Review of optical coherence tomography in oncology

Abstract

The application of optical coherence tomography (OCT) in the field of oncology has been prospering over the past decade. OCT imaging has been used to image a broad spectrum of malignancies, including those arising in the breast, brain, bladder, the gastrointestinal, respiratory, and reproductive tracts, the skin, and oral cavity, among others. OCT imaging has initially been applied for guiding biopsies, for intraoperatively evaluating tumor margins and lymph nodes, and for the early detection of small lesions that would often not be visible on gross examination, tasks that align well with the clinical emphasis on early detection and intervention. Recently, OCT imaging has been explored for imaging tumor cells and their dynamics, and for the monitoring of tumor responses to treatments. This paper reviews the evolution of OCT technologies for the clinical application of OCT in surgical and noninvasive interventional oncology procedures and concludes with a discussion of the future directions for OCT technologies, with particular emphasis on their applications in oncology.

Keywords: cancer; intraoperative; oncology; optical coherence tomography; surgery; tumor.

Fig. 1

Comparison of oblique cross sections with matching histology of ex vivo breast tumor samples measured using PS-OCT. (a, d) Structural intensity (I), (b, e) overlay of tissue birefringence and intensity and (c, f) matching histological section stained with haematoxylin and eosin (H&E). (a–c) are from a wide-local excision (lumpectomy) of a 20 mm, grade 1 invasive ductal carcinoma. (d–f) are from a mastectomy of a 20 mm, grade 2 invasive ductal carcinoma. The needle track visible in (c) is due to a needle inserted into the tissue after imaging to guide the collection of histology, and hence does not appear in the OCT images. Scale bar is 1 mm and applies to all panels. Color range indicates birefringence of $0.18\times {10}^{-3}$ to $2.2\times {10}^{-3}$. Brightness range is 10 to 40 dB. Figure reprinted with permission from Ref.

Fig. 2

Video OCT cross-sectional images of a positive tumor margin from the in vivo resection bed and ex vivo excised tissue. Images are from a 72-year-old female WLE patient with invasive ductal carcinoma of the left breast. Diagrams on the left indicate the imaged regions (dashed boxes) of the resection bed or the excised specimen (not to scale), and the solid black lines in the black dashed boxes indicate the top of the corresponding OCT image. The red and green dashed regions correspond to areas identified as cancer and normal areas, respectively. (a) OCT image of the positive in vivo lateral tumor margin. (b) OCT image of the positive ex vivo lateral specimen margin, with corresponding histology. (c) OCT image of the positive additional ex vivo lateral margin tissue [same tissue as imaged in vivo in (a)], with corresponding histology. (d) OCT image of the final negative in vivo lateral margin. Areas of interest are magnified and shown in the insets to compare normal stroma and adipose with cancerous regions. Note that histology images are only provided for the corresponding OCT images in (b) and (c), because the images in (a) and (d) were acquired in vivo and hence do not have corresponding histology images. Figure reprinted with permission from Ref. .

Fig. 3

In vivo brain cancer imaging in a mouse with patient-derived high grade brain cancer (GBM272). (a and b) Brain tissues were imaged in vivo in mice ($n=5$) undergoing brain cancer resection. After imaging, the mice were sacrificed and their brains were processed for histology. The representative results of a mouse brain at the cancer site before surgery (a) and at the resection cavity after surgery (b) are shown. (c) Corresponding histology for the resection cavity after surgery. (d and e) From the same mouse, (d) control images were acquired from a seemingly healthy area on the contralateral side of the brain, (e) with the corresponding histology. The red circle indicates cancer, the gray circle indicates the resection cavity, and the square indicates the OCT field of view. Two-dimensional optical property maps were displayed using an attenuation threshold of $5.5{\mathrm{mm}}^{-1}$. Aliasing artifacts at the image boundaries, which were produced when dorsal structures from outside the OCT depth were folded back into the image, were cropped out of image. 3-D volumetric reconstructions were overlaid with optical property maps on the top surface. Optical attenuation properties were averaged for each subvolume of $0.326\mathrm{mm}\times 0.008\mathrm{mm}\times 1.8\mathrm{mm}$ within the tissue block, with a step size of 0.033 mm in the $x$-direction. Each histological image (c and e) represented a cross-sectional view of the tissue block: the image corresponds to a single perpendicular slice through the attenuation map, along the dotted lines in (b) and (d), respectively. Residual cancer cells were marked with black arrows and correspond to yellow/red regions on the attenuation maps (at the level of the dotted line). Abbreviations: C, cancer; W, noncancer white matter; M, noncancer meninges. Scale bars represent 0.2 mm. Figure reprinted with permission from Ref. .

Fig. 4

PS-OCT of poorly differentiated carcinoma with surrounding fibrosis in ex vivo lung. (a) Structural OCT does not clearly show a distinction between solid carcinoma and adjacent fibrosis. Calcifications (C) within the fibrosis can be seen as signal-poor structures. (b) PS-OCT shows a clear delineation between solid carcinoma (left of line) and fibrosis (right of line), with no birefringence signal in the regions of carcinoma and high birefringence signal in the regions of fibrosis. (c) Matched histology confirming the demarcation between carcinoma and fibrosis. Scale bars represent 1 mm. Figure reprinted with permission from Ref. .

Fig. 5

Tethered capsule endomicroscopy data from a patient with a diagnosis of Barrett’s esophagus and high-grade dysplasia, with intramucosal carcinoma. (a–c) Portion of a cross-sectional tethered capsule microscopy image of (a) the stomach, (b) Barrett’s esophagus mucosa with architectural atypia suggestive of high-grade dysplasia, and (c) squamous mucosa at the distal, mid, and proximal ends of the esophagus, respectively. (d) A three-dimensional representation of the tethered capsule endomicroscopy data showing a 4-cm segment of Barrett’s esophagus with multiple raised plaques and nodules, one of which corresponds to the features in (b). (e–g) Three-dimensional fly-through views of: (e) the stomach, (f) Barrett’s segment, and (g) squamous mucosa showing a clear difference between the superficial appearance of the rugal folds of the stomach, the crypt pattern of Barrett’s esophagus, and the smooth surface of the squamous mucosa. Tick marks and scale bars represent: (a–c) 1 mm; scale bars: (d) 1 cm. Figure reprinted with permission from Ref. .

Fig. 6

In vivo surface, cross-sectional OCT, and H&E-stained histological images of normal human bladder versus a papillary TCC. Image sizes: $\sim \varphi 20\mathrm{mm}$ in (a, d) and 4.6 mm laterally by 2.1 mm axially in (b, e, c, and f). The morphological details of normal bladder (B), including urothelium (U), lamina propria (LP), and upper muscularis (M) were clearly delineated by OCT based on their backscattering differences, whereas those (LP, M) below the papillary TCC (e) are diminished. Solid arrows: subsurface blood vessels; dashed arrows: papillary features; dashed circle: TCC (low backscattering) identified by OCT based on increased urothelial heterogeneity; dashed line: boundary with adjacent normal bladder. Diagnoses of the normal bladder via OCT, cystoscopy, and histology were all negative, and voided cytology was positive. Diagnoses of a papillary lesion via OCT, cystoscopy, and histology were positive, while cytology was negative. Figure reprinted with permission from Ref. .

Fig. 7

(a) Representative intensity, (b) phase retardation, and (c) histology images of healthy and BCC human skin. (a), (b), and (c) represent the images of a healthy skin. Normal skin appendages such as a hair follicle (HF, yellow arrow) and sebaceous glands (SG, light pink arrow) are observed. (d), (e), and (f) images represent the case of a nodular BCC, and (g), (h), and (i) images represent a case of infiltrative BCC. The white arrows point to nodular tumor islands. Scale bars represent $500\mu \mathrm{m}\times 500\mu \mathrm{m}$ and are applicable to all images in a row. Figure reprinted with permission from Ref. .

Fig. 8

OCT imaging of a submucosal fibrotic lesion on the buccal mucosa of a 48-year-old male patient. The pullback direction is from left to right corresponding to the posterior to anterior orientation. (b) Clinical photo of the lesion being imaged with the modified saliva ejector catheter holder. Structural OCT with (a) en face projection and (c) azimuthal slices. The clinically visible lesion is indicated between the solid (pink) vertical lines. Slices along the dotted (red) and dashed (green) lines are shown in Cartesian images in (d) and (e), respectively. (f, g, and h) Retardation images corresponding to the structural images (c, d, e), respectively. The images are averaged with a triangular kernel of width 5 ($w=5$). The white bars in the images represent 1 mm in length. Figure used with permission.

Fig. 9

(a) Intraoperative view of the glottic surface showing probe placement at the interface between the normal vocal fold and carcinoma on the right side. (b) Conventional OCT image shows a signal void in the area of cancer (scca) with sharp contrast to the gray scale image of normal tissue (arrows). (c) Clear distinction between the cancer, which is seen as a black area on the left side of the image, and normal vocal fold, which contains the light–dark–light banding pattern. Arrow depicts the clear boundary between cancer (scca) and normal. Figure reprinted with permission from Ref. .

Fig. 10

Representative images of normal and high-grade CIN with epithelium segmentation results. White curves and white arrows indicate the probe–tissue interface segmented by the computer-aided diagnosis algorithm, and black curves and black arrows indicate the segmented boundary between the epithelium and stroma. (a)–(d) Typical normal cervical OCT images and segmentation results. All structures are well defined, including the epithelium (EP), the BM, and the stroma (ST). [(e)–(l)] OCT images of CIN 2 and CIN 3. The layered architecture becomes irregular or is not apparent. Images shown in (e) and (f), and (i) and (j) were correctly classified. Images shown in (g) and (h), and (k) and (l) were misclassified. Figure reprinted with permission from Ref. .

Fig. 11

Multiparametric response of directed anticancer therapy characterized by OCT. (a) OCT images of representative control and treated tumors 5 days after initiation of antiangiogenic VEGFR-2. The lymphatic vascular networks are also presented (blue) for both tumors. (b) Quantification of tumor volume, vascular geometry, and morphology in response to VEGFR-2 blockade. Control, $n=5$; treated, $n=6$. (c) OCT images of tissue scattering immediately before and 2 days after administration of targeted cytotoxic therapy (diphtheria toxin) or saline to mice bearing human tumor xenografts (LS174T) in dorsal skinfold chambers. Apoptosis induced by the diphtheria toxin is manifested as increased tissue scattering relative to control mice. (d) Quantification of the response to diphtheria toxin administration. Control, $n=3$; treated, $n=3$. Scale bars represent $500\mu \mathrm{m}$. Statistically significant differences ($p<0.05$) at given time points are denoted by asterisks. Data are presented as $\text{mean}\pm \mathrm{s.e.m}$. Figure reprinted with permission from Ref. .