Intravoxel incoherent motion diffusion weighted MRI of cervical cancer - Correlated with tumor differentiation and perfusion

Parametric response mapping of co-registered intravoxel incoherent motion magnetic resonance imaging and positron emission tomography in locally advanced cervical cancer undergoing concurrent chemoradiation therapy

Background and Purpose

Intravoxel-incoherent-motion (IVIM) magnetic-resonance-imaging (MRI) and positron-emission-tomography (PET) have been investigated independently but not voxel-wise to evaluate tumor microenvironment in cervical carcinoma patients. Whether regionally combined information of IVIM and PET offers additional predictive benefit over each modality independently has not been explored. Here, we investigated parametric-response-mapping (PRM) of co-registered PET and IVIM in cervical cancer patients to identify sub-volumes that may predict tumor shrinkage to concurrent-chemoradiation-therapy (CCRT).

Materials and Methods

Twenty cervical cancer patients (age: 63[41-85]) were retrospectively evaluated. Diffusion-weighted-images (DWIs) were acquired on 3.0 T MRIs using a free-breathing single-shot-spin echo-planar-imaging (EPI) sequence. Pre- and on-treatment (∼after four-weeks of CCRT) MRI and pre-treatment FDG-PET/CT were acquired. IVIM model-fitting on the DWIs was performed using a Bayesian-fitting simplified two-compartment model. Three-dimensional rigidly-registered maps of PET/CT standardized-uptake-value (SUV) and IVIM diffusion-coefficient (D) and perfusion-fraction (f) were generated. Population-means of PET-SUV, IVIM-D and IVIM-f from pre-treatment-scans were calculated and used to generate PRM via a voxel-wise joint-histogram-analysis to classify voxels as high/low metabolic-activity and with high/low (hi/lo) cellular-density. Similar PRM maps were generated for SUV and f.

Results

Tumor-volume (p < 0.001) significantly decreased, while IVIM-f (p = 0.002) and IVIM-D (p = 0.03) significantly increased on-treatment. Pre-treatment tumor-volume (r = -0.45,p = 0.04) and PRM-SUVhi D lo (r = -0.65,p = 0.002) negatively correlated with ΔGTV, while pre-treatment IVIM-D (r = 0.64,p = 0.002), PRM-SUVlo f hi (r = 0.52,p = 0.02), and PRM-SUVlo D hi (r = 0.74,p < 0.001) positively correlated with ΔGTV.

Conclusion

IVIM and PET was performed on cervical cancer patients undergoing CCRT and we observed that both IVIM-f and IVIM-D increased during treatment. Additionally, PRM was applied, and sub-volumes were identified that were related to ΔGTV.

Sequential multi-parametric MRI in assessment of the histological subtype and features in the malignant pleural mesothelioma xenografts

Objective

It is still a challenge to find a noninvasive technique to distinguish the histological subtypes of malignant pleural mesothelioma (MPM) and characterize the development of related histological features. We investigated the potential value of multiparametric MRI in the assessment of the histological subtype and development of histologic features in the MPM xenograft model.

Methods

MPM xenograft models were developed by injecting tumour cells into the right axillary space of nude mice. The T1, T2, R2*, T2*, apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), and perfusion fraction (f) at 14 d, 28 d, and 42 d were measured and compared between the epithelial and biphasic MPM. Correlations between multiparametric MRI parameters and histologic features, including necrotic fraction (NF) and microvessel density (MVD), were analysed.

Results

This study found that T2, T2* and IVIM-DWI parameters can reflect the spatial and temporal heterogeneity of MPM. Compared to the epithelial MPM, T2 and T2* were higher and ADC, D, D*, and f were lower in the biphasic MPM (P < 0.05). MRI parameters were different in different stages of epithelial and biphasic MPM. Moderate correlations were found between ADC and tumor volume and NF in the epithelial MPM, and there was a correlation between f and tumor volume and NF and MVD in the two groups.

Conclusion

MRI parameters changed with tumor progression in a xenograft model of MPM. MRI parameters may provide useful biomarkers for evaluating the histological subtype and histological features development of MPM.

Combining Clinicopathology, IVIM-DWI and Texture Parameters for a Nomogram to Predict Treatment Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients

Objectives

This study aimed to create a nomogram for the risk prediction of neoadjuvant chemoradiotherapy (nCRT) resistance in locally advanced rectal cancer (LARC).

Methods

Clinical data in this retrospective study were collected from a total of 135 LARC patients admitted to our hospital from June 2016 to December 2020. After screening by inclusion and exclusion criteria, 62 patients were included in the study. Texture analysis (TA) was performed on T2WI and DWI images. Patients were divided into response group (CR+PR) and no-response group (SD+PD) according to efficacy assessment. Multivariate analysis was performed on clinicopathology, IVIM-DWI and texture parameters for screening of independent predictors. A nomogram was created and model fit and clinical net benefit were assessed.

Results

Multivariate analysis of clinicopathology parameters showed that the differentiation and T stage were independent predictors (OR values were 14.516 and 11.589, resp.; P<0.05). Multivariate analysis of IVIM-DWI and texture parameters showed that f value and Rads-score were independent predictors (OR values were 0.855, 2.790, resp.; P<0.05). In this study, clinicopathology together with IVIM-DWI and texture parameters showed the best predictive efficacy (AUC=0.979). The nomogram showed good predictive performance and stability in identifying high-risk LARC patients who are resistant to nCRT (C-index=0.979). Decision curve analyses showed that the nomogram had the best clinical net benefit. Ten-fold cross-validation results showed that the average AUC value was 0.967, and the average C-index was 0.966.

Conclusions

The nomogram combining the differentiation, T stage, f value and Rads-score can effectively estimate the risk of nCRT resistance in patients with LARC.

Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging for Monitoring the Immune Response of Immunogenic Chemotherapy

Objective

To evaluate the predictive value of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) in the quantitative assessment of conventional chemotherapy-activated immune responses in mouse tumor models and clinics.

Methods

A total of 19 subcutaneous tumor-bearing mice were randomly divided into treated and control groups. Both groups had orderly IVIM DWI examinations before and on days 6 and 12 after the administration of cyclophosphamide (CPA) or saline. Pathologic examinations were performed, including HE staining and immunohistochemistry (IHC). The expressions of immune-related genes in the tumor were measured by qPCR. In addition, six patients with breast cancer requiring neoadjuvant chemotherapy (NACT) also underwent functional MRI examinations and IHC to determine potential antitumor immune response.

Results

At the end of the study, the CPA treatment group showed the lowest tumor volume compared to the control group. For pathological examinations, the CPA treatment group showed a lower percentage of CD31 staining (P &lt; 0.01) and Ki-67 staining (P&lt;0.01), and a higher percentage of TUNEL staining (P &lt; 0.01). The tumoral pseudodiffusion coefficient (D*) value showed a positive correlation with the CD31-positive staining rate (r = 0.729, P &lt; 0.0001). The diffusion related parameters (D) value was positively correlated with TUNEL (r = 0.858, P &lt; 0.0001) and negatively correlated with Ki-67 (r = -0.904, P &lt; 0.0001). Moreover, a strong induction of the expression of the immune responses in the CPA treatment group was observed on day 12. D values showed a positive correlation with the Ifnb1-, CD8a-, Mx1-, Cxcl10- (r = 0.868, 0.864, 0.874, and 0.885, respectively, P &lt; 0.0001 for all). Additionally, the functional MRI parameters and IHC results in patients with breast cancer after NACT also showed a close correlation between D value and CD8a (r = 0.631, P = 0.028).

Conclusions

The treatment response induced by immunogenic chemotherapy could be effectively evaluated using IVIM-DWI. The D values could be potential, sensitive imaging marker for identifying the antitumor immune response initiated by immunogenic chemotherapy.

A comparative study of four diffusion-weighted imaging models in the diagnosis of cervical cancer

BACKGROUND

Most commonly used diffusion-weighted imaging (DWI) models include intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential model (SEM), and mono-exponential model (MEM). Previous studies of the four models were inconsistent on which model was more effective in distinguishing cervical cancer from normal cervical tissue.

PURPOSE

To assess the performance of four DWI models in characterizing cervical cancer and normal cervical tissue.

MATERIAL AND METHODS

Forty-seven women with suspected cervical carcinoma underwent DWI using eight b-values before treatment. Imaging parameters, calculated using IVIM, SEM, DKI, and MEM, were compared between cervical cancer and normal cervical tissue. The diagnostic performance of the models was evaluated using independent t-test, Mann-Whitney U test, receiver operating characteristic (ROC) curve analysis, and multivariate logistic regression analysis.

RESULTS

All parameters except pseudo-diffusion coefficient (D*) differed significantly between cervical cancer and normal cervical tissue (P < 0.001). Through logistic regression analysis, all combined models showed a significant improvement in area under the ROC curve (AUC) compared to individual DWI parameters. The model with combined IVIM parameters had a larger AUC value compared to those of other combined models (P < 0.05).

CONCLUSION

All four DWI models are useful for differentiating cervical cancer from normal cervical tissue and IVIM may be the optimal model.

A Combination Analysis of IVIM-DWI Biomarkers and T2WI-Based Texture Features for Tumor Differentiation Grade of Cervical Squamous Cell Carcinoma

Purpose

To explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and texture analysis on T2-weighted imaging (T2WI) for evaluating pathological differentiation of cervical squamous cell carcinoma.

Method

This retrospective study included a total of 138 patients with pathologically confirmed poor/moderate/well-differentiated (71/49/18) who underwent conventional MRI and IVIM-DWI scans. The values of ADC, D, D ∗ , and f and 58 T2WI-based texture features (18 histogram features, 24 gray-level co-occurrence matrix features, and 16 gray-level run length matrix features) were obtained. Multiple comparison, correlation, and regression analyses were used.

Results

For IVIM-DWI, the ADC, D, D ∗ , and f were significantly different among the three groups (p < 0.05). ADC, D, and D ∗ were positively correlated with pathological differentiation (r = 0.262, 0.401, 0.401; p < 0.05), while the correlation was negative for f (r = -0.221; p < 0.05). The comparison of 52 parameters of texture analysis on T2WI reached statistically significant levels (p < 0.05). Multivariate logistic regression analysis incorporated significant IVIM-DWI, and texture features on T2WI showed good diagnostic performance both in the four differentiation groups (poorly vs. moderately, area under the curve(AUC) = 0.797; moderately vs. well, AUC = 0.954; poorly vs. moderately and well, AUC = 0.795; and well vs. moderately and poorly, AUC = 0.952). The AUCs of each parameters alone were smaller than that of each regression model (0.503∼0.684, 0.547∼0.805, 0.511∼0.712, and 0.636∼0.792, respectively; pairwise comparison of ROC curves between regression model and individual variables, p < 0.05).

Conclusions

IVIM-DWI biomarkers and T2WI-based texture features had potential to evaluate the pathological differentiation of cervical squamous cell carcinoma. The combination of IVIM-DWI with texture analysis improved the predictive performance.

Combining Intravoxel Incoherent Motion Diffusion Weighted Imaging and Texture Analysis for a Nomogram to Predict Early Treatment Response to Concurrent Chemoradiotherapy in Cervical Cancer Patients

This study aimed to predict early treatment response to concurrent chemoradiotherapy (CCRT) by combining intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) with texture analysis (TA) for cervical cancer patients and to develop a nomogram for estimating the risk of residual tumor. Ninty-three cervical cancer patients underwent conventional MRI and IVIM-DWI before CCRT. We conducted TA using T2WI. The patients were allocated to partial response (PR) and complete response (CR) groups on the basis of posttreatment MRI. Multivariate logistic regression analysis on IVIM-DWI parameters and texture features was employed to filter the independent predictors and construct the predictive nomogram. Its discrimination and calibration performances were estimated. Multivariate analysis on the IVIM-DWI parameters showed that D and f were independent predictors (OR = 4.029 and 0.889, resp.; p < 0.05). However, the multivariate analysis on the texture features indicated that GLCM-correlation, GLRLM-LRE, and GLSZM-ZE were independent predictors (OR = 43.789, 9.774, and 23.738, resp.;p < 0.05). The combination of IVIM-DWI parameters and texture features exhibited the highest predictive performance (AUC = 0.975). The nomogram to identify the patients with high-risk residual tumors exhibited an acceptable predictive performance and stability with a C-index of 0.953. Decision curve analysis demonstrated the clinical use of the nomogram. The results demonstrate that D, f, GLCM-correlation, GLRLM-LRE, and GLSZM-ZE were independent predictors for cervical cancer. The nomogram combining IVIM-DWI parameters and texture features makes it possible to identify cervical cancer patients at a high risk of residual tumor after CCRT.

Comparison of Diagnostic Performance between Perfusion-Related Intravoxel Incoherent Motion DWI and Dynamic Contrast-Enhanced MRI in Rectal Cancer

This study was aimed to determine the diagnostic performance of perfusion-related parameters derived from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) by comparing them with quantitative parameters from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) based on differentiation grades of rectal cancer. We retrospectively analyzed 98 patients with rectal cancer. Perfusion-related IVIM parameters (D^∗, f, and f·D^∗) and quantitative DCE parameters (K^trans, K_ep, V_e, and V_p) were obtained by plotting the volume-of-interest on in-house software. Furthermore, we compared the difference and diagnostic performance of all well-moderately and poorly differentiated rectal cancer parameters. Finally, we analyzed the correlation between those DCE and IVIM parameters and pathological differentiation grade. The values of f, K^trans, and K_ep significantly differentiated poor and well-moderate rectal cancers. K^trans achieved the highest area under the curve (AUC) value compared to perfusion-related IVIM and DCE parameters. Furthermore, K^trans showed a better correlation with pathological differentiation grade than f. The diagnostic efficiency of DCE-MRI was greater than perfusion-related IVIM parameters. The f value derived from perfusion-related IVIM offered a diagnostic performance similar to DCE-MRI for patients with renal insufficiency.

Uterine Cervical Carcinoma: Evaluation Using Non-Gaussian Diffusion Kurtosis Imaging and Its Correlation With Histopathological Findings

OBJECTIVE

The aim of the study was to assess non-Gaussian diffusion kurtosis imaging (DKI)'s usefulness as a noninvasive method to evaluate tumor invasion depth, histological grade, and lymph node metastasis in cervical carcinoma (CC) patients.

METHODS

Twenty-two consecutive patients with histologically confirmed CC were examined by 1.5-T MRI and non-Gaussian DKI with 4 b values of 0, 500, 1000, and 2000 s/mm2. Kurtosis (K), diffusivity (D), and apparent diffusion coefficient (ADC) maps were compared with histopathological findings.

RESULTS

Kurtosis maps revealed the fibrous stroma as a distinct high K zone (1.442 ± 0.373) that was significantly different from values of the cervical mucosa, outer stroma, and parametrium (0.648 ± 0.083, 0.715 ± 0.113, and 0.504 ± 0.060, respectively, P < 0.0001). Kurtosis (1.189 ± 0.228) and D (0.961 ± 0.198 × 10-3 mm2/s) values of all CCs were significantly different from those of all uterine cervical wall layers. Kurtosis and D values were significantly correlated with histological grades of CCs (r = 0.934, P < 0.0001, and r = -0.925, P < 0.0001, respectively), whereas no significant differences were found in ADC values between grades 2 and 3 CCs (P = 0.787). Metastatic and nonmetastatic lymph nodes showed significantly different K (P < 0.0001) and D (P < 0.0001) values; however, their ADC values did not show significant differences (P = 0.437). For differentiating grade 3 CCs from grade 1 or 2 CCs, the areas under the curve for K (0.991, P = 0.0375) and D (0.982, P = 0.0337) values were significantly higher than those for ADC values (0.759). For differentiating metastatic and nonmetastatic lymph nodes, the areas under the curve for K (0.974, P = 0.0028) and D (0.968, P = 0.0018) values were significantly higher than those for ADC (0.596).

CONCLUSIONS

Non-Gaussian DKI may be clinically useful for noninvasive evaluation of tumor invasion depth, histological grade, and lymph node metastasis in CC patients.

Prediction of early response to concurrent chemoradiotherapy in cervical cancer: Value of multi-parameter MRI combined with clinical prognostic factors

PURPOSE

This study aimed to investigate the prediction of early response to concurrent chemoradiotherapy (CCRT) through a combination of pretreatment multi-parametric magnetic resonance imaging (MRI) with clinical prognostic factors (CPF) in cervical cancer patients.

METHODS

Eighty-five patients with pathologically confirmed cervical cancer underwent conventional MRI, intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI), and dynamic contrast-enhanced MRI (DCE-MRI) before CCRT. The patients were divided into non- and residual tumor groups according to post-treatment MRI. Univariable and multivariable analyses were performed to pretreatment MRI parameters and CPF between the two groups, and optimal thresholds and predictive performance for post-treatment residual tumor occurrence were estimated by drawing the receiver operating characteristic (ROC) curve.

RESULTS

There were 52 patients in non- and 33 in residual group. The residual group showed a lower perfusion fraction (f) value and volume transfer constant (Ktrans) value, a higher apparent diffusion coefficient (ADC) value, diffusion coefficient (D) value and volume fraction of extravascular extracellular space (Ve) value, and a higher stage than the non-residual tumor group (all P < .05). D, Ktrans, Ve and stage were independent prognostic factors. The combination of D, Ktrans and Ve improved the diagnostic performance compared with individual MRI parameters. A further combination of these three MRI parameters with stage exhibited the highest predictive performance.

CONCLUSIONS

Pretreatment D, Ktrans, Ve and stage were independent prognostic factors for cervical cancer. The predictive capacity of multi-parametric MRI was superior to individual MRI parameters. The combination of multi-parametric MRI with CPF further improved the predictive performance.

Perfusion parameters of intravoxel incoherent motion based on tumor edge region of interest in cervical cancer: evaluation of differentiation and correlation with dynamic contrast-enhanced MRI

BACKGROUND

Intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) is a functional magnetic resonance imaging (MRI) sequence.

PURPOSE

To evaluate the value of perfusion parameters derived from IVIM-DWI based on tumor edge region of interest (ROI) in differentiation in cervical cancer and investigate the relationship between IVIM and dynamic contrast-enhanced MRI (DCE-MRI).

MATERIAL AND METHODS

Thirty-three patients with pathologically diagnosed squamous cell carcinoma who underwent IVIM-DWI (nine b-values: 1-1000 s/mm²) and DCE-MRI were retrospectively assessed in this study. Parameters of IVIM (D, f, D*, fD*) and quantitative parameters of DCE-MRI (Ktrans, Kep, Ve) were derived using tumor edge ROI. Mann-Whitney U test was used to compare parameters between pathological grades and receiver operating characteristic (ROC) curves were used. Pearson's correlation coefficient (r) evaluated the correlation between perfusion parameters derived from IVIM and DCE-MRI.

RESULTS

The poorly differentiated group showed the significantly lower D value and the higher f, Ktrans and Kep values than the well-to-moderately differentiated group (P < 0.05). ROC curves indicated that f < 26%, Ktrans <0.38/min, and Kep <1.62/min could differentiate the poorly differentiated group from the well-to-moderately differentiated group (AUC 0.753-0.808). Significantly positive correlations were found between f and Ktrans (r = 0.422, P = 0.014) and between fD* and Ktrans (r = 0.448, P = 0.009).

CONCLUSION

Perfusion parameters derived from IVIM based on tumor edge ROI may offer additional value in differentiation in cervical cancer, and the IVIM perfusion parameters showed moderate positive correlations with quantitative perfusion parameters from DCE-MRI, while f and fD* showed promising significance.

The invasion status of lymphovascular space and lymph nodes in cervical cancer assessed by mono-exponential and bi-exponential DWI-related parameters

AIM

To investigate whether mono-exponential and bi-exponential diffusion-weighted imaging (DWI)-related parameters of the primary tumour can evaluate the status of lymphovascular space invasion (LVSI) and lymph node metastasis (LNM) in patients with cervical carcinoma preoperatively.

MATERIALS AND METHODS

Eighty patients with cervical carcinoma were enrolled, who underwent preoperative multi b-value DWI and radical hysterectomy. They were classified into LVSI(+) versus LVSI(-) and LNM(+) versus LNM(-) according to postoperative pathology. The apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion coefficient (D∗), and perfusion fraction (f) were calculated from the whole tumour (__whole) and tumour margin (__margin). All parameters were compared between LVSI(+) and LVSI(-) and between LNM(+) and LNM(-). Logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed to evaluate the diagnostic performance of these parameters.

RESULTS

f__margin and D∗__whole showed significant differences in differentiating LVSI(+) from LVSI(-) tumours (p=0.002, 0.008, respectively), while LNM(+) tumours presented with significantly higher ADC__margin than that of LNM(-) tumours (p=0.009). The other parameters were not independent related factors with the status of LVSI or LNM according to logistic regression analysis (p>0.05). The area under the ROC curve of f__margin combined with D∗__whole in discriminating LVSI(+) from LVSI(-) was 0.826 (95% confidence interval [CI]: 0.691-0.961), while ADC__margin in differentiating LNM(+) from LNM(-) was 0.788 (95% CI: 0.648-0.928).

CONCLUSIONS

The parameters generated from mono-exponential and bi-exponential DWI of the primary cervical carcinoma could help discriminate its status regarding LVSI (f__margin and D∗__whole) and LNM (ADC__margin).

Perfusion-driven Intravoxel Incoherent Motion (IVIM) MRI in Oncology: Applications, Challenges, and Future Trends

Recent developments in MR hardware and software have allowed a surge of interest in intravoxel incoherent motion (IVIM) MRI in oncology. Beyond diffusion-weighted imaging (and the standard apparent diffusion coefficient mapping most commonly used clinically), IVIM provides information on tissue microcirculation without the need for contrast agents. In oncology, perfusion-driven IVIM MRI has already shown its potential for the differential diagnosis of malignant and benign tumors, as well as for detecting prognostic biomarkers and treatment monitoring. Current developments in IVIM data processing, and its use as a method of scanning patients who cannot receive contrast agents, are expected to increase further utilization. This paper reviews the current applications, challenges, and future trends of perfusion-driven IVIM in oncology.

Diffusion-Tensor Imaging of Uterine Cervical Carcinoma: Correlation With Histopathologic Findings

The authors investigated the usefulness of diffusion-tensor imaging (DTI) for evaluating tumor invasion depth, histologic grade, and lymph node metastasis in patients with cervical carcinoma (CC). Fifteen consecutive patients with histologically confirmed CC underwent 1.5-T magnetic resonance imaging and DTI. The CCs were clearly depicted as hypointense areas on all DTI maps. Fractional anisotropy, mean diffusivity, and axial diffusivity showed significantly inverse correlations with CC histologic grades and were significantly different between metastatic and nonmetastatic lymph nodes.

Texture Analysis of Apparent Diffusion Coefficient Maps in Cervical Carcinoma: Correlation with Histopathologic Findings and Prognosis

Purpose

To determine the feasibility of texture analysis of apparent diffusion coefficient (ADC) maps and to assess the performance of texture analysis and ADC to predict histologic grade, parametrial invasion, lymph node metastasis, International Federation of Gynecology and Obstetrics (FIGO) stage, recurrence, and recurrence-free survival (RFS) in patients with cervical carcinoma.

Materials and Methods

This retrospective study included 58 patients with cervical carcinoma who were examined with a 1.5-T MRI system and diffusion-weighted imaging with b values of 0 and 1000 sec/mm². Software with volumes of interest on ADC maps was used to extract 45 texture features, including higher-order texture features. Receiver operating characteristic (ROC) analysis was performed to compare the diagnostic performance of ADC map random forest models and of ADC values. Dunnett test, Spearman rank correlation coefficient, Kaplan-Meier analyses, log-rank test, and Cox proportional hazards regression analyses were also used for statistical analyses.

Results

The ADC map random forest models showed a significantly larger area under the ROC curve (AUC) than the AUC of ADC values for predicting high-grade cervical carcinoma (P = .0036), but not for parametrial invasion, lymph node metastasis, stages III-IV, and recurrence (P = .0602, .3176, .0924, and .5633, respectively). The random forest models predicted that the mean RFS rates were significantly shorter for high-grade cervical carcinomas, parametrial invasion, lymph node metastasis, stages III-IV, and recurrence (P = .0405, < .0001, .0344, .0001, and .0015, respectively); the random forest models for parametrial invasion and stages III-IV were more useful than ADC values (P = .0018) for predicting RFS.

Conclusion

The ADC map random forest models were more useful for noninvasively evaluating histologic grade, parametrial invasion, lymph node metastasis, FIGO stage, and recurrence and for predicting RFS in patients with cervical carcinoma than were ADC values.Keywords: Comparative Studies, Genital/Reproductive, MR-Diffusion Weighted Imaging, MR-Imaging, Neoplasms-Primary, Pathology, Pelvis, Tissue Characterization, UterusSupplemental material is available for this article.© RSNA, 2020See also the commentary by Reinhold and Nougaret in this issue.

B-Value Optimization in the Estimation of Intravoxel Incoherent Motion Parameters in Patients with Cervical Cancer

OBJECTIVE

This study aimed to find the optimal number of b-values for intravoxel incoherent motion (IVIM) imaging analysis, using simulated and in vivo data from cervical cancer patients.

MATERIALS AND METHODS

Simulated data were generated using literature pooled means, which served as reference values for simulations. In vivo data from 100 treatment-naïve cervical cancer patients with IVIM imaging (13 b-values, scan time, 436 seconds) were retrospectively reviewed. A stepwise b-value fitting algorithm calculated optimal thresholds. Feed forward selection determined the optimal subsampled b-value distribution for biexponential IVIM fitting, and simplified IVIM modeling using monoexponential fitting was attempted. IVIM parameters computed using all b-values served as reference values for in vivo data.

RESULTS

In simulations, parameters were accurately estimated with six b-values, or three b-values for simplified IVIM, respectively. In vivo data showed that the optimal threshold was 40 s/mm² for patients with squamous cell carcinoma and a subsampled acquisition of six b-values (scan time, 198 seconds) estimated parameters were not significantly different from reference parameters (individual parameter error rates of less than 5%). In patients with adenocarcinoma, the optimal threshold was 100 s/mm², but an optimal subsample could not be identified. Irrespective of the histological subtype, only three b-values were needed for simplified IVIM, but these parameters did not retain their discriminative ability.

CONCLUSION

Subsampling of six b-values halved the IVIM scan time without significant losses in accuracy and discriminative ability. Simplified IVIM is possible with only three b-values, at the risk of losing diagnostic information.

Using amide proton transfer to identify cervical squamous carcinoma/adenocarcinoma and evaluate its differentiation grade

PURPOSE

To explore the possibility of using amide proton transfer-weighted imaging (APTWI) for the identification and diagnosis of cervical squamous carcinoma (CSC), cervical adenocarcinoma (CA) and different levels of CSC.

MATERIALS AND METHODS

Seventy-six patients with newly diagnosed uterine cervical cancer (UCC) were studied prior to treatment, including 20 with poorly differentiated (Grade 3) CSC, 23 with moderately differentiated (Grade 2) CSC, 17 with well-differentiated (Grade 1) CSC, and 16 with CA (13 with poorly differentiated (Grade 3) CA and 3 with moderately differentiated (Grade 2) CA). Differences in the magnetization transfer ratio at 3.5 ppm (MTRasym (3.5 ppm)) were identified between CSC and CA and between high-level (Grade 3) CSC and low-level (Grade 2 and Grade 1) CSC, as well as among all three grades of CSC differentiation. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic thresholds and performance of the parameters. Spearman correlation analysis was used to examine the correlation between the MTRasym (3.5 ppm) and histological grade.

RESULTS

The MTRasym (3.5 ppm) in CA was higher than that in CSC (P = 0.001). The MTRasym (3.5 ppm) in high-level CSC was higher than that in low-level CSC (P = 0.001). The MTRasym (3.5 ppm) was positively correlated with the grade of CSC differentiation (r = 0.498, P = 0.001). The MTRasym (3.5 ppm) in Grade 3 CSC was higher than that in Grade 2 and Grade 1 CSC (P = 0.02/0.01). No significant difference in the MTRasym (3.5 ppm) was found between Grade 2 CSC and Grade 1 CSC (P = 0.173). The area under the ROC curve (AUC) for the MTRasym (3.5 ppm) in distinguishing CSC and CA was 0.779, with a cut-off, sensitivity, and specificity of 2.97%, 60.0% and 82.5%, respectively. The AUC for distinguishing high-/low-level CSC was 0.756, with a cut-off, sensitivity, and specificity of 3.29%, 68.8% and 83.3%, respectively.

CONCLUSION

APTWI may be a useful technique for the identification and diagnosis of CSC, CA and different levels of CSC, which may have an important impact on clinical strategies for treating patients with UCC.

Endometrial cancer: an overview of novelties in treatment and related imaging keypoints for local staging

Endometrial cancer is the most common gynaecologic malignancy in developed countries and its incidence is increasing. First-level treatment, if no contraindicated, is based on surgery. Pre-operative imaging is needed for evaluation of local extent and detection of distant metastases in order to guide treatment planning. Radiological evaluation, based on transvaginal ultrasound, MR and CT, can make the difference in disease management, paying special attention to assessment of entity of myometrial invasion, cervical stromal extension, and assessment of lymph nodal involvement and distant metastases.

Potentials and challenges of diffusion-weighted magnetic resonance imaging in radiotherapy

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Discussion of DW imaging protocols and imaging setup.

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Discussion of mono- and bi-exponential models for quantitative parameter extraction.

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Review of recent publications investigating potential benefits of using DWI in RT, including detailed synoptic table.

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Detailed discussion of geometric and quantitative accuracy of DW imaging and DW-derived parameters.

Purpose

To review the potential and challenges of integrating diffusion weighted magnetic resonance imaging (DWI) into radiotherapy (RT).

Content

Details related to image acquisition of DWI for RT purposes are discussed, along with the challenges with respect to geometric accuracy and the robustness of quantitative parameter extraction. An overview of diffusion- and perfusion-related parameters derived from mono- and bi-exponential models is provided, and their role as potential RT biomarkers is discussed. Recent studies demonstrating potential of DWI in different tumor sites such as the head and neck, rectum, cervix, prostate, and brain, are reviewed in detail.

Conclusion

DWI has shown promise for RT outcome prediction, response assessment, as well as for tumor delineation and characterization in several cancer types. Geometric and quantification robustness is challenging and has to be addressed adequately. Evaluation in larger clinical trials with well designed imaging protocol and advanced analysis models is needed to develop the optimal strategy for integrating DWI in RT.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging of Advanced Cervical Carcinoma: The Advantage of Perfusion Parameters From the Peripheral Region in Predicting the Early Response to Radiotherapy

Objective

This study aimed to investigate the importance of perfusion parameters from the peripheral region in predicting the early response to radiotherapy for advanced cervical carcinoma by using dynamic contrast-enhanced (DCE) perfusion magnetic resonance imaging (MRI).

Methods

One hundred eight patients with advanced cervical carcinoma were enrolled into this study. Dynamic contrast-enhanced perfusion MR examinations were performed for all the patients before radiotherapy. Perfusion parameters were obtained from the central region and the peripheral region of tumor respectively. After radiotherapy, the patients were classified into responders and nonresponders according to tumor shrinkage on the basis of follow-up MRI examination. The mean follow-up time lasted 12 months. The perfusion parameters were compared between the 2 groups. The relationship between perfusion parameters from 2 different regions of tumor and treatment effect was analyzed.

Results

The mean value of volume transfer constant (Ktrans), rate constant (Kep) or extravascular extracellular volume fraction (Ve) from the peripheral region was higher than that from the central region of tumor, respectively (P = 0.01, 004, 0.03). Responders had higher Ktransperipheral (Ktrans from the peripheral region) and Ktranscentral (Ktrans from the central region) values than nonresponders (P = 0.04, 0.01). Responders had higher Kepperipheral (Kep from the peripheral region) than nonresponders (P = 0.03). Responders had lower Veperipheral (Ve from the peripheral region) than nonresponders (P = 0.04). At logistic regression analysis, the perfusion parameters that had predicting value were Ktransperipheral, Veperipheral, Kepperipheral and Ktranscentral according to diagnostic potency.

Conclusions

Compared with perfusion parameters from the central region of tumor, perfusion parameters from the peripheral region are more valuable in predicting the early response to radiotherapy for advanced cervical carcinoma.

A study on diffusion and kurtosis features of cervical cancer based on non-Gaussian diffusion weighted model

OBJECTIVE

To explore the diffusion and kurtosis features of cervical cancer (CC) and study the feasibility of diffusion kurtosis imaging (DKI) based on the non-Gaussian diffusion-weighted model to differentiate the stage and grade of CC.

METHODS

A total of 50 patients with pathologically confirmed CC were enrolled. MRI examinations including DKI (with 5b values 200, 500, 1000, 1500, and 2000smm^-2 were performed before any treatment. The apparent coefficient (D_app) and the apparent kurtosis value (K_app) were derived from the non-gaussian diffusion model, and the apparent diffusion coefficient (ADC) was derived from the Gaussian model. The parameters of CC and normal tissue (myometrium) were obtained, analyzed statistically, and evaluated with respect to differentiating stage and grade between the tissue and the CC.

RESULTS

ADC and D_app values of CC were significantly lower than that of the normal myometrium (P=0.024 and P<0.001, respectively), while the K_app value was not found to exhibit a significant difference. Compared to the well/moderately differentiated CC, poorly differentiated CC had a significantly decreased mean ADC and D_app (P=0.018 and P=0.026, respectively); however, the mean K_app (P=0.035) increased significantly. In the clinical staging, the DKI sequence was advantageous over conventional MRI sequences (degree of accuracy: 90% vs. 74%), Although in the quantitative analysis, these parameters did not show a significant difference.

CONCLUSIONS

The pilot study demonstrated that these diffusion and kurtosis indices from DKI based on the non-Gaussian diffusion-weighted model putatively differentiated the grade and stage of CC.

The value of advanced MRI techniques in the assessment of cervical cancer: a review

OBJECTIVES

To assess the value of new magnetic resonance imaging (MRI) techniques in cervical cancer.

METHODS

We searched PubMed and MEDLINE and reviewed articles published from 1990 to 2016 to identify studies that used MRI techniques, such as diffusion weighted imaging (DWI), intravoxel incoherent motion (IVIM) and dynamic contrast enhancement (DCE) MRI, to assess parametric invasion, to detect lymph node metastases, tumour subtype and grading, and to detect and predict tumour recurrence.

RESULTS

Seventy-nine studies were included. The additional use of DWI improved the accuracy and sensitivity of the evaluation of parametrial extension. Most studies reported improved detection of nodal metastases. Functional MRI techniques have the potential to assess tumour subtypes and tumour grade differentiation, and they showed additional value in detecting and predicting treatment response. Limitations included a lack of technical standardisation, which limits reproducibility.

CONCLUSIONS

New advanced MRI techniques allow improved analysis of tumour biology and the tumour microenvironment. They can improve TNM staging and show promise for tumour classification and for assessing the risk of tumour recurrence. They may be helpful for developing optimised and personalised therapy for patients with cervical cancer.

TEACHING POINTS

• Conventional MRI plays a key role in the evaluation of cervical cancer. • DWI improves tumour delineation and detection of nodal metastases in cervical cancer. • Advanced MRI techniques show promise regarding histological grading and subtype differentiation. • Tumour ADC is a potential biomarker for response to treatment.

Intravoxel Incoherent Motion Diffusion-Weighted Magnetic Resonance Imaging of Cervical Cancer With Different b-Values

OBJECTIVE

The aims of this study were to evaluate the dependence of diffusion parameters on the b values adopted for intravoxel incoherent motion diffusion-weighted magnetic resonance imaging and to investigate the application value of multiple diffusion parameters obtained from monoexponential and biexponential models in subjects with a normal cervix and in cervical cancer patients.

METHODS

A total of 120 female patients with cervical cancer and 21 female control subjects with a normal cervix underwent diffusion-weighted magnetic resonance imaging with 13 b values (0-2000 s/mm) at 3 T. The standard apparent diffusion coefficient (Dst), diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were calculated by fitting with monoexponential and biexponential models at 2 different ranges of b values: 0 to 1000 and 0 to 2000 s/mm. A univariate analysis was performed to identify factors that could distinguish cervical carcinoma from normal cervical tissue. Parameters that correlated with the pathological grade and stage of cervical cancer were also evaluated. Receiver operating characteristic curves were used to evaluate the diagnostic efficiency of every parameter.

RESULTS

All the tested parameters, except the D* of the 2 different ranges of b value groups, significantly differed between the patients with cervical carcinoma and control subjects (P < 0.01). D2000, Dst2000, and D1000 showed comparable diagnostic value, with an area under the curve of 0.923, 0.909, and 0.907, respectively. Dst2000, D2000, Dst1000, and D1000 differed significantly among the 3 degrees of cervical stromal infiltration depth (P < 0.05).

CONCLUSIONS

D2000 and Dst2000 tended to outperform D1000 in terms of diagnostic efficiency, but there was no significant difference in their ability to differentiate cervical carcinoma from normal cervix. Cervical cancers with lower Dst and D values tended to have greater infiltration depth.

Assessment of Cervical Cancer with a Parameter-Free Intravoxel Incoherent Motion Imaging Algorithm

Objective

To evaluate the feasibility of a parameter-free intravoxel incoherent motion (IVIM) approach in cervical cancer, to assess the optimal b-value threshold, and to preliminarily examine differences in the derived perfusion and diffusion parameters for different histological cancer types.

Materials and Methods

After Institutional Review Board approval, 19 female patients (mean age, 54 years; age range, 37–78 years) gave consent and were enrolled in this prospective magnetic resonance imaging study. Clinical staging and biopsy results were obtained. Echo-planar diffusion weighted sequences at 13 b-values were acquired at 3 tesla field strength. Single-sliced region-of-interest IVIM analysis with adaptive b-value thresholds was applied to each tumor, yielding the optimal fit and the optimal parameters for pseudodiffusion (D^*), perfusion fraction (F_p) and diffusion coefficient (D). Monoexponential apparent diffusion coefficient (ADC) was calculated for comparison with D.

Results

Biopsy revealed squamous cell carcinoma in 10 patients and adenocarcinoma in 9. The b-value threshold (median [interquartile range]) depended on the histological type and was 35 (22.5–50) s/mm² in squamous cell carcinoma and 150 (100–150) s/mm² in adenocarcinoma (p < 0.05). Comparing squamous cell vs. adenocarcinoma, D^* (45.1 [25.1–60.4] × 10⁻³ mm²/s vs. 12.4 [10.5–21.2] × 10⁻³ mm²/s) and F_p (7.5% [7.0–9.0%] vs. 9.9% [9.0–11.4%]) differed significantly between the subtypes (p < 0.02), whereas D did not (0.89 [0.75–0.94] × 10⁻³ mm²/s vs. 0.90 [0.82–0.97] × 10⁻³ mm²/s, p = 0.27). The residuals did not differ (0.74 [0.60–0.92] vs. 0.94 [0.67–1.01], p = 0.32). The ADC systematically underestimated the magnitude of diffusion restriction compared to D (p < 0.001).

Conclusion

The parameter-free IVIM approach is feasible in cervical cancer. The b-value threshold and perfusion-related parameters depend on the tumor histology type.

Primary and metastatic ovarian cancer: Characterization by 3.0T diffusion-weighted MRI

Objectives

We aimed to investigate whether apparent diffusion coefficients (ADCs) measured by 3.0T diffusion-weighted magnetic resonance imaging (DWI) associate with histological aggressiveness of ovarian cancer (OC) or predict the clinical outcome. This prospective study enrolled 40 patients with primary OC, treated 2011-2014.

Methods

DWI was performed prior to surgery. Two observers used whole lesion single plane region of interest (WLsp-ROI) and five small ROIs (S-ROI) to analyze ADCs. Samples from tumours and metastases were collected during surgery. Immunohistochemistry and quantitative reverse transcription polymerase chain reaction (qRT-PCR) were used to measure the expression of vascular endothelial growth factor (VEGF) and its receptors.

Results

The interobserver reliability of ADC measurements was excellent for primary tumours ICC 0.912 (WLsp-ROI). Low ADCs significantly associated with poorly differentiated OC (WLsp-ROI P = 0.035). In primary tumours, lower ADCs significantly associated with high Ki-67 (P = 0.001) and low VEGF (P = 0.001) expression. In metastases, lower ADCs (WLsp-ROI) significantly correlated with low VEGF receptors mRNA levels. ADCs had predictive value; 3-year overall survival was poorer in patients with lower ADCs (WLsp-ROI P = 0.023, S-ROI P = 0.038).

Conclusion

Reduced ADCs are associated with histological severity and worse outcome in OC. ADCs measured with WLsp-ROI may serve as a prognostic biomarker of OC.

Key Points

• Reduced ADCs correlate with prognostic markers: poor differentiation and high Ki-67 expression

• ADCs also significantly correlated with VEGF protein expression in primary tumours

• Lower ADC values are associated with poorer survival in ovarian cancer

• Whole lesion single plane-ROI ADCs may be used as a prognostic biomarker in OC

Hypoxia in cervical cancer: from biology to imaging

PURPOSE

Hypoxia imaging may improve identification of cervical cancer patients at risk of treatment failure and be utilized in treatment planning and monitoring, but its clinical potential is far from fully realized. Here, we briefly describe the biology of hypoxia in cervix tumors of relevance for imaging, and evaluate positron emission tomography (PET) and magnetic resonance imaging (MRI) techniques that have shown promise for assessing hypoxia in a clinical setting. We further discuss emerging imaging approaches, and how imaging can play a role in future treatment strategies to target hypoxia.

METHODS

We performed a PubMed literature search, using keywords related to imaging and hypoxia in cervical cancer, with a particular emphasis on studies correlating imaging with other hypoxia measures and treatment outcome.

RESULTS

Only a few and rather small studies have utilized PET with tracers specific for hypoxia, and no firm conclusions regarding preferred tracer or clinical potential can be drawn so far. Most studies address indirect hypoxia imaging with dynamic contrast-enhanced techniques. Strong evidences for a role of these techniques in hypoxia imaging have been presented. Pre-treatment images have shown significant association to outcome in several studies, and images acquired during fractionated radiotherapy may further improve risk stratification. Multiparametric MRI and multimodality PET/MRI enable combined imaging of factors of relevance for tumor hypoxia and warrant further investigation.

CONCLUSIONS

Several imaging approaches have shown promise for hypoxia imaging in cervical cancer. Evaluation in large clinical trials is required to decide upon the optimal modality and approach.