Improved detection of multiple sclerosis lesions with T2-prepared double inversion recovery at 3T

J Neuroimaging. 2022 Sep;32(5):902-909. doi: 10.1111/jon.13021. Epub 2022 Jul 1.

Abstract

Background and purpose: Double inversion recovery (DIR) imaging is used in multiple sclerosis (MS) clinical protocols to improve the detection of cortical and juxtacortical gray matter lesions by nulling confounding signals originating from the cerebrospinal fluid and white matter. Achieving a high isotropic spatial resolution, to depict the neocortex and its typically small lesions, is challenged by the reduced signal-to-noise ratio (SNR) determined by multiple tissue signal nulling. Here, we evaluate both conventional and optimized DIR implementations to improve tissue contrast (TC), SNR, and MS lesion conspicuity.

Methods: DIR images were obtained from MS patients and healthy controls using both conventional and prototype implementations featuring a T2-preparation module (T2P), to improve SNR and TC, as well as an image reconstruction routine with iterative denoising (ID). We obtained quantitative measures of SNR and TC, and evaluated the visibility of MS cortical, cervical cord, and optic nerve lesions in the different DIR images.

Results: DIR implementations adopting T2P and ID enabled improving the SNR and TC of conventional DIR. In MS patients, 34% of cortical, optic nerve, and cervical cord lesions were visible only in DIR images acquired with T2P, and not in conventional DIR images. In the studied cases, image reconstruction with ID did not improve lesion conspicuity.

Conclusions: DIR with T2P should be preferred to conventional DIR imaging in protocols studying MS patients, as it improves SNR and TC and determines an improvement in cortical, optic nerve, and cervical cord lesion conspicuity.

Keywords: cervical cord; gray matter; magnetic resonance imaging; multiple sclerosis; optic nerve.

MeSH terms

  • Humans
  • Image Processing, Computer-Assisted / methods
  • Magnetic Resonance Imaging / methods
  • Multiple Sclerosis* / pathology
  • Signal-To-Noise Ratio
  • White Matter* / pathology