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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. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.

Significance: Current imaging paradigms for differential diagnosis of suspicious breast lesions suffer from high false positive rates that force patients to undergo unnecessary biopsies. Diffuse optical spectroscopic imaging (DOSI) noninvasively probes functional hemodynamic and compositional parameters in deep tissue and has been shown to be sensitive to contrast between normal and malignant tissues. Aim: DOSI methods are under investigation as an adjunct to mammography and ultrasound that could reduce false positive rates and unnecessary biopsies, particularly in radiographically dense breasts. Methods: We performed a retrospective analysis of 212 subjects with suspicious breast lesions who underwent DOSI imaging. Physiological tissue parameters were z-score normalized to the patient’s contralateral breast tissue and input to univariate logistic regression models to discriminate between malignant tumors and the surrounding normal tissue. The models were then used to differentiate malignant lesions from benign lesions. Results: Models incorporating several individual hemodynamic parameters were able to accurately distinguish malignant tumors from both the surrounding background tissue and benign lesions with area under the curve (AUC) ≥0.85. Z-score normalization improved the discriminatory ability and calibration of these predictive models relative to unnormalized or ratio-normalized data. Conclusions: Findings from a large subject population study show how DOSI data normalization that accounts for normal tissue heterogeneity and quantitative statistical regression approaches can be combined to improve the ability of DOSI to diagnose malignant lesions. This improved diagnostic accuracy, combined with the modality’s inherent logistical advantages of portability, low cost, and nonionizing radiation, could position DOSI as an effective adjunct modality that could be used to reduce the number of unnecessary invasive biopsies.

Significance: Diffuse optical imaging (DOI) provides in vivo quantification of tissue chromophores such as oxy- and deoxyhemoglobin (HbO2 and HHb, respectively). These parameters have been shown to be useful for predicting neoadjuvant treatment response in breast cancer patients. However, most DOI devices designed for the breast are nonportable, making frequent longitudinal monitoring during treatment a challenge. Furthermore, hemodynamics related to the respiratory cycle are currently unexplored in the breast and may have prognostic value. Aim: To design, fabricate, and validate a high optode-density wearable continuous wave diffuse optical probe for the monitoring of breathing hemodynamics in breast tissue. Approach: The probe has a rigid-flex design with 16 dual-wavelength sources and 16 detectors. Performance was characterized on tissue-simulating phantoms, and validation was performed through flow phantom and cuff occlusion measurements. The breasts of N = 4 healthy volunteers were measured while performing a breathing protocol. Results: The probe has 512 unique source-detector (S-D) pairs that span S-D separations of 10 to 54 mm. It exhibited good performance characteristics: ma drift of 0.34%/h, ma precision of 0.063%, and mean SNR > 24 dB up to 41 mm S-D separation. Absorption contrast was detected in flow phantoms at depths exceeding 28 mm. A cuff occlusion measurement confirmed the ability of the probe to track expected hemodynamics in vivo. Breast measurements on healthy volunteers during paced breathing revealed median signal-to-motion artifact ratios ranging from 8.1 to 8.7 dB. Median DHbO2 and DHHb amplitudes ranged from 0.39 to 0.67 mM and 0.08 to 0.12 mM, respectively. Median oxygen saturations at the respiratory rate ranged from 82% to 87%. Conclusions: A wearable diffuse optical probe has been designed and fabricated for the measurement of breast tissue hemodynamics. This device is capable of quantifying breathing-related hemodynamics in healthy breast tissue.

Significance: Re-excision rates for women with invasive breast cancer undergoing breast conserving surgery (or lumpectomy) have decreased in the past decade but remain substantial. This is mainly due to the inability to assess the entire surface of an excised lumpectomy specimen efficiently and accurately during surgery. Aim: The goal of this study was to develop a deep-ultraviolet scanning fluorescence microscope (DUV-FSM) that can be used to accurately and rapidly detect cancer cells on the surface of excised breast tissue. Approach: A DUV-FSM was used to image the surfaces of 47 (31 malignant and 16 normal/benign) fresh breast tissue samples stained in propidium iodide and eosin Y solutions. A set of fluorescence images were obtained from each sample using low magnification (4×) and fully automated scanning. The images were stitched to form a color image. Three nonmedical evaluators were trained to interpret and assess the fluorescence images. Nuclear–cytoplasm ratio (N/C) was calculated and used for tissue classification. Results: DUV-FSM images a breast sample with subcellular resolution at a speed of 1.0 min/cm2. Fluorescence images show excellent visual contrast in color, tissue texture, cell density, and shape between invasive carcinomas and their normal counterparts. Visual interpretation of fluorescence images by nonmedical evaluators was able to distinguish invasive carcinoma from normal samples with high sensitivity (97.62%) and specificity (92.86%). Using N/C alone was able to differentiate patch-level invasive carcinoma from normal breast tissues with reasonable sensitivity (81.5%) and specificity (78.5%). Conclusions: DUV-FSM achieved a good balance between imaging speed and spatial resolution with excellent contrast, which allows either visual or quantitative detection of invasive cancer cells on the surfaces of a breast surgical specimen.

Objective: We investigated the effectiveness of a self-help intervention named PERANTARA, which aims to improve adherence to diagnostic procedures among women with breast cancer (BC) symptoms to reduce the time to a definitive diagnosis. Methods: With a cluster randomized crossover design across four hospitals, PERANTARA and treatment as usual (TAU) or TAU only was provided at successive periods in a randomly determined order. The main outcome was the time between the first medical consultation and the definitive diagnosis. Secondary outcomes were BC knowledge, measured by the Breast Cancer Knowledge Test (BCKT); symptoms of anxiety and depression, measured by the Hospital Anxiety and Depression Scale (HADS); quality of life, measured by the World Health Organization Quality of Life-BREF (WHOQOL-BREF); and health status, measured by the EQ-5D-5L. A linear mixed model analysis was conducted to analyse the outcomes. Results: We recruited 132 women with BC symptoms from four hospitals; 67 participants were in the intervention group, and 65 participants were in the control group. PERANTARA reduced the time to definitive diagnosis by 13.3 days (M [SD]: 25.90 [23.20] in the intervention group vs 39.29 [35.10] in the control group; mean difference = −13.26, 95% CI = −24.51 to −2.00, P =.02). No significant difference was found between the groups in BC knowledge, symptoms of anxiety, depression, quality of life, or health status. Conclusions: PERANTARA reduced the time to definitive diagnosis among Indonesian women with BC symptoms. Psychoeducation may be an important addition to regular BC care to prevent undue delays in diagnostic procedures.

Multiphoton microscopy provides a suitable technique for imaging biological tissues with submicrometer resolution. Usually a Gaussian beam (GB) is used for illumination, leading to a reduced power efficiency in the multiphoton response and vignetting for a square-shaped imaging area. A flat-top beam (FTB) provides a uniform spatial intensity distribution that equalizes the probability of a multiphoton effect across the imaging area. We employ a customized widefield multiphoton microscope to compare the performance of a square-shaped FTB illumination with that based on using a GB, for both two-photon fluorescence (TPF) and second-harmonic generation (SHG) imaging. The variation in signal-to-noise ratio across TPF images of fluorescent dyes spans ∼5.6 dB for the GB and ∼1.2 dB for the FTB illumination, respectively. For the GB modality, TPF images of mouse colon and Convallaria root, and SHG images of chicken tendon and human breast biopsy tissue showcase ∼20% area that are not imaged due to either insufficient or lack of illumination. For quantitative analysis that depends on the illuminated area, this effect can potentially lead to inaccuracies. This work emphasizes the applicability of FTB illumination to multiphoton applications.

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

Opto-acoustic imaging involves using light to produce sound waves for visualizing blood in biological tissue. By using multiple optical wavelengths, diagnostic images of blood oxygen saturation and total hemoglobin are generated using endogenous optical contrast, without injection of any external contrast agent and without using any ionizing radiation. The technology has been used in recent clinical studies for diagnosis of breast cancer to help distinguish benign from malignant lesions, potentially reducing the need for biopsy through improved diagnostic imaging accuracy. To enable this application, techniques for mapping oxygen saturation differences within tissue are necessary. Using biologically relevant opto-acoustic phantoms, we analyze the ability of an opto-acoustic imaging system to display colorized parametric maps that are generated using a statistical mapping approach. To mimic breast tissue, a material with closely matching properties for optical absorption, optical scattering, acoustic attenuation, and speed of sound is used. The phantoms include two vessels filled with whole blood at oxygen saturation levels determined using a sensor-based approach. A flow system with gas-mixer and membrane oxygenator adjusts the oxygen saturation of each vessel independently. Datasets are collected with an investigational Imagio® breast imaging system. We examine the ability to distinguish vessels as the oxygen saturation level and imaging depth are varied. At depth of 15 mm and hematocrit of 42%, a sufficient level of contrast to distinguish between two 1.6-mm diameter vessels was measured for an oxygen saturation difference of ∼4.6%. In addition, an oxygenated vessel was visible at a depth of 48 mm using an optical wavelength of 1064 nm, and a deoxygenated vessel was visible to a depth of 42 mm with 757 nm. The results provide insight toward using color mapped opto-acoustic images for diagnosing breast cancer.

Relatively few imaging and sensing technologies are employed to study human lactation physiology. In particular, human mammary development during pregnancy as well as mammary involution after lactation have been poorly described, despite their importance for breast cancer diagnosis and treatment during these phases. Our case study shows the potential of diffuse optical spectroscopic imaging (DOSI) to uniquely study the spatiotemporal changes in mammary tissue composition during the involution of the lactating breast toward its pre-pregnant state. At nine time intervals over a period of eight months after the cessation of breastfeeding, we reconstructed 2-D maps of mammary water content, lipid content, total hemoglobin (THb) concentration, oxygen saturation (StO2), and tissue optical scattering. Mammary lipid content in the nonareolar region showed a significant relative increase of 59%, whereas water content and THb concentration showed a significant relative decrease of 50% and 48%, respectively. Significant changes were also found in StO2 and tissue optical scattering. Our findings are consistent with the gradual replacement of fibroglandular tissue by adipose tissue and vascular regression during mammary involution. Moreover, our data provide unique insight into the dynamics of breast tissue composition and demonstrate the effectiveness of DOSI as a technique to study human lactation physiology.

We propose a new intrinsic cancer marker in fixed tissue biopsy slides, which is based on the local spatial autocorrelation length obtained from quantitative phase images. The spatial autocorrelation length in a small region of the tissue phase image is sensitive to the nanoscale cellular morphological alterations and can hence inform on carcinogenesis. Therefore, this metric can potentially be used as an intrinsic cancer marker in histopathology. Typically, these correlation length maps are calculated by computing 2D Fourier transforms over image sub-regions – requiring long computational times. In this paper, we propose a more time efficient method of computing the correlation map and demonstrate its value for diagnosis of benign and malignant breast tissues. Our methodology is based on highly sensitive quantitative phase imaging data obtained by spatial light interference microscopy (SLIM).

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.

Intraoperative margin assessment is imperative to cancer cure but is a continued challenge to successful surgery. Breast conserving surgery is a relevant example, where a cosmetically improved outcome is gained over mastectomy, but re-excision is required in >25% of cases due to positive or closely involved margins. Clinical translation of margin assessment modalities that must directly contact the patient or required administered contrast agents are time consuming and costly to move from bench to bedside. Tumor resections provide a unique surgical opportunity to deploy margin assessment technologies including contrast agents on the resected tissues, substantially shortening the path to the clinic. However, staining of resected tissues is plagued by nonspecific uptake. A ratiometric imaging approach where matched targeted and untargeted probes are used for staining has demonstrated substantially improved biomarker quantification over staining with conventional targeted contrast agents alone. Our group has developed an antibody-based ratiometric imaging technology using fluorescently labeled, spectrally distinct targeted and untargeted antibody probes termed dual-stain difference specimen imaging (DDSI). Herein, the targeted biomarker expression level and pattern are evaluated for their effects on DDSI diagnostic potential. Epidermal growth factor receptor expression level was correlated to DDSI diagnostic potential, which was found to be robust to spatial pattern expression variation. These results highlight the utility of DDSI for accurate margin assessment of freshly resected tumor specimens.

Intraoperative assessment of breast surgical margins will be of value for reducing the rate of re-excision surgeries for lumpectomy patients. While frozen-section histology is used for intraoperative guidance of certain cancers, it provides limited sampling of the margin surface (typically

Physiological fluctuations are expected to be a dominant source of noise in blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) experiments to assess tumour oxygenation and angiogenesis. This work investigates the impact of various physiological noise regressors: retrospective image correction (RETROICOR), heart rate (HR) and respiratory volume per unit time (RVT), on signal variance and the detection of BOLD contrast in the breast in response to a modulated respiratory stimulus. BOLD MRI was performed at 3 T in ten volunteers at rest and during cycles of oxygen and carbogen gas breathing. RETROICOR was optimized using F-tests to determine which cardiac and respiratory phase terms accounted for a significant amount of signal variance. A nested regression analysis was performed to assess the effect of RETROICOR, HR and RVT on the model fit residuals, temporal signal-to-noise ratio, and BOLD activation parameters. The optimized RETROICOR model accounted for the largest amount of signal variance (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$ \Delta R_{\text{adj}}^{2}$ \end{document}ΔRadj2 = 3.3 ± 2.1%) and improved the detection of BOLD activation (P = 0.002). Inclusion of HR and RVT regressors explained additional signal variance, but had a negative impact on activation parameter estimation (P

Imaging Cherenkov emission during radiotherapy permits real-time visualization of external beam delivery on superficial tissue. This signal is linear with absorbed dose in homogeneous media, indicating potential for quantitative dosimetry. In humans, the inherent heterogeneity of tissue optical properties (primarily from blood and skin pigment) distorts the linearity between detected Cherenkov signal and absorbed dose. We examine the potential to correct for superficial vasculature using spatial frequency domain imaging (SFDI) to map tissue optical properties for large fields of view. In phantoms, applying intensity corrections to simulate blood vessels improves Cherenkov image (CI) negative contrast by 24% for a vessel 1.9-mm-in diameter. In human trials, SFDI and CI are acquired for women undergoing whole breast radiotherapy. Applied corrections reduce heterogeneity due to vasculature within the sampling limits of the SFDI from a 22% difference as compared to the treatment plan, down to 6% in one region and from 14% down to 4% in another region. The optimal use for this combined imaging system approach is to correct for small heterogeneities such as superficial blood vessels or for interpatient variations in blood/melanin content such that the corrected CI more closely represents the surface dose delivered.

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

Introduction Non-epithelial breast malignancies include primary lymphomas, sarcomas, haematological malignancies, melanomas as well as secondary metastases to the breast. They account for less than 1% of all breast tumours. The demographics and clinical features are similar to epithelial breast cancers but the prognosis and management options are often very different. Most reported series are small with limited follow-up. The main aim of this study was to review our experience for these malignancies and to compare this with the published literature. Methods A 14-year retrospective review of all breast resection specimens was completed in the Antrim Area Hospital Cancer Unit. Clinical records of patients diagnosed with non-epithelial breast malignancies were then reviewed for data regarding patient demographics, clinical presentation, pre-operative investigations, operative findings and outcome. Pathology reports were examined carefully for tumour type, location and for evidence of lymphovascular spread. This data was compared with the available literature. Results Nineteen (F = 16) patients were found to have non-epithelial breast malignancies between April 1994 and August 2007. Mean age was 61.6 years (range 25–86). 17 patients (89.5%) presented with a palpable lump, mastalgia or skin change, while 2 (10.5%) patients' tumours were detected through screening. The histological types of non-epithelial malignancies were as follows: lymphoma (n = 8; M = 1 and F = 7, mean age: 68.5 range 52–86), sarcoma (n = 5; M = 1 and F = 4, mean age 56.4 range 29–69), malignant melanoma (n = 3; M = 1 and F = 2, mean age 54.3 range 25–70), multiple myeloma (n = 1; F, 71), metastatic renal cell carcinoma (n = 1; F, 63) and metastatic carcinoid tumour (n = 1; F, 52). The mean follow-up was 1541 days (32–4589 days). Nine patients were alive at the end of follow-up. Only 1 of 11 deaths was not directly related to the malignancy. The average time from surgery to death was 798.5 days (range 32–3248 days). Conclusion Non-epithelial breast malignancies are rare cancers with significant mortality rates. Correct diagnosis and avoidance of inappropriate therapies requires a comprehensive triple assessment and a multidisciplinary management approach.

The process of proteolysis is important at several stages of the metastatic cascade. A balance between the expression of the genes encoding endogenous proteinases and inhibitors exists and when the production of proteinases exceeds that of inhibitors proteolysis occurs.To determine whether differences in the profile and activity of proteinases and inhibitors exist within breast tumour tissue (n = 51), surrounding background breast tissue (n = 43), normal breast tissue from breast reduction mammoplasty operations (n = 10), and cells of the breast cancer cell line, MCF-7.Proteinase (matrix metalloproteinase 1 (MMP-1), MMP-2, MMP-3, MMP-9, urokinase-type plasminogen activator (uPA), and tissue-type PA (tPA)) and inhibitor (tissue inhibitor of metalloproteinases; TIMP-1 and TIMP-2) expression and proteinase activity were compared using substrate zymography, western blotting, immunohistochemistry, and quenched fluorescent substrate hydrolysis.The presence of all proteinases and inhibitors was greater in breast tumour tissue when compared with all other types of breast tissue (p0.05). The activity of total MMPs as determined by quenched fluorescent substrate hydrolysis was also greater in breast tumours (p0.05).There is increased proteolysis in human breast tumours when compared with other breast tissues.

Virtual clinical trials (VCTs) can be used to evaluate and optimise medical imaging systems. VCTs are based on computer simulations of human anatomy, imaging modalities and image interpretation. OpenVCT is an open-source framework for conducting VCTs of medical imaging, with a particular focus on breast imaging. The aim of this paper was to evaluate the OpenVCT framework in two tasks involving digital breast tomosynthesis (DBT). First, VCTs were used to perform a detailed comparison of virtual and clinical reading studies for the detection of lesions in digital mammography and DBT. Then, the framework was expanded to include mechanical imaging (MI) and was used to optimise the novel combination of simultaneous DBT and MI. The first experiments showed close agreement between the clinical and the virtual study, confirming that VCTs can predict changes in performance of DBT accurately. Work in simultaneous DBT and MI system has demonstrated that the system can be optimised in terms of the DBT image quality. We are currently working to expand the OpenVCT software to simulate MI acquisition more accurately and to include models of tumour growth. Based on our experience to date, we envision a future in which VCTs have an important role in medical imaging, including support for more imaging modalities, use with rare diseases and a role in training and testing artificial intelligence (AI) systems.

The monoclonal antibodies HMFG-1 and HMFG-2 are directed against different epitopes on a large molecule in the human milk fat globule and are also expressed on breast tumors. Here we examine the relative intensity of staining of the two antibodies in formalin fixed paraffin embedded tissue sections from malignant and benign mammary lesions. Most ductal carcinomas and their lymph node metastases stained more strongly with HMFG-2 whereas primary lobular carcinomas are more variable but the majority of their lymph node metastases stained more strongly with HMFG-1. Western blots of gel separated extracts of formalin fixed, paraffin embedded tumor tissue, stained with the antibodies in an ELISA assay, show that the molecular weight of components expressing the antigenic determinants varies. Smaller molecular weight components recognised by HMFG-2 and present in metastatic tumors may be lost during tissue processing. To assess the importance of the molecular weight parameter in tumor classification and prognosis it will be necessary to use frozen tissue.

We present the Twente Photoacoustic Mammoscope 2, a photoacoustic breast imaging system employing a tomographic configuration. It images one breast pendant inside an imaging tank filled with water while a woman lies prone on a bed. A dual-head laser (755 and 1064 nm) illuminates the breast with one beam directed at the nipple and nine beams directed at the sides. Ultrasound signals are detected using 12 arc-shaped arrays, each curving along the pendant breast. Each array comprises 32 piezocomposite elements each with a center frequency of 1 MHz. The imaging tank and the ultrasound arrays rotate around the breast in steps to obtain additional multiple projections. Three-dimensional images are reconstructed using a filtered backprojection algorithm. The system is described in detail, and measurements on a test object are presented. As part of a preliminary study to assess the system’s in vivo performance, the breasts of two healthy volunteers were imaged. These images show the breast contour, the nipple, and the vascular anatomy within the breast. In the nipple of one case, multiple high-intensity “hot spots” are observed, which we suspect are associated with the lactiferous ducts terminating in the nipple.