Oscillating Gradient Diffusion-Weighted MRI for Risk Stratification of Uterine Endometrial Cancer

BACKGROUND

Oscillating gradient diffusion-weighted imaging (DWI) enables elucidation of microstructural characteristics in cancers; however, there are limited data to evaluate its utility in patients with endometrial cancer.

PURPOSE

To investigate the utility of oscillating gradient DWI for risk stratification in patients with uterine endometrial cancer compared with conventional pulsed gradient DWI.

STUDY TYPE

Retrospective.

SUBJECTS

Sixty-three women (mean age: 58 [range: 32-85] years) with endometrial cancer.

FIELD STRENGTH/SEQUENCE

3 T MRI including DWI using oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE) research sequences.

ASSESSMENT

Mean value of the apparent diffusion coefficient (ADC) values for OGSE (ADCOGSE) and PGSE (ADCPGSE) as well as the ADC ratio (ADCOGSE/ADCPGSE) within endometrial cancer were measured using regions of interest. Prognostic factors (histological grade, deep myometrial invasion, lymphovascular invasion, International Federation of Gynecology and Obstetrics [FIGO] stage, and prognostic risk classification) were tabulated.

STATISTICAL TESTS

Interobserver agreement was analyzed by calculating the intraclass correlation coefficient. The associations of ADCOGSE, ADCPGSE, and ADCOGSE/ADCPGSE with prognostic factors were examined using the Kendall rank correlation coefficient, Mann-Whitney U test, and receiver operating characteristic (ROC) curve. A P value of <0.05 was statistically significant.

RESULTS

Compared with ADCOGSE and ADCPGSE, ADCOGSE/ADCPGSE was significantly and strongly correlated with histological grade (observer 1, τ = 0.563; observer 2, τ = 0.456), FIGO stage (observer 1, τ = 0.354; observer 2, τ = 0.324), and prognostic risk classification (observer 1, τ = 0.456; observer 2, τ = 0.385). The area under the ROC curves of ADCOGSE/ADCPGSE for histological grade (observer 1, 0.92, 95% confidence intervals [CIs]: 0.83-0.98; observer 2, 0.84, 95% CI: 0.73-0.92) and prognostic risk (observer 1, 0.80, 95% CI: 0.68-0.89; observer 2, 0.76, 95% CI: 0.63-0.86) were significantly higher than that of ADCOGSE and ADCPGSE.

DATA CONCLUSION

The ADC ratio obtained via oscillating gradient and pulsed gradient DWIs might be useful imaging biomarkers for risk stratification in patients with endometrial cancer.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Whole-tumor apparent diffusion coefficient histogram analysis for preoperative risk stratification in endometrial endometrioid adenocarcinoma

OBJECTIVE

To investigate the application of whole-tumor apparent diffusion coefficient (ADC) histogram metrics for preoperative risk stratification in endometrial endometrioid adenocarcinoma (EEA).

METHODS

Preoperative MRI of 502 EEA patients were retrospectively analyzed. Whole tumor ADC histogram analysis was performed with regions of interest drawn on all tumor slices of diffusion-weighted imaging scans. Risk stratification was based on ESMO-ESTRO-ESP guidelines: low-, intermediate-, high-intermediate-, and high-risk. Univariable analysis was used to compare ADC histogram metrics (tumor volume, minADC, maxADC, and meanADC; 10th, 25th, 50th, 75th, and 90th percentiles of ADC [recorded as P10, P25, P50, P75, and P90 ADC, respectively]; skewness; and kurtosis) between different risk EEAs, and multivariable logistic regression analysis to determine the optimal metric or combined model for risk stratifications. Receiver operating characteristic curve analysis with the area under the curve (AUC) was used for diagnostic performance evaluation.

RESULTS

A decreasing tendency in multiple ADC values was observed from the low- to high-intermediate-risk EEAs. The (low + intermediate)-risk EEAs and low-risk EEAs had significantly smaller tumor volumes and higher minADCs, meanADCs, P10, P25, P50, P75, and P90 ADCs than the (high-intermediate + high)-risk EEAs and non-low-risk EEAs (all P < 0.05), respectively. The combined models of the (meanADC + volume) and the (P75 ADC + volume) yielded the largest AUCs of 0.775 and 0.780 in identifying the (low + intermediate)- and the low-risk EEAs from the other EEAs, respectively.

CONCLUSION

Whole-tumor ADC histogram metrics might be helpful for preoperatively identifying low- and (low + intermediate)-risk EEAs, facilitating personalized therapeutic planning.

PET/MRI in Endometrial Cancer: Imaging Biomarkers are Associated with Disease Progression and Overall Survival

RATIONALE AND OBJECTIVES

To evaluate the association between positron emission tomography (PET)/magnetic resonance imaging (MRI) biomarkers and survival outcomes in patients with endometrial cancer.

MATERIALS AND METHODS

Between April 2014 and April 2016, 88 patients with newly diagnosed endometrial cancer participated this prospective study and underwent [18F] fluorodeoxyglucose PET/MRI. Sixty-nine patients with measurable tumors on PET/MRI were included in the image analysis. Imaging biomarkers included the minimum and mean apparent diffusion coefficients (ADCmin and ADCmean), maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumors. The log-rank test and Cox proportional hazards model were used to assess the relationship between imaging biomarkers and survival.

RESULTS

After a median follow-up of 80 months, 15 (22%) patients had tumor progression and six (9%) patients died. The results of ADCmin, ADCmean, and SUVmax did not show a significant association with progression-free survival (PFS) and overall survival (OS). Significantly shorter PFS was noted in patients with primary tumors with higher MTV (P < 0.001) and TLG (P < 0.001). Significantly shorter OS was also noted in patients with primary tumors with higher MTV (P = 0.048) and TLG (P = 0.034). In the multivariate analysis, MTV was an independent predictor of PFS (hazard ratio = 10.84, P = 0.033).

CONCLUSION

PET/MRI biomarkers, particularly MTV and TLG, are associated with PFS and OS in patients with endometrial cancer. MTV was an independent predictor of PFS.

Clinical Utility of Diffusion-Weighted Imaging in Gynecological Imaging: Revisited

ABSTRACT

Diffusion-weighted imaging (DWI) is an increasingly valuable sequence in daily clinical practice, providing both functional and morphological information. The use of DWI can help quantify diffusion using the apparent diffusion coefficient, which reflects the physiological features of the tissue and tumor microcirculation. This knowledge is crucial for understanding and interpreting gynecological imaging. This article reviews the clinical utility of DWI for gynecological imaging, highlighting its ability to aid in the detection of endometrial and cervical cancers, as well as tumor extension and metastasis. In addition, DWI can easily detect the solid components of ovarian cancer (including dissemination), assist in the diagnosis of adnexal torsion, and potentially show bone marrow status. Apparent diffusion coefficient measurement is useful for differentiating between endometrial lesions, uterine leiomyomas, and sarcomas, and may provide important information for predicting the prognosis of gynecological cancers.

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

PURPOSE

This study aimed to compare the variability of the uterus during the menses phase (MP), follicular phase (FP), and luteal phase (LP) of the menstrual cycle using intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI).

METHODS

This prospective study was conducted at the Guangdong Provincial Hospital of Traditional Chinese Medicine between January 2022 and January 2023. Women of childbearing age (18-45 years) with appropriate progesterone levels were included in this study. Conventional magnetic resonance imaging and IVIM-DWI scans were performed during the MP, FP, and LP. The differences in IVIM-DWI-derived parameters between these phases were then compared, and the overlap was quantitatively described.

RESULTS

The apparent diffusion coefficient (ADC) and pure molecular diffusion coefficient (D) values from the endometrium, uterine junctional zone (UJZ), and myometrium indicated statistical differences between the MP and FP and the MP and LP (ADC: endometrium, both P < 0.001; UJZ, P = 0.008 and P < 0.001, respectively; myometrium, P = 0.033 and P = 0.006, respectively; D: endometrium, both P < 0.001; UJZ, P = 0.008 and P = 0.006, respectively; myometrium, P = 0.041 and P = 0.045, respectively). The perfusion-related diffusion coefficient (D*) values from the myometrium indicated statistical differences between the FP and MP and the FP and LP (D*: myometrium, P = 0.049 and P = 0.009, respectively). The overlapping endometrium ratios between the MP and FP or LP were lower than 50% in the ADC and D values (ADC: overlapping of MP and FP: 33.33%, overlapping of MP and LP: 23.33%; D: overlapping of MP and FP: 40.00%, overlapping of MP and LP: 43.33%).

CONCLUSION

The ADC and IVIM-derived parameters indicated differences in the uterus in diverse phases of the menstrual cycle, especially in the endometrium in relation to ADC and D values.

Diagnostic value of the apparent diffusion coefficient in differentiating malignant from benign endometrial lesions

Introduction

Magnetic resonance imaging (MRI) with its innovative techniques, such as diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC), increases the diagnostic accuracy in distinguishing between malignant and benign lesions of the endometrium. The aim of the study was MRI differentiation between malignant and benign endometrial lesions and correlation with histopathological findings with a special emphasis on quantitative analysis. An additional aim was to correlate the ADC values and histological tumor grades.

Methods

The prospective study included 119 female patients with or without vaginal bleeding and pathological values of endometrial thickness, who underwent MRI examinations. According to MRI reports the patients were divided into 45 suspicious malignant and 74 suspicious benign endometrial lesions. The radiological diagnosis was compared to the histopathological evaluation, which confirmed 37 malignant lesions while the rest were benign.

Results

The mean ADC value for malignant lesions was 0.761 ± 0.13×10^-3 mm²/s and for benign lesions was 1.318 ± 0.20×10^-3 mm²/s. The ADC values for malignant lesions were expectedly lower than those of benign lesions (p<0.001). The ADC cut-off value was 1.007×10^-3 mm²/s with a sensitivity of 100%, specificity of 92.7%, a positive predictive value of 60.3%, and a negative predictive value of 100%. In comparison with the histopathological findings, the sensitivity of MRI was 100%, specificity 90.2%, positive predictive value was 82.2%, and negative predictive value was 100%. Observing the histological grades 1, 2, and 3 of endometrial carcinoma, no statistically significant differences of mean ADC values were found. The mean ADC values for histological tumor grades 1,2 and 3 were 0.803 ± 0.13×10^-3 mm²/s, 0.754 ± 0.12×10^-3 mm²/s and 0.728 ± 0.13×10^-3 mm²/s, respectively.

Conclusion

DWI and ADC values represent clinically useful tools for the differentiation between malignant and benign endometrial lesions with high sensitivity and good specificity, but the results failed to demonstrate their usefulness in differentiating histological grades of endometrial cancer.

Diagnostic value of integrated 18F-FDG PET/MRI for staging of endometrial carcinoma: comparison with PET/CT

Purpose

To explore the diagnostic value of integrated positron emission tomography/magnetic resonance imaging (PET/MRI) for the staging of endometrial carcinoma and to investigate the associations between quantitative parameters derived from PET/MRI and clinicopathological characteristics of endometrial carcinoma.

Methods

Altogether, 57 patients with endometrial carcinoma who underwent PET/MRI and PET/computed tomography (PET/CT) preoperatively were included. Diagnostic performance of PET/MRI and PET/CT for staging was compared by three readers. Associations between PET/MRI quantitative parameters of primary tumor lesions and clinicopathological characteristics of endometrial carcinoma were analyzed. Histopathological results were used as the standard.

Results

The overall accuracy of the International Federation of Gynecology and Obstetrics (FIGO) staging for PET/MRI and PET/CT was 86.0% and 77.2%, respectively. PET/MRI had higher accuracy in diagnosing myometrial invasion and cervical invasion and an equivalent accuracy in diagnosing pelvic lymph node metastasis against PET/CT, although without significance. All PET/MRI quantitative parameters were significantly different between stage I and stage III tumors. Only SUV_max/ADC_min were significantly different between stage I and II tumors. No parameters were significantly different between stage II and III tumors. The SUV_max/ADC_min in the receiving operating characteristic (ROC) curve had a higher area under the ROC curve for differentiating stage I tumors and other stages of endometrial carcinoma.

Conclusions

PET/MRI had a higher accuracy for the staging of endometrial carcinoma, mainly for FIGO stage I tumors compared to PET/CT. PET/MRI quantitative parameters, especially SUV_max/ADC_min, were associated with tumor stage and other clinicopathological characteristics. Hence, PET/MRI may be a valuable imaging diagnostic tool for preoperative staging of endometrial carcinoma.

Whole-lesion apparent diffusion coefficient (ADC) histogram as a quantitative biomarker to preoperatively differentiate stage IA endometrial carcinoma from benign endometrial lesions

BACKGROUND

To assess the value of whole-lesion apparent diffusion coefficient (ADC) histogram analysis in differentiating stage IA endometrial carcinoma (EC) from benign endometrial lesions (BELs) and characterizing histopathologic features of stage IA EC preoperatively.

METHODS

One hundred and six BEL and 126 stage IA EC patients were retrospectively enrolled. Eighteen volumetric histogram parameters were extracted from the ADC map of each lesion. The Mann-Whitney U or Student's t-test was used to compare the differences between the two groups. Models based on clinical parameters and histogram features were established using multivariate logistic regression. Receiver operating characteristic (ROC) analysis and calibration curves were used to assess the models.

RESULTS

Stage IA EC showed lower ADC_10th, ADC_90th, ADC_min, ADC_max, ADC_mean, ADC_median, interquartile range, mean absolute deviation, robust mean absolute deviation (rMAD), root mean squared, energy, total energy, entropy, variance, and higher skewness, kurtosis and uniformity than BELs (all p < 0.05). ADC_median yielded the highest area under the ROC curve (AUC) of 0.928 (95% confidence interval [CI] 0.895-0.960; cut-off value = 1.161 × 10^-3 mm²/s) for differentiating stage IA EC from BELs. Moreover, multivariate analysis demonstrated that ADC-score (ADC_10th + skewness + rMAD + total energy) was the only significant independent predictor (OR = 2.641, 95% CI 2.045-3.411; p < 0.001) for stage IA EC when considering clinical parameters. This ADC histogram model (ADC-score) achieved an AUC of 0.941 and a bias-corrected AUC of 0.937 after bootstrap resampling. The model performed well for both premenopausal (accuracy = 0.871) and postmenopausal (accuracy = 0.905) patients. Besides, ADC_min and ADC_10th were significantly lower in Grade 3 than in Grade 1/2 stage IA EC (p = 0.022 and 0.047). At the same time, no correlation was found between ADC histogram parameters and the expression of Ki-67 in stage IA EC (all p > 0.05).

CONCLUSIONS

Whole-lesion ADC histogram analysis could serve as an imaging biomarker for differentiating stage IA EC from BELs and assisting in tumor grading of stage IA EC, thus facilitating personalized clinical management for premenopausal and postmenopausal patients.

Diffusion Weighted Imaging in the Assessment of Tumor Grade in Endometrial Cancer Based on Intravoxel Incoherent Motion MRI

The aim of this study is to investigate the possibility of predicting histological grade in patients with endometrial cancer on the basis of intravoxel incoherent motion (IVIM)-related histogram analysis parameters. This prospective study included 52 women with endometrial cancer (EC) who underwent MR imaging as initial staging in our hospital, allocated into low-grade (G1 and G2) and high-grade (G3) tumors according to the pathology reports. Regions of interest (ROIs) were drawn on the diffusion weighted images and apparent diffusion coefficient (ADC), true diffusivity (D), and perfusion fraction (f) using diffusion models were computed. Mean, median, skewness, kurtosis, and interquartile range (IQR) were calculated from the whole-tumor histogram. The IQR of the diffusion coefficient (D) was significantly lower in the low-grade tumors from that of the high-grade group with an adjusted p-value of less than 5% (0.048). The ROC curve analysis results of the statistically significant IQR of the D yielded an accuracy, sensitivity, and specificity of 74.5%, 70.1%, and 76.5% respectively, for discriminating low from high-grade tumors, with an optimal cutoff of 0.206 (×10⁻³ mm²/s) and an AUC of 75.4% (95% CI: 62.1 to 88.8). The IVIM modeling coupled with histogram analysis techniques is promising for preoperative differentiation between low- and high-grade EC tumors.

Hybrid PET/MRI in Staging Endometrial Cancer: Diagnostic and Predictive Value in a Prospective Cohort

AIM

The assessment of deep myometrial invasion (MI) and lymph node involvement is of utmost importance in the preoperative staging of endometrial cancer (EC). Imaging parameters derived respectively from MRI and PET have shown good predictive value. The main aim of the present study is to assess the diagnostic performance of hybrid 18F-FDG PET/MRI in EC staging, with particular focus on MI and lymphnodal involvement detection.

PATIENTS AND METHODS

Prospective monocentric study including 35 patients with biopsy-proven EC undergoing preoperative 18F-FDG PET/MRI (December 2018-March 2021) for staging purpose. Histological examination was the reference standard. PET (SUVmax, SUVmean with a threshold of 40% of SUVmax-SUVmean40, metabolic tumor volume, total lesion glycolysis) and MRI (volume index [VI], total tumor volume, tumor volume ratio [TVR], mean apparent diffusion coefficient, minimum apparent diffusion coefficient) parameters were calculated on the primary tumor, and their role in predicting EC risk group, the presence of lymphovascular space invasion (LVSI), and MI was assessed. Receiver operating characteristics analysis was used to assess the predictive value of PET and MRI parameters on EC characteristics.

RESULTS

Patients' median age was 66.57 years (SD, 10.21 years). 18F-FDG PET/MRI identified the primary tumor in all patients. Twenty-two of 35 patients had high-risk EC and 13/35 low-risk disease; 13/35 presented LVSI, 22/35 had deep MI at histological examination, and 13/35 had p53 hyperexpression.PET/MRI was able to detect lymphnodal involvement with high accuracy and high specificity (sensitivity of 0.8571, specificity of 0.9286, accuracy of 0.9143), also showing a high negative predictive value (NPV) for lymphnodal involvement (NPV of 0.9630, positive predictive value [PPV] of 0.7500).The assessment of deep MI using PET/MRI correctly staged 27 patients (77.1%; sensitivity of 0.7273, specificity of 0.8462, accuracy of 0.7714), with also a good PPV (PPV of 0.8889, NPV of 0.647).MRI-derived total tumor volume, VI, and TVR were significant in predicting EC groups (high-risk vs low-risk patients) (P = 0.0059, 0.0235, 0.0181, respectively). MRI-derived volume, VI, TVR, and PET-derived metabolic tumor volume and total lesion glycolysis were able to predict LVSI (P = 0.0023, 0.0068, 0.0068, 0.0027, 0.01394, respectively). Imaging was not able to predict grading, presence of deep MI, nor hyperexpression of p53.

CONCLUSIONS

18F-FDG PET/MRI has good accuracy in preoperative staging of EC; PET and MRI parameters have synergic role in preoperatively predicting LVSI, with MRI parameters being also predictive for EC risk group.

Use of diffusion-weighted imaging and diffusion tensor imaging in assessment of myometrial invasion in patients of endometrial carcinoma and its correlation with histopathological grading (Prospective study)

Background

Endometrial cancer (EMC) is considered one of the most common gynecological cancers worldwide. In particular, the depth of myometrial invasion and histological grade of endometrial cancers (EMCs) are strong prognostic factors. Diffusion tensor measurements as mean diffusivity (MD) and fractional anisotropy (FA) values could be useful for assessing the depth of tumor invasion and its histological grade. The study aimed to evaluate the role of diffusion-weighted imaging (DWI) and diffusion tensor imaging in the detection of myometrial invasion in cases of endometrial carcinoma and prediction of its grade in vivo.

Results

This study included 50 female patients with pathologically proved endometrial carcinoma, and their ages ranged from 38 to 67 years; the mean age was 56.15 years (± 8.229 standard deviation “SD”). There was a significant statistical difference regarding the mean values of diffusion tensor fractional anisotropy (DT-FA), diffusion tensor mean diffusivity (DT-MD) and diffusion-weighted apparent diffusion coefficient(DW-ADC) values in differentiating between intact and infiltrated myometrium with (P value ≤ 0.001). The accuracy of DT-MD, DT-FA and DWI-ADC was 98%, 90% and 86%, respectively, in the detection of myometrial invasion. There was a statistically significant difference in the mean values of DT-FA, DT-MD and DW-ADC for differentiating endometrioid adenocarcinoma grades with the overall P values (˂0.001). The accuracy of DT-FA, DT- MD and DWI-ADC for differentiating grade 3 from grade 1 or 2 endometrioid adenocarcinoma was 94.9%, 84.6% and 74.4%, respectively. For differentiating grade 1 from grade 2 or 3 endometrioid adenocarcinoma, the accuracy of DT-FA, DT-MD and DWI-ADC was 90%, 89.7% and 84.6%, respectively. Mean DT-FA, DT-MD and DW-ADC values were inversely proportional to the degree of pathological grading with r =  − 0.867, − 0.762 and − 0.706, respectively.

Conclusion

Diffusion tensor imaging and DWI are helpful in the assessment of myometrial invasion and have a high negative correlation with histopathological grading in patients with endometrial cancer.

Pathological characteristics and risk stratification in patients with stage I endometrial cancer: utility of apparent diffusion coefficient histogram analysis

OBJECTIVES

Accurate pre-operative prediction of risk stratification using a non-invasive imaging tool is clinically important for planning optimal treatment strategies, particularly in early-stage endometrial cancer (EC). This study aimed to investigate the utility of apparent diffusion coefficient (ADC) histogram analysis in evaluating the pathological characteristics and risk stratification in patients with Stage I EC.

METHODS

Between October 2009 and December 2014, a total of 108 patients with surgically proven Stage I EC (endometrioid type = 91; non-endometrioid type = 17) excluding stage ≥II that underwent preoperative 3T-diffusion-weighted imaging without administration of contrast medium were enrolled in this retrospective study. Risk stratification was divided into four risk categories based on the ESMO-ESGO-ESTRO Guidelines: low, intermediate, high-intermediate, and high risk. The ADC histogram parameters (minimum, mean [ADCmean], 10th-90th percentile, and maximum [ADCmax]) of the tumor were generated using an in-house software. The ADC histogram parameters were compared between patients with endometrioid type and non-endometrioid type, between Stage IA and IB, between histological grades, and evaluated for differentiating non-high risk group from high risk group. Inter-reader agreement for tumor ADC measurements was also evaluated. Statistical analyses were performed using the Student's t-test, Mann-Whitney U test, receiver operating characteristics (ROC) analysis, or intraclass correlation coefficient (ICC).

RESULTS

In differentiating endometrioid type from non-endometrioid type EC, all ADC histogram parameters were statistically significant (p < 0.05). In differentiating histological grades, 90th percentile ADC and ADCmax showed significantly higher values in tumor Grade III than in tumor Grade I-II (p < 0.05). In differentiating superficial myometrial invasion from deep myometrial invasion, all ADC histogram parameters were statistically significant (p < 0.05), except ADCmax. In differentiating non-high risk group from high risk group, ADCmean, 75th-90th percentile ADC, and ADCmax were statistically significant (p < 0.05). For predicting the high risk group, the area under the ROC curve of ADCmax was 0.628 and the highest among other histogram parameters. All histogram parameters revealed moderate to good inter-reader reliability (ICC = 0.581‒0.769).

CONCLUSION

The ADC histogram analysis as reproducible tool may be useful for evaluating the pathological characteristics and risk stratification in patients with early-stage EC.

ADVANCES IN KNOWLEDGE

ADC histogram analysis may be useful for evaluating risk stratification in early-stage endometrial cancer patients.

Tumor stiffness measured by 3D magnetic resonance elastography can help predict the aggressiveness of endometrial carcinoma: preliminary findings

Background

Preoperative evaluation of aggressiveness, including tumor histological subtype, grade of differentiation, Federation International of Gynecology and Obstetrics (FIGO) stage, and depth of myometrial invasion, is significant for treatment planning and prognosis in endometrial carcinoma (EC). The purpose of this study was to evaluate whether three-dimensional (3D) magnetic resonance elastography (MRE) can help predict the aggressiveness of EC.

Methods

From August 2015 to January 2019, 82 consecutive patients with suspected uterine tumors underwent pelvic MRI and MRE scans, and 15 patients with confirmed EC after surgical resection were enrolled. According to pathological results (tumor grade, histological subtype, FIGO stage, and myometrial invasiveness), the patients were divided into two subgroups. The independent-samples t-test or Mann-Whitney U test was used to compare the stiffness between different groups. The diagnostic performance was determined with receiver operating characteristic (ROC) curve analysis.

Results

The stiffness of EC with ≥ 50 % (n = 6) myometrial invasion was significantly higher than that with < 50 % (n = 9) myometrial invasion (3.68 ± 0.59 kPa vs. 2.61 ± 0.72 kPa, p = 0.009). Using a stiffness of 3.04 kPa as a cutoff value resulted in 100 % sensitivity and 77.8 % specificity for differentiating ≥ 50 % myometrial invasion from < 50 % myometrial invasion of EC. The stiffness of poorly differentiated EC (n = 8) was significantly higher than that of well/moderately differentiated EC (n = 7) (3.47 ± 0.64 kPa vs. 2.55 ± 0.82 kPa, p = 0.028). Using a stiffness of 3.04 kPa as a cutoff value resulted in 75 % sensitivity and 71.4 % specificity for differentiating poorly differentiated from well/moderately differentiated EC. The stiffness of FIGO stage II/III EC was significantly higher than that of FIGO stage I EC (3.69 ± 0.65 kPa vs. 2.72 ± 0.76 kPa, p = 0.030). Using a stiffness of 3.04 kPa as a cutoff value resulted in 100 % sensitivity and 70 % specificity for differentiating FIGO stage I EC from FIGO stage II/III EC. The tumor stiffness value in type II (n = 3) EC was higher than that in type I (n = 12) EC (3.67 ± 0.59 kPa vs. 2.88 ± 0.85 kPa), but the difference was not significant (p = 0.136).

Conclusions

Tumor stiffness measured by 3D MRE may be potentially useful for predicting tumor grade, FIGO stage and myometrial invasion of EC and can aid in the preoperative risk stratification of EC.

The value of the apparent diffusion coefficient in differentiating type II from type I endometrial carcinoma

BACKGROUND

Diagnostic type II endometrial carcinoma (EC) is considered more aggressive and has a poorer prognosis than type I EC; differentiation between them is helpful for preoperative clinical decision-making. However, the diagnostic value of the apparent diffusion coefficient (ADC) in differentiating them remains unclear.

PURPOSE

To investigate the value of ADC in differentiating type II EC from type I EC.

MATERIAL AND METHODS

Ninety-four patients with EC who underwent diffusion-weighted imaging (DWI) were retrospectively included and divided into type I and type II subgroups, based on the postoperative pathologic results. We analyzed the clinical characteristics, conventional magnetic resonance imaging manifestations, and ADC mean values (ADC_mean), ADC minimum values (ADC_min), and ADC max values (ADC_max). Receiver operating characteristic (ROC) curve analysis was further used to assess the predictive performance.

RESULTS

The ADC_mean, ADC_min, and tumor size differed significantly between the two subtypes. The area under the ROC curve (AUC) for ADC_mean and ADC_min was 0.787 (95% confidence interval [CI] = 0.692-0.88) and 0.835 (95% CI = 0.751-0.919) for predicting type II EC, respectively. The optimal cut-off value of ADC_mean for prediction was 0.757 × 10^-3 mm²/s with a sensitivity of 91%, a specificity of 58%, and an accuracy of 74%, while for ADC_min was 0.637 × 10^-3 mm²/s with a sensitivity of 82%, a specificity of 73%, and an accuracy of 75%.

CONCLUSION

EC with lower ADC_mean and ADC_min values derived from DWI, and a larger size, are indicative of type II EC.

Volumetric ADC histogram analysis for preoperative evaluation of LVSI status in stage I endometrioid adenocarcinoma

OBJECTIVES

To investigate the value of volumetric ADC histogram metrics for evaluating lymphovascular space invasion (LVSI) status in stage I endometrioid adenocarcinoma (EAC).

METHODS

Preoperative MRI of 227 patients with stage I EAC were retrospectively analyzed. ADC histogram data were derived from the whole tumor with ROIs drawn on all slices of DWI scans (b = 0, 1000 s/mm²). The Student t-test was performed to compare ADC histogram metrics (minADC, maxADC, and meanADC; 10th, 25th, 50th, 75th, and 90th percentiles of ADC; skewness; and kurtosis) between the LVSI-positive and LVSI-negative groups, as well as between stage Ia and Ib EACs. ROC curve analysis was carried out to evaluate the diagnostic performance of ADC histogram metrics in predicting LVSI status in EAC.

RESULTS

The minADC and meanADC and 10th, 25th, 50th, 75th, and 90th percentiles of ADC were significantly lower in LVSI-positive EACs compared with those in the LVSI-negative groups for stage I, Ia, and Ib EACs (all p < 0.05). MeanADC ≤ 0.857 × 10^-3 mm²/s, meanADC ≤ 0.854 × 10^-3 mm²/s, and the 90th percentile of ADC ≤ 1.06 × 10^-3 mm²/s yielded the largest AUC of 0.844, 0.844, and 0.849 for evaluating LVSI positivity in stage I, Ia, and Ib tumors, respectively, with sensitivity of 75.4%, 75.0%, and 76.2%; specificity of 80.0%, 83.1%, and 82.1%; and accuracy of 79.3%, 81.5%, and 79.6%, respectively.

CONCLUSION

Volumetric ADC histogram metrics might be helpful for the preoperative evaluation of LVSI status and personalized clinical management in patients with stage I EAC.

KEY POINTS

• Volumetric ADC histogram analysis helps evaluate LVSI status preoperatively. • LVSI-positive EAC is associated with a reduction in multiple volumetric ADC histogram metrics. • MeanADC and the 90th percentile of ADC were shown to be best in evaluating LVSI- positivity in stage Ia and Ib EACs, respectively.

Evaluation of amide proton transfer-weighted imaging for endometrial carcinoma histological features: a comparative study with diffusion kurtosis imaging

OBJECTIVES

To investigate whether amide proton transfer-weighted imaging (APTWI) and diffusion kurtosis imaging (DKI) can be used to evaluate endometrial carcinoma (EC) in terms of clinical type, histological grade, subtype, and Ki-67 index.

METHODS

Eighty-eight patients with EC underwent pelvic DKI and APTWI. The non-Gaussian diffusion coefficient (D_app), apparent kurtosis coefficient (K_app), and magnetization transfer ratio asymmetry (MTRasym (3.5 ppm)) were calculated and compared based on the clinical type (type I, II), histological grade (high- and low-grade), and subtype (endometrioid adenocarcinoma (EA) and non-EA). Correlation coefficients were calculated for each parameter with histological grades and the Ki-67 index.

RESULTS

The MTRasym (3.5 ppm) and K_app values were higher in the type II group and high-grade group than in the type I and low-grade groups, respectively, while the D_app values were lower in the type I and low-grade groups, respectively (all p < 0.05). The K_app value was higher in the EA group than in the non-EA group (p = 0.022). The K_app value was the only independent predictor for the histological grade of EA and the clinical type of EC. The AUC (DKI) was higher than the AUC (APTWI) in the identification of type I and II EC and high- and low-grade EA (Z = 2.042, 2.013, p = 0.041, 0.044), while in the identification of EA and non-EA, only the difference in K_app was statistically significant. Moreover, the K_app and MTRasym (3.5 ppm) values and D_app values correlated positively and negatively, respectively, with histological grade (r = 0.759, 0.555, 0.624, and 0.462, all p < 0.05) and Ki-67 index (r = -0.704, -0.507, all p < 0.05).

CONCLUSION

Both DKI- and APTWI-related parameters have potential as imaging markers in estimating the histological features of EC, while DKI shows better performance than APTWI in this study.

KEY POINTS

• DKI and APTWI can be used to preliminarily evaluate the histological characteristics of endometrial carcinoma (EC). • The K_app was the only independent predictor for the histological grade of EA and the clinical type of EC. • The K_app, MTRasym (3.5 ppm), and D_app correlated positively and negatively, respectively, with histological grade and Ki-67 index.

The apparent diffusion coefficient (ADC) on 3-T MRI differentiates myometrial invasion depth and histological grade in patients with endometrial cancer

BACKGROUND

Diffusion-weighted magnetic resonance imaging (DW-MRI) with apparent diffusion coefficient (ADC) measurement provides additional information about tumor microstructure with potential relevance for staging and predicting aggressive disease in patients with endometrial cancer (EC).

PURPOSE

To determine whether ADC values in EC diverge according to the tumor's histologic grade and myometrial invasion depth.

MATERIAL AND METHODS

A sample of 48 pathologically confirmed cases of EC were reviewed retrospectively. The sample was distributed as follows: G1 (n = 9); G2 (n = 18); G3 (n = 21); with myometrial invasion <50% (n = 31); and with myometrial invasion ≥50% (n = 17). DW images were performed at 3.0T with b factors of 0-1000/mm². The region of interest (ROI) was defined within the tumor with T1-weighted and T2-weighted imaging and copied manually to an ADC map. The tumor's grade and myometrial invasion's depth were determined by postoperative histopathological tests.

RESULTS

The means of ADC_min and ADC_mean values were significantly lower for patients with G2 and G3 endometrial tumors than G1. The same tendency was observed in myometrial invasion, as both ADC_min and ADC_mean values were lower for patients with deep than for those with superficial myometrial invasion. The cut-off values of the ADC_min and ADC_mean that predicted high-grade tumors were 0.69 × 10^-3 mm²/s and 0.82 × 10^-3 mm²/s, respectively, while those for myometrial infiltration were 0.70 × 10^-3 mm²/s (ADC_min) and 0.88 × 10^-3 mm²/s (ADC_mean).

CONCLUSION

ADC_min and ADC_mean values correlated with histologic tumor grade and myometrial invasion depth; therefore, it is suggested that ADC on MRI may be a useful indicator to predict malignancy of ECs.

Quantitative assessment of diffusion kurtosis imaging depicting deep myometrial invasion: a comparative analysis with diffusion-weighted imaging

PURPOSE

We aimed to investigate histogram analysis of diffusion kurtosis imaging (DKI) and conventional diffusion-weighted imaging (DWI) to distinguish between deep myometrial invasion and superficial myometrial invasion in endometrial carcinoma (EC).

METHODS

A total of 118 pathologically confirmed EC patients with preoperative DWI were included. The data were postprocessed with a DKI (b value of 0, 700, 1400, and 2000 s/mm2) model for quantitation of apparent diffusion values (D) and apparent kurtosis coefficient values (K) for non-Gaussian distribution. The apparent diffusion coefficient (ADC) was postprocessed with a conventional DWI model (b values of 0 and 800 s/mm2). A whole-tumor analysis approach was used. Comparisons of the histogram parameters of D, K, and ADC were carried out for the deep myometrial invasion and superficial myometrial invasion subgroups. Diagnostic performance of the imaging parameters was assessed.

RESULTS

The Dmean, D10th, and D90th in deep myometrial invasion group were significantly lower than those in superficial invasion group (P < 0.001, P < 0.001, and P = 0.023, respectively), as well as the ADCmean, ADC10th, and ADC90th (P = 0.001, P = 0.001, and P = 0.042, respectively). The Kmean and K90th were significantly higher in deep invasion group than those in superficial myometrial invasion group (P = 0.002 and P = 0.026, respectively). The D10th, Kmean, and ADC10th had a relatively higher area under the curve (AUC) (0.72, 0.66, and 0.71, respectively) than other parameters for distinguishing deep myometrial invasion of EC. D10th showed a relatively higher AUC than ADC10th for the differentiation of lesions with deep myometrial invasion from those with superficial myometrial invasion (0.72 vs. 0.71), but the variation was not statistically significant (P = 0.35).

CONCLUSION

Distribution of DKI and conventional DWI parameters characterized by histogram analysis may represent an indicator for deep myometrial invasion in EC. Both DKI and DWI models showed relatively equivalent effectiveness.

Utility of diffusion-weighted imaging in association with pathologic upgrading in biopsy-proven grade I endometrial cancer

BACKGROUND

Prediction of pathologic upgrading is clinically meaningful to identify the optimal candidate of fertility-preserving hormonal treatment in the young patients with biopsy-proven grade I endometrial cancer.

PURPOSE

To investigate the utility of diffusion-weighted imaging (DWI) in association with pathologic upgrading in endometrial cancer.

STUDY TYPE

Retrospective.

SUBJECTS

Preoperative MRI datasets of 221 patients with grade I endometrial cancer on endometrial biopsy (n = 146), dilatation and curettage (n = 66), or either (n = 9).

FIELD STRENGTH/SEQUENCE

3.0T, including T2 -weighted imaging, DWI with a b-value of 1000 s/mm2 , and dynamic contrast enhanced imaging.

ASSESSMENT

The tumor size was determined as the longest diameter of the lesion. The minimum apparent diffusion coefficient (ADCmin ) was calculated using histogram analysis of the entire tumor.

STATISTICAL TESTS

Mann-Whitney U-test, Pearson's chi-square test, Fisher's exact test, intraclass correlation coefficient (ICC) analysis, receiver operating characteristic (ROC) curve analysis, univariate and multivariate logistic regression analysis.

RESULTS

Pathologic upgrading was identified in 42 patients (19.0%). Patients with pathologic upgrading had larger tumors and showed lower ADCmin values than those without pathologic upgrading (both P < 0.001). The area under the ROC curve of ADCmin and tumor size was 0.812 and 0.758, respectively. On multivariate analysis, tumor ADCmin ≤0.600 × 10-3 mm2 /s (odds ratio [OR], 11.8; P < 0.001) and tumor size on MRI >3 cm (OR, 3.24; P = 0.009) were independently associated with pathologic upgrading. Upgrading occurred in 23 of 31 patients (74.2%) with ADCmin ≤0.600 × 10-3 mm2 /s and tumor size >3 cm, and in 7 of 114 patients (6.1%) with ADCmin >0.600 × 10-3 mm2 /s and tumor size ≤3 cm.

DATA CONCLUSION

Tumor ADC and tumor size on MRI may be useful parameters in association with pathologic upgrading in biopsy-proven grade I endometrial cancer.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:117-123.

Endometrial Carcinoma: Texture Analysis of Apparent Diffusion Coefficient Maps and Its Correlation with Histopathologic Findings and Prognosis

PURPOSE

To determine the feasibility of texture analysis (TA) of apparent diffusion coefficient (ADC) maps for predicting histologic grade (HG) and recurrence-free survival (RFS) in patients with endometrial carcinoma (EMC).

MATERIALS AND METHODS

One hundred twenty-one patients with EMC were examined by using a 1.5-T MRI system and diffusion-weighted imaging (DWI) 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 analysis was performed to compare the diagnostic performance of the random forest (RF) model and ADC values for HG and recurrence.

RESULTS

Area under the curve (AUC) for predicting high-grade EMCs was significantly larger for RF model than for ADC values (0.967 vs 0.898; P = .0336). AUC for predicting recurrence was larger for the RF model than for ADC values (0.890 vs 0.875; P = .7248), although the difference was not significant. Mean RFS was significantly shorter for high-grade EMCs than for low-grade EMCs (P = .0002; hazard ratio, 4.9) and for ADC values less than or equal to 0.802 × 10^-3 mm²/sec than for ADC values greater than 0.802 × 10^-3 mm²/sec (P < .0001; hazard ratio, 32.9). RF model showed that the mean RFS was significantly shorter for the presence of recurrence than for its absence (P < .0001; hazard ratio, 94.7).

CONCLUSION

TA of ADC maps had significantly higher diagnostic performance than did ADC values for predicting HG and was a more useful indicator than HG and ADC values for predicting RFS in patients with EMC.Keywords: Comparative Studies, Genital/Reproductive, MR-Diffusion Weighted Imaging, MR-Imaging, Neoplasms-Primary, Pathology, Pelvis, Tissue Characterization, Uterus© RSNA, 2019.

Apparent diffusion coefficients measured using different regions of interest in differentiating borderline from malignant ovarian tumors

Background

Apparent diffusion coefficients (ADCs) measured using different regions of interest (ROIs) are widely used in differentiating ovarian tumors.

Purpose

To evaluate the diagnostic performance of ADCs with different ROIs in differentiating borderline ovarian tumors (BOTs) from malignant ovarian tumors (MOTs).

Material and Methods

Thirty-five BOTs and 54 MOTs who underwent diffusion-weighted magnetic resonance imaging (MRI) were evaluated retrospectively. ADC values were independently measured using five ROI methods: round; rectangle; hot-spot; edge drawing; and five sample ROIs. The inter- and intraclass correlation coefficients (ICCs), one-way analysis of variance, receiver operating characteristic curve analysis, and unpaired t-tests were used to perform the statistical analyses.

Results

The measurement reproducibility of the minimum ADC and mean ADC values were good or excellent for BOTs and MOTs (ICC = 0.70–0.95). The minimum and mean ADC value by the edge drawing ROI were significantly higher than those of the other ROI methods (both P < 0.05). The area under the curve (AUC) of the minimum ADC value was less than that of the mean ADC value from the five ROI methods, whereas the AUCs of the mean ADC values from the round ROI and five sample ROIs were significantly larger than those of the other ROI methods ( P < 0.05). The minimum and mean ADC values from the five ROI methods showed significant differences between BOTs and MOTs (all P < 0.05).

Conclusion

The ROI shape influences the diagnostic performance of ADC value for differentiating BOTs from MOTs. The mean ADC values from the round ROI and five sample ROIs have better diagnostic efficiency.

Repeatability analysis of ADC histogram metrics of the uterus

BACKGROUND

Recently, histogram analysis based on voxel-wise apparent diffusion coefficient (ADC) value distribution has been increasingly performed. However, few studies have been reported regarding its repeatability.

PURPOSE

To evaluate the repeatability of ADC histogram metrics of the uterus in clinical magnetic resonance imaging (MRI).

MATERIAL AND METHODS

Thirty-three female patients who underwent pelvic MRI including diffusion-weighted imaging (DWI) were prospectively included after providing informed consent. Two sequential DWI acquisitions with identical parameters and position were obtained. Regions of interest (ROIs) for histologically confirmed uterine lesions (five cervical and three endometrial cancers, and one endometrial hyperplasia) and normal appearing tissues (21 endometrium and 33 myometrium) were assigned on the first DWI dataset and then pasted onto the second DWI dataset. ADC histogram metrics within the ROIs were calculated and repeatability was evaluated by calculating within-subject coefficient of variance (%) (wCV (%)) and Bland-Altman plot (%).

RESULTS

ADC 10%, 25%, median, 75%, 90%, maximum, mean, and entropy showed high repeatability (wCV (%) < 7, 95% limit of agreement in Bland-Altman plot (%) < ±20), followed by ADC minimum (wCV (%) = 8.12, 95% limit of agreement in Bland-Altman plot (%) < ±30). However, ADC skewness and kurtosis showed very low repeatability in all evaluations.

CONCLUSION

ADC histogram metrics like ADC 10%, 25%, median, 75%, 90%, maximum, mean, and entropy are robust biomarkers and could be applicable to clinical use. However, ADC skewness and kurtosis lack robustness. Radiologists should keep these characteristics and limitations in mind when interpreting quantitative DWI.

Utility of the relative apparent diffusion coefficient for preoperative assessment of low risk endometrial carcinoma

OBJECTIVES

Lymphadenectomy is not recommended for low risk stage I endometrial carcinoma (EC) patients. This study was to investigate the predictive value of apparent diffusion coefficient (ADC) values in predicting patients with low risk EC, and to identify an optimum ADC measurement for preoperative assessment.

MATERIALS AND METHODS

Eighty-one patients with stage I EC who underwent diffusion-weighted imaging (DWI) at 1.5T were included and divided into low group and intermediate-high risk group based on the ESMO-ESGO-ESTRO classification. Clinical indexes, conventional MRI parameters, minimum ADC values (minADC), mean ADC values (meanADC) and relative ADC values (rADC) were compared between those two groups. rADC was calculated using the equation ADC (cancer)/ADC (reference) with the obturator internus muscle as reference. The optimal ADC measurement and cut-off ADC value for low risk EC were calculated using the receiver operating characteristic (ROC) curve.

RESULTS

The low risk group had significantly higher meanADC, minADC, and rADC values than did the intermediate-high risk group (1.095 vs. 0.902 × 10^-3 mm²/s, 0.755 vs. 0.657 × 10^-3 mm²/s, 0.754 vs. 0.603, respectively). In assessments of low risk EC patients, the area under the curve (AUC) values for meanADC, minADC, and rADC were 0.840 (95%CI, 0.749,0.931), 0.681 (95% CI: 0.561,0.800), and 0.876(95% CI: 0.798,0.954), respectively. The optimal cut-off rADC value for prediction was 0.669, the maximum Youden index, sensitivity, specificity, and accuracy values were 0.683, 81.8%, 86.5%, and 84.0%, respectively.

CONCLUSIONS

rADC is superior to minADC and meanADC for predicting patients with low risk EC, and could potentially aid to the surgical management of these patients in avoiding unnecessary lymphadenectomy.

Utility of Clinical Parameters and Multiparametric MRI as Predictive Factors for Differentiating Uterine Sarcoma From Atypical Leiomyoma

OBJECTIVES

The objective of this study was to find clinical parameters and qualitative and quantitative magnetic resonance imaging (MRI) features for differentiating uterine sarcoma from atypical leiomyoma (ALM) preoperatively and to calculate predictive values for uterine sarcoma.

MATERIALS AND METHODS

Data from 60 patients with uterine sarcoma and 88 patients with ALM confirmed by surgery and pathology were collected. Clinical parameters, qualitative MRI features, diffusion-weighted imaging with apparent diffusion coefficient values, and quantitative parameters of dynamic contrast-enhanced MRI of these two tumor types were compared. Predictive values for uterine sarcoma were calculated using multivariable logistic regression.

RESULTS

Patient clinical manifestations, tumor locations, margins, T2-weighted imaging signals, mean apparent diffusion coefficient values, minimum apparent diffusion coefficient values, and time-signal intensity curves of solid tumor components were obvious significant parameters for distinguishing between uterine sarcoma and ALM (all P <.001). Abnormal vaginal bleeding, tumors located mainly in the uterine cavity, ill-defined tumor margins, and mean apparent diffusion coefficient values of <1.272 × 10^-3mm²/s were significant preoperative predictors of uterine sarcoma. When the overall scores of these four predictors were greater than or equal to 7 points, the sensitivity, the specificity, the accuracy, and the positive and negative predictive values were 88.9%, 99.9%, 95.7%, 97.0%, and 95.1%, respectively.

CONCLUSIONS

The use of clinical parameters and multiparametric MRI as predictive factors was beneficial for diagnosing uterine sarcoma preoperatively. These findings could be helpful for guiding treatment decisions.

Correlation of Minimum Apparent Diffusion Coefficient and Maximum Standardized Uptake Value of the Primary Tumor with Clinicopathologic Characteristics in Endometrial Cancer

Objective:

To explore the correlation of the primary tumor’s maximum standardized uptake value (SUV_max) and minimum apparent diffusion coefficient (ADC_min) with clinicopathologic features, and to determine their predictive power in endometrial cancer (EC).

Methods:

A total of 45 patients who had undergone staging surgery after a preoperative evaluation with ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography/computerized tomography (PET/CT) and diffusion-weighted magnetic resonance imaging (DW-MRI) were included in a prospective case-series study with planned data collection. Multiple linear regression analysis was used to determine the correlations between the study variables.

Results:

The mean ADC_min and SUV_max values were determined as 0.72±0.22 and 16.54±8.73, respectively. A univariate analysis identified age, myometrial invasion (MI) and lymphovascular space involvement (LVSI) as the potential factors associated with ADC_min while it identified age, stage, tumor size, MI, LVSI and number of metastatic lymph nodes as the potential variables correlated to SUV_max. In multivariate analysis, on the other hand, MI was the only significant variable that correlated with ADC_min (p=0.007) and SUV_max (p=0.024). Deep MI was best predicted by an ADC_min cutoff value of ≤0.77 [93.7% sensitivity, 48.2% specificity, and 93.0% negative predictive value (NPV)] and SUV_max cutoff value of >20.5 (62.5% sensitivity, 86.2% specificity, and 81.0% NPV); however, the two diagnostic tests were not significantly different (p=0.266).

Conclusion:

Among clinicopathologic features, only MI was independently correlated with SUV_max and ADC_min. However, the routine use of ¹⁸F-FDG PET/CT or DW-MRI cannot be recommended at the moment due to less than ideal predictive performances of both parameters.

Magnetic Resonance Imaging of Gynecological Malignancies: Role in Personalized Management

Gynecological malignancies are a leading cause of mortality and morbidity in women and pose a significant health problem around the world. Currently used staging systems for management of gynecological malignancies have unresolved issues, the most important being recommendations on the use of imaging. Although not mandatory as per the International Federation of Gynecology and Obstetrics recommendations, preoperative cross-sectional imaging is strongly recommended for adequate and optimal management of patients with gynecological malignancies. Standardized disease-specific magnetic resonance imaging protocols help assess disease spread accurately and avoid pitfalls. Multiparametric imaging holds promise as a roadmap to personalized management in gynecological malignancies. In this review, we will highlight the role of magnetic resonance imaging in cervical, endometrial, and ovarian carcinomas.

Standardized uptake value and apparent diffusion coefficient of endometrial cancer evaluated with integrated whole-body PET/MR: Correlation with pathological prognostic factors

PURPOSE

To evaluate the correlation between maximum standardized uptake value (SUVmax ) and minimum apparent diffusion coefficient (ADCmin ) of endometrial cancer derived from an integrated positron emission tomography / magnetic resonance (PET/MR) system and to determine their correlation with pathological prognostic factors.

MATERIALS AND METHODS

This prospective study was approved by the Institutional Review Board of the hospital, and informed consent was obtained. Between April and December 2014, 47 consecutive patients with endometrial cancer were enrolled and underwent simultaneous PET/MR examinations before surgery. Thirty-six patients with measurable tumors on PET/MR were included for image analysis. Pearson's correlation coefficient was used to evaluate the correlation between SUVmax and ADCmin of the tumors. The Mann-Whitney U-test was utilized to evaluate relationships between these two imaging biomarkers and pathological prognostic factors.

RESULTS

The mean SUVmax and ADCmin were 14.7 ± 7.1 and 0.48 ± 0.13 × 10(-3) mm(2) /s, respectively. A significant inverse correlation was found between SUVmax and ADCmin (r = -0.53; P = 0.001). SUVmax was significantly higher in tumors with advanced stage, deep myometrial invasion, cervical invasion, lymphovascular space involvement, and lymph node metastasis (P < 0.05). ADCmin was lower in tumors with higher grade, advanced stage, and cervical invasion (P < 0.05). The ratio of SUVmax to ADCmin was higher in tumors with higher grade, advanced stage, deep myometrial invasion, cervical invasion, lymphovascular space involvement, and lymph node metastasis (P < 0.05).

CONCLUSION

SUVmax and ADCmin of endometrial cancer derived from integrated PET/MR are inversely correlated and are associated with pathological prognostic factors.

Prognostic Role of Diffusion-weighted MR Imaging for Resectable Gastric Cancer

PURPOSE

To prospectively investigate the role of apparent diffusion coefficient (ADC) calculated from diffusion-weighted magnetic resonance (MR) imaging as a potential prognostic biomarker in the evaluation of the aggressiveness of gastric cancer.

MATERIALS AND METHODS

This prospective study had institutional review board approval. Informed consent was obtained from all patients. Between October 2009 and December 2013, a total of 99 patients (65 men, 34 women; mean age, 62.02 years; age range, 32.33-85.15 years) with biopsy-proved cancer (28 esophagogastric junction and 71 gastric cancers) were examined with a 1.5-T MR imaging system, including T1-, T2-, and diffusion-weighted sequences. ADC measurements were obtained. Seventy-one patients were directly treated with surgery, while 28 underwent neoadjuvant chemotherapy beforehand. Pathologic ADC, pathologic T and N stages, tumor location, surgical approach, and histologic subtype were investigated with univariate and multivariate analyses by using the Cox regression model.

RESULTS

At a total median follow-up period of 21 months, 31 patients had died. The median follow-up was 25 months for the surgery-only group (19 of 31 events [61%]) and 28 months for the chemotherapy group (12 of 31 events [39%]). In the multivariate analysis, ADC values of 1.5 × 10(-3) mm(2)/sec or lower were associated with a negative prognosis, both in the total population (log-relative risk, 1.73; standard error, 0.56; P = .002) and in the surgery-only (log-relative risk, 1.97; standard error, 0.66; P = .003) and chemotherapy (log-relative risk, 2.93; standard error, 1.41; P = .03) groups, along with other significant prognostic factors (in particular, pathologic T and N stages).

CONCLUSION

Pathologic ADC represents a strong independent prognostic factor in the evaluation of the aggressiveness of gastric cancer, in addition to clinical and surgical variables.

Usefulness of DWI in preoperative assessment of deep myometrial invasion in patients with endometrial carcinoma: a systematic review and meta-analysis

BACKGROUND

The objective of this study was to perform a systematic review and a meta-analysis in order to estimate the diagnostic accuracy of diffusion weighted imaging (DWI) in the preoperative assessment of deep myometrial invasion in patients with endometrial carcinoma.

METHODS

Studies evaluating DWI for the detection of deep myometrial invasion in patients with endometrial carcinoma were systematically searched for in the MEDLINE, EMBASE, and Cochrane Library from January 1995 to January 2014. Methodologic quality was assessed by using the Quality Assessment of Diagnostic Accuracy Studies tool. Bivariate random-effects meta-analytic methods were used to obtain pooled estimates of sensitivity, specificity, diagnostic odds ratio (DOR) and receiver operating characteristic (ROC) curves. The study also evaluated the clinical utility of DWI in preoperative assessment of deep myometrial invasion.

RESULTS

Seven studies enrolling a total of 320 individuals met the study inclusion criteria. The summary area under the ROC curve was 0.91. There was no evidence of publication bias (P = 0.90, bias coefficient analysis). Sensitivity and specificity of DWI for detection of deep myometrial invasion across all studies were 0.90 and 0.89, respectively. Positive and negative likelihood ratios with DWI were 8 and 0.11 respectively. In patients with high pre-test probabilities, DWI enabled confirmation of deep myometrial invasion; in patients with low pre-test probabilities, DWI enabled exclusion of deep myometrial invasion. The worst case scenario (pre-test probability, 50%) post-test probabilities were 89% and 10% for positive and negative DWI results, respectively.

CONCLUSION

DWI has high sensitivity and specificity for detecting deep myometrial invasion and more importantly can reliably rule out deep myometrial invasion. Therefore, it would be worthwhile to add a DWI sequence to the standard MRI protocols in preoperative evaluation of endometrial cancer in order to detect deep myometrial invasion, which along with other poor prognostic factors like age, tumor grade, and LVSI would be useful in stratifying high risk groups thereby helping in the tailoring of surgical approach in patient with low risk of endometrial carcinoma.