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Ewald R Weibel - One of the best experts on this subject based on the ideXlab platform.
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Lung Structure and the intrinsic challenges of gas exchange
Comprehensive Physiology, 2016Co-Authors: Connie C W Hsia, Dallas M Hyde, Ewald R WeibelAbstract:Structural and functional complexities of the mammalian Lung evolved to meet a unique set of challenges, namely, the provision of efficient delivery of inspired air to all Lung units within a confined thoracic space, to build a large gas exchange surface associated with minimal barrier thickness and a microvascular network to accommodate the entire right ventricular cardiac output while withstanding cyclic mechanical stresses that increase several folds from rest to exercise. Intricate regulatory mechanisms at every level ensure that the dynamic capacities of ventilation, perfusion, diffusion, and chemical binding to hemoglobin are commensurate with usual metabolic demands and periodic extreme needs for activity and survival. This article reviews the structural design of mammalian and human Lung, its functional challenges, limitations, and potential for adaptation. We discuss (i) the evolutionary origin of alveolar Lungs and its advantages and compromises, (ii) structural determinants of alveolar gas exchange, including architecture of conducting bronchovascular trees that converge in gas exchange units, (iii) the challenges of matching ventilation, perfusion, and diffusion and tissue-erythrocyte and thoracopulmonary interactions. The notion of erythrocytes as an integral component of the gas exchanger is emphasized. We further discuss the signals, sources, and limits of structural plasticity of the Lung in alveolar hypoxia and following a loss of Lung units, and the promise and caveats of interventions aimed at augmenting endogenous adaptive responses. Our objective is to understand how individual components are matched at multiple levels to optimize organ function in the face of physiological demands or pathological constraints. © 2016 American Physiological Society. Compr Physiol 6:827-895, 2016.
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The challenge of measuring Lung Structure. On the "Standards for the Quantitative Assessment of Lung Structure".
The journal of the Japanese Respiratory Society, 2010Co-Authors: Ewald R WeibelAbstract:: The purpose of this review is to call attention of respiratory scientists to an Official Policy Statement jointly issued by the American Thoracic Society and the European Respiratory Society on "Standards for the Quantitative Assessment of Lung Structure", based on an extended report of a joint task force of 20 experts, and recently published in the Am. J. Respir. Crit. Care Med. This document provides investigators of normal and diseased Lung Structure with a review of the stereological methods that allow measurements to be done on sections. It critically discusses the preparation procedures, the conditions for unbiased sampling of the Lung for microscopic study, and the potential applications of such methods. Here we present some case studies that underpin the importance of using accurate methods of Structure quantification and outline paths into the future for Structure-function studies on Lung diseases.
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Last Word on Viewpoint: Standards for quantitative assessment of Lung Structure
Journal of Applied Physiology, 2010Co-Authors: Wayne Mitzner, Ewald R WeibelAbstract:to the editor: We wish to thank the commentators (see Ref. [3][1]) for bringing up a number of new perspectives that can broaden the range of applicability of the Standards for the Quantitative Assessment of Lung Structure ([1][2]). It is quite clear that these guidelines cannot definitively deal
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Standards for quantitative assessment of Lung Structure.
Journal of Applied Physiology, 2010Co-Authors: Wayne Mitzner, Ewald R WeibelAbstract:the february 15th, 2010, issue of the American Journal of Respiratory and Critical Care Medicine contains an official research policy statement on quantitative assessment of Lung Structure ([1][1]). This document is the product of a Joint American Thoracic Society (ATS) and European Respiratory
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an official research policy statement of the american thoracic society european respiratory society standards for quantitative assessment of Lung Structure
American Journal of Respiratory and Critical Care Medicine, 2010Co-Authors: Connie C W Hsia, Matthias Ochs, Dallas M Hyde, Ewald R WeibelAbstract:1.1. The Challenges To understand normal Lung function, the processes of growth and development, and the mechanisms and effects of diseases, we need information about the 3D Structure of the Lung. Quantification of organ Structure is based upon 3D physical attributes of tissues, cells, organelles, alveoli, airways, and blood vessels. When Structures of interest are inaccessible or too small to be seen macroscopically, we rely on physical or optical sections through a few representative samples taken from the large heterogeneous organ. The resulting 2D images confer incomplete information about the 3D Structure, and may not accurately represent true 3D properties, leading to possible misinterpretation when measurements are made on 2D sections. Because structural quantification is often considered the “gold standard” in evaluating experimental intervention, disease severity, and treatment response, it is imperative that these quantitative methods are (1) accurate to allow meaningful interpretation of results, (2) efficient to yield adequate precision with reasonable effort, (3) of adequate statistical power to encompass inherent variability, and (4) adherent to uniform standards to facilitate comparisons among experimental groups and across different studies. The Lung poses special challenges, some of which are outlined below and discussed in later sections: (a) Heterogeneity of Lung Structure requires standardized preparation methods. The inflated Lung consists of mostly air; only 10 to 15% of its volume consists of tissue (cells, fibers, and matrix) and blood. In vivo Lung volume and relative volumes of air, tissue, and blood fluctuate widely, while gravitational and nongravitational gradients cause spatial heterogeneity in Structure and function. Failure to standardize physiological variables or minimize tissue distortion introduces uncertainties or errors into subsequent measurements, to the point of their being meaningless (1). Careful selection of fixation and preparation methods that minimize shrinkage obviates this problem (Section 3). (b) Selected microscopic sections should provide a fair sample of the whole organ. The practice of picking specific samples or sections often fails to account for regional heterogeneity, leading to biased conclusions with respect to the whole organ. Deliberately choosing sections that contain a particular compartment (e.g., profiles of alveolar type 2 epithelial cells) overestimates their abundance within the whole Lung. Using a sampling scheme that covers all regions with equal probability alleviates this problem (Section 4). (c) Measurements made on microscopic sections must be related to the whole organ or an appropriate reference volume. Studies continue to appear that report only relative measurements (i.e., volume and surface densities or ratios) without knowledge of the Lung volume. These ratios are dependent on Lung inflation, and must be multiplied by absolute Lung volume to obtain accurate total quantities of the Structures of interest. Uncertainties regarding Lung volume can bias data interpretation. For example, enlarged mean airspace size need not signify emphysema or alveolar hypoplasia; the finding could also be caused by overinflation. Careful measurement of the Lung volume eliminates this error (Section 5). (d) Lung Structures are irregular and their geometry easily altered by pathology and intervention. Measurements on 2D images that rely on assumed geometry may misrepresent the 3D Structure. Examples include estimating alveolar size from cross-sectional areas of alveolar profiles, and reporting alveolar surface area by the length of alveolar profile boundary. These measures can severely misrepresent the 3D Structure of interest. Airspace size is often inferred from the mean linear intercept (Lm), which in fact measures airspace volume-to-surface ratio and can be converted to diameter or volume only by assuming a shape factor. Airspace distortion, or selective distortion of alveolar ducts but not alveolar sacs, can invalidate shape assumptions (Section 6). (e) The number of Lung cells cannot be estimated by counting their profiles on random histologic sections because larger cells have a greater probability of being sampled. For example, if experimental intervention causes selective cell hypertrophy, the increased probability of counting cell profiles will lead to wrong conclusions. Again, using stereologic methods that are free of geometric assumptions eliminates this error (Sections 6–7). (f) In contrast to acinar Structures that exhibit nearly random orientation (isotropy) and homogeneous distribution, conducting airways and blood vessels exhibit preferred directions (anisotropy) and inhomogeneous distribution, which alter their sampling probability on random sections. Specific sampling procedures that account for their nonrandom nature should be employed to ensure unbiased representation on 2D sections (Section 8). (g) Assessment of endobronchial or Lung biopsy specimens is limited by their nonrandom nature and a lack of external reference parameter. Endobronchial biopsy specimens are also anisotropic with distinct luminal and basal sides and with respect to airway generations. To minimize potential errors in quantification, specimens should be processed with their orientation randomized and analyzed with respect to an internal reference parameter (Section 9). (h) The new imaging techniques CT and MRI offer the possibility of obtaining high-fidelity images of Lung Structure in vivo that can be used for quantitative assessment of structural changes. Since their images are sections of the organ, stereology can ensure accurate measurements (Section 10). Definition of terms (section of text where term is defined) Accuracy (Sec. 1.2); ALP-sector (Sec. 2.1, item a); Anisotropy (Sec. 1.1, item f); Apparent diffusion coefficient (ADC) (Sec. 10.4.1); Arithmetic mean thickness of air-blood barrier (Sec. 6.7); Bias (Sec. 1.2); Buffon's needle (Sec. 1.3); Cavalieri Principle/Method (Sec. 1.3); Coarse nonparenchyma (Sec. 6.2); Coarse parenchyma (Sec. 6.2); Computer-aided stereology systems (Sec. 2.2, item c); Connectivity of airway branching systems (Sec. 8.1); Delesse principle (Sec. 1.3); “Design-based” (Sec. 1.2); Dichotomous branching of airways (Sec. 8.1, Fig. 9A); Disector principle: physical, optical (Sec. 2.1, items d and e); “Do more less well” (Sec. 2.2, item c); Sec. 4.4; Efficiency (Sec. 4.4); Euler characteristic (Sec. 6.4); Fine nonparenchyma (Sec. 6.2; Figure 5); Fine parenchyma (Sec. 6.2; Equation 12); Fractal tree (Sec. 8.1); Fractionator sampling (Sec. 4.2.5; Figure 4); Global estimators (Sec. 2.1); “Gold standard” in fixation (Sec. 3.1); Harmonic mean thickness of air–blood barrier (Sec. 6.7); Horsfield ordering system (Sec. 8.1; Figure 9b); Isector (isotropic orientation) (Figure 4); Isotropic uniform random (IUR) sampling (Sec. 4.2.3); Isotropy (Sec. 1.1, item f); Local estimators (Sec. 2.1, item e); Mean chord length or mean linear intercept (Sec. 6.6); Monopodial airway branching (Sec. 8.1); Morphometry (Sec. 2.1); Multistage stratified morphometric analysis (Sec. 6.1); Multistage stratified sampling (Sec. 4.2.6); Nucleator (Sec. 2.1, item e); Number-weighted mean particle volume (Sec. 2.1, items e and f); Orientator (Sec. 4.2.3); Point-sampled intercept (Sec. 2.1, item e); Precision (Sec. 1.2); Reference space (Sec. 5); Reference Lung volume (Sec. 5.1); “Reference trap” (Sec. 5); Relative deposition index (RDI) (Sec. 7.2); Relative labeling index (RLI) (Sec. 7.2); Rotator (Sec. 2.1, item e); Sampling (Sec. 2.1, Sec. 4); Sampling fraction (Sec. 6.4; Figure 4); Sampling procedures (Sec. 4.2); Sampling rules (Sec. 4.1); “Silver standards” in fixation technique (Sec. 3.1; Sec. 3.3); Stereology (Sec. 2.1); Strahler ordering system (Sec. 8.1; Figure 9b); Stratified uniform random (StUR) sampling (Sec. 4.2.2); Surface density (Sec 2.1, item b; Sec. 6.3); Systematic uniform random sampling (SURS) (Sec. 4.2.1); Test probes, test systems (Sec. 2.1, item a; Sec. 6.9; Figure 6); Uniform random sections (Sec. 4.2.1; Sec. 4.2.2; Sec. 4.2.3); Vertical sections (Sec. 4.2.4; Figure 3); Volume density (Sec. 2.1, item b; Sec. 6.2); Volume-weighted mean particle volume (Sec. 2.1, items e and f). Open in a separate window Figure 3. Vertical sections. (A) An arbitrary horizontal reference plane, such as a cutting board, is considered fixed and the vertical section is perpendicular to this horizontal plane. Airways selected by microdissection can be sampled by this vertical section scheme, by bisecting the airway longitudinally and laying it flat with the luminal surface up. In this orientation, the arrow that runs from base to apex of the epithelium indicates the direction of the vertical axis, V. (B) Bisected airway can be cut into strips of tissue. (C) Each airway tissue strip is cut following a random rotation of the cutting angle to achieve uniform randomness. (D) The blocks are then selected by SURS procedures for embedding with the vertical direction maintained in the embedding mold. Reproduced by permission from Reference 208.
Connie C W Hsia - One of the best experts on this subject based on the ideXlab platform.
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Lung Structure and the intrinsic challenges of gas exchange
Comprehensive Physiology, 2016Co-Authors: Connie C W Hsia, Dallas M Hyde, Ewald R WeibelAbstract:Structural and functional complexities of the mammalian Lung evolved to meet a unique set of challenges, namely, the provision of efficient delivery of inspired air to all Lung units within a confined thoracic space, to build a large gas exchange surface associated with minimal barrier thickness and a microvascular network to accommodate the entire right ventricular cardiac output while withstanding cyclic mechanical stresses that increase several folds from rest to exercise. Intricate regulatory mechanisms at every level ensure that the dynamic capacities of ventilation, perfusion, diffusion, and chemical binding to hemoglobin are commensurate with usual metabolic demands and periodic extreme needs for activity and survival. This article reviews the structural design of mammalian and human Lung, its functional challenges, limitations, and potential for adaptation. We discuss (i) the evolutionary origin of alveolar Lungs and its advantages and compromises, (ii) structural determinants of alveolar gas exchange, including architecture of conducting bronchovascular trees that converge in gas exchange units, (iii) the challenges of matching ventilation, perfusion, and diffusion and tissue-erythrocyte and thoracopulmonary interactions. The notion of erythrocytes as an integral component of the gas exchanger is emphasized. We further discuss the signals, sources, and limits of structural plasticity of the Lung in alveolar hypoxia and following a loss of Lung units, and the promise and caveats of interventions aimed at augmenting endogenous adaptive responses. Our objective is to understand how individual components are matched at multiple levels to optimize organ function in the face of physiological demands or pathological constraints. © 2016 American Physiological Society. Compr Physiol 6:827-895, 2016.
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an official research policy statement of the american thoracic society european respiratory society standards for quantitative assessment of Lung Structure
American Journal of Respiratory and Critical Care Medicine, 2010Co-Authors: Connie C W Hsia, Matthias Ochs, Dallas M Hyde, Ewald R WeibelAbstract:1.1. The Challenges To understand normal Lung function, the processes of growth and development, and the mechanisms and effects of diseases, we need information about the 3D Structure of the Lung. Quantification of organ Structure is based upon 3D physical attributes of tissues, cells, organelles, alveoli, airways, and blood vessels. When Structures of interest are inaccessible or too small to be seen macroscopically, we rely on physical or optical sections through a few representative samples taken from the large heterogeneous organ. The resulting 2D images confer incomplete information about the 3D Structure, and may not accurately represent true 3D properties, leading to possible misinterpretation when measurements are made on 2D sections. Because structural quantification is often considered the “gold standard” in evaluating experimental intervention, disease severity, and treatment response, it is imperative that these quantitative methods are (1) accurate to allow meaningful interpretation of results, (2) efficient to yield adequate precision with reasonable effort, (3) of adequate statistical power to encompass inherent variability, and (4) adherent to uniform standards to facilitate comparisons among experimental groups and across different studies. The Lung poses special challenges, some of which are outlined below and discussed in later sections: (a) Heterogeneity of Lung Structure requires standardized preparation methods. The inflated Lung consists of mostly air; only 10 to 15% of its volume consists of tissue (cells, fibers, and matrix) and blood. In vivo Lung volume and relative volumes of air, tissue, and blood fluctuate widely, while gravitational and nongravitational gradients cause spatial heterogeneity in Structure and function. Failure to standardize physiological variables or minimize tissue distortion introduces uncertainties or errors into subsequent measurements, to the point of their being meaningless (1). Careful selection of fixation and preparation methods that minimize shrinkage obviates this problem (Section 3). (b) Selected microscopic sections should provide a fair sample of the whole organ. The practice of picking specific samples or sections often fails to account for regional heterogeneity, leading to biased conclusions with respect to the whole organ. Deliberately choosing sections that contain a particular compartment (e.g., profiles of alveolar type 2 epithelial cells) overestimates their abundance within the whole Lung. Using a sampling scheme that covers all regions with equal probability alleviates this problem (Section 4). (c) Measurements made on microscopic sections must be related to the whole organ or an appropriate reference volume. Studies continue to appear that report only relative measurements (i.e., volume and surface densities or ratios) without knowledge of the Lung volume. These ratios are dependent on Lung inflation, and must be multiplied by absolute Lung volume to obtain accurate total quantities of the Structures of interest. Uncertainties regarding Lung volume can bias data interpretation. For example, enlarged mean airspace size need not signify emphysema or alveolar hypoplasia; the finding could also be caused by overinflation. Careful measurement of the Lung volume eliminates this error (Section 5). (d) Lung Structures are irregular and their geometry easily altered by pathology and intervention. Measurements on 2D images that rely on assumed geometry may misrepresent the 3D Structure. Examples include estimating alveolar size from cross-sectional areas of alveolar profiles, and reporting alveolar surface area by the length of alveolar profile boundary. These measures can severely misrepresent the 3D Structure of interest. Airspace size is often inferred from the mean linear intercept (Lm), which in fact measures airspace volume-to-surface ratio and can be converted to diameter or volume only by assuming a shape factor. Airspace distortion, or selective distortion of alveolar ducts but not alveolar sacs, can invalidate shape assumptions (Section 6). (e) The number of Lung cells cannot be estimated by counting their profiles on random histologic sections because larger cells have a greater probability of being sampled. For example, if experimental intervention causes selective cell hypertrophy, the increased probability of counting cell profiles will lead to wrong conclusions. Again, using stereologic methods that are free of geometric assumptions eliminates this error (Sections 6–7). (f) In contrast to acinar Structures that exhibit nearly random orientation (isotropy) and homogeneous distribution, conducting airways and blood vessels exhibit preferred directions (anisotropy) and inhomogeneous distribution, which alter their sampling probability on random sections. Specific sampling procedures that account for their nonrandom nature should be employed to ensure unbiased representation on 2D sections (Section 8). (g) Assessment of endobronchial or Lung biopsy specimens is limited by their nonrandom nature and a lack of external reference parameter. Endobronchial biopsy specimens are also anisotropic with distinct luminal and basal sides and with respect to airway generations. To minimize potential errors in quantification, specimens should be processed with their orientation randomized and analyzed with respect to an internal reference parameter (Section 9). (h) The new imaging techniques CT and MRI offer the possibility of obtaining high-fidelity images of Lung Structure in vivo that can be used for quantitative assessment of structural changes. Since their images are sections of the organ, stereology can ensure accurate measurements (Section 10). Definition of terms (section of text where term is defined) Accuracy (Sec. 1.2); ALP-sector (Sec. 2.1, item a); Anisotropy (Sec. 1.1, item f); Apparent diffusion coefficient (ADC) (Sec. 10.4.1); Arithmetic mean thickness of air-blood barrier (Sec. 6.7); Bias (Sec. 1.2); Buffon's needle (Sec. 1.3); Cavalieri Principle/Method (Sec. 1.3); Coarse nonparenchyma (Sec. 6.2); Coarse parenchyma (Sec. 6.2); Computer-aided stereology systems (Sec. 2.2, item c); Connectivity of airway branching systems (Sec. 8.1); Delesse principle (Sec. 1.3); “Design-based” (Sec. 1.2); Dichotomous branching of airways (Sec. 8.1, Fig. 9A); Disector principle: physical, optical (Sec. 2.1, items d and e); “Do more less well” (Sec. 2.2, item c); Sec. 4.4; Efficiency (Sec. 4.4); Euler characteristic (Sec. 6.4); Fine nonparenchyma (Sec. 6.2; Figure 5); Fine parenchyma (Sec. 6.2; Equation 12); Fractal tree (Sec. 8.1); Fractionator sampling (Sec. 4.2.5; Figure 4); Global estimators (Sec. 2.1); “Gold standard” in fixation (Sec. 3.1); Harmonic mean thickness of air–blood barrier (Sec. 6.7); Horsfield ordering system (Sec. 8.1; Figure 9b); Isector (isotropic orientation) (Figure 4); Isotropic uniform random (IUR) sampling (Sec. 4.2.3); Isotropy (Sec. 1.1, item f); Local estimators (Sec. 2.1, item e); Mean chord length or mean linear intercept (Sec. 6.6); Monopodial airway branching (Sec. 8.1); Morphometry (Sec. 2.1); Multistage stratified morphometric analysis (Sec. 6.1); Multistage stratified sampling (Sec. 4.2.6); Nucleator (Sec. 2.1, item e); Number-weighted mean particle volume (Sec. 2.1, items e and f); Orientator (Sec. 4.2.3); Point-sampled intercept (Sec. 2.1, item e); Precision (Sec. 1.2); Reference space (Sec. 5); Reference Lung volume (Sec. 5.1); “Reference trap” (Sec. 5); Relative deposition index (RDI) (Sec. 7.2); Relative labeling index (RLI) (Sec. 7.2); Rotator (Sec. 2.1, item e); Sampling (Sec. 2.1, Sec. 4); Sampling fraction (Sec. 6.4; Figure 4); Sampling procedures (Sec. 4.2); Sampling rules (Sec. 4.1); “Silver standards” in fixation technique (Sec. 3.1; Sec. 3.3); Stereology (Sec. 2.1); Strahler ordering system (Sec. 8.1; Figure 9b); Stratified uniform random (StUR) sampling (Sec. 4.2.2); Surface density (Sec 2.1, item b; Sec. 6.3); Systematic uniform random sampling (SURS) (Sec. 4.2.1); Test probes, test systems (Sec. 2.1, item a; Sec. 6.9; Figure 6); Uniform random sections (Sec. 4.2.1; Sec. 4.2.2; Sec. 4.2.3); Vertical sections (Sec. 4.2.4; Figure 3); Volume density (Sec. 2.1, item b; Sec. 6.2); Volume-weighted mean particle volume (Sec. 2.1, items e and f). Open in a separate window Figure 3. Vertical sections. (A) An arbitrary horizontal reference plane, such as a cutting board, is considered fixed and the vertical section is perpendicular to this horizontal plane. Airways selected by microdissection can be sampled by this vertical section scheme, by bisecting the airway longitudinally and laying it flat with the luminal surface up. In this orientation, the arrow that runs from base to apex of the epithelium indicates the direction of the vertical axis, V. (B) Bisected airway can be cut into strips of tissue. (C) Each airway tissue strip is cut following a random rotation of the cutting angle to achieve uniform randomness. (D) The blocks are then selected by SURS procedures for embedding with the vertical direction maintained in the embedding mold. Reproduced by permission from Reference 208.
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An Official Research Policy Statement of the American Thoracic Society/European Respiratory Society: Standards for Quantitative Assessment of Lung Structure
American Journal of Respiratory and Critical Care Medicine, 2010Co-Authors: Connie C W Hsia, Matthias Ochs, Dallas M Hyde, Ewald R WeibelAbstract:1.1. The Challenges To understand normal Lung function, the processes of growth and development, and the mechanisms and effects of diseases, we need information about the 3D Structure of the Lung. Quantification of organ Structure is based upon 3D physical attributes of tissues, cells, organelles, alveoli, airways, and blood vessels. When Structures of interest are inaccessible or too small to be seen macroscopically, we rely on physical or optical sections through a few representative samples taken from the large heterogeneous organ. The resulting 2D images confer incomplete information about the 3D Structure, and may not accurately represent true 3D properties, leading to possible misinterpretation when measurements are made on 2D sections. Because structural quantification is often considered the “gold standard” in evaluating experimental intervention, disease severity, and treatment response, it is imperative that these quantitative methods are (1) accurate to allow meaningful interpretation of results, (2) efficient to yield adequate precision with reasonable effort, (3) of adequate statistical power to encompass inherent variability, and (4) adherent to uniform standards to facilitate comparisons among experimental groups and across different studies. The Lung poses special challenges, some of which are outlined below and discussed in later sections: (a) Heterogeneity of Lung Structure requires standardized preparation methods. The inflated Lung consists of mostly air; only 10 to 15% of its volume consists of tissue (cells, fibers, and matrix) and blood. In vivo Lung volume and relative volumes of air, tissue, and blood fluctuate widely, while gravitational and nongravitational gradients cause spatial heterogeneity in Structure and function. Failure to standardize physiological variables or minimize tissue distortion introduces uncertainties or errors into subsequent measurements, to the point of their being meaningless (1). Careful selection of fixation and preparation methods that minimize shrinkage obviates this problem (Section 3). (b) Selected microscopic sections should provide a fair sample of the whole organ. The practice of picking specific samples or sections often fails to account for regional heterogeneity, leading to biased conclusions with respect to the whole organ. Deliberately choosing sections that contain a particular compartment (e.g., profiles of alveolar type 2 epithelial cells) overestimates their abundance within the whole Lung. Using a sampling scheme that covers all regions with equal probability alleviates this problem (Section 4). (c) Measurements made on microscopic sections must be related to the whole organ or an appropriate reference volume. Studies continue to appear that report only relative measurements (i.e., volume and surface densities or ratios) without knowledge of the Lung volume. These ratios are dependent on Lung inflation, and must be multiplied by absolute Lung volume to obtain accurate total quantities of the Structures of interest. Uncertainties regarding Lung volume can bias data interpretation. For example, enlarged mean airspace size need not signify emphysema or alveolar hypoplasia; the finding could also be caused by overinflation. Careful measurement of the Lung volume eliminates this error (Section 5). (d) Lung Structures are irregular and their geometry easily altered by pathology and intervention. Measurements on 2D images that rely on assumed geometry may misrepresent the 3D Structure. Examples include estimating alveolar size from cross-sectional areas of alveolar profiles, and reporting alveolar surface area by the length of alveolar profile boundary. These measures can severely misrepresent the 3D Structure of interest. Airspace size is often inferred from the mean linear intercept (Lm), which in fact measures airspace volume-to-surface ratio and can be converted to diameter or volume only by assuming a shape factor. Airspace distortion, or selective distortion of alveolar ducts but not alveolar sacs, can invalidate shape assumptions (Section 6). (e) The number of Lung cells cannot be estimated by counting their profiles on random histologic sections because larger cells have a greater probability of being sampled. For example, if experimental intervention causes selective cell hypertrophy, the increased probability of counting cell profiles will lead to wrong conclusions. Again, using stereologic methods that are free of geometric assumptions eliminates this error (Sections 6–7). (f) In contrast to acinar Structures that exhibit nearly random orientation (isotropy) and homogeneous distribution, conducting airways and blood vessels exhibit preferred directions (anisotropy) and inhomogeneous distribution, which alter their sampling probability on random sections. Specific sampling procedures that account for their nonrandom nature should be employed to ensure unbiased representation on 2D sections (Section 8). (g) Assessment of endobronchial or Lung biopsy specimens is limited by their nonrandom nature and a lack of external reference parameter. Endobronchial biopsy specimens are also anisotropic with distinct luminal and basal sides and with respect to airway generations. To minimize potential errors in quantification, specimens should be processed with their orientation randomized and analyzed with respect to an internal reference parameter (Section 9). (h) The new imaging techniques CT and MRI offer the possibility of obtaining high-fidelity images of Lung Structure in vivo that can be used for quantitative assessment of structural changes. Since their images are sections of the organ, stereology can ensure accurate measurements (Section 10). Definition of terms (section of text where term is defined) Accuracy (Sec. 1.2); ALP-sector (Sec. 2.1, item a); Anisotropy (Sec. 1.1, item f); Apparent diffusion coefficient (ADC) (Sec. 10.4.1); Arithmetic mean thickness of air-blood barrier (Sec. 6.7); Bias (Sec. 1.2); Buffon's needle (Sec. 1.3); Cavalieri Principle/Method (Sec. 1.3); Coarse nonparenchyma (Sec. 6.2); Coarse parenchyma (Sec. 6.2); Computer-aided stereology systems (Sec. 2.2, item c); Connectivity of airway branching systems (Sec. 8.1); Delesse principle (Sec. 1.3); “Design-based” (Sec. 1.2); Dichotomous branching of airways (Sec. 8.1, Fig. 9A); Disector principle: physical, optical (Sec. 2.1, items d and e); “Do more less well” (Sec. 2.2, item c); Sec. 4.4; Efficiency (Sec. 4.4); Euler characteristic (Sec. 6.4); Fine nonparenchyma (Sec. 6.2; Figure 5); Fine parenchyma (Sec. 6.2; Equation 12); Fractal tree (Sec. 8.1); Fractionator sampling (Sec. 4.2.5; Figure 4); Global estimators (Sec. 2.1); “Gold standard” in fixation (Sec. 3.1); Harmonic mean thickness of air–blood barrier (Sec. 6.7); Horsfield ordering system (Sec. 8.1; Figure 9b); Isector (isotropic orientation) (Figure 4); Isotropic uniform random (IUR) sampling (Sec. 4.2.3); Isotropy (Sec. 1.1, item f); Local estimators (Sec. 2.1, item e); Mean chord length or mean linear intercept (Sec. 6.6); Monopodial airway branching (Sec. 8.1); Morphometry (Sec. 2.1); Multistage stratified morphometric analysis (Sec. 6.1); Multistage stratified sampling (Sec. 4.2.6); Nucleator (Sec. 2.1, item e); Number-weighted mean particle volume (Sec. 2.1, items e and f); Orientator (Sec. 4.2.3); Point-sampled intercept (Sec. 2.1, item e); Precision (Sec. 1.2); Reference space (Sec. 5); Reference Lung volume (Sec. 5.1); “Reference trap” (Sec. 5); Relative deposition index (RDI) (Sec. 7.2); Relative labeling index (RLI) (Sec. 7.2); Rotator (Sec. 2.1, item e); Sampling (Sec. 2.1, Sec. 4); Sampling fraction (Sec. 6.4; Figure 4); Sampling procedures (Sec. 4.2); Sampling rules (Sec. 4.1); “Silver standards” in fixation technique (Sec. 3.1; Sec. 3.3); Stereology (Sec. 2.1); Strahler ordering system (Sec. 8.1; Figure 9b); Stratified uniform random (StUR) sampling (Sec. 4.2.2); Surface density (Sec 2.1, item b; Sec. 6.3); Systematic uniform random sampling (SURS) (Sec. 4.2.1); Test probes, test systems (Sec. 2.1, item a; Sec. 6.9; Figure 6); Uniform random sections (Sec. 4.2.1; Sec. 4.2.2; Sec. 4.2.3); Vertical sections (Sec. 4.2.4; Figure 3); Volume density (Sec. 2.1, item b; Sec. 6.2); Volume-weighted mean particle volume (Sec. 2.1, items e and f). Open in a separate window Figure 3. Vertical sections. (A) An arbitrary horizontal reference plane, such as a cutting board, is considered fixed and the vertical section is perpendicular to this horizontal plane. Airways selected by microdissection can be sampled by this vertical section scheme, by bisecting the airway longitudinally and laying it flat with the luminal surface up. In this orientation, the arrow that runs from base to apex of the epithelium indicates the direction of the vertical axis, V. (B) Bisected airway can be cut into strips of tissue. (C) Each airway tissue strip is cut following a random rotation of the cutting angle to achieve uniform randomness. (D) The blocks are then selected by SURS procedures for embedding with the vertical direction maintained in the embedding mold. Reproduced by permission from Reference 208.
Eric A Hoffman - One of the best experts on this subject based on the ideXlab platform.
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a genetic risk score associated with chronic obstructive pulmonary disease susceptibility and Lung Structure on computed tomography
American Journal of Respiratory and Critical Care Medicine, 2019Co-Authors: Elizabeth C Oelsner, Victor E Ortega, Benjamin M Smith, Jennifer Nguyen, Ani Manichaikul, Eric A Hoffman, Kent D Taylor, Prescott G Woodruff, David Couper, Nadia N HanselAbstract:Rationale: Chronic obstructive pulmonary disease (COPD) has been associated with numerous genetic variants, yet the extent to which its genetic risk is mediated by variation in Lung Structure remai...
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late breaking abstract associations between a copd genetic risk score and Lung Structure on computed tomography ct spiromics
European Respiratory Journal, 2018Co-Authors: Elizabeth C Oelsner, Benjamin M Smith, Jennifer Nguyen, Ani Manichaikul, Eric A Hoffman, Kent D Taylor, Elizabeth J Ampleford, Latchezar Dimitrov, Eugene R Bleecker, Xignan LiAbstract:Background: The extent to which genetic risk of COPD is mediated by variation in Lung Structure remains unknown. Aims: To determine whether a recently developed genetic risk score for Lung function (GRS; Wain LV et al, Nat Genet 2017; 49(3):416-425) is associated with CT Lung Structure. Methods: In SPIROMICS, a cohort of COPD subjects and at-risk smokers (≥20 pack-years), a weighted GRS was calculated from 83 of 95 single nucleotide polymorphisms genotyped or imputed across 3 race/ethnic groups. Post-bronchodilator spirometry and CT scan measures (via Apollo/VIDA) of Lung density, spatially-matched airway dimensions, and small airway counts (generations 6-9) were evaluated in models adjusted for age, age-squared, sex, height, BMI, principal components, smoking status, pack-years, CT model and voxel size. Results: Among 2,579 participants (average age 63 years, 53% male, 76% non-Hispanic White, 18% African-American, 6% Asian, 37% current smokers, median 44 pack-years, 63% with COPD), higher GRS was associated with lower FEV1 and FEV1/FVC, and the highest GRS quintile was associated with doubling of risk for moderate-to-severe COPD (p Conclusions: Variation in Lung Structure, whether developmental or acquired, is an important mediator of the genetic risk factors underlying COPD.
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not all measures of hyperinflation are created equal Lung Structure and clinical correlates of gas trapping and hyperexpansion in copd the multi ethnic study of atherosclerosis mesa copd study
Chest, 2014Co-Authors: Benjamin M Smith, Eric A Hoffman, Robert C Basner, Steven M Kawut, Ravi Kalhan, Graham R BarrAbstract:Background Hyperinflation refers to a nonspecific increase in absolute Lung volumes and has a poor prognosis in COPD. The relative contribution of increased airways resistance and increased parenchymal compliance to hyperinflation of each absolute Lung volume is poorly understood. We hypothesized that increased residual volume (RV) and RV/total Lung capacity (TLC) would be associated with reduced airway lumen dimensions, whereas increased functional residual capacity (FRC), TLC, and reduced inspiratory capacity (IC)/TLC would be associated with emphysema on CT scan. We examined whether clinical characteristics differed accordingly. Methods The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study recruited smokers aged 50 to 79 years who were free of clinical cardiovascular disease. Gas trapping was defined as RV or RV/TLC greater than the upper limit of normal and hyperexpansion as FRC or TLC greater than the upper limit of normal or IC/TLC less than the lower limit of normal. Airway lumen diameters and percent emphysema Results Among 116 participants completing plethysmography, 15% had gas trapping, 18% has hyperexpansion, and 22% had both. Gas trapping was associated with smaller airway lumen diameters ( P = .001), greater dyspnea ( P = .01), and chronic bronchitis ( P = .03). Hyperexpansion was associated with percent emphysema ( P P = .04), and higher hemoglobin concentration ( P = .001). Conclusions Gas trapping and hyperexpansion on plethysmography were associated with distinct differences in Lung Structure and clinical characteristics. Absolute Lung volumes should not be considered equivalent in their estimation of hyperinflation and provide insight into the extent of airway and parenchymal abnormalities in COPD.
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asthma and Lung Structure on computed tomography the multi ethnic study of atherosclerosis Lung study
The Journal of Allergy and Clinical Immunology, 2013Co-Authors: Kathleen M Donohue, Eric A Hoffman, Heather Baumhauer, Firas S Ahmed, Gina S Lovasi, David R Jacobs, Paul L Enright, Graham R BarrAbstract:Background The potential consequences of asthma in childhood and young adulthood on Lung Structure in older adults have not been studied in a large, population-based cohort. Objective The authors hypothesized that a history of asthma onset in childhood (age 18 years or before) or young adulthood (age 19-45 years) was associated with altered Lung Structure on computed tomography in later life. Methods The Multi-Ethnic Study of Atherosclerosis Lung Study recruited 3965 participants and assessed asthma history by using standardized questionnaires, guideline-based spirometry, and segmental airway dimensions and percentage of low attenuation area (%LAA) on computed tomographic scans. Results Asthma with onset in childhood and young adulthood was associated with large decrements in FEV 1 among participants with a mean age of 66 years (−365 mL and −343 mL, respectively; P P P P Conclusion Asthma with onset in childhood or young adulthood was associated with reduced Lung function, narrower airways, and among asthmatic patients who smoked, greater %LAA in later life.
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Lung Structure phenotype variation in inbred mouse strains revealed through in vivo micro ct imaging
Journal of Applied Physiology, 2010Co-Authors: Jacqueline Thiesse, Joseph M. Reinhardt, Eric A Hoffman, Eman Namati, Jessica C Sieren, Amanda R Smith, Geoffrey MclennanAbstract:Within pulmonary research, the development of mouse models has provided insight into disease development, progression, and treatment. Structural phenotypes of the Lung in healthy inbred mouse strains are necessary for comparison to disease models. To date, progress in the assessment of Lung function in these small animals using whole Lung function tests has been made. However, assessment of in vivo Lung Structure of inbred mouse strains has yet to be well defined. Therefore, the link between the Structure and function phenotypes is still unclear. With advancements in small animal imaging it is now possible to investigate Lung Structures such as the central and peripheral airways, whole Lung, and lobar volumes of mice in vivo, through the use of micro-CT imaging. In this study, we performed in vivo micro-CT imaging of the C57BL/6, A/J, and BALB/c mouse strains using the intermittent iso-pressure breath hold (IIBH) technique. The resulting high-resolution images were used to extract Lung Structure phenotypes. The three-dimensional lobar Structures and airways were defined and a meaningful mouse airway nomenclature was developed. In addition, using these techniques we have uncovered significant differences in the airway Structures between inbred mouse strains in vivo.
Juan Parrarobles - One of the best experts on this subject based on the ideXlab platform.
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simultaneous imaging of Lung Structure and function with triple nuclear hybrid mr imaging
Radiology, 2013Co-Authors: Jim M. Wild, Helen Marshall, Graham Norquay, Xiaoxun Xu, S R Parnell, Matthew Clemence, P D Griffiths, Juan ParraroblesAbstract:In this article, we demonstrate an integrated engineering system for the rapid acquisition of triple-nuclear MR images in the Lungs, which is implemented by using a standard 3-T clinical MR imaging system.
Dallas M Hyde - One of the best experts on this subject based on the ideXlab platform.
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Lung Structure and the intrinsic challenges of gas exchange
Comprehensive Physiology, 2016Co-Authors: Connie C W Hsia, Dallas M Hyde, Ewald R WeibelAbstract:Structural and functional complexities of the mammalian Lung evolved to meet a unique set of challenges, namely, the provision of efficient delivery of inspired air to all Lung units within a confined thoracic space, to build a large gas exchange surface associated with minimal barrier thickness and a microvascular network to accommodate the entire right ventricular cardiac output while withstanding cyclic mechanical stresses that increase several folds from rest to exercise. Intricate regulatory mechanisms at every level ensure that the dynamic capacities of ventilation, perfusion, diffusion, and chemical binding to hemoglobin are commensurate with usual metabolic demands and periodic extreme needs for activity and survival. This article reviews the structural design of mammalian and human Lung, its functional challenges, limitations, and potential for adaptation. We discuss (i) the evolutionary origin of alveolar Lungs and its advantages and compromises, (ii) structural determinants of alveolar gas exchange, including architecture of conducting bronchovascular trees that converge in gas exchange units, (iii) the challenges of matching ventilation, perfusion, and diffusion and tissue-erythrocyte and thoracopulmonary interactions. The notion of erythrocytes as an integral component of the gas exchanger is emphasized. We further discuss the signals, sources, and limits of structural plasticity of the Lung in alveolar hypoxia and following a loss of Lung units, and the promise and caveats of interventions aimed at augmenting endogenous adaptive responses. Our objective is to understand how individual components are matched at multiple levels to optimize organ function in the face of physiological demands or pathological constraints. © 2016 American Physiological Society. Compr Physiol 6:827-895, 2016.
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an official research policy statement of the american thoracic society european respiratory society standards for quantitative assessment of Lung Structure
American Journal of Respiratory and Critical Care Medicine, 2010Co-Authors: Connie C W Hsia, Matthias Ochs, Dallas M Hyde, Ewald R WeibelAbstract:1.1. The Challenges To understand normal Lung function, the processes of growth and development, and the mechanisms and effects of diseases, we need information about the 3D Structure of the Lung. Quantification of organ Structure is based upon 3D physical attributes of tissues, cells, organelles, alveoli, airways, and blood vessels. When Structures of interest are inaccessible or too small to be seen macroscopically, we rely on physical or optical sections through a few representative samples taken from the large heterogeneous organ. The resulting 2D images confer incomplete information about the 3D Structure, and may not accurately represent true 3D properties, leading to possible misinterpretation when measurements are made on 2D sections. Because structural quantification is often considered the “gold standard” in evaluating experimental intervention, disease severity, and treatment response, it is imperative that these quantitative methods are (1) accurate to allow meaningful interpretation of results, (2) efficient to yield adequate precision with reasonable effort, (3) of adequate statistical power to encompass inherent variability, and (4) adherent to uniform standards to facilitate comparisons among experimental groups and across different studies. The Lung poses special challenges, some of which are outlined below and discussed in later sections: (a) Heterogeneity of Lung Structure requires standardized preparation methods. The inflated Lung consists of mostly air; only 10 to 15% of its volume consists of tissue (cells, fibers, and matrix) and blood. In vivo Lung volume and relative volumes of air, tissue, and blood fluctuate widely, while gravitational and nongravitational gradients cause spatial heterogeneity in Structure and function. Failure to standardize physiological variables or minimize tissue distortion introduces uncertainties or errors into subsequent measurements, to the point of their being meaningless (1). Careful selection of fixation and preparation methods that minimize shrinkage obviates this problem (Section 3). (b) Selected microscopic sections should provide a fair sample of the whole organ. The practice of picking specific samples or sections often fails to account for regional heterogeneity, leading to biased conclusions with respect to the whole organ. Deliberately choosing sections that contain a particular compartment (e.g., profiles of alveolar type 2 epithelial cells) overestimates their abundance within the whole Lung. Using a sampling scheme that covers all regions with equal probability alleviates this problem (Section 4). (c) Measurements made on microscopic sections must be related to the whole organ or an appropriate reference volume. Studies continue to appear that report only relative measurements (i.e., volume and surface densities or ratios) without knowledge of the Lung volume. These ratios are dependent on Lung inflation, and must be multiplied by absolute Lung volume to obtain accurate total quantities of the Structures of interest. Uncertainties regarding Lung volume can bias data interpretation. For example, enlarged mean airspace size need not signify emphysema or alveolar hypoplasia; the finding could also be caused by overinflation. Careful measurement of the Lung volume eliminates this error (Section 5). (d) Lung Structures are irregular and their geometry easily altered by pathology and intervention. Measurements on 2D images that rely on assumed geometry may misrepresent the 3D Structure. Examples include estimating alveolar size from cross-sectional areas of alveolar profiles, and reporting alveolar surface area by the length of alveolar profile boundary. These measures can severely misrepresent the 3D Structure of interest. Airspace size is often inferred from the mean linear intercept (Lm), which in fact measures airspace volume-to-surface ratio and can be converted to diameter or volume only by assuming a shape factor. Airspace distortion, or selective distortion of alveolar ducts but not alveolar sacs, can invalidate shape assumptions (Section 6). (e) The number of Lung cells cannot be estimated by counting their profiles on random histologic sections because larger cells have a greater probability of being sampled. For example, if experimental intervention causes selective cell hypertrophy, the increased probability of counting cell profiles will lead to wrong conclusions. Again, using stereologic methods that are free of geometric assumptions eliminates this error (Sections 6–7). (f) In contrast to acinar Structures that exhibit nearly random orientation (isotropy) and homogeneous distribution, conducting airways and blood vessels exhibit preferred directions (anisotropy) and inhomogeneous distribution, which alter their sampling probability on random sections. Specific sampling procedures that account for their nonrandom nature should be employed to ensure unbiased representation on 2D sections (Section 8). (g) Assessment of endobronchial or Lung biopsy specimens is limited by their nonrandom nature and a lack of external reference parameter. Endobronchial biopsy specimens are also anisotropic with distinct luminal and basal sides and with respect to airway generations. To minimize potential errors in quantification, specimens should be processed with their orientation randomized and analyzed with respect to an internal reference parameter (Section 9). (h) The new imaging techniques CT and MRI offer the possibility of obtaining high-fidelity images of Lung Structure in vivo that can be used for quantitative assessment of structural changes. Since their images are sections of the organ, stereology can ensure accurate measurements (Section 10). Definition of terms (section of text where term is defined) Accuracy (Sec. 1.2); ALP-sector (Sec. 2.1, item a); Anisotropy (Sec. 1.1, item f); Apparent diffusion coefficient (ADC) (Sec. 10.4.1); Arithmetic mean thickness of air-blood barrier (Sec. 6.7); Bias (Sec. 1.2); Buffon's needle (Sec. 1.3); Cavalieri Principle/Method (Sec. 1.3); Coarse nonparenchyma (Sec. 6.2); Coarse parenchyma (Sec. 6.2); Computer-aided stereology systems (Sec. 2.2, item c); Connectivity of airway branching systems (Sec. 8.1); Delesse principle (Sec. 1.3); “Design-based” (Sec. 1.2); Dichotomous branching of airways (Sec. 8.1, Fig. 9A); Disector principle: physical, optical (Sec. 2.1, items d and e); “Do more less well” (Sec. 2.2, item c); Sec. 4.4; Efficiency (Sec. 4.4); Euler characteristic (Sec. 6.4); Fine nonparenchyma (Sec. 6.2; Figure 5); Fine parenchyma (Sec. 6.2; Equation 12); Fractal tree (Sec. 8.1); Fractionator sampling (Sec. 4.2.5; Figure 4); Global estimators (Sec. 2.1); “Gold standard” in fixation (Sec. 3.1); Harmonic mean thickness of air–blood barrier (Sec. 6.7); Horsfield ordering system (Sec. 8.1; Figure 9b); Isector (isotropic orientation) (Figure 4); Isotropic uniform random (IUR) sampling (Sec. 4.2.3); Isotropy (Sec. 1.1, item f); Local estimators (Sec. 2.1, item e); Mean chord length or mean linear intercept (Sec. 6.6); Monopodial airway branching (Sec. 8.1); Morphometry (Sec. 2.1); Multistage stratified morphometric analysis (Sec. 6.1); Multistage stratified sampling (Sec. 4.2.6); Nucleator (Sec. 2.1, item e); Number-weighted mean particle volume (Sec. 2.1, items e and f); Orientator (Sec. 4.2.3); Point-sampled intercept (Sec. 2.1, item e); Precision (Sec. 1.2); Reference space (Sec. 5); Reference Lung volume (Sec. 5.1); “Reference trap” (Sec. 5); Relative deposition index (RDI) (Sec. 7.2); Relative labeling index (RLI) (Sec. 7.2); Rotator (Sec. 2.1, item e); Sampling (Sec. 2.1, Sec. 4); Sampling fraction (Sec. 6.4; Figure 4); Sampling procedures (Sec. 4.2); Sampling rules (Sec. 4.1); “Silver standards” in fixation technique (Sec. 3.1; Sec. 3.3); Stereology (Sec. 2.1); Strahler ordering system (Sec. 8.1; Figure 9b); Stratified uniform random (StUR) sampling (Sec. 4.2.2); Surface density (Sec 2.1, item b; Sec. 6.3); Systematic uniform random sampling (SURS) (Sec. 4.2.1); Test probes, test systems (Sec. 2.1, item a; Sec. 6.9; Figure 6); Uniform random sections (Sec. 4.2.1; Sec. 4.2.2; Sec. 4.2.3); Vertical sections (Sec. 4.2.4; Figure 3); Volume density (Sec. 2.1, item b; Sec. 6.2); Volume-weighted mean particle volume (Sec. 2.1, items e and f). Open in a separate window Figure 3. Vertical sections. (A) An arbitrary horizontal reference plane, such as a cutting board, is considered fixed and the vertical section is perpendicular to this horizontal plane. Airways selected by microdissection can be sampled by this vertical section scheme, by bisecting the airway longitudinally and laying it flat with the luminal surface up. In this orientation, the arrow that runs from base to apex of the epithelium indicates the direction of the vertical axis, V. (B) Bisected airway can be cut into strips of tissue. (C) Each airway tissue strip is cut following a random rotation of the cutting angle to achieve uniform randomness. (D) The blocks are then selected by SURS procedures for embedding with the vertical direction maintained in the embedding mold. Reproduced by permission from Reference 208.
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An Official Research Policy Statement of the American Thoracic Society/European Respiratory Society: Standards for Quantitative Assessment of Lung Structure
American Journal of Respiratory and Critical Care Medicine, 2010Co-Authors: Connie C W Hsia, Matthias Ochs, Dallas M Hyde, Ewald R WeibelAbstract:1.1. The Challenges To understand normal Lung function, the processes of growth and development, and the mechanisms and effects of diseases, we need information about the 3D Structure of the Lung. Quantification of organ Structure is based upon 3D physical attributes of tissues, cells, organelles, alveoli, airways, and blood vessels. When Structures of interest are inaccessible or too small to be seen macroscopically, we rely on physical or optical sections through a few representative samples taken from the large heterogeneous organ. The resulting 2D images confer incomplete information about the 3D Structure, and may not accurately represent true 3D properties, leading to possible misinterpretation when measurements are made on 2D sections. Because structural quantification is often considered the “gold standard” in evaluating experimental intervention, disease severity, and treatment response, it is imperative that these quantitative methods are (1) accurate to allow meaningful interpretation of results, (2) efficient to yield adequate precision with reasonable effort, (3) of adequate statistical power to encompass inherent variability, and (4) adherent to uniform standards to facilitate comparisons among experimental groups and across different studies. The Lung poses special challenges, some of which are outlined below and discussed in later sections: (a) Heterogeneity of Lung Structure requires standardized preparation methods. The inflated Lung consists of mostly air; only 10 to 15% of its volume consists of tissue (cells, fibers, and matrix) and blood. In vivo Lung volume and relative volumes of air, tissue, and blood fluctuate widely, while gravitational and nongravitational gradients cause spatial heterogeneity in Structure and function. Failure to standardize physiological variables or minimize tissue distortion introduces uncertainties or errors into subsequent measurements, to the point of their being meaningless (1). Careful selection of fixation and preparation methods that minimize shrinkage obviates this problem (Section 3). (b) Selected microscopic sections should provide a fair sample of the whole organ. The practice of picking specific samples or sections often fails to account for regional heterogeneity, leading to biased conclusions with respect to the whole organ. Deliberately choosing sections that contain a particular compartment (e.g., profiles of alveolar type 2 epithelial cells) overestimates their abundance within the whole Lung. Using a sampling scheme that covers all regions with equal probability alleviates this problem (Section 4). (c) Measurements made on microscopic sections must be related to the whole organ or an appropriate reference volume. Studies continue to appear that report only relative measurements (i.e., volume and surface densities or ratios) without knowledge of the Lung volume. These ratios are dependent on Lung inflation, and must be multiplied by absolute Lung volume to obtain accurate total quantities of the Structures of interest. Uncertainties regarding Lung volume can bias data interpretation. For example, enlarged mean airspace size need not signify emphysema or alveolar hypoplasia; the finding could also be caused by overinflation. Careful measurement of the Lung volume eliminates this error (Section 5). (d) Lung Structures are irregular and their geometry easily altered by pathology and intervention. Measurements on 2D images that rely on assumed geometry may misrepresent the 3D Structure. Examples include estimating alveolar size from cross-sectional areas of alveolar profiles, and reporting alveolar surface area by the length of alveolar profile boundary. These measures can severely misrepresent the 3D Structure of interest. Airspace size is often inferred from the mean linear intercept (Lm), which in fact measures airspace volume-to-surface ratio and can be converted to diameter or volume only by assuming a shape factor. Airspace distortion, or selective distortion of alveolar ducts but not alveolar sacs, can invalidate shape assumptions (Section 6). (e) The number of Lung cells cannot be estimated by counting their profiles on random histologic sections because larger cells have a greater probability of being sampled. For example, if experimental intervention causes selective cell hypertrophy, the increased probability of counting cell profiles will lead to wrong conclusions. Again, using stereologic methods that are free of geometric assumptions eliminates this error (Sections 6–7). (f) In contrast to acinar Structures that exhibit nearly random orientation (isotropy) and homogeneous distribution, conducting airways and blood vessels exhibit preferred directions (anisotropy) and inhomogeneous distribution, which alter their sampling probability on random sections. Specific sampling procedures that account for their nonrandom nature should be employed to ensure unbiased representation on 2D sections (Section 8). (g) Assessment of endobronchial or Lung biopsy specimens is limited by their nonrandom nature and a lack of external reference parameter. Endobronchial biopsy specimens are also anisotropic with distinct luminal and basal sides and with respect to airway generations. To minimize potential errors in quantification, specimens should be processed with their orientation randomized and analyzed with respect to an internal reference parameter (Section 9). (h) The new imaging techniques CT and MRI offer the possibility of obtaining high-fidelity images of Lung Structure in vivo that can be used for quantitative assessment of structural changes. Since their images are sections of the organ, stereology can ensure accurate measurements (Section 10). Definition of terms (section of text where term is defined) Accuracy (Sec. 1.2); ALP-sector (Sec. 2.1, item a); Anisotropy (Sec. 1.1, item f); Apparent diffusion coefficient (ADC) (Sec. 10.4.1); Arithmetic mean thickness of air-blood barrier (Sec. 6.7); Bias (Sec. 1.2); Buffon's needle (Sec. 1.3); Cavalieri Principle/Method (Sec. 1.3); Coarse nonparenchyma (Sec. 6.2); Coarse parenchyma (Sec. 6.2); Computer-aided stereology systems (Sec. 2.2, item c); Connectivity of airway branching systems (Sec. 8.1); Delesse principle (Sec. 1.3); “Design-based” (Sec. 1.2); Dichotomous branching of airways (Sec. 8.1, Fig. 9A); Disector principle: physical, optical (Sec. 2.1, items d and e); “Do more less well” (Sec. 2.2, item c); Sec. 4.4; Efficiency (Sec. 4.4); Euler characteristic (Sec. 6.4); Fine nonparenchyma (Sec. 6.2; Figure 5); Fine parenchyma (Sec. 6.2; Equation 12); Fractal tree (Sec. 8.1); Fractionator sampling (Sec. 4.2.5; Figure 4); Global estimators (Sec. 2.1); “Gold standard” in fixation (Sec. 3.1); Harmonic mean thickness of air–blood barrier (Sec. 6.7); Horsfield ordering system (Sec. 8.1; Figure 9b); Isector (isotropic orientation) (Figure 4); Isotropic uniform random (IUR) sampling (Sec. 4.2.3); Isotropy (Sec. 1.1, item f); Local estimators (Sec. 2.1, item e); Mean chord length or mean linear intercept (Sec. 6.6); Monopodial airway branching (Sec. 8.1); Morphometry (Sec. 2.1); Multistage stratified morphometric analysis (Sec. 6.1); Multistage stratified sampling (Sec. 4.2.6); Nucleator (Sec. 2.1, item e); Number-weighted mean particle volume (Sec. 2.1, items e and f); Orientator (Sec. 4.2.3); Point-sampled intercept (Sec. 2.1, item e); Precision (Sec. 1.2); Reference space (Sec. 5); Reference Lung volume (Sec. 5.1); “Reference trap” (Sec. 5); Relative deposition index (RDI) (Sec. 7.2); Relative labeling index (RLI) (Sec. 7.2); Rotator (Sec. 2.1, item e); Sampling (Sec. 2.1, Sec. 4); Sampling fraction (Sec. 6.4; Figure 4); Sampling procedures (Sec. 4.2); Sampling rules (Sec. 4.1); “Silver standards” in fixation technique (Sec. 3.1; Sec. 3.3); Stereology (Sec. 2.1); Strahler ordering system (Sec. 8.1; Figure 9b); Stratified uniform random (StUR) sampling (Sec. 4.2.2); Surface density (Sec 2.1, item b; Sec. 6.3); Systematic uniform random sampling (SURS) (Sec. 4.2.1); Test probes, test systems (Sec. 2.1, item a; Sec. 6.9; Figure 6); Uniform random sections (Sec. 4.2.1; Sec. 4.2.2; Sec. 4.2.3); Vertical sections (Sec. 4.2.4; Figure 3); Volume density (Sec. 2.1, item b; Sec. 6.2); Volume-weighted mean particle volume (Sec. 2.1, items e and f). Open in a separate window Figure 3. Vertical sections. (A) An arbitrary horizontal reference plane, such as a cutting board, is considered fixed and the vertical section is perpendicular to this horizontal plane. Airways selected by microdissection can be sampled by this vertical section scheme, by bisecting the airway longitudinally and laying it flat with the luminal surface up. In this orientation, the arrow that runs from base to apex of the epithelium indicates the direction of the vertical axis, V. (B) Bisected airway can be cut into strips of tissue. (C) Each airway tissue strip is cut following a random rotation of the cutting angle to achieve uniform randomness. (D) The blocks are then selected by SURS procedures for embedding with the vertical direction maintained in the embedding mold. Reproduced by permission from Reference 208.
