Apparent Diffusion Coefficient Profiles Research Articles

Long-Term Stability of Gradient Characteristics Warrants Model-Based Correction of Diffusion Weighting Bias.

The study aims to test the long-term stability of gradient characteristics for model-based correction of diffusion weighting (DW) bias in an apparent diffusion coefficient (ADC) for multisite imaging trials. Single spin echo (SSE) DWI of a long-tube ice-water phantom was acquired quarterly on six MR scanners over two years for individual diffusion gradient channels, along with mapping, as a function of right-left (RL) and superior-inferior (SI) offsets from the isocenter. Additional double spin-echo (DSE) DWI was performed on two systems. The offset dependences of derived ADC were fit to 4th-order polynomials. Chronic shim gradients were measured from spatial derivatives of maps along the tube direction. Gradient nonlinearity (GNL) was modeled using vendor-provided gradient field descriptions. Deviations were quantified by root-mean-square differences (RMSD), normalized to reference ice-water ADC, between the model and reference (), measurement and model (), and temporal measurement variations (). Average was 4.9 ± 3.2 (%RL) and –14.8 ± 3.8 (%SI), and threefold larger than . was close to measurement errors (~3%). GNL-induced bias across gradient systems varied up to 20%, while deviation from the model accounted at most for 6.5%, and temporal variation for less than 3% of ADC reproducibility error. Higher SSE = 7.5–11% was reduced to 2.5–4.8% by DSE, consistent with the eddy current origin. Measured chronic shim gradients below 0.1 mT/m had a minor contribution to ADC bias. The demonstrated long-term stability of spatial ADC profiles and consistency with system GNL models justifies retrospective and prospective DW bias correction based on system gradient design models. Residual errors due to eddy currents and shim gradients should be corrected independent of GNL.

Histogram Analysis of Diffusion Weighted Imaging in Low-Grade Gliomas: in vivo Characterization of Tumor Architecture and Corresponding Neuropathology.

Background: Low-grade gliomas (LGG) in adults are usually slow growing and frequently asymptomatic brain tumors, originating from glial cells of the central nervous system (CNS). Although regarded formally as “benign” neoplasms, they harbor the potential of malignant transformation associated with high morbidity and mortality. Their complex and unpredictable tumor biology requires a reliable and conclusive presurgical magnetic resonance imaging (MRI). A promising and emerging MRI approach in this context is histogram based apparent diffusion coefficient (ADC) profiling, which recently proofed to be capable of providing prognostic relevant information in different tumor entities. Therefore, our study investigated whether histogram profiling of ADC distinguishes grade I from grade II glioma, reflects the proliferation index Ki-67, as well as the IDH (isocitrate dehydrogenase) mutation and MGMT (methylguanine-DNA methyl-transferase) promotor methylation status.Material and Methods: Pre-treatment ADC volumes of 26 LGG patients were used for histogram-profiling. WHO-grade, Ki-67 expression, IDH mutation, and MGMT promotor methylation status were evaluated. Comparative and correlative statistics investigating the association between histogram-profiling and neuropathology were performed.Results: Almost the entire ADC profile (p25, p75, p90, mean, median) was significantly lower in grade II vs. grade I gliomas. Entropy, as second order histogram parameter of ADC volumes, was significantly higher in grade II gliomas compared with grade I gliomas. Mean, maximum value (ADCmax) and the percentiles p10, p75, and p90 of ADC histogram were significantly correlated with Ki-67 expression. Furthermore, minimum ADC value (ADCmin) was significantly associated with MGMT promotor methylation status as well as ADC entropy with IDH-1 mutation status.Conclusions: ADC histogram-profiling is a valuable radiomic approach, which helps differentiating tumor grade, estimating growth kinetics and probably prognostic relevant genetic as well as epigenetic alterations in LGG.

Quantitative MRI demonstrates abnormalities of the third ventricle subventricular zone in neurofibromatosis type-1 and sporadic paediatric optic pathway glioma

BackgroundThe subventricular zone of the third ventricle (TVZ) is a germinal stem cell niche, identified as the possible location of optic pathway glioma (OPG) cell origin. Paediatric OPGs are predominantly diagnosed as low-grade astrocytomas, which are either sporadic or are associated with neurofibromatosis type-1 (NF1). These tumours often cause a significant impairment to visual acuity (VA). Infiltrative/invasive tumour activity is associated with increased apparent diffusion coefficient (ADC) and cerebral blood flow (CBF). This study aimed to determine whether TVZ imaging features differed between sporadic-OPG, NF1-OPG and controls, and whether the ADC and CBF profile at the germinal stem cell niche (the TVZ) correlated with the primary outcome of VA. MethodsADC and CBF MRI data were acquired from 30 paediatric OPG patients (median age 6 years; range 8 months–17 years), along with VA measurements, during clinical surveillance of their tumour. Values for mean ADC and maximum CBF were measured at the TVZ, and normalized to normal-appearing grey matter. These values were compared between the two OPG groups and the healthy control subjects, and multivariate linear regression was used to test the linear association between these values and patient’s VA. ResultsIn the TVZ, normalized mean ADC was higher in NF1-associated OPG patients (N = 15), compared to both sporadic OPG patients (N = 15; p = 0.010) and healthy controls (N = 14; p < 0.001). In the same region, normalized maximum CBF was higher in sporadic OPG patients compared to both NF1-OPG patients (p = 0.016) and healthy controls (p < 0.001). In sporadic OPG patients only, normalized mean ADC in the TVZ was significantly correlated with visual acuity (R2 = 0.41, p = 0.019). No significant correlations were found between TVZ CBF and ADC values and visual acuity in the NF1-associated OPG patients. ConclusionQuantitative MRI detects TVZ abnormalities in both sporadic and NF1-OPG patients, and identifies TVZ features that differentiate the two. TVZ features may be useful MRI markers of interest in future predictive studies involving sporadic OPG.

239. A protocol for advanced QA in DW

Purpose The aim of this study is to propose a protocol for DWI QA being easy to implement while still providing quantitative information on relevant parameters for the scanner QC as well as for clinical applications. The measured quantity is the apparent diffusion coefficient (ADC) and its dependence from gradient diffusion direction (Gdd) and phase encoding direction (PED). Methods A spherical water phantom (14 cm diameter), designed to allow fast and easy measurement of solution temperature, is proposed. The phantom is filled with doped aqueous solution (ADC value certified) and placed at isocentre of scanner. The protocol consists of five set of acquisition of 19 slices, repeated for three orthogonal Gdd. First and second acquisitions are identical, the others differ for the PED and acquisition plane. Each slice (for each Gdd) is acquired with six different b-values varying from 0 s/mm2 to 1000 s/mm2. From each acquisition and Gdd, ADC map of the phantom is generated with monoexponential fit, corrected for temperature and ADC profile along three orthogonal direction is extracted. From first two acquisitions short term reproducibility and SNR are evaluated; second and third acquisitions are used to detect phase encoding direction effects, lasts three maps are used to detect acquisition plane effects on ADC (details in Table 1 ). Results A preliminary test of the protocol on 1.5T MRI scanner demonstrated its applicability to routine QA. Relative difference between on-centre and periphery ADC values varies from −5% and +3% and phase encoding effect is less than 0.5%. Gdd variations are around +1%. Acquisition plane differences are less than 1% at isocentre and of the order of 5% in periphery. SNR at isocenter is 550 and short term variation is 0.2%. Conclusions The proposed protocol provides a simple QA procedure for DWI application. Selected indexes provide quantitative information on many relevant acquisition parameters.

Predictive indicators for the development of epilepsy after acute encephalopathy with biphasic seizures and late reduced diffusion

Acute encephalopathy with biphasic seizures and late reduced diffusion (AESD) is a newly defined clinicoradiologic syndrome characterized by biphasic seizures and altered consciousness followed by restricted diffusion in the white matter on magnetic resonance imaging in acute phase. Intractable epilepsy commonly occurs as the late complication. This study aimed to search predisposing factors to the development of epilepsy after AESD. Consecutively treated 22 patients with AESD in our institution from 2006 to 2016 were grouped into those with post-encephalopathic epilepsy (PEE, n = 10) or without PEE (n = 12). There was no difference between two groups in age at the onset of AESD, duration of the initial seizures, or the follow-up periods after discharge. PEE group patients more frequently showed coma or involuntary movements during the course of AESD than non-PEE group patients (36% vs. 8%, p = 0.008). The quantitative analysis of apparent diffusion coefficient (ADC) map revealed that PEE group showed broader areas with reduced diffusion in the posterior lobes at the onsets of AESD than non-PEE group (0.113 vs. 0.013, p = 0.035). On the other hand, the atrophy on day 30-ADC map did not correlate with the development or control of epilepsy. These results suggest that the clinical severity and ADC profiles in acute phase, rather than the brain atrophy in convalescent phase, may predict the development of post-AESD epilepsy.

Diffusion Profiling via a Histogram Approach Distinguishes Low-grade from High-grade Meningiomas, Can Reflect the Respective Proliferative Potential and Progesterone Receptor Status.

Presurgical grading, estimation of growth kinetics, and other prognostic factors are becoming increasingly important for selecting the best therapeutic approach for meningioma patients. Diffusion-weighted imaging (DWI) provides microstructural information and reflects tumor biology. A novel DWI approach, histogram profiling of apparent diffusion coefficient (ADC) volumes, provides more distinct information than conventional DWI. Therefore, our study investigated whether ADC histogram profiling distinguishes low-grade from high-grade lesions and reflects Ki-67 expression and progesterone receptor status. Pretreatment ADC volumes of 37 meningioma patients (28 low-grade, 9 high-grade) were used for histogram profiling. WHO grade, Ki-67 expression, and progesterone receptor status were evaluated. Comparative and correlative statistics investigating the association between histogram profiling and neuropathology were performed. The entire ADC profile (p10, p25, p75, p90, mean, median) was significantly lower in high-grade versus low-grade meningiomas. The lower percentiles, mean, and modus showed significant correlations with Ki-67 expression. Skewness and entropy of the ADC volumes were significantly associated with progesterone receptor status and Ki-67 expression. ROC analysis revealed entropy to be the most accurate parameter distinguishing low-grade from high-grade meningiomas. ADC histogram profiling provides a distinct set of parameters, which help differentiate low-grade versus high-grade meningiomas. Also, histogram metrics correlate significantly with histological surrogates of the respective proliferative potential. More specifically, entropy revealed to be the most promising imaging biomarker for presurgical grading. Both, entropy and skewness were significantly associated with progesterone receptor status and Ki-67 expression and therefore should be investigated further as predictors for prognostically relevant tumor biological features. Since absolute ADC values vary between MRI scanners of different vendors and field strengths, their use is more limited in the presurgical setting.

Pediatric Brain Tumor Consortium Multisite Assessment of Apparent Diffusion Coefficient z-Axis Variation Assessed with an Ice–Water Phantom

Magnetic resonance diffusion imaging can characterize physiologic characteristics of pediatric brain tumors used to assess therapy response. The purpose of this study was to assess the variability of the apparent diffusion coefficient (ADC) along z-axis of scanners in the multicenter Pediatric Brain Tumor Consortium (PBTC). Ice-water diffusion phantoms for each PBTC site were distributed with a specific diffusion imaging protocol. The phantom was scanned four successive times to 1) confirm water in the tube reached thermal equilibrium and 2) allow for assessment of intra-examination ADC repeatability. ADC profiles across slice positions for each vendor and institution combination were characterized using linear regression modeling with a quadratic fit. Eleven sites collected data with a high degree of compliance to the diffusion protocol for each scanner. The mean ADC value at slice position zero for vendor A was 1.123×10(-3)mm(2)/s, vendor B was 1.0964×10(-3)mm(2)/s, and vendor C was 1.110×10(-3)mm(2)/s. The percentage coefficient of variation across all sites was 0.309% (standard deviation=0.322). The ADC values conformed well to a second-order polynomial along the z-axis, (ie, following a linear model pattern with quadratic fit) for vendor-institution combinations and across vendor-institution combinations as shown in the longitudinal model. Assessment of the variability of diffusion metrics is essential for establishing the validity of using these quantitative metrics in multicenter trials. The low variability in ADC values across vendors and institutions and validates the use of ADC as a quantitative tumor marker in pediatric multicenter trials.

Apparent diffusion coefficient-based differentiation of cystic lesions of the mandible

To evaluate the apparent diffusion coefficient (ADC) for differentiation of cystic lesions of the mandible. We retrospectively evaluated 27 cystic lesions of the mandible. We determined the overall ADCs and the pixel-based ADC profiles (ADC mapping) of the fluid areas using two b values (500 and 1000 s/mm2). The overall ADCs of the fluid areas of ameloblastomas (2.45 ± 0.27 × 10−3 mm2/s) and simple bone cysts (2.52 ± 0.14 × 10−3 mm2/s) were significantly larger than those of dentigerous cysts (1.50 ± 0.49 × 10−3 mm2/s; p = 0.047 and p = 0.041, respectively), radicular cysts (0.90 ± 0.21 × 10−3 mm2/s; p = 0.048 and p = 0.042, respectively), and keratocystic odontogenic tumors (0.87 ± 0.13 × 10−3 mm2/s; p = 0.032 and p = 0.021, respectively). However, the overall ADCs were similar between ameloblastomas and simple bone cysts and among dentigerous cysts, radicular cysts, and keratocystic odontogenic tumors. ADC mapping demonstrated that ameloblastomas and simple bone cysts had 80–99 % fluid areas with high ADC levels, whereas radicular cysts and keratocystic odontogenic tumors had 66–100 % fluid areas with low or extremely low ADC levels. However, the ADC mapping profiles of dentigerous cysts differed substantially among the cases. The ADC-based criteria did not effectively differentiate between ameloblastomas and simple bone cysts or between radicular cysts and keratocystic odontogenic tumors. The ADC-based differentiation was effective for discriminating some types of cystic lesion of the mandible.

Higher Order Positive Semidefinite Diffusion Tensor Imaging

Due to the well-known limitations of diffusion tensor imaging, high angular resolution diffusion imaging (HARDI) is used to characterize non-Gaussian diffusion processes. One approach to analyzing HARDI data is to model the apparent diffusion coefficient (ADC) with higher order diffusion tensors. The diffusivity function is positive semidefinite. In the literature, some methods have been proposed to preserve positive semidefiniteness of second order and fourth order diffusion tensors. None of them can work for arbitrarily high order diffusion tensors. In this paper, we propose a comprehensive model to approximate the ADC profile by a positive semidefinite diffusion tensor of either second or higher order. We call this the positive semidefinite diffusion tensor (PSDT) model. PSDT is a convex optimization problem with a convex quadratic objective function constrained by the nonnegativity requirement on the smallest Z-eigenvalue of the diffusivity function. The smallest Z-eigenvalue is a computable measure of the extent of positive definiteness of the diffusivity function. We also propose some other invariants for the ADC profile analysis. Experiment results show that higher order tensors could improve the estimation of anisotropic diffusion and that the PSDT model can depict the characterization of diffusion anisotropy which is consistent with known neuroanatomy.

A nonstandard smoothing in reconstruction of apparent diffusion coefficient profiles from diffusion weighted images

We present a new variational framework for simultaneous smoothing and estimation of apparent diffusion coefficient (ADC) profiles from High Angular Resolution Diffusion-weighted MRI. The model approximates the ADC profiles at each voxel by a 4th order spherical harmonic series (SHS). The coefficients in SHS are obtained by solving a constrained minimization problem. The smoothing with feature preserved is achieved by minimizing a variable exponent, linear growth functional, and the data constraint is determined by the original Stejskal-Tanner equation. The antipodal symmetry and positiveness of the ADC are accommodated in the model. We use these coefficients and variance of the ADC profiles from its mean to classify the diffusion in each voxel as isotropic, anisotropic with single fiber orientation, or two fiber orientations. The proposed model has been applied to both simulated data and HARD MRI human brain data . The experiments demonstrated the effectiveness of our method in estimation and smoothing of ADC profiles and in enhancement of diffusion anisotropy. Further characterization of non-Gaussian diffusion based on the proposed model showed a consistency between our results and known neuroanatomy.

How accurately can the diffusion profiles indicate multiple fiber orientations? A study on general fiber crossings in diffusion MRI

The q-space imaging techniques and high angular resolution diffusion (HARD) imaging have shown promise to identify intravoxel multiple fibers. The measured orientation distribution function (ODF) and apparent diffusion coefficient (ADC) profiles can be used to identify the orientations of the actual intravoxel fibers. The present study aims to examine the accuracy of these profile-based orientation methods by comparing the angular deviations between the estimated local maxima of the profiles and the real fiber orientation for a fiber crossing simulated with various intersection angles under different b values in diffusion-weighted MRI experiments. Both noisy and noise-free environments were investigated. The diffusion spectrum imaging (DSI), q-ball imaging (QBI), and HARD techniques were used to generate ODF and ADC profiles. To provide a better comparison between ODF and ADC techniques, the phase-corrected angular deviations were also presented for the ADC method based on a circular spectrum mapping method. The results indicate that systematic angular deviations exist between the actual fiber orientations and the corresponding local maxima of either the ADC or ODF profiles. All methods are apt to underestimation of acute intersection and overestimation of obtuse intersection angle. For a typical slow-exchange fiber crossing, the ODF methods have a non-deviation zone around the 90° intersection. Before the phase-correction, the deviation of ADC profiles approaches a peak at the 90° intersection, while after the correction the ADC deviations are significantly reduced. When the b factor is larger than 1000 s/mm 2, the ODF methods have smaller angular deviations than the ADC methods for the intersections close to 90°. QBI method demonstrates a slight yet consistent advantage over the DSI method under the same conditions. In the noisy environment, the mean value of the deviation angles shows a high consistency with the corresponding deviation in the nose-free condition.

A rotation-invariant spherical harmonic decomposition method for mapping intravoxel multiple fiber structures

A new rotation-invariant spherical harmonic decomposition (SHD) method is proposed in this paper for analyzing high angular resolution diffusion (HARD) imaging. Regular SHD methods have been used to characterize the features of the apparent diffusion coefficient (ADC) profile measured by the HARD technique. However, these regular SHD methods are rotation-variant, i.e., the magnitude and/or the phase of the harmonic components changes with the rotation of the ADC profile. We propose a new rotation-invariant SHD (RI-SHD) method based on the rotation-invariant property of a diffusion tensor model. The basic idea of the proposed method is to reorient the measured ADC profile into a local coordinate system determined by the three eigenvectors of the diffusion tensor in each imaging voxel, and then apply a SHD to the ADC profile. Both simulations and in vivo experiments were carried out to validate the method. Comparisons were made between the component maps from a regular SHD method, diffusion circular spectrum mapping (DCSM) method and the proposed RI-SHD method. The results indicate that the regular SHD maps vary significantly with the rotation of the diffusion-encoding scheme, whereas the maps of the DCSM and the proposed method remain unchanged. In particular, the (0,0)-th, (2,2)-th and (4,4)-th component maps from the RI-SHD method exhibited good consistency with the 0th, 2nd and 4th order maps of the DCSM method, respectively. Compared with the regular SHD methods used in HARD imaging, the proposed RI-SHD method is superior in characterizing the diffusion patterns of multiple fiber structures between different brain regions or across subjects.

23Na-MRI quantification of sodium and water mobility in pork during brine curing

A model study on movements of sodium ions in pork loin during brining was carried out using 23Na-magnetic resonance imaging ( 23Na-MRI). Samples of different pH and post-mortem age were mounted in Plexiglas ® cylinders with built-in phantoms and cured in 18.9% and 18.1% NaCl (w/v), respectively. One-dimensional 23Na-MRI and apparent diffusion coefficient (ADC) profiles were obtained over 5 days with intervals of 24 h. On day 5 the meat was cut into 1 cm slices and analyzed for chloride content. 23Na-MRI and ADC profiles of meat provided detailed non-destructive information about salt and water movements during brine curing. Quantification of salt concentration in meat by one-dimensional 23Na-MRI profiling proved successful at values above 0.9 g NaCl/100 g sample in the meat. 23Na measurements were calibrated against chemically determined chloride, yielding a linear relationship. 23Na-MRI profiles suggested that the diffusion of salt into whole meat cuts cannot be described by simple ordinary Fickian diffusion with a constant diffusion coefficient. The diffusion coefficient is suggested to be affected by changes in NaCl concentration, swelling and degree of dehydration.

Regional assessment of tissue oxygenation and the temporal evolution of hemodynamic parameters and water diffusion during acute focal ischemia in rat brain

We assessed the temporal and spatial correlation between perfusion deficits and tissue damage in the first hours of focal cerebral ischemia in the rat. Repetitive dynamic susceptibility contrast-enhanced (`bolus track') and diffusion-weighted (DW) MRI, performed from ca. 0.5 up to 6 h after intraluminal middle cerebral artery occlusion (MCA-O), allowed the determination of the time course of various hemodynamic parameters and ischemic tissue damage in specific brain regions. In addition, blood oxygenation level dependent (BOLD) MRI combined with a respiratory challenge provided complementary information on brain hemodynamics. Within the territory of reduced blood flow, the degree of the hemodynamic disturbances was heterogeneous. Interestingly, the spatial pattern of perfusion deficiencies remained essentially the same from ca. 0.5 to 6 h post-MCA-O. However, the area and the extent of ischemic tissue damage, as expressed by reductions in the apparent diffusion coefficient (ADC) of tissue water, tended to progress with increasing occlusion time. Different ADC profiles correlated with different degrees of hemodynamic disturbances. In the ischemic core, which showed severely compromized perfusion, the ADC dropped significantly within 1 h. In perifocal areas, ADC reductions were delayed and less pronounced. Data from the bolus track and BOLD MRI experiments revealed the existence of residual flow, particularly in perifocal regions. Our data point to a time-dependent change in the relationship between ADC reductions and hemodynamic alterations and, therefore, agree with the concept of a progressively increasing perfusion threshold for ischemic tissue damage as a function of time of ischemia.