Saadallah Ramadan

Diffusion-weighted Imaging of the Breast: Principles and Clinical Applications

Diffusion-weighted imaging provides a novel contrast mechanism in magnetic resonance (MR) imaging and has a high sensitivity in the detection of changes in the local biologic environment. A significant advantage of diffusion-weighted MR imaging over conventional contrast material-enhanced MR imaging is its high sensitivity to change in the microscopic cellular environment without the need for intravenous contrast material injection. Approaches to the assessment of diffusion-weighted breast imaging findings include assessment of these data alone and interpretation of the data in conjunction with T2-weighted imaging findings. In addition, the analysis of apparent diffusion coefficient (ADC) value can be undertaken either in isolation or in combination with diffusion-weighted and T2-weighted imaging. Most previous studies have evaluated ADC value alone; however, overlap in the ADC values of malignant and benign disease has been observed. This overlap may be partly due to selection of b value, which can influence the concomitant effect of perfusion and emphasize the contribution of multicomponent model influences. The simultaneous assessment of diffusion-weighted and T2-weighted imaging data and ADC value has the potential to improve specificity. In addition, the use of diffusion-weighted imaging in a standard breast MR imaging protocol may heighten sensitivity and thereby improve diagnostic accuracy. Standardization of diffusion-weighted imaging parameters is needed to allow comparison of multicenter studies and assessment of the clinical utility of diffusion-weighted imaging and ADC values in breast evaluation.

Neurospectroscopy: The Past, Present and Future

Neurospectroscopy with respect to its past, present and future has been reported. It is helpful to understand the biochemical relevance of each of the major resonances in the brain spectra. Lactate is seen in the spectrum as a doublet at 1.33 ppm. Healthy tissues do not have sufficient lactate to be detectable by MRS. Neurospectroscopy provides information on brain constituents. Pattern recognition blends pattern recognition techniques and multivariate statistical analysis with solid, comprehensive software engineering practices. Neurospectroscopy offers a window into the chemistry of the human brain, reporting on normal mechanisms as well as the changes that occur with degeneration, disease, pain, cancer, and infection. Alzheimers disease can now be identified much earlier than before offering earlier management before the disease progresses. The long-term effect of shaken baby syndrome and traumatic brain injury can be gauged by neurospectroscopy.

Glutamate and glutamine: a review of in vivo MRS in the human brain

Our understanding of the roles that the amino acids glutamate (Glu) and glutamine (Gln) play in the mammalian central nervous system has increased rapidly in recent times. Many conditions are known to exhibit a disturbance in Glu–Gln equilibrium, and the exact relationships between these changed conditions and these amino acids are not fully understood. This has led to increased interest in Glu/Gln quantitation in the human brain in an array of conditions (e.g. mental illness, tumor, neuro‐degeneration) as well as in normal brain function.

Spectroscopic imaging with improved gradient modulated constant adiabaticity pulses on high-field clinical scanners.

The purpose of this work was to design and implement constant adiabaticity gradient modulated pulses that have improved slice profiles and reduced artifacts for spectroscopic imaging on 3T clinical scanners equipped with standard hardware. The newly proposed pulses were designed using the gradient offset independent adiabaticity (GOIA, Tannus and Garwood[13]) method using WURST modulation for RF and gradient waveforms. The GOIA-WURST pulses were compared with GOIA-HSn (GOIA based on nth-order hyperbolic secant) and FOCI (frequency offset corrected inversion) pulses of the same bandwidth and duration. Numerical simulations and experimental measurements in phantoms and healthy volunteers are presented. GOIA-WURST pulses provide improved slice profile that have less slice smearing for off-resonance frequencies compared to GOIA-HSn pulses. The peak RF amplitude of GOIA-WURST is much lower (40% less) than FOCI but slightly higher (14.9% more) to GOIA-HSn. The quality of spectra as shown by the analysis of lineshapes, eddy currents artifacts, subcutaneous lipid contamination and SNR is improved for GOIA-WURST. GOIA-WURST pulse tested in this work shows that reliable spectroscopic imaging could be obtained in routine clinical setup and might facilitate the use of clinical spectroscopy.

Proton MRS of the breast in the clinical setting.

Information for determining whether a primary breast lesion is invasive and its receptor status and grade can be obtained before surgery by performing proton MRS on a fine‐needle aspiration biopsy (FNAB) specimen and analyzing the MRS information by a pattern recognition method. Two‐dimensional MRS, on either specimens or cells, allows the unambiguous assignment of most resonances. When correlated with the spectral regions selected by the pattern recognition method, there are strong indications for the biochemical markers responsible for prognostic information of invasive capacity and metastatic spread. Spectral assignments and biological correlations can be made using cell models. In vivo MRS can distinguish invasive from benign lesions. This pathological distinction can be made from the presence of resonances at discrete frequencies. To achieve this level of spectral resolution and signal‐to‐noise ratio, there are stringent requirements when acquiring and processing the data. The challenge now is to implement two‐dimensional MRS in vivo. Until this is realized, the combination of in vivo MR, for diagnosis and spatial location, and MRS, for image‐guided biopsy to provide information on tumor spread, promises to provide a higher level of preoperative diagnosis than previously achieved. Copyright

Neuro magnetic resonance spectroscopy using wavelet decomposition and statistical testing identifies biochemical changes in people with spinal cord injury and pain.

Spinal cord injury (SCI) can be accompanied by chronic pain, the mechanisms for which are poorly understood. Here we report that magnetic resonance spectroscopy measurements from the brain, collected at 3T, and processed using wavelet-based feature extraction and classification algorithms, can identify biochemical changes that distinguish control subjects from subjects with SCI as well as subdividing the SCI group into those with and without chronic pain. The results from control subjects (n=10) were compared to those with SCI (n=10). The SCI cohort was made up of subjects with chronic neuropathic pain (n=5) and those without chronic pain (n=5). The wavelet-based decomposition of frequency domain MRS signals employs statistical significance testing to identify features best suited to discriminate different classes. Moreover, the features benefit from careful attention to the post-processing of the spectroscopy data prior to the comparison of the three cohorts. The spectroscopy data, from the thalamus, best distinguished control subjects without SCI from those with SCI with a sensitivity and specificity of 0.9 (Percentage of Correct Classification). The spectroscopy data obtained from the prefrontal cortex and anterior cingulate cortex both distinguished between SCI subjects with chronic neuropathic pain and those without pain with a sensitivity and specificity of 1.0. In this study, where two underlying mechanisms co-exist (i.e. SCI and pain), the thalamic changes appear to be linked more strongly to SCI, while the anterior cingulate cortex and prefrontal cortex changes appear to be specifically linked to the presence of pain.

MR image segmentation of the knee bone using phase information

Magnetic resonance (MR) imaging is a widely available and well accepted non invasive imaging technique. Development of automatic and semi-automatic techniques to analyse MR images has been the focus of much research and numerous publications. However, most of this research only uses the magnitude of the acquired complex MR signal, discarding the phase information. In MR, the phase relates to the magnetic properties of tissues, information which is not found in the magnitude signal. As a result, phase is a complement to the magnitude signal and can improve the segmentation and analysis of MR images. In this paper, we consider the automatic classification of textured tissues in 3D MRI. Specifically, we include features extracted from the phase of the MR signal to improve texture discrimination in the bone segmentation. Our approach does not require phase unwrapping, with the MR signal processed in its complex form. The extra information extracted from the phase provides better segmentation, compared to only using magnitude features. The segmentation approach is integrated within a novel multiscale scheme, designed to improve the speed of pixel based classification algorithms, such as support vector machines. An order of magnitude increase is obtained, by reducing the number of pixels that need to be classified.

Investigation of breast cancer using two-dimensional MRS

Proton (1H) MRS enables non‐invasive biochemical assay with the potential to characterize malignant, benign and healthy breast tissues. In vitro studies using perchloric acid extracts and ex vivo magic angle spinning spectroscopy of intact biopsy tissues have been used to identify detectable metabolic alterations in breast cancer. The challenges of 1H MRS in vivo include low sensitivity and significant overlap of resonances due to limited chemical shift dispersion and significant inhomogeneous broadening at most clinical magnetic field strengths. Improvement in spectral resolution can be achieved in vivo and in vitro by recording the MR spectra spread over more than one dimension, thus facilitating unambiguous assignment of metabolite and lipid resonances in breast cancer. This article reviews the recent progress with two‐dimensional MRS of breast cancer in vitro, ex vivo and in vivo. The discussion includes unambiguous detection of saturated and unsaturated fatty acids, as well as choline‐containing groups such as free choline, phosphocholine, glycerophosphocholine and ethanolamines using two‐dimensional MRS. In addition, characterization of invasive ductal carcinomas and healthy fatty/glandular breast tissues non‐invasively using the classification and regression tree (CART) analysis of two‐dimensional MRS data is reviewed. Copyright

Echo planar correlated spectroscopic imaging: implementation and pilot evaluation in human calf in vivo.

Exploiting the speed benefits of echo‐planar imaging (EPI), the echo‐planar spectroscopic imaging (EPSI) sequence facilitates recording of one spectral and two to three spatial dimensions faster than the conventional magnetic resonance spectroscopic imaging (MRSI). A novel four dimensional (4D) echo‐planar correlated spectroscopic imaging (EP‐COSI) was implemented on a whole body 3 T MRI scanner combining two spectral with two spatial encodings. Similar to EPSI, the EP‐COSI sequence used a bipolar spatial read‐out train facilitating simultaneous spatial and spectral encoding, and the conventional phase and spectral encodings for the other spatial and indirect spectral dimensions, respectively. Multiple 2D correlated spectroscopy (COSY) spectra were recorded over the spatially resolved volume of interest (VOI) localized by a train of three slice‐selective radiofrequency (RF) pulses (90°–180°–90°). After the initial optimization using phantom solutions, the EP‐COSI data were recorded from the lower leg of eight healthy volunteers including one endurance trained volunteer. Pilot results showed acceptable spatial and spectral quality achievable using the EP‐COSI sequence. There was a detectable separation of cross peaks arising from the skeletal muscle intramyocellular lipids (IMCLs) and extramyocellular lipids (EMCLs) saturated and unsaturated pools. Residual dipolar interaction between the N‐methylene and N‐methyl protons of creatine/phosphocreatine (Cr/PCr) was also observed in the tibialis anterior region. Magn Reson Med, 2010.

Proton magnetic resonance spectroscopy of the central, transition and peripheral zones of the prostate: Assignments and correlation with histopathology

Proton magnetic resonance spectroscopy (MRS) is used to compare the chemistry of the transition, central and peripheral zones of the prostate. The assignments are made using two-dimensional correlated spectroscopy and the results compared with histopathology. The chemistry associated with benign prostatic hyperplasia (BPH), prostate intraepithelial neoplasia (PIN) and malignant biopsy tissues are described. There are distinct MR spectral patterns for glandular and stromal BPH, PIN and adenocarcinoma. Importantly, there are also different spectral patterns from BPH in the transitional and central zones when compared to BPH in the peripheral zone. A pattern recognition method is used to analyze the MR spectra from the biopsy specimens. The resultant mathematical classifiers generated a high level of accuracy (sensitivity and specificity of 100 and 97%). It was found that for this accuracy to be achieved, the classifiers need to be developed by comparing the spectra with specialist serial sectioned histopathology. With serial sectioned pathology the pattern recognition method was capable of identifying less than 5% of adenocarcinoma in a given piece of tissue. Many of the chemicals identified in the biopsy specimens are available for inspection from the prostate, in vivo, at 3 T.