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A novel approach for quantitative assessment of mucosal damage in inflammatory bowel disease.

Matalka II, Al-Omari FA, Salama RM, Mohtaseb AH - Diagn Pathol (2013)

Bottom Line: One of the main reliable histological features to suggest the diagnosis of inflammatory bowel disease is the presence of significant distortion of the crypt architecture indicating the chronic nature of the disease resulting in mucosal damage.This feature has a considerable intra-observer and inter-observer variability leading to significant subjectivity in colonic biopsy assessment.The developed system proved to be reliable, robust, and minimizes subjectivity and inter- and intra-observer variability.

View Article: PubMed Central - HTML - PubMed

Affiliation: Computer Engineering Department, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid 21163, Jordan. fomari@junet.edu.jo.

ABSTRACT

Aims: One of the main reliable histological features to suggest the diagnosis of inflammatory bowel disease is the presence of significant distortion of the crypt architecture indicating the chronic nature of the disease resulting in mucosal damage. This feature has a considerable intra-observer and inter-observer variability leading to significant subjectivity in colonic biopsy assessment. In this paper, we present a novel automated system to assess mucosal damage and architectural distortion in inflammatory bowel disease (IBD).

Methods: The proposed system relies on advanced image understating and processing techniques to segment digitally acquired images of microscopic biopsies, then, to extract key features to quantify the crypts irregularities in shape and distribution. These features were used as inputs to an artificial intelligent classifier that, after a training phase, can carry out the assessment automatically.

Results: The developed system was evaluated using 118 IBD biopsies. 116 out of 118 biopsies were correctly classified as compared to the consensus of three expert pathologists, achieving an overall precision of 98.31%.

Conclusions: An automated intelligent system to quantitatively assess inflammatory bowel disease was developed. The proposed system utilized advanced image understanding techniques together with an intelligent classifier to conduct the assessment. The developed system proved to be reliable, robust, and minimizes subjectivity and inter- and intra-observer variability.

Virtual slides: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1797721309305023.

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Acquired images representing IBD biopsies graded manually as (a) normal, (b) grade I, (c) grade II, and (d) grade III.
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Figure 1: Acquired images representing IBD biopsies graded manually as (a) normal, (b) grade I, (c) grade II, and (d) grade III.

Mentions: Microscopic digital colored images were captured for all 118 studied biopsies at the department of pathology, King Abdullah University Hospital (KAUH), Irbid, Jordan. Images were captured using DP20 camera set from Olympus™. DP20 is a 2 Megapixel color CCD digital microscope camera, with a resolution of 1600 × 1200 pixels, and pixel size of 4.2 μm × 4.2 μm. Images were captured at 10×, in an aim to capture the widest possible field from the tissue. The reasonably high resolution was used to obtain high quality images for processing in later stages of the assessment procedure. Furthermore, any illumination irregularities were compensated for by subtracting a background image from the captured image. The background image is captured for each slide under similar microscope setup options. Figure 1 illustrates four of the acquired images graded manually as Normal, Grade I IBD, Grade II, and Grade III, respectively.


A novel approach for quantitative assessment of mucosal damage in inflammatory bowel disease.

Matalka II, Al-Omari FA, Salama RM, Mohtaseb AH - Diagn Pathol (2013)

Acquired images representing IBD biopsies graded manually as (a) normal, (b) grade I, (c) grade II, and (d) grade III.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3852335&req=5

Figure 1: Acquired images representing IBD biopsies graded manually as (a) normal, (b) grade I, (c) grade II, and (d) grade III.
Mentions: Microscopic digital colored images were captured for all 118 studied biopsies at the department of pathology, King Abdullah University Hospital (KAUH), Irbid, Jordan. Images were captured using DP20 camera set from Olympus™. DP20 is a 2 Megapixel color CCD digital microscope camera, with a resolution of 1600 × 1200 pixels, and pixel size of 4.2 μm × 4.2 μm. Images were captured at 10×, in an aim to capture the widest possible field from the tissue. The reasonably high resolution was used to obtain high quality images for processing in later stages of the assessment procedure. Furthermore, any illumination irregularities were compensated for by subtracting a background image from the captured image. The background image is captured for each slide under similar microscope setup options. Figure 1 illustrates four of the acquired images graded manually as Normal, Grade I IBD, Grade II, and Grade III, respectively.

Bottom Line: One of the main reliable histological features to suggest the diagnosis of inflammatory bowel disease is the presence of significant distortion of the crypt architecture indicating the chronic nature of the disease resulting in mucosal damage.This feature has a considerable intra-observer and inter-observer variability leading to significant subjectivity in colonic biopsy assessment.The developed system proved to be reliable, robust, and minimizes subjectivity and inter- and intra-observer variability.

View Article: PubMed Central - HTML - PubMed

Affiliation: Computer Engineering Department, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid 21163, Jordan. fomari@junet.edu.jo.

ABSTRACT

Aims: One of the main reliable histological features to suggest the diagnosis of inflammatory bowel disease is the presence of significant distortion of the crypt architecture indicating the chronic nature of the disease resulting in mucosal damage. This feature has a considerable intra-observer and inter-observer variability leading to significant subjectivity in colonic biopsy assessment. In this paper, we present a novel automated system to assess mucosal damage and architectural distortion in inflammatory bowel disease (IBD).

Methods: The proposed system relies on advanced image understating and processing techniques to segment digitally acquired images of microscopic biopsies, then, to extract key features to quantify the crypts irregularities in shape and distribution. These features were used as inputs to an artificial intelligent classifier that, after a training phase, can carry out the assessment automatically.

Results: The developed system was evaluated using 118 IBD biopsies. 116 out of 118 biopsies were correctly classified as compared to the consensus of three expert pathologists, achieving an overall precision of 98.31%.

Conclusions: An automated intelligent system to quantitatively assess inflammatory bowel disease was developed. The proposed system utilized advanced image understanding techniques together with an intelligent classifier to conduct the assessment. The developed system proved to be reliable, robust, and minimizes subjectivity and inter- and intra-observer variability.

Virtual slides: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1797721309305023.

Show MeSH
Related in: MedlinePlus