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Verburg N, Barthel FP, Anderson KJ, Johnson KC, Koopman T, Yaqub MM, Hoekstra OS, Lammertsma AA, Barkhof F, Pouwels PJW, Reijneveld JC, Rozemuller AJM, Beliën JAM, Boellaard R, Taylor MD, Das S, Costello JF, Vandertop WP, Wesseling P, de Witt Hamer PC, Verhaak RGW. Spatial concordance of DNA methylation classification in diffuse glioma. Neuro Oncol 2021; 23:2054-2065. [PMID: 34049406 PMCID: PMC8643482 DOI: 10.1093/neuonc/noab134] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [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] [Indexed: 12/13/2022] Open
Abstract
Background Intratumoral heterogeneity is a hallmark of diffuse gliomas. DNA methylation profiling is an emerging approach in the clinical classification of brain tumors. The goal of this study is to investigate the effects of intratumoral heterogeneity on classification confidence. Methods We used neuronavigation to acquire 133 image-guided and spatially separated stereotactic biopsy samples from 16 adult patients with a diffuse glioma (7 IDH-wildtype and 2 IDH-mutant glioblastoma, 6 diffuse astrocytoma, IDH-mutant and 1 oligodendroglioma, IDH-mutant and 1p19q codeleted), which we characterized using DNA methylation arrays. Samples were obtained from regions with and without abnormalities on contrast-enhanced T1-weighted and fluid-attenuated inversion recovery MRI. Methylation profiles were analyzed to devise a 3-dimensional reconstruction of (epi)genetic heterogeneity. Tumor purity was assessed from clonal methylation sites. Results Molecular aberrations indicated that tumor was found outside imaging abnormalities, underlining the infiltrative nature of this tumor and the limitations of current routine imaging modalities. We demonstrate that tumor purity is highly variable between samples and explains a substantial part of apparent epigenetic spatial heterogeneity. We observed that DNA methylation subtypes are often, but not always, conserved in space taking tumor purity and prediction accuracy into account. Conclusion Our results underscore the infiltrative nature of diffuse gliomas and suggest that DNA methylation subtypes are relatively concordant in this tumor type, although some heterogeneity exists.
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Affiliation(s)
- Niels Verburg
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit, and Brain Tumor Centre, Cancer Center Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands.,Cambridge Brain Tumor Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Hill Rd, Cambridge CB2 0QQ, UK
| | - Floris P Barthel
- The Jackson Laboratory For Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Kevin J Anderson
- The Jackson Laboratory For Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Kevin C Johnson
- The Jackson Laboratory For Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Thomas Koopman
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Maqsood M Yaqub
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Otto S Hoekstra
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Adriaan A Lammertsma
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands.,UCL institutes of Neurology & Healthcare Engineering, Gower St, Bloomsbury, London WC1E 6BT, United Kingdom
| | - Petra J W Pouwels
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Jaap C Reijneveld
- Department of Neurology, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands.,Department of Neurology, Stichting Epilepsie Instellingen Nederland, Heemstede, The Netherlands
| | - Annemieke J M Rozemuller
- Department of Pathology, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Jeroen A M Beliën
- Department of Pathology, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Ronald Boellaard
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Michael D Taylor
- Department of Neurosurgery, The Hospital for Sick Children, 555 University Ave, Toronto, ON M5G 1X8, Canada.,Arthur and Sonia Labatt Brain Tumour Research Centre, Hospital for Sick Kids, Toronto, Ontario Canada
| | - Sunit Das
- Arthur and Sonia Labatt Brain Tumour Research Centre, Hospital for Sick Kids, Toronto, Ontario Canada.,Division of Neurosurgery, Li Ka Shing Knowledge Institute, St. Michael's Hospital, University of Toronto, Toronto, Ontario Canada
| | - Joseph F Costello
- Department of Neurological Surgery, UCSF, 505 Parnassus Ave, San Francisco, CA 94143, USA
| | - W Pieter Vandertop
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit, and Brain Tumor Centre, Cancer Center Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Pieter Wesseling
- Department of Pathology, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands.,Princess Máxima Centre for Paediatric Oncology, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Philip C de Witt Hamer
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit, and Brain Tumor Centre, Cancer Center Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Roel G W Verhaak
- Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit, and Brain Tumor Centre, Cancer Center Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands.,The Jackson Laboratory For Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
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2
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Koopman T, Martens R, Gurney‐Champion OJ, Yaqub M, Lavini C, de Graaf P, Castelijns J, Boellaard R, Marcus JT. Repeatability of IVIM biomarkers from diffusion-weighted MRI in head and neck: Bayesian probability versus neural network. Magn Reson Med 2021; 85:3394-3402. [PMID: 33501657 PMCID: PMC7986193 DOI: 10.1002/mrm.28671] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 12/14/2020] [Accepted: 12/17/2020] [Indexed: 12/16/2022]
Abstract
Purpose The intravoxel incoherent motion (IVIM) model for DWI might provide useful biomarkers for disease management in head and neck cancer. This study compared the repeatability of three IVIM fitting methods to the conventional nonlinear least‐squares regression: Bayesian probability estimation, a recently introduced neural network approach, IVIM‐NET, and a version of the neural network modified to increase consistency, IVIM‐NETmod. Methods Ten healthy volunteers underwent two imaging sessions of the neck, two weeks apart, with two DWI acquisitions per session. Model parameters (ADC, diffusion coefficient Dt, perfusion fraction fp, and pseudo‐diffusion coefficient Dp) from each fit method were determined in the tonsils and in the pterygoid muscles. Within‐subject coefficients of variation (wCV) were calculated to assess repeatability. Training of the neural network was repeated 100 times with random initialization to investigate consistency, quantified by the coefficient of variance. Results The Bayesian and neural network approaches outperformed nonlinear regression in terms of wCV. Intersession wCV of Dt in the tonsils was 23.4% for nonlinear regression, 9.7% for Bayesian estimation, 9.4% for IVIM‐NET, and 11.2% for IVIM‐NETmod. However, results from repeated training of the neural network on the same data set showed differences in parameter estimates: The coefficient of variances over the 100 repetitions for IVIM‐NET were 15% for both Dt and fp, and 94% for Dp; for IVIM‐NETmod, these values improved to 5%, 9%, and 62%, respectively. Conclusion Repeatabilities from the Bayesian and neural network approaches are superior to that of nonlinear regression for estimating IVIM parameters in the head and neck.
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Affiliation(s)
- Thomas Koopman
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Roland Martens
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
| | | | - Maqsood Yaqub
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Cristina Lavini
- Department of RadiologyAmsterdam UMC, University of AmsterdamAmsterdamthe Netherlands
| | - Pim de Graaf
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Jonas Castelijns
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
- Department of Radiologythe Netherlands Cancer Institute–Antoni van LeeuwenhoekAmsterdamthe Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
- Department of Nuclear Medicine and Molecular ImagingUniversity Medical Center GroningenGroningenthe Netherlands
| | - J. Tim Marcus
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamthe Netherlands
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Verburg N, Koopman T, Yaqub MM, Hoekstra OS, Lammertsma AA, Barkhof F, Pouwels PJW, Reijneveld JC, Heimans JJ, Rozemuller AJM, Bruynzeel AME, Lagerwaard F, Vandertop WP, Boellaard R, Wesseling P, de Witt Hamer PC. Improved detection of diffuse glioma infiltration with imaging combinations: a diagnostic accuracy study. Neuro Oncol 2021; 22:412-422. [PMID: 31550353 PMCID: PMC7058442 DOI: 10.1093/neuonc/noz180] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [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: 05/14/2019] [Accepted: 09/13/2019] [Indexed: 11/22/2022] Open
Abstract
Background Surgical resection and irradiation of diffuse glioma are guided by standard MRI: T2/fluid attenuated inversion recovery (FLAIR)–weighted MRI for non-enhancing and T1-weighted gadolinium-enhanced (T1G) MRI for enhancing gliomas. Amino acid PET has been suggested as the new standard. Imaging combinations may improve standard MRI and amino acid PET. The aim of the study was to determine the accuracy of imaging combinations to detect glioma infiltration. Methods We included 20 consecutive adults with newly diagnosed non-enhancing glioma (7 diffuse astrocytomas, isocitrate dehydrogenase [IDH] mutant; 1 oligodendroglioma, IDH mutant and 1p/19q codeleted; 1 glioblastoma IDH wildtype) or enhancing glioma (glioblastoma, 9 IDH wildtype and 2 IDH mutant). Standardized preoperative imaging (T1-, T2-, FLAIR-weighted, and T1G MRI, perfusion and diffusion MRI, MR spectroscopy and O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET) PET) was co-localized with multiregion stereotactic biopsies preceding resection. Tumor presence in the biopsies was assessed by 2 neuropathologists. Diagnostic accuracy was determined using receiver operating characteristic analysis. Results A total of 174 biopsies were obtained (63 from 9 non-enhancing and 111 from 11 enhancing gliomas), of which 129 contained tumor (50 from non-enhancing and 79 from enhancing gliomas). In enhancing gliomas, the combination of apparent diffusion coefficient (ADC) with [18F]FET PET (area under the curve [AUC], 95% CI: 0.89, 0.79‒0.99) detected tumor better than T1G MRI (0.56, 0.39‒0.72; P < 0.001) and [18F]FET PET (0.76, 0.66‒0.86; P = 0.001). In non-enhancing gliomas, no imaging combination detected tumor significantly better than standard MRI. FLAIR-weighted MRI had an AUC of 0.81 (0.65–0.98) compared with 0.69 (0.56–0.81; P = 0.019) for [18F]FET PET. Conclusion Combining ADC and [18F]FET PET detects glioma infiltration better than standard MRI and [18F]FET PET in enhancing gliomas, potentially enabling better guidance of local therapy.
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Affiliation(s)
- Niels Verburg
- Brain Tumor Center Amsterdam, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands.,Neurosurgical Center Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Thomas Koopman
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location Free University Medical Center (VUmc), Amsterdam, Netherlands
| | - Maqsood M Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location Free University Medical Center (VUmc), Amsterdam, Netherlands
| | - Otto S Hoekstra
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location Free University Medical Center (VUmc), Amsterdam, Netherlands
| | - Adriaan A Lammertsma
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location Free University Medical Center (VUmc), Amsterdam, Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location Free University Medical Center (VUmc), Amsterdam, Netherlands.,University College London Institute of Neurology and Healthcare Engineering, London, UK
| | - Petra J W Pouwels
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location Free University Medical Center (VUmc), Amsterdam, Netherlands
| | - Jaap C Reijneveld
- Brain Tumor Center Amsterdam, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands.,Department of Neurology, Amsterdam UMC, VUmc, Amsterdam, Netherlands
| | - Jan J Heimans
- Department of Neurology, Amsterdam UMC, VUmc, Amsterdam, Netherlands
| | | | | | - Frank Lagerwaard
- Department of Radiotherapy, Amsterdam UMC, VUmc, Amsterdam, Netherlands
| | - William P Vandertop
- Brain Tumor Center Amsterdam, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands.,Neurosurgical Center Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location Free University Medical Center (VUmc), Amsterdam, Netherlands
| | - Pieter Wesseling
- Brain Tumor Center Amsterdam, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands.,Neurosurgical Center Amsterdam, Amsterdam UMC, Amsterdam, Netherlands.,Department of Pathology, Amsterdam UMC, VUmc, Amsterdam, Netherlands.,Princess Máxima Center for Pediatric Oncology and Department of Pathology, UMC Utrecht, Utrecht, Netherlands
| | - Philip C de Witt Hamer
- Brain Tumor Center Amsterdam, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands.,Neurosurgical Center Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
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4
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Barthel F, Verburg N, Anderson K, Koopman T, Johnson K, Wesseling P, de Witt Hamer P, Verhaak R. EPCO-09. STEREOTACTIC IMAGE-GUIDED EPIGENOME PROFILING REVEALS DIVERSE EVOLUTIONARY GROWTH ROUTES IN DIFFUSE GLIOMAS. Neuro Oncol 2020. [DOI: 10.1093/neuonc/noaa215.288] [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: 11/13/2022] Open
Abstract
Abstract
Intratumoral heterogeneity is a hallmark of diffuse gliomas and inhibits effective prediction of clinical outcome. To devise a three-dimensional reconstruction of tumor lineage, we used neuronavigation to acquire eight to twelve image-guided and spatially separated stereotactic biopsy samples from 16 adult patients with a diffuse glioma, which we characterized using DNA methylation arrays. A total of 133 samples were obtained from regions with and without imaging abnormalities. Methylation profiles were analyzed to construct phylogenetic trees and subsequently projected on image-derived tumor maps. Lineage analysis of these evolutionary trees indicated that the sampled gliomas largely evolved stochastically, suggesting that critical tumor drivers were acquired early in time. These results were further validated using 102 multi-region samples from 24 independent patients. Patristic (evolutionary) and cartesian (spatial) distances between pairs of tumor samples from the same patient demonstrated strong correlations, suggesting that this information could be used to determine trajectories of tumor evolution. Evolutionary and spatial distance metrics were combined with histologically obtained and computationally quantified cellularity and proliferation rates to infer vectors representing the direction and magnitude of tumor growth. Using the resulting vector field we determined the minimum and maximum rates of change in order infer the tumor’s evolutionary trajectory. Using this metric we identified three distinct growth patterns: (1) tumors with a trajectory oriented towards the tumor core, (2) outward growing tumors with a linear trajectory pointing outside tumor boundaries, and (3) outward growing tumors with a branching trajectory directed outside tumor boundaries. Association of evolutionary growth patterns with survival demonstrated distinct impacts on outcome, suggesting that growth patterns are an important determinant of tumor aggressiveness. Taken together, although our analyses indicated that the observed glioma heterogeneity is small and largely stochastic, when spatially mapped these changes can be used to track tumor lineage and identify clinically relevant growth patterns.
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Affiliation(s)
- Floris Barthel
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Niels Verburg
- Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Kevin Anderson
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Thomas Koopman
- Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Kevin Johnson
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | | | | | - Roel Verhaak
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
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5
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Martens RM, Koopman T, Noij DP, Pfaehler E, Übelhör C, Sharma S, Vergeer MR, Leemans CR, Hoekstra OS, Yaqub M, Zwezerijnen GJ, Heymans MW, Peeters CFW, de Bree R, de Graaf P, Castelijns JA, Boellaard R. Predictive value of quantitative 18F-FDG-PET radiomics analysis in patients with head and neck squamous cell carcinoma. EJNMMI Res 2020; 10:102. [PMID: 32894373 PMCID: PMC7477048 DOI: 10.1186/s13550-020-00686-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [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: 03/20/2020] [Accepted: 08/13/2020] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Radiomics is aimed at image-based tumor phenotyping, enabling application within clinical-decision-support-systems to improve diagnostic accuracy and allow for personalized treatment. The purpose was to identify predictive 18-fluor-fluoro-2-deoxyglucose (18F-FDG) positron-emission tomography (PET) radiomic features to predict recurrence, distant metastasis, and overall survival in patients with head and neck squamous cell carcinoma treated with chemoradiotherapy. METHODS Between 2012 and 2018, 103 retrospectively (training cohort) and 71 consecutively included patients (validation cohort) underwent 18F-FDG-PET/CT imaging. The 434 extracted radiomic features were subjected, after redundancy filtering, to a projection resulting in outcome-independent meta-features (factors). Correlations between clinical, first-order 18F-FDG-PET parameters (e.g., SUVmean), and factors were assessed. Factors were combined with 18F-FDG-PET and clinical parameters in a multivariable survival regression and validated. A clinically applicable risk-stratification was constructed for patients' outcome. RESULTS Based on 124 retained radiomic features from 103 patients, 8 factors were constructed. Recurrence prediction was significantly most accurate by combining HPV-status, SUVmean, SUVpeak, factor 3 (histogram gradient and long-run-low-grey-level-emphasis), factor 4 (volume-difference, coarseness, and grey-level-non-uniformity), and factor 6 (histogram variation coefficient) (CI = 0.645). Distant metastasis prediction was most accurate assessing metabolic-active tumor volume (MATV)(CI = 0.627). Overall survival prediction was most accurate using HPV-status, SUVmean, SUVmax, factor 1 (least-axis-length, non-uniformity, high-dependence-of-high grey-levels), and factor 5 (aspherity, major-axis-length, inversed-compactness and, inversed-flatness) (CI = 0.764). CONCLUSIONS Combining HPV-status, first-order 18F-FDG-PET parameters, and complementary radiomic factors was most accurate for time-to-event prediction. Predictive phenotype-specific tumor characteristics and interactions might be captured and retained using radiomic factors, which allows for personalized risk stratification and optimizing personalized cancer care. TRIAL REGISTRATION Trial NL3946 (NTR4111), local ethics commission reference: Prediction 2013.191 and 2016.498. Registered 7 August 2013, https://www.trialregister.nl/trial/3946.
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Affiliation(s)
- Roland M Martens
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, De Boelelaan 1117, PO Box 7057, 1007, Amsterdam, MB, Netherlands.
| | - Thomas Koopman
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, De Boelelaan 1117, PO Box 7057, 1007, Amsterdam, MB, Netherlands
| | - Daniel P Noij
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, De Boelelaan 1117, PO Box 7057, 1007, Amsterdam, MB, Netherlands
| | - Elisabeth Pfaehler
- Department of Nuclear Medicine and Molecular Imaging, Medical Imaging Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Caroline Übelhör
- Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Sughandi Sharma
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, De Boelelaan 1117, PO Box 7057, 1007, Amsterdam, MB, Netherlands
| | - Marije R Vergeer
- Department of Radiation Oncology, Amsterdam University Medical Center, De Boelelaan, 1117, Amsterdam, Netherlands
| | - C René Leemans
- Department of Otolaryngology-Head and Neck Surgery, Amsterdam University Medical Center, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Otto S Hoekstra
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, De Boelelaan 1117, PO Box 7057, 1007, Amsterdam, MB, Netherlands
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, De Boelelaan 1117, PO Box 7057, 1007, Amsterdam, MB, Netherlands
| | - Gerben J Zwezerijnen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, De Boelelaan 1117, PO Box 7057, 1007, Amsterdam, MB, Netherlands
| | - Martijn W Heymans
- Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Carel F W Peeters
- Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Remco de Bree
- Department of Head and Neck Surgical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Pim de Graaf
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, De Boelelaan 1117, PO Box 7057, 1007, Amsterdam, MB, Netherlands
| | - Jonas A Castelijns
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, De Boelelaan 1117, PO Box 7057, 1007, Amsterdam, MB, Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, De Boelelaan 1117, PO Box 7057, 1007, Amsterdam, MB, Netherlands.,Department of Nuclear Medicine and Molecular Imaging, Medical Imaging Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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6
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Koopman T, Martens RM, Lavini C, Yaqub M, Castelijns JA, Boellaard R, Marcus JT. Repeatability of arterial input functions and kinetic parameters in muscle obtained by dynamic contrast enhanced MR imaging of the head and neck. Magn Reson Imaging 2020; 68:1-8. [DOI: 10.1016/j.mri.2020.01.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 12/23/2019] [Accepted: 01/19/2020] [Indexed: 12/13/2022]
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Koopman T, Verburg N, Pouwels PJ, Wesseling P, Hoekstra OS, De Witt Hamer PC, Lammertsma AA, Yaqub M, Boellaard R. Quantitative parametric maps of O-(2-[ 18F]fluoroethyl)-L-tyrosine kinetics in diffuse glioma. J Cereb Blood Flow Metab 2020; 40:895-903. [PMID: 31122112 PMCID: PMC7074601 DOI: 10.1177/0271678x19851878] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
Quantitative parametric images of O-(2-[18F]fluoroethyl)-L-tyrosine kinetics in diffuse gliomas could be used to improve glioma grading, tumour delineation or the assessment of the uptake distribution of this positron emission tomography tracer. In this study, several parametric images and tumour-to-normal maps were compared in terms of accuracy of region averages (when compared to results from nonlinear regression of a reversible two-tissue compartment plasma input model) and image noise using 90 min of dynamic scan data acquired in seven patients with diffuse glioma. We included plasma input methods (the basis function implementation of the single-tissue compartment model, spectral analysis and Logan graphical analysis) and reference tissue methods (basis function implementations of the simplified reference tissue model, variations of the multilinear reference tissue model and non-invasive Logan graphical analysis) as well as tumour-to-normal ratio maps at three intervals. (Non-invasive) Logan graphical analysis provided volume of distribution maps and distribution volume ratio maps with the lowest level of noise, while the basis function implementations provided the best accuracy. Tumour-to-normal ratio maps provided better results if later interval times were used, i.e. 60-90 min instead of 20-40 min, leading to lower bias (2.9% vs. 10.8%, respectively) and less noise (12.8% vs. 14.4%).
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Affiliation(s)
- Thomas Koopman
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Niels Verburg
- Neurosurgical Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Brain Tumor Center Amsterdam, Amsterdam, The Netherlands
| | - Petra Jw Pouwels
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Pieter Wesseling
- Department of Pathology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.,Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Otto S Hoekstra
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Philip C De Witt Hamer
- Neurosurgical Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Brain Tumor Center Amsterdam, Amsterdam, The Netherlands
| | - Adriaan A Lammertsma
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Ronald Boellaard
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Nuclear Medicine & Molecular Imaging, University Medical Center Groningen, Groningen, The Netherlands
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8
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Verburg N, Barthel F, Anderson K, Koopman T, Yaqub M, Hoekstra O, Lammertsma A, Barkhof F, Pouwels P, C Reijneveld J, Heijmans J, Rozemuller A, Costello J, Taylor M, Vandertop W, Boellaard R, Johnson KC, Wesseling P, de Witt Hamer P, Verhaak R. PATH-48. THE DNA METHYLATION LANDSCAPE OF CORE AND PERIPHERAL DIFFUSE GLIOMA REGIONS SHOWS LITTLE SPATIAL SUBTYPE HETEROGENEITY AFTER CONSIDERING TUMOR PURITY. Neuro Oncol 2019. [DOI: 10.1093/neuonc/noz175.644] [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: 11/12/2022] Open
Abstract
Abstract
While diffuse gliomas are notorious for their histopathological, genetic and transcriptional spatial heterogeneity, little is known about their epigenetic spatial heterogeneity. The result of spatial (epi)genetic analysis is strongly influenced by the proportion of cancer cells in a sample, so called tumor purity. However, a gold standard for assessment of tumor purity is lacking. We set out to analyze tumor purity using different measurement modalities and explore tumor purity-corrected DNA methylation spatial heterogeneity in glioma. DNA methylation(-derived), quantitative histological and radiological measurements of tumor purity, as well as DNA methylation profiles, were analyzed in 133 image-guided multi-sector stereotactic biopsy samples of 16 patients with newly diagnosed glioma. These biopsies were acquired in regions with and without abnormalities on MRI. Data was validated in two independent populations of respectively 102 multi-region samples in 24 glioma patients and 64 single-region samples from patients without glioma. DNA methylation profiles from The Cancer Genome Atlas and the patients without glioma was used to predict DNA methylation and transcriptional subtype. Consensus measurement of tumor purity estimates (CPE) ranged from 0 to 91% and was most correlated with the DNA methylation measurement of tumor purity. Neuropathological qualitative assessment of tumor presence generally corresponded well with CPE, but occasionally samples reported as ‘histologically normal’ demonstrated tumor purities up to 53%. After filtering specimens with tumor purity less than 50%, DNA methylation subtype showed little spatial heterogeneity, this in contrast to transcriptional subtype. Samples from core and peripheral regions showed similar DNA methylation profiles. Non-purity related intratumoral heterogeneity for promotor methylation of epigenetically regulated genes was minimal, but higher in IDH-wildtype than in IDH-mutant gliomas. In conclusion, after considering DNA methylation-based measurement of tumor purity DNA methylation in diffuse gliomas shows little spatial heterogeneity; incorporating such tumor purity information can further increase the reliability of methylation-profiling-based tumor classification.
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Affiliation(s)
| | - Floris Barthel
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Kevin Anderson
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | | | | | | | | | | | | | - Jaap C Reijneveld
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology, Amsterdam, Netherlands
| | | | | | | | | | | | | | - Kevin C Johnson
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | | | | | - Roel Verhaak
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
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9
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Verburg N, Koopman T, Yaqub M, Hoekstra OS, Lammertsma AA, Schwarte LA, Barkhof F, Pouwels PJW, Heimans JJ, Reijneveld JC, Rozemuller AJM, Vandertop WP, Wesseling P, Boellaard R, de Witt Hamer PC. Direct comparison of [ 11C] choline and [ 18F] FET PET to detect glioma infiltration: a diagnostic accuracy study in eight patients. EJNMMI Res 2019; 9:57. [PMID: 31254208 PMCID: PMC6598977 DOI: 10.1186/s13550-019-0523-8] [Citation(s) in RCA: 5] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Accepted: 05/28/2019] [Indexed: 02/07/2023] Open
Abstract
Background Positron emission tomography (PET) is increasingly used to guide local treatment in glioma. The purpose of this study was a direct comparison of two potential tracers for detecting glioma infiltration, O-(2-[18F]-fluoroethyl)-l-tyrosine ([18F] FET) and [11C] choline. Methods Eight consecutive patients with newly diagnosed diffuse glioma underwent dynamic [11C] choline and [18F] FET PET scans. Preceding craniotomy, multiple stereotactic biopsies were obtained from regions inside and outside PET abnormalities. Biopsies were assessed independently for tumour presence by two neuropathologists. Imaging measurements were derived at the biopsy locations from 10 to 40 min [11C] choline and 20–40, 40–60 and 60–90 min [18F] FET intervals, as standardized uptake value (SUV) and tumour-to-brain ratio (TBR). Diagnostic accuracies of both tracers were compared using receiver operating characteristic analysis and generalized linear mixed modelling with consensus histopathological assessment as reference. Results Of the 74 biopsies, 54 (73%) contained tumour. [11C] choline SUV and [18F] FET SUV and TBR at all intervals were higher in tumour than in normal samples. For [18F] FET, the diagnostic accuracy of TBR was higher than that of SUV for intervals 40–60 min (area under the curve: 0.88 versus 0.81, p = 0.026) and 60–90 min (0.90 versus 0.81, p = 0.047). The diagnostic accuracy of [18F] FET TBR 60–90 min was higher than that of [11C] choline SUV 20–40 min (0.87 versus 0.67, p = 0.005). Conclusions [18F] FET was more accurate than [11C] choline for detecting glioma infiltration. Highest accuracy was found for [18F] FET TBR for the interval 60–90 min post-injection. Electronic supplementary material The online version of this article (10.1186/s13550-019-0523-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Niels Verburg
- Neurosurgical Center Amsterdam, Brain Tumour Center Amsterdam, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Thomas Koopman
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Otto S Hoekstra
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Adriaan A Lammertsma
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Lothar A Schwarte
- Department of Anaesthesiology, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.,UCL institutes of Neurology & Healthcare Engineering, Gower St, Bloomsbury, London, WC1E 6BT, UK
| | - Petra J W Pouwels
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Jan J Heimans
- Department of Neurology, Brain Tumour Center Amsterdam, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Jaap C Reijneveld
- Department of Neurology, Brain Tumour Center Amsterdam, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Annemieke J M Rozemuller
- Department of Pathology, Brain Tumour Center Amsterdam, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - William P Vandertop
- Neurosurgical Center Amsterdam, Brain Tumour Center Amsterdam, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Pieter Wesseling
- Department of Pathology, Brain Tumour Center Amsterdam, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.,Princess Máxima Center for Paediatric Oncology, and Department of Pathology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Ronald Boellaard
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Philip C de Witt Hamer
- Neurosurgical Center Amsterdam, Brain Tumour Center Amsterdam, Amsterdam UMC, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
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10
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Martens RM, Noij DP, Koopman T, Zwezerijnen B, Heymans M, de Jong MC, Hoekstra OS, Vergeer MR, de Bree R, Leemans CR, de Graaf P, Boellaard R, Castelijns JA. Predictive value of quantitative diffusion-weighted imaging and 18-F-FDG-PET in head and neck squamous cell carcinoma treated by (chemo)radiotherapy. Eur J Radiol 2019; 113:39-50. [PMID: 30927958 DOI: 10.1016/j.ejrad.2019.01.031] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [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: 08/27/2018] [Revised: 12/28/2018] [Accepted: 01/29/2019] [Indexed: 01/15/2023]
Abstract
BACKGROUND AND PURPOSE In head and neck squamous cell carcinoma (HNSCC) (chemo)radiotherapy is increasingly used to preserve organ functionality. The purpose of this study was to identify predictive pretreatment DWI- and 18F-FDG-PET/CT-parameters for treatment failure (TF), locoregional recurrence (LR) and death in HNSCC patients treated by (chemo)radiotherapy. MATERIALS AND METHODS We retrospectively included 134 histologically proven HNSCC patients treated with (chemo)radiotherapy between 2012-2017. In 58 patients pre-treatment DWI and 18F-FDG-PET/CT were performed, in 31 patients DWI only and in 45 patients 18F-FDG-PET/CT only. Primary tumor (PT) and largest lymph node (LN) metastasis were quantitatively assessed for TF, LR and death. Multivariate analysis was performed for 18F-FDG-PET/CT and DWI separately and thereafter combined. In patients with both imaging modalities, positive and negative predictive value in TF and differences in LR and death, were assessed. RESULTS Mean follow-up was 25.6 months (interquartile-range; 14.0-37.1 months). Predictors of treatment failure, corrected for TNM-stage and HPV-status, were SUVmax-PT, ADCmax-PT, total lesion glycolysis (TLG-LN), ADCp20-LN (P = 0.049, P = 0.024, P = 0.031, P = 0.047, respectively). TLG-PT was predictive for LR (P = 0.003). Metabolic active tumor volume (MATV-PT) (P = 0.003), ADCGTV-PT (P < 0.001), ADCSD (P = 0.048) were significant predictors for death. In patients with both imaging modalities SUVmax-PT remained predictive for treatment failure (P = 0.049), TLG-LN for LR (P = 0.003) and ADCGTV-PT for death (P < 0.001). Higher predictive value for treatment failure was found for the combination of SUVmax-PT and ADCmax-PT, compared to either one separately. CONCLUSION Both DWI- and 18F-FDG-PET/CT-parameters appear to have predictive value for treatment failure, locoregional recurrence and death. Combining SUVmax-PT and ADCmax-PT resulted in better prediction of treatment failure compared to single parameter assessment.
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Affiliation(s)
- Roland M Martens
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands.
| | - Daniel P Noij
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Thomas Koopman
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Ben Zwezerijnen
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Martijn Heymans
- Department of Epidemiology and Biostatistics, the Netherlands
| | - Marcus C de Jong
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Otto S Hoekstra
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Marije R Vergeer
- Department of Radiation Oncology, VU University Medical Center, Amsterdam, the Netherlands
| | - Remco de Bree
- Department of Otolaryngology - Head and Neck Surgery, VU University Medical Center, Amsterdam, the Netherlands; Department of Head and Neck Surgical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - C René Leemans
- Department of Otolaryngology - Head and Neck Surgery, VU University Medical Center, Amsterdam, the Netherlands
| | - Pim de Graaf
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Jonas A Castelijns
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
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11
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Koopman T, Yaqub M, Heijtel DF, Nederveen AJ, van Berckel BN, Lammertsma AA, Boellaard R. Semi-quantitative cerebral blood flow parameters derived from non-invasive [ 15O]H 2O PET studies. J Cereb Blood Flow Metab 2019; 39:163-172. [PMID: 28901822 PMCID: PMC6311619 DOI: 10.1177/0271678x17730654] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Quantification of regional cerebral blood flow (CBF) using [15O]H2O positron emission tomography (PET) requires the use of an arterial input function. Arterial sampling, however, is not always possible, for example in ill-conditioned or paediatric patients. Therefore, it is of interest to explore the use of non-invasive methods for the quantification of CBF. For validation of non-invasive methods, test-retest normal and hypercapnia data from 15 healthy volunteers were used. For each subject, the data consisted of up to five dynamic [15O]H2O brain PET studies of 10 min and including arterial sampling. A measure of CBF was estimated using several non-invasive methods earlier reported in literature. In addition, various parameters were derived from the time-activity curve (TAC). Performance of these methods was assessed by comparison with full kinetic analysis using correlation and agreement analysis. The analysis was repeated with normalization to the whole brain grey matter value, providing relative CBF distributions. A reliable, absolute quantitative estimate of CBF could not be obtained with the reported non-invasive methods. Relative (normalized) CBF was best estimated using the double integration method.
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Affiliation(s)
- Thomas Koopman
- 1 Department of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Maqsood Yaqub
- 1 Department of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Dennis Fr Heijtel
- 1 Department of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands.,2 Philips Healthcare, Best, the Netherlands
| | - Aart J Nederveen
- 3 Department of Radiology, Academic Medical Center, Amsterdam, the Netherlands
| | - Bart Nm van Berckel
- 1 Department of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Adriaan A Lammertsma
- 1 Department of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Ronald Boellaard
- 1 Department of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands.,4 Department of Nuclear Medicine & Molecular imaging, University Medical Center Groningen, Groningen, the Netherlands
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12
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Martens RM, Noij DP, Ali M, Koopman T, Marcus JT, Vergeer MR, de Vet H, de Jong MC, Leemans CR, Hoekstra OS, de Bree R, de Graaf P, Boellaard R, Castelijns JA. Functional imaging early during (chemo)radiotherapy for response prediction in head and neck squamous cell carcinoma; a systematic review. Oral Oncol 2018; 88:75-83. [PMID: 30616800 DOI: 10.1016/j.oraloncology.2018.11.005] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [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: 09/16/2018] [Revised: 11/02/2018] [Accepted: 11/05/2018] [Indexed: 10/27/2022]
Abstract
This systematic review gives an extensive overview of the current state of functional imaging during (chemo)radiotherapy to predict locoregional control (LRC) and overall survival (OS) for head and neck squamous cell carcinoma. MEDLINE and EMBASE were searched for literature until April 2018 assessing the predictive performance of functional imaging (computed tomography perfusion (CTp), MRI and positron-emission tomography (PET)) within 4 weeks after (chemo)radiotherapy initiation. Fifty-two studies (CTp: n = 4, MRI: n = 19, PET: n = 26, MRI/PET: n = 3) were included involving 1623 patients. Prognostic information was extracted according the PRISMA protocol. Pooled estimation and subgroup analyses were performed for comparable parameters and outcome. However, the heterogeneity of included studies limited the possibility for comparison. Early tumoral changes from (chemo)radiotherapy can be captured by functional MRI and 18F-FDG-PET and could allow for personalized treatment adaptation. Lesions showed potentially prognostic intratreatment changes in perfusion, diffusion and metabolic activity. Intratreatment ADCmean increase (decrease of diffusion restriction) and low SUVmax (persistent low or decrease of 18F-FDG uptake) were most predictive of LRC. Intratreatment persistent high or increase of perfusion on CT/MRI (i.e. blood flow, volume, permeability) also predicted LRC. Low SUVmax and total lesion glycolysis (TLG) predicted favorable OS. The optimal timing to perform functional imaging to predict LRC or OS was 2-3 weeks after treatment initiation.
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Affiliation(s)
- Roland M Martens
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands.
| | - Daniel P Noij
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Meedie Ali
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Thomas Koopman
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - J Tim Marcus
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Marije R Vergeer
- Department of Radiation Oncology, VU University Medical Center, Amsterdam, the Netherlands
| | - Henrica de Vet
- Department of Epidemiology and Biostatistics and the EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands
| | - Marcus C de Jong
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - C René Leemans
- Department of Otolaryngology - Head and Neck Surgery, VU University Medical Center, Amsterdam, the Netherlands
| | - Otto S Hoekstra
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Remco de Bree
- Department of Head and Neck Surgical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Pim de Graaf
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Jonas A Castelijns
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
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13
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Noij DP, Martens RM, Koopman T, Hoekstra OS, Comans EFI, Zwezerijnen B, de Bree R, de Graaf P, Castelijns JA. Use of Diffusion-Weighted Imaging and 18F-Fluorodeoxyglucose Positron Emission Tomography Combined With Computed Tomography in the Response Assessment for (Chemo)radiotherapy in Head and Neck Squamous Cell Carcinoma. Clin Oncol (R Coll Radiol) 2018; 30:780-792. [PMID: 30318343 DOI: 10.1016/j.clon.2018.09.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [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: 04/07/2018] [Revised: 07/12/2018] [Accepted: 08/20/2018] [Indexed: 11/12/2022]
Abstract
AIMS Our purpose was to assess the diagnostic accuracy and prognostic value of diffusion-weighted imaging (DWI) and 18F-fluorodeoxyglucose positron emission tomography combined with computed tomography (18F-FDG-PET/CT) carried out 3-6 months after (chemo)radiotherapy in head and neck squamous cell carcinoma. MATERIALS AND METHODS For this retrospective cohort study we included 82 patients with advanced-stage head and neck squamous cell carcinoma treated between 2012 and 2015. Primary tumours and lymph nodes were assessed separately. DWI was analysed qualitatively and quantitatively. 18F-FDG-PET/CT was evaluated using the Hopkins criteria. Dichotomous qualitative analysis was carried out for both modalities. Cox regression analysis was used for univariate analysis of recurrence-free survival (RFS). Significant univariate parameters were included in multivariate analysis. RESULTS In 12 patients, locoregional recurrence occurred. With all imaging strategies, either single-modality or multi-modality, a high negative predictive value (NPV) was achieved (94.3-100%). In response evaluation of the primary site, the preferred strategy is 18F-FDG-PET/CT only, which resulted in a sensitivity of 85.7%, specificity of 86.5%, positive predictive value (PPV) of 37.5% and NPV of 98.5%. For response evaluation of the neck, the best results were obtained with a sequential approach only including the second modality in positive reads of the first modality. It did not matter which modality was assessed first. This strategy for lymph node assessment resulted in a sensitivity, specificity, PPV and NPV of 83.3%, 95.6%, 62.5%, and 98.5%, respectively. After correction for received treatment and human papillomavirus status, primary tumour (P = 0.009) or lymph node (P < 0.001) Hopkins score ≥4 on 18F-FDG-PET/CT remained significant predictors of RFS. CONCLUSION For response evaluation of the primary tumour 18F-FDG-PET/CT only is the preferred strategy, whereas for the neck a sequential approach including both DWI and 18F-FDG-PET/CT resulted in the best diagnostic accuracy for follow-up after (chemo)radiotherapy. Qualitative analysis of 18F-FDG-PET/CT is a stronger predictor of RFS than DWI analysis.
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Affiliation(s)
- D P Noij
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands.
| | - R M Martens
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - T Koopman
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - O S Hoekstra
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - E F I Comans
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - B Zwezerijnen
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - R de Bree
- Department of Otolaryngology-Head and Neck Surgery, VU University Medical Center, Amsterdam, the Netherlands; Department of Head and Neck Surgical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - P de Graaf
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - J A Castelijns
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
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14
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Koopman T, Verburg N, Schuit RC, Pouwels PJW, Wesseling P, Windhorst AD, Hoekstra OS, de Witt Hamer PC, Lammertsma AA, Boellaard R, Yaqub M. Quantification of O-(2-[ 18F]fluoroethyl)-L-tyrosine kinetics in glioma. EJNMMI Res 2018; 8:72. [PMID: 30066053 PMCID: PMC6068050 DOI: 10.1186/s13550-018-0418-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Accepted: 06/27/2018] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND This study identified the optimal tracer kinetic model for quantification of dynamic O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) positron emission tomography (PET) studies in seven patients with diffuse glioma (four glioblastoma, three lower grade glioma). The performance of more simplified approaches was evaluated by comparison with the optimal compartment model. Additionally, the relationship with cerebral blood flow-determined by [15O]H2O PET-was investigated. RESULTS The optimal tracer kinetic model was the reversible two-tissue compartment model. Agreement analysis of binding potential estimates derived from reference tissue input models with the distribution volume ratio (DVR)-1 derived from the plasma input model showed no significant average difference and limits of agreement of - 0.39 and 0.37. Given the range of DVR-1 (- 0.25 to 1.5), these limits are wide. For the simplified methods, the 60-90 min tumour-to-blood ratio to parent plasma concentration yielded the highest correlation with volume of distribution VT as calculated by the plasma input model (r = 0.97). The 60-90 min standardized uptake value (SUV) showed better correlation with VT (r = 0.77) than SUV based on earlier intervals. The 60-90 min SUV ratio to contralateral healthy brain tissue showed moderate agreement with DVR with no significant average difference and limits of agreement of - 0.24 and 0.30. A significant but low correlation was found between VT and CBF in the tumour regions (r = 0.61, p = 0.007). CONCLUSION Uptake of [18F]FET was best modelled by a reversible two-tissue compartment model. Reference tissue input models yielded estimates of binding potential which did not correspond well with plasma input-derived DVR-1. In comparison, SUV ratio to contralateral healthy brain tissue showed slightly better performance, if measured at the 60-90 min interval. SUV showed only moderate correlation with VT. VT shows correlation with CBF in tumour.
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Affiliation(s)
- Thomas Koopman
- Department of Radiology and Nuclear Medicine, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, The Netherlands
| | - Niels Verburg
- Neurosurgical Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
- Brain Tumor Center Amsterdam, Amsterdam, The Netherlands
| | - Robert C. Schuit
- Department of Radiology and Nuclear Medicine, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, The Netherlands
| | - Petra J. W. Pouwels
- Department of Radiology and Nuclear Medicine, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, The Netherlands
| | - Pieter Wesseling
- Department of Pathology, VU University Medical Center, Amsterdam, The Netherlands
- Department of Pathology, Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
- Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Albert D. Windhorst
- Department of Radiology and Nuclear Medicine, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, The Netherlands
| | - Otto S. Hoekstra
- Department of Radiology and Nuclear Medicine, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, The Netherlands
| | - Philip C. de Witt Hamer
- Neurosurgical Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
- Brain Tumor Center Amsterdam, Amsterdam, The Netherlands
| | - Adriaan A. Lammertsma
- Department of Radiology and Nuclear Medicine, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, The Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, The Netherlands
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, The Netherlands
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Koopman T, Smits MM, Louwen M, Hage M, Boot H, Imholz ALT. HER2 positivity in gastric and esophageal adenocarcinoma: clinicopathological analysis and comparison. J Cancer Res Clin Oncol 2014; 141:1343-51. [PMID: 25544671 DOI: 10.1007/s00432-014-1900-3] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2014] [Accepted: 12/18/2014] [Indexed: 12/13/2022]
Abstract
PURPOSE Primary tumor classification of gastric or esophageal cancer has changed significantly with recent alterations of the tumor-node-metastasis (TNM) staging system. Considering these alterations, human epidermal growth factor receptor 2 (HER2) positivity rates were determined and compared in gastric and esophageal adenocarcinoma. Additionally, HER2 positivity in relation to other clinicopathological characteristics was evaluated. METHODS A total of 321 patients with histologically confirmed invasive gastric or esophageal adenocarcinoma were examined for HER2 by immunohistochemy (IHC) and chromogenic in situ hybridization (CISH). IHC 3+ or IHC 2+/CISH-positive tumors were considered HER2 positive. Clinicopathological characteristics were retrospectively retrieved from the patient records. RESULTS HER2 positivity was found in 50 of 321 patients (15.6 %). In univariate and multivariate logistic models, HER2 positivity rates were significantly higher in esophageal primary tumors (esophageal 25.0 % vs. gastric 7.4 %) and in intestinal histological tumor type (intestinal 22.6 % vs. diffuse/mixed 5.7 %). No significant differences in HER2 positivity were found between males and females, age below and above 65 years, biopsies and surgical specimens or advanced and early-stage disease. Using the 7th TNM edition, many tumors (30.5 % of all included tumors and 64.5 % of all esophageal primary tumors) previously classified as gastric cancer are now classified as esophageal cancer. CONCLUSIONS HER2 positivity occurs in 15.6 % of invasive gastroesophageal adenocarcinoma in Western patients, of which the majority is esophageal primary tumors and of the intestinal tumor type. With the introduction of the 7th TNM edition, a large number of tumors previously classified as gastric are now classified as esophageal tumors instead, with relatively high HER2 positivity rates in these esophageal primary tumors.
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Affiliation(s)
- T Koopman
- Department of Medical Oncology, Deventer Hospital, Nico Bolkesteinlaan 75, 7416 SE, Deventer, The Netherlands
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Ferrer MS, Lutjemeier BJ, Koopman T, Pierucci-Alves F, Weiss ML. Xenogeneic transplantation of equine testicular cells into seminiferous tubules of immunocompetent rats. Theriogenology 2011; 75:1258-64. [PMID: 21316749 PMCID: PMC3073581 DOI: 10.1016/j.theriogenology.2010.11.039] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [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: 07/09/2010] [Revised: 11/15/2010] [Accepted: 11/28/2010] [Indexed: 01/15/2023]
Abstract
The objectives were to develop a transplantation assay for equine testicular cells using busulfan-treated prepubertal immunocompetent rats as recipients, and to determine if putative equine spermatogonial stem cells (SSCs) could be enriched by flow cytometric cell sorting (based on light scattering properties), thereby improving engraftment efficiency. Four weeks after transplantation of frozen/thawed PKH26-labeled equine testicular cells, 0.029 ± 0.045% (mean ± SD) of viable donor cells transplanted had engrafted. Donor cells were present in seminiferous tubules of all recipient rats forming chains, pairs, mesh structures, or clusters (with two to >30 cells/structure). Cells were localized to the basal compartment by the basement membrane. Although equine cells proliferated within rat seminiferous tubules, no donor-derived spermatogenesis was evident. Furthermore, there was no histologic evidence of acute cellular rejection. No fluorescent cells were present in control testes. When equine testicular cells were sorted based on light scattering properties, the percentage of transplanted donor cells that engrafted was higher after injection of cells from the small, low complexity fraction (II; 0.169 ± 0.099%) than from either the large, high complexity fraction (I; 0.046 ± 0.051%) or unsorted cells (0.009 ± 0.007%; P < 0.05). Seminiferous tubules of busulfan-treated prepubertal immunocompetent rats provided a suitable niche for engraftment and proliferation, but not differentiation, of equine testicular cells. Sorting equine testicular cells based on light scattering properties resulted in a 19-fold improvement in colonization efficiency by cells with high forward scatter and low side scatter, which may represent putative equine SSCs.
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Affiliation(s)
- M S Ferrer
- Department of Clinical Sciences, College of Veterinary Medicine, Kansas State University, Manhattan, KS 66506, USA.
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Wilkerson MJ, Dolce K, Koopman T, Shuman W, Chun R, Garrett L, Barber L, Avery A. Lineage differentiation of canine lymphoma/leukemias and aberrant expression of CD molecules. Vet Immunol Immunopathol 2005; 106:179-96. [PMID: 15963817 DOI: 10.1016/j.vetimm.2005.02.020] [Citation(s) in RCA: 80] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2004] [Revised: 01/26/2005] [Accepted: 02/04/2005] [Indexed: 10/25/2022]
Abstract
Multiparameter flow cytometry analysis and specific cluster differentiation (CD) molecules were used to determine the expression profiles of B- and T-cell antigens on lymph node preparations from 59 dogs with generalized or multisystemic lymphoma. Lymph node samples from 11 healthy dogs were labeled to validate the specificity of antibodies and to formulate guidelines for interpretation of the results obtained from lymphoma samples. In normal lymph nodes, T-lymphocytes expressing CD3, CD4, or CD8 beta represented 59+/-11%, 43+/-8%, or 16+/-5% of the total cells, whereas B-lymphocytes expressing either CD21 or surface IgM (IgM) represented 37+/-9% or 14+/-5%, respectively. Small lymphocytes could be distinguished from large lymphocytes by forward light scatter. Of the patient samples 29 different breeds were represented with Golden and Labrador retriever being the most common. The lymphoma samples segregated into three groups based on CD antigen expression. Thirty cases predominantly expressed one or more combinations of CD79a, IgM, and CD21 representing a B-cell lineage. Three B-cell cases also expressed the stem cell antigen, CD34. Sixteen cases expressed one or more combinations of CD3, CD4, and CD8 consistent with a T-cell lineage and CD3+CD4+CD8--phenotype was the most common. Thirteen cases showed a mixed expression profile for T- and B-cell antigens and in three cases CD14 was highly expressed. Clinical response was poorest for T-cell lymphomas. Leukemic states occurred in all three phenotypes; but mixed cell cases had the greatest proportion. Dual immunofluorescence staining confirmed co-expression of T-cell (CD3) and B-cell antigens (CD79a or CD21) on neoplastic lymphocytes of six mixed cell cases. In one mixed cell case, dual immunostaining identified lymphocyte populations that stained mutually exclusive for CD79a and CD3. Six mixed cell lymphomas tested by PCR showed clonality for rearranged antigen receptor. Four cases that were CD79a+CD3+ had TCRgamma chain gene rearrangements, whereas two cases that were CD3+CD8+CD21+ had Ig heavy chain rearrangement. One case expressing multiple CD molecules (CD3+CD8+CD21+CD14+) was PCR negative for both Ig and TCRgamma gene rearrangement and could not be classified into a B- or T-cell lineage. We show for the first time co-expression of B- and T-cell markers on lymphoma cells that had specific T- or B-cell gene rearrangements. These findings suggest that aberrant CD molecule expression is not an uncommon finding in canine lymphomas and is a useful diagnostic marker for malignancy.
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Affiliation(s)
- M J Wilkerson
- Department of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS 66506, USA.
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