How Does Target Lesion Selection Affect RECIST? A Computer Simulation Study.

IF 7 1区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Investigative Radiology Pub Date : 2024-06-01 Epub Date: 2023-11-03 DOI:10.1097/RLI.0000000000001045
Teresa M Tareco Bucho, Renaud L M Tissier, Kevin B W Groot Lipman, Zuhir Bodalal, Andrea Delli Pizzi, Thi Dan Linh Nguyen-Kim, Regina G H Beets-Tan, Stefano Trebeschi
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引用次数: 0

Abstract

Objectives: Response Evaluation Criteria in Solid Tumors (RECIST) is grounded on the assumption that target lesion selection is objective and representative of the change in total tumor burden (TTB) during therapy. A computer simulation model was designed to challenge this assumption, focusing on a particular aspect of subjectivity: target lesion selection.

Materials and methods: Disagreement among readers and the disagreement between individual reader measurements and TTB were analyzed as a function of the total number of lesions, affected organs, and lesion growth.

Results: Disagreement rises when the number of lesions increases, when lesions are concentrated on a few organs, and when lesion growth borders the thresholds of progressive disease and partial response. There is an intrinsic methodological error in the estimation of TTB via RECIST 1.1, which depends on the number of lesions and their distributions. For example, for a fixed number of lesions at 5 and 15, distributed over a maximum of 4 organs, the error rates are observed to be 7.8% and 17.3%, respectively.

Conclusions: Our results demonstrate that RECIST can deliver an accurate estimate of TTB in localized disease, but fails in cases of distal metastases and multiple organ involvement. This is worsened by the "selection of the largest lesions," which introduces a bias that makes it hardly possible to perform an accurate estimate of the TTB. Including more (if not all) lesions in the quantitative analysis of tumor burden is desirable.

靶病变选择如何影响RECIST?计算机模拟研究。
目的:实体瘤疗效评估标准(RECIST)基于这样一种假设,即靶病变的选择是客观的,并能代表治疗期间肿瘤总负荷(TTB)的变化。设计了一个计算机模拟模型来挑战这一假设,重点关注主观性的一个特定方面:目标病变的选择。材料和方法:将读者之间的分歧以及个体读者测量值和TTB之间的分歧作为病变总数、受影响器官和病变生长的函数进行分析。结果:当病变数量增加时,当病变集中在少数器官时,以及当病变生长接近进行性疾病和部分反应的阈值时,分歧加剧。通过RECIST 1.1估计TTB存在固有的方法学错误,这取决于病变的数量及其分布。例如,对于5个和15个固定数量的病变,分布在最多4个器官上,观察到错误率分别为7.8%和17.3%。结论:我们的研究结果表明,RECIST可以在局部疾病中准确估计TTB,但在远端转移和多器官受累的情况下失败。这种情况因“选择最大的病变”而恶化,这引入了一种偏差,使得很难对TTB进行准确估计。在肿瘤负荷的定量分析中包括更多(如果不是全部的话)病变是可取的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Investigative Radiology
Investigative Radiology 医学-核医学
CiteScore
15.10
自引率
16.40%
发文量
188
审稿时长
4-8 weeks
期刊介绍: Investigative Radiology publishes original, peer-reviewed reports on clinical and laboratory investigations in diagnostic imaging, the diagnostic use of radioactive isotopes, computed tomography, positron emission tomography, magnetic resonance imaging, ultrasound, digital subtraction angiography, and related modalities. Emphasis is on early and timely publication. Primarily research-oriented, the journal also includes a wide variety of features of interest to clinical radiologists.
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