Lalit Kumar1,2, Vimal Kishore3, Manindra Bhushan2, Pawan Kumar1, Rahul Lal Chaudhary2. 1. Department of Applied Science and Humanities, Dr. A.P.J Abdul Kalam Technical University, Lucknow, India. 2. Medical Physics Division and Radiation Oncology Department, Rajiv Gandhi Cancer Institute and Research Center, New Delhi, India. 3. Department of Applied Science and Humanities, Bundelkhand Institute of Engineering and Technology, Jhansi, India.
Abstract
BACKGROUND: Acuros XB (AXB) may predict better rectal toxicities and treatment outcomes in cervix carcinoma. The aim of the study was to quantify the potential impact of AXB computations on the cervix radiotherapy using the RapidArc (RA ) technique as compared to anisotropic analytical algorithm (AA) computations. MATERIALS AND METHODS: A cohort of 30 patients previously cared for cervix carcinoma (stages II-IIIB) was selected for the present analysis. The RA plans were computed using AA and AXB dose computation engines under identical beam setup and MLC pattern. RESULTS: There was no significant (p > 0.05) difference in D95% and D98% to the planning target volume (PTV); moreover, a significant (p < 0.05) rise was noticed for mean dose to the PTV (0.26%), D50% (0.26%), D2% (0.80%) and V110% (44.24%) for AXB computation as compared to AA computations. Further, AXB estimated a significantly (p < 0.05) lower value for maximum and minimum dose to the PTV. Additionally, there was a significant (p < 0.05) reduction observed in mean dose to organs at risk (OARs) for AXB computation as compared to AA, though the reduction in mean dose was non-significant (p > 0.05) for the rectum. The maximum difference observed was 4.78% for the rectum V50Gy, 1.72%, 1.15% in mean dose and 2.22%, 1.48% in D2% of the left femur and right femur, respectively, between AA and AXB dose estimations. CONCLUSION: For similar target coverage, there were significant differences observed between the AAA and AXB computations. AA underestimates the V50Gy of the rectum and overestimates the mean dose and D2% for femoral heads as compared to AXB. Therefore, the use of AXB in the case of cervix carcinoma may predict better rectal toxicities and treatment outcomes in cervix carcinoma using the RA technique.
BACKGROUND: Acuros XB (AXB) may predict better rectal toxicities and treatment outcomes in cervix carcinoma. The aim of the study was to quantify the potential impact of AXB computations on the cervix radiotherapy using the RapidArc (RA ) technique as compared to anisotropic analytical algorithm (AA) computations. MATERIALS AND METHODS: A cohort of 30 patients previously cared for cervix carcinoma (stages II-IIIB) was selected for the present analysis. The RA plans were computed using AA and AXB dose computation engines under identical beam setup and MLC pattern. RESULTS: There was no significant (p > 0.05) difference in D95% and D98% to the planning target volume (PTV); moreover, a significant (p < 0.05) rise was noticed for mean dose to the PTV (0.26%), D50% (0.26%), D2% (0.80%) and V110% (44.24%) for AXB computation as compared to AA computations. Further, AXB estimated a significantly (p < 0.05) lower value for maximum and minimum dose to the PTV. Additionally, there was a significant (p < 0.05) reduction observed in mean dose to organs at risk (OARs) for AXB computation as compared to AA, though the reduction in mean dose was non-significant (p > 0.05) for the rectum. The maximum difference observed was 4.78% for the rectum V50Gy, 1.72%, 1.15% in mean dose and 2.22%, 1.48% in D2% of the left femur and right femur, respectively, between AA and AXB dose estimations. CONCLUSION: For similar target coverage, there were significant differences observed between the AAA and AXB computations. AA underestimates the V50Gy of the rectum and overestimates the mean dose and D2% for femoral heads as compared to AXB. Therefore, the use of AXB in the case of cervix carcinoma may predict better rectal toxicities and treatment outcomes in cervix carcinoma using the RA technique.
Authors: Oleg N Vassiliev; Todd A Wareing; Ian M Davis; John McGhee; Douglas Barnett; John L Horton; Kent Gifford; Gregory Failla; Uwe Titt; Firas Mourtada Journal: Int J Radiat Oncol Biol Phys Date: 2008-09-01 Impact factor: 7.038
Authors: Marc Arbyn; Elisabete Weiderpass; Laia Bruni; Silvia de Sanjosé; Mona Saraiya; Jacques Ferlay; Freddie Bray Journal: Lancet Glob Health Date: 2019-12-04 Impact factor: 26.763