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Oglesby RT, Lam WW, Ruschin M, Holden L, Sarfehnia A, Yeboah C, Sahgal A, Soliman H, Detsky J, Tseng CL, Myrehaug S, Husain Z, Lau AZ, Stanisz GJ, Chugh BP. Skull phantom-based methodology to validate MRI co-registration accuracy for Gamma Knife radiosurgery. Med Phys 2022; 49:7071-7084. [PMID: 35842918 DOI: 10.1002/mp.15851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/09/2022] [Accepted: 06/28/2022] [Indexed: 12/13/2022] Open
Abstract
PURPOSE Target localization, for stereotactic radiosurgery (SRS) treatment with Gamma Knife, has become increasingly reliant on the co-registration between the planning MRI and the stereotactic cone-beam computed tomography (CBCT). Validating image registration between modalities would be particularly beneficial when considering the emergence of novel functional and metabolic MRI pulse sequences for target delineation. This study aimed to develop a phantom-based methodology to quantitatively compare the co-registration accuracy of the standard clinical imaging protocol to a representative MRI sequence that was likely to fail co-registration. The comparative methodology presented in this study may serve as a useful tool to evaluate the clinical translatability of novel MRI sequences. METHODS A realistic human skull phantom with fiducial marker columns was designed and manufactured to fit into a typical MRI head coil and the Gamma Knife patient positioning system. A series of "optimized" 3D MRI sequences-T1 -weighted Dixon, T1 -weighted fast field echo (FFE), and T2 -weighted fluid-attenuated inversion recovery (FLAIR)-were acquired and co-registered to the CBCT. The same sequences were "compromised" by reconstructing without geometric distortion correction and re-collecting with lower signal-to-noise-ratio (SNR) to simulate a novel MRI sequence with poor co-registration accuracy. Image similarity metrics-structural similarity (SSIM) index, mean squared error (MSE), and peak SNR (PSNR)-were used to quantitatively compare the co-registration of the optimized and compromised MR images. RESULTS The ground truth fiducial positions were compared to positions measured from each optimized image volume revealing a maximum median geometric uncertainty of 0.39 mm (LR), 0.92 mm (AP), and 0.13 mm (SI) between the CT and CBCT, 0.60 mm (LR), 0.36 mm (AP), and 0.07 mm (SI) between the CT and T1 -weighted Dixon, 0.42 mm (LR), 0.23 mm (AP), and 0.08 mm (SI) between the CT and T1 -weighted FFE, and 0.45 mm (LR), 0.19 mm (AP), and 1.04 mm (SI) between the CT and T2 -weighted FLAIR. Qualitatively, pairs of optimized and compromised image slices were compared using a fusion image where separable colors were used to differentiate between images. Quantitatively, MSE was the most predictive and SSIM the second most predictive metric for evaluating co-registration similarity. A clinically relevant threshold of MSE, SSIM, and/or PSNR may be defined beyond which point an MRI sequence should be rejected for target delineation based on its dissimilarity to an optimized sequence co-registration. All dissimilarity thresholds calculated using correlation coefficients with in-plane geometric uncertainty would need to be defined on a sequence-by-sequence basis and validated with patient data. CONCLUSION This study utilized a realistic skull phantom and image similarity metrics to develop a methodology capable of quantitatively assessing whether a modern research-based MRI sequence can be co-registered to the Gamma Knife CBCT with equal or less than equal accuracy when compared to a clinically accepted protocol.
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Affiliation(s)
- Ryan T Oglesby
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Wilfred W Lam
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Mark Ruschin
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Lori Holden
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Arman Sarfehnia
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada.,Department of Physics, Ryerson University, Toronto, Ontario, Canada
| | - Collins Yeboah
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Arjun Sahgal
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Hany Soliman
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Jay Detsky
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Chia-Lin Tseng
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Sten Myrehaug
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Zain Husain
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Angus Z Lau
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Greg J Stanisz
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Neurosurgery and Paediatric Neurosurgery, Medical University of Lublin, Lublin, Poland.,Department of Physics, Ryerson University, Toronto, Ontario, Canada
| | - Brige P Chugh
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada.,Department of Physics, Ryerson University, Toronto, Ontario, Canada
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Chan RW, Lawrence LSP, Oglesby RT, Chen H, Stewart J, Theriault A, Campbell M, Ruschin M, Myrehaug S, Atenafu EG, Keller B, Chugh B, MacKenzie S, Tseng CL, Detsky J, Maralani PJ, Czarnota GJ, Stanisz GJ, Sahgal A, Lau AZ. Chemical exchange saturation transfer MRI in central nervous system tumours on a 1.5 T MR-Linac. Radiother Oncol 2021; 162:140-149. [PMID: 34280403 DOI: 10.1016/j.radonc.2021.07.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 07/06/2021] [Accepted: 07/08/2021] [Indexed: 11/30/2022]
Abstract
PURPOSE To describe the implementation and initial results of using Chemical Exchange Saturation Transfer (CEST) for monitoring patients with central nervous system (CNS) tumours treated using a 1.5 tesla MR-guided radiotherapy system. METHODS CNS patients were treated with up to 30 fractions (total dose up to 60 Gy) using a 1.5 T Elekta Unity MR-Linac. CEST scans were obtained in 54 subjects at one or more time points during treatment. CEST metrics, including the amide magnetization transfer ratio (MTRAmide), nuclear Overhauser effect (NOE) MTR (MTRNOE) and asymmetry, were quantified in phantoms and CNS patients. The signal was investigated between tumour and white matter, across time, and across disease categories including high- and low-grade tumours. RESULTS The gross tumour volume (GTV) exhibited lower MTRAmide and MTRNOE and higher asymmetry compared to contralateral normal appearing white matter. Signal changes in the GTV during fractionated radiotherapy were observed. There were differences between high- and low-grade tumours, with higher CEST asymmetry associated with higher grade disease. CONCLUSION CEST MRI using a 1.5 T MR-Linac was demonstrated to be feasible for in vivo imaging of CNS tumours. CEST images showed tumour/white-matter contrast, temporal CEST signal changes, and associations with tumour grade. These results show promise for the eventual goal of using metabolic imaging to inform the design of adaptive radiotherapy protocols.
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Affiliation(s)
- Rachel W Chan
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada.
| | - Liam S P Lawrence
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Ryan T Oglesby
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Hanbo Chen
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - James Stewart
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Aimee Theriault
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Mikki Campbell
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Mark Ruschin
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Sten Myrehaug
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Eshetu G Atenafu
- Department of Biostatistics, University Health Network, University of Toronto, Toronto, Canada
| | - Brian Keller
- Department of Biostatistics, University Health Network, University of Toronto, Toronto, Canada
| | - Brige Chugh
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada; Department of Physics, Ryerson University, Toronto, Canada
| | - Scott MacKenzie
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Jay Detsky
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Pejman J Maralani
- Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Greg J Czarnota
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Greg J Stanisz
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada; Department of Neurosurgery and Pediatric Neurosurgery, Medical University of Lublin, Lublin, Poland
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Angus Z Lau
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada
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Oglesby RT, Lam WW, Stanisz GJ. A strategy to prevent a temperature-induced MRI artifact in warm liquid phantoms due to convection currents. NMR Biomed 2021; 34:e4494. [PMID: 33586271 DOI: 10.1002/nbm.4494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 01/16/2021] [Accepted: 02/02/2021] [Indexed: 06/12/2023]
Abstract
MRI phantom studies often fail to mimic the temperature of the human body, which can negatively impact accuracy. An artifact induced by increasing temperature in liquid phantoms was observed, presenting a significant challenge to temperature-controlled experiments. In this study we characterize and provide a solution to eliminate this temperature-induced MRI artifact. Low concentration (0.5-2.5 mM) agar phantoms were prepared. Utilizing a temperature-controlled phantom holder, T1 - and T2 -weighted structural images were acquired at 7 T along with quantitative B0 , B1 , T1 , T2 and ADC maps at both 25 and 37°C. Additionally, computer simulations were conducted to demonstrate the fluid flow and thermal flux patterns in water to provide an insight into the origins of the artifact. Evidence from computer simulation and quantitative MRI strongly suggest the artifact was caused by heat transfer in the form of natural convection leading to structured patterns of signal loss in MR images. The artifact was present up to agar concentrations of 1.5 mM (T1 = 3068 ± 16 ms, T2 = 1052 ± 20 ms, ADC = 2.29 ± 0.36 × 10-3 mm2 /s at 25°C; T1 = 3928 ± 44 ms, T2 = 1122 ± 24 ms, ADC = 2.64 ± 0.49 × 10-3 mm2 /s at 37°C), above which point increased sample viscosity no longer allows for convection currents, thereby eliminating the artifact. The methodology described in this work simplifies quantitative MR acquisition of liquid phantoms at physiological temperature by suppressing convection currents with relatively small changes to intrinsic MR parameters (T1 increased by 1.4% and T2 decreased by 17% for 1.5 mM agar at 25°C).
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Affiliation(s)
- Ryan T Oglesby
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
- Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Wilfred W Lam
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Greg J Stanisz
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
- Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Neurosurgery and Paediatric Neurosurgery, Medical University of Lublin, Lublin, Poland
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