Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions

Heavy smokers undergoing screening with low-dose chest CT are affected by cardiovascular disease as much as by lung cancer. Low-dose chest CT scans acquired in screening enable quantification of atherosclerotic calcifications and thus enable identification of subjects at increased cardiovascular risk. This paper presents a method for automatic detection of coronary artery, thoracic aorta and cardiac valve calcifications in low-dose chest CT using two consecutive convolutional neural networks. The first network identifies and labels potential calcifications according to their anatomical location and the second network identifies true calcifications among the detected candidates. This method was trained and evaluated on a set of 1744 CT scans from the National Lung Screening Trial. To determine whether any reconstruction or only images reconstructed with soft tissue filters can be used for calcification detection, we evaluated the method on soft and medium/sharp filter reconstructions separately. On soft filter reconstructions, the method achieved F1 scores of 0.89, 0.89, 0.67, and 0.55 for coronary artery, thoracic aorta, aortic valve and mitral valve calcifications, respectively. On sharp filter reconstructions, the F1 scores were 0.84, 0.81, 0.64, and 0.66, respectively. Linearly weighted kappa coefficients for risk category assignment based on per subject coronary artery calcium were 0.91 and 0.90 for soft and sharp filter reconstructions, respectively. These results demonstrate that the presented method enables reliable automatic cardiovascular risk assessment in all low-dose chest CT scans acquired for lung cancer screening

Systems Radiology and Personalized Medicine

Medicine has evolved into a high level of specialization using the very detailed imaging of organs [...]

The Incidence of Trilateral Retinoblastoma : A Systematic Review and Meta-Analysis

PURPOSE: To estimate the incidence of trilateral retinoblastoma in patients with retinoblastoma. " DESIGN: Systematic review and meta-analysis. METHODS: We searched Medline and Embase for scientific literature published between January 1966 and July 2015 that assessed trilateral retinoblastoma incidence. We used a random-effects model for the statistical analyses. " RESULTS: We included 23 retinoblastoma cohorts from 26 studies. For patients with bilateral retinoblastoma the unadjusted chance of developing trilateral retinoblastoma across all cohorts was 5.3% (95% confidence interval [CI]: 3.3%-7.7%); the chance of pineal trilateral retinoblastoma was 4.2% (95% CI: 2.6%-6.2%) and the chance of nonpineal trilateral retinoblastoma was 0.8% (95% CI: 0.4%-1.3%). In patients with hereditary retinoblastoma (all bilateral cases, and the unilateral cases with a family history or germline RB1 mutation) we found a trilateral retinoblastoma incidence of 4.1% (95% CI: 1.9%-7.1%) and a pineal trilateral retinoblastoma incidence of 3.7% (95% CI: 1.8%-6.2%). To reduce the risk of overestimation bias we restricted analysis to retinoblastoma cohorts with a minimum size of 100 patients, resulting in adjusted incidences of 3.8% (95% CI: 2.4%-5.4%), 2.9% (95% CI: 1.9%-4.2%), and 0.7% (95% CI: 0.3%-1.2%) for any, pineal, and nonpineal trilateral retinoblastoma, respectively, among patients with bilateral retinoblastoma. Among hereditary retinoblastoma we found an adjusted trilateral retinoblastoma incidence of 3.5% (95% CI: 1.2%-6.7%) and a pineal trilateral retinoblastoma incidence of 3.2% (95% CI: 1.4%-5.6%). CONCLUSION: The estimated incidence of trilateral retinoblastoma is lower than what is reported in previous literature, especially after exclusion of small cohorts that were subject to overestimation bias in this context. (C) 2015 by Elsevier Inc. All rights reserved.)Peer reviewe

Incidental Indeterminate Renal Lesions: Distinguishing Non-Enhancing from Potential Enhancing Renal Lesions Using Iodine Quantification on Portal Venous Dual-Layer Spectral CT

The purpose of our study is to determine a threshold for iodine quantification to distinguish definitely non-enhancing benign renal lesions from potential enhancing masses on portal venous dual-layer spectral computed tomography (CT) to reduce the need for additional multiphase CT. In this single-center retrospective study, patients (≥18 years) scanned between April 2021 and January 2023 following the local renal CT protocol were included. Exclusion criteria were patients without renal lesions, lesions smaller than 10 mm, only fat-containing lesions, abscesses or infarction, follow-up after radiofrequent ablation, wrong scan protocol, or artefacts. Scans were performed on a dual layer detector-based spectral CT (CT 7500, Philips Healthcare, Best, The Netherlands). Iodine concentration (mgI/mL) in renal lesions was determined using spectral data. Analyses were performed for all lesions and for lesions of >30 HU on portal venous CT. Enhancement on multiphase CT (≥20 ΔHU from true unenhanced (TUE) to portal venous phase (PVP) CT) was used as reference standard. To determine thresholds for iodine concentration receiver operating characteristic (ROC) curves, area under the curve (AUC) and 95% confidence intervals were calculated. To obtain thresholds for definite (non-)enhancement, 100% sensitivity with maximum specificity and 100% specificity with maximum sensitivity were noted. Data were measured using one reader. To assess interobserver agreement, a second reader performed measurements on the PVP CT scans. A total of 103 patients (62 years ± 14, 68 men) were included. We measured 328 renal lesions, 56 enhancing lesions (17%) in 38 patients and 272 non-enhancing lesions (83%) in 86 patients. The threshold for non-enhancing lesions was 0.76 mgI/mL or lower (100% sensitivity, 76% specificity). The threshold for a definite enhancing mass was 1.69 mgI/mL or higher (100% specificity, 78% sensitivity). A total of 77% of indeterminate lesions (>30 HU on PVP CT) in our study could be definitely characterized. Renal lesions can be definitively classified as non-enhancing or enhancing on PVP spectral CT using thresholds of 0.76 mgI/mL or 1.69 mgI/mL, respectively, eliminating the need for multiphase imaging

Abdominal aortic calcification: from ancient friend to modern foe

BACKGROUND: Abdominal aortic calcifications were already ubiquitous in ancient populations from all continents. Although nowadays generally considered as an innocent end stage of stabilised atherosclerotic plaques, increasing evidence suggests that arterial calcifications contribute to cardiovascular risk. In this review we address abdominal aortic calcification from an evolutionary perspective and review the literature on histology, prevalence, risk factors, clinical outcomes and pharmacological interventions of abdominal aortic calcification. DESIGN: The design of this study was based on a literature review. METHODS: Pubmed and Embase were systematically searched for articles on abdominal aortic calcification and its synonyms without language restrictions. Articles with data on histology, prevalence, risk factors clinical outcomes and/or pharmacological interventions were selected. RESULTS: Abdominal aortic calcification is highly prevalent in the general population and prevalence and extent increase with age. Prevalence and risk factors differ between males and females and different ethnicities. Risk factors include traditional cardiovascular risk factors and decreased bone mineral density. Abdominal aortic calcification is shown to contribute to arterial stiffness and is a strong predictor of cardiovascular events and mortality. Several therapies to inhibit arterial calcification have been developed and investigated in small clinical trials. CONCLUSIONS: Abdominal aortic calcification is from all eras and increasingly acknowledged as an independent contributor to cardiovascular disease. Large studies with long follow-up must be carried out to show whether inhibition of abdominal aortic calcification will further reduce cardiovascular risk