Visually isoattenuating pancreatic adenocarcinoma at dynamic-enhanced CT: frequency, clinical and pathologic characteristics, and diagnosis at imaging examinations

Imaging for Early Detection of Pancreatic Ductal Adenocarcinoma: Updates and Challenges in the Implementation of Screening and Surveillance Programs

Pancreatic ductal adenocarcinoma (PDA) is one of the most aggressive cancers. It has a poor 5-year survival rate of 12%, partly because most cases are diagnosed at advanced stages, precluding curative surgical resection. Early-stage PDA has significantly better prognoses due to increased potential for curative interventions, making early detection of PDA critically important to improved patient outcomes. We examine current and evolving early detection concepts, screening strategies, diagnostic yields among high-risk individuals, controversies, and limitations of standard-of-care imaging.

Preliminary study on the ability of the machine learning models based on 18F-FDG PET/CT to differentiate between mass-forming pancreatic lymphoma and pancreatic carcinoma

PURPOSE

The objective of this study was to preliminarily assess the ability of metabolic parameters and radiomics derived from 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) to distinguish mass-forming pancreatic lymphoma from pancreatic carcinoma using machine learning.

METHODS

A total of 88 lesions from 86 patients diagnosed as mass-forming pancreatic lymphoma or pancreatic carcinoma were included and randomly divided into a training set and a validation set at a 4-to-1 ratio. The segmentation of regions of interest was performed using ITK-SNAP software, PET metabolic parameters and radiomics features were extracted using 3Dslicer and PYTHON. Following the selection of optimal metabolic parameters and radiomics features, Logistic regression (LR), support vector machine (SVM), and random forest (RF) models were constructed for PET metabolic parameters, CT radiomics, PET radiomics, and PET/CT radiomics. Model performance was assessed in terms of area under the curve (AUC), accuracy, sensitivity, and specificity in both the training and validation sets.

RESULTS

Strong discriminative ability observed in all models, with AUC values ranging from 0.727 to 0.978. The highest performance exhibited by the combined PET and CT radiomics features. AUC values for PET/CT radiomics models in the training set were LR 0.994, SVM 0.994, RF 0.989. In the validation set, AUC values were LR 0.909, SVM 0.883, RF 0.844.

CONCLUSION

Machine learning models utilizing the metabolic parameters and radiomics of 18F-FDG PET/CT show promise in distinguishing between pancreatic carcinoma and mass-forming pancreatic lymphoma. Further validation on a larger cohort is necessary before practical implementation in clinical settings.

Pancreatic ductal adenocarcinoma: the latest on diagnosis, molecular profiling, and systemic treatments

Pancreatic ductal adenocarcinoma (PDAC) is currently the fourth leading cause of death in the United States and is expected to be ranked second in the next 10 years due to poor prognosis and a rising incidence. Distant metastatic PDAC is associated with the worst prognosis among the different phases of PDAC. The diagnostic options for PDAC are convenient and available for staging, tumor response evaluation, and management of resectable or borderline resectable PDAC. However, imaging is crucial in PDAC diagnosis, monitoring, resectability appraisal, and response evaluation. The advancement of medical technologies is evolving, hence the use of imaging in PDAC treatment options has grown as well as the utilization of ctDNA as a tumor marker. Treatment options for metastatic PDAC are minimal with the primary goal of therapy limited to symptom relief or palliation, especially in patients with low functional capacity at the point of diagnosis. Molecular profiling has shown promising potential solutions that would push the treatment boundaries for patients with PDAC. In this review, we will discuss the latest updates from evidence-based guidelines regarding diagnosis, therapy response evaluation, prognosis, and surveillance, as well as illustrating novel therapies that have been recently investigated for PDAC, in addition to discussing the molecular profiling advances in PDAC.

Imaging of pancreatic ductal adenocarcinoma - An update for all stages of patient management

Background

Pancreatic ductal adenocarcinoma (PDAC) is a common and lethal cancer. From diagnosis to disease staging, response to neoadjuvant therapy assessment and patient surveillance after resection, imaging plays a central role, guiding the multidisciplinary team in decision-planning.

Review aims and findings

This review discusses the most up-to-date imaging recommendations, typical and atypical findings, and issues related to each step of patient management. Example cases for each relevant condition are presented, and a structured report for disease staging is suggested.

Conclusion

Despite current issues in PDAC imaging at different stages of patient management, the radiologist is essential in the multidisciplinary team, as the conveyor of relevant imaging findings crucial for patient care.

Rim Enhancement on Contrast-Enhanced CT as a Predictor of Prognosis in Patients with Pancreatic Ductal Adenocarcinoma

This study investigated the utility of imaging features, such as rim enhancement on contrast-enhanced CT (CECT), in predicting the prognosis of pancreatic ductal adenocarcinoma (PDAC). This retrospective study included 158 patients (84 men; mean age, 68 years) with pathologically confirmed PDAC. The following imaging features were evaluated on CECT by two radiologists: tumor size, tumor attenuation, and the presence of rim enhancement. Cox proportional hazards analysis was performed to identify the imaging and clinicopathological features for predicting disease-free survival (DFS) and overall survival (OS). Pathological features were compared with the presence of rim enhancement. Among the 158 patients, 106 (67%) underwent curative surgery (surgery group) and 52 (33%) received conservative treatment (non-surgery group). Rim enhancement was observed more frequently in the non-surgery group than in the surgery group (44% vs. 20%; p < 0.001). Rim enhancement showed significant associations with shorter DFS and OS in the surgery group (hazard ratios (HRs), 3.03 and 2.99; p < 0.001 and p = 0.003, respectively), whereas tumor size showed significant associations with shorter OS (HR per 1 mm increase, 1.08; p < 0.001). PDACs with rim enhancement showed significant associations with higher histological tumor grades (p < 0.001). PDAC with rim enhancement on CECT could predict poorer prognosis and more aggressive tumor grades.

Endoscopic Ultrasound Can Differentiate High-Grade Pancreatic Intraepithelial Neoplasia, Small Pancreatic Ductal Adenocarcinoma, and Benign Stenosis

Background/Aims

High-grade pancreatic intraepithelial neoplasia and invasive pancreatic ductal adenocarcinoma ≤10 mm are targets for early detection of pancreatic cancer. However, their imaging characteristics are unknown. We aimed to identify endoscopic ultrasound findings for the detection of these lesions.

Methods

Patients diagnosed with high-grade pancreatic intraepithelial neoplasia (n=29), pancreatic ductal adenocarcinoma ≤10 mm (n=11) (who underwent surgical resection), or benign main pancreatic duct stenosis (n=20) between January 2014 and January 2021 were retrospectively included. Six features differentiating these lesions were examined by endoscopic ultrasonography: main pancreatic duct stenosis, upstream main pancreatic duct dilation, hypoechoic areas surrounding the main pancreatic duct irregularities (mottled areas without demarcation or round areas with demarcation), branch duct dilation, prominent lobular segmentation, and atrophy. Interobserver agreement was assessed by two independent observers.

Results

Hypoechoic areas surrounding the main pancreatic duct irregularities were observed more frequently in high-grade pancreatic intraepithelial neoplasia (82.8%) and pancreatic ductal adenocarcinoma ≤10 mm (90.9%) than in benign stenosis (15.0%) (p<0.001). High-grade pancreatic intraepithelial neoplasia exhibited mottled hypoechoic areas more frequently (79.3% vs 18.9%, p<0.001), and round hypoechoic areas less frequently (3.4% vs 72.7%, p<0.001), than pancreatic ductal adenocarcinoma ≤10 mm. The sensitivity and specificity of hypoechoic areas for differentiating high-grade pancreatic intraepithelial neoplasia, pancreatic ductal adenocarcinoma ≤10 mm, and benign stenosis were both 85.0%, with moderate interobserver agreement.

Conclusions

The hypoechoic areas surrounding main pancreatic duct irregularities on endoscopic ultrasound may differentiate between high-grade pancreatic intraepithelial neoplasia, pancreatic ductal adenocarcinoma ≤10 mm, and benign stenosis (Trial Registration: UMIN Clinical Trials Registry (UMIN000044789).

Pancreatic ductal adenocarcinoma: CEUS characteristics are correlated with pathological findings and help predict early recurrence after resection

OBJECTIVES

To identify characteristics of preoperative contrast-enhanced ultrasound (CEUS) that could predict early recurrence after curative resection of pancreatic ductal adenocarcinoma (PDAC).

METHODS

From January 2017 to September 2022, a total of 110 patients with PDAC (all confirmed by samples obtained via operation) who underwent CEUS within 1 month before surgery were enrolled. We proposed five CEUS enhancement patterns (Pattern I, homogeneous enhancement; Pattern II, heterogeneous enhancement without cystic components; pattern III, ring enhancement; Pattern IV, starry enhancement; Pattern V, heterogeneous enhancement with cystic components) of PDAC. Clinical-pathologic and CEUS characteristics for predicting early recurrence (recurrence within 1 year after curative resection) were analyzed. Important CEUS characteristics were compared with the pathological findings.

RESULTS

Tumor size and TNM stage were closely associated with early recurrence. Incomplete-enhancement and enhancement pattern III, IV and V at CEUS imaging were more prone to early recurrence. Incomplete-enhancement lesions had higher histological tumor grades, less frequent remaining acini, and more frequent necrosis within the tumor. PDACs with pattern I and II had lower histological tumor grades, and pattern III, IV and V had higher histological tumor grades. PDACs with pattern I, II and IV had less frequent intratumoral necrosis than PDACs with pattern III and V, and PDACs with pattern IV had lower MVD values.

CONCLUSIONS

PDACs with incomplete enhancement and enhancement pattern III, IV and V were more prone to early recurrence after attempted curative resection, and these important CEUS characteristics were closely related to the pathological findings of PDAC.

Qualitative flow metabolic phenotype of pancreatic cancer. A new prognostic biomarker?

BACKGROUND

Retrospective analysis to investigate the relationship between the flow-metabolic phenotype and overall survival (OS) of pancreatic ductal adenocarcinoma (PDAC) and its potential clinical utility.

METHODS

Patients with histopathologically proven PDAC between 2005 and 2014 using tumor attenuation on routine pre-operative CECT as a surrogate for the vascularity and [18F]FDG-uptake as a surrogate for metabolic activity on [18F]FDG-PET.

RESULTS

In total, 93 patients (50 male, 43 female, median age 63) were included. Hypoattenuating PDAC with high [18F]FDG-uptake has the poorest prognosis (median OS 7 ± 1 months), compared to hypoattenuating PDAC with low [18F]FDG-uptake (median OS 11 ± 3 months; p = 0.176), iso- or hyperattenuating PDAC with high [18F]FDG-uptake (median OS 15 ± 5 months; p = 0.004) and iso- or hyperattenuating PDAC with low [18F]FDG-uptake (median OS 23 ± 4 months; p = 0.035). In multivariate analysis, surgery combined with tumor differentiation, tumor stage, systemic therapy and flow metabolic phenotype remained independent predictors for overall survival.

DISCUSSION

The novel qualitative flow-metabolic phenotype of PDAC using a combination of CECT and [18F]FDG-PET features, predicted significantly worse survival for hypoattenuating-high uptake pancreatic cancers compared to the other phenotypes.

18F-FDG PET/CT assists the diagnosis of primary pancreatic lymphoma: Two case reports and literature review

Primary pancreatic lymphoma (PPL) is a rare malignancy, which is defined as a mass centered in pancreas with involvement of contiguous lymph nodes and distant spread may exist. Accurate diagnosis of PPL prior to pathological confirmation remains challenging, underscoring the critical significance of preoperative imaging assessments. This case report collected two instances of PPL that underwent initial evaluation via 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) between August 2021 and July 2022. Correspondingly, pertinent literature encompassing 18F-FDG PET/CT data related to PPL was meticulously reviewed. Including our aforementioned pair of cases, a cumulative total of 25 instances of PPL were assembled. The distinctive profile of 18F-FDG PET/CT images of PPL predominantly manifests as hypermetabolic lesions with diminished density. Primarily characterized by singular lesions and comparatively substantial volumetric dimensions, a total of eleven cases revealed contiguous lymph node engagement, with five instances displaying distant dissemination encompassing lymph nodes in multiple locations. Amongst these, ten patients underwent sequential 18F-FDG PET/CT follow-up post-intervention. In comparison to pancreatic carcinoma, PPL lesions exhibited heightened hypermetabolism, augmented volumetric proportions, and distinct patterns of distant metastasis. This study indicates that the pivotal role of 18F-FDG PET/CT in the diagnosis and assessment of therapeutic efficacy in PPL is unequivocal. Combined with the clinical attributes of patients, the integration of 18F-FDG PET/CT augments the differential diagnostic capacity differentiating PPL from pancreatic carcinoma.

Preoperative evaluating early recurrence in resectable pancreatic ductal adenocarcinoma by using CT radiomics

OBJECTIVE

To investigate the feasibility of a radiomics model based on contrast-enhanced CT for preoperatively predicting early recurrence after curative resection in patients with resectable pancreatic ductal adenocarcinoma (PDAC).

METHODS

One hundred and eighty-six patients with resectable PDAC who underwent curative resection were included and allocated to training set (131 patients) and validation set (55 patients). Radiomics features were extracted from arterial phase and portal venous phase images. The Mann-Whitney U test and least absolute shrinkage and selection operator (LASSO) regression were used for feature selection and radiomics signature construction. The radiomics model based on radiomics signature and clinical features was developed by the multivariate logistic regression analysis. Performance of the radiomics model was investigated by the area under the receiver operating characteristic (ROC) curve.

RESULTS

The radiomics signature, consisting of three arterial phase and three venous phase features, showed optimal prediction performance for early recurrence in both training (AUC = 0.73) and validation sets (AUC = 0.66). Multivariate logistic analysis identified the radiomics signature (OR, 2.58; 95% CI 2.36-3.17; p = 0.002) and clinical stage (OR, 1.60; 95% CI 1.15-2.30; p = 0.007) as independent predictors. The AUC values for risk evaluation of early recurrence using the radiomics model incorporating clinical stage were 0.80 (training set) and 0.75 (validation set).

CONCLUSION

The radiomics-based model integrating with clinical stage can predict early recurrence after upfront surgery in patients with resectable PDAC.

Automated Quantitative Analysis of CT Perfusion to Classify Vascular Phenotypes of Pancreatic Ductal Adenocarcinoma

CT perfusion (CTP) analysis is difficult to implement in clinical practice. Therefore, we investigated a novel semi-automated CTP AI biomarker and applied it to identify vascular phenotypes of pancreatic ductal adenocarcinoma (PDAC) and evaluate their association with overall survival (OS).

METHODS

From January 2018 to November 2022, 107 PDAC patients were prospectively included, who needed to undergo CTP and a diagnostic contrast-enhanced CT (CECT). We developed a semi-automated CTP AI biomarker, through a process that involved deformable image registration, a deep learning segmentation model of tumor and pancreas parenchyma volume, and a trilinear non-parametric CTP curve model to extract the enhancement slope and peak enhancement in segmented tumors and pancreas. The biomarker was validated in terms of its use to predict vascular phenotypes and their association with OS. A receiver operating characteristic (ROC) analysis with five-fold cross-validation was performed. OS was assessed with Kaplan-Meier curves. Differences between phenotypes were tested using the Mann-Whitney U test.

RESULTS

The final analysis included 92 patients, in whom 20 tumors (21%) were visually isovascular. The AI biomarker effectively discriminated tumor types, and isovascular tumors showed higher enhancement slopes (2.9 Hounsfield unit HU/s vs. 2.0 HU/s, p < 0.001) and peak enhancement (70 HU vs. 47 HU, p < 0.001); the AUC was 0.86. The AI biomarker's vascular phenotype significantly differed in OS (p < 0.01).

CONCLUSIONS

The AI biomarker offers a promising tool for robust CTP analysis. In PDAC, it can distinguish vascular phenotypes with significant OS prognostication.

Preoperative prediction of disease-free survival in pancreatic ductal adenocarcinoma patients after R0 resection using contrast-enhanced CT and CA19-9

OBJECTIVES

To investigate the efficiency of a combination of preoperative contrast-enhanced computed tomography (CECT) and carbohydrate antigen 19-9 (CA19-9) in predicting disease-free survival (DFS) after R0 resection of pancreatic ductal adenocarcinoma (PDAC).

METHODS

A total of 138 PDAC patients who underwent curative R0 resection were retrospectively enrolled and allocated chronologically to training (n = 91, January 2014-July 2019) and validation cohorts (n = 47, August 2019-December 2020). Using univariable and multivariable Cox regression analyses, we constructed a preoperative clinicoradiographic model based on the combination of CECT features and serum CA19-9 concentrations, and validated it in the validation cohort. The prognostic performance was evaluated and compared with that of postoperative clinicopathological and tumor-node-metastasis (TNM) models. Kaplan-Meier analysis was conducted to verify the preoperative prognostic stratification performance of the proposed model.

RESULTS

The preoperative clinicoradiographic model included five independent prognostic factors (tumor diameter on CECT > 4 cm, extrapancreatic organ infiltration, CECT-reported lymph node metastasis, peripheral enhancement, and preoperative CA19-9 levels > 180 U/mL). It better predicted DFS than did the postoperative clinicopathological (C-index, 0.802 vs. 0.787; p < 0.05) and TNM (C-index, 0.802 vs. 0.711; p < 0.001) models in the validation cohort. Low-risk patients had significantly better DFS than patients at the high-risk, defined by the model preoperatively (p < 0.001, training cohort; p < 0.01, validation cohort).

CONCLUSIONS

The clinicoradiographic model, integrating preoperative CECT features and serum CA19-9 levels, helped preoperatively predict postsurgical DFS for PDAC and could facilitate clinical decision-making.

CLINICAL RELEVANCE STATEMENT

We constructed a simple model integrating clinical and radiological features for the prediction of disease-free survival after curative R0 resection in patients with pancreatic ductal adenocarcinoma; this novel model may facilitate preoperative identification of patients at high risk of recurrence and metastasis that may benefit from neoadjuvant treatments.

KEY POINTS

• Existing clinicopathological predictors for prognosis in pancreatic ductal adenocarcinoma (PDAC) patients who underwent R0 resection can only be ascertained postoperatively and do not allow preoperative prediction. • We constructed a clinicoradiographic model, using preoperative contrast-enhanced computed tomography (CECT) features and preoperative carbohydrate antigen 19-9 (CA19-9) levels, and presented it as a nomogram. • The presented model can predict disease-free survival (DFS) in patients with PDAC better than can postoperative clinicopathological or tumor-node-metastasis (TNM) models.

Pancreas CT assessment for pancreatic ductal adenocarcinoma resectability: effect of tube voltage and slice thickness on image quality and diagnostic performance

OBJECTIVES

To assess the resectability of pancreatic ductal adenocarcinoma (PDAC), the evaluation of tumor vascular contact holds paramount significance. This study aimed to compare the image quality and diagnostic performance of high-resolution (HR) pancreas computed tomography (CT) using an 80 kVp tube voltage and a thin slice (1 mm) for assessing PDAC resectability, in comparison with the standard protocol CT using 120 kVp.

METHODS

This research constitutes a secondary analysis originating from a multicenter prospective study. All participants underwent both the standard protocol pancreas CT using 120 kVp with 3 mm slice thickness (ST) and HR-CT utilizing an 80 kVp tube voltage and 1 mm ST. The contrast-to-noise ratio (CNR) between parenchyma and tumor, along with the degree of enhancement of the abdominal aorta and main portal vein (MPV), were measured and subsequently compared. Additionally, the likelihood of margin-negative resection (R0) was evaluated using a five-point scale. The diagnostic performance of both CT protocols in predicting R0 resection was assessed through the area under the receiver operating characteristic curve (AUC).

RESULTS

A total of 69 patients (37 males and 32 females; median age, 66.5 years) were included in the study. The median CNR of PDAC was 10.4 in HR-CT, which was significantly higher than the 7.1 in the standard CT (P=0.006). Furthermore, HR-CT demonstrated notably higher median attenuation values for both the abdominal aorta (579.5 HU vs. 327.2 HU; P=0.002) and the MPV (263.0 HU vs. 175.6 HU; P=0.004) in comparison with standard CT. Following surgery, R0 resection was achieved in 51 patients. The pooled AUC for HR-CT in predicting R0 resection was 0.727, slightly exceeding the 0.699 of standard CT, albeit lacking a significant statistical distinction (P=0.128).

CONCLUSION

While HR pancreas CT using 80 kVp offered a notably greater degree of contrast enhancement in vessels and a higher CNR for PDAC compared to standard CT, its diagnostic performance in predicting R0 resection remained statistically comparable.

The role of abdominal ultrasonography in patients with isoattenuating pancreatic carcinoma

AIMS

The main objective of this study was to determine the sensitivity of abdominal ultrasonography (US) in patients with isoattenuating pancreatic carcinoma and to compare the frequency of secondary signs on abdominal US and endoscopic ultrasonography (EUS) in these tumours.

METHODS

Twenty-four patients with histologically or cytologically verified isoattenuating pancreatic carcinoma who underwent abdominal US, contrast-enhanced CT and EUS of the pancreas as part of the diagnostic workup were included in this retrospective study. The sensitivity of abdominal US in detecting the isoattenuating pancreatic carcinoma was investigated and the frequency of secondary signs of isoattenuating pancreatic carcinoma on abdominal US and EUS was compared.

RESULTS

In 5 of 24 patients (21%) with isoattenuating pancreatic carcinoma, a hypoechogenic pancreatic lesion was directly visualised on abdominal US. Secondary signs were present on US in 21 patients (88%). These included dilatation of the common bile duct and/or intrahepatic bile ducts in 19/24 (79%), dilatation of the pancreatic duct in 3/24 (13%), abnormal contour/inhomogeneity of the pancreas in 1/24 (4%), and atrophy of the distal parenchyma in 1/24 (4%). Pancreatic duct dilatation was observed more frequently on EUS than on abdominal US (P=0.002). For other secondary signs, there was no significant difference in their detection on abdominal US and EUS (P=0.61-1.00).

CONCLUSION

Abdominal US is capable of detecting secondary signs of isoattenuating pancreatic carcinoma with high sensitivity and has the potential to directly visualise these tumours.

PET/MRI for evaluation of patients with pancreatic cancer

Pancreatic cancers are the third leading cause of cancer-related death in the USA and outcomes remain poor despite improvements in imaging and treatment paradigms. Currently, computed tomography (CT) and magnetic resonance imaging (MRI) are frequently utilized for staging and restaging of these malignancies, but positron emission tomography (PET)/CT can play a role in troubleshooting and improve whole-body staging. PET/MRI is a novel imaging modality that allows for simultaneous acquisition of PET and MRI images, leading to improved image quality and potential increased sensitivity. Early studies suggest that PET/MRI may play a larger role in pancreatic cancer imaging in future. This manuscript will briefly discuss current imaging approaches to pancreatic cancer and outline existing evidence and published data supporting the use of PET/MRI for pancreatic cancers.

The role of subspecialized radiologist reviews in preoperative conference for hepato-pancreato-biliary disease

PURPOSE

To identify the role of subspecialized radiologists in preoperative conferences of radiologists and surgeons in the management of hepato-pancreato-biliary (HPB) diseases.

METHODS

We retrospectively evaluated the prospective data of 247 patients (mean age, 63.8 years; 173 men) who were referred for preoperative conferences (n = 258; 11 were discussed twice) for HPB disease between September 2021 and April 2022. Before each preoperative conference, subspecialized radiologists reviewed all available imaging studies and treatment plan information. After each conference, any change to the treatment plan was documented (major, minor, or none). Additional information provided by the radiologists was collected (significant, supplementary, or none). Uni- and multivariable analyses were performed to determine factors that resulted in a major change to the treatment plan.

RESULTS

Of the 258 reviewed cases, a major change was made to the treatment plan in 26 cases (10.1 %) and a minor change in 41 (15.9 %). Significant information was provided in 27 cases (10.5 %) and supplementary information in 72 (27.9 %). In the multivariable analysis, additional information about local tumor extent (odds ratio [OR], 6.3; 95 % confidence interval [CI], 2.1-19.5; p = 0.001) and distant metastasis detection (OR, 33.2; 95 % CI, 5.1-216.6; p < 0.001) was significantly associated with a major change.

CONCLUSION

The involvement of subspecialized radiologists in preoperative conferences resulted in major treatment plan changes in 10.1 % of the cases, primarily associated with the added information about local tumor extent and distant metastasis.

Pancreatic Ductal Adenocarcinoma: Update of CT-Based Radiomics Applications in the Pre-Surgical Prediction of the Risk of Post-Operative Fistula, Resectability Status and Prognosis

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is the seventh leading cause of cancer-related deaths worldwide. Surgical resection is the main driver to improving survival in resectable tumors, while neoadjuvant treatment based on chemotherapy (and radiotherapy) is the best option-treatment for a non-primally resectable disease. CT-based imaging has a central role in detecting, staging, and managing PDAC. As several authors have proposed radiomics for risk stratification in patients undergoing surgery for PADC, in this narrative review, we have explored the actual fields of interest of radiomics tools in PDAC built on pre-surgical imaging and clinical variables, to obtain more objective and reliable predictors.

METHODS

The PubMed database was searched for papers published in the English language no earlier than January 2018.

RESULTS

We found 301 studies, and 11 satisfied our research criteria. Of those included, four were on resectability status prediction, three on preoperative pancreatic fistula (POPF) prediction, and four on survival prediction. Most of the studies were retrospective.

CONCLUSIONS

It is possible to conclude that many performing models have been developed to get predictive information in pre-surgical evaluation. However, all the studies were retrospective, lacking further external validation in prospective and multicentric cohorts. Furthermore, the radiomics models and the expression of results should be standardized and automatized to be applicable in clinical practice.

Prediction of postoperative recurrence in resectable pancreatic body/tail adenocarcinoma: a novel risk stratification approach using a CT-based nomogram

OBJECTIVES

To identify prognostic CT features that predict recurrence in patients with resectable pancreatic body/tail adenocarcinoma (PBTA) and construct a CT-based nomogram for preoperative risk stratification.

METHODS

A total of 258 patients with resectable PBTA who underwent upfront surgery were retrospectively enrolled (development cohort, n = 172; validation cohort, n = 86), and their clinical and CT features were analyzed. Stepwise Cox proportional hazard analysis was performed to identify prognostic features and construct a predictive nomogram for recurrence-free survival (RFS). The prognostic performance of the CT-based nomogram was validated and compared to the 8th American Joint Committee on Cancer (AJCC) pathological staging system.

RESULTS

In the development cohort, the following five CT features for predicting recurrence were identified to construct the nomogram: tumor density in the venous phase, tumor necrosis, adjacent organ invasion, splenic vein invasion, and superior mesenteric vein/portal vein abutment. In the validation cohort, the CT-based nomogram showed a concordance index of 0.65 (95% confidence interval: 0.58-0.73), which was higher than the 8th AJCC staging system. The area under the curves of the nomogram for predicting recurrence at 0.5, 1, and 2 years were 0.66, 0.71, and 0.72, respectively. Patients were categorized into high- and low-risk groups with 1-year recurrence probabilities of 0.73 and 0.43, respectively.

CONCLUSIONS

The proposed nomogram provided accurate recurrence risk stratification for patients with resectable PBTA in a preoperative setting and may be used to facilitate clinical decision-making.

CLINICAL RELEVANCE STATEMENT

The proposed CT-based nomogram, based on easily available CT features, may serve as an effective and convenient tool for stratifying further the recurrence risk of patients with pancreatic body/tail adenocarcinoma.

KEY POINTS

• The CT-based nomogram, incorporating five commonly used CT features, successfully preoperatively stratified patients with resectable PBTA into distinct prognosis groups. • Tumor density in the venous phase, tumor necrosis, splenic vein invasion, adjacent organ invasion, and superior mesenteric vein/portal vein abutment were associated with RFS in patients with resectable PBTA. • The CT-based nomogram exhibited better predictive performance for recurrence than the 8th AJCC staging system.

Pancreatic Cancer and Its Mimics

Pancreatic ductal adenocarcinoma (PDAC) is the most common primary pancreatic malignancy, ranking fourth in cancer-related mortality in the United States. Typically, PDAC appears on images as a hypovascular mass with upstream pancreatic duct dilatation and abrupt duct cutoff, distal pancreatic atrophy, and vascular encasement, with metastatic involvement including lymphadenopathy. However, atypical manifestations that may limit detection of the underlying PDAC may also occur. Atypical PDAC features include findings related to associated conditions such as acute or chronic pancreatitis, a mass that is isointense to the parenchyma, multiplicity, diffuse tumor infiltration, associated calcifications, and cystic components. Several neoplastic and inflammatory conditions can mimic PDAC, such as paraduodenal "groove" pancreatitis, autoimmune pancreatitis, focal acute and chronic pancreatitis, neuroendocrine tumors, solid pseudopapillary neoplasms, metastases, and lymphoma. Differentiation of these conditions from PDAC can be challenging due to overlapping CT and MRI features; however, certain findings can help in differentiation. Diffusion-weighted MRI can be helpful but also can be nonspecific. Accurate diagnosis is pivotal for guiding therapeutic planning and potential outcomes in PDAC and avoiding biopsy or surgical treatment of some of these mimics. Biopsy may still be required for diagnosis in some cases. The authors describe the typical and atypical imaging findings of PDAC and features that may help to differentiate PDAC from its mimics. ©RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center. See the invited commentary by Zins in this issue.

Progress in the application of dual-energy CT in pancreatic diseases

Pancreatic diseases are difficult to diagnose due to their insidious onset and complex pathophysiological developmental characteristics. In recent years, dual-energy computed tomography (DECT) imaging technology has rapidly advanced. DECT can quantitatively extract and analyze medical imaging features and establish a correlation between these features and clinical results. This feature enables the adoption of more modern and accurate clinical diagnosis and treatment strategies for patients with pancreatic diseases so as to achieve the goal of non-invasive, low-cost, and personalized treatment. The purpose of this review is to elaborate on the application of DECT for the diagnosis, biological characterization, and prediction of the survival of patients with pancreatic diseases (including pancreatitis, pancreatic cancer, pancreatic cystic tumor, pancreatic neuroendocrine tumor, and pancreatic injury) and to summarize its current limitations and future research prospects.

Use of individualized 3D-printed models of pancreatic cancer to improve surgeons' anatomic understanding and surgical planning

OBJECTIVES

Three-dimensional (3D) printing has been increasingly used to create accurate patient-specific 3D-printed models from medical imaging data. We aimed to evaluate the utility of 3D-printed models in the localization and understanding of pancreatic cancer for surgeons before pancreatic surgery.

METHODS

Between March and September 2021, we prospectively enrolled 10 patients with suspected pancreatic cancer who were scheduled for surgery. We created an individualized 3D-printed model from preoperative CT images. Six surgeons (three staff and three residents) evaluated the CT images before and after the presentation of the 3D-printed model using a 7-item questionnaire (understanding of anatomy and pancreatic cancer [Q1-4], preoperative planning [Q5], and education for trainees or patients [Q6-7]) on a 5-point scale. Survey scores on Q1-5 before and after the presentation of the 3D-printed model were compared. Q6-7 assessed the 3D-printed model's effects on education compared to CT. Subgroup analysis was performed between staff and residents.

RESULTS

After the 3D-printed model presentation, survey scores improved in all five questions (before 3.90 vs. after 4.56, p < 0.001), with a mean improvement of 0.57‒0.93. Staff and resident scores improved after a 3D-printed model presentation (p < 0.05), except for Q4 in the resident group. The mean difference was higher among the staff than among the residents (staff: 0.50‒0.97 vs. residents: 0.27‒0.90). The scores of the 3D-printed model for education were high (trainees: 4.47 vs. patients: 4.60) compared to CT.

CONCLUSION

The 3D-printed model of pancreatic cancer improved surgeons' understanding of individual patients' pancreatic cancer and surgical planning.

CLINICAL RELEVANCE STATEMENT

The 3D-printed model of pancreatic cancer can be created using a preoperative CT image, which not only assists surgeons in surgical planning but also serves as a valuable educational resource for patients and students.

KEY POINTS

• A personalized 3D-printed pancreatic cancer model provides more intuitive information than CT, allowing surgeons to better visualize the tumor's location and relationship to neighboring organs. • In particular, the survey score was higher among staff who performed the surgery than among residents. • Individual patient pancreatic cancer models have the potential to be used for personalized patient education as well as resident education.

Improved predictability of pancreatic ductal adenocarcinoma diagnosis using a blood immune cell biomarker panel developed from bulk mRNA sequencing and single-cell RNA-sequencing

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) remains a devastating cancer due to its poor survival rate, early detection, and resectability. This study aimed to determine the peripheral blood mononuclear cell (PBMC) immune biomarkers in patients with PDAC and investigate the PDAC-specific peripheral blood biomarker panel and validate its clinical performance.

METHODS

In this prospective, blinded, case-control study, a biomarker panel formula was generated using a development cohort-including healthy controls, patients at high risk of PDAC, and patients with benign pancreatic disease, PDAC, or other gastrointestinal malignancies-and its diagnostic performance was verified using a validation cohort, including patients with ≥ 1 lesion suspected as PDAC on computed tomography (CT).

RESULTS

RNA-sequencing of PBMCs from patients with PDAC identified three novel immune cell markers, IL-7R, PLD4, and ID3, as specific markers for PDAC. Regarding the diagnostic performance of the regression formula for the three biomarker panels, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 84.0%, 78.8%, 47.2%, 95.6%, and 79.8%, respectively. Based on the formula scores for the biomarker panel, the false-negative rate (FNR) of the biomarkers was 8% (95% confidence interval [CI] 3.0-13.0), which was significantly lower than that based on CT in the validation cohort (29.2%, 95% CI 20.8-37.6).

CONCLUSIONS

The regression formula constructed using three PBMC biomarkers is an inexpensive, rapid, and convenient method that shows clinically useful performance for the diagnosis of PDAC. It aids diagnoses and differential diagnoses of PDAC from pancreatic disease by lowering the FNR compared to CT. Clinical trial registration Clinical Research Information Service, KCT0004614 (08 January 2020).

Combined CT and serum CA19-9 for stratifying risk for progression in patients with locally advanced pancreatic cancer receiving intraoperative radiotherapy

Background and purpose

The aim of this study was to evaluate the significance of baseline computed tomography (CT) imaging features and carbohydrate antigen 19-9 (CA19-9) in predicting prognosis of locally advanced pancreatic cancer (LAPC) receiving intraoperative radiotherapy (IORT) and to establish a progression risk nomogram that helps to identify the potential beneficiary of IORT.

Methods

A total of 88 LAPC patients with IORT as their initial treatment were enrolled retrospectively. Clinical data and CT imaging features were analyzed. Cox regression analyses were performed to identify the independent risk factors for progression-free survival (PFS) and to establish a nomogram. A risk-score was calculated by the coefficients of the regression model to stratify the risk of progression.

Results

Multivariate analyses revealed that relative enhanced value in portal-venous phase (REV-PVP), peripancreatic fat infiltration, necrosis, and CA19-9 were significantly associated with PFS (all p < 0.05). The nomogram was constructed according to the above variables and showed a good performance in predicting the risk of progression with a concordance index (C-index) of 0.779. Our nomogram stratified patients with LAPC into low- and high-risk groups with distinct differences in progression after IORT (p < 0.001).

Conclusion

The integrated nomogram would help clinicians to identify appropriate patients who might benefit from IORT before treatment and to adapt an individualized treatment strategy.

Assessment of main pancreatic duct cutoff with dilatation, but without visible pancreatic focal lesion on MDCT: a novel diagnostic approach for malignant stricture using a CT-based nomogram

OBJECTIVES

To identify useful features to predict hidden pancreatic malignancies in patients with main pancreatic duct (MPD) abrupt cutoff and dilatation, but without visible focal pancreatic lesions on CT.

METHODS

This retrospective study included 92 patients (mean age, 63.4 ± 10.6 years, 63 men and 29 women) with MPD abrupt cutoff and dilatation, but without visible focal pancreatic lesion on contrast-enhanced CT between 2009 and 2021. Two radiologists independently evaluated the CT imaging features. Multivariable logistic regression analysis was performed to identify clinical and CT imaging features for hidden pancreatic malignancies. A nomogram was developed based on these results and assessed its performance.

RESULTS

Thirty-eight (41.3%) and 54 (58.7%) were classified into the malignant and benign groups, respectively. In the multivariable analysis, CA19-9 elevation (odds ratio [OR] 7.5, p = 0.003), duct cutoff site at the head/neck (OR 7.6, p = 0.006), parenchymal contour abnormality at the duct cutoff site (OR 13.7, p < 0.001), and presence of acute pancreatitis (OR 11.5, p = 0.005) were independent predictors of pancreatic malignancy. A combination of any two significant features showed an accuracy of 77.2%, and a combination of any three features exhibited a specificity of 100%. The CT-based nomogram showed an area under the curve (AUC) of 0.84 (95% confidence interval, 0.77-0.90).

CONCLUSIONS

The three CT imaging features and CA19-9 elevation translated into a nomogram permit a reliable estimation of hidden pancreatic malignancies in patients with MPD abrupt cutoff without visible focal pancreatic lesion. It may facilitate determining whether to proceed to further diagnostic tests.

KEY POINTS

• Isoattenuating pancreatic ductal adenocarcinoma can manifest only as an isolated main pancreatic duct (MPD) dilatation with abrupt cutoff, making it difficult to distinguish from benign strictures. • Along with the serum CA 19-9 elevation, MPD cutoff site at the pancreas head or neck, parenchymal contour abnormality at the duct cutoff site, and associated acute pancreatitis indicated a higher probability of the malignant MPD strictures. • The CT-based nomogram provided excellent diagnostic performance (AUC of 0.84) for hidden pancreatic malignancies in patients with MPD abrupt cutoff and dilatation.

Survival Prediction after Curative Resection of Pancreatic Ductal Adenocarcinoma by Imaging-Based Intratumoral Necrosis

We aimed to determine the histopathological characteristics and prognosis of curatively resected pancreatic ductal adenocarcinoma (PDAC) showing intratumoral necrosis on preoperative CT or MRI. This study consecutively included 102 patients who underwent upfront surgery with margin-negative resection from 2012 to 2020. All patients underwent both pancreatic CT and MRI within 1 month before surgery. Two radiologists independently assessed CT/MRI findings, including the presence of CT- and MRI-detected necrosis. Histopathological characteristics of PDACs according to CT or MRI detection of necrosis were evaluated. Disease-free survival (DFS) and overall survival (OS) were assessed by the Kaplan−Meier method and the Cox proportional hazards model. Among the 102 PDAC patients, 14 patients (13.7%) had CT-detected necrosis, and 16 patients (15.7%) had MRI-detected necrosis, of which 9 showed both CT- and MRI-detected necrosis. PDACs with CT- or MRI-detected necrosis demonstrated a significantly higher degree of histopathological necrosis than those without (p < 0.001). Multivariable analysis revealed that tumor size (hazard ratio [HR], 1.19; p = 0.040), tumor location (HR, 0.46; p = 0.009), and MRI-detected necrosis (HR, 2.64; p = 0.002) had independent associations with DFS. Only MRI-detected necrosis was significantly associated with OS (HR, 2.59; p = 0.004). Therefore, MRI-detected necrosis might be a potential imaging predictor of poor survival after curative resection of PDAC.

Value of Dual-Energy Computed Tomography for Detecting Small Pancreatic Ductal Adenocarcinoma

OBJECTIVE

The aim of the study is to evaluate the usefulness of virtual monoenergetic imaging (VMI) generated from dual-energy computed tomography (DECT) in detecting small pancreatic ductal adenocarcinomas (PDACs).

METHODS

This study included 82 patients pathologically diagnosed with small PDAC (≤30 mm) and 20 without pancreatic tumors who underwent triple-phase contrast-enhanced DECT. To assess diagnostic performance for small PDAC detection via a receiver operating characteristic analysis, 3 observers reviewed 2 image sets (conventional computed tomography [CT] set and combined image set [conventional CT + 40-keV VMI from DECT]). The tumor-to-pancreas contrast-to-noise ratio was compared between conventional CT and 40-keV VMI from DECT.

RESULTS

The area under the receiver operating characteristic curve of the 3 observers were 0.97, 0.96, and 0.97 in conventional CT set and 0.99, 0.99, and 0.99 in combined image set (P = 0.017-0.028), respectively. The combined image set yielded a better sensitivity than the conventional CT set (P = 0.001-0.023), without a loss of specificity (all P > 0.999). The tumor-to-pancreas contrast-to-noise ratios of 40-keV VMI from DECT were approximately threefold higher than those of conventional CT at all phases.

CONCLUSIONS

The addition of 40-keV VMI from DECT to conventional CT had better sensitivity for detecting small PDACs without compromising specificity.

The diagnostic performance of contrast-enhanced ultrasound versus contrast-enhanced computed tomography for pancreatic carcinoma: a systematic review and meta-analysis

BACKGROUND

Pancreatic carcinoma is a highly fatal disease, and early diagnosis is of vital importance. This meta-analysis aimed to compare the diagnostic performances of contrast-enhanced ultrasonography (CEUS) against contrast-enhanced computed tomography (CECT) for pancreatic carcinoma, using pathological results or alternative imaging modality as the gold standard.

METHODS

A thorough search was conducted in PubMed, EMBASE, Web of Science and Cochrane Library databases. Two investigators selected the studies and extracted the data independently. A bivariate mixed-effects regression model was used to calculate the pooled data. Subgroup analysis and meta-regression were performed to explore the causes of heterogeneity.

RESULTS

A total of 1,227 records were identified, of which 7 articles with 588 patients were assessed for eligibility. The overall sensitivity, specificity of CEUS and CECT with their 95% confidential intervals (95% CI) were 0.91 (0.85-0.94) and 0.88 (0.81-0.92), 0.83 (0.70-0.91) and 0.87 (0.73-0.94), respectively. The area under curve (AUC) of CEUS and CECT were 0.94 and 0.93. Subgroup analysis showed CEUS may be good at diagnosing lesions with diameters less than 2 cm. Tumor features, region and study type were the main causes of heterogeneity.

CONCLUSIONS

CEUS has a satisfying diagnostic performance for pancreatic carcinoma and it has high sensitivity for small pancreatic carcinomas (≤2 cm); besides, it performs well in discriminating pancreatic cancer from chronic pancreatitis. Therefore, CEUS can be a useful supplement to CECT.

Dual-energy CT with virtual monoenergetic images and iodine maps improves tumor conspicuity in patients with pancreatic ductal adenocarcinoma

Objectives

To evaluate the value of monoenergetic images (MEI [+]) and iodine maps in dual-source dual-energy computed tomography (DECT) for assessing pancreatic ductal adenocarcinoma (PDAC), including the visually isoattenuating PDAC.

Materials and methods

This retrospective study included 75 PDAC patients, who underwent contrast-enhanced DECT examinations. Conventional polyenergetic image (PEI) and 40–80 keV MEI (+) (10-keV increments) were reconstructed. The tumor contrast, contrast-to-noise ratio (CNR) of the tumor and peripancreatic vessels, the signal-to-noise ratio (SNR) of the pancreas and tumor, and the tumor diameters were quantified. On iodine maps, the normalized iodine concentration (NIC) in the tumor and parenchyma was compared. For subjective analysis, two radiologists independently evaluated images on a 5-point scale.

Results

All the quantitative parameters were maximized at 40-keV MEI (+) and decreased gradually with increasing energy. The tumor contrast, SNR of pancreas and CNRs in 40–60 keV MEI (+) were significantly higher than those in PEI (p < 0.05). For visually isoattenuating PDAC, 40–50 keV MEI (+) provided significantly higher tumor CNR compared to PEI (p < 0.05). The reproducibility in tumor measurements was highest in 40-keV MEI (+) between the two radiologists. The tumor and parenchyma NIC were 1.28 ± 0.65 and 3.38 ± 0.72 mg/mL, respectively (p < 0.001). 40–50 keV MEI (+) provided the highest subjective scores, compared to PEI (p < 0.001).

Conclusions

Low-keV MEI (+) of DECT substantially improves the subjective and objective image quality and consistency of tumor measurements in patients with PDAC. Combining the low-keV MEI (+) and iodine maps may yield diagnostically adequate tumor conspicuity in visually isoattenuating PDAC.

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.

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.

Multi-Phase, Contrast-Enhanced Computed Tomography-Based Radiomic Prognostic Marker of Non-Metastatic Pancreatic Ductal Adenocarcinoma

Background/Aim: This study investigated the predictive ability of intra-tumor enhancement on computed tomography (CT) for the outcomes of patients with pancreatic ductal adenocarcinoma (PDA). Methods: Multi-phase, contrast-enhanced CT (including unenhanced, pancreatic parenchymal phase (PPP) and portal venous phase (PVP)) images of patients diagnosed with non-metastatic PDA were analyzed to investigate prognostic factors. Results: Two hundred ninety-eight patients with PDA (159 with resectable pancreatic cancer (RPC) and 139 with borderline resectable pancreatic cancer (BRPC)/locally advanced pancreatic cancer (LAPC)) were included. The attenuation values of PDA during the PPP (94.5 vs. 60.7 HU; p <0.001) and PVP (101.5 vs. 75.5 HU; p <0.001) were higher in patients with RPC than in those with BRPC/LAPC. Well-enhanced PDA during the PPP was associated with longer overall survival in the RPC group (27.9 vs. 15.4 months; p <0.001) and the BRPC/LAPC group (22.7 vs. 13.6 months; p = 0.024). Patients with BRPC/LAPC who underwent neoadjuvant treatment and had well-enhanced PDA during the PPP were more likely to undergo resection. Although tumor size was also an independent prognostic factor, it was not correlated with intra-tumoral enhancement during the PPP. Conclusions: Intra-tumoral contrast enhancement on CT is an independent prognostic factor in patients with non-metastatic PDA.

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.

Identification of intratumoral fluid-containing area by magnetic resonance imaging to predict prognosis in patients with pancreatic ductal adenocarcinoma after curative resection

OBJECTIVES

To compare the prognosis of pancreatic ductal adenocarcinoma (PDAC) after curative resection according to the type of intratumoral fluid-containing area identified on MRI.

METHODS

This retrospective study included 112 consecutive patients who underwent upfront surgery with margin-negative resection between 2012 and 2019. All patients underwent MRI within 1 month before surgery. Three radiologists independently assessed the MRI findings, determined whether intratumoral fluid-containing areas were present, and classified all intratumoral fluid-containing areas by type (i.e., imaging necrosis or neoplastic mucin cysts). Recurrence-free survival (RFS) and overall survival (OS) were evaluated by the Kaplan-Meier method and the Cox proportional hazards model. Histopathological differences according to the type of intratumoral fluid-containing area were assessed.

RESULTS

Of the 112 PDAC patients, intratumoral fluid-containing areas were identified on MRI in 33 (29.5%), among which 18 were classified as imaging necrosis and 15 as neoplastic mucin cysts. PDAC patients with imaging necrosis demonstrated significantly shorter RFS (mean 6.1 months versus 47.3 months; p < .001) and OS (18.4 months versus 55.0 months, p = .001) than those with neoplastic mucin cysts. Multivariable analysis showed that only the type of intratumoral fluid-containing area was significantly associated with RFS (hazard ratio, 2.25 and 0.38; p = .009 and p = .046 for imaging necrosis and neoplastic mucin cysts, respectively). PDAC with imaging necrosis had more frequent histological necrosis, more aggressive tumor differentiation, and higher tumor cellularity than PDAC with neoplastic mucin cysts (p ≤ .02).

CONCLUSION

The detection and discrimination of intratumoral fluid-containing areas on preoperative MRI may be useful in predicting the prognosis of PDAC patients after curative resection.

KEY POINTS

• Pancreatic ductal adenocarcinoma (PDAC) patients with imaging necrosis demonstrated significantly shorter survival than those with neoplastic mucin cysts after curative resection. • Multivariable analysis showed that only the type of intratumoral fluid-containing area identified on MRI was significantly associated with recurrence-free survival. • PDAC with imaging necrosis had more frequent histological necrosis, more aggressive tumor differentiation, and higher tumor cellularity than PDAC with neoplastic mucin cysts.

Clinical suspicion of pancreatic cancer despite negative endoscopic ultrasound-guided fine-needle aspiration biopsy

BACKGROUND

The early and accurate diagnosis of pancreatic ductal adenocarcinoma is vital for improving the efficacy of therapeutic interventions and to provide patients with the best chance of survival. While endoscopic ultrasound-fine needle aspiration (EUS-FNA) has been demonstrated to be a reliable and accurate diagnostic tool for solid pancreatic neoplasms, the ongoing management of patients with a high clinical suspicion for malignancy but with a negative EUS-FNA biopsy result can prove a challenge.

METHODS

We describe five patients from a single centre who presented for further work-up of a pancreatic mass and/or imaging features concerning for a periampullary malignancy.

RESULTS

All patients had at least one EUS-FNA biopsy performed which returned no malignant cells on cytology. Despite these negative cytology results, all patients underwent further invasive investigation through upfront resection (pancreaticoduodenectomy) or extra-pancreatic biopsy (laparoscopic biopsy of peritoneal nodule) due to worrisome features on imaging, biochemical factors and clinical presentation culminating in a high degree of suspicion for malignancy. The final tissue histopathological diagnosis in all patients was pancreatic ductal adenocarcinoma.

CONCLUSION

This case series highlights the important clinical findings, imaging and biochemical features which need to be considered in patients who have high suspicion for malignancy despite having a negative EUS-FNA cytology result. In these patients with a high index of suspicion, surgical intervention through an upfront resection or further invasive investigation should not be delayed.

Diffusion-weighted MR imaging in pancreatic ductal adenocarcinoma: prediction of next-generation sequencing-based tumor cellularity and prognosis after surgical resection

PURPOSE

To identify features on preoperative MR imaging with diffusion-weighted imaging (DWI) for predicting next-generation sequencing (NGS)-based tumor cellularity and patient outcome after surgical resection of pancreatic ductal adenocarcinoma (PDAC).

METHODS

This retrospective study included 105 patients with surgically resected PDAC who underwent preoperative MR imaging with DWI. Tumor cellularity was measured using molecular techniques and bioinformatics methods. Clinico-pathologic findings including tumor T stage for predicting disease-free survival (DFS) and overall survival (OS) were identified using Cox proportional hazards model. Important MR imaging findings including apparent diffusion coefficient (ADC) value of PDAC and modified ADC value (the ratio of the ADC value of PDAC to the ADC value of the spleen) for predicting higher tumor cellularity (≥ 30%) and poor prognosis were also identified.

RESULTS

The median DFS and OS were 12.0 months [95% confidence interval (CI), 8.0-17.0] and 22.0 months (95% CI, 18.0-29.0), respectively. Higher T stage (T3/4) [hazard ratio (HR), 7.720, (95% CI 1.072, 55.612); p = 0.048] and higher tumor cellularity [HR, 1.599 (95% CI, 1.003-2.548); p = 0.048] were significantly associated with worse DFS. Among MR imaging features, the modified ADC value was significantly associated with tumor cellularity [odds ratio, 0.068 (95% CI, 0.012-0.372); p = 0.002], and PDAC with lower modified ADC value [≤ 1.40 (cutoff value)] showed significantly shorter median DFS than PDAC with higher modified ADC value [8 months (95% CI, 4-12) vs. 16 months (95% CI, 10-29); HR, 1.713 (95% CI, 1.073-2.735), log-rank p = 0.024].

CONCLUSION

Higher NGS-based tumor cellularity may be a negative prognostic factor in pancreatic cancer after resection, and modified ADC value derived from DWI could be helpful in predicting tumor cellularity and patient surgical outcome with regard to recurrence.

Korean clinical practice guideline for pancreatic cancer 2021: A summary of evidence-based, multi-disciplinary diagnostic and therapeutic approaches

Pancreatic cancer is the eighth most common cancer and the fifth most common cause of cancer-related death in Korea. To enable standardization of management and facilitate improvements in outcome, a total of 53 multi-disciplinary experts in gastroenterology, surgery, medical oncology, radiation oncology, radiology, nuclear medicine, and pathology in Korea developed new recommendations that integrate the most up-to-date, evidence-based research findings and expert opinions. Recommendations were made on imaging diagnosis, endoscopic management, surgery, radiotherapy, palliative chemotherapy, and specific management procedures, including neoadjuvant treatment or adjuvant treatment for patients with resectable, borderline resectable, and locally advanced unresectable pancreatic cancer. This is the English version of the Korean clinical practice guideline for pancreatic cancer 2021. This guideline includes 20 clinical questions and 32 statements. This guideline represents the most standard guideline for the diagnosis and treatment of patients with pancreatic ductal adenocarcinoma in adults at this time in Korea. The authors believe that this guideline will provide useful and informative advice.

Atypical and uncommon CT and MR imaging presentations of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinomas (PDACs) occasionally have atypical and uncommon imaging presentations that can present a diagnostic dilemma and result in false interpretation. This article aimed to illustrate these CT and MR imaging findings, including isoattenuating PDAC, coexisting acute pancreatitis, PDAC with a cystic feature, groove PDAC, diffuse PDAC, hypointensity on diffusion-weighted imaging (DWI), multifocal PDAC, intratumoral calcification, and extrapancreatic invasion with a barely discernable mass. A subset of PDACs with atypical features are occasionally encountered during routine clinical practice. Knowledge of and attention to these atypical and uncommon variable imaging features may allow radiologists to avoid misinterpretation and a delayed diagnosis.

Diagnostic Performance of EUS-Guided Sampling in Indeterminate Radiological Diagnosis of Pancreatic Disease and Intra-Abdominal Lymphadenopathy

BACKGROUND

Endoscopic ultrasound (EUS)-guided sampling has been widely used for pathologic diagnosis of pancreatic lesions and intra-abdominal lymphadenopathy. However, its effectiveness for diagnostic decision making in indeterminate radiological diagnosis has not been well determined.

MATERIALS AND METHODS

From March 2012 to October 2015, 98 consecutive patients who underwent EUS-guided FNA for solid intra-abdominal lesions were retrospectively analyzed (100 procedures). The purpose of EUS-guided sampling was classified as (1) confirmation of a high-confidence radiological diagnosis (High-confidence group) or (2) decision making in the differential diagnostic dilemma for indeterminate radiological diagnosis (Indeterminate group). The accuracies of EUS-guided sampling according to the purpose were analyzed and then compared.

RESULTS

Of the 100 procedures, 22 procedures (22%) came under the Indeterminate group, whereas 78 came under the High-confidence group. The accuracies did not differ between the Indeterminate and the High-confidence groups (86.4% vs. 88.5%, p = 1.000). Clinical conditions that required EUS-guided sampling for indeterminate radiological diagnosis were (1) pancreatic cancer vs. benign disease (n = 8; e.g., pancreatic cancer vs. mass-forming pancreatitis), (2) recurrence of previous/pre-existing cancer vs. benign disease (n = 5; e.g., recurrent gastric cancer vs. reactive lymph node), (3) pathologic differentiation of presumed malignancy (n = 6; e.g., lymphadenopathies in the previous history of esophageal cancer and colon cancer), or (4) miscellaneous (n = 3; e.g., tuberculous lymphadenopathy vs. other condition).

CONCLUSIONS

EUS-guided sampling demonstrated an accuracy of 86.4% in the clinical setting of indeterminate radiological diagnosis, which was not different from that of the confirmation of high-confidence diagnosis.

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.

Pancreas in Hereditary Syndromes: Cross-sectional Imaging Spectrum

A wide spectrum of hereditary syndromes predispose patients to distinct pancreatic abnormalities, including cystic lesions, recurrent pancreatitis, ductal adenocarcinoma, nonductal neoplasms, and parenchymal iron deposition. While pancreatic exocrine insufficiency and recurrent pancreatitis are common manifestations in cystic fibrosis and hereditary pancreatitis, pancreatic cysts are seen in von Hippel-Lindau disease, cystic fibrosis, autosomal dominant polycystic kidney disease, and McCune-Albright syndrome. Ductal adenocarcinoma can be seen in many syndromes, including Peutz-Jeghers syndrome, familial atypical multiple mole melanoma syndrome, Lynch syndrome, hereditary breast and ovarian cancer syndrome, Li-Fraumeni syndrome, and familial pancreatic cancer syndrome. Neuroendocrine tumors are commonly seen in multiple endocrine neoplasia type 1 syndrome and von Hippel-Lindau disease. Pancreatoblastoma is an essential component of Beckwith-Wiedemann syndrome. Primary hemochromatosis is characterized by pancreatic iron deposition. Pancreatic pathologic conditions associated with genetic syndromes exhibit characteristic imaging findings. Imaging plays a pivotal role in early detection of these conditions and can positively affect the clinical outcomes of those at risk for pancreatic malignancies. Awareness of the characteristic imaging features, imaging-based screening protocols, and surveillance guidelines is crucial for radiologists to guide appropriate patient management. ^©RSNA, 2021.

Survival prediction after upfront surgery in patients with pancreatic ductal adenocarcinoma: Radiomic, clinic-pathologic and body composition analysis

OBJECTIVE

To investigate the value of radiomic features at contrast-enhanced CT integrated with clinic-pathologic features and body composition measures for predicting survival after upfront surgery in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

Two hundred and ninety-nine patients with PDAC who underwent surgical resection were included and allocated to training set (210 patients) and validation set (89 patients). The radiomics signature for predicting survival was constructed by using the least absolute shrinkage and selection operator Cox regression. Multivariable Cox regression analysis was used to construct a radiomics model based on radiomics signature, clinic-pathologic features and body composition measures. A clinical model without radiomics signature was also developed. Model performance was analyzed by Harrell's concordance index (C-index) and time-independent receiver operating characteristic (ROC) analysis. The Kaplan-Meier (KM) method was used for survival analysis.

RESULTS

Five independent variables were selected for the radiomics model: radiomics signature, carbohydrate antigen 19-9, skeletal muscle index, histologic grade and postoperative chemotherapy. The radiomics-based model provided better predictive performance (C-index = 0.73; all p < 0.05) than the clinical model without radiomics signature and American Joint Committee on Cancer (AJCC) TNM staging system. Patients were stratified as high-risk and low-risk group by the radiomics model. The KM analysis showed a significant difference between two groups (p < 0.05).

CONCLUSION

The radiovdmics-based model integrating with clinic-pathologic features and body composition measures could predict survival after surgical resection in PDAC patients.

Improvement of the Diagnosis of Isoattenuating Pancreatic Carcinomas by Defining their Characteristics on Contrast Enhanced Computed Tomography and Endosonography with Fine-Needle Aspiration (EUS-FNA)

(1) Background. The aim was to define typical features of isoattenuating pancreatic carcinomas on computed tomography (CT) and endosonography and determine the yield of fine-needle aspiration endosonography (EUS-FNA) in their diagnosis. (2) Methods. One hundred and seventy-three patients with pancreatic carcinomas underwent multiphase contrast-enhanced CT followed by EUS-FNA at the time of diagnosis. Secondary signs on CT, size and location on EUS, and the yield of EUS-FNA in isoattenuating and hypoattenuating pancreatic cancer, were evaluated. (3) Results. Isoattenuating pancreatic carcinomas occurred in 12.1% of patients. Secondary signs of isoattenuating pancreatic carcinomas on CT were present in 95.2% cases and included dilatation of the pancreatic duct and/or the common bile duct (85.7%), interruption of the pancreatic duct (76.2%), abnormal pancreatic contour (33.3%), and atrophy of the distal parenchyma (9.5%) Compared to hypoattenuating pancreatic carcinomas, isoattenuating carcinomas were more often localized in the pancreatic head (100% vs. 59.2%; p < 0.001). In ROC (receiver operating characteristic) analysis, the optimal cut-off value for the size of isoattenuating carcinomas on EUS was ≤ 25 mm (AUC = 0.898). The sensitivity of EUS-FNA in confirmation of isoattenuating and hypoattenuating pancreatic cancer were 90.5% and 92.8% (p = 0.886). (4) Conclusions. Isoattenuating pancreatic head carcinoma can be revealed by indirect signs on CT and confirmed with high sensitivity by EUS-FNA.

[Computed tomography in determining the differentiation of ductal adenocarcinoma of pancreatic head]

OBJECTIVE

To evaluate the features of «hypervascular rim», tumor dimensions and density as prognostic factors of differentiation of pancreatic head adenocarcinoma.

MATERIAL AND METHODS

Pancreatoduodenectomy was performed in 311 patients with pancreatic head adenocarcinoma for the period 2013-2019. A retrospective study included 81 patients who met the following criteria: available data of morphological and immunohistological examination indicating tumor grade from Grade 1 to Grade 3, as well as available preoperative CT images in four phases (native, arterial, portal and delayed). Tumor dimensions, density of the pancreas, adenocarcinoma and abdominal aorta by the phases of contrast enhancement were analyzed in all patients. Moreover, we estimated coefficient of relative enhancement change. Perifocal hypervascular enhancement was assessed in arterial and portal phases. Contrast-enhanced MRI was performed in 15 out of 81 patients. MR images were analyzed regarding a hypervascular rim, and the last one was compared with CT images.

RESULTS

There was no significant difference in density values between different tumor grades. Coefficient of relative enhancement change >1 was observed in 63.64% of highly-differentiated tumors. REC ≤1 was found in 85.11% of tumors grade 2 and 82.6% of tumors grade 3 (p=0.005). According to Chi-square test, there was a correlation between tumor differentiation and hypervascular rim (p=0.03). Moderate and low differentiation was observed in 96.42% of tumors with perifocal enhancement. Hypervascular rim was absent in 81.82% of tumors grade 1. Adenocarcinoma grade 2 was found in 85.71% of cases with unclear perifocal enhancement.

CONCLUSION

Preoperative contrast-enhanced CT is valuable to assume the tumor grade in patients with pancreatic head adenocarcinoma due to assessment of hypervascular rim and REC.

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.

Adding Delayed Phase Images to Dual-Phase Contrast-Enhanced CT Increases Sensitivity for Small Pancreatic Ductal Adenocarcinoma

BACKGROUND. Contrast-enhanced CT performed for pancreatic ductal adeno-carcinoma (PDAC) detection traditionally uses a dual-phase (pancreatic and portal venous) protocol. However, PDAC may exhibit isoattenuation in these phases, hindering detection. OBJECTIVE. The purpose of this study was to assess the impact on diagnostic performance in detection of small PDAC when a delayed phase is added to dual-phase contrast-enhanced CT. METHODS. A database of 571 patients who underwent triple-phase (pancreatic, portal venous, and delayed) contrast-enhanced MDCT between January 2017 and March 2020 for suspected pancreatic tumor was retrospectively reviewed. A total of 97 patients had pathologically confirmed small PDAC (mean size, 22 mm; range, 7-30 mm). Twenty control patients had no pancreatic tumor suspected on CT, on initial MRI and follow-up CT, or on MRI after 12 months or longer. Three radiologists independently reviewed dual-phase and triple-phase images. Two additional radiologists assessed tumors' visual attenuation on each phase, reaching consensus for differences. Performance of dual- and triple-phase images were compared using ROC analysis, McNemar test, and Fisher exact test. RESULTS. AUC was higher (p < .05) for triple-phase than dual-phase images for all observers (observer 1, 0.97 vs 0.94; observer 2, 0.97 vs 0.94; observer 3, 0.97 vs 0.95). Sensitivity was higher (p < .001) for triple-phase than dual-phase images for all observers (observer 1, 74.2% [72/97] vs 59.8% [58/97]; observer 2, 88.7% [86/97] vs 71.1% [69/97]; observer 3, 86.6% [84/97] vs 72.2% [70/97]). Specificity, PPV, and NPV did not differ between image sets for any reader (p ≥ .05). Seventeen tumors showed pancreatic phase visual isoattenuation, of which nine showed isoattenuation and eight hyperattenuation in the delayed phase. Of these 17 tumors, 16 were not detected by any observer on dual-phase images; of these 16, six were detected by at least two observers and five by at least one observer on triple-phase images. Visual attenuation showed excellent interob-server agreement (κ = 0.89-0.96). CONCLUSION. Addition of a delayed phase to pancreatic and portal venous phase CT increases sensitivity for small PDAC without loss of specificity, partly related to delayed phase hyperattenuation of some small PDACs showing pancreatic phase isoattenuation. CLINICAL IMPACT. Addition of a delayed phase may facilitate earlier PDAC detection and thus improved prognosis.

Reduced Field-of-View Diffusion-Weighted Magnetic Resonance Imaging of the Pancreas With Tilted Excitation Plane: A Preliminary Study

BACKGROUND

Reduced field-of-view diffusion-weighted imaging (rDWI) with tilted two-dimensional radiofrequency (RF) excitation planes has not yet been applied to the imaging of the pancreas although the utility of this technique which allows the acquisition of high-quality images without aliasing artifacts in the phase-encoding direction has been evaluated for brain and spinal cord imaging.

PURPOSE

To evaluate the visual image quality of the pancreas by tilting the excitation plane (tilted rDWI) in comparison to conventional DWI (cDWI) and rDWI without using the tilted excitation plane.

STUDY TYPE

Retrospective.

POPULATION

Thirty-two patients evaluated for suspected pancreatobiliary diseases.

FIELD STRENGTH/SEQUENCE

Echo-planar imaging DWI (cDWI, rDWI, and tilted rDWI) acquired at 3 T.

ASSESSMENT

Images from each DWI sequence were analyzed by five radiologists to compare image quality (conspicuity of pancreatic edges, interslice signal homogeneity, overall image quality, and conspicuity of focal pancreatic lesions) and artifacts (presence of blurring or ghosting artifacts, susceptibility artifacts, and aliasing artifact).

STATISTICAL TESTS

Shapiro-Wilk test was performed to assess whether data were normally distributed. Friedman test followed by Bonferroni-adjusted Wilcoxon signed-rank test for post hoc analysis was performed to compare image quality and artifact scores.

RESULTS

The mean scores for conspicuity of pancreatic edges (3.36 vs. 2.37), interslice signal homogeneity (3.14 vs. 2.81), presence of ghosting artifacts (3.32 vs. 2.66), susceptibility artifacts (3.06 vs. 2.30), and aliasing artifacts (3.90 vs. 2.34), and overall image quality (3.49 vs. 2.36) were significantly higher in the tilted rDWI than in the rDWI (P < 0.017 for all parameters). The conspicuity score for focal pancreatic lesions tended to be higher in tilted rDWI than in rDWI (2.44 vs. 2.00, P = 0.07).

DATA CONCLUSION

Tilted rDWI had better image quality and reduced artifacts relative to cDWI and rDWI techniques in the pancreas.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

[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.

Pre-Operative Imaging and Pathological Diagnosis of Localized High-Grade Pancreatic Intra-Epithelial Neoplasia without Invasive Carcinoma

Pancreatic ductal adenocarcinoma (PDAC) arises from precursor lesions, such as pancreatic intra-epithelial neoplasia (PanIN) and intraductal papillary mucinous neoplasm (IPMN). The prognosis of high-grade precancerous lesions, including high-grade PanIN and high-grade IPMN, without invasive carcinoma is good, despite the overall poor prognosis of PDAC. High-grade PanIN, as a lesion preceding invasive PDAC, is therefore a primary target for intervention. However, detection of localized high-grade PanIN is difficult when using standard radiological approaches. Therefore, most studies of high-grade PanIN have been conducted using specimens that harbor invasive PDAC. Recently, imaging characteristics of high-grade PanIN have been revealed. Obstruction of the pancreatic duct due to high-grade PanIN may induce a loss of acinar cells replaced by fibrosis and lobular parenchymal atrophy. These changes and additional inflammation around the branch pancreatic ducts (BPDs) result in main pancreatic duct (MPD) stenosis, dilation, retention cysts (BPD dilation), focal pancreatic parenchymal atrophy, and/or hypoechoic changes around the MPD. These indirect imaging findings have become important clues for localized, high-grade PanIN detection. To obtain pre-operative histopathological confirmation of suspected cases, serial pancreatic-juice aspiration cytologic examination is effective. In this review, we outline current knowledge on imaging characteristics of high-grade PanIN.

Pancreatic FDG uptake on follow-up PET/CT in patients with cancer

To evaluate the breakdown of unexpected pancreatic ¹⁸F-fluorodeoxyglucose (FDG) uptake and the proportion of secondary primary pancreatic cancer on follow-up, patients with cancer underwent positron emission tomography/computed tomography (PET/CT). The participants consisted of 4,473 consecutive patients with cancer who underwent follow-up PET/CT between January 2015 and March 2019 at Kochi Medical School. Among the participants, 225 with a history of pancreatic cancer were excluded from the present study. Retrospective and blinded PET/CT evaluations of 4,248 patients were performed. In patients with pancreatic FDG uptake, the distribution of FDG uptake in the pancreas was evaluated. The final diagnosis was determined pathologically. A total of 14 (0.3%) of the 4,248 patients exhibited FDG uptake in the pancreatic area. Pancreatic abnormalities were detected in 14 patients, and included five cases of pancreatic metastases (36%), four cases of secondary primary pancreatic cancer (29%), two cases of lymph node metastases (14%), one case of malignant lymphoma (7%), one case of autoimmune pancreatitis (7%) and one case of pseudolesion (7%). One patient with early-stage secondary primary pancreatic cancer had a maximum standardized uptake value (SUV_max) <3.0. The remaining 13 patients had a SUV_max >3.0 in the pancreas. Of the 14 patients, two had multiple foci of FDG uptake in the pancreas. Patients with multiple foci of FDG uptake exhibited pancreatic metastasis from renal cell carcinoma and malignant lymphoma. In conclusion, the majority of patients with unexpected pancreatic FDG uptake on follow-up PET/CT exhibited malignancies; furthermore, ~30% of the malignancies detected in patients with pancreatic FDG uptake were secondary primary pancreatic cancers. In patients with unexpected pancreatic FDG uptake on follow-up PET/CT, primary cancer should be considered as well as metastatic tumors.

Clinical Implementation of Dual-Energy CT for Gastrointestinal Imaging

Dual-energy CT (DECT) overcomes several limitations of conventional single-energy CT (SECT) for the evaluation of gastrointestinal diseases. This article provides an overview of practical aspects of the DECT technology and acquisition protocols, reviews existing clinical applications, discusses current challenges, and describes future directions, with a focus on gastrointestinal imaging. A head-to-head comparison of technical specifications among DECT scanner implementations is provided. Energy- and material-specific DECT image reconstructions enable retrospective (i.e., after examination acquisition) image quality adjustments that are not possible using SECT. Such adjustments may, for example, correct insufficient contrast bolus or metal artifacts, thereby potentially avoiding patient recalls. A combination of low-energy monochromatic images, iodine maps, and virtual unenhanced images can be included in protocols to improve lesion detection and disease characterization. Relevant literature is reviewed regarding use of DECT for evaluation of the liver, gallbladder, pancreas, and bowel. Challenges involving cost, workflow, body habitus, and variability in DECT measurements are considered. Artificial intelligence and machine-learning image reconstruction algorithms, PACS integration, photon-counting hardware, and novel contrast agents are expected to expand the multienergy capability of DECT and further augment its value.