MRI-based radiomic signature as predictive marker for patients with head and neck squamous cell carcinoma

doi:10.1016/j.ejrad.2019.06.019

European Journal of Radiology

Volume 117, August 2019, Pages 193-198

https://doi.org/10.1016/j.ejrad.2019.06.019 Get rights and content

Highlights

•
MRI-based Radiomics signature and nomogram were built for predicting OS of HNSCC.
•
The radiomics signature complements TNM stage in the radiomics nomogram.
•
Compared with TNM stage, radiomics nomogram achieved better predictive ability.
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The study provides an inspiring attempt for prognostic prediction of HNSCC.

Abstract

Purpose

To develop magnetic resonance imaging (MRI)-based radiomic signature and nomogram for preoperatively predicting prognosis in head and neck squamous cell carcinoma (HNSCC) patients.

Method

This retrospective study consisted of a training cohort (n = 85) and a validation cohort (n = 85) of patients with HNSCC. LASSO Cox regression model was used to select the most useful prognostic features with their coefficients, upon which a radiomic signature was generated. The receiver operator characteristics (ROC) analysis and association of the radiomic signature with overall survival (OS) of patients was assessed in both cohorts. A nomogram incorporating the radiomic signature and independent clinical predictors was then constructed. The incremental prognostic value of the radiomic signature was evaluated.

Results

The radiomic signature, consisted of 7 selected features from MR images, was significantly associated with OS of patients with HNSCC (P < 0.0001 for training cohort, P = 0.0013 for validation cohort). The radiomic signature and TNM stage were proved to be independently associated with OS of HNSCC patients, which therefore were incorporated to generate the radiomic nomogram. In the training cohort, the nomogram showed a better prognostic capability than TNM stage only (P =  0.005), which was confirmed in the validation cohort (P =  0.01). Furthermore, the calibration curves of the nomogram demonstrated good agreement with actual observation.

Conclusions

MRI-based radiomic signature is an independent prognostic factor for HNSCC patients. Nomogram based on radiomic signature and TNM stage shows promising in non-invasively and preoperatively predicting prognosis of HNSCC patient in clinical practice.

Introduction

According to the cancer statistics reported by the National Central Cancer Registry (NCCR) of China, approximately 198,700 new cases of head and neck cancer were diagnosed during 2015, with 63,000 deaths occurring annually [1]. The overall survival (OS) of patient with head and neck squamous cell carcinomas (HNSCC) is relatively low due to high rate of regional and distant metastases at diagnosis. Despite advances in multidisciplinary management, the survival rate of patients with HNSCC has only improved marginally [2,3]. Therefore, new tools are urgently needed to preoperatively identify patients who are at risk of having a poor prognosis, to whom more aggressive treatments should be administered. Tumor stage is traditionally acknowledged to be one of the most important prognostic factors [4,5]. However, wide spectrum of survival times still exists within the same staged patients.

Medical imaging has the potential to noninvasively assess tumors, and therefore is routinely used in clinical practice for diagnosis and treatment guidance. However, structural based medical images are traditionally evaluated subjectively and qualitatively, partially depending on the readers’ experience. The term radiomics has attracted recent interest for providing an easily obtainable opportunity for personalized medicine by extracting quantitative imaging features from conventional medical images, to characterize tumor pathology and heterogeneity [[6], [7], [8], [9]]. Evidence has been accumulating suggesting that radiomics features derived from MRI could bring additional prognostic information in glioblastoma [[10], [11], [12], [13], [14], [15]], nasopharyngeal carcinoma [16], prostate cancer [17] and renal cell cancer [18], and serve as prognostic biomarkers.

In prognostic studies of patients with HNSCC, computed tomography (CT)-based radiomics has been demonstrated to be valuable [[19], [20], [21]]. Compared to CT, head and neck MRI has potential advantage of better soft tissue contrast and less artifact [22], which could be expected to bring more information. However, the ability of MRI-based radiomic features for predicting prognosis in HNSCC patients has not been evaluated yet. Therefore, the aim of the current study was to determine whether radiomic features derived from MRI could help to predict the prognosis of HNSCC patients and improve prognostic ability by combining with clinical factors.

Section snippets

Patient selection and clinical follow-up

This retrospective study was approved by Institutional Review Board, and the requirement of informed consent was waived. Patients with histopathologically confirmed HNSCC, who underwent preoperative MRI and received treatment in our institution from January 2013 to December 2015, were collected. Patients were excluded for any of the following reasons: (1) tumor size smaller than 5 mm; (2) imaging artifacts (motion or susceptibility artifacts) impaired correct segmentation; (3) had any prior

Clinical characteristics and OS

A total of 170 patients were included (121 male, 49 female; mean age 59.0 ± 22.9 years). Respectively 85 and 85 patients were randomly allocated into the training cohort and the validation cohort. The clinical characteristics of the patients are summarized in Table 1. No statistical difference was found between the two cohorts in terms of clinical characteristics and follow-up data (all P > 0.05). The median OS time was 1019 days for all patients (range, 52–1599 days). During the follow-up

Discussion

The term radiomics has attracted increased attention in recent years for enabling a noninvasive, low cost and repeatable way to extract quantitative features from conventional medical images, and potentially contributing as decision support for personalized medicine. In the current study, we extracted 485 radiomic features quantifying intensity, shape and texture from pretreatment T2W images of patients with HNSCC. In the HNSCC patients, we selected radiomic features with the highest prognostic

Conclusions

The current study developed and validated pretreatment T2W-MRI based radiomics as a convenient approach to predict OS in patients with HNSCC. The radiomic signature complements traditional staging system in the radiomic nomogram, which potentially serves as decision support for personalized medicine. The current study provides an inspiring attempt for non-invasive pretreatment evaluation of HNSCC, which may help directing individual treatment strategies for patients with HNSCC in the future.

Disclosure paragraph

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Sources of support

This work was supported by funds from the National Scientific Foundation of China (91859202, 81771901), and Clinical Research Plan of SHDC (SHDC22015023).

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¹: These authors contributed equally to this work.

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Research articleMRI-based radiomic signature as predictive marker for patients with head and neck squamous cell carcinoma

Highlights

Abstract

Purpose

Method

Results

Conclusions

Introduction

Section snippets

Patient selection and clinical follow-up

Clinical characteristics and OS

Discussion

Conclusions

Disclosure paragraph

Sources of support

Clin. Radiol.

Eur. J. Cancer

Magn. Reson. Imaging

Curr. Treat. Options Oncol.

Cancer statistics in China, 2015

CA Cancer J. Clin.

Cancer Statistics, 2017

CA Cancer J. Clin.

Global cancer statistics, 2012

CA Cancer J. Clin.

Nomograms predicting long-term overall survival and cancer-specific survival in head and neck squamous cell carcinoma patients

Oncotarget

Relation between the level of lymph node metastasis and survival in locally advanced head and neck squamous cell carcinoma

Cancer

Quantitative radiomics studies for tissue characterization: a review of technology and methodological procedures

Br. J. Radiol.

Magnetic resonance imaging-based radiomic profiles predict patient prognosis in newly diagnosed glioblastoma before therapy

Tomography

Volume of high-risk intratumoral subregions at multi-parametric MR imaging predicts overall survival and complements molecular analysis of glioblastoma

Eur. Radiol.

Large-scale radiomic profiling of recurrent glioblastoma identifies an imaging predictor for stratifying anti-angiogenic treatment response

Clin. Cancer Res.

Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings

Eur. Radiol.

Clinically applicable and biologically validated MRI radiomic test method predicts glioblastoma genomic landscape and survival

Neurosurgery

Research article
MRI-based radiomic signature as predictive marker for patients with head and neck squamous cell carcinoma