Prognostic prediction value of the clinical-radiomics tumour-stroma ratio in locally advanced rectal cancer

•Radiomics models based on patients with rectal cancer receiving surgery alone for tumour-stroma ratio evaluation can be applied in patients with locally advanced rectal cancer treated with neoadjuvant therapy, which always damages the tumor microenvironment, resulting in a incapableness of accurate...

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Veröffentlicht in:European journal of radiology 2024-01, Vol.170, p.111254-111254, Article 111254
Hauptverfasser: Cai, Chongpeng, Hu, Tingdan, Rong, Zening, Gong, Jing, Tong, Tong
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Sprache:eng
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Zusammenfassung:•Radiomics models based on patients with rectal cancer receiving surgery alone for tumour-stroma ratio evaluation can be applied in patients with locally advanced rectal cancer treated with neoadjuvant therapy, which always damages the tumor microenvironment, resulting in a incapableness of accurate tumour-stroma ratio evaluation.•Radiomics model based on high-resolution T2WI and clinical-radiomics model for tumour-stroma ratio evaluation can predict DFS and OS in patients with locally advanced rectal cancer treated with neoadjuvant therapy. To develop and validate a radiomics model based on high-resolution T2WI and a clinical-radiomics model for tumour-stroma ratio (TSR) evaluation with a gold standard of TSR evaluated by rectal specimens without therapeutic interference and further apply them in prognosis prediction of locally advanced rectal cancer (LARC) patients who received neoadjuvant chemoradiotherapy. A total of 178 patients (mean age: 59.35, range 20–85 years; 65 women and 113 men) with rectal cancer who received surgery alone from January 2016 to October 2020 were enrolled and randomly separated at a ratio of 7:3 into training and validation sets. A senior radiologist reviewed after 2 readers manually delineated the whole tumour in consensus on preoperative high-resolution T2WI in the training set. A total of 1046 features were then extracted, and recursive feature elimination embedded with leave-one-out cross validation was applied to select features, with which an MR-TSR evaluation model was built containing 6 filtered features via a support vector machine classifier trained by comparing patients’ pathological TSR. Stepwise logistic regression was employed to integrate clinical factors with the radiomics model (Fusion-TSR) in the training set. Later, the MR-TSR and Fusion-TSR models were replicated in the validation set for diagnostic effectiveness evaluation. Subsequently, 243 patients (mean age: 53.74, range 23–74 years; 63 women and 180 men) with LARC from October 2012 to September 2017 who were treated with NCRT prior to surgery and underwent standard pretreatment rectal MR examination were enrolled. The MR-TSR and Fusion-TSR were applied, and the Kaplan–Meier method and log-rank test were used to compare the survival of patients with different MR-TSR and Fusion-TSR. Cox proportional hazards regression was used to calculate the hazard ratio (HR). Both the MR-TSR and Fusion-TSR models were validated with favourable diagnostic power: the AUC
ISSN:0720-048X
1872-7727
DOI:10.1016/j.ejrad.2023.111254