Assessment of Dynamic Contrast-Enhanced Magnetic Resonance Imaging in the Differentiation of Pancreatic Ductal Adenocarcinoma From Other Pancreatic Solid Lesions:

Efficacy of endoscopic ultrasound-guided tissue acquisition for solid pancreatic lesions 20 mm or less in diameter suspected as neuroendocrine tumors or requiring differentiation

BACKGROUND

For non-functioning pancreatic neuroendocrine tumors (pNETs) ≤ 20 mm, most guidelines consider follow-up observations as an option; however, the various treatment strategies are defined by size alone, even though the Ki-67 index is important for malignancy grading. Endoscopic ultrasound-guided tissue acquisition (EUS-TA) is the standard for the histopathological diagnosis of solid pancreatic lesions; however, recent results for small lesions remain unclear. Therefore, we examined the efficacy of EUS-TA for solid pancreatic lesions ≤ 20 mm suspected as pNETs or requiring differentiation and the non-increase rate in tumor size in follow-up cases.

METHODS

We retrospectively analyzed data of 111 patients (median age = 58 years) with lesions ≤ 20 mm suspected as pNETs or requiring differentiation who underwent EUS-TA. All patients underwent specimen evaluation by rapid onsite evaluation (ROSE).

RESULTS

EUS-TA led to a diagnosis of pNETs in 77 patients (69.4%) and tumors other than pNETs in 22 patients (19.8%). The histopathological diagnostic accuracy of EUS-TA was 89.2% (99/111) overall, 94.3% (50/53) for 10-20 mm lesions, and 84.5% (49/58) for ≤ 10 mm lesions, with no significant difference in diagnostic accuracy (p = 0.13). The Ki-67 index was measurable in all patients with a histopathological diagnosis of pNETs. Among 49 patients with a diagnosis of pNETs who were followed up, one patient (2.0%) showed tumor enlargement.

CONCLUSIONS

EUS-TA for solid pancreatic lesions ≤ 20 mm suspected as pNETs or requiring differentiation is safe and has adequate histopathological diagnostic accuracy, suggesting that follow-up observations of pNETs with a histological pathologic diagnosis are acceptable in the short term.

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.

Qualitative diagnostic signature for pancreatic ductal adenocarcinoma based on the within-sample relative expression orderings

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) accounts for about 90% of pancreatic cancer, which is one of the most aggressive malignant neoplasms with a 9.3% five-year survival rate. The pathological biopsy is the current golden standard for confirming suspicious lesions of PDAC, but it is not entirely reliable because of the insufficient sampling amount and inaccurate sampling location. Therefore, developing a robust signature to aid the accurate diagnosis of PDAC is critical.

METHODS

Based on the within-sample relative expression orderings of gene pairs, we identified a qualitative signature to discriminate both PDAC and adjacent samples from both chronic pancreatitis and normal samples in the training datasets and validated it in other independent datasets produced by different laboratories with different measuring platforms.

RESULTS

A six-gene-pair signature was identified in the training data and validated in eight independent datasets. For surgical samples, 96.63% of 356 PDAC tissues, 100% of 11 pancreatitis tissues of non-cancer patients, and 23 of 24 normal pancreatic tissues were correctly classified. Especially, 59 of 60 cancer-adjacent normal tissues of PDAC patients were correctly identified as PDAC. For biopsy samples, all of 11 PDAC biopsy tissues were correctly classified as PDAC.

CONCLUSION

The signature can distinguish both PDAC and PDAC-adjacent normal tissues from both chronic pancreatitis and normal tissues of non-cancer patients even when the sampling locations are inaccurate, which can aid the diagnosis of PDAC.

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.

Differentiating pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas by the "Duct-Road Sign": A preliminary magnetic resonance imaging study

To assess the duct-road sign and tumor-to-duct ratio (TDR) in MRI for differentiating pancreatic neuroendocrine tumors (PNETs) from pancreatic ductal-adenocarcinomas (PDACs).Retrospectively reviewed MRI characteristics of 78 pancreatic masses (histopathology-proven 25 PNETs and 53 PDACs). Receiver operating characteristics with TDR and diagnostic performance of the duct-road sign for differential diagnosis were performed.The prevalence of duct-road sign in PNETs was higher than that for PDACs (84% vs 0%; P < .001). A strong correlation (r = 0.884, P < .001) was observed between MRI for PNETs and the frequency of this sign. Performance characteristics of the duct-road sign in MRI for PNET diagnosis were sensitivity (84%, [21 of 25]), specificity (100%, [53 of 53]), positive predictive value (100%, [21 of 21]), negative predictive value (92.9%, [53 of 57]), and accuracy (94.8%, [74 of 78]). In the intention-to-diagnose analysis, the corresponding values were 67.7% (21 of 31), 100% (53 of 53), 100% (21 of 21), 84.1% (53 of 63), and 88.1% (74 of 84). The TDR in PNETs was observed to be greater than that in PDACs (14.6 ± 9.3 vs 6.9 ± 3.8, P = .001). TDR with a cut-off value of 7.7 had high sensitivity (84%) and specificity (66%) with area under curve (0.802, 95% CI: 0.699, 0.904; P < .001) for distinguishing PNETs from PDACs.The presence of duct-road sign and TDR > 7.7 on MRI may assist in diagnosis for PNET instead of PDAC.

Imaging modalities in the diagnosis of pancreatic adenocarcinoma: A systematic review and meta-analysis of sensitivity, specificity and diagnostic accuracy

BACKGROUND

Pancreatic cancer, primarily pancreatic ductal adenocarcinoma (PDAC), accounts for 2.4% of cancer diagnoses and 5.8% of cancer death annually. Early diagnoses can improve 5-year survival in PDAC. The aim of this systematic review was to determine the sensitivity, specificity and diagnostic accuracy values for MRI, CT, PET&PET/CT, EUS and transabdominal ultrasound (TAUS) in the diagnosis of PDAC.

METHODS

A systematic review was undertaken to identify studies reporting sensitivity, specificity and/or diagnostic accuracy for the diagnosis of PDAC with MRI, CT, PET, EUS or TAUS. Proportional meta-analysis was performed for each modality.

RESULTS

A total of 5399 patients, 3567 with PDAC, from 52 studies were included. The sensitivity, specificity and diagnostic accuracy were 93% (95% CI=88-96), 89% (95% CI=82-94) and 90% (95% CI=86-94) for MRI; 90% (95% CI=87-93), 87% (95% CI=79-93) and 89% (95% CI=85-93) for CT; 89% (95% CI=85-93), 70% (95% CI=54-84) and 84% (95% CI=79-89) for PET; 91% (95% CI=87-94), 86% (95% CI=81-91) and 89% (95% CI=87-92) for EUS; and 88% (95% CI=86-90), 94% (95% CI=87-98) and 91% (95% C=87-93) for TAUS.

CONCLUSION

This review concludes all modalities, except for PET, are equivalent within 95% confidence intervals for the diagnosis of PDAC.

Imaging modalities for characterising focal pancreatic lesions

BACKGROUND

Increasing numbers of incidental pancreatic lesions are being detected each year. Accurate characterisation of pancreatic lesions into benign, precancerous, and cancer masses is crucial in deciding whether to use treatment or surveillance. Distinguishing benign lesions from precancerous and cancerous lesions can prevent patients from undergoing unnecessary major surgery. Despite the importance of accurately classifying pancreatic lesions, there is no clear algorithm for management of focal pancreatic lesions.

OBJECTIVES

To determine and compare the diagnostic accuracy of various imaging modalities in detecting cancerous and precancerous lesions in people with focal pancreatic lesions.

SEARCH METHODS

We searched the CENTRAL, MEDLINE, Embase, and Science Citation Index until 19 July 2016. We searched the references of included studies to identify further studies. We did not restrict studies based on language or publication status, or whether data were collected prospectively or retrospectively.

SELECTION CRITERIA

We planned to include studies reporting cross-sectional information on the index test (CT (computed tomography), MRI (magnetic resonance imaging), PET (positron emission tomography), EUS (endoscopic ultrasound), EUS elastography, and EUS-guided biopsy or FNA (fine-needle aspiration)) and reference standard (confirmation of the nature of the lesion was obtained by histopathological examination of the entire lesion by surgical excision, or histopathological examination for confirmation of precancer or cancer by biopsy and clinical follow-up of at least six months in people with negative index tests) in people with pancreatic lesions irrespective of language or publication status or whether the data were collected prospectively or retrospectively.

DATA COLLECTION AND ANALYSIS

Two review authors independently searched the references to identify relevant studies and extracted the data. We planned to use the bivariate analysis to calculate the summary sensitivity and specificity with their 95% confidence intervals and the hierarchical summary receiver operating characteristic (HSROC) to compare the tests and assess heterogeneity, but used simpler models (such as univariate random-effects model and univariate fixed-effect model) for combining studies when appropriate because of the sparse data. We were unable to compare the diagnostic performance of the tests using formal statistical methods because of sparse data.

MAIN RESULTS

We included 54 studies involving a total of 3,196 participants evaluating the diagnostic accuracy of various index tests. In these 54 studies, eight different target conditions were identified with different final diagnoses constituting benign, precancerous, and cancerous lesions. None of the studies was of high methodological quality. None of the comparisons in which single studies were included was of sufficiently high methodological quality to warrant highlighting of the results. For differentiation of cancerous lesions from benign or precancerous lesions, we identified only one study per index test. The second analysis, of studies differentiating cancerous versus benign lesions, provided three tests in which meta-analysis could be performed. The sensitivities and specificities for diagnosing cancer were: EUS-FNA: sensitivity 0.79 (95% confidence interval (CI) 0.07 to 1.00), specificity 1.00 (95% CI 0.91 to 1.00); EUS: sensitivity 0.95 (95% CI 0.84 to 0.99), specificity 0.53 (95% CI 0.31 to 0.74); PET: sensitivity 0.92 (95% CI 0.80 to 0.97), specificity 0.65 (95% CI 0.39 to 0.84). The third analysis, of studies differentiating precancerous or cancerous lesions from benign lesions, only provided one test (EUS-FNA) in which meta-analysis was performed. EUS-FNA had moderate sensitivity for diagnosing precancerous or cancerous lesions (sensitivity 0.73 (95% CI 0.01 to 1.00) and high specificity 0.94 (95% CI 0.15 to 1.00), the extremely wide confidence intervals reflecting the heterogeneity between the studies). The fourth analysis, of studies differentiating cancerous (invasive carcinoma) from precancerous (dysplasia) provided three tests in which meta-analysis was performed. The sensitivities and specificities for diagnosing invasive carcinoma were: CT: sensitivity 0.72 (95% CI 0.50 to 0.87), specificity 0.92 (95% CI 0.81 to 0.97); EUS: sensitivity 0.78 (95% CI 0.44 to 0.94), specificity 0.91 (95% CI 0.61 to 0.98); EUS-FNA: sensitivity 0.66 (95% CI 0.03 to 0.99), specificity 0.92 (95% CI 0.73 to 0.98). The fifth analysis, of studies differentiating cancerous (high-grade dysplasia or invasive carcinoma) versus precancerous (low- or intermediate-grade dysplasia) provided six tests in which meta-analysis was performed. The sensitivities and specificities for diagnosing cancer (high-grade dysplasia or invasive carcinoma) were: CT: sensitivity 0.87 (95% CI 0.00 to 1.00), specificity 0.96 (95% CI 0.00 to 1.00); EUS: sensitivity 0.86 (95% CI 0.74 to 0.92), specificity 0.91 (95% CI 0.83 to 0.96); EUS-FNA: sensitivity 0.47 (95% CI 0.24 to 0.70), specificity 0.91 (95% CI 0.32 to 1.00); EUS-FNA carcinoembryonic antigen 200 ng/mL: sensitivity 0.58 (95% CI 0.28 to 0.83), specificity 0.51 (95% CI 0.19 to 0.81); MRI: sensitivity 0.69 (95% CI 0.44 to 0.86), specificity 0.93 (95% CI 0.43 to 1.00); PET: sensitivity 0.90 (95% CI 0.79 to 0.96), specificity 0.94 (95% CI 0.81 to 0.99). The sixth analysis, of studies differentiating cancerous (invasive carcinoma) from precancerous (low-grade dysplasia) provided no tests in which meta-analysis was performed. The seventh analysis, of studies differentiating precancerous or cancerous (intermediate- or high-grade dysplasia or invasive carcinoma) from precancerous (low-grade dysplasia) provided two tests in which meta-analysis was performed. The sensitivity and specificity for diagnosing cancer were: CT: sensitivity 0.83 (95% CI 0.68 to 0.92), specificity 0.83 (95% CI 0.64 to 0.93) and MRI: sensitivity 0.80 (95% CI 0.58 to 0.92), specificity 0.81 (95% CI 0.53 to 0.95), respectively. The eighth analysis, of studies differentiating precancerous or cancerous (intermediate- or high-grade dysplasia or invasive carcinoma) from precancerous (low-grade dysplasia) or benign lesions provided no test in which meta-analysis was performed.There were no major alterations in the subgroup analysis of cystic pancreatic focal lesions (42 studies; 2086 participants). None of the included studies evaluated EUS elastography or sequential testing.

AUTHORS' CONCLUSIONS

We were unable to arrive at any firm conclusions because of the differences in the way that study authors classified focal pancreatic lesions into cancerous, precancerous, and benign lesions; the inclusion of few studies with wide confidence intervals for each comparison; poor methodological quality in the studies; and heterogeneity in the estimates within comparisons.

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.

Discrimination of metastatic from non-metastatic mesorectal lymph nodes in rectal cancer using quantitative dynamic contrast-enhanced magnetic resonance imaging

Preoperative detection of lymph nodes (LNs) metastasis is always highly challenging for radiologists nowadays. The utility of quantitative dynamic contrast-enhanced magnetic resonance imaging (QDCE-MRI) in identifying LNs metastasis is not well understood. In the present study, 59 patients with histologically proven rectal carcinoma underwent preoperative QDCE-MRI. The short axis diameter ratio, long axis diameter ratio, short-to-long axis diameter ratio and QDEC-MRI parameters (K(trans), Kep, fPV and Ve) values were compared between the non-metastatic (n=44) and metastatic (n=35) LNs groups based on pathological examination. Compared with the non-metastatic group, the metastatic group exhibited significantly higher short axis diameter (7.558±0.668 mm vs. 5.427±0.285 mm), K(trans) (0.483±0.198 min(-1) vs. 0.218±0.116 min(-1)) and Ve (0.399±0.118 vs. 0.203±0.096) values (all P<0.05). The short-to-long axis diameter ratio, long axis diameter ratio, Kep and fPV values did not show significant differences between the two groups. In conclusion, our results showed that for LNs larger than 5 mm in rectal cancer, there are distinctive differences in the K(trans) and Ve values between the metastatic and non-metastatic LNs, suggesting that QDCE-MRI may be potentially helpful in identifying LNs status.

Quantitative dynamic contrast-enhanced and diffusion-weighted MRI for differentiation between nasopharyngeal carcinoma and lymphoma at the primary site

OBJECTIVES

To investigate the value of quantitative dynamic contrast-enhanced MRI (QDCE-MRI) and diffusion-weighted MRI (DW-MRI) in differentiating nasopharyngeal carcinoma (NPC) from lymphoma.

METHODS

We retrospectively analysed the data from 102 patients (82 with NPC and 20 with lymphoma) who underwent pre-treatment QDCE-MRI and DW-MRI on a 1.5-T MR unit. QDEC-MRI parameters [influx transfer constant (K(trans)), efflux rate constant (Kep), fractional volume of extravascular extracellular space (Ve) and fractional volume of plasma (fPV)] based on pharmacokinetic model and apparent diffusion coefficient (ADC) were compared between the two nasopharyngeal malignancies.

RESULTS

The K(trans), Kep, Ve, fPV and ADC values (mean ± standard deviation) for NPC were 0.366 ± 0.155 min(-1), 1.353 ± 0.468 min(-1), 0.292 ± 0.117, 0.027 ± 0.024 and 0.981 ± 0.184 × 10(-3) mm(2) s(-1), respectively. The K(trans), Kep, Ve, fPV and ADC values (mean ± standard deviation) for lymphoma were 0.212 ± 0.059 min(-1), 1.073 ± 0.238 min(-1), 0.213 ± 0.104, 0.008 ± 0.007 and 0.760 ± 0.182 × 10(-3) mm(2) s(-1), respectively. Optimal cut-off values (area under the curve, sensitivity, specificity) for distinguishing the two tumours were as follows: K(trans) = 0.262 min(-1) (0.866, 80.49%, 85.00%), Kep = 1.401 min(-1) (0.681, 43.90%, 100.00%), Ve = 0.211 (0.784, 76.83%, 85.00%), fPV = 0.012 (0.779, 60.98%, 85.00%), ADC = 0.761 × 10(-3) mm(2) s(-1) (0.781, 93.90%, 55.00%).

CONCLUSIONS

QDCE-MRI together with DW-MRI is useful for differentiation between NPC and lymphoma.

The Correlation Between Diffusion-Weighted Imaging at 3.0-T Magnetic Resonance Imaging and Histopathology for Pancreatic Ductal Adenocarcinoma

PURPOSE

The aim of this study was to discuss the correlation between diffusion-weighted imaging (DWI) at 3.0-T magnetic resonance and histopathology for pancreatic ductal adenocarcinoma (PDA).

MATERIALS AND METHODS

Twenty-eight patients with histopathologically proven PDA were included in this study after 108 cases of suspected pancreatic tumors had been performed with DWI. The sequences of DWI included respiratory-triggered DWI and breath-hold DWI, which were performed with 2 b values (0 and 500 s/mm; 0 and 1000 s/mm), respectively. According to magnetic resonance images, wax blocks and slices were selected and stained with hematoxylin-eosin for anti-vascular endothelial growth factor (VEGF), anti-CD34, and anti-Ki-67 (Mib-1). The relationship between tumor apparent diffusion coefficient (ADC) and tumor fibrosis, as well as the expression of tumor VEGF, Ki-67, and multivessel density (MVD), were studied.

RESULTS

The ADC values of PDA of different grades of differentiation and fibrosis grade did not show statistically significant difference. The ADC values of PDA did not show the statistically significant correlation with the grades of differentiation, fibrosis grade, Ki-67 expression, and expression of VEGF and MVD.

CONCLUSIONS

The ADC of PDA cannot be used to reflect grades of differentiation, degree of tumor fibrosis, the expression of VEGF, the expression of Ki-67, and the tumor MVD.

Anatomical, Physiological, and Molecular Imaging for Pancreatic Cancer: Current Clinical Use and Future Implications

Pancreatic adenocarcinoma is one of the deadliest human malignancies. Early detection is difficult and effective treatment is limited. Verifying the presence of micrometastatic dissemination and vessel invasion remains elusive, limiting radiological staging once this diagnosis is made. Diagnostic imaging provides independent tools to evaluate and characterize the biologic behavior of pancreatic cancer. Conventional anatomic imaging alone with either CT or MRI yields useful information on organ involvement but is limited in providing molecular and physiological information. Molecular imaging techniques such as PET or MRS provide information on metabolic and signaling pathways. Advanced MR sequences that target physiological parameters expand imaging options to characterize these tumors. By considering the parametric data from these three imaging approaches (anatomic, molecular, and physiological) we can better define specific tumor signatures. Such parametric characterization can provide insight into tumor metabolism, cellular density, protein expression, focal perfusion, and vascular permeability of these tumors. Radiogenomics research has already demonstrated ability to obtain information about cancer's genotype and phenotype; this is without invasive procedures or surgery. Further advances in these areas of experimental imaging hold promise to enable future clinical advances in detection and therapy of pancreatic cancer.

Dynamic contrast-enhanced magnetic resonance imaging for pancreatic ductal adenocarcinoma at 3.0-T magnetic resonance: correlation with histopathology

PURPOSE

The aim of this study was to discuss the correlation of quantitative dynamic contrast-enhanced magnetic resonance imaging (QDCE-MRI) at 3.0-T magnetic resonance and histopathology for pancreatic ductal adenocarcinoma (PDA).

METHODS

Twenty-three patients with histopathologically proven PDA were included in this study after 75 cases of suspected pancreatic tumors had been performed by QDCE-MRI. The quantitative kinetic parameters analyzed by 2-compartment and 3-compartment models were calculated automatically, which included the volume transfer constant of the contrast agent, the rate constant (Kep), the volume as a percentage of the extravascular extracellular leakage space, the time of arrival of contrast agent, the time of peaking of contrast agent, the maximum slope of signal intensity ascent, and the contrast enhancement ratio. According to magnetic resonance images, tissue section were selected and stained for evaluating tumor differentiation, tumor fibrosis, tumor microvessel density, the expression of tumor vascular endothelial growth factor (VEGF) and Ki67. Subsequently, the relationship between the parameters of QDCE-MRI and histopathology of PDA was analyzed.

RESULTS

The tumor Kep and extravascular extracellular leakage space showed a statistically significant correlation with tumor fibrosis; the tumor volume transfer constant of the contrast agent 2-compartment showed a statistically significant correlation with the expressions of tumor VEGF; and the tumor Kep, maximum slope of signal intensity ascent, and contrast enhancement ratio showed a statistically significant correlation with the expression of tumor Ki67.

CONCLUSIONS

The parameters of QDCE-MRI of PDA can be used to evaluate the degrees of tumor fibrosis and the expressions of VEGF and Ki67.