Detection of Provasopressin in Invasive and Non-invasive (DCIS) Human Breast Cancer Using a Monoclonal Antibody Directed Against the C-terminus (MAG1)

The provasopressin protein (proAVP) is expressed by invasive breast cancer and non-invasive breast cancer, or ductal carcinoma in situ (DCIS). Here we demonstrate the ability of the monoclonal antibody MAG1 directed against the C-terminal end of proAVP to identify proAVP in all cases examined of human invasive cancer and DCIS (35 and 26, respectively). Tissues were chosen to represent a relevant variation in tumor type, grade, patient age, and menopausal status. By comparison, there was 65% positive staining for estrogen receptor, 61% for progesterone receptor, 67% for nuclear p53, and 39% for c-Erb-B2 with the invasive breast cancer sections. Reaction with the normal tissue types examined (67) was restricted to the vasopressinergic magnocellular neurons of the hypothalamus, where provasopressin is normally produced, and the posterior pituitary, where these neurons terminate. The breast epithelial tissue sections on the tissue microarray did not react with MAG1. Previously, we demonstrated that polyclonal antibodies to proAVP detected that protein in all breast cancer samples examined, but there was no reaction with breast tissue containing fibrocystic disease. The results presented here not only expand upon those earlier results, but they also demonstrate the specificity and effectiveness of what may be considered a more clinically-relevant agent. Thus, proAVP appears to be an attractive target for the detection of invasive breast cancer and DCIS, and these results suggest that MAG1 may be a beneficial tool for use in the development of such strategies

Scanning in Situ Spectroscopy Pplatform for Imaging Surgical Breast Tissue Specimens

A non-contact localized spectroscopic imaging platform has been developed and optimized to scan 1 x 1 cm² square regions of surgically resected breast tissue specimens with ~150-micron resolution. A color corrected, image-space telecentric scanning design maintained a consistent sampling geometry and uniform spot size across the entire imaging field. Theoretical modeling in ZEMAX allowed estimation of the spot size, which is equal at both the center and extreme positions of the field with ~5% variation across the designed waveband, indicating excellent color correction. The spot sizes at the center and an extreme field position were also measured experimentally using the standard knife-edge technique and were found to be within ~8% of the theoretical predictions. Highly localized sampling offered inherent insensitivity to variations in background absorption allowing direct imaging of local scattering parameters, which was validated using a matrix of varying concentrations of Intralipid and blood in phantoms. Four representative, pathologically distinct lumpectomy tissue specimens were imaged, capturing natural variations in tissue scattering response within a given pathology. Variations as high as 60% were observed in the average reflectance and relative scattering power images, which must be taken into account for robust classification performance. Despite this variation, the preliminary data indicates discernible scatter power contrast between the benign vs malignant groups, but reliable discrimination of pathologies within these groups would require investigation into additional contrast mechanisms

Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures

High positive margin rates in oncologic breast-conserving surgery are a pressing clinical problem. Volumetric X-ray scanning is emerging as a powerful ex vivo specimen imaging technique for analyzing resection margins, but X-rays lack contrast between non-malignant and malignant fibrous tissues. In this study, combined micro-CT and wide-field optical image radiomics were developed to classify malignancy of breast cancer tissues, demonstrating that X-ray/optical radiomics improve malignancy classification. Ninety-two standardized features were extracted from co-registered micro-CT and optical spatial frequency domain imaging samples extracted from 54 breast tumors exhibiting seven tissue subtypes confirmed by microscopic histological analysis. Multimodal feature sets improved classification performance versus micro-CT alone when adipose samples were included (AUC = 0.88 vs. 0.90; p-value = 3.65e−11) and excluded, focusing the classification task on exclusively non-malignant fibrous versus malignant tissues (AUC = 0.78 vs. 0.85; p-value = 9.33e−14). Extending the radiomics approach to high-dimensional optical data—termed “optomics” in this study—offers a promising optical image analysis technique for cancer detection. Radiomic feature data and classification source code are publicly available

Optical assessment of pathology in surgically resected tissues

Multi-spectral spatially modulated light is used to guide localized spectroscopy of surgically resected tissues for cancer involvement. Modulated imaging rapidly quantifies near-infrared optical parameters with sub-millimeter resolution over the entire field for identification of residual disease in resected tissues. Suspicious lesions are further evaluated using a spectroscopy platform designed to image thick tissue samples at a spatial resolution sensitive to the diagnostic gold standard, pathology. MI employs a spatial frequency domain sampling and model-based analysis of the spatial modulation transfer function to interpret a tissue's absorption and scattering parameters at depth. The spectroscopy platform employs a scanning-beam, telecentric dark-field illumination and confocal detection to image fields up to 1cm2 with a broadband source (480:750nm). The sampling spot size (100μm lateral resolution) confines the volume of tissue probed to within a few transport pathlengths so that multiple-scattering effects are minimized and simple empirical models may be used to analyze spectra. Localized spectroscopy of Intralipid and hemoglobin phantoms demonstrate insensitivity of recovered scattering parameters to changes in absorption, but a non-linear dependence of scattering power on Intralipid concentration is observed due to the phase sensitivity of the measurement system. Both systems were validated independently in phantom and murine studies. Ongoing work focuses on assessing the combined utility of these systems to identify cancer involvement in vitro, particularly in the margins of resected breast tumors

Near-Infrared Characterization of Breast Tumors In Vivo using Spectrally-Constrained Reconstruction

Multi-wavelength Near-Infrared (NIR) Tomography was utilized in this study to non-invasively quantify physiological parameters of breast tumors using direct spectral reconstruction. Frequency domain NIR measurements were incorporated with a new spectrally constrained direct chromophore and scattering image reconstruction algorithm, which was validated in simulations and experimental phantoms. Images of total hemoglobin, oxygen saturation, water, and scatter parameters were obtained with higher accuracy than previously reported. Using this spectral approach, in vivo NIR images are presented and interpreted through a series of case studies (n=6 subjects) having differing abnormalities. The corresponding mammograms and ultrasound images are also evaluated. Three of six cases were malignant (infiltrating ductal carcinomas) and showed higher hemoglobin (34–86% increase), a reduction in oxygen saturation, an increase in water content as well as scatter changes relative to surrounding normal tissue. Three of six cases were benign, two of which were diagnosed with fibrocystic disease and showed a dominant contrast in water, consistent with fluid filled cysts. Scatter amplitude was the main source of contrast in the volunteer with the benign condition fibrosis, which typically contains denser collagen tissue. The changes monitored correspond to physiological changes associated with angiogenesis, hypoxia and cell proliferation anticipated in cancers. These changes represent potential diagnostic indicators, which can be assessed to characterize breast tumors

Molecular Dyes used for Surgical Specimen Margin Orientation allow for Intraoperative Optical Assessment During Breast Conserving Surgery

A variety of optical techniques utilizing near-infrared (NIR) light are being proposed for intraoperative breast tumor margin assessment. However, immediately following a lumpectomy excision, the margins are inked, which preserves the orientation of the specimen but prevents optical interrogation of the tissue margins. Here, a workflow is proposed that allows for both NIR optical assessment following full specimen marking using molecular dyes which have negligible absorption and scattering in the NIR. The effect of standard surgical inks in contrast to molecular dyes for an NIR signal is shown. Further, the proposed workflow is demonstrated with full specimen intraoperative imaging on all margins directly after the lumpectomy has been excised and completely marked. This work is an important step in the path to clinical feasibility of intraoperative breast tumor margin assessment using NIR optical methods without having to compromise on the current clinical practice of inking resected specimens for margin orientation

Fractal analysis of scatter imaging signatures to distinguish breast pathologies

Fractal analysis combined with a label-free scattering technique is proposed for describing the pathological architecture of tumors. Clinicians and pathologists are conventionally trained to classify abnormal features such as structural irregularities or high indices of mitosis. The potential of fractal analysis lies in the fact of being a morphometric measure of the irregular structures providing a measure of the object’s complexity and self-similarity. As cancer is characterized by disorder and irregularity in tissues, this measure could be related to tumor growth. Fractal analysis has been probed in the understanding of the tumor vasculature network. This work addresses the feasibility of applying fractal analysis to the scattering power map (as a physical modeling) and principal components (as a statistical modeling) provided by a localized reflectance spectroscopic system. Disorder, irregularity and cell size variation in tissue samples is translated into the scattering power and principal components magnitude and its fractal dimension is correlated with the pathologist assessment of the samples. The fractal dimension is computed applying the box-counting technique. Results show that fractal analysis of ex-vivo fresh tissue samples exhibits separated ranges of fractal dimension that could help classifier combining the fractal results with other morphological features. This contrast trend would help in the discrimination of tissues in the intraoperative context and may serve as a useful adjunct to surgeons.This work has been supported by CYCIT projects DA2TOI (FIS2010-19860) and TFS (TEC2010-20224-C02-02), as well as FPU PhD Scholarship (FPU12/04130), all funded by the Spanish Government