Development of high‐resolution 3D MR fingerprinting for detection and characterization of epileptic lesions

Abstract

Background Conventional MRI can be limited in detecting subtle epileptic lesions or identifying active/epileptic lesions among widespread, multifocal lesions. Purpose We developed a high‐resolution 3D MR fingerprinting (MRF) protocol to simultaneously provide quantitative T1, T2, proton density, and tissue fraction maps for detection and characterization of epileptic lesions. Study type Prospective. Population National Institute of Standards and Technology (NIST) / International Society for Magnetic Resonance in Medicine (ISMRM) phantom, five healthy volunteers and 15 patients with medically intractable epilepsy undergoing presurgical evaluation with noninvasive or invasive electroclinical data. Field Strength/Sequence 3D MRF scans and routine clinical epilepsy MR protocols were acquired at 3 T. Assessment The accuracy of the T1 and T2 values were first evaluated using the NIST/ISMRM phantom. The repeatability was then estimated with both phantom and volunteers based on the coefficient of variance (CV). For epilepsy patients, all the maps were qualitatively reviewed for lesion detection by three independent reviewers (S.E.J., M.L., I.N.) blinded to clinical data. Region of interest (ROI) analysis was performed on T1 and T2 maps to quantify the multiparametric signal differences between lesion and normal tissues. Findings from qualitative review and quantitative ROI analysis were compared with patients' electroclinical data to assess concordance. Statistical Tests Phantom results were compared using R‐squared, and patient results were compared using linear regression models. Results The phantom study showed high accuracy with the standard values, with an R2 of 0.99. The volunteer study showed high repeatability, with an average CV of 4.3% for T1 and T2 in various tissue regions. For the 15 patients, MRF showed additional findings in four patients, with the remaining 11 patients showing findings consistent with conventional MRI. The additional MRF findings were highly concordant with patients' electroclinical presentation. Data Conclusion The 3D MRF protocol showed potential to identify otherwise inconspicuous epileptogenic lesions from the patients with negative conventional MRI diagnosis, as well as to correlate with different levels of epileptogenicity when widespread lesions were present. Level of Evidence: 3. Technical Efficacy Stage: 3. J. Magn. Reson. Imaging 2019;49:1333–1346.

Retrospective rigid motion correction of three‐dimensional magnetic resonance fingerprinting of the human brain

“…Several reconstruction algorithms have been suggested for improving the quality of the maps like multi-scale reconstruction, 15 low-rank models [16][17][18] and sliding window methods. 19 MRF has also been extended to three-dimensional (3D) acquisitions [20][21][22] for improved spatial resolution and diagnostic value, as well as high repeatability, 23 yet several important aspects like motion correction have not been fully addressed.…”

MR fingerprinting for rapid simultaneous T1, T2, and T1ρ relaxation mapping of the human articular cartilage at 3T

“…A general approach proposed by Ma et al 42 can be used to increase accuracy. This problem could also be addressed by using a 3D image‐encoding strategy 43,44 …”

A novel magnetic resonance technique to characterise grey matter microstructure in the human brain

“…Future work may involve integrating the MRF residual analysis framework with previous MRF-based clinical applications (e.g. epilepsy [90,91] and multiple sclerosis [68] diagnosis, characterising age-related microstructural changes [86] Finally, it should be noted that the need for observer-independent microstructural parcellation was one of the main motivations for performing the studies presented in this thesis. However, the analysis pipeline proposed in this thesis was a novel approach to this research problem.…”

“…Epilepsy [90,91] 3D MRF [73] or Sliding Window [92] SSFP-MRF [67] "Better able to identify lesions in less time than existing methods. "…”

“…The acquisition strategy of MRF allows simultaneous quantification of multiple tissue properties through a single scan and is the key to resolving the existing issues with other multi-modal MRI methods. Previous studies have exploited used MRF in a variety of clinical applications including detecting and characterising brain tumours[89,119] and identifying epileptic[90] and multiple sclerosis[68] lesions. The application of MRF in cortical parcellation has also been recently explored[120] but only utilises MR relaxometry measurements derived from the MR fingerprinting pipeline.…”