Intralesional leiomyosarcoma malignant transformation from a biopsied benign angioleiomyoma of the proximal anterior tibia.

We present a novel case of a malignant transformation of an extremity soft tissue angioleiomyoma to leiomyosarcoma in a man in his late 70s who presented with a painful and increasing lump on his anterior tibia. Initial imaging and biopsy showed a benign angioleiomyoma which was excised for symptomatic reasons. An analysis of the resulting specimen revealed a 50×42×15 mm smooth muscle neoplasm consistent with angioleiomyoma with a 22×11 mm entirely intralesional nodular component in keeping with a grade 1 leiomyosarcoma. The malignant constituent of the lesion was entirely encased in benign angioleiomyoma negating the need for further surgery. Systemic staging investigation revealed no evidence of metastatic disease spread final staging as per the eighth edition of the American Joint Committee on Cancer (AJCC) Staging T1N0M0 R0 Stage 1 a.

[Portal leiomyosarcoma: An extremely rare location!] / Léiomyosarcome portal : une localisation extrêmement rare !

Leiomyosarcomas of large vessels are rare. It is a malignant tumour and the vast majority of these tumours arose from the inferior vena cava. We report a rare case of portal vein leiomyosarcoma, in a 56-years-old female patient admitted for chronic abdominal pain with abdominal mass in the right hypochondrium all evolving in a context of deterioration in general condition. We performed an abdominopelvic CT scan and then a MRI with contrast agent which objectified a large tissue mass containing areas of necrosis at the level of the duodeno-pancreatic compartment communicating at a large angle with the portal trunk over its entire length from the hepatic hilum to the spleno-mesenteric confluence responsible for a portal cavernoma downstream. This is associated with multiple secondary nodular tissue hepatic lesions. We also noted a respect for the fatty border separating the mass of the duodenal tract and the head of the pancreas, and also the absence of dilation of the pancreatic ducts making a pancreatic origin unlikely. To eliminate a duodenal origin of the mass we performed an upper digestive endoscopy which came back without any abnormality. An ultrasound-guided trans parietal biopsy of a secondary hepatic lesion was done and the pathological result of which speaks of a secondary hepatic lesion of a leiomyosarcoma.

Deep learning radiomics-based prediction model of metachronous distant metastasis following curative resection for retroperitoneal leiomyosarcoma: a bicentric study.

BACKGROUND: Combining conventional radiomics models with deep learning features can result in superior performance in predicting the prognosis of patients with tumors; however, this approach has never been evaluated for the prediction of metachronous distant metastasis (MDM) among patients with retroperitoneal leiomyosarcoma (RLS). Thus, the purpose of this study was to develop and validate a preoperative contrast-enhanced computed tomography (CECT)-based deep learning radiomics model for predicting the occurrence of MDM in patients with RLS undergoing complete surgical resection. METHODS: A total of 179 patients who had undergone surgery for the treatment of histologically confirmed RLS were retrospectively recruited from two tertiary sarcoma centers. Semantic segmentation features derived from a convolutional neural network deep learning model as well as conventional hand-crafted radiomics features were extracted from preoperative three-phase CECT images to quantify the sarcoma phenotypes. A conventional radiomics signature (RS) and a deep learning radiomics signature (DLRS) that incorporated hand-crafted radiomics and deep learning features were developed to predict the risk of MDM. Additionally, a deep learning radiomics nomogram (DLRN) was established to evaluate the incremental prognostic significance of the DLRS in combination with clinico-radiological predictors. RESULTS: The comparison of the area under the curve (AUC) values in the external validation set, as determined by the DeLong test, demonstrated that the integrated DLRN, DLRS, and RS models all exhibited superior predictive performance compared with that of the clinical model (AUC 0.786 [95% confidence interval 0.649-0.923] vs. 0.822 [0.692-0.952] vs. 0.733 [0.573-0.892] vs. 0.511 [0.359-0.662]; both P < 0.05). The decision curve analyses graphically indicated that utilizing the DLRN for risk stratification provided greater net benefits than those achieved using the DLRS, RS and clinical models. Good alignment with the calibration curve indicated that the DLRN also exhibited good performance. CONCLUSIONS: The novel CECT-based DLRN developed in this study demonstrated promising performance in the preoperative prediction of the risk of MDM following curative resection in patients with RLS. The DLRN, which outperformed the other three models, could provide valuable information for predicting surgical efficacy and tailoring individualized treatment plans in this patient population. TRIAL REGISTRATION: Not applicable.

Breast lump as the initial presentation of metastatic uterine leiomyosarcoma: a case report and comprehensive literature review.

Uterine leiomyosarcoma (uLMS) is a rare but aggressive cancer with a high metastatic potential and an unfavorable prognosis. A 54-year-old woman with a history of uterine fibroids clinically presented with a painless, palpable left breast mass measuring 20 mm. A core biopsy of the breast mass demonstrated a cellular spindle cell neoplasm (a potentially malignant smooth muscle neoplasm; B4). A wide local breast-mass excision was performed, revealing grade-2 leiomyosarcoma. A re-review of the uterine fibroids revealed that the largest one (200 × 130 mm), initially diagnosed as symplastic leiomyoma, was morphologically identical to the breast lesion. Additional diagnostic work-up revealed multiple liver and pulmonary metastases with a suspected metastatic sclerotic lesion in the L3 projection. The patient was subsequently treated with chemotherapy protocol for metastatic uLMS. The latest follow-up in September 2023 confirmed stable disease. This case highlights the importance of considering unusual metastatic patterns when evaluating breast masses, particularly in patients with a history of non-specific uterine conditions. Comprehensive diagnostic work-up, including imaging and histopathologic examinations, is crucial for an accurate diagnosis of uLMS and appropriate treatment selection. Further studies are needed to better understand the underlying mechanisms and optimal management strategies for metastatic uLMS.

[A Case of Resection of Leiomyosarcoma Suspected to Originate from the Right Ovarian Vein].

We present a 58-year-old female patient who underwent resection of a leiomyosarcoma arising from the right ovarian vein. She was referred to our hospital because of lower abdominal pain that had been present for 1 month prior to the visit. Ultrasound examination revealed a well-defined, smooth, lobulated, highly vascular mass(57 mm)adjacent to the distal portion of the duodenum. Contrast-enhanced computed tomography revealed the contrast enhancement mass (60 mm)located surround the right ovarian vein. In abdominal magnetic resonance image examination, the mass exhibited isointense signal on T1-weighted images, high signal on T2-weighted images, and restricted diffusion on diffusion- weighted images. We suspected primary leiomyosarcoma of the ovarian vein and proceeded with surgical intervention. On intraoperative findings, the mass was in contact with the duodenum and the inferior vena cava but dissection was easily achieved. We excised the mass together with the right ovarian vein. Pathological findings showed the mass was composed of proliferating spindle-shaped cells arranged in bundles. Some areas showed polygonal nuclear atypia and abnormal mitotic figures. Additional immunostaining showed positive for α-SMA, caldesmon, calponin, and negative for desmin, CD34, CKA1/AE3, S100. Based on the intraoperative findings, we diagnosed it as leiomyosarcoma arising of the right ovarian vein.

MRI, clinical, and radiomic models for differentiation of uterine leiomyosarcoma and leiomyoma.

PURPOSE: To assess the predictive ability of conventional MRI features and MRI texture features in differentiating uterine leiomyoma (LM) from uterine leiomyosarcoma (LMS). METHODS: This single-center, IRB-approved, HIPAA-compliant retrospective study included 108 patients (69 LM, 39 LMS) who had pathology, preoperative MRI, and clinical data available at our tertiary academic institution. Two radiologists independently evaluated 14 features on preoperative MRI. Texture features based on 3D segmentation were extracted from T2W-weighted MRI (T2WI) using commercially available texture software (TexRAD™, Feedback Medical Ltd., Great Britain). MRI conventional features, and clinical and MRI texture features were compared between LM and LMS groups. Dataset was randomly divided into training (86 cases) and testing (22 cases) cohorts (8:2 ratio); training cohort was further subdivided into training and validation sets using ten-fold cross-validation. Optimal radiomics model was selected out of 90 different machine learning pipelines and five models containing different combinations of MRI, clinical, and radiomics variables. RESULTS: 12/14 MRI conventional features and 2/2 clinical features were significantly different between LM and LMS groups. MRI conventional features had moderate to excellent inter-reader agreement for all but two features. Models combining MRI conventional and clinical features (AUC 0.956) and MRI conventional, clinical, and radiomics features (AUC 0.989) had better performance compared to models containing MRI conventional features alone (AUC 0.846 and 0.890) or radiomics features alone (0.929). CONCLUSION: While multiple MRI and clinical features differed between LM and LMS groups, the model combining MRI, clinical, and radiomic features had the best predictive ability but was only marginally better than a model utilizing conventional MRI and clinical data alone.

Resection of primary left renal vein leiomyosarcoma with renal preservation following an unusual clinical presentation.

An elderly man was referred to vascular surgery on incidental discovery of a left retroperitoneal mass ultimately found to be of left renal vein (LRV) origin. He initially presented with recurring lower back pain. CT of the abdomen/pelvis showed a 6.0×5.5 cm lobulated retroperitoneal mass anterior to the infrarenal aorta. Resection of the mass necessitated a multidisciplinary team consisting of medical oncologists, radiation oncologists, urologists and vascular surgeons. In efforts to obtain an R0 margin, en-bloc resection of the LRV from its confluence with the inferior vena cava (IVC) was necessary. A primary repair of the IVC was performed with preservation of the left kidney. The patient's back pain has since resolved after the surgery. A literature search found IVC reconstructions to be safe and effective in the removal of vascular leiomyosarcomas.

Elevated 68 Ga-FAPI Activity in Leiomyosarcoma.

ABSTRACT: Leiomyosarcoma is an aggressive subtype of soft tissue sarcoma with frequent metastatic relapse after curative surgery. Herein, we report the 68 Ga-FAPI PET/CT findings in a 45-year-old woman with leiomyosarcoma. 68 Ga-FAPI-04 PET/CT detected increased FAPI uptake in abdominal leiomyosarcoma and liver metastases. The positive findings of 68 Ga-FAPI in this case highlighted that 68 Ga-FAPI may have potential value in the evaluation of leiomyosarcoma.

Successful clinical approach to the metastatic uterine leiomyosarcoma to the epicardium-a case report.

BACKGROUND: Uterine leiomyosarcoma is a rare and aggressive tumour with a poor prognosis. Its metastases to the heart are even rarer, especially to the epicardium. The majority of reported cardiac metastases of uterine leiomyosarcoma were in the cardiac chambers or intramyocardial. Surgical resection of the uterine leiomyosarcoma in the early stages is the only definitive treatment for this disease. However, in the cases of cardiac metastasis, surgery is recommended only in emergencies and patients with expected beneficial outcomes. CASE PRESENTATION: Our patient was a 49-year-old female referred to the Department of Cardiac Surgery for scheduled surgery of pericardial neoplasia. The patient underwent a hysterectomy and adnexectomy three years prior owing to the uterine leiomyosarcoma. A regular follow-up magnetic resonance imaging of the abdomen and pelvis discovered neoplasia in the diaphragmic portion of the pericardium. No other signs of primary disease relapse or metastases were found. The patient was asymptomatic. The multidisciplinary team concluded that the patient is a candidate for surgery. Surgery included diastolic cardiac arrest achievement and resection of the tumour. Macroscopically, a parietal layer of the pericardium was completely free from the tumour that invaded only the apical myocardium of the left ventricle. Completed histopathology confirmed the diagnosis of leiomyosarcoma of the uterine origin. Three months after surgery, the patient received adjuvant chemotherapy with doxorubicin and dacarbazine. One year after surgery, there are no signs of new metastases. CONCLUSIONS: Strict surveillance of patients with uterine leiomyosarcoma after successful treatment of the early stage of the disease is of utmost importance to reveal metastatic disease to the heart in a timely manner and to treat it with beneficial outcomes. Surgery with adjuvant chemotherapy might be a good approach in patients with a beneficial prognosis. From a surgical point of view, it is challenging to assess the appropriate width of the resection edges to be radical enough and, at the same time, sufficiently conservative to ensure the satisfactory postoperative function of the remaining myocardium and avoid repetitive tumour growth. Therefore, intraoperative histopathology should always be performed.

Smooth muscle tumours of the uterus: MR imaging malignant predictive features-a 12-year analysis in a referral hospital in Portugal.

PURPOSE: To evaluate the magnetic resonance imaging (MRI) features that may help distinguish leiomyosarcomas from atypical leiomyomas (those presenting hyperintensity on T2-W images equal or superior to 50% compared to the myometrium). MATERIALS AND METHODS: The authors conducted a retrospective single-centre study that included a total of 57 women diagnosed with smooth muscle tumour of the uterus, who were evaluated with pelvic MRI, between January 2009 and March 2020. All cases had a histologically proven diagnosis (31 Atypical Leiomyomas-ALM; 26 Leiomyosarcomas-LMS). The MRI features evaluated in this study included: age at presentation, dimension, contours, intra-tumoral haemorrhagic areas, T2-WI heterogeneity, T2-WI dark areas, flow voids, cyst areas, necrosis, restriction on diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) values, signal intensity and heterogeneity after contrast administration in T1-WI, presence and location of unenhanced areas. The association between the MRI characteristics and the histological subtype was evaluated using Chi-Square and ANOVA tests. RESULTS: The MRI parameters that showed a statistically significance correlation with malignant histology and thus most strongly associated with LMS were found to be: irregular contours (p < 0.001), intra-tumoral haemorrhagic areas (p = 0.028), T2-WI dark areas (p = 0.016), high signal intensity after contrast administration (p = 0.005), necrosis (p = 0.001), central location for unenhanced areas (p = 0.026), and ADC value lower than 0.88 × 10-3 mm2/s (p = 0.002). CONCLUSION: With our work, we demonstrate the presence of seven MRI features that are statistically significant in differentiating between LMS and ALM.

Surgery and stereotactic radiosurgery for spinal leiomyosarcoma: a single-institution retrospective series and systematic review.

OBJECTIVE: Leiomyosarcoma (LMS) is a rare, aggressive soft-tissue sarcoma that seldom spreads to the bone. The spine can be either the site of LMS osseous metastases or the primary tumor site. The optimal treatment option for spinal LMS is still unclear. The authors present a cohort of patients with spinal LMS treated with either upfront surgery or upfront CyberKnife stereotactic radiosurgery (SRS). METHODS: The authors retrospectively studied the clinical and radiological outcomes of 17 patients with spinal LMS treated at their institution between 2004 and 2020. Either surgery or SRS was used as the upfront treatment. The clinical and radiological outcomes were assessed. A systematic review of the literature was also conducted. RESULTS: Of the 17 patients (20 spinal lesions), 12 (70.6%) were female. The median patient age was 61 years (range 41-80 years). Ten patients had upfront surgery for their spinal lesions, and 7 had upfront CyberKnife radiosurgery. The median follow-up was 11 months (range 0.3-130 months). The median overall survival (OS) for the entire cohort was 13 months (range 0.3-97 months). In subgroup analysis, the median OS was lower for the surgical group (13 months, range 0.3-50 months), while the median OS for the SRS group was 15 months (range 5-97 months) (p = 0.5). Forty percent (n = 4) of those treated with surgery presented with local recurrence at a median of 6.7 months (range 0.3-36 months), while only 14% (n = 1) of those treated with CyberKnife radiosurgery had local recurrence after 5 months. Local tumor control (LTC) rates at the 6-, 12-, and 18-month follow-ups were 72%, 58%, and 43%, respectively, for the SRS group and 40%, 30%, and 20%, respectively, for the surgery group (p < 0.05). The literature review included 35 papers with 70 patients harboring spinal LMS; only 2 patients were treated with SRS. The literature review confirms the clinical and radiological outcomes of the surgical group, while data on SRS are anecdotal. CONCLUSIONS: The authors present the largest series in the literature of spinal LMS and the first on SRS for spinal LMS. This study shows that LTC is statistically significantly better in patients receiving upfront SRS instead of surgery. The OS does not appear different between the two groups.

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.

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.

Quantitative MR texture analysis for the differentiation of uterine smooth muscle tumors with high signal intensity on T2-weighted imaging.

The purpose of this study was to distinguish leiomyosarcomas/smooth muscle tumors of uncertain malignant potential (STUMP) from leiomyomas with high signal intensity (SI) on T2-weighted imaging (T2WI) using quantitative MR texture analysis combined with patient characteristics and visual assessment. Thirty-one leiomyomas, 2 STUMPs, and 6 leiomyosarcomas showing high SI on T2WI were included. First, we searched for differences in patient characteristics and visual assessment between leiomyomas and leiomyosarcomas/STUMPs. We also compared the MR texture on T2WI and the apparent diffusion coefficient (ADC) to identify differences between leiomyomas and leiomyosarcomas/STUMPs. In the univariate analysis, significant differences between leiomyomas and leiomyosarcomas/STUMPs were observed in age, menopausal status, margin, hemorrhage, long diameter, T2-variance, T2-volume, ADC-variance, ADC-entropy, ADC-uniformity, ADC-90th and 95th percentile values, and ADC-volume (P < .05, respectively). There were significantly more postmenopausal patients with leiomyosarcomas/STUMPs than with leiomyomas, and leiomyosarcomas/STUMPs had more irregular margins, more frequent presence of hemorrhage and exhibited larger tumor diameters, T2-volume, T2-variance, ADC-volume, ADC-variance, ADC-entropy, and higher ADC-90th and 95th percentile values but lower ADC-uniformity. Multivariate analyses revealed that the independent differentiators were menopausal status, hemorrhage and ADC-entropy (P < .05, respectively). The area under the curve obtained by combining the 3 items was 0.980. The best cutoff value for ADC-entropy was 9.625 (sensitivity: 100%, specificity: 58%). The combination of menopausal status, hemorrhage, and ADC-entropy can help accurately distinguish leiomyosarcomas/STUMPs from leiomyomas with high SI on T2WI; however, external validation in a larger population is required because of the small sample size of our study.