1
|
Mohammadi M, Banisharif S, Moradi F, Zamanian M, Tanzifi G, Ghaderi S. Brain diffusion MRI biomarkers after oncology treatments. Rep Pract Oncol Radiother 2024; 28:823-834. [PMID: 38515826 PMCID: PMC10954263 DOI: 10.5603/rpor.98728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 12/04/2023] [Indexed: 03/23/2024] Open
Abstract
In addition to providing a measurement of the tumor's size and dimensions, magnetic resonance imaging (MRI) provides excellent noninvasive radiographic detection of tumor location. The MRI technique is an important modality that has been shown to be useful in the prognosis, diagnosis, treatment planning, and evaluation of response and recurrence in solid cancers. Diffusion-weighted imaging (DWI) is an imaging technique that quantifies water mobility. This imaging approach is good for identifying sub-voxel microstructure of tissues, correlates with tumor cellularity, and has been proven to be valuable in the early assessment of cytotoxic treatment for a variety of malignancies. Diffusion tensor imaging (DTI) is an MRI method that assesses the preferred amount of water transport inside tissues. This enables precise measurements of water diffusion, which changes according to the direction of white matter fibers, their density, and myelination. This measurement corresponds to some related variables: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), and others. DTI biomarkers can detect subtle changes in white matter microstructure and integrity following radiation therapy (RT) or chemoradiotherapy, which may have implications for cognitive function and quality of life. In our study, these indices were evaluated after brain chemoradiotherapy.
Collapse
Affiliation(s)
- Mahdi Mohammadi
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Shabnam Banisharif
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Science, Isfahan, Iran
| | - Fatemeh Moradi
- Department of Energy Engineering & Physics, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
| | - Maryam Zamanian
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Science, Isfahan, Iran
| | - Ghazal Tanzifi
- Department of Nuclear Engineering, Islamic Azad University, Central Tehran Branch, Tehran, Iran
| | - Sadegh Ghaderi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| |
Collapse
|
2
|
Alirezaei Z, Amouheidari A, Iraji S, Hassanpour M, Hejazi SH, Davanian F, Nami MT, Rastaghi S, Shokrani P, Tsien CI, Nazem-Zadeh MR. Prediction of Normal Tissue Complication Probability (NTCP) After Radiation Therapy Using Imaging and Molecular Biomarkers and Multivariate Modelling. J Mol Neurosci 2023; 73:587-597. [PMID: 37462853 DOI: 10.1007/s12031-023-02136-9] [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: 03/07/2023] [Accepted: 06/12/2023] [Indexed: 09/24/2023]
Abstract
The aim of this study was to design a predictive radiobiological model of normal brain tissue in low-grade glioma following radiotherapy based on imaging and molecular biomarkers. Fifteen patients with primary brain tumors prospectively participated in this study and underwent radiation therapy. Magnetic resonance imaging (MRI) was obtained from the patients, including T1- and T2-weighted imaging and diffusion tensor imaging (DTI), and a generalized equivalent dose (gEUD) was calculated. The radiobiological model of the normal tissue complication probability (NTCP) was performed using the variables gEUD; axial diffusivity (AD) and radial diffusivity (RD) of the corpus callosum; and serum protein S100B by univariate and multivariate logistic regression XLIIIrd Sir Peter Freyer Memorial Lecture and Surgical Symposium (2018). Changes in AD, RD, and S100B from baseline up to the 6 months after treatment had an increasing trend and were significant in some time points (P-value < 0.05). The model resulting from RD changes in the 6 months after treatment was significantly more predictable of necrosis than other univariate models. The bivariate model combining RD changes in Gy40 dose-volume and gEUD, as well as the trivariate model obtained using gEUD, RD, and S100B, had a higher predictive value among multivariate models at the sixth month of the treatment. Changes in RD diffusion indices and in serum protein S100B value were used in the early-delayed stage as reliable biomarkers for predicting late-delayed damage (necrosis) caused by radiation in the corpus callosum. Current findings could pave the way for intervention therapies to delay the severity of damage to white matter structures, minimize cognitive impairment, and improve the quality of life of patients with low-grade glioma.
Collapse
Affiliation(s)
- Zahra Alirezaei
- Medical Physics Department, Isfahan University of Medical Science, Isfahan, Iran
| | - Alireza Amouheidari
- Research & Education, Department of Radiation Oncology, Isfahan Milad Hospital, Isfahan, Iran
| | - Sajjad Iraji
- Medical Physics and Biomedical Engineering Department, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Masoud Hassanpour
- Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Hosein Hejazi
- Skin Diseases and Leishmaniosis Research Center, Department of Parasitology and Mycology, School of Medicine, Isfahan University of Medical Science, Isfahan, Iran
| | - Fariba Davanian
- Radiology Department, School of Medicine, Isfahan University of Medical Science, Isfahan, Iran
| | | | - Sedighe Rastaghi
- Biostatistics Department, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Parvaneh Shokrani
- Medical Physics Department, Isfahan University of Medical Science, Isfahan, Iran
| | - Christina I Tsien
- Radiation Oncology Department, Washington University, St. Louis, MO, USA
| | - Mohammad-Reza Nazem-Zadeh
- Medical Physics and Biomedical Engineering Department, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
- Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran.
| |
Collapse
|
3
|
Flies CM, van Leuken KH, Voorde MT, Verhoeff JJC, De Vos FYF, Seute T, Robe PA, Witkamp TD, Hendrikse J, Dankbaar JW, Snijders TJ. Conventional MRI Criteria to Differentiate Progressive Disease from Treatment-Induced Effects in High-Grade (WHO Grade 3-4) Gliomas. Neurology 2022; 99:e77-e88. [PMID: 35437259 PMCID: PMC9259090 DOI: 10.1212/wnl.0000000000200359] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 02/22/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Post-treatment radiological deterioration of patients with an irradiated high-grade (WHO grade 3-4) glioma (HGG) may be the result of true progressive disease (PD) or treatment-induced effects (TIE). Differentiation between these entities is of great importance, but remains a diagnostic challenge. This study assesses the diagnostic value of conventional MRI characteristics to differentiate PD from TIE in HGGs. MATERIAL AND METHODS In this single-centre, retrospective, consecutive cohort study, we included adults with a HGG, who were treated with (chemo-)radiotherapy and subsequently developed a new or increasing contrast-enhancing lesion on conventional follow-up MRI. TIE and PD were defined radiologically as stable/decreased for ≥6 weeks or RANO-progression, and histologically as TIE without viable tumour or PD. Two neuroradiologists assessed twenty-one preselected MRI characteristics of the progressive lesions. The statistical analysis included logistic regression to develop a) a full multivariable model b) a diagnostic model with model reduction, and a Cohen's Kappa interrater reliability (IRR) coefficient. RESULTS 210 patients (median age=61, IQR=54-68, 189 males) with 284 lesions were included, of which 141 (50%) had PD. Median time to PD was 2 (0.7-6.1) and to TIE 0.9 (0.7-3.5) months after radiotherapy. After multivariable modelling and model reduction, the following determinants prevailed: Radiation dose (Odds ratio (OR)=0.68, 95%-CI=0.49-0.93), longer time to progression (TTP, OR=3.56, 95%-CI=1.84-6.88), marginal enhancement (OR=2.04, 95%-CI=1.09-3.83), soap bubble enhancement (OR=2.63, 95%-CI=1.39-4.98) and isointense apparent diffusion coefficient (ADC)-signal (OR=2.11, 95%-CI=1.05-4.24). ORs>1 indicate higher odds of PD. The Hosmer&Lemeshow test showed good calibration (p=0.947) and the area under the ROC-curve was 0.722 (95%-CI=0.66-0.78). In the glioblastoma subgroup, TTP, marginal enhancement and ADC-signal were significant. IRR analysis between neuroradiologists revealed moderate to near-perfect agreement for the predictive items, but poor agreement for others. DISCUSSION Several characteristics from conventional MRI are significant predictors for the discrimination between PD and TIE. However, IRR was variable. Conventional MRI characteristics from this study should be incorporated into a multimodal diagnostic model with advanced imaging techniques. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that in patients with irradiated HGGs, radiation dose, longer time to progression, marginal enhancement, soap bubble enhancement and isointense apparent ADC-signal distinguish PD from TIE.
Collapse
Affiliation(s)
- Christina M Flies
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Karlijn H van Leuken
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.,Stichting Beroepsopleiding Huisarts, the Netherlands
| | - Marlies Ten Voorde
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.,Mission of the Netherlands Reformed Congregations, in Guinea (Conakry)
| | - Joost J C Verhoeff
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Filip Y F De Vos
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Tatjana Seute
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Pierre A Robe
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Theodoor D Witkamp
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jeroen Hendrikse
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jan Willem Dankbaar
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Tom J Snijders
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| |
Collapse
|
4
|
Early Detection of Radiation-Induced Injury and Prediction of Cognitive Deficit by MRS Metabolites in Radiotherapy of Low-Grade Glioma. BIOMED RESEARCH INTERNATIONAL 2021; 2021:6616992. [PMID: 34258272 PMCID: PMC8260313 DOI: 10.1155/2021/6616992] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 02/04/2021] [Accepted: 02/21/2021] [Indexed: 12/18/2022]
Abstract
Purpose To compare the sensitivity of MRS metabolites and MoCA and ACE-R cognitive tests in the detection of radiation-induced injury in low grade glioma (LGG) patients in early and early delayed postradiation stages. Methods MRS metabolite ratios of NAA/Cr and Cho/Cr, ACE-R and MoCA cognitive tests, and dosimetric parameters in corpus callosum were analyzed during RT and up to 6-month post-RT for ten LGG patients. Results Compared to pre RT baseline, a significant decline in both NAA/Cr and Cho/Cr in the corpus callosum was seen at the 4th week of RT, 1, 3, and 6-month post-RT. These declines were detected at least 3 months before the detection of declines in cognitive functions by ACE-R and MoCA tools. Moreover, NAA/Cr alterations at 4th week of RT and 1-month post-RT were significantly negatively correlated with the mean dose received by the corpus callosum, as well as the corpus callosum 40 Gy dose volume, i.e., the volume of the corpus callosum receiving a dose greater than 40 Gy. Conclusion MRS-based biomarkers may be more sensitive than the state-of-the-art cognitive tests in the prediction of postradiation cognitive impairments. They would be utilized in treatment planning and dose sparing protocols, with a specific focus on the corpus callosum in the radiation therapy of LGG patients.
Collapse
|
5
|
Yahya N, Manan HA. Diffusion tensor imaging indices to predict cognitive changes following adult radiotherapy. Eur J Cancer Care (Engl) 2020; 30:e13329. [PMID: 32909654 DOI: 10.1111/ecc.13329] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 05/01/2020] [Accepted: 08/07/2020] [Indexed: 12/26/2022]
Abstract
BACKGROUND Diffusion tensor imaging (DTI) can detect changes to white matter tracts following assaults including high dose radiation. This study aimed to systematically evaluate DTI indices to predict cognitive changes following adult radiotherapy. MATERIALS AND METHODS We searched PubMed and Scopus electronic databases to identify eligible studies according to PRISMA guidelines. Studies were extracted for information on demographics, DTI changes and associations to cognitive outcomes. RESULTS Six studies were selected for inclusion with 110 patients (median study size: 20). 5/6 studies found significant cognitive decline and analysed relationships to DTI changes. Decreased fractional anisotropy (FA) was consistently associated with cognitive decline. Associations clustered at specific regions of cingulum and corpus callosum. Only one study conducted multivariable analysis. CONCLUSION Fractional anisotropy is a clinically meaningful biomarker for radiotherapy-related cognitive decline. Studies accruing larger patient cohorts are needed to guide therapeutic changes that can abate the decline.
Collapse
Affiliation(s)
- Noorazrul Yahya
- Diagnostic Imaging and Radiotherapy, Faculty of Health Sciences, National University of Malaysia, Kuala Lumpur, Malaysia
| | - Hanani A Manan
- Functional Image Processing Laboratory, Department of Radiology, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
| |
Collapse
|
6
|
Cerebral Radiation Necrosis: Incidence, Pathogenesis, Diagnostic Challenges, and Future Opportunities. Curr Oncol Rep 2019; 21:66. [PMID: 31218455 DOI: 10.1007/s11912-019-0818-y] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
PURPOSE OF REVIEW Cerebral radiation necrosis (CRN) is a major dose-limiting adverse event of radiotherapy. The incidence rate of RN varies with the radiotherapy modality, total dose, dose fractionation, and the nature of the lesion being targeted. In addition to these known and controllable features, there is a stochastic component to the occurrence of CRN-the genetic profile of the host or the lesion and their role in the development of CRN. RECENT FINDINGS Recent studies provide some insight into the genetic mechanisms underlying radiation-induced brain injury. In addition to these incompletely understood host factors, the diagnostic criteria for CRN using structural and functional imaging are also not clear, though multiple structural and functional imaging modalities exist, a combination of which may prove to be the ideal diagnostic imaging approach. As the utilization of novel molecular therapies and immunotherapy increases, the incidence of CNR is expected to increase and its diagnosis will become more challenging. Tissue biopsies can be insensitive and suffer from sampling biases and procedural risks. Liquid biopsies represent a promising, accurate, and non-invasive diagnostic strategy, though this modality is currently in its infancy. A better understanding of the pathogenesis of CRN will expand and optimize the diagnosis and management of CRN by better utilizing existing treatment options including bevacizumab, pentoxifylline, hyperbaric oxygen therapy, and laser interstitial thermal therapy.
Collapse
|
7
|
Quantifying effects of radiotherapy-induced microvascular injury; review of established and emerging brain MRI techniques. Radiother Oncol 2019; 140:41-53. [PMID: 31176207 DOI: 10.1016/j.radonc.2019.05.020] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 05/16/2019] [Accepted: 05/17/2019] [Indexed: 12/17/2022]
Abstract
Microvascular changes are increasingly recognised not only as primary drivers of radiotherapy treatment response in brain tumours, but also as an important contributor to short- and long-term (cognitive) side effects arising from irradiation of otherwise healthy brain tissue. As overall survival of patients with brain tumours is increasing, monitoring long-term sequels of radiotherapy-induced microvascular changes in the context of their potential predictive power for outcome, such as cognitive disability, has become increasingly relevant. Ideally, radiotherapy-induced significant microvascular changes in otherwise healthy brain tissue should be identified as early as possible to facilitate adaptive radiotherapy and to proactively start treatment to minimise the influence on these side-effects on the final outcome. Although MRI is already known to be able to detect significant long-term radiotherapy induced microvascular effects, more recently advanced MR imaging biomarkers reflecting microvascular integrity and function have been reported and might provide a more accurate and earlier detection of microvascular changes. However, the use and validation of both established and new techniques in the context of monitoring early and late radiotherapy-induced microvascular changes in both target-tissue and healthy tissue currently are minimal at best. This review aims to summarise the performance and limitations of existing methods and future opportunities for detection and quantification of radiotherapy-induced microvascular changes, as well as the relation of these findings with key clinical parameters.
Collapse
|
8
|
Das IJ, McGee KP, Tyagi N, Wang H. Role and future of MRI in radiation oncology. Br J Radiol 2018; 92:20180505. [PMID: 30383454 DOI: 10.1259/bjr.20180505] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Technical innovations and developments in areas such as disease localization, dose calculation algorithms, motion management and dose delivery technologies have revolutionized radiation therapy resulting in improved patient care with superior outcomes. A consequence of the ability to design and accurately deliver complex radiation fields is the need for improved target visualization through imaging. While CT imaging has been the standard of care for more than three decades, the superior soft tissue contrast afforded by MR has resulted in the adoption of this technology in radiation therapy. With the development of real time MR imaging techniques, the problem of real time motion management is enticing. Currently, the integration of an MR imaging and megavoltage radiation therapy treatment delivery system (MR-linac or MRL) is a reality that has the potential to provide improved target localization and real time motion management during treatment. Higher magnetic field strengths provide improved image quality potentially providing the backbone for future work related to image texture analysis-a field known as Radiomics-thereby providing meaningful information on the selection of future patients for radiation dose escalation, motion-managed treatment techniques and ultimately better patient care. On-going advances in MRL technologies promise improved real time soft tissue visualization, treatment margin reductions, beam optimization, inhomogeneity corrected dose calculation, fast multileaf collimators and volumetric arc radiation therapy. This review article provides rationale, advantages and disadvantages as well as ideas for future research in MRI related to radiation therapy mainly in adoption of MRL.
Collapse
Affiliation(s)
- Indra J Das
- 1 Department of Radiation Oncology, NYU Langone Medical Center , New York, NY , USA
| | - Kiaran P McGee
- 2 Department of Radiology, Mayo Clinic , Rochester, MN , USA
| | - Neelam Tyagi
- 3 Department of Medical Physics, Memorial Sloan-Kettering Cancer Center , New York, NY , USA
| | - Hesheng Wang
- 1 Department of Radiation Oncology, NYU Langone Medical Center , New York, NY , USA
| |
Collapse
|
9
|
Prevention of radiotherapy-induced neurocognitive dysfunction in survivors of paediatric brain tumours: the potential role of modern imaging and radiotherapy techniques. Lancet Oncol 2017; 18:e91-e100. [DOI: 10.1016/s1470-2045(17)30030-x] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2016] [Revised: 10/24/2016] [Accepted: 10/26/2016] [Indexed: 02/06/2023]
|
10
|
Deasy JO, Mayo CS, Orton CG. Treatment planning evaluation and optimization should be biologically and not dose/volume based. Med Phys 2016; 42:2753-6. [PMID: 26127027 DOI: 10.1118/1.4916670] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Affiliation(s)
- Joseph O Deasy
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York 10065 (Tel: 212-639-8413; E-mail: )
| | - Charles S Mayo
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota 55905 (Tel: 507-293-4577; E-mail: )
| | | |
Collapse
|