Large atypical lipomatous tumours of the limbs: A report of three cases
Bibliographic record
Abstract
Atypical lipomatous tumours (ALT) are rare adipocytic neoplasms classified under well-differentiated liposarcomas. Although they have low metastatic potential, their progressive growth and anatomical location can lead to significant functional impairments. Complete surgical excision remains the primary treatment; however, challenges arise when these tumours are located near critical neurovascular structures. This study presents three clinical cases of large ALT in the limbs, analysing the diagnostic, surgical and prognostic aspects. This study reports on three patients (ages 64, 70 and 69) who presented with large, slowly growing lipomatous masses in the limbs, evolving over several years. The tumours, ranging from 25 to 60 cm in size, were assessed using imaging techniques, including MRI and CT scans. Surgical excision was performed in all cases, ensuring complete tumour resection while preserving adjacent neurovascular structures. Histopathological analysis confirmed the diagnosis of ALT. Postoperative functional recovery and recurrence were monitored over a follow-up period of 24 months. All patients experienced significant clinical improvement, with full restoration of joint mobility and resolution of sensory disturbances. No local tumour recurrence was observed. Postoperative imaging demonstrated effective tissue regeneration without excessive fibrosis or adhesions. The quality-of-life assessment using the Toronto Extremity Salvage Score (TESS) indicated a marked improvement in motor function and autonomy. ALT, despite being a low-grade tumour, requires a multidisciplinary approach for optimal management. Complete surgical excision ensures excellent long-term outcomes, but extended clinical and radiological surveillance remains crucial. Advancements in molecular pathology and imaging techniques may further refine treatment strategies and enhance patient prognosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".