This dataset from the publication entitled "Dataset from "In silico assessment of collateral eddy current heating in biocompatible implants subjected to magnetic hyperthermia treatments" contains simulated data of magnetic hyperthermia treatments for three different indications: colorectal cancer, prostate cancer and head & neck cancer. Since the aim of the study is to evaluate the risk of thermal damage caused by the collateral heating of two common types of passive prostheses (hip and dental implants), eddy currents induced in these implants upon interacting with the externally applied ac field during treatment have been computed for all the evaluated regions. Two different alloys for the implants have been considered for each case as well: Ti6Al4V and CoCrMo. At the same time, besides temperature, the specific abosorption rate (SAR) have been also computed to work out the energy deposition in tissues. Calculations have been carried out using a het exchange model with and without thermoregulation. log-log SAR vs T plots have been obtained and proposed as a quick means to pre-check treatment feasibility in each patient. These graphs are thought to be included in treatment planning prior to the clinical procedure. Other parameters taken into account have been the treatment time (5 and 30 minutes), and the maximum tolerable temperature threshold (1 or 5 ºC, as indicated by the ICNIRP commission), all for three main types of tissues, namely fat, bone and muscle. Each tissue have been simulated using three different field intensities (5, 10 and 15 mT). The field frequency has been 300 kHz in all cases. The files "Dataset_description.doc" and "file_scheme.txt" contain the structure and description of the files that make up the dataset.

This work has been supported by the NoCanTher project, which has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 685795. The authors acknowledge support from the COST Association through the COST actions "RADIOMAG" (TD1402) and "MyWAVE" (CA17115). D.O. and I.R.R. acknowledge financial support from the Community of Madrid under Contract No. PEJD-2017-PRE/IND-3663, from the Spanish Ministry of Science through the Ramón y Cajal grant RYC2018-025253-I and Research Networks RED2018-102626-T, as well as the Ministry of Economy and Competitiveness through the grants MAT2017-85617-R and the "Severo Ochoa" Program for Centers of Excellence in R&D (SEV-2016-0686). We gratefully acknowledge the support of NVIDIA Corporation through the GPU Grant Program with the donation of the Quadro P6000 GPU used for this research.