109P18F-FDG PET/CT textural features as predictors of outcomes in patients with primary advanced colorectal cancer. (24th November 2019)
- Record Type:
- Journal Article
- Title:
- 109P18F-FDG PET/CT textural features as predictors of outcomes in patients with primary advanced colorectal cancer. (24th November 2019)
- Main Title:
- 109P18F-FDG PET/CT textural features as predictors of outcomes in patients with primary advanced colorectal cancer
- Authors:
- Yang, J
Cheng, Y
Ma, X - Abstract:
- Abstract: Background: With 18 F-FDG PET/CT, tumor uptake intensity and textural features have been associated with outcome in several types of cancer. This study was to evaluate the prognostic value of pretreatment 18 F-FDG PET/CT textural parameters in patients with primary metastatic colorectal cancer (CRC). Methods: All patients (n = 104) who had had a pretreatment image of 18 F-FDG PET/CT at our Hospital from January 2009 to December 2015 were included. Volumes of interest (VOIs) were drawn freehand around the tumor, and texture analysis was conducted on both CT and PET images within the same VOIs. A total of 35 features were extracted and analyzed. Univariate and multivariate analyses (logistic regression) were conducted to assess the prognostic value of textural parameters. Moreover, radiomics score (rad-score) was constructed using logistic regression. A multivariate logistic regression model was then used to establish a nomogram including the rad-score and other clinicopathological features. Results: The results of univariate analysis showed that 18 textural parameters such as skewness and kurtosis were significantly associated with survival. In multivariate model, 17 textural parameters were shown to be able to predict PFS, including skewness (HR 2.777, p < 0.001), kurtosis (HR 0.441, p < 0.001), entropy (HR 1.704, p = 0.014), homogeneity (HR 0.548, p = 0.006), SRE (HR 1.853, p = 0.005), LRE (HR, p = 0.005), HGRE (HR 1.616, p = 0.036), LZE (HR 0.597, p = 0.018),Abstract: Background: With 18 F-FDG PET/CT, tumor uptake intensity and textural features have been associated with outcome in several types of cancer. This study was to evaluate the prognostic value of pretreatment 18 F-FDG PET/CT textural parameters in patients with primary metastatic colorectal cancer (CRC). Methods: All patients (n = 104) who had had a pretreatment image of 18 F-FDG PET/CT at our Hospital from January 2009 to December 2015 were included. Volumes of interest (VOIs) were drawn freehand around the tumor, and texture analysis was conducted on both CT and PET images within the same VOIs. A total of 35 features were extracted and analyzed. Univariate and multivariate analyses (logistic regression) were conducted to assess the prognostic value of textural parameters. Moreover, radiomics score (rad-score) was constructed using logistic regression. A multivariate logistic regression model was then used to establish a nomogram including the rad-score and other clinicopathological features. Results: The results of univariate analysis showed that 18 textural parameters such as skewness and kurtosis were significantly associated with survival. In multivariate model, 17 textural parameters were shown to be able to predict PFS, including skewness (HR 2.777, p < 0.001), kurtosis (HR 0.441, p < 0.001), entropy (HR 1.704, p = 0.014), homogeneity (HR 0.548, p = 0.006), SRE (HR 1.853, p = 0.005), LRE (HR, p = 0.005), HGRE (HR 1.616, p = 0.036), LZE (HR 0.597, p = 0.018), LGZE (HR 0.439, p < 0.001) and HGZE (HR 2.085, p = 0.001). In addition, 8 textural parameters such as skewness (HR 4.475, p < 0.001), kurtosis (HR 0.377, p < 0.001), SRHGE (HR 2.062, p = 0.005) and LRLGE (HR 0.475, p = 0.003), were revealed to be independent predictors of OS among our population. Conclusions: The texture analysis of the baseline 18 F-FDG PET/CT appears to be a potential tool to predict outcomes of patients with primary metastatic CRC. However, prospective studies with a large population are needed to confirm the present findings. Legal entity responsible for the study: The authors. Funding: Has not received any funding. Disclosure: All authors have declared no conflicts of interest. … (more)
- Is Part Of:
- Annals of oncology. Volume 30(2019)Supplement 9
- Journal:
- Annals of oncology
- Issue:
- Volume 30(2019)Supplement 9
- Issue Display:
- Volume 30, Issue 9 (2019)
- Year:
- 2019
- Volume:
- 30
- Issue:
- 9
- Issue Sort Value:
- 2019-0030-0009-0000
- Page Start:
- Page End:
- Publication Date:
- 2019-11-24
- Subjects:
- Oncology -- Periodicals
616.992 - Journal URLs:
- https://www.journals.elsevier.com/annals-of-oncology ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/annonc/mdz421.031 ↗
- Languages:
- English
- ISSNs:
- 0923-7534
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1043.320000
British Library DSC - BLDSS-3PM
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