Prospective Evaluation of In Vivo and Phantom Repeatability and Reproducibility of Diffusion-Weighted MRI Sequences on 1.5T MRI-Linear Accelerator (MR-Linac) and MR Simulator Devices for Head and Neck Cancers
McDonald, Brigid A; Salzillo, Travis; Mulder, Samuel; Ahmed, Sara; Dresner, Alex; Preston, Kathryn; He, Renjie; Christodouleas, John; S R Mohamed, Abdallah; Philippens, Marielle; van Houdt, Petra; Thorwarth, Daniela; Wang, Jihong; Shukla Dave, Amita; Boss, Michael; Fuller, Clifton D
(2023) Radiotherapy & Oncology, volume 185
(Article)
Abstract
INTRODUCTION: Diffusion-weighted imaging (DWI) on MRI-linear accelerator (MR-linac) systems can potentially be used for monitoring treatment response and adaptive radiotherapy in head and neck cancers (HNC) but requires extensive validation. We performed technical validation to compare six total DWI sequences on an MR-linac and MR simulator (MR sim) in patients,
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volunteers, and phantoms. METHODS: Ten human papillomavirus-positive oropharyngeal cancer patients and ten healthy volunteers underwent DWI on a 1.5T MR-linac with three DWI sequences: echo planar imaging (EPI), split acquisition of fast spin echo signals (SPLICE), and turbo spin echo (TSE). Volunteers were also imaged on a 1.5T MR sim with three sequences: EPI, BLADE (vendor tradename), and readout segmentation of long variable echo trains (RESOLVE). Participants underwent two scan sessions per device and two repeats of each sequence per session. Repeatability and reproducibility within-subject coefficient of variation (wCV) of mean ADC were calculated for tumors and lymph nodes (patients) and parotid glands (volunteers). ADC bias, repeatability/reproducibility metrics, SNR, and geometric distortion were quantified using a phantom. RESULTS: In vivo repeatability/reproducibility wCV for parotids were 5.41%/6.72%, 3.83%/8.80%, 5.66%/10.03%, 3.44%/5.70%, 5.04%/5.66%, 4.23%/7.36% for EPI MR-linac, SPLICE, TSE, EPI MR sim, BLADE, RESOLVE. Repeatability/reproducibility wCV for EPI MR-linac, SPLICE, TSE were 9.64%/10.28%, 7.84%/8.96%, 7.60%/11.68% for tumors and 7.80%/9.95%, 7.23%/8.48%, 10.82%/10.44% for nodes. All sequences except TSE had phantom ADC biases within ±0.1x10 -3 mm 2/s for most vials (EPI MR-linac, SPLICE, and BLADE had 2, 3, and 1 vials out of 13 with larger biases, respectively). SNR of b=0 images was 87.3, 180.5, 161.3, 171.0, 171.9, 130.2 for EPI MR-linac, SPLICE, TSE, EPI MR sim, BLADE, RESOLVE. CONCLUSION: MR-linac DWI sequences demonstrated near-comparable performance to MR sim sequences and warrant further clinical validation for treatment response assessment in HNC.
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Keywords: Apparent diffusion coefficient, Diffusion-weighted Imaging, Magnetic resonance imaging, MR-guided radiation therapy, MR-Linac, Repeatability and reproducibility, Test-retest, Hematology, Oncology, Radiology Nuclear Medicine and imaging, Journal Article
ISSN: 0167-8140
Publisher: Elsevier Ireland Ltd
Note: Funding Information: The authors would like to acknowledge the following funding sources: B.A. McDonald has The authors would like to acknowledge the following funding sources: B.A. McDonald has received research and training support through a Ruth L. Kirschstein fellowship from NIH/NIDCR (1F31DE029093), a Dr. John J. Kopchick Fellowship from The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, and an Image-Guided Cancer Therapy T32 Fellowship from MD Anderson Cancer Center and NIH/National Cancer Institute. C.D. Fuller and J. Christodouleas receive research support from an academic-industrial partnership R01 grant from the National Institutes of Health (NIH)/National Institute of Dental and Craniofacial Research (NIDCR) (R01DE028290) directly related to this project. C.D. Fuller has received industry research support from Elekta AB. C.D. Fuller reports additional grants from NIH/National Cancer Institute (R01CA218148, 1R01CA225190, 1R01CA214825, P30CA016672, P50CA097007-10), NIH/NIDCR (1R01DE025248/R56DE025248), NIH/National Institute of Biomedical Imaging and Bioengineering (R25EB025787), Patient-centered Outcomes Research Institute (PCS-1609-36195), Sister Institute Network Fund (MD Anderson), and National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation (CMMI 1933369), outside of the scope of the current project. T.C. Salzillo is supported by The University of Texas Health Science Center at Houston Center for Clinical and Translational Sciences TL1 Program (TL1TR003169) Funding Information: The authors would like to acknowledge the following funding sources: B.A. McDonald has The authors would like to acknowledge the following funding sources: B.A. McDonald has received research and training support through a Ruth L. Kirschstein fellowship from NIH/NIDCR (1F31DE029093), a Dr. John J. Kopchick Fellowship from The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, and an Image-Guided Cancer Therapy T32 Fellowship from MD Anderson Cancer Center and NIH/National Cancer Institute. C.D. Fuller and J. Christodouleas receive research support from an academic-industrial partnership R01 grant from the National Institutes of Health (NIH)/National Institute of Dental and Craniofacial Research (NIDCR) (R01DE028290) directly related to this project. C.D. Fuller has received industry research support from Elekta AB. C.D. Fuller reports additional grants from NIH/National Cancer Institute (R01CA218148, 1R01CA225190, 1R01CA214825, P30CA016672, P50CA097007-10), NIH/NIDCR (1R01DE025248/R56DE025248), NIH/National Institute of Biomedical Imaging and Bioengineering (R25EB025787), Patient-centered Outcomes Research Institute (PCS-1609-36195), Sister Institute Network Fund (MD Anderson), and National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation (CMMI 1933369), outside of the scope of the current project. T.C. Salzillo is supported by The University of Texas Health Science Center at Houston Center for Clinical and Translational Sciences TL1 Program (TL1TR003169) Publisher Copyright: © 2023 The Authors
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