HLA-DQA1*04:01 is related to a higher multiple sclerosis lesion load on T2/Flair MRI sequences

ABSTRACT Background: The genetic predisposition to multiple sclerosis (MS) is associated with HLA alleles, especially HLA-DRB1*15:01. Objective: To identify associations between findings in magnetic resonance imaging (MRI) and genetic features in a Brazilian cohort of patients with MS. Methods: We retrospectively studied data from 95 consecutive patients with MS. Two independent observers who were blinded to the clinical data identified black holes and enhanced lesions on T1 MRI sequences, and counted and measured contrast-enhanced lesions on T2 and Flair (fluid attenuation inversion recovery) sequences. Cases were classified according to lesion size, number, and volume. The HLA-DRB1, HLA-DQB1, and HLA-DQA1 alleles, and the rs4774, rs3087456, rs6897932, rs731236, and rs1033182 single nucleotide polymorphisms were identified by polymerase chain reaction amplification with sequence-specific primers using the One Lambda Inc. Kit, Canoga Park, CA, USA. Results: Patients with the HLA-DQA1*04:01 allele had lesion load (adjusted for age, sex, and MS duration) above median compared with patients with other HLA-DQA1 alleles (p=0.02). There were no differences among all the other HLA alleles and single nucleotide polymorphisms and lesion load. Conclusions: The correlation of the HLA-DQA1*04:01 allele with a higher lesion load on T2/Flair MRI sequences suggests that the presence of this allele is associated with the risk of greater MS severity.

Assessment of Artificial Intelligence Automatic Multiple Sclerosis Lesion Delineation Tool for Clinical Use

Purpose To implement and validate an existing algorithm for automatic delineation of white matter lesions on magnetic resonance imaging (MRI) in patients with multiple sclerosis (MS) on a local single-center dataset. Methods We implemented a white matter hyperintensity segmentation model, based on a 2D convolutional neural network, using the conventional T2-weighted fluid attenuated inversion recovery (FLAIR) MRI sequence as input. The model was adapted for delineation of MS lesions by further training on a local dataset of 93 MS patients with a total of 3040 lesions. A quantitative evaluation was performed on ten test patients, in which model-generated masks were compared to manually delineated masks from two expert delineators. A subsequent qualitative evaluation of the implemented model was performed by two expert delineators, in which generated delineation masks on a clinical dataset of 53 patients were rated acceptable (< 10% errors) or unacceptable (> 10% errors) based on the total number of true lesions. Results The quantitative evaluation resulted in an average accuracy score (F1) of 0.71, recall of 0.77 and dice similarity coefficient of 0.62. Our implemented model obtained the highest scores in all three metrics, when compared to three out of the box lesion segmentation models. In the clinical evaluation an average of 94% of our 53 model-generated masks were rated acceptable. Conclusion After adaptation to our local dataset, the implemented segmentation model was able to delineate MS lesions with a high clinical value as rated by delineation experts while outperforming popular out of the box applications. This serves as a promising step towards implementation of automatic lesion delineation in our MS clinic.

The Brain–Heart Link: A Case Report of a Critically Located Multiple Sclerosis Lesion in the Brainstem Leading to Recurrent Takotsubo Syndrome

Various central nervous system (CNS) diseases, including neurovascular and neuroinflammatory diseases, can lead to stress cardiomyopathy, also known as Takotsubo syndrome (TTS). We present a case of a 69-year-old woman with cardiovascular comorbidities, suffering from repeated episodes of TTS and respiratory failure due to a critical lesion in the brainstem, leading to a diagnosis of multiple sclerosis (MS). Despite aggressive treatment, intractable and recurrent symptoms in our patient occurred. Repeated bouts of autonomic dysfunction and respiratory failure ultimately led to installment of palliative care and the patient passing away. TTS should raise suspicion for underlying neurological diseases. Thorough questioning of previous neurological symptoms and extensive neurological workup is warranted. MS should be considered as a trigger of TTS also in elderly patients with cardiovascular risk factors.