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Shi W, Tanzhu G, Chen L, Ning J, Wang H, Xiao G, Peng H, Jing D, Liang H, Nie J, Yi M, Zhou R. Radiotherapy in Preclinical Models of Brain Metastases: A Review and Recommendations for Future Studies. Int J Biol Sci 2024; 20:765-783. [PMID: 38169621 PMCID: PMC10758094 DOI: 10.7150/ijbs.91295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/14/2023] [Indexed: 01/05/2024] Open
Abstract
Brain metastases (BMs) frequently occur in primary tumors such as lung cancer, breast cancer, and melanoma, and are associated with notably short natural survival. In addition to surgical interventions, chemotherapy, targeted therapy, and immunotherapy, radiotherapy (RT) is a crucial treatment for BM and encompasses whole-brain radiotherapy (WBRT) and stereotactic radiosurgery (SRS). Validating the efficacy and safety of treatment regimens through preclinical models is imperative for successful translation to clinical application. This not only advances fundamental research but also forms the theoretical foundation for clinical study. This review, grounded in animal models of brain metastases (AM-BM), explores the theoretical underpinnings and practical applications of radiotherapy in combination with chemotherapy, targeted therapy, immunotherapy, and emerging technologies such as nanomaterials and oxygen-containing microbubbles. Initially, we provided a concise overview of the establishment of AM-BMs. Subsequently, we summarize key RT parameters (RT mode, dose, fraction, dose rate) and their corresponding effects in AM-BMs. Finally, we present a comprehensive analysis of the current research status and future directions for combination therapy based on RT. In summary, there is presently no standardized regimen for AM-BM treatment involving RT. Further research is essential to deepen our understanding of the relationships between various parameters and their respective effects.
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Affiliation(s)
- Wen Shi
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
| | - Guilong Tanzhu
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
| | - Liu Chen
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
| | - Jiaoyang Ning
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
| | - Hongji Wang
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
| | - Gang Xiao
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
| | - Haiqin Peng
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
| | - Di Jing
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
| | - Huadong Liang
- Department of Technology, Hunan SJA Laboratory Animal Co., Ltd., Changsha, Hunan Province, China
| | - Jing Nie
- Department of Technology, Hunan SJA Laboratory Animal Co., Ltd., Changsha, Hunan Province, China
| | - Min Yi
- Department of Technology, Hunan SJA Laboratory Animal Co., Ltd., Changsha, Hunan Province, China
| | - Rongrong Zhou
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- Xiangya Lung Cancer Center, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, China
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Palaniappan P, Knudsen Y, Meyer S, Gianoli C, Schnürle K, Würl M, Bortfeldt J, Parodi K, Riboldi M. Multi-stage image registration based on list-mode proton radiographies for small animal proton irradiation: A simulation study. Z Med Phys 2023:S0939-3889(23)00045-4. [PMID: 37353464 DOI: 10.1016/j.zemedi.2023.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 03/27/2023] [Accepted: 04/03/2023] [Indexed: 06/25/2023]
Abstract
We present a multi-stage and multi-resolution deformable image registration framework for image-guidance at a small animal proton irradiation platform. The framework is based on list-mode proton radiographies acquired at different angles, which are used to deform a 3D treatment planning CT relying on normalized mutual information (NMI) or root mean square error (RMSE) in the projection domain. We utilized a mouse X-ray micro-CT expressed in relative stopping power (RSP), and obtained Monte Carlo simulations of proton images in list-mode for three different treatment sites (brain, head and neck, lung). Rigid transformations and controlled artificial deformation were applied to mimic position misalignments, weight loss and breathing changes. Results were evaluated based on the residual RMSE of RSP in the image domain including the comparison of extracted local features, i.e. between the reference micro-CT and the one transformed taking into account the calculated deformation. The residual RMSE of the RSP showed that the accuracy of the registration framework is promising for compensating rigid (>97% accuracy) and non-rigid (∼95% accuracy) transformations with respect to a conventional 3D-3D registration. Results showed that the registration accuracy is degraded when considering the realistic detector performance and NMI as a metric, whereas the RMSE in projection domain is rather insensitive. This work demonstrates the pre-clinical feasibility of the registration framework on different treatment sites and its use for small animal imaging with a realistic detector. Further computational optimization of the framework is required to enable the use of this tool for online estimation of the deformation.
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Affiliation(s)
- Prasannakumar Palaniappan
- Department of Medical Physics - Experimental Physics, Ludwig-Maximilians-Universität München, Munich, Germany.
| | - Yana Knudsen
- Department of Medical Physics - Experimental Physics, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Sebastian Meyer
- Department of Medical Physics - Experimental Physics, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Chiara Gianoli
- Department of Medical Physics - Experimental Physics, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Katrin Schnürle
- Department of Medical Physics - Experimental Physics, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Matthias Würl
- Department of Medical Physics - Experimental Physics, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Jonathan Bortfeldt
- Department of Medical Physics - Experimental Physics, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Katia Parodi
- Department of Medical Physics - Experimental Physics, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Marco Riboldi
- Department of Medical Physics - Experimental Physics, Ludwig-Maximilians-Universität München, Munich, Germany
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Zhang Z, Yu S, Peng F, Tan Z, Zhang L, Li D, Yang P, Peng Z, Li X, Fang C, Wang Y, Liu Y. Advantages and robustness of partial VMAT with prone position for neoadjuvant rectal cancer evaluated by CBCT-based offline adaptive radiotherapy. Radiat Oncol 2023; 18:102. [PMID: 37330508 DOI: 10.1186/s13014-023-02285-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 05/18/2023] [Indexed: 06/19/2023] Open
Abstract
BACKGROUND AND PURPOSE This study aims to explore the advantages and robustness of the partial arc combined with prone position planning technique for radiotherapy in rectal cancer patients. Adaptive radiotherapy is recalculated and accumulated on the synthesis CT (sCT) obtained by deformable image registration between planning CT and cone beam CT (CBCT). Full and partial volume modulation arc therapy (VMAT) with the prone position on gastrointestinal and urogenital toxicity, based on the probability of normal tissue complications (NTCP) model in rectal cancer patients were evaluated. MATERIALS AND METHODS Thirty-one patients were studied retrospectively. The contours of different structures were outlined in 155 CBCT images. First, full VMAT (F-VMAT) and partial VMAT (P-VMAT) planning techniques were designed and calculated using the same optimization constraints for each individual patient. The Acuros XB (AXB) algorithm was used in order to generate more realistic dose distributions and DVH, considering the air cavities. Second, the Velocity 4.0 software was used to fuse the planning CT and CBCT to obtain the sCT. Then, the AXB algorithm was used in the Eclipse 15.6 software to conduct re-calculation based on the sCT to obtain the corresponding dose. Furthermore, the NTCP model was used to analyze its radiobiological side effects on the bladder and the bowel bag. RESULTS With a CTV coverage of 98%, when compared with F-VMAT, P-VMAT with the prone position technique can effectively reduce the mean dose of the bladder and the bowel bag. The NTCP model showed that the P-VMAT combined with the prone planning technique resulted in a significantly lower complication probability of the bladder (1.88 ± 2.08 vs 1.62 ± 1.41, P = 0.041) and the bowel bag (1.28 ± 1.70 vs 0.95 ± 1.52, P < 0.001) than the F-VMAT. In terms of robustness, P-VMAT was more robust than F-VMAT, considering that less dose and NTCP variation was observed in the CTV, bladder and bowel bag. CONCLUSION This study analyzed the advantages and robustness of the P-VMAT in the prone position from three aspects, based on the sCT fused by CBCT. Whether it is in regards to dosimetry, radiobiological effects or robustness, P-VMAT in the prone position has shown comparative advantages.
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Affiliation(s)
- Zhe Zhang
- Department of Radiation Oncology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Shou Yu
- Department of Radiation Oncology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Feng Peng
- Department of Radiation Oncology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Zhibo Tan
- Department of Radiation Oncology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Lei Zhang
- Department of Radiation Oncology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Daming Li
- Department of Radiation Oncology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Pengfei Yang
- Department of Radiation Oncology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Zhaoming Peng
- Department of Radiation Oncology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Xin Li
- Department of Radiation Oncology, Peking University Shenzhen Hospital, Shenzhen, China
- Shenzhen-Peking University, Hong Kong University of Science and Technology Medical Center, Shenzhen, China
| | - Chunfeng Fang
- Department of Radiation Oncology, Hebei Yizhou Cancer Hospital, Zhuozhou, China
| | - Yuenan Wang
- Department of Radiation Oncology, Peking University Shenzhen Hospital, Shenzhen, China.
| | - Yajie Liu
- Department of Radiation Oncology, Peking University Shenzhen Hospital, Shenzhen, China.
- Shenzhen-Peking University, Hong Kong University of Science and Technology Medical Center, Shenzhen, China.
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