Analysis of arterial sub-trees affected by Pulmonary Emboli

©2004 SPIE--The International Society for Optical Engineering. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. The electronic version of this article is the complete one and can be found online at: http://dx.doi.org/10.1117/12.535993DOI: 10.1117/12.535993Presented at Medical imaging 2004. Image processing : 16-19 February 2004, San Diego, California, USA.Although Pulmonary Embolism (PE) is one of the most common causes of unexpected death in the U.S., it may also be one of the most preventable. Images acquired from 16-slice Computed Tomography (CT) machines of contrast-injected patients provide sufficient resolution for the localization and analysis of emboli located in segmental and sub-segmental arteries. After a PE is found, it is difficult to assess the local characteristics of the affected arterial tree without automation. We propose a method to compute characteristics of the local arterial tree given the location of a PE. The computed information localizes the portion of the arterial tree that is affected by the embolism. Our method is based on the segmentation of the arteries and veins followed by a localized tree computation at the given site. The method determines bifurcation points and the remaining arterial tree. A preliminary segmentation method is also demonstrated to locally eliminate over-segmentation of the arterial tree. The final result can then be used assess the affected lung volume and arterial supply. Initial tests revealed a good ability to compute local tree characteristics of selected sites

Mathematical modeling of thermal power plant's boiler air-gas flow path regulation modes

В работе предлагаются математические модели газовоздушного тракта котла и механизмов собственных нужд ТЭС. С использованием табличных и графических представлений напорных характеристик серийных вентиляторов и дымососов получены эквивалентные соотношения для сети механизмов. Исследована задача нахождения оптимальных параметров управления для группы центробежных механизмов, обеспечивающих работу газовоздушного тракта котла. Исследовано влияние разрежения в топке котла на режим работы его вспомогательных механизмов. Приводятся результаты моделирования для типичных последовательно-параллельных соединений механизмов в гидравлических сетях ТЭС.The paper presents a mathematical model for thermal power plant's boiler air-gas flow paths and auxiliaries. With application of production fans' and flue gas extractor fans' head-capacity curves and tables, equivalent relations for the net of the mechanisms are obtained. A problem of determining the optimal control parameters for a group of centrifugal mechanisms in the air-gas path is studied. The effect of the boiler furnace draft on its auxiliaries operation is analyzed. The results of mathematical modeling for typical serial and parallel connections of the mechanisms in the thermal power plant hydraulic network are given

Identification of an autoantibody panel to separate lung cancer from smokers and nonsmokers

<p>Abstract</p> <p>Background</p> <p>Sera from lung cancer patients contain autoantibodies that react with tumor associated antigens (TAAs) that reflect genetic over-expression, mutation, or other anomalies of cell cycle, growth, signaling, and metabolism pathways.</p> <p>Methods</p> <p>We performed immunoassays to detect autoantibodies to ten tumor associated antigens (TAAs) selected on the basis of previous studies showing that they had preferential specificity for certain cancers. Sera examined were from lung cancer patients (22); smokers with ground-glass opacities (GGOs) (46), benign solid nodules (55), or normal CTs (35); and normal non-smokers (36). Logistic regression models based on the antibody biomarker levels among the high risk and lung cancer groups were developed to identify the combinations of biomarkers that predict lung cancer in these cohorts.</p> <p>Results</p> <p>Statistically significant differences in the distributions of each of the biomarkers were identified among all five groups. Using Receiver Operating Characteristic (ROC) curves based on age, c-myc, Cyclin A, Cyclin B1, Cyclin D1, CDK2, and survivin, we obtained a sensitivity = 81% and specificity = 97% for the classification of cancer vs smokers(no nodules, solid nodules, or GGO) and correctly predicted 31/36 healthy controls as noncancer.</p> <p>Conclusion</p> <p>A pattern of autoantibody reactivity to TAAs may distinguish patients with lung cancer versus smokers with normal CTs, stable solid nodules, ground glass opacities, or normal healthy never smokers.</p

CT Scan Screening for Lung Cancer: Risk Factors for Nodules and Malignancy in a High-Risk Urban Cohort

Low-dose computed tomography (CT) for lung cancer screening can reduce lung cancer mortality. The National Lung Screening Trial reported a 20% reduction in lung cancer mortality in high-risk smokers. However, CT scanning is extremely sensitive and detects non-calcified nodules (NCNs) in 24-50% of subjects, suggesting an unacceptably high false-positive rate. We hypothesized that by reviewing demographic, clinical and nodule characteristics, we could identify risk factors associated with the presence of nodules on screening CT, and with the probability that a NCN was malignant.We performed a longitudinal lung cancer biomarker discovery trial (NYU LCBC) that included low-dose CT-screening of high-risk individuals over 50 years of age, with more than 20 pack-year smoking histories, living in an urban setting, and with a potential for asbestos exposure. We used case-control studies to identify risk factors associated with the presence of nodules (n=625) versus no nodules (n=557), and lung cancer patients (n=30) versus benign nodules (n=128).The NYU LCBC followed 1182 study subjects prospectively over a 10-year period. We found 52% to have NCNs >4 mm on their baseline screen. Most of the nodules were stable, and 9.7% of solid and 26.2% of sub-solid nodules resolved. We diagnosed 30 lung cancers, 26 stage I. Three patients had synchronous primary lung cancers or multifocal disease. Thus, there were 33 lung cancers: 10 incident, and 23 prevalent. A sub-group of the prevalent group were stable for a prolonged period prior to diagnosis. These were all stage I at diagnosis and 12/13 were adenocarcinomas.NCNs are common among CT-screened high-risk subjects and can often be managed conservatively. Risk factors for malignancy included increasing age, size and number of nodules, reduced FEV1 and FVC, and increased pack-years smoking. A sub-group of screen-detected cancers are slow-growing and may contribute to over-diagnosis and lead-time biases

The Lung Image Database Consortium (LIDC): An Evaluation of Radiologist Variability in the Identification of Lung Nodules on CT Scans

RATIONALE AND OBJECTIVES: The purpose of this study was to analyze the variability of experienced thoracic radiologists in the identification of lung nodules on CT scans and thereby to investigate variability in the establishment of the “truth” against which nodule-based studies are measured. MATERIALS AND METHODS: Thirty CT scans were reviewed twice by four thoracic radiologists through a two-phase image annotation process. During the initial “blinded read” phase, radiologists independently marked lesions they identified as “nodule ≥ 3mm (diameter),” “nodule < 3mm,” or “non-nodule ≥ 3mm.” During the subsequent “unblinded read” phase, the blinded read results of all radiologists were revealed to each of the four radiologists, who then independently reviewed their marks along with the anonymous marks of their colleagues; a radiologist’s own marks then could be deleted, added, or left unchanged. This approach was developed to identify, as completely as possible, all nodules in a scan without requiring forced consensus. RESULTS: After the initial blinded read phase, a total of 71 lesions received “nodule ≥ 3mm” marks from at least one radiologist; however, all four radiologists assigned such marks to only 24 (33.8%) of these lesions. Following the unblinded reads, a total of 59 lesions were marked as “nodule ≥ 3 mm” by at least one radiologist. 27 (45.8%) of these lesions received such marks from all four radiologists, 3 (5.1%) were identified as such by three radiologists, 12 (20.3%) were identified by two radiologists, and 17 (28.8%) were identified by only a single radiologist. CONCLUSION: The two-phase image annotation process yields improved agreement among radiologists in the interpretation of nodules ≥ 3mm. Nevertheless, substantial variabilty remains across radiologists in the task of lung nodule identification

Doctors as servants of patients: Surely we can do better than this

©2004 SPIE--The International Society for Optical Engineering. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. The electronic version of this article is the complete one and can be found online at: DOI Link: http://dx.doi.org/10.1117/12.532892Presented at Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display,: 15 February 2004, San Diego, California, USA.DOI: 10.1117/12.532892Pulmonary Embolism (PE) is one of the most common causes of unexpected death in the US. The recent introduction of 16-slice Computed Tomography (CT) machines allows the acquisition of very high-resolution datasets. This has made CT a more attractive means for diagnosing PE, especially for previously difficult to identify small subsegmental peripheral emboli. However, the large size of these datasets makes it desirable to have an automated method to help radiologists focus directly on potential candidates that might otherwise be overlooked. We propose a novel method to highlight potential PEs on a 3D representation of the pulmonary arterial tree. First lung vessels are segmented using mathematical morphology techniques. The density values inside the vessels are then used to color the outside of a Shaded Surface Display (SSD) of the vessel tree. As PEs are clots of significantly lower Hounsfield Unit (HU) values than surrounding contrast-enhanced blood, they appear as salient contrasted patches in this 3D rendering. During preliminary testing on 6 datasets 19 PEs out of 22 were detected (sensitivity 86%) with 2 false positives for every true positive (Positive Predictive Value 33%)