Breast cancer detection using infrared spectral pathology from H&E stained tissue on glass slides
Breast cancer detection using infrared spectral pathology from H&E stained tissue on glass slides
复制标题
使用 H 的红外光谱病理学检测乳腺癌
DOI:
10.1016/j.clispe.2021.100008
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发表时间:
2021
期刊:
影响因子:
--
通讯作者:
Tang J
中科院分区:
文献类型:
--
作者:
Tang J
Infrared spectral pathology has gained significant attention in the last few years, since it has been demonstrated to be able to readily identify cancerous tissue in biopsy samples. The Infrared technique, however, normally requires tissue sections to be mounted on infrared transparent slides. Unfortunately, these slides are both expensive and particularly frangible. In addition, mounting samples on specialist slides is an additional step in the sample preparation workflow, which ideally should be avoided. Applying infrared imaging directly to the H&E stained tissue on the glass slides that are normally used by pathologists, could help the infrared imaging technique be incorporated into current cancer diagnosis work flow and lower the total cost of detection. The disadvantage of using glass slides is that the spectral range available is restricted to just the high wavenumber region (2500–3600 cm−1). In this work a study has been conducted on 120 breast tissues biopsy cores from different patients, to demonstrate that with the limited spectral information, breast cancer can be identified from the H&E glass slides. A four-class histological Adboost classification model has been constructed. Optimisation of the classification threshold was carried out to reduce the number of false negatives. Using a threshold of 0.1 the cancerous cores could be detected with an accuracy of 95.8 %. This was incorporated into a simple traffic light system that could be used as a prescreening tool. This work, demonstrating the use of infrared spectral pathology on standard pathology samples slide, thus goes some way to overcome one of the barriers to successful translation of the infrared technique into the clinic.
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DOI:
10.1039/c4an01832j
发表时间:
2015
期刊:
The Analyst
影响因子:
--
作者:
Mu,Xinying;Kon,Mark;Ergin,Ayşegül;Remiszewski,Stan;Akalin,Ali;Thompson,ClayM;Diem,Max
通讯作者:
Diem,Max
影响因子:
7.4
作者:
Bassan, Paul;Mellor, Joe;Gardner, Peter
通讯作者:
Gardner, Peter
影响因子:
3.8
作者:
Shachi Mittal;T. Wróbel;L. S. Leslie;Andre Kadjacsy;R. Bhargava
通讯作者:
R. Bhargava
影响因子:
4.2
作者:
Bassan, Paul;Weida, Miles J.;Gardner, Peter
通讯作者:
Gardner, Peter
影响因子:
7.4
作者:
D. Mayerich;M. Walsh;Andre Kadjacsy;Shachi Mittal;R. Bhargava
通讯作者:
R. Bhargava