Computer-assisted image analysis of amyloid deposits in abdominal fat pad aspiration biopsies
dc.contributor.author | Bardarov, Svetoslav | en_US |
dc.contributor.author | Michael, Claire W. | en_US |
dc.contributor.author | Pu, Robert T. | en_US |
dc.contributor.author | Pang, Yijun | en_US |
dc.date.accessioned | 2009-01-07T15:30:42Z | |
dc.date.available | 2010-03-01T21:10:28Z | en_US |
dc.date.issued | 2009-01 | en_US |
dc.identifier.citation | Bardarov, Svetoslav; Michael, Claire W.; Pu, Robert T.; Pang, Yijun (2009). "Computer-assisted image analysis of amyloid deposits in abdominal fat pad aspiration biopsies." Diagnostic Cytopathology 37(1): 30-35. <http://hdl.handle.net/2027.42/61453> | en_US |
dc.identifier.issn | 8755-1039 | en_US |
dc.identifier.issn | 1097-0339 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/61453 | |
dc.identifier.uri | http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=18973119&dopt=citation | en_US |
dc.description.abstract | Amyloidosis is a heterogeneous group of diseases with a common outcome: deposition of insoluble protein in the visceral organs and tissues. Primary amyloidosis is a consequence of different plasma cell disorders, and it is the most common form of amyloidosis in the United States with an estimated 2,000 new cases annually. Other forms of amyloidosis include chronic inflammatory processes, familial type of amyloidosis, and localized forms like Alzheimer's disease. The diagnosis of amyloidosis is based on the clinical picture and demonstration of amyloid deposit in tissues with Congo-red stain. In our article, we describe a simple methodology for image analysis of fat pad biopsies for amyloidosis using a commercially available software Adobe Photoshop CS3© Extended Edition. The principle is based on calculation of the mean gray value of each blue and green channel and comparison of their ratios. As a negative control, we have used samples from heart, scar tissue, and skin with their representative control. Fibrous tissue often gives a white:blue to blue:green birefringence, which often is confused with the apple: green birefringence of the amyloid stain; however, we were successful in discriminating these colors using the methodology described in this article. We also analyzed 22 patients with at least 2 years follow-up in our institution. The specificity and the sensitivity of the computer-assisted image analysis were calculated to be 75% and 100%, respectively. These results are in agreement with the published papers (references here); however, caution should be exercised before drawing firm conclusions because of the small sample size presented here. Diagn. Cytopathol. 2009. © 2008 Wiley-Liss, Inc. | en_US |
dc.format.extent | 159870 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.publisher | Wiley Subscription Services, Inc., A Wiley Company | en_US |
dc.subject.other | Life and Medical Sciences | en_US |
dc.subject.other | Cancer Research, Oncology and Pathology | en_US |
dc.title | Computer-assisted image analysis of amyloid deposits in abdominal fat pad aspiration biopsies | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Pathology | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Cytopathology, University of Michigan, Ann Arbor, Michigan | en_US |
dc.contributor.affiliationum | Department of Cytopathology, University of Michigan, Ann Arbor, Michigan | en_US |
dc.contributor.affiliationum | Department of Cytopathology, University of Michigan, Ann Arbor, Michigan | en_US |
dc.contributor.affiliationum | Department of Cytopathology, University of Michigan, Ann Arbor, Michigan ; Department of Pathology, 1500 East Medical Drive, Ann Arbor, MI 48109 | en_US |
dc.identifier.pmid | 18973119 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/61453/1/20948_ftp.pdf | |
dc.identifier.doi | http://dx.doi.org/10.1002/dc.20948 | en_US |
dc.identifier.source | Diagnostic Cytopathology | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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