Biomedical subjects

R Sinkus

Publications and source records attributed to R Sinkus.

5 recordsLinked to original sources

PubMed2002

MR elastography of the breast:preliminary clinical results.

PURPOSE: Imaging of breast tumors and various breast tissues using magnetic resonance (MR) elastography (MRE) to explore the potential of elasticity as a new parameter for the diagnosis of breast lesions. METHODS: Low-frequency mechanical waves are transmitted into breast tissue by means of an oscillator. The local characteristics of the mechanical wave are determined by the underlying elastic properties of the tissue. Theses waves can be displayed by means of a motion-sensitive spin-echo MR sequence within the phase of the MR image. Elasticity reconstruction is performed on the basis of 8 "snapshots" of each wave within the three spatial directions. We performed in-vivo measurements in 15 female patients with malignant tumors of the breast, 5 patients with benign breast tumors, and 15 healthy volunteers. RESULTS: Malignant invasive breast tumors documented the highest values of elasticity with a median of 15.9 kPa and a wide range of stiffnesses between 8 and 28 kPa. In contrast, benign breast lesions represented low values of elasticity, which were significantly different from malignant breast tumors (median elasticity: 7.0 kPa; p = 0.0012). This was comparable to the stiffest tissue areas in healthy volunteers (median elasticity 7.0 kPa), whereas breast parenchyma (median: 2.5 kPa) and fatty breast tissue (median: 1.7 kPa) showed the lowest values of elasticity. Two invasive ductal carcinomas had elasticity values of 8 kPa and two stiff parenchyma areas in healthy volunteers had elasticities of 13 and 15 kPa. These lesions could not be differentiated by their elasticity. CONCLUSION: We conclude that MRE is a promising new imaging modality with the capability to assess the viscoelastic properties of breast tumors and the surrounding tissues. However, from our preliminary results in a small number of patients it is obvious that there is an overlap in the elasticity ranges of soft malignant tumors and stiff benign lesions.

Adult↗

PubMed2001

[Imaging of breast tumors using MR elastography].

PURPOSE: Imaging of breast tumors using MR-Elastography. MATERIAL AND METHOD: Low-frequency mechanical waves are transmitted into breast-tissue by means of an oscillator. The local characteristics of the mechanical wave are determined by the elastic properties of the tissue. By means of a motion-sensitive spin-echo-sequence these waves can be displayed within the phase of the MR image. Subsequently, these images can be used to reconstruct the local distribution of elasticity. In-vivo measurements were performed in 3 female patients with malignant tumors of the breast. RESULTS: All patients tolerated the measurement set-up without any untoward sensation in the contact area of skin and oszillator. The waves completely penetrated the breast, encompassing the axilla and regions close to the chest wall. All tumors were localized by MRE as structures of markedly stiffer tissue when compared to the surrounding tissue. Furthermore, in one patient, a metastasis in an axillary lymph node was detected. In all patients, local regions of increased elasticity were found in the remaining parenchyma of the breast, which, however, did not reach the high levels of elasticity found in the tumors. CONCLUSION: MRE is an imaging modality enabling adjunct tissue differentiation of mammary tumors.

Adult↗

PubMed2000

High-resolution tensor MR elastography for breast tumour detection.

MR elastography is a novel imaging technique for the visualization of elastic properties of tissue. It is expected that this method will have diagnostic value for the clarification of suspicious breast lesions. Low-frequency mechanical waves are coupled into the tissue and visualized via an MR sequence which is phase-locked to the mechanical excitation. Commonly, elasticity is assumed to be isotropic and reconstruction is performed in only two dimensions. The technique is extended to three dimensions such that the entire symmetric elasticity tensor is assessed. This is achieved by measuring different phases of the mechanical wave during one oscillatory cycle. Thereby it is possible to provide information about the anisotropy of the elasticity tensor. Finite-element simulations as well as phantom experiments are performed to demonstrate the feasibility of the method. Initial clinical results of a breast carcinoma are presented. The analysis of the eigenvalues of the elasticity tensor support the hypothesis that breast carcinoma might exhibit an anisotropic elasticity distribution. The surrounding benign tissue appears isotropic. Thereby new and additional diagnostic information is provided which might help in distinguishing between benign and malignant breast diseases.

Algorithms↗

PubMed1999

Motion pattern adapted real-time respiratory gating.

The information about the current respiratory motion state used in conventional gating to accept or to reject data can further be used to obtain motion statistics during an MR scan. This can serve to monitor changes in the respiratory pattern of the patient by comparison of motion statistics subsequently obtained during scanning. Two indicators are introduced: first a parameter that registers changes of the motion pattern, and second an indicator that expresses the quality of the data set already obtained. Based on these indicators, the gating algorithm decides to change gating parameters during scanning automatically. This new approach has the potential to increase the scan efficiency considerably without the need of operator interaction and/or significant patient cooperation. The basic principle is described and illustrated for the motion-adapted gating technique, and first in vivo results are presented to underline the feasibility of this concept.

Abdomen↗

PubMed1999

Resampling of data between arbitrary grids using convolution interpolation.

For certain medical applications resampling of data is required. In magnetic resonance tomography (MRT) or computer tomography (CT), e.g., data may be sampled on nonrectilinear grids in the Fourier domain. For the image reconstruction a convolution-interpolation algorithm, often called gridding, can be applied for resampling of the data onto a rectilinear grid. Resampling of data from a rectilinear onto a nonrectilinear grid are needed, e.g., if projections of a given rectilinear data set are to be obtained. In this paper we introduce the application of the convolution interpolation for resampling of data from one arbitrary grid onto another. The basic algorithm can be split into two steps. First, the data are resampled from the arbitrary input grid onto a rectilinear grid and second, the rectilinear data is resampled onto the arbitrary output grid. Furthermore, we like to introduce a new technique to derive the sampling density function needed for the first step of our algorithm. For fast, sampling-pattern-independent determination of the sampling density function the Voronoi diagram of the sample distribution is calculated. The volume of the Voronoi cell around each sample is used as a measure for the sampling density. It is shown that the introduced resampling technique allows fast resampling of data between arbitrary grids. Furthermore, it is shown that the suggested approach to derive the sampling density function is suitable even for arbitrary sampling patterns. Examples are given in which the proposed technique has been applied for the reconstruction of data acquired along spiral, radial, and arbitrary trajectories and for the fast calculation of projections of a given rectilinearly sampled image.

Algorithms↗