迈向人工智能辅助临床实践中的自动化治疗计划：高剂量率前列腺近距离治疗中首次临床经验的前瞻性研究。

Towards artificial intelligence-based automated treatment planning in clinical practice: A prospective study of the first clinical experiences in high-dose-rate prostate brachytherapy.

机构信息

Department of Radiation Oncology, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands; Cancer Center Amsterdam, Cancer Treatment and Quality of Life, Amsterdam, The Netherlands.

出版信息

Brachytherapy. 2023 Mar-Apr;22(2):279-289. doi: 10.1016/j.brachy.2022.11.013. Epub 2023 Jan 10.

DOI:10.1016/j.brachy.2022.11.013

PMID:36635201

Abstract

PURPOSE

This prospective study evaluates our first clinical experiences with the novel ``BRachytherapy via artificial Intelligent GOMEA-Heuristic based Treatment planning'' (BRIGHT) applied to high-dose-rate prostate brachytherapy.

METHODS AND MATERIALS

Between March 2020 and October 2021, 14 prostate cancer patients were treated in our center with a 15Gy HDR-brachytherapy boost. BRIGHT was used for bi-objective treatment plan optimization and selection of the most desirable plans from a coverage-sparing trade-off curve. Selected BRIGHT plans were imported into the commercial treatment planning system Oncentra Brachy . In Oncentra Brachy a dose distribution comparison was performed for clinical plan choice, followed by manual fine-tuning of the preferred BRIGHT plan when deemed necessary. The reasons for plan selection, clinical plan choice, and fine-tuning, as well as process speed were monitored. For each patient, the dose-volume parameters of the (fine-tuned) clinical plan were evaluated.

RESULTS

In all patients, BRIGHT provided solutions satisfying all protocol values for coverage and sparing. In four patients not all dose-volume criteria of the clinical plan were satisfied after manual fine-tuning. Detailed information on tumour coverage, dose-distribution, dwell time pattern, and insight provided by the patient-specific trade-off curve, were used for clinical plan choice. Median time spent on treatment planning was 42 min, consisting of 16 min plan optimization and selection, and 26 min undesirable process steps.

CONCLUSIONS

BRIGHT is implemented in our clinic and provides automated prostate high-dose-rate brachytherapy planning with trade-off based plan selection. Based on our experience, additional optimization aims need to be implemented to further improve direct clinical applicability of treatment plans and process efficiency.

摘要

目的

本前瞻性研究评估了我们在新型“基于人工智能 GOMEA 启发式的 BRACHYTHERAPY via 智能治疗计划”（BRIGHT）应用于高剂量率前列腺近距离放射治疗方面的首次临床经验。

方法与材料

在 2020 年 3 月至 2021 年 10 月期间，我们中心对 14 例前列腺癌患者进行了 15Gy 的 HDR 近距离放疗强化治疗。BRIGHT 用于双目标治疗计划优化，并从覆盖范围与保护的权衡曲线上选择最理想的计划。从权衡曲线上选择的 BRIGHT 计划被导入商业治疗计划系统 Oncentra Brachy 中。在 Oncentra Brachy 中，对临床计划进行剂量分布比较，以选择临床计划，然后在必要时对首选的 BRIGHT 计划进行手动微调。监测了计划选择、临床计划选择和微调的原因以及处理速度。对于每个患者，评估（微调后的）临床计划的剂量体积参数。

结果

在所有患者中，BRIGHT 提供的解决方案均满足覆盖和保护的所有方案值。在 4 例患者中，手动微调后未满足临床计划的所有剂量体积标准。使用肿瘤覆盖、剂量分布、驻留时间模式和患者特定权衡曲线提供的详细信息来选择临床计划。治疗计划的中位时间为 42 分钟，包括 16 分钟的计划优化和选择，以及 26 分钟的不理想过程步骤。