Article ; Online: Elastic scattering spectroscopy for early detection of breast cancer: partially supervised Bayesian image classification of scanned sentinel lymph nodes.
2018 Volume 23, Issue 8, Page(s) 1–9
Abstract: Sentinel lymph node biopsy is a standard diagnosis procedure to determine whether breast cancer has spread to the lymph glands in the armpit (the axillary nodes). The metastatic status of the sentinel node (the first node in the axillary chain that ... ...
| Abstract | Sentinel lymph node biopsy is a standard diagnosis procedure to determine whether breast cancer has spread to the lymph glands in the armpit (the axillary nodes). The metastatic status of the sentinel node (the first node in the axillary chain that drains the affected breast) is the determining factor in surgery between conservative lumpectomy and more radical mastectomy including axillary node excision. The traditional assessment of the node requires sample preparation and pathologist interpretation. An automated elastic scattering spectroscopy (ESS) scanning device was constructed to take measurements from the entire cut surface of the excised sentinel node and to produce ESS images for cancer diagnosis. Here, we report on a partially supervised image classification scheme employing a Bayesian multivariate, finite mixture model with a Markov random field (MRF) spatial prior. A reduced dimensional space was applied to represent the scanning data of the node by a statistical image, in which normal, metastatic, and nonnodal-tissue pixels are identified. Our results show that our model enables rapid imaging of lymph nodes. It can be used to recognize nonnodal areas automatically at the same time as diagnosing sentinel node metastases with sensitivity and specificity of 85% and 94%, respectively. ESS images can help surgeons by providing a reliable and rapid intraoperative determination of sentinel nodal metastases in breast cancer. |
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| MeSH term(s) | Bayes Theorem ; Breast Neoplasms/diagnostic imaging ; Breast Neoplasms/pathology ; Early Detection of Cancer/methods ; Elasticity Imaging Techniques/methods ; Female ; Humans ; Image Interpretation, Computer-Assisted/methods ; Markov Chains ; Principal Component Analysis ; Sensitivity and Specificity ; Sentinel Lymph Node/diagnostic imaging ; Sentinel Lymph Node/pathology ; Spectrum Analysis/methods |
| Language | English |
| Publishing date | 2018-08-10 |
| Publishing country | United States |
| Document type | Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S. |
| ZDB-ID | 1309154-2 |
| ISSN | 1560-2281 ; 1083-3668 |
| ISSN (online) | 1560-2281 |
| ISSN | 1083-3668 |
| DOI | 10.1117/1.JBO.23.8.085004 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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