Mapping breast tissue types by miniature radio-frequency near-field spectroscopy sensor in ex-vivo freshly excised specimens

Multispectral Imaging of Intrinsic Metabolic Fluorophores: Detection of Human Breast Cancer in Fresh Ex Vivo Specimens

A growing number of women develop breast cancer and require surgery. Many lumpectomies lead to follow-up procedures after the initial surgery. Advanced scanning technologies have reduced the number of second and third surgeries, but only by about 50%. This paper assesses the potential of using multispectral images of intrinsic fluorescence to detect breast cancer. Images and spectra of intrinsic fluorescence from fresh ex vivo human specimens are related to pathological analysis, and predict high sensitivity and specificity. A design for a hand-held surgical scanning tool is presented.

The distinguishing electrical properties of cancer cells

In recent decades, medical research has been primarily focused on the inherited aspect of cancers, despite the reality that only 5-10% of tumours discovered are derived from genetic causes. Cancer is a broad term, and therefore it is inaccurate to address it as a purely genetic disease. Understanding cancer cells' behaviour is the first step in countering them. Behind the scenes, there is a complicated network of environmental factors, DNA errors, metabolic shifts, and electrostatic alterations that build over time and lead to the illness's development. This latter aspect has been analyzed in previous studies, but how the different electrical changes integrate and affect each other is rarely examined. Every cell in the human body possesses electrical properties that are essential for proper behaviour both within and outside of the cell itself. It is not yet clear whether these changes correlate with cell mutation in cancer cells, or only with their subsequent development. Either way, these aspects merit further investigation, especially with regards to their causes and consequences. Trying to block changes at various levels of occurrence or assisting in their prevention could be the key to stopping cells from becoming cancerous. Therefore, a comprehensive understanding of the current knowledge regarding the electrical landscape of cells is much needed. We review four essential electrical characteristics of cells, providing a deep understanding of the electrostatic changes in cancer cells compared to their normal counterparts. In particular, we provide an overview of intracellular and extracellular pH modifications, differences in ionic concentrations in the cytoplasm, transmembrane potential variations, and changes within mitochondria. New therapies targeting or exploiting the electrical properties of cells are developed and tested every year, such as pH-dependent carriers and tumour-treating fields. A brief section regarding the state-of-the-art of these therapies can be found at the end of this review. Finally, we highlight how these alterations integrate and potentially yield indications of cells' malignancy or metastatic index.

Three-Dimensional Microwave Head Imaging with GPU-Based FDTD and the DBIM Method

We present a preliminary study of microwave head imaging using a three-dimensional (3-D) implementation of the distorted Born iterative method (DBIM). Our aim is to examine the benefits of using the more computationally intensive 3-D implementation in scenarios where limited prior information is available, or when the target occupies an area that is not covered by the imaging array’s transverse planes. We show that, in some cases, the 3-D implementation outperforms its two-dimensional (2-D) counterpart despite the increased number of unknowns for the linear problem at each DBIM iteration. We also discuss how the 3-D algorithm can be implemented efficiently using graphic processing units (GPUs) and validate this implementation with experimental data from a simplified brain phantom. In this work, we have implemented a non-linear microwave imaging approach using DBIM with GPU-accelerated FDTD. Moreover, the paper offers a direct comparison of 2-D and 3-D microwave tomography implementations for head imaging and stroke detection in inhomogenous anatomically complex numerical head phantoms.

Characterising acute ischaemic stroke thrombi: insights from histology, imaging and emerging impedance-based technologies

Treatment of acute ischaemic stroke (AIS) focuses on rapid recanalisation of the occluded artery. In recent years, advent of mechanical thrombectomy devices and new procedures have accelerated the analysis of thrombi retrieved during the endovascular thrombectomy procedure. Despite ongoing developments and progress in AIS imaging techniques, it is not yet possible to conclude definitively regarding thrombus characteristics that could advise on the probable efficacy of thrombolysis or thrombectomy in advance of treatment. Intraprocedural devices with dignostic capabilities or new clinical imaging approaches are needed for better treatment of AIS patients. In this review, what is known about the composition of the thrombi that cause strokes and the evidence that thrombus composition has an impact on success of acute stroke treatment has been examined. This review also discusses the evidence that AIS thrombus composition varies with aetiology, questioning if suspected aetiology could be a useful indicator to stroke physicians to help decide the best acute course of treatment. Furthermore, this review discusses the evidence that current widely used radiological imaging tools can predict thrombus composition. Further use of new emerging technologies based on bioimpedance, as imaging modalities for diagnosing AIS and new medical device tools for detecting thrombus composition in situ has been introduced. Whether bioimpedance would be beneficial for gaining new insights into in situ thrombus composition that could guide choice of optimum treatment approach is also reviewed.

Low-Field NMR Relaxometry for Intraoperative Tumour Margin Assessment in Breast-Conserving Surgery

Simple Summary

Breast cancer is the most diagnosed cancer for women, and clear surgical margins in breast-conserving surgery (BCS) are essential for preventing recurrence. In this study, the potential of fast field-cycling ¹H-NMR relaxometry as a new tool for intraoperative margin assessment was evaluated. The technique allows the determination of the tissue proton relaxation rates as a function of the applied magnetic field on small tissue samples excised from surgical specimens, at the margins of tumour resection, prior to histopathological analysis. It was found that a good accuracy in margin assessment, i.e., a sensitivity of 92% and a specificity of 85%, can be achieved. The discriminating ability shown by the relaxometric assay relies mainly on the difference of fat/water content between healthy and tumour cells. The information obtained has the potential to support the surgeon in real-time margin assessment during BCS.

Abstract

As conserving surgery is routinely applied for the treatment of early-stage breast cancer, the need for new technology to improve intraoperative margin assessment has become increasingly important. In this study, the potential of fast field-cycling ¹H-NMR relaxometry as a new diagnostic tool was evaluated. The technique allows the determination of the tissue proton relaxation rates (R₁), as a function of the applied magnetic field, which are affected by the changes in the composition of the mammary gland tissue occurring during the development of neoplasia. The study involved 104 small tissue samples obtained from surgical specimens destined for histopathology. It was found that a good accuracy in margin assessment, i.e., a sensitivity of 92% and a specificity of 85%, can be achieved by using two quantifiers, namely (i) the slope of the line joining the R₁ values measured at 0.02 and 1 MHz and (ii) the sum of the R₁ values measured at 0.39 and 1 MHz. The method is fast, and it does not rely on the expertise of a pathologist or cytologist. The obtained results suggest that a simplified, low-cost, automated instrument might compete well with the currently available tools in margin assessment.

Discrete Dipole Approximation-Based Microwave Tomography for Fast Breast Cancer Imaging

This paper describes a fast microwave tomography reconstruction algorithm based on the two-dimensional discrete dipole approximation. Synthetic data from a finite-element based solver and experimental data from a microwave imaging system are used to reconstruct images and to validate the algorithm. The microwave measurement system consists of 16 monopole antennas immersed in a tank filled with lossy coupling liquid and a vector network analyzer. The low-profile antennas and lossy nature of system make the discrete dipole approximation an ideal forward solver in the image reconstructions. The results show that the algorithm can readily reconstruct a 2D plane of a cylindrical phantom. The proposed forward solver combined with the nodal adjoint method for computing the Jacobian matrix enables the algorithm to reconstruct an image within 6 seconds. This implementation provides a significant time savings and reduced memory requirements and is a dramatic improvement over previous implementations.

Expansion of the Nodal-Adjoint Method for Simple and Efficient Computation of the 2D Tomographic Imaging Jacobian Matrix

This paper focuses on the construction of the Jacobian matrix required in tomographic reconstruction algorithms. In microwave tomography, computing the forward solutions during the iterative reconstruction process impacts the accuracy and computational efficiency. Towards this end, we have applied the discrete dipole approximation for the forward solutions with significant time savings. However, while we have discovered that the imaging problem configuration can dramatically impact the computation time required for the forward solver, it can be equally beneficial in constructing the Jacobian matrix calculated in iterative image reconstruction algorithms. Key to this implementation, we propose to use the same simulation grid for both the forward and imaging domain discretizations for the discrete dipole approximation solutions and report in detail the theoretical aspects for this localization. In this way, the computational cost of the nodal adjoint method decreases by several orders of magnitude. Our investigations show that this expansion is a significant enhancement compared to previous implementations and results in a rapid calculation of the Jacobian matrix with a high level of accuracy. The discrete dipole approximation and the newly efficient Jacobian matrices are effectively implemented to produce quantitative images of the simplified breast phantom from the microwave imaging system.

Structured light imaging for breast-conserving surgery, part II: texture analysis and classification

Subdiffuse spatial frequency domain imaging (sd-SFDI) data of 42 freshly excised, bread-loafed tumor resections from breast-conserving surgery (BCS) were evaluated using texture analysis and a machine learning framework for tissue classification. Resections contained 56 regions of interest (RoIs) determined by expert histopathological analysis. RoIs were coregistered with sd-SFDI data and sampled into ∼4  ×  4  mm2 subimage samples of confirmed and homogeneous histological categories. Sd-SFDI reflectance textures were analyzed using gray-level co-occurrence matrix pixel statistics, image primitives, and power spectral density curve parameters. Texture metrics exhibited statistical significance (p-value  <  0.05) between three benign and three malignant tissue subtypes. Pairs of benign and malignant subtypes underwent texture-based, binary classification with correlation-based feature selection. Classification performance was evaluated using fivefold cross-validation and feature grid searching. Classification using subdiffuse, monochromatic reflectance (illumination spatial frequency of fx  =  1.37  mm  −  1, optical wavelength of λ  =  490  nm) achieved accuracies ranging from 0.55 (95% CI: 0.41 to 0.69) to 0.95 (95% CI: 0.90 to 1.00) depending on the benign–malignant diagnosis pair. Texture analysis of sd-SFDI data maintains the spatial context within images, is free of light transport model assumptions, and may provide an alternative, computationally efficient approach for wide field-of-view (cm2) BCS tumor margin assessment relative to pixel-based optical scatter or color properties alone.

Application of Two-Dimensional Discrete Dipole Approximation in Simulating Electric Field of a Microwave Breast Imaging System

The two-dimensional electric field distribution of the microwave imaging system is numerically simulated for a simplified breast tumour model. The proposed two-dimensional discrete dipole approximation (DDA) has the potential to improve computational speed compared to other numerical methods while retaining comparable accuracy. We have modeled the field distributions in COMSOL Multiphysics as baseline results to benchmark the DDA simulations. We have also investigated the adequate sampling size and the effect of inclusion size and property contrast on solution accuracy. In this way, we can utilize the 2D DDA as an alternative, fast and reliable forward solver for microwave tomography. From a mathematical perspective, the derivation of the 2D DDA and its application to microwave imaging is new and not previously implemented. The simulation results and the measurements show that the 2D DDA is a well-grounded forward solver for the specified microwave breast imaging system.

Towards mm-wave spectroscopy for dielectric characterization of breast surgical margins

PURPOSE

The evaluation of the surgical margin in breast conservative surgery is a matter of general interest as such treatments are subject to the critical issue of margin status as positive surgical margins can undermine the effectiveness of the procedure. The relatively unexplored ability of millimeter-wave (mm-wave) spectroscopy to provide insight into the dielectric properties of breast tissues was investigated as a precursor to their possible use in assessment of surgical margins.

METHODS

We assessed the ability of a mm-wave system with a roughly hemispherical sensitive volume of ∼3 mm radius to distinguish malignant breast lesions in prospectively and consecutively collected tumoral and non-tumoral ex-vivo breast tissue samples from 91 patients. We characterized the dielectric properties of 346 sites in these samples, encompassing malignant, fibrocystic disease and normal breast tissues. An expert pathologist subsequently evaluated all measurement sites.

RESULTS

At multivariate analysis, mm-wave dielectric properties were significantly correlated to histologic diagnosis and fat content. Further, using 5-fold cross-validation in a Bayesian logistic mixed model that considered the patient as a random effect, the mm-wave dielectric properties of neoplastic tissues were significantly different from normal breast tissues, but not from fibrocystic tissue.

CONCLUSION

Reliable discrimination of malignant from normal, fat-rich breast tissue to a depth compatible with surgical margin assessment requirements was achieved with mm-wave spectroscopy.

Dielectric properties for non-invasive detection of normal, benign, and malignant breast tissues using microwave theories

Background

Despite the high incidence of breast cancer worldwide, methods for early non‐invasive diagnosis and sensitive and specific prognostic evaluation remain difficult. In this study, we investigated microwave parameters as a potential non‐invasive approach to detect breast cancer.

Methods

Samples of freshly excised breast tissues (n = 509) from 98 patients were identified as normal, benign tumor, or malignant cancer via histology. Further samples were prepared and the microwave effective dielectric permittivity and effective conductivity were measured every 0.0375 GHz from 0.5 GHz to 8 GHz. These parameters were compared among the breast tissue types.

Results

The effective relative permittivity and effective conductivity at each frequency was significantly higher in breast cancer tissues compared with benign tumors, which in turn was significantly higher than in normal breast tissue. The standard deviation of each parameter was narrowest at ~2.5 GHz in both normal and malignant breast tissues.

Conclusions

The effective dielectric permittivity and effective conductivity, measured via microwave technology, could differentiate breast cancer from normal and benign tumor tissues.

Calibration and analysis of a multimodal micro-CT and structured light imaging system for the evaluation of excised breast tissue

A multimodal micro-computed tomography (CT) and multi-spectral structured light imaging (SLI) system is introduced and systematically analyzed to test its feasibility to aid in margin delineation during breast conserving surgery (BCS). Phantom analysis of the micro-CT yielded a signal-to-noise ratio of 34, a contrast of 1.64, and a minimum detectable resolution of 240 μm for a 1.2 min scan. The SLI system, spanning wavelengths 490 nm to 800 nm and spatial frequencies up to 1.37 [Formula: see text], was evaluated with aqueous tissue simulating phantoms having variations in particle size distribution, scatter density, and blood volume fraction. The reduced scattering coefficient, [Formula: see text] and phase function parameter, γ, were accurately recovered over all wavelengths independent of blood volume fractions from 0% to 4%, assuming a flat sample geometry perpendicular to the imaging plane. The resolution of the optical system was tested with a step phantom, from which the modulation transfer function was calculated yielding a maximum resolution of 3.78 cycles per mm. The three dimensional spatial co-registration between the CT and optical imaging space was tested and shown to be accurate within 0.7 mm. A freshly resected breast specimen, with lobular carcinoma, fibrocystic disease, and adipose, was imaged with the system. The micro-CT provided visualization of the tumor mass and its spiculations, and SLI yielded superficial quantification of light scattering parameters for the malignant and benign tissue types. These results appear to be the first demonstration of SLI combined with standard medical tomography for imaging excised tumor specimens. While further investigations are needed to determine and test the spectral, spatial, and CT features required to classify tissue, this study demonstrates the ability of multimodal CT/SLI to quantify, visualize, and spatially navigate breast tumor specimens, which could potentially aid in the assessment of tumor margin status during BCS.