ABSTRACT
@#China is a country with a high incidence of esophageal cancer. Most patients are already in the locally advanced stage when first diagnosed. Preoperative neoadjuvant therapy followed by surgery has become the standard treatment mode for them. Closely related to prognosis, the evaluation of tumor response is essential. Response evaluation criteria in solid tumors is the gold standard to evaluate tumor response, but the lesions must meet the measurement standards. Tumor regression grading (TRG) systems are designed to classify regressive changes after neoadjuvant treatment based on histopathological results to reveal prognostic information. Concentrating on pathologic assessment of esophageal cancer following neoadjuvant therapy, this article reviews histopathological changes, commonly used TRG systems and current debate.
ABSTRACT
Introduction: Colorectal cancer is one of the most common malignant tumors and has a relatively poor prognosis. Lymph node involvement is considered the most important prognostic factor. Materials and Methods: During a retrospective cohort study, 132 patients with locally advanced rectal cancer who underwent neoadjuvant chemoradiotherapy followed by surgery for resectable rectal cancer from 2010 to 2015 in Sina hospital were reviewed. Results: Multivariable analysis was performed and shown the clinical stage was not a representative factor for disease-free survival (P = 0.187), but Dworak Tumor Regression Grading were significantly associated with higher disease-free survival (P = 0.000) in stage II and stage III. The total number of retrieved lymph nodes and involved lymph nodes in the same clinical stage were statistically associated with higher mean disease-free survival in patients (P = 0.000 in both conditions). Conclusion: In the same clinical stage, increasing the Dworak Tumor Regression Grading reduced the risk of rectal cancer recurrence. Increasing total number of retrieved lymph nodes and involved lymph nodes, 2.14 times and 3.87 times increased the risk of recurrence, respectively.
ABSTRACT
Objective: Pelvic high-resolution magnetic resonance imaging (MRI) has now become a standard method for evaluating the efficacy of neoadjuvant treatment for locally advanced rectal cancer (LARC). However, this traditional morphological qualitative assessment method based on T2-weighted imaging (T2WI) is not effective in predicting pathological complete remission (pCR). The purpose of this study is to investigate whether combining the magnetic resonance tumor regression grade (mrTRG) with apparent diffusion coefficient (ADC) can improve diagnostic value for pCR after preoperative neoadjuvant chemoradiotherapy (nCRT) of LARC. Methods: This was a diagnostic study. Clinicopathological data of 134 LARC patients who received nCRT and radical surgery in the First Affiliated Hospital of Kunming Medical University from January 2017 to December 2019 were retrospectively analyzed. All the patients underwent MRI which included T2WI and DWI sequences before and 8 weeks after nCRT. Two radiologists independently drew ROIs on T2WI and DWI to estimate mrTRG stage and calculate the mean ADC value. Receiver operating characteristics (ROC) method was applied to evaluate the predict value of mrTRG combined with mean ADC value for pCR. Results: Of 134 LARC patients, 85 were male and 49 were female with median age of 58 (28-82) years. After nCRT, MRI suggested 21 patients (15.7%) had clinical complete remission (cCR), e.g. mrTRG stage 1-2. Postoperative pathology revealed 31 (23.1%) patients had pCR. The evaluations of mrTRG and ADC value by the two readers were highly consistent, and the intra-group correlation coefficients were 0.83 (95% CI: 0.703-0.881) and 0.96 (95% CI: 0.989-0.996), respectively. There was a negative correlation between mrTRG and pCR (r(s)=-0.505, P<0.01), and a positive correlation between mean ADC value and pCR (r(s)=0.693, P<0.01). The ROC curve showed that mrTRG alone had a medium predictive value for pCR, with an area under the curve (AUC) of 0.832 (95% CI: 0.743-0.921); the mean ADC value had a higher predictive value for pCR, with AUC of 0.906 (95% CI: 0.869-0.962). The predictive value of the combined model of mrTRG and ADC value for pCR was significantly better than that of mrTRG alone (P=0.015), and the AUC was 0.908 (95% CI: 0.849-0.968). Conclusion: Both mrTRG and mean ADC value can be non-invasive methods to predict the efficacy of nCRT for LARC. Combining the mean ADC value with mrTRG can result in better pCR prediction.