Comparative Assessment of Digital Pathology Systems for Primary Diagnosis

Abstract

Background: Despite increasing interest in whole-slide imaging (WSI) over optical microscopy (OM), limited information on comparative assessment of various digital pathology systems (DPSs) is available. Materials and Methods: A comprehensive evaluation was undertaken to investigate the technical performance–assessment and diagnostic accuracy of four DPSs with an objective to establish the noninferiority of WSI over OM and find out the best possible DPS for clinical workflow. Results: A total of 2376 digital images, 15,775 image reads (OM - 3171 + WSI - 12,404), and 6100 diagnostic reads (OM - 1245, WSI - 4855) were generated across four DPSs (coded as DPS: 1, 2, 3, and 4) using a total 240 cases (604 slides). Onsite technical evaluation revealed successful scan rate: DPS3 < DPS2 < DPS4 < DPS1; mean scanning time: DPS4 < DPS1 < DPS2 < DPS3; and average storage space: DPS3 < DPS2 < DPS1 < DPS4. Overall diagnostic accuracy, when compared with the reference standard for OM and WSI, was 95.44% (including 2.48% minor and 2.08% major discordances) and 93.32% (including 4.28% minor and 2.4% major discordances), respectively. The difference between the clinically significant discordances by WSI versus OM was 0.32%. Major discordances were observed mostly using DPS4 and least in DPS1; however, the difference was statistically insignificant. Almost perfect (κ ≥ 0.8)/substantial (κ = 0.6–0.8) inter/intra-observer agreement between WSI and OM was observed for all specimen types, except cytology. Overall image quality was best for DPS1 followed by DPS4. Mean digital artifact rate was 6.8% (163/2376 digital images) and maximum artifacts were noted in DPS2 ( n = 77) followed by DPS3 ( n = 36). Most pathologists preferred viewing software of DPS1 and DPS2. Conclusion: WSI was noninferior to OM for all specimen types, except for cytology. Each DPS has its own pros and cons; however, DPS1 closely emulated the real-world clinical environment. This evaluation is intended to provide a roadmap to pathologists for the selection of the appropriate DPSs while adopting WSI.

Validation of a Portable Whole-Slide Imaging System for Frozen Section Diagnosis

“…Recently published guidelines advocate robust validation of WSI platforms for each application before adoption into clinical practice. [ 5 10 11 ] Increased interest in the use of DP for FS diagnosis was observed recently. However, its actual use for routine FS practice is still very limited.…”

“…All participating pathologists had previous experience in evaluating digital images and were involved in validation of WSI for primary diagnosis in surgical pathology at our institute. [ 4 5 ]…”

“…Evolving technological advancements and regulatory approval for various TP systems have paved the way for digital pathology (DP) to move from research and education to routine diagnostic workflow. [ 1 2 3 4 5 ] One of the most promising applications of TP is intra-operative consultation, i e., frozen section (FS) diagnosis. This facility enables remote sites lacking direct pathologist support/specialist pathologist to obtain expert consultation intraoperatively, thereby reducing costs, preventing medical errors, and improving quality.…”

Deep learning accelerates whole slide imaging for next-generation digital pathology applications

“…It is undeniable that the next Machine Learning (ML) revolution in histopathology will be fueled by large-scale annotated databases. However, one of the biggest culprits is the current speed and throughput of digital pathology scanners 4 . Scanning each histology slide (using e.g., 40×/0.75NA objective lens) often yields Gigapixel-worth of information.…”

“…Scanning each histology slide (using e.g., 40×/0.75NA objective lens) often yields Gigapixel-worth of information. While hardware and software advances in recent years resulted in a speed-up of the scanning time 2 , 4 , it is still a rate-limiting step that adds a burden on innovation in the field, as the price of these high-throughput scanners is in the range of ~$150–300 K, making the scanner a “unicorn” in many deployment scenarios, as purchasing multiple scanners becomes highly costly.…”