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CCR Translation for This Article from Scatter Spectroscopic Imaging Distinguishes between Breast Pathologies in Tissues Relevant to Surgical Margin Assessment

PDF file, 133K, Diagnostic distribution of tissue population and mean+/-standard deviation for spectrally derived scattering parameters per diagnostic category.

Biological tissue characterization using optical imaging techniques often focus on optical property quantification, a process that relies on a diffuse or sub-diffuse light transport model. Assumptions associated with each light transport model reduce the applicability and increase the computational and/or experimental complexity of the techniques. Scattering orientation index and texture metrics quantified for human breast tissues are free of light transport assumptions and were quantified using the demodulated reflectance from wide-field structured light imaging. This work suggests that wide-field tissue diagnostics might be possible without model-based optical property quantification and instead using assumption-free scatter orientation and textural information.

The most common treatment for early-stage breast cancer involves breast-conserving surgery (BCS), which is a local resection of malignant tissue. BCS success relies on the presence of healthy tissue margins surrounding each resection. However, approximately 20% of BCS patients require follow-up surgery to remove residual tumor. Micro-computed tomography and optical structured light imaging were investigated for intraoperative margin assessment. Specimens were imaged immediately after resection and before surgical inking, and image data were compared to postoperative histopathology. The study demonstrated the feasibility of imaging during BCS and generated a baseline multimodal dataset of whole BCS resections, including positive margin signatures.

Wire-localized excision of nonpalpable breast cancer is imprecise, resulting in positive margins 25-30% of the time.Patients underwent preoperative supine magnetic resonance imaging (MRI). A radiologist outlined the tumor edges on consecutive images, creating a three-dimensional (3D) view of its location. Using 3D printing, a bra-like plastic form (the Breast Cancer Locator [BCL]) was fabricated, with features that allowed a surgeon to (1) mark the edges of the tumor on the breast surface; (2) inject blue dye into the breast 1 cm from the tumor edges; and (3) place a wire in the tumor at the time of surgery.Nineteen patients with palpable cancers underwent partial mastectomy after placement of surgical cues using patient-specific BCLs. The cues were in place in5 min and no adverse events occurred. The BCL accurately localized 18/19 cancers. In the 18 accurately localized cases, all 68 blue-dye injections were outside of the tumor edges. Median distance from the blue-dye center to the pathologic tumor edge was 1.4 cm, while distance from the blue dye to the tumor edge was5 mm in 4% of injections, 0.5-2.0 cm in 72% of injections, and2 cm in 24% of injections. Median distance from the tumor center to the BCL-localized wire and to the clip placed at the time of diagnosis was similar (0.49 vs. 0.73 cm) on specimen mammograms.Information on breast cancer location and shape derived from a supine MRI can be transferred safely and accurately to patients in the operating room using a 3D-printed form.

Structured light imaging (SLI) with high spatial frequency (HSF) illumination provides a method to amplify native tissue scatter contrast and better differentiate superficial tissues. This was investigated for margin analysis in breast-conserving surgery (BCS) and imaging gross clinical tissues from 70 BCS patients, and the SLI distinguishability was examined for six malignancy subtypes relative to three benign/normal breast tissue subtypes. Optical scattering images recovered were analyzed with five different color space representations of multispectral demodulated reflectance. Excluding rare combinations of invasive lobular carcinoma and fibrocystic disease, SLI was able to classify all subtypes of breast malignancy from surrounding benign tissues (p-value

A cohort of N=42 breast lesions has been imaged in-situ with a structured light imaging system through an ongoing clinical study. Multispectral, high spatial frequency scatter images provide additional modes contrast across the tumor-normal boundary.

A multimodal micro-computed tomography (CT) and multi-spectral structured light imaging (SLI) system is introduced and systematically analyzed to test its feasibility to aid in margin delineation during breast conserving surgery (BCS). Phantom analysis of the micro-CT yielded a signal-to-noise ratio of 34, a contrast of 1.64, and a minimum detectable resolution of 240 μm for a 1.2 min scan. The SLI system, spanning wavelengths 490 nm to 800 nm and spatial frequencies up to 1.37 [Formula: see text], was evaluated with aqueous tissue simulating phantoms having variations in particle size distribution, scatter density, and blood volume fraction. The reduced scattering coefficient, [Formula: see text] and phase function parameter, γ, were accurately recovered over all wavelengths independent of blood volume fractions from 0% to 4%, assuming a flat sample geometry perpendicular to the imaging plane. The resolution of the optical system was tested with a step phantom, from which the modulation transfer function was calculated yielding a maximum resolution of 3.78 cycles per mm. The three dimensional spatial co-registration between the CT and optical imaging space was tested and shown to be accurate within 0.7 mm. A freshly resected breast specimen, with lobular carcinoma, fibrocystic disease, and adipose, was imaged with the system. The micro-CT provided visualization of the tumor mass and its spiculations, and SLI yielded superficial quantification of light scattering parameters for the malignant and benign tissue types. These results appear to be the first demonstration of SLI combined with standard medical tomography for imaging excised tumor specimens. While further investigations are needed to determine and test the spectral, spatial, and CT features required to classify tissue, this study demonstrates the ability of multimodal CT/SLI to quantify, visualize, and spatially navigate breast tumor specimens, which could potentially aid in the assessment of tumor margin status during BCS.

In spatial frequency domain imaging (SFDI), a spatially modulated intensity pattern is projected on to tissue, with the demodulated reflectance having more superficial sensitivity with increasing spatial modulation frequency. With sub-diffusive SFDI, very high (>0.5 mm-1) spatial modulation frequencies are projected yielding sensitivity to the directionality of light scattering with only few scattering events occurring and sub-millimeter penetration depth and spatial resolution. This technique has been validated in a series of phantom experiments, where fractal distributions of polystyrene spheres were imaged, and through a model based inversion, the size scale distribution versus overall density of these particles could be separated and visualized in spatially resolved maps. With sensitivity to localized light scattering over a wide field of view (11 cm x 14 cm), this technique is being translated for the application of intraoperative breast tumor margin assessment. To test sensitivity to changes in human breast tissue morphology, a cohort of over 30 freshly excised human breast tissue specimens, including adipose, fibroglandular, fibroadenoma, and invasive carcinoma, have been imaged and co-registered to whole specimen histology. Statistical analysis of the distributions of both textual raw reflectance parameters and model based optical properties for each type of tissue will be presented. Furthermore, classification algorithm development and analysis to predicted likelihood of cancer on the surface of the tissue will also be presented. Reflectance maps, optical property maps, and probability likelihood maps of spatially heterogeneous samples with multiple tissue types will also be shown.

There is a dire clinical need for surgical margin guidance in breast conserving therapy (BCT). We present a multispectral spatial frequency domain imaging (SFDI) system, spanning the visible and near-infrared (NIR) wavelengths, combined with a shielded X-ray computed tomography (CT) system, designed for intraoperative breast tumor margin assessment. While the CT can provide a volumetric visualization of the tumor core and its spiculations, the co-registered SFDI can provide superficial and quantitative information about localized changes tissue morphology from light scattering parameters. These light scattering parameters include both model-based parameters of sub-diffusive light scattering related to the particle size scale distribution and also textural information of the high spatial frequency reflectance. Because the SFDI and CT components are rigidly fixed, a simple transformation can be used to simultaneously display the SFDI and CT data in the same coordinate system. This is achieved through the Visualization Toolkit (vtk) file format in the open-source Slicer medical imaging software package. In this manuscript, the instrumentation, data processing, and preliminary human specimen data will be presented. The ultimate goal of this work is to evaluate this technology in a prospective clinical trial, and the current limitations and engineering solutions to meet this goal will also be discussed.

Subdiffuse spatial frequency domain imaging (sd-SFDI) data of 42 freshly excised, bread-loafed tumor resections from breast-conserving surgery (BCS) were evaluated using texture analysis and a machine learning framework for tissue classification. Resections contained 56 regions of interest (RoIs) determined by expert histopathological analysis. RoIs were coregistered with sd-SFDI data and sampled into ∼4 × 4 mm2 subimage samples of confirmed and homogeneous histological categories. Sd-SFDI reflectance textures were analyzed using gray-level co-occurrence matrix pixel statistics, image primitives, and power spectral density curve parameters. Texture metrics exhibited statistical significance (p-value 0.05) between three benign and three malignant tissue subtypes. Pairs of benign and malignant subtypes underwent texture-based, binary classification with correlation-based feature selection. Classification performance was evaluated using fivefold cross-validation and feature grid searching. Classification using subdiffuse, monochromatic reflectance (illumination spatial frequency of fx = 1.37 mm − 1, optical wavelength of λ = 490 nm) achieved accuracies ranging from 0.55 (95% CI: 0.41 to 0.69) to 0.95 (95% CI: 0.90 to 1.00) depending on the benign–malignant diagnosis pair. Texture analysis of sd-SFDI data maintains the spatial context within images, is free of light transport model assumptions, and may provide an alternative, computationally efficient approach for wide field-of-view (cm2) BCS tumor margin assessment relative to pixel-based optical scatter or color properties alone.

Purpose: A new approach to spectroscopic imaging was developed to detect and discriminate microscopic pathologies in resected breast tissues; diagnostic performance of the prototype system was tested in 27 tissues procured during breast conservative surgery. Experimental Design: A custom-built, scanning in situ spectroscopy platform sampled broadband reflectance from a 150-μm-diameter spot over a 1 × 1 cm2 field using a dark field geometry and telecentric lens; the system was designed to balance sensitivity to cellular morphology and imaging the inherent diversity within tissue subtypes. Nearly 300,000 broadband spectra were parameterized using light scattering models and spatially dependent spectral signatures were interpreted using a cooccurrence matrix representation of image texture. Results: Local scattering changes distinguished benign from malignant pathologies with 94% accuracy, 93% sensitivity, 95% specificity, and 93% positive and 95% negative predictive values using a threshold-based classifier. Texture and shape features were important to optimally discriminate benign from malignant tissues, including pixel-to-pixel correlation, contrast and homogeneity, and the shape features of fractal dimension and Euler number. Analysis of the region-based diagnostic performance showed that spectroscopic image features from 1 × 1 mm2 areas were diagnostically discriminant and enabled quantification of within-class tissue heterogeneities. Conclusions: Localized scatter-imaging signatures detected by the scanning spectroscopy platform readily distinguished benign from malignant pathologies in surgical tissues and showed new spectral-spatial signatures of clinical breast pathologies. Clin Cancer Res; 18(22); 6315–25. ©2012 AACR.

Localized measurements of scattering in biological tissue provide sensitivity to microstructural morphology but have limited utility to wide-field applications, such as surgical guidance. This study introduces sub-diffusive spatial frequency domain imaging (sd-SFDI), which uses high spatial frequency illumination to achieve wide-field sampling of localized reflectances. Model-based inversion recovers macroscopic variations in the reduced scattering coefficient [Formula: see text] and the phase function backscatter parameter (γ). Measurements in optical phantoms show quantitative imaging of user-tuned phase-function-based contrast with accurate decoupling of parameters that define both the density and the size-scale distribution of scatterers. Measurements of fresh ex vivo breast tissue samples revealed, for the first time, unique clustering of sub-diffusive scattering properties for different tissue types. The results support that sd-SFDI provides maps of microscopic structural biomarkers that cannot be obtained with diffuse wide-field imaging and characterizes spatial variations not resolved by point-based optical sampling.

Sub-diffusive structured light imaging can quantitate the density of scatterers versus their size scale distribution in a wide-field geometry. Phantoms with unique fractal distributions and n=22 fresh human breast specimens are imaged and analyzed.

This study aims to determine if light scatter parameters measured with spatial frequency domain imaging (SFDI) can accurately predict stromal, epithelial, and adipose fractions in freshly resected, unstained human breast specimens. An explicit model was developed to predict stromal, epithelial, and adipose fractions as a function of light scattering parameters, which was validated against a quantitative analysis of digitized histology slides for N = 31 specimens using leave-one-out cross-fold validation. Specimen mean stromal, epithelial, and adipose volume fractions predicted from light scattering parameters strongly correlated with those calculated from digitized histology slides (r = 0.90, 0.77, and 0.91, respectively, p-value

Electromagnetic (EM) breast imaging provides low-cost, safe and potentially a more specific modality for cancer detection than conventional imaging systems. A primary difficulty in validating these EM imaging modalities is that the true dielectric property values of the particular breast being imaged are not readily available on an individual subject basis. Here, we describe our initial experience in seeking to correlate tomographic EM imaging studies with discrete point spectroscopy measurements of the dielectric properties of breast tissue. The protocol we have developed involves measurement of in vivo tissue properties during partial and full mastectomy procedures in the operating room (OR) followed by ex vivo tissue property recordings in the same locations in the excised tissue specimens in the pathology laboratory immediately after resection. We have successfully applied all of the elements of this validation protocol in a series of six women with cancer diagnoses. Conductivity and permittivity gauged from ex vivo samples over the frequency range 100 Hz–8.5 GHz are found to be similar to those reported in the literature. A decrease in both conductivity and permittivity is observed when these properties are gauged from ex vivo samples instead of in vivo. We present these results in addition to a case study demonstrating how discrete point spectroscopy measurements of the tissue can be correlated and used to validate EM imaging studies.

Introduction Nationally, 25% to 50% of patients undergoing lumpectomy for local management of breast cancer require a secondary excision because of the persistence of residual tumor. Intraoperative assessment of specimen margins by frozen-section analysis is not widely adopted in breast-conserving surgery. Here, a new approach to wide-field optical imaging of breast pathology in situ was tested to determine whether the system could accurately discriminate cancer from benign tissues before routine pathological processing. Methods Spatial frequency domain imaging (SFDI) was used to quantify near-infrared (NIR) optical parameters at the surface of 47 lumpectomy tissue specimens. Spatial frequency and wavelength-dependent reflectance spectra were parameterized with matched simulations of light transport. Spectral images were co-registered to histopathology in adjacent, stained sections of the tissue, cut in the geometry imaged in situ. A supervised classifier and feature-selection algorithm were implemented to automate discrimination of breast pathologies and to rank the contribution of each parameter to a diagnosis. Results Spectral parameters distinguished all pathology subtypes with 82% accuracy and benign (fibrocystic disease, fibroadenoma) from malignant (DCIS, invasive cancer, and partially treated invasive cancer after neoadjuvant chemotherapy) pathologies with 88% accuracy, high specificity (93%), and reasonable sensitivity (79%). Although spectral absorption and scattering features were essential components of the discriminant classifier, scattering exhibited lower variance and contributed most to tissue-type separation. The scattering slope was sensitive to stromal and epithelial distributions measured with quantitative immunohistochemistry. Conclusions SFDI is a new quantitative imaging technique that renders a specific tissue-type diagnosis. Its combination of planar sampling and frequency-dependent depth sensing is clinically pragmatic and appropriate for breast surgical-margin assessment. This study is the first to apply SFDI to pathology discrimination in surgical breast tissues. It represents an important step toward imaging surgical specimens immediately ex vivo to reduce the high rate of secondary excisions associated with breast lumpectomy procedures.

Optical spectroscopy probes increasingly have been employed for diagnostic sensing during breast conserving surgery to aid surgeons in complete resection while minimizing damage to healthy tissues; however, traditional fiber probe-based systems rely on the assumption that ultra-structural changes associated with malignancy yield disease-specific contrast in a single, volume-averaged measure. A scanning-beam spectroscopy platform was designed to efficiently realize the imaging extension of probe-based spectroscopy methods and to selectively sample the scattering response of breast surgical specimens. The imaging system employs dark-field illumination and confocal detection to rapidly sample broadband spectra at 100μm lateral resolution over a 1cm2 field of view. Optical scattering is exquisitely sensitive to the morphological features observed in pathology, the diagnostic gold standard, and has not been studied sufficiently in thick tissues in a waveband that avoids absorption. In this study, 29 fresh breast tissue specimens procured during conservative surgery were imaged and returned to pathology for standard histological processing. A protocol was developed for accurate co-registration between the imaged field and histology. Over 300,00 broadband spectra were sampled and parameterized according to an empirical approximation to Mie theory. Further, the gray-level co-occurrence matrix representation of texture features was used to mathematically represent intensity-level spatial dependence in the scattering images. Spatially, the intra and inter-patient scattering response is quite heterogeneous; but imaging accounts for this natural variance so that diagnostic classification improved. The average scattering power per 100x100 pixel field of view was sufficient to discriminate between benign and malignant pathologies with a positive and negative predictive value of 1.00 and 0.90 respectively, using a simple, threshold-based classification. As compared to classification on a per-spectrum basis, which yielded positive and negative predictive values of just 0.71 and 0.75 respectively. Further, textural features yielded discriminated between invasive and in situ carcinomas with p Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3670. doi:1538-7445.AM2012-3670

Hepatocellular carcinoma (HCC) affects over 600,000 patients worldwide and is the third leading cause of cancer-related death. Understanding signaling pathways that may be targeted for the treatment of HCC has been a major goal. A growing body of data indicates that inhibiting the type 1 insulin-like growth factor receptor (IGF-1R) might be an especially effective treatment strategy for HCC. Increased expression of IGF-2 as well as phospho-IGF-1R is observed in a subset of HCC tumors, and blockade of IGF-1R results in inhibition of proliferation for preclinical HCC cell models. OSI-906 is a small molecule dual IGF-1R/IR inhibitor currently in advanced clinical development. In this report we sought to determine the effect of OSI-906 on proliferation for a panel of 21 HCC tumor cell lines as well as to investigate molecular determinants of responsiveness to OSI-906. A subset of HCC tumor cell lines was sensitive to OSI-906 in proliferation assays. Sensitivity to OSI-906 correlated with epithelial-mesenchymal-transition (EMT) status where the majority of epithelial HCC cell lines, but none of mesenchymal cell lines, were sensitive to OSI-906. We also found differential expression of IGF axis components, including IGF-2, in epithelial and mesenchymal tumor cell lines, which correlated with sensitivity to OSI-906. Induction of EMT upon treatment with TGFβ reduced sensitivity to OSI-906. Within a human HCC tumor database, epithelial tumors were identified to be enriched in one subgroup with higher IGF2 expression. We have previously shown that both IGF-1R and IR can maintain tumor growth in a mouse mammary tumor model, and co-inhibition of both receptors is required for maximal inhibition of tumor growth. Herein, we find that OSI-906 sensitive HCC tumor cell lines expressed both phosphorylated IGF-1R and IR, and dual targeting of both receptors appears to be important for maximal inhibition of proliferation. Treatment of HuH-7 tumor cells with an IGF-1R neutralizing antibody was associated with increased IR signaling. In contrast OSI-906 fully inhibited both phosphorylated IR and IGF-1R and achieved greater inhibition of the IRS-AKT pathway compared to the IGF-1R antibody. Collectively, these data support the concept for dual IGF-1R/IR targeting HCC, where EMT status and expression of IGF-2 could be utilized to identify those patients most likely to benefit from treatment. A phase 2 clinical study evaluating OSI-906 in HCC is currently ongoing. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3150. doi:10.1158/1538-7445.AM2011-3150