2020
DOI: 10.3174/ajnr.a6557
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MRI Signal Intensity and Electron Ultrastructure Classification Predict the Long-Term Outcome of Skull Base Chordomas

Abstract: BACKGROUND AND PURPOSE: MR imaging is a useful and widely used evaluation for chordomas. Prior studies have classified chordomas into cell-dense type and matrix-rich type according to the ultrastructural features. However, the relationship between the MR imaging signal intensity and ultrastructural classification is unknown. We hypothesized that MR imaging signal intensity may predict both tumor ultrastructural classification and prognosis.MATERIALS AND METHODS: Seventy-nine patients with skull base chordomas … Show more

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Cited by 5 publications
(2 citation statements)
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“…Therefore, in this study, the SIR was used as a quantitative parameter to eliminate the influence of different MRI scanners and imaging parameters on the results. Similar to our study design, the SIR also showed potential for differential diagnosis in other scenarios (12,(24)(25)(26). However, different from previous studies, we used an external test cohort to further clarify the actual diagnostic performance of the SIR.…”
Section: Discussionmentioning
confidence: 85%
“…Therefore, in this study, the SIR was used as a quantitative parameter to eliminate the influence of different MRI scanners and imaging parameters on the results. Similar to our study design, the SIR also showed potential for differential diagnosis in other scenarios (12,(24)(25)(26). However, different from previous studies, we used an external test cohort to further clarify the actual diagnostic performance of the SIR.…”
Section: Discussionmentioning
confidence: 85%
“…Additionally, the limited phenotypic characterization of SBC prevents an optimal patient stratification to improve treatment outcomes. In this context, the growing availability of imaging data can be favourably exploited as a source of prognostic factors [ 8 , 9 ], with studies in the literature supporting the predictive power of the appearance of chordomas on diagnostic imaging, such as CT and MRI [ 10 ]. More recently, qualitative imaging factors are being complemented by quantitative ones, such as radiomic features [ 11 ].…”
Section: Introductionmentioning
confidence: 99%