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In this article, we present an advanced metabolite quantification method for MRSI data, in which the available spatial information is considered. A nonlinear least\u2010squares algorithm is proposed in which prior knowledge is included in the form of proximity constraints on the spectral parameters within a grid and optimized starting values. A penalty term that promotes a spatially smooth spectral parameter map is added to the fitting algorithm. This method is adaptive, in the sense that several sweeps through the grid are performed and each solution may tune some hyperparameters at run\u2010time. Simulation studies of MRSI data showed significantly improved metabolite estimates after the inclusion of spatial information. Improved metabolite maps were also demonstrated by applying the method to <jats:italic>in vivo<\/jats:italic> MRSI data. Overlapping peaks or peaks of compounds present at low concentration can be better quantified with the proposed method than with single\u2010voxel approaches. The new approach compares favorably against the multivoxel approach embedded in the well\u2010known quantification software LCModel. Copyright \u00a9 2010 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/nbm.1628","type":"journal-article","created":{"date-parts":[[2010,12,28]],"date-time":"2010-12-28T06:56:17Z","timestamp":1293519377000},"page":"824-835","source":"Crossref","is-referenced-by-count":18,"title":["Exploiting spatial information to estimate metabolite levels in two\u2010dimensional MRSI of heterogeneous brain lesions"],"prefix":"10.1002","volume":"24","author":[{"given":"Anca R.","family":"Croitor Sava","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diana M.","family":"Sima","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jean\u2010Baptiste","family":"Poullet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alan J.","family":"Wright","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arend","family":"Heerschap","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sabine","family":"Van Huffel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2010,12,28]]},"reference":[{"key":"e_1_2_8_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/81401"},{"key":"e_1_2_8_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2004.06.022"},{"key":"e_1_2_8_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.nec.2004.07.004"},{"key":"e_1_2_8_5_2","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.1347"},{"key":"e_1_2_8_6_2","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.22163"},{"key":"e_1_2_8_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmr.2004.06.010"},{"key":"e_1_2_8_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmr.2006.10.017"},{"key":"e_1_2_8_9_2","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1910060111"},{"key":"e_1_2_8_10_2","doi-asserted-by":"publisher","DOI":"10.1006\/jmre.1997.1244"},{"key":"e_1_2_8_11_2","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1910300604"},{"key":"e_1_2_8_12_2","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.698"},{"key":"e_1_2_8_13_2","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1910390607"},{"key":"e_1_2_8_14_2","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.895"},{"key":"e_1_2_8_15_2","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.1112"},{"key":"e_1_2_8_16_2","unstructured":"PelsP.Analysis and Improvement of Quantification Algorithms for Magnetic Resonance Spectroscopy. 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