Diffusion-weighted MRI in the differential diagnosis of uterine endometrial cavity tumors

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.

The Preeminent Value of the Apparent Diffusion Coefficient in Assessing High-Risk Factors and Prognosis for Stage I Endometrial Carcinoma Patients

Objectives

To evaluate the role of the apparent diffusion coefficient (ADC) value in the individualized management of stage I endometrial carcinoma (EC).

Methods

A retrospective analysis was performed on 180 patients with stage I EC who underwent 1.5-T magnetic resonance imaging. The mean ADC (mADC), minimum ADC (minADC), and maximum ADC (maxADC) values of each group were measured and compared. We analyzed the relationship between ADC values and stage I EC prognosis by Kaplan-Meier method and Cox proportional hazards analysis.

Results

Patients with lower ADC values were more likely to be characterized by higher grades, specific histological subtypes and deeper myometrial invasion. The mADC, minADC and maxADC values (×10^-3 mm²/s) were 1.045, 0.809 and 1.339, respectively, in grade 1/2 endometrioid carcinoma with superficial myometrial invasion, which significantly differed from those in grade 3 or nonendometrioid carcinoma or with deep myometrial invasion (0.929, 0.714 and 1.215) (P=<0.001, <0.001 and <0.001). ADC values could be used to predict these clinicopathological factors. Furthermore, the group with higher ADC values showed better disease-free survival and overall survival.

Conclusions

The present study indicated that ADC values were associated with the high-risk factors for stage I EC and to assess whether fertility-sparing, ovarian preservation or omission of lymphadenectomy represent viable treatment options. Moreover, this information may be applied to predict prognosis. Thus, ADC values could contribute to managing individualized therapeutic schedules to improve quality of life.

Uterine leiomyomas revisited with review of literature

Uterine leiomyomas, more commonly known as fibroids, are the most common neoplasms of the uterus. These tumors have a profound effect on health care and cost worldwide. Depending on the race, uterine leiomyomas can be seen in 70-80% of all women. Although majority of the women with uterine leiomyomas remain asymptomatic, approximately 30% can present with symptoms. Diagnosing typical leiomyomas on imaging is straightforward. However, when large, located extrauterine and especially with degeneration, the diagnosis can be challenging on imaging. In this article, apart from reviewing the demographics and management of patients with leiomyomas, we describe in detail the imaging appearance of various atypical leiomyomas, uncommon locations outside the uterus and their important differential diagnosis that can have a profound effect on patient management.

The prominent value of apparent diffusion coefficient in assessing high-risk factors and prognosis for patients with endometrial carcinoma before treatment

BACKGROUND

To date, there are no consensus methods to evaluate the high-risk factors and prognosis for managing the personalized treatment schedule of patients with endometrial carcinoma (EC) before treatment. Apparent diffusion coefficient (ADC) is regarded as a kind of technique to assess heterogeneity of malignant tumor.

PURPOSE

To explore the role of ADC value in assessing the high-risk factors and prognosis of EC.

MATERIAL AND METHODS

A retrospective analysis was made on 185 patients with EC who underwent 1.5-T magnetic resonance imaging (MRI). Mean ADC (mADC), minimum ADC (minADC), and maximum ADC (maxADC) were measured and compared in different groups.

RESULTS

Among the 185 patients with EC, the mADC and maxADC values in those with high-risk factors (type 2, deep myometrial invasion, and lymph node metastasis) were significantly lower than in those without. According to receiver operating characteristic (ROC) curve analysis, the areas under the curve (AUC) were significant for mADC, minADC, and maxADC predicting high-risk factors. Furthermore, the AUCs were significant for mADC and maxADC predicting lymph node metastasis but were not significant for minADC. Patients with lower mADC were associated with worse overall survival and disease-free survival; the opposite was true for patients with higher mADC.

CONCLUSION

Our study showed that ADC values could be applied to assess the high-risk factors of EC before treatment and might significantly relate to the prognosis of EC. It might contribute to managing initial individualized treatment schedule and improve outcome in patients with EC.

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.

The value of clinical parameters combined with magnetic resonance imaging (MRI) features for preoperatively distinguishing different subtypes of uterine sarcomas: An observational study (STROBE compliant)

To investigate clinical parameters combined with magnetic resonance imaging (MRI) features including apparent diffusion coefficient (ADC) values in preoperative identification of different subtypes of uterine sarcomas including uterine leiomyosarcoma (LMS), endometrial stromal sarcoma (ESS), and carcinosarcoma (CS).Data from 71 patients with uterine sarcoma confirmed by surgery and pathology were collected. The clinical characteristics, conventional MRI features, mean ADC values, minimum ADC values, and lesion-muscle ADC ratio (rADC) values were compared with different subtypes of uterine sarcomas.Age, clinical manifestation, tumor location, shape, and T1-weighted image (T1WI) signals were significantly different between CS and LMS or ESS (all P < .01). The presence of band sign was significantly higher in ESS than in LMS or CS (both P < .001). The cystic change or necrosis and enhancement could help to differentiate LMS from ESS or CS (both P < .02). Significant differences were observed in T2-weighted image (T2WI) signals of the solid components of LMS compared with CS (P < .001). There was a significant difference between ESS and CS in the rADC values (P = .004).Clinical parameters combined with MRI features could help narrowing preoperative diagnostic possibilities in distinguishing subtypes of uterine sarcomas. These findings may be beneficial in helping guide operative decisions.

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.

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.

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.

Volumetric segmentation of ADC maps and utility of standard deviation as measure of tumor heterogeneity in soft tissue tumors

PURPOSE

Determine interobserver concordance of semiautomated three-dimensional volumetric and two-dimensional manual measurements of apparent diffusion coefficient (ADC) values in soft tissue masses (STMs) and explore standard deviation (SD) as a measure of tumor ADC heterogeneity.

RESULTS

Concordance correlation coefficients for mean ADC increased with more extensive sampling. Agreement on the SD of tumor ADC values was better for large regions of interest and multislice methods. Correlation between mean and SD ADC was low, suggesting that these parameters are relatively independent.

CONCLUSION

Mean ADC of STMs can be determined by volumetric quantification with high interobserver agreement. STM heterogeneity merits further investigation as a potential imaging biomarker that complements other functional magnetic resonance imaging parameters.