A digital x-ray tomosynthesis coupled near infrared spectral tomography system for dual-modality breast imaging

Compact breast shape acquisition system for improving diffuse optical tomography image reconstructions

Diffuse optical tomography (DOT) has been investigated for diagnosing malignant breast lesions, but its accuracy relies on model-based image reconstructions, which in turn depends on the accuracy of breast shape acquisition. In this work, we have developed a dual-camera structured light imaging (SLI) breast shape acquisition system tailored for a mammography-like compression setting. Illumination pattern intensity is dynamically adjusted to account for skin tone differences, while thickness-informed pattern masking reduces artifacts due to specular reflections. This compact system is affixed to a rigid mount that can be installed into existing mammography or parallel-plate DOT systems without the need for camera-projector re-calibration. Our SLI system produces sub-millimeter resolution with a mean surface error of 0.26 mm. This breast shape acquisition system results in more accurate surface recovery, with an average 1.6-fold reduction in surface estimation errors over a reference method via contour extrusion. Such improvement translates to 25% to 50% reduction in mean squared error in the recovered absorption coefficient for a series of simulated tumors 1-2 cm below the skin.

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

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

Multi-objective optimization for structured illumination in dynamic x-ray tomosynthesis

Dynamic coded x-ray tomosynthesis (CXT) uses a set of encoded x-ray sources to interrogate objects lying on a moving conveyor mechanism. The object is reconstructed from the encoded measurements received by the uniform linear array detectors. We propose a multi-objective optimization (MO) method for structured illuminations to balance the reconstruction quality and radiation dose in a dynamic CXT system. The MO framework is established based on a dynamic sensing geometry with binary coding masks. The Strength Pareto Evolutionary Algorithm 2 is used to solve the MO problem by jointly optimizing the coding masks, locations of x-ray sources, and exposure moments. Computational experiments are implemented to assess the proposed MO method. They show that the proposed strategy can obtain a set of Pareto optimal solutions with different levels of radiation dose and better reconstruction quality than the initial setting.

Single-snapshot X-ray imaging for nonlinear compressive tomosynthesis

Traditional compressive X-ray tomosynthesis uses sequential illumination to interrogate the object, leading to long scanning time and image distortion due to the object variation. This paper proposes a single-snapshot compressive tomosynthesis imaging approach, where the object is simultaneously illuminated by multiple X-ray emitters equipped with coded apertures. Based on rank, intensity and sparsity prior models, a nonlinear image reconstruction framework is established. The coded aperture patterns are optimized based on uniform sensing criteria. Then, a modified split Bregman algorithm is developed to reconstruct the object from the set of nonlinear compressive measurements. It is shown that the proposed method can be used to reduce the inspection time and achieve robust reconstruction with respect to shape variation or motion of objects.

Development of digital breast tomosynthesis and diffuse optical tomography fusion imaging for breast cancer detection

Diffuse optical tomography (DOT) non-invasively measures the functional characteristics of breast lesions using near infrared light to probe tissue optical properties. This study aimed to evaluate a new digital breast tomosynthesis (DBT)/DOT fusion imaging technique and obtain preliminary data for breast cancer detection. Twenty-eight women were prospectively enrolled and underwent both DBT and DOT examinations. DBT/DOT fusion imaging was created after acquisition of both examinations. Two breast radiologists analyzed DBT and DOT images independently, and then finally evaluated the fusion images. The diagnostic performance of each reading session was compared and interobserver agreement was assessed. The technical success rate was 96.4%, with one failure due to an error during DOT data storage. Among the 27 women finally included in the analysis, 13 had breast cancer. The areas under the receiver operating characteristic curve (AUCs) for DBT were 0.783 and 0.854 for readers 1 and 2, respectively. DOT showed comparable diagnostic performance to DBT for both readers. The AUCs were significantly improved (P = 0.004) when the DBT/DOT fusion images were used. Interobserver agreements were highest for the DBT/DOT fusion images. In conclusion, this study suggests that DBT/DOT fusion imaging technique appears to be a promising tool for breast cancer diagnosis.

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

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

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

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

Convolutional neural network-based approach to estimate bulk optical properties in diffuse optical tomography

Deep learning has been actively investigated for various applications such as image classification, computer vision, and regression tasks, and it has shown state-of-the-art performance. In diffuse optical tomography (DOT), the accurate estimation of the bulk optical properties of a medium is paramount because it directly affects the overall image quality. In this work, we exploit deep learning to propose a novel, to the best of our knowledge, convolutional neural network (CNN)-based approach to estimate the bulk optical properties of a highly scattering medium such as biological tissue in DOT. We validated the proposed method by using experimental, as well as, simulated data. For performance assessment, we compared the results of the proposed method with those of existing approaches. The results demonstrate that the proposed CNN-based approach for bulk optical property estimation outperforms existing methods in terms of estimation accuracy, with lower computation time.

Current and future trends in photoacoustic breast imaging

Non-invasive detection of breast cancer has been regarded as the holy grail of applications for photoacoustic (optoacoustic) imaging right from the early days of re-discovery of the method. Two-and-a-half decades later we report on the state-of-the-art in photoacoustic breast imaging technology and clinical studies. Even within the single application of breast imaging, we find imagers with various measurement geometries, ultrasound detection characteristics, illumination schemes, and image reconstruction strategies. We first analyze the implications on performance of a few of these design choices in a generic imaging system, before going into detailed descriptions of the imagers. Per imaging system we present highlights of patient studies, which barring a couple are mostly in the nature of technology demonstrations and proof-of-principle studies. We close this work with a discussion on several aspects that may turn out to be crucial for the future clinical translation of the method.

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.

Source and coded aperture joint optimization for compressive X-ray tomosynthesis

Compressive X-ray tomosynthesis is an emerging technique to reconstruct three-dimensional (3D) objects from two-dimensional projection measurements generated by a set of spatially distributed X-ray sources, where coded apertures are used in front of each source to modulate a set of X-rays to interrogate an object with a reduced radiation dose without loss of image reconstruction quality. The reconstruction performance in compressive tomosynthesis is influenced by several factors including the locations of the X-ray sources, their incident angles, and the coded apertures that determine the structured illumination patterns. This paper develops a source and coded aperture joint optimization (SCO) approach to improve the image reconstruction performance of compressive X-ray tomosynthesis. Based on compressive sensing theory, the synergy among the source pattern, source orientation, and the coded apertures is utilized to minimize the coherence of the sensing matrix of the imaging system. In concert with a gradient-based optimization algorithm, regularization methods are used to reduce the convergence error and achieve uniform sensing of the object under inspection. Compared to the optimization of either the source orientation, or the coded aperture individually, the proposed method effectively increases the degree of optimization freedom, and thus achieves considerable improvement in the 3D imaging reconstruction accuracy.

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

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

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

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

Emerging Breast Imaging Technologies on the Horizon

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

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.

Multimodal breast cancer imaging using coregistered dynamic diffuse optical tomography and digital breast tomosynthesis

Diffuse optical tomography (DOT) is emerging as a noninvasive functional imaging method for breast cancer diagnosis and neoadjuvant chemotherapy monitoring. In particular, the multimodal approach of combining DOT with x-ray digital breast tomosynthesis (DBT) is especially synergistic as DBT prior information can be used to enhance the DOT reconstruction. DOT, in turn, provides a functional information overlay onto the mammographic images, increasing sensitivity and specificity to cancer pathology. We describe a dynamic DOT apparatus designed for tight integration with commercial DBT scanners and providing a fast (up to 1 Hz) image acquisition rate to enable tracking hemodynamic changes induced by the mammographic breast compression. The system integrates 96 continuous-wave and 24 frequency-domain source locations as well as 32 continuous wave and 20 frequency-domain detection locations into low-profile plastic plates that can easily mate to the DBT compression paddle and x-ray detector cover, respectively. We demonstrate system performance using static and dynamic tissue-like phantoms as well as in vivo images acquired from the pool of patients recalled for breast biopsies at the Massachusetts General Hospital Breast Imaging Division.

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

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

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

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

Digital Breast Tomosynthesis: State of the Art

This topical review on digital breast tomosynthesis (DBT) is provided with the intent of describing the state of the art in terms of technology, results from recent clinical studies, advanced applications, and ongoing efforts to develop multimodality imaging systems that include DBT. Particular emphasis is placed on clinical studies. The observations of increase in cancer detection rates, particularly for invasive cancers, and the reduction in false-positive rates with DBT in prospective trials indicate its benefit for breast cancer screening. Retrospective multireader multicase studies show either noninferiority or superiority of DBT compared with mammography. Methods to curtail radiation dose are of importance. (©) RSNA, 2015.

Frequency domain near-infrared multiwavelength imager design using high-speed, direct analog-to-digital conversion

Frequency domain near-infrared spectroscopy (FD-NIRS) has proven to be a reliable method for quantification of tissue absolute optical properties. We present a full-sampling direct analog-to-digital conversion FD-NIR imager. While we developed this instrument with a focus on high-speed optical breast tomographic imaging, the proposed design is suitable for a wide-range of biophotonic applications where fast, accurate quantification of absolute optical properties is needed. Simultaneous dual wavelength operation at 685 and 830 nm is achieved by concurrent 67.5 and 75 MHz frequency modulation of each laser source, respectively, followed by digitization using a high-speed (180  MS/s) 16-bit A/D converter and hybrid FPGA-assisted demodulation. The instrument supports 25 source locations and features 20 concurrently operating detectors. The noise floor of the instrument was measured at <1.4  pW/√Hz, and a dynamic range of 115+ dB, corresponding to nearly six orders of magnitude, has been demonstrated. Titration experiments consisting of 200 different absorption and scattering values were conducted to demonstrate accurate optical property quantification over the entire range of physiologically expected values.

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

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

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.

Does adding diffuse optical tomography to sonography improve differentiation between benign and malignant breast lesions? Observer performance study

OBJECTIVES

The purpose of this study was to investigate the added value of diffuse optical tomographic categories combined with conventional sonography for differentiating between benign and malignant breast lesions.

METHODS

In this retrospective database review, we included 145 breast lesions (116 benign and 29 malignant) from 145 women (mean age, 46 years; range, 16-86 years). Five radiologists independently reviewed sonograms with and without a diffuse optical tomographic category. Each lesion was scored on a scale of 0% to 100% for suspicion of malignancy and rated according to the American College of Radiology Breast Imaging Reporting and Data System classification. Diagnostic performance was analyzed by comparing area under receiver operating characteristic curve values. Reader agreement was assessed by intraclass correlation coefficients.

RESULTS

In the multireader multicase receiver operating characteristic analysis, adding a diffuse optical tomographic category to sonography improved the diagnostic accuracy of sonography (mean areas under the curve, 0.923 for sonography alone and 0.969 for sonography with diffuse optical tomography; P = .039). The interobserver correlation was also improved (0.798 for sonography alone and 0.904 for sonography with diffuse optical tomography). The specificity increased for 4 reviewers from a mean of 19.5% to 45.8% (P < .001 for reviewers 1-4; P = .238 for reviewer 5) with no significant change in the sensitivity. When the diffuse optical tomographic category was applied strictly, the specificity increased for all reviewers from a mean of 19.5% to 68.3% (P < .001 for all reviewers) with no significant change in the sensitivity.

CONCLUSIONS

The addition of diffuse optical tomographic categories to sonography may improve diagnostic performance and markedly decrease false-positive biopsy recommendations.

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.

Sparse-view computed laminography with a spherical sinusoidal scan for nondestructive testing

X-ray computed laminography is widely used in nondestructive testing of relatively flat objects using an oblique scanning configuration for data acquisition. In this work, a new scanning scheme is proposed in conjunction with the compressive-sensing-based image reconstruction for reducing imaging radiation dose and scanning time. We performed a numerical study comparing image qualities acquired by various scanning configurations that are practically implementable: single-arc, double-arc, oblique, and spherical-sinusoidal trajectories. A compressive-sensing-inspired total-variation (TV) minimization algorithm was used to reconstruct the images from the data acquired at only 40 projection views in those trajectories. It was successfully demonstrated that the proposed scanning scheme outperforms the others in terms of image contrast and spatial resolution, although the oblique scanning scheme showed a comparable resolution property. We believe that the proposed scanning method may provide a solution to fast and low-dose nondestructive testing of radiation-sensitive and highly integrated devices such as multilayer microelectronic circuit boards.

Integration of microwave tomography with magnetic resonance for improved breast imaging

PURPOSE

Breast magnetic resonance imaging is highly sensitive but not very specific for the detection of breast cancer. Opportunities exist to supplement the image acquisition with a more specific modality provided the technical challenges of meeting space limitations inside the bore, restricted breast access, and electromagnetic compatibility requirements can be overcome. Magnetic resonance (MR) and microwave tomography (MT) are complementary and synergistic because the high resolution of MR is used to encode spatial priors on breast geometry and internal parenchymal features that have distinct electrical properties (i.e., fat vs fibroglandular tissue) for microwave tomography.

METHODS

The authors have overcome integration challenges associated with combining MT with MR to produce a new coregistered, multimodality breast imaging platform--magnetic resonance microwave tomography, including: substantial illumination tank size reduction specific to the confined MR bore diameter, minimization of metal content and composition, reduction of metal artifacts in the MR images, and suppression of unwanted MT multipath signals.

RESULTS

MR SNR exceeding 40 dB can be obtained. Proper filtering of MR signals reduces MT data degradation allowing MT SNR of 20 dB to be obtained, which is sufficient for image reconstruction. When MR spatial priors are incorporated into the recovery of MT property estimates, the errors between the recovered versus actual dielectric properties approach 5%.

CONCLUSIONS

The phantom and human subject exams presented here are the first demonstration of combining MT with MR to improve the accuracy of the reconstructed MT images.

Anthropomorphic breast phantoms with physiological water, lipid, and hemoglobin content for near-infrared spectral tomography

Breast mimicking tissue optical phantoms with sufficient structural integrity to be deployed as stand-alone imaging targets are developed and successfully constructed with biologically relevant concentrations of water, lipid, and blood. The results show excellent material homogeneity and reproducibility with inter- and intraphantom variability of 3.5 and 3.8%, respectively, for water and lipid concentrations ranging from 15 to 85%. The phantoms were long-lasting and exhibited water and lipid fractions that were consistent to within 5% of their original content when measured 2 weeks after creation. A breast-shaped three-compartment model of adipose, fibroglandular, and malignant tissues was created with water content ranging from 30% for the adipose simulant to 80% for the tumor. Mean measured water content ranged from 30% in simulated adipose to 73% in simulated tumor with the higher water localized to the tumor-like material. This novel heterogeneous phantom design is composed of physiologically relevant concentrations of the major optical absorbers in the breast in the near-infrared wavelengths that should significantly improve imaging system characterization and optimization because the materials have stand-alone structural integrity and can be readily molded into the sizes and shapes of tissues commensurate with clinical breast imaging.

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.