Liposarcoma is the most common soft tissue sarcoma in adults, accounting for roughly 20 percent of all sarcomas. The World Health Organization recognizes four principal subtypes: well-differentiated, dedifferentiated, myxoid, and pleomorphic. The dedifferentiated form, abbreviated DDLPS, arises when a slow-growing, well-differentiated liposarcoma undergoes a malignant transformation into a non-fatty, high-grade sarcoma. It represents about 15 to 20 percent of all liposarcomas and arises de novo in roughly 90 percent of cases. Compared with its well-differentiated cousin, DDLPS carries substantially higher morbidity and mortality, and while more than 80 percent of cases occur in the retroperitoneum, the space behind the abdominal organs, extremity tumors such as those in the thigh do occur and pose particularly thorny diagnostic problems.

At the molecular level, DDLPS carries a signature that has become a cornerstone of modern sarcoma diagnostics: co-amplification of two genes, MDM2 and CDK4, on chromosome 12q13-15. MDM2 encodes a protein that suppresses p53, the cell’s most famous tumor-suppressor and a key trigger of apoptosis, or programmed cell death. CDK4, meanwhile, drives unrestrained progression through the G1/S checkpoint of the cell cycle, effectively removing a critical brake on cell division. Together, these amplifications allow tumor cells to evade both death signals and growth arrest. In clinical practice, MDM2 immunohistochemistry shows a reported sensitivity of 100 percent for well-differentiated and dedifferentiated liposarcoma, with CDK4 approaching 83 percent, and fluorescence in situ hybridization for MDM2 amplification serves as the most specific confirmatory test. In this case, resource constraints meant neither molecular test was performed, and the diagnosis rested on classical histomorphological criteria alone.

The patient’s medical history complicated matters from the start. She had a ten-year history of type 2 diabetes mellitus, hypertension, hypothyroidism, and chronic kidney disease. Six months before admission, a mildly painful swelling on the postero-medial aspect of her left thigh was evaluated with Doppler ultrasonography, which showed a 9.5 by 6.1 centimeter lesion with predominantly arterial flow. The radiologist interpreted this as a hemangioma, and she was managed conservatively without a tissue biopsy. In retrospect, those arterial signals reflected tumor-associated neo-angiogenesis, the chaotic sprouting of new blood vessels that is a hallmark of high-grade sarcomas, rather than a benign vascular malformation. The lesion continued to enlarge, and systemic symptoms followed: intermittent fever, loss of appetite, weakness, and an involuntary weight loss of approximately six kilograms in a single month.

On admission, examination revealed a deep-seated, tense, tender, warm swelling with intact overlying skin, along with pitting edema from the ankle to the knee. Laboratory results painted a picture that pointed firmly toward infection: neutrophilic leukocytosis, markedly elevated erythrocyte sedimentation rate and C-reactive protein, moderate anemia refractory to erythropoiesis-stimulating agents, and deranged renal parameters. Bone marrow examination showed a hypercellular marrow with myeloid hyperplasia, attributed to chronic systemic inflammation. This biochemical constellation, combined with fever, would steer most clinicians toward an infectious diagnosis, and it did exactly that.

Contrast-enhanced CT revealed a mixed-density lesion of roughly 19 by 12 centimeters within the medial compartment muscles, featuring a large central necrotic zone and an irregularly enhancing peripheral wall. The radiological impression was an organized abscess. MRI added detail: an encapsulated mass measuring 18.4 by 11.2 by 10.6 centimeters, hypointense on T1-weighted sequences, hyperintense on T2 and STIR sequences, with peripheral enhancement, central necrosis, and prominent intra-tumoral flow voids. Those flow voids, dark signal voids caused by rapidly flowing blood, were a critical red flag, reflecting pathological tumor angiogenesis rather than a true vascular malformation. The tumor had invaded the adductor magnus muscle and extended through the upper two-thirds of the thigh. Notably, the central necrosis seen on imaging corresponded directly to the enormous volume of necrotic material later aspirated, underscoring the direct pathological link between tumor death and its clinical mimicry of a pyogenic collection.

Acting on the abscess impression, clinicians performed ultrasound-guided aspiration, yielding 600 milliliters of thick, purulent-appearing fluid. But the microbiology told a different story. Gram stain showed no organisms, culture and sensitivity returned sterile, and cytology revealed a mixed cellular pattern of 98,000 red blood cells and 25,000 white blood cells, atypical for a bacterial infection. A second aspiration two days later drained an additional 150 milliliters that had re-accumulated, itself an unusual behavior for a successfully treated abscess. The material was reclassified as necrotic tumor debris mimicking pus. The biology is well understood: in high-grade sarcomas, rapid tumor growth outpaces the blood supply, generating extensive intra-tumoral hypoxia, coagulative necrosis, and liquefaction that produce macroscopically purulent-looking but microbiologically sterile material. Concurrent core biopsies taken from the lesion wall during the procedure provided the definitive answer.

Histopathological examination showed a spindle cell neoplasm with marked nuclear pleomorphism, atypical mitotic figures, lipoblastic differentiation, a residual well-differentiated lipomatous component, and extensive tumor necrosis, classified as dedifferentiated liposarcoma, FNCLCC Grade 2. Staging PET-CT demonstrated a metabolically active mass of about 150 by 119 by 117 millimeters with peripheral FDG uptake, central necrosis, and diffuse reactive marrow uptake, but no distant metastasis. A multidisciplinary oncology team planned a wide local excision, the standard of care for DDLPS, which requires histologically negative surgical margins and often adjuvant radiotherapy. Chemotherapy plays a limited role, with anthracycline-based regimens achieving objective responses in only about 12 percent of advanced cases. For this patient, however, no intervention would arrive in time: the night after referral, she was found unresponsive in her hospital bed, and advanced cardiac life support failed. No autopsy was performed, so the formal cause of death could not be established.

The authors of the report carefully outline plausible mechanisms rather than assigning a definitive one. The most immediately life-threatening possibility is cancer-associated venous thromboembolism with fatal pulmonary embolism. In cancer patients, pulmonary embolism is the second leading cause of death after cancer progression itself, with a four- to seven-fold elevated risk of venous thromboembolism compared with the general population, and in-hospital mortality from cancer-associated pulmonary embolism ranges from 10 to 30 percent. The patient’s unilateral leg edema may have reflected venous compression by the tumor and underlying deep vein thrombosis, compounded by prolonged hospitalization, immobility, active malignancy, chronic kidney disease, diabetes, and systemic inflammation. A second mechanism is cancer cachexia-related cardiac dysfunction: tumor-derived cytokines such as TNF-alpha and IL-6 drive cardiac muscle atrophy, myocardial fibrosis, and ventricular dysfunction, potentially precipitating fatal arrhythmia or acute heart failure. A third possibility is acute hemodynamic compromise from intra-tumoral hemorrhage, sudden expansion of the necrotic cavity, or bacterial superinfection with septic shock, given the enormous tumor burden and its proximity to pelvic vasculature.

The lessons of this case reach beyond a single tragic outcome. A microbiologically sterile necrotic aspirate does not exclude malignancy, and the authors argue that concurrent core biopsy of the lesion wall should be mandatory in any deep soft tissue aspiration with atypical features. Red flags included the sheer size of the lesion, far larger than typical abscesses, the insidious six-month onset, thick and irregular enhancing walls on MRI, intra-tumoral flow voids, rapid re-accumulation after drainage, and the absence of clinical improvement with antibiotics. Clinicians are urged to maintain a low threshold for malignancy in any progressively enlarging deep soft tissue mass, regardless of radiological or inflammatory findings, and to manage thromboembolic risk, cachexia, and hemodynamic vulnerability proactively from the moment of diagnosis. Early biopsy, the authors conclude, is not merely diagnostically valuable; in cases like this one, it may be lifesaving.

Subject of Research: Dedifferentiated liposarcoma of the thigh mimicking an abscess, diagnosed by biopsy after sterile aspiration

Article Title: A Rare Case Report on Dedifferentiated Liposarcoma of the Thigh Mimicking an Abscess With Vascular Features: A Diagnostic Challenge With Fatal Outcome

Article References: Sazal, R. S., Shawon, M. H. H., Zubaer, M., Azad, M. A. K., Murshed, K. M., & Aftab, K. A. (2026). A Rare Case Report on Dedifferentiated Liposarcoma of the Thigh Mimicking an Abscess With Vascular Features: A Diagnostic Challenge With Fatal Outcome. Clinical Case Reports, 14(10), Article e73630. https://doi.org/10.1002/ccr3.73630

Image Credits: AI Generated

DOI: 10.1002/ccr3.73630

Keywords: dedifferentiated liposarcoma, soft tissue sarcoma, liposarcoma, misdiagnosis, abscess mimicry, MDM2, CDK4, MRI, biopsy, pulmonary embolism, cancer cachexia, neo-angiogenesis

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