Preoperative evaluation in women with uterine leiomyosarcoma. A nationwide cohort study

Intraperitoneal spread in uterine sarcoma following unprotected laparoscopic transvaginal uterine morcellation: a case report and literature review

Clinically and through auxiliary examinations, distinguishing uterine leiomyoma from early-stage uterine sarcoma presents significant challenges. A 48-year-old patient underwent a laparoscopic hysterectomy for uterine leiomyoma, during which a large uterus was excised through the vagina and extracted. Four months post-operation, the patient developed abdominal distension, indicative of extensive pelvic-abdominal dissemination of uterine sarcoma. We hypothesize that unprotected fibroid fragmentation increases the risk of uterine sarcoma spread, thereby worsening the prognosis. Our literature review aims to thoroughly understand the risks associated with unprotected transvaginal laparoscopic tumor division.

Results of Endometrial Biopsy and Its Impact on Survival Data in Patients with High-Risk Uterine Sarcoma

Background: There are conflicting data regarding the detection rate of high-risk uterine sarcoma (HRUS) by endometrial biopsy. In addition, there are no studies in the literature on its impact on the chosen surgical approach and survival. Methods: This study includes 415 patients with HRUS. Of these, 178 (42.9%) patients had undergone endometrial biopsy. We analyzed the detection rate of endometrial biopsy and its impact on surgical approach and survival data. Results: Correct specific histologic diagnosis was achieved in only 30.0% of LMS and 33.3% of HGESS/UUS. Other uterine sarcoma, unspecified malignant mesenchymal tumor, carcinosarcoma or carcinoma were found in 45% of LMS and 78.2% of HGESS/UUS. As a result of the histologic findings, the rate of inadequate surgery was reduced by up to 19.9%. As tumor morcellation was performed significantly less often with biopsy (32.5% with vs. 55.4% without biopsy, p < 0.001), the locoregional recurrence-free interval remained unaffected between the two groups (p = 0.81). This is obviously an advantage of biopsy, although it does not affect the local recurrence rate in morcellated patients. Conclusions: Indicated endometrial biopsy is an important step in the diagnosis of HRUS, despite its low detection rate. It helps to avoid inappropriate surgical procedures but does not affect OS.

Prevalence of sonographic signs in women with uterine sarcoma: a systematic review and meta-analysis

OBJECTIVE

To assess the prevalence of sonographic signs in women with uterine sarcoma.

MATERIALS AND METHODS

A systematic review and meta-analysis were performed. Five electronic databases were searched from inception to June 2022 for all studies allowing calculation of the prevalence of sonographic signs in women with uterine sarcoma. Pooled prevalence with 95% confidence intervals was calculated for each sonographic sign and was a priori defined as "very high" when it was ≥ 80%, "high" when it ranged from 80% to 70%, and less relevant when it was ≤ 70%.

RESULTS

6 studies with 317 sarcoma patients were included. The pooled prevalence was: · 25.0% (95%CI:15.4-37.9%) for absence of visibility of the myometrium. · 80.5% (95%CI:74.8-85.2%) for solid component. · 78.3% (95%CI:59.3-89.9%) for inhomogeneous echogenicity of solid component. · 47.9% (95%CI:41.1-54.8%) for cystic areas. · 80.7% (95%CI:68.3-89.0%) for irregular walls of cystic areas. · 72.3% (95%CI:16.7-97.2%) for anechoic cystic areas. · 54.8% (95%CI:34.0-74.1%) for absence of shadowing. · 73.5% (95%CI:43.3-90.9%) for absence of calcifications. · 48.7% (95%CI:18.6-79.8%) for color score 3 or 4. · 47.3% (95%CI:37.0-57.8%) for irregular tumor borders. · 45.4% (95%CI:27.6-64.3%) for endometrial cavity not visualizable. · 10.9% (95%CI:3.5-29.1%) for free pelvic fluid. · 6.4% (95%CI:1.1-30.2%) for ascites. · 21.2% (95%CI:2.1-76.8%) for intracavitary process. · 81.5% (95%CI:56.1-93.8%) for singular lesion..

CONCLUSION

Solid component, irregular walls of cystic areas, and singular lesions are signs with very high prevalence, while inhomogeneous echogenicity of solid component, anechoic cystic areas, and absence of calcifications are signs with high prevalence. The remaining signs were less relevant.

Machine Learning Applied to Pre-Operative Computed-Tomography-Based Radiomic Features Can Accurately Differentiate Uterine Leiomyoma from Leiomyosarcoma: A Pilot Study

BACKGROUND

The accurate discrimination of uterine leiomyosarcomas and leiomyomas in a pre-operative setting remains a current challenge. To date, the diagnosis is made by a pathologist on the excised tumor. The aim of this study was to develop a machine learning algorithm using radiomic data extracted from contrast-enhanced computed tomography (CECT) images that could accurately distinguish leiomyosarcomas from leiomyomas.

METHODS

Pre-operative CECT images from patients submitted to surgery with a histological diagnosis of leiomyoma or leiomyosarcoma were used for the region of interest identification and radiomic feature extraction. Feature extraction was conducted using the PyRadiomics library, and three feature selection methods combined with the general linear model (GLM), random forest (RF), and support vector machine (SVM) classifiers were built, trained, and tested for the binary classification task (malignant vs. benign). In parallel, radiologists assessed the diagnosis with or without clinical data.

RESULTS

A total of 30 patients with leiomyosarcoma (mean age 59 years) and 35 patients with leiomyoma (mean age 48 years) were included in the study, comprising 30 and 51 lesions, respectively. Out of nine machine learning models, the three feature selection methods combined with the GLM and RF classifiers showed good performances, with predicted area under the curve (AUC), sensitivity, and specificity ranging from 0.78 to 0.97, from 0.78 to 1.00, and from 0.67 to 0.93, respectively, when compared to the results obtained from experienced radiologists when blinded to the clinical profile (AUC = 0.73 95%CI = 0.62-0.84), as well as when the clinical data were consulted (AUC = 0.75 95%CI = 0.65-0.85).

CONCLUSIONS

CECT images integrated with radiomics have great potential in differentiating uterine leiomyomas from leiomyosarcomas. Such a tool can be used to mitigate the risks of eventual surgical spread in the case of leiomyosarcoma and allow for safer fertility-sparing treatment in patients with benign uterine lesions.

Diagnostic Accuracy of Ultrasound in the Diagnosis of Uterine Leiomyomas and Sarcomas

BACKGROUND

Differential diagnosis between uterine leiomyomas and sarcomas is challenging. Ultrasound shows an uncertain role in the clinical practice given that pooled estimates about its diagnostic accuracy are lacking.

OBJECTIVES

To assess the accuracy of ultrasound in the differential diagnosis between uterine leiomyomas and sarcomas.

DATA SOURCES

A systematic review was performed searching 5 electronic databases (MEDLINE, Web of Sciences, Google Scholar, Scopus, and ClinicalTrial.gov) from their inception to June 2023.

METHODS OF STUDY SELECTION

All peer-reviewed observational or randomized clinical trials that reported an unbiased postoperative histologic diagnosis of uterine leiomyoma or uterine sarcoma that also comprised a preoperative ultrasonographic evaluation of the uterine mass.

TABULATION, INTEGRATION, AND RESULTS

Sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratio, and area under the curve on summary receiver operating characteristic were calculated for each included study and as pooled estimate, with 95% confidence interval (CI); 972 women (694 with uterine leiomyomas and 278 with uterine sarcomas) were included. Ultrasound showed pooled sensitivity of 0.76 (95% CI, 0.70-0.81), specificity of 0.89 (95% CI, 0.87-0.92), positive and negative likelihood ratios of 6.65 (95% CI, 4.45-9.93) and 0.26 (95% CI, 0.07-1.0) respectively, diagnostic odds ratio of 23.06 (95% CI, 4.56-116.53), and area under the curve of 0.8925.

CONCLUSIONS

Ultrasound seems to have only a moderate diagnostic accuracy in the differential diagnosis between uterine leiomyomas and sarcomas, with a lower sensitivity than specificity.

Survivin-Sodium Iodide Symporter Reporter as a Non-Invasive Diagnostic Marker to Differentiate Uterine Leiomyosarcoma from Leiomyoma

Leiomyosarcoma (LMS) has been challenging to diagnose because of limitations in clinical and radiographic predictors, as well as the lack of reliable serum or urinary biomarkers. Most uterine masses consist of benign leiomyoma (LM). However, it is currently a significant challenge in gynecology practice to differentiate LMS from LM. This inability poses grave consequences for patients, leading to a high number of unnecessary hysterectomies, infertility, and other major morbidities and possible mortalities. This study aimed to evaluate the use of Survivin-Sodium iodide symporter (Ad-Sur-NIS) as a reporter gene biomarker to differentiate malignant LMS from benign LM by using an F18-NaBF4 PET/CT scan. The PET/CT scan images showed a significantly increased radiotracer uptake and a decreased radiotracer decay attributable to the higher abundance of Ad-Sur-NIS in the LMS tumors compared to LM (p < 0.05). An excellent safety profile was observed, with no pathological or metabolic differences detected in Ad-Sur-NIS-treated animal versus the vehicle control. Ad-Sur-NIS as a PET scan reporter is a promising imaging biomarker that can differentiate uterine LMS from LM using F18-NaBF4 as a radiotracer. As a new diagnostic method, the F18 NaBF4 PET/CT scan can provide a much-needed tool in clinical practices to effectively triage women with suspicious uterine masses and avoid unnecessary invasive interventions.

A human-interpretable machine learning pipeline based on ultrasound to support leiomyosarcoma diagnosis

The preoperative evaluation of myometrial tumors is essential to avoid delayed treatment and to establish the appropriate surgical approach. Specifically, the differential diagnosis of leiomyosarcoma (LMS) is particularly challenging due to the overlapping of clinical, laboratory and ultrasound features between fibroids and LMS. In this work, we present a human-interpretable machine learning (ML) pipeline to support the preoperative differential diagnosis of LMS from leiomyomas, based on both clinical data and gynecological ultrasound assessment of 68 patients (8 with LMS diagnosis). The pipeline provides the following novel contributions: (i) end-users have been involved both in the definition of the ML tasks and in the evaluation of the overall approach; (ii) clinical specialists get a full understanding of both the decision-making mechanisms of the ML algorithms and the impact of the features on each automatic decision. Moreover, the proposed pipeline addresses some of the problems concerning both the imbalance of the two classes by analyzing and selecting the best combination of the synthetic oversampling strategy of the minority class and the classification algorithm among different choices, and the explainability of the features at global and local levels. The results show very high performance of the best strategy (AUC = 0.99, F1 = 0.87) and the strong and stable impact of two ultrasound-based features (i.e., tumor borders and consistency of the lesions). Furthermore, the SHAP algorithm was exploited to quantify the impact of the features at the local level and a specific module was developed to provide a template-based natural language (NL) translation of the explanations for enhancing their interpretability and fostering the use of ML in the clinical setting.

High negative prediction for the Basel sarcoma score: Sonographic assessment of features suspicious of uterine sarcoma

INTRODUCTION

In the management of uterine myomas, laparoscopic surgery with morcellation enables a minimal invasive procedure. Cases of unsuspected uterine sarcoma dissemination have been reported and led to regulative restrictions. To help to distinguish preoperatively myomas from sarcomas, we assessed the value of six sonographic criteria (Basel Sarcoma Score, BSS) in a prospective outpatient cohort of consecutive patients with uterine masses.

MATERIAL AND METHODS

We prospectively evaluated all patients presenting with myoma-like masses planned for surgery with standardized ultrasound examination. BSS including the following criteria was investigated: rapid growth in past three months, high blood flow, atypical growth, irregular lining, central necrosis and oval solitary lesion. For each criterion, a score 0/1 was given. BSS (0-6) equals the sum of all given scores. Histological diagnosis was used as reference.

RESULTS

Among 545 patients, 522 had the final diagnosis of myoma, 16 had peritoneal masses with sarcomatous components (PMSC), and seven had other malignancies. Median BSS for PMSC was 2.5 (range: 0-4) vs 0 for myomas (range: 0-3). The most common sonographic criteria leading to a false positive score in myomas were rapid growth in past three months and high blood flow. For the detection of sarcomatous masses with BSS threshold of >1, sensitivity was 93.8%, specificity 97.9%, and positive predictive value (PPV) and negative predictive value (NPV) were 57.7% and 99.8%, respectively (AUC 0.95).

CONCLUSION

BSS can help distinguishing between myomas and sarcomatous masses, with high NPV. Caution is required when >1 criterion is present. As a simple tool, it could easily be integrated into routine myoma sonographic examination and help develop standardized assessment of uterine masses for better preoperative triage.

Overlap of Suspicious and Non-Suspicious Features in the Ultrasound Evaluations of Leiomyosarcoma: A Single-Center Experience

Leiomyosarcoma (LMS) is a rare type of mesenchymal tumor. Suspecting LMS before surgery is crucial for proper patient management. Ultrasound is the primary method for assessing myometrial lesions. The overlapping of clinical, laboratory, as well as ultrasound features between fibroids and LMS makes differential diagnosis difficult. We report our single-center experience in ultrasound imaging assessment of LMS patients, highlighting that misleading findings such as shadowing and absent or minimal vascularization may also occur in LMS. To avoid mistakes, a comprehensive evaluation of potentially overlapping ultrasound features is necessary in preoperative ultrasound evaluations of all myometrial tumors.

Sarcoma of the Uterus. Guideline of the DGGG, OEGGG and SGGG (S2k-Level, AWMF Registry No. 015/074, April 2021)

Purpose This is an official guideline, published and coordinated by the Germany Society for Gynecology and Obstetrics (Deutsche Gesellschaft für Gynäkologie und Geburtshilfe, DGGG). Because of their rarity and heterogeneous histopathology, uterine sarcomas are challenging in terms of their clinical management and therefore require a multidisciplinary approach. To our knowledge, there are currently no binding evidence-based recommendations for the appropriate management of this heterogeneous group of tumors. Methods This S2k guideline was first published in 2015. The update published here is once again the result of the consensus of a representative interdisciplinary committee of experts who were commissioned by the Guidelines Committee of the DGGG to carry out a systematic search of the literature on uterine sarcomas. Members of the participating professional societies achieved a formal consensus after a structured consensus process. Recommendations 1.1 Epidemiology, classification, staging of uterine sarcomas. 1.2 Symptoms, general diagnostic workup, general pathology or genetic predisposition to uterine sarcomas. 2. Management of leiomyosarcomas. 3. Management of low-grade endometrial stromal sarcomas. 4. Management of high-grade endometrial stromal sarcoma and undifferentiated uterine sarcomas. 5. Management of adenosarcomas. 6. Rhabdomyosarcomas of the uterus in children and adolescents. 7. Follow-up of uterine sarcomas. 8. Management of morcellated uterine sarcomas. 9. Information provided to patients.

Development of a deep learning method for improving diagnostic accuracy for uterine sarcoma cases

Uterine sarcomas have very poor prognoses and are sometimes difficult to distinguish from uterine leiomyomas on preoperative examinations. Herein, we investigated whether deep neural network (DNN) models can improve the accuracy of preoperative MRI-based diagnosis in patients with uterine sarcomas. Fifteen sequences of MRI for patients (uterine sarcoma group: n = 63; uterine leiomyoma: n = 200) were used to train the models. Six radiologists (three specialists, three practitioners) interpreted the same images for validation. The most important individual sequences for diagnosis were axial T2-weighted imaging (T2WI), sagittal T2WI, and diffusion-weighted imaging. These sequences also represented the most accurate combination (accuracy: 91.3%), achieving diagnostic ability comparable to that of specialists (accuracy: 88.3%) and superior to that of practitioners (accuracy: 80.1%). Moreover, radiologists' diagnostic accuracy improved when provided with DNN results (specialists: 89.6%; practitioners: 92.3%). Our DNN models are valuable to improve diagnostic accuracy, especially in filling the gap of clinical skills between interpreters. This method can be a universal model for the use of deep learning in the diagnostic imaging of rare tumors.

Preoperative Differentiation of Uterine Leiomyomas and Leiomyosarcomas: Current Possibilities and Future Directions

The distinguishing of uterine leiomyosarcomas (ULMS) and uterine leiomyomas (ULM) before the operation and histopathological evaluation of tissue is one of the current challenges for clinicians and researchers. Recently, a few new and innovative methods have been developed. However, researchers are trying to create different scales analyzing available parameters and to combine them with imaging methods with the aim of ULMs and ULM preoperative differentiation ULMs and ULM. Moreover, it has been observed that the technology, meaning machine learning models and artificial intelligence (AI), is entering the world of medicine, including gynecology. Therefore, we can predict the diagnosis not only through symptoms, laboratory tests or imaging methods, but also, we can base it on AI. What is the best option to differentiate ULM and ULMS preoperatively? In our review, we focus on the possible methods to diagnose uterine lesions effectively, including clinical signs and symptoms, laboratory tests, imaging methods, molecular aspects, available scales, and AI. In addition, considering costs and availability, we list the most promising methods to be implemented and investigated on a larger scale.

Clinical value of pre-operative scoring systems to predict leiomyosarcoma: results of a validation study in 177 patients from the NOGGO-REGSA Registry

Objectives

Benign leiomyomas are the most common uterine tumors. In contrast, uterine leiomyosarcomas are malignancies with a poor prognosis due to difficulties in early diagnosis and inappropriate surgical treatment. Most often they are diagnosed incidentally after surgery performed for treatment of leiomyoma. As the appropriate surgical treatment is crucial for survival of the patient, there is a high demand to predict leiomyosarcoma pre-operatively. Available scoring systems to discriminate leiomyoma from leiomyosarcoma are based on retrospective studies with limited numbers of patients and are not implemented in routine clinical practice.

Methods

The aim of our study was to evaluate a recently published score—the pre-operative leiomyosarcoma (pLMS) score—to determine whether it would have been predictive of leiomyosarcoma in 177 patients from the NOGGO-REGSA study, a German register of histologically proven gynecological sarcoma detected during routine clinical investigation.

Results

The threshold of the pLMS score for ‘leiomyosarcoma not probable’ (< −3) failed for 7.5% of the patients and the threshold ‘indicator for leiomyosarcoma’ (>+1) was true for 39.1% of the patients. 53.4% of the patients were attributed to the group ‘additional investigations are recommended’ (−3 to +1). The most relevant parameters in our analysis were suspicious sonography and rapid growth, but neither have been quantitatively defined.

Conclusion

In our validation cohort, the pLMS score seems not to be a reliable tool to predict leiomyosarcoma and therefore we do not recommend its clinical implementation to identify leiomyosarcoma.

MR Imaging of uterine sarcomas: a comprehensive review with radiologic-pathologic correlation

The aim of this article is to summarize the MRI features of each sarcoma subtype and to correlate them with its pathological findings. Literature review through PubMed/Medline database to identify relevant articles on uterine sarcomas, with a special emphasis on their MRI findings and pathological features. While several, more generalistic, MRI findings of a uterine tumour should raise suspicion for malignancy (including irregular contour, intra-tumoral necrosis/hemorrhage and low ADC values), some particular features may suggest their specific histological subtype such as the gross lymphovascular invasion associated with endometrial stromal sarcomas, the "bag of worms" appearance of the low-grade endometrial stromal sarcoma and the "lattice-like" aspect of adenosarcomas which results from the mixed composition of solid and multiseptated cystic components. Knowledge of the different histological uterine sarcoma subtypes, their specific MRI features and comprehension of their pathological background allows for a more confident diagnosis and may indicate the correct histological subtype.

Impact of Intraoperative Tumor Spillage in Uterine Leiomyosarcoma: a Retrospective Single-Institution Analysis

Uterine leiomyosarcoma is a rare female reproductive system tumor which is difficult to distinguish from uterine leiomyoma preoperatively. Manual and power morcellation are used to remove the large uterus through the vagina or small abdominal incision. Worse outcome with use of power morcellation is now clear but impact of manual morcellation on survival outcome not established till date. The objective of the present study was to find impact of tumor spillage and to evaluate influencing factors for oncological outcome and prognosis in uterine leiomyosarcoma patients. This is a single-institutional retrospective cohort study including all uterine leiomyosarcoma patients from January 2005 to December 2017. Role of intraoperative tumor spillage and other influencing factors on oncological outcome were assessed. Thirty-three patients with median follow-up period of 49.7 months were evaluated. Stage 1 and absence of tumor spill had significant association with prolonged progression-free survival. Stage 1 uterine leiomyosarcoma (56.8 vs 6.8 months, p =  < 0.001), intraoperative tumor spillage (p = 0.03) and progression-free survival > 15 months (68.5 vs 12.2 months, p =  < 0.001) were favourable prognostic factors to predict better survival outcome but unable to establish significance on multivariate analysis. Survival plot did not reach median limit for stage I uterine leiomyosarcoma patients with preoperative suspicion. Age, site of recurrence and mitotic index had no significant association with better survival in the present study. Stage I disease and absence of tumor spillage during surgery improved progression-free survival but did not affect overall survival. Progression-free survival more than 15 months can predict better overall survival.

Differentiating leiomyosarcoma from leiomyoma: in support of an MR imaging predictive scoring system

PURPOSE

The purpose of this study was to determine the Magnetic Resonance (MR) imaging features that best differentiate leiomyosarcoma (LMS) from leiomyoma, and to explore a scoring system to preoperatively identify those at highest risk of having LMS.

METHODS

Our Institutional Review Board approved this retrospective HIPAA-compliant study with a waiver for written informed consent. Institutional Research Patient Data Registry identified patients with histopathologically-proven LMS (n = 19) or leiomyoma (n = 25) and a pelvic MRI within six months prior to surgery. Qualitative differentiating MRI features were selected based on prior publications and clinical experience. Patient and MRI characteristics for leiomyomas versus LMS were compared using Wilcoxon rank-sum tests or Fisher's exact tests and using a basic classification tree. Hypothesis testing was two-tailed, with a p value < 0.001 used to determine inclusion of variables into an MR imaging predictive (MRP) score. Diagnostic performance [sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV)] of the MRP in diagnosis of LMS used all possible scores as cutoffs.

RESULTS

Seven out of 15 MRI features were found to have an association with LMS. The final MRP scores ranged from 0 to 7: a score of 0-3 was associated with 100% NPV for LMS, and a MRP score of 6-7 with 100% PPV for LMS.

CONCLUSION

Seven qualitative MR imaging features, extracted from a standard MR imaging protocol, allow differentiation of LMS from leiomyoma. An exploratory risk stratification MRP score can be used to determine the likelihood of LMS being present.

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 Value of Preoperative CA125, LDH and HE4 for Leiomyosarcoma of the Female Reproductive System

Purpose

Leiomyosarcoma (LMS) is a rare and extremely aggressive malignancy that is derived from or shows evidence of differentiation toward smooth muscle. If LMS occurs in the female reproductive system, preoperative diagnosis can be difficult, as LMS is easily mistaken for a uterine leiomyoma, especially a degenerated uterine fibroid (DUF). Thus, we assessed the diagnostic value of the preoperative serum concentrations of cancer antigen 125 (CA125), lactate dehydrogenase (LDH) and human epididymis protein 4 (HE4) for differentiating LMS from DUF.

Patients and Methods

We enrolled patients with LMS or DUF who were receiving treatment in The First Affiliated Hospital of Chongqing Medical University between 2009 and 2020. If the preoperative serum concentrations of CA125, LDH and HE4 of our study participants had been tested, these data were analyzed. The preoperative serum concentrations of CA125, LDH and HE4 in participants with LMS (n = 37) were compared with those of participants with pathologically diagnosed DUF (n = 102), who served as the control group.

Results

The preoperative serum concentrations of CA125, LDH and HE4 of participants with LMS of the female reproductive system were significantly higher than those of participants with DUF (P = 0.009, P < 0.001, P = 0.001, respectively). The cut-off preoperative serum concentrations of CA125, LDH and HE4 were 30.85 U/mL, 186.50 U/L and 50.50 pmol/L, respectively. When these three parameters were used for an analysis of their combined diagnostic utility, the area under the curve (AUC) was 0.892, the sensitivity was 68.4% and the specificity was 95.1% (P < 0.001).

Conclusion

A combined analysis of the preoperative serum concentrations of CA125, LDH and HE4 could be a promising method for diagnostically differentiating LMS of the female reproductive system from DUF.

Multiparametric MR evaluation of uterine leiomyosarcoma and STUMP versus leiomyoma in symptomatic women planned for high frequency focussed ultrasound: accuracy of imaging parameters and interobserver agreement for identification of malignancy

OBJECTIVE

To assess accuracy of and interobserver agreement on multiparametric MR findings to distinguish uterine leiomyoma (LM) from uterine leiomyosarcoma (LMS) and soft tissue tumour of unknown malignant potential.

METHODS

Inclusion criteria: All females over 18 years with least one uterine mass measuring 5 cm or more in at least one of the three standard orthogonal dimensions on MR with histopathological confirmation of LM, LMS, or soft tissue tumour of unknown malignant potential (STUMP) in the 3 months following MR. Patients with LMS were drawn from a larger cohort being assessed for MR-guided focussed ultrasound (MRgFUS) suitability. Image evaluation: Assessed variables were: lesion margin, margin definition, T2 signal homogeneity, >50% of lesion with T2 signal brighter than myometrium, haemorrhage, restricted diffusion, contrast enhancement (CE), CE pattern, local lymphadenopathy and ascites.

RESULTS

32 LM, 10 LMS and 1 STUMP were evaluated. Ill-defined (p-value = 0.0003-0.0004) or irregular (p = 0.003-0.004) lesion margin, T2 hyperintensity >50% (p = 0.001-0.004), and peripheral CE (p = 0.02-0.05) were significantly more common in LMS/STUMP than LM for both radiologists. 10/11 (Reader 2) and 11/11 (Reader 1) LMS/STUMP displayed restricted diffusion but so did 63-80% of LM. Agreement was greatest for margin characteristics (κ = 0.73-0.81).

CONCLUSION

Irregular/ill-defined lesion margin best distinguished LMS/STUMP from LM with good interrater reliability.

ADVANCES IN KNOWLEDGE

Assessment of agreement regarding MR parameters distinguishing LM from LMS and STUMP has not previously been undertaken in a cohort including a large number of patients with LMS. This will help inform evaluation of females considering minimally invasive LM treatment.

Outcomes of patients with pelvic leiomyosarcoma treated by surgery and relevant auxiliary diagnosis

BACKGROUND

Leiomyosarcoma is a subtype of soft tissue sarcoma with adverse outcomes. Leiomyosarcoma accounts for nearly 70% of all uterine sarcomas and is responsible for a considerable proportion of deaths because of uterine cancer. Clinical characteristics and relevant diagnosis of pelvic leiomyosarcoma should be further explored.

AIM

To identify the outcome and relevant perioperative evaluation of patients with pelvic leiomyosarcoma.

METHODS

The Kaplan-Meier method was used to determine progression-free survival and overall survival rates. Factors predictive of outcomes were identified using univariate and multivariate Cox proportional hazards models.

RESULTS

Fifty-one patients with pelvic leiomyosarcoma were enrolled and divided into two groups including uterine leiomyosarcoma and non-uterine leiomyosarcoma. Overall, 28.6% and 45.5% of uterine leiomyosarcoma and non-uterine leiomyosarcoma patients, respectively, had elevated carbohydrate antigen 125 levels, whereas 45.7% and 68.8%, respectively, underwent ultrasonography. Although 68.8% of uterine leiomyosarcoma patients were initially diagnosed with hysteromyoma, 72.7% of non-uterine leiomyosarcoma patients had pelvic and abdominal masses. Moreover, 93.3% of the recurrent lesions were detected using ultrasonography. Patients with International Federation of Gynaecology and Obstetrics (FIGO) stages III–IV disease had poorer progression-free survival values than those with FIGO stages I–II (P = 0.027) disease. FIGO stage was significantly associated with poor progression-free survival in the univariate (hazard ratio = 2.64, P = 0.03) and multivariate (hazard ratio = 2.49, P = 0.048) analyses.

CONCLUSION

Serum tumour biomarkers cannot be used for pelvic leiomyosarcoma diagnosis. FIGO stage is critical to predict the outcome of uterine leiomyosarcoma. Ultrasonography is more reliable for postoperative follow-up than preoperative diagnosis.

A national survey: Evaluating current practice and risk assessment in morcellation amongst gynaecologists in the United Kingdom

OBJECTIVE

To evaluate current practice and adherence to AAGL and BSGE power morcellation guidelines.

STUDY DESIGN

Cross-sectional survey.

SETTING

United Kingdom.

PATIENTS/POPULATION

157 National Health Service (NHS) hospital trusts (organisation comprising of one or more hospitals) offering gynaecological services.

INTERVENTION

A questionnaire was emailed between March-July 2018 and completed by Lead/ Directors of Gynaecology within each organisation. Descriptive statistics were used to present results from this study.

MEASUREMENTS/RESULTS

We assessed power morcellation practice patterns, informed consent processes and outcomes over the last 12 months. We received 136 responses (87 % response rate). Power morcellation was performed by a third (59, 37.6 %) of all UK hospitals. The median number of gynecologists performing morcellation per organisation was 2 (Q1-Q3: 2-4). A median of 7 morcellators (Q1-Q3: 0-17) were purchased and 7 morcellators (Q1-Q3: 1.25-15.75) used per annum. A median of 10 (Q1-Q3: 2.0-15.0) laparoscopic hysterectomies and 5 (Q1-Q3: 0.5-9.0) myomectomies requiring morcellation were performed per annum. Almost, a third of hospitals did not perform an endometrial biopsy or MRI. 79.7 % (47) of trusts consented for power morcellation and 76 %, (46) explained risk of inadvertent leiomyosarcoma. 83.3 %, (50) had no patient literature and almost half had no audit process 45 %, (27).

CONCLUSION

Current UK practice does not reflect recommendations from the AAGL or BSGE. Deficiencies were identified in pre-operative evaluation, local governance procedures, and consenting practices regarding use of a power morcellator and risk of occult leiomyosarcoma.

Benign uterine mass-discrimination from leiomyosarcoma by a preoperative risk score: a multicenter cohort study

PURPOSE

Discrimination of uterine leiomyosarcoma (LMS) and leiomyoma (LM) prior to surgery by basic preoperative characteristics and development of a preoperative leiomyosarcoma score.

METHODS

A predominantly prospective cohort of 826 patients with LM from a clinical institution and an outpatient center was included in the study. Further a predominantly retrospective cohort of 293 patients with LMS was included from the counseling database of the German Clinical Center of Excellence for Genital Sarcoma and Mixed Tumors (DKSM, University Medicine Greifswald, Germany). We analyzed and compared anamnestic, epidemiological and clinical findings between both cohorts. Tenfold cross-validated logistic regression and random forest was performed on the 80% training set. The preoperative LMS score (pLMS) was developed based on logistic regression and independently evaluated by analyzing the area under the receiver operating characteristic curve (AUC) with the 20% test set.

RESULTS

In the LMS cohort, 63.1% had initially surgery for presumed LM and only 39.6% of endometrial biopsies revealed LMS. Key features for LMS discrimination were found to be bleeding symptoms: intermenstrual bleeding [RR_c = 2.71, CI = (1.90-3.49), p < 0.001], hypermenorrhea [RR_c = 0.28, CI = (0.15-0.50), p < 0.001], dysmenorrhea [RR_c = 0.22, CI = (0.10-0.51), p < 0.001], postmenstrual bleeding [RR_c = 2.08, CI = (1.30-2.75), p < 0.001], suspicious sonography [RR_c = 1.21, CI = (1.19-1.22), p < 0.001] and the tumor diameter (each centimeter difference: β = 0.24, SD = 0.04, p < 0.001). pLMS achieved a mean cross-validated AUC of 0.969 (SD = 0.019) in the training set and an AUC of 0.968 in the test set.

CONCLUSIONS

The presented score is based on basic clinical characteristics and allows the prediction of LMS prior to a planned surgery of a uterine mass. In case pLMS is between - 3 and + 1, we suggest subsequent diagnostics, such as endometrial biopsy, color Doppler sonography, LDH measurement, MRI and transcervical biopsy.

Sarcoma of the Uterus. Guideline of the DGGG and OEGGG (S2k Level, AWMF Register Number 015/074, February 2019)

Aims This is an official guideline published and coordinated by the German Society of Gynecology and Obstetrics (DGGG) and the Austrian Society of Gynecology and Obstetrics (OEGGG). Because of their rarity and heterogeneous histopathology, uterine sarcomas are challenging in terms of how they should be managed clinically, and treatment requires a multidisciplinary approach. To our knowledge, there are currently no binding evidence-based recommendations for the appropriate management of this heterogeneous group of tumors. Methods This S2k guideline was first published in 2015. The update published here is the result of the consensus of a representative interdisciplinary group of experts who carried out a systematic search of the literature on uterine sarcomas in the context of the guidelines program of the DGGG, OEGGG and SGGG. Members of the participating professional societies achieved a formal consensus after a moderated structured consensus process. Recommendations The consensus-based recommendations and statements include the epidemiology, classification, staging, symptoms, general diagnostic work-up and general pathology of uterine sarcomas as well as the genetic predisposition to develop uterine sarcomas. Also included are statements on the management of leiomyosarcomas, (low and high-grade) endometrial stromal sarcomas and undifferentiated uterine sarcomas and adenosarcomas. Finally, the guideline considers the follow-up and morcellation of uterine sarcomas and the information provided to patients.

How to differentiate uterine leiomyosarcoma from leiomyoma with imaging

Uterine leiomyomas, the most frequent benign myomatous tumors of the uterus, often cannot be distinguished from malignant uterine leiomyosarcomas using clinical criteria. Furthermore, imaging differentiation between both entities is frequently challenging due to their potential overlapping features. Because a suspected leiomyoma is often managed conservatively or with minimally invasive treatments, the misdiagnosis of leiomyosarcoma for a benign leiomyoma could potentially result in significant treatment delays, therefore increasing morbidity and mortality. In this review, we provide an overview of the differences between leiomyoma and leiomyosarcoma, mainly focusing on imaging characteristics, but also briefly touching upon their demographic, histopathological and clinical differences. The main indications and limitations of available cross-sectional imaging techniques are discussed, including ultrasound, computed tomography, magnetic resonance imaging (MRI) and positron emission tomography/computed tomography. A particular emphasis is placed on the review of specific MRI features that may allow distinction between leiomyomas and leiomyosarcomas according to the most recent evidence in the literature. The potential contribution of texture analysis is also discussed. In order to help guide-imaging diagnosis, we provide an MRI-based diagnostic algorithm which takes into account morphological and functional features, both individually and in combination, in an attempt to optimize radiologic differentiation of leiomyomas from leiomyosarcomas.

Uterine smooth muscle tumors of unknown malignant potential: A challenging question

Uterine smooth muscle tumors of unknown malignant potential [STUMP]s are neoplasms with pathological features that preclude an equivocal diagnosis of leiomyosarcoma, but that do not fulfill the criteria for leiomyoma or its variants, and raise concerns that the tumors may behave in a malign fashion. Total hysterectomy with or without bilateral salpingo-oophorectomy is the standard treatment if fertility is completed, whereas myomectomy alone can be taken into consideration in young patients who desire to preserve childbearing potential. A careful surveillance every 6 months for 5 years and then yearly is strongly warranted. Patients with STUMP can relapse as either STUMP or leiomyosarcoma in approximately 11-13% of the cases, and their 5-year overall survival ranges from 92 to 100%. The present paper reviews the clinicopathological features of uterine STUMPs with a particular focus on most commonly accepted histopathological criteria for the diagnosis and on biological behaviour of these controversial neoplasms.

Increased LDH5/LDH1 ratio in preoperative diagnosis of uterine sarcoma with inconclusive MRI and LDH total activity but suggestive CT scan: a case report

BACKGROUND

Morcellation of undiagnosed uterine sarcoma is cause of abdominal/pelvic dissemination, residual tumor and recurrence. In the preoperative evaluation of suspect uterine masses, magnetic resonance imaging (MRI) and serum lactate dehydrogenase (LDH) total activity are referred to as the most effective tools, while computed tomography scan (CT) and LDH isoenzymes are less considered in literature.

CASE PRESENTATION

A 46 year old woman was admitted to our department with a large uterine mass. Ultrasonography, MRI and LDH total activity did not allow a diagnosis of malignancy, and the woman expressed the wish to avoid hysterectomy. In spite of this, we opted for a total abdominal hysterectomy instead of a laparoscopic myomectomy, due to an elevation of LDH5/LDH1 ratio and CT findings indicative of sarcoma. Histological examination revealed a high grade leiomyosarcoma, confirming our suspicion. Thus, we had avoided the risks linked to morcellation.

CONCLUSIONS

Our experience suggests that LDH isoenzymes assessment may be relevant in preoperative diagnosis of uterine sarcoma. Further studies are necessary to determine its role in a diagnostic algorithm. We think it may be useful especially for patients with clinical or ultrasonographic suspicion of uterine sarcoma not confirmed by imaging techniques. Furthermore, the role of less considered imaging techniques, such as CT, should not be underestimated in challenging cases.

Occult Leiomyosarcomas in a Canadian Province: A Retrospective Cohort Study

OBJECTIVE

The risk of unexpected uterine leiomyosarcoma (LMS) following surgery for presumed benign leiomyoma is quoted to be between 1 in 498 and 1 in 5000. The objectives of the present study were to determine the prevalence of uterine LMS in a specific patient population and the rate of diagnosis of occult uterine LMS and to evaluate the risk of unintended morcellation of LMS in Saskatchewan.

METHODS

This study was a Canadian Task Force Classification II-2 multicentre retrospective cohort study in academic-affiliated tertiary care centres. All women with the histopathologic diagnosis of uterine LMS in Saskatchewan between January 2000 and December 2014 were included. Women with metastatic LMS at diagnosis or other types of uterine sarcomas were excluded. Data including patients' characteristics, clinical presentation, physical examination findings, imaging, pathology reports, surgical interventions, and survival outcomes were reviewed.

RESULTS

A total of 28 patients had a confirmed histopathologic diagnosis of LMS over the 15-year study period. Approximately 26 212 hysterectomies were performed in Saskatchewan over the same time frame. The prevalence of uterine LMS in this patient population over the study time frame is estimated to be one in 853. Mean age at diagnosis was 53.8 ± 10.0. Medical records of 25 patients could be retrieved, and 15 cases (60%) had an occult diagnosis. There were five cases of unintended morcellation (one power, four mechanical). Survival outcomes were comparable in women with unintended morcellation of occult disease and in those without morcellation.

CONCLUSION

This study contributes to the existing body of literature on morcellation of occult LMS, and it ascertains the rate of LMS in a patient population. The results of this study provide valuable information to health care professionals, policy makers, and women in Saskatchewan so that they may make more informed decisions concerning uterine masses.

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.

STUMP, a surprise finding in a large fibroid uterus in a 20-year-old woman

We report on a case of a 20-year-old nulliparous woman with menorrhagia associated with a smooth muscle tumor of uncertain malignant potential (STUMP) that was responsive to Goserelin. This case details the investigation and management of a young woman who desires ongoing fertility preservation. STUMP is a rare uterine tumor with a paucity of literature available regarding management and subsequent malignant potential, particularly in the case of a patient who desires fertility preservation.

Uterine sarcoma - current perspectives

Uterine sarcomas comprise a group of rare tumors with differing tumor biology, natural history and response to treatment. Diagnosis is often made following surgery for presumed benign disease. Currently, preoperative imaging does not reliably distinguish between benign leiomyomas and other malignant pathology. Uterine leiomyosarcoma is the most common sarcoma, but other subtypes include endometrial stromal sarcoma (low grade and high grade), undifferentiated uterine sarcoma and adenosarcoma. Clinical trials have shown no definite survival benefit of adjuvant radiotherapy or chemotherapy and have been hampered by the rarity and heterogeneity of these disease types. There is a role of adjuvant treatment in carefully selected cases following multidisciplinary discussion at sarcoma reference centers. In patients with metastatic disease, systemic chemotherapy can then be considered. There is activity of a number of agents, including doxorubicin, trabectedin, gemcitabine-based chemotherapy, eribulin and pazopanib. Patients should be considered for clinical trial entry where possible. Close international collaboration is important to allow progress in this group of diseases.