Effects of pure and hybrid iterative reconstruction algorithms on high-resolution computed tomography in the evaluation of interstitial lung disease

Image Quality and Lesion Detection of Multiplanar Reconstruction Images Using Deep Learning: Comparison with Hybrid Iterative Reconstruction

Background

We assessed and compared the image quality of normal and pathologic structures as well as the image noise in chest computed tomography images using "adaptive statistical iterative reconstruction-V" (ASiR-V) or deep learning reconstruction "TrueFidelity".

Methods

Forty consecutive patients with suspected lung disease were evaluated. The 1.25-mm axial images and 2.0-mm coronal multiplanar images were reconstructed under the following three conditions: (i) ASiR-V, lung kernel with 60% of ASiR-V; (ii) TF-M, standard kernel, image filter (Lung) with TrueFidelity at medium strength; and (iii) TF-H, standard kernel, image filter (Lung) with TrueFidelity at high strength. Two radiologists (readers) independently evaluated the image quality of anatomic structures using a scale ranging from 1 (best) to 5 (worst). In addition, readers ranked their image preference. Objective image noise was measured using a circular region of interest in the lung parenchyma. Subjective image quality scores, total scores for normal and abnormal structures, and lesion detection were compared using Wilcoxon's signed-rank test. Objective image quality was compared using Student's paired t-test and Wilcoxon's signed-rank test. The Bonferroni correction was applied to the P value, and significance was assumed only for values of P < 0.016.

Results

Both readers rated TF-M and TF-H images significantly better than ASiR-V images in terms of visualization of the centrilobular region in axial images. The preference score of TF-M and TF-H images for reader 1 were better than that of ASiR-V images, and the preference score of TF-H images for reader 2 were significantly better than that of ASiR-V and TF-M images. TF-M images showed significantly lower objective image noise than ASiR-V or TF-H images.

Conclusion

TrueFidelity showed better image quality, especially in the centrilobular region, than ASiR-V in subjective and objective evaluations. In addition, the image texture preference for TrueFidelity was better than that for ASiR-V.

Comparison of Deep-Learning Image Reconstruction With Hybrid Iterative Reconstruction for Evaluating Lung Nodules With High-Resolution Computed Tomography

OBJECTIVE

This study aimed to investigate the impact of deep-learning reconstruction (DLR) on the detailed evaluation of solitary lung nodule using high-resolution computed tomography (HRCT) compared with hybrid iterative reconstruction (hybrid IR).

METHODS

This retrospective study was approved by our institutional review board and included 68 consecutive patients (mean ± SD age, 70.1 ± 12.0 years; 37 men and 31 women) who underwent computed tomography between November 2021 and February 2022. High-resolution computed tomography images with a targeted field of view of the unilateral lung were reconstructed using filtered back projection, hybrid IR, and DLR, which is commercially available. Objective image noise was measured by placing the regions of interest on the skeletal muscle and recording the SD of the computed tomography attenuation. Subjective image analyses were performed by 2 blinded radiologists taking into consideration the subjective noise, artifacts, depictions of small structures and nodule rims, and the overall image quality. In subjective analyses, filtered back projection images were used as controls. Data were compared between DLR and hybrid IR using the paired t test and Wilcoxon signed-rank sum test.

RESULTS

Objective image noise in DLR (32.7 ± 4.2) was significantly reduced compared with hybrid IR (35.3 ± 4.4) (P < 0.0001). According to both readers, significant improvements in subjective image noise, artifacts, depictions of small structures and nodule rims, and overall image quality were observed in images derived from DLR compared with those from hybrid IR (P < 0.0001 for all).

CONCLUSIONS

Deep-learning reconstruction provides a better high-resolution computed tomography image with improved quality compared with hybrid IR.

Diagnosis and monitoring of systemic sclerosis-associated interstitial lung disease using high-resolution computed tomography

Patients with systemic sclerosis are at high risk of developing systemic sclerosis-associated interstitial lung disease. Symptoms and outcomes of systemic sclerosis-associated interstitial lung disease range from subclinical lung involvement to respiratory failure and death. Early and accurate diagnosis of systemic sclerosis-associated interstitial lung disease is therefore important to enable appropriate intervention. The most sensitive and specific way to diagnose systemic sclerosis-associated interstitial lung disease is by high-resolution computed tomography, and experts recommend that high-resolution computed tomography should be performed in all patients with systemic sclerosis at the time of initial diagnosis. In addition to being an important screening and diagnostic tool, high-resolution computed tomography can be used to evaluate disease extent in systemic sclerosis-associated interstitial lung disease and may be helpful in assessing prognosis in some patients. Currently, there is no consensus with regards to frequency and scanning intervals in patients at risk of interstitial lung disease development and/or progression. However, expert guidance does suggest that frequency of screening using high-resolution computed tomography should be guided by risk of developing interstitial lung disease. Most experienced clinicians would not repeat high-resolution computed tomography more than once a year or every other year for the first few years unless symptoms arose. Several computed tomography techniques have been developed in recent years that are suitable for regular monitoring, including low-radiation protocols, which, together with other technologies, such as lung ultrasound and magnetic resonance imaging, may further assist in the evaluation and monitoring of patients with systemic sclerosis-associated interstitial lung disease. A video abstract to accompany this article is available at: https://www.globalmedcomms.com/respiratory/Khanna/HRCTinSScILD.

Artificial Intelligence Algorithm-Based High-Resolution Computed Tomography Image in the Treatment of Children with Bronchiolitis Obliterans by Traditional Chinese Medicine Method of Resolving Phlegm and Removing Blood Stasis

This research was aimed to explore the application of high-resolution computed tomography (HRCT) based on intelligent iterative reconstruction technique in the early diagnosis and treatment of bronchiolitis obliterans (BO) in children and to explore the efficacy of traditional Chinese medicine (TCM) in resolving phlegm and removing blood stasis. Sixty pediatric patients with BO were selected as the study subjects and diagnosed by HRCT scanning, and the scanned images were processed by iterative reconstruction technique. The patients were treated with TCM therapy of resolving phlegm and removing blood stasis alone (group A), HRCT-guided TCM therapy of resolving phlegm and removing blood stasis (group B), and iterative reconstruction HRCT-guided TCM therapy of resolving phlegm and removing blood stasis (group C). The results showed that the lung HRCT image after iterative reconstruction was closer to the original image than that after filtered back projection reconstruction, and the edge of the image after filtered back projection reconstruction was more blurred and the noise was higher. The image obtained by iterative reconstruction technique was smoother and clearer, and the image stability after iterative reconstruction was higher. The treatment results showed that the proportion of moderate and severe obstruction in group C was 5.18%, which was significantly lower than that in group A (18.75%) and group B (11.29%), and group B was significantly lower than that in group A (18.75%) (P < 0.05). The proportion of clinical effect in group C after treatment was 70.18%, significantly higher than that in group A (55.5%) and group B (63.34%), and that in group B was significantly higher than that in group A (55.5%) (P < 0.05). In summary, the lung HRCT after iterative reconstruction can more clearly and intuitively show the lesion site, which has a key role in guiding the early diagnosis and treatment planning of BO; the HRCT image based on iterative reconstruction technique combined with TCM treatment of removing blood stasis and resolving phlegm has a better therapeutic effect on children, with a high application value.

Comparison of lung image quality between CT Ark and Brilliance 64 CT during COVID-19

AIM

This study is to compare the lung image quality between shelter hospital CT (CT Ark) and ordinary CT scans (Brilliance 64) scans.

METHODS

The patients who received scans with CT Ark or Brilliance 64 CT were enrolled. Their lung images were divided into two groups according to the scanner. The objective evaluation methods of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were used. The subjective evaluation methods including the evaluation of the fine structure under the lung window and the evaluation of the general structure under the mediastinum window were compared. Kappa method was used to assess the reliability of the subjective evaluation. The subjective evaluation results were analyzed using the Wilcoxon rank sum test. SNR and CNR were tested using independent sample t tests.

RESULTS

There was no statistical difference in somatotype of enrolled subjects. The Kappa value between the two observers was between 0.68 and 0.81, indicating good consistency. For subjective evaluation results, the rank sum test P value of fine structure evaluation and general structure evaluation by the two observers was ≥ 0.05. For objective evaluation results, SNR and CNR between the two CT scanners were significantly different (P<0.05). Notably, the absolute values ​​of SNR and CNR of the CT Ark were larger than Brilliance 64 CT scanner.

CONCLUSION

CT Ark is fully capable of scanning the lungs of the COVID-19 patients during the epidemic in the shelter hospital.

Practical Imaging Interpretation in Patients Suspected of Having Idiopathic Pulmonary Fibrosis: Official Recommendations from the Radiology Working Group of the Pulmonary Fibrosis Foundation

Imaging serves a key role in the diagnosis of patients suspected of having idiopathic pulmonary fibrosis (IPF). Accurate pattern classification at thin-section chest CT is a key step in multidisciplinary discussions, guiding the need for surgical lung biopsy and determining available pharmacologic therapies. The recent approval of new treatments for fibrosing lung disease has made it more critical than ever for radiologists to facilitate accurate and early diagnosis of IPF. This document was developed by the Radiology Working Group of the Pulmonary Fibrosis Foundation with the goal of providing a practical guide for radiologists. In this review, the critical imaging patterns of IPF, pitfalls in imaging classifications, confounding imaging findings with other fibrotic lung diseases, and reporting standards for cases of lung fibrosis will be discussed.

Published under a CC BY 4.0 license.

See also the commentary by White and Galvin in this issue.

Deep learning trained algorithm maintains the quality of half-dose contrast-enhanced liver computed tomography images: Comparison with hybrid iterative reconstruction: Study for the application of deep learning noise reduction technology in low dose

PURPOSE

This study compares the image and diagnostic qualities of a DEep Learning Trained Algorithm (DELTA) for half-dose contrast-enhanced liver computed tomography (CT) with those of a commercial hybrid iterative reconstruction (HIR) method used for standard-dose CT (SDCT).

METHODS

This study enrolled 207 adults, and they were divided into two groups: SDCT and low-dose CT (LDCT). SDCT was reconstructed using the HIR method (SDCT_HIR), and LDCT was reconstructed using both the HIR method (LDCT_HIR) and DELTA (LDCT_DL). Noise, Hounsfield unit (HU) values, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between three image series. Two radiologists assessed the noise, artefacts, overall image quality, visualisation of critical anatomical structures and lesion detection, characterisation and visualisation.

RESULTS

The mean effective doses were 5.64 ± 1.96 mSv for SDCT and 2.87 ± 0.87 mSv for LDCT. The noise of LDCT_DL was significantly lower than that of SDCT_HIR and LDCT_HIR. The SNR and CNR of LDCT_DL were significantly higher than those of the other two groups. The overall image quality, visualisation of anatomical structures and lesion visualisation between LDCT_DL and SDCT_HIR were not significantly different. For lesion detection, the sensitivities and specificities of SDCT_HIR vs. LDCT_DL were 81.9 % vs. 83.7 % and 89.1 % vs. 86.3 %, respectively, on a per-patient basis. SDCT_HIR showed 75.4 % sensitivity and 82.6 % specificity for lesion characterisation on a per-patient basis, whereas LDCT_DL showed 73.5 % sensitivity and 82.4 % specificity.

CONCLUSIONS

LDCT with DELTA had approximately 49 % dose reduction compared with SDCT with HIR while maintaining image quality on contrast-enhanced liver CT.

The influence of model iterative reconstruction on the image quality in standard and low-dose computer tomography of the chest. Experimental study

Background. One of the ways to reduce the radiation dose in CT is to the image reconstruction algorithms. The latest offer from CT scanner manufacturers is Model Iterative Reconstruction (MIR). Aims: to compare the quality of visualization of the structures of the chest organs and to prove the effectiveness of the low-dose protocol with iterative model reconstruction. Methods. A calibration phantom with a spatial resolution module and an anthropomorphic phantom of the upper body of an adult with nodules in the lungs were scanned using two CT scanners of different manufacturers. Two protocols were applied: the standard dose protocol (SDCT) with the algorithms of hybrid iterative reconstruction (HIR) of images and MIR and a low-dose protocol (LDCT) with the MIRalgorithm. The quality of the obtained images was evaluated by the following parameters: noise (SD), the contrast-to-noise ratio (CNR), spatial resolution and visualization of pulmonary nodules. The radiation dose was calculated according to the scanner data, the data of individual dosimeters placed on the anthropomorphic phantom, and using a dosimetric phantom. Results. The average SD was 11.5; 24.4 and 21.6; CNR 85.47; 40.6 and 45.6; spatial resolution 2 mm; 2 mm and 3 mm for SDCT with MIR, SDCT with HIR and LDCT with MIR respectively. Visualization of the pulmonary lesions remained excellent in all cases. The radiation dose in case of SDCT was 2.7, and in case of LDCT 0.67 mSv. The dose reduction was confirmed by the dosimeter data. Similar results were obtained by repeating the experiment with a second scanner. Conclusions. The model iterative reconstruction application will allow reducing the irradiatin dose during CT scanning of the chest organs without deterioration of the visualization quality.

New Fast kVp Switching Dual-Energy CT: Reduced Severity of Beam Hardening Artifacts and Improved Image Quality in Reduced-Iodine Virtual Monochromatic Imaging

RATIONALE AND OBJECTIVES

To compare degradation of the image quality due to beam hardening artifacts in reduced-iodine-dose virtual monochromatic imaging (VMI) between a new fast kVp switching dual-energy computed tomography (CT) scanner (Revolution CT) and the conventional dual-energy scanner (Discovery CT).

MATERIALS AND METHODS

First, a phantom study was performed to quantitatively evaluate beam hardening artifacts in images obtained by VMI reconstruction at different energy levels. In the second study, we performed a retrospective evaluation of the images of 28 patients who had undergone reduced-iodine (300 mg/kg) dual-energy scanning in both Revolution CT and Discovery CT. We evaluated each image quantitatively by measuring the contrast-to-noise ratio (CNR) and qualitatively by scoring the artifacts and image quality. We also calculated the modulation transfer function (MTF) and noise power spectrum (NPS) of the two scanners.

RESULTS

In the phantom study, VMI reconstruction of the CT images at 40-70 keV was associated with a significantly greater reduction in the severity of the artifacts in the Revolution CT images as compared to the Discovery CT images. In the retrospective study, there were no significant differences in the CT value of the aorta, noise, or CNR between the two scanners, but the scores for image quality were significantly higher in the Revolution CT images as compared to the Discovery CT images. The MTF of Revolution CT was higher than that of Discovery CT, reflecting the better spatial resolution.

CONCLUSION

In Revolution CT, beam hardening artifacts were reduced in reduced-iodine VMI at lower energy levels compared to Discovery CT, contributing to better image quality.

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.

Image quality and radiation dose reduction in chest CT in pulmonary infection

PURPOSE

To evaluate the effect of dose reduction with iterative reconstruction (IR) on image quality of chest CT scan comparing two protocols.

MATERIALS AND METHODS

Fifty-nine patients were enrolled. The two CT protocols were applied using Iterative Reconstruction (ASIR™) 40% but different noise indexes, recording dose-length product (DLP) and volume computed tomography dose index (CTDI_vol). The subjective IQ was rated based on the distinction of anatomic details using a 4-point Likert scale based on the European Guidelines on Quality Criteria for CT. For each patient, two single CTs, at enrollment (group 1) and at follow-up after lowering the dose (group 2), were evaluated by two radiologists evaluating, for each examination, five different lung regions (central zone-CZ; peripheral zone-PZ; sub-pleural region-SPR; centrilobular region-CLR; and apical zone-AZ). An inter-observer agreement was expressed by weighted Cohen's kappa statistics (k) and intra-individual differences of subjective image analysis through visual grading characteristic (VGC) analysis.

RESULTS

An average 50.4% reduction in CTDI_vol and 51.5% reduction in DLP delivered were observed using the dose-reduced protocol. An agreement between observers evaluating group 1 CTs was perfect (100%) and moderate to good in group 2 examinations (k-Cohen ranging from 0.56 for PZ and AZ to 0.70 for SPR). In the VGC analysis, image quality ratings were significantly better for group 1 than group 2 scans for all regions (AUC_VGC ranging from 0.56 for CZ to 0.62). However, disagreement was limited to a score 4 (excellent)-to-score 3 (good) IQ transition; apart from a single case in PZ, both the observers scored the IQ at follow-up as 2 (sufficient) starting from a score 4 (excellent).

CONCLUSION

Dose reduction achieved in the follow-up CT scans, although a lower IQ still allows a good diagnostic confidence.

Comparison of full-iodine conventional CT and half-iodine virtual monochromatic imaging: advantages and disadvantages

PURPOSE

To compare image quality of abdominal arteries between full-iodine-dose conventional CT and half-iodine-dose virtual monochromatic imaging (VMI).

MATERIALS AND METHODS

We retrospectively evaluated images of 21 patients (10 men, 11 women; mean age, 73.9 years) who underwent both full-iodine (600 mg/kg) conventional CT and half-iodine (300 mg/kg) VMI. For each patient, we measured and compared CT attenuation and the contrast-to-noise ratio (CNR) of the aorta, celiac artery, and superior mesenteric artery (SMA). We also compared CT dose index (CTDI). Two board-certified diagnostic radiologists evaluated visualisation of the main trunks and branches of the celiac artery and SMA in maximum-intensity-projection images. We evaluated spatial resolution of the two scans using an acrylic phantom.

RESULTS

The two scans demonstrated no significant difference in CT attenuation of the aorta, celiac artery, and SMA, but CNRs of the aorta and celiac artery were significantly higher in VMI (p = 0.011 and 0.030, respectively). CTDI was significantly higher in VMI (p = 0.024). There was no significant difference in visualisation of the main trunk of the celiac artery and SMA, but visualisation of the gastroduodenal artery, pancreatic arcade, branch of the SMA, marginal arteries, and vasa recta was significantly better in the conventional scan (p < 0.001). The calculated modular transfer function (MTF) suggested decreased spatial resolution of the half-iodine VMI.

CONCLUSION

Large-vessel depiction and CNRs were comparable between full-iodine conventional CT and half-iodine VMI images, but VMI did not permit clear visualisation of small arteries and required a larger radiation dose.

KEY POINTS

・Reducing the dose of iodine contrast medium is essential for chronic kidney disease patients to prevent contrast-induced nephropathy. ・In virtual monochromatic images at low keV, contrast of relatively large vessels is maintained even with reduced iodine load, but visibility of small vessels is impaired with decreased spatial resolution. ・We should be aware about the advantages and disadvantages associated with virtual monochromatic imaging with reduced iodine dose.

Single-energy metal artifact reduction technique for reducing metallic coil artifacts on post-interventional cerebral CT and CT angiography

PURPOSE

To evaluate the effects of the single-energy metal artifact reduction (SEMAR) algorithm on image quality of cerebral CT and CT angiography (CTA) for patients who underwent intracranial aneurysm coiling.

METHODS

Twenty patients underwent cerebral CT and CTA using a 320-detector row CT after intracranial aneurysm coiling. Images with and without application of the SEMAR algorithm (SEMAR CT and standard CT images, respectively) were reconstructed for each patient. The images were qualitatively assessed by two independent radiologists in a blinded manner for the depiction of anatomical structures around the coil, delineation of the arteries around the coil, and the depiction of the status of coiled aneurysms. Artifact strength was quantitatively assessed by measuring the standard deviation of attenuation values around the coil.

RESULTS

The strength of artifacts measured in SEMAR CT images was significantly lower than that in standard CT images (25.7 ± 10.2 H.U. vs. 80.4 ± 67.2 H.U., p < 0.01, Student's paired t test). SEMAR CT images were significantly improved compared with standard CT images in the depiction of anatomical structures around the coil (p < 0.01, the sign test), delineation of the arteries around the coil (p < 0.01), and the depiction of the status of coiled aneurysms (p < 0.01).

CONCLUSION

The SEMAR algorithm significantly reduces metal artifacts from intracranial aneurysm coiling and improves visualization of anatomical structures and arteries around the coil, and depiction of the status of coiled aneurysms on post-interventional cerebral CT.