Quantitative analysis of diffusion weighted imaging to predict pathological good response to neoadjuvant chemoradiation for locally advanced rectal cancer

Tang, Zhenchao; Zhang, Xiaoyan; Liu, Zhenyu; Li, Xiaoting; Shi, Yan‐Jie; Shou, Wang; Fang, Mengjie; Shen, Chen; Dong, Enqing; Sun, Ying‐Shi; Tian, Jie

doi:10.1016/j.radonc.2018.11.007

Cited by 32 publications

(21 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This nomogram contained improved the prognostic ability of the clinical staging system, and could be developed as an easy-to-use tool. In addition, the clinical utility of radiomic nomogram was assessed using decision curve analysis, which is commonly used method in radiomic studies 27,28 , and the results suggest that the radiomic nomogram could benefit patients.…”

Section: Discussionmentioning

confidence: 99%

Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer

et al. 2020

Self Cite

View full text Add to dashboard Cite

Distant metastasis (DM) is the main cause of treatment failure in locally advanced rectal cancer. Adjuvant chemotherapy is usually used for distant control. However, not all patients can benefit from adjuvant chemotherapy, and particularly, some patients may even get worse outcomes after the treatment. We develop and validate an MRI-based radiomic signature (RS) for prediction of DM within a multicenter dataset. The RS is proved to be an independent prognostic factor as it not only demonstrates good accuracy for discriminating patients into high and low risk of DM in all the four cohorts, but also outperforms clinical models. Within the stratified analysis, good chemotherapy efficacy is observed for patients with pN2 disease and low RS, whereas poor chemotherapy efficacy is detected in patients with pT1-2 or pN0 disease and high RS. The RS may help individualized treatment planning to select patients who may benefit from adjuvant chemotherapy for distant control.

show abstract

Section: Discussionmentioning

confidence: 99%

Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…189 Other groups have identified other MRI-features with the possibility to find good or complete response. 190,191 However, these are recently published and the findings needs to be confirmed in other settings. Further, no genetic profiles have been found with the ability to predict response to CRT.…”

Section: Organ Preservationmentioning

confidence: 98%

Tumour regression after radiotherapy for rectal cancer – Results from the randomised Stockholm III trial

Erlandsson

Lörinc

Ahlberg

et al. 2019

Radiotherapy and Oncology

112

View full text Add to dashboard Cite

“…Radiomics has facilitated progress in precise diagnosis,17,18 prediction of lymph node metastasis,19,20 and survival analysis 21,22. Previous radiomic studies focused on therapeutic responses in LARC patients were mainly based on combining pre- and post-therapeutic imaging data or images obtained during neoadjuvant therapy 23–25. Most of these studies focused on single-modality imaging, such as dynamic contrast-enhanced MRI,26 diffusion-weighted MRI,27 T2-weighted MRI,28 and fluorodeoxyglucose positron emission tomography,29 which may have inherent limitations in reflecting tumor biology.…”

mentioning

confidence: 99%

Radiomics-Based Pretherapeutic Prediction of Non-response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer

Zhou

Liu

et al. 2019

Ann Surg Oncol

Self Cite

View full text Add to dashboard Cite

Objective The aim of this study was to investigate whether pretherapeutic, multiparametric magnetic resonance imaging (MRI) radiomic features can be used for predicting non-response to neoadjuvant therapy in patients with locally advanced rectal cancer (LARC). Methods We retrospectively enrolled 425 patients with LARC [allocated in a 3:1 ratio to a primary ( n = 318) or validation ( n = 107) cohort] who received neoadjuvant therapy before surgery. All patients underwent T1-weighted, T2-weighted, diffusion-weighted, and contrast-enhanced T1-weighted MRI scans before receiving neoadjuvant therapy. We extracted 2424 radiomic features from the pretherapeutic, multiparametric MR images of each patient. The Wilcoxon rank-sum test, Spearman correlation analysis, and least absolute shrinkage and selection operator regression were successively performed for feature selection, whereupon a multiparametric MRI-based radiomic model was established by means of multivariate logistic regression analysis. This feature selection and multivariate logistic regression analysis was also performed on all single-modality MRI data to establish four single-modality radiomic models. The performance of the five radiomic models was evaluated by receiver operating characteristic (ROC) curve analysis in both cohorts. Results The multiparametric, MRI-based radiomic model based on 16 features showed good predictive performance in both the primary ( p < 0.01) and validation ( p < 0.05) cohorts, and performed better than all single-modality models. The area under the ROC curve of this multiparametric MRI-based radiomic model achieved a score of 0.822 (95% CI 0.752–0.891). Conclusions We demonstrated that pretherapeutic, multiparametric MRI radiomic features have potential in predicting non-response to neoadjuvant therapy in patients with LARC. Electronic supplementary material The online version of this article (10.1245/s10434-019-07300-3) contains supplementary material, which is available to authorized users.

show abstract

Quantitative analysis of diffusion weighted imaging to predict pathological good response to neoadjuvant chemoradiation for locally advanced rectal cancer

Cited by 32 publications

References 59 publications

Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer

Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer

Tumour regression after radiotherapy for rectal cancer – Results from the randomised Stockholm III trial

Radiomics-Based Pretherapeutic Prediction of Non-response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer

Contact Info

Product

Resources

About