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Their numbers vary with cellular location and physiological and pathophysiological states. AI models were developed to derive granular glycogen content from electron-microscopic images of human muscle. Two UNet-type semantic segmentation models were built: \u201cLocations\u201d classified pixels as belonging to different regions in the cell; \u201cGranules\u201d identified pixels within granules. From their joint output, a pixel fraction pf was calculated for images from patients positive (MHS) or negative (MHN) to a test for malignant hyperthermia susceptibility. pf was used to derive vf, the volume fraction occupied by granules. The relationship vf (pf) was derived from a simulation of volumes (\u201cbaskets\u201d) containing virtual granules at realistic concentrations. The simulated granules had diameters matching the real ones, which were measured by adapting a utility devised for calcium sparks. Applying this relationship to the pf measured in images, vf was calculated for every region and patient, and from them a glycogen concentration. The intermyofibrillar spaces and the sarcomeric I band had the highest granular content. The measured glycogen concentration was low enough to allow for a substantial presence of non-granular glycogen. The MHS samples had an approximately threefold lower concentration (significant in a hierarchical test), consistent with earlier evidence of diminished glucose processing in MHS. The AI models and the approach to infer three-dimensional magnitudes from two-dimensional images should be adaptable to other tasks on a variety of images from patients and animal models and different disease conditions.<\/jats:p>","DOI":"10.1085\/jgp.202413595","type":"journal-article","created":{"date-parts":[[2024,7,9]],"date-time":"2024-07-09T09:12:43Z","timestamp":1720516363000},"update-policy":"https:\/\/doi.org\/10.1085\/jgp.crossmarkpolicy","source":"Crossref","is-referenced-by-count":6,"title":["Artificial intelligence approaches to the volumetric quantification of glycogen granules in EM images of human tissue"],"prefix":"10.1085","volume":"156","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0985-8997","authenticated-orcid":true,"given":"Eduardo","family":"R\u00edos","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01k9xac83","id-type":"ROR","asserted-by":"publisher"}],"name":"Rush University 1 Department of Physiology and Biophysics, , Chicago, IL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2788-3283","authenticated-orcid":true,"given":"Montserrat","family":"Sams\u00f3","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/02nkdxk79","id-type":"ROR","asserted-by":"publisher"}],"name":"Virginia Commonwealth University 2 Department of Physiology and Biophysics, , Richmond, VA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4323-4507","authenticated-orcid":true,"given":"Lourdes C.","family":"Figueroa","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01k9xac83","id-type":"ROR","asserted-by":"publisher"}],"name":"Rush University 1 Department of Physiology and Biophysics, , Chicago, IL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1120-9606","authenticated-orcid":true,"given":"Carlo","family":"Manno","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01k9xac83","id-type":"ROR","asserted-by":"publisher"}],"name":"Rush University 1 Department of Physiology and Biophysics, , Chicago, IL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7290-9326","authenticated-orcid":true,"given":"Eshwar R.","family":"Tammineni","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01k9xac83","id-type":"ROR","asserted-by":"publisher"}],"name":"Rush University 1 Department of Physiology and Biophysics, , Chicago, IL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-1190-9254","authenticated-orcid":true,"given":"Lucas","family":"Rios Giordano","sequence":"additional","affiliation":[{"name":"LRG Architects 3 , Santa Monica, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0670-1516","authenticated-orcid":true,"given":"Sheila","family":"Riazi","sequence":"additional","affiliation":[{"name":"University of Toronto 4 Department of Anesthesia and Pain Management, , Toronto, ON, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"291","published-online":{"date-parts":[[2024,7,9]]},"reference":[{"key":"2024072213460479000_bib1","doi-asserted-by":"publisher","first-page":"1126","DOI":"10.1096\/fasebj.9.12.7672505","article-title":"A new look at the biogenesis of glycogen","volume":"9","author":"Alonso","year":"1995","journal-title":"FASEB J."},{"key":"2024072213460479000_bib2","doi-asserted-by":"publisher","first-page":"777728","DOI":"10.3389\/fcomp.2022.777728","article-title":"LABKIT: Labeling and segmentation toolkit for big image data","volume":"4","author":"Arzt","year":"2022","journal-title":"Front. 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