Computational electromagnetics models of microwave interactions with the human breast serve as an invaluable tool for exploring the feasibility of new technologies and improving design concepts related to microwave breast cancer detection and treatment. In this paper we report the development of a collection of anatomically realistic 3D numerical breast phantoms of varying shape, size, and radiographic density which can be readily used in FDTD computational electromagnetics models. The phantoms are derived from T1-weighted magnetic resonance images (MRIs) of prone patients. Each MRI is transformed into a uniform grid of dielectric properties using several steps. First, the structure of each phantom is identified by applying image processing techniques to the MRI. Next, the voxel intensities of the MRI are converted to frequency-dependent and tissue-dependent dielectric properties of normal breast tissues via a piecewise-linear map. The dielectric properties of normal breast tissue are taken from the recently completed large-scale experimental study of normal breast tissue dielectric properties conducted by the Universities of Wisconsin and Calgary. The comprehensive collection of numerical phantoms is made available to the scientific community through an online repository.

Dual energy CT scanning (tomochemistry) has been proposed as a method for determining various parameters relating to the elemental composition of the tissues. In this paper, our aim is to study the relative noise inherent in two proposed techniques for dual energy scanning; a "two crystal" technique and a "two kV" technique. In the two crystal technique, a split crystal detector is used to simultaneously obtain the high and low energy data during one scan at high kV. The two kV technique requires two scans taken with widely different kV settings. We first review three commonly used approaches for utilizing the scan data to compute the relevant parameters. A theoretical formalism is constructed which aids in understanding these methods. Then this formalism is used to study the influence of CT image noise on measurement precision in the case where the unknown parameters are densities. It is shown that, (1) the unavoidable overlap in the spectral data obtained by the two crystal technique results in a much lower signal-to-noise ratio than can be obtained by using the two kV technique, (2) the necessity for hard filtration of the high energy beam in the two kV technique has not heretofore been appreciated, and (3) the dose for a given x-ray tube heat load is also lower with the two kV technique.

A sufficient decrease in tumor vascular parameters was observed at a dose chosen for additional phase II testing by conventional toxicity criteria. In addition, the day 2 vascular response measured using DCE-MRI seems to be a useful indicator of drug pharmacology, and additional research is needed to determine if it is a suitable marker for predicting clinical activity.

In this animal model, unenhanced CT was an effective way to monitor RF ablation compared with sonography because of increased lesion discrimination, reproducible decreased attenuation during ablation, and improved correlation to pathologic size.

Characterization of architectural tissue features such as the shape, margin, and size of a suspicious lesion is commonly performed in conjunction with medical imaging to provide clues about the nature of an abnormality. In this paper, we numerically investigate the feasibility of using multichannel microwave backscatter in the 1-11 GHz band to classify the salient features of a dielectric target. We consider targets with three shape characteristics: smooth, microlobulated, and spiculated; and four size categories ranging from 0.5 to 2 cm in diameter. The numerical target constructs are based on Gaussian random spheres allowing for moderate shape irregularities. We perform shape and size classification for a range of signal-to-noise ratios (SNRs) to demonstrate the potential for tumor characterization based on ultrawideband (UWB) microwave backscatter. We approach classification with two basis selection methods from the literature: local discriminant bases and principal component analysis. Using these methods, we construct linear classifiers where a subset of the bases expansion vectors are the input features and we evaluate the average rate of correct classification as a performance measure. We demonstrate that for 10 dB SNR, the target size is very reliably classified with over 97% accuracy averaged over 360 targets; target shape is classified with over 70% accuracy. The relationship between the SNR of the test data and classifier performance is also explored. The results of this study are very encouraging and suggest that both shape and size characteristics of a dielectric target can be classified directly from its UWB backscatter. Hence, characterization can easily be performed in conjunction with UWB radar-based breast cancer detection without requiring any special hardware or additional data collection.

Current study results suggest that the addition of quantitative 1H MR spectroscopy to the breast MR imaging examination may help to improve the radiologist's ability to distinguish benign from malignant breast lesions.

Off-resonance spin locking is investigated as a low power method for achieving low field spin-lattice relaxation contrast using high field clinical MR imaging systems (e.g., 1.5 tesla). Spin-lattice relaxation times and equilibrium magnetizations in the off-resonance rotating frame (T1 rho(off), beta) were measured for tissue-mimicking phantom materials as a function of the ratio of the amplitude to the resonance offset of the spin-locking pulse (f1/delta). The phantom materials consisted of vegetable oil to simulate fat and two different gels containing 2% and 4% agar to simulate nonfatty tissues with different macromolecular compositions. These measurements were used to verify a signal strength equation for a multislice off-resonance spin-locking technique implemented on a clinical MR imaging system operating at 1.5 tesla. Although the oil showed little change in image contrast with increasing f1/delta, the two gels demonstrated a strong variation which provided improved discrimination compared to T1-weighted imaging. Off-resonance spin locking is suggested as a method for improving delineation of breast lesions and a preliminary clinical example from a patient volunteer is presented.

Application of the three-time-point method permitted, in most cases, differentiation of malignant and benign lesions, even in the presence of complex breast enhancement patterns. Sensitivity for solid tumors was higher than for ductal carcinoma in situ.