Response assessment in pancreatic ductal adenocarcinoma: role of imaging

Metabolic responses to the occurrence and chemotherapy of pancreatic cancer: biomarker identification and prognosis prediction

As the most malignant tumor, the prognosis of pancreatic cancer is not ideal even in the small number of patients who can undergo radical surgery. As a highly heterogeneous tumor, chemotherapy resistance is a major factor leading to decreased efficacy and postoperative recurrence of pancreatic cancer. In this study, nuclear magnetic resonance (NMR)-based metabolomics was applied to identify serum metabolic characteristics of pancreatic ductal adenocarcinoma (PDAC) and screen the potential biomarkers for its diagnosis. Metabolic changes of patients with different CA19-9 levels during postoperative chemotherapy were also monitored and compared to identify the differential metabolites that may affect the efficacy of chemotherapy. Finally, 19 potential serum biomarkers were screened to serve the diagnosis of PDAC, and significant metabolic differences between the two CA19-9 stratifications of PDAC were involved in energy metabolism, lipid metabolism, amino acid metabolism, and citric acid metabolism. Enrichment analysis of metabolic pathways revealed six shared pathways by PDAC and chemotherapy such as alanine, aspartate and glutamate metabolism, arginine biosynthesis, glutamine and glutamate metabolism, citrate cycle, pyruvate metabolism, and glycogolysis/gluconeogeneis. The similarity between the metabolic characteristics of PDAC and the metabolic responses to chemotherapy provided a reference for clinical prediction of benefits of postoperative chemotherapy in PDAC patients.

Mitochondrial energy metabolism-related gene signature as a prognostic indicator for pancreatic adenocarcinoma

Background: Pancreatic adenocarcinoma (PAAD) is a highly malignant gastrointestinal tumor and is associated with an unfavorable prognosis worldwide. Considering the effect of mitochondrial metabolism on the prognosis of pancreatic cancer has rarely been investigated, we aimed to establish prognostic gene markers associated with mitochondrial energy metabolism for the prediction of survival probability in patients with PAAD. Methods: Gene expression data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases, and the mitochondrial energy metabolism-related genes were obtained from the GeneCards database. Based on mitochondrial energy metabolism score (MMs), differentially expressed MMRGs were established for MMs-high and MMs-low groups using ssGSEA. After the univariate Cox and least absolute and selection operator (LASSO) analyses, a prognostic MMRG signature was used in the multivariate Cox proportional regression model. Survival and immune cell infiltration analyses were performed. In addition, a nomogram based on the risk model was used to predict the survival probability of patients with PAAD. Finally, the expression of key genes was verified using quantitative polymerase chain reaction and immunohistochemical staining. Intro cell experiments were performed to evaluated the proliferation and invasion of pancreatic cancer cells. Results: A prognostic signature was constructed consisting of two mitochondrial energy metabolism-related genes (MMP11, COL10A1). Calibration and receiver operating characteristic (ROC) curves verified the good predictability performance of the risk model for the survival rate of patients with PAAD. Finally, immune-related analysis explained the differences in immune status between the two subgroups based on the risk model. The high-risk score group showed higher estimate, immune, and stromal scores, expression of eight checkpoint genes, and infiltration of M0 macrophages, which might indicate a beneficial response to immunotherapy. The qPCR results confirmed high expression of MMP11 in pancreatic cancer cell lines, and IHC also verified high expression of MMP11 in clinical pancreatic ductal adenocarcinoma tissues. In vitro cell experiments also demonstrated the role of MMP11 in cell proliferation and invasion. Conclusion: Our study provides a novel two-prognostic gene signature-based on MMRGs-that accurately predicted the survival of patients with PAAD and could be used for mitochondrial energy metabolism-related therapies in the future.

18F-FAPI-04 Outperforms 18F-FDG PET/CT in Clinical Assessments of Patients with Pancreatic Adenocarcinoma

Accurate diagnosis and staging are crucial for selecting treatment for patients with pancreatic ductal adenocarcinoma (PDAC). The desmoplastic responses associated with PDAC are often characterized by hypometabolism. Here, we investigated 18F-fibroblast activation protein inhibitor (FAPI)-04 PET/CT in evaluation of PDAC and compared the findings with those obtained using 18F-FDG. Methods: Sixty-two PDAC patients underwent 18F-FAPI-04 PET/CT and 18F-FDG PET/CT. Identification of primary lesions, lymph node (LN) metastasis, and distant metastasis (DM) by these methods was evaluated, and TNM staging was performed. Correlation between SUVmax of the primary lesion and treatment response was explored in patients who received systemic therapy. Results: 18F-FAPI-04 PET/CT identified all patients with PDAC; 18F-FDG PET/CT missed 1 patient. Tracer uptake was higher in 18F-FAPI-04 PET/CT than in 18F-FDG PET/CT in primary tumors (10.63 vs. 2.87, P < 0.0001), LN metastasis (2.90 vs. 1.43, P < 0.0001), and DM (liver, 6.11 vs. 3.10, P = 0.002; peritoneal, 4.70 vs. 2.08, P = 0.015). The methods showed no significant difference in the T staging category, but the N and M values were significantly higher for 18F-FAPI-04 PET/CT than for 18F-FDG PET/CT (P = 0.002 and 0.008, respectively). Thus, 14 patients were upgraded, and only 1 patient was downgraded, by 18F-FAPI-04 PET/CT compared with 18F-FDG PET/CT. A high SUVmax of the primary tumor did not correlate with treatment response for either 18F-FAPI-04 or 18F-FDG. Conclusion: 18F-FAPI-04 PET/CT performed better than 18F-FDG PET/CT in identification of primary tumors, LN metastasis, and DM and in TNM staging of PDAC.

Exploratory analysis of mesenteric-portal axis CT radiomic features for survival prediction of patients with pancreatic ductal adenocarcinoma

OBJECTIVE

To develop and evaluate task-based radiomic features extracted from the mesenteric-portal axis for prediction of survival and response to neoadjuvant therapy in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

Consecutive patients with PDAC who underwent surgery after neoadjuvant therapy from two academic hospitals between December 2012 and June 2018 were retrospectively included. Two radiologists performed a volumetric segmentation of PDAC and mesenteric-portal axis (MPA) using a segmentation software on CT scans before (CTtp0) and after (CTtp1) neoadjuvant therapy. Segmentation masks were resampled into uniform 0.625-mm voxels to develop task-based morphologic features (n = 57). These features aimed to assess MPA shape, MPA narrowing, changes in shape and diameter between CTtp0 and CTtp1, and length of MPA segment affected by the tumor. A Kaplan-Meier curve was generated to estimate the survival function. To identify reliable radiomic features associated with survival, a Cox proportional hazards model was used. Features with an ICC  ≥ 0.80 were used as candidate variables, with clinical features included a priori.

RESULTS

In total, 107 patients (60 men) were included. The median survival time was 895 days (95% CI: 717, 1061). Three task-based shape radiomic features (Eccentricity mean tp0, Area minimum value tp1, and Ratio 2 minor tp1) were selected. The model showed an integrated AUC of 0.72 for prediction of survival. The hazard ratio for the Area minimum value tp1 feature was 1.78 (p = 0.02) and 0.48 for the Ratio 2 minor tp1 feature (p = 0.002).

CONCLUSION

Preliminary results suggest that task-based shape radiomic features can predict survival in PDAC patients.

KEY POINTS

• In a retrospective study of 107 patients who underwent neoadjuvant therapy followed by surgery for PDAC, task-based shape radiomic features were extracted and analyzed from the mesenteric-portal axis. • A Cox proportional hazards model that included three selected radiomic features plus clinical information showed an integrated AUC of 0.72 for prediction of survival, and a better fit compared to the model with only clinical information.

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.

The role of the multidisciplinary tumor board (MDTB) in the assessment of pancreatic cancer diagnosis and resectability: A tertiary referral center experience

Background

The introduction of multidisciplinary tumor boards (MDTBs) for the diagnostic and therapeutic pathway of several oncological disease significantly ameliorated patients' outcomes. However, only few evidences are currently present on the potential impact of the MDTB on pancreatic cancer (PC) management. Aim of this study is to report how MDTB may influence PC diagnosis and treatment, with particular focus on PC resectability assessment and the correspondence between MDTB definition of resectability and intraoperative findings.

Methods

All patients with a proven or suspected diagnosis of PC discussed at the MDTB between 2018 and 2020 were included in the study. An evaluation of diagnosis, tumor response to oncological/radiation therapy and resectability before and after the MDTB was conducted. Moreover, a comparison between the MDTB resectability assessment and the intraoperative findings was performed.

Results

A total of 487 cases were included in the analysis: 228 (46.8%) for diagnosis evaluation, 75 (15.4%) for tumor response assessment after/during medical treatment, 184 (37.8%) for PC resectability assessment. As a whole, MDTB led to a change in treatment management in 89 cases (18.3%): 31/228 (13.6%) in the diagnosis group, 13/75 (17.3%) in the assessment of treatment response cohort and 45/184 (24.4%) in the PC resectability evaluation group. As a whole, 129 patients were given indication to surgery. Surgical resection was accomplished in 121 patients (93.7%), with a concordance rate of resectability between MDTB discussion and intraoperative findings of 91.5%. Concordance rate was 99% for resectable lesions and 64.3% for borderline PCs.

Conclusions

MDTB discussion consistently influences PC management, with significant variations in terms of diagnosis, tumor response assessment and resectability. In this last regard, MDTB discussion plays a key role, as demonstrated by the high concordance rate between MDTB resectability definition and intraoperative findings.

Differentiation between Pancreatic Ductal Adenocarcinoma and Normal Pancreatic Tissue for Treatment Response Assessment using Multi-Scale Texture Analysis of CT Images

Background

Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent type of pancreas cancer with a high mortality rate and its staging is highly dependent on the extent of involvement between the tumor and surrounding vessels, facilitating treatment response assessment in PDAC.

Objective

This study aims at detecting and visualizing the tumor region and the surrounding vessels in PDAC CT scan since, despite the tumors in other abdominal organs, clear detection of PDAC is highly difficult.

Material and Methods

This retrospective study consists of three stages: 1) a patch-based algorithm for differentiation between tumor region and healthy tissue using multi-scale texture analysis along with L1-SVM (Support Vector Machine) classifier, 2) a voting-based approach, developed on a standard logistic function, to mitigate false detections, and 3) 3D visualization of the tumor and the surrounding vessels using ITK-SNAP software.

Results

The results demonstrate that multi-scale texture analysis strikes a balance between recall and precision in tumor and healthy tissue differentiation with an overall accuracy of 0.78±0.12 and a sensitivity of 0.90±0.09 in PDAC.

Conclusion

Multi-scale texture analysis using statistical and wavelet-based features along with L1-SVM can be employed to differentiate between healthy and pancreatic tissues. Besides, 3D visualization of the tumor region and surrounding vessels can facilitate the assessment of treatment response in PDAC. However, the 3D visualization software must be further developed for integrating with clinical applications.

Metabolomic analyses redefine the biological classification of pancreatic cancer and correlate with clinical outcomes

Pancreatic ductal adenocarcinoma (PDAC) is characterized by high heterogeneity, and the postoperative prognosis of different patients often varies greatly. Therefore, the classification of pancreatic cancer patients and precise treatment becomes particularly important. In our study, 1 H NMR spectroscopy was used to analyze the 76 PDAC serum samples and identify the potential metabolic subtypes. The metabolic characteristics of each metabolic subtype were screened out and the relationship between metabolic subtype and the long-term prognosis was further identified. The clinical stages of PDAC did not show the metabolic differences at the serum metabolomic level. And three metabolic subtypes, basic, choline-like and amino acid-enriched types, were defined by the hierarchical cluster analysis of the serum metabolites and the disturbed metabolic pathways. The characteristic metabolites of each PDAC subtype were identified, and the metabolite model was established to distinguish the PDAC patients in the different subtypes. Among the three metabolic subtypes, choline-like type displayed better long-term prognosis compared to the other two types of patients. Metabolic subtypes are of clinical importance and are closer to expressing the heterogeneity in the actual life activities of pancreatic cancer than molecular typing. The excavation of metabolic subtypes based on this will be more in line with clinical reality and more promising to guide clinical precision individualization treatment.

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.

Retrospective Evaluation of Treatment Response in Patients with Nonmetastatic Pancreatic Cancer Using CT and CA 19-9

Background Imaging studies have limitations in evaluating pancreatic ductal adenocarcinoma (PDAC) treatment response. Purpose To investigate the effectiveness of combined CT and carbohydrate antigen 19-9 (CA 19-9) evaluation at 8 weeks after first-line treatment to predict overall survival (OS) of patients with nonmetastatic PDAC. Materials and Methods Patients with nonmetastatic PDAC who received first-line treatment with either chemotherapy or concurrent chemoradiation in a single-center PDAC cohort registry were retrospectively enrolled in the study between January 2013 and December 2016. Follow-up CT images obtained 8 weeks after treatment were evaluated according to Response Evaluation Criteria in Solid Tumors. Patients with partial response (PR) or stable disease (SD) were defined as CT responders, and those with progressive disease (PD) were defined as CT nonresponders. Patients with a normalized CA 19-9 level at 8-week follow-up were defined as CA 19-9 responders, and those with a nonnormalized or nonelevated CA 19-9 level were defined as CA 19-9 nonresponders. OS was compared using the Kaplan-Meier method with Breslow analysis. Results A total of 197 patients (mean age ± standard deviation, 65 years ± 10; 107 men) were evaluated. Patients with PD (n = 17) showed shorter OS than those with SD (n = 147; P < .001) or PR (n = 33; P = .003). OS did not differ between the patients with PR and those with SD (P = .60). When the CT and CA 19-9 responses were integrated, OS was longest in CT and CA 19-9 responders (group 1, n = 27; median OS, 26.6 months [95% CI: 9.0, 44.1]), followed by CT responders but CA 19-9 nonresponders (group 2, n = 153; median OS, 15.9 months [95% CI: 13.3, 18.5]; P = .007 vs group 1) and CT and CA 19-9 nonresponders (group 3, n = 17; median OS, 6.5 months [95% CI: 0.8, 12.2]; P < .001 vs group 2). Conclusion Integrated evaluation with CT and carbohydrate antigen 19-9 response allowed more accurate stratification of survival in patients with pancreatic ductal adenocarcinoma in the early treatment period than did evaluation according to Response Evaluation Criteria in Solid Tumors. © RSNA, 2022 Online supplemental material is available for this article.

Application of Magnetic Resonance Imaging in Neoadjuvant Treatment of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignant tumors of the human digestive system. Due to its insidious onset, many patients have already lost the opportunity for radical resection upon tumor diagnosis. In recent years, neoadjuvant treatment for patients with borderline resectable PDAC has been recommended by multiple guidelines to increase the resection rate of radical surgery and improve the postoperative survival. However, further developments are required to accurately assess the tumor response to neoadjuvant therapy and to select the population suitable for such treatment. Reductions in drug toxicity and the number of neoadjuvant cycles are also critical. At present, the clinical evaluation of neoadjuvant treatment is mainly based on several serological and imaging indicators; however, the unique characteristics of PDAC and the insufficient sensitivity and specificity of the markers render this system ineffective. The imaging evaluation system, magnetic resonance imaging (MRI), has its own unique imaging advantages compared with computed tomography (CT) and other imaging examinations. One key advantage is the ability to reflect the changes more rapidly in tumor tissue components, such as the degree of fibrosis, microvessel density, and tissue hypoxia. It can also perform multiparameter quantitative analysis of tumor tissue and changes, attributing to its increasingly important role in imaging evaluation, and potentially the evaluation of neoadjuvant treatment of pancreatic cancer, as several current articles have studied. At the same time, owing to the complexity of MRI and some of its limitations, its wider application is limited. Compared with CT imaging, few relevant studies have been conducted. In this review article, we will investigate and summarize the advantages, limitations, and future development of MRI in the evaluation of neoadjuvant treatment of PDAC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Emerging Role for 7T MRI and Metabolic Imaging for Pancreatic and Liver Cancer

Advances in magnet technologies have led to next generation 7T magnetic resonance scanners which can fit in the footprint and price point of conventional hospital scanners (1.5−3T). It is therefore worth asking if there is a role for 7T magnetic resonance imaging and spectroscopy for the treatment of solid tumor cancers. Herein, we survey the medical literature to evaluate the unmet clinical needs for patients with pancreatic and hepatic cancer, and the potential of ultra-high field proton imaging and phosphorus spectroscopy to fulfil those needs. We draw on clinical literature, preclinical data, nuclear magnetic resonance spectroscopic data of human derived samples, and the efforts to date with 7T imaging and phosphorus spectroscopy. At 7T, the imaging capabilities approach histological resolution. The spectral and spatial resolution enhancements at high field for phospholipid spectroscopy have the potential to reduce the number of exploratory surgeries due to tumor boundaries undefined at conventional field strengths. Phosphorus metabolic imaging at 7T magnetic field strength, is already a mainstay in preclinical models for molecular phenotyping, energetic status evaluation, dosimetry, and assessing treatment response for both pancreatic and liver cancers. Metabolic imaging of primary tumors and lymph nodes may provide powerful metrics to aid staging and treatment response. As tumor tissues contain extreme levels of phospholipid metabolites compared to the background signal, even spectroscopic volumes containing less than 50% tumor can be detected and/or monitored. Phosphorus spectroscopy allows non-invasive pH measurements, indicating hypoxia, as a predictor of patients likely to recur. We conclude that 7T multiparametric approaches that include metabolic imaging with phosphorus spectroscopy have the potential to meet the unmet needs of non-invasive location-specific treatment monitoring, lymph node staging, and the reduction in unnecessary surgeries for patients undergoing resections for pancreatic cancer. There is also potential for the use of 7T phosphorous spectra for the phenotyping of tumor subtypes and even early diagnosis (<2 mL). Whether or not 7T can be used for all patients within the next decade, the technology is likely to speed up the translation of new therapeutics.

Segmentation of pancreatic ductal adenocarcinoma (PDAC) and surrounding vessels in CT images using deep convolutional neural networks and texture descriptors

Fully automated and volumetric segmentation of critical tumors may play a crucial role in diagnosis and surgical planning. One of the most challenging tumor segmentation tasks is localization of pancreatic ductal adenocarcinoma (PDAC). Exclusive application of conventional methods does not appear promising. Deep learning approaches has achieved great success in the computer aided diagnosis, especially in biomedical image segmentation. This paper introduces a framework based on convolutional neural network (CNN) for segmentation of PDAC mass and surrounding vessels in CT images by incorporating powerful classic features, as well. First, a 3D-CNN architecture is used to localize the pancreas region from the whole CT volume using 3D Local Binary Pattern (LBP) map of the original image. Segmentation of PDAC mass is subsequently performed using 2D attention U-Net and Texture Attention U-Net (TAU-Net). TAU-Net is introduced by fusion of dense Scale-Invariant Feature Transform (SIFT) and LBP descriptors into the attention U-Net. An ensemble model is then used to cumulate the advantages of both networks using a 3D-CNN. In addition, to reduce the effects of imbalanced data, a multi-objective loss function is proposed as a weighted combination of three classic losses including Generalized Dice Loss (GDL), Weighted Pixel-Wise Cross Entropy loss (WPCE) and boundary loss. Due to insufficient sample size for vessel segmentation, we used the above-mentioned pre-trained networks and fine-tuned them. Experimental results show that the proposed method improves the Dice score for PDAC mass segmentation in portal-venous phase by 7.52% compared to state-of-the-art methods in term of DSC. Besides, three dimensional visualization of the tumor and surrounding vessels can facilitate the evaluation of PDAC treatment response.

Overview and Future Perspectives on Tumor-Targeted Positron Emission Tomography and Fluorescence Imaging of Pancreatic Cancer in the Era of Neoadjuvant Therapy

BACKGROUND

Despite recent advances in the multimodal treatment of pancreatic ductal adenocarcinoma (PDAC), overall survival remains poor with a 5-year cumulative survival of approximately 10%. Neoadjuvant (chemo- and/or radio-) therapy is increasingly incorporated in treatment strategies for patients with (borderline) resectable and locally advanced disease. Neoadjuvant therapy aims to improve radical resection rates by reducing tumor mass and (partial) encasement of important vascular structures, as well as eradicating occult micrometastases. Results from recent multicenter clinical trials evaluating this approach demonstrate prolonged survival and increased complete surgical resection rates (R0). Currently, tumor response to neoadjuvant therapy is monitored using computed tomography (CT) following the RECIST 1.1 criteria. Accurate assessment of neoadjuvant treatment response and tumor resectability is considered a major challenge, as current conventional imaging modalities provide limited accuracy and specificity for discrimination between necrosis, fibrosis, and remaining vital tumor tissue. As a consequence, resections with tumor-positive margins and subsequent early locoregional tumor recurrences are observed in a substantial number of patients following surgical resection with curative intent. Of these patients, up to 80% are diagnosed with recurrent disease after a median disease-free interval of merely 8 months. These numbers underline the urgent need to improve imaging modalities for more accurate assessment of therapy response and subsequent re-staging of disease, thereby aiming to optimize individual patient's treatment strategy. In cases of curative intent resection, additional intra-operative real-time guidance could aid surgeons during complex procedures and potentially reduce the rate of incomplete resections and early (locoregional) tumor recurrences. In recent years intraoperative imaging in cancer has made a shift towards tumor-specific molecular targeting. Several important molecular targets have been identified that show overexpression in PDAC, for example: CA19.9, CEA, EGFR, VEGFR/VEGF-A, uPA/uPAR, and various integrins. Tumor-targeted PET/CT combined with intraoperative fluorescence imaging, could provide valuable information for tumor detection and staging, therapy response evaluation with re-staging of disease and intraoperative guidance during surgical resection of PDAC.

METHODS

A literature search in the PubMed database and (inter)national trial registers was conducted, focusing on studies published over the last 15 years. Data and information of eligible articles regarding PET/CT as well as fluorescence imaging in PDAC were reviewed. Areas covered: This review covers the current strategies, obstacles, challenges, and developments in targeted tumor imaging, focusing on the feasibility and value of PET/CT and fluorescence imaging for integration in the work-up and treatment of PDAC. An overview is given of identified targets and their characteristics, as well as the available literature of conducted and ongoing clinical and preclinical trials evaluating PDAC-targeted nuclear and fluorescent tracers.

The Association of Real-World CA 19-9 Level Monitoring Patterns and Clinical Outcomes Among Patients With Metastatic Pancreatic Ductal Adenocarcinoma

Background

Pancreatic cancer is expected to be the third deadliest cancer in the US in 2021. Evaluation of treatment response in patients with mPDAC necessitates scheduled clinical and radiographic assessments along with monitoring serum CA 19-9 levels. Currently available single-institution data examining the importance of CA 19-9 monitoring cannot be generalized to real-world settings. We investigated the impact of serum CA 19-9 monitoring and its association with clinical outcomes in patients with mPDAC in a population-based setting.

Methods

Data were extracted from the Flatiron Health electronic health record (EHR)-derived de-identified database for patients diagnosed with mPDAC between January 1, 2015, and June 30, 2020. Serum CA 19-9 levels at baseline – defined as the values obtained ≤ 60 days prior to treatment initiation - and during treatment were extracted. CA 19-9 levels > 40 IU/mL were considered elevated. Survival outcomes were compared based on testing frequency, baseline CA 19-9 levels, and change in CA 19-9.

Results

6,118 patients with mPDAC who received treatment were included in the analysis. The median age at diagnosis was 68 years (IQR: 61-75). Patients with normal baseline CA 19-9 experienced longer median survival than patients with elevated levels [1L: 8.8 months (95% CI: 7.9 - 10) vs. 7.2 months (6.8 – 7.5), p < 0.001; 2L: 7.2 months (6.1 – 9.2) vs. 5.2 months (4.9 – 5.6), p < 0.001; 3L: 6.1 months (5.4 – 9.1) vs. 3.9 months (3.4 – 4.3), p < 0.001]. Patients with decreasing/stable CA 19-9 during treatment experienced longer survival than patients who experienced an increase in CA 19-9 levels [1L: 10.9 months (10.5 – 11.3) vs. 5.4 months (5.1 – 5.9), p < 0.0001; 2L: 8.2 months (7.7 – 8.5) vs. 4.3 months (4.1 – 4.7), p < 0.001; 3L: 7.5 months (6.6 – 9.2) vs. 3.7 months (3.4 – 4.3), p < 0.001].

Conclusions

In one of the largest, contemporary, real-world studies of patients with mPDAC, elevated CA 19-9 level at treatment initiation demonstrated a prognostic impact. Routine serial monitoring of CA 19-9 levels during treatment may be warranted, in addition to clinical and radiographic assessment, and may translate into better patient outcomes. Further validation studies are needed to understand the generalizability of these results.

Role of 3D Volumetric and Perfusion Imaging for Detecting Early Changes in Pancreatic Adenocarcinoma

Purpose

There is a major shortage of reliable early detection methods for pancreatic cancer in high-risk groups. The focus of this preliminary study was to use Time Intensity-Density Curve (TIDC) and Marley Equation analyses, in conjunction with 3D volumetric and perfusion imaging to demonstrate their potential as imaging biomarkers to assist in the early detection of Pancreatic Ductal Adenocarcinoma (PDAC).

Experimental Designs

A quantitative retrospective and prospective study was done by analyzing multi-phase Computed Tomography (CT) images of 28 patients undergoing treatment at different stages of pancreatic adenocarcinoma using advanced 3D imaging software to identify the perfusion and radio density of tumors.

Results

TIDC and the Marley Equation proved useful in quantifying tumor aggressiveness. Perfusion delays in the venous phase can be linked to Vascular Endothelial Growth Factor (VEGF)-related activity which represents the active part of the tumor. 3D volume analysis of the multiphase CT scan of the patient showed clear changes in arterial and venous perfusion indicating the aggressive state of the tumor.

Conclusion

TIDC and 3D volumetric analysis can play a significant role in defining the response of the tumor to treatment and identifying early-stage aggressiveness.

The impact of the multidisciplinary tumor board (MDTB) on the management of pancreatic diseases in a tertiary referral center

BACKGROUND

The implementation of multidisciplinary tumor board (MDTB) meetings significantly ameliorated the management of oncological diseases. However, few evidences are currently present on their impact on pancreatic cancer (PC) management. The aim of this study was to evaluate the impact of the MDTB on PC diagnosis, resectability and tumor response to oncological treatment compared with indications before discussion.

PATIENTS AND METHODS

All patients with a suspected or proven diagnosis of PC presented at the MDTB from 2017 to 2019 were included in the study. Changes of diagnosis, resectability and tumor response to oncological/radiation treatment between pre- and post-MDTB discussion were analyzed.

RESULTS

A total of 438 cases were included in the study: 249 (56.8%) were presented as new diagnoses, 148 (33.8%) for resectability assessment and 41 (9.4%) for tumor response evaluation to oncological treatment. MDTB discussion led to a change in diagnosis in 54/249 cases (21.7%), with a consequent treatment strategy variation in 36 cases (14.5%). Change in resectability was documented in 44/148 cases (29.7%), with the highest discrepancy for borderline lesions. The treatment strategy was thus modified in 27 patients (18.2%). The MDTB brought a modification in the tumor response assessment in 6/41 cases (14.6%), with a consequent protocol modification in four (9.8%) cases.

CONCLUSIONS

MDTB discussion significantly impacts on PC management, especially in high-volume centers, with consistent variations in terms of diagnosis, resectability and tumor response assessment compared with indications before discussion.

The Role of Imaging in Current Treatment Strategies for Pancreatic Adenocarcinoma

In pancreatic cancer, imaging plays an essential role in surveillance, diagnosis, resectability evaluation, and treatment response evaluation. Pancreatic cancer surveillance in high-risk individuals has been attempted using endoscopic ultrasound (EUS) or magnetic resonance imaging (MRI). Imaging diagnosis and resectability evaluation are the most important factors influencing treatment decisions, where computed tomography (CT) is the preferred modality. EUS, MRI, and positron emission tomography play a complementary role to CT. Treatment response evaluation is of increasing clinical importance, especially in patients undergoing neoadjuvant therapy. This review aimed to comprehensively review the role of imaging in relation to the current treatment strategy for pancreatic cancer, including surveillance, diagnosis, evaluation of resectability and treatment response, and prediction of prognosis.

Bacterial lipopolysaccharide as negative predictor of gemcitabine efficacy in advanced pancreatic cancer - translational results from the AIO-PK0104 Phase 3 study

Background

Gram-negative bacteria mediated gemcitabine resistance in pre-clinical models. We determined if intratumoural lipopolysaccharide (LPS) detection by immunohistochemistry is associated with outcome in advanced pancreatic ductal adenocarcinoma (PDAC) treated with gemcitabine and non-gemcitabine containing 1st-line chemotherapy.

Methods

We examined LPS on tumour tissue from 130 patients treated within the randomised AIO-PK0104 trial and a validation cohort (n = 113) and analysed the association of LPS detection to patient outcome according to treatment subgroups.

Results

In 24% of samples from the AIO-PK0104 study LPS was detected; in LPS-positive patients median OS was 4.4 months, compared to 7.3 months with LPS negative tumours (HR 1.732, p = 0.010). A difference in OS was detected in 1st-line gemcitabine-treated patients (n = 71; HR 2.377, p = 0.002), but not in the non-gemcitabine treatment subgroup (n = 59; HR 1.275, p = 0.478). Within the validation cohort, the LPS positivity rate was 23%, and LPS detection was correlated with impaired OS in the gemcitabine subgroup (n = 94; HR 1.993, p = 0.008) whereas no difference in OS was observed in the non-gemcitabine subgroup (n = 19; HR 2.596, p = 0.219).

Conclusions

The detection of intratumoural LPS as surrogate marker for gram-negative bacterial colonisation may serve as a negative predictor for gemcitabine efficacy in advanced PDAC.

Clinical trial registry

The Clinical trial registry identifier is NCT00440167.

Multiparametric MRI for prediction of treatment response to neoadjuvant FOLFIRINOX therapy in borderline resectable or locally advanced pancreatic cancer

OBJECTIVES

To identify multiparametric MRI biomarkers to predict the tumor response to neoadjuvant FOLFIRINOX therapy in patients with borderline resectable (BR) or locally advanced (LA) pancreatic ductal adenocarcinoma (PDAC).

METHODS

From May 2016 to March 2018, adult patients with BR or LA PDAC were prospectively enrolled in this study. They received eight cycles of FOLFIRINOX therapy and underwent multiparametric MRI twice (at baseline and after the second cycle). MRI evaluations included dynamic contrast-enhanced MRI, intravoxel incoherent motion diffusion-weighted imaging, and assessment of T2* relaxivity (R2*) and the change in T1 relaxivity (ΔR1, equilibrium phase R1 minus non-enhanced R1) of the tumors. Factors to predict the responders determined by the best overall response during FOLFIRINOX therapy and those to predict progression-free survival (PFS) and overall survival (OS) were evaluated using multivariable logistic regression and the Cox proportional hazard model.

RESULTS

Forty-one patients (mean age, 60.3 years ± 9.3; 24 men) were included. Among the clinical and MRI factors, the baseline ΔR1 (adjusted odds ratio, 31.07; p = 0.008) was the only independent predictor for tumor response. The baseline ΔR1 was also an independent predictor for PFS (adjusted hazard ratio, 0.40; p = 0.033) along with R0 resection. The use of a cutoff ΔR1 value of ≥ 1.31 s^-1 enabled prognostic stratification (median PFS, 16.0 months vs.10.0 months; p = 0.029; median OS, 34.9 months vs. 16.6 months; p = 0 .023, respectively).

CONCLUSIONS

The baseline tumor ΔR1 value may be useful to predict tumor response and survival in patients with BR or LA PDAC receiving FOLFIRINOX neoadjuvant therapy.

KEY POINTS

• Baseline ΔR1 was an independent predictor for tumor response (adjusted odds ratio, 31.07; p = 0.008) and progression-free survival (adjusted hazard ratio, 0.40; p = 0.033) in patients with borderline resectable or locally advanced pancreatic ductal adenocarcinoma receiving neoadjuvant FOLFIRINOX therapy. • The criterion of baseline ΔR1 value ≥ 1.31 s^-1 allowed for the prediction of favorable tumor response and survival outcome after neoadjuvant FOLFIRINOX therapy.

Fibrotic Response to Neoadjuvant Therapy Predicts Survival in Pancreatic Cancer and Is Measurable with Collagen-Targeted Molecular MRI

PURPOSE

To evaluate the prognostic value of posttreatment fibrosis in human PDAC patients, and to compare a type I collagen targeted MRI probe, CM-101, to the standard contrast agent, Gd-DOTA, for their abilities to identify FOLFIRINOX-induced fibrosis in a murine model of PDAC.

EXPERIMENTAL DESIGN

Ninety-three chemoradiation-treated human PDAC samples were stained for fibrosis and outcomes evaluated. For imaging, C57BL/6 and FVB mice were orthotopically implanted with PDAC cells and FOLFIRINOX was administered. Mice were imaged with Gd-DOTA and CM-101.

RESULTS

In humans, post-chemoradiation PDAC tumor fibrosis was associated with longer overall survival (OS) and disease-free survival (DFS) on multivariable analysis (OS P = 0.028, DFS P = 0.047). CPA increased the prognostic accuracy of a multivariable logistic regression model comprised of previously established PDAC risk factors [AUC CPA (-) = 0.76, AUC CPA (+) = 0.82]. In multiple murine orthotopic PDAC models, FOLFIRINOX therapy reduced tumor weight (P < 0.05) and increased tumor fibrosis by collagen staining (P < 0.05). CM-101 MR signal was significantly increased in fibrotic tumor regions. CM-101 signal retention was also increased in the more fibrotic FOLFIRINOX-treated tumors compared with untreated controls (P = 0.027), consistent with selective probe binding to collagen. No treatment-related differences were observed with Gd-DOTA imaging.

CONCLUSIONS

In humans, post-chemoradiation tumor fibrosis is associated with OS and DFS. In mice, our MR findings indicate that translation of collagen molecular MRI with CM-101 to humans might provide a novel imaging technique to monitor fibrotic response to therapy to assist with prognostication and disease management.

Elastography of pancreatic ductal adenocarcinoma following EUS-guided radiofrequency ablation (with video)

Patients presenting with pancreatic ductal adenocarcinoma in an advanced inoperable stage receive chemoradiotherapy. Endoscopic ultrasound guided radiofrequency ablation (EUS-RFA) has been proposed as a new therapeutic option for these patients alongside chemotherapy. The evaluation of treatment response is mainly based on radiological evaluation of the changes in tumour size. Unfortunately, the currently available radiological methods cannot clearly differentiate between necrotic tissue and viable tumour. EUS elastography is an ultrasound technique that can grade the hardness of a lesion and classify it as benign, inflammatory or neoplastic as previously reported. This case report of 2 patients shows that using EUS elastography is beneficial in characterizing the nature of the changes occurring to the tumour mass following EUS-RFA of pancreatic tumour.

Imaging diagnosis and staging of pancreatic ductal adenocarcinoma: a comprehensive review

Pancreatic ductal adenocarcinoma (PDAC) has continued to have a poor prognosis for the last few decades in spite of recent advances in different imaging modalities mainly due to difficulty in early diagnosis and aggressive biological behavior. Early PDAC can be missed on CT due to similar attenuation relative to the normal pancreas, small size, or hidden location in the uncinate process. Tumor resectability and its contingency on the vascular invasion most commonly assessed with multi-phasic thin-slice CT is a continuously changing concept, particularly in the era of frequent neoadjuvant therapy. Coexistent celiac artery stenosis may affect the surgical plan in patients undergoing pancreaticoduodenectomy. In this review, we discuss the challenges related to the imaging of PDAC. These include radiological and clinical subtleties of the tumor, evolving imaging criteria for tumor resectability, preoperative diagnosis of accompanying celiac artery stenosis, and post-neoadjuvant therapy imaging. For each category, the key imaging features and potential pitfalls on cross-sectional imaging will be discussed. Also, we will describe the imaging discriminators of potential mimickers of PDAC.

White paper on pancreatic ductal adenocarcinoma from society of abdominal radiology's disease-focused panel for pancreatic ductal adenocarcinoma: Part II, update on imaging techniques and screening of pancreatic cancer in high-risk individuals

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive gastrointestinal malignancy with a poor 5-year survival rate. Its high mortality rate is attributed to its aggressive biology and frequently late presentation. While surgical resection remains the only potentially curative treatment, only 10-20% of patients will present with surgically resectable disease. Over the past several years, development of vascular bypass graft techniques and introduction of neoadjuvant treatment regimens have increased the number of patients who can undergo resection with a curative intent. While the role of conventional imaging in the detection, characterization, and staging of patients with PDAC is well established, its role in monitoring treatment response, particularly following neoadjuvant therapy remains challenging because of the complex anatomic and histological nature of PDAC. Novel morphologic and functional imaging techniques (such as DECT, DW-MRI, and PET/MRI) are being investigated to improve the diagnostic accuracy and the ability to measure response to therapy. There is also a growing interest to detect PDAC and its precursor lesions at an early stage in asymptomatic patients to increase the likelihood of achieving cure. This has led to the development of pancreatic cancer screening programs. This article will review recent updates in imaging techniques and the current status of screening and surveillance of individuals at a high risk of developing PDAC.

Clinical application of dynamic contrast enhanced ultrasound in monitoring the treatment response of chemoradiotherapy of pancreatic ductal adenocarcinoma

OBJECTIVES

To investigate the value of dynamic contrast enhanced ultrasound (D-CEUS) in monitoring the chemoradiotherapy (CRT) therapeutic response of local advanced pancreatic ductal adenocarcinoma (LAPC).

PATIENTS AND METHODS

From October 2017 to December 2018, 11 patients diagnosed as LAPC were included (7 men, 4 women; mean age: 61.1±8.6 years). The algorithm of CRT was as following: the radiotherapy dose was 50.4 Gy/28Fx with S-1 40 mg bid orally taken in radiotherapy day. Conventional ultrasound scan and CEUS were performed before and 4 weeks after CRT. All ultrasound examinations were performed by an ACUSON Oxana 2 ultrasound equipment (Siemens Medical Solutions, Germany) with a C 6-1 convex array transducer (1-6 MHz). Time intensity curves (TICs) were generated in the region of interests (ROIs) both in LAPC lesions and in its surrounding pancreas parenchyma by SonoLiver software (TOMTEC Imaging Systems). Quantitative perfusion parameters including maximum intensity (MI), rise time (RT), mean transit time (mTT) and time to peak (TTP) were analyzed and compared before and after CRT.

RESULTS

No significant difference could be found by conventional B mode ultrasound scan after CRT. TICs of CEUS showed lower ascending and descending slopes rate after CRT. Among all perfusion quantitative parameters, MI decreased significantly after CRT (42.1±18.8% vs 27.8±17.2%, P < 0.05).

CONCLUSIONS

Depending on its unique advantages as non-radiation, effective and convenient, D-CEUS analysis and quantitative parameters, particularly MI, has potential application value in following up of the CRT treatment response in LAPC patients.

PDS5B regulates cell proliferation and motility via upregulation of Ptch2 in pancreatic cancer cells

Pds5b (precocious dissociation of sisters 5B) is involved in both tumorigenesis and cancer progression; however, the functions and molecular mechanisms of Pds5b in pancreatic cancer (PC) are unknown. Several approaches were conducted to investigate the molecular basis of Pds5b-related PC progression, including transfection, MTT, FACS, western blotting, wound healing assay, transwell chamber invasion assay, and immunohistochemical methods. Pds5b overexpression inhibited cell growth and induced apoptosis, whereas the inhibition of Pds5b promoted growth of PC cells. Moreover, Pds5b overexpression inhibited cell migration and invasion, while the downregulation of Pds5b enhanced cell motility. Furthermore, reduced Pds5b expression was associated with survival in PC patients. Mechanistically, Pds5b positively regulated the expression of Ptch2 to influence the Sonic hedgehog signaling pathway. Consistently, Ptch2 downregulation enhanced cell growth, migration, and invasion, while inhibiting cell apoptosis. Notably, the downregulation of Ptch2 abolished Pds5b-mediated anti-tumor activity in PC cells. Strikingly, Pds5b expression was positively associated with levels of Ptch2 in PC patient samples, suggesting that the Pds5b/Ptch2 axis regulates cell proliferation and invasion in PC cells. Our findings indicate that targeting Pds5b and Ptch2 may represent a novel therapeutic approach for PC.

Analyzing the post-contrast attenuation of the esophageal wall on routine contrast-enhanced MDCT examination can improve the diagnostic accuracy in response evaluation of the squamous cell esophageal carcinoma to neoadjuvant chemoradiotherapy in comparison with the esophageal wall thickness

PURPOSE

To evaluate the accuracy of the multidetector computed tomography (MDCT) in the response evaluation of the esophageal squamous cell carcinoma (ESCC) to neoadjuvant chemoradiotherapy (nCRT) by analyzing the thickness and post-contrast attenuation of the esophageal wall after the nCRT.

METHODS

Contrast-enhanced (CE)-MDCT examinations in portal venous phase of one hundred patients with locally advanced ESCC who received nCRT and underwent esophageal resection and histopathology assessment of tumor regression grade (TRG) were retrospectively analyzed by measuring the maximal thickness and mean density of the esophageal wall in the segment involved by tumor and visually searching for hyperdense foci within it. Diagnostic performance was evaluated using the ROC analysis.

RESULTS

Average attenuation of the esophageal wall had stronger diagnostic performance for predicting pathologic complete regression (pCR) (AUC = 0.994; p < 0.001) in relation to maximal esophageal wall thickness (AUC = 0.731; p < 0.001). Maximal esophageal wall thickness ≤ 9 mm and average attenuation of the esophageal wall ≤ 64 HU predicted pCR with the sensitivity, specificity, and overall accuracy of 62.5%, 77.9%, and 73%, and 96.9%, 98.5%, and 98%, respectively. Combination of both cutoff values enabled correct assessment of pCR with the 100% accuracy. Visual detection of the hyperdense focus within the esophageal wall predicted pCR with the sensitivity, specificity, and overall accuracy values of 100%, 94.1%, and 96%, respectively.

CONCLUSION

Visual analysis and measurement of post-contrast attenuation of the esophageal wall after the nCRT can improve diagnostic accuracy of MDCT in the response evaluation of the ESCC to nCRT in comparison with measuring the esophageal wall thickness.

MRI evaluation of pancreatic ductal adenocarcinoma: diagnosis, mimics, and staging

The radiologist's role in the evaluation of pancreatic ductal adenocarcinoma remains critical in the management of this deadly disease. Imaging plays a vital role in the diagnosis and staging of pancreatic cancer. Although CT is more commonly used for staging pancreatic cancer, MR is increasingly playing an important role in this regard. In our institution, all pancreatic malignancies undergo staging with MRI. In this pictoral essay, we illustrate the MR imaging features of pancreatic ductal adenocarcinoma and its mimics, and we also discuss pearls and pitfalls in MR staging of pancreatic carcinoma.