Neil R. Epstein

Microwave imaging for neoadjuvant chemotherapy monitoring: initial clinical experience

IntroductionMicrowave tomography recovers images of tissue dielectric properties, which appear to be specific for breast cancer, with low-cost technology that does not present an exposure risk, suggesting the modality may be a good candidate for monitoring neoadjuvant chemotherapy.MethodsEight patients undergoing neoadjuvant chemotherapy for locally advanced breast cancer were imaged longitudinally five to eight times during the course of treatment. At the start of therapy, regions of interest (ROIs) were identified from contrast-enhanced magnetic resonance imaging studies. During subsequent microwave examinations, subjects were positioned with their breasts pendant in a coupling fluid and surrounded by an immersed antenna array. Microwave property values were extracted from the ROIs through an automated procedure and statistical analyses were performed to assess short term (30 days) and longer term (four to six months) dielectric property changes.ResultsTwo patient cases (one complete and one partial response) are presented in detail and demonstrate changes in microwave properties commensurate with the degree of treatment response observed pathologically. Normalized mean conductivity in ROIs from patients with complete pathological responses was significantly different from that of partial responders (P value = 0.004). In addition, the normalized conductivity measure also correlated well with complete pathological response at 30 days (P value = 0.002).ConclusionsThese preliminary findings suggest that both early and late conductivity property changes correlate well with overall treatment response to neoadjuvant therapy in locally advanced breast cancer. This result is consistent with earlier clinical outcomes that lesion conductivity is specific to differentiating breast cancer from benign lesions and normal tissue.

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.

Surface wave multipath signals in near-field microwave imaging

Microwave imaging techniques are prone to signal corruption from unwanted multipath signals. Near-field systems are especially vulnerable because signals can scatter and reflect from structural objects within or on the boundary of the imaging zone. These issues are further exacerbated when surface waves are generated with the potential of propagating along the transmitting and receiving antenna feed lines and other low-loss paths. In this paper, we analyze the contributions of multi-path signals arising from surface wave effects. Specifically, experiments were conducted with a near-field microwave imaging array positioned at variable heights from the floor of a coupling fluid tank. Antenna arrays with different feed line lengths in the fluid were also evaluated. The results show that surface waves corrupt the received signals over the longest transmission distances across the measurement array. However, the surface wave effects can be eliminated provided the feed line lengths are sufficiently long independently of the distance of the transmitting/receiving antenna tips from the imaging tank floor. Theoretical predictions confirm the experimental observations.

Microwave imaging for breast cancer detection: Advances in three — Dimensional image reconstruction

Microwave imaging is based on the electrical property (permittivity and conductivity) differences in materials. Microwave imaging for biomedical applications is particularly interesting, mainly due to the fact that available range of dielectric properties for different tissues can provide important functional information about their health. Under the assumption that a 3D scattering problem can be reasonably represented as a simplified 2D model, one can take advantage of the simplicity and lower computational cost of 2D models to characterize such 3D phenomenon. Nonetheless, by eliminating excessive model simplifications, 3D microwave imaging provides potentially more valuable information over 2D techniques, and as a result, more accurate dielectric property maps may be obtained. In this paper, we present some advances we have made in three-dimensional image reconstruction, and show the results from a 3D breast phantom experiment using our clinical microwave imaging system at Dartmouth Hitchcock Medical Center (DHMC), NH.

Microwave dielectric contrast imaging in a magnetic resonant environment and the effect of using magnetic resonant spatial information in image reconstruction

Microwave Tomography (MT) can determine the permittivity and conductivity of a volume of interest; it has been shown that a contrast exists between these electrical properties in healthy and malignant tissues, and MT can be used to discern the dielectric contrast image of these tissues by recovering their electrical property values. Simulation and phantom experiments of objects with known spatial locations have shown that using boundary information derived from internal structures in the imaged volume greatly increases the accuracy of the recovered property values. In practice this spatial information, which will be used for reconstructing the tissues electrical property images, must be determined with high enough resolution to segment boundary regions and internal structures of interest. This experiment investigates the use of Magnetic Resonant Imaging (MRI) in obtaining the desired spatial information used in mesh generation for image reconstruction and provides microwave image results comparing electrical properties recovered with and without this prior spatial information.

Three-dimensional Microwave Imaging with Incorporated Prior Structural Information

Microwave imaging for biomedical applications, especially for early detection of breast cancer and effective treatment monitoring, has attracted increasing interest in last several decades. This fact is due to the high contrast between the dielectric properties of the normal and malignant breast tissues at microwave frequencies. The available range of dielectric properties for different soft tissue can provide important functional information about tissue health. Nonetheless, one of the limiting weaknesses of microwave imaging is that unlike conventional modalities, such as X-ray CT or MRI, it inherently cannot provide high-resolution images. The conventional modalities can produce highly resolved anatomical information but often cannot provide the functional information required for diagnoses. Previously, we have developed a regularization strategy that can incorporate prior anatomical information from MR or other sources and use it in a way to refine the resolution of the microwave images, while also retaining the functional nature of the reconstructed property values. In the present work, we extend the use of prior structural information in microwave imaging from 2D to 3D. This extra dimension adds a significant layer of complexity to the entire image reconstruction procedure. In this paper, several challenges with respect to the 3D microwave imaging will be discussed and the results of a series of 3D simulation and phantom experiments with prior structural information will be studied.

MR-guided conformal microwave imaging for enhanced inclusion detection within irregularly shaped volumes

Approximately 1 in 8 women will develop breast cancer in their lifetime. Estimates suggest 230,500 new cases of invasive breast cancer in 2011, resulting in approximately 40,000 deaths. Traditional screening technologies, such as X-ray mammography use ionizing radiation and suffer from high false-positive and false-negative rates. Due to the high contrast that exists between the dielectric properties of normal and abnormal breast tissue, microwave-imaging spectroscopy has proven an attractive breast cancer imaging modality. We have shown that the incorporation of a volume’s internal structural information into our image reconstruction algorithm can increase the accuracy of recovered dielectric properties. Additionally, image reconstruction has benefited from the use of a custom reconstruction mesh generated from the imaged volume’s perimeter boundary. This information is used in a conformal microwave image (CMI) reconstruction process, and has increased the accuracy of recovered high contrast regions within the volume’s perimeter without the use of prior internal spatial information. In simulation and phantom experiments with regular geometries, boundary information is obtained through spatial measurements. For irregularly shaped boundaries, alternative means are necessary for accurate boundary extraction. In this paper we demonstrate the MR-guided CMI reconstruction process for an irregularly shaped boundary; boundary information extracted from MR images will be used to generate a custom boundary-derived mesh for microwave image reconstruction. Results from images reconstructed using the MR-guided CMI reconstruction process will be compared with uniformly reconstructed images, highlighting the increased accuracy of high contrast features within the volume without the use of prior internal spatial information.

Spectral imaging for complex clinical breast structures

We have imaged several breast cancer patients at multiple intervals during her neoadjuvant chemotherapy to assess the capability of microwave tomography as a therapy monitoring device. For the patient discussed here, we illustrate the spectral behavior of our tomographic approach in the context of a complex imaging situation with a large scattering tumor along with less frequently encountered structures such as thickened skin in the tumor vicinity. These results demonstrate that the microwave technology is sensitive to dielectric property perturbations associated with treatment-induced physiological changes. In addition, it also confirms previously hypothesized notions that the lower frequency images provide lower resolution but useful counterparts to the enhanced resolution, higher frequency images. This spectral data can be instructive for both UWB radar approaches and multi-frequency or time-domain tomographic approaches. The chemotherapy patients are unique with respect to breast cancer imaging cases in that they usually involve electrically large tumors along with other non-standard features such as extra-thick skin (easily as thick as 1 cm). These large, high contrast features are quite challenging for all types of microwave imaging (radar and tomography-based) and form an important benchmark for testing imaging techniques. For our efforts, we have developed a log transformation as part of the image reconstruction process which we have shown to have superior convergence behavior (i.e. no local minima) while retaining phase wrapping information that is generally lost when only considering more classical minimization criteria. As we will show, this technique requires broadband scattering data which we provide from measurements using our ultrawideband monopole antennas.

Parameter scaling in non-linear microwave tomography

Non-linear microwave tomographic imaging of the breast is a challenging computational problem. The breast is heterogeneous and contains several high-contrast and lossy regions, resulting in large differences in the measured signal levels. This implies that special care must be taken when the imaging problem is formulated. Under such conditions, microwave imaging systems will most often be considerably more sensitive to changes in the electromagnetic properties in certain regions of the breast. The result is that the parameters might not be reconstructed correctly in the less sensitive regions. In this paper, a method for obtaining a more uniform sensitivity throughout the breast is investigated. The method for obtaining uniform sensitivity throughout the imaging domain is a scaling of the parameters to be reconstructed. This scaling, based on the norms of the columns of the Jacobian, is also introduced as a measure of the sensitivity. The scaling of the parameters is shown to improve performance of the microwave imaging system when applied to reconstruction of images from 2-D simulated data and measurement data.

Noninvasive bulk dielectric testing

The complex dielectric properties can be quite unique for different substances. Non-invasive microwave imaging which recovers the associated properties of commercial products could prove useful in numerous settings such as assessing the integrity of solids and testing for spoilage of food stuffs. We have adapted our microwave breast imaging system for testing arbitrarily shaped targets with varying properties. This exploits a new soft prior regularization strategy which only requires spatial geometry information along with the measured field data to reconstruct accurate property measurements of the target under test (TUT). Refining the target interface and optimizing the reconstruction code for this specific application could facilitate near real-time assessment for a range of targets.