OBJECTIVES: To investigate whether proton density fat fraction (PDFF) measurements using a six-echo modified Dixon sequence can help to differentiate between benign and malignant vertebral bone marrow lesions. METHODS: Sixty-six patients were prospectively enrolled in our study. In addition to conventional MRI at 3.0-Tesla including at least sagittal T2-weighted/spectral attenuated inversion recovery and T1-weighted sequences, all patients underwent a sagittal six-echo modified Dixon sequence of the spine. The mean PDFF was calculated using regions of interest and compared between vertebral lesions. A cut-off value of 6.40% in PDFF was determined by receiver operating characteristic curves and used to differentiate between malignant (< 6.40%) and benign (≥ 6.40%) vertebral lesions. RESULTS: There were 77 benign and 44 malignant lesions. The PDFF of malignant lesions was statistically significant lower in comparison with benign lesions (p < 0.001) and normal vertebral bone marrow (p < 0.001). The areas under the curves (AUC) were 0.97 for differentiating benign from malignant lesions (p < 0.001) and 0.95 for differentiating acute vertebral fractures from malignant lesions (p < 0.001). This yielded a diagnostic accuracy of 96% in the differentiation of both benign lesions and acute vertebral fractures from malignancy. CONCLUSION: PDFF derived from six-echo modified Dixon allows for differentiation between benign and malignant vertebral lesions with a high diagnostic accuracy. KEY POINTS: • Establishing a diagnosis of indeterminate vertebral lesions is a common clinical problem • Benign bone marrow processes may mimic the signal alterations observed in malignancy • PDFF differentiates between benign and malignant lesions with a high diagnostic accuracy • PDFF of non-neoplastic vertebral lesions is significantly higher than that of malignancy • PDFF from six-echo modified Dixon may help avoid potentially harmful bone biopsy.
OBJECTIVES: To investigate whether proton density fat fraction (PDFF) measurements using a six-echo modified Dixon sequence can help to differentiate between benign and malignant vertebral bone marrow lesions. METHODS: Sixty-six patients were prospectively enrolled in our study. In addition to conventional MRI at 3.0-Tesla including at least sagittal T2-weighted/spectral attenuated inversion recovery and T1-weighted sequences, all patients underwent a sagittal six-echo modified Dixon sequence of the spine. The mean PDFF was calculated using regions of interest and compared between vertebral lesions. A cut-off value of 6.40% in PDFF was determined by receiver operating characteristic curves and used to differentiate between malignant (< 6.40%) and benign (≥ 6.40%) vertebral lesions. RESULTS: There were 77 benign and 44 malignant lesions. The PDFF of malignant lesions was statistically significant lower in comparison with benign lesions (p < 0.001) and normal vertebral bone marrow (p < 0.001). The areas under the curves (AUC) were 0.97 for differentiating benign from malignant lesions (p < 0.001) and 0.95 for differentiating acute vertebral fractures from malignant lesions (p < 0.001). This yielded a diagnostic accuracy of 96% in the differentiation of both benign lesions and acute vertebral fractures from malignancy. CONCLUSION: PDFF derived from six-echo modified Dixon allows for differentiation between benign and malignant vertebral lesions with a high diagnostic accuracy. KEY POINTS: • Establishing a diagnosis of indeterminate vertebral lesions is a common clinical problem • Benign bone marrow processes may mimic the signal alterations observed in malignancy • PDFF differentiates between benign and malignant lesions with a high diagnostic accuracy • PDFF of non-neoplastic vertebral lesions is significantly higher than that of malignancy • PDFF from six-echo modified Dixon may help avoid potentially harmful bone biopsy.
Entities:
Keywords:
Bone marrow malignancy; Chemical shift encoded imaging; MRI; Modified Dixon method; Proton density fat fraction
Authors: Dimitrios C Karampinos; Stefan Ruschke; Michael Dieckmeyer; Holger Eggers; Hendrik Kooijman; Ernst J Rummeny; Jan S Bauer; Thomas Baum Journal: NMR Biomed Date: 2015-10-01 Impact factor: 4.044
Authors: Donald C Zajick; William B Morrison; Mark E Schweitzer; Joan Antoni Parellada; John A Carrino Journal: Radiology Date: 2005-11 Impact factor: 11.105
Authors: Anwar R Padhani; Katherine van Ree; David J Collins; Shirley D'Sa; Andreas Makris Journal: AJR Am J Roentgenol Date: 2013-01 Impact factor: 3.959
Authors: Catherine D G Hines; Huanzhou Yu; Ann Shimakawa; Charles A McKenzie; Jean H Brittain; Scott B Reeder Journal: J Magn Reson Imaging Date: 2009-11 Impact factor: 4.813
Authors: Frederic Carsten Schmeel; Julian Alexander Luetkens; Simon Jonas Enkirch; Andreas Feißt; Christoph Hans-Jürgen Endler; Leonard Christopher Schmeel; Peter Johannes Wagenhäuser; Frank Träber; Hans Heinz Schild; Guido Matthias Kukuk Journal: Eur Radiol Date: 2018-06-01 Impact factor: 5.315
Authors: F T Gassert; A Kufner; F G Gassert; Y Leonhardt; S Kronthaler; B J Schwaiger; C Boehm; M R Makowski; J S Kirschke; T Baum; D C Karampinos; A S Gersing Journal: Osteoporos Int Date: 2021-09-18 Impact factor: 4.507
Authors: Frederic Carsten Schmeel; Simon Jonas Enkirch; Julian Alexander Luetkens; Anton Faron; Nils Lehnen; Alois Martin Sprinkart; Leonard Christopher Schmeel; Alexander Radbruch; Ulrike Attenberger; Guido Matthias Kukuk; Petra Mürtz Journal: Clin Neuroradiol Date: 2021-03-31 Impact factor: 3.649
Authors: Tobias Greve; Nithin Manohar Rayudu; Michael Dieckmeyer; Christof Boehm; Stefan Ruschke; Egon Burian; Christopher Kloth; Jan S Kirschke; Dimitrios C Karampinos; Thomas Baum; Karupppasamy Subburaj; Nico Sollmann Journal: Front Endocrinol (Lausanne) Date: 2022-07-11 Impact factor: 6.055
Authors: Sebastien Bacher; Steven David Hajdu; Yael Maeder; Vincent Dunet; Tom Hilbert; Patrick Omoumi Journal: Eur Radiol Date: 2021-05-26 Impact factor: 5.315