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Abstract
This prospective study explored the application of texture features extracted from T2WI and apparent diffusion coefficient (ADC) maps in predicting recurrence of advanced cervical cancer patients treated with concurrent chemoradiotherapy (CCRT). We included 34 patients with advanced cervical cancer who underwent pelvic MR imaging before, during and after CCRT. Radiomic feature extraction was performed by using software at T2WI and ADC maps. The performance of texture parameters in predicting recurrence was evaluated. After a median follow-up of 31 months, eleven patients (32.4%) had recurrence. At four weeks after CCRT initiated, the most textural parameters (four T2 textural parameters and two ADC textural parameters) showed significant difference between the recurrence and nonrecurrence group (P values range, 0.002~0.046). Among them, RunLengthNonuniformity (RLN) from T2 and energy from ADC maps were the best selected predictors and together yield an AUC of 0.885. The support vector machine (SVM) classifier using ADC textural parameters performed best in predicting recurrence, while combining T2 textural parameters may add little value in prognosis. T2 and ADC textural parameters have potential as non-invasive imaging biomarkers in early predicting recurrence in advanced cervical cancer treated with CCRT.
Highlights
Cervical cancer is the fourth leading cause of cancer death in females worldwide
Sylvain et al and Ho et al found texture features extracted from positron emission tomography (PET) images could predict recurrence of cervical cancer better than SUVmax while PET is less clinically used than magnetic resonance imaging (MRI) with radiation exposure[14,15]
We aimed to explore more promising texture features extracted from pre- and post-treatment T2- weighted images (T2WI) and apparent diffusion coefficient (ADC) maps to non-invasively predict recurrence of advanced cervical cancer patients treated with concurrent chemoradiotherapy (CCRT)
Summary
Cervical cancer is the fourth leading cause of cancer death in females worldwide. Concurrent chemoradiotherapy (CCRT) is the standard treatment for locally advanced cervical cancer. As a noninvasive functional imaging technique, diffusion weighted imaging (DWI) has been widely used in the prediction of treatment outcome in cervical cancer research but the accuracy is limited. A recent study reported that texture features were associated with pathologic complete response only at T2WI but not at DCE in breast cancer treated with neoadjuvant chemotherapy[20]. Carlo et al demonstrated the efficacy of using texture analysis based on T2WI to predict tumor response to neoadjuvant chemoradiotherapy in rectal cancer[21]. To the best of our knowledge, there have been no previous reports examining texture analysis based on routine T2WI or DWI sequences for the prognosis of cervical cancer
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