April 27, 2018April 10, 2018Free AccessThe ENIGMA Cancer and Chemotherapy Working Group and Cancer-Related Cognitive Impairment (P6.171)Mark Shiroishi, Vikash Gupta, Joshua Faskowitz, Bavrina Bigjahan, Steven Cen, Faisal Rashid, Darryl Hwang, … Show All … , Alexander Lerner, Orest Boyko, Chia-Shang Jason Liu, Meng Law, Paul Thompson, and Neda Jahanshad Show FewerAuthors Info & AffiliationsApril 10, 2018 issue90 (15_supplement) Letters to the Editor

BACKGROUND:Cognitive deficit associated with cancer and its treatment is called cancer-related cognitive impairment (CRCI). Increases in cancer survival have made understanding the basis of CRCI more important. CRCI neuroimaging studies have traditionally used dedicated research brain MRIs in breast cancer survivors after chemotherapy with small sample sizes; little is known about other non-central nervous system (CNS) cancers after chemotherapy as well as those not exposed to chemotherapy. However, there may be a wealth of unused data from clinically-indicated MRIs that could be used to study CRCI.OBJECTIVE:Evaluate brain cortical structural differences in those with various non-CNS cancers using clinically-indicated MRIs.DESIGN:Cross-sectional.PATIENTS:Adult non-CNS cancer and non-cancer control (C) patients who underwent clinically-indicated MRIs.METHODS:Brain cortical surface area and thickness were measured using 3D T1-weighted images. An age-adjusted linear regression model was used and the Benjamini and Hochberg false discovery rate (FDR) corrected for multiple comparisons. Group comparisons were: cancer cases with chemotherapy (Ch+), cancer cases without chemotherapy (Ch-) and subgroup of lung cancer cases with and without chemotherapy vs C.RESULTS:Sixty-four subjects were analyzed: 22 Ch+, 23 Ch- and 19 C patients. Subgroup analysis of 16 lung cancer (LCa) patients was also performed. Statistically significant decreases in either cortical surface area or thickness were found in multiple regions of interest (ROIs) primarily within the frontal and temporal lobes for all comparisons. Effect sizes were variable with the greatest seen in the left middle temporal surface area ROI (Cohen's d -0.690) in the Ch- vs C group comparison.LIMITATIONS:Several limitations were apparent including a small sample size that precluded adjustment for other covariates.CONCLUSIONS:Our preliminary results suggest that, in addition to breast cancer, other types of non-CNS cancers treated with chemotherapy may result in brain structural abnormalities. Similar findings also appear to occur in those not exposed to chemotherapy. These results also suggest that there is potentially a wealth of untapped clinical MRIs that could be used for future CRCI studies.

This article provides an overview of the neuroimaging literature focused on preoperative prediction of meningioma consistency. A validated, noninvasive neuroimaging method to predict tumor consistency can provide valuable information regarding neurosurgical planning and patient counseling. Most of the neuroimaging literature indicates conventional MRI using T2-weighted imaging may be helpful to predict meningioma consistency; however, further rigorous validation is necessary. Much less is known about advanced MRI techniques, such as diffusion MRI, MR elastography (MRE), and MR spectroscopy. Of these methods, MRE and diffusion tensor imaging appear particularly promising.

The quantitative, multiparametric assessment of brain lesions requires coregistering different parameters derived from MRI sequences. This will be followed by analysis of the voxel values of the ROI within the sequences and calculated parametric maps, and deriving multiparametric models to classify imaging data. There is a need for an intuitive, automated quantitative processing framework that is generalized and adaptable to different clinical and research questions. As such flexible frameworks have not been previously described, we proceeded to construct a quantitative post-processing framework with commonly available software components. Matlab was chosen as the programming/integration environment, and SPM was chosen as the coregistration component. Matlab routines were created to extract and concatenate the coregistration transforms, take the coregistered MRI sequences as inputs to the process, allow specification of the ROI, and store the voxel values to the database for statistical analysis. The functionality of the framework was validated using brain tumor MRI cases. The implementation of this quantitative post-processing framework enables intuitive creation of multiple parameters for each voxel, facilitating near real-time in-depth voxel-wise analysis. Our initial empirical evaluation of the framework is an increased usage of analysis requiring post-processing and increased number of simultaneous research activities by clinicians and researchers with non-technical backgrounds. We show that common software components can be utilized to implement an intuitive real-time quantitative post-processing framework, resulting in improved scalability and increased adoption of post-processing needed to answer important diagnostic questions.

A 15-year-old male high school football player presented with episodes of headache and complete body stiffness, especially in the arms, lower back, and thighs, immediately following a football game. This was accompanied by severe nausea and vomiting for several days. Viral meningitis was suspected by the primary clinician, and treatment with corticosteroids was initiated. Over the next several weeks, there was gradual symptom improvement and the patient returned to his baseline clinical status. The patient experienced a severe recurrence of the previous myriad of symptoms following a subsequent football game, without an obvious isolated traumatic episode. In addition, he experienced a new left sided headache, fatigue, and difficulty ambulating. He was admitted and an extensive workup was performed. CT and MRI of the head revealed concurrent intracranial and spinal subdural hematomas (SDH). Clinical workup did not reveal any evidence of coagulopathy or predisposing vascular lesions. Spinal SDH is an uncommon condition whose concurrence with intracranial SDH is an even greater clinical rarity. We suggest that our case represents an acute on chronic intracranial SDH with rebleeding, membrane rupture, and symptomatic redistribution of hematoma to the spinal subdural space.

PurposeTo investigate the spectrum of MRI appearances of ovarian serous borderline tumor (SBT).Materials and MethodsFollowing ethics approval, 31 patients with 51 histologically proven ovarian SBTs underwent preoperative MRI. Images were evaluated, by two observers for the location, shape, size, internal architecture, signal intensity, and extent or stage of the tumors. The MRI findings were correlated with pathological findings.ResultsTwenty of 31 patients (65%) demonstrated bilateral ovarian SBTs on MRI. Three MRI morphological patterns of ovarian SBT were identified: (i) Mainly cystic mass with multiple intracystic papillary projections from the wall and septations was observed in 24 (47%) tumors. (ii) Solid mass with hierarchical branching papillary and fibrous stalk architecture was observed in 8 (16%) tumors. The branching papillary projections were hyperintensity on T2WI, intermediate intense on DWI, and enhanced intensely after the administration of Gd‐DTPA. The internal branching fibrous stalks were hypointensity on T2WI and enhanced slightly. (iii) Mixed cystic‐solid mass was observed in 19 (37%) tumors. The cystic and solid components had the architecture and signal intensity similar to those of cystic and solid SBTs. Papillary projections were the common architecture of all three types of tumors.ConclusionOn MRI, the ovarian SBT has some morphological distinguishing features. The solid papillary architecture with internal branching fibrous stalk is a somewhat more characteristic MRI appearance. J. Magn. Reson. Imaging 2014;40:151–156. © 2013 Wiley Periodicals, Inc.

BACKGROUNDBilateral vocal cord paralysis is a risk of anterior cervical discoidectomy and fusion. We discuss the mechanism of vocal cord paralysis and the precautions necessary to avoid this catastrophic complication. A rare case of bilateral vocal cord paralysis after anterior cervical discoidectomy and fusion (ACD/F) is reported.CASE DESCRIPTIONThe patient, a 37-year-old male, was paraplegic, had bilateral intrinsic hand muscle weakness and sphincter involvement following a whiplash cervical spinal injury. A C5-C6 ACD/F for traumatic C5-C6 disc prolapse was performed. On the third postoperative day, he developed difficulty in coughing and a husky voice. Otolaryngological evaluation revealed bilateral vocal cord paralysis. He later required a tracheostomy that partially alleviated his major symptoms.CONCLUSIONIn patients undergoing ACD/F, a mandatory preoperative evaluation of the vocal cords should be performed. An appropriate modification in surgical planning should be made if vocal cord palsy is diagnosed preoperatively to prevent bilateral vocal cord paralysis. Proper and judicious use of Cloward retractors is advocated.

We propose a novel Dynamic Recursive Partitioning approach for discovering discriminative patterns of functional MRI activation. The goal is to efficiently identify spatial regions that are associated with non-spatial variables through adaptive recursive partitioning of the 3D space into a number of hyper-rectangles utilizing statistical tests. As a case study, we analyze fMRI datasets obtained from a study that explores neuroanatomical correlates of semantic processing in Alzheimer's disease. We seek to discover brain activation areas that discriminate controls from patients. We evaluate the results by presenting classification experiments that utilize information extracted from these regions. The discovered areas elucidated large hemispheric and lobar differences being consistent with prior findings. The overall classification accuracy based on activation patterns in these areas exceeded 90%. The proposed approach being general enough has great potential for elucidating structure-function relationships and can be valuable to human brain mapping.

Purpose: To effectively identify discriminative spatial areas in MRI and fMRI and make image classification, similarity searches and mining of associations between spatial distributions and other clinical assessment feasible we have developed brain informatics tools that are based on adaptive recursive partitioning and use of statistical tests. Method We developed a methodology for classification and association mining that is based on adaptive recursive partitioning of a 3D volume into a number of hyper-rectangles. The goal is to efficiently identify spatial regions that are associated with non-spatial variables thus reducing the computational complexity of the voxel-based approach and resolving the multiple comparisons problem due to reduction on the number of tests performed. The main idea is that a particular hyper-rectangle is further partitioned if it does not have high discriminative power determined by a statistical test (chi-square/Fisher's exact, t-test, Wilcoxon rank sum test), but it is sufficiently large for further splitting. The statistical test is applied so many times as the number of partitions rather than as the number of voxels in a voxel-based analysis. In preliminary analysis, we consider, as a potential attribute for each hyper-rectangle, the sum of mean value of voxels that belong to regions of interest. The attributes of the final discriminative hyper-rectangles form new attributes that are used with classification models such as neural networks and decision trees. Using the proposed adaptive recursive partitioning method we performed initial analysis of an fMRI Alzheimer's contrast data set. The particular study (1) was designed to systematically explore neuroanatomical correlates of semantic processing in Alzheimer disease by contrasting patterns of neural activation in patients with those of controls during a series of semantic decision tasks. These tasks were selected to differentially probe semantic knowledge of categorical, functional, and phonological congruence between word pairs. Each class of this dataset consisted of 9 subjects and the experimental results were evaluated using 9-fold cross validation. Results The adaptive recursive partitioning technique found certain activation areas within the medial temporal lobe that discriminate best Alzheimer patients from controls. Although the classification accuracy of statistical distance based and maximum likelihood methods was almost 50% (same as random guess) the proposed adaptive recursive partitioning technique achieved classification accuracy of 90%. This result is really impressive given the small data set of 9 controls and 9 subjects, its heterogeneity, and difficulty in generalizing the patterns observed. Conclusions The proposed method has been shown capable of identifying discriminative spatial areas of brain activation maps between Alzheimer and normal subjects providing also accurate classification. The proposed approach being general enough can be potential applied to elucidate structure-function relationships and be valuable to human brain mapping.

Richard F. Thompson's cerebellar model of classical eyeblink conditioning highlights Purkinje cells in cerebellar cortex and principal cells in the deep cerebellar nucleus as the integrating cells for acquisition of conditioned responses (CRs). CR acquisition is significantly slower in rabbits with lesions to cerebellar cortex and in Purkinje cell-deficient mice that lose all cerebellar cortical Purkinje cells. Purkinje cells are the largest neurons in the cerebellum and contribute significantly to cerebellar volume. Magnetic resonance imaging (MRI) was used to assess cerebellar volume in humans. Cerebellar volume was related to eyeblink conditioning (400-ms delay procedure) in 8 adults (21-35 years) and compared to 8 older adults (77-95 years) tested previously (Woodruff-Pak, Goldenberg, Downey-Lamb, Boyko, & Lemieux, 2000). In the young adult sample, there was a high correlation between percentage of CRs in a session and cerebellar volume (corrected for total intracranial volume [TIV], r =.58, p =.066). There were statistically significant age differences in cerebellar volume, t(14) = 8.96, p <.001, and percentage of CRs, t(14) = 3.85, p <.002, but no age difference in TIV. Combining the young and older adult sample, the correlation between percentage of CRs and cerebellar volume (corrected for TIV) was.832 (p <.001). Cerebellar volume showed age-related deficits likely due to Purkinje cell loss. Individual differences in classical eyeblink conditioning are associated with differences in cerebellar volume, supporting Thompson's model of a cerebellar cortical role in facilitating this form of associative learning.

Neural circuits in the cerebellum are essential for eyeblink classical conditioning, and hippocampal activation is also present during acquisition. Anatomical (volumetric) brain MRI, delay eyeblink conditioning and neuropsychological tests were administered to eight healthy older subjects. The correlation between cerebellar volume (corrected for total cerebral volume) and conditioned response percentage was 0.81 (p < 0.02), but neither hippocampal nor total cerebral volume correlated with conditioning or any neuropsychological test scores. There was no relationship between age and cerebellar volume, but the correlation between hippocampal volume and age was −0.80 (p < 0.02). These volumetric results add to the increasing evidence in humans demonstrating a relationship between the integrity of the cerebellum and eyeblink classical conditioning.

Magnetic resonance spectroscopy (MRS) is a non-invasive functional imaging technique that can measure various brain tissue metabolites such as N-acetylaspartate (NAA), choline (Cho), creatine-phosphocreatine (Cr), myo-inositol (mI) and other metabolites. Morphological studies have indicated the pons and cerebellum as possible sites of abnormal functioning in schizophrenic patients. This study examines schizophrenic patients for the presence of abnormalities in proton MRS (1H-MRS) measured metabolites in two regions of the posterior fossa. Twelve schizophrenic patients and eight non-schizophrenic control subjects were studied by measuring the ratios of NAA/Cr, Cho/Cr and mI/Cr from 1H-spectra obtained from the pons and right or left cerebellum using an integrated MRI/MRS protocol. Spectra were obtained from a voxel in the pons and voxels from the left and/or right lateral cerebellum. Data were analyzed in the absorption mode and fitted to Lorentzian lineshapes using a Marquart algorithm. Significantly lower NAA/Cr ratios were found in the pons of schizophrenic patients than in the control subjects, but not in the cerebellum. This study is the first to measure brain tissue metabolites using 1H-MRS in the pons and cerebellum of schizophrenic patients. Significant alterations of 1H-MRS metabolites may suggest the involvement of the posterior fossa as a part of the pathological substrate underlying schizophrenia.

1. Seven subjects with depression and matched controls were studied using proton spectroscopy to test the hypothesis that choline will be elevated in depression.2. The proton spectroscopy was repeated after recovery from depression.3. The study confirmed a state dependent increase in choline in the brain.4. This change may be used as an in vivo marker of change in depression.

1. The present study was done to assess the brain metabolites measured by proton magnetic resonance spectroscopy (MRS) in normal individuals. 2. Proton spectroscopy STEAM voxel technique with chemical shift imaging was used to provide localized metabolic information from the brains of 34 normal volunteers (15 males) between the ages of 21 and 75 years. 3. Choline, Creatine and N-acetyl aspartate (NAA) was lower in white matter than gray matter. Choline/NAA and choline/creatine ratios were also lower in white matter. The choline, creatine and NAA were lower in older subjects in the voxel representing cortical and subcortical gray matter. There were no differences between males and females. 4. This preliminary study suggests that age matching is essential for comparative studies of disease states using proton MRS.