Chemotherapy response evaluation in a mouse model of gastric cancer using intravoxel incoherent motion diffusion-weighted MRI and histopathology

The value of intravoxel incoherent motion diffusion-weighted imaging in predicting perineural invasion for resectable gastric cancer: a prospective study

AIM

To investigate the potential of intravoxel incoherent motion (IVIM) diffusion-weighted imaging to predict perineural invasion (PNI) preoperatively in resectable gastric cancer (GC).

MATERIALS AND METHODS

This study prospectively recruited 85 surgically resected GC patients (58 men, 27 women) aged 60.87 ± 10.17 (39-81) years, who underwent IVIM sequence within 1 week before surgery. According to histopathological PNI diagnoses, patients were divided into PNI positive and negative groups. Conventional apparent diffusion coefficient (ADC) and the IVIM parameters, including true diffusion coefficient (D), pseudodiffusion coefficient (D∗), and pseudodiffusion fraction (f), were compared between the two groups. Morphological MRI features were also analysed. Multivariate logistic regression was used to screen independent predictors of PNI. Receiver-operating characteristic curve analyses were preformed to evaluate the efficacy. Spearman's correlation test was performed to analyse the relationship between MRI parameters and PNI.

RESULTS

Tumour thickness and f in PNI-positive group were higher, whereas the ADC, D were lower than those in PNI-negative group (p<0.05). These four parameters correlated with PNI (p<0.05). The D, f, and tumour thickness were independent predictors of PNI. The area under the curve of ADC, D, f, thickness, and the combined parameter (D + f + thickness) were 0.648, 0.745, 0.698, 0.725, and 0.869, respectively. The combined parameter demonstrated higher efficacy than any other parameters (p<0.05).

CONCLUSION

The ADC, D, and f can effectively distinguish PNI status in GC. The D, f, and thickness were independent predictors of PNI.

Toward peripheral nerve mechanical characterization using Brillouin imaging spectroscopy

Significance

Peripheral nerves are viscoelastic tissues with unique elastic characteristics. Imaging of peripheral nerve elasticity is important in medicine, particularly in the context of nerve injury and repair. Elasticity imaging techniques provide information about the mechanical properties of peripheral nerves, which can be useful in identifying areas of nerve damage or compression, as well as assessing the success of nerve repair procedures.

Aim

We aim to assess the feasibility of Brillouin microspectroscopy for peripheral nerve imaging of elasticity, with the ultimate goal of developing a new diagnostic tool for peripheral nerve injury in vivo.

Approach

Viscoelastic properties of the peripheral nerve were evaluated with Brillouin imaging spectroscopy.

Results

An external stress exerted on the fixed nerve resulted in a Brillouin shift. Quantification of the shift enabled correlation of the Brillouin parameters with nerve elastic properties.

Conclusions

Brillouin microscopy provides sufficient sensitivity to assess viscoelastic properties of peripheral nerves.

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.

Dynamic Contrast-Enhanced Ultrasound Modeling of an Analog to Pseudo-Diffusivity in Intravoxel Incoherent Motion Magnetic Resonance Imaging

Tumor perfusion and vascular properties are important determinants of cancer response to therapy and thus various approaches for imaging perfusion are being explored. In particular, Intravoxel Incoherent Motion (IVIM) MRI has been actively researched as an alternative to Dynamic-Contrast-Enhanced (DCE) CT and DCE-MRI as it offers non-ionizing, non-contrast-based perfusion imaging. However, for repetitive treatment assessment in a short time period, high cost, limited access, and inability to scan at the bedside remain disadvantages of IVIM MRI. We propose an analysis framework that may enable 3D DCE Ultrasound (DCE-US) - low cost, bedside imaging with excellent safety record - as an alternative modality to IVIM MRI for the generation of DCE-US based pseudo-diffusivity maps in acoustically accessible anatomy and tumors. Modelling intravascular contrast propagation as a convective-diffusive process, we reconstruct parametric maps of pseudo-diffusivity by solving a large-scale fully coupled inverse problem without any assumptions regarding local constancy of the reconstructed parameters. In a mouse tumor model, we demonstrate that the 3D DCE-US pseudo-diffusivity is repeatable, sensitive to treatment with an antiangiogenic agent, and moderately correlated to histological measures of perfusion and angiogenesis.

Dynamic contrast-enhanced and diffusion-weighted MR imaging in early prediction of pathologic response to neoadjuvant chemotherapy in locally advanced gastric cancer

PURPOSE

To investigate the efficacy of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the early prediction of the pathologic response to neoadjuvant chemotherapy (NAC) in patients with locally advanced gastric cancer (LAGC).

METHODS

Fifty patients with LAGC who were treated with NAC followed by radical gastrectomy were enrolled. Uncontrasted and DCE-MRI were performed within 1 week before NAC. According to tumor regression grading (TRG), patients were labeled as responders (TRG = 0 + 1) and non-responders (TRG = 2 + 3). Apparent diffusion coefficients (ADC) and DCE-MRI kinetics (K^trans, V_e, and K_ep) were compared between the two groups. Logistic regression analysis was performed to screen independent factors to predict the NAC efficacy. The relationship between MRI parameters and TRG was studied by Spearman's correlation analysis. Receiver-operating characteristic curve analyses were applied to evaluate the efficacy.

RESULTS

ADC, K^trans, and K_ep values were higher in responders than in non-responders (p < 0.05) and correlated with TRG (p < 0.05). The ADC and K_ep values were independent markers for predicting TRG. The area under the curve, sensitivities, specificities of ADC, K^trans, K_ep, and ADC + K_ep were 0.813, 0.699, 0.709, 0.886;73.64%, 65.54%, 63.21%, 70.37%; 86.47%, 54.97%, 79.47%, 95.65%; respectively. ADC + K_ep demonstrated a higher efficacy than K^trans and K_ep (p = 0.012, 0.011), but without improvement compared with ADC (p > 0.05).

CONCLUSION

Both DWI and DCE-MRI can effectively predict the pathologic response to NAC in LAGC. A combination of ADC and K_ep increased the efficacy, and ADC is the most valuable imaging parameter.

The Value of Whole-Tumor Histogram and Texture Analysis Using Intravoxel Incoherent Motion in Differentiating Pathologic Subtypes of Locally Advanced Gastric Cancer

Purpose

To determine if whole-tumor histogram and texture analyses using intravoxel incoherent motion (IVIM) parameters values could differentiate the pathologic characteristics of locally advanced gastric cancer.

Methods

Eighty patients with histologically confirmed locally advanced gastric cancer who received surgery in our institution were retrospectively enrolled into our study between April 2017 and December 2018. Patients were excluded if they had lesions with the smallest diameter < 5 mm and severe image artifacts. MR scanning included IVIM sequences (9 b values, 0, 20, 40, 60, 100, 150,200, 500, and 800 s/mm²) used in all patients before treatment. Whole tumors were segmented by manually drawing the lesion contours on each slice of the diffusion-weighted imaging (DWI) images (with b=800). Histogram and texture metrics for IVIM parameters values and apparent diffusion coefficient (ADC) values were measured based on whole-tumor volume analyses. Then, all 24 extracted metrics were compared between well, moderately, and poorly differentiated tumors, and between different Lauren classifications, signet-ring cell carcinomas, and other poorly cohesive carcinomas using univariate analyses. Multivariate logistic analyses and multicollinear tests were used to identify independent influencing factors from the significant variables of the univariate analyses to distinguish tumor differentiation and Lauren classifications. ROC curve analyses were performed to evaluate the diagnostic performance of these independent influencing factors for determining tumor differentiation and Lauren classifications and identifying signet-ring cell carcinomas. The interobserver agreement was also conducted between the two observers for image quality evaluations and parameter metric measurements.

Results

For diagnosing tumor differentiation, the ADC_median, pure diffusion coefficient median (Dslow_median), and pure diffusion coefficient entropy (Dslow_entropy) showed the greatest AUCs: 0.937, 0.948, and 0.850, respectively, and no differences were found between the three metrics, P>0.05). The 95th percentile perfusion factor (FP _P95th) was the best metric to distinguish diffuse-type GCs vs. intestinal/mixed (AUC=0.896). The ROC curve to distinguish signet-ring cell carcinomas from other poorly cohesive carcinomas showed that the Dslow_median had AUC of 0.738. For interobserver reliability, image quality evaluations showed excellent agreement (interclass correlation coefficient [ICC]=0.85); metrics measurements of all parameters indicated good to excellent agreement (ICC=0.65-0.89), except for the Dfast metric, which showed moderate agreement (ICC=0.41-0.60).

Conclusions

The whole-tumor histogram and texture analyses of the IVIM parameters based on the biexponential model provided a non-invasive method to discriminate pathologic tumor subtypes preoperatively in patients with locally advanced gastric cancer. The metric FP _P95th derived from IVIM performed better in determining Lauren classifications than the mono-exponential model.

Precise Targeting Therapy of Orthotopic Gastric Carcinoma by siRNA and Chemotherapeutic Drug Codelivered in pH-Sensitive Nano Platform

Gastric cancer is one of the most common malignant tumors, which remains as an obstacle to human health. Nowadays, targeted nanoparticles to gastric tumor tissues, provide new strategy for improved therapy but still remain challenging. The major hurdle of targeted therapeutic nanoparticles comes from the limited enrichment and poor selectivity of therapeutic agents in in situ tumor. Herein, a pH-sensitive targeted nano platform coloaded As₂ O₃ and human epidermal growth factor receptor-2 (HER2)-siRNA (AH RNPs) is developed to achieve targeting therapy in orthotopic gastric carcinoma. AH RNPs can effectively prevent the degradation of siRNA and overcome the poor solubility of As₂ O₃ . In vitro studies show that AH RNPs could achieve synergistic inhibition of growth and metastasis on SGC7901 cells. Surprisingly, AH RNPs not only target gastric subcutaneous tumor, but also target in situ tumor, and express loaded genes in in situ tumor. Moreover, AH RNPs show excellent antitumor effect in orthotopic gastric tumor model and the anticancer mechanism is related about inhibiting the activation of ERK signal and downregulating the expression of cxc chemokine receptor 4 (CXCR4), HER2, MMP2, and MMP9 protein. This study provides a multi-functional vector for precise targeting therapy of gastric cancer, which may serve as a potential clinical application for future gastric cancer.

Apatinib inhibits the proliferation of gastric cancer cells via the AKT/GSK signaling pathway in vivo

Gastric cancer (GC) is the third leading cause of cancer-associated mortality globally. Although the diagnosis and therapeutic strategies for GC have improved, the prognosis for advanced gastric cancer (AGC) remains poor. Hence, the present study sought to design a zebrafish model established by microinjecting human MGC-803 GC cell line for studying personalized molecular-targeted cancer therapy. Apatinib, a novel molecular-targeted agent, was evaluated for its in vivo efficacy through a comparison among the control groups (no treatment) and subject groups (treatment). Newly formed vessel length and tumor volume were measured in all of the groups for further study. The length of newly formed vessels was obviously shortened after apatinib treatment in the zebrafish model established in this study. Meanwhile, apatinib exhibited the best antitumor growth effect with dose and time dependence by suppressing AKT/GSK3α/β signaling, which may be the mechanism underlying the profound antitumor clinical effect of apatinib. The data indicated that apatinib therapy exerts an anti-angiogenesis effect and it can be recommended as a proper antitumor growth therapy for GC patients. Additionally, zebrafish models could be designed as a potential practical tool to explore new anti-GC cancer drugs.

Application of Multiparametric Magnetic Resonance Imaging to Monitor the Early Antitumor Effect of CuS@GOD Nanoparticles in a 4 T1 Breast Cancer Xenograft Model

BACKGROUND

We have developed hybrid nanoparticles (NPs) by co-loading copper sulfide (CuS) NPs and glucose oxidase (GOD) (CuS@GOD NPs) to explore their antitumor properties.

PURPOSE

To investigate the feasibility of using multiparametric magnetic resonance imaging (MRI) including intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and R₂ * mapping to quantitatively assess the early antitumor effect of CuS@GOD NPs.

STUDY TYPE

Prospective.

ANIMAL MODEL

The orthotopic BALB/c mice 4 T1 breast cancer model. The 4 T1 xenografts in group 1 mice received normal saline, group 2 received CuS@GOD NPs, group 3 received CuS NPs plus laser, and group 4 received CuS@GOD NPs plus laser (n = 28 for each group).

FIELD STRENGTH/SEQUENCE

A 3.0 T/IVIM-DWI MRI single-shot echo-planar imaging, R₂ * mapping spoiled gradient recalled echo (SPGR) sequence, T2-weighted images (T2WI) and T1-weighted images (T1WI) fast spin echo (FSE) sequence.

ASSESSMENT

The IVIM-DWI and R₂ * mapping were performed before and after treatment at 0 hour, 0.5 hour, 1 hour, 2 hours, 4 hours, and 24 hours in four groups and the MRI parameters were obtained. Correlation analysis between the MRI parameters and histological analyses was conducted.

STATISTICAL TESTS

One-way ANOVA, Pearson's correlation analysis, two independent samples t test, intraclass correlation coefficient. P < 0.05 was considered to be statistically significant.

RESULTS

In group 4, the tumoral D value was significantly higher than that of group 2 at 24 hours (0.541 ± 0.065 vs. 0.492 ± 0.051). The f value of group 4 was significantly lower than that of groups 1 and 2 at 2 hours (10.83 ± 2.16 vs. 14.28 ± 1.86, 16.67 ± 3.53, respectively). The R₂ * value was significantly increased at 0 hour in group 4 compared to that of groups 1 and 2 (64.552 ± 4.663 vs. 42.441 ± 1.516, 43.165 ± 1.709, respectively). D, f, and R₂ * were correlated with the histological staining results (r = 0.695-0.970).

DATA CONCLUSION

The IVIM-DWI-derived D and f and R₂ * mapping-derived R₂ * could monitor early response to CuS@GOD NPs treatment in vivo.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Diffusion kurtosis imaging in the prediction of poor responses of locally advanced gastric cancer to neoadjuvant chemotherapy

PURPOSE

To assess the efficacy of diffusion kurtosis imaging (DKI) in the prediction of the treatment response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer (LAGC).

METHODS

A total of 31 LAGC patients were enrolled in this prospective study. All patients underwent diffusion-weighted MRI examination (with b = 0₁, 200₁, 500₁, 800₂, 1000₄, 1500₄, 2000₆ s/mm², the subscript denotes the number of signal averages) before and after chemotherapy. DKI and mono-exponential (b = 0, 800 s/mm²) models were built. Apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) of the LAGC tumors were measured. The absolute change values (ΔX) and percentage change values (%ΔX) of the above parameters post neoadjuvant chemotherapy (NACT) were calculated. The response was evaluated according to the pathological tumor regression grade scores (effective response group: TRG 0-2, poor response group: TRG 3). Mann-Whitney U test and receiver operating characteristic (ROC) curves were applicated for statistical analysis.

RESULTS

There were 17 patients in the effective response group (ERG), and 14 patients in the poor response group (PRG). The MK_pre and MK_post values in PRG were significantly higher than those in ERG [(0.671 ± 0.026) and (0.641 ± 0.019) vs. (0.584 ± 0.023) and (0.519 ± 0.018), p < 0.001]. ADC_post and MD_post in PRG were significantly lower than those in ERG (p = 0.005, p =0.001). Significant differences were also observed for % ΔMK, ΔMD and ΔMK between the two groups (p < 0.05). The area under the curve (AUC) for the prediction of PRG was highest for MK_post (AUC = 0.958, cutoff value = 0.614). The MK_pre and MK_post had the highest sensitivity (91.70 %) and specificity (93.80 %) in the prediction of PRG, respectively.

CONCLUSION

Both DKI and ADC values show potential for the prediction of the PRG in LAGC patients. The DKI parameters, especially MK_post displayed the best performance.

The role of MRI in the diagnosis and treatment of gastric cancer

Gastric cancer is the fifth most common malignancies and the third leading cause of cancer-related death worldwide, with more than 40% of new cases occurring in China. With the advancement of treatment methods, the application of adjuvant therapy and targeted drugs, the prognosis of patients with gastric cancer has been significantly improved. In recent years, more and more studies have reported that magnetic resonance imaging (MRI) showed great value in the clinical application among patients with gastric cancer, including preoperative staging, treatment response evaluation, predicting prognosis and histopathological features, treatment guidance, and molecular imaging. The remarkable research progress of MRI in gastric cancer will provide new evaluation and treatment approaches for clinical diagnosis and treatment. This article aims to review the current status of the application and research progress of MRI in patients with gastric cancer.

Predicting the pathological response to chemoradiotherapy of non-mucinous rectal cancer using pretreatment texture features based on intravoxel incoherent motion diffusion-weighted imaging

OBJECTIVES

To investigate the performance of the mean parametric values and texture features based on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) on identifying pathological complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC).

METHODS

Pretreatment IVIM-DWI was performed on 41 LARC patients receiving nCRT in this prospective study. The values of IVIM-DWI parameters (apparent diffusion coefficient, ADC; pure diffusion coefficient, D; pseudo-diffusion coefficient, D* and perfusion fraction, f), the first-order, and gray-level co-occurrence matrix (GLCM) texture features were compared between the pCR (n = 9) and non-pathological responder (non-pCR, n = 32) groups. Receiver operating characteristic (ROC) curves in univariate and multivariate logistic regression analysis were generated to determine the efficiency for identifying pCR.

RESULTS

The values of IVIM-DWI parameters and first-order texture features did not show significant differences between the pCR and non-pCR groups. The pCR group had lower Contrast and DifVarnc values extracted from the ADC, D, and D* maps, respectively, as well as lower Correlat_D value. Higher Correlat_D*, Correlat_f, SumAverg_ADC, and SumAverg_D values were observed in the pCR group. The area under the ROC curve (AUC) values for the individual predictors in univariate analysis ranged from 0.698 to 0.837, with sensitivities from 43.75% to 87.50% and specificities from 66.67 to 100.00%. In multivariate analysis, Correlat_D* (P < 0.001), DifVarnc_ADC (P = 0.024), and DifVarnc_D (P < 0.001) were the independent predictors to pCR, with an AUC of 0.986, a sensitivity of 93.75%, and a specificity of 100.00%.

CONCLUSION

Pretreatment GLCM analysis based on IVIM-DWI may be a potential approach to identify the pathological response of LARC.

Could intravoxel incoherent motion diffusion-weighted magnetic resonance imaging be feasible and beneficial to the evaluation of gastrointestinal tumors histopathology and the therapeutic response?

Gastrointestinal tumors (GTs) are among the most common tumors of the digestive system and are among the leading causes of cancer death worldwide. Functional magnetic resonance imaging (MRI) is crucial for assessment of histopathological changes and therapeutic responses of GTs before and after chemotherapy and radiotherapy. A new functional MRI technique, intravoxel incoherent motion (IVIM), could reveal more detailed useful information regarding many diseases. Currently, IVIM is widely used for various tumors because the derived parameters (diffusion coefficient, D; pseudo-perfusion diffusion coefficient, D*; and perfusion fraction, f) are thought to be important surrogate imaging biomarkers for gaining insights into tissue physiology. They can simultaneously reflect the microenvironment, microcirculation in the capillary network (perfusion) and diffusion in tumor tissues without contrast agent intravenous administration. The sensitivity and specificity of these parameters used in the evaluation of GTs vary, the results of IVIM in GTs are discrepant and the variability of IVIM measurements in response to chemotherapy and/or radiotherapy in these studies remains a source of controversy. Therefore, there are questions as to whether IVIM diffusion-weighted MRI is feasible and helpful in the evaluation of GTs, and whether it is worthy of expanded use.