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Gilani N, Mikheev A, Brinkmann IM, Kumbella M, Babb JS, Basukala D, Wetscherek A, Benkert T, Chandarana H, Sigmund EE. Spatial profiling of in vivo diffusion-weighted MRI parameters in the healthy human kidney. MAGMA 2024:10.1007/s10334-024-01159-6. [PMID: 38703246 DOI: 10.1007/s10334-024-01159-6] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 01/17/2024] [Accepted: 03/26/2024] [Indexed: 05/06/2024]
Abstract
OBJECTIVE Diffusion-weighted MRI is a technique that can infer microstructural and microcirculatory features from biological tissue, with particular application to renal tissue. There is extensive literature on diffusion tensor imaging (DTI) of anisotropy in the renal medulla, intravoxel incoherent motion (IVIM) measurements separating microstructural from microcirculation effects, and combinations of the two. However, interpretation of these features and adaptation of more specific models remains an ongoing challenge. One input to this process is a whole organ distillation of corticomedullary contrast of diffusion metrics, as has been explored for other renal biomarkers. MATERIALS AND METHODS In this work, we probe the spatial dependence of diffusion MRI metrics with concentrically layered segmentation in 11 healthy kidneys at 3 T. The metrics include those from DTI, IVIM, a combined approach titled "REnal Flow and Microstructure AnisotroPy (REFMAP)", and a multiply encoded model titled "FC-IVIM" providing estimates of fluid velocity and branching length. RESULTS Fractional anisotropy decreased from the inner kidney to the outer kidney with the strongest layer correlation in both parenchyma (including cortex and medulla) and medulla with Spearman correlation coefficients and p-values (r, p) of (0.42, <0.001) and (0.37, <0.001), respectively. Also, dynamic parameters derived from the three models significantly decreased with a high correlation from the inner to the outer parenchyma or medulla with (r, p) ranges of (0.46-0.55, <0.001). CONCLUSIONS These spatial trends might find implications for indirect assessments of kidney physiology and microstructure using diffusion MRI.
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Affiliation(s)
- Nima Gilani
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA.
| | - Artem Mikheev
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA
| | | | - Malika Kumbella
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA
| | - James S Babb
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA
| | - Dibash Basukala
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Thomas Benkert
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Hersh Chandarana
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA
| | - Eric E Sigmund
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA
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Persson E, Goodwin E, Eiben B, Wetscherek A, Nill S, Oelfke U. Real-time motion-including dose estimation of simulated multi-leaf collimator-tracked magnetic resonance-guided radiotherapy. Med Phys 2024; 51:2221-2229. [PMID: 37898109 DOI: 10.1002/mp.16798] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 09/28/2023] [Accepted: 09/28/2023] [Indexed: 10/30/2023] Open
Abstract
BACKGROUND Real-time dose estimation is a key-prerequisite to enable online intra-fraction treatment adaptation in magnetic resonance (MR)-guided radiotherapy (MRgRT). It is an essential component for the assessment of the dosimetric benefits and risks of online adaptive treatments, such as multi-leaf collimator (MLC)-tracking. PURPOSE We present a proof-of-concept for a software workflow for real-time dose estimation of MR-guided adaptive radiotherapy based on real-time data-streams of the linac delivery parameters and target positions. METHODS A software workflow, combining our in-house motion management software DynaTrack, a real-time dose calculation engine that connects to a research version of the treatment planning software (TPS) Monaco (v.6.09.00, Elekta AB, Stockholm, Sweden) was developed and evaluated. MR-guided treatment delivery on the Elekta Unity MR-linac was simulated with and without MLC-tracking for three prostate patients, previously treated on the Elekta Unity MR-linac (36.25 Gy/five fractions). Three motion scenarios were used: no motion, regular motion, and erratic prostate motion. Accumulated monitor units (MUs), centre of mass target position and MLC-leaf positions, were forwarded from DynaTrack at a rate of 25 Hz to a Monte Carlo (MC) based dose calculation engine which utilises the research GPUMCD-library (Elekta AB, Stockholm, Sweden). A rigid isocentre shift derived from the selected motion scenarios was applied to a bulk density-assigned session MR-image. The respective electron density used for treatment planning was accessed through the research Monaco TPS. The software workflow including the online dose reconstruction was validated against offline dose reconstructions. Our investigation showed that MC-based real-time dose calculations that account for all linac states (including MUs, MLC positions and target position) were infeasible, hence states were randomly sampled and used for calculation as follows; Once a new linac state was received, a dose calculation with 106 photons was started. Linac states that arrived during the time of the ongoing calculation were put into a queue. After completion of the ongoing calculation, one new linac state was randomly picked from the queue and assigned the MU accumulated from the previous state until the last sample in the queue. The queue was emptied, and the process repeated throughout treatment simulation. RESULTS On average 27% (23%-30%) of received samples were used in the real-time calculation, corresponding to a calculation time for one linac state of 148 ms. Median gamma pass rate (2%/3 mm local) was 100.0% (99.9%-100%) within the PTV volume and 99.1% (90.1%-99.4.0%) with a 15% dose cut off. Differences in PTVDmean , CTVDmean , RectumD2% , and BladderD2% (offline-online, % of prescribed dose) were below 0.64%. Beam-by-beam comparisons showed deviations below 0.07 Gy. Repeated simulations resulted in standard deviations below 0.31% and 0.12 Gy for the investigated volume and dose criteria respectively. CONCLUSIONS Real-time dose estimation was successfully performed using the developed software workflow for different prostate motion traces with and without MLC-tracking. Negligible dosimetric differences were seen when comparing online and offline reconstructed dose, enabling online intra-fraction treatment decisions based on estimates of the delivered dose.
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Affiliation(s)
- Emilia Persson
- Joint Department of Physics, The Royal Marsden Hospital and The Institute of Cancer Research, Sutton, UK
| | - Edmund Goodwin
- Joint Department of Physics, The Royal Marsden Hospital and The Institute of Cancer Research, Sutton, UK
| | - Björn Eiben
- Joint Department of Physics, The Royal Marsden Hospital and The Institute of Cancer Research, Sutton, UK
| | - Andreas Wetscherek
- Joint Department of Physics, The Royal Marsden Hospital and The Institute of Cancer Research, Sutton, UK
| | - Simeon Nill
- Joint Department of Physics, The Royal Marsden Hospital and The Institute of Cancer Research, Sutton, UK
| | - Uwe Oelfke
- Joint Department of Physics, The Royal Marsden Hospital and The Institute of Cancer Research, Sutton, UK
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Wetscherek A. Editorial for "Reproducibility and Repeatability of Intravoxel Incoherent Motion MRI Acquisition Methods in Liver". J Magn Reson Imaging 2024. [PMID: 38400891 DOI: 10.1002/jmri.29319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 01/17/2024] [Indexed: 02/26/2024] Open
Affiliation(s)
- Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and the Royal Marsden NHS Foundation Trust, London, UK
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Eiben B, Bertholet J, Tran EH, Wetscherek A, Shiarli AM, Nill S, Oelfke U, McClelland JR. Respiratory motion modelling for MR-guided lung cancer radiotherapy: model development and geometric accuracy evaluation. Phys Med Biol 2024; 69:055009. [PMID: 38266298 PMCID: PMC10875968 DOI: 10.1088/1361-6560/ad222f] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 01/03/2024] [Accepted: 01/24/2024] [Indexed: 01/26/2024]
Abstract
Objective.Respiratory motion of lung tumours and adjacent structures is challenging for radiotherapy. Online MR-imaging cannot currently provide real-time volumetric information of the moving patient anatomy, therefore limiting precise dose delivery, delivered dose reconstruction, and downstream adaptation methods.Approach.We tailor a respiratory motion modelling framework towards an MR-Linac workflow to estimate the time-resolved 4D motion from real-time data. We develop a multi-slice acquisition scheme which acquires thick, overlapping 2D motion-slices in different locations and orientations, interleaved with 2D surrogate-slices from a fixed location. The framework fits a motion model directly to the input data without the need for sorting or binning to account for inter- and intra-cycle variation of the breathing motion. The framework alternates between model fitting and motion-compensated super-resolution image reconstruction to recover a high-quality motion-free image and a motion model. The fitted model can then estimate the 4D motion from 2D surrogate-slices. The framework is applied to four simulated anthropomorphic datasets and evaluated against known ground truth anatomy and motion. Clinical applicability is demonstrated by applying our framework to eight datasets acquired on an MR-Linac from four lung cancer patients.Main results.The framework accurately reconstructs high-quality motion-compensated 3D images with 2 mm3isotropic voxels. For the simulated case with the largest target motion, the motion model achieved a mean deformation field error of 1.13 mm. For the patient cases residual error registrations estimate the model error to be 1.07 mm (1.64 mm), 0.91 mm (1.32 mm), and 0.88 mm (1.33 mm) in superior-inferior, anterior-posterior, and left-right directions respectively for the building (application) data.Significance.The motion modelling framework estimates the patient motion with high accuracy and accurately reconstructs the anatomy. The image acquisition scheme can be flexibly integrated into an MR-Linac workflow whilst maintaining the capability of online motion-management strategies based on cine imaging such as target tracking and/or gating.
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Affiliation(s)
- Björn Eiben
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom
| | - Jenny Bertholet
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Elena H Tran
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Anna-Maria Shiarli
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
- Cambridge University Hospitals NHS Trust, Cambridge, United Kingdom
| | - Simeon Nill
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Uwe Oelfke
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Jamie R McClelland
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, United Kingdom
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Bano W, Holmes W, Goodburn R, Golbabaee M, Gupta A, Withey S, Tree A, Oelfke U, Wetscherek A. Joint radial trajectory correction for accelerated T 2 * mapping on an MR-Linac. Med Phys 2023; 50:7027-7038. [PMID: 37245075 PMCID: PMC10946747 DOI: 10.1002/mp.16479] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 04/20/2023] [Accepted: 04/28/2023] [Indexed: 05/29/2023] Open
Abstract
BACKGROUND T2 * mapping can characterize tumor hypoxia, which may be associated with resistance to therapy. Acquiring T2 * maps during MR-guided radiotherapy could inform treatment adaptation by, for example, escalating the dose to resistant sub-volumes. PURPOSE The purpose of this work is to demonstrate the feasibility of the accelerated T2 * mapping technique using model-based image reconstruction with integrated trajectory auto-correction (TrACR) for MR-guided radiotherapy on an MR-Linear accelerator (MR-Linac). MATERIALS AND METHODS The proposed method was validated in a numerical phantom, where two T2 * mapping approaches (sequential and joint) were compared for different noise levels (0,0.1,0.5,1) and gradient delays ([1, -1] and [1, -2] in units of dwell time for x- and y-axis, respectively). Fully sampled k-space was retrospectively undersampled using two different undersampling patterns. Root mean square errors (RMSEs) were calculated between reconstructed T2 * maps and ground truth. In vivo data was acquired twice weekly in one prostate and one head and neck cancer patient undergoing treatment on a 1.5 T MR-Linac. Data were retrospectively undersampled and T2 * maps reconstructed, with and without trajectory corrections were compared. RESULTS Numerical simulations demonstrated that, for all noise levels, T2 * maps reconstructed with a joint approach demonstrated less error compared to an uncorrected and sequential approach. For a noise level of 0.1, uniform undersampling and gradient delay [1, -1] (in units of dwell time for x- and y-axis, respectively), RMSEs for sequential and joint approaches were 13.01 and 9.32 ms, respectively, which reduced to 10.92 and 5.89 ms for a gradient delay of [1, 2]. Similarly, for alternate undersampling and gradient delay [1, -1], RMSEs for sequential and joint approaches were 9.80 and 8.90 ms, respectively, which reduced to 9.10 and 5.40 ms for gradient delay [1, 2]. For in vivo data, T2 * maps reconstructed with our proposed approach resulted in less artifacts and improved visual appearance compared to the uncorrected approach. For both prostate and head and neck cancer patients, T2 * maps reconstructed from different treatment fractions showed changes within the planning target volume (PTV). CONCLUSION Using the proposed approach, a retrospective data-driven gradient delay correction can be performed, which is particularly relevant for hybrid devices, where full information on the machine configuration is not available for image reconstruction. T2 * maps were acquired in under 5 min and can be integrated into MR-guided radiotherapy treatment workflows, which minimizes patient burden and leaves time for additional imaging for online adaptive radiotherapy on an MR-Linac.
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Affiliation(s)
- Wajiha Bano
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUK
| | - Will Holmes
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUK
| | - Rosie Goodburn
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUK
| | | | - Amit Gupta
- The Royal Marsden NHS Foundation Trust and The Institute of Cancer ResearchLondonUK
| | - Sam Withey
- The Royal Marsden NHS Foundation Trust and The Institute of Cancer ResearchLondonUK
| | - Alison Tree
- The Royal Marsden NHS Foundation Trust and The Institute of Cancer ResearchLondonUK
| | - Uwe Oelfke
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUK
| | - Andreas Wetscherek
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUK
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Bisgaard ALH, Keesman R, van Lier ALHMW, Coolens C, van Houdt PJ, Tree A, Wetscherek A, Romesser PB, Tyagi N, Lo Russo M, Habrich J, Vesprini D, Lau AZ, Mook S, Chung P, Kerkmeijer LGW, Gouw ZAR, Lorenzen EL, van der Heide UA, Schytte T, Brink C, Mahmood F. Recommendations for improved reproducibility of ADC derivation on behalf of the Elekta MRI-linac consortium image analysis working group. Radiother Oncol 2023; 186:109803. [PMID: 37437609 DOI: 10.1016/j.radonc.2023.109803] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 06/30/2023] [Accepted: 07/06/2023] [Indexed: 07/14/2023]
Abstract
BACKGROUND AND PURPOSE The apparent diffusion coefficient (ADC), a potential imaging biomarker for radiotherapy response, needs to be reproducible before translation into clinical use. The aim of this study was to evaluate the multi-centre delineation- and calculation-related ADC variation and give recommendations to minimize it. MATERIALS AND METHODS Nine centres received identical diffusion-weighted and anatomical magnetic resonance images of different cancerous tumours (adrenal gland, pelvic oligo metastasis, pancreas, and prostate). All centres delineated the gross tumour volume (GTV), clinical target volume (CTV), and viable tumour volume (VTV), and calculated ADCs using both their local calculation methods and each of the following calculation conditions: b-values 0-500 vs. 150-500 s/mm2, region-of-interest (ROI)-based vs. voxel-based calculation, and mean vs. median. ADC variation was assessed using the mean coefficient of variation across delineations (CVD) and calculation methods (CVC). Absolute ADC differences between calculation conditions were evaluated using Friedman's test. Recommendations for ADC calculation were formulated based on observations and discussions within the Elekta MRI-linac consortium image analysis working group. RESULTS The median (range) CVD and CVC were 0.06 (0.02-0.32) and 0.17 (0.08-0.26), respectively. The ADC estimates differed 18% between b-value sets and 4% between ROI/voxel-based calculation (p-values < 0.01). No significant difference was observed between mean and median (p = 0.64). Aligning calculation conditions between centres reduced CVC to 0.04 (0.01-0.16). CVD was comparable between ROI types. CONCLUSION Overall, calculation methods had a larger impact on ADC reproducibility compared to delineation. Based on the results, significant sources of variation were identified, which should be considered when initiating new studies, in particular multi-centre investigations.
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Affiliation(s)
- Anne L H Bisgaard
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19.3, 5000 Odense Denmark.
| | - Rick Keesman
- Department of Radiation Oncology, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.
| | - Astrid L H M W van Lier
- Department of Radiotherapy, University Medical Centre Utrecht, Heidelberglaan 100, 3584 CX,Utrecht, The Netherlands.
| | - Catherine Coolens
- Department of Medical Physics, Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, M5G 2M9 Toronto, ON, Canada.
| | - Petra J van Houdt
- Department of Radiation Oncology, the Netherlands Cancer Institute, Postbus 90203, 1006 BE Amsterdam, The Netherlands.
| | - Alison Tree
- Department of Urology, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey, SM2 5PT London, UK.
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, SM2 5NG London, UK.
| | - Paul B Romesser
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, Box 22, NY 10065, New York, USA.
| | - Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 545 E. 73rd street, NY 10021, New York, USA.
| | - Monica Lo Russo
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany.
| | - Jonas Habrich
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany.
| | - Danny Vesprini
- Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, University of Toronto, 2075 Bayview Avenue, M4N 3M5 Toronto, ON, Canada.
| | - Angus Z Lau
- Physical Sciences Platform, Sunnybrook Research Institute. Department of Medical Biophysics, University of Toronto, 2075 Bayview Avenue, M4N 3M5 Toronto, ON, Canada.
| | - Stella Mook
- Department of Radiotherapy, University Medical Centre Utrecht, Heidelberglaan 100, 3584 CX,Utrecht, The Netherlands.
| | - Peter Chung
- Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network. Department of Radiation Oncology, University of Toronto, 610 University Avenue, M5G 2M9 Toronto, ON, Canada.
| | - Linda G W Kerkmeijer
- Department of Radiation Oncology, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.
| | - Zeno A R Gouw
- Department of Radiation Oncology, the Netherlands Cancer Institute, Postbus 90203, 1006 BE Amsterdam, The Netherlands.
| | - Ebbe L Lorenzen
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark.
| | - Uulke A van der Heide
- Department of Radiation Oncology, the Netherlands Cancer Institute, Postbus 90203, 1006 BE Amsterdam, The Netherlands.
| | - Tine Schytte
- Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19.3, 5000 Odense Denmark; Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark.
| | - Carsten Brink
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19.3, 5000 Odense Denmark.
| | - Faisal Mahmood
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19.3, 5000 Odense Denmark.
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Lecoeur B, Barbone M, Gough J, Oelfke U, Luk W, Gaydadjiev G, Wetscherek A. Accelerating 4D image reconstruction for magnetic resonance-guided radiotherapy. Phys Imaging Radiat Oncol 2023; 27:100484. [PMID: 37664799 PMCID: PMC10474606 DOI: 10.1016/j.phro.2023.100484] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 08/15/2023] [Accepted: 08/16/2023] [Indexed: 09/05/2023] Open
Abstract
Background and purpose Physiological motion impacts the dose delivered to tumours and vital organs in external beam radiotherapy and particularly in particle therapy. The excellent soft-tissue demarcation of 4D magnetic resonance imaging (4D-MRI) could inform on intra-fractional motion, but long image reconstruction times hinder its use in online treatment adaptation. Here we employ techniques from high-performance computing to reduce 4D-MRI reconstruction times below two minutes to facilitate their use in MR-guided radiotherapy. Material and methods Four patients with pancreatic adenocarcinoma were scanned with a radial stack-of-stars gradient echo sequence on a 1.5T MR-Linac. Fast parallelised open-source implementations of the extra-dimensional golden-angle radial sparse parallel algorithm were developed for central processing unit (CPU) and graphics processing unit (GPU) architectures. We assessed the impact of architecture, oversampling and respiratory binning strategy on 4D-MRI reconstruction time and compared images using the structural similarity (SSIM) index against a MATLAB reference implementation. Scaling and bottlenecks for the different architectures were studied using multi-GPU systems. Results All reconstructed 4D-MRI were identical to the reference implementation (SSIM > 0.99). Images reconstructed with overlapping respiratory bins were sharper at the cost of longer reconstruction times. The CPU + GPU implementation was over 17 times faster than the reference implementation, reconstructing images in 60 ± 1 s and hyper-scaled using multiple GPUs. Conclusion Respiratory-resolved 4D-MRI reconstruction times can be reduced using high-performance computing methods for online workflows in MR-guided radiotherapy with potential applications in particle therapy.
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Affiliation(s)
- Bastien Lecoeur
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, 15 Cotswold Rd, London SM2 5NG, United Kingdom
- Department of Computing, Imperial College London, Exhibition Rd, South Kensington, London SW7 2BX, United Kingdom
| | - Marco Barbone
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, 15 Cotswold Rd, London SM2 5NG, United Kingdom
- Department of Computing, Imperial College London, Exhibition Rd, South Kensington, London SW7 2BX, United Kingdom
| | - Jessica Gough
- Department of Radiotherapy at the Royal Marsden NHS Foundation Trust, Downs Rd, London SM2 5PT, United Kingdom
| | - Uwe Oelfke
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, 15 Cotswold Rd, London SM2 5NG, United Kingdom
| | - Wayne Luk
- Department of Computing, Imperial College London, Exhibition Rd, South Kensington, London SW7 2BX, United Kingdom
| | - Georgi Gaydadjiev
- Department of Computing, Imperial College London, Exhibition Rd, South Kensington, London SW7 2BX, United Kingdom
- Bernoulli Institute, University of Groningen, Nijenborgh 9, Groningen 9747 AG, The Netherlands
| | - Andreas Wetscherek
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, 15 Cotswold Rd, London SM2 5NG, United Kingdom
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Wetscherek MTA, McNaughton E, Majcher V, Wetscherek A, Sadler TJ, Alsinbili A, Teh WH, Moore SD, Patel N, Smith WPW, Krishnan U. Incidental coronary artery calcification on non-gated CT thorax correlates with risk of cardiovascular events and death. Eur Radiol 2023:10.1007/s00330-023-09428-z. [PMID: 36705681 PMCID: PMC9881510 DOI: 10.1007/s00330-023-09428-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 01/02/2023] [Accepted: 01/04/2023] [Indexed: 01/28/2023]
Abstract
OBJECTIVES To assess coronary artery calcification (CAC) on non-contrast non-ECG-gated CT thorax (NC-NECG-CTT) and to evaluate its correlation with short-term risk of cardiovascular disease (CVD) events and death. METHODS Single-institution retrospective study including all patients 40-70 years old who underwent NC-NECG-CTT over a period of 6 months. Individuals with known CVD were excluded. The presence of CAC was assessed and quantified by the Agatston score (CACS). CAC severity was defined as mild (< 100), moderate (100-400), or severe (> 400). CVD events (including CVD death, myocardial infarction, revascularisation procedures, ischaemic stroke, acute peripheral atherosclerotic ischaemia), and all-cause mortality over a median of 3.5 years were recorded. Cox proportional-hazards regression modelling was performed including CACS, age, gender and CVD risk factors (smoking, hypertension, diabetes mellitus, dyslipidaemia, and family history of CVD). RESULTS Of the total 717 eligible cases, 325 (45%) had CAC. In patients without CAC, there was only one CVD event, compared to 26 CVD events including 5 deaths in patients with CAC. The presence and severity of CAC correlated with CVD events (p < 0.001). A CACS > 100 was significantly associated with both CVD events, hazard ratio (HR) 5.74, 95% confidence interval: 2.19-15.02; p < 0.001, and all-cause mortality, HR 1.7, 95% CI: 1.08-2.66; p = 0.02. Ever-smokers with CAC had a significantly higher risk for all-cause mortality compared to never-smokers (p = 0.03), but smoking status was not an independent predictor for CVD events in any subgroup category of CAC severity. CONCLUSIONS The presence and severity of CAC assessed on NC-NECG-CTT correlates with short-term cardiovascular events and death. KEY POINTS • Patients aged 40-70 years old without known CVD but with CAC on NC-NECG-CTT have a higher risk of CVD events compared to those without CAC. • CAC (Agatston) score above 100 confers a 5.7-fold increase in the risk of short-term CVD events in these patients. • The presence and severity of CAC on NC-NECG-CTT may have prognostic and therapeutic implications.
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Affiliation(s)
- Maria T A Wetscherek
- Department of Radiology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Rd, Cambridge, CB2 0QQ, UK.
| | - Edwina McNaughton
- Department of Cardiology, Royal Papworth Hospital NHS Foundation Trust, Papworth Rd, Trumpington, Cambridge, CB2 0AY, UK
| | - Veronika Majcher
- Department of Radiology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Rd, Cambridge, CB2 0QQ, UK
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, 15 Cotswold Rd, London, SM2 5NG, UK
| | - Timothy J Sadler
- Department of Radiology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Rd, Cambridge, CB2 0QQ, UK
| | - Ahmed Alsinbili
- Department of Cardiology, Royal Papworth Hospital NHS Foundation Trust, Papworth Rd, Trumpington, Cambridge, CB2 0AY, UK
| | - Wen Hui Teh
- Department of Cardiology, Royal Papworth Hospital NHS Foundation Trust, Papworth Rd, Trumpington, Cambridge, CB2 0AY, UK
| | - Samuel D Moore
- School of Clinical Medicine, University of Cambridge, Hills Rd, Cambridge, CB2 0SP, UK
| | - Nirav Patel
- School of Clinical Medicine, University of Cambridge, Hills Rd, Cambridge, CB2 0SP, UK
| | - William P W Smith
- School of Clinical Medicine, University of Cambridge, Hills Rd, Cambridge, CB2 0SP, UK
| | - Unni Krishnan
- Department of Cardiology, Royal Papworth Hospital NHS Foundation Trust, Papworth Rd, Trumpington, Cambridge, CB2 0AY, UK
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Goodburn RJ, Philippens MEP, Lefebvre TL, Khalifa A, Bruijnen T, Freedman JN, Waddington DEJ, Younus E, Aliotta E, Meliadò G, Stanescu T, Bano W, Fatemi‐Ardekani A, Wetscherek A, Oelfke U, van den Berg N, Mason RP, van Houdt PJ, Balter JM, Gurney‐Champion OJ. The future of MRI in radiation therapy: Challenges and opportunities for the MR community. Magn Reson Med 2022; 88:2592-2608. [PMID: 36128894 PMCID: PMC9529952 DOI: 10.1002/mrm.29450] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 08/17/2022] [Accepted: 08/22/2022] [Indexed: 01/11/2023]
Abstract
Radiation therapy is a major component of cancer treatment pathways worldwide. The main aim of this treatment is to achieve tumor control through the delivery of ionizing radiation while preserving healthy tissues for minimal radiation toxicity. Because radiation therapy relies on accurate localization of the target and surrounding tissues, imaging plays a crucial role throughout the treatment chain. In the treatment planning phase, radiological images are essential for defining target volumes and organs-at-risk, as well as providing elemental composition (e.g., electron density) information for radiation dose calculations. At treatment, onboard imaging informs patient setup and could be used to guide radiation dose placement for sites affected by motion. Imaging is also an important tool for treatment response assessment and treatment plan adaptation. MRI, with its excellent soft tissue contrast and capacity to probe functional tissue properties, holds great untapped potential for transforming treatment paradigms in radiation therapy. The MR in Radiation Therapy ISMRM Study Group was established to provide a forum within the MR community to discuss the unmet needs and fuel opportunities for further advancement of MRI for radiation therapy applications. During the summer of 2021, the study group organized its first virtual workshop, attended by a diverse international group of clinicians, scientists, and clinical physicists, to explore our predictions for the future of MRI in radiation therapy for the next 25 years. This article reviews the main findings from the event and considers the opportunities and challenges of reaching our vision for the future in this expanding field.
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Affiliation(s)
- Rosie J. Goodburn
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | | | - Thierry L. Lefebvre
- Department of PhysicsUniversity of CambridgeCambridgeUnited Kingdom
- Cancer Research UK Cambridge Research InstituteUniversity of CambridgeCambridgeUnited Kingdom
| | - Aly Khalifa
- Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
| | - Tom Bruijnen
- Department of RadiotherapyUniversity Medical Center UtrechtUtrechtNetherlands
| | | | - David E. J. Waddington
- Faculty of Medicine and Health, Sydney School of Health Sciences, ACRF Image X InstituteThe University of SydneySydneyNew South WalesAustralia
| | - Eyesha Younus
- Department of Medical Physics, Odette Cancer CentreSunnybrook Health Sciences CentreTorontoOntarioCanada
| | - Eric Aliotta
- Department of Medical PhysicsMemorial Sloan Kettering Cancer CenterNew YorkNew YorkUSA
| | - Gabriele Meliadò
- Unità Operativa Complessa di Fisica SanitariaAzienda Ospedaliera Universitaria Integrata VeronaVeronaItaly
| | - Teo Stanescu
- Department of Radiation Oncology, University of Toronto and Medical Physics, Princess Margaret Cancer CentreUniversity Health NetworkTorontoOntarioCanada
| | - Wajiha Bano
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Ali Fatemi‐Ardekani
- Department of PhysicsJackson State University (JSU)JacksonMississippiUSA
- SpinTecxJacksonMississippiUSA
- Department of Radiation OncologyCommunity Health Systems (CHS) Cancer NetworkJacksonMississippiUSA
| | - Andreas Wetscherek
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Uwe Oelfke
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Nico van den Berg
- Department of RadiotherapyUniversity Medical Center UtrechtUtrechtNetherlands
| | - Ralph P. Mason
- Department of RadiologyUniversity of Texas Southwestern Medical CenterDallasTexasUSA
| | - Petra J. van Houdt
- Department of Radiation OncologyNetherlands Cancer InstituteAmsterdamNetherlands
| | - James M. Balter
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA
| | - Oliver J. Gurney‐Champion
- Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam UMCUniversity of AmsterdamAmsterdamNetherlands
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10
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Ingle M, Blackledge M, White I, Wetscherek A, Lalondrelle S, Hafeez S, Bhide S. Quantitative analysis of diffusion weighted imaging in rectal cancer during radiotherapy using a magnetic resonance imaging integrated linear accelerator. Phys Imaging Radiat Oncol 2022; 23:32-37. [PMID: 35756883 PMCID: PMC9214864 DOI: 10.1016/j.phro.2022.06.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 05/16/2022] [Accepted: 06/02/2022] [Indexed: 11/25/2022] Open
Abstract
Background and purpose Magnetic resonance imaging integrated linear accelerator (MR-Linac) platforms enable acquisition of diffusion weighted imaging (DWI) during treatment providing potential information about treatment response. Obtaining DWI on these platforms is technically different from diagnostic magnetic resonance imaging (MRI) scanners. The aim of this project was to determine feasibility of obtaining DWI and calculating apparent diffusion coefficient (ADC) parameters longitudinally in rectal cancer patients on the MR-Linac. Materials and methods Nine patients undergoing treatment on MR-Linac had DWI acquired using b-values 0, 30, 150, 500 s/mm2. Gross tumour volume (GTV) and normal tissue was delineated on DWI throughout treatment and median ADC was calculated using an in-house tool (pyOsirix ®). Results Seven out of nine patients were included in the analysis; all demonstrated downstaging at follow-up. A total of 63 out of 70 DWI were analysed (7 excluded due to poor image quality). An increasing trend of ADC median for GTV (1.15 × 10-3 mm2/s interquartile range (IQ): 1.05-1.17 vs 1.59 × 10-3 mm2/s IQ: 1.37 - 1.64; p = 0.0156), correlating to treatment response. In comparison ADC median for normal tissue remained the same between first and last fraction (1.61 × 10-3 mm2/s IQ: 1.56-1.71 vs 1.67 × 10-3 mm2/s IQ: 1.37-2.00; p = 0.9375). Conclusions DWI assessment in rectal cancer patients on MR-Linac is feasible. Initial results provide foundations for further studies to determine DWI use for treatment adaptation in rectal cancer.
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Affiliation(s)
- Manasi Ingle
- The Royal Marsden Hospital NHS Trust, 203 Fulham Road, London SW3 6JJ, UK
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Matthew Blackledge
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Ingrid White
- Guys and St Thomas NHS Trust, Great Maze Pond, London SE1 9RT, UK
| | - Andreas Wetscherek
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Susan Lalondrelle
- The Royal Marsden Hospital NHS Trust, 203 Fulham Road, London SW3 6JJ, UK
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Shaista Hafeez
- The Royal Marsden Hospital NHS Trust, 203 Fulham Road, London SW3 6JJ, UK
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Shreerang Bhide
- The Royal Marsden Hospital NHS Trust, 203 Fulham Road, London SW3 6JJ, UK
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
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11
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Wetscherek A. SP-0536 Quantitative MRI on an MR-Linac. Radiother Oncol 2022. [DOI: 10.1016/s0167-8140(22)03992-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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12
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Ingle M, Blackledge M, Wetscherek A, Huddart R, Lalondrelle S, Bhide S, Hafeez S. PO-1749 Evaluating diffusion weighted signal change on the MR-Linac during bladder cancer radiotherapy. Radiother Oncol 2022. [DOI: 10.1016/s0167-8140(22)03713-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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13
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Gupta A, Bano W, Barnes H, Newbold K, Nutting C, Bhide S, Harrington K, Wetscherek A, Wong K. PO-1111 Hypoxia and Perfusion MR-Imaging on the MR-Linear Accelerator for Head and Neck Cancer. Radiother Oncol 2022. [DOI: 10.1016/s0167-8140(22)03075-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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14
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Wetscherek A, Bijl E, Lier A, Jackson S, Gibson S, Pelt V, Hasler S, Tijssen R. OC-0776 Preliminary report on Longitudinal Stability of MRI QA up to 2 years on 7 clinical 1.5 T MR-Linacs. Radiother Oncol 2022. [DOI: 10.1016/s0167-8140(22)02682-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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15
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Führes T, Riexinger AJ, Loh M, Martin J, Wetscherek A, Kuder TA, Uder M, Hensel B, Laun FB. Echo time dependence of biexponential and triexponential intravoxel incoherent motion parameters in the liver. Magn Reson Med 2021; 87:859-871. [PMID: 34453445 DOI: 10.1002/mrm.28996] [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: 04/26/2021] [Revised: 08/12/2021] [Accepted: 08/12/2021] [Indexed: 11/09/2022]
Abstract
PURPOSE Intravoxel incoherent motion (IVIM) studies are performed with different acquisition protocols. Comparing them requires knowledge of echo time (TE) dependencies. The TE-dependence of the biexponential perfusion fraction f is well-documented, unlike that of its triexponential counterparts f1 and f2 and the biexponential and triexponential pseudodiffusion coefficients D* , D 1 ∗ , and D 2 ∗ . The purpose was to investigate the TE-dependence of these parameters and to check whether the triexponential pseudodiffusion compartments are associated with arterial and venous blood. METHODS Fifteen healthy volunteers (19-58 y; mean: 24.7 y) underwent diffusion-weighted imaging of the abdomen with 24 b-values (0.2-800 s/mm2 ) at TEs of 45, 60, 75, and 90 ms. Regions of interest (ROIs) were manually drawn in the liver. One set of bi- and triexponential IVIM parameters per volunteer and TE was determined. The TE-dependence was assessed with the Kruskal-Wallis test. RESULTS TE-dependence was observed for f (P < .001), f1 (P = .001), and f2 (P < .001). Their median values at the four measured TEs were: f: 0.198/0.240/0.274/0.359, f1 : 0.113/0.139/0.146/0.205, f2 : 0.115/0.155/0.182/0.194. D, D* , D 1 ∗ , and D 2 ∗ showed no significant TE-dependence. Their values were: diffusion coefficient D (10-4 mm2 /s): 9.45/9.63/9.75/9.41, biexponential D* (10-2 mm2 /s): 5.26/5.52/6.13/5.82, triexponential D 1 ∗ (10-2 mm2 /s): 1.73/2.91/2.25/2.51, triexponential D 2 ∗ (mm2 /s): 0.478/1.385/0.616/0.846. CONCLUSION f1 and f2 show similar TE-dependence as f, ie, increase with rising TE; an effect that must be accounted for when comparing different studies. The diffusion and pseudodiffusion coefficients might be compared without TE correction. Because of the similar TE-dependence of f1 and f2 , the triexponential pseudodiffusion compartments are most probably not associated to venous and arterial blood.
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Affiliation(s)
- Tobit Führes
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Andreas Julian Riexinger
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Martin Loh
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | | | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Tristan Anselm Kuder
- Department of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Uder
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Bernhard Hensel
- Center for Medical Physics and Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Frederik Bernd Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
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16
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Kooreman ES, van Houdt PJ, Keesman R, van Pelt VWJ, Nowee ME, Pos F, Sikorska K, Wetscherek A, Müller AC, Thorwarth D, Tree AC, van der Heide UA. Daily Intravoxel Incoherent Motion (IVIM) In Prostate Cancer Patients During MR-Guided Radiotherapy-A Multicenter Study. Front Oncol 2021; 11:705964. [PMID: 34485138 PMCID: PMC8415108 DOI: 10.3389/fonc.2021.705964] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 07/16/2021] [Indexed: 12/11/2022] Open
Abstract
PURPOSE Daily quantitative MR imaging during radiotherapy of cancer patients has become feasible with MRI systems integrated with linear accelerators (MR-linacs). Quantitative images could be used for treatment response monitoring. With intravoxel incoherent motion (IVIM) MRI, it is possible to acquire perfusion information without the use of contrast agents. In this multicenter study, daily IVIM measurements were performed in prostate cancer patients to identify changes that potentially reflect response to treatment. MATERIALS AND METHODS Forty-three patients were included, treated with 20 fractions of 3 Gy on a 1.5 T MR-linac. IVIM measurements were performed on each treatment day. The diffusion coefficient (D), perfusion fraction (f), and pseudo-diffusion coefficient (D*) were calculated based on the median signal intensities in the non-cancerous prostate and the tumor. Repeatability coefficients (RCs) were determined based on the first two treatment fractions. Separate linear mixed-effects models were constructed for the three IVIM parameters. RESULTS In total, 726 fractions were analyzed. Pre-treatment average values, measured on the first fraction before irradiation, were 1.46 × 10-3 mm2/s, 0.086, and 28.7 × 10-3 mm2/s in the non-cancerous prostate and 1.19 × 10-3 mm2/s, 0.088, and 28.9 × 10-3 mm2/s in the tumor, for D, f, and D*, respectively. The repeatability coefficients for D, f, and D* in the non-cancerous prostate were 0.09 × 10-3 mm2/s, 0.05, and 15.3 × 10-3 mm2/s. In the tumor, these values were 0.44 × 10-3 mm2/s, 0.16, and 76.4 × 10-3 mm2/s. The mixed effects analysis showed an increase in D of the tumors over the course of treatment, while remaining stable in the non-cancerous prostate. The f and D* increased in both the non-cancerous prostate and tumor. CONCLUSIONS It is feasible to perform daily IVIM measurements on an MR-linac system. Although the repeatability coefficients were high, changes in IVIM perfusion parameters were measured on a group level, indicating that IVIM has potential for measuring treatment response.
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Affiliation(s)
- Ernst S. Kooreman
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Petra J. van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Rick Keesman
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Vivian W. J. van Pelt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Marlies E. Nowee
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Floris Pos
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Karolina Sikorska
- Department of Biometrics, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Andreas Wetscherek
- Joint Department of Physics, The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, United Kingdom
| | | | - Daniela Thorwarth
- Section of Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Alison C. Tree
- Joint Department of Physics, The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, United Kingdom
| | - Uulke A. van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
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17
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van Houdt PJ, Saeed H, Thorwarth D, Fuller CD, Hall WA, McDonald BA, Shukla-Dave A, Kooreman ES, Philippens MEP, van Lier ALHMW, Keesman R, Mahmood F, Coolens C, Stanescu T, Wang J, Tyagi N, Wetscherek A, van der Heide UA. Integration of quantitative imaging biomarkers in clinical trials for MR-guided radiotherapy: Conceptual guidance for multicentre studies from the MR-Linac Consortium Imaging Biomarker Working Group. Eur J Cancer 2021; 153:64-71. [PMID: 34144436 PMCID: PMC8340311 DOI: 10.1016/j.ejca.2021.04.041] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 04/27/2021] [Indexed: 12/14/2022]
Abstract
Quantitative imaging biomarkers (QIBs) derived from MRI techniques have the potential to be used for the personalised treatment of cancer patients. However, large-scale data are missing to validate their added value in clinical practice. Integrated MRI-guided radiotherapy (MRIgRT) systems, such as hybrid MRI-linear accelerators, have the unique advantage that MR images can be acquired during every treatment session. This means that high-frequency imaging of QIBs becomes feasible with reduced patient burden, logistical challenges, and costs compared to extra scan sessions. A wealth of valuable data will be collected before and during treatment, creating new opportunities to advance QIB research at large. The aim of this paper is to present a roadmap towards the clinical use of QIBs on MRIgRT systems. The most important need is to gather and understand how the QIBs collected during MRIgRT correlate with clinical outcomes. As the integrated MRI scanner differs from traditional MRI scanners, technical validation is an important aspect of this roadmap. We propose to integrate technical validation with clinical trials by the addition of a quality assurance procedure at the start of a trial, the acquisition of in vivo test-retest data to assess the repeatability, as well as a comparison between QIBs from MRIgRT systems and diagnostic MRI systems to assess the reproducibility. These data can be collected with limited extra time for the patient. With integration of technical validation in clinical trials, the results of these trials derived on MRIgRT systems will also be applicable for measurements on other MRI systems.
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Affiliation(s)
- Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 102, Amsterdam, 1066CX, the Netherlands.
| | - Hina Saeed
- Department of Radiation Oncology, Medical College of Wisconsin, 9200 W Wisconsin Av, Milwaukee, WI, 53226, USA.
| | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, Tübingen, 72076, Germany.
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 0097, Houston, TX, 77030, USA.
| | - William A Hall
- Department of Radiation Oncology, Medical College of Wisconsin, 9200 W Wisconsin Av, Milwaukee, WI, 53226, USA.
| | - Brigid A McDonald
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 0097, Houston, TX, 77030, USA.
| | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.
| | - Ernst S Kooreman
- Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 102, Amsterdam, 1066CX, the Netherlands.
| | - Marielle E P Philippens
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands.
| | - Astrid L H M W van Lier
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands.
| | - Rick Keesman
- Department of Radiation Oncology, Radboud University Medical Center, Geert Grooteplein Zuid 32, Nijmegen, 6525GA, the Netherlands.
| | - Faisal Mahmood
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, Odense C, 5000, Denmark; Department of Clinical Research, University of Southern Denmark, J. B. Winsløws Vej 19.3, Odense C, 5000, Denmark.
| | - Catherine Coolens
- Department of Medical Physics, Princess Margaret Cancer Centre and University Health Network, 700 University Avenue, Toronto, Ontario, M5M 1G7, Canada.
| | - Teodor Stanescu
- Department of Medical Physics, Princess Margaret Cancer Centre and University Health Network, 700 University Avenue, Toronto, Ontario, M5M 1G7, Canada; Department of Radiation Oncology, University of Toronto, 610 University Avenue, Toronto, Ontario, M5G 2M9, Canada.
| | - Jihong Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 0097, Houston, TX, 77030, USA.
| | - Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and the Royal Marsden NHS Foundation Trust, 15 Cotswold Road, London, SM2 5NG, United Kingdom.
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 102, Amsterdam, 1066CX, the Netherlands.
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18
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Alexander S, Lawes R, Adair Smith G, Barnes H, Hanson I, Herbert T, Huddart R, Lacey C, McNair H, Mitchell A, Nill S, Ockwell C, Oelfke U, Taylor H, Wetscherek A, Aitken K, Hunt A. PH-0164 Abdominal compression; development of a non-gated pancreas MRIgRT workflow. Radiother Oncol 2021. [DOI: 10.1016/s0167-8140(21)07256-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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19
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Freedman JN, Gurney-Champion OJ, Nill S, Shiarli AM, Bainbridge HE, Mandeville HC, Koh DM, McDonald F, Kachelrieß M, Oelfke U, Wetscherek A. Rapid 4D-MRI reconstruction using a deep radial convolutional neural network: Dracula. Radiother Oncol 2021; 159:209-217. [PMID: 33812914 PMCID: PMC8216429 DOI: 10.1016/j.radonc.2021.03.034] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 03/07/2021] [Accepted: 03/26/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE 4D and midposition MRI could inform plan adaptation in lung and abdominal MR-guided radiotherapy. We present deep learning-based solutions to overcome long 4D-MRI reconstruction times while maintaining high image quality and short scan times. METHODS Two 3D U-net deep convolutional neural networks were trained to accelerate the 4D joint MoCo-HDTV reconstruction. For the first network, gridded and joint MoCo-HDTV-reconstructed 4D-MRI were used as input and target data, respectively, whereas the second network was trained to directly calculate the midposition image. For both networks, input and target data had dimensions of 256 × 256 voxels (2D) and 16 respiratory phases. Deep learning-based MRI were verified against joint MoCo-HDTV-reconstructed MRI using the structural similarity index (SSIM) and the naturalness image quality evaluator (NIQE). Moreover, two experienced observers contoured the gross tumour volume and scored the images in a blinded study. RESULTS For 12 subjects, previously unseen by the networks, high-quality 4D and midposition MRI (1.25 × 1.25 × 3.3 mm3) were each reconstructed from gridded images in only 28 seconds per subject. Excellent agreement was found between deep-learning-based and joint MoCo-HDTV-reconstructed MRI (average SSIM ≥ 0.96, NIQE scores 7.94 and 5.66). Deep-learning-based 4D-MRI were clinically acceptable for target and organ-at-risk delineation. Tumour positions agreed within 0.7 mm on midposition images. CONCLUSION Our results suggest that the joint MoCo-HDTV and midposition algorithms can each be approximated by a deep convolutional neural network. This rapid reconstruction of 4D and midposition MRI facilitates online treatment adaptation in thoracic or abdominal MR-guided radiotherapy.
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Affiliation(s)
- Joshua N Freedman
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Oliver J Gurney-Champion
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom; Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, The Netherlands.
| | - Simeon Nill
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Anna-Maria Shiarli
- Department of Radiotherapy, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Hannah E Bainbridge
- Department of Radiotherapy, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom; Department of Radiotherapy, Portsmouth Hospitals University NHS Trust, Queen Alexandra Hospital, United Kingdom.
| | - Henry C Mandeville
- Department of Radiotherapy, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Dow-Mu Koh
- Department of Radiology, The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Fiona McDonald
- Department of Radiotherapy, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Marc Kachelrieß
- Division of X-Ray Imaging and CT, German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Uwe Oelfke
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
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Kooreman ES, van Houdt PJ, Keesman R, Pos FJ, van Pelt VWJ, Nowee ME, Wetscherek A, Tijssen RHN, Philippens MEP, Thorwarth D, Wang J, Shukla-Dave A, Hall WA, Paulson ES, van der Heide UA. ADC measurements on the Unity MR-linac - A recommendation on behalf of the Elekta Unity MR-linac consortium. Radiother Oncol 2020; 153:106-113. [PMID: 33017604 PMCID: PMC8327388 DOI: 10.1016/j.radonc.2020.09.046] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 09/23/2020] [Accepted: 09/23/2020] [Indexed: 01/23/2023]
Abstract
BACKGROUND AND PURPOSE Diffusion-weighted imaging (DWI) for treatment response monitoring is feasible on hybrid magnetic resonance linear accelerator (MR-linac) systems. The MRI scanner of the Elekta Unity system has an adjusted design compared to diagnostic scanners. We investigated its impact on measuring the DWI-derived apparent diffusion coefficient (ADC) regarding three aspects: the choice of b-values, the spatial variation of the ADC, and scanning during radiation treatment. The aim of this study is to give recommendations for accurate ADC measurements on Unity systems. MATERIALS AND METHODS Signal-to-noise ratio (SNR) measurements with increasing b-values were done to determine the highest bvalue that can be measured reliably. The spatial variation of the ADC was assessed on six Unity systems with a cylindrical phantom of 40 cm diameter. The influence of gantry rotation and irradiation was investigated by acquiring DWI images before and during treatment of 11 prostate cancer patients. RESULTS On the Unity system, a maximum b-value of 500 s/mm2 should be used for ADC quantification, as a trade-off between SNR and diffusion weighting. Accurate ADC values were obtained within 7 cm from the iso-center, while outside this region ADC values deviated more than 5%. The ADC was not influenced by the rotating linac or irradiation during treatment. CONCLUSION We provide Unity system specific recommendations for measuring the ADC. This will increase the consistency of ADC values acquired in different centers on the Unity system, enabling large cohort studies for biomarker discovery and treatment response monitoring.
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Affiliation(s)
- Ernst S Kooreman
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Rick Keesman
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Floris J Pos
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Vivian W J van Pelt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Marlies E Nowee
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research, and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Rob H N Tijssen
- Department of Radiotherapy, University Medical Center Utrecht, The Netherlands
| | | | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany
| | - Jihong Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, United States
| | - Amita Shukla-Dave
- Departments of Medical Physics and Radiology, Memorial Sloan Kettering Cancer Center, New York, United States
| | - William A Hall
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, United States
| | - Eric S Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, United States
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
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21
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Riexinger A, Martin J, Wetscherek A, Kuder TA, Uder M, Hensel B, Laun FB. An optimized b-value distribution for triexponential intravoxel incoherent motion (IVIM) in the liver. Magn Reson Med 2020; 85:2095-2108. [PMID: 33201549 DOI: 10.1002/mrm.28582] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [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: 06/18/2020] [Revised: 10/09/2020] [Accepted: 10/13/2020] [Indexed: 12/15/2022]
Abstract
PURPOSE To find an optimized b-value distribution for reproducible triexponential intravoxel incoherent motion (IVIM) exams in the liver. METHODS A numeric optimization of b-value distributions was performed using the triexponential IVIM equation and 27 different IVIM parameter sets. Starting with an initially optimized distribution of 6 b-values, the number of b-values was increased stepwise. Each new b-value was chosen from a set of 64 predefined b-values based on the computed summed relative mean error of the fitted triexponential IVIM parameters. This process was repeated for up to 100 b-values. In simulations and in vivo measurements, optimized b-value distributions were compared to 4 representative distributions found in literature. RESULTS The first 16 optimized b-values were 0, 0.3, 0.3, 70, 200, 800, 70, 1, 3.5, 5, 70, 1.2, 6, 45, 1.5, and 60 in units of s/mm2 . Low b-values were much more frequent than high b-values. The optimized b-value distribution resulted in a higher fit stability compared to distributions used in literature in both, simulation and in vivo measurements. Using more than 6 b-values, ideally 16 or more, increased the fit stability considerably. CONCLUSION Using optimized b-values, the fit uncertainty in triexponential IVIM can be largely reduced. Ideally, 16 or more b-values should be acquired.
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Affiliation(s)
- Andreas Riexinger
- Institute of Radiology, University Hospital Erlangen, Erlangen, Germany
| | - Jan Martin
- Institute of Radiology, University Hospital Erlangen, Erlangen, Germany
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Tristan Anselm Kuder
- Department of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Uder
- Institute of Radiology, University Hospital Erlangen, Erlangen, Germany
| | - Bernhard Hensel
- Center for Medical Physics and Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
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22
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Eiben B, Tran E, Wetscherek A, Shiarli A, Bertholet J, Oelfke U, McClelland J. OC-0338: High-resolution image reconstruction and motion modelling for a lung cancer patient on an MRLinac. Radiother Oncol 2020. [DOI: 10.1016/s0167-8140(21)00362-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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23
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Nill S, Hanson I, Costa F, Menten M, Wetscherek A, Oelfke U. PO-1595: MR guided tumour tracking on a high field MR Linac: feasibility and first experimental results. Radiother Oncol 2020. [DOI: 10.1016/s0167-8140(21)01613-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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24
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Buzan MT, Wetscherek A, Rank CM, Kreuter M, Heussel CP, Kachelrieß M, Dinkel J. Delayed contrast dynamics as marker of regional impairment in pulmonary fibrosis using 5D MRI - a pilot study. Br J Radiol 2020; 93:20190121. [PMID: 32584606 DOI: 10.1259/bjr.20190121] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
OBJECTIVE To analyse delayed contrast dynamics of fibrotic lesions in interstitial lung disease (ILD) using five dimensional (5D) MRI and to correlate contrast dynamics with disease severity. METHODS 20 patients (mean age: 71 years; M:F, 13:7), with chronic fibrosing ILD: n = 12 idiopathic pulmonary fibrosis (IPF) and n = 8 non-IPF, underwent thin-section multislice CT as part of the standard diagnostic workup and additionally MRI of the lung. 2 min after contrast injection, a radial gradient echo sequence with golden-angle spacing was acquired during 5 min of free-breathing, followed by 5D image reconstruction. Disease was categorized as severe or non-severe according to CT morphological regional severity. For each patient, 10 lesions were analysed. RESULTS IPF lesions showed later peak enhancement compared to non-IPF (severe: p = 0.01, non-severe: p = 0.003). Severe lesions showed later peak enhancement compared to non-severe lesions, in non-IPF (p = 0.04), but not in IPF (p = 0.35). There was a tendency towards higher accumulation and washout rates in IPF compared to non-IPF in non-severe disease. Severe lesions had lower washout rate than non-severe ones in both IPF (p = 0.003) and non-IPF (p = 0.005). Continuous contrast agent accumulation, without washout, was found only in IPF lesions. CONCLUSIONS Contrast agent dynamics are influenced by type and severity of pulmonary fibrosis, which might enable a more thorough characterisation of disease burden. The regional impairment is of particular interest in the context of antifibrotic treatments and was characterised using a non-invasive, non-irradiating, free-breathing method. ADVANCES IN KNOWLEDGE Delayed contrast enhancement patterns allow the assessment of regional lung impairment which could represent different disease stages or phenotypes in ILD.
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Affiliation(s)
- Maria Ta Buzan
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany.,Department of Pneumology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.,Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany.,Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Andreas Wetscherek
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Christopher M Rank
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Kreuter
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany.,Center for Rare and Interstitial Lung Diseases, Pneumology and respiratory critical care medicine, Thoraxklinik, Heidelberg University Hospital, Heidelberg, Germany
| | - Claus Peter Heussel
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany.,Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany.,Center for Rare and Interstitial Lung Diseases, Pneumology and respiratory critical care medicine, Thoraxklinik, Heidelberg University Hospital, Heidelberg, Germany
| | - Marc Kachelrieß
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Julien Dinkel
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany.,Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital Munich, Munich, Germany.,Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
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25
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Alzahrani M, Broadbent DA, Chuter R, Al-Qaisieh B, Jackson S, Michael H, Johnstone RI, Shah S, Wetscherek A, Chick HJ, Wyatt JJ, McCallum HM, Speight R. Audit feasibility for geometric distortion in magnetic resonance imaging for radiotherapy. Phys Imaging Radiat Oncol 2020; 15:80-84. [PMID: 33163632 PMCID: PMC7607582 DOI: 10.1016/j.phro.2020.07.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 06/27/2020] [Accepted: 07/22/2020] [Indexed: 11/02/2022] Open
Abstract
BACKGROUND AND PURPOSE Magnetic Resonance Imaging (MRI) is increasingly being used in radiotherapy (RT). However, geometric distortions are a known challenge of using MRI in RT. The aim of this study was to demonstrate feasibility of a national audit of MRI geometric distortions. This was achieved by assessing large field of view (FOV) MRI distortions on a number of scanners used clinically for RT. MATERIALS AND METHODS MRI scans of a large FOV MRI geometric distortion phantom were acquired on 11 MRI scanners that are used clinically for RT in the UK. The mean and maximum distortions and variance between scanners were reported at different distances from the isocentre. RESULTS For a small FOV representing a brain (100-150 mm from isocentre) all distortions were < 2 mm except for the maximum distortion of one scanner. For a large FOV representing a head and neck/pelvis (200-250 mm from isocentre) mean distortions were < 2 mm except for one scanner, maximum distortions were > 10 mm in some cases. The variance between scanners was low and was found to increase with distance from isocentre. CONCLUSIONS This study demonstrated feasibility of the technique to be repeated in a country wide geometric distortion audit of all MRI scanners used clinically for RT. Recommendations were made for performing such an audit and how to derive acceptable limits of distortion in such an audit.
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Affiliation(s)
- Meshal Alzahrani
- Department of Diagnostic Radiology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - David A Broadbent
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Robert Chuter
- Christie Medical Physics and Engineering (CMPE), The Christie NHS Foundation Trust, Manchester, UK
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Bashar Al-Qaisieh
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Steven Jackson
- Christie Medical Physics and Engineering (CMPE), The Christie NHS Foundation Trust, Manchester, UK
| | - Hutton Michael
- Christie Medical Physics and Engineering (CMPE), The Christie NHS Foundation Trust, Manchester, UK
| | | | - Simon Shah
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Andreas Wetscherek
- Joint Department of Physics at the Institute of Cancer Research and the Royal Marsden NHS Foundation Trust, London, UK
| | - H. Joan Chick
- Joint Department of Physics at the Institute of Cancer Research and the Royal Marsden NHS Foundation Trust, London, UK
| | - Jonathan J Wyatt
- Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle, UK
- Centre for Cancer, Newcastle University, Newcastle, UK
| | - Hazel Mhairi McCallum
- Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle, UK
- Centre for Cancer, Newcastle University, Newcastle, UK
| | - Richard Speight
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, UK
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26
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Tran EH, Eiben B, Wetscherek A, Oelfke U, Meedt G, Hawkes DJ, McClelland JR. Evaluation of MRI-derived surrogate signals to model respiratory motion. Biomed Phys Eng Express 2020; 6:045015. [PMID: 33194224 PMCID: PMC7655234 DOI: 10.1088/2057-1976/ab944c] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 05/07/2020] [Accepted: 05/19/2020] [Indexed: 12/25/2022]
Abstract
An MR-Linac can provide motion information of tumour and organs-at-risk before, during, and after beam delivery. However, MR imaging cannot provide real-time high-quality volumetric images which capture breath-to-breath variability of respiratory motion. Surrogate-driven motion models relate the motion of the internal anatomy to surrogate signals, thus can estimate the 3D internal motion from these signals. Internal surrogate signals based on patient anatomy can be extracted from 2D cine-MR images, which can be acquired on an MR-Linac during treatment, to build and drive motion models. In this paper we investigate different MRI-derived surrogate signals, including signals generated by applying principal component analysis to the image intensities, or control point displacements derived from deformable registration of the 2D cine-MR images. We assessed the suitability of the signals to build models that can estimate the motion of the internal anatomy, including sliding motion and breath-to-breath variability. We quantitatively evaluated the models by estimating the 2D motion in sagittal and coronal slices of 8 lung cancer patients, and comparing them to motion measurements obtained from image registration. For sagittal slices, using the first and second principal components on the control point displacements as surrogate signals resulted in the highest model accuracy, with a mean error over patients around 0.80 mm which was lower than the in-plane resolution. For coronal slices, all investigated signals except the skin signal produced mean errors over patients around 1 mm. These results demonstrate that surrogate signals derived from 2D cine-MR images, including those generated by applying principal component analysis to the image intensities or control point displacements, can accurately model the motion of the internal anatomy within a single sagittal or coronal slice. This implies the signals should also be suitable for modelling the 3D respiratory motion of the internal anatomy.
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Affiliation(s)
- Elena H Tran
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Björn Eiben
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Uwe Oelfke
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Gustav Meedt
- Elekta, Medical Intelligence Medizintechnik GmbH, Schwabmünchen, Germany
| | - David J Hawkes
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Jamie R McClelland
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
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27
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Menten MJ, Mohajer JK, Nilawar R, Bertholet J, Dunlop A, Pathmanathan AU, Moreau M, Marshall S, Wetscherek A, Nill S, Tree AC, Oelfke U. Automatic reconstruction of the delivered dose of the day using MR-linac treatment log files and online MR imaging. Radiother Oncol 2020; 145:88-94. [PMID: 31931291 PMCID: PMC7191265 DOI: 10.1016/j.radonc.2019.12.010] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 12/11/2019] [Accepted: 12/15/2019] [Indexed: 01/24/2023]
Abstract
BACKGROUND AND PURPOSE Anatomical changes during external beam radiotherapy prevent the accurate delivery of the intended dose distribution. Resolving the delivered dose, which is currently unknown, is crucial to link radiotherapy doses to clinical outcomes and ultimately improve the standard of care. MATERIAL AND METHODS In this study, we present a dose reconstruction workflow based on data routinely acquired during MR-guided radiotherapy. It employs 3D MR images, 2D cine MR images and treatment machine log files to calculate the delivered dose taking intrafractional motion into account. The developed pipeline was used to measure anatomical changes and assess their dosimetric impact in 89 prostate radiotherapy fractions delivered with a 1.5 T MR-linac at our institute. RESULTS Over the course of radiation delivery, the CTV shifted 0.6 mm ± 2.1 mm posteriorly and 1.3 mm ± 1.5 mm inferiorly. When extrapolating the dose changes in each case to 20 fractions, the mean clinical target volume D98% and clinical target volume D50% dose-volume metrics decreased by 1.1 Gy ± 1.6 Gy and 0.1 Gy ± 0.2 Gy, respectively. Bladder D3% did not change (0.0 Gy ± 1.2 Gy), while rectum D3% decreased by 1.0 Gy ± 2.0 Gy. Although anatomical changes and their dosimetric impact were small in the majority of cases, large intrafractional motion caused the delivered dose to substantially deviate from the intended plan in some fractions. CONCLUSIONS The presented end-to-end workflow is able to reliably, non-invasively and automatically reconstruct the delivered prostate radiotherapy dose by processing MR-linac treatment log files and online MR images. In the future, we envision this workflow to be adapted to other cancer sites and ultimately to enter widespread clinical use.
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Affiliation(s)
- Martin J Menten
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK.
| | - Jonathan K Mohajer
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Rahul Nilawar
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Jenny Bertholet
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Alex Dunlop
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Angela U Pathmanathan
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | | | | | - Andreas Wetscherek
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Simeon Nill
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Alison C Tree
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Uwe Oelfke
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
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28
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Gurney‐Champion OJ, Rauh SS, Harrington K, Oelfke U, Laun FB, Wetscherek A. Optimal acquisition scheme for flow-compensated intravoxel incoherent motion diffusion-weighted imaging in the abdomen: An accurate and precise clinically feasible protocol. Magn Reson Med 2020; 83:1003-1015. [PMID: 31566262 PMCID: PMC6899942 DOI: 10.1002/mrm.27990] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 08/14/2019] [Accepted: 08/17/2019] [Indexed: 12/16/2022]
Abstract
PURPOSE Flow-compensated (FC) diffusion-weighted MRI (DWI) for intravoxel-incoherent motion (IVIM) modeling allows for a more detailed description of tissue microvasculature than conventional IVIM. The long acquisition time of current FC-IVIM protocols, however, has prohibited clinical application. Therefore, we developed an optimized abdominal FC-IVIM acquisition with a clinically feasible scan time. METHODS Precision and accuracy of the FC-IVIM parameters were assessed by fitting the FC-IVIM model to signal decay curves, simulated for different acquisition schemes. Diffusion-weighted acquisitions were added subsequently to the protocol, where we chose the combination of b-value, diffusion time and gradient profile (FC or bipolar) that resulted in the largest improvement to its accuracy and precision. The resulting two optimized FC-IVIM protocols with 25 and 50 acquisitions (FC-IVIMopt25 and FC-IVIMopt50 ), together with a complementary acquisition consisting of 50 diffusion-weighting (FC-IVIMcomp ), were acquired in repeated abdominal free-breathing FC-IVIM imaging of seven healthy volunteers. Intersession and intrasession within-subject coefficient of variation of the FC-IVIM parameters were compared for the liver, spleen, and kidneys. RESULTS Simulations showed that the performance of FC-IVIM improved in tissue with larger perfusion fraction and signal-to-noise ratio. The scan time of the FC-IVIMopt25 and FC-IVIMopt50 protocols were 8 and 16 min. The best in vivo performance was seen in FC-IVIMopt50 . The intersession within-subject coefficients of variation of FC-IVIMopt50 were 11.6%, 16.3%, 65.5%, and 36.0% for FC-IVIM model parameters diffusivity, perfusion fraction, characteristic time and blood flow velocity, respectively. CONCLUSIONS We have optimized the FC-IVIM protocol, allowing for clinically feasible scan times (8-16 min).
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Affiliation(s)
- Oliver J. Gurney‐Champion
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Susanne S. Rauh
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUnited Kingdom
- Institute of RadiologyUniversity Hospital Erlangen, Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU)ErlangenGermany
| | - Kevin Harrington
- Targeted Therapy teamThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Uwe Oelfke
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Frederik B. Laun
- Institute of RadiologyUniversity Hospital Erlangen, Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU)ErlangenGermany
| | - Andreas Wetscherek
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUnited Kingdom
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Martin J, Endt S, Wetscherek A, Kuder TA, Doerfler A, Uder M, Hensel B, Laun FB. Contrast-to-noise ratio analysis of microscopic diffusion anisotropy indices in q-space trajectory imaging. Z Med Phys 2020; 30:4-16. [DOI: 10.1016/j.zemedi.2019.01.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Revised: 12/20/2018] [Accepted: 01/29/2019] [Indexed: 12/26/2022]
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30
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Shiarli AM, Brown S, Cobben D, Wetscherek A, Dubec M, Herbert T, Smith G, Lawes R, Barnes H, Faivre-Finn C, McDonald F. MRI image acquisition on the MR-Linac for patients with locally advanced lung cancer (LALC). Lung Cancer 2020. [DOI: 10.1016/s0169-5002(20)30111-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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31
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Martin J, Endt S, Wetscherek A, Kuder TA, Doerfler A, Uder M, Hensel B, Laun FB. Twice‐refocused stimulated echo diffusion imaging: Measuring diffusion time dependence at constant
T
1
weighting. Magn Reson Med 2019; 83:1741-1749. [DOI: 10.1002/mrm.28046] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 09/30/2019] [Accepted: 09/30/2019] [Indexed: 02/04/2023]
Affiliation(s)
- Jan Martin
- Institute of Radiology University Hospital ErlangenFriedrich‐Alexander‐Universität Erlangen‐Nürnberg Erlangen Germany
| | - Sebastian Endt
- Institute of Radiology University Hospital ErlangenFriedrich‐Alexander‐Universität Erlangen‐Nürnberg Erlangen Germany
- Department of Computer Science Technical University of Munich Garching Germany
| | - Andreas Wetscherek
- Joint Department of Physics The Institute of Cancer Research and the Royal Marsden NHS Foundation Trust London United Kingdom
| | - Tristan Anselm Kuder
- Department Medical Physics in Radiology German Cancer Research Center Heidelberg Germany
| | - Arnd Doerfler
- Institute of Neuroradiology University Hospital ErlangenFriedrich‐Alexander‐Universität Erlangen‐Nürnberg Erlangen Germany
| | - Michael Uder
- Institute of Radiology University Hospital ErlangenFriedrich‐Alexander‐Universität Erlangen‐Nürnberg Erlangen Germany
| | - Bernhard Hensel
- Center for Medical Physics and Engineering Friedrich‐Alexander‐Universität Erlangen‐Nürnberg Erlangen Germany
| | - Frederik Bernd Laun
- Institute of Radiology University Hospital ErlangenFriedrich‐Alexander‐Universität Erlangen‐Nürnberg Erlangen Germany
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Gurney-Champion OJ, Collins DJ, Wetscherek A, Rata M, Klaassen R, van Laarhoven HWM, Harrington KJ, Oelfke U, Orton MR. Erratum: Principal component analysis for fast and model-free denoising of multi b-value diffusion-weighted MR images (2019 Phys. Med. Biol. 64 105015). Phys Med Biol 2019. [DOI: 10.1088/1361-6560/ab318a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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White IM, Scurr E, Wetscherek A, Brown G, Sohaib A, Nill S, Oelfke U, Dearnaley D, Lalondrelle S, Bhide S. Realizing the potential of magnetic resonance image guided radiotherapy in gynaecological and rectal cancer. Br J Radiol 2019; 92:20180670. [PMID: 30933550 PMCID: PMC6592079 DOI: 10.1259/bjr.20180670] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 02/24/2019] [Accepted: 03/21/2019] [Indexed: 12/25/2022] Open
Abstract
CT-based radiotherapy workflow is limited by poor soft tissue definition in the pelvis and reliance on rigid registration methods. Current image-guided radiotherapy and adaptive radiotherapy models therefore have limited ability to improve clinical outcomes. The advent of MRI-guided radiotherapy solutions provides the opportunity to overcome these limitations with the potential to deliver online real-time MRI-based plan adaptation on a daily basis, a true "plan of the day." This review describes the application of MRI guided radiotherapy in two pelvic tumour sites likely to benefit from this approach.
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Affiliation(s)
- Ingrid M White
- Institute of Cancer Research and Royal Marsden National Health Service Foundation Trust, Sutton, Surrey, UK
| | - Erica Scurr
- Institute of Cancer Research and Royal Marsden National Health Service Foundation Trust, Sutton, Surrey, UK
| | - Andreas Wetscherek
- Institute of Cancer Research and Royal Marsden National Health Service Foundation Trust, Sutton, Surrey, UK
| | - Gina Brown
- Institute of Cancer Research and Royal Marsden National Health Service Foundation Trust, Sutton, Surrey, UK
| | - Aslam Sohaib
- Institute of Cancer Research and Royal Marsden National Health Service Foundation Trust, Sutton, Surrey, UK
| | - Simeon Nill
- Institute of Cancer Research and Royal Marsden National Health Service Foundation Trust, Sutton, Surrey, UK
| | - Uwe Oelfke
- Institute of Cancer Research and Royal Marsden National Health Service Foundation Trust, Sutton, Surrey, UK
| | - David Dearnaley
- Institute of Cancer Research and Royal Marsden National Health Service Foundation Trust, Sutton, Surrey, UK
| | - Susan Lalondrelle
- Institute of Cancer Research and Royal Marsden National Health Service Foundation Trust, Sutton, Surrey, UK
| | - Shreerang Bhide
- Institute of Cancer Research and Royal Marsden National Health Service Foundation Trust, Sutton, Surrey, UK
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Freedman JN, Bainbridge HE, Nill S, Collins DJ, Kachelrieß M, Leach MO, McDonald F, Oelfke U, Wetscherek A. Synthetic 4D-CT of the thorax for treatment plan adaptation on MR-guided radiotherapy systems. Phys Med Biol 2019; 64:115005. [PMID: 30844775 PMCID: PMC8208601 DOI: 10.1088/1361-6560/ab0dbb] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Revised: 01/04/2019] [Accepted: 03/07/2019] [Indexed: 12/20/2022]
Abstract
MR-guided radiotherapy treatment planning utilises the high soft-tissue contrast of MRI to reduce uncertainty in delineation of the target and organs at risk. Replacing 4D-CT with MRI-derived synthetic 4D-CT would support treatment plan adaptation on hybrid MR-guided radiotherapy systems for inter- and intrafractional differences in anatomy and respiration, whilst mitigating the risk of CT to MRI registration errors. Three methods were devised to calculate synthetic 4D and midposition (time-weighted mean position of the respiratory cycle) CT from 4D-T1w and Dixon MRI. The first approach employed intensity-based segmentation of Dixon MRI for bulk-density assignment (sCTD). The second step added spine density information using an atlas of CT and Dixon MRI (sCTDS). The third iteration used a polynomial function relating Hounsfield units and normalised T1w image intensity to account for variable lung density (sCTDSL). Motion information in 4D-T1w MRI was applied to generate synthetic CT in midposition and in twenty respiratory phases. For six lung cancer patients, synthetic 4D-CT was validated against 4D-CT in midposition by comparison of Hounsfield units and dose-volume metrics. Dosimetric differences found by comparing sCTD,DS,DSL and CT were evaluated using a Wilcoxon signed-rank test (p = 0.05). Compared to sCTD and sCTDS, planning on sCTDSL significantly reduced absolute dosimetric differences in the planning target volume metrics to less than 98 cGy (1.7% of the prescribed dose) on average. When comparing sCTDSL and CT, average radiodensity differences were within 97 Hounsfield units and dosimetric differences were significant only for the planning target volume D99% metric. All methods produced clinically acceptable results for the organs at risk in accordance with the UK SABR consensus guidelines and the LungTech EORTC phase II trial. The overall good agreement between sCTDSL and CT demonstrates the feasibility of employing synthetic 4D-CT for plan adaptation on hybrid MR-guided radiotherapy systems.
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Affiliation(s)
- Joshua N Freedman
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
- CR UK Cancer Imaging Centre, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Hannah E Bainbridge
- Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Simeon Nill
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - David J Collins
- CR UK Cancer Imaging Centre, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Marc Kachelrieß
- Medical Physics in Radiology, The German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Martin O Leach
- CR UK Cancer Imaging Centre, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
- Author to whom any correspondence should be addressed
| | - Fiona McDonald
- Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Uwe Oelfke
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
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Gurney-Champion OJ, Collins DJ, Wetscherek A, Rata M, Klaassen R, van Laarhoven HWM, Harrington KJ, Oelfke U, Orton MR. Principal component analysis fosr fast and model-free denoising of multi b-value diffusion-weighted MR images. Phys Med Biol 2019; 64:105015. [PMID: 30965296 PMCID: PMC7655121 DOI: 10.1088/1361-6560/ab1786] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 03/18/2019] [Accepted: 04/09/2019] [Indexed: 02/08/2023]
Abstract
Despite the utility of tumour characterisation using quantitative parameter maps from multi-b-value diffusion-weighted MRI (DWI), clinicians often prefer the use of the image with highest diffusion-weighting (b-value), for instance for defining regions of interest (ROIs). However, these images are typically degraded by noise, as they do not utilize the information from the full acquisition. We present a principal component analysis (PCA) approach for model-free denoising of DWI data. PCA-denoising was compared to synthetic MRI, where a diffusion model is fitted for each voxel and a denoised image at a given b-value is generated from the model fit. A quantitative comparison of systematic and random errors was performed on data simulated using several diffusion models (mono-exponential, bi-exponential, stretched-exponential and kurtosis). A qualitative visual comparison was also performed for in vivo images in six healthy volunteers and three pancreatic cancer patients. In simulations, the reduction in random errors from PCA-denoising was substantial (up to 55%) and similar to synthetic MRI (up to 53%). Model-based synthetic MRI denoising resulted in substantial (up to 29% of signal) systematic errors, whereas PCA-denoising was able to denoise without introducing systematic errors (less than 2%). In vivo, the signal-to-noise ratio (SNR) and sharpness of PCA-denoised images were superior to synthetic MRI, resulting in clearer tumour boundaries. In the presence of motion, PCA-denoising did not cause image blurring, unlike image averaging or synthetic MRI. Multi-b-value MRI can be denoised model-free with our PCA-denoising strategy that reduces noise to a level similar to synthetic MRI, but without introducing systematic errors associated with the synthetic MRI method.
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Affiliation(s)
- Oliver J Gurney-Champion
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden
NHS Foundation Trust, London, United
Kingdom
| | - David J Collins
- Cancer Research UK Cancer Imaging Centre,
The Institute of Cancer Research and The
Royal Marsden NHS Foundation Trust, London, United
Kingdom
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden
NHS Foundation Trust, London, United
Kingdom
| | - Mihaela Rata
- Cancer Research UK Cancer Imaging Centre,
The Institute of Cancer Research and The
Royal Marsden NHS Foundation Trust, London, United
Kingdom
| | - Remy Klaassen
- Department of Medical Oncology, Cancer Center
Amsterdam, Amsterdam UMC, University of
Amsterdam, Amsterdam, The Netherlands
| | - Hanneke W M van Laarhoven
- Department of Medical Oncology, Cancer Center
Amsterdam, Amsterdam UMC, University of
Amsterdam, Amsterdam, The Netherlands
| | - Kevin J Harrington
- Targeted Therapy Team, The Institute of Cancer Research and The Royal Marsden
NHS Foundation Trust, London, United
Kingdom
| | - Uwe Oelfke
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden
NHS Foundation Trust, London, United
Kingdom
| | - Matthew R Orton
- Cancer Research UK Cancer Imaging Centre,
The Institute of Cancer Research and The
Royal Marsden NHS Foundation Trust, London, United
Kingdom
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Riexinger AJ, Martin J, Rauh S, Wetscherek A, Pistel M, Kuder TA, Nagel AM, Uder M, Hensel B, Müller L, Laun FB. On the Field Strength Dependence of Bi- and Triexponential Intravoxel Incoherent Motion (IVIM) Parameters in the Liver. J Magn Reson Imaging 2019; 50:1883-1892. [PMID: 30941806 DOI: 10.1002/jmri.26730] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [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: 12/14/2018] [Revised: 03/12/2019] [Accepted: 03/12/2019] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Studies on intravoxel incoherent motion (IVIM) imaging are carried out with different acquisition protocols. PURPOSE To investigate the dependence of IVIM parameters on the B0 field strength when using a bi- or triexponential model. STUDY TYPE Prospective. STUDY POPULATION 20 healthy volunteers (age: 19-28 years). FIELD STRENGTH/SEQUENCE Volunteers were examined at two field strengths (1.5 and 3T). Diffusion-weighted images of the abdomen were acquired at 24 b-values ranging from 0.2 to 500 s/mm2 . ASSESSMENT ROIs were manually drawn in the liver. Data were fitted with a bi- and a triexponential IVIM model. The resulting parameters were compared between both field strengths. STATISTICAL TESTS One-way analysis of variance (ANOVA) and Kruskal-Wallis test were used to test the obtained IVIM parameters for a significant field strength dependency. RESULTS At b-values below 6 s/mm2 , the triexponential model provided better agreement with the data than the biexponential model. The average tissue diffusivity was D = 1.22/1.00 μm2 /msec at 1.5/3T. The average pseudodiffusion coefficients for the biexponential model were D* = 308/260 μm2 /msec at 1.5/3T; and for the triexponential model D 1 * = 81.3/65.9 μm2 /msec, D 2 * = 2453/2333 μm2 /msec at 1.5/3T. The average perfusion fractions for the biexponential model were f = 0.286/0.303 at 1.5/3T; and for the triexponential model f1 = 0.161/0.174 and f2 = 0.152/0.159 at 1.5/3T. A significant B0 dependence was only found for the biexponential pseudodiffusion coefficient (ANOVA/KW P = 0.037/0.0453) and tissue diffusivity (ANOVA/KW: P < 0.001). DATA CONCLUSION Our experimental results suggest that triexponential pseudodiffusion coefficients and perfusion fractions obtained at different field strengths could be compared across different studies using different B0 . However, it is recommended to take the field strength into account when comparing tissue diffusivities or using the biexponential IVIM model. Considering published values for oxygenation-dependent transversal relaxation times of blood, it is unlikely that the two blood compartments of the triexponential model represent venous and arterial blood. LEVEL OF EVIDENCE 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:1883-1892.
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Affiliation(s)
- Andreas Julian Riexinger
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Jan Martin
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Susanne Rauh
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Andreas Wetscherek
- Joint Department of Physics, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, UK
| | - Mona Pistel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Tristan Anselm Kuder
- Department of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Armin Michael Nagel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Michael Uder
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Bernhard Hensel
- Center for Medical Physics and Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Lars Müller
- Department of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,CUBRIC, School of Psychology, Cardiff University, Cardiff, UK
| | - Frederik Bernd Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
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Tran E, Eiben B, Wetscherek A, Oelfke U, Meedt G, Hawkes D, McClelland J. OC-0413 MR-derived signals for respiratory motion models evaluated using sagittal and coronal datasets. Radiother Oncol 2019. [DOI: 10.1016/s0167-8140(19)30833-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Cobben D, Bainbridge H, Belderbos J, Cheung P, Dubec M, Gomez D, Gore E, Knowles E, Lalezari F, Oelfke U, Sonke J, Tijssen R, Van Es C, Van Herk M, Wetscherek A, McDonald F, Faivre-Finn C. EP-1346 A framework for systematic clinical evaluation of the MR-linac for treatment of lung cancer patients. Radiother Oncol 2019. [DOI: 10.1016/s0167-8140(19)31766-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Shiarli A, Brown S, Dubec M, Bainbridge H, Koh D, Lalezari F, Van Herk M, Wetscherek A, Knowles E, Faivre-Finn C, Mcdonald F. Gross tumour volume (GTV) delineation on magnetic resonance imaging (MRI), for stage III lung cancer: consensus recommendations needed to ensure contouring consistency. Lung Cancer 2019. [DOI: 10.1016/s0169-5002(19)30229-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Cobben D, Bainbridge H, Belderbos J, Cheung P, Dubec M, Gomez D, Gore E, Knowles E, Lalezari F, Oelfke U, Sonke J, Tijssen R, Van Es C, Van Herk M, Wetscherek A, Mcdonald F, Faivre-Finn C. A framework for systematic clinical evaluation of technical innovations in lung cancer patients treated on the MR-linac (MRL). Lung Cancer 2019. [DOI: 10.1016/s0169-5002(19)30184-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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41
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Tijssen RHN, Philippens MEP, Paulson ES, Glitzner M, Chugh B, Wetscherek A, Dubec M, Wang J, van der Heide UA. MRI commissioning of 1.5T MR-linac systems - a multi-institutional study. Radiother Oncol 2018; 132:114-120. [PMID: 30825959 DOI: 10.1016/j.radonc.2018.12.011] [Citation(s) in RCA: 92] [Impact Index Per Article: 15.3] [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: 08/17/2018] [Revised: 11/14/2018] [Accepted: 12/11/2018] [Indexed: 10/27/2022]
Abstract
BACKGROUND Magnetic Resonance linear accelerator (MR-linac) systems represent a new type of technology that allows for online MR-guidance for high precision radiotherapy (RT). Currently, the first MR-linac installations are being introduced clinically. Since the imaging performance of these integrated MR-linac systems is critical for their application, a thorough commissioning of the MRI performance is essential. However, guidelines on the commissioning of MR-guided RT systems are not yet defined and data on the performance of MR-linacs are not yet available. MATERIALS & METHODS Here we describe a comprehensive commissioning protocol, which contains standard MRI performance measurements as well as dedicated hybrid tests that specifically assess the interactions between the Linac and the MRI system. The commissioning results of four MR-linac systems are presented in a multi-center study. RESULTS Although the four systems showed similar performance in all the standard MRI performance tests, some differences were observed relating to the hybrid character of the systems. Field homogeneity measurements identified differences in the gantry shim configuration, which was later confirmed by the vendor. CONCLUSION Our results highlight the importance of dedicated hybrid commissioning tests and the ability to compare the machines between institutes at this very early stage of clinical introduction. Until formal guidelines and tolerances are defined the tests described in this study may be used as a practical guideline. Moreover, the multi-center results provide initial bench mark data for future MR-linac installations.
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Affiliation(s)
- Rob H N Tijssen
- Department of Radiotherapy, University Medical Center Utrecht, the Netherlands.
| | | | - Eric S Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, United States
| | - Markus Glitzner
- Department of Radiotherapy, University Medical Center Utrecht, the Netherlands
| | - Brige Chugh
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Andreas Wetscherek
- Joint Department of Physics, the Institute of Cancer Research and the Royal Marsden Hospital NHS Foundation Trust, London, UK
| | - Michael Dubec
- The Christie NHS Foundation Trust and the University of Manchester, UK
| | - Jihong Wang
- Department of Radiation Physics, the University of Texas MD Anderson Cancer Center, Houston, United States
| | - Uulke A van der Heide
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
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Freedman JN, Collins DJ, Gurney-Champion OJ, McClelland JR, Nill S, Oelfke U, Leach MO, Wetscherek A. Super-resolution T2-weighted 4D MRI for image guided radiotherapy. Radiother Oncol 2018; 129:486-493. [PMID: 29871813 PMCID: PMC6294732 DOI: 10.1016/j.radonc.2018.05.015] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2017] [Revised: 05/02/2018] [Accepted: 05/14/2018] [Indexed: 11/28/2022]
Abstract
BACKGROUND AND PURPOSE The superior soft-tissue contrast of 4D-T2w MRI motivates its use for delineation in radiotherapy treatment planning. We address current limitations of slice-selective implementations, including thick slices and artefacts originating from data incompleteness and variable breathing. MATERIALS AND METHODS A method was developed to calculate midposition and 4D-T2w images of the whole thorax from continuously acquired axial and sagittal 2D-T2w MRI (1.5 × 1.5 × 5.0 mm3). The method employed image-derived respiratory surrogates, deformable image registration and super-resolution reconstruction. Volunteer imaging and a respiratory motion phantom were used for validation. The minimum number of dynamic acquisitions needed to calculate a representative midposition image was investigated by retrospectively subsampling the data (10-30 dynamic acquisitions). RESULTS Super-resolution 4D-T2w MRI (1.0 × 1.0 × 1.0 mm3, 8 respiratory phases) did not suffer from data incompleteness and exhibited reduced stitching artefacts compared to sorted multi-slice MRI. Experiments using a respiratory motion phantom and colour-intensity projection images demonstrated a minor underestimation of the motion range. Midposition diaphragm differences in retrospectively subsampled acquisitions were <1.1 mm compared to the full dataset. 10 dynamic acquisitions were found sufficient to generate midposition MRI. CONCLUSIONS A motion-modelling and super-resolution method was developed to calculate high quality 4D/midposition T2w MRI from orthogonal 2D-T2w MRI.
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Affiliation(s)
- Joshua N Freedman
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK; CR UK Cancer Imaging Centre, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - David J Collins
- CR UK Cancer Imaging Centre, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Oliver J Gurney-Champion
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Jamie R McClelland
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, UK
| | - Simeon Nill
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Uwe Oelfke
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Martin O Leach
- CR UK Cancer Imaging Centre, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK.
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
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Menten MJ, Fast MF, Wetscherek A, Rank CM, Kachelrieß M, Collins DJ, Nill S, Oelfke U. The impact of 2D cine MR imaging parameters on automated tumor and organ localization for MR-guided real-time adaptive radiotherapy. Phys Med Biol 2018; 63:235005. [PMID: 30465542 PMCID: PMC6372137 DOI: 10.1088/1361-6560/aae74d] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 09/22/2018] [Accepted: 10/10/2018] [Indexed: 12/25/2022]
Abstract
2D cine MR imaging may be utilized to monitor rapidly moving tumors and organs-at-risk for real-time adaptive radiotherapy. This study systematically investigates the impact of geometric imaging parameters on the ability of 2D cine MR imaging to guide template-matching-driven autocontouring of lung tumors and abdominal organs. Abdominal 4D MR images were acquired of six healthy volunteers and thoracic 4D MR images were obtained of eight lung cancer patients. At each breathing phase of the images, the left kidney and gallbladder or lung tumor, respectively, were outlined as volumes of interest. These images and contours were used to create artificial 2D cine MR images, while simultaneously serving as 3D ground truth. We explored the impact of five different imaging parameters (pixel size, slice thickness, imaging plane orientation, number and relative alignment of images as well as strategies to create training images). For each possible combination of imaging parameters, we generated artificial 2D cine MR images as training and test images. A template-matching algorithm used the training images to determine the tumor or organ position in the test images. Subsequently, a 3D base contour was shifted to the determined position and compared to the ground truth via centroid distance and Dice similarity coefficient. The median centroid distance between adapted and ground truth contours was 1.56 mm for the kidney, 3.81 mm for the gallbladder and 1.03 mm for the lung tumor (median Dice similarity coefficient: 0.95, 0.72 and 0.93). We observed that a decrease in image resolution led to a modest decrease in localization accuracy, especially for the small gallbladder. However, for all volumes of interest localization accuracy varied substantially more between subjects than due to the different imaging parameters. Automated tumor and organ localization using 2D cine MR imaging and template-matching-based autocontouring is robust against variation of geometric imaging parameters. Future work and optimization efforts of 2D cine MR imaging for real-time adaptive radiotherapy is needed to characterize the influence of sequence- and anatomical site-specific imaging contrast.
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Affiliation(s)
- Martin J Menten
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Martin F Fast
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Andreas Wetscherek
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Christopher M Rank
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Marc Kachelrieß
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - David J Collins
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Simeon Nill
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Uwe Oelfke
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
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Cobben D, Bainbridge H, Belderbos J, Cheung P, Dubec M, Gomez D, Gore E, Knowles E, Lalezari F, Oelfke U, Sonke J, Tijssen R, Van Es C, Van Herk M, Wetscherek A, Mcdonald F, Faivre-Finn C. P3.01-26 A Framework for Systematic Clinical Evaluation of Technical Innovations in Lung Cancer Patients Treated on the MR-Linac (MRL). J Thorac Oncol 2018. [DOI: 10.1016/j.jtho.2018.08.1586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Schneider TM, Nagel AM, Zorn M, Wetscherek A, Bendszus M, Ladd ME, Straub S. Quantitative susceptibility mapping and 23 Na imaging-based in vitro characterization of blood clotting kinetics. NMR Biomed 2018; 31:e3926. [PMID: 29694688 DOI: 10.1002/nbm.3926] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Revised: 02/16/2018] [Accepted: 03/04/2018] [Indexed: 06/08/2023]
Abstract
Blood clotting is a fundamental biochemical process in post-hemorrhagic hemostasis. Although the varying appearance of coagulating blood in T1 - and T2 -weighted images is widely used to qualitatively determine bleeding age, the technique permits only a rough discrimination of coagulation stages, and it remains difficult to distinguish acute and chronic hemorrhagic stages because of low T1 - and T2 -weighted signal intensities in both instances. To investigate new biomedical parameters for magnetic resonance imaging-based characterization of blood clotting kinetics, sodium imaging and quantitative susceptibility mapping (QSM) were compared with conventional T1 - and T2 -weighted imaging, as well as with biochemical hemolysis parameters. For this purpose, a blood-filled spherical agar phantom was investigated daily for 14 days, as well as after 24 days at 7 T after initial preparation with fresh blood. T1 - and T2 -weighted sequences, a three-dimensional (3D) gradient echo sequence and a density-adapted 3D radial projection reconstruction pulse sequence for 23 Na imaging were applied. For hemolysis estimations, free hemoglobin and free potassium concentrations were measured photometrically and with the direct ion-selective electrode method, respectively, in separate heparinized whole-blood samples along the same timeline. Initial mean susceptibility was low (0.154 ± 0.020 ppm) and increased steadily during the course of coagulation to reach up to 0.570 ± 0.165 ppm. The highest total sodium (NaT) values (1.02 ± 0.06 arbitrary units) in the clot were observed initially, dropped to 0.69 ± 0.13 arbitrary units after one day and increased again to initial values. Compartmentalized sodium (NaS) showed a similar signal evolution, and the NaS/NaT ratio steadily increased over clot evolution. QSM depicts clot evolution in vitro as a process associated with hemoglobin accumulation and transformation, and enables the differentiation of the acute and chronic coagulation stages. Sodium imaging visualizes clotting independent of susceptibility and seems to correspond to clot integrity. A combination of QSM and sodium imaging may enhance the characterization of hemorrhage.
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Affiliation(s)
- Till M Schneider
- Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany
| | - Armin M Nagel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
- Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Markus Zorn
- Department of Medical Chemistry, University of Heidelberg, Heidelberg, Germany
| | - Andreas Wetscherek
- Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany
| | - Mark E Ladd
- Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Sina Straub
- Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
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Abstract
PURPOSE To characterize the diffusion coefficient of human blood for accurate results in intravoxel incoherent motion imaging. METHODS Diffusion-weighted MRI of blood samples from 10 healthy volunteers was acquired with a single-shot echo-planar-imaging sequence at body temperature. Effects of gradient profile (monopolar or flow-compensated), diffusion time (40-100 ms), and echo time (60-200 ms) were investigated. RESULTS Although measured apparent diffusion coefficients of blood were larger for flow-compensated than for monopolar gradients, no dependence of the apparent diffusion coefficient on the diffusion time was found. Large differences between individual samples were observed, with results ranging from 1.26 to 1.66 µm2 /ms for flow-compensated and 0.94 to 1.52 µm2 /ms for monopolar gradients. Statistical analysis indicates correlations of the flow-compensated apparent diffusion coefficient with hematocrit (P = 0.007) and hemoglobin (P = 0.017), but not with mean corpuscular volume (P = 0.64). Results of Monte-Carlo simulations support the experimental observations. CONCLUSIONS Measured blood apparent diffusion coefficient values depend on hematocrit/hemoglobin concentration and applied gradient profile due to non-Gaussian diffusion. Because in vivo measurement is delicate, an estimation based on blood count results could be an alternative. For intravoxel incoherent motion modeling, the use of a blood self-diffusion constant Db = 1.54 ± 0.12 µm2 /ms for flow-compensated and Db = 1.30 ± 0.18 µm2 /ms for monopolar encoding is suggested. Magn Reson Med 79:2752-2758, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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Affiliation(s)
- Carsten Funck
- Medical Physics in Radiology, German Cancer Research Center (DKFZ)HeidelbergGermany
| | - Frederik Bernd Laun
- Medical Physics in Radiology, German Cancer Research Center (DKFZ)HeidelbergGermany
- Institute of RadiologyUniversity Hospital ErlangenErlangenGermany
| | - Andreas Wetscherek
- Medical Physics in Radiology, German Cancer Research Center (DKFZ)HeidelbergGermany
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUnited Kingdom
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Tran E, Eiben B, Wetscherek A, Collins D, Oelfke U, Meedt G, Hawkes D, McClelland J. OC-0411: Investigation of MRI-derived surrogate signals for modelling respiratory motion on an MRI-Linac. Radiother Oncol 2018. [DOI: 10.1016/s0167-8140(18)30721-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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Eiben B, Tran E, Menten M, Wetscherek A, Hawkes D, Oelfke U, McClelland J. EP-2135: Statistical motion masks to identify sliding surfaces for motion models used on an MR-Linac. Radiother Oncol 2018. [DOI: 10.1016/s0167-8140(18)32444-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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Bainbridge H, Salem A, Tijssen RHN, Dubec M, Wetscherek A, Van Es C, Belderbos J, Faivre-Finn C, McDonald F. Magnetic resonance imaging in precision radiation therapy for lung cancer. Transl Lung Cancer Res 2017; 6:689-707. [PMID: 29218271 PMCID: PMC5709138 DOI: 10.21037/tlcr.2017.09.02] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Accepted: 09/08/2017] [Indexed: 12/25/2022]
Abstract
Radiotherapy remains the cornerstone of curative treatment for inoperable locally advanced lung cancer, given concomitantly with platinum-based chemotherapy. With poor overall survival, research efforts continue to explore whether integration of advanced radiation techniques will assist safe treatment intensification with the potential for improving outcomes. One advance is the integration of magnetic resonance imaging (MRI) in the treatment pathway, providing anatomical and functional information with excellent soft tissue contrast without exposure of the patient to radiation. MRI may complement or improve the diagnostic staging accuracy of F-18 fluorodeoxyglucose position emission tomography and computerized tomography imaging, particularly in assessing local tumour invasion and is also effective for identification of nodal and distant metastatic disease. Incorporating anatomical MRI sequences into lung radiotherapy treatment planning is a novel application and may improve target volume and organs at risk delineation reproducibility. Furthermore, functional MRI may facilitate dose painting for heterogeneous target volumes and prediction of normal tissue toxicity to guide adaptive strategies. MRI sequences are rapidly developing and although the issue of intra-thoracic motion has historically hindered the quality of MRI due to the effect of motion, progress is being made in this field. Four-dimensional MRI has the potential to complement or supersede 4D CT and 4D F-18-FDG PET, by providing superior spatial resolution. A number of MR-guided radiotherapy delivery units are now available, combining a radiotherapy delivery machine (linear accelerator or cobalt-60 unit) with MRI at varying magnetic field strengths. This novel hybrid technology is evolving with many technical challenges to overcome. It is anticipated that the clinical benefits of MR-guided radiotherapy will be derived from the ability to adapt treatment on the fly for each fraction and in real-time, using 'beam-on' imaging. The lung tumour site group of the Atlantic MR-Linac consortium is working to generate a challenging MR-guided adaptive workflow for multi-institution treatment intensification trials in this patient group.
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Affiliation(s)
- Hannah Bainbridge
- The Institute of Cancer Research and The Royal Marsden Hospital NHS Foundation Trust, London, UK
| | - Ahmed Salem
- The University of Manchester and The Christie NHS Foundation Trust, Manchester, UK
| | | | - Michael Dubec
- The University of Manchester and The Christie NHS Foundation Trust, Manchester, UK
| | - Andreas Wetscherek
- The Institute of Cancer Research and The Royal Marsden Hospital NHS Foundation Trust, London, UK
| | - Corinne Van Es
- The University Medical Center Utrecht, Utrecht, the Netherlands
| | - Jose Belderbos
- The Netherlands Cancer Institute and The Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Corinne Faivre-Finn
- The University of Manchester and The Christie NHS Foundation Trust, Manchester, UK
| | - Fiona McDonald
- The Institute of Cancer Research and The Royal Marsden Hospital NHS Foundation Trust, London, UK
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Abstract
Stereotactic body radiotherapy (SBRT) is rapidly becoming an alternative to surgery for the treatment of early-stage non-small cell lung cancer patients. Lung SBRT is administered in a hypo-fractionated, conformal manner, delivering high doses to the target. To avoid normal-tissue toxicity, it is crucial to limit the exposure of nearby healthy organs-at-risk (OAR). Current image-guided radiotherapy strategies for lung SBRT are mostly based on X-ray imaging modalities. Although still in its infancy, magnetic resonance imaging (MRI) guidance for lung SBRT is not exposure-limited and MRI promises to improve crucial soft-tissue contrast. Looking beyond anatomical imaging, functional MRI is expected to inform treatment decisions and adaptations in the future. This review summarises and discusses how MRI could be advantageous to the different links of the radiotherapy treatment chain for lung SBRT: diagnosis and staging, tumour and OAR delineation, treatment planning, and inter- or intrafractional motion management. Special emphasis is placed on a new generation of hybrid MRI treatment devices and their potential for real-time adaptive radiotherapy.
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Affiliation(s)
- Martin J Menten
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK.
| | - Andreas Wetscherek
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Martin F Fast
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK.
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