Natalie M. Schenker-Ahmed

Postmortem examination of patient H.M.’s brain based on histological sectioning and digital 3D reconstruction

Modern scientific knowledge of how memory functions are organized in the human brain originated from the case of Henry G. Molaison (H.M.), an epileptic patient whose amnesia ensued unexpectedly following a bilateral surgical ablation of medial temporal lobe structures, including the hippocampus. The neuroanatomical extent of the 1953 operation could not be assessed definitively during H.M.’s life. Here we describe the results of a procedure designed to reconstruct a microscopic anatomical model of the whole brain and conduct detailed 3D measurements in the medial temporal lobe region. This approach, combined with cellular-level imaging of stained histological slices, demonstrates a significant amount of residual hippocampal tissue with distinctive cytoarchitecture. Our study also reveals diffuse pathology in the deep white matter and a small, circumscribed lesion in the left orbitofrontal cortex. The findings constitute new evidence that may help elucidate the consequences of H.M.’s operation in the context of the brain’s overall pathology.

Novel technique for characterizing prostate cancer utilizing MRI restriction spectrum imaging: proof of principle and initial clinical experience with extraprostatic extension

Background:Standard magnetic resonance imaging (MRI) of the prostate lacks sensitivity in the diagnosis and staging of prostate cancer (PCa). To improve the operating characteristics of prostate MRI in the detection and characterization of PCa, we developed a novel, enhanced MRI diffusion technique using restriction spectrum imaging (RSI-MRI).Methods:We compared the efficacy of our novel RSI-MRI technique with standard MRI for detecting extraprostatic extension (EPE) among 28 PCa patients who underwent MRI and RSI-MRI prior to radical prostatectomy, 10 with histologically proven pT3 disease. RSI cellularity maps isolating the restricted isotropic water fraction were reconstructed based on all b-values and then standardized across the sample with z-score maps. Distortion correction of the RSI maps was performed using the alternating phase-encode technique.Results:27 patients were evaluated, excluding one patient where distortion could not be performed. Preoperative standard MRI correctly identified extraprostatic the extension in two of the nine pT3 (22%) patients, whereas RSI-MRI identified EPE in eight of nine (89%) patients. RSI-MRI correctly identified pT2 disease in the remaining 18 patients.Conclusions:In this proof of principle study, we conclude that our novel RSI-MRI technology is feasible and shows promise for substantially improving PCa imaging. Further translational studies of prostate RSI-MRI in the diagnosis and staging of PCa are indicated.

Evidence for evolutionary specialization in human limbic structures

Increasingly, functional and evolutionary research has highlighted the important contribution emotion processing makes to complex human social cognition. As such, it may be asked whether neural structures involved in emotion processing, commonly referred to as limbic structures, have been impacted in human brain evolution. To address this question, we performed an extensive evolutionary analysis of multiple limbic structures using modern phylogenetic tools. For this analysis, we combined new volumetric data for the hominoid (human and ape) amygdala and 4 amygdaloid nuclei, hippocampus, and striatum, collected using stereological methods in complete histological series, with previously published datasets on the amygdala, orbital and medial frontal cortex, and insula, as well as a non-limbic structure, the dorsal frontal cortex, for contrast. We performed a parallel analysis using large published datasets including many anthropoid species (human, ape, and monkey), but fewer hominoids, for the amygdala and 2 amygdaloid subdivisions, hippocampus, schizocortex, striatum, and septal nuclei. To address evolutionary change, we compared observed human values to values predicted from regressions run through (a) non-human hominoids and (b) non-human anthropoids, assessing phylogenetic influence using phylogenetic generalized least squares regression. Compared with other hominoids, the volumes of the hippocampus, the lateral nucleus of the amygdala, and the orbital frontal cortex were, respectively, 50, 37, and 11% greater in humans than predicted for an ape of human hemisphere volume, while the medial and dorsal frontal cortex were, respectively, 26 and 29% significantly smaller. Compared with other anthropoids, only human values for the striatum fell significantly below predicted values. Overall, the data present support for the idea that regions involved in emotion processing are not necessarily conserved or regressive, but may even be enhanced in recent human evolution.

Prostate diffusion imaging with distortion correction

PURPOSE Diffusion imaging in the prostate is susceptible to distortion from B0 inhomogeneity. Distortion correction in prostate imaging is not routinely performed, resulting in diffusion images without accurate localization of tumors. We performed and evaluated distortion correction for diffusion imaging in the prostate. MATERIALS AND METHODS 28 patients underwent pre-operative MRI (T2, Gadolinium perfusion, diffusion at b=800 s/mm(2)). The restriction spectrum protocol parameters included b-values of 0, 800, 1500, and 4000 s/mm(2) in 30 directions for each nonzero b-value. To correct for distortion, forward and reverse trajectories were collected at b=0 s/mm(2). Distortion maps were generated to reflect the offset of the collected data versus the corrected data. Whole-mount histology was available for correlation. RESULTS Across the 27 patients evaluated (excluding one patient due to data collection error), the average root mean square distortion distance of the prostate was 3.1 mm (standard deviation, 2.2mm; and maximum distortion, 12 mm). CONCLUSION Improved localization of prostate cancer by MRI will allow better surgical planning, targeted biopsies and image-guided treatment therapies. Distortion distances of up to 12 mm due to standard diffusion imaging may grossly misdirect treatment decisions. Distortion correction for diffusion imaging in the prostate improves tumor localization.

MRI-Derived Restriction Spectrum Imaging Cellularity Index is Associated with High Grade Prostate Cancer on Radical Prostatectomy Specimens.

Purpose: We evaluate a novel magnetic resonance imaging (MRI) technique to improve detection of aggressive prostate cancer (PCa). Materials and Methods: We performed a retrospective analysis of pre-surgical prostate MRI scans using an advanced diffusion-weighted imaging technique called restriction spectrum imaging (RSI), which can be presented as a normalized z-score statistic. Scans were acquired prior to radical prostatectomy. Prostatectomy specimens were processed using whole-mount sectioning and regions of interest (ROIs) were drawn around individual PCa tumors. Corresponding ROIs were drawn on the MRI imaging and paired with ROIs in regions with no pathology. RSI z-score and conventional apparent diffusion coefficient (ADC) values were recorded for each ROI. Paired t-test, ANOVA, and logistic regression analyses were performed. Results: We evaluated 28 patients with 64 ROIs (28 benign and 36 PCa). The mean difference in RSI z-score (PCa ROI–Benign ROI) was 2.17 (SE = 0.11; p < 0.001) and in ADC was 551 mm2/s (SE = 80 mm2/s; paired t-test, p < 0.001). The differences in the means among all groups (benign, primary Gleason 3, and primary Gleason 4) was significant for both RSI z-score (F3,64 = 97.7, p < 0.001) and ADC (F3,64 = 13.9, p < 0.001). A t-test was performed on only PCa tumor ROIs (n = 36) to determine PCa aggressiveness (Gleason 3 vs. Gleason 4) revealing that RSI z-score was still significant (p = 0.03), whereas, ADC values were no longer significant (p = 0.08). In multivariable analysis adjusting for age and race, RSI z-score was associated with PCa aggressiveness (OR 10.3, 95% CI: 1.4–78.0, p = 0.02) while ADC trended to significance (p = 0.07). Conclusion: The RSI-derived normalized cellularity index is associated with aggressive PCa as determined by pathologic Gleason scores. Further utilization of RSI techniques may serve to enhance standardized reporting systems for PCa in the future.

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.

In vivo prostate cancer detection and grading using restriction spectrum imaging-MRI.

Background:Magnetic resonance imaging (MRI) is emerging as a robust, noninvasive method for detecting and characterizing prostate cancer (PCa), but limitations remain in its ability to distinguish cancerous from non-cancerous tissue. We evaluated the performance of a novel MRI technique, restriction spectrum imaging (RSI-MRI), to quantitatively detect and grade PCa compared with current standard-of-care MRI.Methods:In a retrospective evaluation of 33 patients with biopsy-proven PCa who underwent RSI-MRI and standard MRI before radical prostatectomy, receiver-operating characteristic (ROC) curves were performed for RSI-MRI and each quantitative MRI term, with area under the ROC curve (AUC) used to compare each term’s ability to differentiate between PCa and normal prostate. Spearman rank-order correlations were performed to assess each term’s ability to predict PCa grade in the radical prostatectomy specimens.Results:RSI-MRI demonstrated superior differentiation of PCa from normal tissue, with AUC of 0.94 and 0.85 for RSI-MRI and conventional diffusion MRI, respectively (P=0.04). RSI-MRI also demonstrated superior performance in predicting PCa aggressiveness, with Spearman rank-order correlation coefficients of 0.53 (P=0.002) and −0.42 (P=0.01) for RSI-MRI and conventional diffusion MRI, respectively, with tumor grade.Conclusions:RSI-MRI significantly improves upon current noninvasive PCa imaging and may potentially enhance its diagnosis and characterization.

Demonstration of Non-Gaussian Restricted Diffusion in Tumor Cells Using Diffusion Time-Dependent Diffusion-Weighted Magnetic Resonance Imaging Contrast

The diffusion-weighted magnetic resonance imaging (DWI) technique enables quantification of water mobility for probing microstructural properties of biological tissue and has become an effective tool for collecting information about the underlying pathology of cancerous tissue. Measurements using multiple b-values have indicated biexponential signal attenuation, ascribed to “fast” (high ADC) and “slow” (low ADC) diffusion components. In this empirical study, we investigate the properties of the diffusion time (Δ)-dependent components of the diffusion-weighted (DW) signal in a constant b-value experiment. A xenograft gliobastoma mouse was imaged using Δ = 11 ms, 20 ms, 40 ms, 60 ms, and b = 500–4000 s/mm2 in intervals of 500 s/mm2. Data were corrected for EPI distortions, and the Δ-dependence on the DW-signal was measured within three regions of interest [intermediate- and high-density tumor regions and normal-appearing brain (NAB) tissue regions]. In this study, we verify the assumption that the slow decaying component of the DW-signal is non-Gaussian and dependent on Δ, consistent with restricted diffusion of the intracellular space. As the DW-signal is a function of Δ and is specific to restricted diffusion, manipulating Δ at constant b-value (cb) provides a complementary and direct approach for separating the restricted from the hindered diffusion component. We found that Δ-dependence is specific to the tumor tissue signal. Based on an extended biexponential model, we verified the interpretation of the diffusion time-dependent contrast and successfully estimated the intracellular restricted ADC, signal volume fraction, and cell size within each ROI.

Cortical mapping by magnetic resonance imaging (MRI) and quantitative cytological analysis in the human brain: A feasibility study in the fusiform gyrus

The cerebral cortex is a layered cellular structure that is tangentially organized into a mosaic of anatomically and functionally distinct fields. In spite of centuries of investigation, the precise localization and classification of many areas in the cerebral cortex remain problematic because the relationship between functional specificity and intra-cortical structure has not been firmly established. Furthermore, it is not yet clear how surface landmarks, visible through gross examination and, more recently, using non-invasive magnetic resonance imaging (MRI), relate to underlying microstructural borders and to the topography of functional activation. We have designed a multi-modal neuroimaging protocol that combines MRI and quantitative microscopic analysis in the same individual to clarify the topography of cytoarchitecture underlying gross anatomical landmarks in the cerebral cortex. We tested our approach in the region of the fusiform gyrus (FG) because, in spite of its seemingly smooth appearance on the ventral aspect of both hemispheres, this structure houses many functionally defined areas whose histological borders remain unclear. In practice, we used MRI-based automated segmentation to define the region of interest from which we could then collect quantitative histological data (specifically, neuronal size and density). A modified stereological approach was used to sample the cortex within the FG without a priori assumptions on the location of architectonic boundaries. The results of these analyses illustrate architectonic variations along the FG and demonstrate that it is possible to correlate quantitative histological data to measures that are obtained in the context of large-scale, non-invasive MRI-based population studies.

Voxel Level Radiologic–Pathologic Validation of Restriction Spectrum Imaging Cellularity Index with Gleason Grade in Prostate Cancer

Purpose: Restriction spectrum imaging (RSI-MRI), an advanced diffusion imaging technique, can potentially circumvent current limitations in tumor conspicuity, in vivo characterization, and location demonstrated by multiparametric magnetic resonance imaging (MP-MRI) techniques in prostate cancer detection. Prior reports show that the quantitative signal derived from RSI-MRI, the cellularity index, is associated with aggressive prostate cancer as measured by Gleason grade (GG). We evaluated the reliability of RSI-MRI to predict variance with GG at the voxel-level within clinically demarcated prostate cancer regions. Experimental Design: Ten cases were processed using whole mount sectioning after radical prostatectomy. Regions of tumor were identified by an uropathologist. Stained prostate sections were scanned at high resolution (75 μm/pixel). A grid of tiles corresponding to voxel dimensions was graded using the GG system. RSI-MRI cellularity index was calculated from presurgical prostate MR scans and presented as normalized z-score maps. In total, 2,795 tiles were analyzed and compared with RSI-MRI cellularity. Results: RSI-MRI cellularity index was found to distinguish between prostate cancer and benign tumor (t = 25.48, P < 0.00001). Significant differences were also found between benign tissue and prostate cancer classified as low-grade (GG = 3; t = 11.56, P < 0.001) or high-grade (GG ≥ 4; t = 24.03, P < 0.001). Furthermore, RSI-MRI differentiated between low and high-grade prostate cancer (t = 3.23; P = 0.003). Conclusions: Building on our previous findings of correlation between GG and the RSI-MRI among whole tumors, our current study reveals a similar correlation at voxel resolution within tumors. Because it can detect variations in tumor grade with voxel-level precision, RSI-MRI may become an option for planning targeted procedures where identifying the area with the most aggressive disease is important. Clin Cancer Res; 22(11); 2668–74. ©2016 AACR.