Liposarcoma or lipoma: does genetics change classic imaging criteria?

Diagnostic accuracy of CT and MR features for detecting atypical lipomatous tumors and malignant liposarcomas: a systematic review and meta-analysis

OBJECTIVES

This systematic review and meta-analysis evaluated the diagnostic accuracy of CT and MRI for differentiating atypical lipomatous tumors and malignant liposarcomas from benign lipomatous lesions.

METHODS

MEDLINE, EMBASE, Scopus, the Cochrane Library, and the gray literature from inception to January 2022 were systematically evaluated. Original studies with > 5 patients evaluating the accuracy of CT and/or MRI for detecting liposarcomas with a histopathological reference standard were included. Meta-analysis was performed using a bivariate mixed-effects regression model. Risk of bias was evaluated using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). This study is registered on PROSPERO, number CRD42022306479.

RESULTS

Twenty-six studies with a total of 2613 patients were included. Mean/median reported patient ages ranged between 50 and 63 years. The summary sensitivity and specificity of radiologist gestalt for detecting liposarcomas was 85% (79-90% 95% CI) and 63% (52-72%), respectively. Deep depth to fascia, thickened septations, enhancing components, and lesion size (≥ 10 cm) all demonstrated sensitivities ≥ 85%. Other imaging characteristics including heterogenous/amorphous signal intensity, irregular tumor margin, and nodules present demonstrated lower sensitivities ranging from 43 to 65%. Inter-reader reliability for radiologist gestalt within studies ranged from fair to substantial (k = 0.23-0.7). Risk of bias was predominantly mixed for patient selection, low for index test and reference standard, and unclear for flow and timing.

CONCLUSION

Higher sensitivities for detecting liposarcomas were achieved with radiologist gestalt, deep depth to fascia, thickened septations, enhancing components, and large size. Combined clinical and imaging scoring and/or radiomics both show promise for optimal performance, though require further analysis with prospective study designs.

CLINICAL RELEVANCE

This pooled analysis evaluates the accuracy of CT and MRI for detecting atypical lipomatous tumors and malignant liposarcomas. Radiologist gestalt, deep depth to fascia, thickened septations, enhancing components, and large size demonstrate the highest overall sensitivities.

KEY POINTS

• The summary sensitivity and specificity of radiologist gestalt for detecting liposarcomas was 85% (79-90% 95% CI) and 63% (52-72%), respectively. • Radiologist gestalt, deep depth to fascia, thickened septations, enhancing components, and large tumor size (≥ 10 cm) showed the highest sensitivities for detecting atypical lipomatous tumors/well-differentiated liposarcomas and malignant liposarcomas. • A combined clinical and imaging scoring system and/or radiomics is likely to provide the best overall diagnostic accuracy, although currently proposed scoring systems and radiomic feature analysis require further study with prospective study designs.

Development and Evaluation of MR-Based Radiogenomic Models to Differentiate Atypical Lipomatous Tumors from Lipomas

Background: The aim of this study was to develop and validate radiogenomic models to predict the MDM2 gene amplification status and differentiate between ALTs and lipomas on preoperative MR images. Methods: MR images were obtained in 257 patients diagnosed with ALTs (n = 65) or lipomas (n = 192) using histology and the MDM2 gene analysis as a reference standard. The protocols included T2-, T1-, and fat-suppressed contrast-enhanced T1-weighted sequences. Additionally, 50 patients were obtained from a different hospital for external testing. Radiomic features were selected using mRMR. Using repeated nested cross-validation, the machine-learning models were trained on radiomic features and demographic information. For comparison, the external test set was evaluated by three radiology residents and one attending radiologist. Results: A LASSO classifier trained on radiomic features from all sequences performed best, with an AUC of 0.88, 70% sensitivity, 81% specificity, and 76% accuracy. In comparison, the radiology residents achieved 60–70% accuracy, 55–80% sensitivity, and 63–77% specificity, while the attending radiologist achieved 90% accuracy, 96% sensitivity, and 87% specificity. Conclusion: A radiogenomic model combining features from multiple MR sequences showed the best performance in predicting the MDM2 gene amplification status. The model showed a higher accuracy compared to the radiology residents, though lower compared to the attending radiologist.

Differentiating atypical lipomatous tumors from lipomas with magnetic resonance imaging: a comparison with MDM2 gene amplification status

Background

To evaluate the diagnostic value of MR imaging for the differentiation of lipomas and atypical lipomatous tumors (ALT) in comparison with histology and MDM2 amplification status.

Methods

Patients with well-differentiated lipomatous tumors (n = 113), of which 66 were diagnosed as lipoma (mean age 53 years (range, 13–82); 47% women) and 47 as atypical lipomatous tumor (ALT; mean age 60 years (range, 28–88); 64% women), were included into this study using histology and MDM2 amplification status by fluorescence in situ hybridization (FISH) as standard of reference. Preoperative MR images were retrospectively assessed by two radiologists for the following imaging features: maximum tumor diameter (mm) as well as the affected compartment (intramuscular, intermuscular or subcutaneous), septa (absent, thin (< 2 mm) or thick septa (> 2 mm) with nodular components); contrast enhancing areas within the lipomatous tumor (< 1/3 of the tumor volume, > 1/3 of the tumor volume);

Results

Of the 47 patients with ALT, 40 (85.1%) presented thick septa (> 2 mm) and this finding significantly increased the likelihood of ALT (OR 6.24, 95% CI 3.36–11.59; P < 0.001). The likelihood of ALT was increased if the tumor exceeded a maximum diameter of 130.0 mm (OR 2.74, 95% CI 1.82–4.11, P < 0.001). The presence of contrast enhancement in lipomatous tumors significantly increased the likelihood of ALT (Odds ratio (OR) 2.95, 95% confidence interval (CI) 2.01–4.31; P < 0.001). Of the lipomas, 21.1% were located subcutaneously, 63.6% intramuscularly and 15.2% intermuscularly. On the other hand, none of the ALTs were located subcutaneously, the majority was located intermuscularly (87.3%) and a small number of ALTs was located intramuscularly (12.7%).

Conclusions

Our results suggest that using specific morphological MR imaging characteristics (maximum tumor diameter, thick septa and contrast enhancement) and the information on the localization of the lipomatous tumor, a high sensitivity and substantial specificity can be achieved for the diagnosis of lipomas and ALTs.

Non-Radiographic Risk Factors Differentiating Atypical Lipomatous Tumors from Lipomas

PURPOSE

To determine non-radiographic risk factors differentiating atypical lipomatous tumors (ALTs) from lipomas.

METHODS

All patients with deep-seated lipomatous tumors of the extremities treated from January 2000 to October 2010 were retrospectively reviewed. Factors reviewed included age, gender, tumor location, size, histology, local recurrence, dedifferentiation, and metastasis. Multivariate logistic regression models were used to evaluate the effects of patient characteristics on ALT status.

RESULTS

Ninety-four lipomas and 46 ALTs were included. Patients with an ALT were older (median: 60.5 vs. 55 years). Lipomas were evenly distributed between upper (48.9%) and lower extremities (51.1%), whereas ALTs predominately involved the lower extremities (91.3%). Median ALT size (22 cm) was greater than lipomas (10 cm), p < 0.0001. One lipoma (1.04%) recurred at 77 months and five ALTs (10.9%) recurred at an average of 39 months (19-64 months). Two ALTs originally treated with wide resection recurred with a dedifferentiated component and were treated with wide re-excision and chemotherapy. No metastases or tumor-related deaths occurred in either group at the time of last follow-up. Patients older than 60 years, tumors greater than 10 cm, or thigh location, were more likely to be diagnosed with an ALT (p < 0.05).

CONCLUSION

Lipomatous tumors were more likely to be ALTs when the tumor was at least 10 cm in size, located in the thigh, or found in patients that were 60 years of age or older. These risk factors may be used to guide management and surveillance strategies, when lipomatous tumors do not display characteristic radiographic features.

Recurrence After Marginal Excision for Atypical Lipomatous Tumors Versus Lipomas of the Extremities

This study reviewed the medical records of 90 patients with lipomas (47 patients) and atypical lipomatous tumors (ALT)/well-differentiated liposarcomas (WDL) (43 patients) of the extremities treated from 2006 to 2012. All patients had preoperative biopsy and postoperative histologic analysis of the tumors; surgical margins were marginal in all cases. Histologic sections of the tissue blocks from the excised specimens were re-reviewed for all patients; a consensus with postoperative histologic analysis was confirmed. Molecular chromosome analysis was performed on fluorescence in situ hybridization in tissue sections from the tissue blocks in all cases for the purpose of this study; a ratio greater than 2 was considered to represent murine double-minute 2 (MDM2) amplification consistent with a diagnosis of ALT/WDL. Mean follow-up was 52 months (range, 14-96 months). Local recurrence and metastasis rates and the relationship of patient age and sex with tumor size and location were evaluated. None of the patients with lipomas experienced local recurrence compared with 6 patients (13.9%) with ALT/WDL who experienced local recurrence within a mean of 48 months (range, 33-96 months); this difference was statistically significant. None of the patients in either group experienced metastasis prior to the study period. Local recurrence did not correlate statistically with patient age or sex, or with tumor size or location. [Orthopedics. 2016; 39(4):e610-e614.].

Differentiation of lipoma from liposarcoma on MRI using texture and shape analysis

RATIONALE AND OBJECTIVES

To determine if differentiation of lipoma from liposarcoma on magnetic resonance imaging can be improved using computer-assisted diagnosis (CAD).

MATERIALS AND METHODS

Forty-four histologically proven lipomatous tumors (24 lipomas and 20 liposarcomas) were studied retrospectively. Studies were performed at 1.5T and included T1-weighted, T2-weighted, T2-fat-suppressed, short inversion time inversion recovery, and contrast-enhanced sequences. Two experienced musculoskeletal radiologists blindly and independently noted their degree of confidence in malignancy using all available images/sequences for each patient. For CAD, tumors were segmented in three dimensions using T1-weighted images. Gray-level co-occurrence and run-length matrix textural features, as well as morphological features, were extracted from each tumor volume. Combinations of shape and textural features were used to train multiple, linear discriminant analysis classifiers. We assessed sensitivity, specificity, and accuracy of each classifier for delineating lipoma from liposarcoma using 10-fold cross-validation. Diagnostic accuracy of the two radiologists was determined using contingency tables. Interreader agreement was evaluated by Cohen kappa.

RESULTS

Using optimum-threshold criteria, CAD produced superior values (sensitivity, specificity, and accuracy are 85%, 96%, and 91%, respectively) compared to radiologist A (75%, 83%, and 80%) and radiologist B (80%, 75%, and 77%). Interreader agreement between radiologists was substantial (kappa [95% confidence interval]=0.69 [0.48-0.90]).

CONCLUSIONS

CAD may help radiologists distinguish lipoma from liposarcoma.

Incidental pancreatic lipomas: computed tomography imaging findings with emphasis on diagnostic challenges

PURPOSE

The purpose of this study was to describe the computed tomography (CT) findings of pancreatic lipomas of 9 cases, with emphasis to diagnostic challenges.

METHODS

Between March 2006 and April 2008, 9 patients with pancreatic lipomas that were diagnosed by CT were reviewed in the present study. Clinical data and CT features of these 9 cases were retrospectively analysed. The patient population included 5 men and 4 women, aged 42-81 years (mean age, 65.8 years). The patients were followed up for at least 2 years with control CTs.

RESULTS

In all 9 cases, a well-bordered nodular fat density lesion was incidentally detected in the pancreas. Four of the lesions had a lobulated contour, and 2 of them had septations. Two of the lipomas were located in the head, 3 in the neck, 3 in the corpus, and 1 in the tail. The CT densitometric values were between -90 and -120 HU, with a mean value of -106 HU. No pancreatic or biliary dilatation or compression to the adjacent structures was seen. All the cases had control CTs, and the lipomas remained unchanged during the follow-up period. Histopathologic confirmation of the diagnosis was not planned for the cases.

CONCLUSION

Lipomas are rarely encountered in the pancreas. They often are diagnosed coincidentally as small, well-circumscribed, encapsulated, homogeneous, mature adipose masses on imaging studies. Imaging follow-up strategy or histopathologic confirmation is not necessary in asymptomatic patients.