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Review
. 2019 Jun 28;25(24):3021-3029.
doi: 10.3748/wjg.v25.i24.3021.

Imaging biomarkers for the treatment of esophageal cancer

Koichi Hayano  1 , Gaku Ohira  2 , Atsushi Hirata  2 , Tomoyoshi Aoyagi  2 , Shunsuke Imanishi  2 , Toru Tochigi  2 , Toshiharu Hanaoka  2 , Kiyohiko Shuto  3 , Hisahiro Matsubara  2
Affiliations
Review

Imaging biomarkers for the treatment of esophageal cancer

Koichi Hayano et al. World J Gastroenterol. .

Abstract

Esophageal cancer is known as one of the malignant cancers with poor prognosis. To improve the outcome, combined multimodality treatment is attempted. On the other hand, advances in genomics and other "omic" technologies are paving way to the patient-oriented treatment called "personalized" or "precision" medicine. Recent advancements of imaging techniques such as functional imaging make it possible to use imaging features as biomarker for diagnosis, treatment response, and prognosis in cancer treatment. In this review, we will discuss how we can use imaging derived tumor features as biomarker for the treatment of esophageal cancer.

Keywords: Computed tomography perfusion; Diffusion-weighted imaging; Dynamic-contrast-enhanced magnetic resonance imaging; Esophageal cancer; Positron emission tomography; Texture analysis.

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Conflict of interest statement

Conflict-of-interest statement: We confirm that there are no known conflicts of interest associated with this publication, and there has been no significant financial support for this work that may have influence on the contents.

Figures

Figure 1
Figure 1
Perfusion change of esophageal cancer during chemoradiation therapy. A: Computed tomography (CT) image at baseline; B: CT image at post-chemoradiation therapy (CRT); C: Blood flow map by CT perfusion at baseline; D: Blood flow map at post-CRT. Baseline blood flow of this tumor was low, and this patient was diagnosed as no-responder. CRT: Chemoradiation therapy; CT: Computed tomography.
Figure 2
Figure 2
Histogram analysis of diffusion-weighted imaging. Histogram analysis is one of the texture analyses. This is the histogram analysis of apparent diffusion coefficient (ADC) map. Region of interest (ROI) for the tumor is drawn on ADC map, and distribution of pixels in the ROI is quantified as histogram parameters such as kurtosis and skewness. ADC: Apparent diffusion coefficient; ROI: Region of interest.
Figure 3
Figure 3
Advanced esophageal squamous cell carcinoma in contrast enhanced computed tomography image and diffusion-weighted imaging at b = 1000. A: Contrast enhanced computed tomography image; B: Diffusion-weighted imaging. The tumor showed conspicuous high signal intensity on high b-value diffusion-weighted imaging.
Figure 4
Figure 4
18F-fluorodeoxyglucose positron emission tomography image of esophageal cancer. A: Axial image; B: Coronal image. Malignancies exhibit strongly enhanced energy consumption, resulting in increased 18F-fluorodeoxyglucose uptake.
See this image and copyright information in PMC

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