Myxoid leiomyosarcoma, often abbreviated mLMS, is a rare morphological variant of leiomyosarcoma, a cancer arising from smooth muscle tissue. What distinguishes the myxoid variant is its abundant gelatinous stroma, a matrix that separates the neoplastic smooth muscle cells and gives the tumor a deceptively bland appearance under the microscope. While the uterus is the most common primary site, extra-uterine occurrences involving the retroperitoneum, the intra-abdominal cavity, and soft tissues are exceedingly rare. Population-based data confirm this extreme rarity and identify elderly females as the demographic most frequently affected, with the uterus representing the predominant primary site among myxosarcoma subtypes. Because so few cases exist, the clinicopathological behavior of extra-uterine disease remains poorly characterized, and management protocols are largely extrapolated from data on uterine leiomyosarcoma.

The prognosis of myxoid leiomyosarcoma is a subject of genuine scientific debate, and the disagreement is striking. Some clinical series report a highly aggressive course, with five-year overall survival as low as 11.1 percent, driven by a strong propensity for local recurrence and distant metastasis. In contrast, a Norwegian population-based study reported five-year survival approaching 73 percent, slightly more favorable than conventional leiomyosarcoma, and another investigation documented recurrence in only five of twelve cases over follow-up periods ranging from three to nine years. Researchers believe this discrepancy likely reflects heterogeneity in the diagnostic criteria applied across studies and, more fundamentally, underlying molecular diversity within the entity. Large-scale molecular profiling of uterine sarcomas has underscored that molecular classification refines both diagnosis and prognosis, suggesting that the apparent clinical variability of myxoid leiomyosarcoma may mask several biologically distinct subtypes awaiting precise definition.

Diagnostically, the tumor presents formidable challenges because its morphological and radiological features overlap with a spectrum of benign and malignant myxoid lesions, including myxoid leiomyoma, aggressive angiomyxoma, and low-grade endometrial stromal sarcoma. The myxoid matrix imparts low-attenuation characteristics on computed tomography and heterogeneous signal on other imaging modalities, frequently mimicking benign cystic structures or other soft tissue tumors, which renders imaging insufficient for definitive characterization. In the newly reported case, a contrast-enhanced abdominal CT scan revealed a large, poorly enhanced, heterogeneous soft tissue mass measuring 11.8 centimeters in the left peritoneal space, together with a separate complex cystic-solid lesion measuring 5.8 centimeters in the left lower abdomen. The presence of two spatially distinct lesions raised the possibility of a primary intra-abdominal neoplasm with a satellite deposit or multifocal disease, and a CT-guided core needle biopsy could only suggest an atypical myxoid neoplasm without definitive classification.

Definitive answers came only after surgical excision, performed for concurrent diagnosis and treatment. Gross examination of the resected specimen revealed a multilobulated mass with a gelatinous cut surface and a small adjacent satellite nodule. Under the microscope, the tumor showed a spindle cell proliferation with mild nuclear atypia and high mitotic activity, with 26 mitoses counted per ten high-power fields, all embedded within abundant myxoid stroma. Immunohistochemistry, the technique of using antibodies to detect specific proteins in tissue sections, played a pivotal role. The tumor cells displayed strong and diffuse positivity for desmin, a marker of muscle lineage, but were negative for SMA, h-Caldesmon, and SMMHC, a pattern consistent with the incomplete smooth muscle differentiation profile characteristic of myxoid leiomyosarcoma. Unlike conventional leiomyosarcoma, the myxoid variant frequently shows reduced or absent reactivity for these markers while retaining desmin in most cases, an inconsistency that can easily mislead observers unfamiliar with the entity.

The immunophenotype grew more complicated still. The tumor co-expressed the estrogen and progesterone receptors along with CD10 and Cyclin D1, a combination that prompted consideration of endometrial stromal sarcoma, another uterine mesenchymal malignancy with which myxoid leiomyosarcoma is frequently confused. However, the retention of desmin positivity, the morphological context, and subsequent molecular results argued against that diagnosis. Crucially, immunohistochemistry also revealed strong and diffuse nuclear overexpression of the PLAG1 protein, a finding that prompted a dedicated molecular workup. Overexpression of the MDM2 protein was identified as well, but fluorescence in situ hybridization, or FISH, confirmed a PLAG1 break-apart signal consistent with PLAG1 gene rearrangement while demonstrating an absence of MDM2 gene amplification. That combination effectively excluded well-differentiated and dedifferentiated liposarcoma, tumors that can morphologically overlap with myxoid lesions and that are defined by MDM2 amplification.

The PLAG1 rearrangement carries substantial diagnostic weight. Previous molecular studies have identified PLAG1 gene rearrangement in approximately 25 percent of uterine myxoid leiomyosarcoma cases, and it represents a highly specific biomarker that distinguishes this entity from ZC3H7B-BCOR high-grade endometrial stromal sarcoma and from myxoid inflammatory myofibroblastic tumor. Importantly, strong and diffuse nuclear PLAG1 immunoexpression, as observed in this patient, reliably identifies tumors harboring the rearrangement and serves as a practical triage tool before confirmatory FISH is performed. Integrating the histomorphological pattern, the immunophenotype, and the molecular findings, the clinical team rendered a definitive diagnosis of myxoid leiomyosarcoma harboring PLAG1 gene rearrangement, an example of how modern pathology increasingly depends on layered molecular evidence rather than morphology alone.

Of particular clinical significance is the patient’s prior laparoscopic myomectomy, performed two years earlier for a 13-centimeter submucosal uterine myoma. Surgical oncology literature emphasizes that myomectomy is strictly indicated for benign leiomyomas, and that inadvertent surgery on an occult leiomyosarcoma carries the risk of intraperitoneal tumor dissemination even in the absence of morcellation, the mechanical fragmentation of tissue during minimally invasive removal. Tumor cells have been detected in peritoneal fluid following myomectomy alone. The multilesional intraperitoneal distribution observed in this patient, with two spatially separate masses and an adjacent satellite nodule, raises strong suspicion that iatrogenic peritoneal seeding secondary to the prior myomectomy may have contributed to the tumor’s distribution. The authors of the report stress that any leiomyosarcoma diagnosis arising after a prior myomectomy warrants complete surgical re-evaluation, including hysterectomy, and close surveillance for intraperitoneal disease, and that the case reinforces the critical need for accurate preoperative differentiation between benign leiomyoma and leiomyosarcoma, particularly in younger patients with large or atypical uterine masses.

Treatment and outcomes in this case offer a measure of reassurance alongside the cautionary elements. The patient recovered smoothly after her tumor excision, experiencing only transient abdominal distention, and was discharged on the tenth postoperative day. At six-month outpatient follow-up she remained completely asymptomatic, with no clinical or radiological evidence of recurrence. Complete surgical excision with negative margins remains the cornerstone of curative-intent management for localized myxoid leiomyosarcoma, since standardized treatment guidelines for the rare entity remain elusive. For advanced disease, systemic therapy is an important consideration given the high rates of metastatic failure following resection. Doxorubicin has long been the standard first-line agent for metastatic leiomyosarcoma, but the LMS-04 Phase III randomized controlled trial demonstrated that combining doxorubicin with trabectedin significantly improved progression-free survival compared with doxorubicin monotherapy in metastatic or unresectable disease, an advance that should inform treatment planning for patients with unresectable or metastatic myxoid leiomyosarcoma.

The broader lessons of this single case extend well beyond one patient’s chart. The combination of an incomplete smooth muscle immunophenotype, strong diffuse nuclear PLAG1 expression, and confirmatory FISH proved instrumental in establishing a definitive molecular diagnosis that morphology and imaging alone could never deliver. The authors argue that comprehensive molecular workup, including PLAG1 immunohistochemistry and FISH, should be considered in all myxoid intra-abdominal tumors, particularly in patients with a prior history of uterine surgery. At the same time, the prognostic significance of PLAG1 rearrangement itself remains unresolved and, according to the report, warrants dedicated prospective investigation. For clinicians, the case is a reminder that the gelatinous, deceptively bland tumors encountered in the abdomen may conceal a malignant smooth muscle origin, and for surgeons and patients contemplating fibroid removal, it underscores the enduring importance of rigorous preoperative risk stratification before any uterine operation is undertaken.

Subject of Research: Intra-abdominal myxoid leiomyosarcoma with PLAG1 gene rearrangement following prior laparoscopic myomectomy

Article Title: Intra‐Abdominal Myxoid Leiomyosarcoma With PLAG1 Gene Rearrangement Following Prior Laparoscopic Myomectomy: A Case Report and Literature Review

Article References: Hsieh, C.-E., Wu, P.-H., Su, C.-W., Ma, Y.-C., & Huang, H.-Y. (2026). Intra‐Abdominal Myxoid Leiomyosarcoma With PLAG1 Gene Rearrangement Following Prior Laparoscopic Myomectomy: A Case Report and Literature Review. Clinical Case Reports, 14(9), Article e73539. https://doi.org/10.1002/ccr3.73539

Image Credits: AI Generated

DOI: 10.1002/ccr3.73539

Keywords: myxoid leiomyosarcoma, PLAG1 gene rearrangement, leiomyosarcoma, myomectomy, fibroid surgery, peritoneal seeding, molecular diagnostics, FISH, immunohistochemistry, endometrial stromal sarcoma, trabectedin, soft tissue sarcoma

Researchers led by Enlong Zhang and Yuan Li of Peking University Third Hospital, together with colleagues at Tsinghua University Hospital and Peking University International Hospital, developed a tumor habitat-based radiomics approach to distinguish retroperitoneal non-fatty dedifferentiated liposarcoma from leiomyosarcoma. Their retrospective study included 166 patients, 102 with dedifferentiated liposarcoma and 64 with leiomyosarcoma, all of whom underwent multiphase contrast-enhanced CT. Rather than treating each tumor as a single uniform blob, the team borrowed a concept from oncology known as intratumoral heterogeneity, the recognition that a cancer is a patchwork of biologically distinct microenvironments, each with its own cellularity, vascularity, necrosis, and stromal composition.

The technical core of the method is elegantly simple. On the largest axial slice of each tumor, the researchers applied a Simple Linear Iterative Clustering algorithm, a superpixel segmentation technique originally developed for computer vision, to divide the tumor image into hundreds of small, coherent regions of similar pixel intensity. A K-means clustering step then grouped these superpixels into three habitat subregions, effectively partitioning each tumor into three zones that reflect different levels of attenuation, a radiological proxy for tissue density. The team designated these subregions ROI1, ROI2, and ROI3, with ROI2 corresponding to the intermediate-attenuation zone that often represents a transitional territory between viable cellular tissue and degenerative change.

From each habitat subregion, across three imaging phases, the non-contrast phase, the arterial phase, and the venous phase, the researchers extracted a comprehensive panel of quantitative radiomics features. These included shape descriptors such as major axis length, first-order statistics capturing the distribution of gray values, and higher-order texture features derived from gray-level co-occurrence matrices, run-length matrices, size zone matrices, dependence matrices, and neighborhood gray-tone difference matrices, as well as wavelet-transformed versions of these features that probe texture at multiple spatial scales. Feature selection was performed independently within each subregion using LASSO regression, and predictive models were then built with XGBoost, a gradient-boosted decision tree algorithm renowned for its performance on tabular biomedical data.

The results point to a clear conclusion: contrast matters. Habitat radiomics models derived from contrast-enhanced CT generally outperformed those built on non-contrast images, suggesting that the way tumor subregions take up iodinated contrast, and therefore their vascular perfusion characteristics, carries diagnostic information that plain density measurements miss. The single best-performing model was built from the venous-phase intermediate-attenuation subregion, VP-ROI2. In the testing cohort it achieved an area under the receiver operating characteristic curve of 0.834, with a 95 percent confidence interval of 0.713 to 0.950, alongside an accuracy of 0.820, a sensitivity of 0.871, and a specificity of 0.737.

The venous-phase advantage is physiologically plausible. The venous phase of a contrast-enhanced CT, typically acquired around sixty to ninety seconds after injection, captures the period of maximum enhancement in many soft-tissue tumors, when contrast has diffused into the extracellular space and reflects capillary permeability and interstitial volume. Dedifferentiated liposarcoma and leiomyosarcoma differ in their microvascular architecture and stromal composition, and those differences apparently imprint distinguishable enhancement patterns on the intermediate-attenuation habitat. Interestingly, VP-ROI2 showed only a nominally significant advantage over its non-contrast counterpart, NP-ROI2, with a P value of 0.048 that fell to an adjusted P value of 0.173 after false discovery rate correction, a statistical caution the authors appropriately acknowledge. ROI2 nevertheless emerged as the most discriminative subregion on both arterial and venous phases.

Perhaps the most compelling aspect of the study is its commitment to interpretability, a virtue not always found in machine learning medicine. Using SHAP, or SHapley Additive exPlanations, a game-theoretic framework that quantifies each feature’s contribution to individual predictions, the team identified original_shape_MajorAxisLength and wavelet-based texture features as the most influential predictors. Shape matters, which makes intuitive sense: dedifferentiated liposarcomas and leiomyosarcomas differ in their growth patterns and margins. But the prominence of wavelet texture features, which encode fine-scale spatial patterning of pixel intensities, indicates that the microscopic organization of tumor tissue, its heterogeneity at radiologically invisible scales, is what truly separates the two diagnoses. The models were built and reported following established standards, including the Image Biomarker Standardization Initiative nomenclature and the TRIPOD guidelines for prediction model reporting, and the study received an assessment of radiomics quality.

The clinical implications are significant. Today, distinguishing these sarcomas preoperatively often depends on biopsy, and even then core needle sampling of a large heterogeneous tumor can miss the diagnostic territory, a problem known as sampling error. Accurate preoperative differentiation guides the surgical plan: dedifferentiated liposarcoma demands wide clearance of the fatty component along with the dedifferentiated nodule, whereas leiomyosarcoma management hinges more on vascular involvement and multimodal planning. A noninvasive imaging biomarker that can flag the likely diagnosis before the first incision could help surgeons counsel patients, select neoadjuvant strategies, and design clinical trials that stratify patients by histological subtype rather than by the blunt label of retroperitoneal sarcoma.

The authors are careful to frame this as a promising step rather than a finished clinical tool. The cohort was retrospective and drawn from Chinese hospitals, the tumors were segmented on the largest axial slice rather than in three dimensions, and the performance figures, while respectable, leave room for improvement before the model could stand beside pathology. External validation in independent, multiethnic cohorts and prospective testing will be essential before VP-ROI2-based habitat radiomics enters routine decision-making. Still, the study offers a vivid demonstration of a broader idea now sweeping through oncological imaging: that every tumor is a landscape of habitats, and that the map of that landscape, drawn automatically from a routine contrast-enhanced CT scan, may hold answers that biopsies, radiologists, and even pathologists struggle to provide. The venous phase, long treated as a routine addendum to the arterial spectacle, turns out to be where the sarcomas reveal their secrets.

Subject of Research: Venous-phase CT-based tumor habitat radiomics for differentiating retroperitoneal non-fatty dedifferentiated liposarcoma from leiomyosarcoma

Article Title: Venous-phase CT-based tumor habitat radiomics for differentiating retroperitoneal non-fatty dedifferentiated liposarcoma from leiomyosarcoma

Article References: Zhang, E., Li, Y., Ma, L., Ji, D., Zhang, M., & Lang, N. (2026). Venous-phase CT-based tumor habitat radiomics for differentiating retroperitoneal non-fatty dedifferentiated liposarcoma from leiomyosarcoma. BMC Medical Imaging. https://doi.org/10.1186/s12880-026-02784-4

Image Credits: AI Generated

DOI: 10.1186/s12880-026-02784-4

Keywords: retroperitoneal sarcoma, dedifferentiated liposarcoma, leiomyosarcoma, radiomics, tumor habitat, intratumoral heterogeneity, computed tomography, machine learning, XGBoost, SHAP, cancer imaging, preoperative diagnosis