Development and Testing of a Single Frequency Terahertz Imaging System for Breast Cancer Detection

Abstract

The ability to discern malignant from benign tissue in excised human breast specimens in Breast Conservation Surgery (BCS) was evaluated using single frequency terahertz radiation. Terahertz (THz) images of the specimens in reflection mode were obtained by employing a gas laser source and mechanical scanning. The images were correlated with optical histological micrographs of the same specimens, and a mean discrimination of 73% was found for five out of six samples using Receiver Operating Characteristic (ROC) analysis. The system design and characterization is discussed in detail. The initial results are encouraging but further development of the technology and clinical evaluation is needed to evaluate its feasibility in the clinical environment.

Assessment of Terahertz Imaging for Excised Breast Cancer Tumors with Image Morphing

“…It does not clearly show the classification of the different regions at low magnification, and its accurate interpretation requires high magnification and the expertise of a pathologist. To enable the direct and pixel-by-pixel comparison between the pathology and THz image, it is necessary to convert the colored pathology image into a new one that clearly define the classification of each pixel based on the report from the pathologist [4]. The algorithm uses the gray scale color representation of the pathology image for the classification of the regions in samples with 2 regions and the hue-saturation-value (HSV) color representation in samples with 3 or more regions.…”

“…On the other hand, in [3,4,10], the THz images were quantitatively evaluated using different types of tools. For example, in [3], the imaging results were evaluated by computing the Spearman rank correlation coefficient between the number of cancer pixels on the delineated THz and pathology images.…”

“…The sections were then compared to calculate the receiver operating characteristic (ROC) curve. The ROC curves were also generated in [4] by performing a pixel-by-pixel comparison between the THz image and a histology map, which was manually created by overlapping of the pathology results on the THz image with software assistance. All the above quantitative methods required manual generation or adjustment of the pathology image, which are time consuming and prone to human errors and bias.…”

Pulsed terahertz imaging of breast cancer in freshly excised murine tumors

“…Digitization of pathology in this work is obtained using a morphing algorithm, which enables a pixel-by-pixel comparison between the THz images and digitized pathology results. 7,17 Of classification methods used for THz imaging of fresh tissue, the use of support vector machines (SVM) and principal component analysis (PCA) reported up to 92% accuracy for breast cancer when combined. 18 The techniques used separately showed a 96% sensitivity and 87% specificity for SVM and 92% sensitivity and 87% specificity for PCA of normal versus dysplastic tissue in colon cancer imaging.…”

“…19 SVM also attained a 72% discrimination in 1.89-THz continuous wave imaging of breast cancer. 7 In applications not handling fresh tissue, SVM was used for FFPE tissue imaging and spectroscopy. 5,20,21 Only a few other methods have been used for fresh tissue imaging, such as PCA for murine brain glioma.…”