Initial Performance Characterization of a Clinical Noise–Suppressing Reconstruction Algorithm for MDCT

A Novel Artificial Intelligence Based Denoising Method for Ultra-Low Dose CT Used for Lung Cancer Screening

RATIONALE AND OBJECTIVES

To assess ultra-low-dose (ULD) computed tomography as well as a novel artificial intelligence-based reconstruction denoising method for ULD (dULD) in screening for lung cancer.

MATERIALS AND METHODS

This prospective study included 123 patients, 84 (70.6%) men, mean age 62.6 ± 5.35 (55-75), who had a low dose and an ULD scan. A fully convolutional-network, trained using a unique perceptual loss was used for denoising. The network used for the extraction of the perceptual features was trained in an unsupervised manner on the data itself by denoising stacked auto-encoders. The perceptual features were a combination of feature maps taken from different layers of the network, instead of using a single layer for training. Two readers independently reviewed all sets of images.

RESULTS

ULD decreased average radiation-dose by 76% (48%-85%). When comparing negative and actionable Lung-RADS categories, there was no difference between dULD and LD (p = 0.22 RE, p > 0.999 RR) nor between ULD and LD scans (p = 0.75 RE, p > 0.999 RR). ULD negative likelihood ratio (LR) for the readers was 0.033-0.097. dULD performed better with a negative LR of 0.021-0.051. Coronary artery calcifications (CAC) were documented on the dULD scan in 88(74%) and 81(68%) patients, and on the ULD in 74(62.2%) and 77(64.7%) patients. The dULD demonstrated high sensitivity, 93.9%-97.6%, with an accuracy of 91.7%. An almost perfect agreement between readers was noted for CAC scores: for LD (ICC = 0.924), dULD (ICC = 0.903), and for ULD (ICC = 0.817) scans.

CONCLUSION

A novel AI-based denoising method allows a substantial decrease in radiation dose, without misinterpretation of actionable pulmonary nodules or life-threatening findings such as aortic aneurysms.

Iterative Reconstruction: State-of-the-Art and Future Perspectives

ABSTRACT

Image reconstruction processing in computed tomography (CT) has evolved tremendously since its creation, succeeding at optimizing radiation dose while maintaining adequate image quality. Computed tomography vendors have developed and implemented various technical advances, such as automatic noise reduction filters, automatic exposure control, and refined imaging reconstruction algorithms.Focusing on imaging reconstruction, filtered back-projection has represented the standard reconstruction algorithm for over 3 decades, obtaining adequate image quality at standard radiation dose exposures. To overcome filtered back-projection reconstruction flaws in low-dose CT data sets, advanced iterative reconstruction algorithms consisting of either backward projection or both backward and forward projections have been developed, with the goal to enable low-dose CT acquisitions with high image quality. Iterative reconstruction techniques play a key role in routine workflow implementation (eg, screening protocols, vascular and pediatric applications), in quantitative CT imaging applications, and in dose exposure limitation in oncologic patients.Therefore, this review aims to provide an overview of the technical principles and the main clinical application of iterative reconstruction algorithms, focusing on the strengths and weaknesses, in addition to integrating future perspectives in the new era of artificial intelligence.

Comparison of Knowledge-based Iterative Model Reconstruction (IMR) with Hybrid Iterative Reconstruction (iDose4) Techniques for Evaluation of Hepatocellular Carcinomas Using Computed Tomography

RATIONALE AND OBJECTIVES

To compare tumor conspicuity of small hepatocellular carcinomas (HCCs) and image quality on knowledge-based iterative model reconstruction low-dose computed tomography (IMR-LDCT) with hybrid iterative reconstruction standard-dose CT (iDose⁴-SDCT).

METHODS

Thirty-two patients (mean age 61.9 ± 9.7 years; male:female 27:5; mean body mass index 25.6 ± 3.8 kg/m²) with cirrhosis and 40 HCCs in IMR-LDCT group and 33 patients (mean age 60.1 ± 7.4 years; male:female 28:5; body mass index 26.7 ± 3.2 kg/m²) with cirrhosis and 40 HCCs in iDose⁴-SDCT group were included in this retrospective study. Objective analysis of reconstructed iDose⁴ and IMR images was done for contrast-to-noise ratio of HCCs (CNR_HCC), image noise, signal-to-noise ratio of portal vein (SNR_PV)_, and inferior vena cava (SNR_IVC). Subjective analysis of tumor conspicuity and image quality was done by two independent reviewers in a blinded manner. Mean volume CT dose index, dose length product, and effective dose for both groups were compared.

RESULTS

The CNR_HCC was significantly higher in IMR-LDCT compared to iDose⁴-SDCT in both arterial phase (AP), p < 0.0001, and delayed phase (DP), p < 0.0001. Image noise was significantly lower in IMR-LDCT compared to iDose⁴-SDCT in AP, portal venous phase, and DP with p < 0.0001. IMR-LDCT showed significantly higher SNR_PV (p < 0.0001) and SNR_IVC (p < 0.0001) compared to iDose⁴-SDCT. On subjective analysis, IMR-LDCT images showed better image quality in AP, portal venous phase, and DP and better tumor conspicuity in AP and DP. IMR-LDCT (21.4 ± 4.6 mSv) achieved 36.9% reduction in the effective dose compared to iDose⁴-SDCT (33.9 ± 6.2 mSv).

CONCLUSION

IMR algorithm provides better image quality and tumor conspicuity with considerable decrease in image noise compared to iDose⁴ reconstruction technique even on LDCT.

Association of Lesion Pattern and Dysphagia in Acute Intracerebral Hemorrhage

[Figure: see text].

Association of Low-Dose Whole-Body Computed Tomography With Missed Injury Diagnoses and Radiation Exposure in Patients With Blunt Multiple Trauma

Question

Is low-dose whole-body computed tomography with statistical image reconstruction associated with similar rates of missed injuries and accuracy but reduced radiation exposure compared with standard-dose whole-body computed tomography in the primary diagnostic workup of blunt multiple trauma?

Findings

In this quasi-experimental cohort study of 971 patients with suspected blunt multiple trauma, participants in the standard-dose and low-dose whole-body computed tomography groups had the same risk of missed injury diagnoses. Low-dose scanning markedly reduced exposure to radiation, improved the contrast-to-noise ratio, and showed similar diagnostic accuracy among the investigated anatomical areas and organs when compared with standard-dose scanning.

Meaning

These findings suggest that low-dose whole-body computed tomography may safely replace standard-dose scanning in the primary diagnostic workup of blunt multiple trauma.

Importance

Initial whole-body computed tomography (WBCT) for screening patients with suspected blunt multiple trauma remains controversial and a source of excess radiation exposure.

Objective

To determine whether low-dose WBCT scanning using an iterative reconstruction algorithm does not increase the rate of missed injury diagnoses at the point of care compared with standard-dose WBCT with the benefit of less radiation exposure.

Design, Setting, and Participants

This quasi-experimental, prospective time-series cohort study recruited 1074 consecutive patients admitted for suspected blunt multiple trauma to an academic metropolitan trauma center in Germany from September 3, 2014, through July 26, 2015, for the standard-dose protocol, and from August 7, 2015, through August 20, 2016, for the low-dose protocol. Five hundred sixty-five patients with suspected blunt multiple trauma prospectively received standard-dose WBCT, followed by 509 patients who underwent low-dose WBCT. Confounding was controlled by segmented regression analysis and a secondary multivariate logistic regression model. Data were analyzed from January 16, 2017, through October 14, 2019.

Interventions

Standard- or low-dose WBCT.

Main Outcomes and Measures

The primary outcome was the incidence of missed injury diagnoses at the point of care, using a synopsis of clinical, surgical, and radiological findings as an independent reference test. The secondary outcome was radiation exposure with either imaging strategy.

Results

Of 1074 eligible patients, 971 (mean [SD] age, 52.7 [19.5] years; 649 men [66.8%]) completed the study. A total of 114 patients (11.7%) had multiple trauma, as defined by an Injury Severity Score of 16 or greater. The proportion of patients with any missed injury diagnosis at the point of care was 109 of 468 (23.3%) in the standard-dose and 107 of 503 (21.3%) in the low-dose WBCT groups (risk difference, −2.0% [95% CI, −7.3% to 3.2%]; unadjusted odds ratio, 0.89 [95% CI, 0.66-1.20]; P = .45). Adjustments for autocorrelation and multiple confounding variables did not alter the results. Radiation exposure, measured by the volume computed tomography dose index, was lowered from a median of 11.7 (interquartile range, 11.7-17.6) mGy in the standard-dose WBCT group to 5.9 (interquartile range, 5.9-8.8) mGy in the low-dose WBCT group (P < .001).

Conclusions and Relevance

Low-dose WBCT using iterative image reconstruction does not appear to increase the risk of missed injury diagnoses at the point of care compared with standard-dose protocols while almost halving the exposure to diagnostic radiation.

Technical background of a novel detector-based approach to dual-energy computed tomography

Dual-energy information in computed tomography can be obtained through different technical approaches. Most available scanner designs acquire examination with two different X-ray spectra. Recently, the first detector-based approach became clinically available. Upfront, physical principles of dual-energy CT are reviewed, including the interaction of photons with matter in terms of the Photoelectric effect and Compton scattering. In addition, available concepts to dual energy computed tomography are described. Afterwards, the spectral detector CT system is described in detail. The design of the of the stacked detector design and its inherent technical advantages and disadvantages are discussed. Further, the principles of image reconstruction, their possibilities and limitations are referred. The increase in reconstructions and data pose some challenges to both, clinical and technological workflow which are hereafter addressed. Finally, the detector-based approach is discussed in light of other, emission-based DECT approaches.

Technological developments of X-ray computed tomography over half a century: User's influence on protocol optimization

Since the introduction of Computed Tomography (CT), technological improvements have been impressive. At the same time, the number of adjustable acquisition and reconstruction parameters has increased substantially. Overall, these developments led to improved image quality at a reduced radiation dose. However, many parameters are interrelated and part of automated algorithms. This makes it more complicated to adjust them individually and more difficult to comprehend their influence on CT protocol adjustments. Moreover, the user's influence in adapting protocol parameters is sometimes limited by the manufacturer's policy or the user's knowledge. As a consequence, optimization can be a challenge. A literature search in Embase, Medline, Cochrane, and Web of Science was performed. The literature was reviewed with the objective to collect information regarding technological developments in CT over the past five decades and the role of the associated acquisition and reconstruction parameters in the optimization process.

Spatial Distribution of Noise Reduction in Four Iterative Reconstruction Algorithms in CT—A Technical Evaluation

Iterative reconstruction (IR) is a computed tomgraphy (CT) reconstruction algorithm aiming at improving image quality by reducing noise in the image. During this process, IR also changes the noise properties in the images. To assess how IR algorithms from four vendors affect the noise properties in CT images, an anthropomorphic phantom was scanned and images reconstructed with filtered back projection (FBP), and a medium and high level of IR. Each image acquisition was performed 30 times at the same slice position, to create noise maps showing the inter-image pixel standard deviation through the 30 images. We observed that IR changed the noise properties in the CT images by reducing noise more in homogeneous areas than at anatomical edges between structures of different densities. This difference increased with increasing IR level, and with increasing difference in density between two adjacent structures. Each vendor’s IR algorithm showed slightly different noise reduction properties in how much noise was reduced at different positions in the phantom. Users need to be aware of these differences when working with optimization of protocols using IR across scanners from different vendors.

Feasibility of extremely reduced-dose CT of the thoracic spine in human cadavers

BACKGROUND

According to the as low as reasonably achievable (ALARA) principle, radiation exposure in computed tomography (CT) should be minimized while maintaining adequate image quality. Dedicated CT protocols combined with iterative reconstruction (IR) can reduce radiation dose and/or improve image quality.

PURPOSE

To investigate the feasibility of extremely reduced-dose (RD) CT of the thoracic spine in human cadavers using a standard-dose (SD) and three different RDCT protocols reconstructed with filtered back projection (FBP) and IR.

MATERIAL AND METHODS

The thoracic spines of 11 cadavers were examined using different RDCT protocols with decreasing reference tube currents (RDCT-1: 50 mAs; RDCT-2: 30 mAs; RDCT-3: 10 mAs) at 140 kV. A clinical SDCT (70 mAs, 140 kV) served as reference. Raw data were reconstructed using FBP and two increasing levels of IR (IRL4 and IRL6). Images were evaluated for image quality, diagnostic acceptability, and visibility of anatomical structures according to a 5-point-scale.

RESULTS

Regardless of the reconstruction technique, image quality was rated as diagnostically acceptable for all cadavers in SDCT and RDCT-1. Image quality of reconstructions with FBP were generally rated lower. Application of IR improved image quality ratings in SDCT and RDCT. RDCT-2 with IR was the most reduced-dose CT protocol which enabled diagnostically acceptable image quality in all cadavers. Compared to SDCT, RDCT protocols resulted in significantly reduced effective radiation doses (SDCT: 4.1 ± 1.5 mSv; RDCT-1: 2.9 ± 1.1 mSv; 2:1.7 ± 0.6 mSv; 3:0.6 ± 0.1 mSv; P = 0.001).

CONCLUSION

Diagnostically acceptable RDCT of the thoracic spine with 1.7 mSv is feasible using IR.

Cardiac computed tomography angiography in the paediatric population: Expert consensus from the Filiale de cardiologie pédiatrique et congénitale (FCPC) and the Société française d'imagerie cardiaque et vasculaire diagnostique et interventionnelle (SFICV)

This paper aims to provide a paediatric cardiac computed tomography angiography expert panel consensus based on the opinions of experts from the Société française d'imagerie cardiaque et vasculaire diagnostique et interventionnelle (SFICV) and the Filiale de cardiologie pédiatrique congénitale (FCPC). This expert panel consensus includes recommendations for indications, patient preparation, computed tomography angiography radiation dose reduction techniques and postprocessing techniques. We think that to realize its full potential and to avoid pitfalls, cardiac computed tomography angiography in children with congenital heart disease requires training and experience. Moreover, paediatric cardiac computed tomography angiography protocols should be standardized to acquire optimal images in this population with the lowest radiation dose possible, to prevent unnecessary radiation exposure. We also provide a suggested structured report and a list of acquisition protocols and technical parameters in relation to specific vendors.

Pediatric cardiac computed tomography angiography: Expert consensus from the Filiale de Cardiologie Pédiatrique et Congénitale (FCPC) and the Société Française d'Imagerie Cardiaque et Vasculaire diagnostique et interventionnelle (SFICV)

This article was designed to provide a pediatric cardiac computed tomography angiography (CCTA) expert panel consensus based on opinions of experts of the Société Française d'Imagerie Cardiaque et Vasculaire diagnostique et interventionnelle (SFICV) and of the Filiale de Cardiologie Pédiatrique Congénitale (FCPC). This expert panel consensus includes recommendations for indications, patient preparation, CTA radiation dose reduction techniques, and post-processing techniques. The consensus was based on data from available literature (original papers, reviews and guidelines) and on opinions of a group of specialists with extensive experience in the use of CT imaging in congenital heart disease. In order to reach high potential and avoid pitfalls, CCTA in children with congenital heart disease requires training and experience. Moreover, pediatric cardiac CCTA protocols should be standardized to acquire optimal images in this population with the lowest radiation dose possible to prevent unnecessary radiation exposure. We also provided a suggested structured report and a list of acquisition protocols and technical parameters in relation to specific vendors.

Evaluation of low-contrast detectability for iterative reconstruction in pediatric abdominal computed tomography: a phantom study

BACKGROUND

Iterative reconstruction is offered by all vendors to achieve similar or better CT image quality at lower doses than images reconstructed with filtered back-projection.

OBJECTIVE

The purpose of this study was to investigate the dose-reduction potential for pediatric abdominal CT imaging when using either a commercially available hybrid or a commercially available model-based iterative reconstruction algorithm from a single manufacturer.

MATERIALS AND METHODS

A phantom containing four low-contrast inserts and a uniform background with total attenuation equivalent to the abdomen of an average 8-year-old child was imaged on a CT scanner (IQon; Philips Healthcare, Cleveland, OH). We reconstructed images using both hybrid iterative reconstruction (iDose⁴) and model-based iterative reconstruction (Iterative Model Reconstruction). The four low-contrast inserts had circular cross-section with diameters of 3 mm, 5 mm, 7 mm and 10 mm and contrasts of 14 Hounsfield units (HU), 7 HU, 5 HU and 3 HU, respectively. Helical scans with identical kilovoltage (kV), pitch, rotation time, and collimation were repeated on the phantom at volume CT dose index (CTDI_vol) of 2.0 milligrays (mGy), 3.0 mGy, 4.5 mGy and 6.0 mGy. We measured the contrast-to-noise ratio (CNR) in each rod across scans. Additionally, we collected sub-images containing each rod and sub-images containing the background and used them in two-alternative forced choice observer experiments with four observers (two radiologists and two physicists). We calculated the dose-reduction potential of both iterative reconstruction algorithms relative to a scan performed at 6 mGy and reconstructed with filtered back-projection.

RESULTS

We calculated dose-reduction potential by either matching average equal observer performance in the two-alternative forced choice experiments or matching CNR. When matching CNR, the dose-reduction potential was 34% to 45% for hybrid iterative reconstruction and 89% to 95% for model-based iterative reconstruction. When matching average observer performance, the dose-reduction potential was 9% to 30% for hybrid iterative reconstruction and 57% to 74% for model-based iterative reconstruction. The range in dose-reduction potential depended on the rod size and contrast level.

CONCLUSION

Observer performance in this phantom study indicates that the dose-reduction potential indicated by an observer study is less than that of CNR; extrapolating the results to clinical studies suggests that the dose-reduction potential would also be less.

Optimization of pulmonary emphysema quantification on CT scans of COPD patients using hybrid iterative and post processing techniques: correlation with pulmonary function tests

Objectives

The aim of this study was to assess the effect of hybrid iterative reconstruction and post processing on emphysema quantification in low-dose CT scans of COPD patients using pulmonary function tests (PFT) as a reference.

Methods

CT scans of 23 COPD patients diagnosed with GOLD I or higher were reconstructed with iDose⁴ level 1 to 7 in IntelliSpace Portal (ISP) 6 and 7. ISP7 was used with and without specific denoising filter for COPD. The extent of emphysema was measured as percentage of lung voxels with attenuation < − 950 Hounsfield units (%LAA-950). The correlation between %LAA-950 and PFT, age, BMI, pack years, and the Clinical COPD Questionnaire (CCQ) and Medical Research Council dyspnea scale (MRC) was determined.

Results

Denoising significantly reduced %LAA-950 as was demonstrated by lower %LAA-950 in ISP7 with denoising filter and a significant reduction in %LAA-950 with higher iDose⁴ levels. All PFT except forced vital capacity (FVC) were significantly inversely correlated with %LAA-950. There was a trend toward a stronger correlation at higher iDose⁴ levels. %LAA-950 was also significantly correlated with BMI, GOLD class, and CCQ scores.

Conclusions

Our study showed that hybrid iterative reconstruction and use of post processing denoising can optimize the use of emphysema quantification in CT scans as a complimentary diagnostic tool to stage COPD in addition to PFT.

Effect of Statistically Iterative Image Reconstruction on Vertebral Bone Strength Prediction Using Bone Mineral Density and Finite Element Modeling: A Preliminary Study

Statistical iterative reconstruction (SIR) using multidetector computed tomography (MDCT) is a promising alternative to standard filtered back projection (FBP), because of lower noise generation while maintaining image quality. Hence, we investigated the feasibility of SIR in predicting MDCT-based bone mineral density (BMD) and vertebral bone strength from finite element (FE) analysis. The BMD and FE-predicted bone strength derived from MDCT images reconstructed using standard FBP (FFBP) and SIR with (FSIR) and without regularization (FSIRB0) were validated against experimental failure loads (Fexp). Statistical iterative reconstruction produced the best quality images with regard to noise, signal-to-noise ratio, and contrast-to-noise ratio. Fexp significantly correlated with FFBP, FSIR, and FSIRB0. FFBP had a significant correlation with FSIRB0 and FSIR. The BMD derived from FBP, SIRB0, and SIR were significantly correlated. Effects of regularization should be further investigated with FE and BMD analysis to allow for an optimal iterative reconstruction algorithm to be implemented in an in vivo scenario.

Effects of virtual tube current reduction and sparse sampling on MDCT-based femoral BMD measurements

This study investigates the impact of tube current reduction and sparse sampling on femoral bone mineral density (BMD) measurements derived from multi-detector computed tomography (MDCT). The application of sparse sampling led to robust and clinically acceptable BMD measurements. In contrast, BMD measurements derived from MDCT with virtually reduced tube currents showed a considerable increase when compared to original data.

INTRODUCTION

The study aims to evaluate the effects of radiation dose reduction by using virtual reduction of tube current or sparse sampling combined with standard filtered back projection (FBP) and statistical iterative reconstruction (SIR) on femoral bone mineral density (BMD) measurements derived from multi-detector computed tomography (MDCT).

METHODS

In routine MDCT scans of 41 subjects (65.9% men; age 69.3 ± 10.1 years), reduced radiation doses were simulated by lowering tube currents and applying sparse sampling (50, 25, and 10% of the original tube current and projections, respectively). Images were reconstructed using FBP and SIR. BMD values were assessed in the femoral neck and compared between the different dose levels, numbers of projections, and image reconstruction approaches.

RESULTS

Compared to full-dose MDCT, virtual lowering of the tube current by applying our simulation algorithm resulted in increases in BMD values for both FBP (up to a relative change of 32.5%) and SIR (up to a relative change of 32.3%). In contrast, the application of sparse sampling with a reduction down to 10% of projections showed robust BMD values, with clinically acceptable relative changes of up to 0.5% (FBP) and 0.7% (SIR).

CONCLUSIONS

Our simulations, which still require clinical validation, indicate that reductions down to ultra-low tube currents have a significant impact on MDCT-based femoral BMD measurements. In contrast, the application of sparse-sampled MDCT seems a promising future clinical option that may enable a significant reduction of the radiation dose without considerable changes of BMD values.

The evolution of image reconstruction for CT-from filtered back projection to artificial intelligence

Abstract

The first CT scanners in the early 1970s already used iterative reconstruction algorithms; however, lack of computational power prevented their clinical use. In fact, it took until 2009 for the first iterative reconstruction algorithms to come commercially available and replace conventional filtered back projection. Since then, this technique has caused a true hype in the field of radiology. Within a few years, all major CT vendors introduced iterative reconstruction algorithms for clinical routine, which evolved rapidly into increasingly advanced reconstruction algorithms. The complexity of algorithms ranges from hybrid-, model-based to fully iterative algorithms. As a result, the number of scientific publications on this topic has skyrocketed over the last decade. But what exactly has this technology brought us so far? And what can we expect from future hardware as well as software developments, such as photon-counting CT and artificial intelligence? This paper will try answer those questions by taking a concise look at the overall evolution of CT image reconstruction and its clinical implementations. Subsequently, we will give a prospect towards future developments in this domain.

Key Points

• Advanced CT reconstruction methods are indispensable in the current clinical setting.

• IR is essential for photon-counting CT, phase-contrast CT, and dark-field CT.

• Artificial intelligence will potentially further increase the performance of reconstruction methods.

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

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 iDose⁴ ( 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.

CNN as model observer in a liver lesion detection task for x-ray computed tomography: A phantom study

PURPOSE

The purpose of this study was the evaluation of anthropomorphic model observers trained with neural networks for the prediction of a human observer's performance.

METHODS

To simulate liver lesions, a phantom with contrast targets (acrylic spheres, varying diameters, +30 HU) was repeatedly scanned on a computed tomography scanner. Image data labeled with confidence ratings assessed in a reader study for a detection task of liver lesions were used to build several anthropomorphic model observers. Models were trained with images reconstructed with iterative reconstruction and evaluated with images reconstructed with filtered backprojection. A neural network, based on softmax regression (SR-MO), and convolutional neural networks (CNN-MO) were used to predict the performance of a human observer and compared to a channelized Hotelling observer [with Gabor channels and internal channel noise (CHOi)]. Model observers were evaluated by a receiver operating characteristic curve analysis and compared to the results in the reader study. Two strategies were used to train the SR-MO and CNN-MO: A) building a separate model for each lesion size; B) building one model that was applied to lesions of all sizes.

RESULTS

All tested model observers and the human observer were highly correlated at each lesion size and dose level. With strategy A, Pearson's product-moment correlation coefficients r were 0.926 (95% confidence interval (CI): 0.679-0.985) for SR-MO and 0.979 (95% CI: 0.902-0.996) for CNN-MO. With strategy B, r was 0.860 (95% CI: 0.454-0.970) for SR-MO and 0.918 (95% CI: 0.651-0.983) for CNN-MO. For CHOi, r was 0.945 (95% CI: 0.755-0.989). With strategy A, mean absolute percentage differences (MAPD) between the model observers and the human observer were 3.7% for SR-MO and 1.2% for CNN-MO. With strategy B, MAPD were 3.7% for SR-MO and 3.0% for CNN-MO. For the CHOi the MAPD was 2.2%.

CONCLUSION

Convolutional neural network model observers can accurately predict the performance of a human observer for all lesion sizes and dose levels in the evaluated signal detection task.

Machine learning-based dual-energy CT parametric mapping

The aim is to develop and evaluate machine learning methods for generating quantitative parametric maps of effective atomic number (Z_eff), relative electron density (ρ _e), mean excitation energy (I _x ), and relative stopping power (RSP) from clinical dual-energy CT data. The maps could be used for material identification and radiation dose calculation. Machine learning methods of historical centroid (HC), random forest (RF), and artificial neural networks (ANN) were used to learn the relationship between dual-energy CT input data and ideal output parametric maps calculated for phantoms from the known compositions of 13 tissue substitutes. After training and model selection steps, the machine learning predictors were used to generate parametric maps from independent phantom and patient input data. Precision and accuracy were evaluated using the ideal maps. This process was repeated for a range of exposure doses, and performance was compared to that of the clinically-used dual-energy, physics-based method which served as the reference. The machine learning methods generated more accurate and precise parametric maps than those obtained using the reference method. Their performance advantage was particularly evident when using data from the lowest exposure, one-fifth of a typical clinical abdomen CT acquisition. The RF method achieved the greatest accuracy. In comparison, the ANN method was only 1% less accurate but had much better computational efficiency than RF, being able to produce parametric maps in 15 s. Machine learning methods outperformed the reference method in terms of accuracy and noise tolerance when generating parametric maps, encouraging further exploration of the techniques. Among the methods we evaluated, ANN is the most suitable for clinical use due to its combination of accuracy, excellent low-noise performance, and computational efficiency.

Multidetector Computed Tomography Imaging: Effect of Sparse Sampling and Iterative Reconstruction on Trabecular Bone Microstructure

Multidetector computed tomography-based trabecular bone microstructure analysis ensures promising results in fracture risk prediction caused by osteoporosis. Because multidetector computed tomography is associated with high radiation exposure, its clinical routine use is limited. Hence, in this study, we investigated in 11 thoracic midvertebral specimens whether trabecular texture parameters are comparable derived from (1) images reconstructed using statistical iterative reconstruction (SIR) and filtered back projection as criterion standard at different exposures (80, 150, 220, and 500 mAs) and (2) from SIR-based sparse sampling projections (12.5%, 25%, 50%, and 100%) and equivalent exposures as criterion standard. Twenty-four texture features were computed, and those that showed similar values between (1) filtered back projection and SIR at the different exposure levels and (2) sparse sampling and equivalent exposures and reconstructed with SIR were identified. These parameters can be of equal value in determining trabecular bone microstructure with lower radiation exposure using sparse sampling and SIR.

MDCT in suspected lumbar spine fracture: comparison of standard and reduced dose settings using iterative reconstruction

AIM

To compare standard (SD-) and reduced-dose computed tomography (RD-CT) in combination with iterative reconstruction (IR) in emergency patients with suspected lumbar spine fracture.

MATERIAL AND METHODS

Forty emergency patients with suspected lumbar spinal disorder who underwent RD-CT and 40 body mass index-matched patients undergoing SD-CT were enrolled in this retrospective study. Raw data for RD-CT were reconstructed using two increasing IR levels (IRL) 4 and 6, while SD-CT was reconstructed with IRL3. Two radiologists assessed image quality, image noise, and reader confidence in interpreting findings of spinal fractures in a blinded manner.

RESULTS

Effective radiation dose was reduced by 50% using RD-CT. Overall subjective image quality (SIQ) was high for both protocols and slightly superior in the RD-CT protocol for both IRL compared to SD-CT. The detection rate of spinal disorders was high for both protocols with a high interobserver agreement.

CONCLUSION

RD-CT with higher levels of IR results in substantial dose reduction of 50% in lumbar spine CT while maintaining an excellent subjective image quality resulting in a high diagnostic confidence.

Nonlinear statistical iterative reconstruction for propagation-based phase-contrast tomography

Propagation-based phase-contrast tomography has become a valuable tool for visualization of three-dimensional biological samples, due to its high sensitivity and its potential in providing increased contrast between materials with similar absorption properties. We present a statistical iterative reconstruction algorithm for this imaging technique in the near-field regime. Under the assumption of a single material, the propagation of the x-ray wavefield-relying on the transport-of-intensity equation-is made an integral part of the tomographic reconstruction problem. With a statistical approach acting directly on the measured intensities, we find an unconstrained nonlinear optimization formulation whose solution yields the three-dimensional distribution of the sample. This formulation not only omits the intermediate step of retrieving the projected thicknesses but also takes the statistical properties of the measurements into account and incorporates prior knowledge about the sample in the form of regularization techniques. We show some advantages of this integrated approach compared to two-step approaches on data obtained using a commercially available x-ray micro-tomography system. In particular, we address one of the most considerable challenges of the imaging technique, namely, the artifacts arising from samples containing highly absorbing features. With the use of statistical weights in our noise model, we can account for these materials and recover features in the vicinity of the highly absorbing features that are lost in the conventional two-step approaches. In addition, the statistical modeling of our reconstruction approach will prove particularly beneficial in the ongoing transition of this imaging technique from synchrotron facilities to laboratory setups.

Quantitative Image Quality and Histogram-Based Evaluations of an Iterative Reconstruction Algorithm at Low-to-Ultralow Radiation Dose Levels: A Phantom Study in Chest CT

Objective

To describe the quantitative image quality and histogram-based evaluation of an iterative reconstruction (IR) algorithm in chest computed tomography (CT) scans at low-to-ultralow CT radiation dose levels.

Materials and Methods

In an adult anthropomorphic phantom, chest CT scans were performed with 128-section dual-source CT at 70, 80, 100, 120, and 140 kVp, and the reference (3.4 mGy in volume CT Dose Index [CTDI_vol]), 30%-, 60%-, and 90%-reduced radiation dose levels (2.4, 1.4, and 0.3 mGy). The CT images were reconstructed by using filtered back projection (FBP) algorithms and IR algorithm with strengths 1, 3, and 5. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were statistically compared between different dose levels, tube voltages, and reconstruction algorithms. Moreover, histograms of subtraction images before and after standardization in x- and y-axes were visually compared.

Results

Compared with FBP images, IR images with strengths 1, 3, and 5 demonstrated image noise reduction up to 49.1%, SNR increase up to 100.7%, and CNR increase up to 67.3%. Noteworthy image quality degradations on IR images including a 184.9% increase in image noise, 63.0% decrease in SNR, and 51.3% decrease in CNR, and were shown between 60% and 90% reduced levels of radiation dose (p < 0.0001). Subtraction histograms between FBP and IR images showed progressively increased dispersion with increased IR strength and increased dose reduction. After standardization, the histograms appeared deviated and ragged between FBP images and IR images with strength 3 or 5, but almost normally-distributed between FBP images and IR images with strength 1.

Conclusion

The IR algorithm may be used to save radiation doses without substantial image quality degradation in chest CT scanning of the adult anthropomorphic phantom, down to approximately 1.4 mGy in CTDI_vol (60% reduced dose).

Assessment of quantification accuracy and image quality of a full-body dual-layer spectral CT system

The performance of a recently introduced spectral computed tomography system based on a dual-layer detector has been investigated. A semi-anthropomorphic abdomen phantom for CT performance evaluation was imaged on the dual-layer spectral CT at different radiation exposure levels (CTDIvol of 10 mGy, 20 mGy and 30 mGy). The phantom was equipped with specific low-contrast and tissue-equivalent inserts including water-, adipose-, muscle-, liver-, bone-like materials and a variation in iodine concentrations. Additionally, the phantom size was varied using different extension rings to simulate different patient sizes. Contrast-to-noise (CNR) ratio over the range of available virtual mono-energetic images (VMI) and the quantitative accuracy of VMI Hounsfield Units (HU), effective-Z maps and iodine concentrations have been evaluated. Central and peripheral locations in the field-of-view have been examined. For all evaluated imaging tasks the results are within the calculated theoretical range of the tissue-equivalent inserts. Especially at low energies, the CNR in VMIs could be boosted by up to 330% with respect to conventional images using iDose/spectral reconstructions at level 0. The mean bias found in effective-Z maps and iodine concentrations averaged over all exposure levels and phantom sizes was 1.9% (eff. Z) and 3.4% (iodine). Only small variations were observed with increasing phantom size (+3%) while the bias was nearly independent of the exposure level (±0.2%). Therefore, dual-layer detector based CT offers high quantitative accuracy of spectral images over the complete field-of-view without any compromise in radiation dose or diagnostic image quality.

Joint Statistical Iterative Material Image Reconstruction for Spectral Computed Tomography Using a Semi-Empirical Forward Model

By acquiring tomographic measurements with several distinct photon energy spectra, spectral computed tomography (spectral CT) is able to provide additional material-specific information compared with conventional CT. This information enables the generation of material selective images, which have found various applications in medical imaging. However, material decomposition typically leads to noise amplification and a degradation of the signal-to-noise ratio. This is still a fundamental problem of spectral CT, especially for low-dose medical applications. Inspired by the success for low-dose conventional CT, several statistical iterative reconstruction algorithms for spectral CT have been developed. These algorithms typically rely on detailed knowledge about the spectrum and the detector response. Obtaining this knowledge is often difficult in practice, especially if photon counting detectors are used to acquire the energy specific information. In this paper, a new algorithm for joint statistical iterative material image reconstruction is presented. It relies on a semi-empirical forward model which is tuned by calibration measurements. This strategy allows to model spatially varying properties of the imaging system without requiring detailed prior knowledge of the system parameters. We employ an efficient optimization algorithm based on separable surrogate functions to accelerate convergence and reduce the reconstruction time. Numerical as well as real experiments show that our new algorithm leads to reduced statistical bias and improved image quality compared with projection-based material decomposition followed by analytical or iterative image reconstruction.

Feasibility study of iterative model reconstruction combined with low tube voltage, low iodine load, and low iodine delivery rate in craniocervical CT angiography

AIM

To investigate the feasibility of iterative model reconstruction (IMR) combined with low tube voltage, low iodine load, and low iodine deliver rate in craniocervical computed tomography angiography (CTA).

MATERIALS AND METHODS

Sixty patients were randomly divided into two groups (n=30 for each): group A: 120 kVp, 50 ml of iopromide at a flow rate of 5 ml/s; filtered back projection (FBP) reconstruction; group B: 80 kVp, 30 ml of iohexol at 4.5 ml/s; hybrid iterative reconstruction (HIR) for group B1 and IMR for group B2. CT attenuation values, image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), subjective image quality, effective dose (ED), iodine load, and iodine delivery rate (IDR) were compared.

RESULTS

CT attenuation values of the arteries were higher in groups B1 and B2 than group A. The SNR and CNR were higher, while image noise was lower, for group B2 compared with groups B1 and A. The best subjective image quality was obtained with group B2. ED, iodine load, and IDR reduction of 69.6%, 51.4%, 27%, respectively, was obtained in group B compared with group A.

CONCLUSION

IMR combined with 80 kVp and 30 ml of iohexol at a flow rate of 4.5 ml/s for craniocervical CTA can reduce ED, iodine load, and IDR, while improving image quality.

Low-Dose CCT to Exclude Contraindications to Lumbar Puncture : Benefits and Limitations

BACKGROUND

Low-dose cranial computed tomography (LD-CCT) based on iterative reconstruction has been shown to have sufficient image quality to assess cerebrospinal fluid spaces (CSF) and midline structures but not to exclude subtle parenchymal pathologies. Patients without focal neurological deficits often undergo CCT before lumbar puncture (LP) to exclude contraindications to LP including brain herniation or increased CSF pressure. We performed LD-CCT to assess if image quality is appropriate for this indication.

METHODS

A total of 58 LD-CCT (220 mA/120 kV) of patients before LP were retrospectively evaluated and compared to 79 normal standard dose cranial computed tomography (SD-CCT) (350 mA/120 kV). Iterative reconstruction used for both dose levels was increased by one factor for LD-CCT. We assessed the signal-to-noise (SNR) and contrast-to-noise ratio (CNR), the dose estimates and scored diagnostic image quality by two raters independently. Significance level was set at p < 0.05.

RESULTS

The inner and outer CSF spaces except the sulci were equally well depicted by the LD-CCT and SD-CCT; however, depiction of the subtle density differences of the brain parenchyma and the sulci was significantly worse in the LD-CCT (p < 0.0001). The SNR in the gray matter (9.35 vs. 10.61, p < 0.05) and white matter (7.23 vs. 8.15, p < 0.001) were significantly lower in LD-CCT than in SD-CCT with significantly lower dose estimates (1.04 vs. 1.69 mSv, respectively p < 0.0001).

CONCLUSION

The use of LD-CCT with a dose reduction of almost 50% is sufficient to exclude contraindications to LP; however, LD-CCT cannot exclude subtle parenchymal pathologies. Therefore, in patients with suspected parenchymal pathology, SD-CCT is still the method of choice.

Revising the lower statistical limit of x-ray grating-based phase-contrast computed tomography

Phase-contrast x-ray computed tomography (PCCT) is currently investigated as an interesting extension of conventional CT, providing high soft-tissue contrast even if examining weakly absorbing specimen. Until now, the potential for dose reduction was thought to be limited compared to attenuation CT, since meaningful phase retrieval fails for scans with very low photon counts when using the conventional phase retrieval method via phase stepping. In this work, we examine the statistical behaviour of the reverse projection method, an alternative phase retrieval approach and compare the results to the conventional phase retrieval technique. We investigate the noise levels in the projections as well as the image quality and quantitative accuracy of the reconstructed tomographic volumes. The results of our study show that this method performs better in a low-dose scenario than the conventional phase retrieval approach, resulting in lower noise levels, enhanced image quality and more accurate quantitative values. Overall, we demonstrate that the lower statistical limit of the phase stepping procedure as proposed by recent literature does not apply to this alternative phase retrieval technique. However, further development is necessary to overcome experimental challenges posed by this method which would enable mainstream or even clinical application of PCCT.

Is multidetector CT-based bone mineral density and quantitative bone microstructure assessment at the spine still feasible using ultra-low tube current and sparse sampling?

Objective

Osteoporosis diagnosis using multidetector CT (MDCT) is limited to relatively high radiation exposure. We investigated the effect of simulated ultra-low-dose protocols on in-vivo bone mineral density (BMD) and quantitative trabecular bone assessment.

Materials and methods

Institutional review board approval was obtained. Twelve subjects with osteoporotic vertebral fractures and 12 age- and gender-matched controls undergoing routine thoracic and abdominal MDCT were included (average effective dose: 10 mSv). Ultra-low radiation examinations were achieved by simulating lower tube currents and sparse samplings at 50%, 25% and 10% of the original dose. BMD and trabecular bone parameters were extracted in T10–L5.

Results

Except for BMD measurements in sparse sampling data, absolute values of all parameters derived from ultra-low-dose data were significantly different from those derived from original dose images (p<0.05). BMD, apparent bone fraction and trabecular thickness were still consistently lower in subjects with than in those without fractures (p<0.05).

Conclusion

In ultra-low-dose scans, BMD and microstructure parameters were able to differentiate subjects with and without vertebral fractures, suggesting osteoporosis diagnosis is feasible. However, absolute values differed from original values. BMD from sparse sampling appeared to be more robust. This dose-dependency of parameters should be considered for future clinical use.

Key Points

• BMD and quantitative bone parameters are assessable in ultra-low-dose in vivo MDCT scans.

• Bone mineral density does not change significantly when sparse sampling is applied.

• Quantitative trabecular bone microstructure measurements are sensitive to dose reduction.

• Osteoporosis subjects could be differentiated even at 10% of original dose.

• Radiation exposure should be considered when comparing quantitative bone parameters.

Electronic supplementary material

The online version of this article (doi:10.1007/s00330-017-4904-y) contains supplementary material, which is available to authorized users.

In vivo coronary artery plaque assessment with computed tomography angiography: is there an impact of iterative reconstruction on plaque volume and attenuation metrics?

Background Coronary computed tomography angiography (CTA) allows the evaluation of coronary plaque volume and low attenuation (lipid-rich) component, for plaque vulnerability assessment. Purpose To determine the effect of iterative reconstruction (IR) on coronary plaque volume and composition. Material and Methods Consecutive patients without coronary artery disease were prospectively enrolled for 256-slice CT. Images were reconstructed with both filtered back projection (FBP) and a hybrid IR algorithm (iDose⁴, Philips) levels 1, 3, 5, and 7. Coronary plaques were assessed according to predefined Hounsfield unit (HU) attenuation intervals, for total plaque and HU-interval volumes. Results Fifty-three patients (mean age, 53.6 years) were included. Noise was significantly decreased and signal-to-noise ratio (SNR) / contrast-to-noise (CNR) were both significantly improved at all IR levels in comparison to FBP. Plaque characterization was performed in 41 patients for a total of 125 plaques. Total plaque volume ranged from 104.4 ± 120.7 to 107.4 ± 128.9 mm³ and low attenuation plaque component from 40.5 ± 54.7 to 43.5 ± 58.9 mm³, with no statistically significant differences between all IR levels and FBP ( P = 0.786 and P ≥ 0.078, respectively). Conclusion IR improved image quality. Total and low attenuation plaque volumes were similar using either IR or FBP.

CT Angiography: Post-processed Contrast Enhancement for Improved Detection of Pulmonary Embolism

RATIONALE AND OBJECTIVES

The study aimed to improve the detection of pulmonary embolism via an iodine contrast enhancement tool in patients who underwent suboptimal enhanced computed tomography angiography (CTA).

MATERIALS AND METHODS

We evaluated the CT examinations of 41 patients who underwent CTA for evaluation of the pulmonary arteries which suffered from suboptimal contrast enhancement. The contrast enhancement of the reconstructed images was increased via a post-processing tool (vContrast). Image noise and contrast-to-noise ratio (CNR) were assessed in eight different regions: main pulmonary artery, right and left pulmonary arteries, right and left segment arteries, muscle, subcutaneous fat, and bone. For subjective image assessment, three experienced radiologists evaluated the diagnostic quality.

RESULTS

While employing the post-processing algorithm, the CNR for contrast-filled lumen and thrombus/muscle improves significantly by a factor of 1.7 (CNR without vContrast = 8.48 ± 6.79/CNR with vContrast = 14.46 ± 5.29) (P <0.01). No strengthening of artifacts occurred, and the mean Hounsfield unit values of the muscle, subcutaneous fat, and the bone showed no significant changes. Subjective image analysis illustrated a significant improvement using post-processing for clinically relevant criteria such as diagnostic confidence.

CONCLUSIONS

vContrast makes CT angiograms with inadequate contrast applicable for diagnostic evaluation, offering an improved visualization of the pulmonary arteries. In addition, vContrast can help in the significant reduction of the iodine contrast material.

Usefulness of low dose chest CT for initial evaluation of blunt chest trauma

We aimed to compare the diagnostic performance and inter-observer consistency between low dose chest CT (LDCT) and standard dose chest CT (SDCT) in the patients with blunt chest trauma.A total of 69 patients who met criteria indicative of blunt chest trauma (77% of male; age range, 16-85) were enrolled. All patients underwent LDCT without intravenous (IV) contrast and SDCT with IV contrast using parameters as following: LDCT, 40 mAs with automatic tube current modulation (ATCM) and 100 kVp (BMI <25, n = 51) or 120 kVp (BMI>25, n = 18); SDCT, 180 mAs with ATCM and 120 kVp. Transverse, coronal, sagittal images were reconstructed with 3-mm slice thickness without gap and provided for evaluation of 3 observers. Reference standard images (transverse, coronal, sagittal) were reconstructed using SDCT data with 1-mm slice thickness without gap. Reference standard was established by 2 experienced thoracic radiologists by consensus. Three observers independently evaluated each data set of LDCT and SDCT.Multiple-reader receiver operating characteristic analysis for comparing areas under the ROC curves demonstrated that there was no significant difference of diagnostic performance between LDCT and SDCT for the diagnosis of pulmonary injury, skeletal trauma, mediastinal injury, and chest wall injury (P > 0.05). The intraclass correlation coefficient was measured for inter-observer consistency and revealed that there was good inter-observer consistency in each examination of LDCT and SDCT for evaluation of blunt chest injury (0.8601-1.000). Aortic and upper abdominal injury could not be appropriately compared as LDCT was performed without using contrast materials and this was limitation of this study.The effective radiation dose of LDCT (average DLP = 1.52 mSv⋅mGy cm) was significantly lower than those of SDCT (7.21 mSv mGy cm).There is a great potential benefit to use of LDCT for initial evaluation of blunt chest trauma because LDCT could maintain diagnostic image quality as SDCT and provide significant radiation dose reduction. A further study of LDCT with IV contrast for evaluation of aortic and upper abdominal injury is needed.

Iterative model reconstruction reduces calcified plaque volume in coronary CT angiography

OBJECTIVE

To assess the impact of iterative model reconstruction (IMR) on calcified plaque quantification as compared to filtered back projection reconstruction (FBP) and hybrid iterative reconstruction (HIR) in coronary computed tomography angiography (CTA).

METHODS

Raw image data of 52 patients who underwent 256-slice CTA were reconstructed with IMR, HIR and FBP. We evaluated qualitative, quantitative image quality parameters and quantified calcified and partially calcified plaque volumes using automated software.

RESULTS

Overall qualitative image quality significantly improved with HIR as compared to FBP, and further improved with IMR (p<0.01 all). Contrast-to-noise ratios were improved with IMR, compared to HIR and FBP (51.0 [43.5-59.9], 20.3 [16.2-25.9] and 14.0 [11.2-17.7], respectively, all p<0.01) Overall plaque volumes were lowest with IMR and highest with FBP (121.7 [79.3-168.4], 138.7 [90.6-191.7], 147.0 [100.7-183.6]). Similarly, calcified volumes (>130 HU) were decreased with IMR as compared to HIR and FBP (105.9 [62.1-144.6], 110.2 [63.8-166.6], 115.9 [81.7-164.2], respectively, p<0.05 all). High-attenuation non-calcified volumes (90-129 HU) yielded similar values with FBP and HIR (p=0.81), however it was lower with IMR (p < 0.05 both). Intermediate- (30-89 HU) and low-attenuation (<30 HU) non-calcified volumes showed no significant difference (p=0.22 and p=0.67, respectively).

CONCLUSIONS

IMR improves image quality of coronary CTA and decreases calcified plaque volumes.

Submillisievert Radiation Dose Coronary CT Angiography: Clinical Impact of the Knowledge-Based Iterative Model Reconstruction

RATIONALE AND OBJECTIVES

The purpose of this study was to evaluate the noise and image quality of images reconstructed with a knowledge-based iterative model reconstruction (knowledge-based IMR) in ultra-low dose cardiac computed tomography (CT).

MATERIALS AND METHODS

We performed submillisievert radiation dose coronary CT angiography on 43 patients. We also performed a phantom study to evaluate the influence of object size with the automatic exposure control phantom. We reconstructed clinical and phantom studies with filtered back projection (FBP), hybrid iterative reconstruction (hybrid IR), and knowledge-based IMR. We measured effective dose of patients and compared CT number, image noise, and contrast noise ratio in ascending aorta of each reconstruction technique. We compared the relationship between image noise and body mass index for the clinical study, and object size for phantom study.

RESULTS

The mean effective dose was 0.98 ± 0.25 mSv. The image noise of knowledge-based IMR images was significantly lower than those of FBP and hybrid IR images (knowledge-based IMR: 19.4 ± 2.8; FBP: 126.7 ± 35.0; hybrid IR: 48.8 ± 12.8, respectively) (P < .01). The contrast noise ratio of knowledge-based IMR images was significantly higher than those of FBP and hybrid IR images (knowledge-based IMR: 29.1 ± 5.4; FBP: 4.6 ± 1.3; hybrid IR: 13.1 ± 3.5, respectively) (P < .01). There were moderate correlations between image noise and body mass index in FBP (r = 0.57, P < .01) and hybrid IR techniques (r = 0.42, P < .01); however, these correlations were weak in knowledge-based IMR (r = 0.27, P < .01).

CONCLUSION

Compared to FBP and hybrid IR, the knowledge-based IMR offers significant noise reduction and improvement in image quality in submillisievert radiation dose cardiac CT.

Ultra Low Dose CT Pulmonary Angiography with Iterative Reconstruction

Objective

Evaluation of a new iterative reconstruction algorithm (IMR) for detection/rule-out of pulmonary embolism (PE) in ultra-low dose computed tomography pulmonary angiography (CTPA).

Methods

Lower dose CT data sets were simulated based on CTPA examinations of 16 patients with pulmonary embolism (PE) with dose levels (DL) of 50%, 25%, 12.5%, 6.3% or 3.1% of the original tube current setting. Original CT data sets and simulated low-dose data sets were reconstructed with three reconstruction algorithms: the standard reconstruction algorithm “filtered back projection” (FBP), the first generation iterative reconstruction algorithm iDose and the next generation iterative reconstruction algorithm “Iterative Model Reconstruction” (IMR). In total, 288 CTPA data sets (16 patients, 6 tube current levels, 3 different algorithms) were evaluated by two blinded radiologists regarding image quality, diagnostic confidence, detectability of PE and contrast-to-noise ratio (CNR).

Results

iDose and IMR showed better detectability of PE than FBP. With IMR, sensitivity for detection of PE was 100% down to a dose level of 12.5%. iDose and IMR showed superiority to FBP regarding all characteristics of subjective (diagnostic confidence in detection of PE, image quality, image noise, artefacts) and objective image quality. The minimum DL providing acceptable diagnostic performance was 12.5% (= 0.45 mSv) for IMR, 25% (= 0.89 mSv) for iDose and 100% (= 3.57 mSv) for FBP. CNR was significantly (p < 0.001) improved by IMR compared to FBP and iDose at all dose levels.

Conclusion

By using IMR for detection of PE, dose reduction for CTPA of up to 75% is possible while maintaining full diagnostic confidence. This would result in a mean effective dose of approximately 0.9 mSv for CTPA.

CT Pulmonary Angiography at Reduced Radiation Exposure and Contrast Material Volume Using Iterative Model Reconstruction and iDose4 Technique in Comparison to FBP

Purpose

To assess image quality of CT pulmonary angiography (CTPA) at reduced radiation exposure (RD-CTPA) and contrast medium (CM) volume using two different iterative reconstruction (IR) algorithms (iDose⁴ and iterative model reconstruction (IMR)) in comparison to filtered back projection (FBP).

Materials and Methods

52 patients (body weight < 100 kg, mean BMI: 23.9) with suspected pulmonary embolism (PE) underwent RD-CTPA (tube voltage: 80 kV; mean CTDIvol: 1.9 mGy) using 40 ml CM. Data were reconstructed using FBP and two different IR algorithms (iDose⁴ and IMR). Subjective and objective image quality and conspicuity of PE were assessed in central, segmental, and subsegmental arteries.

Results

Noise reduction of 55% was achieved with iDose⁴ and of 85% with IMR compared to FBP. Contrast-to-noise ratio significantly increased with iDose⁴ and IMR compared to FBP (p<0.05). Subjective image quality was rated significantly higher at IMR reconstructions in comparison to iDose⁴ and FBP. Conspicuity of central and segmental PE significantly improved with the use of IMR. In subsegmental arteries, iDose⁴ was superior to IMR.

Conclusions

CTPA at reduced radiation exposure and contrast medium volume is feasible with the use of IMR, which provides improved image quality and conspicuity of pulmonary embolism in central and segmental arteries.

Comparison of image quality and visibility of normal and abnormal findings at submillisievert chest CT using filtered back projection, iterative model reconstruction (IMR) and iDose4™

OBJECTIVE

To compare both image quality and visibility of normal and abnormal findings at submillisievert chest CT (smSv-CT) using filtered back projection (FBP) and the two different iterative reconstruction (IR) techniques iterative model reconstruction (IMR) and iDose⁴™.

MATERIALS AND METHODS

This institutional review board approved study was based on retrospective interpretation of clinically indicated acquired data. The requirement to obtain informed consent was waived. 81 patients with suspected pneumonia underwent smSv-CT (Brilliance iCT, Philips Healthcare; mean effective dose: 0.86±0.2mSv). Data were reconstructed using FBP and two different IR techniques iDose⁴™ and IMR (Philips Healthcare) at various iteration levels. Objective image noise (OIN) was measured. Two experienced readers independently assessed all images for image noise, image appearance and visibility of normal anatomic and abnormal findings. A random intercept model was used for statistical analysis.

RESULTS

Compared to FBP and iDose⁴™, IMR reduced OIN up to 88% and 72%, respectively (p<0.001). A mild blotchy image appearance was seen in IMR images, affecting diagnostic confidence. iDose⁴™ images provided satisfactory to good image quality for visibility of normal and abnormal findings and were superior to FBP (p<0.001). IMR images were significantly inferior for visibility of normal structures compared to iDose⁴™, while being superior for visibility of abnormal findings except for reticular pattern (p<0.001).

CONCLUSION

IMR results for visibility of normal and abnormal lung findings are heterogeneous, indicating that IMR may not represent a priority technique for clinical routine. iDose⁴™ represents a suitable method for evaluation of lung tissue at submillisievert chest CT.

Effect of Low-Dose MDCT and Iterative Reconstruction on Trabecular Bone Microstructure Assessment

We investigated the effects of low-dose multi detector computed tomography (MDCT) in combination with statistical iterative reconstruction algorithms on trabecular bone microstructure parameters. Twelve donated vertebrae were scanned with the routine radiation exposure used in our department (standard-dose) and a low-dose protocol. Reconstructions were performed with filtered backprojection (FBP) and maximum-likelihood based statistical iterative reconstruction (SIR). Trabecular bone microstructure parameters were assessed and statistically compared for each reconstruction. Moreover, fracture loads of the vertebrae were biomechanically determined and correlated to the assessed microstructure parameters. Trabecular bone microstructure parameters based on low-dose MDCT and SIR significantly correlated with vertebral bone strength. There was no significant difference between microstructure parameters calculated on low-dose SIR and standard-dose FBP images. However, the results revealed a strong dependency on the regularization strength applied during SIR. It was observed that stronger regularization might corrupt the microstructure analysis, because the trabecular structure is a very small detail that might get lost during the regularization process. As a consequence, the introduction of SIR for trabecular bone microstructure analysis requires a specific optimization of the regularization parameters. Moreover, in comparison to other approaches, superior noise-resolution trade-offs can be found with the proposed methods.

Iterative Reconstruction Improves Both Objective and Subjective Image Quality in Acute Stroke CTP

PURPOSE

Computed tomography perfusion (CTP) imaging in acute ischemic stroke (AIS) suffers from measurement errors due to image noise. The purpose of this study was to investigate if iterative reconstruction (IR) algorithms can be used to improve the diagnostic value of standard-dose CTP in AIS.

METHODS

Twenty-three patients with AIS underwent CTP with standardized protocol and dose. Raw data were reconstructed with filtered back projection (FBP) and IR with intensity levels 3, 4, 5. Image quality was objectively (quantitative perfusion values, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)) and subjectively (overall image quality) assessed. Ischemic core and perfusion mismatch were visually rated. Discriminative power for tissue outcome prediction was determined by the area under the receiver operating characteristic curve (AUC) resulting from the overlap between follow-up infarct lesions and stepwise thresholded CTP maps.

RESULTS

With increasing levels of IR, objective image quality (SNR and CNR in white matter and gray matter, elimination of error voxels) and subjective image quality improved. Using IR, mean transit time (MTT) was higher in ischemic lesions, while there was no significant change of cerebral blood volume (CBV) and cerebral blood flow (CBF). Visual assessments of perfusion mismatch changed in 4 patients, while the ischemic core remained constant in all cases. Discriminative power for infarct prediction as represented by AUC was not significantly changed in CBV, but increased in CBF and MTT (mean (95% CI)): 0.72 (0.67-0.76) vs. 0.74 (0.70-0.78) and 0.65 (0.62-0.67) vs 0.67 (0.64-0.70).

CONCLUSION

In acute stroke patients, IR improves objective and subjective image quality when applied to standard-dose CTP. This adds to the overall confidence of CTP in acute stroke triage.

Usefulness of Ultralow-Dose (Submillisievert) Chest CT Using Iterative Reconstruction for Initial Evaluation of Sharp Fish Bone Esophageal Foreign Body

OBJECTIVE

The purpose of this article was to evaluate the usefulness of ultralow-dose chest CT as an initial imaging study for evaluation of sharp fish bone esophageal foreign body (FB).

MATERIALS AND METHODS

A total of 57 subjects who underwent ultralow-dose chest CT were included in this retrospective study. All subjects had a history of ingestion and symptoms of esophageal FB. All ultralow-dose chest CT data were reconstructed twice, once with filtered back projection (FBP) and once with iterative reconstruction, and three observers reviewed the images independently. ROC analysis was used to evaluate diagnostic performance of ultralow-dose chest CT. Intraclass correlation coefficient (ICC) was calculated for analysis of interobserver agreement.

RESULTS

Among 57 patients, 42 were confirmed as having esophageal FB. Significant objective noise reduction of mediastinum was achieved using an iterative reconstruction technique. Subjective image noise of iterative reconstruction was significantly better than that of FBP. Overall diagnostic performance of ultralow-dose chest CT for esophageal FB of iterative reconstruction (AUC = 0.999) was significantly better than that of FBP (AUC = 0.95) (p = 0.02). Interobserver agreement was greater for iterative reconstruction (ICC = 0.944) than for FBP (ICC = 0.778).

CONCLUSION

Ultralow-dose chest CT using iterative reconstruction provided satisfactory diagnostic image quality for identifying fish bone esophageal FB with reduced radiation dose and high observer accuracy. Therefore, ultralow-dose chest CT would be adequate as a first-line imaging modality for fish bone esophageal FB.