Dataset Information

Development and validation of a prognostic model incorporating texture analysis derived from standardised segmentation of PET in patients with oesophageal cancer.

ABSTRACT:

Objectives

This retrospective cohort study developed a prognostic model incorporating PET texture analysis in patients with oesophageal cancer (OC). Internal validation of the model was performed.

Methods

Consecutive OC patients (n = 403) were chronologically separated into development (n = 302, September 2010-September 2014, median age = 67.0, males = 227, adenocarcinomas = 237) and validation cohorts (n = 101, September 2014-July 2015, median age = 69.0, males = 78, adenocarcinomas = 79). Texture metrics were obtained using a machine-learning algorithm for automatic PET segmentation. A Cox regression model including age, radiological stage, treatment and 16 texture metrics was developed. Patients were stratified into quartiles according to a prognostic score derived from the model. A p-value < 0.05 was considered statistically significant. Primary outcome was overall survival (OS).

Results

Six variables were significantly and independently associated with OS: age [HR =1.02 (95% CI 1.01-1.04), p < 0.001], radiological stage [1.49 (1.20-1.84), p < 0.001], treatment [0.34 (0.24-0.47), p < 0.001], log(TLG) [5.74 (1.44-22.83), p = 0.013], log(Histogram Energy) [0.27 (0.10-0.74), p = 0.011] and Histogram Kurtosis [1.22 (1.04-1.44), p = 0.017]. The prognostic score demonstrated significant differences in OS between quartiles in both the development (X² 143.14, df 3, p < 0.001) and validation cohorts (X² 20.621, df 3, p < 0.001).

Conclusions

This prognostic model can risk stratify patients and demonstrates the additional benefit of PET texture analysis in OC staging.

Key points

• PET texture analysis adds prognostic value to oesophageal cancer staging. • Texture metrics are independently and significantly associated with overall survival. • A prognostic model including texture analysis can help risk stratify patients.

SUBMITTER: Foley KG

PROVIDER: S-EPMC5717119 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Publications

Development and validation of a prognostic model incorporating texture analysis derived from standardised segmentation of PET in patients with oesophageal cancer.

Foley Kieran G KG Hills Robert K RK Berthon Beatrice B Marshall Christopher C Parkinson Craig C Lewis Wyn G WG Crosby Tom D L TDL Spezi Emiliano E Roberts Stuart Ashley SA

European radiology 20170802 1

<h4>Objectives</h4>This retrospective cohort study developed a prognostic model incorporating PET texture analysis in patients with oesophageal cancer (OC). Internal validation of the model was performed.<h4>Methods</h4>Consecutive OC patients (n = 403) were chronologically separated into development (n = 302, September 2010-September 2014, median age = 67.0, males = 227, adenocarcinomas = 237) and validation cohorts (n = 101, September 2014-July 2015, median age = 69.0, males = 78, adenocarcino ...[more]

PMID: 28770406

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Dataset Information

Development and validation of a prognostic model incorporating texture analysis derived from standardised segmentation of PET in patients with oesophageal cancer.

Objectives

Methods

Results

Conclusions

Key points

Publications

Development and validation of a prognostic model incorporating texture analysis derived from standardised segmentation of PET in patients with oesophageal cancer.

Similar Datasets

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