Automated algorithm for differentiation of human breast tissue using low coherence interferometry for fine needle aspiration biopsy guidance.

Fine needle aspiration biopsy (FNAB) is a rapid and cost-effective method for obtaining a first-line diagnosis of a palpable mass of the breast. However, because it can be difficult to manually discriminate between adipose tissue and the fibroglandular tissue more likely to harbor disease, this technique is plagued by a high number of nondiagnostic tissue draws. We have developed a portable, low coherence interferometry (LCI) instrument for FNAB guidance to combat this problem. The device contains an optical fiber probe inserted within the bore of the fine gauge needle and is capable of obtaining tissue structural information with a spatial resolution of 10 mum over a depth of approximately 1.0 mm. For such a device to be effective clinically, algorithms that use the LCI data must be developed for classifying different tissue types. We present an automated algorithm for differentiating adipose tissue from fibroglandular human breast tissue based on three parameters computed from the LCI signal (slope, standard deviation, spatial frequency content). A total of 260 breast tissue samples from 58 patients were collected from excised surgical specimens. A training set (N=72) was used to extract parameters for each tissue type and the parameters were fit to a multivariate normal density. The model was applied to a validation set (N=86) using likelihood ratios to classify groups. The overall accuracy of the model was 91.9% (84.0 to 96.7) with 98.1% (89.7 to 99.9) sensitivity and 82.4% (65.5 to 93.2) specificity where the numbers in parentheses represent the 95% confidence intervals. These results suggest that LCI can be used to determine tissue type and guide FNAB of the breast.

Rapid fabrication of silk films with controlled architectures via electrogelation.

Current methods to produce silk films include casting and spin coating. Here we introduce a new method for the fabrication of silk films: electrogelation. Through use of a closed-loop anode, films with high surface smoothness and optical transparency are produced. Bending the electrode loop allows films with three-dimensional topologies to be formed, possessing thicknesses capable of descending into the submicron thin film regime.

Identifying intestinal metaplasia at the squamocolumnar junction by using optical coherence tomography.

BACKGROUND: Optical coherence tomography (OCT) is an optical imaging method that produces high-resolution cross-sectional images of the esophagus. The accuracy of OCT for differentiating tissue types at the squamocolumnar junction (SCJ) has not been established. OBJECTIVE: The purpose of this study was to identify and validate OCT image criteria for distinguishing metaplastic from nonmetaplastic tissue at the SCJ. DESIGN: A total of 196 biopsy-correlated OCT images of the SCJ were acquired from 113 patients undergoing upper endoscopy. A pathologist blinded to the OCT results reviewed each pathology specimen and determined the presence of the following histopathology: gastric cardia, squamous mucosa, pancreatic metaplasia, and intestinal metaplasia. An algorithm for diagnosing specialized intestinal metaplasia (SIM) was created by reviewing a training set of 40 biopsy-correlated OCT images. Two blinded investigators prospectively tested the algorithm on a validation set of 123 images. RESULTS: OCT images of squamous mucosa were characterized by a layered appearance without epithelial glands; gastric cardia, by vertical pit and gland structure, a well-defined epithelial surface reflectivity, and relatively poor image penetration; and SIM by an irregular architecture and good image penetration. The OCT criteria were 85% sensitive and 95% specific for SIM when applied retrospectively to the training set. When applied to the validation set, the algorithm was 81% sensitive for both OCT readers and 66% and 57% specific for diagnosing SIM. The interobserver agreement was good (kappa = 0.53). CONCLUSIONS: OCT imaging can identify SIM at the SCJ with an accuracy similar to that of endoscopy.

Measurement of collagen and smooth muscle cell content in atherosclerotic plaques using polarization-sensitive optical coherence tomography.

OBJECTIVES: The purpose of this study was to investigate the measurement of collagen and smooth muscle cell (SMC) content in atherosclerotic plaques using polarization-sensitive optical coherence tomography (PSOCT). BACKGROUND: A method capable of evaluating plaque collagen content and SMC density can provide a measure of the mechanical fidelity of the fibrous cap and can enable the identification of high-risk lesions. Optical coherence tomography has been demonstrated to provide cross-sectional images of tissue microstructure with a resolution of 10 mum. A recently developed technique, PSOCT measures birefringence, a material property that is elevated in tissues such as collagen and SMCs. METHODS: We acquired PSOCT images of 87 aortic plaques obtained from 20 human cadavers. Spatially averaged PSOCT birefringence, Phi, was measured and compared with plaque collagen and SMC content, quantified morphometrically by picrosirius red and smooth muscle actin staining at the corresponding locations. RESULTS: There was a high positive correlation between PSOCT measurements of Phi and total collagen content in all plaques (r = 0.67, p < 0.001) and in fibrous caps of necrotic core fibroatheromas (r = 0.68, p < 0.001). Polarization-sensitive optical coherence tomography measurements of Phi demonstrated a strong positive correlation with thick collagen fiber content (r = 0.76, p < 0.001) and SMC density (r = 0.74, p < 0.01). CONCLUSIONS: Our results demonstrate that PSOCT enables the measurement of birefringence in plaques and in fibrous caps of necrotic core fibroatheromas. Given its potential to evaluate collagen content, collagen fiber thickness, and SMC density, we anticipate that PSOCT will significantly improve our ability to evaluate plaque stability in patients.

Diagnostic accuracy of optical coherence tomography and integrated backscatter intravascular ultrasound images for tissue characterization of human coronary plaques.

OBJECTIVES: The purpose of the present study was to validate the diagnostic accuracy of optical coherence tomography (OCT), integrated backscatter intravascular ultrasound (IB-IVUS), and conventional intravascular ultrasound (C-IVUS) for tissue characterization of coronary plaques and to evaluate the advantages and limitations of each of these modalities. BACKGROUND: The diagnostic accuracy of OCT for characterizing tissue types is well established. However, comparisons among OCT, C-IVUS, and IB-IVUS have not been done. METHODS: We examined 128 coronary arterial sites (42 coronary arteries) from 17 cadavers; IVUS and OCT images were acquired on the same slice as histology. Ultrasound signals were obtained using an IVUS system with a 40-MHz catheter and digitized at 1 GHz with 8-bit resolution. The IB values of the ultrasound signals were calculated with a fast Fourier transform. RESULTS: Using histological images as a gold standard, the sensitivity of OCT for characterizing calcification, fibrosis, and lipid pool was 100%, 98%, and 95%, respectively. The specificity of OCT was 100%, 94%, and 98%, respectively (Cohen's kappa = 0.92). The sensitivity of IB-IVUS was 100%, 94%, and 84%, respectively. The specificity of IB-IVUS was 99%, 84%, and 97%, respectively (Cohen's kappa = 0.80). The sensitivity of C-IVUS was 100%, 93%, and 67%, respectively. The specificity of C-IVUS was 99%, 61%, and 95%, respectively (Cohen's kappa = 0.59). CONCLUSIONS: Within the penetration depth of OCT, OCT has a best potential for tissue characterization of coronary plaques. Integrated backscatter IVUS has a better potential for characterizing fibrous lesions and lipid pools than C-IVUS.

Optical coherence tomography to identify intramucosal carcinoma and high-grade dysplasia in Barrett's esophagus.

BACKGROUND & AIMS: Optical coherence tomography (OCT) is an optical technique that produces high-resolution images of the esophagus during endoscopy. OCT can distinguish specialized intestinal metaplasia (SIM) from squamous mucosa, but image criteria for differentiating intramucosal carcinoma (IMC) and high-grade dysplasia (HGD) from low-grade dysplasia (LGD), indeterminate-grade dysplasia (IGD), and SIM without dysplasia have not been validated. The purpose of this study was to establish OCT image characteristics of IMC and HGD in Barrett's esophagus. METHODS: Biopsy-correlated OCT images were acquired from patients with Barrett's esophagus undergoing endoscopic surveillance. Two pathologists rendered consensus diagnoses of the biopsy specimens. A blinded investigator reviewed the biopsy-correlated OCT images and scored each for surface maturation and gland architecture. For each image the scores were summed to determine an OCT "dysplasia index." RESULTS: A total of 177 biopsy-correlated images were analyzed. The corresponding histopathology diagnosis was IMC/HGD in 49 cases, LGD in 15, IGD in 8, SIM in 100, and gastric mucosa in 5. A significant relationship was found between a histopathologic diagnosis of IMC/HGD and scores for each image feature (dysplasia index [Spearman correlation coefficient, r = 0.50, P < .0001], surface maturation [r = 0.48, P < .0001], and gland architecture [r = 0.41, P < .0001]). When a dysplasia index threshold of >or=2 was used, the sensitivity and specificity for diagnosing IMC/HGD were 83% and 75%, respectively. CONCLUSIONS: An OCT image scoring system based on histopathologic characteristics has the potential to identify IMC and HGD in Barrett's esophagus.