Pancreatic adenocarcinoma: MRI conspicuity and pathologic correlations. ACTA ACUST UNITED AC. 2015;40:85-94. [PMID: 25030776 DOI: 10.1007/s00261-014-0196-8]

Quantitative Magnetic Resonance Imaging for the Pancreas: Current Status

ABSTRACT

Magnetic resonance imaging (MRI) is important for evaluating pancreatic disorders, and anatomical landmarks play a major role in the interpretation of results. Quantitative MRI is an effective diagnostic modality for various pathologic conditions, as it allows the investigation of various physical parameters. Recent advancements in quantitative MRI techniques have significantly improved the accuracy of pancreatic MRI. Consequently, this method has become an essential tool for the diagnosis, treatment, and monitoring of pancreatic diseases. This comprehensive review article presents the currently available evidence on the clinical utility of quantitative MRI of the pancreas.

Interobserver Variability and Accuracy of Preoperative CT and MRI in Pancreatic Ductal Adenocarcinoma Size Estimation: A Retrospective Cohort Study

Purpose: To assess interobserver variability and accuracy of preoperative computed tomography (CT) and magnetic resonance imaging (MRI) in pancreatic ductal adenocarcinoma (PDAC) size estimation using surgical specimens as standard of reference. Methods: Patients with PDAC who underwent preoperative CT and MRI examinations before surgery were included. PDAC largest axial dimension was measured by 2 readers on 8 MRI sequence and 2 CT imaging phases (pancreatic parenchymal and portal venous). Measurements were compared to actual tumour size at pathologic examination. Interobserver variability was assessed using intraclass correlation coefficients (ICC) and Bland-Altman plots. Differences in tumour size (Δdiameter) between imaging and actual tumour size were searched using Wilcoxon rank sum test. Results: Twenty-nine patients (16 men; median age, 70 years) with surgically resected PDAC were included. Interobserver reproducibility was good to excellent for all MRI sequences and the 2 CT imaging phases with ICCs between .862 (95%CI: .692-.942) for fat-saturated in-phase T1-weighted sequence and .955 (95%CI: .898-.980) for portal venous phase CT images. Best accuracy in PDAC size measurement was obtained with pancreatic parenchymal phase CT images with median Δdiameters of -2 mm for both readers, mean relative differences of -9% and -6% and no significant differences with dimensions at histopathological analysis (P = .051). All MRI sequences led to significant underestimation of PDAC size (median Δdiameters, -6 to -1 mm; mean relative differences, -21% to -11%). Conclusions: Most accurate measurement of PDAC size is obtained with CT images obtained during the pancreatic parenchymal phase. MRI results in significant underestimation of PDAC size.

Magnetic Resonance Radiomics and Machine-learning Models: An Approach for Evaluating Tumor-stroma Ratio in Patients with Pancreatic Ductal Adenocarcinoma

OBJECTIVE

To develop and validate a magnetic resonance imaging (MRI)-based machine learning classifier for evaluating the tumor-stroma ratio (TSR) in patients with pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

In this retrospective study, 148 patients with PDAC underwent an MR scan and surgical resection. We used hematoxylin and eosin to quantify the TSR. For each patient, we extracted 1,409 radiomics features and reduced them using the least absolute shrinkage and selection operator logistic regression algorithm. The extreme gradient boosting (XGBoost) classifier was developed using a training set comprising 110 consecutive patients, admitted between December 2016 and December 2017. The model was validated in 38 consecutive patients, admitted between January 2018 and April 2018. We determined the performance of the XGBoost classifier based on its discriminative ability, calibration, and clinical utility.

RESULTS

A log-rank test revealed significantly longer survival in the TSR-low group. The prediction model displayed good discrimination in the training (area under the curve [AUC], 0.82) and validation set (AUC, 0.78). While the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for the training set were 77.14%, 75.00%, 0.76%, 0.84%, and 0.65%, respectively, those for the validation set were 58.33%, 92.86%, 0.71%, 0.93%, and 0.57%, respectively.

CONCLUSION

We developed an XGBoost classifier based on MRI radiomics features, a non-invasive prediction tool that can evaluate the TSR of patients with PDAC. Moreover, it will provide a basis for interstitial targeted therapy selection and monitoring.

Fractal analysis improves tumour size measurement on computed tomography in pancreatic ductal adenocarcinoma: comparison with gross pathology and multi-parametric MRI

Objectives

Tumour size measurement is pivotal for staging and stratifying patients with pancreatic ductal adenocarcinoma (PDA). However, computed tomography (CT) frequently underestimates tumour size due to insufficient depiction of the tumour rim. CT-derived fractal dimension (FD) maps might help to visualise perfusion chaos, thus allowing more realistic size measurement.

Methods

In 46 patients with histology-proven PDA, we compared tumour size measurements in routine multiphasic CT scans, CT-derived FD maps, multi-parametric magnetic resonance imaging (mpMRI), and, where available, gross pathology of resected specimens. Gross pathology was available as reference for diameter measurement in a discovery cohort of 10 patients. The remaining 36 patients constituted a separate validation cohort with mpMRI as reference for diameter and volume.

Results

Median RECIST diameter of all included tumours was 40 mm (range: 18–82 mm). In the discovery cohort, we found significant (p = 0.03) underestimation of tumour diameter on CT compared with gross pathology (Δdiameter_3D = −5.7 mm), while realistic diameter measurements were obtained from FD maps (Δdiameter_3D = 0.6 mm) and mpMRI (Δdiameter_3D = −0.9 mm), with excellent correlation between the two (R² = 0.88). In the validation cohort, CT also systematically underestimated tumour size in comparison to mpMRI (Δdiameter_3D = −10.6 mm, Δvolume = −10.2 mL), especially in larger tumours. In contrast, FD map measurements agreed excellently with mpMRI (Δdiameter_3D = +1.5 mm, Δvolume = −0.6 mL). Quantitative perfusion chaos was significantly (p = 0.001) higher in the tumour rim (FD_rim = 4.43) compared to the core (FD_core = 4.37) and remote pancreas (FD_pancreas = 4.28).

Conclusions

In PDA, fractal analysis visualises perfusion chaos in the tumour rim and improves size measurement on CT in comparison to gross pathology and mpMRI, thus compensating for size underestimation from routine CT.

Key Points

• CT-based measurement of tumour size in pancreatic adenocarcinoma systematically underestimates both tumour diameter (Δdiameter = −10.6 mm) and volume (Δvolume = −10.2 mL), especially in larger tumours.

• Fractal analysis provides maps of the fractal dimension (FD), which enable a more reliable and size-independent measurement using gross pathology or multi-parametric MRI as reference standards.

• FD quantifies perfusion chaos—the underlying pathophysiological principle—and can separate the more chaotic tumour rim from the tumour core and adjacent non-tumourous pancreas tissue.

The Role of MRI Pancreatic Protocol in Assessing Response to Neoadjuvant Therapy for Patients With Borderline Resectable Pancreatic Cancer

BACKGROUND

Borderline Resectable Pancreatic Cancer (BRPC) remains a unique entity that is difficult to categorize due to variance in definitions and the small number of patients. The ultimate goal is to achieve a free resection (R0) after a favorable response to neoadjuvant therapy that is somewhat difficult to assess by current radiological parameters.

AIM

To evaluate the role of Magnetic Resonance Imaging (MRI) pancreatic protocol, including Diffusion-Weighted Imaging (DWI), in patients with BRPC receiving neoadjuvant therapy, and further compare it to RECIST criteria and outcome.

METHODS

Histologically confirmed BRPC patients were prospectively included. DWI-MRI was performed pre- and post-therapy. Clinical characteristics with ensuing operability were recorded and correlated to radiological RECIST/apparent diffusion coefficient (ADC) change, preoperative therapy administrated, surgical resection status, and survival.

RESULTS

Out of 30 BRPC cases, only 11 (36.7%) ultimately underwent pancreaticoduodenectomy. Attaining a stationary or stable disease via ADC/RECIST was achieved in the majority of cases (60%/53.3% respectively). Of the 12 patients (40%) who achieved a regression by ADC, 11 underwent surgery with an R0 status. These surgical cases showed variable RECIST responses (PR=5, SD=4, PD=3). Responders by ADC to neoadjuvant therapy were significantly associated to presenting with abdominal pain (p =0.07), a decline in post-therapy CA19-9 (p<0.001), going through surgery (p<0.001), and even achieving better survival (p<0.001 vs. 0.66).

CONCLUSION

DWI-MRI ADC picked up patients most likely to undergo a successful operative procedure better than traditional RECIST criteria. An algorithm incorporating novel radiological advances with CA19-9 deserves further assessment in future studies.

CT Radiomics and Machine-Learning Models for Predicting Tumor-Stroma Ratio in Patients With Pancreatic Ductal Adenocarcinoma

Purpose

To develop and validate a machine learning classifier based on multidetector computed tomography (MDCT), for the preoperative prediction of tumor-stroma ratio (TSR) expression in patients with pancreatic ductal adenocarcinoma (PDAC).

Materials and Methods

In this retrospective study, 227 patients with PDAC underwent an MDCT scan and surgical resection. We quantified the TSR by using hematoxylin and eosin staining and extracted 1409 arterial and portal venous phase radiomics features for each patient, respectively. Moreover, we used the least absolute shrinkage and selection operator logistic regression algorithm to reduce the features. The extreme gradient boosting (XGBoost) was developed using a training set consisting of 167 consecutive patients, admitted between December 2016 and December 2017. The model was validated in 60 consecutive patients, admitted between January 2018 and April 2018. We determined the XGBoost classifier performance based on its discriminative ability, calibration, and clinical utility.

Results

We observed low and high TSR in 91 (40.09%) and 136 (59.91%) patients, respectively. A log-rank test revealed significantly longer survival for patients in the TSR-low group than those in the TSR-high group. The prediction model revealed good discrimination in the training (area under the curve [AUC]= 0.93) and moderate discrimination in the validation set (AUC= 0.63). While the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for the training set were 94.06%, 81.82%, 0.89, 0.89, and 0.90, respectively, those for the validation set were 85.71%, 48.00%, 0.70, 0.70, and 0.71, respectively.

Conclusions

The CT radiomics-based XGBoost classifier provides a potentially valuable noninvasive tool to predict TSR in patients with PDAC and optimize risk stratification.

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.

Repeatability of Apparent Diffusion Coefficient at 3.0 Tesla in Normal Pancreas

Purpose: To evaluate the apparent diffusion coefficient (ADC) test-retest repeatability of the normal pancreas based on diffusion-weighted imaging (DWI).

Methods: Twenty-six healthy volunteers (mean 47.6 years; 13 men) were included and scanned twice with reposition for a DWI sequence at 3.0-T. Two readers measured the ADCs of pancreatic head, body and tail for two DWIs, independently. The mean ADCs of the pancreatic head, body and tail were calculated as the global pancreatic ADC. Test-retest repeatability and agreement of ADC measurement were evaluated by the Bland-Altman analysis, intra-class correlation coefficient (ICC) and coefficient of variation (CV).

Results: The global pancreatic ADC showed the best test-retest repeatability (mean difference ± limits of agreement were 0.05 ± 0.25×10^-3 mm²/s; ICC, 0.79; CV, 6%). Test-retest repeatabilities for ADC of pancreatic head, body or tail were scattered, with mean difference ± limits of agreement between two tests were 0.03 ± 0.47, 0.05 ± 0.42 and 0.06 ± 0.31 (×10^-3 mm²/s) (ICCs, 0.81, 0.52 and 0.68; CVs, 9%, 8% and 8%), respectively. Both intra-observer repeatability and inter-observer reproducibility were acceptable for global pancreatic ADC between measurements of the two DWIs.

Conclusions:The best test-retest repeatability of ADC in the normal pancreas was only for the whole pancreas with a CV of 6%. Cautions should be taken in interpreting longitudinal clinical changes in ADC values of the normal pancreas for the measurements do have an inherent variability by locations.

S100A4 overexpression in pancreatic ductal adenocarcinoma: imaging biomarkers from whole-tumor evaluation with MRI and texture analysis

OBJECTIVE

To investigate the relationship between imaging findings and S100A4 overexpression in pancreatic ductal adenocarcinoma (PDAC) and to determine imaging biomarkers of S100A4 overexpression from whole-tumor evaluation with MRI and texture analysis.

METHODS

A total of 60 patients with pathologically confirmed PDAC were included in the study. All patients underwent preoperative abdominal contrast-enhanced MRI examination with Magnetom Aera (Siemens Healthcare, Germany, 1.5 T) at our institute. Whole-tumor evaluation including texture analysis was performed. Sections of specimens were reviewed, and the S100A4 expression status was quantitatively evaluated. Univariate and multivariate logistic regression analyses were conducted to find imaging biomarkers that could predict S100A4 overexpression.

RESULTS

Twenty-four tumors (40.0%) had negative results for S100A4 overexpression, and 36 tumors (60.0%) exhibited overexpression. After univariate and multivariate analysis, distal pancreatic duct dilatation, T₁WI_10th percentile and the enhancement rate difference between delayed phase (DP) and portal venous phase (PVP) were identified to predict S100A4 overexpression in PDAC independently (p = 0.009, 0.012 and 0.044), with odds ratios (ORs) of 0.102, 0.139 and 4.645, respectively. The area under the ROC curve (AUC) values were 0.715, 0.707 and 0.691. The AUC value of the proposed model was 0.877 with a sensitivity of 80.6% and specificity of 75.0%.

CONCLUSION

A model including distal pancreatic duct dilatation, T₁WI_10th percentile and the enhancement rate difference between the DP and PVP could predict S100A4 overexpression in PDAC as imaging biomarkers.

Pancreatic adenocarcinoma: variability in measurements of tumor size among computed tomography, magnetic resonance imaging, and pathologic specimens

PURPOSE

To compare the tumor size measurements assessed by computed tomography (CT) and magnetic resonance imaging (MRI) versus measurements of resected pathologic specimens from patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

This study included 114 patients with histologically confirmed PDAC who underwent contrast-enhanced CT and MRI before surgery. The tumor sizes from CT, MRI, and pathologic specimens were compared by using Bland-Altman analyses and intraclass correlation coefficients (ICCs). The discrepancies in PDAC size between CT/MRI and pathologic specimens were calculated and contributing factors for the discrepancies, including tumor locations (pancreatic head/neck, body, or tail), T stages (T1, T2, or T3), and N stages (N0, N1, or N2), were analyzed with Pearson's correlation coefficients and multivariable linear regression analyses.

RESULTS

There was significant difference among the mean tumor sizes of three measurements (P < 0.001). The difference in mean tumor size between the pathologic sizes for PDAC was 4.3 mm (ICC 0.67) on CT and 5.8 mm (ICC 0.65) on MRI. Both CT and MRI showed wide ranges of limits of agreement (LOAs) between the pathologic specimens for tumor size measurements (LOAs, - 28.9 to 21.4 and - 29.4 to 17.8, respectively). The tumor size on CT or MRI was estimated to be smaller than that on pathology when the tumor was > 30 mm. The discrepancies in the tumor size estimated between CT/MRI and pathologic specimens were significantly different for tumors of different T stages (P < 0.001).

CONCLUSIONS

Both contrast-enhanced CT and MRI underestimate the mean tumor size by 4.3 mm and 5.8 mm, respectively, compared to the size of pathologic specimens. A larger tumor size indicates a greater discrepancy in the PDAC size measurements between CT/MRI and pathologic specimens.

Differential Diagnosis of Nonhypervascular Pancreatic Neuroendocrine Neoplasms From Pancreatic Ductal Adenocarcinomas, Based on Computed Tomography Radiological Features and Texture Analysis

RATIONALE AND OBJECTIVES

To determine computed tomography (CT) radiological features and texture features that are rewarding in differentiating nonhypervascular pancreatic neuroendocrine neoplasms (PNENs) from pancreatic ductal adenocarcinomas (PDACs).

MATERIALS AND METHODS

We compared patients to pathologically proven nonhypervascular PNENs and age-matched controls with pathologically proven PDACs in a 1:2 ratio. Preoperative CT images in the arterial phase (AP) and portal vein phase (PVP) were obtained. Two radiologists independently reviewed the morphological characteristics of each tumor. Three-dimensional regions of interest (ROIs), drawn using ITK-SNAP software, were input into AK software (Artificial Intelligent Kit, GE) to extract texture features from AP and PVP images. Differences between PNENs and PDACs were analyzed with the chi-squared test, least absolute shrinkage and selection operator, kappa statistics, and uni- and multivariate logistic regression analyses.

RESULTS

In total, 40 nonhypervascular PNENs and 80 PDACs were evaluated. Maximum diameter on axial section, margin, calcification, vascularity in the tumor, and tumor heterogeneity were significantly different between PDACs and nonhypervascular PNENs. Multivariate analysis showed well-defined tumor margin (odds ratio: 21.0) and presence of calcification (odds ratio: 4.4) were significant predictors of nonhypervascular PNENs. The area under the receiver operating characteristic curve of the radiological feature model, AP texture model, and PVP texture model were 0.780, 0.855, and 0.929, respectively, based on logistic regression.

CONCLUSION

A well-defined margin and calcification in the tumor were helpful in discriminating nonhypervascular PNENs from PDACs. Texture analysis of contrast-enhanced CT images could be beneficial in differentially diagnosing nonhypervascular PNENs and PDACs.

A planning strategy for combined motion-assisted/gated MR guided focused ultrasound treatment of the pancreas

Objective: To develop and evaluate a combined motion-assisted/gated MRHIFU heating strategy designed to accelerate the treatment procedure by reducing the required number of sonications to ablate a target volume in the pancreas. Methods: A planning method for combined motion-assisted/gated MRHIFU using 4D-MRI and motion characterization is introduced. Six healthy volunteers underwent 4D-MRI for target motion characterization on a 3.0-T clinical scanner. Using displacement patterns, simulations were performed for all volunteers for three sonication approaches: gated, combined motion-assisted/gated, and static. The number of sonications needed to ablate the pancreas head was compared. The influence of displacement amplitude and target volume size was investigated. Spherical target volumes (8, 15, 20 and 34 mL) and displacement amplitudes ranging from 5 to 25 mm were evaluated. For this case, the number of sonications required to ablate the whole target was determined. Results: The number of required sonications was lowest for a static target, 62 on average (range 49-78). The gated approach required most sonications, 126 (range 97-159). The combined approach was almost as efficient as the hypothetical static case, with an average of 78 (range 53-123). Simulations showed that with a 5-mm displacement amplitude, the target could be treated by making use of motion-assisted MRHIFU sonications only. In that case, this approach allowed the lowest number of sonication, while for 10 mm and above, the number of required sonications increased. Conclusion: The use of a combined motion-assisted/gated MRHIFU strategy may accelerate tumor ablation in the pancreas when respiratory-induced displacement amplitudes are between 5 and 10 mm.

Staging of pancreatic cancer: resectable, borderline resectable, and unresectable disease

Pancreatic ductal adenocarcinoma (PDAC) is a relatively common malignancy that carries an overall poor prognosis, with five-year survival below 10%. Despite ongoing research, surgical resection remains the only potentially curative treatment. Therefore, accurate identification of those patients who would benefit from surgical resection is of paramount importance. High-quality imaging and image interpretation is central to this process. Radiology helps in the determination of whether patients are resectable, borderline resectable, or unresectable and guides treatment planning.

Comparison of Navigator Triggering Reduced Field of View and Large Field of View Diffusion-Weighted Imaging of the Pancreas

RATIONALE AND OBJECTIVES

The purpose of this study is to compare image quality, presence and grade of artifacts, signal-to-noise ratio, and apparent diffusion coefficient (ADC) values in pancreatic tissue between high-resolution navigator-triggered (NT) restricted field of view (rFOV) FOCUS single-shot (SS) echo-planar imaging (EPI) diffusion-weighted imaging (DWI) and NT large FOV SS-EPI DWI.

MATERIALS AND METHODS

Magnetic resonance imaging examinations were performed with GE 3-T systems using a 32-channel body array coil. Seventeen consecutive patients were imaged. A 5-point scale semiquantitative grading system was used to evaluate image quality and general artifacts. Signal-to-noise ratio and ADC were measured in the head, body, and tail of the pancreas. Statistical analysis was performed using Student t test and Wilcoxon signed rank test, with differences considered significant for P value less than 0.05.

RESULTS

More artifacts were present on large FOV compared with rFOV FOCUS SS-EPI DW images (P < 0.01). Restricted field of view image quality was subjectively better (P < 0.01). No difference in the signal-to-noise ratio was demonstrated between the 2 image datasets. Apparent diffusion coefficient values were significantly lower (P < 0.01) when calculated from rFOV images than large FOV images.

CONCLUSIONS

Our results demonstrate better image quality and reduced artifacts in rFOV images compared with large FOV DWI. Measurements from ADC maps derived from rFOV DWI show significantly lower ADC values when compared with ADC maps derived from large FOV DWI.

Single extracorporeal shock-wave lithotripsy for proximal ureter stones: Can CT texture analysis technique help predict the therapeutic effect?

PURPOSE

To explore whether the computed tomography texture analysis (CTTA) technique can help predict the curative effects of a single extracorporeal shock-wave lithotripsy (ESWL) for proximal ureteral stones.

MATERIALS AND METHODS

In all, 100 patients with proximal ureteral stone underwent non-enhanced multi-detector computed tomography (MDCT) before ESWL. The patients were divided into success and failure groups. Success of ESWL was defined as the patients being stone-free or having residual stone fragments of ≤2 mm. Traditional characteristics, such as stone size, body mass index (BMI), and skin-to-stone distance (SSD), and CTTA metrics, such as the mean Hounsfield unit (HU) density, entropy, kurtosis, and skewness, were analyzed and compared between two groups by univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curves were generated to determine Youden index-based cutoff values.

RESULT

Failure of stone removal was observed in 36 patients (36%). Stone height, stone cross-sectional diameter, largest cross-sectional area, stone volume, stone density (mean HU), and CTTA metrics (kurtosis and entropy) were the significant independent predictors of ESWL success on univariate analysis (p < 0.05). On multivariate analysis, mean HU, skewness, and kurtosis were shown to be significant predictors of ESWL success (p < 0.05). In subgroup analysis based on the cutoff value of mean stone density (HU = 857), the only significant independent factor associated with both subgroups was kurtosis (p < 0.05).

CONCLUSIONS

As a quantitative analysis method, CTTA may be helpful in selecting appropriate ESWL patients. High kurtosis and low mean HU values simultaneously indicate a relatively higher ESWL success rate.

Changes in the microarchitecture of the pancreatic cancer stroma are linked to neutrophil-dependent reprogramming of stellate cells and reflected by diffusion-weighted magnetic resonance imaging

In pancreatic cancer (PDAC) intratumor infiltration of polymorphonuclear neutrophils (PMN) is associated with histologically apparent alterations of the tumor growth pattern. The aim of this study was to examine possible associations between PMN infiltration, tumor microarchitecture, and water diffusivity in diffusion-weighted magnetic resonance imaging (DW-MRI), and to further asses the underlying mechanisms.

Methods: DW-MRI was performed in 33 PDAC patients prior to surgery. In parallel, tissue specimen were examined histologically for growth pattern, azurocidin-positive PMN infiltrates, and the presence of alpha-smooth muscle actin (α-SMA) and metalloproteinase 9 (MMP9)-positive myofibroblastic cells. For confirmation of the histological findings, a tissue microarray of a second cohort of patients (n=109) was prepared and examined similarly. For in vitro studies, the pancreatic stellate cell line RLT was co-cultivated either with isolated PMN, PMN-lysates, or recombinant azurocidin and characterized by Western blot, flow cytometry, and proteome profiler arrays.

Results: Tumors with high PMN density showed restricted water diffusion in DW-MRI and histologic apparent alterations of the tumor microarchitecture (microglandular, micropapillary, or overall poorly differentiated growth pattern) as opposed to tumors with scattered PMN. Areas with altered growth pattern lacked α-SMA-positive myofibroblastic cells. Tissue microarrays confirmed a close association of high PMN density with alterations of the tumor microarchitecture and revealed a significant association of high PMN density with poor histologic grade of differentiation (G3). In vitro experiments provided evidence for direct effects of PMN on stellate cells, where a change to a spindle shaped cell morphology in response to PMN and to PMN-derived azurocidin was seen. Azurocidin incorporated into stellate cells, where it associated with F-actin. Down-regulation of α-SMA was seen within hours, as was activation of the p38-cofilin axis, up-regulation of MMP9, and acquisition of intracellular lipid droplets, which together indicate a phenotype switch of the stellate cells.

Conclusion: In PDAC, PMN infiltrates are associated with alterations of the tumor microarchitecture. As a causal relationship, we propose a reprogramming of stellate cells by PMN-derived azurocidin towards a phenotype, which affects the microarchitecture of the tumor.

Nonhypervascular Pancreatic Neuroendocrine Tumors: Differential Diagnosis from Pancreatic Ductal Adenocarcinomas at MR Imaging-Retrospective Cross-sectional Study

Purpose To determine useful magnetic resonance (MR) imaging features to differentiate nonhypervascular pancreatic neuroendocrine tumors (PNETs) from pancreatic ductal adenocarcinomas (PDACs). Materials and Methods The institutional review board approved this retrospective study and waived the informed consent requirement. Seventy-four patients with surgically confirmed PNETs and 82 patients with PDACs who underwent gadobutrol-enhanced MR imaging were included. Two radiologists independently evaluated the morphologic characteristics and temporal enhancement patterns of each tumor. Quantitative analysis, including measurement of tumor size, maximal upstream parenchymal thickness (MUPT), contrast-to-noise ratio, and apparent diffusion coefficient values, was performed. Uni- and multivariate logistic regression analyses were performed to identify relevant features to differentiate between PNETs and PDACs. Results On the basis of arterial enhancement, 38 PNETs (51%, 38 of 74) were hypervascular and 36 PNETs (49%, 36 of 74) were nonhypervascular. At MR imaging, nonhypervascular PNETs showed significantly higher frequencies of a well-defined margin, portal hyper- or isoenhancement, and MUPT of 10 mm or greater but lower frequencies of ductal dilatation, vascular invasion, and peripancreatic infiltration when compared with PDACs (P < .05 for all). At multivariate analysis, a well-defined margin and portal hyper- or isoenhancement were independent significant differentiators of PNETs from PDACs (odds ratio, 20.3 and 16.1, respectively). When applying the criteria of a well-defined margin and portal hyper- or isoenhancement, 64% of sensitivity and 99% of specificity were observed for the differential diagnosis of PNETs from PDACs. Conclusion A well-defined margin and hyper- or isoenhancement in the portal venous phase are useful MR imaging features that are more common in nonhypervascular PNETs and may help discriminate nonhypervascular PNETs from PDACs. © RSNA, 2017 Online supplemental material is available for this article.

Optimized ROI size on ADC measurements of normal pancreas, pancreatic cancer and mass-forming chronic pancreatitis

Objectives

To investigate the effects of region of interest (ROI) sizes on apparent diffusion coefficient (ADC) measurements for the differentiation of normal pancreas (NP), pancreatic ductal adenocarcinoma (PDAC) and mass-forming chronic pancreatitis (MFCP).

Results

There were no significant differences for the mean ADCs measured by 12 different-size ROIs for MFCP, or PDAC and NP (P = 0.858–1.0). With the increase of ROI size (≥ 55 mm²), ADCs of PDAC were significantly lower than those of NP (all P < 0.05), but there was no difference of the accuracy in ADC for differentiating the two groups only at a ROI size of 214 mm². When ROI size was above 99 mm², ADCs of MFCP were significantly lower than those of NP (all P < 0.05). There were no significant differences for any of the mean ADCs measured by 12 different-size ROIs between PDAC and MFCP (P > 0.05).

Materials and Methods

Diffusion-weighted imaging (DWI) was performed on 89 participants: 64 with PDAC, 7 with MFCP, as well as 18 healthy volunteers. ADC maps were created using mono-exponential model. A homemade software was used to measure the mean ADC values of 12 concentric round ROIs (areas: 15, 46, 55, 82, 99, 121, 134, 152, 161, 189, 214, 223, and 245 mm²) for the mass of lesions and the NP tissue.

Conclusions

In ADC measurements, the optimized ROI size is 214 mm² for the differentiation of PDAC and NP; ROI size of ≥ 99 mm² is recommended to differentiate between MFCP and NP. ADC was not useful for the differentiation of PDAC and MFCP.

MR and CT imaging characteristics and ablation zone volumetry of locally advanced pancreatic cancer treated with irreversible electroporation

OBJECTIVES

To assess specific imaging characteristics after irreversible electroporation (IRE) for locally advanced pancreatic carcinoma (LAPC) with contrast-enhanced (ce)MRI and ceCT, and to explore the correlation of these characteristics with the development of recurrence.

METHODS

Qualitative and quantitative analyses of imaging data were performed on 25 patients treated with percutaneous IRE for LAPC. Imaging characteristics of the ablation zone on ceCT and ceMRI were assessed over a 6-month follow-up period. Contrast ratio scores between pre- and post-treatment were compared. To detect early imaging markers for treatment failure, attenuation characteristics at 6 weeks were linked to the area of recurrence within 6 months.

RESULTS

Post-IRE, diffusion-weighted imaging (DWI)-b800 signal intensities decreased in all cases (p < 0.05). Both ceMRI and ceCT revealed absent or decreased contrast enhancement, with a hyperintense rim on ceMRI. Ablation zone volume increase was noted on both modalities in the first 6 weeks, followed by a decrease (p < 0.05). In the patients developing tumour recurrence (5/25), a focal DWI-b800 hyperintense spot at 6 weeks predated unequivocal recurrence on CT.

CONCLUSION

The most remarkable signal alterations after pancreatic IRE were shown by DWI-b800 and ceMRI. These early imaging characteristics may be useful to establish technical success and predict treatment outcome.

KEY POINTS

• This study describes imaging characteristics after irreversible electroporation (IRE) for pancreatic adenocarcinoma. • Familiarity with typical post-IRE imaging characteristics helps to interpret ablation zones. • Post-IRE, no central and variable rim enhancement are visible on contrast-enhanced imaging. • DWI-b800 may prove useful to predict early tumour recurrence. • Post-IRE examinations reveal an initial volume increase followed by a decrease.

Effect of region of interest size on ADC measurements in pancreatic adenocarcinoma

BACKGROUND

To investigate the influence of region of interest (ROI) size on tumor apparent diffusion coefficient (ADC) measurements in pancreatic cancer.

METHODS

The study population consisted of 64 patients with pathologically proved pancreatic ductal adenocarcinomas (PDACs), who underwent preoperative magnetic resonance imaging (MRI) examinations including diffusion-weighted imaging (DWI). The tumor ADCs were measured by two independent readers using six round ROIs with sizes ranging from 20 to 214 mm² (9 to 97 pixels) in both the six separate measurements. The intra- and inter-observer variabilities were analyzed by using the coefficient of variance (CV), the interclass correlation coefficient (ICC) and Bland-Altman analysis. The mean ADCs measured with the 6 different-sized ROIs were compared using one-way repeated analysis of variance. The sample sizes were calculated by using 80% power and a 5% significance level to detect 10 to 25% changes in ADC measurements.

RESULTS

The largest ROI (ROI₂₁₄) yielded the best intra-observer repeatability (CV, 6.3%; ICC, 0.93) and inter-observer reproducibility (CV, 10.1%; ICC, 0.84). The mean differences in ADC measurements ± limits of agreement between the two readers were (0.06 ± 0.47) × 10^-3 mm² for ROI₂₀, (0.08 ± 0.46) × 10^-3 mm² for ROI₄₆, (0.05 ± 0.37) × 10^-3 mm² for ROI₈₂, (0.07 ± 0.42) × 10^-3 mm² for ROI₁₁₅, (0.05 ± 0.43) × 10^-3 mm² for ROI₁₅₂ and (-0.02 ± 0.29) × 10^-3 mm² for ROI₂₁₄.

CONCLUSIONS

ROI size had a considerable influence on the ADC measurements of PDACs.

Diffusion-weighted and dynamic contrast-enhanced MRI of pancreatic adenocarcinoma xenografts: associations with tumor differentiation and collagen content

PURPOSE

The aggressiveness of pancreatic ductal adenocarcinoma (PDAC) is highly dependent on the level of differentiation and the composition of the stroma. In this preclinical study, we investigated the potential of diffusion-weighted magnetic resonance imaging (DW-MRI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as noninvasive methods for providing information on the differentiation and the stroma of PDACs.

METHODS

Xenografted tumors initiated from four PDAC cell lines (BxPC-3, Capan-2, MIAPaCa-2, and Panc-1) were included in the study. DW-MRI and DCE-MRI were carried out on a 7.05-T MR scanner, and tumor images of ADC (the apparent diffusion coefficient), K (trans) (the volume transfer constant of Gd-DOTA), and v e (the fractional distribution volume of Gd-DOTA) were produced. The level of differentiation and the amount and structure of collagen I and collagen IV were determined by examining histological preparations.

RESULTS

Differentiated tumors showed lower levels of collagen I and collagen IV than non-differentiated tumors. Significant correlations were found between ADC and v e, and both parameters differentiated clearly between collagen-rich non-differentiated tumors and differentiated tumors containing less collagen.

CONCLUSION

Differentiated PDAC xenografts show higher ADC values and higher v e values than their non-differentiated counterparts. This observation supports the application of parametric MR images as tumor biomarkers in PDAC. Patients showing low values of ADC and v e most likely have non-differentiated tumors with extensive stroma and, hence, poor prognosis.

Diffusion-weighted MR imaging of pancreatic cancer and inflammation: Prognostic significance of pancreatic inflammation in pancreatic cancer patients

BACKGROUND

Pancreatic cancer often accompanies chronic obstructive pancreatitis (COP) due to obstruction of the main pancreatic duct, and the inflammatory environment may enhance cancer progression. The purpose of this study is to evaluate COP using the apparent diffusion coefficient (ADC) value measured by diffusion-weighted MR imaging (DWI), and to assess its prognostic significance in pancreatic cancer.

METHODS

Twenty-eight patients (16 men, 12 women; mean age 67.1 years) with pancreatic cancers who underwent DWI followed by curative surgery were evaluated. The ADC value of pancreatic parenchyma upstream to the tumor (upstream pancreas) was measured and compared with the upstream pancreatic duct dilatation to assess whether DWI could reflect COP. The ADC values of tumor and upstream portion were compared with overall survival (OS) using Cox regression and Kaplan-Meier analysis.

RESULTS

The ADC value of upstream pancreas was significantly lower in patients with greater dilated pancreatic duct than those with less (P = 0.03). In univariate Cox regression analysis, the ADC value of upstream pancreas showed a significant association with OS (P = 0.01), but that of tumor did not (P = 0.06). In Kaplan-Meier analysis, patients with lower ADC value of upstream pancreas (<1.36 × 10(-3) mm(2)/s) were significantly associated with poor OS (P = 0.0006). In multivariate analysis, the ADC value of upstream pancreas was identified as an independent prognostic factor (P = 0.01; hazards ratio, 0.05; 95% CI, 0.004-0.59).

CONCLUSIONS

The ADC value of upstream pancreas was an independent prognostic factor for OS in pancreatic cancer patients. Inflammatory environment may play an important role in pancreatic cancer progression.

Pancreatic Neuroendocrine Neoplasms: Clinical Value of Diffusion-Weighted Imaging

BACKGROUND/AIMS

Diffusion-weighted imaging (DWI) can depict random motions of water molecules in biological tissues during magnetic resonance (MR) examinations. Few papers have tested its application to pancreatic neuroendocrine neoplasms (PanNENs). The aim of this paper is to assess the clinical value of DWI regarding the identification and characterization of PanNENs and diagnosis of liver metastases.

METHODS

Preoperative MR examinations of 30 PanNEN patients were retrospectively reviewed; 30 patients with pathologically proven pancreatic ductal adenocarcinoma (PDAC) were included to compare the imaging features. Qualitative and quantitative MR features were compared between histotypes. A blinded-reader comparison of diagnostic confidence for PanNENs and liver metastases was conducted on randomized image sets. All results were compared with pathological data.

RESULTS

PanNEN conspicuity was higher on DW images compared to conventional MR sequences. DWI had higher detection rates for PanNENs than had conventional sequences (93.3 vs. 71.1%). Sharp margins and absence of main pancreatic duct/common bile duct dilation and chronic pancreatitis were more common among PanNENs as compared to PDACs. Arterial iso- or hyperenhancement and portal hyperenhancement were more frequent within PanNENs as compared to PDACs. No differences between histotypes were found for quantitative features. Arterial-phase images had the highest interobserver agreement for the diagnosis of PanNEN (Cohen's κ = 0.667). DWI provided the highest detection rate for liver metastases as well as excellent interobserver agreement for the diagnosis of liver metastases (κ = 0.932), with good accuracy (AUC = 0.879-0.869).

CONCLUSION

DWI has clinical value regarding the identification of PanNENs and the diagnosis of liver metastases, while conventional MR sequences are fundamental for their characterization.

Comparison of the Diagnostic Performances of Three Techniques of ROI Placement for ADC Measurements in Pancreatic Adenocarcinoma

RATIONALE AND OBJECTIVES

To prospectively investigate and compare three techniques of region of interest (ROI) placement for apparent diffusion coefficient (ADC) measurements in patients with pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

Twenty-one patients with surgical pathology-proven PDAC and 18 healthy volunteers were included. Respiratory-triggered single-shot echo-planar diffusion-weighted imaging (b values = 0, 600 s/mm(2)) was used to calculate the ADC maps across all participants. Three readers independently measured the ADCs according to three ROI methods: whole-volume, single-slice, and small solid samples of tumor. Mean ADCs for the healthy pancreas were calculated using three measurements from pancreatic head to tail, and ADCs of distal pancreas to the tumor were also measured. The interobserver variability for the three techniques was measured using the interclass correlation coefficient. The diagnostic performances were calculated and compared using the receiver operating characteristic curves (ROC).

RESULTS

All the ADCs measured from the three ROI placements on PDAC were significantly lower than that from the normal pancreas. ADCs of solid tumor samples were significantly lower than that measured from whole volume or single slice (both P < .001). Only the ADCs measured from the solid sample ROI placements on tumor were observed significantly lower than the ADC of distal pancreatic parenchyma (P = .005). Areas under the ROC for the identification of PDAC, based on small solid samples, single-slice and whole-volume ROIs, respectively, were 0.939, 0.791, and 0.735.

CONCLUSIONS

ADC based on the small solid samples of tumor provided the highest diagnostic performance in assessing PDAC and was more accurate than ADCs measured from single-slice or whole-volume ROI.

Diffusion-weighted imaging of pancreatic cancer

Magnetic resonance imaging (MRI) is a reliable and accurate imaging method for the evaluation of patients with pancreatic ductal adenocarcinoma (PDAC). Diffusion-weighted imaging (DWI) is a relatively recent technological improvement that expanded MRI capabilities, having brought functional aspects into conventional morphologic MRI evaluation. DWI can depict the random diffusion of water molecules within tissues (the so-called Brownian motions). Modifications of water diffusion induced by different factors acting on the extracellular and intracellular spaces, as increased cell density, edema, fibrosis, or altered functionality of cell membranes, can be detected using this MR sequence. The intravoxel incoherent motion (IVIM) model is an advanced DWI technique that consent a separate quantitative evaluation of all the microscopic random motions that contribute to DWI, which are essentially represented by molecular diffusion and blood microcirculation (perfusion). Technological improvements have made possible the routine use of DWI during abdominal MRI study. Several authors have reported that the addition of DWI sequence can be of value for the evaluation of patients with PDAC, especially improving the staging; nevertheless, it is still unclear whether and how DWI could be helpful for identification, characterization, prognostic stratification and follow-up during treatment. The aim of this paper is to review up-to-date literature data regarding the applications of DWI and IVIM to PDACs.

Apparent diffusion coefficient (ADC) measurements in pancreatic adenocarcinoma: A preliminary study of the effect of region of interest on ADC values and interobserver variability

PURPOSE

To assess the influence of region of interest (ROI) on tumor apparent diffusion coefficient (ADC) measurements and interobserver variability in pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

Twenty-two patients recruited with pathology-proven PDAC underwent diffusion-weighted imaging (DWI, 3.0T) prior to the surgical resection. Two independent readers measured tumor ADCs according to three ROI methods: whole-volume, single-slice, and small solid sample of tumor. Minimum and mean ADCs were obtained. The interobserver variability for each of the three methods was analyzed using interclass correlation coefficient (ICC) and Bland-Altman analysis. The minimum and mean ADCs among the ROI methods were compared using nonparametric tests.

RESULTS

The single-slice ROI method showed the best reproducibility in the minimum ADC measurements (mean difference ± limits of agreement between two readers were 0.025 ± 0.25 × 10(-3) mm2 /s; ICC, 0.92) among the three ROI methods. For the solid tumor sample ROI, both minimum ADC and mean ADC measurements reproducibility were the worst, with limits of agreement up to ±0.50 × 10(-3) mm2 /s and ±0.32 × 10(-3) mm2 /s, respectively (ICCs, 0.41/0.58). Both the minimum and mean ADCs demonstrated significant differences among the three ROI methods (both P < 0.001). The post-hoc analyses results showed no significant difference with regard to the mean ADCs between whole-volume and single-slice ROI methods (P = 0.14).

CONCLUSION

The ROI method had a considerable influence on both the minimum and mean ADC values and the interobserver variability in PDAC. The worst interobserver variability was observed for both the minimum and mean ADCs derived from small solid-sample ROI.

Prognostication and response assessment in liver and pancreatic tumors: The new imaging

Diffusion-weighted imaging (DWI), dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and perfusion computed tomography (CT) are technical improvements of morphologic imaging that can evaluate functional properties of hepato-bilio-pancreatic tumors during conventional MRI or CT examinations. Nevertheless, the term “functional imaging” is commonly used to describe molecular imaging techniques, as positron emission tomography (PET) CT/MRI, which still represent the most widely used methods for the evaluation of functional properties of solid neoplasms; unlike PET or single photon emission computed tomography, functional imaging techniques applied to conventional MRI/CT examinations do not require the administration of radiolabeled drugs or specific equipments. Moreover, DWI and DCE-MRI can be performed during the same session, thus providing a comprehensive “one-step” morphological and functional evaluation of hepato-bilio-pancreatic tumors. Literature data reveal that functional imaging techniques could be proposed for the evaluation of these tumors before treatment, given that they may improve staging and predict prognosis or clinical outcome. Microscopic changes within neoplastic tissues induced by treatments can be detected and quantified with functional imaging, therefore these techniques could be used also for post-treatment assessment, even at an early stage. The aim of this editorial is to describe possible applications of new functional imaging techniques apart from molecular imaging to hepatic and pancreatic tumors through a review of up-to-date literature data, with a particular emphasis on pathological correlations, prognostic stratification and post-treatment monitoring.

Diffusion tensor magnetic resonance imaging of the pancreas

PURPOSE

To develop a diffusion-tensor-imaging (DTI) protocol that is sensitive to the complex diffusion and perfusion properties of the healthy and malignant pancreas tissues.

MATERIALS AND METHODS

Twenty-eight healthy volunteers and nine patients with pancreatic-ductal-adenocacinoma (PDAC), were scanned at 3T with T2-weighted and DTI sequences. Healthy volunteers were also scanned with multi-b diffusion-weighted-imaging (DWI), whereas a standard clinical protocol complemented the PDAC patients' scans. Image processing at pixel resolution yielded parametric maps of three directional diffusion coefficients λ1, λ2, λ3, apparent diffusion coefficient (ADC), and fractional anisotropy (FA), as well as a λ1-vector map, and a main diffusion-direction map.

RESULTS

DTI measurements of healthy pancreatic tissue at b-values 0,500 s/mm² yielded: λ1 = (2.65±0.35)×10⁻³, λ2 = (1.87±0.22)×10⁻³, λ3 = (1.20±0.18)×10⁻³, ADC = (1.91±0.22)×10⁻³ (all in mm²/s units) and FA = 0.38±0.06. Using b-values of 100,500 s/mm² led to a significant reduction in λ1, λ2, λ3 and ADC (p<.0001) and a significant increase (p<0.0001) in FA. The reduction in the diffusion coefficients suggested a contribution of a fast intra-voxel-incoherent-motion (IVIM) component at b≤100 s/mm², which was confirmed by the multi-b DWI results. In PDACs, λ1, λ2, λ3 and ADC in both 0,500 s/mm² and 100,500 s/mm² b-values sets, as well as the reduction in these diffusion coefficients between the two sets, were significantly lower in comparison to the distal normal pancreatic tissue, suggesting higher cellularity and diminution of the fast-IVIM component in the cancer tissue.

CONCLUSION

DTI using two reference b-values 0 and 100 s/mm² enabled characterization of the water diffusion and anisotropy of the healthy pancreas, taking into account a contribution of IVIM. The reduction in the diffusion coefficients of PDAC, as compared to normal pancreatic tissue, and the smaller change in these coefficients in PDAC when the reference b-value was modified from 0 to 100 s/mm², helped identifying the presence of malignancy.