MRI-guided diffuse optical spectroscopy of malignant and benign breast lesions

Deep learning-based fusion of widefield diffuse optical tomography and micro-CT structural priors for accurate 3D reconstructions

Widefield illumination and detection strategies leveraging structured light have enabled fast and robust probing of tissue properties over large surface areas and volumes. However, when applied to diffuse optical tomography (DOT) applications, they still require a time-consuming and expert-centric solving of an ill-posed inverse problem. Deep learning (DL) models have been recently proposed to facilitate this challenging step. Herein, we expand on a previously reported deep neural network (DNN) -based architecture (modified AUTOMAP - ModAM) for accurate and fast reconstructions of the absorption coefficient in 3D DOT based on a structured light illumination and detection scheme. Furthermore, we evaluate the improved performances when incorporating a micro-CT structural prior in the DNN-based workflow, named Z-AUTOMAP. This Z-AUTOMAP significantly improves the widefield imaging process's spatial resolution, especially in the transverse direction. The reported DL-based strategies are validated both in silico and in experimental phantom studies using spectral micro-CT priors. Overall, this is the first successful demonstration of micro-CT and DOT fusion using deep learning, greatly enhancing the prospect of rapid data-integration strategies, often demanded in challenging pre-clinical scenarios.

In Vivo Validation of Diffuse Optical Imaging with a Dual-Direction Measuring Module of Parallel-Plate Architecture for Breast Tumor Detection

We demonstrate a working prototype of an optical breast imaging system involving parallel-plate architecture and a dual-direction scanning scheme designed in combination with a mammography machine; this system was validated in a pilot study to demonstrate its application in imaging healthy and malignant breasts in a clinical environment. The components and modules of the self-developed imaging system are demonstrated and explained, including its measuring architecture, scanning mechanism, and system calibration, and the reconstruction algorithm is presented. Additionally, the evaluation of feature indices that succinctly demonstrate the corresponding transmission measurements may provide insight into the existence of malignant tissue. Moreover, five cases are presented including one subject without disease (a control measure), one benign case, one suspected case, one invasive ductal carcinoma, and one positive case without follow-up treatment. A region-of-interest analysis demonstrated significant differences in absorption between healthy and malignant breasts, revealing the average contrast between the abnormalities and background tissue to exceed 1.4. Except for ringing artifacts, the average scattering property of the structure densities was 0.65–0.85 mm−1.

Deep-learning based image reconstruction for MRI-guided near-infrared spectral tomography

Non-invasive near-infrared spectral tomography (NIRST) can incorporate the structural information provided by simultaneous magnetic resonance imaging (MRI), and this has significantly improved the images obtained of tissue function. However, the process of MRI guidance in NIRST has been time consuming because of the needs for tissue-type segmentation and forward diffuse modeling of light propagation. To overcome these problems, a reconstruction algorithm for MRI-guided NIRST based on deep learning is proposed and validated by simulation and real patient imaging data for breast cancer characterization. In this approach, diffused optical signals and MRI images were both used as the input to the neural network, and simultaneously recovered the concentrations of oxy-hemoglobin, deoxy-hemoglobin, and water via end-to-end training by using 20,000 sets of computer-generated simulation phantoms. The simulation phantom studies showed that the quality of the reconstructed images was improved, compared to that obtained by other existing reconstruction methods. Reconstructed patient images show that the well-trained neural network with only simulation data sets can be directly used for differentiating malignant from benign breast tumors.

Evaluation of a pipeline for simulation, reconstruction, and classification in ultrasound-aided diffuse optical tomography of breast tumors

SIGNIFICANCE

Diffuse optical tomography is an ill-posed problem. Combination with ultrasound can improve the results of diffuse optical tomography applied to the diagnosis of breast cancer and allow for classification of lesions.

AIM

To provide a simulation pipeline for the assessment of reconstruction and classification methods for diffuse optical tomography with concurrent ultrasound information.

APPROACH

A set of breast digital phantoms with benign and malignant lesions was simulated building on the software VICTRE. Acoustic and optical properties were assigned to the phantoms for the generation of B-mode images and optical data. A reconstruction algorithm based on a two-region nonlinear fitting and incorporating the ultrasound information was tested. Machine learning classification methods were applied to the reconstructed values to discriminate lesions into benign and malignant after reconstruction.

RESULTS

The approach allowed us to generate realistic US and optical data and to test a two-region reconstruction method for a large number of realistic simulations. When information is extracted from ultrasound images, at least 75% of lesions are correctly classified. With ideal two-region separation, the accuracy is higher than 80%.

CONCLUSIONS

A pipeline for the generation of realistic ultrasound and diffuse optics data was implemented. Machine learning methods applied to a optical reconstruction with a nonlinear optical model and morphological information permit to discriminate malignant lesions from benign ones.

Accurately calibrated frequency domain diffuse optical spectroscopy compared against chemical analysis of porcine adipose tissue

Frequency domain diffuse optical spectroscopy (fdDOS) is a noninvasive technique to estimate tissue composition and hemodynamics. While fdDOS has been established as a valuable modality for clinical research, comparison of fdDOS with direct chemical analysis (CA) methods has yet to be reported. To compare the two approaches, we propose a procedure to confirm accurate calibration by use of liquid emulsion and solid silicone phantoms. Tissue fat (FAT) and water (H₂ O) content of two ex vivo porcine tissue samples were optically measured by fdDOS and compared to CA values. We show an average H₂ O error (fdDOS minus CA) and SD of 1.9 ± 0.2% and -0.9 ± 0.2% for the two samples. For FAT, we report a mean error of -9.3 ± 1.3% and 0.8 ± 1.3%. We also measured various body sites of a healthy human subject using fdDOS with results suggesting that accurate calibration may improve device sensitivity.

Performance assessment of MRI guided continuous wave near-infrared spectral tomography for breast imaging

Integration of magnetic resonance imaging (MRI) and near-infrared spectral tomography (NIRST) has yielded promising diagnostic performance for breast imaging in the past. This study focused on whether MRI-guided NIRST can quantify hemoglobin concentration using only continuous wave (CW) measurements. Patients were classified into four breast density groups based on their MRIs. Optical scattering properties were assigned based on average values obtained from these density groups, and MRI-guided NIRST images were reconstructed from calibrated CW data. Total hemoglobin (HbT) contrast between suspected lesions and surrounding normal tissue was used as an indicator of the malignancy. Results obtained from simulations and twenty-four patient cases indicate that the diagnostic power when using only CW data to differentiate malignant from benign abnormalities is similar to that obtained from combined frequency domain (FD) and CW data. These findings suggest that eliminating FD detection to reduce the cost and complexity of MRI-guided NIRST is possible.

Machine learning model with physical constraints for diffuse optical tomography

A machine learning model with physical constraints (ML-PC) is introduced to perform diffuse optical tomography (DOT) reconstruction. DOT reconstruction is an ill-posed and under-determined problem, and its quality suffers by model mismatches, complex boundary conditions, tissue-probe contact, noise etc. Here, for the first time, we combine ultrasound-guided DOT with ML to facilitate DOT reconstruction. Our method has two key components: (i) a neural network based on auto-encoder is adopted for DOT reconstruction, and (ii) physical constraints are implemented to achieve accurate reconstruction. Both qualitative and quantitative results demonstrate that the accuracy of the proposed method surpasses that of existing models. In a phantom study, compared with the Born conjugate gradient descent (Born-CGD) reconstruction method, the ML-PC method decreases the mean percentage error of the reconstructed maximum absorption coefficient from 16.41% to 13.4% for high contrast phantoms and from 23.42% to 9.06% for low contrast phantoms, with improved depth distribution of the target absorption maps. In a clinical study, better contrast was obtained between malignant and benign breast lesions, with the ratio of the medians of the maximum absorption coefficient improved from 1.63 to 2.22.

Enhanced diffuse optical tomographic reconstruction using concurrent ultrasound information

Multimodal imaging is an active branch of research as it has the potential to improve common medical imaging techniques. Diffuse optical tomography (DOT) is an example of a low resolution, functional imaging modality that typically has very low resolution due to the ill-posedness of its underlying inverse problem. Combining the functional information of DOT with a high resolution structural imaging modality has been studied widely. In particular, the combination of DOT with ultrasound (US) could serve as a useful tool for clinicians for the formulation of accurate diagnosis of breast lesions. In this paper, we propose a novel method for US-guided DOT reconstruction using a portable time-domain measurement system. B-mode US imaging is used to retrieve morphological information on the probed tissues by means of a semi-automatical segmentation procedure based on active contour fitting. A two-dimensional to three-dimensional extrapolation procedure, based on the concept of distance transform, is then applied to generate a three-dimensional edge-weighting prior for the regularization of DOT. The reconstruction procedure has been tested on experimental data obtained on specifically designed dual-modality silicon phantoms. Results show a substantial quantification improvement upon the application of the implemented technique. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Broadband diffuse optical spectroscopy of absolute methemoglobin concentration can distinguish benign and malignant breast lesions

SIGNIFICANCE

Noninvasive diffuse optical spectroscopy (DOS) is a promising adjunct diagnostic imaging technique for distinguishing benign and malignant breast lesions. Most DOS approaches require normalizing lesion biomarkers to healthy tissue since major tissue constituents exhibit large interpatient variations. However, absolute optical biomarkers are desirable as it avoids reference measurements which may be difficult or impractical to acquire.

AIM

Our goal is to determine whether absolute measurements of minor absorbers such as collagen and methemoglobin (metHb) can successfully distinguish lesions. We hypothesize that metHb would exhibit less interpatient variability and be more suitable as an absolute metric for malignancy. However, we would expect collagen to exhibit more variability, because unlike metHb, collagen is also present in the healthy tissue.

APPROACH

In this retrospective clinical study, 30 lesions with breast imaging reporting and database system score   (  BIRADS  )    >    =  3 (12 benign and 18 malignant) measured with broadband quantitative DOS were analyzed for their oxyhemoglobin (HbO), deoxyhemoglobin (HHb), water, lipids, collagen, metHb concentrations, and optical scattering characteristics. Wilcoxon rank sum test was used to compare benign and malignant lesions for all variables in both normalized and absolute forms.

RESULTS

Among all absolute DOS parameters considered, only absolute metHb was observed to be significant for lesion discrimination (0.43  ±  0.18  μM for benign versus 0.87  ±  0.32  μM for malignant, p  =  0.0002). Absolute metHb concentration was also determined to be the best predictor of malignancy with an area under the curve of 0.89.

CONCLUSIONS

Our findings demonstrate that lesion metHb concentration measured by DOS can improve noninvasive optical diagnosis of breast malignancies. Since metHb concentration found in normal breast tissue is extremely low, metHb may be a more direct indicator of malignancy that does not depend on other biomarkers found in healthy tissue with significant variability. Furthermore, absolute parameters require reduced measurement time and can be utilized in cases where healthy reference tissue is not available.

Localization of Fluorescent Targets in Deep Tissue With Expanded Beam Illumination for Studies of Cancer and the Brain

Imaging fluorescence through millimeters or centimeters of tissue has important in vivo applications, such as guiding surgery and studying the brain. Often, the important information is the location of one of more optical reporters, rather than the specifics of the local geometry, motivating the need for a localization method that provides this information. We present an optimization approach based on a diffusion model for the fast localization of fluorescent inhomogeneities in deep tissue with expanded beam illumination that simplifies the experiment and the reconstruction. We show that the position of a fluorescent inhomogeneity can be estimated while assuming homogeneous tissue parameters and without having to model the excitation profile, reducing the computational burden and improving the utility of the method. We perform two experiments as a demonstration. First, a tumor in a mouse is localized using a near infrared folate-targeted fluorescent agent (OTL38). This result shows that localization can quickly provide tumor depth information, which could reduce damage to healthy tissue during fluorescence-guided surgery. Second, another near infrared fluorescent agent (ATTO647N) is injected into the brain of a rat, and localized through the intact skull and surface tissue. This result will enable studies of protein aggregation and neuron signaling.

A review of optical breast imaging: Multi-modality systems for breast cancer diagnosis

This review of optical breast imaging describes basic physical and system principles and summarizes technological evolution with a focus on multi-modality platforms and recent clinical trial results. Ultrasound-guided diffuse optical tomography and co-registered ultrasound and photoacoustic imaging systems are emphasized as models of state of the art optical technology that are most conducive to clinical translation.

Optimal breast cancer diagnostic strategy using combined ultrasound and diffuse optical tomography

Ultrasound (US)-guided near-infrared diffuse optical tomography (DOT) has demonstrated great potential as an adjunct breast cancer diagnosis tool to US imaging alone, especially in reducing unnecessary benign biopsies. However, DOT data processing and image reconstruction speeds remain slow compared to the real-time speed of US. Real-time or near real-time diagnosis with DOT is an important step toward the clinical translation of US-guided DOT. Here, to address this important need, we present a two-stage diagnostic strategy that is both computationally efficient and accurate. In the first stage, benign lesions are identified in near real-time by use of a random forest classifier acting on the DOT measurements and the radiologists' US diagnostic scores. Any lesions that cannot be reliably classified by the random forest classifier will be passed on to the second stage which begins with image reconstruction. Functional information from the reconstructed hemoglobin concentrations is employed by a Support Vector Machine (SVM) classifier for diagnosis at the end of the second stage. This two-step classification approach which combines both perturbation data and functional features, results in improved classification, as denoted by the receiver operating characteristic (ROC) curve. Using this two-step approach, the area under the ROC curve (AUC) is 0.937 ± 0.009, with a sensitivity of 91.4% and specificity of 85.7%. In comparison, using functional features and US score yields an AUC of 0.892 ± 0.027, with a sensitivity of 90.2% and specificity of 74.5%. Most notably, the specificity is increased by more than 10% due to the implementation of the random forest classifier.

Fluorescence Imaging of Breast Tumors and Gastrointestinal Cancer

Optical imaging offers a high potential for noninvasive detection and therapy of cancer in humans. Recent advances in instrumentation for diffuse optical imaging have led to new capabilities for the detection of cancer in highly scattering tissue such as the female breast. In particular, fluorescence imaging was made applicable as a sensitive technique to image molecular probes in vivo. We review recent developments in the detection of breast cancer and fluorescence-guided surgery of the breast by contrast agents available for application on humans. Detection of cancer has been investigated with the unspecific contrast agents "indocyanine green" and "omocianine" so far. Hereby, indocyanine green was found to offer high potential for the differentiation of malignant and benign lesions by exploiting vessel permeability for macromolecules as a cancer-specific feature. Tumor-specific molecular targeting and activatable probes have been investigated in clinical trials for fluorescence-guided tumor margin detection. In this application, high spatial resolution can be achieved, since tumor regions are visualized mainly at the tissue surface. As another example of superficial tumor tissue, imaging of lesions in the gastrointestinal tract is discussed. Promising results have been obtained on high-risk patients with Barrett´s esophagus and with ulcerative colitis by administering 5-aminolevulinic acid which induces accumulation of protoporphyrin IX serving as a tumor-specific fluorescent marker. Time-gated fluorescence imaging and spectroscopy are effective ways to suppress underlying background from tissue autofluorescence. Furthermore, recently developed tumor-specific molecular probes have been demonstrated to be superior to white-light endoscopy offering new ways for early detection of malignancies in the gastrointestinal tract.

Twente Photoacoustic Mammoscope 2: system overview and three-dimensional vascular network images in healthy breasts

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.

Systematic study of the effect of ultrasound gel on the performances of time-domain diffuse optics and diffuse correlation spectroscopy

Recently, multimodal imaging has gained an increasing interest in medical applications thanks to the inherent combination of strengths of the different techniques. For example, diffuse optics is used to probe both the composition and the microstructure of highly diffusive media down to a depth of few centimeters, but its spatial resolution is intrinsically low. On the other hand, ultrasound imaging exhibits the higher spatial resolution of morphological imaging, but without providing solid constitutional information. Thus, the combination of diffuse optical imaging and ultrasound may improve the effectiveness of medical examinations, e.g. for screening or diagnosis of tumors. However, the presence of an ultrasound coupling gel between probe and tissue can impair diffuse optical measurements like diffuse optical spectroscopy and diffuse correlation spectroscopy, since it may provide a direct path for photons between source and detector. A systematic study on the effect of different ultrasound coupling fluids was performed on tissue-mimicking phantoms, confirming that a water-clear gel can produce detrimental effects on optical measurements when recovering absorption/reduced scattering coefficients from time-domain spectroscopy acquisitions as well as particle Brownian diffusion coefficient from diffuse correlation spectroscopy ones. On the other hand, we show the suitability for optical measurements of other types of diffusive fluids, also compatible with ultrasound imaging.

Reducing image artifact in diffuse optical tomography by iterative perturbation correction based on multiwavelength measurements

Ultrasound (US) guided diffuse optical tomography has demonstrated great potential for breast cancer diagnosis, treatment monitoring, and chemotherapy response prediction. Optical measurements of four different wavelengths are used to reconstruct unknown optical absorption maps, which are then used to calculate the hemoglobin concentration distribution of the US visible lesion. Reconstructed absorption maps are prone to image artifacts from outliers in measurement data from tissue heterogeneity, bad coupling between tissue and light guides, and motion by patient or operator. We propose an automated iterative perturbation correction algorithm to reduce image artifacts based on the structural similarity index (SSIM) of absorption maps of four optical wavelengths. The initial image is estimated from the truncated pseudoinverse solution. The SSIM was calculated for each wavelength to assess its similarity with other wavelengths. An absorption map is repeatedly reconstructed and projected back into measurement space to quantify projection error. Outlier measurements with highest projection errors are iteratively removed until all wavelength images are structurally similar with SSIM values greater than a threshold. Clinical data demonstrate statistically significant improvement in image artifact reduction.

Improving DOT reconstruction with a Born iterative method and US-guided sparse regularization

Ultrasound (US)-guided diffuse optical tomography (DOT) is a promising low-cost imaging technique for diagnosis and assessment of breast cancer. US-guided DOT is best implemented in reflection geometry, which can be co-registered with US pulse-echo imaging and also minimizes the tissue depth for adequate light penetration. However, due to intense light scattering, the DOT reconstruction problem is ill-posed. In this communication, we describe a new non-linear Born iterative reconstruction method with US-guided depth-dependent ℓ 1 sparse regularization for improving DOT reconstruction by incorporating a priori lesion depth and shape information from the co-registered US image. Our method iteratively solves the inverse problem by updating the photon-density wave using the finite difference method, computing the weight matrix based on Born approximation, and reconstructing the absorption map using the fast iterative shrinkage-thresholding optimization algorithm (FISTA). We validate our method using both phantom and patient data and compare the results with those using the first order linear Born method. Phantom experiments demonstrate that the non-linear Born method provides more accurate target absorption reconstruction and better resolution than the linear Born method. Clinical studies on 20 patients show that non-linear Born reconstructs more realistic tumor shapes than linear Born, and improves the malignant-to-benign lesion contrast ratio from 2.73 to 3.07 , which is a 12.5 % improvement. For lesions approximately more than 2.0 cm in diameter, the average malignant-to-benign lesion contrast ratio is increased from 2.68 to 3.31 , which is a 23.5 % improvement.

In vivo and in vitro application of near-infrared fiber optic probe for Ehrlich carcinoma distinction: Towards the development of real-time tumor margins assessment tool

This report describes a full-scale experiment on intradermal Ehrlich carcinoma (EC) differentiation in mouse model using NIR spectroscopy in diffuse reflectance mode and chemometric data processing. EC is widely used as an experimental tumor model due to its resemblance with human undifferentiated epithelial tumors and can be applied as a preclinical testing in order to verify the capability of NIR spectroscopy to distinguish cancer from healthy tissues before a clinical research with an aim of creating a new analytical tool for on-line intraoperative tumor margins assessment. The study consists of five steps of NIR spectra measurements: in vivo on the early stage of carcinoma growth; in vivo on the advanced stage of carcinoma growth; in vivo during the surgery; in vitro study of the post-operative materials stored in formalin; in vitro study of the post-operative materials stored in paraffin. It was shown that reliable tumor differentiation with a compact optic fiber probe was possible in all these cases. The classification models were built on two data sets, obtained during in vivo and in vitro measurements; both of them demonstrated 100% specificity and sensitivity.

Comparison of Lipid and Water Contents by Time-domain Diffuse Optical Spectroscopy and Dual-energy Computed Tomography in Breast Cancer Patients

We previously compared time-domain diffuse optical spectroscopy (TD-DOS) with magnetic resonance imaging (MRI) using various water/lipid phantoms. However, it is difficult to conduct similar comparisons in the breast, because of measurement differences due to modality-dependent differences in posture. Dual-energy computed tomography (DECT) examination is performed in the same supine position as a TD-DOS measurement. Therefore, we first verified the accuracy of the measured fat fraction of fibroglandular tissue in the normal breast on DECT by comparing it with MRI in breast cancer patients (n = 28). Then, we compared lipid and water signals obtained in TD-DOS and DECT from normal and tumor-tissue regions (n = 16). The TD-DOS breast measurements were carried out using reflectance geometry with a source–detector separation of 3 cm. A semicircular region of interest (ROI), with a transverse diameter of 3 cm and a depth of 2 cm that included the breast surface, was set on the DECT image. Although the measurement area differed between the modalities, the correlation coefficients of lipid and water signals between TD-DOS and DECT were rs = 0.58 (p < 0.01) and rs = 0.90 (p < 0.01), respectively. These results indicate that TD-DOS captures the characteristics of the lipid and water contents of the breast.

An Automated Preprocessing Method for Diffuse Optical Tomography to Improve Breast Cancer Diagnosis

The ultrasound-guided diffuse optical tomography is a noninvasive imaging technique for breast cancer diagnosis and treatment monitoring. The technique uses a handheld probe capable of providing measurements of multiple wavelengths in a few seconds. These measurements are used to estimate optical absorptions of lesions and calculate the total hemoglobin concentration. Any measurement errors caused by low signal to noise ratio data and/or movements during data acquisition would reduce the accuracy of reconstructed total hemoglobin concentration. In this article, we introduce an automated preprocessing method that combines data collected from multiple sets of lesion measurements of 4 optical wavelengths to detect and correct outliers in the perturbation. Two new measures of correlation between each pair of wavelength measurements and a wavelength consistency index of all reconstructed absorption maps are introduced. For phantom and patients' data without evidence of measurement errors, the correlation coefficient between each pair of wavelength measurements was above 0.6. However, for patients with measurement errors, the correlation coefficient was much lower. After applying the correction method to 18 patients' data with measurement errors, the correlation has improved and the wavelength consistency index is in the same range as the cases without wavelength-dependent measurement errors. The results show an improvement in classification of malignant and benign lesions.

Hybrid time-domain and continuous-wave diffuse optical tomography instrument with concurrent, clinical magnetic resonance imaging for breast cancer imaging

Diffuse optical tomography has demonstrated significant potential for clinical utility in the diagnosis and prognosis of breast cancer, and its use in combination with other structural imaging modalities improves lesion localization and the quantification of functional tissue properties. Here, we introduce a hybrid diffuse optical imaging system that operates concurrently with magnetic resonance imaging (MRI) in the imaging suite, utilizing commercially available MR surface coils. The instrument acquires both continuous-wave and time-domain diffuse optical data in the parallel-plate geometry, permitting both absolute assignment of tissue optical properties and three-dimensional tomography; moreover, the instrument is designed to incorporate diffuse correlation spectroscopic measurements for probing tissue blood flow. The instrument is described in detail here. Image reconstructions of a tissue phantom are presented as an initial indicator of the system's ability to accurately reconstruct optical properties and the concrete benefits of the spatial constraints provided by concurrent MRI. Last, we briefly discuss how various data combinations that the instrument could facilitate, including tissue perfusion, can enable more comprehensive assessment of lesion physiology.

Back-propagation neural network-based reconstruction algorithm for diffuse optical tomography

Diffuse optical tomography (DOT) is a promising noninvasive imaging modality and is capable of providing functional characteristics of biological tissue by quantifying optical parameters. The DOT image reconstruction is ill-posed and ill-conditioned, due to the highly diffusive nature of light propagation in biological tissues and limited boundary measurements. The widely used regularization technique for DOT image reconstruction is Tikhonov regularization, which tends to yield oversmoothed and low-quality images containing severe artifacts. It is necessary to accurately choose a regularization parameter for Tikhonov regularization. To overcome these limitations, we develop a noniterative reconstruction method, whereby optical properties are recovered based on a back-propagation neural network (BPNN). We train the parameters of BPNN before DOT image reconstruction based on a set of training data. DOT image reconstruction is achieved by implementing a single evaluation of the trained network. To demonstrate the performance of the proposed algorithm, we compare with the conventional Tikhonov regularization-based reconstruction method. The experimental results demonstrate that image quality and quantitative accuracy of reconstructed optical properties are significantly improved with the proposed algorithm.

Compact ultrasound-guided diffuse optical tomography system for breast cancer imaging

Near-infrared diffuse optical tomography (DOT) has demonstrated a great potential as an adjunct modality for differentiation of malignant and benign breast lesions and for monitoring treatment response in patients with locally advanced breast cancers. The path toward commercialization of DOT techniques depends upon the improvement of robustness and user-friendliness of this technique in hardware and software. In this study, we introduce our recently developed ultrasound-guided DOT system, which has been improved in system compactness, robustness, and user-friendliness by custom-designed electronics, automated data preprocessing, and implementation of a new two-step reconstruction algorithm. The system performance has been tested with several sets of solid and blood phantoms and the results show accuracy in reconstructed absorption coefficients as well as blood oxygen saturation. A clinical example of a breast cancer patient, who was undergoing neoadjuvant chemotherapy, is given to demonstrate the system performance.

Weighting function effects in a direct regularization method for image-guided near-infrared spectral tomography of breast cancer

Structural image-guided near-infrared spectral tomography (NIRST) has been developed as a way to use diffuse NIR spectroscopy within the context of image-guided quantification of tissue spectral features. A direct regularization imaging (DRI) method for NIRST has the value of not requiring any image segmentation. Here, we present a comprehensive investigational study to analyze the impact of the weighting function implied when weighting the recovery of optical coefficients in DRI based NIRST. This was done using simulations, phantom and clinical patient exam data. Simulations where the true object is known indicate that changes to this weighting function can vary the contrast by 10%, the contrast to noise ratio by 20% and the full width half maximum (FWHM) by 30%. The results from phantoms and human images show that a linear inverse distance weighting function appears optimal, and that incorporation of this function can generally improve the recovered total hemoglobin contrast of the tumor to the normal surrounding tissue by more than 15% in human cases.

Single-breath-hold photoacoustic computed tomography of the breast

We have developed a single-breath-hold photoacoustic computed tomography (SBH-PACT) system to reveal detailed angiographic structures in human breasts. SBH-PACT features a deep penetration depth (4 cm in vivo) with high spatial and temporal resolutions (255 µm in-plane resolution and a 10 Hz 2D frame rate). By scanning the entire breast within a single breath hold (~15 s), a volumetric image can be acquired and subsequently reconstructed utilizing 3D back-projection with negligible breathing-induced motion artifacts. SBH-PACT clearly reveals tumors by observing higher blood vessel densities associated with tumors at high spatial resolution, showing early promise for high sensitivity in radiographically dense breasts. In addition to blood vessel imaging, the high imaging speed enables dynamic studies, such as photoacoustic elastography, which identifies tumors by showing less compliance. We imaged breast cancer patients with breast sizes ranging from B cup to DD cup, and skin pigmentations ranging from light to dark. SBH-PACT identified all the tumors without resorting to ionizing radiation or exogenous contrast, posing no health risks.

Direct Regularization From Co-Registered Contrast MRI Improves Image Quality of MRI-Guided Near-Infrared Spectral Tomography of Breast Lesions

An approach using direct regularization from co-registered dynamic contrast enhanced magnetic reson- ance images was used to reconstruct near-infrared spectral tomography patient images, which does not need image segmentation. 20 patients with mammography/ultrasound confirmed breast abnormalities were involved in this paper, and the resulting images indicated that tumor total hemoglobin concentration contrast differentiated malignant from benign cases (p-value = 0.021). The approach prod- uced reconstructed images, which significantly reduced surface artifacts near the source-detector locations (p-value = 4.16e-6).

Correlations Among Ultrasound-Guided Diffuse Optical Tomography, Microvessel Density, and Breast Cancer Prognosis

OBJECTIVES

To investigate the correlation among ultrasound-guided diffuse optical tomography (DOT), microvessel density, and breast cancer prognosis.

METHODS

Before surgery, the total hemoglobin (Hb) concentrations of 184 female patients with breast cancer with only a single lesion were measured. During follow-up, 23 patients had recurrence or metastatic disease after surgery. Among these patients, 18 with recurrence or metastatic disease within 3 years after surgery were paired with 18 patients without recurrence or metastatic disease. We retrospectively reviewed the pathologic sections of those 36 patients, conducted immunohistochemical staining, and counted the microvessel densities. Then we analyzed the correlation between microvessel density and total Hb, compared total Hb and microvessel density among breast cancers with different prognoses, and tested the value of DOT in predicting the prognosis of breast cancer.

RESULTS

Microvessel density and total Hb were linearly correlated (r = 0.584; P < .001). Total Hb and microvessel density were significantly increased in the metastasis group (P = .001 and .027, respectively). A receiver operating characteristic curve analysis showed that at a total Hb cutoff value of 221.7 μmol/L, the sensitivity, specificity, and area under the curve of DOT for predicting recurrence or metastasis were 0.826, 0.516, and 0.660, respectively.

CONCLUSIONS

The total Hb concentration can reflect a tumor's blood supply. Patients with a high total Hb concentration and microvessel density have a higher risk for a poorer prognosis. Total Hb can be used as an indicator of breast cancer prognosis. Diffuse optical tomography can help physicians identify patients with a high risk of metastasis and make clinical decisions.

Emerging Breast Imaging Technologies on the Horizon

Early detection of breast cancers by mammography in conjunction with adjuvant therapy has contributed to reduction in breast cancer mortality. Mammography remains the "gold-standard" for breast cancer screening but is limited by tissue superposition. Digital breast tomosynthesis and more recently, dedicated breast computed tomography have been developed to alleviate the tissue superposition problem. However, all of these modalities rely upon x-ray attenuation contrast to provide anatomical images, and there are ongoing efforts to develop and clinically translate alternative modalities. These emerging modalities could provide for new contrast mechanisms and may potentially improve lesion detection and diagnosis. In this article, several of these emerging modalities are discussed with a focus on technologies that have advanced to the stage of in vivo clinical evaluation.

Collagen quantification in breast tissue using a 12-wavelength near infrared spectral tomography (NIRST) system

A portable near infrared spectral tomography (NIRST) system was adapted for breast cancer detection and treatment monitoring with improved speed of acquisition for parallel 12 wavelengths of parallel frequency-domain (FD) and continuous-wavelength (CW) measurement. Using a novel gain adjustment scheme in the Photomultiplier Tube detectors (PMTs), the data acquisition time for simultaneous acquisition involving three FD and three CW wavelengths, has been reduced from 90 to 55 seconds, while signal variation was also reduced from 2.1% to 1.1%. Tomographic images of breast collagen content have been recovered for the first time, and image reconstruction approaches with and without collagen content included have been validated in simulation studies and normal subject exams. Simulations indicate that including collagen content into the reconstruction procedure can significantly reduce the overestimation in total hemoglobin, water and lipid by 8.9μM, 1.8% and 15.8%, respectively, and underestimates in oxygen saturation by 9.5%, given an average 10% background collagen content. A breast cancer patient with invasive ductal carcinoma was imaged and the reconstructed images show that the recovered tumor/background contrast in total hemoglobin increased from 1.5 to 1.7 when collagen was included in reconstruction.

Multispectral optoacoustic tomography of the human breast: characterisation of healthy tissue and malignant lesions using a hybrid ultrasound-optoacoustic approach

BACKGROUND AND AIM

Multispectral optoacoustic tomography (MSOT) represents a new in vivo imaging technique with high resolution (~250 μm) and tissue penetration (>1 cm) using the photoacoustic effect. While ultrasound contains anatomical information for lesion detection, MSOT provides functional information based on intrinsic tissue chromophores. We aimed to evaluate the feasibility of combined ultrasound/MSOT imaging of breast cancer in patients compared to healthy volunteers.

METHODS

Imaging was performed using a handheld MSOT system for clinical use in healthy volunteers (n = 6) and representative patients with histologically confirmed invasive breast carcinoma (n = 5) and ductal carcinoma in situ (DCIS, n = 2). MSOT values for haemoglobin and oxygen saturation were assessed at 0.5, 1.0 and 1.5 cm depth and selected wavelengths between 700 and 850 nm.

RESULTS

Reproducible signals were obtained in all wavelengths with consistent MSOT signals in superficial tissue in breasts of healthy individuals. In contrast, we found increased signals for haemoglobin in invasive carcinoma, suggesting a higher perfusion of the tumour and tumour environment. For DCIS, MSOT values showed only little variation compared to healthy tissue.

CONCLUSIONS

This preliminary MSOT breast imaging study provided stable, reproducible data on tissue composition and physiological properties, potentially enabling differentiation of solid malignant and healthy tissue.

KEY POINTS

• A handheld MSOT probe enables real-time molecular imaging of the breast. • MSOT of healthy controls provides a reproducible reference for pathology identification. • MSOT parameters allows for differentiation of invasive carcinoma and healthy tissue.

Heterodyne frequency-domain multispectral diffuse optical tomography of breast cancer in the parallel-plane transmission geometry

PURPOSE

The authors introduce a state-of-the-art all-optical clinical diffuse optical tomography (DOT) imaging instrument which collects spatially dense, multispectral, frequency-domain breast data in the parallel-plate geometry.

METHODS

The instrument utilizes a CCD-based heterodyne detection scheme that permits massively parallel detection of diffuse photon density wave amplitude and phase for a large number of source-detector pairs (10(6)). The stand-alone clinical DOT instrument thus offers high spatial resolution with reduced crosstalk between absorption and scattering. Other novel features include a fringe profilometry system for breast boundary segmentation, real-time data normalization, and a patient bed design which permits both axial and sagittal breast measurements.

RESULTS

The authors validated the instrument using tissue simulating phantoms with two different chromophore-containing targets and one scattering target. The authors also demonstrated the instrument in a case study breast cancer patient; the reconstructed 3D image of endogenous chromophores and scattering gave tumor localization in agreement with MRI.

CONCLUSIONS

Imaging with a novel parallel-plate DOT breast imager that employs highly parallel, high-resolution CCD detection in the frequency-domain was demonstrated.

Diffuse optical tomography reconstruction method using ultrasound images as prior for regularization matrix

Ultrasound-guided diffuse optical tomography (DOT) is a promising imaging technique that maps hemoglobin concentrations of breast lesions to assist ultrasound (US) for cancer diagnosis and treatment monitoring. The accurate recovery of breast lesion optical properties requires an effective image reconstruction method. We introduce a reconstruction approach in which US images are encoded as prior information for regularization of the inversion matrix. The framework of this approach is based on image reconstruction package “NIRFAST.” We compare this approach to the US-guided dual-zone mesh reconstruction method, which is based on Born approximation and conjugate gradient optimization developed in our laboratory. Results were evaluated using phantoms and clinical data. This method improves classification of malignant and benign lesions by increasing malignant to benign lesion absorption contrast. The results also show improvements in reconstructed lesion shapes and the spatial distribution of absorption maps.

Diffuse optical tomography for breast cancer imaging guided by computed tomography: A feasibility study

Diffuse optical tomography (DOT) has attracted attentions in the last two decades due to its intrinsic sensitivity in imaging chromophores of tissues such as hemoglobin, water, and lipid. However, DOT has not been clinically accepted yet due to its low spatial resolution caused by strong optical scattering in tissues. Structural guidance provided by an anatomical imaging modality enhances the DOT imaging substantially. Here, we propose a computed tomography (CT) guided multispectral DOT imaging system for breast cancer imaging. To validate its feasibility, we have built a prototype DOT imaging system which consists of a laser at the wavelength of 650 nm and an electron multiplying charge coupled device (EMCCD) camera. We have validated the CT guided DOT reconstruction algorithms with numerical simulations and phantom experiments, in which different imaging setup parameters, such as projection number of measurements and width of measurement patch, have been investigated. Our results indicate that an air-cooling EMCCD camera is good enough for the transmission mode DOT imaging. We have also found that measurements at six angular projections are sufficient for DOT to reconstruct the optical targets with 2 and 4 times absorption contrast when the CT guidance is applied. Finally, we have described our future research plan on integration of a multispectral DOT imaging system into a breast CT scanner.

Molecular imaging and cancer gene therapy

Gene therapy is known as one of the most advanced approaches for therapeutic prospects ranging from tackling genetic diseases to combating cancer. In this approach, different viral and nonviral vector systems such as retrovirus, lentivirus, plasmid and transposon have been designed and employed. These vector systems are designed to target different therapeutic genes in various tissues and cells such as tumor cells. Therefore, detection of the vectors containing therapeutic genes and monitoring of response to the treatment are the main issues that are commonly faced by researchers. Imaging techniques have been critical in guiding physicians in the more accurate and precise diagnosis and monitoring of cancer patients in different phases of malignancies. Imaging techniques such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT) are non-invasive and powerful tools for monitoring of the distribution of transgene expression over time and assessing patients who have received therapeutic genes. Here, we discuss most recent advances in cancer gene therapy and molecular approaches as well as imaging techniques that are utilized to detect cancer gene therapeutics and to monitor the patients' response to these therapies worldwide, particularly in Iranian Academic Medical Centers and Hospitals.Cancer Gene Therapy advance online publication, 18 November 2016; doi:10.1038/cgt.2016.62.

Imaging techniques: new avenues in cancer gene and cell therapy

Cancer is one of the world's most concerning health problems and poses many challenges in the range of approaches associated with the treatment of cancer. Current understanding of this disease brings to the fore a number of novel therapies that can be useful in the treatment of cancer. Among them, gene and cell therapies have emerged as novel and effective approaches. One of the most important challenges for cancer gene and cell therapies is correct monitoring of the modified genes and cells. In fact, visual tracking of therapeutic cells, immune cells, stem cells and genetic vectors that contain therapeutic genes and the various drugs is important in cancer therapy. Similarly, molecular imaging, such as nanosystems, fluorescence, bioluminescence, positron emission tomography, single photon-emission computed tomography and magnetic resonance imaging, have also been found to be powerful tools in monitoring cancer patients who have received therapeutic cell and gene therapies or drug therapies. In this review, we focus on these therapies and their molecular imaging techniques in treating and monitoring the progress of the therapies on various types of cancer.

Optical mammography: bilateral breast symmetry in hemoglobin saturation maps

We present a study of the bilateral symmetry of human breast hemoglobin saturation maps measured with a broadband optical mammography instrument. We have imaged 21 patients with unilateral breast cancer, 32 patients with unilateral benign lesions, and 27 healthy patients. An image registration process was applied to the bilateral hemoglobin saturation (SO 2 SO2 ) images by assigning each pixel to the low, middle, or high range of SO 2 SO2 values, where the thresholds for the categories were the 15th and 85th percentiles of the individual saturation range. The Dice coefficient, which is a measure of similarity, was calculated for each patient’s pair of right and left breast SO 2 SO2 images. The invasive cancer patients were found to have an average Dice coefficient value of 0.55±0.07 0.55±0.07 , which was significantly lower than the benign and healthy groups (0.61±0.11 0.61±0.11 and 0.62±0.12 0.62±0.12 , respectively). Although differences were seen in a group analysis, the healthy patient Dice coefficients spanned a wide range, limiting the diagnostic capabilities of this SO 2 SO2 symmetry analysis on an individual basis. Our results suggest that for assessing the SO 2 SO2 contrast of breast lesions, it may be better to select a reference tissue in the ipsilateral rather than the contralateral breast.

Automated data selection method to improve robustness of diffuse optical tomography for breast cancer imaging

Imaging-guided near infrared diffuse optical tomography (DOT) has demonstrated a great potential as an adjunct modality for differentiation of malignant and benign breast lesions and for monitoring treatment response of breast cancers. However, diffused light measurements are sensitive to artifacts caused by outliers and errors in measurements due to probe-tissue coupling, patient and probe motions, and tissue heterogeneity. In general, pre-processing of the measurements is needed by experienced users to manually remove these outliers and therefore reduce imaging artifacts. An automated method of outlier removal, data selection, and filtering for diffuse optical tomography is introduced in this manuscript. This method consists of multiple steps to first combine several data sets collected from the same patient at contralateral normal breast and form a single robust reference data set using statistical tests and linear fitting of the measurements. The second step improves the perturbation measurements by filtering out outliers from the lesion site measurements using model based analysis. The results of 20 malignant and benign cases show similar performance between manual data processing and automated processing and improvement in tissue characterization of malignant to benign ratio by about 27%.

Effects of breast density and compression on normal breast tissue hemodynamics through breast tomosynthesis guided near-infrared spectral tomography

Optically derived tissue properties across a range of breast densities and the effects of breast compression on estimates of hemoglobin, oxygen metabolism, and water and lipid concentrations were obtained from a coregistered imaging system that integrates near-infrared spectral tomography (NIRST) with digital breast tomosynthesis (DBT). Image data were analyzed from 27 women who underwent four IRB approved NIRST/DBT exams that included fully and mildly compressed breast acquisitions in two projections—craniocaudal (CC) and mediolateral-oblique (MLO)—and generated four data sets per patient (full and moderate compression in CC and MLO views). Breast density was correlated with HbT (r=0.64, p=0.001), water (r=0.62, p=0.003), and lipid concentrations (r=?0.74, p<0.001), but not oxygen saturation. CC and MLO views were correlated for individual subjects and demonstrated no statistically significant differences in grouped analysis. Comparison of compressed and uncompressed imaging demonstrated a significant decrease in oxygen saturation under compression (58% versus 50%, p=0.04). Mammographic breast density categorization was correlated with measured optically derived properties.

Multiobjective guided priors improve the accuracy of near-infrared spectral tomography for breast imaging

An image reconstruction regularization approach for magnetic resonance imaging-guided near-infrared spectral tomography has been developed to improve quantification of total hemoglobin (HbT) and water. By combining prior information from dynamic contrast enhanced (DCE) and diffusion weighted (DW) MR images, the absolute bias errors of HbT and water in the tumor were reduced by 22% and 18%, 21% and 6%, and 10% and 11%, compared to that in the no-prior, DCE- or DW-guided reconstructed images in three-dimensional simulations, respectively. In addition, the apparent contrast values of HbT and water were increased in patient image reconstruction from 1.4 and 1.4 (DCE) or 1.8 and 1.4 (DW) to 4.6 and 1.6.

Computational Model for Tumor Oxygenation Applied to Clinical Data on Breast Tumor Hemoglobin Concentrations Suggests Vascular Dilatation and Compression

We present a computational model for trans-vascular oxygen transport in synthetic tumor and host tissue blood vessel networks, aiming at qualitatively explaining published data of optical mammography, which were obtained from 87 breast cancer patients. The data generally show average hemoglobin concentration to be higher in tumors versus host tissue whereas average oxy-to total hemoglobin concentration (vascular segment RBC-volume-weighted blood oxygenation) can be above or below normal. Starting from a synthetic arterio-venous initial network the tumor vasculature was generated by processes involving cooption, angiogenesis, and vessel regression. Calculations of spatially resolved blood flow, hematocrit, oxy- and total hemoglobin concentrations, blood and tissue oxygenation were carried out for ninety tumor and associated normal vessel networks starting from various assumed geometries of feeding arteries and draining veins. Spatial heterogeneity in the extra-vascular partial oxygen pressure distribution can be related to various tumor compartments characterized by varying capillary densities and blood flow characteristics. The reported higher average hemoglobin concentration of tumors is explained by growth and dilatation of tumor blood vessels. Even assuming sixfold metabolic rate of oxygen consumption in tumorous versus host tissue, the predicted oxygen hemoglobin concentrations are above normal. Such tumors are likely associated with high tumor blood flow caused by high-caliber blood vessels crossing the tumor volume and hence oxygen supply exceeding oxygen demand. Tumor oxy- to total hemoglobin concentration below normal could only be achieved by reducing tumor vessel radii during growth by a randomly selected factor, simulating compression caused by intra-tumoral solid stress due to proliferation of cells and extracellular matrix. Since compression of blood vessels will impede chemotherapy we conclude that tumors with oxy- to total hemoglobin concentration below normal are less likely to respond to chemotherapy. Such behavior was recently reported for neo-adjuvant chemotherapy of locally advanced breast tumors.

Assessment of Functional Differences in Malignant and Benign Breast Lesions and Improvement of Diagnostic Accuracy by Using US-guided Diffuse Optical Tomography in Conjunction with Conventional US

Purpose To investigate ultrasonography (US)-guided diffuse optical tomography to distinguish the functional differences of hemoglobin concentrations in a wide range of malignant and benign breast lesions and to improve breast cancer diagnosis in conjunction with conventional US. Materials and Methods The study protocol was approved by the institutional review boards and was HIPAA compliant. Written informed consent was obtained from all patients. Patients (288 women; mean age, 50 years; range, 17-94 years) who underwent US-guided biopsy were imaged with a handheld US and optical probe. The US-imaged lesion was used to guide reconstruction of light absorption maps at four wavelengths, and total hemoglobin (tHb), oxygenated hemoglobin (oxyHb), and deoxygenated hemoglobin (deoxyHb) were computed from the absorption maps. A threshold (80 μmol/L) was chosen on the basis of this study population. Two radiologists retrospectively evaluated US images on the basis of the US Breast Imaging Reporting and Data System lexicon, and a lesion was considered malignant when a score of 4C or 5 was given or a lesion had tHb greater than 80 μmol/L. A two-sample t test was used to calculate significance between groups, and Spearman ρ was computed between hemoglobin parameters and tumor pathologic grades. Results Three tumors were Tis, 37 were T1, 19 were T2-T4 carcinomas, and 233 were benign lesions. The mean maximum tHb, oxyHb, and deoxyHb of Tis-T1 and T2-T4 groups were 89.3 μmol/L ± 20.2 (standard deviation), 65.0 μmol/L ± 20.8, and 33.5 μmol/L ± 11.3, respectively, and 84.7 μmol/L ± 32.8, 57.1 μmol/L ± 19.8, and 34.7 μmol/L ± 18.9, respectively. The corresponding values of benign lesions were 54.1 μmol/L ± 23.5, 38.0 μmol/L ± 17.4, and 25.2 μmol/L ± 13.8, respectively. The mean maximum tHb, oxyHb, and deoxyHb were significantly higher in the malignant groups than the benign group (P <.001, <.001, and .041, respectively). For malignant lesions, the mean maximum tHb moderately correlated with tumor histologic grade and nuclear grade (ρ = 0.283 and 0.315, respectively). The mean maximum oxyHb moderately correlated with tumor nuclear grade (ρ = 0.267). When radiologists' US diagnosis and the tHb were used together, the sensitivity, specificity, positive predictive value, and negative predictive value were 96.6%-100%, 77.3%-83.3%, 52.7%-59.4%, and 99.0%-100%, respectively, for the combined malignant group. Conclusion The tHb and oxyHb correlate with breast cancer pathologic grade and can be used as an adjunct to US to improve sensitivity and negative predictive value in breast cancer diagnosis. (©) RSNA, 2016 Online supplemental material is available for this article.

NIR Spectroscopic Detection of Breast Cancer

Near infrared spectroscopy (NIRS) utilizes intrinsic optical absorption signals of blood, water, and lipid concentration available in the NIR window (600–1000 nm) as well as a developing array of extrinsic organic compounds to detect and localize cancer. This paper reviews optical cancer detection made possible through high tumor-tissue signal-to-noise ratio (SNR) and providing biochemical and physiological data in addition to those obtained via other methods.

NIRS detects cancers in vivo through a combination of blood volume and oxygenation from measurements of oxy- and deoxy-hemoglobin giving signals of tumor angiogenesis and hypermetabolism. The Chance lab tends towards CW breast cancer systems using manually scannable detectors with calibrated low pressure tissue contact. These systems calculate angiogenesis and hypermetabolism by using a pair of wavelengths and referencing the mirror image position of the contralateral breast to achieve high ROC/AUC. Time domain and frequency domain spectroscopy were also used to study similar intrinsic breast tumor characteristics such as high blood volume. Other NIRS metrics are water-fat ratio and the optical scattering coefficient. An extrinsic FDA approved dye, ICG, has been used to measure blood pooling with extravasation, similar to Gadolinium in MRI.

A key future development in NIRS will be new Molecular Beacons targeting cancers and fluorescing in the NIR window to enhance in vivo tumor-tissue ratios and to afford biochemical specificity with the potential for effective photodynamic anti-cancer therapies.

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.

High resolution functional photoacoustic tomography of breast cancer

PURPOSE

To evaluate the feasibility of functional photoacoustic tomography (fPAT) for high resolution detection and characterization of breast cancer and to demonstrate for the first time quantitative hemoglobin concentration and oxygen saturation images of breasts that were formed with model-based reconstruction of tomographic photoacoustic data.

METHODS

The study was HIPAA compliant and was approved by the university institutional review board. Written informed consents were obtained from all the participants. Ten cases, including six cancer and four healthy (mean age = 50 yr; age range = 41-66 yr), were examined. Functional images of breast tissue including absolute total hemoglobin concentration (HbT) and oxygen saturation (StO2%) were obtained by fPAT and cross validated with magnetic resonance imaging (MRI) readings and/or histopathology.

RESULTS

HbT and StO2% maps from all six pathology-confirmed cancer cases (60%) show clear detection of tumor, while MR images indicate clear detection of tumor for five of six cancer cases; one small tumor was read as near-complete-resolution by MRI. The average HbT and StO2% value of suspicious lesion area for the cancer cases was 61.6 ± 18.9 μM/l and 67.5% ± 5.2% compared to 25.6 ± 7.4 μM/l and 65.2% ± 3.8% for background normal tissue.

CONCLUSIONS

fPAT has the potential to be a significant add-on in breast cancer detection and characterization as it provides submillimeter resolution functional images of breast lesions.

Portable, parallel 9-wavelength near-infrared spectral tomography (NIRST) system for efficient characterization of breast cancer within the clinical oncology infusion suite

A portable near-infrared spectral tomography (NIRST) system was developed with simultaneous frequency domain (FD) and continuous-wave (CW) optical measurements for efficient characterization of breast cancer in a clinical oncology setting. Simultaneous FD and CW recordings were implemented to speed up acquisition to 3 minutes for all 9 wavelengths, spanning a range from 661nm to 1064nm. An adjustable interface was designed to fit various breast sizes and shapes. Spatial images of oxy- and deoxy-hemoglobin, water, lipid, and scattering components were reconstructed using a 2D FEM approach. The system was tested on a group of 10 normal subjects, who were examined bilaterally and the recovered optical images were compared to radiographic breast density. Significantly higher total hemoglobin and water were estimated in the high density relative to low density groups. One patient with invasive ductal carcinoma was also examined and the cancer region was characterized as having a contrast ratio of 1.4 in total hemoglobin and 1.2 in water.

Calibration and optimization of 3D digital breast tomosynthesis guided near infrared spectral tomography

Calibration of a three-dimensional multimodal digital breast tomosynthesis (DBT) x-ray and non-fiber based near infrared spectral tomography (NIRST) system is challenging but essential for clinical studies. Phantom imaging results yielded linear contrast recovery of total hemoglobin (HbT) concentration for cylindrical inclusions of 15 mm, 10 mm and 7 mm with a 3.5% decrease in the HbT estimate for each 1 cm increase in inclusion depth. A clinical exam of a patient's breast containing both benign and malignant lesions was successfully imaged, with greater HbT was found in the malignancy relative to the benign abnormality and fibroglandular regions (11 μM vs. 9.5 μM). Tools developed improved imaging system characterization and optimization of signal quality, which will ultimately improve patient selection and subsequent clinical trial results.

Noninvasive Surface Imaging of Breast Cancer in Humans using a Hand-held Optical Imager

X-ray mammography, the current gold standard for breast cancer detection, has a 20% false-negative rate (cancer is undetected) and increases in younger women with denser breast tissue. Diffuse optical imaging (DOI) is a safe (nonionizing), and relatively inexpensive method for noninvasive imaging of breast cancer in human subjects (including dense breast tissues) by providing physiological information (e.g. oxy- and deoxy- hemoglobin concentration). At the Optical Imaging Laboratory, a hand-held optical imager has been developed which employs a breast contourable probe head to perform simultaneous illumination and detection of large surfaces towards near real-time imaging of human breast cancer. Gen-1 and gen-2 versions of the handheld optical imager have been developed and previously demonstrated imaging in tissue phantoms and healthy human subjects. Herein, the hand-held optical imagers are applied towards in vivo imaging of breast cancer subjects in an attempt to determine the ability of the imager to detect breast tumors. Five female human subjects (ages 51-74) diagnosed with breast cancer were imaged with the gen-1 optical imager prior to surgical intervention. One of the subjects was also imaged with the gen-2 optical imager. Both imagers use 785 nm laser diode sources and ICCD camera detectors to generate 2D surfaces maps of total hemoglobin absorption. The subjects lay in supine position and images were collected at various locations on both the ipsilateral (tumor-containing) and contralateral (non-tumor containing) breasts. The optical images (2D surface maps of optical absorption due to total hemoglobin concentration) show regions of higher intensity at the tumor location, which is indicative of increased vasculature and higher blood content due to the presence of the tumor. Additionally, a preliminary result indicates the potential to image lymphatic spread. This study demonstrates the potential of the hand-held optical devices to noninvasively image breast cancer in human subjects.

Alignment of sources and detectors on breast surface for noncontact diffuse correlation tomography of breast tumors

Noncontact diffuse correlation tomography (ncDCT) is an emerging technology for 3D imaging of deep tissue blood flow distribution without distorting hemodynamic properties. To adapt the ncDCT for imaging in vivo breast tumors, we designed a motorized ncDCT probe to scan over the breast surface. A computer-aided design (CAD)-based approach was proposed to create solid volume mesh from arbitrary breast surface obtained by a commercial 3D camera. The sources and detectors of ncDCT were aligned on the breast surface through ray tracing to mimic the ncDCT scanning with CAD software. The generated breast volume mesh along with the boundary data of ncDCT at the aligned source and detector pairs were used for finite-element-method-based flow image reconstruction. We evaluated the accuracy of source alignments on mannequin and human breasts; largest alignment errors were less than 10% in both tangential and radial directions of scanning. The impact of alignment errors (assigned 10%) on the tumor reconstruction was estimated using computer simulations. The deviations of simulated tumor location and blood flow contrast resulted from the alignment errors were 0.77 mm (less than the node distance of 1 mm) and 1%, respectively, which result in minor impact on flow image reconstruction. Finally, a case study on a human breast tumor was conducted and a tumor-to-normal flow contrast was reconstructed, demonstrating the feasibility of ncDCT in clinical application.

Direct regularization from co-registered anatomical images for MRI-guided near-infrared spectral tomographic image reconstruction

Combining anatomical information from high resolution imaging modalities to guide near-infrared spectral tomography (NIRST) is an efficient strategy for improving the quality of the reconstructed spectral images. A new approach for incorporating image information directly into the inversion matrix regularization was examined using Direct Regularization from Images (DRI), which encodes the gray-scale data into the NIRST image reconstruction problem. This process has the benefit of eliminating user intervention such as image segmentation of distinct regions. Specifically, the Dynamic Contrast Enhanced Magnetic Resonance (DCE-MR) image intensity value differences within the anatomical image were used to implement an exponentially-weighted regularization function between the image pixels. The algorithm was validated using simulated reconstructions with noise, and the results showed that spatial resolution and robustness of the reconstructed images were significantly improved by appropriate choice of the regularization weight parameters. The proposed approach was also tested on in vivo breast data acquired in a recent clinical trial combining NIRST / MRI for cancer tumor characterization. Relative to the standard "no priors" diffuse recovery, the contrast of the tumor to the normal surrounding tissue increased from 2.4 to 3.6, and the difference between the tumor size segmented from DCE-MR images and reconstructed optical images decreased from 18% to 6%, while there was an overall decrease in surface artifacts.