A comprehensive assessment of physical image quality of five different scanners for head CT imaging as clinically used at a single hospital centre-A phantom study

Evaluation of Radiation Dose and Image Quality in Clinical Routine Protocols from Three Different CT Scanners

Computed tomography examination plays a vital role in imaging and its use has rapidly increased in radiology diagnosis. This study aimed to assess radiation doses of routine CT protocols of the brain, chest, and abdomen in three different CT scanners, together with a qualitative image quality assessment.

METHODS

A picture archiving and communication system (PACS) and Radimetrics software version 3.4.2 retrospectively collected patients' radiation doses. Radiation doses were recorded as the CTDIvol, dose length product, and effective dose. CT images were acquired using the Catphan700 phantom to evaluate image quality.

RESULTS

The findings revealed that median values for the CTDIvol and DLP across the brain, chest, and abdomen protocols were lower than the national and international DRLs. Effective doses for brain, chest, and abdomen protocols were also below the median value of R. Smith-Bindman. Neusoft achieved higher spatial frequencies in brain protocols, while Siemens outperformed others in chest protocols. Neusoft consistently exhibited superior high-contrast resolution. Siemens and Neusoft outperformed low-contrast detectability, while Siemens also outperformed the contrast-to-noise ratio. In addition, Siemens had the lowest image noise in brain protocols and high uniformity in chest and abdomen protocols. Neusoft showed the lowest noise in chest and abdomen protocols and high uniformity in the brain protocol. The noise power spectrum revealed that Philips had the highest noise magnitude with different noise textures across protocols and scanners.

CONCLUSIONS

This study provides a comprehensive evaluation of radiation doses and image quality for three different CT scanners using standard clinical protocols. Almost all CT protocols exhibited radiation doses below the DRLs and demonstrated varying image qualities across each protocol and scanner. Selecting the right CT scanner for each protocol is essential to ensure that the CT images exhibit the best quality among a wide range of CT machines. The MTF, HCR, LCD, CNR, NPS, noise, and uniformity are suitable parameters for evaluating and monitoring image quality.

Hybrid iterative reconstruction in ultra-low-dose CT for accurate pulmonary nodule assessment: A Phantom study

This study evaluated hybrid iterative reconstruction in ultra-low-dose computed tomography (ULDCT) for solid pulmonary nodule detection. A 256-slice CT machine operating at 120 kVp imaged a chest phantom with 5 mm nodules. The imaging process involved adjusting low-dose computed tomography (LDCT) settings and conducting 3 ULDCT scans (A-C) with varied minimum and maximum mA settings (10/40 mA). Images were processed using iDose4 iterative reconstruction at levels 5 to 7. Measurements were taken for noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), noise power spectrum (NPS), and detectability index (D') to assess image quality, noise texture, and detectability. Analysis of variance (ANOVA) was used to compare the protocols. Noise levels varied significantly across iDose4 iterative reconstruction levels, with the highest noise at 178 HU in iDose4 L5 (protocol C) and the lowest at 54.85 HU in level 7 (protocol A). ULDCT scans showed noise increases of 38.5%, 104.2%, and 118.7% for protocols A, B, and C, respectively, compared to LDCT. Protocol A (iDose4 level 7) significantly improved SNR and CNR (P < .001). The mean volume CT dose index was 2.4 mGy for LDCT and 2.0 mGy, 1.2 mGy, and 0.7 mGy for ULDCT protocols A, B, and C, respectively. Increasing iDose4 levels reduced noise magnitude in the NPS and improved the D'. ULDCT with iDose4 level 7 provides diagnostically acceptable image quality for solid pulmonary nodule assessment at significantly reduced radiation doses. This approach, supported by advanced metrics like NPS and D', demonstrates a potential pathway for safer, effective lung cancer screening in high-risk populations. Further clinical studies are needed to validate these findings in diverse patient populations.

Advancing the understanding and treatment of lung pathologies associated with alpha 1 antitrypsin deficiency

Alpha 1 antitrypsin deficiency (AATD) is a genetic disorder that alters the functionality and/or serum levels of alpha 1 antitrypsin (AAT). Dysfunctional forms of AAT, or low levels of serum AAT, predispose affected individuals to pulmonary complications. When AATD-associated lung disease develops, the most common pulmonary pathology is emphysema. The development of emphysema and decline in lung function varies by AATD genotype and is accelerated by risk factors, such as smoking. To improve the understanding and treatment of AATD, emerging knowledge and unresolved questions need to be discussed. Here we focus on developments in the areas of disease pathogenesis, biomarkers, and clinical endpoints for trials in AATD, as well as barriers to treatment. The clinical impact of AATD on lung function is highly variable and highlights the complexity of AATD pathogenesis, in which multiple underlying processes are involved. Reduced levels of functional AAT disrupt the protease-antiprotease homeostasis, leading to a loss of neutrophil elastase inhibition and the breakdown of elastin within the lung interstitium. Inflammatory processes also play a critical role in the development of AATD-associated lung disease, which is not yet fully understood. Biomarkers associated with the disease and its complications may have an important role in helping to address AATD underdiagnosis and evaluating response to treatment. To improve access to treatment, the problem of underdiagnosis needs to be addressed and the provision of therapeutic options needs to become uniform. Patients should also be empowered to play a key role in the self-management of the disease. Advancing our understanding of the disease will ultimately improve the life expectancy and quality of life for patients affected by AATD.

Image quality and radiation doses in abdominal CT: A multicenter study

PURPOSE

To benchmark image quality and corresponding radiation doses for acute abdominal CT examination across different laboratories and CT manufacturers.

METHOD

An anthropomorphic phantom was scanned once with local abdominal CT protocols at 40 CT scanners, from four vendors, in thirty-three sites. Quantitative image quality was evaluated by CNR and SNR in the liver and kidney parenchyma. Qualitative image quality was assessed by visual grading analysis performed by three experienced radiologists using a five-point Likert scale to score thirteen image quality criteria. The CTDIvol was recorded for each scan. Pearson's correlation coefficient was calculated for the continuous variables, and the intraclass correlation coefficient was used to investigate interrater reliability between the radiologists.

RESULTS

CTDIvol ranged from 3.5 to 12 mGy (median 5.3 mGy, third quartile 6.7 mGy). SNR in liver parenchyma ranged from 4.4 to 14.4 (median 8.5), and CNR ranged from 2.7 to 11.2 (median 6.1). A weak correlation was found between CTDIvol and CNR (r = 0.270, p = 0.092). Variations in CNR across scanners at the same dose level CTDIvol were observed. No significant difference in CTDIvol or CNR was found based on scanner installation year. The oldest scanners had a 15 % higher median CTDIvol and a 12 % lower median CNR. The ICC showed acceptable agreement for all dose groups: low (ICC=0.889), medium (ICC=0.767), high (ICC=0.847), and in low (ICC=0.803) and medium (ICC=0.811) CNR groups.

CONCLUSION

There was large variation in radiation dose and image quality across the different CT scanners. Interestingly, the weak correlation between CTDIvol and CNR indicates that higher doses do not consistently improve CNR, indicating a need for systematic assessment and optimization of image quality and radiation doses for the abdominal CT examination.

Evaluation of low-dose pediatric chest CT examination using in-house developed various age-size pediatric chest phantoms

PURPOSE

This study aims to develop Various Age-size Pediatric Chest Phantoms (VAPC) to evaluate low-dose protocol that approximates clinical conditions achieved by low organ-specific doses and optimal image quality among the challenges of pediatric size variations.

METHODS

Three original pediatric data aged 1, 4, and 7 years were used as a reference for developing VAPC phantoms. Six protocols, namely standard dose (STD) and low dose (low mA and low kV) reconstructed using Filtered Back Projection (FBP) and iterative reconstruction (IR) algorithms, were investigated. This study directly measured the lungs, heart, and spinal cord dose using LD-V1 film. Linearity, Modulation Transfer Function (MTF), Contrast to Noise Ratio (CNR), and Noise Power Spectrum (NPS) were evaluated to assess the CT image quality of the VAPC phantom.

RESULTS

This study found that the mean organ-specific dose was higher than CTDIvol. A Comparison of mean lung doses showed VAPC phantom 1 (y.o.) received 74.8% and 137.2% more doses than 4 (y.o.) and 7 (y.o.), respectively. Low kV produces a lower organ dose than low mA. The linearity of CT numbers is not biased at low doses. Differences in age measures significantly influenced organ-specific dose, MTF, CNR, and NPS.

CONCLUSION

Smaller pediatrics are still exposed to higher doses at low-dose examinations, whereas larger pediatrics have lower contrast resolution and increased image noise. CT number linearity is unbiased. The combination of low kV with FBP produces higher spatial resolution, while low mA with IR effectively reduces noise to detect low-contrast objects better.

Comparison between solid pseudopapillary neoplasms of the pancreas and pancreatic ductal adenocarcinoma with cystic changes using computed tomography

BACKGROUND

Solid pseudopapillary neoplasms of the pancreas (SPN) share similar imaging findings with pancreatic ductal adenocarcinoma with cystic changes (PDAC with cystic changes), which may result in unnecessary surgery.

AIM

To investigate the value of computed tomography (CT) in differentiation of SPN from PDAC with cystic changes.

METHODS

This study retrospectively analyzed the clinical and imaging findings of 32 patients diagnosed with SPN and 14 patients diagnosed with PDAC exhibiting cystic changes, confirmed through pathological diagnosis. Quantitative and qualitative analysis was performed, including assessment of age, sex, tumor size, shape, margin, density, enhancement pattern, CT values of tumors, CT contrast enhancement ratios, "floating cloud sign," calcification, main pancreatic duct dilatation, pancreatic atrophy, and peripancreatic invasion or distal metastasis. Multivariate logistic regression analysis was used to identify relevant features to differentiate between SPN and PDAC with cystic changes, and receiver operating characteristic curves were obtained to evaluate the diagnostic performance of each variable and their combination.

RESULTS

When compared to PDAC with cystic changes, SPN had a lower age (32 years vs 64 years, P < 0.05) and a slightly larger size (5.41 cm vs 3.90 cm, P < 0.05). SPN had a higher frequency of "floating cloud sign" and peripancreatic invasion or distal metastasis than PDAC with cystic changes (both P < 0.05). No significant difference was found with respect to sex, tumor location, shape, margin, density, main pancreatic duct dilatation, calcification, pancreatic atrophy, enhancement pattern, CT values of tumors, or CT contrast enhancement ratios between the two groups (all P > 0.05). The area under the receiver operating characteristic curve of the combination was 0.833 (95% confidence interval: 0.708-0.957) with 78.6% sensitivity, 81.3% specificity, and 80.4% accuracy in differentiation of SPN from PDAC with cystic changes.

CONCLUSION

A larger tumor size, "floating cloud sign," and peripancreatic invasion or distal metastasis are useful CT imaging features that are more common in SPN and may help discriminate SPN from PDAC with cystic changes.

Investigation of a potential upstream harmonization based on image appearance matching to improve radiomics features robustness: a phantom study

Objective. Radiomics is a promising valuable analysis tool consisting in extracting quantitative information from medical images. However, the extracted radiomics features are too sensitive to variations in used image acquisition and reconstruction parameters. This limited robustness hinders the generalizable validity of radiomics-assisted models. Our aim is to investigate a possible harmonization strategy based on matching image quality to improve feature robustness.Approach.We acquired CT scans of a phantom with two scanners across different dose levels and percentages of Iterative Reconstruction algorithms. The detectability index was used as a comprehensive task-based image quality metric. A statistical analysis based on the Intraclass Correlation Coefficient was performed to determine if matching image quality/appearance could enhance the robustness of radiomics features extracted from the phantom images. Additionally, an Artificial Neural Network was trained on these features to automatically classify the scanner used for image acquisition.Main results.We found that the ICC of the features across protocols providing a similar detectability index improves with respect to the ICC of the features across protocols providing a different detectability index. This improvement was particularly noticeable in features relevant for distinguishing between scanners.Significance.This preliminary study demonstrates that a harmonization based on image quality/appearance matching could improve radiomics features robustness and heterogeneous protocols can be used to obtain a similar image appearance in terms of the detectability index. Thus protocols with a lower dose level could be selected to reduce the amount of radiation dose delivered to the patient and simultaneously obtain a more robust quantitative analysis.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

A Review of Imaging Methods to Assess Ultrasound-Mediated Ablation

Ultrasound ablation techniques are minimally invasive alternatives to surgical resection and have rapidly increased in use. The response of tissue to HIFU ablation differs based on the relative contributions of thermal and mechanical effects, which can be varied to achieve optimal ablation parameters for a given tissue type and location. In tumor ablation, similar to surgical resection, it is desirable to include a safety margin of ablated tissue around the entirety of the tumor. A factor in optimizing ablative techniques is minimizing the recurrence rate, which can be due to incomplete ablation of the target tissue. Further, combining focal ablation with immunotherapy is likely to be key for effective treatment of metastatic cancer, and therefore characterizing the impact of ablation on the tumor microenvironment will be important. Thus, visualization and quantification of the extent of ablation is an integral component of ablative procedures. The aim of this review article is to describe the radiological findings after ultrasound ablation across multiple imaging modalities. This review presents readers with a general overview of the current and emerging imaging methods to assess the efficacy of ultrasound ablative treatments.