Carcinosarcoma of the uterus: MRI findings including diffusion-weighted imaging and MR spectroscopy

Evaluation of Uterine Carcinosarcoma and Uterine Endometrial Carcinoma Using Magnetic Resonance Imaging Findings and Texture Features

Aim  This study aimed to evaluate the diagnostic feasibility of magnetic resonance imaging (MRI) findings and texture features (TFs) for differentiating uterine endometrial carcinoma from uterine carcinosarcoma. Methods This retrospective study included 102 patients who were histopathologically diagnosed after surgery with uterine endometrial carcinoma (n=68) or uterine carcinosarcoma (n=34) between January 2008 and December 2021. We assessed conventional MRI findings and measurements (cMRFMs) and TFs on T2-weighted images (T2WI) and apparent diffusion coefficient (ADC) map, as well as their combinations, in differentiating between uterine endometrial carcinoma and uterine carcinosarcoma. The least absolute shrinkage and selection operator (LASSO) was used to select three features with the highest absolute value of the LASSO regression coefficient for each model and construct a discriminative model. Binary logistic regression analysis was used to analyze the disease models and conduct receiver operating characteristic analyses on the cMRFMs, T2WI-TFs, ADC-TFs, and their combined model to compare the two diseases. Results A total of four models were constructed from each of the three selected features. The area under the curve (AUC) of the discriminative model using these features was 0.772, 0.878, 0.748, and 0.915 for the cMRFMs, T2WI-TFs, ADC-TFs, and a combined model of cMRFMs and TFs, respectively. The combined model showed a higher AUC than the other models, with a high diagnostic performance (AUC=0.915). Conclusion A combined model using cMRFMs and TFs might be helpful for the differential diagnosis of uterine endometrial carcinoma and uterine carcinosarcoma.

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.

Magnetic resonance imaging for the diagnosis of malignant mixed Mullerian tumor of ovary: Two case reports

RATIONALE

Malignant mixed Mullerian tumor (MMMT) is also known as carcinosarcoma, mostly occurring in the uterus, and occurred in ovary is very rare. The disease is highly aggressive. Two cases of MMMT of ovary and their imaging characteristics were collected in our study.

PATIENT CONCERNS

A 77-year-old and an 80-year-old woman were admitted to the obstetrics and gynecology department of our hospital on June 22, 2019, and December 10, 2019, respectively. The first patient presented with abdominal distension with poor appetite without obvious triggers. Another patient had been menopausal for 18 years and presented with vaginal bleeding with dull pain in the left lower abdomen without obvious cause.

DIAGNOSES

Both patients underwent pelvic magnetic resonance imaging plain and enhanced scan after admission, which indicated pelvic mass. Postoperative pathology confirmed MMMT in the adnexal region.

INTERVENTIONS

Both patients underwent total hysterectomy and bilateral adnexectomy.

OUTCOMES

Postoperatively, the first patient developed complications such as renal failure and gastrointestinal bleeding and was sometimes unconscious. Symptomatic treatment was not effective, and the patient died about 1 month after discharge. The other patient recovered well after surgery, and imaging examinations confirmed no evidence of regrowth of the tumor during an average 36-month follow-up.

LESSONS

The disease is highly malignant and progresses rapidly. The elevation of CA125 should be taken seriously. The imaging findings of MMMT has certain characteristics. Multi-sequence magnetic resonance imaging may help to distinguish this disease from other pelvic tumors. Once found, surgical treatment is needed as soon as possible, followed by postoperative adjuvant radiotherapy and chemotherapy.

Clinical and imaging features of carcinosarcoma of the uterus and cervix

Aim

The purpose of our study was to analyze the clinical and imaging features of uterine carcinosarcoma (UCS) and cervical carcinosarcoma (CCS), and to explore the diagnostic and staging accuracy of computed tomography (CT) and magnetic resonance imaging (MRI) examinations.

Methods

41 patients including 37 with UCS and 4 with CCS from July 2011 to September 2020 were enrolled in the study. Of the 37 UCS cases, 7 had CT images, 27 had MRI images, and 3 had both CT and MRI images. The Clinical data, CT or MRI imaging findings were analyzed. Diagnosis and staging accuracy of CT and MRI images were also analyzed.

Results

Carcinosarcoma usually occurs in postmenopausal women (40/41), with the typical clinical symptom being vaginal bleeding (33/41). The CA125 degree was significantly different between the two invasion depth groups (p = 0.011). Most uterine carcinosarcomas showed unclear boundaries, uneven density, low or equal signal on T1WI, high or mixed signal on T2WI, uneven high signal on diffusion-weighted image (DWI), and mild enhancement. The diagnostic accuracies of CT and MRI for carcinosarcoma were 0% and 3.33%, respectively. The diagnostic accuracy for malignant tumors on CT and MRI was 50% and 83.33%, respectively.

Conclusions

Carcinosarcoma lesions presented with huge mass filling in the cavity, and some presented with small polypoid lesions or endometrial thickening. Evaluation of lymph node metastasis is a significant challenge for imaging staging.

Pathological characteristics and risk stratification in patients with stage I endometrial cancer: utility of apparent diffusion coefficient histogram analysis

OBJECTIVES

Accurate pre-operative prediction of risk stratification using a non-invasive imaging tool is clinically important for planning optimal treatment strategies, particularly in early-stage endometrial cancer (EC). This study aimed to investigate the utility of apparent diffusion coefficient (ADC) histogram analysis in evaluating the pathological characteristics and risk stratification in patients with Stage I EC.

METHODS

Between October 2009 and December 2014, a total of 108 patients with surgically proven Stage I EC (endometrioid type = 91; non-endometrioid type = 17) excluding stage ≥II that underwent preoperative 3T-diffusion-weighted imaging without administration of contrast medium were enrolled in this retrospective study. Risk stratification was divided into four risk categories based on the ESMO-ESGO-ESTRO Guidelines: low, intermediate, high-intermediate, and high risk. The ADC histogram parameters (minimum, mean [ADCmean], 10th-90th percentile, and maximum [ADCmax]) of the tumor were generated using an in-house software. The ADC histogram parameters were compared between patients with endometrioid type and non-endometrioid type, between Stage IA and IB, between histological grades, and evaluated for differentiating non-high risk group from high risk group. Inter-reader agreement for tumor ADC measurements was also evaluated. Statistical analyses were performed using the Student's t-test, Mann-Whitney U test, receiver operating characteristics (ROC) analysis, or intraclass correlation coefficient (ICC).

RESULTS

In differentiating endometrioid type from non-endometrioid type EC, all ADC histogram parameters were statistically significant (p < 0.05). In differentiating histological grades, 90th percentile ADC and ADCmax showed significantly higher values in tumor Grade III than in tumor Grade I-II (p < 0.05). In differentiating superficial myometrial invasion from deep myometrial invasion, all ADC histogram parameters were statistically significant (p < 0.05), except ADCmax. In differentiating non-high risk group from high risk group, ADCmean, 75th-90th percentile ADC, and ADCmax were statistically significant (p < 0.05). For predicting the high risk group, the area under the ROC curve of ADCmax was 0.628 and the highest among other histogram parameters. All histogram parameters revealed moderate to good inter-reader reliability (ICC = 0.581‒0.769).

CONCLUSION

The ADC histogram analysis as reproducible tool may be useful for evaluating the pathological characteristics and risk stratification in patients with early-stage EC.

ADVANCES IN KNOWLEDGE

ADC histogram analysis may be useful for evaluating risk stratification in early-stage endometrial cancer patients.

Differentiating uterine sarcoma from leiomyoma: BET1T2ER Check!

Although rare, uterine sarcoma is a diagnosis that no one wants to miss. Often benign leiomyomas (fibroids) and uterine sarcomas can be differentiated due to the typical low T2 signal intensity contents and well-defined appearances of benign leiomyomas compared to the suspicious appearances of sarcomas presenting as large uterine masses with irregular outlines and intermediate T2 signal intensity together with possible features of secondary spread. The problem is when these benign lesions are atypical causing suspicious imaging features. This article provides a review of the current literature on imaging features of atypical fibroids and uterine sarcomas with an aide-memoire BET¹T²ER Check! to help identify key features more suggestive of a uterine sarcoma.

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.

Multiparametric magnetic resonance imaging of endometrial polypoid lesions

Endometrial polypoid lesions encompass various conditions from physiologic changes to benign or malignant disease. Differentiating between the various causes of endometrial polypoid lesions remains difficult by transvaginal sonography. Magnetic resonance imaging (MRI) can provide valuable information regarding endometrial polypoid lesions in situations where it is difficult to obtain histologic samples. Multiparametric MRI including T2-weighted images, T1-weighted fat-saturation contrast-enhanced images, and diffusion-weighted images may be helpful for differentiating the various endometrial polypoid lesions and establishing specific diagnoses and appropriate treatment.

Imaging Features of Carcinosarcoma Arising from Adenofibroma of the Uterus: A Case Report

BACKGROUND

Adenofibroma is a benign tumor composed histologically of epithelial elements and mesenchymal stroma. Carcinosarcoma is a malignant neoplasm that contains elements of carcinoma and sarcoma. Carcinosarcoma arising from adenofibroma of the uterus has never been reported in the literature in English language. Case Presentaion: We report a case of a 56-year-old woman who complained vaginal spotting persisting for several months. We described here for the first time a case of malignant transformation of uterine endometrial adenofibroma into carcinosarcoma that was depicted as a multilocular cystic lesion with enhancing solid portions and stalk-like structure between the myometrium and endometrial mass.

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.

Staging MRI of uterine malignant mixed Müllerian tumors versus endometrial carcinomas with emphasis on dynamic enhancement characteristics

PURPOSE

To determine whether staging pelvic magnetic resonance imaging (MRI) can distinguish malignant mixed Müllerian tumor (MMMT) from EC.

METHODS

Thirty-seven treatment-naïve patients with histologically proven uterine MMMT and 42 treatment-naïve patients with EC, treated at our institution, were included in our retrospective study. Staging pelvic MRI scans were reviewed for tumor size, prolapse through cervical os, and other features. Time-intensity curves for tumor and surrounding myometrium regions of interest were generated, and positive enhancement integral (PEI), maximum slope of increase (MSI), and signal enhancement ratio (SER) were measured. The Fisher's exact test or Wilcoxon rank-sum test was used to compare characteristics between disease groups. Multivariate and univariate logistic regression models were used to distinguish MMMT from EC. Receiver operating characteristic analysis and the area under the curve (AUC) were used to evaluate prediction ability.

RESULTS

MMMTs were larger than ECs with higher rate of tumor prolapse and more heterogeneous tumor enhancement compared to ECs. During the late phase of contrast enhancement, 100% of ECs, but only 84% of MMMTs, had lower signal intensity than the myometrium. Threshold PEI ratio ≥ 0.67 predict MMMT with 76% sensitivity, 84%, specificity and 0.83 AUC. Threshold SER ≤ 125 predict MMMT with 90% sensitivity, 50% specificity, and 0.72 AUC.

CONCLUSION

MMMTs may show more frequent tumor prolapse, more heterogeneous enhancement, delayed iso- or hyper-enhancement, higher PEI ratios, and lower tumor SERs compared with EC. MRI can be used as a biomarker to distinguish MMMT from EC based on the enhancement pattern.

Utility of diffusion-weighted and contrast-enhanced magnetic resonance imaging in diagnosing and differentiating between high- and low-grade uterine endometrial stromal sarcoma

BACKGROUND

Endometrial stromal sarcoma (ESS) is a rare uterine malignancy that features different prognoses for its high- and low-grade subtypes. We investigated the diagnostic accuracy of magnetic resonance (MR) imaging in diagnosing and differentiating between high- and low-grade ESS.

METHODS

We retrospectively reviewed the preoperative pelvic MR images of consecutive patients who received histologically confirmed diagnoses of high-grade ESS (n = 11) and low-grade ESS (n = 9) and T2-hyperintense leiomyoma (n = 16). Two radiologists independently evaluated imaging features in T1-, T2-, and diffusion-weighted and contrast-enhanced MR images. Statistical analysis included Mann-Whitney tests and Fisher's exact test, with sensitivity, specificity and diagnostic accuracy of imaging features.

RESULTS

High-grade ESS was associated with significantly more extensive necrosis and hemorrhage and distinct feather-like enhancement compared with low-grade ESS (P < .05 for all). The feather-like enhancement pattern yielded a diagnostic accuracy of 95%, sensitivity of 91%, and specificity of 100% in differentiating high-grade from low-grade ESS. This imaging characteristic was significantly superior to the necrosis (80%, P = .033) or hemorrhage (75%, P = .007). Both high- and low-grade ESS demonstrated T2 hypointense bands, marginal nodules, intratumoral nodules, and worm-like intra-myometrial nodules, and their tumor apparent diffusion coefficient (ADC) values were significantly lower than those of T2-hyperintense leiomyomas (P < .001).

CONCLUSIONS

Diffusion-weighted MR imaging is useful in diagnosing ESS against T2-hyperintense leiomyomas, and contrast enhancement aids in further differentiating between high- and low-grade ESS.

Current Status of Magnetic Resonance Imaging in Patients with Malignant Uterine Neoplasms: A Review

In this study, we summarize the clinical role of magnetic resonance imaging (MRI) in the diagnosis of patients with malignant uterine neoplasms, including leiomyosarcoma, endometrial stromal sarcoma, adenosarcoma, uterine carcinosarcoma, and endometrial cancer, with emphasis on the challenges and disadvantages. MRI plays an essential role in patients with uterine malignancy, for the purpose of tumor detection, primary staging, and treatment planning. MRI has advanced in scope beyond the visualization of the many aspects of anatomical structures, including diffusion-weighted imaging, dynamic contrast enhancement-MRI, and magnetic resonance spectroscopy. Emerging technologies coupled with the use of artificial intelligence in MRI are expected to lead to progressive improvement in case management of malignant uterine neoplasms.

Early Diffusion-Weighted Imaging and Proton Magnetic Resonance Spectroscopy Features of Liver Transplanted Tumors Treated with Radiation in Rabbits: Correlation with Histopathology

In this study, we sought to determine how diffusion-weighted imaging (DWI) and proton magnetic resonance spectroscopy (¹H-MRS) features are associated with histopathological results, and explored the cellular mechanisms of DWI and ¹H-MRS in early radiosensitivity of transplanted liver tumors. VX2 tumors were implanted into the hind leg muscles of 60 New Zealand White Rabbits. All rabbits were randomly divided into ten subgroups according to treatment: irradiated or nonirradiated and according to different times postirradiation. Magnetic resonance scanning was then performed one day before irradiation and on days 1, 3, 5 and 7 postirradiation. Differences in tumor volume, apparent diffusion coefficient (ADC) value, choline/creatine ratio and lipid/creatine ratio, and their associations with histopathological findings, were assessed. Tumor volumes in the irradiated groups were smaller than control values, while ADC values increased gradually with time postirradiation; choline/creatine ratios were reduced while lipid/creatine ratios were larger compared to control values. Bax protein levels after irradiation increased with time. Interestingly, the ADC value and Bax-positive grade showed the same increasing trend (r = 0.900, P < 0.001). Additionally, choline/creatine and lipid/creatine ratios were respectively significantly associated with Bax-positive grade. Furthermore, significant associations of tumor volume with ADC value, choline/creatine ratio and lipid/creatine ratio were observed. These findings demonstrated that ADC value, choline/creatine ratio and lipid/creatine ratio, indicators of early radiosensitivity, are related to cell apoptosis.

Clinical applications of in vivo magnetic resonance spectroscopy in oncology

Magnetic resonance spectroscopy (MRS) can be performed in vivo using commercial MRI systems to obtain biochemical information about tissues and cancers. Applications in brain, prostate and breast aid lesion detection and characterisation (differential diagnosis), treatment planning and response assessment. Multi-centre clinical trials have been performed in all these tissues. Single centre studies have been performed in many other tissues including cervix, uterus, musculoskeletal and liver. While generally MRS is used to study endogenous metabolites it has also been used in drug studies, for example those that include 19F as part of their structure. Recently the hyperpolarisation of compounds enriched with 13C such as [1-13C] pyruvate has been demonstrated in animal models and now in preliminary clinical studies, permitting the monitoring of biochemical processes with unprecedented sensitivity. This review briefly introduces the underlying methods and then discusses the current status of these applications.

Utility of Clinical Parameters and Multiparametric MRI as Predictive Factors for Differentiating Uterine Sarcoma From Atypical Leiomyoma

OBJECTIVES

The objective of this study was to find clinical parameters and qualitative and quantitative magnetic resonance imaging (MRI) features for differentiating uterine sarcoma from atypical leiomyoma (ALM) preoperatively and to calculate predictive values for uterine sarcoma.

MATERIALS AND METHODS

Data from 60 patients with uterine sarcoma and 88 patients with ALM confirmed by surgery and pathology were collected. Clinical parameters, qualitative MRI features, diffusion-weighted imaging with apparent diffusion coefficient values, and quantitative parameters of dynamic contrast-enhanced MRI of these two tumor types were compared. Predictive values for uterine sarcoma were calculated using multivariable logistic regression.

RESULTS

Patient clinical manifestations, tumor locations, margins, T2-weighted imaging signals, mean apparent diffusion coefficient values, minimum apparent diffusion coefficient values, and time-signal intensity curves of solid tumor components were obvious significant parameters for distinguishing between uterine sarcoma and ALM (all P <.001). Abnormal vaginal bleeding, tumors located mainly in the uterine cavity, ill-defined tumor margins, and mean apparent diffusion coefficient values of <1.272 × 10^-3mm²/s were significant preoperative predictors of uterine sarcoma. When the overall scores of these four predictors were greater than or equal to 7 points, the sensitivity, the specificity, the accuracy, and the positive and negative predictive values were 88.9%, 99.9%, 95.7%, 97.0%, and 95.1%, respectively.

CONCLUSIONS

The use of clinical parameters and multiparametric MRI as predictive factors was beneficial for diagnosing uterine sarcoma preoperatively. These findings could be helpful for guiding treatment decisions.

Renal cell carcinoma with venous extension: prediction of inferior vena cava wall invasion by MRI

BACKGROUND

Renal cell carcinoma (RCC) are accompanied by inferior vena cava (IVC) thrombus in up to 10% of the cases, with surgical resection remaining the only curative option. In case of IVC wall invasion, the operative procedure is more challenging and may even require IVC resection. This study aims to determine the diagnostic performance of contrast-enhanced magnetic resonance imaging (MRI) for the assessment of wall invasion by IVC thrombus in patients with RCC, validated with intraoperative findings.

METHODS

Data were collected on 81 patients with RCC and IVC thrombus, who received a radical nephrectomy and vena cava thrombectomy between February 2008 and November 2017. Forty eight patients met the inclusion criteria. Sensitivity and specificity as well as the positive and negative predictive values were calculated for preoperative MRI, based on the assessments of the two readers for visual wall invasion. Furthermore, a logistic regression model was used to determine if there was an association between intraoperative wall adherence and IVC diameter.

RESULTS

Complete occlusion of the IVC lumen or vessel breach could reliably assess IVC wall invasion with a sensitivity of 92.3% (95%-CI: 0.75-0.99) and a specificity of 86.4% (95%-CI: 0.65-0.97) (Fisher-test: p-value< 0.001). The positive predictive value (PPV) was 88.9% (95%-CI: 0.71-0.98) and the negative predictive value reached 90.5% (95%-CI: 0.70-0.99). There was an excellent interobserver agreement for determining IVC wall invasion with a kappa coefficient of 0.90 (95%CI: 0.79-1.00).

CONCLUSIONS

The present study indicates that standard preoperative MR imaging can be used to reliably assess IVC wall invasion, evaluating morphologic features such as the complete occlusion of the IVC lumen or vessel breach. Increases in IVC diameter are associated with a higher probability of IVC wall invasion.

In vivo MR spectroscopy predicts high tumor grade in endometrial cancer

Background In vivo magnetic resonance spectroscopy (MRS) enables non-invasive measurements of tumor metabolites. Choline-containing metabolites play a key role in tumor metabolism. Purpose To explore whether preoperative MRS-derived tumor choline levels are associated with clinical and histological features in endometrial carcinomas. Material and Methods Preoperative pelvic magnetic resonance imaging (MRI) (1.5T), including structural and diffusion-weighted imaging and localized multivoxel proton MR (1H-MR) spectroscopy, was performed in 77 prospectively included patients with histologically confirmed endometrial carcinomas. Relative levels of total choline-containing metabolites (tCho) in tumor and myometrium were measured using the ratios: tCho/Creatine; tCho/Water; and tCho/Noise. MRS parameters were analyzed in relation to histological subtype and grade, surgicopathological staging parameters, MRI-measured tumor volume, and tumor apparent diffusion coefficient (ADC) value and clinical outcome. Results Tumor tissue had significantly higher ratios for tCho/Creatine, tCho/Water, and tCho/Noise than normal myometrial tissue ( P < 0.001 for all). High tumor tCho/Water ratio was significantly associated with high tumor grade in endometrioid tumors ( P = 0.02). Tumor tCho/Creatine ratio was positively correlated to MRI-measured tumor volume (r_s = 0.25; P = 0.03). Conclusion High choline levels in tumor are associated with high-risk features. In vivo MRS may potentially aid in the preoperative risk stratification in endometrial cancer.

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

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

Diagnostic accuracy of 3.0T diffusion-weighted MRI for patients with uterine carcinosarcoma: Assessment of tumor extent and lymphatic metastasis

BACKGROUND

Assessment of tumor extent and lymphatic metastasis of uterine carcinosarcomas is important for treatment planning.

PURPOSE/HYPOTHESIS

To evaluate the diagnostic accuracy of 3.0T diffusion-weighted (DW) MRI for patients with uterine carcinosarcoma, in assessment of tumor extent and lymphatic metastasis.

STUDY TYPE

Retrospective diagnostic accuracy study.

POPULATION

A consecutive cohort of 68 patients with pathologically proved carcinosarcoma between January 2006 and July 2014.

FIELD STRENGTH/SEQUENCE

3T DW MRI.

ASSESSMENT

Maximal tumor and uterus size, presence of deep myometrial invasion, cervical invasion, adnexal invasion, lymphadenopathy, and the apparent diffusion coefficient (ADC) values of each tumor were used. Histopathology was the gold standard.

STATISTICAL TESTS

Diagnostic accuracy. Logistic regression.

RESULTS

In all, 38 patients entered the final analysis, with median age of 58 years (range, 35-79 years). The sensitivity and specificity in detecting deep myometrial invasion, cervical stromal invasion, adnexal invasion, as well as pelvic and para-aortic lymph node metastases were 65% and 72%, 91% and 85%, 50% and 100%, 33% and 89%, and 33% and 100%, respectively. The largest tumor diameters predicted deep myometrium invasion (anteroposterior direction, P = 0.004) and cervical stroma invasion (craniocaudal direction, P = 0.008). Tumor ADCmin significantly predicted the lymphovascular permeation (P = 0.025; odds ratio = 0.96).

DATA CONCLUSION

Preoperative DW MRI is useful to assess deep myometrial or cervical stromal invasion in uterine carcinosarcoma, yet the diagnostic performance for detecting adnexal invasion and lymphatic metastasis requires further improvement.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

A predictive diagnostic model using multiparametric MRI for differentiating uterine carcinosarcoma from carcinoma of the uterine corpus

PURPOSE

To construct a diagnostic model for differentiating carcinosarcoma from carcinoma of the uterus.

MATERIALS AND METHODS

Twenty-six patients with carcinosarcomas and 26 with uterine corpus carcinomas constituted a derivation cohort. The following nine MRI features of the tumors were evaluated: inhomogeneity, predominant signal intensity, presence of hyper- and hypointense areas, conspicuity of tumor margin, cervical canal extension on T2WI, presence of hyperintense areas on T1WI, contrast defect area volume percentage, and degree of enhancement. Two predictive models-with and without contrast-were constructed using multivariate logistic regression analysis. Fifteen other patients with carcinosarcomas and 30 patients with carcinomas constituted a validation cohort. The sensitivity and specificity of each model for the validation cohort were calculated.

RESULTS

Inhomogeneity, predominant signal intensity on T2WI, and presence of hyperintense areas on T1WI were significant predictors in the unenhanced-MRI-based model. Presence of hyperintensity on T1WI, contrast defect area volume percentage, and degree of enhancement were significant predictors in the enhanced-MRI-based model. The sensitivity/specificity of unenhanced MRI were 87/73 and 87/70% according to reviewer 1 and 2, respectively. The sensitivity/specificity of the enhanced-MRI-based model were 87/70% according to both reviewers.

CONCLUSIONS

Our diagnostic models can differentiate carcinosarcoma from carcinoma of the uterus with high sensitivity and moderate specificity.