Amir H. Golnabi

Clinical Microwave Tomographic Imaging of the Calcaneus: A First-in-Human Case Study of Two Subjects

We have acquired 2-D and 3-D microwave tomographic images of the calcaneus bones of two patients to assess correlation of the microwave properties with X-ray density measures. The two volunteers were selected because each had one leg immobilized for at least six weeks during recovery from a lower leg injury. A soft-prior regularization technique was incorporated with the microwave imaging to quantitatively assess the bulk dielectric properties within the bone region. Good correlation was observed between both permittivity and conductivity and the computed tomography-derived density measures. These results represent the first clinical examples of microwave images of the calcaneus and some of the first 3-D tomographic images of any anatomical site in the living human.

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.

Tomographic Microwave Imaging With Incorporated Prior Spatial Information

We have implemented a soft prior regularization technique for microwave tomographic imaging that exploits spatial prior information from alternative imaging modalities. We have previously demonstrated in both simulation and phantom experiments that this approach is capable of improved property recovery compared with our conventional Tikhonov regularized method. An important concern with this type of integration is that the spatial information could be implemented in such a way as to overly influence or even bias the final results. For this reason, we have performed a rigorous quantitative analysis of this approach using both simulation and phantom experiments to investigate the sensitivity to inaccurate or even false spatial information. The majority of cases tested here involved simple targets to easily assess problems when the prior shapes are incorrect with respect to size and location or even when there is an extra target that does not exist in the actual imaging situation. In addition, we have also performed a simulated experiment utilizing anthropomorphic breast structural information to explore the capabilities in more challenging situations. The results are encouraging and demonstrate that the soft prior regularization can be a powerful tool, especially where the goal is specificity instead of sensitivity.

Bone dielectric property variation as a function of mineralization at microwave frequencies

A critical need exists for new imaging tools to more accurately characterize bone quality beyond the conventional modalities of dual energy X-ray absorptiometry (DXA), ultrasound speed of sound, and broadband attenuation measurements. In this paper we investigate the microwave dielectric properties of ex vivo trabecular bone with respect to bulk density measures. We exploit a variation in our tomographic imaging system in conjunction with a new soft prior regularization scheme that allows us to accurately recover the dielectric properties of small, regularly shaped and previously spatially defined volumes. We studied six excised porcine bone samples from which we extracted cylindrically shaped trabecular specimens from the femoral heads and carefully demarrowed each preparation. The samples were subsequently treated in an acid bath to incrementally remove volumes of hydroxyapatite, and we tested them with both the microwave measurement system and a micro-CT scanner. The measurements were performed at five density levels for each sample. The results show a strong correlation between both the permittivity and conductivity and bone volume fraction and suggest that microwave imaging may be a good candidate for evaluating overall bone health.

Microwave imaging for breast cancer detection and therapy monitoring

Microwave imaging is based on recovering the electrical properties, namely permittivity and conductivity, of materials. Microwave imaging for biomedical applications is particularly interesting, because the available range of dielectric properties of different tissues can provide substantial functional information about their health. Breast cancer detection and treatment response monitoring are areas where microwave imaging is becoming a promising alternative/complementary technique to current imaging modalities, mainly due to the significant dielectric property contrast between normal and malignant breast tissues. In this paper, we present our latest clinical microwave imaging system along with some 2D and 3D reconstructed images from different phantom experiments and patient data.

Comparison of no-prior and soft-prior regularization in biomedical microwave imaging

Microwave imaging for medical applications is attractive because the range of dielectric properties of different soft tissues can be substantial. Breast cancer detection and monitoring of treatment response are areas where this technology could be important because of the contrast between normal and malignant tissue. Unfortunately, the technique is unable to achieve the high spatial resolution at depth in tissue which is available from other conventional modalities such as x-ray computed tomography (CT) or magnetic resonance imaging (MRI). We have incorporated a soft-prior regularization strategy within our microwave reconstruction algorithm and compared it with the images obtained with traditional no-prior (Levenberg-Marquardt) regularization. Initial simulation and phantom results show a significant improvement of the recovered electrical properties. Specifically, errors in the microwave property estimates were improved by as much as 95%. The effects of a false-inclusion region were also evaluated and the results show that a small residual property bias of 6% in permittivity and 15% in conductivity can occur that does not otherwise degrade the property recovery accuracy of inclusions that actually exist. The work sets the stage for integrating microwave imaging with MR for improved resolution and functional imaging of the breast in the future.

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 tomography for bone imaging

Osteoporosis is a major health problem affecting roughly 55% of the U.S. population 50 years of age or older. Current methods to detect osteoporosis or assess bone fracture risk involve a bone mineral density (BMD) exam generally using x-ray techniques - primarily dual x-ray absorptiometry (DXA). While this technique provides a measure of the bone mass, it does not offer any insight into bone quality, structure or biology which are regarded as important components of bone health. Microwave tomography for bone imaging consists of recovering bone dielectric properties, which have been shown to have strong correlations with clinically important mechanical properties of bone. In this paper we present some preliminary results from a simulation experiment along with some patient data.

Clinical microwave breast imaging — 2D results and the evolution to 3D

The incidence of breast cancer and associated deaths are a recognized world health problem. Conventional screening approaches such as x-ray mammography, ultrasound and increasingly contrast-enhanced MRI are life saving to many women. However, the sensitivity and specificity of these modalities are still limited and there is clearly room for alternatives. Microwave imaging is a potentially important approach in this area because the tissue dielectric properties present important functional information which can be exploited to improve overall sensitivity and specificity in breast imaging. At Dartmouth College, our microwave breast imaging system is currently being used in pilot clinical studies for both tumor diagnosis and for monitoring treatment response during neoadjuvant chemotherapy. These early 2D imaging studies have demonstrated significance with respect to distinguishing tumors from normal tissue in the diagnostic mode and an ability to predict treatment response at a relatively early stage of treatment. The associated innovations and clinical results set a solid foundation as we advance towards full 3D imaging.

Microwave imaging utilizing a soft prior constraint

Microwave imaging for breast cancer detection is becoming a promising alternative technique to current imaging modalities. The significant contrast between dielectric properties of normal and malignant breast tissues makes microwave imaging a useful technique to provide important functional information for diagnoses. However, one of its limitations is that it intrinsically cannot produce high resolution images as other conventional techniques such as MRI or X-ray CT do. Those modalities are capable of producing high quality anatomical images, but unlike microwave imaging, they often cannot provide the necessary functional information about tissue health. In order to refine the resolution of the microwave images while also preserving the functional information, we have recently developed a new strategy, called soft prior regularization. In this new approach, the prior anatomical information of the tissue from either x-ray, MR or other sources is incorporated into our microwave imaging reconstruction algorithm through the following steps: First, the anatomical information is used to create a reconstruction mesh which defines the boundaries of different internal regions. Second, based on location of each mesh node, an associated weighting matrix is defined, such that all nodes within each region are grouped with each other. Finally, the soft prior matrix is used as a regularizing term for our original Gauss- Newton reconstruction algorithm. Results from initial phantom experiments show a significant improvement in the recovered dielectric properties.