Mammary tumors in Sprague Dawley rats induced by N-ethyl-N-nitrosourea for evaluating terahertz imaging of breast cancer

Abstract

Purpose: The objective of this study is to quantitatively evaluate terahertz (THz) imaging for differentiating cancerous from non-cancerous tissues in mammary tumors developed in response to injection of N-ethyl-N-nitrosourea (ENU) in Sprague Dawley rats. Approach: While previous studies have investigated the biology of mammary tumors of this model, the current work is the first study to employ an imaging modality to visualize these tumors. A pulsed THz imaging system is utilized to experimentally collect the time-domain reflection signals from each pixel of the rat's excised tumor. A statistical segmentation algorithm based on the expectation-maximization (EM) classification method is implemented to quantitatively assess the obtained THz images. The model classification of cancer is reported in terms of the receiver operating characteristic (ROC) curves and the areas under the curves. Results: The obtained low-power microscopic images of 17 ENU-rat tumor sections exhibited the presence of healthy connective tissue adjacent to cancerous tissue. The results also demonstrated that high reflection THz signals were received from cancerous compared with non-cancerous tissues. Decent tumor classification was achieved using the EM method with values ranging from 83% to 96% in fresh tissues and 89% to 96% in formalin-fixed paraffin-embedded tissues. Conclusions: The proposed ENU breast tumor model of Sprague Dawley rats showed a potential to obtain cancerous tissues, such as human breast tumors, adjacent to healthy tissues. The implemented EM classification algorithm quantitatively demonstrated the ability of THz imaging in differentiating cancerous from non-cancerous tissues.

Keywords: ENU-rat tumor induction; Sprague Dawley rats; Terahertz imaging; breast cancer; expectation-maximization classification method; microscopic imaging; reflection mode.

Fig. 1

Terahertz system diagram in reflection mode (a) for fresh tissue placed between two polystyrene plates; (b) for FFPE tissue block; (c) time-domain THz pulse; (d) Fourier transform of the THz pulse in (c); and (e) reflection signals from the polystyrene-tissue arrangement in (a).

Fig. 2

Rat # 1 fresh tissue preparation for THz imaging. (a) Photograph of bulk tumor excised from rat tumor #1; (b) bulk tumor bisected into two halves; (c) tumor placed on filter paper to remove excess fluid; (d) tumor positioned between two polystyrene plates; and (e) polystyrene-tumor-polystyrene arrangement placed on the scanning window.

Fig. 3

Low-power microscopic images of 17 tumor sections obtained from nine rat tumors. (a) Rat #1-section 1, (b) rat #1-section 2, (c) rat #2-section 1, (d) rat #2-section 2, (e) rat #3, (f) rat #4-section 1, (g) rat #4-section 2, (h) rat #5-section 1, (i) rat #5-section 2, (j) rat #6-section 1, (k) rat #6-section 2, (l) rat #7-section 1, (m) rat #7-section 2, (n) rat #8-section 1, (o) rat #8-section 2, (p) rat #9-section 1, and (q) rat #9-section 2.

Fig. 4

THz reflection imaging results. (a)–(d) Rat tumor #1-section 2: (a) photograph of the fresh tissue, (b) the low power pathology image, (c) the THz power spectra image of the fresh tissue, (d) the THz time-domain peak reflection image of the FFPE block. (e)–(h) Rat tumor #2-section 2: (e) photograph of the fresh tissue, (f) the low power pathology image, (g) the THz power spectra image of the fresh tissue, (h) the THz time-domain peak reflection image of the FFPE block. (i)–(l) Rat tumor #9-section 2: (i) photograph of the fresh tissue, (j) the low power pathology image, (k) the THz power spectra image of the fresh tissue, (l) the THz time-domain peak reflection image of the FFPE block. (m)–(p) Xenograft mouse tumor #9-section 2: (m) photograph of the fresh tissue, (n) the low power pathology image, (o) the THz power spectra image of the fresh tissue, and (p) the THz time-domain peak reflection image of the FFPE block. (q)–(t) Transgenic mouse tumor #14 C: (q) photograph of the fresh tissue, (r) the low power pathology image, (s) the THz power spectra image of the fresh tissue, and (t) the THz time-domain peak reflection image of the FFPE block. (m)–(p) Reproduced with permission from the IEEE. (q)–(t) Reproduced with permission from the IOP Publishing, Ltd.

Fig. 5

Percentage of cancerous pixels in each tumor THz image in Fig. 4.

Fig. 6

Statistical classification. (a)–(d) Rat #1: (a) the morphed pathology for the fresh tissue, (b) the 3D EM detection model results for the fresh tissue, (c) the morphed pathology image for the FFPE tissue block, and (d) the 4D EM detection model results for the FFPE block tissue. (e)–(h) Rat # 2: (e) the morphed pathology for the fresh tissue, (f) the 2D EM detection model results for the fresh tissue, (g) the morphed pathology image for the FFPE tissue block, and (h) the 4D EM detection model results for the FFPE block tissue. (i)–(l) Rat #9: (i) the morphed pathology for the fresh tissue, (j) the 2D EM detection model results for the fresh tissue, (k) the morphed pathology image for the FFPE tissue block, and (l) the 4D EM detection model results for the FFPE block tissue. (m)–(p) Xenograft mouse #9: (m) the morphed pathology for the fresh tissue, (n) the 2D EM detection model results for the fresh tissue, (o) the morphed pathology image for the FFPE tissue block, and (p) the 3D EM detection model results for the FFPE block tissue. (q)–(t) Transgenic mouse #14 C: (q) the morphed pathology for the fresh tissue, (r) the 2D EM detection model results for the fresh tissue, (s) the morphed pathology image for the FFPE tissue block, and (t) the 2D EM detection model results for the FFPE block tissue.

Fig. 7

ROC curves of cancer using the EM technique. (a) Fresh tissues and (b) FFPE tissues.

Fig. 8

Stitching microscopic images of mammary tumor from rat # 1. (a) H&E-stained tissue slide of rat tumor #1-section 2; (b) low-power microscopic images of the slide in (a) at $6.7\times$ magnification; (c) compiled image in the software after mapping of common points between all images in (b); (d) stitched pathology image; and (e) high power images obtained at $100\times$ magnification for the tissue regions marked (1) and (2) in (d).