Difference in Diffusion-Weighted Magnetic Resonance Imaging and Diffusion Tensor Imaging Parameters Between Endometrioid Endometrial Adenocarcinoma and Uterine Serous Adenocarcinoma

Song, Tian; Liu, Ailian; Zhu, Wen; Li, Ye; Chen, Lihua; Chen, Anliang; Shen, Jialong; Song, Qingwei; Wei, Qiang

doi:10.1097/igc.0000000000001054

Cited by 12 publications

(7 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[8][9][10][11][12][13][14] Therefore, our data support the observation that DTI is more accurate than conventional DWI for differentiating among histologic grades of carcinomas. Further, although a previous study has shown that DWI and DTI are useful for distinguishing between endometrioid endometrial adenocarcinoma and uterine serous adenocarcinoma, 30 it did not examine the usefulness of DTI maps for differentiating among histologic grades of EMACs; to the best of our knowledge, this is the first report to do so. We did not investigate the ability of DTI to distinguish the various subtypes of EMC because we did not have enough cases of nonendometrioid subtypes in our series.…”

Section: Discussionmentioning

confidence: 83%

“…21,22 This may have affected calculations of eigenvalues and DTI parameters; nevertheless, the DTI parameters reported here are comparable with those reported in previous studies. 15,16,30 Our ultimate goal would be routine application of DTI in patients with EMC as a noninvasive method for obtaining vital tumor-related information to guide selection of optimal therapy within a clinically feasible duration.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Endometrial carcinoma: Evaluation using diffusion‐tensor imaging and its correlation with histopathologic findings

Yamada

Wakana

Kobayashi

et al. 2018

Magnetic Resonance Imaging

View full text Add to dashboard Cite

Background Although the prognosis of endometrial carcinoma (EMC) patients strictly depends on tumor invasion depth and its histologic grade, accurate preoperative assessment of these prognostic factors is often difficult. Purpose To determine the usefulness of diffusion‐tensor imaging (DTI) as a noninvasive method for evaluating tumor invasion depth and its histologic grade in patients with EMC. Study Type Prospective. Population Twenty‐five consecutive patients with histologically confirmed EMC who were surgically treated at our institution. Field Strength/Sequence DTI was performed with a 1.5T MRI system using a single‐shot echo‐planar imaging sequence with b values of 0 and 1000 s/mm2 and motion‐probing gradients in nine noncollinear directions. Assessment Fractional anisotropy (FA), mean diffusivity (MD), and axial diffusivity (AD) maps were analyzed by three observers and compared with histopathologic findings. Statistical Tests Dunnett's test, Spearman's rank correlation coefficient, and receiver operating characteristic (ROC) curve analyses. Results FA maps from all patients distinctly identified the junctional zone as a high‐FA zone (0.864 ± 0.037) that was significantly different from the endometrium and outer myometrium (0.251 ± 0.030 and 0.471 ± 0.091, respectively; P < 0.001). All EMCs were clearly depicted as hypointense areas on all DTI maps. AD maps provided the best tumor‐to‐uterus contrast, and EMCs (0.977 ± 0.120 × 10−3 mm2/s) had significantly lower AD values than all other layers of the normal uterine wall (2.166 ± 0.408, 2.010 ± 0.289, and 2.655 ± 0.203 × 10−3 mm2/s, respectively; P < 0.001). EMCs were clearly demarcated from the normal uterine wall, and DTI maps and histopathologic data yielded identical findings regarding tumor invasion depth. FA values showed a significant inverse correlation (r = –0.818; P < 0.001) with histologic grades 1, 2, and 3 of endometrioid adenocarcinomas. Data Conclusion In patients with EMC, DTI may be useful for evaluating tumor invasion depth and its histologic grade. Level of Evidence: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:250–260.

show abstract

Section: Discussionmentioning

confidence: 83%

Section: Discussionmentioning

confidence: 99%

Endometrial carcinoma: Evaluation using diffusion‐tensor imaging and its correlation with histopathologic findings

Yamada

Wakana

Kobayashi

et al. 2018

Magnetic Resonance Imaging

View full text Add to dashboard Cite

show abstract

“…Recently, magnetic resonance imaging (MRI) as a non-invasive preoperative risk assessment method that has been widely used in malignant tumors with functional and molecular imaging technology and reflects both the local and overall characteristics of lesions. The diffusion-weighted imaging (DWI) can identify the histological type of malignant tumor by diffusion of water molecules, which can be quantified by the apparent diffusion coefficient (ADC) value ( 10 , 11 ). Radiomics can extract features of medical images and transform them into quantitative data, reflecting the intensity, location, and spatial arrangement of voxels, which has been used to evaluate heterogeneity, aggressiveness, and prognosis of malignant tumors ( 12 , 13 ).…”

Section: Introductionmentioning

confidence: 99%

Nomograms of Combining Apparent Diffusion Coefficient Value and Radiomics for Preoperative Risk Evaluation in Endometrial Carcinoma

Zhang

Fang

et al. 2021

Front. Oncol.

View full text Add to dashboard Cite

ObjectivesTo evaluate the value of nomogram models combining apparent diffusion coefficient (ADC) value and radiomic features on magnetic resonance imaging (MRI) in predicting the type, grade, deep myometrial invasion (DMI), lymphovascular space invasion (LVSI), and lymph node metastasis (LNM) of endometrial carcinoma (EC) preoperatively.MethodsThis study included 210 EC patients. ADC value was calculated, and radiomic features were measured on T2-weighted images. The univariate and multivariate logistic regressions and cross-validations were performed to reduce valueless features, then radiomics signatures were developed. Nomogram models using ADC combined with radiomic features were developed in the training cohort. The receiver operating characteristic (ROC) curve was performed to estimate the diagnostic efficiency of nomogram models by the area under the curve (AUC) in the training and validation cohorts.ResultsThe ADC value was significantly different between each subgroup. Radiomic features were ultimately limited to four features for type, six features for grade, six features for DMI, four features for LVSI, and eight features for LNM for the nomogram models. The AUC of the nomogram model combining ADC value and radiomic features in the training and validation cohorts was 0.851 and 0.867 for type, 0.959 and 0.880 for grade, 0.839 and 0.766 for DMI, 0.816 and 0.746 for LVSI, and 0.910 and 0.897 for LNM.ConclusionsThe nomogram models of ADC value combined with radiomic features were associated with the type, grade, DMI, LVSI, and LNM of EC, and provide an effective, non-invasive method to evaluate preoperative risk stratification for EC.

show abstract

“…In 2014, Zhao emphasized that DWI could be used for the differentiation of malignant epithelial and borderline ovarian tumors (24). In endometrial neoplasia, it has been reported that DWI can be used for the differentiation of malignant and benign endometrial tissues, as well as differentiation of endometrial serous and adenocancer (25)(26)(27).…”

Section: Discussionmentioning

confidence: 99%

Apparent Diffusion Coefficient Value Changes of Normal Uterine Cervix with Aging

Elibol

Köseoğlu

2019

Iran J Radiol

View full text Add to dashboard Cite

Background: In the magnetic resonance imaging (MRI) of many tissues, apparent diffusion coefficient (ADC) values vary with age. In the literature, there are no studies in which normal cervix ADC values and their relationship with age is analyzed. Objectives: To evaluate whether changes occur in ADC values with aging in the uterine cervix with 3-Tesla MRI. Patients and Methods: Female patients aged between 18 and 70 years who were found to have lower abdominal diffusion-weighted magnetic resonance imaging (DWI) in the radiology database from December 2017 to May 2018 were evaluated. All DWI examinations were performed using a 3-T MR with 2 b values (b = 50, 800 s/mm 2). A total of 161 patients were divided into two groups according to their menopausal status (premenopausal n = 106, postmenopausal n = 55). To evaluate the correlation between the age of the patient and the ADC values, Pearson correlation analysis was performed. Results: The mean age of the patients was 41.4 ± 11.6 years. The mean ADC value was 1.276 ± 0.25 mm 2 /sec × 10-3 in the whole population. There was a negative correlation between age and ADC values. The mean cervix ADC value of premenopausal and postmenopausal patients was 1.333 ± 0.23 mm 2 /sec × 10-3 and 1.165 ± 0.25 mm 2 /sec × 10-3 , respectively. There was a statistically significant difference between the groups in term of cervix ADC value (P < 0.05). Conclusion: A negative correlation between aging and ADC values was found. Menopausal status has an effect on the ADC values of the cervix. These findings may indicate cellular and extracellular matrix changes in the cervix tissue with aging and menopausal status.

show abstract

Difference in Diffusion-Weighted Magnetic Resonance Imaging and Diffusion Tensor Imaging Parameters Between Endometrioid Endometrial Adenocarcinoma and Uterine Serous Adenocarcinoma

Abstract: We suggest that both DWI and DTI could be used in distinguishing EEA from SA. Apparent diffusion coefficient and ADC possess potential diagnostic value with high sensitivity and specificity.

Cited by 12 publications

References 25 publications

Endometrial carcinoma: Evaluation using diffusion‐tensor imaging and its correlation with histopathologic findings

Endometrial carcinoma: Evaluation using diffusion‐tensor imaging and its correlation with histopathologic findings

Nomograms of Combining Apparent Diffusion Coefficient Value and Radiomics for Preoperative Risk Evaluation in Endometrial Carcinoma

Apparent Diffusion Coefficient Value Changes of Normal Uterine Cervix with Aging

Contact Info

Product

Resources

About