High optode-density wearable diffuse optical probe for monitoring paced breathing hemodynamics in breast tissue.

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: µa drift of 0.34%/h, µa 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 ΔHbO2 and ΔHHb amplitudes ranged from 0.39 to 0.67 µM and 0.08 to 0.12 µM, 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.

Diffuse optical spectroscopic imaging reveals distinct early breast tumor hemodynamic responses to metronomic and maximum tolerated dose regimens.

BACKGROUND: Breast cancer patients with early-stage disease are increasingly administered neoadjuvant chemotherapy (NAC) to downstage their tumors prior to surgery. In this setting, approximately 31% of patients fail to respond to therapy. This demonstrates the need for techniques capable of providing personalized feedback about treatment response at the earliest stages of therapy to identify patients likely to benefit from changing treatment. Diffuse optical spectroscopic imaging (DOSI) has emerged as a promising functional imaging technique for NAC monitoring. DOSI uses non-ionizing near-infrared light to provide non-invasive measures of absolute concentrations of tissue chromophores such as oxyhemoglobin. In 2011, we reported a new DOSI prognostic marker, oxyhemoglobin flare: a transient increase in oxyhemoglobin capable of discriminating NAC responders within the first day of treatment. In this follow-up study, DOSI was used to confirm the presence of the flare as well as to investigate whether DOSI markers of NAC response are regimen dependent. METHODS: This dual-center study examined 54 breast tumors receiving NAC measured with DOSI before therapy and the first week following chemotherapy administration. Patients were treated with either a standard of care maximum tolerated dose (MTD) regimen or an investigational metronomic (MET) regimen. Changes in tumor chromophores were tracked throughout the first week and compared to pathologic response and treatment regimen at specific days utilizing generalized estimating equations (GEE). RESULTS: Within patients receiving MTD therapy, the oxyhemoglobin flare was confirmed as a prognostic DOSI marker for response appearing as soon as day 1 with post hoc GEE analysis demonstrating a difference of 48.77% between responders and non-responders (p < 0.0001). Flare was not observed in patients receiving MET therapy. Within all responding patients, the specific treatment was a significant predictor of day 1 changes in oxyhemoglobin, showing a difference of 39.45% (p = 0.0010) between patients receiving MTD and MET regimens. CONCLUSIONS: DOSI optical biomarkers are differentially sensitive to MTD and MET regimens at early timepoints suggesting the specific treatment regimen should be considered in future DOSI studies. Additionally, DOSI may help to identify regimen-specific responses in a more personalized manner, potentially providing critical feedback necessary to implement adaptive changes to the treatment strategy.

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.

Optical sampling depth in the spatial frequency domain.

We present a Monte Carlo (MC) method to determine depth-dependent probability distributions of photon visitation and detection for optical reflectance measurements performed in the spatial frequency domain (SFD). These distributions are formed using an MC simulation for radiative transport that utilizes a photon packet weighting procedure consistent with the two-dimensional spatial Fourier transform of the radiative transport equation. This method enables the development of quantitative metrics for SFD optical sampling depth in layered tissue and its dependence on both tissue optical properties and spatial frequency. We validate the computed depth-dependent probability distributions using SFD measurements in a layered phantom system with a highly scattering top layer of variable thickness supported by a highly absorbing base layer. We utilize our method to establish the spatial frequency-dependent optical sampling depth for a number of tissue types and also provide a general tool to determine such depths for tissues of arbitrary optical properties.

Two-layer inverse model for improved longitudinal preclinical tumor imaging in the spatial frequency domain.

Spatial frequency domain imaging (SFDI) is a widefield, noncontact, and label-free imaging modality that is currently being explored as a new tool for longitudinal tracking of cancer therapies in the preclinical setting. We describe a two-layer look-up-table (LUT) inversion algorithm for SFDI that better accounts for the skin (top layer) and tumor (bottom layer) tissue geometry in subcutaneous tumor models. Monte Carlo (MC) simulations were conducted natively in the spatial frequency domain, avoiding discretization errors associated with Fourier or Hankel transforms of conventional MC simulation results. The two-layer LUT was validated using two-layer tissue mimicking optical phantoms, in which the optical property extractions of the bottom (tumor) layer were determined to be within 20% and 11% of the true values for µa and µs', respectively. A sensitivity analysis was conducted to evaluate how imperfect top layer estimates affect bottom-layer optical property extractions. Finally, the two-layer LUT was used to reanalyze a prior longitudinal data set, which revealed larger therapy-induced changes in optical scattering and a more hypoxic tumor environment compared to the homogeneous LUT. The two-layer LUT described here improves the accuracy of subcutaneous tumor imaging, and the general methodology can be applied for arbitrary multilayer SFDI applications.

Optical property uncertainty estimates for spatial frequency domain imaging.

Spatial frequency domain imaging (SFDI) is a wide-field diffuse optical imaging modality that has attracted considerable interest in recent years. Typically, diffuse reflectance measurements of spatially modulated light are used to quantify the optical absorption and reduced scattering coefficients of tissue, and with these, chromophore concentrations are extracted. However, uncertainties in estimated absorption and reduced scattering coefficients are rarely reported, and we know of no method capable of providing these when look-up table (LUT) algorithms are used to recover the optical properties. We present a method to generate optical property uncertainty estimates from knowledge of diffuse reflectance measurement errors. By employing the Cramér-Rao bound, we can quickly and efficiently explore theoretical SFDI performance as a function of spatial frequencies and sample optical properties, allowing us to optimize spatial frequency selection for a given application. In practice, we can also obtain useful uncertainty estimates for optical properties recovered with a two-frequency LUT algorithm, as we demonstrate with tissue-simulating phantom and in vivo experiments. Finally, we illustrate how absorption coefficient uncertainties can be propagated forward to yield uncertainties for chromophore concentrations, which could significantly impact the interpretation of experimental results.

Near infrared spectroscopy for measuring changes in bone hemoglobin content after exercise in individuals with spinal cord injury.

Bone blood perfusion has an essential role in maintaining a healthy bone. However, current methods for measuring bone blood perfusion are expensive and highly invasive. This study presents a custom built near-infrared spectroscopy (NIRS) instrument to measure changes in bone blood perfusion. We demonstrated the efficacy of this device by monitoring oxygenated and deoxygenated hemoglobin changes in the human tibia during and after exercise in able-bodied and in individuals with spinal cord injury (SCI), a population with known impaired peripheral blood perfusion. Nine able-bodied individuals and six volunteers with SCI performed a 10 min rowing exercise (functional electrical stimulation rowing for those with SCI). With exercise, during rowing, able-bodied showed an increase in deoxygenated hemoglobin in the tibia. Post rowing, able-bodied showed an increase in total blood content, characterized by an increase in total hemoglobin content due primarily to an increase in deoxygenated hemoglobin. During rowing and post-rowing, those with SCI showed no change in total blood content in the tibia. The current study demonstrates that NIRS can non-invasively detect changes in hemoglobin concentration in the tibia. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:183-191, 2018.

Diffuse fluorescence fiber probe for in vivo detection of circulating cells.

There has been significant recent interest in the development of technologies for enumeration of rare circulating cells directly in the bloodstream in many areas of research, for example, in small animal models of circulating tumor cell dissemination during cancer metastasis. We describe a fiber-based optical probe that allows fluorescence detection of labeled circulating cells in vivo in a diffuse reflectance configuration. We validated this probe in a tissue-mimicking flow phantom model in vitro and in nude mice injected with fluorescently labeled multiple myeloma cells in vivo. Compared to our previous work, this design yields an improvement in detection signal-to-noise ratio of 10 dB, virtually eliminates problematic motion artifacts due to mouse breathing, and potentially allows operation in larger animals and limbs.

Wearable near-infrared optical probe for continuous monitoring during breast cancer neoadjuvant chemotherapy infusions.

We present a new continuous-wave wearable diffuse optical probe aimed at investigating the hemodynamic response of locally advanced breast cancer patients during neoadjuvant chemotherapy infusions. The system consists of a flexible printed circuit board that supports an array of six dual wavelength surface-mount LED and photodiode pairs. The probe is encased in a soft silicone housing that conforms to natural breast shape. Probe performance was evaluated using tissue-simulating phantoms and in vivo normal volunteer measurements. High SNR (71 dB), low source-detector crosstalk ( ? 60 ?? dB ), high measurement precision (0.17%), and good thermal stability (0.22% V rms / ° C ) were achieved in phantom studies. A cuff occlusion experiment was performed on the forearm of a healthy volunteer to demonstrate the ability to track rapid hemodynamic changes. Proof-of-principle normal volunteer measurements were taken to demonstrate the ability to collect continuous in vivo breast measurements. This wearable probe is a first of its kind tool to explore prognostic hemodynamic changes during chemotherapy in breast cancer patients.

Multiplexed fluorescence mediated tomography with temporal and spectral data.

We recently developed an algorithm for multiplexed fluorescence tomographic imaging of at least four fluorophores concurrently in the red and near-infrared wavelength region by jointly using spectral and temporal data. We report the design of a fluorescence tomography instrument that acquires spectral and temporal data, and validate its use in tissue-mimicking phantoms with four embedded fluorescent targets with highly overlapped spectral signatures. Critically, this requires measurement or computation of extended fluorophore signature libraries, which capture the variability in the measured signal due to the unknown position of the targets in the media. We demonstrate that we can demix and tomographically image all four fluorophores with zero image cross-talk, and 1 mm or better spatial resolution.

Multiplexed fluorescence tomography with spectral and temporal data: demixing with intrinsic regularization.

We consider the joint use of spectral and temporal data for multiplexed fluorescence molecular tomography to enable high-throughput imaging of multiple fluorescent targets in bulk tissue. This is a challenging problem due to the narrow near-infrared diagnostic window and relatively broad emission spectra of common fluorophores, and the distortion ("redshift") that the fluorophore signals undergo as they propagate through tissue. We show through a Cramér-Rao lower bound analysis that demixing with spectral-temporal data could result in an order of magnitude improvement in performance over either modality alone. To cope with the resulting large data set, we propose a novel two-stage algorithm that decouples the demixing and tomographic reconstruction operations. In this work we concentrate on the demixing stage. We introduce an approach which incorporates ideas from sparse subspace clustering and compressed sensing and does not require a regularization parameter. We report on simulations in which we simultaneously demixed four fluorophores with closely overlapping spectral and temporal profiles in a 25 mm diameter cross-sectional area with a root-mean-square error of less than 3% per fluorophore, as well as on studies of sensitivity of the method to model mismatch.

On the use of the Cramér-Rao lower bound for diffuse optical imaging system design.

We evaluated the potential of the Cramér-Rao lower bound (CRLB) to serve as a design metric for diffuse optical imaging systems. The CRLB defines the best achievable precision of any estimator for a given data model; it is often used in the statistical signal processing community for feasibility studies and system design. Computing the CRLB requires inverting the Fisher information matrix (FIM), however, which is usually ill-conditioned (and often underdetermined) in the case of diffuse optical tomography (DOT). We regularized the FIM by assuming that the inhomogeneity to be imaged was a point target and assessed the ability of point-target CRLBs to predict system performance in a typical DOT setting in silico. Our reconstructions, obtained with a common iterative algebraic technique, revealed that these bounds are not good predictors of imaging performance across different system configurations, even in a relative sense. This study demonstrates that agreement between the trends predicted by the CRLBs and imaging performance obtained with reconstruction algorithms that rely on a different regularization approach cannot be assumed a priori. Moreover, it underscores the importance of taking into account the intended regularization method when attempting to optimize source-detector configurations.

A computer vision approach to rare cell in vivo fluorescence flow cytometry.

Noninvasive enumeration of rare circulating cell populations in small animals is of great importance in many areas of biomedical research. In this work, we describe a macroscopic fluorescence imaging system and automated computer vision algorithm that allows in vivo detection, enumeration and tracking of circulating fluorescently-labeled cells from multiple large blood vessels in the ear of a mouse. This imaging system uses a 660 nm laser and a high sensitivity electron-multiplied charge coupled device camera (EMCCD) to acquire fluorescence image sequences from relatively large (∼5 × 5 mm(2) ) imaging areas. The primary technical challenge was developing an automated method for identifying and tracking rare cell events in image sequences with substantial autofluorescence and noise content. To achieve this, we developed a two-step image analysis algorithm that first identified cell candidates in individual frames, and then merged cell candidates into tracks by dynamic analysis of image sequences. The second step was critical since it allowed rejection of >97% of false positive cell counts. Overall, our computer vision IVFC (CV-IVFC) approach allows single-cell detection sensitivity at estimated concentrations of 20 cells/mL of peripheral blood. In addition to simple enumeration, the technique recovers the cell's trajectory, which in the future could be used to automatically identify, for example, in vivo homing and docking events.

Maximum likelihood tomographic reconstruction of extremely sparse solutions in diffuse fluorescence flow cytometry.

We apply reparameterization and the maximum likelihood method to a specific fluorescence-mediated tomography problem where the solution is known a priori to be extremely sparse (i.e., all image values are zero except for one). Our algorithm performs significantly better than a standard image reconstruction method, particularly for deep-seated targets, and achieves close to 150 µm accuracy in a 3 mm diameter cross-sectional area with only 12 measurements. Moreover, results do not depend on the selection of a regularization parameter or other ad hoc values, and since reconstructions can be computed very quickly, the algorithm is also suitable for real-time implementation.

Spatial and spectral information in optical mammography.

This article reviews our research activities in the area of optical mammography and relates them to the historical developments and the current state and trends in the field. The guiding threads for this article are the roles played in optical mammography by spatial and spectral information. The first feature, spatial information, is limited by the diffusive nature of light propagation but can take advantage of the exceptionally high optical contrast featured by blood vessels and blood-rich areas in the breast. We describe a method to correct for edge effects, a spatial second-derivative algorithm, and a two-dimensional phased-array approach that enhance the image contrast, the spatial resolution, and the depth discrimination in optical mammograms. The second feature, spectral information, is the most powerful and unique capability of optical mammography, and allows for functional measurements associated with hemoglobin concentration and oxygenation, water concentration, lipids content, and the wavelength dependence of tissue scattering. We present oxygenation-index images obtained from multi-wavelength optical data that point to the diagnostic potential of oxygenation information in optical mammography. The optimization of the spatial and spectral information in optical mammography has the potential to create a role for this imaging modality in the detection and monitoring of breast cancer.

Near-infrared imaging of the human breast: complementing hemoglobin concentration maps with oxygenation images.

We have previously reported a comparison between edge-corrected near-infrared optical mammograms and those that have undergone a further image-processing step based on a spatial second derivative. In this work, we go a step further by combining the second-derivative images from four wavelengths (690, 750, 788, and 856 nm) to obtain oxygenation-index images. While the spatial second derivative improves contrast and allows for visibility of fine structures in the images, thereby improving the sensitivity to tumor detection, additional information is needed to avoid false-positive results. The oxygenation-index images are introduced to address this issue. Oxygenation information may help discriminate benign from malignant breast lesions, thereby effectively complementing single-wavelength optical mammograms that display optically dense regions within the breast with high sensitivity.

Spatial second-derivative image processing: an application to optical mammography to enhance the detection of breast tumors.

We present an image-processing method that enhances the detection of regions of higher absorbance in optical mammograms. At the heart of this method lies a second-derivative operator that is commonly employed in edge-detection algorithms. The resulting images possess a high contrast, an automatic display scale, and a greater sensitivity to smaller departures from the local background absorbance. Moreover, the images are free of artifacts near the breast edge. This second-derivative method enhances the display of structural information in optical mammograms and may be used to robustly select areas of interest to be further analyzed spectrally to determine the oxygenation level of breast lesions.