The British journal of radiology · 2025
How can MRI descriptors be optimally combined to predict idiopathic intracranial hypertension?
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Bitar George G, Touska Philip, Siddiqui Ata, Harvey Joshua, Edi-Osagie Ndidi, Chowdhury Haziq, McHugh James, O'Sullivan Eoin, Connor Steve
Аннотация
OBJECTIVES: To establish how MRI descriptors on standard MRI sequences can be optimally combined to predict idiopathic intracranial hypertension (IIH).
METHODS: A retrospective single-institution cross-sectional study evaluated consecutive IIH patients undergoing MRI between 2002 and 2015 and a control group. Six established and 8 exploratory MRI descriptors were evaluated. Two observers independently analysed MRI descriptors on T1w sagittal and T2w axial sequences while blinded to clinical data with consensus obtained. Inter-rater reliability was calculated, and the presence of MRI descriptors was compared between IIH patients and controls (Bonferroni correction, P < 0.004). Forward stepwise logistic regression determined which combination of MRI descriptors best predicted IIH.
RESULTS: Fifty-four IIH patients (mean age 31.2, standard deviation 10.2, 3 men) and 54 control subjects (mean age 31.7, standard deviation 7.1, 3 men) were evaluated. There was excellent inter-rater reliability for 13/14 MRI descriptors. There were 4/6 established and 6/8 exploratory MRI descriptors associated with IIH (P < 0.004). The optimal combination of descriptors to predict IIH was vertical tortuosity of the optic nerve, enlarged optic nerve sheath, globe flattening score ≥ 2, Yuh score ≥ 3, cervical skin folding, and cervical fat thickness ≥ 10.5 mm. The model correctly classified 93.5% of cases (sensitivity 94.4%, specificity 92.6%, area under the receiver operating characteristic curve [AUC] 0.965).
CONCLUSIONS: Evaluating a combination of vertical tortuosity of the optic nerve, enlarged optic nerve sheath, globe flattening, Yuh score, cervical skin folding, and cervical fat thickness optimally predicts IIH.
ADVANCES IN KNOWLEDGE: New MRI features are validated for the diagnosis of IIH and the optimal combination for diagnosis is established.
REGISTRATION NUMBER: N006 (local institutional review). The full study protocol can be requested from the corresponding author.
METHODS: A retrospective single-institution cross-sectional study evaluated consecutive IIH patients undergoing MRI between 2002 and 2015 and a control group. Six established and 8 exploratory MRI descriptors were evaluated. Two observers independently analysed MRI descriptors on T1w sagittal and T2w axial sequences while blinded to clinical data with consensus obtained. Inter-rater reliability was calculated, and the presence of MRI descriptors was compared between IIH patients and controls (Bonferroni correction, P < 0.004). Forward stepwise logistic regression determined which combination of MRI descriptors best predicted IIH.
RESULTS: Fifty-four IIH patients (mean age 31.2, standard deviation 10.2, 3 men) and 54 control subjects (mean age 31.7, standard deviation 7.1, 3 men) were evaluated. There was excellent inter-rater reliability for 13/14 MRI descriptors. There were 4/6 established and 6/8 exploratory MRI descriptors associated with IIH (P < 0.004). The optimal combination of descriptors to predict IIH was vertical tortuosity of the optic nerve, enlarged optic nerve sheath, globe flattening score ≥ 2, Yuh score ≥ 3, cervical skin folding, and cervical fat thickness ≥ 10.5 mm. The model correctly classified 93.5% of cases (sensitivity 94.4%, specificity 92.6%, area under the receiver operating characteristic curve [AUC] 0.965).
CONCLUSIONS: Evaluating a combination of vertical tortuosity of the optic nerve, enlarged optic nerve sheath, globe flattening, Yuh score, cervical skin folding, and cervical fat thickness optimally predicts IIH.
ADVANCES IN KNOWLEDGE: New MRI features are validated for the diagnosis of IIH and the optimal combination for diagnosis is established.
REGISTRATION NUMBER: N006 (local institutional review). The full study protocol can be requested from the corresponding author.