3-D Microwave Tomography Using the Soft Prior Regularization Technique: Evaluation in Anatomically Realistic MRI-Derived Numerical Breast Phantoms.

OBJECTIVE: Fusion of magnetic resonance imaging (MRI) breast images with microwave tomography is accomplished through a soft prior technique, which incorporates spatial information (from MRI), i.e., accurate boundary location of different regions of interest, into the regularization process of the microwave image reconstruction algorithm. METHODS: Numerical experiments were completed on a set of three-dimensional (3-D) breast geometries derived from MR breast data with different parenchymal densities, as well as a simulated tumor to evaluate the performance over a range of breast shapes, sizes, and property distributions. RESULTS: When the soft prior regularization technique was applied, both permittivity and conductivity relative root mean square error values decreased by more than 87% across all breast densities, except in two cases where the error decrease was only 55% and 78%. In addition, the incorporation of structural priors increased contrast between tumor and fibroglandular tissue by 59% in permittivity and 192% in conductivity. CONCLUSION: This study confirmed that the soft prior algorithm is robust in 3-D and can function successfully across a range of complex geometries and tissue property distributions. SIGNIFICANCE: This study demonstrates that our microwave tomography is capable of recovering accurate tissue property distributions when spatial information from MRI is incorporated through soft prior regularization.

Tri-Ponderal Mass Index vs Body Mass Index in Estimating Body Fat During Adolescence.

Importance: Body mass index (BMI) is used to diagnose obesity in adolescents worldwide, despite evidence that weight does not scale with height squared in adolescents. To account for this, health care providers diagnose obesity using BMI percentiles for each age (BMI z scores), but this does not ensure that BMI is accurate in adolescents. Objective: To compare the accuracy of BMI vs other body fat indices of the form body mass divided by heightn in estimating body fat levels in adolescents. Design, Setting, and Participants: Cross-sectional data from the 1999 to 2006 US National Health and Nutrition Examination Survey were analyzed between September 2015 and December 2016. Main Outcomes and Measures: Dual-energy x-ray absorptiometry and anthropometric data were used to determine changes in body fat levels, body proportions, and the scaling relationships among body mass, height, and percent body fat. To assess the merits of each adiposity index, 3 criteria were used: stability with age, accuracy in estimating percent body fat, and accuracy in classifying adolescents as overweight vs normal weight. Results: Participants included 2285 non-Hispanic white participants aged 8 to 29 years. Percent body fat varied with both age and height during adolescence, invalidating the standard weight-to-height regression as the way of finding the optimal body fat index. Because the correct regression model (percent body fat is proportional to mass divided by heightn) suggested that percent body fat scales to height with an exponent closer to 3, we therefore focused on the tri-ponderal mass index (TMI; mass divided by height cubed) as an alternative to BMI z scores. For ages 8 to 17 years, TMI yielded greater stability with age and estimated percent body fat better than BMI (R2 = 0.64 vs 0.38 in boys and R2 = 0.72 vs 0.66 in girls). Moreover, TMI misclassified adolescents as overweight vs normal weight less often than BMI z scores (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 19.4%; 95% CI, 17.8%-20.0%; P < .001) and performed equally as well as updated BMI percentiles derived from the same data set (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 8.0%; 95% CI, 6.9%-9.1%; P = .62). Conclusions and Relevance: The tri-ponderal mass index estimates body fat levels more accurately than BMI in non-Hispanic white adolescents aged 8 to 17 years. Moreover, TMI diagnoses adolescents as overweight more accurately than BMI z scores and equally as well as updated BMI percentiles but is much simpler to use than either because it does not involve complicated percentiles. Taken together, it is worth considering replacing BMI z scores with TMI to estimate body fat levels in adolescents.

3D microwave tomography of the breast using prior anatomical information.

PURPOSE: The authors have developed a new 3D breast image reconstruction technique that utilizes the soft tissue spatial resolution of magnetic resonance imaging (MRI) and integrates the dielectric property differentiation from microwave imaging to produce a dual modality approach with the goal of augmenting the specificity of MR imaging, possibly without the need for nonspecific contrast agents. The integration is performed through the application of a soft prior regularization which imports segmented geometric meshes generated from MR exams and uses it to constrain the microwave tomography algorithm to recover nearly uniform property distributions within segmented regions with sharp delineation between these internal subzones. METHODS: Previous investigations have demonstrated that this approach is effective in 2D simulation and phantom experiments and also in clinical exams. The current study extends the algorithm to 3D and provides a thorough analysis of the sensitivity and robustness to misalignment errors in size and location between the spatial prior information and the actual data. RESULTS: Image results in 3D were not strongly dependent on reconstruction mesh density, and the changes of less than 30% in recovered property values arose from variations of more than 125% in target region size-an outcome which was more robust than in 2D. Similarly, changes of less than 13% occurred in the 3D image results from variations in target location of nearly 90% of the inclusion size. Permittivity and conductivity errors were about 5 times and 2 times smaller, respectively, with the 3D spatial prior algorithm in actual phantom experiments than those which occurred without priors. CONCLUSIONS: The presented study confirms that the incorporation of structural information in the form of a soft constraint can considerably improve the accuracy of the property estimates in predefined regions of interest. These findings are encouraging and establish a strong foundation for using the soft prior technique in clinical studies, where their microwave imaging system and MRI can simultaneously collect breast exam data in patients.

Deep inspiration and the emergence of ventilation defects during bronchoconstriction: a computational study.

Deep inspirations (DIs) have a dilatory effect on airway smooth muscle (ASM) that helps to prevent or reduce more severe bronchoconstriction in healthy individuals. However, this bronchodilation appears to fail in some asthmatic patients or under certain conditions, and the reason is unclear. Additionally, quantitative effects of the frequency and magnitude of DIs on bronchodilation are not well understood. In the present study, we used a computational model of bronchoconstriction to study the effects of DI volumes, time intervals between intermittent DIs, relative speed of ASM constriction, and ASM activation on bronchoconstriction and the emergence of ventilation defects (VDefs). Our results showed a synergistic effect between the volume of DIs and the time intervals between them on bronchoconstriction and VDefs. There was a domain of conditions with sufficiently large volumes of DIs and short time intervals between them to prevent VDefs. Among conditions without VDefs, larger volumes of DIs resulted in greater airway dilation. Similarly, the time interval between DIs, during which the activated ASM re-constricts, affected the amplitude of periodic changes in airway radii. Both the relative speed of ASM constriction and ASM activation affected what volume of DIs and what time interval between them could prevent the emergence of VDefs. In conclusion, quantitative characteristics of DIs, such as their volume and time interval between them, affect bronchoconstriction and may contribute to difficulties in asthma. Better understanding of the quantitative aspects of DIs may result in novel or improved therapeutic approaches.

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.

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.

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 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 tissue's 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.