Macroscopic optical physiological parameters correlate with microscopic proliferation and vessel area breast cancer signatures

A comprehensive overview of diffuse correlation spectroscopy: Theoretical framework, recent advances in hardware, analysis, and applications

Diffuse correlation spectroscopy (DCS) is a powerful tool for assessing microvascular hemodynamic in deep tissues. Recent advances in sensors, lasers, and deep learning have further boosted the development of new DCS methods. However, newcomers might feel overwhelmed, not only by the already-complex DCS theoretical framework but also by the broad range of component options and system architectures. To facilitate new entry to this exciting field, we present a comprehensive review of DCS hardware architectures (continuous-wave, frequency-domain, and time-domain) and summarize corresponding theoretical models. Further, we discuss new applications of highly integrated silicon single-photon avalanche diode (SPAD) sensors in DCS, compare SPADs with existing sensors, and review other components (lasers, sensors, and correlators), as well as data analysis tools, including deep learning. Potential applications in medical diagnosis are discussed and an outlook for the future directions is provided, to offer effective guidance to embark on DCS research.

A Device-on-Chip Solution for Real-Time Diffuse Correlation Spectroscopy Using FPGA

Diffuse correlation spectroscopy (DCS) is a non-invasive technology for the evaluation of blood perfusion in deep tissue. However, it requires high computational resources for data analysis, which poses challenges in its implementation for real-time applications. To address the unmet need, we developed a novel device-on-chip solution that fully integrates all the necessary computational components needed for DCS. It takes the output of a photon detector and determines the blood flow index (BFI). It is implemented on a field-programmable gate array (FPGA) chip including a multi-tau correlator for the calculation of the temporal light intensity autocorrelation function and a DCS analyzer to perform the curve fitting operation that derives the BFI at a rate of 6000 BFIs/s. The FPGA DCS system was evaluated against a lab-standard DCS system for both phantom and cuff ischemia studies. The results indicate that the autocorrelation of the light correlation and BFI from both the FPGA DCS and the reference DCS matched well. Furthermore, the FPGA DCS system was able to achieve a measurement rate of 50 Hz and resolve pulsatile blood flow. This can significantly lower the cost and footprint of the computational components of DCS and pave the way for portable, real-time DCS systems.

Neoadjuvant chemotherapy for breast cancer: an evaluation of its efficacy and research progress

Neoadjuvant chemotherapy (NAC) for breast cancer is widely used in the clinical setting to improve the chance of surgery, breast conservation and quality of life for patients with advanced breast cancer. A more accurate efficacy evaluation system is important for the decision of surgery timing and chemotherapy regimen implementation. However, current methods, encompassing imaging techniques such as ultrasound and MRI, along with non-imaging approaches like pathological evaluations, often fall short in accurately depicting the therapeutic effects of NAC. Imaging techniques are subjective and only reflect macroscopic morphological changes, while pathological evaluation is the gold standard for efficacy assessment but has the disadvantage of delayed results. In an effort to identify assessment methods that align more closely with real-world clinical demands, this paper provides an in-depth exploration of the principles and clinical applications of various assessment approaches in the neoadjuvant chemotherapy process.

Design of a Low-Cost Diffuse Optical Mammography System for Biomedical Image Processing in Breast Cancer Diagnosis

Worldwide, breast cancer is the most common type of cancer that mainly affects women. Several diagnosis techniques based on optical instrumentation and image analysis have been developed, and these are commonly used in conjunction with conventional diagnostic devices such as mammographs, ultrasound, and magnetic resonance imaging of the breast. The cost of using these instruments is increasing, and developing countries, whose deaths indices due to breast cancer are high, cannot access conventional diagnostic methods and have even less access to newer techniques. Other studies, based on the analysis of images acquired by traditional methods, require high resolutions and knowledge of the origin of the captures in order to avoid errors. For this reason, the design of a low-cost diffuse optical mammography system for biomedical image processing in breast cancer diagnosis is presented. The system combines the acquisition of breast tissue photographs, diffuse optical reflectance (as a biophotonics technique), and the processing of digital images for the study and diagnosis of breast cancer. The system was developed in the form of a medical examination table with a 638 nm red-light source, using light-emitted diode technology (LED) and a low-cost web camera for the acquisition of breast tissue images. The system is automatic, and its control, through a graphical user interface (GUI), saves costs and allows for the subsequent analysis of images using a digital image-processing algorithm. The results obtained allow for the possibility of planning in vivo measurements. In addition, the acquisition of images every 30° around the breast tissue could be used in future research in order to perform a three-dimensional (3D) reconstruction and an analysis of the captures through deep learning techniques. These could be combined with virtual, augmented, or mixed reality environments to predict the position of tumors, increase the likelihood of a correct medical diagnosis, and develop a training system for specialists. Furthermore, the system allows for the possibility to develop analysis of optical characterization for new phantom studies in breast cancer diagnosis through bioimaging techniques.

Diffuse Reflectance Spectroscopy of Changes in Tumor Microenvironment in Response to Different Doses of Radiation

Radiation therapy plays an important role in cancer treatment, as it is an established method used as part of the treatment plan for the majority of cancer patients. Real-time monitoring of the effects of radiation on the tumor microenvironment can contribute to the development of better treatment plans. In this study, we use diffuse reflectance spectroscopy, a non-invasive optical fiber-based technique, to determine the effects of different doses of radiation on the tumor microenvironment, as well as to determine the sensitivity of diffuse reflectance spectroscopy to low doses of radiation that are used in the treatment of certain cancers. We injected 4T1 cells into 50 Balb/c mice to generate tumor xenografts. When the tumors grew to 200 mm3, we distributed the mice into a control group or one of three radiation groups: 1, 2, or 4 Gy/fraction, and they underwent treatment for five consecutive days. We measured the tumor volume and collected diffuse reflectance spectra every day, with optical measurements being acquired both before and one h postirradiation on the five days of treatment. Based on the diffusely reflected light, we quantified vascular oxygenation, total hemoglobin content, and tissue scattering within these tumors. There was a significant increase in tumor vascular oxygenation, which was primarily due to an increase in oxygenated hemoglobin, in response to a 1 Gy/fraction of radiation, while there was a decrease in tissue scattering in response to all doses of radiation. Immunohistochemical analysis revealed that tumor cell proliferation and apoptosis were higher in irradiated groups compared to the control group. Our findings show that diffuse reflectance spectroscopy is sensitive to microenvironmental changes in tumors treated with doses of radiation as low as 1 Gy/fraction.

A biophotonic platform for quantitative analysis in the spatial, spectral, polarimetric, and goniometric domains

Advanced instrumentation and versatile setups are needed for understanding light interaction with biological targets. Such instruments include (1) microscopes and 3D scanners for detailed spatial analysis, (2) spectral instruments for deducing molecular composition, (3) polarimeters for assessing structural properties, and (4) goniometers probing the scattering phase function of, e.g., tissue slabs. While a large selection of commercial biophotonic instruments and laboratory equipment are available, they are often bulky and expensive. Therefore, they remain inaccessible for secondary education, hobbyists, and research groups in low-income countries. This lack of equipment impedes hands-on proficiency with basic biophotonic principles and the ability to solve local problems with applied physics. We have designed, prototyped, and evaluated the low-cost Biophotonics, Imaging, Optical, Spectral, Polarimetric, Angular, and Compact Equipment (BIOSPACE) for high-quality quantitative analysis. BIOSPACE uses multiplexed light-emitting diodes with emission wavelengths from ultraviolet to near-infrared, captured by a synchronized camera. The angles of the light source, the target, and the polarization filters are automated by low-cost mechanics and a microcomputer. This enables multi-dimensional scatter analysis of centimeter-sized biological targets. We present the construction, calibration, and evaluation of BIOSPACE. The diverse functions of BIOSPACE include small animal spectral imaging, measuring the nanometer thickness of a bark-beetle wing, acquiring the scattering phase function of a blood smear and estimating the anisotropic scattering and the extinction coefficients, and contrasting muscle fibers using polarization. We provide blueprints, component list, and software for replication by enthusiasts and educators to simplify the hands-on investigation of fundamental optical properties in biological samples.

Optical scattering as an early marker of apoptosis during chemotherapy and antiangiogenic therapy in murine models of prostate and breast cancer

Monitoring of the in vivo tumor state to track therapeutic response in real time may help to evaluate new drug candidates, maximize treatment efficacy, and reduce the burden of overtreatment. Current preclinical tumor imaging methods have largely focused on anatomic imaging (e.g., MRI, ultrasound), functional imaging (e.g., FDG-PET), and molecular imaging with exogenous contrast agents (e.g., fluorescence optical tomography). Here we utalize spatial frequency domain imaging (SFDI), a noninvasive, label-free optical technique, for the wide-field quantification of changes in tissue optical scattering in preclinical tumor models during treatment with chemotherapy and antiangiogenic agents. Optical scattering is particularly sensitive to tissue micro-architectural changes, including those that occur during apoptosis, an early indicator of response to cytotoxicity induced by chemotherapy, thermotherapy, cryotherapy, or radiation therapy. We utilized SFDI to monitor responses of PC3/2G7 prostate tumors and E0771 mammary tumors to treatment with cyclophosphamide or the antiangiogenic agent DC101 for up to 49 days. The SFDI-derived scattering amplitude was highly correlated with cleaved caspase-3, a marker of apoptosis (ρ_p = 0.75), while the exponent of the scattering wavelength-dependence correlated with the cell proliferation marker PCNA (ρ_p = 0.69). These optical parameters outperformed tumor volume and several functional parameters (e.g., oxygen saturation and hemoglobin concentration) as an early predictive biomarker of treatment response. Quantitative diffuse optical scattering is thus a promising new early marker of treatment response, which does not require radiation or exogenous contrast agents.

Mechanical and hemodynamic responses of breast tissue under mammographic-like compression during functional dynamic optical imaging

Studying tissue hemodynamics following breast compression has the potential to reveal new contrast mechanisms for evaluating breast cancer. However, how compression will be distributed and, consequently, how hemodynamics will be altered inside the compressed breast remain unclear. To explore the effect of compression, 12 healthy volunteers were studied by applying a step compression increase (4.5-53.4 N) using an optical imaging system capable of concurrently measuring pressure distribution and hemodynamic responses. Finite element analysis was used to predict the distribution of internal fluid pressure (IFP) in breast models. Comparisons between the measured pressure distribution and the reconstructed hemodynamic images for the healthy volunteers indicated significant (p < 0.05) negative correlations. The findings from a breast cancer patient showed that IFP distribution during compression strongly correlates with the observed differential hemodynamic images. We concluded that dynamic breast compression results in non-uniform internal pressure distribution throughout the breast that could potentially drive directed blood flow. The encouraging results obtained highlight the promise of developing dynamic optical imaging biomarkers for breast cancer by interpreting differential hemodynamic images of breast tissue during compression in the context of measured pressure distribution and predicted IFP.

Enhancement of diffuse correlation spectroscopy tissue blood flow measurement by acoustic radiation force

The current research on acousto-optic effects focuses on the interactions of acoustic waves with static optical properties rather than dynamic features such as tissue blood flow. Diffuse correlation spectroscopy (DCS) is an emerging technology capable of direct measurements of tissue blood flow by probing the movements of red blood cells (RBCs). In this article, we investigated the relations between the acoustic radiation force (ARF) and ultrasonic patterns by the finite element simulations. Based on the outcomes, we experimentally explored how the ultrasound-generated ARF enhance the DCS data as well as the blood flow measurements. The results yield the optimal pattern to generate ARF and elucidate the relations between the ultrasonic emission and flow elevations. The flow modality combing the DCS with ARF modulations, which was proposed in this study for the first time, would promote disease diagnosis and therapeutic assessment in the situation wherein the blood flow contrast between healthy and pathological tissues is insufficient.

Diffuse and nonlinear imaging of multiscale vascular parameters for in vivo monitoring of preclinical mammary tumors

Diffuse optical imaging (DOI) techniques provide a wide-field or macro assessment of the functional tumor state and have shown substantial promise for monitoring treatment efficacy in cancer. Conversely, intravital microscopy provides a high-resolution view of the tumor state and has played a key role in characterizing treatment response in the preclinical setting. There has been little prior work in investigating how the macro and micro spatial scales can be combined to develop a more comprehensive and translational view of treatment response. To address this, a new multiscale preclinical imaging technique called diffuse and nonlinear imaging (DNI) was developed. DNI combines multiphoton microscopy with spatial frequency domain imaging (SFDI) to provide multiscale data sets of tumor microvascular architecture coregistered within wide-field hemodynamic maps. A novel method was developed to match the imaging depths of both modalities by utilizing informed SFDI spatial frequency selection. An in vivo DNI study of murine mammary tumors revealed multiscale relationships between tumor oxygen saturation and microvessel diameter, and tumor oxygen saturation and microvessel length (|Pearson's ρ| ≥ 0.5, P < 0.05). Going forward, DNI will be uniquely enabling for the investigation of multiscale relationships in tumors during treatment.

Approaches to denoise the diffuse optical signals for tissue blood flow measurement

Various diseases are relevant to the abnormal blood flow in tissue. Diffuse correlation spectroscopy (DCS) is an emerging technology to extract the blood flow index (BFI) from light electric field temporal autocorrelation data. To account for tissue heterogeneity and irregular geometry, we developed an innovative DCS algorithm (i.e., the Nth order linear algorithm, or simply the NL algorithm) previously, in which the DCS signals are fully utilized through iterative linear regressions. Under the framework of NL algorithm, the BFI to be extracted is significantly influenced by the linear regression approach adopted. In this study, three approaches were proposed and evaluated for performing the iterative linear regressions, in order to understand what are the appropriate regression methods for BFI estimation. The three methods are least-squared minimization (L₂ norm), least-absolute minimization (L₁ norm) and support vector regression (SVR), where L₂ norm is a conventional approach to perform linear regression. L₁ norm and SVR are the approaches newly introduced here to process the DCS data. Computer simulations and the autocorrelation data collected from liquid phantom and human tissues are utilized to evaluate the three approaches. The results show that the best performance is achieved by the SVR approach in extracting the BFI values, with an error rate of 2.23% at 3.0 cm source-detector separation. The L₁ norm method gives a medium error of 2.81%. In contrast, the L₂ norm method leads to the largest error (3.93%) in extracting the BFI values. The outcomes derived from this study will be very helpful for the tissue blood flow measurements, which is critical for translating the DCS technology to the clinic.

Impact of errors in experimental parameters on reconstructed breast images using diffuse optical tomography

Near-infrared diffuse optical tomography (NIR-DOT) is an emerging technology that offers hemoglobin based, functional imaging tumor biomarkers for breast cancer management. The most promising clinical translation opportunities are in the differential diagnosis of malignant vs. benign lesions, and in early response assessment and guidance for neoadjuvant chemotherapy. Accurate quantification of the tissue oxy- and deoxy-hemoglobin concentration across the field of view, as well as repeatability during longitudinal imaging in the context of therapy guidance, are essential for the successful translation of NIR-DOT to clinical practice. The ill-posed and ill-condition nature of the DOT inverse problem makes this technique particularly susceptible to model errors that may occur, for example, when the experimental conditions do not fully match the assumptions built into the image reconstruction process. To evaluate the susceptibility of DOT images to experimental errors that might be encountered in practice for a parallel-plate NIR-DOT system, we simulated 7 different types of errors, each with a range of magnitudes. We generated simulated data by using digital breast phantoms derived from five actual mammograms of healthy female volunteers, to which we added a 1-cm tumor. After applying each of the experimental error types and magnitudes to the simulated measurements, we reconstructed optical images with and without structural prior guidance and assessed the overall error in the total hemoglobin concentrations (HbT) and in the HbT contrast between the lesion and surrounding area vs. the best-case scenarios. It is found that slight in-plane probe misalignment and plate rotation did not result in large quantification errors. However, any out-of-plane probe tilting could result in significant deterioration in lesion contrast. Among the error types investigated in this work, optical images were the least likely to be impacted by breast shape inaccuracies but suffered the largest deterioration due to cross-talk between signal channels. However, errors in optical images could be effectively controlled when experimental parameters were properly estimated during data acquisition and accounted for in the image processing procedure. Finally, optical images recovered using structural priors were, in general, less susceptible to experimental errors; however, lesion contrasts were more sensitive to errors when tumor locations were used as a priori info. Findings in this simulation study can provide guidelines for system design and operation in optical breast imaging studies.

Pre-clinical longitudinal monitoring of hemodynamic response to anti-vascular chemotherapy by hybrid diffuse optics

The longitudinal effect of an anti-vascular endothelial growth factor receptor 2 (VEGFR-2) antibody (DC 101) therapy on a xenografted renal cell carcinoma (RCC) mouse model was monitored using hybrid diffuse optics. Two groups of immunosuppressed male nude mice (seven treated, seven controls) were measured. Tumor microvascular blood flow, total hemoglobin concentration and blood oxygenation were investigated as potential biomarkers for the monitoring of the therapy effect twice a week and were related to the final treatment outcome. These hemodynamic biomarkers have shown a clear differentiation between two groups by day four. Moreover, we have observed that pre-treatment values and early changes in hemodynamics are highly correlated with the therapeutic outcome demonstrating the potential of diffuse optics to predict the therapy response at an early time point.

Clinical applications of near-infrared diffuse correlation spectroscopy and tomography for tissue blood flow monitoring and imaging

OBJECTIVE

Blood flow is one such available observable promoting a wealth of physiological insight both individually and in combination with other metrics.

APPROACH

Near-infrared diffuse correlation spectroscopy (DCS) and, to a lesser extent, diffuse correlation tomography (DCT), have increasingly received interest over the past decade as noninvasive methods for tissue blood flow measurements and imaging. DCS/DCT offers several attractive features for tissue blood flow measurements/imaging such as noninvasiveness, portability, high temporal resolution, and relatively large penetration depth (up to several centimeters).

MAIN RESULTS

This review first introduces the basic principle and instrumentation of DCS/DCT, followed by presenting clinical application examples of DCS/DCT for the diagnosis and therapeutic monitoring of diseases in a variety of organs/tissues including brain, skeletal muscle, and tumor.

SIGNIFICANCE

Clinical study results demonstrate technical versatility of DCS/DCT in providing important information for disease diagnosis and intervention monitoring.

Diffuse optical tomography changes correlate with residual cancer burden after neoadjuvant chemotherapy in breast cancer patients

PURPOSE

Breast cancer (BC) patients who achieve a favorable residual cancer burden (RCB) after neoadjuvant chemotherapy (NACT) have an improved recurrence-free survival. Those who have an unfavorable RCB will have gone through months of ineffective chemotherapy. No ideal method exists to predict a favorable RCB early during NACT. Diffuse optical tomography (DOT) is a novel imaging modality that uses near-infrared light to assess hemoglobin concentrations within breast tumors. We hypothesized that the 2-week percent change in DOT-measured hemoglobin concentrations would associate with RCB.

METHODS

We conducted an observational study of 40 women with stage II-IIIC BC who received standard NACT. DOT imaging was performed at baseline and 2 weeks after treatment initiation. We evaluated the associations between the RCB index (continuous measure), class (categorical 0, I, II, III), and response (RCB class 0/I = favorable, RCB class II/III = unfavorable) with changes in DOT-measured hemoglobin concentrations.

RESULTS

The RCB index correlated significantly with the 2-week percent change in oxyhemoglobin [HbO₂] (r = 0.5, p = 0.003), deoxyhemoglobin [Hb] (r = 0.37, p = 0.03), and total hemoglobin concentrations [HbT] (r = 0.5, p = 0.003). The RCB class and response significantly associated with the 2-week percent change in [HbO₂] (p ≤ 0.01) and [HbT] (p ≤ 0.02). [HbT] 2-week percent change had sensitivity, specificity, positive, and negative predictive values for a favorable RCB response of 86.7, 68.4, 68.4, and 86.7%, respectively.

CONCLUSION

The 2-week percent change in DOT-measured hemoglobin concentrations was associated with the RCB index, class, and response. DOT may help guide NACT for women with BC.

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.

Diffuse Optical Characterization of the Healthy Human Thyroid Tissue and Two Pathological Case Studies

The in vivo optical and hemodynamic properties of the healthy (n = 22) and pathological (n = 2) human thyroid tissue were measured non-invasively using a custom time-resolved spectroscopy (TRS) and diffuse correlation spectroscopy (DCS) system. Medical ultrasound was used to guide the placement of the hand-held hybrid optical probe. TRS measured the absorption and reduced scattering coefficients (μ_a, μ_s′) at three wavelengths (690, 785 and 830 nm) to derive total hemoglobin concentration (THC) and oxygen saturation (StO₂). DCS measured the microvascular blood flow index (BFI). Their dependencies on physiological and clinical parameters and positions along the thyroid were investigated and compared to the surrounding sternocleidomastoid muscle. The THC in the thyroid ranged from 131.9 μM to 144.8 μM, showing a 25–44% increase compared to the surrounding sternocleidomastoid muscle tissue. The blood flow was significantly higher in the thyroid (BFI_thyroid = 16.0 × 10^-9 cm²/s) compared to the muscle (BFI_muscle = 7.8 × 10^-9 cm²/s), while StO₂ showed a small (StO_{2, muscle} = 63.8% to StO_{2, thyroid} = 68.4%), yet significant difference. Two case studies with thyroid nodules underwent the same measurement protocol prior to thyroidectomy. Their THC and BFI reached values around 226.5 μM and 62.8 × 10^-9 cm²/s respectively showing a clear contrast to the nodule-free thyroid tissue as well as the general population. The initial characterization of the healthy and pathologic human thyroid tissue lays the ground work for the future investigation on the use of diffuse optics in thyroid cancer screening.