Pancreatic Cancer CT: Prediction of Resectability according to NCCN Criteria

Comparison of the different versions of NCCN guidelines for predicting margin-negative resection of pancreatic cancer in patients undergoing upfront surgery

OBJECTIVES

The purpose of this study was to compare the different versions of the National Comprehensive Cancer Network (NCCN) guidelines for defining resectability of pancreatic ductal adenocarcinoma (PDAC) in predicting margin-negative (R0) resection, and to assess inter-reader agreement.

METHODS

This retrospective study included 283 patients (mean age, 65.1 years ± 9.4 [SD]; 155 men) who underwent upfront pancreatectomy for PDAC between 2017 and 2019. Two radiologists independently determined the resectability on preoperative CT according to the 2017, 2019, and 2020 NCCN guidelines. The sensitivity and specificity for R0 resection were analyzed using a multivariable logistic regression analysis with generalized estimating equations. Inter-reader agreement was assessed using kappa statistics.

RESULTS

R0 resection was accomplished in 239 patients (84.5%). The sensitivity and specificity averaged across two readers were, respectively, 76.6% and 29.5% for the 2020 guidelines, 74.1% and 32.9% for the 2019 guidelines, and 72.6% and 34.1% for the 2017 guidelines. Compared with the 2020 guidelines, both 2019 and 2017 guidelines showed significantly lower sensitivity for R0 resection (p ≤ .009). Specificity was significantly higher with the 2017 guidelines (p = .043) than with the 2020 guidelines. Inter-reader agreements for determining the resectability of PDCA were strong (k ≥ 0.83) with all guidelines, being highest with the 2020 guidelines (k = 0.91).

CONCLUSION

The 2020 NCCN guidelines showed significantly higher sensitivity for prediction of R0 resection than the 2017 and 2019 guidelines.

Predicting Recurrence-Free Survival After Upfront Surgery in Resectable Pancreatic Ductal Adenocarcinoma: A Preoperative Risk Score Based on CA 19-9, CT, and 18F-FDG PET/CT

OBJECTIVE

To develop and validate a preoperative risk score incorporating carbohydrate antigen (CA) 19-9, CT, and fluorine-18-fluorodeoxyglucose (18F-FDG) PET/CT variables to predict recurrence-free survival (RFS) after upfront surgery in patients with resectable pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

Patients with resectable PDAC who underwent upfront surgery between 2014 and 2017 (development set) or between 2018 and 2019 (test set) were retrospectively evaluated. In the development set, a risk-scoring system was developed using the multivariable Cox proportional hazards model, including variables associated with RFS. In the test set, the performance of the risk score was evaluated using the Harrell C-index and compared with that of the postoperative pathological tumor stage.

RESULTS

A total of 529 patients, including 335 (198 male; mean age ± standard deviation, 64 ± 9 years) and 194 (103 male; mean age, 66 ± 9 years) patients in the development and test sets, respectively, were evaluated. The risk score included five variables predicting RFS: tumor size (hazard ratio [HR], 1.29 per 1 cm increment; P < 0.001), maximal standardized uptake values of tumor ≥ 5.2 (HR, 1.29; P = 0.06), suspicious regional lymph nodes (HR, 1.43; P = 0.02), possible distant metastasis on 18F-FDG PET/CT (HR, 2.32; P = 0.03), and CA 19-9 (HR, 1.02 per 100 U/mL increment; P = 0.002). In the test set, the risk score showed good performance in predicting RFS (C-index, 0.61), similar to that of the pathologic tumor stage (C-index, 0.64; P = 0.17).

CONCLUSION

The proposed risk score based on preoperative CA 19-9, CT, and 18F-FDG PET/CT variables may have clinical utility in selecting high-risk patients with resectable PDAC.

Multicenter Prospective Cohort Study of Neoadjuvant Chemotherapy for Borderline Resectable Pancreatic Cancer (YPB-001)

OBJECTIVES

The present multicenter prospective observational study investigated the effectiveness and safety of neoadjuvant chemotherapy (NAC) for patients with borderline resectable pancreatic cancer (BRPC) and those with RPC contacting major vessels, with respect to a historical control of upfront surgery.

MATERIALS AND METHODS

Patients with BRPC and RPC contacting major vessels were prospectively registered and administered NAC with durations and regimens determined by the corresponding treating physician. Our primary aim was to assess the R0 resection rate, and secondary aim was to evaluate safety, resection rate, time to treatment failure, overall survival, and response rate.

RESULTS

Fifty of 52 enrolled patients were analyzed; 2 with serious comorbidities died during treatment. Thirty-one patients underwent resection, with R0 resection being achieved in 26 (52% of total and 84% of all resected cases). Univariate and multivariate analyses indicated age (≥75 years) as the only independent predictor of nonresection. Median progression-free survival and median survival time were longer in the prospective cohort than in the historical cohort.

CONCLUSIONS

Overall, NAC for BRPC in real-world setting might yield R0 resection rates similar to those reported in previous clinical studies. Development of safe regimens and management strategies that can maintain treatment intensity in geriatric patients is warranted.

Predicting resection margin status of pancreatic neuroendocrine tumors on CT: performance of NCCN resectability criteria

OBJECTIVE

To test the performance of the National Comprehensive Cancer Network (NCCN) CT resectability criteria for predicting the surgical margin status of pancreatic neuroendocrine tumor (PNET) and to identify factors associated with margin-positive resection.

METHODS

Eighty patients with pre-operative CT and upfront surgery were retrospectively enrolled. Two radiologists assessed the CT resectability (resectable [R], borderline resectable [BR], unresectable [UR]) of the PNET according to NCCN criteria. Logistic regression was used to identify factors associated with resection margin status. κ statistics were used to evaluate interreader agreements. Kaplan-Meier method with log-rank test was used to estimate and compare recurrence-free survival (RFS).

RESULTS

Forty-five patients (56.2%) received R0 resection and 35 (43.8%) received R1 or R2 resection. R0 resection rates were 63.6-64.2%, 20.0-33.3%, and 0% for R, BR, and UR diseases, respectively (all p ≤ 0.002), with a good interreader agreement (κ, 0.74). Tumor size (<2 cm, 2-4 cm, and >4 cm; odds ratio (OR), 9.042-18.110; all p ≤ 0.007) and NCCN BR/UR diseases (OR, 5.918; p = 0.032) were predictors for R1 or R2 resection. The R0 resection rate was 91.7% for R disease <2 cm and decreased for larger R disease. R0 resection and smaller tumor size in R disease improved RFS.

CONCLUSION

NCCN resectability criteria can stratify patients with PNET into distinct groups of R0 resectability. Adding tumor size to R disease substantially improves the prediction of R0 resection, especially for PNETs <2 cm.

ADVANCES IN KNOWLEDGE

Tumor size and radiologic resectability independently predicted margin status of PNETs.

A Rulefit-based prognostic analysis using structured MRI report to select potential beneficiaries from induction chemotherapy in advanced nasopharyngeal carcinoma: A dual-centre study

BACKGROUND AND PURPOSE

Structured MRI report facilitate prognostic prediction for nasopharyngeal carcinoma (NPC). However, the intrinsic association among structured variables is not fully utilised. This study aimed to investigate the performance of a Rulefit-based model in feature integration behind structured MRI report and prognostic prediction in advanced NPC.

MATERIALS AND METHODS

We retrospectively enrolled 1207 patients diagnosed with non-metastatic advanced NPC from two centres, and divided into training (N = 544), internal testing (N = 367), and external testing (N = 296) cohorts. Machine learning algorithms including multivariate analysis, deep learning, Lasso, and Rulefit were used to establish corresponding prognostic models. The concordance indices (C- indices) of three clinical and six combined models with different algorithms for overall survival (OS) prediction were compared. Survival benefits of induction chemotherapy (IC) were calculated among risk groups stratified by different models. A website was established for individualised survival visualisation.

RESULTS

Incorporating structured variables into Stage model significantly improved the prognostic prediction performance. Six prognostic rules with structured variables were identified by Rulefit. OS prediction of Rules model was comparable to Lasso model in internal testing cohort (C-index: 0.720 vs. 0.713, P = 0.100) and achieved the highest C-index of 0.711 in external testing cohort, indicating better generalisability. The Rules model stratified patients into risk groups with significant 5-year OS differences in each cohort, and revealed significant survival benefits from additional IC in high-risk group.

CONCLUSION

The Rulefit-based Rules model, with the revelation of intrinsic associations behind structured variables, is promising in risk stratification and guiding individualised IC treatment for advanced NPC.

Practice Patterns and Survival in Patients with Resected Pancreatic Ductal Adenocarcinomas (PDAC) - Results from the Multicentre Indian Pancreatic & Periampullary Adenocarcinoma Project (MIPPAP) Study

BACKGROUND

There is limited data from India with regard to presentation, practice patterns and survivals in resected pancreatic ductal adenocarcinomas (PDACs).

METHODS

The Multicentre Indian Pancreatic & Periampullary Adenocarcinoma Project (MIPPAP) included data from 8 major academic institutions across India and presents the outcomes in upfront resected PDACs from January 2015 to June 2019.

RESULTS

Of 288 patients, R0 resection was achieved in 81% and adjuvant therapy was administered in 75% of patients. With a median follow-up of 42 months (95% CI: 39-45), median DFS for the entire cohort was 39 months (95% CI: 25.4-52.5), and median overall survival (OS) was 45 months (95% CI: 32.3-57.7). A separate analysis was done in which patients were divided into 3 groups: (a) those with stage I and absent PNI (SI&PNI-), (b) those with either stage II/III OR presence of PNI (SII/III/PNI+), and (c) those with stage II/III AND presence of PNI (SII/III&PNI+). The DFS was significantly lesser in patients with SII/III&PNI+ (median 25, 95% CI: 14.1-35.9 months), compared to SII/III/PNI + (median 40, 95% CI: 24-55 months) and SI&PNI- (median, not reached) (p = 0.036)).

CONCLUSIONS

The MIPPAP study shows that resectable PDACs in India have survivals at par with previously published data. Adjuvant therapy was administered in 75% patients. Adjuvant radiotherapy does not seem to add to survival after R0 resection.

Determination of "borderline resectable" pancreatic cancer - A global assessment of 30 shades of grey

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with a poor prognosis. Accurate preoperative assessment using computed tomography (CT) to determine resectability is crucial in ensuring patients are offered the most appropriate therapeutic strategy. Despite the use of classification guidelines, any interobserver variability between reviewing surgeons and radiologists may confound decisions influencing patient treatment pathways.

METHODS

In this multicentre observational study, an international group of 96 clinicians (42 hepatopancreatobiliary surgeons and 54 radiologists) were surveyed and asked to report 30 pancreatic CT scans of pancreatic cancer deemed borderline at respective multidisciplinary meetings (MDM). The degree of interobserver agreement in resectability among radiologists and surgeons was assessed and subgroup regression analysis was performed.

RESULTS

Interobserver variability between reviewers was high with no unanimous agreement. Overall interobserver agreement was fair with a kappa value of 0.32 with a higher rate of agreement among radiologists over surgeons.

CONCLUSION

Interobserver variability among radiologists and surgeons globally is high, calling into question the consistency of clinical decision making for patients with PDAC and suggesting that central review may be required for studies of neoadjuvant or adjuvant approaches in future as well as ongoing quality control initiatives, even amongst experts in the field.

Evaluation of the performance of and interobserver agreement on postoperative baseline CT findings in the identification of locoregional recurrence in patients with pancreatic ductal adenocarcinoma

PURPOSE

To evaluate interobserver agreement on the findings of baseline contrast-enhanced multidetector computed tomography (CE-MDCT) performed at the postoperative third month in patients who underwent surgery due to ductal adenocarcinoma of the pancreatic head and investigate the value of these findings in predicting locoregional recurrence.

MATERIAL AND METHODS

The baseline CE-MDCT images of 198 patients who underwent the Whipple procedure due to pancreatic head tumors were evaluated independently by three radiologists at the postoperative third month. The radiologists were asked to note suspicious findings in terms of locoregional recurrence, including postoperative fat stranding, the presence of perivascular contrast-enhanced solid tissue, short diameter of solid tissue if present, the shape of solid tissue (convex/concave), presence of peritoneal implants, diameter (mm) of pancreatic duct dilatation if present, the presence of lymph nodes larger than 5 mm, portal vein stenosis (≥50 and <50%), the presence of ascites, and the presence of distant metastases, as specified by the Society of Abdominal Radiology in October 2022. The agreement between the radiologists and the value of these parameters in predicting locoregional recurrence were investigated.

RESULTS

Among the CE-MDCT findings evaluated, the radiologists had a moderate-to-high level of agreement concerning the presence of perivascular contrast-enhanced solid tissue. However, there was a poor interobserver agreement on the shape of solid tissue. A very high level of agreement was found among the radiologists in the evaluation of pancreatic duct dilatation, peritoneal implants, ascites, and the presence of distant metastases. According to the univariate analysis, the rates of portal vein stenosis had a 1.419 -fold effect [odds ratio (OR)=1.419, [95% confidence interval (CI)= 0.548-3.679, p=0.041], lymph node presence had a 2.337 -fold effect [odds ratio (OR)=2.337, [95% confidence interval (CI)= 1.165-4.686, p=0.015], perivascular contrast-enhanced solid tissue had 2.241 -fold effect [odds ratio (OR)=2.241, [95% confidence interval (CI)= 1.072-4.684, p=0.005]. In the multivariate analysis, perivascular contrast-enhanced solid tissue had 2.241 -fold effect [odds ratio (OR)=2.519, [95% confidence interval (CI)= 1.132-5.605, p=0.024].

CONCLUSION

In the postoperative baseline CE-MDCT examination, the presence of solid tissue, lymph node presence, and portal vein stenosis in the surgical bed are among the findings that may indicate early locoregional recurrence in patients with pancreatic ductal adenocarcinoma.

Pancreatic Adenocarcinoma: Real World Evidence of Care Delivery in AccessHope Data

BACKGROUND

Pancreatic adenocarcinoma is an aggressive disease and the delivery of comprehensive care to individuals with this cancer is critical to achieve appropriate outcomes. The identification of gaps in care delivery facilitates the design of interventions to optimize care delivery and improve outcomes in this population.

METHODS

AccessHope™ is a growing organization that connects oncology subspecialists with treating providers through contracts with self-insured employers. Data from 94 pancreatic adenocarcinoma cases (August 2019-December 2022) in the AccessHope dataset were used to describe gaps in care delivery.

RESULTS

In all but 6% of cases, the subspecialist provided guideline-concordant recommendations anticipated to improve outcomes. Gaps in care were more pronounced in patients with non-metastatic pancreatic cancer. There was a significant deficiency in germline testing regardless of the stage, with only 59% of cases having completed testing. Only 20% of cases were receiving palliative care or other allied support services. There was no difference in observed care gaps between patients receiving care in the community setting vs. those receiving care in the academic setting.

CONCLUSIONS

There are significant gaps in the care delivered to patients with pancreatic adenocarcinoma. A concurrent subspecialist review has the opportunity to identify and address these gaps in a timely manner.

A phase II study of neoadjuvant liposomal irinotecan with 5-FU and oxaliplatin (NALIRIFOX) in pancreatic adenocarcinoma

For patients with localized pancreatic cancer with minimal vascular involvement, optimal survivability requires a multidisciplinary approach of surgical resection and systemic chemotherapy. FOLFIRINOX is a combination chemotherapy regimen that offers promising results in the perioperative and metastatic settings; however, it can cause significant adverse effects. Such toxicity can negatively impact some patients, resulting in chemotherapy discontinuation or surgical unsuitability. In an effort to reduce toxicities and optimize outcomes, this investigation explores the safety and feasibility of substituting liposomal irinotecan (nal-IRI) for nonliposomal irinotecan to improve tumor drug delivery and potentially reduce toxicity. This regimen, NALIRIFOX, has the potential to be both safer and more effective when administered in the preoperative setting.

High-resolution pancreatic computed tomography for assessing pancreatic ductal adenocarcinoma resectability: a multicenter prospective study

OBJECTIVE

This prospective multicenter study aimed to evaluate the diagnostic performance of 80-kVp thin-section pancreatic CT in determining pancreatic ductal adenocarcinoma (PDAC) resectability according to the recent National Comprehensive Cancer Network (NCCN) guidelines.

METHODS

We prospectively enrolled surgical resection candidates for PDAC from six tertiary referral hospitals (study identifier: NCT03895177). All participants underwent pancreatic CT using 80 kVp tube voltage with 1-mm reconstruction interval. The local resectability was prospectively evaluated using NCCN guidelines at each center and classified into three categories: resectable, borderline resectable, and unresectable.

RESULTS

A total of 138 patients were enrolled; among them, 60 patients underwent neoadjuvant therapy. R0 resection was achieved in 103 patients (74.6%). The R0 resection rates were 88.7% (47/53), 52.4% (11/21), and 0.0% (0/4) for resectable, borderline resectable, and unresectable disease, respectively, in 78 patients who underwent upfront surgery. Meanwhile, the rates were 90.9% (20/22), 76.7% (23/30), and 25.0% (2/8) for resectable, borderline resectable, and unresectable PDAC, respectively, in patients who received neoadjuvant therapy. The area under curve of high-resolution CT in predicting R0 resection was 0.784, with sensitivity, specificity, and accuracy of 87.4% (90/103), 48.6% (17/35), and 77.5% (107/138), respectively. Tumor response was significantly associated with the R0 resection after neoadjuvant therapy (odds ratio [OR] = 38.99, p = 0.016).

CONCLUSION

An 80-kVp thin-section pancreatic CT has excellent diagnostic performance in assessing PDAC resectability, enabling R0 resection rates of 88.7% and 90.9% for patients with resectable PDAC who underwent upfront surgery and patients with resectable PDAC after neoadjuvant therapy, respectively.

KEY POINTS

• The margin-negative (R0) resection rates were 88.7% (47/53), 52.4% (11/21), and 0.0% (0/4) for resectable, borderline resectable, and unresectable pancreatic ductal adenocarcinoma (PDAC), respectively, on 80-kVp thin-section pancreatic CT in the 78 patients who underwent upfront surgery. • Among the 60 patients who underwent neoadjuvant therapy, the R0 rates were 90.9% (20/22), 76.7% (23/30), and 25.0% (2/8) for resectable, borderline resectable, and unresectable PDAC, respectively. • Tumor response, along with the resectability status on pancreatic CT, was significantly associated with the R0 resection rate after neoadjuvant therapy.

Innovative Imaging Techniques Used to Evaluate Borderline-Resectable Pancreatic Adenocarcinoma

A diagnosis of pancreatic cancer carries a 5-y survival rate of less than 10%. Furthermore, the detection of pancreatic cancer occurs most often in later stages of the disease due to its location in the retroperitoneum and lack of symptoms (in most cases) until tumors become more advanced. Once diagnosed, cross-sectional imaging techniques are heavily utilized to determine the tumor stage and the potential for surgical resection. However, a major determinant of resectability is the extent of local vascular involvement of the mesenteric vessels and critical tributaries; current imaging techniques have limited capacity to accurately determine vascular involvement. Surrounding inflammation and fibrosis can be difficult to discriminate from viable tumor, making determination of the degree of vascular involvement unreliable. New innovations in fluorescence and optoacoustic imaging techniques may overcome these limitations and make determination of resectability more accurate. These imaging modalities are able to more clearly discern between viable tumor tissue and non-neoplastic inflammation or desmoplasia, allowing clinicians to more reliably characterize vascular involvement and develop individualized treatment plans for patients. This review will discuss the current imaging techniques used to diagnose pancreatic cancer, the barriers that current techniques raise to accurate staging, and novel fluorescence and optoacoustic imaging techniques that may provide more accurate clinical staging of pancreatic cancer.

Imaging Recommendations for Diagnosis, Staging, and Management of Pancreatic Cancer

Pancreatic cancer is the fourth most prevalent cause of cancer-related death worldwide, with a fatality rate equal to its incidence rate. Pancreatic cancer is a rare malignancy with a global incidence and death ranking of 14th and 7th, respectively. Pancreatic cancer cases are divided into three categories without metastatic disease: resectable, borderline resectable, or locally advanced disease. The category is determined by the tumor's location in the pancreas and whether it is abutting or encasing the adjacent arteries and/or vein/s.

The stage of disease and the location of the primary tumor determine the clinical presentation: the pancreatic head, neck, or uncinate process, the body or tail, or multifocal disease. Imaging plays a crucial role in the diagnosis and follow-up of pancreatic cancers. Various imaging modalities available for pancreatic imaging are ultrasonography (USG), contrast-enhanced computed tomography (CECT), magnetic resonance imaging (MRI), and 18-fluoro-deoxy glucose positron emission tomography (FDG PET).

Even though surgical resection is possible in both resectable and borderline resectable non-metastatic cases, neoadjuvant chemotherapy with or without radiotherapy has become the standard practice for borderline resectable cases as it gives a high yield of R0 resection.

Machine-learning based investigation of prognostic indicators for oncological outcome of pancreatic ductal adenocarcinoma

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a poor prognosis. Surgical resection remains the only potential curative treatment option for early-stage resectable PDAC. Patients with locally advanced or micrometastatic disease should ideally undergo neoadjuvant therapy prior to surgical resection for an optimal treatment outcome. Computerized tomography (CT) scan is the most common imaging modality obtained prior to surgery. However, the ability of CT scans to assess the nodal status and resectability remains suboptimal and depends heavily on physician experience. Improved preoperative radiographic tumor staging with the prediction of postoperative margin and the lymph node status could have important implications in treatment sequencing. This paper proposes a novel machine learning predictive model, utilizing a three-dimensional convoluted neural network (3D-CNN), to reliably predict the presence of lymph node metastasis and the postoperative positive margin status based on preoperative CT scans.

Methods

A total of 881 CT scans were obtained from 110 patients with PDAC. Patients and images were separated into training and validation groups for both lymph node and margin prediction studies. Per-scan analysis and per-patient analysis (utilizing majority voting method) were performed.

Results

For a lymph node prediction 3D-CNN model, accuracy was 90% for per-patient analysis and 75% for per-scan analysis. For a postoperative margin prediction 3D-CNN model, accuracy was 81% for per-patient analysis and 76% for per-scan analysis.

Discussion

This paper provides a proof of concept that utilizing radiomics and the 3D-CNN deep learning framework may be used preoperatively to improve the prediction of positive resection margins as well as the presence of lymph node metastatic disease. Further investigations should be performed with larger cohorts to increase the generalizability of this model; however, there is a great promise in the use of convoluted neural networks to assist clinicians with treatment selection for patients with PDAC.

Risk factors of positive resection margin differ in pancreaticoduodenectomy and distal pancreatosplenectomy for pancreatic ductal adenocarcinoma undergoing upfront surgery

OBJECTIVE

Positive resection margin indicates worse prognosis. The present study identified the independent risk factors of R1 resection in pancreaticoduodenectomy (PD) and distal pancreatosplenectomy (DP) for patients with pancreatic ductal adenocarcinoma (PDAC).

METHOD

Consecutive patients who were operated from 1st December 2017 to 30th December 2018 were analyzed retrospectively. A standardized pathological examination with digital whole-mount slide images (DWMSIs) was utilized for evaluation of resection margin status. R1 was defined as microscopic tumor infiltration within 1 mm to the resection margin. The potential risk factors of R1 resection for PD and DP were analyzed separately by univariate and multivariate logistic regression analyses.

RESULTS

For the 192 patients who underwent PD, and the 87 patients who underwent DP, the R1 resection rates were 31.8% and 35.6%, respectively. Univariate analysis on risk factors of R1 resection for PD were tumor location, lymphovascular invasion, N staging, and TNM staging; while those for DP were T staging and TNM staging. Multivariate logistic regression analysis showed the location of tumor in the neck and uncinate process, and N1/2 staging were independent risk factors of R1 resection for PD; while those for DP were T3 staging.

CONCLUSIONS

The clarification of the risk factors of R1 resection might clearly make surgeons take reasonable decisions on surgical strategies for different surgical procedures in patients with PDAC, so as to obtain the first attempt of R0 resection.

Discovery of the inhibitor of DNA binding 1 as a novel marker for radioresistance in pancreatic cancer using genome-wide RNA-seq

Purpose/Objective(s): Discovery of genetic drivers of radioresistance is critical for developing novel therapeutic strategies to combine with radiotherapy of radioresistant PDAC. In this study, we used genome-wide RNA-seq to identify genes upregulated in generated radioresistant PDAC cell lines and discovered the Inhibitor of DNA Binding 1 (ID1) gene as a potential regulator of radioresistance in PDAC. Materials/Methods: Radioresistant clones of the PDAC cell lines MIA PaCa-2 and PANC-1 were generated by delivering daily ionizing irradiation (IR) (2 Gy/day) in vitro over two weeks (total 20 Gy) followed by standard clonogenic assays following one week from the end of IR. The generated RR and parental cell lines were submitted for RNA-seq analysis to identify differentially expressed genes. The Limma R package was used to calculate differential expression among genes. Log2 fold change values were calculated for each sample compared to the control. Genes with an absolute fold change > 1 were considered significant. RNA sequencing expression data from the Cancer Genome Atlas (TCGA) database was analyzed through the online databases GEPIA, cBioPortal, and the Human Protein Atlas. Results: Following exposure to two weeks of 2 Gy daily IR in vitro, the two PDAC cell lines showed significantly greater clonogenic cell survival than their parental cell lines, indicating enhanced RR in these cells. RNA-seq analysis comparing parental and RR cell lines found upregulated seven genes (TNS4, ZDHHC8P1, APLNR, AQP3, SPP1, ID1, ID2) and seven genes downregulated (PTX3, ITGB2, EPS8L1, ALDH1L2, KCNT2, ARHGAP9, IFI16) in both RR cell lines. Western blotting confirmed increased expression of the ID1 protein in the RR cell lines compared to their parental cell lines. We found that ID1 mRNA was significantly higher in PDAC tumors compared to matched normal and high ID1 expression correlated with significantly worse disease-free survival (DFS) in PDAC patients (HR = 2.2, log rank P = 0.009). ID1 mRNA expression was also strongly correlated in tumors with TP53 mutation, a known driver of radioresistance. Conclusion: Our analysis indicates a novel role of ID1 in PDAC radioresistance. ID1 expression is higher in tumor tissue compared to normal, and high expression correlates with both worse DFS and association with the TP53 mutation, suggesting that targeting ID1 prior to IR is an attractive strategy for overcoming radioresistance in PDAC.

Management of Advanced Pancreatic Cancer through Stromal Depletion and Immune Modulation

Pancreatic cancer is one of the leading causes of cancer-related deaths worldwide. Unfortunately, therapeutic gains in the treatment of other cancers have not successfully translated to pancreatic cancer treatments. Management of pancreatic cancer is difficult due to the lack of effective therapies and the rapid development of drug resistance. The cytotoxic agent gemcitabine has historically been the first-line treatment, but combinations of other immunomodulating and stroma-depleting drugs are currently undergoing clinical testing. Moreover, the treatment of pancreatic cancer is complicated by its heterogeneity: analysis of genomic alterations and expression patterns has led to the definition of multiple subtypes, but their usefulness in the clinical setting is limited by inter-tumoral and inter-personal variability. In addition, various cell types in the tumor microenvironment exert immunosuppressive effects that worsen prognosis. In this review, we discuss current perceptions of molecular features and the tumor microenvironment in pancreatic cancer, and we summarize emerging drug options that can complement traditional chemotherapies.

Pancreatic cancer, radiomics and artificial intelligence

Patients with pancreatic ductal adenocarcinoma (PDAC) are generally classified into four categories based on contrast-enhanced CT at diagnosis: resectable, borderline resectable, unresectable, and metastatic disease. In the initial grading and staging of PDAC, structured radiological templates are useful but limited, as there is a need to define the aggressiveness and microscopic disease stage of these tumours to ensure adequate treatment allocation. Quantitative imaging analysis allows radiomics and dynamic imaging features to provide information of clinical outcomes, and to construct clinical models based on radiomics signatures or imaging phenotypes. These quantitative features may be used as prognostic and predictive biomarkers in clinical decision-making, enabling personalised management of advanced PDAC. Deep learning and convolutional neural networks also provide high level bioinformatics tools that can help define features associated with a given aspect of PDAC biology and aggressiveness, paving the way to define outcomes based on these features. Thus, the prediction of tumour phenotype, treatment response and patient prognosis may be feasible by using such comprehensive and integrated radiomics models. Despite these promising results, quantitative imaging is not ready for clinical implementation in PDAC. Limitations include the instability of metrics and lack of external validation. Large properly annotated datasets, including relevant semantic features (demographics, blood markers, genomics), image harmonisation, robust radiomics analysis, clinically significant tasks as outputs, comparisons with gold-standards (such as TNM or pretreatment classifications) and fully independent validation cohorts, will be required for the development of trustworthy radiomics and artificial intelligence solutions to predict PDAC aggressiveness in a clinical setting.

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.

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.

Real-world staging computed tomography scanning technique and important reporting discrepancies in pancreatic ductal adenocarcinoma

BACKGROUND

Computed tomography (CT) is the first-line staging imaging modality for pancreatic ductal adenocarcinoma (PDAC) which determines resectability and treatment pathways.

METHODS

Between January 2016 and December 2019, prospectively collated data from two Australian cancer centres was extracted from the PURPLE Pancreatic Cancer registry. Real-world staging CTs and corresponding reports were blindly reviewed by a sub-specialist radiologist and compared to initial reports.

RESULTS

Of 131 patients assessed, 117 (89.3%) presented with symptoms, 74 (56.5%) CTs included slices ≤3 mm thickness and CT pancreas protocol was applied in 69 (52.7%) patients. Initial reports lacked synoptic reporting in 131 (100%), tumour identification in 2 (1.6%) and tumour measurement in 13 (9.9%) cases. Tumour-vascular relationship reporting was missing in 69-109 (52.7-83.2%) for regarding the key arterial and venous structures that is required to assess resectability. Initial reports had no comment on venous thrombus or venous collaterals in 80 (61.1%) and 109 (83.2%) and lacked locoregional lymphadenopathy interpretation in 13 (9.9%) cases. Complete initial staging report was present in 72 (55.0%) patients. Sub-specialist radiological review resulted in down-staging in 16 (22.2%) and up-staging in 1 (1.4%) patient. Staging discrepancies were mainly regarding metastatic disease (12, 70.6%) and tumour-vascular relationship (5, 29.4%).

CONCLUSION

Real-world staging imaging in PDAC patients show low proportion of dedicated CT pancreas protocol, high proportion of incomplete staging reports and no synoptic reporting. The most common discrepancy between initial and sub-specialist reporting was regarding metastases and tumour-vascular relationship assessment resulting in sub-specialist down-staging in almost every fifth case.

Prognostic value of preoperative enhanced computed tomography as a quantitative imaging biomarker in pancreatic cancer

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies with high mortality and short survival time. Computed tomography (CT) plays an important role in the diagnosis, staging and treatment of pancreatic tumour. Pancreatic cancer generally shows a low enhancement pattern compared with normal pancreatic tissue.

AIM

To analyse whether preoperative enhanced CT could be used to predict postoperative overall survival in patients with PDAC.

METHODS

Sixty-seven patients with PDAC undergoing pancreatic resection were enrolled retrospectively. All patients underwent preoperative unenhanced and enhanced CT examination, the CT values of which were measured. The ratio of the preoperative CT value increase from the nonenhancement phase to the portal venous phase between pancreatic tumour and normal pancreatic tissue was calculated. The cut-off value of ratios was obtained by the receiver operating characteristic (ROC) curve of the tumour relative enhancement ratio (TRER), according to which patients were divided into low- and high-enhancement groups. Univariate and multivariate analyses were performed using Cox regression based on TRER grouping. Finally, the correlation between TRER and clinicopathological characteristics was analysed.

RESULTS

The area under the curve of the ROC curve was 0.768 (P < 0.05), and the cut-off value of the ROC curve was calculated as 0.7. TRER ≤ 0.7 was defined as the low-enhancement group, and TRER > 0.7 was defined as the high-enhancement group. According to the TRER grouping, the Kaplan-Meier survival curve analysis results showed that the median survival (10.0 mo) with TRER ≤ 0.7 was significantly shorter than that (22.0 mo) with TRER > 0.7 (P < 0.05). In the univariate and multivariate analyses, the prognosis of patients with TRER ≤ 0.7 was significantly worse than that of patients with TRER > 0.7 (P < 0.05). Our results demonstrated that patients in the low TRER group were more likely to have higher American Joint Committee on Cancer stage, tumour stage and lymph node stage (all P < 0.05), and TRER was significantly negatively correlated with tumour size (P < 0.05).

CONCLUSION

TRER ≤ 0.7 in patients with PDAC may represent a tumour with higher clinical stage and result in a shorter overall survival.

Prediction of Margin-Negative Resection of Pancreatic Ductal Adenocarcinoma Following Neoadjuvant Therapy: Diagnostic Performance of NCCN Criteria for Resection vs. CT-Determined Resectability

BACKGROUND

Accurate assessment of pancreatic ductal adenocarcinoma (PDAC) resectability after neoadjuvant therapy (NAT) is crucial. Recently, the NCCN introduced criteria for resection of PDAC following NAT.

METHODS

We analyzed 127 patients who underwent NAT and pancreatectomy for PDAC between January 2010 and March 2020. CT-determined resectability according to the NCCN guideline, and CA 19-9 level was evaluated before and after NAT. Diagnostic performance of the NCCN criteria for margin-negative (R0) resection was investigated and compared with CT alone.

RESULTS

R0 resection was achieved in 104 (81.9%) patients. After NAT, there were 30 (23.6%) resectable, 90 (70.9%) borderline resectable, and seven (5.5%) locally advanced tumors. Significantly decreased or stable CA 19-9 levels were noted in 114 (89.8%) patients. The sensitivity and specificity of the NCCN criteria were 87.5% (91/104) and 21.7% (5/23), respectively, which were significantly different from CT including only resectable PDAC (26.9% [28/104] and 91.3% [21/23]; p<0.001), but less prominently different from CT including resectable and borderline resectable PDAC (95.2% [99/104]; p=0.022 and 8.7% [2/23]; p=0.375).

CONCLUSIONS

The NCCN criteria for resection following NAT showed high sensitivity and low specificity for predicting R0 resection. It had supplementary benefit over CT alone, mainly in preventing underestimation of R0 resection.

Prognostic stratification in patients with pancreatic ductal adenocarcinoma after curative resection based on preoperative pancreatic contrast-enhanced CT findings

PURPOSE

To establish a prognostic stratification model for predicting prognosis in patients with pancreatic ductal adenocarcinoma (PDAC) after curative resection based on preoperative contrast-enhanced computed tomography (CECT) findings.

METHOD

From January 2014 to June 2020, 126 patients with radically resected PDAC were reviewed and divided into a development cohort (n = 90) and a validation cohort (n = 36). In the development cohort, clinicopathological parameters and preoperative CECT findings associated with recurrence-free survival (RFS) and overall survival (OS) were identified by using univariate and multivariate analyses. Nomograms were constructed based on Cox proportional hazards regression models. New prognostic nomograms were certificated in the validation cohort. Model performance was evaluated based on calibration, discrimination, and clinical utility.

RESULTS

Tumor size >4 cm, adjacent organs invasion, suspicious lymph nodes, and rim enhancement were independently associated with worse RFS and OS (all P values were < 0.05). In the validation cohort, the nomograms based on pancreatic CECT showed good discrimination capability and outperformed the TNM staging system in outcomes prediction. Patients were stratified into low- and high-risk groups based on nomograms, and RFS and OS rates in the low-risk group were significantly higher than those in the high-risk group (P < 0.001 and <0.01, respectively).

CONCLUSIONS

Nomograms based on preoperative pancreatic CECT findings can predict RFS and OS for PDAC patients after curative resection and facilitate further prognostic stratification.

Diagnostic Accuracy of CT for Evaluating Circumferential Resection Margin Status in Resectable or Borderline Resectable Pancreatic Head Cancer: A Prospective Study Using Axially Sliced Surgical Pathologic Correlation

OBJECTIVE

CT plays a central role in determining the resectability of pancreatic cancer, which directs the use of neoadjuvant therapy. This study aimed to assess the diagnostic accuracy of CT in predicting circumferential resection margin (CRM) involvement in patients with resectable or borderline resectable pancreatic head cancer.

MATERIALS AND METHODS

Seventy-seven patients who were scheduled for upfront surgery for resectable or borderline resectable pancreatic head cancer were prospectively enrolled, and 75 patients (38 male and 37 female; mean age ± standard deviation, 68 ± 11 years) were finally analyzed. The CRM status was evaluated separately for the superior mesenteric artery (SMA) and posterior and superior mesenteric vein/portal vein (SMV/PV) margins. Three independent radiologists reviewed the preoperative CT images and evaluated the resection margin status. The reference standard for CRM status was pathologic examination of pancreaticoduodenectomy specimens in an axial plane perpendicular to the axis of the second portion of the duodenum. The diagnostic accuracy of CT was assessed for overall CRM involvement, defined as involvement of the SMA or posterior margins (per-patient analysis), and involvement of each of the three resection margins (per-margin analysis). The data were pooled using a crossed random effects model.

RESULTS

Forty patients had pathologically confirmed overall CRM involvement in pancreatic cancer, while CRM involvement was not seen in 35 patients. For overall CRM involvement, the pooled sensitivity and specificity were 15% (95% confidence interval: 7%-49%) and 99% (96%-100%), respectively. For each of the resection margins, the pooled sensitivity and specificity were 14% (9%-54%) and 99% (38%-100%) for the SMA margin, 12% (8%-46%) and 99% (97%-100%) for the posterior margin; and 37% (29%-53%) and 96% (31%-100%) for the SMV/PV margin, respectively.

CONCLUSION

CT showed very high specificity but low sensitivity in predicting pathological CRM involvement in pancreatic cancer.

Pretherapeutic Assessment of Pancreatic Cancer: Comparison of FDG PET/CT Plus Delayed PET/MR and Contrast-Enhanced CT/MR

PURPOSE

This study aims to determine the diagnostic performance of whole-body FDG PET/CT plus delayed abdomen PET/MR imaging in the pretherapeutic assessment of pancreatic cancer in comparison with that of contrast-enhanced (CE)-CT/MR imaging.

MATERIALS AND METHODS

Forty patients with pancreatic cancer underwent nonenhanced whole-body FDG PET/CT, delayed abdomen PET/MR imaging, and CE-CT/MR imaging. Two nuclear medicine physicians independently reviewed these images and discussed to reach a consensus, determining tumor resectability according to a 5-point scale, N stage (N0 or N positive), and M stage (M0 or M1). With use of clinical-surgical-pathologic findings as the reference standard, diagnostic performances of the two imaging sets were compared by using the McNemar test.

RESULTS

The diagnostic performance of FDG PET/CT plus delayed PET/MR imaging was not significantly different from that of CE-CT/MR imaging in the assessment of tumor resectability [area under the receiver operating characteristic curve: 0.927 vs. 0.925 (p = 0.975)], N stage (accuracy: 80% (16 of 20 patients) vs. 55% (11 of 20 patients), p = 0.125), and M stage (accuracy: 100% (40 of 40 patients) vs. 93% (37 of 40 patients), p = 0.250). Moreover, 14 of 40 patients had liver metastases. The number of liver metastases detected by CE-CT/MR imaging, PET/CT, and PET/MR imaging were 33, 18, and 61, respectively. Compared with CE-CT/MR imaging, PET/MR imaging resulted in additional findings of more liver metastases in 9/14 patients, of which 3 patients were upstaged. Compared with PET/CT, PET/MR imaging resulted in additional findings of more liver metastases in 12/14 patients, of which 6 patients were upstaged.

CONCLUSIONS

Although FDG PET/CT plus delayed PET/MR imaging showed a diagnostic performance similar to that of CE-CT/MR imaging in the pretherapeutic assessment of the resectability and staging of pancreatic tumors, it still has potential as the more efficient and reasonable work-up approach for the additional value of metastatic information provided by delayed PET/MR imaging.

Current trends in the diagnosis of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a dreaded malignancy with a dismal 5-year survival rate despite maximal efforts on optimizing treatment strategies. Currently, early detection is considered to be the most effective way to improve survival as radical resection is the only potential cure. PDAC is often divided into four categories based on the extent of disease: resectable, borderline resectable, locally advanced, and metastatic. Unfortunately, the majority of patients are diagnosed with locally advanced or metastatic disease, which renders them ineligible for curative resection. This is mainly due to the lack of or vague symptoms while the disease is still localized, although appropriate utilization and prompt availability of adequate diagnostic tools is also critical given the aggressive nature of the disease. A cost-effective biomarker with high specificity and sensitivity allowing early detection of PDAC without the need for advanced or invasive methods is still not available. This leaves the diagnosis dependent on radiodiagnostic methods or endoscopic ultrasound. Here we summarize the latest epidemiological data, risk factors, clinical manifestation, and current diagnostic trends and implications of PDAC focusing on serum biomarkers and imaging modalities. Additionally, up-to-date management and therapeutic algorithms are outlined.

CT Radiomic Features of Superior Mesenteric Artery Involvement in Pancreatic Ductal Adenocarcinoma: A Pilot Study

Background Current imaging methods for prediction of complete margin resection (R0) in patients with pancreatic ductal adenocarcinoma (PDAC) are not reliable. Purpose To investigate whether tumor-related and perivascular CT radiomic features improve preoperative assessment of arterial involvement in patients with surgically proven PDAC. Materials and Methods This retrospective study included consecutive patients with PDAC who underwent surgery after preoperative CT between 2012 and 2019. A three-dimensional segmentation of PDAC and perivascular tissue surrounding the superior mesenteric artery (SMA) was performed on preoperative CT images with radiomic features extracted to characterize morphology, intensity, texture, and task-based spatial information. The reference standard was the pathologic SMA margin status of the surgical sample: SMA involved (tumor cells ≤1 mm from margin) versus SMA not involved (tumor cells >1 mm from margin). The preoperative assessment of SMA involvement by a fellowship-trained radiologist in multidisciplinary consensus was the comparison. High reproducibility (intraclass correlation coefficient, 0.7) and the Kolmogorov-Smirnov test were used to select features included in the logistic regression model. Results A total of 194 patients (median age, 66 years; interquartile range, 60-71 years; age range, 36-85 years; 99 men) were evaluated. Aside from surgery, 148 patients underwent neoadjuvant therapy. A total of 141 patients' samples did not involve SMA, whereas 53 involved SMA. A total of 1695 CT radiomic features were extracted. The model with five features (maximum hugging angle, maximum diameter, logarithm robust mean absolute deviation, minimum distance, square gray level co-occurrence matrix correlation) showed a better performance compared with the radiologist assessment (model vs radiologist area under the curve, 0.71 [95% CI: 0.62, 0.79] vs 0.54 [95% CI: 0.50, 0.59]; P < .001). The model showed a sensitivity of 62% (33 of 53 patients) (95% CI: 51, 77) and a specificity of 77% (108 of 141 patients) (95% CI: 60, 84). Conclusion A model based on tumor-related and perivascular CT radiomic features improved the detection of superior mesenteric artery involvement in patients with pancreatic ductal adenocarcinoma. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Do and Kambadakone in this issue.

Role of multidetector computed tomography in evaluation of resectability of pancreatic cancer

Background

Pancreatic cancer is one of the most significant causes and one of the most lethal malignant neoplasms in the world of cancer death in the developed nations. It was named the “silent killer” for its quiet course, late clinical presentation, and the trend of rapid growth. The aim of this study is to detect the reliability of multidetector CT (MDCT) as diagnostic tool in assessing the possibility of eradicating pancreatic cancer.

Results

Twenty-four patients (57%) were not suitable for surgery with non-resectable mass; the remaining eighteen patients (43%) were considered suitable according to MDCT criteria for surgical resection of the tumor. Fourteen out of the sixteen patients (87.5%) had a successful removal of the lump, while the remaining two cases (12.5%) during surgery, the mass was unresectable. The results of the pathology specimens showed that fourteen out of the fourteen patients (100%) had successful operation with no cancer cells in the margin, and a positive predictive value of 87.5% and accuracy of 89.47%.

Conclusions

The advancement of MDCT expertise improves the outcome of pancreatic cancer resectability.

Application and progress of medical imaging in total mesopancreas excision for pancreatic head carcinoma

Pancreatic head carcinoma (PHC) is one of the common gastrointestinal malignancies with a high morbidity and poor prognosis. At present, radical surgery is still the curative treatment for PHC. However, in clinical practice, the actual R0 resection rate, the local recurrence rate, and the prognosis of PHC are unsatisfactory. Therefore, the concept of total mesopancreas excision (TMpE) is proposed to achieve R0 resection. Although there have various controversies and discussions on the definition, the range of excision, and clinical prognosis of TMpE, the concept of TMpE can effectively increase the R0 resection rate, reduce the local recurrence rate, and improve the prognosis of PHC. Imaging is of importance in preoperative examination for PHC; however, traditional imaging assessment of PHC does not focus on mesopancreas. This review discusses the application of medical imaging in TMpE for PHC, to provide more accurate preoperative evaluation, range of excision, and more valuable postoperative follow-up evaluation for TMpE through imaging. It is believed that with further extensive research and exploratory application of TMpE for PHC, large-sample and multicenter studies will be realized, thus providing reliable evidence for imaging evaluation.

Resectable and Borderline Resectable Pancreatic Ductal Adenocarcinoma: Role of the Radiologist and Oncologist in the Era of Precision Medicine

The incidence and mortality of pancreatic ductal adenocarcinoma are growing over time. The management of patients with pancreatic ductal adenocarcinoma involves a multidisciplinary team, ideally involving experts from surgery, diagnostic imaging, interventional endoscopy, medical oncology, radiation oncology, pathology, geriatric medicine, and palliative care. An adequate staging of pancreatic ductal adenocarcinoma and re-assessment of the tumor after neoadjuvant therapy allows the multidisciplinary team to choose the most appropriate treatment for the patient. This review article discusses advancement in the molecular basis of pancreatic ductal adenocarcinoma, diagnostic tools available for staging and tumor response assessment, and management of resectable or borderline resectable pancreatic cancer.

Systematic review and meta-analysis of diagnostic performance of CT imaging for assessing resectability of pancreatic ductal adenocarcinoma after neoadjuvant therapy: importance of CT criteria

PURPOSE

To assess the CT diagnostic performance for evaluating resectability of pancreatic ductal adenocarcinoma (PDAC) after neoadjuvant therapy and identify the factor(s) that affect(s) diagnostic performance.

METHODS

Databases were searched to identify studies published from January 1, 2000, to November 5, 2019 that evaluated the CT diagnostic performance for assessing resectability of post-neoadjuvant PDAC. Two reviewers independently extracted data and assessed the study quality. A meta-analysis was performed to obtain summary sensitivity and specificity values using a bivariate random-effects model, and heterogeneity across studies was assessed. Univariable meta-regression analysis was performed with eight variables, including the different CT criteria for resectability, conventional National Comprehensive Cancer Network (NCCN) criteria for upfront surgery, and modified criteria for post-neoadjuvant surgery.

RESULTS

Ten studies were included and analyzed. The summary sensitivity and specificity for resectability were 78% (95% CI 68-86%) and 60% (95% CI 44-74%), respectively. No significant heterogeneity was identified (bivariate correlation coefficient ρ = - 1, p-value for hierarchical summary receiver operating characteristics model β = 0.667). The two different CT criteria showed different diagnostic performance (p < 0.01), with higher sensitivity (81% [95% CI 73-90%] vs. 28% [95% CI 15-42%], p < 0.01) and lower specificity (57% [95% CI 41-73%] vs. 90% [95% CI 80-100%], p < 0.01) for the modified criteria. No other variables affected the diagnostic performance.

CONCLUSION

CT criteria were the factors that affected the diagnostic performance. Modification of the conventional criteria improved sensitivity but lowered specificity. Further modifications are required to improve specificity and uniformity.

Arterial involvement and resectability scoring system to predict R0 resection in patients with pancreatic ductal adenocarcinoma treated with neoadjuvant chemoradiation therapy

OBJECTIVES

To derive a CT-based scoring system incorporating arterial involvement and resectability status to predict R0 resection in patients with pancreatic ductal adenocarcinoma (PDAC) undergoing neoadjuvant chemoradiation therapy (CRT).

METHODS

This retrospective study included 112 patients with PDAC who underwent dynamic contrast-enhanced CT before and after neoadjuvant CRT. A 5-point score was used to determine arterial involvement (A score; 1 = no involvement, 2 = haziness, 3 = abutment, 4 = encasement, 5 = deformity) and 4-point score evaluating resectability status (R score; 1 = resectable, 2 = borderline resectable [BR] with venous involvement, 3 = BR with arterial involvement, 4 = locally advanced [LA]). A score before and after CRT were summed with R score before and after CRT to compute the AR score (AR_total). The associations between AR_total, R0 resection, overall survival (OS), and disease-free survival (DFS) were assessed.

RESULTS

The AR_total was associated with R0 resection (p < .001) and showed area under the ROC curve of 0.79 for differentiating R0 and R1 resections. Median OS was significantly lower for patients with AR_total  > 9 (median: 35.2 months) compared to patients with AR_total ≤ 9 (median: not estimable) (p < .001). Similar results were observed for DFS (median, 16.8 months in > 9 vs median, not estimable in ≤ 9; p < .001).

CONCLUSIONS

A composite score which incorporates degree of arterial involvement and resectability status before and after neoadjuvant CRT is associated with R0 resection and discriminates between R0 and R1 resections in PDAC.

KEY POINTS

• A scoring system incorporating arterial involvement and resectability status was associated with R0 resection. • AR_total >  9 could predict patients' overall and disease-free survival.

Predictors of conversion surgery in patients with pancreatic cancer who underwent neoadjuvant or palliative FOLFIRINOX treatment using baseline and follow-up CT

PURPOSE

We aimed to evaluate the predictive factors of conversion surgery in pancreatic adenocarcinoma (PAC) after neoadjuvant or palliative FOLFIRINOX using baseline and follow-up CT.

METHODS

We retrospectively included 189 patients who had undergone more than 4 cycles of FOLFIRINOX. We reviewed baseline CT (B-CT), 1st follow-up CT (1st-CT), and the preoperative or last follow-up CT (L-CT) and determined tumor size changes according to the Response Evaluation Criteria in Solid Tumors (RECIST 1.1). Extra-pancreatic perineural invasion (EPNI) and resectability using NCCN 2019 guideline were evaluated. Subgroup analysis by baseline resectability was performed.

RESULTS

B-CT included resectable (n = 25, 23.2%), borderline (n = 55, 29.1%), locally advanced (n = 44, 23.3%), and metastatic (n = 65, 34.4%) PAC. Seventy-four patients had undergone surgery (39.2%) with an 83.8% (62/74) R0 resection. For operability, resectable status at L-CT (hazard ratio (HR) 65.5; 95% confidence interval (CI) 5.0-865; P = 0.002), RECIST (partial response) at 1st-CT (HR 3.6; 95% CI 1.1-11.7; P = 0.032), and baseline borderline resectability (HR 8.6; 95% CI 1.6-46.4; P = 0.013) were important predictors. Based on a size reduction cut-off of 22.2%, the area under the receiver operating characteristic (ROC) curve (Az) was 0.761 (sensitivity = 70.3%, specificity = 74.8%). In subgroup analysis, RECIST (partial response) at 1st-CT was a significant predictor of locally advanced PAC (HR 32; 95% CI 4.5-227, P 0.001), and the optimal cut-off was 22.2% (Az = 0.914; sensitivity = 100%, specificity = 75%). Baseline tumor size ([Formula: see text] 4 cm) (HR 5.6, 95% CI 1.3-24.3, P = 0.022) and unresectable status at 1st-CT (HR 4.8, 95% CI 1.1-20.6, P = 0.035) were significantly associated with margin-positive resection.

CONCLUSION

Both baseline and follow-up CT findings are useful to predict conversion surgery for PAC after FOLFIRINOX.

DeepPrognosis: Preoperative prediction of pancreatic cancer survival and surgical margin via comprehensive understanding of dynamic contrast-enhanced CT imaging and tumor-vascular contact parsing

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and carries a dismal prognosis of ∼10% in five year survival rate. Surgery remains the best option of a potential cure for patients who are evaluated to be eligible for initial resection of PDAC. However, outcomes vary significantly even among the resected patients who were the same cancer stage and received similar treatments. Accurate quantitative preoperative prediction of primary resectable PDACs for personalized cancer treatment is thus highly desired. Nevertheless, there are a very few automated methods yet to fully exploit the contrast-enhanced computed tomography (CE-CT) imaging for PDAC prognosis assessment. CE-CT plays a critical role in PDAC staging and resectability evaluation. In this work, we propose a novel deep neural network model for the survival prediction of primary resectable PDAC patients, named as 3D Contrast-Enhanced Convolutional Long Short-Term Memory network (CE-ConvLSTM), which can derive the tumor attenuation signatures or patterns from patient CE-CT imaging studies. Tumor-vascular relationships, which might indicate the resection margin status, have also been proven to hold strong relationships with the overall survival of PDAC patients. To capture such relationships, we propose a self-learning approach for automated pancreas and peripancreatic anatomy segmentation without requiring any annotations on our PDAC datasets. We then employ a multi-task convolutional neural network (CNN) to accomplish both tasks of survival outcome and margin prediction where the network benefits from learning the resection margin related image features to improve the survival prediction. Our presented framework can improve overall survival prediction performances compared with existing state-of-the-art survival analysis approaches. The new staging biomarker integrating both the proposed risk signature and margin prediction has evidently added values to be combined with the current clinical staging system.

Effect of deep learning image reconstruction in the prediction of resectability of pancreatic cancer: Diagnostic performance and reader confidence

OBJECTIVE

To assess the diagnostic performance and reader confidence in determining the resectability of pancreatic cancer at computed tomography (CT) using a new deep learning image reconstruction (DLIR) algorithm.

METHODS

A retrospective review was conduct of on forty-seven patients with pathologically confirmed pancreatic cancers who underwent baseline multiphasic contrast-enhanced CT scan. Image data sets were reconstructed using filtered back projection (FBP), hybrid model-based adaptive statistical iterative reconstruction (ASiR-V) 60 %, and DLIR "TrueFidelity" at low(L), medium(M), and high strength levels(H). Four board-certified abdominal radiologists reviewed the CT images and classified cancers as resectable, borderline resectable, or unresectable. Diagnostic performance and reader confidence for categorizing the resectability of pancreatic cancer were evaluated based on the reference standards, and the interreader agreement was assessed using Fleiss k statistics.

RESULTS

For prediction of margin-negative resections(ie, R0), the average area under the receiver operating characteristic curve was significantly higher with DLIR-H (0.91; 95 % confidence interval [CI]: 0.79, 0.98) than FBP (0.75; 95 % CI:0.60, 0.86) and ASiR-V (0.81; 95 % CI:0.67, 0.91) (p = 0.030 and 0.023 respectively). Reader confidence scores were significantly better using DLIR compared to FBP and ASiR-V 60 % and increased linearly with the increase of DLIR strength level (all p < 0.001). Among the image reconstructions, DLIR-H showed the highest interreader agreement in the resectability classification and lowest subject variability in the reader confidence.

CONCLUSIONS

The DLIR-H algorithm may improve the diagnostic performance and reader confidence in the CT assignment of the local resectability of pancreatic cancer while reducing the interreader variability.

Simulated twin-phase pancreatic CT generated using single portal venous phase dual-energy CT acquisition in pancreatic ductal adenocarcinoma

PURPOSE

To evaluate the diagnostic performance of a simulated twin-phase pancreatic protocol CT generated from a single portal venous phase (PVP) dual-energy CT (DECT) acquisition in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

In this retrospective study, we included 63 patients with PDAC who underwent pancreatic protocol (pancreatic phase [PP] and PVP) DECT. Two data sets were created from this original acquisition-(1) Standard protocol (50 keV PP/65 keV PVP) and (2) Simulated protocol (40 keV/65 keV PVP). Using a 5-point scale, three readers scored image quality, tumor conspicuity, and arterial involvement by the PDAC. Signal-to-noise ratio (SNR) of the pancreas and tumor-to-pancreas contrast-to-noise ratio (CNR) were calculated. Qualitative scores, quantitative parameters, and radiation dose were compared between standard and simulated protocols.

RESULTS

No significant difference in detection rate of PDAC was seen between the standard (58/63, 92.1%) and simulated protocols (56/63, 88.9%) (P = 0.76). Subjective scoring for arterial involvement for celiac (P = 0.86), superior mesenteric (P = 0.88), splenic (P = 0.86), common hepatic (P = 0.52), gastroduodenal (P = 0.95), first jejunal (P = 0.48) arteries, and aorta (P = 1.00) were comparable between two protocols. The image quality (P = 0.14), the SNR of the pancreas (P = 0.15), and CNR (P = 0.54) were comparable between two protocols. The projected mean dose-length product (DLP) (629.6 ± 148.3 mGy cm) in the simulated protocol showed a 44% reduction in radiation dose compared to the standard protocol (mean DLP, 1123.3 ± 268.9 mGy cm) (P < 0.0001).

CONCLUSIONS

Low keV images generated from a PVP DECT acquisition allows creation of a twin-phase pancreatic protocol CT with comparable diagnostic accuracy for detecting PDAC with significant reduction in radiation dose. Reduced radiation dose is desirable in surveillance and screening for pancreatic diseases.

Preoperative CT predictors of survival in patients with pancreatic ductal adenocarcinoma undergoing curative intent surgery

PURPOSE

To evaluate the associations between computed tomography (CT) imaging features extracted from the structured American Pancreatic Association (APA)/Society of Abdominal Radiology (SAR) template and overall survival in patients with resected pancreatic ductal adenocarcinoma (PDAC).

METHODS

This retrospective analysis included consecutive patients with PDAC who consented to genomic tumor testing and underwent preoperative imaging and curative intent surgical resection from December 2006 to July 2017. Two radiologists assessed preoperative CT imaging using the APA/SAR PDAC-reporting template. Univariable associations between overall survival and imaging variables were evaluated using Cox proportional hazards regression.

RESULTS

The study included 168 patients (66 years ± 11; 91 women). 126/168 patients (75%) received upfront surgical resection whereas 42/168 (25%) received neoadjuvant therapy prior to surgical resection. In the entire cohort, features associated with decreased overall survival were tumor arterial contact of any kind (hazard ratio (HR) 1.89, 95% CI 1.13-3.14, p = 0.020), tumor contact with the common hepatic artery (HR 2.33, 95% CI 1.35-4.04, p = 0.009), and portal vein deformity (HR 3.22, 95% CI 1.63-6.37, p = 0.003). In the upfront surgical group, larger tumor size was associated with decreased overall survival (HR 2.30, 95% CI 1.19-4.42, p = 0.013). In the neoadjuvant therapy group, the presence of venous collaterals was the only feature associated with decreased overall survival (HR 2.28, 95% CI 1.04-4.99, p = 0.042).

CONCLUSION

The application of the APA/SAR pancreatic adenocarcinoma reporting template may identify predictors of survival that can aid in preoperative stratification of patients.

Low keV portal venous phase as a surrogate for pancreatic phase in a pancreatic protocol dual-energy CT: feasibility, image quality, and lesion conspicuity

OBJECTIVE

To assess the feasibility of a proposed pancreatic protocol CT generated from portal-venous phase (PVP) dual-energy CT (DECT) acquisition and its impact on image quality, lesion conspicuity, and arterial visualization/involvement.

METHODS

We included 111 patients (mean age, 66.8 years) who underwent pancreatic protocol DECT (pancreatic phase, PP, and PVP). The original DECT acquisition was used to create two data sets-standard protocol (50 keV PP/65 keV PVP) and proposed protocol (40 keV/65 keV PVP). Three reviewers evaluated the two data sets for image quality, lesion conspicuity, and arterial visualization/involvement using a 5-point scale. The signal-to-noise ratio (SNR) of pancreas and lesion-to-pancreas contrast-to-noise ratio (CNR) was calculated. Qualitative scores, quantitative parameters, and dose-length product (DLP) were compared between standard and proposed protocols.

RESULTS

The image quality, SNR of pancreas, and lesion-to-pancreas CNR of the standard and proposed protocol were comparable (p = 0.11-1.00). Lesion conspicuity was comparable between the standard and proposed protocols for pancreatic ductal adenocarcinoma (p = 0.55) and pancreatic cysts (p = 0.28). The visualization of larger arteries and arterial involvement were comparable between the two protocols (p = 0.056-1.00) while the scores were higher for smaller vessels in the standard protocol (p < 0.0001-0.0015). DLP of the proposed protocol (670.4 mGy·cm) showed a projected 42% reduction than the standard protocol (1145.9 mGy·cm) (p < 0.0001).

CONCLUSION

Pancreatic protocol CT generated from a single PVP DECT acquisition is feasible and could potentially be an alternative to the standard pancreatic protocol with PP and PVP.

KEY POINTS

• The lesion conspicuity for focal pancreatic lesions was comparable between the proposed protocol and standard dual-phase pancreatic protocol CT. • Qualitative and quantitative image assessments were almost comparable between two protocols. • The radiation dose of a proposed protocol showed a projected 42% reduction from the conventional protocol.

Preoperative assessment of the resectability of pancreatic ductal adenocarcinoma on CT according to the NCCN Guidelines focusing on SMA/SMV branch invasion

OBJECTIVES

For patients with pancreatic adenocarcinoma (PAC), adequate determination of disease extent is critical for optimal management. We aimed to evaluate diagnostic accuracy of CT in determining the resectability of PAC based on 2020 NCCN Guidelines.

METHODS

We retrospectively enrolled 368 consecutive patients who underwent upfront surgery for PAC and preoperative pancreas protocol CT from January 2012 to December 2017. The resectability of PAC was assessed based on 2020 NCCN Guidelines and compared to 2017 NCCN Guidelines using chi-square tests. Overall survival (OS) was estimated using the Kaplan-Meier method and compared using log-rank test. R0 resection-associated factors were identified using logistic regression analysis.

RESULTS

R0 rates were 80.8% (189/234), 67% (71/106), and 10.7% (3/28) for resectable, borderline resectable, and unresectable PAC according to 2020 NCCN Guidelines, respectively (p < 0.001). The estimated 3-year OS was 28.9% for borderline resectable PAC, which was significantly lower than for resectable PAC (43.6%) (p = 0.004) but significantly higher than for unresectable PAC (0.0%) (p < 0.001). R0 rate was significantly lower in patients with unresectable PAC according to 2020 NCCN Guidelines (10.7%, 3/28) than in those with unresectable PAC according to the previous version (31.7%, 20/63) (p = 0.038). In resectable PAC, tumor size ≥ 3 cm (p = 0.03) and abutment to portal vein (PV) (p = 0.04) were independently associated with margin-positive resection.

CONCLUSIONS

The current NCCN Guidelines are useful for stratifying patients according to prognosis and perform better in R0 prediction in unresectable PAC than the previous version. Larger tumor size and abutment to PV were associated with margin-positive resection in patients with resectable PAC.

KEY POINTS

• The updated 2020 NCCN Guidelines were useful for stratifying patients according to prognosis. • The updated 2020 NCCN Guidelines performed better in the prediction of margin-positive resection in unresectable cases than the previous version. • Tumor size ≥ 3 cm and abutment to the portal vein were associated with margin-positive resection in patients with resectable pancreatic adenocarcinoma.

Diagnosis of Pancreatic Ductal Adenocarcinoma by Immuno-Positron Emission Tomography

Diagnosis of pancreatic ductal adenocarcinoma (PDAC) by current imaging techniques is useful and widely used in the clinic but presents several limitations and challenges, especially in small lesions that frequently cause radiological tumors infra-staging, false-positive diagnosis of metastatic tumor recurrence, and common occult micro-metastatic disease. The revolution in cancer multi-"omics" and bioinformatics has uncovered clinically relevant alterations in PDAC that still need to be integrated into patients' clinical management, urging the development of non-invasive imaging techniques against principal biomarkers to assess and incorporate this information into the clinical practice. "Immuno-PET" merges the high target selectivity and specificity of antibodies and engineered fragments toward a given tumor cell surface marker with the high spatial resolution, sensitivity, and quantitative capabilities of positron emission tomography (PET) imaging techniques. In this review, we detail and provide examples of the clinical limitations of current imaging techniques for diagnosing PDAC. Furthermore, we define the different components of immuno-PET and summarize the existing applications of this technique in PDAC. The development of novel immuno-PET methods will make it possible to conduct the non-invasive diagnosis and monitoring of patients over time using in vivo, integrated, quantifiable, 3D, whole body immunohistochemistry working like a "virtual biopsy".

[Radiologic Evaluation for Resectability of Pancreatic Adenocarcinoma]

Imaging studies play an important role in the detection, diagnosis, assessment of resectability, staging, and determination of patient-tailored treatment options for pancreatic adenocarcinoma. Recently, for patients diagnosed with borderline resectable or locally advanced pancreatic cancers, it is recommended to consider curative-intent surgery following neoadjuvant or palliative therapy, if possible. This review covers how to interpret imaging tests and what to consider when assessing resectability, diagnosing distant metastasis, and re-assessing the resectability of pancreatic cancer after neoadjuvant or palliative therapy.

Hyperdense Pancreatic Ductal Adenocarcinoma: Clinical Characteristics and Proteomic Landscape

Purpose

Hypodensity of pancreatic ductal adenocarcinoma (PDAC) during contrast-enhanced computed tomography (CECT) examination is common, but a minority of PDAC patients exhibit hyperdense images. The present study examined the clinical characteristics and protein landscape of PDAC with hyperdensity.

Materials and Methods

A total of 844 pathologically confirmed PDAC patients who underwent CECT before surgery were included. During the parenchymal phase of CECT, patients were assigned to the hyperdense or hypodense group based on CT values. Clinical and CT characteristics for predicting relapse-free survival (RFS) and overall survival (OS) were analyzed using the Kaplan–Meier method and Cox proportional hazards model. The expression of the tumor angiogenesis marker CD31 and stroma-related protein CTHRC1 were analyzed using immunohistochemistry (IHC) assay to evaluate differences between the two groups. Proteomics was performed to compare the possible mechanisms underlying the differential enhancement on CT scans.

Results

Based on CECT, 43 and 801 PDAC patients had hyperdense and hypodense lesions, respectively. All 43 patients presented a hyperdense lesion in the parenchymal phase. The mean CECT values of the hyperdense group were higher than the hypodense group (102.5 ± 17.4 and 53.7 ± 18.7, respectively, P< 0.001). The hyperdense group had a better prognosis than the hypodense group (median RFS, 19.97 vs. 12.34 months, P = 0.0176; median OS, 33.6 vs. 20.3 months, P = 0.047). Multivariate analysis showed that age, higher CA19-9 levels (> 300 U/ml), tumor stage, tumor differentiation, tumor CT density, and adjuvant chemotherapy were significant independent prognostic factors for OS. CD31 immunohistochemical staining showed that the hyperdense PDACs had a higher microvessel density than the hypodense group (P< 0.001). CTHRC1 expression was higher in the hypodense group (P = 0.019). Sixty-eight differentially expressed proteins were found using the tandem mass tag labeling-based quantification of the proteomes of PDAC tissue samples, and 7 proteins (POFUT1, PKP2, P0DOX4, ITPR1, HBG2, IGLC3, SAA2) were related to angiogenesis.

Conclusion

Patients who presented with a hyperdense mass on CECT had a higher microvessel density and better prognosis. Anti-angiogenic therapy may be suitable for these patients.

Radiomics-Assisted Presurgical Prediction for Surgical Portal Vein-Superior Mesenteric Vein Invasion in Pancreatic Ductal Adenocarcinoma

Objectives

To develop a radiomics signature for predicting surgical portal vein-superior mesenteric vein (PV-SMV) in patients with pancreatic ductal adenocarcinoma (PDAC) and measure the effect of providing the predictions of radiomics signature to radiologists with different diagnostic experiences during imaging interpretation.

Methods

Between February 2008 and June 2020, 146 patients with PDAC in pancreatic head or uncinate process from two institutions were retrospectively included and randomly split into a training (n = 88) and a validation (n =58) cohort. Intraoperative vascular exploration findings were used to identify surgical PV-SMV invasion. Radiomics features were extracted from the portal venous phase CT images. Radiomics signature was built with a linear elastic-net regression model. Area under receiver operating characteristic curve (AUC) of the radiomics signature was calculated. A senior and a junior radiologist independently review CT scans and made the diagnosis for PV-SMV invasion both with and without radiomics score (Radscore) assistance. A 2-sided Pearson's chi-squared test was conducted to evaluate whether there was a difference in sensitivity, specificity, and accuracy between the radiomics signature and the unassisted radiologists. To assess the incremental value of providing Radscore predictions to the radiologists, we compared the performance between unassisted evaluation and Radscore-assisted evaluation by using the McNemar test.

Results

Numbers of patients identified as presence of surgical PV-SMV invasion were 33 (37.5%) and 19 (32.8%) in the training and validation cohort, respectively. The radiomics signature achieved an AUC of 0.848 (95% confidence interval, 0.724-0.971) in the validation cohort and had a comparable sensitivity, specificity, and accuracy as the senior radiologist in predicting PV-SMV invasion (all p-values > 0.05). Providing predictions of radiomics signature increased both radiologists' sensitivity in identifying PV-SMV invasion, while only the increase of the junior radiologist was significant (63.2 vs 89.5%, p-value = 0.025) instead of the senior radiologist (73.7 vs 89.5%, p-value = 0.08). Both radiologists' accuracy had no significant increase when provided radiomics signature assistance (both p-values > 0.05).

Conclusions

The radiomics signature can predict surgical PV-SMV invasion in patients with PDAC and may have incremental value to the diagnostic performance of radiologists during imaging interpretation.

Use of imaging as staging and surgical planning for pancreatic surgery

Importance

In the past few decades, there has been rapid advancements in imaging technologies that have become irreplaceable in the pre-operative assessment of patients with pancreatic tumors. Modern imaging modalities, including computed tomography (CT) and endoscopic ultrasound (EUS), can provide critical information of the absence or presence of metastatic disease in pancreatic cancer, as well as details on the local extent and resectability, allowing for the selection of stage appropriate treatments and pre-operatively determined surgical approach.

Objective

The aim of this review is to discuss staging, resectability, and imaging for patients with pancreatic tumors.

Evidence Review

A literature review was performed of articles relevant to the topics of staging, resectability, and imaging of pancreatic tumors. Imaging modalities included CT, EUS, magnetic resonance imaging (MRI), positron emission tomography (PET), antibody-based and narrow band imaging.

Findings

CT pancreas protocol combined with EUS serve as the primary modalities in diagnosis, staging, and surgical planning in patients with pancreatic tumors. MRI is an alternative to CT with near equivalent utility in the pre-operative setting. In some circumstances, PET-CT may be a cost-effective initial study to detect distant disease.

Conclusions and Relevance

Current imaging technologies play a critical role in the evaluation of patients with pancreatic tumors. Advances in the past 3 decades in imaging technologies have revolutionized the process of assessment of stage and resectability in patients with pancreatic tumors. Future imaging technologies will address current limitation in the evaluation of occult metastatic disease.

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.