As　a　new　molecular　imaging　technology,　Cherenkov-excited　luminescence　scanned　imaging　(CELSI)　has　merits　of　high　spatial　resolution　and　large　imaging　depth,　therefore　showing　a　potential　for　monitoring　the　physiological　changes　of　tumors　during　radiotherapy.　In　our　previous　work,　we　developed　a　tomographic　technique　for　CELSI　based　on　Tikhonov　method,　which　is　problematic　to　reconstruct　accurate　fluorescent　targets　with　position　depth　larger　than　3　cm　or　with　low　contrast.　To　overcome　this　problem,　we　develop　a　sparse　reconstruction　method　for　tomographic　CELSI　based　on　approximate　message　passing.　To　demonstrate　the　merits　of　the　proposed　algorithm,　we　compare　it　with　traditional　Tikhonov　regularization　and　three　sparse　based　reconstruction　algorithms.　Our　results　show　that　the　proposed　method　can　achieve　best　performance　in　terms　of　mean　-square　error　and　contrast　noise　ratio.