Evaluation of whole slide image immunohistochemistry interpretation in challenging prostate needle biopsies.
Whole slide images (WSIs), also known as virtual slides, can support electronic distribution of immunohistochemistry (IHC) stains to pathologists that rely on remote sites for these services. This may lead to improvement in turnaround times, reduction of courier costs, fewer errors in slide distribution, and automated image analyses. Although this approach is practiced de facto today in some large laboratories, there are no clinical validation studies on this approach. Our retrospective study evaluated the interpretation of IHC stains performed in difficult prostate biopsies using WSIs. The study included 30 foci with IHC stains identified by the original pathologist as both difficult and pivotal to the final diagnosis. WSIs were created from the glass slides using a scanning robot (T2, Aperio Technologies, Vista, CA). An evaluation form was designed to capture data in 2 phases: (1) interpretation of WSIs and (2) interpretation of glass slides. Data included stain interpretations, diagnoses, and other parameters such as time required to diagnose and image/slide quality. Data were also collected from an expert prostate pathologist, consensus meetings, and a poststudy focus group. WSI diagnostic validity (intraobserver pairwise kappa statistics) was "almost perfect" for 1 pathologist, "substantial" for 3 pathologists, and "moderate" for 1 pathologist. Diagnostic agreement between the final/consensus diagnoses of the group and those of the domain expert was "almost perfect" (kappa = 0.817). Except for one instance, WSI technology was not felt to be the cause of disagreements. These results are encouraging and compare favorably with other efforts to quantify diagnostic variability in surgical pathology. With thorough training, careful validation of specific applications, and regular postsignout review of glass IHC slides (eg, quality assurance review), WSI technology can be used for IHC stain interpretation.
Fine
Jeffrey L
JL
Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA. finejl@upmc.edu
Grzybicki
Dana M
DM
Silowash
Russell
R
Ho
Jonhan
J
Gilbertson
John R
JR
Anthony
Leslie
L
Wilson
Robb
R
Parwani
Anil V
AV
Bastacky
Sheldon I
SI
Epstein
Jonathan I
JI
Jukic
Drazen M
DM
D000230:Adenocarcinoma / Q000175:diagnosis / Q000473:pathology*; D001707:Biopsy, Needle; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007150:Immunohistochemistry; D008297:Male; D011471:Prostatic Neoplasms / Q000175:diagnosis / Q000473:pathology*; D012984:Software