Pancreatic cancer: utility of dynamic contrast-enhanced MR imaging in assessment of antiangiogenic therapy

Multiparametric quantitative diffusion weighted magnetic resonance imaging can effectively predict the response to neoadjuvant therapy in borderline resectable pancreatic ductal adenocarcinoma

PURPOSE

To investigate whether multiparametric quantitative diffusion weighted magnetic resonance imaging (DWI) can effectively predict the neoadjuvant therapy (NAT) response in borderline resectable pancreatic ductal adenocarcinoma (BRPC).

METHODS

The clinicopathological data, including tumor size, location, and CA19-9 values, as well as DWI parameters(ADC, D, and f values) from 72 patients with BRPC, were analyzed. The differences and changes in these factors before and after NAT were compared to identify those most accurately reflect the response to NAT. ROC analysis was used to evaluate the diagnostic efficacy, and Kaplan-Meier survival analysis explored the relationship between DWI parameters and prognosis. Subgroup survival analysis to further identify populations potentially benefiting from NAT based on multiparametric DWI.

RESULTS

After-NAT, the response group showed significantly higher ADC and D values and lower f values compared to the non-response group. The ΔADC (OR: 12.24, P = 0.013) emerged as the most important independent factor for tumor response, demonstrating the highest diagnostic accuracy for NAT response with an AUC of 0.936. Kaplan-Meier showed the high ADC value group, high D value group and low f value group were associated with better prognosis after NAT; and the ΔADC ≥ 0 group, ΔD ≥ 0 group, and Δf < 0 group was significantly associated with better prognosis. In addition, subgroup analysis suggested two groups of patients might potentially benefit from NAT.

CONCLUSIONS

Multiparametric quantitative DWI may offer valuable insights into the efficacy and prognosis of NAT in BRPC. These findings have the potential to support the evaluation and decision-making process for patients undergoing NAT.

Rim enhancement of pancreatic ductal adenocarcinoma: investigating the relationship with DCE-MRI-based radiomics and next-generation sequencing

PURPOSE

To identify the clinical and genetic variables associated with rim enhancement of pancreatic ductal adenocarcinoma (PDAC) and to develop a dynamic contrast-enhanced (DCE) MRI-based radiomics model for predicting the genetic status from next-generation sequencing (NGS).

MATERIALS AND METHODS

Patients with PDAC, who underwent pretreatment pancreatic DCE-MRI between November 2019 and July 2021, were eligible in this prospective study. Two radiologists evaluated presence of rim enhancement in PDAC, a known radiological prognostic indicator, on DCE MRI. NGS was conducted for the tissue from the lesion. The Mann-Whitney U and Chi-square tests were employed to identify clinical and genetic variables associated with rim enhancement in PDAC. For continuous variables predicting rim enhancement, the cutoff value was set based on the Youden's index from the receiver operating characteristic (ROC) curve. Radiomics features were extracted from a volume-of-interest of PDAC on four DCE maps (Ktrans, Kep, Ve, and iAUC). A random forest (RF) model was constructed using 10 selected radiomics features from a pool of 392 original features. This model aimed to predict the status of significant NGS variables associated with rim enhancement. The performance of the model was validated using test set.

RESULTS

A total of 55 patients (32 men; median age 71 years) were randomly assigned to the training (n = 41) and test (n = 14) sets. In the training set, KRAS, TP53, CDKN2A, and SMAD4 mutation rates were 92.3%, 61.8%, 14.5%, and 9.1%, respectively. Tumor size and KRAS variant allele frequency (VAF) differed between rim-enhancing (n = 12) and nonrim-enhancing (n = 29) PDACs with a cutoff of 17.22%. The RF model's average AUC from 10-fold cross-validation for predicting KRAS VAF status was 0.698. In the test set comprising 6 tumors with low KRAS VAF and 8 with high KRAS VAF, the RF model's AUC reached 1.000, achieving a sensitivity of 75.0%, specificity of 100% and accuracy of 87.5%.

CONCLUSION

Rim enhancement of PDAC is associated with KRAS VAF derived from NGS-based genetic information. For predicting the KRAS VAF status in PDAC, a radiomics model based on DCE maps showed promising results.

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.

Optimal Temporal Resolution to Achieve Good Image Quality and Perform Pharmacokinetic Analysis in Free-breathing Dynamic Contrast-enhanced MR Imaging of the Pancreas

PURPOSE

The optimal temporal resolution for free-breathing dynamic contrast-enhanced MRI (FBDCE-MRI) of the pancreas has not been determined. This study aimed to evaluate the appropriate temporal resolution to achieve good image quality and to perform pharmacokinetic analysis in FBDCE-MRI of the pancreas using golden-angle radial sparse parallel (GRASP).

METHODS

Sixteen participants (53 ± 15 years, eight females) undergoing FBDCE-MRI were included in this prospective study. Images were retrospectively reconstructed at four temporal resolutions (1.8, 3.0, 4.8, and 7.8s). Two radiologists (5 years of experience) evaluated the image quality of each reconstructed image by assessing the visualization of the celiac artery (CEA), the common hepatic artery, the splenic artery, each area of the pancreas, and artifacts using a 5-point scale. Using Tissue-4D, pharmacokinetic parameters were calculated for each area in the reconstructed images at each temporal resolution for 16 examinations, excluding two with errors in the pharmacokinetic modeling analysis. Friedman and Bonferroni tests were used for analysis. A P value < 0.05 was considered statistically significant.

RESULTS

During vascular assessment, only scores for the CEA at 7.8s were significantly lower than the other temporal resolutions. Scores of all pancreatic regions and artifacts were significantly lower at 1.8s than at 4.8s and 7.8s. In the pharmacokinetic analysis, all volume transfer coefficients (Ktrans), rate constants (Kep), and the initial area under the concentration curve (iAUC) in the pancreatic head and tail were significantly lower at 4.8s and 7.8s than at 1.8s. iAUC in the pancreatic body and extracellular extravascular volume fraction (Ve) in the pancreatic head were significantly lower at 7.8s than at 1.8s.

CONCLUSION

A temporal resolution of 3.0s is appropriate to achieve image quality and perform pharmacokinetic analysis in FBDCE-MRI of the pancreas using GRASP.

Retrospective quantification of clinical abdominal DCE-MRI using pharmacokinetics-informed deep learning: a proof-of-concept study

Introduction

Dynamic contrast-enhanced (DCE) MRI has important clinical value for early detection, accurate staging, and therapeutic monitoring of cancers. However, conventional multi-phasic abdominal DCE-MRI has limited temporal resolution and provides qualitative or semi-quantitative assessments of tissue vascularity. In this study, the feasibility of retrospectively quantifying multi-phasic abdominal DCE-MRI by using pharmacokinetics-informed deep learning to improve temporal resolution was investigated.

Method

Forty-five subjects consisting of healthy controls, pancreatic ductal adenocarcinoma (PDAC), and chronic pancreatitis (CP) were imaged with a 2-s temporal-resolution quantitative DCE sequence, from which 30-s temporal-resolution multi-phasic DCE-MRI was synthesized based on clinical protocol. A pharmacokinetics-informed neural network was trained to improve the temporal resolution of the multi-phasic DCE before the quantification of pharmacokinetic parameters. Through ten-fold cross-validation, the agreement between pharmacokinetic parameters estimated from synthesized multi-phasic DCE after deep learning inference was assessed against reference parameters from the corresponding quantitative DCE-MRI images. The ability of the deep learning estimated parameters to differentiate abnormal from normal tissues was assessed as well.

Results

The pharmacokinetic parameters estimated after deep learning have a high level of agreement with the reference values. In the cross-validation, all three pharmacokinetic parameters (transfer constant K trans , fractional extravascular extracellular volume v e , and rate constant k ep ) achieved intraclass correlation coefficient and R2 between 0.84-0.94, and low coefficients of variation (10.1%, 12.3%, and 5.6%, respectively) relative to the reference values. Significant differences were found between healthy pancreas, PDAC tumor and non-tumor, and CP pancreas.

Discussion

Retrospective quantification (RoQ) of clinical multi-phasic DCE-MRI is possible by deep learning. This technique has the potential to derive quantitative pharmacokinetic parameters from clinical multi-phasic DCE data for a more objective and precise assessment of cancer.

Pancreatic cancer, autoimmune or chronic pancreatitis, beyond tissue diagnosis: Collateral imaging and clinical characteristics may differentiate them

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies and is developing into the 2nd leading cause of cancer-related death. Often, the clinical and radiological presentation of PDAC may be mirrored by other inflammatory pancreatic masses, such as autoimmune pancreatitis (AIP) and mass-forming chronic pancreatitis (MFCP), making its diagnosis challenging. Differentiating AIP and MFCP from PDAC is vital due to significant therapeutic and prognostic implications. Current diagnostic criteria and tools allow the precise differentiation of benign from malignant masses; however, the diagnostic accuracy is imperfect. Major pancreatic resections have been performed in AIP cases under initial suspicion of PDAC after a diagnostic approach failed to provide an accurate diagnosis. It is not unusual that after a thorough diagnostic evaluation, the clinician is confronted with a pancreatic mass with uncertain diagnosis. In those cases, a re-evaluation must be entertained, preferably by an experienced multispecialty team including radiologists, pathologists, gastroenterologists, and surgeons, looking for disease-specific clinical, imaging, and histological hallmarks or collateral evidence that could favor a specific diagnosis. Our aim is to describe current diagnostic limitations that hinder our ability to reach an accurate diagnosis among AIP, PDAC, and MFCP and to highlight those disease-specific clinical, radiological, serological, and histological characteristics that could support the presence of any of these three disorders when facing a pancreatic mass with uncertain diagnosis after an initial diagnostic approach has been unsuccessful.

Evaluation of Perfusion Change According to Pancreatic Cancer and Pancreatic Duct Dilatation Using Free-Breathing Golden-Angle Radial Sparse Parallel (GRASP) Magnetic Resonance Imaging

PURPOSE

To evaluate perfusion changes in the pancreas with pancreatic cancer and pancreatic duct dilatation using dynamic contrast-enhanced MRI (DCE-MRI).

METHOD

We evaluate the pancreas DCE-MRI of 75 patients. The qualitative analysis includes pancreas edge sharpness, motion artifacts, streak artifacts, noise, and overall image quality. The quantitative analysis includes measuring the pancreatic duct diameter and drawing six regions of interest (ROIs) in the three areas of the pancreas (head, body, and tail) and three vessels (aorta, celiac axis, and superior mesenteric artery) to measure the peak-enhancement time, delay time, and peak concentration. We evaluate the differences in three quantitative parameters among the ROIs and between patients with and without pancreatic cancer. The correlations between pancreatic duct diameter and delay time are also analyzed.

RESULTS

The pancreas DCE-MRI demonstrates good image quality, and respiratory motion artifacts show the highest score. The peak-enhancement time does not differ among the three vessels or among the three pancreas areas. The peak-enhancement time and concentrations in the pancreas body and tail and the delay time in the three pancreas areas are significantly longer (p < 0.05) in patients with pancreatic cancer than in those without pancreatic cancer. The delay time was significantly correlated with the pancreatic duct diameters in the head (p < 0.02) and body (p < 0.001).

CONCLUSION

DCE-MRI can display the perfusion change in the pancreas with pancreatic cancer. A perfusion parameter in the pancreas is correlated with the pancreatic duct diameter reflecting a morphological change in the pancreas.

Hypoxia, a Targetable Culprit to Counter Pancreatic Cancer Resistance to Therapy

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, and it is a disease of dismal prognosis. While immunotherapy has revolutionized the treatment of various solid tumors, it has achieved little success in PDAC. Hypoxia within the stroma-rich tumor microenvironment is associated with resistance to therapies and promotes angiogenesis, giving rise to a chaotic and leaky vasculature that is inefficient at shuttling oxygen and nutrients. Hypoxia and its downstream effectors have been implicated in immune resistance and could be contributing to the lack of response to immunotherapy experienced by patients with PDAC. Paradoxically, increasing evidence has shown hypoxia to augment genomic instability and mutagenesis in cancer, suggesting that hypoxic tumor cells could have increased production of neoantigens that can potentially enable their clearance by cytotoxic immune cells. Strategies aimed at relieving this condition have been on the rise, and one such approach opts for normalizing the tumor vasculature to reverse hypoxia and its downstream support of tumor pathogenesis. An important consideration for the successful implementation of such strategies in the clinic is that not all PDACs are equally hypoxic, therefore hypoxia-detection approaches should be integrated to enable optimal patient selection for achieving improved patient outcomes.

Multitasking dynamic contrast enhanced magnetic resonance imaging can accurately differentiate chronic pancreatitis from pancreatic ductal adenocarcinoma

Background and aims

Accurate differentiation of chronic pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC) is an area of unmet clinical need. In this study, a novel Multitasking dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) technique was used to quantitatively evaluate the microcirculation properties of pancreas in CP and PDAC and differentiate between them.

Methods

The Multitasking DCE technique was able to acquire one 3D image per second during the passage of MRI contrast agent, allowing the quantitative estimation of microcirculation properties of tissue, including blood flow F_p, plasma volume fraction v_p, transfer constant K^trans, and extravascular extracellular volume fraction v_e. Receiver operating characteristic (ROC) analysis was performed to differentiate the CP pancreas, PDAC pancreas, normal control pancreas, PDAC tumor, PDAC upstream, and PDAC downstream. ROCs from quantitative analysis and conventional analysis were compared.

Results

Fourteen PDAC patients, 8 CP patients and 20 healthy subjects were prospectively recruited. The combination of F_p, v_p, K^trans, and v_e can differentiate CP versus PDAC pancreas with good AUC (AUC [95% CI] = 0.821 [0.654 - 0.988]), CP versus normal pancreas with excellent AUC (1.000 [1.000 - 1.000]), PDAC pancreas versus normal pancreas with excellent AUC (1.000 [1.000 - 1.000]), CP versus PDAC tumor with excellent AUC (1.000 [1.000 - 1.000]), CP versus PDAC downstream with excellent AUC (0.917 [0.795 - 1.000]), and CP versus PDAC upstream with fair AUC (0.722 [0.465 - 0.980]). This quantitative analysis outperformed conventional analysis in differentiation of each pair.

Conclusion

Multitasking DCE MRI is a promising clinical tool that is capable of unbiased quantitative differentiation between CP from PDAC.

Pancreatic adenocarcinoma: imaging techniques for diagnosis and management

Pancreatic cancer is a leading cause of death from cancer but only a minority of patients with pancreatic ductal adenocarcinomas are eligible for curative resection. The increasing role of neoadjuvant therapy provides hope of improving outcomes. However, progress is also reliant on advances in imaging that can identify disease earlier and accurately assess treatment response. Computed tomography remains the cornerstone in evaluation of resectability, offering excellent spatial resolution. However, in high-risk patients, additional magnetic resonance imaging and positron emission tomography-computed tomography may further guide treatment decisions. Conventional computed tomography can be limited in its ability to determine disease response after neoadjuvant therapy. Dual-energy computed tomography and computed tomography or magnetic resonance imaging perfusion studies emerging as potentially better alternatives. Combined with pioneering advances in radiomic analysis, these modalities also show promise in analysing tumour heterogeneity and thereby more accurately predicting outcomes. This article reviews these imaging techniques.

Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging

Dynamic contrast-enhanced (DCE) imaging is a non-invasive technique used for the evaluation of tissue vascularity features through imaging series acquisition after contrast medium administration. Over the years, the study technique and protocols have evolved, seeing a growing application of this method across different imaging modalities for the study of almost all body districts. The main and most consolidated current applications concern MRI imaging for the study of tumors, but an increasing number of studies are evaluating the use of this technique also for inflammatory pathologies and functional studies. Furthermore, the recent advent of artificial intelligence techniques is opening up a vast scenario for the analysis of quantitative information deriving from DCE. The purpose of this article is to provide a comprehensive update on the techniques, protocols, and clinical applications - both established and emerging - of DCE in whole-body imaging.

Scintigraphic Imaging of Neovascularization With 99mTc-3PRGD2 for Evaluating Early Response to Endostar Involved Therapies on Pancreatic Cancer Xenografts In Vivo

Background

Molecular imaging targeting angiogenesis can specifically monitor the early therapeutic effect of antiangiogenesis therapy. We explore the predictive values of an integrin αvβ3-targeted tracer, 99mTc-PEG4-E[PEG4-c(RGDfK)]2 (99mTc-3PRGD2), for monitoring the efficacy of Endostar antiangiogenic therapy and chemotherapy in animal models.

Methods

The pancreatic cancer xenograft mice were randomly divided into four groups, with seven animals in each group and treated in different groups with 10 mg/kg/day of Endostar, 10 mg/kg/day of gemcitabine, 10 mg/kg/day of Endostar +10 mg/kg/day of gemcitabine at the same time, and the control group with 0.9% saline (0.1 ml/day). 99mTc-3PRGD2 scintigraphic imaging was carried out to monitor therapeutic effects. Microvessel density (MVD) was measured using immunohistochemical staining of the tumor tissues. The region of interest (ROI) of tumor (T) and contralateral corresponding site (NT) was delineated, and the ratio of radioactivity (T/NT) was calculated. Two-way repeated-measure analysis of variance (ANOVA) was used to assess differences between treatment groups.

Results

Tumor growth was significantly lower in treatment groups than that in the control group (p < 0.05), and the differences were noted on day 28 posttreatment. The differences of 99mTc-3PRGD2 uptakes were observed between the control group and Endostar group (p = 0.033) and the combined treatment group (p < 0.01) on day 7 posttreatment and on day 14 posttreatment between the control group and gemcitabine group (p < 0.01). The accumulation of 99mTc-3PRGD2 was significantly correlated with MVD (r = 0.998, p = 0.002).

Conclusion

With 99mTc-3PRGD2 scintigraphic imaging, the tumor response to antiangiogenic therapy, chemotherapy, and the combined treatment can be observed at an early stage of the treatments, much earlier than the tumor volume change. It provides new opportunities for developing individualized therapies and dose optimization.

Extracellular volume fraction with MRI: As an alternative predictive biomarker to dynamic contrast-enhanced MRI for chemotherapy response of pancreatic ductal adenocarcinoma

PURPOSE

To assess the feasibility of extracellular volume (ECV) fraction determined with equilibrium contrast-enhanced MRI for prediction of treatment response to chemotherapy in pancreatic ductal adenocarcinoma (PDAC) in comparison with dynamic contrast-enhanced MRI (DCE-MRI), and to clarify the association between ECV fraction and DCE-MRI-derived pharmacokinetic parameters.

METHODS

This retrospective study included 58 consecutive patients with histologically confirmed PDAC who underwent DCE-MRI before systemic chemotherapy. Tumor pharmacokinetic parameters, including the volume transfer coefficient (K^trans), rate constant (k_ep), and extracellular extravascular volume fraction (v_e) of DCE-MRI, and ECV fraction determined with equilibrium contrast-enhanced MRI were compared between the response and non-response groups. The correlation of tumor ECV fraction with each DCE-MRI-derived pharmacokinetic parameter was examined using Spearman's rank correlation coefficient.

RESULTS

Tumor K^trans, v_e, and ECV fraction were significantly higher in the response group than in the non-response group (all, P < 0.001), whereas no significant difference was found in k_ep (P = 0.119). Tumor ECV fraction showed the highest area under receiver operating characteristic curve of 0.918, with a sensitivity of 89.3%, specificity of 90.0%, and accuracy of 89.7% (cut off, >37.6%). The ECV fraction showed a significant positive correlation with K^trans (Spearman's coefficient = 0.66, P < 0.001) and v_e (Spearman's coefficient = 0.79, P < 0.001).

CONCLUSIONS

ECV fraction determined with equilibrium contrast-enhanced MRI was as useful as DCE-MRI-derived pharmacokinetic parameters for predicting treatment response to chemotherapy in patients with PDAC.

Longitudinal Monitoring of Simulated Interstitial Fluid Pressure for Pancreatic Ductal Adenocarcinoma Patients Treated with Stereotactic Body Radiotherapy

Simple Summary

High vessel permeability, poor perfusion, low lymphatic drainage, and dense abundant stroma elevate interstitial fluid pressures (IFP) in pancreatic ductal adenocarcinoma (PDAC). The present study aims to monitor longitudinal changes in simulated tumor IFP and velocity (IFV) values using a dynamic contrast-enhanced (DCE)-MRI-based computational fluid modeling (CFM) approach in PDAC. Nine PDAC patients underwent DCE-MRI acquisition on a 3-Tesla MRI scanner at pre-treatment (TX (0)), immediately after the first fraction of stereotactic body radiotherapy (SBRT, (D1-TX)), and six weeks post-TX (D2-TX). The partial differential equation of IFP formulated from the continuity equation using the Starling Principle of fluid exchange and Darcy velocity–pressure relationship was solved in COMSOL Multiphysics software to generate IFP and IFV parametric maps using relevant tumor tissue physiological parameters. Initial results suggest that after validation, IFP and IFV can be imaging biomarkers of early response to therapy that may guide precision medicine in PDAC.

Abstract

The present study aims to monitor longitudinal changes in simulated tumor interstitial fluid pressure (IFP) and velocity (IFV) values using dynamic contrast-enhanced (DCE)-MRI-based computational fluid modeling (CFM) in pancreatic ductal adenocarcinoma (PDAC) patients. Nine PDAC patients underwent MRI, including DCE-MRI, on a 3-Tesla MRI scanner at pre-treatment (TX (0)), after the first fraction of stereotactic body radiotherapy (SBRT, (D1-TX)), and six weeks post-TX (D2-TX). The partial differential equation of IFP formulated from the continuity equation, incorporating the Starling Principle of fluid exchange, Darcy velocity, and volume transfer constant (K^trans), was solved in COMSOL Multiphysics software to generate IFP and IFV maps. Tumor volume (V_t), K^trans, IFP, and IFV values were compared (Wilcoxon and Spearman) between the time- points. D2-TX K^trans values were significantly different from pre-TX and D1-TX (p < 0.05). The D1-TX and pre-TX mean IFV values exhibited a borderline significant difference (p = 0.08). The IFP values varying <3.0% between the three time-points were not significantly different (p > 0.05). V_t and IFP values were strongly positively correlated at pre-TX (ρ = 0.90, p = 0.005), while IFV exhibited a strong negative correlation at D1-TX (ρ = −0.74, p = 0.045). V_t, K^trans, IFP, and IFV hold promise as imaging biomarkers of early response to therapy in PDAC.

Consistency of Pituitary Adenoma: Prediction by Pharmacokinetic Dynamic Contrast-Enhanced MRI and Comparison with Histologic Collagen Content

Simple Summary

Transsphenoidal resection of hard pituitary adenomas have a particularly high risk of residual tumor and complications. Therefore, prediction of tumor consistency is valuable for planning pituitary adenoma surgery. We prospectively examined whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of pituitary adenoma in 49 participants. We found that the measure of volume of extravascular extracellular space per unit volume of tissue derived from DCE-MRI could predict the consistency of pituitary adenomas. Furthermore, the volume of extravascular extracellular space per unit volume of tissue was significantly positively correlated with histopathologic collagen content of the adenoma. Our results suggest that volume of extravascular extracellular space per unit volume of tissue derived from quantitative pharmacokinetic analysis of DCE-MRI has a predictive value for consistency of pituitary adenomas.

Abstract

Prediction of tumor consistency is valuable for planning transsphenoidal surgery for pituitary adenoma. A prospective study was conducted involving 49 participants with pituitary adenoma to determine whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of adenomas. Pharmacokinetic parameters in the adenomas including volume of extravascular extracellular space (EES) per unit volume of tissue (v_e), blood plasma volume per unit volume of tissue (v_p), volume transfer constant between blood plasma and EES (K^trans), and rate constant between EES and blood plasma (k_ep) were obtained. The pharmacokinetic parameters and the histologic percentage of collagen content (PCC) were compared between soft and hard adenomas using Mann–Whitney U test. Pearson’s correlation coefficient was used to correlate pharmacokinetic parameters with PCC. Hard adenomas showed significantly higher PCC (44.08 ± 15.14% vs. 6.62 ± 3.47%, p < 0.01), v_e (0.332 ± 0.124% vs. 0.221 ± 0.104%, p < 0.01), and K^trans (0.775 ± 0.401/min vs. 0.601 ± 0.612/min, p = 0.02) than soft adenomas. Moreover, a significant positive correlation was found between v_e and PCC (r = 0.601, p < 0.01). The v_e derived using DCE-MRI may have predictive value for consistency of pituitary adenoma.

Feasibility Study on Using Dynamic Contrast Enhanced MRI to Assess the Effect of Tyrosine Kinase Inhibitor Therapy within the STAR Trial of Metastatic Renal Cell Cancer

Objective: To identify dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters predictive of early disease progression in patients with metastatic renal cell cancer (mRCC) treated with anti-angiogenic tyrosine kinase inhibitors (TKI). Methods: The study was linked to a phase II/III randomised control trial. Patients underwent DCE-MRI before, at 4- and 10-weeks after initiation of TKI. DCE-MRI parameters at each time-point were derived from a single-compartment tracer kinetic model, following semi-automated tumour segmentation by two independent readers. Primary endpoint was correlation of DCE-MRI parameters with disease progression at 6-months. Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) values were calculated for parameters associated with disease progression at 6 months. Inter-observer agreement was assessed using the intraclass correlation coefficient (ICC). Results: 23 tumours in 14 patients were measurable. Three patients had disease progression at 6 months. The percentage (%) change in perfused tumour volume between baseline and 4-week DCE-MRI (p = 0.016), mean transfer constant K^trans change (p = 0.038), and % change in extracellular volume (p = 0.009) between 4- and 10-week MRI, correlated with early disease progression (AUC 0.879 for each parameter). Inter-observer agreement was excellent for perfused tumour volume, K^trans and extracellular volume (ICC: 0.928, 0.949, 0.910 respectively). Conclusions: Early measurement of DCE-MRI biomarkers of tumour perfusion at 4- and 10-weeks predicts disease progression at 6-months following TKI therapy in mRCC.

Diffusion-Weighted and Dynamic Contrast-Enhanced MRI Derived Imaging Metrics for Stereotactic Body Radiotherapy of Pancreatic Ductal Adenocarcinoma: Preliminary Findings

We aimed to assess longitudinal changes in quantitative imaging metric values obtained from diffusion-weighted (DW-) and dynamic contrast-enhanced magnetic resonance imaging (DCE)-MRI at pre-treatment (TX[0]), immediately after the first fraction of stereotactic body radiotherapy (D1-TX[1]), and 6 weeks post-TX (Post-TX[2]) in patients with pancreatic ductal adenocarcinoma. Ten enrolled patients (n = 10) underwent DW- and DCE-MRI examinations on a 3.0 T scanner. The apparent diffusion coefficient, ADC (mm²/s), was derived from DW imaging data using a monoexponential model. The tissue relaxation rate, R _1t, time-course data were fitted with a shutter-speed model, which provides estimates of the volume transfer constant, K ^trans (min^-1), extravascular extracellular volume fraction, v_e , and mean lifetime of intracellular water protons, τ _i (seconds). Wilcoxon rank-sum test compared the mean values, standard deviation, skewness, kurtosis, and relative percentage (r, %) changes (Δ) in ADC, K ^trans, v_e , and τ _i values between the magnetic resonance examinations. rADC_Δ2-0 values were significantly greater than rADC_Δ1-0 values (P = .009). rK ^trans _Δ2-0 values were significantly lower than rK ^trans _Δ1-0 values (P = .048). rv_{e Δ2-1} and rv_eΔ2-0 values were significantly different (P = .016). rτ _{i Δ2-1} values were significantly lower than rτ _{i Δ2-0} values (P = .008). For group comparison, the pre-TX mean and kurtosis of ADC (P = .18 and P = .14), skewness and kurtosis of K ^trans values (P = .14 for both) showed a leaning toward significant difference between patients who experienced local control (n = 2) and failed early (n = 4). DW- and DCE-MRI-derived quantitative metrics could be useful biomarkers to evaluate longitudinal changes to stereotactic body radiotherapy in patients with pancreatic ductal adenocarcinoma.

Diagnostic performance of diffusion MRI for pancreatic ductal adenocarcinoma characterisation: A meta-analysis

PURPOSE

To assess the diagnostic performance of intravoxel incoherent motion (IVIM) and diffusion-weighted imaging (DWI) for characterising pancreatic ductal adenocarcinoma (PDAC).

METHOD

A literature search was performed through PubMed, Web of Science, the Cochrane Library, and Embase databases. The search date was updated to extend until 28 October 2020, with no starting time limitation. The pooled sensitivity and specificity were calculated using a bivariate random effects model. Summary receiver operating characteristic curves were constructed, and area under the curve (AUC) of each diffusion parameter was calculated. Subgroup and meta-regression analyses were performed to assess for heterogeneity. Study quality was assessed.

RESULTS

Twenty-nine studies involving 1579 participants were included, of which 26 evaluated the apparent diffusion coefficient (ADC) and eight evaluated IVIM, with five evaluating both ADC and IVIM. Pooled sensitivity and specificity of ADC were 83 % (95 % CI, 76 %-88 %, I² = 86 %) and 85 % (95 % CI, 79 %-90 %, I² = 77 %), respectively, and AUC was 0.91 (95 % CI, 0.88-0.93). The perfusion fraction had the highest diagnostic accuracy in the IVIM model; the pooled sensitivity, specificity, and AUC were 87 % (95 % CI, 81 %-92 %, I² = 45 %), 88 % (95 % CI, 77 %-94 %, I² = 57 %), and 0.93 (95 % CI, 0.91-0.95), respectively. The pooled sensitivity, specificity and AUC for the tissue diffusion coefficient were 74 % (95 % CI, 55 %-87 %, I² = 87 %), 69 % (95 % CI, 52 %-82 %, I² = 73 %), and 0.77 (95 % CI, 0.73-0.81), respectively. And the pooled sensitivity, specificity, and AUC for the pseudodiffusion coefficient were 89 % (95 % CI, 77 %-96 %, I² = 79 %), 74 % (95 % CI, 60 %-84 %, I² = 78 %), and 0.88(95 %CI,0.85-0.91), respectively. Meta-regression analyses revealed that study design (specificity, P＜0.01), region-of-interest delineation (sensitivity, P = 0.02;specificity, P = 0.03), field strength (sensitivity, P＜0.01), and thickness (sensitivity, P＜0.01; specificity, P = 0.01) were sources of ADC heterogeneity.

CONCLUSIONS

DWI and IVIM have comparable diagnostic power and good diagnostic performance for characterising PDAC.

Advances and challenges of neoadjuvant therapy in pancreatic cancer

Pancreatic cancer has been becoming the second cause of cancer death in the western world, and its disease burden has increased. Neoadjuvant therapy is one of the current research hotspots in the field of pancreatic cancer, aiming to improve the surgical rate and prognosis of pancreatic cancer. Based on the latest evidence, this review discussed neoadjuvant therapy in pancreatic cancer from the following three aspects: patient selection, protocols selection of neoadjuvant therapy, and treatment response evaluation and resectability prediction. A big controversy existed on the indications of neoadjuvant treatment, but it was agreed that any patient who is likely to achieve R0 resection due to neoadjuvant therapy should be the targeted population. A variety of chemotherapy regimens were tried for neoadjuvant therapy in pancreatic cancer, and FOLFIRINOX and Nab-Paclitaxel plus Gemcitabine are two preferred regimens at present. It was challenging to evaluate treatment response and predict resectability after neoadjuvant therapy, although imaging by CT is widely used. Based on new findings of the remarkable performance of several chemotherapy regimens with or without radiotherapy, the neoadjuvant indications of pancreatic cancer have extended in recent years. However, it is still a challenge to assess the neoadjuvant treatment response and determine the timing of surgery.

Dynamic contrast-enhanced magnetic resonance imaging biomarkers predict chemotherapeutic responses and survival in primary central-nervous-system lymphoma

OBJECTIVES

To evaluate the utility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the response of chemotherapy and clinical outcomes in primary central-nervous-system lymphoma (PCNSL) patients.

METHODS

DCE-MRI in 56 patients enrolled in a prospective study was performed at baseline and 30 days after treatment from 2016 to 2019. Multivariate logistic regression analyses were performed to assess risk factors for tumor responses. The predictive values of related parameters derived from DCE were analyzed via receiver operating characteristic (ROC) curve analysis. To evaluate prognostic factors, the Kaplan-Meier survival analysis with log-rank tests and Cox regression tests were analyzed.

RESULTS

K^trans and V_e were higher in the non-response group than in the response group (p < 0.05). The K^trans and the percentage of K^trans decreased after 30 days of treatment were independent predictors of chemotherapy responses (p = 0.034 and p = 0.019). ROC analysis indicated that the cut-off point of K^trans for predicting chemotherapeutic responses was 0.353 min^-1 (AUC, 0.941; 95% CI, 0.87-1; p < 0.001) and percentage of K^trans decreased after 30 days of treatment was 15.2% (AUC, 0.858; 95% CI, 0.742-0.970; p < 0.001). The greater decrease in K^trans correlated with a longer progression-free survival (PFS) (χ² = 13.203, p < 0.001). The higher K^trans was an independent predictor for shorter PFS (hazard ratio, 10.182; 95% CI, 2.510-41.300; p = 0.001).

CONCLUSIONS

K^trans and K^trans change measured by DCE-MRI were reliable biomarkers for predicting chemotherapy responses in PCNSL patients.

KEY POINTS

• Baseline K^trans and greater decrease in K^trans can predict chemotherapeutic efficacy. • DCE-MRI provides quantitative parameters reflecting the tumor microenvironment. • Targeted treatment therapy can be given with more evidence in the future.

Visual enhancement pattern during the delayed phase of enhanced CT as an independent prognostic factor in stage IV pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has substantial heterogeneity in biophysical features and in outcomes of patients. Identifying reliable pretreatment imaging biomarkers for PDAC with distant metastases (stage IV) is a key imperative. Our objective was to determine whether visual tumor enhancement pattern on enhanced computed tomography (CT) can be used as a prognostic factor in stage IV PDAC treated with chemotherapy.

METHODS

This is a retrospective cohort study of 133 patients with stage IV PDAC who underwent multiphasic enhanced CT before systemic chemotherapy. The enhancement pattern of PDAC was qualitatively categorized as hypoattenuation, isoattenuation, or hyperattenuation on each of the pancreatic, portal venous, and delayed phases. The effects of clinical prognostic factors and the visual tumor enhancement pattern on progression-free survival (PFS) and overall survival (OS) were assessed in univariate and multivariate analyses using Cox proportional hazards models.

RESULTS

On univariate analysis, the number of metastatic organs and the visual tumor enhancement pattern during the delayed phase were significantly associated with PFS (p = 0.003 and < 0.001, respectively) and OS (p = 0.005 and < 0.001, respectively). Multivariate analysis identified the number of metastatic organs (PFS, p = 0.021; OS, p = 0.041) and visual tumor enhancement pattern during the delayed phase (PFS, p < 0.001; OS, p < 0.001) as independent predictors of PFS and OS.

CONCLUSION

Visual enhancement pattern of PDAC on delayed phase enhanced CT appears to be associated with outcomes and could be a useful prognostic factor in stage IV PDAC, despite the need to add the delayed phase to CT protocol for pancreatic disease.

The Role of Imaging in Current Treatment Strategies for Pancreatic Adenocarcinoma

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

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

KEY POINTS

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

MRI of the Pancreas

MRI has played a critical role in the evaluation of patients with pancreatic pathologies, from screening of patients at high risk for pancreatic cancer to the evaluation of pancreatic cysts and indeterminate pancreatic lesions. The high mortality associated with pancreatic adenocarcinomas has spurred much interest in developing effective screening tools, with MRI using magnetic resonance cholangiopancreatography (MRCP) playing a central role in the hopes of identifying cancers at earlier stages amenable to curative resection. Ongoing efforts to improve the resolution and robustness of imaging of the pancreas using MRI may thus one day reduce the mortality of this deadly disease. However, the increasing use of cross-sectional imaging has also generated a concomitant clinical conundrum: How to manage incidental pancreatic cystic lesions that are found in over a quarter of patients who undergo MRCP. Efforts to improve the specificity of MRCP for patients with pancreatic cysts and with indeterminate pancreatic masses may be achieved with continued technical advances in MRI, including diffusion-weighted and T₁ -weighted dynamic contrast-enhanced MRI. However, developments in quantitative MRI of the pancreas remain challenging, due to the small size of the pancreas and its upper abdominal location, adjacent to bowel and below the diaphragm. Further research is needed to improve MRI of the pancreas as a clinical tool, to positively affect the lives of patients with pancreatic abnormalities. This review focuses on various MR techniques such as MRCP, quantitative imaging, and dynamic contrast-enhanced imaging and their clinical applicability in the imaging of the pancreas, with an emphasis on pancreatic malignant and premalignant lesions. Level of Evidence 5 Technical Efficacy Stage 3 J. MAGN. RESON. IMAGING 2021;53:347-359.

WITHDRAWN: Risks and Benefits of Gadolinium-Based Contrast Enhanced MRI

The Publisher regrets that this article is an accidental duplication of an article that has already been published in [Seminars in Ultrasound, CT, and MRI, 41/2 (2020) 170–182], https://dx.doi.org/10.1053/j.sult.2019.12.005. The duplicate article has therefore been withdrawn. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal

MRI radiomics for early prediction of response to vaccine therapy in a transgenic mouse model of pancreatic ductal adenocarcinoma

BACKGROUND

There is a lack of well-established clinical tools for predicting dendritic cell (DC) vaccination response of pancreatic ductal adenocarcinoma (PDAC). DC vaccine treatment efficiency was demonstrated using histological analysis in pre-clinical studies; however, its usage was limited due to invasiveness. In this study, we aimed to investigate the potential of MRI texture features for detection of early immunotherapeutic response as well as overall survival (OS) of PDAC subjects following dendritic cell (DC) vaccine treatment in LSL-KrasG12D;LSL-Trp53R172H;Pdx-1-Cre (KPC) transgenic mouse model of pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

KPC mice were treated with DC vaccines, and tumor growth was dynamically monitored. A total of a hundred and fifty-two image features of T2-weighted MRI images were analyzed using a kernel-based support vector machine model to detect treatment effects following the first and third weeks of the treatment. Moreover, univariate analysis was performed to describe the association between MRI texture and survival of KPC mice as well as histological tumor biomarkers.

RESULTS

OS for mice in the treatment group was 54.8 ± 22.54 days while the control group had 35.39 ± 17.17 days. A subset of three MRI features distinguished treatment effects starting from the first week with increasing accuracy throughout the treatment (75% to 94%). Besides, we observed that short-run emphasis of approximate wavelet coefficients had a positive correlation with the survival of the KPC mice (r = 0.78, p < 0.001). Additionally, tissue-specific MRI texture features showed positive association with fibrosis percentage (r = 0.84, p < 0.002), CK19 positive percentage (r = - 0.97, p < 0.001), and Ki67 positive cells (r = 0.81, p < 0.02) as histological disease biomarkers.

CONCLUSION

Our results demonstrate that MRI texture features can be used as imaging biomarkers for early detection of therapeutic response following DC vaccination in the KPC mouse model of PDAC. Besides, MRI texture can be utilized to characterize tumor microenvironment reflected with histology analysis.

Six-dimensional quantitative DCE MR Multitasking of the entire abdomen: Method and application to pancreatic ductal adenocarcinoma

PURPOSE

To develop a quantitative DCE MRI technique enabling entire-abdomen coverage, free-breathing acquisition, 1-second temporal resolution, and T₁ -based quantification of contrast agent concentration and kinetic modeling for the characterization of pancreatic ductal adenocarcinoma (PDAC).

METHODS

Segmented FLASH readouts following saturation-recovery preparation with randomized 3D Cartesian undersampling was used for incoherent data acquisition. MR Multitasking was used to reconstruct 6-dimensional images with 3 spatial dimensions, 1 T₁ recovery dimension for dynamic T₁ quantification, 1 respiratory dimension to resolve respiratory motion, and 1 DCE time dimension to capture the contrast kinetics. Sixteen healthy subjects and 14 patients with pathologically confirmed PDAC were recruited for the in vivo studies, and kinetic parameters v_p , K^trans , v_e , and K_ep were evaluated for each subject. Intersession repeatability of Multitasking DCE was assessed in 8 repeat healthy subjects. One-way unbalanced analysis of variance was performed between control and patient groups.

RESULTS

In vivo studies demonstrated that v_p , K^trans , and K_ep of PDAC were significantly lower compared with nontumoral regions in the patient group (P = .002, .003, .004, respectively) and normal pancreas in the control group (P = .011, <.001, <.001, respectively), while v_e was significantly higher than nontumoral regions (P < .001) and healthy pancreas (P < .001). The kinetic parameters showed good in vivo repeatability (interclass correlation coefficient: v_p , 0.95; K^trans , 0.98; v_e , 0.96; K_ep , 0.99).

CONCLUSION

The proposed Multitasking DCE is promising for the quantification of vascular properties of PDAC. Quantitative DCE parameters were repeatable in vivo and showed significant differences between normal pancreas and both tumor and nontumoral regions in patients with PDAC.

Quantitative Magnetic Resonance Imaging of the Pancreas of Individuals With Diabetes

Magnetic resonance imaging (MRI) has the potential to improve our understanding of diabetes and improve both diagnosis and monitoring of the disease. Although the spatial resolution of MRI is insufficient to directly image the endocrine pancreas in people, the increasing awareness that the exocrine pancreas is also involved in diabetes pathogenesis has spurred new MRI applications. These techniques build upon studies of exocrine pancreatic diseases, for which MRI has already developed into a routine clinical tool for diagnosis and monitoring of pancreatic cancer and pancreatitis. By adjusting the imaging contrast and carefully controlling image acquisition and processing, MRI can quantify a variety of tissue pathologies. This review introduces a number of quantitative MRI techniques that have been applied to study the diabetic pancreas, summarizes progress in validating and standardizing each technique, and discusses the need for image analyses that account for spatial heterogeneity in the pancreas.

Clinical MR Biomarkers

Non-invasive magnetic resonance imaging (MRI) techniques are increasingly applied in the clinic with a fast growing body of evidence regarding its value for clinical decision making. In contrast to biochemical or histological markers, the key advantages of imaging biomarkers are the non-invasive nature and the spatial and temporal resolution of these approaches. The following chapter focuses on clinical applications of novel MR biomarkers in humans with a strong focus on oncologic diseases. These include both clinically established biomarkers (part 1-4) and novel MRI techniques that recently demonstrated high potential for clinical utility (part 5-7).

Dynamic Contrast-Enhanced MRI for Measuring Pancreatic Perfusion in Acute Pancreatitis: A Preliminary Study

RATIONALE AND OBJECTIVES

To assess the characteristics of pancreatic perfusion in normal pancreas and acute pancreatitis (AP) by using dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI).

METHOD AND MATERIALS

Eighty-One AP patients and 26 normal subjects underwent DCE-MRI. The Omitk-Tool was used to analyze perfusion parameters such as Ktrans, Vp, and AUC. The parameters of pancreas between AP and control groups were compared. In AP patients, the parameters were compared between edematous and necrotizing pancreatitis and among different grades of AP as determined by MR severity index (MRSI) and the 2012 Revised Atlanta Classification of AP.

RESULTS

The Ktrans, Vp, and AUC values of AP were lower than those of the control group (p = 0.007, 0.000, and 0.025). According to MRSI, the Ktrans and AUC values were significantly different between mild and moderate (p = 0.000, 0.000) and between mild and severe (p = 0.008, 0.016) AP but not between moderate and severe AP (p = 0.218, 0.217). Based on the 2012 Revised Atlanta Classification, the Ktrans values were significantly different between mild and moderately severe (p = 0.000) and between mild and severe (p = 0.005) AP, but not between moderately severe and severe AP (p = 0.619). The Ktrans values were significantly different between edematous and necrotizing pancreatitis (p = 0.03).

CONCLUSION

The application of DCE-MRI to evaluate pancreatic perfusion contributes to the diagnosis of AP and its severity grade. Pancreatic perfusion is lower in AP patients than in patients with a normal pancreas, and pancreatic perfusion tends to decrease as the severity of AP increases.

Quantitative dynamic contrast-enhanced MR imaging for the preliminary prediction of the response to gemcitabine-based chemotherapy in advanced pancreatic ductal carcinoma

PURPOSE

To investigate the role of the quantitative parameters of dynamic contrast-enhanced MR imaging (DCE-MRI) in the prediction of the response to chemotherapy in pancreatic ductal carcinoma (PDC).

METHOD

Forty patients with histologically confirmed PDC who underwent quantitative DCE-MRI were retrospectively analyzed. All patients were divided into groups of responders and nonresponders. DCE-MRI parameters, including the volume transfer constant (K^trans), the extracellular extravascular volume fraction (v_e), the rate constant (k_ep) and the initial area under the concentration curve in 60 s (iAUC60), were measured and compared. DCE-MRI parameters were obtained from different ROIs.

RESULTS

The values of K^trans in responders with peripheral, whole tumor slice, and adjacent non-tumorous region ROIs were significantly higher than those in nonresponders (P = 0.015, 0.043, and 0.025, respectively). Responders showed a significantly higher k_ep with peripheral area ROI compared with nonresponders (P =  0.013). Ve and iAUC60 with all ROIs were not significantly different between responders and nonresponders (P = 0.140-0.968). Kep with periphery ROI showed the highest area under the ROC curve (AUC) of 0.806, but there were no statistical differences when compared with values of K^trans.There were statistically significant differences for DCE-MRI parameters among four ROIs (all P <  0.05). All parameters showed good to excellent intra and interobserver agreement.

CONCLUSIONS

Quantitative parameters derived from DCE-MRI might be a potential predictor of response to gemcitabine in patients with PDC. Perfusion parameters were diverse depending on the location of the ROI on different tumoral and peritumoral areas.

Differentiation of atypical non-functional pancreatic neuroendocrine tumor and pancreatic ductal adenocarcinoma using CT based radiomics

PURPOSE

To develop and validate an effective model to differentiate NF-pNET from PDAC.

MATERIALS AND METHODS

Between July 2014 and December 2017, 147 patients (80 patients with PDAC and 67 patients with atypical NF-pNET) with pathology results and enhanced CT were consecutively enrolled and chronologically divided into primary and validation cohorts. Three models were built to differentiate atypical NF-pNET from PDAC, including a model based on radiomic signature alone, one based on clinicoradiological features alone and one that integrated the two. The diagnostic performance of the three models was estimated and compared with the area under the receiver operating characteristic curve (AUC) in the validation cohort. A nomogram was used to represent the model with the best performance, and the associated calibration was also assessed.

RESULTS

In the validation cohort, the AUC for differential diagnosis was 0.884 with the integrated model, which was significantly improved over that of the model based on clinicoradiological features (AUC = 0.775, p value = 0.004) and was comparable to that of the model based on the radiomic signature (AUC = 0.873, p value = 0.512). The nomogram representing the integrated model achieved good discrimination performances in both the primary and validation cohorts, with C-indices of 0.960 and 0.884, respectively.

CONCLUSION

The integrated model outperformed the model based on clinicoradiological features alone and was comparable to the model based on the radiomic signature alone with respect to the differential diagnosis of atypical NF-pNET and PDAC. The nomogram achieved an optimal preoperative, noninvasive differential diagnosis between atypical pNET and PDAC, which can better inform therapeutic choice in clinical practice.

Dynamic Contrast-enhanced MRI Detects Responses to Stroma-directed Therapy in Mouse Models of Pancreatic Ductal Adenocarcinoma

PURPOSE

The dense stroma underlies the drug resistance of pancreatic ductal adenocarcinoma (PDA) and has motivated the development of stroma-directed drugs. Our objective is to test the concept that dynamic contrast-enhanced (DCE) MRI using FDA-approved contrast media, an imaging method sensitive to the tumor microenvironment, can detect early responses to stroma-directed drug.

EXPERIMENTAL DESIGN

Imaging studies were performed in three mouse models exhibiting high desmoplastic reactions: the autochthonous PDA in genetically engineered mice (KPC), an orthotopic model in syngeneic mice, and a xenograft model of human PDA in athymic mice. An investigational drug, PEGPH20 (pegvorhyaluronidase alfa), which degrades hyaluronan (HA) in the stroma of PDA, was injected alone or in combination with gemcitabine.

RESULTS

At 24 hours after a single injection of PEGPH20, Ktrans , a DCE-MRI-derived marker that measures how fast a unit volume of contrast media is transferred from capillaries to interstitial space, increased 56% and 50% from baseline in the orthotopic and xenograft tumors, respectively, compared with a 4% and 6% decrease in vehicle groups (both P < 0.05). Similarly, after three combined treatments, Ktrans in KPC mice increased 54%, whereas it decreased 4% in controls treated with gemcitabine alone (P < 0.05). Consistently, after a single injection of PEGPH20, tumor HA content assessed by IHC was reduced substantially in all three models while drug delivery (measured by paclitaxel accumulation in tumor) was increased by 2.6-fold.

CONCLUSIONS

These data demonstrated a DCE-MRI marker, Ktrans , can detect early responses to stroma-directed drug and reveal the sustained effect of combination treatment (PEGPH20+ gemcitabine).

Advanced MR Imaging Techniques for Pancreas Imaging

Advances in MR imaging with optimization of hardware, software, and techniques have allowed for an increased role of MR in the identification and characterization of pancreatic disorders. Diffusion-weighted imaging improves the detection and staging of pancreatic neoplasms and aides in the evaluation of acute, chronic and autoimmune pancreatitis. The use of secretin-enhanced MR cholangiography improves the detection of morphologic ductal anomalies, and assists in the characterization of pancreatic cystic lesions and evaluation of acute and chronic pancreatitis. Emerging MR techniques such as MR perfusion, T1 mapping/relaxometry, and MR elastography show promise in further evaluating pancreatic diseases.

Accurate Therapeutic Response Assessment of Pancreatic Ductal Adenocarcinoma Using Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging With a Point-of-Care Perfusion Phantom: A Pilot Study

OBJECTIVES

The aim of this study was to test the feasibility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with concurrent perfusion phantom for monitoring therapeutic response in patients with pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

A prospective pilot study was conducted with 8 patients (7 men and 1 woman) aged 46 to 78 years (mean age, 66 years). Participants had either locally advanced (n = 7) or metastatic (n = 1) PDAC, and had 2 DCE-MRI examinations: one before and one 8 ± 1 weeks after starting first-line chemotherapy. A small triplicate perfusion phantom was imaged with each patient, serving as an internal reference for accurate quantitative image analysis. Tumor perfusion was measured with K using extended Tofts model before and after phantom-based data correction. Results are presented as mean ± SD and 95% confidence intervals (CIs). Statistical difference was evaluated with 1-way analysis of variance.

RESULTS

Tumor-size change of responding group (n = 4) was -12% ± 4% at 8 weeks of therapy, while that of nonresponding group (n = 4) was 18% ± 15% (P = 0.0100). Before phantom-based data correction, the K change of responding tumors was 69% ± 23% (95% CI, 32% to 106%) at 8 weeks, whereas that of nonresponding tumors was -1% ± 41% (95% CI, -65% to 64%) (P = 0.0247). After correction, the data variation in each group was significantly reduced; the K change of responding tumors was 73% ± 6% (95% CI, 64% to 82%) compared with nonresponding tumors of -0% ± 5% (95% CI, -7% to 8%) (P < 0.0001).

CONCLUSIONS

Quantitative DCE-MRI measured the significant perfusion increase of PDAC tumors responding favorably to chemotherapy, with decreased variability after correction using a perfusion phantom.

Feasibility of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Using Low-Dose Gadolinium: Comparative Performance With Standard Dose in Prostate Cancer Diagnosis

OBJECTIVES

This study investigates whether administration of low doses of gadolinium-based contrast agent (GBCA) for dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) can be as effective as a standard dose in distinguishing prostate cancer (PCa) from benign tissue. In addition, we evaluated the combination of kinetic parameters from the low- and high-dose injection as a new diagnostic marker.

MATERIALS AND METHODS

Patients (n = 17) with histologically confirmed PCa underwent preoperative 3 T MRI. Dynamic contrast-enhanced MRI images were acquired at 8.3-second temporal resolution with a low dose (0.015 mmol/kg) and close to the standard dose (0.085 mmol/kg) of gadobentate dimeglumine bolus injections. Low-dose images were acquired for 3.5 minutes, followed by a 5-minute gap before acquiring standard dose images for 8.3 minutes. The data were analyzed qualitatively to investigate whether lesions could be detected based on early focal enhancement and quantitatively by fitting signal intensity as a function of time with an empirical mathematical model to obtain a maximum enhancement projection (MEP) and signal enhancement rate (α).

RESULTS

Both low- and standard-dose DCE-MRI showed similar sensitivity (13/26 = 50%) and lesion conspicuity score (4.0 ± 1.0 vs 4.2 ± 0.9; P = 0.317) for PCa diagnosis on qualitative analysis. Prostate cancer showed significantly increased α compared with benign tissue for low (9.98 ± 5.84 vs 5.12 ± 2.95 s) but not for standard (4.27 ± 2.20 vs 3.35 ± 1.48 s) dose. The ratio of low-dose α to standard-dose α was significantly greater (P = 0.02) for PCa (2.8 ± 2.3) than for normal prostate (1.6 ± 0.9), suggesting changes in water exchange and T2* effects associated with cancer. In addition, decreases in the percentage change in T1 relaxation rate as a function of increasing contrast media concentration (ie, the "saturation effect") can also contribute to the observed differences in high-dose and low-dose α. Area under the receiver operating characteristic curve for differentiating PCa from benign tissue using α was higher for low dose (0.769) compared with standard dose (0.625). There were no significant differences between MEP calculated for PCa and normal tissue at the low and standard doses. Moderate significant Pearson correlation for DCE parameters, MEP (r = 0.53) and α (r = 0.58), was found between low and standard doses of GBCA.

CONCLUSIONS

These preliminary results suggest that DCE-MRI with a low GBCA dose distinguishes PCa from benign prostate tissue more effectively than does the standard GBCA dose, based on signal enhancement rate. Diagnostic accuracy is similar on qualitative assessment. Prostate cancer diagnosis may be feasible with DCE-MRI with low-dose GBCA. In addition, comparison of enhancement kinetics after low and high doses of contrast media may provide diagnostically useful information.

Multiparametric PET/MR imaging biomarkers are associated with overall survival in patients with pancreatic cancer

PURPOSE

To correlate the overall survival (OS) with the imaging biomarkers of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), diffusion-weighted imaging (DWI), magnetic resonance spectroscopy, and glucose metabolic activity derived from integrated fluorine 18 fluorodeoxyglucose positron emission tomography (18F-FDG PET)/MRI in patients with pancreatic cancer.

METHODS

This prospective study was approved by the institutional review board and informed consent was obtained from all participants. Sixty-three consecutive patients (mean age, 62.7 ± 12 y; men/women, 40/23) with pancreatic cancer underwent PET/MRI before treatment. The imaging biomarkers were comprised of DCE-MRI parameters (peak, IAUC 60 , K trans , k ep , v e ), the minimum apparent diffusion coefficient (ADCmin), choline level, standardized uptake values, metabolic tumor volume, and total lesion glycolysis (TLG) of the tumors. The relationships between these imaging biomarkers with OS were evaluated with the Kaplan-Meier and Cox proportional hazard models.

RESULTS

Seventeen (27%) patients received curative surgery, with the median follow-up duration being 638 days. Univariate analysis showed that patients at a low TNM stage (≦3, P = 0.041), high peak (P = 0.006), high ADCmin (P = 0.002) and low TLG (P = 0.01) had better OS. Moreover, high TLG/peak ratio was associated with poor OS (P = 0.016). Multivariate analysis indicated that ADCmin (P = 0.011) and TLG/peak ratio (P = 0.006) were independent predictors of OS after adjustment for age, gender, tumor size, and TNM stage. The TLG/peak ratio was an independent predictor of OS in a subgroup of patients who did not receive curative surgery (P = 0.013).

CONCLUSION

The flow-metabolism mismatch reflected by the TLG/peak ratio may better predict OS than other imaging biomarkers from PET/MRI in pancreatic cancer patients.

Pancreatic Adenocarcinoma Staging in the Era of Preoperative Chemotherapy and Radiation Therapy

Pancreatic ductal adenocarcinoma (PDA) remains among the most challenging malignancies to treat. At diagnosis, the tumor often already extends beyond the confines of the pancreas, spreading to an extent such that primary surgery with curative intent is very rarely feasible. Considerable momentum is now being given to a treatment strategy involving neoadjuvant chemotherapy or chemotherapy and radiation therapy in patients with nonmetastatic PDA. The main advantage of this strategy is better selection of patients likely to benefit from curative-intent surgery through the achievement of negative resection margins. Patients with rapidly progressive disease are identified and are spared ineffective surgery with its attendant morbidity. Neoadjuvant therapy can downstage tumors classified as locally advanced at initial imaging studies to resectable tumors. However, the imaging study evaluation of the response to neoadjuvant therapy is extremely complex. Thus, the diagnostic performance of imaging studies is not sufficient to ensure the accurate selection of patients in whom negative-margin resection is likely to be achieved. More specifically, standard criteria for predicting vascular invasion, based on the amount of tumor-vessel contact, are not valid after neoadjuvant therapy. ^©RSNA, 2018.

DCE-MRI for Early Prediction of Response in Hepatocellular Carcinoma after TACE and Sorafenib Therapy: A Pilot Study

Objective:

Dynamic contrast-enhanced MRI (DCE-MRI) can measure the changes in tumor blood flow, vascular permeability and interstitial and intravascular volume. The objective was to evaluate the efficacy of DCE-MRI in prediction of Barcelona Clinic Liver Cancer (BCLC) staging B or C hepatocellular carcinoma (HCC) response after treatment with transcatheter arterial chemoembolization (TACE) followed by sorafenib therapy.

Methods:

Sorafenib was administered four days after TACE of BCLC staging B or C HCC in 11 patients (21 lesions). DCE-MRI was performed with Gd-EOB-DTPA contrast before TACE and three and 10 days after TACE. DCE-MRI acquisitions were taken pre-contrast, hepatic arterial-dominant phase and 60, 120, 180, 240, 330, 420, 510 and 600 seconds post-contrast. Distribution volume of contrast agent (DV) and transfer constant Ktrans were calculated. Patients were grouped by mRECIST after one month or more post-TACE into responders (complete response, partial response) and non-responders (stable disease, progressive disease).

Results:

DV was reduced in responders at three and 10 days post-TACE (p = 0.008 and p = 0.008 respectively). DV fell in non-responders at three days (p = 0.025) but was not significantly changed from pre-TACE values after sorafenib. Sensitivity and specificity for DV 10 days post-TACE were 88% and 77% respectively.

Conclusion:

DV may be a useful biomarker for early prediction of therapeutic outcome in intermediate HCC.

Multiparametric MR imaging detects therapy efficacy of radioactive seeds brachytherapy in pancreatic ductal adenocarcinoma xenografts

OBJECTIVE

To investigate the therapeutic efficacy of Iodine-125 (¹²⁵I) seeds brachytherapy to pancreatic ductal adenocarcinoma (PDAC) xenografts via multiparametric magnetic resonance imaging (MRI) analysis.

MATERIALS AND METHODS

Twenty mice were implanted subcutaneously with SW-1990 PDAC xenografts. The tumor-bearing mice were randomly divided into ¹²⁵I seeds group (n = 10) and blank control group (n = 10). Treatment response was monitored by diffusion-weighted magnetic resonance imaging (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI) obtained 1 day before, 14 and 60 days after treatment. Imaging results were correlated with histopathology.

RESULTS

¹²⁵I seeds brachytherapy resulted in a significant increase in mean tumor apparent diffusion coefficient (ADC) values compared to the control at 14 and 60 days after treatment (p < 0.05). DCE-MRI showed a significant decrease in the perfusion parameters including K^trans and K_ep (p < 0.05). The mean ADCs within the peripheral region of the tumors were linearly proportional to the mean apoptotic cell density (p = 0.015; Spearman's coefficient = 0.945). The K^trans and K_ep were linearly proportional to microvessel density (MVD) (p = 0.043, 0.047; Spearman's coefficient = 0.891, 0.884).

CONCLUSION

¹²⁵I seeds brachytherapy leads to effective inhibition of PDAC cell proliferation, higher degree of necrosis and necroptosis, and lower MVD. Both DW-MRI and DCE-MRI are feasible to monitor a response to ¹²⁵I seeds brachytherapy in the PDAC xenografts. This paper shows an original project concerning about a possible palliative treatment not only in a murine model (preclinical setting) but also in humans.

Repeatability and correlations of dynamic contrast enhanced and T2* MRI in patients with advanced pancreatic ductal adenocarcinoma

BACKGROUND

In current oncological practice of pancreatic ductal adenocarcinoma (PDAC), there is a great demand for response predictors and markers for early treatment evaluation. In this study, we investigated the repeatability and the interaction of dynamic contrast enhanced (DCE) and T2* MRI in patients with advanced PDAC to enable for such evaluation using these techniques.

MATERIALS & METHODS

15 PDAC patients underwent two DCE, T2* and anatomical 3 T MRI sessions before start of treatment. Parametric maps were calculated for the transfer constant (K^trans), rate constant (k_ep), extracellular extravascular space (v_e) and perfusion fraction (v_p). Quantitative R2* (1/T2*) maps were obtained from the multi-echo T2* images. Differences between normal and cancerous pancreas were determined using a Wilcoxon matched pairs test. Repeatability was obtained using Bland-Altman analysis and relations between DCE and T2*/R2* were observed by Spearman correlation and voxel-wise binned plots of tumor voxels.

RESULTS

PDAC K^trans (p = 0.007), k_ep (p < 0.001), v_p (p = 0.035) were lower and v_e (p < 0.001) was higher compared to normal pancreas. The coefficient of variation between sessions was 21.8% for K^trans, 9.9% for k_ep, 19.3% for v_e, 18.2% for v_p and 18.7% for R2*. Variation between patients ranged from 20.2% for k_ep to 43.6% for K^trans. In the tumor both K^trans (r = 0.56, p = 0.030) and v_e (r = 0.54, p = 0.037) showed a positive correlation with T2*. Voxel wise analysis showed a steep increase in R2* for tumor voxels with lower K^trans and v_e.

CONCLUSION

We showed good repeatability of DCE and T2* related MRI parameters in advanced PDAC patients. Furthermore, we have illustrated the relation of DCE K^trans and v_e with tissue T2* and R2* indicating substantial value of these parameters for detecting tumor hypoxia in future studies. The results from our study pave the way for further response evaluation studies and patient selection based on DCE and T2* parameters.

The feasibility of 18F-AlF-NOTA-PRGD2 PET/CT for monitoring early response of Endostar antiangiogenic therapy in human nasopharyngeal carcinoma xenograft model compared with 18F-FDG

Purpose

Radiolabeled arginine-glycine-aspartic acid (RGD) peptides have been developed for PET imaging of integrin avβ3 in the tumor vasculature, leading to great potential for noninvasively evaluating tumor angiogenesis and monitoring antiangiogenic treatment. The aim of this study was to investigate a novel one-step labeled integrin-targeted tracer, ¹⁸F-AlF-NOTA-PRGD2, for PET/CT for detecting tumor angiogenesis and monitoring the early therapeutic efficacy of antiangiogenic agent Endostar in human nasopharyngeal carcinoma (NPC) xenograft model.

Experimental design and results

Mice bearing NPC underwent ¹⁸F-AlF-NOTA-PRGD2 PET/CT at baseline and after 2, 4, 7, and 14 days of consecutive treatment with Endostar or PBS, compared with ¹⁸F-FDG PET/CT. Tumors were harvested at all imaging time points for histopathological analysis with H & E and microvessel density (MVD) and integrin avβ3 immunostaining. The maximum percent injected dose per gram of body weight (%ID/gmax) tumor uptake of ¹⁸F-AlF-NOTA-PRGD2 PET/CT was significantly lower than that in the control group starting from day 2 (p < 0.01), much earlier and more accurately than that of ¹⁸F-FDG PET/CT. Moreover, a moderate linear correlation was observed between tumor MVD and the corresponding tumor uptake of ¹⁸F-AlF-NOTA-PRGD2 PET/CT (r = 0.853, p < 0.01).

Conclusions

¹⁸F-AlF-NOTA-PRGD2 PET/CT can be used for in vivo angiogenesis imaging and monitoring early response to Endostar antiangiogenic treatment in NPC xenograft model, favoring its potential clinical translation.

The application of high-field magnetic resonance perfusion imaging in the diagnosis of pancreatic cancer

Pancreatic cancer is the fourth leading cause of cancer death in the world. It is a disease of insidious progression and high lethality. The present study was to investigate the diagnostic value of high-filed magnetic resonance (MR) perfusion imaging in pancreatic cancer. Thirty-three patients with suspected pancreatic cancer were recruited in our study and underwent routine MR imaging. When compared with para-tumoral and normal tissue, the pancreatic lesions showed significant lower slope, peak enhancement (PE), and signal enhancement ratio (SER) as well as higher time to peak (TTP). Para-tumoral tissue was found to have significantly lower slope and PE, slightly higher TTP than normal tissue. MR perfusion imaging displays hemodynamic alterations in both pancreatic cancer and surrounding pancreatic tissue, and provides indirect assessment of tumor vascularity. In conclusion, high field MR perfusion imaging has important clinical significance in early diagnosis of pancreatic cancer.

Differentiation of pancreatic carcinoma and mass-forming focal pancreatitis: qualitative and quantitative assessment by dynamic contrast-enhanced MRI combined with diffusion-weighted imaging

Differentiation between pancreatic carcinoma (PC) and mass-forming focal pancreatitis (FP) is invariably difficult. For the differential diagnosis, we qualitatively and quantitatively assessed the value of dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI) in PC and FP in the present study. This study included 32 PC and 18 FP patients with histological confirmation who underwent DCE-MRI and DWI. The time-signal intensity curve (TIC) of PC and FP were classified into 5 types according to the time of reaching the peak, namely, type I, II, III, IV, and V, respectively, and two subtypes, namely, subtype-a (washout type) and subtype-b (plateau type) according to the part of the TIC profile after the peak. Moreover, the mean and relative apparent diffusion coefficient (ADC) value between PC and FP on DWI were compared. The type V TIC was only recognized in PC group (P < 0.01). Type IV b were more frequently observed in PC (P = 0.036), while type- IIa (P < 0.01), type- Ia (P = 0.037) in FP. We also found a significant difference in the mean and relative ADC value between PC and FP. The combined image set of DCE-MRI and DWI yielded an excellent sensitivity, specificity, and diagnostic accuracy (96.9%, 94.4%, and 96.0%). The TIC of DCE-MRI and ADC value of DWI for pancreatic mass were found to provide reliable information in differentiating PC from FP, and the combination of DCE-MRI and DWI can achieve a higher sensitivity, specificity, and diagnostic accuracy.