Evaluation of dose reduction and image quality in chest CT using adaptive statistical iterative reconstruction with the same group of patients

Contrast-Enhanced Chest Computed Tomography (CT) Scan with Low Radiation and Total Iodine Dose for Lung Cancer Detection Using Adaptive Statistical Iterative Reconstruction

Background: Contrast-enhanced chest computed tomography (CT) is useful for the detection and follow-up of patients with lung cancer. However, reaching balance between diagnostic image quality, radiation dose, and iodixanol dose is a cause of concern. Objectives: To investigate the clinical value of adaptive statistical iterative reconstruction (ASIR) in reducing the iodixanol content and radiation dose during contrast-enhanced chest CT scan for patients diagnosed with lung masses/nodules based on the analysis of image quality. Methods: This prospective study was conducted on 80 patients diagnosed with nodules or masses, who required contrast-enhanced chest CT scans. The experimental group (n = 40) was subjected to iohexol at a high concentration (350 mgI/L) with a tube voltage of 120 kVp and a filter back projection (FBP) reconstruction algorithm. The comparison group (n = 40) was subject to iodixanol at a lower concentration (270 mgI/L) with a tube voltage of 100 kVp and ASIR (blending ratio, 40%). The radiation dose and total iodixanol content, as well as subjective and objective evaluations of image quality, were analyzed and compared. Results: The two groups obtained non-significantly different subjective scores for five structures detected in the lung window and five structures detected in the mediastinal window, as well as the overall image (P > 0.05 for all). Both the two-group images obtained diagnosis-acceptable scores (≥ 3 points) on displays of 10 structures and overall image quality. The mean CT value of vessels (100 kVp vs. 120 kVp: 314.90 ± 23.42 vs. 308.93 ± 21.40; P > 0.05), standard deviation (13.03 ± 0.88 vs.12.83 ± 0.90; P > 0.05), and contrast-to-noise ratio (20.77 ± 2.20 vs. 20.36 ± 1.94; P > 0.05) were not significantly different between two groups. However, the CT dose index, dose-length product, effective dose, and total iodine dose were reduced by 27.58%, 36.65%, 36.59%, and 22.86% in the 100-kVp group compared to the 120-kVp group. Conclusions: The ASIR showed great potential in reducing the radiation dose and iodine contrast dose, while maintaining good image quality and providing strong confidence for the diagnosis of lung cancer.

Improving image quality and lung nodule detection for low-dose chest CT by using generative adversarial network reconstruction

OBJECTIVES

To investigate the improvement of two denoising models with different learning targets (Dir and Res) of generative adversarial network (GAN) on image quality and lung nodule detectability in chest low-dose CT (LDCT).

METHODS

In training phase, by using LDCT images simulated from standard dose CT (SDCT) of 200 participants, Dir model was trained targeting SDCT images, while Res model targeting the residual between SDCT and LDCT images. In testing phase, a phantom and 95 chest LDCT, exclusively with training data, were included for evaluation of imaging quality and pulmonary nodules detectability.

RESULTS

For phantom images, structural similarity, peak signal-to-noise ratio of both Res and Dir models were higher than that of LDCT. Standard deviation of Res model was the lowest. For patient images, image noise and quality of both two models, were better than that of LDCT. Artifacts of Res model was less than that of LDCT. The diagnostic sensitivity of lung nodule by two readers for LDCT, Res and Dir model, were 72/77%, 79/83% and 72/79% respectively.

CONCLUSION

Two GAN denoising models, including Res and Dir trained with different targets, could effectively reduce image noise of chest LDCT. The image quality evaluation scoring and nodule detectability of Res denoising model was better than that of Dir denoising model and that of hybrid IR images.

ADVANCES IN KNOWLEDGE

The GAN-trained model, which learned the residual between SDCT and LDCT images, reduced image noise and increased the lung nodule detectability by radiologists on chest LDCT. This demonstrates the potential for clinical benefit.

The Actual Role of Iterative Reconstruction Algorithm Methods in Several Saudi Hospitals As A Tool For Radiation Dose Minimization of Ct Scan Examinations

Background

Iterative reconstruction algorithm (IR) techniques were developed to maintain a lower radiation dose for patients as much as possible while achieving the required image quality and medical benefits. The main purpose of the current research was to assess the level and usage extent of IR techniques in computed tomographic (CT) scan exams. Also, the obligation of practitioners in several hospitals in Saudi Arabia to implement IR in CT exams was assessed.

Material and Methodology

The recent research was based on two studies: data collection and a survey study. Data on the CT scan examinations were retrospectively collected from CT scanners. The survey was conducted using a questionnaire to evaluate radiographers’ and radiologists’ perceptions about IR and their practices with IR techniques. The statistical analysis results were performed to measure the usage strength level of IR methods.

Results and Discussions

The IR strength level of 50% was selected for nearly 80% of different CT examinations and patients of different ages and weights. About 46% of the participants had not learned about IR methods during their college studies, and 54% had not received formal training in applying IR techniques. Only 32% of the participants had adequate experience with IR. Half of the participants were not involved in the updating process of the CT protocol.

Conclusion

The results indicate that the majority of radiographer and radiologist at four different hospitals in Saudi Arabia have no explicit or understandable knowledge of selecting IR strength levels during the CT examination of patients. There is a need for more training in IR applications for both radiologists and radiographers. Training sessions were suggested to support radiographers and radiologists to efficiently utilize IR techniques to optimize image quality. Further studies are required to adjust CT exam protocols effectively to utilize the IR technique.

Performance of a deep learning-based CT image denoising method: Generalizability over dose, reconstruction kernel and slice thickness

PURPOSE

Deep learning (DL) is rapidly finding applications in low-dose CT image denoising. While having the potential to improve image quality (IQ) over the filtered back projection method (FBP) and produce images quickly, performance generalizability of the data-driven DL methods is not fully understood yet. The main purpose of this work is to investigate the performance generalizability of a low-dose CT image denoising neural network in data acquired under different scan conditions, particularly relating to these three parameters: reconstruction kernel, slice thickness and dose (noise) level. A secondary goal is to identify any underlying data property associated with the CT scan settings that might help predict the generalizability of the denoising network.

METHODS

We select the residual encoder-decoder convolutional neural network (REDCNN) as an example of a low-dose CT image denoising technique in this work. To study how the network generalizes on the three imaging parameters, we grouped the CT volumes in the Low-Dose Grand Challenge (LDGC) data into three pairs of training datasets according to their imaging parameters, changing only one parameter in each pair. We trained REDCNN with them to obtain six denoising models. We test each denoising model on datasets of matching and mismatching parameters with respect to its training sets regarding dose, reconstruction kernel and slice thickness, respectively, to evaluate the denoising performance changes. Denoising performances are evaluated on patient scans, simulated phantom scans and physical phantom scans using IQ metrics including mean squared error (MSE), contrast-dependent modulation transfer function (MTF), pixel-level noise power spectrum (pNPS) and low-contrast lesion detectability (LCD).

RESULTS

REDCNN had larger MSE when the testing data was different from the training data in reconstruction kernel, but no significant MSE difference when varying slice thickness in the testing data. REDCNN trained with quarter-dose data had slightly worse MSE in denoising higher-dose images than that trained with mixed-dose data (17-80%). The MTF tests showed that REDCNN trained with the two reconstruction kernels and slice thicknesses yielded images of similar image resolution. However, REDCNN trained with mixed-dose data preserved the low-contrast resolution better compared to REDCNN trained with quarter-dose data. In the pNPS test, it was found that REDCNN trained with smooth-kernel data could not remove high-frequency noise in the test data of sharp kernel, possibly because the lack of high-frequency noise in the smooth-kernel data limited the ability of the trained model in removing high-frequency noise. Finally, in the LCD test, REDCNN improved the lesion detectability over the original FBP images regardless of whether the training and testing data had matching reconstruction kernels.

CONCLUSIONS

REDCNN is observed to be poorly generalizable between reconstruction kernels, more robust in denoising data of arbitrary dose levels when trained with mixed-dose data, and not highly sensitive to slice thickness. It is known that reconstruction kernel affects the in-plane pNPS shape of a CT image whereas slice thickness and dose level do not, so it is possible that the generalizability performance of this CT image denoising network highly correlates to the pNPS similarity between the testing and training data. This article is protected by copyright. All rights reserved.

The investigation of dose and image quality of chest computed tomography using different combinations of noise index and adaptive statistic iterative reconstruction level

Background

Computed tomography (CT) automatic tube current modulation (ATCM) systems and iterative reconstruction (IR) play an important role in CT radiation dose optimization. How the two can best be used together is one of the challenges faced by radiology professionals.

Aim

To determine optimum settings of ATCM noise index (NI) together with adaptive statistic iterative reconstruction (ASIR) for a general electric (GE) scanner that aims to achieve similar image quality to the standard protocol used in the hospital (Smart mA technique with NI of 11.57 and 30% ASIR reconstruction) with a lower dose.

Methods

Different NI and ASIR levels were set for scans of a phantom. Objective image quality assessments in terms of noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), low-contrast detectability (LCD), and modulation transfer function (MTF) were carried out in an anthropomorphic chest and a Catphan 700 phantom. Subjective image quality assessment was also performed with five readers to confirm whether the image quality of the new protocols was adequate.

Result and Conclusion

SNR and CNR increased with the strength of ASIR, and decreased with higher NI settings. The MTF improved slightly for higher dose levels and from filtered back projection (FBP) to higher strength of ASIR. LCD improved with ASIR compared to FBP and with higher strengths of ASIR. Qualitative scoring ranged between 3.0 and 4.6. A moderate degree of reliability was found between scoring. Use of NI 15.04 with 70% ASIR can reduce dose by 41% compared to the standard protocol of NI 11.57 with 30% ASIR without degradation of image quality.

Ultra-low-dose thoracic CT with model-based iterative reconstruction (MBIR) in cystic fibrosis patients undergoing treatment with cystic fibrosis transmembrane conductance regulators (CFTR)

AIM

To assess the utility of a volumetric low-dose computed tomography (CT) thorax (LDCTT) protocol at a dose equivalent to a posteroanterior (PA) and lateral chest radiograph for surveillance of cystic fibrosis (CF) patients.

MATERIALS AND METHODS

A prospective study was undertaken of 19 adult patients with CF that proceeded to LDCTT at 12 and 24 months following initiation of ivacaftor. A previously validated seven-section, low-dose axial CT protocol was used for the 12-month study. A volumetric LDCTT protocol was developed for the 24-month study and reconstructed with hybrid iterative reconstruction (LD-ASIR) and pure iterative reconstruction (model-based IR [LD-MBIR]). Radiation dose was recorded for each scan. Image quality was assessed quantitatively and qualitatively, and disease severity was assessed using a modified Bhalla score. Statistical analysis was performed and p-values of <0.05 were considered statistically significant.

RESULTS

Volumetric LD-MBIR studies were acquired at a lower radiation dose than the seven-section studies (0.08 ± 0.01 versus 0.10 ± 0.02 mSv; p=0.02). LD-MBIR and seven-section ASIR images had significantly lower levels of image noise compared with LD-ASIR images (p<0.0001). Diagnostic acceptability scores and depiction of bronchovascular structures were found to be acceptable for axial and coronal LD-MBIR images. LD-MBIR images were superior to LD-ASIR images for all qualitative parameters assessed (p<0.0001). No significant change was observed in mean Bhalla score between 1-year and 2-year studies (p=0.84).

CONCLUSIONS

The use of a volumetric LDCTT protocol (reconstructed with pure IR) enabled acquisition of diagnostic quality CT images, which were considered extremely useful for surveillance of CF patients, at a dose equivalent to a PA and lateral chest radiograph.

Reducing Radiation Dose and Improving Image Quality in CT Portal Venography Using 80 kV and Adaptive Statistical Iterative Reconstruction-V in Slender Patients

OBJECTIVE

To explore the feasibility of reducing radiation dose and improving image quality in CT portal venography (CTPV) using 80 kV and adaptive statistical iterative reconstruction-V(ASIR-V) in slender patients in comparison with conventional protocol using 120 kV and ASIR.

METHODS

Sixty slender patients for enhanced abdominal CT scanning were randomly divided into group A and group B. Group A used the conventional 120 kV tube voltage, 600 mgI/kg contrast dose and reconstructed with the recommended 40% ASIR. Group B used 80 kV tube voltage, 350 mgI/kg contrast dose and reconstructed with ASIR-V from 40% to 100% with 10% interval. The CT values and standard deviation (SD) values of the main portal vein, left branch, and right branch of portal vein, liver, and erector spinae at the same level were measured to calculate the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The image quality was subjectively scored by two experienced radiologists blindly using a 5-point criterion. The contrast dose, volumetric CT dose index, and dose length product were recorded in both groups and the effective dose was calculated.

RESULTS

There was no significant difference in general data between the two groups (p > 0.05), the effective dose and contrast dose in group B were reduced by 63.3% (p < 0.001) and 39.7% (p < 0.001), respectively compared with group A. With the percentage of ASIR-V increased in group B, the CT values showed no significant difference, while the SD values gradually decreased and SNR values and CNR values increased accordingly. Compared with group A, group B demonstrated similar CT values (p > 0.05), while the SD values with 80% ASIR-V to 100% ASIR-V were significantly lower than those of 40% ASIR (p < 0.001), and the SNR values and CNR values with 70% ASIR-V to 100% ASIR-V were significantly higher than those of 40% ASIR (p < 0.001). The subjective image quality scores by the two radiologists had excellent consistency (kappa value>0.75, p < 0.001), and the final subjective image quality scores and the subjective scores in each of the 5 scoring categories with 60% ASIR-V to 100% ASIR-V were all significantly higher than those of 40% ASIR, and 80% ASIR-V obtained the highest subjective score among different reconstructions.

CONCLUSION

In CTPV, the application of 80 kV and ASIR-V reconstruction in slender patients can significantly reduce radiation dose (by 63.3%) and contrast agent dose (by 39.7%). Compared with the recommended 40% ASIR using 120 kV, ASIR-V with 80% to 100% percentages can further improve image quality and with 80% ASIR-V being the best reconstruction algorithm.

ADVANCES IN KNOWLEDGE

CTPV with 80 kV and ASIR-V algorithm in slender patients can significantly reduce radiation dose and contrast agent dose as well as improve image quality, compared with the conventional 120 kV protocol using 40% ASIR.

Ultra-low-dose chest computed tomography without anesthesia in the assessment of pediatric pulmonary diseases

OBJECTIVE

To evaluate the feasibility of using ultra-low-dose computed tomography of the chest with iterative reconstruction without anesthesia for assessment of pulmonary diseases in children.

METHODS

This prospective study enrolled 86 consecutive pediatric patients (ranging from 1 month to 18 years) that underwent ultra-low-dose computed tomography due to suspicion of pulmonary diseases, without anesthesia and contrast. Parameters used were: 80kVp; 15-30mA; acquisition time, 0.5s; and pitch, 1.375. The adaptive statistical iterative reconstruction technique was used. Subjective visual evaluation and quantitative assessment of image quality were done using a 5-point scale in 12 different structures of the chest.

RESULTS

Mean age was 66 months (interquartile range, 16-147). Final diagnosis was performed in all exams, and 44 (51.2%) were diagnosed with cystic fibrosis, 27 (31.4%) with bronchiolitis obliterans, and 15 (17.4%) with congenital pulmonary airways malformations. Diagnostic quality was achieved in 98.9%, of which 82.6% were considered excellent and 16.3% were slightly blurred but did not interfere with image evaluation. Only one case (1.2%) presented moderate blurring that slightly compromised the image, and previous examinations demonstrated findings compatible with bronchiolitis obliterans. Mean effective radiation dose was 0.39±0.15mSv. Percentages of images with motion artifacts were 0.3% for cystic fibrosis, 1.3% for bronchiolitis obliterans, and 1.1% for congenital pulmonary airways malformations.

CONCLUSION

Chest ultra-low-dose computed tomography without sedation or anesthesia delivering a sub-millisievert dose can provide image quality to allow identification of common pulmonary anatomy and diseases.

Application of Adaptive Statistical Iterative Reconstruction-V With Combination of 80 kV for Reducing Radiation Dose and Improving Image Quality in Renal Computed Tomography Angiography for Slim Patients

OBJECTIVES

To explore the application of adaptive statistical iterative reconstruction-V (ASIR-V) with combination of 80 kV for reducing radiation dose and improving image quality in renal computed tomography angiography (CTA) for slim patients compared with traditional filtered back projection (FBP) reconstruction using 120 kV.

METHODS

Eighty patients for renal CTA were prospectively enrolled and randomly divided into group A and group B. Group A used 120 kV and 600 mgI/kg contrast agent and FBP reconstruction, while group B used 80 kV and 350 mgI/kg contrast agent and both FBP and ASIR-V reconstruction from 10%ASIR-V to 100%ASIR-V with 10%ASIR-V interval. The CT values and SD values of the right renal artery and left renal artery were measured to calculate the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The image quality was subjectively scored by two experienced radiologists blindly using a five-point criterion. The contrast agent, volumetric CT dose index (CTDI_vol), and dose length product in both groups were recorded and the effective radiation dose was calculated.

RESULTS

There were no significant difference in patient characteristics between two groups (p > 0.05). The CTDI_vol, dose length product and effective radiation dose in group B were 59.0%, 65.0%, and 65.1% lower than those in group A, respectively (all p < 0.05), and the contrast agent in group B was 42.2% lower than that in group A (p < 0.05). In group B, with the increase of ASIR-V percentage, CT values showed no significant difference, SD values decreased gradually, SNR values and CNR values increased gradually. The CT values showed no statistically significant difference (p > 0.05) between two groups with different reconstructions. The SD values with 40%ASIR-V to 100%ASIR-V reconstruction in group B was significantly lower(p < 0.5), while the SNR values with 50% ASIR-V to 100% ASIR-V reconstruction and CNR values with 70%ASIR-V to 100%ASIR-V were significantly higher than those of group A with FBP reconstruction (p < 0.5). Two radiologists had excellent consistency in subjective scores of image quality for renal CTA (kappa >0.75, p < 0.05). The subjective scores with 60% ASIR-V to 90% ASIR-V in group B were significantly higher than those of FBP in group A (p < 0.5), of which 70%ASIR-V reconstruction obtained the highest subjective score for renal CTA.

CONCLUSION

ASIR-V with combination of 80 kV can significantly reduce effective radiation dose (about 65.1%) and contrast agent (about 42.2%) and improve image quality in renal CTA for slim patients compared with traditional FBP reconstruction using 120 kV, and the 70% ASIR-V was the best reconstruction algorithm in 80 kV renal CTA.

ADVANCES IN KNOWLEDGE

Using 80 kV with combination of ASIR-V can significantly reduce radiation dose and contrast agent dose as well as improve image quality in renal CTA for thin patients when compared with FBP using 120 kV.

Predictors of Initial Smear-Negative Active Pulmonary Tuberculosis with Acute Early Stage Lung Injury by High-Resolution Computed Tomography and Clinical Manifestations: An Auxiliary Model in Critical Patients

This study evaluated the diagnostic use of high-resolution computed tomography (HRCT), chest X-ray (CXR), and clinical manifestations (CM) to identify initial smear-negative (iSN) active pulmonary tuberculosis (aPTB) [iSN-aPTB] in patients with iSN-pulmonary diseases (PD) and acute lung injury (ALI). In the derivation cohort, the [iSN-PD] with ALI patients were divided into the [iSN-aPTB] (G1, n = 26) and [non-aPTB-PD] (G2, n = 233) groups. Lung morphology, number, and lobar (segmental) distribution were evaluated using CXR and HRCT. A multivariate analysis was performed to identify independent variables associated with G1, which were used to generate predictive score models for G1. The predictive model was validated in a separate population of patients (n = 372) with [iSN-PD] and (ALI). The validated model for [HRCT (CXR + Hypoalbuminemia)] had 93.5% (25.8%) sensitivity, 99.5% (89.4%) specificity, and a negative predictive value of 99.5% (93.0%). For [iSN-aPTB], the post-test probability in the derivation cohort (prevalence = 10%), validation cohort (prevalence = 8.3%), and the given prevalence (prevalence = 1%) was 88.7%, 94.4%, and 41.5%, respectively. The HRCT model effectively identified the [iSN-aPTB] subjects among the [iSN-PD] with ALI, regardless of CM. The [non-aPTB-PD] were also correctly classified by the HRCT and [CXR + Hypoalbuminemia] models.

CT automated exposure control using a generalized detectability index

PURPOSE

Identifying an appropriate tube current setting can be challenging when using iterative reconstruction due to the varying relationship between spatial resolution, contrast, noise, and dose across different algorithms. This study developed and investigated the application of a generalized detectability index ( d gen ' ) to determine the noise parameter to input to existing automated exposure control (AEC) systems to provide consistent image quality (IQ) across different reconstruction approaches.

METHODS

This study proposes a task-based automated exposure control (AEC) method using a generalized detectability index ( d gen ' ). The proposed method leverages existing AEC methods that are based on a prescribed noise level. The generalized d gen ' metric is calculated using lookup tables of task-based modulation transfer function (MTF) and noise power spectrum (NPS). To generate the lookup tables, the American College of Radiology CT accreditation phantom was scanned on a multidetector CT scanner (Revolution CT, GE Healthcare) at 120 kV and tube current varied manually from 20 to 240 mAs. Images were reconstructed using a reference reconstruction algorithm and four levels of an in-house iterative reconstruction algorithm with different regularization strengths (IR1-IR4). The task-based MTF and NPS were estimated from the measured images to create lookup tables of scaling factors that convert between d gen ' and noise standard deviation. The performance of the proposed d gen ' -AEC method in providing a desired IQ level over a range of iterative reconstruction algorithms was evaluated using the American College of Radiology (ACR) phantom with elliptical shell and using a human reader evaluation on anthropomorphic phantom images.

RESULTS

The study of the ACR phantom with elliptical shell demonstrated reasonable agreement between the d gen ' predicted by the lookup table and d ' measured in the images, with a mean absolute error of 15% across all dose levels and maximum error of 45% at the lowest dose level with the elliptical shell. For the anthropomorphic phantom study, the mean reader scores for images resulting from the d gen ' -AEC method were 3.3 (reference image), 3.5 (IR1), 3.6 (IR2), 3.5 (IR3), and 2.2 (IR4). When using the d gen ' -AEC method, the observers' IQ scores for the reference reconstruction were statistical equivalent to the scores for IR1, IR2, and IR3 iterative reconstructions (P > 0.35). The d gen ' -AEC method achieved this equivalent IQ at lower dose for the IR scans compared to the reference scans.

CONCLUSIONS

A novel AEC method, based on a generalized detectability index, was investigated. The proposed method can be used with some existing AEC systems to derive the tube current profile for iterative reconstruction algorithms. The results provide preliminary evidence that the proposed d gen ' -AEC can produce similar IQ across different iterative reconstruction approaches at different dose levels.

Assessment of noise reduction potential and image quality improvement of a new generation adaptive statistical iterative reconstruction (ASIR-V) in chest CT

OBJECTIVE

To evaluate the image quality improvement and noise reduction in routine dose, non-enhanced chest CT imaging by using a new generation adaptive statistical iterative reconstruction (ASIR-V) in comparison with ASIR algorithm.

METHODS

30 patients who underwent routine dose, non-enhanced chest CT using GE Discovery CT750HU (GE Healthcare, Waukesha, WI) were included. The scan parameters included tube voltage of 120 kVp, automatic tube current modulation to obtain a noise index of 14HU, rotation speed of 0.6 s, pitch of 1.375:1 and slice thickness of 5 mm. After scanning, all scans were reconstructed with the recommended level of 40%ASIR for comparison purpose and different percentages of ASIR-V from 10% to 100% in a 10% increment. The CT attenuation values and SD of the subcutaneous fat, back muscle and descending aorta were measured at the level of tracheal carina of all reconstructed images. The signal-to-noise ratio (SNR) was calculated with SD representing image noise. The subjective image quality was independently evaluated by two experienced radiologists.

RESULTS

For all ASIR-V images, the objective image noise (SD) of fat, muscle and aorta decreased and SNR increased along with increasing ASIR-V percentage. The SD of 30% ASIR-V to 100% ASIR-V was significantly lower than that of 40% ASIR (p < 0.05). In terms of subjective image evaluation, all ASIR-V reconstructions had good diagnostic acceptability. However, the 50% ASIR-V to 70% ASIR-V series showed significantly superior visibility of small structures when compared with the 40% ASIR and ASIR-V of other percentages (p < 0.05), and 60% ASIR-V was the best series of all ASIR-V images, with a highest subjective image quality. The image sharpness was significantly decreased in images reconstructed by 80% ASIR-V and higher.

CONCLUSION

In routine dose, non-enhanced chest CT, ASIR-V shows greater potential in reducing image noise and artefacts and maintaining image sharpness when compared to the recommended level of 40%ASIR algorithm. Combining both the objective and subjective evaluation of images, non-enhanced chest CT images reconstructed with 60% ASIR-V have the highest image quality. Advances in knowledge: This is the first clinical study to evaluate the clinical value of ASIR-V in the same patients using the same CT scanner in the non-enhanced chest CT scans. It suggests that ASIR-V provides the better image quality and higher diagnostic confidence in comparison with ASIR algorithm.

Use of pulmonary CT angiography with low tube voltage and low-iodine-concentration contrast agent to diagnose pulmonary embolism

Pulmonary CT angiography (CTPA) is regarded as the preferred imaging method in diagnosing pulmonary embolism (PE). Considering the harm of radiation exposure and the side effect of iodinated contrast agent, CTPA protocol with low tube voltage and low dose of contrast agent became research hotspot in last decade. The present study evaluates the image quality, radiation dose, positive rate of PE and the location of PE with a CTPA protocol using low tube voltage (80 kVp) and low-iodine-concentration contrast agent (270 mg I/ml) in patients suspected of PE compared to a conventional CTPA protocol (120 kVp, 350 mg I/ml). The results showed that 80 kVp CTPA protocol with 40 ml 270 mg I/ml achieved equally subjective image quality and a positive rate for diagnosing PE, though the quantitative image quality was reduced compared to the 120 kVp CTPA protocol with 40 ml 350 mg I/ml administered, with a 63.6% decrease in radiation dose and a 22.9% reduction in iodine content of contrast agent. Our results document that CTPA protocol with low tube voltage and low iodine concentration of contrast agent is satisfied to the clinical application.

Ultra-low-dose chest CT with iterative reconstruction does not alter anatomical image quality

PURPOSE

To evaluate the effect of dose reduction with iterative reconstruction (IR) on image quality of chest CT scan.

MATERIALS AND METHODS

Eighteen human cadavers had chest CT with one reference CT protocol (RP-CT; 120kVp/200mAs) and two protocols with dose reduction: low-dose-CT (LD-CT; 120kVp/40mAs) and ultra-low-dose CT (ULD-CT; 120kVp/10mAs). Data were reconstructed with filter-back-projection (FBP) for RP-CT and with FBP and IR (sinogram affirmed iterative reconstruction [SAFIRE^®]) algorithm for LD-CT and ULD-CT. Volume CT dose index (CTDIvol) were recorded. The signal-to-noise (SNR), contrast-to-noise (CNR) ratios of LD-CT and ULD-CT and quantitative parameters were compared to RP-CT. Two radiologists reviewed the CT examinations assessed independently the quality of anatomical structures and expressed a confidence level using a 2-point scale (50% and 95%).

RESULTS

CTDIvol was 2.69 mGy for LD-CT (-80%; P<0.01) and 0.67 mGy for ULD-CT (-95%; P<0.01) as compared to 13.42 mGy for RP-CT. SNR and CNR were significantly decreased (P<0.01) for LD-CT and ULD-CT, but IR improved these values satisfactorily. No significant differences were observed for quantitative measurements. Radiologists rated excellent/good the RP-CT and LD-CT images, whereas good/fair the ULD-CT images. Confidence level for subjective anatomical analysis was 95% for all protocols.

CONCLUSIONS

Dose reduction with a dose lower than 1 mGy, used in conjunction with IR allows performing chest CT examinations that provide a high quality of anatomical structures.

Effect of reconstruction methods and x-ray tube current-time product on nodule detection in an anthropomorphic thorax phantom: A crossed-modality JAFROC observer study

Purpose:

To evaluate nodule detection in an anthropomorphic chest phantom in computed tomography (CT) images reconstructed with adaptive iterative dose reduction 3D (AIDR^3D) and filtered back projection (FBP) over a range of tube current–time product (mAs).

Methods:

Two phantoms were used in this study: (i) an anthropomorphic chest phantom was loaded with spherical simulated nodules of 5, 8, 10, and 12 mm in diameter and +100, −630, and −800 Hounsfield units electron density; this would generate CT images for the observer study; (ii) a whole-body dosimetry verification phantom was used to ultimately estimate effective dose and risk according to the model of the BEIR VII committee. Both phantoms were scanned over a mAs range (10, 20, 30, and 40), while all other acquisition parameters remained constant. Images were reconstructed with both AIDR^3D and FBP. For the observer study, 34 normal cases (no nodules) and 34 abnormal cases (containing 1–3 nodules, mean 1.35 ± 0.54) were chosen. Eleven observers evaluated images from all mAs and reconstruction methods under the free-response paradigm. A crossed-modality jackknife alternative free-response operating characteristic (JAFROC) analysis method was developed for data analysis, averaging data over the two factors influencing nodule detection in this study: mAs and image reconstruction (AIDR^3D or FBP). A Bonferroni correction was applied and the threshold for declaring significance was set at 0.025 to maintain the overall probability of Type I error at α = 0.05. Contrast-to-noise (CNR) was also measured for all nodules and evaluated by a linear least squares analysis.

Results:

For random-reader fixed-case crossed-modality JAFROC analysis, there was no significant difference in nodule detection between AIDR^3D and FBP when data were averaged over mAs [F(1, 10) = 0.08, p = 0.789]. However, when data were averaged over reconstruction methods, a significant difference was seen between multiple pairs of mAs settings [F(3, 30) = 15.96, p < 0.001]. Measurements of effective dose and effective risk showed the expected linear dependence on mAs. Nodule CNR was statistically higher for simulated nodules on images reconstructed with AIDR^3D (p < 0.001).

Conclusions:

No significant difference in nodule detection performance was demonstrated between images reconstructed with FBP and AIDR^3D. mAs was found to influence nodule detection, though further work is required for dose optimization.

Computed tomography in trauma patients using iterative reconstruction: reducing radiation exposure without loss of image quality

BACKGROUND

Rising numbers of computed tomography (CT) examinations worldwide have led to a focus on dose reduction in the latest developments in CT technology. Iterative reconstruction (IR) models bear the potential to effectively reduce dose while maintaining adequate image quality.

PURPOSE

To assess the impact of adaptive statistical iterative reconstruction (ASIR) technique on dose reduction and image quality in a dedicated whole body CT (WBCT) protocol for trauma patients.

MATERIAL AND METHODS

A total of 122 subjects with multiple trauma was prospectively included in our study. Subjects who had to undergo a WBCT following a severe trauma were randomly assigned to two different groups: Group A was examined with an ASIR protocol for the body series (n = 64), group B (n = 58) was examined using a standard filtered back projection (FBP) protocol. Image quality was assessed both quantitatively by calculating signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNRs) and qualitatively by two observers who evaluated image quality using a 5-point scale system. Applied dose was analyzed as CTDIvol (mGy), total DLP (mGyxcm), and effective dose (mSv).

RESULTS

Applied dose for the body series in group A was about 23% lower than in group B (P < 0.05). SNR and CNRs for different tissues were not significantly different. Subjective image quality ratings were excellent and showed no significant difference, with a high inter-reader agreement.

CONCLUSION

ASIR contributes to a relevant dose reduction without any loss of image quality in a dedicated WBCT protocol for patients with multiple trauma.

A pilot study using low-dose Spectral CT and ASIR (Adaptive Statistical Iterative Reconstruction) algorithm to diagnose solitary pulmonary nodules

BACKGROUND

Lung cancer is the most common cancer which has the highest mortality rate. With the development of computed tomography (CT) techniques, the case detection rates of solitary pulmonary nodules (SPN) has constantly increased and the diagnosis accuracy of SPN has remained a hot topic in clinical and imaging diagnosis. The aim of this study was to evaluate the combination of low-dose spectral CT and ASIR (Adaptive Statistical Iterative Reconstruction) algorithm in the diagnosis of solitary pulmonary nodules (SPN).

METHODS

62 patients with SPN (42 cases of benign SPN and 20 cases of malignant SPN, pathology confirmed) were scanned by spectral CT with a dual-phase contrast-enhanced method. The iodine and water concentration (IC and WC) of the lesion and the artery in the image that had the same density were measured by the GSI (Gemstone Spectral Imaging) software. The normalized iodine and water concentration (NIC and NWC) of the lesion and the normalized iodine and water concentration difference (ICD and WCD) between the arterial and venous phases (AP and VP) were also calculated. The spectral HU (Hounsfield Unit ) curve was divided into 3 sections based on the energy (40-70, 70-100 and 100-140 keV) and the slopes (λHU) in both phases were calculated. The ICAP, ICVP, WCAP and WCVP, NIC and NWC, and the λHU in benign and malignant SPN were compared by independent sample t-test.

RESULTS

The iodine related parameters (ICAP, ICVP, NICAP, NICVP, and the ICD) of malignant SPN were significantly higher than that of benign SPN (t = 3.310, 1.330, 2.388, 1.669 and 3.251, respectively, P <0.05). The 3 λHU values of venous phase in malignant SPN were higher than that of benign SPN (t = 3.803, 2.846 and 3.205, P <0.05). The difference of water related parameters (WCAP, WCVP, NWCAP, NWCVP and WCD) between malignant and benign SPN were not significant (t = 0.666, 0.257, 0.104, 0.550 and 0.585, P > 0.05).

CONCLUSIONS

The iodine related parameters and the slope of spectral curve are useful markers to distinguish the benign from the malignant lung diseases, and its application is extremely feasible in clinical applications.

The Impact of Iterative Reconstruction on Computed Tomography Radiation Dosimetry: Evaluation in a Routine Clinical Setting

Purpose

To evaluate the effect of introduction of iterative reconstruction as a mandated software upgrade on radiation dosimetry in routine clinical practice over a range of computed tomography examinations.

Methods

Random samples of scanning data were extracted from a centralised Picture Archiving Communication System pertaining to 10 commonly performed computed tomography examination types undertaken at two hospitals in Western Australia, before and after the introduction of iterative reconstruction. Changes in the mean dose length product and effective dose were evaluated along with estimations of associated changes to annual cancer incidence.

Results

We observed statistically significant reductions in the effective radiation dose for head computed tomography (22–27%) consistent with those reported in the literature. In contrast the reductions observed for non-contrast chest (37–47%); chest pulmonary embolism study (28%), chest/abdominal/pelvic study (16%) and thoracic spine (39%) computed tomography. Statistically significant reductions in radiation dose were not identified in angiographic computed tomography. Dose reductions translated to substantial lowering of the lifetime attributable risk, especially for younger females, and estimated numbers of incident cancers.

Conclusion

Reduction of CT dose is a priority Iterative reconstruction algorithms have the potential to significantly assist with dose reduction across a range of protocols. However, this reduction in dose is achieved via reductions in image noise. Fully realising the potential dose reduction of iterative reconstruction requires the adjustment of image factors and forgoing the noise reduction potential of the iterative algorithm. Our study has demonstrated a reduction in radiation dose for some scanning protocols, but not to the extent experimental studies had previously shown or in all protocols expected, raising questions about the extent to which iterative reconstruction achieves dose reduction in real world clinical practice.

Achievable dose reduction using iterative reconstruction for chest computed tomography: A systematic review

OBJECTIVES

Iterative reconstruction (IR) allows for dose reduction with maintained image quality in CT imaging. In this systematic review the reported effective dose reductions for chest CT and the effects on image quality are investigated.

METHODS

A systematic search in PubMed and EMBASE was performed. Primary outcome was the reported local reference and reduced effective dose and secondary outcome was the image quality with IR. Both non contrast-enhanced and enhanced studies comparing reference dose with reduced dose were included.

RESULTS

24 studies were included. The median number of patients per study was 66 (range 23-200) with in total 1806 patients. The median reported local reference dose of contrast-enhanced chest CT with FBP was 2.6 (range 1.5-21.8) mSv. This decreased to 1.4 (range 0.4-7.3) mSv at reduced dose levels using IR. With non contrast-enhanced chest CT the dose decreased from 3.4 (range 0.7-7.8) mSv to 0.9 (range 0.1-4.5) mSv. Objective mage quality and diagnostic confidence and acceptability remained the same or improved with IR compared to FBP in most studies while data on diagnostic accuracy was limited.

CONCLUSION

Radiation dose can be reduced to less than 2 mSv for contrast-enhanced chest CT and non contrast-enhanced chest CT is possible at a submillisievert dose using IR algorithms.

How low can we go in contrast-enhanced CT imaging of the chest?: A dose-finding cadaver study using the model-based iterative image reconstruction approach

RATIONALE AND OBJECTIVES

Dose reduction may compromise patients because of a decrease of image quality. Therefore, the amount of dose savings in new dose-reduction techniques needs to be thoroughly assessed. To avoid repeated studies in one patient, chest computed tomography (CT) scans with different dose levels were performed in corpses comparing model-based iterative reconstruction (MBIR) as a tool to enhance image quality with current standard full-dose imaging.

MATERIALS AND METHODS

Twenty-five human cadavers were scanned (CT HD750) after contrast medium injection at different, decreasing dose levels D0-D5 and respectively reconstructed with MBIR. The data at full-dose level, D0, have been additionally reconstructed with standard adaptive statistical iterative reconstruction (ASIR), which represented the full-dose baseline reference (FDBR). Two radiologists independently compared image quality (IQ) in 3-mm multiplanar reformations for soft-tissue evaluation of D0-D5 to FDBR (-2, diagnostically inferior; -1, inferior; 0, equal; +1, superior; and +2, diagnostically superior). For statistical analysis, the intraclass correlation coefficient (ICC) and the Wilcoxon test were used.

RESULTS

Mean CT dose index values (mGy) were as follows: D0/FDBR = 10.1 ± 1.7, D1 = 6.2 ± 2.8, D2 = 5.7 ± 2.7, D3 = 3.5 ± 1.9, D4 = 1.8 ± 1.0, and D5 = 0.9 ± 0.5. Mean IQ ratings were as follows: D0 = +1.8 ± 0.2, D1 = +1.5 ± 0.3, D2 = +1.1 ± 0.3, D3 = +0.7 ± 0.5, D4 = +0.1 ± 0.5, and D5 = -1.2 ± 0.5. All values demonstrated a significant difference to baseline (P < .05), except mean IQ for D4 (P = .61). ICC was 0.91.

CONCLUSIONS

Compared to ASIR, MBIR allowed for a significant dose reduction of 82% without impairment of IQ. This resulted in a calculated mean effective dose below 1 mSv.

Task-based measures of image quality and their relation to radiation dose and patient risk

The theory of task-based assessment of image quality is reviewed in the context of imaging with ionizing radiation, and objective figures of merit (FOMs) for image quality are summarized. The variation of the FOMs with the task, the observer and especially with the mean number of photons recorded in the image is discussed. Then various standard methods for specifying radiation dose are reviewed and related to the mean number of photons in the image and hence to image quality. Current knowledge of the relation between local radiation dose and the risk of various adverse effects is summarized, and some graphical depictions of the tradeoffs between image quality and risk are introduced. Then various dose-reduction strategies are discussed in terms of their effect on task-based measures of image quality.

70 kV computed tomography of the thorax: valence for computer-assisted nodule evaluation and radiation dose - first clinical results

BACKGROUND

Computed tomography (CT) is the gold standard for evaluation of pulmonary nodules and is at the same time responsible for the majority of the collective effective dose.

PURPOSE

To evaluate radiation dose and efficacy of computer-assisted detection (CAD) for solid pulmonary nodules in low dose chest CT performed at 70 kV.

MATERIAL AND METHODS

CAD was performed upon chest CT with 70 kV and 100 kV (gold standard) at manufacture's recommended tube current of 87 mAs (collimation, 64 × 0.6 mm). Detection rate for pulmonary nodules and size measurements of both techniques were compared to each other. Radiation dosage in terms of effective dose (E) was measured using an Alderson-Rando Phantom.

RESULTS

Seventy-four patients with 301 solid nodules were included in the study. CAD detection rate was similar for 70 kV (94.7%) and 100 kV (92.4%). Mean transversal nodule diameter was 5.5 mm for 70 kV and 5.7 mm for 100 kV with an average volume of 0.12 mL (both techniques). Derived from the phantom measurements patient examinations resulted in an E of 0.51 mSv (70 kV) versus 2.02 mSv (100 kV).

CONCLUSION

70 kV low-dose chest CT is suitable for CAD based lung nodule analysis at a fraction of the radiation burden of the standard technique. Since the measurements are highly accurate, 70 kV CT could be used for detection of pulmonal lesions as well as follow-up studies.

Reducing radiation dose in the diagnosis of pulmonary embolism using adaptive statistical iterative reconstruction and lower tube potential in computed tomography

OBJECTIVES

To assess the impact of ASIR (adaptive statistical iterative reconstruction) and lower tube potential on dose reduction and image quality in chest computed tomography angiographies (CTAs) of patients with pulmonary embolism.

MATERIALS AND METHODS

CT data from 44 patients with pulmonary embolism were acquired using different protocols-Group A: 120 kV, filtered back projection, n = 12; Group B: 120 kV, 40 % ASIR, n = 12; Group C: 100 kV, 40 % ASIR, n = 12 and Group D: 80 kV, 40 % ASIR, n = 8. Normalised effective dose was calculated; image quality was assessed quantitatively and qualitatively.

RESULTS

Normalised effective dose in Group B was 33.8 % lower than in Group A (p = 0.014) and 54.4 % lower in Group C than in Group A (p < 0.001). Group A, B and C did not show significant differences in qualitative or quantitative analysis of image quality. Group D showed significantly higher noise levels in qualitative and quantitative analysis, significantly more artefacts and decreased overall diagnosability. Best results, considering dose reduction and image quality, were achieved in Group C.

CONCLUSIONS

The combination of ASIR and lower tube potential is an option to reduce radiation without significant worsening of image quality in the diagnosis of pulmonary embolism.

KEY POINTS

• Iterative algorithms and lowering of tube potential reduce radiation without compromising interpretability • 40 % ASIR and 100 kV tube potential led to a 54.4 % dose reduction • 40 % ASIR and 80 kV tube potential led to significantly worse image quality.

Ultra low-dose chest CT using filtered back projection: comparison of 80-, 100- and 120 kVp protocols in a prospective randomized study

PURPOSE

To assess lesion detection and diagnostic image quality of filtered back projection (FBP) reconstruction technique in ultra low-dose chest CT examinations.

METHODS AND MATERIALS

In this IRB-approved ongoing prospective clinical study, 116 CT-image-series at four different radiation-doses were performed for 29 patients (age, 57-87 years; F:M - 15:12; BMI 16-32 kg/m(2)). All patients provided written-informed-consent for the acquisitions of additional ultra low-dose (ULD) series on a 256-slice MDCT (iCT, Philips Healthcare). In-addition to their clinical standard-dose chest CT (SD, 120 kV mean CTDIvol, 6 ± 1 mGy), ULD-CT was subsequently performed at three-dose-levels (0.9 mGy [120 kV]; 0.5 mGy [100 kV] and 0.2 mGy [80 kV]). Images were reconstructed with FBP (2.5mm 1.25 mm) resulting into four-stacks: SD-FBP (reference-standard), FBP0.9, FBP0.5, and FBP0.2. Four thoracic-radiologists from two-teaching-hospitals independently-evaluated data for lesion-detection and visibility-of-small-structures. Friedman's-non-parametric-test with post hoc Dunn's-test was used for data-analysis.

RESULTS

Interobserver-agreement was substantial between radiologists (k=0.6-0.8). With pooled analysis, 146-pulmonary (27-groundglass-opacities, 64-solid-lung-nodules, 7-consolidations, 27-emphysema) and 347-mediastinal/soft tissue lesions (87-mediastinal, 46-hilar, 62-axillary-lymph-nodes, and 11-mediastinal-masses) were evaluated. Compared to the SD-FBP, 100% pulmonary-lesions were seen with FBP0.9, up to 81% with FBP0.5 (missed: 4), and up to 30% with FBP0.2 images (missed:16). Compared to SD-FBP, all enlarged mediastinal-lymph-nodes were seen with FBP0.9 images. All mediastinal-masses (>2 cm, 11/11) were seen equivalent to SD-FBP images at 0.9 mGy. Across all sizes of patients, FBP0.9 images had optimal visualization for lung findings. They were optimal for mediastinal soft tissues for only non-obese patients.

CONCLUSION

Filtered-back-projection technique allows optimal lesion detection and acceptable image quality for chest-CT examinations at CDTIvol of 0.9 mGy for lung and mediastinal findings in selected sizes of patients.

What is the minimal radiation dose that can be used for detecting pleural effusion?

OBJECTIVE

The objective of our study was to assess the effect of radiation dose reduction on the detection of pleural effusions, thickening, and calcifications.

MATERIALS AND METHODS

Forty-five human cadavers (mean age at death, 60 ± 17 [SD] years; male-female ratio, 29:16; mean body mass index, 29 ± 5.7 [SD] kg/m(2)) were scanned at seven different dose levels (CT Dose Index volume [CTDIvol] = 20, 12, 10, 6, 4, 2, and 0.8 mGy) on a 128-MDCT unit (Definition FLASH). Images were reconstructed at a 3-mm slice thickness and 2-mm increment with filtered back projection (FBP) technique. Two chest radiologists independently reviewed all image series for the detection of pleural effusion, pleural calcification, and adjacent parenchymal opacification from atelectasis or consolidation. Objective image noise was measured at each dose level on the pleural effusion using ImageJ software. Data analysis was performed with the Student t test and kappa test.

RESULTS

Pleural effusions were seen in 39 of 45 cadavers on image series acquired at 2-20 mGy. Only 14 of 39 pleural effusions were identified at 0.8 mGy. Pleural effusions were not detected in 25 of 39 cadavers at 0.8 mGy because of photon starvation and increased image noise. Patient size was significantly larger in subjects with undetected pleural effusion than in those with detectable pleural effusion at 0.8 mGy (p < 0.01). Pleural calcifications and thickening (seen at 2-10 mGy images in three of three cadavers) were not identified on 0.8-mGy FBP images. On the other hand, adjacent parenchymal opacification could be assessed at all dose levels. The mean CT numbers of the pleural effusion were significantly lower on 0.8-mGy images than on images obtained at all other dose levels (-21 ± 55 [SD] vs 17.6 ± 19 HU, respectively) (p < 0.001).

CONCLUSION

Pleural effusions, thickening, and calcifications can be seen on FBP images reconstructed at a CTDIvol as low as 2 mGy (32-cm body phantom). CT at 0.8 mGy may provide suboptimal information on very small pleural effusions, pleural thickening, and calcifications.

Standard chest CT using combined automated tube potential selection and iterative reconstruction: image quality and radiation dose reduction

OBJECTIVE

To evaluate the image quality and radiation dose reduction of chest computed tomography (CT) using combined automated tube potential selection (ATPS) and iterative reconstruction (IR).

MATERIALS AND METHODS

Image quality and radiation dose were compared between conventional contrast-enhanced chest CT using 120 kVp and filtered back projection (Protocol A) and CT using ATPS and IR (Protocol B) in 43 patients.

RESULTS

The effective radiation dose was 3.6 ± 0.4 mSv for Protocol A and 2.2 ± 0.6 mSv for Protocol B (mean dose reduction, 39.7%). Protocol B showed diagnostic image quality in all patients.

CONCLUSION

ATPS and IR allows for radiation dose reduction while maintaining diagnostic image quality.

256-MDCT for evaluation of urolithiasis: iterative reconstruction allows for a significant reduction of the applied radiation dose while maintaining high subjective and objective image quality

PURPOSE

Multidetector CT (MDCT) is the established imaging modality in diagnostics of urolithiasis. The aim of iterative reconstruction (IR) is to allow for a radiation dose reduction while maintaining high image quality. This study evaluates its performance in MDCT for assessment of urolithiasis.

MATERIALS AND METHODS

Fifty-two patients underwent non-contrast abdominal MDCT. Twenty-six patients were referred to MDCT under suspicion of urolithiasis, and examined using a dose-reduced scan protocol (RDCT). Twenty-six patients, who had undergone standard-dose MDCT, served as reference for radiation dose comparison. RDCT images were reconstructed using an IR system (iDose4™, Philips Healthcare, Cleveland, OH, USA). Objective image noise (OIN) was recorded and five radiologists rated the subjective image quality independently. Radiation parameters were derived from the scan protocols.

RESULTS

The CTDIvol could be reduced by 50% to 5.8 mGy (P < 0.0001). The same reduction was achieved for DLP and effective dose to 253 ± 27 mGy*cm (P < 0.0001) and 3.9 ± 0.4 mSv (P < 0.0001). IR led to a reduction of the OIN of up to 61% compared with classic filtered back projection (FBP) (P < 0.0001). The OIN declined with increasing IR levels. RDCT with FBP showed the lowest scores of subjective image quality (2.32 ± 0.04). Mean scores improved with increasing IR levels. iDose6 was rated with the best mean score (3.66 ± 0.04).

CONCLUSION

The evaluated IR-tool and protocol may be applied to achieve a considerable radiation dose reduction in MDCT for diagnostics of urolithiasis while maintaining a confident image quality. Best image quality, suitable for evaluation of the entire abdomen concerning differential diagnoses, was achieved with iDose6.

Clinical and morphologic factors associated with suture anchor refixation of labral tears in the hip

BACKGROUND

The acetabular labrum is critical to hip function. Surgical options for treatment of a damaged labrum include removal, debridement, and refixation using suture anchors.

QUESTIONS/PURPOSES

The purpose of this study is to determine if certain patient demographic and osseous morphological factors result in increased labral damage requiring refixation.

METHODS

Data was collected prospectively from a consecutive series of 334 procedures performed from August 2010 to June 2011 for femoroacetabular impingement. Demographic data, including age, sex, and race, was collected from patient charts. Three-dimensional (3D) CT scans were reviewed to retrieve alpha angles, acetabular version, femoral version, and lateral center edge angle on the symptomatic hip.

RESULTS

In 238 (71.3%) of the procedures, the labrum required refixation using suture anchors with a mean of 2.74 anchors being used. Of males, 78.8% required suture anchors and 62.3% of females required suture anchors. Among procedures requiring suture anchors, significantly more suture anchors were used in males (2.92) than females (2.47). Regression analysis showed a positive association between alpha angle, acetabular retroversion at 1 and 2 o'clock, and the number of suture anchors used. The mean alpha angle in the cohort that required suture anchors (63.1°) was significantly greater than the cohort that did not (59.4°).

CONCLUSION

This study found femoral deformities to contribute more to labral damage than acetabular deformities and highlighted the importance of preoperative 3D CT scans. This study provides demographic and morphologic factors to review preoperatively to evaluate if extensive labral damage is present and if suture anchor refixation will be required.

Subcutaneous tissue thickness is an independent predictor of image noise in cardiac CT

BACKGROUND

Few data on the definition of simple robust parameters to predict image noise in cardiac computed tomography (CT) exist.

OBJECTIVES

To evaluate the value of a simple measure of subcutaneous tissue as a predictor of image noise in cardiac CT.

METHODS

86 patients underwent prospective ECG-gated coronary computed tomographic angiography (CTA) and coronary calcium scoring (CAC) with 120 kV and 150 mA. The image quality was objectively measured by the image noise in the aorta in the cardiac CTA, and low noise was defined as noise < 30 HU. The chest anteroposterior diameter and lateral width, the image noise in the aorta and the skin-sternum (SS) thickness were measured as predictors of cardiac CTA noise. The association of the predictors and image noise was performed by using Pearson correlation.

RESULTS

The mean radiation dose was 3.5 ± 1.5 mSv. The mean image noise in CT was 36.3 ± 8.5 HU, and the mean image noise in non-contrast scan was 17.7 ± 4.4 HU. All predictors were independently associated with cardiac CTA noise. The best predictors were SS thickness, with a correlation of 0.70 (p < 0.001), and noise in the non-contrast images, with a correlation of 0.73 (p < 0.001). When evaluating the ability to predict low image noise, the areas under the ROC curve for the non-contrast noise and for the SS thickness were 0.837 and 0.864, respectively.

CONCLUSION

Both SS thickness and CAC noise are simple accurate predictors of cardiac CTA image noise. Those parameters can be incorporated in standard CT protocols to adequately adjust radiation exposure.

Reducing Radiation Dose in Emergency CT Scans While Maintaining Equal Image Quality: Just a Promise or Reality for Severely Injured Patients?

Objective. This study aims to assess the impact of adaptive statistical iterative reconstruction (ASIR) on CT imaging quality, diagnostic interpretability, and radiation dose reduction for a proven CT acquisition protocol for total body trauma. Methods. 18 patients with multiple trauma (ISS ≥ 16) were examined either with a routine protocol (n = 6), 30% (n = 6), or 40% (n = 6) of iterative reconstruction (IR) modification in the raw data domain of the routine protocol (140 kV, collimation: 40, noise index: 15). Study groups were matched by scan range and maximal abdominal diameter. Image noise was quantitatively measured. Image contrast, image noise, and overall interpretability were evaluated by two experienced and blinded readers. The amount of radiation dose reductions was evaluated. Results. No statistically significant differences between routine and IR protocols regarding image noise, contrast, and interpretability were present. Mean effective dose for the routine protocol was 25.3 ± 2.9 mSv, 19.7 ± 5.8 mSv for the IR 30, and 17.5 ± 4.2 mSv for the IR 40 protocol, that is, 22.1% effective dose reduction for IR 30 (P = 0.093) and 30.8% effective dose reduction for IR 40 (P = 0.0203). Conclusions. IR does not reduce study interpretability in total body trauma protocols while providing a significant reduction in effective radiation dose.

Influence of sinogram affirmed iterative reconstruction of CT data on image noise characteristics and low-contrast detectability: an objective approach

Objectives

To utilize a novel objective approach combining a software phantom and an image quality metric to systematically evaluate the influence of sinogram affirmed iterative reconstruction (SAFIRE) of multidetector computed tomography (MDCT) data on image noise characteristics and low-contrast detectability (LCD).

Materials and Methods

A low-contrast and a high-contrast phantom were examined on a 128-slice scanner at different dose levels. The datasets were reconstructed using filtered back projection (FBP) and SAFIRE and virtual low-contrast lesions (-20HU) were inserted. LCD was evaluated using the multiscale structural similarity index (MS-SIM*). Image noise texture and spatial resolution were objectively evaluated.

Results

The use of SAFIRE led to an improvement of LCD for all dose levels and lesions sizes. The relative improvement of LCD was inversely related to the dose level, declining from 208%(±37%), 259%(±30%) and 309%(±35%) at 25mAs to 106%(±6%), 119%(±9%) and 123%(±8%) at 200mAs for SAFIRE filter strengths of 1, 3 and 5 (p<0.05). SAFIRE reached at least the LCD of FBP at a relative dose of 50%. There was no statistically significant difference in spatial resolution. The use of SAFIRE led to coarser image noise granularity.

Conclusion

A novel objective approach combining a software phantom and the MS-SSIM* image quality metric was used to analyze the detectability of virtual low-contrast lesions against the background of image noise as created using SAFIRE in comparison to filtered back-projection. We found, that image noise characteristics using SAFIRE at 50% dose were comparable to the use of FBP at 100% dose with respect to lesion detectability. The unfamiliar imaging appearance of iteratively reconstructed datasets may in part be explained by a different, coarser noise characteristic as demonstrated by a granulometric analysis.