Mapping prostatic microscopic anisotropy using linear and spherical b-tensor encoding: A preliminary study.

PURPOSE: Tensor-valued diffusion encoding provides more specific information than conventional diffusion-weighted imaging (DWI), but has mainly been applied in neuroimaging studies. This study aimed to assess its potential for the imaging of prostate cancer (PCa). METHODS: Seventeen patients with histologically proven PCa were enrolled. DWI of the prostate was performed with linear and spherical tensor encoding using a maximal b-value of 1.5 ms/µm2 and a voxel size of 3 × 3 × 4 mm3 . The gamma-distribution model was used to estimate the mean diffusivity (MD), the isotropic kurtosis (MKI ), and the anisotropic kurtosis (MKA ). Regions of interest were placed in MR-defined cancerous tissues, as well as in apparently healthy tissues in the peripheral and transitional zones (PZs and TZs). RESULTS: DWI with linear and spherical encoding yielded different image contrasts at high b-values, which enabled the estimation of MKA and MKI . Compared with healthy tissue (PZs and TZs combined) the cancers displayed a significantly lower MD (P < .05), higher MKI (P < 10-5 ), and lower MKA (P < .05). Compared with the TZ, tissue in the PZ showed lower MD (P < 10-3 ) and higher MKA (P < 10-3 ). No significant differences were found between cancers of different Gleason scores, possibly because of the limited sample size. CONCLUSION: Tensor-valued diffusion encoding enabled mapping of MKA and MKI in the prostate. The elevated MKI in PCa compared with normal tissues suggests an elevated heterogeneity in the cancers. Increased in-plane resolution could improve tumor delineation in future studies.

Multidimensional Diffusion Magnetic Resonance Imaging for Characterization of Tissue Microstructure in Breast Cancer Patients: A Prospective Pilot Study.

Diffusion-weighted imaging is a non-invasive functional imaging modality for breast tumor characterization through apparent diffusion coefficients. Yet, it has so far been unable to intuitively inform on tissue microstructure. In this IRB-approved prospective study, we applied novel multidimensional diffusion (MDD) encoding across 16 patients with suspected breast cancer to evaluate its potential for tissue characterization in the clinical setting. Data acquired via custom MDD sequences was processed using an algorithm estimating non-parametric diffusion tensor distributions. The statistical descriptors of these distributions allow us to quantify tissue composition in terms of metrics informing on cell densities, shapes, and orientations. Additionally, signal fractions from specific cell types, such as elongated cells (bin1), isotropic cells (bin2), and free water (bin3), were teased apart. Histogram analysis in cancers and healthy breast tissue showed that cancers exhibited lower mean values of "size" (1.43 ± 0.54 × 10-3 mm2/s) and higher mean values of "shape" (0.47 ± 0.15) corresponding to bin1, while FGT (fibroglandular breast tissue) presented higher mean values of "size" (2.33 ± 0.22 × 10-3 mm2/s) and lower mean values of "shape" (0.27 ± 0.11) corresponding to bin3 (p < 0.001). Invasive carcinomas showed significant differences in mean signal fractions from bin1 (0.64 ± 0.13 vs. 0.4 ± 0.25) and bin3 (0.18 ± 0.08 vs. 0.42 ± 0.21) compared to ductal carcinomas in situ (DCIS) and invasive carcinomas with associated DCIS (p = 0.03). MDD enabled qualitative and quantitative evaluation of the composition of breast cancers and healthy glands.

Glioma grading, molecular feature classification, and microstructural characterization using MR diffusional variance decomposition (DIVIDE) imaging.

OBJECTIVE: To evaluate the potential of diffusional variance decomposition (DIVIDE) for grading, molecular feature classification, and microstructural characterization of gliomas. MATERIALS AND METHODS: Participants with suspected gliomas underwent DIVIDE imaging, yielding parameter maps of fractional anisotropy (FA), mean diffusivity (MD), anisotropic mean kurtosis (MKA), isotropic mean kurtosis (MKI), total mean kurtosis (MKT), MKA/MKT, and microscopic fractional anisotropy (µFA). Tumor type and grade, isocitrate dehydrogenase (IDH) 1/2 mutant status, and the Ki-67 labeling index (Ki-67 LI) were determined after surgery. Statistical analysis included 33 high-grade gliomas (HGG) and 17 low-grade gliomas (LGG). Tumor diffusion metrics were compared between HGG and LGG, among grades, and between wild and mutated IDH types using appropriate tests according to normality assessment results. Receiver operating characteristic and Spearman correlation analysis were also used for statistical evaluations. RESULTS: FA, MD, MKA, MKI, MKT, µFA, and MKA/MKT differed between HGG and LGG (FA: p = 0.047; MD: p = 0.037, others p < 0.001), and among glioma grade II, III, and IV (FA: p = 0.048; MD: p = 0.038, others p < 0.001). All diffusion metrics differed between wild-type and mutated IDH tumors (MKI: p = 0.003; others: p < 0.001). The metrics that best discriminated between HGG and LGGs and between wild-type and mutated IDH tumors were MKT and FA respectively (area under the curve 0.866 and 0.881). All diffusion metrics except FA showed significant correlation with Ki-67 LI, and MKI had the highest correlation coefficient (rs = 0.618). CONCLUSION: DIVIDE is a promising technique for glioma characterization and diagnosis. KEY POINTS: • DIVIDE metrics MKI is related to cell density heterogeneity while MKA and µFA are related to cell eccentricity. • DIVIDE metrics can effectively differentiate LGG from HGG and IDH mutation from wild-type tumor, and showed significant correlation with the Ki-67 labeling index. • MKI was larger than MKA which indicates predominant cell density heterogeneity in gliomas. • MKA and MKI increased with grade or degree of malignancy, however with a relatively larger increase in the cell eccentricity metric MKA in relation to the cell density heterogeneity metric MKI.

Toward nonparametric diffusion- T1 characterization of crossing fibers in the human brain.

PURPOSE: To estimate T1 for each distinct fiber population within voxels containing multiple brain tissue types. METHODS: A diffusion- T1 correlation experiment was carried out in an in vivo human brain using tensor-valued diffusion encoding and multiple repetition times. The acquired data were inverted using a Monte Carlo algorithm that retrieves nonparametric distributions P(D,R1) of diffusion tensors and longitudinal relaxation rates R1=1/T1 . Orientation distribution functions (ODFs) of the highly anisotropic components of P(D,R1) were defined to visualize orientation-specific diffusion-relaxation properties. Finally, Monte Carlo density-peak clustering (MC-DPC) was performed to quantify fiber-specific features and investigate microstructural differences between white matter fiber bundles. RESULTS: Parameter maps corresponding to P(D,R1) 's statistical descriptors were obtained, exhibiting the expected R1 contrast between brain tissue types. Our ODFs recovered local orientations consistent with the known anatomy and indicated differences in R1 between major crossing fiber bundles. These differences, confirmed by MC-DPC, were in qualitative agreement with previous model-based works but seem biased by the limitations of our current experimental setup. CONCLUSIONS: Our Monte Carlo framework enables the nonparametric estimation of fiber-specific diffusion- T1 features, thereby showing potential for characterizing developmental or pathological changes in T1 within a given fiber bundle, and for investigating interbundle T1 differences.

Liquid crystal phantom for validation of microscopic diffusion anisotropy measurements on clinical MRI systems.

PURPOSE: To develop a phantom for validating MRI pulse sequences and data processing methods to quantify microscopic diffusion anisotropy in the human brain. METHODS: Using a liquid crystal consisting of water, detergent, and hydrocarbon, we designed a 0.5-L spherical phantom showing the theoretically highest possible degree of microscopic anisotropy. Data were acquired on the Connectome scanner using echo-planar imaging signal readout and diffusion encoding with axisymmetric b-tensors of varying magnitude, anisotropy, and orientation. The mean diffusivity, fractional anisotropy (FA), and microscopic FA (µFA) parameters were estimated. RESULTS: The phantom was observed to have values of mean diffusivity similar to brain tissue, and relaxation times compatible with echo-planar imaging echo times on the order of 100 ms. The estimated values of µFA were at the theoretical maximum of 1.0, whereas the values of FA spanned the interval from 0.0 to 0.8 as a result of varying orientational order of the anisotropic domains within each voxel. CONCLUSIONS: The proposed phantom can be manufactured by mixing three widely available chemicals in volumes comparable to a human head. The acquired data are in excellent agreement with theoretical predictions, showing that the phantom is ideal for validating methods for measuring microscopic diffusion anisotropy on clinical MRI systems. Magn Reson Med 79:1817-1828, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Apparent exchange rate for breast cancer characterization.

Although diffusion MRI has shown promise for the characterization of breast cancer, it has low specificity to malignant subtypes. Higher specificity might be achieved if the effects of cell morphology and molecular exchange across cell membranes could be disentangled. The quantification of exchange might thus allow the differentiation of different types of breast cancer cells. Based on differences in diffusion rates between the intra- and extracellular compartments, filter exchange spectroscopy/imaging (FEXSY/FEXI) provides non-invasive quantification of the apparent exchange rate (AXR) of water between the two compartments. To test the feasibility of FEXSY for the differentiation of different breast cancer cells, we performed experiments on several breast epithelial cell lines in vitro. Furthermore, we performed the first in vivo FEXI measurement of water exchange in human breast. In cell suspensions, pulsed gradient spin-echo experiments with large b values and variable pulse duration allow the characterization of the intracellular compartment, whereas FEXSY provides a quantification of AXR. These experiments are very sensitive to the physiological state of cells and can be used to establish reliable protocols for the culture and harvesting of cells. Our results suggest that different breast cancer subtypes can be distinguished on the basis of their AXR values in cell suspensions. Time-resolved measurements allow the monitoring of the physiological state of cells in suspensions over the time-scale of hours, and reveal an abrupt disintegration of the intracellular compartment. In vivo, exchange can be detected in a tumor, whereas, in normal tissue, the exchange rate is outside the range experimentally accessible for FEXI. At present, low signal-to-noise ratio and limited scan time allows the quantification of AXR only in a region of interest of relatively large tumors.

Formation of internally nanostructured triblock copolymer particles.

Particles with an internal structure have been found in dilute water solutions of a triblock copolymer of poly(ethylene oxide) (PEO) and poly(propylene oxide) (PPO), which has short hydrophilic PEO endblocks compared to the central hydrophobic PPO block (EO5PO68EO5, L121). The properties of the block copolymer particles (i.e., their structure, size, and time stability) have been investigated using cryogenic transmission electron microscopy (cryo-TEM) in combination with dynamic light scattering (DLS) and turbidity measurements. The particles were formed in dilute solutions by quenching the temperature to temperatures where the reversed hexagonal phase is in equilibrium with a solution of unaggregated L121 copolymers (L1). From the DLS measurements, a mean hydrodynamic radius of 158 nm was extracted. The time-scan turbidity measurements were found to be unchanged for about 46 h. At higher copolymer concentrations, a reversed hexagonal phase (H2) exists in the L121/water system. SAXS was used to investigate the internal structure of the dispersed L121-based particles containing 15 wt % L121. It was found that the internal structure transforms from H2 to an inverse micellar system (L2) as the temperature increases from 37 to 70 degrees C.

Vesicle formation from temperature jumps in a nonionic surfactant system.

When heating a dilute sample of the binary system of tetraethyleneglycol dodecyl ether (C12E4) and water from the micellar phase (L1) into the two-phase region of a lamellar phase (L(alpha)), and excess water (W) vesicles are formed. During heating, one passes a region of phase separation in the micellar phase (L1' + L1'') where the initial micelles rapidly fuse into larger aggregates forming the concentrated L1 phase (L1'') with a structure of branched cylindrical micelles, a so-called "living network". The static correlation length of the micelles are increasing with increasing concentration, from ca. 10 nm to 80 nm in the concentration range of 0.0001 g/cm3-0.0035 g/cm3. The overlap concentration was determined to 0.0035 g/cm3. When the temperature reaches the L1' + L(alpha) region the network particles transform into bilayer vesicles with a z-average apparent hydrodynamic radius in the order of 200 nm depending on the composition. The size of the final vesicles depends on the extent of aggregation/fusion in the L1' + L1'' region and hence on the rate of heating. The aggregation/fusion in the L1' + L1'' is slower than diffusion-limited aggregation, and it is shown that 1/100 of the collisions are sticky results in the fusion event.