Rim Enhancement and Peripancreatic Fat Stranding in Preoperative MDCT as Predictors for Occult Metastasis in PDAC Patients

Identification of SMAD4-mutated pancreatic ductal adenocarcinoma using preoperative contrast-enhanced MRI and clinical characteristics

AIM

To assess the value of preoperatively contrast-enhanced MRI and clinical characteristics for identification of SMAD4-mutated pancreatic ductal adenocarcinoma (PDAC) patients.

MATERIALS AND METHODS

This retrospective study included patients with surgically confirmed PDAC from January 2016 to December 2022. Based on immunostaining results indicating the mutation of SMAD4, the enrolled participants were grouped into SMAD4-mutated PDAC and non-SMAD4-mutated PDAC. Contrast-enhanced MRI findings, clinical-pathological characteristics, and prognosis were recorded and reviewed. The pathological findings and clinical prognosis were compared between the two groups. Uni- and multivariable logistic regression analyses were further performed to determine the radiological and clinical predictive factors for the mutation of SMAD4.

RESULTS

In total, 428 PDAC patients were enrolled and analyzed, who were grouped as SMAD4-mutated PDAC (n = 224) and non-SMAD4-mutated PDAC (n = 204). SMAD4-mutated PDAC demonstrated higher frequency of pathological fatty infiltration (83.4% vs. 74.2%, P = 0.016), peripheral nerve infiltration (84.4% vs. 76.5%, P = 0.039). and higher recurrence rates (43.6% vs. 58.9%, P = 0.045) than non-SMAD4-mutated PDAC. The 3-year recurrence-free survival rates were worse for SMAD4-mutated PDAC (28.7% vs. 39.1%). In multivariable logistic regression analyses, CA19-9 > 100 U/mL (odds ratio [OR] = 1.519, P = 0.041), CBD dilation (OR = 1.564, P = 0.036), and rim enhancement (OR = 1.631, P = 0.025) were independent predictive factors.

CONCLUSION

Rim enhancement, CBD dilation on contrast-enhanced MRI and higher CA19-9 level are promising radiological and clinical factors for identifying SMAD4-mutated PDAC.

Performance of different CT enhancement quantification methods as predictors of pancreatic cancer recurrence after upfront surgery

The prognosis of pancreatic cancer (PDAC) after tumor resection remains poor, mostly due to a high but variable risk of recurrence. A promising tool for improved prognostication is the quantification of CT tumor enhancement. For this, various enhancement formulas have been used in previous studies. However, a systematic comparison of these formulas is lacking. In the present study, we applied twenty-three previously published CT enhancement formulas to our cohort of 92 PDAC patients who underwent upfront surgery. We identified seven formulas that could reliably predict tumor recurrence. Using these formulas, weak tumor enhancement was associated with tumor recurrence at one and two years after surgery (p ≤ 0.030). Enhancement was inversely associated with adverse clinicopathological features. Low enhancement values were predictive of a high recurrence risk (Hazard Ratio ≥ 1.659, p ≤ 0.028, Cox regression) and a short time to recurrence (TTR) (p ≤ 0.027, log-rank test). Some formulas were independent predictors of TTR in multivariate models. Strikingly, almost all of the best-performing formulas measure solely tumor tissue, suggesting that normalization to non-tumor structures might be unnecessary. Among the top performers were also the absolute arterial/portal venous tumor attenuation values. These can be easily implemented in clinical practice for better recurrence prediction, thus potentially improving patient management.

Rim Enhancement on Contrast-Enhanced CT as a Predictor of Prognosis in Patients with Pancreatic Ductal Adenocarcinoma

This study investigated the utility of imaging features, such as rim enhancement on contrast-enhanced CT (CECT), in predicting the prognosis of pancreatic ductal adenocarcinoma (PDAC). This retrospective study included 158 patients (84 men; mean age, 68 years) with pathologically confirmed PDAC. The following imaging features were evaluated on CECT by two radiologists: tumor size, tumor attenuation, and the presence of rim enhancement. Cox proportional hazards analysis was performed to identify the imaging and clinicopathological features for predicting disease-free survival (DFS) and overall survival (OS). Pathological features were compared with the presence of rim enhancement. Among the 158 patients, 106 (67%) underwent curative surgery (surgery group) and 52 (33%) received conservative treatment (non-surgery group). Rim enhancement was observed more frequently in the non-surgery group than in the surgery group (44% vs. 20%; p < 0.001). Rim enhancement showed significant associations with shorter DFS and OS in the surgery group (hazard ratios (HRs), 3.03 and 2.99; p < 0.001 and p = 0.003, respectively), whereas tumor size showed significant associations with shorter OS (HR per 1 mm increase, 1.08; p < 0.001). PDACs with rim enhancement showed significant associations with higher histological tumor grades (p < 0.001). PDAC with rim enhancement on CECT could predict poorer prognosis and more aggressive tumor grades.

Rim enhancement of pancreatic ductal adenocarcinoma: investigating the relationship with DCE-MRI-based radiomics and next-generation sequencing

Purpose

To identify the clinical and genetic variables associated with rim enhancement of pancreatic ductal adenocarcinoma (PDAC) and to develop a dynamic contrast-enhanced (DCE) MRI-based radiomics model for predicting the genetic status from next-generation sequencing (NGS).

Materials and methods

Patients with PDAC, who underwent pretreatment pancreatic DCE-MRI between November 2019 and July 2021, were eligible in this prospective study. Two radiologists evaluated presence of rim enhancement in PDAC, a known radiological prognostic indicator, on DCE MRI. NGS was conducted for the tissue from the lesion. The Mann-Whitney U and Chi-square tests were employed to identify clinical and genetic variables associated with rim enhancement in PDAC. For continuous variables predicting rim enhancement, the cutoff value was set based on the Youden's index from the receiver operating characteristic (ROC) curve. Radiomics features were extracted from a volume-of-interest of PDAC on four DCE maps (Ktrans, Kep, Ve, and iAUC). A random forest (RF) model was constructed using 10 selected radiomics features from a pool of 392 original features. This model aimed to predict the status of significant NGS variables associated with rim enhancement. The performance of the model was validated using test set.

Results

A total of 55 patients (32 men; median age 71 years) were randomly assigned to the training (n = 41) and test (n = 14) sets. In the training set, KRAS, TP53, CDKN2A, and SMAD4 mutation rates were 92.3%, 61.8%, 14.5%, and 9.1%, respectively. Tumor size and KRAS variant allele frequency (VAF) differed between rim-enhancing (n = 12) and nonrim-enhancing (n = 29) PDACs with a cutoff of 17.22%. The RF model's average AUC from 10-fold cross-validation for predicting KRAS VAF status was 0.698. In the test set comprising 6 tumors with low KRAS VAF and 8 with high KRAS VAF, the RF model's AUC reached 1.000, achieving a sensitivity of 75.0%, specificity of 100% and accuracy of 87.5%.

Conclusion

Rim enhancement of PDAC is associated with KRAS VAF derived from NGS-based genetic information. For predicting the KRAS VAF status in PDAC, a radiomics model based on DCE maps showed promising results.