Diffusion-weighted imaging in the assessment of tumour grade in endometrial cancer

Updated endometrial cancer FIGO staging: the role of MRI in determining newly included histopathological criteria

PURPOSE

Endometrial cancer (EC) is among the prevalent malignancies in gynecology, showing an increasing occurrence and mortality rate. The updated 2023 FIGO staging integrates both histopathological and molecular analyses, which significantly impact the prognosis and treatment approaches. This research aims to examine the effectiveness of MRI in identifying essential histopathological tumor features, including histological subtype, grade, and lymphovascular space invasion.

METHODS

A total of 106 patients diagnosed with EC from February 2018 to December 2023 underwent preoperative pelvic MRI. Surgical procedures followed ESMO guidelines, with histopathological assessments using FIGO 2009 criteria. Two radiologists independently evaluated MRI images, measuring maximum tumor size, minimum tumor ADC value (using a free-hand ROI technique), and ADC tumor/myometrium ratio. MRI findings were compared with histopathological data.

RESULTS

Peritoneal implant presence and tumor size exhibited significant differences between endometrioid adenocarcinoma (EAC) and non-endometrioid endometrial carcinoma (NEEC), with p values of < 0.001 and 0.003, respectively. Significant differences in age, tumor size, ADC tumor, and ADC tumor/myometrium between low-grade and high-grade tumors were observed, with p values of < 0.001, 0.004, 0.006, and 0.011, respectively. Increased tumor size, reduced ADC tumor, ADC tumor/myometrium, and pelvic peritoneal implant presence were significantly associated with LVSI, with p values of < 0.001, 0.001, 0.002, and 0.001, respectively. The AUC values for tumor size, ADC tumor, and ADC tumor/myometrium were 0.842, 0.781 and 0.747, respectively, in distinguishing between low and high-grade endometrial tumors. Similarly, obtained AUC values for predicting LVSI were 0.836, 0.719, and 0.696, respectively.

CONCLUSION

Our study emphasizes MRI's role in predicting tumor characteristics such as histological subtype, grade, and LVSI based on updated FIGO criteria. By highlighting the potential of MRI, this research contributes to our comprehension of improving diagnostic and clinical management for EC. Further multicenter studies are warranted to validate these findings and establish MRI's role in EC management.

Can the ADC Value Be Used as an Imaging "Biopsy" in Endometrial Cancer?

BACKGROUND

The tumor histological grade is closely related to the prognosis of patients with endometrial cancer (EC). Multiparametric MRI, including diffusion-weighted imaging (DWI), provides information about the cellular density that may be useful to differentiate between benign and malignant uterine lesions. However, correlations between apparent diffusion coefficient (ADC) values and histopathological grading in endometrial cancer remain controversial.

MATERIAL AND METHODS

We retrospectively evaluated 92 patients with endometrial cancers, including both endometrioid adenocarcinomas (64) and non-endometrioid adenocarcinomas (28). All patients underwent DWI procedures, and mean ADC values were calculated in a region of interest. These values were then correlated with the tumor grading offered by the histopathological examination, which was considered the gold standard. In this way, the patients were divided into three groups (G1, G2, and G3). The ADC values were then compared to the results offered by the biopsy to see if the DWI sequence and ADC map could replace this procedure. We also compared the mean ADC values to the myometrial invasion (50%) and lymphovascular space invasion.

RESULTS

We have divided the ADC values into three categories corresponding to three grades: >0.850 × 10-3 mm2/s (ADC1), 0.730-0.849 × 10-3 mm2/s (ADC2) and <0.730 × 10-3 mm2/s (ADC3). The diagnostic accuracy of the ADC value was 85.71% for ADC1, 75.76% for ADC2, and 91.66% for ADC3. In 77 cases out of 92, the category in which they were placed using the ADC value corresponded to the result offered by the histopathological exam with an accuracy of 83.69%. For only 56.52% of patients, the biopsy result included the grading system. For each grading category, the mean ADC value showed better results than the biopsy; for G1 patients, the mean ADC value had an accuracy of 85.71% compared to 66.66% in the biopsy, G2 had 75.76% compared to 68.42%, and G3 had 91.66 compared to 75%. For both deep myometrial invasion and lymphovascular space invasion, there is a close, inversely proportional correlation with the mean ADC value.

CONCLUSIONS

Mean endometrial tumor ADC on MR-DWI is inversely related to the histological grade, deep myometrial invasion and lymphovascular space invasion. Using this method, the patients could be better divided into risk categories for personalized treatment.

Imaging of Endometrial Cancer

Endometrial cancer is the most common gynecologic cancer in the United States and Europe, with an increasing incidence rate in high-income countries. MR imaging is recommended for treatment planning because it provides critical information on the extent of myometrial and cervical invasion, extrauterine spread, and lymph node status, all of which are important in the selection of the most appropriate therapy. This article highlights the added value of imaging, focused on MR imaging, in the assessment of endometrial cancer and summarizes the role of MR imaging for endometrial cancer risk stratification and management.

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.

Tissue Characteristics of Endometrial Carcinoma Analyzed by Quantitative Synthetic MRI and Diffusion-Weighted Imaging

BACKGROUND

This study investigates the association of T1, T2, proton density (PD) and the apparent diffusion coefficient (ADC) with histopathologic features of endometrial carcinoma (EC).

METHODS

One hundred and nine EC patients were prospectively enrolled from August 2019 to December 2020. Synthetic magnetic resonance imaging (MRI) was acquired through one acquisition, in addition to diffusion-weighted imaging (DWI) and other conventional sequences using 1.5T MRI. T1, T2, PD derived from synthetic MRI and ADC derived from DWI were compared among different histopathologic features, namely the depth of myometrial invasion (MI), tumor grade, cervical stromal invasion (CSI) and lymphovascular invasion (LVSI) of EC by the Mann-Whitney U test. Classification models based on the significant MRI metrics were constructed with their respective receiver operating characteristic (ROC) curves, and their micro-averaged ROC was used to evaluate the overall performance of these significant MRI metrics in determining aggressive histopathologic features of EC.

RESULTS

EC with MI had significantly lower T2, PD and ADC than those without MI (p = 0.007, 0.006 and 0.043, respectively). Grade 2-3 EC and EC with LVSI had significantly lower ADC than grade 1 EC and EC without LVSI, respectively (p = 0.005, p = 0.020). There were no differences in the MRI metrics in EC with or without CSI. Micro-averaged ROC of the three models had an area under the curve of 0.83.

CONCLUSIONS

Synthetic MRI provided quantitative metrics to characterize EC with one single acquisition. Low T2, PD and ADC were associated with aggressive histopathologic features of EC, offering excellent performance in determining aggressive histopathologic features of EC.

Update on MRI in Evaluation and Treatment of Endometrial Cancer

Endometrial cancer is the second most common gynecologic cancer worldwide and the most common gynecologic cancer in the United States, with an increasing incidence in high-income countries. Although the International Federation of Gynecology and Obstetrics (FIGO) staging system for endometrial cancer is a surgical staging system, contemporary published evidence-based data and expert opinions recommend MRI for treatment planning as it provides critical diagnostic information on tumor size and depth, extent of myometrial and cervical invasion, extrauterine extent, and lymph node status, all of which are essential in choosing the most appropriate therapy. Multiparametric MRI using a combination of T2-weighted sequences, diffusion-weighted imaging, and multiphase contrast-enhanced imaging is the mainstay for imaging assessment of endometrial cancer. Identification of important prognostic factors at MRI improves both treatment selection and posttreatment follow-up. MRI also plays a crucial role for fertility-preserving strategies and in patients who are not surgical candidates by helping guide therapy and identify procedural complications. This review is a product of the Society of Abdominal Radiology Uterine and Ovarian Cancer Disease-Focused Panel and reflects a multidisciplinary international collaborative effort to summarize updated information highlighting the role of MRI for endometrial cancer depiction and delineation, treatment planning, and follow-up. The article includes information regarding dedicated MRI protocols, tips for MRI reporting, imaging pitfalls, and strategies for image quality optimization. The roles of MRI-guided radiation therapy, hybrid PET/MRI, and advanced MRI techniques that are applicable to endometrial cancer imaging are also discussed. Online supplemental material is available for this article. ^©RSNA, 2022.

The Value of First-Order Features Based on the Apparent Diffusion Coefficient Map in Evaluating the Therapeutic Effect of Low-Intensity Pulsed Ultrasound for Acute Traumatic Brain Injury With a Rat Model

Purpose

In order to evaluate the neuroprotective effect of low-intensity pulsed ultrasound (LIPUS) for acute traumatic brain injury (TBI), we studied the potential of apparent diffusion coefficient (ADC) values and ADC-derived first-order features regarding this problem.

Methods

Forty-five male Sprague Dawley rats (sham group: 15, TBI group: 15, LIPUS treated: 15) were enrolled and underwent magnetic resonance imaging. Scanning layers were acquired using a multi-shot readout segmentation of long variable echo trains (RESOLVE) to decrease distortion. The ultrasound transducer was applied to the designated region in the injured cortical areas using a conical collimator and was filled with an ultrasound coupling gel. Regions of interest were manually delineated in the center of the damaged cortex on the diffusion weighted images (b = 800 s/mm²) layer by layer for the TBI and LIPUS treated groups using the open-source software ITK-SNAP. Before analysis and modeling, the features were normalized using a z-score method, and a logistic regression model with a backward filtering method was employed to perform the modeling. The entire process was completed using the R language.

Results

During the observation time, the ADC values ipsilateral to the trauma in the TBI and LIPUS groups increased rapidly up to 24 h. After statistical analysis, the 10th percentile, 90th percentile, mean, skewness, and uniformity demonstrated a significant difference among three groups. The receiver operating characteristic curve (ROC) analysis shows that the combined LR model exhibited the highest area under the curve value (AUC: 0.96).

Conclusion

The combined LR model of first-order features based on the ADC map can acquire a higher diagnostic performance than each feature only in evaluating the neuroprotective effect of LIPUS for TBI. Models based on first-order features may have potential value in predicting the therapeutic effect of LIPUS in clinical practice in the future.

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.

Diagnostic accuracy of calculated tumor volumes and apparent diffusion coefficient values in predicting endometrial cancer grade

Background:

Magnetic resonance imaging (MRI) has been shown to be an accurate imaging technique for the preoperative assessment of local staging of endometrial cancer and for evaluating the depth of myometrial invasion.

Materials and Methods:

This was a single-center retrospective study performed on patients with histopathologically proven endometrial carcinoma who underwent an MRI examination of the pelvis between October 2017 and May 2020.

Results:

In the present analysis, mean apparent diffusion coefficient (ADC) values for each histologic grade were 0.72 ± 0.13 × 10⁻³ mm²/s (G1), 0.76 ± 0.17 × 10⁻³ mm²/s (G2), and 0.74 ± 0.12 × 10⁻³ mm²/s (G3), respectively, showing no significant correlation between ADC values and tumor grade (P = 0.73). Overall, ADC minimum was significant in differentiating grades of endometrial carcinoma (P = 0.02) with the ability to differentiate Grade I and II lesions (P = 0.01). A mean tumor volume of 25.2 cc could differentiate low-grade tumors (Grade I and Grade II) from high-grade tumors (Grade III) with a sensitivity and specificity of 88% and specificity of 89%. The tumor volume/uterine volume ratio (TV/UV) differentiates high-grade tumors from low-grade tumors (P < 0.001), however, no significant difference in the ratio was observed among Grade I and II lesions (P = 0.48). The area under the curve of tumor volume was 0.875 (95% confidence interval 0.0–1.00) (P = 0.001), indicating that tumor volume was an effective tool for distinguishing high-grade and low-grade endometrioid adenocarcinomas. The corresponding sensitivity and specificity were 88.0% and 89.0%, respectively.

Conclusion:

Preoperative noninvasive radiological assessment for tumor volume, TV/ UV or tumor volume/uterine volume is important surrogate markers for preoperative prognostication of endometrial carcinoma.

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.

Synergic role of preoperative 18F-fluorodeoxyglucose PET and MRI parameters in predicting histopathological features of endometrial cancer

BACKGROUND

The aim of the present study is to explore the correlation between PET and MRI parameters of primary tumour and clinicopathological features and to determine their synergic predictive role in patients with endometrial cancer candidate to surgery.

METHODS

Retrospective study including 27 patients with endometrial cancer and preoperative 18F-fluorodeoxyglucose (18F-FDG)-PET and MRI scan. The following parameters, calculated on the primary tumour, were used for analysis: maximum standardized uptake value (SUVmax), SUVmean, metabolic tumour volume (MTV) and total lesion glycolysis (TLG) for PET scans; mean apparent diffusion coefficient (ADCmean) and volume index for MRI scans. FIGO stage, grade, histotype, lymphovascular space invasion (LVSI) and myometrial invasion were the considered clinicopathological features.

RESULTS

MRI volume index was a good predictor for deep myometrial invasion [area under the curve (AUC) = 0.85; P = 0.003] and for LVSI (AUC = 0.74; P = 0.039). A cutoff value of 9.555 for MRI volume index was predictive for deep myometrial invasion (sensitivity = 84.6%; specificity = 76.9%); a cutoff of 12.165 was predictive for LVSI (sensitivity = 69.2%; specificity = 83.3%). A TLG cutoff value of 26.03 was predictive for deep myometrial invasion (sensitivity = 84.6%; specificity = 76.9%). A high-direct correlation was found with MRI volume index (rho = 0.722; P < 0.001); low-direct correlation with SUVmax (rho = 0.484; P = 0.012), SUVmean (rho = 0.47; P = 0.015) and TLG (rho = 0.482; P = 0.013) were identified. The SUVmax/ADCmean ratio showed a low-direct correlation with percentage of myometrial invasion (rho = 0.467; P = 0.016).

CONCLUSION

Volume index, TLG and SUVmax/ADCmean ratio are associated with deep myometrial invasion. As myometrial invasion is the index used to predict lymph node involvement in endometrial cancer, the synergic use of these imaging parameters may be suggested to predict lymphnodal metastases.

The role of volumetric ADC histogram analysis in preoperatively evaluating the tumour subtype and grade of endometrial cancer

PURPOSE

To assess the value of volumetric ADC histogram metrics in evaluating the histological subtype and grade of endometrial cancer.

METHOD

Preoperative MRI datasets of 317 patients with endometrial cancer were used to obtain volumetric ADC histogram metrics (tumour volume; minADC, maxADC and meanADC; 10th, 25th, 50th, 75th and 90th percentiles of ADC; skewness; and kurtosis). The Mann-Whitney test or Student's t-test was used to compare the difference in ADC histogram metrics between endometrioid adenocarcinomas (EACs) and serous endometrial cancers (SECs) and between different tumour grades (G1, G2, G3). The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate the performance of ADC histogram metrics or combined models in predicting the tumour subtype and grade.

RESULTS

SECs showed a significantly larger tumour volume (P < 0.001) and lower meanADC, 50th, 75th and 90th percentiles of ADC than EACs (all P < 0.05). MinADC, maxADC, meanADC, 10th, 25th, 50th, 75th, 90th percentiles of ADC were significantly higher in G1 than in G2 and G3 EACs (all P < 0.05), while were not significantly different between G2 and G3 EACs (all P > 0.05). A tumour volume ≥ 7.752 cm³ allowed for the prediction of SECs, with an AUC of 0.765 (0.714-0.810). A meanADC ≥ 0.892 × 10^-3  mm²/s enabled to discriminate G1 from G2 and G3 EACs, with an AUC of 0.818 (0.769-0.861).

CONCLUSION

Volumetric ADC histogram analysis is helpful for non-invasive preoperatively predicting the subtype of endometrial cancer and differentiating G1 from G2 and G3 EACs.

Diagnostic performance of apparent diffusion coefficient (ADC) for differentiating endometrial carcinoma from benign lesions: a systematic review and meta-analysis

To determine the diagnostic performance of mean ADC values in the characterization of endometrial carcinoma (EC) from benign lesions by systematic review of the literature and performing meta-analysis. A systematic search of major electronic bibliographic databases was performed to find studies that used ADC values for differentiating EC from benign lesions. Two reviewers independently screened the titles and abstracts of the search results and then by reading the full texts selected the pertinent studies for final analyses. A bivariate random-effects model with pooled sensitivity and specificity values with 95% CI (confidence interval) was used. Summary receiver operating characteristic (SROC) curve and area under curve (AUC) were created. Between-study heterogeneity was measured using I squared (I2) index. Eleven studies including 269 ECs and 208 benign lesions were analyzed. Pooled average (95% CI) ADC in EC and benign lesions groups were, respectively, 0.82 (0.77-0.87) × 10-3 mm2/s and 1.41 (1.29-1.52) × 10-3 mm2/s. The combined (95% CI) sensitivity and specificity of mean ADC values for differentiating EC from benign lesions were 93% (87-96%; I2 = 41.19%) and 94% (88-97%; I2 = 46.91%), respectively. The AUC (95% CI) of the SROC curve was 98% (96-99%). ADC values had good diagnostic accuracy for differentiating EC from benign lesions. In order to recommend ADC measurement for detecting endometrial lesions in routine clinical practice, more primary studies, especially trials and comparative studies including hysteroscopically-guided biopsy method, with larger sample sizes are still required.

Magnetic resonance scoring system for assessment of adnexal masses: added value of diffusion-weighted imaging including apparent diffusion coefficient map

OBJECTIVES

To validate prospectively the ADNEX magnetic resonance (MR) scoring system to assess adnexal masses and to evaluate a new, modified ADNEX MR scoring system that incorporates diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping.

METHODS

Between January 2015 and September 2018, 323 consecutive women with adnexal masses diagnosed on transvaginal ultrasound (TVS) underwent standardized MR imaging (MRI) including diffusion and dynamic contrast-enhanced sequences. Of these, 131 underwent subsequent surgery. For interpretation of the MRI examinations, we applied the five-category ADNEX MR scoring system, along with a modified scoring system including DWI with ADC mapping. For both scoring systems, a score was given for all adnexal masses. Histological diagnosis was considered as the gold standard and lesions were classified as benign or malignant. The difference between the predictive values for diagnosing malignancy of the classical and modified scoring systems was assessed on the basis of the areas under the receiver-operating-characteristics (AUC) curves. The sensitivity and specificity for diagnosing malignancy of each score were also calculated.

RESULTS

Among the 131 women with adnexal mass(es) diagnosed on TVS who underwent MRI and subsequent surgery, the surgery revealed 161 adnexal masses in 126 women; five women had no mass. Histological examination confirmed 161 adnexal masses, of which all had been detected on MRI: 32 malignant tumors, 15 borderline tumors, which were classified as part of the malignant group (n = 47), and 114 benign lesions. The AUC for prediction of a malignant lesion was 0.938 (95% CI, 0.902-0.975) using the classical ADNEX MR scoring system and 0.974 (95% CI, 0.953-0.996) using the modified scoring system. Pairwise comparison of these AUCs revealed a significant difference (P = 0.0032). The sensitivity and specificity for diagnosing malignancy with an ADNEX MR score of 4 or more were 95.5% and 86.6%, respectively, using the classic scoring system, and 95.7% and 93.3%, respectively, using the modified scoring system.

CONCLUSION

DWI with ADC mapping could be integrated into the ADNEX MR scoring system to improve specificity, thereby potentially optimizing clinical management by avoiding unnecessary surgery. © 2020 International Society of Ultrasound in Obstetrics and Gynecology.

Is the standard deviation of the apparent diffusion coefficient a potential tool for the preoperative prediction of tumor grade in endometrial cancer?

BACKGROUND

The tumor histological grade is closely related to the prognosis of endometrial cancer (EC). The use of the apparent diffusion coefficient (ADC), tumor volume, and MRI-based texture analysis has allowed exciting advances in predicting EC grade before surgery. However, whether this constitutes a simple, convenient, and powerful diagnostic method remains unknown.

PURPOSE

To explore the utility of standard deviation (SD) of the ADC (ADC_SD) for predicting the tumor grade in patients with EC.

MATERIAL AND METHODS

We retrospectively evaluated 138 patients with EC. All patients underwent unenhanced MRI and diffusion-weighted imaging (DWI). The mean ADC value (ADC_mean) and SD were obtained using a freehand region of interest traced on the ADC map. Spearman's linear correlation coefficients were calculated to analyze the correlations between the indexes (including ADC_SD and the ADC_mean) and the Ki-67 index. The Kruskal-Wallis and Mann-Whitney U tests were used to compare differences in the index results among tumor grades.

RESULTS

A significant difference in ADC_SD was observed among the tumor grades (P=0.000), and the ADC_SD value was significantly higher for high-grade EC than for low-grade tumors (289.7 vs. 216.3×10^-6mm² /s, P=0.000). A statistically significant positive correlation was observed between ADC_SD and the Ki-67 index (r=0.364, P=0.000). According to the receiver operating characteristic curve, ADC_SD ≥240.2×10^-6mm² /s predicted high-grade EC with a sensitivity, specificity, and accuracy of 73.1%, 80.2%, and 77.5%, respectively.

CONCLUSION

Based on the intratumor heterogeneity of EC, ADC_SD represents a potential method for the preoperative prediction of high-grade EC, although further studies are needed.

Normalized apparent diffusion coefficient: a novel paradigm for characterization of endometrial and subendometrial lesions

OBJECTIVES

To assess the role of normalized apparent diffusion coefficient (ADC) in characterization of endometrial and subendometrial masses, measured as a ratio of the mean ADC of the pathology to mean ADC of two different internal controls, normal myometrium and gluteus maximus muscle, referred to as nADC_m and nADC_g respectively.

METHODS

55 females with pathologically proven endometrial and subendometrial lesions, including 27 cases of endometrial carcinoma, and 28 cases of benign masses were enrolled in this prospective study and assessed with single-shot echoplanar diffusion-weighted imaging. The normalized and absolute ADC of the lesions, measured by two radiologists, were compared in different pathologies and receiver operating characteristics (ROC) performed to distinguish benign and malignant endometrial masses. In the endometrial carcinoma group, the ADC values were further compared with tumor grade and subtype.

RESULTS

There was good interobserver agreement (>0.800) for both internal controls, however it was higher for myometrium [intraclass correlation coefficient-0.92; confidence interval (0.86-0.95)] than gluteus maximus muscle [ICC-0.84; CI (0.72-0.90)]. There were statistically significant differences in absolute ADC (p-0.02), nADC_m (p-0.02) and nADC_g (p < 0.0001) of benign and malignant endometrial masses.

CONCLUSION

Normalized ADC is useful to distinguish benign and malignant masses with comparable accuracy as absolute ADC.

ADVANCES IN KNOWLEDGE

Normalized ADC represents an easily measurable quantitative parameter which limits the influence of endogenous and exogenous factors that affect its reproducibility.

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.

The diagnostic performance of ADC value for tumor grade, deep myometrial invasion and lymphovascular space invasion in endometrial cancer: a meta-analysis

BACKGROUND

Disputes exist regarding whether the apparent diffusion coefficient (ADC) can differentiate the tumor grade, deep myometrial invasion and lymphovascular space invasion (LVSI) in endometrial cancer. The aim of this review was to assess the diagnostic performance of the ADC value in endometrial cancer.

MATERIAL AND METHODS

The PubMed, Web of Science, Embase and Cochrane Library databases were searched for studies that used the ADC value to assess tumor grade, deep myometrial invasion and LVSI in endometrial cancer. We used forest plots to analyze the heterogeneity and generate the pooled sensitivity (SEN) and specificity (SPE). We used summary receiver operating characteristic (SROC) curves to work out the area under the SROC curve (AUC). Likelihood ratios (LRs) were also obtained.

RESULTS

Of the 460 identified studies, 11 studies met our inclusion criteria and were included. Overall, nine studies (491 patients) aimed at differentiating high tumor grade had a pooled SEN, SPE and AUC of 77%, 73% and 81%, respectively; three studies (181 patients) for differentiating deep myometrial invasion had a pooled SEN, SPE and AUC of 71%, 67% and 77%, respectively; and two studies (106 patients) for differentiating LVSI had a pooled SEN and SPE of 66% and 74%, respectively. The positive and negative LRs were 2.77 and 0.35 for the tumor grade, 2.08 and 0.45 for deep myometrial invasion, and 2.48 and 0.45 for LVSI.

CONCLUSION

This meta-analysis showed that the ADC value had a moderate diagnostic performance for the tumor grade, deep myometrial invasion and LVSI in endometrial cancer.

Assessment of Early Therapeutic Response to Nitroxoline in Temozolomide-Resistant Glioblastoma by Amide Proton Transfer Imaging: A Preliminary Comparative Study with Diffusion-weighted Imaging

Amide proton transfer (APT) imaging is a novel molecular MRI technique to detect endogenous mobile proteins and peptides through chemical exchange saturation transfer. In this preliminary study, the purpose was to evaluate the feasibility of APT imaging in monitoring the early therapeutic response to nitroxoline (NTX) in a temozolomide (TMZ)-resistant glioblastoma multiforme (GBM) mouse model, which was compared with diffusion-weighted imaging (DWI). Here, we prepared TMZ-resistant GBM mouse model (n = 12), which were treated with 100 mg/kg/day of NTX (n = 4) or TMZ (n = 4), or saline (n = 4) for 7 days for the evaluation of short-term treatment by using APT imaging and DWI sequentially. The APT signal intensities and apparent diffusion coefficient (ADC) values were calculated and compared before and after treatment. Moreover, immunohistological analysis was also employed for the correlation between APT imaging and histopathology. The association between the APT value and Ki-67 labeling index was evaluated by using simple linear regression analysis. The short-term NTX treatment resulted in significant decrease in APT value as compared to untreated and TMZ group, in which APT signals were increased. However, we did not observe significantly increased mean ADC value following short-term NTX treatment. The Ki-67 labeling index shows a correlation with APT value. APT imaging could show the earlier response to NTX treatment as compared to ADC values in a TMZ-resistant mouse model. We believe that APT imaging can be a useful imaging biomarker for the early therapeutic evaluation in GBM patients.

Comparative analysis of the value of diffusion kurtosis imaging and diffusion-weighted imaging in evaluating the histological features of endometrial cancer

Purpose

This study evaluated and compared the performances of diffusion kurtosis imaging (DKI) and diffusion-weighted imaging (DWI) for diagnosing and histologically grading endometrial cancer.

Materials and methods

In this retrospective study, DKI and DWI data for 61 patients with endometrial cancer and 30 patients with a normal endometrium were analyzed, and the mean kurtosis (MK), mean diffusion coefficient (MD) and apparent diffusion coefficient (ADC) values for the endometrial cancer tissue and normal endometrial tissue were acquired. The parameters for the normal endometrium group (G0) and the endometrial cancer groups (G1, G2 and G3) were compared and analyzed. The receiver operating characteristic (ROC) curve was used to evaluate each parameter’s diagnostic accuracy and threshold. Spearman correlation analysis was used to analyze the correlations between all parameters and histological grades.

Results

The MK values for the G0, G1, G2 and G3 groups increased gradually, while the MD and ADC values decreased gradually. Except for the differences in the ADC values between G0 and G1, the differences among the groups were statistically significant (P < 0.05). The MK values had the highest diagnostic accuracy in differentiating G0 and (G1 + G2 + G3), G0 and G1, G1 and G2, and G2 and G3 (AUC = 0.93, 0.76, 0.91, 0.91, P < 0.05). MK was maximally correlated with histological grade, followed by MD and ADC (MK > MD > ADC; r = − 0.85, + 0.82, + 0.76, P < 0.01).

Conclusion

Both DKI and DWI can be used to evaluate the diagnosis and histological grading of endometrial cancer. Compared with DWI, the DKI model is a more complete mathematical model with more sensitive parameters, which can more effectively evaluate the pathological and physiological characteristics of endometrial cancer.

The ability of ADC measurements in the assessment of patients with stage I endometrial carcinoma based on three risk categories

BACKGROUND

Better selection of patients with intermediate and high-risk stage I endometrial carcinoma (EC) for lymphadenectomy has an important effect on the prognosis.

PURPOSE

To investigate the role of apparent diffusion coefficient (ADC) measurements in the assessment of stage I EC patients based on three risk categories.

MATERIAL AND METHODS

We retrospectively studied 80 patients with EC and 28 cervical cancer patients with normal endometrium. 1.5-T conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) (b = 0, 1000 s/mm²) were performed, and ADC values were calculated. Sixty-eight stage I EC patients were divided into three groups: low-risk EC (group 1); intermediate-risk EC (group 2); and high-risk EC (group 3). The remaining 12 EC patients were in stages II and III. Intraclass coefficient, Mann-Whitney U test, Kruskal-Wallis test, and receiver operating characteristics were used for statistical analysis.

RESULTS

The mean ADC values ( × 10^-3 mm² /s) were 0.851 ± 0.131, 0.734 ± 0.108, and 0.710 ± 0.108 for groups 1, 2 and 3, respectively. Significant statistical differences were achieved for the three groups ( P = 0.0005). The mean ADC values of group 1 were significantly lower than those in group 2 + 3 (0.725 ± 0.106; P = 0.0001). For the prediction of groups 2 + 3, the area under the curve of 0.786 and the cut-off value of ≤ 0.742 were identified, with a sensitivity, specificity, and accuracy of 66.67%, 84.09%, and 73.53%, respectively.

CONCLUSION

ADC measurements may have the potential to select intermediate-risk and high-risk stage I EC patients for lymphadenectomy.

Preoperative diffusion-weighted magnetic resonance imaging and intraoperative frozen sections for predicting the tumor grade in endometrioid endometrial cancer

Objective

The histological tumor grade is a strong predictor of nodal metastasis in endometrial cancer; as such, an accurate pre- or intraoperative diagnosis is important for performing lymphadenectomy.

Methods

Ninety-one patients with endometrioid endometrial cancer were imaged on DW-MRI with the apparent diffusion coefficient (ADC) calculated and a frozen section (FS) diagnosis made before and at hysterectomy. The diagnostic accuracy for predicting the tumor grade for diffusion weighted magnetic resonance inaging (DW-MRI) and the FS diagnosis compared to the ultimate histologic status was analyzed.

Results

Among 91 patients with endometrioid endometrial cancer, high-grade (endometrioid G3) tumors had lower ADC values than low-grade (endometrioid G1/2) tumors. The cut-off of the mean ADC_mean values for predicting high-grade tumors resulted in 743×10^-6 mm²/sec according to the receiver operating characteristic curve. The true positive rates of ADC values and FSs for the prediction of high-grade tumors did not differ to a statistically significant extent (73.3% vs. 66.7%, p=0.7), however, the true negative rate of ADC values for the prediction of low-grade tumors was significantly lower than that of the FSs (64.5% vs. 98.7%, p=0.01). The kappa statistics of ADC values and FSs were 0.23 and 0.73, respectively. Of note, all five patients with high-grade tumors for whom intraoperative FSs indicated low-grade tumors were predicted to have high-grade tumors on preoperative DW-MRI.

Conclusion

A FS diagnosis is more suitable for predicting high-grade tumors than DW-MRI; however, physicians should pay close attention to tumors with low ADC values on preoperative DW-MRI.

Evaluation and validation of the diagnostic value of the apparent diffusion coefficient for differentiating early-stage endometrial carcinomas from benign mimickers at 3T MRI

Previous researchers obtained various apparent diffusion coefficient (ADC) cutoff values to differentiate endometrial carcinoma from benign mimickers with 1.5T magnetic resonance imaging (MRI). Few studies have used 3T MRI or validated the effectiveness of these cutoff ADC values prospectively. This study was designed in two stages to obtain a cutoff ADC value at 3T MRI and to validate prospectively the role of the ADC value. First, we conducted a retrospective study of 60 patients to evaluate the diagnostic value of ADC by obtain a theoretical cutoff ADC value for differentiating between benign and malignant endometrial lesions. Student's t test revealed that ADC values for stage I endometrial carcinomas were significantly lower than those for benign lesions. The area under the curve value of the receiver operating characteristic curve was 0.993, and the cutoff ADC value was 0.98 × 10-3 mm2/s. The sensitivity, specificity, and overall accuracy of diagnosing stage I endometrial carcinoma were 100%, 97.1%, and 98.3%, respectively. Second, we conducted a prospective study of 26 patients to validate the use of the cutoff ADC value obtained in the study's first stage. The sensitivity, specificity, and overall accuracy for differentiating malignant from benign endometrial lesions based on the cutoff ADC value obtained earlier were as follows: radiologist 1 attained 86.67%, 100.0%, and 92.31%, respectively; radiologist 2 attained 86.67%, 91.0%, and 88.5%, respectively. Our results suggest that ADC values could be a potential biomarker for use as a quantitative and qualitative tool for differentiating between early-stage endometrial carcinomas and benign mimickers.

Can the apparent diffusion coefficient differentiate the grade of endometrioid adenocarcinoma and the histological subtype of endometrial cancer?

Background Diffusion-weighted imaging (DWI) provides useful information for the identification of benign and malignant uterine lesions. However, the use of the apparent diffusion coefficient (ADC) for histopathological grading of endometrial cancer is controversial. Purpose To explore the use of ADC values in differentiating the preoperative tumor grading of endometrioid adenocarcinomas and investigate the relationship between the ADC values of endometrial cancer and the histological tumor subtype. Material and Methods We retrospectively evaluated 98 patients with endometrial cancers, including both endometrioid adenocarcinomas (n = 80) and non-endometrioid adenocarcinomas (n = 18). All patients underwent DWI procedures and ADC values were calculated. The Kruskal-Wallis test and the independent samples Mann-Whitney U test were used to compare differences in the ADC values between different tumor grades and different histological subtypes. Results The mean ADC values (ADCmean) for high-grade endometrioid adenocarcinomas were significantly lower than the values for low-grade tumors (0.800 versus 0.962 × 10^-3 mm²/s) ( P = 0.002). However, no significant differences in ADCmean and minimum ADC values (ADCmin) were found between tumor grades (G1, G2, and G3) of endometrial cancer. Compared with endometrioid adenocarcinomas, the adenocarcinoma with squamous differentiation showed lower ADC values (mean/minimum = 0.863/0.636 versus 0.962/0.689 × 10^-3 mm²/s), but the differences were not significant ( P_mean = 0.074, P_min = 0.441). Moreover, ADCmean for carcinosarcomas was significantly higher than the value for G3 non-carcinosarcoma endometrial cancers (1.047 versus 0.823 × 10^-3 mm²/s) ( P = 0.001). Conclusion The ADCmean was useful for identifying high-grade and low-grade endometrioid adenocarcinomas. Additionally, squamous differentiation may decrease ADCmean and ADCmin of endometrioid adenocarcinoma, and carcinosarcomas showed relatively high ADCmean.

Application of non-Gaussian water diffusional kurtosis imaging in the assessment of uterine tumors: A preliminary study

OBJECTIVES

To evaluate the interobserver reliability and value of diffusional kurtosis imaging (DKI) in the assessment of uterine tumors compared with those of conventional diffusion-weighted imaging (DWI).

METHODS

This retrospective study was approved by our institutional review board, which waived the requirement for informed consent. Fifty-eight women (mean age: 55.0 ± 13.6 years; range: 30-89 years) with suspected malignant uterine tumors underwent 3-T magnetic resonance imaging using DKI and DWI. Twelve had coexisting leiomyoma. Two observers analyzed region-of-interest measurements of diffusivity (D), kurtosis (K), and the apparent diffusion coefficient (ADC) of uterine lesions and healthy adjacent tissues. Interobserver agreement was evaluated using the intra-class correlation coefficient (ICC). The mean values were compared using one-way analysis of variance with a post-hoc Tukey's honestly significant difference test. The diagnostic accuracy of D and ADC in differentiating malignant tumors from benign leiomyomas was analyzed using receiver operating characteristic (ROC) analysis.

RESULTS

The ICCs between the two observers in evaluating D, K, and the ADC of the malignant tumors were higher than 0.84, suggesting excellent interobserver agreements. The mean D (×10-3 mm2/s) of uterine cancers (1.05 ± 0.41 and 1.09 ± 0.40 for observers 1 and 2, respectively) were significantly lower than those of leiomyoma (1.40 ± 0.37 and 1.56 ± 0.33, respectively; P < 0.05), healthy myometrium (1.72 ± 0.27 and 1.69 ± 0.30, respectively; P < 0.001), and healthy endometrium (1.53 ± 0.35 and 1.42 ± 0.37, respectively; P < 0.005). There was no significant difference in the area under the ROC curve between D and ADC. The mean K of uterine cancers (0.88 ± 0.28 and 0.90 ± 0.23, respectively) were higher than those of myometrium (0.72 ± 0.10 and 0.73 ± 0.10, respectively; P < 0.001), healthy endometrium (0.65 ± 0.13 and 0.60 ± 0.18, respectively; P < 0.001), and leiomyoma (0.76 ± 0.14 and 0.77 ± 0.16, respectively; not significant, P > 0.1).

CONCLUSIONS

Interobserver agreements in evaluating D, K, and ADC were moderate to excellent. D performed equally to conventional DWI in differentiating between benign and malignant uterine lesions. The mean K of malignant uterine lesions was significantly higher than that of non-tumorous myometrium or endometrium.

Diffusion-weighted MRI and intravoxel incoherent motion model for diagnosis of pediatric solid abdominal tumors

Background

Pediatric retroperitoneal tumors in the renal bed are often large and heterogeneous, and their diagnosis based on conventional imaging alone is not possible. More advanced imaging methods, such as diffusion‐weighted (DW) MRI and the use of intravoxel incoherent motion (IVIM), have the potential to provide additional biomarkers that could facilitate their noninvasive diagnosis.

Purpose

To assess the use of an IVIM model for diagnosis of childhood malignant abdominal tumors and discrimination of benign from malignant lesions.

Study Type

Retrospective.

Population

Forty‐two pediatric patients with abdominal lesions (n = 32 malignant, n = 10 benign), verified by histopathology.

Field Strength/Sequence

1.5T MRI system and a DW‐MRI sequence with six b‐values (0, 50, 100, 150, 600, 1000 s/mm²).

Assessment

Parameter maps of apparent diffusion coefficient (ADC), and IVIM maps of slow diffusion coefficient (D), fast diffusion coefficient (D*), and perfusion fraction (f) were computed using a segmented fitting model. Histograms were constructed for whole‐tumor regions of each parameter.

Statistical Tests

Comparison of histogram parameters of and their diagnostic performance was determined using Kruskal–Wallis, Mann–Whitney U, and receiver‐operating characteristic (ROC) analysis.

Results

IVIM parameters D* and f were significantly higher in neuroblastoma compared to Wilms' tumors (P < 0.05). The ROC analysis showed that the best diagnostic performance was achieved with D* 90^th percentile (area under the curve [AUC] = 0.935; P = 0.002; cutoff value = 32,376 × 10⁻⁶ mm²/s) and f mean values (AUC = 1.00; P < 0.001; cutoff value = 14.7) in discriminating between neuroblastoma (n = 11) and Wilms' tumors (n = 8). Discrimination between tumor types was not possible with IVIM D or ADC parameters. Malignant tumors revealed significantly lower ADC, D, and higher D* values than in benign lesions (all P < 0.05).

Data Conclusion

IVIM perfusion parameters could distinguish between malignant childhood tumor types, providing potential imaging biomarkers for their diagnosis.

Level of Evidence: 4

Technical Efficacy: Stage 2

J. Magn. Reson. Imaging 2018;47:1475–1486.

Role of Imaging in Fertility-sparing Treatment of Gynecologic Malignancies

Treatments for gynecologic cancer usually result in loss of fertility due to surgery or radical radiation therapy in the pelvis. In countries with an established screening program for cervical cancer, the majority of gynecologic malignancies occur in postmenopausal women. However, a substantial number of affected women are of childbearing age and have not completed their families. In these younger women, consideration of fertility preservation may be important. This article describes the fertility-sparing treatment options that are currently available and outlines the role of imaging in the selection of eligible patients on the basis of a review of the literature. In the setting of cervical cancer, magnetic resonance (MR) imaging is used to delineate the size, position, and stage of the tumor for selection of patients who are suitable for radical trachelectomy. In patients with solitary complex adnexal masses, diffusion- and perfusion-weighted MR imaging sequences are used to categorize the likelihood of invasive or borderline malignancy for consideration of unilateral ovarian resection, with fertility preservation when possible. In patients with endometrial cancer, MR imaging is used to rule out signs of invasive disease before hormone therapy is considered. Imaging is also used at patient follow-up to detect recurrent disease; however, evidence to support this application is limited. In conclusion, imaging is an essential tool in the care of patients with gynecologic malignancies who are considering fertility-preserving treatment options. ^©RSNA, 2016.

Diffusion-weighted imaging in gynaecological malignancy

Diffusion weighted imaging (DWI) has become an essential part of the gynaecological magnetic resonance imaging (MRI) protocol. DWI is used as an adjunct to conventional MRI sequences and has been shown to improve reporting accuracy in the imaging of gynaecological malignancy. In this review, we discuss the role of DWI in the diagnosis, staging, and assessment of treatment response of endometrial, cervical, and ovarian cancer. We also review the role of DWI in the assessment of the sonographically indeterminate ovarian lesion. Further, we highlight potential pitfalls that can beset the accurate interpretation of DWI in patients with gynaecological malignancy.

Role of diffusion-weighted MRI in the differential diagnosis of endometrioid and non-endometrioid cancer of the uterus

Background Many publications have examined the relationship between apparent diffusion coefficient (ADC) values and tumor grade in endometrial cancer. Nevertheless, none were designed to evaluate according to the histopathological type of endometrioid and non-endometrioid tumors. Purpose To evaluate the role of diffusion-weighted imaging (DWI) in the differential diagnosis of endometrioid and non-endometrioid cancer of the uterus, by comparing them with contrast-enhanced magnetic resonance imaging (MRI) findings. Material and Methods Institutional review board approval and informed consent were obtained. The MRI findings of 63 patients with endometrial cancer were retrospectively evaluated and divided into four groups: Grades I, II, and III endometrioid tumors, and non-endometrioid tumors. ADC values, DWI quotients ( b = 1000 s/mm²), and post-contrast signal intensities between lesions and the myometrium (b1000q-Cq values) were evaluated. The one-way-ANOVA, student's t-test, Kruskal-Wallis test, and receiver operating characteristic (ROC) analysis were used for statistical evaluation. Results Mean ADC values were 0.86 ± 0.14 in Grade I, 0.80 ± 0.7 in Grade II, 0.71 ± 0.14 in Grade III for endometrioid tumors, and 0.70 ± 0.12 in non-endometrioid tumors. There was a significant difference in ADC values between Grade I and Grade III ( P = 0.006), and non-endometrioid tumors ( P = 0.003). The difference was also significant between Grades I + II and Grade III ( P = 0.009), and non-endometrioid tumors ( P = 0.004). Besides, there was a significant difference between endometrioid and non-endometrioid tumors ( P = 0.022). However, when considering b1000q (F = 0.640, P = 0.593) and Cq (χ²= 6.233; P = 0.101), no significant difference was detected among the groups. Conclusion The difference in ADC values between the endometrioid and non-endometrioid tumors was statistically significant. However, the difference in DWI and contrast-enhancement findings were not statistically significant. Furthermore, the mean ADC values had an inverse relationship with tumor grade in the endometrioid cancer group.

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.

Functional MR Imaging in Gynecologic Cancer

Dynamic-contrast enhanced (DCE) and diffusion-weighted (DW) MR imaging are invaluable in the detection, staging, and characterization of uterine and ovarian malignancies, for monitoring treatment response, and for identifying disease recurrence. When used as adjuncts to morphologic T2-weighted (T2-W) MR imaging, these techniques improve accuracy of disease detection and staging. DW-MR imaging is preferred because of its ease of implementation and lack of need for an extrinsic contrast agent. MR spectroscopy is difficult to implement in the clinical workflow and lacks both sensitivity and specificity. If used quantitatively in multicenter clinical trials, standardization of DCE- and DW-MR imaging techniques and rigorous quality assurance is mandatory.

Diffusion-weighted magnetic resonance imaging in cancer: Reported apparent diffusion coefficients, in-vitro and in-vivo reproducibility

There is considerable disparity in the published apparent diffusion coefficient (ADC) values across different anatomies. Institutions are increasingly assessing repeatability and reproducibility of the derived ADC to determine its variation, which could potentially be used as an indicator in determining tumour aggressiveness or assessing tumour response. In this manuscript, a review of selected articles published to date in healthy extra-cranial body diffusion-weighted magnetic resonance imaging is presented, detailing reported ADC values and discussing their variation across different studies. In total 115 studies were selected including 28 for liver parenchyma, 15 for kidney (renal parenchyma), 14 for spleen, 13 for pancreatic body, 6 for gallbladder, 13 for prostate, 13 for uterus (endometrium, myometrium, cervix) and 13 for fibroglandular breast tissue. Median ADC values in selected studies were found to be 1.28 × 10(-3) mm(2)/s in liver, 1.94 × 10(-3) mm(2)/s in kidney, 1.60 × 10(-3) mm(2)/s in pancreatic body, 0.85 × 10(-3) mm(2)/s in spleen, 2.73 × 10(-3) mm(2)/s in gallbladder, 1.64 × 10(-3) mm(2)/s and 1.31 × 10(-3) mm(2)/s in prostate peripheral zone and central gland respectively (combined median value of 1.54×10(-3) mm(2)/s), 1.44 × 10(-3) mm(2)/s in endometrium, 1.53 × 10(-3) mm(2)/s in myometrium, 1.71 × 10(-3) mm(2)/s in cervix and 1.92 × 10(-3) mm(2)/s in breast. In addition, six phantom studies and thirteen in vivo studies were summarized to compare repeatability and reproducibility of the measured ADC. All selected phantom studies demonstrated lower intra-scanner and inter-scanner variation compared to in vivo studies. Based on the findings of this manuscript, it is recommended that protocols need to be optimised for the body part studied and that system-induced variability must be established using a standardized phantom in any clinical study. Reproducibility of the measured ADC must also be assessed in a volunteer population, as variations are far more significant in vivo compared with phantom studies.

Diffusion volume (DV) measurement in endometrial and cervical cancer: A new MRI parameter in the evaluation of the tumor grading and the risk classification

PURPOSE

A new MRI parameter representative of active tumor burden is proposed: diffusion volume (DV), defined as the sum of all the voxels within a tumor with apparent diffusion coefficient (ADC) values within a specific range. The aims of the study were: (a) to calculate DV on ADC maps in patients with cervical/endometrial cancer; (b) to correlate DV with histological grade (G) and risk classification; (c) to evaluate intra/inter-observer agreement of DV calculation.

MATERIALS AND METHODS

Fifty-three patients with endometrial (n=28) and cervical (n=25) cancers underwent pelvic MRI with DWI sequences. Both endometrial and cervical tumors were classified on the basis of G (G1/G2/G3) and FIGO staging (low/medium/high-risk). A semi-automated segmentation procedure was used to calculate the DV. A freehand closed ROI outlined the whole visible tumor on the most representative slice of ADC maps defined as the slice with the maximum diameter of the solid neoplastic component. Successively, two thresholds were generated on the basis of the mean and standard deviation (SD) of the ADC values: lower threshold (LT="mean minus three SD") and higher threshold (HT="mean plus one SD"). The closed ROI was expanded in 3D, including all the contiguous voxels with ADC values in the range LT-HT × 10-3mm(2)/s. A Kruskal-Wallis test was used to assess the differences in DV among G and risk groups. Intra-/inter-observer variability for DV measurement was analyzed according to the method of Bland and Altman and the intraclass-correlation-coefficient (ICC).

RESULTS

DV values were significantly different among G and risk groups in both endometrial (p<0.05) and cervical cancers (p ≤ 0.01). For endometrial cancer, DV of G1 (mean ± sd: 2.81 ± 3.21 cc) neoplasms were significantly lower than G2 (9.44 ± 9.58 cc) and G3 (11.96 ± 8.0 cc) ones; moreover, DV of low risk cancers (5.23 ± 8.0 cc) were significantly lower than medium (7.28 ± 4.3 cc) and high risk (14.7 ± 9.9 cc) ones. For cervical cancer, DV of G1 (0.31 ± 0.13 cc) neoplasms was significantly lower than G3 (40.68 ± 45.65 cc) ones; moreover, DV of low risk neoplasms (6.98 ± 8.08 cc) was significantly lower than medium (21.7 ± 17.13 cc) and high risk (62.9 ± 51.12 cc) ones and DV of medium risk neoplasms was significantly lower than high risk ones. The intra-/inter-observer variability for DV measurement showed an excellent correlation for both cancers (ICC ≥ 0.86).

CONCLUSIONS

DV is an accurate index for the assessment of G and risk classification of cervical/endometrial cancers with low intra-/inter-observer variability.