Contrast-to-noise ratio and low-contrast object resolution on full- and low-dose MDCT: SAFIRE versus filtered back projection in a low-contrast object phantom and in the liver. AJR Am J Roentgenol. 2012;199:8-18. [PMID: 22733888 DOI: 10.2214/ajr.11.7421]

A Practical Method for Slice Spacing Measurement Using the American Association of Physicists in Medicine Computed Tomography Performance Phantom

Background

The slice spacing has a crucial role in the accuracy of computed tomography (CT) images in sagittal and coronal planes. However, there is no practical method for measuring the accuracy of the slice spacing.

Purpose

This study proposes a novel method to automatically measure the slice spacing using the American Association of Physicists in Medicine (AAPM) CT performance phantom.

Methods

The AAPM CT performance phantom module 610-04 was used to measure slice spacing. The process of slice spacing measurement involves a pair of axial images of the module containing ramp aluminum objects located at adjacent slice positions. The middle aluminum plate of each image was automatically segmented. Next, the two segmented images were combined to produce one image with two stair objects. The centroid coordinates of two stair objects were automatically determined. Subsequently, the distance between these two centroids was measured to directly indicate the slice spacing. For comparison, the slice spacing was calculated by accessing the slice position attributes from the DICOM header of both images. The proposed method was tested on phantom images with variations in slice spacing and field of view (FOV).

Results

The results showed that the automatic measurement of slice spacing was quite accurate for all variations of slice spacing and FOV, with average differences of 9.0% and 9.3%, respectively.

Conclusion

A new automated method for measuring the slice spacing using the AAPM CT phantom was successfully demonstrated and tested for variations of slice spacing and FOV. Slice spacing measurement may be considered an additional parameter to be checked in addition to other established parameters.

Impact of radiation dose on the detection of interstitial lung changes and image quality in low-dose chest CT - Assessment in multiple dose levels from a single patient scan

PURPOSE

To assess image quality and detectability of interstitial lung changes using multiple radiation doses from the same chest CT scan of patients with suspected interstitial lung disease (ILD).

METHOD

Retrospective study of consecutive adult patients with suspected ILD receiving unenhanced chest CT as single-energy dual-source acquisition at 100 kVp (Dual-split mode). 67% and 33% of the overall tube current time product were assigned to tube A and B, respectively. 100%-dose was 2.34 ± 0.97 mGy. Five different radiation doses (100%, 67%, 45%, 39%, 33%) were reconstructed from this single acquisition using linear-blending technique. Two blinded radiologists assessed reticulations, ground-glass opacities (GGO) and honeycombing as well as subjective image noise. Percentage agreement (PA) as compared to 100%-dose were calculated. Non-parametric statistical tests were used.

RESULTS

A total of 228 patients were included (61.2 ± 14.6 years,146 female). PA was highest for honeycombing (>96%) and independent of dose reduction (P > 0.8). PA for reticulations and GGO decreased when reducing the radiation dose from 100% to 67% for both readers (reticulations: 83.3% and 93.9%; GGO: 87.7% and 79.8% for reader 1 and 2, respectively). Additional dose reduction did not significantly change PA for both readers (all P > 0.05). Subjective image noise increased with decreasing radiation dose (Spearman Rho of ρ = 0.34 and ρ = 0.53 for reader 1 and 2, respectively, P < 0.001).

CONCLUSIONS

Radiation dose reduction had a stronger impact on subtle interstitial lung changes. Detectability decreased with initial dose reduction indicating that a minimum dose is needed to maintain diagnostic accuracy in chest CT for suspected ILD.

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

OBJECTIVES

To assess image noise, diagnostic performance, and potential for radiation dose reduction of photon-counting detector (PCD) computed tomography (CT) with quantum iterative reconstruction (QIR) in the detection of hypoattenuating and hyperattenuating focal liver lesions compared with energy-integrating detector (EID) CT.

MATERIALS AND METHODS

A medium-sized anthropomorphic abdominal phantom with liver parenchyma and lesions (diameter, 5-10 mm; hypoattenuating and hyperattenuating from -30 HU to +90 HU at 120 kVp) was used. The phantom was imaged on ( a ) a third-generation dual-source EID-CT (SOMATOM Force, Siemens Healthineers) in the dual-energy mode at 100 and 150 kVp with tin filtration and ( b ) a clinical dual-source PCD-CT at 120 kVp (NAEOTOM Alpha, Siemens). Scans were repeated 10 times for each of 3 different radiation doses of 5, 2.5, and 1.25 mGy. Datasets were reconstructed as virtual monoenergetic images (VMIs) at 60 keV for both scanners and as linear-blended images (LBIs) for EID-CT. For PCD-CT, VMIs were reconstructed with different strength levels of QIR (QIR 1-4) and without QIR (QIR-off). For EID-CT, VMIs and LBIs were reconstructed using advanced modeled iterative reconstruction at a strength level of 3. Noise power spectrum was measured to compare image noise magnitude and texture. A channelized Hotelling model observer was used to assess diagnostic accuracy for lesion detection. The potential for radiation dose reduction using PCD-CT was estimated for the QIR strength level with the highest area under the curve compared with EID-CT for each radiation dose.

RESULTS

Image noise decreased with increasing QIR level at all radiation doses. Using QIR-4, noise reduction was 41%, 45%, and 59% compared with EID-CT VMIs and 12%, 18%, and 33% compared with EID-CT LBIs at 5, 2.5, and 1.25 mGy, respectively. The peak spatial frequency shifted slightly to lower frequencies at higher QIR levels. Lesion detection accuracy increased at higher QIR levels and was higher for PCD-CT compared with EID-CT VMIs. The improvement in detection with PCD-CT was strongest at the lowest radiation dose, with an area under the receiver operating curve of 0.917 for QIR-4 versus 0.677 for EID-CT VMIs for hyperattenuating lesions, and 0.900 for QIR-4 versus 0.726 for EID-CT VMIs for hypoattenuating lesions. Compared with EID-CT LBIs, detection was higher for QIR 1-4 at 2.5 mGy and for QIR 2-4 at 1.25 mGy (eg, 0.900 for QIR-4 compared with 0.854 for EID-CT LBIs at 1.25 mGy). Radiation dose reduction potential of PCD-CT with QIR-4 was 54% at 5 mGy compared with VMIs and 39% at 2.5 mGy compared with LBIs.

CONCLUSIONS

Compared with EID-CT, PCD-CT with QIR substantially improved focal liver lesion detection, especially at low radiation dose. This enables substantial radiation dose reduction while maintaining diagnostic accuracy.

W, Barreto LO, Secaf A, Mermejo LM, Lucchesi FR, Tucci Jr. S, Elias Junior J, Molina CAF, Muglia VF. Histogram analysis in the differentiation between adrenal adenomas and pheochromocytomas: the value of a single measurement

Objective

To assess the diagnostic accuracy of histogram analysis on unenhanced computed tomography (CT) for differentiating between adrenal adenomas and pheochromocytomas (PCCs).

Materials and Methods

We retrospectively identified patients with proven PCCs who had undergone CT examinations between January 2009 and July 2019 at one of two institutions. For each PCC, we selected one or two adenomas diagnosed within two weeks of the date of diagnosis of the PCC. For each lesion, two readers scored the size, determined the mean attenuation, and generated a voxel histogram. The 10th percentile (P10) was obtained from the conventional histogram analysis, as well as being calculated with the following formula: P10 = mean attenuation - (1.282 × standard deviation). The mean attenuation threshold, histogram analysis (observed) P10, and calculated P10 (calcP10) were compared in terms of their diagnostic accuracy.

Results

We included 52 adenomas and 29 PCCs. The sensitivity, specificity, and accuracy of the mean attenuation threshold were 75.0%, 100.0%, and 82.5%, respectively, for reader 1, whereas they were 71.5%, 100.0%, and 81.5%, respectively, for reader 2. The sensitivity, specificity, and accuracy of the observed P10 and calcP10 were equal for both readers: 90.4%, 96.5%, and 92.6%, respectively, for reader 1; and 92.3%, 93.1%, and 92.6%, respectively, for reader 2. The increase in sensitivity was significant for both readers (p = 0.009 and p = 0.005, respectively).

Conclusion

For differentiating between adenomas and PCCs, the histogram analysis (observed P10 and calcP10) appears to outperform the mean attenuation threshold as a diagnostic criterion.

Submillisievert CT chest for COVID-19 patients in a rural hospital with limited resources

Background

This is a secondary analysis of prospectively acquired data approved by the hospital institutional board committee. We performed a retrospective chart review of 463 patients who underwent a CT Chest for suspected COVID-19 infection between April 1st, 2020, and March 31st, 2021. Patients were grouped based on the CT chest obtained protocol: ultra-low dose or full dose. The likelihood of suspicion of COVID-19 infection was classified on a Likert scale based on the probability of pulmonary involvement. For each group, the sensitivity and specificity of CT were compared to nasopharyngeal swab as standard of reference. The median dose length product and duration of apnea were compared between both groups using two-tailed Mann–Whitney U test. The aim of this study is to share our experience of reducing radiation dose in COVID-19 patients by using an ultra-low dose CT chest protocol on a 16 row multidetector CT scan in a hospital with limited resources.

Results

Two hundred sixty-nine patients underwent a full dose CT and 194 patients an ultra-low dose CT. In the former group, the median dose length product was 341.11 mGy*cm [Interquartile range (IQR), 239.1–443.2] and the median duration of apnea was 13.29 s [IQR, 10.85–15.73]. In the latter group, the median dose length product was 30.8 mGy*cm [IQR, 28.9–32.7] and median duration of apnea was 8.27 s [IQR, 7.69–8.85]. The sensitivity of the ultra-low dose CT was 91.2% and that of the full dose was 94%.

Conclusion

A 90% reduction in estimated dose and 38% reduction in apnea duration could be achieved using an ultra-low dose CT chest protocol on a 16-row MDCT without significant loss in the sensitivity of CT to detect COVID-related parenchymal involvement.

A Review of Deep Learning CT Reconstruction: Concepts, Limitations, and Promise in Clinical Practice

Purpose of Review

Deep Learning reconstruction (DLR) is the current state-of-the-art method for CT image formation. Comparisons to existing filter back-projection, iterative, and model-based reconstructions are now available in the literature. This review summarizes the prior reconstruction methods, introduces DLR, and then reviews recent findings from DLR from a physics and clinical perspective.

Recent Findings

DLR has been shown to allow for noise magnitude reductions relative to filtered back-projection without suffering from “plastic” or “blotchy” noise texture that was found objectionable with most iterative and model-based solutions. Clinically, early reader studies have reported increases in subjective quality scores and studies have successfully implemented DLR-enabled dose reductions.

Summary

The future of CT image reconstruction is bright; deep learning methods have only started to tackle problems in this space via addressing noise reduction. Artifact mitigation and spectral applications likely be future candidates for DLR applications.

Unenhanced abdominal low-dose CT reconstructed with deep learning-based image reconstruction: image quality and anatomical structure depiction

Purpose

To evaluate the utility of deep learning-based image reconstruction (DLIR) algorithm in unenhanced abdominal low-dose CT (LDCT).

Materials and methods

Two patient groups were included in this prospective study: 58 consecutive patients who underwent unenhanced abdominal standard-dose CT reconstructed with hybrid iterative reconstruction (SDCT group) and 48 consecutive patients who underwent unenhanced abdominal LDCT reconstructed with high strength level of DLIR (LDCT group). The background noise and signal-to-noise ratio (SNR) of the liver, pancreas, spleen, kidney, abdominal aorta, inferior vena cava, and portal vein were calculated. Two radiologists qualitatively assessed the overall image noise, overall image quality, and abdominal anatomical structures depiction. Quantitative and qualitative parameters and size-specific dose estimates (SSDE) were compared between SDCT and LDCT groups.

Results

The background noise was lower in LDCT group than in SDCT group (P = 0.02). SNRs were higher in LDCT group than in SDCT group (P < 0.001–0.004) except for the liver. Overall image noise was superior in LDCT group than in SDCT group (P < 0.001). Overall image quality was not different between SDCT and LDCT groups (P = 0.25–0.26). Depiction of almost all abdominal anatomical structures was equal to or better in LDCT group than in SDCT group (P < 0.001–0.88). The SSDE was lower in LDCT group (4.0 mGy) than in SDCT group (20.6 mGy) (P < 0.001).

Conclusions

DLIR facilitates substantial radiation dose reduction of > 75% and significantly reduces background noise. DLIR can maintain image quality and anatomical structure depiction in unenhanced abdominal LDCT.

Effect of a new deep learning image reconstruction algorithm for abdominal computed tomography imaging on image quality and dose reduction compared with two iterative reconstruction algorithms: a phantom study

Background

New reconstruction algorithms based on deep learning have been developed to correct the image texture changes related to the use of iterative reconstruction algorithms. The purpose of this study was to evaluate the impact of a new deep learning image reconstruction [Advanced intelligent Clear-IQ Engine (AiCE)] algorithm on image-quality and dose reduction compared to a hybrid iterative reconstruction (AIDR 3D) algorithm and a model-based iterative reconstruction (FIRST) algorithm.

Methods

Acquisitions were carried out using the ACR 464 phantom (and its body ring) at six dose levels (volume computed tomography dose index 15/10/7.5/5/2.5/1 mGy). Raw data were reconstructed using three levels (Mild/Standard/Strong) of AIDR 3D, of FIRST and AiCE. Noise-power-spectrum (NPS) and task-based transfer function (TTF) were computed. Detectability index was computed to model the detection of a small calcification (1.5-mm diameter and 500 HU) and a large mass in the liver (25-mm diameter and 120 HU).

Results

NPS peaks were lower with AiCE than with AIDR 3D (-41%±6% for all levels) or FIRST (-15%±6% for Strong level and -41%±11% for both other levels). The average NPS spatial frequency was lower with AICE than AIDR 3D (-9%±2% using Mild and -3%±2% using Strong) but higher than FIRST for Standard (6%±3%) and Strong (25%±3%) levels. For acrylic insert, values of TTF at 50 percent were higher with AICE than AIDR 3D and FIRST, except for Mild level (-6%±6% and -13%±3%, respectively). For bone insert, values of TTF at 50 percent were higher with AICE than AIDR 3D but lower than FIRST (-19%±14%). For both simulated lesions, detectability index values were higher with AICE than AIDR 3D and FIRST (except for Strong level and for the small feature; -21%±14%). Using the Standard level, dose could be reduced by -79% for the small calcification and -57% for the large mass using AICE compared to AIDR 3D.

Conclusions

The new deep learning image reconstruction algorithm AiCE generates an image-quality with less noise and/or less smudged/smooth images and a higher detectability than the AIDR 3D or FIRST algorithms. The outcomes of our phantom study suggest a good potential of dose reduction using AiCE but it should be confirmed clinically in patients.

Estimating subjective evaluation of low-contrast resolution using convolutional neural networks

To develop a convolutional neural network-based method for the subjective evaluation of computed tomography (CT) images having low-contrast resolution due to imaging conditions and nonlinear image processing. Four radiological technologists visually evaluated CT images that were reconstructed using three nonlinear noise reduction processes (AIDR 3D, AIDR 3D Enhanced, AiCE) on a CT system manufactured by CANON. The visual evaluation consisted of two items: low contrast detectability (score: 0-9) and texture pattern (score: 1-5). Four AI models with different convolutional and max pooling layers were constructed and trained on pairs of CANON CT images and average visual assessment scores of four radiological technologists. CANON CT images not used for training were used to evaluate prediction performance. In addition, CT images scanned with a SIEMENS CT system were input to each AI model for external validation. The mean absolute error and correlation coefficients were used as evaluation metrics. Our proposed AI model can evaluate low-contrast detectability and texture patterns with high accuracy, which varies with the dose administered and the nonlinear noise reduction process. The proposed AI model is also expected to be suitable for upcoming reconstruction algorithms that will be released in the future.

A pilot study of near-infrared fluorescence guided surgery for primary tumor localization and lymph node mapping in colorectal cancer

Background

This pilot study aimed to evaluate the feasibility of near-infrared fluorescence imaging for primary tumor localization, lymph node mapping, and metastatic lymph node detection in colorectal cancer (CRC) using indocyanine green (ICG).

Methods

A total of 11 patients with CRC were prospectively enrolled. ICG (25 mg dissolved in 30 mL sterile water) was intravenously injected preoperatively, and the fluorescence intensity of the primary tumor, lymph nodes, and normal tissues, as well as the signal-to-background ratio (SBR) and contrast-to-noise ratio (CNR) were measured at 0.5, 1, 2, 4, and 24 h after ICG injection.

Results

The primary tumor could be located intraoperatively, and the tumor boundary was clear at 2–4 h. There was good contrast in the fluorescence intensity between tumor and normal tissues (SBR =2.11±0.36, CNR =8.74±0.35). The lymph node detection rate was 95% (38/40), and the SBR threshold of lymph nodes was 1.13.

Conclusions

This pilot study showed that primary tumor localization and lymph node mapping in CRC is feasible using near-infrared fluorescence imaging technology, though metastatic lymph nodes cannot be discriminated from benign ones. In addition, cancer nodules missed by both white light mode and palpation by the surgeon were unexpectedly found, resulting in a change in the surgical prognosis in 9.1% (1/11) of patients.

CT Noise-Reduction Methods for Lower-Dose Scanning: Strengths and Weaknesses of Iterative Reconstruction Algorithms and New Techniques

Iterative reconstruction (IR) algorithms are the most widely used CT noise-reduction method to improve image quality and have greatly facilitated radiation dose reduction within the radiology community. Various IR methods have different strengths and limitations. Because IR algorithms are typically nonlinear, they can modify spatial resolution and image noise texture in different regions of the CT image; hence traditional image-quality metrics are not appropriate to assess the ability of IR to preserve diagnostic accuracy, especially for low-contrast diagnostic tasks. In this review, the authors highlight emerging IR algorithms and CT noise-reduction techniques and summarize how these techniques can be evaluated to help determine the appropriate radiation dose levels for different diagnostic tasks in CT. In addition to advanced IR techniques, we describe novel CT noise-reduction methods based on convolutional neural networks (CNNs). CNN-based noise-reduction techniques may offer the ability to reduce image noise while maintaining high levels of image detail but may have unique drawbacks. Other novel CT noise-reduction methods are being developed to leverage spatial and/or spectral redundancy in multiphase or multienergy CT. Radiologists and medical physicists should be familiar with these different alternatives to adapt available CT technology for different diagnostic tasks. The scope of this article is (a) to review the clinical applications of IR algorithms as well as their strengths, weaknesses, and methods of assessment and (b) to explore new CT image reconstruction and noise-reduction techniques that promise to facilitate radiation dose reduction. ^©RSNA, 2021.

Effect of energy level on the spatial resolution and noise frequency characteristics of virtual monochromatic images: a phantom experiment using four types of CT scanners

PURPOSE

The purpose of the study is to evaluate the effect of energy level on the modulation transfer functions (MTF) and noise power spectra (NPS) of virtual monochromatic images (VMIs) obtained using four types of computed-tomographic (CT) scanners: Revolution, SOMATOM, IQon, and Aquilion.

MATERIALS AND METHODS

VMIs were obtained at 70, 60, and 50 kiloelectron volts (keV), and also at the lowest keV available in each scanner. We evaluated the MTF and NPS in the VMIs obtained at each keV.

RESULTS

No significant effect of the energy level on the MTF was observed in IQon, whereas the spatial resolution decreased as the energy level decreased in the other types of scanners. The NPS curves tended to increase as the energy levels decreased with three types of scanners other than Aquilion.

CONCLUSION

The spatial resolution and noise frequency characteristics of VMIs may be affected by the energy level, and the effects of energy level on these characteristics differ depending on the type of CT scanners.

The potential of iodinated contrast reduction in dual-energy CT thoracic angiography; an evaluation of image quality

INTRODUCTION

The purpose of this study was to compare a dual energy CT (DECT) protocol with 50% reduction of iodinated contrast to a single energy CT (SECT) protocol using standard contrast dose in imaging of the thoracic aorta.

METHODS

DECT with a 50% reduction in iodinated contrast was compared with SECT. For DECT, monoenergetic images at 50, 55, 60, 65, 68, 70, and 74 keV were reconstructed with adaptive statistical iterative reconstruction (ASiR-V) of 50% and 80%. Objective image quality parameters included intravascular attenuation (HU), image noise (SD), contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR). Two independent radiologists subjectively assessed the image quality for the 55 and 68 keV DECT reconstructions and SECT on a five-point Likert scale.

RESULTS

Across 14 patients, the intravascular attenuation at 50-55 keV was comparable to SECT (p > 0.05). The CNRs were significantly lower for DECT with ASIR-V 50% compared to SECT for all keV-values (p < 0.05 for all). For ASIR-V 80%, CNR was comparable to SECT at energies below 60 keV (p > 0.05). The subjective image quality was comparable between DECT and SECT independent of keV level.

CONCLUSION

This study indicates that a 50% reduction in iodinated contrast may result in adequate image quality using DECT with monoenergetic reconstructions at lower energy levels for the imaging of the thoracic aorta. The best image quality was obtained for ASiR-V 80% image reconstructions at 55 keV.

IMPLICATIONS OF PRACTICE

Dual energy CT with a reduction in iodinated contrast may result in adequate image quality in imaging of the thoracic aorta. However, increased radiation dose may limit the use to patients in which a reduction in fluid and iodinated contrast volume may outweigh this risk.

Evaluation of Spatial Resolution of Virtual Monochromatic Imaging In Vitro: Effect of Energy Level and Contrast

OBJECTIVE

Our aim was to evaluate effects of the energy level and contrast on the spatial resolution of virtual monochromatic imaging (VMI).

METHODS

With 2 types of computed tomographic (CT) scanners (Discovery CT750 HD and Revolution CT), we scanned an elliptical cylinder acrylic phantom with 20- or 40-fold dilutions of contrast medium and obtained VMI data sets at 40, 50, 60, and 70 keV. We evaluated the effects of energy levels and contrast on modulation transfer function (MTF) and the effect of energy levels on noise power spectra (NPS).

RESULTS

With both CT scanners, MTF decreased significantly as the energy level decreased. The effect of the dilution of contrast media on MTF varied with CT scanners. With both scanners, NPS curves demonstrate uniform increase in NPS across the entire spatial frequency as the energy levels decreased.

CONCLUSIONS

The energy level and contrast can affect the spatial resolution of VMIs.

Impact of novel deep learning image reconstruction algorithm on diagnosis of contrast-enhanced liver computed tomography imaging: Comparing to adaptive statistical iterative reconstruction algorithm

OBJECTIVE

To assess clinical application of applying deep learning image reconstruction (DLIR) algorithm to contrast-enhanced portal venous phase liver computed tomography (CT) for improving image quality and lesions detection rate compared with using adaptive statistical iterative reconstruction (ASIR-V) algorithm under routine dose.

METHODS

The raw data from 42 consecutive patients who underwent contrast-enhanced portal venous phase liver CT were reconstructed using three strength levels of DLIRs (low [DL-L]; medium [DL-M]; high [DL-H]) and two levels of ASIR-V (30%[AV-30]; 70%[AV-70]). Objective image parameters, including noise, signal-to-noise (SNR), and the contrast-to-noise ratio (CNR) relative to muscle, as well as subjective parameters, including noise, artifact, hepatic vein-clarity, index lesion-clarity, and overall scores were compared pairwise. For the lesions detection rate, the five reconstructions in patients who underwent subsequent contrast-enhanced magnetic resonance imaging (MRI) examinations were compared.

RESULTS

For objective parameters, DL-H exhibited superior image quality of lower noise and higher SNR than AV-30 and AV-70 (all P < 0.05). CNR was not statistically different between AV-70, DL-M, and DL-H (all P > 0.05). In both objective and subjective parameters, only image noise was statistically reduced as the strength of DLIR increased compared with ASIR-V (all P < 0.05). Regarding the lesions detection rate, a total of 45 lesions were detected by MRI examination and all five reconstructions exhibited similar lesion-detection rate (25/45, 55.6%).

CONCLUSION

Compared with AV-30 and AV 70, DLIR leads to better image quality with equal lesion detection rate for liver CT imaging under routine dose.

[Effects of Iterative Reconstruction on Image Quality of Pediatric Body Computed Tomography Images]

This study evaluated the effects of three types of hybrid iterative reconstruction (IR) on image quality of pediatric body computed tomography images. The image quality components evaluated were noise power spectrum (NPS), task-based modulation transfer function (TTF), and system performance function (SPF). As the IR strength was increased while reducing the radiation dose, the NPS increased in a low-frequency range and the TTF decreased in low-contrast regions. In the low-contrast regions, the calculated SPF decreased over the entire frequency range. Alternatively, in the high-contrast regions, the SPF decreased in the low-frequency regions and increased in the high-frequency regions. The radiation dose reduction using the hybrid IR resulted in the deterioration of the image quality in the low-contrast regions and changes in the spatial frequency characteristics in the high-contrast regions.

Third-generation iterative reconstruction on a dual-source, high-pitch, low-dose chest CT protocol with tin filter for spectral shaping at 100 kV: a study on a small series of COVID-19 patients

Objectives

To investigate the role of third-generation iterative reconstruction (ADMIRE) in dual-source, high-pitch chest CT protocol with spectral shaping at 100 kVp in Coronavirus disease 2019 (COVID-19).

Methods

Confirmed COVID-19 inpatients undergoing to unenhanced chest CT were scanned with a dual-energy acquisition (DECT, 90/150Sn kV) and a dual-source, high-pitch acquisition with tin-filtered 100 kVp (LDCT). On the DECT with ADMIRE 3 (DECT3) were evaluated the pulmonary findings and their extension (25-point score). Two radiologists in consensus evaluated with 5-point scales the overall image quality, the anatomical structures, and the elementary findings on LDCT reconstructed with filtered backprojection (LDCT0), with ADMIRE 3 (LDCT3) and 5 (LDCT5), and on DECT3. The signal-to-noise ratio (SNR), the body mass index, the exposure times, and the radiation doses were recorded.

Results

Seventy-five patients (57 M/18F; median age: 63 y.o.) were included, with median pulmonary extension of 13/25 points. The imaging findings were detected in proportion comparable to the available literature. The ADMIRE significantly improved the SNR in LDCT (p < 0.00001) with almost no significant differences in overweight patients. The LDCT had median effective dose of 0.39 mSv and acquisition time of 0.71 s with significantly less motion artifacts than DECT (p < 0.00001). The DECT3 and LDCT3 provided the best image quality and depiction of pulmonary anatomy and imaging findings, with significant differences among all the series (p < 0.00001).

Conclusion

The LDCT with spectral shaping and ADMIRE3 provided acceptable image quality in the evaluation of patients with COVID-19, with significantly reduced radiation dose and motion artifacts.

Evaluation of Image Quality for 7 Iterative Reconstruction Algorithms in Chest Computed Tomography Imaging: A Phantom Study

OBJECTIVES

This study aimed to evaluate the image quality of 7 iterative reconstruction (IR) algorithms in comparison to filtered back-projection (FBP) algorithm.

METHODS

An anthropomorphic chest phantom was scanned on 4 computed tomography scanners and reconstructed with FBP and IR algorithms. Image quality of anatomical details-large/medium-sized pulmonary vessels, small pulmonary vessels, thoracic wall, and small and large lesions-was scored. Furthermore, general impression of noise, image contrast, and artifacts were evaluated. Visual grading regression was used to analyze the data. Standard deviations were measured, and the noise power spectrum was calculated.

RESULTS

Iterative reconstruction algorithms showed significantly better results when compared with FBP for these criteria (regression coefficients/P values in parentheses): vessels (FIRST: -1.8/0.05, AIDR Enhanced: <-2.3/0.01, Veo: <-0.1/0.03, ADMIRE: <-2.1/0.04), lesions (FIRST: <-2.6/0.01, AIDR Enhanced: <-1.9/0.03, IMR1: <-2.7/0.01, Veo: <-2.4/0.02, ADMIRE: -2.3/0.02), image noise (FIRST: <-3.2/0.004, AIDR Enhanced: <-3.5/0.002, IMR1: <-6.1/0.001, iDose: <-2.3/0.02, Veo: <-3.4/0.002, ADMIRE: <-3.5/0.02), image contrast (FIRST: -2.3/0.01, AIDR Enhanced: -2.5/0.01, IMR1: -3.7/0.001, iDose: -2.1/0.02), and artifacts (FIRST: <-3.8/0.004, AIDR Enhanced: <-2.7/0.02, IMR1: <-2.6/0.02, iDose: -2.1/0.04, Veo: -2.6/0.02). The iDose algorithm was the only IR algorithm that maintained the noise frequencies.

CONCLUSIONS

Iterative reconstruction algorithms performed differently on all evaluated criteria, showing the importance of careful implementation of algorithms for diagnostic purposes.

Dynamic Hepatocellular Carcinoma Model Within a Liver Phantom for Multimodality Imaging

Introduction

Hepatocellular carcinoma (HCC) is one of the most common cancer in the world, and the effectiveness of its treatment lies in its detection in its early stages. The aim of this study is to mimic HCC dynamically through a liver phantom and apply it in multimodality medical imaging techniques including magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound.

Methods and materials

The phantom is fabricated with two main parts, liver parenchyma and HCC inserts. The liver parenchyma was fabricated by adding 2.5 wt% of agarose powder combined with 2.6 wt% of wax powder while the basic material for the HCC samples was made from polyurethane solution combined with 5 wt% glycerol. Three HCC samples were inserted into the parenchyma by using three cylinders implanted inside the liver parenchyma. An automatic injector is attached to the input side of the cylinders and a suction device connected to the output side of the cylinders. After the phantom was prepared, the contrast materials were injected into the phantom and imaged using MRI, CT, and ultrasound.

Results

Both HCC samples and liver parenchyma were clearly distinguished using the three imaging modalities: MRI, CT, and ultrasound. Doppler ultrasound was also applied through the HCC samples and the flow pattern was observed through the samples.

Conclusion

A multimodal dynamic liver phantom, with HCC tumor models have been fabricated. This phantom helps to improve and develop different methods for detecting HCC in its early stages.

The Feasibility of Contrast-to-Noise Ratio on Measurements to Evaluate CT Image Quality in Terms of Low-Contrast Detailed Detectability

Background: To evaluate contrast-to-noise ratio (CNR) measurements in assessing image quality, in the context of the detectability performance of low-contrast detail (LCD), in computed tomography (CT) images, since exposure to elevated ionising-type radiation is considered to present excessive carcinogenic risk, whilst also causing distress in study subjects. Methods: An LCD phantom module (CTP515) was utilised in the study. Three dissimilar contrast items were used to analyse the ramifications of the proportions of an object on the CNR. Three multidetector CT (MDCT) scanners were used, with 16-MDCT, 64-MDCT and 80-MDCT frameworks, respectively. The CT scans were recreated using three dissimilar remaking algorithms—soft, standard and lung. The effects exerted on the CNR by various remodelling algorithms, as well as the contrast of various objects along with the size of the objects, were explored. The Hounsfield units of each chosen object (one unit representing the outer portion of the object) and the background and the standard deviation of the noise parameter were quantified, and algorithms were developed using MATLAB. Results: The CNR information was greatly influenced by changing the image recreation calculations and was very much increased in the soft-tissue recreation images using 16-MDCT and 64-MDCT. The CNR information was also increased more in the optimum recreation images than in the reproduced images from the computational procedure used in the 80-MDCT. The results did not show any remarkable contrasts in the CNR values between the different object sizes. Overall, a higher kVp produced an improved CNR in all the CT scanners. In particular, there were prominent upgrades in the CNR information when the kVp was increased from 80 to 120. Higher mAs levels gave better CNR values overall, especially for greater section thicknesses. Based on the CNR estimations, the 64-MDCT provided the best correlation among the CT scanners. Conclusions: The objective LCD appraisal method, based on CNR measurements, was confirmed as being useful for checking the different impacts of kVp, mAs and section thickness on the nature of the picture. This procedure was similarly viable in assessing the impacts of the different reconstruction calculations and the different differentiation questions on the nature of the image.

Image Quality Assessment of Abdominal CT by Use of New Deep Learning Image Reconstruction: Initial Experience

OBJECTIVE. The purpose of this study was to perform quantitative and qualitative evaluation of a deep learning image reconstruction (DLIR) algorithm in contrast-enhanced oncologic CT of the abdomen. MATERIALS AND METHODS. Retrospective review (April-May 2019) of the cases of adults undergoing oncologic staging with portal venous phase abdominal CT was conducted for evaluation of standard 30% adaptive statistical iterative reconstruction V (30% ASIR-V) reconstruction compared with DLIR at low, medium, and high strengths. Attenuation and noise measurements were performed. Two radiologists, blinded to examination details, scored six categories while comparing reconstructions for overall image quality, lesion diagnostic confidence, artifacts, image noise and texture, lesion conspicuity, and resolution. RESULTS. DLIR had a better contrast-to-noise ratio than 30% ASIR-V did; high-strength DLIR performed the best. High-strength DLIR was associated with 47% reduction in noise, resulting in a 92-94% increase in contrast-to-noise ratio compared with that of 30% ASIR-V. For overall image quality and image noise and texture, DLIR scored significantly higher than 30% ASIR-V with significantly higher scores as DLIR strength increased. A total of 193 lesions were identified. The lesion diagnostic confidence, conspicuity, and artifact scores were significantly higher for all DLIR levels than for 30% ASIR-V. There was no significant difference in perceived resolution between the reconstruction methods. CONCLUSION. Compared with 30% ASIR-V, DLIR improved CT evaluation of the abdomen in the portal venous phase. DLIR strength should be chosen to balance the degree of desired denoising for a clinical task relative to mild blurring, which increases with progressively higher DLIR strengths.

Can iterative reconstruction algorithms replace tube loading compensation in low kVp hepatic CT? Subjective versus objective image quality

Background

Hepatic computed tomography (CT) with decreased peak kilovoltage (kVp) may be used to reduce contrast medium doses in patients at risk of contrast-induced acute kidney injury (CI-AKI); however, it increases image noise. To preserve image quality, noise has been controlled by X-ray tube loading (mAs) compensation (TLC), i.e. increased mAs. Another option to control image noise would be to use iterative reconstructions (IR) algorithms without TLC (No-TLC). It is unclear whether this may preserve image quality or only reduce image noise.

Purpose

To evaluate image quality of 80 kVp hepatic CT with TLC and filtered back projection (FBP) compared with 80 kVp with No-TLC and IR algorithms (SAFIRE 3 and 5) in patients with eGFR <45 mL/min.

Material and Methods

Forty patients (BMI 18–32 kg/m²) were examined with both protocols following injection of 300 mg I/kg. Hepatic attenuation, image noise, enhancement, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and subjective image quality were evaluated for each patient.

Results

Comparing TLC/FBP with No-TLC/IR-S5, there were no significant differences regarding hepatic attenuation, image noise, enhancement, SNR and CNR: 114 vs. 115 HU, 14 vs. 14 HU, 55 vs. 57 HU, 8.0 vs. 8.4, and 3.8 vs. 4.0 in median, respectively. No-TLC/IR-S3 resulted in higher image noise and lower SNR and CNR than TLC/FBP. Subjective image quality scoring with visual grading showed statistically significantly inferior scores for IR-S5 images.

Conclusion

CT of 80 kVp to reduce contrast medium dose in patients at risk of CI-AKI combined with IR algorithms with unchanged tube loading to control image noise does not provide sufficient diagnostic quality.

Prior iterative reconstruction (PIR) to lower radiation dose and preserve radiologist performance for multiphase liver CT: a multi-reader pilot study

PURPOSE

Prior iterative reconstruction (PIR) spatially registers CT image data from multiple phases of enhancement to reduce image noise. We evaluated PIR in contrast-enhanced multiphase liver CT.

METHODS

Patients with archived projection CT data with proven malignant or benign liver lesions, or without lesions, by reference criteria were included. Lower-dose PIR images were reconstructed using validated noise insertion from multiphase CT exams (50% dose in 2 phases, 25% dose in 1 phase). The phase of enhancement most relevant to the diagnostic task was selected for evaluation. Four radiologists reviewed routine-dose and lower-dose PIR images, circumscribing liver lesions and rating confidence for malignancy (0 to 100) and image quality. JAFROC Figures of Merit (FOM) were calculated.

RESULTS

31 patients had 60 liver lesions (28 primary hepatic malignancies, 6 hepatic metastases, 26 benign lesions). Pooled JAFROC FOM for malignancy for routine-dose CT was 0.615 (95% CI 0.464, 0.767) compared to 0.662 for PIR (95% CI 0.527, 0.797). The estimated FOM difference between the routine-dose and lower-dose PIR images was + 0.047 (95% CI - 0.023, + 0.116). Pooled sensitivity/specificity for routine-dose images was 70%/68% compared to 73%/66% for lower-dose PIR. Lower-dose PIR had lower diagnostic image quality (mean 3.8 vs. 4.2, p = 0.0009) and sharpness (mean 2.3 vs. 2.0, p = 0.0071).

CONCLUSIONS

PIR is a promising method to reduce radiation dose for multiphase abdominal CT, preserving observer performance despite small reductions in image quality. Further work is warranted.

Assessment of potential reduction in multidetector computed tomography doses using FBP and SAFIRE for detection and measurement of the position of the inferior alveolar canal

OBJECTIVE

The objective was to identify the lowest doses required to detect and measure the position of the inferior alveolar canal (IAC) on multidetector computed tomography (MDCT) images using filtered backprojection (FBP) and sinogram-affirmed iterative reconstructions (SAFIRE) 3 and SAFIRE 5.

STUDY DESIGN

Four cadaveric mandibles were imaged using a reference protocol with standard dose and FBP and 3 ultra-low-dose protocols (LD1-LD3), using an MDCT scanner. All test examinations were reconstructed with FBP, SAFIRE 3, and SAFIRE 5. Subjective visibility of the IAC in the images and digital measurements of the height of the ridge above the IAC were recorded from test images and compared with those from the reference image using one-sample t tests, Bland-Altman plots, and linear regression.

RESULTS

Subjective visibility comparable to the standard protocol was obtained with an 84.6% dose reduction using the LD2 protocol. No statistically significant difference was found between the height measurements from the reference protocol and any of the LD1 and LD2 protocols. The t tests indicated a significant difference between the measurements from the reference and all LD3 test protocols. SAFIRE did not have an advantage over FBP images.

CONCLUSIONS

Significant dose reduction from the reference dose can allow adequate detection and measurements of the IAC.

Dose Reduction While Preserving Diagnostic Quality in Head CT: Advancing the Application of Iterative Reconstruction Using a Live Animal Model

BACKGROUND AND PURPOSE

Iterative reconstruction has promise in lowering the radiation dose without compromising image quality, but its full potential has not yet been realized. While phantom studies cannot fully approximate the subjective effects on image quality, live animal models afford this assessment. We characterize dose reduction in head CT by applying advanced modeled iterative reconstruction (ADMIRE) in a live ovine model while evaluating preservation of gray-white matter detectability and image texture compared with filtered back-projection.

MATERIALS AND METHODS

A live sheep was scanned on a Force CT scanner (Siemens) at 12 dose levels (82-982 effective mAs). Images were reconstructed with filtered back-projection and ADMIRE (strengths, 1-5). A total of 72 combinations (12 doses × 6 reconstructions) were evaluated qualitatively for resemblance to the reference image (highest dose with filtered back-projection) using 2 metrics: detectability of gray-white matter differentiation and noise-versus-smoothness in image texture. Quantitative analysis for noise, SNR, and contrast-to-noise was also performed across all dose-strength combinations.

RESULTS

Both qualitative and quantitative results confirm that gray-white matter differentiation suffers at a lower dose but recovers when complemented by higher iterative reconstruction strength, and image texture acquires excessive smoothness with a higher iterative reconstruction strength but recovers when complemented by dose reduction. Image quality equivalent to the reference image is achieved by a 58% dose reduction with ADMIRE-5.

CONCLUSIONS

An approximately 60% dose reduction may be possible while preserving diagnostic quality with the appropriate dose-strength combination. This in vivo study can serve as a useful guide for translating the full implementation of iterative reconstruction in clinical practice.

Reducing radiation dose for multi-phase contrast-enhanced dual energy renal CT: pilot study evaluating prior iterative reconstruction

PURPOSE

Prior iterative reconstruction (PIR) uses spatial information from one phase of enhancement to reduce image noise in other phases. We sought to determine if PIR could reduce radiation dose while preserving observer performance and CT number at multi-phase dual energy (DE) renal CT.

METHODS

CT projection data from multi-phase DE renal CT examinations were collected. Images corresponding to 40% radiation dose were reconstructed using validated noise insertion and PIR. Three genitourinary radiologists examined routine and 40% dose PIR images. Probability of malignancy was assessed [from 0 to 100] with malignancy assumed at probability ≥ 75. Observer performance was compared on a per patient and per lesion level. CT number accuracy was measured.

RESULTS

Twenty-three patients had 49 renal lesions (11 solid renal neoplasms). CT number was nearly identical between techniques (mean CT number difference: unenhanced 2 ± 2 HU; enhanced 4 ± 4 HU). AUC for malignancy was similar between multi-phase routine dose DE and lower dose PIR images [per patient: 0.950 vs. 0.916 (p = 0.356); per lesion: 0.931 vs. 0.884 (p = 0.304)]. Per patient sensitivity was also similar (78% routine dose vs. 82% lower dose [p ≥ 0.99]), as was specificity (91% routine dose vs. 93% lower dose PIR [p > 0.99]), with similar findings on a per lesion level. Subjective image quality was also similar (p = 0.34).

CONCLUSIONS

Prior iterative reconstruction is a new reconstruction method for multi-phase CT examinations that promises to facilitate radiation dose reduction by over 50% for multi-phase DE renal CT exams without compromising CT number or observer performance.

Adaptive statistical iterative reconstruction (ASIR) affects CT radiomics quantification in primary colorectal cancer

OBJECTIVES

To investigate whether adaptive statistical iterative reconstruction (ASIR), a hybrid iterative CT image reconstruction algorithm, affects radiomics feature quantification in primary colorectal cancer compared to filtered back projection. Additionally, to establish whether radiomics from single-slice analysis undergo greater change than those from multi-slice analysis.

METHODS

Following review board approval, contrast-enhanced CT studies from 32 prospective primary colorectal cancer patients were reconstructed with 20% ASIR level increments, from 0 to 100%. Radiomics analysis was applied to single-slice and multi-slice regions of interest outlining the tumour: 70 features, including statistical (first-, second- and high-order) and fractal radiomics, were generated per dataset. The effect of ASIR was calculated by means of multilevel linear regression.

RESULTS

Twenty-eight CT datasets were suitable for analysis. Incremental ASIR levels determined a significant change (p < 0.001) in most statistical radiomics features, best described by a simple linear relationship. First-order statistical features, including mean, standard deviation, skewness, kurtosis, energy and entropy, underwent a relatively small change in both single-slice and multi-slice analysis (median standardised effect size B = 0.08). Second-order statistical features, including grey-level co-occurrence and difference matrices, underwent a greater change in single-slice analysis (median B = 0.36) than in multi-slice analysis (median B = 0.13). Fractal features underwent a significant change only in single-slice analysis (median B = 0.49).

CONCLUSIONS

Incremental levels of ASIR affect significantly CT radiomics quantification in primary colorectal cancer. Second-order statistical and fractal features derived from single-slice analysis undergo greater change than those from multi-slice analysis.

KEY POINTS

• Incremental levels of ASIR determine a significant change in most statistical (first-, second- and high-order) CT radiomics features measured in primary colorectal cancer, best described by a linear relationship. • First-order statistical features undergo a small change, both from single-slice and multi-slice radiomics analyses. • Most second-order statistical features undergo a greater change in single-slice analysis than in multi-slice analysis. Fractal features are only affected in single-slice analysis.

Image Quality Performance of Virtual Single-Source CT Using Dual-Source Computed Tomography

RATIONALE AND OBJECTIVES

The aim of this study is to analyze the image quality provided by a dual-source (DS) data set and a single-source (SS) data set at the same radiation exposure, in order to evaluate a dose splitting method for dual-source scanning protocols.

MATERIALS AND METHODS

A 192-slice dual-source third generation CT (Somatom Force; Siemens Healthcare, Forchheim, Germany) was used to image a Catphan phantom (Catphan503; The Phantom Laboratory, Salem, New York) utilizing different X-ray tube voltages from 70 to 120 kVp with an organ-based tube-current modulation technique (X-CARE; Siemens Healthcare, Forchheim, Germany). In order to keep the radiation dose (given by volume computed tomography dose index) in a clinically relevant range, different X-ray tube time-current products ranging from 80 to 300 mAs were selected. The data sets by each X-ray tube voltage were collected using a single-source as well as a dual-source mode. The measurements in the dual-source mode were performed with five different tube currents of the X-ray tube A and B. Thereby, the tube current ratios were 50%|50% (DS 0.5), 60%|40% (DS 0.6), 70%|30% (DS 0.7), 80%|20% (DS 0.8), and 90%|10% (DS 0.9). The images were reconstructed by the use of a filter-back projection (Br40) and an advanced mode led iterative reconstruction algorithms (advanced modeled iterative reconstruction algorithms [ADMIRE]; Siemens Healthcare, Forchheim, Germany) with a strength range of 1-5. The image quality was evaluated in terms of noise, contrast-to-noise ratio (CNR), low-contrast detectability expressed as the structural similarity index (SSIM) and spatial resolution quantified by the full width at half maximum of the line-spread function.

RESULTS

Image noise decreased by the use of the dual-source mode, which led to improvement of their CNR compared to the single-source mode. SSIM showed an almost constant behavior by both modes. The spatial resolution indicated a lower trend by the dual-source mode in comparison to the single-source mode. However, the loss of the spatial resolution performance was lower than 5% for the dual-source modes.

CONCLUSION

The presented phantom study demonstrated that SSIM and spatial resolution performance obtained by dual-source CT protocols showed a negligible variation to those by the single-source CT. However, the noise and CNR displayed an improvement for the dual-source CT. Therefore, the use of the dual-source CT enables to split the radiation dose between X-ray tubes and to compare the data sets with different radiation dose levels without loss in the image quality.

Comparison of standard-dose and half-dose dual-source abdominopelvic CT scans for evaluation of acute abdominal pain

Background

With the increasing number of computed tomography (CT) scans used for evaluation of acute abdominal pain, patient radiation exposure has increased rapidly.

Purpose

To determine whether the diagnostic performance of half-dose abdominopelvic CT is non-inferior to that of standard-dose CT for patients with acute abdominal pain.

Material and Methods

Ninety-eight patients with acute abdominal pain underwent dual-source abdominopelvic CT. Three sets of CT images were reconstructed: standard-dose filtered back projection (FBP); half-dose FBP; and half-dose sinogram-affirmed iterative reconstruction (SAFIRE3). Diagnostic performance of the standard-dose scan was compared with that of the half-dose scans by using a non-inferiority test with a 10% margin. The overall image quality was subjectively measured.

Results

Diagnostic performance for overall disease diagnosis with half-dose scans (area under the receiver operating characteristic curve [AUC] = 0.835 for FBP, 0.881 for SAFIRE3) was non-inferior to that of standard-dose FBP (AUC = 0.891) (95% confidence interval lower limit difference = −5.6% [half-dose FBP], −1.2% [half-dose SAFIRE3]). The diagnostic sensitivity for detection of neoplastic disease was lower with half-dose (75.0%) than with standard-dose FBP (91.7%). Effective dose and dose-length product with standard-dose imaging were 7.99 ± 2.55 mSv and 533.1 ± 170.3 mGy·cm, respectively; those of half-dose imaging were 3.99 ± 1.28 mSv and 266.6 ± 85.2 mGy·cm, respectively. The image quality was lower with half-dose than with standard-dose FBP scans ( P < 0.01).

Conclusion

Diagnostic performance of half-dose CT is non-inferior to that of standard-dose scan for evaluation of acute abdominal pain, despite inferior image quality.

Localization of liver lesions in abdominal CT imaging: I. Correlation of human observer performance between anatomical and uniform backgrounds

The purpose of this study was to determine the correlation between human observer performance for localization of small low contrast lesions within uniform water background versus an anatomical liver background, under the conditions of varying dose, lesion size, and reconstruction algorithm. Liver lesions (5 mm, 7 mm, and 9 mm, contrast:  -21 HU) were digitally inserted into CT projection data of ten normal patients in vessel-free liver regions. Noise was inserted into the projection data to create three image sets: full dose and simulated half and quarter doses. Images were reconstructed with a standard filtered back projection (FBP) and an iterative reconstruction (IR) algorithm. Lesion and noise insertion procedures were repeated with water phantom data. Two-dimensional regions of interest (66 lesion-present, 34 lesion-absent) were selected, randomized, and independently reviewed by three medical physicists to identify the most likely location of the lesion and provide a confidence score. Locations and confidence scores were assessed using the area under the localization receiver operating characteristic curve (Az_LROC). We examined the correlation between human performance for the liver and uniform water backgrounds as dose, lesion size, and reconstruction algorithm varied. As lesion size or dose increased, reader localization performance improved. For full dose IR images, the Az_LROC for 5, 7, and 9 mm lesions were 0.53, 0.91, and 0.97 (liver) and 0.51, 0.96, and 0.99 (uniform water), respectively. Similar trends were seen with other parameters. Performance values for liver and uniform backgrounds were highly correlated for both reconstruction algorithms, with a Spearman correlation of ρ  =  0.97, and an average difference in Az_LROC of 0.05  ±  0.04. For the task of localizing low contrast liver lesions, human observer performance was highly correlated between anatomical and uniform backgrounds, suggesting that lesion localization studies emulating a clinical test of liver lesion detection can be performed using a uniform background.

Evaluation of Adaptive Statistical Iterative Reconstruction-V Reconstruction Algorithm vs Filtered Back Projection in the Detection of Hypodense Liver Lesions: Reader Performance and Preferences

OBJECTIVE

The aim of the study was to evaluate diagnostic accuracy and readers' experience in the detection of focal liver lesions on computed tomography with Adaptive Statistical Iterative Reconstruction-V (ASIR-V) reconstruction compared with filtered back projection (FBP) scans.

METHODS

Fifty-five patients with liver lesions had FBP and ASIR-V scans. Two radiologists independently reviewed both sets of computed tomography scans, identifying and characterizing liver lesions.

RESULTS

Adaptive Statistical Iterative Reconstruction-V scans had a reduction in dose length product (P < 0.0001) with no difference in image contrast (P = 0.1805); image noise was less for the ASIR-V scans (P < 0.0001) and contrast-to-noise ratio was better for ASIR-V (P = 0.0002). Both readers found more hypodense liver lesions on the FBP (P = 0.01) scans. Multiple subjective imaging scores were significantly less for the ASIR-V scans for both readers.

CONCLUSIONS

Although ASIR-V scans were objectively better, our readers performed worse in lesion detection on them, suggesting a need for better education/experience with this technology during implementation.

Detection of Colorectal Hepatic Metastases Is Superior at Standard Radiation Dose CT versus Reduced Dose CT

Purpose To evaluate colorectal cancer hepatic metastasis detection and characterization between reduced radiation dose (RD) and standard dose (SD) contrast material-enhanced CT of the abdomen and to qualitatively compare between filtered back projection (FBP) and iterative reconstruction algorithms. Materials and Methods In this prospective study (from May 2017 through November 2017), 52 adults with biopsy-proven colorectal cancer and suspected hepatic metastases at baseline CT underwent two portal venous phase CT scans: SD and RD in the same breath hold. Three radiologists, blinded to examination details, performed detection and characterization of 2-15-mm lesions on the SD FBP and RD adaptive statistical iterative reconstruction (ASIR)-V 60% series images. Readers assessed overall image quality and lesions between SD FBP and seven different iterative reconstructions. Two nonblinded consensus reviewers established the reference standard using the picture archiving and communication system lesion marks of each reader, multiple comparison examinations, and clinical data. Results RD CT resulted in a mean dose reduction of 54% compared with SD. Of the 260 lesions (233 metastatic, 27 benign), 212 (82%; 95% confidence interval [CI]: 76%, 86%) were detected with RD CT, whereas 252 (97%; 95% CI: 94%, 99%) were detected with SD (P < .001); per-lesion sensitivity was 79% (95% CI: 74%, 84%) and 94% (95% CI: 90%, 96%) (P < .001), respectively. Mean qualitative scores ranked SD images as higher quality than RD series images, and ASIR-V ranked higher than ASIR and Veo 3.0. Conclusion CT evaluation of colorectal liver metastases is compromised with modest radiation dose reduction, and the use of iterative reconstructions could not maintain observer performance. © RSNA, 2018.

Observer Performance with Varying Radiation Dose and Reconstruction Methods for Detection of Hepatic Metastases

Purpose To estimate the ability of lower dose levels and iterative reconstruction (IR) to display hepatic metastases that can be detected by radiologists. Materials and Methods Projection data from 83 contrast agent-enhanced CT examinations were collected. Metastases were defined by histopathologic analysis or progression and regression. Lower radiation dose configurations were reconstructed at five dose levels with filtered back projection (FBP) and IR (automatic exposure control settings: 80, 100, 120, 160, and 200 quality reference mAs [QRM]). Three abdominal radiologists circumscribed metastases, indicating confidence (confidence range, 0-100) and image quality. Noninferiority was assessed by using jackknife alternative free-response receiver operating characteristic (JAFROC) analysis (noninferiority limit, -0.10) and reader agreement rules, which required identification of metastases identified at routine dose, and no nonlesion localizations in patients negative for metastases, in 71 or more patient CT examinations (of 83), for each configuration. Results There were 123 hepatic metastases (mean size, 1.4 cm; median volume CT dose index and size-specific dose estimate, 11.0 and 13.4 mGy, respectively). By using JAFROC figure of merit, 100 QRM FBP did not meet noninferiority criteria and had estimated performance difference from routine dose of -0.08 (95% confidence interval: -0.11, -0.04). Preset reader agreement rules were not met for 100 QRM IR or 80 QRM IR, but were met for doses 120 QRM or higher (ie, size-specific dose estimate ≥ 8.0 mGy). IR improved image quality (P < .05) but not reader performance. Other than 160 QRM IR, lower dose levels were associated with reduced confidence in metastasis detection (P < .001). Conclusion For detection of hepatic metastases by using contrast-enhanced CT, dose levels that corresponded to 120 quality reference mAs (size-specific dose estimate, 8.0 mGy) and higher performed similarly to 200 quality reference mAs with filtered back projection. © RSNA, 2018 Online supplemental material is available for this article.

Comparison of Full- and Half-Dose Image Reconstruction With Filtered Back Projection or Sinogram-Affirmed Iterative Reconstruction in Dual-Source Single-Energy MDCT Urography

OBJECTIVE

The purpose of this study is to prospectively compare the image quality of and confidence in the presence of a lesion on CT urography images acquired using filtered back projection (FBP) with 100% and 50% radiation doses with those for images simultaneously acquired using sinogram-affirmed iterative reconstruction with strength 3 (SAFIRE) with 50% and 25% radiation doses for patients with a high risk for urothelial carcinomas.

SUBJECTS AND METHODS

A total of 150 patients randomly underwent CT urography examinations performed using a dual-source single-energy scanner. After the radiation output of each tube was adjusted, datasets at three radiation dose levels were reconstructed using FBP and SAFIRE. Seven radiologists subjectively assessed image quality and confidence in the presence of a lesion for a total of 1200 datasets. Nonparametric methods for cluster data were used to estimate AUC values for variance methods on the basis of a noninferiority margin of 0.05.

RESULTS

The mean AUC value for image quality in SAFIRE with a 25% radiation dose was significantly lower than that of FBP with 100% radiation dose (p < 0.05 for all). The mean AUC values for the presence of a lesion were 0.907 and 0.894 for FBP, respectively, at 100% and 50% radiation doses, respectively, and 0.900 and 0.799 for SAFIRE at 50% and 25% radiation doses, respectively. However, the image quality of images acquired with SAFIRE at a 25% radiation dose was significantly inferior to that of images acquired with FBP at a 100% radiation dose.

CONCLUSION

Regardless of the experience of the radiologist, CT urography images acquired with FBP and SAFIRE with a 50% radiation dose were noninferior to those acquired with FBP with a 100% radiation dose in terms of image quality and confidence in the presence of a lesion, whereas those acquired with SAFIRE with 25% radiation dose were inferior.

CT Detectability of Small Low-Contrast Hypoattenuating Focal Lesions: Iterative Reconstructions versus Filtered Back Projection

Purpose To investigate performance in detectability of small (≤1 cm) low-contrast hypoattenuating focal lesions by using filtered back projection (FBP) and iterative reconstruction (IR) algorithms from two major CT vendors across a range of 11 radiation exposures. Materials and Methods A low-contrast detectability phantom consisting of 21 low-contrast hypoattenuating focal objects (seven sizes between 2.4 and 10.0 mm, three contrast levels) embedded into a liver-equivalent background was scanned at 11 radiation exposures (volume CT dose index range, 0.5-18.0 mGy; size-specific dose estimate [SSDE] range, 0.8-30.6 mGy) with four high-end CT platforms. Data sets were reconstructed by using FBP and varied strengths of image-based, model-based, and hybrid IRs. Sixteen observers evaluated all data sets for lesion detectability by using a two-alternative-forced-choice (2AFC) paradigm. Diagnostic performances were evaluated by calculating area under the receiver operating characteristic curve (AUC) and by performing noninferiority analyses. Results At benchmark exposure, FBP yielded a mean AUC of 0.79 ± 0.09 (standard deviation) across all platforms which, on average, was approximately 2% lower than that observed with the different IR algorithms, which showed an average AUC of 0.81 ± 0.09 (P = .12). Radiation decreases of 30%, 50%, and 80% resulted in similar declines of observer detectability with FBP (mean AUC decrease, -0.02 ± 0.05, -0.03 ± 0.05, and -0.05 ± 0.05, respectively) and all IR methods investigated (mean AUC decrease, -0.00 ± 0.05, -0.04 ± 0.05, and -0.04 ± 0.05, respectively). For each radiation level and CT platform, variance in performance across observers was greater than that across reconstruction algorithms (P = .03). Conclusion Iterative reconstruction algorithms have limited radiation optimization potential in detectability of small low-contrast hypoattenuating focal lesions. This task may be further complicated by a high degree of variation in radiologists' performances, seemingly exceeding real performance differences among reconstruction algorithms. © RSNA, 2018 Online supplemental material is available for this article.

Task-based quantification of image quality using a model observer in abdominal CT: a multicentre study

Objective

We investigated the variability in diagnostic information inherent in computed tomography (CT) images acquired at 68 different CT units, with the selected acquisition protocols aiming to answer the same clinical question.

Methods

An anthropomorphic abdominal phantom with two optional rings was scanned on 68 CT systems from 62 centres using the local clinical acquisition parameters of the portal venous phase for the detection of focal liver lesions. Low-contrast detectability (LCD) was assessed objectively with channelised Hotelling observer (CHO) using the receiver operating characteristic (ROC) paradigm. For each lesion size, the area under the ROC curve (AUC) was calculated and considered as a figure of merit. The volume computed tomography dose index (CTDI_vol) was used to indicate radiation dose exposure.

Results

The median CTDI_vol used was 5.8 mGy, 10.5 mGy and 16.3 mGy for the small, medium and large phantoms, respectively. The median AUC obtained from clinical CT protocols was 0.96, 0.90 and 0.83 for the small, medium and large phantoms, respectively.

Conclusions

Our study used a model observer to highlight the difference in image quality levels when dealing with the same clinical question. This difference was important and increased with growing phantom size, which generated large variations in patient exposure. In the end, a standardisation initiative may be launched to ensure comparable diagnostic information for well-defined clinical questions. The image quality requirements, related to the clinical question to be answered, should be the starting point of patient dose optimisation.

Key Points

• Model observers enable to assess image quality objectively based on clinical tasks.

• Objective image quality assessment should always include several patient sizes.

• Clinical diagnostic image quality should be the starting point for patient dose optimisation.

• Dose optimisation by applying DRLs only is insufficient for ensuring clinical requirements.

Assessment of organ dose and image quality in head and chest CT examinations: a phantom study

The purpose of this study is to assess dose for radiosensitive organs and image quality in head and chest computed tomography (CT) examinations. Our focus was in the brain, eye lens and lung organs using two protocols; one protocol with fixed mAs and filtered back projection (FBP) and another with tube current modulation (TCM) and sinogram affirmed iterative reconstruction (SAFIRE). Measurements were performed on a 128-slice CT scanner by placing thermoluminescent dosimeters (TLDs) in an anthropomorphic adult phantom. Results were compared to a CT-Expo software. Objective image quality was assessed in terms of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). SPSS software was used for data analyses. Results showed that, using TCM, doses were reduced by 22.84%-25.06% for brain, by 21.82%-23.48% for eye lens and by 54%-53.22% for lung with TLD and CT-Expo respectively. The increased SNR and CNR values achieved for scans performed with TCM combined with iterative reconstruction techniques were 38.68%-58.81% and 38.91%-43.60% respectively. We conclude that, using TCM, a significant mean organ dose reduction is achieved for brain, eye lens and lung organs. Then, combined with iterative reconstruction, image quality was well maintained in terms of SNR and CNR. Thus it is highly recommended in clinical practice optimization in head and chest CT examinations.

SPIROMICS Protocol for Multicenter Quantitative Computed Tomography to Phenotype the Lungs

Multidetector row computed tomography (MDCT) is increasingly taking a central role in identifying subphenotypes within chronic obstructive pulmonary disease (COPD), asthma, and other lung-related disease populations, allowing for the quantification of the amount and distribution of altered parenchyma along with the characterization of airway and vascular anatomy. The embedding of quantitative CT (QCT) into a multicenter trial with a variety of scanner makes and models along with the variety of pressures within a clinical radiology setting has proven challenging, especially in the context of a longitudinal study. SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), sponsored by the National Institutes of Health, has established a QCT lung assessment system (QCT-LAS), which includes scanner-specific imaging protocols for lung assessment at total lung capacity and residual volume. Also included are monthly scanning of a standardized test object and web-based tools for subject registration, protocol assignment, and data transmission coupled with automated image interrogation to assure protocol adherence. The SPIROMICS QCT-LAS has been adopted and contributed to by a growing number of other multicenter studies in which imaging is embedded. The key components of the SPIROMICS QCT-LAS along with evidence of implementation success are described herein. While imaging technologies continue to evolve, the required components of a QCT-LAS provide the framework for future studies, and the QCT results emanating from SPIROMICS and the growing number of other studies using the SPIROMICS QCT-LAS will provide a shared resource of image-derived pulmonary metrics.

Quantifying potential reduction in contrast dose with monoenergetic images synthesized from dual-layer detector spectral CT

OBJECTIVE

To estimate the potential dose reduction in iodinated contrast when interpreting monoenergetic images from spectral CT.

METHODS

51 paediatric patients received contrast-enhanced CT simulation for radiation therapy using a single-source, dual-layer detector spectral CT. The contrast-to-noise ratios (CNRs) of blood vessels were measured relative to surrounding soft tissue. CNRs on monoenergetic 40-70 keV images were compared with polychromatic 120 kVp images. To compare with in vivo results, a phantom with iodine inserts (2-20 mg ml-1 concentration) was scanned and CNRs were calculated relative to water background.

RESULTS

Monoenergetic keV and body site had significant effects on CNR ratio (p < 0.0001). Across all body sites, the mean CNR ratio (monoenergetic/polychromatic CNR) was 3.3 (20th percentile [%20] 2.6), 2.4 (%20 2.1), 1.7 (%20 1.5), 1.2 (%20 1.0) for 40, 50, 60 and 70 keV images, respectively. Image noise was highest at 40 keV and lowest at 70 keV. Phantom measurements indicated that the same CNR as 120 kVp images can be achieved with a 4.0-fold lower iodine concentration on 40 keV images and 2.5-fold lower on 50 keV images.

CONCLUSION

50 keV monoenergetic images provided the best balance of improved CNR on all studies (mean 2.4-fold increase in vivo) for enhancing vessels vs image noise. A 50% reduction in contrast dose on a 50 keV image should maintain comparable or better CNR as compared with polychromatic CT in over 80% of CT studies. Advances in knowledge: Use of a novel, single-source, dual-layer detector spectral CT scanner to improve visualization of contrast-enhanced blood vessels will reduce the amount of iodinated contrast required for radiation oncology treatment planning.

Axial or Helical? Considerations for wide collimation CT scanners capable of volumetric imaging in both modes

PURPOSE

To determine whether axial or helical mode is more appropriate for a 16 cm collimation CT scanner capable of step-and-shoot volumetric axial coverage, in terms of radiation dose, image quality, and scan duration.

METHODS

All scans were performed with a Revolution CT (GE Healthcare) operating at 120 kV and 100 mAs. Using calibrated optically stimulated luminescence detectors, radiation dose along the axial scan profile was evaluated at the isocenter, including the overlap region between two axial sections. This overlap region measures 3 cm in the z-axis at the isocenter and is required to obtain sufficient projection data from the relatively large cone-beam angles. Using an image quality phantom (Gammex Model 464), spatial resolution, CT number uniformity, image noise, and low contrast detectability (LCD) were evaluated under five different conditions: in the middle of a helical acquisition, in the middle of a 16 cm axial section, at both ends of an axial section and in the overlap region between two axial sections. Scan durations and dose length products (DLP) were recorded for prescribed scan lengths of 2.5-100 cm.

RESULTS

The overlap region between two axial sections received a dose 83% higher than the single-exposure region at the isocenter. Within a single axial section, the dose at the anode end was 37% less than at the cathode end due to the anode heel effect. Image noise ranged from a low of 13 HU for the cathode end of an axial section up to 14.7 HU for the anode end (P < 0.001). The LCD was at lower at the anode end of the axial section compared to both the cathode end (P < 0.05) and the overlap location (P < 0.02). The spatial resolution and CT number uniformity were consistent among all conditions. Scan durations were shorter (0.28 s) for the axial mode compared to the helical mode at scan lengths ≤ 16 cm, and longer at scan lengths ≥ 16 cm where more than one table position was required, up to a difference of 13.9 s for a the 100 cm scan length (3.8 s for helical compared to 17.6 s for axial). DLPs were consistent between scan modes; slightly lower in axial mode at shorter scan lengths due to helical overranging, and slightly higher in axial mode at longer scan lengths due to the axial overlap regions.

CONCLUSIONS

To ensure the most consistent radiation dose and image quality along the scan length, we recommend helical mode for scans longer than the 16 cm coverage of a single axial section. For scan lengths ≤ 16 cm, axial scanning is the most practical option, with a shorter scan duration and higher dose efficiency.

Low Tube Voltage Liver MDCT with Sinogram-Affirmed Iterative Reconstructions for the Detection of Hepatocellular Carcinoma

Aim of this study was to compare low tube voltage computed tomography (80 kV) of the liver using iterative image reconstruction (SAFIRE) with standard computed tomography (120 kV) using filtered back-projection (FBP) for the detection of hepatocellular carcinoma (HCC). 46 patients (43 men) with 93 HCC confirmed by 3 T MRI with Gd-EOB-DPTA, in inconclusive cases combined with contrast-enhanced ultrasound, underwent dual-energy CT. The raw data of the 80 kV tube was reconstructed using the iterative reconstruction algorithm SAFIRE with two strengths (I3 and I5). The virtual 120 kV image data set was reconstructed using FBP. The CT images were reviewed to determine the lesion-to-liver contrast (LLC), the lesion contrast-to-noise ratio (CNR) and the sensitivity. The LLC (57.1/54.3 [I3/I5] vs. 34.9 [FBP]; p ≤ 0.01), CNR (3.67/4.45 [I3/I5] vs. 2.48 [FBP]; p < 0.01) and sensitivity (91.4%/88.2% [I3/I5] vs. 72.0% [FBP]; p ≤ 0.01) were significantly higher in the low-voltage protocol using SAFIRE. Therefore, low tube voltage CT using SAFIRE results in an increased lesion-to-liver contrast as well as an improved lesion contrast-to-noise ratio compared to FBP at 120 kV which results in a higher sensitivity for the detection of HCC.