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

Artifact reduction in low and ultra-low dose chest computed tomography for patients with pacemaker: A phantom study

INTRODUCTION

Implanted pacemakers (PM) would decrease the detection of lung nodules in chest computed tomography (CT) due to the metal artifact. This study aimed to explore the computer-aided diagnosis (CAD) detectability of pulmonary nodules for the patients implanted with PMs in low- and ultra-low-dose chest CT screening.

METHODS

Four different sizes of artificial nodules were placed in an anthropomorphic chest phantom with two alternative diameters utilized. A commercially available PM was placed on the surface of the left chest wall of the phantom. The image acquisitions were performed with 120 kV and 150 kV with a dedicated selective photon shield made of tin filter (Sn150 kV) at low- and ultra-low- radiation doses (1.0 and 0.5 mGy of volume CT dose index), and reconstructed with and without Iterative Metal Artifact Reduction (iMAR, Siemens Healthineers, Erlangen, Germany). The relative artifact index (AIr) was calculated as an index of metal artifacts, and the nodule detectability was evaluated with a CAD system.

RESULTS

Sn150 kV reduced AIr in all acquisitions when comparing 120 kV and Sn150 kV. Although PM reduced the detectability of nodules, Sn150 kV showed higher detectability compared to 120 kV. The use of iMAR showed inconsistent results in nodule detectability.

CONCLUSION

Sn150 kV reduced PM-induced metal artifacts and improved nodule detectability with CAD compared to 120 kV acquisition in many conditions including low and ultra-low doses and large phantoms, but iMAR did not improve the detectability.

IMPLICATIONS FOR PRACTICE

Based on the results of the current phantom study, low and ultra-low dose with Sn150 kV acquisition reduced PM-induced metal artifacts and improved nodule detectability.

Multiphase photon counting detector CT data sets - Which combination of contrast phase and virtual non-contrast algorithm is best suited to replace true non-contrast series in the assessment of active bleeding?

PURPOSE

Aim of this study was to determine which virtual non-contrast (VNC) reconstruction algorithm, applied to which contrast phase of computed tomography angiography, best matches true non-contrast (TNC) images in the assessment of active bleeding.

METHOD

Patients who underwent a triphasic scan (pre-contrast, arterial, portal venous contrast) on a photon-counting detector CT (PCD-CT) (120 kV, image quality level 68) with suspected active (tumor, postoperative, spontaneous or other) bleeding were retrospectively included in this study. Conventional (VNCConv) and a calcium-preserving VNC algorithm (VNCPC) were derived from both arterial (art) and portal venous (pv) contrast scans, and analyzed quantitatively and qualitatively by two independent and blinded raters.

RESULTS

40 patients (22 female, mean age 76 years) were included. Measurements of CT values showed significant albeit small differences between TNC and VNC for most analyzed tissue regions without clear superiority of a VNC algorithm or contrast phase (e.g. ΔHU fat TNC to VNCPCpv 3.1 HU). However, qualitative analysis showed a preference to VNCPCpv in terms of image quality (on a 5-point Likert scale VNCConvart = 3.5 ± 0.8, VNCPCart = 3.7 ± 0.7, VNCConvpv = 3.7 ± 0.7, VNCPCpv = 3.8 ± 0.7) and residual calcium contrast (VNCConvart = 3.0 ± 0.8, VNCPCart = 3.5 ± 0.7, VNCConvpv = 3.6 ± 0.7, VNCPCpv = 3.9 ± 0.6).

CONCLUSIONS

When multiple post-contrast phases are available, VNCPC series based on portal venous phase are the most suitable replacement for an additional pre-contrast scan, with the prospect of a significant reduction in patient radiation dose.

Impact of radiation dose on the detection of interstitial lung changes and image quality in low-dose chest CT - Assessment in multiple dose levels from a single patient scan

PURPOSE

To assess image quality and detectability of interstitial lung changes using multiple radiation doses from the same chest CT scan of patients with suspected interstitial lung disease (ILD).

METHOD

Retrospective study of consecutive adult patients with suspected ILD receiving unenhanced chest CT as single-energy dual-source acquisition at 100 kVp (Dual-split mode). 67% and 33% of the overall tube current time product were assigned to tube A and B, respectively. 100%-dose was 2.34 ± 0.97 mGy. Five different radiation doses (100%, 67%, 45%, 39%, 33%) were reconstructed from this single acquisition using linear-blending technique. Two blinded radiologists assessed reticulations, ground-glass opacities (GGO) and honeycombing as well as subjective image noise. Percentage agreement (PA) as compared to 100%-dose were calculated. Non-parametric statistical tests were used.

RESULTS

A total of 228 patients were included (61.2 ± 14.6 years,146 female). PA was highest for honeycombing (>96%) and independent of dose reduction (P > 0.8). PA for reticulations and GGO decreased when reducing the radiation dose from 100% to 67% for both readers (reticulations: 83.3% and 93.9%; GGO: 87.7% and 79.8% for reader 1 and 2, respectively). Additional dose reduction did not significantly change PA for both readers (all P > 0.05). Subjective image noise increased with decreasing radiation dose (Spearman Rho of ρ = 0.34 and ρ = 0.53 for reader 1 and 2, respectively, P < 0.001).

CONCLUSIONS

Radiation dose reduction had a stronger impact on subtle interstitial lung changes. Detectability decreased with initial dose reduction indicating that a minimum dose is needed to maintain diagnostic accuracy in chest CT for suspected ILD.

CT in the detection of latent tuberculosis: a systematic review

AIM

To evaluate the use of computed tomography (CT) and low-dose CT in the detection of latent tuberculosis (TB).

MATERIALS AND METHODS

A systematic search of literature in adherence with the PRISMA guidelines was carried out. Quality assessment of the included studies was conducted.

RESULTS

The search strategy identified a total of 4,621 studies. Sixteen studies were considered eligible and included in the review. There was high heterogeneity among all studies. CT was identified as much more sensitive for the detection of latent TB in all studies despite chest radiography often being recommended in guidelines to assess patients for latent TB. Low-dose CT showed promising results in four of the studies; however, these results were limited due to small sample sizes.

CONCLUSION

CT is much superior to chest radiography consistently identifying additional cases of latent TB. There are limited high-quality publications available using low-dose CT but findings thus far suggest low-dose CT could be used as an alternative to standard-dose CT for the detection of latent TB. It is recommended that a randomised controlled trial investigating low-dose CT should be carried out.

Reduction of scan duration and radiation dose in cerebral CT perfusion imaging of acute stroke using a recurrent neural network

Objective. Cerebral CT perfusion (CTP) imaging is most commonly used to diagnose acute ischaemic stroke and support treatment decisions. Shortening CTP scan duration is desirable to reduce the accumulated radiation dose and the risk of patient head movement. In this study, we present a novel application of a stochastic adversarial video prediction approach to reduce CTP imaging acquisition time.Approach. A variational autoencoder and generative adversarial network (VAE-GAN) were implemented in a recurrent framework in three scenarios: to predict the last 8 (24 s), 13 (31.5 s) and 18 (39 s) image frames of the CTP acquisition from the first 25 (36 s), 20 (28.5 s) and 15 (21 s) acquired frames, respectively. The model was trained using 65 stroke cases and tested on 10 unseen cases. Predicted frames were assessed against ground-truth in terms of image quality and haemodynamic maps, bolus shape characteristics and volumetric analysis of lesions.Main results. In all three prediction scenarios, the mean percentage error between the area, full-width-at-half-maximum and maximum enhancement of the predicted and ground-truth bolus curve was less than 4 ± 4%. The best peak signal-to-noise ratio and structural similarity of predicted haemodynamic maps was obtained for cerebral blood volume followed (in order) by cerebral blood flow, mean transit time and time to peak. For the 3 prediction scenarios, average volumetric error of the lesion was overestimated by 7%-15%, 11%-28% and 7%-22% for the infarct, penumbra and hypo-perfused regions, respectively, and the corresponding spatial agreement for these regions was 67%-76%, 76%-86% and 83%-92%.Significance. This study suggests that a recurrent VAE-GAN could potentially be used to predict a portion of CTP frames from truncated acquisitions, preserving the majority of clinical content in the images, and potentially reducing the scan duration and radiation dose simultaneously by 65% and 54.5%, respectively.

Dynamic chest radiography: a state-of-the-art review

Dynamic chest radiography (DCR) is a real-time sequential high-resolution digital X-ray imaging system of the thorax in motion over the respiratory cycle, utilising pulsed image exposure and a larger field of view than fluoroscopy coupled with a low radiation dose, where post-acquisition image processing by computer algorithm automatically characterises the motion of thoracic structures. We conducted a systematic review of the literature and found 29 relevant publications describing its use in humans including the assessment of diaphragm and chest wall motion, measurement of pulmonary ventilation and perfusion, and the assessment of airway narrowing. Work is ongoing in several other areas including assessment of diaphragmatic paralysis. We assess the findings, methodology and limitations of DCR, and we discuss the current and future roles of this promising medical imaging technology.Critical relevance statement Dynamic chest radiography provides a wealth of clinical information, but further research is required to identify its clinical niche.

Imaging of lung cancer

Lung cancer is the leading cause of cancer-related mortality globally. Imaging is essential in the screening, diagnosis, staging, response assessment, and surveillance of patients with lung cancer. Subtypes of lung cancer can have distinguishing imaging appearances. The most frequently used imaging modalities include chest radiography, computed tomography, magnetic resonance imaging, and positron emission tomography. Artificial intelligence algorithms and radiomics are emerging technologies with potential applications in lung cancer imaging.

Diagnostic clues for the identification of pediatric foreign body aspirations and consideration of novel imaging techniques

OBJECTIVE

To better understand the diagnosis of foreign body aspiration by elucidating key components of its clinical presentation.

METHODS

This is a retrospective cohort study of pediatric patients with suspected foreign body aspiration. We collected information regarding demographics, history, symptoms, physical exam, imaging, and operative findings for rigid bronchoscopies. An evaluation of these findings for an association with foreign body aspiration and the overall diagnostic algorithm was performed.

RESULTS

518 pediatric patients presented with 75.2 % presenting within one day of the inciting event. Identified history findings included wheeze (OR: 5.83, p < 0.0001) and multiple encounters (OR: 5.46, p < 0.0001). Oxygen saturation was lower in patients with foreign body aspiration (97.3 %, p < 0.001). Identified physical exam findings included wheeze (OR: 7.38, p < 0.001) and asymmetric breath sounds (OR: 5.48, p < 0.0001). The sensitivity and specificity of history findings was 86.7 % and 23.1 %, physical exam was 60.8 % and 88.4 %, and chest radiographs was 45.3 % and 88.0 %. 25 CT scans were performed with a sensitivity and specificity of 100 % and 85.7 %. Combining two components of the diagnostic algorithm yielded a high sensitivity and moderate specificity; the best combination was the history and physical exam. 186 rigid bronchoscopies were performed with 65.6 % positive for foreign body aspiration.

CONCLUSION

Accurate diagnosis of foreign body aspiration requires careful history taking and examination. Low-dose CT should be included in the diagnostic algorithm. The combination of any two components of the diagnostic algorithm is the most accurate for foreign body aspiration.

Limited Clinical Impact of Ultralow-Dose Computed Tomography in Suspected Community-Acquired Pneumonia

Patients clinically suspected of community-acquired pneumonia (CAP) were randomized between ultralow-dose chest computed tomography ([ULDCT] 261 patients) and chest radiograph ([CXR] 231 patients). We did not find evidence that performing ULDCT instead of CXR affects antibiotic treatment policy or patient outcomes. However, in a subgroup of afebrile patients, there were more patients diagnosed with CAP in the ULDCT group (ULDCT, 106 of 608 patients; CXR, 71 of 654 patients; P = .001).

Low-Dose Chest CT Protocols for Imaging COVID-19 Pneumonia: Technique Parameters and Radiation Dose

Chest computed tomography (CT) plays a vital role in the early diagnosis, treatment, and follow-up of COVID-19 pneumonia during the pandemic. However, this raises concerns about excessive exposure to ionizing radiation. This study aimed to survey radiation doses in low-dose chest CT (LDCT) and ultra-low-dose chest CT (ULD) protocols used for imaging COVID-19 pneumonia relative to standard CT (STD) protocols so that the best possible practice and dose reduction techniques could be recommended. A total of 564 articles were identified by searching major scientific databases, including ISI Web of Science, Scopus, and PubMed. After evaluating the content and applying the inclusion criteria to technical factors and radiation dose metrics relevant to the LDCT protocols used for imaging COVID-19 patients, data from ten articles were extracted and analyzed. Technique factors that affect the application of LDCT and ULD are discussed, including tube current (mA), peak tube voltage (kVp), pitch factor, and iterative reconstruction (IR) algorithms. The CTDIvol values for the STD, LDCT, and ULD chest CT protocols ranged from 2.79-13.2 mGy, 0.90-4.40 mGy, and 0.20-0.28 mGy, respectively. The effective dose (ED) values for STD, LDCT, and ULD chest CT protocols ranged from 1.66-6.60 mSv, 0.50-0.80 mGy, and 0.39-0.64 mSv, respectively. Compared with the standard (STD), LDCT reduced the dose reduction by a factor of 2-4, whereas ULD reduced the dose reduction by a factor of 8-13. These dose reductions were achieved by applying scan parameters and techniques such as iterative reconstructions, ultra-long pitches, and fast spectral shaping with a tin filter. Using LDCT, the cumulative radiation dose of serial CT examinations during the acute period of COVID-19 may have been inferior or equivalent to that of conventional CT.

Ultra-low dose computed tomography protocols using spectral shaping for lung cancer screening: Comparison with low-dose for volumetric LungRADS classification

PURPOSE

To compare Low-Dose Computed Tomography (LDCT) with four different Ultra-Low-Dose Computed Tomography (ULDCT) protocols for PN classification according to the Lung Reporting and Data System (LungRADS).

METHODS

Three hundred sixty-one participants of an ongoing lung cancer screening (LCS) underwent single-breath-hold double chest Computed Tomography (CT), including LDCT (120kVp, 25mAs; CTDIvol 1,62 mGy) and one ULDCT among: fully automated exposure control ("ULDCT₁"); fixed tube-voltage and current according to patient size ("ULDCT₂"); hybrid approach with fixed tube-voltage ("ULDCT₃") and tube current automated exposure control ("ULDCT₄"). Two radiologists (R1, R2) assessed LungRADS 2022 categories on LDCT, and then after 2 weeks on ULDCT using two different kernels (R1: Qr49_{ADMIRE 4}; R2: Br49_{ADMIRE 3}). Intra-subject agreement for LungRADS categories between LDCT and ULDCT was measured by the k-Cohen Index with Fleiss-Cohen weights.

RESULTS

LDCT-dominant PNs were detected in ULDCT in 87 % of cases on Qr49_{ADMIRE 4} and 88 % on Br49_{ADMIRE 3}. The intra-subject agreement was: κULDCT₁ = 0.89 [95 %CI 0.82-0.96]; κULDCT₂ = 0.90 [0.81-0.98]; κULDCT₃ = 0.91 [0.84-0.99]; κULDCT₄ = 0.88 [0.78-0.97] on Qr49_{ADMIRE 4}, and κULDCT₁ = 0.88 [0.80-0.95]; κULDCT₂ = 0.91 [0.86-0.96]; κULDCT₃ = 0.87 [0.78-0.95]; and κULDCT₄ = 0.88 [0.82-0.94] on Br49_{ADMIRE 3}. LDCT classified as LungRADS 4B were correctly identified as LungRADS 4B at ULDCT₃, with the lowest radiation exposure among the tested protocols (median effective doses were 0.31, 0.36, 0.27 and 0.37 mSv for ULDCT₁, ULDCT₂, ULDCT₃, and ULDCT₄, respectively).

CONCLUSIONS

ULDCT by spectral shaping allows the detection and characterization of PNs with an excellent agreement with LDCT and can be proposed as a feasible approach in LCS.

APPLICATION OF CT PULMONARY ANGIOGRAPHY WITH "ULTRA-DOUBLE-LOW" AND ITERATIVE MODEL RECONSTRUCTION FOR ACUTE PULMONARY EMBOLISM

The study is to investigate the feasibility of computed tomography pulmonary angiography (CTPA) with iterative model reconstruction (IMR) and "Ultra-double-low" (Ultra-low dose, Ultra-low contrast agent volume). Thirty-six patients who tested positive for pulmonary embolism in CTPA were enrolled in the study. Another CTPA was performed 1 week after thrombolytic therapy. The first examination was routine CTPA (Routine Group) with the parameters as follows: automatic mA scanning, 120 kV and image reconstruction by using iDose4 iterative reconstruction (Lever 4), iodine concentration and dose of contrast agent: 300 mgI/ml and 0.5 gI/kg, respectively. The latter one was ultra-low dose CTPA examination (Ultra-low Group): 40 mAs, 80 kV and IMR (Lever 3), contrast agent: 300 mgI/ml and 15 mL, respectively. Effective dose (ED), CT dose index volume (CTDIvol), dose length product (DLP), attenuation of pulmonary artery, contrast noise ratio (CNR) and signal noise ratio (SNR) were recorded and calculated. The imaging qualities were subjectively assessed. The Eds/CTDIvols/DLPs of Ultra-low Group are lower than the Routine Group (P < 0.05). The differences in attenuation between the two groups are not significant (P > 0.05). The differences in CNR and SNR between the two groups are significant (P < 0.05). The differences in imaging qualities between the two groups when subjectively assessed are not significant (P > 0.05). The 256-slice spiral CT combined with IMR and "Ultra-double-low" is feasible for the acute pulmonary embolism examination and the radiation dose and the volume of contrast agent can be greatly reduced.

Comparison of image quality and radiation dose of different scanning methods used for computed tomography of the unilateral shoulder

BACKGROUND

The effect of different computed tomography (CT) scanning methods of the shoulder on image quality is uncertain.

PURPOSE

To compare the effect of different methods of CT scanning of the right shoulder on image quality and radiation dose.

MATERIAL AND METHODS

A total of 30 adults were divided into five groups. Group A received scans centered on the body's long axis, a scout direction of 0° + 90°, and automatic tube current modulation (ATCM). The other four groups (B, C, D, E) received isocenter scans centered on the shoulder with different scout directions (B and C: 0° + 90°, D: 0°, E: 0° + 270°) and tube currents (B: 420 mA; C, D, E: ATCM). The volume CT dose index (CTDI_vol), dose-length product (DLP), image objective noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared. Three subjective measures were also compared (noise, stripe artifacts, diagnostic confidence).

RESULTS

The five groups differed significantly in all subjective and objective indexes. The CTDI_vol and DLP decreased in the order of groups C, A, B, E, and D; the differences between groups A and B were not significant (P > 0.05). Groups B, C, and E had better SNR and CNR than groups A and D (P < 0.01). Subjective evaluations indicated group D was worse than groups B, C, and E (P < 0.05).

CONCLUSION

In the ATCM system that uses the last scout view, CT of the shoulder should use isocenter scanning with the lateral scout view when the tube is away from the long axis of the body as the last execution direction.

Ultra-Low Dose CT Chest in Acute COVID-19 Pneumonia: A Pilot Study from India

The rapid increase in the number of CT acquisitions during the COVID-19 pandemic raised concerns about increased radiation exposure to patients and the resultant radiation-induced health risks. It prompted researchers to explore newer CT techniques like ultra-low dose CT (ULDCT), which could improve patient safety. Our aim was to study the utility of ultra-low dose CT (ULDCT) chest in the evaluation of acute COVID-19 pneumonia with standard-dose CT (SDCT) chest as a reference standard. This was a prospective study approved by the institutional review board. 60 RT-PCR positive COVID-19 patients with valid indication for CT chest underwent SDCT and ULDCT. ULDCT and SDCT were compared in terms of objective (noise and signal-to-noise ratio) and subjective (noise, sharpness, artifacts and diagnostic confidence) image quality, various imaging patterns of COVID-19, CT severity score and effective radiation dose. The sensitivity, specificity, positive and negative predictive value, and diagnostic accuracy of ULDCT for detecting lung lesions were calculated by taking SDCT as a reference standard. The mean age of subjects was 47.2 ± 10.7 years, with 66.67% being men. 90% of ULDCT scans showed no/minimal noise and sharp images, while 93.33% had image quality of high diagnostic confidence. The major imaging findings detected by SDCT were GGOs (90%), consolidation (76.67%), septal thickening (60%), linear opacities (33.33%), crazy-paving pattern (33.33%), nodules (30%), pleural thickening (30%), lymphadenopathy (30%) and pleural effusion (23.33%). Sensitivity, specificity and diagnostic accuracy of ULDCT for detecting most of the imaging patterns were 100% (p < 0.001); except for GGOs (sensitivity: 92.59%, specificity: 100%, diagnostic accuracy: 93.33%), consolidation (sensitivity: 100%, specificity: 71.43%, diagnostic accuracy: 93.33%) and linear opacity (sensitivity: 90.00%, specificity: 100%, diagnostic accuracy: 96.67%). CT severity score (range: 15-25) showed 100% concordance on SDCT and ULDCT, while effective radiation dose was 4.93 ± 1.11 mSv and 0.26 ± 0.024 mSv, respectively. A dose reduction of 94.38 ± 1.7% was achieved with ULDCT. Compared to SDCT, ULDCT chest yielded images of reasonable and comparable diagnostic quality with the advantage of significantly reduced radiation dose; thus, it can be a good alternative to SDCT in the evaluation of COVID-19 pneumonia.

Association of Respiratory Functional Indices and Smoking with Pleural Movement and Mean Lung Density Assessed Using Four-Dimensional Dynamic-Ventilation Computed Tomography in Smokers and Patients with COPD

Purpose

To correlate the ratio of the non-dependent to dependent aspects of the maximal pleural movement vector (MPMV_ND/D) and gravity-oriented collapse ratio (GCR_ND/D), and the mean lung field density (MLD) obtained using four-dimensional (4D) dynamic-ventilation computed tomography (DVCT) with airflow limitation parameters and the Brinkman index.

Materials and Methods

Forty-seven patients, including 22 patients with COPD, 13 non-COPD smokers, and 12 non-smokers, with no/slight pleural adhesion confirmed using a thoracoscope, underwent 4D-DVCT with 16 cm coverage. Coordinates for the lung field center, as well as ventral and dorsal pleural points, set on the central trans-axial levels in the median and para-median sagittal planes at end-inspiration, were automatically measured (13-17 frame images, 0.35 seconds/frame). MPMV_ND/D and GCR_ND/D were calculated based on MPMV and GCR values for all the included points and the lung field center. MLD was automatically measured in each of the time frames, and the maximal change ratio of MLD (MLD_CR) was calculated. These measured values were compared among COPD patients, non-COPD smokers, and non-smokers, and were correlated with the Brinkman index, FEV₁/FVC, FEV₁ predicted, RV/TLC, and FEF_25-75% using Spearman's rank coefficients.

Results

MPMV_ND/D was highest in non-smokers (0.819±0.464), followed by non-COPD smokers (0.405±0.131) and patients with COPD (-0.219±0.900). GCR_ND/D in non-smokers (1.003±1.384) was higher than that in patients with COPD (-0.164±1.199). MLD_CR in non-COPD smokers (0.105±0.028) was higher than that in patients with COPD (0.078±0.027). MPMV_ND/D showed positive correlations with FEV₁ predicted (r=0.397, p=0.006), FEV₁/FVC (r=0.501, p<0.001), and FEF_25-75% (r=0.368, p=0.012). GCR_ND/D also demonstrated positive correlations with FEV₁ (r=0.397, p=0.006), FEV₁/FVC (r=0.445, p=0.002), and FEF_25-75% (r=0.371, p=0.011). MPMV_ND/D showed a negative correlation with the Brinkman index (r=-0.398, p=0.006).

Conclusion

We demonstrated that reduced MPMV_ND/D and GCR_ND/D were associated with respiratory functional indices, in addition to a negative association of MPMV_ND/D with the Brinkman index, which should be recognized when assessing local pleural adhesion on DVCT, especially for ventral pleural aspects.

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.

Agreement between low-dose and ultra-low-dose chest CT for the diagnosis of viral pneumonia imaging patterns during the COVID-19 pandemic

Background

Chest CT scan has an important role in the diagnosis and management of COVID-19 infection. A major concern in radiologic assessment of the patients is the radiation dose. Research has been done to evaluate low-dose chest CT in the diagnosis of pulmonary lesions with promising findings. We decided to determine diagnostic performance of ultra-low-dose chest CT in comparison to low-dose CT for viral pneumonia during the COVID-19 pandemic.

Results

167 patients underwent both low-dose and ultra-low-dose chest CT scans. Two radiologists blinded to the diagnosis independently examined ultra-low-dose chest CT scans for findings consistent with COVID-19 pneumonia. In case of any disagreement, a third senior radiologist made the final diagnosis. Agreement between two CT protocols regarding ground-glass opacity, consolidation, reticulation, and nodular infiltration were recorded. On low-dose chest CT, 44 patients had findings consistent with COVID-19 infection. Ultra-low-dose chest CT had sensitivity and specificity values of 100% and 98.4%, respectively for diagnosis of viral pneumonia. Two patients were falsely categorized to have pneumonia on ultra-low-dose CT scan. Positive predictive value and negative predictive value of ultra-low-dose CT scan were respectively 95.7% and 100%. There was good agreement between low-dose and ultra-low-dose methods (kappa = 0.97; P < 0.001). Perfect agreement between low-dose and ultra-low-dose scans was found regarding diagnosis of ground-glass opacity (kappa = 0.83, P < 0.001), consolidation (kappa = 0.88, P < 0.001), reticulation (kappa = 0.82, P < 0.001), and nodular infiltration (kappa = 0.87, P < 0.001).

Conclusion

Ultra-low-dose chest CT scan is comparable to low-dose chest CT for detection of lung infiltration during the COVID-19 outbreak while maintaining less radiation dose. It can also be used instead of low-dose chest CT scan for patient triage in circumstances where rapid-abundant PCR tests are not available.

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.

Evaluation of Ultra-Low-Dose Chest Computed Tomography Images in Detecting Lung Lesions Related to COVID-19: A Prospective Study

Background

The present study aimed to evaluate the effectiveness of ultra-low-dose (ULD) chest computed tomography (CT) in comparison with the routine dose (RD) CT images in detecting lung lesions related to COVID-19.

Methods

A prospective study was conducted during April-September 2020 at Shahid Faghihi Hospital affiliated with Shiraz University of Medical Sciences, Shiraz, Iran. In total, 273 volunteers with suspected COVID-19 participated in the study and successively underwent RD-CT and ULD-CT chest scans. Two expert radiologists qualitatively evaluated the images. Dose assessment was performed by determining volume CT dose index, dose length product, and size-specific dose estimate. Data analysis was performed using a ranking test and kappa coefficient (κ). P<0.05 was considered statistically significant.

Results

Lung lesions could be detected with both RD-CT and ULD-CT images in patients with suspected or confirmed COVID-19 (κ=1.0, P=0.016). The estimated effective dose for the RD-CT protocol was 22-fold higher than in the ULD-CT protocol. In the case of the ULD-CT protocol, sensitivity, specificity, accuracy, and positive predictive value for the detection of consolidation were 60%, 83%, 80%, and 20%, respectively. Comparably, in the case of RD-CT, these percentages for the detection of ground-glass opacity (GGO) were 62%, 66%, 66%, and 18%, respectively. Assuming the result of real-time polymerase chain reaction as true-positive, analysis of the receiver-operating characteristic curve for GGO detected using the ULD-CT protocol showed a maximum area under the curve of 0.78.

Conclusion

ULD-CT, with 94% dose reduction, can be an alternative to RD-CT to detect lung lesions for COVID-19 diagnosis and follow-up.An earlier preliminary report of a similar work with a lower sample size was submitted to the arXive as a preprint. The preprint is cited as: https://arxiv.org/abs/2005.03347.

Can deep learning improve image quality of low-dose CT: a prospective study in interstitial lung disease

OBJECTIVES

To investigate whether deep learning reconstruction (DLR) could keep image quality and reduce radiation dose in interstitial lung disease (ILD) patients compared with HRCT reconstructed with hybrid iterative reconstruction (hybrid-IR).

METHODS

Seventy ILD patients were prospectively enrolled and underwent HRCT (120 kVp, automatic tube current) and LDCT (120 kVp, 30 mAs) scans. HRCT images were reconstructed with hybrid-IR (Adaptive Iterative Dose Reduction 3-Dimensional [AIDR3D], standard-setting); LDCT images were reconstructed with DLR (Advanced Intelligence Clear-IQ Engine [AiCE], lung/bone, mild/standard/strong setting). Image noise, streak artifact, overall image quality, and visualization of normal and abnormal features of ILD were evaluated.

RESULTS

The mean radiation dose of LDCT was 38% of HRCT. Objective image noise of reconstructed LDCT images was 33.6 to 111.3% of HRCT, and signal-to-noise ratio (SNR) was 0.9 to 3.1 times of the latter (p < 0.001). LDCT-AiCE was not significantly different from or even better than HRCT in overall image quality and visualization of normal lung structures. LDCT-AiCE (lung, mild/standard/strong) showed progressively better recognition of ground glass opacity than HRCT-AIDR3D (p < 0.05, p < 0.01, p < 0.001), and LDCT-AiCE (lung, mild/standard/strong; bone, mild) was superior to HRCT-AIDR3D in visualization of architectural distortion (p < 0.01, p < 0.01, p < 0.01; p < 0.05). LDCT-AiCE (bone, strong) was better than HRCT-AIDR3D in the assessment of bronchiectasis and/or bronchiolectasis (p < 0.05). LDCT-AiCE (bone, mild/standard/strong) was significantly better at the visualization of honeycombing than HRCT-AIDR3D (p < 0.05, p < 0.05, p < 0.01).

CONCLUSION

Deep learning reconstruction could effectively reduce radiation dose and keep image quality in ILD patients compared to HRCT with hybrid-IR.

KEY POINTS

• Deep learning reconstruction was a novel image reconstruction algorithm based on deep convolutional neural networks. It was applied in chest CT studies and received auspicious results. • HRCT plays an essential role in the whole process of diagnosis, treatment efficacy evaluation, and follow-ups for interstitial lung disease patients. However, cumulative radiation exposure could increase the risks of cancer. • Deep learning reconstruction method could effectively reduce the radiation dose and keep the image quality compared with HRCT reconstructed with hybrid iterative reconstruction in patients with interstitial lung disease.

Ultra-low-dose CT versus chest X-ray for patients suspected of pulmonary disease at the emergency department: a multicentre randomised clinical trial

BACKGROUND

Chest CT displays chest pathology better than chest X-ray (CXR). We evaluated the effects on health outcomes of replacing CXR by ultra-low-dose chest-CT (ULDCT) in the diagnostic work-up of patients suspected of non-traumatic pulmonary disease at the emergency department.

METHODS

Pragmatic, multicentre, non-inferiority randomised clinical trial in patients suspected of non-traumatic pulmonary disease at the emergency department. Between 31 January 2017 and 31 May 2018, every month, participating centres were randomly allocated to using ULDCT or CXR. Primary outcome was functional health at 28 days, measured by the Short Form (SF)-12 physical component summary scale score (PCS score), non-inferiority margin was set at 1 point. Secondary outcomes included hospital admission, hospital length of stay (LOS) and patients in follow-up because of incidental findings.

RESULTS

2418 consecutive patients (ULDCT: 1208 and CXR: 1210) were included. Mean SF-12 PCS score at 28 days was 37.0 for ULDCT and 35.9 for CXR (difference 1.1; 95% lower CI: 0.003). After ULDCT, 638/1208 (52.7%) patients were admitted (median LOS of 4.8 days; IQR 2.1-8.8) compared with 659/1210 (54.5%) patients after CXR (median LOS 4.6 days; IQR 2.1-8.8). More ULDCT patients were in follow-up because of incidental findings: 26 (2.2%) versus 4 (0.3%).

CONCLUSIONS

Short-term functional health was comparable between ULDCT and CXR, as were hospital admissions and LOS, but more incidental findings were found in the ULDCT group. Our trial does not support routine use of ULDCT in the work-up of patients suspected of non-traumatic pulmonary disease at the emergency department.

TRIAL REGISTRATION NUMBER

NTR6163.

Liver Attenuation Assessment in Reduced Radiation Chest Computed Tomography

OBJECTIVE

This study aimed to evaluate the reliability of liver and spleen Hounsfield units (HU) measurements in reduced radiation computed tomography (RRCT) of the chest within the sub-millisievert range.

METHODS

We performed a prospective, institutional review board-approved study of accrued patients who underwent unenhanced normal-dose chest CT (NDCT) and with an average radiation dose of less than 5% of NDCT. In-house artificial intelligence-based denoising methods produced 2 denoised RRCT (dRRCT) series. Hepatic and splenic attenuations were measured on all 4 series: NDCT, RRCT, dRRCT1, and dRRCT2. Statistical analyses assessed the differences between the HU measurements of the liver and spleen in RRCTs and NDCT. As a test case, we assessed the performance of RRCTs for fatty liver detection, considering NDCT to be the reference standard.

RESULTS

Wilcoxon test compared liver and spleen attenuation in the 72 patients included in our cohort. The liver attenuation in NDCT (median, 59.38 HU; interquartile range, 55.00-66.06 HU) was significantly different from the attenuation in RRCT, dRRCT1, and dRRCT2 (median, 63.63, 42.00, and 33.67 HU; interquartile range, 56.19-67.19, 37.33-45.83, and 30.33-38.50 HU, respectively), all with a P value <0.01. Six patients (8.3%) were considered to have fatty liver on NDCT. The specificity, sensitivity, and accuracy of fatty liver detection by RRCT were greater than 98.5%, 50%, and 94.3%, respectively.

CONCLUSIONS

Attenuation measurements were significantly different between NDCT and RRCTs, but may still have diagnostic value in appreciating hepatosteastosis. Abdominal organ attenuation on RRCT protocols may differ from attenuation on NDCT and should be validated when new low-dose protocols are used.

1-year radiological, functional and quality-of-life outcomes in patients with SARS-CoV-2 pneumonia - A prospective observational study

All over the world, SARS-CoV-2 pneumonia is causing a significant short and medium-term morbidity and mortality, with reported persisting symptoms, radiological and lung alterations up to 6 months after symptoms onset. Nevertheless, the 1-year impact on affected patients is still poorly known. In this prospective observational study, 39 patients with SARS-CoV-2 pneumonia were recruited from a single COVID-19 hospital in Southern Switzerland. They underwent a 3-month and 1-year follow-ups. At 1 year, 38 patients underwent functional follow-up through lung function tests and six minutes walking test and submitted SF-12 and SGRQ questionnaires about health-related quality of life. At 1 year most of the patients showed a persistence of the radiological and functional abnormalities and a reduction of the health-related quality of life. Thirty patients (96.8%) still presented some residual abnormalities on CT scans (31 patients at 3 months), though with a general reduction of the lesional load in all lung lobes. Twenty patients (52.6%) had persisting lung function tests impairment, with an overall improvement of DLCO. As concerning the functional status, lowest SpO2 during 6MWT increased significantly. Finally, 19 patients (50%) reported a pathological St. George’s Respiratory Questionnaire, and respectively 12 (31.6%) and 11 (28.9%) patients a pathological Short Form Survey-12 in physical and mental components. At 1-year follow-up SARS-CoV-2 pneumonia survivors still present a substantial impairment in radiological and functional findings and in health-related quality of life, despite showing a progressive recovery.

Detection of pulmonary nodules with scoutless fixed-dose ultra-low-dose CT: a prospective study

OBJECTIVES

To determine the accuracy of scoutless, fixed-dose ultra-low-dose (ULD) CT compared to standard-dose (SD) CT for pulmonary nodule detection and semi-automated nodule measurement, across different patient sizes.

METHODS

Sixty-three patients underwent ULD and SD CT. Two readers examined all studies visually and with computer-aided detection (CAD). Nodules detected on SD CT were included in the reference standard by consensus and stratified into 4 categories (nodule category, NODCAT) from the Dutch-Belgian Lung Cancer Screening trial (NELSON). Effects of NODCAT and patient size on nodule detection were determined. For each nodule, volume and diameter were compared between both scans.

RESULTS

The reference standard comprised 173 nodules. For both readers, detection rates on ULD versus SD CT were not significantly different for NODCAT 3 and 4 nodules > 50 mm³ (reader 1: 93% versus 89% (p = 0.257); reader 2: 96% versus 98% (p = 0.317)). For NODCAT 1 and 2 nodules < 50 mm³, detection rates on ULD versus SD CT dropped significantly (reader 1: 66% versus 80% (p = 0.023); reader 2: 77% versus 87% (p = 0.039)). Body mass index and chest circumference did not influence nodule detectability (p = 0.229 and p = 0.362, respectively). Calculated volumes and diameters were smaller on ULD CT (p < 0.0001), without altering NODCAT (84% agreement).

CONCLUSIONS

Scoutless ULD CT reliably detects solid lung nodules with a clinically relevant volume (> 50 mm³) in lung cancer screening, irrespective of patient size. Since detection rates were lower compared to SD CT for nodules < 50 mm³, its use for lung metastasis detection should be considered on a case-by-case basis.

KEY POINTS

• Detection rates of pulmonary nodules > 50 mm³are not significantly different between scoutless ULD and SD CT (i.e. volumes clinically relevant in lung cancer screening based on the NELSON trial), but were different for the detection of nodules < 50 mm³(i.e. volumes still potentially relevant in lung metastasis screening). • Calculated nodule volumes were on average 0.03 mL or 9% smaller on ULD CT, which is below the 20-25% interscan variability previously reported with software-based volumetry. • Even though a scoutless, fixed-dose ULD CT protocol was used (CTDI_vol0.15 mGy), pulmonary nodule detection was not influenced by patient size.

Personalized Chest Computed Tomography: Minimum Diagnostic Radiation Dose Levels for the Detection of Fibrosis, Nodules, and Pneumonia

OBJECTIVES

The purpose of this study was to evaluate the minimum diagnostic radiation dose level for the detection of high-resolution (HR) lung structures, pulmonary nodules (PNs), and infectious diseases (IDs).

MATERIALS AND METHODS

A preclinical chest computed tomography (CT) trial was performed with a human cadaver without known lung disease with incremental radiation dose using tin filter-based spectral shaping protocols. A subset of protocols for full diagnostic evaluation of HR, PN, and ID structures was translated to clinical routine. Also, a minimum diagnostic radiation dose protocol was defined (MIN). These protocols were prospectively applied over 5 months in the clinical routine under consideration of the individual clinical indication. We compared radiation dose parameters, objective and subjective image quality (IQ).

RESULTS

The HR protocol was performed in 38 patients (43%), PN in 21 patients (24%), ID in 20 patients (23%), and MIN in 9 patients (10%). Radiation dose differed significantly among HR, PN, and ID (5.4, 1.2, and 0.6 mGy, respectively; P < 0.001). Differences between ID and MIN (0.2 mGy) were not significant (P = 0.262). Dose-normalized contrast-to-noise ratio was comparable among all groups (P = 0.087). Overall IQ was perfect for the HR protocol (median, 5.0) and decreased for PN (4.5), ID-CT (4.3), and MIN-CT (2.5). The delineation of disease-specific findings was high in all dedicated protocols (HR, 5.0; PN, 5.0; ID, 4.5). The MIN protocol had borderline IQ for PN and ID lesions but was insufficient for HR structures. The dose reductions were 78% (PN), 89% (ID), and 97% (MIN) compared with the HR protocols.

CONCLUSIONS

Personalized chest CT tailored to the clinical indications leads to substantial dose reduction without reducing interpretability. More than 50% of patients can benefit from such individual adaptation in a clinical routine setting. Personalized radiation dose adjustments with validated diagnostic IQ are especially preferable for evaluating ID and PN lesions.

Automatic Segmentation of Bone Selective MR Images for Visualization and Craniometry of the Cranial Vault

RATIONALE AND OBJECTIVES

Solid-state MRI has been shown to provide a radiation-free alternative imaging strategy to CT. However, manual image segmentation to produce bone-selective MR-based 3D renderings is time and labor intensive, thereby acting as a bottleneck in clinical practice. The objective of this study was to evaluate an automatic multi-atlas segmentation pipeline for use on cranial vault images entirely circumventing prior manual intervention, and to assess concordance of craniometric measurements between pipeline produced MRI and CT-based 3D skull renderings.

MATERIALS AND METHODS

Dual-RF, dual-echo, 3D UTE pulse sequence MR data were obtained at 3T on 30 healthy subjects along with low-dose CT images between December 2018 to January 2020 for this prospective study. The four-point MRI datasets (two RF pulse widths and two echo times) were combined to produce bone-specific images. CT images were thresholded and manually corrected to segment the cranial vault. CT images were then rigidly registered to MRI using mutual information. The corresponding cranial vault segmentations were then transformed to MRI. The "ground truth" segmentations served as reference for the MR images. Subsequently, an automated multi-atlas pipeline was used to segment the bone-selective images. To compare manually and automatically segmented MR images, the Dice similarity coefficient (DSC) and Hausdorff distance (HD) were computed, and craniometric measurements between CT and automated-pipeline MRI-based segmentations were examined via Lin's concordance coefficient (LCC).

RESULTS

Automated segmentation reduced the need for an expert to obtain segmentation. Average DSC was 90.86 ± 1.94%, and average 95th percentile HD was 1.65 ± 0.44 mm between ground truth and automated segmentations. MR-based measurements differed from CT-based measurements by 0.73-1.2 mm on key craniometric measurements. LCC for distances between CT and MR-based landmarks were vertex-basion: 0.906, left-right frontozygomatic suture: 0.780, and glabella-opisthocranium: 0.956 for the three measurements.

CONCLUSION

Good agreement between CT and automated MR-based 3D cranial vault renderings has been achieved, thereby eliminating the laborious manual segmentation process. Target applications comprise craniofacial surgery as well as imaging of traumatic injuries and masses involving both bone and soft tissue.

Photon Starvation Artifact Reduction by Shift-Variant Processing

The x-ray computed tomography (CT) images with low dose are noisy and may contain photon starvation artifacts. The artifacts are location and direction dependent. Therefore, the common shift-invariant denoising filters do not work well. The state-of-the-art methods to process the low-dose CT images are image reconstruction based; they require the raw projection data. In many situations, the raw CT projections are not accessible. This paper suggests a method to denoise the low-dose CT image using the pseudo projections generated by the application of a forward projector on the low-dose CT image. The feasibility of the proposed method is demonstrated by real clinical data.

Pragmatic approaches to reducing radiation dose in brain computed tomography scan using scan parameter modification

Background:

High radiation dose of patients has become a concern in the computed tomography (CT) examinations. The aim of this study is to guide the radiology technician in modifying or optimizing the underlying parameters of the CT scan to reduce the patient radiation dose and produce an acceptable image quality for diagnosis.

Methods:

The body mass measurement device phantom was repeatedly scanned by changing the scan parameters. To analyze the image quality, software-based and observer-based evaluations were employed. To study the effect of scan parameters such as slice thickness and reconstruction filter on image quality and radiation dose, the structural equation modeling was used.

Results:

By changing the reconstruction filter from standard to soft and slice thickness from 2.5 mm to 5 mm, low-contrast resolution did not change significantly. In addition, by increasing the slice thickness and changing the reconstruction filter, the spatial resolution at different radiation conditions did not significantly differ from the standard irradiation conditions (P > 0.05).

Conclusion:

In this study, it was shown that in the brain CT scan imaging, the radiation dose was reduced by 30%–50% by increasing the slice thickness or changing the reconstruction filter. It is necessary to adjust the CT scan protocols according to clinical requirements or the special conditions of some patients while maintaining acceptable image quality.

Ultra-low-dose chest CT protocol during the second wave of COVID-19 pandemic: a double-observer prospective study on 250 patients to evaluate its detection accuracy

Background

While the second wave of COVID-19 pandemic almost reached its climax, unfortunately, new viral strains are rapidly spreading, and numbers of infected young adults are rising. Consequently, chest high-resolution computed tomography (HRCT) demands are increasing, regarding patients’ screening, initial evaluation and follow up. This study aims to evaluate the detection accuracy of ultra-low-dose chest CT in comparison with the routine low-dose chest CT to reduce the irradiation exposure hazards.

Results

This study was prospectively conducted on 250 patients during the period from 15th December 2020 to 10th February 2021. All of the included patients were clinically suspected of COVID-19 infection. All patients were subjected to routine low-dose (45 mAs) and ultra-low-dose (22 mAs) chest CT examinations. Finally, all patients had confirmatory PCR swab tests and other dedicated laboratory tests. They included 149 males and 101 females (59.6%:40.4%). Their age ranged from 16 to 84 years (mean age 50 ± 34 SD). Patients were divided according to body weight; 104 patients were less than 80 kg, and 146 patients were more than 80 kg. HRCT findings were examined by two expert consultant radiologists independently, and data analysis was performed by other two expert specialist and consultant radiologists. The inter-observer agreement (IOA) was excellent (96–100%). The ultra-low-dose chest CT reached 93.53–96.84% sensitivity and 90.38–93.84% accuracy. The signal-to-noise ratio (SNR) is 12.8:16.1; CTDIvol (mGy) = 1.1 ± 0.3, DLP (mGy cm) = 42.2 ± 7.9, mean effective dose (mSv/mGy cm) = 0.59 and absolute cancer risk = 0.02 × 10^-4.

Conclusion

Ultra-low-dose HRCT can be reliably used during the second wave of COVID-19 pandemic to reduce the irradiation exposure hazards.

Diagnostic yield, safety, and advantages of ultra-low dose chest CT compared to chest radiography in early stage suspected SARS-CoV-2 pneumonia: A retrospective observational study

ABSTRACT

To determine the role of ultra-low dose chest computed tomography (uld CT) compared to chest radiographs in patients with laboratory-confirmed early stage SARS-CoV-2 pneumonia.Chest radiographs and uld CT of 12 consecutive suspected SARS-CoV-2 patients performed up to 48 hours from hospital admission were reviewed by 2 radiologists. Dosimetry and descriptive statistics of both modalities were analyzed.On uld CT, parenchymal abnormalities compatible with SARS-CoV-2 pneumonia were detected in 10/12 (83%) patients whereas on chest X-ray in, respectively, 8/12 (66%) and 5/12 (41%) patients for reader 1 and 2. The average increment of diagnostic performance of uld CT compared to chest X-ray was 29%. The average effective dose was, respectively, of 0.219 and 0.073 mSv.Uld CT detects substantially more lung injuries in symptomatic patients with suspected early stage SARS-CoV-2 pneumonia compared to chest radiographs, with a significantly better inter-reader agreement, at the cost of a slightly higher equivalent radiation dose.

Low Dose Chest CT and Lung Ultrasound for the Diagnosis and Management of COVID-19

BACKGROUND

The COVID-19 pandemic has provided an opportunity to use low- and non-radiating chest imaging techniques on a large scale in the context of an infectious disease, which has never been done before. Previously, low-dose techniques were rarely used for infectious diseases, despite the recognised danger of ionising radiation.

METHOD

To evaluate the role of low-dose computed tomography (LDCT) and lung ultrasound (LUS) in managing COVID-19 pneumonia, we performed a review of the literature including our cases.

RESULTS

Chest LDCT is now performed routinely when diagnosing and assessing the severity of COVID-19, allowing patients to be rapidly triaged. The extent of lung involvement assessed by LDCT is accurate in terms of predicting poor clinical outcomes in COVID-19-infected patients. Infectious disease specialists are less familiar with LUS, but this technique is also of great interest for a rapid diagnosis of patients with COVID-19 and is effective at assessing patient prognosis.

CONCLUSIONS

COVID-19 is currently accelerating the transition to low-dose and "no-dose" imaging techniques to explore infectious pneumonia and their long-term consequences.

Clinical, radiological and functional outcomes in patients with SARS-CoV-2 pneumonia: a prospective observational study

BACKGROUND

All over the world, SARS-CoV-2 pneumonia is causing a significant short-term morbidity and mortality, but the medium-term impact on lung function and quality of life of affected patients are still unknown.

METHODS

In this prospective observational study, 39 patients with SARS-CoV-2 pneumonia were recruited from a single COVID-19 hospital in Southern Switzerland. At three months patients underwent radiological and functional follow-up through CT scan, lung function tests, and 6 min walking test. Furthermore, quality of life was assessed through self-reported questionnaires.

RESULTS

Among 39 patients with SARS-CoV-2 pneumonia, 32 (82% of all participants) presented abnormalities in CT scan and 25 (64.1%) had lung function tests impairment at three months. Moreover, 31 patients (79.5%) reported a perception of poor health due to respiratory symptoms and all 39 patients showed an overall decreased quality of life.

CONCLUSIONS

Medium-term follow up at three months of patients diagnosed with SARS-CoV-2 pneumonia shows the persistence of abnormalities in CT scans, a significant functional impairment assessed by lung function tests and a decreased quality of life in affected patients. Further studies evaluating the long-term impact are warranted to guarantee an appropriate follow-up to patients recovering from SARS-CoV-2 pneumonia.

Comparison of conventional chest x ray with a novel projection technique for ultra-low dose CT

PURPOSE

To compare a novel thick-slab projection technique for ultra-low dose computed tomography (CT; thoracic tomogram) with conventional chest x ray with respect to 13 diagnostic categories.

METHODS

With the approval of the institutional ethics board, a dataset was retrospectively collected of 22 consecutive patients who had undergone a clinically requested emergency room conventional chest x ray (CXR) and a same-day standard-of-care non-contrast CT. Scanner specific noise was added to the CT images to simulate a target dose of 0.18 mSv. A novel algorithm was used to post-process CT images as coronal isotropic reformats by applying a voxel-based, locally normalized weighted-intensity projection to generate 2 cm thick slabs with 1 cm overlap. Three chest radiologists with no prior training for the study reviewed the CXR and thoracic tomogram for each case and assessed each diagnostic category (pneumonic infiltrates, pulmonary edema, interstitial lung disease, nodules > 5 mm, nodules < 5 mm, pleural effusion, pericardial effusion, heart size, acute bone fractures, foreign bodies, pneumothorax, mediastinal vessel diameter, free abdominal air) on a Likert scale from -4 (definitely absent/normal) to +4 (definitely present/abnormal). MRMC ROC curves were generated for each category. Time for interpretation and subjective image quality score (0-10) were also assessed.

RESULTS

For focal lung disease (pneumonic infiltrates, nodules < 5 mm, nodules > 5mm), the area under the ROC curve (AUC) was significantly higher for thoracic tomograms than CXR (0.803 vs 0.648, respectively, P = 0.02). For non-focal lung disease (pulmonary edema, interstitial lung disease) and effusions (pulmonary, pericardial), the AUC was larger for thoracic tomograms than CXR but the difference did not reach significance (0.870 vs 0.833, P = 0.141; and 0.823 vs 0.752, P = 0.296, respectively). For acute bone fractures and foreign bodies, the AUC was smaller for thoracic tomograms than CXR, the difference was however not significant (0.491 vs 0.532, P = 0.42; and 0.871 vs 0.971, P = 0.39, respectively). Other diagnostic categories had no true positive cases in the dataset. The mean time for interpretation for each was 36.9 and 24.0 s with standard deviations of 0.857 and 5.977. The image quality score for each was 8.2 and 7.8 with standard deviations of 0.970 and 1.614.

CONCLUSION

Thoracic tomograms were found to be diagnostically superior to CXR for focal lung disease, at no increased radiation dose. The thoracic tomogram presents an opportunity to improve the standard-of-care for patients who would otherwise receive a conventional CXR.

The future of CT: deep learning reconstruction

There have been substantial advances in computed tomography (CT) technology since its introduction in the 1970s. More recently, these advances have focused on image reconstruction. Deep learning reconstruction (DLR) is the latest complex reconstruction algorithm to be introduced, which harnesses advances in artificial intelligence (AI) and affordable supercomputer technology to achieve the previously elusive triad of high image quality, low radiation dose, and fast reconstruction speeds. The dose reductions achieved with DLR are redefining ultra-low-dose into the realm of plain radiographs whilst maintaining image quality. This review aims to demonstrate the advantages of DLR over other reconstruction methods in terms of dose reduction and image quality in addition to being able to tailor protocols to specific clinical situations. DLR is the future of CT technology and should be considered when procuring new scanners.

Dosimetry and Comparison between Different CT Protocols (Low Dose, Ultralow Dose, and Conventional CT) for Lung Nodules' Detection in a Phantom

Background

The effects of dose reduction in lung nodule detection need better understanding.

Purpose

To compare the detection rate of simulated lung nodules in a chest phantom using different computed tomography protocols, low dose (LD), ultralow dose (ULD), and conventional (CCT), and to quantify their respective amount of radiation.

Materials and Methods

A chest phantom containing 93 simulated lung nodules was scanned using five different protocols: ULD (80 kVp/30 mA), LD A (120 kVp/20 mA), LD B (100 kVp/30 mA), LD C (120 kVp/30 mA), and CCT (120 kVp/automatic mA). Four chest radiologists analyzed a selected image from each protocol and registered in diagrams the nodules they detected. Kruskal-Wallis and McNemar's tests were performed to determine the difference in nodule detection. Equivalent doses were estimated by placing thermoluminescent dosimeters on the surface and inside the phantom.

Results

There was no significant difference in lung nodules' detection when comparing ULD and LD protocols (p=0.208 to p=1.000), but there was a significant difference when comparing each one of those against CCT (p < 0.001). The detection rate of nodules with CT attenuation values lower than -600 HU was also different when comparing all protocols against CCT (p < 0.001 to p=0.007). There was at least moderate agreement between observers in all protocols (κ-value >0.41). Equivalent dose values ranged from 0.5 to 9 mSv.

Conclusion

There is no significant difference in simulated lung nodules' detection when comparing ULD and LD protocols, but both differ from CCT, especially when considering lower-attenuating nodules.

Image quality of ultralow-dose chest CT using deep learning techniques: potential superiority of vendor-agnostic post-processing over vendor-specific techniques

OBJECTIVE

To compare the image quality between the vendor-agnostic and vendor-specific algorithms on ultralow-dose chest CT.

METHODS

Vendor-agnostic deep learning post-processing model (DLM), vendor-specific deep learning image reconstruction (DLIR, high level), and adaptive statistical iterative reconstruction (ASiR, 70%) algorithms were employed. One hundred consecutive ultralow-dose noncontrast CT scans (CTDI_vol; mean, 0.33 ± 0.056 mGy) were reconstructed with five algorithms: DLM-stnd (standard kernel), DLM-shrp (sharp kernel), DLIR, ASiR-stnd, and ASiR-shrp. Three thoracic radiologists blinded to the reconstruction algorithms reviewed five sets of 100 images and assessed subjective noise, spatial resolution, distortion artifact, and overall image quality. They selected the most preferred algorithm among five image sets for each case. Image noise and signal-to-noise ratio were measured. Edge-rise-distance was measured at a pulmonary vessel, i.e., the distance between two points where attenuation was 10% and 90% of maximal intravascular intensity. The skewness of attenuation was calculated in homogeneous areas.

RESULTS

DLM-stnd, followed by DLIR, showed the best subjective noise on both lung and mediastinal windows, while DLIR yielded the least measured noise (ps < .0001). Compared to DLM-stnd, DLIR showed inferior subjective spatial resolution on lung window and higher edge-rise-distance (ps < .0001). Additionally, DLIR showed the most frequent distortion artifacts and deviated skewness (ps < .0001). DLM-stnd scored the best overall image quality, followed by DLM-shrp and DLIR (mean score 3.89 ± 0.19, 3.68 ± 0.24, and 3.53 ± 0.33; ps < .001). Two among three readers preferred DLM-stnd on both windows.

CONCLUSION

Although DLIR provided the best quantitative noise profile, DLM-stnd showed the best overall image quality with fewer artifacts and was preferred by two among three readers.

KEY POINTS

• A vendor-agnostic deep learning post-processing algorithm applied to ultralow-dose chest CT exhibited the best image quality compared to vendor-specific deep learning algorithm and ASiR techniques. • Two out of three readers preferred a vendor-agnostic deep learning post-processing algorithm in comparison to vendor-specific deep learning algorithm and ASiR techniques. • A vendor-specific deep learning reconstruction algorithm yielded the least image noise, but showed significantly more frequent specific distortion artifacts and increased skewness of attenuation compared to a vendor-agnostic algorithm.

Dosimetric and radiation cancer risk evaluation of high resolution thorax CT during COVID-19 outbreak

PURPOSE

The aim of this work was to evaluate the dosimetric impact of high-resolution thorax CT during COVID-19 outbreak in the University Hospital of Parma. In two months we have performed a huge number of thorax CT scans collecting effective and equivalent organ doses and evaluating also the lifetime attributable risk (LAR) of lung and other major cancers.

MATERIALS AND METHOD

From February 24th to April 28th, 3224 high-resolution thorax CT were acquired. For all patients we have examined the volumetric computed tomography dose index (CTDIvol), the dose length product (DLP), the size-specific dose estimate (SSDE) and effective dose (E103) using a dose tracking software (Radimetrics Bayer HealthCare). From the equivalent dose to organs for each patient, LAR for lung and major cancers were estimated following the method proposed in BEIR VII which considers age and sex differences.

RESULTS

Study population included 3224 patients, 1843 male and 1381 female, with an average age of 67 years. The average CTDIvol, SSDE and DLP, and E103 were 6.8 mGy, 8.7 mGy, 239 mGy·cm and 4.4 mSv respectively. The average LAR of all solid cancers was 2.1 cases per 10,000 patients, while the average LAR of leukemia was 0.2 cases per 10,000 patients. For both male and female the organ with a major cancer risk was lung.

CONCLUSIONS

Despite the impressive increment in thoracic CT examinations due to COVID-19 outbreak, the high resolution low dose protocol used in our hospital guaranteed low doses and very low risk estimation in terms of LAR.

Diagnosis of COVID-19: facts and challenges

At the end of 2019, the novel coronavirus disease 2019 (COVID-19) emerged in Wuhan, China, then spread rapidly across the country and throughout the world. The causative agent is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); according to the International Committee on Taxonomy of Viruses, this virus has a nucleic acid sequence that is different from other known coronaviruses but has some similarity to the beta coronavirus identified in bats. Coronaviruses are a large virus group of enveloped positive-sense single-stranded RNA. They are divided into four genera-alpha, beta, delta and gamma-and alpha and beta coronaviruses are known to infect humans. Rapid and early diagnosis of COVID-19 is a challenging issue for physicians and other healthcare personnel. The sensitivity and specificity of the clinical, radiologic and laboratory tests used to diagnose COVID-19 are variable and largely differ in efficacy depending on the disease's stage of presentation.

Single spectrum three-material decomposition with grating-based x-ray phase-contrast CT

Grating-based x-ray phase-contrast imaging provides three simultaneous image channels originating from a single image acquisition. While the phase signal provides direct access to the electron density in tomography, there is additional information on sub-resolutional structural information which is called dark-field signal in analogy to optical microscopy. The additional availability of the conventional attenuation image qualifies the method for implementation into existing diagnostic routines. The simultaneous access to the attenuation coefficient and the electron density allows for quantitative two-material discrimination as demonstrated lately for measurements at a quasi-monochromatic compact synchrotron source. Here, we investigate the transfer of the method to conventional polychromatic x-ray sources and the additional inclusion of the dark-field signal for three-material decomposition. We evaluate the future potential of grating-based x-ray phase-contrast CT for quantitative three-material discrimination for the specific case of early stroke diagnosis at conventional polychromatic x-ray sources. Compared to conventional CT, the method has the potential to discriminate coagulated blood directly from contrast agent extravasation within a single CT acquisition. Additionally, the dark-field information allows for the clear identification of hydroxyapatite clusters due to their micro-structure despite a similar attenuation as the applied contrast agent. This information on materials with sub-resolutional microstructures is considered to comprise advantages relevant for various pathologies.

Low-dose chest CT and the impact on nodule visibility

INTRODUCTION

The need to continually optimise CT protocols is essential to ensure the lowest possible radiation dose for the clinical task and individual patient. The aim of this study was to explore the effect of reducing effective mAs on nodule detection and radiation dose across six scanners.

METHODS

An anthropomorphic chest phantom was scanned using a low-dose chest CT protocol, with the effective mAs lowered to the lowest permissible level. All other acquisition parameters remained consistent. Images were evaluated by five radiologists to determine their sensitivity in detecting six simulated nodules within the phantom. Image noise was calculated together with DLP.

RESULTS

The lowest possible mAs achievable ranged from 7 to 19 mAs. The two highest mAs setting (17 mAs + 19 mAs) had kV modulation enabled (100 kV instead of 120 kV) which consequently resulted in a higher nodule detection rate. Overall nodule detection averaged at 91% (range 80-97%). Out of a possible 180 nodules, 16 were missed, with 12 of those 16 being the same nodule. Noise was double for the Somatom Sensation scanner when compared to the others; however, this scanner did not have iterative reconstruction and it was installed over 10 years ago. There was a strong correlation between image noise and scanner age.

CONCLUSION

This study highlighted that nodules can be detected at very low effective mAs (<20 mAs) but only when other acquisition parameters are optimised i.e. iterative reconstruction and kV modulation. Nodule detection rates were affected by nodule location and image noise.

IMPLICATIONS FOR PRACTICE

This study consolidates previous findings on how to successfully optimise low-dose chest CT. It also highlights the difficulty with standardisation owing to factors such as scanner age and different vendor attributes.

Comparison between CT and MRI in detection of metastasis of the retroperitoneum in testicular germ cell tumors: a prospective trial

Introduction: To minimize the radiation exposure of mostly young testicular cancer patients, it is essential to find out whether CT could be replaced by magnetic resonance imaging (MRI) in the staging and follow-up of the patients. In this trial, we examined whether abdominal MRI is as effective as computed tomography (CT) in the detection of retroperitoneal metastases of testicular cancer.Material and methods: This prospective study included 50 patients, 46 cases of retroperitoneal metastases and 4 controls without abdominal metastases (mean age 33, 5 years, range 20-65 years). Imaging of the retroperitoneum was performed using CT and 1.5 T MRI with diffusion weighted imaging (DWI). One experienced radiologist re-analyzed all of the examinations without knowledge of clinical information. All metastatic or suspicious lymph nodes were noted and measured two-dimensionally from axial images. Nodal detection and the size of detected nodes on CT and MRI were compared.Results: There was no significant difference in the detection of retroperitoneal metastasis between CT and MRI. The sensitivity of MRI was 0.98. There was no statistically significant difference in the sizes of lymph nodes found in CT and MRI, and even very small lymph nodes could be detected in MRI as well as in CT.Conclusion: MRI with DWI is as good as CT in detection of retroperitoneal lymph node metastases regardless of lymph node size, and it can be used as part of follow-up of testicular cancer patients instead of ionizing radiation producing imaging methods.

OPTimal IMAging strategy in patients suspected of non-traumatic pulmonary disease at the emergency department: chest X-ray or ultra-low-dose chest CT (OPTIMACT) trial-statistical analysis plan

Background

A chest X-ray is a standard imaging procedure in the diagnostic work-up of patients suspected of having non-traumatic pulmonary disease. Compared to a chest X-ray, an ultra-low-dose (ULD) chest computed tomography (CT) scan provides substantially more detailed information on pulmonary conditions. To what extent this translates into an improvement in patient outcomes and health care efficiency is yet unknown. The OPTimal IMAging strategy in patients suspected of non-traumatic pulmonary disease at the emergency department: chest X-ray or ultra-low-dose chest CT (OPTIMACT) study is a multicenter, pragmatic, non-inferiority randomized controlled trial designed to evaluate replacement of chest X-ray by ULD chest CT in the diagnostic work-up of such patients, in terms of patient-related health outcomes and costs. During randomly assigned periods of 1 calendar month, either conventional chest X-ray or ULD chest CT scan was used as the imaging strategy. This paper presents in detail the statistical analysis plan of the OPTIMACT trial, developed prior to data analysis.

Methods/results

Functional health at 28 days is the primary clinical outcome. Functional health at 28 days is measured by the physical component summary scale of the Short Form (SF)-12 questionnaire version 1. Secondary outcomes are mental health (mental component summary scale of the SF-12), length of hospital stay, mortality within 28 days, quality-adjusted life year equivalent during the first 28 days (derived from the EuroQol five-dimension, five-level instrument), correct diagnoses at emergency department discharge as compared to the final post hoc diagnosis at day 28, number of patients in follow-up because of incidental findings on chest X-ray or ULD chest CT, and health care costs.

Conclusions

After this pragmatic trial we will have precise estimates of the effectiveness of replacing chest X-ray with ULD chest CT in terms of patient-related health outcomes and costs.

Trial registration

Netherlands National Trial Register: NTR6163. Registered on 6 December 2016.