In the last decade numerous attempts were considered to co-register and integrate different imaging data. Like PET/CT the integration of PET to MR showed great interest. PET/MR scanners are recently tested on different distrectual or systemic pathologies. Unfortunately PET/MR scanners are expensive and diagnostic protocols are still under studies and investigations. Nuclear Medicine imaging highlights functional and biometabolic information but has poor anatomic details. The aim of this study is to integrate MR and PET data to produce distrectual or whole body fused images acquired from different scanners even in different days. We propose an offline method to fuse PET with MR data using an open-source software that has to be inexpensive, reproducible and capable to exchange data over the network. We also evaluate global quality, alignment quality, and diagnostic confidence of fused PET-MR images. We selected PET/CT studies performed in our Nuclear Medicine unit, MR studies provided by patients on DICOM CD media or network received. We used Osirix 5.7 open source version. We aligned CT slices with the first MR slice, pointed and marked for co-registration using MR-T1 sequence and CT as reference and fused with PET to produce a PET-MR image. A total of 100 PET/CT studies were fused with the following MR studies: 20 head, 15 thorax, 24 abdomen, 31 pelvis, 10 whole body. An interval of no more than 15 days between PET and MR was the inclusion criteria. PET/CT, MR and fused studies were evaluated by two experienced radiologist and two experienced nuclear medicine physicians. Each one filled a five point based evaluation scoring scheme based on image quality, image artifacts, segmentation errors, fusion misalignment and diagnostic confidence. Our fusion method showed best results for head, thorax and pelvic districts in terms of global quality, alignment quality and diagnostic confidence,while for the abdomen and pelvis alignement quality and global quality resulted poor due to internal organs filling variation and time shifting beetwen examinations. PET/CT images with time of flight reconstruction and real attenuation correction were combined with anatomical detailed MRI images. We used Osirix, an image processing Open Source Software dedicated to DICOM images. No additional costs, to buy and upgrade proprietary software are required for combining data. No high technology or very expensive PET/MR scanner, that requires dedicated shielded room spaces and personnel to be employed or to be trained, are needed. Our method allows to share patient PET/MR fused data with different medical staff using dedicated networks. The proposed method may be applied to every MR sequence (MR-DWI and MR-STIR, magnet enhanced sequences) to characterize soft tissue alterations and improve discrimination diseases. It can be applied not only to PET with MR but virtually to every DICOM study.