CT Imaging Biomarkers Predict Clinical Outcomes After Pancreatic Cancer Surgery

Looking at or beyond the tumor - a systematic review and meta-analysis of quantitative imaging biomarkers predicting pancreatic cancer prognosis

OBJECTIVES

To evaluate the prognostic value of quantitative imaging biomarkers derived from computed tomography (CT) and magnetic resonance imaging (MRI) for pancreatic cancer (PC), with a particular focus on body composition parameters beyond the traditional intrinsic features of the tumor.

METHODS

PubMed, EMBASE, and Cochrane Library databases were searched for articles on quantitative imaging biomarkers obtained from CT or MRI in predicting PC prognosis published between January 2014 and August 2024. The Newcastle-Ottawa scale was used to assess the quality of the included studies. Survival outcomes, such as overall survival (OS) and recurrence-free survival (RFS), were evaluated. The pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using a random-effects model. In case of high heterogeneity, subgroup analyses and sensitivity analyses were performed to identify potential sources of heterogeneity among the studies.

RESULTS

We performed a meta-analysis of ten imaging biomarkers investigated in 43 included studies. Larger tumor size, lower skeletal muscle radiodensity, lower skeletal muscle index (SMI), presence of sarcopenic obesity, lower psoas muscle index (PMI), higher visceral to subcutaneous adipose tissue area ratio, and lower visceral adipose tissue index were associated with significantly worse OS. In particular, lower SMI and lower PMI had relatively high HRs (1.65 for SMI, 95% CI 1.39-1.96, and 2.20 for PMI, 95% CI 1.74-2.78). Patients with lower SMI exhibited poorer RFS (HR 1.78, 95% CI 1.46-2.18). Subgroup analyses identified the origin region of the study and intervention type as potential factors of heterogeneity for SMI in predicting OS.

CONCLUSIONS

Imaging biomarkers indicating body composition at PC diagnosis may play an important role in predicting patient prognosis. Further prospective multi-center studies with large sample sizes are needed for validation and translation into clinical practice.

Preoperative Prognostic Factors in Resectable Pancreatic Cancer: State of the Art and Prospects

BACKGROUND

Only 15% to 20% of patients with pancreatic ductal adenocarcinoma (PDAC) have access to surgical resection, which represents the only chance of curative treatment. Current resection classifications are almost exclusively anatomic and do not correlate sufficiently with patient survival. It is essential to develop preoperative prognostic factors to distinguish patients at high risk of early postoperative recurrence from those who will have prolonged survival after surgery. In some cases, PDACs may present biomolecular differences reflecting their aggressiveness that are not yet assessable by the current clinical-biologic assessment. This study aimed to assess the preoperative prognostic factors that are already available and the future perspectives being developed.

METHOD

This study reviewed the literature using the PubMed public database for preoperative prognostic factors for resectable PDAC.

CONCLUSION

Validated preoperative prognostic factors, whether clinical, biologic, radiologic, or histologic, are very important in anticipating the course of each patient's disease. The identification of potential new prognostic biomarkers such as genomic, transcriptomic, and proteomic analyses and the dosage of circulating tumor DNA are very serious avenues to be developed, but the extraction and analysis techniques as well as the interpretation of their results need to be standardized in prospective studies.

Performance of different CT enhancement quantification methods as predictors of pancreatic cancer recurrence after upfront surgery

The prognosis of pancreatic cancer (PDAC) after tumor resection remains poor, mostly due to a high but variable risk of recurrence. A promising tool for improved prognostication is the quantification of CT tumor enhancement. For this, various enhancement formulas have been used in previous studies. However, a systematic comparison of these formulas is lacking. In the present study, we applied twenty-three previously published CT enhancement formulas to our cohort of 92 PDAC patients who underwent upfront surgery. We identified seven formulas that could reliably predict tumor recurrence. Using these formulas, weak tumor enhancement was associated with tumor recurrence at one and two years after surgery (p ≤ 0.030). Enhancement was inversely associated with adverse clinicopathological features. Low enhancement values were predictive of a high recurrence risk (Hazard Ratio ≥ 1.659, p ≤ 0.028, Cox regression) and a short time to recurrence (TTR) (p ≤ 0.027, log-rank test). Some formulas were independent predictors of TTR in multivariate models. Strikingly, almost all of the best-performing formulas measure solely tumor tissue, suggesting that normalization to non-tumor structures might be unnecessary. Among the top performers were also the absolute arterial/portal venous tumor attenuation values. These can be easily implemented in clinical practice for better recurrence prediction, thus potentially improving patient management.

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.

Radiomics analysis with three-dimensional and two-dimensional segmentation to predict survival outcomes in pancreatic cancer

BACKGROUND

Radiomics can assess prognostic factors in several types of tumors, but considering its prognostic ability in pancreatic cancer has been lacking.

AIM

To evaluate the performance of two different radiomics software in assessing survival outcomes in pancreatic cancer patients.

METHODS

We retrospectively reviewed pretreatment contrast-enhanced dual-energy computed tomography images from 48 patients with biopsy-confirmed pancreatic ductal adenocarcinoma who later underwent neoadjuvant chemoradiation and surgery. Tumors were segmented using TexRad software for 2-dimensional (2D) analysis and MIM software for 3D analysis, followed by radiomic feature extraction. Cox proportional hazard modeling correlated texture features with overall survival (OS) and progression-free survival (PFS). Cox regression was used to detect differences in OS related to pretreatment tumor size and residual tumor following treatment. The Wilcoxon test was used to show the relationship between tumor volume and the percent of residual tumor. Kaplan-Meier analysis was used to compare survival in patients with different tumor densities in Hounsfield units for both 2D and 3D analysis.

RESULTS

3D analysis showed that higher mean tumor density [hazard ratio (HR) = 0.971, P = 0.041)] and higher median tumor density (HR = 0.970, P = 0.037) correlated with better OS. 2D analysis showed that higher mean tumor density (HR = 0.963, P = 0.014) and higher mean positive pixels (HR = 0.962, P = 0.014) correlated with better OS; higher skewness (HR = 3.067, P = 0.008) and higher kurtosis (HR = 1.176, P = 0.029) correlated with worse OS. Higher entropy correlated with better PFS (HR = 0.056, P = 0.036). Models determined that patients with increased tumor size greater than 1.35 cm were likely to have a higher percentage of residual tumors of over 10%.

CONCLUSION

Several radiomics features can be used as prognostic tools for pancreatic cancer. However, results vary between 2D and 3D analyses. Mean tumor density was the only variable that could reliably predict OS, irrespective of the analysis used.

Predicting the Efficacy of Neoadjuvant Chemotherapy for Pancreatic Cancer Using Deep Learning of Contrast-Enhanced Ultrasound Videos

Contrast-enhanced ultrasound (CEUS) is a promising imaging modality in predicting the efficacy of neoadjuvant chemotherapy for pancreatic cancer, a tumor with high mortality. In this study, we proposed a deep-learning-based strategy for analyzing CEUS videos to predict the prognosis of pancreatic cancer neoadjuvant chemotherapy. Pre-trained convolutional neural network (CNN) models were used for binary classification of the chemotherapy as effective or ineffective, with CEUS videos collected before chemotherapy as the model input, and with the efficacy after chemotherapy as the reference standard. We proposed two deep learning models. The first CNN model used videos of ultrasound (US) and CEUS (US+CEUS), while the second CNN model only used videos of selected regions of interest (ROIs) within CEUS (CEUS-ROI). A total of 38 patients with strict restriction of clinical factors were enrolled, with 76 original CEUS videos collected. After data augmentation, 760 and 720 videos were included for the two CNN models, respectively. Seventy-six-fold and 72-fold cross-validations were performed to validate the classification performance of the two CNN models. The areas under the curve were 0.892 and 0.908 for the two models. The accuracy, recall, precision and F1 score were 0.829, 0.759, 0.786, and 0.772 for the first model. Those were 0.864, 0.930, 0.866, and 0.897 for the second model. A total of 38.2% and 40.3% of the original videos could be clearly distinguished by the deep learning models when the naked eye made an inaccurate classification. This study is the first to demonstrate the feasibility and potential of deep learning models based on pre-chemotherapy CEUS videos in predicting the efficacy of neoadjuvant chemotherapy for pancreas cancer.

Diffuse Involvement of Pancreas is not Always Autoimmune Pancreatitis

RATIONALE AND OBJECTIVES

To determine the prevalence of diffuse involvement of pancreas and to identify the findings of malignancies using enhancement computed tomography (CT).

MATERIALS AND METHODS

A total of 1,0249 patients performed enhancement CT in our hospital over 62 months were investigated and the final study cohort includes 245 patients (170 males, 75 females; mean age, 56.94 ± 12.17 years). The reference standard is the final clinical/pathological diagnosis. The lesion-to-aorta enhancement ratio (LAR) on the pancreatic arterial phase, portal phase and delayed phase (DP) and the traditional CT findings were evaluated. Intergroup comparisons between malignancies and non-malignancies lesions were performed. Univariate and multivariate analyses were conducted to identify findings predicting malignancies.

RESULTS

The prevalence of malignancy was 45.3% (111/245) of diffuse enlargement of pancreas. All benign lesions were autoimmune pancreatitis 54.7% (n = 134). The most common malignant lesion was pancreatic ductal adenocarcinoma (n = 88, 35.9%). Other rare lesions with malignant potential included pancreatic neuroendocrine tumor (n = 11, 4.5%), lymphoma (n = 4, 1.6%), metastasis (n = 4, 1.6%), solid pseudopapillary neoplasm (n = 3, 1.2%) and acinar cell carcinoma (n = 1, 0.4%). Residual normal pancreas parenchyma, heterogeneity, short axis (cut-off value, 3.15 cm) and LARDP (cut-off value, 0.75) were independent predictors of malignancies. When the above predictors were combined, a sensitivity of 94.2%, a specificity of 90.8% were attained.

CONCLUSION

Diffuse involvement of the pancreas is rare and is not a specific sign of autoimmune pancreatitis, and it is associated with a wide spectrum of malignant conditions. Dynamic enhancement CT is helpful to identifying malignancies.

Imaging of Pancreatic Ductal Adenocarcinoma: An Update on Recent Advances

Pancreatic ductal carcinoma (PDAC) is one of the leading causes of cancer-related death worldwide. Computed tomography (CT) remains the primary imaging modality for diagnosis of PDAC. However, CT has limitations for early pancreatic tumor detection and tumor characterization so that it is currently challenged by magnetic resonance imaging. More recently, a particular attention has been given to radiomics for the characterization of pancreatic lesions using extraction and analysis of quantitative imaging features. In addition, radiomics has currently many applications that are developed in conjunction with artificial intelligence (AI) with the aim of better characterizing pancreatic lesions and providing a more precise assessment of tumor burden. This review article sums up recent advances in imaging of PDAC in the field of image/data acquisition, tumor detection, tumor characterization, treatment response evaluation, and preoperative planning. In addition, current applications of radiomics and AI in the field of PDAC are discussed.

A predictive model for recurrence after upfront surgery in patients with resectable pancreatic ductal adenocarcinoma (PDAC) by using preoperative clinical data and CT characteristics

BACKGROUND

The overall survival for patients with resectable PDAC following curative surgical resection hasn't been improved significantly, as a considerable proportion of patients develop recurrence within a year. The purpose of this study was to develop and validate a predictive model to assess recurrence risk in patients with PDAC after upfront surgery by using preoperative clinical data and CT characteristics.

METHODS

The predictive model was developed based on a retrospective set of 141 pancreatic cancer patients after surgery. A separate set of 77 patients was used to validate model. Between January 2017 and December 2019, all patients underwent multidetector pancreatic CT and upfront surgery. Univariable and multivariate Cox regression was used to determine the risk factors related to recurrence and then establish a nomogram to estimate the 1-year recurrence probability. The Harrell C-index was employed in evaluating the discrimination and calibration of the model.

RESULTS

A total of 218 patients in this retrospective cohort. A recurrence model in nomogram form was developed with predictors including tumor size (hazard ratio [HR], 1.277; 95% CI 1.098, 1.495; P = 0.002), tumor density in the portal vein phase (HR, 0.598; 95% CI 0.424, 0.844; P = 0.003), peripancreatic infiltration (HR, 4.151; 95% CI 2.077, 8.298; P < 0.001), suspicious metastatic lymph node (HR, 2.561; 95% CI 1.653, 3.967; P < 0.001), Neutrophils/Lymphocytes ratio (HR, 1.111; 95% CI 1.016, 1.215; P = 0.020). The predictive nomogram had good discrimination capability with these predictors with an area under curve at 1 year of 0.84 (95%CI 0.77, 0.91) in the development set and 0.82 (95% CI 0.72, 0.92) and 0.84 (95% CI 0.74, 0.94) in the validation set for two radiologists reading respectively.

CONCLUSIONS

The model developed based on preoperative clinical data and CT characteristics of resectable pancreatic ductal adenocarcinoma patients, which can helpfully estimate the recurrence-free survival. It may be a useful tool for clinician to select optimal candidates for upfront surgery or neoadjuvant therapy.

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.

Basic pancreatic lesions: Radiologic-pathologic correlation

The basic pancreatic lesions include location, size, shape, number, capsule, calcification/calculi, hemorrhage, cystic degeneration, fibrosis, pancreatic duct alterations, and microvessel. One or more basic lesions form a kind of pancreatic disease. As recognizing the characteristic imaging features of pancreatic basic lesions and their relationships with pathology aids in differentiating the variety of pancreatic diseases. The purpose of this study is to review the pathological and imaging features of the basic pancreatic lesions.

Correlation Between Enhancement Patterns on Transabdominal Ultrasound and Survival for Pancreatic Ductal Adenocarcinoma

Objective

Investigate the CEUS enhancement patterns of PDAC and analyse correlations between the CEUS enhancement pattern and both the degree of tumour tissue differentiation and overall survival (OS).

Methods

The study included 56 patients with locally advanced PDAC, performed conventional ultrasound and CEUS, and analysed characteristics of the CEUS enhancement patterns. In addition, clinical data, such as serum level of CA19-9, TNM stage were collected, and patients’ survival times were followed up. TICs of dynamic CEUS images were acquired using image processing software to obtain the peak, TP, sharpness, and AUC. Correlations of the CEUS enhancement patterns of PDAC with the degree of differentiation of tumour tissue and OS were quantitatively analysed, as were the correlations of the TIC parameters and CEUS enhancement patterns with OS.

Results

Enhancement in the arterial phase included iso-enhancement (30.3%) and hypo-enhancement (69.6%), and was not significantly correlated with sex, age at disease onset, or lesion size. Also was not significantly correlated with tumour tissue differentiation. Clear survival times were obtained for 50 patients during follow-up, and the median survival time was significantly longer for the patients with iso-enhancement than hypo-enhancement. Among the TIC parameters, peak_tumour, sharpness_tumour, AEsharpness, and REsharpness differed significantly between the group with iso-enhancement and hypo-enhancement (p < 0.05).

Conclusion

The CEUS enhancement patterns of PDAC in the arterial phase include iso-enhancement and hypo-enhancement. Enhancement pattern was not significantly correlated with the degree of differentiation of tumour tissue, but patient survival time differed significantly between the two enhancement patterns, with longer survival for patients with iso-enhancement.

[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.

Predictive Modeling for Voxel-Based Quantification of Imaging-Based Subtypes of Pancreatic Ductal Adenocarcinoma (PDAC): A Multi-Institutional Study

Previously, we characterized qualitative imaging-based subtypes of pancreatic ductal adenocarcinoma (PDAC) on computed tomography (CT) scans. Conspicuous (high delta) PDAC tumors are more likely to have aggressive biology and poorer clinical outcomes compared to inconspicuous (low delta) tumors. Here, we developed a quantitative classification of this imaging-based subtype (quantitative delta; q-delta). Retrospectively, baseline pancreatic protocol CT scans of three cohorts (cohort#1 = 101, cohort#2 = 90 and cohort#3 = 16 [external validation]) of patients with PDAC were qualitatively classified into high and low delta. We used a voxel-based method to volumetrically quantify tumor enhancement while referencing normal-pancreatic-parenchyma and used machine learning-based analysis to build a predictive model. In addition, we quantified the stromal content using hematoxylin- and eosin-stained treatment-naïve PDAC sections. Analyses revealed that PDAC quantitative enhancement values are predictive of the qualitative delta scoring and were used to build a classification model (q-delta). Compared to high q-delta, low q-delta tumors were associated with improved outcomes, and the q-delta class was an independent prognostic factor for survival. In addition, low q-delta tumors had higher stromal content and lower cellularity compared to high q-delta tumors. Our results suggest that q-delta classification provides a clinically and biologically relevant tool that may be integrated into ongoing and future clinical trials.

CT and MRI of pancreatic tumors: an update in the era of radiomics

Radiomics is a relatively new approach for image analysis. As a part of radiomics, texture analysis, which consists in extracting a great amount of quantitative data from original images, can be used to identify specific features that can help determining the actual nature of a pancreatic lesion and providing other information such as resectability, tumor grade, tumor response to neoadjuvant therapy or survival after surgery. In this review, the basic of radiomics, recent developments and the results of texture analysis using computed tomography and magnetic resonance imaging in the field of pancreatic tumors are presented. Future applications of radiomics, such as artificial intelligence, are discussed.

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.

Enhancement parameters of contrast-enhanced computed tomography for pancreatic ductal adenocarcinoma: Correlation with pathologic grading

BACKGROUND

Pancreatic ductal adenocarcinoma (PDA) is a malignancy with a high mortality rate and short survival time. The conventional computed tomography (CT) has been worldwide used as a modality for diagnosis of PDA, as CT enhancement pattern has been thought to be related to tumor angiogenesis and pathologic grade of PDA.

AIM

To evaluate the relationship between the pathologic grade of pancreatic ductal adenocarcinoma and the enhancement parameters of contrast-enhanced CT.

METHODS

In this retrospective study, 42 patients (Age, mean ± SD: 62.43 ± 11.42 years) with PDA who underwent surgery after preoperative CT were selected. Two radiologists evaluated the CT images and calculated the value of attenuation at the aorta in the arterial phase and the pancreatic phase (VA_arterial and VA_pancreatic) and of the tumor (VT_arterial and VT_pancreatic) by finding out four regions of interest. Ratio between the tumor and the aorta enhancement on the arterial phase and the pancreatic phase (TAR_arterial and TAR_pancreatic) was figured out through dividing VT_arterial by VA_arterial and VT_pancreatic by VA_pancreatic. Tumor-to-aortic enhancement fraction (TAF) was expressed as the ratio of the difference between attenuation of the tumor on arterial and parenchymal images to that between attenuation of the aorta on arterial and pancreatic images. The Kruskal-Wallis analysis of variance and Mann-Whitney U test for statistical analysis were used.

RESULTS

Forty-two PDAs (23 men and 19 women) were divided into three groups: Well-differentiated (n = 13), moderately differentiated (n = 21), and poorly differentiated (n = 8). TAF differed significantly between the three groups (P = 0.034) but TAR_arterial (P = 0.164) and TAR_pancreatic (P = 0.339) did not. The median value of TAF for poorly differentiated PDAs (0.1011; 95%CI: 0.01100-0.1796) was significantly higher than that for well-differentiated PDAs (0.1941; 95%CI: 0.1463-0.3194).

CONCLUSION

Calculation of TAF might be useful in predicting the pathologic grade of PDA.

Pancreatic adenocarcinoma: quantitative CT features are correlated with fibrous stromal fraction and help predict outcome after resection

OBJECTIVES

To identify quantitative imaging features of contrast-enhanced computed tomography (CE-CT) that may be prognostically favorable after resection of smaller (≤ 30 mm) pancreatic ductal adenocarcinomas (PDACs) located at head.

METHODS

This retrospective study included two independent cohorts (discovery cohort, n = 212; test cohort, n = 100) of patients who underwent resection of head PDACs ≤ 30 mm and preoperative CE-CT. We examined tumor and surrounding parenchymal attenuation differences (deltas), and tumor attenuation changes across phases (ratios). Semantic features of PDACs were evaluated by two radiologists. Clinicopathologic and imaging features for predicting disease-free survival (DFS) and overall survival (OS) were analyzed via multivariate Lasso-penalized Cox proportional-hazards models. Survival rates were derived by Kaplan-Meier method.

RESULTS

Imaging features achieved C-indices of 0.766 (discovery cohort) and 0.739 (test cohort) for DFS, and 0.790 (discovery cohort) and 0.772 (test cohort) for OS estimates through incorporation of clinicopathologic features. The most decisive imaging feature was delta 3, denoting attenuation differences between tumor and surrounding pancreas at pancreatic phase (DFS: HR = 2.122; OS: HR = 2.375; both p < 0.001). Compared with inconspicuous (low-delta-3, < 28 HU) tumors, conspicuous (high-delta-3) tumors correlated significantly with more aggressive histologic grades (p = 0.014) and less extensive tumor fibrous stromal fractions (p < 0.001). Patients with low-delta-3 tumors ≤ 20 mm experienced the most favorable outcomes (DFS, 36 months; OS, 42 months), whereas those with high-delta-3 tumors fared poorly, regardless of tumor size (DFS, 12 months; OS, 19 months).

CONCLUSIONS

Quantifiable CT imaging features reflect heterogeneous fibrous stromal fractions and histologic grades of PDAC at head locations that help stratify patients with disparate clinical outcomes.

KEY POINTS

• Quantitative and semantic imaging features achieved promising results for the prognosis of resected PDAC (≤ 30 mm) at head location, through incorporation of clinicopathologic features. • Attenuation difference at tumor-parenchyma interface (delta 3) emerged as the most decisive imaging feature, enabling further stratification of patients into distinct prognostic subtypes by tumor size. • High delta 3 signifies sharper contrast between tumor and surrounding pancreas, correlating with more aggressive histologic grades and less extensive tumor fibrous stromal fractions.

Integrin beta 4 (ITGB4) and its tyrosine-1510 phosphorylation promote pancreatic tumorigenesis and regulate the MEK1-ERK1/2 signaling pathway

Pancreatic cancer is the fourth leading cause of cancer death, with a 5-year survival rate of only 1–4%. Integrin-mediated cell adhesion is critical for the initiation, progression, and metastasis of cancer. In this study we investigated the role of integrin β4 (ITGB4) and its phosphorylation at tyrosine Y1510 (p-ITGB4-Y1510) in the tumorigenesis of pancreatic cancer. We analyzed the expression of ITGB4 and p-ITGB4-Y1510 in pancreatic cancer tissue and cell lines using immunohistochemistry, Western blot, or semi-quantitative reverse transcription PCR. ITGB4 and p-ITGB4-Y1510 were highly expressed in pancreatic cancer (n = 176) compared with normal pancreatic tissue (n = 171). High p-ITGB4-Y1510 expression correlated with local invasion and distant metastasis of pancreatic cancer, and high ITGB4 was significantly associated with poor survival of patients. Inhibition of ITGB4 by siRNA significantly reduced migration and invasion of PC-1.0 and AsPC-1 cells. Overexpression of the mutant ITGB4-Y1510A (a mutation of tyrosine to alanine at 1510 position) in PC-1.0 and AsPC-1 cells not only blocked the ITGB4 phosphorylation at Y1510 but also suppressed the expression of ITGB4 (p < 0.05 vs. wild-type ITGB4). The transfection of PC-1.0 and AsPC-1 cells with ITGB4-Y1510A significantly decreased the level of p-mitogen-activated protein kinase kinase (MEK)1 (T292) and p-extracellular signal-regulated kinase (ERK)1/2 but did not affect the level of p-MEK1 (T386) and p-MEK2 (T394). Overall, our study showed that ITGB4 and its phosphorylated form promote cell migration and invasion in pancreatic cancer and that p-ITGB4-Y1510 regulates the downstream MEK1-ERK1/2 signaling cascades. Targeting ITGB4 or its phosphorylation at Y1510 may be a novel therapeutic option for pancreatic cancer.

Main Pancreatic Duct to Parenchymal Thickness Ratio at Preoperative Imaging is Associated with Overall Survival in Upfront Resected Pancreatic Cancer

BACKGROUND

Pancreatic cancer induces parenchymal atrophy and duct dilation. The aim of this study was to evaluate whether these radiologic modifications are associated with outcomes.

METHODS

Upfront pancreaticoduodenectomy patients with available preoperative contrast enhanced CT scan imaging were retrospectively analyzed. Thickness of the pancreas, size of the main pancreatic duct (MPD), and distance of the tumor from the ampulla were assessed. A training cohort was selected, including short- (3-12 months following surgery) and long-term (≥ 36 months) survivors. Identified survival determinants were validated in the overall cohort.

RESULTS

Two-hundred-sixteen patients were analyzed. In the training cohort (N = 118), 68 patients (57.6%) were in the short-term and 50 (42.4%) in the long-term survival group. The short-term survival group had significantly higher CA 19-9 levels (p = 0.027), larger tumors (32.6 ± 12.1 mm vs. 26.5 ± 11.6 mm, p = 0.007), poorer differentiation (p = 0.003), higher rate of R < 1 mm resections (54% vs. 32%, p = 0.008), and reduced receipt of adjuvant chemotherapy (p = 0.020). The MPD-to-pancreatic thickness ratio was significantly lower in the short-term survivors (3.6 ± 6.2 vs. 8.2 ± 12.0, p = 0.016). In the entire cohort, an MPD-to-pancreatic thickness ratio ≥ 3.5 was associated with improved OS [median 33.0 months IQR (19.7-48.1) versus 17 months IQR (14.8-19.2), p = 0.004], and confirmed by a Cox-proportional hazards model independently associated with OS (HR = 0.58; p = 0.009), together with tumor size (HR = 1.02; p =0.012), R1/R2 status (HR = 1.53; p = 0.029), and receipt of adjuvant treatment (HR = 0.61; p = 0.021).

CONCLUSIONS

High MPD-to-pancreatic thickness ratio was associated with improved long-term survival in pancreaticoduodenectomy for cancer. Whether these features are related to tumor chronicity, indolent biology, or local growth over metastasis remains to be determined.

MDCT findings predicting post-operative residual tumor and survival in patients with pancreatic cancer

OBJECTIVES

To predict residual tumor (R) classification and overall survival (OS) on preoperative MDCT in patients who underwent first-line surgery for pancreatic ductal adenocarcinoma (PDA).

METHODS

Three hundred sixteen patients with PDA who underwent MDCT and first-line surgery were included. Patients were divided into a test (n = 216) and a validation group (n = 100). The R classification was categorized into R0 (no residual tumor) and R1/R2 (microscopic/macroscopic residual tumor). We assessed the correlation between the MDCT findings and the R classification. For survival analysis, we used the Kaplan-Meier estimation and Cox proportional hazard model to determine the prognostic factors for OS. Validation of the prediction models for the R classification and OS was performed using C statistics and calibration plot.

RESULTS

Peritumoral fat stranding (odds ratio (OR) 3.826), suspicious distant metastasis (OR 2.916), portal vein involvement (OR 2.795), and tumor size (OR 1.045) were independent predictors for residual tumor (p < .05). On survival analysis, common hepatic artery involvement (hazard ratio (HR) 5.656), R1/R2 stage (HR 2.476), and N1 stage (HR 1.745) were predictors of poor OS (p < .05). C statistics for prediction models for R classification and OS were 0.816 and 0.662, respectively. Calibration plots showed good predictive performance in a high probability of the R1/R2 stage or poor OS.

CONCLUSION

Preoperative MDCT is useful for predicting the R classification using the tumor size, peritumoral fat stranding, portal vein involvement, and suspicious distant metastasis, as well as for anticipating poor OS using the N1 stage, common hepatic artery involvement, and R1/R2 stage in patients with PDA.

KEY POINTS

• Thorough assessment of the involvement of common hepatic artery or portal vein and peritumoral fat stranding is warranted for predicting prognosis in patients with pancreatic ductal adenocarcinoma. • Not only encasement but also abutment of common hepatic artery or portal vein by tumor predicts poor prognosis after upfront surgery. • If residual tumor or poor overall survival is anticipated on preoperative MDCT, neoadjuvant treatment can be performed.

Clinical significance of defining borderline resectable pancreatic cancer

Since the introduction of the concept of borderline resectable pancreatic cancer (BRPC), various definitions of this disease entity have been suggested. However, there are several obstacles in defining this disease category. The current diagnostic criteria of BRPC mainly focuses on its expanded 'technical resectability'; however, they are difficult to interpret because of their ambiguity using potential subjective or arbitrary terminology, In addition, limitations in current imaging technology and a lack of evidence in radiological-pathological-clinical correlation make it difficult to refine the criteria. On the other hand, neoadjuvant treatment is usually applied to increase the R0 resection rate of BRPC focusing on the 'oncological curability'. However, evidence is needed concerning the effect of neoadjuvant treatment by quality-controlled prospective randomized clinical trials based on a standardized radiologic and pathologic reporting system. In conclusion, there are two aspects in the current concept of BRPC, which are technical resectability and oncological curability. Although the recent evolution of surgical techniques is expanding the scope of technical resectability, it should not be overlooked that the disease entity must be defined based on the evidence of oncological curability.

Imaging-based biomarkers: Changes in the tumor interface of pancreatic ductal adenocarcinoma on computed tomography scans indicate response to cytotoxic therapy

BACKGROUND

The assessment of pancreatic ductal adenocarcinoma (PDAC) response to therapy remains challenging. The objective of this study was to investigate whether changes in the tumor/parenchyma interface are associated with response.

METHODS

Computed tomography (CT) scans before and after therapy were reviewed in 4 cohorts: cohort 1 (99 patients with stage I/II PDAC who received neoadjuvant chemoradiation and surgery); cohort 2 (86 patients with stage IV PDAC who received chemotherapy), cohort 3 (94 patients with stage I/II PDAC who received protocol‐based neoadjuvant gemcitabine chemoradiation), and cohort 4 (47 patients with stage I/II PDAC who received neoadjuvant chemoradiation and were prospectively followed in a registry). The tumor/parenchyma interface was visually classified as either a type I response (the interface remained or became well defined) or a type II response (the interface became poorly defined) after therapy. Consensus (cohorts 1‐3) and individual (cohort 4) visual scoring was performed. Changes in enhancement at the interface were quantified using a proprietary platform.

RESULTS

In cohort 1, type I responders had a greater probability of achieving a complete or near‐complete pathologic response (21% vs 0%; P = .01). For cohorts 1, 2, and 3, type I responders had significantly longer disease‐free and overall survival, independent of traditional covariates of outcomes and of baseline and normalized cancer antigen 19‐9 levels. In cohort 4, 2 senior radiologists achieved a κ value of 0.8, and the interface score was associated with overall survival. The quantitative method revealed high specificity and sensitivity in classifying patients as type I or type II responders (with an area under the receiver operating curve of 0.92 in cohort 1, 0.96 in cohort 2, and 0.89 in cohort 3).

CONCLUSIONS

Changes at the PDAC/parenchyma interface may serve as an early predictor of response to therapy. Cancer 2018;124:1701‐9. © 2018 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

An imaging feature of pancreatic cancer is identified that indicates a response to cytotoxic therapies. This may be helpful as an early predictor of response for clinical trials and for deciding whether to change therapy.

Novel Diagnostic and Predictive Biomarkers in Pancreatic Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease for a multitude of reasons including very late diagnosis. This in part is due to the lack of understanding of the biological behavior of PDAC and the ineffective screening for this disease. Significant efforts have been dedicated to finding the appropriate serum and imaging biomarkers to help early detection and predict response to treatment of PDAC. Carbohydrate antigen 19-9 (CA 19-9) has been the most validated serum marker and has the highest positive predictive value as a stand-alone marker. When combined with carcinoembryonic antigen (CEA) and carbohydrate antigen 125 (CA 125), CA 19-9 can help predict the outcome of patients to surgery and chemotherapy. A slew of novel serum markers including multimarker panels as well as genetic and epigenetic materials have potential for early detection of pancreatic cancer, although these remain to be validated in larger trials. Imaging studies may not correlate with elevated serum markers. Critical features for determining PDAC include the presence of a mass, dilated pancreatic duct, and a duct cut-off sign. Features that are indicative of early metastasis includes neurovascular bundle involvement, duodenal invasion, and greater post contrast enhancement. 18-F-fluorodeoxyglucose (18-FDG) radiotracer uptake and changes following treatment may predict patient overall survival following treatment. Similarly, pretreatment apparent diffusion coefficient (ADC) values may predict prognosis with lower ADC lesions having worse outcome. Although these markers have provided significant improvement in the care of pancreatic cancer patients, further advancements can be made with perhaps better combination of markers or discovery of unique marker(s) to pancreatic cancer.

Resectable pancreatic adenocarcinoma: Role of CT quantitative imaging biomarkers for predicting pathology and patient outcomes

BACKGROUNDS

Patients with a pancreatic cancer amenable to surgery still have a poor prognosis and high risk of post-operative recurrence. We aimed to assess the value of quantitative imaging biomarkers using computed-tomography (CT) texture analysis to evaluate the pathologic tumor aggressiveness and predict disease-free survival (DFS) in patients with resectable pancreatic adenocarcinoma.

METHODS

We retrospectively performed attenuation measurements and texture analysis on the portal-venous phase of the pre-operative CT scan of 99 patients that underwent resection of a pancreatic ductal adenocarcinoma in two university hospitals. Tumor attenuation parameters included: mean attenuation value of the whole tumor (WHOLE-AV), and of the most hypoattenuating area within the tumor (CENTRAL-AV). Tumor heterogeneity parameters included: standard deviation, entropy, skewness, and kurtosis.

RESULTS

Tumor attenuation parameters showed significant association with the tumor differentiation grade (CENTRAL-AV, Odds ratio (OR) 0.968, 95% confidence interval (CI) 0.94-0.998) and lymph node invasion (WHOLE-AV, OR 0.886, CI 0.823-0.955). Variables associated with early-recurrence were: lymph node ratio (R²=0.15), kurtosis (R²=0.08), and CENTRAL-AV (R²=0.04). Lymph node ratio (Hazard ratio (HR) 1.02), and CENTRAL-AV (HR 0.98) were independently associated with shorter DFS. Patients with CENTRAL-AV<62 Hounsfield units had a shorter 1-year DFS (35% versus 68%, p=0.004).

CONCLUSION

Tumors that are more hypoattenuating on the portal-venous phase on CT scan are potentially more aggressive with higher tumor grade, greater lymph node invasion, and shorter DFS.

Erratum: CT Imaging Biomarkers Predict Clinical Outcomes After Pancreatic Cancer Surgery: Erratum

[This corrects the article DOI: 10.1097/MD.0000000000002664.].