Dov Grobgeld

Parametric diffusion tensor imaging of the breast

Objectives:To investigate the ability of parametric diffusion tensor imaging (DTI), applied at 3 Tesla, to dissect breast tissue architecture and evaluate breast lesions. Materials and Methods:All protocols were approved and a signed informed consent was obtained from all subjects. The study included 21 healthy women, 26 women with 33 malignant lesions, and 14 women with 20 benign lesions. Images were recorded at 3 Tesla with a protocol optimized for breast DTI at a spatial resolution of 1.9 × 1.9 × (2–2.5) mm3. Image processing algorithms and software, applied at pixel resolution, yielded vector maps of prime diffusion direction and parametric maps of the 3 orthogonal diffusion coefficients and of the fractional anisotropy and maximal anisotropy. Results:The DTI-derived vector maps and parametric maps revealed the architecture of the entire mammary fibroglandular tissue and allowed a reliable detection of malignant lesions. Cancer lesions exhibited significantly lower values of the orthogonal diffusion coefficients, &lgr;1, &lgr;2, &lgr;3, and of the maximal anisotropy index &lgr;1-&lgr;3 as compared with normal breast tissue (P < 0.0001) and to benign breast lesions (P < 0.0009 and 0.004, respectively). Maps of &lgr;1 exhibited the highest contrast-to-noise ratio enabling delineation of the cancer lesions. These maps also provided high sensitivity/specificity of 95.6%/97.7% for differentiating cancers from benign lesions, which were similar to the sensitivity/specificity of dynamic contrast-enhanced magnetic resonance imaging of 94.8%/92.9%. Maps of &lgr;1-&lgr;3 provided a secondary independent diagnostic parameter with high sensitivity of 92.3%, but low specificity of 69.5% for differentiating cancers from benign lesions. Conclusion:Mapping the diffusion tensor parameters at high spatial resolution provides a potential novel means for dissecting breast architecture. Parametric maps of &lgr;1 and &lgr;1-&lgr;3 facilitate the detection and diagnosis of breast cancer.

Critical role of spatial resolution in dynamic contrast-enhanced breast MRI†

The spatial resolution of three‐dimensional (3D) gradient‐echo T1‐weighted images, from 40 women with 25 malignant and 23 benign lesions, was purposely degraded to determine the role of spatial resolution in recording, analysis, and diagnosis of dynamic contrast‐enhanced breast MRI. Images were recorded and analyzed at pixel resolution according to the 3TP method (Degani et al., Nat Med 1997;3:780–782). Reduction in spatial resolution degraded the appearance of foci with fast wash‐in and fast washout dynamics. This resulted in an increase in false‐negative diagnoses. The sensitivity for differentiating between malignant and benign lesions, using threshold criteria defined by the 3TP analysis, of 76% decreased to 60% and 24% for a 2‐ and 4‐fold reduction in spatial resolution, respectively, without affecting significantly the high specificity (96–100%). In order to minimize false‐negative diagnoses of contrast‐enhanced breast MRI and maintain high specificity, it is essential to record and analyze the dynamic behavior at high spatial resolution. J. Magn. Reson. Imaging 2001;13:862–867.

Diffusion-Tensor MR Imaging of the Breast: Hormonal Regulation

PURPOSE To investigate the parameters obtained with magnetic resonance (MR) diffusion-tensor imaging (DTI) of the breast throughout the menstrual cycle phases, during lactation, and after menopause, with and without hormone replacement therapy (HRT). MATERIALS AND METHODS All protocols were approved by the internal review board, and signed informed consent was obtained from all participants. Forty-five healthy volunteers underwent imaging by using T2-weighted and DTI MR sequences at 3 T. Premenopausal volunteers (n = 16) underwent imaging weekly, four times during one menstrual cycle. Postmenopausal volunteers (n = 19) and lactating volunteers (n = 10) underwent imaging once. The principal diffusion coefficients (λ1, λ2, and λ3), apparent diffusion coefficient (ADC), fractional anisotropy (FA), and maximal anisotropy (λ1-λ3) were calculated pixel by pixel for the fibroglandular tissue in the entire breast. RESULTS In all premenopausal volunteers, the DTI parameters exhibited high repeatability, remaining almost equal along the menstrual cycle, with a low mean within-subject coefficient of variance of λ1, λ2, λ3, and ADC (1%-2% for all) and FA (5%), as well as a high intraclass correlation of 0.92-0.98. The diffusion coefficients were significantly lower (a) in the group without HRT use as compared with the group with HRT use (P < .01) and premenopausal volunteers (P < .01) and (b) in the lactating volunteers as compared with the premenopausal volunteers (P < .005). No significant differences in DTI parameters were found between premenopausal volunteers free of oral contraceptives and those who used oral contraceptives (P = .28-0.82) and between premenopausal volunteers and postmenopausal volunteers who used HRT (P = .31-0.93). CONCLUSION DTI parameters are not sensitive to menstrual cycle changes, while menopause, long-term HRT, and presence of milk in lactating women affected the DTI parameters. Therefore, the timing for performing breast DTI is not restricted throughout the menstrual cycle, whereas the modulations in diffusion parameters due to HRT and lactation should be taken into account in DTI evaluation.

Diffusion Tensor Magnetic Resonance Imaging of the Pancreas

Purpose To develop a diffusion-tensor-imaging (DTI) protocol that is sensitive to the complex diffusion and perfusion properties of the healthy and malignant pancreas tissues. Materials and Methods Twenty-eight healthy volunteers and nine patients with pancreatic-ductal-adenocacinoma (PDAC), were scanned at 3T with T2-weighted and DTI sequences. Healthy volunteers were also scanned with multi-b diffusion-weighted-imaging (DWI), whereas a standard clinical protocol complemented the PDAC patients’ scans. Image processing at pixel resolution yielded parametric maps of three directional diffusion coefficients λ1, λ2, λ3, apparent diffusion coefficient (ADC), and fractional anisotropy (FA), as well as a λ1-vector map, and a main diffusion-direction map. Results DTI measurements of healthy pancreatic tissue at b-values 0,500 s/mm2yielded: λ1 = (2.65±0.35)×10−3, λ2 = (1.87±0.22)×10−3, λ3 = (1.20±0.18)×10−3, ADC = (1.91±0.22)×10−3 (all in mm2/s units) and FA = 0.38±0.06. Using b-values of 100,500 s/mm2 led to a significant reduction in λ1, λ2, λ3 and ADC (p<.0001) and a significant increase (p<0.0001) in FA. The reduction in the diffusion coefficients suggested a contribution of a fast intra-voxel-incoherent-motion (IVIM) component at b≤100 s/mm2, which was confirmed by the multi-b DWI results. In PDACs, λ1, λ2, λ3 and ADC in both 0,500 s/mm2 and 100,500 s/mm2 b-values sets, as well as the reduction in these diffusion coefficients between the two sets, were significantly lower in comparison to the distal normal pancreatic tissue, suggesting higher cellularity and diminution of the fast-IVIM component in the cancer tissue. Conclusion DTI using two reference b-values 0 and 100 s/mm2 enabled characterization of the water diffusion and anisotropy of the healthy pancreas, taking into account a contribution of IVIM. The reduction in the diffusion coefficients of PDAC, as compared to normal pancreatic tissue, and the smaller change in these coefficients in PDAC when the reference b-value was modified from 0 to 100 s/mm2, helped identifying the presence of malignancy.

Can diffusion tensor anisotropy indices assist in breast cancer detection

To evaluate whether the various anisotropy indices derived from breast diffusion tensor imaging (DTI) can characterize the healthy breast structure and differentiate cancer from normal breast tissue.

A numerical method for locating stable periodic orbits in chaotic systems

Abstract A numerical method aimed at locating stable periodic orbits in strongly chaotic systems is presented. The method is based on the selection of trajectory segments which are characterized by a relatively low positive local Lyapunov exponent. Once such a selection is made, convergence to stable (or weakly unstable) periodic orbits is obtained by a Newton method. The algorithm is rather general and can be used for systems with more than two degrees of freedom. The proposed approach is tested on the quartic oscillator model and on the potential of the hydrogen atom in a strong magnetic field. In the latter case new stable periodic orbits are found in the region of strong chaotic motion. The possible quantum localization on these orbits is discussed briefly.

Advantages and drawbacks of breast DTI

In 1965, Stejskal and Tanner developed the pulsed gradient spin echo (PGSE) technique for measuring the diffusion coefficient in solution [1]. The discovery of MRI led to the development of diffusion imaging sequences particularly sequences based on echo planar imaging – EPI that facilitate fast clinical diffusion measurements. As a result of gradient strength limitations in most human scanners, it is necessary to use long finite-width gradient pulses in order to achieve high b values and hence, the short gradient pulse approximation breaks down. Nevertheless, it was shown by Zielinski and Sen [2] that diffusion experiments with long diffusion gradient pulses still measure a physical parameter reflecting self diffusion in systems that have open geometry and large amount of restriction as is the case in most tissues. Water diffusion in tissues presents a highly complex process as the system is composed of several different compartments with partial restriction processes within the compartments. Water diffusion coefficients of tissues are not merely affected by Brownian motion, but also by additional contributions of flow, restriction by cell membrane, extracellular tortuosity and exchange between tissue compartments. Water diffusion in tissues is often anisotropic due to restriction by membranes and walls of various micro-structures. Namely, anisotropic diffusion leads to variable diffusion coefficients for various directions and hence the diffusion coefficients are described by a diffusion tensor. The diffusion of water molecules in the mammary tissue presents a particular example of restricted movement in well defined microstructures composed of the ductal/ glandular trees. The, diffusion in parallel to the walls of the ducts is free; however, it is restricted in the directions perpendicular to the walls. The extent of restriction will depend on the experimental diffusion time versus the size of the ductal and glandular regions. Blockage of the ducts by cancer cells predominantly affects the free diffusion in parallel to the walls, reducing the diffusion coefficient in all directions, and consequently the extent of anisotropy. We have applied an experimental protocol to track this anisotropic motion using diffusion gradients in 30 to 60 directions and two b-values with a relatively high diffusion time [3]. In voxels with anisotropic water diffusion the distribution of the fraction of change in signal intensity in all directions of the field gradients assumed an anisotropic ellipsoid form, whereas in voxels with isotropic

Tracking the mammary architectural features and detecting breast cancer with magnetic resonance diffusion tensor imaging.

Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.

Vascular perfusion of human lung cancer in a rat orthotopic model using dynamic contrast‐enhanced magnetic resonance imaging

Lung cancer is the leading cause of death among cancers. Early detection and diagnosis present a major goal in the efforts to improve survival rates of lung cancer patients. Changes in angiogenic activity and microvascular perfusion properties in cancers can serve as markers of malignancy. The aim of this study was to employ MRI means to measure the microvascular perfusion parameters of orthotopic nonsmall cell lung cancer, using the experimental rat model. Anatomical and dynamic contrast‐enhanced lung images were acquired at high spatial resolution, and registered and analyzed, pixel by pixel and globally, by means of a model‐based algorithm. The MRI output yielded color‐coded parametric images of the influx and efflux transcapillary transfer constants that indicated rapid microvascular perfusion. The transfer constants were about 1 order of magnitude higher than those found in other tumors or in nonorthotopic lung cancer, with the influx constant median value of 0.42 min−1 and the efflux constant median value of 1.61 min−1. The rapid perfusion was in accord with the immunostaining of the capillaries, which suggested the tumor exploitation of the existing alveolar vessels. The results showed that high resolution, dynamic, contrast‐enhanced MRI is an effective tool for the quantitative measurement of spatial and temporal changes in lung cancer perfusion and vasculature.

Monitoring In-Vivo the Mammary Gland Microstructure during Morphogenesis from Lactation to Post-Weaning Using Diffusion Tensor MRI

Lactation and the return to the pre-conception state during post-weaning are regulated by hormonal induced processes that modify the microstructure of the mammary gland, leading to changes in the features of the ductal / glandular tissue, the stroma and the fat tissue. These changes create a challenge in the radiological workup of breast disorder during lactation and early post-weaning. Here we present non-invasive MRI protocols designed to record in vivo high spatial resolution, T2-weighted images and diffusion tensor images of the entire mammary gland. Advanced imaging processing tools enabled tracking the changes in the anatomical and microstructural features of the mammary gland from the time of lactation to post-weaning. Specifically, by using diffusion tensor imaging (DTI) it was possible to quantitatively distinguish between the ductal / glandular tissue distention during lactation and the post-weaning involution. The application of the T2-weighted imaging and DTI is completely safe, non-invasive and uses intrinsic contrast based on differences in transverse relaxation rates and water diffusion rates in various directions, respectively. This study provides a basis for further in-vivo monitoring of changes during the mammary developmental stages, as well as identifying changes due to malignant transformation in patients with pregnancy associated breast cancer (PABC).