Value of high‐resolution full‐field optical coherence tomography and dynamic cell imaging for one‐stop rapid diagnosis breast clinic

Author:

Simon Alexis1,Badachi Yasmina1,Ropers Jacques2,Laurent Isaura2,Dong Lida3,Da Maia Elisabeth3,Bourcier Agnès4,Canlorbe Geoffroy456,Uzan Catherine456ORCID

Affiliation:

1. Department of Radiology, Pitié‐Salpêtrière Hospital Assistance Publique‐Hôpitaux de Paris (AP‐HP) Paris France

2. Clinical Research Unit, Pitié‐Salpêtrière Hospital Assistance Publique‐Hôpitaux de Paris (AP‐HP) Paris France

3. Department of Pathology, Pitié‐Salpêtrière Hospital Assistance Publique‐Hôpitaux de Paris (AP‐HP) Paris France

4. Department of Gynaecological and Breast Surgery and Oncology Assistance Publique des Hôpitaux de Paris (AP‐HP) Paris France

5. Centre de Recherche Saint‐Antoine (CRSA), INSERM UMR_S_938, Cancer Biology and Therapeutics Sorbonne University Paris France

6. Institut Universitaire de Cancérologie (IUC) Sorbonne University Paris France

Abstract

AbstractBackgroundFull‐field optical coherence tomography combined with dynamic cell imaging (D‐FFOCT) is a new, simple‐to‐use, nondestructive, quick technique that can provide sufficient spatial resolution to mimic histopathological analysis. The objective of this study was to evaluate diagnostic performance of D‐FFOCT for one‐stop rapid diagnosis breast clinic.MethodsDynamic full‐field optical coherence tomography was applied to fresh, untreated breast and nodes biopsies. Four different readers (senior and junior radiologist, surgeon, and pathologist) analyzed the samples without knowing final histological diagnosis or American College of Radiology classification. The results were compared to conventional processing and staining (hematoxylin–eosin).ResultsA total of 217 biopsies were performed on 152 patients. There were 144 breast biopsies and 61 lymph nodes with 101 infiltrative cancers (49.27%), 99 benign lesions (48.29%), 3 ductal in situ carcinoma (1.46%), and 2 atypias (0.98%). The diagnostic performance results were as follow: sensitivity: 77% [0.7;0.82], specificity: 64% [0.58;0.71], PPV: 74% [0.68;0.78], and NPV: 75% [0.72;0.78]. A large image atlas was created as well as a diagnosis algorithm from the readers' experience.ConclusionWith 74% PPV and 75% NPV, D‐FFOCT is not yet ready to be used in clinical practice to identify breast cancer. This is mainly explained by the lack of experience and knowledge of this new technic by the four lectors. By training with the diagnosis algorithm and the image atlas, radiologists could have better outcomes allowing quick detection of breast cancer and lymph node involvement. Deep learning could also be used, and further investigation will follow.

Publisher

Wiley

Subject

Cancer Research,Radiology, Nuclear Medicine and imaging,Oncology

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