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Śledzińska-Bebyn P, Furtak J, Bebyn M, Serafin Z. Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling. Magn Reson Imaging 2024; 112:63-81. [PMID: 38914147 DOI: 10.1016/j.mri.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/20/2024] [Accepted: 06/20/2024] [Indexed: 06/26/2024]
Abstract
This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.
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Affiliation(s)
- Paulina Śledzińska-Bebyn
- Department of Radiology, 10th Military Research Hospital and Polyclinic, 85-681 Bydgoszcz, Poland.
| | - Jacek Furtak
- Department of Clinical Medicine, Faculty of Medicine, University of Science and Technology, Bydgoszcz, Poland; Department of Neurosurgery, 10th Military Research Hospital and Polyclinic, 85-681 Bydgoszcz, Poland
| | - Marek Bebyn
- Department of Internal Diseases, 10th Military Clinical Hospital and Polyclinic, 85-681 Bydgoszcz, Poland
| | - Zbigniew Serafin
- Department of Radiology and Diagnostic Imaging, Nicolaus Copernicus University, Collegium Medicum, Bydgoszcz, Poland
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Noble DJ, Ramaesh R, Brothwell M, Elumalai T, Barrett T, Stillie A, Paterson C, Ajithkumar T. The Evolving Role of Novel Imaging Techniques for Radiotherapy Planning. Clin Oncol (R Coll Radiol) 2024; 36:514-526. [PMID: 38937188 DOI: 10.1016/j.clon.2024.05.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Revised: 05/20/2024] [Accepted: 05/30/2024] [Indexed: 06/29/2024]
Abstract
The ability to visualise cancer with imaging has been crucial to the evolution of modern radiotherapy (RT) planning and delivery. And as evolving RT technologies deliver increasingly precise treatment, the importance of accurate identification and delineation of disease assumes ever greater significance. However, innovation in imaging technology has matched that seen with RT delivery platforms, and novel imaging techniques are a focus of much research activity. How these imaging modalities may alter and improve the diagnosis and staging of cancer is an important question, but already well served by the literature. What is less clear is how novel imaging techniques may influence and improve practical and technical aspects of RT planning and delivery. In this review, current gold standard approaches to integration of imaging, and potential future applications of bleeding-edge imaging technology into RT planning pathways are explored.
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Affiliation(s)
- D J Noble
- Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK; Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK.
| | - R Ramaesh
- Department of Radiology, Western General Hospital, Edinburgh, UK
| | - M Brothwell
- Department of Clinical Oncology, University College London Hospitals, London, UK
| | - T Elumalai
- Department of Oncology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, UK
| | - T Barrett
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, UK
| | - A Stillie
- Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - C Paterson
- Beatson West of Scotland Cancer Centre, Great Western Road, Glasgow G12 0YN, UK
| | - T Ajithkumar
- Department of Oncology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, UK
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3
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Flies CM, Snijders TJ, De Leeuw BI, van Maren EA, Kersten BJP, Verhoeff JJC, De Vos FYF, Robe PA, Hendrikse J, Dankbaar JW. The Differentiation between Progressive Disease and Treatment-Induced Effects with Perfusion-Weighted Arterial Spin-Labeling in High-Grade Gliomas. AJNR Am J Neuroradiol 2024; 45:920-926. [PMID: 38871374 DOI: 10.3174/ajnr.a8336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 02/05/2024] [Indexed: 06/15/2024]
Abstract
BACKGROUND AND PURPOSE Treatment-induced effects are difficult to differentiate from progressive disease in radiologically progressing diffuse gliomas after treatment. This retrospective, single-center cohort study investigated the diagnostic value of arterial spin-labeling perfusion in differentiating progressive disease from treatment-induced effects in irradiated patients with a high-grade glioma. MATERIALS AND METHODS Adults with a high-grade glioma diagnosed between January 1, 2012, and December 31, 2018, with a new or increasing contrast-enhancing lesion after radiotherapy with or without chemotherapy and arterial spin-labeling were consecutively included. Arterial spin-labeling is part of the routine follow-up examinations of patients with a high-grade glioma. The outcomes of progressive disease or treatment-induced effects were defined after histologic or >6 weeks radiologic follow-up. Two neuroradiologists graded the arterial spin-labeling visually as negative (hypointense to gray matter) or positive (iso-/hyperintense). Additionally, the arterial spin-labeling signal intensity in the enhancing lesion was compared quantitatively with that in the contralateral normal brain. Diagnostic test properties and the Cohen κ inter- and intrarater reliability were determined. We present data according to the time after radiation therapy. RESULTS We included 141 patients with 173 lesions (median age, 63 years). Ninety-four (54%) lesions showed treatment-induced effects, and 79 (46%), progressive disease. For visual analysis, the ORs of an arterial spin-labeling positive for progressive disease in the group with progression within 3, between 3 and 6, and after 6 months after radiation therapy were 0.65 (95% CI, 0.28-1.51; P = .319), 3.5 (95% CI, 0.69-17.89; P = .132), and 6.8 (95% CI, 1.48-32; P = .014). The areas under the curve were 0.456, 0.652, and 0.719. In quantitative analysis, the areas under the curve were 0.520, 0.588, and 0.587 in these groups. Inter- and intrarater reliability coefficients were 0.67 and 0.62. CONCLUSIONS Arterial spin-labeling performed poorly in differentiating progressive disease from treatment-induced effects in high-grade gliomas within 6 months after radiation therapy, with fair performance after this period. Arterial spin-labeling may need to be combined with other imaging features and clinical information for better performance.
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Affiliation(s)
- Christina Maria Flies
- From the Department of Neurology and Neurosurgery (C.M.F., T.J.S., B.I.d.L., B.J.P.K., P.A.R.), UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Tom Jan Snijders
- From the Department of Neurology and Neurosurgery (C.M.F., T.J.S., B.I.d.L., B.J.P.K., P.A.R.), UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Beverly Iendra De Leeuw
- From the Department of Neurology and Neurosurgery (C.M.F., T.J.S., B.I.d.L., B.J.P.K., P.A.R.), UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Emiel Alexander van Maren
- Department of Radiology (E.A.v.M., J.H., J.W.D.), University Medical Center Utrecht, Utrecht, the Netherlands
| | - Bart Jean Pieter Kersten
- From the Department of Neurology and Neurosurgery (C.M.F., T.J.S., B.I.d.L., B.J.P.K., P.A.R.), UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
- Faculty of Medicine (B.J.P.K.), Utrecht University, Utrecht, the Netherlands
| | | | - Filip Yves Francine De Vos
- Department of Medical Oncology (F.Y.F.D.V.), University Medical Center Utrecht, Utrecht, the Netherlands
| | - Pierre Alain Robe
- From the Department of Neurology and Neurosurgery (C.M.F., T.J.S., B.I.d.L., B.J.P.K., P.A.R.), UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Jeroen Hendrikse
- Department of Radiology (E.A.v.M., J.H., J.W.D.), University Medical Center Utrecht, Utrecht, the Netherlands
| | - Jan Willem Dankbaar
- Department of Radiology (E.A.v.M., J.H., J.W.D.), University Medical Center Utrecht, Utrecht, the Netherlands
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Sollmann N, Hoffmann G, Schramm S, Reichert M, Hernandez Petzsche M, Strobel J, Nigris L, Kloth C, Rosskopf J, Börner C, Bonfert M, Berndt M, Grön G, Müller HP, Kassubek J, Kreiser K, Koerte IK, Liebl H, Beer A, Zimmer C, Beer M, Kaczmarz S. Arterial Spin Labeling (ASL) in Neuroradiological Diagnostics - Methodological Overview and Use Cases. ROFO-FORTSCHR RONTG 2024; 196:36-51. [PMID: 37467779 DOI: 10.1055/a-2119-5574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/21/2023]
Abstract
BACKGROUND Arterial spin labeling (ASL) is a magnetic resonance imaging (MRI)-based technique using labeled blood-water of the brain-feeding arteries as an endogenous tracer to derive information about brain perfusion. It enables the assessment of cerebral blood flow (CBF). METHOD This review aims to provide a methodological and technical overview of ASL techniques, and to give examples of clinical use cases for various diseases affecting the central nervous system (CNS). There is a special focus on recent developments including super-selective ASL (ssASL) and time-resolved ASL-based magnetic resonance angiography (MRA) and on diseases commonly not leading to characteristic alterations on conventional structural MRI (e. g., concussion or migraine). RESULTS ASL-derived CBF may represent a clinically relevant parameter in various pathologies such as cerebrovascular diseases, neoplasms, or neurodegenerative diseases. Furthermore, ASL has also been used to investigate CBF in mild traumatic brain injury or migraine, potentially leading to the establishment of imaging-based biomarkers. Recent advances made possible the acquisition of ssASL by selective labeling of single brain-feeding arteries, enabling spatial perfusion territory mapping dependent on blood flow of a specific preselected artery. Furthermore, ASL-based MRA has been introduced, providing time-resolved delineation of single intracranial vessels. CONCLUSION Perfusion imaging by ASL has shown promise in various diseases of the CNS. Given that ASL does not require intravenous administration of a gadolinium-based contrast agent, it may be of particular interest for investigations in pediatric cohorts, patients with impaired kidney function, patients with relevant allergies, or patients that undergo serial MRI for clinical indications such as disease monitoring. KEY POINTS · ASL is an MRI technique that uses labeled blood-water as an endogenous tracer for brain perfusion imaging.. · It allows the assessment of CBF without the need for administration of a gadolinium-based contrast agent.. · CBF quantification by ASL has been used in several pathologies including brain tumors or neurodegenerative diseases.. · Vessel-selective ASL methods can provide brain perfusion territory mapping in cerebrovascular diseases.. · ASL may be of particular interest in patient cohorts with caveats concerning gadolinium administration..
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Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- cBrain, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Gabriel Hoffmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Severin Schramm
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Miriam Reichert
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Moritz Hernandez Petzsche
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Joachim Strobel
- Department of Nuclear Medicine, University Hospital Ulm, Ulm, Germany
| | - Lorenzo Nigris
- cBrain, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Christopher Kloth
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Johannes Rosskopf
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Section of Neuroradiology, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Corinna Börner
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- LMU Hospital, Department of Pediatrics - Dr. von Hauner Children's Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
- LMU Center for Children with Medical Complexity - iSPZ Hauner, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Michaela Bonfert
- LMU Hospital, Department of Pediatrics - Dr. von Hauner Children's Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
- LMU Center for Children with Medical Complexity - iSPZ Hauner, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Maria Berndt
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Georg Grön
- Department of Psychiatry and Psychotherapy III, University Hospital Ulm, Ulm, Germany
| | | | - Jan Kassubek
- Department of Neurology, University Hospital Ulm, Ulm, Germany
- German Center for Neurodegenerative Diseases (DZNE), Ulm University, Ulm, Germany
| | - Kornelia Kreiser
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Radiology and Neuroradiology, Universitäts- und Rehabilitationskliniken Ulm, Ulm, Germany
| | - Inga K Koerte
- cBrain, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Boston, United States
- Department of Psychiatry, Harvard Medical School, Massachusetts General Hospital, Boston, United States
| | - Hans Liebl
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Radiology, Berufsgenossenschaftliche Unfallklinik Murnau, Murnau, Germany
| | - Ambros Beer
- Department of Nuclear Medicine, University Hospital Ulm, Ulm, Germany
- MoMan - Center for Translational Imaging, University Hospital Ulm, Ulm, Germany
- i2SouI - Innovative Imaging in Surgical Oncology, University Hospital Ulm, Ulm, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- MoMan - Center for Translational Imaging, University Hospital Ulm, Ulm, Germany
- i2SouI - Innovative Imaging in Surgical Oncology, University Hospital Ulm, Ulm, Germany
| | - Stephan Kaczmarz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Market DACH, Philips GmbH, Hamburg, Germany
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Teunissen WHT, Lavrova A, van den Bent M, van der Hoorn A, Warnert EAH, Smits M. Arterial spin labelling MRI for brain tumour surveillance: do we really need cerebral blood flow maps? Eur Radiol 2023; 33:8005-8013. [PMID: 37566264 PMCID: PMC10598159 DOI: 10.1007/s00330-023-10099-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 06/09/2023] [Accepted: 07/01/2023] [Indexed: 08/12/2023]
Abstract
OBJECTIVES Arterial spin labelling (ASL) perfusion MRI is one of the available advanced MRI techniques for brain tumour surveillance. The first aim of this study was to investigate the correlation between quantitative cerebral blood flow (CBF) and non-quantitative perfusion weighted imaging (ASL-PWI) measurements. The second aim was to investigate the diagnostic accuracy of ASL-CBF and ASL-PWI measurements as well as visual assessment for identifying tumour progression. METHODS A consecutive cohort of patients who underwent 3-T MRI surveillance containing ASL for treated brain tumours was used. ROIs were drawn in representative parts of tumours in the ASL-CBF maps and copied to the ASL-PWI. ASL-CBF ratios and ASL-PWI ratios of the tumour ROI versus normal appearing white matter (NAWM) were correlated (Pearson correlation) and AUCs were calculated to assess diagnostic accuracy. Additionally, lesions were visually classified as hypointense, isointense, or hyperintense. We calculated accuracy at two thresholds: low threshold (between hypointense-isointense) and high threshold (between isointense-hyperintense). RESULTS A total of 173 lesions, both enhancing and non-enhancing, measured in 115 patients (93 glioma, 16 metastasis, and 6 lymphoma) showed a very high correlation of 0.96 (95% CI: 0.88-0.99) between ASL-CBF ratios and ASL-PWI ratios. AUC was 0.76 (95%CI: 0.65-0.88) for ASL-CBF ratios and 0.72 (95%CI: 0.58-0.85) for ASL-PWI ratios. Diagnostic accuracy of visual assessment for enhancing lesions was 0.72. CONCLUSION ASL-PWI ratios and ASL-CBF ratios showed a high correlation and comparable AUCs; therefore, quantification of ASL-CBF could be omitted in these patients. Visual classification had comparable diagnostic accuracy to the ASL-PWI or ASL-CBF ratios. CLINICAL RELEVANCE STATEMENT This study shows that CBF quantification of ASL perfusion MRI could be omitted for brain tumour surveillance and that visual assessment provides the same diagnostic accuracy. This greatly reduces the complexity of the use of ASL in routine clinical practice. KEY POINTS • Arterial spin labelling MRI for clinical brain tumour surveillance is undervalued and underinvestigated. • Non-quantitative and quantitative arterial spin labelling assessments show high correlation and comparable diagnostic accuracy. • Quantification of arterial spin labelling MRI could be omitted to improve daily clinical workflow.
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Affiliation(s)
- Wouter H T Teunissen
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
- Medical Delta, Delft, The Netherlands.
| | - Anna Lavrova
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Radiology, University of Michigan Hospital, Ann Arbor, MI, USA
| | - Martin van den Bent
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
- Department of Neurology, Erasmus MC, Rotterdam, The Netherlands
| | - Anouk van der Hoorn
- Medical Imaging Center, Department of Radiology, University Medical Center Groningen, Groningen, The Netherlands
| | - Esther A H Warnert
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
- Medical Delta, Delft, The Netherlands
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
- Medical Delta, Delft, The Netherlands.
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Sollmann N, Zhang H, Kloth C, Zimmer C, Wiestler B, Rosskopf J, Kreiser K, Schmitz B, Beer M, Krieg SM. Modern preoperative imaging and functional mapping in patients with intracranial glioma. ROFO-FORTSCHR RONTG 2023; 195:989-1000. [PMID: 37224867 DOI: 10.1055/a-2083-8717] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Magnetic resonance imaging (MRI) in therapy-naïve intracranial glioma is paramount for neuro-oncological diagnostics, and it provides images that are helpful for surgery planning and intraoperative guidance during tumor resection, including assessment of the involvement of functionally eloquent brain structures. This study reviews emerging MRI techniques to depict structural information, diffusion characteristics, perfusion alterations, and metabolism changes for advanced neuro-oncological imaging. In addition, it reflects current methods to map brain function close to a tumor, including functional MRI and navigated transcranial magnetic stimulation with derived function-based tractography of subcortical white matter pathways. We conclude that modern preoperative MRI in neuro-oncology offers a multitude of possibilities tailored to clinical needs, and advancements in scanner technology (e. g., parallel imaging for acceleration of acquisitions) make multi-sequence protocols increasingly feasible. Specifically, advanced MRI using a multi-sequence protocol enables noninvasive, image-based tumor grading and phenotyping in patients with glioma. Furthermore, the add-on use of preoperatively acquired MRI data in combination with functional mapping and tractography facilitates risk stratification and helps to avoid perioperative functional decline by providing individual information about the spatial location of functionally eloquent tissue in relation to the tumor mass. KEY POINTS:: · Advanced preoperative MRI allows for image-based tumor grading and phenotyping in glioma.. · Multi-sequence MRI protocols nowadays make it possible to assess various tumor characteristics (incl. perfusion, diffusion, and metabolism).. · Presurgical MRI in glioma is increasingly combined with functional mapping to identify and enclose individual functional areas.. · Advancements in scanner technology (e. g., parallel imaging) facilitate increasing application of dedicated multi-sequence imaging protocols.. CITATION FORMAT: · Sollmann N, Zhang H, Kloth C et al. Modern preoperative imaging and functional mapping in patients with intracranial glioma. Fortschr Röntgenstr 2023; 195: 989 - 1000.
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Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, United States
| | - Haosu Zhang
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
| | - Christopher Kloth
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, München, Germany
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- TranslaTUM - Central Institute for Translational Cancer Research, Klinikum rechts der Isar, Technical University of Munich, München, Germany
| | - Johannes Rosskopf
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Section of Neuroradiology, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Kornelia Kreiser
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Radiology and Neuroradiology, Universitäts- und Rehabilitationskliniken Ulm, Ulm, Germany
| | - Bernd Schmitz
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Section of Neuroradiology, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Sandro M Krieg
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
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Chauvie S, Mazzoni LN, O’Doherty J. A Review on the Use of Imaging Biomarkers in Oncology Clinical Trials: Quality Assurance Strategies for Technical Validation. Tomography 2023; 9:1876-1902. [PMID: 37888741 PMCID: PMC10610870 DOI: 10.3390/tomography9050149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 10/10/2023] [Accepted: 10/13/2023] [Indexed: 10/28/2023] Open
Abstract
Imaging biomarkers (IBs) have been proposed in medical literature that exploit images in a quantitative way, going beyond the visual assessment by an imaging physician. These IBs can be used in the diagnosis, prognosis, and response assessment of several pathologies and are very often used for patient management pathways. In this respect, IBs to be used in clinical practice and clinical trials have a requirement to be precise, accurate, and reproducible. Due to limitations in imaging technology, an error can be associated with their value when considering the entire imaging chain, from data acquisition to data reconstruction and subsequent analysis. From this point of view, the use of IBs in clinical trials requires a broadening of the concept of quality assurance and this can be a challenge for the responsible medical physics experts (MPEs). Within this manuscript, we describe the concept of an IB, examine some examples of IBs currently employed in clinical practice/clinical trials and analyze the procedure that should be carried out to achieve better accuracy and reproducibility in their use. We anticipate that this narrative review, written by the components of the EFOMP working group on "the role of the MPEs in clinical trials"-imaging sub-group, can represent a valid reference material for MPEs approaching the subject.
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Affiliation(s)
- Stephane Chauvie
- Medical Physics Division, Santa Croce e Carle Hospital, 12100 Cuneo, Italy;
| | | | - Jim O’Doherty
- Siemens Medical Solutions, Malvern, PA 19355, USA;
- Department of Radiology & Radiological Sciences, Medical University of South Carolina, Charleston, SC 20455, USA
- Radiography & Diagnostic Imaging, University College Dublin, D04 C7X2 Dublin, Ireland
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Hirschler L, Sollmann N, Schmitz‐Abecassis B, Pinto J, Arzanforoosh F, Barkhof F, Booth T, Calvo‐Imirizaldu M, Cassia G, Chmelik M, Clement P, Ercan E, Fernández‐Seara MA, Furtner J, Fuster‐Garcia E, Grech‐Sollars M, Guven NT, Hatay GH, Karami G, Keil VC, Kim M, Koekkoek JAF, Kukran S, Mancini L, Nechifor RE, Özcan A, Ozturk‐Isik E, Piskin S, Schmainda K, Svensson SF, Tseng C, Unnikrishnan S, Vos F, Warnert E, Zhao MY, Jancalek R, Nunes T, Emblem KE, Smits M, Petr J, Hangel G. Advanced MR Techniques for Preoperative Glioma Characterization: Part 1. J Magn Reson Imaging 2023; 57:1655-1675. [PMID: 36866773 PMCID: PMC10946498 DOI: 10.1002/jmri.28662] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/08/2023] [Accepted: 02/09/2023] [Indexed: 03/04/2023] Open
Abstract
Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2.
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Affiliation(s)
- Lydiane Hirschler
- C.J. Gorter MRI Center, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Nico Sollmann
- Department of Diagnostic and Interventional RadiologyUniversity Hospital UlmUlmGermany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der IsarTechnical University of MunichMunichGermany
- TUM‐Neuroimaging Center, Klinikum rechts der IsarTechnical University of MunichMunichGermany
| | - Bárbara Schmitz‐Abecassis
- Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
- Medical Delta FoundationDelftThe Netherlands
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK
| | | | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamThe Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Thomas Booth
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Department of NeuroradiologyKing's College Hospital NHS Foundation TrustLondonUK
| | | | | | - Marek Chmelik
- Department of Technical Disciplines in Medicine, Faculty of Health CareUniversity of PrešovPrešovSlovakia
| | - Patricia Clement
- Department of Diagnostic SciencesGhent UniversityGhentBelgium
- Department of Medical ImagingGhent University HospitalGhentBelgium
| | - Ece Ercan
- Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Maria A. Fernández‐Seara
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
| | - Julia Furtner
- Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Research Center of Medical Image Analysis and Artificial IntelligenceDanube Private UniversityKrems an der DonauAustria
| | - Elies Fuster‐Garcia
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y ComunicacionesUniversitat Politècnica de ValènciaValenciaSpain
| | - Matthew Grech‐Sollars
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
| | - Nazmiye Tugay Guven
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Gokce Hale Hatay
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Golestan Karami
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Vera C. Keil
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamThe Netherlands
- Cancer Center AmsterdamAmsterdamThe Netherlands
| | - Mina Kim
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of NeuroinflammationUniversity College LondonLondonUK
| | - Johan A. F. Koekkoek
- Department of NeurologyLeiden University Medical CenterLeidenThe Netherlands
- Department of NeurologyHaaglanden Medical CenterThe HagueThe Netherlands
| | - Simran Kukran
- Department of BioengineeringImperial College LondonLondonUK
- Department of Radiotherapy and ImagingInstitute of Cancer ResearchLondonUK
| | - Laura Mancini
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
- Department of Brain Repair and Rehabilitation, Institute of NeurologyUniversity College LondonLondonUK
| | - Ruben Emanuel Nechifor
- Department of Clinical Psychology and PsychotherapyInternational Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Babes‐Bolyai UniversityCluj‐NapocaRomania
| | - Alpay Özcan
- Electrical and Electronics Engineering DepartmentBogazici University IstanbulIstanbulTurkey
| | - Esin Ozturk‐Isik
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Senol Piskin
- Department of Mechanical Engineering, Faculty of Natural Sciences and EngineeringIstinye University IstanbulIstanbulTurkey
| | - Kathleen Schmainda
- Department of BiophysicsMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Siri F. Svensson
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
- Department of PhysicsUniversity of OsloOsloNorway
| | - Chih‐Hsien Tseng
- Medical Delta FoundationDelftThe Netherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftThe Netherlands
| | - Saritha Unnikrishnan
- Faculty of Engineering and DesignAtlantic Technological University (ATU) SligoSligoIreland
- Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE), ATU SligoSligoIreland
| | - Frans Vos
- Medical Delta FoundationDelftThe Netherlands
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamThe Netherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftThe Netherlands
| | - Esther Warnert
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamThe Netherlands
| | - Moss Y. Zhao
- Department of RadiologyStanford UniversityStanfordCaliforniaUSA
- Stanford Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
| | - Radim Jancalek
- Department of NeurosurgerySt. Anne's University Hospital, BrnoBrnoCzech Republic
- Faculty of Medicine, Masaryk UniversityBrnoCzech Republic
| | - Teresa Nunes
- Department of NeuroradiologyHospital Garcia de OrtaAlmadaPortugal
| | - Kyrre E. Emblem
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
| | - Marion Smits
- Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamThe Netherlands
- Brain Tumour CentreErasmus MC Cancer InstituteRotterdamThe Netherlands
| | - Jan Petr
- Helmholtz‐Zentrum Dresden‐RossendorfInstitute of Radiopharmaceutical Cancer ResearchDresdenGermany
| | - Gilbert Hangel
- Department of NeurosurgeryMedical University of ViennaViennaAustria
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for MR Imaging BiomarkersViennaAustria
- Medical Imaging ClusterMedical University of ViennaViennaAustria
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9
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di Noia C, Grist JT, Riemer F, Lyasheva M, Fabozzi M, Castelli M, Lodi R, Tonon C, Rundo L, Zaccagna F. Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI. Diagnostics (Basel) 2022; 12:diagnostics12092125. [PMID: 36140526 PMCID: PMC9497964 DOI: 10.3390/diagnostics12092125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 08/05/2022] [Accepted: 08/17/2022] [Indexed: 11/24/2022] Open
Abstract
Given growing clinical needs, in recent years Artificial Intelligence (AI) techniques have increasingly been used to define the best approaches for survival assessment and prediction in patients with brain tumors. Advances in computational resources, and the collection of (mainly) public databases, have promoted this rapid development. This narrative review of the current state-of-the-art aimed to survey current applications of AI in predicting survival in patients with brain tumors, with a focus on Magnetic Resonance Imaging (MRI). An extensive search was performed on PubMed and Google Scholar using a Boolean research query based on MeSH terms and restricting the search to the period between 2012 and 2022. Fifty studies were selected, mainly based on Machine Learning (ML), Deep Learning (DL), radiomics-based methods, and methods that exploit traditional imaging techniques for survival assessment. In addition, we focused on two distinct tasks related to survival assessment: the first on the classification of subjects into survival classes (short and long-term or eventually short, mid and long-term) to stratify patients in distinct groups. The second focused on quantification, in days or months, of the individual survival interval. Our survey showed excellent state-of-the-art methods for the first, with accuracy up to ∼98%. The latter task appears to be the most challenging, but state-of-the-art techniques showed promising results, albeit with limitations, with C-Index up to ∼0.91. In conclusion, according to the specific task, the available computational methods perform differently, and the choice of the best one to use is non-univocal and dependent on many aspects. Unequivocally, the use of features derived from quantitative imaging has been shown to be advantageous for AI applications, including survival prediction. This evidence from the literature motivates further research in the field of AI-powered methods for survival prediction in patients with brain tumors, in particular, using the wealth of information provided by quantitative MRI techniques.
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Affiliation(s)
- Christian di Noia
- Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum—University of Bologna, 40125 Bologna, Italy
| | - James T. Grist
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford OX1 3PT, UK
- Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
- Oxford Centre for Clinical Magnetic Research Imaging, University of Oxford, Oxford OX3 9DU, UK
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham B15 2SY, UK
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, N-5021 Bergen, Norway
| | - Maria Lyasheva
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | - Miriana Fabozzi
- Centro Medico Polispecialistico (CMO), 80058 Torre Annunziata, Italy
| | - Mauro Castelli
- NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, Campus de Campolide, 1070-312 Lisboa, Portugal
| | - Raffaele Lodi
- Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum—University of Bologna, 40125 Bologna, Italy
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, 40139 Bologna, Italy
| | - Caterina Tonon
- Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum—University of Bologna, 40125 Bologna, Italy
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, 40139 Bologna, Italy
| | - Leonardo Rundo
- Department of Information and Electrical Engineering and Applied Mathematics, University of Salerno, 84084 Fisciano, Italy
| | - Fulvio Zaccagna
- Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum—University of Bologna, 40125 Bologna, Italy
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, 40139 Bologna, Italy
- Correspondence: ; Tel.: +39-0514969951
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