Abstract-Pulmonary embolism (PE) is a common life-threatening disorder for which an early diagnosis is desirable. We propose a new system for the automatic detection of PE in contrast-enhanced CT images. The system consists of candidate detection, feature computation and classification. Candidate detection focusses on the inclusion of PE-even complete occlusions-and the exclusion of false detections, such as tissue and parenchymal diseases. Feature computation does not only focus on the intensity, shape and size of an embolus, but also on locations and the shape of the pulmonary vascular tree. Several classifiers have been tested and the results show that the performance is optimized by using a bagged tree classifier with two features based on the shape of a blood vessel and the distance to the vessel boundary. The system was trained on 38 CT data sets. Evaluation on 19 other data sets showed that the system generalizes well. The sensitivity of our system on the evaluation data is 63% at 4.9 false positives per data set, which allowed the radiologist to improve the number of detected PE by 22%.Index Terms-Computed-aided detection, computed tomography (CT), pulmonary embolism (PE).

PurposeThe 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.MethodsIn 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.ResultsOriginal 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 ≤5 FP were found, 13% of studies had ≥10 FP.ConclusionCAD 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.

There is a strong association between CT image quality and the number of FP findings indicated by a CAD algorithm for the detection of PE.

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<p class="p1">The projected increase in poleward moisture transport (PMT) towards warmer climate has mainly been linked to the larger moisture holding capacity of warmer air masses. However, the future of interannual fluctuations of PMT and associated driving mechanisms are fairly uncertain. This study demonstrates the extent to which atmospheric rivers (ARs) explain the interannual variability of PMT, as well as related variables such as temperature, precipitation and sea ice. Such linkages help to clarify if extreme precipitation or melt events over Arctic regions are dominantly caused by the occurrence of ARs. A main focus is set on the impact of ARs on Arctic sea ice on interannual timescales, which so far has been poorly studied, and varies from colder to warmer climates.</p> <p class="p1">To robustly study these interannual linkages of ARs and Arctic Climate, we examine Arctic ARs in long climate runs of one present and two future climates (+2°C and +3°C), simulated by the global climate model EC-Earth 2.3. To enhance the significance of the results, three different moisture thresholds were used to detect ARs. Further, the use of additional thresholds relative to the 2°C and 3° warmer climates allowed a distinction between thermodynamic and dynamic processes that lead to changes of ARs from colder to warmer climates. It is found that most PMT variability is driven by ARs, and that the share of ARs which explain moisture transport increases towards warmer climates. We also discuss the role of the position and strength of the jet stream in driving AR variability and highlight the importance of ARs in generating interannual fluctuations of Arctic climate variables such as temperature and precipitation.</p>