Adaptive iterative dose reduction 3D versus filtered back projection in CT: evaluation of image quality

Improvement of image quality of dentomaxillofacial region in ultra-high-resolution CT: a phantom study

OBJECTIVES

The purpose of this study was to compare the image quality of ultra-high-resolution CT (U-HRCT) with that of conventional multidetector row CT (convCT) and demonstrate its usefulness in the dentomaxillofacial region.

METHODS

Phantoms were helically scanned with U-HRCT and convCT scanners using clinical protocols. In U-HRCT, phantoms were scanned in super-high-resolution (SHR) mode, and hybrid iterative reconstruction (HIR) and filtered-back projection (FBP) techniques were performed using a bone kernel (FC81). The FBP technique was performed using the same kernel as in convCT (reference). Two observers independently evaluated the 54 resulting images using a 5-point scale (5 = excellent diagnostic image quality; 4 = above average; 3 = average; 2 = subdiagnostic; and 1 = unacceptable). The system performance function (SPF) was calculated for a comprehensive evaluation of the image quality using the task transfer function and noise power spectrum. Statistical analysis using the Kruskal-Wallis test was performed to compare the image quality among the 3 protocols.

RESULTS

The observers assigned higher scores to images acquired with the SHRHIR and SHRFBP protocols than to those acquired with the reference (P < 0.0001 and P < 0.0001, respectively). The relative SPF value at 1.0 cycles/mm in SHRHIR and SHRFBP compared to the reference protocol were 151.5% and 45.6%, respectively.

CONCLUSIONS

Through phantom experiments, this study demonstrated that U-HRCT can provide superior-quality images compared to conventional CT in the dentomaxillofacial region. The development of a better image reconstruction method is required to improve image quality and optimize the radiation dose.

Low-contrast lesion detection in neck CT: a multireader study comparing deep learning, iterative, and filtered back projection reconstructions using realistic phantoms

BACKGROUND

Computed tomography (CT) reconstruction algorithms can improve image quality, especially deep learning reconstruction (DLR). We compared DLR, iterative reconstruction (IR), and filtered back projection (FBP) for lesion detection in neck CT.

METHODS

Nine patient-mimicking neck phantoms were examined with a 320-slice scanner at six doses: 0.5, 1, 1.6, 2.1, 3.1, and 5.2 mGy. Each of eight phantoms contained one circular lesion (diameter 1 cm; contrast -30 HU to the background) in the parapharyngeal space; one phantom had no lesions. Reconstruction was made using FBP, IR, and DLR. Thirteen readers were tasked with identifying and localizing lesions in 32 images with a lesion and 20 without lesions for each dose and reconstruction algorithm. Receiver operating characteristic (ROC) and localization ROC (LROC) analysis were performed.

RESULTS

DLR improved lesion detection with ROC area under the curve (AUC) 0.724 ± 0.023 (mean ± standard error of the mean) using DLR versus 0.696 ± 0.021 using IR (p = 0.037) and 0.671 ± 0.023 using FBP (p < 0.001). Likewise, DLR improved lesion localization, with LROC AUC 0.407 ± 0.039 versus 0.338 ± 0.041 using IR (p = 0.002) and 0.313 ± 0.044 using FBP (p < 0.001). Dose reduction to 0.5 mGy compromised lesion detection in FBP-reconstructed images compared to doses ≥ 2.1 mGy (p ≤ 0.024), while no effect was observed with DLR or IR (p ≥ 0.058).

CONCLUSION

DLR improved the detectability of lesions in neck CT imaging. Dose reduction to 0.5 mGy maintained lesion detectability when denoising reconstruction was used.

RELEVANCE STATEMENT

Deep learning enhances lesion detection in neck CT imaging compared to iterative reconstruction and filtered back projection, offering improved diagnostic performance and potential for x-ray dose reduction.

KEY POINTS

Low-contrast lesion detectability was assessed in anatomically realistic neck CT phantoms. Deep learning reconstruction (DLR) outperformed filtered back projection and iterative reconstruction. Dose has little impact on lesion detectability against anatomical background structures.

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 reduction profile: A new method for evaluation of noise reduction techniques in CT

Purpose

Noise power spectrum (NPS) is a commonly used performance metric to evaluate noise‐reduction techniques (NRT) in imaging systems. The images reconstructed with and without an NRT can be compared via their NPS to better understand the NRT's effects on image noise. However, when comparing NPSs, simple visual assessments or a comparison of NPS peaks or medians are often used. These assessments make it difficult to objectively evaluate the effect of noise reduction across all spatial frequencies. In this work, we propose a new noise reduction profile (NRP) to facilitate a more complete and objective evaluation of NPSs for a range of NRTs used specifically in computed tomography (CT).

Methods and materials

The homogeneous section of the ACR or Catphan phantoms was scanned on different CT scanners equipped with the following NRTs: AIDR3D, AiCE, ASiR, ASiR‐V, TrueFidelity, iDose, SAFIRE, and ADMIRE. The images were then reconstructed with all strengths of each NRT in reference to the baseline filtered back projection (FBP) images. One set of the baseline FBP images was also processed with PixelShine, an NRT based on artificial intelligence. The NPSs of the images before and after noise reduction were calculated in both the xy‐plane and along the z‐direction. The difference in the logarithmic scale between each NPS (baseline FBP and NRT) was then calculated and deemed the NRP. Furthermore, the relationship between the NRP and NPS peak positions was mathematically analyzed.

Results

Each NRT has its own unique NRP. By comparing the NPS and NRP for each NRT, it was found that NRP is related to the peak shift of NPS. Additionally, under the assumption that the NPS has one peak and is differentiable, a relationship was mathematically derived between the slope of the NRP at the peak position of the NPS before noise reduction and the shift of the NPS peak position after noise reduction.

Conclusions

A new metric, NRP, was proposed based on NPS to objectively evaluate and compare methods for noise reduction in CT. The NRP can be used to compare the effects of various NRTs on image noise in both the xy‐plane and z‐direction. It also enables unbiased assessment of the detailed noise reduction properties of each NRT over all relevant spatial frequencies.

Comparison of low-contrast detectability between uniform and anatomically realistic phantoms-influences on CT image quality assessment

Objectives

To evaluate the effects of anatomical phantom structure on task-based image quality assessment compared with a uniform phantom background.

Methods

Two neck phantom types of identical shape were investigated: a uniform type containing 10-mm lesions with 4, 9, 18, 30, and 38 HU contrast to the surrounding area and an anatomically realistic type containing lesions of the same size and location with 10, 18, 30, and 38 HU contrast. Phantom images were acquired at two dose levels (CTDIvol of 1.4 and 5.6 mGy) and reconstructed using filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR 3D). Detection accuracy was evaluated by seven radiologists in a 4-alternative forced choice experiment.

Results

Anatomical phantom structure impaired lesion detection at all lesion contrasts (p < 0.01). Detectability in the anatomical phantom at 30 HU contrast was similar to 9 HU contrast in uniform images (91.1% vs. 89.5%). Detection accuracy decreased from 83.6% at 5.6 mGy to 55.4% at 1.4 mGy in uniform FBP images (p < 0.001), whereas AIDR 3D preserved detectability at 1.4 mGy (80.7% vs. 85% at 5.6 mGy, p = 0.375) and was superior to FBP (p < 0.001). In the assessment of anatomical images, superiority of AIDR 3D was not confirmed and dose reduction moderately affected detectability (74.6% vs. 68.2%, p = 0.027 for FBP and 81.1% vs. 73%, p = 0.018 for AIDR 3D).

Conclusions

A lesion contrast increase from 9 to 30 HU is necessary for similar detectability in anatomical and uniform neck phantom images. Anatomical phantom structure influences task-based assessment of iterative reconstruction and dose effects.

Key Points

• A lesion contrast increase from 9 to 30 HU is necessary for similar low-contrast detectability in anatomical and uniform neck phantom images.

• Phantom background structure influences task-based assessment of iterative reconstruction and dose effects.

• Transferability of CT assessment to clinical imaging can be expected to improve as the realism of the test environment increases.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-021-08248-3.

Scanner dependence of adaptive statistical iterative reconstruction with 3D noise power spectrum central frequency and noise magnitude ratios

PURPOSE

In this study, the noise reduction properties of the adaptive statistical iterative reconstruction (IR) on two different CT scanners of 64 and 256-slice were compared and their differences were assessed.

METHODS AND MATERIALS

The homogeneous module of the ACR CT phantom was scanned on the 64 and 256 slices CT scanners from the same vendor in the range of 15-40 mA. On each scanner, the data were reconstructed using filtered back projection (FBP) and at all strengths of IR with the STANDARD kernel. For each reconstruction, a 3D noise power spectrum (NPS) was calculated and the central frequency ratio in the xy plane (CFR_xy ), CFR in the z-direction (CFR_z ), and noise magnitude ratio (NMR) were derived. CFR is the central frequency ratio of NPS between the denoised image and the FBP image, and NMR is the ratio of the areas under the NPS curves. Ideally, both CFR_xy and CFR_z should be near 1, indicating minimal texture changes in both xy and z directions, while NMR should be as close to 0 as possible, indicating more noise reduction.

RESULTS

When comparing strengths with equivalent impact on noise texture, IR on the 64-slice reduced the noise magnitude in the xy plane more than that on the 256-slice. In the z-direction, the IR on the 256-slice produced a central frequency shift on the 256-slice but not on the 64-slice. In addition, the noise reduction effects of the IR on the 256-slice were affected when radiation exposure was below 2.0 mGy, but there was no observable dose-dependence on the 64-slice.

CONCLUSIONS

Our noise property analysis revealed that iterative reconstructions on different scanner platforms from the same vendor can be distinct, with unique effects on the noise texture and magnitude in CT images. The IR on a 64-slice scanner provides slightly enhanced noise reduction and maintains a noise reduction rate independent of dose, unlike the one on a 256-slice scanner. Notably, the IR on the 64-slice scanner was a 2D noise reduction technique (NRT), while the one on the 256-slice was a 3D NRT. These observations showcase the impact of different NRTs on clinical CT images, even when comparing the same NRT on different scanners.

Comparison of CT image quality between the AIDR 3D and FIRST iterative reconstruction algorithms: an assessment based on phantom measurements and clinical images

Modern CT iterative reconstruction algorithms are transitioning from a statistical-based to model-based approach. However, increasing complexity does not ensure improved image quality for all indications, and thorough characterization of new algorithms is important to understand their potential clinical impacts. This study performs both quantitative and qualitative analyses of image quality to compare Canon's statistical-based Adaptive Iterative Dose Reduction 3D (AIDR 3D) algorithm to its model-based algorithm, Forward-projected model-based Iterative Reconstruction SoluTion(FIRST). A phantom was used to measure the task-specific modulation transfer function (MTF_Task), the noise power spectrum (NPS), and the low-contrast object-specific CNR (CNR_LO) for each algorithm using three dose levels and the convolution algorithm (kernel) appropriate for abdomen, lung, and brain imaging. Additionally, MTF_Taskwas measured at four contrast levels, and CNR_LOwas measured for two object sizes. Lastly, three radiologists participated in a preference study to compare clinical image quality for three study types: non-contrast abdomen, pulmonary embolism (PE), and lung screening. Nine questions related to the appearance of anatomical features or image quality characteristics were scored for twenty exams of each type. The behavior of both algorithms depended strongly on the kernel selected. Phantom measurements suggest that FIRST should be beneficial over AIDR 3D for abdomen imaging, but do not suggest a clear overall benefit to FIRST for lung or brain imaging; metrics suggest performance may be equivalent to or slightly favor AIDR 3D, depending on the size of the object being imaged and whether spatial resolution or low-contrast resolution is more important for the task at hand. Overall, radiologists strongly preferred AIDR 3D for lung screening, slightly preferred AIDR 3D for non-contrast abdomen, and had no preference for PE. FIRST was superior for the reduction of metal artifacts. Radiologist preference may be influenced by changes to noise texture.

Forward-projected Model-based Iterative Reconstruction SoluTion in Temporal Bone Computed Tomography: A Comparison Study of All Reconstruction Modes

OBJECTIVE

Identify appropriate reconstruction modes of Forward-projected model-based Iterative Reconstruction SoluTion (FIRST) in temporal bone computed tomography (CT) and investigate the contribution of spatial resolution and noise to the visual assessment.

METHODS

Sixteen temporal bone CT images were reconstructed. Two blinded radiologists assessed 8 anatomical structures and classified the visual assessment. These visual scores were compared across reconstruction modes among each anatomical structure. Visual scores and contrast-to-noise ratio, noise power spectrum (NPS) at low (NPSLow) and high (NPSHigh) spatial frequencies, and 50% modulation transfer function relationships were evaluated.

RESULTS

Visual scores differed significantly for the stapedius muscle and osseous spiral lamina, with CARDIAC SHARP, BONE, and LUNG modes for the osseous spiral lamina scoring highest. Visual scores significantly positively correlated with NPSLow, NPSHigh, and 50% modulation transfer function but negatively with contrast-to-noise ratio.

CONCLUSIONS

Modes providing higher spatial resolution and lower noise reduction showed an improved visual assessment of CT images reconstructed with FIRST.

Task-based assessment of neck CT protocols using patient-mimicking phantoms-effects of protocol parameters on dose and diagnostic performance

Objectives

To assess how modifying multiple protocol parameters affects the dose and diagnostic performance of a neck CT protocol using patient-mimicking phantoms and task-based methods.

Methods

Six patient-mimicking neck phantoms containing hypodense lesions of 1 cm diameter and 30 HU contrast and one non-lesion phantom were examined with 36 CT protocols. All possible combinations of the following parameters were investigated: 100- and 120-kVp tube voltage; tube current modulation (TCM) noise levels of SD 7.5, 10, and 14; pitches of 0.637, 0.813, and 1.388; filtered back projection (FBP); and iterative reconstruction (AIDR 3D). Dose-length products (DLPs) and lesion detectability (assessed by 14 radiologists) were compared with the clinical standard protocol (120 kVp, TCM SD 7.5, 0.813 pitch, AIDR 3D).

Results

The DLP of the standard protocol was 25 mGy•cm; the area under the curve (AUC) was 0.839 (95%CI: 0.790–0.888). Combined effects of tube voltage reduction to 100 kVp and TCM noise level increase to SD 10 optimized protocol performance by improving dose (7.3 mGy•cm) and detectability (AUC 0.884, 95%CI: 0.844–0.924). Diagnostic performance was significantly affected by the TCM noise level at 120 kVp (AUC 0.821 at TCM SD 7.5 vs. 0.776 at TCM SD 14, p = 0.003), but not at 100-kVp tube voltage (AUC 0.839 at TCM SD 7.5 vs. 0.819 at TCM SD 14, p = 0.354), the reconstruction method at 100 kVp (AUC 0.854 for AIDR 3D vs. 0.806 for FBP, p < 0.001), but not at 120-kVp tube voltage (AUC 0.795 for AIDR 3D vs. 0.793 for FBP, p = 0.822), and the tube voltage for AIDR 3D reconstruction (p < 0.001), but not for FBP (p = 0.226).

Conclusions

Combined effects of 100-kVp tube voltage, TCM noise level of SD 10, a pitch of 0.813, and AIDR 3D resulted in an optimal neck protocol in terms of dose and diagnostic performance. Protocol parameters were subject to complex interactions, which created opportunities for protocol improvement.

Key Points

• A task-based approach using patient-mimicking phantoms was employed to optimize a CT system for neck imaging through systematic testing of protocol parameters.

• Combined effects of 100-kVp tube voltage, TCM noise level of SD 10, a pitch of 0.813, and AIDR 3D reconstruction resulted in an optimal protocol in terms of dose and diagnostic performance.

• Interactions of protocol parameters affect diagnostic performance and should be considered when optimizing CT techniques.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07374-8) contains supplementary material, which is available to authorized users.

Association of Radiation Doses and Cancer Risks from CT Pulmonary Angiography Examinations in Relation to Body Diameter

In this study, we aimed to estimate the probability of cancer risk induced by CT pulmonary angiography (CTPA) examinations concerning effective body diameter. One hundred patients who underwent CTPA examinations were recruited as subjects from a single institution in Kuala Lumpur. Subjects were categorized based on their effective diameter size, where 19-25, 25-28, and >28 cm categorized as Groups 1, 2, and 3, respectively. The mean value of the body diameter of the subjects was 26.82 ± 3.12 cm, with no significant differences found between male and female subjects. The risk of cancer in breast, lung, and liver organs was 0.009%, 0.007%, and 0.005% respectively. The volume-weighted CT dose index (CTDIvol) was underestimated, whereas the size-specific dose estimates (SSDEs) provided a more accurate description of the radiation dose and the risk of cancer. CTPA examinations are considered safe but it is essential to implement a protocol optimized following the As Low as Reasonably Achievable (ALARA) principle.

Evaluation of three-dimensional iterative image reconstruction in virtual monochromatic imaging at 40 kilo-electron volts: phantom and clinical studies to assess the image noise and image quality in comparison with other reconstruction techniques

OBJECTIVE

The purpose of this study was to evaluate the image quality in virtual monochromatic imaging (VMI) at 40 kilo-electron volts (keV) with three-dimensional iterative image reconstruction (3D-IIR).

METHODS

A phantom study and clinical study (31 patients) were performed with dual-energy CT (DECT). VMI at 40 keV was obtained and the images were reconstructed using filtered back projection (FBP), 50% adaptive statistical iterative reconstruction (ASiR), and 3D-IIR. We conducted subjective and objective evaluations of the image quality with each reconstruction technique.

RESULTS

The image contrast-to-noise ratio and image noise in both the clinical and phantom studies were significantly better with 3D-IIR than with 50% ASiR, and with 50% ASiR than with FBP (all, p < 0.05). The standard deviation and noise power spectra of the reconstructed images decreased in the order of 3D-IIR to 50% ASiR to FBP, while the modulation transfer function was maintained across the three reconstruction techniques. In most subjective evaluations in the clinical study, the image quality was significantly better with 3D-IIR than with 50% ASiR, and with 50% ASiR than with FBP (all, p < 0.001). Regarding the diagnostic acceptability, all images using 3D-IIR were evaluated as being fully or probably acceptable.

CONCLUSIONS

The quality of VMI at 40 keV is improved by 3D-IIR, which allows the image noise to be reduced and structural details to be maintained.

ADVANCES IN KNOWLEDGE

The improvement of the image quality of VMI at 40 keV by 3D-IIR may increase the subjective acceptance in the clinical setting.

Improved scan method for dental imaging using multidetector computed tomography: a phantom study

OBJECTIVES

This study aimed to propose an improved scan method to shorten irradiation time and reduce radiation exposure.

METHODS

The maxilla of a human head CT phantom and a Catphan phantom were used for qualitative and quantitative assessment, respectively. The phantoms were scanned by a 160-row multidetector CT scanner using volumetric and helical scanning. In volumetric scanning, the tube current varied from 120 to 60 to 30 to 20 mA with a tube voltage of 120 kV. Images were reconstructed with a bone kernel using iterative reconstruction (IR) and filtered back projection. As a reference protocol, helical scanning was performed using our clinical setting with 120 kV. Two dental radiologists independently graded the quality of dental images using a 4-point scale (4, superior to reference; 1, unacceptable). For the quantitative assessment, we assessed the system performance from each scan.

RESULTS

There was no significant difference between the image quality of volumetric scanning using the 60 mA protocol reconstructed with IR and that of the reference (3.08 and 3.00, p = 0.3388). The system performance values at 1.0 cycles/mm of volumetric scanning and 60 mA protocol reconstructed with IR and reference were 0.0038 and 0.0041, respectively. The effective dose of volumetric scanning using the 60 mA protocol was 51.8 µSv, which is a 64.2% reduction to that of the reference.

CONCLUSIONS

We proposed an improved scan method resulting in a 64.2% reduction of radiation dose with one-fourth of irradiation time by combining volumetric scanning and IR technique in multidetector CT.

Image quality of early postoperative CT angiography with reduced contrast material and radiation dose using model-based iterative reconstruction for screening of renal pseudoaneurysms after partial nephrectomy

PURPOSE

To evaluate the image quality of early postoperative CT angiography with low contrast material and radiation dose using model-based iterative reconstruction (FIRST) for screening pseudoaneurysms after partial nephrectomy.

METHODS

CT angiography was obtained before surgery using conventional iterative dose reduction reconstruction (AIDR 3D) with 120 kVp and 600 mgI/kg of contrast material and obtained after partial nephrectomy using FIRST with 80-100 kVp and 360 mgI/kg in 35 patients. Contrast-to-noise ratio, visual image quality scores using a 5-point scale, and longest length of the unaffected renal arteries on maximum intensity projection images were retrospectively compared between FIRST and AIDR 3D.

RESULTS

No significant differences existed in contrast-to-noise ratio or image quality scores of the renal arteries between FIRST and AIDR 3D (25.8 ± 6.6 vs. 25.4 ± 7.0, p = 0.991 and 4.8 ± 0.4 vs. 4.5 ± 0.9, p = 0.515, respectively). Visualization scores and longest length of the peripheral renal arteries in FIRST were significantly superior to those of AIDR 3D (4.3 ± 0.8 vs. 3.5 ± 1.0, p < 0.001 and 100.4 ± 14.9 mm vs. 90.2 ± 15.7 mm, p = 0.010, respectively). The dose-length product with FIRST was significantly lower than that with AIDR 3D (566.1 ± 217.4 mGy.cm vs. 829.8 ± 324.9 mGy.cm, p < 0.001).

CONCLUSION

FIRST can improve visualization of the peripheral renal arteries with contrast material and radiation dose reduced by approximately 30 % compared with AIDR 3D, which enables adequate evaluation of pseudoaneurysms after partial nephrectomy.

Added Value of Ultra-low-dose Computed Tomography, Dose Equivalent to Chest X-Ray Radiography, for Diagnosing Chest Pathology

Purpose:

The purpose of this study was to assess the clinical value of ultra–low-dose computed tomography (ULDCT) compared with chest x-ray radiography (CXR) for diagnosing chest pathology.

Materials and Methods:

A total of 200 patients referred for CXR by outpatient clinics or general practitioners were enrolled prospectively. They underwent CXR (posteroanterior and lateral) and ULDCT (120 kV, 3 mAs) on the same day. In-room time and effective dose were recorded for each examination. Studies were categorized whether they were diagnostic or not, relevant radiologic diagnostic findings were reported, and confidence for diagnosis was recorded by a Likert scale. Differences in diagnostic confidence and effect on management decision were compared.

Results:

In-room time was <2 minutes for CXR and <3 minutes for ULDCT. Effective dose was 0.040 mSv for CXR and 0.071 mSv for ULDCT. CXR was considered diagnostic in 98% and ULDCT in 100%. The mean perceived confidence for diagnosis was 88±12% with CXR and 98±2% with ULDCT (P<0.0001), whereas discrepant findings between CXR and ULDCT were found in 101 of 200 patients. As compared with CXR, ULDCT had added value for management decisions in 40 of 200 patients.

Conclusions:

ULDCT provided added value to the radiologist by improved perceived confidence with a reduction in false-positive and false-negative CXR investigations that had management implications in 20% of patients. The effective dose of ULDCT will not be a limiting factor for introducing ULDCT of the chest on a broad scale in clinical practice.

A method to measure slice sensitivity profiles of CT images under low-contrast and high-noise conditions

Noise reduction features of iterative reconstruction (IR) methods in computed tomography might accompany the sacrifice of the longitudinal resolution, or slice sensitivity profile (SSP), at low contrast-to-noise ratio (CNR) conditions. To assess the benefit of IR methods correctly, the difference of SSP between IR methods and filtered-backprojection (FBP) must be taken into account. Therefore, SSP measurement under low-CNR conditions is necessary. Although edge methods are predominantly used, their performance under low-CNR conditions appears to be not fully established. We developed a method that is compatible with extremely low-CNR conditions. Thin plastic disk-shaped sheets embedded in acrylic resin were used as low-contrast test objects. The lowest peak contrast used was approximately 17 [HU]. We assessed the performance of our method by using FBP images. We identified a source of measurement instability aside from noise: the measured thin-slice SSP is dependent on the orbital phase of helical scan, presumably because of cone-beam artifacts. This impediment to high accuracy is manageable using phase-controlled scans. We confirmed that table position repeatability is much better than the value of the specifications, and therefore the ensemble-averaged images of multiple scans can be used for SSP measurement. Accurate measurement of SSP under extremely low-CNR conditions is possible, even when the test object is visually indiscernible from the noisy background. Low-contrast SSP behavior is elucidated for IR methods (AIDR-3D, FIRST, and AiSR-V) by using this measurement method.

[Improvement of Image Quality in the Axial Section Using High-resolution Scan Mode and Hybrid Iterative Reconstruction in Ultra-high-resolution Computed Tomography]

The purpose of this study is to compare the physical characteristics and visibility of high-resolution and conventional images acquired with the same X-ray dose, and to investigate the superiority of super high-resolution imaging. A Catphan phantom was scanned in the normal resolution (NR), high-resolution (HR), and super high-resolution (SHR) modes of ultra-high-resolution computed tomography at 120 kV and 75 mAs. All images were reconstructed into a 5-mm thick image slices with filtered back-projection (FBP) and hybrid image reconstruction (HIR), which included normal and enhanced adaptive iterative dose reduction 3D (AIDR and eAIDR, respectively). The modulation transfer function (MTF) and noise power spectrum (NPS) were measured using the circular edge method and radial frequency method, respectively. The signal-to-noise ratio (SNR) was then calculated. High-contrast resolution and low-contrast detectability were evaluated visually by five radiological technologists. The MTFs of HR_eAIDR and HR_FBP images were higher than those of NR_FBP images. However, the NPSs of HR_eAIDR and HR_FBP images were larger than those of NR_FBP images. The SNR of HR_eAIDR images was higher than that of NR_FBP and HR_FBP images. The scores of high-contrast resolution of HR_eAIDR, NR_FBP, and HR_FBP images were 13, 8, and 13 cycles/cm, respectively, and the scores of low-contrast detectability were 5, 5, and 6 mm, respectively. Hence, an improvement in high-contrast resolution of signal more than 400 HU in the axial section can be achieved without increasing the radiation dose and decreasing low-contrast detectability with 10 HU using the HR mode and eAIDR.

Periradicular infiltration of the lumbar spine: is iterative reconstruction software necessary to establish ultra-low-dose protocols? A quantitative and qualitative approach

PURPOSE

Computed tomography (CT)-guided periradicular infiltration therapy has emerged as an effective treatment option for patients with low back pain. Concern about radiation exposure requires approaches allowing significant dose reduction. The purpose of this study is to evaluate the need for iterative reconstruction software in CT-guided periradicular infiltration therapy with an ultra-low-dose protocol.

MATERIALS AND METHODS

One hundred patients underwent CT-guided periradicular infiltration therapy of the lumbar spine using an ultra-low-dose protocol with adaptive iterative dose reduction 3D (AIDR 3D) for image reconstruction. In addition, images were reconstructed with filtered back-projection (FBP). Four experienced raters evaluated both reconstruction types for conspicuity of anatomical and instrumental features important for ensuring safe patient treatment. Image noise was measured as a quantitative marker of image quality.

RESULTS

Interrater agreement was good for both AIDR 3D (Kendall's W = 0.83) and FBP (0.78) reconstructions. Readers assigned the same scores for all features and both reconstruction algorithms in 81.3% of cases. Image noise was significantly lower (average SD of 60.07 vs. 99.54, p < 0.05) for AIDR 3D-reconstructed images.

CONCLUSION

Although it significantly lowers image noise, iterative reconstruction software is not mandatory to achieve adequate image quality with an ultra-low-dose CT protocol for guiding periradicular infiltration therapy of the lumbar spine.

Impact of iterative reconstruction vs. filtered back projection on image quality in 320-slice CT coronary angiography: Insights from the CORE320 multicenter study

Iterative reconstruction has been shown to reduce image noise compared with traditional filtered back projection with quantum denoising software (FBP/QDS+) in CT imaging but few comparisons have been made in the same patients without the influence of interindividual factors. The objective of this study was to investigate the impact of adaptive iterative dose reduction in 3-dimensional (AIDR 3D) and FBP/QDS+-based image reconstruction on image quality in the same patients.We randomly selected 100 patients enrolled in the coronary evaluation using 320-slice CT study who underwent CT coronary angiography using prospectively electrocardiogram triggered image acquisition with a 320-detector scanner. Both FBP/QDS+ and AIDR 3D reconstructions were performed using original data. Studies were blindly analyzed for image quality by measuring the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Image quality was assessed qualitatively using a 4-point scale.Median age was 63 years (interquartile range [IQR]: 56-71) and 72% were men, median body mass index 27 (IQR: 24-30) and median calcium score 222 (IQR: 11-644). For all regions of interest, mean image noise was lower for AIDR 3D vs. FBP/QDS+ (31.69 vs. 34.37, P ≤ .001). SNR and CNR were significantly higher for AIDR 3D vs. FBP/QDS+ (16.28 vs. 14.64, P < .001 and 19.21 vs. 17.06, P < .001, respectively). Subjective (qualitative) image quality scores were better using AIDR 3D vs. FBP/QDS+ with means of 1.6 and 1.74, respectively (P ≤ .001).Assessed in the same individuals, iterative reconstruction decreased image noise and raised SNR/CNR as well as subjective image quality scores compared with traditional FBP/QDS+ in 320-slice CT coronary angiography at standard radiation doses.

A simple method for low-contrast detectability, image quality and dose optimisation with CT iterative reconstruction algorithms and model observers

BACKGROUND

The aim of this work was to evaluate detection of low-contrast objects and image quality in computed tomography (CT) phantom images acquired at different tube loadings (i.e. mAs) and reconstructed with different algorithms, in order to find appropriate settings to reduce the dose to the patient without any image detriment.

METHODS

Images of supraslice low-contrast objects of a CT phantom were acquired using different mAs values. Images were reconstructed using filtered back projection (FBP), hybrid and iterative model-based methods. Image quality parameters were evaluated in terms of modulation transfer function; noise, and uniformity using two software resources. For the definition of low-contrast detectability, studies based on both human (i.e. four-alternative forced-choice test) and model observers were performed across the various images.

RESULTS

Compared to FBP, image quality parameters were improved by using iterative reconstruction (IR) algorithms. In particular, IR model-based methods provided a 60% noise reduction and a 70% dose reduction, preserving image quality and low-contrast detectability for human radiological evaluation. According to the model observer, the diameters of the minimum detectable detail were around 2 mm (up to 100 mAs). Below 100 mAs, the model observer was unable to provide a result.

CONCLUSION

IR methods improve CT protocol quality, providing a potential dose reduction while maintaining a good image detectability. Model observer can in principle be useful to assist human performance in CT low-contrast detection tasks and in dose optimisation.

Assessment of structural similarity in CT using filtered backprojection and iterative reconstruction: a phantom study with 3D printed lung vessels

OBJECTIVE

To compare the performance of three generations of CT reconstruction techniques using structural similarity (SSIM) as a measure of image quality for CT scans of a chest phantom with 3D printed lung vessels.

METHODS

CT images of the chest phantom were acquired at seven dose levels by changing the tube current while other acquisition parameters were kept constant. Three CT reconstruction techniques were applied on each acquisition. The first technique was filtered backprojection (FBP), the second technique was FBP with iterative filtering (adaptive iteration dose reduction in 3 dimensions (AIDR 3D)) and the third technique was model-based iterative reconstruction (Forward projected model-based Iterative Reconstruction SoluTion (FIRST)). Image quality of the CT data was quantified in terms of SSIM. The SSIM index was used for image quality comparison between the dose levels and different reconstruction techniques. The SSIM index gives a value between 0 and 1, with 0 as the lowest image quality and 1 as an excellent image quality.

RESULTS

The lowest SSIM index was observed for FBP at all dose levels. The reconstruction technique with the highest SSIM depends on the dose level. For tube currents higher than 80 mA, AIDR 3D showed the highest SSIM index, and for tube currents lower or equal to 80 mA FIRST showed the highest SSIM index.

CONCLUSION

SSIM index is a robust quantity and is correlated to the image quality as perceived by the humans. Advanced CT reconstruction techniques provide better image quality in all conditions compared to FBP. Advances in knowledge: SSIM is a robust measure to compare CT image quality for advanced reconstruction techniques relative to a reference. The 3D print technology is an useful method for the development of dedicated phantoms for CT image quality evaluation.

Objective performance assessment of five computed tomography iterative reconstruction algorithms

OBJECTIVE

Iterative algorithms are gaining clinical acceptance in CT. We performed objective phantom-based image quality evaluation of five commercial iterative reconstruction algorithms available on four different multi-detector CT (MDCT) scanners at different dose levels as well as the conventional filtered back-projection (FBP) reconstruction.

METHODS

Using the Catphan500 phantom, we evaluated image noise, contrast-to-noise ratio (CNR), modulation transfer function (MTF) and noise-power spectrum (NPS). The algorithms were evaluated over a CTDIvol range of 0.75-18.7 mGy on four major MDCT scanners: GE DiscoveryCT750HD (algorithms: ASIR™ and VEO™); Siemens Somatom Definition AS+ (algorithm: SAFIRE™); Toshiba Aquilion64 (algorithm: AIDR3D™); and Philips Ingenuity iCT256 (algorithm: iDose4™). Images were reconstructed using FBP and the respective iterative algorithms on the four scanners.

RESULTS

Use of iterative algorithms decreased image noise and increased CNR, relative to FBP. In the dose range of 1.3-1.5 mGy, noise reduction using iterative algorithms was in the range of 11%-51% on GE DiscoveryCT750HD, 10%-52% on Siemens Somatom Definition AS+, 49%-62% on Toshiba Aquilion64, and 13%-44% on Philips Ingenuity iCT256. The corresponding CNR increase was in the range 11%-105% on GE, 11%-106% on Siemens, 85%-145% on Toshiba and 13%-77% on Philips respectively. Most algorithms did not affect the MTF, except for VEO™ which produced an increase in the limiting resolution of up to 30%. A shift in the peak of the NPS curve towards lower frequencies and a decrease in NPS amplitude were obtained with all iterative algorithms. VEO™ required long reconstruction times, while all other algorithms produced reconstructions in real time. Compared to FBP, iterative algorithms reduced image noise and increased CNR.

CONCLUSIONS

The iterative algorithms available on different scanners achieved different levels of noise reduction and CNR increase while spatial resolution improvements were obtained only with VEO™. This study is useful in that it provides performance assessment of the iterative algorithms available from several mainstream CT manufacturers.

Metal artefact reduction for patients with metallic dental fillings in helical neck computed tomography: comparison of adaptive iterative dose reduction 3D (AIDR 3D), forward-projected model-based iterative reconstruction solution (FIRST) and AIDR 3D with single-energy metal artefact reduction (SEMAR)

OBJECTIVES

To compare the differences in metal artefact degree and the depiction of structures in helical neck CT, in patients with metallic dental fillings, among adaptive iterative dose reduction three dimensional (AIDR 3D), forward-projected model-based iterative reconstruction solution (FIRST) and AIDR 3D with single-energy metal artefact reduction (SEMAR-A).

METHODS

In this retrospective clinical study, 22 patients (males, 13; females, 9; mean age, 64.6 ± 12.6 years) with metallic dental fillings who underwent contrast-enhanced helical CT involving the oropharyngeal region were included. Neck axial images were reconstructed with AIDR 3D, FIRST and SEMAR-A. Metal artefact degree and depiction of structures (the apex and root of the tongue, parapharyngeal space, superior portion of the internal jugular chain and parotid gland) were evaluated on a four-point scale by two radiologists. Placing regions of interest, standard deviations of the oral cavity and nuchal muscle (at the slice where no metal exists) were measured and metal artefact indices were calculated (the square root of the difference of the squares of them).

RESULTS

In SEMAR-A, metal artefact was significantly reduced and depictions of all structures were significantly improved compared with those in FIRST and AIDR 3D (p ≤ 0.001, sign test). Metal artefact index for the oral cavity in AIDR 3D/FIRST/SEMAR-A was 572.0/477.7/88.4, and significant differences were seen between each reconstruction algorithm (p < 0.0001, Wilcoxon signed-rank test).

CONCLUSIONS

SEMAR-A could provide images with lesser metal artefact and better depiction of structures than AIDR 3D and FIRST.

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.

Image Quality and Radiation Dose of CT Coronary Angiography with Automatic Tube Current Modulation and Strong Adaptive Iterative Dose Reduction Three-Dimensional (AIDR3D)

Purpose

To investigate image quality and radiation dose of CT coronary angiography (CTCA) scanned using automatic tube current modulation (ATCM) and reconstructed by strong adaptive iterative dose reduction three-dimensional (AIDR3D).

Methods

Eighty-four consecutive CTCA patients were collected for the study. All patients were scanned using ATCM and reconstructed with strong AIDR3D, standard AIDR3D and filtered back-projection (FBP) respectively. Two radiologists who were blinded to the patients' clinical data and reconstruction methods evaluated image quality. Quantitative image quality evaluation included image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). To evaluate image quality qualitatively, coronary artery is classified into 15 segments based on the modified guidelines of the American Heart Association. Qualitative image quality was evaluated using a 4-point scale. Radiation dose was calculated based on dose-length product.

Results

Compared with standard AIDR3D, strong AIDR3D had lower image noise, higher SNR and CNR, their differences were all statistically significant (P<0.05); compared with FBP, strong AIDR3D decreased image noise by 46.1%, increased SNR by 84.7%, and improved CNR by 82.2%, their differences were all statistically significant (P<0.05 or 0.001). Segments with diagnostic image quality for strong AIDR3D were 336 (100.0%), 486 (96.4%), and 394 (93.8%) in proximal, middle, and distal part respectively; whereas those for standard AIDR3D were 332 (98.8%), 472 (93.7%), 378 (90.0%), respectively; those for FBP were 217 (64.6%), 173 (34.3%), 114 (27.1%), respectively; total segments with diagnostic image quality in strong AIDR3D (1216, 96.5%) were higher than those of standard AIDR3D (1182, 93.8%) and FBP (504, 40.0%); the differences between strong AIDR3D and standard AIDR3D, strong AIDR3D and FBP were all statistically significant (P<0.05 or 0.001). The mean effective radiation dose was (2.55±1.21) mSv.

Conclusion

Compared with standard AIDR3D and FBP, CTCA with ATCM and strong AIDR3D could significantly improve both quantitative and qualitative image quality.

A Survey of Radiation Doses in CT Urography Before and After Implementation of Iterative Reconstruction

OBJECTIVE

The purpose of this study was to survey the radiation dose used in CT urography (CTU) in routine clinical practice, both before and after implementation of a scanning protocol that uses iterative reconstruction (Adaptive Iterative Dose Reduction 3D [AIDR 3D]).

MATERIALS AND METHODS

We retrospectively surveyed dose reports from consecutive CTU examinations performed in 2011 with the use of 64- and 320-MDCT scanners that were reconstructed with filtered back projection (FBP) and from CTU examinations performed from May 2012 through November 2013 that were reconstructed with the use of AIDR 3D. Findings from these dose reports were then correlated with such patient characteristics as weight and body mass index (BMI; weight in kilograms divided by the square of height in meters). Only dose reports from single-bolus three-phase CTU examinations were included in the study. The volume CT dose index, dose-length product (DLP), and effective dose were surveyed both per examination and per phase by use of published effective dose DLP conversion factors. Image quality was evaluated subjectively for a subset of patients.

RESULTS

The two study cohorts included 82 patients (median patient weight, 75.0 kg; median BMI, 25.3) who underwent CTU with FBP and 85 patients (median patient weight, 78.0 kg; median BMI, 24.5) who underwent CTU with AIDR 3D. The median total DLP and median effective dose were 924 mGy · cm and 13.0 mSv, respectively, in the CTU with the FBP cohort and 433 mGy · cm and 6.1 mSv, respectively, in the CTU with the AIDR 3D cohort. The median DLP in the unenhanced, nephrogenic, and excretory phases was 218, 300, and 441 mGy · cm, respectively, in patients undergoing CTU with FBP and 114, 121, and 190 mGy · cm, respectively, in patients undergoing CTU with AIDR 3D. Image quality was diagnostic in both groups, with relatively fewer artifacts noted on scans obtained using CTU with AIDR 3D.

CONCLUSION

Our study presents detailed dose data from three-phase CTU examinations performed both before and after implementation of iterative reconstruction. Implementation of a CTU protocol using iterative reconstruction resulted in a mean effective dose of 6.1 mSv with preservation of clinical diagnostic image quality.

Added value of a single-energy projection-based metal-artifact reduction algorithm for the computed tomography evaluation of oral cavity cancers

PURPOSE

The purpose of our study was to investigate the added value of the single-energy projection-based metallic artifact reduction (SEMAR) technique on the visualization and diagnostic confidence of oral cavity cancers.

MATERIALS AND METHODS

Contrast-enhanced CT was performed on 40 patients with dental metalwork. Of these, 18 patients had pathologically confirmed oral cavity cancer, and the other 22 patients had no lesions. CT attenuation and noise in the oral cavity were compared between the conventional and SEMAR images. Two radiologists visually graded the diagnostic confidence on a 5-point scale from 1 (definitely absent) to 5 (definitely present). The value of the SEMAR was assessed in a receiver-operating characteristic curve analysis.

RESULTS

The artifact of the SEMAR images was significantly lower than that of the conventional images (38.4 ± 18.0 HU vs. 187.7 ± 162.7 HU; P < 0.01). Reviewers 1 and 2 detected 10 and 7 more lesions with the SEMAR, respectively. Areas under the curve for the conventional and SEMAR reconstruction were 0.761 and 0.942, respectively, for reviewer 1 and 0.701 and 0.864, respectively, for reviewer 2.

CONCLUSION

The SEMAR significantly improved the oral cavity cancer visualization and diagnostic confidence.

Diagnostic Performance and Dose Comparison of Filtered Back Projection and Adaptive Iterative Dose Reduction Three-dimensional CT Enterography in Children and Young Adults

PURPOSE

To investigate diagnostic performance and radiation dose with the use of computed tomographic (CT) enterography in children and young adults and to compare reconstruction with filtered back projection (FBP) to that with adaptive iterative dose reduction (AIDR) with three-dimensional (3D) processing.

MATERIALS AND METHODS

This retrospective investigation was HIPAA compliant and approved by the institutional review board. Informed consent was waived. CT enterographic examinations performed between October 2008 and June 2009 with FBP and between August 2012 and April 2014 with AIDR 3D in patients who had received histologic evaluation within 45 days of imaging were included. Two reviewers retrospectively and independently evaluated the studies for findings of active inflammation, and diagnostic performance and interreader reliability were assessed. The reference standard was histologic findings. Objective and subjective image quality also was assessed. The size-specific dose estimate was compared between the two groups. Two-sample t tests or analysis of variance tests were performed to assess for differences in diagnostic accuracy, image quality, and radiation dose between the FBP and AIDR 3D examinations.

RESULTS

Fifty patients were included in the FBP group (mean age, 14.1 years; range, 8-21 years) and 68 patients were in the AIDR 3D group (mean age, 13.2 years; range, 2-29 years). Sensitivity and specificity for detection of active inflammation were 96% (26 of 27) and 96% (22 of 23), respectively, for the FBP group and 90% (45 of 50) and 89% (16 of 18), respectively, for the AIDR 3D group. Dichotomous interreader reliability (κ) for the entire group was 0.86. The mean size-specific dose estimate for all weights was significantly lower for the AIDR 3D group (6.1 mGy ± 2.1) than that for the FBP group (16.7 mGy ± 5.2; P < .0001). No significant difference was found in objective image noise for soft-tissue structures (P = .2-.8).

CONCLUSION

CT enterography is highly accurate for detection of active inflammation in pediatric patients and has excellent interreader reliability. Reduced-dose CT enterography with AIDR 3D allowed substantial dose reduction compared with that used with FBP CT enterographic examinations, while maintaining a high diagnostic performance.

Choosing the best reconstruction technique in abdominal computed tomography: a systematic approach

OBJECTIVE

There is uncertainty regarding the effect of iterative reconstruction (IR) techniques and other reconstruction algorithms on image quality. The aim of this study was to optimize image quality in relation to radiation dose in computed tomography (CT) liver examinations by comparing images reconstructed with different abdominal filters with and without IR.

METHODS

An anthropomorphic phantom was scanned on a Toshiba Aquilion ONE CT scanner. Images at 2 different dose levels were reconstructed with 12 different body reconstruction filters, all with both filtered back-projection and Adaptive Iterative Dose Reduction 3 dimensional. Receiver operating characteristic curves were constructed. The 2 reconstruction combinations with the highest scores from the phantom study were evaluated in a second comparison of clinical images. Six liver examinations were reconstructed with both filters and evaluated using visual grading analysis.

RESULTS

Two combinations of reconstruction filters and IR were the only 2 options among the 8 best images at both dose levels (area under the curve, 0.96 and 0.94 for 15 mGy as well as 0.86 and 0.84 for 10 mGy). In the patient study, one of these filters in combination with IR scored slightly higher than the other in combination with IR (mean score, 2.60 and 2.57, respectively; P = 0.56). Iterative reconstruction did not significantly increase lesion detectability for any of the filters.

CONCLUSIONS

This study indicates that the preferred choice for reconstruction of CT liver examinations performed with the Toshiba Aquilion ONE should be the FC18 filter with IR, although the IR technique did not significantly improve lesion detectability and did not compensate for the dose reduction in this study.

Comparison between human and model observer performance in low-contrast detection tasks in CT images: application to images reconstructed with filtered back projection and iterative algorithms

OBJECTIVE

To compare low-contrast detectability (LCDet) performance between a model [non-pre-whitening matched filter with an eye filter (NPWE)] and human observers in CT images reconstructed with filtered back projection (FBP) and iterative [adaptive iterative dose reduction three-dimensional (AIDR 3D; Toshiba Medical Systems, Zoetermeer, Netherlands)] algorithms.

METHODS

Images of the Catphan® phantom (Phantom Laboratories, New York, NY) were acquired with Aquilion ONE™ 320-detector row CT (Toshiba Medical Systems, Tokyo, Japan) at five tube current levels (20-500 mA range) and reconstructed with FBP and AIDR 3D. Samples containing either low-contrast objects (diameters, 2-15 mm) or background were extracted and analysed by the NPWE model and four human observers in a two-alternative forced choice detection task study. Proportion correct (PC) values were obtained for each analysed object and used to compare human and model observer performances. An efficiency factor (η) was calculated to normalize NPWE to human results.

RESULTS

Human and NPWE model PC values (normalized by the efficiency, η = 0.44) were highly correlated for the whole dose range. The Pearson's product-moment correlation coefficients (95% confidence interval) between human and NPWE were 0.984 (0.972-0.991) for AIDR 3D and 0.984 (0.971-0.991) for FBP, respectively. Bland-Altman plots based on PC results showed excellent agreement between human and NPWE [mean absolute difference 0.5 ± 0.4%; range of differences (-4.7%, 5.6%)].

CONCLUSION

The NPWE model observer can predict human performance in LCDet tasks in phantom CT images reconstructed with FBP and AIDR 3D algorithms at different dose levels.

ADVANCES IN KNOWLEDGE

Quantitative assessment of LCDet in CT can accurately be performed using software based on a model observer.