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食管癌放射性淋巴细胞减少深度学习模型的临床转化

Clinical Translation of a Deep Learning Model of Radiation-Induced Lymphopenia for Esophageal Cancer.

作者信息

Hu Zongsheng, Mohan Radhe, Chu Yan, Wang Xiaochun, van Rossum Peter S N, Chen Yiqing, Grayson Madison E, Gearhardt Angela G, Grassberger Clemens, Zhi Degui, Hobbs Brian P, Lin Steven H, Cao Wenhua

机构信息

Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.

The University of Texas Health Science Center at Houston, Houston, Texas, USA.

出版信息

Int J Part Ther. 2024 Aug 5;13:100624. doi: 10.1016/j.ijpt.2024.100624. eCollection 2024 Sep.

Abstract

PURPOSE

Radiation-induced lymphopenia is a common immune toxicity that adversely impacts treatment outcomes. We report here our approach to translate a deep-learning (DL) model developed to predict severe lymphopenia risk among esophageal cancer into a strategy for incorporating the immune system as an organ-at-risk (iOAR) to mitigate the risk.

MATERIALS AND METHODS

We conducted "virtual clinical trials" utilizing retrospective data for 10 intensity-modulated radiation therapy (IMRT) and 10 passively-scattered proton therapy (PSPT) esophageal cancer patients. For each patient, additional treatment plans of the modality other than the original were created employing standard-of-care (SOC) dose constraints. Predicted values of absolute lymphocyte count (ALC) nadir for all plans were estimated using a previously-developed DL model. The model also yielded the relative magnitudes of contributions of iOARs dosimetric factors to ALC nadir, which were used to compute iOARs dose-volume constraints, which were incorporated into optimization criteria to produce "IMRT-enhanced" and "intensity-modulated proton therapy (IMPT)-enhanced" plans.

RESULTS

Model-predicted ALC nadir for the original IMRT (IMRT-SOC) and PSPT plans agreed well with actual values. IMPT-SOC showed greater immune sparing vs IMRT and PSPT. The average mean body doses were 13.10 Gy vs 7.62 Gy for IMRT-SOC vs IMPT-SOC for patients treated with IMRT-SOC; and 8.08 Gy vs 6.68 Gy for PSPT vs IMPT-SOC for patients treated with PSPT. For IMRT patients, the average predicted ALC nadir of IMRT-SOC, IMRT-enhanced, IMPT-SOC, and IMPT-enhanced was 281, 327, 351, and 392 cells/µL, respectively. For PSPT patients, the average predicted ALC nadir of PSPT, IMPT-SOC, and IMPT-enhanced was 258, 316, and 350 cells/µL, respectively. Enhanced plans achieved higher predicted ALC nadir, with an average improvement of 40.8 cells/µL (20.6%).

CONCLUSION

The proposed DL model-guided strategy to incorporate the immune system as iOAR in IMRT and IMPT optimization has the potential for radiation-induced lymphopenia mitigation. A prospective clinical trial is planned.

摘要

目的

辐射诱导的淋巴细胞减少是一种常见的免疫毒性,会对治疗结果产生不利影响。我们在此报告我们的方法,即将一个为预测食管癌严重淋巴细胞减少风险而开发的深度学习(DL)模型转化为一种将免疫系统作为危及器官(iOAR)纳入其中以降低风险的策略。

材料与方法

我们利用10例接受调强放射治疗(IMRT)和10例接受被动散射质子治疗(PSPT)的食管癌患者的回顾性数据进行了“虚拟临床试验”。对于每位患者,采用标准治疗(SOC)剂量限制创建了除原始治疗方式之外的其他治疗方式的额外治疗计划。使用先前开发的DL模型估计所有计划的绝对淋巴细胞计数(ALC)最低点的预测值。该模型还得出了iOAR剂量学因素对ALC最低点贡献的相对大小,用于计算iOAR剂量体积限制,并将其纳入优化标准以生成“IMRT增强型”和“调强质子治疗(IMPT)增强型”计划。

结果

原始IMRT(IMRT-SOC)和PSPT计划的模型预测ALC最低点与实际值吻合良好。IMPT-SOC与IMRT和PSPT相比显示出更大的免疫保护作用。接受IMRT-SOC治疗的患者,IMRT-SOC与IMPT-SOC的平均平均体部剂量分别为13.10 Gy和7.62 Gy;接受PSPT治疗的患者,PSPT与IMPT-SOC的平均平均体部剂量分别为8.08 Gy和6.68 Gy。对于IMRT患者,IMRT-SOC、IMRT增强型、IMPT-SOC和IMPT增强型的平均预测ALC最低点分别为281、327、351和392个细胞/微升。对于PSPT患者,PSPT、IMPT-SOC和IMPT增强型的平均预测ALC最低点分别为258、316和350个细胞/微升。增强型计划实现了更高的预测ALC最低点,平均提高了40.8个细胞/微升(20.6%)。

结论

所提出的将免疫系统作为iOAR纳入IMRT和IMPT优化的DL模型指导策略具有减轻辐射诱导淋巴细胞减少的潜力。计划进行一项前瞻性临床试验。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf7e/11369390/0467a85f9dc5/gr1.jpg

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