1
|
Moltoni G, Romano A, Capriotti G, Campagna G, Ascolese AM, Romano A, Dellepiane F, Minniti G, Signore A, Bozzao A. ASL, DSC, DCE perfusion MRI and 18F-DOPA PET/CT in differentiating glioma recurrence from post-treatment changes. LA RADIOLOGIA MEDICA 2024; 129:1382-1393. [PMID: 39117936 PMCID: PMC11379733 DOI: 10.1007/s11547-024-01862-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Accepted: 07/25/2024] [Indexed: 08/10/2024]
Abstract
OBJECTIVES To discriminate between post-treatment changes and tumor recurrence in patients affected by glioma undergoing surgery and chemoradiation with a new enhancing lesion is challenging. We aimed to evaluate the role of ASL, DSC, DCE perfusion MRI, and 18F-DOPA PET/CT in distinguishing tumor recurrence from post-treatment changes in patients with glioma. MATERIALS AND METHODS We prospectively enrolled patients with treated glioma (surgery plus chemoradiation) and a new enhancing lesion doubtful for recurrence or post-treatment changes. Each patient underwent a 1.5T MRI examination, including ASL, DSC, and DCE PWI, and an 18F-DOPA PET/CT examination. For each lesion, we measured ASL-derived CBF and normalized CBF, DSC-derived rCBV, DCE-derived Ktrans, Vp, Ve, Kep, and PET/CT-derived SUV maximum. Clinical and radiological follow-up determined the diagnosis of tumor recurrence or post-treatment changes. RESULTS We evaluated 29 lesions (5 low-grade gliomas and 24 high-grade gliomas); 14 were malignancies, and 15 were post-treatment changes. CBF ASL, nCBF ASL, rCBV DSC, and PET SUVmax were associated with tumor recurrence from post-treatment changes in patients with glioma through an univariable logistic regression. Whereas the multivariable logistic regression results showed only nCBF ASL (p = 0.008) was associated with tumor recurrence from post-treatment changes in patients with glioma with OR = 22.85, CI95%: (2.28-228.77). CONCLUSION In our study, ASL was the best technique, among the other two MRI PWI and the 18F-DOPA PET/CT PET, in distinguishing disease recurrence from post-treatment changes in treated glioma.
Collapse
Affiliation(s)
- Giulia Moltoni
- NESMOS, Department of Neuroradiology, S. Andrea Hospital, University Sapienza, Via di Grottarossa 1035/1039, 00189, Rome, Italy.
| | - Andrea Romano
- NESMOS, Department of Neuroradiology, S. Andrea Hospital, University Sapienza, Via di Grottarossa 1035/1039, 00189, Rome, Italy
| | - Gabriela Capriotti
- Department of Medical-Surgical Sciences and Translational Medicine, University of Rome "Sapienza", Rome, Italy
| | - Giuseppe Campagna
- Department of Medical-Surgical Sciences and Translational Medicine, University of Rome "Sapienza", Rome, Italy
| | - Anna Maria Ascolese
- SMCMT Department, Radiotherapy Oncology, S. Andrea Hospital, University Sapienza, Rome, Italy
| | - Allegra Romano
- NESMOS, Department of Neuroradiology, S. Andrea Hospital, University Sapienza, Via di Grottarossa 1035/1039, 00189, Rome, Italy
| | - Francesco Dellepiane
- NESMOS, Department of Neuroradiology, S. Andrea Hospital, University Sapienza, Via di Grottarossa 1035/1039, 00189, Rome, Italy
| | - Giuseppe Minniti
- Department of Radiological, Oncological and Pathological Sciences, "Sapienza" University of Rome, 00138, Rome, Italy
- IRCCS Neuromed, 86077, Pozzilli, Italy
| | - Alberto Signore
- Department of Medical-Surgical Sciences and Translational Medicine, University of Rome "Sapienza", Rome, Italy
| | - Alessandro Bozzao
- NESMOS, Department of Neuroradiology, S. Andrea Hospital, University Sapienza, Via di Grottarossa 1035/1039, 00189, Rome, Italy
| |
Collapse
|
2
|
Ghaderi S, Mohammadi S, Mohammadi M, Pashaki ZNA, Heidari M, Khatyal R, Zafari R. A systematic review of brain metastases from lung cancer using magnetic resonance neuroimaging: Clinical and technical aspects. J Med Radiat Sci 2024; 71:269-289. [PMID: 38234262 PMCID: PMC11177032 DOI: 10.1002/jmrs.756] [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: 08/15/2023] [Accepted: 01/06/2024] [Indexed: 01/19/2024] Open
Abstract
INTRODUCTION Brain metastases (BMs) are common in lung cancer (LC) and are associated with poor prognosis. Magnetic resonance imaging (MRI) plays a vital role in the detection, diagnosis and management of BMs. This review summarises recent advances in MRI techniques for BMs from LC. METHODS This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive literature search was conducted in three electronic databases: PubMed, Scopus and the Web of Science. The search was limited to studies published between January 2000 and March 2023. The quality of the included studies was evaluated using appropriate tools for different study designs. A narrative synthesis was carried out to describe the key findings of the included studies. RESULTS Sixty-five studies were included. Standard MRI sequences such as T1-weighted (T1w), T2-weighted (T2w) and fluid-attenuated inversion recovery (FLAIR) were commonly used. Advanced techniques included perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and radiomics analysis. DWI and PWI parameters could distinguish tumour recurrence from radiation necrosis. Radiomics models predicted genetic mutations and the risk of BMs. Diagnostic accuracy was improved with deep learning (DL) approaches. Prognostic factors such as performance status and concurrent chemotherapy impacted survival. CONCLUSION Advanced MRI techniques and specialised MRI methods have emerging roles in managing BMs from LC. PWI and DWI improve diagnostic accuracy in treated BMs. Radiomics and DL facilitate personalised prognosis and treatment. Magnetic resonance imaging plays a key role in the continuum of care for BMs of patients with LC, from screening to treatment monitoring.
Collapse
Affiliation(s)
- Sadegh Ghaderi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in MedicineTehran University of Medical SciencesTehranIran
| | - Sana Mohammadi
- Department of Medical Sciences, School of MedicineIran University of Medical SciencesTehranIran
| | - Mahdi Mohammadi
- Department of Medical Physics and Biomedical Engineering, School of MedicineTehran University of Medical SciencesTehranIran
| | | | - Mehrsa Heidari
- Department of Medical Science, School of MedicineAhvaz Jundishapur University of Medical SciencesAhvazIran
| | - Rahim Khatyal
- Department of Radiology, Faculty of Allied Medical SciencesTabriz University of Medical SciencesTabrizIran
| | - Rasa Zafari
- School of MedicineTehran University of Medical SciencesTehranIran
| |
Collapse
|
3
|
Park CJ, Kim S, Han K, Ahn SS, Kim D, Park YW, Chang JH, Kim SH, Lee SK. Diffusion- and Perfusion-Weighted MRI Radiomics for Survival Prediction in Patients with Lower-Grade Gliomas. Yonsei Med J 2024; 65:283-292. [PMID: 38653567 PMCID: PMC11045349 DOI: 10.3349/ymj.2023.0323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 10/27/2023] [Accepted: 12/13/2023] [Indexed: 04/25/2024] Open
Abstract
PURPOSE Lower-grade gliomas of histologic grades 2 and 3 follow heterogenous clinical outcomes, which necessitates risk stratification. This study aimed to evaluate whether diffusion-weighted and perfusion-weighted MRI radiomics allow overall survival (OS) prediction in patients with lower-grade gliomas and investigate its prognostic value. MATERIALS AND METHODS In this retrospective study, radiomic features were extracted from apparent diffusion coefficient, relative cerebral blood volume map, and Ktrans map in patients with pathologically confirmed lower-grade gliomas (January 2012-February 2019). The radiomics risk score (RRS) calculated from selected features constituted a radiomics model. Multivariable Cox regression analysis, including clinical features and RRS, was performed. The models' integrated area under the receiver operating characteristic curves (iAUCs) were compared. The radiomics model combined with clinical features was presented as a nomogram. RESULTS The study included 129 patients (median age, 44 years; interquartile range, 37-57 years; 63 female): 90 patients for training set and 39 patients for test set. The RRS was an independent risk factor for OS with a hazard ratio of 6.01. The combined clinical and radiomics model achieved superior performance for OS prediction compared to the clinical model in both training (iAUC, 0.82 vs. 0.72, p=0.002) and test sets (0.88 vs. 0.76, p=0.04). The radiomics nomogram combined with clinical features exhibited good agreement between the actual and predicted OS with C-index of 0.83 and 0.87 in the training and test sets, respectively. CONCLUSION Adding diffusion- and perfusion-weighted MRI radiomics to clinical features improved survival prediction in lower-grade glioma.
Collapse
Affiliation(s)
- Chae Jung Park
- Department of Radiology, Research Institute of Radiological Science, Yongin Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sooyon Kim
- Department of Applied Statistics, Yonsei University, Seoul, Korea
| | - Kyunghwa Han
- Department of Radiology, Center for Clinical Imaging Data Science, Research Institute of Radiological Sciences, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sung Soo Ahn
- Department of Radiology, Center for Clinical Imaging Data Science, Research Institute of Radiological Sciences, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
| | - Dain Kim
- Graduate School of Artificial Intelligence, Pohang University of Science and Technology, Pohang, Korea
| | - Yae Won Park
- Department of Radiology, Center for Clinical Imaging Data Science, Research Institute of Radiological Sciences, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Jong Hee Chang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea
| | - Se Hoon Kim
- Department of Pathology, Yonsei University College of Medicine, Seoul, Korea
| | - Seung-Koo Lee
- Department of Radiology, Center for Clinical Imaging Data Science, Research Institute of Radiological Sciences, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| |
Collapse
|
4
|
Endrikat J, Gutberlet M, Barkhausen J, Schöckel L, Bhatti A, Harz C, Hoffmann KT. Clinical Efficacy of Gadobutrol: Review of Over 25 Years of Use Exceeding 100 Million Administrations. Invest Radiol 2024; 59:345-358. [PMID: 37972293 DOI: 10.1097/rli.0000000000001041] [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: 11/19/2023]
Abstract
BACKGROUND Gadobutrol has been administered more than 100 million times worldwide, since February 1998, that is, over the last 25 years. Numerous clinical studies in a broad range of indications document the long-term experience with gadobutrol. OBJECTIVE The aim of this study was to provide a literature-based overview on gadobutrol's efficacy in 9 approved indications and use in children. MATERIALS AND METHODS Efficacy results in patients of all age groups including sensitivity, specificity, accuracy, and positive/negative predictive values were identified by a systematic literature search on Embase until December 31, 2022. Nine approved indications were considered: central nervous system (CNS), magnetic resonance angiography (MRA), breast, heart, prostate, kidney, liver, musculoskeletal, whole body, and various indications in children. RESULTS Sixty-five publications (10 phase III, 2 phase IV, 53 investigator-initiated studies) reported diagnostic efficacy results obtained from 7806 patients including 271 children, at 369 centers worldwide. Indication-specific sensitivity ranges were 59%-98% (CNS), 53%-100% (MRA), 80%-100% (breast), 64%-90% (heart), 64%-96% (prostate), 71-85 (kidney), 79%-100% (liver), 53%-98% (musculoskeletal), and 78%-100% (children). Indication-specific specificity ranges were 75%-100% (CNS), 64%-99% (MRA), 58%-98% (breast), and 47%-100% (heart). CONCLUSIONS The evaluated body of evidence, consisting of 65 studies with 7806 patients, including 271 children and 7535 adults, showed that gadobutrol is an efficacious magnetic resonance imaging contrast agent for all age groups in various approved indications throughout the whole body.
Collapse
Affiliation(s)
- Jan Endrikat
- From the Radiology, Bayer AG, Berlin, Germany (J.E., L.S., C.H.); Department of Gynecology, Obstetrics, and Reproductive Medicine, University Medical School of Saarland, Homburg/Saar, Germany (J.E.); Department of Diagnostic and Interventional Radiology, University of Leipzig, Heart Center, Leipzig, Germany (M.G.); Department of Radiology and Nuclear Medicine, University Hospital Schleswig Holstein-Campus Luebeck, Luebeck, Germany (J.B.); Bayer US LLC, Benefit-Risk Management Pharmacovigilance, Whippany, NJ (A.B.); and Department of Neuroradiology, University of Leipzig, Leipzig, Germany (K.-T.H.)
| | | | | | | | | | | | | |
Collapse
|
5
|
Ortiz de Mendivil A, Martín-Medina P, García-Cañamaque L, Jiménez-Munarriz B, Ciérvide R, Diamantopoulos J. Challenges in radiological evaluation of brain metastases, beyond progression. RADIOLOGIA 2024; 66:166-180. [PMID: 38614532 DOI: 10.1016/j.rxeng.2024.03.003] [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: 11/15/2022] [Accepted: 04/02/2023] [Indexed: 04/15/2024]
Abstract
MRI is the cornerstone in the evaluation of brain metastases. The clinical challenges lie in discriminating metastases from mimickers such as infections or primary tumors and in evaluating the response to treatment. The latter sometimes leads to growth, which must be framed as pseudo-progression or radionecrosis, both inflammatory phenomena attributable to treatment, or be considered as recurrence. To meet these needs, imaging techniques are the subject of constant research. However, an exponential growth after radiotherapy must be interpreted with caution, even in the presence of results suspicious of tumor progression by advanced techniques, because it may be due to inflammatory changes. The aim of this paper is to familiarize the reader with inflammatory phenomena of brain metastases treated with radiotherapy and to describe two related radiological signs: "the inflammatory cloud" and "incomplete ring enhancement", in order to adopt a conservative management with close follow-up.
Collapse
Affiliation(s)
- A Ortiz de Mendivil
- Servicio de Radiodiagnóstico, Sección de Neurorradiología, Hospital Universitario HM Sanchinarro, Madrid, Spain.
| | - P Martín-Medina
- Servicio de Radiodiagnóstico, Sección de Neurorradiología, Hospital Universitario HM Sanchinarro, Madrid, Spain
| | | | - B Jiménez-Munarriz
- Servicio de Oncología Médica, Hospital Universitario HM Sanchinarro, Madrid, Spain
| | - R Ciérvide
- Servicio de Oncología Radioterápica, Hospital Universitario HM Sanchinarro, Madrid, Spain
| | | |
Collapse
|
6
|
Lee J, Chen MM, Liu HL, Ucisik FE, Wintermark M, Kumar VA. MR Perfusion Imaging for Gliomas. Magn Reson Imaging Clin N Am 2024; 32:73-83. [PMID: 38007284 DOI: 10.1016/j.mric.2023.07.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2023]
Abstract
Accurate diagnosis and treatment evaluation of patients with gliomas is imperative to make clinical decisions. Multiparametric MR perfusion imaging reveals physiologic features of gliomas that can help classify them according to their histologic and molecular features as well as distinguish them from other neoplastic and nonneoplastic entities. It is also helpful in distinguishing tumor recurrence or progression from radiation necrosis, pseudoprogression, and pseudoresponse, which is difficult with conventional MR imaging. This review provides an update on MR perfusion imaging for the diagnosis and treatment monitoring of patients with gliomas following standard-of-care chemoradiation therapy and other treatment regimens such as immunotherapy.
Collapse
Affiliation(s)
- Jina Lee
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA
| | - Melissa M Chen
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA
| | - Ho-Ling Liu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA
| | - F Eymen Ucisik
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA
| | - Max Wintermark
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA
| | - Vinodh A Kumar
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA.
| |
Collapse
|
7
|
Sanvito F, Kaufmann TJ, Cloughesy TF, Wen PY, Ellingson BM. Standardized brain tumor imaging protocols for clinical trials: current recommendations and tips for integration. FRONTIERS IN RADIOLOGY 2023; 3:1267615. [PMID: 38152383 PMCID: PMC10751345 DOI: 10.3389/fradi.2023.1267615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 11/24/2023] [Indexed: 12/29/2023]
Abstract
Standardized MRI acquisition protocols are crucial for reducing the measurement and interpretation variability associated with response assessment in brain tumor clinical trials. The main challenge is that standardized protocols should ensure high image quality while maximizing the number of institutions meeting the acquisition requirements. In recent years, extensive effort has been made by consensus groups to propose different "ideal" and "minimum requirements" brain tumor imaging protocols (BTIPs) for gliomas, brain metastases (BM), and primary central nervous system lymphomas (PCSNL). In clinical practice, BTIPs for clinical trials can be easily integrated with additional MRI sequences that may be desired for clinical patient management at individual sites. In this review, we summarize the general concepts behind the choice and timing of sequences included in the current recommended BTIPs, we provide a comparative overview, and discuss tips and caveats to integrate additional clinical or research sequences while preserving the recommended BTIPs. Finally, we also reflect on potential future directions for brain tumor imaging in clinical trials.
Collapse
Affiliation(s)
- Francesco Sanvito
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | | | - Timothy F. Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, MA, United States
| | - Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| |
Collapse
|
8
|
Dobeson CB, Birkbeck M, Bhatnagar P, Hall J, Pearson R, West S, English P, Butteriss D, Perthen J, Lewis J. Perfusion MRI in the evaluation of brain metastases: current practice review and rationale for study of baseline MR perfusion imaging prior to stereotactic radiosurgery (STARBEAM-X). Br J Radiol 2023; 96:20220462. [PMID: 37660364 PMCID: PMC10646666 DOI: 10.1259/bjr.20220462] [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: 04/29/2022] [Revised: 07/04/2023] [Accepted: 08/21/2023] [Indexed: 09/05/2023] Open
Abstract
Stereotactic radiosurgery is an established focal treatment for brain metastases with high local control rates. An important side-effect of stereotactic radiosurgery is the development of radionecrosis. On conventional MR imaging, radionecrosis and tumour progression often have similar appearances, but have contrasting management approaches. Perfusion MR imaging is often used in the post-treatment setting in order to help distinguish between the two, but image interpretation can be fraught with challenges.Perfusion MR plays an established role in the baseline and post-treatment evaluation of primary brain tumours and a number of studies have concentrated on the value of perfusion imaging in brain metastases. Of the parameters generated, relative cerebral blood volume is the most widely used variable in terms of its clinical value in differentiating between radionecrosis and tumour progression. Although it has been suggested that the relative cerebral blood volume tends to be elevated in active metastatic disease following treatment with radiosurgery, but not with treatment-related changes, the literature available on interpretation of the ratios provided in the context of defining tumour progression is not consistent.This article aims to provide an overview of the role perfusion MRI plays in the assessment of brain metastases and introduces the rationale for the STARBEAM-X study (Study of assessment of radionecrosis in brain metastases using MR perfusion extra imaging), which will prospectively evaluate baseline perfusion imaging in brain metastases. We hope this will allow insight into the vascular appearance of metastases from different primary sites, and aid in the interpretation of post-treatment perfusion imaging.
Collapse
Affiliation(s)
| | - Matthew Birkbeck
- Northern Medical Physics and Clinical Engineering, Freeman Hospital, Newcastle upon Tyne, UK
| | - Priya Bhatnagar
- Department of Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne, UK
| | - Julie Hall
- Department of Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne, UK
| | - Rachel Pearson
- Department of Oncology, Northern Centre for Cancer Care, Freeman Hospital, Newcastle upon Tyne, UK
| | - Serena West
- Department of Oncology, Northern Centre for Cancer Care, Freeman Hospital, Newcastle upon Tyne, UK
| | - Philip English
- Department of Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne, UK
| | - David Butteriss
- Department of Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne, UK
| | - Joanna Perthen
- Department of Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne, UK
| | - Joanne Lewis
- Department of Oncology, Northern Centre for Cancer Care, Freeman Hospital, Newcastle upon Tyne, UK
| |
Collapse
|
9
|
Romano A, Moltoni G, Blandino A, Palizzi S, Romano A, de Rosa G, De Blasi Palma L, Monopoli C, Guarnera A, Minniti G, Bozzao A. Radiosurgery for Brain Metastases: Challenges in Imaging Interpretation after Treatment. Cancers (Basel) 2023; 15:5092. [PMID: 37894459 PMCID: PMC10605307 DOI: 10.3390/cancers15205092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 10/13/2023] [Accepted: 10/18/2023] [Indexed: 10/29/2023] Open
Abstract
Stereotactic radiosurgery (SRS) has transformed the management of brain metastases by achieving local tumor control, reducing toxicity, and minimizing the need for whole-brain radiation therapy (WBRT). This review specifically investigates radiation-induced changes in patients treated for metastasis, highlighting the crucial role of magnetic resonance imaging (MRI) in the evaluation of treatment response, both at very early and late stages. The primary objective of the review is to evaluate the most effective imaging techniques for assessing radiation-induced changes and distinguishing them from tumor growth. The limitations of conventional imaging methods, which rely on size measurements, dimensional criteria, and contrast enhancement patterns, are critically evaluated. In addition, it has been investigated the potential of advanced imaging modalities to offer a more precise and comprehensive evaluation of treatment response. Finally, an overview of the relevant literature concerning the interpretation of brain changes in patients undergoing immunotherapies is provided.
Collapse
Affiliation(s)
- Andrea Romano
- NESMOS Department, U.O.C. Neuroradiology “Sant’Andrea” University Hospital, 00189 Rome, Italy; (A.R.); (G.M.); (A.B.); (S.P.); (A.R.); (G.d.R.); (L.D.B.P.); (C.M.); (A.G.); (A.B.)
| | - Giulia Moltoni
- NESMOS Department, U.O.C. Neuroradiology “Sant’Andrea” University Hospital, 00189 Rome, Italy; (A.R.); (G.M.); (A.B.); (S.P.); (A.R.); (G.d.R.); (L.D.B.P.); (C.M.); (A.G.); (A.B.)
| | - Antonella Blandino
- NESMOS Department, U.O.C. Neuroradiology “Sant’Andrea” University Hospital, 00189 Rome, Italy; (A.R.); (G.M.); (A.B.); (S.P.); (A.R.); (G.d.R.); (L.D.B.P.); (C.M.); (A.G.); (A.B.)
| | - Serena Palizzi
- NESMOS Department, U.O.C. Neuroradiology “Sant’Andrea” University Hospital, 00189 Rome, Italy; (A.R.); (G.M.); (A.B.); (S.P.); (A.R.); (G.d.R.); (L.D.B.P.); (C.M.); (A.G.); (A.B.)
| | - Allegra Romano
- NESMOS Department, U.O.C. Neuroradiology “Sant’Andrea” University Hospital, 00189 Rome, Italy; (A.R.); (G.M.); (A.B.); (S.P.); (A.R.); (G.d.R.); (L.D.B.P.); (C.M.); (A.G.); (A.B.)
| | - Giulia de Rosa
- NESMOS Department, U.O.C. Neuroradiology “Sant’Andrea” University Hospital, 00189 Rome, Italy; (A.R.); (G.M.); (A.B.); (S.P.); (A.R.); (G.d.R.); (L.D.B.P.); (C.M.); (A.G.); (A.B.)
| | - Lara De Blasi Palma
- NESMOS Department, U.O.C. Neuroradiology “Sant’Andrea” University Hospital, 00189 Rome, Italy; (A.R.); (G.M.); (A.B.); (S.P.); (A.R.); (G.d.R.); (L.D.B.P.); (C.M.); (A.G.); (A.B.)
| | - Cristiana Monopoli
- NESMOS Department, U.O.C. Neuroradiology “Sant’Andrea” University Hospital, 00189 Rome, Italy; (A.R.); (G.M.); (A.B.); (S.P.); (A.R.); (G.d.R.); (L.D.B.P.); (C.M.); (A.G.); (A.B.)
| | - Alessia Guarnera
- NESMOS Department, U.O.C. Neuroradiology “Sant’Andrea” University Hospital, 00189 Rome, Italy; (A.R.); (G.M.); (A.B.); (S.P.); (A.R.); (G.d.R.); (L.D.B.P.); (C.M.); (A.G.); (A.B.)
| | - Giuseppe Minniti
- Department of Radiological, Oncological and Pathological Sciences, “Sapienza” University of Rome, 00138 Rome, Italy
- IRCCS Neuromed, 86077 Pozzilli, Italy
| | - Alessandro Bozzao
- NESMOS Department, U.O.C. Neuroradiology “Sant’Andrea” University Hospital, 00189 Rome, Italy; (A.R.); (G.M.); (A.B.); (S.P.); (A.R.); (G.d.R.); (L.D.B.P.); (C.M.); (A.G.); (A.B.)
| |
Collapse
|
10
|
Khan F, Jones K, Lyon P. Immune checkpoint inhibition: a future guided by radiology. Br J Radiol 2023; 96:20220565. [PMID: 36752570 PMCID: PMC10321249 DOI: 10.1259/bjr.20220565] [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: 06/01/2022] [Revised: 01/04/2023] [Accepted: 01/29/2023] [Indexed: 02/09/2023] Open
Abstract
The limitation of the function of antitumour immune cells is a common hallmark of cancers that enables their survival. As such, the potential of immune checkpoint inhibition (ICI) acts as a paradigm shift in the treatment of a range of cancers but has not yet been fully capitalised. Combining minimally and non-invasive locoregional therapies offered by radiologists with ICI is now an active field of research with the aim of furthering therapeutic capabilities in medical oncology. In parallel to this impending advancement, the "imaging toolbox" available to radiologists is also growing, enabling more refined tumour characterisation as well as greater accuracy in evaluating responses to therapy. Options range from metabolite labelling to cellular localisation to immune checkpoint screening. It is foreseeable that these novel imaging techniques will be integrated into personalised treatment algorithms. This growth in the field must include updating the current standardised imaging criteria to ensure they are fit for purpose. Such criteria is crucial to both appropriately guide clinical decision-making regarding next steps of treatment, but also provide reliable prognosis. Quantitative approaches to these novel imaging techniques are also already being investigated to further optimise personalised therapeutic decision-making. The therapeutic potential of specific ICIs and locoregional therapies could be determined before administration thus limiting unnecessary side-effects whilst maintaining efficacy. Several radiological aspects of oncological care are advancing simultaneously. Therefore, it is essential that each development is assessed for clinical use and optimised to ensure the best treatment decisions are being offered to the patient. In this review, we discuss state of the art advances in novel functional imaging techniques in the field of immuno-oncology both pre-clinically and clinically.
Collapse
Affiliation(s)
- Faraaz Khan
- Foundation Doctor, Buckinghamshire Hospitals NHS Trust, Amersham, Buckinghamshire, United Kingdom
| | - Keaton Jones
- Academic Clinical Lecturer Nuffield Department of Surgical Sciences University of Oxford, Wellington Square, Oxford, United Kingdom
| | - Paul Lyon
- Consultant Radiologist, Department of Radiology, Oxford University Hospitals, Headington, Oxford, United Kingdom
| |
Collapse
|
11
|
Eraky AM. Radiological Biomarkers for Brain Metastases Prognosis: Quantitative Magnetic Resonance Imaging (MRI) Modalities As Non-invasive Biomarkers for the Effect of Radiotherapy. Cureus 2023; 15:e38353. [PMID: 37266043 PMCID: PMC10229388 DOI: 10.7759/cureus.38353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/28/2023] [Indexed: 06/03/2023] Open
Abstract
Radiotherapy effect is achieved by its ability to cause DNA damage and induce apoptosis. In contrast, radiation can induce tumor cells' proliferation, invasiveness, and epithelial-mesenchymal transition (EMT). Besides developing radioresistance, this paradoxical effect of radiotherapy is considered a challenging problem in the field of radiotherapy. This highlights the importance of developing new modalities to diagnose radioresistance early to avoid any unnecessary exposure to radiation and differentiate between metastases recurrence versus post-radiation changes. Quantitative magnetic resonance imaging (MRI) techniques including diffusion-weighted imaging (DWI), dynamic susceptibility contrast (DSC), arterial spin labeling (ASL), and dynamic contrast-enhanced (DCE) represent potential biomarkers to diagnose metastases recurrence and radioresistance. In this review, we will focus on recent studies discussing the possibility of using DWI, DSC, ASL, and DCE to diagnose radioresistance and recurrence in patients with brain metastases.
Collapse
Affiliation(s)
- Akram M Eraky
- Neurological Surgery, Medical College of Wisconsin, Milwaukee, USA
| |
Collapse
|
12
|
Chiu FY, Yen Y. Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives. Biomark Res 2023; 11:35. [PMID: 36991494 DOI: 10.1186/s40364-023-00476-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 03/16/2023] [Indexed: 03/31/2023] Open
Abstract
Biomarker discovery and development are popular for detecting the subtle diseases. However, biomarkers are needed to be validated and approved, and even fewer are ever used clinically. Imaging biomarkers have a crucial role in the treatment of cancer patients because they provide objective information on tumor biology, the tumor's habitat, and the tumor's signature in the environment. Tumor changes in response to an intervention complement molecular and genomic translational diagnosis as well as quantitative information. Neuro-oncology has become more prominent in diagnostics and targeted therapies. The classification of tumors has been actively updated, and drug discovery, and delivery in nanoimmunotherapies are advancing in the field of target therapy research. It is important that biomarkers and diagnostic implements be developed and used to assess the prognosis or late effects of long-term survivors. An improved realization of cancer biology has transformed its management with an increasing emphasis on a personalized approach in precision medicine. In the first part, we discuss the biomarker categories in relation to the courses of a disease and specific clinical contexts, including that patients and specimens should both directly reflect the target population and intended use. In the second part, we present the CT perfusion approach that provides quantitative and qualitative data that has been successfully applied to the clinical diagnosis, treatment and application. Furthermore, the novel and promising multiparametric MR imageing approach will provide deeper insights regarding the tumor microenvironment in the immune response. Additionally, we briefly remark new tactics based on MRI and PET for converging on imaging biomarkers combined with applications of bioinformatics in artificial intelligence. In the third part, we briefly address new approaches based on theranostics in precision medicine. These sophisticated techniques merge achievable standardizations into an applicatory apparatus for primarily a diagnostic implementation and tracking radioactive drugs to identify and to deliver therapies in an individualized medicine paradigm. In this article, we describe the critical principles for imaging biomarker characterization and discuss the current status of CT, MRI and PET in finiding imaging biomarkers of early disease.
Collapse
Affiliation(s)
- Fang-Ying Chiu
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Center for Brain and Neurobiology Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Teaching and Research Headquarters for Sustainable Development Goals, Tzu Chi University, Hualien City, 970374, Taiwan.
| | - Yun Yen
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Ph.D. Program for Cancer Biology and Drug Discovery, Taipei Medical University, Taipei City, 110301, Taiwan.
- Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei City, 110301, Taiwan.
- TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei City, 110301, Taiwan.
- Cancer Center, Taipei Municipal WanFang Hospital, Taipei City, 116081, Taiwan.
| |
Collapse
|
13
|
Baba A, Kurokawa R, Kurokawa M, Ota Y, Srinivasan A. Dynamic Contrast-Enhanced MRI Parameters and Normalized ADC Values Could Aid Differentiation of Skull Base Osteomyelitis from Nasopharyngeal Cancer. AJNR Am J Neuroradiol 2023; 44:74-78. [PMID: 36521963 PMCID: PMC9835913 DOI: 10.3174/ajnr.a7740] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 11/15/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND AND PURPOSE The skull base osteomyelitis sometimes can be difficult to distinguish from nasopharyngeal cancer. This study aimed to investigate the differences between skull base osteomyelitis and nasopharyngeal cancer using dynamic contrast-enhanced MR imaging and normalized ADC values. MATERIALS AND METHODS This study included 8 and 12 patients with skull base osteomyelitis and nasopharyngeal cancer, respectively, who underwent dynamic contrast-enhanced MR imaging and DWI before primary treatment. Quantitative dynamic contrast-enhanced MR imaging parameters and ADC values of the ROIs were analyzed. Normalized ADC parameters were calculated by dividing the ROIs of the lesion by that of the spinal cord. RESULTS The rate transfer constant between extravascular extracellular space and blood plasma per minute (Kep) was significantly lower in patients with skull base osteomyelitis than in those with nasopharyngeal cancer (median, 0.43 versus 0.57; P = .04). The optimal cutoff value of Kep was 0.48 (area under the curve, 0.78; 95% CI, 0.55-1). The normalized mean ADC was significantly higher in patients with skull base osteomyelitis than in those with nasopharyngeal cancer (median, 1.90 versus 0.87; P < .001). The cutoff value of normalized mean ADC was 1.55 (area under the curve, 0.96; 95% CI, 0.87-1). The area under the curve of the combination of dynamic contrast-enhanced MR imaging parameters (Kep and extravascular extracellular space volume per unit tissue volume) was 0.89 (95% CI, 0.73-1), and the area under the curve of the combination of dynamic contrast-enhanced MR imaging parameters and normalized mean ADC value was 0.98 (95% CI, 0.93-1). CONCLUSIONS Quantitative dynamic contrast-enhanced MR imaging parameters and normalized ADC values may be useful in differentiating skull base osteomyelitis and nasopharyngeal cancer. The combination of dynamic contrast-enhanced MR imaging parameters and normalized ADC values outperformed each measure in isolation.
Collapse
Affiliation(s)
- A Baba
- From the Division of Neuroradiology (A.B., R.K., M.K., Y.O., A.S.), Department of Radiology, University of Michigan, Ann Arbor, Michigan
- Department of Radiology (A.B.), The Jikei University School of Medicine, Tokyo, Japan
| | - R Kurokawa
- From the Division of Neuroradiology (A.B., R.K., M.K., Y.O., A.S.), Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | - M Kurokawa
- From the Division of Neuroradiology (A.B., R.K., M.K., Y.O., A.S.), Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | - Y Ota
- From the Division of Neuroradiology (A.B., R.K., M.K., Y.O., A.S.), Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | - A Srinivasan
- From the Division of Neuroradiology (A.B., R.K., M.K., Y.O., A.S.), Department of Radiology, University of Michigan, Ann Arbor, Michigan
| |
Collapse
|
14
|
Teunissen WHT, Govaerts CW, Kramer MCA, Labrecque JA, Smits M, Dirven L, van der Hoorn A. Diagnostic accuracy of MRI techniques for treatment response evaluation in patients with brain metastasis: A systematic review and meta-analysis. Radiother Oncol 2022; 177:121-133. [PMID: 36377093 DOI: 10.1016/j.radonc.2022.10.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 10/11/2022] [Accepted: 10/21/2022] [Indexed: 11/12/2022]
Abstract
BACKGROUND Treatment response assessment in patients with brain metastasis uses contrast enhanced T1-weighted MRI. Advanced MRI techniques have been studied, but the diagnostic accuracy is not well known. Therefore, we performed a metaanalysis to assess the diagnostic accuracy of the currently available MRI techniques for treatment response. METHODS A systematic literature search was done. Study selection and data extraction were done by two authors independently. Meta-analysis was performed using a bivariate random effects model. An independent cohort was used for DSC perfusion external validation of diagnostic accuracy. RESULTS Anatomical MRI (16 studies, 726 lesions) showed a pooled sensitivity of 79% and a specificity of 76%. DCE perfusion (4 studies, 114 lesions) showed a pooled sensitivity of 74% and a specificity of 92%. DSC perfusion (12 studies, 418 lesions) showed a pooled sensitivity was 83% with a specificity of 78%. Diffusion weighted imaging (7 studies, 288 lesions) showed a pooled sensitivity of 67% and a specificity of 79%. MRS (4 studies, 54 lesions) showed a pooled sensitivity of 80% and a specificity of 78%. Combined techniques (6 studies, 375 lesions) showed a pooled sensitivity of 84% and a specificity of 88%. External validation of DSC showed a lower sensitivity and a higher specificity for the reported cut-off values included in this metaanalysis. CONCLUSION A combination of techniques shows the highest diagnostic accuracy differentiating tumor progression from treatment induced abnormalities. External validation of imaging results is important to better define the reliability of imaging results with the different techniques.
Collapse
Affiliation(s)
- Wouter H T Teunissen
- Erasmus MC, department of Radiology and Nuclear Medicine, Rotterdam, the Netherlands; Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands; Medical Delta, Delft, The Netherlands
| | - Chris W Govaerts
- University Medical Center Groningen, Medical imaging center, department of Radiology, Groningen, the Netherlands
| | - Miranda C A Kramer
- University Medical Center Groningen, department of Radiotherapy, Groningen, the Netherlands
| | - Jeremy A Labrecque
- Erasmus MC, Netherlands Institute for Health Science (NIHES), Rotterdam, the Netherlands
| | - Marion Smits
- Erasmus MC, department of Radiology and Nuclear Medicine, Rotterdam, the Netherlands; Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands; Medical Delta, Delft, The Netherlands
| | - Linda Dirven
- Leiden University Medical Center, department of Neurology, Leiden, the Netherlands; Haaglanden Medical Center, department of Neurology, The Hague, the Netherlands
| | - Anouk van der Hoorn
- University Medical Center Groningen, Medical imaging center, department of Radiology, Groningen, the Netherlands.
| |
Collapse
|
15
|
KALA D, ŠULC V, OLŠEROVÁ A, SVOBODA J, PRYSIAZHNIUK Y, POŠUSTA A, KYNČL M, ŠANDA J, TOMEK A, OTÁHAL J. Evaluation of blood-brain barrier integrity by the analysis of dynamic contrast-enhanced MRI - a comparison of quantitative and semi-quantitative methods. Physiol Res 2022; 71:S259-S275. [PMID: 36647914 PMCID: PMC9906669 DOI: 10.33549/physiolres.934998] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Disruption of the blood-brain barrier (BBB) is a key feature of various brain disorders. To assess its integrity a parametrization of dynamic magnetic resonance imaging (DCE MRI) with a contrast agent (CA) is broadly used. Parametrization can be done quantitatively or semi-quantitatively. Quantitative methods directly describe BBB permeability but exhibit several drawbacks such as high computation demands, reproducibility issues, or low robustness. Semi-quantitative methods are fast to compute, simply mathematically described, and robust, however, they do not describe the status of BBB directly but only as a variation of CA concentration in measured tissue. Our goal was to elucidate differences between five semi-quantitative parameters: maximal intensity (Imax), normalized permeability index (NPI), and difference in DCE values between three timepoints: baseline, 5 min, and 15 min (delta5-0, delta15-0, delta15-5) and two quantitative parameters: transfer constant (Ktrans) and an extravascular fraction (Ve). For the purpose of comparison, we analyzed DCE data of four patients 12-15 days after the stroke with visible CA enhancement. Calculated parameters showed abnormalities spatially corresponding with the ischemic lesion, however, findings in individual parameters morphometrically differed. Ktrans and Ve were highly correlated. Delta5-0 and delta15-0 were prominent in regions with rapid CA enhancement and highly correlated with Ktrans. Abnormalities in delta15-5 and NPI were more homogenous with less variable values, smoother borders, and less detail than Ktrans. Moreover, only delta15-5 and NPI were able to distinguish vessels from extravascular space. Our comparison provides important knowledge for understanding and interpreting parameters derived from DCE MRI by both quantitative and semi-quantitative methods.
Collapse
Affiliation(s)
- David KALA
- Laboratory of Developmental Epileptology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic,Faculty of Electrical Engineering, Czech Technical University in Prague, Czech Republic
| | - Vlastimil ŠULC
- Department of Neurology, Second Faculty of Medicine, Charles University and University Hospital Motol, Prague, Czech Republic
| | - Anna OLŠEROVÁ
- Department of Neurology, Second Faculty of Medicine, Charles University and University Hospital Motol, Prague, Czech Republic
| | - Jan SVOBODA
- Laboratory of Developmental Epileptology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
| | - Yeva PRYSIAZHNIUK
- Laboratory of Developmental Epileptology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
| | - Antonín POŠUSTA
- Laboratory of Developmental Epileptology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
| | - Martin KYNČL
- Department of Radiology, Second Faculty of Medicine, Charles University and University Hospital Motol, Prague, Czech Republic
| | - Jan ŠANDA
- Department of Radiology, Second Faculty of Medicine, Charles University and University Hospital Motol, Prague, Czech Republic
| | - Aleš TOMEK
- Department of Neurology, Second Faculty of Medicine, Charles University and University Hospital Motol, Prague, Czech Republic
| | - Jakub OTÁHAL
- Laboratory of Developmental Epileptology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic,Department of Pathophysiology, Second Faculty of Medicine, Charles University, Czech Republic
| |
Collapse
|
16
|
Michalet M, Riou O, Azria D, Decoene C, Crop F. News in magnetic resonance imaging use for radiation oncology. Cancer Radiother 2022; 26:784-788. [PMID: 36031496 DOI: 10.1016/j.canrad.2022.06.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 06/28/2022] [Accepted: 06/30/2022] [Indexed: 11/29/2022]
Abstract
The purpose of this article is to give a summary of the progress of magnetic resonance imaging (MRI) in radiotherapy. MRI is an important imaging modality for treatment planning in radiotherapy. However, the registration step with the simulation scanner can be a source of errors, motivating the implementation of all-MRI simulation methods and new accelerators coupled with on-board MRI. First, practical MRI imaging for radiotherapy is detailed, but also the importance of a coherent imaging workflow incorporating all imaging modalities. Second, future evolutions and research domains such as quantitative imaging biomarkers, MRI-only pseudo computed tomography and radiomics are discussed. Finally, the application of MRI during radiotherapy treatment is reviewed: the use of MR-linear accelerators. MRI is increasingly integrated into radiotherapy. Advances in diagnostic imaging can thus benefit radiotherapy, but specific radiotherapy constraints lead to additional challenges and require close collaboration between radiologists, radiation oncologists, technologists and physicists. The integration of quantitative imaging biomarkers in the radiotherapy process will result in mutual benefit for diagnostic imaging and radiotherapy. MRI-guided radiotherapy has already been used for several years in clinical routine. Abdominopelvic neoplasias (pancreas, liver, prostate) are the preferred locations for treatment because of their favourable contrast in MRI, their movement during irradiation and their proximity to organs at risk of radiation exposure, making the tracking and daily adaptation of the plan essential. MRI has emerged as an increasingly necessary imaging modality for radiotherapy planning. Inclusion of patients in clinical trials evaluating new MRI-guided radiotherapy techniques and associated quantitative imaging biomarkers will be necessary to assess the benefits.
Collapse
Affiliation(s)
- M Michalet
- Institut du cancer de Montpellier, Fédération universitaire d'oncologie-radiothérapie d'Occitanie Méditerranée (Forom), Inserm U1194 IRCM, 208, avenue des Apothicaires, 34298 Montpellier, France.
| | - O Riou
- Institut du cancer de Montpellier, Fédération universitaire d'oncologie-radiothérapie d'Occitanie Méditerranée (Forom), Inserm U1194 IRCM, 208, avenue des Apothicaires, 34298 Montpellier, France
| | - D Azria
- Institut du cancer de Montpellier, Fédération universitaire d'oncologie-radiothérapie d'Occitanie Méditerranée (Forom), Inserm U1194 IRCM, 208, avenue des Apothicaires, 34298 Montpellier, France
| | - C Decoene
- Medical physics, centre Oscar-Lambret, 3, rue Frédéric-Combemale, 59000 Lille, France
| | - F Crop
- Medical physics, centre Oscar-Lambret, 3, rue Frédéric-Combemale, 59000 Lille, France
| |
Collapse
|
17
|
Li AY, Iv M. Conventional and Advanced Imaging Techniques in Post-treatment Glioma Imaging. FRONTIERS IN RADIOLOGY 2022; 2:883293. [PMID: 37492665 PMCID: PMC10365131 DOI: 10.3389/fradi.2022.883293] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 06/06/2022] [Indexed: 07/27/2023]
Abstract
Despite decades of advancement in the diagnosis and therapy of gliomas, the most malignant primary brain tumors, the overall survival rate is still dismal, and their post-treatment imaging appearance remains very challenging to interpret. Since the limitations of conventional magnetic resonance imaging (MRI) in the distinction between recurrence and treatment effect have been recognized, a variety of advanced MR and functional imaging techniques including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), MR spectroscopy (MRS), as well as a variety of radiotracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) have been investigated for this indication along with voxel-based and more quantitative analytical methods in recent years. Machine learning and radiomics approaches in recent years have shown promise in distinguishing between recurrence and treatment effect as well as improving prognostication in a malignancy with a very short life expectancy. This review provides a comprehensive overview of the conventional and advanced imaging techniques with the potential to differentiate recurrence from treatment effect and includes updates in the state-of-the-art in advanced imaging with a brief overview of emerging experimental techniques. A series of representative cases are provided to illustrate the synthesis of conventional and advanced imaging with the clinical context which informs the radiologic evaluation of gliomas in the post-treatment setting.
Collapse
Affiliation(s)
- Anna Y. Li
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
| | - Michael Iv
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
| |
Collapse
|
18
|
Malik DG, Rath TJ, Urcuyo Acevedo JC, Canoll PD, Swanson KR, Boxerman JL, Quarles CC, Schmainda KM, Burns TC, Hu LS. Advanced MRI Protocols to Discriminate Glioma From Treatment Effects: State of the Art and Future Directions. FRONTIERS IN RADIOLOGY 2022; 2:809373. [PMID: 37492687 PMCID: PMC10365126 DOI: 10.3389/fradi.2022.809373] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 03/01/2022] [Indexed: 07/27/2023]
Abstract
In the follow-up treatment of high-grade gliomas (HGGs), differentiating true tumor progression from treatment-related effects, such as pseudoprogression and radiation necrosis, presents an ongoing clinical challenge. Conventional MRI with and without intravenous contrast serves as the clinical benchmark for the posttreatment surveillance imaging of HGG. However, many advanced imaging techniques have shown promise in helping better delineate the findings in indeterminate scenarios, as posttreatment effects can often mimic true tumor progression on conventional imaging. These challenges are further confounded by the histologic admixture that can commonly occur between tumor growth and treatment-related effects within the posttreatment bed. This review discusses the current practices in the surveillance imaging of HGG and the role of advanced imaging techniques, including perfusion MRI and metabolic MRI.
Collapse
Affiliation(s)
- Dania G. Malik
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Tanya J. Rath
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Javier C. Urcuyo Acevedo
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Peter D. Canoll
- Departments of Pathology and Cell Biology, Columbia University, New York, NY, United States
| | - Kristin R. Swanson
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Jerrold L. Boxerman
- Department of Diagnostic Imaging, Brown University, Providence, RI, United States
| | - C. Chad Quarles
- Department of Neuroimaging Research & Barrow Neuroimaging Innovation Center, Barrow Neurologic Institute, Phoenix, AZ, United States
| | - Kathleen M. Schmainda
- Department of Biophysics & Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Terry C. Burns
- Departments of Neurologic Surgery and Neuroscience, Mayo Clinic, Rochester, MN, United States
| | - Leland S. Hu
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| |
Collapse
|
19
|
Albano D, Bruno F, Agostini A, Angileri SA, Benenati M, Bicchierai G, Cellina M, Chianca V, Cozzi D, Danti G, De Muzio F, Di Meglio L, Gentili F, Giacobbe G, Grazzini G, Grazzini I, Guerriero P, Messina C, Micci G, Palumbo P, Rocco MP, Grassi R, Miele V, Barile A. Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging. Jpn J Radiol 2021; 40:341-366. [PMID: 34951000 DOI: 10.1007/s11604-021-01223-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 11/17/2021] [Indexed: 12/18/2022]
Abstract
Dynamic contrast-enhanced (DCE) imaging is a non-invasive technique used for the evaluation of tissue vascularity features through imaging series acquisition after contrast medium administration. Over the years, the study technique and protocols have evolved, seeing a growing application of this method across different imaging modalities for the study of almost all body districts. The main and most consolidated current applications concern MRI imaging for the study of tumors, but an increasing number of studies are evaluating the use of this technique also for inflammatory pathologies and functional studies. Furthermore, the recent advent of artificial intelligence techniques is opening up a vast scenario for the analysis of quantitative information deriving from DCE. The purpose of this article is to provide a comprehensive update on the techniques, protocols, and clinical applications - both established and emerging - of DCE in whole-body imaging.
Collapse
Affiliation(s)
- Domenico Albano
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- IRCCS Istituto Ortopedico Galeazzi, Milan, Italy
- Dipartimento Di Biomedicina, Neuroscienze E Diagnostica Avanzata, Sezione Di Scienze Radiologiche, Università Degli Studi Di Palermo, via Vetoio 1L'Aquila, 67100, Palermo, Italy
| | - Federico Bruno
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy.
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
| | - Andrea Agostini
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Clinical, Special and Dental Sciences, Department of Radiology, University Politecnica delle Marche, University Hospital "Ospedali Riuniti Umberto I - G.M. Lancisi - G. Salesi", Ancona, Italy
| | - Salvatore Alessio Angileri
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Radiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Massimo Benenati
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Dipartimento di Diagnostica per Immagini, Fondazione Policlinico Universitario A. Gemelli IRCCS, Oncologia ed Ematologia, RadioterapiaRome, Italy
| | - Giulia Bicchierai
- Diagnostic Senology Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Michaela Cellina
- Department of Radiology, ASST Fatebenefratelli Sacco, Ospedale Fatebenefratelli, Milan, Italy
| | - Vito Chianca
- Ospedale Evangelico Betania, Naples, Italy
- Clinica Di Radiologia, Istituto Imaging Della Svizzera Italiana - Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Diletta Cozzi
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Emergency Radiology, Careggi University Hospital, Florence, Italy
| | - Ginevra Danti
- Department of Emergency Radiology, Careggi University Hospital, Florence, Italy
| | - Federica De Muzio
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, Campobasso, Italy
| | - Letizia Di Meglio
- Postgraduation School in Radiodiagnostics, University of Milan, Milan, Italy
| | - Francesco Gentili
- Unit of Diagnostic Imaging, Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Giuliana Giacobbe
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Precision Medicine, University of Campania "L. Vanvitelli", Naples, Italy
| | - Giulia Grazzini
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Irene Grazzini
- Department of Radiology, Section of Neuroradiology, San Donato Hospital, Arezzo, Italy
| | - Pasquale Guerriero
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, Campobasso, Italy
| | | | - Giuseppe Micci
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Dipartimento Di Biomedicina, Neuroscienze E Diagnostica Avanzata, Sezione Di Scienze Radiologiche, Università Degli Studi Di Palermo, via Vetoio 1L'Aquila, 67100, Palermo, Italy
| | - Pierpaolo Palumbo
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Abruzzo Health Unit 1, Department of diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, L'Aquila, Italy
| | - Maria Paola Rocco
- Department of Precision Medicine, University of Campania "L. Vanvitelli", Naples, Italy
| | - Roberto Grassi
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Precision Medicine, University of Campania "L. Vanvitelli", Naples, Italy
| | - Vittorio Miele
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Antonio Barile
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| |
Collapse
|
20
|
Radiotherapy in Current Neuro-Oncology: There Is Still Much to Reveal. Life (Basel) 2021; 11:life11121412. [PMID: 34947942 PMCID: PMC8706956 DOI: 10.3390/life11121412] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 12/11/2021] [Accepted: 12/16/2021] [Indexed: 01/07/2023] Open
|
21
|
Abstract
Imaging of brain metastases (BMs) has advanced greatly over the past decade. In this review, we discuss the main challenges that BMs pose in clinical practice and describe the role of imaging.Firstly, we describe the increased incidence of BMs of different primary tumours and the rationale for screening. A challenge lies in selecting the right patients for screening: not all cancer patients develop BMs in their disease course.Secondly, we discuss the imaging techniques to detect BMs. A three-dimensional (3D) T1W MRI sequence is the golden standard for BM detection, but additional anatomical (susceptibility weighted imaging, diffusion weighted imaging), functional (perfusion MRI) and metabolic (MR spectroscopy, positron emission tomography) information can help to differentiate BMs from other intracranial aetiologies.Thirdly, we describe the role of imaging before, during and after treatment of BMs. For surgical resection, imaging is used to select surgical patients, but also to assist intraoperatively (neuronavigation, fluorescence-guided surgery, ultrasound). For treatment planning of stereotactic radiosurgery, MRI is combined with CT. For surveillance after both local and systemic therapies, conventional MRI is used. However, advanced imaging is increasingly performed to distinguish true tumour progression from pseudoprogression.FInally, future perspectives are discussed, including radiomics, new biomarkers, new endogenous contrast agents and theranostics.
Collapse
Affiliation(s)
- Sophie H A E Derks
- Department of Neuro-Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.,Department of Radiology & Nuclear Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.,Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Astrid A M van der Veldt
- Department of Radiology & Nuclear Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.,Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| |
Collapse
|
22
|
Abstract
PURPOSE OF REVIEW This review aims to cover current MRI techniques for assessing treatment response in brain tumors, with a focus on radio-induced lesions. RECENT FINDINGS Pseudoprogression and radionecrosis are common radiological entities after brain tumor irradiation and are difficult to distinguish from real progression, with major consequences on daily patient care. To date, shortcomings of conventional MRI have been largely recognized but morphological sequences are still used in official response assessment criteria. Several complementary advanced techniques have been proposed but none of them have been validated, hampering their clinical use. Among advanced MRI, brain perfusion measures increase diagnostic accuracy, especially when added with spectroscopy and susceptibility-weighted imaging. However, lack of reproducibility, because of several hard-to-control variables, is still a major limitation for their standardization in routine protocols. Amide Proton Transfer is an emerging molecular imaging technique that promises to offer new metrics by indirectly quantifying intracellular mobile proteins and peptide concentration. Preliminary studies suggest that this noncontrast sequence may add key biomarkers in tumor evaluation, especially in posttherapeutic settings. SUMMARY Benefits and pitfalls of conventional and advanced imaging on posttreatment assessment are discussed and the potential added value of APT in this clinicoradiological evolving scenario is introduced.
Collapse
Affiliation(s)
- Lucia Nichelli
- Department of Neuroradiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière-Charles Foix
- Sorbonne Université, INSERM, CNRS, Assistance Publique-Hôpitaux de Paris, Institut du Cerveau et de la Moelle épinière, boulevard de l’Hôpital, Paris
| | - Stefano Casagranda
- Department of Research & Innovation, Olea Medical, avenue des Sorbiers, La Ciotat, France
| |
Collapse
|
23
|
Ko CC, Yeh LR, Kuo YT, Chen JH. Imaging biomarkers for evaluating tumor response: RECIST and beyond. Biomark Res 2021; 9:52. [PMID: 34215324 PMCID: PMC8252278 DOI: 10.1186/s40364-021-00306-8] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 06/10/2021] [Indexed: 12/12/2022] Open
Abstract
Response Evaluation Criteria in Solid Tumors (RECIST) is the gold standard for assessment of treatment response in solid tumors. Morphologic change of tumor size evaluated by RECIST is often correlated with survival length and has been considered as a surrogate endpoint of therapeutic efficacy. However, the detection of morphologic change alone may not be sufficient for assessing response to new anti-cancer medication in all solid tumors. During the past fifteen years, several molecular-targeted therapies and immunotherapies have emerged in cancer treatment which work by disrupting signaling pathways and inhibited cell growth. Tumor necrosis or lack of tumor progression is associated with a good therapeutic response even in the absence of tumor shrinkage. Therefore, the use of unmodified RECIST criteria to estimate morphological changes of tumor alone may not be sufficient to estimate tumor response for these new anti-cancer drugs. Several studies have reported the low reliability of RECIST in evaluating treatment response in different tumors such as hepatocellular carcinoma, lung cancer, prostate cancer, brain glioma, bone metastasis, and lymphoma. There is an increased need for new medical imaging biomarkers, considering the changes in tumor viability, metabolic activity, and attenuation, which are related to early tumor response. Promising imaging techniques, beyond RECIST, include dynamic contrast-enhanced computed tomography (CT) or magnetic resonance imaging (MRI), diffusion-weight imaging (DWI), magnetic resonance spectroscopy (MRS), and 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET). This review outlines the current RECIST with their limitations and the new emerging concepts of imaging biomarkers in oncology.
Collapse
Affiliation(s)
- Ching-Chung Ko
- Department of Medical Imaging, Chi Mei Medical Center, Tainan, Taiwan.,Department of Health and Nutrition, Chia Nan University of Pharmacy and Science, Tainan, Taiwan
| | - Lee-Ren Yeh
- Department of Radiology, E-DA Hospital, I-Shou University, Kaohsiung, Taiwan
| | - Yu-Ting Kuo
- Department of Medical Imaging, Chi Mei Medical Center, Tainan, Taiwan.,Department of Medical Imaging, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Jeon-Hor Chen
- Department of Radiology, E-DA Hospital, I-Shou University, Kaohsiung, Taiwan. .,Tu & Yuan Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, 164 Irvine Hall, Irvine, CA, 92697 - 5020, USA.
| |
Collapse
|
24
|
A Multiparametric MRI-Based Radiomics Analysis to Efficiently Classify Tumor Subregions of Glioblastoma: A Pilot Study in Machine Learning. J Clin Med 2021; 10:jcm10092030. [PMID: 34068528 PMCID: PMC8126019 DOI: 10.3390/jcm10092030] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 04/29/2021] [Accepted: 05/05/2021] [Indexed: 12/24/2022] Open
Abstract
Glioblastoma multiforme (GBM) carries a poor prognosis and usually presents with heterogenous regions of a necrotic core, solid part, peritumoral tissue, and peritumoral edema. Accurate demarcation on magnetic resonance imaging (MRI) between the active tumor region and perifocal edematous extension is essential for planning stereotactic biopsy, GBM resection, and radiotherapy. We established a set of radiomics features to efficiently classify patients with GBM and retrieved cerebral multiparametric MRI, including contrast-enhanced T1-weighted (T1-CE), T2-weighted, T2-weighted fluid-attenuated inversion recovery, and apparent diffusion coefficient images from local patients with GBM. A total of 1316 features on the raw MR images were selected for each annotated area. A leave-one-out cross-validation was performed on the whole dataset, the different machine learning and deep learning techniques tested; random forest achieved the best performance (average accuracy: 93.6% necrosis, 90.4% solid part, 95.8% peritumoral tissue, and 90.4% peritumoral edema). The features from the enhancing tumor and the tumor shape elongation of peritumoral edema region for high-risk groups from T1-CE. The multiparametric MRI-based radiomics model showed the efficient classification of tumor subregions of GBM and suggests that prognostic radiomic features from a routine MRI exam may also be significantly associated with key biological processes that affect the response to chemotherapy in GBM.
Collapse
|
25
|
Diffusion- and Perfusion-Weighted Magnetic Resonance Imaging Methods in Nonenhancing Gliomas. World Neurosurg 2020; 141:123-130. [DOI: 10.1016/j.wneu.2020.05.278] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 05/29/2020] [Accepted: 05/30/2020] [Indexed: 12/21/2022]
|
26
|
Lee D, Riestenberg RA, Haskell-Mendoza A, Bloch O. Brain Metastasis Recurrence Versus Radiation Necrosis: Evaluation and Treatment. Neurosurg Clin N Am 2020; 31:575-587. [PMID: 32921353 DOI: 10.1016/j.nec.2020.06.007] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Radiation necrosis (RN) occurs in 5% to 25% of patients with brain metastases treated with stereotactic radiosurgery. RN must be distinguished from recurrent tumor to determine appropriate treatment. Stereotactic biopsy remains the gold standard for identifying RN. Initial treatment of RN often involves management of edema using corticosteroids, antiangiogenic therapies, and hyperbaric oxygen therapy. For refractory symptoms, surgical resection can be considered. Minimally invasive stereotactic laser ablation has the benefit of providing tissue diagnosis and treating RN or recurrent tumor with similar efficacy. Laser ablation should be considered for lesions in need of intervention where the diagnosis requires tissue confirmation.
Collapse
Affiliation(s)
- Dennis Lee
- Department of Neurological Surgery, University of California Davis, 4860 Y Street, Suite 3740, Sacramento, CA 95817, USA
| | - Robert A Riestenberg
- Department of Neurological Surgery, University of California Davis, 4860 Y Street, Suite 3740, Sacramento, CA 95817, USA
| | - Aden Haskell-Mendoza
- Department of Neurological Surgery, University of California Davis, 4860 Y Street, Suite 3740, Sacramento, CA 95817, USA
| | - Orin Bloch
- Department of Neurological Surgery, University of California, Davis School of Medicine, University of California Davis, 4860 Y Street, Suite 3740, Sacramento, CA 95817, USA.
| |
Collapse
|
27
|
Sanders JW, Chen HSM, Johnson JM, Schomer DF, Jimenez JE, Ma J, Liu HL. Synthetic generation of DSC-MRI-derived relative CBV maps from DCE MRI of brain tumors. Magn Reson Med 2020; 85:469-479. [PMID: 32726488 DOI: 10.1002/mrm.28432] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2020] [Revised: 06/21/2020] [Accepted: 06/24/2020] [Indexed: 12/26/2022]
Abstract
PURPOSE Perfusion MRI with gadolinium-based contrast agents is useful for diagnosis and treatment response evaluation of brain tumors. Dynamic susceptibility contrast (DSC) MRI and dynamic contrast enhanced (DCE) MRI are two gadolinium-based contrast agent perfusion imaging techniques that provide complementary information about the tumor vasculature. However, each requires a separate administration of a gadolinium-based contrast agent. The purpose of this retrospective study was to determine the feasibility of synthesizing relative cerebral blood volume (rCBV) maps, as computed from DSC MRI, from DCE MRI of brain tumors. METHODS One hundred nine brain-tumor patients underwent both DCE and DSC MRI. Relative CBV maps were computed from the DSC MRI, and blood plasma volume fraction maps were computed from the DCE MRIs. Conditional generative adversarial networks were developed to synthesize rCBV maps from the DCE MRIs. Tumor-to-white matter ratios were calculated from real rCBV, synthetic rCBV, and plasma volume fraction maps and compared using correlation analysis. Real and synthetic rCBV in white and gray matter regions were also compared. RESULTS Pearson correlation analysis showed that both the tumor rCBV and tumor-to-white matter ratios in the synthetic and real rCBV maps were strongly correlated (ρ = 0.87, P < .05 and ρ = 0.86, P < .05, respectively). Tumor plasma volume fraction and real rCBV were not strongly correlated (ρ = 0.47). Bland-Altman analysis showed a mean difference between the synthetic and real rCBV tumor-to-white matter ratios of 0.20 with a 95% confidence interval of ±0.47. CONCLUSION Realistic rCBV maps can be synthesized from DCE MRI and contain quantitative information, enabling robust brain-tumor perfusion imaging of DSC and DCE parameters with a single gadolinium-based contrast agent administration.
Collapse
Affiliation(s)
- Jeremiah W Sanders
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,Medical Physics Graduate Program, The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, Texas, USA
| | - Henry Szu-Meng Chen
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jason M Johnson
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Donald F Schomer
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jorge E Jimenez
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,Medical Physics Graduate Program, The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, Texas, USA
| | - Ho-Ling Liu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| |
Collapse
|
28
|
Schmitt D, Blanck O, Gauer T, Fix MK, Brunner TB, Fleckenstein J, Loutfi-Krauss B, Manser P, Werner R, Wilhelm ML, Baus WW, Moustakis C. Technological quality requirements for stereotactic radiotherapy : Expert review group consensus from the DGMP Working Group for Physics and Technology in Stereotactic Radiotherapy. Strahlenther Onkol 2020; 196:421-443. [PMID: 32211939 PMCID: PMC7182540 DOI: 10.1007/s00066-020-01583-2] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2020] [Accepted: 01/13/2020] [Indexed: 12/25/2022]
Abstract
This review details and discusses the technological quality requirements to ensure the desired quality for stereotactic radiotherapy using photon external beam radiotherapy as defined by the DEGRO Working Group Radiosurgery and Stereotactic Radiotherapy and the DGMP Working Group for Physics and Technology in Stereotactic Radiotherapy. The covered aspects of this review are 1) imaging for target volume definition, 2) patient positioning and target volume localization, 3) motion management, 4) collimation of the irradiation and beam directions, 5) dose calculation, 6) treatment unit accuracy, and 7) dedicated quality assurance measures. For each part, an expert review for current state-of-the-art techniques and their particular technological quality requirement to reach the necessary accuracy for stereotactic radiotherapy divided into intracranial stereotactic radiosurgery in one single fraction (SRS), intracranial fractionated stereotactic radiotherapy (FSRT), and extracranial stereotactic body radiotherapy (SBRT) is presented. All recommendations and suggestions for all mentioned aspects of stereotactic radiotherapy are formulated and related uncertainties and potential sources of error discussed. Additionally, further research and development needs in terms of insufficient data and unsolved problems for stereotactic radiotherapy are identified, which will serve as a basis for the future assignments of the DGMP Working Group for Physics and Technology in Stereotactic Radiotherapy. The review was group peer-reviewed, and consensus was obtained through multiple working group meetings.
Collapse
Affiliation(s)
- Daniela Schmitt
- Klinik für Radioonkologie und Strahlentherapie, National Center for Radiation Research in Oncology (NCRO), Heidelberger Institut für Radioonkologie (HIRO), Universitätsklinikum Heidelberg, Heidelberg, Germany.
| | - Oliver Blanck
- Klinik für Strahlentherapie, Universitätsklinikum Schleswig-Holstein, Kiel, Germany
| | - Tobias Gauer
- Klinik für Strahlentherapie und Radioonkologie, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Michael K Fix
- Abteilung für Medizinische Strahlenphysik und Universitätsklinik für Radio-Onkologie, Inselspital-Universitätsspital Bern, Universität Bern, Bern, Switzerland
| | - Thomas B Brunner
- Universitätsklinik für Strahlentherapie, Universitätsklinikum Magdeburg, Magdeburg, Germany
| | - Jens Fleckenstein
- Klinik für Strahlentherapie und Radioonkologie, Universitätsmedizin Mannheim, Universität Heidelberg, Mannheim, Germany
| | - Britta Loutfi-Krauss
- Klinik für Strahlentherapie und Onkologie, Universitätsklinikum Frankfurt, Frankfurt am Main, Germany
| | - Peter Manser
- Abteilung für Medizinische Strahlenphysik und Universitätsklinik für Radio-Onkologie, Inselspital-Universitätsspital Bern, Universität Bern, Bern, Switzerland
| | - Rene Werner
- Institut für Computational Neuroscience, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Maria-Lisa Wilhelm
- Klinik für Strahlentherapie, Universitätsmedizin Rostock, Rostock, Germany
| | - Wolfgang W Baus
- Klinik für Radioonkologie, CyberKnife- und Strahlentherapie, Universitätsklinikum Köln, Cologne, Germany
| | - Christos Moustakis
- Klinik für Strahlentherapie-Radioonkologie, Universitätsklinikum Münster, Münster, Germany
| |
Collapse
|
29
|
Tong E, McCullagh KL, Iv M. Advanced Imaging of Brain Metastases: From Augmenting Visualization and Improving Diagnosis to Evaluating Treatment Response. Front Neurol 2020; 11:270. [PMID: 32351445 PMCID: PMC7174761 DOI: 10.3389/fneur.2020.00270] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 03/24/2020] [Indexed: 12/11/2022] Open
Abstract
Early detection of brain metastases and differentiation from other neuropathologies is crucial. Although biopsy is often required for definitive diagnosis, imaging can provide useful information. After treatment commences, imaging is also performed to assess the efficacy of treatment. Contrast-enhanced magnetic resonance imaging (MRI) is the traditional imaging method for the evaluation of brain metastases, as it provides information about lesion size, morphology, and macroscopic properties. Newer MRI sequences have been developed to increase the conspicuity of detecting enhancing metastases. Other advanced MRI techniques, that have the capability to probe beyond the anatomic structure, are available to characterize micro-structures, cellularity, physiology, perfusion, and metabolism. Artificial intelligence provides powerful computational tools for detection, segmentation, classification, prediction, and prognosis. We highlight and review a few advanced MRI techniques for the assessment of brain metastases-specifically for (1) diagnosis, including differentiating between malignancy types and (2) evaluation of treatment response, including the differentiation between radiation necrosis and disease progression.
Collapse
Affiliation(s)
- Elizabeth Tong
- Stanford University Medical Center, Stanford, CA, United States
| | | | - Michael Iv
- Stanford University Medical Center, Stanford, CA, United States
| |
Collapse
|
30
|
Foray C, Barca C, Backhaus P, Schelhaas S, Winkeler A, Viel T, Schäfers M, Grauer O, Jacobs AH, Zinnhardt B. Multimodal Molecular Imaging of the Tumour Microenvironment. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2020; 1225:71-87. [PMID: 32030648 DOI: 10.1007/978-3-030-35727-6_5] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The tumour microenvironment (TME) surrounding tumour cells is a highly dynamic and heterogeneous composition of immune cells, fibroblasts, precursor cells, endothelial cells, signalling molecules and extracellular matrix (ECM) components. Due to the heterogeneity and the constant crosstalk between the TME and the tumour cells, the components of the TME are important prognostic parameters in cancer and determine the response to novel immunotherapies. To improve the characterization of the TME, novel non-invasive imaging paradigms targeting the complexity of the TME are urgently needed.The characterization of the TME by molecular imaging will (1) support early diagnosis and disease follow-up, (2) guide (stereotactic) biopsy sampling, (3) highlight the dynamic changes during disease pathogenesis in a non-invasive manner, (4) help monitor existing therapies, (5) support the development of novel TME-targeting therapies and (6) aid stratification of patients, according to the cellular composition of their tumours in correlation to their therapy response.This chapter will summarize the most recent developments and applications of molecular imaging paradigms beyond FDG for the characterization of the dynamic molecular and cellular changes in the TME.
Collapse
Affiliation(s)
- Claudia Foray
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany.,PET Imaging in Drug Design and Development (PET3D), Münster, Germany
| | - Cristina Barca
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany.,PET Imaging in Drug Design and Development (PET3D), Münster, Germany
| | - Philipp Backhaus
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany.,Department of Nuclear Medicine, University Hospital Münster, Westfälische Wilhelms University Münster, Münster, Germany
| | - Sonja Schelhaas
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany
| | - Alexandra Winkeler
- UMR 1023, IMIV, Service Hospitalier Frédéric Joliot, CEA, Inserm, Université Paris Sud, CNRS, Université Paris-Saclay, Orsay, France
| | - Thomas Viel
- Paris Centre de Recherche Cardiovasculaire, INSERM-U970, Université Paris Descartes, Paris, France
| | - Michael Schäfers
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany.,Department of Nuclear Medicine, University Hospital Münster, Westfälische Wilhelms University Münster, Münster, Germany
| | - Oliver Grauer
- Department of Neurology, University Hospital Münster, Münster, Germany
| | - Andreas H Jacobs
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany.,PET Imaging in Drug Design and Development (PET3D), Münster, Germany.,Department of Geriatrics, Johanniter Hospital, Evangelische Kliniken, Bonn, Germany
| | - Bastian Zinnhardt
- European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany. .,PET Imaging in Drug Design and Development (PET3D), Münster, Germany. .,Department of Nuclear Medicine, University Hospital Münster, Westfälische Wilhelms University Münster, Münster, Germany.
| |
Collapse
|
31
|
Yang Y, Yang Y, Wu X, Pan Y, Zhou D, Zhang H, Chen Y, Zhao J, Mo Z, Huang B. Adding DSC PWI and DWI to BT-RADS can help identify postoperative recurrence in patients with high-grade gliomas. J Neurooncol 2020; 146:363-371. [PMID: 31902040 DOI: 10.1007/s11060-019-03387-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 12/27/2019] [Indexed: 12/22/2022]
Abstract
BACKGROUND The Brain Tumor Reporting and Data System (BT-RADS) category 3 is suitable for identifying cases with intermediate probability of tumor recurrence that do not meet the Response Assessment in Neuro-Oncology (RANO) criteria for progression. The aim of this study was to evaluate the added value of dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC PWI) and diffusion-weighted imaging (DWI) to BT-RADS for differentiating tumor recurrence from non-recurrence in postoperative high-grade glioma (HGG) patients with category 3 lesions. METHODS Patients with BT-RADS category 3 lesions were included. The maximal relative cerebral blood volume (rCBVmax) and the mean apparent diffusion coefficient (ADCmean) values were measured. The added value of DSC PWI and DWI to BT-RADS was evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS Fifty-one of 91 patients had tumor recurrence, and 40 patients did not. There were significant differences in rCBVmax and ADCmean between the tumor recurrence group and non-recurrence group. Compared to BT-RADS alone, the addition of DSC PWI to BT-RADS increased the area under curve (AUC) from 0.76 (95% confidence interval [CI] 0.66-0.84) to 0.90 (95% CI 0.81-0.95) for differentiating tumor recurrence from non-recurrence. The addition of DWI to BT-RADS increased the AUC from 0.76 (95% CI 0.66-0.84) to 0.88 (95% CI 0.80-0.94). The combination of BT-RADS, DSC PWI, and DWI exhibited the best diagnostic performance (AUC = 0.95; 95% CI 0.88-0.98) for differentiating tumor recurrence from non-recurrence. CONCLUSION Adding DSC PWI and DWI to BT-RADS can significantly improve the diagnostic performance for differentiating tumor recurrence from non-recurrence in BT-RADS category 3 lesions.
Collapse
Affiliation(s)
- Yuelong Yang
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Yunjun Yang
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Xiaoling Wu
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Yi Pan
- Department of Radiotherapy, Cancer Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Dong Zhou
- Department of Neurosurgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Hongdan Zhang
- Department of Radiotherapy, Cancer Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Yonglu Chen
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Jiayun Zhao
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Zihua Mo
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Biao Huang
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China.
| |
Collapse
|