An update on advanced dual-energy CT for head and neck cancer imaging

被引:54
作者
Forghani, Reza [1 ,2 ,3 ,4 ,5 ,6 ,7 ]
机构
[1] McGill Univ, Dept Radiol, Montreal, PQ, Canada
[2] McGill Univ, Hlth Ctr, Montreal, PQ, Canada
[3] McGill Univ, Hlth Ctr, Canc Res Program, Res Inst, Montreal, PQ, Canada
[4] Jewish Gen Hosp, Segal Canc Ctr, Montreal, PQ, Canada
[5] Jewish Gen Hosp, Lady Davis Inst Med Res, Montreal, PQ, Canada
[6] McGill Univ, Gerald Bronfman Dept Oncol, Montreal, PQ, Canada
[7] McGill Univ, Dept Otolaryngol Head & Neck Surg, Montreal, PQ, Canada
关键词
Dual energy CT; spectral CT; head and neck cancer; squamous cell carcinoma; thyroid cartilage invasion; cervical lymph nodes; lymphadenopathy; TNM; SQUAMOUS-CELL CARCINOMA; TOMOGRAPHY PHYSICAL PRINCIPLES; VIRTUAL MONOCHROMATIC IMAGES; ARTIFACT REDUCTION SOFTWARE; COMPUTED-TOMOGRAPHY; DIAGNOSTIC-ACCURACY; TEXTURE ANALYSIS; IODINE OVERLAY; DIFFERENTIATION; KVP;
D O I
10.1080/14737140.2019.1626234
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Introduction: Dual-energy-computed tomography (DECT) is an advanced form of computed tomography (CT) that enables spectral tissue characterization beyond what is possible with conventional CT scans. DECT can improve non-invasive diagnostic evaluation of the neck, especially for the evaluation of head and neck cancer. Areas covered: This article is a review of current applications of DECT for the evaluation of head and neck cancer, focusing largely on squamous cell carcinoma (HNSCC). The article will begin with a brief overview of principles and different approaches for DECT scanning. This will be followed by a review of different DECT applications in diagnostic imaging and radiation oncology, practical and workflow considerations, and various emerging advanced applications for tumor analysis, including the use of DECT datasets for radiomics and machine learning applications. Expert opinion: Using a multi-parametric approach, different DECT reconstructions can be used to improve diagnostic evaluation and surveillance of head and neck cancer, including improving visibility of HNSCC, determination of tumor boundaries and extent, and invasion of critical organs such as the thyroid cartilage. In the future, the large amount of quantitative information on DECT scans may be leveraged for improving radiomic and machine learning models for tumor characterization.
引用
收藏
页码:633 / 644
页数:12
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