Evaluation of the Impact of Magnetic Resonance Imaging (MRI) on Gross Tumor Volume (GTV) Definition for Radiation Treatment Planning (RTP) of Inoperable High Grade Gliomas (HGGs)

Sager, Omer; Dincoglan, Ferrat; Demiral, Selcuk; Gamsiz, Hakan; Uysal, Bora; Ozcan, Fatih; Colak, Onurhan; Dirican, Bahar; Beyzadeoglu, Murat

doi:https://doi.org/10.1155/2019/4282754

Concepts in Magnetic Resonance Part A, Bridging Education and Research

On this page

Abstract Introduction Materials and Methods Results Discussion Data Availability Conflicts of Interest Authors’ Contributions References Copyright Related Articles

Research Article | Open Access

Volume 2019 | Article ID 4282754 | https://doi.org/10.1155/2019/4282754

Evaluation of the Impact of Magnetic Resonance Imaging (MRI) on Gross Tumor Volume (GTV) Definition for Radiation Treatment Planning (RTP) of Inoperable High Grade Gliomas (HGGs)

Omer Sager,¹Ferrat Dincoglan,¹Selcuk Demiral,¹Hakan Gamsiz,¹Bora Uysal,¹Fatih Ozcan,¹Onurhan Colak,¹Bahar Dirican,¹and Murat Beyzadeoglu¹

Academic Editor: Giacomo Parigi

Received29 Mar 2019

Revised26 Jun 2019

Accepted01 Jul 2019

Published01 Aug 2019

Abstract

Aim and Background. Inoperable high-grade gliomas (HGGs) comprise a specific group of brain tumors portending a very poor prognosis. In the absence of surgical management, radiation therapy (RT) offers the primary local treatment modality for inoperable HGGs. Optimal target definition for radiation treatment planning (RTP) of HGGs is a difficult task given the diffusely infiltrative nature of the disease. In this context, detailed multimodality imaging information may add to the accuracy of target definition in HGGs. We evaluated the impact of Magnetic Resonance Imaging (MRI) on Gross Tumor Volume (GTV) definition for RTP of inoperable HGGs in this study. Materials and Methods. Twenty-five inoperable patients with a clinical diagnosis of HGG were included in the study. GTV definition was based on Computed Tomography- (CT-) simulation images only or both CT-simulation and MR images, and a comparative assessment was performed to investigate the incorporation of MRI into RTP of HGGs. Results. Median volume of GTV acquired by using CT-simulation images only and by use of CT and MR images was 65.3 (39.6-94.3) cc and 76.1 (46.8-108.9) cc, respectively. Incorporation of MRI into GTV definition has resulted in a median increase of 12.61% (6%-19%) in the volume of GTV defined by using the CT-simulation images only, which was statistically significant (p < 0.05). Conclusion. Incorporation of MRI into RTP of inoperable HGGs may improve GTV definition and may have implications for dose escalation/intensification strategies despite the need for further supporting evidence.

1. Introduction

High-grade gliomas (HGGs) refer to World Health Organization (WHO) grades III and IV gliomas including glioblastoma (GB), anaplastic astrocytoma, and anaplastic oligodendroglioma [1]. GB, the most common primary brain tumor in adults, remains to be a formidable challenge to the treating physicians with a dismal prognosis despite multimodality management [2, 3]. Several studies have focused on strategies for improving the poor outcome in the setting of newly diagnosed or recurrent disease by use of dose escalation, radiosensitization, immunotherapy, radiosurgery, and evolving intensified treatment approaches [4–10]. Maximal surgical removal of the tumor followed by chemoradiotherapy has been the standard of care for newly diagnosed GB patients after the landmark trial of European Organisation for Research and Treatment of Cancer (EORTC)/National Cancer Institute of Canada Clinical Trials Group (NCIC-CTG) in 2005 and has been widely practiced worldwide [11]. This practice-changing study has demonstrated prolonged overall survival with the addition of temozolomide (TMZ) to conventionally fractionated radiation therapy (RT) and paved the way for future trials for further achievements [11]. Nevertheless, there is still room for improvement, and there is extensive research on management of GB [12].

Radiation treatment planning (RTP) for HGGs is typically accomplished by use of Computed Tomography- (CT-) simulation. This practice allows for achieving improved precision compared to conventional planning methods utilized before the modern RT era. However, optimal target definition for RTP of HGGs is a difficult task given the diffusely infiltrative nature of the disease. In this context, detailed multimodality imaging information may add to the accuracy of target definition in HGGs. The usefulness of neuroimaging with Magnetic Resonance Imaging (MRI) for several purposes including diagnosis, lesion characterization, presurgical planning and navigation for preservation of eloquent brain regions and fiber tracts, brain tumor segmentation, disease monitoring, and discrimination of tumor progression from adverse effects of irradiation has been widely addressed in the literature [13–18]. Nevertheless, there is paucity of data on its utility for RT target definition for the distinct group of patients with inoperable HGGs. In this study, we evaluated the impact of MRI on Gross Tumor Volume (GTV) definition for RTP of inoperable HGGs.

2. Materials and Methods

Twenty-five patients with a clinical diagnosis of HGG based on MR spectroscopy and imaging features were included in this study to investigate the impact of MRI for GTV definition in RTP of inoperable HGGs. All patients were deemed to be medically inoperable due to comorbidities and/or poor performance status and were referred for definitive RT after detailed assessment by a multidisciplinary team of experts from neuroradiology, neurosurgery, and radiation oncology. Treatment with RT was decided after thorough evaluation of the patients taking into account symptomatology, lesion size, location, and association with critical neurovascular structures. Patients were informed about the details of the RT procedure including potential benefits and adverse effects. Written informed consents were obtained from all patients before RT and the study was conducted in compliance with the principles of Declaration of Helsinki. All patients had a pre-RT MRI within 1 week before CT-simulation including T1-gadolinium (Gd-DTPA, gadolinium diethylenetriaminepentaacetic acid, Magnevist®) enhanced images along with T2-weighted-fluid-attenuated inversion recovery (T2-FLAIR) images, and CT-simulations were performed at the CT-simulator (GE LightSpeed RT, GE Healthcare, Chalfont St. Giles, UK) available at our institution. Immobilization was secured by use of a thermoplastic mask for all patients. Thin-slice planning CT images including the region from the vertex to the 2 cm below the cervical spine were acquired at CT-simulation and were then transferred to the delineation workstation (SimMD, GE, UK) for contouring of treatment volumes along with neighbouring critical structures such as the brainstem, optic apparatus, cerebellum, hippocampus, and cerebral hemispheres. GTV definition was based on CT-simulation images only or both CT-simulation and MR images, and a comparative assessment was performed to investigate the incorporation of MRI into RTP of HGGs. For the purpose of this study, ground truth GTV was generated by collaboration and consensus of the board-certified radiation oncologists after detailed assessment of available imaging data of all patients. Ground truth GTV was utilized for RT of patients and was also used as a reference for comparison with GTVs defined based on CT-simulation images only or both CT-simulation and MR images. Statistical Package for the Social Sciences (SPSS, Inc., Chicago, IL) software (version 15.0) was used for data analysis with the level of significance set at p < 0.05.

3. Results

A total of 25 patients referred for definitive RT at our institution for inoperable HGG were assessed for GTV definition based on CT-simulation images only or both CT-simulation and MR images. Patient and tumor characteristics are shown on Table 1.

Axial, coronal, and sagittal images were used for determination of GTV as areas of contrast enhancement on CT and postcontrast T1-weighted MR images. Axial, coronal, and sagittal MR images of a patient used for RTP are shown in Figures 1, 2, and 3, respectively.

Median volume of GTV acquired by using CT-simulation images only, by use of CT and MR images, and by consensus of the treatment team was 65.3 (39.6-94.3) cc, 76.1 (46.8-108.9) cc, and 75.7 (46.3-108.3) cc, respectively (Figure 4).

Table 2 shows volumetric comparison of GTVs defined by CT-simulation images only, CT-simulation and MR images, and consensus of the treatment team.

When compared to GTV acquired by use of CT and MR images and by consensus of the treatment team, there was a 12.61% (6%-19%) and 12.11% (5.6%-18.63%) increase, respectively, in volume of GTV acquired by using CT-simulation images only, both with statistical significance (p < 0.05) (Table 2). There was a median decrease of 0.49% (0.37%-0.95%) in GTV based on CT-simulation and MR images compared to GTV defined by consensus of the treatment team, without statistical significance (p > 0.05) (Table 2).

4. Discussion

A critical issue in RT of HGG is optimal target definition. There may be variations in institutional practices on definition of target volumes even among cooperative group trials and large-scale studies [11, 12, 22–28]. Whole-brain irradiation (WBI) has been considered in earlier studies given the diffusely infiltrative nature of GB; however, this practice has been widely abandoned after comparative trials reported no advantage of WBI over partial brain irradiation with recurrences typically occurring within 2-3 centimeters of the original tumor [29–32]. Considering a relationship between adverse radiation effects and irradiated volumes, the rationale behind focusing on smaller target volumes is avoidance of excessive treatment related toxicity [33–35].

Since the main challenge for HGG treatment remains to be nearly inevitable recurrence in overwhelming majority of the patients typically within the vicinity of original tumor, precise definition of GTV for RTP is of utmost importance for the medically inoperable patient group with a worse prognosis compared to patients with tumors amenable to complete/maximal resection [36, 37]. Radiation dose escalation strategies may be more strongly considered for this patient group given the relentless disease course in patients with excessive tumor burden. Focusing on the GTV harboring the cancer stem cells, which may be responsible for radioresistance and aggressive progression, is an area of extensive research.

Besides its usefulness in brain tumor diagnosis, treatment response assessment, differentiation of adverse radiation effects from recurrence, and detection and characterization of lesions with the capability of functional imaging techniques, a very critical and relevant benefit of MRI is in RTP. Utility of MRI for GTV definition in RTP of inoperable HGGs has been poorly addressed in the literature, and our study supports its incorporation into the RTP process for this specific group of patients to improve precision in target delineation. In our study, incorporation of MRI into GTV definition has resulted in a median increase of 12.61% in the volume of GTV defined by using the CT-simulation images only, and this difference was statistically significant (Table 2). There was no statistically significant difference in target definition by consensus of the treatment team as the ground truth GTV and by incorporation of MRI, supporting the utility of MRI for improved GTV definition. Ground truth GTV defined by collaboration and consensus of the board-certified radiation oncologists after assessment of all available imaging data of the patients has been used for RT of patients in our study. This ground truth GTV has also served as a reference for comparison purposes, since interobserver variations may lead to substantial diversity in definition of target volumes for HGGs. Several studies have also used the ground truth target volume defined by experienced physicians and experts as a reference for comparison [15–17]. Ground truth GTV was used for RT of patients and for validation of the results in our study, consistent with the methodology of aforementioned studies [15–17]. Given the negligible and statistically insignificant difference between GTV defined by incorporation of MRI and ground truth GTV, we suggest that incorporation of MRI into RTP of inoperable HGGs improves target definition.

Although not focusing on the inoperable HGG patient group exclusively, several studies have investigated the utility of MRI in RT target volume definition for brain tumors and typically reported larger GTVs when MRI was incorporated [19–21]. Table 3 shows selected series assessing target definition in HGGs with incorporation of MRI into RTP.

Results of our study are consistent with the literature supporting the utility of MRI for GTV definition of HGGs [19–21]. While irradiation of smaller target volumes may improve the toxicity profile of RT with a typically lower risk of adverse radiation effects such as cognitive decline and radionecrosis, vigilance is required for avoiding any geographical misses which may lead to marginal failures and fatal disease recurrences [23, 38, 39]. This is a challenging trade-off between toxicity and treatment failure, and decision-making should take into account individualized consideration of patient and disease characteristics at referral treatment centers.

While MRI may offer several advantages over CT with its distinctive capabilities such as functional imaging, superior soft tissue contrast, and ability to acquire various different image contrasts of identical anatomy, there is still room for improvement [40, 41]. Clearly, image quality and performance of the scanners may affect the usefulness of MRI for RTP. A recent study by Regnery et al. compared a 7 Tesla FLAIR sequence with clinical FLAIR imaging at 3 Tesla for RTP of GB [42]. The study revealed that high-resolution 7 Tesla FLAIR imaging may add to the accuracy of target volume and critical organ delineation for RTP of GB [42]. The technology is evolving with further refinements in neuroimaging by MRI [18, 42, 43]. Although ground truth GTV defined by experienced physicians and experts has been used as a reference for comparison in our study to validate the results, target volume definition may have been affected by image quality and performance of the scanners. Nevertheless, our study adds to the existing body of evidence by reporting improved definition of GTV through incorporation of MRI into RTP for a distinct group of patients with inoperable HGGs.

In conclusion, inoperable HGGs comprise a specific group of brain tumors portending a very poor prognosis. In the absence of surgical management, RT offers the primary local treatment modality for inoperable HGGs. Incorporation of MRI into RTP of inoperable HGGs may improve GTV definition and may have implications for dose escalation/intensification strategies despite the need for further supporting evidence.

Data Availability

The data used to support the findings of this study are included within the article.

Conflicts of Interest

The authors declare that there are no conflicts of interest, financial or otherwise.

Authors’ Contributions

Omer Sager contributed to study conception and design, data collection, data analysis and interpretation, and manuscript drafting. Ferrat Dincoglan contributed to study conception and design, data collection, and manuscript drafting. Selcuk Demiral contributed to study conception and design, data collection, and data analysis and interpretation. Hakan Gamsiz contributed to study conception and design, data analysis and interpretation, and manuscript drafting. Bora Uysal contributed to data collection, data analysis and interpretation, and manuscript drafting. Fatih Ozcan contributed to data collection, data analysis and interpretation, and manuscript drafting. Onurhan Colak contributed to data collection, data analysis and interpretation, and manuscript drafting. Bahar Dirican contributed to study conception and design, data analysis and interpretation, and manuscript drafting. Murat Beyzadeoglu contributed to study conception and design, data collection, and data analysis and interpretation.

References

D. N. Louis, A. Perry, G. Reifenberger et al., “The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary,” Acta Neuropathologica, vol. 131, no. 6, pp. 803–820, 2016.
View at: Publisher Site | Google Scholar
Q. T. Ostrom, H. Gittleman, G. Truitt, A. Boscia, C. Kruchko, and J. S. Barnholtz-Sloan, “CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2011–2015,” Neuro-Oncology, vol. 20, no. supplement 4, pp. iv1–iv86, 2018.
View at: Publisher Site | Google Scholar
A. Shergalis, A. Bankhead, U. Luesakul, N. Muangsin, N. Neamati, and E. L. Barker, “Current challenges and opportunities in treating glioblastoma,” Pharmacological Reviews, vol. 70, no. 3, pp. 412–445, 2018.
View at: Publisher Site | Google Scholar
M. Paolillo, C. Boselli, and S. Schinelli, “Glioblastoma under siege: an overview of current therapeutic strategies,” Brain Sciences, vol. 8, no. 1, p. E15, 2018.
View at: Publisher Site | Google Scholar
D. Ghosh, S. Nandi, and S. Bhattacharjee, “Combination therapy to checkmate Glioblastoma: clinical challenges and advances,” Clinical and Translational Medicine, vol. 7, no. 1, p. 33, 2018.
View at: Publisher Site | Google Scholar
J. S. Young, F. Dayani, R. A. Morshed, H. Okada, and M. K. Aghi, “Immunotherapy for high-grade gliomas: a clinical update and practical considerations for neurosurgeons,” World Neurosurgery, vol. 124, pii: S1878-8750(19)30106-8, pp. 397–409, 2019.
View at: Publisher Site | Google Scholar
O. Sager, F. Dincoglan, S. Demiral et al., “A concise review of immunotherapy for glioblastoma,” Neuroimmunology and Neuroinflammation, vol. 5, no. 6, p. 25, 2018.
View at: Publisher Site | Google Scholar
F. Dincoglan, O. Sager, S. Demiral et al., “Radiosurgery for recurrent glioblastoma: a review article,” Neurological Disorders and Therapeutics, vol. 1, no. 4, pp. 1–5, 2017.
View at: Publisher Site | Google Scholar
F. Dincoglan, M. Beyzadeoglu, O. Sager et al., “Management of patients with recurrent glioblastoma using hypofractionated stereotactic radiotherapy,” Tumori Journal, vol. 101, no. 2, pp. 179–184, 2015.
View at: Publisher Site | Google Scholar
S. Sirin, K. Oysul, S. Surenkok et al., “Linear accelerator-based stereotactic radiosurgery in recurrent glioblastoma: a single center experience,” Vojnosanitetski Pregled, vol. 68, no. 11, pp. 961–966, 2011.
View at: Publisher Site | Google Scholar
R. Stupp, W. P. Mason, M. J. van den Bent et al., “Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma,” The New England Journal of Medicine, vol. 352, no. 10, pp. 987–996, 2005.
View at: Publisher Site | Google Scholar
T. Kazda, A. Dziacky, P. Burkon et al., “Radiotherapy of glioblastoma 15 years after the landmark Stupp’s trial: more controversies than standards?” Radiology and Oncology, vol. 52, no. 2, pp. 121–128, 2018.
View at: Publisher Site | Google Scholar
C. Li, S. Wang, J. Yan et al., “Characterizing tumor invasiveness of glioblastoma using multiparametric magnetic resonance imaging,” Journal of Neurosurgery, pp. 1–8, 2019.
View at: Publisher Site | Google Scholar
A. Laprie, S. Ken, T. Filleron et al., “Dose-painting multicenter phase III trial in newly diagnosed glioblastoma: the SPECTRO-GLIO trial comparing arm A standard radiochemotherapy to arm B radiochemotherapy with simultaneous integrated boost guided by MR spectroscopic imaging,” BMC Cancer, vol. 19, no. 1, p. 167, 2019.
View at: Publisher Site | Google Scholar
L. Guo, P. Wang, R. Sun et al., “A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy,” Scientific Reports, vol. 8, no. 1, article no. 3231, 2018.
View at: Publisher Site | Google Scholar
G. P. Beyer, R. P. Velthuizen, F. R. Murtagh, and J. L. Pearlman, “Technical aspects and evaluation methodology for the application of two automated brain MRI tumor segmentation methods in radiation therapy planning,” Magnetic Resonance Imaging, vol. 24, no. 9, pp. 1167–1178, 2006.
View at: Publisher Site | Google Scholar
G. P. Mazzara, R. P. Velthuizen, J. L. Pearlman, H. M. Greenberg, and H. Wagner, “Brain tumor target volume determination for radiation treatment planning through automated MRI segmentation,” International Journal of Radiation Oncology • Biology • Physics, vol. 59, no. 1, pp. 300–312, 2004.
View at: Publisher Site | Google Scholar
K. M. Jones, K. A. Michel, J. A. Bankson, C. D. Fuller, A. H. Klopp, and A. M. Venkatesan, “Emerging magnetic resonance imaging technologies for radiation therapy planning and response assessment,” International Journal of Radiation Oncology • Biology • Physics, vol. 101, no. 5, pp. 1046–1056, 2018.
View at: Publisher Site | Google Scholar
C. Weltens, J. Menten, M. Feron et al., “Interobserver variations in gross tumor volume delineation of brain tumors on computed tomography and impact of magnetic resonance imaging,” Radiotherapy & Oncology, vol. 60, no. 1, pp. 49–59, 2001.
View at: Publisher Site | Google Scholar
N. Datta, R. David, R. Gupta, and P. Lal, “Implications of contrast-enhanced CT-based and MRI-based target volume delineations in radiotherapy treatment planning for brain tumors,” Journal of Cancer Research and Therapeutics, vol. 4, no. 1, pp. 9–13, 2008.
View at: Publisher Site | Google Scholar
A. Fiorentino, R. Caivano, P. Pedicini, and V. Fusco, “Clinical target volume definition for glioblastoma radiotherapy planning: magnetic resonance imaging and computed tomography,” Clinical and Translational Oncology, vol. 15, no. 9, pp. 754–758, 2013.
View at: Publisher Site | Google Scholar
E. P. Sulman, N. Ismaila, T. S. Armstrong et al., “Radiation therapy for glioblastoma: american society of clinical oncology clinical practice guideline endorsement of the american society for radiation oncology guideline,” Journal of Clinical Oncology, vol. 35, no. 3, pp. 361–369, 2017.
View at: Publisher Site | Google Scholar
F. Zhao, M. Li, L. Kong, G. Zhang, and J. Yu, “Delineation of radiation therapy target volumes for patients with postoperative glioblastoma: a review,” OncoTargets and Therapy, vol. 2016, no. 9, pp. 3197–3204, 2016.
View at: Publisher Site | Google Scholar
G. Minniti, D. Amelio, M. Amichetti et al., “Patterns of failure and comparison of different target volume delineations in patients with glioblastoma treated with conformal radiotherapy plus concomitant and adjuvant temozolomide,” Radiotherapy & Oncology, vol. 97, no. 3, pp. 377–381, 2010.
View at: Publisher Site | Google Scholar
H. Colman, B. A. Berkey, M. H. Maor et al., “Phase II Radiation Therapy Oncology Group trial of conventional radiation therapy followed by treatment with recombinant interferon-β for supratentorial glioblastoma: results of RTOG 9710,” International Journal of Radiation Oncology • Biology • Physics, vol. 66, no. 3, pp. 818–824, 2006.
View at: Publisher Site | Google Scholar
M. Niyazi, M. Brada, A. J. Chalmers et al., “ESTRO-ACROP guideline ‘target delineation of glioblastomas’,” Radiotherapy & Oncology, vol. 118, no. 1, pp. 35–42, 2016.
View at: Publisher Site | Google Scholar
A. Ghose, G. Lim, and S. Husain, “Treatment for glioblastoma multiforme: current guidelines and Canadian practice,” Current Oncology, vol. 17, no. 6, pp. 52–58, 2010.
View at: Publisher Site | Google Scholar
M. W. McDonald, H. G. Shu, W. J. Curran, and I. R. Crocker, “Pattern of failure after limited margin radiotherapy and temozolomide for glioblastoma,” International Journal of Radiation Oncology • Biology • Physics, vol. 79, no. 1, pp. 130–136, 2011.
View at: Publisher Site | Google Scholar
B. J. Gebhardt, M. C. Dobelbower, W. H. Ennis, A. K. Bag, J. M. Markert, and J. B. Fiveash, “Patterns of failure for glioblastoma multiforme following limited-margin radiation and concurrent temozolomide,” Journal of Radiation Oncology, vol. 9, no. 1, p. 130, 2014.
View at: Publisher Site | Google Scholar
C. F. Hess, J. C. Schaaf, R. D. Kortmann, M. Schabet, and M. Bamberg, “Malignant glioma: patterns of failure following individually tailored limited volume irradiation,” Radiotherapy & Oncology, vol. 30, no. 2, pp. 146–149, 1994.
View at: Publisher Site | Google Scholar
K. E. Wallner, J. H. Galicich, G. Krol, E. Arbit, and M. G. Malkin, “Patterns of failure following treatment for glioblastoma multiforme and anaplastic astrocytoma,” International Journal of Radiation Oncology • Biology • Physics, vol. 16, no. 6, pp. 1405–1409, 1989.
View at: Publisher Site | Google Scholar
W. R. Shapiro, S. B. Green, P. C. Burger et al., “Randomized trial of three chemotherapy regimens and two radiotherapy regimens in postoperative treatment of malignant glioma. Brain Tumor Cooperative Group Trial 8001,” Journal of Neurosurgery, vol. 71, no. 1, pp. 1–9, 1989.
View at: Publisher Site | Google Scholar
M. Buglione, S. Pedretti, P. L. Poliani et al., “Pattern of relapse of glioblastoma multiforme treated with radical radio-chemotherapy: could a margin reduction be proposed?” Journal of Neuro-Oncology, vol. 128, no. 2, pp. 303–312, 2016.
View at: Publisher Site | Google Scholar
LS. Constine, A. Konski, S. Ekholm et al., “Adverse effects of brain irradiation correlated with MR and CT imaging,” International Journal of Radiation Oncology • Biology • Physics, vol. 15, no. 2, pp. 319–330, 1988.
View at: Publisher Site | Google Scholar
J. E. Marks, R. J. Bagĺan, S. C. Prassad, and W. F. Blank, “Cerebral radionecrosis: Incidence and risk in relation to dose, time, fractionation and volume,” International Journal of Radiation Oncology • Biology • Physics, vol. 7, no. 2, pp. 243–252, 1981.
View at: Publisher Site | Google Scholar
T. J. Brown, M. C. Brennan, M. Li et al., “Association of the extent of resection with survival in glioblastoma: a systematic review and meta-analysis,” JAMA Oncology, vol. 2, no. 11, pp. 1460–1469, 2016.
View at: Publisher Site | Google Scholar
J. P. Almeida, K. L. Chaichana, J. Rincon-Torroella, and A. Quinones-Hinojosa, “The value of extent of resection of glioblastomas: clinical evidence and current approach,” Current Neurology and Neuroscience Reports, vol. 15, no. 2, p. 517, 2015.
View at: Publisher Site | Google Scholar
S. H. Choi, J. W. Kim, J. S. Chang et al., “Impact of including peritumoral edema in radiotherapy target volume on patterns of failure in glioblastoma following temozolomide-based chemoradiotherapy,” Scientific Reports, vol. 7, no. 1, p. 42148, 2017.
View at: Publisher Site | Google Scholar
R. Manon, S. Hui, P. Chinnaiyan et al., “The impact of mid-treatment MRI on defining boost volumes in the radiation treatment of glioblastoma multiforme,” Technology in Cancer Research & Treatment, vol. 3, no. 3, pp. 303–307, 2004.
View at: Publisher Site | Google Scholar
S. Kathiravan and J. Kanakaraj, “A review on potential issues and challenges in MR imaging,” The Scientific World Journal, vol. 2013, Article ID 783715, 10 pages, 2013.
View at: Publisher Site | Google Scholar
A. McWilliam, B. Rowland, and M. van Herk, “The challenges of using MRI during radiotherapy,” Clinical Oncology, vol. 30, no. 11, pp. 680–685, 2018.
View at: Publisher Site | Google Scholar
S. Regnery, B. R. Knowles, D. Paech et al., “High-resolution FLAIR MRI at 7 Tesla for treatment planning in glioblastoma patients,” Radiotherapy & Oncology, vol. 130, pp. 180–184, 2019.
View at: Publisher Site | Google Scholar
I. Compter, J. Peerlings, D. B. Eekers et al., “Technical feasibility of integrating 7 T anatomical MRI in image-guided radiotherapy of glioblastoma: a preparatory study,” Magnetic Resonance Materials in Physics, Biology and Medicine, vol. 29, no. 3, pp. 591–603, 2016.
View at: Publisher Site | Google Scholar

Copyright

Copyright © 2019 Omer Sager et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

2194

Downloads

1526

Citations