Noncontact diffuse correlation tomography of human breast tumor

A comprehensive overview of diffuse correlation spectroscopy: Theoretical framework, recent advances in hardware, analysis, and applications

Diffuse correlation spectroscopy (DCS) is a powerful tool for assessing microvascular hemodynamic in deep tissues. Recent advances in sensors, lasers, and deep learning have further boosted the development of new DCS methods. However, newcomers might feel overwhelmed, not only by the already-complex DCS theoretical framework but also by the broad range of component options and system architectures. To facilitate new entry to this exciting field, we present a comprehensive review of DCS hardware architectures (continuous-wave, frequency-domain, and time-domain) and summarize corresponding theoretical models. Further, we discuss new applications of highly integrated silicon single-photon avalanche diode (SPAD) sensors in DCS, compare SPADs with existing sensors, and review other components (lasers, sensors, and correlators), as well as data analysis tools, including deep learning. Potential applications in medical diagnosis are discussed and an outlook for the future directions is provided, to offer effective guidance to embark on DCS research.

Depth-sensitive diffuse speckle contrast topography for high-density mapping of cerebral blood flow in rodents

Significance

Frequent assessment of cerebral blood flow (CBF) is crucial for the diagnosis and management of cerebral vascular diseases. In contrast to large and expensive imaging modalities, such as nuclear medicine and magnetic resonance imaging, optical imaging techniques are portable and inexpensive tools for continuous measurements of cerebral hemodynamics. The recent development of an innovative noncontact speckle contrast diffuse correlation tomography (scDCT) enables three-dimensional (3D) imaging of CBF distributions. However, scDCT requires complex and time-consuming 3D reconstruction, which limits its ability to achieve high spatial resolution without sacrificing temporal resolution and computational efficiency.

Aim

We investigate a new diffuse speckle contrast topography (DSCT) method with parallel computation for analyzing scDCT data to achieve fast and high-density two-dimensional (2D) mapping of CBF distributions at different depths without the need for 3D reconstruction.

Approach

A new moving window method was adapted to improve the sampling rate of DSCT. A fast computation method utilizing MATLAB functions in the Image Processing Toolbox™ and Parallel Computing Toolbox™ was developed to rapidly generate high-density CBF maps. The new DSCT method was tested for spatial resolution and depth sensitivity in head-simulating layered phantoms and in-vivo rodent models.

Results

DSCT enables 2D mapping of the particle flow in the phantom at different depths through the top layer with varied thicknesses. Both DSCT and scDCT enable the detection of global and regional CBF changes in deep brains of adult rats. However, DSCT achieves fast and high-density 2D mapping of CBF distributions at different depths without the need for complex and time-consuming 3D reconstruction.

Conclusions

The depth-sensitive DSCT method has the potential to be used as a noninvasive, noncontact, fast, high resolution, portable, and inexpensive brain imager for basic neuroscience research in small animal models and for translational studies in human neonates.

Massively parallel, real-time multispeckle diffuse correlation spectroscopy using a 500 × 500 SPAD camera

Diffuse correlation spectroscopy (DCS) is a promising noninvasive technique for monitoring cerebral blood flow and measuring cortex functional activation tasks. Taking multiple parallel measurements has been shown to increase sensitivity, but is not easily scalable with discrete optical detectors. Here we show that with a large 500 × 500 SPAD array and an advanced FPGA design, we achieve an SNR gain of almost 500 over single-pixel mDCS performance. The system can also be reconfigured to sacrifice SNR to decrease correlation bin width, with 400 ns resolution being demonstrated over 8000 pixels.

Imaging Dynamics Beneath Turbid Media via Parallelized Single-Photon Detection

Noninvasive optical imaging through dynamic scattering media has numerous important biomedical applications but still remains a challenging task. While standard diffuse imaging methods measure optical absorption or fluorescent emission, it is also well-established that the temporal correlation of scattered coherent light diffuses through tissue much like optical intensity. Few works to date, however, have aimed to experimentally measure and process such temporal correlation data to demonstrate deep-tissue video reconstruction of decorrelation dynamics. In this work, a single-photon avalanche diode array camera is utilized to simultaneously monitor the temporal dynamics of speckle fluctuations at the single-photon level from 12 different phantom tissue surface locations delivered via a customized fiber bundle array. Then a deep neural network is applied to convert the acquired single-photon measurements into video of scattering dynamics beneath rapidly decorrelating tissue phantoms. The ability to reconstruct images of transient (0.1-0.4 s) dynamic events occurring up to 8 mm beneath a decorrelating tissue phantom with millimeter-scale resolution is demonstrated, and it is highlighted how the model can flexibly extend to monitor flow speed within buried phantom vessels.

Noninvasive hemoglobin sensing and imaging: optical tools for disease diagnosis

SIGNIFICANCE

Measurement and imaging of hemoglobin oxygenation are used extensively in the detection and diagnosis of disease; however, the applied instruments vary widely in their depth of imaging, spatiotemporal resolution, sensitivity, accuracy, complexity, physical size, and cost. The wide variation in available instrumentation can make it challenging for end users to select the appropriate tools for their application and to understand the relative limitations of different methods.

AIM

We aim to provide a systematic overview of the field of hemoglobin imaging and sensing.

APPROACH

We reviewed the sensing and imaging methods used to analyze hemoglobin oxygenation, including pulse oximetry, spectral reflectance imaging, diffuse optical imaging, spectroscopic optical coherence tomography, photoacoustic imaging, and diffuse correlation spectroscopy.

RESULTS

We compared and contrasted the ability of different methods to determine hemoglobin biomarkers such as oxygenation while considering factors that influence their practical application.

CONCLUSIONS

We highlight key limitations in the current state-of-the-art and make suggestions for routes to advance the clinical use and interpretation of hemoglobin oxygenation information.

Transient Motion Classification Through Turbid Volumes via Parallelized Single-Photon Detection and Deep Contrastive Embedding

Fast noninvasive probing of spatially varying decorrelating events, such as cerebral blood flow beneath the human skull, is an essential task in various scientific and clinical settings. One of the primary optical techniques used is diffuse correlation spectroscopy (DCS), whose classical implementation uses a single or few single-photon detectors, resulting in poor spatial localization accuracy and relatively low temporal resolution. Here, we propose a technique termed ClassifyingRapid decorrelationEvents viaParallelized single photon dEtection (CREPE), a new form of DCS that can probe and classify different decorrelating movements hidden underneath turbid volume with high sensitivity using parallelized speckle detection from a 32 × 32 pixel SPAD array. We evaluate our setup by classifying different spatiotemporal-decorrelating patterns hidden beneath a 5 mm tissue-like phantom made with rapidly decorrelating dynamic scattering media. Twelve multi-mode fibers are used to collect scattered light from different positions on the surface of the tissue phantom. To validate our setup, we generate perturbed decorrelation patterns by both a digital micromirror device (DMD) modulated at multi-kilo-hertz rates, as well as a vessel phantom containing flowing fluid. Along with a deep contrastive learning algorithm that outperforms classic unsupervised learning methods, we demonstrate our approach can accurately detect and classify different transient decorrelation events (happening in 0.1–0.4 s) underneath turbid scattering media, without any data labeling. This has the potential to be applied to non-invasively monitor deep tissue motion patterns, for example identifying normal or abnormal cerebral blood flow events, at multi-Hertz rates within a compact and static detection probe.

Speckle contrast diffuse correlation tomography of cerebral blood flow in perinatal disease model of neonatal piglets

We adapted and tested an innovative noncontact speckle contrast diffuse correlation tomography (scDCT) system for 3D imaging of cerebral blood flow (CBF) variations in perinatal disease models utilizing neonatal piglets, which closely resemble human neonates. CBF variations were concurrently measured by the scDCT and an established diffuse correlation spectroscopy (DCS) during global ischemia, intraventricular hemorrhage, and asphyxia; significant correlations were observed. Moreover, CBF variations associated reasonably with vital pathophysiological changes. In contrast to DCS measurements of mixed signals from local scalp, skull and brain, scDCT generates 3D images of CBF distributions at prescribed depths within the head, thus enabling specific determination of regional cerebral ischemia. With further optimization and validation in animals and human neonates, scDCT has the potential to be a noninvasive imaging tool for both basic neuroscience research in laboratories and clinical applications in neonatal intensive care units.

Collimating micro-lens fiber array for noncontact near-infrared diffuse correlation tomography

Near-infrared diffuse correlation spectroscopy/tomography (DCS/DCT) has recently emerged as a noninvasive measurement/imaging technology for tissue blood flow. In DCT studies, the high-dense collection of light temporal autocorrelation curves (g ₂(τ)) via fiber array are critical for image reconstruction of blood flow. Previously, the camera-based fiber array limits the field of view (FOV), precluding its applications on large-size human tissues. The line-shape fiber probe based on lens combination, which is predominantly used in current DCT studies, requires rotated-scanning over the surface of target tissue, substantially prolonging the measurement time and increasing the system instability. In this study, we design a noncontact optical probe for DCT based on collimating micro-lens fiber array, termed as FA-nc-DCT system. For each source/detector fiber, a single optical path was collimated by coupling with one micro-lens in the fiber array that is integrated in a square-shape base. Additionally, an 8×8 optical switch is used to share the hardware laser and detectors without spatial scanning. The FA-nc approach for the precise collection of g ₂(τ) curves was validated through a speed-varied phantom experiment and the human experiments of cuff occlusion, from which the expected value of the blood flow index (BFI) was obtained. Furthermore, the flow anomaly in the phantom and the ischemic muscle in human were accurately reconstructed from the FA-nc-DCT system, which is combined with the imaging framework based on the Nth-order linear algorithm that we recently created. Those outcomes demonstrated the great potential of FA-nc-DCT technology for fast and robust imaging of various diseases such as human breast cancers.

Longitudinal 3D Blood Flow Distribution Provided by Diffuse Correlation Tomography during Bone Healing in a Murine Fracture Model

Noninvasive monitoring of vascularization can potentially diagnose impaired bone healing earlier than current radiographic methods. In this study, a noncontact diffuse correlation tomography (DCT) technique was employed to measure longitudinal blood flow changes during bone healing in a murine femoral fracture model. The three-dimensional distribution of the relative blood flow was quantified from one day pre-fracture to 48 days post-fracture. For three mice, frequent DCT measurements were performed every other day for one week after fracture, and then weekly thereafter. A decrease in blood flow was observed in the bone fracture region at one day post-fracture, followed by a monotonic increase in blood flow beyond the pre-injury baseline until five to seven days post-fracture. For the remaining 12 mice, only weekly DCT measurements were performed. Data collected on a weekly basis show the blood flow for most mice was elevated above baseline during the first two post-fracture weeks, followed by a subsequent decrease. Torsional strength of the excised femurs was measured for all 15 mice after 7 weeks of healing. A metric based on the early blood flow changes shows a statistically significant difference between the high strength group and the low strength group.

Enhancement of diffuse correlation spectroscopy tissue blood flow measurement by acoustic radiation force

The current research on acousto-optic effects focuses on the interactions of acoustic waves with static optical properties rather than dynamic features such as tissue blood flow. Diffuse correlation spectroscopy (DCS) is an emerging technology capable of direct measurements of tissue blood flow by probing the movements of red blood cells (RBCs). In this article, we investigated the relations between the acoustic radiation force (ARF) and ultrasonic patterns by the finite element simulations. Based on the outcomes, we experimentally explored how the ultrasound-generated ARF enhance the DCS data as well as the blood flow measurements. The results yield the optimal pattern to generate ARF and elucidate the relations between the ultrasonic emission and flow elevations. The flow modality combing the DCS with ARF modulations, which was proposed in this study for the first time, would promote disease diagnosis and therapeutic assessment in the situation wherein the blood flow contrast between healthy and pathological tissues is insufficient.

High-density speckle contrast optical tomography of cerebral blood flow response to functional stimuli in the rodent brain

Noninvasive, three-dimensional, and longitudinal imaging of cerebral blood flow (CBF) in small animal models and ultimately in humans has implications for fundamental research and clinical applications. It enables the study of phenomena such as brain development and learning and the effects of pathologies, with a clear vision for translation to humans. Speckle contrast optical tomography (SCOT) is an emerging optical method that aims to achieve this goal by directly measuring three-dimensional blood flow maps in deep tissue with a relatively inexpensive and simple system. High-density SCOT is developed to follow CBF changes in response to somatosensory cortex stimulation. Measurements are carried out through the intact skull on the rat brain. SCOT is able to follow individual trials in each brain hemisphere, where signal averaging resulted in comparable, cortical images to those of functional magnetic resonance images in spatial extent, location, and depth. Sham stimuli are utilized to demonstrate that the observed response is indeed due to local changes in the brain induced by forepaw stimulation. In developing and demonstrating the method, algorithms and analysis methods are developed. The results pave the way for longitudinal, nondestructive imaging in preclinical rodent models that can readily be translated to the human brain.

Portable Near-Infrared Technologies and Devices for Noninvasive Assessment of Tissue Hemodynamics

Tissue hemodynamics, including the blood flow, oxygenation, and oxygen metabolism, are closely associated with many diseases. As one of the portable optical technologies to explore human physiology and assist in healthcare, near-infrared diffuse optical spectroscopy (NIRS) for tissue oxygenation measurement has been developed for four decades. In recent years, a dynamic NIRS technology, namely, diffuse correlation spectroscopy (DCS), has been emerging as a portable tool for tissue blood flow measurement. In this article, we briefly describe the basic principle and algorithms for static NIRS and dynamic NIRS (i.e., DCS). Then, we elaborate on the NIRS instrumentation, either commercially available or custom-made, as well as their applications to physiological studies and clinic. The extension of NIRS/DCS from spectroscopy to imaging was depicted, followed by introductions of advanced algorithms that were recently proposed. The future prospective of the NIRS/DCS and their feasibilities for routine utilization in hospital is finally discussed.

Approaches to denoise the diffuse optical signals for tissue blood flow measurement

Various diseases are relevant to the abnormal blood flow in tissue. Diffuse correlation spectroscopy (DCS) is an emerging technology to extract the blood flow index (BFI) from light electric field temporal autocorrelation data. To account for tissue heterogeneity and irregular geometry, we developed an innovative DCS algorithm (i.e., the Nth order linear algorithm, or simply the NL algorithm) previously, in which the DCS signals are fully utilized through iterative linear regressions. Under the framework of NL algorithm, the BFI to be extracted is significantly influenced by the linear regression approach adopted. In this study, three approaches were proposed and evaluated for performing the iterative linear regressions, in order to understand what are the appropriate regression methods for BFI estimation. The three methods are least-squared minimization (L₂ norm), least-absolute minimization (L₁ norm) and support vector regression (SVR), where L₂ norm is a conventional approach to perform linear regression. L₁ norm and SVR are the approaches newly introduced here to process the DCS data. Computer simulations and the autocorrelation data collected from liquid phantom and human tissues are utilized to evaluate the three approaches. The results show that the best performance is achieved by the SVR approach in extracting the BFI values, with an error rate of 2.23% at 3.0 cm source-detector separation. The L₁ norm method gives a medium error of 2.81%. In contrast, the L₂ norm method leads to the largest error (3.93%) in extracting the BFI values. The outcomes derived from this study will be very helpful for the tissue blood flow measurements, which is critical for translating the DCS technology to the clinic.

Temporal blood flow changes measured by diffuse correlation tomography predict murine femoral graft healing

Blood flow changes during bone graft healing have the potential to provide important information about graft success, as the nutrients, oxygen, circulating cells and growth factors essential for integration are delivered by blood. However, longitudinal monitoring of blood flow changes during graft healing has been a challenge due to limitations in current techniques. To this end, non-invasive diffuse correlation tomography (DCT) was investigated to enable longitudinal monitoring of three-dimensional blood flow changes in deep tissue. Specific to this study, longitudinal blood flow changes were utilized to predict healing outcomes of common interventions for massive bone defects using a common mouse femoral defect model. Weekly blood flow changes were non-invasively measured using a diffuse correlation tomography system for 9 weeks in three types of grafts: autografts (N = 7), allografts (N = 6) and tissue-engineered allografts (N = 6). Healing outcomes were quantified using an established torsion testing method 9 weeks after transplantation. Analysis of the spatial and temporal blood flow reveals that major differences among the three groups were captured in weeks 1-5 after graft transplantation. A multivariate model to predict maximum torque by relative blood flow changes over 5 weeks after graft transplantation was built using partial least squares regression. The results reveal lower bone strength correlates with greater cumulative blood flow over an extended period of time (i.e., 1-5 weeks). The current research demonstrates that DCT-measured blood flow changes after graft transplantation can be utilized to predict long-term healing outcomes in a mouse femoral graft model.

Nth-order linear algorithm for diffuse correlation tomography

The current approaches to imaging the tissue blood flow index (BFI) from diffuse correlation tomography (DCT) data are either an analytical solution or a finite element method, both of which are unable to simultaneously account for the tissue heterogeneity and fully utilize the DCT data. In this study, a new imaging concept for DCT, namely NL-DCT, was created by us in which the medical images are combined with light Monte Carlo simulation to provide geometrical and heterogeneous information in tissue. Moreover, the DCT data at multiple delay time are fully utilized via iterative linear regression. The unique merit of NL-DCT in utilizing the medical images as prior information, when combined with a split Bregman algorithm for total variation minimization (Bregman-TV), was validated on a realistic human head model. Computer simulation outcomes demonstrate the accuracy and robustness of NL-DCT in localizing and separating the flow anomalies as well as the capability to preserve edges of anomalies.

Noncontact 3-D Speckle Contrast Diffuse Correlation Tomography of Tissue Blood Flow Distribution

Recent advancements in near-infrared diffuse correlation techniques and instrumentation have opened the path for versatile deep tissue microvasculature blood flow imaging systems. Despite this progress there remains a need for a completely noncontact, noninvasive device with high translatability from small/testing (animal) to large/target (human) subjects with trivial application on both. Accordingly, we discuss our newly developed setup which meets this demand, termed noncontact speckle contrast diffuse correlation tomography (nc_scDCT). The nc_scDCT provides fast, continuous, portable, noninvasive, and inexpensive acquisition of 3-D tomographic deep (up to 10 mm) tissue blood flow distributions with straightforward design and customization. The features presented include a finite-element-method implementation for incorporating complex tissue boundaries, fully noncontact hardware for avoiding tissue compression and interactions, rapid data collection with a diffuse speckle contrast method, reflectance-based design promoting experimental translation, extensibility to related techniques, and robust adjustable source and detector patterns and density for high resolution measurement with flexible regions of interest enabling unique application-specific setups. Validation is shown in the detection and characterization of both high and low contrasts in flow relative to the background using tissue phantoms with a pump-connected tube (high) and phantom spheres (low). Furthermore, in vivo validation of extracting spatiotemporal 3-D blood flow distributions and hyperemic response during forearm cuff occlusion is demonstrated. Finally, the success of instrument feasibility in clinical use is examined through the intraoperative imaging of mastectomy skin flap.

A Novel Noncontact Diffuse Correlation Spectroscopy Device for Assessing Blood Flow in Mastectomy Skin Flaps: A Prospective Study in Patients Undergoing Prosthesis-Based Reconstruction

A new advanced technology, noncontact diffuse correlation spectroscopy, has been recently developed for the measurement of tissue blood flow through analyzing the motions of red blood cells in deep tissues. This technology is portable, inexpensive, and noninvasive, and can measure up to 1.5-cm tissue depth. In this prospective study, the authors aimed to explore the use of this novel device in the prediction of mastectomy skin flap necrosis. The noncontact diffuse correlation spectroscopy device was used to measure mastectomy skin flap flow in patients undergoing mastectomy and immediate implant-based breast reconstruction before and immediately after mastectomy, and after placement of the prosthesis. Patients were tracked for the development of complications, including skin necrosis and the need for further surgery. Nineteen patients were enrolled in the study. Four patients (21 percent) developed skin necrosis, one of which required additional surgery. The difference in relative blood flow levels immediately after mastectomy in patients with or without necrosis was statistically significant, with values of 0.27 ± 0.11 and 0.66 ± 0.22, respectively (p = 0.0005). Relative blood flow measurements immediately after mastectomy show a significant high accuracy in prediction of skin flap necrosis, with an area under the receiver operating characteristic curve of 0.95 (95 percent confidence interval, 0.81 to 1). The noncontact diffuse correlation spectroscopy device is a promising tool that provides objective information regarding mastectomy skin flap viability intraoperatively, allowing surgeons early identification of those compromised and ischemic flaps with the hope of potentially salvaging them.

CLINICAL QUESTION/LEVEL OF EVIDENCE

Diagnostic, IV.

Clinical applications of near-infrared diffuse correlation spectroscopy and tomography for tissue blood flow monitoring and imaging

OBJECTIVE

Blood flow is one such available observable promoting a wealth of physiological insight both individually and in combination with other metrics.

APPROACH

Near-infrared diffuse correlation spectroscopy (DCS) and, to a lesser extent, diffuse correlation tomography (DCT), have increasingly received interest over the past decade as noninvasive methods for tissue blood flow measurements and imaging. DCS/DCT offers several attractive features for tissue blood flow measurements/imaging such as noninvasiveness, portability, high temporal resolution, and relatively large penetration depth (up to several centimeters).

MAIN RESULTS

This review first introduces the basic principle and instrumentation of DCS/DCT, followed by presenting clinical application examples of DCS/DCT for the diagnosis and therapeutic monitoring of diseases in a variety of organs/tissues including brain, skeletal muscle, and tumor.

SIGNIFICANCE

Clinical study results demonstrate technical versatility of DCS/DCT in providing important information for disease diagnosis and intervention monitoring.

Non-invasive diffuse correlation tomography reveals spatial and temporal blood flow differences in murine bone grafting approaches

Longitudinal blood flow during murine bone graft healing was monitored non-invasively using diffuse correlation tomography. The system utilized spatially dense data from a scanning set-up, non-linear reconstruction, and micro-CT anatomical information. Weekly in vivo measurements were performed. Blood flow changes in autografts, which heal successfully, were localized to graft regions and consistent across mice. Poor healing allografts showed heterogeneous blood flow elevation and high inter-subject variabilities. Allografts with tissue-engineered periosteum showed responses intermediate to both autografts and allografts, consistent with healing observed. These findings suggest that spatiotemporal blood flow changes can be utilized to differentiate the degree of bone graft healing.

Scanning, non-contact, hybrid broadband diffuse optical spectroscopy and diffuse correlation spectroscopy system

A scanning system for small animal imaging using non-contact, hybrid broadband diffuse optical spectroscopy (ncDOS) and diffuse correlation spectroscopy (ncDCS) is presented. The ncDOS uses a two-dimensional spectrophotometer retrieving broadband (610-900 nm) spectral information from up to fifty-seven source-detector distances between 2 and 5 mm. The ncDCS data is simultaneously acquired from four source-detector pairs. The sample is scanned in two dimensions while tracking variations in height. The system has been validated with liquid phantoms, demonstrated in vivo on a human fingertip during an arm cuff occlusion and on a group of mice with xenoimplanted renal cell carcinoma.

Non-Invasive Monitoring of Temporal and Spatial Blood Flow during Bone Graft Healing Using Diffuse Correlation Spectroscopy

Vascular infiltration and associated alterations in microvascular blood flow are critical for complete bone graft healing. Therefore, real-time, longitudinal measurement of blood flow has the potential to successfully predict graft healing outcomes. Herein, we non-invasively measure longitudinal blood flow changes in bone autografts and allografts using diffuse correlation spectroscopy in a murine femoral segmental defect model. Blood flow was measured at several positions proximal and distal to the graft site before implantation and every week post-implantation for a total of 9 weeks (autograft n = 7 and allograft n = 10). Measurements of the ipsilateral leg with the graft were compared with those of the intact contralateral control leg. Both autografts and allografts exhibited an initial increase in blood flow followed by a gradual return to baseline levels. Blood flow elevation lasted up to 2 weeks in autografts, but this duration varied from 2 to 6 weeks in allografts depending on the spatial location of the measurement. Intact contralateral control leg blood flow remained at baseline levels throughout the 9 weeks in the autograft group; however, in the allograft group, blood flow followed a similar trend to the graft leg. Blood flow difference between the graft and contralateral legs (ΔrBF), a parameter defined to estimate graft-specific changes, was elevated at 1–2 weeks for the autograft group, and at 2–4 weeks for the allograft group at the proximal and the central locations. However, distal to the graft, the allograft group exhibited significantly greater ΔrBF than the autograft group at 3 weeks post-surgery (p < 0.05). These spatial and temporal differences in blood flow supports established trends of delayed healing in allografts versus autografts.

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.