Assessment of early response to concurrent chemoradiotherapy in cervical cancer: value of diffusion-weighted and dynamic contrast-enhanced MR imaging.

Purpose: To investigate diffusion-weighted (DWI) and dynamic contrast-enhanced MR imaging (DCE-MRI) as early response predictors in cervical cancer patients who received concurrent chemoradiotherapy (CCRT).

Materials And Methods: Sixteen patients with cervical cancer underwent DWI and DCE-MRI before CCRT (preTx), at 1week (postT1) and 4weeks (postT2) after initiating treatment, and 1month after the end of treatment (postT3). At each point, apparent diffusion coefficient (ADC) and DCE-MRI parameters were measured in tumors and gluteus muscles (GM).

The principal of dynamic contrast enhanced MRI, the method of pharmacokinetic analysis, and its application in the head and neck region.

Many researchers have established the utility of the dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) in the differential diagnosis in the head and neck region, especially in the salivary gland tumors. The subjective assessment of the pattern of the time-intensity curve (TIC) or the simple quantification of the TIC, such as the time to peak enhancement (T(peak)) and the wash-out ratio (WR), is commonly used. Although the semiquantitative evaluations described above have been widely applied, they do not provide information on the underlying pharmacokinetic analysis in tissue.

Pharmacokinetic analysis based on dynamic contrast-enhanced MRI for evaluating tumor response to preoperative therapy for oral cancer.

Purpose: To evaluate whether a pharmacokinetic analysis is useful for monitoring the response of oral cancer to chemoradiotherapy (CRT).

Materials And Methods: Twenty-nine patients were included. They underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) before and after CRT.

Tumour hyperthermia and ablation in rats using a clinical MR-HIFU system equipped with a dedicated small animal set-up.

Purpose: We report on the design, performance, and specifications of a dedicated set-up for the treatment of rats on a clinical magnetic resonance high intensity focused ultrasound (MR-HIFU) system.

Materials And Methods: The small animal HIFU-compatible 4-channel MR receiver volume coil and animal support were designed as add-on to a clinical 3T Philips Sonalleve MR-HIFU system. Prolonged hyperthermia (T ≈ 42°C, 15 min) and thermal ablation (T = 65°C) was performed in vivo on subcutaneous rat tumours using 1.

Nosologic imaging of the brain: segmentation and classification using MRI and MRSI.

A new technique is presented to create nosologic images of the brain based on magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI). A nosologic image summarizes the presence of different tissues and lesions in a single image by color coding each voxel or pixel according to the histopathological class it is assigned to. The proposed technique applies advanced methods from image processing as well as pattern recognition to segment and classify brain tumors.

Automated planning of scan geometries in spine MRI scans.

Consistency of MR scan planning is very important for diagnosis, especially in multi-site trials and follow-up studies, where disease progress or response to treatment is evaluated. Accurate manual scan planning is tedious and requires skillful operators. On the other hand, automated scan planning is difficult due to relatively low quality of survey images ("scouts") and strict processing time constraints.

An automated quantitation of short echo time MRS spectra in an open source software environment: AQSES.

This paper describes a new quantitation method called AQSES for short echo time magnetic resonance spectra. This method is embedded in a software package available online from www.esat.

A low temperature embedding and section registration strategy for 3D image reconstruction of the rat brain from autoradiographic sections.

In studies on animal models of human brain pathologies, three-dimensional reconstruction from histological sections is particularly useful when assessing the morphologic, functional and biochemical changes induced by pathology. It allows assessing lesion heterogeneity in planes different from the cutting plane and allows correlating the histology with images obtained in vivo, such as by means of magnetic resonance imaging. To create a 3D volume from autoradiographic sections with minimal distortion, both cryosectioning as well as section registration need to be optimal.

Development of a decision support system for diagnosis and grading of brain tumours using in vivo magnetic resonance single voxel spectra.

A computer-based decision support system to assist radiologists in diagnosing and grading brain tumours has been developed by the multi-centre INTERPRET project. Spectra from a database of 1H single-voxel spectra of different types of brain tumours, acquired in vivo from 334 patients at four different centres, are clustered according to their pathology, using automated pattern recognition techniques and the results are presented as a two-dimensional scatterplot using an intuitive graphical user interface (GUI). Formal quality control procedures were performed to standardize the performance of the instruments and check each spectrum, and teams of expert neuroradiologists, neurosurgeons, neurologists and neuropathologists clinically validated each case.

Combination of feature-reduced MR spectroscopic and MR imaging data for improved brain tumor classification.

The purpose of this paper is to evaluate the effect of the combination of magnetic resonance spectroscopic imaging (MRSI) data and magnetic resonance imaging (MRI) data on the classification result of four brain tumor classes. Suppressed and unsuppressed short echo time MRSI and MRI were performed on 24 patients with a brain tumor and four volunteers. Four different feature reduction procedures were applied to the MRSI data: simple quantitation, principal component analysis, independent component analysis and LCModel.

A chemometric approach for brain tumor classification using magnetic resonance imaging and spectroscopy.

A new classification approach was developed to improve the noninvasive diagnosis of brain tumors. Within this approach, information is extracted from magnetic resonance imaging and spectroscopy data, from which the relative location and distribution of selected tumor classes in feature space can be calculated. This relative location and distribution is used to select the best information extraction procedure, to identify overlapping tumor classes, and to calculate probabilities of class membership.