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. 2017 Aug 10;12(8):e0182883.
doi: 10.1371/journal.pone.0182883. eCollection 2017.

CT texture analysis in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: A potential imaging biomarker for treatment response and prognosis

Choong Guen Chee  1 , Young Hoon Kim  1 , Kyoung Ho Lee  1 , Yoon Jin Lee  1 , Ji Hoon Park  1 , Hye Seung Lee  2 , Soyeon Ahn  3 , Bohyoung Kim  4
Affiliations

CT texture analysis in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: A potential imaging biomarker for treatment response and prognosis

Choong Guen Chee et al. PLoS One. .

Abstract

Purpose: To evaluate the association of computed tomography (CT) texture features of locally advanced rectal cancer with neoadjuvant chemoradiotherapy (CRT) response and disease-free survival (DFS).

Methods and findings: The institutional review board approved this retrospective study. 95 patients who received neoadjuvant CRT, followed by surgery, for locally advanced rectal cancer were included. Texture features (entropy, uniformity, kurtosis, skewness, and standard deviation) were assessed in pretreatment CT images and obtained without filtration and with Laplacian of Gaussian spatial filter of various filter values (1.0, 1.5, 2.0, and 2.5). Dworak pathologic grading was used for treatment response assessment. Independent t-test was used to compare each texture feature between the treatment responder and non-responder groups. DFS was assessed with Kaplan-Meier method, and differences were compared with log-rank test. Cox proportional hazards models were constructed to predict prognosis based on stage, age, and each texture feature. Treatment responders (n = 32) showed significantly lower entropy, higher uniformity, and lower standard deviation in no filtration, fine (1.0), and medium (1.5) filter values. Entropy, uniformity, and standard deviation without filtration showed significant difference in DFS in Kaplan-Meier analysis (P = 0.015, 0.025, and 0.038). Homogeneous texture features (≤ 6.7 for entropy, > 0.0118 for uniformity, and ≤ 28.06 for standard deviation) were associated with higher DFS. Entropy, uniformity, and standard deviation were independent texture features in predicting DFS (P = 0.017, 0.03, and 0.036).

Conclusions: Homogeneous texture features are associated with better neoadjuvant CRT response and higher DFS in patients with locally advanced rectal cancer.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Patient flow diagram.
Fig 2
Fig 2. Texture analysis.
(a) Manually outlining and filtering out the pixels with attenuation under -50 HU in locally advanced rectal cancer in 76-year-old man. (b) Corresponding images in the same patient applying LoG filters with fine, medium, and coarse filter values.
Fig 3
Fig 3. Kaplan–Meier curves according to texture features.
Kaplan-Meier curves without filtration showed a significant difference in DFS for (a) entropy, (b) uniformity, and (c) standard deviation.
See this image and copyright information in PMC

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