Standard Chest Research Articles

Construction of U-Net++ pulmonary nodule intelligent analysis model based on feature weighted aggregation.

Lung cancer is a malignant tumor originating from the bronchial mucosa or glands of the lung. Early lung cancer patients often have no obvious symptoms, but early detection and treatment have an important clinical significance for prognostic effect. Computed tomography (CT) is one of the important means in the diagnosis of lung cancer. In order to better solve the problem of diagnosis efficiency, and reduce the rate of misdiagnosis and missed diagnosis, computer aided diagnosis are employed in the accurate localization and segmentation of pulmonary nodules through imaging diagnostics, image processing technology, and other clinical means. This present study was envisaged to establish an intelligent segmentation model of pulmonary nodules to improve the accuracy of early screening for lung cancer patients. Compared with the traditional segmentation model of fully convolutional neural network, the U-Net++ algorithm based on feature-weighted integration (WI-U-Net++) effectively utilized the feature weight information, adopted the adaptive weighted method for weighted integration, and performed an intelligent segmentation of the anatomical structure and image details, which was applied in the auxiliary diagnosis of pulmonary nodules in CT images. Standard chest X-ray phantom was selected as CT scanning objects, and 30 spherical and irregular simulated nodules were built into them, respectively. CT images were collected by setting different tube voltage and noise index, and randomly included into the training set, validation set and test set at a ratio of 8:1:1. The experimental results showed that the segmentation accuracy of WI-U-Net++ algorithm for spheroid nodules and irregular nodules was 98.75% and 83.47%, respectively, which was better than that of U-Net and U-Net++ algorithm. In the auxiliary diagnosis, the recall rate of the WI-U-Net++ algorithm for spheroid nodules and irregular nodules was 93.47% and 84.52%, respectively. The accuracy of the benign or malignant identification was 80.27%, and the AUC was 0.9342. U-Net++ algorithm based on feature-weighted integration could improve the segmentation effect of pulmonary nodules. Especially in the case of irregular nodules with malignant signs, the accuracy of clinical diagnosis was significantly improved, and the level of differential diagnosis between benign and malignant was improved.

Ultra-low-dose emergency chest computed tomography protocols in three vendors: A technical note.

In suspected community-acquired pneumonia (CAP), chest CT is superior to the routinely obtained radiographs (CXR), but administers higher radiation doses. However, ultra-low-dose CT (ULDCT) has shown promising results. To compare radiation dose and image quality using standard and ULDCT protocols designed for a multicenter study encompassing three CT scanner models from GE, Canon, and Siemens. Patients with suspected CAP were referred for non-contrast standard dose chest CT (NCCT) and ULDCT. Effective radiation dose and Contrast-to-Noise Ratio (CNR) was calculated. Mean effective doses were GE (n = 10) 6.93mSv in NCCT and 0.27mSv in ULDCT; Canon (n = 9) 3.48 in mSv NCCT and 1.11mSv in ULDCT; Siemens (n = 10) 2.85mSv in NCCT and 0.45mSv in ULDCT. CNR was reduced by 29-39% in ULDCT. The proposed CT protocols yielded dose reductions of 96%, 68%, and 84% using a GE, Canon, and Siemens scanner, respectively.

New technique and application of truncated CBCT processing in adaptive radiotherapy for breast cancer

ObjectiveA generative adversarial network (TCBCTNet) was proposed to generate synthetic computed tomography (sCT) from truncated low-dose cone-beam computed tomography (CBCT) and planning CT (pCT). The sCT was applied to the dose calculation of radiotherapy for patients with breast cancer. MethodsThe low-dose CBCT and pCT images of 80 female thoracic patients were used for training. The CBCT, pCT, and replanning CT (rCT) images of 20 thoracic patients and 20 patients with breast cancer were used for testing. All patients were fixed in the same posture with a vacuum pad. The CBCT images were scanned under the Fast Chest M20 protocol with a 50% reduction in projection frames compared with the standard Chest M20 protocol. Rigid registration was performed between pCT and CBCT, and deformation registration was performed between rCT and CBCT. In the training stage of the TCBCTNet, truncated CBCT images obtained from complete CBCT images by simulation were used. The input of the CBCT→CT generator was truncated CBCT and pCT, and TCBCTNet was applied to patients with breast cancer after training. The accuracy of the sCT was evaluated by anatomy and dosimetry and compared with the generative adversarial network with UNet and ResNet as the generators (named as UnetGAN, ResGAN). ResultsThe three models could improve the image quality of CBCT and reduce the scattering artifacts while preserving the anatomical geometry of CBCT. For the chest test set, TCBCTNet achieved the best mean absolute error (MAE, 21.18±3.76 HU), better than 23.06±3.90 HU in UnetGAN and 22.47±3.57 HU in ResGAN. When applied to patients with breast cancer, TCBCTNet performance decreased, and MAE was 25.34±6.09 HU. Compared with rCT, sCT by TCBCTNet showed consistent dose distribution and subtle absolute dose differences between the target and the organ at risk. The 3D gamma pass rates were 98.98%±0.64% and 99.69%±0.22% at 2 mm/2% and 3 mm/3%, respectively. Ablation experiments confirmed that pCT and content loss played important roles in TCBCTNet. ConclusionsHigh-quality sCT images could be synthesized from truncated low-dose CBCT and pCT by using the proposed TCBCTNet model. In addition, sCT could be used to accurately calculate the dose distribution for patients with breast cancer.

Real-Time Ultrasound Tip Location Reduces Malposition and Radiation Exposure during Epicutaneo-Caval Catheter Placement in Neonates.

Epicutaneo-caval catheters (ECCs) are essential for the care of sick infants who require long-term medical and nutritional management. The aim of this study was to investigate the use of real-time ultrasound as an alternative to X-rays to reduce the incidence of primary malpositions during catheter insertion. Data on ECCs were retrospectively collected in a tertiary neonatal intensive care unit. Catheter were analyzed considering the tip location technique (standard chest-abdominal radiograph vs real-time ultrasound) RESULTS: A total of 248 ECCs were analyzed. Of these, 118 catheters had primary malposition (47.6%). The tip of 165 catheters was assessed using standard chest-abdominal X-rays and 107 (64.8%) were found to be in an inappropriate location. In the group of 83 catheters that were placed using real-time ultrasound for tip location, only 11 catheters (13.2%) had primary malposition. The rate of malposition among the two groups showed a statistically significant difference (p < 0.001). Hypothetically, 300 chest X-rays could have been saved if real-time ultrasound had been used to locate the tip, reducing radiation exposure to infants. The use of a real-time ultrasound may be beneficial in reducing primary catheter malpositions compared with conventional radiography. In addition, secondary malpositions and catheter-related complications can be monitored over time. · Conventional radiology cannot be considered the "gold standard" for ECC tip location.. · Ultrasound is more accurate and reduces insertion time reducing the rate of primary malposition.. · Ultrasound can be performed in real time and it is the best technique for ECC tip location in infants..

Automated analysis of lung lesions in COVID-19: comparison of standard and low-dose CT

Introduction. Chest computed tomography (CT) plays a prominent role in determining the extent of pulmonary parenchymal lesions in COVID-19. At the same time, subjectivity of lung lesion volume assessment using 0-4 CT scale in COVID-19 and gradual introduction of low-dose CT (LDCT) requires an investigation of semi-automated lung segmentation accuracy in LDCT compared to CT.Study Objective. To compare the accuracy of affected lung tissue volume calculation between CT and LDCT in COVID-19 using a semi-automatic segmentation program.Material and Methods. The retrospective study was performed on data from the earlier prospective multicenter study registered at ClinicalTrials.gov, NCT04379531. CT and LDCT data were processed in 3D Slicer software with Lung CT Segmenter and Lung CT Analyzer extensions, and the volume of affected lung tissue and lung volume were determined by thresholding.Results. The sample size was 84 patients with signs of COVID-19-associated pneumonia. Mean age was 50.6 ± 13.3 years, and the median body mass index (BMI) was 28.15 [24.85; 31.31] kg/m2. The effective doses were 10.1 ± 3.26 mSv for the standard CT protocol and 2.64 mSv [1.99; 3.67] for the developed LDCT protocol. The analysis of absolute lung lesion volume in cubic centimeters with Wilcoxon Signed Ranks Test revealed a statistically significant difference between CT and LDCT (p-value &lt; 0.001). No statistically significant differences were found in the relative values of lung tissue lesion volume (lesion volume/lung volume) between CT and LDCT using Wilcoxon Signed Ranks Test (p-value = 0.95).Conclusion. The reliability of developed LDCT protocol in COVID-19 for the semi-automated calculation of affected tissue percentage was comparable to the standard chest CT protocol when using 3D Slicer with Lung CT Segmenter and Lung CT Analyzer extensions.

Importance of incidental coronary artery calcification in early diagnosis of obstructive coronary artery disease.

The early diagnosis of coronary artery disease (CAD) enables early intervention for the modifiable risk factors of the disease. Coronary artery calcification (CAC) detected incidentally on standard noncontrast chest computed tomography (CT) provides an opportunity for the early diagnosis of CAD. The purpose of this study was to demonstrate that CAC should be routinely reported when evaluating thoracic CT examinations. Routine reporting of CAC will contribute to the early diagnosis of CAD. The present study included 279 patients who underwent conventional coronary angiography (CAG) and CT within one month before undergoing CAG. The CAG and CT images of the patients were evaluated retrospectively. The levels of coronary artery stenosis were determined in reference to the CAG images. The CAC scores of the patients were calculated using the Weston method based on their chest CT images. The mean age of the patients was 63.2 ± 11.5 (range, 41-93) years, and 172 (61.6%) of them were men. The Weston score (WS) was 0 in 18.9% of the patients with obstructive CAD (OCAD), whereas it was ≥ 7 in 27.9% of patients. All patients with a WS of ≥ 7 had OCAD. All patients without luminal stenosis or < 50% stenosis had a WS of < 7. The CAC score is useful for the diagnosis of CAD and OCAD. If CAC is identified on standard noncontrast chest CT, it should be scored and reported accordingly. The WS can be used for CAC scoring.

Etiological and Radiological Profile of Acute Lower Respiratory Infections during the Pre-COVID Period in the Paediatric Ward of the Teaching Hospital of Mali and in the Community Health Centre of Yirimadio in Bamako

Introduction: Every year, nearly 4 million people pass away from acute respiratory infections. 98% of such deaths are due to lower respiratory tract infections. Even though studies have been carried on lower respiratory infections x-ray aspects in Mali, very few studies have been done to reveal bacteriological and virological evidence of this disease. Materials and methods: It is about a descriptive prospective study carried out from January to December 2018 having involved patients of all ages, coming for medical consultation at the Yirimadio Community-based health center as well as children from 6 months to 15 years old coming at the pediatric department of UHC Hôpital du Mali for a lower respiratory infection. They had all undergone chest X-ray and a PCR. The purpose: of this work is to study etiological and x-ray aspects of acute lower respiratory infections at the Yirimadio Community-based Health Center and at the UHC pediatric department of Hôpital du Mali. Findings: From January to December 2018, we recorded a frequency of 1.19%. The age group 0 - 5 years was the most represented (64.5%) with a sex ratio of 0.97 for women. Cough was the most common clinical sign (98.7%) followed by fever (58.9%). Standard frontal chest X-ray was pathological in 70% of our patients. It was bronchitis in 75.4% of cases, pneumonia (13.5%), and bronchopneumonia (12.3%). PCR positive was in 83.9% of patients. It revealed a co-infection in more than half of the patients (52.5%), bacterial infection (16.1%) and viral infection (15.2%). Pathogens isolated ranked by frequency were Streptococcus pneumoniaa (87.6%) followed by Staphylococcus aureus (24.9%) and human rhinovirus (17%). The most common viral causes were human rhinovirus (17%), followed by influenza A and B virus (7%) and human parainfluenza virus (7%). Conclusion: It stemed from the study that lower respiratory infections were mainly due to Streptococcus pneumonea and human rhinovirus during pre-COVID at the Yirimadio Community-based health center and UHC Hôpital du Mali.

Biomonitoring Exposure and Early Diagnosis in Silicosis: A Comprehensive Review of the Current Literature.

Silicosis is a particular form of lung fibrosis attributable to occupational exposure to crystalline silica. The occupational exposure to crystalline silica also increases the risk of chronic obstructive pulmonary disease (COPD), cancer and lung infections, especially pulmonary tuberculosis. Silicosis is currently diagnosed in previously exposed workers by standard chest X-ray, when lesions are visible and irreversible. Therefore, it would be necessary to find specific and non-invasive markers that could detect silicosis in earlier stages, before the occurrence of X-ray opacities. In this narrative review, we present several diagnostic, monitoring and predictive biomarkers with high potential in the management of silicosis, such as: pro- and anti-inflammatory cytokines (TNF (Tumour necrosis factor-α), IL-1 (Interleukin-1), IL-6, IL-10), CC16 (Clara cell 16, an indirect marker of epithelial cell destruction), KL-6 (Krebs von den Lungen 6, an indirect marker of alveolar epithelial damage), neopterin (indicator of cellular immunity) and MUC5B gene (Mucin 5B, a gel-forming mucin in mucus). Studies have shown that all the aforementioned markers have a high potential for early diagnosis or evaluation of progression in silicosis and represent promising alternatives to radiology. We consider that a multicentric study is needed to evaluate these biomarkers in correlation with occupational history, histopathological examination, imaging signs and pulmonary functions tests on large groups of subjects to better evaluate the accuracy of the presented biomarkers.

A few-shot approach for COVID-19 screening in standard and portable chest X-ray images

Reliable and effective diagnostic systems are of vital importance for COVID-19, specifically for triage and screening procedures. In this work, a fully automatic diagnostic system based on chest X-ray images (CXR) has been proposed. It relies on the few-shot paradigm, which allows to work with small databases. Furthermore, three components have been added to improve the diagnosis performance: (1) a region proposal network which makes the system focus on the lungs; (2) a novel cost function which adds expert knowledge by giving specific penalties to each misdiagnosis; and (3) an ensembling procedure integrating multiple image comparisons to produce more reliable diagnoses. Moreover, the COVID-SC dataset has been introduced, comprising almost 1100 AnteroPosterior CXR images, namely 439 negative and 653 positive according to the RT-PCR test. Expert radiologists divided the negative images into three categories (normal lungs, COVID-related diseases, and other diseases) and the positive images into four severity levels. This entails the most complete COVID-19 dataset in terms of patient diversity. The proposed system has been compared with state-of-the-art methods in the COVIDGR-1.0 public database, achieving the highest accuracy (81.13% ± 2.76%) and the most robust results. An ablation study proved that each system component contributes to improve the overall performance. The procedure has also been validated on the COVID-SC dataset under different scenarios, with accuracies ranging from 70.81 to 87.40%. In conclusion, our proposal provides a good accuracy appropriate for the early detection of COVID-19.

Long-term lung ultrasound follow-up in patients after COVID-19 pneumonia hospitalization: A prospective comparative study with chest computed tomography

During COVID-19 pandemic, lung ultrasound (LUS) proved to be of great value in the diagnosis and monitoring of patients with pneumonia. However, limited data exist regarding its use to assess aeration changes during follow-up (FU).Our study aims to prospectively evaluate 232 subjects who underwent a 3-month-FU program after hospitalization for COVID-19 at the University Hospital of Pisa. The goals were to assess the usefulness of standardized LUS compared with the gold standard chest computed tomography (CT) to evaluate aeration changes and to verify LUS and CT agreement at FU.Patients underwent in the same day a standardized 16-areas LUS and high-resolution chest CT reported by expert radiologists, assigning interpretative codes.Based on observations distribution, LUS score cut-offs of 3 and 7 were selected, corresponding to the 50th and 75th percentile, respectively. Patients with LUS scores above both these thresholds were older and with longer hospital stay. Patients with a LUS score ≥3 had more comorbidities. LUS and chest CT showed a high agreement in identifying residual pathological findings, using both cut-off scores of 3 (OR 14,7; CL 3,6–64,5, Sensitivity 91%, Specificity 49%) and 7 (OR 5,8; CL 2,3–14,3, Sensitivity 65%, Specificity 79%).Our data suggest that LUS is very sensitive in identifying pathological findings at FU after a hospitalization for COVID-19 pneumonia, compared to CT. Given its low cost and safety, LUS could replace CT in selected cases, such as in contexts with limited resources or it could be used as a gate-keeper examination before more advanced techniques.

Left ventricle chest compression improves ETCO2, blood pressure, and cerebral blood velocity in a swine model of cardiac arrest and cardiopulmonary resuscitation

IntroductionDuring cardiopulmonary resuscitation (CPR), high quality chest compressions are critical to organ perfusion, especially the brain. Yet, the optimal location for chest compressions is unclear. It was hypothesized that compared with the standard chest compression (SCC) location, left ventricle chest compressions (LVCCs) would result in greater end-tidal carbon dioxide (ETCO2), blood pressure (BP), and cerebral blood velocity (CBV) during CPR in swine. MethodsFemale Landrace swine (N = 32; 35 ± 2 kg) underwent two mins of untreated asphyxiated cardiac arrest (CA). Thereafter, swine were treated with three 2-min cycles of either SCC or LVCC mechanical basic life support CPR (LUCAS 3). ETCO2 (in-line sampling), BP (arterial catheter line), and CBV (transcranial Doppler) were measured during the pre-CA, untreated-CA, and CPR-treated phases. ResultsETCO2, BP, and CBV were similar between groups at pre- and during untreated-CA (P ≥ 0.188). During CPR, ETCO2 (36 ± 6 versus 24 ± 10 mmHg, P < 0.001), mean arterial BP (MAP; 49 ± 9 versus 37 ± 9 mmHg, P = 0.002), and CBV (11 ± 5 versus 5 ± 2 cm/s, P < 0.001) were significantly greater in the LVCC versus SCC group. Moreover, a greater proportion of animals obtained targets for ETCO2 (ETCO2 ≥ 20 mmHg; 52 % (17/33) versus 100 % (32/32), P < 0.001) and diastolic BP (DBP ≥ 25 mmHg; 82 % (33/40) versus 97 % (48/49), P = 0.020) in the LVCC versus SCC group. ConclusionIndicators of cardiac output, BP, and cerebral perfusion during CPR were greatest in the LVCC group, suggesting the quality of chest compressions during BLS CPR may be improved by performing compressions over the left ventricle compared to the centre of the chest.

Chest CT for Breast Cancer Diagnosis.

Background: We report the results of our retrospective analysis of the ability of standard chest CT scans to correctly diagnose cancer in the breast. Methods: Four hundred and fifty-three consecutive women with chest CT scans (contrast and non-contrast) preceding mammograms within one year comprise the study population. All chest CT images were reviewed by an experienced fellowship-trained chest radiologist and mammograms by an experienced fellowship-trained mammographer without the benefit of prior or ancillary studies; only four mammographic views were included for analysis. The size, location, and shape of breast masses were documented; on CT, the average Hounsfield units were measured. On both imaging modalities, the presence of lymphadenopathy, architectural distortion, skin thickening, and microcalcifications were recorded. Ultimately, the interpreting radiologist was asked to decide if a biopsy was indicated, and these recommendations were correlated with the patient’s outcome. Findings: Nineteen of four hundred and fifty-three patients had breast cancer at the time of the mammography. Breast masses were the most common finding on chest CT, leading to the recommendation for biopsy. Hounsfield units were the most important feature for discerning benign from malignant masses. CT sensitivity, specificity, and accuracy of CT for breast cancer detection was 84.21%, 99.3%, and 98.68% compared to 78.95%, 93.78%, and 93.16% for four-view mammography. Chest CT scans with or without contrast had similar outcomes for specificity and accuracy, but sensitivity was slightly less without contrast. Chest CT alone, without the benefit of prior exams and patient recall, correctly diagnosed cancer with a p-value of <0.0001 compared to mammography with the same limitations. Conclusion: Chest CT accurately diagnosed breast cancer with few false positives and negatives and did so without the need for patient recall for additional imaging.

Are Diagnostic Computed Tomography Chest Scans Sufficient for Detecting Supraclavicular in Initial Breast Cancer Staging?

<h3>Purpose/Objective(s)</h3> Initial staging workup strategies for locally advanced or suspected stage IV breast cancer can include computed tomography (CT) of the chest, abdomen, pelvis (CAP) and bone scan or, alternatively, a whole-body positron emission tomography/computed tomography (PET/CT). Variations in intravenous contrast injection site and bolus timing, arm positioning, and acquisition techniques on a CT chest scan could limit visualization of supraclavicular (SCV) and supracricoid cervical lymph nodes, which are critical for staging, prognosis, and treatment recommendations. The study's purpose is to determine whether there is a difference between the incidences of SCV and cervical lymphadenopathy detected on staging CT CAP versus PET/CT scans. <h3>Materials/Methods</h3> The records of consecutive newly diagnosed breast cancer patients who received initial staging scans at a single institution from 2012 to 2017 were reviewed in a HIPAA compliant, institutional review board-approved study. De-identified information was reviewed for inclusion: new breast cancer diagnosis, >18 years old, and availability of staging. Exclusion criteria were prior breast cancer treatment, re-staging for known recurrence, and nondiagnostic imaging examinations. Radiology reports were searched for SCV and cervical lymphadenopathy to determine the incidence detected by each imaging modality. A board certified neuroradiologist reviewed and characterized scans that noted cervical or SCV lymphadenopathy. <h3>Results</h3> The initial search resulted in 3,126 PET/CT and 631 CT CAP scans with 588 patients fulfilling the inclusion criteria. PET/CT scans had been performed in 539 patients and 49 received CT CAP and bone scans. The two groups were well matched by stage (Table 1). Metastatic cervical lymphadenopathy was detected by PET-CT in 50 patients (7.9%) versus two (3.7%) with CT CAP. Out of the 50 patients who had cervical lymphadenopathy detected by PET-CT, 30 (60%) had metastatic cervical lymphadenopathy above the level of the lung apex, the typical upper extent of a CT chest field of view. Although 25 (50%) patients had additional areas of distant metastatic disease, cervical lymphadenopathy above the thoracic inlet was the only site of distant metastasis for 13 patients (26%), and would not have been detectable by CT CAP. <h3>Conclusion</h3> PET/CT detected more cervical and SCV lymphadenopathy than CT CAP in initial staging scans for breast cancer, with 60% of those detected on PET/CTs in areas that would have been occult on standard CT chest scans. Such nodal involvement constituted the only site of distant metastatic disease in 26% of the patients. Thus, dedicated CT neck imaging may be a reasonable addition to CT CAP as an initial staging strategy to determine accurate staging and radiation treatment field volumes and borders.

Three-dimensional computed tomography reconstruction invideo-assisted thoracoscopic segmentectomy (DRIVATS): Aprospective, multicenter randomized controlled trial.

ObjectiveAnatomical segmentectomy has been proven to be a viable surgical treatment for small-size peripheral lung nodules. Three-dimensional (3D) reconstruction computed tomography (CT) has been proposed as an effective approach to overcome the challenges of encountering pulmonary anatomical variations when performing segmentectomy. Therefore, to further investigate the usefulness of preoperative 3D reconstruction CT in segmentectomy, we will conduct this prospective, multicenter randomized controlled DRIVATS study to compare the use of 3D reconstruction CT with standard chest CT in video-assisted segmentectomy (ClinicalTrials.gov ID: NCT04004494).MethodsThis study began in July 2019 and a total of 190 patients will be accrued from three clinical centers within 4 years. The main inclusion criteria are patients with a single peripheral nodule 0.8–2 cm with at least one of the following requirements: (i) histology of adenocarcinoma in situ; (ii) nodule has ≥50% ground-glass appearance on CT; (iii) radiologic surveillance confirms a long doubling time (≥400 days). Surgical procedures include segmental resection of the lesion and mediastinal lymph node sampling (subsegmental resection or combined subsegmental resection will not be included in this study). The primary endpoint is operative time. The secondary endpoints include incidence of change of surgical plan, intraoperative blood loss, conversion rate, operative accident event, incidence of postoperative complications, postoperative hospital stay, length of hospitalization, duration of chest tube placement, postoperative 30-day mortality, dissection of lymph nodes, overall survival, disease-free survival, preoperative lung function, and postoperative lung function.DiscussionThis multicenter DRIVATS study aims to verify the usefulness of preoperative 3D reconstruction CT compared with standard chest CT in segmentectomy. If successfully completed, this multicenter prospective study will provide a higher level of evidence for the use of 3D reconstruction CT in segmentectomy.

Semi-automated volumetry of pulmonary nodules: Intra-individual comparison of standard dose and chest X-ray equivalent ultralow dose chest CT scans

PurposeTo assess the performance of semi-automated volumetry of solid pulmonary nodules on single-energy tin-filtered ultralow dose (ULD) chest CT scans at a radiation dose equivalent to chest X-ray relative to standard dose (SD) chest CT scans and assess the impact of kernel and iterative reconstruction selection. MethodsNinety-four consecutive patients from a prospective single-center study were included and underwent clinically indicated SD chest CT (1.9 ± 0.8 mSv) and additional ULD chest CT (0.13 ± 0.01 mSv) in the same session. All scans were reconstructed with a soft tissue (Br40) and lung (Bl64) kernel as well as with Filtered Back Projection (FBP) and Iterative Reconstruction (ADMIRE-3 and ADMIRE-5). One hundred and forty-eight solid pulmonary nodules were identified and analysed by semi-automated volumetry on all reconstructions. Nodule volumes were compared amongst all reconstructions thereby focusing on the agreement between SD and ULD scans. ResultsNodule volumes ranged from 58.5 (28.8–126) mm3 for ADMIRE-5 Br40 ULD reconstructions to 72.5 (39–134) mm3 for FBP Bl64 SD reconstructions with significant differences between reconstructions (p < 0.001). Interscan agreement of volumes between two given reconstructions ranged from ICC = 0.605 to ICC = 0.999. Between SD and ULD scans, agreement of nodule volumes was highest for FBP Br40 (ICC = 0.995), FBP Bl64 (ICC = 0.939) and ADMIRE-5 Bl64 (ICC = 0.994) reconstructions. ADMIRE-3 reconstructions exhibited reduced interscan agreement of nodule volumes (ICCs from 0.788 − 0.882). ConclusionsThe interscan agreement of node volumes between SD and ULD is high depending on the choice of kernel and reconstruction algorithm. However, caution should be exercised when comparing two image series that were not identically reconstructed.

Quantitative estimation of pulmonary artery wedge pressure from chest radiographs by a regression convolutional neural network

Abstract Introduction Recent studies reported that a convolutional neural network (CNN; a deep learning model) can detect elevated pulmonary artery wedge pressure (PAWP) from chest radiographs, the diagnostic images most commonly used for assessing pulmonary congestion in heart failure. However, no method has been published for quantitatively estimating PAWP from such radiographs. We hypothesized that a regression CNN, an alternative type of deep learning, could be a useful tool for quantitatively estimating PAWP from chest radiographs in cardiovascular diseases. Methods We retrospectively enrolled 936 patients with cardiovascular diseases who had undergone right heart catheterization (RHC) and chest radiography and estimated PAWP by constructing a regression CNN based on the VGG16 model. We randomly categorized 80% of the data as training data (training group, n=748) and 20% as test data (test group, n=188). Moreover, we tuned the learning rate–one of the model parameters–by 5-hold cross-validation of the training group. Correlations between PAWP measured by RHC (ground truth [GT] PAWP) and PAWP derived from the regression CNN (estimated PAWP) were tested. To visualize how the regression CNN assessed the images, we created a regression activation map (RAM), a visualization technique for regression CNN. Results Estimated PAWP correlated significantly with GT PAWP in both the training (r=0.76, P&amp;lt;0.001) and test group (r=0.62, P&amp;lt;0.001). Bland-Altman plots found a mean (SEM) difference between GT and estimated PAWP of −0.23 (0.16) mm Hg in the training and −0.05 (0.41) mm Hg in the test group. The RAM showed that our regression CNN model estimated high PAWP by focusing on the cardiomegaly and pulmonary congestion. In the test group, the area under the curve (AUC) for detecting elevated PAWP (≥18 mm Hg) produced by the regression CNN model was similar to the AUC of an experienced cardiologist (0.86 vs 0.83, respectively; P=0.24). Conclusion This proof-of-concept study shows that regression CNN can quantitatively estimate PAWP from standard chest radiographs in cardiovascular diseases. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): The Bayer Academic Support

Definition, evaluation and therapy of progressive fibrosing interstitial lung disease associated with rheumatic diseases - a consensus paper of the Romanian Society of Rheumatology and Romanian Society of Pneumology

Interstitial lung diseases (ILD), of which the most well-known is idiopathic pulmonary fibrosis (IPF), are a heterogeneous group of diseases, with similar, inflammatory and/or fibrosing mechanisms, which lead to the rapid decline of lung function and implicitly to a high degree of morbidity and mortality. Besides IPF, other interstitial lung diseases, such as those associated with connective tissue diseases, the most common being rheumatoid arthritis and systemic sclerosis, can develop a progressive fibrosing phenotype. Thus, because they have similar pathogenic mechanisms and clinical manifestations, all these diseases are described under the term of progressive fibrosing interstitial lung disease (PF-ILD). It is recommended that the diagnosis, clinical and paraclinical evaluation of ILD be made through a standardized management, within a multidisciplinary team that must include a pulmonologist, radiologist and rheumatologist, evaluation after which the subsequent treatment will be decided. Early diagnosis leads to an effective therapeutic intervention and decreased mortality. The progressive character has been defined if the progression occurs despite the current optimal management and treatment, which includes glucocorticoids and immunosuppressive therapy, at which point the indication of the antifibrotic treatment appears. The complete evaluation of ILD involves a rigorous anamnesis and clinical examination to identify environmental and professional risk factors, the patient’s chronic medication, family and personal history, the onset of the disease, as well as the identification by auscultation of bilateral basal crackles. From the paraclinical examination, the most important is the imaging studies (standard chest X-rays and mandatory HR-CT) which provide information about the anatomy, pattern, evolution in time or clues related to the underlying disease. The progressive character has been defined if the progression occurs despite the current optimal management and treatment, which includes glucocorticoids and immunosuppressive therapy, at which point the indication of the antifibrotic treatment appears. Evaluation of lung function is very important to complete the patient picture with PF-ILD, and the gold standard is the combination of spirometry, body plethysmography with diffusing capacity for carbon monoxide (DLCO), gasometry and an exercise test. Using this information, the optimal treatment will be led by the same multidisciplinary team that established the diagnosis, taking into account many aspects related to the characteristics of the disease, the cause, the safety profile and it will be monitored according to the existing protocols.

Latest in Resuscitation Research: Highlights From the 2021 American Heart Association's Resuscitation Science Symposium.

Latest in Resuscitation Research: Highlights From the 2021 American Heart Association's Resuscitation Science Symposium.

Bilateral Orbital Tuberculosis with Unilateral Severe Irrversible Vision Loss in Children: A Case Report

Introduction: Tuberculosis is a transmissible infectious disease caused by mycobacterium tuberculosis. Ocular tuberculosis is rare representing between 1% to 18% of all forms of tuberculosis and only 0.3% of patients develop the orbital form. The focus is usually unilateral, we report through this observation a case of bilateral orbital tuberculosis in a 12 year old girl. Observation: A 12-year-old girl was admitted to the department of infectious and tropical diseases of the National Hospital of Zinder for long term fever and violent headache. The ophthalmological examination revealed a visual acuity of 1/10 on the right, absence of light perception on the left and bilateral exophthalmos. Biomicroscopic examination showed superficial punctate keratitis bilaterally, a normal fundus on the right and left atrophy. In view of the long-lasting fever and the biological inflammatory syndrome, the diagnosis of tuberculosis was evoked. The tuberculin intradermal test (IDR) was positive and the search for BK in the bronchial lavage revealed BAARs. HIV serology was negative. The standard chest X-ray was normal but the CT scan of the orbito- cerebral cavity showed two cystic foci with grade III exophthalmos. After 3 months of anticillary treatment the evolution was considered satisfactory. Conclusion: The orbital involvement of tuberculosis was generally unilateral, its bilateral localization is unusual. It must be systematically evoked in front of any case of bilateral exophthalmos especially in an infectious context in order to avoid irrevesible vsion loss.

A phantom study of a protective trolley for neonatal radiographic imaging: new equipment to protect the operator from scatter radiation.

Chest radiography is commonly performed as a diagnostic tool of neonatal diseases. Contact-based radiation personal protective equipment (RPPE) has been widely used for radiation protection, but it does not provide full body protection and it is often shared between users, which has become a major concern during the coronavirus disease 2019 (COVID-19) pandemic. To address these issues, we developed a novel trolley to protect radiographers against X-ray radiation by reducing scatter radiation during neonatal radiographic examinations. We measured the scatter radiation doses from a standard neonatal chest radiograph to the radiosensitive organs using a phantom operator in three protection scenarios (trolley, radiation personal protective equipment [RPPE], no protection) and at three distances. The results showed that the scatter radiation surface doses were significantly reduced when using the trolley compared with RPPE and with no protection at a short distance (P<0.05 for both scenarios in all radiosensitive organs). The novel protective trolley provides a non-contact protective tool for radiographers against the hazard of scatter radiation during neonatal radiography examinations.