Literature DB >> 33254066

Long-term diagnostic value of MRI in detecting recurrent aggressive fibromatosis at two multidisciplinary sarcoma centers.

Sam Sedaghat1, Maya Sedaghat2, Sebastian Krohn3, Olav Jansen4, Kai Freund5, Arne Streitbürger6, Benjamin Reichardt7.   

Abstract

PURPOSE: To assess the diagnostic accuracy of MRI in detecting recurrent aggressive fibromatosis (AF) during long-term follow-up at two multidisciplinary sarcoma centers.
METHODS: Seventy-nine patients from two sarcoma centers were included in this IRB-approved study and were examined postoperatively using 1.5-T MRI. MRI follow-up scans were reviewed for true-positive/-negative and false-positive/-negative results. Available pathological reports and MRI follow-ups were set as reference.
RESULTS: The median age of the patients was 38.1 ± 15.3 years. Of the patients 27.9 % showed recurrent AF lesions. The most common localizations of AF were the axilla/shoulder (n = 15) and the thigh (n = 11). From 498 postoperative MRI follow-ups, 24 true-positive, 16 false-positive, 6 false-negative, and 452 true-negative MRI follow-ups were identified. The overall sensitivity and specificity for detecting recurrent AF was 80 % and 97 %, respectively. There was no significant difference in the diagnostic accuracy at the two sarcoma centers. All false-negative results were found in small lesions. False-positive results mostly mimicked streaky (n = 10) and small ovoid/nodular (n = 5) lesions. The configuration of recurrent AF was significantly most often fascicular (50 %; p = 0.001-0.005).
CONCLUSION: MRI shows a high long-term diagnostic value in detecting AF recurrences. Nevertheless, radiologists should pay close attention when lesions are small, as they may remain undetected. Although the configuration of recurrent AF is most often fascicular, recurrences may also appear in different shapes.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Aggressive fibromatosis; Diagnostic accuracy; Long-Tterm; MRI; Sarcoma center

Mesh:

Year:  2020        PMID: 33254066     DOI: 10.1016/j.ejrad.2020.109406

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  1 in total

1.  Development, Validation, and Visualization of A Web-Based Nomogram for Predicting the Recurrence-Free Survival Rate of Patients With Desmoid Tumors.

Authors:  Haotian Liu; Kai Huang; Tao Li; Tielong Yang; Zhichao Liao; Chao Zhang; Lijie Xiang; Yong Chen; Jilong Yang
Journal:  Front Oncol       Date:  2021-02-25       Impact factor: 6.244

  1 in total

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