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Strahlentherapie und Onkologie
Published in: Strahlentherapie und Onkologie 1/2024

Open Access 02-01-2024 | Magnetic Resonance Imaging | Review Article

Quality requirements for MRI simulation in cranial stereotactic radiotherapy: a guideline from the German Taskforce “Imaging in Stereotactic Radiotherapy”

Authors: PD Dr. Florian Putz, Michael Bock, Daniela Schmitt, Christoph Bert, Oliver Blanck, Maximilian I. Ruge, Elke Hattingen, Christian P. Karger, Rainer Fietkau, Johanna Grigo, Manuel A. Schmidt, Tobias Bäuerle, Andrea Wittig

Published in: Strahlentherapie und Onkologie | Issue 1/2024

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Abstract

Accurate Magnetic Resonance Imaging (MRI) simulation is fundamental for high-precision stereotactic radiosurgery and fractionated stereotactic radiotherapy, collectively referred to as stereotactic radiotherapy (SRT), to deliver doses of high biological effectiveness to well-defined cranial targets. Multiple MRI hardware related factors as well as scanner configuration and sequence protocol parameters can affect the imaging accuracy and need to be optimized for the special purpose of radiotherapy treatment planning. MRI simulation for SRT is possible for different organizational environments including patient referral for imaging as well as dedicated MRI simulation in the radiotherapy department but require radiotherapy-optimized MRI protocols and defined quality standards to ensure geometrically accurate images that form an impeccable foundation for treatment planning. For this guideline, an interdisciplinary panel including experts from the working group for radiosurgery and stereotactic radiotherapy of the German Society for Radiation Oncology (DEGRO), the working group for physics and technology in stereotactic radiotherapy of the German Society for Medical Physics (DGMP), the German Society of Neurosurgery (DGNC), the German Society of Neuroradiology (DGNR) and the German Chapter of the International Society for Magnetic Resonance in Medicine (DS-ISMRM) have defined minimum MRI quality requirements as well as advanced MRI simulation options for cranial SRT.
Literature
1.
Potter R et al (1992) Sagittal and coronal planes from MRI for treatment planning in tumors of brain, head and neck: MRI assisted simulation. Radiother Oncol 23(2):127–130PubMedCrossRef
2.
Guckenberger M et al (2020) Definition and quality requirements for stereotactic radiotherapy: consensus statement from the DEGRO/DGMP Working Group Stereotactic Radiotherapy and Radiosurgery. Strahlenther Onkol 196(5):417–420PubMedPubMedCentralCrossRef
3.
Schmitt, D., et al., 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(5): p. 421–443.
4.
Kirkpatrick JP et al (2015) Defining the optimal planning target volume in image-guided stereotactic radiosurgery of brain metastases: results of a randomized trial. Int J Radiat Oncol Biol Phys 91(1):100–108PubMedCrossRef
5.
Lo A et al (2018) Population-Based Study of Stereotactic Radiosurgery or Fractionated Stereotactic Radiation Therapy for Vestibular Schwannoma: Long-Term Outcomes and Toxicities. Int J Radiat Oncol Biol Phys 100(2):443–451PubMedCrossRef
6.
Sheehan J et al (2022) An international multicenter matched cohort analysis of incidental meningioma progression during active surveillance or after stereotactic radiosurgery: the IMPASSE study. Neuro Oncol 24(1):116–124PubMedCrossRef
7.
Seymour ZA et al (2015) Interval From Imaging to Treatment Delivery in the Radiation Surgery Age: How Long Is Too Long? Int J Radiat Oncol Biol Phys 93(1):126–132PubMedCrossRef
8.
Salkeld AL et al (2018) Changes in Brain Metastasis During Radiosurgical Planning. Int J Radiat Oncol Biol Phys 102(4):727–733PubMedCrossRef
9.
Seibert TM et al (2016) Distortion inherent to magnetic resonance imaging can lead to geometric miss in radiosurgery planning. Pract Radiat Oncol 6(6):e319–e328PubMedPubMedCentralCrossRef
10.
Glide-Hurst CK et al (2021) Task group 284 report: magnetic resonance imaging simulation in radiotherapy: considerations for clinical implementation, optimization, and quality assurance. Med Phys 48(7):e636–e670PubMedCrossRef
11.
Tanadini-Lang S et al (2023) An ESTRO-ACROP guideline on quality assurance and medical physics commissioning of online MRI guided radiotherapy systems based on a consensus expert opinion. Radiother Oncol 181:109504PubMedCrossRef
12.
Baldwin LN et al (2007) Characterization, prediction, and correction of geometric distortion in 3 T MR images. Med Phys 34(2):388–399PubMedCrossRef
13.
Sumanaweera TS et al (1994) Characterization of spatial distortion in magnetic resonance imaging and its implications for stereotactic surgery. Neurosurgery 35(4):696–703 (discussion 703–4)PubMedCrossRef
14.
Khoo VS et al (1997) Magnetic resonance imaging (MRI): considerations and applications in radiotherapy treatment planning. Radiother Oncol 42(1):1–15PubMedCrossRef
15.
Baldwin LN, Wachowicz K, Fallone BG (2009) A two-step scheme for distortion rectification of magnetic resonance images. Med Phys 36(9):3917–3926PubMedCrossRef
16.
Putz, F., et al., Magnetic resonance imaging for brain stereotactic radiotherapy : A review of requirements and pitfalls. Strahlenther Onkol, 2020. 196(5): p. 444–456.
17.
Wang H, Balter J, Cao Y (2013) Patient-induced susceptibility effect on geometric distortion of clinical brain MRI for radiation treatment planning on a 3T scanner. Phys Med Biol 58(3):465–477PubMedCrossRef
18.
Jovicich J et al (2006) Reliability in multi-site structural MRI studies: effects of gradient non-linearity correction on phantom and human data. Neuroimage 30(2):436–443PubMedCrossRef
19.
Pappas EP et al (2017) MRI-Related Geometric Distortions in Stereotactic Radiotherapy Treatment Planning: Evaluation and Dosimetric Impact. Technol Cancer Res Treat 16(6):1120–1129PubMedPubMedCentralCrossRef
20.
Kondziolka D et al (1992) A comparison between magnetic resonance imaging and computed tomography for stereotactic coordinate determination. Neurosurgery 30(3):402–406 (discussion 406–7)PubMedCrossRef
21.
Stanescu T et al (2008) A study on the magnetic resonance imaging (MRI)-based radiation treatment planning of intracranial lesions. Phys Med Biol 53(13):3579–3593PubMedCrossRef
22.
Mengling, V., et al., Evaluation of the influence of susceptibility-induced magnetic field distortions on the precision of contouring intracranial organs at risk for stereotactic radiosurgery. Phys Imaging Radiat Oncol, 2020. 15: p. 91–97.
23.
Fransson A, Andreo P, Potter R (2001) Aspects of MR image distortions in radiotherapy treatment planning. Strahlenther Onkol 177(2):59–73PubMedCrossRef
24.
Paulson ES et al (2015) Comprehensive MRI simulation methodology using a dedicated MRI scanner in radiation oncology for external beam radiation treatment planning. Med Phys 42(1):28–39PubMedCrossRef
25.
Reinsberg SA et al (2005) A complete distortion correction for MR images: II. Rectification of static-field inhomogeneities by similarity-based profile mapping. Phys Med Biol 50(11):2651–2661PubMedCrossRef
26.
Doran SJ et al (2005) A complete distortion correction for MR images: I. Gradient warp correction. Phys Med Biol 50(7):1343–1361PubMedCrossRef
27.
Karger CP et al (2006) Accuracy of device-specific 2D and 3D image distortion correction algorithms for magnetic resonance imaging of the head provided by a manufacturer. Phys Med Biol 51(12):N253–61PubMedCrossRef
28.
Torfeh T et al (2016) Characterization of 3D geometric distortion of magnetic resonance imaging scanners commissioned for radiation therapy planning. Magn Reson Imaging 34(5):645–653PubMedCrossRef
29.
Janke A et al (2004) Use of spherical harmonic deconvolution methods to compensate for nonlinear gradient effects on MRI images. Magn Reson Med 52(1):115–122PubMedCrossRef
30.
Paulson ES et al (2016) Consensus opinion on MRI simulation for external beam radiation treatment planning. Radiother Oncol 121(2):187–192PubMedCrossRef
31.
Matheoud R et al (2023) EFOMP’s protocol quality controls in PET/CT and PET/MR. Phys Med 105:102506PubMedCrossRef
32.
Price R et al (2015) MRI Quality Control. Manual, vol 2015. American College of Radiology
33.
Wang D, Doddrell DM, Cowin G (2004) A novel phantom and method for comprehensive 3‑dimensional measurement and correction of geometric distortion in magnetic resonance imaging. Magn Reson Imaging 22(4):529–542PubMedCrossRef
34.
Schad, L., et al., Correction of spatial distortion in MR imaging: a prerequisite for accurate stereotaxy. J Comput Assist Tomogr, 1987. 11(3): p. 499–505.
35.
Stanescu T, Wachowicz K, Jaffray DA (2012) Characterization of tissue magnetic susceptibility-induced distortions for MRIgRT. Med Phys 39(12):7185–7193PubMedCrossRef
36.
Bednarz G et al (1999) Evaluation of the spatial accuracy of magnetic resonance imaging-based stereotactic target localization for gamma knife radiosurgery of functional disorders. Neurosurgery 45(5):1156–1161 (discussion 1161–3)PubMedCrossRef
37.
Schmidt MA et al (2017) Stereotactic radiosurgery planning of vestibular schwannomas: Is MRI at 3 Tesla geometrically accurate? Med Phys 44(2):375–381PubMedCrossRef
38.
Walker A et al (2014) MRI distortion: considerations for MRI based radiotherapy treatment planning. Australas Phys Eng Sci Med 37(1):103–113PubMedCrossRef
39.
Jezzard P, Balaban RS (1995) Correction for geometric distortion in echo planar images from B0 field variations. Magn Reson Med 34(1):65–73PubMedCrossRef
40.
Shariff M et al (2022) End-to-end testing for stereotactic radiotherapy including the development of a Multi-Modality phantom. Z Med Phys
41.
Smith AS et al (1990) Intracranial chemical-shift artifacts on MR images of the brain: observations and relation to sampling bandwidth. AJR Am J Roentgenol 154(6):1275–1283PubMedCrossRef
42.
Soher, B.J., B.M. Dale, and E.M. Merkle, A review of MR physics: 3T versus 1.5T. Magn Reson Imaging Clin N Am, 2007. 15(3): p. 277–90, v.
43.
Kaufmann TJ et al (2020) Consensus recommendations for a standardized brain tumor imaging protocol for clinical trials in brain metastases. Neuro Oncol 22(6):757–772PubMedPubMedCentralCrossRef
44.
Zhang B et al (2010) Development of a geometrically accurate imaging protocol at 3 Tesla MRI for stereotactic radiosurgery treatment planning. Phys Med Biol 55(22):6601–6615PubMedCrossRef
45.
Wen N et al (2018) Evaluation of a magnetic resonance guided linear accelerator for stereotactic radiosurgery treatment. Radiother Oncol 127(3):460–466PubMedPubMedCentralCrossRef
46.
Slagowski JM et al (2020) Dosimetric feasibility of brain stereotactic radiosurgery with a 0.35 T MRI-guided linac and comparison vs a C-arm-mounted linac. Med Phys 47(11):5455–5466PubMedCrossRef
47.
Retif P et al (2022) Evaluation of the ability of the Brainlab Elements Cranial Distortion Correction algorithm to correct clinically relevant MRI distortions for cranial SRT. Strahlenther Onkol 198(10):907–918PubMedCrossRef
48.
Calvo-Ortega JF et al (2019) Evaluation of a novel software application for magnetic resonance distortion correction in cranial stereotactic radiosurgery. Med Dosim 44(2):136–143PubMedCrossRef
49.
Shi L et al (2021) Benchmarking of Deformable Image Registration for Multiple Anatomic Sites Using Digital Data Sets With Ground-Truth Deformation Vector Fields. Pract Radiat Oncol 11(5):404–414PubMedCrossRef
50.
Brock KK et al (2017) Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the AAPM Radiation Therapy Committee Task Group No. 132. Med Phys 44(7):e43–e76PubMedCrossRef
51.
52.
Anzalone, N., et al., Optimizing contrast-enhanced magnetic resonance imaging characterization of brain metastases: relevance to stereotactic radiosurgery. Neurosurgery, 2013. 72(5): p. 691–701.
53.
Snell, J.W., et al., Assessment of imaging studies used with radiosurgery: a volumetric algorithm and an estimation of its error. Technical note. J Neurosurg, 2006. 104(1): p. 157–62.
54.
Mugler JP 3rd, Brookeman JR (1990) Three-dimensional magnetization-prepared rapid gradient-echo imaging (3D MP RAGE). Magn Reson Med 15(1):152–157PubMedCrossRef
55.
Danieli L et al (2019) Brain Tumor-Enhancement Visualization and Morphometric Assessment: A Comparison of MPRAGE, SPACE, and VIBE MRI Techniques. AJNR Am J Neuroradiol 40(7):1140–1148PubMedPubMedCentralCrossRef
56.
Chappell PM et al (1994) Comparison of lesion enhancement on spin-echo and gradient-echo images. AJNR Am J Neuroradiol 15(1):37–44PubMedPubMedCentral
57.
Reichert, M., et al., Contrast-enhanced 3‑dimensional SPACE versus MP-RAGE for the detection of brain metastases: considerations with a 32-channel head coil. Invest Radiol, 2013. 48(1): p. 55–60.
58.
Komada T et al (2008) Contrast-enhanced MR imaging of metastatic brain tumor at 3 tesla: utility of T(1)-weighted SPACE compared with 2D spin echo and 3D gradient echo sequence. Magn Reson Med Sci 7(1):13–21PubMedCrossRef
59.
Welzel T et al (2022) Stereotactic radiotherapy of brain metastases: clinical impact of three-dimensional SPACE imaging for 3T-MRI-based treatment planning. Strahlenther Onkol 198(10):926–933PubMedPubMedCentralCrossRef
60.
Mugler JP 3rd, Brookeman JR (1993) Theoretical analysis of gadopentetate dimeglumine enhancement in T1-weighted imaging of the brain: comparison of two-dimensional spin-echo and three-dimensional gradient-echo sequences. J Magn Reson Imaging 3(5):761–769PubMedCrossRef
61.
62.
Wu X et al (2014) Contrast-enhanced radial 3D fat-suppressed T1-weighted gradient-recalled echo sequence versus conventional fat-suppressed contrast-enhanced T1-weighted studies of the head and neck. AJR Am J Roentgenol 203(4):883–889PubMedCrossRef
63.
Garcia MA et al (2018) Brain metastasis growth on preradiosurgical magnetic resonance imaging. Pract Radiat Oncol 8(6):e369–e376PubMedCrossRef
64.
Kutuk T et al (2022) Dedicated isotropic 3‑D T1 SPACE sequence imaging for radiosurgery planning improves brain metastases detection and reduces the risk of intracranial relapse. Radiother Oncol 173:84–92PubMedCrossRef
65.
Naganawa S (2015) The Technical and Clinical Features of 3D-FLAIR in Neuroimaging. Magn Reson Med Sci 14(2):93–106PubMedCrossRef
66.
Jaju A et al (2022) Imaging of pediatric brain tumors: A COG Diagnostic Imaging Committee/SPR Oncology Committee/ASPNR White Paper. Pediatr Blood Cancer p:e30147
67.
Gürün E et al (2021) Evaluation of schwannoma using the 3D-SPACE sequence: comparison with the 3D-CISS sequence in 3T-MRI. Turk J Med Sci 51(3):1123–1135PubMedPubMedCentralCrossRef
68.
Yang D et al (2000) Increased conspicuity of intraventricular lesions revealed by three-dimensional constructive interference in steady state sequences. AJNR Am J Neuroradiol 21(6):1070–1072PubMedPubMedCentral
69.
Yousry I et al (2000) Visualization of cranial nerves I–XII: value of 3D CISS and T2-weighted FSE sequences. Eur Radiol 10(7):1061–1067PubMedCrossRef
70.
Hessen, E.D., et al., Significant tumor shift in patients treated with stereotactic radiosurgery for brain metastasis. Clin Transl Radiat Oncol, 2017. 2: p. 23–28.
71.
Yuh WT et al (1995) The effect of contrast dose, imaging time, and lesion size in the MR detection of intracerebral metastasis. AJNR Am J Neuroradiol 16(2):373–380PubMedPubMedCentral
72.
Baleriaux D et al (2002) Magnetic resonance imaging of metastatic disease to the brain with gadobenate dimeglumine. Neuroradiology 44(3):191–203PubMedCrossRef
73.
Kushnirsky M et al (2016) Time-delayed contrast-enhanced MRI improves detection of brain metastases and apparent treatment volumes. J Neurosurg 124(2):489–495PubMedCrossRef
74.
75.
Voigt R et al (2023) Kranielle MRT-Simulation für die Bestrahlungsplanung: Erfahrungen und Bildgebungsprotokolle nach 1000 dedizierten Planungs-MRT-Untersuchungen. Strahlenther Onkol 199(Suppl 1):8
76.
Bonneville F, Savatovsky J, Chiras J (2007) Imaging of cerebellopontine angle lesions: an update. Part 1: enhancing extra-axial lesions. Eur Radiol 17(10):2472–2482PubMedCrossRef
77.
Cavallaro M et al (2022) Three-Dimensional Constructive Interference in Steady State (3D CISS) Imaging and Clinical Applications in Brain Pathology. Biomedicines 10(11)
78.
Tsukamoto T, Miki Y (2023) Imaging of pituitary tumors: an update with the 5th WHO Classifications—part 2. Neoplasms other than PitNET and tumor-mimicking lesions. Jpn J Radiol
79.
Cai J et al (2015) Diagnostic value of 3D time-of-flight MRA in trigeminal neuralgia. J Clin Neurosci 22(8):1343–1348PubMedCrossRef
80.
Bonne, N.-X., et al., Imaging of Jugular Paragangliomas, in Contemporary Management of Jugular Paraganglioma, G.B. Wanna, M.L. Carlson, and J.L. Netterville, Editors. 2018, Springer International Publishing: Cham. p. 49–62.
81.
Weissmann, T., et al., Paragangliomas of the Head and Neck: Local Control and Functional Outcome Following Fractionated Stereotactic Radiotherapy. Am J Clin Oncol, 2019. 42(11): p. 818–823.
82.
Glazebrook KN et al (2011) Imaging features of glomus tumors. Skelet Radiol 40(7):855–862CrossRef
83.
Loy, D.N., et al., Time-of-flight magnetic resonance angiography imaging of a residual arteriovenous malformation nidus after Onyx embolization for stereotactic radiosurgery planning. Technical note. Neurosurg Focus, 2009. 26(5): p. E13.
84.
Geibprasert S et al (2010) Radiologic assessment of brain arteriovenous malformations: what clinicians need to know. Radiographics 30(2):483–501PubMedCrossRef
85.
Nardone V et al (2019) Role of perilesional edema and tumor volume in the prognosis of non-small cell lung cancer (NSCLC) undergoing radiosurgery (SRS) for brain metastases. Strahlenther Onkol 195(8):734–744PubMedCrossRef
86.
Andersen C, Astrup J, Gyldensted C (1994) Quantitative MR analysis of glucocorticoid effects on peritumoral edema associated with intracranial meningiomas and metastases. J Comput Assist Tomogr 18(4):509–518PubMedCrossRef
87.
Scharl S et al (2019) Cavity volume changes after surgery of a brain metastasis-consequences for stereotactic radiation therapy. Strahlenther Onkol 195(3):207–217PubMedCrossRef
88.
Kutuk T et al (2021) Impact of MRI timing on tumor volume and anatomic displacement for brain metastases undergoing stereotactic radiosurgery. Neurooncol Pract 8(6):674–683PubMedPubMedCentral
89.
Hessen E et al (2019) Predicting and implications of target volume changes of brain metastases during fractionated stereotactic radiosurgery. Radiother Oncol
90.
91.
Kawashima M et al (2022) Interfractional change of tumor volume during fractionated stereotactic radiotherapy using gamma knife for brain metastases. J Neurooncol 159(2):409–416PubMedCrossRef
92.
Veninga T et al (2004) Clinical validation of the normalized mutual information method for registration of CT and MR images in radiotherapy of brain tumors. J Appl Clin Med Phys 5(3):66–79PubMedPubMedCentralCrossRef
93.
Masitho S et al (2022) Accuracy of MRI-CT registration in brain stereotactic radiotherapy: Impact of MRI acquisition setup and registration method. Z Med Phys 32(4):477–487PubMedPubMedCentralCrossRef
94.
Owrangi AM, Greer PB, Glide-Hurst CK (2018) MRI-only treatment planning: benefits and challenges. Phys Med Biol 63(5):5–tr1CrossRef
95.
Ulin K, Urie MM, Cherlow JM (2010) Results of a multi-institutional benchmark test for cranial CT/MR image registration. Int J Radiat Oncol Biol Phys 77(5):1584–1589PubMedPubMedCentralCrossRef
96.
Hanvey S, Glegg M, Foster J (2009) Magnetic resonance imaging for radiotherapy planning of brain cancer patients using immobilization and surface coils. Phys Med Biol 54(18):5381–5394PubMedCrossRef
97.
98.
Wong OL et al (2017) Image quality assessment of a 1.5T dedicated magnetic resonance-simulator for radiotherapy with a flexible radio frequency coil setting using the standard American College of Radiology magnetic resonance imaging phantom test. Quant Imaging Med Surg 7(2):205–214PubMedPubMedCentralCrossRef
99.
Mengling V et al (2021) Implementation of a dedicated 1.5T MR scanner for radiotherapy treatment planning featuring a novel high-channel coil setup for brain imaging in treatment position. Strahlenther Onkol 197(3):246–256PubMedCrossRef
100.
Masitho, S., et al., Feasibility of artificial-intelligence-based synthetic computed tomography in a magnetic resonance-only radiotherapy workflow for brain radiotherapy: Two-way dose validation and 2D/2D kV-image-based positioning. Phys Imaging Radiat Oncol, 2022. 24: p. 111–117.
101.
Johnstone E et al (2018) Systematic Review of Synthetic Computed Tomography Generation Methodologies for Use in Magnetic Resonance Imaging-Only Radiation Therapy. Int J Radiat Oncol Biol Phys 100(1):199–217PubMedCrossRef
102.
Kazemifar S et al (2019) MRI-only brain radiotherapy: Assessing the dosimetric accuracy of synthetic CT images generated using a deep learning approach. Radiother Oncol 136:56–63PubMedCrossRef
103.
Edmund JM et al (2015) Cone beam computed tomography guided treatment delivery and planning verification for magnetic resonance imaging only radiotherapy of the brain. Acta Oncol 54(9):1496–1500PubMedCrossRef
104.
Buhl SK et al (2010) Clinical evaluation of 3D/3D MRI-CBCT automatching on brain tumors for online patient setup verification—A step towards MRI-based treatment planning. Acta Oncol 49(7):1085–1091PubMedCrossRef
Metadata
Title
Quality requirements for MRI simulation in cranial stereotactic radiotherapy: a guideline from the German Taskforce “Imaging in Stereotactic Radiotherapy”
Authors
PD Dr. Florian Putz
Michael Bock
Daniela Schmitt
Christoph Bert
Oliver Blanck
Maximilian I. Ruge
Elke Hattingen
Christian P. Karger
Rainer Fietkau
Johanna Grigo
Manuel A. Schmidt
Tobias Bäuerle
Andrea Wittig
Publication date
02-01-2024
Publisher
Springer Berlin Heidelberg
Published in
Strahlentherapie und Onkologie / Issue 1/2024
Print ISSN: 0179-7158
Electronic ISSN: 1439-099X
DOI
https://doi.org/10.1007/s00066-023-02183-6

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