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Validation of in-house knowledge-based planning model for advance-stage lung cancer patients treated using VMAT radiotherapy.


  • 影响因子:2.12
  • DOI:10.1259/bjr.20190535
  • 作者列表:"Tambe NS","Pires IM","Moore C","Cawthorne C","Beavis AW
  • 发表时间:2020-02-01

OBJECTIVES:Radiotherapy plan quality may vary considerably depending on planner's experience and time constraints. The variability in treatment plans can be assessed by calculating the difference between achieved and the optimal dose distribution. The achieved treatment plans may still be suboptimal if there is further scope to reduce organs-at-risk doses without compromising target coverage and deliverability. This study aims to develop a knowledge-based planning (KBP) model to reduce variability of volumetric modulated arc therapy (VMAT) lung plans by predicting minimum achievable lung volume-dose metrics. METHODS:Dosimetric and geometric data collected from 40 retrospective plans were used to develop KBP models aiming to predict the minimum achievable lung dose metrics via calculating the ratio of the residual lung volume to the total lung volume. Model accuracy was verified by replanning 40 plans. Plan complexity metrics were calculated using locally developed script and their effect on treatment delivery was assessed via measurement. RESULTS:The use of KBP resulted in significant reduction in plan variability in all three studied dosimetric parameters V5, V20 and mean lung dose by 4.9% (p = 0.007, 10.8 to 5.9%), 1.3% (p = 0.038, 4.0 to 2.7%) and 0.9 Gy (p = 0.012, 2.5 to 1.6Gy), respectively. It also increased lung sparing without compromising the overall plan quality. The accuracy of the model was proven as clinically acceptable. Plan complexity increased compared to original plans; however, the implication on delivery errors was clinically insignificant as demonstrated by plan verification measurements. CONCLUSION:Our in-house model for VMAT lung plans led to a significant reduction in plan variability with concurrent decrease in lung dose. Our study also demonstrated that treatment delivery verifications are important prior to clinical implementation of KBP models. ADVANCES IN KNOWLEDGE:In-house KBP models can predict minimum achievable lung dose-volume constraints for advance-stage lung cancer patients treated with VMAT. The study demonstrates that plan complexity could increase and should be assessed prior to clinical implementation.


目的: 放疗计划的质量可能有很大的不同,取决于计划者的经验和时间限制。治疗计划的可变性可以通过计算实现和最佳剂量分布之间的差异来评估。如果在不损害目标覆盖率和递送能力的情况下,有进一步的范围来减少器官风险剂量,则所实现的治疗计划可能仍然是次优的。本研究旨在开发一个基于知识的计划 (KBP) 模型,通过预测最小可实现的肺体积剂量指标来降低容积调制arc治疗 (VMAT) 肺计划的变异性。 方法: 使用从 40 个回顾性计划收集的剂量测定和几何数据来开发KBP模型,旨在通过计算残余肺体积与总肺体积的比率来预测最小可实现的肺剂量指标。通过重新规划 40 个计划验证了模型的准确性。使用本地开发的脚本计算计划复杂性度量,并通过测量评估其对治疗递送的影响。 结果: 使用KBP导致所有三个研究剂量学参数V5 、V20 和平均肺剂量的计划变异性显著降低 4.9% (p = 0.007 、 10.8 ~ 5.9%),1.3% (p = 0.038,4.0 ~ 2.7%) 和 0.9 gy gy (p = 0.012,2.5 ~ 1.6Gy)。它还增加了肺的保留,而不损害总体计划质量。该模型的准确性被证明是临床上可接受的。与原始计划相比,计划复杂性增加; 然而,如计划验证测量所证明的,对递送错误的影响在临床上是不重要的。 结论: 我们的VMAT肺计划的内部模型导致了计划变异性的显著降低,同时降低了肺剂量。我们的研究还表明,在临床实施KBP模型之前,治疗递送验证是重要的。 知识进展: 内部KBP模型可以预测接受VMAT治疗的晚期肺癌患者的最小可实现肺剂量-体积约束。该研究表明,计划复杂性可能增加,应在临床实施前进行评估。



作者列表:["Mammana M","Zuin A","Serra E","Bellini A","Rea F"]

METHODS::Pulmonary artery sling is a rare congenital anomaly of the origin and course of the left pulmonary artery. Patients with this condition typically present with respiratory failure in young infancy, and asymptomatic cases are uncommon. We describe the case of an adult patient with a lung adenocarcinoma of the right upper lobe, extending into the hilum and superior mediastinum, and with a previously unknown pulmonary artery sling anomaly. The local invasiveness of the tumor and the peculiar vascular anatomy contributed to a unique surgical scenario, wherein multiple reconstructive procedures were required.

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作者列表:["Hata A","Nakajima T","Matsusaka K","Fukuyo M","Morimoto J","Yamamoto T","Sakairi Y","Rahmutulla B","Ota S","Wada H","Suzuki H","Matsubara H","Yoshino I","Kaneda A"]

METHODS::Patients with idiopathic pulmonary fibrosis (IPF) have higher risk of developing lung cancer, for example, squamous cell carcinoma (SCC), and show poor prognosis, while the molecular basis has not been fully investigated. Here we conducted DNA methylome analysis of lung SCC using 20 SCC samples with/without IPF, and noncancerous lung tissue samples from smokers/nonsmokers, using Infinium HumanMethylation 450K array. SCC was clustered into low- and high-methylation epigenotypes by hierarchical clustering analysis. Genes hypermethylated in SCC significantly included genes targeted by polycomb repressive complex in embryonic stem cells, and genes associated with Gene Ontology terms, for example, "transcription" and "cell adhesion," while genes hypermethylated specifically in high-methylation subgroup significantly included genes associated with "negative regulation of growth." Low-methylation subgroup significantly correlated with IPF (78%, vs. 17% in high-methylation subgroup, p = 0.04), and the correlation was validated by additional Infinium analysis of SCC samples (n = 44 in total), and data from The Cancer Genome Atlas (n = 390). The correlation between low-methylation subgroup and IPF was further validated by quantitative methylation analysis of marker genes commonly hypermethylated in SCC (HOXA2, HOXA9 and PCDHGB6), and markers specifically hypermethylated in high-methylation subgroup (DLEC1, CFTR, MT1M, CRIP3 and ALDH7A1) in 77 SCC cases using pyrosequencing (p = 0.003). Furthermore, low-methylation epigenotype significantly correlated with poorer prognosis among all SCC patients, or among patients without IPF. Multivariate analysis showed that low-methylation epigenotype is an independent predictor of poor prognosis. These may suggest that lung SCC could be stratified into molecular subtypes with distinct prognosis, and low-methylation lung SCC that significantly correlates with IPF shows unfavorable outcome.

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作者列表:["Zhang L","Yang Y","Chai L","Bu H","Yang Y","Huang H","Ran J","Zhu Y","Li L","Chen F","Li W"]

METHODS::The role of Fyn-related kinase (FRK) in malignant tumors remains controversial. Our study investigated the function of FRK in lung cancer. Immunohistochemistry staining and generating a knockout of FRK by CRISPR/Cas9 in H1299 (FRK-KO-H1299) cells were strategies used to explore the role of FRK. Immunohistochemistry staining indicated that FRK expression was elevated in 223 lung cancer tissues compared to 26 distant normal lung tissues. FRK contributed to poor survival status in lung cancer patients and acted as a predictor for poor prognosis of lung cancer. Knockout of FRK by CRISPR/Cas9 markedly inhibited proliferation, invasion, colony formation and epithelial-mesenchymal transition (EMT) process in the lung cancer cell line H1299. Further exploration indicated that FRK-KO damaged the stemness phenotype of H1299 by inhibiting CD44 and CD133 expression. Seahorse detection and a U-13 C flux assay revealed that FRK-KO induced metabolism reprogramming by inhibiting the Warburg effect and changing the energy type in H1299 cells. Epidermal growth factor stimulation recovered the expression of FRK and biological functions, metabolic reprogramming and stemness phenotype of H1299 cells. FRK plays an oncogenic role in lung cancer cells via a novel regulation mechanism of enhancing the stemness of H1299 cells by inducing metabolism reprogramming, which finally promotes EMT and metastasis. Our study also indicates that FRK could be used as a potential therapeutic target for drug development.

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