Cell Counting in Human Endobronchial Biopsies - Disagreement of 2D versus 3D Morphometry
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{"title"=>"Cell counting in human endobronchial biopsies - Disagreement of 2D versus 3D morphometry", "type"=>"journal", "authors"=>[{"first_name"=>"Vlad A.", "last_name"=>"Bratu", "scopus_author_id"=>"16300970600"}, {"first_name"=>"Veit J.", "last_name"=>"Erpenbeck", "scopus_author_id"=>"6603596294"}, {"first_name"=>"Antonia", "last_name"=>"Fehrenbach", "scopus_author_id"=>"6603873814"}, {"first_name"=>"Tanja", "last_name"=>"Rausch", "scopus_author_id"=>"25951662200"}, {"first_name"=>"Susanne", "last_name"=>"Rittinghausen", "scopus_author_id"=>"6603690828"}, {"first_name"=>"Norbert", "last_name"=>"Krug", "scopus_author_id"=>"36618807500"}, {"first_name"=>"Jens M.", "last_name"=>"Hohlfeld", "scopus_author_id"=>"7006477184"}, {"first_name"=>"Heinz", "last_name"=>"Fehrenbach", "scopus_author_id"=>"7004749959"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "pui"=>"373007531", "doi"=>"10.1371/journal.pone.0092510", "sgr"=>"84899733963", "scopus"=>"2-s2.0-84899733963", "pmid"=>"24663339"}, "id"=>"c95a737a-feb4-3140-84ff-fe08e83826d4", "abstract"=>"QUESTION: Inflammatory cell numbers are important endpoints in clinical studies relying on endobronchial biopsies. Assumption-based bidimensional (2D) counting methods are widely used, although theoretically design-based stereologic three-dimensional (3D) methods alone offer an unbiased quantitative tool. We assessed the method agreement between 2D and 3D counting designs in practice when applied to identical samples in parallel.\\n\\nMATERIALS AND METHODS: Biopsies from segmental bronchi were collected from healthy non-smokers (n = 7) and smokers (n = 7), embedded and sectioned exhaustively. Systematic uniform random samples were immunohistochemically stained for macrophages (CD68) and T-lymphocytes (CD3), respectively. In identical fields of view, cell numbers per volume unit (NV) were assessed using the physical disector (3D), and profiles per area unit (NA) were counted (2D). For CD68+ cells, profiles with and without nucleus were separately recorded. In order to enable a direct comparison of the two methods, the zero-dimensional CD68+/CD3+-ratio was calculated for each approach. Method agreement was tested by Bland-Altmann analysis.\\n\\nRESULTS: In both groups, mean CD68+/CD3+ ratios for NV and NA were significantly different (non-smokers: 0.39 and 0.68, p<0.05; smokers: 0.49 and 1.68, p<0.05). When counting only nucleated CD68+ profiles, mean ratios obtained by 2D and 3D counting were similar, but the regression-based Bland-Altmann analysis indicated a bias of the 2D ratios proportional to their magnitude. This magnitude dependent deviation differed between the two groups.\\n\\nCONCLUSIONS: 2D counts of cell and nuclear profiles introduce a variable size-dependent bias throughout the measurement range. Because the deviation between the 3D and 2D data was different in the two groups, it precludes establishing a 'universal conversion formula'.", "link"=>"http://www.mendeley.com/research/cell-counting-human-endobronchial-biopsies-disagreement-2d-versus-3d-morphometry", "reader_count"=>7, "reader_count_by_academic_status"=>{"Student > Doctoral Student"=>1, "Researcher"=>2, "Student > Ph. D. Student"=>3, "Professor"=>1}, "reader_count_by_user_role"=>{"Student > Doctoral Student"=>1, "Researcher"=>2, "Student > Ph. D. Student"=>3, "Professor"=>1}, "reader_count_by_subject_area"=>{"Medicine and Dentistry"=>3, "Agricultural and Biological Sciences"=>1, "Computer Science"=>2, "Engineering"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Computer Science"=>{"Computer Science"=>2}}, "reader_count_by_country"=>{"Germany"=>1}, "group_count"=>0}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1433335"], "description"=>"<p>Mean counts per unit volume and area (mean + SD) by group and cell population.</p>", "links"=>[], "tags"=>["anatomy", "histology", "Respiratory system", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "t cells", "Immune cells", "immunology", "Clinical immunology", "Pulmonology", "Chronic Obstructive Pulmonary Disease", "Histochemistry and cytochemistry techniques", "Immunohistochemistry techniques", "Immunohistochemical analysis", "Immunologic techniques", "counts"], "article_id"=>972749, "categories"=>["Biological Sciences"], "users"=>["Vlad A. Bratu", "Veit J. Erpenbeck", "Antonia Fehrenbach", "Tanja Rausch", "Susanne Rittinghausen", "Norbert Krug", "Jens M. Hohlfeld", "Heinz Fehrenbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092510.g003", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mean_counts_per_unit_volume_and_area_mean_SD_by_group_and_cell_population_/972749", "title"=>"Mean counts per unit volume and area (mean + SD) by group and cell population.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-24 03:54:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1433343"], "description"=>"<p><i>Definition of abbreviations</i>: 3D  =  physical disector, 2D nucleus  =  counts of nuclear profiles, 2D cell  =  counts of cell profiles (with and without nucleus),  =  coefficient of error of the mean ratio estimate.</p>", "links"=>[], "tags"=>["anatomy", "histology", "Respiratory system", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "t cells", "Immune cells", "immunology", "Clinical immunology", "Pulmonology", "Chronic Obstructive Pulmonary Disease", "Histochemistry and cytochemistry techniques", "Immunohistochemistry techniques", "Immunohistochemical analysis", "Immunologic techniques", "ratios", "counting"], "article_id"=>972757, "categories"=>["Biological Sciences"], "users"=>["Vlad A. Bratu", "Veit J. Erpenbeck", "Antonia Fehrenbach", "Tanja Rausch", "Susanne Rittinghausen", "Norbert Krug", "Jens M. Hohlfeld", "Heinz Fehrenbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092510.t003", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_CD68_CD3_Cell_Ratios_by_Group_and_Counting_Design_/972757", "title"=>"CD68<sup>+</sup>/CD3<sup>+</sup> Cell Ratios by Group and Counting Design.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-24 03:54:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1433320"], "description"=>"<p>After exhaustive sectioning, every three sections were mounted on numbered glass slides (1 to 28 in this example). With a random outset between the 1<sup>st</sup> and the 9<sup>th</sup> slide, nine slide samples, each consisting of every 9<sup>th</sup> glass slide, were collected and stained.</p>", "links"=>[], "tags"=>["anatomy", "histology", "Respiratory system", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "t cells", "Immune cells", "immunology", "Clinical immunology", "Pulmonology", "Chronic Obstructive Pulmonary Disease", "Histochemistry and cytochemistry techniques", "Immunohistochemistry techniques", "Immunohistochemical analysis", "Immunologic techniques", "sur", "sampling", "sections"], "article_id"=>972742, "categories"=>["Biological Sciences"], "users"=>["Vlad A. Bratu", "Veit J. Erpenbeck", "Antonia Fehrenbach", "Tanja Rausch", "Susanne Rittinghausen", "Norbert Krug", "Jens M. Hohlfeld", "Heinz Fehrenbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092510.g001", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_SUR_sampling_of_the_sections_of_a_biopsy_/972742", "title"=>"Schematic SUR sampling of the sections of a biopsy.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-24 03:54:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1433342"], "description"=>"<p>Dashed line y = 0 represents the line of equality, which stands for perfect agreement. (a) Regression based mean difference (bias) and 95% limits of agreement for the differences of the CD68<sup>+</sup>/CD3<sup>+</sup> cell density ratios as determined by the 2D nucleus and 3D approaches in the non-smoker group. All values lie within the interval between the calculated 95% limits of agreement; (b) Regression based mean difference (bias) with 95% C.I. of the regression line (dotted) for the differences of the CD68<sup>+</sup>/CD3<sup>+</sup> cell density ratios in the smoker group. The 95% C.I. includes several horizontal lines (slope = 0) so that the fitted linear model does not achieve the desired statistical significance. Two large outliers encircled; (c) Regression based mean difference (bias) and 95% limits of agreement for the differences of the CD68<sup>+</sup>/CD3<sup>+</sup> cell density ratios as determined by the 2D nucleus and 3D approaches in the smoker group after removing the two large outliers. All values lie within the interval between the calculated 95% limits of agreement. Notice the similar slope to the fitted model in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092510#pone-0092510-g007\" target=\"_blank\">Figure 7a</a> (non-smoker group).</p>", "links"=>[], "tags"=>["anatomy", "histology", "Respiratory system", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "t cells", "Immune cells", "immunology", "Clinical immunology", "Pulmonology", "Chronic Obstructive Pulmonary Disease", "Histochemistry and cytochemistry techniques", "Immunohistochemistry techniques", "Immunohistochemical analysis", "Immunologic techniques", "noticed"], "article_id"=>972756, "categories"=>["Biological Sciences"], "users"=>["Vlad A. Bratu", "Veit J. Erpenbeck", "Antonia Fehrenbach", "Tanja Rausch", "Susanne Rittinghausen", "Norbert Krug", "Jens M. Hohlfeld", "Heinz Fehrenbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092510.g007", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_clear_correlation_between_the_difference_and_the_mean_magnitude_can_be_noticed_for_both_groups_/972756", "title"=>"A clear correlation between the difference and the mean magnitude can be noticed for both groups.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-24 03:54:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1433338"], "description"=>"<p>Mean CD68<sup>+</sup>/CD3<sup>+</sup> cell density ratios (mean ± SEM) for each design and study group.</p>", "links"=>[], "tags"=>["anatomy", "histology", "Respiratory system", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "t cells", "Immune cells", "immunology", "Clinical immunology", "Pulmonology", "Chronic Obstructive Pulmonary Disease", "Histochemistry and cytochemistry techniques", "Immunohistochemistry techniques", "Immunohistochemical analysis", "Immunologic techniques", "ratios"], "article_id"=>972752, "categories"=>["Biological Sciences"], "users"=>["Vlad A. Bratu", "Veit J. Erpenbeck", "Antonia Fehrenbach", "Tanja Rausch", "Susanne Rittinghausen", "Norbert Krug", "Jens M. Hohlfeld", "Heinz Fehrenbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092510.g005", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mean_CD68_CD3_cell_density_ratios_mean_177_SEM_for_each_design_and_study_group_/972752", "title"=>"Mean CD68<sup>+</sup>/CD3<sup>+</sup> cell density ratios (mean ± SEM) for each design and study group.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-24 03:54:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1433336"], "description"=>"<p>(a) T-lymphocytes, non-smokers, r = 0.84, <i>p</i> = 0.017; (b) T-lymphocytes, smokers, r = 0.96, <i>p</i><0.001; (c) macrophages, non-smokers, r<sub>nucleus</sub> = 0.95, <i>p</i> = 0.001; r<sub>cell</sub> = 0.76, <i>p</i> = 0.046; (d) macrophages, smokers, r<sub>nucleus</sub> = 0.98, <i>p</i><0.001; r<sub>cell</sub> = 0.89, <i>p</i> = 0.007</p>", "links"=>[], "tags"=>["anatomy", "histology", "Respiratory system", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "t cells", "Immune cells", "immunology", "Clinical immunology", "Pulmonology", "Chronic Obstructive Pulmonary Disease", "Histochemistry and cytochemistry techniques", "Immunohistochemistry techniques", "Immunohistochemical analysis", "Immunologic techniques", "profiles", "3d", "numerical"], "article_id"=>972750, "categories"=>["Biological Sciences"], "users"=>["Vlad A. Bratu", "Veit J. Erpenbeck", "Antonia Fehrenbach", "Tanja Rausch", "Susanne Rittinghausen", "Norbert Krug", "Jens M. Hohlfeld", "Heinz Fehrenbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092510.g004", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_2D_profiles_per_unit_area_versus_3D_numerical_density_/972750", "title"=>"2D profiles per unit area <i>versus</i> 3D numerical density.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-24 03:54:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1433333"], "description"=>"<p>Red triangles mark cell profiles seen in the reference section which are not present in the look-up section (bidirectional counting); green circles mark all cell profiles seen in the right section; yellow squares mark each assessed counting frame/field of view. The cell profile cutting the lower exclusion (red) line is not counted either in 3D or in 2D.</p>", "links"=>[], "tags"=>["anatomy", "histology", "Respiratory system", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "t cells", "Immune cells", "immunology", "Clinical immunology", "Pulmonology", "Chronic Obstructive Pulmonary Disease", "Histochemistry and cytochemistry techniques", "Immunohistochemistry techniques", "Immunohistochemical analysis", "Immunologic techniques", "disector", "counting", "look-up"], "article_id"=>972747, "categories"=>["Biological Sciences"], "users"=>["Vlad A. Bratu", "Veit J. Erpenbeck", "Antonia Fehrenbach", "Tanja Rausch", "Susanne Rittinghausen", "Norbert Krug", "Jens M. Hohlfeld", "Heinz Fehrenbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092510.g002", "stats"=>{"downloads"=>1, "page_views"=>22, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Physical_disector_3D_and_profile_counting_2D_within_a_consecutive_reference_and_look_up_section_/972747", "title"=>"Physical disector (3D) and profile counting (2D) within a consecutive reference and look-up section.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-24 03:54:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1433345"], "description"=>"<p>Subject Demographics.</p>", "links"=>[], "tags"=>["anatomy", "histology", "Respiratory system", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "t cells", "Immune cells", "immunology", "Clinical immunology", "Pulmonology", "Chronic Obstructive Pulmonary Disease", "Histochemistry and cytochemistry techniques", "Immunohistochemistry techniques", "Immunohistochemical analysis", "Immunologic techniques"], "article_id"=>972759, "categories"=>["Biological Sciences"], "users"=>["Vlad A. Bratu", "Veit J. Erpenbeck", "Antonia Fehrenbach", "Tanja Rausch", "Susanne Rittinghausen", "Norbert Krug", "Jens M. Hohlfeld", "Heinz Fehrenbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092510.t001", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Subject_Demographics_/972759", "title"=>"Subject Demographics.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-24 03:54:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1433344"], "description"=>"<p><i>Definition of abbreviations</i>: N<sub>V</sub>  =  numerical density, N<sub>A nucleus</sub>  =  nuclear profile per unit area, N<sub>A cell</sub>  =  cell profile per unit area,  =  coefficient of error of the mean estimate, N. A.  =  not analysed</p>", "links"=>[], "tags"=>["anatomy", "histology", "Respiratory system", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "t cells", "Immune cells", "immunology", "Clinical immunology", "Pulmonology", "Chronic Obstructive Pulmonary Disease", "Histochemistry and cytochemistry techniques", "Immunohistochemistry techniques", "Immunohistochemical analysis", "Immunologic techniques", "morphological"], "article_id"=>972758, "categories"=>["Biological Sciences"], "users"=>["Vlad A. Bratu", "Veit J. Erpenbeck", "Antonia Fehrenbach", "Tanja Rausch", "Susanne Rittinghausen", "Norbert Krug", "Jens M. Hohlfeld", "Heinz Fehrenbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092510.t002", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Quantitative_Morphological_Data_by_Group_and_Cell_Type_/972758", "title"=>"Quantitative Morphological Data by Group and Cell Type.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-24 03:54:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1433340"], "description"=>"<p>CD68<sup>+</sup>/CD3<sup>+</sup> cell density ratios estimated by the 2D (nucleus) and 3D design for the non-smoker, r = 0.97, p<0.001 (a) and smoker, r = 0.77, p<0.05 (b) group with the line of equality (y = x).</p>", "links"=>[], "tags"=>["anatomy", "histology", "Respiratory system", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "t cells", "Immune cells", "immunology", "Clinical immunology", "Pulmonology", "Chronic Obstructive Pulmonary Disease", "Histochemistry and cytochemistry techniques", "Immunohistochemistry techniques", "Immunohistochemical analysis", "Immunologic techniques", "ratios", "2d", "3d"], "article_id"=>972754, "categories"=>["Biological Sciences"], "users"=>["Vlad A. Bratu", "Veit J. Erpenbeck", "Antonia Fehrenbach", "Tanja Rausch", "Susanne Rittinghausen", "Norbert Krug", "Jens M. Hohlfeld", "Heinz Fehrenbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092510.g006", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_CD68_CD3_cell_density_ratios_estimated_by_the_2D_nucleus_and_3D_design_for_the_non_smoker_r_8202_8202_0_97_p_lt_0_001_a_and_smoker_r_8202_8202_0_77_p_lt_0_05_b_group_with_the_line_of_equality_y_8202_8202_x_/972754", "title"=>"CD68<sup>+</sup>/CD3<sup>+</sup> cell density ratios estimated by the 2D (nucleus) and 3D design for the non-smoker, r = 0.97, p<0.001 (a) and smoker, r = 0.77, p<0.05 (b) group with the line of equality (y = x).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-24 03:54:16"}

PMC Usage Stats | Further Information

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Relative Metric

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