The effect of radiotherapy on fat content and fatty acids in myxoid liposarcomas quantified by MRI.

Magn Reson Imaging

Department of Medical Radiation Physics, Karolinska University Hospital, Stockholm, Sweden; Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden.

Published: November 2017

Background: Myxoid liposarcomas are highly radiosensitive. Consequently radiotherapy is often used pre-operatively to reduce tumor volume and lessen the post-operative deficit. In soft-tissue sarcomas therapy response is mainly evaluated using magnetic resonance imaging (MRI) and the fundamental criterion for a positive response is decreased tumor size. In myxoid liposarcomas an increased fat content is also known to occur as a response to radiotherapy.

Objective: To highlight the difficulties of MRI for therapy response evaluation in irradiated myxoid liposarcomas, by using MRI Dixon techniques enabling objective quantification of proton density fat fraction (%) and the number of double bonds (ndb; unsaturation degree) of fatty acids. Secondly, to compare quantitative fat fraction measurements versus visual grading of fat content on T1-weighted images.

Case Descriptions: Prior to surgery, two patients with myxoid liposarcoma were treated with 50Gy. Following radiotherapy, both tumors on MRI showed reduced size, elevated fat fraction and transformed fat fraction histograms with diverse changes of ndb, while histopathological specimens showed discordant treatment effects; one case having good response and the other having poor response.

Conclusions: A decrease in tumor size and increase in fat content on MRI cannot be interpreted as positive therapy response in radiotherapy of myxoid liposarcomas. Our data also give further supporting evidence that differentiation and maturation of tumor cells is the cause for the lipoma-like areas seen after radiotherapy. Finally, quantitative MRI Dixon techniques are preferable to visual grading for estimating the fat content in lipomatous tumors.

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http://dx.doi.org/10.1016/j.mri.2017.07.005DOI Listing

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