Use of Model-Based Iterative Reconstruction (MBIR) in reduced-dose CT for routine follow-up of patients with malignant lymphoma: dose savings, image quality and phantom study

Image Quality and Lesion Detectability of Pancreatic Phase Thin-Slice Computed Tomography Images With a Deep Learning-Based Reconstruction Algorithm

OBJECTIVE

To evaluate the image quality and lesion detectability of pancreatic phase thin-slice computed tomography (CT) images reconstructed with a deep learning-based reconstruction (DLR) algorithm compared with filtered-back projection (FBP) and hybrid iterative reconstruction (IR) algorithms.

METHODS

Fifty-three patients who underwent dynamic contrast-enhanced CT including pancreatic phase were enrolled in this retrospective study. Pancreatic phase thin-slice (0.625 mm) images were reconstructed with each FBP, hybrid IR, and DLR. Objective image quality and signal-to-noise ratio of the pancreatic parenchyma, and contrast-to-noise ratio of pancreatic lesions were compared between the 3 reconstruction algorithms. Two radiologists independently assessed the image quality of all images. The diagnostic performance for the detection of pancreatic lesions was compared among the reconstruction algorithms using jackknife alternative free-response receiver operating characteristic analysis.

RESULTS

Deep learning-based reconstruction resulted in significantly lower image noise and higher signal-to-noise ratio and contrast-to-noise ratio than hybrid IR and FBP ( P < 0.001). Deep learning-based reconstruction also yielded significantly higher visual scores than hybrid IR and FBP ( P < 0.01). The diagnostic performance of DLR for detecting pancreatic lesions was highest for both readers, although a significant difference was found only between DLR and FBP in one reader ( P = 0.02).

CONCLUSIONS

Deep learning-based reconstruction showed improved objective and subjective image quality of pancreatic phase thin-slice CT relative to other reconstruction algorithms and has potential for improving lesion detectability.

Noise power spectrum properties of deep learning-based reconstruction and iterative reconstruction algorithms: Phantom and clinical study

PURPOSE

To compare the noise power spectrum (NPS) properties and perform a qualitative analysis of hybrid iterative reconstruction (IR), model-based IR (MBIR), and deep learning-based reconstruction (DLR) at a similar noise level in clinical study and compare these outcomes with those in phantom study.

METHODS

A Catphan phantom with an external body ring was used in the phantom study. In the clinical study, computed tomography (CT) examination data of 34 patients were reviewed. NPS was calculated from DLR, hybrid IR, and MBIR images. The noise magnitude ratio (NMR) and the central frequency ratio (CFR) were calculated from DLR, hybrid IR, and MBIR images relative to filtered back-projection images using NPS. Clinical images were independently reviewed by two radiologists.

RESULTS

In the phantom study, DLR with a mild level had a similar noise level as hybrid IR and MBIR with strong levels. In the clinical study, DLR with a mild level had a similar noise level as hybrid IR with standard and MBIR with strong levels. The NMR and CFR were 0.40 and 0.76 for DLR, 0.42 and 0.55 for hybrid IR, and 0.48 and 0.62 for MBIR. The visual inspection of the clinical DLR image was superior to that of the hybrid IR and MBIR images.

CONCLUSION

Deep learning-based reconstruction improves overall image quality with substantial noise reduction while maintaining image noise texture compared with the CT reconstruction techniques.

"Image quality evaluation of the Precise image CT deep learning reconstruction algorithm compared to Filtered Back-projection and iDose4: a phantom study at different dose levels"

PURPOSE

To characterize the performance of the Precise Image (PI) deep learning reconstruction (DLR) algorithm for abdominal Computed Tomography (CT) imaging.

METHODS

CT images of the Catphan-600 phantom (equipped with an external annulus) were acquired using an abdominal protocol at four dose levels and reconstructed using FBP, iDose⁴ (levels 2,5) and PI ('Soft Tissue' definition, levels 'Sharper','Sharp','Standard','Smooth','Smoother'). Image noise, image non-uniformity, noise power spectrum (NPS), target transfer function (TTF), detectability index (d'), CT numbers accuracy and image histograms were analyzed.

RESULTS

The behavior of the PI algorithm depended strongly on the selected level of reconstruction. The phantom analysis suggested that the PI image noise decreased linearly by varying the level of reconstruction from Sharper to Smoother, expressing a noise reduction up to 80% with respect to FBP. Additionally, the non-uniformity decreased, the histograms became narrower, and d' values increased as PI reconstruction levels changed from Sharper to Smoother. PI had no significant impact on the average CT number of different contrast objects. The conventional FBP NPS was deeply altered only by Smooth and Smoother levels of reconstruction. Furthermore, spatial resolution was found to be dose- and contrast-dependent, but in each analyzed condition it was greater than or comparable to FBP and iDose⁴ TTFs.

CONCLUSIONS

The PI algorithm can reduce image noise with respect to FBP and iDose⁴; spatial resolution, CT numbers and image uniformity are generally preserved by the algorithm but changes in NPS for the Smooth and Smoother levels need to be considered in protocols implementation.

A novel protocol for abdominal low-dose CT scans adapted with a model-based iterative reconstruction method

PURPOSE

This study aims to introduce a novel low-dose abdominal computed tomography (CT) protocol adapted with model-based iterative reconstruction (MBIR), To validate the adaptability of this protocol, objective image quality and subjective clinical scores of low-dose MBIR images are compared with the normal-dose images.

METHODS

Normal-dose abdominal CT images of 58 patients and low-dose abdominal CT images of 52 patients are reconstructed using both conventional filtered back projection (FBP) and MBIR methods with and without smooth applying. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) are used to compare image quality between the normal-dose and low-dose CT scans. CT dose indices (CTDI) of normal-dose and low-dose abdominal CT images on post-contrast venous phase are also compared.

RESULTS

The SNR, CNR and clinical score of low-dose MBIR images all show significant higher values (Bonferroni p < 0.05) than those of normal-dose images with conventional FBP method. A total of around 40% radiation dose reduction (CTDI: 5.3 vs 8.7 mGy) could be achieved via our novel abdominal CT protocol.

CONCLUSIONS

With the higher SNR/CNR and clinical scores, the low-dose CT abdominal imaging protocol with MBIR could effectively reduce the radiation for patients and provide equal or even higher image quality and also its adaptability in clinical abdominal CT image diagnosis.

The effect of computed tomography parameters on sarcopenia and myosteatosis assessment: a scoping review

Computed tomography (CT) is a valuable assessment method for muscle pathologies such as sarcopenia, cachexia, and myosteatosis. However, several key underappreciated scan imaging parameters need consideration for both research and clinical use, specifically CT kilovoltage and the use of contrast material. We conducted a scoping review to assess these effects on CT muscle measures. We reviewed articles from PubMed, Scopus, and Web of Science from 1970 to 2020 on the effect of intravenous contrast material and variation in CT kilovoltage on muscle mass and density. We identified 971 articles on contrast and 277 articles on kilovoltage. The number of articles that met inclusion criteria for contrast and kilovoltage was 11 and 7, respectively. Ten studies evaluated the effect of contrast on muscle density of which nine found that contrast significantly increases CT muscle density (arterial phase 6-23% increase, venous phase 19-57% increase, and delayed phase 23-43% increase). Seven out of 10 studies evaluating the effect of contrast on muscle area found significant increases in area due to contrast (≤2.58%). Six studies evaluating kilovoltage on muscle density found that lower kilovoltage resulted in a higher muscle density (14-40% increase). One study reported a significant decrease in muscle area when reducing kilovoltage (2.9%). The use of contrast and kilovoltage variations can have dramatic effects on skeletal muscle analysis and should be considered and reported in CT muscle analysis research. These significant factors in CT skeletal muscle analysis can alter clinical and research outcomes and are therefore a barrier to clinical application unless better appreciated.

Low-dose abdominopelvic computed tomography in patients with lymphoma: An image quality and radiation dose reduction study

This study aimed to evaluate image quality, the detection rate of enlarged lymph nodes, and radiation dose exposure of ultralow-dose and low-dose abdominopelvic computed tomography (CT) in patients with lymphoma. Patients with lymphoma who underwent abdominopelvic CT using dual-source scanner were retrospectively recruited from a single center. CT images were obtained at 90 kVp dual-source mode reformatted in three data sets using the advanced modelled iterative reconstruction algorithm: 100% (standard-dose CT), 66.7% (low-dose CT), and 33.3% (ultralow-dose CT). Two radiologists analyzed subjective image quality and detection of abdominal enlarged lymph nodes on ultralow-dose, low-dose, and standard-dose CT blindly and independently. The results were compared with reference standards. Three readers (two radiologists and one hematologist) reviewed overall image quality and spleen size. In total, 128 consecutive CT scans (77 complete response, 44 partial response, 6 progressive disease, and 1 initial evaluation) from 86 patients (64 B-cell lymphoma, 14 T/NK-cell lymphoma, and 8 Hodgkin’s lymphoma cases) were assessed. The enlarged lymph node-based detection rates for two readers were 97.0% (96/99) and 94.0% (93/99) on standard-dose CT, 97.0% (96/99) and 94.0% (93/99) on low-dose CT, and 94.0% (93/99) and 89.9% (89/99) on ultralow-dose CT. Overall image quality was 3.8 ± 0.5, 3.9 ± 0.5, and 4.1 ± 0.5 on ultralow-dose CT; 4.7 ± 0.4, 4.6 ± 0.5, and 4.8 ± 0.3 on low-dose CT; and 4.8 ± 0.4, 4.7 ± 0.4, and 4.9 ± 0.2 on standard-dose CT, according to two radiologists and one hematologist, respectively. Intraclass correlation coefficients of spleen size were 0.90 (95% confidence interval [CI], 0.87–0.93), 0.91 (95% CI, 0.88–0.93), and 0.91 (95% CI, 0.88–0.93) on ultralow-dose, low-dose, and standard-dose CT, respectively. Mean effective radiation doses of standard-dose, low-dose, and ultralow-dose CT were 5.7 ±1.8 mSv, 3.8 ± 1.2 mSv, and 1.9 ± 0.6 mSv, respectively. Our findings suggest that ultralow-dose and low-dose CT, even with radiation doses reduced by 66.7% and 33.3%, respectively, maintained adequate image quality. These imaging modalities may be employed for follow-up lymphoma evaluation in consideration of the long surveillance periods.

Model-based reconstruction algorithm in the detection of acute trauma-related lesions in brain CT examinations

BACKGROUND AND PURPOSE

To evaluate the added value of a model-based reconstruction algorithm in the assessment of acute traumatic brain lesions in emergency non-enhanced computed tomography, in comparison with a standard hybrid iterative reconstruction approach.

MATERIALS AND METHODS

We retrospectively evaluated a total of 350 patients who underwent a 256-row non-enhanced computed tomography scan at the emergency department for brain trauma. Images were reconstructed both with hybrid and model-based iterative algorithm. Two radiologists, blinded to clinical data, recorded the presence, nature, number, and location of acute findings. Subjective image quality was performed using a 4-point scale. Objective image quality was determined by computing the signal-to-noise ratio and contrast-to-noise ratio. The agreement between the two readers was evaluated using k-statistics.

RESULTS

A subjective image quality analysis using model-based iterative reconstruction gave a higher detection rate of acute trauma-related lesions in comparison to hybrid iterative reconstruction (extradural haematomas 116 vs. 68, subdural haemorrhages 162 vs. 98, subarachnoid haemorrhages 118 vs. 78, parenchymal haemorrhages 94 vs. 64, contusive lesions 36 vs. 28, diffuse axonal injuries 75 vs. 31; all P<0.001). Inter-observer agreement was moderate to excellent in evaluating all injuries (extradural haematomas k=0.79, subdural haemorrhages k=0.82, subarachnoid haemorrhages k=0.91, parenchymal haemorrhages k=0.98, contusive lesions k=0.88, diffuse axonal injuries k=0.70). Quantitatively, the mean standard deviation of the thalamus on model-based iterative reconstruction images was lower in comparison to hybrid iterative one (2.12 ± 0.92 vsa 3.52 ± 1.10; P=0.030) while the contrast-to-noise ratio and signal-to-noise ratio were significantly higher (contrast-to-noise ratio 3.06 ± 0.55 vs. 1.55 ± 0.68, signal-to-noise ratio 14.51 ± 1.78 vs. 8.62 ± 1.88; P<0.0001). Median subjective image quality values for model-based iterative reconstruction were significantly higher (P=0.003).

CONCLUSION

Model-based iterative reconstruction, offering a higher image quality at a thinner slice, allowed the identification of a higher number of acute traumatic lesions than hybrid iterative reconstruction, with a significant reduction of noise.

Model-based iterative reconstruction in CT of paranasal sinuses in cystic fibrosis

AIM

To assess image quality and dose-reduction efficacy of model-based iterative reconstruction (MBIR) in computed tomography (CT) of the paranasal sinus (CTPNS) compared with adaptive statistical iterative reconstruction (ASIR) in cystic fibrosis (CF) patients.

MATERIALS AND METHODS

Unenhanced CTPNS studies performed in adult CF patients from 2014 to 2020 were included. MBIR and ASIR were used and compared. Two radiologists assessed the CT images blindly and randomly. Quantitative assessment of noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) was performed in the maxillary sinus, sphenoid body, temporalis, and background air. Qualitative assessment performed included image sharpness, noise and contrast.

RESULTS

Thirty-seven MBIR and 45 ASIR CT PNS studies were included. MBIR achieved a 74% effective median dose reduction (0.039 mSv) compared with ASIR (0.147 mSv). Measured noise was significantly lower in all regions using MBIR (p<0.001) with superior SNR (p<0.001). MBIR had higher CNR compared to ASIR (4.567 versus 2.03, p<0.001). MBIR images were sharper and less noisy, with equal contrast. Cohen's weighted kappa value was 0.824 for qualitative analysis, indicating good inter-rater agreement. Both methods had 100% diagnostic acceptability.

CONCLUSION

MBIR produces high-quality CTPNS images at a significantly lower dose compared with ASIR. It is the preferred imaging surveillance method in CF patients and may have roles in other patient cohorts.

Application of low-dose CT combined with model-based iterative reconstruction algorithm in oncologic patients during follow-up: dose reduction and image quality

OBJECTIVES

To compare image quality and radiation dose of CT images reconstructed with model-based iterative reconstruction (MBIR) and hybrid-iterative (HIR) algorithm in oncologic patients.

METHODS

125 oncologic patients underwent both contrast-enhanced low- (100 kV), and standard (120 kV) dose CT, were enrolled. Image quality was assessed by using a 4-point Likert scale. CT attenuation values, expressed in Hounsfield unit (HU), were recorded within a regions of interest (ROI) of liver, spleen, paraspinal muscle, aortic lumen, and subcutaneous fat tissue. Image noise, expressed as standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated. Radiation dose were analyzed. Paired Student's t-test was used to compare all continuous variables.

RESULTS

The overall median score assessed as image quality for CT images with the MBIR algorithm was significantly higher in comparison with HIR [4 (range 3-4) vs 3 (3-4), p = 0.017].CT attenuation values and SD were significantly higher and lower, respectively, in all anatomic districts in images reconstructed with MBIR in comparison with HIR ones (all p < 0.001). SNR and CNR values were higher in CT images reconstructed with MBIR, reaching a significant difference in all districts (all p < 0.001). Radiation dose were significantly lower in the MBIR group compared with the HIR group (p < 0.001).

CONCLUSIONS

MBIR combined with low-kV setting allows an important dose reduction in whole-body CT imaging, reaching a better image quality both qualitatively and quantitatively.

ADVANCES IN KNOWLEDGE

MBIR with low-dose approach allows a reduction of dose exposure, maintaining high image quality, especially in patients which deserve a longlasting follow-up.

A prospective study on the use of ultralow-dose computed tomography with iterative reconstruction for the follow-up of patients liver and renal abscess

Background

Radiation dose reduction is a major concern in patients who undergo computed tomography (CT) to follow liver and renal abscess.

Objectives

The purpose of this study is to investigate the feasibility of ultralow-dose CT with iterative reconstruction (IR) to follow patients with liver and renal abscess.

Methods

This prospective study included 18 patients who underwent ultralow-dose CT with IR to follow abscesses (liver abscesses in 10 patients and renal abscesses in 8 patients; ULD group). The control group consisted of 14 patients who underwent follow-up standard-dose CT for liver abscesses during the same period. The objective image noise was evaluated by measuring standard deviation (SD) in the liver and subcutaneous fat to select a specific IR for qualitative analysis. Two radiologists independently evaluated subjective image quality, noise, and diagnostic confidence to evaluate abscess using a five-point Likert scale. Qualitative parameters were compared between the ULD and control groups with the Mann-Whitney U test.

Results

The mean CT dose index volume and dose length product of standard-dose CT were 8.7 ± 1.8 mGy and 555.8 ± 142.8 mGy·cm, respectively. Mean dose reduction of ultralow-dose CT was 71.8% compared to standard-dose CT. After measuring SDs, iDose level 5, which showed similar SD to standard-dose CT in both the subcutaneous fat and liver (P = 0.076, and P = 0.124), was selected for qualitative analysis. Ultralow-dose CT showed slightly worse subjective image quality (P < 0.001 for reader 1, and P = 0.005 for reader 2) and noise (P = 0.004 for reader 1, and P = 0.001 for reader 2) than standard-dose CT. However, the diagnostic confidence of ultralow-dose CT for evaluating abscess was comparably excellent to standard-dose CT (P = 0.808 for reader 1, and P = 0.301 for reader 2).

Conclusions

Ultralow-dose CT with IR can be used in the follow-up of liver and renal abscess with comparable diagnostic confidence.

Improved Depictions of the Anterior Choroidal Artery and Thalamoperforating Arteries on 3D-CTA Images Using Model-based Iterative Reconstruction

RATIONALE AND OBJECTIVES

To evaluate the depictability of intracranial small arteries using high-resolution CTA with model-based iterative reconstruction (MBIR).

MATERIALS AND METHODS

We retrospectively analyzed 21 patients who underwent brain 3D-CTA. Axial and volume-rendered (VR) images were reconstructed from the 3D-CTA raw data using adaptive statistical image reconstruction (ASIR) and MBIR. As a quantitative assessment, intra-arterial CT values of the ICA and contrast-to-noise ratio were measured to evaluate vessel enhancement. Additionally, CT values and standard deviations (SDs) of CT values and signal to noise ratio in white matter parenchyma were measured to evaluate background noise. As a qualitative assessment, the degree of vessel depictability in the anterior choroidal artery (AchoA) and the perforating branches of thalamoperforating arteries (TPA) on VR images using two different reconstruction algorithms was visually evaluated using a 3-point grading system.

RESULTS

The CT value of the ICA [605.27± 89.76 Hounsfield units (HU)] was significantly increased and the SD value (i.e., image noise) of the white matter parenchyma [6.79 ± 0.81(HU)] was decreased on MBIR compared with ASIR [546.76 ± 85.27 (HU)] and [8.04 ± 1.08 HU)] (p <.05 for all). Contrast-to-noise ratio of ICA [84.48 ± 20.17] and signal to noise ratio of white matter [6.18 ± 0.75] with MBIR were significantly higher than ASIR [65.98 ± 13.08] and [5.28 ± 0.78] (p < 0.05 for all). In addition, depictions of the AchoA and TPA on VR images were significantly improved using MBIR compared with ASIR (p < 0.05).

CONCLUSION

MBIR allows depiction of small intracranial arteries such as AchoA and TPA with better visibility than ASIR without increasing the dose of radiation and the amount of contrast agent.

Combination of Deep Learning-Based Denoising and Iterative Reconstruction for Ultra-Low-Dose CT of the Chest: Image Quality and Lung-RADS Evaluation

OBJECTIVE. The objective of our study was to assess the effect of the combination of deep learning-based denoising (DLD) and iterative reconstruction (IR) on image quality and Lung Imaging Reporting and Data System (Lung-RADS) evaluation on chest ultra-low-dose CT (ULDCT). MATERIALS AND METHODS. Forty-one patients with 252 nodules were evaluated retrospectively. All patients underwent ULDCT (mean ± SD, 0.19 ± 0.01 mSv) and standard-dose CT (SDCT) (6.46 ± 2.28 mSv). ULDCT images were reconstructed using hybrid iterative reconstruction (HIR) and model-based iterative reconstruction (MBIR), and they were postprocessed using DLD (i.e., HIR-DLD and MBIR-DLD). SDCT images were reconstructed using filtered back projection. Three independent radiologists subjectively evaluated HIR, HIR-DLD, MBIR, and MBIR-DLD images on a 5-point scale in terms of noise, streak artifact, nodule edge, clarity of small vessels, homogeneity of the normal lung parenchyma, and overall image quality. Two radiologists independently evaluated the nodules according to Lung-RADS using HIR, MBIR, HIR-DLD, and MBIR-DLD ULDCT images and SDCT images. The median scores for subjective analysis were analyzed using Wilcoxon signed rank test with Bonferroni correction. Intraobserver agreement for Lung-RADS category between ULDCT and SDCT was evaluated using the weighted kappa coefficient. RESULTS. In the subjective analysis, ULDCT with DLD showed significantly better scores than did ULDCT without DLD (p < 0.001), and MBIR-DLD showed the best scores among the ULDCT images (p < 0.001) for all items. In the Lung-RADS evaluation, HIR showed fair or moderate agreement (reader 1 and reader 2: κw = 0.46 and 0.32, respectively); MBIR, moderate or good agreement (κw = 0.68 and 0.57); HIR-DLD, moderate agreement (κw = 0.53 and 0.48); and MBIR-DLD, good agreement (κw = 0.70 and 0.72). CONCLUSION. DLD improved the image quality of both HIR and MBIR on ULDCT. MBIR-DLD was superior to HIR_DLD for image quality and for Lung-RADS evaluation.

Influence of acquisition settings and radiation exposure on CT lung densitometry-An anthropomorphic ex vivo phantom study

Objectives

To systematically evaluate the influence of acquisition settings in conjunction with raw-data based iterative image reconstruction (IR) on lung densitometry based on multi-row detector computed tomography (CT) in an anthropomorphic chest phantom.

Materials and methods

Ten porcine heart-lung explants were mounted in an ex vivo chest phantom shell, six with highly and four with low attenuating chest wall. CT (Somatom Definition Flash, Siemens Healthineers) was performed at 120kV_p and 80kV_p, each combined with current-time products of 120, 60, 30, and 12mAs, and was reconstructed with filtered back projection (FBP) and IR (Safire, Siemens Healthineers). Mean lung density (LD), air density (AD) and noise were measured by semi-automated region-of interest (ROI) analysis, with 120kV_p/120 mAs serving as the standard of reference.

Results

Using IR, noise in lung parenchyma was reduced by ~ 31% at high attenuating chest wall and by ~ 22% at low attenuating chest wall compared to FBP, respectively (p<0.05). IR induced changes in the order of ±1 HU to mean absolute LD and AD compared to corresponding FBP reconstructions which were statistically significant (p<0.05).

Conclusions

Densitometry is influenced by acquisition parameters and reconstruction algorithms to a degree that may be clinically negligible. However, in longitudinal studies and clinical research identical protocols and potentially other measures for calibration may be required.

A phantom study of the performance of model-based iterative reconstruction in low-dose chest and abdominal CT: When are benefits maximized?

INTRODUCTION

The aim of this study was to assess and compare the effects of CT image reconstruction techniques on low-dose CT image quality using phantoms.

METHODS

Anthropomorphic torso and spatial/contrast-resolution phantoms were scanned at decreasing tube currents between 400 and 10 mA. CT thorax and abdomen/pelvis series were reconstructed with filtered back projection (FBP) alone, combined 40% adaptive statistical iterative reconstruction & FBP (ASIR40), and model-based iterative reconstruction (MBIR) [(resolution-preference 05 (RP05) and RP20 in the thorax and RP05 and noise-reduction 05 (NR05) in the abdomen)]. Two readers rated image quality quantitatively and qualitatively.

RESULTS

In thoracic CT, objective image noise on MBIR RP05 data sets outperformed FBP at 200, 100, 50 and 10 mA and outperformed ASIR40 at 50 and 10 mA (p < 0.001). MBIR RP20 outperformed FBP at 50 and 10 mA and outperformed ASIR40 at 10 mA (p < 0.001). Compared with both FBP and ASIR40, MBIR RP05 demonstrated significantly better signal-to-noise ratio (SNR) at 10 mA. In abdomino-pelvic CT, MBIR RP05 and NR05 outperformed FBP and ASIR at all tube current levels for objective image noise. NR05 demonstrated greater SNR at 200, 100, 50 and 10 mA and RP05 demonstrated greater SNR at 50 and 10 mA compared with both FBP and ASIR. MBIR images demonstrated better subjective image quality scores. Spatial resolution, low-contrast detectability and contrast-to-noise ratio (CNR) were comparable between image reconstruction techniques.

CONCLUSION

CTs reconstructed with MBIR have lower image noise and improved image quality compared with FBP and ASIR. These effects increase with reduced radiation exposure confirming optimal use for low-dose CT imaging.

The Application of a New Model-Based Iterative Reconstruction in Low-Dose Upper Abdominal CT

RATIONALE AND OBJECTIVES

To compare upper abdominal computed tomography (CT) image quality of new model-based iterative reconstruction (MBIR) with low-contrast resolution preference (MBIR_NR40), conventional MBIR (MBIR_c), and adaptive statistical iterative reconstruction (ASIR) at low dose with ASIR at routine-dose.

MATERIALS AND METHODS

Study included phantom and 60 patients who had initial and follow-up CT scans. For patients, the delay phase was acquired at routine-dose (noise index = 10 HU) for the initial scan and low dose (noise index = 20 HU) for the follow-up. The low-dose CT was reconstructed with 40% and 60% ASIR, MBIR_c, and MBIR_NR40, while routine-dose CT was reconstructed with 40% ASIR. CT value and noise measurements of the subcutaneous fat, back muscle, liver, and spleen parenchyma were compared using one-way ANOVA. Two radiologists used semiquantitative 7-scale (-3 to +3) to rate image quality and artifacts.

RESULTS

The phantom study revealed superior low-contrast resolution with MBIR_NR40. For patient scans, the CT dose index for the low-dose CT was 3.00 ± 1.32 mGy, 75% lower than the 11.90 ± 4.75 mGy for the routine-dose CT. Image noise for the low-dose MBIR_NR40 images was significantly lower than the low-dose MBIR_c and ASIR images, and routine-dose ASIR images (p < 0.05). Subjective ratings showed higher image quality for low-dose MBIR_NR40, with lower noise, better low-contrast resolution for abdominal structures, and finer lesion contours than those of low-dose MBIR_c and ASIR images, and routine-dose ASIR images (p < 0.05).

CONCLUSION

MBIR_NR40 with low-contrast resolution preference provides significantly lower noise and better image quality than MBIR_c and ASIR in low-dose abdominal CT; significantly better objective and subjective image quality than the routine-dose ASIR with 75% dose reduction.

Impact of CT reconstruction algorithm on auto-segmentation performance

Model‐based iterative reconstruction (MBIR) reduces CT imaging dose while maintaining image quality. However, MBIR reduces noise while preserving edges which may impact intensity‐based tasks such as auto‐segmentation. This work evaluates the sensitivity of an auto‐contouring prostate atlas across multiple MBIR reconstruction protocols and benchmarks the results against filtered back projection (FBP). Images were created from raw projection data for 11 prostate cancer cases using FBP and nine different MBIR reconstructions (3 protocols/3 noise reduction levels) yielding 10 reconstructions/patient. Five bony structures, bladder, rectum, prostate, and seminal vesicles (SVs) were segmented using an auto‐segmentation pipeline that renders 3D binary masks for analysis. Performance was evaluated for volume percent difference (VPD) and Dice similarity coefficient (DSC), using FBP as the gold standard. Nonparametric Friedman tests plus post hoc all pairwise comparisons were employed to test for significant differences (P < 0.05) for soft tissue organs and protocol/level combinations. A physician performed qualitative grading of 396 MBIR contours across the prostate, bladder, SVs, and rectum in comparison to FBP using a six‐point scale. MBIR contours agreed with FBP for bony anatomy (DSC ≥ 0.98), bladder (DSC ≥ 0.94, VPD < 8.5%), and prostate (DSC = 0.94 ± 0.03, VPD = 4.50 ± 4.77% (range: 0.07–26.39%). Increased variability was observed for rectum (VPD = 7.50 ± 7.56% and DSC = 0.90 ± 0.08) and SVs (VPD and DSC of 8.23 ± 9.86% range (0.00–35.80%) and 0.87 ± 0.11, respectively). Over the all protocol/level comparisons, a significant difference was observed for the prostate VPD between BSPL1 and BSTL2 (adjusted P‐value = 0.039). Nevertheless, 300 of 396 (75.8%) of the four soft tissue structures using MBIR were graded as equivalent or better than FBP, suggesting that MBIR offered potential improvements in auto‐segmentation performance when compared to FBP. Future work may involve tuning organ‐specific MBIR parameters to further improve auto‐segmentation performance. Running title: Impact of CT Reconstruction Algorithm on Auto‐segmentation Performance.

Ultra-low-dose chest computed tomography for interstitial lung disease using model-based iterative reconstruction with or without the lung setting

The aim of this study was to assess the effects of reconstruction on the image quality and quantitative analysis for interstitial lung disease (ILD) using filtered back projection (FBP) and model-based iterative reconstruction (MBIR) with the lung setting and the conventional setting on ultra-low-dose computed tomography (CT).Fifty-two patients with known ILD were prospectively enrolled and underwent CT at an ultra-low dose (0.18 ± 0.02 mSv) and a standard dose (7.01 ± 2.66 mSv). Ultra-low-dose CT was reconstructed using FBP (uFBP) and MBIR with the lung setting (uMBIR-Lung) and the conventional setting (uMBIR-Stnd). Standard-dose CT was reconstructed using FBP (sFBP). Three radiologists subjectively evaluated the images on a 3-point scale (1 = worst, 3 = best). For objective image quality analysis, regions of interest were placed in the lung parenchyma and the axillary fat, and standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were evaluated. For 32 patients with clinically diagnosed idiopathic interstitial pneumonia, quantitative measurements including total lung volume (TLV) and the percentage of ILD volume (%ILDV) were obtained. The medians of 3 radiologists' scores were analyzed using the Wilcoxon signed-rank test and the objective noise was analyzed using the paired t test. The Bonferroni correction was used for multiple comparisons. The quantitative measurements were analyzed using the Bland-Altman method.uMBIR-Lung scored better than uMBIR-Stnd and worse than sFBP (P < .001), except for noise and streak artifact in subjective analysis. The SD decreased significantly in the order of uMBIR-Stnd, uMBIR-Lung, sFBP, and uFBP (P < .001). The SNR and CNR increased significantly in the order of uMBIR-Stnd, uMBIR-Lung, sFBP, and uFBP (P < .001). For TLV, there was no significant bias between ultra-low-dose MBIRs and sFBP (P > .3). For %ILDV, there was no significant bias between uMBIR-Lung and sFBP (p = 0.8), but uMBIR-Stnd showed significantly lower %ILDV than sFBP (P = .013).uMBIR-Lung provided more appropriate image quality than uMBIR-Stnd. Although inferior to standard-dose CT for image quality, uMBIR-Lung showed equivalent CT quantitative measurements to standard-dose CT.

The Use of Model-based Iterative Reconstruction to Optimize Chest CT Examinations for Diagnosing Lung Metastases in Patients with Sarcoma: A Phantom Study

RATIONALE AND OBJECTIVES

This phantom study aimed to evaluate low-dose (LD) chest computed tomography (CT) protocols using model-based iterative reconstruction (MBIR) for diagnosing lung metastases in patients with sarcoma.

MATERIALS AND METHODS

An adult female anthropomorphic phantom was scanned with a 64-slice CT using four LD protocols and a standard-dose protocol. Absorbed organ doses were measured with 10 metal-oxide-semiconductor field-effect transistor dosimeters. Furthermore, Monte Carlo simulations were performed to estimate organ and effective doses. Image quality in terms of image noise, contrast, and resolution was measured from the CT images reconstructed with conventional filtered back projection, adaptive statistical iterative reconstruction, and MBIR algorithms. All the results were compared to the performance of the standard-dose protocol.

RESULTS

Mean absorbed organ and effective doses were reduced by approximately 95% with the LD protocol (100-kVp tube voltage and a fixed 10-mA tube current) compared to the standard-dose protocol (120-kVp tube voltage and tube current modulation) while yielding an acceptable image quality for diagnosing round-shaped lung metastases. The effective doses ranged from 0.16 to 2.83 mSv in the studied protocols. The image noise, contrast, and resolution were maintained or improved when comparing the image quality of LD protocols using MBIR to the performance of the standard-dose chest CT protocol using filtered back projection. The small round-shaped lung metastases were delineated at levels comparable to the used protocols.

CONCLUSIONS

Radiation exposure in patients can be reduced significantly by using LD chest CT protocols and MBIR algorithm while maintaining image quality for detecting round-shaped lung metastases.

The effect of vertical centering and scout direction on automatic tube voltage selection in chest CT: a preliminary phantom study on two different CT equipments

Purpose

To determine the effect of patient's vertical off-centering and scout direction on the function of automatic tube voltage selection (ATVS) and tube current modulation (TCM) in chest computed tomography (CT).

Methods

Chest phantom was scanned with Siemens and GE CT systems using three clinical chest CT protocols exploiting ATVS and a fixed 120 kVp chest protocol. The scans were performed at five vertical positions of the phantom (-6 to +6 cm from the scanner isocenter). The effects of scout direction (posterior-to-anterior, anterior-to-posterior, and lateral) and vertical off-centering on the function of ATVS and TCM were studied by examining changes in selected voltage, radiation dose (volume CT dose index, CTDI_vol), and image noise and contrast.

Results

Both scout direction and vertical off-centering affected ATVS. The effect differed between the vendors for the studied geometry, demonstrating differences in technical approaches. The greatest observed increase in CTDI_vol due to off-centering was 91%. Anterior-to-posterior scout produced highest doses at the uppermost table position, whereas posterior-to-anterior scout produced highest doses at the lowermost table position. Dose varied least using lateral scouts. Vertical off-centering impacted image noise and contrast due to the combined effect of ATVS, TCM, structural noise, and bowtie filters.

Conclusions

Patient vertical off-centering and scout direction affected substantially the CTDI_vol and image quality in chest CT examinations. Vertical off-centering caused variation also in the selected tube voltage. The function of ATVS and TCM methods differ significantly between the CT vendors, resulting in differences in CTDI_vol and image noise characteristics.

Low-dose CT imaging of the acute abdomen using model-based iterative reconstruction: a prospective study

OBJECTIVES

Performance of a modified abdominopelvic CT protocol reconstructed using full iterative reconstruction (IR) was assessed for imaging patients presenting with acute abdominal symptoms.

MATERIALS AND METHODS

Fifty-seven patients (17 male, 40 female; mean age of 56.5 ± 8 years) were prospectively studied. Low-dose (LD) and conventional-dose (CD) CTs were contemporaneously acquired between November 2015 and March 2016. The LD and CD protocols imparted radiation exposures approximating 10-20% and 80-90% those of routine abdominopelvic CT, respectively. The LD images were reconstructed with model-based iterative reconstruction (MBIR), and CD images with hybrid IR (40% adaptive statistical iterative reconstruction (ASIR)). Image quality was assessed quantitatively and qualitatively. Independent clinical interpretations were performed with a 6-week delay between reviews.

RESULTS

A 74.7% mean radiation dose reduction was achieved: LD effective dose (ED) 2.38 ± 1.78 mSv (size-specific dose estimate (SSDE) 3.77 ± 1.97 mGy); CD ED 7.04 ± 4.89 mSv (SSDE 10.74 ± 5.5 mGy). LD-MBIR images had significantly lower objective and subjective image noise compared with CD-ASIR (p < 0.0001). Noise reduction for LD-MBIR studies was greater for patients with BMI < 25 kg/m² than those with BMI ≥ 25 kg/m² (5.36 ± 3.2 Hounsfield units (HU) vs. 4.05 ± 3.1 HU, p < 0.0001). CD-ASIR studies had significantly better contrast resolution, and diagnostic acceptability (p < 0.0001 for all). LD-MBIR studies had significantly lower streak artifact (p < 0.0001). There was no difference in sensitivity for primary findings between the low-dose and conventional protocols with the exception of one case of enteritis.

CONCLUSIONS

Low-dose abdominopelvic CT performed with MBIR is a feasible radiation dose reduction strategy for imaging patients presenting with acute abdominal pain.

Pulmonary Emphysema Quantification on Ultra-Low-Dose Computed Tomography Using Model-Based Iterative Reconstruction With or Without Lung Setting

OBJECTIVES

To evaluate the influence of model-based iterative reconstruction (MBIR) with lung setting and conventional setting on pulmonary emphysema quantification by ultra-low-dose computed tomography (ULDCT) compared with standard-dose CT (SDCT).

METHODS

Forty-five patients who underwent ULDCT (0.18 ± 0.02 mSv) and SDCT (6.66 ± 2.69 mSv) were analyzed in this retrospective study. Images were reconstructed using filtered back projection (FBP) with smooth and sharp kernels and MBIR with conventional and lung settings. Extent of emphysema was evaluated using fully automated software. Correlation between ULDCT and SDCT was assessed by interclass correlation coefficiency (ICC) and Bland-Altman analysis.

RESULTS

Excellent correlation was seen between MBIR with conventional setting on ULDCT and FBP with smooth kernel on SDCT (ICC, 0.97; bias, -0.31%) and between MBIR with lung setting on ULDCT and FBP with sharp kernel on SDCT (ICC, 0.82; bias, -2.10%).

CONCLUSION

Model-based iterative reconstruction improved the agreement between ULDCT and SDCT on emphysema quantification.

Iterative reconstructions in multiphasic CT imaging of the liver: qualitative and task-based analyses of image quality

AIM

To evaluate the clinical benefits on image quality (IQ) of adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) in multiphasic liver CT compared to filtered back-projection (FBP), in patients and on phantoms using a novel task-based metric.

MATERIALS AND METHODS

Image data of 65 patients who underwent a routine multiphasic liver CT during a 1-month period were reconstructed with FBP, ASIR50, ASIR80, and MBIR. IQ was assessed qualitatively by ranking the most distal hepatic artery (HA) and portal vein (PV) visible; and quantitatively by measuring contrast-to-noise ratio (CNR) of the liver parenchyma, HA and PV. IQ was compared between each reconstruction and correlated to CNR and detectability index (d') measurements computed on phantoms scanned with the same CT protocol as for patients.

RESULTS

HA and PV were seen more distally on MBIR and ASIR80 compared to FBP (p≤0.001). The CNR correlated weakly between patient and phantom (r=0.76 and 0.80 for HA and PV, respectively), whereas d' correlated strongly with the division order of HA and PV (r=0.96 and 0.95, respectively).

CONCLUSION

MBIR and ASIR significantly improve the IQ of multiphasic liver CT, especially through better distal detection of HA and PV, in agreement with the adapted task-based metric d' estimated on phantoms.

Assessment of image quality in abdominal CT: potential dose reduction with model-based iterative reconstruction

PURPOSE

To estimate potential dose reduction in abdominal CT by visually comparing images reconstructed with filtered back projection (FBP) and strengths of 3 and 5 of a specific MBIR.

MATERIAL AND METHODS

A dual-source scanner was used to obtain three data sets each for 50 recruited patients with 30, 70 and 100% tube loads (mean CTDIvol 1.9, 3.4 and 6.2 mGy). Six image criteria were assessed independently by five radiologists. Potential dose reduction was estimated with Visual Grading Regression (VGR).

RESULTS

Comparing 30 and 70% tube load, improved image quality was observed as a significant strong effect of log tube load and reconstruction method with potential dose reduction relative to FBP of 22-47% for MBIR strength 3 (p < 0.001). For MBIR strength 5 no dose reduction was possible for image criteria 1 (liver parenchyma), but dose reduction between 34 and 74% was achieved for other criteria. Interobserver reliability showed agreement of 71-76% (κw 0.201-0.286) and intra-observer reliability of 82-96% (κw 0.525-0.783).

CONCLUSION

MBIR showed improved image quality compared to FBP with positive correlation between MBIR strength and increasing potential dose reduction for all but one image criterion.

KEY POINTS

• MBIR's main advantage is its de-noising properties, which facilitates dose reduction. • MBIR allows for potential dose reduction in relation to FBP. • Visual Grading Regression (VGR) produces direct numerical estimates of potential dose reduction. • MBIR strengths 3 and 5 dose reductions were 22-34 and 34-74%. • MBIR strength 5 demonstrates inferior performance for liver parenchyma.

Determination of a suitable low-dose abdominopelvic CT protocol using model-based iterative reconstruction through cadaveric study

INTRODUCTION

Cadaveric studies provide a means of safely assessing new technologies and optimizing scanning prior to clinical validation. Reducing radiation exposure in a clinical setting can entail incremental dose reductions to avoid missing important clinical findings. The use of cadavers allows assessment of the impact of more substantial dose reductions on image quality. Our aim was to identify a suitable low-dose abdominopelvic CT protocol for subsequent clinical validation.

METHODS

Five human cadavers were scanned at one conventional dose and three low-dose settings. All scans were reconstructed using three different reconstruction algorithms: filtered back projection (FBP), hybrid iterative reconstruction (60% FBP and 40% adaptive statistical iterative reconstruction (ASIR40)), and model-based iterative reconstruction (MBIR). Two readers rated the image quality both quantitatively and qualitatively.

RESULTS

Model-based iterative reconstruction images had significantly better objective image noise and higher qualitative scores compared with both FBP and ASIR40 images at all dose levels. The greatest absolute noise reduction, between MBIR and FBP, of 34.3 HU (equating to a 68% reduction) was at the lowest dose level. MBIR reduced image noise and improved image quality even in CT images acquired with a mean radiation dose reduction of 62% compared with conventional dose studies reconstructed with ASIR40, with lower levels of objective image noise, superior diagnostic acceptability and contrast resolution, and comparable subjective image noise and streak artefact scores.

CONCLUSION

This cadaveric study demonstrates that MBIR reduces image noise and improves image quality in abdominopelvic CT images acquired with dose reductions of up to 62%.

Iterative Reconstructions in Reduced-Dose CT: Which Type Ensures Diagnostic Image Quality in Young Oncology Patients?

RATIONALE AND OBJECTIVES

To compare adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) algorithms for reduced-dose computed tomography (CT).

MATERIALS AND METHODS

Forty-four young oncology patients (mean age 30 ± 9 years) were included. After routine thoraco-abdominal CT (dose 100%, average CTDI_vol 9.1 ± 2.4 mGy, range 4.4-16.9 mGy), follow-up CT was acquired at 50% (average CTDI_vol 4.5 ± 1.2 mGy, range 2.2-8.4 mGy) in 29 patients additionally at 20% dose (average CTDI_vol 1.9 ± 0.5 mGy, range 0.9-3.4 mGy). Each reduced-dose CT was reconstructed using both ASIR and MBIR. Four radiologists (two juniors and two seniors) blinded to dose and technique read each set of CT images regarding objective and subjective image qualities (high- or low-contrast structures), subjective noise or pixilated appearance, diagnostic confidence, and lesion detection.

RESULTS

At all dose levels, objective image noise was significantly lower with MBIR than with ASIR (P < 0.001). The subjective image quality for low-contrast structures was significantly higher with MBIR than with ASIR (P < 0.001). Reduced-dose abdominal CT images of patients with higher body mass index (BMI) were read with significantly higher diagnostic confidence than images of slimmer patients (P < 0.001) and had higher subjective image quality, regardless of technique. Although MBIR images appeared significantly more pixilated than ASIR images, they were read with higher diagnostic confidence, especially by juniors (P < 0.001).

CONCLUSIONS

Reduced-dose CT during the follow-up of young oncology patients should be reconstructed with MBIR to ensure diagnostic quality. Elevated body mass index does not hamper the quality of reduced-dose CT.

Reduced dose CT with model-based iterative reconstruction compared to standard dose CT of the chest, abdomen, and pelvis in oncology patients: intra-individual comparison study on image quality and lesion conspicuity

PURPOSE

To compare image quality and lesion conspicuity of reduced dose (RD) CT with model-based iterative reconstruction (MBIR) compared to standard dose (SD) CT in patients undergoing oncological follow-up imaging.

METHODS

Forty-four cancer patients who had a staging SD CT within 12 months were prospectively included to undergo a weight-based RD CT with MBIR. Radiation dose was recorded and tissue attenuation and image noise of four tissue types were measured. Reproducibility of target lesion size measurements of up to 5 target lesions per patient were analyzed. Subjective image quality was evaluated for three readers independently utilizing 4- or 5-point Likert scales.

RESULTS

Median radiation dose reduction was 46% using RD CT (P < 0.01). Median image noise across all measured tissue types was lower (P < 0.01) in RD CT. Subjective image quality for RD CT was higher (P < 0.01) in regard to image noise and overall image quality; however, there was no statistically significant difference regarding image sharpness (P = 0.59). There were subjectively more artifacts on RD CT (P < 0.01). Lesion conspicuity was subjectively better in RD CT (P < 0.01). Repeated target lesion size measurements were highly reproducible both on SD CT (ICC = 0.987) and RD CT (ICC = 0.97).

CONCLUSIONS

RD CT imaging with MBIR provides diagnostic imaging quality and comparable lesion conspicuity on follow-up exams while allowing dose reduction by a median of 46% compared to SD CT imaging.

Improvement of image quality and dose management in CT fluoroscopy by iterative 3D image reconstruction

OBJECTIVES

The objective of this study was to assess the influence of an iterative CT reconstruction algorithm (IA), newly available for CT-fluoroscopy (CTF), on image noise, readers' confidence and effective dose compared to filtered back projection (FBP).

METHODS

Data from 165 patients (FBP/IA = 82/74) with CTF in the thorax, abdomen and pelvis were included. Noise was analysed in a large-diameter vessel. The impact of reconstruction and variables (e.g. X-ray tube current I) influencing noise and effective dose were analysed by ANOVA and a pairwise t-test with Bonferroni-Holm correction. Noise and readers' confidence were evaluated by three readers.

RESULTS

Noise was significantly influenced by reconstruction, I, body region and circumference (all p ≤ 0.0002). IA reduced the noise significantly compared to FBP (p = 0.02). The effect varied for body regions and circumferences (p ≤ 0.001). The effective dose was influenced by the reconstruction, body region, interventional procedure and I (all p ≤ 0.02). The inter-rater reliability for noise and readers' confidence was good (W ≥ 0.75, p < 0.0001). Noise and readers' confidence were significantly better in AIDR-3D compared to FBP (p ≤ 0.03). Generally, IA yielded a significant reduction of the median effective dose.

CONCLUSION

The CTF reconstruction by IA showed a significant reduction in noise and effective dose while readers' confidence increased.

KEY POINTS

• CTF is performed for image guidance in interventional radiology. • Patient exposure was estimated from DLP documented by the CT. • Iterative CT reconstruction is appropriate to reduce image noise in CTF. • Using iterative CT reconstruction, the effective dose was significantly reduced in abdominal interventions.

Emergency assessment of patients with acute abdominal pain using low-dose CT with iterative reconstruction: a comparative study

OBJECTIVES

To determine if radiation dose delivered by contrast-enhanced CT (CECT) for acute abdominal pain can be reduced to the dose administered in abdominal radiography (<2.5 mSv) using low-dose CT (LDCT) with iterative reconstruction algorithms.

METHODS

One hundred and fifty-one consecutive patients requiring CECT for acute abdominal pain were included, and their body mass index (BMI) was calculated. CECT was immediately followed by LDCT. LDCT series was processed using 1) 40% iterative reconstruction algorithm blended with filtered back projection (LDCT-IR-FBP) and 2) model-based iterative reconstruction algorithm (LDCT-MBIR). LDCT-IR-FBP and LDCT-MBIR images were reviewed independently by two board-certified radiologists (Raters 1 and 2).

RESULTS

Abdominal pathology was revealed on CECT in 120 (79%) patients. In those with BMI <30, accuracies for correct diagnosis by Rater 1 with LDCT-IR-FBP and LDCT-MBIR, when compared to CECT, were 95.4% (104/109) and 99% (108/109), respectively, and 92.7% (101/109) and 100% (109/109) for Rater 2. In patients with BMI ≥30, accuracies with LDCT-IR-FBP and LDCT-MBIR were 88.1% (37/42) and 90.5% (38/42) for Rater 1 and 78.6% (33/42) and 92.9% (39/42) for Rater 2.

CONCLUSIONS

The radiation dose delivered by CT to non-obese patients with acute abdominal pain can be safely reduced to levels close to standard radiography using LDCT-MBIR.

KEY POINTS

• LDCT-MBIR (<2.5 mSv) can be used to assess acute abdominal pain. • LDCT-MBIR (<2.5 mSv) cannot safely assess acute abdominal pain in obese patients. • LDCT-IR-FBP (<2.5 mSv) cannot safely assess patients with acute abdominal pain.

Iterative reconstruction: comparison of techniques for reduced-dose liver computed tomography following transarterial chemoembolization for hepatocellular carcinoma

Background Adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) algorithms have the potential to reduce dose while maintaining image quality. Purpose To compare computed tomography (CT) image quality and diagnostic performance among three reconstruction techniques - ASIR, MBIR, and filtered back projection (FBP) - after transcatheter arterial chemoembolization (TACE) of hepatocellular carcinomas (HCC). Material and Methods Of 60 patients that underwent initial TACE for HCCs, half underwent dynamic liver CT with conventional scanning protocol, and the other half with dose reduction to approximately 60% of conventional exposure. All images were reconstructed using three algorithms: FBP, ASIR, and MBIR. For objective analysis, image noise and signal-to-noise ratio (SNR) were compared. For subjective analysis, three radiologists independently assessed image quality. Ability to detect viable HCCs was also evaluated. Results MBIR and ASIR produced images with less noise and higher SNR compared with FBP regardless of radiation dosage ( P < 0.017). However, in terms of subjective parameters, such as image blotchiness, artifacts, and overall quality, MBIR was inferior to FBP and ASIR ( P < 0.001). Regarding diagnostic performance, there were no significant differences among reviewers in the detection of viable HCCs depending on the reconstruction algorithm, regardless of the dose reduction protocol ( P > 0.017). Conclusion Although subjective evaluations suggest that MBIR images are of lower quality compared with FBP and ASIR regardless of radiation dosage, there were no significant differences among reconstruction algorithms in diagnosis of viable HCC after TACE.

Cerebral CTA with Low Tube Voltage and Low Contrast Material Volume for Detection of Intracranial Aneurysms

BACKGROUND AND PURPOSE

Multidetector row CTA has become the primary imaging technique for detecting intracranial aneurysms. Technical progress enables the use of cerebral CTA with lower radiation doses and contrast media. We evaluated the diagnostic accuracy of 80-kV(peak) cerebral CTA with 30 mL of contrast agent for detecting intracranial aneurysms.

MATERIALS AND METHODS

Two hundred four patients were randomly divided into 2 groups. Patients in group A (n = 102) underwent 80-kVp CTA with 30 mL of contrast agent, while patients in group B (n = 102) underwent conventional CTA (120 kVp, 60 mL of contrast agent). All patients underwent DSA. Image quality, diagnostic accuracy, and radiation dose between the 2 groups were compared.

RESULTS

Diagnostic image quality was obtained in 100 and 99 patients in groups A and B, respectively (P = .65). With DSA as reference standard, diagnostic accuracy on a per-aneurysm basis was 89.9% for group A and 93.9% for group B. For evaluating smaller aneurysms (<3 mm), the diagnostic accuracy of groups A and B was 86.3% and 90.8%, respectively. There was no difference in diagnostic accuracy between each CTA group and DSA (all, P > .05) or between the 2 CTA groups (all, P > .05). The effective dose in group A was reduced by 72.7% compared with group B.

CONCLUSIONS

In detecting intracranial aneurysms with substantial radiation dose and contrast agent reduction, 80-kVp/30-mL contrast CTA provides the same diagnostic accuracy as conventional CTA.

Submillisievert CT using model-based iterative reconstruction with lung-specific setting: An initial phantom study

OBJECTIVE

To assess image quality of filtered back-projection (FBP) and model-based iterative reconstruction (MBIR) with a conventional setting and a new lung-specific setting on submillisievert CT.

METHODS

A lung phantom with artificial nodules was scanned with 10 mA at 120 kVp and 80 kVp (0.14 mSv and 0.05 mSv, respectively); images were reconstructed using FBP and MBIR with conventional setting (MBIR_Stnd) and lung-specific settings (MBIR_RP20/Tx and MBIR_RP20). Three observers subjectively scored overall image quality and image findings on a 5-point scale (1 = worst, 5 = best) compared with reference standard images (50 mA-FBP at 120, 100, 80 kVp). Image noise was measured objectively.

RESULTS

MBIR_RP20/Tx performed significantly better than MBIR_Stnd for overall image quality in 80-kVp images (p < 0.01), blurring of the border between lung and chest wall in 120p-kVp images (p < 0.05) and the ventral area of 80-kVp images (p < 0.001), and clarity of small vessels in the ventral area of 80-kVp images (p = 0.037). At 120 kVp, 10 mA-MBIR_RP20 and 10 mA-MBIR_RP20/Tx showed similar performance to 50 mA-FBP. MBIR_Stnd was better for noise reduction. Except for blurring in 120 kVp-MBIR_Stnd, MBIRs performed better than FBP.

CONCLUSION

Although a conventional setting was advantageous in noise reduction, a lung-specific setting can provide more appropriate image quality, even on submillisievert CT.

KEY POINTS

• Lung-specific submillisievert 10 mA-MBIR CT setting has similar performance to 50 mA-FBP • The new lung-specific settings improve vessel clarity and blurring of borders • The new settings may provide more appropriate images than conventional settings.

Comparison of the image qualities of filtered back-projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction for CT venography at 80 kVp

PURPOSE

To evaluate the subjective and objective qualities of computed tomography (CT) venography images at 80 kVp using model-based iterative reconstruction (MBIR) and to compare these with those of filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR) using the same CT data sets.

MATERIALS AND METHODS

Forty-four patients (mean age: 56.1 ± 18.1) who underwent 80 kVp CT venography (CTV) for the evaluation of deep vein thrombosis (DVT) during 4 months were enrolled in this retrospective study. The same raw data were reconstructed using FBP, ASIR, and MBIR. Objective and subjective image analysis were performed at the inferior vena cava (IVC), femoral vein, and popliteal vein.

RESULTS

The mean CNR of MBIR was significantly greater than those of FBP and ASIR and images reconstructed using MBIR had significantly lower objective image noise (p < .001). Subjective image quality and confidence of detecting DVT by MBIR group were significantly greater than those of FBP and ASIR (p < .005), and MBIR had the lowest score for subjective image noise (p < .001).

CONCLUSION

CTV at 80 kVp with MBIR was superior to FBP and ASIR regarding subjective and objective image qualities.

KEY POINTS

• MBIR provides superior image quality compared with FBP and ASIR • CTV at 80kVp with MBIR improves diagnostic confidence in diagnosing DVT • CTV at 80kVp with MBIR presents better image quality with low radiation.