Abstract

Little is known about mechanical processes of alveolar tissue during mechanical ventilation. Optical coherence tomography (OCT) as a three-dimensional and high-resolution imaging modality can be used to visualize subpleural alveoli during artificial ventilation. The quality of OCT images can be increased by matching the refractive index inside the alveoli to the one of tissue via liquid-filling. Thereby, scattering loss can be decreased and higher penetration depth and tissue contrast can be achieved. We show the liquid-filling of alveolar structures verified by optical coherence tomography and intravital microscopy (IVM) and the advantages of index matching for OCT imaging of subpleural alveoli in a mouse model using a custom-made liquid ventilator.

©2013 Optical Society of America

1. Introduction

Airway and lung related diseases form a clinical picture that arises more and more frequently. Breathing difficulties and lung insufficiency often enforce the use of technical ventilation support. Therefore, artificial ventilation becomes more important not only as life-saving measure, but also as long-term therapy and to assure living comfort. There is a need to develop new methods to protect the sensitive lung tissue and to keep alveolar structures from overexpansion and cell damage during artificial ventilation, but the mechanical processes are still unknown. To investigate protective ventilation strategies, detailed knowledge about mechanics and dynamics of the lung tissue at an alveolar level is necessary. One approach to get a closer look on lung function is optical coherence tomography (OCT) as a three-dimensional, non-invasive and contactless imaging modality. With its high spatial resolution and the possibility of in vivo measurements, this technique allows new insights into lung function and mechanics [1, 2]. OCT is based on near-infrared light and therefore the main limitation is the scattering loss of light in higher depth due to the difference of refractive index between air-filled alveoli and surrounding tissue. Hence, the visualization of alveolar structures is limited to the first one or two layers of alveoli, corresponding to approximately 300 µm beneath the pleura, which is an obvious reduction compared to the imaging depth of 0.5 to 1 mm in biological samples such as skin. To overcome this disadvantage, one can match the differences of refractive indexes by filling the lung with liquids. So far, images of liquid-filled lungs were acquired only in isolated and fixed lungs [3, 10]. But those studies show the potential increase of OCT image quality by reducing scattering loss, which results in three-fold higher penetration depth and reduced image artifacts. To use the advantages of liquid-filling for in vivo imaging of small rodent lungs, a suitable breathing fluid and a special liquid ventilator are necessary. The concept of total liquid ventilation was already developed in the 1960s as a special therapy method for patients with severe lung diseases like toxication or inspiration of saline water. Though liquid ventilation underwent further investigation, an early trial in humans showed no benefit in patient’s outcome compared to conventional gas ventilation what could be caused by the poor equipment used. From this, the development of liquid ventilation strategies and techniques stops and today there is no serious clinical sufficiency of this artificial ventilation method. The presented results demonstrate that total liquid ventilation (TLV) could be a new approach to improve OCT image quality for animal experiments to investigate lung tissue behavior more detailed. Based on this feasibility study, the aim of further investigations is to compare lung mechanics in healthy and diseased lung tissue during artificial ventilation with air and liquid to understand the influence of liquid-filling on tissue behavior especially in diseased lungs. Furthermore, the findings regarding image formation and image artifact reduction from OCT data of liquid-filled tissue will lead to a better understanding which artifacts occur and how they can be corrected in OCT images of air-filled tissue.

2. Methodology

2.1 Liquid ventilation and ventilator setup

The concept of total liquid ventilation was used to show the advantages of liquid-filled tissue for OCT imaging of subpleural alveoli by matching the refractive index inside the alveoli to the one of tissue. Therefore, the whole lung is filled with liquid and artificial ventilation is performed by a special liquid ventilator, which inserts and withdraws the liquid tidal volume actively. A suitable breathing medium for this approach is perfluorodecaline because the refractive index is similar to the refractive index of lung tissue. Some characteristics of perfluorodecalin are shown in Table 1 compared to other substances of lung tissue (water and blood) showing the high transport capacities for O2 and CO2, the refractive index (n = 1.31) and the low surface tension (σ = 15 mN/m), which is similar to surfactant (σ = 7 mN/m) [9] that is lining the inner alveolar walls in healthy lungs to avoid collapse during expiration.

Tables Icon

Table 1. Characteristic properties of perfluorodecalin compared to water and blood. Due to its high solubility for oxygen and carbone dioxide and its refractive index similar to the one of water, perfluorodecalin is an excellent candidate for improved OCT imaging of lung tissue during in vivo experiments.

A schematic of the developed ventilator prototype is shown in Fig. 1. The supply unit is used to warm the breathing medium to 37 °C and to saturate it with pure oxygen in a membrane oxygenator (Havard Apparatus, USA). The exhaled carbon dioxide is bound by conventional absorbance. Gas exchange is driven by a gas-diaphragm pump (HAGEN, Canada) through the oxygenator by a counter-current principle. The breathing medium is continuously circulated through the supply unit by a peristaltic pump (VWR, Germany) to maintain temperature and oxygen saturation of the breathing medium. Two independent syringe pumps (one for inspiration and one for expiration) and two pinch valves (ASCO Numatics, Germany) to ensure flow direction form the virtual ventilation unit.

 figure: Fig. 1

Fig. 1 Ventilator setup for air and liquid ventilation. Inspiration and expiration unit consist of high precision linear stages (3) and common syringes (1). The exchange of breathing medium both from air to liquid and vice versa, can be performed without disconnecting the animal from the ventilator by using two external reservoirs (2). The custom-made software allows online access to ventilation parameters in a volume- or pressure- controlled ventilation mode and displays pressure, tidal volume and flow in each ventilation cycle. Other components: (4) pressure transducer; (5) operation table; (6) peristaltic pump; (7) membrane oxygenator; (8) CO2 absorbents; (9) gas diaphragm pump.

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The syringe pumps consist of a linear stage (LS-65, MICOS GmbH, Germany) and a custom-made syringe mount. The ventilation cycle is time-controlled by a custom-made software (Labview 2010, National Instruments, USA), which also visualizes ventilation pressure and tidal volume and allows the manual adjustment of ventilation parameters. The device is designed to be used for volume- or pressure-controlled air and liquid ventilation in which the exchange of the breathing medium can be performed without disconnecting the animal from the device. With this ventilator, rodents from mice to rabbits are appropriate for the investigation of lung tissue behavior during different conditions of artificial ventilation using different syringes in accordance to the required ventilation volume.

In this study, the steady state ventilation cycle with air or liquid is pressure-controlled to assure adequate ventilation and to avoid ventilator-induced lung injury, especially in the case of liquid ventilation. The ventilation pressure is measured with a sampling rate of 50 Hz by a pressure transducer (B.Braun, Germany) located in front of the tracheal tube. The peak pressure and the positive end-expiratory pressure (PEEP) can be defined via the user interface and adjusted during ventilation. The change from air to liquid ventilation is performed by reducing the breathing frequency observing the tracheal pressure and the ventilated tidal volume. Before starting TLV, perfluorodecalin is heated up to 37 °C and saturated with oxygen. The system is filled with liquid via the peristaltic pump from the connected external reservoir, as shown in Fig. 1. Likewise, a change back to air ventilation can be performed by disconnecting the external perfluorodecalin reservoir and extracting the liquid from the system into the second external reservoir.

2.2 Experimental protocol

All experiments were approved by the animal care and use committee of the local government authorities and were performed in accordance with the Guide for Care and Use of Laboratory Animals (Institute of Laboratory Animal Resources, 7th edition, 1996). For imaging subpleural alveoli as realistic as possible and to verify the developed ventilator prototype, an in situ mouse model [4] was utilized. In this feasibility study, animals were anesthetized and sacrificed afterwards. For imaging lung tissue with OCT and intravital microscopy (IVM), a thoracic window was dissected in which tissue and three ribs above the lung were removed. After this, the window is sealed with a transparent membrane and negative pressure is reconstituted by sucking out air of the thorax via a thoracic catheter placed before sealing. The animal was connected to the ventilator prototype by a tracheal tube and pressure-controlled ventilation (PEEP = 2 mbar; Ppeak = 12 mbar) was initialized with 100% of oxygen for two minutes to remove nitrogen from the lung. The initial state of lung tissue was imaged by OCT and IVM. Afterwards, the system was filled with pre-oxygenated perfluorodecalin and ventilation settings were adjusted to liquid ventilation by reducing breathing frequency from 80 bpm (conventional mechanical ventilation) to 5 bpm (total liquid ventilation) [5, 6] in steps of 10 bpm. Mean experimental duration was 1.5 h and the filling of subpleural alveolar structures was visualized by OCT and IVM. After the experiments, the whole lung was removed to check liquid distribution, to control tissue for tightness or even ventilator induced injury.

2.3 Image acquisition

Image acquisition was performed by using a combined Fourier domain OCT and intravital microscopy system [7] for simultaneous measurements of 2D IVM and 3D OCT data. The OCT system uses a superluminescence diode centered at 845 nm with a full width at half maximum of 50 nm and an optical power of 1.5 mW. The near-infrared light is guided to the scanner head by a single mode fiber and transferred into a free-space beam by a collimator. For OCT imaging, the optical beam is separated into a reference beam and a sample beam by an 20:80 beam splitter. The sample beam is deflected by two galvanometer scanners in x and y direction to perform 2D scan pattern over the sample. Backscattered light returns the same way to the beam splitter, where it is superimposed with the reference light. The interfering light is guided by an optical fiber to a spectrometer, where it is spectrally resolved. The interference spectrum is acquired by a charge-coupled device line detector with a pixel rate of 25 MHz. The depth dependent information is calculated after resampling to wavenumber by a fast Fourier transformation from the spectral data. The amplitudes are transformed to a logarithmic scale and displayed as 8 bit gray values. To provide a better visual contrast, the 8 bit data was matched to a lookup table (LUT) using FIJI software (NIH, USA) providing color images from violet (lowest intensity) to yellow (highest intensity). The system provides a resolution of 11 µm and 7 µm axial and lateral in air, respectively. The A-scan rate is 12 kHz, which allows the acquisition of a cross section (320 x 512 pixels, 1.28 x 2.56 mm2) within 29 ms. The same beam path used for the near-infrared light is also used to perform IVM with a conventional 2 megapixel video camera (SMX-M72, SUMIX, USA). Therefore, visible light coming from the sample is coupled out by a dichroic mirror and guided through a lens with a focal length of 100 mm.

The acquired OCT image stacks show a sample region of 1.28 x 1.28 mm2 (320 x 320 pixels) and one corresponding IVM image is taken for each OCT volume stack. Data acquisition is performed after two minutes of conventional ventilation with pure oxygen to show the initial state of the lung tissue. Additional data were taken in steps of 5 to 10 minutes after initializing the total liquid ventilation to observe the liquid-filling with IVM and OCT and to investigate different lung areas within the thoracic window. The data of lung tissue shown here were taken at a positive airway pressure of 10 mbar during a breath holding maneuver.

3. Results

Following the experimental protocol, the animal is connected to the ventilator prototype after the surgical preparation and treated with pure oxygen to remove nitrogen from the lung in a pressure-controlled manner. The initial state of the lung tissue during gas ventilation is imaged by OCT (compare right image in Fig. 2) and IVM (not shown here). After the change to total liquid ventilation, the lung-filling was visualized with OCT after 5, 12, 18 and 30 minutes showing the differences in image quality due to the refractive index matching (Fig. 2). Figure 2 and Fig. 3 are representative examples of two mice demonstrating what can be observed during the experiments. The examples shown here were supported by approximately 30 animal experiments and additional studies on isolated organs showing the enhancement of OCT image quality due to the liquid-filling. One can observe a three-fold increase of imaging depth in the total liquid-filled lung compared to the initial state during air ventilation. Additionally, deeper structures become visible, which increase the information content of the liquid-filled images. A quantification of this increase in imaging depth is difficult to perform, because due to the lung tissue structure the mean OCT signal attenuation is comparable between air and liquid-filling (see diagram in Fig. 2), but the considerable differences in image quality result from the significant reduction in scattering loss and the decrease of image artifacts leading to the visualization of deeper alveolar structures. This effect can be well observed in Fig. 3 where adjacent areas of air and liquid-filled tissue were imaged at the same time with OCT. The diagram in Fig. 2 shows the intensity plot from a maximum intensity projection of 200 adjacent cross-sections of 3D OCT data sets from the initial state with air ventilation, after 12 minutes of TLV and after 30 minutes of TLV, respectively. To achieve this, the lung surface was aligned to an image depth of 460 µm in each cross section and a median filter with a 2 x 2 pixel width was used to reduce speckle noise. Due to the liquid-filling the signal exhibits a delimited plateau in a depth range between 750 µm and 1200 µm (see arrow in the diagram of Fig. 2) which can be used as an indicator for the enhanced imaging depth.

 figure: Fig. 2

Fig. 2 Time course of liquid-filling in the lung. One can compare the change of OCT image quality due to the different states of liquid-filling during one experiment. The pictures show OCT cross sections of air ventilated tissue as initial state and images at 5, 12, 18 and 30 min after beginning TLV. The penetration depth and also the structural resolution increase, whereas image artifacts are decreased showing sharp tissue walls without Fresnel reflections at air-tissue interface. The diagram shows three different plots of a maximum intensity projection from the 3D OCT data stacks of air ventilation, after 12 minutes and 30 minutes of TLV, respectively. The surface was aligned to an image depth of 460 µm to compare the different plots. The mean signal attenuation is comparable for air and liquid ventilation, but due to the reduction of scattering loss an increase of signal from higher depths can be observed (see arrow). Scale bar is 200 µm.

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 figure: Fig. 3

Fig. 3 Transition from an air-filled to a liquid-filled region in OCT and IVM. These pictures show the influence of liquid-filling for OCT and IVM lung imaging after 18 minutes of total liquid ventilation. While image quality for OCT is considerably increased in the liquid-filled area, the contrast for IVM is decreased due to the refractive index matching. The depth of tissue visualization is nearly tripled in the liquid-filled area due to the reduction of scattering loss. The arrows a, b and c in the 3D OCT image (left) were used for a better understanding of the OCT and IVM en face view (middle row) and the OCT cross section (right). For the 3D image, the pleura was hidden to get a look on the first layer of subpleural alveoli. Scale bar is 200 µm.

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Because of the animal’s supine position and the high density of perfluorodecaline, dorsobasal areas were filled with liquid first. Therefore, it takes 10 to 20 minutes to see the liquid-filling of the subpleural lung structures, which can be visualized with OCT and IVM. The images of Fig. 3 were acquired 18 minutes after beginning total liquid ventilation and show a partial liquid-filled area. Due to the refractive index matching, scattering loss for OCT is significantly reduced in the liquid-filled area resulting in a decrease of image artifacts and an increase of structural resolution. The contrast in IVM is much lower compared to the air-filled area but it is also possible to differentiate tissue walls.

4. Conclusion and discussion

This first feasibility study showed that total liquid ventilation can be a useful method to increase OCT information content for imaging subpleural alveoli. The usage of the developed ventilator prototype and perfluorodecalin as breathing medium lead to a decrease of image artifacts and an increase of structural information in OCT data. The combination of OCT and total liquid ventilation seems to be a promising approach to overcome the disadvantages of imaging isolated and fixed organs [7, 8] and to perform in vivo animal experiments. However, the effects of TLV on the lung tissue geometry and physiology still have to be investigated in further studies. Like surfactant, which is lining the inner alveolar wall to reduce surface tension between tissue and air (surface tension σ = 2 mN/m to 17 mN/m depending on lung volume [9, 11]), perfluorocarbons are also surface active liquids (σ = 15 mN/m, compare Table 1). Therefore, there is no evidence to expect significant differences of lung mechanics in healthy tissue due to the influence of liquid filling, whereas the investigations in diseased tissue will probably show considerable differences during air and liquid ventilation. Therefore, the comparability between OCT data from air-filled and liquid-filled lung tissue has to be assured. Furthermore, healthy lung tissue and different disease models have to be investigated to compare the acquired data and to find quantitative differences in lung mechanics on the alveolar level. The study of tissue behavior during mechanical ventilation in healthy and injured lungs will be the first step for the investigation and development of new and more protective ventilation strategies for humans.

Acknowledgments

This project was supported by the German Research Foundation (DFG) “Protective artificial Respiration” (PAR) – KO 1814/6-1 and KO 1814/6-2.

References and links

1. B. C. Quirk, R. A. McLaughlin, A. Curatolo, R. W. Kirk, P. B. Noble, and D. D. Sampson, “In situ imaging of lung alveoli with an optical coherence tomography needle probe,” J. Biomed. Opt. 16(3), 036009 (2011). [CrossRef]   [PubMed]  

2. D. Schwenninger, H. Runck, S. Schumann, J. Haberstroh, S. Meissner, E. Koch, and J. Guttmann, “Intravital microscopy of subpleural alveoli via transthoracic endoscopy,” J. Biomed. Opt. 16(4), 046002 (2011). [CrossRef]   [PubMed]  

3. S. Meissner, L. Knels, and E. Koch, “Improved three-dimensional Fourier domain optical coherence tomography by index matching in alveolar structures,” J. Biomed. Opt. 14(6), 064037 (2009). [CrossRef]   [PubMed]  

4. A. Tabuchi, A. R. Pries, and W. M. Kuebler, “A new model for intravital microscopy of the murine pulmonary microcirculation,” FASEB J. 20, A285–A286 (2006).

5. P. A. Koen, M. R. Wolfson, and T. H. Shaffer, “Fluorocarbon ventilation: Maximal expiratory flows and Co2 elimination,” Pediatr. Res. 24(3), 291–296 (1988). [CrossRef]   [PubMed]  

6. K. Matsuda, S. Sawada, R. H. Bartlett, and R. B. Hirschl, “Effect of ventilatory variables on gas exchange and hemodynamics during total liquid ventilation in a rat model,” Crit. Care Med. 31(7), 2034–2040 (2003). [CrossRef]   [PubMed]  

7. S. Meissner, L. Knels, A. Krueger, T. Koch, and E. Koch, “Simultaneous three-dimensional optical coherence tomography and intravital microscopy for imaging subpleural pulmonary alveoli in isolated rabbit lungs,” J. Biomed. Opt. 14(5), 054020 (2009). [CrossRef]   [PubMed]  

8. N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005). [CrossRef]   [PubMed]  

9. S. Schürch, M. Lee, and P. Gehr, “Pulmonary surfactant: Surface properties and function of alveolar and airway surfactant,” Pure Appl. Chem. 64(11), 1745–1750 (1992). [CrossRef]  

10. C. I. Unglert, E. Namati, W. C. Warger 2nd, L. Liu, H. Yoo, D. Kang, B. E. Bouma, and G. J. Tearney, “Evaluation of optical reflectance techniques for imaging of alveolar structure,” J. Biomed. Opt. 17(7), 071303 (2012). [CrossRef]   [PubMed]  

11. T. A. Wilson and H. Bachofen, “A model for mechanical structure of the alveolar duct,” J. Appl. Physiol. 52(4), 1064–1070 (1982). [PubMed]  

References

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  1. B. C. Quirk, R. A. McLaughlin, A. Curatolo, R. W. Kirk, P. B. Noble, and D. D. Sampson, “In situ imaging of lung alveoli with an optical coherence tomography needle probe,” J. Biomed. Opt. 16(3), 036009 (2011).
    [Crossref] [PubMed]
  2. D. Schwenninger, H. Runck, S. Schumann, J. Haberstroh, S. Meissner, E. Koch, and J. Guttmann, “Intravital microscopy of subpleural alveoli via transthoracic endoscopy,” J. Biomed. Opt. 16(4), 046002 (2011).
    [Crossref] [PubMed]
  3. S. Meissner, L. Knels, and E. Koch, “Improved three-dimensional Fourier domain optical coherence tomography by index matching in alveolar structures,” J. Biomed. Opt. 14(6), 064037 (2009).
    [Crossref] [PubMed]
  4. A. Tabuchi, A. R. Pries, and W. M. Kuebler, “A new model for intravital microscopy of the murine pulmonary microcirculation,” FASEB J. 20, A285–A286 (2006).
  5. P. A. Koen, M. R. Wolfson, and T. H. Shaffer, “Fluorocarbon ventilation: Maximal expiratory flows and Co2 elimination,” Pediatr. Res. 24(3), 291–296 (1988).
    [Crossref] [PubMed]
  6. K. Matsuda, S. Sawada, R. H. Bartlett, and R. B. Hirschl, “Effect of ventilatory variables on gas exchange and hemodynamics during total liquid ventilation in a rat model,” Crit. Care Med. 31(7), 2034–2040 (2003).
    [Crossref] [PubMed]
  7. S. Meissner, L. Knels, A. Krueger, T. Koch, and E. Koch, “Simultaneous three-dimensional optical coherence tomography and intravital microscopy for imaging subpleural pulmonary alveoli in isolated rabbit lungs,” J. Biomed. Opt. 14(5), 054020 (2009).
    [Crossref] [PubMed]
  8. N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005).
    [Crossref] [PubMed]
  9. S. Schürch, M. Lee, and P. Gehr, “Pulmonary surfactant: Surface properties and function of alveolar and airway surfactant,” Pure Appl. Chem. 64(11), 1745–1750 (1992).
    [Crossref]
  10. C. I. Unglert, E. Namati, W. C. Warger, L. Liu, H. Yoo, D. Kang, B. E. Bouma, and G. J. Tearney, “Evaluation of optical reflectance techniques for imaging of alveolar structure,” J. Biomed. Opt. 17(7), 071303 (2012).
    [Crossref] [PubMed]
  11. T. A. Wilson and H. Bachofen, “A model for mechanical structure of the alveolar duct,” J. Appl. Physiol. 52(4), 1064–1070 (1982).
    [PubMed]

2012 (1)

C. I. Unglert, E. Namati, W. C. Warger, L. Liu, H. Yoo, D. Kang, B. E. Bouma, and G. J. Tearney, “Evaluation of optical reflectance techniques for imaging of alveolar structure,” J. Biomed. Opt. 17(7), 071303 (2012).
[Crossref] [PubMed]

2011 (2)

B. C. Quirk, R. A. McLaughlin, A. Curatolo, R. W. Kirk, P. B. Noble, and D. D. Sampson, “In situ imaging of lung alveoli with an optical coherence tomography needle probe,” J. Biomed. Opt. 16(3), 036009 (2011).
[Crossref] [PubMed]

D. Schwenninger, H. Runck, S. Schumann, J. Haberstroh, S. Meissner, E. Koch, and J. Guttmann, “Intravital microscopy of subpleural alveoli via transthoracic endoscopy,” J. Biomed. Opt. 16(4), 046002 (2011).
[Crossref] [PubMed]

2009 (2)

S. Meissner, L. Knels, and E. Koch, “Improved three-dimensional Fourier domain optical coherence tomography by index matching in alveolar structures,” J. Biomed. Opt. 14(6), 064037 (2009).
[Crossref] [PubMed]

S. Meissner, L. Knels, A. Krueger, T. Koch, and E. Koch, “Simultaneous three-dimensional optical coherence tomography and intravital microscopy for imaging subpleural pulmonary alveoli in isolated rabbit lungs,” J. Biomed. Opt. 14(5), 054020 (2009).
[Crossref] [PubMed]

2006 (1)

A. Tabuchi, A. R. Pries, and W. M. Kuebler, “A new model for intravital microscopy of the murine pulmonary microcirculation,” FASEB J. 20, A285–A286 (2006).

2005 (1)

N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005).
[Crossref] [PubMed]

2003 (1)

K. Matsuda, S. Sawada, R. H. Bartlett, and R. B. Hirschl, “Effect of ventilatory variables on gas exchange and hemodynamics during total liquid ventilation in a rat model,” Crit. Care Med. 31(7), 2034–2040 (2003).
[Crossref] [PubMed]

1992 (1)

S. Schürch, M. Lee, and P. Gehr, “Pulmonary surfactant: Surface properties and function of alveolar and airway surfactant,” Pure Appl. Chem. 64(11), 1745–1750 (1992).
[Crossref]

1988 (1)

P. A. Koen, M. R. Wolfson, and T. H. Shaffer, “Fluorocarbon ventilation: Maximal expiratory flows and Co2 elimination,” Pediatr. Res. 24(3), 291–296 (1988).
[Crossref] [PubMed]

1982 (1)

T. A. Wilson and H. Bachofen, “A model for mechanical structure of the alveolar duct,” J. Appl. Physiol. 52(4), 1064–1070 (1982).
[PubMed]

Bachofen, H.

T. A. Wilson and H. Bachofen, “A model for mechanical structure of the alveolar duct,” J. Appl. Physiol. 52(4), 1064–1070 (1982).
[PubMed]

Bartlett, R. H.

K. Matsuda, S. Sawada, R. H. Bartlett, and R. B. Hirschl, “Effect of ventilatory variables on gas exchange and hemodynamics during total liquid ventilation in a rat model,” Crit. Care Med. 31(7), 2034–2040 (2003).
[Crossref] [PubMed]

Bouma, B. E.

C. I. Unglert, E. Namati, W. C. Warger, L. Liu, H. Yoo, D. Kang, B. E. Bouma, and G. J. Tearney, “Evaluation of optical reflectance techniques for imaging of alveolar structure,” J. Biomed. Opt. 17(7), 071303 (2012).
[Crossref] [PubMed]

Brenner, M.

N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005).
[Crossref] [PubMed]

Chen, Z.

N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005).
[Crossref] [PubMed]

Colt, H.

N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005).
[Crossref] [PubMed]

Curatolo, A.

B. C. Quirk, R. A. McLaughlin, A. Curatolo, R. W. Kirk, P. B. Noble, and D. D. Sampson, “In situ imaging of lung alveoli with an optical coherence tomography needle probe,” J. Biomed. Opt. 16(3), 036009 (2011).
[Crossref] [PubMed]

Gehr, P.

S. Schürch, M. Lee, and P. Gehr, “Pulmonary surfactant: Surface properties and function of alveolar and airway surfactant,” Pure Appl. Chem. 64(11), 1745–1750 (1992).
[Crossref]

Guo, S.

N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005).
[Crossref] [PubMed]

Guttmann, J.

D. Schwenninger, H. Runck, S. Schumann, J. Haberstroh, S. Meissner, E. Koch, and J. Guttmann, “Intravital microscopy of subpleural alveoli via transthoracic endoscopy,” J. Biomed. Opt. 16(4), 046002 (2011).
[Crossref] [PubMed]

Haberstroh, J.

D. Schwenninger, H. Runck, S. Schumann, J. Haberstroh, S. Meissner, E. Koch, and J. Guttmann, “Intravital microscopy of subpleural alveoli via transthoracic endoscopy,” J. Biomed. Opt. 16(4), 046002 (2011).
[Crossref] [PubMed]

Hanna, N.

N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005).
[Crossref] [PubMed]

Hirschl, R. B.

K. Matsuda, S. Sawada, R. H. Bartlett, and R. B. Hirschl, “Effect of ventilatory variables on gas exchange and hemodynamics during total liquid ventilation in a rat model,” Crit. Care Med. 31(7), 2034–2040 (2003).
[Crossref] [PubMed]

Jung, W.

N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005).
[Crossref] [PubMed]

Kang, D.

C. I. Unglert, E. Namati, W. C. Warger, L. Liu, H. Yoo, D. Kang, B. E. Bouma, and G. J. Tearney, “Evaluation of optical reflectance techniques for imaging of alveolar structure,” J. Biomed. Opt. 17(7), 071303 (2012).
[Crossref] [PubMed]

Kirk, R. W.

B. C. Quirk, R. A. McLaughlin, A. Curatolo, R. W. Kirk, P. B. Noble, and D. D. Sampson, “In situ imaging of lung alveoli with an optical coherence tomography needle probe,” J. Biomed. Opt. 16(3), 036009 (2011).
[Crossref] [PubMed]

Knels, L.

S. Meissner, L. Knels, and E. Koch, “Improved three-dimensional Fourier domain optical coherence tomography by index matching in alveolar structures,” J. Biomed. Opt. 14(6), 064037 (2009).
[Crossref] [PubMed]

S. Meissner, L. Knels, A. Krueger, T. Koch, and E. Koch, “Simultaneous three-dimensional optical coherence tomography and intravital microscopy for imaging subpleural pulmonary alveoli in isolated rabbit lungs,” J. Biomed. Opt. 14(5), 054020 (2009).
[Crossref] [PubMed]

Koch, E.

D. Schwenninger, H. Runck, S. Schumann, J. Haberstroh, S. Meissner, E. Koch, and J. Guttmann, “Intravital microscopy of subpleural alveoli via transthoracic endoscopy,” J. Biomed. Opt. 16(4), 046002 (2011).
[Crossref] [PubMed]

S. Meissner, L. Knels, and E. Koch, “Improved three-dimensional Fourier domain optical coherence tomography by index matching in alveolar structures,” J. Biomed. Opt. 14(6), 064037 (2009).
[Crossref] [PubMed]

S. Meissner, L. Knels, A. Krueger, T. Koch, and E. Koch, “Simultaneous three-dimensional optical coherence tomography and intravital microscopy for imaging subpleural pulmonary alveoli in isolated rabbit lungs,” J. Biomed. Opt. 14(5), 054020 (2009).
[Crossref] [PubMed]

Koch, T.

S. Meissner, L. Knels, A. Krueger, T. Koch, and E. Koch, “Simultaneous three-dimensional optical coherence tomography and intravital microscopy for imaging subpleural pulmonary alveoli in isolated rabbit lungs,” J. Biomed. Opt. 14(5), 054020 (2009).
[Crossref] [PubMed]

Koen, P. A.

P. A. Koen, M. R. Wolfson, and T. H. Shaffer, “Fluorocarbon ventilation: Maximal expiratory flows and Co2 elimination,” Pediatr. Res. 24(3), 291–296 (1988).
[Crossref] [PubMed]

Krueger, A.

S. Meissner, L. Knels, A. Krueger, T. Koch, and E. Koch, “Simultaneous three-dimensional optical coherence tomography and intravital microscopy for imaging subpleural pulmonary alveoli in isolated rabbit lungs,” J. Biomed. Opt. 14(5), 054020 (2009).
[Crossref] [PubMed]

Kuebler, W. M.

A. Tabuchi, A. R. Pries, and W. M. Kuebler, “A new model for intravital microscopy of the murine pulmonary microcirculation,” FASEB J. 20, A285–A286 (2006).

Lee, M.

S. Schürch, M. Lee, and P. Gehr, “Pulmonary surfactant: Surface properties and function of alveolar and airway surfactant,” Pure Appl. Chem. 64(11), 1745–1750 (1992).
[Crossref]

Liu, L.

C. I. Unglert, E. Namati, W. C. Warger, L. Liu, H. Yoo, D. Kang, B. E. Bouma, and G. J. Tearney, “Evaluation of optical reflectance techniques for imaging of alveolar structure,” J. Biomed. Opt. 17(7), 071303 (2012).
[Crossref] [PubMed]

Matsuda, K.

K. Matsuda, S. Sawada, R. H. Bartlett, and R. B. Hirschl, “Effect of ventilatory variables on gas exchange and hemodynamics during total liquid ventilation in a rat model,” Crit. Care Med. 31(7), 2034–2040 (2003).
[Crossref] [PubMed]

McLaughlin, R. A.

B. C. Quirk, R. A. McLaughlin, A. Curatolo, R. W. Kirk, P. B. Noble, and D. D. Sampson, “In situ imaging of lung alveoli with an optical coherence tomography needle probe,” J. Biomed. Opt. 16(3), 036009 (2011).
[Crossref] [PubMed]

Meissner, S.

D. Schwenninger, H. Runck, S. Schumann, J. Haberstroh, S. Meissner, E. Koch, and J. Guttmann, “Intravital microscopy of subpleural alveoli via transthoracic endoscopy,” J. Biomed. Opt. 16(4), 046002 (2011).
[Crossref] [PubMed]

S. Meissner, L. Knels, and E. Koch, “Improved three-dimensional Fourier domain optical coherence tomography by index matching in alveolar structures,” J. Biomed. Opt. 14(6), 064037 (2009).
[Crossref] [PubMed]

S. Meissner, L. Knels, A. Krueger, T. Koch, and E. Koch, “Simultaneous three-dimensional optical coherence tomography and intravital microscopy for imaging subpleural pulmonary alveoli in isolated rabbit lungs,” J. Biomed. Opt. 14(5), 054020 (2009).
[Crossref] [PubMed]

Milliken, J.

N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005).
[Crossref] [PubMed]

Mukai, D.

N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005).
[Crossref] [PubMed]

Namati, E.

C. I. Unglert, E. Namati, W. C. Warger, L. Liu, H. Yoo, D. Kang, B. E. Bouma, and G. J. Tearney, “Evaluation of optical reflectance techniques for imaging of alveolar structure,” J. Biomed. Opt. 17(7), 071303 (2012).
[Crossref] [PubMed]

Noble, P. B.

B. C. Quirk, R. A. McLaughlin, A. Curatolo, R. W. Kirk, P. B. Noble, and D. D. Sampson, “In situ imaging of lung alveoli with an optical coherence tomography needle probe,” J. Biomed. Opt. 16(3), 036009 (2011).
[Crossref] [PubMed]

Pries, A. R.

A. Tabuchi, A. R. Pries, and W. M. Kuebler, “A new model for intravital microscopy of the murine pulmonary microcirculation,” FASEB J. 20, A285–A286 (2006).

Quirk, B. C.

B. C. Quirk, R. A. McLaughlin, A. Curatolo, R. W. Kirk, P. B. Noble, and D. D. Sampson, “In situ imaging of lung alveoli with an optical coherence tomography needle probe,” J. Biomed. Opt. 16(3), 036009 (2011).
[Crossref] [PubMed]

Runck, H.

D. Schwenninger, H. Runck, S. Schumann, J. Haberstroh, S. Meissner, E. Koch, and J. Guttmann, “Intravital microscopy of subpleural alveoli via transthoracic endoscopy,” J. Biomed. Opt. 16(4), 046002 (2011).
[Crossref] [PubMed]

Saltzman, D.

N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005).
[Crossref] [PubMed]

Sampson, D. D.

B. C. Quirk, R. A. McLaughlin, A. Curatolo, R. W. Kirk, P. B. Noble, and D. D. Sampson, “In situ imaging of lung alveoli with an optical coherence tomography needle probe,” J. Biomed. Opt. 16(3), 036009 (2011).
[Crossref] [PubMed]

Sasse, S.

N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005).
[Crossref] [PubMed]

Sawada, S.

K. Matsuda, S. Sawada, R. H. Bartlett, and R. B. Hirschl, “Effect of ventilatory variables on gas exchange and hemodynamics during total liquid ventilation in a rat model,” Crit. Care Med. 31(7), 2034–2040 (2003).
[Crossref] [PubMed]

Schumann, S.

D. Schwenninger, H. Runck, S. Schumann, J. Haberstroh, S. Meissner, E. Koch, and J. Guttmann, “Intravital microscopy of subpleural alveoli via transthoracic endoscopy,” J. Biomed. Opt. 16(4), 046002 (2011).
[Crossref] [PubMed]

Schürch, S.

S. Schürch, M. Lee, and P. Gehr, “Pulmonary surfactant: Surface properties and function of alveolar and airway surfactant,” Pure Appl. Chem. 64(11), 1745–1750 (1992).
[Crossref]

Schwenninger, D.

D. Schwenninger, H. Runck, S. Schumann, J. Haberstroh, S. Meissner, E. Koch, and J. Guttmann, “Intravital microscopy of subpleural alveoli via transthoracic endoscopy,” J. Biomed. Opt. 16(4), 046002 (2011).
[Crossref] [PubMed]

Shaffer, T. H.

P. A. Koen, M. R. Wolfson, and T. H. Shaffer, “Fluorocarbon ventilation: Maximal expiratory flows and Co2 elimination,” Pediatr. Res. 24(3), 291–296 (1988).
[Crossref] [PubMed]

Tabuchi, A.

A. Tabuchi, A. R. Pries, and W. M. Kuebler, “A new model for intravital microscopy of the murine pulmonary microcirculation,” FASEB J. 20, A285–A286 (2006).

Tearney, G. J.

C. I. Unglert, E. Namati, W. C. Warger, L. Liu, H. Yoo, D. Kang, B. E. Bouma, and G. J. Tearney, “Evaluation of optical reflectance techniques for imaging of alveolar structure,” J. Biomed. Opt. 17(7), 071303 (2012).
[Crossref] [PubMed]

Unglert, C. I.

C. I. Unglert, E. Namati, W. C. Warger, L. Liu, H. Yoo, D. Kang, B. E. Bouma, and G. J. Tearney, “Evaluation of optical reflectance techniques for imaging of alveolar structure,” J. Biomed. Opt. 17(7), 071303 (2012).
[Crossref] [PubMed]

Warger, W. C.

C. I. Unglert, E. Namati, W. C. Warger, L. Liu, H. Yoo, D. Kang, B. E. Bouma, and G. J. Tearney, “Evaluation of optical reflectance techniques for imaging of alveolar structure,” J. Biomed. Opt. 17(7), 071303 (2012).
[Crossref] [PubMed]

Wilson, T. A.

T. A. Wilson and H. Bachofen, “A model for mechanical structure of the alveolar duct,” J. Appl. Physiol. 52(4), 1064–1070 (1982).
[PubMed]

Wolfson, M. R.

P. A. Koen, M. R. Wolfson, and T. H. Shaffer, “Fluorocarbon ventilation: Maximal expiratory flows and Co2 elimination,” Pediatr. Res. 24(3), 291–296 (1988).
[Crossref] [PubMed]

Yoo, H.

C. I. Unglert, E. Namati, W. C. Warger, L. Liu, H. Yoo, D. Kang, B. E. Bouma, and G. J. Tearney, “Evaluation of optical reflectance techniques for imaging of alveolar structure,” J. Biomed. Opt. 17(7), 071303 (2012).
[Crossref] [PubMed]

Crit. Care Med. (1)

K. Matsuda, S. Sawada, R. H. Bartlett, and R. B. Hirschl, “Effect of ventilatory variables on gas exchange and hemodynamics during total liquid ventilation in a rat model,” Crit. Care Med. 31(7), 2034–2040 (2003).
[Crossref] [PubMed]

FASEB J. (1)

A. Tabuchi, A. R. Pries, and W. M. Kuebler, “A new model for intravital microscopy of the murine pulmonary microcirculation,” FASEB J. 20, A285–A286 (2006).

J. Appl. Physiol. (1)

T. A. Wilson and H. Bachofen, “A model for mechanical structure of the alveolar duct,” J. Appl. Physiol. 52(4), 1064–1070 (1982).
[PubMed]

J. Biomed. Opt. (5)

C. I. Unglert, E. Namati, W. C. Warger, L. Liu, H. Yoo, D. Kang, B. E. Bouma, and G. J. Tearney, “Evaluation of optical reflectance techniques for imaging of alveolar structure,” J. Biomed. Opt. 17(7), 071303 (2012).
[Crossref] [PubMed]

B. C. Quirk, R. A. McLaughlin, A. Curatolo, R. W. Kirk, P. B. Noble, and D. D. Sampson, “In situ imaging of lung alveoli with an optical coherence tomography needle probe,” J. Biomed. Opt. 16(3), 036009 (2011).
[Crossref] [PubMed]

D. Schwenninger, H. Runck, S. Schumann, J. Haberstroh, S. Meissner, E. Koch, and J. Guttmann, “Intravital microscopy of subpleural alveoli via transthoracic endoscopy,” J. Biomed. Opt. 16(4), 046002 (2011).
[Crossref] [PubMed]

S. Meissner, L. Knels, and E. Koch, “Improved three-dimensional Fourier domain optical coherence tomography by index matching in alveolar structures,” J. Biomed. Opt. 14(6), 064037 (2009).
[Crossref] [PubMed]

S. Meissner, L. Knels, A. Krueger, T. Koch, and E. Koch, “Simultaneous three-dimensional optical coherence tomography and intravital microscopy for imaging subpleural pulmonary alveoli in isolated rabbit lungs,” J. Biomed. Opt. 14(5), 054020 (2009).
[Crossref] [PubMed]

J. Thorac. Cardiovasc. Surg. (1)

N. Hanna, D. Saltzman, D. Mukai, Z. Chen, S. Sasse, J. Milliken, S. Guo, W. Jung, H. Colt, and M. Brenner, “Two-dimensional and 3-dimensional optical coherence tomographic imaging of the airway, lung, and pleura,” J. Thorac. Cardiovasc. Surg. 129(3), 615–622 (2005).
[Crossref] [PubMed]

Pediatr. Res. (1)

P. A. Koen, M. R. Wolfson, and T. H. Shaffer, “Fluorocarbon ventilation: Maximal expiratory flows and Co2 elimination,” Pediatr. Res. 24(3), 291–296 (1988).
[Crossref] [PubMed]

Pure Appl. Chem. (1)

S. Schürch, M. Lee, and P. Gehr, “Pulmonary surfactant: Surface properties and function of alveolar and airway surfactant,” Pure Appl. Chem. 64(11), 1745–1750 (1992).
[Crossref]

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Figures (3)

Fig. 1
Fig. 1 Ventilator setup for air and liquid ventilation. Inspiration and expiration unit consist of high precision linear stages (3) and common syringes (1). The exchange of breathing medium both from air to liquid and vice versa, can be performed without disconnecting the animal from the ventilator by using two external reservoirs (2). The custom-made software allows online access to ventilation parameters in a volume- or pressure- controlled ventilation mode and displays pressure, tidal volume and flow in each ventilation cycle. Other components: (4) pressure transducer; (5) operation table; (6) peristaltic pump; (7) membrane oxygenator; (8) CO2 absorbents; (9) gas diaphragm pump.
Fig. 2
Fig. 2 Time course of liquid-filling in the lung. One can compare the change of OCT image quality due to the different states of liquid-filling during one experiment. The pictures show OCT cross sections of air ventilated tissue as initial state and images at 5, 12, 18 and 30 min after beginning TLV. The penetration depth and also the structural resolution increase, whereas image artifacts are decreased showing sharp tissue walls without Fresnel reflections at air-tissue interface. The diagram shows three different plots of a maximum intensity projection from the 3D OCT data stacks of air ventilation, after 12 minutes and 30 minutes of TLV, respectively. The surface was aligned to an image depth of 460 µm to compare the different plots. The mean signal attenuation is comparable for air and liquid ventilation, but due to the reduction of scattering loss an increase of signal from higher depths can be observed (see arrow). Scale bar is 200 µm.
Fig. 3
Fig. 3 Transition from an air-filled to a liquid-filled region in OCT and IVM. These pictures show the influence of liquid-filling for OCT and IVM lung imaging after 18 minutes of total liquid ventilation. While image quality for OCT is considerably increased in the liquid-filled area, the contrast for IVM is decreased due to the refractive index matching. The depth of tissue visualization is nearly tripled in the liquid-filled area due to the reduction of scattering loss. The arrows a, b and c in the 3D OCT image (left) were used for a better understanding of the OCT and IVM en face view (middle row) and the OCT cross section (right). For the 3D image, the pleura was hidden to get a look on the first layer of subpleural alveoli. Scale bar is 200 µm.

Tables (1)

Tables Icon

Table 1 Characteristic properties of perfluorodecalin compared to water and blood. Due to its high solubility for oxygen and carbone dioxide and its refractive index similar to the one of water, perfluorodecalin is an excellent candidate for improved OCT imaging of lung tissue during in vivo experiments.

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