Two Classes of T1 Hypointense Lesions in Multiple Sclerosis With Different Clinical Relevance

Krisztián Kocsis; Nikoletta Szabó; Eszter Tóth; András Király; Péter Faragó; Bálint Kincses; Dániel Veréb; Bence Bozsik; Katalin Boross; Melinda Katona; Péter Bodnár; Nyúl Gábor László; László Vécsei; Péter Klivényi; Krisztina Bencsik; Zsigmond Tamás Kincses

doi:10.3389/fneur.2021.619135

Two Classes of T1 Hypointense Lesions in Multiple Sclerosis With Different Clinical Relevance

Front Neurol. 2021 Mar 3:12:619135. doi: 10.3389/fneur.2021.619135. eCollection 2021.

Authors

Krisztián Kocsis¹, Nikoletta Szabó¹, Eszter Tóth¹, András Király¹, Péter Faragó¹, Bálint Kincses¹, Dániel Veréb², Bence Bozsik¹, Katalin Boross¹, Melinda Katona³, Péter Bodnár³, Nyúl Gábor László³, László Vécsei^{1

4}, Péter Klivényi¹, Krisztina Bencsik¹, Zsigmond Tamás Kincses^{1

2}

Affiliations

¹ Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary.
² Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary.
³ Department of Image Processing and Computer Graphics, University of Szeged, Szeged, Hungary.
⁴ Magyar Tudományos Akadémia-Szegedi Tudományegyetem (MTA-SZTE) Neuroscience Research Group, Szeged, Hungary.

Abstract

Background: Hypointense lesions on T1-weighted images have important clinical relevance in multiple sclerosis patients. Traditionally, spin-echo (SE) sequences are used to assess these lesions (termed black holes), but Fast Spoiled Gradient-Echo (FSPGR) sequences provide an excellent alternative. Objective: To determine whether the contrast difference between T1 hypointense lesions and the surrounding normal white matter is similar on the two sequences, whether different lesion types could be identified, and whether the clinical relevance of these lesions types are different. Methods: Seventy-nine multiple sclerosis patients' lesions were manually segmented, then registered to T1 sequences. Median intensity values of lesions were identified on all sequences, then K-means clustering was applied to assess whether distinct clusters of lesions can be defined based on intensity values on SE, FSPGR, and FLAIR sequences. The standardized intensity of the lesions in each cluster was compared to the intensity of the normal appearing white matter in order to see if lesions stand out from the white matter on a given sequence. Results: 100% of lesions on FSPGR images and 69% on SE sequence in cluster #1 exceeded a standardized lesion distance of Z = 2.3 (p < 0.05). In cluster #2, 78.7% of lesions on FSPGR and only 17.7% of lesions on SE sequence were above this cutoff value, meaning that these lesions were not easily seen on SE images. Lesion count in the second cluster (lesions less identifiable on SE) significantly correlated with the Expanded Disability Status Scale (EDSS) (R: 0.30, p ≤ 0.006) and with disease duration (R: 0.33, p ≤ 0.002). Conclusion: We showed that black holes can be separated into two distinct clusters based on their intensity values on various sequences, only one of which is related to clinical parameters. This emphasizes the joint role of FSPGR and SE sequences in the monitoring of MS patients and provides insight into the role of black holes in MS.

Keywords: MRI protocol; T1 hypointense lesions; black holes; clinical state; clustering; multiple sclerosis.