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Chiou YR, Lin TC, Ji JH, Shiau AC, Huang CH, Liang JA. Large Pleural Metastases With Significant Inter-fractional Volume Reduction During Online Adaptive Radiotherapy: A Case Report With Dosimetry Comparison. Cureus 2024; 16:e68407. [PMID: 39360108 PMCID: PMC11445199 DOI: 10.7759/cureus.68407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/30/2024] [Indexed: 10/04/2024] Open
Abstract
Online adaptive radiotherapy (oART) dose calculation relies on synthetic computed tomography (sCT), which notably influences anatomical changes. This study elucidates how sCT may respond to significant inter-fractional tumor volume reduction and its subsequent impact on dose distribution. In this case report, we exported sCT and cone-beam CT (CBCT) images from each treatment session. We retrospectively analyzed 20 adaptive and scheduled plans of a patient receiving oART for large pleural metastases with notable inter-fractional tumor regression. By overriding the CT number of the dissipated tumor volume with that of the lungs on each sCT, we recalculated each plan. We compared the dose distribution between the adaptive and scheduled plans. Percentage dose difference and 3D gamma analysis were employed to assess dose variability. Results of the dose analysis showed that, compared to the online (non-overridden) plans, the recalculated plans using overridden sCT demonstrated right-shifted dose-volume histogram curves for the targets and right lung, with a slight but statistically significant increase of no less than 1.5% in D mean and D max for the targets and right lung. The location of hotspots shifted in alignment with tumor shrinkage and beam arrangement. Both recalculated adaptive and scheduled plans achieved ideal GTV, CTV, and PTV coverage, with adaptive plans significantly reducing the dose and irradiated volume to the right lung. In conclusion, as the pleural tumor volume decreased, online plans slightly underestimated the dose distribution and shifted the location of hotspots, though this remained clinically acceptable. Importantly, adaptive plans significantly minimized the irradiated volume of the critical OAR (right lung) while ensuring optimal dose coverage of the target volume, demonstrating the potential of sCT and adaptive oART to enhance treatment precision and efficacy in dynamically changing tumor environments.
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Affiliation(s)
- Yu-Rou Chiou
- Department of Radiation Oncology, China Medical University Hospital, Taichung City, TWN
| | - Ting Chun Lin
- Department of Radiation Oncology, China Medical University Hospital, Taichung City, TWN
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung City, TWN
| | - Jin-Huei Ji
- Department of Radiation Oncology, China Medical University Hospital, Taichung City, TWN
| | - An-Cheng Shiau
- Department of Radiation Oncology, China Medical University Hospital, Taichung City, TWN
- Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, TWN
| | - Chi-Hsien Huang
- Department of Radiation Oncology, China Medical University Hospital, Taichung City, TWN
| | - Ji-An Liang
- Department of Radiation Oncology, China Medical University Hospital, Taichung City, TWN
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Hering S, Nieto A, Marschner S, Hofmaier J, Schmidt-Hegemann NS, da Silva Mendes V, Landry G, Niyazi M, Manapov F, Belka C, Corradini S, Eze C. The role of online MR-guided multi-fraction stereotactic ablative radiotherapy in lung tumours. Clin Transl Radiat Oncol 2024; 45:100736. [PMID: 38433949 PMCID: PMC10909605 DOI: 10.1016/j.ctro.2024.100736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 01/18/2024] [Accepted: 01/21/2024] [Indexed: 03/05/2024] Open
Abstract
Background The aim of this prospective observational study was to evaluate the dosimetry benefits, changes in pulmonary function, and clinical outcome of online adaptive MR-guided SBRT. Methods From 11/2020-07/2022, 45 consecutive patients with 59 lesions underwent multi-fraction SBRT (3-8 fractions) at our institution. Patients were eligible if they had biopsy-proven NSCLC or lung cancer/metastases diagnosed via clinical imaging. Endpoints were local control (LC) and overall survival (OS). We evaluated PTV/GTV dose coverage, organs at risk exposure, and changes in pulmonary function (PF). Acute toxicity was classified per the National Cancer Institute-Common Terminology Criteria for Adverse Events version 5.0. Results The median PTV was 14.4 cm3 (range: 3.4 - 96.5 cm3). In total 195/215 (91%) plans were reoptimised. In the reoptimised vs. predicted plans, PTV coverage by the prescribed dose increased in 94.6% of all fractions with a median increase in PTV VPD of 5.6% (range: -1.8 - 44.6%, p < 0.001), increasing the number of fractions with PTV VPD ≥ 95% from 33% to 98%. The PTV D95% and D98% (BED10) increased in 93% and 95% of all fractions with a median increase of 7.7% (p < 0.001) and 10.6% (p < 0.001). The PTV D95% (BED10) increased by a mean of 9.6 Gy (SD: 10.3 Gy, p < 0.001). At a median follow-up of 21.4 months (95% CI: 12.3-27.0 months), 1- and 2-year LC rates were 94.8% (95% CI: 87.6 - 100.0%) and 91.1% (95% CI: 81.3 - 100%); 1- and 2-year OS rates were 85.6% (95% CI: 75.0 - 96.3%) and 67.1 % (95% CI: 50.3 - 83.8%). One grade ≥ 3 toxicity and no significant reduction in short-term PF parameters were recorded. Conclusions Online adaptive MR-guided SBRT is an effective, safe and generally well tolerated treatment option for lung tumours achieving encouraging local control rates with significantly improved target volume coverage.
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Affiliation(s)
- Svenja Hering
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Alexander Nieto
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Sebastian Marschner
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Jan Hofmaier
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | | | | | - Guillaume Landry
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Maximilian Niyazi
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Farkhad Manapov
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
- Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
| | - Claus Belka
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
| | - Stefanie Corradini
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Chukwuka Eze
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
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Callens D, Aerts K, Berkovic P, Vandewinckele L, Lambrecht M, Crijns W. Are offline ART decisions for NSCLC impacted by the type of dose calculation algorithm? Tech Innov Patient Support Radiat Oncol 2024; 29:100236. [PMID: 38313556 PMCID: PMC10835600 DOI: 10.1016/j.tipsro.2024.100236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 01/03/2024] [Accepted: 01/09/2024] [Indexed: 02/06/2024] Open
Abstract
Introduction Decisions for plan-adaptations may be impacted by a transitioning from one dose-calculation algorithm to another. This study examines the impact on dosimetric-triggered offline adaptation in LA-NSCLC in the context of a transition from superposition/convolution dose calculation algorithm (Type-B) to linear Boltzmann equation solver dose calculation algorithms (Type-C). Materials & Methods Two dosimetric-triggered offline adaptive treatment workflows are compared in a retrospective planning study on 30 LA-NSCLC patients. One workflow uses a Type-B dose calculation algorithm and the other uses Type-C. Treatment plans were re-calculated on the anatomy of a mid-treatment synthetic-CT utilizing the same algorithm utilized for pre-treatment planning. Assessment for plan-adaptation was evaluated through a decision model based on target coverage and OAR constraint violation. The impact of algorithm during treatment planning was controlled for by recalculating the Type-B plan with Type-C. Results In the Type-B approach, 13 patients required adaptation due to OAR-constraint violations, while 15 patients required adaptation in the Type-C approach. For 8 out of 30 cases, the decision to adapt was opposite in both approaches. None of the patients in our dataset encountered CTV-target underdosage that necessitated plan-adaptation. Upon recalculating the Type-B approach with the Type-C algorithm, it was shown that 10 of the original Type-B plans revealed clinically relevant dose reductions (≥3%) on the CTV in their original plans. This re-calculation identified 21 plans in total that required ART. Discussion In our study, nearly one-third of the cases would have a different decision for plan-adaption when utilizing Type-C instead of Type-B. There was no substantial increase in the total number of plan-adaptations for LA-NSCLC. However, Type-C is more sensitive to altered anatomy during treatment compared to Type-B. Recalculating Type-B plans with the Type-C algorithm revealed an increase from 13 to 21 cases triggering ART.
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Affiliation(s)
- Dylan Callens
- Laboratory of Experimental Radiotherapy, KU Leuven, Leuven, Belgium
- Department of Radiation Oncology, UZ Leuven, Leuven, Belgium
| | - Karel Aerts
- Laboratory of Experimental Radiotherapy, KU Leuven, Leuven, Belgium
| | - Patrick Berkovic
- Laboratory of Experimental Radiotherapy, KU Leuven, Leuven, Belgium
- Department of Radiation Oncology, UZ Leuven, Leuven, Belgium
| | - Liesbeth Vandewinckele
- Laboratory of Experimental Radiotherapy, KU Leuven, Leuven, Belgium
- Department of Radiation Oncology, UZ Leuven, Leuven, Belgium
| | - Maarten Lambrecht
- Laboratory of Experimental Radiotherapy, KU Leuven, Leuven, Belgium
- Department of Radiation Oncology, UZ Leuven, Leuven, Belgium
| | - Wouter Crijns
- Laboratory of Experimental Radiotherapy, KU Leuven, Leuven, Belgium
- Department of Radiation Oncology, UZ Leuven, Leuven, Belgium
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Lemus OMD, Tanny S, Cummings M, Webster M, Wancura J, Jung H, Zhou Y, Yoon J, Pacella M, Zheng D. Influence of air mapping errors on the dosimetric accuracy of prostate CBCT-guided online adaptive radiation therapy. J Appl Clin Med Phys 2023; 24:e14057. [PMID: 37276082 PMCID: PMC10562036 DOI: 10.1002/acm2.14057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 04/27/2023] [Accepted: 05/11/2023] [Indexed: 06/07/2023] Open
Abstract
PURPOSE CBCT-guided online adaptive radiotherapy (oART) plans presently utilize daily synthetic CTs (sCT) that are automatically generated using deformable registration algorithms. These algorithms may have poor performance at reproducing variable volumes of gas present during treatment. Therefore, we have analyzed the air mapping error between the daily CBCTs and the corresponding sCT and explored its dosimetric effect on oART plan calculation. METHODS Abdominopelvic air volume was contoured on both the daily CBCT images and the corresponding synthetic images for 207 online adaptive pelvic treatments. Air mapping errors were tracked over all fractions. For two case studies representing worst case scenarios, dosimetric effects of air mapping errors were corrected in the sCT images using the daily CBCT air contours, then recalculating dose. Dose volume histogram statistics and 3D gamma passing rates were used to compare the original and air-corrected sCT-based dose calculations. RESULTS All analyzed patients showed observable air pocket contour differences between the sCT and the CBCT images. The largest air volume difference observed in daily CBCT images for a given patient was 276.3 cc, a difference of more than 386% compared to the sCT. For the two case studies, the largest observed change in DVH metrics was a 2.6% reduction in minimum PTV dose, with all other metrics varying by less than 1.5%. 3D gamma passing rates using 1%/1 mm criteria were above 90% when comparing the uncorrected and corrected dose distributions. CONCLUSION Current CBCT-based oART workflow can lead to inaccuracies in the mapping of abdominopelvic air pockets from daily CBCT to the sCT images used for the optimization and calculation of the adaptive plan. Despite the large observed mapping errors, the dosimetric effects of such differences on the accuracy of the adapted plan dose calculation are unlikely to cause differences greater than 3% for prostate treatments.
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Affiliation(s)
- Olga M. Dona Lemus
- Department of Radiation OncologyUniversity of Rochester Medical CenterNew YorkNew YorkUSA
| | - Sean Tanny
- Department of Radiation OncologyUniversity of Rochester Medical CenterNew YorkNew YorkUSA
| | - Michael Cummings
- Department of Radiation OncologyUniversity of Rochester Medical CenterNew YorkNew YorkUSA
| | - Matthew Webster
- Department of Radiation OncologyUniversity of Rochester Medical CenterNew YorkNew YorkUSA
| | - Joshua Wancura
- Department of Radiation OncologyUniversity of Rochester Medical CenterNew YorkNew YorkUSA
| | - Hyunuk Jung
- Department of Radiation OncologyUniversity of Rochester Medical CenterNew YorkNew YorkUSA
| | - Yuwei Zhou
- Department of Radiation OncologyUniversity of Rochester Medical CenterNew YorkNew YorkUSA
| | - Jihyung Yoon
- Department of Radiation OncologyUniversity of Rochester Medical CenterNew YorkNew YorkUSA
| | - Matthew Pacella
- Department of Radiation OncologyUniversity of Rochester Medical CenterNew YorkNew YorkUSA
| | - Dandan Zheng
- Department of Radiation OncologyUniversity of Rochester Medical CenterNew YorkNew YorkUSA
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Sager O, Dincoglan F, Demiral S, Uysal B, Gamsiz H, Ozcan F, Colak O, Elcim Y, Gundem E, Dirican B, Beyzadeoglu M. Adaptive radiation therapy (art) for patients with limited-stage small cell lung cancer (LS-SCLC): A dosimetric evaluation. Indian J Cancer 2022; 0:358503. [PMID: 36861709 DOI: 10.4103/ijc.ijc_73_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Background Adaptive radiation therapy (ART) refers to redesigning of radiation therapy (RT) treatment plans with respect to dynamic changes in tumor size and location throughout the treatment course. In this study, we performed a comparative volumetric and dosimetric analysis to investigate the impact of ART for patients with limited-stage small cell lung cancer (LS-SCLC). Methods Twenty-four patients with LS-SCLC receiving ART and concomitant chemotherapy were included in the study. ART was performed by replanning of patients based on a mid-treatment computed tomography (CT)-simulation which was routinely scheduled for all patients 20-25 days after the initial CT-simulation. While the first 15 RT fractions were planned using the initial CT-simulation images, the latter 15 RT fractions were planned using the mid-treatment CT-simulation images acquired 20-25 days after the initial CT-simulation. In order to document the impact of ART, target and critical organ dose-volume parameters acquired from this adaptive radiation treatment planning (RTP) were compared with the RTP based solely on the initial CT-simulation to deliver the whole RT dose of 60 Gy. Results Statistically significant reduction was detected in gross tumor volume (GTV) and planning target volume (PTV) during the conventionally fractionated RT course along with statistically significant reduction in critical organ doses with incorporation of ART. Conclusion One-third of the patients in our study who were otherwise ineligible for curative intent RT due to violation of critical organ dose constraints could be treated with full dose irradiation by use of ART. Our results suggest significant benefit of ART for patients with LS-SCLC.
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Affiliation(s)
- Omer Sager
- Department of Radiation Oncology, University of Health Sciences, Gulhane Medical Faculty, Ankara, Turkey
| | - Ferrat Dincoglan
- Department of Radiation Oncology, University of Health Sciences, Gulhane Medical Faculty, Ankara, Turkey
| | - Selcuk Demiral
- Department of Radiation Oncology, University of Health Sciences, Gulhane Medical Faculty, Ankara, Turkey
| | - Bora Uysal
- Department of Radiation Oncology, University of Health Sciences, Gulhane Medical Faculty, Ankara, Turkey
| | - Hakan Gamsiz
- Department of Radiation Oncology, University of Health Sciences, Gulhane Medical Faculty, Ankara, Turkey
| | - Fatih Ozcan
- Department of Radiation Oncology, University of Health Sciences, Gulhane Medical Faculty, Ankara, Turkey
| | - Onurhan Colak
- Department of Radiation Oncology, University of Health Sciences, Gulhane Medical Faculty, Ankara, Turkey
| | - Yelda Elcim
- Department of Radiation Oncology, University of Health Sciences, Gulhane Medical Faculty, Ankara, Turkey
| | - Esin Gundem
- Department of Radiation Oncology, University of Health Sciences, Gulhane Medical Faculty, Ankara, Turkey
| | - Bahar Dirican
- Department of Radiation Oncology, University of Health Sciences, Gulhane Medical Faculty, Ankara, Turkey
| | - Murat Beyzadeoglu
- Department of Radiation Oncology, University of Health Sciences, Gulhane Medical Faculty, Ankara, Turkey
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Rodríguez De Dios N, Navarro-Martin A, Cigarral C, Chicas-Sett R, García R, Garcia V, Gonzalez JA, Gonzalo S, Murcia-Mejía M, Robaina R, Sotoca A, Vallejo C, Valtueña G, Couñago F. GOECP/SEOR radiotheraphy guidelines for non-small-cell lung cancer. World J Clin Oncol 2022; 13:237-266. [PMID: 35582651 PMCID: PMC9052073 DOI: 10.5306/wjco.v13.i4.237] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 08/27/2021] [Accepted: 04/09/2022] [Indexed: 02/06/2023] Open
Abstract
Non-small cell lung cancer (NSCLC) is a heterogeneous disease accounting for approximately 85% of all lung cancers. Only 17% of patients are diagnosed at an early stage. Treatment is multidisciplinary and radiotherapy plays a key role in all stages of the disease. More than 50% of patients with NSCLC are treated with radiotherapy (curative-intent or palliative). Technological advances-including highly conformal radiotherapy techniques, new immobilization and respiratory control systems, and precision image verification systems-allow clinicians to individualize treatment to maximize tumor control while minimizing treatment-related toxicity. Novel therapeutic regimens such as moderate hypofractionation and advanced techniques such as stereotactic body radiotherapy (SBRT) have reduced the number of radiotherapy sessions. The integration of SBRT into routine clinical practice has radically altered treatment of early-stage disease. SBRT also plays an increasingly important role in oligometastatic disease. The aim of the present guidelines is to review the role of radiotherapy in the treatment of localized, locally-advanced, and metastatic NSCLC. We review the main radiotherapy techniques and clarify the role of radiotherapy in routine clinical practice. These guidelines are based on the best available evidence. The level and grade of evidence supporting each recommendation is provided.
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Affiliation(s)
- Núria Rodríguez De Dios
- Department of Radiation Oncology, Hospital del Mar, Barcelona 08003, Spain
- Radiation Oncology Research Group, Hospital Del Mar Medical Research Institution, Barcelona 08003, Spain
- Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona 08003, Spain
| | - Arturo Navarro-Martin
- Department of Radiation Oncology, Thoracic Malignancies Unit, Hospital Duran i Reynals. ICO, L´Hospitalet de L, Lobregat 08908, Spain
| | - Cristina Cigarral
- Department of Radiation Oncology, Hospital Clínico de Salamanca, Salamanca 37007, Spain
| | - Rodolfo Chicas-Sett
- Department of Radiation Oncology, ASCIRES Grupo Biomédico, Valencia 46004, Spain
| | - Rafael García
- Department of Radiation Oncology, Hospital Ruber Internacional, Madrid 28034, Spain
| | - Virginia Garcia
- Department of Radiation Oncology, Hospital Universitario Arnau de Vilanova, Lleida 25198, Spain
| | | | - Susana Gonzalo
- Department of Radiation Oncology, Hospital Universitario La Princesa, Madrid 28006, Spain
| | - Mauricio Murcia-Mejía
- Department of Radiation Oncology, Hospital Universitario Sant Joan de Reus, Reus 43204, Tarragona, Spain
| | - Rogelio Robaina
- Department of Radiation Oncology, Hospital Universitario Arnau de Vilanova, Lleida 25198, Spain
| | - Amalia Sotoca
- Department of Radiation Oncology, Hospital Ruber Internacional, Madrid 28034, Spain
| | - Carmen Vallejo
- Department of Radiation Oncology, Hospital Universitario Ramón y Cajal, Madrid 28034, Spain
| | - German Valtueña
- Department of Radiation Oncology, Hospital Clínico Universitario Lozano Blesa, Zaragoza 50009, Spain
| | - Felipe Couñago
- Department of Radiation Oncology, Hospital Universitario Quirónsalud, Madrid 28223, Spain
- Department of Radiation Oncology, Hospital La Luz, Madrid 28003, Spain
- Department of Clinical, Universidad Europea, Madrid 28670, Spain
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Møller DS, Lutz CM, Khalil AA, Alber M, Holt MI, Kandi M, Schmidt HH, Tvilum M, Appelt A, Knap MM, Hoffmann L. Survival benefits for non-small cell lung cancer patients treated with adaptive radiotherapy. Radiother Oncol 2022; 168:234-240. [PMID: 35121030 DOI: 10.1016/j.radonc.2022.01.039] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 12/11/2021] [Accepted: 01/27/2022] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Tumor match and adaptive radiotherapy based on on-treatment imaging increases the precision of RT. This allows a reduction of treatment volume and, consequently, of the dose to organs at risk. We investigate the clinical benefits of tumor match and adaptive radiotherapy for a cohort of non-small cell lung cancer patients (NSCLC). METHODS In 2013, tumor match and adaptive radiotherapy based on daily cone-beam CT scans was introduced to ensure adaption of the radiotherapy treatment plan for all patients with significant anatomical changes during radiotherapy. Before 2013, the daily cone-beam CT scans were matched on the vertebra and anatomical changes were not evaluated systematically. To estimate the effect of tumor match and adaptive radiotherapy, 439 consecutive NSCLC patients treated with definitive chemo-radiotherapy (50-66 Gy/25-33 fractions, 2010-2018) were investigated retrospectively. They were split in two groups, pre-ART (before tumor match and adaptive radiotherapy, 184 patients), and ART (after tumor match and adaptive radiotherapy, 255 patients) and compared with respect to clinical, treatment-specific and dosimetric variables (χ2 tests, Mann Whitney U tests), progression, survival and radiation pneumonits (CTCAEv3). Progression-free and overall survival as well as radiation pneumonitis were compared with log-rank tests. Hazard ratios were estimated from Cox proportional hazard regression. RESULTS No significant differences in stage (p = 0.36), histology (p = 0.35), PS (p = 0.12) and GTV volumes (p = 0.24) were observed. Concomitant chemotherapy was administered more frequently in the ART group (78%) compared to preART (64%), p < 0.001. Median[range] PTV volumes decreased from 456 [71;1262] cm3 (preART) to 270 [31;1166] cm3 (ART), p < 0.001, thereby significantly reducing mean doses to lungs (median, preART 16.4 [1.9;24.7] Gy, ART 12.1 [1.7;19.4] Gy, p < 0.001) and heart (median, preART 8.0 [0.1;32.1] Gy, ART 4.4 [0.1;33.9] Gy, p < 0.001). The incidence of RP at nine months decreased significantly with ART (50% to 20% for symptomatic RP (≥G2), 21% to 7% for severe RP (≥G3), 6% to 0.4% for lethal RP (G5), all p < 0.001). The two-year progression free survival increased from 22% (preART) to 30% (ART), while the overall survival increased from 43% (preART) to 56% (ART). The median overall survival time increased from 20 (preART) to 28 months (ART). CONCLUSION Tumor match and adaptive radiotherapy significantly decreased radiation pneumonitis, while maintaining loco-regional control. Further, we observed a significantly improved progression-free and overall survival.
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Affiliation(s)
| | | | | | - Markus Alber
- Department of Radiation Oncology, Heidelberg University Hospital, Germany; Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg University Hospital, Germany
| | | | - Maria Kandi
- Department of Oncology, Aarhus University Hospital, Denmark
| | | | - Marie Tvilum
- Department of Oncology, Aarhus University Hospital, Denmark
| | - Ane Appelt
- Leeds Institute of Medical Research at St James's, University of Leeds, United Kingdom; Leeds Cancer Centre, St James's University Hospital, Leeds, United Kingdom
| | | | - Lone Hoffmann
- Department of Oncology, Aarhus University Hospital, Denmark
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Piperdi H, Portal D, Neibart SS, Yue NJ, Jabbour SK, Reyhan M. Adaptive Radiation Therapy in the Treatment of Lung Cancer: An Overview of the Current State of the Field. Front Oncol 2021; 11:770382. [PMID: 34912715 PMCID: PMC8666420 DOI: 10.3389/fonc.2021.770382] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 11/09/2021] [Indexed: 12/25/2022] Open
Abstract
Lung cancer treatment is constantly evolving due to technological advances in the delivery of radiation therapy. Adaptive radiation therapy (ART) allows for modification of a treatment plan with the goal of improving the dose distribution to the patient due to anatomic or physiologic deviations from the initial simulation. The implementation of ART for lung cancer is widely varied with limited consensus on who to adapt, when to adapt, how to adapt, and what the actual benefits of adaptation are. ART for lung cancer presents significant challenges due to the nature of the moving target, tumor shrinkage, and complex dose accumulation because of plan adaptation. This article presents an overview of the current state of the field in ART for lung cancer, specifically, probing topics of: patient selection for the greatest benefit from adaptation, models which predict who and when to adapt plans, best timing for plan adaptation, optimized workflows for implementing ART including alternatives to re-simulation, the best radiation techniques for ART including magnetic resonance guided treatment, algorithms and quality assurance, and challenges and techniques for dose reconstruction. To date, the clinical workflow burden of ART is one of the major reasons limiting its widespread acceptance. However, the growing body of evidence demonstrates overwhelming support for reduced toxicity while improving tumor dose coverage by adapting plans mid-treatment, but this is offset by the limited knowledge about tumor control. Progress made in predictive modeling of on-treatment tumor shrinkage and toxicity, optimizing the timing of adaptation of the plan during the course of treatment, creating optimal workflows to minimize staffing burden, and utilizing deformable image registration represent ways the field is moving toward a more uniform implementation of ART.
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Affiliation(s)
- Huzaifa Piperdi
- Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States
| | - Daniella Portal
- Rutgers Robert Wood Johnson Medical School, Rutgers, The State of New Jersey University, Piscataway, NJ, United States
| | - Shane S. Neibart
- Rutgers Robert Wood Johnson Medical School, Rutgers, The State of New Jersey University, Piscataway, NJ, United States
| | - Ning J. Yue
- Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States
| | - Salma K. Jabbour
- Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States
- Rutgers Robert Wood Johnson Medical School, Rutgers, The State of New Jersey University, Piscataway, NJ, United States
| | - Meral Reyhan
- Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States
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Paganetti H, Botas P, Sharp GC, Winey B. Adaptive proton therapy. Phys Med Biol 2021; 66:10.1088/1361-6560/ac344f. [PMID: 34710858 PMCID: PMC8628198 DOI: 10.1088/1361-6560/ac344f] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 10/28/2021] [Indexed: 12/25/2022]
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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10
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Holm AIS, Nyeng TB, S. Møller D, Assenholt MS, Hansen R, Nyvang L, Ravkilde T, Thomsen MS, Hoffmann L. Density calibrated cone beam CT as a tool for adaptive radiotherapy. Acta Oncol 2021; 60:1275-1282. [PMID: 34224288 DOI: 10.1080/0284186x.2021.1945678] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND Visual inspections of anatomical changes observed on daily cone-beam CT (CBCT) images are often used as triggers for radiotherapy plan adaptation to avoid unacceptable dose levels to the target or OARs. Direct CBCT dose calculations would improve the ability to adapt only those plans where dosimetric changes are observed. This study investigates the accuracy of dose calculations on CBCTs. MATERIALS AND METHODS Calibration curves were obtained for CBCT imagers at nine identical accelerators. CBCT scans of a phantom with different density inserts were recorded for two scan modes (Head-Neck and Pelvis) and mean calibration curves were calculated. Subsequently, CBCT scans of the phantom with six different density inserts were recorded, the dose distributions on the CBCTs were calculated and compared to dose on the planning CT (pCT). The uncertainty was quantified by the dosimetric difference between the pCT and the CBCT. The two mean calibration curves were used to calculate the daily delivered CBCT dose for ten Head-Neck-, eleven Lung-, and ten pelvic patients. Additional patient calculations were performed using low-HU empirically corrected calibration curves. Patient doses were compared on target coverage and mean dose, and D1cc for OARs. RESULTS The dose differences between pCT and CBCT for phantom data were small for all DVH parameters, with mean deviations below ±0.6% for both CBCT modes. For patient data, it was found that low-HU corrected calibration curves performed the best. The mean deviations for the mean dose and coverage of the target were 0.2%±0.7% and 0.1%±0.6%, across all patient groups. CONCLUSION Dose calculation on CBCT images results in target coverage and mean dose with an accuracy of the order of 1%, which makes this acceptable for clinical use. The CBCT mode specific calibration curves can be used at all identical imaging devices and for all patient groups.
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Affiliation(s)
- Anne I. S. Holm
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Tine B. Nyeng
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Ditte S. Møller
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Marianne S. Assenholt
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Rune Hansen
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Lars Nyvang
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Thomas Ravkilde
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Mette S. Thomsen
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
| | - Lone Hoffmann
- Department of Oncology, Section for Medical Physics, Aarhus University Hospital, Aarhus, Denmark
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11
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Rong Y, Rosu-Bubulac M, Benedict SH, Cui Y, Ruo R, Connell T, Kashani R, Latifi K, Chen Q, Geng H, Sohn J, Xiao Y. Rigid and Deformable Image Registration for Radiation Therapy: A Self-Study Evaluation Guide for NRG Oncology Clinical Trial Participation. Pract Radiat Oncol 2021; 11:282-298. [PMID: 33662576 PMCID: PMC8406084 DOI: 10.1016/j.prro.2021.02.007] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 01/05/2021] [Accepted: 02/16/2021] [Indexed: 02/08/2023]
Abstract
PURPOSE The registration of multiple imaging studies to radiation therapy computed tomography simulation, including magnetic resonance imaging, positron emission tomography-computed tomography, etc. is a widely used strategy in radiation oncology treatment planning, and these registrations have valuable roles in image guidance, dose composition/accumulation, and treatment delivery adaptation. The NRG Oncology Medical Physics subcommittee formed a working group to investigate feasible workflows for a self-study credentialing process of image registration commissioning. METHODS AND MATERIALS The American Association of Physicists in Medicine (AAPM) Task Group 132 (TG132) report on the use of image registration and fusion algorithms in radiation therapy provides basic guidelines for quality assurance and quality control of the image registration algorithms and the overall clinical process. The report recommends a series of tests and the corresponding metrics that should be evaluated and reported during commissioning and routine quality assurance, as well as a set of recommendations for vendors. The NRG Oncology medical physics subcommittee working group found incompatibility of some digital phantoms with commercial systems. Thus, there is still a need to provide further recommendations in terms of compatible digital phantoms, clinical feasible workflow, and achievable thresholds, especially for future clinical trials involving deformable image registration algorithms. Nine institutions participated and evaluated 4 commonly used commercial imaging registration software and various versions in the field of radiation oncology. RESULTS AND CONCLUSIONS The NRG Oncology Working Group on image registration commissioning herein provides recommendations on the use of digital phantom/data sets and analytical software access for institutions and clinics to perform their own self-study evaluation of commercial imaging systems that might be employed for coregistration in radiation therapy treatment planning and image guidance procedures. Evaluation metrics and their corresponding values were given as guidelines to establish practical tolerances. Vendor compliance for image registration commissioning was evaluated, and recommendations were given for future development.
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Affiliation(s)
- Yi Rong
- Department of Radiation Oncology, University of California Davis Cancer Center, Sacramento, California; Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
| | - Mihaela Rosu-Bubulac
- Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia
| | - Stanley H Benedict
- Department of Radiation Oncology, University of California Davis Cancer Center, Sacramento, California
| | - Yunfeng Cui
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina
| | - Russell Ruo
- Department of Medical Physics, McGill University Health Center, Montreal, QC, Canada
| | - Tanner Connell
- Department of Medical Physics, McGill University Health Center, Montreal, QC, Canada
| | - Rojano Kashani
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Kujtim Latifi
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center, Tampa, Florida
| | - Quan Chen
- Department of Radiation Medicine, University of Kentucky, Lexington, Kentucky
| | - Huaizhi Geng
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jason Sohn
- Department of Radiation Oncology, Allegheny Health Network, Pittsburgh, Pennsylvania
| | - Ying Xiao
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania
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12
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Jiang J, Riyahi Alam S, Chen I, Zhang P, Rimner A, Deasy JO, Veeraraghavan H. Deep cross-modality (MR-CT) educed distillation learning for cone beam CT lung tumor segmentation. Med Phys 2021; 48:3702-3713. [PMID: 33905558 DOI: 10.1002/mp.14902] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Revised: 03/27/2021] [Accepted: 04/06/2021] [Indexed: 12/25/2022] Open
Abstract
PURPOSE Despite the widespread availability of in-treatment room cone beam computed tomography (CBCT) imaging, due to the lack of reliable segmentation methods, CBCT is only used for gross set up corrections in lung radiotherapies. Accurate and reliable auto-segmentation tools could potentiate volumetric response assessment and geometry-guided adaptive radiation therapies. Therefore, we developed a new deep learning CBCT lung tumor segmentation method. METHODS The key idea of our approach called cross-modality educed distillation (CMEDL) is to use magnetic resonance imaging (MRI) to guide a CBCT segmentation network training to extract more informative features during training. We accomplish this by training an end-to-end network comprised of unpaired domain adaptation (UDA) and cross-domain segmentation distillation networks (SDNs) using unpaired CBCT and MRI datasets. UDA approach uses CBCT and MRI that are not aligned and may arise from different sets of patients. The UDA network synthesizes pseudo MRI from CBCT images. The SDN consists of teacher MRI and student CBCT segmentation networks. Feature distillation regularizes the student network to extract CBCT features that match the statistical distribution of MRI features extracted by the teacher network and obtain better differentiation of tumor from background. The UDA network was implemented with a cycleGAN improved with contextual losses separately on Unet and dense fully convolutional segmentation networks (DenseFCN). Performance comparisons were done against CBCT only using 2D and 3D networks. We also compared against an alternative framework that used UDA with MR segmentation network, whereby segmentation was done on the synthesized pseudo MRI representation. All networks were trained with 216 weekly CBCTs and 82 T2-weighted turbo spin echo MRI acquired from different patient cohorts. Validation was done on 20 weekly CBCTs from patients not used in training. Independent testing was done on 38 weekly CBCTs from patients not used in training or validation. Segmentation accuracy was measured using surface Dice similarity coefficient (SDSC) and Hausdroff distance at 95th percentile (HD95) metrics. RESULTS The CMEDL approach significantly improved (p < 0.001) the accuracy of both Unet (SDSC of 0.83 ± 0.08; HD95 of 7.69 ± 7.86 mm) and DenseFCN (SDSC of 0.75 ± 0.13; HD95 of 11.42 ± 9.87 mm) over CBCT only 2DUnet (SDSC of 0.69 ± 0.11; HD95 of 21.70 ± 16.34 mm), 3D Unet (SDSC of 0.72 ± 0.20; HD95 15.01 ± 12.98 mm), and DenseFCN (SDSC of 0.66 ± 0.15; HD95 of 22.15 ± 17.19 mm) networks. The alternate framework using UDA with the MRI network was also more accurate than the CBCT only methods but less accurate the CMEDL approach. CONCLUSIONS Our results demonstrate feasibility of the introduced CMEDL approach to produce reasonably accurate lung cancer segmentation from CBCT images. Further validation on larger datasets is necessary for clinical translation.
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Affiliation(s)
- Jue Jiang
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 1006, USA
| | - Sadegh Riyahi Alam
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 1006, USA
| | - Ishita Chen
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 1006, USA
| | - Perry Zhang
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 1006, USA
| | - Andreas Rimner
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 1006, USA
| | - Joseph O Deasy
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 1006, USA
| | - Harini Veeraraghavan
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 1006, USA
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13
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Nenoff L, Matter M, Amaya EJ, Josipovic M, Knopf AC, Lomax AJ, Persson GF, Ribeiro CO, Visser S, Walser M, Weber DC, Zhang Y, Albertini F. Dosimetric influence of deformable image registration uncertainties on propagated structures for online daily adaptive proton therapy of lung cancer patients. Radiother Oncol 2021; 159:136-143. [PMID: 33771576 DOI: 10.1016/j.radonc.2021.03.021] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 03/14/2021] [Accepted: 03/15/2021] [Indexed: 12/25/2022]
Abstract
PURPOSE A major burden of introducing an online daily adaptive proton therapy (DAPT) workflow is the time and resources needed to correct the daily propagated contours. In this study, we evaluated the dosimetric impact of neglecting the online correction of the propagated contours in a DAPT workflow. MATERIAL AND METHODS For five NSCLC patients with nine repeated deep-inspiration breath-hold CTs, proton therapy plans were optimised on the planning CT to deliver 60 Gy-RBE in 30 fractions. All repeated CTs were registered with six different clinically used deformable image registration (DIR) algorithms to the corresponding planning CT. Structures were propagated rigidly and with each DIR algorithm and reference structures were contoured on each repeated CT. DAPT plans were optimised with the uncorrected, propagated structures (propagated DAPT doses) and on the reference structures (ideal DAPT doses), non-adapted doses were recalculated on all repeated CTs. RESULTS Due to anatomical changes occurring during the therapy, the clinical target volume (CTV) coverage of the non-adapted doses reduces on average by 9.7% (V95) compared to an ideal DAPT doses. For the propagated DAPT doses, the CTV coverage was always restored (average differences in the CTV V95 < 1% compared to the ideal DAPT doses). Hotspots were always reduced with any DAPT approach. CONCLUSION For the patients presented here, a benefit of online DAPT was shown, even if the daily optimisation is based on propagated structures with some residual uncertainties. However, a careful (offline) structure review is necessary and corrections can be included in an offline adaption.
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Affiliation(s)
- Lena Nenoff
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland; Department of Physics, ETH Zurich, Switzerland.
| | - Michael Matter
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland; Department of Physics, ETH Zurich, Switzerland
| | | | - Mirjana Josipovic
- Department of Oncology, Rigshospitalet Copenhagen University Hospital, Denmark
| | - Antje-Christin Knopf
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, The Netherlands
| | - Antony John Lomax
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland; Department of Physics, ETH Zurich, Switzerland
| | - Gitte F Persson
- Department of Oncology, Rigshospitalet Copenhagen University Hospital, Denmark; Department of Oncology, Herlev-Gentofte Hospital Copenhagen University Hospital, Denmark; Department of Clinical Medicine, Faculty of Medical Sciences, University of Copenhagen, Denmark
| | - Cássia O Ribeiro
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, The Netherlands
| | - Sabine Visser
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, The Netherlands
| | - Marc Walser
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
| | - Damien Charles Weber
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland; Department of Radiation Oncology, University Hospital Zurich, Switzerland; Department of Radiation Oncology, University Hospital Bern, Switzerland
| | - Ye Zhang
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
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14
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Crockett CB, Samson P, Chuter R, Dubec M, Faivre-Finn C, Green OL, Hackett SL, McDonald F, Robinson C, Shiarli AM, Straza MW, Verhoeff JJC, Werner-Wasik M, Vlacich G, Cobben D. Initial Clinical Experience of MR-Guided Radiotherapy for Non-Small Cell Lung Cancer. Front Oncol 2021; 11:617681. [PMID: 33777759 PMCID: PMC7988221 DOI: 10.3389/fonc.2021.617681] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 01/12/2021] [Indexed: 02/06/2023] Open
Abstract
Curative-intent radiotherapy plays an integral role in the treatment of lung cancer and therefore improving its therapeutic index is vital. MR guided radiotherapy (MRgRT) systems are the latest technological advance which may help with achieving this aim. The majority of MRgRT treatments delivered to date have been stereotactic body radiation therapy (SBRT) based and include the treatment of (ultra-) central tumors. However, there is a move to also implement MRgRT as curative-intent treatment for patients with inoperable locally advanced NSCLC. This paper presents the initial clinical experience of using the two commercially available systems to date: the ViewRay MRIdian and Elekta Unity. The challenges and potential solutions associated with MRgRT in lung cancer will also be highlighted.
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Affiliation(s)
- Cathryn B. Crockett
- Radiotherapy Related Research, The Christie NHS Foundation Trust, Manchester, United Kingdom
| | - Pamela Samson
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, United States
| | - Robert Chuter
- Radiotherapy Related Research, The Christie NHS Foundation Trust, Manchester, United Kingdom
- Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
| | - Michael Dubec
- Radiotherapy Related Research, The Christie NHS Foundation Trust, Manchester, United Kingdom
- Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
| | - Corinne Faivre-Finn
- Radiotherapy Related Research, The Christie NHS Foundation Trust, Manchester, United Kingdom
- Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
| | - Olga L. Green
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, United States
| | - Sara L. Hackett
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Fiona McDonald
- Department of Radiotherapy, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Clifford Robinson
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, United States
| | - Anna-Maria Shiarli
- Department of Radiotherapy, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Michael W. Straza
- Department of Radiation Oncology, Froedtert and the Medical College of Wisconsin, Milwaukee, WI, United States
| | - Joost J. C. Verhoeff
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Maria Werner-Wasik
- Department of Radiation Oncology, Sidney Kimmel Cancer Center at Thomas Jefferson University, Philadelphia, PA, United States
| | - Gregory Vlacich
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, United States
| | - David Cobben
- Radiotherapy Related Research, The Christie NHS Foundation Trust, Manchester, United Kingdom
- Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
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15
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Kooshkaki O, Rezaei Z, Rahmati M, Vahedi P, Derakhshani A, Brunetti O, Baghbanzadeh A, Mansoori B, Silvestris N, Baradaran B. MiR-144: A New Possible Therapeutic Target and Diagnostic/Prognostic Tool in Cancers. Int J Mol Sci 2020; 21:ijms21072578. [PMID: 32276343 PMCID: PMC7177921 DOI: 10.3390/ijms21072578] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Revised: 04/02/2020] [Accepted: 04/04/2020] [Indexed: 12/14/2022] Open
Abstract
MicroRNAs (miRNAs) are small and non-coding RNAs that display aberrant expression in the tissue and plasma of cancer patients when tested in comparison to healthy individuals. In past decades, research data proposed that miRNAs could be diagnostic and prognostic biomarkers in cancer patients. It has been confirmed that miRNAs can act either as oncogenes by silencing tumor inhibitors or as tumor suppressors by targeting oncoproteins. MiR-144s are located in the chromosomal region 17q11.2, which is subject to significant damage in many types of cancers. In this review, we assess the involvement of miR-144s in several cancer types by illustrating the possible target genes that are related to each cancer, and we also briefly describe the clinical applications of miR-144s as a diagnostic and prognostic tool in cancers.
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Affiliation(s)
- Omid Kooshkaki
- Student Research Committee, Birjand University of Medical Sciences, Birjand 9717853577, Iran;
- Department of Immunology, Birjand University of Medical Sciences, Birjand 9717853577, Iran
| | - Zohre Rezaei
- Cellular and Molecular Research Center, Birjand University of Medical Sciences, Birjand 9717853577, Iran;
- Department of Biology, University of Sistan and Baluchestan, Zahedan 9816745845, Iran
| | - Meysam Rahmati
- Infectious and Tropical Diseases Research Center, Tabriz University of Medical Sciences, Tabriz 5166/15731, Iran;
| | - Parviz Vahedi
- Department of Anatomical Sciences, Maragheh University of Medical Sciences, Maragheh 5165665931, Iran;
| | - Afshin Derakhshani
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz 5165665811, Iran; (A.D.); (A.B.)
| | - Oronzo Brunetti
- Medical Oncology Unit—IRCCS Istituto Tumori “Giovanni Paolo II” of Bari, 70124 Bari, Italy;
| | - Amir Baghbanzadeh
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz 5165665811, Iran; (A.D.); (A.B.)
| | - Behzad Mansoori
- Department of Cancer and Inflammation Research, Institute for Molecular Medicine, University of Southern Denmark, 5230 Odense, Denmark;
| | - Nicola Silvestris
- Medical Oncology Unit—IRCCS Istituto Tumori “Giovanni Paolo II” of Bari, 70124 Bari, Italy;
- Department of Biomedical Sciences and Human Oncology DIMO—University of Bari, 70124 Bari, Italy
- Correspondence: (N.S.); (B.B.); Tel.: +39-0805555419 (N.S.); +98-413-3371440 (B.B.)
| | - Behzad Baradaran
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz 5165665811, Iran; (A.D.); (A.B.)
- Department of Immunology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz 5166614766, Iran
- Correspondence: (N.S.); (B.B.); Tel.: +39-0805555419 (N.S.); +98-413-3371440 (B.B.)
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