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Objective:To effectively quantify and evaluate the quality of different deformation registration algorithms, in order to enhance the possibility of implementing deformation registration in clinical practice.Methods:The Jacobian determinant mean (JDM) is proposed based on the Jacobian determinant (JD) of displacement vector field (DVF), and the Jacobian determinant error (DJDE) is introduced by incorporating the JD of the inverse DVF. The optical flow method (OF-DIR) and fast demons method with elastic regularization (FD-DIR) were tested on nasopharyngeal and lung cancer datasets. Finally, JDM and DJDE with the Jacobian determinant negative percentage (JDNP), inverse consistency error (ICE) and normalized mean square error (NMSE) were used to evaluate the registration algorithms and compare the differences evaluation indicators in different tumor images and different algorithms, and the receiver operating curve (ROC) was analyzed in evaluation.Results:In lung cancer, OF-DIR outperformed FD-DIR in terms of JDM, NMSE, DJDE and ICE, and the difference was statistically significant( z = -2.24, -4.84, t = 4.01, 6.54, P<0.05). In nasopharyngeal carcinoma, DJDE, ICE and NMSE of OF-DIR were superior to FD-DIR, and the difference was statistically significant ( t = 4.46, -7.49, z = -2.22, P<0.05), but there was no significant difference in JDM ( P>0.05). In lung cancer and nasopharyngeal carcinoma, JDNP of OF-DIR was worse than that of FD-DIR, and the difference was statistically significant ( z = -4.29, -4.02, P<0.01). In addition, DJDE is more specific and sensitive on ROC curve (AUC=0.77), and has different performance result for tumor images at different sites. Conclusions:The JDM and DJDE evaluation metrics proposed are effective for deformation registration algorithms. OF-DIR is suitable for both lung cancer and nasopharyngeal carcinoma, while the influence of organ motion on the registration effect should be considered when using FD-DIR.
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Objective:To investigate the necessity of adaptive re-planning during radiotherapy for nasopharyngeal carcinoma (NPC) and its impact on dose improvement.Methods:Clinical data of 89 NPC patients admitted to Sun Yat-sen University Cancer Center from July 2014 to December 2017 were retrospectively analyzed. All patients received 25+7 rounds of adaptive re-planning during radiotherapy. Plan-A was defined as the initial CT scan-based 25-fraction radiotherapy plan, while plan-B was defined as the re-planned 7-fraction radiotherapy plan based on a subsequent CT scan. The changes in the target and parotid gland volumes were compared between plan-A and plan-B. Plan-I was a one-time simulation of plan-A extended to 32 fraction radiotherapy plan, and plan-II was generated through registration and fusion of the plan-A and plan-B for adaptive re-planning. The differences in dose metrics, homogeneity index (HI), conformity index (CI), and dose to organs at risk (OAR) were compared between plan-I and plan-II. Statistical analysis was performed by using paired t-test. Results:Compared with plan-A, the gross tumor volume of massive bleeding lesions (GTV nx) and parotid gland volume of plan-B were decreased by 13.14% and 11.12%, respectively (both P<0.001). While planning clinical target volume of metastatic lymph nodes (PCTV nd) of plan-B was increased by 7.75%( P<0.001). There were significant changes in the lymph nodes of plan-A and plan-B. The D mean, D 5%, D 95% of massive bleeding lesions planning target volume (PTV nx) and D 5% of high risk planning target volume (PTV1) in plan-II were all significantly higher than those in plan-I (all P<0.05). The CI of PTV nx and PTV1 in plan-II was closer to 1 than that in plan-I. In all assessed OAR, the D mean, D 50%, and D max of plan-II were significantly lower than those of plan-I (all P<0.05). Conclusions:During radiotherapy, NPC patients may experience varying degrees of primary tumor shrinkage, parotid gland atrophy, and lymph node changes. It is necessary to deliver re-planning and significantly improve the dose of target areas and OAR.
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Objective:To analyze the dosimetric differences of volumetric modulated arc therapy (VMAT) plans for lung cancer caused by different dose calculation algorithms and radiation field settings and thus to provide a reference for designing clinical VMAT plans for lung cancer.Methods:This study randomly selected 20 patients with lung cancer and divided them into four groups of VMAT plans, namely, a group adopting two fields and two arcs based on the AAA algorithm (2F2A_AAA), a group employing two fields and two arcs based on the AXB algorithm (2F2A_AXB), a group using two fields and two arcs based on the MC algorithm (2F2A_MC), and a group adopting one field and two arcs based on the MC algorithm (1F2A_MC). Then, this study evaluated the target coverage, high-dose control, dose homogeneity index (HI), conformity index (CI), and organs at risk (OARs) of the plans using different algorithms and radiation field settings.Results:The planning target volume (PTV) results of two fields combined with two arcs (2F2A) of three groups using different algorithms are as follows. 2F2A_MC achieved better results in both D1% and V 95% (the relative volume of the target volume surrounded by 95% of the prescribed dose) of planning gross target volume (PGTV) than 2F2A_AAA (D1%: t=-2.44, P=0.03; V95%:z=-2.04, P=0.04) and 2F2A_AXB (D1%: t=2.34, P=0.03; z=-3.21, P < 0.01). 2F2A_AXB outperformed 2F2A_AAA ( z=-3.66, P < 0.01) and was comparable to 2F2A_MC in terms of the CI of PGTV. Regarding OARs, 2F2A_AXB and 2F2A_MC decreased the V5 Gy of the whole lung by 0.68% ( z=-2.69, P=0.01) and 3.05% ( z=-3.52, P < 0.01), respectively compared to 2F2A_AAA. 2F2A_AXB achieved a whole-lung Dmean of 1776.44 cGy, which was superior to that of 2F2A_MC ( t=2.67, P=0.02) and 2F2A_AAA ( t=8.62, P < 0.01). Compared to 2F2A_AAA and 2F2A_MC, 2F2A_AXB decreased the V20 Gy of Body_5 mm by 1.45% ( z=-3.88, P < 0.01) and 2.01% ( z=-3.66, P < 0.01), respectively. The results of the two groups with different field settings showed that 1F2A_MC was superior to 2F2A_MC in both the CI of PTV1 and the HI of PTV2 (CI: t=2.61, P=0.02; HI: z=-2.20, P=0.03). Moreover, 1F2A_MC increased the Dmean of the whole lung by 26.29 cGy compared to 2F2A_MC ( t=2.28, P=0.04). Conclusions:Regarding the design of VMAT plans for lung cancer, the MC algorithm is suitable for the target priority and the AXB algorithm is suitable for the OAR priority. When only the MC algorithm is available, it is recommended to choose 1F2A in the case of target priority and select 2F2A in the case of OAR priority.