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Zhong AY, Lui AJ, Katz MS, Berlin A, Kamran SC, Kishan AU, Murthy V, Nagar H, Seible D, Stish BJ, Tree AC, Seibert TM. Use of focal radiotherapy boost for prostate cancer: radiation oncologists' perspectives and perceived barriers to implementation. Radiat Oncol 2023; 18:188. [PMID: 37950310 PMCID: PMC10638743 DOI: 10.1186/s13014-023-02375-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 11/05/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND In a recent phase III randomized control trial, delivering a focal radiotherapy (RT) boost to tumors visible on MRI was shown to improve disease-free survival and regional/distant metastasis-free survival for patients with prostate cancer-without increasing toxicity. The aim of this study was to assess how widely this technique is being applied in current practice, as well as physicians' perceived barriers toward its implementation. METHODS We invited radiation oncologists to complete an online questionnaire assessing their use of intraprostatic focal boost in December 2022 and February 2023. To include perspectives from a broad range of practice settings, the invitation was distributed to radiation oncologists worldwide via email list, group text platform, and social media. RESULTS 263 radiation oncologist participants responded. The highest-represented countries were the United States (42%), Mexico (13%), and the United Kingdom (8%). The majority of participants worked at an academic medical center (52%) and considered their practice to be at least partially genitourinary (GU)-subspecialized (74%). Overall, 43% of participants reported routinely using intraprostatic focal boost. Complete GU-subspecialists were more likely to implement focal boost, with 61% reporting routine use. In both high-income and low-to-middle-income countries, less than half of participants routinely use focal boost. The most cited barriers were concerns about registration accuracy between MRI and CT (37%), concerns about risk of additional toxicity (35%), and challenges to accessing high-quality MRI (29%). CONCLUSIONS Two years following publication of a randomized trial of patient benefit without increased toxicity, almost half of the radiation oncologists surveyed are now routinely offering focal RT boost. Further adoption of this technique might be aided by increased access to high-quality MRI, better registration algorithms of MRI to CT simulation images, physician education on benefit-to-harm ratio, and training on contouring prostate lesions on MRI.
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Affiliation(s)
- Allison Y Zhong
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA
| | - Asona J Lui
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA
| | - Matthew S Katz
- Department of Radiation Medicine, Lowell General Hospital, Lowell, MA, USA
| | - Alejandro Berlin
- Radiation Medicine Program, Princess Margaret Cancer Centre, University of Toronto, Toronto, Canada
| | - Sophia C Kamran
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Amar U Kishan
- Departments of Radiation Oncology and Urology, UCLA, Los Angeles, CA, USA
| | - Vedang Murthy
- ACTREC, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, India
| | | | - Daniel Seible
- Anchorage and Valley Radiation Therapy Centers, Anchorage, AK, USA
| | - Bradley J Stish
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN, USA
| | - Alison C Tree
- The Royal Marsden NHS Foundation Trust/The Institute of Cancer Research, London, UK
| | - Tyler M Seibert
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.
- Departments of Radiology and Bioengineering, University of California San Diego, La Jolla, CA, USA.
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Merten R, Fischer M, Christiansen H, Hellms S, von Klot CAJ, Thomas NH, Knöchelmann AC. Using a Further Planning MRI after Neoadjuvant Androgen Deprivation Therapy Significantly Reduces the Radiation Exposure of Organs at Risk in External Beam Radiotherapy of Prostate Cancer. J Clin Med 2023; 12:jcm12020574. [PMID: 36675503 PMCID: PMC9860985 DOI: 10.3390/jcm12020574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 01/01/2023] [Accepted: 01/07/2023] [Indexed: 01/13/2023] Open
Abstract
Radiotherapy for prostate cancer is often preceded by neoadjuvant androgen deprivation therapy (ADT), which leads to a reduction in the size of the prostate. This study examines whether it is relevant for treatment planning to acquire a second planning magnetic resonance imaging (MRI) after ADT (=MRI 2) or whether it can be planned without disadvantage based on an MRI acquired before starting ADT (=MRI 1). The imaging data for the radiotherapy treatment planning of 17 patients with prostate cancer who received two planning MRIs (before and after neoadjuvant ADT) were analyzed as follows: detailed comparable radiation plans were created separately, each based on the planning CT scan and either MRI 1 or MRI 2. After ADT for an average of 17.2 weeks, the prostate was reduced in size by an average of 24%. By using MRI 2 for treatment planning, the V60Gy of the rectum could be significantly relieved by an average of 15% with the same coverage of the target volume, and the V70Gy by as much as 33% (compared to using MRI 1 alone). Using a second MRI for treatment planning after neoadjuvant ADT in prostate cancer leads to a significant relief for the organs at risk, especially in the high dose range, with the same irradiation of the target volume, and should therefore be carried out regularly. Waiting for the prostate to shrink after a few months of ADT contributes to relief for the organs at risk and to lowering the toxicity. However, the use of reduced target volumes requires an image-guided application, and the oncological outcome needs to be verified in further studies.
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Affiliation(s)
- Roland Merten
- Clinic for Radiotherapy, Hannover Medical School, 30625 Hannover, Germany
- Correspondence: ; Tel.: +49-511-532-2574
| | - Mirko Fischer
- Clinic for Radiotherapy, Hannover Medical School, 30625 Hannover, Germany
| | - Hans Christiansen
- Clinic for Radiotherapy, Hannover Medical School, 30625 Hannover, Germany
| | - Susanne Hellms
- Institute for Radiology, Hannover Medical School, 30625 Hannover, Germany
| | | | - Nele Henrike Thomas
- Institute for Biostatistics, Hannover Medical School, 30625 Hannover, Germany
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Hasan MM, Mohanan P, Bibi S, Babu C, Roy YJ, Mathews A, Khatri G, Papadakos SP. Radiotherapy in Breast Cancer. INTERDISCIPLINARY CANCER RESEARCH 2023:69-95. [DOI: 10.1007/16833_2023_176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/16/2024]
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Chourak H, Barateau A, Tahri S, Cadin C, Lafond C, Nunes JC, Boue-Rafle A, Perazzi M, Greer PB, Dowling J, de Crevoisier R, Acosta O. Quality assurance for MRI-only radiation therapy: A voxel-wise population-based methodology for image and dose assessment of synthetic CT generation methods. Front Oncol 2022; 12:968689. [PMID: 36300084 PMCID: PMC9589295 DOI: 10.3389/fonc.2022.968689] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
The quality assurance of synthetic CT (sCT) is crucial for safe clinical transfer to an MRI-only radiotherapy planning workflow. The aim of this work is to propose a population-based process assessing local errors in the generation of sCTs and their impact on dose distribution. For the analysis to be anatomically meaningful, a customized interpatient registration method brought the population data to the same coordinate system. Then, the voxel-based process was applied on two sCT generation methods: a bulk-density method and a generative adversarial network. The CT and MRI pairs of 39 patients treated by radiotherapy for prostate cancer were used for sCT generation, and 26 of them with delineated structures were selected for analysis. Voxel-wise errors in sCT compared to CT were assessed for image intensities and dose calculation, and a population-based statistical test was applied to identify the regions where discrepancies were significant. The cumulative histograms of the mean absolute dose error per volume of tissue were computed to give a quantitative indication of the error for each generation method. Accurate interpatient registration was achieved, with mean Dice scores higher than 0.91 for all organs. The proposed method produces three-dimensional maps that precisely show the location of the major discrepancies for both sCT generation methods, highlighting the heterogeneity of image and dose errors for sCT generation methods from MRI across the pelvic anatomy. Hence, this method provides additional information that will assist with both sCT development and quality control for MRI-based planning radiotherapy.
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Affiliation(s)
- Hilda Chourak
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
- The Australian eHealth Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Health and Biosecurity, Brisbane, QLD, Australia
- *Correspondence: Hilda Chourak, ; Jason Dowling,
| | - Anaïs Barateau
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Safaa Tahri
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Capucine Cadin
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Caroline Lafond
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Jean-Claude Nunes
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Adrien Boue-Rafle
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Mathias Perazzi
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Peter B. Greer
- School of Mathematical and Physical Sciences, University of Newcastle, Newcastle, NSW, Australia
- Radiation Oncology, Calvary Mater Newcastle Hospital, Newcastle, NSW, Australia
| | - Jason Dowling
- The Australian eHealth Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Health and Biosecurity, Brisbane, QLD, Australia
- *Correspondence: Hilda Chourak, ; Jason Dowling,
| | - Renaud de Crevoisier
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Oscar Acosta
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
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Pham J, Savjani RR, Yoon SM, Yang T, Gao Y, Cao M, Hu P, Sheng K, Low DA, Steinberg M, Kishan A, Yang Y. Urethral Interfractional Geometric and Dosimetric Variations of Prostate Cancer Patients: A Study Using an Onboard MRI. Front Oncol 2022; 12:916254. [PMID: 35912253 PMCID: PMC9334678 DOI: 10.3389/fonc.2022.916254] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Accepted: 06/14/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose For a cohort of prostate cancer patients treated on an MR-guided radiotherapy (MRgRT) system, we retrospectively analyzed urethral interfractional geometric and dosimetric variations based on onboard MRIs acquired at different timepoints and evaluated onboard prostatic urethra visualization for urethra-focused online adaptive RT. Methods Twenty-six prostate cancer patients were prospectively scanned on a 0.35-T MRgRT system using an optimized T2-weighted HASTE sequence at simulation and final fraction. Two radiation oncologists (RO1 and RO2) contoured the urethras on all HASTE images. The simulation and final fraction HASTE images were rigidly registered, and urethral interobserver and interfractional geometric variation was evaluated using the 95th percentile Hausdorff distance (HD95), mean distance to agreement (MDA), center-of-mass shift (COMS), and DICE coefficient. For dosimetric analysis, simulation and final fraction HASTE images were registered to the 3D bSSFP planning MRI and 3D bSSFP final setup MRI, respectively. Both ROs’ urethra contours were transferred from HASTE images for initial treatment plan optimization and final fraction dose estimation separately. Stereotactic body radiotherapy (SBRT) plans, 40 Gy in 5 fractions, were optimized to meet clinical constraints, including urethral V42Gy ≤0.03 cc, on the planning MRI. The initial plan was then forward calculated on the final setup MRI to estimate urethral dose on the final fraction and evaluate urethral dosimetric impact due to anatomy change. Results The average interobserver HD95, MDA, COMS, and DICE were 2.85 ± 1.34 mm, 1.02 ± 0.36 mm, 3.16 ± 1.61 mm, and 0.58 ± 0.15, respectively. The average interfractional HD95, MDA, COMS, and DICE were 3.26 ± 1.54 mm, 1.29 ± 0.54 mm, 3.34 ± 2.01 mm, and 0.49 ± 0.18, respectively. All patient simulation MRgRT plans met all clinical constraints. For RO1 and RO2, 23/26 (88%) and 21/26 (81%) patients’ final fraction estimated urethral dose did not meet the planned constraint. The average urethral V42Gy change was 0.48 ± 0.58 cc. Conclusion Urethral interfractional motion and anatomic change can result in daily treatment violating urethral constraints. Onboard MRI with good visualization of the prostatic urethra can be a valuable tool to help better protect the urethra through patient setup or online adaptive RT.
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Affiliation(s)
- Jonathan Pham
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Ricky R. Savjani
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Stephanie M. Yoon
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Tiffany Yang
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Yu Gao
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Minsong Cao
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Peng Hu
- Department of Radiology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Ke Sheng
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Daniel A. Low
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Michael Steinberg
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Amar U. Kishan
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Urology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Yingli Yang
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States
- *Correspondence: Yingli Yang,
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Fu Y, Wang T, Lei Y, Patel P, Jani AB, Curran WJ, Liu T, Yang X. Deformable MR-CBCT prostate registration using biomechanically constrained deep learning networks. Med Phys 2020; 48:253-263. [PMID: 33164219 DOI: 10.1002/mp.14584] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 10/23/2020] [Accepted: 11/02/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND AND PURPOSE Radiotherapeutic dose escalation to dominant intraprostatic lesions (DIL) in prostate cancer could potentially improve tumor control. The purpose of this study was to develop a method to accurately register multiparametric magnetic resonance imaging (MRI) with CBCT images for improved DIL delineation, treatment planning, and dose monitoring in prostate radiotherapy. METHODS AND MATERIALS We proposed a novel registration framework which considers biomechanical constraint when deforming the MR to CBCT. The registration framework consists of two segmentation convolutional neural networks (CNN) for MR and CBCT prostate segmentation, and a three-dimensional (3D) point cloud (PC) matching network. Image intensity-based rigid registration was first performed to initialize the alignment between MR and CBCT prostate. The aligned prostates were then meshed into tetrahedron elements to generate volumetric PC representation of the prostate shapes. The 3D PC matching network was developed to predict a PC motion vector field which can deform the MRI prostate PC to match the CBCT prostate PC. To regularize the network's motion prediction with biomechanical constraints, finite element (FE) modeling-generated motion fields were used to train the network. MRI and CBCT images of 50 patients with intraprostatic fiducial markers were used in this study. Registration results were evaluated using three metrics including dice similarity coefficient (DSC), mean surface distance (MSD), and target registration error (TRE). In addition to spatial registration accuracy, Jacobian determinant and strain tensors were calculated to assess the physical fidelity of the deformation field. RESULTS The mean and standard deviation of our method were 0.93 ± 0.01, 1.66 ± 0.10 mm, and 2.68 ± 1.91 mm for DSC, MSD, and TRE, respectively. The mean TRE of the proposed method was reduced by 29.1%, 14.3%, and 11.6% as compared to image intensity-based rigid registration, coherent point drifting (CPD) nonrigid surface registration, and modality-independent neighborhood descriptor (MIND) registration, respectively. CONCLUSION We developed a new framework to accurately register the prostate on MRI to CBCT images for external beam radiotherapy. The proposed method could be used to aid DIL delineation on CBCT, treatment planning, dose escalation to DIL, and dose monitoring.
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Affiliation(s)
- Yabo Fu
- Department of Radiation Oncology, Emory University, Atlanta, GA, USA
| | - Tonghe Wang
- Department of Radiation Oncology, Emory University, Atlanta, GA, USA.,Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Yang Lei
- Department of Radiation Oncology, Emory University, Atlanta, GA, USA
| | - Pretesh Patel
- Department of Radiation Oncology, Emory University, Atlanta, GA, USA.,Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Ashesh B Jani
- Department of Radiation Oncology, Emory University, Atlanta, GA, USA.,Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Walter J Curran
- Department of Radiation Oncology, Emory University, Atlanta, GA, USA.,Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Tian Liu
- Department of Radiation Oncology, Emory University, Atlanta, GA, USA.,Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Xiaofeng Yang
- Department of Radiation Oncology, Emory University, Atlanta, GA, USA.,Winship Cancer Institute, Emory University, Atlanta, GA, USA
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Bui V, Hsu LY, Shanbhag SM, Tran L, Bandettini WP, Chang LC, Chen MY. Improving multi-atlas cardiac structure segmentation of computed tomography angiography: A performance evaluation based on a heterogeneous dataset. Comput Biol Med 2020; 125:104019. [PMID: 33038614 PMCID: PMC7655721 DOI: 10.1016/j.compbiomed.2020.104019] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 09/22/2020] [Accepted: 09/23/2020] [Indexed: 11/21/2022]
Abstract
Multi-atlas based segmentation is an effective technique that transforms a representative set of atlas images and labels into a target image for structural segmentation. However, a significant limitation of this approach relates to the fact that the atlas and the target images need to be similar in volume orientation, coverage, or acquisition protocols in order to prevent image misregistration and avoid segmentation fault. In this study, we aim to evaluate the impact of using a heterogeneous Computed Tomography Angiography (CTA) dataset on the performance of a multi-atlas cardiac structure segmentation framework. We propose a generalized technique based upon using the Simple Linear Iterative Clustering (SLIC) supervoxel method to detect a bounding box region enclosing the heart before subsequent cardiac structure segmentation. This technique facilitates our framework to process CTA datasets acquired from distinct imaging protocols and to improve its segmentation accuracy and speed. In a four-way cross comparison based on 60 CTA studies from our institution and 60 CTA datasets from the Multi-Modality Whole Heart Segmentation MICCAI challenge, we show that the proposed framework performs well in segmenting seven different cardiac structures based upon interchangeable atlas and target datasets acquired from different imaging settings. For the overall results, our automated segmentation framework attains a median Dice, mean distance, and Hausdorff distance of 0.88, 1.5 mm, and 9.69 mm over the entire datasets. The average processing time was 1.55 min for both datasets. Furthermore, this study shows that it is feasible to exploit heterogenous datasets from different imaging protocols and institutions for accurate multi-atlas cardiac structure segmentation.
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Affiliation(s)
- Vy Bui
- National Heart, Lung, And Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA; Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, 20064, USA
| | - Li-Yueh Hsu
- National Heart, Lung, And Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA; Department of Radiology and Imaging Sciences, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - Sujata M Shanbhag
- National Heart, Lung, And Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Loc Tran
- Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, 20064, USA
| | - W Patricia Bandettini
- National Heart, Lung, And Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Lin-Ching Chang
- Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, 20064, USA
| | - Marcus Y Chen
- National Heart, Lung, And Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
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Computed Tomography/Magnetic Resonance Imaging (CT/MRI) Image Registration and Fusion Assessment for Accurate Glioblastoma Radiotherapy Treatment Planning. INTERNATIONAL JOURNAL OF CANCER MANAGEMENT 2020. [DOI: 10.5812/ijcm.103160] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: In this study, computed tomography/magnetic resonance imaging (CT/MRI) image registration and fusion in the 3D conformal radiotherapy treatment planning of Glioblastoma brain tumor was investigated. Good CT/MRI image registration and fusion made a great impact on dose calculation and treatment planning accuracy. Indeed, the uncertainly associated with the registration and fusion methods must be well verified and communicated. Unfortunately, there is no standard procedure or mathematical formalism to perform this verification due to noise, distortion, and complicated anatomical situations. Objectives: This study aimed at assessing the effective contribution of MRI in Glioma radiotherapy treatment by improving the localization of target volumes and organs at risk (OARs). It is also a question to provide clinicians with some suitable metrics to evaluate the CT/MRI image registration and fusion results. Methods: Quantitative image registration and fusion evaluation were used in this study to compare Eclipse TPS tools and Elastix CT/MRI image registration fusion. Thus, Dice score coefficient (DSC), Jaccard similarity coefficient (JSC), and Hausdorff distance (HD) were found to be suitable metrics for the evaluation and comparison of the image registration and fusion methods of Eclipse TPS and Elastix. Results: The programmed tumor’s volumes (PTV) delineated on CT slices were approximately 1.38 times smaller than those delineated on CT/MRI fused images. Large differences were observed for the edema and the brainstem. It was also found that MRI considerably optimized the dose to be delivered to the optic nerve and brainstem. Conclusions: Image registration and fusion is a fundamental step for suitable and efficient Glioma treatment planning in 3D conformal radiotherapy that ensure accurate dose delivery and unnecessary OAR irradiation. MRI can provide accurate localization of targeted volumes leading to better irradiation control of Glioma tumor.
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Multiatlas Fusion with a Hybrid CT Number Correction Technique for Subject-Specific Pseudo-CT Estimation in the Context of MRI-Only Radiation Therapy. J Med Imaging Radiat Sci 2019; 50:425-440. [PMID: 31128942 DOI: 10.1016/j.jmir.2019.03.184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Revised: 02/26/2019] [Accepted: 03/07/2019] [Indexed: 11/22/2022]
Abstract
OBJECTIVE To propose a hybrid multiatlas fusion and correction approach to estimate a pseudo-computed tomography (pCT) image from T2-weighted brain magnetic resonance (MR) images in the context of MRI-only radiotherapy. MATERIALS AND METHODS A set of eleven pairs of T2-weighted MR and CT brain images was included. Using leave-one-out cross-validation, atlas MR images were registered to the target MRI with multimetric, multiresolution deformable registration. The subsequent deformations were applied to the atlas CT images, producing uncorrected pCT images. Afterward, a three-dimensional hybrid CT number correction technique was used. This technique uses information about MR intensity, spatial location, and tissue label from segmented MR images with the fuzzy c-means algorithm and combines them in a weighted fashion to correct Hounsfield unit values of the uncorrected pCT images. The corrected pCT images were then fused into a final pCT image. RESULTS The proposed hybrid approach proved to be performant in correcting Hounsfield unit values in terms of qualitative and quantitative measures. Average correlation was 0.92 and 0.91 for the proposed approach by taking the mean and the median, respectively, compared with 0.86 for the uncorrected unfused version. Average values of dice similarity coefficient for bone were 0.68 and 0.72 for the fused corrected pCT images by taking the mean and the median, respectively, compared with 0.65 for the uncorrected unfused version indicating a significant bone estimation improvement. CONCLUSION A hybrid fusion and correction method is presented to estimate a pCT image from T2-weighted brain MR images.
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Nejad‐Davarani SP, Sevak P, Moncion M, Garbarino K, Weiss S, Kim J, Schultz L, Elshaikh MA, Renisch S, Glide‐Hurst C. Geometric and dosimetric impact of anatomical changes for MR-only radiation therapy for the prostate. J Appl Clin Med Phys 2019; 20:10-17. [PMID: 30821881 PMCID: PMC6448347 DOI: 10.1002/acm2.12551] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2018] [Revised: 01/28/2019] [Accepted: 01/29/2019] [Indexed: 12/25/2022] Open
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.
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Affiliation(s)
| | - Parag Sevak
- The Cancer CenterColumbus Regional HealthColumbusINUSA
| | - Michael Moncion
- Radiation Oncology DepartmentSt. Jude Children's Research HospitalMemphisTNUSA
| | | | - Steffen Weiss
- Department of Digital ImagingPhilips Research LaboratoriesHamburgGermany
| | - Joshua Kim
- Department of Radiation OncologyHenry Ford Cancer InstituteDetroitMIUSA
| | - Lonni Schultz
- Department of Public Health SciencesHenry Ford Health SystemDetroitMIUSA
| | | | - Steffen Renisch
- Department of Digital ImagingPhilips Research LaboratoriesHamburgGermany
| | - Carri Glide‐Hurst
- Department of Radiation OncologyHenry Ford Cancer InstituteDetroitMIUSA
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Ciardo D, Jereczek-Fossa BA, Petralia G, Timon G, Zerini D, Cambria R, Rondi E, Cattani F, Bazani A, Ricotti R, Garioni M, Maestri D, Marvaso G, Romanelli P, Riboldi M, Baroni G, Orecchia R. Multimodal image registration for the identification of dominant intraprostatic lesion in high-precision radiotherapy treatments. Br J Radiol 2017; 90:20170021. [PMID: 28830203 DOI: 10.1259/bjr.20170021] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
PURPOSE The integration of CT and multiparametric MRI (mpMRI) is a challenging task in high-precision radiotherapy for prostate cancer. A simple methodology for multimodal deformable image registration (DIR) of prostate cancer patients is presented. METHODS CT and mpMRI of 10 patients were considered. Organs at risk and prostate were contoured on both scans. The dominant intraprostatic lesion was additionally delineated on MRI. After a preliminary rigid image registration, the voxel intensity of all the segmented structures in both scans except the prostate was increased by a specific amount (a constant additional value, A), in order to enhance the contrast of the main organs influencing its position and shape. 70 couples of scans were obtained by varying A from 0 to 800 and they were subsequently non-rigidly registered. Quantities derived from image analysis and contour statistics were considered for the tuning of the best performing A. RESULTS A = 200 resulted the minimum enhancement value required to obtain statistically significant superior registration results. Mean centre of mass distance between corresponding structures decreases from 7.4 mm in rigid registration to 5.3 mm in DIR without enhancement (DIR-0) and to 2.7 mm in DIR with A = 200 (DIR-200). Mean contour distance was 2.5, 1.9 and 0.67 mm in rigid registration, DIR-0 and DIR-200, respectively. In DIR-200 mean contours overlap increases of +13 and +24% with respect to DIR-0 and rigid registration, respectively. CONCLUSION Contour propagation according to the vector field resulting from DIR-200 allows the delineation of dominant intraprostatic lesion on CT scan and its use for high-precision radiotherapy treatment planning. Advances in knowledge: We investigated the application of a B-spline, mutual information-based multimodal DIR coupled with a simple, patient-unspecific but efficient contrast enhancement procedure in the pelvic body area, thus obtaining a robust and accurate methodology to transfer the functional information deriving from mpMRI onto a planning CT reference volume.
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Affiliation(s)
- Delia Ciardo
- 1 Division of Radiation Oncology, European Institute of Oncology, Milan, Italy
| | - Barbara Alicja Jereczek-Fossa
- 1 Division of Radiation Oncology, European Institute of Oncology, Milan, Italy.,2 Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy
| | - Giuseppe Petralia
- 3 Division of Radiology, European Institute of Oncology, Milan, Italy
| | - Giorgia Timon
- 1 Division of Radiation Oncology, European Institute of Oncology, Milan, Italy
| | - Dario Zerini
- 1 Division of Radiation Oncology, European Institute of Oncology, Milan, Italy
| | - Raffaella Cambria
- 4 Unit of Medical Physics, European Institute of Oncology, Milan, Italy
| | - Elena Rondi
- 4 Unit of Medical Physics, European Institute of Oncology, Milan, Italy
| | - Federica Cattani
- 4 Unit of Medical Physics, European Institute of Oncology, Milan, Italy
| | - Alessia Bazani
- 4 Unit of Medical Physics, European Institute of Oncology, Milan, Italy
| | - Rosalinda Ricotti
- 1 Division of Radiation Oncology, European Institute of Oncology, Milan, Italy
| | - Maria Garioni
- 4 Unit of Medical Physics, European Institute of Oncology, Milan, Italy
| | - Davide Maestri
- 4 Unit of Medical Physics, European Institute of Oncology, Milan, Italy
| | - Giulia Marvaso
- 1 Division of Radiation Oncology, European Institute of Oncology, Milan, Italy
| | - Paola Romanelli
- 1 Division of Radiation Oncology, European Institute of Oncology, Milan, Italy
| | - Marco Riboldi
- 5 Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Guido Baroni
- 5 Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.,6 Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica (CNAO Foundation), Pave, Italy
| | - Roberto Orecchia
- 2 Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy.,7 Department of Medical Imaging and Radiation Sciences, European Institute of Oncology, Milan, Italy
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Wang K, Mullins BT, Falchook AD, Lian J, He K, Shen D, Dance M, Lin W, Sills TM, Das SK, Huang BY, Chera BS. Evaluation of PET/MRI for Tumor Volume Delineation for Head and Neck Cancer. Front Oncol 2017; 7:8. [PMID: 28168166 PMCID: PMC5253486 DOI: 10.3389/fonc.2017.00008] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Accepted: 01/09/2017] [Indexed: 12/20/2022] Open
Abstract
Introduction Computed tomography (CT), combined positron emitted tomography and CT (PET/CT), and magnetic resonance imaging (MRI) are commonly used in head and neck radiation planning. Hybrid PET/MRI has garnered attention for potential added value in cancer staging and treatment planning. Herein, we compare PET/MRI vs. planning CT for head and neck cancer gross tumor volume (GTV) delineation. Material and methods We prospectively enrolled patients with head and neck cancer treated with definitive chemoradiation to 60–70 Gy using IMRT. We performed pretreatment contrast-enhanced planning CT and gadolinium-enhanced PET/MRI. Primary and nodal volumes were delineated on planning CT (GTV-CT) prospectively before treatment and PET/MRI (GTV-PET/MRI) retrospectively after treatment. GTV-PET/MRI was compared to GTV-CT using separate rigid registrations for each tumor volume. The Dice similarity coefficient (DSC) metric evaluating spatial overlap and modified Hausdorff distance (mHD) evaluating mean orthogonal distance difference were calculated. Minimum dose to 95% of GTVs (D95) was compared. Results Eleven patients were evaluable (10 oropharynx, 1 larynx). Nine patients had evaluable primary tumor GTVs and seven patients had evaluable nodal GTVs. Mean primary GTV-CT and GTV-PET/MRI size were 13.2 and 14.3 cc, with mean intersection 8.7 cc, DSC 0.63, and mHD 1.6 mm. D95 was 65.3 Gy for primary GTV-CT vs. 65.2 Gy for primary GTV-PET/MRI. Mean nodal GTV-CT and GTV-PET/MRI size were 19.0 and 23.0 cc, with mean intersection 14.4 cc, DSC 0.69, and mHD 2.3 mm. D95 was 62.3 Gy for both nodal GTV-CT and GTV-PET/MRI. Conclusion In this series of patients with head and neck (primarily oropharynx) cancer, PET/MRI and CT-GTVs had similar volumes (though there were individual cases with larger differences) with overall small discrepancies in spatial overlap, small mean orthogonal distance differences, and similar radiation doses.
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Affiliation(s)
- Kyle Wang
- Department of Radiation Oncology, University of North Carolina Hospitals , Chapel Hill, NC , USA
| | - Brandon T Mullins
- Department of Radiation Oncology, University of North Carolina Hospitals , Chapel Hill, NC , USA
| | - Aaron D Falchook
- Department of Radiation Oncology, University of North Carolina Hospitals , Chapel Hill, NC , USA
| | - Jun Lian
- Department of Radiation Oncology, University of North Carolina Hospitals , Chapel Hill, NC , USA
| | - Kelei He
- State Key Laboratory for Novel Software Technology, Nanjing University , Nanjing , China
| | - Dinggang Shen
- Department of Radiology, University of North Carolina Hospitals , Chapel Hill, NC , USA
| | - Michael Dance
- Department of Radiation Oncology, University of North Carolina Hospitals , Chapel Hill, NC , USA
| | - Weili Lin
- Department of Radiology, University of North Carolina Hospitals , Chapel Hill, NC , USA
| | - Tiffany M Sills
- Department of Radiology, University of North Carolina Hospitals , Chapel Hill, NC , USA
| | - Shiva K Das
- Department of Radiation Oncology, University of North Carolina Hospitals , Chapel Hill, NC , USA
| | - Benjamin Y Huang
- Department of Radiology, University of North Carolina Hospitals , Chapel Hill, NC , USA
| | - Bhishamjit S Chera
- Department of Radiation Oncology, University of North Carolina Hospitals , Chapel Hill, NC , USA
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