The Value of IVIM DWI in Combination with Conventional MRI in Identifying the Residual Tumor After Cone Biopsy for Early Cervical Carcinoma

Field-of-view optimized and constrained undistorted single shot intravoxel incoherent motion diffusion-weighted imaging of the cervix during the menstrual cycle: A prospective study

OBJECTIVE

To provide insight into the biological characteristics of the healthy cervix by defining intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters across the menstrual cycle.

METHODS

Forty-three females of reproductive age (18-45 years old) were included in this prospective study. Conventional magnetic resonance imaging (MRI) and IVIM-DWI scans were performed at multiple time-points across the menstrual cycle: T1 (menses), T2 (follicular phase), T3 (luteal phase). Intra- and interobserver repeatability of the IVIM-DWI values were evaluated with intraclass correlation coefficients (ICC), and D* was excluded from the analyses due to poor repeatability. Differences in each IVIM-DWI parameter among T1, T2, and T3 were explored. Subjects were stratified by age and parity for subgroup analyses (younger [18 - < 30 years] vs. older [≥30-45 years]; parity 0 vs. parity 1 and 2). Correlations between subject age and IVIM-DWI parameters were assessed. The overlap for each IVIM-DWI parameter among T1, T2, and T3 was evaluated.

RESULTS

ADC and D values of the cervix were significantly lower at T3 compared with T1 (p = 0.02 and 0.03) or T2 (p < 0.01 and < 0.01). In younger subjects (n = 26), ADC and D values were significantly lower at T3 compared with T1 (p < 0.01 and p = 0.02) or T2 (p = 0.03 and p = 0.04). In older subjects (n = 17), ADC values were significantly higher at T2 compared with T1 (p = 0.01) or T3 (p = 0.01). There were significant differences in ADC values at T1 in subgroup analyses stratified by age and parity (both p < 0.01). There was a moderate correlation between age and ADC values at T1. Overlap for IVIM-DWI parameters across the menstrual cycle was >50%.

CONCLUSION

ADC and D values of the heathy cervix differed across the menstrual cycle. Age and parity may influence the ADC value.

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.

Application of intravoxel incoherent motion diffusion-weighted imaging for preoperative knowledge of lymphovascular invasion in gastric cancer: a prospective study

PURPOSE

To investigate the potential of intravoxel incoherent motion diffusion-weighted imaging (IVIM) for preoperative prediction of lymphovascular invasion (LVI) in gastric cancer (GC).

METHODS

This study prospectively enrolled 90 patients (62 males, 28 females, 60.79 ± 9.99 years old) who received radical gastrostomy. Abdominal MRI examinations including IVIM were performed within 1 week before surgery. Patients were divided into LVI-positive and -negative group according to pathological diagnosis after surgery. The apparent diffusion coefficient (ADC) and IVIM parameters, including true diffusion coefficient (D), pseudodiffusion coefficient (D*), and pseudodiffusion fraction (f), were compared between the two groups. The relationship between MRI parameters and LVI was studied by Spearman's correlation analysis. Multivariable logistic regression analysis was used to screen independent predictors of LVI. Receiver-operating characteristic curve analyses were applied to evaluate the efficacy.

RESULTS

The ADC, D in LVI-positive group were lower, whereas tumor thickness and f parameter in LVI-positive group were higher than those in LVI-negative group, and they were statistically correlated with LVI (p < 0.05). D, f and tumor thickness were independent risk factors of LVI. The area under the curve of ADC, D, f, thickness, and the combined parameter (D + f + thickness) were 0.667, 0.754, 0.695, 0.792, and 0.876, respectively. The combined parameter demonstrated higher efficacy than any other parameters (p < 0.05).

CONCLUSION

The ADC, D, and f can effectively distinguish LVI status of GC. The D, f and thickness were independent predictors. The combination of the three predictors further improved the efficacy.

Investigating the effect of ARHGEF10L gene on tumor growth in gastric cancer in a nude mouse model using quantitative MRI parameters

Background

The quantitative magnetic resonance imaging (MRI) parameters were initially used in the study of central nervous system diseases and has since been widely used in the diagnosis of breast, liver, rectum, and prostate diseases. In our study, we aimed to evaluate the effect of ARHGEF10L gene on tumor growth in gastric cancer in nude mice using quantitative MRI parameters.

Subjects and Methods

A nude mice model of gastric cancer was established, and the mice were divided into a control group and an shARHGEF10L group (N = 10). T2-fs and intravoxel incoherent motions (IVIM) imaging were performed in the mice coil with a 3.0 T MR system. The differences in quantitative parameters (apparent diffusion coefficient [ADC], D, D *, f values) were compared between both groups, and the effect of ARHGEF10L expression on tumor growth in tumor-bearing mice was investigated. The data were analyzed using Statistical Package for the Social Sciences (SPSS) 17.0 software package.

Results

The ADC and D values of tumor imaging in the shARHGEF10L group were higher than those in the control group, and the differences were statistically significant. There was no significant difference in the D* or F values between both groups.

Conclusions

The ADC and D values of the quantitative IVIM imaging parameters can be used to effectively assess the growth of gastric cancer in nude mice, suggesting that ARHGEF10L may promote the growth of tumor cells.

Classifying early stages of cervical cancer with MRI-based radiomics

This study aims to establish a MRI-based classifier to distinguish early stages of cervical cancer with improved diagnostic performance to assist clinical diagnosis and treatment. 57 patients with pathological diagnosis of cervical cancer from January 2018 to May 2019 were enrolled in this study. MRI examinations, including T1-weighted image(T1WI), T2-weighted image(T2W), diffusion weighted imaging (DWI) and dynamic contrast enhanced (DCE), were performed before surgery. MR images from patients of stage Ib or IIa cervical cancer with tumor segmented were used as input. Feature extraction process extracted first-order statistics and texture and applied filters. The dimensionality of the radiomic features was reduced using the least absolute shrinkage and selection operator (LASSO). Models were trained by three machine-learning (k-nearest neighbor (KNN), support vector machine (SVM), and logistic regression (LR)) and diagnostic performance in differentiating stage Ib and stage IIa cases was evaluated. A total of 27 features were extracted to establish models, including 2 features from T1WI, 5 features from T2WI, 5 features from DWI (b = 50), 4 features from DWI (b = 800), 5 features from DCE, and 6 features from ADC. For each machine learning (ML) classifier, six sequences of training set and testing set are modeled and analyzed. Among all the models, the training set and testing set of T2WI model built by SVM classifier were the best (Area under the curve (AUC) 0.915) / (AUC 0.907). Radiomic analysis of ML-based texture features and first-order statistics features can be used to stage the early cervical cancer pre-operatively.

The role of MRI in cervical cancer > 2 cm (FIGO stage IB2-IIA1) conservatively treated with neoadjuvant chemotherapy followed by conization: a pilot study

Introduction

MRI is very accurate in selecting young women with cervical cancer for fertility-sparing surgery (FSS), in particular radical hysterectomy (RH). In order to improve obstetrical outcomes, neoadjuvant chemotherapy (NACT) followed by cold knife conization (CKC) has been proposed as alternative technique.

Objective

To investigate the role of MRI in evaluation of response to treatment after neoadjuvant chemotherapy (NACT), followed by CKC, in patients with cervical cancer FIGO stage IB2-IIA1 with tumor size 2 – 4 cm, desiring to preserve their fertility.

Methods

13 young women (23–36 years old) with cervical cancer stage IB2-IIA1 desiring to preserve their fertility were included. Tumor diameter at baseline and after treatment was detected on 1.5 T MRI. Treatment response was assessed according to Response Evaluation Criteria in Solid Tumors (RECIST 1.1) and then compared to histopathology result.

Results

MRI correctly assessed 11 out of 13 cases, according to RECIST 1.1, compared to histopathology. Among these 7 patients with partial response (PR), 2 cases of CR, 1 SD and 1 PD with persistence or enlargement of primary tumor.

Conclusion

Our pilot study supports the usefulness of MRI in assessment of treatment response after NACT, followed by CKC.

Trial registration number

ClinicalTrials.gov: NCT02323841