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Buti G, Ajdari A, Hochreuter K, Shih H, Bridge CP, Sharp GC, Bortfeld T. The influence of anisotropy on the clinical target volume of brain tumor patients. Phys Med Biol 2024; 69:10.1088/1361-6560/ad1997. [PMID: 38157552 PMCID: PMC10863979 DOI: 10.1088/1361-6560/ad1997] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 12/29/2023] [Indexed: 01/03/2024]
Abstract
Objective.Current radiotherapy guidelines for glioma target volume definition recommend a uniform margin expansion from the gross tumor volume (GTV) to the clinical target volume (CTV), assuming uniform infiltration in the invaded brain tissue. However, glioma cells migrate preferentially along white matter tracts, suggesting that white matter directionality should be considered in an anisotropic CTV expansion. We investigate two models of anisotropic CTV expansion and evaluate their clinical feasibility.Approach.To incorporate white matter directionality into the CTV, a diffusion tensor imaging (DTI) atlas is used. The DTI atlas consists of water diffusion tensors that are first spatially transformed into local tumor resistance tensors, also known as metric tensors, and secondly fed to a CTV expansion algorithm to generate anisotropic CTVs. Two models of spatial transformation are considered in the first step. The first model assumes that tumor cells experience reduced resistance parallel to the white matter fibers. The second model assumes that the anisotropy of tumor cell resistance is proportional to the anisotropy observed in DTI, with an 'anisotropy weighting parameter' controlling the proportionality. The models are evaluated in a cohort of ten brain tumor patients.Main results.To evaluate the sensitivity of the model, a library of model-generated CTVs was computed by varying the resistance and anisotropy parameters. Our results indicate that the resistance coefficient had the most significant effect on the global shape of the CTV expansion by redistributing the target volume from potentially less involved gray matter to white matter tissue. In addition, the anisotropy weighting parameter proved useful in locally increasing CTV expansion in regions characterized by strong tissue directionality, such as near the corpus callosum.Significance.By incorporating anisotropy into the CTV expansion, this study is a step toward an interactive CTV definition that can assist physicians in incorporating neuroanatomy into a clinically optimized CTV.
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Affiliation(s)
- Gregory Buti
- Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Division of Radiation Biophysics, 100 Blossom St, Boston, MA 02114, United States of America
| | - Ali Ajdari
- Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Division of Radiation Biophysics, 100 Blossom St, Boston, MA 02114, United States of America
| | - Kim Hochreuter
- Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Division of Radiation Biophysics, 100 Blossom St, Boston, MA 02114, United States of America
- Aarhus University Hospital, Danish Centre for Particle Therapy, Palle Juul-Jensens Blvd. 99, DK-8200 Aarhus, Denmark
- Aarhus University, Department of Clinical Medicine, Palle Juul-Jensens Blvd. 82, DK-8200 Aarhus, Denmark
| | - Helen Shih
- Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, 100 Blossom St, Boston, MA 02114, United States of America
| | - Christopher P Bridge
- Massachusetts General Hospital and Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, 149 Thirteenth St, Charlestown, MA 02129, United States of America
| | - Gregory C Sharp
- Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Division of Radiation Biophysics, 100 Blossom St, Boston, MA 02114, United States of America
| | - Thomas Bortfeld
- Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Division of Radiation Biophysics, 100 Blossom St, Boston, MA 02114, United States of America
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Saraf A, Tahir I, Hu B, Dietrich ASW, Tonnesen PE, Sharp GC, Tillman G, Roeland EJ, Nipp RD, Comander A, Peppercorn J, Fintelmann FJ, Jimenez RB. Association of Sarcopenia With Toxicity-Related Discontinuation of Adjuvant Endocrine Therapy in Women With Early-Stage Hormone Receptor-Positive Breast Cancer. Int J Radiat Oncol Biol Phys 2024; 118:94-103. [PMID: 37506979 DOI: 10.1016/j.ijrobp.2023.07.018] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/27/2023] [Accepted: 07/14/2023] [Indexed: 07/30/2023]
Abstract
PURPOSE Sarcopenia, an age-related decline in muscle mass and physical function, is associated with increased toxicity and worse outcomes in women with breast cancer (BC). Sarcopenia may contribute to toxicity-related early discontinuation of adjuvant endocrine therapy (aET) in women with hormone receptor-positive (HR+) BC but remains poorly characterized. METHODS AND MATERIALS This multicenter, retrospective cohort study included consecutive women with stage 0-II HR+ BC who received breast conserving therapy (lumpectomy and radiation therapy) and aET from 2011 to 2017 with a 5-year follow-up. Skeletal muscle index (SMI, cm2/m2) was analyzed using a deep learning model on routine cross-sectional radiation simulation imaging; sarcopenia was dichotomized according to previously validated reports. The primary endpoint was toxicity-related aET discontinuation; logistic regression analysis evaluated associations between SMI/sarcopenia and aET discontinuation. Cox regression analysis evaluated associations with time to aET toxicity, ipsilateral breast tumor recurrence (IBTR), and disease-free survival (DFS). RESULTS A total of 305 women (median follow-up, 89 months) were included with a median age of 67 years and early-stage BC (12% stage 0, 65% stage I). A total of 60 (20%) women experienced toxicity-related aET discontinuation. Sarcopenia was associated with toxicity-related early discontinuation of aET (odds ratio, 2.18; P = .036) and shorter time to aET toxicity (hazard ratio [HR], 1.62; P = .031). SMI or sarcopenia were not independently associated with IBTR or DFS; toxicity-related aET discontinuation was associated with worse IBTR (HR, 9.47; P = .002) and worse DFS (HR, 4.53; P = .001). CONCLUSIONS Among women with early-stage HR+ BC who receive adjuvant radiation therapy and hormone therapy, sarcopenia is associated with toxicity-related early discontinuation of aET. Further studies should validate these findings in women who did not receive adjuvant radiation therapy. These high-risk patients may be candidates for aggressive symptom management and/or alternative treatment strategies to improve outcomes.
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Affiliation(s)
- Anurag Saraf
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts.
| | - Ismail Tahir
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Bonnie Hu
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | | | - P Erik Tonnesen
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Gayle Tillman
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Eric J Roeland
- Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Ryan D Nipp
- Department of Medical Oncology, University of Oklahoma Stephenson Cancer Center, Oklahoma City, Oklahoma
| | - Amy Comander
- Department of Medical Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Jeffery Peppercorn
- Department of Medical Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | | | - Rachel B Jimenez
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
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Mayo CS, Feng MU, Brock KK, Kudner R, Balter P, Buchsbaum JC, Caissie A, Covington E, Daugherty EC, Dekker AL, Fuller CD, Hallstrom AL, Hong DS, Hong JC, Kamran SC, Katsoulakis E, Kildea J, Krauze AV, Kruse JJ, McNutt T, Mierzwa M, Moreno A, Palta JR, Popple R, Purdie TG, Richardson S, Sharp GC, Satomi S, Tarbox LR, Venkatesan AM, Witztum A, Woods KE, Yao Y, Farahani K, Aneja S, Gabriel PE, Hadjiiski L, Ruan D, Siewerdsen JH, Bratt S, Casagni M, Chen S, Christodouleas JC, DiDonato A, Hayman J, Kapoor R, Kravitz S, Sebastian S, Von Siebenthal M, Bosch W, Hurkmans C, Yom SS, Xiao Y. Operational Ontology for Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data From Patients Treated for Cancer. Int J Radiat Oncol Biol Phys 2023; 117:533-550. [PMID: 37244628 PMCID: PMC10741247 DOI: 10.1016/j.ijrobp.2023.05.033] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 05/17/2023] [Accepted: 05/19/2023] [Indexed: 05/29/2023]
Abstract
PURPOSE The ongoing lack of data standardization severely undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), radiation oncology information systems, treatment planning systems, and other cancer care and outcomes databases. We sought to create a standardized ontology for clinical data, social determinants of health, and other radiation oncology concepts and interrelationships. METHODS AND MATERIALS The American Association of Physicists in Medicine's Big Data Science Committee was initiated in July 2019 to explore common ground from the stakeholders' collective experience of issues that typically compromise the formation of large inter- and intra-institutional databases from EHRs. The Big Data Science Committee adopted an iterative, cyclical approach to engaging stakeholders beyond its membership to optimize the integration of diverse perspectives from the community. RESULTS We developed the Operational Ontology for Oncology (O3), which identified 42 key elements, 359 attributes, 144 value sets, and 155 relationships ranked in relative importance of clinical significance, likelihood of availability in EHRs, and the ability to modify routine clinical processes to permit aggregation. Recommendations are provided for best use and development of the O3 to 4 constituencies: device manufacturers, centers of clinical care, researchers, and professional societies. CONCLUSIONS O3 is designed to extend and interoperate with existing global infrastructure and data science standards. The implementation of these recommendations will lower the barriers for aggregation of information that could be used to create large, representative, findable, accessible, interoperable, and reusable data sets to support the scientific objectives of grant programs. The construction of comprehensive "real-world" data sets and application of advanced analytical techniques, including artificial intelligence, holds the potential to revolutionize patient management and improve outcomes by leveraging increased access to information derived from larger, more representative data sets.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Dan Ruan
- University of California, Los Angeles
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- University of California, San Francisco
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Nenoff L, Sudhyadhom A, Lau J, Sharp GC, Paganetti H, Pursley J. Comparing Predicted Toxicities between Hypofractionated Proton and Photon Radiotherapy of Liver Cancer Patients with Different Adaptive Schemes. Cancers (Basel) 2023; 15:4592. [PMID: 37760560 PMCID: PMC10526201 DOI: 10.3390/cancers15184592] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 08/30/2023] [Accepted: 09/11/2023] [Indexed: 09/29/2023] Open
Abstract
With the availability of MRI linacs, online adaptive intensity modulated radiotherapy (IMRT) has become a treatment option for liver cancer patients, often combined with hypofractionation. Intensity modulated proton therapy (IMPT) has the potential to reduce the dose to healthy tissue, but it is particularly sensitive to changes in the beam path and might therefore benefit from online adaptation. This study compares the normal tissue complication probabilities (NTCPs) for liver and duodenal toxicity for adaptive and non-adaptive IMRT and IMPT treatments of liver cancer patients. Adaptive and non-adaptive IMRT and IMPT plans were optimized to 50 Gy (RBE = 1.1 for IMPT) in five fractions for 10 liver cancer patients, using the original MRI linac images and physician-drawn structures. Three liver NTCP models were used to predict radiation-induced liver disease, an increase in albumin-bilirubin level, and a Child-Pugh score increase of more than 2. Additionally, three duodenal NTCP models were used to predict gastric bleeding, gastrointestinal (GI) toxicity with grades >3, and duodenal toxicity grades 2-4. NTCPs were calculated for adaptive and non-adaptive IMRT and IMPT treatments. In general, IMRT showed higher NTCP values than IMPT and the differences were often significant. However, the differences between adaptive and non-adaptive treatment schemes were not significant, indicating that the NTCP benefit of adaptive treatment regimens is expected to be smaller than the expected difference between IMRT and IMPT.
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Affiliation(s)
- Lena Nenoff
- Harvard Medical School, Boston, MA 02114, USA (J.P.)
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Atchar Sudhyadhom
- Harvard Medical School, Boston, MA 02114, USA (J.P.)
- Radiation Oncology, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Jackson Lau
- Harvard Medical School, Boston, MA 02114, USA (J.P.)
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Gregory C. Sharp
- Harvard Medical School, Boston, MA 02114, USA (J.P.)
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Harald Paganetti
- Harvard Medical School, Boston, MA 02114, USA (J.P.)
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jennifer Pursley
- Harvard Medical School, Boston, MA 02114, USA (J.P.)
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, USA
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Lalonde A, Bobić M, Sharp GC, Chamseddine I, Winey B, Paganetti H. Evaluating the effect of setup uncertainty reduction and adaptation to geometric changes on normal tissue complication probability using online adaptive head and neck intensity modulated proton therapy. Phys Med Biol 2023; 68:115018. [PMID: 37164020 PMCID: PMC10351361 DOI: 10.1088/1361-6560/acd433] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 05/03/2023] [Accepted: 05/10/2023] [Indexed: 05/12/2023]
Abstract
Objective. To evaluate the impact of setup uncertainty reduction (SUR) and adaptation to geometrical changes (AGC) on normal tissue complication probability (NTCP) when using online adaptive head and neck intensity modulated proton therapy (IMPT).Approach.A cohort of ten retrospective head and neck cancer patients with daily scatter corrected cone-beam CT (CBCT) was studied. For each patient, two IMPT treatment plans were created: one with a 3 mm setup uncertainty robustness setting and one with no explicit setup robustness. Both plans were recalculated on the daily CBCT considering three scenarios: the robust plan without adaptation, the non-robust plan without adaptation and the non-robust plan with daily online adaptation. Online-adaptation was simulated using an in-house developed workflow based on GPU-accelerated Monte Carlo dose calculation and partial spot-intensity re-optimization. Dose distributions associated with each scenario were accumulated on the planning CT, where NTCP models for six toxicities were applied. NTCP values from each scenario were intercompared to quantify the reduction in toxicity risk induced by SUR alone, AGC alone and SUR and AGC combined. Finally, a decision tree was implemented to assess the clinical significance of the toxicity reduction associated with each mechanism.Main results. For most patients, clinically meaningful NTCP reductions were only achieved when SUR and AGC were performed together. In these conditions, total reductions in NTCP of up to 30.48 pp were obtained, with noticeable NTCP reductions for aspiration, dysphagia and xerostomia (mean reductions of 8.25, 5.42 and 5.12 pp respectively). While SUR had a generally larger impact than AGC on NTCP reductions, SUR alone did not induce clinically meaningful toxicity reductions in any patient, compared to only one for AGC alone.SignificanceOnline adaptive head and neck proton therapy can only yield clinically significant reductions in the risk of long-term side effects when combining the benefits of SUR and AGC.
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Affiliation(s)
- Arthur Lalonde
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Mislav Bobić
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- ETH Zürich, Zürich, Switzerland
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Ibrahim Chamseddine
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Brian Winey
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
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Salari E, Mazur TR, Sharp GC. A stochastic control approach to intrafraction motion management in intensity-modulated radiotherapy. Phys Med Biol 2023; 68. [PMID: 36944246 DOI: 10.1088/1361-6560/acc631] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 03/21/2023] [Indexed: 03/23/2023]
Abstract
OBJECTIVE The goal of this research is to demonstrate proof-of-principle for managing intrafraction motion via feedback control of delivered dose to achieve dosimetry comparable to respiratory gating without compromising delivery efficiency. APPROACH We develop a stochastic control approach for step-and-shoot intensity-modulated radiotherapy (IMRT) in which the cumulative delivered dose and future trajectory of intrafraction motion are dynamically estimated by combining pre-treatment four-dimensional computed tomography (4D-CT) imaging and intrafraction respiratory-motion surrogates. The IMRT plan is then re-optimized in real time to ensure delivery of the planned dose in the presence of free-breathing motion. We compare the performance of the proposed approach against traditional motion-management techniques, namely, respiratory gating and internal target volume (ITV) planning, using the four-dimensional extended cardiac-torso (4D-XCAT) computational phantom. MAIN RESULTS We simulate the delivery of treatment plans for a lung tumor in the presence of variable breathing amplitude, tumor size, and location. Results show that the proposed method reduces irradiated tissue volume compared to ITV treatment. Additionally, it significantly reduces treatment time compared to traditional respiratory-gated treatment, without compromising the dosimetric quality. SIGNIFICANCE Respiratory gating is a common technique to manage intra-fraction motion. While gating supports reduced treatment volumes, it also prolongs the treatment delivery time. The proposed stochastic control approach can help improve the delivery efficiency of respiratory gating without compromising the dose quality.
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Affiliation(s)
- Ehsan Salari
- Industrial Engineering, Wichita State University, 1845 N Fairmount, Wichita, Kansas, 67220, UNITED STATES
| | - Thomas R Mazur
- Radiation Oncology, Washington University in Saint Louis School of Medicine, 660 S. Euclid Ave, MSC 8224-35-LL, Saint Louis, Missouri, 63110, UNITED STATES
| | - Gregory C Sharp
- Dept of Radiation Oncology, Massachusetts General Hospital, 100 Blossom Street, Cox Building, 302, Boston, MA 02114, USA, Boston, 02114, UNITED STATES
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Bobić M, Lalonde A, Nesteruk KP, Lee H, Nenoff L, Gorissen BL, Bertolet A, Busse PM, Chan AW, Winey BA, Sharp GC, Verburg JM, Lomax AJ, Paganetti H. Large anatomical changes in head-and-neck cancers – a dosimetric comparison of online and offline adaptive proton therapy. Clin Transl Radiat Oncol 2023; 40:100625. [PMID: 37090849 PMCID: PMC10120292 DOI: 10.1016/j.ctro.2023.100625] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 03/30/2023] [Indexed: 04/03/2023] Open
Abstract
Purpose This work evaluates an online adaptive (OA) workflow for head-and-neck (H&N) intensity-modulated proton therapy (IMPT) and compares it with full offline replanning (FOR) in patients with large anatomical changes. Methods IMPT treatment plans are created retrospectively for a cohort of eight H&N cancer patients that previously required replanning during the course of treatment due to large anatomical changes. Daily cone-beam CTs (CBCT) are acquired and corrected for scatter, resulting in 253 analyzed fractions. To simulate the FOR workflow, nominal plans are created on the planning-CT and delivered until a repeated-CT is acquired; at this point, a new plan is created on the repeated-CT. To simulate the OA workflow, nominal plans are created on the planning-CT and adapted at each fraction using a simple beamlet weight-tuning technique. Dose distributions are calculated on the CBCTs with Monte Carlo for both delivery methods. The total treatment dose is accumulated on the planning-CT. Results Daily OA improved target coverage compared to FOR despite using smaller target margins. In the high-risk CTV, the median D98 degradation was 1.1 % and 2.1 % for OA and FOR, respectively. In the low-risk CTV, the same metrics yield 1.3 % and 5.2 % for OA and FOR, respectively. Smaller setup margins of OA reduced the dose to all OARs, which was most relevant for the parotid glands. Conclusion Daily OA can maintain prescription doses and constraints over the course of fractionated treatment, even in cases of large anatomical changes, reducing the necessity for manual replanning in H&N IMPT.
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Nesteruk KP, Bobić M, Sharp GC, Lalonde A, Winey BA, Nenoff L, Lomax AJ, Paganetti H. Low-Dose Computed Tomography Scanning Protocols for Online Adaptive Proton Therapy of Head-and-Neck Cancers. Cancers (Basel) 2022; 14:cancers14205155. [PMID: 36291939 PMCID: PMC9600085 DOI: 10.3390/cancers14205155] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 10/15/2022] [Accepted: 10/19/2022] [Indexed: 01/11/2023] Open
Abstract
PURPOSE To evaluate the suitability of low-dose CT protocols for online plan adaptation of head-and-neck patients. METHODS We acquired CT scans of a head phantom with protocols corresponding to CT dose index volume CTDIvol in the range of 4.2-165.9 mGy. The highest value corresponds to the standard protocol used for CT simulations of 10 head-and-neck patients included in the study. The minimum value corresponds to the lowest achievable tube current of the GE Discovery RT scanner used for the study. For each patient and each low-dose protocol, the noise relative to the standard protocol, derived from phantom images, was applied to a virtual CT (vCT). The vCT was obtained from a daily CBCT scan corresponding to the fraction with the largest anatomical changes. We ran an established adaptive workflow twice for each low-dose protocol using a high-quality daily vCT and the corresponding low-dose synthetic vCT. For a relative comparison of the adaptation efficacy, two adapted plans were recalculated in the high-quality vCT and evaluated with the contours obtained through deformable registration of the planning CT. We also evaluated the accuracy of dose calculation in low-dose CT volumes using the standard CT protocol as reference. RESULTS The maximum differences in D98 between low-dose protocols and the standard protocol for the high-risk and low-risk CTV were found to be 0.6% and 0.3%, respectively. The difference in OAR sparing was up to 3%. The Dice similarity coefficient between propagated contours obtained with low-dose and standard protocols was above 0.982. The mean 2%/2 mm gamma pass rate for the lowest-dose image, using the standard protocol as reference, was found to be 99.99%. CONCLUSION The differences between low-dose protocols and the standard scanning protocol were marginal. Thus, low-dose CT protocols are suitable for online adaptive proton therapy of head-and-neck cancers. As such, considering scanning protocols used in our clinic, the imaging dose associated with online adaption of head-and-neck cancers treated with protons can be reduced by a factor of 40.
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Affiliation(s)
- Konrad P. Nesteruk
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Correspondence:
| | - Mislav Bobić
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Physics, ETH Zurich, CH-8093 Zurich, Switzerland
| | - Gregory C. Sharp
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Arthur Lalonde
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Brian A. Winey
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Lena Nenoff
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Antony J. Lomax
- Department of Physics, ETH Zurich, CH-8093 Zurich, Switzerland
- Center for Proton Therapy, Paul Scherrer Institute, CH-5232 Villigen, Switzerland
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
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Taeubert MJ, de Prado-Bert P, Geurtsen ML, Mancano G, Vermeulen MJ, Reiss IKM, Caramaschi D, Sunyer J, Sharp GC, Julvez J, Muckenthaler MU, Felix JF. Maternal iron status in early pregnancy and DNA methylation in offspring: an epigenome-wide meta-analysis. Clin Epigenetics 2022; 14:59. [PMID: 35505416 PMCID: PMC9066980 DOI: 10.1186/s13148-022-01276-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 04/11/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Unbalanced iron homeostasis in pregnancy is associated with an increased risk of adverse birth and childhood health outcomes. DNA methylation has been suggested as a potential underlying mechanism linking environmental exposures such as micronutrient status during pregnancy with offspring health. We performed a meta-analysis on the association of maternal early-pregnancy serum ferritin concentrations, as a marker of body iron stores, and cord blood DNA methylation. We included 1286 mother-newborn pairs from two population-based prospective cohorts. Serum ferritin concentrations were measured in early pregnancy. DNA methylation was measured with the Infinium HumanMethylation450 BeadChip (Illumina). We examined epigenome-wide associations of maternal early-pregnancy serum ferritin and cord blood DNA methylation using robust linear regression analyses, with adjustment for confounders and performed fixed-effects meta-analyses. We additionally examined whether associations of any CpGs identified in cord blood persisted in the peripheral blood of older children and explored associations with other markers of maternal iron status. We also examined whether similar findings were present in the association of cord blood serum ferritin concentrations with cord blood DNA methylation. RESULTS Maternal early-pregnancy serum ferritin concentrations were inversely associated with DNA methylation at two CpGs (cg02806645 and cg06322988) in PRR23A and one CpG (cg04468817) in PRSS22. Associations at two of these CpG sites persisted at each of the follow-up time points in childhood. Cord blood serum ferritin concentrations were not associated with cord blood DNA methylation levels at the three identified CpGs. CONCLUSION Maternal early-pregnancy serum ferritin concentrations were associated with lower cord blood DNA methylation levels at three CpGs and these associations partly persisted in older children. Further studies are needed to uncover the role of these CpGs in the underlying mechanisms of the associations of maternal iron status and offspring health outcomes.
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Affiliation(s)
- M J Taeubert
- The Generation R Study Group, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Pediatric Oncology, Hematology and Immunology, University Medical Center Heidelberg, Heidelberg, Germany
| | - P de Prado-Bert
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - M L Geurtsen
- The Generation R Study Group, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Pediatrics, Sophia's Children's Hospital, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - G Mancano
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School Population Health Sciences, University of Bristol, Bristol, UK
| | - M J Vermeulen
- Department of Pediatrics, Sophia's Children's Hospital, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - I K M Reiss
- Department of Pediatrics, Sophia's Children's Hospital, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - D Caramaschi
- College of Life and Environmental Sciences, Psychology, University of Exeter, Exeter, UK
| | - J Sunyer
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - G C Sharp
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School Population Health Sciences, University of Bristol, Bristol, UK
- School of Oral and Dental Sciences, University of Bristol, Bristol, UK
| | - J Julvez
- ISGlobal, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Institut d'Investigació Sanitària Pere Virgili, Hospital Universitari Sant Joan de Reus, Reus, Spain
| | - M U Muckenthaler
- Department of Pediatric Oncology, Hematology and Immunology, University Medical Center Heidelberg, Heidelberg, Germany
| | - J F Felix
- The Generation R Study Group, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.
- Department of Pediatrics, Sophia's Children's Hospital, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
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Clasie BM, Bortfeld TR, Kooy HM, Seybolt K, Sharp GC, Winey B. Retrofitting LINAC Vaults for Compact Proton Systems—Experiences Learned. IEEE Trans Radiat Plasma Med Sci 2022. [DOI: 10.1109/trpms.2021.3083982] [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: 11/05/2022]
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Abstract
Radiation therapy treatments are typically planned based on a single image set, assuming that the patient's anatomy and its position relative to the delivery system remains constant during the course of treatment. Similarly, the prescription dose assumes constant biological dose-response over the treatment course. However, variations can and do occur on multiple time scales. For treatment sites with significant intra-fractional motion, geometric changes happen over seconds or minutes, while biological considerations change over days or weeks. At an intermediate timescale, geometric changes occur between daily treatment fractions. Adaptive radiation therapy is applied to consider changes in patient anatomy during the course of fractionated treatment delivery. While traditionally adaptation has been done off-line with replanning based on new CT images, online treatment adaptation based on on-board imaging has gained momentum in recent years due to advanced imaging techniques combined with treatment delivery systems. Adaptation is particularly important in proton therapy where small changes in patient anatomy can lead to significant dose perturbations due to the dose conformality and finite range of proton beams. This review summarizes the current state-of-the-art of on-line adaptive proton therapy and identifies areas requiring further research.
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Affiliation(s)
- Harald Paganetti
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Pablo Botas
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Foundation 29 of February, Pozuelo de Alarcón, Madrid, Spain
| | - Gregory C Sharp
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Brian Winey
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
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12
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Lalonde A, Winey B, Verburg J, Paganetti H, Sharp GC. Erratum: Evaluation of CBCT scatter correction using deep convolutional neural networks for head and neck adaptive proton therapy (2020 Phys. Med. Biol.65245022). Phys Med Biol 2021; 66. [PMID: 34190689 DOI: 10.1088/1361-6560/ac0cc2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 06/18/2021] [Indexed: 11/11/2022]
Affiliation(s)
- Arthur Lalonde
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Brian Winey
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Joost Verburg
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
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13
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Lalonde A, Bobić M, Winey B, Verburg J, Sharp GC, Paganetti H. Anatomic changes in head and neck intensity-modulated proton therapy: Comparison between robust optimization and online adaptation. Radiother Oncol 2021; 159:39-47. [PMID: 33741469 PMCID: PMC8205952 DOI: 10.1016/j.radonc.2021.03.008] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [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: 11/06/2020] [Revised: 03/08/2021] [Accepted: 03/08/2021] [Indexed: 11/18/2022]
Abstract
BACKGROUND/PURPOSE Setup variations and anatomical changes can severely affect the quality of head and neck intensity-modulated proton therapy (IMPT) treatments. The impact of these changes can be alleviated by increasing the plan's robustness a priori, or by adapting the plan online. This work compares these approaches in the context of head and neck IMPT. MATERIALS/METHODS A representative cohort of 10 head and neck squamous cell carcinoma (HNSCC) patients with daily cone-beam computed tomography (CBCT) was evaluated. For each patient, three IMPT plans were created: 1- a classical robust optimization (cRO) plan optimized on the planning CT, 2- an anatomical robust optimization (aRO) plan additionally including the two first daily CBCTs and 3- a plan optimized without robustness constraints, but online-adapted (OA) daily, using a constrained spot intensity re-optimization technique only. RESULTS The cumulative dose following OA fulfilled the clinical objective of both the high-risk and low-risk clinical target volumes (CTV) coverage in all 10 patients, compared to 8 for aRO and 4 for cRO. aRO did not significantly increase the dose to most organs at risk compared to cRO, although the integral dose was higher. OA significantly reduced the integral dose to healthy tissues compared to both robust methods, while providing equivalent or superior target coverage. CONCLUSION Using a simple spot intensity re-optimization, daily OA can achieve superior target coverage and lower dose to organs at risk than robust optimization methods.
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Affiliation(s)
- Arthur Lalonde
- Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, USA.
| | - Mislav Bobić
- Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, USA; ETH Zürich, Zürich, Switzerland
| | - Brian Winey
- Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, USA
| | - Joost Verburg
- Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, USA
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, USA
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, USA
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14
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Shah KD, Shackleford JA, Kandasamy N, Sharp GC. A generalized framework for analytic regularization of uniform cubic B-spline displacement fields. Biomed Phys Eng Express 2021; 7. [PMID: 33878749 DOI: 10.1088/2057-1976/abf9e6] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 04/20/2021] [Indexed: 11/11/2022]
Abstract
Image registration is an inherently ill-posed problem that lacks the constraints needed for a unique mapping between voxels of the two images being registered. As such, one must regularize the registration to achieve physically meaningful transforms. The regularization penalty is usually a function of derivatives of the displacement-vector field and can be calculated either analytically or numerically. The numerical approach, however, is computationally expensive depending on the image size, and therefore a computationally efficient analytical framework has been developed. Using cubic B-splines as the registration transform, we develop a generalized mathematical framework that supports five distinct regularizers: diffusion, curvature, linear elastic, third-order, and total displacement. We validate our approach by comparing each with its numerical counterpart in terms of accuracy. We also provide benchmarking results showing that the analytic solutions run significantly faster-up to two orders of magnitude-than finite differencing based numerical implementations.
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Affiliation(s)
- Keyur D Shah
- Electrical and Computer Engineering Department, Drexel University, Philadelphia, PA 19104, United States of America
| | - James A Shackleford
- Electrical and Computer Engineering Department, Drexel University, Philadelphia, PA 19104, United States of America
| | - Nagarajan Kandasamy
- Electrical and Computer Engineering Department, Drexel University, Philadelphia, PA 19104, United States of America
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, United States of America
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15
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Abstract
The dosimetric advantages of particle therapy lead to significantly reduced integral dose to normal tissues, making it an attractive treatment option for body sites such as the thorax. With reduced normal tissue dose comes the potential for dose escalation, toxicity reduction, or hypofractionation. While proton and heavy ion therapy have been used extensively for NSCLC, there are challenges in planning and delivery compared with X-ray-based radiation therapy. Particularly, range uncertainties compounded by breathing motion have to be considered. This article summarizes the current state of particle therapy for NSCLC with a specific focus on the impact of dosimetric uncertainties in planning and delivery.
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Affiliation(s)
- Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA.
| | - Clemens Grassberger
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
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Bobić M, Lalonde A, Sharp GC, Grassberger C, Verburg JM, Winey BA, Lomax AJ, Paganetti H. Comparison of weekly and daily online adaptation for head and neck intensity-modulated proton therapy. Phys Med Biol 2021; 66. [PMID: 33503592 DOI: 10.1088/1361-6560/abe050] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [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: 11/20/2020] [Accepted: 01/27/2021] [Indexed: 12/11/2022]
Abstract
The high conformality of intensity-modulated proton therapy (IMPT) dose distributions causes treatment plans to be sensitive to geometrical changes during the course of a fractionated treatment. This can be addressed using adaptive proton therapy (APT). One important question in APT is the frequency of adaptations performed during a fractionated treatment, which is related to the question whether plan adaptation has to be done online or offline. The purpose of this work is to investigate the impact of weekly and daily online IMPT plan adaptation on the treatment quality for head and neck patients. A cohort of ten head and neck patients with daily acquired cone-beam CT (CBCT) images was evaluated retrospectively. Dose tracking of the IMPT treatment was performed for three scenarios: base plan with no adaptation (BP), weekly online adaptation (OAW), and daily online adaptation (OAD). Both adaptation schemes used an in-house developed online APT workflow, performing Monte Carlo (MC) dose calculations on scatter-corrected CBCTs. IMPT plan adaptation was achieved by only tuning the weights of a subset of beamlets, based on deformable image registration from the planning CT to each CBCT. Although OADmitigated random delivery errors more effectively than OAWon a fraction per fraction basis, both OAWand OADachieved the clinical goals for all ten patients, while BP failed for six cases. In the high-risk CTV, accumulated values of D98%ranged between 97.15% and 99.73% of the prescription dose for OAD, with a median of 98.07%. For OAW, values between 95.02% and 99.26% were obtained, with a median of 97.61% of the prescription dose. Otherwise, the dose to most organs at risk was similar for all three scenarios. Globally, our results suggest that OAWcould be used as an alternative approach to OADfor most patients in order to reduce the clinical workload.
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Affiliation(s)
- Mislav Bobić
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts, UNITED STATES
| | - Arthur Lalonde
- Radiation-Oncology, Massachusetts General Hospital, Boston, Massachusetts, 02114-2696, UNITED STATES
| | - Gregory C Sharp
- Dept of Radiation Oncology, Massachusetts General Hospital, 100 Blossom Street, Cox Building, 302, Boston, MA 02114, USA, Boston, UNITED STATES
| | | | - Joost M Verburg
- Department of Radiation Oncology, Harvard Medical School, Massachussets General Hospital, Francis H Burr Proton Therapy Center, 30 Fruit Street, Boston, 02114, UNITED STATES
| | - Brian A Winey
- Department of Radiation Oncology, Harvard Medical School, FH Burr Proton Therapy Center, 55 Fruit St, Boston, Massachusetts, 02114, UNITED STATES
| | - Antony John Lomax
- Department of Radiation Medicine, Paul Scherrer Institute, CH-5232 Villigen PSI, Villigen, SWITZERLAND
| | - Harald Paganetti
- Northeast Proton Therapy Centre, Massachusetts General Hospital, 30 Fruit Street, Boston, MA 02114, USA, Boston, Massachusetts, 02114, UNITED STATES
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Mirzapour SA, Mazur TR, Harold Li H, Salari E, Sharp GC. Technical Note: Cumulative dose modeling for organ motion management in MRI-guided radiation therapy. Med Phys 2020; 48:597-604. [PMID: 32990373 DOI: 10.1002/mp.14500] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [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: 02/17/2020] [Revised: 06/17/2020] [Accepted: 08/08/2020] [Indexed: 11/11/2022] Open
Abstract
PURPOSE To develop a method for continuous online dose accumulation during irradiation in MRI-guided radiation therapy (MRgRT) and to demonstrate its application in evaluating the impact of internal organ motion on cumulative dose. METHODS An intensity-modulated radiation therapy (IMRT) treatment plan is partitioned into its unique apertures. Dose for each planned aperture is calculated using Monte Carlo dose simulation on each phase of a four-dimensional computed tomography (4D-CT) dataset. Deformable image registration is then performed both (a) between each frame of a cine-MRI acquisition obtained during treatment and a reference frame, and (b) between each volume of the 4D-CT phases and a reference phase. These registrations are used to associate each cine image with a 4D-CT phase. Additionally, for each 4D-CT phase, the deformation vector field (DVF) is used to warp the pre-calculated dose volumes per aperture onto the reference CT dataset. To estimate the dose volume delivered during each frame of the cine-MRI acquisition, we retrieve the pre-calculated warped dose volume for the delivered aperture on the associated 4D-CT phase and adjust it by a rigid translation to account for baseline drift and instances where motion on the cine image exceeds the amplitude observed between 4D-CT phases. RESULTS The proposed dose accumulation method is retrospectively applied to a liver cancer case previously treated on an MRgRT platform. Cumulative dose estimated for free-breathing and respiration-gated delivery is compared against dose calculated on static anatomy. In this sample case, the target minimum dose and D 98 varied by as much as 5% and 7%, respectively. CONCLUSION We demonstrate a technique suitable for continuous online dose accumulation during MRgRT. In contrast to other approaches, dose is pre-calculated per aperture and phase and then retrieved based on a mapping scheme between cine MRI and 4D-CT datasets, aiming at reducing the computational burden for potential real-time applications.
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Affiliation(s)
- Seyed Ali Mirzapour
- Department of Industrial, Systems, and Manufacturing Engineering, Wichita State University, Wichita, KS, 67260, USA
| | - Thomas R Mazur
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, 63110, USA
| | - H Harold Li
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, 63110, USA
| | - Ehsan Salari
- Department of Industrial, Systems, and Manufacturing Engineering, Wichita State University, Wichita, KS, 67260, USA
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA, 02114, USA
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Lalonde A, Winey B, Verburg J, Paganetti H, Sharp GC. Evaluation of CBCT scatter correction using deep convolutional neural networks for head and neck adaptive proton therapy. Phys Med Biol 2020; 65. [DOI: 10.1088/1361-6560/ab9fcb] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 06/24/2020] [Indexed: 12/11/2022]
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19
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Andersen AG, Park YK, Elstrøm UV, Petersen JBB, Sharp GC, Winey B, Dong L, Muren LP. Evaluation of an a priori scatter correction algorithm for cone-beam computed tomography based range and dose calculations in proton therapy. Phys Imaging Radiat Oncol 2020; 16:89-94. [PMID: 33458349 PMCID: PMC7807858 DOI: 10.1016/j.phro.2020.09.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [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] [Received: 05/18/2020] [Revised: 09/22/2020] [Accepted: 09/30/2020] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND AND PURPOSE Scatter correction of cone-beam computed tomography (CBCT) projections may enable accurate online dose-delivery estimations in photon and proton-based radiotherapy. This study aimed to evaluate the impact of scatter correction in CBCT-based proton range/dose calculations, in scans acquired in both proton and photon gantries. MATERIAL AND METHODS CBCT projections of a Catphan and an Alderson phantom were acquired on both a proton and a photon gantry. The scatter corrected CBCTs (corrCBCTs) and the clinical reconstructions (stdCBCTs) were compared against CTs rigidly registered to the CBCTs (rigidCTs). The CBCTs of the Catphan phantom were segmented by materials for CT number analysis. Water equivalent path length (WEPL) maps were calculated through the Alderson phantom while proton plans optimized on the rigidCT and recalculated on all CBCTs were compared in a gamma analysis. RESULTS In medium and high-density materials, the corrCBCT CT numbers were much closer to those of the rigidCT than the stdCBCTs. E.g. in the 50% bone segmentations the differences were reduced from above 300 HU (with stdCBCT) to around 60-70 HU (with corrCBCT). Differences in WEPL from the rigidCT were typically well below 5 mm for the corrCBCTs, compared to well above 10 mm for the stdCBCTs with the largest deviations in the head and thorax regions. Gamma pass rates (2%/2mm) when comparing CBCT-based dose re-calculations to rigidCT calculations were improved from around 80% (with stdCBCT) to mostly above 90% (with corrCBCT). CONCLUSION Scatter correction leads to substantial artefact reductions, improving accuracy of CBCT-based proton range/dose calculations.
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Affiliation(s)
| | | | - Ulrik Vindelev Elstrøm
- Danish Centre for Particle Therapy, Aarhus University Hospital/Aarhus University, Aarhus, Denmark
| | | | - Gregory C. Sharp
- Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Brian Winey
- Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Lei Dong
- University of Pennsylvania, Philadelphia, PA, USA
| | - Ludvig Paul Muren
- Danish Centre for Particle Therapy, Aarhus University Hospital/Aarhus University, Aarhus, Denmark
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20
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Zhang X, Tang J, Sharp GC, Xiao L, Xu S, Lu HM. A new respiratory monitor system for four-dimensional computed tomography by measuring the pressure change on the back of body. Br J Radiol 2020; 93:20190303. [PMID: 31912746 DOI: 10.1259/bjr.20190303] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE A novel respiratory monitoring method based on the periodical pressure change on the patient's back was proposed and assessed by applying to four-dimensional CT (4DCT) scanning. METHODS A pressure-based respiratory monitoring system is developed and validated by comparing to real-time position management (RPM) system. The pressure change and the RPM signal are compared with phase differences and correlations calculated. The 4DCT images are reconstructed by these two signals. Internal and skin artifacts due to mismatch between CT slices and respiratory phases are evaluated. RESULTS The pressure and RPM signals shows strong consistency (R = 0.68±0.19 (1SD)). The time shift is 0.26 ± 0.51 (1SD) s and the difference of breath cycle is 0.02 ± 0.17 (1SD) s. The quality of 4DCT images reconstructed by two signals is similar. For both methods, the number of patients with artifacts is eight and the maximum magnitudes of artifacts are 20 mm (internal) and 10 mm (skin). The average magnitudes are 8.8 mm (pressure) and 8.2 mm (RPM) for internal artifacts, and 5.2 mm (pressure) and 4.6 mm (RPM) for skin artifacts. The mean square gray value difference shows no significant difference (p = 0.52). CONCLUSION The pressure signal provides qualified results for respiratory monitoring in 4DCT scanning, demonstrating its potential application for respiration monitoring in radiotherapy. ADVANCES IN KNOWLEDGE Pressure change on the back of body is a novel and promising method to monitor respiration in radiotherapy, which may improve treatment comfort and provide more information about respiration and body movement.
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Affiliation(s)
- Xianwen Zhang
- Nanjing Research Institute of Electronics Technology, Nanjing, 210039, China
| | - Jintian Tang
- Key Laboratory of Particle and Radiation Imaging, Tsinghua University, Ministry of Education, Beijing, 100084, China
| | - Gregory C Sharp
- Department of Radiation Oncology, Francis H Burr Proton Therapy Center, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Lei Xiao
- Master School of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin, 300387, China
| | - Shouping Xu
- Department of Radiation Oncology, Chinese PLA General Hospital, Beijing, 100853, China
| | - Hsiao-Ming Lu
- Department of Radiation Oncology, Francis H Burr Proton Therapy Center, Massachusetts General Hospital, Boston, MA 02114, USA
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21
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Meschini G, Seregni M, Molinelli S, Vai A, Phillips J, Sharp GC, Pella A, Valvo F, Ciocca M, Riboldi M, Paganetti H, Baroni G. Validation of a model for physical dose variations in irregularly moving targets treated with carbon ion beams. Med Phys 2019; 46:3663-3673. [PMID: 31206718 DOI: 10.1002/mp.13662] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [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: 11/22/2018] [Revised: 06/07/2019] [Accepted: 06/07/2019] [Indexed: 12/14/2022] Open
Abstract
PURPOSE In particle therapy, conventional treatment planning systems rely on an imaging representation of the irradiated region to compute the dose. For irregular breathing, when an imaging dataset describing the actual motion is not available, a different approach for dose estimation is needed. To this aim, we validate a method for the estimation of physical dose variations in gated carbon ion treatments, providing also a demonstration of the feasibility of physical dose metrics to assess the method performance. Finally, we describe a sample use case, in which this method is used to assess plan robustness with respect to undetected irregular tumor motion. METHODS The method entails the definition of a patient- and beam-specific water equivalent depth (WED) space, the simulation of motion as a translation equal to tumor displacement, and the reconstruction of the altered dose. We validated the approach using four-dimensional computed tomographies (4DCTs) and clinical plans in 12 patients, treated with respiratory gated carbon ion beams at the National Centre for Oncological Hadrontherapy (Pavia, Italy). Using the end-exhale CT and dose distribution as a reference, the physical dose delivered at the end-inhale tumor position was estimated and compared to the ground-truth dose recalculation on the end-inhale CT. Biologically effective and physical dose variations between the plan and the recalculation were compared as well. As a use case, we evaluated dose changes caused by simulated irregular tumor motion, that is, linear and nonlinear baseline shifts and/or amplitude variations with hysteresis. RESULTS The ratio between biologically effective and physical equivalent uniform dose (EUD) variations due to end-exhale to end-inhale motion was less than one for 96% of investigated structures. In the validation study, we found a median error corresponding to a 14% EUD overestimation for the tumor and 4% EUD underestimation for a subgroup of organs at risk, together with a high EUD variation due to motion [median 352% EUD variation between end-exhale and end-inhale doses in the planning tumor volume (PTV)]. Considering relevant dose-volume histogram (DVH) metrics, the median difference between estimated and ground truth doses was ≤ 4%. Gamma analysis between estimated and recalculated dose distributions resulted in a pass rate > 80% for 83% of the target volumes. For the two patients selected for the sample use case, a patient-specific assessment of the method performance was performed on the 4DCT and it was possible to relate EUD variations of both tumor and organs at risk to the simulated target motion. CONCLUSIONS The physical dose distribution was found to be more sensitive to motion with respect to the biologically effective one, suggesting the suitability of the physical dose metrics for the WED-space method validation. We showed that the method can compensate for intra-fractional tumor motion with proper accuracy in the selected patient group, although its use is recommended when limited deformations are expected. In conclusion, the WED-space method can provide simulations of dose alteration due to irregular breathing when imaging data are lacking, and, once integrated with relative biological effectiveness (RBE) modeling, it would be useful in evaluating the robustness of carbon ion treatment plans.
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Affiliation(s)
| | | | | | - Alessandro Vai
- Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
| | - Justin Phillips
- Alexian Brothers Medical Center, Elk Grove Village, IL, 60007, USA
| | | | - Andrea Pella
- Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
| | - Francesca Valvo
- Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
| | - Mario Ciocca
- Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
| | - Marco Riboldi
- Ludwig-Maximilians-Universität, Munich, 80539, Germany
| | | | - Guido Baroni
- Politecnico di Milano, Milan, 20133, Italy.,Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
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22
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Li Y, Dykstra M, Best TD, Pursley J, Chopra N, Keane FK, Khandekar MJ, Sharp GC, Paganetti H, Willers H, Fintelmann FJ, Grassberger C. Differential inflammatory response dynamics in normal lung following stereotactic body radiation therapy with protons versus photons. Radiother Oncol 2019; 136:169-175. [PMID: 31015121 DOI: 10.1016/j.radonc.2019.04.004] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [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: 11/19/2018] [Revised: 03/29/2019] [Accepted: 04/03/2019] [Indexed: 12/15/2022]
Abstract
BACKGROUND AND PURPOSE To compare time-dependent changes in lung parenchyma of early-stage non-small cell lung carcinoma (NSCLC) patients after stereotactic body radiation therapy with protons (SBPT) or photons (SBRT). MATERIALS AND METHOD We retrospectively identified NSCLC patients treated with SBPT and matched each one with a SBRT patient by patient, tumor, and treatment characteristics. Lung parenchyma on serial post-treatment chest computer tomography (CT) scans was deformably registered with the treatment plan to analyze lung density changes as function of dose, quantified by Houndsfield Unit (HU)/Gy. A thoracic radiologist also evaluated the CTs using an established grading system. RESULTS We matched 23 SBPT/SBRT pairs, including 5 patients treated with both modalities (internally matched cohort). Normal lung response following SBPT significantly increased in the early time period (CTs acquired <6 months, median 3 months) post-treatment, and then did not change significantly in the later time period (CTs acquired 6-14 months, median 9 months). For SBRT, the normal lung response was similar to SBPT in the early time period, but then increased significantly from the early to the late time period (p = 0.007). These differences were most pronounced in sensitive (response >6 HU/Gy) patients and in the internally matched cohort. However, there was no significant difference in the maximum observed response in the entire cohort over all time periods, median 3.4 [IQR, 1.0-5.4] HU/Gy (SBPT) versus 2.5 [1.6-5.2] HU/Gy (SBRT). Qualitative radiological evaluation was highly correlated with the quantitative analysis (p < 0.0001). CONCLUSION While there was no significant difference in maximum response after SBPT versus SBRT, dose-defined lung inflammation occurred earlier after proton irradiation. Further investigation is warranted into the mechanisms of inflammation and therapeutic consequences after proton versus photon irradiation.
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Affiliation(s)
- Yanjing Li
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA
| | - Michael Dykstra
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA; Harvard Medical School, Boston, USA
| | - Till D Best
- Department of Radiology, Massachusetts General Hospital, Boston, USA
| | - Jennifer Pursley
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA
| | - Nitish Chopra
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA
| | - Florence K Keane
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA
| | - Melin J Khandekar
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA
| | - Henning Willers
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA
| | | | - Clemens Grassberger
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA.
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Zhang R, Sharp GC, Jee KW, Cascio E, Harms J, Flanz JB, Lu HM. Iterative optimization of relative stopping power by single detector based multi-projection proton radiography. ACTA ACUST UNITED AC 2019; 64:065022. [DOI: 10.1088/1361-6560/aaf976] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Tappeiner E, Pröll S, Hönig M, Raudaschl PF, Zaffino P, Spadea MF, Sharp GC, Schubert R, Fritscher K. Multi-organ segmentation of the head and neck area: an efficient hierarchical neural networks approach. Int J Comput Assist Radiol Surg 2019; 14:745-754. [PMID: 30847761 DOI: 10.1007/s11548-019-01922-4] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [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: 08/17/2018] [Accepted: 02/04/2019] [Indexed: 12/01/2022]
Abstract
PURPOSE In radiation therapy, a key step for a successful cancer treatment is image-based treatment planning. One objective of the planning phase is the fast and accurate segmentation of organs at risk and target structures from medical images. However, manual delineation of organs, which is still the gold standard in many clinical environments, is time-consuming and prone to inter-observer variations. Consequently, many automated segmentation methods have been developed. METHODS In this work, we train two hierarchical 3D neural networks to segment multiple organs at risk in the head and neck area. First, we train a coarse network on size-reduced medical images to locate the organs of interest. Second, a subsequent fine network on full-resolution images is trained for a final accurate segmentation. The proposed method is purely deep learning based; accordingly, no pre-registration or post-processing is required. RESULTS The approach has been applied on a publicly available computed tomography dataset, created for the MICCAI 2015 Auto-Segmentation challenge. In an extensive evaluation process, the best configurations for the trained networks have been determined. Compared to the existing methods, the presented approach shows state-of-the-art performance for the segmentation of seven different structures in the head and neck area. CONCLUSION We conclude that 3D neural networks outperform the most existing model- and atlas-based methods for the segmentation of organs at risk in the head and neck area. The ease of use, high accuracy and the test time efficiency of the method make it promising for image-based treatment planning in clinical practice.
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Affiliation(s)
- Elias Tappeiner
- Department of Biomedical Computer Science and Mechatronics, University for Health Sciences, Medical Informatics and Technology, 6060, Hall, Tyrol, Austria.
| | - Samuel Pröll
- Department of Biomedical Computer Science and Mechatronics, University for Health Sciences, Medical Informatics and Technology, 6060, Hall, Tyrol, Austria
| | - Markus Hönig
- Department of Biomedical Computer Science and Mechatronics, University for Health Sciences, Medical Informatics and Technology, 6060, Hall, Tyrol, Austria
| | - Patrick F Raudaschl
- Department of Biomedical Computer Science and Mechatronics, University for Health Sciences, Medical Informatics and Technology, 6060, Hall, Tyrol, Austria
| | - Paolo Zaffino
- Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, 88100, Catanzaro, Italy
| | - Maria F Spadea
- Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, 88100, Catanzaro, Italy
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Rainer Schubert
- Department of Biomedical Computer Science and Mechatronics, University for Health Sciences, Medical Informatics and Technology, 6060, Hall, Tyrol, Austria
| | - Karl Fritscher
- Department of Biomedical Computer Science and Mechatronics, University for Health Sciences, Medical Informatics and Technology, 6060, Hall, Tyrol, Austria
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Shusharina N, Fullerton B, Adams JA, Sharp GC, Chan AW. Impact of aeration change and beam arrangement on the robustness of proton plans. J Appl Clin Med Phys 2019; 20:14-21. [PMID: 30756466 PMCID: PMC6414139 DOI: 10.1002/acm2.12503] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Revised: 09/10/2018] [Accepted: 10/18/2018] [Indexed: 11/16/2022] Open
Abstract
This study determines the impact of change in aeration in sinonasal cavities on the robustness of passive‐scattering proton therapy plans in patients with sinonasal and nasopharyngeal malignancies. Fourteen patients, each with one planning CT and one CT acquired during radiotherapy were studied. Repeat and planning CTs were rigidly aligned and contours were transferred using deformable registration. The amount of air, tumor, and fluid within the cavity containing the tumor were measured on both CTs. The original plans were recalculated on the repeat CT. Dosimetric changes were measured for the targets and critical structures. Median decrease in gross tumor volume (GTV) was 19.8% and correlated with the time of rescan. The median change in air content was 7.1% and correlated with the tumor shrinkage. The median of the mean dose Dmean change was +0.4% for GTV and +0.3% for clinical target volume. Median change in the maximum dose Dmax of the critical structures were as follows: optic chiasm +0.66%, left optic nerve +0.12%, right optic nerve +0.38%, brainstem +0.6%. The dose to the GTV decreased by more than 5% in 1 case, and the dose to critical structure(s) increased by more than 5% in three cases. These four patients had sinonasal cancers and were treated with anterior proton fields that directly transversed through the involved sinus cavities. The change in dose in the replanning was strongly correlated with the change in aeration (P = 0.02). We found that the change in aeration in the vicinity of the target and the arrangement of proton beams affected the robustness of proton plan.
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Affiliation(s)
- Nadya Shusharina
- Department of Radiation OncologyMassachusetts General HospitalHarvard Medical SchoolBostonMAUSA
| | - Barbara Fullerton
- Department of Radiation OncologyMassachusetts General HospitalHarvard Medical SchoolBostonMAUSA
- Department of OtolaryngologyMassachusetts Eye and Ear InfirmaryHarvard Medical SchoolBostonMAUSA
| | - Judy A. Adams
- Department of Radiation OncologyMassachusetts General HospitalHarvard Medical SchoolBostonMAUSA
| | - Gregory C. Sharp
- Department of Radiation OncologyMassachusetts General HospitalHarvard Medical SchoolBostonMAUSA
| | - Annie W. Chan
- Department of Radiation OncologyMassachusetts General HospitalHarvard Medical SchoolBostonMAUSA
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Huo W, Zwart T, Cooley J, Huang K, Finley C, Jee KW, Sharp GC, Rosenthal S, Xu XG, Lu HM. A single detector energy-resolved proton radiography system: a proof of principle study by Monte Carlo simulations. ACTA ACUST UNITED AC 2019; 64:025016. [DOI: 10.1088/1361-6560/aaf96f] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Maier-Hein L, Eisenmann M, Reinke A, Onogur S, Stankovic M, Scholz P, Arbel T, Bogunovic H, Bradley AP, Carass A, Feldmann C, Frangi AF, Full PM, van Ginneken B, Hanbury A, Honauer K, Kozubek M, Landman BA, März K, Maier O, Maier-Hein K, Menze BH, Müller H, Neher PF, Niessen W, Rajpoot N, Sharp GC, Sirinukunwattana K, Speidel S, Stock C, Stoyanov D, Taha AA, van der Sommen F, Wang CW, Weber MA, Zheng G, Jannin P, Kopp-Schneider A. Why rankings of biomedical image analysis competitions should be interpreted with care. Nat Commun 2018; 9:5217. [PMID: 30523263 PMCID: PMC6284017 DOI: 10.1038/s41467-018-07619-7] [Citation(s) in RCA: 143] [Impact Index Per Article: 23.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Accepted: 11/07/2018] [Indexed: 11/08/2022] Open
Abstract
International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of common practices related to the organization of challenges has not yet been performed. In this paper, we present a comprehensive analysis of biomedical image analysis challenges conducted up to now. We demonstrate the importance of challenges and show that the lack of quality control has critical consequences. First, reproducibility and interpretation of the results is often hampered as only a fraction of relevant information is typically provided. Second, the rank of an algorithm is generally not robust to a number of variables such as the test data used for validation, the ranking scheme applied and the observers that make the reference annotations. To overcome these problems, we recommend best practice guidelines and define open research questions to be addressed in the future.
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Affiliation(s)
- Lena Maier-Hein
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany.
| | - Matthias Eisenmann
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Annika Reinke
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Sinan Onogur
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Marko Stankovic
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Patrick Scholz
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Tal Arbel
- Centre for Intelligent Machines, McGill University, Montreal, QC, H3A0G4, Canada
| | - Hrvoje Bogunovic
- Christian Doppler Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology, Medical University Vienna, 1090, Vienna, Austria
| | - Andrew P Bradley
- Science and Engineering Faculty, Queensland University of Technology, Brisbane, QLD, 4001, Australia
| | - Aaron Carass
- Department of Electrical and Computer Engineering, Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Carolin Feldmann
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Alejandro F Frangi
- CISTIB - Center for Computational Imaging & Simulation Technologies in Biomedicine, The University of Leeds, Leeds, Yorkshire, LS2 9JT, UK
| | - Peter M Full
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Bram van Ginneken
- Department of Radiology and Nuclear Medicine, Medical Image Analysis, Radboud University Center, 6525 GA, Nijmegen, The Netherlands
| | - Allan Hanbury
- Institute of Information Systems Engineering, TU Wien, 1040, Vienna, Austria
- Complexity Science Hub Vienna, 1080, Vienna, Austria
| | - Katrin Honauer
- Heidelberg Collaboratory for Image Processing (HCI), Heidelberg University, 69120, Heidelberg, Germany
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Masaryk University, 60200, Brno, Czech Republic
| | - Bennett A Landman
- Electrical Engineering, Vanderbilt University, Nashville, TN, 37235-1679, USA
| | - Keno März
- Division of Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Oskar Maier
- Institute of Medical Informatics, Universität zu Lübeck, 23562, Lübeck, Germany
| | - Klaus Maier-Hein
- Division of Medical Image Computing (MIC), German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Bjoern H Menze
- Institute for Advanced Studies, Department of Informatics, Technical University of Munich, 80333, Munich, Germany
| | - Henning Müller
- Information System Institute, HES-SO, Sierre, 3960, Switzerland
| | - Peter F Neher
- Division of Medical Image Computing (MIC), German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Wiro Niessen
- Departments of Radiology, Nuclear Medicine and Medical Informatics, Erasmus MC, 3015 GD, Rotterdam, The Netherlands
| | - Nasir Rajpoot
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, 02114, USA
| | | | - Stefanie Speidel
- Division of Translational Surgical Oncology (TCO), National Center for Tumor Diseases Dresden, 01307, Dresden, Germany
| | - Christian Stock
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Danail Stoyanov
- Centre for Medical Image Computing (CMIC) & Department of Computer Science, University College London, London, W1W 7TS, UK
| | - Abdel Aziz Taha
- Data Science Studio, Research Studios Austria FG, 1090, Vienna, Austria
| | - Fons van der Sommen
- Department of Electrical Engineering, Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands
| | - Ching-Wei Wang
- AIExplore, NTUST Center of Computer Vision and Medical Imaging, Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, 106, Taiwan
| | - Marc-André Weber
- Institute of Diagnostic and Interventional Radiology, University Medical Center Rostock, 18051, Rostock, Germany
| | - Guoyan Zheng
- Institute for Surgical Technology and Biomechanics, University of Bern, Bern, 3014, Switzerland
| | - Pierre Jannin
- Univ Rennes, Inserm, LTSI (Laboratoire Traitement du Signal et de l'Image) - UMR_S 1099, Rennes, 35043, Cedex, France
| | - Annette Kopp-Schneider
- Division of Biostatistics, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
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Pileggi G, Speier C, Sharp GC, Izquierdo Garcia D, Catana C, Pursley J, Amato F, Seco J, Spadea MF. Proton range shift analysis on brain pseudo-CT generated from T1 and T2 MR. Acta Oncol 2018; 57:1521-1531. [PMID: 29842815 DOI: 10.1080/0284186x.2018.1477257] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND In radiotherapy, MR imaging is only used because it has significantly better soft tissue contrast than CT, but it lacks electron density information needed for dose calculation. This work assesses the feasibility of using pseudo-CT (pCT) generated from T1w/T2w MR for proton treatment planning, where proton range comparisons are performed between standard CT and pCT. MATERIAL AND METHODS MR and CT data from 14 glioblastoma patients were used in this study. The pCT was generated by using conversion libraries obtained from tissue segmentation and anatomical regioning of the T1w/T2w MR. For each patient, a plan consisting of three 18 Gy beams was designed on the pCT, for a total of 42 analyzed beams. The plan was then transferred onto the CT that represented the ground truth. Range shift (RS) between pCT and CT was computed at R80 over 10 slices. The acceptance threshold for RS was according to clinical guidelines of two institutions. A γ-index test was also performed on the total dose for each patient. RESULTS Mean absolute error and bias for the pCT were 124 ± 10 and -16 ± 26 Hounsfield Units (HU), respectively. The median and interquartile range of RS was 0.5 and 1.4 mm, with highest absolute value being 4.4 mm. Of the 42 beams, 40 showed RS less than the clinical range margin. The two beams with larger RS were both in the cranio-caudal direction and had segmentation errors due to the partial volume effect, leading to misassignment of the HU. CONCLUSIONS This study showed the feasibility of using T1w and T2w MRI to generate a pCT for proton therapy treatment, thus avoiding the use of a planning CT and allowing better target definition and possibilities for online adaptive therapies. Further improvements of the methodology are still required to improve the conversion from MRI intensities to HUs.
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Affiliation(s)
- Giampaolo Pileggi
- Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy
- Radiation Oncology Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Christoph Speier
- Radiation Oncology Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Radiation Oncology, Universitätsklinikum Erlangen Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Gregory C. Sharp
- Radiation Oncology Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - David Izquierdo Garcia
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Ciprian Catana
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Jennifer Pursley
- Radiation Oncology Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Francesco Amato
- Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy
| | - Joao Seco
- Biomedical Physics in Radiation Oncology, DKFZ – Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - Maria Francesca Spadea
- Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy
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Yang J, Veeraraghavan H, Armato SG, Farahani K, Kirby JS, Kalpathy-Kramer J, van Elmpt W, Dekker A, Han X, Feng X, Aljabar P, Oliveira B, van der Heyden B, Zamdborg L, Lam D, Gooding M, Sharp GC. Autosegmentation for thoracic radiation treatment planning: A grand challenge at AAPM 2017. Med Phys 2018; 45:4568-4581. [PMID: 30144101 DOI: 10.1002/mp.13141] [Citation(s) in RCA: 127] [Impact Index Per Article: 21.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Revised: 08/15/2018] [Accepted: 08/15/2018] [Indexed: 12/25/2022] Open
Abstract
PURPOSE This report presents the methods and results of the Thoracic Auto-Segmentation Challenge organized at the 2017 Annual Meeting of American Association of Physicists in Medicine. The purpose of the challenge was to provide a benchmark dataset and platform for evaluating performance of autosegmentation methods of organs at risk (OARs) in thoracic CT images. METHODS Sixty thoracic CT scans provided by three different institutions were separated into 36 training, 12 offline testing, and 12 online testing scans. Eleven participants completed the offline challenge, and seven completed the online challenge. The OARs were left and right lungs, heart, esophagus, and spinal cord. Clinical contours used for treatment planning were quality checked and edited to adhere to the RTOG 1106 contouring guidelines. Algorithms were evaluated using the Dice coefficient, Hausdorff distance, and mean surface distance. A consolidated score was computed by normalizing the metrics against interrater variability and averaging over all patients and structures. RESULTS The interrater study revealed highest variability in Dice for the esophagus and spinal cord, and in surface distances for lungs and heart. Five out of seven algorithms that participated in the online challenge employed deep-learning methods. Although the top three participants using deep learning produced the best segmentation for all structures, there was no significant difference in the performance among them. The fourth place participant used a multi-atlas-based approach. The highest Dice scores were produced for lungs, with averages ranging from 0.95 to 0.98, while the lowest Dice scores were produced for esophagus, with a range of 0.55-0.72. CONCLUSION The results of the challenge showed that the lungs and heart can be segmented fairly accurately by various algorithms, while deep-learning methods performed better on the esophagus. Our dataset together with the manual contours for all training cases continues to be available publicly as an ongoing benchmarking resource.
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Affiliation(s)
- Jinzhong Yang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Samuel G Armato
- Department of Radiology, The University of Chicago, Chicago, IL, USA
| | - Keyvan Farahani
- Cancer Imaging Program, National Cancer Institute, Bethesda, MD, USA
| | - Justin S Kirby
- Cancer Imaging Program, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, MD, USA
| | | | - Wouter van Elmpt
- Department of Radiation Oncology (MAASTRO), GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Andre Dekker
- Department of Radiation Oncology (MAASTRO), GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Xiao Han
- Elekta Inc., Maryland Heights, MO, USA
| | - Xue Feng
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | | | - Bruno Oliveira
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal.,ICVS/3Bs - PT Government Associaste Laboratory, Braga/Guimares, Portugal
| | - Brent van der Heyden
- Department of Radiation Oncology (MAASTRO), GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Leonid Zamdborg
- Department of Radiation Oncology, Beaumont Health, Royal Oak, MI, USA
| | - Dao Lam
- Department of Radiation Oncology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
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Chang Y, Sharp GC, Li Q, Shih HA, El Fakhri G, Ra JB, Woo J. Subject-specific Brain Tumor Growth Modelling via An Efficient Bayesian Inference Framework. Proc SPIE Int Soc Opt Eng 2018; 10574. [PMID: 30050231 DOI: 10.1117/12.2293145] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
An accurate prediction of brain tumor progression is crucial for optimized treatment of the tumors. Gliomas are primarily treated by combining surgery, external beam radiotherapy, and chemotherapy. Among them, radiotherapy is a non-invasive and effective therapy, and an understanding of tumor growth will allow better therapy planning. In particular, estimating parameters associated with tumor growth, such as the diffusion coefficient and proliferation rate, is crucial to accurately characterize physiology of tumor growth and to develop predictive models of tumor infiltration and recurrence. Accurate parameter estimation, however, is a challenging task due to inaccurate tumor boundaries and the approximation of the tumor growth model. Here, we introduce a Bayesian framework for a subject-specific tumor growth model that estimates the tumor parameters effectively. This is achieved by using an improved elliptical slice sampling method based on an adaptive sample region. Experimental results on clinical data demonstrate that the proposed method provides a higher acceptance rate, while preserving the parameter estimation accuracy, compared with other state-of-the-art methods such as Metropolis-Hastings and elliptical slice sampling without any modification. Our approach has the potential to provide a method to individualize therapy, thereby offering an optimized treatment.
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Affiliation(s)
- Yongjin Chang
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Quanzheng Li
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Helen A Shih
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Jong Beom Ra
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea
| | - Jonghye Woo
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
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Moteabbed M, Trofimov A, Khan FH, Wang Y, Sharp GC, Zietman AL, Efstathiou JA, Lu HM. Impact of interfractional motion on hypofractionated pencil beam scanning proton therapy and VMAT delivery for prostate cancer. Med Phys 2018; 45:4011-4019. [PMID: 30007067 DOI: 10.1002/mp.13091] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [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: 01/18/2018] [Revised: 05/07/2018] [Accepted: 06/01/2018] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Hypofractionated radiotherapy of prostate cancer is gaining clinical acceptance given its potential increase in therapeutic ratio and evidence for noninferiority and lack of added late toxicities compared to conventional fractionation. However, concerns have been raised that smaller number of fractions might lead to larger dosimetric influence by interfractional motion. We aim to compare the effect of these variations on hypofractionated pencil beam scanning (PBS) proton therapy and volumetric modulated arc therapy (VMAT) for localized prostate cancer. METHODS Weekly CT images were acquired for 6 patients participating in a randomized clinical trial. PBS plans featuring bilateral (BL) and a combination of lateral and anterior-oblique beams (AOL), and VMAT plans were created. All patients were treated to a conventional 79.2 Gy total dose in 44 fractions. For this study, hypofractionated dose to the prostate gland was 51.6 Gy in 12 fractions or 36.25 Gy in 5 fractions, and 32.8, and 23.1 Gy to proximal seminal vesicles, respectively. Patients were simulated with endorectal balloons to aid gland immobilization. Three fiducial markers were implanted for setup guidance. All plans were recomputed on the weekly CT images after aligning with the simulation CT. The entire set of 9 CT images was used for dose recalculation for 12-fraction and only 5 used for the 5-fraction case. Adaptive range adjustments were applied to anterior-oblique beams assuming clinical availability of in vivo range verification. Fractional doses were summed using deformable dose accumulation to approximate the delivered dose. Biologically equivalent dose to 2 Gy(EQD2) was calculated assuming α/β of 1.5 Gy for prostate and 3 Gy for bladder and rectum. RESULTS The median delivered prostate D98 was 0.13/0.14/0.13 Gy(EQD2) smaller than planned for PBS-BL, 0.13/0.27/0.17 Gy(EQD2) for PBS-AOL and 0.59/0.66/0.59 Gy(EQD2) for VMAT, for 44/12/5 fractions, respectively. The largest D98 reduction was 1.5 and 3.5 Gy(EQD2) for CTV1 and CTV2, respectively. Target dose degradation was comparable for all fractionation schemes within each modality. The maximum increase in rectum D2 was 0.98 Gy(EQD2) for a 5-fraction PBS case. CONCLUSIONS The robustness of PBS and VMAT were comparable for all patients for the studied fractionations. The delivered target dose generally remained within clinical tolerance and the deviations were relatively minor for both fractionation schemes. The delivered OAR dose stayed in compliance with the RTOG hypofractionation constraints for all cases.
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Affiliation(s)
- Maryam Moteabbed
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Alexei Trofimov
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Fazal H Khan
- Department of Radiation Oncology, Miami Cancer Institute, Miami, FL, USA
| | - Yi Wang
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Anthony L Zietman
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jason A Efstathiou
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Hsiao-Ming Lu
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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Zaffino P, Ciardo D, Raudaschl P, Fritscher K, Ricotti R, Alterio D, Marvaso G, Fodor C, Baroni G, Amato F, Orecchia R, Jereczek-Fossa BA, Sharp GC, Spadea MF. Multi atlas based segmentation: should we prefer the best atlas group over the group of best atlases? Phys Med Biol 2018; 63:12NT01. [PMID: 29787381 DOI: 10.1088/1361-6560/aac712] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Multi atlas based segmentation (MABS) uses a database of atlas images, and an atlas selection process is used to choose an atlas subset for registration and voting. In the current state of the art, atlases are chosen according to a similarity criterion between the target subject and each atlas in the database. In this paper, we propose a new concept for atlas selection that relies on selecting the best performing group of atlases rather than the group of highest scoring individual atlases. Experiments were performed using CT images of 50 patients, with contours of brainstem and parotid glands. The dataset was randomly split into two groups: 20 volumes were used as an atlas database and 30 served as target subjects for testing. Classic oracle selection, where atlases are chosen by the highest dice similarity coefficient (DSC) with the target, was performed. This was compared to oracle group selection, where all the combinations of atlas subgroups were considered and scored by computing DSC with the target subject. Subsequently, convolutional neural networks were designed to predict the best group of atlases. The results were also compared with the selection strategy based on normalized mutual information (NMI). Oracle group was proven to be significantly better than classic oracle selection (p < 10-5). Atlas group selection led to a median ± interquartile DSC of 0.740 ± 0.084, 0.718 ± 0.086 and 0.670 ± 0.097 for brainstem and left/right parotid glands respectively, outperforming NMI selection 0.676 ± 0.113, 0.632 ± 0.104 and 0.606 ± 0.118 (p < 0.001) as well as classic oracle selection. The implemented methodology is a proof of principle that selecting the atlases by considering the performance of the entire group of atlases instead of each single atlas leads to higher segmentation accuracy, being even better then current oracle strategy. This finding opens a new discussion about the most appropriate atlas selection criterion for MABS.
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Affiliation(s)
- Paolo Zaffino
- Department of Experimental and Clinical Medicine, Magna Graecia University, 88100 Catanzaro, Italy
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Reinke A, Eisenmann M, Onogur S, Stankovic M, Scholz P, Full PM, Bogunovic H, Landman BA, Maier O, Menze B, Sharp GC, Sirinukunwattana K, Speidel S, van der Sommen F, Zheng G, Müller H, Kozubek M, Arbel T, Bradley AP, Jannin P, Kopp-Schneider A, Maier-Hein L. How to Exploit Weaknesses in Biomedical Challenge Design and Organization. Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 2018. [DOI: 10.1007/978-3-030-00937-3_45] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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Zhang R, Jee KW, Cascio E, Sharp GC, Flanz JB, Lu HM. Improvement of single detector proton radiography by incorporating intensity of time-resolved dose rate functions. ACTA ACUST UNITED AC 2017; 63:015030. [DOI: 10.1088/1361-6560/aa9913] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Zhang R, Baer E, Jee KW, Sharp GC, Flanz J, Lu HM. Investigation of real tissue water equivalent path lengths using an efficient dose extinction method. ACTA ACUST UNITED AC 2017. [DOI: 10.1088/1361-6560/aa782c] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Raudaschl PF, Zaffino P, Sharp GC, Spadea MF, Chen A, Dawant BM, Albrecht T, Gass T, Langguth C, Lüthi M, Jung F, Knapp O, Wesarg S, Mannion-Haworth R, Bowes M, Ashman A, Guillard G, Brett A, Vincent G, Orbes-Arteaga M, Cárdenas-Peña D, Castellanos-Dominguez G, Aghdasi N, Li Y, Berens A, Moe K, Hannaford B, Schubert R, Fritscher KD. Evaluation of segmentation methods on head and neck CT: Auto-segmentation challenge 2015. Med Phys 2017; 44:2020-2036. [PMID: 28273355 DOI: 10.1002/mp.12197] [Citation(s) in RCA: 136] [Impact Index Per Article: 19.4] [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: 05/19/2016] [Revised: 10/13/2016] [Accepted: 02/22/2017] [Indexed: 01/28/2023] Open
Abstract
PURPOSE Automated delineation of structures and organs is a key step in medical imaging. However, due to the large number and diversity of structures and the large variety of segmentation algorithms, a consensus is lacking as to which automated segmentation method works best for certain applications. Segmentation challenges are a good approach for unbiased evaluation and comparison of segmentation algorithms. METHODS In this work, we describe and present the results of the Head and Neck Auto-Segmentation Challenge 2015, a satellite event at the Medical Image Computing and Computer Assisted Interventions (MICCAI) 2015 conference. Six teams participated in a challenge to segment nine structures in the head and neck region of CT images: brainstem, mandible, chiasm, bilateral optic nerves, bilateral parotid glands, and bilateral submandibular glands. RESULTS This paper presents the quantitative results of this challenge using multiple established error metrics and a well-defined ranking system. The strengths and weaknesses of the different auto-segmentation approaches are analyzed and discussed. CONCLUSIONS The Head and Neck Auto-Segmentation Challenge 2015 was a good opportunity to assess the current state-of-the-art in segmentation of organs at risk for radiotherapy treatment. Participating teams had the possibility to compare their approaches to other methods under unbiased and standardized circumstances. The results demonstrate a clear tendency toward more general purpose and fewer structure-specific segmentation algorithms.
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Affiliation(s)
- Patrik F Raudaschl
- Department of Biomedical Computer Science and Mechatronics, Institute for Biomedical Image Analysis, UMIT, Hall, Tyrol, 6060, Austria
| | - Paolo Zaffino
- Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, 88100, Italy
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Maria Francesca Spadea
- Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, 88100, Italy
| | - Antong Chen
- Merck and Co., Inc., West Point, PA, 19422, USA
| | - Benoit M Dawant
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, 37235, USA
| | | | - Tobias Gass
- Varian Medical Systems, Baden, 5404, Switzerland
| | | | | | | | | | | | | | - Mike Bowes
- Imorphics Ltd., Kilburn House, Manchester Science Park, Manchester, M15 6SE, UK
| | - Annaliese Ashman
- Imorphics Ltd., Kilburn House, Manchester Science Park, Manchester, M15 6SE, UK
| | - Gwenael Guillard
- Imorphics Ltd., Kilburn House, Manchester Science Park, Manchester, M15 6SE, UK
| | - Alan Brett
- Imorphics Ltd., Kilburn House, Manchester Science Park, Manchester, M15 6SE, UK
| | - Graham Vincent
- Imorphics Ltd., Kilburn House, Manchester Science Park, Manchester, M15 6SE, UK
| | | | - David Cárdenas-Peña
- Signal Processing and Recognition Group, Universidad Nacional de Colombia, Colombia
| | | | - Nava Aghdasi
- University of Washington, Seattle, WA, 98105, USA
| | - Yangming Li
- University of Washington, Seattle, WA, 98105, USA
| | | | - Kris Moe
- University of Washington, Seattle, WA, 98105, USA
| | | | - Rainer Schubert
- Department of Biomedical Computer Science and Mechatronics, Institute for Biomedical Image Analysis, UMIT, Hall, Tyrol, 6060, Austria
| | - Karl D Fritscher
- Department of Biomedical Computer Science and Mechatronics, Institute for Biomedical Image Analysis, UMIT, Hall, Tyrol, 6060, Austria
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Moteabbed M, Trofimov A, Sharp GC, Wang Y, Zietman AL, Efstathiou JA, Lu HM. Proton therapy of prostate cancer by anterior-oblique beams: implications of setup and anatomy variations. Phys Med Biol 2017; 62:1644-1660. [DOI: 10.1088/1361-6560/62/5/1644] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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Kurz C, Kamp F, Park YK, Zöllner C, Rit S, Hansen D, Podesta M, Sharp GC, Li M, Reiner M, Hofmaier J, Neppl S, Thieke C, Nijhuis R, Ganswindt U, Belka C, Winey BA, Parodi K, Landry G. Investigating deformable image registration and scatter correction for CBCT-based dose calculation in adaptive IMPT. Med Phys 2016; 43:5635. [DOI: 10.1118/1.4962933] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
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Zaffino P, Raudaschl P, Fritscher K, Sharp GC, Spadea MF. Technical Note: plastimatch mabs
, an open source tool for automatic image segmentation. Med Phys 2016; 43:5155. [DOI: 10.1118/1.4961121] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [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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Park YK, Sharp GC, Phillips J, Winey BA. Proton dose calculation on scatter-corrected CBCT image: Feasibility study for adaptive proton therapy. Med Phys 2016; 42:4449-59. [PMID: 26233175 DOI: 10.1118/1.4923179] [Citation(s) in RCA: 95] [Impact Index Per Article: 11.9] [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 To demonstrate the feasibility of proton dose calculation on scatter-corrected cone-beam computed tomographic (CBCT) images for the purpose of adaptive proton therapy. METHODS CBCT projection images were acquired from anthropomorphic phantoms and a prostate patient using an on-board imaging system of an Elekta infinity linear accelerator. Two previously introduced techniques were used to correct the scattered x-rays in the raw projection images: uniform scatter correction (CBCTus) and a priori CT-based scatter correction (CBCTap). CBCT images were reconstructed using a standard FDK algorithm and GPU-based reconstruction toolkit. Soft tissue ROI-based HU shifting was used to improve HU accuracy of the uncorrected CBCT images and CBCTus, while no HU change was applied to the CBCTap. The degree of equivalence of the corrected CBCT images with respect to the reference CT image (CTref) was evaluated by using angular profiles of water equivalent path length (WEPL) and passively scattered proton treatment plans. The CBCTap was further evaluated in more realistic scenarios such as rectal filling and weight loss to assess the effect of mismatched prior information on the corrected images. RESULTS The uncorrected CBCT and CBCTus images demonstrated substantial WEPL discrepancies (7.3 ± 5.3 mm and 11.1 ± 6.6 mm, respectively) with respect to the CTref, while the CBCTap images showed substantially reduced WEPL errors (2.4 ± 2.0 mm). Similarly, the CBCTap-based treatment plans demonstrated a high pass rate (96.0% ± 2.5% in 2 mm/2% criteria) in a 3D gamma analysis. CONCLUSIONS A priori CT-based scatter correction technique was shown to be promising for adaptive proton therapy, as it achieved equivalent proton dose distributions and water equivalent path lengths compared to those of a reference CT in a selection of anthropomorphic phantoms.
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Affiliation(s)
- Yang-Kyun Park
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114
| | - Justin Phillips
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114
| | - Brian A Winey
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114
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Bian J, Sharp GC, Park YK, Ouyang J, Bortfeld T, El Fakhri G. Investigation of cone-beam CT image quality trade-off for image-guided radiation therapy. Phys Med Biol 2016; 61:3317-46. [PMID: 27032676 DOI: 10.1088/0031-9155/61/9/3317] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
It is well-known that projections acquired over an angular range slightly over 180° (so-called short scan) are sufficient for fan-beam reconstruction. However, due to practical imaging conditions (projection data and reconstruction image discretization, physical factors, and data noise), the short-scan reconstructions may have different appearances and properties from the full-scan (scans over 360°) reconstructions. Nevertheless, short-scan configurations have been used in applications such as cone-beam CT (CBCT) for head-neck-cancer image-guided radiation therapy (IGRT) that only requires a small field of view due to the potential reduced imaging time and dose. In this work, we studied the image quality trade-off for full, short, and full/short scan configurations with both conventional filtered-backprojection (FBP) reconstruction and iterative reconstruction algorithms based on total-variation (TV) minimization for head-neck-cancer IGRT. Anthropomorphic and Catphan phantoms were scanned at different exposure levels with a clinical scanner used in IGRT. Both visualization- and numerical-metric-based evaluation studies were performed. The results indicate that the optimal exposure level and number of views are in the middle range for both FBP and TV-based iterative algorithms and the optimization is object-dependent and task-dependent. The optimal view numbers decrease with the total exposure levels for both FBP and TV-based algorithms. The results also indicate there are slight differences between FBP and TV-based iterative algorithms for the image quality trade-off: FBP seems to be more in favor of larger number of views while the TV-based algorithm is more robust to different data conditions (number of views and exposure levels) than the FBP algorithm. The studies can provide a general guideline for image-quality optimization for CBCT used in IGRT and other applications.
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Affiliation(s)
- Junguo Bian
- Department of Radiology, Massachusetts General Hospital & Harvard Medical School, Boston, MA 02114, USA
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Fritscher K, Raudaschl P, Zaffino P, Spadea MF, Sharp GC, Schubert R. Deep Neural Networks for Fast Segmentation of 3D Medical Images. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016 2016. [DOI: 10.1007/978-3-319-46723-8_19] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
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Moteabbed M, Sharp GC, Wang Y, Trofimov A, Efstathiou JA, Lu HM. Validation of a deformable image registration technique for cone beam CT-based dose verification. Med Phys 2015; 42:196-205. [PMID: 25563260 DOI: 10.1118/1.4903292] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
PURPOSE As radiation therapy evolves toward more adaptive techniques, image guidance plays an increasingly important role, not only in patient setup but also in monitoring the delivered dose and adapting the treatment to patient changes. This study aimed to validate a method for evaluation of delivered intensity modulated radiotherapy (IMRT) dose based on multimodal deformable image registration (dir) for prostate treatments. METHODS A pelvic phantom was scanned with CT and cone-beam computed tomography (CBCT). Both images were digitally deformed using two realistic patient-based deformation fields. The original CT was then registered to the deformed CBCT resulting in a secondary deformed CT. The registration quality was assessed as the ability of the dir method to recover the artificially induced deformations. The primary and secondary deformed CT images as well as vector fields were compared to evaluate the efficacy of the registration method and it's suitability to be used for dose calculation. plastimatch, a free and open source software was used for deformable image registration. A B-spline algorithm with optimized parameters was used to achieve the best registration quality. Geometric image evaluation was performed through voxel-based Hounsfield unit (HU) and vector field comparison. For dosimetric evaluation, IMRT treatment plans were created and optimized on the original CT image and recomputed on the two warped images to be compared. The dose volume histograms were compared for the warped structures that were identical in both warped images. This procedure was repeated for the phantom with full, half full, and empty bladder. RESULTS The results indicated mean HU differences of up to 120 between registered and ground-truth deformed CT images. However, when the CBCT intensities were calibrated using a region of interest (ROI)-based calibration curve, these differences were reduced by up to 60%. Similarly, the mean differences in average vector field lengths decreased from 10.1 to 2.5 mm when CBCT was calibrated prior to registration. The results showed no dependence on the level of bladder filling. In comparison with the dose calculated on the primary deformed CT, differences in mean dose averaged over all organs were 0.2% and 3.9% for dose calculated on the secondary deformed CT with and without CBCT calibration, respectively, and 0.5% for dose calculated directly on the calibrated CBCT, for the full-bladder scenario. Gamma analysis for the distance to agreement of 2 mm and 2% of prescribed dose indicated a pass rate of 100% for both cases involving calibrated CBCT and on average 86% without CBCT calibration. CONCLUSIONS Using deformable registration on the planning CT images to evaluate the IMRT dose based on daily CBCTs was found feasible. The proposed method will provide an accurate dose distribution using planning CT and pretreatment CBCT data, avoiding the additional uncertainties introduced by CBCT inhomogeneity and artifacts. This is a necessary initial step toward future image-guided adaptive radiotherapy of the prostate.
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Affiliation(s)
- M Moteabbed
- Massachusetts General Hospital, Boston, Massachusetts 02114 and Harvard Medical School, Boston, Massachusetts 02115
| | - G C Sharp
- Massachusetts General Hospital, Boston, Massachusetts 02114 and Harvard Medical School, Boston, Massachusetts 02115
| | - Y Wang
- Massachusetts General Hospital, Boston, Massachusetts 02114 and Harvard Medical School, Boston, Massachusetts 02115
| | - A Trofimov
- Massachusetts General Hospital, Boston, Massachusetts 02114 and Harvard Medical School, Boston, Massachusetts 02115
| | - J A Efstathiou
- Massachusetts General Hospital, Boston, Massachusetts 02114 and Harvard Medical School, Boston, Massachusetts 02115
| | - H-M Lu
- Massachusetts General Hospital, Boston, Massachusetts 02114 and Harvard Medical School, Boston, Massachusetts 02115
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Rehani MM, Gupta R, Bartling S, Sharp GC, Pauwels R, Berris T, Boone JM. Radiological Protection in Cone Beam Computed Tomography (CBCT). ICRP Publication 129. Ann ICRP 2015; 44:9-127. [PMID: 26116562 DOI: 10.1177/0146645315575485] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
The objective of this publication is to provide guidance on radiological protection in the new technology of cone beam computed tomography (CBCT). Publications 87 and 102 dealt with patient dose management in computed tomography (CT) and multi-detector CT. The new applications of CBCT and the associated radiological protection issues are substantially different from those of conventional CT. The perception that CBCT involves lower doses was only true in initial applications. CBCT is now used widely by specialists who have little or no training in radiological protection. This publication provides recommendations on radiation dose management directed at different stakeholders, and covers principles of radiological protection, training, and quality assurance aspects. Advice on appropriate use of CBCT needs to be made widely available. Advice on optimisation of protection when using CBCT equipment needs to be strengthened, particularly with respect to the use of newer features of the equipment. Manufacturers should standardise radiation dose displays on CBCT equipment to assist users in optimisation of protection and comparisons of performance. Additional challenges to radiological protection are introduced when CBCT-capable equipment is used for both fluoroscopy and tomography during the same procedure. Standardised methods need to be established for tracking and reporting of patient radiation doses from these procedures. The recommendations provided in this publication may evolve in the future as CBCT equipment and applications evolve. As with previous ICRP publications, the Commission hopes that imaging professionals, medical physicists, and manufacturers will use the guidelines and recommendations provided in this publication for implementation of the Commission's principle of optimisation of protection of patients and medical workers, with the objective of keeping exposures as low as reasonably achievable, taking into account economic and societal factors, and consistent with achieving the necessary medical outcomes.
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Park YK, Sharp GC, Gierga DP, Ye SJ, Winey BA. SU-D-207-05: Real-Time Intrafractional Motion Tracking During VMAT Delivery Using a Conventional Elekta CBCT System. Med Phys 2015. [DOI: 10.1118/1.4923906] [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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46
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Moteabbed M, Trofimov A, Sharp GC, Wang Y, Zietman AL, Efstathiou JA, Lu H. SU-E-T-457: Impact of Interfractional Variations On Anterior Vs. Lateral-Field Proton Therapy of Prostate Cancer. Med Phys 2015. [DOI: 10.1118/1.4924819] [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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Park YK, Sharp GC. Gain Correction for an X-ray Imaging System With a Movable Flat Panel Detector and Intrinsic Localization Crosshair. Technol Cancer Res Treat 2015; 15:387-95. [PMID: 25795048 DOI: 10.1177/1533034615576829] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [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: 06/16/2014] [Accepted: 01/15/2015] [Indexed: 11/16/2022] Open
Abstract
Gain calibration for X-ray imaging systems with a movable flat panel detector and an intrinsic crosshair is a challenge due to the geometry-dependent heel effect and crosshair artifact. This study aims to develop a gain correction method for such systems by implementing the Multi-Acquisition Gain Image Correction technique. Flood field images containing crosshair and heel effect were acquired in 4 different flat panel detector positions at fixed exposure parameters. The crosshair region was automatically detected using common image processing algorithms and removed by a simple interpolation procedure, resulting in a crosshair-removed image. A large kernel-based correction was then used to remove the heel effect. Mask filters corresponding to each crosshair region were applied to the resultant heel effect-removed images to invalidate the pixels of the original crosshair region. Finally, a seamless gain map was composed with corresponding valid pixels from the processed images either by the sequential replacement or by the selective averaging techniques developed in this study. Quantitative evaluation was performed based on normalized noise power spectrum and detective quantum efficiency improvement factor for the flood field images corrected by the Multi-Acquisition Gain Image Correction-based gain maps. For comparison purposes, a single crosshair-removed gain map was also tested. As a result, it was demonstrated that the Multi-Acquisition Gain Image Correction technique achieved better image quality than the crosshair-removed technique, showing lower normalized noise power spectrum values over most of spatial frequencies. The improvement was more obvious at the priori-crosshair region of the gain map. The mean detective quantum efficiency improvement factor was 1.09 ± 0.06, 2.46 ± 0.32, and 3.34 ± 0.36 in the priori-crosshair region and 2.35 ± 0.31, 2.33 ± 0.31, and 3.09 ± 0.34 in the normal region, for crosshair-removed, Multi-Acquisition Gain Image Correction-sequential replacement, and Multi-Acquisition Gain Image Correction-selective averaging techniques, respectively. Therefore, this study indicates that the introduced Multi-Acquisition Gain Image Correction technique is an appropriate method for gain calibration of an imaging system associated with a moving flat panel detector and an intrinsic crosshair.
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Affiliation(s)
- Yang-Kyun Park
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, USA
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, USA
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Peroni M, Golland P, Sharp GC, Baroni G. Stopping Criteria for Log-Domain Diffeomorphic Demons Registration: An Experimental Survey for Radiotherapy Application. Technol Cancer Res Treat 2014; 15:77-90. [PMID: 24000996 DOI: 10.7785/tcrtexpress.2013.600269] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [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: 02/05/2013] [Accepted: 06/26/2013] [Indexed: 11/06/2022] Open
Abstract
A crucial issue in deformable image registration is achieving a robust registration algorithm at a reasonable computational cost. Given the iterative nature of the optimization procedure an algorithm must automatically detect convergence, and stop the iterative process when most appropriate. This paper ranks the performances of three stopping criteria and six stopping value computation strategies for a Log-Domain Demons Deformable registration method simulating both a coarse and a fine registration. The analyzed stopping criteria are: (a) velocity field update magnitude, (b) mean squared error, and (c) harmonic energy. Each stoping condition is formulated so that the user defines a threshold ∊, which quantifies the residual error that is acceptable for the particular problem and calculation strategy. In this work, we did not aim at assigning a value to e, but to give insights in how to evaluate and to set the threshold on a given exit strategy in a very popular registration scheme. Experiments on phantom and patient data demonstrate that comparing the optimization metric minimum over the most recent three iterations with the minimum over the fourth to sixth most recent iterations can be an appropriate algorithm stopping strategy. The harmonic energy was found to provide best trade-off between robustness and speed of convergence for the analyzed registration method at coarse registration, but was outperformed by mean squared error when all the original pixel information is used. This suggests the need of developing mathematically sound new convergence criteria in which both image and vector field information could be used to detect the actual convergence, which could be especially useful when considering multi-resolution registrations. Further work should be also dedicated to study same strategies performances in other deformable registration methods and body districts.
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Affiliation(s)
- M Peroni
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italia
| | - P Golland
- Computer Science and Artificial Intelligence Laboratory, Electrical Engineering & Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - G C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA Harvard Medical School, Boston, MA
| | - G Baroni
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italia Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, Pavia, Italy
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Shusharina N, Sharp GC, Choi NC. Correlation of 18F-FDG PET avid volumes on pre-radiation therapy and post-radiation therapy FDG PET scans in recurrent lung cancer. In reply to Saraiya et al. Int J Radiat Oncol Biol Phys 2014; 90:969-70. [PMID: 25585791 DOI: 10.1016/j.ijrobp.2014.07.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2014] [Revised: 07/13/2014] [Accepted: 07/13/2014] [Indexed: 11/16/2022]
Affiliation(s)
- Nadya Shusharina
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Noah C Choi
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
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Phillips J, Gueorguiev G, Shackleford JA, Grassberger C, Dowdell S, Paganetti H, Sharp GC. Computing proton dose to irregularly moving targets. Phys Med Biol 2014; 59:4261-73. [PMID: 25029239 DOI: 10.1088/0031-9155/59/15/4261] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
PURPOSE While four-dimensional computed tomography (4DCT) and deformable registration can be used to assess the dose delivered to regularly moving targets, there are few methods available for irregularly moving targets. 4DCT captures an idealized waveform, but human respiration during treatment is characterized by gradual baseline shifts and other deviations from a periodic signal. This paper describes a method for computing the dose delivered to irregularly moving targets based on 1D or 3D waveforms captured at the time of delivery. METHODS The procedure uses CT or 4DCT images for dose calculation, and 1D or 3D respiratory waveforms of the target position at time of delivery. Dose volumes are converted from their Cartesian geometry into a beam-specific radiological depth space, parameterized in 2D by the beam aperture, and longitudinally by the radiological depth. In this new frame of reference, the proton doses are translated according to the motion found in the 1D or 3D trajectory. These translated dose volumes are weighted and summed, then transformed back into Cartesian space, yielding an estimate of the dose that includes the effect of the measured breathing motion. The method was validated using a synthetic lung phantom and a single representative patient CT. Simulated 4DCT was generated for the phantom with 2 cm peak-to-peak motion. RESULTS A passively-scattered proton treatment plan was generated using 6 mm and 5 mm smearing for the phantom and patient plans, respectively. The method was tested without motion, and with two simulated breathing signals: a 2 cm amplitude sinusoid, and a 2 cm amplitude sinusoid with 3 cm linear drift in the phantom. The tumor positions were equally weighted for the patient calculation. Motion-corrected dose was computed based on the mid-ventilation CT image in the phantom and the peak exhale position in the patient. Gamma evaluation was 97.8% without motion, 95.7% for 2 cm sinusoidal motion, 95.7% with 3 cm drift in the phantom (2 mm, 2%), and 90.8% (3 mm, 3%)for the patient data. CONCLUSIONS We have demonstrated a method for accurately reproducing proton dose to an irregularly moving target from a single CT image. We believe this algorithm could prove a useful tool to study the dosimetric impact of baseline shifts either before or during treatment.
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Affiliation(s)
- Justin Phillips
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
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