RT Journal Article
SR Electronic
T1 Magnetic Resonance Imaging Assessment of Lipomatous Soft-tissue Tumors
JF In Vivo
JO In Vivo
FD International Institute of Anticancer Research
SP 387
OP 395
VO 31
IS 3
A1 CORAN, ALESSANDRO
A1 ORTOLAN, PAOLO
A1 ATTAR, SHADY
A1 ALBERIOLI, ENRICO
A1 PERISSINOTTO, EGLE
A1 TOSI, ANNA LISA
A1 MONTESCO, MARIA CRISTINA
A1 ROSSI, CARLO RICCARDO
A1 TROPEA, SAVERIA
A1 RASTRELLI, MARCO
A1 STRAMARE, ROBERTO
YR 2017
UL http://iv.iiarjournals.org/content/31/3/387.abstract
AB Aim: To establish the accuracy of magnetic resonance imaging (MRI) in distinguishing between benign and malignant lipomatous tumors; to evaluate the reproducibility of the MRI interpretation assessing the agreement between judgments of two radiologists with the same experience in soft-tissue sarcomas; to identify an association among MRI findings (size, depth, septa, nodules, signal homogeneity) and nature of the lesion. Materials and Methods: A total of 54 patients (28 men and 26 women), with a mean age of 56 (range=27-84) were included years. All subjects followed-up by the Multidisciplinary Sarcoma Group. The following MRI findings were judged in a blind study by two radiologists: size, localization, septa, nodules and signal homogeneity. A diagnostic indication was then given from among lipoma, atypical lipomatous tumour (ALT) and liposarcoma. Accuracy in distinguishing between benign and malignant lesions, and between lipoma and ALT (Fisher's exact test), inter-operator agreement (Cohen's kappa), association of MRI findings and malignancy of the lesion (Fisher's exact test and odds ratio) were evaluated. Results: The inter-operator agreement was complete (100%). The agreement between diagnostic hypothesis and histological diagnosis was statistically significant (p<0.05). Among the radiological findings taken into account, only septa and signal homogeneity were significantly associated with the malignancy of the lesion (p<0.05). Conclusion: MRI could be helpful in distinguishing lipomatous tumors, allowing biopsy to be avoided in some cases (negative predictive value=100%).