Breast cancer detection based on incremental biochemical and physiological properties of breast cancers: a six-year, two-site study

Assessment of Oxygen Saturation in Breast Lesions Using Photoacoustic Imaging: Correlation With Benign and Malignant Disease

BACKGROUND

Hypoxia is a hallmark of breast cancer (BC). Photoacoustic (PA) imaging, based on the use of laser-generated ultrasound (US), can detect oxygen saturation (So2) in the tissues of breast lesion patients.

PURPOSE

To measure the oxygenation status of tissue in and on both sides of the lesion in breast lesion participants using a multimodal Photoacoustic/ultrasound (PA/US) imaging system and to determine the correlation between So2 measured by PA imaging and benign or malignant disease.

MATERIALS AND METHODS

Multimodal PA/US imaging and gray-scale US (GSUS) of breast lesion was performed in consecutive breast lesion participants imaged in the US Outpatient Clinic between 2022 and 2023. Dual-wavelength PA imaging was used to measure the So2 value inside the lesion and on both sides of the tissue, and to distinguish benign from malignant lesions based on the So2 value. The ability of So2 to distinguish benign from malignant breast lesions was evaluated by the receiver operating characteristic curve (ROC) and the De-Long test.

RESULTS

A total of 120 breast lesion participants (median age, 42.5 years) were included in the study. The malignant lesions exhibited lower So2 levels compared to benign lesions (malignant: 71.30%; benign: 83.81%; P < .01). Moreover, PA/US imaging demonstrates superior diagnostic results compared to GSUS, with an area under the curve (AUC) of 0.89 versus 0.70, sensitivity of 89.58% versus 85.42%, and specificity of 86.11% versus 55.56% at the So2 cut-off value of 78.85 (P < .001). The false positive rate in GSUS reduced by 30.75%, and the false negative rate diminished by 4.16% with PA /US diagnosis. Finally, the So2 on both sides tissues of malignant lesions are lower than that of benign lesions (P < .01).

CONCLUSION

PA imaging allows for the assessment of So2 within the lesions of breast lesion patients, thereby facilitating a superior distinction between benign and malignant lesions.

Two-stage classification strategy for breast cancer diagnosis using ultrasound-guided diffuse optical tomography and deep learning

Significance

Ultrasound (US)-guided diffuse optical tomography (DOT) has demonstrated great potential for breast cancer diagnosis in which real-time or near real-time diagnosis with high accuracy is desired.

Aim

We aim to use US-guided DOT to achieve an automated, fast, and accurate classification of breast lesions.

Approach

We propose a two-stage classification strategy with deep learning. In the first stage, US images and histograms created from DOT perturbation measurements are combined to predict benign lesions. Then the non-benign suspicious lesions are passed through to the second stage, which combine US image features, DOT histogram features, and 3D DOT reconstructed images for final diagnosis.

Results

The first stage alone identified 73.0% of benign cases without image reconstruction. In distinguishing between benign and malignant breast lesions in patient data, the two-stage classification approach achieved an area under the receiver operating characteristic curve of 0.946, outperforming the diagnoses of all single-modality models and of a single-stage classification model that combines all US images, DOT histogram, and imaging features.

Conclusions

The proposed two-stage classification strategy achieves better classification accuracy than single-modality-only models and a single-stage classification model that combines all features. It can potentially distinguish breast cancers from benign lesions in near real-time.

Stable tissue-mimicking phantoms for longitudinal multimodality imaging studies that incorporate optical, CT, and MRI contrast

Significance

Tissue phantoms that mimic the optical and radiologic properties of human or animal tissue play an important role in the development, characterization, and evaluation of imaging systems. Phantoms that are easily produced and stable for longitudinal studies are highly desirable.

Aim

A new type of long-lasting phantom was developed with commercially available materials and was assessed for fabrication ease, stability, and optical property control. Magnetic resonance imaging (MRI) and x-ray computed tomography (CT) contrast properties were also evaluated.

Approach

A systematic investigation of relationships between concentrations of skin-like pigments and composite optical properties was conducted to realize optical property phantoms in the red and near-infrared (NIR) wavelength range that also offered contrast for CT and MRI.

Results

Phantom fabrication time was < 1    h and did not involve any heating or cooling processes. Changes in optical properties were < 2 % over a 12-month period. Phantom optical and spectral features were similar to human soft tissue over the red to NIR wavelength ranges. Pigments used in the study also had CT and MRI contrasts for multimodality imaging studies.

Conclusions

The phantoms described here mimic optical properties of soft tissue and are suitable for multimodality imaging studies involving CT or MRI without adding secondary contrast agents.

Insights into Biochemical Sources and Diffuse Reflectance Spectral Features for Colorectal Cancer Detection and Localization

Colorectal cancer (CRC) is the third most common and second most deadly type of cancer worldwide. Early detection not only reduces mortality but also improves patient prognosis by allowing the use of minimally invasive techniques to remove cancer while avoiding major surgery. Expanding the use of microsurgical techniques requires accurate diagnosis and delineation of the tumor margins in order to allow complete excision of cancer. We have used diffuse reflectance spectroscopy (DRS) to identify the main optical CRC biomarkers and to optimize parameters for the integration of such technologies into medical devices. A total number of 2889 diffuse reflectance spectra were collected in ex vivo specimens from 47 patients. Short source-detector distance (SDD) and long-SDD fiber-optic probes were employed to measure tissue layers from 0.5 to 1 mm and from 0.5 to 1.9 mm deep, respectively. The most important biomolecules contributing to differentiating DRS between tissue types were oxy- and deoxy-hemoglobin (Hb and HbO₂), followed by water and lipid. Accurate tissue classification and potential DRS device miniaturization using Hb, HbO₂, lipid and water data were achieved particularly well within the wavelength ranges 350-590 nm and 600-1230 nm for the short-SDD probe, and 380-400 nm, 420-610 nm, and 650-950 nm for the long-SDD probe.

Difference imaging from single measurements in diffuse optical tomography: a deep learning approach

SIGNIFICANCE

"Difference imaging," which reconstructs target optical properties using measurements with and without target information, is often used in diffuse optical tomography (DOT) in vivo imaging. However, taking additional reference measurements is time consuming, and mismatches between the target medium and the reference medium can cause inaccurate reconstruction.

AIM

We aim to streamline the data acquisition and mitigate the mismatch problems in DOT difference imaging using a deep learning-based approach to generate data from target measurements only.

APPROACH

We train an artificial neural network to output data for difference imaging from target measurements only. The model is trained and validated on simulation data and tested with simulations, phantom experiments, and clinical data from 56 patients with breast lesions.

RESULTS

The proposed method has comparable performance to the traditional approach using measurements without mismatch between the target side and the reference side, and it outperforms the traditional approach using measurements when there is a mismatch. It also improves the target-to-artifact ratio and lesion localization in patient data.

CONCLUSIONS

The proposed method can simplify the data acquisition procedure, mitigate mismatch problems, and improve reconstructed image quality in DOT difference imaging.

Evaluation of Tumor Development Using Hemoglobin Saturation Profile on Rodent Dorsal Window Chamber

Tumor development can be indirectly evaluated using features of the tumor microenvironment (TME), such as hemoglobin saturation (HbSat), blood vessel dilation, and formation of new vessels. High values of HbSat and other features of the TME could indicate high metabolic activity and could precede the formation of angiogenic tumors; therefore, changes in HbSat profile can be used as a biomarker for tumor progression. One methodology to evaluate HbSat profile over time, and correlate it with tumor development in vivo in a preclinical model, is through a dorsal skin-fold window chamber. In this chapter, we provide a detailed description of this methodology to evaluate hemoglobin saturation profile and to predict tumor development. We will cover the surgical preparation of the mouse, the installation/maintenance of the dorsal window chamber, and the imaging processing and evaluation to the HbSat profile to predict new development of new tumor areas over time. We included, in this chapter, step by step examples of the imaging processing method to obtain pixel level HbSat values from raw pixels data, the computational method to determine the HbSat profile, and the steps for the classification of the areas into tumor and no-tumor.

Deep learning-based method to accurately estimate breast tissue optical properties in the presence of the chest wall

SIGNIFICANCE

In general, image reconstruction methods used in diffuse optical tomography (DOT) are based on diffusion approximation, and they consider the breast tissue as a homogenous, semi-infinite medium. However, the semi-infinite medium assumption used in DOT reconstruction is not valid when the chest wall is underneath the breast tissue.

AIM

We aim to reduce the chest wall's effect on the estimated average optical properties of breast tissue and obtain accurate forward model for DOT reconstruction.

APPROACH

We propose a deep learning-based neural network approach where a convolution neural network (CNN) is trained to simultaneously obtain accurate optical property values for both the breast tissue and the chest wall.

RESULTS

The CNN model shows great promise in reducing errors in estimating the optical properties of the breast tissue in the presence of a shallow chest wall. For patient data, the CNN model predicted the breast tissue optical absorption coefficient, which was independent of chest wall depth.

CONCLUSIONS

Our proposed method can be readily used in DOT and diffuse spectroscopy measurements to improve the accuracy of estimated tissue optical properties.

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.

Ultrasound segmentation-guided edge artifact reduction in diffuse optical tomography using connected component analysis

Ultrasound (US)-guided diffuse optical tomography (DOT) has demonstrated potential value for breast cancer diagnosis and treatment response assessment. However, in clinical use, the chest wall, poor probe-tissue contact, and tissue heterogeneity can all cause image artifacts. These image artifacts, appearing commonly as hot spots in the non-lesion regions (edge artifacts), can decrease the reconstruction accuracy and cause misinterpretation of lesion images. Here we introduce an iterative, connected component analysis-based image artifact reduction algorithm. A convolutional neural network (CNN) is used to segment co-registered US images to extract the lesion location and size to guide the artifact reduction. We demonstrate its performance using Monte Carlo simulations on VICTRE digital breast phantoms and breast patient images. In simulated tissue mismatch models, this algorithm successfully reduces edge artifacts without significantly changing the reconstructed target absorption coefficients. With clinical data it improves the optical contrast between malignant and benign groups, from 1.55 without artifact reduction to 1.91 with artifact reduction. The proposed algorithm has a broad range of applications in other modality-guided DOT imaging.

Development of a digital breast phantom for photoacoustic computed tomography

Photoacoustic (PA) imaging provides morphological and functional information about angiogenesis and thus is potentially suitable for breast cancer diagnosis. However, the development of PA breast imaging has been hindered by inadequate patients and a lack of ground truth images. Here, we report a digital breast phantom with realistic acoustic and optical properties, with which a digital PA-ultrasound imaging pipeline is developed to create a diverse pool of virtual patients with three types of masses: ductal carcinoma in situ, invasive breast cancer, and fibroadenoma. The experimental results demonstrate that our model is realistic, flexible, and can be potentially useful for accelerating the development of PA breast imaging technology.

Breast cancer differential diagnosis using diffuse optical spectroscopic imaging and regression with z-score normalized data

SIGNIFICANCE

Current imaging paradigms for differential diagnosis of suspicious breast lesions suffer from high false positive rates that force patients to undergo unnecessary biopsies. Diffuse optical spectroscopic imaging (DOSI) noninvasively probes functional hemodynamic and compositional parameters in deep tissue and has been shown to be sensitive to contrast between normal and malignant tissues.

AIM

DOSI methods are under investigation as an adjunct to mammography and ultrasound that could reduce false positive rates and unnecessary biopsies, particularly in radiographically dense breasts.

METHODS

We performed a retrospective analysis of 212 subjects with suspicious breast lesions who underwent DOSI imaging. Physiological tissue parameters were z-score normalized to the patient's contralateral breast tissue and input to univariate logistic regression models to discriminate between malignant tumors and the surrounding normal tissue. The models were then used to differentiate malignant lesions from benign lesions.

RESULTS

Models incorporating several individual hemodynamic parameters were able to accurately distinguish malignant tumors from both the surrounding background tissue and benign lesions with area under the curve (AUC) ≥0.85. Z-score normalization improved the discriminatory ability and calibration of these predictive models relative to unnormalized or ratio-normalized data.

CONCLUSIONS

Findings from a large subject population study show how DOSI data normalization that accounts for normal tissue heterogeneity and quantitative statistical regression approaches can be combined to improve the ability of DOSI to diagnose malignant lesions. This improved diagnostic accuracy, combined with the modality's inherent logistical advantages of portability, low cost, and nonionizing radiation, could position DOSI as an effective adjunct modality that could be used to reduce the number of unnecessary invasive biopsies.

Effect and correction of optode coupling errors in breast imaging using diffuse optical tomography

In diffuse optical tomography (DOT) and spectroscopy (DOS) using handheld probes, tissue curvature can cause bad fiber-to-tissue contact. Understanding and minimizing image artifacts caused by these coupling errors would significantly improve DOT and DOS image quality. In this work, we utilized Monte Carlo simulations and experiments with gelatin-Intralipid phantoms to systematically study the influence of source or detector (optode) coupling errors. Optode coupling errors can increase the amplitude and decrease the phase of the measured diffuse reflectance, creating artifacts in the reconstructed absorption maps, such as hot spots on the edges. We propose an outlier removal algorithm that can correct these image artifacts, and we demonstrate its performance using simulations, phantom experiments, and breast patient data acquired with bad probe contact due to a dense or small breast. Further, we designed and implemented a new resistance-type thin-film force sensor array that provides real-time optode coupling feedback and guides the outlier removal to minimize optode coupling errors. Our approaches and study results have significant implications for reducing image artifacts arising from handheld probes, which are commonly used with mobile and wearable DOT and DOS devices.

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.

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.

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.

Clinical optoacoustic imaging combined with ultrasound for coregistered functional and anatomical mapping of breast tumors

Optoacoustic imaging, based on the differences in optical contrast of blood hemoglobin and oxyhemoglobin, is uniquely suited for the detection of breast vasculature and tumor microvasculature with the inherent capability to differentiate hypoxic from the normally oxygenated tissue. We describe technological details of the clinical ultrasound (US) system with optoacoustic (OA) imaging capabilities developed specifically for diagnostic imaging of breast cancer. The combined OA/US system provides co-registered and fused images of breast morphology based upon gray scale US with the functional parameters of total hemoglobin and blood oxygen saturation in the tumor angiogenesis related microvasculature based upon OA images. The system component that enabled clinical utility of functional OA imaging is the hand-held probe that utilizes a linear array of ultrasonic transducers sensitive within an ultrawide-band of acoustic frequencies from 0.1 MHz to 12 MHz when loaded to the high-impedance input of the low-noise analog preamplifier. The fiberoptic light delivery system integrated into a dual modality probe through a patented design allowed acquisition of OA images while minimizing typical artefacts associated with pulsed laser illumination of skin and the probe components in the US detection path. We report technical advances of the OA/US imaging system that enabled its demonstrated clinical viability. The prototype system performance was validated in well-defined tissue phantoms. Then a commercial prototype system named Imagio™ was produced and tested in a multicenter clinical trial termed PIONEER. We present examples of clinical images which demonstrate that the spatio-temporal co-registration of functional and anatomical images permit radiological assessment of the vascular pattern around tumors, microvascular density of tumors as well as the relative values of the total hemoglobin [tHb] and blood oxygen saturation [sO2] in tumors relative to adjacent normal breast tissues. The co-registration technology enables increased accuracy of radiologist assessment of malignancy by confirming, upgrading and/or downgrading US categorization of breast tumors according to Breast Imaging Reporting And Data System (BI-RADS). Microscopic histologic examinations on the biopsied tissue of the imaged tumors served as a gold standard in verifying the functional and anatomic interpretations of the OA/US image feature analysis.

Factors affecting measurement of optic parameters by time-resolved near-infrared spectroscopy in breast cancer

The purpose of this study was to evaluate the effects of the thickness and depth of tumors on hemoglobin measurements in breast cancer by optical spectroscopy and to demonstrate tissue oxygen saturation (SO2) and reduced scattering coefficient (μs') in breast tissue and breast cancer in relation to the skin-to-chest wall distance. We examined 53 tumors from 44 patients. Total hemoglobin concentration (tHb), SO2, and μs' were measured by time-resolved spectroscopy (TRS). The skin-to-chest wall distance and the size and depth of tumors were measured by ultrasonography. There was a positive correlation between tHb and tumor thickness, and a negative correlation between tHb and tumor depth. SO2 in breast tissue decreased when the skin-to-chest wall distance decreased, and SO2 in tumors tended to be lower than in breast tissue. In breast tissue, there was a negative correlation between μs' and the skin-to-chest wall distance, and μs' in tumors was higher than in breast tissue. Measurement of tHb in breast cancer by TRS was influenced by tumor thickness and depth. Although SO2 seemed lower and μs' was higher in breast cancer than in breast tissue, the skin-to-chest wall distance may have affected the measurements.

Near-Infrared Visual Differentiation in Normal and Abnormal Breast Using Hemoglobin Concentrations

Introduction: Near-infrared (NIR) optical imaging is a non-ionizing modality that is emerging as a diagnostic/prognostic tool for breast cancer according to NIR differentiation of hemoglobin (Hb) concentration. Methods: The transmission values of LED-sourced light at 625 nm were measured by power meter to evaluate the optical properties of Hb in breast phantom containing major and minor vessels. For the simulation of blood variations in cancerous breast condition, we prepared 2 concentrations of pre-menopausal Hb and 4 concentrations of post-menopausal Hb and, for comparison with normal tissue, one concentration of Hb injected inside the phantom's vessels. Imaging procedure on the phantom was also conducted by LED source and CCD camera. The images from the experiments were compared with the results obtained from the images analyzed by MATLAB software. Finally, mammography of phantom including various concentration of Hb was prepared. Results: The transmitting intensities of NIR in blood containing 1, 2 and 4 concentrations of Hb in the major vessels were 52.83±2.85, 43.00±3.11 and 31.17±2.27 µW, respectively, and in minor vessels containing similar Hb concentrations were 73.50±2.43, 60.08±5.09 and 42.42±4.86 µW, respectively. The gray-scale levels on the major vessel were about 96, 124, 162 and on the minor vessel about 72, 100, 130 measured for 1, 2 and 4 Hb concentrations, respectively. The sensitivity and specificity of NIR imaging differentiation were 97.4% and 91.3%, respectively. Conclusion: Significant differences in transmitting intensity, optical imaging as well as software analysis of images were observed for 1, 2 and 4 concentrations of Hb in major and minor breast phantom vessels. Differentiation capability of minor vessels was higher than major vessels for Hb concentrations. Despite a good detection for location of vessels by mammography, it could not show differences between vessels with various concentrations. However, NIR optical imaging demonstrated a good image contrast for showing vessels in terms of concentration. This study recommends NIR optical imaging for prescreening breast cancer due to its potential for early diagnosis.

Diffuse optical tomography using semiautomated coregistered ultrasound measurements

Diffuse optical tomography (DOT) has demonstrated huge potential in breast cancer diagnosis and treatment monitoring. DOT image reconstruction guided by ultrasound (US) improves the diffused light localization and lesion reconstruction accuracy. However, DOT reconstruction depends on tumor geometry provided by coregistered US. Experienced operators can manually measure these lesion parameters; however, training and measurement time are needed. The wide clinical use of this technique depends on its robustness and faster imaging reconstruction capability. This article introduces a semiautomated procedure that automatically extracts lesion information from US images and incorporates it into the optical reconstruction. An adaptive threshold-based image segmentation is used to obtain tumor boundaries. For some US images, posterior shadow can extend to the chest wall and make the detection of deeper lesion boundary difficult. This problem can be solved using a Hough transform. The proposed procedure was validated from data of 20 patients. Optical reconstruction results using the proposed procedure were compared with those reconstructed using extracted tumor information from an experienced user. Mean optical absorption obtained from manual measurement was 0.21±0.06  cm-1 for malignant and 0.12±0.06  cm-1 for benign cases, whereas for the proposed method it was 0.24±0.08  cm-1 and 0.12±0.05  cm-1, respectively.

Two step imaging reconstruction using truncated pseudoinverse as a preliminary estimate in ultrasound guided diffuse optical tomography

Due to the correlated nature of diffused light, the problem of reconstructing optical properties using diffuse optical tomography (DOT) is ill-posed. US-, MRI- or x-ray-guided DOT approaches can reduce the total number of parameters to be estimated and improve optical reconstruction accuracy. However, when the target volume is large, the number of parameters to estimate can exceed the number of measurements, resulting in an underdetermined imaging model. In such cases, accurate image reconstruction is difficult and regularization methods should be employed to obtain a useful solution. In this manuscript, a simple two-step reconstruction method that can produce useful image estimates in DOT is proposed and investigated. In the first step, a truncated Moore-Penrose Pseudoinverse solution is computed to obtain a preliminary estimate of the image that can be reliably determined from the measured data; subsequently, this preliminary estimate is incorporated into the design of a penalized least squares estimator that is employed to compute the final image estimate. By use of phantom data, the proposed method was demonstrated to yield more accurate images than those produced by conventional reconstruction methods. The method was also evaluated with clinical data that included 10 benign and 10 malignant cases. The capability of reconstructing high contrast malignant lesions was demonstrated to be improved by use of the proposed method.

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.

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%.

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.

Broadband optical mammography instrument for depth-resolved imaging and local dynamic measurements

We present a continuous-wave instrument for non-invasive diffuse optical imaging of the breast in a parallel-plate transmission geometry. The instrument measures continuous spectra in the wavelength range 650-1000 nm, with an intensity noise level <1.5% and a spatial sampling rate of 5 points/cm in the x- and y-directions. We collect the optical transmission at four locations, one collinear and three offset with respect to the illumination optical fiber, to recover the depth of optical inhomogeneities in the tissue. We imaged a tissue-like, breast shaped, silicone phantom (6 cm thick) with two embedded absorbing structures: a black circle (1.7 cm in diameter) and a black stripe (3 mm wide), designed to mimic a tumor and a blood vessel, respectively. The use of a spatially multiplexed detection scheme allows for the generation of on-axis and off-axis projection images simultaneously, as opposed to requiring multiple scans, thus decreasing scan-time and motion artifacts. This technique localizes detected inhomogeneities in 3D and accurately assigns their depth to within 1 mm in the ideal conditions of otherwise homogeneous tissue-like phantoms. We also measured induced hemodynamic changes in the breast of a healthy human subject at a selected location (no scanning). We applied a cyclic, arterial blood pressure perturbation by alternating inflation (to a pressure of 200 mmHg) and deflation of a pneumatic cuff around the subject's thigh at a frequency of 0.05 Hz, and measured oscillations with amplitudes up to 1 μM and 0.2 μM in the tissue concentrations of oxyhemoglobin and deoxyhemoglobin, respectively. These hemodynamic oscillations provide information about the vascular structure and functional integrity in tissue, and may be used to assess healthy or abnormal perfusion in a clinical setting.

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.

Optical imaging for breast cancer prescreening

Breast cancer prescreening is carried out prior to the gold standard screening using X-ray mammography and/or ultrasound. Prescreening is typically carried out using clinical breast examination (CBE) or self-breast examinations (SBEs). Since CBE and SBE have high false-positive rates, there is a need for a low-cost, noninvasive, non-radiative, and portable imaging modality that can be used as a prescreening tool to complement CBE/SBE. This review focuses on the various hand-held optical imaging devices that have been developed and applied toward early-stage breast cancer detection or as a prescreening tool via phantom, in vivo, and breast cancer imaging studies. Apart from the various optical devices developed by different research groups, a wide-field fiber-free near-infrared optical scanner has been developed for transillumination-based breast imaging in our Optical Imaging Laboratory. Preliminary in vivo studies on normal breast tissues, with absorption-contrasted targets placed in the intramammary fold, detected targets as deep as 8.8 cm. Future work involves in vivo imaging studies on breast cancer subjects and comparison with the gold standard X-ray mammography approach.

Estimation and imaging of breast lesions using a two-layer tissue structure by ultrasound-guided optical tomography

A new two-step estimation and imaging method is developed for a two-layer breast tissue structure consisting of a breast tissue layer and a chest wall underneath. First, a smaller probe with shorter distance source-detector pairs was used to collect the reflected light mainly from the breast tissue layer. Then, a larger probe with 9×14 source-detector pairs and a centrally located ultrasound transducer was used to collect reflected light from the two-layer tissue structure. The data collected from the smaller probe were used to estimate breast tissue optical properties. With more accurate estimation of the average breast tissue properties, the second layer properties can be assessed from data obtained from the larger probe. Using this approach, the unknown variables have been reduced from four to two and the estimated bulk tissue optical properties are more accurate and robust. In addition, a two-step reconstruction using a genetic algorithm and conjugate gradient method is implemented to simultaneously reconstruct the absorption and reduced scattering maps of targets inside a two-layer tissue structure. Simulations and phantom experiments have been performed to validate the new reconstruction method, and a clinical example is given to demonstrate the feasibility of this approach.

MR-Guided Near-Infrared Spectral Tomography Increases Diagnostic Performance of Breast MRI

PURPOSE

The purpose of this study was to determine the diagnostically most important molecular biomarkers quantified by magnetic resonance-guided (MR) near-infrared spectral tomography (NIRST) that distinguish malignant breast lesions from benign abnormalities when combined with outcomes from clinical breast MRI.

EXPERIMENTAL DESIGN

The study was HIPAA compliant and approved by the Dartmouth Institutional Review Board, the NIH, the United States State Department, and Xijing Hospital. MR-guided NIRST evaluated hemoglobin, water, and lipid content in regions of interest defined by concurrent dynamic contrast-enhanced MRI (DCE-MRI) in the breast. MRI plus NIRST was performed in 44 subjects (median age, 46, age range, 20-81 years), 28 of whom had subsequent malignant pathologic diagnoses, and 16 had benign conditions. A subset of 30 subject examinations yielded optical data that met minimum sensitivity requirements to the suspicious lesion and were included in the analyses of diagnostic performance.

RESULTS

In the subset of 30 subject examinations meeting minimum optical data sensitivity criterion, the MR-guided NIRST separated malignant from benign lesions using total hemoglobin (HbT; P < 0.01) and tissue optical index (TOI; P < 0.001). Combined MRI plus TOI data caused one false positive and 1 false negative, and produced the best diagnostic performance, yielding an AUC of 0.95, sensitivity of 95%, specificity of 89%, positive predictive value of 95%, and negative predictive value of 89%, respectively.

CONCLUSIONS

MRI plus NIRST results correlated well with histopathologic diagnoses and could provide additional information to reduce the number of MRI-directed biopsies.

Light-emitting diode-based multiwavelength diffuse optical tomography system guided by ultrasound

Laser diodes are widely used in diffuse optical tomography (DOT) systems but are typically expensive and fragile, while light-emitting diodes (LEDs) are cheaper and are also available in the near-infrared (NIR) range with adequate output power for imaging deeply seated targets. In this study, we introduce a new low-cost DOT system using LEDs of four wavelengths in the NIR spectrum as light sources. The LEDs were modulated at 20 kHz to avoid ambient light. The LEDs were distributed on a hand-held probe and a printed circuit board was mounted at the back of the probe to separately provide switching and driving current to each LED. Ten optical fibers were used to couple the reflected light to 10 parallel photomultiplier tube detectors. A commercial ultrasound system provided simultaneous images of target location and size to guide the image reconstruction. A frequency-domain (FD) laser-diode-based system with ultrasound guidance was also used to compare the results obtained from those of the LED-based system. Results of absorbers embedded in intralipid and inhomogeneous tissue phantoms have demonstrated that the LED-based system provides a comparable quantification accuracy of targets to the FD system and has the potential to image deep targets such as breast lesions.

Optically measured microvascular blood flow contrast of malignant breast tumors

Microvascular blood flow contrast is an important hemodynamic and metabolic parameter with potential to enhance in vivo breast cancer detection and therapy monitoring. Here we report on non-invasive line-scan measurements of malignant breast tumors with a hand-held optical probe in the remission geometry. The probe employs diffuse correlation spectroscopy (DCS), a near-infrared optical method that quantifies deep tissue microvascular blood flow. Tumor-to-normal perfusion ratios are derived from thirty-two human subjects. Mean (95% confidence interval) tumor-to-normal ratio using surrounding normal tissue was 2.25 (1.92–2.63); tumor-to-normal ratio using normal tissues at the corresponding tumor location in the contralateral breast was 2.27 (1.94–2.66), and using normal tissue in the contralateral breast was 2.27 (1.90–2.70). Thus, the mean tumor-to-normal ratios were significantly different from unity irrespective of the normal tissue chosen, implying that tumors have significantly higher blood flow than normal tissues. Therefore, the study demonstrates existence of breast cancer contrast in blood flow measured by DCS. The new, optically accessible cancer contrast holds potential for cancer detection and therapy monitoring applications, and it is likely to be especially useful when combined with diffuse optical spectroscopy/tomography.

Adaptable near-infrared spectroscopy fiber array for improved coupling to different breast sizes during clinical MRI

RATIONALE AND OBJECTIVES

Near-infrared spectroscopy (NIRS) of breast can provide functional information on the vascular and structural compartments of tissues in regions identified during simultaneous magnetic resonance imaging (MRI). NIRS can be acquired during dynamic contrast-enhanced MRI (DCE-MRI) to accomplish image-guided spectroscopy of the enhancing regions, potentially increasing the diagnostic specificity of the examination and reducing the number of biopsies performed as a result of inconclusive MRI breast imaging studies.

MATERIALS AND METHODS

We combine synergistic attributes of concurrent DCE-MRI and NIRS with a new design of the clinical NIRS breast interface that couples to a standard MR breast coil and allows imaging of variable breast sizes. Spectral information from healthy volunteers and cancer patients is recovered, providing molecular information in regions defined by the segmented MR image volume.

RESULTS

The new coupling system significantly improves examination utility by allowing improved coupling of the NIR fibers to breasts of all cup sizes and lesion locations. This improvement is demonstrated over a range of breast sizes (cup size A through D) and normal tissue heterogeneity using a group of eight healthy volunteers and two cancer patients. Lesions located in the axillary region and medial-posterior breast are now accessible to NIRS optodes. Reconstructed images were found to have biologically plausible hemoglobin content, oxygen saturation, and water and lipid fractions.

CONCLUSIONS

In summary, a new NIRS/MRI breast interface was developed to accommodate the variation in breast sizes and lesion locations that can be expected in clinical practice. DCE-MRI-guided NIRS quantifies total hemoglobin, oxygenation, and scattering in MR-enhancing regions, increasing the diagnostic information acquired from MR examinations.

Imaging breast cancer response during neoadjuvant systemic therapy

Neoadjuvant systemic therapy is used to enable breast-conserving surgery in patients with large primary operable breast cancers. It is important to be able to accurately assess response to systemic therapy, both to assist the surgeon and for prognostic purposes. Moreover, a proportion of women will fail to respond to treatment and would potentially benefit from either a change in therapy or earlier surgery rather than continuing completion of the planned course of treatment. Conventional techniques of assessing response (clinical examination, x-ray mammography and breast ultrasound) rely on changes in tumor size, which are often delayed and do not always correlate with pathologic response. This review examines the evidence for functional imaging techniques including scintimammography, functional computed tomography, dynamic magnetic resonance imaging, spectroscopy and positron emission tomography. These techniques measure changes in tumor vasculature, metabolism or proliferation and may prove to be earlier and more sensitive measures of response to systemic therapy, thus enabling tailoring of an individual's treatment.

Indocyanine green enhanced co-registered diffuse optical tomography and photoacoustic tomography

To overcome the intensive light scattering in biological tissue, diffuse optical tomography (DOT) in the near-infrared range for breast lesion detection is usually combined with other imaging modalities, such as ultrasound, x-ray, and magnetic resonance imaging, to provide guidance. However, these guiding imaging modalities may depend on different contrast mechanisms compared to the optical contrast in the DOT. As a result, they cannot provide reliable guidance for DOT because some lesions may not be detectable by a nonoptical modality but may have a high optical contrast. An imaging modality that relies on optical contrast to provide guidance is desirable for DOT. We present a system that combines a frequency-domain DOT and real-time photoacoustic tomography (PAT) systems to detect and characterize deeply seated targets embedded in a turbid medium. To further improve the contrast, the exogenous contrast agent, indocyanine green (ICG), is used. Our experimental results show that the combined system can detect a tumor-mimicking phantom, which is immersed in intralipid solution with the concentrations ranging from 100 to 10 μM and with the dimensions of 0.8 cm × 0.8 cm × 0.6 cm, up to 2.5 cm in depth. Mice experiments also confirmed that the combined system can detect tumors and monitor the ICG uptake and washout in the tumor region. This method can potentially improve the accuracy to detect small breast lesions as well as lesions that are sensitive to background tissue changes, such as the lesions located just above the chest wall.

Towards non-invasive characterization of breast cancer and cancer metabolism with diffuse optics

We review recent developments in diffuse optical imaging and monitoring of breast cancer, i.e. optical mammography. Optical mammography permits non-invasive, safe and frequent measurement of tissue hemodynamics oxygen metabolism and components (lipids, water, etc.), the development of new compound indices indicative of the risk and malignancy, and holds potential for frequent non-invasive longitudinal monitoring of therapy progression.

Depth discrimination in diffuse optical transmission imaging by planar scanning off-axis fibers: initial applications to optical mammography

We present a method for depth discrimination in parallel-plate, transmission mode, diffuse optical imaging. The method is based on scanning a set of detector pairs, where the two detectors in each pair are separated by a distance δDi along direction δ D i within the x-y scanning plane. A given optical inhomogeneity appears shifted by αi δ D i (with 0≤ αi ≤1) in the images collected with the two detection fibers of the i-th pair. Such a spatial shift can be translated into a measurement of the depth z of the inhomogeneity, and the depth measurements based on each detector pair are combined into a specially designed weighted average. This depth assessment is demonstrated on tissue-like phantoms for simple inhomogeneities such as straight rods in single-rod or multiple-rod configurations, and for more complex curved structures which mimic blood vessels in the female breast. In these phantom tests, the method has recovered the depth of single inhomogeneities in the central position of the phantom to within 4 mm of their actual value, and within 7 mm for more superficial inhomogeneities, where the thickness of the phantom was 65 mm. The application of this method to more complex images, such as optical mammograms, requires a robust approach to identify corresponding structures in the images collected with the two detectors of a given pair. To this aim, we propose an approach based on the inner product of the skeleton images collected with the two detectors of each pair, and we present an application of this approach to optical in vivo images of the female breast. This depth discrimination method can enhance the spatial information content of 2D projection images of the breast by assessing the depth of detected structures, and by allowing for 3D localization of breast tumors.

Three-dimensional fluorescence tomography of human breast tissues in vivo using a hand-held optical imager

Diffuse optical imaging using non-ionizing radiation is a non-invasive method that shows promise towards breast cancer diagnosis. Hand-held optical imagers show potential for clinical translation of the technology, yet they have not been used towards 3D tomography. Herein, 3D tomography of human breast tissue in vivo is demonstrated for the first time using a hand-held optical imager with automated coregistration facilities. Simulation studies are performed on breast geometries to demonstrate the feasibility of 3D tomographic imaging using a hand-held imager under perfect (1:0) and imperfect (100:1, 50:1) fluorescence absorption contrast ratios. Experimental studies are performed in vivo using a 1 µM ICG filled phantom target placed non-invasively underneath the flap of the breast tissue. Results show the ability to perform automated tracking and coregistered imaging of human breast tissue (with tracking accuracy on the order of ∼1 cm). Three-dimensional tomography results demonstrated the ability to recover a single target placed at a depth of 2.5 cm, from both the simulated (at 1:0, 100:1 and 50:1 contrasts) and experimental cases on actual breast tissues. Ongoing efforts to improve target depth recovery are carried out via implementation of transmittance imaging in the hand-held imager.

Combined hemoglobin and fluorescence diffuse optical tomography for breast tumor diagnosis: a pilot study on time-domain methodology

A combined time-domain fluorescence and hemoglobin diffuse optical tomography (DOT) system and the image reconstruction methods are proposed for enhancing the reliability of breast-dedicated optical measurement. The system equipped with two pulsed laser diodes at wavelengths of 780 nm and 830 nm that are specific to the peak excitation and emission of the FDA-approved ICG agent, and works with a 4-channel time-correlated single photon counting device to acquire the time-resolved distributions of the light re-emissions at 32 boundary sites of tissues in a tandem serial-to-parallel mode. The simultaneous reconstruction of the two optical (absorption and scattering) and two fluorescent (yield and lifetime) properties are achieved with the respective featured-data algorithms based on the generalized pulse spectrum technique. The performances of the methodology are experimentally assessed on breast-mimicking phantoms for hemoglobin- and fluorescence-DOT alone, as well as for fluorescence-guided hemoglobin-DOT. The results demonstrate the efficacy of improving the accuracy of hemoglobin-DOT based on a priori fluorescence localization.

Two-step reconstruction method using global optimization and conjugate gradient for ultrasound-guided diffuse optical tomography

Ultrasound-guided diffuse optical tomography (DOT) is a promising method for characterizing malignant and benign lesions in the female breast. We introduce a new two-step algorithm for DOT inversion in which the optical parameters are estimated with the global optimization method, genetic algorithm. The estimation result is applied as an initial guess to the conjugate gradient (CG) optimization method to obtain the absorption and scattering distributions simultaneously. Simulations and phantom experiments have shown that the maximum absorption and reduced scattering coefficients are reconstructed with less than 10% and 25% errors, respectively. This is in contrast with the CG method alone, which generates about 20% error for the absorption coefficient and does not accurately recover the scattering distribution. A new measure of scattering contrast has been introduced to characterize benign and malignant breast lesions. The results of 16 clinical cases reconstructed with the two-step method demonstrates that, on average, the absorption coefficient and scattering contrast of malignant lesions are about 1.8 and 3.32 times higher than the benign cases, respectively.

Optical malignancy parameters for monitoring progression of breast cancer neoadjuvant chemotherapy

We introduce and demonstrate use of a novel, diffuse optical tomography (DOT) based breast cancer signature for monitoring progression of neoadjuvant chemotherapy. This signature, called probability of malignancy, is obtained by statistical image analysis of total hemoglobin concentration, blood oxygen saturation, and scattering coefficient distributions in the breast tomograms of a training-set population with biopsy-confirmed breast cancers. A pilot clinical investigation adapts this statistical image analysis approach for chemotherapy monitoring of three patients. Though preliminary, the study shows how to use the malignancy parameter for separating responders from partial-responders and demonstrates the potential utility of the methodology compared to traditional DOT quantification schemes.

Breast cancer: assessing response to neoadjuvant chemotherapy by using US-guided near-infrared tomography

PURPOSE

To assess initial breast tumor hemoglobin (Hb) content before the initiation of neoadjuvant chemotherapy, monitor the Hb changes at the end of each treatment cycle, and correlate these findings with tumor pathologic response.

MATERIALS AND METHODS

The HIPAA-compliant study protocol was approved by the institutional review boards of both institutions. Written informed consent was obtained from all patients. Patients who were eligible for neoadjuvant chemotherapy were recruited between December 2007 and May 2011, and their tumor Hb content was assessed by using a near-infrared imager coupled with an ultrasonography (US) system. Thirty-two women (mean age, 48 years; range, 32-82 years) were imaged before treatment, at the end of every treatment cycle, and before definitive surgery. The patients were graded in terms of their final pathologic response on the basis of the Miller-Payne system as nonresponders and partial responders (grades 1-3) and near-complete and complete responders (grades 4 and 5). Tumor vascularity was assessed from total Hb (tHb), oxygenated Hb (oxyHb), and deoxygenated Hb (deoxyHb) concentrations. Tumor vascularity changes during treatment were assessed from percentage tHb normalized to the pretreatment level. A two-sample two-sided t test was used to calculate the P value and to evaluate statistical significance between groups. Bonferroni-Holm correction was applied to obtain the corrected P value for multiple comparisons.

RESULTS

There were 20 Miller-Payne grade 1-3 tumors and 14 grade 4 or 5 tumors. Mean maximum pretreatment tHb, oxyHb, and deoxyHb levels were significantly higher in grade 4 and 5 tumors than in grade 1-3 tumors (P = .005, P = .008, and P = .017, respectively). The mean percentage tHb changes were significantly higher in grade 4 or 5 tumors than in grade 1-3 tumors at the end of treatment cycles 1-3 (P = .009 and corrected P = .009, P = .002 and corrected P = .004, and P < .001 and corrected P < .001, respectively).

DISCUSSION

These findings indicate that initial tumor Hb content is a strong predictor of final pathologic response. Additionally, the tHb changes during early treatment cycles can further predict final pathologic response.

Characterization of materials for optimal near-infrared and x-ray imaging of the breast

Development of a detector case for complete co-registration of images in a non-fiber-based combined near-infrared spectral tomography and digital breast tomosynthesis, required analysis to find materials that could support a breast under full mammographic compression without affecting the x-ray images or the quality of the near infrared measurements. Several possible solutions were considered, and many types of plastics were tested in the development of the detector case. Light channeling within the detector case changed the data obtained in resin and agarose phantoms, lowering recovered absorption values. Additional developments focusing on blocking stray light were successful and permitted a normal subject imaging exam.

Hand-held optical imager (Gen-2): improved instrumentation and target detectability

Hand-held optical imagers are developed by various researchers towards reflectance-based spectroscopic imaging of breast cancer. Recently, a Gen-1 handheld optical imager was developed with capabilities to perform two-dimensional (2-D) spectroscopic as well as three-dimensional (3-D) tomographic imaging studies. However, the imager was bulky with poor surface contact (~30%) along curved tissues, and limited sensitivity to detect targets consistently. Herein, a Gen-2 hand-held optical imager that overcame the above limitations of the Gen-1 imager has been developed and the instrumentation described. The Gen-2 hand-held imager is less bulky, portable, and has improved surface contact (~86%) on curved tissues. Additionally, the forked probe head design is capable of simultaneous bilateral reflectance imaging of both breast tissues, and also transillumination imaging of a single breast tissue. Experimental studies were performed on tissue phantoms to demonstrate the improved sensitivity in detecting targets using the Gen-2 imager. The improved instrumentation of the Gen-2 imager allowed detection of targets independent of their location with respect to the illumination points, unlike in Gen-1 imager. The developed imager has potential for future clinical breast imaging with enhanced sensitivity, via both reflectance and transillumination imaging.

Mono- and multimodal registration of optical breast images

Optical breast imaging offers the possibility of noninvasive, low cost, and high sensitivity imaging of breast cancers. Poor spatial resolution and a lack of anatomical landmarks in optical images of the breast make interpretation difficult and motivate registration and fusion of these data with subsequent optical images and other breast imaging modalities. Methods used for registration and fusion of optical breast images are reviewed. Imaging concerns relevant to the registration problem are first highlighted, followed by a focus on both monomodal and multimodal registration of optical breast imaging. Where relevant, methods pertaining to other imaging modalities or imaged anatomies are presented. The multimodal registration discussion concerns digital x-ray mammography, ultrasound, magnetic resonance imaging, and positron emission tomography.

Diffuse Optical Monitoring of the Neoadjuvant Breast Cancer Therapy

Recent advances in the use of diffuse optical techniques for monitoring the hemodynamic, metabolic and physiological signatures of the neoadjuvant breast cancer therapy effectiveness is critically reviewed. An extensive discussion of the state-of-theart diffuse optical mammography is presented alongside a discussion of the current approaches to breast cancer therapies. Overall, the diffuse optics field is growing rapidly with a great deal of promise to fill an important niche in the current approaches to monitor, predict and personalize neoadjuvant breast cancer therapies.

NIRViz: 3D visualization software for multimodality optical imaging using visualization toolkit (VTK) and insight segmentation toolkit (ITK)

Optical imaging using near-infrared light is used for noninvasive probing of tissues to recover vascular and molecular status of healthy and diseased tissues using hemoglobin contrast arising due to absorption of light. While multimodality optical techniques exist, visualization techniques in this area are limited. Addressing this issue, we present a simple framework for image overlay of optical and magnetic resonance (MRI) or computerized tomographic images which is intuitive and easily usable, called NIRViz. NIRViz is a multimodality software platform for the display and navigation of Digital Imaging and Communications in Medicine (DICOM) MRI datasets and 3D optical image solutions geared toward visualization and coregistration of optical contrast in diseased tissues such as cancer. We present the design decisions undertaken during the design of the software, the libraries used in the implementation, and other implementation details as well as preliminary results from the software package. Our implementation uses the Visualization Toolkit library to do most of the work, with a Qt graphical user interface for the front end. Challenges encountered include reslicing DICOM image data and coregistration of image space and mesh space. The resulting software provides a simple and customized platform to display surface and volume meshes with optical parameters such as hemoglobin concentration, overlay them on magnetic resonance images, allow the user to interactively change transparency of different image sets, rotate geometries, clip through the resulting datasets, obtain mesh and optical solution information, and successfully interact with both functional and structural medical image information.

Diffuser-aided diffuse optical imaging for breast tumor: a feasibility study based on time-resolved three-dimensional Monte Carlo modeling

This study proposed diffuser-aided diffuse optical imaging (DADOI) as a new approach to improve the performance of the conventional diffuse optical tomography (DOT) approach for breast imaging. The 3-D breast model for Monte Carlo simulation is remodeled from clinical MRI image. The modified Beer-Lambert's law is adopted with the DADOI approach to substitute the complex algorithms of inverse problem for mapping of spatial distribution, and the depth information is obtained based on the time-of-flight estimation. The simulation results demonstrate that the time-resolved Monte Carlo method can be capable of performing source-detector separations analysis. The dynamics of photon migration with various source-detector separations are analyzed for the characterization of breast tissue and estimation of optode arrangement. The source-detector separations should be less than 4 cm for breast imaging in DOT system. Meanwhile, the feasibility of DADOI was manifested in this study. In the results, DADOI approach can provide better imaging contrast and faster imaging than conventional DOT measurement. The DADOI approach possesses great potential to detect the breast tumor in early stage and chemotherapy monitoring that implies a good feasibility for clinical application.