR (TrueFidelity). Twenty-four readers of varying experience levels evaluated images using a two-alternative forced choice. A task-based observer model (detectability index [d']) was calculated. Reader performance was estimated by calculating the AUC using a noninferiority method. RESULTS. Compared with FBP and IR methods at routine radiation levels, DLIR medium and DLIR high settings showed noninferior performance through a 90% radiation reduction (except DLIR medium setting at 70% reduced level). The IR method was non-inferior to routine radiation FBP only for 30% and 50% radiation reductions. No significant difference in d' was observed between routine radiation FBP and DLIR high setting through a 70% radiation reduction. Reader experience was not correlated with diagnostic accuracy (R2 = 0.005). CONCLUSION. Compared with FBP or IR methods at routine radiation levels, certain DLIR algorithm weightings yielded noninferior low-contrast detectability with radiation reductions of up to 90% as measured by 24 human readers and up to 70% as assessed by a task-based observer model. CLINICAL IMPACT. DLIR has substantial potential to preserve contrast-dependent spatial resolution for the detection of hypoattenuating lesions at decreased radiation levels in a phantom model, addressing a major shortcoming of current IR techniques.

Photon-Counting Detector CT With Quantum Iterative Reconstruction: Impact on Liver Lesion Detection and Radiation Dose Reduction.

To assess image noise, diagnostic performance, and potential for radiation dose reduction of photon-counting detector (PCD) computed tomography (CT) with quantum iterative reconstruction (QIR) in the detection of hypoattenuating and hyperattenuating focal liver lesions compared with energy-integrating detector (EID) CT. A medium-sized anthropomorphic abdominal phantom with liver parenchyma and lesions (diameter, 5-10 mm; hypoattenuating and hyperattenuating from -30 HU to +90 HU at 120 kVp) was used. The phantom was imaged on ( a ) a third-generation dual-source EID-CT (SOMATOM Force, Siemens Healthineers) in the dual-energy mode at 100 and 150 kVp with tin filtration and ( b ) a clinical dual-source PCD-CT at 120 kVp (NAEOTOM Alpha, Siemens). Scans were repeated 10 times for each of 3 different radiation doses of 5, 2.5, and 1.25 mGy. Datasets were reconstructed as virtual monoenergetic images (VMIs) at 60 keV for both scanners and as linear-blended images (LBIs) for EID-CT. For PCD-CT, VMIs were reconstructed with different strength levels of QIR (QIR 1-4) and without QIR (QIR-off). For EID-CT, VMIs and LBIs were reconstructed using advanced modeled iterative reconstruction at a strength level of 3. Noise power spectrum was measured to compare image noise magnitude and texture. A channelized Hotelling model observer was used to assess diagnostic accuracy for lesion detection. The potential for radiation dose reduction using PCD-CT was estimated for the QIR strength level with the highest area under the curve compared with EID-CT for each radiation dose. Image noise decreased with increasing QIR level at all radiation doses. Using QIR-4, noise reduction was 41%, 45%, and 59% compared with EID-CT VMIs and 12%, 18%, and 33% compared with EID-CT LBIs at 5, 2.5, and 1.25 mGy, respectively. The peak spatial frequency shifted slightly to lower frequencies at higher QIR levels. Lesion detection accuracy increased at higher QIR levels and was higher for PCD-CT compared with EID-CT VMIs. The improvement in detection with PCD-CT was strongest at the lowest radiation dose, with an area under the receiver operating curve of 0.917 for QIR-4 versus 0.677 for EID-CT VMIs for hyperattenuating lesions, and 0.900 for QIR-4 versus 0.726 for EID-CT VMIs for hypoattenuating lesions. Compared with EID-CT LBIs, detection was higher for QIR 1-4 at 2.5 mGy and for QIR 2-4 at 1.25 mGy (eg, 0.900 for QIR-4 compared with 0.854 for EID-CT LBIs at 1.25 mGy). Radiation dose reduction potential of PCD-CT with QIR-4 was 54% at 5 mGy compared with VMIs and 39% at 2.5 mGy compared with LBIs. Compared with EID-CT, PCD-CT with QIR substantially improved focal liver lesion detection, especially at low radiation dose. This enables substantial radiation dose reduction while maintaining diagnostic accuracy.

A Critical Survey on Developed Reconstruction Algorithms for Computed Tomography Imaging from a Limited Number of Projections

Rapid system and hardware development of X-ray computed tomography (CT) technologies has been accompanied by equally exciting advances in image reconstruction algorithms. Of the two reconstruction algorithms, analytical and iterative, iterative reconstruction (IR) algorithms have become a clinically viable option in CT imaging. The first CT scanners in the early 1970s used IR algorithms, but lack of computation power prevented their clinical use. In 2009, the first IR algorithms became commercially available and replaced conventionally established analytical algorithms as filtered back projection. Since then, IR has played a vital role in the field of radiology. Although all available IR algorithms share the common mechanism of artifact reduction and/or potential for radiation dose reduction, the magnitude of these effects depends upon specific IR algorithms. IR reconstructs images by iteratively optimizing an objective function. The objective function typically consists of a data integrity term and a regularization term. Therefore, different regularization priors are used in IR algorithms. This paper will briefly look at the overall evolution of CT image reconstruction and the regularization priors used in IR algorithms. Finally, a discussion is presented based on the reality of various reconstruction methodologies at a glance to find the preferred one. Consequently, we will present anticipation towards future advancements in this domain.

Impact of noise reduction on radiation dose reduction potential of virtual monochromatic spectral images: Comparison of phantom images with conventional 120 kVp images using deep learning image reconstruction and hybrid iterative reconstruction

PurposeTo assess the effects of deep learning image reconstruction (DLIR) and hybrid iterative reconstruction (HIR) on the image quality of virtual monochromatic spectral (VMS) images and to investigate the dose reduction potential of the VMS and conventional 120 kVp images. MethodsA cylindrical phantom simulating an adult abdomen was used. The contrast was set to 60 (medium) and 300 (high) Hounsfield units. CT acquisitions were performed at three dose levels: 12, 9, and 6 mGy. Images were reconstructed via filtered back projection (FBP), DLIR, and HIR. The noise power spectrum (NPS) and task transfer function (TTF) were measured, and the system performance (SP) function was calculated (TTF2/NPS). ResultsThe noise magnitudes at low spatial frequencies with DLIR and HIR were lower than that with FBP by 45.6% and 24.4%, respectively. Compared to the FBP results, the TTF values at 50% with DLIR at medium and high contrast changed by –13.2% and +25.3% with the VMS images and –2.0% and +9.3% with the 120 kVp images, respectively. In the VMS and 120 kVp images, compared to the SP values of 12 mGy FBP images, SP values of 6 mGy DLIR images decreased at medium contrast and increased at high contrast. ConclusionsDLIR achieved better noise reduction than HIR. The spatial resolution of VMS-DLIR varied significantly depending on the contrast. The image quality of VMS-DLIR and 120 kVp-DLIR potentially decrease in medium contrast tasks and increase in high contrast tasks with 50% dose reduction.

Low-contrast detectability and potential for radiation dose reduction using deep learning image reconstruction—A 20-reader study on a semi-anthropomorphic liver phantom

BackgroundA novel deep learning image reconstruction (DLIR) algorithm for CT has recently been clinically approved. PurposeTo assess low-contrast detectability and dose reduction potential for CT images reconstructed with the DLIR algorithm and compare with filtered back projection (FBP) and hybrid iterative reconstruction (IR). Material and methodsA customized upper-abdomen phantom containing four cylindrical liver inserts with low-contrast lesions was scanned at CT dose indexes of 5, 10, 15, 20 and 25 mGy. Images were reconstructed with FBP, 50% hybrid IR (IR50), and DLIR of low strength (DLL), medium strength (DLM) and high strength (DLH). Detectability was assessed by 20 independent readers using a two-alternative forced choice approach. Dose reduction potential was estimated separately for each strength of DLIR using a fitted model, with the detectability performance of FBP and IR50 as reference. ResultsFor the investigated dose levels of 5 and 10 mGy, DLM improved detectability compared to FBP by 5.8 and 6.9 percentage points (p.p.), and DLH improved detectability by 9.6 and 12.3 p.p., respectively (all p < .007). With IR50 as reference, DLH improved detectability by 5.2 and 9.8 p.p. for the 5 and 10 mGy dose level, respectively (p < .03). With respect to this low-contrast detectability task, average dose reduction potential relative to FBP was estimated to 39% for DLM and 55% for DLH. Relative to IR50, average dose reduction potential was estimated to 21% for DLM and 42% for DLH. Conclusions:Low-contrast detectability performance is improved when applying a DLIR algorithm, with potential for radiation dose reduction.

Image texture, low contrast liver lesion detectability and impact on dose: Deep learning algorithm compared to partial model-based iterative reconstruction

ObjectivesTo compare deep learning (True Fidelity, TF) and partial model based Iterative Reconstruction (ASiR-V) algorithm for image texture, low contrast lesion detectability and potential dose reduction. MethodsAnthropomorphic phantoms (mimicking non-overweight and overweight patient), containing lesions of 6 mm in diameter with 20HU contrast, were scanned at five different dose levels (2,6,10,15,20 mGy) on a CT system, using clinical routine protocols for liver lesion detection. Images were reconstructed using ASiR-V 0% (surrogate for FBP), 60 % and TF at low, medium and high strength. Noise texture was characterized by computing a normalized Noise Power Spectrum filtered by an eye filter. The similarity against FBP texture was evaluated using peak frequency difference (PFD) and root mean square deviation (RMSD). Low contrast detectability was assessed using a channelized Hotelling observer and the area under the ROC curve (AUC) was used as figure of merit. Potential dose reduction was calculated to obtain the same AUC for TF and ASiR-V. ResultsFBP-like noise texture was more preserved with TF (PFD from -0.043mm-1 to -0.09mm-1, RMSD from 0.12mm-1 to 0.21mm-1) than with ASiR-V (PFD equal to 0.12 mm-1, RMSD equal to 0.53mm-1), resulting in a sharper image. AUC was always higher with TF than ASIR-V. In average, TF compared to ASiR-V, enabled a radiation dose reduction potential of 7%, 25 % and 33 % for low, medium and high strength respectively. ConclusionCompared to ASIR-V, TF at high strength does not impact noise texture and maintains low contrast liver lesions detectability at significant lower dose.

Abstract No. 454 Photon counting C-arm computed tomography for thoracoabdominal interventional imaging: an in vivo porcine feasibility study

Prior studies on conventional CT demonstrate improved contrast resolution and radiation dose efficiency using direct conversion and energy-resolving photon counting detectors (PCD). The objective of this study was to determine the feasibility of using a prototype C-arm based PCD-CT system for thoracoabdominal interventional imaging and assess the potential benefits in comparison to flat panel detector-based cone-beam CT (FPD-CBCT). A 51 cm × 0.6 cm CdTe-based PCD strip with 100 μm pixel size was mounted to the front of the FPD of a Siemens Artis Zee interventional system. The PCD has a max frame rate of 150 fps and two adjustable energy thresholds for high-speed dual energy imaging. Eight-second rotational FPD-CBCT and PCD-CT acquisitions of the upper abdomen and lower thorax were performed in three female domestic swine (49.3 ± 2.5 kg). Acquisitions in one of the animals were performed after a stent graft was placed during a TIPS procedure. To assess radiation dose reduction potential, PCD-CT scans were performed at 25% (7.5 mGy) of the standard CTDIvol level (30 mGy) used by the conventional FPD-CBCT protocol. Images were assessed for artifacts, noise, contrast and spatial resolution. PCD-CT images had lower noise due to rejection of electronic noise by the PCD. This resulted in higher spatial and contrast resolution for PCD-CT, even at a lower radiation dose (25% of the FPD-CBCT). Blooming and streak artifacts from iodine accumulated in the kidney and bone were lower on the PCD images. Increased soft tissue contrast on the PCD images improved visualization of visceral detail, especially of bowel. Blooming and shading artifacts near the TIPS stent graft were suppressed in PCD-CT images. In this preliminary study, a prototype C-arm based PCD-CT system demonstrated potential benefits in image quality and radiation dose efficiency when compared to FDP-CBCT. Further investigation of C-arm PCD-CT is warranted in order to assess the potential for applying this technology in improving thoracoabdominal interventions.

Dose reduction for CT coronary calcium scoring with a calcium-aware image reconstruction technique: a phantom study

ObjectiveTo assess the dose reduction potential of a calcium-aware reconstruction technique, which aims at tube voltage-independent computed tomography (CT) numbers for calcium.Methods and materialsA cardiothoracic phantom, mimicking three different patient sizes, was scanned with two calcium inserts (named D100 and CCI), containing calcifications varying in size and density. Tube voltage was varied both manually (range 70–150 and Sn100 kVp) and automatically. Tube current was automatically adapted to maintain reference image quality defined at 120 kVp. Data was reconstructed with the standard reconstruction technique (kernel Qr36) and the calcium-aware reconstruction technique (kernel Sa36). We assessed the radiation dose reduction potential (volumetric CT dose index values (CTDIvol)), noise (standard deviation (SD)), mean CT number (HU) of each calcification, and Agatston scores for varying kVp. Results were compared with the reference acquired at 120 kVp and reconstructed with Qr36.ResultsAutomatic selection of the optimal tube voltage resulted in a CTDIvol reduction of 22%, 15%, and 12% compared with the reference for the small, medium, and large phantom, respectively. CT numbers differed up to 64% for the standard reconstruction and 11% for the calcium-aware reconstruction. Similarly, Agatston scores deviated up to 40% and 8% for the standard and calcium-aware reconstruction technique, respectively.ConclusionCT numbers remained consistent with comparable calcium scores when the calcium-aware image reconstruction technique was applied with varying tube voltage. Less consistency was observed in small calcifications with low density. Automatic reduction of tube voltage resulted in a dose reduction of up to 22%.Key Points• The calcium-aware image reconstruction technique allows for consistent CT numbers when varying the tube voltage.• Automatic reduction of tube voltage results in a reduced radiation exposure of up to 22%.• This study stresses the known limitations of the current Agatston score technique.

Low-kV coronary artery calcium scoring with tin filtration using a kV-independent reconstruction algorithm

PurposeTo investigate the accuracy of Agatston scoring and potential for radiation dose reduction of a coronary artery calcium scoring (CACS) CT protocol at 100 kV with tin filtration (Sn100kV) and kV-independent iterative reconstruction, compared to standard 120 kV acquisitions. Materials and methodsWith IRB approval and in HIPAA compliance, 114 patients (61.8 ± 9.6 years; 66 men) underwent CACS using a standard 120 kV protocol and an additional Sn100kV CACS scan. The two datasets were reconstructed using a medium sharp convolution algorithm and in addition the Sn100kV scans were reconstructed iteratively based on a kV-independent algorithm. Agatston scores and radiation dose values were compared between the Sn100kV and the standard 120 kV protocol. ResultsMedian Agatston scores derived from the Sn100kV protocol with the kV-independent algorithm and the standard 120 kV were 21.4 (IQR, 0–173.8) and 24.7 (IQR, 0–171.1) respectively, with no significant differences (p=0.18). Agatston scores derived from the two different protocols had an excellent correlation (r = 0.99). The dose-length-product was 11.5 ± 4.1 mGy × cm using Sn100kV and 50.4 ± 24.9 mGy × cm using the standard 120 kV protocol (p < 0.01), resulting in a significantly lower (77%) effective dose at Sn100kV (0.16 ± 0.06 mSv vs. 0.71 ± 0.35 mSv, p < 0.01). Additionally, 99% of the patients were classified into the same risk category (0, 1–10, 11–100, 101–400, or >400) using the Sn100kV protocol. ConclusionCACS at Sn100kV using the kV-independent iterative algorithm is feasible and provides high accuracy when compared to standard 120 kV scanning. Furthermore, radiation dose can be significantly reduced for this screening application in a priori healthy individuals.

Regularization Analysis and Design for Prior-Image-Based X-Ray CT Reconstruction.

Prior-image-based reconstruction (PIBR) methods have demonstrated great potential for radiation dose reduction in computed tomography applications. PIBR methods take advantage of shared anatomical information between sequential scans by incorporating a patient-specific prior image into the reconstruction objective function, often as a form of regularization. However, one major challenge with PIBR methods is how to optimally determine the prior image regularization strength which balances anatomical information from the prior image with data fitting to the current measurements. Too little prior information yields limited improvements over traditional model-based iterative reconstruction, while too much prior information can force anatomical features from the prior image not supported by the measurement data, concealing true anatomical changes. In this paper, we develop quantitative measures of the bias associated with PIBR. This bias exhibits as a fractional reconstructed contrast of the difference between the prior image and current anatomy, which is quite different from traditional reconstruction biases that are typically quantified in terms of spatial resolution or artifacts. We have derived an analytical relationship between the PIBR bias and prior image regularization strength and illustrated how this relationship can be used as a predictive tool to prospectively determine prior image regularization strength to admit specific kinds of anatomical change in the reconstruction. Because bias is dependent on local statistics, we further generalized shift-variant prior image penalties that permit uniform (shift invariant) admission of anatomical changes across the imaging field of view. We validated the mathematical framework in phantom studies and compared bias predictions with estimates based on brute force exhaustive evaluation using numerous iterative reconstructions across regularization values. The experimental results demonstrate that the proposed analytical approach can predict the bias-regularization relationship accurately, allowing for prospective determination of the prior image regularization strength in PIBR. Thus, the proposed approach provides an important tool for controlling image quality of PIBR methods in a reliable, robust, and efficient fashion.

A Third-Generation Adaptive Statistical Iterative Reconstruction Technique: Phantom Study of Image Noise, Spatial Resolution, Lesion Detectability, and Dose Reduction Potential.

The purpose of this study was to assess image noise, spatial resolution, lesion detectability, and the dose reduction potential of a proprietary third-generation adaptive statistical iterative reconstruction (ASIR-V) technique. A phantom representing five different body sizes (12-37 cm) and a contrast-detail phantom containing lesions of five low-contrast levels (5-20 HU) and three sizes (2-6 mm) were deployed. Both phantoms were scanned on a 256-MDCT scanner at six different radiation doses (1.25-10 mGy). Images were reconstructed with filtered back projection (FBP), ASIR-V with 50% blending with FBP (ASIR-V 50%), and ASIR-V without blending (ASIR-V 100%). In the first phantom, noise properties were assessed by noise power spectrum analysis. Spatial resolution properties were measured by use of task transfer functions for objects of different contrasts. Noise magnitude, noise texture, and resolution were compared between the three groups. In the second phantom, low-contrast detectability was assessed by nine human readers independently for each condition. The dose reduction potential of ASIR-V was estimated on the basis of a generalized linear statistical regression model. On average, image noise was reduced 37.3% with ASIR-V 50% and 71.5% with ASIR-V 100% compared with FBP. ASIR-V shifted the noise power spectrum toward lower frequencies compared with FBP. The spatial resolution of ASIR-V was equivalent or slightly superior to that of FBP, except for the low-contrast object, which had lower resolution. Lesion detection significantly increased with both ASIR-V levels (p = 0.001), with an estimated radiation dose reduction potential of 15% ± 5% (SD) for ASIR-V 50% and 31% ± 9% for ASIR-V 100%. ASIR-V reduced image noise and improved lesion detection compared with FBP and had potential for radiation dose reduction while preserving low-contrast detectability.

Advanced Modeled Iterative Reconstruction (ADMIRE) Facilitates Radiation Dose Reduction in Abdominal CT

This study aimed to determine the potential degree of radiation dose reduction achievable using Advanced Modeled Iterative Reconstruction (ADMIRE) in abdominal computed tomography (CT) while maintaining image quality. Moreover, this study compared differences in image noise reduction of this iterative algorithm with radiation dose reduction. Eleven consecutive patients scheduled for abdominal CT were scanned according to our institute's standard protocol (100 kV, 289 reference mAs). Using a proprietary reconstruction software, CT images of these patients were reconstructed as either full-dose weighted filtered back projections or with simulated radiation dose reductions down to 10% of the full-dose level and ADMIRE at either strength 3 or strength 5. Images were marked with arrows pointing on anatomic structures of the abdomen, differing in their contrast to the surrounding tissue. Structures were grouped into high-, medium-, and low-contrast subgroups. In addition, the intrinsic noise of these structures was measured. That followed, image pairs were presented to observers, with five readers assessing image quality using two-alternative-forced-choice comparisons. In total, 3000 comparisons were performed that way. Both ADMIRE 3 and 5 decreased noise of the anatomic structures significantly compared to the filtered back projection, with an additional significant difference between ADMIRE 3 and 5. Radiation dose reduction potential for ADMIRE ranged from 29.0% to 53.5%, with no significant differences between ADMIRE 3 and 5 within the contrast subgroups.The potential levels of radiation dose reduction for ADMIRE 3 differed significantly between high-, medium-, and low-contrast structures, whereas for ADMIRE 5, there was only a significant difference between the high- and the medium-contrast subgroups. Although ADMIRE 5 permits significantly higher noise reduction potential than ADMIRE 3, it does not facilitate higher levels of radiation dose reduction. ADMIRE nonetheless holds remarkable potential for radiation dose reduction, which features a certain dependency on the contrast of the structure of interest. Applying ADMIRE with a strength of 3 in abdominal CT may permit radiation dose reduction of about 30%.

Virtual single source CT using dual source acquisition: Clinical applicability in run-off CT-angiography for intra-individual comparison of different scan protocols

PurposeVirtual single source computed tomography (VSS-CT) acquisition on a dual source CT (DSCT) has been demonstrated to allow for dose-neutral intra-individual comparison of three acquisition protocols at different radiation dose levels (RDL) within one acquisition in a phantom. The purpose of this study was twofold: first to evaluate the applicability of VSS-CT in patients and second to optimize the task-dependent trade-off between radiation dose and image quality of lower extremity CT angiography (run-off CTA). Material and methodsIn this IRB-approved prospective study 52 patients underwent run-off CTA between 06/2012 and 06/2013. VSS-CT acquisition was conducted using a first generation DSCT applying equal X-ray tube settings (120 kVp), collimation (2 × 32 × 0.6 mm), and slice thickness (1.0 mm) but different effective tube current-time products (tube A: 80 mAs, tube B: 40 mAs). Three different image datasets representing three different radiation dose levels (RDL40, RDL80, RDL120) were reconstructed using a soft kernel from the raw data of tube B, tube A or both tubes combined. Dose length products (DLP) of each raw data set were documented. Quantitative image quality (IQ) was assessed for five anatomical levels using image noise and contrast-to-noise ratio (CNR). To investigate dose efficiency of each acquisition, the dose-weighted CNR (CNRD) was determined. Qualitative IQ was evaluated by two blinded readers in consensus using a 5-point Likert scale and compared with a Friedman- and posthoc Wilcoxon test. ResultsMean DLP was 200 ± 40, 400 ± 90 and 600 ± 130 mGy·cm for the RDL40, RDL80 and RDL120, respectively. Image noise and CNR were best for RDL120 and decreased significantly for RDL80 and RDL40, independent of the anatomic level (p < 0.001). CNRD showed no significant differences at the abdominal and pelvic level between the investigated radiation dose levels. However, for thigh to foot level a significant increase of CNRD was noted between RDL120, RDL80 and RDL40. Significant differences of qualitative IQ were observed between RDL120 and RDL40 from the abdominal to the foot level, whereas no difference was seen for the other dose levels. ConclusionRadiation dose splitting with VSS-CT can be applied to run-off CTA facilitating intra-individual comparison of different acquisition protocols without additional radiation exposure. Furthermore, a radiation dose reduction potential for run-off CTA of approximately 1/3 as compared to the acquisition protocol recommended by the manufacturer could be identified in this study.

Evaluation of a High Concentrated Contrast Media Injection Protocol in Combination with Low Tube Current for Dose Reduction in Coronary Computed Tomography Angiography: A Randomized, Two-center Prospective Study

The study aimed to prospectively evaluate the radiation dose reduction potential and image quality (IQ) of a high-concentration contrast media (HCCM) injection protocol in combination with a low tube current (mAs) in coronary computed tomography angiography. Eighty-one consecutive patients (mean age: 62 years; 34 females; body mass index: 18-31) were included and randomized-assigned into two groups. All computed tomography (CT) examinations were performed in two groups with the same tube voltage (100 kV), flow rate of contrast medium (5.0 mL/s), and iodine dose (22.8 g). An automatic mAs and low concentration contrast medium (300 mgI/mL) were used in group A, whereas effective mAs was reduced by a factor 0.6 along with HCCM (400 mgI/mL) in group B. Radiation dose was assessed (CT dose index [CTDIvol] and dose length product), and vessel-based objective IQ for various regions of interest (enhancement, noise, signal-to-noise ratio, and contrast-to-noise ratio), subjective IQ, noise, and motion artifacts were analyzed overall and vessel-based with a 5-point Likert scale. The CT attenuation of coronary arteries and image noise in group B were significantly higher than those in group A (ranges: 507.5-548.1 Hounsfield units vs 407.5-444.5 Hounsfield units; and 20.3 ± 8.6 vs 17.7 ± 8.0) (P ≤ 0.0166). There was no significant difference between the two groups in signal-to-noise ratio, contrast-to-noise ratio, and subjective IQ of coronary arteries (29.4-31.7, 30.0-37.0, and medium score of 5 in group A vs 29.4-32.4, 27.7-36.3, and medium score of 5 in group B, respectively, P ≥ 0.1859). Both mean CTDIvol and dose length product in group B were 58% of those of group A. HCCM combined with low tube current allows dose reduction in coronary computed tomography angiography and does not compromise IQ.

Image quality, diagnostic accuracy, and potential for radiation dose reduction in thoracoabdominal CT, using Sinogram Affirmed Iterative Reconstruction (SAFIRE) technique in a longitudinal study.

ObjectiveTo step-wise evaluate image quality of sinogram-affirmed iterative reconstruction (SAFIRE) in reduced-dose (RD) thoracoabdominal computed tomography (CT) compared to full-dose (FD) and RD filtered back projection (FBP) in a longitudinal study.Materials and methods122 patients were included in this prospective study. 49 patients (14 men: mean age ± SD, 56±0.4 years; 35 women: 58±1.3 years) completed FD, RD1 (80%-dose) and RD2 (60%-dose) thoracoabdominal CT. Each CT dataset was reconstructed with FBP and SAFIRE. For quantitative image analysis image noise was measured in defined tissue regions. Qualitative image evaluation was performed according to the European Guidelines on Quality criteria for CT. Additionally artifacts, lesion conspicuity, and edge sharpness were assessed.ResultsCompared to FD-FBP noise in soft tissue increased by 12% in RD1-FBP and 27% in RD2-FBP reconstructions, whereas SAFIRE lead to a decrease of 28% (RD1) and 17% (RD2), respectively (all p <0.001). Visually sharp reproduction, lesion conspicuity, edge sharpness of pathologic findings, and overall image quality did not differ statistically significant between FD-FBP and RD-SAFIRE datasets. Image quality decreased in RD1- and RD2-FBP compared to FD-FBP, reaching statistically significance in RD2 datasets (p <0.001). In RD1- and RD2-FBP (p <0.001) streak artifacts were noted.ConclusionUsing SAFIRE the reference mAs in thoracoabdominal CT can be reduced by at least 30% in clinical routine without loss of image quality or diagnostic information.

Effect of Radiation Dose Reduction and Reconstruction Algorithm on Image Noise, Contrast, Resolution, and Detectability of Subtle Hypoattenuating Liver Lesions at Multidetector CT: Filtered Back Projection versus a Commercial Model-based Iterative Reconstruction Algorithm.

Purpose To determine the effect of radiation dose and iterative reconstruction (IR) on noise, contrast, resolution, and observer-based detectability of subtle hypoattenuating liver lesions and to estimate the dose reduction potential of the IR algorithm in question. Materials and Methods This prospective, single-center, HIPAA-compliant study was approved by the institutional review board. A dual-source computed tomography (CT) system was used to reconstruct CT projection data from 21 patients into six radiation dose levels (12.5%, 25%, 37.5%, 50%, 75%, and 100%) on the basis of two CT acquisitions. A series of virtual liver lesions (five per patient, 105 total, lesion-to-liver prereconstruction contrast of -15 HU, 12-mm diameter) were inserted into the raw CT projection data and images were reconstructed with filtered back projection (FBP) (B31f kernel) and sinogram-affirmed IR (SAFIRE) (I31f-5 kernel). Image noise (pixel standard deviation), lesion contrast (after reconstruction), lesion boundary sharpness (average normalized gradient at lesion boundary), and contrast-to-noise ratio (CNR) were compared. Next, a two-alternative forced choice perception experiment was performed (16 readers [six radiologists, 10 medical physicists]). A linear mixed-effects statistical model was used to compare detection accuracy between FBP and SAFIRE and to estimate the radiation dose reduction potential of SAFIRE. Results Compared with FBP, SAFIRE reduced noise by a mean of 53% ± 5, lesion contrast by 12% ± 4, and lesion sharpness by 13% ± 10 but increased CNR by 89% ± 19. Detection accuracy was 2% higher on average with SAFIRE than with FBP (P = .03), which translated into an estimated radiation dose reduction potential (±95% confidence interval) of 16% ± 13. Conclusion SAFIRE increases detectability at a given radiation dose (approximately 2% increase in detection accuracy) and allows for imaging at reduced radiation dose (16% ± 13), while maintaining low-contrast detectability of subtle hypoattenuating focal liver lesions. This estimated dose reduction is somewhat smaller than that suggested by past studies. © RSNA, 2017 Online supplemental material is available for this article.

Radiation Dose Reduction in Pediatric Body CT Using Iterative Reconstruction and a Novel Image-Based Denoising Method.

The objective of this study was to evaluate the radiation dose reduction potential of a novel image-based denoising technique in pediatric abdominopelvic and chest CT examinations and compare it with a commercial iterative reconstruction method. Data were retrospectively collected from 50 (25 abdominopelvic and 25 chest) clinically indicated pediatric CT examinations. For each examination, a validated noise-insertion tool was used to simulate half-dose data, which were reconstructed using filtered back-projection (FBP) and sinogram-affirmed iterative reconstruction (SAFIRE) methods. A newly developed denoising technique, adaptive nonlocal means (aNLM), was also applied. For each of the 50 patients, three pediatric radiologists evaluated four datasets: full dose plus FBP, half dose plus FBP, half dose plus SAFIRE, and half dose plus aNLM. For each examination, the order of preference for the four datasets was ranked. The organ-specific diagnosis and diagnostic confidence for five primary organs were recorded. The mean (± SD) volume CT dose index for the full-dose scan was 5.3 ± 2.1 mGy for abdominopelvic examinations and 2.4 ± 1.1 mGy for chest examinations. For abdominopelvic examinations, there was no statistically significant difference between the half dose plus aNLM dataset and the full dose plus FBP dataset (3.6 ± 1.0 vs 3.6 ± 0.9, respectively; p = 0.52), and aNLM performed better than SAFIRE. For chest examinations, there was no statistically significant difference between the half dose plus SAFIRE and the full dose plus FBP (4.1 ± 0.6 vs 4.2 ± 0.6, respectively; p = 0.67), and SAFIRE performed better than aNLM. For all organs, there was more than 85% agreement in organ-specific diagnosis among the three half-dose configurations and the full dose plus FBP configuration. Although a novel image-based denoising technique performed better than a commercial iterative reconstruction method in pediatric abdominopelvic CT examinations, it performed worse in pediatric chest CT examinations. A 50% dose reduction can be achieved while maintaining diagnostic quality.