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For: Giglioli FR, Clemente S, Esposito M, Fiandra C, Marino C, Russo S, Strigari L, Villaggi E, Stasi M, Mancosu P. Frontiers in planning optimization for lung SBRT. Physica Medica 2017;44:163-70. [DOI: 10.1016/j.ejmp.2017.05.064] [Cited by in Crossref: 16] [Cited by in F6Publishing: 18] [Article Influence: 3.2] [Reference Citation Analysis]
Number Citing Articles
1 An X, Dong Z. Development and evaluation of a three-step automatic planning technique for lung Stereotactic Body Radiation Therapy based on performance examination of advanced settings in Pinnacle's auto-planning module. Applied Radiation and Isotopes 2022. [DOI: 10.1016/j.apradiso.2022.110434] [Reference Citation Analysis]
2 Wei Z, Peng X, He L, Wang J, Liu Z, Xiao J. Treatment plan comparison of volumetric-modulated arc therapy to intensity-modulated radiotherapy in lung stereotactic body radiotherapy using either 6- or 10-MV photon energies. J Appl Clin Med Phys 2022;:e13714. [PMID: 35808973 DOI: 10.1002/acm2.13714] [Reference Citation Analysis]
3 Yoosuf AM, Ahmad MB, AlShehri S, Alhadab A, Alqathami M. Investigation of optimum minimum segment width on VMAT plan quality and deliverability: A comprehensive dosimetric and clinical evaluation using DVH analysis. J Appl Clin Med Phys 2021;22:29-40. [PMID: 34592787 DOI: 10.1002/acm2.13417] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
4 Critchfield LS, Visak J, Bernard ME, Randall ME, McGarry RC, Pokhrel D. Automation and integration of a novel restricted single-isocenter stereotactic body radiotherapy (a-RESIST) method for synchronous two lung lesions. J Appl Clin Med Phys 2021;22:56-65. [PMID: 34032380 DOI: 10.1002/acm2.13259] [Reference Citation Analysis]
5 Sevillano D, Núñez LM, Chevalier M, García-Vicente F. Application of discrete cosine transform to assess the effect of tumor motion variations on the definition of ITV in lung and liver SBRT. Phys Med 2021;84:132-40. [PMID: 33894583 DOI: 10.1016/j.ejmp.2021.03.036] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
6 Mancosu P, Russo S, Antonucci AR, Stasi M. Lean Thinking to manage a national working group on physics aspects of Stereotactic Body Radiation Therapy. Med Phys 2021;48:2050-6. [PMID: 33598932 DOI: 10.1002/mp.14783] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Desai D, Narayanasamy G, Bimali M, Cordrey I, Elasmar H, Srinivasan S, Johnson EL. Cleaning the dose falloff in lung SBRT plan. J Appl Clin Med Phys 2021;22:100-8. [PMID: 33285036 DOI: 10.1002/acm2.13113] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
8 Merlotti A, Bonomo P, Ragona R, Trovò M, Alongi F, Mazzola R, Vigna Taglianti R, Gianello L, Reali A, Bergesio F, Lucio F, Boriano A, De Maggi A, Russi E. Dose prescription in SBRT for early-stage non-small cell lung cancer: are we all speaking the same language? Tumori 2021;107:182-7. [PMID: 32515301 DOI: 10.1177/0300891620929425] [Reference Citation Analysis]
9 Marino C, Garibaldi C, Veronese I, Carbonini C, Russo S, Stasi M, Mancosu P. A national survey on technology and quality assurance for stereotactic body radiation therapy. Physica Medica 2019;65:6-14. [DOI: 10.1016/j.ejmp.2019.07.025] [Cited by in Crossref: 4] [Cited by in F6Publishing: 7] [Article Influence: 1.3] [Reference Citation Analysis]
10 Chun M, Joon An H, Kwon O, Oh DH, Park JM, Kim JI. Impact of plan parameters and modulation indices on patient-specific QA results for standard and stereotactic VMAT. Phys Med 2019;62:83-94. [PMID: 31153402 DOI: 10.1016/j.ejmp.2019.05.005] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 1.7] [Reference Citation Analysis]
11 Alharthi T, Arumugam S, Vial P, Holloway L, Thwaites D. EPID sensitivity to delivery errors for pre-treatment verification of lung SBRT VMAT plans. Phys Med 2019;59:37-46. [PMID: 30928064 DOI: 10.1016/j.ejmp.2019.02.007] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
12 Esposito M, Masi L, Zani M, Doro R, Fedele D, Garibaldi C, Clemente S, Fiandra C, Giglioli FR, Marino C, Orsingher L, Russo S, Stasi M, Strigari L, Villaggi E, Mancosu P. SBRT planning for spinal metastasis: indications from a large multicentric study. Strahlenther Onkol 2019;195:226-35. [PMID: 30353349 DOI: 10.1007/s00066-018-1383-2] [Cited by in Crossref: 14] [Cited by in F6Publishing: 18] [Article Influence: 3.5] [Reference Citation Analysis]
13 Vloet A, Li W, Giuliani M, Seco P, Silver L, Sun A, Bissonnette JP. Comparison of residual geometric errors obtained for lung SBRT under static beams and VMAT techniques: Implications for PTV margins. Phys Med 2018;52:129-32. [PMID: 30139601 DOI: 10.1016/j.ejmp.2018.07.009] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 0.8] [Reference Citation Analysis]
14 Garibaldi C, Moretti E, Russo S, Talamonti C, Villaggi E, Mancosu P. SBRT for pancreatic cancer: In regard of Bohoudi et al. Radiotherapy and Oncology 2018;127:509-10. [DOI: 10.1016/j.radonc.2018.04.001] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
15 Alharthi T, Pogson EM, Arumugam S, Holloway L, Thwaites D. Pre-treatment verification of lung SBRT VMAT plans with delivery errors: Toward a better understanding of the gamma index analysis. Physica Medica 2018;49:119-28. [DOI: 10.1016/j.ejmp.2018.04.005] [Cited by in Crossref: 9] [Cited by in F6Publishing: 11] [Article Influence: 2.3] [Reference Citation Analysis]
16 Mancosu P, Nisbet A, Jornet N. Editorial: The role of medical physics in lung SBRT. Phys Med 2018;45:205-6. [PMID: 29325801 DOI: 10.1016/j.ejmp.2018.01.001] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 0.8] [Reference Citation Analysis]
17 Liu H, Andrews M, Markovich A, Zhuang T. Dosimetric effect of uncorrected rotations in lung SBRT with stereotactic imaging guidance. Physica Medica 2017;42:197-202. [DOI: 10.1016/j.ejmp.2017.09.135] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 1.0] [Reference Citation Analysis]
18 Kawata Y, Arimura H, Ikushima K, Jin Z, Morita K, Tokunaga C, Yabu-Uchi H, Shioyama Y, Sasaki T, Honda H, Sasaki M. Impact of pixel-based machine-learning techniques on automated frameworks for delineation of gross tumor volume regions for stereotactic body radiation therapy. Phys Med. 2017;42:141-149. [PMID: 29173908 DOI: 10.1016/j.ejmp.2017.08.012] [Cited by in Crossref: 8] [Cited by in F6Publishing: 11] [Article Influence: 1.6] [Reference Citation Analysis]