Evaluation of pancreatic cancer by multiple breath-hold dynamic contrast-enhanced magnetic resonance imaging at 3.0T

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.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Measuring Perfusion in Pancreatic Ductal Adenocarcinoma and Different Tumor Grade: A Preliminary Single Center Study

BACKGROUND

Dynamic contrast-enhanced magnetic resonance imaging is a noninvasive imaging modality that can supply information regarding the tumor anatomy and physiology. The aim of the study was to analyze DCE-MRI perfusion parameters in normal pancreatic parenchymal tissue and PDAC and to evaluate the efficacy of this diagnostic modality in determining the tumor grade.

METHODS

A single-center retrospective study was performed. A total of 28 patients with histologically proven PDAC underwent DCE-MRI; the control group enrolled 14 patients with normal pancreatic parenchymal tissue; the radiological findings were compared with histopathological data. The study patients were further grouped according to the differentiation grade (G value): well- and moderately differentiated and poorly differentiated PDAC.

RESULTS

The median values of K^trans, k_ep and iAUC were calculated lower in PDAC compared with the normal pancreatic parenchymal tissue (p < 0.05). The mean value of Ve was higher in PDAC, compared with the normal pancreatic tissue (p < 0.05). K^trans, k_ep and iAUC were lower in poorly differentiated PDAC, whereas Ve showed no differences between groups.

CONCLUSIONS

Ve and iAUC DCE-MRI perfusion parameters are important as independent diagnostic criteria predicting the probability of PDAC; the Ktrans and iAUC DCE-MRI perfusion parameters may serve as effective independent prognosticators preoperatively identifying poorly differentiated PDAC.

NMFNA: A Non-negative Matrix Factorization Network Analysis Method for Identifying Modules and Characteristic Genes of Pancreatic Cancer

Pancreatic cancer (PC) is a highly fatal disease, yet its causes remain unclear. Comprehensive analysis of different types of PC genetic data plays a crucial role in understanding its pathogenic mechanisms. Currently, non-negative matrix factorization (NMF)-based methods are widely used for genetic data analysis. Nevertheless, it is a challenge for them to integrate and decompose different types of genetic data simultaneously. In this paper, a non-NMF network analysis method, NMFNA, is proposed, which introduces a graph-regularized constraint to the NMF, for identifying modules and characteristic genes from two-type PC data of methylation (ME) and copy number variation (CNV). Firstly, three PC networks, i.e., ME network, CNV network, and ME-CNV network, are constructed using the Pearson correlation coefficient (PCC). Then, modules are detected from these three PC networks effectively due to the introduced graph-regularized constraint, which is the highlight of the NMFNA. Finally, both gene ontology (GO) and pathway enrichment analyses are performed, and characteristic genes are detected by the multimeasure score, to deeply understand biological functions of PC core modules. Experimental results demonstrated that the NMFNA facilitates the integration and decomposition of two types of PC data simultaneously and can further serve as an alternative method for detecting modules and characteristic genes from multiple genetic data of complex diseases.

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.

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 K^trans, V_p^, 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 K^trans, V_p^, 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 K^trans 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 K^trans 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 K^trans 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.

Functional imaging in pancreatic disease

In addition to the classical morphological evaluation of pancreatic disease, the constant technological advances in imaging techniques based fundamentally on computed tomography and magnetic resonance imaging have enabled the quantitative functional and molecular evaluation of this organ. In many cases, this imaging-based information results in substantial changes to patient management and can be a fundamental tool for the development of biomarkers. The aim of this article is to review the role of emerging functional and molecular techniques based on computed tomography and magnetic resonance imaging in the evaluation of pancreatic disease.

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 (ADC_min), 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 ADC_min (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 ADC_min (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.

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.

Dynamic contrast-enhanced MRI of the microenvironment of pancreatic adenocarcinoma xenografts

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with poor outcome. Resistance to treatment is associated with impaired vascularity, extensive hypoxia, and interstitial hypertension. In this study, the potential of dynamic contrast-enhanced (DCE)-MRI as a method for assessing the microvascular density (MVD), the fraction of hypoxic tissue, and the interstitial fluid pressure (IFP) of PDACs was investigated.

MATERIAL AND METHODS

Intramuscular BxPC-3, Capan-2, MIAPaCa-2, and Panc-1 PDAC xenografts were used as preclinical models of human PDACs. DCE-MRI with Gd-DOTA as contrast agent was conducted with a 7.05-T scanner, and the DCE-MRI series were analyzed voxelwise by using the Tofts pharmacokinetic model. Tumor MVD and hypoxia were measured in histological preparations by using pimonidazole as a hypoxia marker and CD31 as a marker of endothelial cells. IFP was measured with a Millar catheter.

RESULTS

K^trans (the volume transfer constant of Gd-DOTA) increased with increasing MVD and decreased with increasing hypoxic fraction, but was not associated with IFP. Any association between v_e (the fractional distribution volume of Gd-DOTA) and MVD, hypoxic fraction, or IFP could not be detected.

CONCLUSIONS

This study shows that DCE-MRI is a useful modality for assessing important features of the microenvironment of PDAC xenografts and thus provides the basis for future preclinical and clinical DCE-MRI investigations of PDAC.

Pancreatic adenocarcinoma: a pilot study of quantitative perfusion and diffusion-weighted breath-hold magnetic resonance imaging

PURPOSE

To confirm the feasibility of breath-hold DCE-MRI and DWI at 3T to obtain the intra-abdominal quantitative physiologic parameters, K(trans), k ep, and ADC, in patients with untreated pancreatic ductal adenocarcinomas.

METHODS

Diffusion-weighted single-shot echo-planar imaging (DW-SS-EPI) and dynamic contrast-enhanced (DCE) MRI were used for 16 patients with newly diagnosed biopsy-proven pancreatic ductal adenocarcinomas. K(trans), k ep, and apparent diffusion coefficient (ADC) values of pancreatic tumors, non-tumor adjacent pancreatic parenchyma (NAP), liver metastases, and normal liver tissues were quantitated and statistically compared.

RESULTS

Fourteen patients were able to adequately hold their breath for DCE-MRI, and 15 patients for DW-SS-EPI. Four patients had liver metastases within the 6 cm of Z axis coverage centered on the pancreatic primary tumors. K(trans) values (10(-3) min(-1)) of primary pancreatic tumors, NAP, liver metastases, and normal liver tissues were 7.3 ± 4.2 (mean ± SD), 25.8 ± 14.9, 8.1 ± 5.9, and 45.1 ± 15.6, respectively, k ep values (10(-2) min(-1)) were 3.0 ± 0.9, 7.4 ± 3.1, 5.2 ± 2.0, and 12.1 ± 2.8, respectively, and ADC values (10(-3) mm(2)/s) were 1.3 ± 0.2, 1.6 ± 0.3, 1.1 ± 0.1, and 1.3 ± 0.1, respectively. K(trans), k ep, and ADC values of primary pancreatic tumors were significantly lower than those of NAP (p < 0.05), while K(trans) and k ep values of liver metastases were significantly lower than those of normal liver tissues (p < 0.05).

CONCLUSIONS

3T breath-hold quantitative physiologic MRI is a feasible technique that can be applied to a majority of patients with pancreatic adenocarcinomas.

Pancreatic Cancer: a Challenge to Cure

Pancreatic ductal adenocarcinoma (PDA) is a challenging disease, as overall survival has not improved over the last several decades. The disease is characterized by late diagnosis, difficult major surgery in resectable patients, and a biologically chemoresistant tumor. Intense research in the field is ongoing to develop biomarkers for early detection and prognostication. Surgery is presently the crux of the management of PDA and has been standardized over the years with high-volume centers reporting <5 % operative mortality. The biggest problem is to overcome the inherent chemoresistance of the tumor that is densely fibrotic and hypoxic and has a tendency to invade surrounding neuronal plexuses. This review attempts to summarize in brief the reasons why PDA is difficult to treat, and provides a glimpse of the ongoing research in the field.

Advances in Biomedical Imaging, Bioengineering, and Related Technologies for the Development of Biomarkers of Pancreatic Disease: Summary of a National Institute of Diabetes and Digestive and Kidney Diseases and National Institute of Biomedical Imaging and Bioengineering Workshop

A workshop sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases and the National Institute of Biomedical Imaging and Bioengineering focused on research gaps and opportunities in the development of new biomarkers of pancreatic disease. The session was held on July 22, 2015, and structured into 6 sessions: 1) Introduction and Overview; 2) Keynote Address; 3) New Approaches to the Diagnosis of Chronic Pancreatitis; 4) Biomarkers of Pain and Inflammation; 5) New Approaches to the Detection of Pancreatic Cancer; and 6) Shed Exosomes, Shed Cells, and Shed Proteins. Recent advances in the fields of pancreatic imaging, functional markers of pancreatic disease, proteomics, molecular and cellular imaging, and detection of circulating cancer cells and exosomes were reviewed. Knowledge gaps and research needs were highlighted. The development of new methods for the noninvasive determination of pancreatic pathology; the use of cellular markers of pancreatic function, inflammation, pain, and malignancy; and the refinement of methods to identify cells and cellular constituents of pancreatic cancer were discussed. The further refinement of sophisticated technical methods and the need for clinical studies to validate these new approaches in large-scale studies of patients at risk for the development of pancreatic disease were repeatedly emphasized.

Pancreatic cancer: why is it so hard to treat?

No common malignancy is as rapidly and inevitably fatal as pancreatic ductal adenocarcinoma (PDA). This grim fact has driven substantial research efforts into this disease in recent decades. Unfortunately, the investment has yet to result in a meaningful increase in 5-year survival. This has prompted many pancreatic cancer researchers and advocates to redouble their efforts, but also requires one to step back and ask why the previous efforts were lacking and to consider why pancreatic cancer is so difficult to treat. The difficulties are legion. PDA is characterized by an insidious clinical syndrome, but is rarely diagnosed at a time when surgical resection is feasible. We lack markers of early detection and screening programs remain unproven even in high risk populations. The location of the tumor in the retroperitoneum, the advanced age of patients, and the systemic effects of disease limit the options for local therapy. Chemotherapy may provide a small benefit, but most efforts to improve on the current regimens consistently and stubbornly fail in advanced clinical trials. The molecular and cellular features of ductal pancreatic tumors are aggressive and underlay multiple levels of therapeutic resistance. Non-cell-autonomous features including stromal proliferation, reduced vascular density and immune suppression also contribute to therapeutic resistance. Growing awareness of these the fundamental features of PDA has begun to guide ongoing research efforts. Clinical trials are now specifically targeting these tumor properties and actively focusing on the therapeutic implications of tumor stroma. As reviewed here, reflecting on the fundamental question of why pancreatic cancer is so difficult to treat is a necessary and informative exercise that will aid our efforts to improve patient outcomes. These efforts will lead to improvements in clinical trial design, expand our focus to include the molecular and histologic implications of novel treatment paradigms, and ultimately change the lives of our patients.