Comparison of magnetic resonance imaging of inhaled SF6 with respiratory gas analysis

Magnetic resonance imaging of inhaled fluorinated inert gases ((19)F-MRI) such as sulfur hexafluoride (SF(6)) allows for analysis of ventilated air spaces. In this study, the possibility of using this technique to image lung function was assessed. For this, (19)F-MRI of inhaled SF(6) was compared with respiratory gas analysis, which is a global but reliable measure of alveolar gas fraction. Five anesthetized pigs underwent multiple-breath wash-in procedures with a gas mixture of 70% SF(6) and 30% oxygen. Two-dimensional (19)F-MRI and end-expiratory gas fraction analysis were performed after 4 to 24 inhaled breaths. Signal intensity of (19)F-MRI and end-expiratory SF(6) fraction were evaluated with respect to linear correlation and reproducibility. Time constants were estimated by both MRI and respiratory gas analysis data and compared for agreement. A good linear correlation between signal intensity and end-expiratory gas fraction was found (correlation coefficient 0.99+/-0.01). The data were reproducible (standard error of signal intensity 8% vs. that of gas fraction 5%) and the comparison of time constants yielded a sufficient agreement. According to the good linear correlation and the acceptable reproducibility, we suggest the (19)F-MRI to be a valuable tool for quantification of intrapulmonary SF(6) and hence lung function.

Wild-type and splice-variant secretin receptors in lung cancer: overexpression in carcinoid tumors and peritumoral lung tissue

Gastrointestinal peptide hormone receptors, like somatostatin receptors, are often overexpressed in human cancer, allowing receptor-targeted tumor imaging and therapy. A novel candidate for these applications is the secretin receptor recently identified in pancreatic and cholangiocellular carcinomas. In the present study, secretin receptors were assessed in a non-gastrointestinal tissue, the human lung. Non-small-cell lung cancers (n=26), small-cell lung cancers (n=10), bronchopulmonary carcinoid tumors (n=29), and non-neoplastic lung (n=46) were investigated for secretin receptor protein expression with in vitro receptor autoradiography, using (125)I-[Tyr(10)] rat secretin and for secretin receptor transcripts with RT-PCR. Secretin receptor protein expression was found in 62% of bronchopulmonary carcinoids in moderate to high density, in 12% of non-small cell lung cancers in low density, but not in small cell lung cancers. In tumors found to be secretin receptor positive by autoradiography, RT-PCR revealed transcripts for the wild-type secretin receptor and for novel secretin receptor splice variants. In the non-neoplastic lung, secretin receptor protein expression was observed in low density along the alveolar septa in direct tumor vicinity in cases of acute inflammation, but not in histologically normal lung. In the autoradiographically positive peritumoral lung, RT-PCR showed transcripts for the wild-type secretin receptor and for a secretin receptor spliceoform different from those occurring in lung and gut tumors. In conclusion, secretin receptors are new markers for bronchopulmonary carcinoid tumors, and represent the molecular basis for an in vivo targeting of carcinoid tumors for diagnosis and therapy. Furthermore, secretin receptors may play a role in peritumoral lung pathophysiology. Secretin receptor mis-splicing specifically occurs in tumor and non-tumor lung pathology.

Narrow band imaging (NBI) during medical thoracoscopy: first impressions

Background This is the first ever evaluation of narrow band imaging (NBI), an innovative endoscopic imaging procedure, for the visualisation of pleural processes. Methods The pleural cavity was examined in 26 patients with pleural effusions using both white light and narrow band imaging during thoracoscopy under local anaesthesia. Results In the great majority of the patients narrow band imaging depicted the blood vessels more clearly than white light, but failed to reveal any differences in number, shape or size. Only in a single case with pleura thickened by chronic inflammation and metastatic spread of lung cancer did narrow band imaging show vessels that were not detectable under white light. Conclusion It is not yet possible to assess to what extent the evidence provided by NBI is superior to that achieved with white light. Further studies are required, particularly in the early stages of pleural processes.

Visualization of alveolar recruitment in a porcine model of unilateral lung lavage using 3He-MRI

BACKGROUND: In the acute respiratory distress syndrome potentially recruitable lung volume is currently discussed. (3)He-magnetic resonance imaging ((3)He-MRI) offers the possibility to visualize alveolar recruitment directly. METHODS: With the approval of the state animal care committee, unilateral lung damage was induced in seven anesthetized pigs by saline lavage of the right lungs. The left lung served as an intraindividual control (healthy lung). Unilateral lung damage was confirmed by conventional proton MRI and spiral-CT scanning. The total aerated lung volume was determined both at a positive end-expiratory pressure (PEEP) of 0 and 10 mbar from three-dimensionally reconstructed (3)He images, both for healthy and damaged lungs. The fractional increase of aerated volume in damaged and healthy lungs, followed by a PEEP increase from 0 to 10 mbar, was compared. RESULTS: Aerated gas space was visualized with a high spatial resolution in the three-dimensionally reconstructed (3)He-MR images, and aeration defects in the lavaged lung matched the regional distribution of atelectasis in proton MRI. After recruitment and PEEP increase, the aerated volume increased significantly both in healthy lungs from 415 ml [270-445] (median [min-max]) to 481 ml [347-523] and in lavaged lungs from 264 ml [71-424] to 424 ml [129-520]. The fractional increase in lavaged lungs was significantly larger than that in healthy lungs (healthy: 17% [11-38] vs. lavage: 42% [14-90] (P=0.031). CONCLUSION: The (3)He-MRI signal might offer an experimental approach to discriminate atelectatic vs. poor aerated lung areas in a lung damage animal model. Our results confirm the presence of potential recruitable lung volume by either alveolar collapse or alveolar flooding, in accordance with previous reports by computed tomography.

Dose optimization approach to fast X-ray microtomography of the lung alveoli

A basic prerequisite for in vivo X-ray imaging of the lung is the exact determination of radiation dose. Achieving resolutions of the order of micrometres may become particularly challenging owing to increased dose, which in the worst case can be lethal for the imaged animal model. A framework for linking image quality to radiation dose in order to optimize experimental parameters with respect to dose reduction is presented. The approach may find application for current and future in vivo studies to facilitate proper experiment planning and radiation risk assessment on the one hand and exploit imaging capabilities on the other.

Optimal dose levels in screening chest CT for unimpaired detection and volumetry of lung nodules, with and without computer assisted detection at minimal patient radiation

OBJECTIVES The aim of this phantom study was to minimize the radiation dose by finding the best combination of low tube current and low voltage that would result in accurate volume measurements when compared to standard CT imaging without significantly decreasing the sensitivity of detecting lung nodules both with and without the assistance of CAD. METHODS An anthropomorphic chest phantom containing artificial solid and ground glass nodules (GGNs, 5-12 mm) was examined with a 64-row multi-detector CT scanner with three tube currents of 100, 50 and 25 mAs in combination with three tube voltages of 120, 100 and 80 kVp. This resulted in eight different protocols that were then compared to standard CT sensitivity (100 mAs/120 kVp). For each protocol, at least 127 different nodules were scanned in 21-25 phantoms. The nodules were analyzed in two separate sessions by three independent, blinded radiologists and computer-aided detection (CAD) software. RESULTS The mean sensitivity of the radiologists for identifying solid lung nodules on a standard CT was 89.7% ± 4.9%. The sensitivity was not significantly impaired when the tube and current voltage were lowered at the same time, except at the lowest exposure level of 25 mAs/80 kVp [80.6% ± 4.3% (p = 0.031)]. Compared to the standard CT, the sensitivity for detecting GGNs was significantly lower at all dose levels when the voltage was 80 kVp; this result was independent of the tube current. The CAD significantly increased the radiologists' sensitivity for detecting solid nodules at all dose levels (5-11%). No significant volume measurement errors (VMEs) were documented for the radiologists or the CAD software at any dose level. CONCLUSIONS Our results suggest a CT protocol with 25 mAs and 100 kVp is optimal for detecting solid and ground glass nodules in lung cancer screening. The use of CAD software is highly recommended at all dose levels.

Lung Volume Reduction in Pulmonary Emphysema from the Radiologist's Perspective

Pulmonary emphysema causes decrease in lung function due to irreversible dilatation of intrapulmonary air spaces, which is linked to high morbidity and mortality. Lung volume reduction (LVR) is an invasive therapeutical option for pulmonary emphysema in order to improve ventilation mechanics. LVR can be carried out by lung resection surgery or different minimally invasive endoscopical procedures. All LVR-options require mandatory preinterventional evaluation to detect hyperinflated dysfunctional lung areas as target structures for treatment. Quantitative computed tomography can determine the volume percentage of emphysematous lung and its topographical distribution based on the lung's radiodensity. Modern techniques allow for lobebased quantification that facilitates treatment planning. Clinical tests still play the most important role in post-interventional therapy monitoring, but CT is crucial in the detection of postoperative complications and foreshadows the method's high potential in sophisticated experimental studies. Within the last ten years, LVR with endobronchial valves has become an extensively researched minimally-invasive treatment option. However, this therapy is considerably complicated by the frequent occurrence of functional interlobar shunts. The presence of "collateral ventilation" has to be ruled out prior to valve implantations, as the presence of these extraanatomical connections between different lobes may jeopardize the success of therapy. Recent experimental studies evaluated the automatic detection of incomplete lobar fissures from CT scans, because they are considered to be a predictor for the existence of shunts. To date, these methods are yet to show acceptable results. KEY POINTS Today, surgical and various minimal invasive methods of lung volume reduction are in use. Radiological and nuclear medical examinations are helpful in the evaluation of an appropriate lung area. Imaging can detect periinterventional complications. Reduction of lung volume has not yet been conclusively proven to be effective and is a therapeutical option with little scientific evidence.

Pulmonary lymphangioleiomyomatosis: analysis of disease manifestation by region-based quantification of lung parenchyma

PURPOSE Lymphangioleiomyomatosis (LAM) is characterized by proliferation of smooth muscle tissue that causes bronchial obstruction and secondary cystic destruction of lung parenchyma. The aim of this study was to evaluate the typical distribution of cystic defects in LAM with quantitative volumetric chest computed tomography (CT). MATERIALS AND METHODS CT examinations of 20 patients with confirmed LAM were evaluated with region-based quantification of lung parenchyma. Additionally, 10 consecutive patients were identified who had recently undergone CT imaging of the lung at our institution, in which no pathologies of the lung were found, to serve as a control group. Each lung was divided into three regions (upper, middle and lower thirds) with identical number of slices. In addition, we defined a "peel" and "core" of the lung comprising the 2 cm subpleural space and the remaining inner lung area. Computerized detection of lung volume and relative emphysema was performed with the PULMO 3D software (v3.42, Fraunhofer MEVIS, Bremen, Germany). This software package enables the quantification of emphysematous lung parenchyma by calculating the pixel index, which is defined as the ratio of lung voxels with a density <-950HU to the total number of voxels in the lung. RESULTS Cystic changes accounted for 0.1-39.1% of the total lung volume in patients with LAM. Disease manifestation in the central lung was significantly higher than in peripheral areas (peel median: 15.1%, core median: 20.5%; p=0.001). Lower thirds of lung parenchyma showed significantly less cystic changes than upper and middle lung areas combined (lower third: median 13.4, upper and middle thirds: median 19.0, p=0.001). CONCLUSION The distribution of cystic lesions in LAM is significantly more pronounced in the central lung compared to peripheral areas. There is a significant predominance of cystic changes in apical and intermediate lung zones compared to the lung bases.

Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network

Automated tissue characterization is one of the most crucial components of a computer aided diagnosis (CAD) system for interstitial lung diseases (ILDs). Although much research has been conducted in this field, the problem remains challenging. Deep learning techniques have recently achieved impressive results in a variety of computer vision problems, raising expectations that they might be applied in other domains, such as medical image analysis. In this paper, we propose and evaluate a convolutional neural network (CNN), designed for the classification of ILD patterns. The proposed network consists of 5 convolutional layers with 2×2 kernels and LeakyReLU activations, followed by average pooling with size equal to the size of the final feature maps and three dense layers. The last dense layer has 7 outputs, equivalent to the classes considered: healthy, ground glass opacity (GGO), micronodules, consolidation, reticulation, honeycombing and a combination of GGO/reticulation. To train and evaluate the CNN, we used a dataset of 14696 image patches, derived by 120 CT scans from different scanners and hospitals. To the best of our knowledge, this is the first deep CNN designed for the specific problem. A comparative analysis proved the effectiveness of the proposed CNN against previous methods in a challenging dataset. The classification performance (~85.5%) demonstrated the potential of CNNs in analyzing lung patterns. Future work includes, extending the CNN to three-dimensional data provided by CT volume scans and integrating the proposed method into a CAD system that aims to provide differential diagnosis for ILDs as a supportive tool for radiologists.

Correlation between alveolar ventilation and electrical properties of lung parenchyma.

One key problem in modern medical imaging is linking measured data and actual physiological quantities. In this article we derive such a link between the electrical bioimpedance of lung parenchyma, which can be measured by electrical impedance tomography (EIT), and the magnitude of regional ventilation, a key to understanding lung mechanics and developing novel protective ventilation strategies. Two rat-derived three-dimensional alveolar microstructures obtained from synchrotron-based x-ray tomography are each exposed to a constant potential difference for different states of ventilation in a finite element simulation. While the alveolar wall volume remains constant during stretch, the enclosed air volume varies, similar to the lung volume during ventilation. The enclosed air, serving as insulator in the alveolar ensemble, determines the resulting current and accordingly local tissue bioimpedance. From this we can derive a relationship between lung tissue bioimpedance and regional alveolar ventilation. The derived relationship shows a linear dependence between air content and tissue impedance and matches clinical data determined from a ventilated patient at the bedside.