Abstract P4-03-05: Wide-field optical coherence tomography (WF-OCT) for near real-time, point-of-care assessment of margin status in breast-conserving surgery specimens: Results of a feasibility study at a high-volume single-centre
Notice bibliographique
Résumé
Abstract Wide-Field Optical Coherence Tomography (WF-OCT) is a non-destructive, non-contact light imaging modality capable of label-free visualization of the internal microscopic architecture of breast tissue specimens. Its unique combination of high-resolution imaging in near real-time with tissue penetration depths approaching 2-mm makes it a promising imaging modality for obtaining detailed surgical margin status in breast-conserving surgery (BCS) specimens. A prototype WF-OCT imaging platform developed by Perimeter Medical Imaging, Inc. (Toronto, Canada) has permitted fully-automated, dynamically-focused visualization of margin widths around the intact surfaces of freshly excised BCS specimens. Herein are reported the results of a feasibility study at a high-volume single-centre evaluating the routine use of WF-OCT for sampling of surgical margin status in BCS specimens at the point-of-care. Methods: Women with biopsy confirmed breast cancer and scheduled for primary BCS were recruited at Princess Margaret Cancer Centre (Toronto, Canada). Standard medical care was not altered. Freshly excised BCS specimens including all lumpectomy samples were imaged by WF-OCT immediately prior to standard histological processing. The system acquired dynamically-focused, hemispherical coverage over two contra-lateral surfaces of the intact BCS specimen within the time constraints of the cold ischemic time window. High-resolution (10 μm) images of the tissue surface down to a 1 to 2-mm depth were obtained. Blinded assessments were performed on image data sets by two clinical readers (surgeon and radiologist) trained on a validated and unrelated data set correlating OCT images with histology slides. The readers were first asked to independently assess margin status using only blinded pre- and intra-operative knowledge (without OCT). Upon completion, the readers were provided OCT images of all scanned surface and similarly asked to assess the margin status with the additional OCT information. These assessments were subsequently evaluated by a breast pathologist comparing the OCT images and corresponding histopathology sections. The added utility of WF-OCT imaging information for margin prediction was studied. Results: [Pending study completion in August 2015]. Through accurate correlation with the histopathologic gold standard, OCT demonstrated capability to differentiate tissue microstructures, including: distinctive patterns for adipose tissue, fibrous stroma, breast lobules and ducts, cysts and microcysts, as well as in-situ and invasive carcinomas. Implications: The fully-automated WF-OCT imaging platform can integrate conveniently into standard pathological processing workflows to provide comprehensive sampling of surgical margin status in BCS specimens at the point-of-care. Clinical readers from surgical and radiological backgrounds can be trained to competently interpret WF-OCT images of BCS specimens for accurate prediction margin status. The implementation of WF-OCT at the point-of-care for routine surgical margin assessments will be further explored in future clinical trials. Citation Format: Valic MS, Leong WL, Done SJ, Wilson BC, Kulkarni S, McCready DR, Niu CJ, Atachia Y, Munro EA, Rempel D. Wide-field optical coherence tomography (WF-OCT) for near real-time, point-of-care assessment of margin status in breast-conserving surgery specimens: Results of a feasibility study at a high-volume single-centre. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-03-05.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».