Emphysema quantification and lung volumetry in chest X-ray equivalent ultralow dose CT - Intra-individual comparison with standard dose CT

[Using Artificial Intelligence Software for Diagnosing Emphysema and Interstitial Lung Disease]

Researchers have developed various algorithms utilizing artificial intelligence (AI) to automatically and objectively diagnose patterns and extent of pulmonary emphysema or interstitial lung diseases on chest CT scans. Studies show that AI-based quantification of emphysema on chest CT scans reveals a connection between an increase in the relative percentage of emphysema and a decline in lung function. Notably, quantifying centrilobular emphysema has proven helpful in predicting clinical symptoms or mortality rates of chronic obstructive pulmonary disease. In the context of interstitial lung diseases, AI can classify the usual interstitial pneumonia pattern on CT scans into categories like normal, ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation. This classification accuracy is comparable to chest radiologists (70%-80%). However, the results generated by AI are influenced by factors such as scan parameters, reconstruction algorithms, radiation doses, and the training data used to develop the AI. These limitations currently restrict the widespread adoption of AI for quantifying pulmonary emphysema and interstitial lung diseases in daily clinical practice. This paper will showcase the authors' experience using AI for diagnosing and quantifying emphysema and interstitial lung diseases through case studies. We will primarily focus on the advantages and limitations of AI for these two diseases.

Advances in COPD imaging using CT and MRI: linkage with lung physiology and clinical outcomes

Recent years have witnessed major advances in lung imaging in patients with COPD. These include significant refinements in images obtained by computed tomography (CT) scans together with the introduction of new techniques and software that aim for obtaining the best image whilst using the lowest possible radiation dose. Magnetic resonance imaging (MRI) has also emerged as a useful radiation-free tool in assessing structural and more importantly functional derangements in patients with well-established COPD and smokers without COPD, even before the existence of overt changes in resting physiological lung function tests. Together, CT and MRI now allow objective quantification and assessment of structural changes within the airways, lung parenchyma and pulmonary vessels. Furthermore, CT and MRI can now provide objective assessments of regional lung ventilation and perfusion, and multinuclear MRI provides further insight into gas exchange; this can help in structured decisions regarding treatment plans. These advances in chest imaging techniques have brought new insights into our understanding of disease pathophysiology and characterising different disease phenotypes. The present review discusses, in detail, the advances in lung imaging in patients with COPD and how structural and functional imaging are linked with common resting physiological tests and important clinical outcomes.

Superior metal artifact reduction of tin-filtered low-dose CT in imaging of lumbar spinal instrumentation compared to conventional computed tomography

OBJECTIVE

To compare the image quality of low-dose CT (LD-CT) with tin filtration of the lumbar spine after metal implants to standard clinical CT, and to evaluate the potential for metal artifact and dose reduction.

MATERIALS AND METHODS

CT protocols were optimized in a cadaver torso. Seventy-four prospectively included patients with metallic lumbar implants were scanned with both standard CT (120 kV) and tin-filtered LD-CT (Sn140kV). CT dose parameters and qualitative measures (1 = worst,4 = best) were compared. Quantitative measures included noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and the width and attenuation of the most prominent hypodense metal artifact. Standard CT and LD-CT were assessed for imaging findings.

RESULTS

Tin-filtered LD-CT was performed with 60% dose saving compared to standard CT (median effective dose 3.22 mSv (quartile 1-3: 2.73-3.49 mSv) versus 8.02 mSv (6.42-9.27 mSv; p < .001). Image quality of CT and tin-filtered low-dose CT was good with excellent depiction of anatomy, while image noise was lower for CT and artifacts were weaker for tin-filtered LD-CT. Quantitative measures also revealed increased noise for tin-filtered low-dose CT (41.5HU), lower SNR (2) and CNR (0.6) compared to CT (32HU,3.55,1.03, respectively) (all p < .001). However, tin-filtered LD-CT performed superior regarding the width and attenuation of hypodense metal artifacts (2.9 mm and -767.5HU for LD-CT vs. 4.1 mm and -937HU for CT; all p < .001). No difference between methods was observed in detection of imaging findings.

CONCLUSION

Tin-filtered LD-CT with 60% dose saving performs comparable to standard CT in detection of pathology and surgery related complications after lumbar spinal instrumentation, and shows superior metal artifact reduction.

Correlation of lung function with ultra-low-dose CT-detected lung parenchymal abnormalities: a cohort study of 1344 asbestos exposed individuals

INTRODUCTION

Deliberate exposure to medical ionising radiation should be as low as reasonably practicable but the reduction of radiation from CT should be balanced against diagnostic image quality. The ability of ultra-low-dose CT (uLDCT: similar radiation to chest X-ray) to demonstrate low contrast abnormalities (emphysema and interstitial lung abnormality (ILA)) is unclear.The aim of this cross-sectional study was to analyse the lung parenchymal findings from uLDCT scans against physiological measures of respiratory function.

METHODS

WA Asbestos Review Programme participants were eligible if they had an uLDCT scan and lung function assessment between Janary and December 2018. All scans were performed using a single CT machine and reported using a standardised, semiquantitative synoptic report which includes emphysema and linear fibrosis (ILA) scores.

RESULTS

Of 1344 participants, median (IQR) age was 72.0 (65.0-78.0) years, the majority were males (84.9%) with mixed occupational asbestos exposure (68.1%). There were 721 (53.6%) with no abnormality, 158 (11.8%) with emphysema, 465 (34.6%) with ILA. Mean radiation dose was 0.12 mSv. There was statistically significant between group differences for all physiological parameters of lung function compared with controls. For instance, the emphysema score significantly correlated with obstructive forced expiratory volume in 1 s (FEV₁)/forced vital capacity ratio (r=0.512), per cent predicted FEV₁ (r=0.24) and lower diffusion of carbon monoxide (DLCO) (r=0.337). Multivariate modelling demonstrated that increasing age, emphysema and fibrosis scores predicted reduced DLCO (adjusted R²=0.30).

DISCUSSION

uLDCT-detected parenchymal lung abnormalities correlate strongly with significant changes on lung function testing suggesting the observed CT abnormalities are of physiological and clinical significance.

Chest CT scan for the screening of air anomalies at risk of pulmonary barotrauma for the initial medical assessment of fitness to dive in a military population

Introduction: The presence of intra-pulmonary air lesions such as cysts, blebs and emphysema bullae, predisposes to pulmonary barotrauma during pressure variations, especially during underwater diving activities. These rare accidents can have dramatic consequences. Chest radiography has long been the baseline examination for the detection of respiratory pathologies in occupational medicine. It has been replaced since 2018 by the thoracic CT scan for military diving fitness in France. The objective of this work was to evaluate the prevalence of the pulmonary abnormalities of the thoracic CT scan, and to relate them to the characteristics of this population and the results of the spirometry.

Methods: 330 records of military diving candidates who underwent an initial assessment between October 2018 and March 2021 were analyzed, in a single-center retrospective analysis. The following data were collected: sex, age, BMI, history of respiratory pathologies and smoking, treatments, allergies, diving practice, results of spirometry, reports of thoracic CT scans, as well as fitness decision.

Results: The study included 307 candidates, mostly male, with a median age of 25 years. 19% of the subjects had abnormal spirometry. We identified 25% of divers with CT scan abnormalities. 76% of the abnormal scans were benign nodules, 26% of which measured 6 mm or more. Abnormalities with an aerial component accounted for 13% of the abnormal scans with six emphysema bullae, three bronchial dilatations and one cystic lesion. No association was found between the presence of nodules and the general characteristics of the population, whereas in six subjects emphysema bullae were found statistically associated with active smoking or abnormal spirometry results.

Conclusion: The systematic performance of thoracic CT scan in a young population free of pulmonary pathology revealed a majority of benign nodules. Abnormalities with an aerial component are much less frequent, but their presence generally leads to a decision of unfitness. These results argue in favor of a systematic screening of aeric pleuro-pulmonary lesions during the initial assessment for professional divers.

Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry

In recent years, pulmonary imaging has seen enormous progress, with the introduction, validation and implementation of new hardware and software. There is a general trend from mere visual evaluation of radiological images to quantification of abnormalities and biomarkers, and assessment of ‘non visual’ markers that contribute to establishing diagnosis or prognosis. Important catalysts to these developments in thoracic imaging include new indications (like computed tomography [CT] lung cancer screening) and the COVID‐19 pandemic. This review focuses on developments in CT, radiomics, artificial intelligence (AI) and x‐ray velocimetry for imaging of the lungs. Recent developments in CT include the potential for ultra‐low‐dose CT imaging for lung nodules, and the advent of a new generation of CT systems based on photon‐counting detector technology. Radiomics has demonstrated potential towards predictive and prognostic tasks particularly in lung cancer, previously not achievable by visual inspection by radiologists, exploiting high dimensional patterns (mostly texture related) on medical imaging data. Deep learning technology has revolutionized the field of AI and as a result, performance of AI algorithms is approaching human performance for an increasing number of specific tasks. X‐ray velocimetry integrates x‐ray (fluoroscopic) imaging with unique image processing to produce quantitative four dimensional measurement of lung tissue motion, and accurate calculations of lung ventilation.

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Emphysema Quantification Using Ultra-Low-Dose Chest CT: Efficacy of Deep Learning-Based Image Reconstruction

Background and Objectives: Although reducing the radiation dose level is important during diagnostic computed tomography (CT) applications, effective image quality enhancement strategies are crucial to compensate for the degradation that is caused by a dose reduction. We performed this prospective study to quantify emphysema on ultra-low-dose CT images that were reconstructed using deep learning-based image reconstruction (DLIR) algorithms, and compared and evaluated the accuracies of DLIR algorithms versus standard-dose CT. Materials and Methods: A total of 32 patients were prospectively enrolled, and all underwent standard-dose and ultra-low-dose (120 kVp; CTDIvol < 0.7 mGy) chest CT scans at the same time in a single examination. A total of six image datasets (filtered back projection (FBP) for standard-dose CT, and FBP, adaptive statistical iterative reconstruction (ASIR-V) 50%, DLIR-low, DLIR-medium, DLIR-high for ultra-low-dose CT) were reconstructed for each patient. Image noise values, emphysema indices, total lung volumes, and mean lung attenuations were measured in the six image datasets and compared (one-way repeated measures ANOVA). Results: The mean effective doses for standard-dose and ultra-low-dose CT scans were 3.43 ± 0.57 mSv and 0.39 ± 0.03 mSv, respectively (p < 0.001). The total lung volume and mean lung attenuation of five image datasets of ultra-low-dose CT scans, emphysema indices of ultra-low-dose CT scans reconstructed using ASIR-V 50 or DLIR-low, and the image noise of ultra-low-dose CT scans that were reconstructed using DLIR-low were not different from those of standard-dose CT scans. Conclusions: Ultra-low-dose CT images that were reconstructed using DLIR-low were found to be useful for emphysema quantification at a radiation dose of only 11% of that required for standard-dose CT.

Performance of virtual non-contrast images generated on clinical photon-counting detector CT for emphysema quantification: proof of concept

OBJECTIVE

To evaluate the performance of virtual non-contrast images (VNC) compared to true non-contrast (TNC) images in photon-counting detector computed tomography (PCD-CT) for the evaluation of lung parenchyma and emphysema quantification.

METHODS

65 (mean age 73 years; 48 male) consecutive patients who underwent a three-phase (non-contrast, arterial and venous) chest/abdomen CT on a first-generation dual-source PCD-CT were retrospectively included. Scans were performed in the multienergy (QuantumPlus) mode at 120 kV with 70 ml intravenous contrast agent at an injection rate of 4 ml s-1. VNC were reconstructed from the arterial (VNCart) and venous phase (VNCven). TNC and VNC images of the lung were assessed quantitatively by calculating the global noise index (GNI) and qualitatively by two independent, blinded readers (overall image quality and emphysema assessment). Emphysema quantification was performed using a commercially available software tool at a threshold of -950 HU for all data sets. TNC images served as reference standard for emphysema quantification. Low attenuation values (LAV) were compared in a Bland-Altman plot.

RESULTS

GNI was similar in VNCart (103.0 ± 30.1) and VNCven (98.2 ± 22.2) as compared to TNC (100.9 ± 19.0, p = 0.546 and p = 0.272, respectively). Subjective image quality (emphysema assessment and overall image quality) was highest for TNC (p = 0.001), followed by VNCven and VNCart. Both, VNCart and VNCven showed no significant difference in emphysema quantification as compared to TNC (p = 0.409 vs. p = 0.093; respectively).

CONCLUSION

Emphysema evaluation is feasible using virtual non-contrast images from PCD-CT.

ADVANCES IN KNOWLEDGE

Emphysema quantification is feasible and accurate using VNC images in PCD-CT. Based on these findings, additional TNC scans for emphysema quantification could be omitted in the future.

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.

Improved precision of noise estimation in CT with a volume-based approach

Assessment of image noise is a relevant issue in computed tomography (CT). Noise is routinely measured by the standard deviation of density values (Hounsfield units, HU) within a circular region of interest (ROI). We explored the effect of a spherical volume of interest (VOI) on noise measurements. Forty-nine chronic obstructive pulmonary disease patients underwent CT with clinical protocol (regular dose [RD], volumetric CT dose index [CTDIvol] 3.04 mGy, 64-slice unit), and ultra-low dose (ULD) protocol (median CTDIvol 0.38 mGy, dual-source unit). Noise was measured in 27 1-cm² ROIs and 27 0.75-cm³ VOIs inside the trachea. Median true noise was 21 HU (range 17-29) for RD-CT and 33 HU (26-39) for ULD-CT. The VOI approach resulted in a lower mean distance between limits of agreement compared to ROI: 5.9 versus 10.0 HU for RD-CT (-40%); 4.7 versus 9.9 HU for ULD-CT (-53%). Mean systematic bias barely changed: -1.6 versus -0.9HU for RD-CT; 0.0 to 0.4HU for ULD-CT. The average measurement time was 6.8 s (ROI) versus 9.7 (VOI), independent of dose level. For chest CT, measuring noise with a VOI-based instead of a ROI-based approach reduces variability by 40-53%, without a relevant effect on systematic bias and measurement time.

Computed tomography-identified phenotypes of small airway obstructions in chronic obstructive pulmonary disease

ABSTRACT

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease characteristic of small airway inflammation, obstruction, and emphysema. It is well known that spirometry alone cannot differentiate each separate component. Computed tomography (CT) is widely used to determine the extent of emphysema and small airway involvement in COPD. Compared with the pulmonary function test, small airway CT phenotypes can accurately reflect disease severity in patients with COPD, which is conducive to improving the prognosis of this disease. CT measurement of central airway morphology has been applied in clinical, epidemiologic, and genetic investigations as an inference of the presence and severity of small airway disease. This review will focus on presenting the current knowledge and methodologies in chest CT that aid in identifying discrete COPD phenotypes.

Pelvic bone CT: can tin-filtered ultra-low-dose CT and virtual radiographs be used as alternative for standard CT and digital radiographs?

Objectives

To compare ultra-low-dose CT (ULD-CT) of the osseous pelvis with tin filtration to standard clinical CT (CT), and to assess the quality of computed virtual pelvic radiographs (VRs).

Methods

CT protocols were optimized in a phantom and three pelvic cadavers. Thirty prospectively included patients received both standard CT (automated tube voltage selection and current modulation) and tin-filtered ULD-CT of the pelvis (Sn140kV/50mAs). VRs of ULD-CT data were computed using an adapted cone beam–based projection algorithm and were compared to digital radiographs (DRs) of the pelvis. CT and DR dose parameters and quantitative and qualitative measures (1 = worst, 4 = best) were compared. CT and ULD-CT were assessed for osseous pathologies.

Results

Dose reduction of ULD-CT was 84% compared to CT, with a median effective dose of 0.38 mSv (quartile 1–3: 0.37–0.4 mSv) versus 2.31 mSv (1.82–3.58 mSv; p < .001), respectively. Mean dose of DR was 0.37 mSv (± 0.14 mSv). The median signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of bone were significantly higher for CT (64.3 and 21.5, respectively) compared to ULD-CT (50.4 and 18.8; p ≤ .01), while ULD-CT was significantly more dose efficient (figure of merit (FOM) 927.6) than CT (FOM 167.6; p < .001). Both CT and ULD-CT were of good image quality with excellent depiction of anatomy, with a median score of 4 (4–4) for both methods (p = .1). Agreement was perfect between both methods regarding the prevalence of assessed osseous pathologies (p > .99). VRs were successfully calculated and were equivalent to DRs.

Conclusion

Tin-filtered ULD-CT of the pelvis at a dose equivalent to standard radiographs is adequate for assessing bone anatomy and osseous pathologies and had a markedly superior dose efficiency than standard CT.

Key Points

• Ultra-low-dose pelvic CT with tin filtration (0.38 mSv) can be performed at a dose of digital radiographs (0.37 mSv), with a dose reduction of 84% compared to standard CT (2.31 mSv).

• Tin-filtered ultra-low-dose CT had lower SNR and CNR and higher image noise than standard CT, but showed clear depiction of anatomy and accurate detection of osseous pathologies.

• Virtual pelvic radiographs were successfully calculated from ultra-low-dose CT data and were equivalent to digital radiographs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-021-07824-x.

Ultra-low-dose CT combined with noise reduction techniques for quantification of emphysema in COPD patients: An intra-individual comparison study with standard-dose CT

PURPOSE

Phantom studies in CT emphysema quantification show that iterative reconstruction and deep learning-based noise reduction (DLNR) allow lower radiation dose. We compared emphysema quantification on ultra-low-dose CT (ULDCT) with and without noise reduction, to standard-dose CT (SDCT) in chronic obstructive pulmonary disease (COPD).

METHOD

Forty-nine COPD patients underwent ULDCT (third generation dual-source CT; 70ref-mAs, Sn-filter 100kVp; median CTDIvol 0.38 mGy) and SDCT (64-multidetector CT; 40mAs, 120kVp; CTDIvol 3.04 mGy). Scans were reconstructed with filtered backprojection (FBP) and soft kernel. For ULDCT, we also applied advanced modelled iterative reconstruction (ADMIRE), levels 1/3/5, and DLNR, levels 1/3/5/9. Emphysema was quantified as Low Attenuation Value percentage (LAV%, ≤-950HU). ULDCT measures were compared to SDCT as reference standard.

RESULTS

For ULDCT, the median radiation dose was 84 % lower than for SDCT. Median extent of emphysema was 18.6 % for ULD-FBP and 15.4 % for SDCT (inter-quartile range: 11.8-28.4 % and 9.2 %-28.7 %, p = 0.002). Compared to SDCT, the range in limits of agreement of emphysema quantification as measure of variability was 14.4 for ULD-FBP, 11.0-13.1 for ULD-ADMIRE levels and 10.1-13.9 for ULD-DLNR levels. Optimal settings were ADMIRE 3 and DLNR 3, reducing variability of emphysema quantification by 24 % and 27 %, at slight underestimation of emphysema extent (-1.5 % and -2.9 %, respectively).

CONCLUSIONS

Ultra-low-dose CT in COPD patients allows dose reduction by 84 %. State-of-the-art noise reduction methods in ULDCT resulted in slight underestimation of emphysema compared to SDCT. Noise reduction methods (especially ADMIRE 3 and DLNR 3) reduced variability of emphysema quantification in ULDCT by up to 27 % compared to FBP.

Cycle-Consistent Generative Adversarial Network: Effect on Radiation Dose Reduction and Image Quality Improvement in Ultralow-Dose CT for Evaluation of Pulmonary Tuberculosis

Objective

To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis.

Materials and Methods

Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively.

Results

With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT.

Conclusion

The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.

Advances in imaging for lung emphysema

Lung emphysema represents a major public health burden and still accounts for five percent of all deaths worldwide. Hence, it is essential to further understand this disease in order to develop effective diagnostic and therapeutic strategies. Lung emphysema is an irreversible enlargement of the airways distal to the terminal bronchi (i.e., the alveoli) due to the destruction of the alveolar walls. The two most important causes of emphysema are (I) smoking and (II) α1-antitrypsin-deficiency. In the former lung emphysema is predominant in the upper lung parts, the latter is characterized by a predominance in the basal areas of the lungs. Since quantification and evaluation of the distribution of lung emphysema is crucial in treatment planning, imaging plays a central role. Imaging modalities in lung emphysema are manifold: computed tomography (CT) imaging is nowadays the gold standard. However, emerging imaging techniques like dynamic or functional magnetic resonance imaging (MRI), scintigraphy and lately also the implementation of radiomics and artificial intelligence are more and more diffused in the evaluation, diagnosis and quantification of lung emphysema. The aim of this review is to shortly present the different subtypes of lung emphysema, to give an overview on prediction and risk assessment in emphysematous disease and to discuss not only the traditional, but also the new imaging techniques for diagnosis, quantification and evaluation of lung emphysema.

Feasibility of bronchial wall quantification in low- and ultralow-dose third-generation dual-source CT: An ex vivo lung study

PURPOSE

To investigate image quality and bronchial wall quantification in low- and ultralow-dose third-generation dual-source computed tomography (CT).

METHODS

A lung specimen from a formerly healthy male was scanned using third-generation dual-source CT at standard-dose (51 mAs/120 kV, CTDI_vol 3.41 mGy), low-dose (1/4th and 1/10th of standard dose), and ultralow-dose setting (1/20th). Low kV (70, 80, 90, and Sn100 kV) scanning was applied in each low/ultralow-dose setting, combined with adaptive mAs to keep a constant dose. Images were reconstructed at advanced modeled iterative reconstruction (ADMIRE) levels 1, 3, and 5 for each scan. Bronchial wall were semi-automatically measured from the lobar level to subsegmental level. Spearman correlation analysis was performed between bronchial wall quantification (wall thickness and wall area percentage) and protocol settings (dose, kV, and ADMIRE). ANOVA with a post hoc pairwise test was used to compare signal-to-noise ratio (SNR), noise and bronchial wall quantification values among standard- and low/ultralow-dose settings, and among ADMIRE levels.

RESULTS

Bronchial wall quantification had no correlation with dose level, kV, or ADMIRE level (|correlation coefficients| < 0.3). SNR and noise showed no statistically significant differences at different kV in the same ADMIRE level (1, 3, or 5) and in the same dose group (P > 0.05). Generally, there were no significant differences in bronchial wall quantification among the standard- and low/ultralow-dose settings, and among different ADMIRE levels (P > 0.05).

CONCLUSION

The combined use of low/ultralow-dose scanning and ADMIRE does not influence bronchial wall quantification compared to standard-dose CT. This specimen study suggests the potential that an ultralow-dose scan can be used for bronchial wall quantification.

The effect of pectus excavatum deformity on lung volume: fact or myth?

BACKGROUND AND PURPOSE

Most of the previous studies evaluating lung volume of pectus excavatum (PE) patients were based on spirometric measurements. We aimed to calculate lung volume of patients with PE and compare them with lung volume of patients without chest wall deformity using CT volumetry.

METHODS

After institutional review board approval, preoperative chest CT of PE patients who underwent minimal invasive procedure between January 2012 and February 2018, were evaluated retrospectively. As a control group, age and sex matched patients who underwent chest CT scan in the same period were enrolled. Total, right and left lung volumes were calculated using an automated software. Haller indexes were measured for both groups. Lung volumes and Haller indexes compared between the two groups. We also compared left and right lung volumes in both groups. We evaluated whether there is a correlation across the Haller index and total lung volume.

RESULTS

Total, right and left lung volumes were not statistically different between the two groups. While left lung volumes were significantly smaller in PE group (p = 0.041), there was no significant difference between the left and right lung volume in the control group (p = 0.12). Haller index and total lung volume showed no significant correlation between patients with the same age and gender (p = 0.14, R = -0.3).

CONCLUSIONS

PE deformity does not reduce lung volume when compared to age and sex matched control group. Quantitative CT volumetric evaluation of lung gives valuable data about lung volume.

Potential for dose reduction in CT emphysema densitometry with post-scan noise reduction: a phantom study

OBJECTIVE

The aim of this phantom study was to investigate the effect of scan parameters and noise suppression techniques on the minimum radiation dose for acceptable image quality for CT emphysema densitometry.

METHODS

The COPDGene phantom was scanned on a third generation dual-source CT system with 16 scan setups (CTDI_vol 0.035-10.680 mGy). Images were reconstructed at 1.0/0.7 mm slice thickness/increment, with three kernels (one soft, two hard), filtered backprojection and three grades of third-generation iterative reconstruction (IR). Additionally, deep learning-based noise suppression software was applied. Main outcomes: overlap in area of the normalized histograms of CT density for the emphysema insert and lung material, and the radiation dose required for a maximum of 4.3% overlap (defined as acceptable image quality).

RESULTS

In total, 384 scan reconstructions were analyzed. Decreasing radiation dose resulted in an exponential increase of the overlap in normalized histograms of CT density. The overlap was 11-91% for the lowest dose setting (CTDI_vol 0.035mGy). The soft kernel reconstruction showed less histogram overlap than hard filter kernels. IR and noise suppression also reduced overlap. Using intermediate grade IR plus noise suppression software allowed for 85% radiation dose reduction while maintaining acceptable image quality.

CONCLUSION

CT density histogram overlap can quantify the degree of discernibility of emphysema and healthy lung tissue. Noise suppression software, IR, and soft reconstruction kernels substantially decrease the dose required for acceptable image quality.

ADVANCES IN KNOWLEDGE

Noise suppression software, IR, and soft reconstruction kernels allow radiation dose reduction by 85% while still allowing differentiation between emphysema and normal lung tissue.

Emphysema quantification using chest CT: influence of radiation dose reduction and reconstruction technique

BACKGROUND

Computed tomography (CT) emphysema quantification is affected by both radiation dose (i.e. image noise) and reconstruction technique. At reduced dose, filtered back projection (FBP) results in an overestimation of the amount of emphysema due to higher noise levels, while the use of iterative reconstruction (IR) can result in an underestimation due to reduced noise. The objective of this study was to determine the influence of dose reduction and hybrid IR (HIR) or model-based IR (MIR) on CT emphysema quantification.

METHODS

Twenty-two patients underwent inspiratory chest CT scan at routine radiation dose and at 45%, 60% and 75% reduced radiation dose. Acquisitions were reconstructed with FBP, HIR and MIR. Emphysema was quantified using the 15th percentile of the attenuation curve and the percentage of voxels below -950 HU. To determine whether the use of a different percentile or HU threshold is more accurate at reduced dose levels and with IR, additional measurements were performed using different percentiles and HU thresholds to determine the optimal combination.

RESULTS

Dose reduction resulted in a significant overestimation of emphysema, while HIR and MIR resulted in an underestimation. Lower HU thresholds with FBP at reduced dose and higher HU thresholds with HIR and MIR resulted in emphysema percentages comparable to the reference. The 15th percentile quantification method showed similar results as the HU threshold method.

CONCLUSIONS

This within-patients study showed that CT emphysema quantification is significantly affected by dose reduction and IR. This can potentially be solved by adapting commonly used thresholds.

Unilateral Chronic Lung Allograft Dysfunction Assessed by Biphasic Computed Tomographic Volumetry in Bilateral Living-donor Lobar Lung Transplantation

Background

Early diagnosis of unilateral chronic lung allograft dysfunction (CLAD) is difficult because the unaffected contralateral lung functions as a reservoir in bilateral living-donor lobar lung transplantation (LDLLT). We previously reported the usefulness of ¹³³Xe ventilation scintigraphy for detection of unilateral change, but the supply of ¹³³Xe has been stopped globally. The present study aimed to examine the usefulness of inspiratory and expiratory computed tomography (I/E CT) volumetry for detection of unilateral change in CLAD patients.

Methods

This was a retrospective single-center, observational study using prospectively collected data. A total of 58 patients who underwent bilateral LDLLT from August 2008 to February 2017 were analyzed. Respiratory function tests, I/E CT were prospectively conducted. ΔLung volume was defined as the value obtained by subtracting expiratory lung volume from inspiratory lung volume.

Results

Fourteen (24%) cases were clinically diagnosed with CLAD, of which 10 (71%) were diagnosed as unilateral CLAD. ΔLung volume of bilateral lungs strongly correlated with forced vital capacity (r = 0.92, P < 0.01) and forced expiratory volume in 1 second (r = 0.80, P < 0.01). Regardless the phenotypes (bronchiolitis obliterans syndrome or restrictive allograft syndrome) of CLAD, Δlung volume onset/baseline significantly decreased compared with that in the non-CLAD group. Among the 10 unilateral CLAD patients, 3 with clinically suspected unilateral rejection yet did not show a 20% decline in forced expiratory volume in 1 second. In 2 of these, Δlung volume of unilateral lungs on the rejection side decreased by 20% or more.

Conclusions

Our findings suggest that I/E CT volumetry may be useful for assessment and early diagnosis of unilateral CLAD after bilateral LDLLT.

Chest CT Scan at Radiation Dose of a Posteroanterior and Lateral Chest Radiograph Series: A Proof of Principle in Lymphangioleiomyomatosis

BACKGROUND

Given the rising utilization of medical imaging and the risks of radiation, there is increased interest in reducing radiation exposure. The objective of this study was to evaluate, as a proof of principle, CT scans performed at radiation doses equivalent to that of a posteroanterior and lateral chest radiograph series in the cystic lung disease lymphangioleiomyomatosis (LAM).

METHODS

From November 2016 to May 2018, 105 consecutive subjects with LAM received chest CT scans at standard and ultra-low radiation doses. Standard and ultra-low-dose images, respectively, were reconstructed with routine iterative and newer model-based iterative reconstruction. LAM severity can be quantified as cyst score (percentage of lung occupied by cysts), an ideal benchmark for validating CT scans performed at a reduced dose compared with a standard dose. Cyst scores were quantified using semi-automated software and evaluated by linear correlation and Bland-Altman analysis.

RESULTS

Overall, ultra-low-dose CT scans represented a 96% dose reduction, with a median dose equivalent to 1 vs 22 posteroanterior and lateral chest radiograph series (0.14 mSv; 5th-95th percentile, 0.10-0.20 vs standard dose 3.4 mSv; 5th-95th percentile, 1.5-7.4; P < .0001). The mean difference in cyst scores between ultra-low- and standard-dose CT scans was 1.1% ± 2.0%, with a relative difference in cyst score of 11%. Linear correlation coefficient was excellent at 0.97 (P < .0001).

CONCLUSIONS

In LAM chest CT scan at substantial radiation reduction to doses equivalent to that of a posteroanterior and lateral chest radiograph series provides cyst score quantification similar to that of standard-dose CT scan.

TRIAL REGISTRY

ClinicalTrials.gov; Nos.: NCT00001465 and NCT00001532; URL: www.clinicaltrials.gov.

Pulmonary Emphysema Quantification on Ultra-Low-Dose Computed Tomography Using Model-Based Iterative Reconstruction With or Without Lung Setting

OBJECTIVES

To evaluate the influence of model-based iterative reconstruction (MBIR) with lung setting and conventional setting on pulmonary emphysema quantification by ultra-low-dose computed tomography (ULDCT) compared with standard-dose CT (SDCT).

METHODS

Forty-five patients who underwent ULDCT (0.18 ± 0.02 mSv) and SDCT (6.66 ± 2.69 mSv) were analyzed in this retrospective study. Images were reconstructed using filtered back projection (FBP) with smooth and sharp kernels and MBIR with conventional and lung settings. Extent of emphysema was evaluated using fully automated software. Correlation between ULDCT and SDCT was assessed by interclass correlation coefficiency (ICC) and Bland-Altman analysis.

RESULTS

Excellent correlation was seen between MBIR with conventional setting on ULDCT and FBP with smooth kernel on SDCT (ICC, 0.97; bias, -0.31%) and between MBIR with lung setting on ULDCT and FBP with sharp kernel on SDCT (ICC, 0.82; bias, -2.10%).

CONCLUSION

Model-based iterative reconstruction improved the agreement between ULDCT and SDCT on emphysema quantification.

Diagnostic accuracy of chest X-ray dose-equivalent CT for assessing calcified atherosclerotic burden of the thoracic aorta

OBJECTIVE

To determine the value of ultralow-dose chest CT for estimating the calcified atherosclerotic burden of the thoracic aorta using tin-filter CT and compare its diagnostic accuracy with chest direct radiography.

METHODS

A total of 106 patients from a prospective, IRB-approved single-centre study were included and underwent standard dose chest CT (1.7 ± 0.7 mSv) by clinical indication followed by ultralow-dose CT with 100 kV and spectral shaping by a tin filter (0.13 ± 0.01 mSv) to achieve chest X-ray equivalent dose in the same session. Two independent radiologists reviewed the CT images, rated image quality and estimated presence and extent of calcification of aortic valve, ascending aorta and aortic arch. Conventional radiographs were also reviewed for presence of aortic calcifications.

RESULTS

The sensitivity of ultralow-dose CT for the detection of calcifications of the aortic valve, ascending aorta and aortic arch was 93.5, 96.2 and 96.2%, respectively, compared with standard dose CT. The sensitivity for the detection of thoracic aortic calcification was significantly lower on chest X-ray (52.3%) compared with ultralow-dose CT (p < 0.001).

CONCLUSION

A reliable estimation of calcified atherosclerotic burden of the thoracic aorta can be achieved with modern tin-filter CT at dose values comparable to chest direct radiography. Advances in knowledge: Our findings suggest that ultralow-dose CT is an excellent tool for assessing the calcified atherosclerotic burden of the thoracic aorta with higher diagnostic accuracy than conventional chest radiography and importantly without the additional cost of increased radiation dose.