We conclude that a reduced slice thickness may have an important positive impact on the treatment and outcome of patients with pulmonary metastases. The use of 3-mm slice thickness helical CT may raise the sensitivity for pulmonary metastases detection compared to 5-mm images, but the rate of false positive results may also increase.
The proliferation of digital data sets and the increasing amount of images, e. g. through the use of multislice spiral CT or multiple follow-up examinations in the context of new therapies, are ideal prerequisites for computer-aided diagnosis (CAD) in chest radiology. Multiple studies have described the applications and advantages of computer assistance in performing different diagnostic tasks. More powerful computers will enable the introduction of these systems into the clinical routine and could provide an enormous increase in morphological and functional information. The commercial introduction of tools for detection and visualization of pulmonary nodules has already begun. This is one of the most widely-reported applications in view of the ongoing studies on lung cancer screening. The next generation of tools will improve the diagnosis of emphysema through detection, quantification and classification. Many more uses are being developed, for instance the detection and classification of infiltrates, volume measurements or functional pulmonary imaging (e. g. dynamic ventilation CT or (3)Helium-MRI). Grossly simplified, most systems use a three level structure consisting of segmentation/feature extraction, classification of extracted features and an output unit. The output can be mere visualization through color-coding, volume measurements or calculated probabilities. The output supports the radiologist in establishing his findings and preparing differential and final diagnoses as well as providing quantitative data for follow-up studies. Different techniques are used for segmentation of lung areas as the basis for a variety of applications. Some commonly-used techniques for this and other tasks are density masks and threshold-based algorithms. Data processing is predominantly carried out with Bayesian classifiers or neural networks. This article describes the current status of research and provides insight into the common schemes and capabilities of the systems. It focuses particularly on common topics such as segmentation, volume measurement, detection of pulmonary nodules, quantification of emphysema and analysis of ground glass opacities.
In HRCT reports multiple different, often synonymous, German and English terms are used. The variety of terms impede understanding and acceptance of HRCT. Purpose of this paper is to present a scheme, which is based on the anatomic landmarks (secondary lobule), and the density of pathologic changes, as well as a glossary from the German HRCT-literature, including suitable terms, definitions, synonyms and English terms. Low attenuation changes include emphysemas, air-filled cavities (bullae, cysts, cavitations, honeycombing) and bronchial dilatation, changes with increased density consist of diffuse (ground glass opacity, consolidation) and focal processes (reticular and nodular densities). Reticular densities are categorised in thickened interlobular septae and translobular lines with differentiation of a reticular pattern and curvilinear lines. Nodular processes are categorised according to size, density, morphology, localisation and distribution. Parenchymal distortion and destruction indicate the severity of these processes. Certain patterns are indicative for possible differential diagnoses, and a recommendation for further procedures is given.
Current imaging methods of the lung concentrate on morphology as well as on the depiction of the pulmonary parenchyma. The need of an advanced and more subtle imaging technology compared to conventional radiography is met by computed topography as the method of choice. Nevertheless, computed tomography yields very limited functional information. This is to be derived from arterial blood gas analysis, spirometry and body plethysmography. These methods, however, lack the scope for regional allocation of any pathology. Magnetic resonance imaging of the lung has been advanced by the use of hyperpolarised (3)Helium as an inhaled gaseous contrast agent. The inhalation of the gas provides functional data by distribution, diffusion and relaxation of its hyperpolarised state. Because anatomical landmarks of the lung can be visualised as well, functional information can be linked with regional information. Furthermore, the method provides high spatial and temporal resolution and lacks the potential side-effects of ionising radiation. Four different modalities have been established: 1. Spin density imaging studies the distribution of gas, normally after a single inhalation of contrast gas in inspiratory breath hold. 2. Dynamic cine imaging studies the distribution of gas with respect to regional time constants of pulmonary gas inflow. 3. Diffusion weighted imaging can exhibit the presence and severity of pulmonary airspace enlargement, as in pulmonary emphysema. 4. Oxygen sensitive imaging displays intrapulmonary oxygen partial pressure and its distribution. Currently, the method is limited by comparably high costs and limited availability. As there have been recent developments which might bring this modality closer to clinical use, this review article will comprise the methodology as well as the current state of the art and standard of knowledge of magnetic resonance imaging of the lung using hyperpolarised (3)Helium.
Self-organizing neural nets combined with fuzzy rules are ready for use in the automatic detection and volumetry of the spleen in spiral CT scans.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.