Detection of cerebral cortical vein thrombosis with high-resolution susceptibility weighted imaging -  A comparison with MR venography and standard MR sequences.

Comparison of the performance of high-resolution susceptibility weighted imaging with standard MR sequences and MR venography to identify cortical vein clots. A retrospective review of 51 consecutive cases of cerebral venous thrombosis and 27 controls was performed with independent analysis of all MR sequences. Reference standard was obtained with consensus in a separate session by reviewing all MR sequences together. Cortical vein clots were observed in 30 cases including 9 males and 21 females in the age range of 1 month to 70 years (Mean 34.9 ± 20.2 years). Sensitivity, specificity, negative predictive value, positive predictive value and accuracy of susceptibility weighted imaging for the identification of cortical vein clots were 0.93, 1.0, 1.0, 0.96 and 0.97 respectively. For all other sequences, sensitivity ranged from 0.06 to 0.39 and accuracy from 0.60 to 0.73. Combination of all sequences yielded a value of 1.0 for sensitivity, specificity, positive predictive value, negative predictive value and accuracy for the detection of cortical vein clots. Significant result for area under the receiver operating curve was observed only for SWI with a value of 0.91 (p - .000). Susceptibility weighted imaging demonstrates the best sensitivity and accuracy among standard MR sequences including MR venography for the detection of early stage cortical vein clots. However, it needs to be interpreted in combination with other MR sequences for the most accurate evaluation of cortical vein clots. © 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Citation

Faiza Boukerche, Sivasubramanian Balakrishnan, Paul Kalapos, Krishnamoorthy Thamburaj. Detection of cerebral cortical vein thrombosis with high-resolution susceptibility weighted imaging -  A comparison with MR venography and standard MR sequences. Neuroradiology. 2023 May;65(5):885-892

Mesh Tags

PMID: 36720750

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