Impact of beam collimation of z-overscanning on dose to the lens and thyroid gland in paediatric thoracic computed tomography imaging.

BACKGROUND: Adaptive collimation reduces the dose deposited outside the imaged volume along the z-axis. An increase in the dose deposited outside the imaged volume (to the lens and thyroid) in the z-axis direction is a concern in paediatric computed tomography (CT). OBJECTIVE: To compare the dose deposited outside the imaged volume (to the lens and thyroid) between 40-mm and 80-mm collimation during thoracic paediatric helical CT. MATERIALS AND METHODS: We used anthropomorphic phantoms of newborns and 5-year-olds with 40-mm and 80-mm collimation during helical CT. We compared the measured dose deposited outside the imaged volume using optically stimulated luminescence dosimeters (OSLD) at the surfaces of the lens and thyroid and the image noise between the 40-mm and 80-mm collimations. RESULTS: There were significant differences in the dose deposited outside the imaged volume (to the lens and thyroid) between the 40-mm and 80-mm collimations for both phantoms (P < 0.01). CONCLUSION: Compared with that observed for 80-mm collimation in helical CT scans of the paediatric thorax, the dose deposited outside the imaged volume (to the lens and thyroid) was significantly lower in newborns and 5-year-olds with 40-mm collimation.

The Role of Chest Imaging in Patient Management during the COVID-19 Pandemic: A Multinational Consensus Statement from the Fleischner Society.

With more than 900 000 confirmed cases worldwide and nearly 50 000 deaths during the first 3 months of 2020, the coronavirus disease 2019 (COVID-19) pandemic has emerged as an unprecedented health care crisis. The spread of COVID-19 has been heterogeneous, resulting in some regions having sporadic transmission and relatively few hospitalized patients with COVID-19 and others having community transmission that has led to overwhelming numbers of severe cases. For these regions, health care delivery has been disrupted and compromised by critical resource constraints in diagnostic testing, hospital beds, ventilators, and health care workers who have fallen ill to the virus exacerbated by shortages of personal protective equipment. Although mild cases mimic common upper respiratory viral infections, respiratory dysfunction becomes the principal source of morbidity and mortality as the disease advances. Thoracic imaging with chest radiography and CT are key tools for pulmonary disease diagnosis and management, but their role in the management of COVID-19 has not been considered within the multivariable context of the severity of respiratory disease, pretest probability, risk factors for disease progression, and critical resource constraints. To address this deficit, a multidisciplinary panel comprised principally of radiologists and pulmonologists from 10 countries with experience managing patients with COVID-19 across a spectrum of health care environments evaluated the utility of imaging within three scenarios representing varying risk factors, community conditions, and resource constraints. Fourteen key questions, corresponding to 11 decision points within the three scenarios and three additional clinical situations, were rated by the panel based on the anticipated value of the information that thoracic imaging would be expected to provide. The results were aggregated, resulting in five main and three additional recommendations intended to guide medical practitioners in the use of chest radiography and CT in the management of COVID-19.

Machine-learning classification of texture features of portable chest X-ray accurately classifies COVID-19 lung infection.

BACKGROUND: The large volume and suboptimal image quality of portable chest X-rays (CXRs) as a result of the COVID-19 pandemic could post significant challenges for radiologists and frontline physicians. Deep-learning artificial intelligent (AI) methods have the potential to help improve diagnostic efficiency and accuracy for reading portable CXRs. PURPOSE: The study aimed at developing an AI imaging analysis tool to classify COVID-19 lung infection based on portable CXRs. MATERIALS AND METHODS: Public datasets of COVID-19 (N = 130), bacterial pneumonia (N = 145), non-COVID-19 viral pneumonia (N = 145), and normal (N = 138) CXRs were analyzed. Texture and morphological features were extracted. Five supervised machine-learning AI algorithms were used to classify COVID-19 from other conditions. Two-class and multi-class classification were performed. Statistical analysis was done using unpaired two-tailed t tests with unequal variance between groups. Performance of classification models used the receiver-operating characteristic (ROC) curve analysis. RESULTS: For the two-class classification, the accuracy, sensitivity and specificity were, respectively, 100%, 100%, and 100% for COVID-19 vs normal; 96.34%, 95.35% and 97.44% for COVID-19 vs bacterial pneumonia; and 97.56%, 97.44% and 97.67% for COVID-19 vs non-COVID-19 viral pneumonia. For the multi-class classification, the combined accuracy and AUC were 79.52% and 0.87, respectively. CONCLUSION: AI classification of texture and morphological features of portable CXRs accurately distinguishes COVID-19 lung infection in patients in multi-class datasets. Deep-learning methods have the potential to improve diagnostic efficiency and accuracy for portable CXRs.

Axial or Helical? CT imaging of the thorax for dyspnoea patients with free-breathing using 16 cm wide-detector CT.

AIM: To compare image quality and radiation dose between fast-helical mode (FHM) and two-axial mode (TAM) in chest computed tomography (CT) with 16 cm wide-detector for emergency patients with dyspnoea. MATERIALS AND METHODS: Ninety-six emergency chest CT patients who cannot comply with breathing instructions were prospectively divided randomly into two groups: the FHM group (n=48, helical scan with 80 mm collimation and pitch 0.992:1), the TAM group (n=48, two axial scans with 160 mm collimation). Both groups used 0.28 seconds rotation speed and automatic tube current modulation. All scans were performed in free breathing. CT value, image noise, and signal-to-noise ratio (SNR) were measured on the descending thoracic aorta, lung parenchyma, and paraspinal muscle at the carina level. Two radiologists assessed images for subjective image quality, motion artefacts and diagnostic confidence. The volume CT dose index and dose-length product (DLP) were evaluated and effective dose (ED) was calculated. RESULTS: The TAM group required less exposure time than the FHM group (0.56 versus 1.14 seconds, p<0.001), reduced the frequency of motion artefacts caused by the diaphragm and heart by 50% and provided higher diagnostic confidence score (3.83 versus 3.58, p<0.05). TAM resulted in 24% lower DLP (96.76±31.58 versus 126.99±33.37 mGy·cm) and ED (1.36±0.44 versus 1.78±0.47 mSv) than FHM (p<0.001), but there was no difference in the CT value, image noise, and SNR between the two groups (p>0.05). CONCLUSIONS: TAM with 16 cm detector coverage further reduces the exposure time in chest CT for dyspnoea patients and ensures good image quality with 24% radiation dose reduction, compared with fast-helical chest CT with 80 mm collimation.

Pediatric chest computed tomography at 100 kVp with tin filtration: comparison of image quality with 70-kVp imaging at comparable radiation dose.

BACKGROUND: Radiation dose reduction is a primary objective in pediatric populations owing to the well-known risks of radiation-induced cancers. Low-energy photons participate in the radiation dose without significantly contributing to image formation. Their suppression by means of tin filtration should decrease the image noise, anticipating a subsequent application to dose saving. OBJECTIVE: To investigate the level of noise reduction achievable with tin (Sn) filtration at 100 kVp for chest computed tomography (CT) in comparison with a standard scanning mode at 70 kVp with comparable radiation dose. MATERIALS AND METHODS: Fifty consecutive children (Group 1) underwent non-contrast chest CT examinations on a third-generation dual-source CT system at tin-filtered 100 kVp and pitch 2. The tube-current time product (mAs) was adjusted to maintain the predicted dose length product (DLP) value at 70 kVp for the respective patient. Each child was then paired by weight and age to a child scanned at 70 kVp on the same CT unit (Group 2); Group 2 patients were consecutive patients, retrospectively selected from our database of children prospectively scanned at 70 kVp. Objective and subjective image quality were compared between the two groups of patients to investigate the overall image quality and level of noise reduction that could be subsequently achievable with tin filtration in clinical practice. RESULTS: The mean image noise was significantly lower in Group 1 compared to Group 2 when measured in the air (P<0.0001) and inside the aorta (P<0.001). The mean noise reduction was 21.6% (standard deviation [SD] 16.1) around the thorax and 12.0% (SD 32.7) inside the thorax. There was no significant difference in subjective image quality of lung and mediastinal images with excellent overall subjective scores in both groups. CONCLUSION: At comparable radiation dose, the image noise was found to be reduced by 21.6% compared to the 70-kVp protocol, providing basis for dose reduction without altering image quality in further investigations.

Diagnosis of foreign body aspiration with ultralow-dose CT using a tin filter: a comparison study.

PURPOSE: Suspected airway foreign body aspiration (FBA) is a common event in paediatric emergency units, especially in children under 3 years of age. It can be a life-threatening event if not diagnosed promptly and accurately. The purpose of this study is to compare the diagnostic performance of an ultralow-dose CT (DLP of around 1 mGycm) with that of conventional radiographic methods (fluoroscopy and chest radiography of the airways) in the diagnosis of FBA children's airways. METHODS: Retrospective cross-sectional study. Data from 136 children were collected: 75 were examined with conventional radiographic methods and 61 with ultralow-dose CT. Effective doses were compared using independent t tests. The results of bronchoscopy, if performed, were used in creating contingency 2 × 2 tables to assess the diagnostic performance between modalities. An extra triple reading of all images was applied for this purpose. RESULTS: The effective doses used in the ultralow-dose CT examinations were lower compared with those in conventional methods (p < 0.001). The median dose for CT was 0.04 mSv compared with 0.1 mSv for conventional methods. Sensitivity and specificity were higher for ultralow-dose CT than those for conventional methods (100% and 98% versus 33% and 96%) as were the positive and negative predicted values (90% and 100% versus 60% and 91%). CONCLUSION: Ultralow-dose CT can be used as the imaging of choice in the diagnosis of airway FBA in emergency settings, thereby avoiding concerns about radiation doses and negative bronchoscopy outcomes.

Use of a portable computed tomography scanner for chest imaging of COVID-19 patients in the urgent care at a tertiary cancer center.

To present a novel use of a portable computed tomography (CT) for evaluation of COVID-19 patients presenting to an urgent care center (UCC). Infection control is imperative for hospitals treating patients with COVID-19, even more so in cancer centers, where the majority of the patient population is susceptible to adverse outcomes from the infection. Over the past several weeks, our department has worked to repurpose a portable CT scanner from our surgical colleagues that operates with fixed-parameters to perform non-contrast, helical, thin-slice chest imaging to address the known pulmonary complications of COVID-19. Despite the technical limitations of the portable CT unit that was repurposed for the UCC, diagnostic-quality images in an acute care setting were successfully obtained. Repurposing of a portable CT scanner for use in COVID-19 patients offers a feasible option to obtain diagnostic quality images while minimizing the risk of exposing other patients and hospital staff to an infected patient.

Optimal beam quality for chest flat panel detector system: realistic phantom study.

OBJECTIVE: To investigate optimal beam quality for chest flat panel detector (FPD) system by semi-quantitatively assessment using a realistic lung phantom. MATERIALS AND METHODS: Chest FPD radiographs were obtained on a realistic lung phantom with simulated lung opacities using various X-ray tube voltage levels (90-140 kV) with/without copper filter. Entrance skin dose was set to maintain identical for all images (0.1 mGy). Three chest radiologists unaware of the exposure settings independently evaluated the image quality of each simulated opacity and normal structure using a 5-point scale (+ 2: clearly superior to the standard; + 1: slightly superior to the standard; 0: equal to the standard; - 1: slightly inferior to the standard; - 2: clearly inferior to the standard). The traditional FPD image obtained at a tube voltage of 120 kV was used as the standard. The scores of image quality were statistically compared using the Wilcoxon rank test with Bonferroni correction. RESULTS: FPD images using 90-kV shot with copper filter were superior to the traditional 120-kV shot without filter with respect to the visibility of vertebra, pulmonary vessels, and nodules overlapping diaphragm and heart (p < 0.05). There was no significant difference with respect to the visibility of all other simulated lung opacities (lung nodules except for overlying diaphragm/heart and honeycomb opacity) between each tube voltage level with/without copper filter and the traditional 120-kV shot without filter. CONCLUSION: Image quality of FPD images using 90 kV with copper filtration is superior to that using standard tube voltage when dose is identical. KEY POINTS: • FPD image quality using 90 kV with filter is superior to that using traditional beam. • Ninety-kilovolt shot with copper filter may be suitable for chest FPD image. • Clinical study dealing with chest FPD beam optimization would be warranted.

Prototype Ultrahigh-Resolution Computed Tomography for Chest Imaging: Initial Human Experience.

OBJECTIVE: The objective of this study was to evaluate a prototype, ultrahigh-resolution computed tomography offering higher reconstruction matrix (1024 × 1024) and spatial resolution (0.15 mm) for chest imaging. METHODS: Higher (1024) matrix reconstruction enabled by ultrahigh-resolution computed tomography scanner (128-detector rows; detector width, 0.25 mm; spatial resolution, 0.15 mm) was compared with conventional (512) reconstruction with image quality grading on a Likert scale (1, excellent; 5, nondiagnostic) for image noise, artifacts, contrast, small detail, lesion conspicuity, image sharpness, and diagnostic confidence. Image noise and signal-to-noise ratio were quantified. RESULTS: Diagnostic image quality was achieved for all scans on 101 patients. The 1024 reconstruction demonstrated increased image noise (20.2 ± 4.0 vs 17.2 ± 3.8, P < 0.001) and a worse noise rating (1.98 ± 0.63 vs 1.75 ± 0.61, P < 0.001) but performed significantly better than conventional 512 matrix with fewer artifacts (1.37 ± 0.43 vs 1.50 ± 0.48, P < 0.001), better contrast (1.50 ± 0.56 vs 1.62 ± 0.57, P < 0.001), small detail detection (1.06 ± 0.19 vs 2.02 ± 0.22, P < 0.001), lesion conspicuity (1.08 ± 0.23 vs 2.02 ± 0.24, P < 0.001), sharpness (1.09 ± 0.24 vs 2.02 ± 0.28, P < 0.001), and overall diagnostic confidence (1.09 ± 0.25 vs 1.18 ± 0.34, P < 0.001). CONCLUSIONS: Ultrahigh-resolution computed tomography enabled a higher reconstruction matrix and improved image quality compared with conventional matrix reconstruction, with a minor increase in noise.

Improved visualization of peripherally inserted central catheters on chest radiographs of neonates using fractional multiscale image processing.

BACKGROUND: Peripherally inserted central catheters (PICCs) provide secure intravenous access for the delivery of life-sustaining medications and nutrition. They are commonly used in pediatrics. Confirmation of correct central catheter tip position is crucial. Verification is usually done by a radiograph. The aim of this study is to evaluate the ability of Fractional Multiscale image Processing (FMP) to detect PICC tips on the digital chest radiographs of neonates. METHODS: A total of 94 radiographs of 47 patients were included in the study. 29 patients were male, 18 were female. The mean age of all examined children was 9.2 days (range 0-99 days). In total, six readers (two radiologists, two residents in radiology, one last year medical student, one neonatologist) evaluated 94 unprocessed and catheter-enhanced radiographs using a 5-point Likert scale (1 = poor catheter tip visualization, 5 = excellent catheter tip visualization). Additionally, the two radiologists evaluated the diagnostic confidence for chest pathologies using a 5-point Likert scale (1 = poor diagnostic confidence, 5 = excellent diagnostic confidence). Radiographs were evaluated on a dedicated workstation. RESULTS: In all cases, the catheter-enhanced radiograph rated higher than (n = 471), or equal (n = 93) to, the unprocessed radiograph when visualizing catheter tips. 87% of the catheter-enhanced radiographs obtained a rating of 4 or higher, while only 42% of unprocessed radiographs received 4 or more points. Regarding diagnostic confidence for chest pathologies one radiologist rated two catheter-enhanced radiographs higher than the unprocessed radiographs, while all other 186 evaluations rated the catheter-enhanced radiographs equal to (n = 78) or lower than (n = 108) the unprocessed radiographs. Only 60% of the catheter-enhanced radiographs yielded a diagnostic confidence of 4 or higher, while 90% of the unprocessed images received 4 or more points. CONCLUSION: Catheter-enhanced digital chest radiographs demonstrate improved visualization of low contrast PICC tips in neonates compared to unprocessed radiographs. Furthermore, they enable detection of accompanying chest pathologies. However, definitive diagnosis of chest pathologies should be made on unprocessed radiographs.

The Utility of a Portable X-ray System.

Fujifilm (Tokyo, Japan) developed a portable X-ray system called the CALNEO Xair. We herein report our experience in using this portable X-ray system at the scene after transportation by a doctor helicopter (DH). An explosion suddenly occurred while a 42-year-old man was handling toluene in a factory, causing his clothes to catch on fire. When the staff of a physician-staffed helicopter (DH) equipped with a portable X-ray system checked the man at the rendezvous point, he had second- and third-degree flame burns to > 70% of his total body surface area. A chest X-ray obtained using the portable X-ray system showed clear lung fields. A noninvasive carboxyhemoglobin monitor indicated a carboxyhemoglobin value of 6%. He was transferred to a special burn center by the DH. This is the first reported case in which a portable X-ray system was used to evaluate blast injuries in the prehospital setting. This system may be useful for performing prehospital medical treatment for blast injury victims.

Visual grading analysis of digital neonatal chest phantom X-ray images: Impact of detector type, dose and image processing on image quality.

OBJECTIVES: To evaluate the impact of digital detector, dose level and post-processing on neonatal chest phantom X-ray image quality (IQ). METHODS: A neonatal phantom was imaged using four different detectors: a CR powder phosphor (PIP), a CR needle phosphor (NIP) and two wireless CsI DR detectors (DXD and DRX). Five different dose levels were studied for each detector and two post-processing algorithms evaluated for each vendor. Three paediatric radiologists scored the images using European quality criteria plus additional questions on vascular lines, noise and disease simulation. Visual grading characteristics and ordinal regression statistics were used to evaluate the effect of detector type, post-processing and dose on VGA score (VGAS). RESULTS: No significant differences were found between the NIP, DXD and CRX detectors (p>0.05) whereas the PIP detector had significantly lower VGAS (p< 0.0001). Processing did not influence VGAS (p=0.819). Increasing dose resulted in significantly higher VGAS (p<0.0001). Visual grading analysis (VGA) identified a detector air kerma/image (DAK/image) of ~2.4 µGy as an ideal working point for NIP, DXD and DRX detectors. CONCLUSIONS: VGAS tracked IQ differences between detectors and dose levels but not image post-processing changes. VGA showed a DAK/image value above which perceived IQ did not improve, potentially useful for commissioning. KEY POINTS: • A VGA study detects IQ differences between detectors and dose levels. • The NIP detector matched the VGAS of the CsI DR detectors. • VGA data are useful in setting initial detector air kerma level. • Differences in NNPS were consistent with changes in VGAS.

Effect of CT Acquisition Parameters on Iodine Density Measurement at Dual-Layer Spectral CT.

OBJECTIVE: We aimed to evaluate the effect of tube voltage, tube current-time product, and iterative reconstruction on iodine quantification using a dual-layer spectral CT scanner. MATERIALS AND METHODS: Two mediastinal iodine phantoms, each containing six tubes of different iodine concentrations (0, 1, 2.5, 5, 10, and 20 mg I/mL; the two phantoms had tubes with contrast media diluted in water and in 10% amino acid solution, respectively), were inserted into an anthropomorphic chest phantom and scanned with varying acquisition parameters (120 and 140 kVp; 20, 40, 60, 80, 100, 150, and 200 mAs; and spectral reconstruction levels 0 and 6). Thereafter, iodine density was measured (in milligrams of iodine per milliliter) using a dedicated software program, and the effect of acquisition parameters on iodine density and on its relative measurement error (RME) was analyzed using a linear mixed-effects model. RESULTS: Tube voltages (all, p < 0.001) and tube current-time products (p < 0.05, depending on the interaction terms for iodine density; p = 0.023 for RME) had statistically significant effects on iodine density and RME. However, the magnitude of their effects was minimal. That is, estimated differences between tube voltage settings ranged from 0 to 0.8 mg I/mL for iodine density and from 1.0% to 4.2% for RME. For tube current-time product, alteration of 100 mAs caused changes in iodine density and RME of approximately 0.1 mg I/mL and 0.6%, respectively. Spectral level was not an affecting factor for iodine quantification (p = 0.647 for iodine density and 0.813 for RME). CONCLUSION: Iodine quantification using dual-layer spectral CT was feasible irrespective of CT acquisition parameters because their effects on iodine density and RME were minimal.

Selection of appropriate endotracheal tube size using thoracic radiography in Beagle dogs.

OBJECTIVE: To determine the optimal endotracheal tube size in Beagle dogs using thoracic radiography. STUDY DESIGN: Prospective, randomized, crossover experimental study. ANIMALS: A total of eight healthy adult Beagle dogs. METHODS: Lateral thoracic radiographs were used to measure the internal tracheal diameter at the thoracic inlet. This measurement was multiplied by 60, 70 and 80% to determine the outer diameter of the endotracheal tube for each dog. In each treatment, medetomidine (5 µg kg-1) was administered intravenously (IV) for premedication. Anesthesia was induced with alfaxalone (2 mg kg-1) IV and maintained with isoflurane. After induction of anesthesia, the resistance to passage of the endotracheal tube through the trachea was scored by a single anesthesiologist. Air leak pressures (Pleak) were measured at intracuff pressures (Pcuff) of 20 and 25 mmHg (27 and 34 cmH2O). The results were analyzed using Friedman tests and repeated measures anova. RESULTS: There were statistically significant increases in resistance as the endotracheal tube size increased (p = 0.003). When Pcuff was 20 mmHg, mean Pleak for the 60, 70 and 80% treatments were 9.7 ± 6.7, 16.2 ± 4.2 and 17.4 ± 3.9 cmH2O, respectively, but no significant differences were found. When Pcuff was 25 mmHg, mean Pleak for the 60, 70 and 80% treatments were 10.6 ± 8.5, 19.7 ± 4.9 and 20.8 ± 3.6 cmH2O, respectively, and statistically significant increases were found between treatments 60 and 70% (p = 0.011) and between treatments 60 and 80% (p = 0.020). Three dogs in the 80% treatment had bloody mucus on the endotracheal tube cuff after extubation. CONCLUSIONS AND CLINICAL RELEVANCE: Results based on resistance to insertion of the endotracheal tube and the ability to achieve an air-tight seal suggest that an appropriately sized endotracheal tube for Beagle dogs is 70% of the internal tracheal diameter measured on thoracic radiography.

Feasibility of Dose-reduced Chest CT with Photon-counting Detectors: Initial Results in Humans.

Purpose To investigate whether photon-counting detector (PCD) technology can improve dose-reduced chest computed tomography (CT) image quality compared with that attained with conventional energy-integrating detector (EID) technology in vivo. Materials and Methods This was a HIPAA-compliant institutional review board-approved study, with informed consent from patients. Dose-reduced spiral unenhanced lung EID and PCD CT examinations were performed in 30 asymptomatic volunteers in accordance with manufacturer-recommended guidelines for CT lung cancer screening (120-kVp tube voltage, 20-mAs reference tube current-time product for both detectors). Quantitative analysis of images included measurement of mean attenuation, noise power spectrum (NPS), and lung nodule contrast-to-noise ratio (CNR). Images were qualitatively analyzed by three radiologists blinded to detector type. Reproducibility was assessed with the intraclass correlation coefficient (ICC). McNemar, paired t, and Wilcoxon signed-rank tests were used to compare image quality. Results Thirty study subjects were evaluated (mean age, 55.0 years ± 8.7 [standard deviation]; 14 men). Of these patients, 10 had a normal body mass index (BMI) (BMI range, 18.5-24.9 kg/m2; group 1), 10 were overweight (BMI range, 25.0-29.9 kg/m2; group 2), and 10 were obese (BMI ≥30.0 kg/m2, group 3). PCD diagnostic quality was higher than EID diagnostic quality (P = .016, P = .016, and P = .013 for readers 1, 2, and 3, respectively), with significantly better NPS and image quality scores for lung, soft tissue, and bone and with fewer beam-hardening artifacts (all P < .001). Image noise was significantly lower for PCD images in all BMI groups (P < .001 for groups 1 and 3, P < .01 for group 2), with higher CNR for lung nodule detection (12.1 ± 1.7 vs 10.0 ± 1.8, P < .001). Inter- and intrareader reproducibility were good (all ICC > 0.800). Conclusion Initial human experience with dose-reduced PCD chest CT demonstrated lower image noise compared with conventional EID CT, with better diagnostic quality and lung nodule CNR. © RSNA, 2017 Online supplemental material is available for this article.

Submillisievert Computed Tomography of the Chest Using Model-Based Iterative Algorithm: Optimization of Tube Voltage With Regard to Patient Size.

OBJECTIVE: The aim of this study was to define optimal tube potential for soft tissue and vessel visualization in dose-reduced chest CT protocols using model-based iterative algorithm in average and overweight patients. METHODS: Thirty-six patients receiving chest CT according to 3 protocols (120 kVp/noise index [NI], 60; 100 kVp/NI, 65; 80 kVp/NI, 70) were included in this prospective study, approved by the ethics committee. Patients' physical parameters and dose descriptors were recorded. Images were reconstructed with model-based algorithm. Two radiologists evaluated image quality and lesion conspicuity; the protocols were intraindividually compared with preceding control CT reconstructed with statistical algorithm (120 kVp/NI, 20). Mean and standard deviation of attenuation of the muscle and fat tissues and signal-to-noise ratio of the aorta were measured. RESULTS: Diagnostic images (lesion conspicuity, 95%-100%) were acquired in average and overweight patients at 1.34, 1.02, and 1.08 mGy and at 3.41, 3.20, and 2.88 mGy at 120, 100, and 80 kVp, respectively. Data are given as CT dose index volume values. CONCLUSIONS: Model-based algorithm allows for submillisievert chest CT in average patients; the use of 100 kVp is recommended.

Scout-Based Automated Tube Potential Selection Technique (kV Assist) in Enhanced Chest Computed Tomography: Effects on Radiation Exposure and Image Quality.

OBJECTIVE: The aim of our study was to assess radiation dose reduction and image quality for enhanced chest CT examinations with a scout-based automated tube potential selection technique (kV Assist) compared with a standard 120-kV protocol. METHODS: Prospective study of enhanced chest CT examinations was performed in 100 consecutive patients with kV Assist and in 100 consecutive patients with conventional 120-kV protocol on a multislice CT (Discovery CT750 HD). The body mass index, CT dose index volume, and dose length product were recorded from the examination protocol. Image noise and CT value was measured on region of interest, signal-to-noise ratio, and contrast-to-noise ratio was calculated. The subjective image quality was assessed by two radiologists blinded to the respective protocol with the use of a 3-grade scale (3, superior quality; 2, moderate quality; 1, inferior quality). RESULTS: With kV Assist, the percentages of patients being scanned using 80, 100, and 120 kV were 12.0%, 80.0%, and 8.0%, respectively. The kilovolt setting was related with body mass index (r = 0.565, P = 0.000). Compared with the conventional 120 kV protocol, kV Assist allowed for an overall average decrease of 30.6% in CT dose index volume (kV Assist, 11.05 ± 4.78 mGy; 120 kV, 15.92 ± 6.89 mGy) (P < 0.001) and 32.3% in dose length product (kV Assist, 386.41 ± 184.02 mGy cm; 120 kV, 571.14 ± 286.68 mGy cm) (P < 0.001). In the kV Assist, mean attenuation of regions of interest inside the aorta was significantly higher than that in 120-kV protocols (kV Assist, 310.27 ± 73.70 HU; 120 kV, 239.44 ± 47.65 HU) (P < 0.001), resulting in increased contrast-to-noise ratio (kV Assist, 26.69 ± 7.78; 120 kV, 21.38 ± 6.05) (P < 0.001). There was no significant difference in subjective image quality scores between the 2 groups. CONCLUSIONS: The use of attenuation-based kV Assist technique enables significant dose reduction in enhanced chest CT scan while improving arterial enhancement and preserving image quality at adequate levels.

Image Quality in Oncologic Chest Computerized Tomography With Iterative Reconstruction: A Phantom Study.

OBJECTIVE: The purpose of this study was to validate iterative reconstruction technique in oncologic chest computed tomography (CT). METHODS: An anthropomorphic thorax phantom with 4 simulated tumors was scanned on a 64-slice CT scanner with 2 different iterative reconstruction techniques: one model based (MBIR) and one hybrid (ASiR). Dose levels of 14.9, 11.1, 6.7, and 0.6 mGy were used, and all images were reconstructed with filtered back projection (FBP) and both iterative reconstruction algorithms. Hounsfield units (HU) and absolute noise were measured in the tumors, lung, heart, diaphragm, and muscle. Contrast-to-noise ratios (CNRs) and signal-to-noise ratios (SNRs) were calculated. RESULTS: Model-based iterative reconstruction (MBIR) increased CNRs of the tumors (21.1-192.2) and SNRs in the lung (-49.0-165.6) and heart (3.1-8.5) at all dose levels compared with FBP (CNR, 1.1-23.0; SNR, -7.5-31.6 and 0.2-1.1) and with adaptive statistical iterative reconstruction (CNR, 1.2-33.2; SNR, -7.3-37.7 and 0.2-1.5). At the lowest dose level (0.6 mGy), MBIR reduced the cupping artifact (HU range: 17.0 HU compared with 31.4-32.2). An HU shift in the negative direction was seen with MBIR. CONCLUSIONS: Quantitative image quality parameters in oncologic chest CT are improved with MBIR compared with FBP and simpler iterative reconstruction algorithms. Artifacts at low doses are reduced. A shift in HU values was shown; thus, absolute HU values should be used with care.

Examination for Effectiveness of Scatter Correction in Portable Chest Radiography.

OBJECTIVES: The aim of this study was to evaluate the effectiveness of scatter correction in the portable chest radiography. METHODS: Digital radiographies were performed without anti-scatter grid (grid), with the scatter correction and with the grid ratio of 3 : 1 in this study. The scatter fraction and the detectability of low contrast signals were measured using the four acrylic phantoms of different thicknesses. The chest phantom radiographs were assessed subjectively, in random order, by six radiologic technologists. RESULTS: The scatter fraction was higher in the no-grid technique, and was lower for the grid technique. The detectability of low contrast signals did not significantly differ between the scatter correction and the grid technique (p>0.05). The area under the receiver operating characteristic curve for the grid technique was higher than that for the scatter correction technique (0.888 vs. 0.855), although no significant difference was found between the grid and the scatter correction technique (p> 0.05). The ability to detect the nasogastric tube was significantly better in the grid technique (p<0.001). DISCUSSION: In the scatter correction technique, the ability of scatter removal increased as the scatter fraction increased. The scatter correction technique was unnecessary to extremely accurate alignment. In addition, patient dose can be reduced by the scatter correction technique. CONCLUSIONS: It seemed to be effective for the scatter correction in the portable chest radiography.

Lung segmentation on standard and mobile chest radiographs using oriented Gaussian derivatives filter.

BACKGROUND: Unsupervised lung segmentation method is one of the mandatory processes in order to develop a Content Based Medical Image Retrieval System (CBMIRS) of CXR. The purpose of the study is to present a robust solution for lung segmentation of standard and mobile chest radiographs using fully automated unsupervised method. METHODS: The novel method is based on oriented Gaussian derivatives filter with seven orientations, combined with Fuzzy C-Means (FCM) clustering and thresholding to refine the lung region. In addition, a new algorithm to automatically generate a threshold value for each Gaussian response is also proposed. The algorithms are applied to both PA and AP chest radiographs from both public JSRT dataset and our private datasets from collaborative hospital. Two pre-processing blocks are introduced to standardize the images from different machines. Comparisons with the previous works found in the literature on JSRT dataset shows that our method gives a reasonably good result. We also compare our algorithm with other unsupervised methods to provide fairly comparative measures on the performances for all datasets. RESULTS: Performance measures (accuracy, F-score, precision, sensitivity and specificity) for the segmentation of lung in public JSRT dataset are above 0.90 except for the overlap measure is 0.87. The standard deviations for all measures are very low, from 0.01 to 0.06. The overlap measure for the private image database is 0.81 (images from standard machine) and 0.69 (images from two mobile machines). The algorithm is fully automated and fast, with the average execution time of 12.5 s for 512 by 512 pixels resolution. CONCLUSIONS: Our proposed method is fully automated, unsupervised, with no training or learning stage is necessary to segment the lungs taken using both a standard machine and two different mobile machines. The proposed pre-processing blocks are significantly useful to standardize the radiographs from mobile machines. The algorithm gives good performance measures, robust, and fast for the application of the CBMIRS.