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000182640 0247_ $$2doi$$a10.1002/mrm.29476
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000182640 041__ $$aEnglish
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000182640 1001_ $$00000-0002-5978-3383$$aRuck, Laurent$$b0
000182640 245__ $$aInfluence of image contrasts and reconstruction methods on the classification of multiple sclerosis-like lesions in simulated sodium magnetic resonance imaging.
000182640 260__ $$aNew York, NY [u.a.]$$bWiley-Liss$$c2023
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000182640 500__ $$a#LA:E020# / 2023 Mar;89(3):1102-1116
000182640 520__ $$aTo evaluate the classifiability of small multiple sclerosis (MS)-like lesions in simulated sodium (23 Na) MRI for different 23 Na MRI contrasts and reconstruction methods.23 Na MRI and 23 Na inversion recovery (IR) MRI of a phantom and simulated brain with and without lesions of different volumes (V = 1.3-38.2 nominal voxels) were simulated 100 times by adding Gaussian noise matching the SNR of real 3T measurements. Each simulation was reconstructed with four different reconstruction methods (Gridding without and with Hamming filter, Compressed sensing (CS) reconstruction without and with anatomical 1 H prior information). Based on the mean signals within the lesion volumes of simulations with and without lesions, receiver operating characteristics (ROC) were determined and the area under the curve (AUC) was calculated to assess the classifiability for each lesion volume.Lesions show higher classifiability in 23 Na MRI than in 23 Na IR MRI. For typical parameters and SNR of a 3T scan, the voxel normed minimal classifiable lesion volume (AUC > 0.9) is 2.8 voxels for 23 Na MRI and 19 voxels for 23 Na IR MRI, respectively. In terms of classifiability, Gridding with Hamming filter and CS without anatomical 1 H prior outperform CS reconstruction with anatomical 1 H prior.Reliability of lesion classifiability strongly depends on the lesion volume and the 23 Na MRI contrast. Additional incorporation of 1 H prior information in the CS reconstruction was not beneficial for the classification of small MS-like lesions in 23 Na MRI.
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000182640 650_7 $$2Other$$aX-nuclei MRI
000182640 650_7 $$2Other$$aanatomical prior information
000182640 650_7 $$2Other$$acompressed sensing (CS)
000182640 650_7 $$2Other$$alesion classification
000182640 650_7 $$2Other$$amultiple sclerosis (MS)
000182640 650_7 $$2Other$$asodium (23Na)
000182640 7001_ $$aMennecke, Angelika$$b1
000182640 7001_ $$00000-0002-2520-9025$$aWilferth, Tobias$$b2
000182640 7001_ $$aLachner, Sebastian$$b3
000182640 7001_ $$aMüller, Max$$b4
000182640 7001_ $$aEgger, Nico$$b5
000182640 7001_ $$aDoerfler, Arnd$$b6
000182640 7001_ $$aUder, Michael$$b7
000182640 7001_ $$0P:(DE-He78)054fd7a5195b75b11fbdc5c360276011$$aNagel, Armin$$b8$$eLast author$$udkfz
000182640 773__ $$0PERI:(DE-600)1493786-4$$a10.1002/mrm.29476$$gp. mrm.29476$$n3$$p1102-1116$$tMagnetic resonance in medicine$$v89$$x0740-3194$$y2023
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