Digital Versus Optical Diagnosis of Follicular Patterned Thyroid Lesions

Abstract

Objectives To study the concordance between pathologists in the diagnosis of follicular patterned thyroid lesions using both digital and conventional optical settings. Material and Methods Five pathologists reviewed 50 hematoxylin and eosin-stained slides of follicular patterned thyroid lesions using both digital (the D-Sight 2.0 scanner and navigator viewer) and conventional optical instruments with washout interval time. ResultsThe mean concordance rate with the ground truth (GT) was similar between conventional optical and digital observation (83.2 and 85.2%, respectively). The most frequent reason for diagnostic discordance with GT on both systems was the evaluation of nuclear features (69.1% for conventional optical observation and 59.4% for digital observation). The intraobserver diagnostic concordance mean was 86.8%. Time for digital observation (mean time per case = 2.9 ± 0.8 min) was higher than that for conventional optical observation (mean time per case = 2.0 ± 0.7 min). Interobserver correlation of measurements was higher in the digital observation than the conventional optical observation. Conclusion Conventional optical and digital observation settings showed a comparable accuracy for the diagnosis of follicular patterned thyroid nodules, as well as substantial intraobserver agreement and a significant improvement in the reproducibility of the measurements that support the use of digital diagnosis in thyroid pathology. The origins underlying the variability of the diagnosis were the same in both conventional optical microscopy and digital pathology systems.

Current Developments of Artificial Intelligence in Digital Pathology and Its Future Clinical Applications in Gastrointestinal Cancers

“…This digital process is termed “digital pathology” and has additional benefits compared to traditional pathology, including the ease of quickly and securely sharing pathology WSIs worldwide with other pathologists for second opinions, as well as providing a better view of the tissue with additional annotation and measurement tools while allowing for rapid access to archived cases without loss of quality [ 44 ]. Previous literature reports support the safe transition to digital pathology, showing high concordance of diagnosis using digital pathology with WSIs as compared to traditional slides with light microscopy [ 45 , 46 , 47 , 48 , 49 ]. The quality of WSIs is a major factor that affects concordance rates and diagnostic accuracy.…”

Revisiting the utility of identifying nuclear grooves as unique nuclear changes by an object detector model

“…While nuclear grooves are typically visualized in most PTC cytology MGG-stained slides, this staining method primarily highlights cytoplasmic detail, potentially compromising the visualization of nuclear structures [24][25][26]. Furthermore, considering that the evaluation of nuclear structures constitutes an important cause of diagnostic disagreement between optical and digital observation of cytology, the annotations may not have been the most representative [48].…”

Role of artificial intelligence in digital pathology for gynecological cancers

“…Digital slides are easier to preserve, share and annotate, and facilitate remote diagnosis or educational purposes [23] . The automation and efficiency afforded by digital pathology can enhance productivity and cost-efficiency [26] , with its performance having demonstrated superiority over conventional microscopy [28] , [29] . Recently, the Food and Drug Administration (FDA) has approved the use of digital pathology for primary diagnosis [30] .…”