Andre van der Kouwe

Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain

We present a technique for automatically assigning a neuroanatomical label to each voxel in an MRI volume based on probabilistic information automatically estimated from a manually labeled training set. In contrast to existing segmentation procedures that only label a small number of tissue classes, the current method assigns one of 37 labels to each voxel, including left and right caudate, putamen, pallidum, thalamus, lateral ventricles, hippocampus, and amygdala. The classification technique employs a registration procedure that is robust to anatomical variability, including the ventricular enlargement typically associated with neurological diseases and aging. The technique is shown to be comparable in accuracy to manual labeling, and of sufficient sensitivity to robustly detect changes in the volume of noncortical structures that presage the onset of probable Alzheimers disease.

Sequence-independent segmentation of magnetic resonance images

We present a set of techniques for embedding the physics of the imaging process that generates a class of magnetic resonance images (MRIs) into a segmentation or registration algorithm. This results in substantial invariance to acquisition parameters, as the effect of these parameters on the contrast properties of various brain structures is explicitly modeled in the segmentation. In addition, the integration of image acquisition with tissue classification allows the derivation of sequences that are optimal for segmentation purposes. Another benefit of these procedures is the generation of probabilistic models of the intrinsic tissue parameters that cause MR contrast (e.g., T1, proton density, T2*), allowing access to these physiologically relevant parameters that may change with disease or demographic, resulting in nonmorphometric alterations in MR images that are otherwise difficult to detect. Finally, we also present a high band width multiecho FLASH pulse sequence that results in high signal-to-noise ratio with minimal image distortion due to B0 effects. This sequence has the added benefit of allowing the explicit estimation of T2* and of reducing test-retest intensity variability.

Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer.

In vivo MRI-derived measurements of human cerebral cortex thickness are providing novel insights into normal and abnormal neuroanatomy, but little is known about their reliability. We investigated how the reliability of cortical thickness measurements is affected by MRI instrument-related factors, including scanner field strength, manufacturer, upgrade and pulse sequence. Several data processing factors were also studied. Two test-retest data sets were analyzed: 1) 15 healthy older subjects scanned four times at 2-week intervals on three scanners; 2) 5 subjects scanned before and after a major scanner upgrade. Within-scanner variability of global cortical thickness measurements was <0.03 mm, and the point-wise standard deviation of measurement error was approximately 0.12 mm. Variability was 0.15 mm and 0.17 mm in average, respectively, for cross-scanner (Siemens/GE) and cross-field strength (1.5 T/3 T) comparisons. Scanner upgrade did not increase variability nor introduce bias. Measurements across field strength, however, were slightly biased (thicker at 3 T). The number of (single vs. multiple averaged) acquisitions had a negligible effect on reliability, but the use of a different pulse sequence had a larger impact, as did different parameters employed in data processing. Sample size estimates indicate that regional cortical thickness difference of 0.2 mm between two different groups could be identified with as few as 7 subjects per group, and a difference of 0.1 mm could be detected with 26 subjects per group. These results demonstrate that MRI-derived cortical thickness measures are highly reliable when MRI instrument and data processing factors are controlled but that it is important to consider these factors in the design of multi-site or longitudinal studies, such as clinical drug trials.

Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data

Longitudinal and multi-site clinical studies create the imperative to characterize and correct technological sources of variance that limit image reproducibility in high-resolution structural MRI studies, thus facilitating precise, quantitative, platform-independent, multi-site evaluation. In this work, we investigated the effects that imaging gradient non-linearity have on reproducibility of multi-site human MRI. We applied an image distortion correction method based on spherical harmonics description of the gradients and verified the accuracy of the method using phantom data. The correction method was then applied to the brain image data from a group of subjects scanned twice at multiple sites having different 1.5 T platforms. Within-site and across-site variability of the image data was assessed by evaluating voxel-based image intensity reproducibility. The image intensity reproducibility of the human brain data was significantly improved with distortion correction, suggesting that this method may offer improved reproducibility in morphometry studies. We provide the source code for the gradient distortion algorithm together with the phantom data.

MRI-derived measurements of human subcortical, ventricular and intracranial brain volumes: Reliability effects of scan sessions, acquisition sequences, data analyses, scanner upgrade, scanner vendors and field strengths

Automated MRI-derived measurements of in-vivo human brain volumes provide novel insights into normal and abnormal neuroanatomy, but little is known about measurement reliability. Here we assess the impact of image acquisition variables (scan session, MRI sequence, scanner upgrade, vendor and field strengths), FreeSurfer segmentation pre-processing variables (image averaging, B1 field inhomogeneity correction) and segmentation analysis variables (probabilistic atlas) on resultant image segmentation volumes from older (n=15, mean age 69.5) and younger (both n=5, mean ages 34 and 36.5) healthy subjects. The variability between hippocampal, thalamic, caudate, putamen, lateral ventricular and total intracranial volume measures across sessions on the same scanner on different days is less than 4.3% for the older group and less than 2.3% for the younger group. Within-scanner measurements are remarkably reliable across scan sessions, being minimally affected by averaging of multiple acquisitions, B1 correction, acquisition sequence (MPRAGE vs. multi-echo-FLASH), major scanner upgrades (Sonata-Avanto, Trio-TrioTIM), and segmentation atlas (MPRAGE or multi-echo-FLASH). Volume measurements across platforms (Siemens Sonata vs. GE Signa) and field strengths (1.5 T vs. 3 T) result in a volume difference bias but with a comparable variance as that measured within-scanner, implying that multi-site studies may not necessarily require a much larger sample to detect a specific effect. These results suggest that volumes derived from automated segmentation of T1-weighted structural images are reliable measures within the same scanner platform, even after upgrades; however, combining data across platform and across field-strength introduces a bias that should be considered in the design of multi-site studies, such as clinical drug trials. The results derived from the young groups (scanner upgrade effects and B1 inhomogeneity correction effects) should be considered as preliminary and in need for further validation with a larger dataset.

Brain Morphometry with Multiecho MPRAGE

In brain morphometry studies using magnetic resonance imaging, several scans with a range of contrasts are often collected. The images may be locally distorted due to imperfect shimming in regions where magnetic susceptibility changes rapidly, and all scans may not be distorted in the same way. In multispectral studies it is critical that the edges of structures align precisely across all contrasts. The MPRAGE (MPR) sequence has excellent contrast properties for cortical segmentation, while multiecho FLASH (MEF) provides better contrast for segmentation of subcortical structures. Here, a multiecho version of the MPRAGE (MEMPR) is evaluated using SIENA and FreeSurfer. The higher bandwidth of the MEMPR results in reduced distortions that match those of the MEF while the SNR is recovered by combining the echoes. Accurate automatic identification of cortex and thickness estimation is frustrated by the presence of dura adjacent to regions such as the entorhinal cortex. In the typical MPRAGE protocol, dura and cortex are approximately isointense. However, dura has substantially smaller T2* than cortex. This information is represented in the multiple echoes of the MEMPR. An algorithm is described for correcting cortical thickness using T2*. It is shown that with MEMPR, SIENA generates more reliable percentage brain volume changes and FreeSurfer generates more reliable cortical models. The regions where cortical thickness is affected by dura are shown. MEMPR did not substantially improve subcortical segmentations. Since acquisition time is the same for MEMPR as for MPRAGE, and it has better distortion properties and additional T2* information, MEMPR is recommended for morphometry studies.

Toward Implementing an MRI-Based PET Attenuation-Correction Method for Neurologic Studies on the MR-PET Brain Prototype

Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype. Methods: The focus was on the problem of bone–air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the radiofrequency coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI–based AC method were compared with the PET images that had been reconstructed using a CT-based AC method. Results: Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm−1 to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the radiofrequency coil attenuation can cause large underestimations (i.e., ≤50%) in the reconstructed images. Furthermore, the coil location in the PET field of view has to be accurately known. High-quality bone–air segmentation can be performed using the DUTE data. The PET images obtained using the DUTE MRI– and CT-based AC methods compare favorably in most of the brain structures. Conclusion: A DUTE MRI–based AC method considering all these factors was implemented. Preliminary results suggest that this method could potentially be as accurate as the segmented CT method and could be used for quantitative neurologic MR-PET studies.

Real-time rigid body motion correction and shimming using cloverleaf navigators

Subject motion during scanning can greatly reduce MRI image quality and is a major reason for discarding data in both clinical and research scanning. The quality of the high‐resolution structural data used for morphometric analysis is especially compromised by subject movement because high‐resolution scans are of longer duration. A method is presented that measures and corrects rigid body motion and associated first‐order shim changes in real time, using a pulse sequence with embedded cloverleaf navigators and a feedback control mechanism. The procedure requires a 12‐s preliminary mapping scan. A single‐path, 4.2‐ms cloverleaf navigator is inserted every repetition time (TR) after the readout of a 3D fast low‐angle shot (FLASH) sequence, requiring no additional RF pulses and minimally impacting scan duration. Every TR, a rigid body motion estimate is made and a correction is fed back to adjust the gradients and shim offsets. Images are corrected and reconstructed on the scanner computer for immediate access. Correction for between‐scan motion can be accomplished by using the same reference map for each scan repetition. Human and phantom tests demonstrated a consistent improvement in image quality if motion occurred during the acquisition. Magn Reson Med, 2006.

Volumetric navigators for prospective motion correction and selective reacquisition in neuroanatomical MRI.

We introduce a novel method of prospectively compensating for subject motion in neuroanatomical imaging. Short three‐dimensional echo‐planar imaging volumetric navigators are embedded in a long three‐dimensional sequence, and the resulting image volumes are registered to provide an estimate of the subjects location in the scanner at a cost of less than 500 ms, ∼ 1% change in contrast, and ∼3% change in intensity. This time fits well into the existing gaps in sequences routinely used for neuroimaging, thus giving a motion‐corrected sequence with no extra time required. We also demonstrate motion‐driven selective reacquisition of k‐space to further compensate for subject motion. We perform multiple validation experiments to evaluate accuracy, navigator impact on tissue intensity/contrast, and the improvement in final output. The complete system operates without adding additional hardware to the scanner and requires no external calibration, making it suitable for high‐throughput environments. Magn Reson Med, 2012.

Cannabis Use Is Quantitatively Associated with Nucleus Accumbens and Amygdala Abnormalities in Young Adult Recreational Users

Marijuana is the most commonly used illicit drug in the United States, but little is known about its effects on the human brain, particularly on reward/aversion regions implicated in addiction, such as the nucleus accumbens and amygdala. Animal studies show structural changes in brain regions such as the nucleus accumbens after exposure to Δ9-tetrahydrocannabinol, but less is known about cannabis use and brain morphometry in these regions in humans. We collected high-resolution MRI scans on young adult recreational marijuana users and nonusing controls and conducted three independent analyses of morphometry in these structures: (1) gray matter density using voxel-based morphometry, (2) volume (total brain and regional volumes), and (3) shape (surface morphometry). Gray matter density analyses revealed greater gray matter density in marijuana users than in control participants in the left nucleus accumbens extending to subcallosal cortex, hypothalamus, sublenticular extended amygdala, and left amygdala, even after controlling for age, sex, alcohol use, and cigarette smoking. Trend-level effects were observed for a volume increase in the left nucleus accumbens only. Significant shape differences were detected in the left nucleus accumbens and right amygdala. The left nucleus accumbens showed salient exposure-dependent alterations across all three measures and an altered multimodal relationship across measures in the marijuana group. These data suggest that marijuana exposure, even in young recreational users, is associated with exposure-dependent alterations of the neural matrix of core reward structures and is consistent with animal studies of changes in dendritic arborization.