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Internal cohort: 311 epilepsy patients split into training\/validation\/internal test sets (\n n<\/jats:italic>\n \u2009=\u2009249\/31\/31; age 18.79\u2009\u00b1\u200916.33\/22.20\u2009\u00b1\u200911.21\/21.65\u2009\u00b1\u200917.62\u2009years; male\/female 145\/104, 13\/18, 22\/9). External cohort: 115 temporal lobe epilepsy patients (age 25.36\u2009\u00b1\u200910.95\u2009years; male\/female 68\/47) and 55 healthy controls (age 27.62\u2009\u00b1\u20095.82\u2009years; male\/female 24\/31); 92 had surgery with 1\u2010year outcome.\n <\/jats:p>\n <\/jats:sec>\n \n Field Strength<\/jats:title>\n Hybrid PET\/MR at 3.0\u2009T; gradient\u2010echo T1WI, echo\u2010planar imaging and resting\u2010state BOLD gradient\u2010echo EPI.<\/jats:p>\n <\/jats:sec>\n \n Assessment<\/jats:title>\n Performance was assessed using SSIM, PSNR, MSE, NRMSE, SUVR correlation, and Bland\u2013Altman analysis. Three blinded readers performed visual quality grading and detection of temporal lobe hypometabolism. Hippocampal radiomics was used for classification of hippocampal sclerosis and Engel outcome.<\/jats:p>\n <\/jats:sec>\n \n Statistical Tests<\/jats:title>\n \n t<\/jats:italic>\n \u2010tests, chi\u2010square tests, Pearson correlation, Kolmogorov\u2013Smirnov tests, DeLong tests, and false discovery rate correction.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Excellent\/Good visual ratings occurred in 82.8% (166\/201), with Fleiss'\n \u03ba<\/jats:italic>\n \u2009=\u20090.42. SSIM was 0.98\u2009\u00b1\u20090.01 (internal) and 0.97\u2009\u00b1\u20090.01 (external); PSNR was 66.66\u2009\u00b1\u20091.25 and 64.16\u2009\u00b1\u20091.83, respectively. SUVR correlation with ground\u2010truth PET was\n r<\/jats:italic>\n \u2009=\u20090.94 (internal) and\n r<\/jats:italic>\n \u2009=\u20090.89 (external); Bland\u2013Altman bias was \u22120.02 (95% limits of agreement: \u22120.22 to 0.18) internally and \u22120.00002 (95% limits: \u22120.35 to 0.35) externally. Detection accuracy for temporal hypometabolism was 90.3% (internal;\n \u03ba<\/jats:italic>\n \u2009=\u20090.735) and 87.1% (external;\n \u03ba<\/jats:italic>\n \u2009=\u20090.758). Radiomics AUCs using synthetic PET were 0.72 (95% CI: 0.62\u20130.83) for hippocampal sclerosis versus healthy controls and 0.77 (95% CI: 0.67\u20130.87) for Engel IA versus IB\u2013IV; DeLong tests versus ground\u2010truth PET were non\u2010significant (\n p<\/jats:italic>\n \u2009=\u20090.56 and\n p<\/jats:italic>\n \u2009=\u20090.48).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n Multisequence MRI\u2010based synthetic PET showed high agreement with ground\u2010truth PET across image\u2010quality and quantitative SUVR metrics, providing a PET\u2010like metabolic surrogate when FDG\u2010PET is unavailable or impractical.<\/jats:p>\n <\/jats:sec>\n \n Level of Evidence<\/jats:title>\n Evidence Level 3.<\/jats:p>\n <\/jats:sec>\n \n Stages of Technical Efficacy<\/jats:title>\n Stage 3.<\/jats:p>\n 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