Evaluation of dual-energy CT derived radiomics signatures in predicting outcomes in patients with advanced gastric cancer after neoadjuvant chemotherapy

Chen, Yong; Yuan, Fei; Wang, Lingyun; Li, Elsie; Xu, Zhihan; Wels, Michael; Yao, Weiwu; Zhang, Huan

doi:10.1016/j.ejso.2021.07.014

Cited by 23 publications

(22 citation statements)

References 33 publications

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“…Preoperative chemotherapy is a commonly used treatment method for locally advanced gastric cancer. Its purpose is to improve the R0 resection rate, kill the micro metastasis, and ultimately reduce the postoperative recurrence and mortality rates (13)(14)(15). Thus, it is of great significance to accurately identify the responsiveness of gastric cancer patients to preoperative chemotherapy.…”

Section: Discussionmentioning

confidence: 99%

Association between the apparent diffusion coefficient and the preoperative chemotherapy response of patients with locally advanced gastric cancer

Zhu¹,

Zhou²,

Wang³

et al. 2023

J Gastrointest Oncol

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Background:The apparent diffusion coefficient is a parameter measured by magnetic resonance imaging (MRI). Studies in breast cancer and osteosarcoma have shown that the apparent diffusion coefficient has a good correlation with the efficacy of neoadjuvant chemotherapy. However, to date, no studies have evaluated the association between the apparent diffusion coefficient and the preoperative chemotherapy response of patients with locally advanced gastric cancer. Methods:The data of 143 patients with locally advanced gastric cancer admitted to Zhejiang Medical and Health Group Quzhou Hospital (Zhejiang Quhua Hospital) from January 2018 to January 2019 were retrospectively collected. All the patients underwent preoperative chemotherapy and dynamic enhanced MRI to analyze the correlation between the apparent diffusion coefficient and preoperative chemotherapy response.Results: Compared to the control group, the apparent diffusion coefficient of the objective remission group was significantly increased [(1.16±0.26) ×10 −3 vs. (0.95±0.26) ×10 −3 mm 2 /s, P<0.001]; the rate of the apparent diffusion coefficient >1.095×10 −3 mm 2 /s was significantly increased (61.29% vs. 30.00%, P<0.001).The apparent diffusion coefficient was valuable in predicting objective remission after preoperative chemotherapy in patients with locally advanced gastric cancer, the area under the curve (AUC) was 0.708 [95% confidence interval (CI): 0.621-0.796, P<0.001], the best diagnostic cut-off value was 1.095×10 −3 mm 2 /s, and the sensitivity and specificity were 0.613 and 0.700, respectively. The multivariate logistics regression analysis showed that the apparent diffusion coefficient of >1.095×10 −3 mm 2 /s was associated with the objective response of patients with locally advanced gastric cancer after preoperative chemotherapy [P=0.004, relative risk =3.135 (95% CI: 1.452-6.768)]. The apparent diffusion coefficient was valuable in predicting the non-recurrence of locally advanced gastric cancer patients, and the AUC was 0.647 (95% CI: 0.557-0.738, P=0.003). The apparent diffusion coefficient was also valuable in predicting the postoperative survival of patients with locally advanced gastric cancer, and the AUC was 0.630 (95% CI: 0.537-0.723, P=0.007). Conclusions:The elevated apparent diffusion coefficient was associated with objective remission of the preoperative chemotherapy response and prognosis of patients with locally advanced gastric cancer.

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Section: Discussionmentioning

confidence: 99%

Association between the apparent diffusion coefficient and the preoperative chemotherapy response of patients with locally advanced gastric cancer

Zhu¹,

Zhou²,

Wang³

et al. 2023

J Gastrointest Oncol

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“…[13] Based on the features extracted from MRI images, Dong et al [14] built a model using logistic regression to predict axillary lymph node metastasis with an accuracy of 85 %. Many studies have demonstrated that radiomics can predict the prognosis of malignant tumors such as gastric cancer, [15] non-small-cell lung cancer, [16,17] and clear cell renal cell carcinoma. [18,19] This study aimed to establish a combined model based on image features extracted from preoperative MR images to predict recurrence-free survival (RFS) in patients with TNBC.…”

Section: The Authors Have No Funding and Conflicts Of Interest To Dis...mentioning

confidence: 99%

MRI-based radiomics approach for the prediction of recurrence-free survival in triple-negative breast cancer after breast-conserving surgery or mastectomy

Zhao,

Zhang,

Liu

et al. 2023

Medicine

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To explore the value of a radiomics signature and develop a nomogram combined with a radiomics signature and clinical factors for predicting recurrence-free survival in triple-negative breast cancer patients. We enrolled 151 patients from the cancer imaging archive who underwent preoperative contrast-enhanced magnetic resonance imaging. They were assigned to training, validation and external validation cohorts. Image features with coefficients not equal to zero in the 10-fold cross-validation were selected to generate a radiomics signature. Based on the optimal cutoff value of the radiomics signature determined by maximally selected log-rank statistics, patients were stratified into high- and low-risk groups in the training and validation cohorts. Kaplan–Meier survival analysis was performed for both groups. Kaplan–Meier survival distributions in these groups were compared using log-rank tests. Univariate and multivariate Cox regression analyses were used to construct clinical and combined models. Concordance index was used to assess the predictive performance of the 3 models. Calibration of the combined model was assessed using calibration curves. Four image features were selected to generate the radiomics signature. The Kaplan–Meier survival distributions of patients in the 2 groups were significantly different in the training (P < .001) and validation cohorts (P = .001). The C-indices of the radiomics model, clinical model, and combined model in the training and validation cohorts were 0.772, 0.700, 0.878, and 0.744, 0.574, 0.777, respectively. The C-indices of the radiomics model, clinical model, and combined model in the external validation cohort were 0.778, 0.733, 0.822, respectively. The calibration curves of the combined model showed good calibration. The radiomics signature can predict recurrence-free survival of patients with triple-negative breast cancer and improve the predictive performance of the clinical model.

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“…CT-based radiomic characteristics also perform well in predicting the response to NAC and radiotherapy in patients with advanced GC[ 68 - 71 ]. Jiang et al [ 72 ] showed that a DL CT signature could help to identify patients who might benefit from adjuvant chemotherapy for GC and improve prognostic prediction.…”

Section: Radiomics Workflowmentioning

confidence: 99%

Role of radiomics in the diagnosis and treatment of gastrointestinal cancer

Qi¹,

Zhou²,

Zhao³

et al. 2022

World J Gastroenterol

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Gastrointestinal cancer (GIC) has high morbidity and mortality as one of the main causes of cancer death. Preoperative risk stratification is critical to guide patient management, but traditional imaging studies have difficulty predicting its biological behavior. The emerging field of radiomics allows the conversion of potential pathophysiological information in existing medical images that cannot be visually recognized into high-dimensional quantitative image features. Tumor lesion characterization, therapeutic response evaluation, and survival prediction can be achieved by analyzing the relationships between these features and clinical and genetic data. In recent years, the clinical application of radiomics to GIC has increased dramatically. In this editorial, we describe the latest progress in the application of radiomics to GIC and discuss the value of its potential clinical applications, as well as its limitations and future directions.

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Evaluation of dual-energy CT derived radiomics signatures in predicting outcomes in patients with advanced gastric cancer after neoadjuvant chemotherapy

Cited by 23 publications

References 33 publications

Association between the apparent diffusion coefficient and the preoperative chemotherapy response of patients with locally advanced gastric cancer

Association between the apparent diffusion coefficient and the preoperative chemotherapy response of patients with locally advanced gastric cancer

MRI-based radiomics approach for the prediction of recurrence-free survival in triple-negative breast cancer after breast-conserving surgery or mastectomy

Role of radiomics in the diagnosis and treatment of gastrointestinal cancer

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