Modeling the diffusion-weighted imaging signal for breast lesions in the b = 200 to 3000 s/mm2 range: quality of fit and classification accuracy for different representations.

PURPOSE: To evaluate different non-Gaussian representations for the diffusion-weighted imaging (DWI) signal in the b-value range 200 to 3000 s/mm2 in benign and malignant breast lesions. METHODS: Forty-three patients diagnosed with benign (n = 18) or malignant (n = 25) tumors of the breast underwent DWI (b-values 200, 600, 1200, 1800, 2400, and 3000 s/mm2 ). Six different representations were fit to the average signal from regions of interest (ROIs) at different b-value ranges. Quality of fit was assessed by the corrected Akaike information criterion (AICc), and the Friedman test was used for assessing representation ranks. The area under the curve (AUC) of receiver operating characteristic curves were used to evaluate the power of derived parameters to differentiate between malignant and benign lesions. The lesion ROI was divided in central and peripheral parts to assess potential effect of heterogeneity. Sensitivity to noise-floor correction was also evaluated. RESULTS: The Padé exponent was ranked as the best based on AICc, whereas 3 models (kurtosis, fractional, and biexponential) achieved the highest AUC = 0.99 for lesion differentiation. The monoexponential model at bmax = 600 s/mm2 already provides AUC = 0.96, with considerably shorter acquisition time and simpler analysis. Significant differences between central and peripheral parts of lesions were found in malignant lesions. The mono- and biexponential models were most stable against varying degrees of noise-floor correction. CONCLUSION: Non-Gaussian representations are required for fitting of the DWI curve at high b-values in breast lesions. However, the added clinical value from the high b-value data for differentiation of benign and malignant lesions is not clear.

Restriction spectrum imaging of white matter and its relation to neurological disability in multiple sclerosis.

BACKGROUND: Restriction spectrum imaging (RSI) is a recently introduced magnetic resonance imaging diffusion technique. The utility of RSI in multiple sclerosis (MS) is unknown. OBJECTIVE: To investigate the association between RSI-derived parameters and neurological disability in MS. METHODS: Seventy-seven relapsing-remitting MS patients were scanned with RSI on a 3-T scanner. RSI-derived parameters: fast and slow apparent diffusion coefficient (sADC), fractional anisotropy, restricted fractional anisotropy, neurite density (ND), cellularity, extracellular water fraction, and free water fraction, were obtained in white matter lesions (WML) and normal appearing white matter (NAWM). Patients were divided into three groups according to their expanded disability status scale (EDSS): with minimal, low, and substantial disability (<2.5, 2.5-3, and >3, respectively). Group comparisons and correlation analyses were performed. RESULTS: All tested RSI-derived parameters differed between WML and NAWM ( p < 0.001 for all pairwise comparisons). The sADC in WML showed largest difference across disability subgroups (analysis of variance (ANOVA): F = 5.1, η2 = 0.12, p = 0.008). ND in NAWM showed strongest correlation with disability (ϱ = -0.39, p < 0.001). CONCLUSION: The strongest correlation with EDSS of ND obtained in NAWM indicates that processes outside lesions are important for disability in MS. Our study suggests that RSI-derived parameters may help understand the "clinico-radiological paradox" and improve disease monitoring in MS.

High temporal resolution motion estimation using a self-navigated simultaneous multi-slice echo planar imaging acquisition.

BACKGROUND: Subject motion is known to produce spurious covariance among time-series in functional connectivity that has been reported to induce distance-dependent spurious correlations. PURPOSE: To present a feasibility study for applying the extended Kalman filter (EKF) framework for high temporal resolution motion correction of resting state functional MRI (rs-fMRI) series using each simultaneous multi-slice (SMS) echo planar imaging (EPI) shot as its own navigator. STUDY TYPE: Prospective feasibility study. POPULATION/SUBJECTS: Three human volunteers. FIELD STRENGTH/SEQUENCE: 3T GE DISCOVERY MR750 scanner using a 32-channel head coil. Simultaneous multi-slice rs-fMRI sequence with repetition time (TR)/echo time (TE) = 800/30 ms, and SMS factor 6. ASSESSMENT: Motion estimates were computed using two techniques: a conventional rigid-body volume-wise registration; and a high-temporal resolution motion estimation rigid-body approach. The reference image was resampled using the estimates obtained from both approaches and the difference between these predicted volumes and the original moving series was summarized using the normalized mean squared error (NMSE). STATISTICAL TESTS: Direct comparison of NMSE values. RESULTS: High-temporal motion estimation was always superior to volume-wise motion estimation for the sample presented. For staged continuous rotations, the NMSE using high-temporal resolution motion estimates ranged between [0.130, 0.150] for the first volunteer (in-plane rotations), between [0.060, 0.068] for the second volunteer (in-plane rotations), and between [0.063, 0.080] for the third volunteer (through-plane rotations). These values went up to [0.384, 0.464]; [0.136, 0.179]; and [0.080, 0.096], respectively, when using volume-wise motion estimates. DATA CONCLUSION: Accurate high-temporal rigid-body motion estimates can be obtained for rs-fMRI taking advantage of simultaneous multi-slice EPI sub-TR shots. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.

Molecular classification of patients with grade II/III glioma using quantitative MRI characteristics.

BACKGROUND: Molecular markers of WHO grade II/III glioma are known to have important prognostic and predictive implications and may be associated with unique imaging phenotypes. The purpose of this study is to determine whether three clinically relevant molecular markers identified in gliomas-IDH, 1p/19q, and MGMT status-show distinct quantitative MRI characteristics on FLAIR imaging. METHODS: Sixty-one patients with grade II/III gliomas who had molecular data and MRI available prior to radiation were included. Quantitative MRI features were extracted that measured tissue heterogeneity (homogeneity and pixel correlation) and FLAIR border distinctiveness (edge contrast; EC). T-tests were conducted to determine whether patients with different genotypes differ across the features. Logistic regression with LASSO regularization was used to determine the optimal combination of MRI and clinical features for predicting molecular subtypes. RESULTS: Patients with IDH wildtype tumors showed greater signal heterogeneity (p = 0.001) and lower EC (p = 0.008) within the FLAIR region compared to IDH mutant tumors. Among patients with IDH mutant tumors, 1p/19q co-deleted tumors had greater signal heterogeneity (p = 0.002) and lower EC (p = 0.005) compared to 1p/19q intact tumors. MGMT methylated tumors showed lower EC (p = 0.03) compared to the unmethylated group. The combination of FLAIR border distinctness, heterogeneity, and pixel correlation optimally classified tumors by IDH status. CONCLUSION: Quantitative imaging characteristics of FLAIR heterogeneity and border pattern in grade II/III gliomas may provide unique information for determining molecular status at time of initial diagnostic imaging, which may then guide subsequent surgical and medical management.

Relationship between kurtosis and bi-exponential characterization of high b-value diffusion-weighted imaging: application to prostate cancer.

BACKGROUND: High b-value diffusion-weighted imaging has application in the detection of cancerous tissue across multiple body sites. Diffusional kurtosis and bi-exponential modeling are two popular model-based techniques, whose performance in relation to each other has yet to be fully explored. PURPOSE: To determine the relationship between excess kurtosis and signal fractions derived from bi-exponential modeling in the detection of suspicious prostate lesions. MATERIAL AND METHODS: This retrospective study analyzed patients with normal prostate tissue (n = 12) or suspicious lesions (n = 13, one lesion per patient), as determined by a radiologist whose clinical care included a high b-value diffusion series. The observed signal intensity was modeled using a bi-exponential decay, from which the signal fraction of the slow-moving component was derived ( SFs). In addition, the excess kurtosis was calculated using the signal fractions and ADCs of the two exponentials ( KCOMP). As a comparison, the kurtosis was also calculated using the cumulant expansion for the diffusion signal ( KCE). RESULTS: Both K and KCE were found to increase with SFs within the range of SFs commonly found within the prostate. Voxel-wise receiver operating characteristic performance of SFs, KCE, and KCOMP in discriminating between suspicious lesions and normal prostate tissue was 0.86 (95% confidence interval [CI] = 0.85 - 0.87), 0.69 (95% CI = 0.68-0.70), and 0.86 (95% CI = 0.86-0.87), respectively. CONCLUSION: In a two-component diffusion environment, KCOMP is a scaled value of SFs and is thus able to discriminate suspicious lesions with equal precision . KCE provides a computationally inexpensive approximation of kurtosis but does not provide the same discriminatory abilities as SFs and KCOMP.

Restriction spectrum imaging: An evolving imaging biomarker in prostate MRI.

Restriction spectrum imaging (RSI) is a novel diffusion-weighted MRI technique that uses the mathematically distinct behavior of water diffusion in separable microscopic tissue compartments to highlight key aspects of the tissue microarchitecture with high conspicuity. RSI can be acquired in less than 5 min on modern scanners using a surface coil. Multiple field gradients and high b-values in combination with postprocessing techniques allow the simultaneous resolution of length-scale and geometric information, as well as compartmental and nuclear volume fraction filtering. RSI also uses a distortion correction technique and can thus be fused to high resolution T2-weighted images for detailed localization, which improves delineation of disease extension into critical anatomic structures. In this review, we discuss the acquisition, postprocessing, and interpretation of RSI for prostate MRI. We also summarize existing data demonstrating the applicability of RSI for prostate cancer detection, in vivo characterization, localization, and targeting. LEVEL OF EVIDENCE: 5 J. Magn. Reson. Imaging 2017;45:323-336.

Imaging correlates for the 2016 update on WHO classification of grade II/III gliomas: implications for IDH, 1p/19q and ATRX status.

The 2016 World Health Organization Classification of Tumors of the Central Nervous System incorporates the use of molecular information into the classification of brain tumors, including grade II and III gliomas, providing new prognostic information that cannot be delineated based on histopathology alone. We hypothesized that these genomic subgroups may also have distinct imaging features. A retrospective single institution study was performed on 40 patients with pathologically proven infiltrating WHO grade II/III gliomas with a pre-treatment MRI and molecular data on IDH, chromosomes 1p/19q and ATRX status. Two blinded Neuroradiologists qualitatively assessed MR features. The relationship between each parameter and molecular subgroup (IDH-wildtype; IDH-mutant-1p/19q codeleted-ATRX intact; IDH-mutant-1p/19q intact-ATRX loss) was evaluated with Fisher's exact test. Progression free survival (PFS) was also analyzed. A border that could not be defined on FLAIR was most characteristic of IDH-wildtype tumors, whereas IDH-mutant tumors demonstrated either well-defined or slightly ill-defined borders (p = 0.019). Degree of contrast enhancement and presence of restricted diffusion did not distinguish molecular subgroups. Frontal lobe predominance was associated with IDH-mutant tumors (p = 0.006). The IDH-wildtype subgroup had significantly shorter PFS than the IDH-mutant groups (p < 0.001). No differences in PFS were present when separating by tumor grade. FLAIR border patterns and tumor location were associated with distinct molecular subgroups of grade II/III gliomas. These imaging features may provide fundamental prognostic and predictive information at time of initial diagnostic imaging.

Erratum to: Imaging correlates for the 2016 update on WHO classification of grade II/III gliomas: implications for IDH, 1p/19q and ATRX status.

In the initial online publication, the values in the last two rows in Table 1 were in the wrong rows. The original article has been corrected.

Abnormalities in hippocampal volume of glioma patients prior to radiotherapy.

BACKGROUND: Radiation-induced cognitive impairment may be mediated by hippocampal damage, but the structural integrity of this region in tumor patients at baseline is unclear. Hippocampal volumes of 31 glioma patients prior to receiving radiotherapy were compared to a group of 34 healthy controls. MATERIALS AND METHODS: Left and right hippocampi on T1-weighted pre-contrast magnetic resonance images were automatically segmented using Freesurfer, and visually inspected for segmentation errors. Normalized hippocampal volume for each subject was calculated as the sum of left and right hippocampal volumes divided by the estimated total intracranial volume. The normalized amygdala volume was similarly analyzed as a reference structure. RESULTS: A Wilcoxon rank-sum test showed a significant difference in normalized hippocampal volumes between patients and controls (mean value 0.499 vs. 0.524, p = .01). No statistically significant difference was found for the amygdala. A post-hoc analysis revealed a significant difference in normalized hippocampal volumes between patients who had experienced seizures (mean value: 0.480, p < .05) and controls. No difference was noted between patients without seizures (mean value: 0.513) and controls. CONCLUSIONS: Hippocampi of glioma patients prior to radiotherapy were significantly smaller than those of age-matched controls. Group differences were larger in patients with tumor-associated seizures. This may be secondary to other processes such as tumor biology and inflammation.

Restriction spectrum imaging reveals decreased neurite density in patients with temporal lobe epilepsy.

OBJECTIVE: Diffusion tensor imaging (DTI) has become a popular tool for delineating the location and extent of white matter injury in temporal lobe epilepsy (TLE). However, DTI yields nonspecific measures that are confounded by changes occurring within both the intracellular and extracellular environments. This study investigated whether an advanced diffusion method, restriction spectrum imaging (RSI) could provide a more robust measure of white matter injury in TLE relative to DTI due to RSI's ability to separate intraaxonal diffusion (i.e., neurite density; ND) from diffusion associated with extraaxonal factors (e.g., inflammation; crossing fibers). METHODS: RSI and DTI scans were obtained on 21 patients with TLE and 11 age-matched controls. RSI-derived maps of ND, isotropic-hindered (IH) and isotropic-free (IF) water, and crossing fibers (CFs) were compared to DTI-derived fractional anisotropy (FA) maps. Voxelwise and tract-based analyses were performed comparing patients with TLE to controls on each diffusion metric. RESULTS: Reductions in FA were seen primarily in frontotemporal white matter in TLE, and they were most pronounced proximal to the seizure focus. Reductions in ND corresponded to those seen in the FA maps; however, ND reductions were greater in magnitude, more lateralized to the epileptogenic hemisphere, and showed a broader pattern. Increases in IF/IH and effects from CFs also contributed to reduced FA in the ipsilateral parahippocampal cingulum and fornix, with decreases in IH extending into extratemporal regions. Reduced ND of the uncinate fasciculus was associated with longer disease duration, whereas FA was not associated with any clinical variables. SIGNIFICANCE: RSI may provide a more specific measure of white matter pathology in TLE, distinguishing regions primarily affected by axonal/myelin loss from those where CFs and increases in extracellular water also play a role. By providing a more specific measure of axonal/myelin loss, RSI-derived ND may better reflect overall white matter burden in epilepsy.

Distinct effects of nuclear volume fraction and cell diameter on high b-value diffusion MRI contrast in tumors.

PURPOSE: While many recent studies have demonstrated improved detection and characterization of malignant lesions using high b-value diffusion imaging techniques, little is known about the underlying physical characteristics of tumor cells that modulate the restricted water signal at high b on clinical scanners. METHODS: Monte Carlo simulations of diffusion in a synthetic tumor cell environment were used to study the specific effects of tumor cell diameter and nuclear volume fraction (ν) on high b diffusion contrast. RESULTS: Results indicate that clinical pulsed-gradient spin-echo diffusion-weighted signals measured at high b (∼4000 s/mm(2)), long diffusion time (Δ âˆ¼40-60 ms), and long echo time (TE ∼60-140 ms) are generally insensitive to tumor cell diameter, but increase exponentially with ν. Moreover, these results are predicted by a simple analytic expression for the intracellular restricted water signal with elevated T2 for the intranuclear versus cytosolic compartment. CONCLUSION: Nuclear volume fraction is an important characteristic of cancer cells that modulates the apparent restriction of water at high b on clinical scanners. This model offers a possible explanation for the apparent unreliable correlation between tumor cell density (cellularity) and traditional ADC.

Combining diffusion and perfusion differentiates tumor from bevacizumab-related imaging abnormality (bria).

A subset of patients with high-grade glioma and brain metastases who are treated with bevacizumab develop regions of marked and persistent restricted diffusion that do not reflect recurrent tumor. Here, we quantify the degree of restricted diffusion and the relative cerebral blood volume (rCBV) within these regions of bevacizumab-related imaging abnormality (BRIA) in order to facilitate differentiation of these lesions from recurrent tumor. Six patients with high-grade glioma and two patients with brain metastases who developed regions of restricted diffusion after initiation of bevacizumab were included. Six pre-treatment GBM controls were also included. Restriction spectrum imaging (RSI) was used to create diffusion maps which were co-registered with rCBV maps. Within regions of restricted diffusion, mean RSI values and mean rCBV values were calculated for patients with BRIA and for the GBM controls. These values were also calculated for normal-appearing white matter (NAWM). RSI values in regions of restricted diffusion were higher for both BRIA and tumor when compared to NAWM; furthermore RSI values in BRIA were slightly higher than in tumor. Conversely, rCBV values were very low in BRIA-lower than both tumor and NAWM. However, there was only a trend for rCBV values to be higher in tumor than in NAWM. When evaluating areas of restricted diffusion in patients with high-grade glioma or brain metastases treated with bevacizumab, RSI is better able to detect the presence of pathology whereas rCBV is better able to differentiate BRIA from tumor. Thus, combining these tools may help to differentiate necrotic tissue related to bevacizumab treatment from recurrent tumor.

Probing tissue microstructure with restriction spectrum imaging: Histological and theoretical validation.

Water diffusion magnetic resonance imaging (dMRI) is a powerful tool for studying biological tissue microarchitectures in vivo. Recently, there has been increased effort to develop quantitative dMRI methods to probe both length scale and orientation information in diffusion media. Diffusion spectrum imaging (DSI) is one such approach that aims to resolve such information based on the three-dimensional diffusion propagator at each voxel. However, in practice, only the orientation component of the propagator function is preserved when deriving the orientation distribution function. Here, we demonstrate how a straightforward extension of the linear spherical deconvolution (SD) model can be used to probe tissue orientation structures over a range (or "spectrum") of length scales with minimal assumptions on the underlying microarchitecture. Using high b-value Cartesian q-space data on a rat brain tissue sample, we demonstrate how this "restriction spectrum imaging" (RSI) model allows for separating the volume fraction and orientation distribution of hindered and restricted diffusion, which we argue stems primarily from diffusion in the extraneurite and intraneurite water compartment, respectively. Moreover, we demonstrate how empirical RSI estimates of the neurite orientation distribution and volume fraction capture important additional structure not afforded by traditional DSI or fixed-scale SD-like reconstructions, particularly in gray matter. We conclude that incorporating length scale information in geometric models of diffusion offers promise for advancing state-of-the-art dMRI methods beyond white matter into gray matter structures while allowing more detailed quantitative characterization of water compartmentalization and histoarchitecture of healthy and diseased tissue.

A Multicompartmental Diffusion Model for Improved Assessment of Whole-Body Diffusion-weighted Imaging Data and Evaluation of Prostate Cancer Bone Metastases.

Purpose To develop a multicompartmental signal model for whole-body diffusion-weighted imaging (DWI) and apply it to study the diffusion properties of normal tissue and metastatic prostate cancer bone lesions in vivo. Materials and Methods This prospective study (ClinicalTrials.gov: NCT03440554) included 139 men with prostate cancer (mean age, 70 years ± 9 [SD]). Multicompartmental models with two to four tissue compartments were fit to DWI data from whole-body scans to determine optimal compartmental diffusion coefficients. Bayesian information criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness of fit. Diffusion coefficients for the optimal model (having lowest BIC) were used to compute compartmental signal-contribution maps. The signal intensity ratio (SIR) of bone lesions to normal-appearing bone was measured on these signal-contribution maps and on conventional DWI scans and compared using paired t tests (α = .05). Two-sample t tests (α = .05) were used to compare compartmental signal fractions between lesions and normal-appearing bone. Results Lowest BIC was observed from the four-compartment model, with optimal compartmental diffusion coefficients of 0, 1.1 × 10-3, 2.8 × 10-3, and >3.0 ×10-2 mm2/sec. Fitting residuals from this model were significantly lower than from conventional apparent diffusion coefficient mapping (P < .001). Bone lesion SIR was significantly higher on signal-contribution maps of model compartments 1 and 2 than on conventional DWI scans (P < .008). The fraction of signal from compartments 2, 3, and 4 was also significantly different between metastatic bone lesions and normal-appearing bone tissue (P ≤ .02). Conclusion The four-compartment model best described whole-body diffusion properties. Compartmental signal contributions from this model can be used to examine prostate cancer bone involvement. Keywords: Whole-Body MRI, Diffusion-weighted Imaging, Restriction Spectrum Imaging, Diffusion Signal Model, Bone Metastases, Prostate Cancer Clinical trial registration no. NCT03440554 Supplemental material is available for this article. © RSNA, 2023 See also commentary by Margolis in this issue.

Prospective motion correction improves diagnostic utility of pediatric MRI scans.

A new technique for prospectively correcting head motion (called PROMO) during acquisition of high-resolution MRI scans has been developed to reduce motion artifacts. To evaluate the efficacy of PROMO, four T1-weighted image volumes (two with PROMO enabled, two uncorrected) were acquired for each of nine children. A radiologist, blind to whether PROMO was used, rated image quality and artifacts on all sagittal slices of every volume. These ratings were significantly better in scans collected with PROMO relative to those collected without PROMO (Mann-Whitney U test, P < 0.0001). The use of PROMO, especially in motion-prone patients, should improve the accuracy of measurements made for clinical care and research, and potentially reduce the need for sedation in children.

Prospective motion correction of high-resolution magnetic resonance imaging data in children.

Motion artifacts pose significant problems for the acquisition and analysis of high-resolution magnetic resonance imaging data. These artifacts can be particularly severe when studying pediatric populations, where greater patient movement reduces the ability to clearly view and reliably measure anatomy. In this study, we tested the effectiveness of a new prospective motion correction technique, called PROMO, as applied to making neuroanatomical measures in typically developing school-age children. This method attempts to address the problem of motion at its source by keeping the measurement coordinate system fixed with respect to the subject throughout image acquisition. The technique also performs automatic rescanning of images that were acquired during intervals of particularly severe motion. Unlike many previous techniques, this approach adjusts for both in-plane and through-plane movement, greatly reducing image artifacts without the need for additional equipment. Results show that the use of PROMO notably enhances subjective image quality, reduces errors in Freesurfer cortical surface reconstructions, and significantly improves the subcortical volumetric segmentation of brain structures. Further applications of PROMO for clinical and cognitive neuroscience are discussed.

Associations Between Microstructure, Amyloid, and Cognition in Amnestic Mild Cognitive Impairment and Dementia.

BACKGROUND: Although amyloid-ß (Aß) and microstructural brain changes are both effective biomarkers of Alzheimer's disease, their independent or synergistic effects on cognitive decline are unclear. OBJECTIVE: To examine associations of Aß and brain microstructure with cognitive decline in amnestic mild cognitive impairment and dementia. METHODS: Restriction spectrum imaging, cerebrospinal fluid Aß, and longitudinal cognitive data were collected on 23 healthy controls and 13 individuals with mild cognitive impairment or mild to moderate Alzheimer's disease. Neurite density (ND) and isotropic free water diffusion (IF) were computed in fiber tracts and cortical regions of interest. We examined associations of Aß with regional and whole-brain microstructure, and assessed whether microstructure mediates effects of Aß on cognitive decline. RESULTS: Lower ND in limbic and association fibers and higher medial temporal lobe IF predicted baseline impairment and longitudinal decline across multiple cognitive domains. ND and IF predicted cognitive outcomes after adjustment for Aß or whole-brain microstructure. Correlations between microstructure and cognition were present for both amyloid-positive and amyloid-negative individuals. Aß correlated with whole-brain, rather than regional, ND and IF. CONCLUSION: Aß correlates with widespread microstructural brain changes, whereas regional microstructure correlates with cognitive decline. Microstructural abnormalities predict cognitive decline regardless of amyloid, and may inform about neural injury leading to cognitive decline beyond that attributable to amyloid.

Optimal diffusion MRI acquisition for fiber orientation density estimation: an analytic approach.

An important challenge in the design of diffusion MRI experiments is how to optimize statistical efficiency, i.e., the accuracy with which parameters can be estimated from the diffusion data in a given amount of imaging time. In model-based spherical deconvolution analysis, the quantity of interest is the fiber orientation density (FOD). Here, we demonstrate how the spherical harmonics (SH) can be used to form an explicit analytic expression for the efficiency of the minimum variance (maximally efficient) linear unbiased estimator of the FOD. Using this expression, we calculate optimal b-values for maximum FOD estimation efficiency with SH expansion orders of L = 2, 4, 6, and 8 to be approximately b = 1,500, 3,000, 4,600, and 6,200 s/mm(2), respectively. However, the arrangement of diffusion directions and scanner-specific hardware limitations also play a role in determining the realizable efficiency of the FOD estimator that can be achieved in practice. We show how some commonly used methods for selecting diffusion directions are sometimes inefficient, and propose a new method for selecting diffusion directions in MRI based on maximizing the statistical efficiency. We further demonstrate how scanner-specific hardware limitations generally lead to optimal b-values that are slightly lower than the ideal b-values. In summary, the analytic expression for the statistical efficiency of the unbiased FOD estimator provides important insight into the fundamental tradeoff between angular resolution, b-value, and FOD estimation accuracy.

Diagnostic utility of restriction spectrum imaging (RSI) in glioblastoma patients after concurrent radiation-temozolomide treatment: A pilot study.

Discriminating between tumor recurrence and treatment effects in glioblastoma patients undergoing radiation-temozolomide (RT/TMZ) therapy remains a major clinical challenge. Here, we report a pilot study to determine the utility of restriction spectrum imaging (RSI), an advanced diffusion-weighted MRI (DWI) technique that affords meso-scale resolution of cell density, in this assessment. A retrospective review of 31 patients with glioblastoma treated between 2011 and 2017 who underwent surgical resection or biopsy over radiographic concern for tumor recurrence following RT/TMZ was performed. All patients underwent RSI prior to surgical resection. Diagnostic utility of RSI for tumor recurrence was determined in comparison to histopathology. Analysis of surgical specimens revealed treatment effects in 6/31 patients (19%) and tumor recurrence in 25/31 patients (81%). There was general concordance between the measured RSI signal and histopathologic diagnosis. RSI was negative in 5/6 patients (83%) in patients with histological evidence of treatment effects. RSI was positive in 21/25 patients (84%) in patients with tumor recurrence. The sensitivity, specificity, positive and negative predictive values of RSI for glioblastoma recurrence were 84%, 86%, 95%, and 60%, respectively. Histopathologic review showed agreement between the RSI signal and cellularity of the tumor specimen. These data support the use of RSI in the evaluation of treatment effects versus tumor recurrence in glioblastoma patients after RT-TMZ therapy.