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Salzillo TC, Dresner MA, Way A, Wahid KA, McDonald BA, Mulder S, Naser MA, He R, Ding Y, Yoder A, Ahmed S, Corrigan KL, Manzar GS, Andring L, Pinnix C, Stafford RJ, Mohamed ASR, Christodouleas J, Wang J, Fuller CD. Development and implementation of optimized endogenous contrast sequences for delineation in adaptive radiotherapy on a 1.5T MR-linear-accelerator: a prospective R-IDEAL stage 0-2a quantitative/qualitative evaluation of in vivo site-specific quality-assurance using a 3D T2 fat-suppressed platform for head and neck cancer. J Med Imaging (Bellingham) 2023; 10:065501. [PMID: 37937259 PMCID: PMC10627232 DOI: 10.1117/1.jmi.10.6.065501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 10/06/2023] [Accepted: 10/16/2023] [Indexed: 11/09/2023] Open
Abstract
Purpose To improve segmentation accuracy in head and neck cancer (HNC) radiotherapy treatment planning for the 1.5T hybrid magnetic resonance imaging/linear accelerator (MR-Linac), three-dimensional (3D), T2-weighted, fat-suppressed magnetic resonance imaging sequences were developed and optimized. Approach After initial testing, spectral attenuated inversion recovery (SPAIR) was chosen as the fat suppression technique. Five candidate SPAIR sequences and a nonsuppressed, T2-weighted sequence were acquired for five HNC patients using a 1.5T MR-Linac. MR physicists identified persistent artifacts in two of the SPAIR sequences, so the remaining three SPAIR sequences were further analyzed. The gross primary tumor volume, metastatic lymph nodes, parotid glands, and pterygoid muscles were delineated using five segmentors. A robust image quality analysis platform was developed to objectively score the SPAIR sequences on the basis of qualitative and quantitative metrics. Results Sequences were analyzed for the signal-to-noise ratio and the contrast-to-noise ratio and compared with fat and muscle, conspicuity, pairwise distance metrics, and segmentor assessments. In this analysis, the nonsuppressed sequence was inferior to each of the SPAIR sequences for the primary tumor, lymph nodes, and parotid glands, but it was superior for the pterygoid muscles. The SPAIR sequence that received the highest combined score among the analysis categories was recommended to Unity MR-Linac users for HNC radiotherapy treatment planning. Conclusions Our study led to two developments: an optimized, 3D, T2-weighted, fat-suppressed sequence that can be disseminated to Unity MR-Linac users and a robust image quality analysis pathway that can be used to objectively score SPAIR sequences and can be customized and generalized to any image quality optimization protocol. Improved segmentation accuracy with the proposed SPAIR sequence will potentially lead to improved treatment outcomes and reduced toxicity for patients by maximizing the target coverage and minimizing the radiation exposure of organs at risk.
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Affiliation(s)
- Joint Head and Neck Radiotherapy-MRI Development Cooperative
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
- Philips Healthcare, Cleveland, Ohio, United States
- MD Anderson Cancer Center, Radiation Physics, Houston, Texas, United States
- MD Anderson Cancer Center, Imaging Physics, Houston, Texas, United States
- Elekta AB, Stockholm, Sweden
| | - Travis C. Salzillo
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
| | | | - Ashley Way
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
| | - Kareem A. Wahid
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
| | - Brigid A. McDonald
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
| | - Sam Mulder
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
| | - Mohamed A. Naser
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
| | - Renjie He
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
| | - Yao Ding
- MD Anderson Cancer Center, Radiation Physics, Houston, Texas, United States
| | - Alison Yoder
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
| | - Sara Ahmed
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
| | - Kelsey L. Corrigan
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
| | - Gohar S. Manzar
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
| | - Lauren Andring
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
| | - Chelsea Pinnix
- MD Anderson Cancer Center, Radiation Oncology, Houston, Texas, United States
| | - R. Jason Stafford
- MD Anderson Cancer Center, Imaging Physics, Houston, Texas, United States
| | | | | | - Jihong Wang
- MD Anderson Cancer Center, Radiation Physics, Houston, Texas, United States
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2
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Weygand J, Armstrong T, Bryant JM, Andreozzi JM, Oraiqat IM, Nichols S, Liveringhouse CL, Latifi K, Yamoah K, Costello JR, Frakes JM, Moros EG, El Naqa IM, Naghavi AO, Rosenberg SA, Redler G. Accurate, repeatable, and geometrically precise diffusion-weighted imaging on a 0.35 T magnetic resonance imaging-guided linear accelerator. Phys Imaging Radiat Oncol 2023; 28:100505. [PMID: 38045642 PMCID: PMC10692914 DOI: 10.1016/j.phro.2023.100505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 10/04/2023] [Accepted: 10/30/2023] [Indexed: 12/05/2023] Open
Abstract
Background and purpose Diffusion weighted imaging (DWI) allows for the interrogation of tissue cellularity, which is a surrogate for cellular proliferation. Previous attempts to incorporate DWI into the workflow of a 0.35 T MR-linac (MRL) have lacked quantitative accuracy. In this study, accuracy, repeatability, and geometric precision of apparent diffusion coefficient (ADC) maps produced using an echo planar imaging (EPI)-based DWI protocol on the MRL system is illustrated, and in vivo potential for longitudinal patient imaging is demonstrated. Materials and methods Accuracy and repeatability were assessed by measuring ADC values in a diffusion phantom at three timepoints and comparing to reference ADC values. System-dependent geometric distortion was quantified by measuring the distance between 93 pairs of phantom features on ADC maps acquired on a 0.35 T MRL and a 3.0 T diagnostic scanner and comparing to spatially precise CT images. Additionally, for five sarcoma patients receiving radiotherapy on the MRL, same-day in vivo ADC maps were acquired on both systems, one of which at multiple timepoints. Results Phantom ADC quantification was accurate on the 0.35 T MRL with significant discrepancies only seen at high ADC. Average geometric distortions were 0.35 (±0.02) mm and 0.85 (±0.02) mm in the central slice and 0.66 (±0.04) mm and 2.14 (±0.07) mm at 5.4 cm off-center for the MRL and diagnostic system, respectively. In the sarcoma patients, a mean pretreatment ADC of 910x10-6 (±100x10-6) mm2/s was measured on the MRL. Conclusions The acquisition of accurate, repeatable, and geometrically precise ADC maps is possible at 0.35 T with an EPI approach.
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Affiliation(s)
- Joseph Weygand
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | | | | | | | | | - Steven Nichols
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | | | - Kujtim Latifi
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | - Kosj Yamoah
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | | | - Jessica M. Frakes
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | - Eduardo G. Moros
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | - Issam M. El Naqa
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
- Department of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA
| | - Arash O. Naghavi
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | | | - Gage Redler
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
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Naser MA, Wahid KA, Ahmed S, Salama V, Dede C, Edwards BW, Lin R, McDonald B, Salzillo TC, He R, Ding Y, Abdelaal MA, Thill D, O'Connell N, Willcut V, Christodouleas JP, Lai SY, Fuller CD, Mohamed ASR. Quality assurance assessment of intra-acquisition diffusion-weighted and T2-weighted magnetic resonance imaging registration and contour propagation for head and neck cancer radiotherapy. Med Phys 2023; 50:2089-2099. [PMID: 36519973 PMCID: PMC10121748 DOI: 10.1002/mp.16128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 11/10/2022] [Accepted: 11/13/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND/PURPOSE Adequate image registration of anatomical and functional magnetic resonance imaging (MRI) scans is necessary for MR-guided head and neck cancer (HNC) adaptive radiotherapy planning. Despite the quantitative capabilities of diffusion-weighted imaging (DWI) MRI for treatment plan adaptation, geometric distortion remains a considerable limitation. Therefore, we systematically investigated various deformable image registration (DIR) methods to co-register DWI and T2-weighted (T2W) images. MATERIALS/METHODS We compared three commercial (ADMIRE, Velocity, Raystation) and three open-source (Elastix with default settings [Elastix Default], Elastix with parameter set 23 [Elastix 23], Demons) post-acquisition DIR methods applied to T2W and DWI MRI images acquired during the same imaging session in twenty immobilized HNC patients. In addition, we used the non-registered images (None) as a control comparator. Ground-truth segmentations of radiotherapy structures (tumour and organs at risk) were generated by a physician expert on both image sequences. For each registration approach, structures were propagated from T2W to DWI images. These propagated structures were then compared with ground-truth DWI structures using the Dice similarity coefficient and mean surface distance. RESULTS 19 left submandibular glands, 18 right submandibular glands, 20 left parotid glands, 20 right parotid glands, 20 spinal cords, and 12 tumours were delineated. Most DIR methods took <30 s to execute per case, with the exception of Elastix 23 which took ∼458 s to execute per case. ADMIRE and Elastix 23 demonstrated improved performance over None for all metrics and structures (Bonferroni-corrected p < 0.05), while the other methods did not. Moreover, ADMIRE and Elastix 23 significantly improved performance in individual and pooled analysis compared to all other methods. CONCLUSIONS The ADMIRE DIR method offers improved geometric performance with reasonable execution time so should be favoured for registering T2W and DWI images acquired during the same scan session in HNC patients. These results are important to ensure the appropriate selection of registration strategies for MR-guided radiotherapy.
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Affiliation(s)
- Mohamed A Naser
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Kareem A Wahid
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Sara Ahmed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Vivian Salama
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Cem Dede
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Benjamin W Edwards
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Ruitao Lin
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Brigid McDonald
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Travis C Salzillo
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Renjie He
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Yao Ding
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Moamen Abobakr Abdelaal
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | | | | | | | | | - Stephen Y Lai
- Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Abdallah S R Mohamed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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4
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Palmér E, Nordström F, Karlsson A, Petruson K, Ljungberg M, Sohlin M. Head and neck cancer patient positioning using synthetic CT data in MRI-only radiation therapy. J Appl Clin Med Phys 2022; 23:e13525. [PMID: 35044070 PMCID: PMC8992936 DOI: 10.1002/acm2.13525] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Purpose The accuracy and precision of patient positioning is crucial in radiotherapy; however, there are no publications available using synthetic computed tomography (sCT) that evaluate rotations in head and neck (H&N) patients positioning or the effect of translation and rotation combined. The aim of this work was to evaluate the differences between using sCT with the CT for 2D‐ and 3D‐patient positioning in a magnetic resonance imaging (MRI)‐only workflow. Methods This study included 14 H&N cancer patients, with generated sCT data (MRI Planner v2.2) and the CT deformably registered to the MRI. Patient positioning was evaluated by comparing sCT against CT data: 3D cone beam CT (CBCT) was registered to the deformed CT (dCT) and sCT in six degrees of freedom (DoF) with a rigid auto‐registration algorithm and bone threshold, and 2D deformed digital reconstructed radiographs (dDRR) and synthetic DRRs (sDRR) were manually registered to orthogonal projections in five DoF by six blinded observers. The difference in displacement in all DoF were calculated for dCT and sCT, as well as for dDRR and sDRR. The interobserver variation was evaluated by separate application of the paired dDRR and sDRR registration matrices to the original coordinates of the planning target volume (PTV) structures and calculation of the Euclidean distance between the corresponding points. The Dice similarity coefficient (DSC) was calculated between dDRR/sDRR‐registered PTVs. Results The mean difference in patient positioning using CBCT was <0.7 mm and <0.3° and using orthogonal projections <0.4 mm and <0.2° in all directions. The maximum Euclidean distance was 5.1 mm, the corresponding mean (1SD) Euclidean distance and mean DSC were 3.5 ± 0.7 mm and 0.93, respectively. Conclusions This study shows that the sCT‐based patient positioning gives a comparable result with that based on CT images, allowing sCT to replace CT as reference for patient treatment positioning.
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Affiliation(s)
- Emilia Palmér
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Fredrik Nordström
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Anna Karlsson
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Karin Petruson
- Department of Oncology and Radiotherapy, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Maria Ljungberg
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Maja Sohlin
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
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5
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Wang J, Salzillo T, Jiang Y, Mackeyev Y, David Fuller C, Chung C, Choi S, Hughes N, Ding Y, Yang J, Vedam S, Krishnan S. Stability of MRI contrast agents in high-energy radiation of a 1.5T MR-Linac. Radiother Oncol 2021; 161:55-64. [PMID: 34089753 PMCID: PMC8324543 DOI: 10.1016/j.radonc.2021.05.023] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 05/24/2021] [Accepted: 05/26/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND Gadolinium-based contrast is often used when acquiring MR images for radiation therapy planning for better target delineation. In some situations, patients may still have residual MRI contrast agents in their tissue while being treated with high-energy radiation. This is especially true when MRI contrast agents are administered during adaptive treatment replanning for patients treated on MR-Linac systems. PURPOSE The purpose of this study was to analyze the molecular stability of MRI contrast agents when exposed to high energy photons and the associated secondary electrons in a 1.5T MR-Linac system. This was the first step in assessing the safety of administering MRI contrast agents throughout the course of treatment. MATERIALS AND METHODS Two common MRI contrast agents were irradiated with 7 MV photons to clinical dose levels. The irradiated samples were analyzed using liquid chromatography-high resolution mass spectrometry to detect degradation products or conformational alterations created by irradiation with high energy photons and associated secondary electrons. RESULTS No significant change in chemical composition or displacement of gadolinium ions from their chelates was discovered in samples irradiated with 7 MV photons at relevant clinical doses in a 1.5T MR-Linac. Additionally, no significant correlation between concentrations of irradiated MRI contrast agents and radiation dose was observed. CONCLUSION The chemical composition stability of the irradiated contrast agents is promising for future use throughout the course of patient treatment. However, in vivo studies are needed to confirm that unexpected metabolites are not created in biological milieus.
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Affiliation(s)
- Jihong Wang
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, United States.
| | - Travis Salzillo
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, United States
| | - Yongying Jiang
- The Institute for Applied Cancer Science, MD Anderson Cancer Center, Houston, United States
| | - Yuri Mackeyev
- Department of Radiation Oncology, Mayo Clinic, Jacksonville, United States
| | - Clifton David Fuller
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, United States
| | - Caroline Chung
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, United States
| | - Seungtaek Choi
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, United States
| | - Neil Hughes
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, United States
| | - Yao Ding
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, United States
| | - Jinzhong Yang
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, United States
| | - Sastry Vedam
- Department of Radiation Oncology, University of Maryland, Baltimore, United States
| | - Sunil Krishnan
- Department of Radiation Oncology, Mayo Clinic, Jacksonville, United States
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6
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Neylon J, Cook KA, Yang Y, Du D, Sheng K, Chin RK, Kishan AU, Lamb JM, Low DA, Cao M. Clinical assessment of geometric distortion for a 0.35T MR-guided radiotherapy system. J Appl Clin Med Phys 2021; 22:303-309. [PMID: 34231963 PMCID: PMC8364259 DOI: 10.1002/acm2.13340] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Purpose To estimate the overall spatial distortion on clinical patient images for a 0.35 T MR‐guided radiotherapy system. Methods Ten patients with head‐and‐neck cancer underwent CT and MR simulations with identical immobilization. The MR images underwent the standard systematic distortion correction post‐processing. The images were rigidly registered and landmark‐based analysis was performed by an anatomical expert. Distortion was quantified using Euclidean distance between each landmark pair and tagged by tissue interface: bone‐tissue, soft tissue, or air‐tissue. For baseline comparisons, an anthropomorphic phantom was imaged and analyzed. Results The average spatial discrepancy between CT and MR landmarks was 1.15 ± 1.14 mm for the phantom and 1.46 ± 1.78 mm for patients. The error histogram peaked at 0–1 mm. 66% of the discrepancies were <2 mm and 51% <1 mm. In the patient data, statistically significant differences (p‐values < 0.0001) were found between the different tissue interfaces with averages of 0.88 ± 1.24 mm, 2.01 ± 2.20 mm, and 1.41 ± 1.56 mm for the air/tissue, bone/tissue, and soft tissue, respectively. The distortion generally correlated with the in‐plane radial distance from the image center along the longitudinal axis of the MR. Conclusion Spatial distortion remains in the MR images after systematic distortion corrections. Although the average errors were relatively small, large distortions observed at bone/tissue interfaces emphasize the need for quantitative methods for assessing and correcting patient‐specific spatial distortions.
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Affiliation(s)
- John Neylon
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Kiri A Cook
- Department of Radiation Medicine, Oregon Health & Science University, Oregon, Portland, OR, USA
| | - Yingli Yang
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Dongsu Du
- Department of Radiation Oncology, City of Hope Cancer Center, Los Angeles, CA, USA
| | - Ke Sheng
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Robert K Chin
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Amar U Kishan
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - James M Lamb
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Daniel A Low
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Minsong Cao
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
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Evaluation of the influence of susceptibility-induced magnetic field distortions on the precision of contouring intracranial organs at risk for stereotactic radiosurgery. Phys Imaging Radiat Oncol 2021; 15:91-97. [PMID: 33458332 PMCID: PMC7807629 DOI: 10.1016/j.phro.2020.08.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 07/31/2020] [Accepted: 08/03/2020] [Indexed: 11/23/2022] Open
Abstract
45 data sets (18 on a 1.5 T MR and 27 on a 3 T MR) were evaluated for susceptibility induced distortions. Maximum distortions of up to 1.7 mm were found for organs at risk in standard diagnostic settings. Median distortions ranged between 0.1 and 0.2 mm for all organs at risk. Active shimming was estimated to reduce distortions by a factor of 2.3 to 2.9. A safety margin of 1 mm would have encompassed 99.8% of the distortions.
Background and purpose Magnetic resonance imaging (MRI) is a crucial factor in optimal treatment planning for stereotactic radiosurgery. To further the awareness of possible errors in MRI, this work aimed to investigate the magnitude of susceptibility induced MRI distortions for intracranial organs at risk (OARs) and test the effectiveness of actively shimming these distortions. Materials and methods Distortion maps for 45 exams of 42 patients (18 on a 1.5 T MRI scanner, 27 on a 3 T MRI scanner) were calculated based on a high-bandwidth double-echo gradient echo sequence. The investigated OARs were brainstem, chiasm, eyes, and optic nerves. The influence of active shimming was investigated by comparing unshimmed 1.5 T data with shimmed 3 T data and comparing the results to a model based prediction. Results The median distortion for the different OARs was found to be between 0.13 and 0.18 mm for 1.5 T and between 0.11 and 0.13 mm for 3 T. The maximum distortion was found to be between 1.3 and 1.7 mm for 1.5 T and between 1.1 and 1.4 mm for 3 T. The variation of values was much higher for 1.5 T than for 3 T across all investigated OARs. Active shimming was found to reduce distortions by a factor of 2.3 to 2.9 compared to the expected values. Conclusions Using a safety margin for OARs of 1 mm would have encompassed 99.8% of the distortions. Since distortions are inversely proportional to the readout bandwidth, they can be further reduced by increasing the bandwidth. Additional error sources like gradient nonlinearities need to be addressed separately.
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Gundog M, Basaran H, Dogan S, Abdulrezzak U. MR-guided simulation is superior than FDG/PET-guided simulation for local control in nasopharyngeal cancer patients treated with intensity-modulated radiotherapy. Asia Pac J Clin Oncol 2020; 17:43-51. [PMID: 32779400 DOI: 10.1111/ajco.13400] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Accepted: 05/21/2020] [Indexed: 11/29/2022]
Abstract
BACKGROUND MRI and PET/CT scans are the main supportive methods for nasopharyngeal cancer (NPC) for staging and planning. The aim of this study is to compare MRI and PET/CT scanning in terms of survival in patients with NPC who had MRI or PET/CT-simulated radiotherapy planning. METHODS Pathological diagnosed nonkeratinized undifferentiated type and stage II-IVA 91 NPC patients with treated intensity-modulated radiotherapy plus chemotherapy were scanned. The patients were immobilized by a customized thermoplastic mask for fusion images both MRI scans and PET/CT scans. CTVs were created via MR-guided simulation and PET/CT-guided simulation. RESULTS PET/CT-guided simulation was performed with 44 patients (56.4%) and MR-guided simulation was performed with 34 patients (43.6%). Local recurrence-free survival (LRFS) of patients was 68.1 months. LRFS of patients with PET/CT-guided simulation was 59.9, while LRFS of patients with MR-guided was 66.9 months. There was a statistically significant difference between groups (P = .03). In the subgroup analyses, the patients were assessed by dividing into the three groups for the T1-T2 stage, T-3 stage, and T-4 stage. In the patients with T1-T2 stage, 5-year LRFS rates were found %74.4 for PET/CT-guided simulation and %83.3 for MR-guided simulation. There was no statistically significant difference between groups (P = .33). In the patients with T-3 stage, 5-year LRFS rates were found %55.6 for PET/CT-guided simulation and %83.3 for MR-guided simulation. There was not a statistically significant difference between groups (P = .59). In the patients with T-4 stage, 5-year LRFS rates were found %42.2 for PET/CT-guided simulation and %85.1 for MR-guided simulation. The difference between groups was found to be statistically significant (P = .04). CONCLUSION In this study, we founded that MR-guided simulation has better than PET/CT-guided simulation for LRFS.
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Affiliation(s)
- Mete Gundog
- Medicine Faculty, Department of Radiation Oncology, Erciyes University, Kayseri, Turkey
| | - Hatice Basaran
- Medicine Faculty, Department of Radiation Oncology, Erciyes University, Kayseri, Turkey
| | - Serap Dogan
- Department of Radiology, Erciyes University, Kayseri, Turkey
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Radiomic biomarkers for head and neck squamous cell carcinoma. Strahlenther Onkol 2020; 196:868-878. [PMID: 32495038 DOI: 10.1007/s00066-020-01638-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 05/13/2020] [Indexed: 12/22/2022]
Abstract
Tumor heterogeneity is a well-known prognostic factor in head and neck squamous cell carcinoma (HNSCC). A major limitation of tissue- and blood-derived tumor markers is the lack of spatial resolution to image tumor heterogeneity. Tissue markers derived from tumor biopsies usually represent only a small tumor subregion at a single timepoint and are therefore often not representative of the tumors' biology or the biological alterations during and after treatment. Similarly, liquid biopsies give an overall picture of the tumors' secreted factors but completely lack any spatial resolution. Radiomics has the potential to give complete three-dimensional information about the tumor. We conducted a comprehensive literature search to assess the correlation of radiomics to tumor biology and treatment outcome in HNSCC and to assess current limitations of the radiomic biomarkers. In total, 25 studies that explored the ability of radiomics to predict tumor biology and phenotype in HNSCC and 28 studies that explored radiomics to predict post-treatment events were identified. Out of these 53 studies, only three failed to show a significant correlation. The major technical challenges are currently artifacts due to metal implants, non-standardized contrast injection, and delineation uncertainties. All studies to date were retrospective and none of the above-mentioned radiomics signatures have been validated in an independent cohort using an independent software implementation, which shows that transferability due to the numerous technical challenges is currently a major limitation. However, radiomics is a very young field and these studies hopefully pave the way for clinical implementation of radiomics for HNSCC in the future.
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Kiser KJ, Smith BD, Wang J, Fuller CD. "Après Mois, Le Déluge": Preparing for the Coming Data Flood in the MRI-Guided Radiotherapy Era. Front Oncol 2019; 9:983. [PMID: 31632914 PMCID: PMC6779062 DOI: 10.3389/fonc.2019.00983] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Accepted: 09/16/2019] [Indexed: 12/17/2022] Open
Abstract
Magnetic resonance imaging provides a sea of quantitative and semi-quantitative data. While radiation oncologists already navigate a pool of clinical (semantic) and imaging data, the tide will swell with the advent of hybrid MRI/linear accelerator devices and increasing interest in MRI-guided radiotherapy (MRIgRT), including adaptive MRIgRT. The variety of MR sequences (of greater complexity than the single parameter Hounsfield unit of CT scanning routinely used in radiotherapy), the workflow of adaptive fractionation, and the sheer quantity of daily images acquired are challenges for scaling this technology. Biomedical informatics, which is the science of information in biomedicine, can provide helpful insights for this looming transition. Funneling MRIgRT data into clinically meaningful information streams requires committing to the flow of inter-institutional data accessibility and interoperability initiatives, standardizing MRIgRT dosimetry methods, streamlining MR linear accelerator workflow, and standardizing MRI acquisition and post-processing. This review will attempt to conceptually ford these topics using clinical informatics approaches as a theoretical bridge.
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Affiliation(s)
- Kendall J Kiser
- John P. and Kathrine G. McGovern Medical School, University of Texas Health Science Center, Houston, TX, United States.,School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, United States.,Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Benjamin D Smith
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jihong Wang
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Clifton D Fuller
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, United States
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Kiser K, Meheissen MA, Mohamed AS, Kamal M, Ng SP, Elhalawani H, Jethanandani A, He R, Ding Y, Rostom Y, Hegazy N, Bahig H, Garden A, Lai S, Phan J, Gunn GB, Rosenthal D, Frank S, Brock KK, Wang J, Fuller CD. Prospective quantitative quality assurance and deformation estimation of MRI-CT image registration in simulation of head and neck radiotherapy patients. Clin Transl Radiat Oncol 2019; 18:120-127. [PMID: 31341987 PMCID: PMC6630195 DOI: 10.1016/j.ctro.2019.04.018] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 04/19/2019] [Accepted: 04/22/2019] [Indexed: 11/23/2022] Open
Abstract
MRI-CT deformable image registration was not superior to rigid registration. Dice similarity coefficients were 0.65, 0.62, and 0.63 for deformable registrations. Dice similarity coefficient was 0.63 for rigid registration. Registration quality was superior in muscle and gland compared to bone and vessel.
Background MRI-guided radiotherapy planning (MRIgRT) may be superior to CT-guided planning in some instances owing to its improved soft tissue contrast. However, MR images do not communicate tissue electron density information necessary for dose calculation and therefore must either be co-registered to CT or algorithmically converted to synthetic CT. No robust quality assessment of commercially available MR-CT registration algorithms is yet available; thus we sought to quantify MR-CT registration formally. Methods Head and neck non-contrast CT and T2 MRI scans acquired with standard treatment immobilization techniques were prospectively acquired from 15 patients. Per scan, 35 anatomic regions of interest (ROIs) were manually segmented. MRIs were registered to CT rigidly (RIR) and by three commercially available deformable registration algorithms (DIR). Dice similarity coefficient (DSC), Hausdorff distance mean (HD mean) and Hausdorff distance max (HD max) metrics were calculated to assess concordance between MRI and CT segmentations. Each DIR algorithm was compared to DIR using the nonparametric Steel test with control for individual ROIs (n = 105 tests) and for all ROIs in aggregate (n = 3 tests). The influence of tissue type on registration fidelity was assessed using nonparametric Wilcoxon pairwise tests between ROIs grouped by tissue type (n = 12 tests). Bonferroni corrections were applied for multiple comparisons. Results No DIR algorithm improved the segmentation quality over RIR for any ROI nor all ROIs in aggregate (all p values >0.05). Muscle and gland ROIs were significantly more concordant than vessel and bone, but DIR remained non-different from RIR. Conclusions For MR-CT co-registration, our results question the utility and applicability of commercially available DIR over RIR alone. The poor overall performance also questions the feasibility of translating tissue electron density information to MRI by CT registration, rather than addressing this need with synthetic CT generation or bulk-density assignment.
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Key Words
- CT, computed tomography
- CT-MRI image registration
- DICOM, digital imaging and communications in medicine
- DIR, deformable image registration
- DSC, dice similarity coefficient
- Deformable image registration
- HD max, Hausdorff maximum distance
- HD mean, Hausdorff mean distance
- HNC, head and neck cancer
- HPV, human papillomavirus
- HU, Hounsfield units
- IMRT, intensity-modulated radiation therapy
- MAE, mean absolute error
- MRI, magnetic resonance imaging
- MRI-guided radiotherapy
- MRIgRT, MRI-guided radiotherapy planning
- MRL, MRI linear accelerator
- OAR, organ(s) at risk
- Quality assessment
- RIR, rigid image registration
- RT, radiation therapy
- Rigid image registration
- sCT, synthetic computed tomography
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Affiliation(s)
| | - Kendall Kiser
- University of Texas, John P. and Kathrine G. McGovern Medical School, 6431 Fannin Street, Houston, TX 77030, USA
- UT Health School of Biomedical Informatics, 7000 Fannin Street, Suite 600, Houston, TX 77030, USA
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Mohamed A.M. Meheissen
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
- Department of Clinical Oncology and Nuclear Medicine, Faculty of Medicine, University of Alexandria, 17 Champilion Street, Alazarita, Alexandria, Egypt
| | - Abdallah S.R. Mohamed
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
- Department of Clinical Oncology and Nuclear Medicine, Faculty of Medicine, University of Alexandria, 17 Champilion Street, Alazarita, Alexandria, Egypt
- MD Anderson Cancer Center/UT Health Graduate School of Biomedical Sciences, 6767 Bertner Avenue, Houston, TX 77030, USA
| | - Mona Kamal
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
- Department of Clinical Oncology and Nuclear Medicine, Faculty of Medicine, University of Ain Shams, Lofty El-Said Street, 1156 Cairo, Egypt
| | - Sweet Ping Ng
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
- Department of Radiation Oncolog, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000, Australia
| | - Hesham Elhalawani
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Amit Jethanandani
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
- College of Medicine, University of Tennessee Health Science Center, 910 Madison Avenue #1002, Memphis, TN 38103, USA
| | - Renjie He
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Yao Ding
- Department of Radiation Physics, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Yousri Rostom
- Department of Clinical Oncology and Nuclear Medicine, Faculty of Medicine, University of Alexandria, 17 Champilion Street, Alazarita, Alexandria, Egypt
| | - Neamat Hegazy
- Department of Clinical Oncology and Nuclear Medicine, Faculty of Medicine, University of Alexandria, 17 Champilion Street, Alazarita, Alexandria, Egypt
| | - Houda Bahig
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
- Department of Radiation Oncology, Centre Hospitalier de l’Universite de Montreal, 1051 Rue Sanguinet, Montreal, QC H2X 3E4, Canada
| | - Adam Garden
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Stephen Lai
- Department of Head and Neck Surgery, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX, 77030, USA
| | - Jack Phan
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Gary B. Gunn
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - David Rosenthal
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Steven Frank
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Kristy K. Brock
- Department of Radiation Physics, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
- Department of Imaging Physics, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Jihong Wang
- Department of Radiation Physics, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Clifton D. Fuller
- Department of Radiation Oncology, the University of Texas MD Anderson Cancer Center, The MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
- Corresponding author.
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Adjeiwaah M, Bylund M, Lundman JA, Söderström K, Zackrisson B, Jonsson JH, Garpebring A, Nyholm T. Dosimetric Impact of MRI Distortions: A Study on Head and Neck Cancers. Int J Radiat Oncol Biol Phys 2018; 103:994-1003. [PMID: 30496879 DOI: 10.1016/j.ijrobp.2018.11.037] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Revised: 11/13/2018] [Accepted: 11/19/2018] [Indexed: 10/27/2022]
Abstract
PURPOSE To evaluate the effect of magnetic resonance (MR) imaging (MRI) geometric distortions on head and neck radiation therapy treatment planning (RTP) for an MRI-only RTP. We also assessed the potential benefits of patient-specific shimming to reduce the magnitude of MR distortions for a 3-T scanner. METHODS AND MATERIALS Using an in-house Matlab algorithm, shimming within entire imaging volumes and user-defined regions of interest were simulated. We deformed 21 patient computed tomography (CT) images with MR distortion fields (gradient nonlinearity and patient-induced susceptibility effects) to create distorted CT (dCT) images using bandwidths of 122 and 488 Hz/mm at 3 T. Field parameters from volumetric modulated arc therapy plans initially optimized on dCT data sets were transferred to CT data to compute a new plan. Both plans were compared to determine the impact of distortions on dose distributions. RESULTS Shimming across entire patient volumes decreased the percentage of voxels with distortions of more than 2 mm from 15.4% to 2.0%. Using the user-defined region of interest (ROI) shimming strategy, (here the Planning target volume (PTV) was the chosen ROI volume) led to increased geometric for volumes outside the PTV, as such voxels within the spinal cord with geometric shifts above 2 mm increased from 11.5% to 32.3%. The worst phantom-measured residual system distortions after 3-dimensional gradient nonlinearity correction within a radial distance of 200 mm from the isocenter was 2.17 mm. For all patients, voxels with distortion shifts of more than 2 mm resulting from patient-induced susceptibility effects were 15.4% and 0.0% using bandwidths of 122 Hz/mm and 488 Hz/mm at 3 T. Dose differences between dCT and CT treatment plans in D50 at the planning target volume were 0.4% ± 0.6% and 0.3% ± 0.5% at 122 and 488 Hz/mm, respectively. CONCLUSIONS The overall effect of MRI geometric distortions on data used for RTP was minimal. Shimming over entire imaging volumes decreased distortions, but user-defined subvolume shimming introduced significant errors in nearby organs and should probably be avoided.
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Affiliation(s)
- Mary Adjeiwaah
- Department of Radiation Sciences, Umeå University, Umeå, Sweden.
| | - Mikael Bylund
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Josef A Lundman
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | | | | | | | | | - Tufve Nyholm
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
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