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DOI: 10.1055/s-0045-1809903
The Role of Apparent Diffusion Coefficient in Differentiating Benign and Malignant Endometrial Pathologies: A Prospective Single-Center Study
Funding None.
Abstract
Purpose
To investigate the added role of apparent diffusion coefficient (ADC) in differentiating benign from malignant pathologies.
Materials and Methods
Hospital-based random sampling was done and all the females with clinical details suggestive of endometrial pathologies and abnormal ultrasound underwent contrast-enhanced magnetic resonance imaging (MRI). In addition to the routine sequences, imaging was done at different b-values and ADC was calculated. The higher the ADC value the more the chances of benignity. Dynamic contrast-enhanced imaging was also done. Two radiologists with 18 and 10 years of experience evaluated the imaging findings and interobserver agreement was also made. Imaging findings were correlated with diagnosis as made by endometrial aspirate biopsy, dilatation–curettage, or postoperative histopathological examination.
Results
The addition of ADC value and dynamic contrast-enhanced MRI showed a significant role in differentiating benign from malignant conditions. The mean ADC measurement in malignant lesions was 0.88 × 10−3 ± 0.27 × 10−3, whereas the mean ADC measurement for benign lesions was 1.03 × 10−3 ± 0.38 × 10−3. The differences between the two were found to be significant (t-value: 2.754, p-value: 0.014). The cutoff of mean ADC and minimum ADC with the highest sensitivity and specificity were reported to be ≤1 × 10−3 and ≤0.8 × 10−3, respectively.
Conclusion
Adding the ADC value with routine magnetic resonance sequences plays a significant role in differentiating between benign and malignant endometrial pathologies, especially in indeterminate cases
Introduction
Pathologies of the endometrium range widely and represent a varied spectrum of disorders, including various benign and malignant conditions. Benign conditions include hyperplasia, polyp, and submucosal fibroid. Malignant conditions range from hyperplasia to carcinoma with different histopathological variants comprising adenocarcinoma, squamous cell, and endometrioid carcinoma. Ultrasound pelvis is the initial investigation that reveals thickening and contour irregularity with or without mass; nonetheless, it can be challenging to differentiate between benign and malignant pathologies. Contrast-enhanced magnetic resonance imaging (CEMRI) is the investigation of choice for pelvic pathology; however, differentiation between benign and malignant is not always possible. Further, endometrial alterations during various phases of menstruation can complicate the diagnosis. The final diagnosis is the endometrial curettage and biopsy; however, due to the invasive nature, associated complications, and difficulty in cases of vaginal stenosis, there is noncompliance of patients; therefore, the diagnosis in these patients remains uncertain in 2 to 28% of the patients.[1]
The primary role of imaging is to differentiate benign conditions from malignant ones due to their different management approach. CEMRI plays a significant role in the diagnosis nonetheless; the diagnosis remains uncertain in some cases. Apparent diffusion coefficient (ADC) map and ADC value, which are computed using diffusion-weighted (DW) sequences at different b-values, aid in the diagnosis of indeterminate cases. The primary aim of our study is to differentiate benign from malignant endometrial pathologies. Apart from the classification into benign and malignant, subclassification of the benign conditions, and the histological grading of endometrial cancers were also predicted depending on the ADC value. Previous studies have been done on the importance of ADC values in differentiating benign from malignant endometrial pathologies; however, predicting the malignant behavior of endometrial cancers and subclassification of benign pathologies has never been studied before. Knowledge of the aggressive nature of the malignant lesion has various clinical implications including planning the management and the modification of treatment.
Materials and Methods
After obtaining approval from the Ethics Committee (AIIMS/IEC/20/56), a dynamic contrast MRI of the pelvis was performed on all the patients, depending on the inclusion and exclusion criteria. Females in the age group 18 to 70 years with abnormal vaginal bleeding who gave consent for the same were included. Females on hormonal therapy, with deranged renal function tests, who were not willing for the study, and patients in whom MRI was contraindicated were excluded from the study. Methodology is outlined in the flowchart ([Fig. 1]).
A hospital-based random sampling of endometrial pathologies was considered. A total of forty benign and malignant cases were recruited for the study. They underwent routine tests, following which a transabdominal or transvaginal ultrasound was performed on all the cases. The physical profile of the participants was noted, and clinical descriptions of the disease were recorded. The cases have had symptoms of vaginal bleeding as a primary complaint. Three patients with hematometra, two with DW images of insufficient quality, and three with no histopathological correlation were excluded. Therefore, a total of 32 patients were taken. All MRIs were done on a 3-Tesla machine (Discovery 750w GE United States). Pelvic MRI was done using a body coil, and various sequences were planned according to the European Society of Urogenital Radiology guidelines and were as follows,[2] and various sequences were done as follows: sagittalT2W, coronal T2W non-FS, and FS, axial T2WFS, axial T1 W, and noncontrast axial T1 W FS . DW imaging was performed using different b-values from 0 to 800 (10, 20, 40, 80, 120, 160, 200, 300, 600, and 800) in axial plane. For dynamic contrast MRI, gadobenate was administered intravenously at 0.1 to 0.2 mmol/kg body weight dosage pre- and postcontrast T1 fat-saturated spoiled gradient (live acquisition with volume acquisition sequence) images were acquired in axial plane every 10 seconds for a duration of 5 minutes in dynamic CEMRI.
Postcontrast T1 FS sagittal and axial sequences were also taken. The DWIs were correlated with conventional magnetic resonance (MR) images for better anatomical localization of the endometrial lesion. DWIs were planned in axial plane according to the lesion site.
The entire procedure took 20 minutes. ADC value was computed using ADW (Advantage workstation) software. The pattern of contrast enhancement was also evaluated in patients, and graphs were plotted using ADW software.
Image Analysis
Two radiologists with 18 and 10 years of experience in MRI evaluated the MR images together. The following imaging characteristics were taken into account to reach the final diagnosis: T1 and T2 signal characteristics, pattern of contrast enhancement, invasion into the myometrium, and ADC value. ADC value was calculated by placing a circular region of interest (ROI) over the enhancing solid component of the lesion while avoiding necrotic and nonenhancing part. The endomyometrial junction, the cystic component of the lesion, and necrotic areas were not included in the ROI. ROI placement was correlated with T2-weighted (T2WI), T1-weighted (T1WI), and DWI before calculating the minimum and mean ADC values ([Fig. 2]). The same ROI was propagated on dynamic T1W CE images, and time–intensity curves were plotted. Based on these imaging findings, the lesion was labeled as benign or malignant. Imaging findings were correlated with diagnosis as made by endometrial aspirate biopsy, dilatation–curettage, or postoperative histopathological examination. All data variables were entered in spreadsheet software. SPSS version 25 for Statistical analyses was used to perform parametric tests to determine the statistical significance.
Continuous variables were described as mean, range with +/− or median with interquartile range (IQR) as applicable. Categorical variables were presented as frequency and percentages. Categorical variables between two groups were analyzed using the chi-square test. The significance level was taken as p < 0.05. ROC curve analysis was performed to predict cutoffs for continuous variables with maximum sensitivity and specificity.
Results
A total of 33 patients were included in the study with a mean age of 47 ± 14 years (IQR: 22–73). Of 32 patients, 16 had malignant lesions, and 17 showed benign lesions.
The spectrum of malignant lesions was as follows: 11 (34%) endometrial adenocarcinoma, 2 (6%) endometrioid carcinoma, and 1 case (3%) each of mucinous endometrial carcinoma, serous endometrial carcinoma, pleomorphic leiomyosarcoma, mesenchymal tumor with osseous metaplasia. The spectrum of benign lesions was as follows: 8 submucosal fibroid (32%) with 1 fibroid showing hyalinization changes, 4 (12%) endometrial polyp, 3 (6%) endometrial hyperplasia, 2 (6%) adenomyosis.
T1W and T2W signals and enhancement of the lesions were compared with those of the normal myometrium.
Lesion Signal Characteristics
The majority (n = 14, 87.5%) of the malignant lesions were hyperintense on T2WI and iso- to hypointense on T1WI and showed nonhomogeneous hypercontrast enhancement compared with the myometrium.
The benign lesions were hyperintense on T2WI and iso- to hypointense on T1WI and showed mild contrast enhancement. Cystic changes were seen in adenomyosis. Fibroids showed enhancement similar to myometrium with internal nonenhancing areas and a nonenhancing capsule. Polyps showed peripheral enhancement and hypoenhancement as compared with myometrium. Stalk of the polyp showed linear enhancement up to the site of attachment. Endometrial hyperplasia showed thickened endometrium with sharp margins and preserved stratifications.
T2 signal and postcontrast enhancement patterns were the most useful in differentiating benign and malignant lesions, with p-values of 0.006 and 0.03, respectively ([Table 1]).
Time–Intensity Curve
The malignant lesions showed a type 3 curve with early enhancement and washout, except for one case of adenocarcinoma, which showed a type 2 curve with plateau enhancement.
The benign lesions showed a type 1 curve with progressive enhancement, except for two cases of leiomyoma and one case of adenomyoma, which showed a type 2 curve with plateau enhancement.
Apparent Diffusion Coefficient Values
The mean ADC measurement in malignant lesions was 0.88 × 10−3 ± 0.27 × 10−3, whereas the mean ADC measurement for benign lesions was 1.03 × 10−3 ± 0.38 × 10−3. Maheshwari et al reported values ranging from 1.05 × 10−3 to 1.28 × 10−3, which were used to differentiate between malignant and benign lesions.[2] The differences between the two were found to be significant (t-value: 2.754, p-value: 0.014).
DWI and dynamic CEMRI were interpreted in combination with conventional MR images. Malignant lesions showed significantly lower ADC values than benign lesions with statistically significant p-value < 0.05. Dynamic CEMRI curves did not show specific patterns with types of lesions.
[Figs. 3] and [4] demonstrate representative endometrial lesions with their morphology, signal characters in conventional sequences, and dynamic contrast time–intensity curves.
[Fig. 5A, B] shows ROC curve analysis for predicting the cutoff of mean ADC values and minimum ADC values, respectively, in predicting malignancy. The cutoff of mean ADC and minimum ADC with the highest sensitivity and specificity were reported to be ≤1 × 10−3 and ≤0.8 × 10−3, respectively.
Discussion
Imaging is indispensable in diagnosing various gynecological malignancies. Pelvic ultrasound is the initial investigation, which is done; however, MRI is the gold standard. MRI helps in diagnosis as well as in staging; however, routine MRI sequences cannot differentiate disease recurrence, postradiotherapy, or chemotherapy changes. Sometimes, it is difficult to differentiate benign from malignant lesions on routine MRI.[3] Functional imaging sequences like DWI, perfusion, and dynamic CEMRI are routinely used to differentiate benign from malignant lesions. DWI detects restricted motion of water molecules. The restriction is seen in malignant lesions due to high cellularity. Restricted movement can be quantified by measuring ADC values. Lesions with high cellularity show low ADC values.[4] Conventional MRI sequences, with DW imaging can help in differentiating benign lesions from malignant lesions, and help in detecting myometrium invasion, pelvic lymph nodes.[5] Utility of conventional MRI is still limited in differentiating tumor recurrence from posttreatment changes.[3] Due to the low resolution of standard DW imaging, the RESOLVE DW sequence—an advanced technique using readout segmentation of long variable echo trains—is utilized for improved image quality, aiding in the evaluation of myometrial invasion and cancer staging.[4]
In this study, we acquired conventional MR sequences, DWI at different b-values and dynamic postcontrast sequences in patients with endometrial lesions. The age of the patients included in our study ranged between 33 and 61 years, with a mean age of 47. Out of a total of 32 patients, 18 patients had benign lesions, and 14 patients had malignant lesions. Endometrial adenocarcinoma was the most common pathology in our study, followed by submucosal fibroids.
Conventional MRI, along with DW imaging in pelvic pathologies helps in differentiating benign from malignant lesions, depicts the invasion of the myometrium in endometrial carcinoma and detects pelvic lymph nodes.[5] In this study, we did DW at different b-values and calculated the corresponding ADC value. Conventional MRI with DW imaging also helps assess invasion into the myometrium and helps diagnose other coexistent lesions like adenomyosis or fibroid etc.[6] Despite a lot of advantages in the pelvis, MRI still lacks the sensitivity in differentiating tumor recurrence from posttreatment changes and detecting peritoneal carcinomatosis.[3]
The age of the patients included in our study ranged between 33 and 61 years, with a mean age of 47. Out of a total of 33 patients, 17 patients had benign lesions, and 16 patients had malignant lesions. Endometrial adenocarcinoma was the most common pathology, seen in nine (34%) patients in our study, followed by submucosal fibroids seen in eight (32%) patients. Hyalinization changes were seen in one fibroid.
Conventional Magnetic Resonance Characteristics of Benign Lesions
Benign lesions display a hypointense signal on T1W, and a hypo- and hyperintense signal on T2W compared with myometrium. Enhancement of benign lesions is usually homogeneous and is equal to or more than myometrial enhancement. Submucosal fibroid showed varied signal intensities from hypointense to hyperintense. on T1W and T2W and homogeneous or heterogeneous enhancement. A case of fibroid with hyalinization depicted heterointense signal on T2W, hypointense on T1, and showed homogeneous enhancement on postcontrast scans. This is in disagreement with the study conducted by Tamai et al[6] in which the fibroids showed a hypointense signal on both T1W and T2W. Fibroids show varying stages of degeneration, including psammomatous degeneration, with deposition of fibrin and calcium. These could lead to hypointense signal on both T1 and T2 images.
In our study, endometrial polyps showed hypointense to isointense signal on T2W and iso- to hypointense on T1W. Only one case appeared hyperintense on T2W. These findings were in agreement with Kierans et al[5] and Inoue et al.[7]
Certain morphological features like presence of pedicles in polyps and submucosal fibroids can be a clue. Previous studies also concluded lacunae in conventional MR sequences.[5]
Conventional Magnetic Resonance Characteristics of Malignant Lesions
Malignant lesions are isointense on T1W, hyperintense on T2W and show heterogeneous postcontrast enhancement less intense than myometrium. Endometrial carcinoma also showed varied signals on T1 and T2W, displayed varied signals, and showed heterogeneous or hypoenhancement and diffusion restriction. Although most of the malignant lesions were bright on DW and low on ADC. However, it is difficult to differentiate endometrial carcinoma from normal endometrium as normal endometrium also shows diffusion restriction. This was in congruence with Wang et al[8] who reported that both endometrial cancers and normal endometrium show diffusion restriction. Normal endometrium shows a smooth outline with sharp demarcation between endometrium and myometrium. Endometrium carcinoma would show a similar appearance in early stages, except in advanced cases myometrial invasion can be seen. Most of the malignant lesions showed hyperintense signals on DWI. In a study conducted by Neves et al fusion of DW and T2W sequence is also used for staging in endometrial carcinoma and in assessing the depth of myometrial invasion.[9]
Benign lesions displayed intermediate signals on DWI. It is in concordance with the study conducted by Dhand et al [10] Inoue et al.[7]
Lane et al[11] described that endometrial hyperplasia, polyp, and endometrial carcinoma can appear as focal mass or diffuse thickening of the endometrium. Hence, it is not always possible to differentiate all of these based on morphology. Few of the endometrial malignancies presented as lobulated large lesions occupying endometrial cavity with fluid collections within the cavity and myometrial invasion. However, the T1, T2, and DWI signals, margins, and invasion into the myometrium can help in the differentiation. This was in agreement with our study as the signal intensities as well as morphology of these lesions were different as described previously.
Role of Apparent Diffusion Coefficient Values: Benign versus Malignant
We observed significantly lower ADC values in malignant lesions than in benign lesions. The mean ADC value in malignant lesions was 0.88 × 10−3 ± 0.27 × 10−3 (IQR: 0.7–1.0). The mean ADC value for benign lesions was 1.03 × 10−3 ± 0.38 × 10−3 (IQR: −1.4 to 2.5). The differences between the two were statistically significant. Our observations were in concordance with Elsammak et al[12] and Bharwani et al[13] who reported cutoff value of 1.28 × 10−3 for differentiating benign from malignant lesions. There was a sensitivity of 87%, specificity of 100%, positive predictive value of 100%, and negative predictive value of 85.7% for malignancy (p < 0.0001). The cutoff values are close to the findings in our study.
The highest ADC was seen in a cellular leiomyoma, 2.5 × 10−3. The lowest ADC value, 0.1 × 10−3, found in one case of adenocarcinoma. However, cases with fibroids also showed low ADC values in areas with T1 and T2 hypointense signals. It can be explained by degenerative changes and microcalcifications leading to ADC blackout.
Role of Apparent Diffusion Coefficient Values: Subtypes of Malignant Lesions
There were significant variations in ADC values in adenocarcinoma ranges, which ranged from 0.2 to 0.8 × 10−3. These could be due to the presence of blood products and areas of necrosis within malignant lesions. Our study also showed that mean ADC was very low in adenocarcinoma and showed different values for different types of adenocarcinomas and was as low as approximately 0.1 × 10−3 in a few cases. This was in contrast with Tamai et al[3] who found that ADC values had a strong relation with the adenocarcinoma grade. Disagreement could be due to a smaller sample size and lack of representative cases of various grades and subtypes.
Role of Apparent Diffusion Coefficient Values: Subtypes of Benign Lesions
Differentiating various benign lesions based on ADC was difficult. In our study, we observed that the ADC value was 1.4 to 1.9 × 10−3 in endometrial polyps and submucosal fibroids. ADC values in endometrial hyperplasia were also 1.4 × 10−3. This disagreed with the study conducted by Shen et al[14] who reported that ADC values of endometrial hyperplasia and endometrial polyp were 1.27 × 10−3.
[Table 2] shows different lesions and their ADC values.
Abbreviation: ADC, apparent diffusion coefficient.
All the lesions were blindly evaluated before the biopsy or the surgery. Structural MR sequences were evaluated for the morphological features of the lesion in addition to the DW and ADC values. ROI was placed in the enhancing part of the lesion after correlating with T2 and T1 images and then copied on DWI and ADC maps to overcome inherently low spatial resolution DWI. The major limitation of our study was a small sample size and a small spectrum of lesion types. Histopathological type prediction based on ADC values is not promising due to the overlap of values. The ADC value did not predict the lesion staging or histopathological grading and aggressiveness in our study. A large-volume study is required for the same.
Our study showed the utility of ADC values to differentiate benign lesions from malignant lesions as a supplement to structural MR sequences and morphological features. Malignant lesions showed a lower ADC value than benign lesions. Developments are still going on in predicting the myometrial invasion and staging using noncontrast MRI with DW. In a recent study conducted by Xie et al,[15] the RESOLVE DW sequence, which is an advanced technique that uses readout segmentation of long variable echo trains, is being utilized for improved image quality, aiding in the evaluation of myometrial invasion and cancer staging.
With the help of the cutoff, ADC can be of great help in indeterminate cases. DWI and ADC values cannot be used in isolation without evaluating conventional T1- and T2 features and morphology. Large sample studies can help to establish ADC values to differentiate various histopathological type of endometrial malignancies.
Conflict of Interest
None declared.
Data Availability Statement
Data are available and will be available on reasonable request.
Authors' Contributions
P.S.: concept and final editing of the manuscript; K.N.: drafting of the manuscript and the images; L.C.: clinical inputs; A.K.: final pathology and providing pathology images; A.S.: drafting of the manuscript; R.K.: statistical analysis
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References
- 1 Basaran I, Cengel F, Bayrak AH. Diffusion-weighted imaging in the benign-malignant differentiation of endometrial pathologies; effectiveness of visual evaluation. J Coll Physicians Surg Pak 2023; 33 (01) 73-78
- 2 Maheshwari E, Nougaret S, Stein EB. et al. Update on MRI in evaluation and treatment of endometrial cancer. Radiographics 2022; 42 (07) 2112-2130
- 3 Tamai K, Koyama T, Saga T. et al. Diffusion-weighted MR imaging of uterine endometrial cancer. J Magn Reson Imaging 2007; 26 (03) 682-687
- 4 Koh DM, Collins DJ. Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol 2007; 188 (06) 1622-1635
- 5 Kierans AS, Bennett GL, Haghighi M, Rosenkrantz AB. Utility of conventional and diffusion-weighted MRI features in distinguishing benign from malignant endometrial lesions. Eur J Radiol 2014; 83 (04) 726-732
- 6 Tamai K, Koyama T, Saga T. et al. The utility of diffusion-weighted MR imaging for differentiating uterine sarcomas from benign leiomyomas. Eur Radiol 2008; 18 (04) 723-730
- 7 Inoue C, Fujii S, Kaneda S. et al. Correlation of apparent diffusion coefficient value with prognostic parameters of endometrioid carcinoma. J Magn Reson Imaging 2015; 41 (01) 213-219
- 8 Wang J, Yu T, Bai R, Sun H, Zhao X, Li Y. The value of the apparent diffusion coefficient in differentiating stage IA endometrial carcinoma from normal endometrium and benign diseases of the endometrium: initial study at 3-T magnetic resonance scanner. J Comput Assist Tomogr 2010; 34 (03) 332-337
- 9 Neves TR, Correia MT, Serrado MA, Horta M, Caetano AP, Cunha TM. Staging of endometrial cancer using fusion T2-weighted images with diffusion-weighted images: a way to avoid gadolinium?. Cancers (Basel) 2022; 14 (02) 384
- 10 Dhanda S, Thakur M, Kerkar R, Jagmohan P. Diffusion-weighted imaging of gynecologic tumors: diagnostic pearls and potential pitfalls. Radiographics 2014; 34 (05) 1393-1416
- 11 Lane BF, Wong-You-Cheong JJ. Imaging of endometrial pathology. Clin Obstet Gynecol 2009; 52 (01) 57-72
- 12 Elsammak A, Shehata SM, Abulezz M, Gouhar G. Efficiency of diffusion weighted magnetic resonance in differentiation between benign and malignant endometrial lesions. Egypt J Radiol Nucl Med 2017; 48 (03) 751-759
- 13 Bharwani N, Miquel ME, Sahdev A. et al. Diffusion-weighted imaging in the assessment of tumour grade in endometrial cancer. Br J Radiol 2011; 84 (1007) 997-1004
- 14 Shen SH, Chiou YY, Wang JH. et al. Diffusion-weighted single-shot echo-planar imaging with parallel technique in assessment of endometrial cancer. AJR Am J Roentgenol 2008; 190 (02) 481-488
- 15 Xie M, Ren Z, Bian D. et al. High resolution diffusion-weighted imaging with readout segmentation of long variable echo-trains for determining myometrial invasion in endometrial carcinoma. Cancer Imaging 2020; 20 (01) 66
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Publication History
Article published online:
24 June 2025
© 2025. Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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References
- 1 Basaran I, Cengel F, Bayrak AH. Diffusion-weighted imaging in the benign-malignant differentiation of endometrial pathologies; effectiveness of visual evaluation. J Coll Physicians Surg Pak 2023; 33 (01) 73-78
- 2 Maheshwari E, Nougaret S, Stein EB. et al. Update on MRI in evaluation and treatment of endometrial cancer. Radiographics 2022; 42 (07) 2112-2130
- 3 Tamai K, Koyama T, Saga T. et al. Diffusion-weighted MR imaging of uterine endometrial cancer. J Magn Reson Imaging 2007; 26 (03) 682-687
- 4 Koh DM, Collins DJ. Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol 2007; 188 (06) 1622-1635
- 5 Kierans AS, Bennett GL, Haghighi M, Rosenkrantz AB. Utility of conventional and diffusion-weighted MRI features in distinguishing benign from malignant endometrial lesions. Eur J Radiol 2014; 83 (04) 726-732
- 6 Tamai K, Koyama T, Saga T. et al. The utility of diffusion-weighted MR imaging for differentiating uterine sarcomas from benign leiomyomas. Eur Radiol 2008; 18 (04) 723-730
- 7 Inoue C, Fujii S, Kaneda S. et al. Correlation of apparent diffusion coefficient value with prognostic parameters of endometrioid carcinoma. J Magn Reson Imaging 2015; 41 (01) 213-219
- 8 Wang J, Yu T, Bai R, Sun H, Zhao X, Li Y. The value of the apparent diffusion coefficient in differentiating stage IA endometrial carcinoma from normal endometrium and benign diseases of the endometrium: initial study at 3-T magnetic resonance scanner. J Comput Assist Tomogr 2010; 34 (03) 332-337
- 9 Neves TR, Correia MT, Serrado MA, Horta M, Caetano AP, Cunha TM. Staging of endometrial cancer using fusion T2-weighted images with diffusion-weighted images: a way to avoid gadolinium?. Cancers (Basel) 2022; 14 (02) 384
- 10 Dhanda S, Thakur M, Kerkar R, Jagmohan P. Diffusion-weighted imaging of gynecologic tumors: diagnostic pearls and potential pitfalls. Radiographics 2014; 34 (05) 1393-1416
- 11 Lane BF, Wong-You-Cheong JJ. Imaging of endometrial pathology. Clin Obstet Gynecol 2009; 52 (01) 57-72
- 12 Elsammak A, Shehata SM, Abulezz M, Gouhar G. Efficiency of diffusion weighted magnetic resonance in differentiation between benign and malignant endometrial lesions. Egypt J Radiol Nucl Med 2017; 48 (03) 751-759
- 13 Bharwani N, Miquel ME, Sahdev A. et al. Diffusion-weighted imaging in the assessment of tumour grade in endometrial cancer. Br J Radiol 2011; 84 (1007) 997-1004
- 14 Shen SH, Chiou YY, Wang JH. et al. Diffusion-weighted single-shot echo-planar imaging with parallel technique in assessment of endometrial cancer. AJR Am J Roentgenol 2008; 190 (02) 481-488
- 15 Xie M, Ren Z, Bian D. et al. High resolution diffusion-weighted imaging with readout segmentation of long variable echo-trains for determining myometrial invasion in endometrial carcinoma. Cancer Imaging 2020; 20 (01) 66