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MR Imaging of Pediatric Brain Tumors. Diagnostics (Basel) 2022; 12:diagnostics12040961. [PMID: 35454009 PMCID: PMC9029699 DOI: 10.3390/diagnostics12040961] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 04/02/2022] [Accepted: 04/05/2022] [Indexed: 02/04/2023] Open
Abstract
Primary brain tumors are the most common solid neoplasms in children and a leading cause of mortality in this population. MRI plays a central role in the diagnosis, characterization, treatment planning, and disease surveillance of intracranial tumors. The purpose of this review is to provide an overview of imaging methodology, including conventional and advanced MRI techniques, and illustrate the MRI appearances of common pediatric brain tumors.
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Kurokawa R, Umemura Y, Capizzano A, Kurokawa M, Baba A, Holmes A, Kim J, Ota Y, Srinivasan A, Moritani T. Dynamic susceptibility contrast and diffusion-weighted MRI in posterior fossa pilocytic astrocytoma and medulloblastoma. J Neuroimaging 2022; 32:511-520. [PMID: 34997668 DOI: 10.1111/jon.12962] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Revised: 12/16/2021] [Accepted: 12/17/2021] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND AND PURPOSE The utility of perfusion MRI in distinguishing between pilocytic astrocytoma (PA) and medulloblastoma (MB) is unclear. This study aimed to evaluate the diagnostic and prognostic performance of dynamic susceptibility contrast (DSC)-MRI parameters and apparent diffusion coefficient (ADC) values between PA and MB. METHODS Between January 2012 and August 2021, 49 (median, 7 years [range, 1-28 years]; 28 females) and 35 (median, 8 years [1-24 years]; 12 females) patients with pathologically confirmed PA and MB, respectively, were included. The normalized relative cerebral blood volume and flow (nrCBV and nrCBF) and mean and minimal normalized ADC (nADCmean and nADCmin) values were calculated using volume-of-interest analyses. Diagnostic performance and Pearson's correlation with progression-free survival were also evaluated. RESULTS The MB group showed a significantly higher nrCBV and nrCBF (nrCBV: 1.69 [0.93-4.23] vs. 0.95 [range, 0.37-2.28], p = .0032; nrCBF: 1.62 [0.93-3.16] vs. 1.07 [0.46-2.26], p = .0084) and significantly lower nADCmean and nADCmin (nADCmean: 0.97 [0.70-1.68] vs. 2.21 [1.44-2.80], p < .001; nADCmin: 0.50 [0.19-0.89] vs. 1.42 [0.89-2.20], p < .001) than the PA group. All parameters exhibited good diagnostic ability (accuracy >0.80) with nADCmin achieving the highest score (accuracy = 1). A moderate correlation was found between nADCmean and progression-free survival for MB (r = 0.44, p = .0084). CONCLUSIONS DSC-MRI parameters and ADC values were useful for distinguishing between PA and MB. A lower ADC indicated an unfavorable MB prognosis, but the DSC-MRI parameters did not correlate with progression-free survival in either group.
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Affiliation(s)
- Ryo Kurokawa
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Yoshie Umemura
- Department of Neurology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Aristides Capizzano
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Mariko Kurokawa
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Akira Baba
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Adam Holmes
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - John Kim
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Yoshiaki Ota
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Ashok Srinivasan
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Toshio Moritani
- Division of Neuroradiology, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
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Dasgupta A, Maitre M, Pungavkar S, Gupta T. Magnetic Resonance Imaging in the Contemporary Management of Medulloblastoma: Current and Emerging Applications. Methods Mol Biol 2022; 2423:187-214. [PMID: 34978700 DOI: 10.1007/978-1-0716-1952-0_18] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Medulloblastoma, the most common malignant primary brain tumor in children, is now considered to comprise of four distinct molecular subgroups-wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4 medulloblastoma, each associated with distinct developmental origins, unique transcriptional profiles, diverse phenotypes, and variable clinical behavior. Due to its exquisite anatomic resolution, multiparametric nature, and ability to image the entire craniospinal axis, magnetic resonance imaging (MRI) is the preferred and recommended first-line imaging modality for suspected brain tumors including medulloblastoma. Preoperative MRI can reliably differentiate medulloblastoma from other common childhood posterior fossa masses such as ependymoma, pilocytic astrocytoma, and brainstem glioma. On T1-weighted images, medulloblastoma is generally iso- to hypointense, while on T2-weighted images, the densely packed cellular component of the tumor is significantly hypointense and displays restricted diffusion on diffusion-weighted imaging. Following intravenous gadolinium, medulloblastoma shows significant but variable and heterogeneous contrast enhancement. Given the propensity of neuraxial spread in medulloblastoma, sagittal fat-suppressed T1-postcontrast spinal MRI is recommended to rule out leptomeningeal metastases for accurate staging. Following neurosurgical excision, postoperative MRI done within 24-48 h confirms the extent of resection, accurately quantifying residual tumor burden imperative for risk assignment. Post-treatment MRI is needed to assess response and effectiveness of adjuvant radiotherapy and systemic chemotherapy. After completion of planned therapy, surveillance MRI is recommended periodically on follow-up for early detection of recurrence for timely institution of salvage therapy, as well as for monitoring treatment-related late complications. Recent studies suggest that preoperative MRI can reliably identify SHH and Group 4 medulloblastoma but has suboptimal predictive accuracy for WNT and Group 3 tumors. In this review, we focus on the role of MRI in the diagnosis, staging, and quantifying residual disease; post-treatment response assessment; and periodic surveillance, and provide a brief summary on radiogenomics in the contemporary management of medulloblastoma.
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Affiliation(s)
- Archya Dasgupta
- Department of Radiation Oncology, Neuro-Oncology Disease Management Group, Tata Memorial Centre, Homi Bhabha National Institute (HBNI), Mumbai, India.
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.
| | - Madan Maitre
- Department of Radiation Oncology, Neuro-Oncology Disease Management Group, Tata Memorial Centre, Homi Bhabha National Institute (HBNI), Mumbai, India
| | - Sona Pungavkar
- Department of Radiodiagnosis and Imaging, Global Hospitals, Mumbai, India
| | - Tejpal Gupta
- Department of Radiation Oncology, Neuro-Oncology Disease Management Group, Tata Memorial Centre, Homi Bhabha National Institute (HBNI), Mumbai, India
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Franco P, Huebschle I, Simon-Gabriel CP, Dacca K, Schnell O, Beck J, Mast H, Urbach H, Wuertemberger U, Prinz M, Hosp JA, Delev D, Mader I, Heiland DH. Mapping of Metabolic Heterogeneity of Glioma Using MR-Spectroscopy. Cancers (Basel) 2021; 13:cancers13102417. [PMID: 34067701 PMCID: PMC8155922 DOI: 10.3390/cancers13102417] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 05/13/2021] [Accepted: 05/15/2021] [Indexed: 01/04/2023] Open
Abstract
Simple Summary Radiomics is a research field that integrates radiological and genetic information, but the application of the techniques that have been developed to this purpose have not been widely established in daily clinical practice. The purpose of our study is the development of a straightforward tool that can easily be used to preoperatively predict and correlate the metabolic signature of different CNS-lesions. Particularly in gliomas, we hope to integrate the molecular profile of these tumors into our prediction model. Our goal is to deliver an open-software tool with the intention of advancing the diagnostic work-up of gliomas to the latest standards. Abstract Proton magnetic resonance spectroscopy (1H-MRS) delivers information about the non-invasive metabolic landscape of brain pathologies. 1H-MRS is used in clinical setting in addition to MRI for diagnostic, prognostic and treatment response assessments, but the use of this radiological tool is not entirely widespread. The importance of developing automated analysis tools for 1H-MRS lies in the possibility of a straightforward application and simplified interpretation of metabolic and genetic data that allow for incorporation into the daily practice of a broad audience. Here, we report a prospective clinical imaging trial (DRKS00019855) which aimed to develop a novel MR-spectroscopy-based algorithm for in-depth characterization of brain lesions and prediction of molecular traits. Dimensional reduction of metabolic profiles demonstrated distinct patterns throughout pathologies. We combined a deep autoencoder and multi-layer linear discriminant models for voxel-wise prediction of the molecular profile based on MRS imaging. Molecular subtypes were predicted by an overall accuracy of 91.2% using a classifier score. Our study indicates a first step into combining the metabolic and molecular traits of lesions for advancing the pre-operative diagnostic workup of brain tumors and improve personalized tumor treatment.
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Affiliation(s)
- Pamela Franco
- Department of Neurosurgery, Medical Center-University of Freiburg, 79106 Freiburg, Germany; (I.H.); (K.D.); (O.S.); (J.B.); (D.H.H.)
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (C.P.S.-G.); (H.U.); (U.W.); (M.P.); (J.A.H.); (I.M.)
- Correspondence: ; Tel.: +49-(0)-761-270-50010; Fax: +49-(0)-761-270-51020
| | - Irene Huebschle
- Department of Neurosurgery, Medical Center-University of Freiburg, 79106 Freiburg, Germany; (I.H.); (K.D.); (O.S.); (J.B.); (D.H.H.)
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (C.P.S.-G.); (H.U.); (U.W.); (M.P.); (J.A.H.); (I.M.)
| | - Carl Philipp Simon-Gabriel
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (C.P.S.-G.); (H.U.); (U.W.); (M.P.); (J.A.H.); (I.M.)
- Department of Radiology, Medical Center-University of Freiburg, 79106 Freiburg, Germany
| | - Karam Dacca
- Department of Neurosurgery, Medical Center-University of Freiburg, 79106 Freiburg, Germany; (I.H.); (K.D.); (O.S.); (J.B.); (D.H.H.)
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (C.P.S.-G.); (H.U.); (U.W.); (M.P.); (J.A.H.); (I.M.)
| | - Oliver Schnell
- Department of Neurosurgery, Medical Center-University of Freiburg, 79106 Freiburg, Germany; (I.H.); (K.D.); (O.S.); (J.B.); (D.H.H.)
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (C.P.S.-G.); (H.U.); (U.W.); (M.P.); (J.A.H.); (I.M.)
| | - Juergen Beck
- Department of Neurosurgery, Medical Center-University of Freiburg, 79106 Freiburg, Germany; (I.H.); (K.D.); (O.S.); (J.B.); (D.H.H.)
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (C.P.S.-G.); (H.U.); (U.W.); (M.P.); (J.A.H.); (I.M.)
| | - Hansjoerg Mast
- Department of Neuroradiology, Medical Center-University of Freiburg, 79106 Freiburg, Germany;
| | - Horst Urbach
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (C.P.S.-G.); (H.U.); (U.W.); (M.P.); (J.A.H.); (I.M.)
- Department of Neuroradiology, Medical Center-University of Freiburg, 79106 Freiburg, Germany;
| | - Urs Wuertemberger
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (C.P.S.-G.); (H.U.); (U.W.); (M.P.); (J.A.H.); (I.M.)
- Department of Neuroradiology, Medical Center-University of Freiburg, 79106 Freiburg, Germany;
| | - Marco Prinz
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (C.P.S.-G.); (H.U.); (U.W.); (M.P.); (J.A.H.); (I.M.)
- Institute of Neuropathology, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
- Signaling Research Centers BIOSS and CIBSS, University of Freiburg, 79106 Freiburg, Germany
- Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Jonas A. Hosp
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (C.P.S.-G.); (H.U.); (U.W.); (M.P.); (J.A.H.); (I.M.)
- Department of Neurology and Neuroscience, Medical Center-University of Freiburg, 79106 Freiburg, Germany
| | - Daniel Delev
- Department of Neurosurgery, RWTH University of Aachen, 52074 Aachen, Germany;
| | - Irina Mader
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (C.P.S.-G.); (H.U.); (U.W.); (M.P.); (J.A.H.); (I.M.)
- Department of Neuroradiology, Medical Center-University of Freiburg, 79106 Freiburg, Germany;
- Specialist Centre for Radiology, Schoen Clinic, 83569 Vogtareuth, Germany
| | - Dieter Henrik Heiland
- Department of Neurosurgery, Medical Center-University of Freiburg, 79106 Freiburg, Germany; (I.H.); (K.D.); (O.S.); (J.B.); (D.H.H.)
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (C.P.S.-G.); (H.U.); (U.W.); (M.P.); (J.A.H.); (I.M.)
- Microenvironment and Immunology Research Laboratory, Medical Center-University of Freiburg, 79106 Freiburg, Germany
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Woitek R, Gallagher FA. The use of hyperpolarised 13C-MRI in clinical body imaging to probe cancer metabolism. Br J Cancer 2021; 124:1187-1198. [PMID: 33504974 PMCID: PMC8007617 DOI: 10.1038/s41416-020-01224-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2019] [Revised: 11/19/2020] [Accepted: 12/02/2020] [Indexed: 01/30/2023] Open
Abstract
Metabolic reprogramming is one of the hallmarks of cancer and includes the Warburg effect, which is exhibited by many tumours. This can be exploited by positron emission tomography (PET) as part of routine clinical cancer imaging. However, an emerging and alternative method to detect altered metabolism is carbon-13 magnetic resonance imaging (MRI) following injection of hyperpolarised [1-13C]pyruvate. The technique increases the signal-to-noise ratio for the detection of hyperpolarised 13C-labelled metabolites by several orders of magnitude and facilitates the dynamic, noninvasive imaging of the exchange of 13C-pyruvate to 13C-lactate over time. The method has produced promising preclinical results in the area of oncology and is currently being explored in human imaging studies. The first translational studies have demonstrated the safety and feasibility of the technique in patients with prostate, renal, breast and pancreatic cancer, as well as revealing a successful response to treatment in breast and prostate cancer patients at an earlier stage than multiparametric MRI. This review will focus on the strengths of the technique and its applications in the area of oncological body MRI including noninvasive characterisation of disease aggressiveness, mapping of tumour heterogeneity, and early response assessment. A comparison of hyperpolarised 13C-MRI with state-of-the-art multiparametric MRI is likely to reveal the unique additional information and applications offered by the technique.
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Affiliation(s)
- Ramona Woitek
- Department of Radiology, University of Cambridge, Cambridge, UK.
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
- Cancer Research UK Cambridge Centre, Cambridge, UK.
| | - Ferdia A Gallagher
- Department of Radiology, University of Cambridge, Cambridge, UK
- Cancer Research UK Cambridge Centre, Cambridge, UK
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