Optimization Strategies for Interactive Classification of Interstitial Lung Disease Textures

For computerized analysis of textures in interstitial lung disease, manual annotations of lung tissue are necessary. Since making these annotations is labor intensive, we previously proposed an interactive annotation framework. In this framework, observers iteratively trained a classifier to distinguish the different texture types by correcting its classification errors. In this work, we investigated three ways to extend this approach, in order to decrease the amount of user interaction required to annotate all lung tissue in a computed tomography scan. First, we conducted automatic classification experiments to test how data from previously annotated scans can be used for classification of the scan under consideration. We compared the performance of a classifier trained on data from one observer, a classifier trained on data from multiple observers, a classifier trained on consensus training data, and an ensemble of classifiers, each trained on data from different sources. Experiments were conducted without and with texture selection (ts). In the former case, training data from all eight textures was used. In the latter, only training data from the texture types present in the scan were used, and the observer would have to indicate textures contained in the scan to be analyzed. Second, we simulated interactive annotation to test the effects of (1) asking observers to perform ts before the start of annotation, (2) the use of a classifier trained on data from previously annotated scans at the start of annotation, when the interactive classifier is untrained, and (3) allowing observers to choose which interactive or automatic classification results they wanted to correct. Finally, various strategies for selecting the classification results that were presented to the observer were considered. Classification accuracies for all possible interactive annotation scenarios were compared. Using the best-performing protocol, in which observers select the textures that should be distinguished in the scan and in which they can choose which classification results to use for correction, a median accuracy of 88% was reached. The results obtained using this protocol were significantly better than results obtained with other interactive or automatic classification protocols

Artificial Intelligence-based Quantification of Pleural Plaque Volume and Association with Lung Function in Asbestos-exposed Patients

Purpose: Pleural plaques (PPs) are morphologic manifestations of long-term asbestos exposure. The relationship between PP and lung function is not well understood, whereas the time-consuming nature of PP delineation to obtain volume impedes research. To automate the laborious task of delineation, we aimed to develop automatic artificial intelligence (AI)-driven segmentation of PP. Moreover, we aimed to explore the relationship between pleural plaque volume (PPV) and pulmonary function tests.Materials and Methods: Radiologists manually delineated PPs retrospectively in computed tomography (CT) images of patients with occupational exposure to asbestos (May 2014 to November 2019). We trained an AI model with a no-new-UNet architecture. The Dice Similarity Coefficient quantified the overlap between AI and radiologists. The Spearman correlation coefficient (r) was used for the correlation between PPV and pulmonary function test metrics. When recorded, these were vital capacity (VC), forced vital capacity (FVC), and diffusing capacity for carbon monoxide (DLCO).Results: We trained the AI system on 422 CT scans in 5 folds, each time with a different fold (n = 84 to 85) as a test set. On these independent test sets combined, the correlation between the predicted volumes and the ground truth was r = 0.90, and the median overlap was 0.71 Dice Similarity Coefficient. We found weak to moderate correlations with PPV for VC (n = 80, r = -0.40) and FVC (n = 82, r = -0.38), but no correlation for DLCO (n = 84, r = -0.09). When the cohort was split on the median PPV, we observed statistically significantly lower VC (P = 0.001) and FVC (P = 0.04) values for the higher PPV patients, but not for DLCO (P = 0.19).Conclusion: We successfully developed an AI algorithm to automatically segment PP in CT images to enable fast volume extraction. Moreover, we have observed that PPV is associated with loss in VC and FVC.</p

Computer-assisted detection of pulmonary embolism: evaluation of pulmonary CT angiograms performed in an on-call setting

Item does not contain fulltextPURPOSE: The purpose of the study was to assess the stand-alone performance of computer-assisted detection (CAD) for evaluation of pulmonary CT angiograms (CTPA) performed in an on-call setting. METHODS: In this institutional review board-approved study, we retrospectively included 292 consecutive CTPA performed during night shifts and weekends over a period of 16 months. Original reports were compared with a dedicated CAD system for pulmonary emboli (PE). A reference standard for the presence of PE was established using independent evaluation by two readers and consultation of a third experienced radiologist in discordant cases. RESULTS: Original reports had described 225 negative studies and 67 positive studies for PE. CAD found PE in seven patients originally reported as negative but identified by independent evaluation: emboli were located in segmental (n = 2) and subsegmental arteries (n = 5). The negative predictive value (NPV) of the CAD algorithm was 92% (44/48). On average there were 4.7 false positives (FP) per examination (median 2, range 0-42). In 72% of studies or=10 FP. CONCLUSION: CAD identified small emboli originally missed under clinical conditions and found 93% of the isolated subsegmental emboli. On average there were 4.7 FP per examination.1 april 201

Visceral Adipose Tissue and Different Measures of Adiposity in Different Severities of Diffuse Idiopathic Skeletal Hyperostosis

BACKGROUND: Diffuse idiopathic skeletal hyperostosis (DISH) is associated with both obesity and type 2 diabetes. Our objective was to investigate the relation between DISH and visceral adipose tissue (VAT) in particular, as this would support a causal role of insulin resistance and low grade inflammation in the development of DISH. METHODS: In 4334 patients with manifest vascular disease, the relation between different adiposity measures and the presence of DISH was compared using z-scores via standard deviation logistic regression analyses. Analyses were stratified by sex and adjusted for age, systolic blood pressure, diabetes, non-HDL cholesterol, smoking status, and renal function. RESULTS: DISH was present in 391 (9%) subjects. The presence of DISH was associated with markers of adiposity and had a strong relation with VAT in males (OR: 1.35; 95%CI: 1.20-1.54) and females (OR: 1.43; 95%CI: 1.06-1.93). In males with the most severe DISH (extensive ossification of seven or more vertebral bodies) the association between DISH and VAT was stronger (OR: 1.61; 95%CI: 1.31-1.98), while increased subcutaneous fat was negatively associated with DISH (OR: 0.65; 95%CI: 0.49-0.95). In females, increased subcutaneous fat was associated with the presence of DISH (OR: 1.43; 95%CI: 1.14-1.80). CONCLUSION: Markers of adiposity, including VAT, are strongly associated with the presence of DISH. Subcutaneous adipose tissue thickness was negatively associated with more severe cases of DISH in males, while in females, increased subcutaneous adipose tissue was associated with the presence of DISH

Imaging of acute pulmonary embolism using multi-detector CT angiography: an update on imaging technique and interpretation

Computed tomography angiography (CTA) of the pulmonary arteries has become the main diagnostic test for the evaluation of pulmonary embolism (PE). Not only due to the good availability, low cost and minimal invasiveness of this technique, but mainly because of the introduction of multi-detector CT techniques resulting in significant improvement in resolution, speed and image quality. This continuous gain in image acquisition speed went along with the introduction of new techniques of image acquisition, such as the dual-source CT scanning and novel concepts of image interpretation beyond morphological findings including the definition of the resulting perfusion defects and assessment of the cardiopulmonary circulation as a functional unit. This article will focus on technical and practical aspects to optimize CTPA examinations with modern multi-detector CT scanners, discusses aspects to be considered in specific patient groups (e.g., during pregnancy, young patients) and outlines new advents such as dual-source lung perfusion and automatic detection of pulmonary embol

Comparison of automated 4-chamber cardiac views versus axial views for measuring right ventricular enlargement in patients with suspected pulmonary embolism

PURPOSE: Compare the right ventricle to left ventricle (RV/LV) diameter ratio obtained from axial pulmonary CT angiograms (CTPA) with those derived from automatically generated 4-chamber (4-CH) reformats in patients with suspected pulmonary embolism (PE). METHODS: In this institutional review board-approved study we included 120 consecutive non ECG-gated CTPA from 3 institutions (mean age 60 ± 16 years; 71 women). Twenty 64-slice CTPA with PE and 20 without PE were selected per institution. For each patient the RV/LV diameter ratio was obtained from both axial CTPA images and automatically generated 4-CH reformats. Measurements were performed twice in two separated sessions by 2 experienced radiologists and 2 residents. The differences between the measurements on both views were evaluated. RESULTS: The 4-CH view was successfully obtained in 113 patients. The mean axial and 4-CH diameter ratios were comparable for three of the four readers (p = 0.56, p = 0.13, p = 0.08). Although the mean diameters (1.0 and 1.03 respectively) for one resident were significantly different (p = 0.013), the difference of 0.03 seems negligible in clinical routine. Three readers achieved equally high intra-reader agreements with both measurements (ICCs of 0.94, 0.95 and 0.96), while one reader showed a different variability with ICCs of 0.96 for the axial view and 0.91 for the 4-CH view. The inter-reader agreement was equally high for both measurement types with ICCs of 0.95 and 0.94, respectively. CONCLUSION: In patients with suspected PE, RV/LV diameters ratio can be measured with the same reproducibility and accuracy using an automatically generated 4-CH view compared to the axial vie

Visceral Adipose Tissue and Different Measures of Adiposity in Different Severities of Diffuse Idiopathic Skeletal Hyperostosis

Contains fulltext : 236989.pdf (Publisher’s version ) (Open Access

Direct X-ray radiogrammetry versus dual-energy X-ray absorptiometry: assessment of bone density in children treated for acute lymphoblastic leukaemia and growth hormone deficiency

BACKGROUND: In recent years interest in bone densitometry in children has increased. OBJECTIVE: To evaluate the clinical application of digital X-ray radiogrammetry (DXR) and compare the results with those of dual-energy X-ray absorptiometry (DXA). MATERIALS AND METHODS: A total of 41 children with acute lymphoblastic leukaemia (ALL) and 26 children with growth hormone deficiency (GHD) were included in this longitudinal study. Radiographs of the left hand were obtained and used for DXR. DXA of the total body and of the lumbar spine was performed. RESULTS: In both study populations significant correlations between DXR and DXA were found, and, with the exception of the correlation between DXR bone mineral density (DXR-BMD) and bone mineral apparent density in the GHD population, all correlations had a P-value of <0.001. During treatment a change in DXR-BMD was found in children with GHD. CONCLUSIONS: Our study showed that DXR in a paediatric population shows a strong correlation with DXA of the lumbar spine and total body and that it is able to detect a change in BMD during treatmen

Observer variability for Lung-RADS categorisation of lung cancer screening CTs: impact on patient management

Objectives: Lung-RADS represents a categorical system published by the American College of Radiology to standardise management in lung cancer screening. The purpose of the study was to quantify how well readers agree in assigning Lung-RADS categories to screening CTs; secondary goals were to assess causes of disagreement and evaluate its impact on patient management. Methods: For the observer study, 80 baseline and 80 follow-up scans were randomly selected from the NLST trial covering all Lung-RADS categories in an equal distribution. Agreement of seven observers was analysed using Cohen’s kappa statistics. Discrepancies were correlated with patient management, test performance and diagnosis of malignancy within the scan year. Results: Pairwise interobserver agreement was substantial (mean kappa 0.67, 95% CI 0.58–0.77). Lung-RADS category disagreement was seen in approximately one-third (29%, 971) of 3360 reading pairs, resulting in different patient management in 8% (278/3360). Out of the 91 reading pairs that referred to scans with a tumour diagnosis within 1 year, discrepancies in only two would have resulted in a substantial management change. Conclusions: Assignment of lung cancer screening CT scans to Lung-RADS categories achieves substantial interobserver agreement. Impact of disagreement on categorisation of malignant nodules was low. Key Points: • Lung-RADS categorisation of low-dose lung screening CTs achieved substantial interobserver agreement. • Major cause for disagreement was assigning a different nodule as risk-dominant. • Disagreement led to a different follow-up time in 8% of reading pairs