Dose-volume histogram predictors of chronic gastrointestinal complications after radical hysterectomy and postoperative intensity modulated radiotherapy for early-stage cervical cancer

BMC cancer(2014)

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摘要
Background The small bowel is one of the critical organs involved in gastrointestinal complications in cervical cancer treated with postoperative intensity modulated radiotherapy. Even with modest doses of radiation therapy (45-50Gy), the risk of severe injury from postoperative radiation therapy is between 5% and 15%. Up to now, a predictive model of acute GI complications of the small bowel has been established with the aid of Quantitative Analyses of Normal Tissue Effects in the Clinic. However, the correlation between dose-volume effect and chronic GI complications of the small bowel has not been extensively investigated. In the article, the correlation has been studied preliminarily. Methods This study analyzed 84 patients who underwent postoperative IMRT. The organ at risk that was contoured was the small bowel loops. DVH parameters subjected to analysis included maximum and mean dose, the volume of these organs receiving more than 30, 40, and 50 Gy (V30-50 volume) and the volume of V30-50 to total volume (V30-50 ratio). Association between DVH parameters or clinical factors and the incidence of grade 1–2 chronic GI complications were evaluated. Results Body position and RT total dose are significantly associated with grade 1–2 chronic GI complications after postoperative IMRT in early-stage cervical cancer patients. Maximum dose and V40 ratio of the small bowel loops were significantly associated with chronic GI complications ( P < 0.05). The optimal threshold were 5586 cGy (maximum dose) and 28% (V40 ratio) of the small bowel loops. Conclusions Maximum dose and V40 ratio of the small bowel loops should be considered synthetically before postoperative IMRT for early-stage cervical cancer.
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关键词
Planning Target Volume,Clinical Target Volume,Radiation Therapy Oncology Group,Radical Hysterectomy,Cervical Cancer Patient
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