Comparison of image quality and radiation exposure between conventional imaging and gemstone spectral imaging in abdominal CT examination

Performance improvements of virtual monoenergetic images in photon-counting detector CT compared with dual source dual-energy CT: Fourier-based assessment

To confirm the performance improvement of virtual monoenergetic images (VMIs) for iodine contrast tasks in a clinical photon-counting detector CT (PCD CT) using Fourier-based assessment, compared with those in the latest-generation dual-source dual-energy CT (DECT). A water-filled bath with a diameter of 300 mm, which contains rod-shaped phantoms equivalent to diluted iodine (2 and 12 mg/mL), was scanned using PCD CT and DECT at 15, 7.5, and 3 mGy. VMIs were generated without any iterative reconstruction algorithm. Task transfer function (TTF), noise power spectrum (NPS), and slice sensitivity profile were evaluated for VMIs at 70 and 40 keV. The detectability index (d') and the squared system performance function (SPF2) calculated by TTF2/NPS were compared. At 40 keV, the d' values of PCD CT were higher (percentage increase of 25.7-39.9%) than those of DECT, whereas at 70 keV, the difference was rather small. The SPF2 values at 40 keV of PCD CT grew notably higher than those of DECT as the spatial frequency increased. The higher SPF2 values endorsed the lower image noise and the sharper edge of the rod phantom as observed. The d' and SPF2 in VMIs at 40 keV of PCD CT were notably higher than those of DECT, which endorsed the clinical advantages of PCD CT that had been previously reported in various studies.

Improved image quality and micronodule detection in thyroid spectral computed tomography using modified swimmer's position

Background

Spectral computed tomography (CT) can be used as a valuable complement to ultrasound (US) in the detection of thyroid nodules. This study sought to investigate the effects of various arm positions during thyroid spectral CT scans in terms of radiation exposure, image quality, and micronodule detection (≤10 mm).

Methods

A total of 180 patients (mean age: 48 years; 136 females) who underwent thyroid spectral CT were assigned to the traditional position (TDN; n=60), swimmer's position (SWIM; n=60), and modified swimmer's position (M-SWIM; n=60) groups. Image quality in the plain, arterial, and venous phases was assessed using a 4-point grading scale, the signal-to-noise ratio (SNR), and the contrast-to-noise ratio (CNR). Radiation exposure was assessed using the volume computed tomography dose index (CTDIvol), dose-length product (DLP), effective dose of the neck (EDN), and effective dose of the thyroid (EDT). The micronodule detection rates for spectral CT and US were compared using the pathology detection rate as a reference.

Results

The M-SWIM group had a significantly higher proportion of 4-point grading, SNR, and CNR than the TDN and SWIM groups (all P<0.001). The CTDIvol, DLP, EDN, and EDT were similar among the three groups (all P>0.05). The micronodule detection rate was higher in the M-SWIM group than the TDN and SWIM groups (total: 90.6% vs. 70.1% vs. 46.8%; benign: 89.1% vs. 66.7% vs. 45.5%; malignant: 94.3% vs. 79.5% vs. 51.5%; all P<0.001), but comparable to that of the US group (total: 90.6% vs. 91.2%; benign: 89.1% vs. 90.6%; malignant: 94.3% vs. 92.5%; all P>0.05).

Conclusions

The proposed M-SWIM improved the image quality of thyroid spectral CT without increasing the radiation dose, and significantly enhanced the micronodule detection rate.

A Deep Learning Image Reconstruction Algorithm for Improving Image Quality and Hepatic Lesion Detectability in Abdominal Dual-Energy Computed Tomography: Preliminary Results

This study aimed to compare the performance of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-Veo (ASIR-V) in improving image quality and diagnostic performance using virtual monochromatic spectral images in abdominal dual-energy computed tomography (DECT). Sixty-two patients [mean age ± standard deviation (SD): 56 years ± 13; 30 men] who underwent abdominal DECT were prospectively included in this study. The 70-keV DECT images in the portal phase were reconstructed at 5-mm and 1.25-mm slice thicknesses with 40% ASIR-V (ASIR-V40%) and at 1.25-mm slice with deep learning image reconstruction at medium (DLIR-M) and high (DLIR-H) levels and then compared. Computed tomography (CT) attenuation, SD values, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured in the liver, spleen, erector spinae, and intramuscular fat. The lesions in each reconstruction group at 1.25-mm slice thickness were counted. The image quality and diagnostic confidence were subjectively evaluated by two radiologists using a 5-point scale. For the 1.25-mm images, DLIR-M and DLIR-H had lower SD, higher SNR and CNR, and better subjective image quality compared with ASIR-V40%; DLIR-H performed the best (all P values < 0.001). Furthermore, the 1.25-mm DLIR-H images had similar SD, SNR, and CNR values as the 5-mm ASIR-V40% images (all P > 0.05). Three image groups had similar lesion detection rates, but DLIR groups exhibited higher confidence in diagnosing lesions. Compared with ASIR-V40% at 70 keV, 70-keV DECT with DLIR-H further reduced image noise and improved image quality. Additionally, it improved diagnostic confidence while ensuring a consistent lesion detection rate of liver lesions.

Virtual monochromatic images of dual-energy CT as an alternative to single-energy CT: performance comparison using a detectability index for different acquisition techniques

OBJECTIVES

To investigate the performance of virtual monochromatic (VM) images with the same dose and iodine contrast as those for single-energy (SE) images using five dual-energy (DE) scanners with DE techniques: two generations of fast kV switching (FKS), two generations of dual source (DS), and one split filter (SF).

METHODS

A water-bath phantom with a diameter of 300 mm, which contains one rod-shaped phantom made of a material equivalent to soft-tissue and two rod-shaped phantoms made of diluted iodine (2 and 12 mg/mL), was scanned using both SE (120, 100, and 80 kV) and DE techniques with the same CT dose index in each scanner. The VM energy at which the CT number of the iodine rod is closest to that of each SE tube voltage was determined as the equivalent energy (Eeq). A detectability index (d') was calculated from the noise power spectrum, the task transfer functions, and a task function corresponding to each rod. The percentage of the d' value of the VM image to that of the corresponding SE image was calculated for performance comparison.

RESULTS

The average percentages of d' of FKS1, FKS2, DS1, DS2, and SF were 84.6%, 96.2%, 94.3%, 107%, and 104% for 120 kV-Eeq; 75.9%, 91.2%, 88.2%, 99.2%, and 82.6% for 100 kV-Eeq; 71.6%, 88.9%, 82.6%, 85.2%, and 62.3% for 80 kV-Eeq, respectively.

CONCLUSION

The performance of VM images was on the whole inferior to that of SE images especially at low equivalent energy levels, depending on the DE techniques and their generations.

KEY POINTS

• This study evaluated the performance of VM images with the same dose and iodine contrast as those for SE images using five DE scanners. • The performance of VM images varied with the DE techniques and their generations and was mostly inferior at low equivalent energy levels. • The results highlight the importance of distribution of available dose over the two energy levels and spectral separation for the performance improvement of VM images.

Harnessing dual-energy CT for glycogen quantification: a phantom analysis

Background

Non-invasive glycogen quantification in vivo could provide crucial information on biological processes for glycogen storage disorder. Using dual-energy computed tomography (DECT), this study aimed to assess the viability of quantifying glycogen content in vitro.

Methods

A fast kilovolt-peak switching DECT was used to scan a phantom containing 33 cylinders with different proportions of glycogen and iodine mixture at varying doses. The virtual glycogen concentration (VGC) was then measured using material composition images. Additionally, the correlations between VGC and nominal glycogen concentration (NGC) were evaluated using least-square linear regression, then the calibration curve was constructed. Quantitative estimation was performed by calculating the linearity, conversion factor (inverse of curve slope), stability, sensitivity (limit of detection/limit of quantification), repeatability (inter-class correlation coefficient), and variability (coefficient of variation).

Results

In all conditions, excellent linear relationship between VGC and NGC were observed (P<0.001, coefficient of determination: 0.989-0.997; residual root-mean-square error of glycogen: 1.862-3.267 mg/mL). The estimated conversion factor from VGC to NGC was 3.068-3.222. In addition, no significant differences in curve slope were observed among different dose levels and iodine densities. The limit of detection and limit of quantification had respective ranges of 6.421-15.315 and 10.95-16.46 mg/mL. The data demonstrated excellent scan-repeat scan agreement (inter-class correlation coefficient, 0.977-0.991) and small variation (coefficient of variation, 0.1-0.2%).

Conclusions

The pilot phantom analysis demonstrated the feasibility and efficacy of detecting and quantifying glycogen using DECT and provided good quantitative performance with significant stability and reproducibility/variability. Thus, in the future, DECT could be used as a convenient method for glycogen quantification to provide more reliable information for clinical decision-making.

No-reference perceptual CT image quality assessment based on a self-supervised learning framework

Accurate image quality assessment (IQA) is crucial to optimize computed tomography (CT) image protocols while keeping the radiation dose as low as reasonably achievable. In the medical domain, IQA is based on how well an image provides a useful and efficient presentation necessary for physicians to make a diagnosis. Moreover, IQA results should be consistent with radiologists’ opinions on image quality, which is accepted as the gold standard for medical IQA. As such, the goals of medical IQA are greatly different from those of natural IQA. In addition, the lack of pristine reference images or radiologists’ opinions in a real-time clinical environment makes IQA challenging. Thus, no-reference IQA (NR-IQA) is more desirable in clinical settings than full-reference IQA (FR-IQA). Leveraging an innovative self-supervised training strategy for object detection models by detecting virtually inserted objects with geometrically simple forms, we propose a novel NR-IQA method, named deep detector IQA (D2IQA), that can automatically calculate the quantitative quality of CT images. Extensive experimental evaluations on clinical and anthropomorphic phantom CT images demonstrate that our D2IQA is capable of robustly computing perceptual image quality as it varies according to relative dose levels. Moreover, when considering the correlation between the evaluation results of IQA metrics and radiologists’ quality scores, our D2IQA is marginally superior to other NR-IQA metrics and even shows performance competitive with FR-IQA metrics.

Plan-Do-Check-Action Circulation Combined with Accelerated Rehabilitation Nursing under Computed Tomography in Prevention and Control of Hospital Infection in Elderly Patients Undergoing Elective Orthopedic Surgery

To explore the adoption of plan-do-check-action (PDCA) circulation combined with accelerated rehabilitation nursing based on gemstone spectral imaging computed tomography (GSICT) in the prevention and control of hospital infection in the elderly patients undergoing the elective orthopedic surgery, 80 elderly patients who underwent the elective orthopedic surgery in the hospital were selected. Then, according to the randomized controlled principle, these 80 patients were divided into control group (40 cases) with conventional nursing and observation group (40 cases) with accelerated rehabilitation surgical nursing combined with PDCA circulation. All the patients underwent the GSICT examination without any contraindicators. Compared with the conventional CT scan, metal artifacts in GSICT were considerably reduced. In the images processed by GSI and metal artifacts reduction system (MARS), metal artifacts were basically eliminated and the positions, forms, and edges of metal artifacts in the human body were clearly presented. Hospital infection occurred in 1 (2.5%) patient in the observation group and 5 (12.5%) patients in the control group, and the difference was statistically significant (P < 0.05). In terms of temperature increase, patients in control group (37.5%) had a remarkably higher value than that of observation group (7.5%). The increase rate of white blood cell (WBC) count in control group (12.5%) was obviously higher than that in observation group (2.5%). Besides, the differences were statistically significant (P < 0.05). After PDCA circulation combined with accelerated rehabilitation nursing mode was applied, the hospitalization time of observation group (5.3 ± 2.4 days) was markedly lower than that of control group (9.7 ± 3.8 days). Moreover, the total hospitalization cost of observation group (791.44 yuan) was notably lower than that of control group (4068.96 yuan), with significant differences (P < 0.05). Nursing satisfaction in observation group (92.5%) was higher than that in control group (77.5%), and the difference was statistically significant (P < 0.05). In short, GSICT could effectively reduce beam hardening artifacts and metal implant artifacts and improve image quality. Furthermore, accelerated rehabilitation nursing combined with PDCA circulation could effectively reduce the incidence of hospital infection and improve nursing satisfaction.

Comparison of two different GSI scanning protocols in head and neck CT angiography: Image quality and radiation dose

OBJECTIVES

To compare image quality and radiation dose of computed tomography angiography (CTA) of the head and neck in patients using two Gemstone Spectral Imaging (GSI) scanning protocols.

METHODS

A total of 100 patients who underwent head-neck CTA were divided into two groups (A and B) according to the scanning protocols, with 50 patients in each group. The patients in group A underwent GSI scanning protocol 1 (GSI profile: head and neck CTA), while those in group B underwent GSI scanning protocol 2 (GSI profile: chest 80 mm). All images were reconstructed using 40% and 70% pre- and post-adaptive level statistical iterative reconstruction V (pre-ASiR-V and post-ASiR-V) algorithms, respectively. The CT dose index (CTDIvol) and dose-length (DLP) product were recorded and the mean value was calculated and converted to the effective dose. CT values, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) of all images were calculated. Additionally, subjective image evaluation was conducted by two independent radiologists using a five-point scoring method. All data were statistically analyzed.

RESULTS

There were no significant differences in the CT values, SNR, CNR, and subjective score between groups A and B (p > 0.05); however, the mean effective dose (1.2±0.1 mSv) in group B was 45.5% lower than that in group A (2.2±0.2 mSv) (p < 0.05).

CONCLUSIONS

GSI scanning protocol 2 could more effectively reduce the radiation dose in head-neck CT angiography while maintaining image quality compared to GSI scanning protocol 1.

Comparison of the image quality and radiation dose of different scanning modes in head-neck CT angiography

OBJECTIVES

To analyze and compare the radiation dose and image quality of different CT scanning modes on head-neck CT angiography.

METHODS

A total of 180 patients were divided into Group A and Group B. The groups were further subdivided according to different scanning modes: subgroups A1, A2, A3, B1, B2, and B3. Subgroups A1 and B1 used conventional CT protocol, subgroups A2 and B2 used the kV-Assist scan mode, and subgroups A3 and B3 used the dual-energy gemstone spectral imaging protocol. The CT dose index and dose-length product were recorded. The objective image quality and subjective image evaluation was conducted by two independent radiologists.

RESULTS

The signal-to-noise ratios, contrast-to-noise ratios, and subjective scores of subgroups A3 and B3 were higher than the other subgroups. In subgroups B1 and B2, the subjective scores of 9 patients and 12 patients were lower than 3, respectively. The subjective scores of subgroups B1 and B2 were lower than the other subgroups. There was no statistically significant difference in signal-to-noise ratios, contrast-to-noise ratios, and subjective scores between subgroups A1 and A2. The effective dose of subgroup A2 was 41.7 and 36.4% lower than that in subgroups A1 and A3, respectively (p < 0.05). In Group B, there were no statistically significant differences in CT dose indexvol, dose-length product, and ED among the subgroups (p > 0.05).

CONCLUSION

In the head-neck CT angiography, the kV-Assist scan mode is recommended for patients with body mass index between 18.5 and 34.9 kg m^-2; gemstone spectral imaging scanning mode is recommended for patients with body mass index ≥34.9 kg m^-2.

Dual-Energy Computed Tomography of the Liver: Uses in Clinical Practices and Applications

Dual-energy computed tomography (DECT) is an imaging technique based on data acquisition at two different energy settings. Recent advances in CT have allowed data acquisitions and simultaneous analyses of X-rays at two energy levels, and have resulted in novel developments in the field of abdominal imaging. The use of low and high X-ray tube voltages in DECT provide fused images that improve the detection of liver tumors owing to the higher contrast-to-noise ratio (CNR) of the tumor compared with the liver. The use of contrast agents in CT scanning improves image quality by enhancing the CNR and signal-to-noise ratio while reducing beam-hardening artifacts. DECT can improve detection and characterization of hepatic abnormalities, including mass lesions. The technique can also be used for the diagnosis of steatosis and iron overload. This article reviews and illustrates the different applications of DECT in liver imaging.

Comparison of image quality and radiation dose using different pre-ASiR-V and post-ASiR-V levels in coronary computed tomography angiography

OBJECTIVE

To determine the optimal pre-adaptive and post-adaptive level statistical iterative reconstruction V (ASiR-V) for improving image quality and reducing radiation dose in coronary computed tomography angiography (CCTA).

METHODS

The study was divided into two parts. In part I, 150 patients for CCTA were prospectively enrolled and randomly divided into 5 groups (A, B, C, D, and E) with progressive scanning from 40% to 80% pre-ASiR-V with 10% intervals and reconstructing with 70% post-ASiR-V. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Subjective image quality was assessed using a 5-point scale. The CT dose index volume (CTDIvol) and dose-length product (DLP) of each patient were recorded and the effective radiation dose (ED) was calculated after statistical analysis by optimizing for the best pre-ASiR-V value with the lowest radiation dose while maintaining overall image quality. In part II, the images were reconstructed with the recommended optimal pre-ASiR-V values in part I (D group) and 40%-90% of post-ASiR-V. The reconstruction group (D group) was divided into 6 subgroups (interval 10%, D0:40% post-ASiR-V, D1:50% post - ASiR-V, D2:60% post-ASiR-V, D3:70% post-ASiR-V, D4:80% post-ASiR-V, and D5:90% post-ASiR-V).The SNR and CNR of D0-D5 subgroups were calculated and analyzed using one-way analysis of variance, and the consistency of the subjective scores used the k test.

RESULTS

There was no significant difference in the SNRs, CNRs, and image quality scores among A, B, C, and D groups (P > 0.05). The SNR, CNR, and image quality scores of the E group were lower than those of the A, B, C, and D groups (P < 0.05). The mean EDs in the B, C, and D groups were reduced by 7.01%, 13.37%, and 18.87%, respectively, when compared with that of the A group. The SNR and CNR of the D4-D5 subgroups were higher than the D0-D3 subgroups, and the image quality scores of the D4 subgroups were higher than the other subgroups (P < 0.05).

CONCLUSION

The wide-detector combined with 70% pre-ASiR-V and 80% post-ASiR-V significantly reduces the radiation dose of CCTA while maintaining overall image quality as compared with the manufacture's recommendation of 40% pre-ASiR-V.

Improved Diagnostic Accuracy of Bone Metastasis Detection by Water-HAP Associated to Non-Contrast CT

We examined whether water-hydroxyapatite (HAP) images improve the diagnostic accuracy of bone metastasis compared with non-contrast CT alone. We retrospectively evaluated dual-energy computed tomography (DECT) images of 83 cancer patients (bone metastasis, 31; without bone metastasis, 52) from May 2018 to June 2019. Initially, two evaluators examined for bone metastasis on conventional CT images. In the second session, both CT and CT images plus water-HAP images on DECT. The confidence of bone metastasis was scored from 1 (benign) to 5 (malignant). The sensitivity, specificity, positive predictive values, and negative predictive values for both modalities were calculated based on true positive and negative findings. The intra-observer area under curve (AUC) for detecting bone metastasis was compared by receiver operating characteristic analysis. Kappa coefficient calculated the inter-observer agreement. In conventional CT images, sensitivity, specificity, positive predictive value, and negative predictive value of raters 1 and 2 for the identification of bone metastases were 0.742 and 0.710, 0.981 and 0.981, 0.958 and 0.957, and 0.864 and 0.850, respectively. In water-HAP, they were 1.00 and 1.00, 0.981 and 1.00, 0.969 and 1.00, and 1.00 and 1.00, respectively. In CT, AUCs were 0.861 and 0.845 in each observer. On water-HAP images, AUCs were 0.990 and 1.00. Kappa coefficient was 0.964 for CT and 0.976 for water-HAP images. The combination of CT and water-HAP images significantly increased diagnostic accuracy for detecting bone metastasis. Water-HAP images on DECT may enable accurate initial staging, reduced radiation exposure, and cost.