A Pilot Validation Study Comparing FIBI, a Slide-Free Imaging Method, with Standard FFPE H&E Tissue Section Histology for Primary Surgical Pathology Diagnosis
Notice bibliographique
Résumé
Abstract Introduction Digital pathology whole slide images (WSI) have been recently approved by the FDA for primary diagnosis in clinical surgical pathology practices. These WSI are generated by digitally scanning standard formalin-fixed and paraffin-embedded (FFPE) H&E-stained tissue sections mounted on glass microscope slides. Novel imaging methods are being developed that can capture the surface of tissue without requiring prior fixation, paraffin embedding, or tissue sectioning. One of these methods, FIBI (Fluorescence Imitating Brightfield Imaging), an optically simple and low-cost technique, was developed by our team and used in this study. Methods 100 de-identified surgical pathology samples were obtained from the UC Davis Health Pathology Laboratory. Samples were first digitally imaged by FIBI, and then embedded in paraffin, sectioned at 4 µm, mounted on glass slides, H&E stained, and scanned using the Aperio/Leica AT2 scanner. The resulting digital images from both FIBI and H&E scan sets were uploaded to PathPresenter and viewed in random order and modality (FIBI or H&E) by each of 4 reading pathologists. After a 30-day washout, the same 100 cases, in random order, were presented in the alternate modality to what was first shown, to the same 4 reading pathologists. The data set consisted, therefore, of 100 reference diagnoses and 800 study pathologist reads (400 FIBI and 400 H&E). Each study read was compared to the reference diagnosis for that case, and also compared to that reader’s diagnosis across both modalities for each case. Categories of concordance, minor and major discordance were adjudicated by the study team based on established criteria. Results The combined category, concordance or minor discordance, was scored as “no major discordance.” The overall agreement rate (compared to the reference diagnosis), across 800 reads, was 97.9%. This consisted of 400 FIBI reads at 97.0% vs. reference and 400 H&E reads vs. reference at 98.8%. Minor discordances (defined as alternative diagnoses without clinical treatment or outcome implications) were 6.1% overall, 7.2% for FIBI and 5.0% for HE. Conclusions Pathologists without specific experience or training in FIBI imaging interpretation can provide accurate diagnosis from FIBI slide-free images. Concordance/discordance rates are similar to published rates for comparisons of WSI to standard light microscopy of glass slides for primary diagnosis that led to FDA approval. The present study was more limited in scope but suggests that a follow-on formal clinical trial is feasible. It may be possible, therefore, to develop a slide-free, non-destructive approach for primary pathology diagnosis. Such a method promises improved speed, reduced cost, and better conservation of tissue for advanced ancillary studies.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,023 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».