Multiparametric MRI-based radiomics nomogram for identifying cervix-corpus junction cervical adenocarcinoma from endometrioid adenocarcinoma.

OBJECTIVE: To developed a magnetic resonance imaging (MRI) radiomics nomogram to identify adenocarcinoma at the cervix-corpus junction originating from the endometrium or cervix in order to better guide clinical treatment. METHODS: Between February 2011 and September 2021, the clinicopathological data and MRI in 143 patients with histopathologically confirmed cervical adenocarcinoma (CAC, n = 86) and endometrioid adenocarcinoma (EAC, n = 57) were retrospectively analyzed at the cervix-corpus junction. Radiomics features were extracted from fat-suppressed T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) maps, and delayed phase contrast-enhanced T1-weighted imaging (CE-T1WI) sequences. A radiomics nomogram was developed integrating radscore with independent clinical risk factors. The area under the curve (AUC) was used to evaluate the diagnostic efficacy of the radscore, nomogram and two different experienced radiologists in differentiating CAC from EAC at the cervix-corpus junction, and Delong test was applied to compare the differences of their diagnostic performance. RESULTS: In the training cohort, the AUC was 0.93 for radscore; 0.97 for radiomics nomograms; 0.85 and 0.86 for radiologists 1 and 2, respectively. Delong test showed that the differential efficacy of nomogram was significant better than those of radiologists in the training cohort (both P < 0.05). CONCLUSIONS: The nomogram based on radscore and clinical risk factors could better differentiate CAC from EAC at the cervix-corpus junction than radiologists, and preoperatively and non-invasively identify the origin of adenocarcinoma at the cervix-corpus junction, which facilitates clinicians to make individualized treatment decision.

Magnetic resonance imaging-based radiomics analysis of the differential diagnosis of ovarian clear cell carcinoma and endometrioid carcinoma: a retrospective study.

PURPOSE: To retrospectively evaluate the diagnostic potential of magnetic resonance imaging (MRI)-based features and radiomics analysis (RA)-based features for discriminating ovarian clear cell carcinoma (CCC) from endometrioid carcinoma (EC). MATERIALS AND METHODS: Thirty-five patients with 40 ECs and 42 patients with 43 CCCs who underwent pretherapeutic MRI examinations between 2011 and 2022 were enrolled. MRI-based features of the two groups were compared. RA-based features were extracted from the whole tumor volume on T2-weighted images (T2WI), contrast-enhanced T1-weighted images (cT1WI), and apparent diffusion coefficient (ADC) maps. The least absolute shrinkage and selection operator (LASSO) regression with tenfold cross-validation method was performed to select features. Logistic regression analysis was conducted to construct the discriminating models. Receiver operating characteristic curve (ROC) analyses were performed to predict CCC. RESULTS: Four features with the highest absolute value of the LASSO algorithm were selected for the MRI-based, RA-based, and combined models: the ADC value, absence of thickening of the uterine endometrium, absence of peritoneal dissemination, and growth pattern of the solid component for the MRI-based model; Gray-Level Run Length Matrix (GLRLM) Long Run Low Gray-Level Emphasis (LRLGLE) on T2WI, spherical disproportion and Gray-Level Size Zone Matrix (GLSZM), Large Zone High Gray-Level Emphasis (LZHGE) on cT1WI, and GLSZM Normalized Gray-Level Nonuniformity (NGLN) on ADC map for the RA-based model; and the ADC value, spherical disproportion and GLSZM_LZHGE on cT1WI, and GLSZM_NGLN on ADC map for the combined model. Area under the ROC curves of those models were 0.895, 0.910, and 0.956. The diagnostic performance of the combined model was significantly superior (p = 0.02) to that of the MRI-based model. No significant differences were observed between the combined and RA-based models. CONCLUSION: Conventional MRI-based analysis can effectively distinguish CCC from EC. The combination of RA-based features with MRI-based features may assist in differentiating between the two diseases.

Clinical and multiparametric MRI features for differentiating uterine carcinosarcoma from endometrioid adenocarcinoma.

INTRODUCTION: The purpose of our study was to differentiate uterine carcinosarcoma (UCS) from endometrioid adenocarcinoma (EAC) by the multiparametric magnetic resonance imaging (MRI) features. METHODS: We retrospectively evaluated clinical and MRI findings in 17 patients with UCS and 34 patients with EAC proven by histologically. The following clinical and pathological features were evaluated: post- or pre-menopausal, clinical presentation, invasion depth, FIGO stage, lymphaticmetastasis. The following MRI features were evaluated: tumor dimension, cystic degeneration or necrosis, hemorrhage, signal intensity (SI) on T2-weighted images (T2WI), relative SI of lesion to myometrium on T2WI, T1WI, DWI, ADCmax, ADCmin, ADCmean (RSI-T2, RSI-T1, RSI-DWI, RSI-ADCmax, RSI-ADCmin, RSI-ADCmean), ADCmax, ADCmin, ADCmean, the maximum, minimum and mean relative enhancement (RE) of lesion to myometrium on the arterial and venous phases (REAmax, REAmin, REAmean, REVmax, REVmin, REVmean). Receiver operating characteristic (ROC) analysis and the area under the curve (AUC) were used to evaluate prediction ability. RESULTS: The mean age of UCS was higher than EAC. UCS occurred more often in the postmenopausal patients. UCS and EAC did not significantly differ in depth of myometrial invasion, FIGO stage and lymphatic metastasis. The anterior-posterior and transverse dimensions were significantly larger in UCS than EAC. Cystic degeneration or necrosis and hemorrhage were more likely occurred in UCS. The SI of tumor on T2WI was more heterogeneous in UCS. The RSI-T2, ADCmax, ADCmean, RSI-ADCmax and RSI-ADCmean of UCS were significantly higher than EAC. The REAmax, REAmin, REAmean, REVmax, REVmin and REVmean of UCS were all higher than EAC. The AUCs were 0.72, 0.71, 0.86, 0.96, 0.89, 0.84, 0.73, 0.97, 0.88, 0.94, 0.91, 0.69 and 0.80 for the anterior-posterior dimension, transverse dimension, RSI-T2, ADCmax, ADCmean, RSI-ADCmax, RSI-ADCmean, REAmax, REAmin, REAmean, REVmax, REVmin and REVmean, respectively. The AUC was 0.997 of the combined of ADCmax, REAmax and REVmax. Our study showed that ADCmax threshold value of 789.05 (10-3mm2/s) can differentiate UCS from EAC with 100% sensitivity, 76.5% specificity, and 0.76 AUC, REAmax threshold value of 0.45 can differentiate UCS from EAC with 88.2% sensitivity, 100% specificity, and 0.88 AUC. CONCLUSION: Multiparametric MRI features may be utilized as a biomarker to distinguish UCS from EAC.

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

OBJECTIVE: To investigate the application of whole-tumor apparent diffusion coefficient (ADC) histogram metrics for preoperative risk stratification in endometrial endometrioid adenocarcinoma (EEA). METHODS: Preoperative MRI of 502 EEA patients were retrospectively analyzed. Whole tumor ADC histogram analysis was performed with regions of interest drawn on all tumor slices of diffusion-weighted imaging scans. Risk stratification was based on ESMO-ESTRO-ESP guidelines: low-, intermediate-, high-intermediate-, and high-risk. Univariable analysis was used to compare ADC histogram metrics (tumor volume, minADC, maxADC, and meanADC; 10th, 25th, 50th, 75th, and 90th percentiles of ADC [recorded as P10, P25, P50, P75, and P90 ADC, respectively]; skewness; and kurtosis) between different risk EEAs, and multivariable logistic regression analysis to determine the optimal metric or combined model for risk stratifications. Receiver operating characteristic curve analysis with the area under the curve (AUC) was used for diagnostic performance evaluation. RESULTS: A decreasing tendency in multiple ADC values was observed from the low- to high-intermediate-risk EEAs. The (low + intermediate)-risk EEAs and low-risk EEAs had significantly smaller tumor volumes and higher minADCs, meanADCs, P10, P25, P50, P75, and P90 ADCs than the (high-intermediate + high)-risk EEAs and non-low-risk EEAs (all P < 0.05), respectively. The combined models of the (meanADC + volume) and the (P75 ADC + volume) yielded the largest AUCs of 0.775 and 0.780 in identifying the (low + intermediate)- and the low-risk EEAs from the other EEAs, respectively. CONCLUSION: Whole-tumor ADC histogram metrics might be helpful for preoperatively identifying low- and (low + intermediate)-risk EEAs, facilitating personalized therapeutic planning.

An MR-based radiomics nomogram including information from the peritumoral region to predict deep myometrial invasion in stage I endometrioid adenocarcinoma: a preliminary study.

OBJECTIVE: To develop and validate an MR-based radiomics nomogram combining different imaging sequences (ADC mapping and T2 weighted imaging (T2WI)), different tumor regions (combined intra- and peritumoral regions), and different parameters (clinical features, tumor morphological features, and radiomics features) while considering different MR field strengths in predicting deep myometrial invasion (MI) in Stage I endometrioid adenocarcinoma (EEA). METHODS: A total of 202 patients were retrospectively analyzed and divided into two cohorts (training cohort, 1.5 T MR, n = 131; validation cohort, 3.0 T MR, n = 71). Axial ADC mapping and T2WI were conducted. Radiomics features were extracted from intra- and peritumoral regions. Least absolute shrinkage and selection operator regression, univariate analysis, and multivariate logistic regression were used to select radiomics features and tumor morphological and clinical parameters. The area under the receiver operator characteristic curve (AUC) was calculated to evaluate the performance of the prediction model and radiomics nomogram. RESULTS: Ten radiomics features, 4 morphological parameters and 1 clinical characteristic were selected. The radiomics nomogram achieved good discrimination between the superficial and deep MI cohorts. The AUC was 0.927 (95% confidence interval [CI]: 0.865, 0.967) in the training cohort and 0.921 (95% CI: 0.872, 0.948) in the validation cohort. The specificity and sensitivity were 92.0 and 78.9% in the training cohort and 83.0 and 77.8% in the validation cohort, respectively. CONCLUSION: The radiomics nomogram showed good performance in predicting the depth of MI in Stage I EEA before surgery and might be useful for surgical patient management. ADVANCES IN KNOWLEDGE: An MR-based radiomics nomogram was useful for predicting deep MI in Stage I EEA patients (AUCtrain = 0.927, AUCvalidation = 0.921). The intra- and peritumoral radiomics features complemented each other. The nomogram was developed and validated with different MR field strengths, suggesting that the model demonstrates good generalizability.

Endometrioid adenocarcinoma of the rectovaginal septum: A case report. / é˜´é“ç›´è‚ éš”å­å®«å† è†œæ ·è ºç™Œ1例.

Primary endometrioid adenocarcinoma of the rectovaginal septum is rare. Its pathogenesis is not clear and there is no standard treatment. One patient with endometrioid adenocarcinoma of the rectovaginal septum arising from deep infiltrative endometriosis was admitted to Qingdao Municipal Hospital. The patient presented with incessant menstruation and abdominal distension. She had bilateral ovarian endometriotic cystectomy 6 years ago. Imaging findings suggested a pelvic mass which might invade the rectovaginal septum. Pathological results of primary surgery confirmed endometrioid carcinoma of the pelvic mass arising from the rectovaginal septum. Then she had a comprehensive staged surgery. Postoperative chemotherapy was given 6 times. No recurrence or metastasis was found during the 2-year follow-up. The possibility of deep infiltrating endometriosis and its malignant transformation should be considered in the differential diagnosis of a new extragonadal pelvic lesion in a patient with a history of endometriosis, which would avoid misdiagnosis and missed diagnosis.

Preoperative prediction of lymphovascular space invasion in endometrioid adenocarcinoma: an MRI-based radiomics nomogram with consideration of the peritumoral region.

BACKGROUND: Lymphovascular space invasion (LVSI) of endometrial cancer (EC) is a postoperative histological index, which is associated with lymph node metastases. A preoperative acknowledgement of LVSI status might aid in treatment decision-making. PURPOSE: To explore the utility of multiparameter magnetic resonance imaging (MRI) and radiomic features obtained from intratumoral and peritumoral regions for predicting LVSI in endometrioid adenocarcinoma (EEA). MATERIAL AND METHODS: A total of 334 EEA tumors were retrospectively analyzed. Axial T2-weighted (T2W) imaging and apparent diffusion coefficient (ADC) mapping were conducted. Intratumoral and peritumoral regions were manually annotated as the volumes of interest (VOIs). A support vector machine was applied to train the prediction models. Multivariate logistic regression analysis was used to develop a nomogram based on clinical and tumor morphological parameters and the radiomics score (RadScore). The predictive performance of the nomogram was assessed by the area under the receiver operator characteristic curve (AUC) in the training and validation cohorts. RESULTS: Among the features obtained from different imaging modalities (T2W imaging and ADC mapping) and VOIs, the RadScore had the best performance in predicting LVSI classification (AUCtrain = 0.919, and AUCvalidation = 0.902). The nomogram based on age, CA125, maximum anteroposterior tumor diameter on sagittal T2W images, tumor area ratio, and RadScore was established to predict LVSI had AUC values in the training and validation cohorts of 0.962 (sensitivity 94.0%, specificity 86.0%) and 0.965 (sensitivity 90.0%, specificity 85.3%), respectively. CONCLUSION: The intratumoral and peritumoral imaging features were complementary, and the MRI-based radiomics nomogram might serve as a non-invasive biomarker to preoperatively predict LVSI in patients with EEA.

Role of tumor volume in endometrial cancer: An imaging analysis and prognosis significance.

OBJECTIVE: To evaluate the prognostic value of tumor volume on preoperative MRI in endometrial cancer (EC) patients and its association with adverse prognostic factors and survival. METHODS: A retrospective observational study with 127 consecutive patients with endometrioid EC was carried out between 2016 and 2021 at Juan Ramón Jiménez University Hospital, Huelva (Spain). All patients underwent preoperative magnetic resonance imaging (MRI) for local staging. The tumor volume was analyzed on MRI by two different methods: by measuring the three maximum diameters of the tumor according to an ellipse formula and by manual region of interest in different sections; the ratio between tumor volume and uterus volume was also calculated as a third tool. The relationships between volume, prognostic factors, and survival were analyzed. RESULTS: A total of 127 patients with endometroid EC underwent preoperative MRI and were included in the study. Tumor volume was significantly higher for deep myometrial invasion, cervical stromal involvement, infiltrated serosa, lymph node metastases, high-grade EC, and lymphovascular space involvement, advanced FIGO stage, and High Recurrence Risk Group (P < 0.001). ROC curves showed that tumor volume greater than 25 cm3 predicts lymph node metastases. Volume index greater than 17 cm3 was associated with reduced disease-free survival (P < 0.001) and overall survival (P < 0.003). Multivariate analysis showed that the greatest tumor volume had an independent impact on recurrence (odds ratio [OR]1.019, 95% confidence interval [CI] 1.005-1.032) and survival (OR 1.027, 95% CI 1.009-1.046). CONCLUSIONS: This study shows an important correlation between tumor volume on MRI and poor prognostic factors. Preoperative tumor volume on MRI is a valuable biomarker to be considered for management of EC.

Endometrioid adenocarcinoma: combined multiparametric MRI and tumour marker HE4 to evaluate tumour grade and lymphovascular space invasion.

AIM: To assess the value of semi-quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and quantitative diffusion-weighted imaging parameters combined with human epididymis protein 4 (HE4) in predicting the pathological grade and lymphovascular space invasion (LVSI) of endometrioid adenocarcinoma (EAC). MATERIALS AND METHODS: Between October 2018 and December 2021, 60 women (mean age, 55 [range, 32-77] years) with EAC underwent preoperative pelvic MRI and HE4 level measurements. The positive enhancement integral (PEI), time to peak, maximum slope of increase (MSI), and maximum slope of decrease were measured by manually drawing a region of interest on the neoplastic tissue. The receiver operating characteristic curve was used to calculate the diagnostic efficiency of the single parameter and combined factors. RESULTS: Lower apparent diffusion coefficients (ADCs) were observed in high-grade tumours (G3) than in low-grade tumours (G1/G2). PEI, MSI, and HE4 levels were higher in the high-grade tumours than in the low-grade tumours (p<0.05). The area under the curve (AUC) for G3 diagnosis using multiparametric MRI combined with HE4 was 0.929. ADC values were significantly lower in the EAC with LVSI than in those without LVSI. Tumours with LVSI showed higher PEI and HE4 levels than those without LVSI (p<0.05). The AUC for LVSI-positive diagnosis using multiparametric MRI combined with HE4 was 0.814. CONCLUSION: Semi-quantitative DCE-MRI, ADC values, and serum HE4 levels can be used to predict tumour grade and LVSI, and the prediction efficiency of multiparametric MRI combined with serum HE4 is better than that of any single factor.

Whole-tumor ADC histogram analysis for differentiating endometriosis-related tumors: seromucinous borderline tumor, clear cell carcinoma and endometrioid carcinoma.

PURPOSE: To investigate the feasibility of whole-tumor apparent diffusion coefficient (ADC) histogram analysis for improving the differentiation of endometriosis-related tumors: seromucinous borderline tumor (SMBT), clear cell carcinoma (CCC) and endometrioid carcinoma (EC). METHODS: Clinical features, solid component ADC (ADCSC) and whole-tumor ADC histogram-derived parameters (volume, the ADCmean, 10th, 50th and 90th percentile ADCs, inhomogeneity, skewness, kurtosis and entropy) were compared among 22 SMBTs, 42 CCCs and 21 ECs. Statistical analyses were performed using chi-square test, one-way ANOVA or Kruskal-Wallis test, and receiver operating characteristic curves. RESULTS: A significantly higher ADCSC and smaller volume were associated with SMBT than with CCC/EC. The ADCmean was significantly higher in CCC than in EC. The 10th percentile ADC was significantly lower in EC than in SMBT/CCC. The 50th and 90th percentile ADCs were significantly higher in CCC than in SMBT/EC. For differentiating SMBT from CCC, AUCs of the ADCSC, volume, and 50th and 90th percentile ADCs were 0.97, 0.86, 0.72 and 0.81, respectively. For differentiating SMBT from EC, AUCs of the ADCSC, volume and 10th percentile ADC were 0.97, 0.71 and 0.72, respectively. For differentiating CCC from EC, AUCs of the ADCmean and 10th, 50th and 90th percentile ADCs were 0.79, 0.72, 0.81 and 0.85, respectively. CONCLUSION: Whole-tumor ADC histogram analysis was valuable for differentiating endometriosis-related tumors, and the 90th percentile ADC was optimal in differentiating CCC from EC.

Predictability of lymph node involvement in uterus-confined endometrioid endometrial cancer by tumour size, pattern and location measured with transvaginal ultrasonography: can we save time?

We aimed to investigate whether transvaginal ultrasonography (TVUSG)-measured tumour size, pattern and location were significant predictors for lymph node metastasis in the uterus-confined endometrioid endometrial cancer (EEC) patients. A total of 213 patients with EEC were recruited and 73 of them were considered eligible and were analysed according to lymph node involvement. Tumour size, pattern and location measured by transvaginal ultrasound were recorded. Thereafter, patients were distributed according to their lymph node involvement and were compared with respect to these parameters. The patients' median age was 56 (27-80). Mean of the resected lymph nodes was 29.68 and 33.5 in lymph-node-negative and positive patients, respectively (p=.525). Tumour diameter was measured >2 cm on transvaginal ultrasound in 28 (48.3%) and 13 (86.7%) cases of the lymph node-negative and positive arms, respectively (p=.008). Transvaginal ultrasound revealed that 18 (31.0%) tumours in lymph node-negative and two (13.3%) in the node positive patients had polypoid pattern (p=.171). Seventeen (54.8%) tumours of the lymph node-negative group and three (42.9%) of the node positive group were determined in the lower uterine segment (p=.250). While tumour diameter measured with TVUSG was predictable for lymph node involvement in the uterus-confined EEC, its pattern and location were not.Impact StatementWhat is already known on this subject? In clinically early-stage endometrioid endometrial cancer (EEC), it has been recognised for decades that selective lymphadenectomy is a more acceptable strategy than the systematic lymphadenectomy, owing to the low rate of lymph node metastases in the patients. Preoperative imaging, frozen section and recently accepted lymph node concept are the prominent methods in designating appropriate candidates for lymphadenectomy. The measurement of tumour diameter or size obtained intraoperatively by frozen section assessment is one of the parameters used in MAYO criteria for selective lymphadenectomy in endometrial cancer patients.What do the results of this study add? In our study, tumour diameter measured with transvaginal ultrasonography was predictable for lymph node involvement in the uterus-confined EEC.What are the implications of these findings for clinical practice and/or further research? Transvaginal ultrasonography-measured tumour diameter can be considered in deciding to proceed with pelvic lymphadenectomy while waiting for the frozen section result. It should be remembered that this approach could be considered only in clinics using MAYO criteria for selective lymphadenectomy, and it needs to be confirmed with more prospective studies.

The impact of preoperative imaging on wait times, surgical approach and overall survival in endometrioid endometrial cancers.

OBJECTIVES: Routine preoperative axial imaging studies (CT/MRI) are not recommended for endometrioid endometrial cancer as they are unlikely to change management and may delay surgery. This study evaluated the association of receiving preoperative imaging on various outcomes. METHODS: A population-based cohort of Endometrioid Endometrial Cancer cases from 2006 to 2016 were identified from the Cancer Registry in Ontario, Canada. Wait time to surgery, type of surgery and overall survival were evaluated in patients with and without preoperative imaging. Predictive factors for wait time > 56 days and aggressive surgery (radical hysterectomy / lymphadenectomy) were determined using multivariable regression analysis. RESULTS: 13,050 cases were included. 22.6% of patients received preoperative imaging, mainly CT scans. Most patients (95.9%) received no neoadjuvant treatment. Patients with preoperative imaging were more likely to have neoadjuvant treatment (11.7% vs. 1.8%) and less likely to have surgery at 180 days post diagnosis (87.9% vs 94.6%). Patients with preoperative imaging had median wait time to surgery of 64 days (47-87), compared to 53 days (36-74) than those without imaging (p < 0.001). Multivariable modeling showed preoperative imaging was associated with decreased odds of having surgery within 56 days (OR = 0.68, 95% CI = 0.62-0.75), and increased odds (OR = 1.73, 95% CI = 1.53-1.95) of having aggressive surgery. The 5-year overall survival for patients with imaging was 84.8% versus 91.1% for patients without preoperative imaging. CONCLUSIONS: Preoperative imaging was associated with longer wait times to surgery, more aggressive surgery, surgery with a gynecologic oncologist and increased use of neoadjuvant and adjuvant treatment. In early-stage disease there was no observed improvement in overall survival for patients with preoperative imaging. Further research on potential benefits of preoperative imaging in higher risk patients is required.

A comparative analysis of MRI findings in endometrial cancer: differentiation between endometrioid adenocarcinoma, serous carcinoma, and clear cell carcinoma.

OBJECTIVE: To assess the magnetic resonance imaging (MRI) findings of endometrial cancers and to reveal the differences between endometrioid carcinoma (EC), serous carcinoma (SC), and clear cell carcinoma (CCC). METHODS: In this study, 274 consecutive patients with histopathologically confirmed endometrial cancer (231 ECs, 25 SCs, and 18 CCCs) who underwent MRI before hysterectomy were enrolled. MRI images were retrospectively reviewed and compared between the three pathologies. RESULTS: The maximum diameters (55.6 ± 34.7 vs. 39.3 ± 21.6 vs. 39.4 ± 26.8 mm) (p < 0.05) and apparent diffusion coefficient (ADC) values (1.11 ± 0.21 vs. 0.84 ± 0.17 vs. 0.86 ± 0.16 × 10-3 mm2/s) (p < 0.01) were significantly greater in CCCs than in ECs and SCs, respectively. Infiltrative growth pattern (33% vs. 6%) (p < 0.01) was more frequent in CCCs than in ECs. Peritoneal dissemination (16% vs. 0%) (p < 0.01) and heterogeneous signal on diffusion-weighted (61% vs. 32%) (p < 0.05) images were more frequent in SCs than in ECs, respectively. Abnormal ascites (12% vs. 11% vs. 0%) and heterogeneous signal on T1-weighted (28% vs. 50% vs. 9%), T2-weighted (64% vs. 72% vs. 36%), and fat-suppressed gadolinium-enhanced T1-weighted (80% vs. 90% vs. 46%) images were more frequent in SCs and CCCs than in ECs, respectively (p < 0.05). CONCLUSIONS: SCs frequently exhibited a heterogeneous signal with peritoneal dissemination and abnormal ascites. Alternatively, CCCs tended to have a larger tumor size and higher ADC values with an infiltrative growth pattern, heterogeneous signal, and abnormal ascites. KEY POINTS: • SCs tend to have a heterogeneous signal intensity with peritoneal dissemination and abnormal ascites compared to ECs. • CCCs tend to have a heterogeneous signal intensity with an infiltrative growth pattern and abnormal ascites compared to ECs. • CCCs have a larger tumor size and higher ADC values compared to ECs and SCs.

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

OBJECTIVES: To investigate the value of volumetric ADC histogram metrics for evaluating lymphovascular space invasion (LVSI) status in stage I endometrioid adenocarcinoma (EAC). METHODS: Preoperative MRI of 227 patients with stage I EAC were retrospectively analyzed. ADC histogram data were derived from the whole tumor with ROIs drawn on all slices of DWI scans (b = 0, 1000 s/mm2). The Student t-test was performed to compare ADC histogram metrics (minADC, maxADC, and meanADC; 10th, 25th, 50th, 75th, and 90th percentiles of ADC; skewness; and kurtosis) between the LVSI-positive and LVSI-negative groups, as well as between stage Ia and Ib EACs. ROC curve analysis was carried out to evaluate the diagnostic performance of ADC histogram metrics in predicting LVSI status in EAC. RESULTS: The minADC and meanADC and 10th, 25th, 50th, 75th, and 90th percentiles of ADC were significantly lower in LVSI-positive EACs compared with those in the LVSI-negative groups for stage I, Ia, and Ib EACs (all p < 0.05). MeanADC ≤ 0.857 × 10-3 mm2/s, meanADC ≤ 0.854 × 10-3 mm2/s, and the 90th percentile of ADC ≤ 1.06 × 10-3 mm2/s yielded the largest AUC of 0.844, 0.844, and 0.849 for evaluating LVSI positivity in stage I, Ia, and Ib tumors, respectively, with sensitivity of 75.4%, 75.0%, and 76.2%; specificity of 80.0%, 83.1%, and 82.1%; and accuracy of 79.3%, 81.5%, and 79.6%, respectively. CONCLUSION: Volumetric ADC histogram metrics might be helpful for the preoperative evaluation of LVSI status and personalized clinical management in patients with stage I EAC. KEY POINTS: • Volumetric ADC histogram analysis helps evaluate LVSI status preoperatively. • LVSI-positive EAC is associated with a reduction in multiple volumetric ADC histogram metrics. • MeanADC and the 90th percentile of ADC were shown to be best in evaluating LVSI- positivity in stage Ia and Ib EACs, respectively.

Transvaginal Ultrasound Versus Magnetic Resonance Imaging for Assessing Myometrial Infiltration in Endometrioid Low Grade Endometrial Cancer: A Prospective Study.

OBJECTIVE: To compare the diagnostic accuracy of transvaginal ultrasound (TVS) and magnetic resonance imaging (MRI) for assessing myometrial infiltration (MI) in patients with low grade endometrioid endometrial cancer. METHODS: Observational prospective study performed at a single tertiary care center from 2016 to 2020, comprising 156 consecutive patients diagnosed by endometrial sampling as having an endometrioid grade 1/grade 2 endometrial cancer. TVS and MRI were performed prior to surgical staging for assessing MI, which was estimated using subjective examiner's impression and Karlsson's method for both TVS and MRI. During surgery, intraoperative assessment of MI was also performed. Definitive pathological study considered as reference standard. Diagnostic accuracy for ultrasound, MRI, and intraoperative biopsy was estimated and compared. RESULTS: Sensitivity and specificity of TVS for detecting deep MI were 75 and 73.5% for subjective impression and 65 and 70% for Karlsson method, respectively (P = .54). Sensitivity and specificity of MRI for detecting deep MI were 80 and 87% for subjective impression and 70 and 71.3% for Karlsson method. MRI subjective impression showed a significant better specificity than MRI Karlsson method (P = .03). MRI showed better specificity than TVS when subjective impression was considered (P <.05), but not for Karlsson method. Sensitivity and specificity of intraoperative were 75 and 97%, respectively. Intraoperative biopsy showed better specificity than ultrasound and MRI either using examiner's impression or Karlsson method (P <.05). CONCLUSIONS: MRI revealed a significant higher specificity than TVS when assessing deep myometrial infiltration. However, the intraoperative biopsy offers a significant better diagnostic accuracy than preoperative imaging techniques.

Diffusion-weighted MRI at 3T in Endometrial Cancer: Correlation of Apparent Diffusion Coefficient with Histopathological Prognostic Parameters.

OBJECTIVE: To evaluate the value of apparent diffusion coefficient (ADC) for the differentiation of histological subtypes in endometrial cancer, and to assess if ADC values correlate with histopathological parameters. STUDY DESIGN: Descriptive study. PLACE AND DURATION OF STUDY: Department of Radiology, Faculty of Medicine, Ondokuz Mayis University between January 2016 and December 2019. METHODOLOGY: Eighty-three patients (mean age: 60.28 ± 9.07) with endometrial cancer underwent diffusion-weighted imaging (DWI) at 3T before surgery. The mean ADC (ADCmean) and minimum ADC (ADCmin) values of the tumours were assessed to predict histological subtype of endometrial cancer, grade of tumour, presence of myometrial invasion, lower uterine segment involvement, cervical involvement, lymphovascular invasion, and lymph node metastasis. RESULTS: Sixty patients (72.3%) were diagnosed with endometrioid carcinoma, and 23 patients (27.7%) were diagnosed with non-endometrioid carcinoma. The median ADCmean/ADCmin of endometrioid and non-endometrioid tumours were 0.72/0.58 ×10-3 mm2/s and 0.82/0.63 ×10-3 mm2/s, respectively. ADCmean and ADCmin were significantly different between endometrioid and non-endometrioid tumours (p=0.016 and p=0.048). For the endometrioid carcinomas, ADCmean and ADCmin were significantly different between low-grade (G1 and G2) and high-grade (G3) tumours (ADCmean/ADCmin = 0.75/0.65 vs. 0.59/0.49 x10-3 mm2/s, p=0.010 and p=0.013). Myometrial invasion, lymphovascular invasion, cervical involvement, lower uterine involvement, serosal involvement and lymph node metastasis were not significantly associated with ADC values. CONCLUSION: ADC measurements were useful for differentiating endometrioid and non-endometrioid carcinomas. High-grade endometrioid carcinomas had significantly lower ADC values compared to low-grade ones. Key Words: Endometrial cancer, Diffusion-weighted MRI, Apparent diffusion coefficient, Prognostic factors, Histological grade.

Combined use of ICG and technetium does not improve sentinel lymph node detection in endometrial cancer: Results of the COMBITEC study.

OBJECTIVE: There is scarce evidence available about the benefit of combining technetium (99mTc) and indocyanine green (ICG) for sentinel lymph node (SLN) biopsy in endometrial cancer. The aim of this study was to compare the overall and bilateral pelvic detection rates of SLNs in two retrospective cohorts: ICG exclusive vs. combined ICG+99mTc. METHODS: The COMBITEC study (COMBined ICG and Technetium for SLN detection in Endometrial Cancer) consisted of a multicentre retrospective study (February 2015-June 2020) including patients diagnosed with endometrial atypical hyperplasia or early-stage endometrial carcinoma who underwent SLN biopsy by cervical injection of ICG with or without 99mTc in four different referral centers in Spain. RESULTS: A total of 180 patients were included, 51% (n = 92) in ICG group and 49% (n = 88) in ICG+99mTc group. Eighty-seven percent of the patients presented endometrioid histology, and over 99% of the procedures were performed by a minimally invasive approach. Both groups were comparable regarding their basal characteristics, except for a higher body mass index in ICG+99mTc group and a bigger proportion of robotic-assisted procedures in ICG group. Overall detection rate was 92.8% without significant differences between groups (ICG: 94.6% vs ICG+99mTc: 90.9%, p = .34). No significant differences were observed neither in bilateral pelvic nor aortic mapping rate. When 99mTc was used, surgical procedures were significantly longer. In 7.3% of mapped patients, at least one positive SLN was found (ICG: 10.3% vs ICG+99mTc: 3.9%, p = .109). Empty node packet rates and number of SLNs retrieved per patient were also similar between cohorts. CONCLUSION: Combining preoperative 99mTc to intraoperative ICG did not improve SLN detection in endometrial cancer, but resulted in longer procedures.

Diagnostic performance of transvaginal ultrasound and magnetic resonance imaging for preoperative evaluation of low-grade endometrioid endometrial carcinoma: prospective comparative study.

OBJECTIVE: To compare the diagnostic performance of transvaginal ultrasound (TVS) and magnetic resonance imaging (MRI) in the prediction of deep myometrial invasion (DMI) and cervical stromal invasion (CSI) in patients with low-grade (Grade 1 or 2) endometrioid endometrial cancer (EEC). METHODS: This was a prospective study including all patients with low-grade EEC diagnosed between October 2013 and July 2018 at the Vall d'Hebron Hospital in Barcelona, Spain. Preoperative staging was performed using TVS and MRI, followed by surgical staging. Final histology was considered as the reference standard. Sensitivity, specificity, likelihood ratios and diagnostic accuracy were calculated for both imaging techniques in the prediction of DMI and CSI, and the agreement index was calculated for both techniques. The STARD 2015 guidelines were followed. RESULTS: A total of 131 patients with low-grade EEC were included consecutively. Sensitivity was higher for TVS than for MRI both for the prediction of DMI (69% (95% CI, 53-82%) vs 51% (95% CI, 36-66%), respectively) and CSI (43% (95% CI, 27-61%) vs 24% (95% CI, 12-41%), respectively). Specificity was similar for TVS and MRI in the prediction of DMI (87% (95% CI, 78-93%) vs 91% (95% CI, 82-96%)) and equal in the prediction of CSI (97% (95% CI, 91-99%) for both). The agreement index between TVS and MRI was 0.84 (95% CI, 0.76-0.90) for DMI and 0.92 (95% CI, 0.85-0.96) for CSI. CONCLUSIONS: The diagnostic performance of TVS is similar to that of MRI for the prediction of DMI and CSI in low-grade EEC, and TVS can play a role as a first-line imaging technique in the preoperative evaluation of low-grade EEC. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Efficacy of Endometrial Cancer Follow-up Protocols: Time to Change?

OBJECTIVE: The aim of the present study was to analyze relapse rates and patterns in patients with endometrial cancer with the aim of evaluating the effectiveness of current follow-up procedures in terms of patient survival, as well as the convenience of modifying the surveillance strategy. METHODS: Retrospective descriptive study including all patients diagnosed with endometrial cancer relapse at the Department of Gynecology and Obstetrics of the Complejo Hospitalario Insular-Materno Infantil de Canarias, between 2005 and 2014. RESULTS: Recurrence was observed in 81 patients (10.04% of the sample); 66.7% of them suffered relapse within 2 years and 80.2% within 3 years after the termination of the primary treatment; 41.9% showed distant metastases while the rest corresponded to local-regional (40.7%) or ganglionar (17.4%) relapse; 42% of these were symptomatic; 14 patients showed more than 1 site of relapse. Relapse was detected mainly through symptoms and physical examination findings (54.3%), followed by elevated serum marker levels (29.6%), computed tomography (CT) images (9.9%) and abnormal vaginal cytology findings (6.2%). No differences in global survival were found between patients with symptomatic or asymptomatic relapse. CONCLUSION: Taking into account that the recurrence rate of endometrial cancer is low, that relapse occurs mainly within the first 3 years post-treatment and that symptom evaluation and physical examination are the most effective follow-up methods, we postulate that a modification of the current model of hospital follow-up should be considered.