医学
放射治疗
锥束ct
宫颈癌
核医学
外照射放疗
子宫颈
放射治疗计划
影像引导放射治疗
放射科
癌症
计算机断层摄影术
近距离放射治疗
内科学
作者
Nina Boje Kibsgaard Jensen,Marianne S. Assenholt,Lars Fokdal,Anne Vestergaard,Annette Schouboe,Eva Bruun Kjaersgaard,Annette Boejen,Lars Nyvang,Jacob Christian Lindegaard,Kari Tanderup
标识
DOI:10.1016/j.phro.2018.12.002
摘要
Organ motion is a challenge during high-precision external beam radiotherapy in cervical cancer, and improved strategies for treatment adaptation and monitoring of target dose coverage are needed. This study evaluates a cone beam computed tomography (CBCT)-based approach.In twenty-three patients, individualized internal target volumes (ITVs) were generated from pre-treatment MRI and CT scans with full and empty bladders. The target volumes encompassed high-risk clinical target volume (CTV-T HR) (gross tumor volume + remaining cervix) and low risk (LR) CTV-T (CTV-T HR + uterus + parametriae + upper vagina). Volumetric Modulated Arc Therapy (VMAT) was used to deliver a dose of 45 Gy in 25 fractions. CBCTs were used for setup and for radiation therapists (RTTs) to evaluate the target coverage (inside/outside the planning target volume). CBCTs were reviewed offline. Estimates of the dose delivered with minimum (point) doses across all fractions to CTV-T HR (aim 42.75 Gy) and CTV-T LR (aim 40 Gy) were assessed. In patients with insufficient dose coverage, re-plans were generated based on previous imaging.Median (range) of the ITV-margins (mean of anterior-posterior margins) related to uterus and cervix was 1.2 (0.5-2.2 and 1.0-2.1) cm. RTTs were able to assess the target coverage in 90% of all CBCTs (505/563). With re-planning, one patient had considerable benefit (12.7 Gy increase of minimum dose) to CTV-T LR_vagina, four patients had improved dose to the CTV-T LR_uterus (1.2-1.8 Gy), and 3 patients did not benefit from re-planning.Daily CBCT-based monitoring of target coverage by the RTTs has proven safe with limited workload. It allows for reduction in the treated volumes without compromising the target dose coverage.
科研通智能强力驱动
Strongly Powered by AbleSci AI