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Quantitative analysis of myocardial tissue with digital autofluorescence microscopy.

Jensen T, Holten-Rossing H, Svendsen IM, Jacobsen C, Vainer B - J Pathol Inform (2016)

Bottom Line: This data may provide a basic histological starting point from which further digital analysis including staining may benefit.The presented method is amply described as a prestain multicomponent quantitation and outlining tool for histological sections of cardiac tissue.The main perspective is the opportunity for combination with digital analysis of stained microsections, for which the method may provide an accurate digital framework.

View Article: PubMed Central - PubMed

Affiliation: Department of Pathology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.

ABSTRACT

Background: The opportunity offered by whole slide scanners of automated histological analysis implies an ever increasing importance of digital pathology. To go beyond the importance of conventional pathology, however, digital pathology may need a basic histological starting point similar to that of hematoxylin and eosin staining in conventional pathology. This study presents an automated fluorescence-based microscopy approach providing highly detailed morphological data from unstained microsections. This data may provide a basic histological starting point from which further digital analysis including staining may benefit.

Methods: This study explores the inherent tissue fluorescence, also known as autofluorescence, as a mean to quantitate cardiac tissue components in histological microsections. Data acquisition using a commercially available whole slide scanner and an image-based quantitation algorithm are presented.

Results: It is shown that the autofluorescence intensity of unstained microsections at two different wavelengths is a suitable starting point for automated digital analysis of myocytes, fibrous tissue, lipofuscin, and the extracellular compartment. The output of the method is absolute quantitation along with accurate outlines of above-mentioned components. The digital quantitations are verified by comparison to point grid quantitations performed on the microsections after Van Gieson staining.

Conclusion: The presented method is amply described as a prestain multicomponent quantitation and outlining tool for histological sections of cardiac tissue. The main perspective is the opportunity for combination with digital analysis of stained microsections, for which the method may provide an accurate digital framework.

No MeSH data available.


Related in: MedlinePlus

Images of the same section demonstrating the analytical verification of the fibrous tissue quantitation. In (a-d), which are Van Gieson-stained, increasing areas of red are demarcated with red going from deep red to lighter nuances of red. In (e-h), which is the blue to red ratio, image pixels with the highest intensity are demarcated in (f) and decreasing intensities are included toward (h) with (h) representing the digital quantitation
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Figure 6: Images of the same section demonstrating the analytical verification of the fibrous tissue quantitation. In (a-d), which are Van Gieson-stained, increasing areas of red are demarcated with red going from deep red to lighter nuances of red. In (e-h), which is the blue to red ratio, image pixels with the highest intensity are demarcated in (f) and decreasing intensities are included toward (h) with (h) representing the digital quantitation

Mentions: As a further means to validate the digitally quantitated fibrous tissue and ECP, an analytical proof of concept is presented in Figures 6 and 7. In Figure 6, part of a VG-stained section is shown that includes strands of fibrous tissue. The red color corresponding to fibrous tissue is demarcated by including increasing intensities of the red spectrum using the RGB color threshold feature of ImageJ, where Figure 6d was set to fit the fibrous tissue as perceived by the author. Figure 6e-h show the same section of the blue-to-red ratio image, where pixels in Panels f-h are increasingly demarcated going from highest to lowest intensity with Panel h representing the digitally determined threshold. It is noted that deeper red in the VG staining corresponds to higher gray scale intensity of the ratio image. The area was chosen, as it includes solely fibrous tissue because myocytes in the VG-staining could not be digitally distinguished from fibrous tissue.


Quantitative analysis of myocardial tissue with digital autofluorescence microscopy.

Jensen T, Holten-Rossing H, Svendsen IM, Jacobsen C, Vainer B - J Pathol Inform (2016)

Images of the same section demonstrating the analytical verification of the fibrous tissue quantitation. In (a-d), which are Van Gieson-stained, increasing areas of red are demarcated with red going from deep red to lighter nuances of red. In (e-h), which is the blue to red ratio, image pixels with the highest intensity are demarcated in (f) and decreasing intensities are included toward (h) with (h) representing the digital quantitation
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4837794&req=5

Figure 6: Images of the same section demonstrating the analytical verification of the fibrous tissue quantitation. In (a-d), which are Van Gieson-stained, increasing areas of red are demarcated with red going from deep red to lighter nuances of red. In (e-h), which is the blue to red ratio, image pixels with the highest intensity are demarcated in (f) and decreasing intensities are included toward (h) with (h) representing the digital quantitation
Mentions: As a further means to validate the digitally quantitated fibrous tissue and ECP, an analytical proof of concept is presented in Figures 6 and 7. In Figure 6, part of a VG-stained section is shown that includes strands of fibrous tissue. The red color corresponding to fibrous tissue is demarcated by including increasing intensities of the red spectrum using the RGB color threshold feature of ImageJ, where Figure 6d was set to fit the fibrous tissue as perceived by the author. Figure 6e-h show the same section of the blue-to-red ratio image, where pixels in Panels f-h are increasingly demarcated going from highest to lowest intensity with Panel h representing the digitally determined threshold. It is noted that deeper red in the VG staining corresponds to higher gray scale intensity of the ratio image. The area was chosen, as it includes solely fibrous tissue because myocytes in the VG-staining could not be digitally distinguished from fibrous tissue.

Bottom Line: This data may provide a basic histological starting point from which further digital analysis including staining may benefit.The presented method is amply described as a prestain multicomponent quantitation and outlining tool for histological sections of cardiac tissue.The main perspective is the opportunity for combination with digital analysis of stained microsections, for which the method may provide an accurate digital framework.

View Article: PubMed Central - PubMed

Affiliation: Department of Pathology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.

ABSTRACT

Background: The opportunity offered by whole slide scanners of automated histological analysis implies an ever increasing importance of digital pathology. To go beyond the importance of conventional pathology, however, digital pathology may need a basic histological starting point similar to that of hematoxylin and eosin staining in conventional pathology. This study presents an automated fluorescence-based microscopy approach providing highly detailed morphological data from unstained microsections. This data may provide a basic histological starting point from which further digital analysis including staining may benefit.

Methods: This study explores the inherent tissue fluorescence, also known as autofluorescence, as a mean to quantitate cardiac tissue components in histological microsections. Data acquisition using a commercially available whole slide scanner and an image-based quantitation algorithm are presented.

Results: It is shown that the autofluorescence intensity of unstained microsections at two different wavelengths is a suitable starting point for automated digital analysis of myocytes, fibrous tissue, lipofuscin, and the extracellular compartment. The output of the method is absolute quantitation along with accurate outlines of above-mentioned components. The digital quantitations are verified by comparison to point grid quantitations performed on the microsections after Van Gieson staining.

Conclusion: The presented method is amply described as a prestain multicomponent quantitation and outlining tool for histological sections of cardiac tissue. The main perspective is the opportunity for combination with digital analysis of stained microsections, for which the method may provide an accurate digital framework.

No MeSH data available.


Related in: MedlinePlus