Effects of neoadjuvant chemotherapy on the contralateral non-tumor-bearing breast assessed by diffuse optical tomography.

BACKGROUND: The purpose of this study is to evaluate whether the changes in optically derived parameters acquired with a diffuse optical tomography breast imager system (DOTBIS) in the contralateral non-tumor-bearing breast in patients administered neoadjuvant chemotherapy (NAC) for breast cancer are associated with pathologic complete response (pCR). METHODS: In this retrospective evaluation of 105 patients with stage II-III breast cancer, oxy-hemoglobin (ctO2Hb) from the contralateral non-tumor-bearing breast was collected and analyzed at different time points during NAC. The earliest monitoring imaging time point was after 2-3 weeks receiving taxane. Longitudinal data were analyzed using linear mixed-effects modeling to evaluate the contralateral breast ctO2Hb changes across chemotherapy when corrected for pCR status, age, and BMI. RESULTS: Patients who achieved pCR to NAC had an overall decrease of 3.88 µM for ctO2Hb (95% CI, 1.39 to 6.37 µM), p = .004, after 2-3 weeks. On the other hand, non-pCR subjects had a non-significant mean reduction of 0.14 µM (95% CI, - 1.30 to 1.58 µM), p > .05. Mixed-effect model results indicated a statistically significant negative relationship of ctO2Hb levels with BMI and age. CONCLUSIONS: This study demonstrates that the contralateral normal breast tissue assessed by DOTBIS is modifiable after NAC, with changes associated with pCR after only 2-3 weeks of chemotherapy.

Diffuse optical tomography breast imaging measurements are modifiable with pre-surgical targeted and endocrine therapies among women with early stage breast cancer.

PURPOSE: Diffuse optical tomography breast imaging system (DOTBIS) non-invasively measures tissue concentration of hemoglobin, which is a potential biomarker of short-term response to neoadjuvant chemotherapy. We evaluated whether DOTBIS-derived measurements are modifiable with targeted therapies, including AKT inhibition and endocrine therapy. METHODS: We conducted a proof of principle study in seven postmenopausal women with stage I-III breast cancer who were enrolled in pre-surgical studies of the AKT inhibitor MK-2206 (n = 4) or the aromatase inhibitors exemestane (n = 2) and letrozole (n = 1). We performed DOTBIS at baseline (before initiation of therapy) and post-therapy in the affected breast (tumor volume) and contralateral, unaffected breast, and measured tissue concentrations (in µM) of total hemoglobin (ctTHb), oxyhemoglobin (ctO2Hb), and deoxyhemoglobin (ctHHb), as well as water fraction (%). RESULTS: We found consistent decreases in DOTBIS-measured hemoglobin concentrations in tumor volume, with median percent changes for ctTHb, ctHHb, ctO2Hb, and water fraction for the entire cohort of - 27.1% (interquartile range [IQR] 37.5%), - 49.8% (IQR 29.3%), - 33.5% (IQR 47.4%), and - 3.6% (IQR 10.6%), respectively. In the contralateral breast, median percent changes for ctTHb, ctHHb, ctO2Hb, and water fraction were + 1.8% (IQR 26.7%), - 8.6% (IQR 29.3%), + 6.2% (IQR 29.5%), and + 1.9% (IQR 30.7%), respectively. CONCLUSION: We demonstrated that DOTBIS-derived measurements are modifiable with pre-surgical AKT inhibition and endocrine therapy, supporting further investigation of DOTBIS as a potential imaging assessment of response to neoadjuvant targeted therapies in early stage breast cancer.

Ultrafast and Ultrahigh-Resolution Diffuse Optical Tomography for Brain Imaging with Sensitivity Equation based Noniterative Sparse Optical Reconstruction (SENSOR).

We introduce a novel image reconstruction method for time-resolved diffuse optical tomography (DOT) that yields submillimeter resolution in less than a second. This opens the door to high-resolution real-time DOT in imaging of the brain activity. We call this approach the sensitivity equation based noniterative sparse optical reconstruction (SENSOR) method. The high spatial resolution is achieved by implementing an asymptotic l 0-norm operator that guarantees to obtain sparsest representation of reconstructed targets. The high computational speed is achieved by employing the nontruncated sensitivity equation based noniterative inverse formulation combined with reduced sensing matrix and parallel computing. We tested the new method with numerical and experimental data. The results demonstrate that the SENSOR algorithm can achieve 1 mm3 spatial-resolution optical tomographic imaging at depth of ∼60 mean free paths (MFPs) in 20∼30 milliseconds on an Intel Core i9 processor.

Dynamic Diffuse Optical Tomography for Monitoring Neoadjuvant Chemotherapy in Patients with Breast Cancer.

Purpose To identify dynamic optical imaging features that associate with the degree of pathologic response in patients with breast cancer during neoadjuvant chemotherapy (NAC). Materials and Methods Of 40 patients with breast cancer who participated in a longitudinal study between June 2011 and March 2016, 34 completed the study. There were 13 patients who obtained a pathologic complete response (pCR) and 21 patients who did not obtain a pCR. Imaging data from six subjects were excluded from the study because either the patients dropped out of the study before it was finished or there was an instrumentation malfunction. Two weeks into the treatment regimen, three-dimensional images of both breasts during a breath hold were acquired by using dynamic diffuse optical tomography. Features from the breath-hold traces were used to distinguish between response groups. Receiver operating characteristic (ROC) curves and sensitivity analysis were used to determine the degree of association with 5-month treatment outcome. Results An ROC curve analysis showed that this method could identify patients with a pCR with a positive predictive value of 70.6% (12 of 17), a negative predictive value of 94.1% (16 of 17), a sensitivity of 92.3% (12 of 13), a specificity of 76.2% (16 of 21), and an area under the ROC curve of 0.85. Conclusion Several dynamic optical imaging features obtained within 2 weeks of NAC initiation were identified that showed statistically significant differences between patients with pCR and patients without pCR as determined 5 months after treatment initiation. If confirmed in a larger cohort prospective study, these dynamic imaging features may be used to predict treatment outcome as early as 2 weeks after treatment initiation. © RSNA, 2018 Online supplemental material is available for this article.

Assessment of Infantile Hemangiomas Using a Handheld Wireless Diffuse Optical Spectroscopic Device.

BACKGROUND/OBJECTIVES: Infantile hemangiomas (IHs) are vascular tumors with the potential for significant morbidity. There is a lack of validated objective tools to assess IH severity and response to treatment. Diffuse optical spectroscopy (DOS), a noninvasive, nonionizing imaging modality, can measure total hemoglobin concentration and hemoglobin oxygen saturation in tissue to assess IH vascularity and response to treatment. Our objective was to evaluate the utility of a wireless, handheld DOS system to assess IH characteristics at selected points during their clinical course. METHODS: Thirteen subjects (initial age 5.8 ± 2.0 mos) with 15 IHs were enrolled. IHs were classified as proliferative, plateau phase, or involuting. Nine patients with 11 IHs were untreated; four patients with 4 IHs were treated with timolol or propranolol. Each IH was evaluated by placing the DOS system directly on the lesion as well a normal contralateral skin site. IH vascularity and oxygenation were scored using a newly defined normalized hypoxia fraction (NHF) coefficient. Measurements were recorded at various intervals from the initial visit to 1 to 2 years of age. RESULTS: For the nine untreated IHs, the NHF was highest at 6 months of age, during proliferation. Differences in NHFs between the proliferation and the plateau (p = 0.02) and involuting (p < 0.001) stages were statistically significant. In treated patients, the NHF normalized to 60% after 2 months. One treated IH came within 5% of the NHF for normal skin after 12 months. CONCLUSIONS: DOS can be used to assess the vascularity and tissue oxygenation of IHs and monitor their progression and response to treatment.

Frequency-domain optical tomographic image reconstruction algorithm with the simplified spherical harmonics (SP3) light propagation model.

We introduce here the finite volume formulation of the frequency-domain simplified spherical harmonics model with n-th order absorption coefficients (FD-SPN) that approximates the frequency-domain equation of radiative transfer (FD-ERT). We then present the FD-SPN based reconstruction algorithm that recovers absorption and scattering coefficients in biological tissue. The FD-SPN model with 3rd order absorption coefficient (i.e., FD-SP3) is used as a forward model to solve the inverse problem. The FD-SP3 is discretized with a node-centered finite volume scheme and solved with a restarted generalized minimum residual (GMRES) algorithm. The absorption and scattering coefficients are retrieved using a limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm. Finally, the forward and inverse algorithms are evaluated using numerical phantoms with optical properties and size that mimic small-volume tissue such as finger joints and small animals. The forward results show that the FD-SP3 model approximates the FD-ERT (S12) solution within relatively high accuracy; the average error in the phase (<3.7%) and the amplitude (<7.1%) of the partial current at the boundary are reported. From the inverse results we find that the absorption and scattering coefficient maps are more accurately reconstructed with the SP3 model than those with the SP1 model. Therefore, this work shows that the FD-SP3 is an efficient model for optical tomographic imaging of small-volume media with non-diffuse properties both in terms of computational time and accuracy as it requires significantly lower CPU time than the FD-ERT (S12) and also it is more accurate than the FD-SP1.

Fast linear solver for radiative transport equation with multiple right hand sides in diffuse optical tomography.

It is well known that radiative transfer equation (RTE) provides more accurate tomographic results than its diffusion approximation (DA). However, RTE-based tomographic reconstruction codes have limited applicability in practice due to their high computational cost. In this article, we propose a new efficient method for solving the RTE forward problem with multiple light sources in an all-at-once manner instead of solving it for each source separately. To this end, we introduce here a novel linear solver called block biconjugate gradient stabilized method (block BiCGStab) that makes full use of the shared information between different right hand sides to accelerate solution convergence. Two parallelized block BiCGStab methods are proposed for additional acceleration under limited threads situation. We evaluate the performance of this algorithm with numerical simulation studies involving the Delta-Eddington approximation to the scattering phase function. The results show that the single threading block RTE solver proposed here reduces computation time by a factor of 1.5~3 as compared to the traditional sequential solution method and the parallel block solver by a factor of 1.5 as compared to the traditional parallel sequential method. This block linear solver is, moreover, independent of discretization schemes and preconditioners used; thus further acceleration and higher accuracy can be expected when combined with other existing discretization schemes or preconditioners.

High-Speed Time-Domain Diffuse Optical Tomography with a Sensitivity Equation-based Neural Network.

Steady progress in time-domain diffuse optical tomography (TD-DOT) technology is allowing for the first time the design of low-cost, compact, and high-performance systems, thus promising more widespread clinical TD-DOT use, such as for recording brain tissue hemodynamics. TD-DOT is known to provide more accurate values of optical properties and physiological parameters compared to its frequency-domain or steady-state counterparts. However, achieving high temporal resolution is still difficult, as solving the inverse problem is computationally demanding, leading to relatively long reconstruction times. The runtime is further compromised by processes that involve 'nontrivial' empirical tuning of reconstruction parameters, which increases complexity and inefficiency. To address these challenges, we present a new reconstruction algorithm that combines a deep-learning approach with our previously introduced sensitivity-equation-based, non-iterative sparse optical reconstruction (SENSOR) code. The new algorithm (called SENSOR-NET) unfolds the iterations of SENSOR into a deep neural network. In this way, we achieve high-resolution sparse reconstruction using only learned parameters, thus eliminating the need to tune parameters prior to reconstruction empirically. Furthermore, once trained, the reconstruction time is not dependent on the number of sources or wavelengths used. We validate our method with numerical and experimental data and show that accurate reconstructions with 1 mm spatial resolution can be obtained in under 20 milliseconds regardless of the number of sources used in the setup. This opens the door for real-time brain monitoring and other high-speed DOT applications.

Postintervention monitoring of peripheral arterial disease wound healing using dynamic vascular optical spectroscopy.

Significance: Due to the persistence of chronic wounds, a second surgical intervention is often necessary for patients with peripheral arterial disease (PAD) within a year of the first intervention. The dynamic vascular optical spectroscopy system (DVOS) may assist physicians in determining patient prognosis only a month after the first surgical intervention. Aim: We aim to assess the DVOS utility in characterizing wound healing in PAD patients after endovascular intervention. Approach: The DVOS used near-infrared light ( 670 < λ < 850 nm ) to record hemodynamic response to a cuff inflation in 14 PAD patients with lower limb ulcers immediately before, immediately after, and at a first follow-up 3 to 4 weeks after intervention. Ankle-brachial index (ABI) and arterial duplex ultrasound (A-DUS) measurements were obtained when possible. Results: The total hemoglobin plateau time differed significantly between patients with ulcers that reduced in size ( N = 9 ) and patients with ulcers that did not ( N = 5 ) 3 to 4 weeks after intervention ( p value < 0.001 ). Data correlated strongly (89% sensitivity, 100% specificity, and AUC = 0.96 ) with long-term wound healing. ABI and A-DUS measurements were not statistically associated with wound healing. Conclusions: This pilot study demonstrates the potential of the DVOS to aid physicians in giving accurate long-term wound healing prognoses 1 month after intervention.

High Resolution, Deep Imaging Using Confocal Time-of-Flight Diffuse Optical Tomography.

Light scattering by tissue severely limits how deep beneath the surface one can image, and the spatial resolution one can obtain from these images. Diffuse optical tomography (DOT) is one of the most powerful techniques for imaging deep within tissue - well beyond the conventional  âˆ¼ 10-15 mean scattering lengths tolerated by ballistic imaging techniques such as confocal and two-photon microscopy. Unfortunately, existing DOT systems are limited, achieving only centimeter-scale resolution. Furthermore, they suffer from slow acquisition times and slow reconstruction speeds making real-time imaging infeasible. We show that time-of-flight diffuse optical tomography (ToF-DOT) and its confocal variant (CToF-DOT), by exploiting the photon travel time information, allow us to achieve millimeter spatial resolution in the highly scattered diffusion regime ( mean free paths). In addition, we demonstrate two additional innovations: focusing on confocal measurements, and multiplexing the illumination sources allow us to significantly reduce the measurement acquisition time. Finally, we rely on a novel convolutional approximation that allows us to develop a fast reconstruction algorithm, achieving a 100× speedup in reconstruction time compared to traditional DOT reconstruction techniques. Together, we believe that these technical advances serve as the first step towards real-time, millimeter resolution, deep tissue imaging using DOT.

Flexible optical imaging band system for the assessment of arthritis in patients with systemic lupus erythematosus.

We have developed a flexible optical imaging system (FOIS) to assess systemic lupus erythematosus (SLE) arthritis in the finger joints. While any part of the body can be affected, arthritis in the finger joints is one of the most common SLE manifestations. There is an unmet need for accurate, low-cost assessment of lupus arthritis that can be easily performed at every clinic visit. Current imaging methods are imprecise, expensive, and time consuming to allow for frequent monitoring. Our FOIS can be wrapped around joints, and multiple light sources and detectors gather reflected and transmitted light intensities. Using data from two SLE patients and two healthy volunteers, we demonstrate the potential of this FOIS for assessment of arthritis in SLE patients.

Changes in Diffuse Optical Tomography Images During Early Stages of Neoadjuvant Chemotherapy Correlate with Tumor Response in Different Breast Cancer Subtypes.

PURPOSE: This study's primary objective was to evaluate the changes in optically derived parameters acquired with a diffuse optical tomography breast imaging system (DOTBIS) in the tumor volume of patients with breast carcinoma receiving neoadjuvant chemotherapy (NAC). EXPERIMENTAL DESIGN: In this analysis of 105 patients with stage II-III breast cancer, normalized mean values of total hemoglobin ([Formula: see text]), oxyhemoglobin ([Formula: see text]), deoxy-hemoglobin concentration ([Formula: see text]), water, and oxygen saturation ([Formula: see text]) percentages were collected at different timepoints during NAC and compared with baseline measurements. This report compared changes in these optical biomarkers measured in patients who did not achieve a pathologic complete response (non-pCR) and those with a pCR. Differences regarding molecular subtypes were included for hormone receptor-positive and HER2-negative, HER2-positive, and triple-negative breast cancer. RESULTS: At baseline, [Formula: see text] was higher for pCR tumors (3.97 ± 2.29) compared with non-pCR tumors (3.00 ± 1.72; P = 0.031). At the earliest imaging point after starting therapy, the mean change of [Formula: see text] compared with baseline ([Formula: see text]) was statistically significantly higher in non-pCR (1.23 ± 0.67) than in those with a pCR (0.87 ± 0.61; P < 0.0005), and significantly correlated to residual cancer burden classification (r = 0.448; P < 0.0005). [Formula: see text] combined with HER2 status was proposed as a two-predictor logistic model, with AUC = 0.891; P < 0.0005; and 95% confidence interval, 0.812-0.969. CONCLUSIONS: This study demonstrates that DOTBIS measured features change over time according to tumor pCR status and may predict early in the NAC treatment course whether a patient is responding to NAC.

Diffuse optical tomography of the breast: a potential modifiable biomarker of breast cancer risk with neoadjuvant chemotherapy.

The purpose of this study is to evaluate whether a diffuse optical tomography breast imaging system (DOTBIS) can provide a comparable optical-based image index of mammographic breast density, an established biomarker of breast cancer risk. Oxyhemoglobin concentration (ctO2Hb) measured by DOTBIS was collected from 40 patients with stage II-III breast cancer. The tumor-free contralateral breast was used for this evaluation. We observed a moderate positive correlation between the patient's mammogram density classification and ctO2Hb, rs = 0.486 (p = 0.001). In addition, significant reduction in ctO2Hb levels were noted during neoadjuvant chemotherapy treatment (p = 0.017). This observation indicates that ctO2Hb levels measured by DOTBIS could be a novel modifiable imaging biomarker of breast cancer risk and warrants further investigation.

Optimal source-modulation frequencies for transport-theory-based optical tomography of small-tissue volumes.

In frequency-domain optical tomography (FDOT) the quality of the reconstruction result is affected by the choice of the source-modulation frequency. In general the accuracy of the reconstructed image should improve as the source-modulation frequency increases. However, this is only true for noise-free data. Experimental data is typically corrupted by noise and the accuracy is compromised. Assuming the validity of the widely used shot noise model, one can show that the signal-to-noise ratio (SNR) of the amplitude signal decreases with increasing frequency, whereas the SNR of the phase shift reaches peak values in the range between 400 MHz and 800 MHz. As a consequence, it can be assumed that there exists an optimal frequency for which the reconstruction accuracy would be highest. To determine optimal frequencies for FDOT, we investigate here the frequency dependence of optical tomographic reconstruction results using the frequency-domain equation of radiative transfer. We present numerical and experimental studies with a focus on small tissue volumes, as encountered in small animal and human finger imaging. Best reconstruction results were achieved in the 600-800 MHz frequency range.

Multiparameter classifications of optical tomographic images.

This research study explores the combined use of more than one parameter derived from optical tomographic images to increase diagnostic accuracy which is measured in terms of sensitivity and specificity. Parameters considered include, for example, smallest or largest absorption or scattering coefficients or the ratios thereof in an image region of interest. These parameters have been used individually in a previous study to determine if a finger joint is affected or not affected by rheumatoid arthritis. To combine these parameters in the analysis we employ here a vector quantization based classification method called Self-Organizing Mapping (SOM). This method allows producing multivariate ROC-curves from which sensitivity and specificities can be determined. We found that some parameter combinations can lead to higher sensitivities whereas others to higher specificities when compared to singleparameter classifications employed in previous studies. The best diagnostic accuracy, in terms of highest Youden index, was achieved by combining three absorption parameters [maximum(micro a), minimum(micro a), and the ratio of minimum(micro a) and maximum(micro a)], which result in a sensitivity of 0.78, a specificity of 0.76, a Youden index of 0.54, and an area under the curve (AUC) of 0.72. These values are higher than for previously reported single parameter classifications with a best sensitivity and specificity of 0.71, a Youden index of 0.41, and an AUC of 0.66.

Multipixel system for gigahertz frequency-domain optical imaging of finger joints.

Frequency-domain optical imaging systems have shown great promise for characterizing blood oxygenation, hemodynamics, and other physiological parameters in human and animal tissues. However, most of the frequency domain systems presented so far operate with source modulation frequencies below 150 MHz. At these low frequencies, their ability to provide accurate data for small tissue geometries such as encountered in imaging of finger joints or rodents is limited. Here, we present a new system that can provide data up to 1 GHz using an intensity modulated charged coupled device camera. After data processing, the images show the two-dimensional distribution of amplitude and phase of the light modulation on the finger surface. The system performance was investigated and test measurements on optical tissue phantoms were taken to investigate whether higher frequencies yield better signal-to-noise ratios (SNRs). It could be shown that local changes in optical tissue properties, as they appear in the initial stages of rheumatoid arthritis in a finger joint, are detectable by simple image evaluation, with the range of modulation frequency around 500 MHz proving to yield the highest SNR.

Special Section Guest Editorial: Pioneer in Biomedical Optics: Introduction to the Special Section in Honor of Steven L. Jacques.

This guest editorial introduces the special section honoring Prof. Steven L. Jacques.

Dynamic optical imaging of vascular and metabolic reactivity in rheumatoid joints.

Dynamic optical imaging is increasingly applied to clinically relevant areas such as brain and cancer imaging. In this approach, some external stimulus is applied and changes in relevant physiological parameters (e.g., oxy- or deoxyhemoglobin concentrations) are determined. The advantage of this approach is that the prestimulus state can be used as a reference or baseline against which the changes can be calibrated. Here we present the first application of this method to the problem of characterizing joint diseases, especially effects of rheumatoid arthritis (RA) in the proximal interphalangeal finger joints. Using a dual-wavelength tomographic imaging system together with previously implemented model-based iterative image reconstruction schemes, we have performed initial dynamic imaging case studies on a limited number of healthy volunteers and patients diagnosed with RA. Focusing on three cases studies, we illustrated our major finds. These studies support our hypothesis that differences in the vascular reactivity exist between affected and unaffected joints.

Digital-signal-processor-based dynamic imaging system for optical tomography.

In this article, we introduce a dynamic optical tomography system that is, unlike currently available analog instrumentation, based on digital data acquisition and filtering techniques. At the core of this continuous wave instrument is a digital signal processor (DSP) that collects, collates, processes, and filters the digitized data set. The processor is also responsible for managing system timing and the imaging routines which can acquire real-time data at rates as high as 150 Hz. Many of the synchronously timed processes are controlled by a complex programmable logic device that is also used in conjunction with the DSP to orchestrate data flow. The operation of the system is implemented through a comprehensive graphical user interface designed with LABVIEW software which integrates automated calibration, data acquisition, data organization, and signal postprocessing. Performance analysis demonstrates very low system noise (approximately 1 pW rms noise equivalent power), excellent signal precision (<0.04%-0.2%) and long term system stability (<1% over 40 min). A large dynamic range (approximately 190 dB) accommodates a wide scope of measurement geometries and tissue types. First experiments on tissue phantoms show that dynamic behavior is accurately captured and spatial location can be correctly tracked using this system.

Optical tomographic imaging of small animals.

Diffuse optical tomography is emerging as a viable new biomedical imaging modality. Using visible and near-infrared light this technique can probe the absorption and scattering properties of biological tissues. The main applications are currently in brain, breast, limb and joint imaging; however, optical tomographic imaging of small animals is attracting increasing attention. This interest is fuelled by recent advances in the transgenic manipulation of small animals that has led to many models of human disease. In addition, an ever increasing number of optically reactive biochemical markers has become available, which allow diseases to be detected at the molecular level long before macroscopic symptoms appear. The past three years have seen an array of novel technological developments that have led to the first optical tomographic studies of small animals in the areas of cerebral ischemia and cancer.