The Use of Optical Coherence Tomography for Gross Examination and Sampling of Fixed Breast Specimens: A Pilot Study

Thorough gross examination of breast cancer specimens is critical in order to sample relevant portions for subsequent microscopic examination. This task would benefit from an imaging tool which permits targeted and accurate block selection. Optical coherence tomography (OCT) is a non-destructive imaging technique that visualizes tissue architecture and has the potential to be an adjunct at the gross bench. Our objectives were: (1) to familiarize pathologists with the appearance of breast tissue entities on OCT; and (2) to evaluate the yield and quality of OCT images of unprocessed, formalin-fixed breast specimens for the purpose of learning and establishment of an OCT–histopathology library. Methods: Firstly, 175 samples from 40 formalin-fixed, unprocessed breast specimens with residual tissue after final diagnosis were imaged with OCT and then processed into histology slides. Histology findings were correlated with features on OCT. Results: Residual malignancy was seen in 30% of tissue samples. Corresponding OCT images demonstrated that tumor can be differentiated from fibrous stroma, based on features such as irregular boundary, heterogeneous texture and reduced penetration depth. Ductal carcinoma in situ can be subtle, and it is made more recognizable by the presence of comedo necrosis and calcifications. OCT features of benign and malignant breast entities were compiled in a granular but user-friendly reference tool. Conclusion: OCT images of fixed breast tissue were of sufficient quality to reproduce features of breast entities previously described in fresh tissue specimens. Our findings support the use of readily available unprocessed, fixed breast specimens for the establishment of an OCT–histopathology library

Assessing the Impact of Color Normalization in Convolutional Neural Network-Based Nuclei Segmentation Frameworks

Image analysis tools for cancer, such as automatic nuclei segmentation, are impacted by the inherent variation contained in pathology image data. Convolutional neural networks (CNN), demonstrate success in generalizing to variable data, illustrating great potential as a solution to the problem of data variability. In some CNN-based segmentation works for digital pathology, authors apply color normalization (CN) to reduce color variability of data as a preprocessing step prior to prediction, while others do not. Both approaches achieve reasonable performance and yet, the reasoning for utilizing this step has not been justified. It is therefore important to evaluate the necessity and impact of CN for deep learning frameworks, and its effect on downstream processes. In this paper, we evaluate the effect of popular CN methods on CNN-based nuclei segmentation frameworks. </p

Breast intraductal papillomas without atypia in radiologic-pathologic concordant core-needle biopsies: Rate of upgrade to carcinoma at excision.

BACKGROUND: The surgical management of mammary intraductal papilloma without atypia (IDP) identified at core-needle biopsy (CNB) is controversial. This study assessed the rate of upgrade to carcinoma at surgical excision (EXC). METHODS: This study identified women with a CNB diagnosis of intraductal papilloma without atypia or carcinoma at a cancer center between 2003 and 2013. Radiologic-pathologic concordance was assessed for all cases, and discordant cases were excluded. The radiologic and clinicopathologic features of patients with a CNB diagnosis of IDP were correlated with an upgrade to carcinoma at EXC. RESULTS: The study population consists of 189 women with 196 IDPs; 166 women (171 IDPs) underwent EXC. The upgrade rate was 2.3% (4 of 171). The upgraded lesions were 2 invasive lobular carcinomas and 2 cases of ductal carcinoma in situ (DCIS). One case of DCIS involved the residual IDP, whereas the other 3 carcinomas were ≥ 8 mm away. Twenty-four women (25 IDPs) did not undergo EXC and had stable imaging on follow-up (median, 23.5 months). CONCLUSIONS: The upgrade rate at EXC for IDPs diagnosed at CNB with radiologic-pathologic concordance was 2.3%. These findings suggest that observation is appropriate for patients with radiologic-pathologic concordant CNB yielding IDP, regardless of its size. Cancer 2016. © 2016 American Cancer Society. Cancer 2016;122:2819-2827. © 2016 American Cancer Society