Prediction of the tumor response and survival based on computed tomography in esophageal squamous cell carcinoma after trimodality therapy

Comparative evaluation of imaging methods for prognosis assessment in esophageal squamous cell carcinoma: focus on diffusion-weighted magnetic resonance imaging, computed tomography and esophagography

Objective

To identify the most sensitive imaging examination method to evaluate the prognosis of esophageal squamous cell carcinoma (ESCC).

Materials and methods

Thirty patients with esophageal squamous cell carcinoma (ESCC) participated in the study and underwent chemoradiotherapy (CRT). They were divided into two groups based on their survival status: the survival group and non-survival group. The diagnostic tests were utilized to determine the most effective imaging examination method for assessing the prognosis.

Results

1. There were no significant differences in tumor length shown on esophagography or computed tomography (CT) or the maximal esophageal wall thickness shown on CT at the specified time points between the two groups. 2. The tumor length on diffusion-weighted imaging (DWI) in the survival group was significantly lower than in the non-survival group at the end of the sixth week of treatment (P=0.001). The area under the ROC curve was 0.840 (P=0.002), and the diagnostic efficiency was moderately accurate. 3. The apparent diffusion coefficient (ADC) values of the survival group were significantly higher than those in the non-survival group at the end of the fourth week and sixth week of treatment (both P<0.001). Areas under the curve were 0.866 and 0.970, with P values of 0.001 and <0.001 and good diagnostic accuracy. Cox regression analyses indicated the ADC at the end of the sixth week of treatment was an independent risk factor.

Conclusions

Compared with esophagography and CT, DW-MRI has certain advantages in predicting the prognosis of ESCC.

CT-based delta-radiomics nomogram to predict pathological complete response after neoadjuvant chemoradiotherapy in esophageal squamous cell carcinoma patients

BACKGROUND

This study developed a nomogram model using CT-based delta-radiomics features and clinical factors to predict pathological complete response (pCR) in esophageal squamous cell carcinoma (ESCC) patients receiving neoadjuvant chemoradiotherapy (nCRT).

METHODS

The study retrospectively analyzed 232 ESCC patients who underwent pretreatment and post-treatment CT scans. Patients were divided into training (n = 186) and validation (n = 46) sets through fivefold cross-validation. 837 radiomics features were extracted from regions of interest (ROIs) delineations on CT images before and after nCRT to calculate delta values. The LASSO algorithm selected delta-radiomics features (DRF) based on classification performance. Logistic regression constructed a nomogram incorporating DRFs and clinical factors. Receiver operating characteristic (ROC) and area under the curve (AUC) analyses evaluated nomogram performance for predicting pCR.

RESULTS

No significant differences existed between the training and validation datasets. The 4-feature delta-radiomics signature (DRS) demonstrated good predictive accuracy for pCR, with α-binormal-based and empirical AUCs of 0.871 and 0.869. T-stage (p = 0.001) and differentiation degree (p = 0.018) were independent predictors of pCR. The nomogram combined the DRS and clinical factors improved the classification performance in the training dataset (AUCαbin = 0.933 and AUCemp = 0.941). The validation set showed similar performance with AUCs of 0.958 and 0.962.

CONCLUSIONS

The CT-based delta-radiomics nomogram model with clinical factors provided high predictive accuracy for pCR in ESCC patients after nCRT.

CT radiomics identifying non-responders to neoadjuvant chemoradiotherapy among patients with locally advanced rectal cancer

BACKGROUND AND PURPOSE

Early detection of non-response to neoadjuvant chemoradiotherapy (nCRT) for locally advanced colorectal cancer (LARC) remains challenging. We aimed to assess whether pretreatment radiotherapy planning computed tomography (CT) radiomics could distinguish the patients with no response or no downstaging after nCRT from those with response and downstaging after nCRT.

MATERIALS AND METHODS

Patients with LARC who were treated with nCRT were retrospectively enrolled between March 2009 and March 2019. Traditional radiological characteristics were analyzed by visual inspection and radiomic features were analyzed through computational methods from the pretreatment radiotherapy planning CT images. Differentiation models were constructed using radiomic methods and clinicopathological characteristics for predicting non-response to nCRT. Model performance was assessed for classification efficiency, calibration, discrimination, and clinical application.

RESULTS

This study enrolled a total of 215 patients, including 151 patients in the training cohort (50 non-responders and 101 responders) and 64 patients in the validation cohort (21 non-responders and 43 responders). For predicting non-response, the model constructed with an ensemble machine learning method had higher performance with area under the curve (AUC) values of 0.92 and 0.89 as compared to the model constructed with the logistic regression method (AUC: 0.72 and 0.71 for the training and validation cohorts, respectively). Both decision curve and calibration curve analyses confirmed that the ensemble machine learning model had higher prediction performance.

CONCLUSION

Pretreatment CT radiomics achieved satisfying performance in predicting non-response to nCRT and could be helpful to assist in treatment planning for patients with LARC.

Evaluation of Neoadjuvant Chemoradiotherapy Followed by Surgery for Borderline Resectable Esophageal Squamous Cell Carcinoma

BACKGROUND

It is occasionally difficult to diagnose cT3 or cT4b using imaging examinations for esophageal cancer. The optimal treatment strategy for borderline resectable esophageal squamous cell carcinoma (BR-ESCC) is unclear.

METHODS

We included 131 patients with cT3 ESCC who received neoadjuvant chemoradiotherapy (NCRT) followed by surgery. The patients were classified as having definitive cT3 (D-cT3) or borderline resectable cT3 (BR-cT3), based on presence of undeniable adjacent organ invasion on pretreatment CT. Surgical outcomes and prognoses were compared among patients with D-cT3 and BR-cT3 tumors, and the risk factors for non-R0 resection were assessed.

RESULTS

Ninety and 41 patients were classified as D-cT3 and BR-cT3, respectively. Although BR-cT3 had a significantly higher non-R0 resection rate than D-cT3 (D-cT3 3.7%; BR-cT3 14.6%), BR-cT3 was not correlated with shorter overall survival (OS) (D-cT3 5-year OS, 50.8%; BR-cT3 5-year OS 38.4%; p = 0.234). Conversely, non-R0 resection was significantly associated with poor OS (R0 resection 5-year OS 48.8%; non-R0 resection 5-year OS 22.2%; p = 0.031). Cox regression analysis of OS demonstrated that BR-cT3 was not a prognostic factor. In the analysis of risk factors for non-R0 resection, BR-cT3 (p = 0.027), suspected invasion of the trachea or bronchus (p = 0.046), and high SUVmax of the primary lesion after NCRT (p = 0.002) were risk factors.

CONCLUSIONS

NCRT followed by surgery achieved a relatively high R0 resection rate and an almost equal overall survival rate for BR-cT3 compared with D-cT3 ESCC. Thus, NCRT followed by surgery is an effective treatment strategy for patients with BR-cT3 ESCC.