Dynamic contrast-enhanced MRI of gastric cancer: Correlation of the perfusion parameters with pathological prognostic factors

Extracellular volume fraction determined by equilibrium contrast-enhanced computed tomography: correlation with histopathological findings in gastric cancer

PURPOSE

To assess the relationship between histopathological features of gastric cancer and the extracellular volume fraction (ECV) measured by preoperative equilibrium contrast-enhanced computed tomography (CECT).

MATERIALS AND METHODS

The study group consisted of 66 patients with surgically resected gastric adenocarcinoma who underwent preoperative multiphasic CECT. Tumor ECVs were calculated using region-of-interest measurements within the gastric cancer and aorta of each case on unenhanced and equilibrium-phase images. The relationship between the mean ECV values and clinicopathological parameters was examined by univariate analysis. Parameters showing a significant difference in the former test were further tested by linear regression and receiver operating characteristic (ROC) curve analyses.

RESULTS

In the univariate analysis, the values of venous invasion (p = 0.0487) and tumor infiltration (INF) pattern (p < 0.0001) were significantly correlated with the tumor ECV. INF was significantly correlated (β = 0.57, p < 0.0001) in the linear regression analysis. The tumor ECV showed better diagnostic accuracy for predicting INF (INFa/b vs INFc), and the area under the ROC curve value was 0.89.

CONCLUSION

Tumor ECV determined by equilibrium CECT is significantly correlated with the pathological INF of gastric cancer.

Multiparametric MRI-based radiomics nomogram for early prediction of pathological response to neoadjuvant chemotherapy in locally advanced gastric cancer

OBJECTIVES

To build and validate a multi-parametric MRI (mpMRI)-based radiomics nomogram for early prediction of treatment response to neoadjuvant chemotherapy (NAC) in locally advanced gastric cancer.

METHODS

Baseline MRI were retrospectively enrolled from 141 patients with gastric adenocarcinoma who received NAC followed by radical gastrectomy. According to pathologic response of tumor regression grading (TRG), patients were labeled as responders (TRG = 0 + 1) and non-responders (TRG = 2 + 3) and further divided into a training (n = 85) and validation dataset (n = 56). Radiomics score (Radscore) were built from T2WI, ADC, and venous phase of dynamic-contrasted-enhanced MR imaging. Clinical information, laboratory indicators, MRI parameters, and follow-up data were also recorded. According to multivariable regression analysis, an mpMRI radiomics nomogram was built and its predictive ability was evaluated by ROC analysis. Decision curve analysis was applied to evaluate the clinical usefulness. Kaplan-Meier survival curves based on the nomogram were used to estimate the progression-free survival (PFS) and overall survival (OS) in the validation dataset.

RESULTS

Both single sequence-based Radscores and mpMRI radiomics nomogram were associated with pathologic response (p < 0.001). The nomogram achieved the highest diagnostic ability with area under ROC curve of 0.844 (95% CI, 0.749-0.914) and 0.820 (95% CI, 0.695-0.910) in the training and validation datasets. The hazard ratio of the nomogram for PFS and OS prediction was 2.597 (95% CI: 1.046-6.451, log-rank p = 0.023) and 2.570 (95% CI: 1.166-5.666, log-rank p = 0.011).

CONCLUSIONS

The mpMRI-based radiomics nomogram showed preferable performance in predicting pathologic response to NAC in LAGC.

KEY POINTS

• This study investigated the value of multi-parametric MRI-based radiomics in predicting pathologic response to neoadjuvant chemotherapy in locally advanced gastric cancer. • The nomogram incorporating T2WI Radscore, ADC Radscore, and DCE Radscore as well as Borrmann classification outperformed the single sequence-based Radscore. • The nomogram also exhibited a promising prognostic ability for patient survival and enriched radiomics studies in gastric cancer.

Gastric Cancer Angiogenesis Assessment by Dynamic Contrast Harmonic Imaging Endoscopic Ultrasound (CHI-EUS) and Immunohistochemical Analysis-A Feasibility Study

Tumor vascular perfusion pattern in gastric cancer (GC) may be an important prognostic factor with therapeutic implications. Non-invasive methods such as dynamic contrast harmonic imaging endoscopic ultrasound (CHI-EUS) may provide details about tumor perfusion and could also lay out another perspective for angiogenesis assessment. Methods: We included 34 patients with GC, adenocarcinoma, with CHI-EUS examinations that were performed before any treatment decision. We analyzed eighty video sequences with a dedicated software for quantitative analysis of the vascular patterns of specific regions of interest (ROI). As a result, time-intensity curve (TIC) along with other derived parameters were automatically generated: peak enhancement (PE), rise time (RT), time to peak (TTP), wash-in perfusion index (WiPI), ROI area, and others. We performed CD105 and CD31 immunostaining to calculate the vascular diameter (vd) and the microvascular density (MVD), and the results were compared with CHI-EUS parameters. Results: High statistical correlations (p < 0.05) were observed between TIC analysis parameters MVD and vd CD31. Strong correlations were also found between tumor grade and 7 CHI-EUS parameters, p < 0.005. Conclusions: GC angiogenesis assessment by CHI-EUS is feasible and may be considered for future studies based on TIC analysis.

Magnetic Fields and Cancer: Epidemiology, Cellular Biology, and Theranostics

Humans are exposed to a complex mix of man-made electric and magnetic fields (MFs) at many different frequencies, at home and at work. Epidemiological studies indicate that there is a positive relationship between residential/domestic and occupational exposure to extremely low frequency electromagnetic fields and some types of cancer, although some other studies indicate no relationship. In this review, after an introduction on the MF definition and a description of natural/anthropogenic sources, the epidemiology of residential/domestic and occupational exposure to MFs and cancer is reviewed, with reference to leukemia, brain, and breast cancer. The in vivo and in vitro effects of MFs on cancer are reviewed considering both human and animal cells, with particular reference to the involvement of reactive oxygen species (ROS). MF application on cancer diagnostic and therapy (theranostic) are also reviewed by describing the use of different magnetic resonance imaging (MRI) applications for the detection of several cancers. Finally, the use of magnetic nanoparticles is described in terms of treatment of cancer by nanomedical applications for the precise delivery of anticancer drugs, nanosurgery by magnetomechanic methods, and selective killing of cancer cells by magnetic hyperthermia. The supplementary tables provide quantitative data and methodologies in epidemiological and cell biology studies. Although scientists do not generally agree that there is a cause-effect relationship between exposure to MF and cancer, MFs might not be the direct cause of cancer but may contribute to produce ROS and generate oxidative stress, which could trigger or enhance the expression of oncogenes.

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.

Predicting T and N Staging of Resectable Gastric Cancer According to Whole Tumor Histogram Analysis About a Non-Cartesian k-Space Acquisition DCE-MRI: A Feasibility Study

Objective

To explore the feasibility of the whole tumor histogram analysis parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) based on stack-of stars (StarVIBE) to predict T and N staging of resectable gastric cancer (GC).

Methods

Eighty-seven patients confirmed as GC by histopathology were enrolled in this prospective study. DCE-MRI were performed before surgery, and quantitative DCE parameters (K^trans, K_ep, V_e) and histogram metrics (Skewness, Kurtosis and Entropy) were measured by Omni-Kinetics software. Intraclass correlation coefficient (ICC) testing was used to determine the consistency of K^trans, K_ep and V_e values and histogram metrics values between two radiologists using Bland–Altman analysis. The quantitative DCE parameters or histogram metrics values between T stage or N stage were compared using ANOVA or Kruskal–Wallis testing. Receiver operating characteristic (ROC) analyses was performed to find out the best parameters for identifying T and N staging.

Results

There was statistical difference in K^trans, K_ep, V_e and entropy to identify T staging (P=0.015, 0.033, <0.001, and 0.007, respectively), and in pairwise comparisons of V_e values showed statistically difference between T1+2 and T3 group (P<0.001), T1+2 and T4 group (P<0.001). There were statistical differences in V_e to identify N staging (P=0.041). In ROC analysis, V_e was the best parameter for identifying T staging (AUC: 0.788, the sensitivity and specificity was 0.929 and 0.578, respectively) and N staging (AUC: 0.590, the sensitivity and specificity was 0.714 and 0.899, respectively).

Conclusion

The whole tumor histogram analysis parameters derived from StarVIBE DCE-MRI may be able to quantitatively evaluate T and N staging of GC, so as to help clinical treatment decision optimization.

Value of quantitative dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging in predicting extramural venous invasion in locally advanced gastric cancer and prognostic significance

Background

Extramural venous invasion (EMVI) has been found to be related to poor prognosis in gastric cancer. Preoperative diagnosis of EMVI is challenging, as it can only be detected by surgical pathology. The present study aimed to investigate the value of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) in predicting EMVI preoperatively, and to determine the relationship between prediction results and prognosis in patients with locally advanced gastric cancer (LAGC).

Methods

Between January, 2015, and June, 2017, 79 LAGC patients underwent MRI preoperatively were enrolled in this study. Pathological EMVI (pEMVI) was used as the gold standard for diagnosis. The differences in quantitative DCE-MRI and DWI parameters between groups with different pEMVI status were analyzed. Multivariate logistic regression was used to build the combined prediction model for pEMVI with statistically significant quantitative parameters. The performance of the model for predicting pEMVI was evaluated using receiver operating characteristic (ROC) analysis. Patients were grouped based on MRI-predicted EMVI (mrEMVI). Kaplan-Meier analysis was used to investigate the relationship between mrEMVI and 2-year recurrence-free survival (RFS).

Results

Of the 79 LAGC patients who underwent MRI, 29 were pEMVI positive and 50 were pEMVI negative. Among the patients' clinical and pathological characteristics, only postoperative staging showed a significant difference between the 2 groups (P=0.015). The pEMVI-positive group had higher volume transfer constant (K^trans) and rate constant (k_ep), and lower apparent diffusion coefficient (ADC) values than the negative group (0.189 vs. 0.082 min^-1, 0.687 vs. 0.475 min^-1, and 1.230×10^-3 vs. 1.463×10^-3 mm²/s, respectively; P<0.05). Quantitative parameters, K^trans and k_ep, and ADC values, were independently associated with pEMVI which odds ratio values were 3.66, 2.65, and 0.30 (P<0.05), respectively, using multivariate logistic regression. ROC analysis showed that the area under the curve, sensitivity, specificity, positive predictive value, and negative predictive value in predicting pEMVI using combined K^trans, k_ep, and ADC values were 0.879, 72.4%, 96%, 91.3%, and 85.7%, respectively. A total of 23 cases were considered to be mrEMVI positive, and 56 cases were considered to be mrEMVI negative, according to the predictive results. The median RFS of the mrEMVI-positive group was significant lower than the negative group (21.7 vs. 31.2 months), and the 2-year RFS rate in the mrEMVI-positive group was significantly lower than that of the negative group (43.6% vs. 72.5%, P=0.010).

Conclusions

The quantitative DCE-MRI parameters, K^trans and k_ep, and DWI parameter, ADC, are independent predictors of pEMVI in LAGC; mrEMVI was confirmed to be a poor prognostic predictor for RFS.

Dynamic contrast-enhanced MRI differentiates hepatocellular carcinoma from hepatic metastasis of rectal cancer by extracting pharmacokinetic parameters and radiomic features

The aim of the present study was to explore how dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may differentiate hepatocellular carcinoma (HCC) from hepatic metastasis of rectal cancer (HMRC) by extracting pharmacokinetic parameters and radiomic features. A total of 75 patients, including 41 cases with HCC and 34 cases with HMRC, underwent DCE-MRI examination. Dual-input two-compartment extended Tofts tracer kinetic model attached to a specialized image post-processing software package from OmniKinetics; GE Healthcare was used to calculate the values of the pharmacokinetic parameters and radiomic features, which were extracted from the lesions at the same region of interest. These values were evaluated using Student's t-test and receiver operating characteristic curves, and discriminant models were built to differentiate between HCC and HRMC. The results identified statistically significant differences in the values of the pharmacokinetic parameters hepatic perfusion index (HPI), endothelial transfer constant (K^trans), initial area under the gadolinium concentration curve during the first 60 sec (IAUC) between the HCC and HRMC groups. In addition, statistically significant differences in 17 radiomic features were observed between the two groups (P<0.05). The areas under the receiver operating characteristic (ROC) curves of the pharmacokinetic parameters K^trans, IAUC and HPI were 0.73, 0.77 and 0.67, respectively. The range of the areas under the ROC curves of the 17 radiomic features with statistical differences was 0.63-0.79. In addition, when pharmacokinetic parameters and radiomic features were incorporated, the area under the ROC curve was 0.86. The accuracy of Fisher's discriminant analysis model based on radiomic features was 89.3%, and the leave-one-out cross-validation accuracy was 80.0%. In conclusion, DCE-MRI was demonstrated to be useful in the differential diagnosis of HCC and HMRC by extracting pharmacokinetic parameters and radiomic features, and incorporation of the two paths improved the diagnostic efficacy. A discriminant model based on radiomic features further enhanced the identification of HCC and HMRC.

Diffusion kurtosis imaging in head and neck cancer: A correlation study with dynamic contrast enhanced MRI

PURPOSE

To investigate the biophysical meaning of Diffusion Kurtosis Imaging (DKI) parameters via correlations with the perfusion parameters obtained from a long Dynamic Contrast Enhanced MRI scan, in head and neck (HN) cancer.

METHODS

Twenty two patients with newly diagnosed HN tumor were included in the present retrospective study. Some patients had multiple lesions, therefore a total of 26 lesions were analyzed. DKI was acquired using 5b values at 0, 500, 1000,1500 and 2000 s/mm². DCE-MRI was obtained with 130 dynamic volumes, with a temporal resolution of 5 s, to achieve a long scan time (>10 min). The apparent diffusion coefficient D_app and apparent diffusional kurtosis K_app were calculated voxel-by-voxel, removing the point at b value = 0 to eliminate possible perfusion effects on the parameter estimations. The transfer constants K^trans and K_ep, v_e, and the histogram-based entropy (En) and interquartile range (IQR) of each DCE-MRI parameter were quantified. Correlations between all variables were investigated by the Spearman's Rho correlation test.

RESULTS

Moderate relationships emerged between D_app and K_ep (Rho =  - 0.510, p = 0.009), and between D_app and v_e (Rho = 0.418, p = 0.038). En(K_ep) was significantly related to K_app (Rho = 0.407, p = 0.043), while IQR(K_ep) showed an inverse association with D_app (Rho = -0.422, p = 0.035).

CONCLUSIONS

A weak to intermediate correlation was found between DKI parameters and both K_ep and v_e. The kurtosis was associated to the intratumoral heterogeneity and complexity of the capillary permeability, expressed by En(K_ep).

Prognostic Value of the Pretreatment Primary Lesion Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Nasopharyngeal Carcinoma

RATIONALE AND OBJECTIVES

Early identifying the long-term outcome of chemoradiotherapy is helpful for personalized treatment in nasopharyngeal carcinoma (NPC). This study aimed to investigate the prognostic significance of pretreatment quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for NPC.

MATERIALS AND METHODS

The relationships between the prognosis and pretreatment quantitative DCE-MRI (K^trans, K_ep, V_e, and f_pv) values of the primary tumors were analyzed in 134 NPC patients who received chemoradiotherapy. Kaplan-Meier analysis was performed to calculate the local-regional relapse-free survival (LRRFS), local relapse-free survival (LRFS), regional relapse-free survival, distant metastasis-free survival (DMFS), progression-free survival, and overall survival rates. Cox proportional hazards model was used to explore the independent predictors for prognosis.

RESULTS

The local-failure group had significantly higher V_e (p = 0.033) and f_pv values (p = 0.005) than the non-local-failure group. The V_e-high group showed significantly lower LRRFS (p = 0.015) , LRFS (p = 0.013) , DMFS (p = 0.027) and progression-free survival (p = 0.035) rates than the V_e-low group. The f_pv-high group exhibited significantly lower LRRFS (p = 0.004) and LRFS (p = 0.005) rates than the f_pv-low group. V_e was the independent predictor for LRRFS (p = 0.008), LRFS (p = 0.007), DMFS (p = 0.041), and overall survival (p = 0.022). f_pv was the independent indicator for LRRFS (p = 0.003) and LRFS (p = 0.001).

CONCLUSION

Baseline quantitative DCE-MRI may be valuable in predicting the prognosis for NPC.

Gastric cancer and image-derived quantitative parameters: Part 2-a critical review of DCE-MRI and 18F-FDG PET/CT findings

Abstract

There is yet no consensus on the application of functional imaging and qualitative image interpretation in the management of gastric cancer. In this second part, we will discuss the role of image-derived quantitative parameters from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) in gastric cancer, as both techniques have been shown to be promising and useful tools in the clinical decision making of this disease. We will focus on different aspects including aggressiveness assessment, staging and Lauren type discrimination, prognosis prediction and response evaluation. Although both the number of articles and the patients enrolled in the studies were rather small, there is evidence that quantitative parameters from DCE-MRI such as K^trans, V_e, K_ep and AUC could be promising image-derived surrogate parameters for the management of gastric cancer. Data from ¹⁸F-FDG PET/CT studies showed that standardised uptake value (SUV) is significantly associated with the aggressiveness, treatment response and prognosis of this disease. Along with the results from diffusion-weighted MRI and contrast-enhanced multidetector computed tomography presented in Part 1 of this critical review, there are additional image-derived quantitative parameters from DCE-MRI and ¹⁸F-FDG PET/CT that hold promise as effective tools in the diagnostic pathway of gastric cancer.

Key Points

• Quantitative analysis from DCE-MRI and¹⁸F-FDG PET/CT allows the extrapolation of multiple image-derived parameters.

• Data from DCE-MRI (K^trans, V_e, K_ep and AUC) and ¹⁸F-FDG PET/CT (SUV) are non-invasive, quantitative image-derived parameters that hold promise in the evaluation of the aggressiveness, treatment response and prognosis of gastric cancer.

Dynamic Contrast-Enhanced Ultrasound of Gastric Cancer: Correlation with Perfusion CT and Histopathology

Objective

To assess the relationship between contrast-enhanced ultrasound (CEUS) parameters and perfusion CT (PCT) parameters of gastric cancers and their correlation with histologic features.

Materials and Methods

This prospective study was approved by our Institutional Review Board. We included 43 patients with pathologically-proven gastric cancers undergoing CEUS using SonoVue® (Bracco) and PCT on the same day. Correlation between the CEUS parameters (peak intensity [PI], area under the curve [AUC], rise time [RT] from 10% to 90% of PI, time to peak [TTP_US], and mean transit time [MTT_US]) and PCT parameters (blood flow, blood volume, TTP_CT, MTT_CT, and permeability surface product) of gastric cancers were analyzed using Spearman's rank correlation test. In cases of surgical resection, the CEUS and PCT parameters were compared according to histologic features using Mann-Whitney test.

Results

CEUS studies were of diagnostic quality in 88.4% (38/43) of patients. Among the CEUS parameters of gastric cancers, RT and TTP_US showed significant positive correlations with TTP_CT (rho = 0.327 and 0.374, p = 0.045 and 0.021, respectively); PI and AUC were significantly higher in well-differentiated or moderately-differentiated tumors (n = 4) than poorly-differentiated tumors (n = 18) (p = 0.026 and 0.033, respectively), whereas MTT_CT showed significant differences according to histologic types (poorly cohesive carcinoma [PCC] vs. non-PCC), T-staging (≤ T2 vs. ≥ T3), N-staging (N0 vs. N-positive), and epidermal growth factor receptor expression (≤ faint vs. ≥ moderate staining) (p values < 0.05).

Conclusion

In patients with gastric cancers, CEUS is technically feasible for the quantification of tumor perfusion and may provide correlative and complementary information to that of PCT, which may allow prediction of histologic features.

Imaging strategies in the management of gastric cancer: current role and future potential of MRI

Accurate preoperative staging of gastric cancer and the assessment of tumor response to neoadjuvant treatment is of importance for treatment and prognosis. Current imaging techniques, mainly endoscopic ultrasonography (EUS), computed tomography (CT) and ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET), have their limitations. Historically, the role of magnetic resonance imaging (MRI) in gastric cancer has been limited, but with the continuous technical improvements, MRI has become a more potent imaging technique for gastrointestinal malignancies. The accuracy of MRI for T- and N-staging of gastric cancer is similar to EUS and CT, making MRI a suitable alternative to other imaging strategies. There is limited evidence on the performance of MRI for M-staging of gastric cancer specifically, but MRI is widely used for diagnosing liver metastases and shows potential for diagnosing peritoneal seeding. Recent pilot studies showed that treatment response assessment as well as detection of lymph node metastases and systemic disease might benefit from functional MRI (e.g. diffusion weighted imaging and dynamic contrast enhancement). Regarding treatment guidance, additional value of MRI might be expected from its role in better defining clinical target volumes and setup verification with MR-guided radiation treatment.

Correlations of TNM staging and lymph node metastasis of gastric cancer with MRI features and VEGF expression

OBJECTIVE

To investigate the correlations of expression of vascular endothelial growth factor (VEGF) in gastric cancer tissues of patients and magnetic resonance imaging (MRI) features with clinical tumor-node-metastasis (TNM) staging and lymph node metastasis, and to analyze the diagnostic value of MRI features for preoperative TNM staging and lymph node metastasis of patients with gastric cancer, and the roles of VEGF in tumor development and metastasis.

METHODS

A total of 120 gastric cancer patients treated in our hospital from May 2015 to July 2017 were selected as objects of study. The VEGF protein expressions in gastric cancer tissues of patients with different TNM staging and lymph node metastasis degrees were detected using immunohistochemical method, and the correlations of VEGF protein expression with TNM staging and lymph node metastasis were analyzed. Before operation, MRI was used to predict TNM staging and lymph node metastasis of all patients, and prediction results were compared with postoperative pathological diagnosis results. At the same time, the differences in lymph node apparent diffusion coefficient (ADC), long diameter and short diameter, relative ADC of primary lesion (rADCp) and relative ADC of muscle (rADCm) were compared and analyzed between lymph node metastasis group and non-lymph node metastasis group.

RESULTS

The VEGF expression in patients with stage-N3 gastric cancer was about 7 times that in patients with stage-N0 gastric cancer, and it was increased with the increased degree of lymph node metastasis (p< 0.01). The VEGF expression in patients with distant metastasis of tumor cells was significantly higher than that in patients without distant metastasis (p< 0.01). The expression of VEGF in stage-T4 gastric cancer was about 10 times that in stage-Tis cancer, and the larger the infiltration depth of tumor cells was, the higher the expression level of VEGF would be (p< 0.01). The VEGF expression in gastric cancer tissues was positively correlated with the infiltration depth, lymph node metastasis and distant metastasis of tumor cells. Moreover, the prediction results of MRI for TNM staging and lymph node metastasis before operation were compared with postoperative pathological results, and it was found that there was better consistency (Kappa = 0.739). ADC, rADCp and rADCm in gastric cancer patients without lymph node metastasis were significantly higher than those in patients with lymph node metastasis, but the short diameter and long diameter were obviously shorter than those in patients with lymph node metastasis, and the differences were statistically significant (p< 0.05).

CONCLUSION

The VEGF protein expression in gastric cancer tissues is positively correlated with TNM staging and lymph node metastasis in patients. The preoperative prediction results of MRI are well consistent with postoperative pathological results, and MRI features are correlated with lymph node metastasis in patients, which has an important guiding significance for the diagnosis and treatment of gastric cancer.

Grading of pancreatic neuroendocrine neoplasms using pharmacokinetic parameters derived from dynamic contrast-enhanced MRI

The present study aimed to evaluate the diagnostic efficacy of pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in prospective evaluation of pancreatic neuroendocrine neoplasms (pNENs) grading. A total of 25 histologically proven patients with pNENs (30 lesions in total) who underwent DCE-MRI were enrolled. Lesions were divided into G1, G2 neuroendocrine tumor (NET) and G3 NET/neuroendocrine carcinoma (NEC) groups based on their histological findings according to 2017 World Health Organization Neuroendocrine Tumor Classification Guideline. In addition, the same numbers of tumor-free regions were selected using as normal control group. For each group, pharmacokinetic DCE parameters: volume transfer constant (K^trans); contrast transfer rate constant (k_ep); extravascular extracellular space volume fraction (v_e); and plasma volume fraction (v_p) were calculated with Extended Tofts Linear model. Receiver operator characteristics analysis was conducted to assess the diagnostic efficacy of these parameters in pNENs grading. There were significant differences of K^trans, k_ep, v_e and v_p between tumor-free areas and G1, G2 NET (P<0.001). The K^trans and k_ep of G1 NET were significantly lower compared with those of G2 ones (P<0.005). The area under the curve of K^trans and k_ep in differentiating G2 from G1 NET were 0.767 and 0.846, respectively. When K^trans was >0.667 and k_ep >1.644, the sensitivity of diagnosing G2 NET was the lowest (53.85%), but the specificity was the highest (93.75%). When K^trans was >0.667 or k_ep >1.644, the sensitivity of diagnosing G2 NET was 92.31%, but the specificity was 75.00%. Pharmacokinetic parameters of DCE-MRI, particularly the quantitative values of K^trans and k_ep, are helpful for differentiating G2 NET from G1 ones.

Feasibility of free-breathing dynamic contrast-enhanced MRI of gastric cancer using a golden-angle radial stack-of-stars VIBE sequence: comparison with the conventional contrast-enhanced breath-hold 3D VIBE sequence

OBJECTIVES

To investigate the feasibility and diagnostic value of free-breathing, radial, stack-of-stars three-dimensional (3D) gradient echo (GRE) sequence ("golden angle") on dynamic contrast-enhanced (DCE) MRI of gastric cancer.

METHODS

Forty-three gastric cancer patients were divided into cooperative and uncooperative groups. Respiratory fluctuation was observed using an abdominal respiratory gating sensor. Those who breath-held for more than 15 s were placed in the cooperative group and the remainder in the uncooperative group. The 3-T MRI scanning protocol included 3D GRE and conventional breath-hold VIBE (volume-interpolated breath-hold examination) sequences, comparing images quantitatively and qualitatively. DCE-MRI parameters from VIBE images of normal gastric wall and malignant lesions were compared.

RESULTS

For uncooperative patients, 3D GRE scored higher qualitatively, and had higher SNRs (signal-to-noise ratios) and CNRs (contrast-to-noise ratios) than conventional VIBE quantitatively. Though 3D GRE images scored lower in qualitative parameters compared with conventional VIBE for cooperative patients, it provided images with fewer artefacts. DCE parameters differed significantly between normal gastric wall and lesions, with higher Ve (extracellular volume) and lower Kep (reflux constant) in gastric cancer.

CONCLUSIONS

The free-breathing, golden-angle, radial stack-of-stars 3D GRE technique is feasible for DCE-MRI of gastric cancer. Dynamic enhanced images can be used for quantitative analysis of this malignancy.

KEY POINTS

• Golden-angle radial stack-of-stars VIBE aids gastric cancer MRI diagnosis. • The 3D GRE technique is suitable for patients unable to suspend respiration. • Method scored higher in the qualitative evaluation for uncooperative patients. • The technique produced images with fewer artefacts than conventional VIBE sequence. • Dynamic enhanced images can be used for quantitative analysis of gastric cancer.

Association between spectral computed tomography images and clinicopathological features in advanced gastric adenocarcinoma

To investigate the role of spectral computed tomography (CT)-generated iodine concentration (IC) in the evaluation of clinicopathological features of advanced gastric adenocarcinoma (AGC), 42 patients who underwent abdominal enhanced CT with spectral imaging mode were selected for the present study. The IC of the primary lesion in the arterial phase (IC_AP) and portal venous phase (IC_VP) was measured and the IC of the aorta was used for a normalized iodine concentration (nIC). Micro-vessel density (MVD) and lymphatic vessel density (LVD) were detected using immunohistochemical assays against cluster of differentiation 34 and D2-40, respectively. Other clinicopathological characteristics were also documented. The IC parameters were revealed to be significantly increased in the high-MVD group, particularly for the nIC_VP (P=0.002). Additionally, the nIC_AP revealed a significant difference (P=0.041) between the high- and low-LVD group. The nIC_AP and nIC_VP were increased in the poorly differentiated group compared with the moderately differentiated group (P=0.040 and P=0.011, respectively). The ICs and MVD demonstrated a statistically significant positive linear correlation. nIC_VP was able to be used to discriminate between the moderately and poorly differentiated carcinomas, with an area under the receiver operating characteristic curve of 0.759. However, IC demonstrated no correlation with serosal involvement, lymph node metastasis, LVD, and nodular or metastatic tumors. The results of the present study suggest that the nIC_VP value may serve as a non-invasive marker for the angiogenesis of, and the differentiations between, patients with AGC.

Diffusion-weighted magnetic resonance imaging in the depiction of gastric cancer: initial experience

The aim of the study was to explore the feasibility of diffusion-weighted magnetic resonance imaging (DW-MRI) in the depiction of gastric cancer and to investigate the signal characteristics and apparent diffusion coefficient (ADC) of gastric cancer. An institutional review board-approved protocol was developed for this prospective study. DW-MRI was performed on 101 patients with gastric cancer that was detected by gastroscopy biopsy. The optimal number of excitations (NEX) for DW-MRI was determined, and the signal characteristics of gastric cancer on DW-MRI were analyzed. The ADC of gastric cancer was measured by two experienced radiologists independently, and the reproducibility of measurement was investigated by the Bland-Altman analysis. When DW-MRI was used with four NEXs, areas of gastric cancer showed a good contrast and contrast-to-noise ratio. Four kinds of signal characteristics of gastric cancer were observed on DW-MRI: uniformly high signal, inner high signal, and outer low signal (two-layer type), high-low-high signal (three-layer sandwich type), and mixed type. The mean ADC of gastric cancer measured by two observers was (1.18 ± 0.29) × 10(-3) mm(2)/s and (1.20 ± 0.31) × 10(-3) mm(2)/s respectively, which showed good agreement with Bland-Altman analysis (95% limits of agreement: -0.16 to +0.19 × 10(-3) mm(2)/s). Gastric cancers have various signal characteristics on DW-MRI and the reproducibility of ADC measurement is satisfactory. DW-MRI is helpful in the depiction of gastric cancer.