Publications by authors named "Kambiz Nael"

80 Publications

Automated detection of critical findings in multi-parametric brain MRI using a system of 3D neural networks.

Sci Rep 2021 Mar 25;11(1):6876. Epub 2021 Mar 25.

Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, USA.

With the rapid growth and increasing use of brain MRI, there is an interest in automated image classification to aid human interpretation and improve workflow. We aimed to train a deep convolutional neural network and assess its performance in identifying abnormal brain MRIs and critical intracranial findings including acute infarction, acute hemorrhage and mass effect. A total of 13,215 clinical brain MRI studies were categorized to training (74%), validation (9%), internal testing (8%) and external testing (8%) datasets. Up to eight contrasts were included from each brain MRI and each image volume was reformatted to common resolution to accommodate for differences between scanners. Following reviewing the radiology reports, three neuroradiologists assigned each study to abnormal vs normal, and identified three critical findings including acute infarction, acute hemorrhage, and mass effect. A deep convolutional neural network was constructed by a combination of localization feature extraction (LFE) modules and global classifiers to identify the presence of 4 variables in brain MRIs including abnormal, acute infarction, acute hemorrhage and mass effect. Training, validation and testing sets were randomly defined on a patient basis. Training was performed on 9845 studies using balanced sampling to address class imbalance. Receiver operating characteristic (ROC) analysis was performed. The ROC analysis of our models for 1050 studies within our internal test data showed AUC/sensitivity/specificity of 0.91/83%/86% for normal versus abnormal brain MRI, 0.95/92%/88% for acute infarction, 0.90/89%/81% for acute hemorrhage, and 0.93/93%/85% for mass effect. For 1072 studies within our external test data, it showed AUC/sensitivity/specificity of 0.88/80%/80% for normal versus abnormal brain MRI, 0.97/90%/97% for acute infarction, 0.83/72%/88% for acute hemorrhage, and 0.87/79%/81% for mass effect. Our proposed deep convolutional network can accurately identify abnormal and critical intracranial findings on individual brain MRIs, while addressing the fact that some MR contrasts might not be available in individual studies.
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http://dx.doi.org/10.1038/s41598-021-86022-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7994311PMC
March 2021

Trans-synaptic degeneration of the optic radiation from optic nerve atrophy.

Radiol Case Rep 2021 Apr 30;16(4):855-857. Epub 2021 Jan 30.

Department of Radiological Sciences, David Geffen School of Medicine at University of California Los Angeles, CA, USA.

Fourty-seven-year-old woman with 5-year history of progressive decreased left eye vision. Optical coherence tomography showed optic nerve atrophy (left > right) and brain MRI revealed T2 hyperintense signal along the course of left optic radiations. We present a case of a trans-synaptic degeneration of the optic radiation in a patient with confirmed optic atrophy. Trans-synaptic degeneration of the optic radiation without associated infarct or inflammatory disease has not been reported before in patients with optic atrophy.
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http://dx.doi.org/10.1016/j.radcr.2021.01.017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7850934PMC
April 2021

GAMER MRI: Gated-attention mechanism ranking of multi-contrast MRI in brain pathology.

Neuroimage Clin 2021 3;29:102522. Epub 2020 Dec 3.

Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel, University Hospital Basel and University of Basel, Basel, Switzerland.

Introduction: During the last decade, a multitude of novel quantitative and semiquantitative MRI techniques have provided new information about the pathophysiology of neurological diseases. Yet, selection of the most relevant contrasts for a given pathology remains challenging. In this work, we developed and validated a method, Gated-Attention MEchanism Ranking of multi-contrast MRI in brain pathology (GAMER MRI), to rank the relative importance of MR measures in the classification of well understood ischemic stroke lesions. Subsequently, we applied this method to the classification of multiple sclerosis (MS) lesions, where the relative importance of MR measures is less understood.

Methods: GAMER MRI was developed based on the gated attention mechanism, which computes attention weights (AWs) as proxies of importance of hidden features in the classification. In the first two experiments, we used Trace-weighted (Trace), apparent diffusion coefficient (ADC), Fluid-Attenuated Inversion Recovery (FLAIR), and T1-weighted (T1w) images acquired in 904 acute/subacute ischemic stroke patients and in 6,230 healthy controls and patients with other brain pathologies to assess if GAMER MRI could produce clinically meaningful importance orders in two different classification scenarios. In the first experiment, GAMER MRI with a pretrained convolutional neural network (CNN) was used in conjunction with Trace, ADC, and FLAIR to distinguish patients with ischemic stroke from those with other pathologies and healthy controls. In the second experiment, GAMER MRI with a patch-based CNN used Trace, ADC and T1w to differentiate acute ischemic stroke lesions from healthy tissue. The last experiment explored the performance of patch-based CNN with GAMER MRI in ranking the importance of quantitative MRI measures to distinguish two groups of lesions with different pathological characteristics and unknown quantitative MR features. Specifically, GAMER MRI was applied to assess the relative importance of the myelin water fraction (MWF), quantitative susceptibility mapping (QSM), T1 relaxometry map (qT1), and neurite density index (NDI) in distinguishing 750 juxtacortical lesions from 242 periventricular lesions in 47 MS patients. Pair-wise permutation t-tests were used to evaluate the differences between the AWs obtained for each quantitative measure.

Results: In the first experiment, we achieved a mean test AUC of 0.881 and the obtained AWs of FLAIR and the sum of AWs of Trace and ADC were 0.11 and 0.89, respectively, as expected based on previous knowledge. In the second experiment, we achieved a mean test F1 score of 0.895 and a mean AW of Trace = 0.49, of ADC = 0.28, and of T1w = 0.23, thereby confirming the findings of the first experiment. In the third experiment, MS lesion classification achieved test balanced accuracy = 0.777, sensitivity = 0.739, and specificity = 0.814. The mean AWs of T1map, MWF, NDI, and QSM were 0.29, 0.26, 0.24, and 0.22 (p < 0.001), respectively.

Conclusions: This work demonstrates that the proposed GAMER MRI might be a useful method to assess the relative importance of MRI measures in neurological diseases with focal pathology. Moreover, the obtained AWs may in fact help to choose the best combination of MR contrasts for a specific classification problem.
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http://dx.doi.org/10.1016/j.nicl.2020.102522DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7773673PMC
December 2020

Prospective Motion Correction for Brain MRI Using an External Tracking System.

J Neuroimaging 2021 Jan 4;31(1):57-61. Epub 2020 Nov 4.

Department of Radiology, Biomedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY.

Background And Purpose: A wide range of strategies have been developed to mitigate motion, as a major source of image quality degradation in clinical MRI. We aimed to assess the efficiency of a commercially available prospective motion correction (PMC) system in reducing motion in acquiring high-resolution 3D magnetization-prepared rapid gradient-echo (MPRAGE).

Methods: A total of 100 patients who referred for brain MRI studies were prospectively imaged using a 3.0T scanner. 3D MPRAGE acquisition was obtained with and without application of PMC. The motion tracking system (KinetiCor Inc.) consisted of a quad camera apparatus, which tracks a specific marker on patient's head by evaluating the marker's optical pattern. The patient's head motion in 6 degrees of freedom throughout the acquisition was then incorporated into the MRI sequence, updating the image acquisition in real time based on the most recent head pose data. MPRAGE images with and without motion correction were assessed independently by two board-certified neuroradiologists using a 5-point Likert scale. Statistical analysis included kappa and Wilcoxon Rank-Sum tests.

Results: Observers 1 and 2 identified nondiagnostic studies in 17.2% and 20.7% of patients (K = .78, 95% CI .70-.86) without motion correction and in 5.7% and 8% of the studies with motion correction (K = .84, 95% CI .76-.92). The number of nondiagnostic studies was significantly (P = .001) reduced from 19.5% to 5.7% after motion correction in consensus read analysis.

Conclusion: The described motion tracking system can be used effectively in clinical practice reducing motion artifact and improving image quality of 3D MPRAGE sequence.
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http://dx.doi.org/10.1111/jon.12806DOI Listing
January 2021

MRI Radiomic Features to Predict IDH1 Mutation Status in Gliomas: A Machine Learning Approach using Gradient Tree Boosting.

Int J Mol Sci 2020 Oct 27;21(21). Epub 2020 Oct 27.

Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

Patients with gliomas, isocitrate dehydrogenase 1 () mutation status have been studied as a prognostic indicator. Recent advances in machine learning (ML) have demonstrated promise in utilizing radiomic features to study disease processes in the brain. We investigate whether ML analysis of multiparametric radiomic features from preoperative Magnetic Resonance Imaging (MRI) can predict mutation status in patients with glioma. This retrospective study included patients with glioma with known status and preoperative MRI. Radiomic features were extracted from Fluid-Attenuated Inversion Recovery (FLAIR) and Diffused Weighted Imaging (DWI). The dataset was split into training, validation, and testing sets by stratified sampling. Synthetic Minority Oversampling Technique (SMOTE) was applied to the training sets. eXtreme Gradient Boosting (XGBoost) classifiers were trained, and the hyperparameters were tuned. Receiver operating characteristic curve (ROC), accuracy, and f1-scores were collected. A total of 100 patients (age: 55 ± 15, M/F 60/40); with mutant ( = 22) and wildtype ( = 78) were included. The best performance was seen with a DWI-trained XGBoost model, which achieved ROC with Area Under the Curve (AUC) of 0.97, accuracy of 0.90, and f1-score of 0.75 on the test set. The FLAIR-trained XGBoost model achieved ROC with AUC of 0.95, accuracy of 0.90, f1-score of 0.75 on the test set. A model that was trained on combined FLAIR-DWI radiomic features did not provide incremental accuracy. The results show that a XGBoost classifier using multiparametric radiomic features derived from preoperative MRI can predict mutation status with > 90% accuracy.
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http://dx.doi.org/10.3390/ijms21218004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7662499PMC
October 2020

Amplified Flow Imaging (aFlow): A Novel MRI-Based Tool to Unravel the Coupled Dynamics Between the Human Brain and Cerebrovasculature.

IEEE Trans Med Imaging 2020 12 30;39(12):4113-4123. Epub 2020 Nov 30.

With each heartbeat, periodic variations in arterial blood pressure are transmitted along the vasculature, resulting in localized deformations of the arterial wall and its surrounding tissue. Quantification of such motions may help understand various cerebrovascular conditions, yet it has proven technically challenging thus far. We introduce a new image processing algorithm called amplified Flow (aFlow) which allows to study the coupled brain-blood flow motion by combining the amplification of cine and 4D flow MRI. By incorporating a modal analysis technique known as dynamic mode decomposition into the algorithm, aFlow is able to capture the characteristics of transient events present in the brain and arterial wall deformation. Validating aFlow, we tested it on phantom simulations mimicking arterial walls motion and observed that aFlow displays almost twice higher SNR than its predecessor amplified MRI (aMRI). We then applied aFlow to 4D flow and cine MRI datasets of 5 healthy subjects, finding high correlations between blood flow velocity and tissue deformation in selected brain regions, with correlation values r = 0.61 , 0.59, 0.52 for the pons, frontal and occipital lobe ( ). Finally, we explored the potential diagnostic applicability of aFlow by studying intracranial aneurysm dynamics, which seems to be indicative of rupture risk. In two patients, aFlow successfully visualized the imperceptible aneurysm wall motion, additionally quantifying the increase in the high frequency wall displacement after a one-year follow-up period (20%, 76%). These preliminary data suggest that aFlow may provide a novel imaging biomarker for the assessment of aneurysms evolution, with important potential diagnostic implications.
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http://dx.doi.org/10.1109/TMI.2020.3012932DOI Listing
December 2020

Addition of arterial spin-labelled MR perfusion to conventional brain MRI: clinical experience in a retrospective cohort study.

BMJ Open 2020 06 11;10(6):e036785. Epub 2020 Jun 11.

Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA

Objective: The usage of arterial spin labelling (ASL) perfusion has exponentially increased due to improved and faster acquisition time and ease of postprocessing. We aimed to report potential additional findings obtained by adding ASL to routine unenhanced brain MRI for patients being scanned in a hospital setting for various neurological indications.

Design: Retrospective.

Setting: Large tertiary hospital.

Participants: 676 patients.

Primary Outcome: Additional findings from ASL sequence compared with conventional MRI.

Results: Our patient cohorts consisted of 676 patients with 257 with acute infarcts and 419 without an infarct. Additional findings from ASL were observed in 13.9% (94/676) of patients. In the non-infarct group, additional findings from ASL were observed in 7.4% (31/419) of patients, whereas in patients with an acute infarct, supplemental information was obtained in 24.5% (63/257) of patients.

Conclusion: The addition of an ASL sequence to routine brain MRI in a hospital setting provides additional findings compared with conventional brain MRI in about 7.4% of patients with additional supplementary information in 24.5% of patients with acute infarct.
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http://dx.doi.org/10.1136/bmjopen-2020-036785DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295400PMC
June 2020

Postoperative outcomes following glioblastoma resection using a robot-assisted digital surgical exoscope: a case series.

J Neurooncol 2020 Jul 9;148(3):519-527. Epub 2020 Jun 9.

Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, NY, USA.

Introduction: Maximal extent of resection (EOR) of glioblastoma (GBM) is associated with greater progression free survival (PFS) and improved patient outcomes. Recently, a novel surgical system has been developed that includes a 2D, robotically-controlled exoscope and brain tractography display. The purpose of this study was to assess outcomes in a series of patients with GBM undergoing resections using this surgical exoscope.

Methods: A retrospective review was conducted for robotic exoscope assisted GBM resections between 2017 and 2019. EOR was computed from volumetric analyses of pre- and post-operative MRIs. Demographics, pathology/MGMT status, imaging, treatment, and outcomes data were collected. The relationship between these perioperative variables and discharge disposition as well as progression-free survival (PFS) was explored.

Results: A total of 26 patients with GBM (median age = 57 years) met inclusion criteria, comprising a total of 28 cases. Of these, 22 (79%) tumors were in eloquent regions, most commonly in the frontal lobe (14 cases, 50%). The median pre- and post-operative volumes were 24.0 cc and 1.3 cc, respectively. The median extent of resection for the cohort was 94.8%, with 86% achieving 6-month PFS. The most common neurological complication was a motor deficit followed by sensory loss, while 8 patients (29%) were symptom-free.

Conclusions: The robotic exoscope is safe and effective for patients undergoing GBM surgery, with a majority achieving large-volume resections. These patients experienced complication profiles similar to those undergoing treatment with the traditional microscope. Further studies are needed to assess direct comparisons between exoscope and microscope-assisted GBM resection.
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http://dx.doi.org/10.1007/s11060-020-03543-3DOI Listing
July 2020

The Aging Imageomics Study: rationale, design and baseline characteristics of the study population.

Mech Ageing Dev 2020 07 11;189:111257. Epub 2020 May 11.

Girona Biomedical Research Institute (IDIBGI), Hospital Universitari de Girona Dr Josep Trueta, Girona, Spain; Department of Medical Sciences, School of Medicine, University of Girona, Girona, Spain; Institut d'Assistència Sanitària, Salt, Spain.

Biomarkers of aging are urgently needed to identify individuals at high risk of developing age-associated disease or disability. Growing evidence from population-based studies points to whole-body magnetic resonance imaging's (MRI) enormous potential for quantifying subclinical disease burden and for assessing changes that occur with aging in all organ systems. The Aging Imageomics Study aims to identify biomarkers of human aging by analyzing imaging, biopsychosocial, cardiovascular, metabolomic, lipidomic, and microbiome variables. This study recruited 1030 participants aged ≥50 years (mean 67, range 50-96 years) that underwent structural and functional MRI to evaluate the brain, large blood vessels, heart, abdominal organs, fat, spine, musculoskeletal system and ultrasonography to assess carotid intima-media thickness and plaques. Patients were notified of incidental findings detected by a certified radiologist when necessary. Extensive data were also collected on anthropometrics, demographics, health history, neuropsychology, employment, income, family status, exposure to air pollution and cardiovascular status. In addition, several types of samples were gathered to allow for microbiome, metabolomic and lipidomic profiling. Using big data techniques to analyze all the data points from biological phenotyping together with health records and lifestyle measures, we aim to cultivate a deeper understanding about various biological factors (and combinations thereof) that underlie healthy and unhealthy aging.
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http://dx.doi.org/10.1016/j.mad.2020.111257DOI Listing
July 2020

Multiparametric MRI for early identification of therapeutic response in recurrent glioblastoma treated with immune checkpoint inhibitors.

Neuro Oncol 2020 11;22(11):1658-1666

UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.

Background: Physiologic changes quantified by diffusion and perfusion MRI have shown utility in predicting treatment response in glioblastoma (GBM) patients treated with cytotoxic therapies. We aimed to investigate whether quantitative changes in diffusion and perfusion after treatment by immune checkpoint inhibitors (ICIs) would determine 6-month progression-free survival (PFS6) in patients with recurrent GBM.

Methods: Inclusion criteria for this retrospective study were: (i) diagnosis of recurrent GBM treated with ICIs and (ii) availability of diffusion and perfusion in pre and post ICI MRI (iii) at ≥6 months follow-up from treatment. After co-registration, mean values of the relative apparent diffusion coefficient (rADC), Ktrans (volume transfer constant), Ve (extravascular extracellular space volume) and Vp (plasma volume), and relative cerebral blood volume (rCBV) were calculated from a volume-of-interest of the enhancing tumor. Final assignment of stable/improved versus progressive disease was determined on 6-month follow-up using modified Response Assessment in Neuro-Oncology criteria.

Results: Out of 19 patients who met inclusion criteria and follow-up (mean ± SD: 7.8 ± 1.4 mo), 12 were determined to have tumor progression, while 7 had treatment response after 6 months of ICI treatment. Only interval change of rADC was suggestive of treatment response. Patients with treatment response (6/7: 86%) had interval increased rADC, while 11/12 (92%) with tumor progression had decreased rADC (P = 0.001). Interval change in rCBV, Ktrans, Vp, and Ve were not indicative of treatment response within 6 months.

Conclusions: In patients with recurrent GBM, interval change in rADC is promising in assessing treatment response versus progression within the first 6 months following ICI treatment.

Key Points: • In recurrent GBM treated with ICIs, interval change in rADC suggests early treatment response.• Interval change in rADC can be used as an imaging biomarker to determine PFS6.• Interval change in MR perfusion and permeability measures do not suggest ICI treatment response.
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http://dx.doi.org/10.1093/neuonc/noaa066DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7846197PMC
November 2020

From "Time is Brain" to "Imaging is Brain": A Paradigm Shift in the Management of Acute Ischemic Stroke.

J Neuroimaging 2020 09 10;30(5):562-571. Epub 2020 Feb 10.

Department of Radiology, University of Manitoba, Winnipeg, Manitoba, Canada.

Arterial recanalization to restore the blood supply and limit the brain damage is the primary goal in the management of acute ischemic stroke (AIS). Since the publication of pivotal randomized clinical trials in 2015, endovascular thrombectomy has become part of the standard of care in selected cases of AIS from large-vessel occlusions up to 6 hours after the onset of symptoms. However, the association between endovascular reperfusion and improved functional outcome is not strictly time dependent. Rather than on rigid time windows, candidates should be selected based on vascular and physiologic information. This approach places imaging data at the center of treatment decisions. Advances in imaging-based management of AIS provide crucial information about vessel occlusion, infarct core, ischemic penumbra, and degree of collaterals. This information is invaluable in identifying patients who are likely to benefit from reperfusion therapies and excluding those who are unlikely to benefit or are at risk of adverse effects. The approach to reperfusion therapies continues to evolve, and imaging is acquiring a greater role in the diagnostic work-up and treatment decisions as shown in recent clinical trials with extended time window. The 2018 American Heart Association/American Stroke Association guidelines reflect a paradigm shift in the management of AIS from "Time is Brain" to "Imaging is Brain." This review discusses the essential role of multimodal imaging developing from recent trials on therapy for AIS.
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http://dx.doi.org/10.1111/jon.12693DOI Listing
September 2020

Detection of Acute Infarction on Non-Contrast-enhanced CT: Closing the Gap with MRI via Machine Learning.

Authors:
Kambiz Nael

Radiology 2020 Mar 28;294(3):645-646. Epub 2020 Jan 28.

From the Department of Radiology, Icahn School of Medicine at Mount Sinai; and Department of Radiological Sciences, David Geffen School of Medicine at UCLA, 757 Westwood Plaza, Suite 1621, Los Angeles, CA, 90095-7532.

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http://dx.doi.org/10.1148/radiol.2020192703DOI Listing
March 2020

Tumoral and immune heterogeneity in an anti-PD-1-responsive glioblastoma: a case study.

Cold Spring Harb Mol Case Stud 2020 04 1;6(2). Epub 2020 Apr 1.

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA.

Clinical benefit of immune checkpoint blockade in glioblastoma (GBM) is rare, and we hypothesize that tumor clonal evolution and the immune microenvironment are key determinants of response. Here, we present a detailed molecular characterization of the intratumoral and immune heterogeneity in an wild-type, -negative GBM patient who plausibly benefited from anti- therapy with an unusually long 25-mo overall survival time. We leveraged multiplex immunohistochemistry, RNA-seq, and whole-exome data from the primary tumor and three resected regions of recurrent disease to survey regional tumor-immune interactions, genomic instability, mutation burden, and expression profiles. We found significant regional heterogeneity in the neoantigenic and immune landscape, with a differential T-cell signature among recurrent sectors, a uniform loss of focal amplifications in , and a novel subclonal mutation. Comparisons with recently reported correlates of checkpoint blockade in GBM and with TCGA-GBM revealed appreciable intratumoral heterogeneity that may have contributed to a differential blockade response.
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http://dx.doi.org/10.1101/mcs.a004762DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7133743PMC
April 2020

Differential Subsampling with Cartesian Ordering for Ultrafast High-Resolution MRA in the Assessment of Intracranial Aneurysms.

J Neuroimaging 2020 01 13;30(1):40-44. Epub 2019 Nov 13.

Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY.

Background And Purpose: We aimed to evaluate the feasibility of an ultrafast whole head contrast-enhanced MRA (CE-MRA) in morphometric assessment of intracranial aneurysms in comparison to routinely used time-of-flight (TOF)-MRA.

Methods: In this prospective single institutional study, patients with known untreated intracranial aneurysm underwent MRA. Routine multislab TOF-MRA was obtained with a 3D voxel sizes of .6 × .6 × 1 (6-minute acquisition time). CE-MRA of whole head was obtained using Differential Subsampling with Cartesian Ordering (DISCO) and 2D Auto-calibrating Reconstruction for Cartesian imaging with a 3D voxel-sizes of .75 × .75 × 1 mm during a 6-second temporal resolution. Morphometric features of intracranial aneurysms, including size, aneurysm sac morphology, and the presence of intraluminal thrombosis, were assessed on both techniques. Statistical analysis was performed using a combination of Kappa test, Bland-Altman, and correlation coefficient analysis.

Results: A total of 34 aneurysms in 28 patients were included. Aneurysm size measurements (mean ± SD) were similar between DISCO-MRA (4.1 ± 2.3 mm) and TOF-MRA (4.3 ± 2.8 mm) (P = .27). Bland-Altman analysis showed a mean difference of .4 mm and there was excellent correlation r = .91 (95% CI: .87-.96). In six aneurysms (17.6%), TOF-MRA was nonconfidant to exclude intraluminal thrombosis. In seven aneurysms (20%), TOF-MRA was unable or nonconfidant in depicting aneurysm sac morphology.

Conclusions: Described ultrafast high spatial-resolution MRA is superior to routinely used TOF-MRA in assessment of morphometric features of intracranial aneurysms, such as intraluminal thrombosis and aneurysm morphology, and is obtained in a fraction of the time (6 seconds).
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http://dx.doi.org/10.1111/jon.12677DOI Listing
January 2020

Automated CT perfusion imaging for acute ischemic stroke: Pearls and pitfalls for real-world use.

Neurology 2019 11 21;93(20):888-898. Epub 2019 Oct 21.

From the Departments of Radiology (A.V), Neurology (P.K), and Neurosurgery (A.G), University of Cincinnati Medical Center, OH; Department of Radiology (M.W), Stanford University and Healthcare, CA, Department of Neurology (M.P., A.B.), Royal Melbourne Hospital, Melbourne Brain Centre, University of Melbourne, Australia; and Department of Radiology (K.N.), Icahn School of Medicine at Mount Sinai, New York, NY.

Recent positive trials have thrust acute cerebral perfusion imaging into the routine evaluation of acute ischemic stroke. Updated guidelines state that in patients with anterior circulation large vessel occlusions presenting beyond 6 hours from time last known well, advanced imaging selection including perfusion-based selection is necessary. Centers that receive patients with acute stroke must now have the capability to perform and interpret CT or magnetic resonance perfusion imaging or provide rapid transfer to centers with the capability of selecting patients for a highly impactful endovascular therapy, particularly in delayed time windows. Many stroke centers are quickly incorporating the use of automated perfusion processing software to interpret perfusion raw data. As CT perfusion (CTP) is being assimilated in real-world clinical practice, it is essential to understand the basics of perfusion acquisition, quantification, and interpretation. It is equally important to recognize the common technical and clinical diagnostic challenges of automated CTP including ischemic core and penumbral misclassifications that could result in underestimation or overestimation of the core and penumbra volumes. This review highlights the pitfalls of automated CTP along with practical pearls to address the common challenges. This is particularly tailored to aid the acute stroke clinician who must interpret automated perfusion studies in an emergency setting to make time-dependent treatment decisions for patients with acute ischemic stroke.
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http://dx.doi.org/10.1212/WNL.0000000000008481DOI Listing
November 2019

Imaging-based Selection for Endovascular Treatment in Stroke.

Radiographics 2019 10;39(6):1696-1713

From the Neuroimaging Advanced and Exploratory Laboratory, Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1234, New York, NY 10029 (K.N., Y.S.); Departments of Neurology (P.K.), Neurosurgery (C.J.P.), and Radiology (A.V.), University of Cincinnati Medical Center, Cincinnati, Ohio; and Department of Radiology, University of Manitoba, Winnipeg, MB, Canada (J.P.).

Treatment of acute ischemic stroke (AIS) has evolved significantly in the past few years. Endovascular treatment (EVT) is now proved to be efficacious up to 24 hours from onset in properly selected patients. The recently updated 2018 American Heart Association-American Stroke Association guidelines reflect the important role of imaging in triage and patient selection for EVT of AIS. Pretreatment imaging in patients with acute stroke should allow assessment for intracranial hemorrhage and demonstrate the extent of early ischemic changes, the presence of large arterial occlusion, and in some cases potential salvageable tissue before the decision to proceed with EVT. The authors review how multimodality imaging can be used for EVT selection in the context of the recent guidelines. They highlight the importance of having streamlined imaging workflows that are integrated with clinical decision making to maximize treatment efficiency. Knowledge of the various imaging criteria including perfusion imaging used for EVT selection is highlighted. The authors discuss variable imaging paradigms used for selection of patients in the early and late windows (who present before vs after 6 hours from onset of symptoms), as reflected in the latest guidelines and in relation to their level of evidence. Finally, they focus on challenges in the subgroups of patients who were excluded from recent EVT trials and with limited evidence to prove the efficacy of EVT, such as patients with low NIHSS (National Institutes of Health Stroke Scale) score, distal occlusion, or large ischemic core. RSNA, 2019 See discussion on this article by Leslie-Mazwi.
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http://dx.doi.org/10.1148/rg.2019190030DOI Listing
October 2019

Machine learning for semi-automated classification of glioblastoma, brain metastasis and central nervous system lymphoma using magnetic resonance advanced imaging.

Ann Transl Med 2019 Jun;7(11):232

Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Background: Differentiating glioblastoma, brain metastasis, and central nervous system lymphoma (CNSL) on conventional magnetic resonance imaging (MRI) can present a diagnostic dilemma due to the potential for overlapping imaging features. We investigate whether machine learning evaluation of multimodal MRI can reliably differentiate these entities.

Methods: Preoperative brain MRI including diffusion weighted imaging (DWI), dynamic contrast enhanced (DCE), and dynamic susceptibility contrast (DSC) perfusion in patients with glioblastoma, lymphoma, or metastasis were retrospectively reviewed. Perfusion maps (rCBV, rCBF), permeability maps (K-trans, Kep, Vp, Ve), ADC, T1C+ and T2/FLAIR images were coregistered and two separate volumes of interest (VOIs) were obtained from the enhancing tumor and non-enhancing T2 hyperintense (NET2) regions. The tumor volumes obtained from these VOIs were utilized for supervised training of support vector classifier (SVC) and multilayer perceptron (MLP) models. Validation of the trained models was performed on unlabeled cases using the leave-one-subject-out method. Head-to-head and multiclass models were created. Accuracies of the multiclass models were compared against two human interpreters reviewing conventional and diffusion-weighted MR images.

Results: Twenty-six patients enrolled with histopathologically-proven glioblastoma (n=9), metastasis (n=9), and CNS lymphoma (n=8) were included. The trained multiclass ML models discriminated the three pathologic classes with a maximum accuracy of 69.2% accuracy (18 out of 26; kappa 0.540, P=0.01) using an MLP trained with the VpNET2 tumor volumes. Human readers achieved 65.4% (17 out of 26) and 80.8% (21 out of 26) accuracies, respectively. Using the MLP VpNET2 model as a computer-aided diagnosis (CADx) for cases in which the human reviewers disagreed with each other on the diagnosis resulted in correct diagnoses in 5 (19.2%) additional cases.

Conclusions: Our trained multiclass MLP using VpNET2 can differentiate glioblastoma, brain metastasis, and CNS lymphoma with modest diagnostic accuracy and provides approximately 19% increase in diagnostic yield when added to routine human interpretation.
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http://dx.doi.org/10.21037/atm.2018.08.05DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603356PMC
June 2019

MRA versus DSA for the follow-up imaging of intracranial aneurysms treated using endovascular techniques: a meta-analysis.

J Neurointerv Surg 2019 Oct 2;11(10):1009-1014. Epub 2019 May 2.

Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Background: Treated aneurysms must be followed over time to ensure durable occlusion, as more than 20% of endovascularly treated aneurysms recur. While digital subtraction angiography (DSA) remains the gold standard, magnetic resonance angiography (MRA) is attractive as a non-invasive follow-up technique. Two different MRA techniques have traditionally been used: time-of-flight (TOF) and contrast-enhanced (CE) MRA. We analysed data from studies comparing MRA techniques with DSA for the follow-up of aneurysms undergoing endovascular treatment. Subgroup analysis of stent-assisted coiling (SAC) and flow diversion (FD) techniques was completed.

Methods: Comprehensive searches using the Embase, PubMed, and Cochrane databases were performed and updated to November 2018. Pooled sensitivity and specificity were calculated using aneurysm occlusion status as defined by the Raymond-Roy occlusion grading scale.

Results: The literature search yielded 1579 unique titles. Forty-three studies were included. For TOF-MRA, sensitivity and specificity of all aneurysms undergoing endovascular therapy were 88% and 94%, respectively. For CE-MRA, the sensitivity and specificity were 88% and 96%, respectively. For SAC and FD techniques, sensitivity and specificity of TOF-MRA were 86% and 95%, respectively. CE-MRA had sensitivity and specificity of 90% and 92%.

Conclusion: MRA is a reliable modality for the follow-up of aneurysms treated using endovascular techniques. While the data are limited, MRA techniques can also be used to reliably follow patients undergoing FD and SAC. However, clinical factors must be used to optimize follow-up regimens for individual patients.
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http://dx.doi.org/10.1136/neurintsurg-2019-014936DOI Listing
October 2019

Spine Oncology: Imaging and Intervention.

Radiol Clin North Am 2019 Mar 10;57(2):377-395. Epub 2018 Dec 10.

RadNet, 5 Columbus Circle 9th Floor, New York, NY 10019, USA.

Osseous metastases are the most common spine tumor and increasingly prevalent as advances in cancer treatments allow patients to live longer with their disease. Evidence-based algorithms derive the majority of their data from imaging studies and reports; the radiologist should understand the most current treatments and report in the language of the treatment team for efficient and effective communication and patient care. Advanced imaging techniques such as diffusion-weighted imaging and dynamic contrast-enhanced MRI are increasingly used for diagnosis and problem solving. Radiologists have a growing role in treatment of patients with metastatic disease, performing cement augmentation and tumor ablation.
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http://dx.doi.org/10.1016/j.rcl.2018.10.002DOI Listing
March 2019

Macrovascular Networks on Contrast-Enhanced Magnetic Resonance Imaging Improves Survival Prediction in Newly Diagnosed Glioblastoma.

Cancers (Basel) 2019 Jan 14;11(1). Epub 2019 Jan 14.

Research Unit of Diagnostic Imaging Institute (IDI), Department of Radiology (Girona Biomedical Research Institute) IDIBGI, Hospital Universitari Dr Josep Trueta, 17007 Girona, Spain.

A higher degree of angiogenesis is associated with shortened survival in glioblastoma. Feasible morphometric parameters for analyzing vascular networks in brain tumors in clinical practice are lacking. We investigated whether the macrovascular network classified by the number of vessel-like structures (nVS) visible on three-dimensional T1-weighted contrast⁻enhanced (3D-T1CE) magnetic resonance imaging (MRI) could improve survival prediction models for newly diagnosed glioblastoma based on clinical and other imaging features. Ninety-seven consecutive patients (62 men; mean age, 58 ± 15 years) with histologically proven glioblastoma underwent 1.5T-MRI, including anatomical, diffusion-weighted, dynamic susceptibility contrast perfusion, and 3D-T1CE sequences after 0.1 mmol/kg gadobutrol. We assessed nVS related to the tumor on 1-mm isovoxel 3D-T1CE images, and relative cerebral blood volume, relative cerebral flow volume (rCBF), delay mean time, and apparent diffusion coefficient in volumes of interest for contrast-enhancing lesion (CEL), non-CEL, and contralateral normal-appearing white matter. We also assessed Visually Accessible Rembrandt Images scoring system features. We used ROC curves to determine the cutoff for nVS and univariate and multivariate cox proportional hazards regression for overall survival. Prognostic factors were evaluated by Kaplan-Meier survival and ROC analyses. Lesions with nVS > 5 were classified as having highly developed macrovascular network; 58 (60.4%) tumors had highly developed macrovascular network. Patients with highly developed macrovascular network were older, had higher volume, increased rCBF, and poor survival; nVS correlated negatively with survival ( = -0.286; = 0.008). On multivariate analysis, standard treatment, age at diagnosis, and macrovascular network best predicted survival at 1 year (AUC 0.901, 83.3% sensitivity, 93.3% specificity, 96.2% PPV, 73.7% NPV). Contrast-enhanced MRI macrovascular network improves survival prediction in newly diagnosed glioblastoma.
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http://dx.doi.org/10.3390/cancers11010084DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6356693PMC
January 2019

Intrasellar herniation: A newly described variant of downward central herniation.

Neurology 2018 11;91(19):889-890

From the Division of Neuroradiology (F.T.P.), Santa Casa de São Paulo School of Medical Sciences and Diagnósticos da América-DASA, Brazil; and Departments of Neuroradiology and Radiology (K.N., P.S.P.), Icahn School of Medicine at Mount Sinai, New York, NY.

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http://dx.doi.org/10.1212/WNL.0000000000006470DOI Listing
November 2018

Estimation of Ischemic Core Volume Using Computed Tomographic Perfusion.

Stroke 2018 10;49(10):2345-2352

From the Department of Radiology (Y.S., B.N.D., A.H.D., K.N.), Icahn School of Medicine at Mount Sinai, New York City, NY.

Background and Purpose- Estimation of infarction based on computed tomographic perfusion (CTP) has been challenging, mainly because of noise associated with CTP data. The Bayesian method is a robust probabilistic method that minimizes effects of oscillation, tracer delay, and noise during residue function estimation compared with other deconvolution methods. This study compares CTP-estimated ischemic core volume calculated by the Bayesian method and by the commonly used block-circulant singular value deconvolution technique. Methods- Patients were included if they had (1) anterior circulation ischemic stroke, (2) baseline CTP, (3) successful recanalization defined by thrombolysis in cerebral infarction ≥IIb, and (4) minimum infarction volume of >5 mL on follow-up magnetic resonance imaging (MRI). CTP data were processed with circulant singular value deconvolution and Bayesian methods. Two established CTP methods for estimation of ischemic core volume were applied: cerebral blood flow (CBF) method (relative CBF, <30% within the region of delay >2 seconds) and cerebral blood volume method (<2 mL per 100 g within the region of relative mean transit time >145%). Final infarct volume was determined on MRI (fluid-attenuated inversion recovery images). CTP and MRI-derived ischemic core volumes were compared by univariate and Bland-Altman analysis. Results- Among 35 patients included, the mean/median (mL) difference for CTP-estimated ischemic core volume against MRI was -4/-7 for Bayesian CBF ( P=0.770), 20/12 for Bayesian cerebral blood volume ( P=0.041), 21/10 for circulant singular value deconvolution CBF ( P=0.006), and 35/18 for circulant singular value deconvolution cerebral blood volume ( P<0.001). Among all methods, Bayesian CBF provided the narrowest limits of agreement (-28 to 19 mL) in comparison with MRI. Conclusions- Despite existing variabilities between CTP postprocessing methods, Bayesian postprocessing increases accuracy and limits variability in CTP estimation of ischemic core.
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http://dx.doi.org/10.1161/STROKEAHA.118.021952DOI Listing
October 2018

Resting-State Functional Connectivity Magnetic Resonance Imaging and Outcome After Acute Stroke.

Stroke 2018 10;49(10):2353-2360

From the Imaging Research Unit, Department of Radiology (Girona Biomedical Research Institute) Girona Biomedical Research Institute, Diagnostic Imaging Institute (IDI) (J.P., G.B., C.B., M.N.-M., C.L.O.-R., S.P.), Dr Josep Trueta University Hospital, Girona, Spain.

Background and Purpose- Physiological effects of stroke are best assessed over entire brain networks rather than just focally at the site of structural damage. Resting-state functional magnetic resonance imaging can map functional-anatomic networks by analyzing spontaneously correlated low-frequency activity fluctuations across the brain, but its potential usefulness in predicting functional outcome after acute stroke remains unknown. We assessed the ability of resting-state functional magnetic resonance imaging to predict functional outcome after acute stroke. Methods- We scanned 37 consecutive reperfused stroke patients (age, 69±14 years; 14 females; 3-day National Institutes of Health Stroke Scale score, 6±5) on day 3 after symptom onset. After imaging preprocessing, we used a whole-brain mask to calculate the correlation coefficient matrices for every paired region using the Harvard-Oxford probabilistic atlas. To evaluate functional outcome, we applied the modified Rankin Scale at 90 days. We used region of interest analyses to explore the functional connectivity between regions and graph-computation analysis to detect differences in functional connectivity between patients with good functional outcome (modified Rankin Scale score ≤2) and those with poor outcome (modified Rankin Scale score >2). Results- Patients with good outcome had greater functional connectivity than patients with poor outcome. Although 3-day National Institutes of Health Stroke Scale score was the most accurate independent predictor of 90-day modified Rankin Scale (84.2%), adding functional connectivity increased accuracy to 94.7%. Preserved bilateral interhemispheric connectivity between the anterior inferior temporal gyrus and superior frontal gyrus and decreased connectivity between the caudate and anterior inferior temporal gyrus in the left hemisphere had the greatest impact in favoring good prognosis. Conclusions- These data suggest that information about functional connectivity from resting-state functional magnetic resonance imaging may help predict 90-day stroke outcome.
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http://dx.doi.org/10.1161/STROKEAHA.118.021319DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6645916PMC
October 2018

Interval Change in Diffusion and Perfusion MRI Parameters for the Assessment of Pseudoprogression in Cerebral Metastases Treated With Stereotactic Radiation.

AJR Am J Roentgenol 2018 Jul 30;211(1):168-175. Epub 2018 Apr 30.

5 Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Pl, Box 1234, New York, NY 10029.

Objective: Apparent increases in the size of cerebral metastases after stereotactic radiosurgery (SRS) can be caused by pseudoprogression or true disease progression, which poses a diagnostic challenge at conventional MRI. The purpose of this study was to assess whether interval change in DWI and perfusion MRI parameters can differentiate pseudoprogression from progressive disease after treatment with SRS.

Materials And Methods: Patients with apparent growth of cerebral metastases after SRS treatment who underwent pre- and post-SRS DWI, dynamic susceptibility contrast (DSC)-MRI, and perfusion dynamic contrast-enhanced (DCE)-MRI were retrospectively evaluated. Final assignment of pseudoprogression or progressive disease was determined at 6-month follow-up imaging using the Response Assessment in Neuro-Oncology Brain Metastases criteria. Mean values of apparent diffusion coefficient (ADC), DCE-MRI-derived volume transfer constant (K), and DSC-MRI-derived relative cerebral blood volume (CBV) from pre- and post-SRS MRI scans were compared between groups using univariate and regression analysis. Fisher exact test was used to compare interval change of imaging biomarkers.

Results: Of 102 cerebral metastases evaluated, 32 lesions in 29 patients met our inclusion criteria. The mean duration of follow-up was 7.2 months (range, 6-14 months). Twenty-two lesions were determined as pseudoprogression, and 10 lesions were determined as progressive disease using the Response Assessment in Neuro-Oncology Brain Metastases criteria at 6-month follow-up MRI. The interval change pattern of our imaging parameters matched the expected patterns of treatment response for ADC (23/32 lesions; 72%; p = 0.055; odds ratio, 5.1), K (24/32 lesions; 75%; p = 0.006; odds ratio, 19.2), and relative CBV (27/32 lesions; 84%; p = 0.001; odds ratio, 25.3).

Conclusion: Pseudoprogression can be distinguished from disease progression in cerebral metastases treated with SRS via an interval decrease in relative CBV and K values.
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http://dx.doi.org/10.2214/AJR.17.18890DOI Listing
July 2018

High-permeability region size on perfusion CT predicts hemorrhagic transformation after intravenous thrombolysis in stroke.

PLoS One 2017 28;12(11):e0188238. Epub 2017 Nov 28.

Department of Neurology, A Coruña University Hospital, Biomedical Research Institute, A Coruña, Spain.

Objective: Blood-brain barrier (BBB) permeability has been proposed as a predictor of hemorrhagic transformation (HT) after tissue plasminogen activator (tPA) administration; however, the reliability of perfusion computed tomography (PCT) permeability imaging for predicting HT is uncertain. We aimed to determine the performance of high-permeability region size on PCT (HPrs-PCT) in predicting HT after intravenous tPA administration in patients with acute stroke.

Methods: We performed a multimodal CT protocol (non-contrast CT, PCT, CT angiography) to prospectively study patients with middle cerebral artery occlusion treated with tPA within 4.5 hours of symptom onset. HT was graded at 24 hours using the European-Australasian Acute Stroke Study II criteria. ROC curves selected optimal volume threshold, and multivariate logistic regression analysis identified predictors of HT.

Results: The study included 156 patients (50% male, median age 75.5 years). Thirty-seven (23,7%) developed HT [12 (7,7%), parenchymal hematoma type 2 (PH-2)]. At admission, patients with HT had lower platelet values, higher NIHSS scores, increased ischemic lesion volumes, larger HPrs-PCT, and poorer collateral status. The negative predictive value of HPrs-PCT at a threshold of 7mL/100g/min was 0.84 for HT and 0.93 for PH-2. The multiple regression analysis selected HPrs-PCT at 7mL/100g/min combined with platelets and baseline NIHSS score as the best model for predicting HT (AUC 0.77). HPrs-PCT at 7mL/100g/min was the only independent predictor of PH-2 (OR 1, AUC 0.68, p = 0.045).

Conclusions: HPrs-PCT can help predict HT after tPA, and is particularly useful in identifying patients at low risk of developing HT.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0188238PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5705117PMC
December 2017

Multiparametric MRI for Differentiation of Radiation Necrosis From Recurrent Tumor in Patients With Treated Glioblastoma.

AJR Am J Roentgenol 2018 Jan 27;210(1):18-23. Epub 2017 Sep 27.

4 Departments of Neurosurgery and Radiation Oncology, University of Arizona, Tucson, AZ.

Objective: Differentiation of radiation necrosis (RN) from recurrent tumor (RT) in treated patients with glioblastoma remains a diagnostic challenge. The purpose of this study is to evaluate the diagnostic performance of multiparametric MRI in distinguishing RN from RT in patients with glioblastoma, with the use of a combination of MR perfusion and diffusion parameters.

Materials And Methods: Patients with glioblastoma who had a new enhancing mass develop after completing standard treatment were retrospectively evaluated. Apparent diffusion coefficient (ADC), volume transfer constant (K), and relative cerebral blood volume (rCBV) values were calculated from the MR images on which the enhancing lesions first appeared. Repeated measure of analysis, logistic regression, and ROC analysis were performed.

Results: Of a total of 70 patients evaluated, 46 (34 with RT and 12 with RN) met our inclusion criteria. Patients with RT had significantly higher mean rCBV (p < 0.001) and K (p = 0.006) values and lower ADC values (p = 0.004), compared with patients with RN. The overall diagnostic accuracy was 85.8% for rCBV, 75.5% for K, and 71.3% for ADC values. The logistic regression model showed a significant contribution of rCBV (p = 0.024) and K (p = 0.040) as independent imaging classifiers for differentiation of RT from RN. Combined use of rCBV and K at threshold values of 2.2 and 0.08 min, respectively, improved the overall diagnostic accuracy to 92.8%.

Conclusion: In patients with treated glioblastoma, rCBV outperforms ADC and K as a single imaging classifier to predict recurrent tumor versus radiation necrosis; however, the combination of rCBV and K may be used to improve overall diagnostic accuracy.
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http://dx.doi.org/10.2214/AJR.17.18003DOI Listing
January 2018

Meningioma With Tyrosine-Rich Crystalloids: A Case Report and Review of the Literature.

Int J Surg Pathol 2018 Apr 17;26(2):157-160. Epub 2017 Aug 17.

3 Mount Sinai Beth Israel Hospital, New York, NY, USA.

We report a case of fibrous meningioma with tyrosine-rich crystalloid in the frontal lobe of a middle-aged woman. The patient presented with a history of several years of worsening headaches and blurry vision, which progressed to include syncopal episodes and right-sided weakness. Imaging demonstrated a dural-based extra-axial mass arising from the right orbital roof and extending superiorly along the right frontal convexity causing right-to-left midline shift. The patient underwent a craniotomy and operative resection. Tumor architecture and cytology was similar to that of a Schwannian neoplasm, with spindled cells arranged in a fascicular architecture and displaying focal nuclear palisading. Immunohistochemical stains confirmed a diagnosis of fibrous meningioma. Light microscopy demonstrated extracellular deposits of eosinophilic crystalline material parallel to the spindled tumor cells, reminiscent of "tyrosine-rich" crystals described in salivary gland neoplasms. This is the third meningioma featuring tyrosine-rich crystalloid reported in the literature; we also summarize the previous 2 reports.
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http://dx.doi.org/10.1177/1066896917727100DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5794632PMC
April 2018

Utility of preoperative meningioma consistency measurement with magnetic resonance elastography (MRE): a review.

Neurosurg Rev 2019 Mar 31;42(1):1-7. Epub 2017 May 31.

Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, Annenberg 8, One Gustave L Levy Pl, New York, NY, 10029, USA.

Meningioma consistency is a critical factor that influences preoperative planning for surgical resection. Recent studies have investigated the utility of preoperative magnetic resonance elastography (MRE) in predicting meningioma consistency. However, it is unclear whether existing methods are optimal for application to clinical practice. The results and conclusions of these studies are limited by their imaging acquisition methods, such as the use of a single MRE frequency and the use of shear modulus as the final measurement variable, rather than its storage and loss modulus components. In addition, existing studies do not account for the effects of cranial anatomy, which have been shown to significantly distort the MRE signal. Given the interaction of meningiomas with these anatomic structures and the lack of supporting evidence with more accurate imaging parameters, MRE may not yet be reliable for use in clinical practice.
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http://dx.doi.org/10.1007/s10143-017-0862-8DOI Listing
March 2019

Diffusion tensor imaging as a prognostic biomarker for motor recovery and rehabilitation after stroke.

Neuroradiology 2017 Apr 14;59(4):343-351. Epub 2017 Mar 14.

Girona Biomedical Research Institute (IDIBGI) - Medical Imaging, Hospital Universitari de Girona Dr. Josep Trueta, 17007, Girona, Spain.

Purpose: Despite improved acute treatment and new tools to facilitate recovery, most patients have motor deficits after stroke, often causing disability. However, motor impairment varies considerably among patients, and recovery in the acute/subacute phase is difficult to predict using clinical measures alone, particularly in severely impaired patients. Accurate early prediction of recovery would help rationalize rehabilitation goals and improve the design of trials testing strategies to facilitate recovery.

Methods: We review the role of diffusion tensor imaging (DTI) in predicting motor recovery after stroke, in monitoring treatment response, and in evaluating white matter remodeling. We critically appraise DTI studies and discuss their limitations, and we explore directions for future study.

Results: Growing evidence suggests that combining clinical scores with information about corticospinal tract (CST) integrity can improve predictions about motor outcome. The extent of CST damage on DTI and/or the overlap between the CST and a lesion are key prognostic factor that determines motor performance and outcome. Three main strategies to quantify stroke-related CST damage have been proposed: (i) measuring FA distal to the stroke area, (ii) measuring the number of fibers that go through the stroke with tractography, and (iii) measuring the overlap between the stroke and a CST map derived from healthy age- and gender-matched controls.

Conclusion: Recovery of motor function probably involves remodeling of the CST proper and/or a greater reliance on alternative motor tracts through spontaneous and treatment-induced plasticity. DTI-metrics represent promising clinical biomarkers to predict motor recovery and to monitor and predict the response to neurorehabilitative interventions.
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http://dx.doi.org/10.1007/s00234-017-1816-0DOI Listing
April 2017

Multiparametric Magnetic Resonance Imaging for Prediction of Parenchymal Hemorrhage in Acute Ischemic Stroke After Reperfusion Therapy.

Stroke 2017 03 30;48(3):664-670. Epub 2017 Jan 30.

From the Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY (K.N.); the Departments of Neurology and Radiology, University of Arizona, Tucson (J.R.K., C.S.K.); the Departments of Radiology and Neurosurgery (R.J.), Biomathematics (J. Gornbein), Neurology (D.S.L., J.L.S.), and Emergency Medicine and Neurology (J. Guzy, S.S.), University of California, Los Angeles; the Departments of Neurology (Z.A.) and Radiology (L.F.), Kaiser Permanente, Los Angeles, CA; the Departments of Neurosciences and the Stroke Center University of California, San Diego (B.C.M.); the Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston (L.H.S.); Texas Stroke Institute, Dallas (A.J.Y.); the Departments of Neurology (R.S.M.) and Neurological Surgery and Radiology (P.M.M.), Columbia University College of Physicians and Surgeons, New York, NY; the Departments of Neurology and Neurosurgery, University of Miami, Jackson Memorial Hospital, FL (D.R.Y.); and the Departments of Radiology and Neurology Stanford University, CA (M.W.).

Background And Purpose: Patients with acute ischemic stroke are at increased risk of developing parenchymal hemorrhage (PH), particularly in the setting of reperfusion therapies. We have developed a predictive model to examine the risk of PH using combined magnetic resonance perfusion and diffusion parameters, including cerebral blood volume (CBV), apparent diffusion coefficient, and microvascular permeability (K2).

Methods: Voxel-based values of CBV, K2, and apparent diffusion coefficient from the ischemic core were obtained using pretreatment magnetic resonance imaging data from patients enrolled in the MR RESCUE clinical trial (Mechanical Retrieval and Recanalization of Stroke Clots Using Embolectomy). The associations between PH and extreme values of imaging parameters were assessed in univariate and multivariate analyses. Receiver-operating characteristic curve analysis was performed to determine the optimal parameter(s) and threshold for predicting PH.

Results: In 83 patients included in this analysis, 20 developed PH. Univariate analysis showed significantly lower 10th percentile CBV and 10th percentile apparent diffusion coefficient values and significantly higher 90th percentile K2 values within the infarction core of patients with PH. Using classification tree analysis, the 10th percentile CBV at threshold of 0.47 and 90th percentile K2 at threshold of 0.28 resulted in overall predictive accuracy of 88.7%, sensitivity of 90.0%, and specificity of 87.3%, which was superior to any individual or combination of other classifiers.

Conclusions: Our results suggest that combined 10th percentile CBV and 90th percentile K2 is an independent predictor of PH in patients with acute ischemic stroke with diagnostic accuracy superior to individual classifiers alone. This approach may allow risk stratification for patients undergoing reperfusion therapies.

Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00389467.
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http://dx.doi.org/10.1161/STROKEAHA.116.014343DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5325250PMC
March 2017