Utility of whole slide imaging and virtual microscopy in prostate pathology
Bibliographic record
Abstract
Whole slide imaging (WSI) has been used in conjunction with virtual microscopy (VM) for training or proficiency testing purposes, multicentre research, remote frozen section diagnosis and to seek specialist second opinion in a number of organ systems. The feasibility of using WSI/VM for routine surgical pathology reporting has also been explored. In this review, we discuss the utility and limitations of WSI/VM technology in the histological assessment of specimens from the prostate. Features of WSI/VM that are particularly well suited to assessment of prostate pathology include the ability to examine images at different magnifications as well as to view histology and immunohistochemistry side-by-side on the screen. Use of WSI/VM would also solve the difficulty in obtaining multiple identical copies of small lesions in prostate biopsies for teaching and proficiency testing. It would also permit annotation of the virtual slides, and has been used in a study of inter-observer variation of Gleason grading to facilitate precise identification of the foci on which grading decisions had been based. However, the large number of sections examined from each set of prostate biopsies would greatly increase time required for scanning as well as the size of the digital file, and would also be an issue if digital archiving of prostate biopsies is contemplated. Z-scanning of glass slides, a process that increases scanning time and file size would be required to permit focusing a virtual slide up and down to assess subtle nuclear features such as nucleolar prominence. The common use of large blocks to process prostatectomy specimens would also be an issue, as few currently available scanners can scan such blocks. A major component of proficiency testing of prostate biopsy assessment involves screening of the cores to detect small atypical foci. However, screening virtual slides of wavy fragmented prostate cores using a computer mouse aided by an overview image is very different from screening glass slides using a microscope stage. Hence, it may be more appropriate in this setting to mark the lesional area and focus only on the interpretation component of competency testing. Other issues limiting the use of digital pathology in prostate pathology include the cost of high quality slide scanners for WSI and high resolution monitors for VM as well as the requirement for fast Internet connection as even a subtle delay in presentation of images on the screen may be very disturbing for a pathologist used to the rapid viewing of glass slides under a microscope. However, these problems are likely to be overcome by technological advances in the future.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".