Abstract
This study aimed to predict early treatment response to concurrent chemoradiotherapy (CCRT) by combining intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) with texture analysis (TA) for cervical cancer patients and to develop a nomogram for estimating the risk of residual tumor. Ninty-three cervical cancer patients underwent conventional MRI and IVIM-DWI before CCRT. We conducted TA using T2WI. The patients were allocated to partial response (PR) and complete response (CR) groups on the basis of posttreatment MRI. Multivariate logistic regression analysis on IVIM-DWI parameters and texture features was employed to filter the independent predictors and construct the predictive nomogram. Its discrimination and calibration performances were estimated. Multivariate analysis on the IVIM-DWI parameters showed that D and f were independent predictors (OR = 4.029 and 0.889, resp.; p < 0.05). However, the multivariate analysis on the texture features indicated that GLCM-correlation, GLRLM-LRE, and GLSZM-ZE were independent predictors (OR = 43.789, 9.774, and 23.738, resp.;p < 0.05). The combination of IVIM-DWI parameters and texture features exhibited the highest predictive performance (AUC = 0.975). The nomogram to identify the patients with high-risk residual tumors exhibited an acceptable predictive performance and stability with a C-index of 0.953. Decision curve analysis demonstrated the clinical use of the nomogram. The results demonstrate that D, f, GLCM-correlation, GLRLM-LRE, and GLSZM-ZE were independent predictors for cervical cancer. The nomogram combining IVIM-DWI parameters and texture features makes it possible to identify cervical cancer patients at a high risk of residual tumor after CCRT.
Highlights
As the fourth most commonly diagnosed type of cancer, cervical cancer globally ranks fourth among cancer-related deaths in female [1]
One month after concurrent chemoradiotherapy (CCRT), there were 58 patients in the complete response (CR) group and 35 in the partial response (PR) group. ere were no significant differences in age, squamous cell carcinoma antigen (SCC), tumor size, Federation of Gynecology and Obstetrics (FIGO) stage, lymph node status, and histological type between the two groups (p > 0.05)
To differentiate CR from PR, the combination of IVIM-diffusion weighted imaging (DWI) and texture analysis (TA) had the highest AUC (0.975, 95%confidence intervals (CIs): 0.950–1.000), accuracy (92.5%), specificity (91.4%), and sensitivity (93.1%). erefore, a nomogram was developed to predict the possibility of residual tumor after one month of CCRT for cervical cancer (Figure 3). e nomogram was based on IVIM-DWI parameters (D, f ) and texture features (GLCM-correlation, GLRLM-LRE, and GLSZM-ZE)
Summary
As the fourth most commonly diagnosed type of cancer, cervical cancer globally ranks fourth among cancer-related deaths in female [1]. Given the tumor heterogeneity, it is unlikely that different types of cancer respond to a particular treatment in the same way [4]. Clinicians will be able to adjust treatment approaches in case of reliable biomarkers identifying patients in time, who are at a high risk of residual tumor. With the emergence of diffusion weighted imaging (DWI), characterization and detection of diseases improved, probing the diffusion of water molecules in biological tissue. IVIMDWI parameters can be used to monitor therapeutic alterations during CCRT, in addition to differentiating benign lesions from cervical cancer [8, 9]. In the previously mentioned studies, significant information is reported on both characterizations of carcinoma and treatment response by IVIM-DWI
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