Comparison of preoperative imaging and pathological findings for pancreatic head adenocarcinoma: A retrospective analysis by the Association Française de Chirurgie

Establishment of a multi-parameters MRI model for predicting small lymph nodes metastases (<10 mm) in patients with resected pancreatic ductal adenocarcinoma

PURPOSE

To evaluate the potential role of MR findings and DWI parameters in predicting small regional lymph nodes metastases (with short-axis diameter < 10 mm) in pancreatic ductal adenocarcinomas (PDACs).

METHODS

A total of 127 patients, 82 in training group and 45 in testing group, with histopathologically diagnosed PDACs who underwent pancreatectomy were retrospectively analyzed. PDACs were divided into two groups of positive and negative lymph node metastases (LNM) based on the pathological results. Pancreatic cancer characteristics, short axis of largest lymph node, and DWI parameters of PDACs were evaluated.

RESULTS

Univariate and multivariate analyses showed that extrapancreatic distance of tumor invasion, short-axis diameter of the largest lymph node, and mean diffusivity of tumor were independently associated with small LNM in patients with PDACs. The combining MRI diagnostic model yielded AUCs of 0.836 and 0.873, and accuracies of 81.7% and 80% in the training and testing groups. The AUC of the MRI model for predicting LNM was higher than that of subjective MRI diagnosis in the training group (rater 1, P = 0.01; rater 2, 0.008) and in a testing group (rater 1, P = 0.036; rater 2, 0.024). Comparing the subjective diagnosis, the error rate of the MRI model was decreased. The defined LNM-positive group by the MRI model showed significantly inferior overall survival compared to the negative group (P = 0.006).

CONCLUSIONS

The MRI model showed excellent performance for individualized and noninvasive prediction of small regional LNM in PDACs. It may be used to identify PDACs with small LNM and contribute to determining an appropriate treatment strategy for PDACs.

Resectable pancreatic ductal adenocarcinoma: association between preoperative CT texture features and metastatic nodal involvement

Background

To explore the relationship between the lymph node status and preoperative computed tomography images texture features in pancreatic cancer.

Methods

A total of 155 operable pancreatic cancer patients (104 men, 51 women; mean age 63.8 ± 9.6 years), who had undergone contrast-enhanced computed tomography in the arterial and portal venous phases, were enrolled in this retrospective study. There were 73 patients with lymph node metastases and 82 patients without nodal involvement. Four different data sets, with thin (1.25 mm) and thick (5 mm) slices (at arterial phase and portal venous phase) were analysed. Texture analysis was performed by using MaZda software. A combination of feature selection algorithms was used to determine 30 texture features with the optimal discriminative performance for differentiation between lymph node positive and negative groups. The prediction performance of the selected feature was evaluated by receiver operating characteristic (ROC) curve analysis.

Results

There were 10 texture features with significant differences between two groups and significance in ROC analysis were identified. They were WavEnLH_s-2(wavelet energy with rows and columns are filtered with low pass and high pass frequency bands with scale factors 2) from wavelet-based features, 135dr_LngREmph (long run emphasis in 135 direction) and 135dr_Fraction (fraction of image in runs in 135 direction) from run length matrix-based features, and seven variables of sum average from coocurrence matrix-based features (SumAverg). The ideal cutoff value for predicting lymph node metastases was 270 for WavEnLH_s-2 (positive likelihood ratio 2.08). In addition, 135dr_LngREmph and 135dr_Fraction were correlated with the ratio of metastatic to examined lymph nodes.

Conclusions

Preoperative computed tomography high order texture features provide a useful imaging signature for the prediction of nodal involvement in pancreatic cancer.

A Single-Institution Validation Study of Lymph Node Staging By the AJCC 8th Edition for Patients with Pancreatic Head Cancer: A Proposal to Subdivide the N2 Category

BACKGROUND

According to the revised staging of the American Joint Committee on Cancer, 8th edition (AJCC8), the N category in pancreatic ductal adenocarcinoma is classified as N0 (0), N1 (1-3), and N2 (≥ 4) based on the number of metastatic lymph nodes (LNs). This study aimed to validate this classification and analyze cutoff values of metastatic LN numbers.

METHODS

Patients with pancreatic head ductal adenocarcinoma who underwent pancreaticoduodenectomy at our institution between 2005 and 2016 without preoperative therapy were retrospectively analyzed. The patients were staged by AJCC8, and prognostic analyses were performed. The best cutoff value for the metastatic LN number was determined by the minimum P value approach.

RESULTS

In 228 of 309 patients, LN metastases were found (median number of examined LNs, 41). The median survival time (MST) was 56 months in the N0 group, 34 months in the N1 group, and 20 months in the N2 group (N0 vs N1: P = 0.023; N1 vs N2: P < 0.001). The best cutoff number of metastatic LNs was 4 for patients with LN metastases and 7 for patients with N2 disease. The MST for patients with four to six positive nodes (N2a) was significantly longer than for those with seven or more positive nodes (N2b) (24.0 vs 19.1 months: P = 0.012). For N2b patients, conventional adjuvant chemotherapy did not show survival benefits (P = 0.133), and overall survival did not differ significantly from that for patients with para-aortic LN metastasis (P = 0.562).

CONCLUSION

The N staging of AJCC8 was valid. Clinicians should regard N2b as similar to distant LN metastasis, and more intensive adjuvant therapy may be indicated for this group.

Intravoxel incoherent motion magnetic resonance imaging for differentiating metastatic and non-metastatic lymph nodes in pancreatic ductal adenocarcinoma

OBJECTIVES

To evaluate the diagnostic potential of intravoxel incoherent motion (IVIM) DWI for differentiating metastatic and non-metastatic lymph node stations (LNS) in pancreatic ductal adenocarcinoma (PDAC).

METHODS

59 LNS histologically diagnosed following surgical resection from 15 patients were included. IVIM DWI with 12 b values was added to the standard MRI protocol. Evaluation of parameters was performed pre-operatively and included the apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*) and perfusion fraction (f). Diagnostic performance of ADC, D, D* and f for differentiating between metastatic and non-metastatic LNS was evaluated using ROC analysis.

RESULTS

Metastatic LNS had significantly lower D, D*, f and ADC values than the non-metastatic LNS (p< 0.01). The best diagnostic performance was found in D, with an area under the ROC curve of 0.979, while the area under the ROC curve values of D*, f and ADC were 0.867, 0.855 and 0.940, respectively. The optimal cut-off values for distinguishing metastatic and non-metastatic lymph nodes were D = 1.180 × 10-3 mm2/s; D* = 14.750 × 10-3 mm2/s, f = 20.65 %, and ADC = 1.390 × 10-3 mm2/s.

CONCLUSION

IVIM DWI is useful for differentiating between metastatic and non-metastatic LNS in PDAC.

KEY POINTS

• IVIM DWI is feasible for diagnosing LN metastasis in PDAC. • Metastatic LNS has lower D, D*, f, ADC values than non-metastatic LNS. • D-value from IVIM model has best diagnostic performance, followed by ADC value. • D* has the lowest AUC value.