Human Brain MRI Research Articles

Mindboggle: a scatterbrained approach to automate brain labeling

Mindboggle ( http://www.binarybottle.com/mindboggle.html) is a fully automated, feature matching approach to label cortical structures and activity anatomically in human brain MRI data. This approach does not assume that the existence of component structures and their relative spatial relationship is preserved from brain to brain, but instead disassembles a labeled atlas and reassembles its pieces to match corresponding pieces in an unlabeled subject brain before labeling. Mindboggle: (1) converts linearly coregistered subject and atlas MRI data into sulcus pieces, (2) matches each atlas piece with a combination of subject pieces by minimizing a cost function, (3) transforms atlas label boundaries to the matching subject pieces, (4) warps atlas labels to their transformed boundaries, and (5) propagates labels to fill remaining gaps in a mask derived from the subject brain. We compared Mindboggle with four registration methods: linear registration, and nonlinear registration using SPM2, AIR, and ANIMAL. Automated labeling by all of the nonlinear methods was found to be at least comparable with linear registration. Mindboggle outperformed every other method, as measured by the agreement between overlapping atlas labels and manually assigned subject labels, with respect to the union or the intersection of voxels. After applying the same procedure that Mindboggle uses to fill a subject's segmented gray matter mask with labels (step 5), the results of the other methods improved. However, after performing a one-way ANOVA (and Tukey's honestly significant difference criterion) in a multiple comparison between the results obtained by the different methods, Mindboggle was still found to be the only nonlinear method whose labeling performance was significantly better than that of linear registration or SPM2. Further advantages to Mindboggle include a high degree of robustness against image artifacts, poor image quality, and incomplete brain data. We tested the latter hypothesis by conducting all of the tests again, this time registering the atlas to an artificially lesioned version of itself, and found that Mindboggle was the only method whose performance did not degrade significantly as the lesion size increased.

Improving tissue segmentation of human brain MRI through preprocessing by the Gegenbauer reconstruction method

The Gegenbauer image reconstruction method, previously shown to improve the quality of magnetic resonance images, is utilized in this study as a segmentation preprocessing step. It is demonstrated that, for all simulated and real magnetic resonance images used in this study, the Gegenbauer reconstruction method improves the accuracy of segmentation. Although it is more desirable to use the k-space data for the Gegenbauer reconstruction method, only information acquired from MR images is necessary for the reconstruction, making the procedure completely self-contained and viable for all human brain segmentation algorithms.

Design of a SENSE‐optimized high‐sensitivity MRI receive coil for brain imaging

An 8-channel receive-only detector array was developed for SENSE MRI of human brain. The coil geometry was based on a gapped element design and used ultra-high impedance preamplifiers for mutual decoupling of the elements. Computer simulations of the electric and magnetic fields showed that excellent signal-to-noise ratio (SNR) and SENSE performance could be achieved by placing the coil elements close to the head and maintaining a substantial gap between the elements. Measurements with a 1.5 T prototype coil showed a 2.7-fold improvement of the SNR averaged over the brain compared to a conventional quadrature birdcage receive coil and an average geometrical noise amplification factor (g-value) of 1.06 and 1.38 for rate-2 and rate-3 SENSE, respectively.

Half-Fourier single-shot STEAM MRI.

As a high-speed imaging technique based on stimulated echoes single-shot STEAM MRI is insensitive to chemical shift artifacts and magnetic susceptibility differences. The achievable signal-to-noise ratio (SNR) is limited by the fact that high flip angles of the read-out excitation pulses cause a steep decay of the stimulated echo train and therefore degrade the point-spread function of the resulting image. The present work investigates the use of half-Fourier phase encoding which weakens the flip angle constraint by reducing the number of necessary excitations. Single-shot STEAM MRI of the normal human brain at 2.0 T demonstrates that half-Fourier versions either reduce the measurement time by almost a factor of two without sacrificing the SNR or increase the SNR by about 40% while keeping the measurement time constant.

Functional MRI of Human Brain during Breath Holding by BOLD and FAIR Techniques

BOLD (blood oxygenation level-dependent) and FAIR (flow-sensitive alternating inversion recovery) imaging techniques were used to investigate the oxygenation and hemodynamic responses of human brain during repeated challenges of breath holding and prolonged single breath holding. The effects of different breathing techniques on BOLD and FAIR image contrasts were carefully examined. With a periodic breath-holding paradigm of 30 s, global changes in gray matter were observable both in T*2-weighted and FAIR images. T*2-weighted images showed 1–4% relative signal intensity increases, while FAIR images demonstrated relative cerebral blood flow (CBF) increase up to 30–70%. The activated pixels depicted in FAIR images were about three times less than those seen in T*2-weighted images. With prolonged breath holding, it was observed that signal intensities in T*2-weighted and FAIR images were dependent on the breathing techniques used. Breath holding after expiration gave rise to immediate signal intensity increases in T*2-weighted and FAIR images, whereas breath holding performed after deep inspiration signals showed a biphasic change both in flow and T*2-weighted. T*2-weighted and FAIR signals showed a transient decrease before rising above the baseline level.

MRI of "diffusion" in the human brain: new results using a modified CE-FAST sequence.

"Diffusion-weighted"MRI in the normal human brain and in a patient with a cerebral metastasis is demonstrated. The method employed was a modified CE-FAST sequence with imaging times of only 6-10 s using a conventional 1.5-T whole-body MRI system (Siemens Magnetom). As with previous phantom and animal studies, the use of strong gradients together with macroscopic motions in vivo causes unavoidable artifacts in diffusion-weighted images of the human brain. While these artifacts are shown to be considerably reduced by averaging of 8-16 images, the resulting diffusion contrast is compromised by unknown signal losses due to motion.