Optical mammography: Diffuse optical imaging of breast cancer

Enhanced full-inversion-based ultrasound elastography for evaluating tumor response to neoadjuvant chemotherapy in patients with locally advanced breast cancer

PURPOSE

An enhanced ultrasound elastography technique is proposed for early assessment of locally advanced breast cancer (LABC) response to neoadjuvant chemotherapy (NAC).

METHODS

The proposed elastography technique inputs ultrasound radiofrequency data obtained through tissue quasi-static stimulation and adapts a strain refinement algorithm formulated based on fundamental principles of continuum mechanics, coupled with an iterative inverse finite element method to reconstruct the breast Young's modulus (E) images. The technique was explored for therapy response assessment using data acquired from 25 LABC patients before and at weeks 1, 2, and 4 after the NAC initiation (100 scans). The E ratio of tumor to the surrounding tissue was calculated at different scans and compared to the baseline for each patient. Patients' response to NAC was determined many months later using standard clinical and histopathological criteria.

RESULTS

Reconstructed E ratio changes obtained as early as one week after the NAC onset demonstrate very good separation between the two cohorts of responders and non-responders to NAC. Statistically significant differences were observed in the E ratio changes between the two patient cohorts at weeks 1 to 4 after treatment (p-value < 0.001; statistical power greater than 97%). A significant difference in axial strain ratio changes was observed only at week 4 (p-value = 0.01; statistical power = 76%). No significant difference was observed in tumor size changes at weeks 1, 2 or 4.

CONCLUSION

The proposed elastography technique demonstrates a high potential for chemotherapy response monitoring in LABC patients and superior performance compared to strain imaging.

Design of a Low-Cost Diffuse Optical Mammography System for Biomedical Image Processing in Breast Cancer Diagnosis

Worldwide, breast cancer is the most common type of cancer that mainly affects women. Several diagnosis techniques based on optical instrumentation and image analysis have been developed, and these are commonly used in conjunction with conventional diagnostic devices such as mammographs, ultrasound, and magnetic resonance imaging of the breast. The cost of using these instruments is increasing, and developing countries, whose deaths indices due to breast cancer are high, cannot access conventional diagnostic methods and have even less access to newer techniques. Other studies, based on the analysis of images acquired by traditional methods, require high resolutions and knowledge of the origin of the captures in order to avoid errors. For this reason, the design of a low-cost diffuse optical mammography system for biomedical image processing in breast cancer diagnosis is presented. The system combines the acquisition of breast tissue photographs, diffuse optical reflectance (as a biophotonics technique), and the processing of digital images for the study and diagnosis of breast cancer. The system was developed in the form of a medical examination table with a 638 nm red-light source, using light-emitted diode technology (LED) and a low-cost web camera for the acquisition of breast tissue images. The system is automatic, and its control, through a graphical user interface (GUI), saves costs and allows for the subsequent analysis of images using a digital image-processing algorithm. The results obtained allow for the possibility of planning in vivo measurements. In addition, the acquisition of images every 30° around the breast tissue could be used in future research in order to perform a three-dimensional (3D) reconstruction and an analysis of the captures through deep learning techniques. These could be combined with virtual, augmented, or mixed reality environments to predict the position of tumors, increase the likelihood of a correct medical diagnosis, and develop a training system for specialists. Furthermore, the system allows for the possibility to develop analysis of optical characterization for new phantom studies in breast cancer diagnosis through bioimaging techniques.

Influence of Tumor Volume on the Fluence Rate Within Human Breast Model Using Continuous-Wave Diffuse Optical Imaging: A Simulation Study

Objective: This article investigates the effect of varying breast tumor size on the fluence rate distribution within a breast model during the diffuse optical imaging procedure. Background: Early detection of breast cancer is of significant importance owing to its wide spread among women worldwide. Mastectomy surgery became very common due to the late detection of breast cancers by the conventional diagnostic methods such as X-ray mammography and magnetic resonance imaging. On the contrary, optical imaging techniques provide a safe and more sensitive methodology, which is suitable for the early detection criteria. Methods: The implementation was performed based on simulating multiple detectors placed on the outer surface of a human breast model to compute the optical fluence rate after probing the breast (normal and different tumor sizes) with laser irradiation. Different laser wavelengths ranging from the red to near-infrared rays spectral range were examined to determine the optimum fluence rate that shows the highest capability to differentiate between normal and cancerous breasts. A three-dimensional breast model was created using the COMSOL multiphysics package where the optical fluence rate was estimated based on the finite-element solution of the diffusion equation. Results: To evaluate the efficiency of the suggested technique for identifying cancers and discriminate them from normal breast at various wavelengths (600-1000 nm) and several tumor sizes. Conclusions: The obtained results reveal different fluence rate distributions in the breast with different radius tumors, especially at 600 nm due to the significant differences in the scattering coefficient between malignancies and healthy tissue.

Unrolled-DOT: an interpretable deep network for diffuse optical tomography

SIGNIFICANCE

Imaging through scattering media is critical in many biomedical imaging applications, such as breast tumor detection and functional neuroimaging. Time-of-flight diffuse optical tomography (ToF-DOT) is one of the most promising methods for high-resolution imaging through scattering media. ToF-DOT and many traditional DOT methods require an image reconstruction algorithm. Unfortunately, this algorithm often requires long computational runtimes and may produce lower quality reconstructions in the presence of model mismatch or improper hyperparameter tuning.

AIM

We used a data-driven unrolled network as our ToF-DOT inverse solver. The unrolled network is faster than traditional inverse solvers and achieves higher reconstruction quality by accounting for model mismatch.

APPROACH

Our model "Unrolled-DOT" uses the learned iterative shrinkage thresholding algorithm. In addition, we incorporate a refinement U-Net and Visual Geometry Group (VGG) perceptual loss to further increase the reconstruction quality. We trained and tested our model on simulated and real-world data and benchmarked against physics-based and learning-based inverse solvers.

RESULTS

In experiments on real-world data, Unrolled-DOT outperformed learning-based algorithms and achieved over 10× reduction in runtime and mean-squared error, compared to traditional physics-based solvers.

CONCLUSION

We demonstrated a learning-based ToF-DOT inverse solver that achieves state-of-the-art performance in speed and reconstruction quality, which can aid in future applications for noninvasive biomedical imaging.

Non-Invasive Microwave-Based Imaging System for Early Detection of Breast Tumours

This work introduces a microwave-based system able to detect tumours in breast phantoms in a non-invasive way. The data acquisition system is composed of a hardware system which involves high-frequency components (antennas, switches and cables), a microcontroller, a vector network analyser used as measurement instrument and a computer devoted to the control and automation of the operation of the system. Concerning the software system, the computer runs a Python script which is in charge of mastering and automatising all the required stages for the data acquisition, from initialisation of the hardware system to performing and saving the measurements. We also report on the design of the high-performance broadband antenna used to carry out the measurements, as well as on the algorithm employed to build the final medical images, based on an adapted version of the so-called Improved Delay-and-Sum (IDAS) algorithm improved by a Hamming window filter and averaging preprocessing. The calibration and start-up of the system are also described. The experimental validation includes the use of different tumour models with different dielectric properties inside the breast phantom. The results show promising tumour detection capabilities, even when there is low dielectric contrast between the tumoural and healthy tissues, as is the usual case for dense breasts in young women.

A modified source-detector configuration for the discrimination between normal and diseased human breast based on the continuous-wave diffuse optical imaging approach: a simulation study

Breast tumors are among the most common types of tumors that can affect both genders. It may spread to the whole breast without any symptoms. Therefore, the early detection and accurate diagnosis of breast tumors are significantly important. Current approaches for breast cancer screening such as positron emission tomography (PET) and magnetic resonance imaging (MRI) have some limitations of being time and money-consuming. In addition, mammography screening is not recommended for women under forty. Consequently, optical techniques have been introduced as safe and functional alternatives. Diffuse optical imaging is a non-invasive imaging technique that utilizes near-infrared light to examine biological tissues based on measuring the optical transmission and/or reflection at various locations on the tissue surface. In this paper, we propose a modified arrangement between the laser source and the detectors for distinguishing tumors from normal breast tissue. A three-dimensional model of the normal human breast with three types of tumors is developed using a COMSOL simulation software based on the finite element solution of Helmholtz equation to estimate optical fluence distribution. The breast model consists of four layers: skin, fat, glandular, and muscle, where the tumor is included in the glandular layer. Different wavelengths were used to determine the most proper wavelength for the discrimination between the normal tissue and tumor. The obtained results were verified using the receiver operating characteristic (ROC) method. The resultant fluence images show different features between normal breast and breast with tumor especially using 600-nm incident laser as demonstrated by the obtained ROC curves.

Variations in tissue optical parameters with the incident power of an infrared laser

Infrared (IR) lasers are extensively utilized as an effective tool in many medical practices. Nevertheless, light penetration into the inspected tissue, which is highly affected by tissue optical properties, is a crucial factor for successful optical procedures. Although the optical properties are highly wavelength-dependent, they can be affected by the power of the incident laser. The present study demonstrates a considerable change in the scattering and absorption coefficients as a result of varying the incident laser power probing into biological samples at a constant laser wavelength (808 nm). The optical parameters were investigated using an integrating sphere and Kubelka-Munk model. Additionally, fluence distribution at the sample's surface was modeled using COMSOL-multiphysics software. The experimental results were validated using Receiver Operating Characteristic (ROC) curves and Monte-Carlo simulation. The results showed that tissue scattering coefficient decreases as the incident laser power increases while the absorption coefficient experienced a slight change. Moreover, the penetration depth increases with the optical parameters. The reduction in the scattering coefficients leads to wider and more diffusive fluence rate distribution at the tissue surface. The simulation results showed a good agreement with the experimental data and revealed that tissue anisotropy may be responsible for this scattering reduction. The present findings could be considered in order for the specialists to accurately specify the laser optical dose in various biomedical applications.

Hemoglobin state-flux: A finite-state model representation of the hemoglobin signal for evaluation of the resting state and the influence of disease

SUMMARY

In this report we introduce a weak-model approach for examination of the intrinsic time-varying properties of the hemoglobin signal, with the aim of advancing the application of functional near infrared spectroscopy (fNIRS) for the detection of breast cancer, among other potential uses. The developed methodology integrates concepts from stochastic network theory with known modulatory features of the vascular bed, and in doing so provides access to a previously unrecognized dense feature space that is shown to have promising diagnostic potential. Notable features of the methodology include access to this information solely from measures acquired in the resting state, and analysis of these by treating the various components of the hemoglobin (Hb) signal as a co-varying interacting system.

APPROACH

The principal data-transform kernel projects Hb state-space trajectories onto a coordinate system that constitutes a finite-state representation of covariations among the principal elements of the Hb signal (i.e., its oxygenated (ΔoxyHb) and deoxygenated (ΔdeoxyHb) forms and the associated dependent quantities: total hemoglobin (ΔtotalHb = ΔoxyHb + ΔdeoxyHb), hemoglobin oxygen saturation (ΔHbO2Sat = 100Δ(oxyHb/totalHb)), and tissue-hemoglobin oxygen exchange (ΔHbO2Exc = ΔdeoxyHb-ΔoxyHb)). The resulting ten-state representation treats the evolution of this signal as a one-space, spatiotemporal network that undergoes transitions from one state to another. States of the network are defined by the algebraic signs of the amplitudes of the time-varying components of the Hb signal relative to their temporal mean values. This assignment produces several classes of coefficient arrays, most with a dimension of 10×10.

BIOLOGICAL MOTIVATION

Motivating our approach is the understanding that effector mechanisms that modulate blood delivery to tissue operate on macroscopic scales, in a spatially and temporally varying manner. Also recognized is that this behavior is sensitive to nonlinear actions of these effectors, which include the binding properties of hemoglobin. Accessible phenomenology includes measures of the kinetics and probabilities of network dynamics, which we treat as surrogates for the actions of feedback mechanisms that modulate tissue-vascular coupling.

FINDINGS

Qualitative and quantitative features of this space, and their potential to serve as markers of disease, have been explored by examining continuous-wave fNIRS 3D tomographic time series obtained from the breasts of women who do and do not have breast cancer. Inspection of the coefficient arrays reveals that they are governed predominantly by first-order rate processes, and that each array class exhibits preferred structure that is mainly independent of the others. Discussed are strategies that may serve to extend evaluation of the accessible feature space and how the character of this information holds potential for development of novel clinical and preclinical uses.

Prediction of neoadjuvant chemotherapy response using diffuse optical spectroscopy in breast cancer

PURPOSE

Near-infrared diffuse optical spectroscopy (DOS) has been recently used to predict neoadjuvant chemotherapy response (NAC). In the present study, we explore the change in blood-oxygen content using DOS to predict NAC response against breast cancer.

MATERIALS AND METHODS

A total of 20 patients were enrolled and underwent DOS scan with blood-oxygen detection before each treatment cycle. The first DOS scan was performed before NAC treatment (pretreatment), and subsequent scans were performed after each NAC treatment circle. Changes in blood content and oxygen content by DOS were evaluated and compared with tumor size, and their changes were analyzed in response versus nonresponse group.

RESULTS

Thirteen patients were classified into response and seven patients into nonresponse group. The tumor blood content value (-1.06 ± 0.43) and oxygen content value (0.48 ± 0.17) of DOS at pretreatment was significantly different from presurgery in response group (P < 0.05), but not in nonresponse group. In response group, the percentage change in blood content (median 91.19%) was significantly larger than tumor size (median 48.89%) (P = 0.0035), while in oxygen content (median 47.11%) is not (P = 0.2815). Comparing each cycle, the percentage change in blood content could distinguish responder from non-responder as early as after the first treatment cycle (19.1 versus 6.6%, P = 0.0265). Blood content percentage sensitivity was 76.9% and specificity was 85.7% (AUC 0.912), while oxygen content percentage sensitivity was 76.9% and specificity was 71.4% (AUC 0.797).

CONCLUSION

Both blood and oxygen content measured by DOS could be used to discriminate responder to the treatment versus non-responder. Among the two, percentage change of blood content was more precise and earlier than that of oxygen content to predicted breast tumor response. The percentage change in blood content could distinguish responder from non-responder after the first treatment cycle.

Ultrasound-Guided Diffuse Optical Tomography for Differentiation of Benign and Malignant Breast Lesions: A Meta-analysis

OBJECTIVES

The purpose of this study was to assess the diagnostic performance of ultrasound-guided diffuse optical tomography for differentiation of benign and malignant breast lesions.

METHODS

The Cochrane Library, PubMed, and Embase databases were searched from inception to February 14, 2016. Sensitivity, specificity, and other information were extracted from the included studies. Sensitivity and specificity were pooled by a bivariate mixed-effects binary regression model. A summary receiver operating characteristic curve was constructed. Heterogeneity and publication bias were explored by Higgins and Deeks tests, respectively.

RESULTS

Seven studies including 768 women with 886 lesions were analyzed. The summary sensitivity, specificity, and diagnostic odds ratio were 95% (95% confidence interval [CI], 85%-98%), 77% (95% CI, 66%-85%), and 57 (95% CI, 12-267), respectively. The area under the summary receiver operating characteristic curve was 91% (95% CI, 89%-94%). No significant heterogeneity or publication bias existed.

CONCLUSIONS

Ultrasound-guided diffuse optical tomography is useful for differentiating breast lesions. Especially, its sensitivity is excellent.

Time-resolved subtraction method for measuring optical properties of turbid media

Near-infrared spectroscopy is a noninvasive optical method used primarily to monitor tissue oxygenation due to the absorption properties of hemoglobin. Accurate estimation of hemoglobin concentrations and other light absorbers requires techniques that can separate the effect of absorption from the much greater effect of light scattering. One of the most advanced methods is time-resolved near-infrared spectroscopy (TR-NIRS), which measures the absorption and scattering coefficients of a turbid medium by modeling the recorded distribution time of flight of photons. A challenge with TR-NIRS is that it requires accurate characterization of the dispersion caused by the system. In this study, we present a method for circumventing this problem by applying statistical moment analysis to two time-of-flight distributions measured at separated source-detector distances. Simulations based on analytical models and Monte Carlo code, and tissue-mimicking phantoms, were used to demonstrate its accuracy for source-detector distances typically used in neuroimaging applications. The simplicity of the approach is well suited to real-time applications requiring accurate quantification of the optical properties of a turbid medium.

Comparison of diffuse optical tomography, ultrasound elastography and mammography in the diagnosis of breast tumors

Previous studies have reported the usefulness of diffuse optical tomography (DOT), ultrasound elastography (UE) and mammography in differentiating breast tumors. This study was aimed at evaluating and comparing DOT, UE and mammography with respect to their diagnostic performance in differentiating benign and malignant breast tumors. Of the 67 tumors, 45 were histopathologically benign, and 22 were malignant. UE was the most specific (93.33%) of the three diagnostics modalities. DOT and UE were both more accurate (80.60% and 89.55%, respectively) than mammography (63.08%). UE + mammography (93.33% and 91.04%) and DOT + mammography (77.78% and 82.09%) exhibited higher specificity and accuracy, respectively, than mammography alone (57.78% and 63.08%). Receiver operating characteristic (ROC) curves were constructed to assess the performance of the modalities. In conclusion, UE and DOT were superior to conventional mammography in terms of both specificity and accuracy. DOT and UE improve the specificity and accuracy of breast cancer diagnosis, and combining the two modalities improves the diagnostic value.

Monitoring the response to primary medical therapy for breast cancer using three- dimensional time-resolved optical mammography

Primary medical therapy is used to reduce tumour size prior to surgery in women with locally advanced breast cancer. Optical tomography is a functional imaging technique using near- infrared light to produce three-dimensional breast images of tissue oxygen saturation and haemoglobin concentration. Its advantages include the ability to display quantitative physiological information, and to allow repeated scans without the hazards associated with exposure to ionising radiation. There is a need for a non-invasive functional imaging tool to evaluate response to treatment, so that non-responders can be given the opportunity to change their treatment regimen. Here, we evaluate the use of optical tomography for this purpose. Four women with newly diagnosed breast cancer who were about to undergo primary medical therapy gave informed and voluntary consent to take part in the study. Changes in physiological and optical properties within the tumour were evaluated during the course of neoadjuvant chemotherapy. Optical imaging was performed prior to treatment, after the first cycle of chemotherapy, halfway through, and on completion of chemotherapy. Images of light absorption and scatter at two wavelengths were produced, from which images of total haemoglobin concentration and oxygen saturation were derived. All patients that showed a good or complete response to treatment on MRI showed a corresponding recovery in the haemoglobin concentration images. Changes in mean tumour total haemoglobin concentration could be seen four weeks into treatment. The tumour oxygen saturation was low compared to background in three out of four patients, and also showed a return to baseline over treatment. Optical imaging of the breast is feasible during primary medical therapy and can be used to assess response to treatment over six months.

Imaging as a diagnostic and therapeutic tool in clinical oncology

According to the WHO report published in 2010, about 13% of all deaths are due to cancer. Of these, lung, liver, stomach, colon and breast cancer are the most prevalent. It was also reported that about 30% of the deaths due to cancer can be avoided, if diagnosed and treated early. Hence, there is an urgent need to diagnose these cancers efficiently. Various imaging and therapeutic methods have been proposed and used to accurately detect cancer. In this special two issues, there are eight papers covering different aspects of oncology using various imaging or therapeutic methods.