Whole-body imaging at 7T: preliminary results.

The objective of this study was to investigate the feasibility of whole-body imaging at 7T. To achieve this objective, new technology and methods were developed. Radio frequency (RF) field distribution and specific absorption rate (SAR) were first explored through numerical modeling. A body coil was then designed and built. Multichannel transmit and receive coils were also developed and implemented. With this new technology in hand, an imaging survey of the "landscape" of the human body at 7T was conducted. Cardiac imaging at 7T appeared to be possible. The potential for breast imaging and spectroscopy was demonstrated. Preliminary results of the first human body imaging at 7T suggest both promise and directions for further development.

Source of low-frequency fluctuations in functional MRI signal.

PURPOSE: To investigate the source of native low-frequency fluctuations (LFF) in functional MRI (fMRI) signal. MATERIALS AND METHODS: Phase analysis was performed on tissue-segmented fMRI data acquired at systematically varying sampling rates. RESULTS: LFF in fMRI signal were both native and aliased in origin. Scanner instability did not contribute to native or aliased LFF. Aliased LFF arose from cardiorespiratory processes and head motion. Native LFF did not arise from cardiorespiratory processes, but did so, at least in part, from head motion. Motion correction reduced native LFF, but did not eliminate them. The residual native LFF in motion-corrected fMRI data showed a systematic phase difference among different tissue structures. The native LFF in fMRI signals of cerebral blood vessels and CSF were synchronous, and preceded those of gray and white matter, indicating that the vascular fluctuations lead the metabolic fluctuations. CONCLUSION: The primary physiologic source of native LFF in fMRI signal is vasomotion.

Adaptive pacing of visual stimulation for fMRI studies involving overt speech.

We report the development of an interactive approach to single-word language production studies in fMRI. The approach, adaptive pacing, involves real-time adjustment of stimulus presentation times based on individual subject performance timing and content. At the same time, it maintains a stochastic distribution of interstimulus intervals to avoid confounding task covariates with speech-related signal variance. Adaptive pacing of overt speech production is an example of a new class of paradigms that require an observational approach to data acquisition and benefit from a "time-aware" acquisition and processing environment. The advantages of adaptive pacing in fMRI of impaired subjects are expected to be the acquisition of more informative data per unit time, less contamination of data by correlates of non-language processes such as emotion, and facilitation of experiments that combine normal and impaired subjects.

Model assessment and model building in fMRI.

Model quality is rarely assessed in fMRI data analyses and less often reported. This may have contributed to several shortcomings in the current fMRI data analyses, including: (1) Model mis-specification, leading to incorrect inference about the activation-maps, SPM[t] and SPM[F]; (2) Improper model selection based on the number of activated voxels, rather than on model quality; (3) Under-utilization of systematic model building, resulting in the common but suboptimal practice of using only a single, pre-specified, usually over-simplified model; (4) Spatially homogenous modeling, neglecting the spatial heterogeneity of fMRI signal fluctuations; and (5) Lack of standards for formal model comparison, contributing to the high variability of fMRI results across studies and centers. To overcome these shortcomings, it is essential to assess and report the quality of the models used in the analysis. In this study, we applied images of the Durbin-Watson statistic (DW-map) and the coefficient of multiple determination (R(2)-map) as complementary tools to assess the validity as well as goodness of fit, i.e., quality, of models in fMRI data analysis. Higher quality models were built upon reduced models using classic model building. While inclusion of an appropriate variable in the model improved the quality of the model, inclusion of an inappropriate variable, i.e., model mis-specification, adversely affected it. Higher quality models, however, occasionally decreased the number of activated voxels, whereas lower quality or inappropriate models occasionally increased the number of activated voxels, indicating that the conventional approach to fMRI data analysis may yield sub-optimal or incorrect results. We propose that model quality maps become part of a broader package of maps for quality assessment in fMRI, facilitating validation, optimization, and standardization of fMRI result across studies and centers. Hum. Brain Mapping 20:227-238, 2003.

Segmentation of wall and plaque in in vitro vascular MR images.

Atherosclerosis leads to heart attack and stroke, which are major killers in the western world. These cardiovascular events frequently result from local rupture of vulnerable atherosclerotic plaque. Non-invasive assessment of plaque vulnerability would dramatically change the way in which atherosclerotic disease is diagnosed, monitored, and treated. In this paper, we report a computerized method for segmentation of arterial wall layers and plaque from high-resolution volumetric MR images. The method uses dynamic programming to detect optimal borders in each MRI frame. The accuracy of the results was tested in 62 T1-weighted MR images from six vessel specimens in comparison to borders manually determined by an expert observer. The mean signed border positioning errors for the lumen, internal elastic lamina, and external elastic lamina borders were -0.1 +/- 0.1, 0.0 +/- 0.1, and -0.1 +/- 0.1 mm, respectively. The presented wall layer segmentation approach is one of the first steps towards non-invasive assessment of plaque vulnerability in atherosclerotic subjects.

Dynamic magnetic resonance imaging of the female pelvis: the relationship with the Pelvic Organ Prolapse quantification staging system.

PURPOSE: Magnetic resonance imaging (MRI) was performed to determine anatomical correlations with respect to physical examination using the Pelvic Organ Prolapse (POP) staging system. In addition, the standard POP staging system was analyzed to obtain normative data and determine any risk factors for prolapse. MATERIALS AND METHODS: A total of 52 continent women 19 to 67 years old participated in our study. Pelvic MRI was performed at 1.5 Tesla. The vagina, bladder and rectum were opacified. Subjects performed pelvic floor contraction, relaxation and straining maneuvers for T1-weighted imaging. One-way analysis of variance, Fisher's exact test and multinomial logistic regression were used to analyze the data. RESULTS: POP stage is quantified from 0 to IV. Stage was 0 to II in 56%, 27% and 17% of cases. POP stage was not significantly influenced by the number of cesarean sections (p = 0.64) or smoking (p = 0.91) but the number of vaginal deliveries significantly correlated with stage. Women with 1 vaginal delivery were at increased risk for a stage I condition (p = 0.018), whereas those with more than 1 were at increased risk for stage II (p = 0.013). On MRI stages 0 versus I or II differed significantly in regard to bladder descent (p = 0.01 and <0.0001, respectively), while stages 0 versus I differed in regard to levator angle (p = 0.007). No significant staging differences were observed in regard to the posterior urethrovesical angle or stages I versus II with respect to all 3 MRI measurements. CONCLUSIONS: MRI appears to detect anatomically measurable changes in POP stage 0 versus other stages in regard to bladder descent and the levator angle and yet it is not sensitive enough to detect differences in stages I and II. It is not unusual for continent women to have a moderate degree of pelvic prolapse and previous vaginal delivery appears to increase this risk.