Whole slide imaging equivalency and efficiency study: experience at a large academic center.


Journal

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
ISSN: 1530-0285
Titre abrégé: Mod Pathol
Pays: United States
ID NLM: 8806605

Informations de publication

Date de publication:
07 2019
Historique:
received: 20 10 2018
accepted: 14 12 2018
revised: 13 12 2018
pubmed: 20 2 2019
medline: 1 5 2020
entrez: 20 2 2019
Statut: ppublish

Résumé

Whole slide imaging is Food and Drug Administration-approved for primary diagnosis in the United States of America; however, relatively few pathology departments in the country have fully implemented an enterprise wide digital pathology system enabled for primary diagnosis. Digital pathology has significant potential to transform pathology practice with several published studies documenting some level of diagnostic equivalence between digital and conventional systems. However, whole slide imaging also has significant potential to disrupt pathology practice, due to the differences in efficiency of manipulating digital images vis-à-vis glass slides, and studies on the efficiency of actual digital pathology workload are lacking. Our randomized, equivalency and efficiency study aimed to replicate clinical workflow, comparing conventional microscopy to a complete digital pathology signout using whole slide images, evaluating the equivalency and efficiency of glass slide to whole slide image reporting, reflective of true pathology practice workloads in the clinical setting. All glass slides representing an entire day's routine clinical signout workload for six different anatomic pathology subspecialties at Memorial Sloan Kettering Cancer Center were scanned on Leica Aperio AT2 at ×40 (0.25 µm/pixel). Integration of whole slide images for each accessioned case is through an interface between the Leica eSlide manager database and the laboratory information system, Cerner CoPathPlus. Pathologists utilized a standard institution computer workstation and viewed whole slide images through an internally developed, vendor agnostic whole slide image viewer, named the "MSK Slide Viewer". Subspecialized pathologists first reported on glass slides from surgical pathology cases using routine clinical workflow. Glass slides were de-identified, scanned, and re-accessioned in the laboratory information system test environment. After a washout period of 13 weeks, pathologists reported the same clinical workload using whole slide image integrated within the laboratory information system. Intraobserver equivalency metrics included top-line diagnosis, margin status, lymphovascular and/or perineural invasion, pathology stage, and the need to order ancillary testing (i.e., recuts, immunohistochemistry). Turnaround time (efficiency) evaluation was defined by the start of each case when opened in the laboratory information system and when the case was completed for that day (i.e., case sent to signout queue or pending ancillary studies). Eight pathologists participated from the following subspecialties: bone and soft tissue, genitourinary, gastrointestinal, breast, gynecologic, and dermatopathology. Glass slides signouts comprised of 204 cases, encompassing 2091 glass slides; and digital signouts comprised of 199 cases, encompassing 2073 whole slide images. The median whole slide image file size was 1.54 GB; scan time/slide, 6 min 24 s; and scan area 32.1 × 18.52 mm. Overall diagnostic equivalency (e.g., top-line diagnosis) was 99.3% between digital and glass slide signout; however, signout using whole slide images showed a median overall 19% decrease in efficiency per case. No significant difference by reader, subspecialty, or specimen type was identified. Our experience is the most comprehensive study to date and shows high intraobserver whole slide image to glass slide equivalence in reporting of true clinical workflows and workloads. Efficiency needs to improve for digital pathology to gain more traction among pathologists.

Identifiants

pubmed: 30778169
doi: 10.1038/s41379-019-0205-0
pii: S0893-3952(22)01041-9
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

916-928

Auteurs

Matthew G Hanna (MG)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.

Victor E Reuter (VE)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.
Warren Alpert Center for Digital and Computational Pathology, New York, NY, USA.

Meera R Hameed (MR)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.
Warren Alpert Center for Digital and Computational Pathology, New York, NY, USA.

Lee K Tan (LK)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.

Sarah Chiang (S)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.

Carlie Sigel (C)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.

Travis Hollmann (T)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.

Dilip Giri (D)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.

Jennifer Samboy (J)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.
Warren Alpert Center for Digital and Computational Pathology, New York, NY, USA.

Carlos Moradel (C)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.

Andrea Rosado (A)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.

John R Otilano (JR)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.

Christine England (C)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.

Lorraine Corsale (L)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.

Evangelos Stamelos (E)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.

Yukako Yagi (Y)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.
Warren Alpert Center for Digital and Computational Pathology, New York, NY, USA.

Peter J Schüffler (PJ)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.
Warren Alpert Center for Digital and Computational Pathology, New York, NY, USA.

Thomas Fuchs (T)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.
Warren Alpert Center for Digital and Computational Pathology, New York, NY, USA.

David S Klimstra (DS)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA.
Warren Alpert Center for Digital and Computational Pathology, New York, NY, USA.

S Joseph Sirintrapun (SJ)

Department of Pathology, Memorial Sloan Kettering, New York, NY, USA. sirintrs@mskcc.org.
Warren Alpert Center for Digital and Computational Pathology, New York, NY, USA. sirintrs@mskcc.org.

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