Comprehensive histological evaluation with clinical analysis of venous invasion in pancreatic ductal adenocarcinoma: From histology to clinical implications

Periarterial divestment for borderline and locally advanced pancreatic cancer: An analysis of 125 cases in a single center

BACKGROUND

Literature on factors influencing prognosis after periarterial divestment for borderline resectable or locally advanced pancreatic ductal adenocarcinoma and preventative measures for postpancreatectomy hemorrhage is scarce. This study aimed to evaluate the efficacy of Neuro-Patch for arterial reinforcement in preventing postpancreatectomy hemorrhage and explore the oncologic outcomes of patients with borderline resectable or locally advanced pancreatic ductal adenocarcinoma following periarterial divestment.

METHODS

We conducted a retrospective analysis of 125 patients with borderline resectable or locally advanced pancreatic ductal adenocarcinoma involving arteries who underwent periarterial divestment between January 2018 and May 2022.

RESULTS

Among the study cohort, 54 patients underwent pancreaticoduodenectomy, 43 had distal pancreatectomy, and 28 received total pancreatectomy, with 74 patients also undergoing combined venous resection. Periarterial divestment was performed on the hepatic artery in 47 patients, the celiac artery in 3, the superior mesenteric artery in 22, and multiple arteries in 53. Neoadjuvant chemotherapy was administered to 24% of patients, with an R0 resection rate of 33.6%. The median postoperative hospital stay was 10 days, with a 90-day mortality rate of 3.2%. Neuro-Patch was used in 51 patients, leading to a significant reduction in postpancreatectomy hemorrhage (odds ratio 0.073, 95% confidence interval 0.007-0.783, P = .031). The median overall survival was 20.6 months, with 1- and 3-year survival rates estimated at 73.2% and 22.9%, respectively. Neoadjuvant chemotherapy (hazard ratio 0.494, 95% confidence interval 0.291-0.839, P = .009) and venous invasion (hazard ratio 2.041, 95% confidence interval 1.308-3.186, P = .002) emerged as independent predictors of overall survival.

CONCLUSION

Neoadjuvant chemotherapy significantly enhances survival outcomes of patients with borderline resectable or locally advanced pancreatic ductal adenocarcinoma undergoing periarterial divestment, and it should be regarded as a standard preoperative approach. The Neuro-Patch provides structural reinforcement to the arterial wall, potentially reducing the risk of postpancreatectomy hemorrhage. However, randomized controlled trials are necessary to substantiate its efficacy and safety.

Development of Clinical Radiomics-Based Models to Predict Survival Outcome in Pancreatic Ductal Adenocarcinoma: A Multicenter Retrospective Study

PURPOSE

This multicenter retrospective study aims to identify reliable clinical and radiomic features to build machine learning models that predict progression-free survival (PFS) and overall survival (OS) in pancreatic ductal adenocarcinoma (PDAC) patients.

METHODS

Between 2010 and 2020 pre-treatment contrast-enhanced CT scans of 287 pathology-confirmed PDAC patients from two sites of the Hopital Universitaire de Bruxelles (HUB) and from 47 hospitals within the HUB network were retrospectively analysed. Demographic, clinical, and survival data were also collected. Gross tumour volume (GTV) and non-tumoral pancreas (RPV) were semi-manually segmented and radiomics features were extracted. Patients from two HUB sites comprised the training dataset, while those from the remaining 47 hospitals of the HUB network constituted the testing dataset. A three-step method was used for feature selection. Based on the GradientBoostingSurvivalAnalysis classifier, different machine learning models were trained and tested to predict OS and PFS. Model performances were assessed using the C-index and Kaplan-Meier curves. SHAP analysis was applied to allow for post hoc interpretability.

RESULTS

A total of 107 radiomics features were extracted from each of the GTV and RPV. Fourteen subgroups of features were selected: clinical, GTV, RPV, clinical & GTV, clinical & GTV & RPV, GTV-volume and RPV-volume both for OS and PFS. Subsequently, 14 Gradient Boosting Survival Analysis models were trained and tested. In the testing dataset, the clinical & GTV model demonstrated the highest performance for OS (C-index: 0.72) among all other models, while for PFS, the clinical model exhibited a superior performance (C-index: 0.70).

CONCLUSIONS

An integrated approach, combining clinical and radiomics features, excels in predicting OS, whereas clinical features demonstrate strong performance in PFS prediction.

A primer on artificial intelligence in pancreatic imaging

Artificial Intelligence (AI) is set to transform medical imaging by leveraging the vast data contained in medical images. Deep learning and radiomics are the two main AI methods currently being applied within radiology. Deep learning uses a layered set of self-correcting algorithms to develop a mathematical model that best fits the data. Radiomics converts imaging data into mineable features such as signal intensity, shape, texture, and higher-order features. Both methods have the potential to improve disease detection, characterization, and prognostication. This article reviews the current status of artificial intelligence in pancreatic imaging and critically appraises the quality of existing evidence using the radiomics quality score.

Immunohistochemical analysis of a panel of cancer stem cell markers and potential therapeutic markers in pancreatic ductal adenocarcinoma

PURPOSE

Pancreatic Ductal Adenocarcinoma (PDAC) is the most common type of pancreatic malignancies. It is known for its aggressive nature and high mortality rate. This calls for an urgent need of new prognostic and therapeutic markers that can be targeted for personalized treatment of the patient.

METHODS

Among 142 patients diagnosed with pancreatic cancers at Aga Khan University Hospital, a total of 62 patients were selected based on their confirmed diagnosis of PDAC. Immunohistochemistry was performed on Formalin-Fixed Paraffin-Embedded (FFPE) sections using selected antibodies (CD44, CD133, L1CAM, HER2, PD-L1, EGFR, COX2 and cyclin D1). All the slides were scored independently by two pathologists as per the set criteria.

RESULTS

Expression of all cancer stem cell markers was found to be significantly associated with one or more potential therapeutic markers. CD44 expression was significantly associated with HER2 (p = 0.032), COX2 (p = 0.005) and EGFR expression (p = 0.008). CD133 expression also showed significant association with HER2 (p = 0.036), COX2 (p = 0.004) and EGFR expression (p = 0.018). L1CAM expression was found to be associated with expression of COX2 (p = 0.017). None of the proteins markers showed association with overall survival of the patient. On the other hand, among the clinicopathological characteristics, histological differentiation (p = 0.047), lymphovascular invasion (p = 0.021) and perineural invasion (p = 0.014) were found to be significantly associated with patient's overall survival.

CONCLUSION

Internationally, this is the first report that assesses the selected panel of cancer stem cell markers and potential therapeutic targets in a single study and evaluates its combined expression. The study clearly demonstrates association between expression of cancer stem cell markers and therapeutic targets hence paves a way for precision medicine for pancreatic cancer patients.

Impact of resection margin status on survival after operation for pancreatic head cancer with extrapancreatic nerve plexus invasion

BACKGROUND

Extrapancreatic nerve plexus (PL) invasion of pancreatic ductal adenocarcinoma (PDAC) is an important factor for determining resectability and surgical method. We sought to clarify the characteristics of PDAC with PL invasion and clinical impact of the resection margin status on prognosis for PDAC with PL invasion.

METHODS

A total of 242 patients with pancreatic head cancer who underwent pancreatectomy were evaluated. Clinicopathological data and patient survival were analyzed.

RESULTS

Pathological PL invasion was observed in 68 patients (28.1%). Patients with PL invasion had significantly shorter disease-free survival (DFS) and showed trends toward worse overall survival (OS) than those without PL invasion. While multivariate analysis revealed that PL invasion was not an independent prognostic factor, PL invasion was associated with extensive venous invasion and a high percentage of lymph node metastases, both of which were independent factors affecting DFS and OS. Among patients with PL invasion, there was no significant difference in DFS and OS between the R0 and R1 resection groups.

CONCLUSIONS

PL invasion is a common pathological feature of aggressive PDAC with high propensity for invasiveness and metastatic potential. The microscopic resection margin status may not affect the survival of pancreatic head cancer patients with PL invasion.

Pancreatic ductal adenocarcinoma with a predominant large duct pattern has better recurrence-free survival than conventional pancreatic ductal adenocarcinoma: a comprehensive histopathological, immunohistochemical, and mutational study

Large duct pattern of pancreatic ductal adenocarcinomas (PDACs) comprises occasional large cancer glands (>0.5 mm in size), along with conventional smaller cancer glands. They histologically mimic intraductal papillary mucinous neoplasms. However, the clinicopathologic significance of PDACs with predominant large duct pattern (PLDP) has not been systematically evaluated. A total of 41 cases of PDACs with PLDP, which were defined as irregularly-shaped cancer glands >0.5 mm in size occupied >50% of tumor volume, were enrolled and their clinicopathological, immunohistochemical, and targeted exome-wise mutational characteristics were compared with 298 conventional PDACs. PDACs with PLDP had cancers with larger tumor sizes (P = 0.025), which were more frequently well to moderately differentiation (P < 0.001), with less lymphovascular invasion (P = 0.013) and had a higher T category (P = 0.023) than conventional PDACs. Immunohistochemically, PDACs with PLDP showed similar abnormal p53 (61%) and SMAD4 (59%) expression patterns as conventional PDACs. In addition, PDACs with PLDP showed diffuse MUC1 (88%), MUC5AC (100%), MUC6 (66%), and focal MUC2 (20%) expressions. More frequent ROS1 mutations were observed in PDACs with PLDP. PDAC patients with PLDP had a better overall and recurrence-free survival (OS and RFS; median, 42 and 34 months) than that of patients with conventional PDACs (34 and 16 months) as per univariate (P = 0.037 and P = 0.001) and multivariate (P = 0.031 and P = 0.034) analyses. PDACs with PLDP showed mutational patterns similar to those of conventional PDACs. They had unique histologic features and longer OS and RFS compared to those of conventional PDACs. Therefore, PDACs with PLDP could be considered a histologic subtype of PDACs.

Desmin and CD31 immunolabeling for detecting venous invasion of the pancreatobiliary tract cancers

Although venous invasion (VI) is a poor prognostic factor for patients with pancreatobiliary tract cancers, its histopathologic characteristics have not been well described. We evaluated the patterns of VI and the added benefit provided by CD31, desmin, and dual CD31‒desmin immunolabeling for identification of VI. We included 120 surgically resected pancreatobiliary tract cancer cases—59 cases as a test set with known VI and 61 cases as a validation set without information of VI. VI was classified into three patterns: intraepithelial neoplasia-like (IN-like), conventional, and destructive. Hematoxylin and eosin (H&E) staining and CD31, desmin, and dual CD31‒desmin immunolabeling were performed. Foci number and patterns of VI were compared with the test and validation sets. More foci of VI were detected by single CD31 (P = 0.022) than H&E staining in the test set. CD31 immunolabeling detected more foci of the conventional pattern of VI, and desmin immunolabeling detected more foci of the destructive pattern (all, P < 0.001). Dual CD31‒desmin immunolabeling identified more foci of VI (P = 0.012) and specifically detected more foci of IN-like (P = 0.045) and destructive patterns (P < 0.001) than H&E staining in the validation set. However, dual CD31‒desmin immunolabeling was not helpful for detecting the conventional pattern of VI in the validation set. Patients with VI detected by dual CD31‒desmin immunolabeling had shorter disease-free survival (P <0.001) than those without VI. VI detected by dual CD31‒desmin immunolabeling was a worse prognostic indicator (P = 0.009). More foci of VI could be detected with additional single CD31 or dual CD31‒desmin immunolabeling. The precise evaluation of VI with dual CD31‒desmin immunolabeling can provide additional prognostic information for patients with surgically resected pancreatobiliary tract cancers.