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Shrot S, Kerpel A, Belenky J, Lurye M, Hoffmann C, Yalon M. MR Imaging Characteristics and ADC Histogram Metrics for Differentiating Molecular Subgroups of Pediatric Low-Grade Gliomas. AJNR Am J Neuroradiol 2022; 43:1356-1362. [PMID: 36007944 PMCID: PMC9451619 DOI: 10.3174/ajnr.a7614] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 06/28/2022] [Indexed: 01/26/2023]
Abstract
BACKGROUND AND PURPOSE BRAF and type 1 neurofibromatosis status are distinctive features in pediatric low-grade gliomas with prognostic and therapeutic implications. We hypothesized that DWI metrics obtained through volumetric ADC histogram analyses of pediatric low-grade gliomas at baseline would enable early detection of BRAF and type 1 neurofibromatosis status. MATERIALS AND METHODS We retrospectively evaluated 40 pediatric patients with histologically proved pilocytic astrocytoma (n = 33), ganglioglioma (n = 4), pleomorphic xanthoastrocytoma (n = 2), and diffuse astrocytoma grade 2 (n = 1). Apart from 1 patient with type 1 neurofibromatosis who had a biopsy, 11 patients with type 1 neurofibromatosis underwent conventional MR imaging to diagnose a low-grade tumor without a biopsy. BRAF molecular analysis was performed for patients without type 1 neurofibromatosis. Eleven patients presented with BRAF V600E-mutant, 20 had BRAF-KIAA rearrangement, and 8 had BRAF wild-type tumors. Imaging studies were reviewed for location, margins, hemorrhage or calcifications, cystic components, and contrast enhancement. Histogram analysis of tumoral diffusivity was performed. RESULTS Diffusion histogram metrics (mean, median, and 10th and 90th percentiles) but not kurtosis or skewness were different among pediatric low-grade glioma subgroups (P < .05). Diffusivity was lowest in BRAF V600E-mutant tumors (the 10th percentile reached an area under the curve of 0.9 on receiver operating characteristic analysis). There were significant differences between evaluated pediatric low-grade glioma margins and cystic components (P = .03 and P = .001, respectively). Well-defined margins were characteristic of BRAF-KIAA or wild-type BRAF rather than BRAF V600E-mutant or type 1 neurofibromatosis tumors. None of the type 1 neurofibromatosis tumors showed a cystic component. CONCLUSIONS Imaging features of pediatric low-grade gliomas, including quantitative diffusion metrics, may assist in predicting BRAF and type 1 neurofibromatosis status, suggesting a radiologic-genetic correlation, and might enable early genetic signature characterization.
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Affiliation(s)
- S Shrot
- From the Section of Neuroradiology, Division of Diagnostic Imaging (S.S., A.K., J.B., C.H.)
- Sackler School of Medicine (S.S., C.H., M.Y.), Tel Aviv University, Tel Aviv, Israel
| | - A Kerpel
- From the Section of Neuroradiology, Division of Diagnostic Imaging (S.S., A.K., J.B., C.H.)
| | - J Belenky
- From the Section of Neuroradiology, Division of Diagnostic Imaging (S.S., A.K., J.B., C.H.)
| | - M Lurye
- Department of Pediatric Hemato-Oncology (M.L., M.Y.), Sheba Medical Center, Ramat-Gan, Israel
| | - C Hoffmann
- From the Section of Neuroradiology, Division of Diagnostic Imaging (S.S., A.K., J.B., C.H.)
- Sackler School of Medicine (S.S., C.H., M.Y.), Tel Aviv University, Tel Aviv, Israel
| | - M Yalon
- Department of Pediatric Hemato-Oncology (M.L., M.Y.), Sheba Medical Center, Ramat-Gan, Israel
- Sackler School of Medicine (S.S., C.H., M.Y.), Tel Aviv University, Tel Aviv, Israel
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2
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Vedmurthy P, Pinto ALR, Lin DDM, Comi AM, Ou Y. Study protocol: retrospectively mining multisite clinical data to presymptomatically predict seizure onset for individual patients with Sturge-Weber. BMJ Open 2022; 12:e053103. [PMID: 35121603 PMCID: PMC8819809 DOI: 10.1136/bmjopen-2021-053103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
INTRODUCTION Secondary analysis of hospital-hosted clinical data can save time and cost compared with prospective clinical trials for neuroimaging biomarker development. We present such a study for Sturge-Weber syndrome (SWS), a rare neurovascular disorder that affects 1 in 20 000-50 000 newborns. Children with SWS are at risk for developing neurocognitive deficit by school age. A critical period for early intervention is before 2 years of age, but early diagnostic and prognostic biomarkers are lacking. We aim to retrospectively mine clinical data for SWS at two national centres to develop presymptomatic biomarkers. METHODS AND ANALYSIS We will retrospectively collect clinical, MRI and neurocognitive outcome data for patients with SWS who underwent brain MRI before 2 years of age at two national SWS care centres. Expert review of clinical records and MRI quality control will be used to refine the cohort. The merged multisite data will be used to develop algorithms for abnormality detection, lesion-symptom mapping to identify neural substrate and machine learning to predict individual outcomes (presence or absence of seizures) by 2 years of age. Presymptomatic treatment in 0-2 years and before seizure onset may delay or prevent the onset of seizures by 2 years of age, and thereby improve neurocognitive outcomes. The proposed work, if successful, will be one of the largest and most comprehensive multisite databases for the presymptomatic phase of this rare disease. ETHICS AND DISSEMINATION This study involves human participants and was approved by Boston Children's Hospital Institutional Review Board: IRB-P00014482 and IRB-P00025916 Johns Hopkins School of Medicine Institutional Review Board: NA_00043846. Participants gave informed consent to participate in the study before taking part. The Institutional Review Boards at Kennedy Krieger Institute and Boston Children's Hospital approval have been obtained at each site to retrospectively study this data. Results will be disseminated by presentations, publication and sharing of algorithms generated.
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Affiliation(s)
- Pooja Vedmurthy
- Department of Neurology and Developmental Medicine, Hugo Moser Research Institute, Baltimore, Maryland, USA
- Department of Neurology and Pediatrics, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Anna L R Pinto
- Department of Neurology, Division of Epilepsy, Harvard Medical School, Boston, Massachusetts, USA
| | - Doris D M Lin
- Neuroradiology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Anne M Comi
- Department of Neurology and Developmental Medicine, Hugo Moser Research Institute, Baltimore, Maryland, USA
- Department of Neurology and Pediatrics, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Neurology and Pediatrics, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Yangming Ou
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, Massachusetts, USA
- Computational Health Informatics Program, Boston Children's Hospital, Boston, Massachusetts, USA
- Department of Radiology, Boston Children's Hospital; Harvard Medical School, Boston, MA, USA
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3
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Hagiwara A, Oughourlian TC, Cho NS, Schlossman J, Wang C, Yao J, Raymond C, Everson R, Patel K, Mareninov S, Rodriguez FJ, Salamon N, Pope WB, Nghiemphu PL, Liau LM, Prins RM, Cloughesy TF, Ellingson BM. Diffusion MRI is an early biomarker of overall survival benefit in IDH wild-type recurrent glioblastoma treated with immune checkpoint inhibitors. Neuro Oncol 2021; 24:1020-1028. [PMID: 34865129 DOI: 10.1093/neuonc/noab276] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Diffusion MRI estimates of the apparent diffusion coefficient (ADC) have been shown to be useful in predicting treatment response in patients with glioblastoma (GBM), with ADC elevations indicating tumor cell death. We aimed to investigate whether the ADC values measured before and after treatment with immune checkpoint inhibitors (ICIs) and the changes in these ADC values could predict overall survival (OS) in patients with recurrent IDH wild-type GBM. METHODS Forty-four patients who met the following inclusion criteria were included in this retrospective study: (i) diagnosed with recurrent IDH wild-type GBM and treated with either pembrolizumab or nivolumab and (ii) availability of diffusion data on pre- and post-ICI MRI. Tumor volume and the median relative ADC (rADC) with respect to the normal-appearing white matter within the enhancing tumor were calculated. RESULTS Median OS among all patients was 8.1 months (range, 1.0-22.5 months). Log-rank test revealed that higher post-treatment rADC was associated with a significantly longer OS (median, 10.3 months for rADC ≧ 1.63 versus 6.1 months for rADC < 1.63; P = 0.02), whereas tumor volume, pre-treatment rADC, and changes in rADC after treatment were not significantly associated with OS. Cox regression analysis revealed that post-treatment rADC significantly influenced OS (P = 0.02, univariate analysis), even after controlling for age and sex (P =0.01, multivariate analysis), and additionally controlling for surgery after ICI treatment (P = 0.045, multivariate analysis). CONCLUSIONS Elevated post-treatment rADC may be an early imaging biomarker for OS benefits in GBM patients receiving ICI treatment.
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Affiliation(s)
- Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Talia C Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.,Neuroscience Interdepartmental PhD Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Nicholas S Cho
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA.,Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Jacob Schlossman
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Richard Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kunal Patel
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sergey Mareninov
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Fausto J Rodriguez
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Phioanh L Nghiemphu
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Robert M Prins
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA.,UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA.,Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
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4
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Song J, Kadaba P, Kravitz A, Hormigo A, Friedman J, Belani P, Hadjipanayis C, Ellingson BM, Nael K. Multiparametric MRI for early identification of therapeutic response in recurrent glioblastoma treated with immune checkpoint inhibitors. Neuro Oncol 2021; 22:1658-1666. [PMID: 32193547 DOI: 10.1093/neuonc/noaa066] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Physiologic changes quantified by diffusion and perfusion MRI have shown utility in predicting treatment response in glioblastoma (GBM) patients treated with cytotoxic therapies. We aimed to investigate whether quantitative changes in diffusion and perfusion after treatment by immune checkpoint inhibitors (ICIs) would determine 6-month progression-free survival (PFS6) in patients with recurrent GBM. METHODS Inclusion criteria for this retrospective study were: (i) diagnosis of recurrent GBM treated with ICIs and (ii) availability of diffusion and perfusion in pre and post ICI MRI (iii) at ≥6 months follow-up from treatment. After co-registration, mean values of the relative apparent diffusion coefficient (rADC), Ktrans (volume transfer constant), Ve (extravascular extracellular space volume) and Vp (plasma volume), and relative cerebral blood volume (rCBV) were calculated from a volume-of-interest of the enhancing tumor. Final assignment of stable/improved versus progressive disease was determined on 6-month follow-up using modified Response Assessment in Neuro-Oncology criteria. RESULTS Out of 19 patients who met inclusion criteria and follow-up (mean ± SD: 7.8 ± 1.4 mo), 12 were determined to have tumor progression, while 7 had treatment response after 6 months of ICI treatment. Only interval change of rADC was suggestive of treatment response. Patients with treatment response (6/7: 86%) had interval increased rADC, while 11/12 (92%) with tumor progression had decreased rADC (P = 0.001). Interval change in rCBV, Ktrans, Vp, and Ve were not indicative of treatment response within 6 months. CONCLUSIONS In patients with recurrent GBM, interval change in rADC is promising in assessing treatment response versus progression within the first 6 months following ICI treatment. KEY POINTS • In recurrent GBM treated with ICIs, interval change in rADC suggests early treatment response.• Interval change in rADC can be used as an imaging biomarker to determine PFS6.• Interval change in MR perfusion and permeability measures do not suggest ICI treatment response.
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Affiliation(s)
- Joseph Song
- Icahn School of Medicine at Mount Sinai, Department of Radiology (Neuroimaging Advanced and Exploratory Lab), New York, New York
| | - Priyanka Kadaba
- Icahn School of Medicine at Mount Sinai, Department of Radiology (Neuroimaging Advanced and Exploratory Lab), New York, New York
| | - Amanda Kravitz
- Icahn School of Medicine at Mount Sinai, Department of Radiology (Neuroimaging Advanced and Exploratory Lab), New York, New York
| | - Adilia Hormigo
- Department of Neurology, Medicine (Div Hem Onc), The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Joshua Friedman
- Department of Neurology, Medicine (Div Hem Onc), The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Puneet Belani
- Icahn School of Medicine at Mount Sinai, Department of Radiology (Neuroimaging Advanced and Exploratory Lab), New York, New York
| | | | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Kambiz Nael
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
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5
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Li J, Chekkoury A, Prakash J, Glasl S, Vetschera P, Koberstein-Schwarz B, Olefir I, Gujrati V, Omar M, Ntziachristos V. Spatial heterogeneity of oxygenation and haemodynamics in breast cancer resolved in vivo by conical multispectral optoacoustic mesoscopy. LIGHT, SCIENCE & APPLICATIONS 2020; 9:57. [PMID: 32337021 PMCID: PMC7154032 DOI: 10.1038/s41377-020-0295-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 02/10/2020] [Accepted: 03/19/2020] [Indexed: 05/11/2023]
Abstract
The characteristics of tumour development and metastasis relate not only to genomic heterogeneity but also to spatial heterogeneity, associated with variations in the intratumoural arrangement of cell populations, vascular morphology and oxygen and nutrient supply. While optical (photonic) microscopy is commonly employed to visualize the tumour microenvironment, it assesses only a few hundred cubic microns of tissue. Therefore, it is not suitable for investigating biological processes at the level of the entire tumour, which can be at least four orders of magnitude larger. In this study, we aimed to extend optical visualization and resolve spatial heterogeneity throughout the entire tumour volume. We developed an optoacoustic (photoacoustic) mesoscope adapted to solid tumour imaging and, in a pilot study, offer the first insights into cancer optical contrast heterogeneity in vivo at an unprecedented resolution of <50 μm throughout the entire tumour mass. Using spectral methods, we resolve unknown patterns of oxygenation, vasculature and perfusion in three types of breast cancer and showcase different levels of structural and functional organization. To our knowledge, these results are the most detailed insights of optical signatures reported throughout entire tumours in vivo, and they position optoacoustic mesoscopy as a unique investigational tool linking microscopic and macroscopic observations.
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Affiliation(s)
- Jiao Li
- School of Precision Instruments and Optoelectronics Engineering, Tianjin University, No.92, Weijin Road, Nankai District, 300072 Tianjin, China
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Ingolstädter Landstr. 1, D-85764 Neuherberg, Germany
- Chair of Biological Imaging, TranslaTUM, Technische Universität München, Ismaningerstr. 22, D-81675 Munich, Germany
| | - Andrei Chekkoury
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Ingolstädter Landstr. 1, D-85764 Neuherberg, Germany
- Chair of Biological Imaging, TranslaTUM, Technische Universität München, Ismaningerstr. 22, D-81675 Munich, Germany
| | - Jaya Prakash
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Ingolstädter Landstr. 1, D-85764 Neuherberg, Germany
- Chair of Biological Imaging, TranslaTUM, Technische Universität München, Ismaningerstr. 22, D-81675 Munich, Germany
- Department of Instrumentation and Applied Physics, Indian Institute of Science Bangalore, CV Raman Rd, Bengaluru, 560012 Karnataka India
| | - Sarah Glasl
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Ingolstädter Landstr. 1, D-85764 Neuherberg, Germany
- Chair of Biological Imaging, TranslaTUM, Technische Universität München, Ismaningerstr. 22, D-81675 Munich, Germany
| | - Paul Vetschera
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Ingolstädter Landstr. 1, D-85764 Neuherberg, Germany
- Chair of Biological Imaging, TranslaTUM, Technische Universität München, Ismaningerstr. 22, D-81675 Munich, Germany
| | - Benno Koberstein-Schwarz
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Ingolstädter Landstr. 1, D-85764 Neuherberg, Germany
- Chair of Biological Imaging, TranslaTUM, Technische Universität München, Ismaningerstr. 22, D-81675 Munich, Germany
| | - Ivan Olefir
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Ingolstädter Landstr. 1, D-85764 Neuherberg, Germany
- Chair of Biological Imaging, TranslaTUM, Technische Universität München, Ismaningerstr. 22, D-81675 Munich, Germany
| | - Vipul Gujrati
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Ingolstädter Landstr. 1, D-85764 Neuherberg, Germany
- Chair of Biological Imaging, TranslaTUM, Technische Universität München, Ismaningerstr. 22, D-81675 Munich, Germany
| | - Murad Omar
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Ingolstädter Landstr. 1, D-85764 Neuherberg, Germany
- Chair of Biological Imaging, TranslaTUM, Technische Universität München, Ismaningerstr. 22, D-81675 Munich, Germany
| | - Vasilis Ntziachristos
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Ingolstädter Landstr. 1, D-85764 Neuherberg, Germany
- Chair of Biological Imaging, TranslaTUM, Technische Universität München, Ismaningerstr. 22, D-81675 Munich, Germany
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Qin L, Li A, Qu J, Reinshagen K, Li X, Cheng SC, Bryant A, Young GS. Normalization of ADC does not improve correlation with overall survival in patients with high-grade glioma (HGG). J Neurooncol 2018; 137:313-319. [PMID: 29383647 DOI: 10.1007/s11060-017-2719-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Accepted: 12/13/2017] [Indexed: 12/29/2022]
Abstract
Mixed reports leave uncertainty about whether normalization of apparent diffusion coefficient (ADC) to a within-subject white matter reference is necessary for assessment of tumor cellularity. We tested whether normalization improves the previously reported correlation of resection margin ADC with 15-month overall survival (OS) in HGG patients. Spin-echo echo-planar DWI was retrieved from 3 T MRI acquired between maximal resection and radiation in 37 adults with new-onset HGG (25 glioblastoma; 12 anaplastic astrocytoma). ADC maps were produced with the FSL DTIFIT tool (Oxford Centre for Functional MRI). 3 neuroradiologists manually selected regions of interest (ROI) in normal appearing white matter (NAWM) and in non-enhancing tumor (NT) < 2 cm from the margin of residual enhancing tumor or resection cavity. Normalized ADC (nADC) was computed as the ratio of absolute NT ADC to NAWM ADC. Reproducibility of nADC and absolute ADC among the readers' ROI was assessed using intra-class correlation coefficient (ICC) and within-subject coefficient of variation (wCV). Correlations of ADC and nADC with OS were compared using receiver operating characteristics (ROC) analysis. A p value 0.05 was considered statistically significant. Both mean ADC and nADC differed significantly between patients subgrouped by 15-month OS (p = 0.0014 and 0.0073 respectively). wCV and ICC among the readers were similar for absolute and normalized ADC. In ROC analysis of correlation with OS, nADC did not perform significantly better than absolute ADC. Normalization does not significantly improve the correlation of absolute ADC with OS in HGG, suggesting that normalization is not necessary for clinical or research ADC analysis in HGG patients.
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Affiliation(s)
- Lei Qin
- Department of Imaging, Dana-Farber Cancer Institute, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Angie Li
- Department of Radiology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA.,The Robert Larner, M.D. College of Medicine, University of Vermont, Burlington, VT, USA
| | - Jinrong Qu
- Department of Radiology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA.,Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Katherine Reinshagen
- Department of Radiology, Harvard Medical School, Boston, MA, USA.,Department of Radiology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA.,Department of Radiology, Massachusetts Eye and Ear Infirmary, Boston, MA, USA
| | - Xiang Li
- Department of Radiology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA.,Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Su-Chun Cheng
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Annie Bryant
- Department of Imaging, Dana-Farber Cancer Institute, Boston, MA, USA.,Department of Behavioral Neuroscience, Northeastern University, Boston, MA, USA
| | - Geoffrey S Young
- Department of Imaging, Dana-Farber Cancer Institute, Boston, MA, USA. .,Department of Radiology, Harvard Medical School, Boston, MA, USA. .,Department of Radiology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA.
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7
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Jerome NP, Miyazaki K, Collins DJ, Orton MR, d'Arcy JA, Wallace T, Moreno L, Pearson ADJ, Marshall LV, Carceller F, Leach MO, Zacharoulis S, Koh DM. Repeatability of derived parameters from histograms following non-Gaussian diffusion modelling of diffusion-weighted imaging in a paediatric oncological cohort. Eur Radiol 2017; 27:345-353. [PMID: 27003140 PMCID: PMC5127877 DOI: 10.1007/s00330-016-4318-2] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2015] [Revised: 02/29/2016] [Accepted: 03/02/2016] [Indexed: 12/18/2022]
Abstract
OBJECTIVES To examine repeatability of parameters derived from non-Gaussian diffusion models in data acquired in children with solid tumours. METHODS Paediatric patients (<16 years, n = 17) were scanned twice, 24 h apart, using DWI (6 b-values, 0-1000 mm-2 s) at 1.5 T in a prospective study. Tumour ROIs were drawn (3 slices) and all data fitted using IVIM, stretched exponential, and kurtosis models; percentage coefficients of variation (CV) calculated for each parameter at all ROI histogram centiles, including the medians. RESULTS The values for ADC, D, DDCα, α, and DDCK gave CV < 10 % down to the 5th centile, with sharp CV increases below 5th and above 95th centile. K, f, and D* showed increased CV (>30 %) over the histogram. ADC, D, DDCα, and DDCK were strongly correlated (ρ > 0.9), DDCα and α were not correlated (ρ = 0.083). CONCLUSION Perfusion- and kurtosis-related parameters displayed larger, more variable CV across the histogram, indicating observed clinical changes outside of D/DDC in these models should be interpreted with caution. Centiles below 5th for all parameters show high CV and are unreliable as diffusion metrics. The stretched exponential model behaved well for both DDCα and α, making it a strong candidate for modelling multiple-b-value diffusion imaging data. KEY POINTS • ADC has good repeatability as low 5th centile of the histogram distribution. • High CV was observed for all parameters at extremes of histogram. • Parameters from the stretched exponential model showed low coefficients of variation. • The median ADC, D, DDC α , and DDC K are highly correlated and repeatable. • Perfusion/kurtosis parameters showed high CV variations across their histogram distributions.
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Affiliation(s)
- Neil P Jerome
- Division of Radiotherapy & Imaging, The Institute of Cancer Research, Cancer Research UK Cancer Imaging Centre, 123 Old Brompton Road, London, SW7 3RP, UK
| | - Keiko Miyazaki
- Division of Radiotherapy & Imaging, The Institute of Cancer Research, Cancer Research UK Cancer Imaging Centre, 123 Old Brompton Road, London, SW7 3RP, UK
| | - David J Collins
- Division of Radiotherapy & Imaging, The Institute of Cancer Research, Cancer Research UK Cancer Imaging Centre, 123 Old Brompton Road, London, SW7 3RP, UK
| | - Matthew R Orton
- Division of Radiotherapy & Imaging, The Institute of Cancer Research, Cancer Research UK Cancer Imaging Centre, 123 Old Brompton Road, London, SW7 3RP, UK
| | - James A d'Arcy
- Division of Radiotherapy & Imaging, The Institute of Cancer Research, Cancer Research UK Cancer Imaging Centre, 123 Old Brompton Road, London, SW7 3RP, UK
| | - Toni Wallace
- Department of Radiology, Royal Marsden NHS Foundation Trust, Sutton, Surrey, SM2 5PT, UK
| | - Lucas Moreno
- Paediatric Drug Development Team, Division of Cancer Therapeutics and Clinical Studies, The Institute of Cancer Research, 123 Old Brompton Road, London, SW7 3RP, UK
- Hospital Niño Jesus, Av Menendez Pelayo 65, Madrid, Spain
- Paediatric Drug Development Unit, Children and Young People's Unit, Royal Marsden NHS Foundation Trust, Sutton, Surrey, SM2 5PT, UK
| | - Andrew D J Pearson
- Paediatric Drug Development Team, Division of Cancer Therapeutics and Clinical Studies, The Institute of Cancer Research, 123 Old Brompton Road, London, SW7 3RP, UK
- Paediatric Drug Development Unit, Children and Young People's Unit, Royal Marsden NHS Foundation Trust, Sutton, Surrey, SM2 5PT, UK
| | - Lynley V Marshall
- Paediatric Drug Development Team, Division of Cancer Therapeutics and Clinical Studies, The Institute of Cancer Research, 123 Old Brompton Road, London, SW7 3RP, UK
- Paediatric Drug Development Unit, Children and Young People's Unit, Royal Marsden NHS Foundation Trust, Sutton, Surrey, SM2 5PT, UK
| | - Fernando Carceller
- Paediatric Drug Development Team, Division of Cancer Therapeutics and Clinical Studies, The Institute of Cancer Research, 123 Old Brompton Road, London, SW7 3RP, UK
- Paediatric Drug Development Unit, Children and Young People's Unit, Royal Marsden NHS Foundation Trust, Sutton, Surrey, SM2 5PT, UK
| | - Martin O Leach
- Division of Radiotherapy & Imaging, The Institute of Cancer Research, Cancer Research UK Cancer Imaging Centre, 123 Old Brompton Road, London, SW7 3RP, UK.
| | - Stergios Zacharoulis
- Paediatric Drug Development Team, Division of Cancer Therapeutics and Clinical Studies, The Institute of Cancer Research, 123 Old Brompton Road, London, SW7 3RP, UK
- Paediatric Drug Development Unit, Children and Young People's Unit, Royal Marsden NHS Foundation Trust, Sutton, Surrey, SM2 5PT, UK
| | - Dow-Mu Koh
- Department of Radiology, Royal Marsden NHS Foundation Trust, Sutton, Surrey, SM2 5PT, UK
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Ceschin R, Kurland BF, Abberbock SR, Ellingson BM, Okada H, Jakacki RI, Pollack IF, Panigrahy A. Parametric Response Mapping of Apparent Diffusion Coefficient as an Imaging Biomarker to Distinguish Pseudoprogression from True Tumor Progression in Peptide-Based Vaccine Therapy for Pediatric Diffuse Intrinsic Pontine Glioma. AJNR Am J Neuroradiol 2015; 36:2170-6. [PMID: 26338910 DOI: 10.3174/ajnr.a4428] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2015] [Accepted: 04/05/2015] [Indexed: 01/08/2023]
Abstract
BACKGROUND AND PURPOSE Immune response to cancer therapy may result in pseudoprogression, which can only be identified retrospectively and may disrupt an effective therapy. This study assesses whether serial parametric response mapping (a voxel-by-voxel method of image analysis also known as functional diffusion mapping) analysis of ADC measurements following peptide-based vaccination may help prospectively distinguish progression from pseudoprogression in pediatric patients with diffuse intrinsic pontine gliomas. MATERIALS AND METHODS From 2009 to 2012, 21 children, 4-18 years of age, with diffuse intrinsic pontine gliomas were enrolled in a serial peptide-based vaccination protocol following radiation therapy. DWI was acquired before immunotherapy and at 6-week intervals during vaccine treatment. Pseudoprogression was identified retrospectively on the basis of clinical and radiographic findings, excluding DWI. Parametric response mapping was used to analyze 96 scans, comparing ADC measures at multiple time points (from the first vaccine to up to 12 weeks after the vaccine was halted) with prevaccine baseline values. Log-transformed fractional increased ADC, fractional decreased ADC, and parametric response mapping ratio (fractional increased ADC/fractional decreased ADC) were compared between patients with and without pseudoprogression, by using generalized estimating equations with inverse weighting by cluster size. RESULTS Median survival was 13.1 months from diagnosis (range, 6.4-24.9 months). Four of 21 children (19%) were assessed as experiencing pseudoprogression. Patients with pseudoprogression had higher fitted average log-transformed parametric response mapping ratios (P = .01) and fractional decreased ADCs (P = .0004), compared with patients without pseudoprogression. CONCLUSIONS Serial parametric response mapping of ADC, performed at multiple time points of therapy, may distinguish pseudoprogression from true progression in patients with diffuse intrinsic pontine gliomas treated with peptide-based vaccination.
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Affiliation(s)
- R Ceschin
- From the Departments of Radiology (R.C., A.P.) Biomedical Informatics (R.C., A.P.), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania Departments of Radiology (R.C., A.P.)
| | - B F Kurland
- Children's Hospital of Pittsburgh, University of Pittsburgh Cancer Institute (B.F.K., S.R.A., H.O., R.I.J., I.F.P., A.P.) Department of Biostatistics, Graduate School of Public Health (B.F.K.), University of Pittsburgh, Pittsburgh, Pennsylvania
| | - S R Abberbock
- Children's Hospital of Pittsburgh, University of Pittsburgh Cancer Institute (B.F.K., S.R.A., H.O., R.I.J., I.F.P., A.P.)
| | - B M Ellingson
- Department of Radiological Sciences (B.M.E.), University of California, Los Angeles, Los Angeles, California
| | - H Okada
- Surgery (H.O.) Neurosurgery (H.O., I.F.P.) Immunology (H.O.) Children's Hospital of Pittsburgh, University of Pittsburgh Cancer Institute (B.F.K., S.R.A., H.O., R.I.J., I.F.P., A.P.)
| | - R I Jakacki
- Pediatrics (R.I.J.) Pediatrics (R.I.J.) Children's Hospital of Pittsburgh, University of Pittsburgh Cancer Institute (B.F.K., S.R.A., H.O., R.I.J., I.F.P., A.P.)
| | - I F Pollack
- Neurosurgery (H.O., I.F.P.) Neurosurgery (I.F.P.) Children's Hospital of Pittsburgh, University of Pittsburgh Cancer Institute (B.F.K., S.R.A., H.O., R.I.J., I.F.P., A.P.)
| | - A Panigrahy
- From the Departments of Radiology (R.C., A.P.) Biomedical Informatics (R.C., A.P.), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania Departments of Radiology (R.C., A.P.) Children's Hospital of Pittsburgh, University of Pittsburgh Cancer Institute (B.F.K., S.R.A., H.O., R.I.J., I.F.P., A.P.)
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Miyazaki K, Jerome NP, Collins DJ, Orton MR, d’Arcy JA, Wallace T, Moreno L, Pearson ADJ, Marshall LV, Carceller F, Leach MO, Zacharoulis S, Koh DM. Demonstration of the reproducibility of free-breathing diffusion-weighted MRI and dynamic contrast enhanced MRI in children with solid tumours: a pilot study. Eur Radiol 2015; 25:2641-50. [PMID: 25773937 PMCID: PMC4529450 DOI: 10.1007/s00330-015-3666-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2014] [Revised: 01/30/2015] [Accepted: 02/12/2015] [Indexed: 12/22/2022]
Abstract
OBJECTIVES The objectives are to examine the reproducibility of functional MR imaging in children with solid tumours using quantitative parameters derived from diffusion-weighted (DW-) and dynamic contrast enhanced (DCE-) MRI. METHODS Patients under 16-years-of age with confirmed diagnosis of solid tumours (n = 17) underwent free-breathing DW-MRI and DCE-MRI on a 1.5 T system, repeated 24 hours later. DW-MRI (6 b-values, 0-1000 sec/mm(2)) enabled monoexponential apparent diffusion coefficient estimation using all (ADC0-1000) and only ≥100 sec/mm(2) (ADC100-1000) b-values. DCE-MRI was used to derive the transfer constant (K(trans)), the efflux constant (kep), the extracellular extravascular volume (ve), and the plasma fraction (vp), using a study cohort arterial input function (AIF) and the extended Tofts model. Initial area under the gadolinium enhancement curve and pre-contrast T1 were also calculated. Percentage coefficients of variation (CV) of all parameters were calculated. RESULTS The most reproducible cohort parameters were ADC100-1000 (CV = 3.26%), pre-contrast T1 (CV = 6.21%), and K(trans) (CV = 15.23%). The ADC100-1000 was more reproducible than ADC0-1000, especially extracranially (CV = 2.40% vs. 2.78%). The AIF (n = 9) derived from this paediatric population exhibited sharper and earlier first-pass and recirculation peaks compared with the literature's adult population average. CONCLUSIONS Free-breathing functional imaging protocols including DW-MRI and DCE-MRI are well-tolerated in children aged 6 - 15 with good to moderate measurement reproducibility. KEY POINTS • Diffusion MRI protocol is feasible and well-tolerated in a paediatric oncology population. • DCE-MRI for pharmacokinetic evaluation is feasible and well tolerated in a paediatric oncology population. • Paediatric arterial input function (AIF) shows systematic differences from the adult population-average AIF. • Variation of quantitative parameters from paired functional MRI measurements were within 20%.
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Affiliation(s)
- Keiko Miyazaki
- Cancer Research UK Cancer Imaging Centre at The Institute of Cancer Research, London, SM2 5NG UK
| | - Neil P. Jerome
- Cancer Research UK Cancer Imaging Centre at The Institute of Cancer Research, London, SM2 5NG UK
| | - David J. Collins
- Cancer Research UK Cancer Imaging Centre at The Institute of Cancer Research, London, SM2 5NG UK
| | - Matthew R. Orton
- Cancer Research UK Cancer Imaging Centre at The Institute of Cancer Research, London, SM2 5NG UK
| | - James A. d’Arcy
- Cancer Research UK Cancer Imaging Centre at The Institute of Cancer Research, London, SM2 5NG UK
| | - Toni Wallace
- Department of Radiology, Royal Marsden Hospital, London, England UK
| | - Lucas Moreno
- Paediatric Drug Development Team, Divisions of Cancer Therapeutics and Clinical Studies, The Institute of Cancer Research, London, SM2 5NG UK
- Clinical Research Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernandez Almagro 3, 28029 Madrid, Spain
- Paediatric Drug Development Unit, Children and Young People’s Unit, The Royal Marsden NHS Foundation Trust, Downs Road, Sutton, SM2 5PT UK
| | - Andrew D. J. Pearson
- Paediatric Drug Development Team, Divisions of Cancer Therapeutics and Clinical Studies, The Institute of Cancer Research, London, SM2 5NG UK
- Paediatric Drug Development Unit, Children and Young People’s Unit, The Royal Marsden NHS Foundation Trust, Downs Road, Sutton, SM2 5PT UK
| | - Lynley V. Marshall
- Paediatric Drug Development Team, Divisions of Cancer Therapeutics and Clinical Studies, The Institute of Cancer Research, London, SM2 5NG UK
- Paediatric Drug Development Unit, Children and Young People’s Unit, The Royal Marsden NHS Foundation Trust, Downs Road, Sutton, SM2 5PT UK
| | - Fernando Carceller
- Paediatric Drug Development Team, Divisions of Cancer Therapeutics and Clinical Studies, The Institute of Cancer Research, London, SM2 5NG UK
- Paediatric Drug Development Unit, Children and Young People’s Unit, The Royal Marsden NHS Foundation Trust, Downs Road, Sutton, SM2 5PT UK
| | - Martin O. Leach
- Cancer Research UK Cancer Imaging Centre at The Institute of Cancer Research, London, SM2 5NG UK
| | - Stergios Zacharoulis
- Paediatric Drug Development Team, Divisions of Cancer Therapeutics and Clinical Studies, The Institute of Cancer Research, London, SM2 5NG UK
- Paediatric Drug Development Unit, Children and Young People’s Unit, The Royal Marsden NHS Foundation Trust, Downs Road, Sutton, SM2 5PT UK
| | - Dow-Mu Koh
- Department of Radiology, Royal Marsden Hospital, London, England UK
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Elson A, Bovi J, Siker M, Schultz C, Paulson E. Evaluation of absolute and normalized apparent diffusion coefficient (ADC) values within the post-operative T2/FLAIR volume as adverse prognostic indicators in glioblastoma. J Neurooncol 2015; 122:549-58. [PMID: 25700835 DOI: 10.1007/s11060-015-1743-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2014] [Accepted: 02/14/2015] [Indexed: 02/03/2023]
Abstract
To evaluate the association of normalized and absolute ADC metrics with progression free survival (PFS) and overall survival (OS) in patients treated for glioblastoma multiforme (GBM). Fifty-two patients with preradiotherapy diffusion weighted imaging treated with post-operative chemoradiation for GBM were evaluated. Region of interest analysis for ADC metrics including mean and minimum ADC value (ADCmean) and (ADCmin) was performed within the T2/FLAIR volume. Normalized (N)ADC values were generated relative to contralateral white matter. PFS and OS were analyzed relative to ADC parameters using a regression model. Kaplan-Meier and Cox proportional hazards analysis with respect to (N)ADCmean, and (N)ADCmin was performed. A (N)ADC threshold <1.3 within the T2/FLAIR volume was analyzed with respect to PFS and OS. Regression analysis indicated that normalized ADC values provide the strongest association with PFS and OS. Kaplan-Meier analysis revealed a non-significant trend toward inferior PFS and OS associated with (N)ADCmean <1.7, and a significant decrement to PFS and OS associated with (N)ADCmin <0.3. (N)ADCmin was a significant prognostic factor when taking into account age, performance status, and extent of resection. ADC thresholding analysis revealed that a retained volume of >0.45 cc per mL FLAIR volume was associated with a trend toward inferior PFS and OS. In the post-operative, pre-radiotherapy setting, the (N)ADCmin is the strongest predictor of outcomes in patients treated for GBM. ADC thresholding analysis indicates that a large volume of normalized ADC value <1.3 may be associated with adverse outcomes.
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Affiliation(s)
- Andrew Elson
- Department of Radiation Oncology, Medical College of Wisconsin, 9200 W. Wisconsin Avenue, Froedtert Hospital East Clinics 3rd Floor, Milwaukee, WI, 53226, USA,
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Foti PV, Farina R, Coronella M, Palmucci S, Montana A, Sigona A, Reibaldi M, Longo A, Russo A, Avitabile T, Caltabiano R, Puzzo L, Ragusa M, Mariotti C, Milone P, Ettorre GC. Diffusion-weighted magnetic resonance imaging for predicting and detecting the response of ocular melanoma to proton beam therapy: initial results. Radiol Med 2015; 120:526-35. [PMID: 25578783 DOI: 10.1007/s11547-014-0488-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2014] [Accepted: 09/15/2014] [Indexed: 10/24/2022]
Abstract
PURPOSE The aim of this study was to investigate the utility of diffusion-weighted magnetic resonance (MR) imaging for prediction and early detection of response to proton beam therapy in ocular melanoma. MATERIALS AND METHODS Ten ocular melanoma patients treated with proton beam therapy were enrolled in the study. All patients underwent conventional MR imaging and diffusion-weighted imaging (DWI) before the start of therapy, and after 1, 3 and 6 months of therapy. Tumour volumes and apparent diffusion coefficient (ADC) values of ocular lesions were measured at each examination. Tumour volumes and mean ADC measurements of the four examination series were compared; correlation of ADC values and tumour regression was investigated. RESULTS Mean ADC value of ocular melanomas significantly increased as early as 3 months after therapy; tumour volume significantly decreased as early as 6 months after therapy. The ADC values of ocular melanomas before therapy significantly correlated with tumour regression. CONCLUSIONS DWI may provide an early surrogate biomarker for prediction and early detection of tumour response to eye-preserving therapies in ocular melanoma.
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Affiliation(s)
- Pietro Valerio Foti
- Dipartimento Specialità Medico-Chirurgiche, Sezione di Scienze Radiologiche, Università di Catania, Via Santa Sofia 78, 95123, Catania, Italy,
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Apparent diffusion coefficient of intracranial germ cell tumors. J Neurooncol 2014; 121:565-71. [DOI: 10.1007/s11060-014-1668-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2014] [Accepted: 11/13/2014] [Indexed: 10/24/2022]
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