头颈部癌症预后放射组学特征：基于多中心 MRI 数据集的建立和验证。

Prognostic radiomic signature for head and neck cancer: Development and validation on a multi-centric MRI dataset.

机构信息

Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milan, Italy.

出版信息

Radiother Oncol. 2023 Jun;183:109638. doi: 10.1016/j.radonc.2023.109638. Epub 2023 Mar 31.

DOI:10.1016/j.radonc.2023.109638

PMID:37004837

Abstract

BACKGROUND AND PURPOSE

Prognosis in locally advanced head and neck cancer (HNC) is currently based on TNM staging system and tumor subsite. However, quantitative imaging features (i.e., radiomic features) from magnetic resonance imaging (MRI) may provide additional prognostic info. The aim of this work is to develop and validate an MRI-based prognostic radiomic signature for locally advanced HNC.

MATERIALS AND METHODS

Radiomic features were extracted from T1- and T2-weighted MRI (T1w and T2w) using the segmentation of the primary tumor as mask. In total 1072 features (536 per image type) were extracted for each tumor. A retrospective multi-centric dataset (n = 285) was used for features selection and model training. The selected features were used to fit a Cox proportional hazard regression model for overall survival (OS) that outputs the radiomic signature. The signature was then validated on a prospective multi-centric dataset (n = 234). Prognostic performance for OS and disease-free survival (DFS) was evaluated using C-index. Additional prognostic value of the radiomic signature was explored.

RESULTS

The radiomic signature had C-index = 0.64 for OS and C-index = 0.60 for DFS in the validation set. The addition of the radiomic signature to other clinical features (TNM staging and tumor subsite) increased prognostic ability for both OS (HPV- C-index 0.63 to 0.65; HPV+ C-index 0.75 to 0.80) and DFS (HPV- C-index 0.58 to 0.61; HPV+ C-index 0.64 to 0.65).

CONCLUSION

An MRI-based prognostic radiomic signature was developed and prospectively validated. Such signature can successfully integrate clinical factors in both HPV+ and HPV- tumors.

摘要

背景与目的

局部晚期头颈部癌症（HNC）的预后目前基于 TNM 分期系统和肿瘤亚部位。然而，磁共振成像（MRI）的定量成像特征（即放射组学特征）可能提供额外的预后信息。本研究旨在开发和验证一种基于 MRI 的局部晚期 HNC 预后放射组学特征。

材料与方法

使用原发肿瘤的分割作为掩模，从 T1 和 T2 加权 MRI（T1w 和 T2w）中提取放射组学特征。每个肿瘤共提取 1072 个特征（每个图像类型 536 个）。回顾性多中心数据集（n=285）用于特征选择和模型训练。选择的特征用于拟合总体生存（OS）的 Cox 比例风险回归模型，该模型输出放射组学特征。然后在前瞻性多中心数据集（n=234）上验证该特征。使用 C 指数评估 OS 和无病生存（DFS）的预后性能。探索放射组学特征的额外预后价值。

结果

在验证集中，该放射组学特征的 OS 的 C 指数为 0.64，DFS 的 C 指数为 0.60。将放射组学特征添加到其他临床特征（TNM 分期和肿瘤亚部位）中，增加了 OS（HPV- C 指数从 0.63 增加到 0.65；HPV+ C 指数从 0.75 增加到 0.80）和 DFS（HPV- C 指数从 0.58 增加到 0.61；HPV+ C 指数从 0.64 增加到 0.65）的预后能力。