Scatter spectroscopic imaging distinguishes between breast pathologies in tissues relevant to surgical margin assessment

Deformable multi-modal image registration for the correlation between optical measurements and histology images

Significance

The accurate correlation between optical measurements and pathology relies on precise image registration, often hindered by deformations in histology images. We investigate an automated multi-modal image registration method using deep learning to align breast specimen images with corresponding histology images.

Aim

We aim to explore the effectiveness of an automated image registration technique based on deep learning principles for aligning breast specimen images with histology images acquired through different modalities, addressing challenges posed by intensity variations and structural differences.

Approach

Unsupervised and supervised learning approaches, employing the VoxelMorph model, were examined using a dataset featuring manually registered images as ground truth.

Results

Evaluation metrics, including Dice scores and mutual information, demonstrate that the unsupervised model exceeds the supervised (and manual) approaches significantly, achieving superior image alignment. The findings highlight the efficacy of automated registration in enhancing the validation of optical technologies by reducing human errors associated with manual registration processes.

Conclusions

This automated registration technique offers promising potential to enhance the validation of optical technologies by minimizing human-induced errors and inconsistencies associated with manual image registration processes, thereby improving the accuracy of correlating optical measurements with pathology labels.

Point Projection Mapping System for Tracking, Registering, Labeling, and Validating Optical Tissue Measurements

The validation of newly developed optical tissue-sensing techniques for tumor detection during cancer surgery requires an accurate correlation with the histological results. Additionally, such an accurate correlation facilitates precise data labeling for developing high-performance machine learning tissue-classification models. In this paper, a newly developed Point Projection Mapping system will be introduced, which allows non-destructive tracking of the measurement locations on tissue specimens. Additionally, a framework for accurate registration, validation, and labeling with the histopathology results is proposed and validated on a case study. The proposed framework provides a more-robust and accurate method for the tracking and validation of optical tissue-sensing techniques, which saves time and resources compared to the available conventional techniques.

High-Resolution Ex Vivo Elastography to Characterize Tumor Stromal Heterogeneity In Situ in Pancreatic Adenocarcinoma

OBJECTIVE

Tumor stiffening in pancreatic adenocarcinoma (PDAC) has been linked to cancer progression and lack of therapy response, yet current elastography tools cannot map stiffness in a whole tumor field-of-view with biologically relevant spatial resolution. Therefore, this study was developed to assess stiffness heterogeneity and geometrical patterns across whole PDAC xenograft ex vivo tumors.

METHODS

The ex vivo elastography (EVE) mapping system was capable of creating stiffness map at 300-micron spatial resolution under a 5-20 mm field of view relevant to whole tumor assessment. The stiffness value at each location was determined by compression testing and an absolute tumor Young's modulus map was calculated based on the calibration between the system and ultrasound elastography (R² = 0.95).

RESULTS

Two PDAC tumor lines AsPC-1 and BxPC-3 implanted in xenograft models were assessed to show tumor stiffness and its linear relationship to collagen content (R² = 0.59). EVE was able to capture stiffness heterogeneity ranging between 5 and 100 kPa in pancreatic tumors with collagen content up to 25%. More importantly, data shows the inverse relationship of local stiffness to local drug distribution (R² = 0.66) and vessel patency (R² = 0.61) in both PDAC tumor lines.

CONCLUSION

The results suggested that elastography could be utilized to predict drug penetration in PDAC tumors or assess response to biological modifying adjunct therapies.

SIGNIFICANCE

This study presents the first attempt to map out stiffness on a biologically relevant spatial scale across whole PDAC tumor slices with spatial resolution in the hundreds of microns.

Elastic scattering spectroscopy for monitoring skin cancer transformation and therapy in the near infrared window

There is a pressing need for monitoring cancerous tissue response to laser therapy. In this work, we evaluate the viability of elastic scattering spectroscopy (ESS) to monitor malignant transformations and effects of laser therapy of induced skin cancer in a hamster model. Skin tumors were induced in 35 mice, half of which were irradiated with 980 nm laser diode. Physiological and morphological transformations in the tumor were monitored over a period of 36 weeks using elastic scattering spectroscopy, in the near infrared window. Analytical model for light scattering was used to derive scattering optical properties for both transformed tissue and laser-treated cancer. The tissue scattering over the wavelength range (700-950 nm) decreased remarkably as the carcinogen-induced tissue transformed towards higher stages. Conversely, reduced scattering coefficient noticeably increased with increasing the number of laser irradiation sessions for the treated tumors. The relative changes in elastic scattering signal for transformed tissue were significantly different (p < .05). Elastic scattering signal intensity for laser-treated tissue was also significantly different (p < .05). Reduced scattering coefficient of treated tissue exhibited nearly 80% recovery of its normal skin value at the end of the experiment, and the treatment outcome could be improved by adjusting the number of sessions, which we can predict through spectroscopic optical feedback. This study demonstrates that ESS can quantitatively provide functional information that closely corresponds to the degree of pathologic transformation. ESS may well be a viable technique to optimize systemic melanoma and non-melanoma skin cancer treatment based on noninvasive tumor response.

Structured light imaging for breast-conserving surgery, part II: texture analysis and classification

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.

Method for coregistration of optical measurements of breast tissue with histopathology: the importance of accounting for tissue deformations

For the validation of optical diagnostic technologies, experimental results need to be benchmarked against the gold standard. Currently, the gold standard for tissue characterization is assessment of hematoxylin and eosin (H&E)-stained sections by a pathologist. When processing tissue into H&E sections, the shape of the tissue deforms with respect to the initial shape when it was optically measured. We demonstrate the importance of accounting for these tissue deformations when correlating optical measurement with routinely acquired histopathology. We propose a method to register the tissue in the H&E sections to the optical measurements, which corrects for these tissue deformations. We compare the registered H&E sections to H&E sections that were registered with an algorithm that does not account for tissue deformations by evaluating both the shape and the composition of the tissue and using microcomputer tomography data as an independent measure. The proposed method, which did account for tissue deformations, was more accurate than the method that did not account for tissue deformations. These results emphasize the need for a registration method that accounts for tissue deformations, such as the method presented in this study, which can aid in validating optical techniques for clinical use.

Light scattering methods for tissue diagnosis

Light scattering has become a common biomedical research tool, enabling diagnostic sensitivity to myriad tissue alterations associated with disease. Light-tissue interactions are particularly attractive for diagnostics due to the variety of contrast mechanisms that can be used, including spectral, angle-resolved, and Fourier-domain detection. Photonic diagnostic tools offer further benefit in that they are non-ionizing, non-invasive, and give real-time feedback. In this review, we summarize recent innovations in light scattering technologies, with a focus on clinical achievements over the previous ten years.

Rapid pathology of lumpectomy margins with open-top light-sheet (OTLS) microscopy

Open-top light-sheet microscopy is a technique that can potentially enable rapid ex vivo inspection of large tissue surfaces and volumes. Here, we have optimized an open-top light-sheet (OTLS) microscope and image-processing workflow for the comprehensive examination of surgical margin surfaces, and have also developed a novel fluorescent analog of H&E staining that is robust for staining fresh unfixed tissues. Our tissue-staining method can be achieved within 2.5 minutes followed by OTLS microscopy of lumpectomy surfaces at a rate of up to 1.5 cm2/minute. An image atlas is presented to show that OTLS image quality surpasses that of intraoperative frozen sectioning and can approximate that of gold-standard H&E histology of formalin-fixed paraffin-embedded (FFPE) tissues. Qualitative evidence indicates that these intraoperative methods do not interfere with downstream post-operative H&E histology and immunohistochemistry. These results should facilitate the translation of OTLS microscopy for intraoperative guidance of lumpectomy and other surgical oncology procedures.

On the spectral signature of melanoma: a non-parametric classification framework for cancer detection in hyperspectral imaging of melanocytic lesions

Early detection and diagnosis is a must in secondary prevention of melanoma and other cancerous lesions of the skin. In this work, we present an online, reservoir-based, non-parametric estimation and classification model that allows for this functionality on pigmented lesions, such that detection thresholding can be tuned to maximize accuracy and/or minimize overall false negative rates. This system has been tested in a dataset consisting of 116 patients and a total of 124 hyperspectral images of nevi, raised nevi and melanomas, detecting up to 100% of the suspicious lesions at the expense of some false positives.

Light scattering measured with spatial frequency domain imaging can predict stromal versus epithelial proportions in surgically resected breast tissue

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 <1  ×  10  -  6). Additionally, the ratio of predicted epithelium to stroma classified malignant specimens with a sensitivity and specificity of 90% and 81%, respectively, and also classified all pixels in malignant lesions with 63% and 79%, at a threshold of 1. All specimens and pixels were classified as malignant, benign, or fat with 84% and 75% accuracy, respectively. These findings demonstrate how light scattering parameters acquired with SFDI can be used to accurately predict and spatially map stromal, epithelial, and adipose proportions in fresh unstained, human breast tissue, and suggest that these estimations could provide diagnostic value.

Microvascular fractal dimension predicts prognosis and response to chemotherapy in glioblastoma: an automatic image analysis study

The microvascular profile has been included in the WHO glioma grading criteria. Nevertheless, microvessels in gliomas of the same WHO grade, e.g., WHO IV glioblastoma (GBM), exhibit heterogeneous and polymorphic morphology, whose possible clinical significance remains to be determined. In this study, we employed a fractal geometry-derived parameter, microvascular fractal dimension (mvFD), to quantify microvessel complexity and developed a home-made macro in Image J software to automatically determine mvFD from the microvessel-stained immunohistochemical images of GBM. We found that mvFD effectively quantified the morphological complexity of GBM microvasculature. Furthermore, high mvFD favored the survival of GBM patients as an independent prognostic indicator and predicted a better response to chemotherapy of GBM patients. When investigating the underlying relations between mvFD and tumor growth by deploying Ki67/mvFD as an index for microvasculature-normalized tumor proliferation, we discovered an inverse correlation between mvFD and Ki67/mvFD. Furthermore, mvFD inversely correlated with the expressions of a glycolytic marker, LDHA, which indicated poor prognosis of GBM patients. Conclusively, we developed an automatic approach for mvFD measurement, and demonstrated that mvFD could predict the prognosis and response to chemotherapy of GBM patients.

Calibration and analysis of a multimodal micro-CT and structured light imaging system for the evaluation of excised breast tissue

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.

Monochromatic subdiffusive spatial frequency domain imaging provides in-situ sensitivity to intratumoral morphological heterogeneity in a murine model

For the first time, spatially resolved quantitative metrics of light scattering recovered with sub-diffusive spatial frequency domain imaging (sd-SFDI) are shown to be sensitive to changes in intratumoral morphology and viability by direct comparison to histopathological analysis. Two freshly excised subcutaneous murine tumor cross-sections were measured with sd-SFDI, and recovered optical scatter parameter maps were co-registered to whole mount histology. Unique clustering of the optical scatter parameters μs' vs. γ (i.e. diffuse scattering vs. relative backscattering) evaluated at a single wavelength showed complete separation between regions of viable tumor, aggresive tumor with stromal growth, varying levels of necrotic tumor, and also peritumor muscle. The results suggest that with further technical development, sd-SFDI may represent a non-destructive screening tool for analysis of excised tissue or a non-invasive approach to investigate suspicious lesions without the need for exogenous labels or spectrally resolved imaging.

Directional Kernel Density Estimation for Classification of Breast Tissue Spectra

In Breast Conserving Therapy, surgeons measure the thickness of healthy tissue surrounding an excised tumor (surgical margin) via post-operative histological or visual assessment tests that, for lack of enough standardization and reliability, have recurrence rates in the order of 33%. Spectroscopic interrogation of these margins is possible during surgery, but algorithms are needed for parametric or dimension reduction processing. One methodology for tumor discrimination based on dimensionality reduction and nonparametric estimation-in particular, Directional Kernel Density Estimation-is proposed and tested on spectral image data from breast samples. Once a hyperspectral image of the tumor has been captured, a surgeon assists by establishing Regions of Interest where tissues are qualitatively differentiable. After proper normalization, Directional KDE is used to estimate the likelihood of every pixel in the image belonging to each specified tissue class. This information is enough to yield, in almost real time and with 98% accuracy, results that coincide with those provided by histological H&E validation performed after the surgery.

Review: in vivo optical spectral tissue sensing-how to go from research to routine clinical application?

Innovations in optical spectroscopy have helped the technology reach a point where performance previously seen only in laboratory settings can be translated and tested in real-world applications. In the field of oncology, spectral tissue sensing (STS) by means of optical spectroscopy is considered to have major potential for improving diagnostics and optimizing treatment outcome. The concept has been investigated for more than two decades and yet spectral tissue sensing is not commonly employed in routine medical practice. It is therefore important to understand what is needed to translate technological advances and insights generated through basic scientific research in this field into clinical practice. The aim of the discussion presented here is not to provide a comprehensive review of all work published over the last decades but rather to highlight some of the challenges found in literature and encountered by our group in the quest to translate optical technologies into useful clinical tools. Furthermore, an outlook is proposed on how translational researchers could proceed to eventually have STS incorporated in the process of clinical decision-making.

Feasibility of spatial frequency domain imaging (SFDI) for optically characterizing a preclinical oncology model

Determination of chemotherapy efficacy early during treatment would provide more opportunities for physicians to alter and adapt treatment plans. Diffuse optical technologies may be ideally suited to track early biological events following chemotherapy administration due to low cost and high information content. We evaluated the use of spatial frequency domain imaging (SFDI) to characterize a small animal tumor model in order to move towards the goal of endogenous optical monitoring of cancer therapy in a controlled preclinical setting. The effects of key measurement parameters including the choice of imaging spatial frequency and the repeatability of measurements were evaluated. The precision of SFDI optical property extractions over repeat mouse measurements was determined to be within 3.52% for move and replace experiments. Baseline optical properties and chromophore values as well as intratumor heterogeneity were evaluated over 25 tumors. Additionally, tumor growth and chemotherapy response were monitored over a 45 day longitudinal study in a small number of mice to demonstrate the ability of SFDI to track treatment effects. Optical scattering and oxygen saturation increased as much as 70% and 25% respectively in treated tumors, suggesting SFDI may be useful for preclinical tracking of cancer therapies.

Uniqueness in multispectral constant-wave epi-illumination imaging

Multispectral tissue imaging based on optical cameras and continuous-wave tissue illumination is commonly used in medicine and biology. Surprisingly, there is a characteristic absence of a critical look at the quantities that can be uniquely characterized from optically diffuse matter by multispectral imaging. Here, we investigate the fundamental question of uniqueness in epi-illumination measurements from turbid media obtained at multiple wavelengths. By utilizing an analytical model, tissue-mimicking phantoms, and an in vivo imaging experiment we show that independent of the bands employed, spectral measurements cannot uniquely retrieve absorption and scattering coefficients. We also establish that it is, nevertheless, possible to uniquely quantify oxygen saturation and the Mie scattering power-a previously undocumented uniqueness condition.

Wide-field quantitative imaging of tissue microstructure using sub-diffuse spatial frequency domain imaging

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.

Noninvasive assessment of hemodynamic and brain metabolism parameters following closed head injury in a mouse model by comparative diffuse optical reflectance approaches

Optical techniques have gained substantial interest over the past four decades for biomedical imaging due to their unique advantages, which may suggest their use as alternatives to conventional methodologies. Several optical techniques have been successfully adapted to clinical practice and biomedical research to monitor tissue structure and function in both humans and animal models. This paper reviews the analysis of the optical properties of brain tissue in the wavelength range between 500 and 1000 nm by three different diffuse optical reflectance methods: spatially modulated illumination, orthogonal diffuse light spectroscopy, and dual-wavelength laser speckle imaging, to monitor changes in brain tissue morphology, chromophore content, and metabolism following head injury. After induction of closed head injury upon anesthetized mice by weight-drop method, significant changes in hemoglobin oxygen saturation, blood flow, and metabolism were readily detectible by all three optical setups, up to 1 h post-trauma. Furthermore, the experimental results clearly demonstrate the feasibility and reliability of the three methodologies, and the differences between the system performances and capabilities are also discussed. The long-term goal of this line of study is to combine these optical systems to study brain pathophysiology in high spatiotemporal resolution using additional models of brain trauma. Such combined use of complementary algorithms should fill the gaps in each system's capabilities, toward the development of a noninvasive, quantitative tool to expand our knowledge of the principles underlying brain function following trauma, and to monitor the efficacy of therapeutic interventions in the clinic.

Spectrally encoded confocal microscopy for diagnosing breast cancer in excision and margin specimens

A large percentage of breast cancer patients treated with breast conserving surgery need to undergo multiple surgeries due to positive margins found during post-operative margin assessment. Carcinomas could be removed completely during the initial surgery and additional surgery avoided if positive margins can be determined intraoperatively. Spectrally encoded confocal microscopy (SECM) is a high-speed reflectance confocal microscopy technology that has a potential to rapidly image the entire surgical margin at subcellular resolution and accurately determine margin status intraoperatively. In this study, in order to test the feasibility of using SECM for intraoperative margin assessment, we have evaluated the diagnostic accuracy of SECM for detecting various types of breast cancers. Forty-six surgically removed breast specimens were imaged with an SECM system. Side-by-side comparison between SECM and histologic images showed that SECM images can visualize key histomorphologic patterns of normal/benign and malignant breast tissues. Small (500 μm × 500 μm) spatially registered SECM and histologic images (n=124 for each) were diagnosed independently by three pathologists with expertise in breast pathology. Diagnostic accuracy of SECM for determining malignant tissues was high, average sensitivity of 0.91, specificity of 0.93, positive predictive value of 0.95, and negative predictive value of 0.87. Intra-observer agreement and inter-observer agreement for SECM were also high, 0.87 and 0.84, respectively. Results from this study suggest that SECM may be developed into an intraoperative margin assessment tool for guiding breast cancer excisions.

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.

Spectral discrimination of breast pathologies in situ using spatial frequency domain imaging

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.

Sub-diffusive scattering parameter maps recovered using wide-field high-frequency structured light imaging

This study investigates the hypothesis that structured light reflectance imaging with high spatial frequency patterns [Formula: see text] can be used to quantitatively map the anisotropic scattering phase function distribution [Formula: see text] in turbid media. Monte Carlo simulations were used in part to establish a semi-empirical model of demodulated reflectance ([Formula: see text]) in terms of dimensionless scattering [Formula: see text] and [Formula: see text], a metric of the first two moments of the [Formula: see text] distribution. Experiments completed in tissue-simulating phantoms showed that simultaneous analysis of [Formula: see text] spectra sampled at multiple [Formula: see text] in the frequency range [0.05-0.5] [Formula: see text] allowed accurate estimation of both [Formula: see text] in the relevant tissue range [0.4-1.8] [Formula: see text], and [Formula: see text] in the range [1.4-1.75]. Pilot measurements of a healthy volunteer exhibited [Formula: see text]-based contrast between scar tissue and surrounding normal skin, which was not as apparent in wide field diffuse imaging. These results represent the first wide-field maps to quantify sub-diffuse scattering parameters, which are sensitive to sub-microscopic tissue structures and composition, and therefore, offer potential for fast diagnostic imaging of ultrastructure on a size scale that is relevant to surgical applications.

MarginProbe: intraoperative margin assessment during breast conserving surgery by using radiofrequency spectroscopy

In breast conserving surgery, the tumor should be removed with a clean margin, a rim of healthy tissue surrounding. Failure to achieve clean margins in the initial surgery results in a re-excision procedure. Re-excision rates are reported as being 11-46% for invasive carcinoma and ductal carcinoma in situ (DCIS). Re-excisions can have negative consequences such as increased postoperative infections, negative impact on cosmesis, patient anxiety and increased medical costs. Therefore, the surgical margin of invasive and intraductal (DCIS) breast tissue is a subject of intense discussion. Different options for intraoperative assessment are available, but all in all, they are unsatisfying. Frozen section margin examination is possible but is time consuming and restricted to the assessment of invasive carcinoma. In the case of DCIS, there is no procedure for intraoperative margin assessment. Thus, a solution for efficient intraoperative surgical margin assessment is needed. For this purpose, an innovative, real-time, intraoperative margin-assessment device (MarginProbe, Dune Medical Devices, Caesarea, Israel) was designed, and recent published clinical data reported a reduction of re-excisions by more than 50%.

Structured light scatteroscopy

A new imaging approach, structured light scatteroscopy (SLS), is demonstrated, which offers rapid wide-field imaging of microscopic morphological variations in bulk tissue surfaces. Elastic scattering of light offers exquisite sensitivity to ultrastructural changes at multiple size scales ranging from nanometers to millimeters, but in bulk tissues the confounding effects of molecular absorption and strong multiple scattering of light often lead to a dramatic reduction in scatter contrast and specificity. It is demonstrated that the SLS using structured high spatial frequency illumination and detection to probe the tissue achieves direct, absorption-independent, high-resolution maps of the scattering response. The scattering response is observed to be dependent on both the wavelength and spatial frequency of choice, indicating a potential for multiscale probing of ultrastructural changes in superficial tissue layers. This methodology can be easily applied in most wide-field imaging systems.

The emerging role of the molecular diagnostics laboratory in breast cancer personalized medicine

Breast cancer is a complex disease characterized by many morphological, clinical, and molecular features. For many years, breast cancer has been classified according to traditional parameters, such as histological type, grade, tumor size, lymph node involvement and vascular invasion, and biomarkers (eg, estrogen receptor, progesterone receptor, and epidermal growth factor receptor 2), which are used in patient management. With emerging imaging techniques (ie, digital mammography, tomosynthesis, ultrasonography, magnetic resonance imaging, nuclear medicine, and genomic techniques, such as real-time RT-PCR and microarrays), breast cancer diagnostics is going through a significant evolution. Imaging technologies have improved breast cancer diagnosis, survival, and treatment by early detection of primary or metastatic lesions, differentiating benign from malignant lesions and promoting intraoperative surgical guidance and postoperative specimen evaluation. Genomic and transcriptomic technologies make the analysis of gene expression signatures and mutation status possible so that tumors may be classified more accurately with respect to diagnosis and prognosis. The -omic era has also made possible the identification of new biomarkers involved in breast cancer development, survival, and invasion that can be gradually incorporated into clinical testing. These advances in both imaging and genomics contribute to more personalized and predictive patient management. We review the progress made in breast cancer diagnosis and management using these new tools.

Optical spectral surveillance of breast tissue landscapes for detection of residual disease in breast tumor margins

We demonstrate a strategy to “sense” the micro-morphology of a breast tumor margin over a wide field of view by creating quantitative hyperspectral maps of the tissue optical properties (absorption and scattering), where each voxel can be deconstructed to provide information on the underlying histology. Information about the underlying tissue histology is encoded in the quantitative spectral information (in the visible wavelength range), and residual carcinoma is detected as a shift in the histological landscape to one with less fat and higher glandular content. To demonstrate this strategy, fully intact, fresh lumpectomy specimens (n = 88) from 70 patients were imaged intra-operatively. The ability of spectral imaging to sense changes in histology over large imaging areas was determined using inter-patient mammographic breast density (MBD) variation in cancer-free tissues as a model system. We discovered that increased MBD was associated with higher baseline β-carotene concentrations (p = 0.066) and higher scattering coefficients (p = 0.007) as measured by spectral imaging, and a trend toward decreased adipocyte size and increased adipocyte density as measured by histological examination in BMI-matched patients. The ability of spectral imaging to detect cancer intra-operatively was demonstrated when MBD-specific breast characteristics were considered. Specifically, the ratio of β-carotene concentration to the light scattering coefficient can report on the relative amount of fat to glandular density at the tissue surface to determine positive margin status, when baseline differences in these parameters between patients with low and high MBD are taken into account by the appropriate selection of threshold values. When MBD was included as a variable a priori, the device was estimated to have a sensitivity of 74% and a specificity of 86% in detecting close or positive margins, regardless of tumor type. Superior performance was demonstrated in high MBD tissue, a population that typically has a higher percentage of involved margins.

Direct identification of breast cancer pathologies using blind separation of label-free localized reflectance measurements

Breast tumors are blindly identified using Principal (PCA) and Independent Component Analysis (ICA) of localized reflectance measurements. No assumption of a particular theoretical model for the reflectance needs to be made, while the resulting features are proven to have discriminative power of breast pathologies. Normal, benign and malignant breast tissue types in lumpectomy specimens were imaged ex vivo and a surgeon-guided calibration of the system is proposed to overcome the limitations of the blind analysis. A simple, fast and linear classifier has been proposed where no training information is required for the diagnosis. A set of 29 breast tissue specimens have been diagnosed with a sensitivity of 96% and specificity of 95% when discriminating benign from malignant pathologies. The proposed hybrid combination PCA-ICA enhanced diagnostic discrimination, providing tumor probability maps, and intermediate PCA parameters reflected tissue optical properties.

System analysis of spatial frequency domain imaging for quantitative mapping of surgically resected breast tissues

The feasibility of spatial frequency domain imaging (SFDI) for breast surgical margin assessment was evaluated in tissue-simulating phantoms and in fully intact lumpectomy specimens at the time of surgery. Phantom data was evaluated according to contrast-detail resolution, quantitative accuracy and model-data goodness of fit, where optical parameters were estimated by minimizing the residual sum of squares between the measured modulation amplitude and its solutions, modeled according to diffusion and scaled-Monte Carlo simulations. In contrast-detail phantoms, a 1.25-mm-diameter surface inclusion was detectable for scattering contrast >28%; a fraction of this scattering contrast (7%) was detectable for a 10 mm surface inclusion and at least 33% scattering contrast was detected up to 1.5 mm below the phantom surface, a probing depth relevant to breast surgical margin assessment. Recovered hemoglobin concentrations were insensitive to changes in scattering, except for overestimation at visible wavelengths for total hemoglobin concentrations <15  μM. The scattering amplitude increased linearly with scattering concentration, but the scattering slope depended on both the particle size and number density. Goodness of fit was comparable for the diffusion and scaled-Monte Carlo models of transport in spatially modulated, near-infrared reflectance acquired from 47 lumpectomy tissues, but recovered absorption parameters varied more linearly with expected hemoglobin concentration in liquid phantoms for the scaled-Monte Carlo forward model. SFDI could potentially reduce the high secondary excision rate associated with breast conserving surgery; its clinical translation further requires reduced image reconstruction time and smart inking strategies.

Real-time pathology to guide breast surgery: seeing alone is not believing

Tissue diagnostic techniques based on optical spectroscopy, in various incarnations, are approaching clinical reality for intraoperative guidance of surgical procedures. Examination of tissue properties by elastic light-scattering spectroscopy may constitute a preferable alternative to frozen-section pathology or touch imprint cytology for intraoperative assessment of resection margins during breast-conserving surgery.