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基于 ADC 与 Gleason 评分映射的前列腺癌剂量雕刻治疗计划的稳健性——提高肿瘤控制概率的潜力如何?

Robust treatment planning of dose painting for prostate cancer based on ADC-to-Gleason score mappings - what is the potential to increase the tumor control probability?

机构信息

Medical radiation sciences, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Section of Medical Physics, Eskilstuna Hospital, Eskilstuna, Sweden.

出版信息

Acta Oncol. 2021 Feb;60(2):199-206. doi: 10.1080/0284186X.2020.1817547. Epub 2020 Sep 17.

Abstract

BACKGROUND AND PURPOSE

The aim of this study was to evaluate the potential to increase the tumor control probability (TCP) with 'dose painting by numbers' (DPBN) plans optimized in a treatment planning system (TPS) compared to uniform dose plans. The DPBN optimization was based on our earlier published formalism for prostate cancer that is driven by dose-responses of Gleason scores mapped from apparent diffusion coefficients (ADC).

MATERIAL AND METHODS

For 17 included patients, a set of DPBN plans were optimized in a TPS by maximizing the TCP for an equal average dose to the prostate volume (CTVT) as for a conventional uniform dose treatment. For the plan optimizations we applied different photon energies, different precisions for the ADC-to-Gleason mappings, and different CTVT positioning uncertainties. The TCP increasing potential was evaluated by the DPBN efficiency, defined as the ratio of TCP increases for DPBN plans by TCP increases for ideal DPBN prescriptions (optimized without considering radiation transport phenomena, uncertainties of the CTVT positioning, and uncertainties of the ADC-to-Gleason mapping).

RESULTS

The median DPBN efficiency for the most conservative planning scenario optimized with a low precision ADC-to-Gleason mapping, and a positioning uncertainty of 0.6 cm was 10%, meaning that more than half of the patients had a TCP gain of at least 10% of the TCP for an ideal DPBN prescription. By increasing the precision of the ADC-to-Gleason mapping, and decreasing the positioning uncertainty the median DPBN efficiency increased by up to 40%.

CONCLUSIONS

TCP increases with DPBN plans optimized in a TPS were found more likely with a high precision mapping of image data into dose-responses and a high certainty of the tumor positioning. These findings motivate further development to ensure precise mappings of image data into dose-responses and to ensure a high spatial certainty of the tumor positioning when implementing DPBN clinically.

摘要

背景与目的

本研究旨在评估通过在治疗计划系统(TPS)中优化“数字剂量描绘”(DPBN)计划相对于均匀剂量计划来提高肿瘤控制概率(TCP)的潜力。DPBN 优化基于我们之前发表的用于前列腺癌的形式主义,该形式主义由映射自表观扩散系数(ADC)的 Gleason 评分的剂量反应驱动。

材料与方法

对于 17 名纳入的患者,通过最大化前列腺体积(CTV)的平均剂量(CTV)与常规均匀剂量治疗相等的 TCP,在 TPS 中为一组 DPBN 计划进行了优化。对于计划优化,我们应用了不同的光子能量、ADC 到 Gleason 映射的不同精度以及 CTV 定位不确定性的不同范围。DPBN 效率定义为 DPBN 计划的 TCP 增加与理想 DPBN 处方的 TCP 增加之比,通过 DPBN 效率评估 TCP 增加的潜力(优化时不考虑辐射传输现象、CTV 定位的不确定性和 ADC 到 Gleason 映射的不确定性)。

结果

在最保守的规划方案中,使用低精度 ADC 到 Gleason 映射和 0.6cm 的定位不确定性进行优化的情况下,DPBN 效率的中位数为 10%,这意味着超过一半的患者的 TCP 增益至少为理想 DPBN 处方的 TCP 增益的 10%。通过提高 ADC 到 Gleason 映射的精度并降低定位不确定性,DPBN 效率的中位数最多可提高 40%。

结论

在 TPS 中优化的 DPBN 计划与高剂量反应图像数据的高精度映射和肿瘤定位的高确定性相结合,发现 TCP 增加的可能性更大。这些发现促使进一步开发,以确保在临床实施 DPBN 时能够精确地将图像数据映射到剂量反应中,并确保肿瘤定位的高空间确定性。

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