Scoring of tumour response after neoadjuvant therapy in resected pancreatic cancer: systematic review

Identification of tumour regression in neoadjuvantly treated pancreatic cancer is based on divergent and nonspecific criteria

AIMS

Following the increased use of neoadjuvant therapy for pancreatic cancer, grading of tumour regression (TR) has become part of routine diagnostics. However, it suffers from marked interobserver variation, which is mainly ascribed to the subjectivity of the defining criteria of the categories in TR grading systems. We hypothesized that a further cause for the interobserver variation is the use of divergent and nonspecific morphological criteria to identify tumour regression.

METHODS AND RESULTS

Twenty treatment-naïve pancreatic cancers and 20 pancreatic cancers treated with neoadjuvant chemotherapy were reviewed by three experienced pancreatic pathologists who, blinded for treatment status, categorized each tumour as treatment-naïve or neoadjuvantly treated, and annotated all tissue areas they considered showing tumour regression. Only 50%-65% of the cases were categorized correctly, and the annotated tissue areas were highly discrepant (only 3%-41% overlap). When the prevalence of various morphological features deemed to indicate TR was compared between treatment-naïve and neoadjuvantly treated tumours, only one pattern, characterized by reduced cancer cell density and prominent stroma affecting a large area of the tumour bed, occurred significantly more frequently, but not exclusively, in the neoadjuvantly treated group. Finally, stromal features, both morphological and biological, were investigated as possible markers for tumour regression, but failed to distinguish TR from native tumour stroma.

CONCLUSION

There is considerable divergence in opinion between pathologists when it comes to the identification of tumour regression. Reliable identification of TR is only possible if it is extensive, while lesser degrees of treatment effect cannot be recognized with certainty.

Microscopic tumor mapping of post-neoadjuvant therapy pancreatic cancer specimens to predict post-surgical recurrence: A prospective cohort study

BACKGROUND

Although various pathological grading systems are available for evaluating the response of pancreatic ductal adenocarcinoma (PDAC) to neoadjuvant therapy (NAT), their prognostic value has not been thoroughly validated. This study examined whether microscopic tumor mapping of post-NAT specimens could predict tumor recurrence.

METHODS

This prospective study enrolled 52 patients who underwent pancreaticoduodenectomy after NAT for PDAC between 2019 and 2021. Microscopic mapping was performed to identify residual tumor loci within the tumor bed using 4 mm2 pixels. Patients were divided into small extent (SE; n = 26) and large extent (LE; n = 26) groups using a cutoff value of 226 mm2. The diagnostic performance for predicting tumor recurrence was evaluated using receiver operating characteristic (ROC) curves.

RESULTS

Carbohydrate antigen 19-9 levels were normalised after NAT in more patients in the SE group (SE 21 [80.8%] vs. LE 13 [50.0%]; P = 0.041). Tumor size (P < 0.001), T stage (P < 0.001), positive lymph node yield (P = 0.024), and perineural invasion rate (P = 0.018) were significantly greater in the LE group. The 3-year disease-free survival rate was significantly lower in the LE group (SE 83.3% vs. LE 50.0%, P = 0.004). The area under the ROC curve for mapping extent was 0.743, which was greater than that of the other tumor response scoring systems.

CONCLUSIONS

Microscopic tumor mapping of the residual tumor in post-NAT specimens is a significant predictor of post-surgical recurrence, and offers better prognostic performance than the current grading systems.

Preoperative chemotherapy, radiotherapy and surgical decision-making in patients with borderline resectable and locally advanced pancreatic cancer

Surgical resection combined with systemic chemotherapy is the cornerstone of treatment for patients with localized pancreatic cancer. Upfront surgery is considered suboptimal in cases with extensive vascular involvement, which can be classified as either borderline resectable pancreatic cancer or locally advanced pancreatic cancer. In these patients, FOLFIRINOX or gemcitabine plus nab-paclitaxel chemotherapy is currently used as preoperative chemotherapy and is eventually combined with radiotherapy. Thus, more patients might reach 5-year overall survival. Patient selection for chemotherapy, radiotherapy and subsequent surgery is based on anatomical, biological and conditional parameters. Current guidelines and clinical practices vary considerably regarding preoperative chemotherapy and radiotherapy, response evaluation, and indications for surgery. In this Review, we provide an overview of the clinical evidence regarding disease staging, preoperative therapy, response evaluation and surgery in patients with borderline resectable pancreatic cancer or locally advanced pancreatic cancer. In addition, a clinical work-up is proposed based on the available evidence and guidelines. We identify knowledge gaps and outline a proposed research agenda.

Added value of digital FDG-PET/CT in disease staging and restaging in patients with resectable or borderline resectable pancreatic cancer

BACKGROUND

We studied the added value of digital FDG-PET/CT in disease staging and restaging compared to the standard work-up with contrast enhanced CT (ceCT) and CA19-9 in patients with resectable or borderline resectable pancreatic cancer who received neo-adjuvant therapy. Primary endpoints were tumor response compared to ceCT and CA19.9 as well as the ability to detect distant metastatic disease.

METHODS

35 patients were included in this dual-center prospective study. FDG-PET using digital photon counting technology combined with CT scans were acquired before (T₁) and after neo-adjuvant therapy (T₂). Patients were staged and restaged based on standard protocol with ceCT and CA 19.9, while all PET/CT scans were stored securely and not included in clinical decision making. After the pancreatic resection, an expert team retrospectively assessed the CT tumor diameter, CA19-9, tumor FDG-uptake, and appearance of metastatic disease of all patients for both time points.

RESULTS

CA19-9 levels, CT tumor diameter, and tumor FDG-uptake on PET significantly decreased from T₁ to T₂ (p = 0.017, p = 0.001, and p < 0.0001). The change in FDG-uptake values showed a strong positive correlation with the change in CT tumor diameter and change in CA19-9 (R = 0.75 and R = 0.73, respectively). In addition, small-volume liver lesions were detected on digital PET/CT in 5/35 patients (14%), 4 of which were pathology confirmed at laparotomy. Only one of these five cases was detected on baseline staging ceCT (3%).

CONCLUSION

We found that adding digital PET/CT strengthens restaging after neo-adjuvant therapy based on the observed strong correlation with ceCT tumor diameter and Ca19.9. Also, digital PET/CT was found to detect occult metastatic disease not visualized on ceCT, that would have resulted in altered disease staging and therapeutic strategy in a substantial proportion of patients.

Routine neoadjuvant chemotherapy for all patients with resectable pancreatic ductal adenocarcinoma? A review of the evidence

Pancreatic ductal adenocarcinoma is an aggressive malignancy that carries a poor prognosis because the majority of patients present with locally advanced or metastatic disease. However, even patients who are fortunate enough to present with resectable disease are often plagued by high recurrence rates. While adjuvant chemotherapy has been shown to decrease the risk of recurrence after surgery, post operative complications and poor performance status after surgery prevent up to 50% of patients from receiving it. Given the benefits of neoadjuvant therapy in patients with borderline resectable disease, it is understandable that neoadjuvant therapy has been steadily increasing in patients with resectable cancers as well. In this review paper, we highlight the rational and existing evidence of using neoadjuvant therapy in all patients with resectable pancreatic adenocarcinoma.

Proper adjuvant therapy in patients with borderline resectable and locally advanced pancreatic cancer who had received neoadjuvant FOLFIRINOX

Background

The complete resection rate of pancreatic cancer has increased because of the advent of efficacious first-line treatments for unresectable pancreatic cancer. Still, strategies regarding adjuvant therapy after neoadjuvant FOLFIRINOX treatment remain to be established.

Methods

Data on 144 patients with borderline resectable and locally advanced pancreatic cancer who underwent resection after neoadjuvant FOLFIRINOX between January 2013 and April 2021 were retrospectively reviewed.

Results

Among the study patients, 113 patients (78.5%) were diagnosed with borderline resectable pancreatic cancer and 31 patients (21.5%) were diagnosed with locally advanced pancreatic cancer. Seventy-five patients (52.1%) received radiotherapy before surgery. After radical resection, 84 patients (58.3%) received 5-fluorouracil-based adjuvant therapy and 60 patients (41.7%) received non-5-fluorouracil-based adjuvant therapy. Adjuvant therapy with 5-fluorouracil-based regimen [hazard ratio (HR), 0.43 (95% CI, 0.21–0.87); p = 0.019], preoperative assessment as locally advanced pancreatic cancer [HR, 2.87 (95% CI, 1.08–7.64); p = 0.035], positive resection margin [HR, 3.91 (95% CI, 1.71–8.94); p = 0.001], and presence of pathologic lymph node involvement [HR, 2.31 (95% CI, 1.00–5.33), p = 0.050] were associated with decreased recurrence-free survival. Adjuvant therapy with 5-fluorouracil-based regimen [HR, 0.35 (95% CI, 0.15–0.84); p = 0.018], positive resection margin [HR, 4.14 (95% CI, 1.75–9.78); p = 0.001], presence of pathologic lymph node involvement [HR, 3.36 (95% CI, 1.23–9.15); p = 0.018], poor differentiation [HR, 5.69 (95% CI, 1.76–18.36); p = 0.004], and dose reduction during adjuvant therapy [HR, 1.78 (95% CI, 1.24–24.37); p = 0.025] were associated with decreased overall survival.

Conclusions

The 5-fluorouracil-based adjuvant therapy seems to be the proper adjuvant therapy for patients who received neoadjuvant FOLFIRINOX for borderline resectable and locally advanced pancreatic cancer.

Setting the Research Agenda for Clinical Artificial Intelligence in Pancreatic Adenocarcinoma Imaging

Simple Summary

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers worldwide, associated with a 98% loss of life expectancy and a 30% increase in disability-adjusted life years. Image-based artificial intelligence (AI) can help improve outcomes for PDAC given that current clinical guidelines are non-uniform and lack evidence-based consensus. However, research on image-based AI for PDAC is too scattered and lacking in sufficient quality to be incorporated into clinical workflows. In this review, an international, multi-disciplinary team of the world’s leading experts in pancreatic cancer breaks down the patient pathway and pinpoints the current clinical touchpoints in each stage. The available PDAC imaging AI literature addressing each pathway stage is then rigorously analyzed, and current performance and pitfalls are identified in a comprehensive overview. Finally, the future research agenda for clinically relevant, image-driven AI in PDAC is proposed.

Abstract

Pancreatic ductal adenocarcinoma (PDAC), estimated to become the second leading cause of cancer deaths in western societies by 2030, was flagged as a neglected cancer by the European Commission and the United States Congress. Due to lack of investment in research and development, combined with a complex and aggressive tumour biology, PDAC overall survival has not significantly improved the past decades. Cross-sectional imaging and histopathology play a crucial role throughout the patient pathway. However, current clinical guidelines for diagnostic workup, patient stratification, treatment response assessment, and follow-up are non-uniform and lack evidence-based consensus. Artificial Intelligence (AI) can leverage multimodal data to improve patient outcomes, but PDAC AI research is too scattered and lacking in quality to be incorporated into clinical workflows. This review describes the patient pathway and derives touchpoints for image-based AI research in collaboration with a multi-disciplinary, multi-institutional expert panel. The literature exploring AI to address these touchpoints is thoroughly retrieved and analysed to identify the existing trends and knowledge gaps. The results show absence of multi-institutional, well-curated datasets, an essential building block for robust AI applications. Furthermore, most research is unimodal, does not use state-of-the-art AI techniques, and lacks reliable ground truth. Based on this, the future research agenda for clinically relevant, image-driven AI in PDAC is proposed.

3D Ultrasound-Guided Photoacoustic Imaging to Monitor the Effects of Suboptimal Tyrosine Kinase Inhibitor Therapy in Pancreatic Tumors

Pancreatic cancer is a disease with an incredibly poor survival rate. As only about 20% of patients are eligible for surgical resection, neoadjuvant treatments that can relieve symptoms and shrink tumors for surgical resection become critical. Many forms of treatments rely on increased vulnerability of cancerous cells, but tumors or regions within the tumors that may be hypoxic could be drug resistant. Particularly for neoadjuvant therapies such as the tyrosine kinase inhibitors utilized to shrink tumors, it is critical to monitor changes in vascular function and hypoxia to predict treatment efficacy. Current clinical imaging modalities used to obtain structural and functional information regarding hypoxia or oxygen saturation (StO₂) do not provide sufficient depth penetration or require the use of exogenous contrast agents. Recently, ultrasound-guided photoacoustic imaging (US-PAI) has garnered significant popularity, as it can noninvasively provide multiparametric information on tumor vasculature and function without the need for contrast agents. Here, we built upon existing literature on US-PAI and demonstrate the importance of changes in StO₂ values to predict treatment response, particularly tumor growth rate, when the outcomes are suboptimal. Specifically, we image xenograft mouse models of pancreatic adenocarcinoma treated with suboptimal doses of a tyrosine kinase inhibitor cabozantinib. We utilize the US-PAI data to develop a multivariate regression model that demonstrates that a therapy-induced reduction in tumor growth rate can be predicted with 100% positive predictive power and a moderate (58.33%) negative predictive power when a combination of pretreatment tumor volume and changes in StO₂ values pretreatment and immediately posttreatment was employed. Overall, our study indicates that US-PAI has the potential to provide label-free surrogate imaging biomarkers that can predict tumor growth rate in suboptimal therapy.

Proposal for a New Pathologic Prognostic Index After Neoadjuvant Chemotherapy in Pancreatic Ductal Adenocarcinoma (PINC)

BACKGROUND

Limited information is available on the relevant prognostic variables after surgery for patients with pancreatic ductal adenocarcinoma (PDAC) subjected to neoadjuvant chemotherapy (NACT). NACT is known to induce a spectrum of histological changes in PDAC. Different grading regression systems are currently available; unfortunately, they lack precision and accuracy. We aimed to identify a new quantitative prognostic index based on tumor morphology.

PATIENTS AND METHODS

The study population was composed of 69 patients with resectable or borderline resectable PDAC treated with preoperative NACT (neoadjuvant group) and 36 patients submitted to upfront surgery (upfront-surgery group). A comprehensive histological assessment on hematoxylin and eosin (H&E) stained sections evaluated 20 morphological parameters. The association between patient survival and morphological variables was evaluated to generate a prognostic index.

RESULTS

The distribution of morphological parameters evaluated was significantly different between upfront-surgery and neoadjuvant groups, demonstrating the effect of NACT on tumor morphology. On multivariate analysis for patients that received NACT, the predictors of shorter overall survival (OS) and disease-free survival (DFS) were perineural invasion and lymph node ratio. Conversely, high stroma to neoplasia ratio predicted longer OS and DFS. These variables were combined to generate a semiquantitative prognostic index based on both OS and DFS, which significantly distinguished patients with poor outcomes from those with a good outcome. Bootstrap analysis confirmed the reproducibility of the model.

CONCLUSIONS

The pathologic prognostic index proposed is mostly quantitative in nature, easy to use, and may represent a reliable tumor regression grading system to predict patient outcomes after NACT followed by surgery for PDAC.

Short-Course or Total Neoadjuvant Chemotherapy in Resectable and Borderline Resectable Pancreatic Cancer - Current Status and Future Perspectives

Neoadjuvant therapy improves overall survival compared with a surgery-first approach in patients with borderline resectable pancreatic cancer (BRPC). Evidence of higher quality is required to determine whether neoadjuvant therapy has potential benefits and improves survival for patients with resectable pancreatic cancer (RPC). Most randomized controlled trials (RCTs) have explored short-course neoadjuvant chemotherapy (SNT), but total neoadjuvant chemotherapy (TNT) is now the experimental arm of ongoing RCTs. This article reviews the current status of SNT and TNT in RPC and BRPC, and provides perspectives of future challenges and research directions in this field.

Longitudinal Study of Circulating Biomarkers in Patients with Resectable Pancreatic Ductal Adenocarcinoma

While patients with resectable pancreatic ductal adenocarcinoma (PDAC) show improved survival compared to their non-resectable counterparts, survival remains low owing to occult metastatic disease and treatment resistance. Liquid biopsy based on circulating tumor cells (CTCs) and cell-free DNA (cfDNA) has been shown to predict recurrence and treatment resistance in various types of cancers, but their utility has not been fully demonstrated in resectable PDAC. We have simultaneously tracked three circulating biomarkers, including CTCs, cfDNA, and circulating tumor DNA (ctDNA), over a period of cancer treatment using a microfluidic device and droplet digital PCR (ddPCR). The microfluidic device is based on the combination of filtration and immunoaffinity mechanisms. We have measured CTCs, cfDNA, and ctDNA in a cohort of seven resectable PDAC patients undergoing neoadjuvant therapy followed by surgery, and each patient was followed up to 10 time points over a period of 4 months. CTCs were detectable in all patients (100%) at some point during treatment but were detectable in only three out of six patients (50%) prior to the start of treatment. Median cfDNA concentrations remained comparable to negative controls throughout treatment. ddPCR was able to find KRAS mutations in six of seven patients (86%); however, these mutations were present in only two of seven patients (29%) prior to treatment. Overall, the majority of circulating biomarkers (81% for CTCs and 91% for cfDNA/ctDNA) were detected after the start of neoadjuvant therapy but before surgery. This study suggests that a longitudinal study of circulating biomarkers throughout treatment provides more useful information than those single time-point tests for resectable PDAC patients.

Artificial Intelligence-Based Segmentation of Residual Tumor in Histopathology of Pancreatic Cancer after Neoadjuvant Treatment

Simple Summary

The use of neoadjuvant therapy (NAT) in patients with pancreatic ductal adenocarcinoma (PDAC) is increasing. Objective quantification of the histopathological response to NAT may be used to guide adjuvant treatment and compare the efficacy of neoadjuvant regimens. However, current tumor response scoring (TRS) systems suffer from interobserver variability, originating from subjective definitions, the sometimes challenging histology, and response heterogeneity throughout the tumor bed. This study investigates if artificial intelligence-based segmentation of residual tumor burden in histopathology of PDAC after NAT may offer a more objective and reproducible TRS solution.

Abstract

Background: Histologic examination of resected pancreatic cancer after neoadjuvant therapy (NAT) is used to assess the effect of NAT and may guide the choice for adjuvant treatment. However, evaluating residual tumor burden in pancreatic cancer is challenging given tumor response heterogeneity and challenging histomorphology. Artificial intelligence techniques may offer a more reproducible approach. Methods: From 64 patients, one H&E-stained slide of resected pancreatic cancer after NAT was digitized. Three separate classes were manually outlined in each slide (i.e., tumor, normal ducts, and remaining epithelium). Corresponding segmentation masks and patches were generated and distributed over training, validation, and test sets. Modified U-nets with varying encoders were trained, and F1 scores were obtained to express segmentation accuracy. Results: The highest mean segmentation accuracy was obtained using modified U-nets with a DenseNet161 encoder. Tumor tissue was segmented with a high mean F1 score of 0.86, while the overall multiclass average F1 score was 0.82. Conclusions: This study shows that artificial intelligence-based assessment of residual tumor burden is feasible given the promising obtained F1 scores for tumor segmentation. This model could be developed into a tool for the objective evaluation of the response to NAT and may potentially guide the choice for adjuvant treatment.

Dataset for the reporting of carcinoma of the exocrine pancreas: recommendations from the International Collaboration on Cancer Reporting (ICCR)

BACKGROUND AND OBJECTIVES

Current guidelines for the pathology reporting on pancreatic cancer differ in certain aspects, resulting in divergent reporting practice and a lack of comparability of data. Here we report on a new international dataset for the pathology reporting of resection specimens with cancer of the exocrine pancreas (ductal adenocarcinoma and acinar cell carcinoma). The dataset was produced under the auspices of the International Collaboration on Cancer Reporting (ICCR), a global alliance of major (inter-)national pathology and cancer organisations.

METHODS AND RESULTS

According to the ICCR's rigorous process for dataset development, an international expert panel consisting of pancreatic pathologists, a pancreatic surgeon and an oncologist produced a set of core and non-core data items based on a critical review and discussion of current evidence. Commentary was provided for each data item to explain the rationale for selecting it as a core or non-core element, its clinical relevance, and to highlight potential areas of disagreement or lack of evidence, in which case a consensus position was formulated. Following international public consultation, the document was finalised and ratified, and the dataset, which includes a synoptic reporting guide, was published on the ICCR website.

CONCLUSIONS

This first international dataset for cancer of the exocrine pancreas is intended to promote high quality, standardised pathology reporting. Its widespread adoption will improve consistency of reporting, facilitate multidisciplinary communication and enhance comparability of data, all of which will help to improve the management of pancreatic cancer patients.

[Standardized diagnosis of pancreatic head carcinoma]

Most pancreatic ductal adenocarcinomas are localized in the pancreatic head. Due to the complex anatomic relationships with the surrounding organs and vascular structures in the retroperitoneal space and to the presence of numerous transection margins and dissection planes, pancreatic head resections belong to the most complex specimens concerning grossing and sampling for histopathologic analysis.Here we discuss current guidelines for standardized grossing and reporting of pancreatic cancer, with special reference to the assessment of the resection margin status. The importance of standardized reporting for the sake of completeness, comprehensibility, comparability, and quality control as well as for the integration of pathology reports in interdisciplinary digital workflows and artificial intelligence applications will be emphasized.