PubMed Health⌕ Search

Biomedical subjects

Ulrich Bick

Publications and source records attributed to Ulrich Bick.

10 recordsLinked to original sources
PubMed2006

A fuzzy c-means (FCM)-based approach for computerized segmentation of breast lesions in dynamic contrast-enhanced MR images.

RATIONALE AND OBJECTIVES: Accurate quantification of the shape and extent of breast tumors has a vital role in nearly all applications of breast magnetic resonance (MR) imaging (MRI). Specifically, tumor segmentation is a key component in the computerized assessment of likelihood of malignancy. However, manual delineation of lesions in four-dimensional MR images is labor intensive and subject to interobserver and intraobserver variations. We developed a computerized lesion segmentation method that has the advantage of being automatic, efficient, and objective. MATERIALS AND METHODS: We present a fuzzy c-means (FCM) clustering-based method for the segmentation of breast lesions in three dimensions from contrast-enhanced MR images. The proposed lesion segmentation algorithm consists of six consecutive stages: region of interest (ROI) selection by a human operator, lesion enhancement within the selected ROI, application of FCM on the enhanced ROI, binarization of the lesion membership map, connected-component labeling and object selection, and hole-filling on the selected object. We applied the algorithm to a clinical MR database consisting of 121 primary mass lesions. Manual segmentation of the lesions by an expert MR radiologist served as a reference in the evaluation of the computerized segmentation method. We also compared the proposed algorithm with a previously developed volume-growing (VG) method. RESULTS: For the 121 mass lesions in our database, 97% of lesions were segmented correctly by means of the proposed FCM-based method at an overlap threshold of 0.4, whereas 84% of lesions were correctly segmented by means of the VG method. CONCLUSION: Our proposed algorithm for breast-lesion segmentation in dynamic contrast-enhanced MRI was shown to be effective and efficient.

Algorithms↗
PubMed2006

Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE-MRI.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast is being used increasingly in the detection and diagnosis of breast cancer as a complementary modality to mammography and sonography. Although the potential diagnostic value of kinetic curves in DCE-MRI is established, the method for generating kinetic curves is not standardized. The inherent reason that curve identification is needed is that the uptake of contrast agent in a breast lesion is often heterogeneous, especially in malignant lesions. It is accepted that manual region of interest selection in 4D breast magnetic resonance (MR) images to generate the kinetic curve is a time-consuming process and suffers from significant inter- and intraobserver variability. We investigated and developed a fuzzy c-means (FCM) clustering-based technique for automatically identifying characteristic kinetic curves from breast lesions in DCE-MRI of the breast. Dynamic contrast-enhanced MR images were obtained using a T1-weighted 3D spoiled gradient echo sequence with Gd-DTPA dose of 0.2 mmol/kg and temporal resolution of 69 s. FCM clustering was applied to automatically partition the signal-time curves in a segmented 3D breast lesion into a number of classes (i.e., prototypic curves). The prototypic curve with the highest initial enhancement was selected as the representative characteristic kinetic curve (CKC) of the lesion. Four features were then extracted from each characteristic kinetic curve to depict the maximum contrast enhancement, time to peak, uptake rate, and washout rate of the lesion kinetics. The performance of the kinetic features in the task of distinguishing between benign and malignant lesions was assessed by receiver operating characteristic analysis. With a database of 121 breast lesions (77 malignant and 44 benign cases), the classification performance of the FCM-identified CKCs was found to be better than that from the curves obtained by averaging over the entire lesion and similar to kinetic curves generated from regions drawn within the lesion by a radiologist experienced in breast MRI.

Adult↗
PubMed2005

Digital mammography using iodine-based contrast media: initial clinical experience with dynamic contrast medium enhancement.

PURPOSE: We sought to evaluate the potential of dynamic contrast enhancement after the intravenous administration of an iodine-based contrast medium in full-field digital mammography. MATERIAL AND METHODS: A protocol for image acquisition was established for contrast-enhanced mammography and the mammography unit (Senographe 2000D, GE Healthcare, Buc, France) changed as required. The effect of the protocol parameters on imaging was investigated. Subsequently, 21 patients with 25 suspicious lesions of the breast (10 benign, 1 borderline, and 14 malignant) underwent mammography with administration of an iodine-based contrast medium (Ultravist 370, Schering AG, Berlin, Germany), after approval of ethical committee as well as permission of German federal office for Radiation protection, and informed consent from each patient was obtained. Three sequential digital mammographic images of the respective breast were acquired after administration of the contrast medium at a dose of 1 mL/kg body weight and a flow of 4 mL/s. The postcontrast images were acquired 60, 120, and 180 seconds after administration. Subsequently, the precontrast image was logarithmically subtracted from the postcontrast images. Enhancement of the lesions was measured in absolute terms as well as relative to the enhancement of the glandular tissue. The subtracted images were evaluated for lesion depiction and dynamic contrast enhancement. Lesion-enhancement kinetics were compared with the histologic findings. RESULTS: All malignant lesions were identified on the contrast-enhanced images of digital mammography. Three of the tumors (2 malignant, 1 benign) were detected only by contrast-enhanced mammography and not by standard mammography. Dynamic enhancement curves of benign and malignant tumors in contrast-enhanced mammography look similar to the curves known from gadolinium-enhanced magnetic resonance imaging. Nevertheless differentiation between malignant and benign tumors based on the enhancement patterns cannot be directly taken over from magnetic resonance imaging, as suggested by our initial results. The results are somewhat better when tumor enhancement relative to surrounding glandular tissue is used instead of absolute enhancement. CONCLUSION: The results of this preliminary study suggest that contrast-enhanced digital mammography is a potentially useful tool for the detection and the differentiation of benign and malignant breast lesions.

Animals↗
PubMed2004

Computerized interpretation of breast MRI: investigation of enhancement-variance dynamics.

The advantages of breast MRI using contrast agent Gd-DTPA in the diagnosis of breast cancer have been well established. The variation of interpretation criteria and absence of interpretation guidelines, however, is a major obstacle for applications of MRI in the routine clinical practice of breast imaging. Our study aims to increase the objectivity and reproducibility of breast MRI interpretation by developing an automated interpretation approach for ultimate use in computer-aided diagnosis. The database in this study contains 121 cases: 77 malignant and 44 benign masses as revealed by biopsy. Images were obtained using a T1-weighted 3D spoiled gradient echo sequence. After the acquisition of the precontrast series, Gd-DTPA contrast agent was injected intravenously by power injection with a dose of 0.2 mmol/kg. Five postcontrast series were then taken with a time interval of 60 s. Each series contained 64 coronal slices with a matrix of 128 x 256 pixels and an in-plane resolution of 1.25 x 1.25 mm2. Slice thickness ranged from 2 to 3 mm depending on breast size. The lesions were delineated by an experienced radiologist as well as independently by computer using an automatic volume-growing algorithm. Fourteen features that were extracted automatically from the lesions could be grouped into three categories based on (I) morphology, (II) enhancement kinetics, and (III) time course of enhancement-variation over the lesion. A stepwise feature selection procedure was employed to select an effective subset of features, which were then combined by linear discriminant analysis (LDA) into a discriminant score, related to the likelihood of malignancy. The classification performances of individual features and the combined discriminant score were evaluated with receiver operating characteristic (ROC) analysis. With the radiologist-delineated lesion contours, stepwise feature selection yielded four features and an Az value of 0.80 for the LDA in leave-one-out cross-validation testing. With the computer-segmented lesion volumes, it yielded six features and an Az value of 0.86 for the LDA in the leave-one-out testing.

Algorithms↗
PubMed2003

New contrast media designed for x-ray energy subtraction imaging in digital mammography.

RATIONALE AND OBJECTIVES: In contrast-enhanced dual-energy subtraction imaging 2 images acquired postcontrast media administration at different energies are subtracted to highlight structures hidden in the absence of contrast media. X-ray spectra of the newly developed digital full-field mammography units (GE Senographe 2000 D) are dominated by the emission lines of the Mo or Rh anodes. The K-edge of Zirconium (Zr) is flanked by these 2 emission lines. Thus, the attenuation of Zr should experience a pronounced change of attenuation in parallel with a change of anodes. Under clinically relevant conditions, the contrasting behavior of Zr should be compared with that of other elements having K-edge energies outside the window spanned by the 2 anode emission lines. METHODS: Solutions containing the contrasting elements Br, Y, Zr, I, and Gd were investigated for dual-energy subtraction in digital mammography with the 2 anode/filter settings (Mo/Mo and Rh/Rh). These solutions were investigated in phantom studies in the energy range conventionally used in mammography. Additionally, the contrasting behavior of Zr and I was compared in an in vivo study in rats. RESULTS: The sweeping over the K-edge by alternating between the Mo and Rh anodes increases the detection of Zr in energy subtraction imaging at constant high voltage. This procedure does not lead to sufficient contrast enhancement for iodine-based contrast media which become detectable by increasing the high voltage to 40-49 kV. CONCLUSION: The instrumental and physical data outlined predestine Zr as contrasting element with a high potential for energy subtraction imaging in digital mammography in the energy range conventionally applied.

Animals↗
PubMed2003

Brain imaging and proton magnetic resonance spectroscopy in patients with phenylketonuria.

Magnetic resonance imaging studies in patients with phenylketonuria (PKU) revealed white matter alterations that correlated to most recent blood phenylalanine (Phe) concentrations as well as to brain Phe concentrations measured by magnetic resonance spectroscopy. The clinical significance of these changes is unknown. Magnetic resonance imaging data thus have no impact on therapeutic recommendations for adolescents and adults with PKU. Kinetic investigations of patients by magnetic resonance spectroscopy showed differences in brain Phe concentrations despite similar blood Phe levels. These were influenced by interindividual variations of blood-brain barrier Phe transport constants and by variations of the individual brain Phe consumption rate. Blood-brain barrier Phe transport characteristics as well as brain Phe consumption rates thus seem to be causative factors for the individual outcome in PKU.

Blood-Brain Barrier↗
PubMed2002

Breast MR imaging with high spectral and spatial resolutions: preliminary experience.

The authors evaluated magnetic resonance (MR) imaging with high spectral and spatial resolutions (HSSR) of water and fat in breasts of healthy volunteers (n = 6) and women with suspicious lesions (n = 6). Fat suppression, edge delineation, and image texture were improved on MR images derived from HSSR data compared with those on conventional MR images. HSSR MR imaging data acquired before and after contrast medium injection showed spectrally inhomogeneous changes in the water resonances in small voxels that were not detectable with conventional MR imaging.

Adult↗