Optimization of tractography of the optic radiations.

Imaging and delineation of the optic radiations (OpRs) remains challenging, despite repeated attempts to achieve reliable validated tractography of this complex structure. Previous studies have used varying methods to generate representations of the OpR which differ markedly from one another and, frequently, from the OpR's known structure. We systematically examined the influence of a key variable that has differed across previous studies, the tractography seed region, in 13 adult participants (nine male; mean age 31 years; SD 8.7 years; range 16-47). First, we compared six seed regions at the lateral geniculate nucleus (LGN) and sagittal stratum based on the literature and known OpR anatomy. Three of the LGN regions seeded streamlines consistent with the OpR's three "bundles," whereas a fourth seeded streamlines consistent with each of the three bundles. The remaining two generated OpR streamlines unreliably and inconsistently. Two stratum regions seeded the radiations. This analysis identified a set of optimal regions of interest (ROI) for seeding OpR tractography and important inclusion and exclusion ROI. An optimized approach was then used to seed LGN regions to the stratum. The radiations, including streamlines consistent with Meyer's Loop, were streamlined in all cases. Streamlines extended 0.2 ± 2.4 mm anterior to the tip of the anterior horn of the lateral ventricle. These data suggest some existing approaches likely seed representations of the OpR that are visually plausible but do not capture all OpR components, and that using an optimized combination of regions seeded previously allows optimal mapping of this complex structure.

Incidence of HER2-expressing brain metastases in patients with HER2-null breast cancer: a matched case analysis.

The HER2-directed antibody-drug conjugate trastuzumab deruxtecan is active against lower levels of HER2 expression than prior-generation therapies. The rate of HER2 expression in brain metastases among patients with initially HER2-null breast cancer is undefined, and receptor discordance in advanced breast cancer with brain metastases may underestimate CNS response potential in the absence of brain metastasis sampling. In this cohort study including 136 patients with 401 samples scored according to ASCO/CAP guidelines, 15/28 patients (54%) with HER2-null primary breast cancer have detectable HER2 expression in subsequently resected brain metastases, a significant discordant population.

White matter mean diffusivity correlates with myelination in tuberous sclerosis complex.

OBJECTIVE: Diffusion tensor imaging (DTI) of the white matter is a biomarker for neurological disease burden in tuberous sclerosis complex (TSC). To clarify the basis of abnormal diffusion in TSC, we correlated ex vivo high-resolution diffusion imaging with histopathology in four tissue types: cortex, tuber, perituber, and white matter. METHODS: Surgical specimens of three children with TSC were scanned in a 3T or 7T MRI with a structural image isotropic resolution of 137-300 micron, and diffusion image isotropic resolution of 270-1,000 micron. We stained for myelin (luxol fast blue, LFB), gliosis (glial fibrillary acidic protein, GFAP), and neurons (NeuN) and registered the digitized histopathology slides (0.686 micron resolution) to MRI for visual comparison. We then performed colocalization analysis in four tissue types in each specimen. Finally, we applied a linear mixed model (LMM) for pooled analysis across the three specimens. RESULTS: In white matter and perituber regions, LFB optical density measures correlated with fractional anisotropy (FA) and inversely with mean diffusivity (MD). In white matter only, GFAP correlated with MD, and inversely with FA. In tubers and in the cortex, there was little variation in mean LFB and GFAP signal intensity, and no correlation with MRI metrics. Neuronal density correlated with MD. In the analysis of the combined specimens, the most robust correlation was between white matter MD and LFB metrics. INTERPRETATION: In TSC, diffusion imaging abnormalities in microscopic tissue types correspond to specific histopathological markers. Across all specimens, white matter diffusivity correlates with myelination.

Analytic quantification of bias and variance of coil sensitivity profile estimators for improved image reconstruction in MRI.

Magnetic resonance (MR) imaging provides a unique in-vivo capability of visualizing tissue in the human brain non-invasively, which has tremendously improved patient care over the past decades. However, there are still prominent artifacts, such as intensity inhomogeneities due to the use of an array of receiving coils (RC) to measure the MR signal or noise amplification due to accelerated imaging strategies. It is critical to mitigate these artifacts for both visual inspection and quantitative analysis. The cornerstone to address this issue pertains to the knowledge of coil sensitivity profiles (CSP) of the RCs, which describe how the measured complex signal decays with the distance to the RC. Existing methods for CSP estimation share a number of limitations: (i) they primarily focus on CSP magnitude, while it is known that the solution to the MR image reconstruction problem involves complex CSPs and (ii) they only provide point estimates of the CSPs, which makes the task of optimizing the parameters and acquisition protocol for their estimation difficult. In this paper, we propose a novel statistical framework for estimating complex-valued CSPs. We define a CSP estimator that uses spatial smoothing and additional body coil data for phase normalization. The main contribution is to provide detailed information on the statistical distribution of the CSP estimator, which yields automatic determination of the optimal degree of smoothing for ensuring minimal bias and provides guidelines to the optimal acquisition strategy.

Tubers are neither static nor discrete: Evidence from serial diffusion tensor imaging.

OBJECTIVE: To assess the extent and evolution of tissue abnormality of tubers, perituber tissue, and normal-appearing white matter (NAWM) in patients with tuberous sclerosis complex using serial diffusion tensor imaging. METHODS: We applied automatic segmentation based on a combined global-local intensity mixture model of 3T structural and 35 direction diffusion tensor MRIs (diffusion tensor imaging) to define 3 regions: tuber tissue, an equal volume perituber rim, and the remaining NAWM. For each patient, scan, lobe, and tissue type, we analyzed the averages of mean diffusivity (MD) and fractional anisotropy (FA) in a generalized additive mixed model. RESULTS: Twenty-five patients (mean age 5.9 years; range 0.5-24.5 years) underwent 2 to 6 scans each, totaling 70 scans. Average time between scans was 1.2 years (range 0.4-2.9). Patient scans were compared with those of 73 healthy controls. FA values were lowest, and MD values were highest in tubers, next in perituber tissue, then in NAWM. Longitudinal analysis showed a positive (FA) and negative (MD) correlation with age in tubers, perituber tissue, and NAWM. All 3 tissue types followed a biexponential developmental trajectory, similar to the white matter of controls. An additional qualitative analysis showed a gradual transition of diffusion values across the tissue type boundaries. CONCLUSIONS: Similar to NAWM, tuber and perituber tissues in tuberous sclerosis complex undergo microstructural evolution with age. The extent of diffusion abnormality decreases with distance to the tuber, in line with known extension of histologic, immunohistochemical, and molecular abnormalities beyond tuber pathology.