Three-dimensional optical tomography: resolution in small-object imaging

Refractive index of biological tissues: Review, measurement techniques, and applications

Refractive index (RI) is a characteristic optical variable that controls the propagation of light in the medium (e.g., biological tissues). Basic research with the aim to investigate the RI of biological tissues is of paramount importance for biomedical optics and associated applications. Herein, we reviewed and summarized the RI data of biological tissues and the associated insights. Different techniques for the measurement of RI of biological tissues are also discussed. Moreover, several examples of the RI applications from basic research, clinics and optics industry are outlined. This study may provide a comprehensive reference for RI data of biological tissues for the biomedical research and beyond.

Nanodiamond phantoms mimicking human liver: perspective to calibration of T1 relaxation time in magnetic resonance imaging

Phantoms of biological tissues are materials that mimic the properties of real tissues. This study shows the development of phantoms with nanodiamond particles for calibration of T1 relaxation time in magnetic resonance imaging. Magnetic resonance imaging (MRI) is a commonly used and non-invasive method of detecting pathological changes inside the human body. Nevertheless, before a new MRI device is approved for use, it is necessary to calibrate it properly and to check its technical parameters. In this article, we present phantoms of tissue with diamond nanoparticles dedicated to magnetic resonance calibration. The method of producing phantoms has been described. As a result of our research, we obtained phantoms that were characterized by the relaxation time T1 the same as the relaxation time of the human tissue T1 = 810.5 ms. Furthermore, the use of diamond nanoparticles in phantoms allowed us to tune the T1 value of the phantoms which open the way to elaborated phantoms of other tissues in the future.

Time-Gated Single-Photon Detection in Time-Domain Diffuse Optics: A Review

This work reviews physical concepts, technologies and applications of time-domain diffuse optics based on time-gated single-photon detection. This particular photon detection strategy is of the utmost importance in the diffuse optics field as it unleashes the full power of the time-domain approach by maximizing performances in terms of contrast produced by a localized perturbation inside the scattering medium, signal-to-noise ratio, measurement time and dynamic range, penetration depth and spatial resolution. The review covers 15 years of theoretical studies, technological progresses, proof of concepts and design of laboratory systems based on time-gated single-photon detection with also few hints on other fields where the time-gated detection strategy produced and will produce further impact.

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.

Noncontact speckle contrast diffuse correlation tomography of blood flow distributions in tissues with arbitrary geometries

A noncontact electron multiplying charge-coupled-device (EMCCD)-based speckle contrast diffuse correlation tomography (scDCT) technology has been recently developed in our laboratory, allowing for noninvasive three-dimensional measurement of tissue blood flow distributions. One major remaining constraint in the scDCT is the assumption of a semi-infinite tissue volume with a flat surface, which affects the image reconstruction accuracy for tissues with irregular geometries. An advanced photometric stereo technique (PST) was integrated into the scDCT system to obtain the surface geometry in real time for image reconstruction. Computer simulations demonstrated that a priori knowledge of tissue surface geometry is crucial for precisely reconstructing the anomaly with blood flow contrast. Importantly, the innovative integration design with one single-EMCCD camera for both PST and scDCT data collection obviates the need for offline alignment of sources and detectors on the tissue boundary. The in vivo imaging capability of the updated scDCT is demonstrated by imaging dynamic changes in forearm blood flow distribution during a cuff-occlusion procedure. The feasibility and safety in clinical use are evidenced by intraoperative imaging of mastectomy skin flaps and comparison with fluorescence angiography.

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).

L1-norm based nonlinear reconstruction improves quantitative accuracy of spectral diffuse optical tomography

Spectrally constrained diffuse optical tomography (SCDOT) is known to improve reconstruction in diffuse optical imaging; constraining the reconstruction by coupling the optical properties across multiple wavelengths suppresses artefacts in the resulting reconstructed images. In other work, L1-norm regularization has been shown to improve certain types of image reconstruction problems as its sparsity-promoting properties render it robust against noise and enable the preservation of edges in images, but because the L1-norm is non-differentiable, it is not always simple to implement. In this work, we show how to incorporate L1 regularization into SCDOT. Three popular algorithms for L1 regularization are assessed for application in SCDOT: iteratively reweighted least square algorithm (IRLS), alternating directional method of multipliers (ADMM), and fast iterative shrinkage-thresholding algorithm (FISTA). We introduce an objective procedure for determining the regularization parameter in these algorithms and compare their performance in simulated experiments, and in real data acquired from a tissue phantom. Our results show that L1 regularization consistently outperforms Tikhonov regularization in this application, particularly in the presence of noise.

Time-Resolved Diffuse Optical Spectroscopy and Imaging Using Solid-State Detectors: Characteristics, Present Status, and Research Challenges

Diffuse optical spectroscopy (DOS) and diffuse optical imaging (DOI) are emerging non-invasive imaging modalities that have wide spread potential applications in many fields, particularly for structural and functional imaging in medicine. In this article, we review time-resolved diffuse optical imaging (TR-DOI) systems using solid-state detectors with a special focus on Single-Photon Avalanche Diodes (SPADs) and Silicon Photomultipliers (SiPMs). These TR-DOI systems can be categorized into two types based on the operation mode of the detector (free-running or time-gated). For the TR-DOI prototypes, the physical concepts, main components, figures-of-merit of detectors, and evaluation parameters are described. The performance of TR-DOI prototypes is evaluated according to the parameters used in common protocols to test DOI systems particularly basic instrumental performance (BIP). In addition, the potential features of SPADs and SiPMs to improve TR-DOI systems and expand their applications in the foreseeable future are discussed. Lastly, research challenges and future developments for TR-DOI are discussed for each component in the prototype separately and also for the entire system.

Time-domain diffuse optical tomography using silicon photomultipliers: feasibility study

Silicon photomultipliers (SiPMs) have been very recently introduced as the most promising detectors in the field of diffuse optics, in particular due to the inherent low cost and large active area. We also demonstrate the suitability of SiPMs for time-domain diffuse optical tomography (DOT). The study is based on both simulations and experimental measurements. Results clearly show excellent performances in terms of spatial localization of an absorbing perturbation, thus opening the way to the use of SiPMs for DOT, with the possibility to conceive a new generation of low-cost and reliable multichannel tomographic systems.

Quantification in time-domain diffuse optical tomography using Mellin-Laplace transforms

Simulations and phantom measurements are used to evaluate the ability of time-domain diffuse optical tomography using Mellin-Laplace transforms to quantify the absorption perturbation of centimetric objects immersed at depth 1-2 cm in turbid media. We find that the estimated absorption coefficient varies almost linearly with the absorption change in the range of 0-0.15 cm^-1 but is underestimated by a factor that depends on the inclusion depth (~2, 3 and 6 for depths of 1.0, 1.5 and 2.0 cm respectively). For larger absorption changes, the variation is sublinear with ~20% decrease for δμ_a = 0.37 cm^-1. By contrast, constraining the absorption change to the actual volume of the inclusion may considerably improve the accuracy and linearity of the reconstructed absorption.

Improving the quantitative accuracy of cerebral oxygen saturation in monitoring the injured brain using atlas based Near Infrared Spectroscopy models

The application of Near Infrared Spectroscopy (NIRS) for the monitoring of the cerebral oxygen saturation within the brain is well established, albeit using temporal data that can only measure relative changes of oxygenation state of the brain from a baseline. The focus of this investigation is to demonstrate that hybridisation of existing near infrared probe designs and reconstruction techniques can pave the way to produce a system and methods that can be used to monitor the absolute oxygen saturation in the injured brain. Using registered Atlas models in simulation, a novel method is outlined by which the quantitative accuracy and practicality of NIRS for specific use in monitoring the injured brain, can be improved, with cerebral saturation being recovered to within 10.1 ± 1.8% of the expected values.

Differentiation of tumor vasculature heterogeneity levels in small animals based on total hemoglobin concentration using magnetic resonance-guided diffuse optical tomography in vivo

Insight into the vasculature of the tumor in small animals has the potential to impact many areas of cancer research. The heterogeneity of the vasculature of a tumor is directly related to tumor stage and disease progression. In this small scale animal study, we investigated the feasibility of differentiating tumors with different levels of vasculature heterogeneity in vivo using a previously developed hybrid magnetic resonance imaging (MRI) and diffuse optical tomography (DOT) system for small animal imaging. Cross-sectional total hemoglobin concentration maps of 10 Fisher rats bearing R3230 breast tumors are reconstructed using multi-wavelength DOT measurements both with and without magnetic resonance (MR) structural a priori information. Simultaneously acquired MR structural images are used to guide and constrain the DOT reconstruction, while dynamic contrast-enhanced MR functional images are used as the gold standard to classify the vasculature of the tumor into two types: high versus low heterogeneity. These preliminary results show that the stand-alone DOT is unable to differentiate tumors with low and high vascular heterogeneity without structural a priori information provided by a high resolution imaging modality. The mean total hemoglobin concentrations comparing the vasculature of the tumors with low and high heterogeneity are significant (p-value 0.02) only when MR structural a priori information is utilized.

Digital Breast Tomosynthesis guided Near Infrared Spectroscopy: Volumetric estimates of fibroglandular fraction and breast density from tomosynthesis reconstructions

A multimodality system combining a clinical prototype digital breast tomosynthesis with its imaging geometry modified to facilitate near-infrared spectroscopic imaging has been developed. The accuracy of parameters recovered from near-infrared spectroscopy is dependent on fibroglandular tissue content. Hence, in this study, volumetric estimates of fibroglandular tissue from tomosynthesis reconstructions were determined. A kernel-based fuzzy c-means algorithm was implemented to segment tomosynthesis reconstructed slices in order to estimate fibroglandular content and to provide anatomic priors for near-infrared spectroscopy. This algorithm was used to determine volumetric breast density (VBD), defined as the ratio of fibroglandular tissue volume to the total breast volume, expressed as percentage, from 62 tomosynthesis reconstructions of 34 study participants. For a subset of study participants who subsequently underwent mammography, VBD from mammography matched for subject, breast laterality and mammographic view was quantified using commercial software and statistically analyzed to determine if it differed from tomosynthesis. Summary statistics of the VBD from all study participants were compared with prior independent studies. The fibroglandular volume from tomosynthesis and mammography were not statistically different (p=0.211, paired t-test). After accounting for the compressed breast thickness, which were different between tomosynthesis and mammography, the VBD from tomosynthesis was correlated with (r =0.809, p<0.001), did not statistically differ from (p>0.99, paired t-test), and was linearly related to, the VBD from mammography. Summary statistics of the VBD from tomosynthesis were not statistically different from prior studies using high-resolution dedicated breast computed tomography. The observation of correlation and linear association in VBD between mammography and tomosynthesis suggests that breast density associated risk measures determined for mammography are translatable to tomosynthesis. Accounting for compressed breast thickness is important when it differs between the two modalities. The fibroglandular volume from tomosynthesis reconstructions is similar to mammography indicating suitability for use during near-infrared spectroscopy.

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.

Noncontact diffuse correlation tomography of human breast tumor

Our first step to adapt our recently developed noncontact diffuse correlation tomography (ncDCT) system for three-dimensional (3-D) imaging of blood flow distribution in human breast tumors is reported. A commercial 3-D camera was used to obtain breast surface geometry, which was then converted to a solid volume mesh. An ncDCT probe scanned over a region of interest on the mesh surface and the measured boundary data were combined with a finite element framework for 3-D image reconstruction of blood flow distribution. This technique was tested in computer simulations and in vivo human breasts with low-grade carcinoma. Results from computer simulations suggest that relatively high accuracy can be achieved when the entire tumor is within the sensitive region of diffuse light. Image reconstruction with a priori knowledge of the tumor volume and location can significantly improve the accuracy in recovery of tumor blood flow contrasts. In vivo imaging results from two breast carcinomas show higher average blood flow contrasts (5.9- and 10.9-fold) in the tumor regions compared to the surrounding tissues, which are comparable with previous findings using diffuse correlation spectroscopy. The ncDCT system has the potential to image blood flow distributions in soft and vulnerable tissues without distorting tissue hemodynamics

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.

Enhancement of fluorescence molecular tomography with structural-prior-based diffuse optical tomography: combating optical background uncertainty

The common approach in fluorescence molecular tomography (FMT) assumes homogeneous distributions of the optical properties and normally results in reconstructions of low sensitivity. A natural enhancement is to incorporate diffuse optical tomography (DOT) to FMT. However, the traditional voxel-based DOT has been a severely ill-posed inverse problem and cannot retrieve the optical property distributions accurately. We present a structural-prior-based DOT method to effectively acquire the heterogeneous optical background with the aid of some imperfect structural priors from x-ray computed tomography and/or magnetic resonance imaging anatomical imaging modalities, and quantitatively compare its hard- and soft-prior schemes for achieving an improved recovery of the fluorescence distribution. Numerical simulations are conducted on a region-labeled three-dimensional (3D) digital mouse model to investigate the performance of this method. Physical experiments on a cylindrical phantom are also conducted to assess this methodology. Our simulated and experimental reconstruction results indicate that the structural-prior-based DOT guided FMT approach can significantly improve the sensitivity of FMT reconstruction, as well as its imaging resolution and quantitative accuracy.

Shape-parameterized diffuse optical tomography holds promise for sensitivity enhancement of fluorescence molecular tomography

A fundamental approach to enhancing the sensitivity of the fluorescence molecular tomography (FMT) is to incorporate diffuse optical tomography (DOT) to modify the light propagation modeling. However, the traditional voxel-based DOT has been involving a severely ill-posed inverse problem and cannot retrieve the optical property distributions with the acceptable quantitative accuracy and spatial resolution. Although, with the aid of an anatomical imaging modality, the structural-prior-based DOT method with either the hard- or soft-prior scheme holds promise for in vivo acquiring the optical background of tissues, the low robustness of the hard-prior scheme to the segmentation error and inferior performance of the soft-prior one in the quantitative accuracy limit its further application. We propose in this paper a shape-parameterized DOT method for not only effectively determining the regional optical properties but potentially achieving reasonable structural amelioration, lending itself to FMT for comparably improved recovery of fluorescence distribution.

Sensitivity of MRI-guided near-infrared spectroscopy clinical breast exam data and its impact on diagnostic performance

In this study, data from breast MRI-guided near infrared spectroscopy (NIRS) exams delivered to 44 patients scheduled for surgical resection (ending in 16 benign and 28 malignant diagnoses) were analyzed using a spatial sensitivity metric to quantify the adequacy of the optical measurements for interrogating the tumor region of interest, as derived from the concurrent MRI scan. Along with positional sensitivity, the incorporation of spectral priors and the selection of an appropriate regularization parameter in the image reconstruction were considered, and found to influence the diagnostic accuracy of the recovered images. Once optimized, the MRI/NIRS data was able to differentiate the malignant from benign lesions through both total hemoglobin (p = 0.0037) and tissue optical index (p = 0.00019), but required the relative spatial sensitivity of the optical measurement data to each lesion to be above 1%. Spectral constraints implemented during the reconstruction were required to obtain statistically significant diagnostic information from images of H2O, lipids, and Tissue Optical Index (TOI). These results confirm the need for optical systems that have homogenous spatial coverage of the breast while still being able to accommodate the normal range of breast sizes.

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.

Hierarchical clustering method to improve transrectal ultrasound-guided diffuse optical tomography for prostate cancer imaging

The inclusion of anatomical prior information in reconstruction algorithms can improve the quality of reconstructed images in near-infrared diffuse optical tomography (DOT). Prior literature on possible locations of human prostate cancer from transrectal ultrasound (TRUS), however, is limited and has led to biased reconstructed DOT images. In this work, we propose a hierarchical clustering method (HCM) to improve the accuracy of image reconstruction with limited prior information. HCM reconstructs DOT images in three steps: 1) to reconstruct the human prostate, 2) to divide the prostate region into geometric clusters to search for anomalies in finer clusters, 3) to continue the geometric clustering within anomalies for improved reconstruction. We demonstrated this hierarchical clustering method using computer simulations and laboratory phantom experiments. Computer simulations were performed using combined TRUS/DOT probe geometry with a multilayered model; experimental demonstration was performed with a single-layer tissue simulating phantom. In computer simulations, two hidden absorbers without prior location information were reconstructed with a recovery rate of 100% in their locations and 95% in their optical properties. In experiments, a hidden absorber without prior location information was reconstructed with a recovery rate of 100% in its location and 83% in its optical property.

Hybrid photomultiplier tube and photodiode parallel detection array for wideband optical spectroscopy of the breast guided by magnetic resonance imaging

A new optical parallel detection system of hybrid frequency and continuous-wave domains was developed to improve the data quality and accuracy in recovery of all breast optical properties. This new system was deployed in a previously existing system for magnetic resonance imaging (MRI)-guided spectroscopy, and allows incorporation of additional near-infrared wavelengths beyond 850 nm, with interlaced channels of photomultiplier tubes (PMTs) and silicon photodiodes (PDs). The acquisition time for obtaining frequency-domain data at six wavelengths (660, 735, 785, 808, 826, and 849 nm) and continuous-wave data at three wavelengths (903, 912, and 948 nm) is 12 min. The dynamic ranges of the detected signal are 105 and 106 for PMT and PD detectors, respectively. Compared to the previous detection system, the SNR ratio of frequency-domain detection was improved by nearly 103 through the addition of an RF amplifier and the utilization of programmable gain. The current system is being utilized in a clinical trial imaging suspected breast cancer tumors as detected by contrast MRI scans.

Small animal fluorescence and bioluminescence tomography: a review of approaches, algorithms and technology update

Emerging fluorescence and bioluminescence tomography approaches have several common, yet several distinct features from established emission tomographies of PET and SPECT. Although both nuclear and optical imaging modalities involve counting of photons, nuclear imaging techniques collect the emitted high energy (100-511 keV) photons after radioactive decay of radionuclides while optical techniques count low-energy (1.5-4.1 eV) photons that are scattered and absorbed by tissues requiring models of light transport for quantitative image reconstruction. Fluorescence imaging has been recently translated into clinic demonstrating high sensitivity, modest tissue penetration depth, and fast, millisecond image acquisition times. As a consequence, the promise of quantitative optical tomography as a complement of small animal PET and SPECT remains high. In this review, we summarize the different instrumentation, methodological approaches and schema for inverse image reconstructions for optical tomography, including luminescence and fluorescence modalities, and comment on limitations and key technological advances needed for further discovery research and translation.

Fast segmentation and high-quality three-dimensional volume mesh creation from medical images for diffuse optical tomography

Multimodal approaches that combine near-infrared (NIR) and conventional imaging modalities have been shown to improve optical parameter estimation dramatically and thus represent a prevailing trend in NIR imaging. These approaches typically involve applying anatomical templates from magnetic resonance imaging/computed tomography/ultrasound images to guide the recovery of optical parameters. However, merging these data sets using current technology requires multiple software packages, substantial expertise, significant time-commitment, and often results in unacceptably poor mesh quality for optical image reconstruction, a reality that represents a significant roadblock for translational research of multimodal NIR imaging. This work addresses these challenges directly by introducing automated digital imaging and communications in medicine image stack segmentation and a new one-click three-dimensional mesh generator optimized for multimodal NIR imaging, and combining these capabilities into a single software package (available for free download) with a streamlined workflow. Image processing time and mesh quality benchmarks were examined for four common multimodal NIR use-cases (breast, brain, pancreas, and small animal) and were compared to a commercial image processing package. Applying these tools resulted in a fivefold decrease in image processing time and 62% improvement in minimum mesh quality, in the absence of extra mesh postprocessing. These capabilities represent a significant step toward enabling translational multimodal NIR research for both expert and nonexpert users in an open-source platform.

Automatic and robust calibration of optical detector arrays for biomedical diffuse optical spectroscopy

The design and testing of a new, fully automated, calibration approach is described. The process was used to calibrate an image-guided diffuse optical spectroscopy system with 16 photomultiplier tubes (PMTs), but can be extended to any large array of optical detectors and associated imaging geometry. The design goals were accomplished by developing a routine for robust automated calibration of the multi-detector array within 45 minutes. Our process was able to characterize individual detectors to a median norm of the residuals of 0.03 V for amplitude and 4.4 degrees in phase and achieved less than 5% variation between all the detectors at the 95% confidence interval for equivalent measurements. Repeatability of the calibrated data from the imaging system was found to be within 0.05 V for amplitude and 0.2 degrees for phase, and was used to evaluate tissue-simulating phantoms in two separate imaging geometries. Spectroscopic imaging of total hemoglobin concentration was recovered to within 5% of the true value in both cases. Future work will focus on streamlining the technology for use in a clinical setting with expectations of achieving accurate quantification of suspicious lesions in the breast.

Dynamic diffuse optical tomography imaging of peripheral arterial disease

Peripheral arterial disease (PAD) is the narrowing of arteries due to plaque accumulation in the vascular walls. This leads to insufficient blood supply to the extremities and can ultimately cause cell death. Currently available methods are ineffective in diagnosing PAD in patients with calcified arteries, such as those with diabetes. In this paper we investigate the potential of dynamic diffuse optical tomography (DDOT) as an alternative way to assess PAD in the lower extremities. DDOT is a non-invasive, non-ionizing imaging modality that uses near-infrared light to create spatio-temporal maps of oxy- and deoxy-hemoglobin in tissue. We present three case studies in which we used DDOT to visualize vascular perfusion of a healthy volunteer, a PAD patient and a diabetic PAD patient with calcified arteries. These preliminary results show significant differences in DDOT time-traces and images between all three cases, underscoring the potential of DDOT as a new diagnostic tool.

Singular value decomposition based regularization prior to spectral mixing improves crosstalk in dynamic imaging using spectral diffuse optical tomography

The spectrally constrained diffuse optical tomography (DOT) method relies on incorporating spectral prior information directly into the image reconstruction algorithm, thereby correlating the underlying optical properties across multiple wavelengths. Although this method has been shown to provide a solution that is stable, the use of conventional Tikhonov-type regularization techniques can lead to additional crosstalk between parameters, particularly in linear, single-step dynamic imaging applications. This is due mainly to the suboptimal regularization of the spectral Jacobian matrix, which smoothes not only the image-data space, but also the spectral mapping space. In this work a novel regularization technique based on the singular value decomposition (SVD) is presented that preserves the spectral prior information while regularizing the Jacobian matrix, leading to dramatically reduced crosstalk between the recovered parameters. Using simulated data, images of changes in oxygenated and deoxygenated hemoglobin concentrations are reconstructed via the SVD-based approach and compared with images reconstructed by using non-spectral and conventional spectral methods. In a 2D, two wavelength example, it is shown that the proposed approach provides a 98% reduction in crosstalk between recovered parameters as compared with conventional spectral reconstruction algorithms, and 60% as compared with non-spectrally constrained algorithms. Using a subject specific multilayered model of the human head, a noiseless dynamic simulation of cortical activation is performed to further demonstrate such improvement in crosstalk. However, with the addition of realistic noise in the data, both non-spectral and proposed algorithms perform similarly, indicating that the use of spectrally constrained reconstruction algorithms in dynamic DOT may be limited by the contrast of the signal as well as the noise characteristics of the system.

High-density diffuse optical tomography of term infant visual cortex in the nursery

Advancements in antenatal and neonatal medicine over the last few decades have led to significant improvement in the survival rates of sick newborn infants. However, this improvement in survival has not been matched by a reduction in neurodevelopmental morbidities with increasing recognition of the diverse cognitive and behavioral challenges that preterm infants face in childhood. Conventional neuroimaging modalities, such as cranial ultrasound and magnetic resonance imaging, provide an important definition of neuroanatomy with recognition of brain injury. However, they fail to define the functional integrity of the immature brain, particularly during this critical developmental period. Diffuse optical tomography methods have established success in imaging adult brain function; however, few studies exist to demonstrate their feasibility in the neonatal population. We demonstrate the feasibility of using recently developed high-density diffuse optical tomography (HD-DOT) to map functional activation of the visual cortex in healthy term-born infants. The functional images show high contrast-to-noise ratio obtained in seven neonates. These results illustrate the potential for HD-DOT and provide a foundation for investigations of brain function in more vulnerable newborns, such as preterm infants.

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.

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.

Comparison of no-prior and soft-prior regularization in biomedical microwave imaging

Microwave imaging for medical applications is attractive because the range of dielectric properties of different soft tissues can be substantial. Breast cancer detection and monitoring of treatment response are areas where this technology could be important because of the contrast between normal and malignant tissue. Unfortunately, the technique is unable to achieve the high spatial resolution at depth in tissue which is available from other conventional modalities such as x-ray computed tomography (CT) or magnetic resonance imaging (MRI). We have incorporated a soft-prior regularization strategy within our microwave reconstruction algorithm and compared it with the images obtained with traditional no-prior (Levenberg-Marquardt) regularization. Initial simulation and phantom results show a significant improvement of the recovered electrical properties. Specifically, errors in the microwave property estimates were improved by as much as 95%. The effects of a false-inclusion region were also evaluated and the results show that a small residual property bias of 6% in permittivity and 15% in conductivity can occur that does not otherwise degrade the property recovery accuracy of inclusions that actually exist. The work sets the stage for integrating microwave imaging with MR for improved resolution and functional imaging of the breast in the future.

Bedside optical imaging of occipital resting-state functional connectivity in neonates

Resting-state networks derived from temporal correlations of spontaneous hemodynamic fluctuations have been extensively used to elucidate the functional organization of the brain in adults and infants. We have previously developed functional connectivity diffuse optical tomography methods in adults, and we now apply these techniques to study functional connectivity in newborn infants at the bedside. We present functional connectivity maps in the occipital cortices obtained from healthy term-born infants and premature infants, including one infant with an occipital stroke. Our results suggest that functional connectivity diffuse optical tomography has potential as a valuable clinical tool for the early detection of functional deficits and for providing prognostic information on future development.

Localization of an absorber in a turbid semi-infinite medium by spatially resolved continuous-wave diffuse reflectance measurements

A method to locate an absorber embedded in a semi-infinite turbid medium by spatially-resolved continuous-wave (SRCW) diffuse reflectance measurements is introduced. The depth of the absorber is assessed by single wavelength SRCW diffuse reflectance measurements by two detectors in a radial row. The ratio of perturbations introduced by the defect at two detectors is used to be matched with the ratio-versus-depth curve, which are generated by approximate formulas of continuous wave diffuse reflectance. The error due to approximation and the error in depth assessment are studied for different cases revealing favorable source-detector placements with respect to planar position of the defect. The effect of lateral displacement of the source with respect to defect is studied. A strategy to overcome errors introduced by erroneous prediction of background medium optical properties is suggested. Theoretical results indicate that the depth of the absorber can be obtained with 0.1 mm precision independent of its absorption coefficient and its size for the values chosen in the study. The approach is tested experimentally and it is observed that theoretical results fit with experimental data.

Remote positioning optical breast magnetic resonance coil for slice-selection during image-guided near-infrared spectroscopy of breast cancer

The design and testing of a pneumatic optical positioning interface produced with the goal of improving fiber positioning in magnetic resonance (MR)-guided diffuse spectral imaging of breast cancer is presented. The system was created for vertical positioning of optical fibers inside the MR bore during a patient exam to target suspicious lesions with MR scans for reference and collect multiple planes of optical data. The interface includes new fiber plates for mechanical and optical coupling to the breast, and was tested in phantoms and human imaging. Reconstructions with data taken in the new interface show acceptable linearity over different absorber concentrations (residual norm = 0.067), and exhibit good contrast recovery at different imaging planes, which is consistent with previous work. An example of human breast imaging through the new interface is shown and a discussion of how it compares to other patient interfaces for breast imaging is presented. Design goals of increasing the available degrees of freedom for fiber positioning while maintaining good patient-fiber contact and comfort were accomplished. This interface allows improved volumetric imaging with interactive and accurate slice selection to quantify targeted suspicious lesions.

MR water quantitative priors improves the accuracy of optical breast imaging

Magnetic resonance (MR) guided optical breast imaging is a promising modality to improve the specificity of breast imaging, because it provides high-resolution quantitative maps of total hemoglobin, oxygen saturation, water content, and optical scattering. These properties have been shown to distinguish malignant from benign lesions. However, the optical detection hardware required for deep tissue imaging has poor spectral sensitivity which limits accurate water quantification; this reduces the accuracy of hemoglobin quantification. We present a methodology to improve optical quantification by utilizing the ability of Dixon MR imaging to quantitatively estimate water and fat; this technique effectively reduces optical crosstalk between water and oxyhemoglobin. The techniques described in this paper reduce hemoglobin quantification error by as much as 38%, as shown in a numerical phantom, and an experimental phantom. Error is reduced by as much 20% when imperfect MR water quantification is given. These techniques may also increase contrast between diseased and normal tissue, as shown in breast tissue in vivo. It is also shown that using these techniques may permit fewer wavelengths to be used with similar quantitative accuracy, enabling higher temporal resolution. In addition, it is shown that these techniques can improve the ability of MRI to quantify water in the presence of bias in the Dixon water/fat separation.

Algorithmic depth compensation improves quantification and noise suppression in functional diffuse optical tomography

Accurate depth localization and quantitative recovery of a regional activation are the major challenges in functional diffuse optical tomography (DOT). The photon density drops severely with increased depth, for which conventional DOT reconstruction yields poor depth localization and quantitative recovery. Recently we have developed a depth compensation algorithm (DCA) to improve the depth localization in DOT. In this paper, we present an approach based on the depth-compensated reconstruction to improve the quantification in DOT by forming a spatial prior. Simulative experiments are conducted to demonstrate the usefulness of this approach. Moreover, noise suppression is a key to success in DOT which also affects the depth localization and quantification. We present quantitative analysis and comparison on noise suppression in DOT with and without depth compensation. The study reveals that appropriate combination of depth-compensated reconstruction with the spatial prior can provide accurate depth localization and improved quantification at variable noise levels.

Characterizing accuracy of total hemoglobin recovery using contrast-detail analysis in 3D image-guided near infrared spectroscopy with the boundary element method

The quantification of total hemoglobin concentration (HbT) obtained from multi-modality image-guided near infrared spectroscopy (IG-NIRS) was characterized using the boundary element method (BEM) for 3D image reconstruction. Multi-modality IG-NIRS systems use a priori information to guide the reconstruction process. While this has been shown to improve resolution, the e(R)ect on quantitative accuracy is unclear. Here, through systematic contrast-detail analysis, the fidelity of IG-NIRS in quantifying HbT was examined using 3D simulations. These simulations show that HbT could be recovered for medium sized (20mm in 100mm total diameter) spherical inclusions with an average error of 15%, for the physiologically relevant situation of 2:1 or higher contrast between background and inclusion. Using partial 3D volume meshes to reduce the ill-posed nature of the image reconstruction, inclusions as small as 14 mm could be accurately quantified with less than 15% error, for contrasts of 1.5 or higher. This suggests that 3D IG-NIRS provides quantitatively accurate results for sizes seen early in treatment cycle of patients undergoing neoadjuvant chemotherapy when the tumors are larger than 30 mm.

Diffuse Optics for Tissue Monitoring and Tomography

This review describes the diffusion model for light transport in tissues and the medical applications of diffuse light. Diffuse optics is particularly useful for measurement of tissue hemodynamics, wherein quantitative assessment of oxy- and deoxy-hemoglobin concentrations and blood flow are desired. The theoretical basis for near-infrared or diffuse optical spectroscopy (NIRS or DOS, respectively) is developed, and the basic elements of diffuse optical tomography (DOT) are outlined. We also discuss diffuse correlation spectroscopy (DCS), a technique whereby temporal correlation functions of diffusing light are transported through tissue and are used to measure blood flow. Essential instrumentation is described, and representative brain and breast functional imaging and monitoring results illustrate the workings of these new tissue diagnostics.

Monitoring of hemodynamic changes induced in the healthy breast through inspired gas stimuli with MR-guided diffuse optical imaging

PURPOSE

The modulation of tissue hemodynamics has important clinical value in medicine for both tumor diagnosis and therapy. As an oncological tool, increasing tissue oxygenation via modulation of inspired gas has been proposed as a method to improve cancer therapy and determine radiation sensitivity. As a radiological tool, inducing changes in tissue total hemoglobin may provide a means to detect and characterize malignant tumors by providing information about tissue vascular function. The ability to change and measure tissue hemoglobin and oxygenation concentrations in the healthy breast during administration of three different types of modulated gas stimuli (oxygen/ carbogen, air/carbogen, and air/oxygen) was investigated.

METHODS

Subjects breathed combinations of gases which were modulated in time. MR-guided diffuse optical tomography measured total hemoglobin and oxygen saturation in the breast every 30 s during the 16 min breathing stimulus. Metrics of maximum correlation and phase lag were calculated by cross correlating the measured hemodynamics with the stimulus. These results were compared to an air/air control to determine the hemodynamic changes compared to the baseline physiology.

RESULTS

This study demonstrated that a gas stimulus consisting of alternating oxygen/carbogen induced the largest and most robust hemodynamic response in healthy breast parenchyma relative to the changes that occurred during the breathing of room air. This stimulus caused increases in total hemoglobin and oxygen saturation during the carbogen phase of gas inhalation, and decreases during the oxygen phase. These findings are consistent with the theory that oxygen acts as a vasoconstrictor, while carbogen acts as a vasodilator. However, difficulties in inducing a consistent change in tissue hemoglobin and oxygenation were observed because of variability in intersubject physiology, especially during the air/oxygen or air/carbogen modulated breathing protocols.

CONCLUSIONS

MR-guided diffuse optical imaging is a unique tool that can measure tissue hemodynamics in the breast during modulated breathing. This technique may have utility in determining the therapeutic potential of pretreatment tissue oxygenation or in investigating vascular function. Future gas modulation studies in the breast should use a combination of oxygen and carbogen as the functional stimulus. Additionally, control measures of subject physiology during air breathing are critical for robust measurements.

Direct-current-based image reconstruction versus direct-current included or excluded frequency-domain reconstruction in diffuse optical tomography

We study the level of image artifacts in optical tomography associated with measurement uncertainty under three reconstruction configurations, namely, by using only direct-current (DC), DC-excluded frequency-domain, and DC-included frequency-domain data. Analytic and synthetic studies demonstrate that, at the same level of measurement uncertainty typical to optical tomography, the ratio of the standard deviation of mu(a) over mu(a) reconstructed by DC only is at least 1.4 times lower than that by frequency-domain methods. The ratio of standard deviations of D (or mu(s)') over D (or mu(s)') reconstructed by DC only are slightly lower than those by frequency-domain methods. Frequency-domain reconstruction including DC generally outperforms that excluding DC, but as the amount of measurements increases, the difference between the two diminishes. Under the condition of a priori structural information, the performances of three reconstruction configurations are seemingly equivalent.

Image reconstruction in diffuse optical tomography based on simplified spherical harmonics approximation

The use of higher order approximations to the Radiative transport equation, through simplified spherical harmonics expansion (SP(N)) in optical tomography are presented. It is shown that, although the anisotropy factor can be modeled in the forward problem, its sensitivity to the measured boundary data is limited to superficial regions and more importantly, due to uniqueness of the inverse problem it cannot be determined using frequency domain data. Image reconstruction through the use of higher ordered models is presented. It is demonstrated that at higher orders (for example SP7) the image reconstruction becomes highly under-determined due to the large increase in the number of unknowns which cannot be adequately recovered. However, reconstruction of diffuse parameters, namely optical absorption and reduced scatter have shown to be more accurate where only the sensitivity matrix used in the inverse problem is based on SP(N) method and image reconstruction is limited to these two diffuse parameters.

Parametric image reconstruction using the discrete cosine transform for optical tomography

It is well known that the inverse problem in optical tomography is highly ill-posed. The image reconstruction process is often unstable and nonunique, because the number of the boundary measurements data is far fewer than the number of the unknown parameters to be reconstructed. To overcome this problem, one can either increase the number of measurement data (e.g., multispectral or multifrequency methods), or reduce the number of unknowns (e.g., using prior structural information from other imaging modalities). We introduce a novel approach for reducing the unknown parameters in the reconstruction process. The discrete cosine transform (DCT), which has long been used in image compression, is here employed to parameterize the reconstructed image. In general, only a few DCT coefficients are needed to describe the main features in an optical tomographic image. Thus, the number of unknowns in the image reconstruction process can be drastically reduced. We show numerical and experimental examples that illustrate the performance of the new algorithm as compared to a standard model-based iterative image reconstructions scheme. We especially focus on the influence of initial guesses and noise levels on the reconstruction results.

Direct reconstruction of pharmacokinetic-rate images of optical fluorophores from NIR measurements

In this paper, we present a new method to form pharmacokinetic-rate images of optical fluorophores directly from near infra-red (NIR) boundary measurements. We first derive a mapping from spatially resolved pharmacokinetic rates to NIR boundary measurements by combining compartmental modeling with a diffusion based NIR photon propagation model. We express this mapping as a state-space equation. Next, we introduce a spatio-temporal prior model for the pharmacokinetic-rate images and combine it with the state-space equation. We address the image formation problem using the extended Kalman filtering framework. We analyze the computational complexity of the resulting algorithms and evaluate their performance in numerical simulations. An important feature of our approach is that the reconstruction of fluorescence concentrations and compartmental modeling are combined into a single step 1) to take advantage of the inherent temporal correlations in dynamic NIR measurements, and 2) to incorporate spatio-temporal a priori information on pharmacokinetic-rate images. Simulation results show that the resulting algorithms are more robust and lead to higher signal-to-noise ratio as compared to existing approaches where the reconstruction of concentrations and compartmental modeling are treated separately. Additionally, we reconstructed pharmacokinetic-rate images using in vivo data obtained from three patients with breast tumors. The reconstruction results show that the pharmacokinetic rates of indocyanine green are higher inside the tumor region as compared to the surrounding tissue.

Early-photon fluorescence tomography: spatial resolution improvements and noise stability considerations

In vivo tissue imaging using near-infrared light suffers from low spatial resolution and poor contrast recovery because of highly scattered photon transport. For diffuse optical tomography (DOT) and fluorescence molecular tomography (FMT), the resolution is limited to about 5-10% of the diameter of the tissue being imaged, which puts it in the range of performance seen in nuclear medicine. This paper introduces the mathematical formalism explaining why the resolution of FMT can be significantly improved when using instruments acquiring fast time-domain optical signals. This is achieved through singular-value analysis of the time-gated inverse problem based on weakly diffused photons. Simulations relevant to mouse imaging are presented showing that, in stark contrast to steady-state imaging, early time-gated intensities (within 200 ps or 400 ps) can in principle be used to resolve small fluorescent targets (radii from 1.5 to 2.5 mm) separated by less than 1.5 mm.

Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction

Diffuse optical tomography, also known as near infrared tomography, has been under investigation, for non-invasive functional imaging of tissue, specifically for the detection and characterization of breast cancer or other soft tissue lesions. Much work has been carried out for accurate modeling and image reconstruction from clinical data. NIRFAST, a modeling and image reconstruction package has been developed, which is capable of single wavelength and multi-wavelength optical or functional imaging from measured data. The theory behind the modeling techniques as well as the image reconstruction algorithms is presented here, and 2D and 3D examples are presented to demonstrate its capabilities. The results show that 3D modeling can be combined with measured data from multiple wavelengths to reconstruct chromophore concentrations within the tissue. Additionally it is possible to recover scattering spectra, resulting from the dominant Mie-type scatter present in tissue. Overall, this paper gives a comprehensive over view of the modeling techniques used in diffuse optical tomographic imaging, in the context of NIRFAST software package.

Spectral distortion in diffuse molecular luminescence tomography in turbid media

The influence of tissue optical properties on the shape of near-infrared (NIR) fluorescence emission spectra propagating through multiple centimeters of tissue-like media was investigated. Fluorescence emission spectra measured from 6 cm homogeneous tissue-simulating phantoms show dramatic spectral distortion which results in emission peak shifts of up to 60 nm in wavelength. Measured spectral shapes are highly dependent on the photon path length and the scattered photon field in the NIR amplifies the wavelength-dependent absorption of the fluorescence spectra. Simulations of the peak propagation using diffusion modeling describe the experimental observations and confirm the path length dependence of fluorescence emission spectra. Spectral changes are largest for long path length measurements and thus will be most important in human tomography studies in the NIR. Spectrally resolved detection strategies are required to detect and interpret these effects which may otherwise produce erroneous intensity measurements. This observed phenomenon is analogous to beam hardening in x-ray tomography, which can lead to image artifacts without appropriate compensation. The peak shift toward longer wavelengths, and therefore lower energy photons, observed for NIR luminescent signals propagating through tissue may readily be described as a beam softening phenomenon.

Differentiation of benign and malignant breast tumors by in-vivo three-dimensional parallel-plate diffuse optical tomography

We have developed a novel parallel-plate diffuse optical tomography (DOT) system for three-dimensional in vivo imaging of human breast tumor based on large optical data sets. Images of oxy-, deoxy-, and total hemoglobin concentration as well as blood oxygen saturation and tissue scattering were reconstructed. Tumor margins were derived using the optical data with guidance from radiology reports and magnetic resonance imaging. Tumor-to-normal ratios of these endogenous physiological parameters and an optical index were computed for 51 biopsy-proven lesions from 47 subjects. Malignant cancers (N=41) showed statistically significant higher total hemoglobin, oxy-hemoglobin concentration, and scattering compared to normal tissue. Furthermore, malignant lesions exhibited a twofold average increase in optical index. The influence of core biopsy on DOT results was also explored; the difference between the malignant group measured before core biopsy and the group measured more than 1 week after core biopsy was not significant. Benign tumors (N=10) did not exhibit statistical significance in the tumor-to-normal ratios of any parameter. Optical index and tumor-to-normal ratios of total hemoglobin, oxy-hemoglobin concentration, and scattering exhibited high area under the receiver operating characteristic curve values from 0.90 to 0.99, suggesting good discriminatory power. The data demonstrate that benign and malignant lesions can be distinguished by quantitative three-dimensional DOT.

Image-guided near infrared spectroscopy using boundary element method: phantom validation

Image-guided near infrared spectroscopy (IG-NIRS) can provide high-resolution vascular, metabolic and molecular characterization of localized tissue volumes in-vivo. The approach for IG-NIRS uses hybrid systems where the spatial anatomical structure of tissue obtained from standard imaging modalities (such as MRI) is combined with tissue information from diffuse optical imaging spectroscopy. There is need to optimize these hybrid systems for large-scale clinical trials anticipated in the near future in order to evaluate the feasibility of this technology across a larger population. However, existing computational methods such as the finite element method mesh arbitrary image volumes, which inhibit automation, especially with large numbers of datasets. Circumventing this issue, a boundary element method (BEM) for IG-NIRS systems in 3-D is presented here using only surface rendering and discretization. The process of surface creation and meshing is faster, more reliable, and is easily generated automatically as compared to full volume meshing. The proposed method has been implemented here for multi-spectral non-invasive characterization of tissue. In phantom experiments, 3-D spectral BEM-based spectroscopy recovered the oxygen dissociation curve with mean error of 6.6% and tracked variation in total hemoglobin linearly.