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Article ; Online: Validation of daily 0.35 T diffusion-weighted MRI for MRI-guided glioblastoma radiotherapy.

Lutsik, Natalia / Nejad-Davarani, Siamak P / Valderrama, Alessandro / Herr, Janette / Maziero, Danilo / Cullison, Kaylie / Azzam, Gregory A / Kubicek, Gregory J / Meshman, Jessica / de la Fuente, Macarena I / Armstrong, Tess / Mellon, Eric A

Medical physics

2024

Abstract: Background: MRI-Linac systems enable daily diffusion-weighed imaging (DWI) MRI scans for assessing glioblastoma tumor changes with radiotherapy treatment.: Purpose: Our study assessed the image quality of echoplanar imaging (EPI)-DWI scans compared ... ...

Abstract	Background: MRI-Linac systems enable daily diffusion-weighed imaging (DWI) MRI scans for assessing glioblastoma tumor changes with radiotherapy treatment. Purpose: Our study assessed the image quality of echoplanar imaging (EPI)-DWI scans compared with turbo spin echo (TSE)-DWI scans at 0.35 Tesla (T) and compared the apparent diffusion coefficient (ADC) values and distortion of EPI-DWI on 0.35 T MRI-Linac compared to high-field diagnostic MRI scanners. Methods: The calibrated National Institute of Standards and Technology (NIST)/Quantitative Imaging Biomarkers Alliance (QIBA) Diffusion Phantom was scanned on a 0.35 T MRI-Linac, and 1.5 T and 3 T MRI with EPI-DWI. Five patients were scanned on a 0.35 T MRI-Linac with a TSE-DWI sequence, and five other patients were scanned with EPI-DWI on a 0.35 T MRI-Linac and a 3 T MRI. The quality of images was compared between the TSE-DWI and EPI-DWI on the 0.35 T MRI-Linac assessing signal-to-noise ratios and presence of artifacts. EPI-DWI ADC values and distortion magnitude were measured and compared between 0.35 T MRI-Linac and high-field MRI for both phantom and patient studies. Results: The average ADC differences between EPI-DWI acquired on the 0.35 T MRI-Linac, 1.5 T and 3 T MRI scanners and published references in the phantom study were 1.7%, 0.4% and 1.0%, respectively. Comparing the ADC values based on EPI-DWI in glioblastoma tumors, there was a 3.36% difference between 0.35 and 3 T measurements. Susceptibility-induced distortions in the EPI-DWI phantoms were 0.46 ± 1.51 mm for 0.35 MRI-Linac, 0.98 ± 0.51 mm for 1.5 T MRI and 1.14 ± 1.88 mm for 3 T MRI; for patients -0.47 ± 0.78 mm for 0.35 T and 1.73 ± 2.11 mm for 3 T MRIs. The mean deformable registration distortion for a phantom was 1.1 ± 0.22 mm, 3.5 ± 0.39 mm and 4.7 ± 0.37 mm for the 0.35 T MRI-Linac, 1.5 T MRI, and 3 T MRI scanners, respectively; for patients this distortion was -0.46 ± 0.57 mm for 0.35 T and 4.2 ± 0.41 mm for 3 T. EPI-DWI 0.35 T MRI-Linac images showed higher SNR and lack of artifacts compared with TSE-DWI, especially at higher b-values up to 1000 s/mm Conclusion: EPI-DWI on a 0.35 T MRI-Linac showed superior image quality compared with TSE-DWI, minor and less distortions than high-field diagnostic scanners, and comparable ADC values in phantoms and glioblastoma tumors. EPI-DWI should be investigated on the 0.35 T MRI-Linac for prediction of early response in patients with glioblastoma.
Language	English
Publishing date	2024-04-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	188780-4
ISSN	2473-4209 ; 0094-2405
ISSN (online)	2473-4209
ISSN	0094-2405
DOI	10.1002/mp.17067
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Article ; Online: Performance of deep learning synthetic CTs for MR-only brain radiation therapy.

Liu, Xiaoning / Emami, Hajar / Nejad-Davarani, Siamak P / Morris, Eric / Schultz, Lonni / Dong, Ming / K Glide-Hurst, Carri

Journal of applied clinical medical physics

2021 Volume 22, Issue 1, Page(s) 308–317

Abstract: Purpose: To evaluate the dosimetric and image-guided radiation therapy (IGRT) performance of a novel generative adversarial network (GAN) generated synthetic CT (synCT) in the brain and compare its performance for clinical use including conventional ... ...

Abstract	Purpose: To evaluate the dosimetric and image-guided radiation therapy (IGRT) performance of a novel generative adversarial network (GAN) generated synthetic CT (synCT) in the brain and compare its performance for clinical use including conventional brain radiotherapy, cranial stereotactic radiosurgery (SRS), planar, and volumetric IGRT. Methods and materials: SynCT images for 12 brain cancer patients (6 SRS, 6 conventional) were generated from T1-weighted postgadolinium magnetic resonance (MR) images by applying a GAN model with a residual network (ResNet) generator and a convolutional neural network (CNN) with 5 convolutional layers as the discriminator that classified input images as real or synthetic. Following rigid registration, clinical structures and treatment plans derived from simulation CT (simCT) images were transferred to synCTs. Dose was recalculated for 15 simCT/synCT plan pairs using fixed monitor units. Two-dimensional (2D) gamma analysis (2%/2 mm, 1%/1 mm) was performed to compare dose distributions at isocenter. Dose-volume histogram (DVH) metrics (D Results: Average gamma passing rates at 1%/1mm and 2%/2mm were 99.0 ± 1.5% and 99.9 ± 0.2%, respectively. Excellent agreement in DVH metrics was observed (mean difference ≤0.10 ± 0.04 Gy for targets, 0.13 ± 0.04 Gy for OARs). The population averaged mean difference in CBCT-synCT registrations were <0.2 mm and 0.1 degree different from simCT-based registrations. The mean difference between kV-synCT DRR and kV-simCT DRR registrations was <0.5 mm with no statistically significant differences observed (P > 0.05). An outlier with a large resection cavity exhibited the worst-case scenario. Conclusion: Brain GAN synCTs demonstrated excellent performance for dosimetric and IGRT endpoints, offering potential use in high precision brain cancer therapy.
MeSH term(s)	Brain/diagnostic imaging ; Brain/surgery ; Deep Learning ; Humans ; Radiotherapy Dosage ; Radiotherapy Planning, Computer-Assisted ; Radiotherapy, Image-Guided
Language	English
Publishing date	2021-01-07
Publishing country	United States
Document type	Journal Article
ZDB-ID	2010347-5
ISSN	1526-9914 ; 1526-9914
ISSN (online)	1526-9914
ISSN	1526-9914
DOI	10.1002/acm2.13139
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Article ; Online: Large field of view distortion assessment in a low-field MR-linac.

Nejad-Davarani, Siamak P / Kim, Joshua P / Du, Dongsu / Glide-Hurst, Carri

Medical physics

2019 Volume 46, Issue 5, Page(s) 2347–2355

Abstract: Purpose: MR-guided radiation therapy (RT) offers unparalleled soft tissue contrast for localization and target tracking. However, MRI distortions may be detrimental to high precision RT. This work characterizes the gradient nonlinearity (GNL) and total ... ...

Abstract	Purpose: MR-guided radiation therapy (RT) offers unparalleled soft tissue contrast for localization and target tracking. However, MRI distortions may be detrimental to high precision RT. This work characterizes the gradient nonlinearity (GNL) and total distortions over the first year of clinical operation of a 0.35T MR-linac. Methods: For GNL characterization, an in-house large field of view (FOV) phantom (60 × 42.5 × 55 cm Results: The scanner's spatial integrity within the first ~10 months was stable (maximum total distortion variation = 10/6/8%, maximum distortion = 1.41/0.99/1.56 mm in Axial/Coronal/Sagittal planes, respectively). GNL distortions measured during this time period <10 cm from isocenter were (-0.74, 0.45), (-0.67, 0.53), and (-0.86, 0.70) mm in AP/LR/SI directions. In the 10-20 cm range, <1.5% of the distortions exceeded 2 mm in the AP and LR axes while <4% of the distortions exceeded 2 mm for SI. After major repairs and magnet re-shim, detectable changes were observed in total and GNL distortions (20% reduction in AP and 36% increase in SI direction in the 20-25 cm range). Across all timepoints and axes, 38-53% of landmarks in the 20-25 cm range were displaced by >1 mm. Conclusions: GNL distortions were negligible within a 10 cm radius from isocenter. However, in the periphery, non-negligible distortions of up to ~7 mm were observed, which may necessitate GNL corrections for MR-IGRT for treatment sites distant from magnet isocenter.
MeSH term(s)	Image Processing, Computer-Assisted ; Magnetic Resonance Imaging/instrumentation ; Nonlinear Dynamics ; Particle Accelerators ; Phantoms, Imaging ; Radiotherapy Planning, Computer-Assisted ; Radiotherapy, Image-Guided
Language	English
Publishing date	2019-03-23
Publishing country	United States
Document type	Journal Article
ZDB-ID	188780-4
ISSN	2473-4209 ; 0094-2405
ISSN (online)	2473-4209
ISSN	0094-2405
DOI	10.1002/mp.13467
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Article ; Online: Impairments of white matter tracts and connectivity alterations in five cognitive networks of patients with multiple sclerosis.

Lashkari, AmirEhsan / Davoodi-Bojd, Esmaeil / Fahmy, Lara / Li, Lian / Nejad-Davarani, Siamak P / Chopp, Michael / Jiang, Quan / Cerghet, Mirela

Clinical neurology and neurosurgery

2020 Volume 201, Page(s) 106424

Abstract: Introduction: MS is associated with structural and functional brain alterations leading to cognitive impairments across multiple domains including attention, memory, and speed of information processing. Here, we analyzed the white matter damage and ... ...

Abstract	Introduction: MS is associated with structural and functional brain alterations leading to cognitive impairments across multiple domains including attention, memory, and speed of information processing. Here, we analyzed the white matter damage and topological organization of white matter tracts in specific brain regions responsible for cognition in MS. Methods: Brain DTI, rs-fMRI, T1, T2, and T2-FLAIR were acquired for 22 MS subjects and 22 healthy controls. Automatic brain parcellation was performed on T1-weighted images. Skull-stripped T1-weighted intensity inverted images were co-registered to the b0 image. Diffusion-weighted images were processed to perform whole brain tractography. The rs-fMRI data were processed, and the connectivity matrixes were analyzed to identify significant differences in the network of nodes between the two groups using NBS analysis. In addition, diffusion entropy maps were produced from DTI data sets using in-house software. Results: MS subjects exhibited significantly reduced mean FA and entropy in 38 and 34 regions, respectively, out of a total of 54 regions. The connectivity values in both structural and functional analyses were decreased in most regions of the default mode network and in four other cognitive networks in MS subjects compared to healthy controls. MS also induced significant reduction in the normalized hippocampus and corpus callosum volumes; the normalized hippocampus volume was significantly correlated with EDSS scores. Conclusion: MS subjects have significant white matter damage and reduction of FA and entropy in various brain regions involved in cognitive networks. Structural and functional connectivity within the default mode network and an additional four cognitive networks exhibited significant changes compared with healthy controls.
MeSH term(s)	Adult ; Attention/physiology ; Cognition/physiology ; Cognitive Dysfunction/physiopathology ; Diffusion Tensor Imaging/methods ; Humans ; Male ; Middle Aged ; Multiple Sclerosis/physiopathology ; Nerve Net/physiopathology ; Neural Pathways/physiopathology ; White Matter/physiopathology
Language	English
Publishing date	2020-12-08
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	193107-6
ISSN	1872-6968 ; 0303-8467
ISSN (online)	1872-6968
ISSN	0303-8467
DOI	10.1016/j.clineuro.2020.106424
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Article ; Online: Generating synthetic CTs from magnetic resonance images using generative adversarial networks.

Emami, Hajar / Dong, Ming / Nejad-Davarani, Siamak P / Glide-Hurst, Carri K

Medical physics

2018

Abstract: Purpose: While MR-only treatment planning using synthetic CTs (synCTs) offers potential for streamlining clinical workflow, a need exists for an efficient and automated synCT generation in the brain to facilitate near real-time MR-only planning. This ... ...

Abstract	Purpose: While MR-only treatment planning using synthetic CTs (synCTs) offers potential for streamlining clinical workflow, a need exists for an efficient and automated synCT generation in the brain to facilitate near real-time MR-only planning. This work describes a novel method for generating brain synCTs based on generative adversarial networks (GANs), a deep learning model that trains two competing networks simultaneously, and compares it to a deep convolutional neural network (CNN). Methods: Post-Gadolinium T1-Weighted and CT-SIM images from fifteen brain cancer patients were retrospectively analyzed. The GAN model was developed to generate synCTs using T1-weighted MRI images as the input using a residual network (ResNet) as the generator. The discriminator is a CNN with five convolutional layers that classified the input image as real or synthetic. Fivefold cross-validation was performed to validate our model. GAN performance was compared to CNN based on mean absolute error (MAE), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR) metrics between the synCT and CT images. Results: GAN training took ~11 h with a new case testing time of 5.7 ± 0.6 s. For GAN, MAEs between synCT and CT-SIM were 89.3 ± 10.3 Hounsfield units (HU) and 41.9 ± 8.6 HU across the entire FOV and tissues, respectively. However, MAE in the bone and air was, on average, ~240-255 HU. By comparison, the CNN model had an average full FOV MAE of 102.4 ± 11.1 HU. For GAN, the mean PSNR was 26.6 ± 1.2 and SSIM was 0.83 ± 0.03. GAN synCTs preserved details better than CNN, and regions of abnormal anatomy were well represented on GAN synCTs. Conclusions: We developed and validated a GAN model using a single T1-weighted MR image as the input that generates robust, high quality synCTs in seconds. Our method offers strong potential for supporting near real-time MR-only treatment planning in the brain.
Language	English
Publishing date	2018-06-14
Publishing country	United States
Document type	Journal Article
ZDB-ID	188780-4
ISSN	2473-4209 ; 0094-2405
ISSN (online)	2473-4209
ISSN	0094-2405
DOI	10.1002/mp.13047
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Article ; Online: Rapid multicontrast brain imaging on a 0.35T MR-linac.

Nejad-Davarani, Siamak P / Zakariaei, Niloufar / Chen, Yongsheng / Haacke, E Mark / Hurst, Newton J / Salim Siddiqui, M / Schultz, Lonni R / Snyder, James M / Walbert, Tobias / Glide-Hurst, Carri K

Medical physics

2020 Volume 47, Issue 9, Page(s) 4064–4076

Abstract: Purpose: Magnetic resonance-guided radiation therapy (MRgRT) has shown great promise for localization and real-time tumor monitoring. However, to date, quantitative imaging has been limited for low field MRgRT. This work benchmarks quantitative T1, R2*, ...

Abstract	Purpose: Magnetic resonance-guided radiation therapy (MRgRT) has shown great promise for localization and real-time tumor monitoring. However, to date, quantitative imaging has been limited for low field MRgRT. This work benchmarks quantitative T1, R2, and Proton Density (PD)mapping in a phantom on a 0.35 T MR-linac and implements a novel acquisition method, STrategically Acquired Gradient Echo (STAGE). To further validate STAGE in a clinical setting, a pilot study was undertaken in a cohort of brain tumor patients to elucidate opportunities for longitudinal functional imaging with an MR-linac in the brain. Methods:* STAGE (two triple-echo gradient echo (GRE) acquisitions) was optimized for a 0.35T low-field MR-linac. Simulations were performed to choose two flip angles to optimize signal-to-noise ratio (SNR) and T1-mapping precision. Tradeoffs between SNR, scan time, and spatial resolution for whole-brain coverage were evaluated in healthy volunteers. Data were inputted into a STAGE processing pipeline to yield four qualitative images (T1-weighted, enhanced T1-weighted, proton-density (PD) weighted, and simulated FLuid-Attenuated Inversion Recovery (sFLAIR)), and three quantitative datasets (T1, PD, and R2). A benchmarking ISMRM/NIST phantom consisting of vials with variable NiCl Results:* In the phantom, RE of measured VFA T1 and STAGE relative to IR reference values were 7.0 ± 2.5% and 9.5 ± 2.2% respectively. RE for the PD vials was 8.1 ± 6.8% and CV for phantom R2* measurements was 10.1 ± 9.9%. Simulations and volunteer experiments yielded final STAGE parameters of FA = 50°/10°, 1 × 1 × 3 mm Conclusion: Quantitative T1, R2*, and PD mapping are promising at 0.35 T agreeing well with reference data. STAGE phantom data offer quantitative representations comparable to traditional methods in a fraction of the acquisition time. Initial feasibility of implementing STAGE at 0.35 T in a patient brain tumor cohort suggests that detectable changes can be observed over time. With confirmation in a larger cohort, results may be implemented to identify areas of recurrence and facilitate adaptive radiation therapy.
MeSH term(s)	Brain/diagnostic imaging ; Humans ; Magnetic Resonance Imaging ; Neoplasm Recurrence, Local ; Neuroimaging ; Phantoms, Imaging ; Pilot Projects ; Reproducibility of Results
Language	English
Publishing date	2020-07-06
Publishing country	United States
Document type	Journal Article
ZDB-ID	188780-4
ISSN	2473-4209 ; 0094-2405
ISSN (online)	2473-4209
ISSN	0094-2405
DOI	10.1002/mp.14251
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Article ; Online: An extended vascular model for less biased estimation of permeability parameters in DCE-T1 images.

Nejad-Davarani, Siamak P / Bagher-Ebadian, Hassan / Ewing, James R / Noll, Douglas C / Mikkelsen, Tom / Chopp, Michael / Jiang, Quan

NMR in biomedicine

2017 Volume 30, Issue 6

Abstract: One of the key elements in dynamic contrast enhanced (DCE) image analysis is the arterial input function (AIF). Traditionally, in DCE studies a global AIF sampled from a major artery or vein is used to estimate the vascular permeability parameters; ... ...

Abstract	One of the key elements in dynamic contrast enhanced (DCE) image analysis is the arterial input function (AIF). Traditionally, in DCE studies a global AIF sampled from a major artery or vein is used to estimate the vascular permeability parameters; however, not addressing dispersion and delay of the AIF at the tissue level can lead to biased estimates of these parameters. To find less biased estimates of vascular permeability parameters, a vascular model of the cerebral vascular system is proposed that considers effects of dispersion of the AIF in the vessel branches, as well as extravasation of the contrast agent (CA) to the extravascular-extracellular space. Profiles of the CA concentration were simulated for different branching levels of the vascular structure, combined with the effects of vascular leakage. To estimate the permeability parameters, the extended model was applied to these simulated signals and also to DCE-T1 (dynamic contrast enhanced T
Language	English
Publishing date	2017-06
Publishing country	England
Document type	Journal Article
ZDB-ID	1000976-0
ISSN	1099-1492 ; 0952-3480
ISSN (online)	1099-1492
ISSN	0952-3480
DOI	10.1002/nbm.3698
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Article ; Online: A parametric model of the brain vascular system for estimation of the arterial input function (AIF) at the tissue level.

Nejad-Davarani, Siamak P / Bagher-Ebadian, Hassan / Ewing, James R / Noll, Douglas C / Mikkelsen, Tom / Chopp, Michael / Jiang, Quan

NMR in biomedicine

2017 Volume 30, Issue 5

Abstract: In this paper, we introduce a novel model of the brain vascular system, which is developed based on laws of fluid dynamics and vascular morphology. This model is used to address dispersion and delay of the arterial input function (AIF) at different ... ...

Abstract	In this paper, we introduce a novel model of the brain vascular system, which is developed based on laws of fluid dynamics and vascular morphology. This model is used to address dispersion and delay of the arterial input function (AIF) at different levels of the vascular structure and to estimate the local AIF in DCE images. We developed a method based on the simplex algorithm and Akaike information criterion to estimate the likelihood of the contrast agent concentration signal sampled in DCE images belonging to different layers of the vascular tree or being a combination of different signal levels from different nodes of this structure. To evaluate this method, we tested the method on simulated local AIF signals at different levels of this structure. Even down to a signal to noise ratio of 5.5 our method was able to accurately detect the branching level of the simulated signals. When two signals with the same power level were combined, our method was able to separate the base signals of the composite AIF at the 50% threshold. We applied this method to dynamic contrast enhanced computed tomography (DCE-CT) data, and using the parameters estimated by our method we created an arrival time map of the brain. Our model corrected AIF can be used for solving the pharmacokinetic equations for more accurate estimation of vascular permeability parameters in DCE imaging studies.
Language	English
Publishing date	2017-05
Publishing country	England
Document type	Journal Article
ZDB-ID	1000976-0
ISSN	1099-1492 ; 0952-3480
ISSN (online)	1099-1492
ISSN	0952-3480
DOI	10.1002/nbm.3695
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Article ; Online: Optimization of a novel large field of view distortion phantom for MR-only treatment planning.

Price, Ryan G / Knight, Robert A / Hwang, Ken-Pin / Bayram, Ersin / Nejad-Davarani, Siamak P / Glide-Hurst, Carri K

Journal of applied clinical medical physics

2017 Volume 18, Issue 4, Page(s) 51–61

Abstract: Purpose: MR-only treatment planning requires images of high geometric fidelity, particularly for large fields of view (FOV). However, the availability of large FOV distortion phantoms with analysis software is currently limited. This work sought to ... ...

Abstract	Purpose: MR-only treatment planning requires images of high geometric fidelity, particularly for large fields of view (FOV). However, the availability of large FOV distortion phantoms with analysis software is currently limited. This work sought to optimize a modular distortion phantom to accommodate multiple bore configurations and implement distortion characterization in a widely implementable solution. Method and materials: To determine candidate materials, 1.0 T MR and CT images were acquired of twelve urethane foam samples of various densities and strengths. Samples were precision-machined to accommodate 6 mm diameter paintballs used as landmarks. Final material candidates were selected by balancing strength, machinability, weight, and cost. Bore sizes and minimum aperture width resulting from couch position were tabulated from the literature (14 systems, 5 vendors). Bore geometry and couch position were simulated using MATLAB to generate machine-specific models to optimize the phantom build. Previously developed software for distortion characterization was modified for several magnet geometries (1.0 T, 1.5 T, 3.0 T), compared against previously published 1.0 T results, and integrated into the 3D Slicer application platform. Results: All foam samples provided sufficient MR image contrast with paintball landmarks. Urethane foam (compressive strength ∼1000 psi, density ~20 lb/ft Conclusion: The design and implementation of a modular, extendable distortion phantom was optimized for several bore configurations. The phantom and analysis software will be available for multi-institutional collaborations and cross-validation trials to support MR-only planning.
Language	English
Publishing date	2017-07
Publishing country	United States
Document type	Journal Article
ZDB-ID	2010347-5
ISSN	1526-9914 ; 1526-9914
ISSN (online)	1526-9914
ISSN	1526-9914
DOI	10.1002/acm2.12090
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Article ; Online: Geometric and dosimetric impact of anatomical changes for MR-only radiation therapy for the prostate.

Nejad-Davarani, Siamak P / Sevak, Parag / Moncion, Michael / Garbarino, Kimberly / Weiss, Steffen / Kim, Joshua / Schultz, Lonni / Elshaikh, Mohamed A / Renisch, Steffen / Glide-Hurst, Carri

Journal of applied clinical medical physics

2019 Volume 20, Issue 4, Page(s) 10–17

Abstract: Purpose: With the move towards magnetic resonance imaging (MRI) as a primary treatment planning modality option for men with prostate cancer, it becomes critical to quantify the potential uncertainties introduced for MR-only planning. This work ... ...

Abstract	Purpose: With the move towards magnetic resonance imaging (MRI) as a primary treatment planning modality option for men with prostate cancer, it becomes critical to quantify the potential uncertainties introduced for MR-only planning. This work characterized geometric and dosimetric intra-fractional changes between the prostate, seminal vesicles (SVs), and organs at risk (OARs) in response to bladder filling conditions. Materials and methods: T2-weighted and mDixon sequences (3-4 time points/subject, at 1, 1.5 and 3.0 T with totally 34 evaluable time points) were acquired in nine subjects using a fixed bladder filling protocol (bladder void, 20 oz water consumed pre-imaging, 10 oz mid-session). Using mDixon images, Magnetic Resonance for Calculating Attenuation (MR-CAT) synthetic computed tomography (CT) images were generated by classifying voxels as muscle, adipose, spongy, and compact bone and by assignment of bulk Hounsfield Unit values. Organs including the prostate, SVs, bladder, and rectum were delineated on the T2 images at each time point by one physician. The displacement of the prostate and SVs was assessed based on the shift of the center of mass of the delineated organs from the reference state (fullest bladder). Changes in dose plans at different bladder states were assessed based on volumetric modulated arc radiotherapy (VMAT) plans generated for the reference state. Results: Bladder volume reduction of 70 ± 14% from the final to initial time point (relative to the final volume) was observed in the subject population. In the empty bladder condition, the dose delivered to 95% of the planning target volume (PTV) (D95%) reduced significantly for all cases (11.53 ± 6.00%) likely due to anterior shifts of prostate/SVs relative to full bladder conditions. D15% to the bladder increased consistently in all subjects (42.27 ± 40.52%). Changes in D15% to the rectum were patient-specific, ranging from -23.93% to 22.28% (-0.76 ± 15.30%). Conclusions: Variations in the bladder and rectal volume can significantly dislocate the prostate and OARs, which can negatively impact the dose delivered to these organs. This warrants proper preparation of patients during treatment and imaging sessions, especially when imaging required longer scan times such as MR protocols.
MeSH term(s)	Adult ; Humans ; Image Processing, Computer-Assisted/methods ; Magnetic Resonance Imaging/methods ; Male ; Middle Aged ; Organs at Risk/radiation effects ; Prognosis ; Prostate/anatomy & histology ; Prostate/radiation effects ; Prostatic Neoplasms/radiotherapy ; Radiometry/methods ; Radiotherapy Dosage ; Radiotherapy Planning, Computer-Assisted/methods ; Radiotherapy, Intensity-Modulated/methods
Language	English
Publishing date	2019-03-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	2010347-5
ISSN	1526-9914 ; 1526-9914
ISSN (online)	1526-9914
ISSN	1526-9914
DOI	10.1002/acm2.12551
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