Diffuse lung disease: CT of the chest with adaptive statistical iterative reconstruction technique

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.

Evaluation of ultralow-dose computed tomography on detection of pulmonary nodules in overweight or obese adult patients

Purpose

To evaluate the accuracy of pulmonary nodule (PN) detection in overweight or obese adult patients using ultralow‐dose computed tomography (ULDCT) with tin filtration at 100 kV and advanced model‐based iterative reconstruction (ADMIRE).

Methods

Eighty‐one patients with body mass indices of ≥25 kg/m² were enrolled. All patients underwent low‐dose chest CT (LDCT), followed by ULDCT. Two radiologists experienced in LDCT established the standard of reference (SOR) for PNs. The number, type, size, and location of PNs were identified in the SOR. Effective dose, objective image quality (IQ), and subjective IQ based on two radiologists’ scores were compared between ULDCT and LDCT. The detection performances of radiologists based on ULDCT were calculated according to the nodule analyses. Logistic regression was used to test for independent predictors of PN detection sensitivity.

Results

Both the effective dose and objective IQ were lower for ULDCT than for LDCT (both p < 0.001). Both radiologists rated the subjective IQ of the overall IQ on ULDCT to be diagnostically sufficient. In total, 234 nodules (mean diameter, 3.4 ± 1.9 mm) were classified into 32 subsolid, 149 solid, and 53 calcified nodules according to the SOR. The overall sensitivity of ULDCT for nodule detection was 93.6%. Based on multivariate analyses, the nodule types (p = 0.015) and sizes (p = 0.013) were independent predictors of nodule detection.

Conclusions

Compared with LDCT, ULDCT with tin filtration at 100 kV and ADMIRE could significantly reduce the radiation dose in overweight or obese patients while maintaining good sensitivity for nodule detection.

Impact of dose reduction and iterative reconstruction algorithm on the detectability of pulmonary nodules by artificial intelligence

PURPOSE

The purpose of this study was to assess whether the performances of an automated software for lung nodule detection with computed tomography (CT) are affected by radiation dose and the use of iterative reconstruction algorithm.

MATERIALS AND METHODS

A chest phantom (Multipurpose Chest Phantom N1; Kyoto Kagaku Co. Ltd, Kyoto, Japan) with 15 pulmonary nodules was scanned with a total of five CT protocol settings with up to 20-fold dose reduction. All CT examinations were reconstructed with iterative reconstruction algorithms ADMIRE 3 and ADMIRE 5 and were then analyzed for the presence of pulmonary nodules with a fully automated computer aided detection software system (InferRead^TM CT Lung, Infervision), which is based on deep neural networks.

RESULTS

The sensitivity of fully automated pulmonary nodule detection for ground-glass nodules at standard dose CT was greater (70.0%; 14/20; 95% CI: 51.6-88.4%) than at 10-fold and 20-fold dose reduction (30.0%; 6/20; 95% CI: 0.0%-62.5%). There were less false positive findings when ADMIRE 5 reconstruction was used (4.0 ± 2.8 [SD]; range: 2-6) instead of ADMIRE 3 reconstruction (25.0 ± 15.6 [SD]; range: 14-36). There was no difference in the sensitivity of detection of solid and subsolid nodules between standard dose (100%; 95% CI: 100-100%) and 10- and 20-fold reduced dose CT (92.5%; 95% CI: 83.8-100.0%). Image noise was significantly greater with ADMIRE 3 (81 ± 2 [SD] [range: 79-84]; 104 ± 3 [SD] [range: 101-107]; 114 ± 5 [SD] [range: 110-119]; 193 ± 10 [SD] [range: 183-203]; 220 ± 16 [SD] [range: 210-238]) compared to ADMIRE 5 (44 ± 2 [SD] [range: 42-46]; 60 ± 2 [SD] [range: 57-61]; 66 ± 1 [SD] [range: 65-67]; 103 ± 4 [SD] [range: 98-106]; 110 ± 1 [SD] [range: 109-111]), respectively in each of the five CT protocols.

CONCLUSION

This phantom study suggests that dose reduction and iterative reconstruction settings have an impact on detectability of pulmonary nodules by artificial intelligence software and we therefore encourage adaption of dose levels and reconstruction methods prior to widespread implementation of fully automatic nodule detection software for lung cancer screening purposes.

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.

Prospective Study of Low- and Standard-dose Chest CT for Pulmonary Nodule Detection: A Comparison of Image Quality, Size Measurements and Radiation Exposure

OBJECTIVE

To comprehensively and accurately analyze the out-performance of low-dose chest CT (LDCT) vs. standard-dose CT (SDCT).

METHODS

The image quality, size measurements and radiation exposure for LDCT and SDCT protocols were evaluated. A total of 117 patients with extra-thoracic malignancies were prospectively enrolled for non-enhanced CT scanning using LDCT and SDCT protocols. Three experienced radiologists evaluated subjective image quality independently using a 5-point score system. Nodule detection efficiency was compared between LDCT and SDCT based on nodule characteristics (size and volume). Radiation metrics and organ doses were analyzed using Radimetrics.

RESULTS

The images acquired with the LDCT protocol yielded comparable quality to those acquired with the SDCT protocol. The sensitivity of LDCT for the detection of pulmonary nodules (n=650) was lower than that of SDCT (n=660). There was no significant difference in the diameter and volume of pulmonary nodules between LDCT and SDCT (for BMI <22 kg/m², 4.37 vs. 4.46 mm, and 43.66 vs. 46.36 mm³; for BMI ≥22 kg/m², 4.3 vs. 4.41 mm, and 41.66 vs. 44.86 mm³) (P>0.05). The individualized volume CT dose index (CTDI_vol), the size specific dose estimate and effective dose were significantly reduced in the LDCT group compared with the SDCT group (all P<0.0001). This was especially true for dose-sensitive organs such as the lung (for BMI <22 kg/m², 2.62 vs. 12.54 mSV, and for BMI ≥22 kg/m², 1.62 vs. 9.79 mSV) and the breast (for BMI <22 kg/m², 2.52 vs. 10.93 mSV, and for BMI ≥22 kg/m², 1.53 vs. 9.01 mSV) (P<0.0001).

CONCLUSION

These results suggest that with the increases in image noise, LDCT and SDCT exhibited a comparable image quality and sensitivity. The LDCT protocol for chest scans may reduce radiation exposure by about 80% compared to the SDCT protocol.

Impact of Morphotype on Image Quality and Diagnostic Performance of Ultra-Low-Dose Chest CT

Objectives: The image quality of an Ultra-Low-Dose (ULD) chest CT depends on the patient’s morphotype. We hypothesize that there is a threshold beyond which the diagnostic performance of a ULD chest CT is too degraded. This work assesses the influence of morphotype (Body Mass Index BMI, Maximum Transverse Chest Diameter MTCD and gender) on image quality and the diagnostic performance of a ULD chest CT. Methods: A total of 170 patients from three prior prospective monocentric studies were retrospectively included. Renewal of consent was waived by our IRB. All the patients underwent two consecutive unenhanced chest CT acquisitions with a full dose (120 kV, automated tube current modulation) and a ULD (135 kV, fixed tube current at 10 mA). Image noise, subjective image quality and diagnostic performance for nine predefined lung parenchyma lesions were assessed by two independent readers, and correlations with the patient’s morphotype were sought. Results: The mean BMI was 26.6 ± 5.3; 20.6% of patients had a BMI > 30. There was a statistically significant negative correlation of the BMI with the image quality (ρ = −0.32; IC95% = (−0.468; −0.18)). The per-patient diagnostic performance of ULD was sensitivity, 77%; specificity, 99%; PPV, 94% and NPV, 65%. There was no statistically significant influence of the BMI, the MTCD nor the gender on the per-patient and per-lesion diagnostic performance of a ULD chest CT, apart from a significant negative correlation for the detection of emphysema. Conclusions: Despite a negative correlation between the BMI and the image quality of a ULD chest CT, we did not find a correlation between the BMI and the diagnostic performance of the examination, suggesting a possible use of the ULD protocol in obese patients.

Ultra-low-dose thoracic CT with model-based iterative reconstruction (MBIR) in cystic fibrosis patients undergoing treatment with cystic fibrosis transmembrane conductance regulators (CFTR)

AIM

To assess the utility of a volumetric low-dose computed tomography (CT) thorax (LDCTT) protocol at a dose equivalent to a posteroanterior (PA) and lateral chest radiograph for surveillance of cystic fibrosis (CF) patients.

MATERIALS AND METHODS

A prospective study was undertaken of 19 adult patients with CF that proceeded to LDCTT at 12 and 24 months following initiation of ivacaftor. A previously validated seven-section, low-dose axial CT protocol was used for the 12-month study. A volumetric LDCTT protocol was developed for the 24-month study and reconstructed with hybrid iterative reconstruction (LD-ASIR) and pure iterative reconstruction (model-based IR [LD-MBIR]). Radiation dose was recorded for each scan. Image quality was assessed quantitatively and qualitatively, and disease severity was assessed using a modified Bhalla score. Statistical analysis was performed and p-values of <0.05 were considered statistically significant.

RESULTS

Volumetric LD-MBIR studies were acquired at a lower radiation dose than the seven-section studies (0.08 ± 0.01 versus 0.10 ± 0.02 mSv; p=0.02). LD-MBIR and seven-section ASIR images had significantly lower levels of image noise compared with LD-ASIR images (p<0.0001). Diagnostic acceptability scores and depiction of bronchovascular structures were found to be acceptable for axial and coronal LD-MBIR images. LD-MBIR images were superior to LD-ASIR images for all qualitative parameters assessed (p<0.0001). No significant change was observed in mean Bhalla score between 1-year and 2-year studies (p=0.84).

CONCLUSIONS

The use of a volumetric LDCTT protocol (reconstructed with pure IR) enabled acquisition of diagnostic quality CT images, which were considered extremely useful for surveillance of CF patients, at a dose equivalent to a PA and lateral chest radiograph.

Ultra-low-dose CT reconstructed with ASiR-V using SmartmA for pulmonary nodule detection and Lung-RADS classifications compared with low-dose CT

AIM

To evaluate the accuracy of ultra-low-dose computed tomography (ULDCT) with ASiR-V using a noise index (SmartmA) for pulmonary nodule detection and Lung CT Screening Reporting And Data System (Lung-RADS) classifications compared with low-dose CT (LDCT).

MATERIALS AND METHODS

Two-hundred and ten patients referred for lung cancer screening underwent conventional chest LDCT (0.80 ± 0.28 mSv) followed immediately by ULDCT (0.16 ± 0.03 mSv). ULDCT was scanned using 120 kV/SmartmA with a noise index of 28 HU and reconstructed with ASiR-V70%. The types and diameters of all nodules were recorded. The attenuation of pure ground-glass nodules (pGGNs) was measured on LDCT. All nodules were further classified using Lung-RADS. Sensitivities of nodule detection on ULDCT were analysed using LDCT as the reference standard. Logistic regression was used to establish a prediction model for the sensitivity of nodules.

RESULTS

LDCT revealed 362 nodules and the overall sensitivity on ULDCT was 90.1%. The sensitivity for solid nodules (SNs) of ≥1 mm diameter was 96.6% (228/236) and 100% (26/26) for SNs of ≥6 mm diameter. For pGGNs of ≥6 mm, the overall sensitivity was 93% (40/43) and 100% (29/29) for nodules with a attenuation value -700 HU or more. The agreement of Lung-RADS classification between two scans was good. On logistic regression, diameter was the only independent predictor for sensitivity of SNs (p<0.05). Diameter and attenuation value were predictors for pGGNs (p<0.05).

CONCLUSION

ULDCT with ASiR-V using SmartmA is suitable for lung-cancer screening in people with a BMI ≤35 kg/m² as it has a low radiation dose of 0.16 mSv, high sensitivity for nodule detection and good performance of Lung-RADS classifications.

The image quality of deep-learning image reconstruction of chest CT images on a mediastinal window setting

AIM

To assess the image quality of deep-learning image reconstruction (DLIR) of chest computed tomography (CT) images on a mediastinal window setting in comparison to an adaptive statistical iterative reconstruction (ASiR-V).

MATERIALS AND METHODS

Thirty-six patients were evaluated retrospectively. All patients underwent contrast-enhanced chest CT and thin-section images were reconstructed using filtered back projection (FBP); ASiR-V (60% and 100% blending setting); and DLIR (low, medium, and high settings). Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were evaluated objectively. Two independent radiologists evaluated ASiR-V 60% and DLIR subjectively, in comparison with FBP, on a five-point scale in terms of noise, streak artefact, lymph nodes, small vessels, and overall image quality on a mediastinal window setting (width 400 HU, level 60 HU). In addition, image texture of ASiR-Vs (60% and 100%) and DLIR-high was analysed subjectively.

RESULTS

Compared with ASiR-V 60%, DLIR-med and DLIR-high showed significantly less noise, higher SNR, and higher CNR (p<0.0001). DLIR-high and ASiR-V 100% were not significantly different regarding noise (p=0.2918) and CNR (p=0.0642). At a higher DLIR setting, noise was lower and SNR and CNR were higher (p<0.0001). DLIR-high showed the best subjective scores for noise, streak artefact, and overall image quality (p<0.0001). Compared with ASiR-V 60%, DLIR-med and DLIR-high scored worse in the assessment of small vessels (p<0.0001). The image texture of DLIR-high was significantly finer than that of ASIR-Vs (p<0.0001).

CONCLUSIONS

DLIR-high improved the objective parameters and subjective image quality by reducing noise and streak artefacts and providing finer image texture.

Health Care Monitoring and Treatment for Coronary Artery Diseases: Challenges and Issues

In-stent restenosis concerning the coronary artery refers to the blood clotting-caused re-narrowing of the blocked section of the artery, which is opened using a stent. The failure rate for stents is in the range of 10% to 15%, where they do not remain open, thereby leading to about 40% of the patients with stent implantations requiring repeat procedure within one year, despite increased risk factors and the administration of expensive medicines. Hence, today stent restenosis is a significant cause of deaths globally. Monitoring and treatment matter a lot when it comes to early diagnosis and treatment. A review of the present stent monitoring technology as well as the practical treatment for addressing stent restenosis was conducted. The problems and challenges associated with current stent monitoring technology were illustrated, along with its typical applications. Brief suggestions were given and the progress of stent implants was discussed. It was revealed that prime requisites are needed to achieve good quality implanted stent devices in terms of their size, reliability, etc. This review would positively prompt researchers to augment their efforts towards the expansion of healthcare systems. Lastly, the challenges and concerns associated with nurturing a healthcare system were deliberated with meaningful evaluations.

Chest CT screening in patients with overweight or obesity using spectral shaping at 150 kVp: compared with 120 kVp protocol and spectral shaping at 100 kVp protocol

PURPOSE

To evaluate the image quality (IQ) and the figure of merit (FoM) of chest CT screening in patients with overweight or obesity using a tin filter for spectral shaping at 150 kVp.

MATERIALS AND METHODS

Patients with overweight or obesity (N = 150, body mass index ≥ 26 kg/m²) with indications for chest CT screening were prospectively enrolled and randomly divided into three groups: 120 kVp group (standard radiation dose/tube voltage, 120 kVp/CT volume does index, 4.68 mGy); Sn100 kVp group (1/10th radiation dose level/100 kVp with a tin filter/0.47 mGy); Sn150 kVp group (1/2th radiation dose level/150 kVp with a tin filter/2.34 mGy). IQ and FoMs were evaluated and compared among the three groups.

RESULTS

Image noise, signal-to-noise ratios and subjective IQ scores were significantly higher in the Sn150 kVp group than those in the Sn100 kVp group (all p < 0.05), but were not significantly different with those in the 120 kVp group. FoMs in the Sn150 kVp group were significantly higher than those in the 120 kVp group (all p < 0.05), but showed no statistical difference with those in the Sn100 kVp group.

CONCLUSIONS

Compared with scanning at 120 kVp, chest CT screening performed at 150 kVp with spectral shaping substantially reduces the radiation dose in overweight and obese patients while maintaining IQ.

Chest CT in patients after lung transplantation: A retrospective analysis to evaluate impact on image quality and radiation dose using spectral filtration tin-filtered imaging

OBJECTIVES

The purpose of this study was to investigate the impact of a 150kV spectral filtration chest imaging protocol (Sn150kVp) combined with advanced modeled iterative reconstruction (ADMIRE) on radiation dose and image quality in patients after lung-transplantation.

METHODS

This study included 102 patients who had unenhanced chest-CT examinations available on both, a second-generation dual-source CT (DSCT) using standard protocol (100kVp, filtered-back-projection) and, on a third-generation DSCT using Sn150kVp protocol with ADMIRE. Signal-to-noise-ratio (SNR) was measured in 6 standardized regions. A 5-point Likert scale was used to evaluate subjective image quality. Radiation metrics were compared.

RESULTS

The mean time interval between the two acquisitions was 1.1±0.7 years. Mean-volume-CT-dose-index, dose-length-product and effective dose were significantly lower for Sn150kVp protocol (2.1±0.5mGy;72.6±16.9mGy*cm;1.3±0.3mSv) compared to 100kVp protocol (6.2±1.8mGy;203.6±55.6mGy*cm;3.7±1.0mSv) (p<0.001), equaling a 65% dose reduction. All studies were considered of diagnostic quality. SNR measured in lung tissue, air inside trachea, vertebral body and air outside the body was significantly higher in 100kVp protocol compared to Sn150kVp protocol (12.5±2.7vs.9.6±1.5;17.4±3.6vs.11.8±1.8;0.7±0.3vs.0.4±0.2;25.2±6.9vs.14.9±3.3;p<0.001). SNR measured in muscle tissue was significantly higher in Sn150kVp protocol (3.2±0.9vs.2.6±1.0;p<0.001). For SNR measured in descending aorta there was a trend towards higher values for Sn150kVp protocol (2.8±0.6 vs. 2.7±0.9;p = 0.3). Overall SNR was significantly higher in 100kVp protocol (5.0±4.0vs.4.0±4.0;p<0.001). On subjective analysis both protocols achieved a median Likert rating of 1 (25th-75th-percentile:1-1;p = 0.122). Interobserver agreement was good (intraclass correlation coefficient = 0.73).

CONCLUSIONS

Combined use of 150kVp tin-filtered chest CT protocol with ADMIRE allows for significant dose reduction while maintaining highly diagnostic image quality in the follow up after lung transplantation when compared to a standard chest CT protocol using filtered back projection.

Usefulness of dictionary learning-based processing for improving image quality of sub-millisievert low-dose chest CT: initial experience

PURPOSE

To develop a dictionary learning (DL)-based processing technique for improving the image quality of sub-millisievert chest computed tomography (CT).

MATERIALS AND METHODS

Standard-dose and sub-millisievert chest CT were acquired in 12 patients. Dictionaries including standard- and low-dose image patches were generated from the CT datasets. For each patient, DL-based processing was performed for low-dose CT using the dictionaries generated from the remaining 11 patients. This procedure was repeated for all 12 patients. Image quality of normal thoracic structures on the processed sub-millisievert CT images was assessed with a 5-point scale (5 = excellent, 1 = very poor). Lung lesion conspicuity was also assessed on a 5-point scale.

RESULTS

Image noise on sub-millisievert CT was significantly decreased with DL-based image processing (48.5 ± 13.7 HU vs 20.4 ± 7.9 HU, p = 0.0005). Image quality of lung structures was significantly improved with DL-based method (middle level of lung, 2.25 ± 0.75 vs 2.92 ± 0.79, p = 0.0078). Lung lesion conspicuity was also significantly improved with DL-based technique (solid nodules, 3.4 ± 0.6 vs 2.7 ± 0.6, p = 0.0273).

CONCLUSION

Image quality and lesion conspicuity on sub-millisievert chest CT images may be improved by DL-based post-processing.

A feasibility study of pulmonary nodule detection by ultralow-dose CT with adaptive statistical iterative reconstruction-V technique

PURPOSE

To evaluate the clinical value of ultralow-dose CT (ULDCT) with adaptive statistical iterative reconstruction-V (ASiR-V) in the detection of pulmonary nodules in a Chinese population.

METHOD

One hundred eighty-eight patients (16.41 ≤ BMI ≤ 29.87 kg/m²) with pulmonary nodules detected on low-dose chest CT (LDCT) underwent local ULDCT at the center of the chosen nodule with a scan length of 3 cm. LDCT was performed using the Assist kV (120/100 kV)/Smart mA mode and at 120 kV/2.8 mAs for ULDCT. After scanning, CT images were reconstructed with ASiR-V 50%. For both scans, nodule diameters were measured and reference standards were established for the presence and types of lung nodules found on LDCT. The sensitivity of ULDCT was compared against the standard, and logistic regression analysis was used to determine the independent predictors for nodule detection.

RESULTS

Compared with LDCT (0.93 ± 0.32 mSv), a 89.7% dose decrease was seen with ULDCT, for which the calculated effective dose was 0.096 ± 0.006 mSv (P < 0.001). LDCT showed 188 nodules, including 123 solid and 65 subsolid nodules. The overall sensitivity for nodule detection in ULDCT was 90.4% (170/188), and 98.2% (54/55) for nodules ≥ 6 mm. In multivariate analysis, nodule types and diameters were independent predictors of sensitivity (P < 0.05). However, patients' BMI had no effect on nodule detection (P > 0.05).

CONCLUSIONS

ULDCT can be used in the management of pulmonary nodules for people with BMI ≤ 30 kg/m² at 10% radiation dose of LDCT.

Volumetric assessment of solid pulmonary nodules on ultralow-dose CT: a phantom study

Background

To reduce the radiation exposure from chest computed tomography (CT), ultralow-dose CT (ULDCT) protocols performed at sub-millisievert levels were previously tested for the evaluation of pulmonary nodules (PNs). The purpose of our study was to investigate the effect of ULDCT and iterative image reconstruction on volumetric measurements of solid PNs.

Methods

CT datasets of an anthropomorphic chest phantom containing solid microspheres were obtained with a third-generation dual-source CT at standard dose, 1/8th, 1/20th and 1/70th of standard dose [CT volume dose index (CTDI_vol): 0.03-2.03 mGy]. Semi-automated volumetric measurements were performed on CT datasets reconstructed with filtered back projection (FBP) and advanced modelled iterative reconstruction (ADMIRE), at strength level 3 and 5. Absolute percentage error (APE) evaluated measurement accuracy related to the effective volume. Scan repetition differences were evaluated using Bland-Altman analysis. Two-way analysis of variance (ANOVA) assessed influence of different scan parameters on APE. Proportional differences (PDs) tested the effect of dose settings and reconstruction algorithms on volumetric measurements, as compared to the standard protocol (standard dose-FBP).

Results

Bland-Altman analysis revealed small mean interscan differences of APE with narrow limits of agreement (-0.1%±4.3% to -0.3%±3.8%). Dose settings (P<0.001), reconstruction algorithms (P<0.001), nodule diameters (P<0.001) and nodule density (P=0.011) had statistically significant influence on APE. Post-hoc Bonferroni tests showed slightly higher APE when scanning with 1/70th of standard dose [mean difference: 3.4%, 95% confidence interval (CI): 2.5-4.3%; P<0.001], and for image reconstruction with ADMIRE5 (mean difference: 1.8%, 95% CI: 1.0-2.5%; P<0.001). No significant differences for scanning with 1/20th of standard dose (P=0.42), and image reconstruction with ADMIRE3 (P=0.19) were found. Scanning with 1/70th of standard dose and image reconstruction with FBP showed the widest range of PDs (-16.8% to 23.4%) compared to standard dose-FBP.

Conclusions

Our phantom study showed no significant difference between nodule volume measurements on standard dose CT (CTDI_vol: 2 mGy) and ULDCT with 1/20th of standard dose (CTDI_vol: 0.10 mGy).

Vendor free basics of radiation dose reduction techniques for CT

Although radiation dose in computed tomography (CT) decreased and CT became safer examinations than before, CT is the most significant source of the medical radiation exposure. Knowledge about available radiation dose reduction methods in CT is essential. Substantial improvement occurred regarding tube current selection (automatic exposure control) and image production method (iterative reconstruction). Optimizing the tube potential selection is expected to contribute to further CT radiation dose reduction. This review article summarizes the principles of radiation dose reduction in CT, principal methods of radiation dose reduction, auxiliary measures of radiation dose saving and recent issues of low dose CT.

Iterative quality enhancement via residual-artifact learning networks for low-dose CT

Radiation exposure and the associated risk of cancer for patients in computed tomography (CT) scans have been major clinical concerns. The radiation exposure can be reduced effectively via lowering the x-ray tube current (mA). However, this strategy may lead to excessive noise and streak artifacts in the conventional filtered back-projection reconstructed images. To address this issue, some deep convolutional neural network (ConvNet) based approaches have been developed for low-dose CT imaging inspired by the recent development of machine learning. Nevertheless, some of the image textures reconstructed by the ConvNet could be corrupted by the severe streaks, especially in ultra-low-dose cases, which could be close to prostheses and hamper diagnosis. Therefore, in this work, we propose an iterative residual-artifact learning ConvNet (IRLNet) approach to improve the reconstruction performance over the ConvNet based approaches. Specifically, the proposed IRLNet estimates the high-frequency details within the noise and then removes them iteratively; after eliminating severe streaks in the low-dose CT images, the residual low-frequency details can be processed through the conventional network. Moreover, the proposed IRLNet scheme can be extended for robust handling of quantitative dual energy CT/cerebral perfusion CT imaging, and statistical iterative reconstruction. Real patient data are used to evaluate the proposed IRLNet, and the experimental results demonstrate that the proposed IRLNet approach outperforms the previous ConvNet based approaches in reducing the image noise and streak artifacts efficiently at the same time as preserving edge details well, suggesting that the proposed IRLNet approach can be used to improve the CT image quality, especially in ultra-low-dose cases.

A CONSORT-compliant prospective randomized controlled trial: radiation dose reducing in computed tomography using an additional lateral scout view combined with automatic tube current modulation: Phantom and patient study

BACKGROUND

Radiation exposure has been a hot point in research field of computed tomography (CT). Recently, automated tube current modulation (ATCM) has emerged as an important technique to reduce radiation exposure. Many studies have shown that the difference in scout view would affect modulation. This prospective randomized controlled study is aimed to investigate the impact of an additional lateral scout view on radiation dose and image quality in CT using ACTM.

METHODS

Combined with ATCM (Care Dose 4D) on multidetector CT, 2 thoracic phantom CT image series were acquired in which planning was conducted with either an anteroposterior (AP) or an AP-lateral scout view. Also, 410 patients underwent thoracic CT examinations using Care Dose 4D modulation and were randomized to either a scan planned with an AP-lateral scout or a single AP scout. Effects of the different scout views on applied effective milliampere seconds (mAs), volume CT dose index (CTDIvol) and dose-length-product (DLP) were analyzed. The quality of patient CT images was also assessed. Data were analyzed using independent t tests and linear correlation analysis.

RESULTS

Compared with AP groups, the mean CTDIvol (phantom, 0.89 ± 0.08 vs 1.36 ± 0.26 mGy, P < .001; in patients, 1.12 [0.96, 1.34] vs 2.16 [1.66, 2.64] mGy, P < .001) and DLP (in phantom, 26 [23.25, 28] vs 40 [34.25, 48] mGy×cm, P < .001; in patients, 41 [33, 41] vs 77 [60.5, 99.5] mGy×cm, P < .001) were significantly reduced by approximately 50% in AP-lateral scout view group. With the AP-lateral topogram, the radiation dose on different off-center positions was essentially equal (CTDIvol: 0.76-0.99 mGy; DLP: 22-28 mGy×cm effective dose: 0.31-0. 39 mSv). For image quality, contrast-to-noise ratio and signal-to-noise ratio values in the AP group were similar to those of AP-lateral scout view group.

CONCLUSION

AP combined with an additional lateral scout view using ACTM can significantly reduce the radiation dose without compromising image quality in chest screening CT.

Performance of Half-dose Chest Computed Tomography in Lung Malignancy Using an Iterative Reconstruction Technique

Objectives The purpose of this study was to evaluate the performance of half-dose chest CT using an iterative reconstruction technique in patients with lung malignancies. Methods The Dual-source CT scans were obtained and half-dose datasets were reconstructed with 5 different strengths in 38 adults with lung malignancies. Two radiologists graded subjective image quality; noise, contrast and sharpness at the central/peripheral lung, mediastinum and chest wall of the reconstructed half-dose images, compared with those of standard-dose images, using a three-point scale. A lesion assessment; lesion conspicuity and diagnostic confidence, was also performed. The quantitative image noises; contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were measured and compared with those of standard-dose images. Results The subjective image noise in the half-dose images was less than that of the standard-dose images. The contrast in strengths 2 to 5 was superior, the sharpness of the lung parenchyma in strengths 3 to 5 was inferior, and the CNR/SNR in all strengths were higher than those of standard-dose images ( P &lt; 0.05). The improvement of subjective image noise and contrast, the decrease in sharpness, were correlated with strength level ( P &lt; 0.05). The lesion conspicuity in half-dose images of strengths 4 and 5 was decreased. The diagnostic confidence of the half-dose images of all strengths was comparable to that of the standard-dose images ( P &lt; 0.05). Conclusions Half-dose chest CT images using an iterative reconstruction technique show decreased image noise, increased contrast, and diagnostic confidence comparable to standard-dose images. Images reconstructed with strength 2 and 3 appear to be the optimal choice in clinical practice.

Impact on Image Quality and Radiation Dose of Third-Generation Dual-Source Computed Tomography of the Coronary Arteries

The aim of this study was to assess the image quality (IQ) and radiation dose of third-generation dual-source computed tomography (CT) coronary angiography (cCTA) in comparison with 64-slice single-source CT. This retrospective study included 140 patients (73 men, mean age 62 ± 11 years) with low-to-intermediate probability of coronary artery disease who underwent either third-generation dual-source cCTA using prospectively electrocardiography-triggered high-pitch spiral acquisition (n = 70) (group 1) or retrospective electrocardiography-gated cCTA on a 64-slice CT system (n = 70) (group 2). Contrast-to-noise and signal-to-noise ratios were measured within the aorta and coronary arteries. Subjective IQ was assessed using a 5-point Likert scale. Effective dose was estimated using specific conversion factors. The contrast-to-noise ratio of group 1 was significantly higher than group 2 at all levels (all p <0.001). Signal-to-noise ratio of group 1 was also significantly higher than group 2 (p <0.05), except for the distal left circumflex artery. Subjective IQ for group 1 was rated significantly better than for group 2 (median score [25th to 75th percentile]: 1 [1 to 2] vs 2 [2 to 3]; p <0.001). The median effective dose was 1.55 mSv (1.09 to 1.88) in group 1 versus 12.29 mSv (11.63 to 14.36) in group 2 (p <0.001) which corresponds to a mean radiation dose reduction of 87.4%. In conclusion, implementation of third-generation dual-source CT system for cCTA leads to improved IQ with significant radiation dose savings.

Image quality evaluation for CARE kV technique combined with iterative reconstruction for chest computed tomography scanning

BACKGROUND

To investigate the radiation dose and image quality for iterative reconstruction combined with the CARE kV technique in chest computed tomography (CT) scanning for physical examination.

METHODS

A total of 130 patients who underwent chest CT scanning were randomly chosen and the quality reference value was set as 80 mAs. The scanning scheme was set and the patients were randomly divided into groups according to the scanning scheme. Sixty patients underwent a chest scan with 100 kV using the CARE kV technique and SAFIRE reconstruction (value=3) (experimental group) and the other 70 patients underwent chest scanning with 120 kV (control group). The mean CT value, image noise (SD), and signal-to-noise ratio (SNR) of the apex of the lung, the level of the descending aorta bifurcation of the trachea, and the middle area of the left atrium were measured. The image quality was assessed on a 5-point scale by two radiologists and results of the two groups were compared. The CT dose index of the volume (CTDIvol), dose length product (DLP), and effective dose (ED) were compared.

RESULTS

All the images for both groups satisfied the diagnosis requirement. There was no statistical difference in the image quality between the two methods (P > 0.05). The mean CT value of the apex of the lung, the level of the descending aorta bifurcation of the trachea, and the middle area of the left atrium were not significantly different for both groups (P > 0.05), while the image noise (SD) and the signal-to-noise ratio (SNR) of the apex of the lung, the level of the descending aorta bifurcation of the trachea, and the middle area of the left atrium were statistically different for both groups (P < 0.05). The CTDIvol was 3.29 ± 1.17 mGy for the experimental group and 5.30 ± 1.53 mGy for the control group. The DLP was 114.9 ± 43.73 mGy cm for the low-dose group and 167.6 ± 44.59 mGy cm for the control group. The ED was 1.61 ± 0.61 mSv for the low-dose group and 2.35 ± 0.62 mSv for the control group (P  < 0.05).

CONCLUSION

The CARE kV technique combined with iterative reconstruction for chest CT scanning for physical examination could reduce the radiation dosage and improve CT image quality, which has a potential clinical value for imaging the thorax.

Assessment of chest CT at CTDIvol less than 1 mGy with iterative reconstruction techniques

OBJECTIVE

To assess the image quality of chest CT reconstructed with image-based iterative reconstruction (SafeCT; MedicVision^®, Tirat Carmel, Israel), adaptive statistical iterative reconstruction (ASIR; GE Healthcare, Waukesha, WI) and model-based iterative reconstruction (MBIR; GE Healthcare, Waukesha, WI) techniques at CT dose index volume (CTDI_vol) <1 mGy.

METHODS

In an institutional review board-approved study, 25 patients gave written informed consent for acquisition of three reduced dose (0.25-, 0.4- and 0.8-mGy) chest CT after standard of care CT (8 mGy) on a 64-channel multidetector CT (MDCT) and reconstructed with SafeCT, ASIR and MBIR. Two board-certified thoracic radiologists evaluated images from the lowest to the highest dose of the reduced dose CT series and subsequently for standard of care CT.

RESULTS

Out of the 182 detected lesions, the missed lesions were 35 at 0.25, 24 at 0.4 and 9 at 0.8 mGy with SafeCT, ASIR and MBIR, respectively. The most missed lesions were non-calcified lung nodules (NCLNs) 25/112 (<5 mm) at 0.25, 18/112 (<5 mm) at 0.4 and 3/112 (<4 mm) at 0.8 mGy. There were 78%, 84% and 97% lung nodules detected at 0.25, 0.4 and 0.8 mGy, respectively regardless of iterative reconstruction techniques (IRTs), Most mediastinum structures were not sufficiently seen at 0.25-0.8 mGy.

CONCLUSION

NCLNs can be missed in chest CT at CTDI_vol of <1 mGy (0.25, 0.4 and 0.8 mGy) regardless of IRTs. The most lung nodules (97%) were detected at CTDI_vol of 0.8 mGy. The most mediastinum structures were not sufficiently seen at 0.25-0.8 mGy. Advances in knowledge: NCLNs can be missed regardless of IRTs in chest CT at CTDI_vol of <1 mGy. The performance of ASIR, SafeCT and MBIR was similar for lung nodule detection at 0.25, 0.4 and 0.8 mGy.

Comparison of image quality and visibility of normal and abnormal findings at submillisievert chest CT using filtered back projection, iterative model reconstruction (IMR) and iDose4™

OBJECTIVE

To compare both image quality and visibility of normal and abnormal findings at submillisievert chest CT (smSv-CT) using filtered back projection (FBP) and the two different iterative reconstruction (IR) techniques iterative model reconstruction (IMR) and iDose⁴™.

MATERIALS AND METHODS

This institutional review board approved study was based on retrospective interpretation of clinically indicated acquired data. The requirement to obtain informed consent was waived. 81 patients with suspected pneumonia underwent smSv-CT (Brilliance iCT, Philips Healthcare; mean effective dose: 0.86±0.2mSv). Data were reconstructed using FBP and two different IR techniques iDose⁴™ and IMR (Philips Healthcare) at various iteration levels. Objective image noise (OIN) was measured. Two experienced readers independently assessed all images for image noise, image appearance and visibility of normal anatomic and abnormal findings. A random intercept model was used for statistical analysis.

RESULTS

Compared to FBP and iDose⁴™, IMR reduced OIN up to 88% and 72%, respectively (p<0.001). A mild blotchy image appearance was seen in IMR images, affecting diagnostic confidence. iDose⁴™ images provided satisfactory to good image quality for visibility of normal and abnormal findings and were superior to FBP (p<0.001). IMR images were significantly inferior for visibility of normal structures compared to iDose⁴™, while being superior for visibility of abnormal findings except for reticular pattern (p<0.001).

CONCLUSION

IMR results for visibility of normal and abnormal lung findings are heterogeneous, indicating that IMR may not represent a priority technique for clinical routine. iDose⁴™ represents a suitable method for evaluation of lung tissue at submillisievert chest CT.

High-Resolution Computed Tomography Examinations for Chronic Suppurative Lung Disease in Early Childhood: Radiation Exposure and Image Quality Evaluations with Iterative Reconstruction Algorithm Use

Purpose

High radiosensitivity of children undergoing repetitive computed tomography examinations necessitates the use of iterative reconstruction algorithms in order to achieve a significant radiation dose reduction. The goal of this study is to compare the iDose iterative reconstruction algorithm with filtered backprojection in terms of radiation exposure and image quality in 33 chest high-resolution computed tomography examinations performed in young children with chronic bronchitis.

Methods

Fourteen patients were scanned using the filtered backprojection protocol while 19 patients using the iDose protocol and reduced milliampere-seconds, both on a 64-detector row computed tomography scanner. The iDose group images were reconstructed with different iDose levels (2, 4, and 6). Radiation exposure quantities were estimated, while subjective and objective image qualities were evaluated. Unpaired t tests were used for data statistical analysis.

Results

The iDose application allowed significant effective dose reduction (about 80%). Subjective image quality evaluation showed satisfactory results even with iDose level 2, whereas it approached excellent image with iDose level 6. Subjective image noise was comparable between the 2 groups with the use of iDose level 4, while objective noise was comparable between filtered backprojection and iterative reconstruction level 6 images.

Conclusions

The iDose algorithm use in pediatric chest high-resolution computed tomography reduces radiation exposure without compromising image quality. Further evaluation with iterative reconstruction algorithms is needed in order to establish high-resolution computed tomography as the gold standard low-dose method for children suffering from chronic lung diseases.

Comparison of the diagnostic accuracy of FBP, ASiR, and MBIR reconstruction during CT angiography in the evaluation of a vessel phantom with calcified stenosis in a distal superficial femoral artery in a cadaver extremity

PURPOSE

To investigate whether adaptive statistical iterative reconstruction (ASiR) or model-based iterative reconstruction (MBIR) improves the diagnostic performance of computed tomography angiography (CTA) for small-vessel calcified lesions relative to filtered back projection (FBP) using cadaver extremities and a calcified stenosis phantom.

METHODS

A cadaver was used in accordance with our institutional regulations, and a calcified stenosis phantom simulating 4 grades of stenosis was prepared. The phantom was inserted within the distal superficial femoral artery of the cadaver leg. Ten CT images per reconstruction type and stenosis grade were acquired using a 64-slice multidetector-row CTA.As an objective measurement, the first and second derivatives of the CT value function profiles were calculated. As a subjective measurement, 2 blinded reviewers measured the stenosis ratio using a quantitative scale. The Wilcoxon rank-sum test was used to evaluate the data.

RESULTS

Objective measurements of both 25% and 50% stenosis differed significantly (P < 0.01) between MBIR (25/50%: 25.80/50.30 ± 3.88/3.86%) and FBP (25/50%: 35.60/83.80 ± 3.44/26.10%), whereas significant differences were not observed between ASiR and FBP.Reviewer 2's subjective measurements of 25% stenosis differed significantly (P < 0.01) between MBIR (35.13 ± 3.25%) and ASiR (40.89 ± 3.14%), and the measurements of 50% stenosis differed significantly (P < 0.01) between MBIR (reviewers 1/2, 62.36/54.78 ± 2.78/4.96%) and FBP (reviewers 1/2, 62.36/74.84 ± 2.78/18.10%). Significant differences in the subjective measurements were not observed between ASiR and FBP.

CONCLUSION

MBIR improves the diagnostic performance of CTA for small-vessel calcified lesions relative to FBP.

Adaptive iterative dose reduction 3D (AIDR 3D) vs. filtered back projection: radiation dose reduction capabilities of wide volume and helical scanning techniques on area-detector CT in a chest phantom study

BACKGROUND

Computed tomography (CT) has important roles for lung cancer screening, and therefore radiation dose reduction by using iterative reconstruction technique and scanning methods receive widespread attention.

PURPOSE

To evaluate the effect of two reconstruction techniques (filtered back projection [FBP] and adaptive iterative dose reduction using three-dimensional processing [AIDR 3D]) and two acquisition techniques (wide-volume scan [WVS] and helical scan as 64-detector-row CT [64HS]) on the lung nodule identifications of using a chest phantom.

MATERIAL AND METHODS

A chest CT phantom including lung nodules was scanned using WVS and 64HS at nine different tube currents (TCs; range, 270-10 mA). All CT datasets were reconstructed with AIDR 3D and FBP. Standard deviation (SD) measurements by region of interest placement and qualitative nodule identifications were statistically compared. 64HS and WVS were evaluated separately, and FBP images acquired with 270 mA was defined as the standard reference.

RESULTS

SDs of all datasets with AIDR 3D showed no significant differences (P > 0.05) with standard reference. When comparing nodule identifications, area under the curve on WVS with AIDR 3D with TC <30 mA, on 64HS with AIDR 3D with TC <40 mA, and on reconstructions with FBP and each scan method with TC <60 mA was significantly lower than with standard reference (P < 0.05). With the same TC and reconstruction, SDs and nodule identifications of WVS were not significantly different from 64HS (P > 0.05).

CONCLUSION

In term of SD of lung parenchyma and nodule identification, AIDR 3D can achieve more radiation dose reduction than FBP and there is no significant different between WVS and 64HS.

A qualitative and quantitative analysis of radiation dose and image quality of computed tomography images using adaptive statistical iterative reconstruction

Image quality is a key issue in radiology, particularly in a clinical setting where it is important to achieve accurate diagnoses while minimizing radiation dose. Some computed tomography (CT) manufacturers have introduced algorithms that claim significant dose reduction. In this study, we assessed CT image quality produced by two reconstruction algorithms provided with GE Healthcare's Discovery 690 Elite positron emission tomography (PET) CT scanner. Image quality was measured for images obtained at various doses with both conventional filtered back‐projection (FBP) and adaptive statistical iterative reconstruction (ASIR) algorithms. A standard CT dose index (CTDI) phantom and a pencil ionization chamber were used to measure the CT dose at 120 kVp and an exposure of 260 mAs. Image quality was assessed using two phantoms. CT images of both phantoms were acquired at tube voltage (kV) of 120 with exposures ranging from 25 mAs to 400 mAs. Images were reconstructed using FBP and ASIR ranging from 10% to 100%, then analyzed for noise, low‐contrast detectability, contrast‐to‐noise ratio (CNR), and modulation transfer function (MTF). Noise was 4.6 HU in water phantom images acquired at 260 mAs/FBP 120 kV and 130 mAs/50% ASIR 120 kV. The large objects (frequency<7 lp/cm) retained fairly acceptable image quality at 130 mAs/50% ASIR, compared to 260 mAs/FBP. The application of ASIR for small objects (frequency>7 lp/cm) showed poor visibility compared to FBP at 260 mAs and even worse for images acquired at less than 130 mAs. ASIR blending more than 50% at low dose tends to reduce contrast of small objects (frequency>7 lp/cm). We concluded that dose reduction and ASIR should be applied with close attention if the objects to be detected or diagnosed are small (frequency>7 lp/cm). Further investigations are required to correlate the small objects (frequency>7 lp/cm) to patient anatomy and clinical diagnosis.

PACS number(s): 87.57.‐s, 87.57.C, 87.57.cf, 87.57.cj, 87.57.cm, 87.57.cp, 87.57.N, 87.57.nf, 87.57.np, 87.57.nt, 87.57.Q, 87.59.‐e, 87.59.B

Emphysema Quantification Using Ultralow-Dose CT With Iterative Reconstruction and Filtered Back Projection

OBJECTIVE

The purpose of this study was to evaluate agreement between standard-dose CT (SDCT) and ultralow-dose CT (ULDCT) findings with respect to emphysema quantification. ULDCT images were reconstructed with and without iterative reconstruction (IR). Adaptive iterative dose reduction with 3D processing was used for IR.

MATERIALS AND METHODS

Fifty patients who underwent SDCT and ULDCT were included. The tube current for SDCT was 250 mA, and that for ULDCT was 10 mA. SDCT, ULDCT without IR, and ULDCT with IR were used for emphysema quantification. The low-attenuation volume percentage (LAV%) in the lungs at four thresholds (-970, -950, -930, and -910 HU), mean lung attenuation, and total lung volume were computed. Concordance correlation coefficients (CCC) were used to assess the agreement of emphysema quantification between SDCT and ULDCT.

RESULTS

The LAV% CCC values were 0.310-0.789 between SDCT and ULDCT without IR and 0.934-0.966 between SDCT and ULDCT with IR. The agreement of LAV% improved when IR was used for ULDCT. The mean lung attenuation CCC value between SDCT and ULDCT without IR was substantial (0.957), whereas that between SDCT and ULDCT with IR was poor (0.890). The total lung volume CCC values were substantial (0.982 with IR, 0.983 without IR).

CONCLUSION

ULDCT with and without IR can substitute for SDCT in emphysema quantification.

Radiation dose reduction in CT with adaptive statistical iterative reconstruction (ASIR) for patients with bronchial carcinoma and intrapulmonary metastases

AIM

To compare the radiation dose and image quality of 64-row chest computed tomography (CT) in patients with bronchial carcinoma or intrapulmonary metastases using full-dose CT reconstructed with filtered back projection (FBP) at baseline and reduced dose with 40% adaptive statistical iterative reconstruction (ASIR) at follow-up.

MATERIALS AND METHODS

The chest CT images of patients who underwent FBP and ASIR studies were reviewed. Dose-length products (DLP), effective dose, and size-specific dose estimates (SSDEs) were obtained. Image quality was analysed quantitatively by signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) measurement. In addition, image quality was assessed by two blinded radiologists evaluating images for noise, contrast, artefacts, visibility of small structures, and diagnostic acceptability using a five-point scale.

RESULTS

The ASIR studies showed 36% reduction in effective dose compared with the FBP studies. The qualitative and quantitative image quality was good to excellent in both protocols, without significant differences. There were also no significant differences for SNR except for the SNR of lung surrounding the tumour (FBP: 35±17, ASIR: 39±22).

DISCUSSION

A protocol with 40% ASIR can provide approximately 36% dose reduction in chest CT of patients with bronchial carcinoma or intrapulmonary metastases while maintaining excellent image quality.

CT Imaging of Interstitial Lung Diseases

Until today, computed tomography (CT) is the most important and valuable radiological modality to detect, analyze, and diagnose diffuse interstitial lung diseases (DILD), based on the unsurpassed morphological detail provided by high-resolution CT technique.

In the past decade, there has been a shift from an isolated histopathological diagnosis to a multidisciplinary acquired diagnosis consensus that is nowadays regarded to provide the highest level of diagnostic accuracy in patients with diffuse interstitial lung diseases. The 2002 ATS/ERS statement on classification of idiopathic interstitial pneumonias assigned a central role to high-resolution CT (HRCT) in the diagnostic workup of idiopathic interstitial pneumonias (ATS/ERS consensus classification 2002). The more recent 2013 ERS/ATS statement reinforced that combined clinical data (presentation, exposures, smoking status, associated diseases, lung function, and laboratory findings) and radiological findings are essential for a multidisciplinary diagnosis (Travis et al., Am J Respir Crit Care Med 188(6):733–748, 2013).

The traditional HRCT consisted of discontinuous 1 mm high-resolution axial slices. The primary focus was on visual pattern analysis demanding for the highest possible spatial resolution. Because of the intrinsic high structural contrast of the lung, it has been possible to substantially reduce dose without losing diagnostic information. This development has been supported by new detection and reconstruction techniques. Not only detection of subtle disease and visual comparison of disease stage but also disease classification and quantification nowadays take advantage of continuous volumetric data acquisition provided by multidetector row (MD) CT technique. The following book chapter will focus on acquisition technique with special emphasis on dose and reconstruction, advantages, and new diagnostic options of volumetric MDCT technique for interstitial lung diseases. Based on evidence from the literature, certain diseases will be covered more specifically, but it has to be noted that for the pattern analysis of the various interstitial lung diseases, the plethora of other publications and books is recommended.

Determination of optimal imaging settings for urolithiasis CT using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR): a physical human phantom study

OBJECTIVE

The purpose of this study was to compare CT image quality for evaluating urolithiasis using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR) according to various scan parameters and radiation doses.

METHODS

A 5 × 5 × 5 mm(3) uric acid stone was placed in a physical human phantom at the level of the pelvis. 3 tube voltages (120, 100 and 80 kV) and 4 current-time products (100, 70, 30 and 15 mAs) were implemented in 12 scans. Each scan was reconstructed with FBP, statistical IR (Levels 5-7) and knowledge-based IMR (soft-tissue Levels 1-3). The radiation dose, objective image quality and signal-to-noise ratio (SNR) were evaluated, and subjective assessments were performed.

RESULTS

The effective doses ranged from 0.095 to 2.621 mSv. Knowledge-based IMR showed better objective image noise and SNR than did FBP and statistical IR. The subjective image noise of FBP was worse than that of statistical IR and knowledge-based IMR. The subjective assessment scores deteriorated after a break point of 100 kV and 30 mAs.

CONCLUSION

At the setting of 100 kV and 30 mAs, the radiation dose can be decreased by approximately 84% while keeping the subjective image assessment.

ADVANCES IN KNOWLEDGE

Patients with urolithiasis can be evaluated with ultralow-dose non-enhanced CT using a knowledge-based IMR algorithm at a substantially reduced radiation dose with the imaging quality preserved, thereby minimizing the risks of radiation exposure while providing clinically relevant diagnostic benefits for patients.

Hybrid Type iterative reconstruction method vs. filter back projection method: Capability for radiation dose reduction and perfusion assessment on dynamic first-pass contrast-enhanced perfusion chest area-detector CT

PURPOSE

To directly compare the capability of hybrid-type iterative reconstruction (i.e., adaptive iterative dose reduction using 3D processing: AIDR 3D) and filter back projection (FBP) for radiation dose reduction during dynamic contrast-enhanced (CE-) perfusion area-detector CT (ADCT) for lung and nodule perfusion assessment.

MATERIALS AND METHODS

Thirty-six patients with lung cancers who underwent perfusion ADCT (SD-ADCT) at 120 mA and were enrolled in this study. ADCT data at 80 mA (reduced-dose ADCT: RD-ADCT), 60 mA (low-dose ADCT: LD-ADCT) and 40 mA (very low-dose ADCT: VLD-ADCT) were computationally simulated using SD-ADCT data, and reconstructed with and without AIDR 3D. Image noise and lung and nodule perfusion parameters were evaluated using ROI measurements. To determine the utility of AIDR 3D for dose reduction, image noise was compared between each protocol with and without AIDR 3D by means of the t-test. Correlations and limits of agreement for parameters obtained with SD-ADCT and other protocols were also evaluated.

RESULTS

Image noise of all protocols with AIDR 3D was significantly lower than that of LD-ADCT and VLD-ADCT without AIDR 3D (p<0.05). Significant correlations for image noise between SD-ADCT and all protocols with AIDR 3D (0.45 ≤ r ≤ 0.99, p<0.0001) were equal to or better than that without AIDR 3D (0.28 ≤ r ≤ 0.99, p<0.0001). The limits of agreement for perfusion parameters with AIDR 3D were smaller than those without AIDR 3D for each tube current.

CONCLUSION

AIDR 3D is more effective than FBP for dose reduction of perfusion ADCT while maintaining image quality and reducing measurement errors.

Adaptive Statistical Iterative Reconstruction-Applied Ultra-Low-Dose CT with Radiography-Comparable Radiation Dose: Usefulness for Lung Nodule Detection

Objective

To assess the performance of adaptive statistical iterative reconstruction (ASIR)-applied ultra-low-dose CT (ULDCT) in detecting small lung nodules.

Materials and Methods

Thirty patients underwent both ULDCT and standard dose CT (SCT). After determining the reference standard nodules, five observers, blinded to the reference standard reading results, independently evaluated SCT and both subsets of ASIR- and filtered back projection (FBP)-driven ULDCT images. Data assessed by observers were compared statistically.

Results

Converted effective doses in SCT and ULDCT were 2.81 ± 0.92 and 0.17 ± 0.02 mSv, respectively. A total of 114 lung nodules were detected on SCT as a standard reference. There was no statistically significant difference in sensitivity between ASIR-driven ULDCT and SCT for three out of the five observers (p = 0.678, 0.735, < 0.01, 0.038, and < 0.868 for observers 1, 2, 3, 4, and 5, respectively). The sensitivity of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT in three out of the five observers (p < 0.01 for three observers, and p = 0.064 and 0.146 for two observers). In jackknife alternative free-response receiver operating characteristic analysis, the mean values of figure-of-merit (FOM) for FBP, ASIR-driven ULDCT, and SCT were 0.682, 0.772, and 0.821, respectively, and there were no significant differences in FOM values between ASIR-driven ULDCT and SCT (p = 0.11), but the FOM value of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT and SCT (p = 0.01 and 0.00).

Conclusion

Adaptive statistical iterative reconstruction-driven ULDCT delivering a radiation dose of only 0.17 mSv offers acceptable sensitivity in nodule detection compared with SCT and has better performance than FBP-driven ULDCT.

Ultra-Low-Dose CT of the Thorax Using Iterative Reconstruction: Evaluation of Image Quality and Radiation Dose Reduction

OBJECTIVE

The purpose of this study is to assess the image quality and radiation dose reduction of ultra-low-dose CT using sinogram-affirmed iterative reconstruction (SAFIRE).

SUBJECTS AND METHODS

This prospective study enrolled 25 patients who underwent three consecutive unenhanced CT scans including low-dose CT (120 kVp and 30 mAs) and two ultra-low-dose CT protocols (protocol A, 100 kVp and 20 mAs; protocol B, 80 kVp and 30 mAs) with image reconstruction using SAFIRE. The image quality and radiation dose reduction were assessed.

RESULTS

The mean (± SD) effective radiation dose was 1.06 ± 0.11, 0.44 ± 0.05, and 0.31 ± 0.03 mSv for low-dose CT, ultra-low-dose CT protocol A, and ultra-low-dose CT protocol B, respectively. Overall image quality was determined as diagnostic in 100% of low-dose CT scans, 96% of ultra-low-dose CT protocol A scans, and 88% of ultra-low-dose CT protocol B scans. All patients with nondiagnostic quality images had a body mass index (weight in kilograms divided by the square of height in meters) greater than 25. There was no statistically significant difference in detection frequencies of 14 lesion types among the three CT protocols, but pulmonary emphysema was detected in fewer patients (3/25) in ultra-low-dose CT protocol B scans compared with ultra-low-dose CT protocol A scans (5/25) or low-dose CT scans (6/25). We measured the longest dimensions of 33 small solid nodules (3.8-12.4 mm in long diameter) and found no statistically significant difference in the values afforded by the three CT protocols (p = 0.135).

CONCLUSION

Iterative reconstruction allows ultra-low-dose CT and affords acceptable image quality, allowing size measurements of solid pulmonary nodules to be made.

Dose reduction in cardiothoracic CT: review of currently available methods

Radiation exposure from computed tomography (CT) has received much attention lately in the medical literature and the media, given the relatively high radiation dose that characterizes a CT examination. Although there are a variety of possible strategies for reducing radiation exposure from CT in an individual patient, optimal CT image acquisition requires that the radiologist understand new scanner technology and how to implement the most effective means of dose reduction while maintaining image quality. The authors describe a practical approach to dose reduction in cardiothoracic radiology, discussing CT radiation dose metrics (eg, CT dose index, dose-length product, effective diameter, and size-specific dose estimate) as well as CT scanner parameters that directly or indirectly influence radiation dose (eg, scan length, x-ray tube output, tube current modulation, pitch, image reconstruction techniques [including iterative reconstruction], and noise reduction). These variables are discussed in terms of their relative importance to image quality and the implications of parametric changes for image quality and diagnostic content, and practical recommendations are made for their immediate implementation in the clinical setting. Taken together, the principles of physics and key parameters involved in reducing radiation dose while maintaining image quality can serve as a "survival guide" for a diagnostic radiology practice.

Sinogram Affirmed Iterative Reconstruction (SAFIRE) versus weighted filtered back projection (WFBP) effects on quantitative measure in the COPDGene 2 test object

PURPOSE

Assessing pulmonary emphysema using Quantitative CT of the lung depends on accurate measures of CT density. Sinogram-Affirmed-Iterative-Reconstruction (SAFIRE) is a new approach for reconstructing CT data acquired at significantly lower doses. However, quantitative effects of this method remain unexplored. The authors investigated the effects on the median values of materials in the COPDGene2 test-object as a function of the reconstruction method [weighted filtered back projection (WFBP) versus SAFIRE], test-object size, dose, and material composition using a Siemens SOMATOM Definition FLASH CT scanner.

METHODS

The COPDGene2 test-object contains eight materials; acrylic, water, four foams (20 lb, 12 lb, lung-equivalent, and 4 lb emphysema-equivalent), internal and external-air. The test-object was scanned with three different outer ring sizes, simulating three different body habitus. There is an average size (36 cm) Ring A, large size (40 cm) Ring B, and small size Ring C (30 cm). The CT protocol used 120 kVp, 0.5 s rotation, 1.0 pitch, and a 0.6 slice collimation with progressively decreasing x-ray exposure values, 11.94-0.74 mGy. With a thorax length of 30 cm, the corresponding effective doses would be 5.01-0.31 mSv. The effects of using SAFIRE versus WFBP were assessed using a two tailed t-test for each ring size, material, and dose. Multivariable linear regression was used to evaluate the relative effects of ring size, material composition, dose, and reconstruction method on the measured median value in HU.

RESULTS

SAFIRE versus WFBP, at the largest ring size and two lowest doses there was a significant difference in median values of 4 lb-foam, p<0.01. Using the smallest ring size at the lowest dose level there was a significant difference in the median value of 4 lb-foam, but the effect size was small, 1 HU. There is a significant difference in median values of both internal and external air using both the small and medium size rings at the three lowest dose levels, p<0.05. There are significant differences noted at both high and low dose levels when using the large ring size in the median values of internal and external air when, p<0.05. These effects on 4 lb-foam, inside and outside air are shown to be in part due to truncation effects on the median value since the lowest HU value in the CT scale used is -1024 HU. Multivariable linear regression results demonstrated significant effects on the measured material median value and standard deviation due to ring size, material composition, dose level, and reconstruction method, p<0.05.

CONCLUSIONS

The authors have shown that there is no significant effect on the median values obtained when using WFBP versus SAFIRE in materials with CT density between 120 and -856 HU using three different test-object sizes and CT doses that vary from 11.94 to 0.74 mGy. The authors have demonstrated there are significant effects on median values obtained when using WFBP versus SAFIRE in materials with CT density values between -937 and -1000 HU depending on the ring size and dose used. As expected, there is considerable reduction in image noise (lower standard deviation) using SAFIRE versus WFBP with all ring sizes, doses, and materials in the COPDGene2 test-object.