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Cao Y, Davarani SN, You D, Feiweier T, Casper K, Balis U, Udager A, Balter J, Mierzwa M. In Vivo Microstructure Imaging in Oropharyngeal Squamous Cell Carcinoma Using the Random Walk With Barriers Model. J Magn Reson Imaging 2024; 59:929-938. [PMID: 37366349 DOI: 10.1002/jmri.28831] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 05/16/2023] [Accepted: 05/18/2023] [Indexed: 06/28/2023] Open
Abstract
BACKGROUND Apparent diffusion coefficient is not specifically sensitive to tumor microstructure and therapy-induced cellular changes. PURPOSE To investigate time-dependent diffusion imaging with the short-time-limit random walk with barriers model (STL-RWBM) for quantifying microstructure parameters and early cancer cellular response to therapy. STUDY TYPE Prospective. POPULATION Twenty-seven patients (median age of 58 years and 7.4% of females) with p16+/p16- oropharyngeal/oral cavity squamous cell carcinomas (OPSCC/OCSCC) underwent MRI scans before therapy, of which 16 patients had second scans at 2 weeks of the 7-weeks chemoradiation therapy (CRT). FIELD STRENGTH/SEQUENCE 3-T, diffusion sequence with oscillating gradient spine echo (OGSE) and pulse gradient spin echo (PGSE). ASSESSMENT Diffusion weighted images were acquired using OGSE and PGSE. Effective diffusion times were derived for the STL-RWBM to estimate free diffusion coefficient D0 , volume-to-surface area ratio of cellular membranes V/S, and cell membrane permeability κ. Mean values of these parameters were calculated in tumor volumes. STATISTICAL TESTS Tumor microstructure parameters were compared with clinical stages of p16+ I-II OPSCC, p16+ III OPSCC, and p16- IV OCSCC by Spearman's rank correlation and with digital pathological analysis of a resected tissue sample. Tumor microstructure parameter responses during CRT in the 16 patients were assessed by paired t-tests. A P-value of <0.05 was considered statistically significant. RESULTS The derived effective diffusion times affected estimated values of V/S and κ by 40%. The tumor V/S values were significantly correlated with clinical stages (r = 0.47) as an increase from low to high clinical stages. The in vivo estimated cell size agreed with one from pathological analysis of a tissue sample. Early tumor cellular responses showed a significant increase in D0 (14%, P = 0.03) and non-significant increases in κ (56%, P = 0.6) and V/S (10%, P = 0.1). DATA CONCLUSION Effective diffusion time estimation might impact microstructure parameter estimation. The tumor V/S was correlated with OPSCC/OCSCC clinical stages. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Yue Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Daekeun You
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Keith Casper
- Department of Otolaryngology, University of Michigan, Ann Arbor, Michigan, USA
| | - Ulysses Balis
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Aaron Udager
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - James Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Michelle Mierzwa
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
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Yoo Y, Gibson E, Zhao G, Sandu A, Re T, Das J, Hesheng W, Kim MM, Shen C, Lee YZ, Kondziolka D, Ibrahim M, Lian J, Jain R, Zhu T, Parmar H, Comaniciu D, Balter J, Cao Y. An Automated Brain Metastasis Detection and Segmentation System from MRI with a Large Multi-Institutional Dataset. Int J Radiat Oncol Biol Phys 2023; 117:S88-S89. [PMID: 37784596 DOI: 10.1016/j.ijrobp.2023.06.414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Developments of automated systems for brain metastasis (BM) detection and segmentation from MRI for assisting early detection and stereotactic radiosurgery (SRS) have been reported but most based upon relatively small datasets from single institutes. This work aims to develop and evaluate a system using a large multi-institutional dataset, and to improve both identification of small/subtle BMs and segmentation accuracy of large BMs. MATERIALS/METHODS A 3D U-Net system was trained and evaluated to detect and segment intraparenchymal BMs with a size > 2mm using 1856 MRI volumes from 1791 patients treated with SRS from seven institutions (1539 volumes for training, 183 for validation, and 134 for testing). All patients had 3D post-Gd T1w MRI scans pre-SRS. Gross tumor volumes (GTVs) of BMs for SRS were curated by each institute first. Then, additional efforts were spent to create GTVs for the untreated and/or uncontoured BMs, including central reviews by two radiologists, to improve accuracy of ground truth. The training dataset was augmented with synthetic BMs of 3773 MRIs using a 3D generative pipeline. Our system consists of two U-Nets with one using small 3D patches dedicated for detecting small BMs and another using large 3D patches for segmenting large BMs, and a random-forest based fusion module for combining the two network outputs. The first U-Net was trained with 3D patches containing at least one BM < 0.1 cm3. For detection performance, we measured BM-level sensitivity and case-level false-positive (FP) rate. For segmentation performance, we measured BM-level Dice similarity coefficient (DSC) and 95-percentile Hausdorff distance (HD95). We also stratified performances based upon BM sizes. RESULTS For 739 BMs in the 134 testing cases, the overall lesion-level sensitivity was 0.870 with an average case-level FP of 1.34±1.92 (95% CI: 1.02-1.67). The sensitivity was >0.969 for the BMs >0.1 cm3, but dropped to 0.755 for the BMs < 0.1 cm3 (Table 1). The average DSC and HD95 for all detected BMs were 0.786 and 1.35mm. The worse performance for BMs > 20 cm3 was caused by a case with 83 cm3 GTV and artifacts in the MRI volume. CONCLUSION We achieved excellent detection sensitivity and segmentation accuracy for BMs > 0.1 cm3, and promising performance for small BMs (<0.1cm3) with a controlled FP rate using a large multi-institutional dataset. Clinical utility for assisting early detection and SRS planning will be investigated. Table 1: Per-lesion detection and segmentation performance stratified by individual BM size. N is the number of BMs in each category.
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Affiliation(s)
- Y Yoo
- Siemens Healthineers, Princeton, NJ
| | - E Gibson
- Siemens Healthineers, Princeton, NJ
| | - G Zhao
- Siemens Healthineers, Princeton, NJ
| | - A Sandu
- Siemens Healthineers, Princeton, NJ
| | - T Re
- Siemens Healthineers, Princeton, NJ
| | - J Das
- Siemens Healthineers, Princeton, NJ
| | | | - M M Kim
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - C Shen
- Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
| | - Y Z Lee
- University of North Carolina, Chapel Hill, NC
| | - D Kondziolka
- Department of Neurosurgery, NYU Langone Health, New York, NY
| | - M Ibrahim
- University of Michigan, Ann Arbor, MI
| | - J Lian
- University of North Carolina, Chapel Hill, NC
| | - R Jain
- New York University, New York, NY
| | - T Zhu
- Washington University, St. Louis, MO
| | - H Parmar
- Department of Radiology, University of Michigan, Ann Arbor, MI
| | | | - J Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - Y Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
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Liu L, Shen L, Johansson A, Cao Y, Balter J, Vitzthum L, Xing L. Real Time Volumetric MRI for MR-Guided 3D Motion Tracking via Sparse Prior-Augmented Neural Representation Learning. Int J Radiat Oncol Biol Phys 2023; 117:S47-S48. [PMID: 37784506 DOI: 10.1016/j.ijrobp.2023.06.327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To reconstruct volumetric MRI from orthogonal cine acquisition aided by sparse priors of 2 static 3D MRI through implicit neural representation (NeRP) learning, with the goal of eliminating large-scale training datasets for data-driven sparse MRI reconstruction and supporting clinical workflow of real time 3D motion tracking during MR-guided radiotherapy. MATERIALS/METHODS A multi-layer perceptron network was trained to learn the NeRP of a patient-specific MRI dataset, where the network takes 4D data coordinates of voxel locations and motion states as inputs and outputs corresponding voxel intensities. By first learning the NeRP of 2 static 3D MRI with different breathing motion states, prior knowledge of patient breathing motion was embedded into network weights through optimization. The prior knowledge was then augmented from 2 to 31 motion states by querying the optimized network at interpolated/extrapolated motion state coordinates. Starting from the prior-augmented network as an initialization point, the network was further trained using sparse samples of 2 orthogonal cine slices. The final volumetric reconstruction was obtained by querying the trained network at desired 3D spatial locations. We evaluated the proposed method using 5-minute volumetric MRI time series with 340 ms temporal resolution collected from 7 liver carcinoma patients. The time series was acquired using golden-angle radial MRI sequence and reconstructed through retrospective sorting. Two MRI with inhale and exhale states respectively were selected from the first 30 sec of the time series for prior embedding and augmentation. The remaining 4.5-min time series was used for volumetric reconstruction evaluation, where we retrospectively subsampled each MRI to 2 orthogonal slices and compared network-reconstructed images to ground truth images in terms of image quality and the capability of supporting 3D target motion tracking. RESULTS Across the 7 patients evaluated, the peak signal to noise ratio between model reconstruction and ground truth was 54.66 ± 6.16 dB and the structural similarity index measure was 0.99 ± 0.01. Gross tumor volume (GTV) contours estimated by deforming a reference state MRI to model-reconstructed and ground truth MRI showed good consistency. The 95-percentile Hausdorff distance between GTV contours was 1.89 ± 1.13 mm, which is less than the voxel dimension. The mean GTV centroid position difference between ground truth and model estimation was less than 1 mm in all 3 orthogonal directions. CONCLUSION Volumetric MRI from orthogonal cine acquisition with sparse priors is feasible by modeling prior knowledge through implicit neural representation learning. The model-reconstructed images showed sufficient accuracy in supporting 3D motion tracking of abdominal targets. By eliminating the need for large scale training datasets, the method promises to enable clinical implementation of 3D motion tracking for precision radiation therapy.
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Affiliation(s)
- L Liu
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - L Shen
- Harvard Medical School, Boston, MA
| | | | - Y Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - J Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - L Vitzthum
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - L Xing
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
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Zhang Y, Balter J, Dow J, Cao Y, Lawrence TS, Kashani R. Development of an abdominal dose accumulation tool and assessments of accumulated dose in gastrointestinal organs. Phys Med Biol 2023; 68:10.1088/1361-6560/acbc61. [PMID: 36791470 PMCID: PMC10131348 DOI: 10.1088/1361-6560/acbc61] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [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: 08/01/2022] [Accepted: 02/15/2023] [Indexed: 02/17/2023]
Abstract
Objective.Online adaptive radiotherapy has demonstrated improved dose conformality in response to inter-fraction geometric variations in the abdomen. The dosimetric impact of intra-fractional variations in anatomic configuration resulting from breathing, gastric contraction and slow configuration motion, however, have been largely ignored, leading to differences between delivered and planned. To investigate the impact of intra-fractional abdominal motions on delivered dose, anatomical deformations due to these three motion modes were extracted from dynamic MRI data using a previously developed hierarchical motion modeling methodology.Approach. Motion magnitudes were extracted from deformation fields between a reference state and all other motion states of the patient. Delivered dose estimates to various gastrointestinal organs (stomach, duodenum, small bowel and colon) were calculated on each motion state of the patient and accumulated to estimate the delivered dose to each organ for the entire treatment fraction.Main results. Across a sample of 10 patients, maximal motions of 33.6, 33.4, 47.6 and 49.2 mm were observed over 20 min for the stomach, duodenum, small bowel and colon respectively. Dose accumulation results showed that motions could lead to average increases of 2.0, 2.1, 1.1, 0.7 Gy to the maximum dose to 0.5cc (D0.5cc) and 3.0, 2.5, 1.3, 0.9 Gy to the maximum dose to 0.1cc (D0.1cc) for these organs at risk. From the 40 dose accumulations performed (10 for each organ at risk), 27 showed increases of modeled delivered dose compared to planned doses, 4 of which exceeded planned dose constraints.Significance. The use of intra-fraction motion measurements to accumulate delivered doses is feasible, and supports retrospective estimation of dose delivery to improve estimates of delivered doses, and further guide strategies for both plan adaptation as well as advances in intra-fraction motion management.
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Affiliation(s)
- Yuhang Zhang
- Department of Radiation Oncology, University of Michigan, United States of America
- Department of Biomedical Engineering, University of Michigan, United States of America
| | - James Balter
- Department of Radiation Oncology, University of Michigan, United States of America
- Department of Biomedical Engineering, University of Michigan, United States of America
| | - Janell Dow
- Department of Radiation Oncology, University of Michigan, United States of America
| | - Yue Cao
- Department of Radiation Oncology, University of Michigan, United States of America
- Department of Biomedical Engineering, University of Michigan, United States of America
- Department of Radiology, University of Michigan, United States of America
| | - Theodore S Lawrence
- Department of Radiation Oncology, University of Michigan, United States of America
| | - Rojano Kashani
- Department of Radiation Oncology, University Hospitals Seidman Cancer Center, United States of America
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Speers C, Murthy VL, Walker EM, Glide-Hurst CK, Marsh R, Tang M, Morris EL, Schipper MJ, Weinberg RL, Gits HC, Hayman J, Feng M, Balter J, Moran J, Jagsi R, Pierce LJ. Cardiac Magnetic Resonance Imaging and Blood Biomarkers for Evaluation of Radiation-Induced Cardiotoxicity in Patients With Breast Cancer: Results of a Phase 2 Clinical Trial. Int J Radiat Oncol Biol Phys 2021; 112:417-425. [PMID: 34509552 DOI: 10.1016/j.ijrobp.2021.08.039] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 08/23/2021] [Accepted: 08/27/2021] [Indexed: 12/25/2022]
Abstract
PURPOSE Radiation therapy (RT) can increase the risk of cardiac events in patients with breast cancer (BC), but biomarkers predicting risk for developing RT-induced cardiac disease are currently lacking. We report results from a prospective clinical trial evaluating early magnetic resonance imaging (MRI) and serum biomarker changes as predictors of cardiac injury and risk of subsequent cardiac events after RT for left-sided disease. METHODS Women with node-negative and node-positive (N-/+) left-sided BC were enrolled on 2 institutional review board (IRB)-approved protocols at 2 institutions. MRI was conducted pretreatment (within 1 week of starting radiation), at the end of treatment (last day of treatment ±1 week), and 3 months after the last day of treatment (±2 weeks) to quantify left and right ventricular volumes and function, myocardial fibrosis, and edema. Perfusion changes during regadenoson stress perfusion were also assessed on a subset of patients (n = 28). Serum was collected at the same time points. Whole heart and cardiac substructures were contoured using CT and MRI. Models were constructed using baseline cardiac and clinical risk factors. Associations between MRI-measured changes and dose were evaluated. RESULTS Among 51 women enrolled, mean heart dose ranged from 0.80 to 4.7 Gy and mean left ventricular (LV) dose from 1.1 to 8.2 Gy, with mean heart dose 2.0 Gy. T1 time, a marker of fibrosis, and right ventricular (RV) ejection fraction (EF) significantly changed with treatment; these were not dose dependent. T2 (marker of edema) and LV EF did not significantly change. No risk factors were associated with baseline global perfusion. Prior receipt of doxorubicin was marginally associated with decreased myocardial perfusion after RT (P = .059), and mean MHD was not associated with perfusion changes. A significant correlation between baseline IL-6 and mean heart dose (MHD) at the end of RT (ρ 0.44, P = .007) and a strong trend between troponin I and MHD at 3 months post-treatment (ρ 0.33, P = .07) were observed. No other significant correlations were identified. CONCLUSIONS In this prospective study of women with left-sided breast cancer treated with contemporary treatment planning, cardiac radiation doses were very low relative to historical doses reported by Darby et al. Although we observed significant changes in T1 and RV EF shortly after RT, these changes were not correlated with whole heart or substructure doses. Serum biomarker analysis of cardiac injury demonstrates an interesting trend between markers and MHD that warrants further investigation.
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Affiliation(s)
- Corey Speers
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Comprehensive Cancer Center, University of Michigan, Ann Arbor, Michigan
| | - Venkatesh L Murthy
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan; Frankel Cardiovascular Center, University of Michigan, Ann Arbor, Michigan
| | - Eleanor M Walker
- Department of Radiation Oncology, Henry Ford Cancer Institute, Detroit, Michigan
| | - Carri K Glide-Hurst
- Department of Human Oncology, School of Medicine and Public Heath, University of Wisconsin-Madison, Madison, Wisconsin
| | - Robin Marsh
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Ming Tang
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Emily L Morris
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Matthew J Schipper
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Richard L Weinberg
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan; Frankel Cardiovascular Center, University of Michigan, Ann Arbor, Michigan
| | - Hunter C Gits
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota
| | - James Hayman
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Comprehensive Cancer Center, University of Michigan, Ann Arbor, Michigan
| | - Mary Feng
- Department of Radiation Oncology, University of California San Francisco, San Francisco, California
| | - James Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Jean Moran
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Reshma Jagsi
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Comprehensive Cancer Center, University of Michigan, Ann Arbor, Michigan
| | - Lori J Pierce
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Comprehensive Cancer Center, University of Michigan, Ann Arbor, Michigan.
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Glide-Hurst CK, Paulson ES, McGee K, Tyagi N, Hu Y, Balter J, Bayouth J. Task group 284 report: magnetic resonance imaging simulation in radiotherapy: considerations for clinical implementation, optimization, and quality assurance. Med Phys 2021; 48:e636-e670. [PMID: 33386620 DOI: 10.1002/mp.14695] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [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: 06/30/2020] [Revised: 12/12/2020] [Accepted: 12/16/2020] [Indexed: 12/18/2022] Open
Abstract
The use of dedicated magnetic resonance simulation (MR-SIM) platforms in Radiation Oncology has expanded rapidly, introducing new equipment and functionality with the overall goal of improving the accuracy of radiation treatment planning. However, this emerging technology presents a new set of challenges that need to be addressed for safe and effective MR-SIM implementation. The major objectives of this report are to provide recommendations for commercially available MR simulators, including initial equipment selection, siting, acceptance testing, quality assurance, optimization of dedicated radiation therapy specific MR-SIM workflows, patient-specific considerations, safety, and staffing. Major contributions include guidance on motion and distortion management as well as MRI coil configurations to accommodate patients immobilized in the treatment position. Examples of optimized protocols and checklists for QA programs are provided. While the recommendations provided here are minimum requirements, emerging areas and unmet needs are also highlighted for future development.
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Affiliation(s)
- Carri K Glide-Hurst
- Department of Human Oncology, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Eric S Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Kiaran McGee
- Department of Diagnostic Radiology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Neelam Tyagi
- Medical Physics Department, Memorial Sloan-Kettering Cancer Center, New York, NY, 10065, USA
| | - Yanle Hu
- Department of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, 85054, USA
| | - James Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - John Bayouth
- Department of Human Oncology, University of Wisconsin-Madison, Madison, WI, 53792, USA
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Owen D, Sun Y, McFarlane M, Viglianti B, Balter J, El Naqa I, Jolly S, Haken RKT, Kong F, Matuszak M. Investigating the Perfusion SPECT Dose-Function Metrics Associated With RILT Risk in NSCLC Patients Undergoing RT. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.666] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [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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Rosen B, Mierzwa M, Lee C, Wilkie J, Schonewolf C, Shah J, Chapman C, Eisbruch A, Aryal M, Cao Y, Balter J. Dixon-based Magnetic Resonance Imaging for Early Prediction of Patient-Reported Acute Xerostomia following Head and Neck Radiotherapy. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.2187] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Kim M, Sun Y, Aryal M, Parmar H, Piert M, Rosen B, Mayo C, Balter J, Schipper M, Gabel N, Briceño E, You D, Heth J, Al-Holou W, Umemura Y, Leung D, Junck L, Wahl D, Lawrence T, Cao Y. A Phase II Study of Dose-Intensified Chemoradiation Using Biologically-Based Target Volume Definition in Patients with Newly Diagnosed Glioblastoma. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.2105] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [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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Speers C, Murthy V, Walker E, Morris E, Glide-Hurst C, Schipper M, Marsh R, Weinberg R, Gits H, Moran J, Hayman J, Feng M, Griffith K, Balter J, Jagsi R, Pierce L. Cardiac MRI for Evaluation of Radiation-Induced Cardiotoxicity in Breast Cancer Patients: A Phase II Clinical Trial. Int J Radiat Oncol Biol Phys 2019. [DOI: 10.1016/j.ijrobp.2019.06.2398] [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: 10/26/2022]
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Gits H, Vineberg K, Kim M, Balter J. Feasibility of MR-Generated Synthetic CT Images for Planning Stereotactic Radiosurgery of Brain Metastases. Int J Radiat Oncol Biol Phys 2018. [DOI: 10.1016/j.ijrobp.2018.06.261] [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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Owen D, Boonstra P, Viglianti B, Balter J, Schipper M, Jackson W, El Naqa I, Jolly S, Haken RKT, Kong F, Matuszak M. Modeling Patient-Specific Dose-Function Response Using SPECT/CT for Personalized Prediction of Radiation-Induced Lung Toxicity. Int J Radiat Oncol Biol Phys 2018. [DOI: 10.1016/j.ijrobp.2018.06.289] [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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Owen D, Vineberg K, Li P, Cao Y, Johansson A, Cuneo K, Lawrence T, Balter J. Utility of 4DMRI for Liver Radiation Planning. Int J Radiat Oncol Biol Phys 2017. [DOI: 10.1016/j.ijrobp.2017.06.444] [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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Johansson A, Balter J, Cao Y. Rigid-body motion correction of the liver in image reconstruction for golden-angle stack-of-stars DCE MRI. Magn Reson Med 2017; 79:1345-1353. [PMID: 28617993 DOI: 10.1002/mrm.26782] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [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: 11/22/2016] [Revised: 05/16/2017] [Accepted: 05/17/2017] [Indexed: 12/25/2022]
Abstract
PURPOSE Respiratory motion can affect pharmacokinetic perfusion parameters quantified from liver dynamic contrast-enhanced MRI. Image registration can be used to align dynamic images after reconstruction. However, intra-image motion blur remains after alignment and can alter the shape of contrast-agent uptake curves. We introduce a method to correct for inter- and intra-image motion during image reconstruction. METHODS Sixteen liver dynamic contrast-enhanced MRI examinations of nine subjects were performed using a golden-angle stack-of-stars sequence. For each examination, an image time series with high temporal resolution but severe streak artifacts was reconstructed. Images were aligned using region-limited rigid image registration within a region of interest covering the liver. The transformations resulting from alignment were used to correct raw data for motion by modulating and rotating acquired lines in k-space. The corrected data were then reconstructed using view sharing. RESULTS Portal-venous input functions extracted from motion-corrected images had significantly greater peak signal enhancements (mean increase: 16%, t-test, P < 0.001) than those from images aligned using image registration after reconstruction. In addition, portal-venous perfusion maps estimated from motion-corrected images showed fewer artifacts close to the edge of the liver. CONCLUSIONS Motion-corrected image reconstruction restores uptake curves distorted by motion. Motion correction also reduces motion artifacts in estimated perfusion parameter maps. Magn Reson Med 79:1345-1353, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Adam Johansson
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - James Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.,Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Yue Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.,Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.,Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
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LaBounty TM, Bhave N, Giri S, Balter J, Conte AH, Shah R, Murthy V. Comparison of ileofemoral arterial access size between noncontrast 3T MR angiography and contrast-enhanced computed tomographic angiography in patients referred for transcatheter aortic valve replacement. J Magn Reson Imaging 2017; 46:1847-1850. [PMID: 28165647 DOI: 10.1002/jmri.25651] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Affiliation(s)
- Troy M LaBounty
- Department of Medicine, University of Michigan, Ann Arbor, Michigan.,Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | - Nicole Bhave
- Department of Medicine, University of Michigan, Ann Arbor, Michigan
| | | | - James Balter
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | | | - Ravi Shah
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Venkatesh Murthy
- Department of Medicine, University of Michigan, Ann Arbor, Michigan.,Department of Radiology, University of Michigan, Ann Arbor, Michigan
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Johansson A, Balter J, Feng M, Cao Y. An Overdetermined System of Transform Equations in Support of Robust DCE-MRI Registration With Outlier Rejection. ACTA ACUST UNITED AC 2016; 2:188-196. [PMID: 28367502 PMCID: PMC5373730 DOI: 10.18383/j.tom.2016.00145] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Quantitative hepatic perfusion parameters derived by fitting dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) of liver to a pharmacokinetic model are prone to errors if the dynamic images are not corrected for respiratory motion by image registration. The contrast-induced intensity variations in pre- and postcontrast phases pose challenges for the accuracy of image registration. We propose an overdetermined system of transformation equations between the image volumes in the DCE-MRI series to achieve robust alignment. In this method, we register each volume to every other volume. From the transforms produced by all pairwise registrations, we constructed an overdetermined system of transform equations that was solved robustly by minimizing the L1/2-norm of the residuals. This method was evaluated on a set of 100 liver DCE-MRI examinations from 35 patients by examining the area under spikes appearing in the voxel time–intensity curves. The robust alignment procedure significantly reduced the area under intensity spikes compared with unregistered volumes (P < .001) and volumes registered to a single reference phase (P < .001). Our registration procedure provides a larger number of reliable time–intensity curve samples. The additional reliable samples in the precontrast baseline are important for calculating the postcontrast signal enhancement and thereby for converting intensity to contrast concentration. On the intensity ramp, retained samples help to better describe the uptake dynamics, providing a better foundation for parameter estimation. The presented method also simplifies the analysis of data sets with many patients by eliminating the need for manual intervention during registration.
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Affiliation(s)
- Adam Johansson
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - James Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Mary Feng
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Yue Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Radiology, University of Michigan, Ann Arbor, Michigan; Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
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17
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Price RG, Kadbi M, Kim J, Balter J, Chetty IJ, Glide-Hurst CK. Technical Note: Characterization and correction of gradient nonlinearity induced distortion on a 1.0 T open bore MR-SIM. Med Phys 2016; 42:5955-60. [PMID: 26429270 DOI: 10.1118/1.4930245] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Distortions in magnetic resonance imaging (MRI) compromise spatial fidelity, potentially impacting delineation and dose calculation. We characterized 2D and 3D large field of view (FOV), sequence-independent distortion at various positions in a 1.0 T high-field open MR simulator (MR-SIM) to implement correction maps for MRI treatment planning. METHODS A 36 × 43 × 2 cm(3) phantom with 255 known landmarks (∼1 mm(3)) was scanned using 1.0 T high-field open MR-SIM at isocenter in the transverse, sagittal, and coronal axes, and a 465 × 350 × 168 mm(3) 3D phantom was scanned by stepping in the superior-inferior direction in three overlapping positions to achieve a total 465 × 350 × 400 mm(3) sampled FOV yielding >13 800 landmarks (3D Gradient-Echo, TE/TR/α = 5.54 ms/30 ms/28°, voxel size = 1 × 1 × 2 mm(3)). A binary template (reference) was generated from a phantom schematic. An automated program converted MR images to binary via masking, thresholding, and testing for connectivity to identify landmarks. Distortion maps were generated by centroid mapping. Images were corrected via warping with inverse distortion maps, and temporal stability was assessed. RESULTS Over the sampled FOV, non-negligible residual gradient distortions existed as close as 9.5 cm from isocenter, with a maximum distortion of 7.4 mm as close as 23 cm from isocenter. Over six months, average gradient distortions were -0.07 ± 1.10 mm and 0.10 ± 1.10 mm in the x and y directions for the transverse plane, 0.03 ± 0.64 and -0.09 ± 0.70 mm in the sagittal plane, and 0.4 ± 1.16 and 0.04 ± 0.40 mm in the coronal plane. After implementing 3D correction maps, distortions were reduced to <1 pixel width (1 mm) for all voxels up to 25 cm from magnet isocenter. CONCLUSIONS Inherent distortion due to gradient nonlinearity was found to be non-negligible even with vendor corrections applied, and further corrections are required to obtain 1 mm accuracy for large FOVs. Statistical analysis of temporal stability shows that sequence independent distortion maps are consistent within six months of characterization.
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Affiliation(s)
- Ryan G Price
- Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan 48202 and Department of Radiation Oncology, Wayne State University School of Medicine, Detroit, Michigan 48201
| | - Mo Kadbi
- Philips Healthcare, Cleveland, Ohio 44143
| | - Joshua Kim
- Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan 48202
| | - James Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan 48109
| | - Indrin J Chetty
- Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan 48202 and Department of Radiation Oncology, Wayne State University School of Medicine, Detroit, Michigan 48201
| | - Carri K Glide-Hurst
- Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan 48202 and Department of Radiation Oncology, Wayne State University School of Medicine, Detroit, Michigan 48201
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18
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Liu L, Jolly S, Cao Y, Vineberg K, Fessler J, Balter J. SU-D-207A-01: Female Pelvic Synthetic CT Generation Based On Joint Shape and Intensity Analysis. Med Phys 2016. [DOI: 10.1118/1.4955648] [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: 11/07/2022] Open
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19
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Owen D, Anderson C, Mayo C, El Naqa I, Ten Haken R, Cao Y, Balter J, Matuszak M. SU-F-J-94: Development of a Plug-in Based Image Analysis Tool for Integration Into Treatment Planning. Med Phys 2016. [DOI: 10.1118/1.4956002] [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: 11/07/2022] Open
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20
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Johansson A, Balter J, Feng M, Cao Y. WE-FG-206-10: Portal Venous Perfusion Quantitation From Liver DCE-MRI by Voxel Uptake Curve Clustering and Input Function Normalization. Med Phys 2016. [DOI: 10.1118/1.4957940] [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: 11/07/2022] Open
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21
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Cazoulat G, Kipritidis J, Siva S, Hofman M, Jolly S, Matuszak M, Balter J, Keall P, Brock K. WE-AB-202-05: Validation of Lung Stress Maps for CT-Ventilation Imaging. Med Phys 2016. [DOI: 10.1118/1.4957746] [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: 11/07/2022] Open
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22
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Bredfeldt JS, Liu L, Feng M, Cao Y, Balter J. TU-AB-BRA-01: Abdominal Synthetic CT Generation in Support of Liver SBRT Dose Calculation. Med Phys 2016. [DOI: 10.1118/1.4957411] [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: 11/07/2022] Open
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23
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Balter J. SP-0594: Individualised image-guided adaptive therapy in Michigan: lessons learned from clinical trial implementation. Radiother Oncol 2016. [DOI: 10.1016/s0167-8140(16)31844-8] [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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24
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Dow J, Matuszak M, Brock K, Haken RKT, Balter J, Lawrence T, Feng M. Potential Benefits of Fractionation Over SBRT for Large Liver Tumors. Int J Radiat Oncol Biol Phys 2015. [DOI: 10.1016/j.ijrobp.2015.07.984] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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25
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Chapman C, Prisciandaro J, Maturen K, Balter J, Cao Y, Mclean K, Jolly S. Vaginal Cuff Underdosing Persists Despite Maximal Insertion Using MRI Guidance. Int J Radiat Oncol Biol Phys 2015. [DOI: 10.1016/j.ijrobp.2015.07.1202] [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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26
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Price R, Balter J, Kim J, Kadbi M, Zheng W, Chetty I, Glide-Hurst C. TH-CD-204-11: Three Dimensional Gradient Nonlinearity Distortion Corrections for 1.0T MR-SIM Patient Images. Med Phys 2015. [DOI: 10.1118/1.4926258] [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: 11/07/2022] Open
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27
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Liu L, Cao Y, Fessler J, Balter J. SU-F-303-14: Investigation of a Pelvic Bone Shape Model in Support of Bone Classification for Synthetic CT Generation. Med Phys 2015. [DOI: 10.1118/1.4925241] [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: 11/07/2022] Open
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28
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Cazoulat G, Owen D, Matuszak M, Balter J, Brock K. SU-E-J-91: Biomechanical Deformable Image Registration of Longitudinal Lung CT Images. Med Phys 2015. [DOI: 10.1118/1.4924178] [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: 11/07/2022] Open
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29
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Chapman CH, Prisciandaro J, Maturen K, Balter J, Cao Y, Young L, Jolly S. MRI-Based Evaluation of Coverage of the Vaginal Cuff in Endometrial Brachytherapy: Are We Missing the Target? Brachytherapy 2015. [DOI: 10.1016/j.brachy.2015.02.209] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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30
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Chapman CH, Jolly S, Young L, Maturen K, Balter J, Owrangi A, Prisciandaro J. Assessing the Need for Dose Calculations to Organs at Risk Using MRI Planning in Vaginal Brachytherapy. Brachytherapy 2015. [DOI: 10.1016/j.brachy.2014.08.023] [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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31
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Liss A, Kapadia N, Marsh R, Rogers V, Balter J, Moran J, Frey K, Pierce L. Decreased Lung Perfusion Following Breast/Chest Wall Irradiation: Preliminary Results of a Prospective Clinical Trial. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.172] [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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32
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Chapman C, Jolly S, Young L, Maturen K, Balter J, Owrangi A, Prisciandaro J. Assessing the Need for Dose Calculations to Organs at Risk Using MRI Planning in Vaginal Brachytherapy. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.1530] [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: 10/24/2022]
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33
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Balter J, Hsu S, Vineberg K, Lawrence T, Feng M, Tsien C, Cao Y. Volumetric Arc Treatment Planning in the Brain Using MRI-Derived Synthetic CT Images. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.750] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Abstract
Geometric accuracy of MRI is one of the main concerns for its use as a sole image modality in precision radiation therapy (RT) planning. In a state-of-the-art scanner, system level geometric distortions are within acceptable levels for precision RT. However, subject-induced B0 inhomogeneity may vary substantially, especially in air-tissue interfaces. Recent studies have shown distortion levels of more than 2 mm near the sinus and ear canal are possible due to subject-induced field inhomogeneity. These distortions can be corrected with the use of accurate B0 inhomogeneity field maps. Most existing methods estimate these field maps from dual gradient-echo (GRE) images acquired at two different echo-times under the assumption that the GRE images are practically undistorted. However distortion that may exist in the GRE images can result in estimated field maps that are distorted in both geometry and intensity, leading to inaccurate correction of clinical images. This work proposes a method for estimating undistorted field maps from GRE acquisitions using an iterative joint estimation technique. The proposed method yields geometrically corrected GRE images and undistorted field maps that can also be used for the correction of images acquired by other sequences. The proposed method is validated through simulation, phantom experiments and applied to patient data. Our simulation results show that our method reduces the root-mean-squared error of the estimated field map from the ground truth by ten-fold compared to the distorted field map. Both the geometric distortion and the intensity corruption (artifact) in the images caused by the B0 field inhomogeneity are corrected almost completely. Our phantom experiment showed improvement in the geometric correction of approximately 1 mm at an air-water interface using the undistorted field map compared to using a distorted field map. The proposed method for undistorted field map estimation can lead to improved geometric distortion correction at air-tissue interfaces, especially in low readout-bandwidth acquisitions, thus making them suitable for clinical use in precision RT without increasing the treatment planning margin.
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Affiliation(s)
- A Matakos
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI 48109, USA
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35
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Brock K, Lee C, Lockhart C, Balter J, Ten HR, Eisbruch A. SU-E-CAMPUS-J-02: Implementation of Routine Clinical Daily Dose Evaluation for Patient Specific Quality Control. Med Phys 2014. [DOI: 10.1118/1.4889022] [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: 11/07/2022] Open
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36
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Matakos A, Balter J, Cao Y. WE-G-18C-01: Novel Method for Geometrically Undistorted B0 Inhomogeneity Field Map Estimation and Image Correction. Med Phys 2014. [DOI: 10.1118/1.4889520] [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: 11/07/2022] Open
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37
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Stanescu T, Balter J, Nyholm T, Lagendijk J. TU-A-BRF-01: MR Guided Radiation Therapy. Med Phys 2014. [DOI: 10.1118/1.4889233] [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: 11/07/2022] Open
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38
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Hsu S, Cao Y, Jolly S, Balter J. SU-C-17A-01: MRI-Based Radiotherapy Treatment Planning In Pelvis. Med Phys 2014. [DOI: 10.1118/1.4889728] [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: 11/07/2022] Open
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39
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Owrangi A, Jolly S, Balter J, Cao Y, Young L, Zhu T, Prisciandaro J. SU-E-T-366: Clinical Implementation of MR-Guided Vaginal Cylinder Brachytherapy. Med Phys 2014. [DOI: 10.1118/1.4888699] [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: 11/07/2022] Open
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40
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Balter J, Eisbruch A. In Reply to Ren et al. Int J Radiat Oncol Biol Phys 2014; 88:1214. [DOI: 10.1016/j.ijrobp.2014.01.028] [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] [Received: 01/16/2014] [Accepted: 01/18/2014] [Indexed: 11/24/2022]
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41
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Matakos A, Balter J, Cao Y. OC-0084: Iterative correction of subject-dependent B0 inhomogeneity field maps for geometric distortion correction. Radiother Oncol 2014. [DOI: 10.1016/s0167-8140(15)30189-4] [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: 11/28/2022]
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42
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Hsu S, Cao Y, Balter J. TH-C-141-01: Differentiation of Air From Bone Using MRI for Radiation Therapy and PET-MRI Reconstruction. Med Phys 2013. [DOI: 10.1118/1.4815769] [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: 11/07/2022] Open
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43
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Molineu A, Miller R, Clements J, Balter J. WE-E-105-01: Managing and Leading Others: Practical Advice for Medical Physicists. Med Phys 2013. [DOI: 10.1118/1.4815577] [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: 11/07/2022] Open
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44
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Wang H, Feng M, Frey K, Balter J, Haken RT, Lawrence T, Cao Y. Hepatic Function Model Based Upon HIDA SPECT and Dose for Physiological Adaptive RT. Pract Radiat Oncol 2013; 3:S2. [DOI: 10.1016/j.prro.2013.01.010] [Citation(s) in RCA: 2] [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: 11/29/2022]
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45
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Wang H, Balter J, Cao Y. Patient-induced susceptibility effect on geometric distortion of clinical brain MRI for radiation treatment planning on a 3T scanner. Phys Med Biol 2013; 58:465-77. [PMID: 23302471 DOI: 10.1088/0031-9155/58/3/465] [Citation(s) in RCA: 72] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Concerns about the geometric accuracy of MRI in radiation therapy (RT) have been present since its invention. Although modern scanners typically have system levels of geometric accuracy that meet requirements of RT, subject-specific distortion is variable, and methods to in vivo assess and control patient-induced geometric distortion are not yet resolved. This study investigated the nature and magnitude of the subject-induced susceptibility effect on geometric distortions in clinical brain MRI, and tested the feasibility of in vivo quality control using field inhomogeneity mapping. For 19 consecutive patients scanned on a dedicated 3T MR scanner, B0 field inhomogeneity maps were acquired and analyzed to determine subject-induced distortions. For 3D T1 weighted images frequency-encoded with a bandwidth of 180 Hz/pixel, 86.9% of the estimated displacements were <0.5 mm, 97.4% <1 mm, and only 0.1% of displacements > 2 mm. The maximum displacement was <4 mm. The greatest distortions were observed at the interfaces with air at the sinuses. Displacements decayed to less than 1 mm over a distance of 8 mm. Metal surgical wires generated smaller distortions, with an averaged maximum displacement of 0.76 mm. Repeat acquisition of the field maps in 17 patients revealed a within-subject standard deviation of 0.25 ppm, equivalent to 0.22 mm displacement in the frequency-encoding direction in the 3D T1 weighted images. Susceptibility-induced voxel displacements in the brain are generally small, but should be monitored for precision RT. These effects are manageable at 3T and lower fields, and the methods applied can be used to monitor for potential local errors in individual patients, as well as to correct for local distortions as needed.
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Affiliation(s)
- H Wang
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI 48109, USA
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46
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Cao Y, Hsu S, Flammang A, Balter J. MRCT: Synthetic CT Imaging for Radiation Oncology Using Magnetic Resonance Images. Int J Radiat Oncol Biol Phys 2012. [DOI: 10.1016/j.ijrobp.2012.07.1981] [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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47
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Hsu S, Cao Y, Balter J. MO-G-BRA-02: Investigation of a Method for Generating Synthetic CT Models from MRI Scans for Radiation Therapy. Med Phys 2012. [DOI: 10.1118/1.4735847] [Citation(s) in RCA: 2] [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: 11/07/2022] Open
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48
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Wang H, Feng M, Frey K, Balter J, Haken RT, Lawrence T, Cao Y. WE-A-217A-04: Hepatic Function Estimated from HIDA SPECT for Assessment of Liver Response to Radiation Therapy. Med Phys 2012. [DOI: 10.1118/1.4736062] [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: 11/07/2022] Open
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49
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Thomas A, Hollister S, Balter J. SU-C-218-05: A CFD-Based Approach to Validating Flow in a Prototype Dynamic Perfusion Phantom for Dynamic Contrast Fnhanced (DCE) Imaging. Med Phys 2012. [DOI: 10.1118/1.4734653] [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: 11/07/2022] Open
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50
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Kim J, Matuszak M, Saitou K, Balter J. MO-F-BRA-01: A Biomechanical Constraint for Intensity-Driven Deformable Alignment of Skeletal Components in the Head and Neck Region. Med Phys 2012; 39:3874-3875. [DOI: 10.1118/1.4735820] [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: 11/07/2022] Open
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