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Wang L, Wang H, D’Angelo F, Curtin L, Sereduk CP, Leon GD, Singleton KW, Urcuyo J, Hawkins-Daarud A, Jackson PR, Krishna C, Zimmerman RS, Patra DP, Bendok BR, Smith KA, Nakaji P, Donev K, Baxter LC, Mrugała MM, Ceccarelli M, Iavarone A, Swanson KR, Tran NL, Hu LS, Li J. Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm. PLoS One 2024; 19:e0299267. [PMID: 38568950 PMCID: PMC10990246 DOI: 10.1371/journal.pone.0299267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 02/06/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND AND OBJECTIVE Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learning (ML) models to quantify intra-tumoral genetic heterogeneity for each patient. This capability holds great promise for enabling better therapeutic selection to improve patient outcome. METHODS We proposed a novel Weakly Supervised Ordinal Support Vector Machine (WSO-SVM) to predict regional genetic alteration status within each GBM tumor using MRI. WSO-SVM was applied to a unique dataset of 318 image-localized biopsies with spatially matched multiparametric MRI from 74 GBM patients. The model was trained to predict the regional genetic alteration of three GBM driver genes (EGFR, PDGFRA and PTEN) based on features extracted from the corresponding region of five MRI contrast images. For comparison, a variety of existing ML algorithms were also applied. Classification accuracy of each gene were compared between the different algorithms. The SHapley Additive exPlanations (SHAP) method was further applied to compute contribution scores of different contrast images. Finally, the trained WSO-SVM was used to generate prediction maps within the tumoral area of each patient to help visualize the intra-tumoral genetic heterogeneity. RESULTS WSO-SVM achieved 0.80 accuracy, 0.79 sensitivity, and 0.81 specificity for classifying EGFR; 0.71 accuracy, 0.70 sensitivity, and 0.72 specificity for classifying PDGFRA; 0.80 accuracy, 0.78 sensitivity, and 0.83 specificity for classifying PTEN; these results significantly outperformed the existing ML algorithms. Using SHAP, we found that the relative contributions of the five contrast images differ between genes, which are consistent with findings in the literature. The prediction maps revealed extensive intra-tumoral region-to-region heterogeneity within each individual tumor in terms of the alteration status of the three genes. CONCLUSIONS This study demonstrated the feasibility of using MRI and WSO-SVM to enable non-invasive prediction of intra-tumoral regional genetic alteration for each GBM patient, which can inform future adaptive therapies for individualized oncology.
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Affiliation(s)
- Lujia Wang
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America
| | - Hairong Wang
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America
| | - Fulvio D’Angelo
- Institute for Cancer Genetics, Columbia University Medical Center, New York City, New York, United States of America
| | - Lee Curtin
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Christopher P. Sereduk
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Gustavo De Leon
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Kyle W. Singleton
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Javier Urcuyo
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Andrea Hawkins-Daarud
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Pamela R. Jackson
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Chandan Krishna
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Richard S. Zimmerman
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Devi P. Patra
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Bernard R. Bendok
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Kris A. Smith
- Department of Neurosurgery, Barrow Neurological Institute—St. Joseph’s Hospital and Medical Center, Phoenix, Arizona, United States of America
| | - Peter Nakaji
- Department of Neurosurgery, Barrow Neurological Institute—St. Joseph’s Hospital and Medical Center, Phoenix, Arizona, United States of America
| | - Kliment Donev
- Department of Pathology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Leslie C. Baxter
- Department of Neuropsychology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Maciej M. Mrugała
- Department of Neuro-Oncology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Michele Ceccarelli
- Department of Electrical Engineering and Information Technology, University of Naples “Federico II”, Naples, Italy
| | - Antonio Iavarone
- Institute for Cancer Genetics, Columbia University Medical Center, New York City, New York, United States of America
| | - Kristin R. Swanson
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Nhan L. Tran
- Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
- Department of Cancer Biology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Leland S. Hu
- Department of Radiology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America
| | - Jing Li
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America
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Jubran JH, Scherschinski L, Dholaria N, Shaftel KA, Farhadi DS, Oladokun FC, Hendricks BK, Smith KA. Magnetic Resonance-Guided Laser Interstitial Thermal Therapy for Recurrent Glioblastoma and Radiation Necrosis: A Single-Surgeon Case Series. World Neurosurg 2024; 182:e453-e462. [PMID: 38036173 DOI: 10.1016/j.wneu.2023.11.120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 11/24/2023] [Indexed: 12/02/2023]
Abstract
OBJECTIVE To evaluate long-term clinical outcomes among patients treated with laser interstitial thermal therapy (LITT) for predicted recurrent glioblastoma (rGBM). METHODS Patients with rGBM treated by LITT by a single surgeon (2013-2020) were evaluated for progression-free survival (PFS), overall survival (OS), and OS after LITT. RESULTS Forty-nine patients (33 men, 16 women; mean [SD] age at diagnosis, 58.7 [12.5] years) were evaluated. Among patients with genetic data, 6 of 34 (18%) had IDH-1 R132 mutations, and 7 of 21 (33%) had MGMT methylation. Patients underwent LITT at a mean (SD) of 23.8 (23.8) months after original diagnosis. Twenty of 49 (40%) had previously undergone stereotactic radiosurgery, 37 (75%) had undergone intensity-modulated radiation therapy, and 49 (100%) had undergone chemotherapy. Patients had undergone a mean of 1.2 (0.7) previous resections before LITT. Mean preoperative enhancing and T2 FLAIR volumes were 13.1 (12.8) cm3 and 35.0 (32.8) cm3, respectively. Intraoperative biopsies confirmed rGBM in 31 patients (63%) and radiation necrosis in 18 patients (37%). Six perioperative complications occurred: 3 (6%) cases of worsening aphasia, 1 (2%) seizure, 1 (2%) epidural hematoma, and 1 (2%) intraparenchymal hemorrhage. For the rGBM group, median PFS was 2.0 (IQR, 4.0) months, median OS was 20.0 (IQR, 29.5) months, and median OS after LITT was 6.0 (IQR, 10.5) months. For the radiation necrosis group, median PFS was 4.0 (IQR, 4.5) months, median OS was 37.0 (IQR, 58.0) months, and median OS after LITT was 8.0 (IQR, 23.5) months. CONCLUSIONS In a diverse rGBM cohort, LITT was associated with a short duration of posttreatment PFS.
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Affiliation(s)
- Jubran H Jubran
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Lea Scherschinski
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Nikhil Dholaria
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Kelly A Shaftel
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Dara S Farhadi
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Femi C Oladokun
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Benjamin K Hendricks
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA.
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3
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Xu Y, Mathis AM, Pollo B, Schlegel J, Maragkou T, Seidel K, Schucht P, Smith KA, Porter RW, Raabe A, Little AS, Sanai N, Agbanyim DC, Martirosyan NL, Eschbacher JM, Quint K, Preul MC, Hewer E. Intraoperative in vivo confocal laser endomicroscopy imaging at glioma margins: can we detect tumor infiltration? J Neurosurg 2024; 140:357-366. [PMID: 37542440 DOI: 10.3171/2023.5.jns23546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 05/19/2023] [Indexed: 08/07/2023]
Abstract
OBJECTIVE Confocal laser endomicroscopy (CLE) is a US Food and Drug Administration-cleared intraoperative real-time fluorescence-based cellular resolution imaging technology that has been shown to image brain tumor histoarchitecture rapidly in vivo during neuro-oncological surgical procedures. An important goal for successful intraoperative implementation is in vivo use at the margins of infiltrating gliomas. However, CLE use at glioma margins has not been well studied. METHODS Matching in vivo CLE images and tissue biopsies acquired at glioma margin regions of interest (ROIs) were collected from 2 institutions. All images were reviewed by 4 neuropathologists experienced in CLE. A scoring system based on the pathological features was implemented to score CLE and H&E images from each ROI on a scale from 0 to 5. Based on the H&E scores, all ROIs were divided into a low tumor probability (LTP) group (scores 0-2) and a high tumor probability (HTP) group (scores 3-5). The concordance between CLE and H&E scores regarding tumor probability was determined. The intraclass correlation coefficient (ICC) and diagnostic performance were calculated. RESULTS Fifty-six glioma margin ROIs were included for analysis. Interrater reliability of the scoring system was excellent when used for H&E images (ICC [95% CI] 0.91 [0.86-0.94]) and moderate when used for CLE images (ICC [95% CI] 0.69 [0.40-0.83]). The ICCs (95% CIs) of the LTP group (0.68 [0.40-0.83]) and HTP group (0.68 [0.39-0.83]) did not differ significantly. The concordance between CLE and H&E scores was 61.6%. The sensitivity and specificity values of the scoring system were 79% and 37%. The positive predictive value (PPV) and negative predictive value were 65% and 53%, respectively. Concordance, sensitivity, and PPV were greater in the HTP group than in the LTP group. Specificity was higher in the newly diagnosed group than in the recurrent group. CONCLUSIONS CLE may detect tumor infiltration at glioma margins. However, it is not currently dependable, especially in scenarios where low probability of tumor infiltration is expected. The proposed scoring system has excellent intrinsic interrater reliability, but its interrater reliability is only moderate when used with CLE images. These results suggest that this technology requires further exploration as a method for consistent actionable intraoperative guidance with high dependability across the range of tumor margin scenarios. Specific-binding and/or tumor-specific fluorophores, a CLE image atlas, and a consensus guideline for image interpretation may help with the translational utility of CLE.
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Affiliation(s)
- Yuan Xu
- 1Department of Neurosurgery, The Loyal and Edith Davis Neurosurgical Research Laboratory, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Andrea M Mathis
- 2Department of Neurosurgery, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Bianca Pollo
- 3Neuropathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy
| | - Jürgen Schlegel
- 4Department of Neuropathology, Institute of Pathology, TUM School of Medicine, Technical University Munich, Germany
| | - Theoni Maragkou
- 5Institute of Tissue Medicine and Pathology, University of Bern, Switzerland
| | - Kathleen Seidel
- 2Department of Neurosurgery, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Philippe Schucht
- 2Department of Neurosurgery, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Kris A Smith
- 1Department of Neurosurgery, The Loyal and Edith Davis Neurosurgical Research Laboratory, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Randall W Porter
- 1Department of Neurosurgery, The Loyal and Edith Davis Neurosurgical Research Laboratory, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Andreas Raabe
- 2Department of Neurosurgery, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Andrew S Little
- 1Department of Neurosurgery, The Loyal and Edith Davis Neurosurgical Research Laboratory, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Nader Sanai
- 1Department of Neurosurgery, The Loyal and Edith Davis Neurosurgical Research Laboratory, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Dennis C Agbanyim
- 2Department of Neurosurgery, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Nikolay L Martirosyan
- 1Department of Neurosurgery, The Loyal and Edith Davis Neurosurgical Research Laboratory, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Jennifer M Eschbacher
- 6Department of Neuropathology, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | | | - Mark C Preul
- 1Department of Neurosurgery, The Loyal and Edith Davis Neurosurgical Research Laboratory, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Ekkehard Hewer
- 8Institute of Pathology, Lausanne University Hospital, University of Lausanne, Switzerland
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4
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Hu LS, D'Angelo F, Weiskittel TM, Caruso FP, Fortin Ensign SP, Blomquist MR, Flick MJ, Wang L, Sereduk CP, Meng-Lin K, De Leon G, Nespodzany A, Urcuyo JC, Gonzales AC, Curtin L, Lewis EM, Singleton KW, Dondlinger T, Anil A, Semmineh NB, Noviello T, Patel RA, Wang P, Wang J, Eschbacher JM, Hawkins-Daarud A, Jackson PR, Grunfeld IS, Elrod C, Mazza GL, McGee SC, Paulson L, Clark-Swanson K, Lassiter-Morris Y, Smith KA, Nakaji P, Bendok BR, Zimmerman RS, Krishna C, Patra DP, Patel NP, Lyons M, Neal M, Donev K, Mrugala MM, Porter AB, Beeman SC, Jensen TR, Schmainda KM, Zhou Y, Baxter LC, Plaisier CL, Li J, Li H, Lasorella A, Quarles CC, Swanson KR, Ceccarelli M, Iavarone A, Tran NL. Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures. Nat Commun 2023; 14:6066. [PMID: 37770427 PMCID: PMC10539500 DOI: 10.1038/s41467-023-41559-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 09/06/2023] [Indexed: 09/30/2023] Open
Abstract
Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular and multi-parametric magnetic resonance imaging (MRI) profiling across 313 multi-regional tumor biopsies, including 111 from the NE, across 68 HGG patients. Whole exome and RNA sequencing uncover unique genomic alterations to unresectable invasive NE tumor, including subclonal events, which inform genomic models predictive of geographic evolution. Infiltrative NE tumor is alternatively enriched with tumor cells exhibiting neuronal or glycolytic/plurimetabolic cellular states, two principal transcriptomic pathway-based glioma subtypes, which respectively demonstrate abundant private mutations or enrichment in immune cell signatures. These NE phenotypes are non-invasively identified through normalized K2 imaging signatures, which discern cell size heterogeneity on dynamic susceptibility contrast (DSC)-MRI. NE tumor populations predicted to display increased cellular proliferation by mean diffusivity (MD) MRI metrics are uniquely associated with EGFR amplification and CDKN2A homozygous deletion. The biophysical mapping of infiltrative HGG potentially enables the clinical recognition of tumor subpopulations with aggressive molecular signatures driving tumor progression, thereby informing precision medicine targeting.
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Affiliation(s)
- Leland S Hu
- Department of Radiology, Mayo Clinic Arizona, Phoenix, AZ, USA.
- Department of Cancer Biology, Mayo Clinic Arizona, Scottsdale, AZ, USA.
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA.
| | - Fulvio D'Angelo
- Department of Neurological Surgery, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, USA.
| | - Taylor M Weiskittel
- Mayo Clinic Alix School of Medicine Minnesota, Rochester, MN, USA
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Francesca P Caruso
- Department of Electrical Engineering and Information Technologies, University of Naples, "Federico II", I-80128, Naples, Italy
- BIOGEM Institute of Molecular Biology and Genetics, I-83031, Ariano Irpino, Italy
| | - Shannon P Fortin Ensign
- Department of Cancer Biology, Mayo Clinic Arizona, Scottsdale, AZ, USA
- Department of Hematology and Oncology, Mayo Clinic Arizona, Phoenix, AZ, USA
| | - Mylan R Blomquist
- Department of Cancer Biology, Mayo Clinic Arizona, Scottsdale, AZ, USA
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
- Mayo Clinic Alix School of Medicine Arizona, Scottsdale, AZ, USA
| | - Matthew J Flick
- Department of Radiology, Mayo Clinic Arizona, Phoenix, AZ, USA
- Department of Cancer Biology, Mayo Clinic Arizona, Scottsdale, AZ, USA
- Mayo Clinic Alix School of Medicine Arizona, Scottsdale, AZ, USA
| | - Lujia Wang
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Christopher P Sereduk
- Department of Cancer Biology, Mayo Clinic Arizona, Scottsdale, AZ, USA
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Kevin Meng-Lin
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Gustavo De Leon
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Ashley Nespodzany
- Department of Neuroimaging Research, Barrow Neurological Institute, Dignity Health, Phoenix, AZ, USA
| | - Javier C Urcuyo
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Ashlyn C Gonzales
- Department of Neuroimaging Research, Barrow Neurological Institute, Dignity Health, Phoenix, AZ, USA
| | - Lee Curtin
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Erika M Lewis
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Kyle W Singleton
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | | | - Aliya Anil
- Department of Neuroimaging Research, Barrow Neurological Institute, Dignity Health, Phoenix, AZ, USA
| | - Natenael B Semmineh
- Department of Cancer Systems Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Teresa Noviello
- Department of Electrical Engineering and Information Technologies, University of Naples, "Federico II", I-80128, Naples, Italy
- BIOGEM Institute of Molecular Biology and Genetics, I-83031, Ariano Irpino, Italy
| | - Reyna A Patel
- Department of Radiology, Mayo Clinic Arizona, Phoenix, AZ, USA
| | - Panwen Wang
- Quantitative Health Sciences, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Junwen Wang
- Division of Applied Oral Sciences & Community Dental Care, The University of Hong Kong, Hong Kong SAR, China
| | - Jennifer M Eschbacher
- Department of Neuropathology, Barrow Neurological Institute, Dignity Health, Phoenix, AZ, USA
| | | | - Pamela R Jackson
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Itamar S Grunfeld
- Department of Psychology, Hunter College, The City University of New York, New York, NY, USA
- Department of Psychology, The Graduate Center, The City University of New York, New York, NY, USA
| | | | - Gina L Mazza
- Quantitative Health Sciences, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Sam C McGee
- Department of Speech and Hearing Science, Arizona State University, Tempe, AZ, USA
| | - Lisa Paulson
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | | | | | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute, Dignity Health, Phoenix, AZ, USA
| | - Peter Nakaji
- Department of Neurosurgery, Banner University Medical Center, University of Arizona, Phoenix, AZ, USA
| | - Bernard R Bendok
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Richard S Zimmerman
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Chandan Krishna
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Devi P Patra
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Naresh P Patel
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Mark Lyons
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Matthew Neal
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Kliment Donev
- Department of Pathology, Mayo Clinic Arizona, Phoenix, AZ, USA
| | | | - Alyx B Porter
- Department of Neurology, Mayo Clinic Arizona, Phoenix, AZ, USA
| | - Scott C Beeman
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | | | - Kathleen M Schmainda
- Departments of Biophysics and Radiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Yuxiang Zhou
- Department of Radiology, Mayo Clinic Arizona, Phoenix, AZ, USA
| | - Leslie C Baxter
- Department of Radiology, Mayo Clinic Arizona, Phoenix, AZ, USA
- Departments of Psychiatry and Psychology, Mayo Clinic, AZ, USA
| | - Christopher L Plaisier
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Jing Li
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Hu Li
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Anna Lasorella
- Department of Biochemistry and Molecular Biology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - C Chad Quarles
- Department of Cancer Systems Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kristin R Swanson
- Department of Cancer Biology, Mayo Clinic Arizona, Scottsdale, AZ, USA
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Michele Ceccarelli
- Department of Public Health Sciences, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, USA.
| | - Antonio Iavarone
- Department of Neurological Surgery, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, USA.
| | - Nhan L Tran
- Department of Cancer Biology, Mayo Clinic Arizona, Scottsdale, AZ, USA.
- Department of Neurological Surgery, Mayo Clinic Arizona, Scottsdale, AZ, USA.
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Abramov I, Furey CG, Xu Y, Eschbacher JM, Smith KA, Preul MC. Intraoperative confocal laser endomicroscopy for interpretation of a sellar hemangioblastoma: illustrative case. J Neurosurg Case Lessons 2023; 6:CASE23417. [PMID: 37756481 PMCID: PMC10555637 DOI: 10.3171/case23417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 08/15/2023] [Indexed: 09/29/2023]
Abstract
BACKGROUND Intraoperative frozen sections play a critical role in surgical strategy because of their ability to provide rapid histopathological information. In cases in which intraoperative biopsy carries a significant risk of bleeding, intraoperative confocal laser endomicroscopy (CLE) can assist in decision-making. OBSERVATIONS The authors present a rare case of a large sellar hemangioblastoma. Preoperative radiographic imaging and normal pituitary function suggested a differential diagnosis that included hemangioblastoma. The patient underwent partial preoperative embolization and a right-sided pterional craniotomy for resection of the lesion. Gross intraoperative examination revealed a highly vascular sellar lesion requiring circumferential dissection to minimize blood loss. The serious vascularity precluded intraoperative frozen section analysis, and CLE imaging was performed. CLE imaging provided excellent visualization of the remarkable vascular structure and characteristic histoarchitecture with microvasculature, intracytoplasmic vacuoles, and atypical cells consistent with hemangioblastoma. Resection and decompression of the chiasm was accomplished, and the patient was discharged with improved vision. The final histopathological diagnosis was hemangioblastoma. LESSONS When the benefits of obtaining intraoperative frozen sections greatly outweigh the associated risks, CLE imaging can aid in decision-making. CLE imaging offers real-time, on-the-fly evaluation of intraoperative tissue without the need to biopsy a vascular lesion.
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Affiliation(s)
- Irakliy Abramov
- 1Department of Neurosurgery, The Loyal and Edith Davis Neurosurgical Research Laboratory, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona; and
| | | | - Yuan Xu
- 1Department of Neurosurgery, The Loyal and Edith Davis Neurosurgical Research Laboratory, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona; and
| | - Jennifer M Eschbacher
- 3Neuropathology, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | | | - Mark C Preul
- 1Department of Neurosurgery, The Loyal and Edith Davis Neurosurgical Research Laboratory, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona; and
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6
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Bond KM, Curtin L, Hawkins-Daarud A, Urcuyo JC, De Leon G, Singleton KW, Afshari AE, Paulson LE, Sereduk CP, Smith KA, Nakaji P, Baxter LC, Patra DP, Gustafson MP, Dietz AB, Zimmerman RS, Bendok BR, Tran NL, Hu LS, Parney IF, Rubin JB, Swanson KR. Image-based models of T-cell distribution identify a clinically meaningful response to a dendritic cell vaccine in patients with glioblastoma. medRxiv 2023:2023.07.13.23292619. [PMID: 37503239 PMCID: PMC10370220 DOI: 10.1101/2023.07.13.23292619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
BACKGROUND Glioblastoma is an extraordinarily heterogeneous tumor, yet the current treatment paradigm is a "one size fits all" approach. Hundreds of glioblastoma clinical trials have been deemed failures because they did not extend median survival, but these cohorts are comprised of patients with diverse tumors. Current methods of assessing treatment efficacy fail to fully account for this heterogeneity. METHODS Using an image-based modeling approach, we predicted T-cell abundance from serial MRIs of patients enrolled in the dendritic cell (DC) vaccine clinical trial. T-cell predictions were quantified in both the contrast-enhancing and non-enhancing regions of the imageable tumor, and changes over time were assessed. RESULTS A subset of patients in a DC vaccine clinical trial, who had previously gone undetected, were identified as treatment responsive and benefited from prolonged survival. A mere two months after initial vaccine administration, responsive patients had a decrease in model-predicted T-cells within the contrast-enhancing region, with a simultaneous increase in the T2/FLAIR region. CONCLUSIONS In a field that has yet to see breakthrough therapies, these results highlight the value of machine learning in enhancing clinical trial assessment, improving our ability to prospectively prognosticate patient outcomes, and advancing the pursuit towards individualized medicine.
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7
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Abramov I, Park MT, Belykh E, Dru AB, Xu Y, Gooldy TC, Scherschinski L, Farber SH, Little AS, Porter RW, Smith KA, Lawton MT, Eschbacher JM, Preul MC. Intraoperative confocal laser endomicroscopy: prospective in vivo feasibility study of a clinical-grade system for brain tumors. J Neurosurg 2023; 138:587-597. [PMID: 35901698 DOI: 10.3171/2022.5.jns2282] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 05/11/2022] [Indexed: 01/15/2023]
Abstract
OBJECTIVE The authors evaluated the feasibility of using the first clinical-grade confocal laser endomicroscopy (CLE) system using fluorescein sodium for intraoperative in vivo imaging of brain tumors. METHODS A CLE system cleared by the FDA was used in 30 prospectively enrolled patients with 31 brain tumors (13 gliomas, 5 meningiomas, 6 other primary tumors, 3 metastases, and 4 reactive brain tissue). A neuropathologist classified CLE images as interpretable or noninterpretable. Images were compared with corresponding frozen and permanent histology sections, with image correlation to biopsy location using neuronavigation. The specificities and sensitivities of CLE images and frozen sections were calculated using permanent histological sections as the standard for comparison. A recently developed surgical telepathology software platform was used in 11 cases to provide real-time intraoperative consultation with a neuropathologist. RESULTS Overall, 10,713 CLE images from 335 regions of interest were acquired. The mean duration of the use of the CLE system was 7 minutes (range 3-18 minutes). Interpretable CLE images were obtained in all cases. The first interpretable image was acquired within a mean of 6 (SD 10) images and within the first 5 (SD 13) seconds of imaging; 4896 images (46%) were interpretable. Interpretable image acquisition was positively correlated with study progression, number of cases per surgeon, cumulative length of CLE time, and CLE time per case (p ≤ 0.01). The diagnostic accuracy, sensitivity, and specificity of CLE compared with frozen sections were 94%, 94%, and 100%, respectively, and the diagnostic accuracy, sensitivity, and specificity of CLE compared with permanent histological sections were 92%, 90%, and 94%, respectively. No difference was observed between lesion types for the time to first interpretable image (p = 0.35). Deeply located lesions were associated with a higher percentage of interpretable images than superficial lesions (p = 0.02). The study met the primary end points, confirming the safety and feasibility and acquisition of noninvasive digital biopsies in all cases. The study met the secondary end points for the duration of CLE use necessary to obtain interpretable images. A neuropathologist could interpret the CLE images in 29 (97%) of 30 cases. CONCLUSIONS The clinical-grade CLE system allows in vivo, intraoperative, high-resolution cellular visualization of tissue microstructure and identification of lesional tissue patterns in real time, without the need for tissue preparation.
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Affiliation(s)
- Irakliy Abramov
- 1The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix.,2Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix
| | - Marian T Park
- 1The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix
| | - Evgenii Belykh
- 4Department of Neurosurgery, Rutgers New Jersey Medical School, Newark, New Jersey
| | - Alexander B Dru
- 1The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix
| | - Yuan Xu
- 1The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix.,2Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix
| | - Timothy C Gooldy
- 2Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix
| | - Lea Scherschinski
- 2Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix
| | - S Harrison Farber
- 2Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix
| | - Andrew S Little
- 2Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix
| | - Randall W Porter
- 2Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix
| | - Kris A Smith
- 2Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix
| | - Michael T Lawton
- 2Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix
| | - Jennifer M Eschbacher
- 3Department of Neuropathology, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona; and
| | - Mark C Preul
- 1The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix.,2Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix
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8
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Scherschinski L, Jubran JH, Shaftel KA, Furey CG, Farhadi DS, Benner D, Hendricks BK, Smith KA. Magnetic Resonance-Guided Laser Interstitial Thermal Therapy for Management of Low-Grade Gliomas and Radiation Necrosis: A Single-Institution Case Series. Brain Sci 2022; 12:brainsci12121627. [PMID: 36552087 PMCID: PMC9775146 DOI: 10.3390/brainsci12121627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 11/10/2022] [Accepted: 11/22/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Laser interstitial thermal therapy (LITT) has emerged as a minimally invasive treatment modality for ablation of low-grade glioma (LGG) and radiation necrosis (RN). OBJECTIVE To evaluate the efficacy, safety, and survival outcomes of patients with radiographically presumed recurrent or newly diagnosed LGG and RN treated with LITT. METHODS The neuro-oncological database of a quaternary center was reviewed for all patients who underwent LITT for management of LGG between 1 January 2013 and 31 December 2020. Clinical data including demographics, lesion characteristics, and clinical and radiographic outcomes were collected. Kaplan-Meier analyses comprised overall survival (OS) and progression-free survival (PFS). RESULTS Nine patients (7 men, 2 women; mean [SD] age 50 [16] years) were included. Patients underwent LITT at a mean (SD) of 11.6 (8.5) years after diagnosis. Two (22%) patients had new lesions on radiographic imaging without prior treatment. In the other 7 patients, all (78%) had surgical resection, 6 (67%) had intensity-modulated radiation therapy and chemotherapy, respectively, and 4 (44%) had stereotactic radiosurgery. Two (22%) patients had lesions that were wild-type IDH1 status. Volumetric assessment of preoperative T1-weighted contrast-enhancing and T2-weighted fluid-attenuated inversion recovery (FLAIR) sequences yielded mean (SD) lesion volumes of 4.1 (6.5) cm3 and 26.7 (27.9) cm3, respectively. Three (33%) patients had evidence of radiographic progression after LITT. The pooled median (IQR) PFS for the cohort was 52 (56) months, median (IQR) OS after diagnosis was 183 (72) months, and median (IQR) OS after LITT was 52 (60) months. At the time of the study, 2 (22%) patients were deceased. CONCLUSIONS LITT is a safe and effective treatment option for management of LGG and RN, however, there may be increased risk of permanent complications with treatment of deep-seated subcortical lesions.
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Affiliation(s)
- Lea Scherschinski
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ 85013, USA
- Department of Neurosurgery, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
- Correspondence: ; Tel.: +1-602-693-5883
| | - Jubran H. Jubran
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ 85013, USA
| | - Kelly A. Shaftel
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ 85013, USA
| | - Charuta G. Furey
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ 85013, USA
| | - Dara S. Farhadi
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ 85013, USA
| | - Dimitri Benner
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ 85013, USA
| | - Benjamin K. Hendricks
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ 85013, USA
| | - Kris A. Smith
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ 85013, USA
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9
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Cho SS, Wakim AA, Teng CW, Sarris CE, Smith KA. Stereotactic-Guided Transcerebellar Cisternoperitoneal Shunt Placement for Idiopathic Intracranial Hypertension. Oper Neurosurg (Hagerstown) 2022; 23:268-275. [PMID: 35972092 DOI: 10.1227/ons.0000000000000289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 03/24/2022] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Idiopathic intracranial hypertension (IIH) can cause debilitating symptoms and optic nerve ischemia if untreated. Cerebrospinal fluid diversion is often necessary to reduce intracranial pressure; however, current ventriculoperitoneal and lumboperitoneal shunting techniques have high failure rates in patients with IIH. OBJECTIVE To describe our experience treating IIH with a novel stereotactic-guided transcerebellar cisternoperitoneal shunt (SGTC-CPS) technique that places the proximal shunt catheter in the posterior cisterna magnum. METHODS Retrospective perioperative and postoperative data from all patients who underwent SGTC-CPS placement for IIH from March 1, 2015, to December 31, 2020, were analyzed. Patients were positioned as for ventriculoperitoneal shunt placement but with the head turned farther laterally to adequately expose the retrosigmoid space. Using neuronavigation, an opening was made near the transverse-sigmoid junction, and the proximal catheter was inserted transcerebellarly into the posterior foramen magnum. RESULTS Thirty-two patients underwent SGTC-CPS placement (29 female; mean body mass index, 36.0 ± 7.5; 14 with prior shunt failures). The mean procedure time for shunt placement was 145 minutes. No intraoperative complications occurred, and all patients were discharged uneventfully. At the 6-month follow-up, 81% of patients (21 of 26) had relief of their presenting symptoms. Shunt survival without revision was 86% (25 of 29) at 1 year and 67% (10 of 15) at 3 years, with no infections. CONCLUSION The SGTC-CPS offers an alternative solution for cerebrospinal fluid diversion in patients with IIH and demonstrates a lower failure rate and more durable symptom relief compared with ventriculoperitoneal or lumboperitoneal shunt placement. Using proper techniques and equipment promotes safe and facile placement of the proximal catheter.
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Affiliation(s)
- Steve S Cho
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Andre A Wakim
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Clare W Teng
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Christina E Sarris
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
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10
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Park MT, Abramov I, Gooldy TC, Smith KA, Porter RW, Little AS, Lawton MT, Eschbacher JM, Preul MC. Introduction of In Vivo Confocal Laser Endomicroscopy and Real-Time Telepathology for Remote Intraoperative Neurosurgery-Pathology Consultation. Oper Neurosurg (Hagerstown) 2022; 23:261-267. [PMID: 35972091 DOI: 10.1227/ons.0000000000000288] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 03/22/2022] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Precise communication between neurosurgeons and pathologists is crucial for optimizing patient care, especially for intraoperative diagnoses. Confocal laser endomicroscopy (CLE) combined with a telepathology software platform (TSP) provides a novel venue for neurosurgeons and pathologists to review CLE images and converse intraoperatively in real-time. OBJECTIVE To describe the feasibility of integrating CLE and a TSP in the surgical workflow for real-time review of in vivo digital fluorescence tissue imaging in 3 patients with intracranial tumors. METHODS Although the neurosurgeon used the CLE probe to generate fluorescence images of histoarchitecture within the operative field that were displayed on monitors in the operating room, the pathologist simultaneously remotely viewed the CLE images. The neurosurgeon and pathologist discussed in real-time the histological structures of intraoperative imaging locations. RESULTS The neurosurgeon placed the CLE probe at various locations on and around the tumor, in the surgical resection bed, and on surrounding brain tissue with communication through the TSP. The neurosurgeon oriented the pathologist to the location of the CLE, and the pathologist and neurosurgeon discussed the CLE images in real-time. The TSP and CLE were integrated successfully and rapidly in the operating room in all 3 cases. No patient had perioperative complications. CONCLUSION Two novel digital neurosurgical cellular imaging technologies were combined with intraoperative neurosurgeon-pathologist communication to guide the identification of abnormal histoarchitectural tissue features in real-time. CLE with the TSP may allow rapid decision-making during tumor resection that may hold significant advantages over the frozen section process and surgical workflow in general.
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Affiliation(s)
- Marian T Park
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Irakliy Abramov
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Timothy C Gooldy
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Kris A Smith
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Randall W Porter
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Andrew S Little
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Michael T Lawton
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Jennifer M Eschbacher
- Department of Neuropathology, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Mark C Preul
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
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11
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McHugh T, Sommer DD, Thamboo A, Tewfik MA, Smith KA. Correction: Image guidance system use amongst Canadian otolaryngologists: a nationwide survey. J Otolaryngol Head Neck Surg 2022; 51:31. [PMID: 35902983 PMCID: PMC9336095 DOI: 10.1186/s40463-022-00589-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- T McHugh
- Division of Otolaryngology, Head and Neck Surgery, Department of Surgery, McGill University, Montreal, QC, Canada.
| | - D D Sommer
- Division of Otolaryngology, Head and Neck Surgery, Department of Surgery, McGill University, Montreal, QC, Canada
| | - A Thamboo
- Division of Otolaryngology, Head and Neck Surgery, Department of Surgery, McGill University, Montreal, QC, Canada.,Division of Otolaryngology, Head and Neck Surgery, Department of Surgery, University of British Columbia, Vancouver, BC, Canada
| | - M A Tewfik
- Department of Otolaryngology, Head and Neck Surgery, University of Manitoba, Winnipeg, MB, Canada
| | - K A Smith
- ENT Clinic, The Montreal Children's Hospital, 1001 Boulevard Décarie, A.RC.4221, Montréal, QC, H4A 3J1, Canada
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12
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Smith KA, Hendricks BK, DiDomenico JD, Conway BN, Smith TL, Azadi A, Fonkem E. Ketogenic Metabolic Therapy for Glioma. Cureus 2022; 14:e26457. [PMID: 35923675 PMCID: PMC9339381 DOI: 10.7759/cureus.26457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/17/2022] [Indexed: 11/15/2022] Open
Abstract
Purpose: This study describes a retrospective case series of patients with glioma who received ketogenic metabolic therapy through dietary adherence and intermittent fasting. Methods: A retrospective chart review of a single surgeon’s clinic records was performed to identify patients who maintained nutritional ketosis for at least four months between January 2015 and October 2020. Results: Sixteen patients who met the inclusion criteria constituted a heterogeneous population of patients with diagnoses including eight World Health Organization (WHO) grade IV gliomas (seven glioblastoma, one gliosarcoma), seven WHO grade III gliomas (three oligodendroglioma, four astrocytoma), and one WHO grade II oligodendroglioma. IDH1 mutation status was present for 12 patients, and MGMT methylation status was present for eight patients. The mean (standard deviation [SD]) duration of ketogenic metabolic therapy was 20.6 (13.8) months. The Response Assessment in Neuro-oncology Criteria was applied during the ketogenic metabolic therapy interval, indicating a complete response in eight patients and partial response in eight patients. The mean (SD) progression-free survival while patients maintained ketogenic metabolic therapy was 20.0 (14.4) months. Conclusion: Ketogenic metabolic therapy appears to convey a survival advantage within this patient series, which highlights the possibility that this therapy, when strictly applied, can augment the standard of care. Further exploration of this modality in a prospective series is warranted to formally explore this therapy.
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13
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McHugh T, Sommer DD, ThambooTewfik AM, Smith KA, McHugh T. Image guidance system use amongst Canadian otolaryngologists: a nationwide survey. J Otolaryngol Head Neck Surg 2022; 51:27. [PMID: 35698181 PMCID: PMC9190092 DOI: 10.1186/s40463-022-00581-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 05/12/2022] [Indexed: 11/17/2022] Open
Abstract
Background The use of image guidance systems has gained widespread acceptance as an adjunctive tool for endoscopic sinus surgery. However, the accessibility and usage of this technology is variable across hospitals in Canada.
Study objective The aim of this study is to investigate the availability, usage, and related issues surrounding the use of image guidance systems in endoscopic sinus surgery across Canadian otolaryngology practice settings. Methods An online survey was electronically distributed to practicing otolaryngologists across Canada. The survey contained 27 questions pertaining to the availability, usage, barriers and overall experience of image guidance systems. Results The survey was electronically sent to a total of 654 Canadian otolaryngologists of which 158 responded (response rate 24.2%). Image guidance was available to 56.3% of respondents. Of the respondents without access to IGS, 85.5% indicated they would use it if it was available. Financial (capital cost) was identified as the most important barrier in obtaining IGS by 76.3% of respondents. Conclusion Over half of Canadian otolaryngologists have access to IGS with over 85% of those without access interested in using it if it was made available. A multitude of different factors contribute to this disparity. We hope that the results of this study will help support Canadian otolaryngologists to access IGS. Graphical Abstract ![]()
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Affiliation(s)
- T McHugh
- Division of Otolaryngology, Head and Neck Surgery, Department of Surgery, McGill University, Montreal, QC, Canada
| | - D D Sommer
- Division of Otolaryngology, Head and Neck Surgery, Department of Surgery, McMaster University, Hamilton, ON, Canada
| | - A Ma ThambooTewfik
- Division of Otolaryngology, Head and Neck Surgery, Department of Surgery, McGill University, Montreal, QC, Canada.,Division of Otolaryngology, Head and Neck Surgery, Department of Surgery, University of British Columbia, Vancouver, BC, Canada
| | - K A Smith
- Department of Otolaryngology, Head and Neck Surgery, University of Manitoba, Winnipeg, MB, Canada
| | - Tobial McHugh
- A.RC.4221 ENT Clinic, The Montreal Children's Hospital, 1001 Boulevard Décarie, Montréal, QC, H4A 3J1, Canada.
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14
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Abramov I, Park MT, Gooldy TC, Xu Y, Lawton MT, Little AS, Porter RW, Smith KA, Eschbacher JM, Preul MC. Real-time intraoperative surgical telepathology using confocal laser endomicroscopy. Neurosurg Focus 2022; 52:E9. [PMID: 35921184 DOI: 10.3171/2022.3.focus2250] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 03/23/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Communication between neurosurgeons and pathologists is mandatory for intraoperative decision-making and optimization of resection, especially for invasive masses. Handheld confocal laser endomicroscopy (CLE) technology provides in vivo intraoperative visualization of tissue histoarchitecture at cellular resolution. The authors evaluated the feasibility of using an innovative surgical telepathology software platform (TSP) to establish real-time, on-the-fly remote communication between the neurosurgeon using CLE and the pathologist. METHODS CLE and a TSP were integrated into the surgical workflow for 11 patients with brain masses (6 patients with gliomas, 3 with other primary tumors, 1 with metastasis, and 1 with reactive brain tissue). Neurosurgeons used CLE to generate video-flow images of the operative field that were displayed on monitors in the operating room. The pathologist simultaneously viewed video-flow CLE imaging using a digital tablet and communicated with the surgeon while physically located outside the operating room (1 pathologist was in another state, 4 were at home, and 6 were elsewhere in the hospital). Interpretations of the still CLE images and video-flow CLE imaging were compared with the findings on the corresponding frozen and permanent H&E histology sections. RESULTS Overall, 24 optical biopsies were acquired with mean ± SD 2 ± 1 optical biopsies per case. The mean duration of CLE system use was 1 ± 0.3 minutes/case and 0.25 ± 0.23 seconds/optical biopsy. The first image with identifiable histopathological features was acquired within 6 ± 0.1 seconds. Frozen sections were processed within 23 ± 2.8 minutes, which was significantly longer than CLE usage (p < 0.001). Video-flow CLE was used to correctly interpret tissue histoarchitecture in 96% of optical biopsies, which was substantially higher than the accuracy of using still CLE images (63%) (p = 0.005). CONCLUSIONS When CLE is employed in tandem with a TSP, neurosurgeons and pathologists can view and interpret CLE images remotely and in real time without the need to biopsy tissue. A TSP allowed neurosurgeons to receive real-time feedback on the optically interrogated tissue microstructure, thereby improving cross-functional communication and intraoperative decision-making and resulting in significant workflow advantages over the use of frozen section analysis.
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Affiliation(s)
- Irakliy Abramov
- 1The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona; and
| | - Marian T Park
- 1The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona; and
| | | | - Yuan Xu
- 1The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona; and
| | | | | | | | | | - Jennifer M Eschbacher
- 3Neuropathology, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Mark C Preul
- 1The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona; and
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15
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Cole TS, Graham DT, Wakim AA, Bohl MA, Morgan CD, Catapano JS, Smith KA, Sanai N, Lawton MT. Local 3-Dimensional Printing of a Calvarium-Anchored Ventricular Catheter Occlusion Device. Neurosurg open 2021. [DOI: 10.1093/neuopn/okab024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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16
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Przybylowski CJ, Whiting AC, Preul MC, Smith KA. Anatomical Subpial Resection of Tumors in the Amygdala and Hippocampus. World Neurosurg 2021; 151:e652-e662. [PMID: 33940265 DOI: 10.1016/j.wneu.2021.04.100] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 04/21/2021] [Accepted: 04/21/2021] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Surgical techniques to achieve complete resection of mesial-basal temporal tumors should be pursued by neurosurgical oncologists. We describe the anatomical subpial amygdalohippocampectomy (SpAH) technique for tumor resection. METHODS The key anatomical landmarks and critical steps of the SpAH technique were outlined and emphasized with medical illustrations and intraoperative photographs. The senior author's 90-day surgical outcomes with this approach were reviewed. RESULTS Twenty-five patients (men, 17 [68%]; women, 8 [32%]; median [range] age, 59 [23-80] years) with temporal tumors involving the amygdalohippocampal region were included. SpAH was performed selectively in 8 [32%] patients, whereas 17 [68%] patients underwent SpAH in conjunction with an anterior temporal lobectomy due to tumor involvement of the anterolateral temporal cortex. The subpial resection of the amygdala protected the critical structures of the suprasellar cistern and sylvian fissure. Identifying the choroidal fissure as the superior-most aspect of hippocampal resection protected the optic tract and the thalamus. Subpial resection of the parahippocampal gyrus inferiorly protected the brainstem and critical structures of the ambient cistern. Tumors in the amygdalohippocampal region were anatomically and completely resected in all 25 patients. Of the 15 patients who presented with seizures, 13 (87%) were seizure-free at the 90-day postsurgical follow-up. Permanent neurologic deficits occurred in 3 patients (12%). CONCLUSIONS The SpAH technique permits complete resection of mesial-basal temporal tumors with an acceptable morbidity profile. An in-depth understanding of temporal lobe anatomy combined with a refined microsurgical technique allows for reproducible resection of tumor in the amygdalohippocampal region while protecting critical neurovascular structures.
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Affiliation(s)
- Colin J Przybylowski
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Alexander C Whiting
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Mark C Preul
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA.
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17
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Hu LS, Wang L, Hawkins-Daarud A, Eschbacher JM, Singleton KW, Jackson PR, Clark-Swanson K, Sereduk CP, Peng S, Wang P, Wang J, Baxter LC, Smith KA, Mazza GL, Stokes AM, Bendok BR, Zimmerman RS, Krishna C, Porter AB, Mrugala MM, Hoxworth JM, Wu T, Tran NL, Swanson KR, Li J. Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma. Sci Rep 2021; 11:3932. [PMID: 33594116 PMCID: PMC7886858 DOI: 10.1038/s41598-021-83141-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Accepted: 01/18/2021] [Indexed: 12/13/2022] Open
Abstract
Radiogenomics uses machine-learning (ML) to directly connect the morphologic and physiological appearance of tumors on clinical imaging with underlying genomic features. Despite extensive growth in the area of radiogenomics across many cancers, and its potential role in advancing clinical decision making, no published studies have directly addressed uncertainty in these model predictions. We developed a radiogenomics ML model to quantify uncertainty using transductive Gaussian Processes (GP) and a unique dataset of 95 image-localized biopsies with spatially matched MRI from 25 untreated Glioblastoma (GBM) patients. The model generated predictions for regional EGFR amplification status (a common and important target in GBM) to resolve the intratumoral genetic heterogeneity across each individual tumor-a key factor for future personalized therapeutic paradigms. The model used probability distributions for each sample prediction to quantify uncertainty, and used transductive learning to reduce the overall uncertainty. We compared predictive accuracy and uncertainty of the transductive learning GP model against a standard GP model using leave-one-patient-out cross validation. Additionally, we used a separate dataset containing 24 image-localized biopsies from 7 high-grade glioma patients to validate the model. Predictive uncertainty informed the likelihood of achieving an accurate sample prediction. When stratifying predictions based on uncertainty, we observed substantially higher performance in the group cohort (75% accuracy, n = 95) and amongst sample predictions with the lowest uncertainty (83% accuracy, n = 72) compared to predictions with higher uncertainty (48% accuracy, n = 23), due largely to data interpolation (rather than extrapolation). On the separate validation set, our model achieved 78% accuracy amongst the sample predictions with lowest uncertainty. We present a novel approach to quantify radiogenomics uncertainty to enhance model performance and clinical interpretability. This should help integrate more reliable radiogenomics models for improved medical decision-making.
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Affiliation(s)
- Leland S Hu
- Department of Radiology, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA. .,School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, 699 S Mill Ave, Tempe, AZ, 85281, USA. .,Mathematical NeuroOncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic Arizona, 5777 East Mayo Blvd, Support Services Building Suite 2-700, Phoenix, AZ, 85054, USA.
| | - Lujia Wang
- Department of Radiology, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA.,School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, 699 S Mill Ave, Tempe, AZ, 85281, USA.,Mathematical NeuroOncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic Arizona, 5777 East Mayo Blvd, Support Services Building Suite 2-700, Phoenix, AZ, 85054, USA
| | - Andrea Hawkins-Daarud
- Mathematical NeuroOncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic Arizona, 5777 East Mayo Blvd, Support Services Building Suite 2-700, Phoenix, AZ, 85054, USA
| | - Jennifer M Eschbacher
- Department of Pathology, Barrow Neurological Institute-St. Joseph's Hospital and Medical Center, Phoenix, AZ, 85013, USA
| | - Kyle W Singleton
- Mathematical NeuroOncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic Arizona, 5777 East Mayo Blvd, Support Services Building Suite 2-700, Phoenix, AZ, 85054, USA
| | - Pamela R Jackson
- Mathematical NeuroOncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic Arizona, 5777 East Mayo Blvd, Support Services Building Suite 2-700, Phoenix, AZ, 85054, USA
| | - Kamala Clark-Swanson
- Mathematical NeuroOncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic Arizona, 5777 East Mayo Blvd, Support Services Building Suite 2-700, Phoenix, AZ, 85054, USA
| | - Christopher P Sereduk
- Department of Neurosurgery, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA.,Department of Cancer Biology, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA
| | - Sen Peng
- Cancer and Cell Biology Division, Translational Genomics Research Institute, Phoenix, AZ, 85004, USA
| | - Panwen Wang
- Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic Arizona, Scottsdale, AZ, 85259, USA
| | - Junwen Wang
- Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic Arizona, Scottsdale, AZ, 85259, USA
| | - Leslie C Baxter
- Department of Neuropsychology, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA
| | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute-St. Joseph's Hospital and Medical Center, Phoenix, AZ, 85013, USA
| | - Gina L Mazza
- Department of Quantitative Health Sciences, Mayo Clinic Arizona, Scottsdale, AZ, 85259, USA
| | - Ashley M Stokes
- Department of Imaging Research, Barrow Neurological Institute-St. Joseph's Hospital and Medical Center, Phoenix, AZ, 85013, USA
| | - Bernard R Bendok
- Department of Neurosurgery, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA
| | - Richard S Zimmerman
- Department of Neurosurgery, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA
| | - Chandan Krishna
- Department of Neurosurgery, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA
| | - Alyx B Porter
- Department of Neuro-Oncology, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA
| | - Maciej M Mrugala
- Department of Neuro-Oncology, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA
| | - Joseph M Hoxworth
- Department of Radiology, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA
| | - Teresa Wu
- Department of Radiology, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA.,School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, 699 S Mill Ave, Tempe, AZ, 85281, USA
| | - Nhan L Tran
- Department of Neurosurgery, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA.,Department of Cancer Biology, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA
| | - Kristin R Swanson
- Mathematical NeuroOncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic Arizona, 5777 East Mayo Blvd, Support Services Building Suite 2-700, Phoenix, AZ, 85054, USA.,Department of Neurosurgery, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA
| | - Jing Li
- Department of Radiology, Mayo Clinic Arizona, 5777 E. Mayo Blvd, Phoenix, AZ, 85054, USA.,School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, 699 S Mill Ave, Tempe, AZ, 85281, USA.,Mathematical NeuroOncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic Arizona, 5777 East Mayo Blvd, Support Services Building Suite 2-700, Phoenix, AZ, 85054, USA
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18
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Chan Y, Angel D, Aron M, Hartl T, Moubayed SP, Smith KA, Sommer DD, Sowerby L, Spafford P, Mertz D, Witterick IJ. CSO (Canadian Society of Otolaryngology - Head & Neck Surgery) position paper on return to Otolaryngology - Head & Neck Surgery Clinic Practice during the COVID-19 pandemic in Canada. J Otolaryngol Head Neck Surg 2020; 49:76. [PMID: 33106189 PMCID: PMC7586368 DOI: 10.1186/s40463-020-00466-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 09/16/2020] [Indexed: 12/14/2022] Open
Abstract
The novel Coronavirus (COVID-19) has created a worldwide deadly pandemic that has become a major public health challenge. All semi-urgent and elective medical care has come to a halt to conserve capacity to care for patients during this pandemic. As the numbers of COVID-19 cases decrease across Canada, our healthcare system also began to reopen various facilities and medical offices. The aim for this document is to compile the current evidence and provide expert consensus on the safe return to clinic practice in Otolaryngology - Head & Neck Surgery. These recommendations will also summarize general precaution principles and practical tips for office across Canada to optimize patient and provider safety. Risk assessment and patient selection are crucial to minimizing exposure to COVID-19. Controversial topics such as COVID-19 mode of transmission, duration of exposure, personal protective equipment, and aerosol-generating procedures will be analyzed and discussed. Practical solutions of pre-visit office preparation, front office and examination room set-up, and check out procedures are explored. Specific considerations for audiology, pediatric population, and high risk AGMPs are also addressed. Given that the literature surrounding COVID-19 is rapidly evolving, these guidelines will serve to start our specialty back into practice over the next weeks to months and they may change as we learn more about this disease.
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Affiliation(s)
- Y Chan
- Department of Otolaryngology - Head & Neck Surgery, University of Toronto, Toronto, ON, Canada.
| | - D Angel
- Division of Otolaryngology - Head & Neck Surgery, Memorial University of Newfoundland, St. John's, NL, Canada
| | - M Aron
- Division of Otolaryngology - Head & Neck Surgery, Department of Surgery, University of British Columbia, Vancouver, BC, Canada
| | - T Hartl
- Division of Otolaryngology - Head & Neck Surgery, Department of Surgery, University of British Columbia, Vancouver, BC, Canada
| | - S P Moubayed
- Division of Otolaryngology - Head & Neck Surgery, University of Montreal, Montreal, QC, Canada
| | - K A Smith
- Department of Otolaryngology - Head & Neck Surgery, University of Manitoba, Winnipeg, MB, Canada
| | - D D Sommer
- Otolaryngology - Head & Neck Surgery Division, Department of Surgery, McMaster University, Hamilton, ON, Canada
| | - L Sowerby
- Department of Otolaryngology - Head & Neck Surgery, Western University, London, ON, Canada
| | - P Spafford
- Division of Otolaryngology - Head and Neck Surgery, Department of Surgery, University of Saskatchewan, Saskatoon, SK, Canada
| | - D Mertz
- Division of Infectious Diseases, Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - I J Witterick
- Department of Otolaryngology - Head & Neck Surgery, University of Toronto, Toronto, ON, Canada
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19
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Catapano JS, Mezher AW, Wang DJ, Whiting AC, Mooney MA, Bohl MA, Sheehy JP, DiDomenico JD, Sarris CE, Smith KA, Lawton MT, Zabramski JM. In Reply to the Letter to the Editor Regarding "Laparoscopic-Assisted Ventriculoperitoneal Shunt Placement and Reduction in Operative Time and Total Hospital Charges". World Neurosurg 2020; 140:442. [PMID: 32797965 DOI: 10.1016/j.wneu.2020.06.054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 06/06/2020] [Indexed: 10/23/2022]
Affiliation(s)
- Joshua S Catapano
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Andrew W Mezher
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Derrick J Wang
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Alexander C Whiting
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Michael A Mooney
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Michael A Bohl
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - John P Sheehy
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Joseph D DiDomenico
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Christina E Sarris
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Michael T Lawton
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Joseph M Zabramski
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA.
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20
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Whiting AC, Cavallo C, Rubel N, Catapano JS, Walker CT, Smith KA. Multiple Subpial Transections in Eloquent Cortex for Refractory Epilepsy: 2-Dimensional Operative Video. Oper Neurosurg (Hagerstown) 2020; 19:E167. [PMID: 31777942 DOI: 10.1093/ons/opz318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 08/15/2019] [Indexed: 11/13/2022] Open
Abstract
Although the epilepsy refractory to medical therapy can potentially be cured by the resection of epileptogenic tissue, many patients do not qualify for surgery, because epileptogenic tissue can arise from eloquent areas of the brain, where surgical resection would result in severe neurological deficits. Palliative surgical treatments currently used in these situations include deep brain stimulation, responsive neurostimulation, and vagal nerve stimulation.1 A previously developed technique, multiple subpial transections (MSTs), although used infrequently, is another effective tool.2 Our patient, a 34-yr-old man, had epilepsy that was refractory to medical management. His preoperative work-up demonstrated a potential seizure focus in the left pars opercularis and left superior temporal gyrus, which was verified using invasive stereoelectroencephalography. Functional magnetic resonance imaging demonstrated a significant verbal and motor function in this region. After informed consent was obtained, the patient underwent a left-sided craniotomy. The central portion of the seizure focus was resected using the subpial technique. The surrounding presumed epileptogenic cortex, which was considered functionally eloquent, was then horizontally disconnected with MSTs. For each transection, a small puncture incision was made in the pia, and a vertical cut was completed using Morrell dissectors.2 MSTs were performed circumferentially around the entire resection cavity in 5-mm increments. All hemostasis was achieved with irrigation instead of electrocautery, although noncauterizing hemostatic agents are also acceptable. The patient was neurologically intact after the operation and was discharged home on postoperative day 2. He was free of seizures at 11-month follow-up. Used with permission from Barrow Neurological Institute, Phoenix, Arizona.
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Affiliation(s)
- Alexander C Whiting
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Claudio Cavallo
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Nicholas Rubel
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Joshua S Catapano
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Corey T Walker
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
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21
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Morris B, Curtin L, Hawkins-Daarud A, Hubbard ME, Rahman R, Smith SJ, Auer D, Tran NL, Hu LS, Eschbacher JM, Smith KA, Stokes A, Swanson KR, Owen MR. Identifying the spatial and temporal dynamics of molecularly-distinct glioblastoma sub-populations. Math Biosci Eng 2020; 17:4905-4941. [PMID: 33120534 PMCID: PMC8382158 DOI: 10.3934/mbe.2020267] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Glioblastomas (GBMs) are the most aggressive primary brain tumours and have no known cure. Each individual tumour comprises multiple sub-populations of genetically-distinct cells that may respond differently to targeted therapies and may contribute to disappointing clinical trial results. Image-localized biopsy techniques allow multiple biopsies to be taken during surgery and provide information that identifies regions where particular sub-populations occur within an individual GBM, thus providing insight into their regional genetic variability. These sub-populations may also interact with one another in a competitive or cooperative manner; it is important to ascertain the nature of these interactions, as they may have implications for responses to targeted therapies. We combine genetic information from biopsies with a mechanistic model of interacting GBM sub-populations to characterise the nature of interactions between two commonly occurring GBM sub-populations, those with EGFR and PDGFRA genes amplified. We study population levels found across image-localized biopsy data from a cohort of 25 patients and compare this to model outputs under competitive, cooperative and neutral interaction assumptions. We explore other factors affecting the observed simulated sub-populations, such as selection advantages and phylogenetic ordering of mutations, which may also contribute to the levels of EGFR and PDGFRA amplified populations observed in biopsy data.
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Affiliation(s)
- Bethan Morris
- School of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Lee Curtin
- Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, 85054, USA
| | | | - Matthew E. Hubbard
- School of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Ruman Rahman
- School of Medicine and Health Sciences, University of Nottingham, Nottingham, NG7 2UH, UK
| | - Stuart J. Smith
- School of Medicine and Health Sciences, University of Nottingham, Nottingham, NG7 2UH, UK
| | - Dorothee Auer
- School of Medicine and Health Sciences, University of Nottingham, Nottingham, NG7 2UH, UK
| | - Nhan L. Tran
- Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, 85054, USA
- Department of Cancer Biology, Mayo Clinic, Phoenix, Arizona 85054, USA
| | - Leland S. Hu
- Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, 85054, USA
- Department of Radiology, Mayo Clinic, Phoenix, Arizona 85054, USA
| | - Jennifer M. Eschbacher
- Department of Pathology, Barrow Neurological Institute - St. Joseph’s Hospital and Medical Center, Phoenix, Arizona 85013, USA
| | - Kris A. Smith
- Department of Neurosurgery, Barrow Neurological Institute - St. Joseph’s Hospital and Medical Center, Phoenix, Arizona 85013, USA
| | - Ashley Stokes
- Department of Imaging Research, Barrow Neurological Institute - St. Joseph’s Hospital and Medical Center, Phoenix, Arizona 85013, USA
| | - Kristin R. Swanson
- Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, Arizona, 85054, USA
- Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona 85054, USA
| | - Markus R. Owen
- School of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD, UK
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22
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Whiting AC, Chen T, Swanson KI, Walker CT, Godzik J, Catapano JS, Smith KA. Seizure and neuropsychological outcomes in a large series of selective amygdalohippocampectomies with a minimally invasive subtemporal approach. J Neurosurg 2020; 134:1685-1693. [PMID: 32534491 DOI: 10.3171/2020.3.jns192589] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 03/30/2020] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Debate continues over proper surgical treatment for mesial temporal lobe epilepsy (MTLE). Few large comprehensive studies exist that have examined outcomes for the subtemporal selective amygdalohippocampectomy (sSAH) approach. This study describes a minimally invasive technique for sSAH and examines seizure and neuropsychological outcomes in a large series of patients who underwent sSAH for MTLE. METHODS Data for 152 patients (94 women, 61.8%; 58 men, 38.2%) who underwent sSAH performed by a single surgeon were retrospectively reviewed. The sSAH technique involves a small, minimally invasive opening and preserves the anterolateral temporal lobe and the temporal stem. RESULTS All patients in the study had at least 1 year of follow-up (mean [SD] 4.52 [2.57] years), of whom 57.9% (88/152) had Engel class I seizure outcomes. Of the patients with at least 2 years of follow-up (mean [SD] 5.2 [2.36] years), 56.5% (70/124) had Engel class I seizure outcomes. Preoperative and postoperative neuropsychological test results indicated no significant change in intelligence, verbal comprehension, perceptual reasoning, attention and processing, cognitive flexibility, visuospatial memory, or mood. There was a significant change in word retrieval regardless of the side of surgery and a significant change in verbal memory in patients who underwent dominant-side resection (p < 0.05). Complication rates were low, with a 1.3% (2/152) permanent morbidity rate and 0.0% mortality rate. CONCLUSIONS This study reports a large series of patients who have undergone sSAH, with a comprehensive presentation of a minimally invasive technique. The sSAH approach described in this study appears to be a safe, effective, minimally invasive technique for the treatment of MTLE.
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23
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Cole TS, Smith KA. Posterior interhemispheric approach for a large falcotentorial meningioma. Interdisciplinary Neurosurgery 2020. [DOI: 10.1016/j.inat.2020.100667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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24
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Hoxworth JM, Eschbacher JM, Gonzales AC, Singleton KW, Leon GD, Smith KA, Stokes AM, Zhou Y, Mazza GL, Porter AB, Mrugala MM, Zimmerman RS, Bendok BR, Patra DP, Krishna C, Boxerman JL, Baxter LC, Swanson KR, Quarles CC, Schmainda KM, Hu LS. Performance of Standardized Relative CBV for Quantifying Regional Histologic Tumor Burden in Recurrent High-Grade Glioma: Comparison against Normalized Relative CBV Using Image-Localized Stereotactic Biopsies. AJNR Am J Neuroradiol 2020; 41:408-415. [PMID: 32165359 DOI: 10.3174/ajnr.a6486] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 12/23/2019] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Perfusion MR imaging measures of relative CBV can distinguish recurrent tumor from posttreatment radiation effects in high-grade gliomas. Currently, relative CBV measurement requires normalization based on user-defined reference tissues. A recently proposed method of relative CBV standardization eliminates the need for user input. This study compares the predictive performance of relative CBV standardization against relative CBV normalization for quantifying recurrent tumor burden in high-grade gliomas relative to posttreatment radiation effects. MATERIALS AND METHODS We recruited 38 previously treated patients with high-grade gliomas (World Health Organization grades III or IV) undergoing surgical re-resection for new contrast-enhancing lesions concerning for recurrent tumor versus posttreatment radiation effects. We recovered 112 image-localized biopsies and quantified the percentage of histologic tumor content versus posttreatment radiation effects for each sample. We measured spatially matched normalized and standardized relative CBV metrics (mean, median) and fractional tumor burden for each biopsy. We compared relative CBV performance to predict tumor content, including the Pearson correlation (r), against histologic tumor content (0%-100%) and the receiver operating characteristic area under the curve for predicting high-versus-low tumor content using binary histologic cutoffs (≥50%; ≥80% tumor). RESULTS Across relative CBV metrics, fractional tumor burden showed the highest correlations with tumor content (0%-100%) for normalized (r = 0.63, P < .001) and standardized (r = 0.66, P < .001) values. With binary cutoffs (ie, ≥50%; ≥80% tumor), predictive accuracies were similar for both standardized and normalized metrics and across relative CBV metrics. Median relative CBV achieved the highest area under the curve (normalized = 0.87, standardized = 0.86) for predicting ≥50% tumor, while fractional tumor burden achieved the highest area under the curve (normalized = 0.77, standardized = 0.80) for predicting ≥80% tumor. CONCLUSIONS Standardization of relative CBV achieves similar performance compared with normalized relative CBV and offers an important step toward workflow optimization and consensus methodology.
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Affiliation(s)
- J M Hoxworth
- From the Departments of Radiology (J.M.H., Y.Z., L.S.H.)
| | | | | | - K W Singleton
- Precision Neurotherapeutics Lab (K.W.S., G.D.L., B.R.B., K.R.S.), Mayo Clinic in Arizona, Phoenix, Arizona
| | - G D Leon
- Precision Neurotherapeutics Lab (K.W.S., G.D.L., B.R.B., K.R.S.), Mayo Clinic in Arizona, Phoenix, Arizona
| | - K A Smith
- Keller Center for Imaging Innovation (A.M.S.), Barrow Neurological Institute, Phoenix, Arizona
| | - A M Stokes
- Keller Center for Imaging Innovation (A.M.S.), Barrow Neurological Institute, Phoenix, Arizona
| | - Y Zhou
- From the Departments of Radiology (J.M.H., Y.Z., L.S.H.)
| | - G L Mazza
- Department of Health Sciences Research (G.L.M.), Division of Biomedical Statistics and Informatics, Mayo Clinic Scottsdale, Scottsdale, Arizona
| | | | | | | | - B R Bendok
- Precision Neurotherapeutics Lab (K.W.S., G.D.L., B.R.B., K.R.S.), Mayo Clinic in Arizona, Phoenix, Arizona
| | - D P Patra
- Departments of Neurosurgery (D.P.P.)
| | | | - J L Boxerman
- Department of Diagnostic Imaging (J.L.B.), Rhode Island Hospital, Providence, Rhode Island
| | - L C Baxter
- Neuropsychology (L.C.B.), Mayo Clinic Hospital, Phoenix, Arizona
| | - K R Swanson
- Precision Neurotherapeutics Lab (K.W.S., G.D.L., B.R.B., K.R.S.), Mayo Clinic in Arizona, Phoenix, Arizona
| | | | - K M Schmainda
- Department of Radiology (K.M.S.), Medical College of Wisconsin, Milwaukee, Wisconsin
| | - L S Hu
- From the Departments of Radiology (J.M.H., Y.Z., L.S.H.)
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25
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Brachman DG, Youssef E, Dardis CJ, Sanai N, Zabramski JM, Smith KA, Little AS, Shetter AG, Thomas T, McBride HL, Sorensen S, Spetzler RF, Nakaji P. Resection and permanent intracranial brachytherapy using modular, biocompatible cesium-131 implants: results in 20 recurrent, previously irradiated meningiomas. J Neurosurg 2019; 131:1819-1828. [DOI: 10.3171/2018.7.jns18656] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Accepted: 07/16/2018] [Indexed: 12/30/2022]
Abstract
OBJECTIVEEffective treatments for recurrent, previously irradiated intracranial meningiomas are limited, and resection alone is not usually curative. Thus, the authors studied the combination of maximum safe resection and adjuvant radiation using permanent intracranial brachytherapy (R+BT) in patients with recurrent, previously irradiated aggressive meningiomas.METHODSPatients with recurrent, previously irradiated meningiomas were treated between June 2013 and October 2016 in a prospective single-arm trial of R+BT. Cesium-131 (Cs-131) radiation sources were embedded in modular collagen carriers positioned in the operative bed on completion of resection. The Cox proportional hazards model with this treatment as a predictive term was used to model its effect on time to local tumor progression.RESULTSNineteen patients (median age 64.5 years, range 50–78 years) with 20 recurrent, previously irradiated tumors were treated. The WHO grade at R+BT was I in 4 (20%), II in 14 (70%), and III in 2 (10%) cases. The median number of prior same-site radiation courses and same-site surgeries were 1 (range 1–3) and 2 (range 1–4), respectively; the median preoperative tumor volume was 11.3 cm3 (range 0.9–92.0 cm3). The median radiation dose from BT was 63 Gy (range 54–80 Gy). At a median radiographic follow-up of 15.4 months (range 0.03–47.5 months), local failure (within 1.5 cm of the implant bed) occurred in 2 cases (10%). The median treatment-site time to progression after R+BT has not been reached; that after the most recent prior therapy was 18.3 months (range 3.9–321.9 months; HR 0.17, p = 0.02, log-rank test). The median overall survival after R+BT was 26 months, with 9 patient deaths (47% of patients). Treatment was well tolerated; 2 patients required surgery for complications, and 2 experienced radiation necrosis, which was managed medically.CONCLUSIONSR+BT utilizing Cs-131 sources in modular carriers represents a potentially safe and effective treatment option for recurrent, previously irradiated aggressive meningiomas.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Theresa Thomas
- 4St. Joseph’s Hospital and Medical Center, Phoenix, Arizona; and
| | | | - Stephen Sorensen
- 4St. Joseph’s Hospital and Medical Center, Phoenix, Arizona; and
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Smith KA, Frazzini Padilla P, Sprague ML. 2131 Trends in Patient Follow-Up after Minimally Invasive Hysterectomy. J Minim Invasive Gynecol 2019. [DOI: 10.1016/j.jmig.2019.09.132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Whiting AC, Catapano JS, Zavala B, Walker CT, Godzik J, Chen T, Smith KA. Doing More with Less: A Minimally Invasive, Cost-Conscious Approach to Stereoelectroencephalography. World Neurosurg 2019; 133:34-40. [PMID: 31541761 DOI: 10.1016/j.wneu.2019.09.055] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 09/09/2019] [Accepted: 09/10/2019] [Indexed: 10/26/2022]
Abstract
BACKGROUND Stereoelectroencephalography (SEEG) is a commonly used technique for mapping the epileptogenic zone before epilepsy surgery. Many SEEG depth electrode implantation techniques involve the use of extensive technological equipment and shaving of the patient's entire head before electrode implantation. Our goal was to evaluate an SEEG depth electrode implantation technique that used readily available cost-effective neurosurgical equipment, was minimally invasive in nature, and required negligible hair shaving. METHODS Data on demographic characteristics, operative time, hemorrhagic complications, implantation complications, infection, morbidity, and mortality among patients who underwent this procedure were reviewed retrospectively. RESULTS Between April 2016 and March 2018, 23 patients underwent implantation of 213 depth electrodes with use of this technique. Mean (SD) operative time was 123 (32) minutes (range, 66-181 minutes). A mean (SD) of 9.3 (1.4) electrodes were placed for each patient (range, 8-13 electrodes). Two of the 213 electrodes (0.9%) were associated with postimplantation asymptomatic hemorrhage. One of the 213 electrodes (0.5%) was placed extradurally or incorrectly. None of the 213 electrodes was associated with symptomatic complications. No patients experienced infectious complications at any point in the preoperative, perioperative, or postoperative stages. CONCLUSIONS This minimally invasive, cost-effective technique for SEEG depth electrode implantation is a safe, efficient method that uses readily available basic neurosurgical equipment. This technique may be useful in neurosurgery centers with more limited resources. This study suggests that leaving the patient's hair largely intact throughout the procedure does not pose an additional infection risk.
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Affiliation(s)
- Alexander C Whiting
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Joshua S Catapano
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Baltazar Zavala
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Corey T Walker
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Jakub Godzik
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Tsinsue Chen
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA.
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Chen T, Mastorakos GM, Swanson KI, Eschbacher JM, Smith KA. Temporal Horn Choroid Plexus Papilloma Presenting with Seizures in Adulthood: Clinical Case Report and Review of the Literature. World Neurosurg 2019; 132:403-407. [PMID: 31493601 DOI: 10.1016/j.wneu.2019.08.201] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Revised: 08/23/2019] [Accepted: 08/24/2019] [Indexed: 10/26/2022]
Abstract
BACKGROUND Choroid plexus papillomas (CPPs) are benign World Health Organization grade I tumors that comprise 2%-4% of all brain tumors among children and less than 1% of brain tumors in adults. Most adult cases occur in the fourth ventricle, with only 1 previous report describing an adult patient with a temporal horn CPP. CASE DESCRIPTION We report a rare case of a temporal horn CPP presenting in an adult with seizures. We performed a minimally invasive subtemporal approach for gross total resection of the lesion. CONCLUSIONS CPP presenting in the temporal horn is rare among adults. We discuss the surgical nuances of the subtemporal approach for resection and review the literature regarding adult presentation of CPP and the treatment strategies for adult CPP.
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Affiliation(s)
- Tsinsue Chen
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA; Department of Neurosurgery, Barrow Neurological Institute, Chandler Regional Medical Center, Chandler, Arizona, USA.
| | | | - Kyle I Swanson
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Jennifer M Eschbacher
- Department of Neuropathology, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
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Swanson KI, Smith KA, Mirzadeh Z, Ponce FA. Epilepsy, Functional Neurosurgery, and Pain. Oper Neurosurg (Hagerstown) 2019; 17:S209-S228. [PMID: 31099850 DOI: 10.1093/ons/opz075] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Accepted: 02/06/2019] [Indexed: 11/12/2022] Open
Affiliation(s)
- Kyle I Swanson
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Zaman Mirzadeh
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Francisco A Ponce
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
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Catapano JS, Whiting AC, Wang DJ, Hlubek RJ, Labib MA, Morgan CD, Brigeman S, Fredrickson VL, Cavalcanti DD, Smith KA, Ducruet AF, Albuquerque FC. Selective posterior cerebral artery amobarbital test: a predictor of memory following subtemporal selective amygdalohippocampectomy. J Neurointerv Surg 2019; 12:165-169. [PMID: 31320550 DOI: 10.1136/neurintsurg-2019-014984] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 06/10/2019] [Accepted: 06/24/2019] [Indexed: 11/03/2022]
Abstract
BACKGROUND The selective posterior cerebral artery (PCA) amobarbital test, or PCA Wada test, is used to predict memory impairment after epilepsy surgery in patients who have previously had a failed internal carotid artery (ICA) amobarbital test. METHODS Medical records from 2012 to 2018 were retrospectively reviewed for all patients with seizures who underwent a selective PCA Wada test at our institution following a failed or inconclusive ICA Wada test. Standardized neuropsychological testing was performed before and during the Wada procedure and postoperatively in patients who underwent resection. RESULTS Thirty-three patients underwent a selective PCA Wada test, with no complications. Twenty-six patients with medically refractory epilepsy had a seizure focus amenable to selective amygdalohippocampectomy (AHE). Six patients (23%, n=26) had a failed PCA Wada test and did not undergo selective AHE, seven (27%) declined surgical resection, leaving 13 patients who underwent subtemporal selective AHE. Hippocampal sclerosis was found in all 13 patients (100%). Twelve patients (92%) subsequently underwent formal neuropsychological testing and all were found to have stable memory. Ten patients (77%) were seizure-free (Engel Class I), with average follow-up of 13 months. CONCLUSION The selective PCA Wada test is predictive of memory outcomes after subtemporal selective AHE in patients with a failed or inconclusive ICA Wada test. Furthermore, given the low risk of complications and potential benefit of seizure freedom, a selective PCA Wada test may be warranted in patients with medically intractable epilepsy who are candidates for a selective AHE and who have a prior failed or inconclusive ICA Wada test.
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Affiliation(s)
- Joshua S Catapano
- Department of Neurosurgery, Barrow Neurological Institute St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Alexander C Whiting
- Department of Neurosurgery, Barrow Neurological Institute St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Derrick J Wang
- Department of Neurosurgery, Barrow Neurological Institute St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Randall J Hlubek
- Department of Neurosurgery, Barrow Neurological Institute St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Mohamed A Labib
- Department of Neurosurgery, Barrow Neurological Institute St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Clinton D Morgan
- Department of Neurosurgery, Barrow Neurological Institute St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Scott Brigeman
- Department of Neurosurgery, Barrow Neurological Institute St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Vance L Fredrickson
- Department of Neurosurgery, Barrow Neurological Institute St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Daniel D Cavalcanti
- Department of Neurosurgery, Barrow Neurological Institute St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Andrew F Ducruet
- Department of Neurosurgery, Barrow Neurological Institute St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
| | - Felipe C Albuquerque
- Department of Neurosurgery, Barrow Neurological Institute St. Joseph's Hospital and Medical Center, Phoenix, Arizona, USA
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Cardenas LM, Bhogal A, Chadwick DR, McGeough K, Misselbrook T, Rees RM, Thorman RE, Watson CJ, Williams JR, Smith KA, Calvet S. Nitrogen use efficiency and nitrous oxide emissions from five UK fertilised grasslands. Sci Total Environ 2019; 661:696-710. [PMID: 30684838 PMCID: PMC6383039 DOI: 10.1016/j.scitotenv.2019.01.082] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 12/31/2018] [Accepted: 01/08/2019] [Indexed: 05/15/2023]
Abstract
Intensification of grasslands is necessary to meet the increasing demand of livestock products. The application of nitrogen (N) on grasslands affects the N balance therefore the nitrogen use efficiency (NUE). Emissions of nitrous oxide (N2O) are produced due to N fertilisation and low NUE. These emissions depend on the type and rates of N applied. In this study we have compiled data from 5 UK N fertilised grassland sites (Crichton, Drayton, North Wyke, Hillsborough and Pwllpeiran) covering a range of soil types and climates. The experiments evaluated the effect of increasing rates of inorganic N fertiliser provided as ammonium nitrate (AN) or calcium ammonium nitrate (CAN). The following fertiliser strategies were also explored for a rate of 320 kg N ha-1: using the nitrification inhibitor dicyandiamide (DCD), changing to urea as an N source and splitting fertiliser applications. We measured N2O emissions for a full year in each experiment, as well as soil mineral N, climate data, pasture yield and N offtake. N2O emissions were greater at Crichton and North Wyke whereas Drayton, Hillsborough and Pwllpeiran had the smallest emissions. The resulting average emission factor (EF) of 1.12% total N applied showed a range of values for all the sites between 0.6 and 2.08%. NUE depended on the site and for an application rate of 320 kg N ha-1, N surplus was on average higher than 80 kg N ha-1, which is proposed as a maximum by the EU Nitrogen Expert Panel. N2O emissions tended to be lower when urea was applied instead of AN or CAN, and were particularly reduced when using urea with DCD. Finally, correlations between the factors studied showed that total N input was related to Nofftake and Nexcess; while cumulative emissions and EF were related to yield scaled emissions.
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Affiliation(s)
- L M Cardenas
- Rothamsted Research, Okehampton, Devon, EX20 2SB, UK.
| | - A Bhogal
- ADAS Boxworth, Battlegate Road, Boxworth, Cambridge CB23 4NN, UK
| | - D R Chadwick
- School of Natural Sciences, Bangor University, Bangor LL57 2UW, UK
| | - K McGeough
- Agri-Food and Biosciences Institute, 18a, Newforge Lane, BT9 5PX Belfast, UK
| | - T Misselbrook
- Rothamsted Research, Okehampton, Devon, EX20 2SB, UK
| | - R M Rees
- Scotland's Rural College (SRUC), King's Buildings, West Mains Road, Edinburgh EH9 3JG, UK
| | - R E Thorman
- ADAS Boxworth, Battlegate Road, Boxworth, Cambridge CB23 4NN, UK
| | - C J Watson
- Agri-Food and Biosciences Institute, 18a, Newforge Lane, BT9 5PX Belfast, UK
| | - J R Williams
- ADAS Boxworth, Battlegate Road, Boxworth, Cambridge CB23 4NN, UK
| | - K A Smith
- School of Geosciences, University of Edinburgh, Crew Building, Alexander Crum Brown Road, Edinburgh EH9 3FF, and Weston Road, Totnes TQ9 5AH, Devon, UK
| | - S Calvet
- Universitat Politècnica de València, Institute of Animal Science and Technology, Camino de Vera s.n., 46022, Valencia, Spain
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Hu LS, Yoon H, Eschbacher JM, Baxter LC, Dueck AC, Nespodzany A, Smith KA, Nakaji P, Xu Y, Wang L, Karis JP, Hawkins-Daarud AJ, Singleton KW, Jackson PR, Anderies BJ, Bendok BR, Zimmerman RS, Quarles C, Porter-Umphrey AB, Mrugala MM, Sharma A, Hoxworth JM, Sattur MG, Sanai N, Koulemberis PE, Krishna C, Mitchell JR, Wu T, Tran NL, Swanson KR, Li J. Accurate Patient-Specific Machine Learning Models of Glioblastoma Invasion Using Transfer Learning. AJNR Am J Neuroradiol 2019; 40:418-425. [PMID: 30819771 DOI: 10.3174/ajnr.a5981] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Accepted: 12/13/2018] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE MR imaging-based modeling of tumor cell density can substantially improve targeted treatment of glioblastoma. Unfortunately, interpatient variability limits the predictive ability of many modeling approaches. We present a transfer learning method that generates individualized patient models, grounded in the wealth of population data, while also detecting and adjusting for interpatient variabilities based on each patient's own histologic data. MATERIALS AND METHODS We recruited patients with primary glioblastoma undergoing image-guided biopsies and preoperative imaging, including contrast-enhanced MR imaging, dynamic susceptibility contrast MR imaging, and diffusion tensor imaging. We calculated relative cerebral blood volume from DSC-MR imaging and mean diffusivity and fractional anisotropy from DTI. Following image coregistration, we assessed tumor cell density for each biopsy and identified corresponding localized MR imaging measurements. We then explored a range of univariate and multivariate predictive models of tumor cell density based on MR imaging measurements in a generalized one-model-fits-all approach. We then implemented both univariate and multivariate individualized transfer learning predictive models, which harness the available population-level data but allow individual variability in their predictions. Finally, we compared Pearson correlation coefficients and mean absolute error between the individualized transfer learning and generalized one-model-fits-all models. RESULTS Tumor cell density significantly correlated with relative CBV (r = 0.33, P < .001), and T1-weighted postcontrast (r = 0.36, P < .001) on univariate analysis after correcting for multiple comparisons. With single-variable modeling (using relative CBV), transfer learning increased predictive performance (r = 0.53, mean absolute error = 15.19%) compared with one-model-fits-all (r = 0.27, mean absolute error = 17.79%). With multivariate modeling, transfer learning further improved performance (r = 0.88, mean absolute error = 5.66%) compared with one-model-fits-all (r = 0.39, mean absolute error = 16.55%). CONCLUSIONS Transfer learning significantly improves predictive modeling performance for quantifying tumor cell density in glioblastoma.
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Affiliation(s)
- L S Hu
- From the Department of Radiology (L.S.H., J.M.H., J.R.M., T.W., J.L.)
| | - H Yoon
- Arizona State University (H.Y., Y.X., L.W., T.W., J.L.), Tempe, Arizona
| | | | | | - A C Dueck
- Department of Biostatistics (A.C.D.), Mayo Clinic in Arizona, Scottsdale, Arizona
| | | | | | - P Nakaji
- Neurosurgery (K.A.S., P.N., N.S.)
| | - Y Xu
- Arizona State University (H.Y., Y.X., L.W., T.W., J.L.), Tempe, Arizona
| | - L Wang
- Arizona State University (H.Y., Y.X., L.W., T.W., J.L.), Tempe, Arizona
| | | | - A J Hawkins-Daarud
- Precision Neurotherapeutics Lab (A.J.H.-D., K.W.S., P.R.J, B.R.B., K.R.S.)
| | - K W Singleton
- Precision Neurotherapeutics Lab (A.J.H.-D., K.W.S., P.R.J, B.R.B., K.R.S.)
| | - P R Jackson
- Precision Neurotherapeutics Lab (A.J.H.-D., K.W.S., P.R.J, B.R.B., K.R.S.)
| | - B J Anderies
- Department of Neurosurgery (B.J.A., B.R.B., R.S.Z., M.G.S., P.E.K., C.K., K.R.S.)
| | - B R Bendok
- Precision Neurotherapeutics Lab (A.J.H.-D., K.W.S., P.R.J, B.R.B., K.R.S.).,Department of Neurosurgery (B.J.A., B.R.B., R.S.Z., M.G.S., P.E.K., C.K., K.R.S.)
| | - R S Zimmerman
- Department of Neurosurgery (B.J.A., B.R.B., R.S.Z., M.G.S., P.E.K., C.K., K.R.S.)
| | - C Quarles
- Neuroimaging Research (C.Q.), Barrow Neurological Institute, Phoenix, Arizona
| | | | - M M Mrugala
- Department of Neuro-Oncology (A.B.P.-U., M.M.M., A.S.)
| | - A Sharma
- Department of Neuro-Oncology (A.B.P.-U., M.M.M., A.S.)
| | - J M Hoxworth
- From the Department of Radiology (L.S.H., J.M.H., J.R.M., T.W., J.L.)
| | - M G Sattur
- Department of Neurosurgery (B.J.A., B.R.B., R.S.Z., M.G.S., P.E.K., C.K., K.R.S.)
| | - N Sanai
- Neurosurgery (K.A.S., P.N., N.S.)
| | - P E Koulemberis
- Department of Neurosurgery (B.J.A., B.R.B., R.S.Z., M.G.S., P.E.K., C.K., K.R.S.)
| | - C Krishna
- Department of Neurosurgery (B.J.A., B.R.B., R.S.Z., M.G.S., P.E.K., C.K., K.R.S.)
| | - J R Mitchell
- From the Department of Radiology (L.S.H., J.M.H., J.R.M., T.W., J.L.).,H. Lee Moffitt Cancer Center and Research Institute (J.R.M.), Tampa, Florida
| | - T Wu
- From the Department of Radiology (L.S.H., J.M.H., J.R.M., T.W., J.L.).,Arizona State University (H.Y., Y.X., L.W., T.W., J.L.), Tempe, Arizona
| | - N L Tran
- Department of Cancer Biology (N.L.T.), Mayo Clinic in Arizona, Phoenix, Arizona
| | - K R Swanson
- Precision Neurotherapeutics Lab (A.J.H.-D., K.W.S., P.R.J, B.R.B., K.R.S.).,Department of Neurosurgery (B.J.A., B.R.B., R.S.Z., M.G.S., P.E.K., C.K., K.R.S.)
| | - J Li
- From the Department of Radiology (L.S.H., J.M.H., J.R.M., T.W., J.L.).,Arizona State University (H.Y., Y.X., L.W., T.W., J.L.), Tempe, Arizona
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Smith CJ, Fairres MJ, Myers CS, Chapple KM, Klysik M, Karis JP, Youssef E, Smith KA. Long-term outcome data from 121 patients treated with Gamma Knife stereotactic radiosurgery as salvage therapy for focally recurrent high-grade gliomas. J Radiosurg SBRT 2019; 6:199-207. [PMID: 31998540 PMCID: PMC6774481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Accepted: 06/09/2019] [Indexed: 06/10/2023]
Abstract
INTRODUCTION We examined patient outcomes after Gamma Knife stereotactic radiosurgery (GKSRS) salvage therapy for recurrent high-grade gliomas (HGGs) to determine whether tumor grade or lesion size affected overall survival (OS) and progression-free survival (PFS). METHODS This single-center retrospective study assessed radiographic response and clinical outcomes following GKSRS salvage treatment of recurrent malignant gliomas (January 2005-March 2014). RESULTS A total of 121 patients (67 female) with 132 tumors were treated. Median (range) PFS was 4.7 (3.9-5.4) months for the cohort, 6.8 (4.6-8.9) months for initial grade 2 tumors, 4.2 (1.9-6.5) months for initial grade 3 tumors, and 4.3 (3.7-4.9) months for initial grade 4 tumors. Patients with small lesions (≤6.7 cm3; n = 53) had significantly longer median (range) PFS (6.8 [4.8-8.8], P=0.02). CONCLUSIONS GKSRS offers meaningful salvage therapy with minimal morbidity in appropriately selected patients with focally recurrent HGGs.
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Affiliation(s)
- Cody J. Smith
- College of Medicine, University of Arizona, Tucson, AZ, USA
| | | | - Charlotte S. Myers
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ, USA
| | - Kristina M. Chapple
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ, USA
| | - Michal Klysik
- Department of Neuroradiology, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ, USA
| | - John P. Karis
- Department of Neuroradiology, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ, USA
| | - Emad Youssef
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ, USA
| | - Kris A. Smith
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ, USA
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Przybylowski CJ, Cole TS, Baranoski JF, Little AS, Smith KA, Shetter AG. Radiosurgery for multiple sclerosis-related trigeminal neuralgia: retrospective review of long-term outcomes. J Neurosurg 2018; 131:1-8. [PMID: 30544359 DOI: 10.3171/2018.5.jns173194] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Accepted: 05/31/2018] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The objective of this study was to assess long-term outcomes of facial pain and numbness after radiosurgery for multiple sclerosis (MS)-related trigeminal neuralgia (MS-TN). METHODS The authors conducted a retrospective review of their Gamma Knife radiosurgeries (GKRSs) to identify all patients treated for MS-TN (1998-2014) with at least 3 years of follow-up. Treatment and clinical data were obtained via chart review and mailed or telephone surveys. Pain control was defined as a facial pain score of I-IIIb on the Barrow Neurological Institute (BNI) Facial Pain Intensity Scale. Kaplan-Meier analysis was performed to determine the rates of pain control after index and first salvage GKRS procedures. Patients could have had more than 1 salvage procedure. Pain control rates were based on the number of patients at risk during follow-up. RESULTS Of the 50 living patients who underwent GKRS, 42 responded to surveys (31 women [74%], median age 59 years, range 32-76 years). During the initial GKRS, the trigeminal nerve root entry zone was targeted with a single isocenter, using a 4-mm collimator with the 90% isodose line completely covering the trigeminal nerve and the 50% isodose line abutting the surface of the brainstem. The median maximum radiation dose was 85 Gy (range 50-85 Gy). The median follow-up period was 78 months (range 36-226 months). The rate of pain control after the index GKRS (n = 42) was 62%, 29%, 22%, and 13% at 1, 3, 5, and 7 years, respectively. Twenty-eight patients (67%) underwent salvage treatment, including 25 (60%) whose first salvage treatment was GKRS. The rate of pain control after the first salvage GKRS (n = 25) was 84%, 50%, 44%, and 17% at 1, 3, 5, and 7 years, respectively. The rate of pain control after the index GKRS with or without 1 salvage GKRS (n = 33) was 92%, 72%, 52%, 46%, and 17% at 1, 3, 5, 7, and 10 years, respectively. At last follow-up, 9 (21%) of the 42 patients had BNI grade I facial pain, 35 (83%) had achieved pain control, and 4 (10%) had BNI grade IV facial numbness (very bothersome in daily life). CONCLUSIONS Index GKRS offers good short-term pain control for MS-TN, but long-term pain control is uncommon. If the index GKRS fails, salvage GKRS appears to offer beneficial pain control with low rates of bothersome facial numbness.
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35
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Hu L, Gaw N, Yoon H, Eschbacher J, C. Baxter L, A. Smith K, Nakaji P, P. Karis J, Whitmire P, Hawkins-Daarud A, Singleton K, Jackson P, Christine Massey S, Bendok B, Mitchell J, Wu T, Tran N, Rubin J, Swanson K, Li J. NIMG-12. RADIOGENOMICS ON VENUS AND MARS: IMPACT OF SEX-DIFFERENCES ON MRI AND GENETIC CORRELATIONS IN GLIOBLASTOMA. Neuro Oncol 2018. [DOI: 10.1093/neuonc/noy148.739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- Leland Hu
- Radiology, Mayo Clinic, Phoenix, AZ, USA
| | - Nathan Gaw
- Arizona State University, Tempe, AZ, USA
| | | | | | | | - Kris A. Smith
- Neurosurgery, Barrow Neurological Institute, Phoenix, AZ, USA
| | - Peter Nakaji
- Neurosurgery, Barrow Neurological Institute, Phoenix, AZ, USA
| | - John P. Karis
- Radiology, Barrow Neurological Institute, Phoenix, AZ, USA
| | - Paula Whitmire
- Mathematical NeuroOncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic Arizona, Phoenix, AZ, Phoenix, AZ, USA
| | | | - Kyle Singleton
- Mathematical NeuroOncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic Arizona, Phoenix, AZ, Phoenix, AZ, USA
| | - Pamela Jackson
- Mathematical Neuro-Oncology Lab, Precision Neurotherapeutics Innovation Program, Neurological Surgery, Mayo Clinic, Phoenix, AZ, USA
| | - Susan Christine Massey
- Mathematical Neuro-Oncology Lab, Precision Neurotherapeutics Innovation Program, Neurological Surgery, Mayo Clinic, Phoenix, AZ, USA
| | | | | | - Teresa Wu
- Arizona State University, Tempe, AZ, USA
| | - Nhan Tran
- Departments of Cancer Biology and Neurosurgery, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Joshua Rubin
- Washington University School of Medicine, St. Louis, MO, USA
| | - Kristin Swanson
- Mathematical Neuro-Oncology Lab, Neurological Surgery, Mayo Clinic, Phoenix, AZ, USA
| | - Jing Li
- Arizona State University, Tempe, AZ, USA
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Bohl MA, Xu DS, Cavallo C, Paisan GM, Smith KA, Nakaji P. The Barrow Innovation Center Case Series: A Novel 3-Dimensional-Printed Retractor for Use with Electromagnetic Neuronavigation Systems. World Neurosurg 2018; 116:e1075-e1078. [PMID: 29864557 DOI: 10.1016/j.wneu.2018.05.167] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Revised: 05/21/2018] [Accepted: 05/23/2018] [Indexed: 01/17/2023]
Abstract
OBJECTIVE The Barrow Innovation Center consists of an educational program that promotes interdisciplinary collaboration among neurosurgery, legal, and engineering professionals to foster the development of new medical devices. This report describes a common issue faced during the placement of ventricular shunts for the treatment of hydrocephalus and the solution to this problem that was developed through the Barrow Innovation Center. METHODS Neurosurgery residents involved in the Barrow Innovation Center presented the problem of ferromagnetic retractors interfering with pinless image-guidance systems at a monthly meeting. Potential solutions were openly discussed by an interdisciplinary committee of neurosurgeons, patent lawyers, and biomedical engineers. The committee decided to pursue development of a novel self-retaining retractor made of nonferromagnetic material as a solution to the problem. RESULTS Each retractor design was tested in the cadaver laboratory for size and functionality. A final design was chosen and used in a surgical case requiring ventriculoperitoneal shunt placement. The new retractor successfully retracted the scalp without interfering with the electromagnetic image-guidance system. CONCLUSIONS Through the interdisciplinary Barrow Innovation Center program, a newly designed, 3-dimensional-printed skin and soft-tissue retractor was created, along with an innovative universal shunt retainer. Through this integrated program dedicated to surgical innovation (i.e., the Barrow Innovation Center), the process of developing and implementing new technology at our institution has been streamlined, creating a culture of innovation within the neurosurgery training program.
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Affiliation(s)
- Michael A Bohl
- Department of Neurosurgery Barrow Neurological Institute St. Joseph's Hospital and Medical Center Phoenix, Arizona, USA
| | - David S Xu
- Department of Neurosurgery Barrow Neurological Institute St. Joseph's Hospital and Medical Center Phoenix, Arizona, USA
| | - Claudio Cavallo
- Department of Neurosurgery Barrow Neurological Institute St. Joseph's Hospital and Medical Center Phoenix, Arizona, USA
| | - Gabriella M Paisan
- Department of Neurosurgery University of Virginia Charlottesville, Virginia, USA
| | - Kris A Smith
- Department of Neurosurgery Barrow Neurological Institute St. Joseph's Hospital and Medical Center Phoenix, Arizona, USA
| | - Peter Nakaji
- Department of Neurosurgery Barrow Neurological Institute St. Joseph's Hospital and Medical Center Phoenix, Arizona, USA.
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Xu DS, Chen T, Hlubek RJ, Bristol RE, Smith KA, Ponce FA, Kerrigan JF, Nakaji P. Magnetic Resonance Imaging-Guided Laser Interstitial Thermal Therapy for the Treatment of Hypothalamic Hamartomas: A Retrospective Review. Neurosurgery 2018; 83:1183-1192. [DOI: 10.1093/neuros/nyx604] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Accepted: 11/27/2017] [Indexed: 11/13/2022] Open
Affiliation(s)
- David S Xu
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Tsinsue Chen
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Randall J Hlubek
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Ruth E Bristol
- Department of Neurosurgery, Barrow Neurological Institute, Phoenix Children's Hospital, Phoenix, Arizona
| | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - Francisco A Ponce
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
| | - John F Kerrigan
- Department of Pediatric Neurology, Barrow Neurological Institute, Phoenix Children's Hospital, Phoenix, Arizona
| | - Peter Nakaji
- Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
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Smith CJ, Myers CS, Chapple KM, Smith KA. Long-Term Follow-up of 25 Cases of Biopsy-Proven Radiation Necrosis or Post-Radiation Treatment Effect Treated With Magnetic Resonance-Guided Laser Interstitial Thermal Therapy. Neurosurgery 2017; 79 Suppl 1:S59-S72. [PMID: 27861326 DOI: 10.1227/neu.0000000000001438] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Magnetic resonance-guided laser-induced thermal therapy (MRgLITT) is a minimally invasive surgical treatment for progressive neoplasms and post-radiation treatment effect (PRTE). OBJECTIVE To evaluate the radiographic response and efficacy of MRgLITT for biopsy-confirmed PRTE and the quality-of-life outcomes of patients following MRgLITT. METHODS We conducted a single-center retrospective study of radiographic responses and clinical outcomes of 25 patients with previously treated primary or secondary brain neoplasms (World Health Organization grades 4 [n = 8], 3 [n = 5], 2 [n = 5]) and metastatic brain tumors (n = 7). MRgLITT was applied directly following stereotactic needle biopsy confirming PRTE without any evidence of tumor presence. RESULTS Mean overall survival times (months) for grades 4 and 3 and for metastatic brain tumors were 39.2 (standard error [SE], 7.6; 95% confidence interval [CI], 24.3-54.1), 29.1 (SE, 7.7; 95% CI, 14.0-44.2), and 55.9 (SE, 10.0; 95% CI, 36.3-75.4), respectively. Mean progression-free survival times after MRgLITT were 9.1 (SE, 3.6; 95% CI, 2.1-16.1), 8.5 (SE, 2.4; 95% CI, 3.9-13.2), and 11.4 (SE, 3.9; 95% CI, 3.8-19.0), respectively. Mean survival times after MRgLITT were 13.1 (SE, 2.3; 95% CI, 8.5-17.6), 12.2 (SE, 4.0; 95% CI, 4.4-20.0), and 19.2 (SE, 5.3; 95% CI, 8.9-29.6), respectively. The SF-36 indicated significant overall effects on mental health (P = .029) and vitality (P = .005). CONCLUSION MRgLITT may be a viable option for patients with symptomatic advancing PRTE and is less invasive than open craniotomy. Although our results suggest a positive effect for MRgLITT on PRTE, prospective randomized trials with larger numbers of patients are needed to validate the study results. ABBREVIATIONS cRBV, relative cerebral blood volumeHIF1a, hypoxia-inducible factor 1aIMRT, intensity-modulated radiation therapyKPS, Karnofsky Performance StatusLITT, laser-induced thermal therapyMBT, metastatic brain tumorMRgLITT, magnetic resonance-guided laser-induced thermal therapyPRTE, post-radiation treatment effectSRS, stereotactic radiosurgeryVEGF, vascular endothelial growth factorWBXRT, whole brain radiation therapy.
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Affiliation(s)
- Cody J Smith
- *School of Medicine, University of Arizona, Tucson, Arizona; ‡Department of Neurosurgery, St. Joseph's Hospital and Medical Center, Barrow Neurological Institute, Phoenix, Arizona
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Hussey EK, Christianson K, Treiman DM, Smith KA, Steinmetz PN. Single neuron recordings of bilinguals performing in a continuous recognition memory task. PLoS One 2017; 12:e0181850. [PMID: 28832639 PMCID: PMC5568109 DOI: 10.1371/journal.pone.0181850] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Accepted: 07/07/2017] [Indexed: 01/09/2023] Open
Abstract
We report the results of a bilingual continuous recognition memory task during which single- and multi-neuron activity was recorded in human subjects with intracranial microwire implants. Subjects (n = 5) were right-handed Spanish-English bilinguals who were undergoing evaluation prior to surgery for severe epilepsy. Subjects were presented with Spanish and English words and the task was to determine whether any given word had been seen earlier in the testing session, irrespective of the language in which it had appeared. Recordings in the left and right hippocampus revealed notable laterality, whereby both Spanish and English items that had been seen previously in the other language (switch trials) triggered increased neural firing in the left hippocampus. Items that had been seen previously in the same language (repeat trials) triggered increased neural firings in the right hippocampus. These results are consistent with theories that propose roles of both the left- and right-hemisphere in real-time linguistic processing. Importantly, this experiment presents the first instance of intracranial recordings in bilinguals performing a task with switching demands.
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Affiliation(s)
- Erika K. Hussey
- Cognitive Science Team, U.S. Army Natick Soldier Research, Development and Engineering Center, Natick, Massachusetts, United States of America
- Center for Applied Brain and Cognitive Sciences, Medford, Massachusetts, United States of America
- Beckman Institute for Advanced Science and Technology, University of Illinois, Urbana, Illinois, United States of America
| | - Kiel Christianson
- Beckman Institute for Advanced Science and Technology, University of Illinois, Urbana, Illinois, United States of America
- Department of Educational Psychology, University of Illinois, Champaign, Illinois, United States of America
| | - David M. Treiman
- Department of Neurology, Barrow Neurological Institute, Phoenix, Arizona, United States of America
| | - Kris A. Smith
- Department of Neurosurgery, Barrow Neurological Institute, Phoenix, Arizona, United States of America
| | - Peter N. Steinmetz
- Department of Neurology, Barrow Neurological Institute, Phoenix, Arizona, United States of America
- Department of Neurosurgery, Barrow Neurological Institute, Phoenix, Arizona, United States of America
- Nakamoto Brain Research Institute, Tempe, Arizona, United States of America
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Xu DS, Hlubek RJ, Mulholland CB, Knievel KL, Smith KA, Nakaji P. Use of Intracranial Pressure Monitoring Frequently Refutes Diagnosis of Idiopathic Intracranial Hypertension. World Neurosurg 2017; 104:167-170. [DOI: 10.1016/j.wneu.2017.04.080] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2016] [Revised: 04/11/2017] [Accepted: 04/12/2017] [Indexed: 11/28/2022]
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Dardis C, Yeo J, Milton K, Ashby LS, Smith KA, Mehta S, Youssef E, Eschbacher J, Tucker K, Dawes L, Lambie N, Algar E, Hovey E. Atypical Teratoid Rhabdoid Tumor: Two Case Reports and an Analysis of Adult Cases with Implications for Pathophysiology and Treatment. Front Neurol 2017; 8:247. [PMID: 28676785 PMCID: PMC5476998 DOI: 10.3389/fneur.2017.00247] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Accepted: 05/18/2017] [Indexed: 12/20/2022] Open
Abstract
We present the first quantitative analysis of atypical teratoid rhabdoid tumors (ATRT) in adults, including two patients from our own institutions. These are of interest as one occurred during pregnancy and one is a long-term survivor. Our review of pathological findings of 50 reported cases of adult ATRT leads us to propose a solely ectodermal origin for the tumor and that epithelial–mesenchymal transition (EMT) is a defining feature. Thus, the term ATRT may be misleading. Our review of clinical findings shows that ATRT tends to originate in mid-line structures adjacent to the CSF, leading to a high rate of leptomeningeal dissemination. Thus, we hypothesize that residual undifferentiated ectoderm in the circumventricular organs, particularly the pituitary and pineal glands, is the most common origin for these tumors. We note that if growth is not arrested soon after diagnosis, or after the first relapse/progression, death is almost universal. While typically rapidly fatal (as in our first case), long-term remission is possible (as in our second). Significant predictors of prognosis were the extent of resection and the use of chemotherapy. Glial differentiation (GFAP staining) was strongly associated with leptomeningeal metastases (chi-squared p = 0.02) and both predicted markedly worse outcomes. Clinical trials including adults are rare. ATRT is primarily a disease of infancy and radiotherapy is generally avoided in those aged less than 3 years old. Treatment options in adults differ from infants in that cranio-spinal irradiation is a viable adjunct to systemic chemotherapy in the adult population. Given the grave prognosis, this combined approach appears reasonable. As effective chemotherapy is likely to cause myelosuppression, we recommend that stem-cell rescue be available locally.
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Affiliation(s)
- Christopher Dardis
- Department of Neurology, Barrow Neurological Institute, Phoenix, AZ, Unites States
| | - Jared Yeo
- University of New South Wales, Sydney, NSW, Australia
| | - Kelly Milton
- Department of Neurology, Barrow Neurological Institute, Phoenix, AZ, Unites States
| | - Lynn S Ashby
- Department of Neurology, Barrow Neurological Institute, Phoenix, AZ, Unites States
| | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Shwetal Mehta
- Laboratory of Glial Tumor Biology, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Emad Youssef
- Department of Radiation Oncology, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Jenny Eschbacher
- Department of Pathology, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Kathy Tucker
- Hereditary Cancer Clinic, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Laughlin Dawes
- Department of Diagnostic Radiology, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Neil Lambie
- Department of Anatomical Pathology, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Elizabeth Algar
- Hudson Institute of Medical Research, Clayton, VIC, Australia
| | - Elizabeth Hovey
- University of New South Wales, Sydney, NSW, Australia.,Department of Medical Oncology, Nelune Comprehensive Cancer Center, Prince of Wales Hospital, Randwick, NSW, Australia
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Hawkins-Daarud A, DeGirolamo L, Jacobs J, Clark-Swanson K, Eschbacher JM, Smith KA, Nakaji P, Baxter LC, Karis JP, Wu T, Mitchell JR, Li J, Hu L, Swanson KR. Abstract A08: Histologic evidence for a bio-mathematical model of glioblastoma invasion. Cancer Res 2017. [DOI: 10.1158/1538-7445.epso16-a08] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Purpose: Investigate the utility of patient-specific spatial predictions of tumor cell density from a bio-mathematical model.
Introduction: Glioblastomas (GBMs) are the most malignant of all primary brain tumors. While it is known there is always a non-detectable portion of the tumor, current techniques of monitoring GBM progression, imaging and initial histological assessment, are not able to reliably estimate the tumor invasion past the enhancing region on T2-Weighted (T2W) imaging. Over the last two decades, a large effort has been made to create a simple patient-specific mathematical model of gliomas. The resulting model, referred to as the Proliferation-Invasion (PI) model, is based on two key parameters, the net growth rate, ρ, and the dispersal coefficient, D. In this model, the ratio of D/ρ is related to degree of invasion and the product D*ρ, is related to the speed of growth.
The intuitive understanding provided by this model has been able to provide patient-specific understanding of disease kinetics enabling prediction of outcomes following surgical resection, radiation and the development of a prognostic response metric. Previous literature utilizing this model has been based on the assumption that what is seen on the pretreatment T1-Weighted contrast-enhanced (T1Gd) and T2W, images correspond to an 80% and 16% tumor cell density threshold respectively. This assumption allows for an estimate of D/ρ from a single time point of imaging. While these values were based on extensive experience, for ethical and technical reasons, they have never been rigorously investigated histologically. Recent technological advances have made it possible for surgeons to use an MRI to guide the acquisition of tissue making it possible to know with a good degree of accuracy where on the MR image the histological specimen comes from.
Methods: Model Calibration : To estimate D/ρ for each patient, we assume abnormalities on the T1Gd and T2W images correspond to an 80% and 16% tumor cell density threshold respectively. We then utilize a Bayesian calibration approach based on adaptive grid refinement while holding the velocity constant to find the most likely value of D/ρ to match the observed radial measurements. Three-Dimensional Density Maps : Given a gray/white segmentation and an estimate for D/ρ, we can build a tumor cell density prediction in the patient's anatomy using the Eikonal equations and the modified Fast Marching Method (FMM) algorithm presented by Konukoglu et al. Patient Cohort : Eighteen patients were recruited with clinically suspected GBM undergoing preoperative stereotactic MRI for surgical resection with IRB approval Barrow Neurological Institute and Mayo Clinic in Arizona. Surgical Biopsy : Pre-operative conventional MRI, including T1Gd and T2W, was utilized to guide stereotactic biopsies. An average of 5–6 tissue specimens were acquired from each tumor by using stereotactic surgical localization, following the smallest possible diameter craniotomies to minimize brain shift. Histological Analysis : 4 μm tissue sections were stained with hematoxylin and eosin (H&E) for neuropathology review. H&E slides were reviewed by a neuropathologist. The percent tumor nuclei in the field was estimated.
Results and Conclusion: Our analysis showed that the intuitive ordering of diffuse to nodular tumor profiles from the PI model is consistent with the histologic data. Further, utilizing the histologic data, limitations to a universal threshold cutoff of the T2/FLAIR region are specified and a better threshold cutoff value is suggested. We hope that this paper will lead to more studies of this kind resulting in more accurate ways to predict the spatial distribution of GBM tumor cells from medical imaging. Such advances could revolutionize surgical procedures and radiation therapy and may enable additional insights into tumor kinetic differences meaningful for treatment.
Citation Format: Andrea Hawkins-Daarud, Lauren DeGirolamo, Joshua Jacobs, Kamala Clark-Swanson, Jennifer M. Eschbacher, Kris A. Smith, Peter Nakaji, Leslie C. Baxter, John P. Karis, Teresa Wu, J. Ross Mitchell, Jing Li, Leland Hu, Kristin R. Swanson. Histologic evidence for a bio-mathematical model of glioblastoma invasion. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr A08.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Teresa Wu
- 4Arizona State University, Tempe, AZ
| | | | - Jing Li
- 4Arizona State University, Tempe, AZ
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Harvey LFB, Smith KA, Curlin H. Improving Operative Room Costs and Efficiency Through Review of Surgeon Preference Cards. J Minim Invasive Gynecol 2016. [DOI: 10.1016/j.jmig.2016.08.097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Ashby LS, Smith KA, Stea B. Gliadel wafer implantation combined with standard radiotherapy and concurrent followed by adjuvant temozolomide for treatment of newly diagnosed high-grade glioma: a systematic literature review. World J Surg Oncol 2016; 14:225. [PMID: 27557526 PMCID: PMC4997737 DOI: 10.1186/s12957-016-0975-5] [Citation(s) in RCA: 111] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2016] [Accepted: 08/09/2016] [Indexed: 12/04/2022] Open
Abstract
Since 2003, only two chemotherapeutic agents, evaluated in phase III trials, have been approved by the US Food and Drug Administration for treatment of newly diagnosed high-grade glioma (HGG): Gliadel wafers (intracranially implanted local chemotherapy) and temozolomide (TMZ) (systemic chemotherapy). Neither agent is curative, but each has been shown to improve median overall survival (OS) compared to radiotherapy (RT) alone. To date, no phase III trial has tested these agents when used in sequential combination; however, a number of smaller trials have reported favorable results. We performed a systematic literature review to evaluate the combination of Gliadel wafers with standard RT (60 Gy) plus concurrent and adjuvant TMZ (RT/TMZ) for newly diagnosed HGG. A literature search was conducted for the period of January 1995 to September 2015. Data were extracted and categorized, and means and ranges were determined. A total of 11 publications met criteria, three prospective trials and eight retrospective studies, representing 411 patients who received Gliadel plus standard RT/TMZ. Patients were similar in age, gender, and performance status. The weighted mean of median OS was 18.2 months (ten trials, n = 379, range 12.7 to 21.3 months), and the weighted mean of median progression-free survival was 9.7 months (seven trials, n = 287, range 7 to 12.9 months). The most commonly reported grade 3 and 4 adverse events were myelosuppression (10.22 %), neurologic deficit (7.8 %), and healing abnormalities (4.3 %). Adverse events reflected the distinct independent safety profiles of Gliadel wafers and RT/TMZ, with little evidence of enhanced toxicity from their use in sequential combination. In the 11 identified trials, an increased benefit from sequentially combining Gliadel wafers with RT/TMZ was strongly suggested. Median OS tended to be improved by 3 to 4 months beyond that observed for Gliadel wafers or TMZ when used alone in the respective phase III trials. Larger prospective trials of Gliadel plus RT/TMZ are warranted.
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Affiliation(s)
- Lynn S Ashby
- Department of Neurology, Barrow Neurological Institute, 500 W. Thomas Rd, Suite 300, Phoenix, AZ, 85013, USA.
| | - Kris A Smith
- Department of Neurosurgery, Barrow Neurological Institute, Phoenix, AZ, 85013, USA
| | - Baldassarre Stea
- Department of Radiation Oncology, Arizona Cancer Center, University of Arizona, Tucson, AZ, 85724, USA
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Hu LS, Ning S, Eschbacher JM, Baxter LC, Gaw N, Ranjbar S, Plasencia J, Dueck AC, Peng S, Smith KA, Nakaji P, Karis JP, Quarles CC, Wu T, Loftus JC, Jenkins RB, Sicotte H, Kollmeyer TM, O'Neill BP, Elmquist W, Hoxworth JM, Frakes D, Sarkaria J, Swanson KR, Tran NL, Li J, Mitchell JR. Radiogenomics to characterize regional genetic heterogeneity in glioblastoma. Neuro Oncol 2016; 19:128-137. [PMID: 27502248 DOI: 10.1093/neuonc/now135] [Citation(s) in RCA: 137] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Glioblastoma (GBM) exhibits profound intratumoral genetic heterogeneity. Each tumor comprises multiple genetically distinct clonal populations with different therapeutic sensitivities. This has implications for targeted therapy and genetically informed paradigms. Contrast-enhanced (CE)-MRI and conventional sampling techniques have failed to resolve this heterogeneity, particularly for nonenhancing tumor populations. This study explores the feasibility of using multiparametric MRI and texture analysis to characterize regional genetic heterogeneity throughout MRI-enhancing and nonenhancing tumor segments. METHODS We collected multiple image-guided biopsies from primary GBM patients throughout regions of enhancement (ENH) and nonenhancing parenchyma (so called brain-around-tumor, [BAT]). For each biopsy, we analyzed DNA copy number variants for core GBM driver genes reported by The Cancer Genome Atlas. We co-registered biopsy locations with MRI and texture maps to correlate regional genetic status with spatially matched imaging measurements. We also built multivariate predictive decision-tree models for each GBM driver gene and validated accuracies using leave-one-out-cross-validation (LOOCV). RESULTS We collected 48 biopsies (13 tumors) and identified significant imaging correlations (univariate analysis) for 6 driver genes: EGFR, PDGFRA, PTEN, CDKN2A, RB1, and TP53. Predictive model accuracies (on LOOCV) varied by driver gene of interest. Highest accuracies were observed for PDGFRA (77.1%), EGFR (75%), CDKN2A (87.5%), and RB1 (87.5%), while lowest accuracy was observed in TP53 (37.5%). Models for 4 driver genes (EGFR, RB1, CDKN2A, and PTEN) showed higher accuracy in BAT samples (n = 16) compared with those from ENH segments (n = 32). CONCLUSION MRI and texture analysis can help characterize regional genetic heterogeneity, which offers potential diagnostic value under the paradigm of individualized oncology.
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Affiliation(s)
- Leland S Hu
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Shuluo Ning
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Jennifer M Eschbacher
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Leslie C Baxter
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Nathan Gaw
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Sara Ranjbar
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Jonathan Plasencia
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Amylou C Dueck
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Sen Peng
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Kris A Smith
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Peter Nakaji
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - John P Karis
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - C Chad Quarles
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Teresa Wu
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Joseph C Loftus
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Robert B Jenkins
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Hugues Sicotte
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Thomas M Kollmeyer
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Brian P O'Neill
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - William Elmquist
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Joseph M Hoxworth
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - David Frakes
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Jann Sarkaria
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Kristin R Swanson
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Nhan L Tran
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - Jing Li
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
| | - J Ross Mitchell
- Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.)
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Pieniazek J, Smith KA, Williams MP, Manangi MK, Vazquez-Anon M, Solbak A, Miller M, Lee JT. Evaluation of increasing levels of a microbial phytase in phosphorus deficient broiler diets via live broiler performance, tibia bone ash, apparent metabolizable energy, and amino acid digestibility. Poult Sci 2016; 96:370-382. [PMID: 27444440 DOI: 10.3382/ps/pew225] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 02/08/2016] [Accepted: 05/09/2016] [Indexed: 11/20/2022] Open
Abstract
The objective was to investigate increasing concentrations of an evolved microbial phytase on male broiler performance, tibia bone ash, AME, and amino acid digestibility when fed diets deficient in available phosphorus (aP). Experiment 1 evaluated the effects of phytase during a 21 d battery cage study and Experiment 2 was a 42 d grow-out. Experiment 1 included six treatments; negative control (NC) with an aP level of 0.23% (starter) and 0.19% (grower), two positive controls (PC) consisting of an additional 0.12% and 0.22% aP (PC 1 and PC 2), and the NC supplemented with three levels of phytase (250, 500, and 2,000 U/kg). The NC diet reduced (P < 0.05) FC, BW, and bone ash. Phytase increased (P < 0.05) BW with 2,000 U/kg phytase yielding similar results to the PC2, and improved FCR and increased bone ash was observed at all phytase levels. Amino acid digestibility coefficients were increased (P < 0.05) with phytase at 250 U/kg. Phytase at all rates increased (P < 0.05) AME to levels similar level as PC diets. Linear regression analysis indicated average P equivalency values for BW and bone ash of 0.137, 0.147, and 0.226 for phytase inclusion of 250, 500, and 2000 U/kg, respectively. Experiment 2 included a PC consisting of 0.45%, 0.41%, and 0.38% aP for the starter, grower, and finisher, respectively; NC with reduced aP of 0.17%; and phytase at 500 and 2,000 U/kg. Phytase increased BW (P < 0.05) compared to the NC as 2,000 U/kg phytase resulted in further BW increases compared to the PC (starter and grower). Phytase improved FCR to levels comparable to the PC, with supplementation at 2,000 U/kg resulting in improvements beyond the PC in the starter phase. Amino acid digestibility coefficients were increased with phytase at 2,000 U/kg to levels comparable to that of the PC. These data confirm that the inclusion of phytase improves broiler performance and bone mineralization in aP reduced diets and levels beyond the traditional 500 U/kg can result in further improvements.
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Affiliation(s)
- J Pieniazek
- Poultry Science Department, Texas A&M AgriLife Research and Extension, Texas A&M System, College Station, TX, USA
| | - K A Smith
- Poultry Science Department, Texas A&M AgriLife Research and Extension, Texas A&M System, College Station, TX, USA
| | - M P Williams
- Poultry Science Department, Texas A&M AgriLife Research and Extension, Texas A&M System, College Station, TX, USA
| | | | | | - A Solbak
- Verenium Corporation, San Diego, CA
| | - M Miller
- Verenium Corporation, San Diego, CA
| | - J T Lee
- Poultry Science Department, Texas A&M AgriLife Research and Extension, Texas A&M System, College Station, TX, USA
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Levitt MR, Hlubek RJ, Moon K, Kalani MYS, Nakaji P, Smith KA, Little AS, Knievel K, Chan JW, McDougall CG, Albuquerque FC. Incidence and predictors of dural venous sinus pressure gradient in idiopathic intracranial hypertension and non-idiopathic intracranial hypertension headache patients: results from 164 cerebral venograms. J Neurosurg 2016; 126:347-353. [PMID: 26967777 DOI: 10.3171/2015.12.jns152033] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Cerebral venous pressure gradient (CVPG) from dural venous sinus stenosis is implicated in headache syndromes such as idiopathic intracranial hypertension (IIH). The incidence of CVPG in headache patients has not been reported. METHODS The authors reviewed all cerebral venograms with manometry performed for headache between January 2008 and May 2015. Patient demographics, headache etiology, intracranial pressure (ICP) measurements, and radiographic and manometric results were recorded. CVPG was defined as a difference ≥ 8 mm Hg by venographic manometry. RESULTS One hundred sixty-four venograms were performed in 155 patients. There were no procedural complications. Ninety-six procedures (58.5%) were for patients with IIH. The overall incidence of CVPG was 25.6% (42 of 164 procedures): 35.4% (34 of 96 procedures) in IIH patients and 11.8% (8 of 68 procedures) in non-IIH patients. Sixty procedures (36.6%) were performed in patients with preexisting shunts. Seventy-seven patients (49.7%) had procedures preceded by an ICP measurement within 4 weeks of venography, and in 66 (85.7%) of these patients, the ICP had been found to be elevated. CVPG was seen in 8.3% (n = 5) of the procedures in the 60 patients with a preexisting shunt and in 0% (n = 0) of the 11 procedures in the 77 patients with normal ICP (p < 0.001 for both). Noninvasive imaging (MR venography, CT venography) was assessed prior to venography in 112 (68.3%) of 164 cases, and dural venous sinus abnormalities were demonstrated in 73 (65.2%) of these cases; there was a trend toward CVPG (p = 0.07). Multivariate analysis demonstrated an increased likelihood of CVPG in patients with IIH (OR 4.97, 95% CI 1.71-14.47) and a decreased likelihood in patients with a preexisting shunt (OR 0.09, 95% CI 0.02-0.44). CONCLUSIONS CVPG is uncommon in IIH patients, rare in those with preexisting shunts, and absent in those with normal ICP.
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Affiliation(s)
- Michael R Levitt
- Departments of 1 Neurological Surgery.,Radiology, and.,Mechanical Engineering, University of Washington, Seattle, Washington; and
| | | | | | | | | | | | | | | | - Jane W Chan
- Neuro-Ophthalmology, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona
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Abstract
OBJECTIVE The purpose of this pilot economic evaluation was to assess the cost-effectiveness of the endoscopic polypectomy in the clinic (EPIC) procedure compared to formal endoscopic sinus surgery (ESS) for the treatment of select chronic rhinosinusitis (CRS) patients with nasal polyposis. DESIGN Cost-effectiveness analysis using a Markov decision tree model with a 30-year time horizon. The two comparative treatment groups were as follows: (i) EPIC and (ii) ESS. Costs and effects were discounted at a rate of 3.5%. A probabilistic sensitivity analysis was performed. SETTING Economic perspective of the Canadian government third-party payer. PARTICIPANTS CRS patients with nasal polyposis who have predominantly isolated symptoms of nasal obstruction with or without olfactory loss. MAIN OUTCOME MEASURES Incremental cost per quality adjusted life year (QALY). RESULTS Over a time period of 30 years, the reference case demonstrated that the ESS strategy cost a total of $21,345 and produced 13.17 QALYs while the EPIC strategy cost a total of $5591 and produced 12.93 QALYs. The ESS versus EPIC incremental cost-effectiveness ratio was $65,641/QALY. The probability that EPIC is cost-effective compared to ESS at a maximum willingness-to-pay threshold of $30,000 and $50,000/QALY is 66% and 60%, respectively. CONCLUSIONS Outcomes from this study have demonstrated that the EPIC procedure may be a cost-effective treatment strategy for 'select' patients with nasal polyposis. Data from this study were obtained from a small pilot trial, and we feel the results warrant a future randomised controlled trial to strengthen the outcomes.
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Affiliation(s)
- L Rudmik
- Division of Otolaryngology - Head and Neck Surgery, Department of Surgery, University of Calgary, Calgary, AB, Canada.,Institute of Public Health (IPH), University of Calgary, Calgary, AB, Canada
| | - K A Smith
- Division of Otolaryngology - Head and Neck Surgery, Department of Surgery, University of Calgary, Calgary, AB, Canada
| | - S Kilty
- Department of Otolaryngology - Head and Neck Surgery, University of Ottawa, Ottawa, ON, Canada.,Ottawa Hospital Research Institute (OHRI), Ottawa, ON, Canada
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Hu LS, Ning S, Eschbacher JM, Gaw N, Dueck AC, Smith KA, Nakaji P, Plasencia J, Ranjbar S, Price SJ, Tran N, Loftus J, Jenkins R, O’Neill BP, Elmquist W, Baxter LC, Gao F, Frakes D, Karis JP, Zwart C, Swanson KR, Sarkaria J, Wu T, Mitchell JR, Li J. Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma. PLoS One 2015; 10:e0141506. [PMID: 26599106 PMCID: PMC4658019 DOI: 10.1371/journal.pone.0141506] [Citation(s) in RCA: 82] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Accepted: 10/08/2015] [Indexed: 01/14/2023] Open
Abstract
Background Genetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM). Contrast-enhanced MRI (CE-MRI) targets enhancing core (ENH) but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT), despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML) algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM. Methods We recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs <80% tumor nuclei) for corresponding samples. In a training set, we used three texture analysis algorithms and three ML methods to identify MRI-texture features that optimized model accuracy to distinguish tumor content. We confirmed model accuracy in a separate validation set. Results We collected 82 biopsies from 18 GBMs throughout ENH and BAT. The MRI-based model achieved 85% cross-validated accuracy to diagnose high- vs low-tumor in the training set (60 biopsies, 11 patients). The model achieved 81.8% accuracy in the validation set (22 biopsies, 7 patients). Conclusion Multi-parametric MRI and texture analysis can help characterize and visualize GBM’s spatial histologic heterogeneity to identify regional tumor-rich biopsy targets.
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Affiliation(s)
- Leland S. Hu
- Department of Radiology, Mayo Clinic, Phoenix, Arizona, United States of America
- Department of Radiology, Barrow Neurological Institute, Phoenix, Arizona, United States of America
- * E-mail:
| | - Shuluo Ning
- School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
| | - Jennifer M. Eschbacher
- Department of Pathology, Barrow Neurological Institute, Phoenix, Arizona, United States of America
| | - Nathan Gaw
- School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
| | - Amylou C. Dueck
- Department of Biostatistics, Mayo Clinic, Phoenix, Arizona, United States of America
| | - Kris A. Smith
- Department of Neurosurgery, Barrow Neurological Institute, Phoenix, Arizona, United States of America
| | - Peter Nakaji
- Department of Neurosurgery, Barrow Neurological Institute, Phoenix, Arizona, United States of America
| | - Jonathan Plasencia
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
| | - Sara Ranjbar
- Department of Radiology, Mayo Clinic, Phoenix, Arizona, United States of America
| | - Stephen J. Price
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Nhan Tran
- Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona, United States of America
| | - Joseph Loftus
- Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, AZ, United States of America
| | - Robert Jenkins
- Department of Pathology, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Brian P. O’Neill
- Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota, United States of America
| | - William Elmquist
- Department of Pharmacology, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Leslie C. Baxter
- Department of Radiology, Barrow Neurological Institute, Phoenix, Arizona, United States of America
| | - Fei Gao
- School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
| | - David Frakes
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
| | - John P. Karis
- Department of Radiology, Barrow Neurological Institute, Phoenix, Arizona, United States of America
| | - Christine Zwart
- Department of Radiology, Mayo Clinic, Phoenix, Arizona, United States of America
| | - Kristin R. Swanson
- Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona, United States of America
| | - Jann Sarkaria
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Teresa Wu
- Department of Radiology, Mayo Clinic, Phoenix, Arizona, United States of America
- School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
| | - J. Ross Mitchell
- Department of Radiology, Mayo Clinic, Phoenix, Arizona, United States of America
| | - Jing Li
- Department of Radiology, Mayo Clinic, Phoenix, Arizona, United States of America
- School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
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