A Digital Pathology Solution to Resolve the Tissue Floater Conundrum.
Context.--Pathologists may encounter extraneous pieces of tissue (tissue floaters) on glass slides because of specimen cross-contamination. Troubleshooting this problem, including performing molecular tests for tissue identification if available, is time consuming and often does not satisfactorily r...
| Publicado en: | Archives of Pathology & Laboratory Medicine Vol. 145; no. 3; pp. 359 - 365 |
|---|---|
| Autores principales: | , , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
College of American Pathologists
Mar2021
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=149134150&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 149134150 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00039985 1FS jtl: Archives of Pathology & Laboratory Medicine issn: 00039985 maglogo: N pubinfo: dt: Mar2021 vid: 145 iid: 3 pid: 2550 pub: College of American Pathologists place: Northfield, Illinois artinfo: ui: 149134150 149134150 149134150 10.5858/arpa.2020-0034-OA 149134150 ppf: 359 ppct: 6 formats: fmt: @attributes: type: P tig: atl: A Digital Pathology Solution to Resolve the Tissue Floater Conundrum. aug: au: Pantanowitz, Liron Michelow, Pamela Hazelhurst, Scott Kalra, Shivam Choi, Charles Shah, Sultaan Babaie, Morteza Tizhoosh, Hamid R. affil: Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania sug: subj: Pathology, Clinical Equipment and Supplies Specimen Handling Methods Digital Technology Utilization Human Molecular Diagnostic Techniques Staining and Labeling Methods Technology, Medical Deep Learning Equipment Contamination Databases Image Retrieval ab: Context.--Pathologists may encounter extraneous pieces of tissue (tissue floaters) on glass slides because of specimen cross-contamination. Troubleshooting this problem, including performing molecular tests for tissue identification if available, is time consuming and often does not satisfactorily resolve the problem. Objective.--To demonstrate the feasibility of using an image search tool to resolve the tissue floater conundrum. Design.--A glass slide was produced containing 2 separate hematoxylin and eosin (H&E)-stained tissue floaters. This fabricated slide was digitized along with the 2 slides containing the original tumors used to create these floaters. These slides were then embedded into a dataset of 2325 whole slide images comprising a wide variety of H&E stained diagnostic entities. Digital slides were broken up into patches and the patch features converted into barcodes for indexing and easy retrieval. A deep learning-based image search tool was employed to extract features from patches via barcodes, hence enabling image matching to each tissue floater. Results.--There was a very high likelihood of finding a correct tumor match for the queried tissue floater when searching the digital database. Search results repeatedly yielded a correct match within the top 3 retrieved images. The retrieval accuracy improved when greater proportions of the floater were selected. The time to run a search was completed within several milliseconds. Conclusions.--Using an image search tool offers pathologists an additional method to rapidly resolve the tissue floater conundrum, especially for those laboratories that have transitioned to going fully digital for primary diagnosis. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|