Use of whole slide imaging in surgical pathology quality assurance: design and pilot validation studies☆☆☆
Received 3 September 2005; received in revised form 7 November 2005; accepted 9 November 2005. published online 27 January 2006.
Summary
By imaging large numbers of slides automatically at high resolution, modern automated whole slide imaging (WSI) systems have the potential to become useful tools in pathology practice. This article describes a pilot validation study for use of automated high-speed WSI systems for surgical pathology quality assurance (QA).
This was a retrospective comparative study in which 24 full genitourinary cases (including 47 surgical parts and 391 slides) were independently reviewed with traditional microscopy and whole slide digital images. Approximately half the cases had neoplasia in the diagnostic line. At the end of the study, diagnostic discrepancies were evaluated by a pathology consensus committee.
The study pathologists felt that the traditional and WSI methods were comparable for case review. They reported no difference in perceived case complexity or diagnostic confidence between the methods. There were 4 clinically insignificant discrepancies with the signed-out cases: 2 from glass slide and 2 with WSI review. Of the 2 discrepancies reported by the WSI method, the committee agreed with the reviewer once and the original report once.
At the end of the study, the participants agreed that automated WSI is a viable potential modality for surgical pathology QA, especially in multifacility health systems that would like to establish interfacility QA. The participants felt that major issues limiting the implementation of WSI-based QA did not involve image acquisition or quality but rather image management issues such as the pathologist's interface, the hospital's network, and integration with the laboratory information system.
aCenter for Pathology Informatics, Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA 15232, USA
bDepartment of Pathology, University of Pittsburgh School of Medicine, UPMC Presbyterian/Shadyside, Pittsburgh, PA 15232, USA
cDepartment of Dermatology, University of Pittsburgh School of Medicine, UPMC Presbyterian/Shadyside, Pittsburgh, PA 15232, USA
dCenter for Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15261, USA
eCenter for Oncology Informatics, Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA 15232, USA
Corresponding author. Centers for Pathology and Oncology Informatics, University of Pittsburgh Medical Center, Pittsburgh, PA 15232, USA.
☆ This work was supported by funding from the US Air Force administered by the US Army Medical Research Acquisition Activity, Fort Detrick, Md, Contract No. DAMD17-03-2-0017. The content of the information does not necessarily reflect the position or policy of the US government, and no official endorsement should be inferred.
☆☆ The University of Pittsburgh Investigational Review Board reviewed this research, No. 0412088, and approved it as exempt from Federal Policy for the Protection of Human Research Subjects.
ABSTRACT