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Here, we overcome this limitation by introducing a two\u2010dimensional liquid chromatography\u2010ion mobility (LC\u2010IM) deconvolution framework that unlocks the full potential of 4D lipidomics. By mathematically modeling the orthogonal LC\u2010IM separation dimensions, our method reconstructs high\u2010quality MS\/MS spectra from highly complex DIA data, effectively disentangling co\u2010eluting lipid interferences. We demonstrate the power of this approach by annotating 491 lipids from 1\u00a0\u00b5L human plasma at a 1% false discovery rate, a two\u2010fold increase in coverage compared to traditional methods. Beyond bulk analysis, we showcase its unique capability for spatial lipidomics, enabling deep profiling of laser\u2010microdissected tissue regions equivalent to only hundreds of cells, revealing metabolic reprogramming in human hepatocellular carcinoma. We further integrate this workflow with six\u2010plex isobaric labeling to achieve high\u2010throughput, high\u2010accuracy quantification in spatial tissue mapping. This transition from one\u2010 to two\u2010dimensional deconvolution establishes a robust, sensitive platform for deep lipidome characterization, bridging the gap between proteomics\u2010grade throughput and lipidomic structural complexity.<\/jats:p>","DOI":"10.1002\/anie.6117030","type":"journal-article","created":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T14:20:29Z","timestamp":1787149229000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Resolving Spectral Complexity in 4D Lipidomics Using a Two\u2010Dimensional Deconvolution Framework"],"prefix":"10.1002","volume":"65","author":[{"given":"Yao","family":"Qian","sequence":"first","affiliation":[{"name":"State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument Tsinghua University  Beijing 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