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Radiomic Deep Brain Stimulation Prediction\u003cbr\u003e\u003csup\u003ewith Quantitative Susceptibility Mapping (RadDBS-QSM)\u003c/sup\u003e\nThis repository hosts the following articles\n\u003e_Technical Feasibility of Quantitative Susceptibility Mapping Radiomics for Predicting\nDeep Brain Stimulation Outcomes in Parkinson’s Disease_\u003cbr\u003e\n\u003e[published](https://pubmed.ncbi.nlm.nih.gov/40965145/)  in [Neurosurgery](https://journals.lww.com/neurosurgery/pages/default.aspx) \n\u003e\n\u003e_Radiomic Prediction of Parkinson’s Disease Deep Brain Stimulation Surgery Outcomes using Quantitative Susceptibility Mapping and Label Noise Compensation_\u003cbr\u003e \n\u003e[published](https://www.brainstimjrnl.com/article/S1935-861X(25)00166-4/fulltext) in [Brain Stimulation](https://www.brainstimjrnl.com/)\n\nand several [conference papers](https://alexandragroberts.com/publications/#radiomic).\n\n## Contents\nDemonstration code can be found in [`main.ipynb`](https://github.com/agr78/RadDBS-QSM/blob/main/src/jupyter/main.ipynb) \u003cbr/\u003e\nRadiomic features can be found in [`npy`](https://github.com/agr78/RadDBS-QSM/tree/main/data/npy/rp) \u003cbr/\u003e\nCustomizable extraction code is located in [`extract.py`](https://github.com/agr78/RadDBS-QSM/blob/main/src/jupyter/extract.py) \u003cbr/\u003e\n\n\n## Summary\nA radiomic model based on presurgical quantitative susceptibility maps (QSM) is used to predict patient outcomes to deep brain stimulation (DBS) surgery for the treatment of Parkinson's disease.\n\n\u003cbr/\u003e\n\n\u003cp align=\"center\"\u003e\n   \u003cimg src=\"./data/jpg/wf.jpg\"/\u003e\u003c/br\u003e\n   \u003ci\u003eModel overview.\u003c/i\u003e\n\u003c/p\u003e\n\n\u003cbr/\u003e\n\nThis project presents a framework to: \u003cbr/\u003e\n* Extract radiomic features for input into a regression model to predict post-surgical motor improvement. \u003cbr/\u003e\n* Incorporate clinical variables such as age, sex, etc.\n* Provide a novel label noise compensation technique improving outcome prediction. \u003cbr/\u003e\n\n\n## Installation\nClone the repository with\n```\ngit clone https://github.com/agr78/RadDBS-QSM.git\n```\nNavigate to the repository\n```\ncd RadDBS-QSM\n```\nRun the setup script\n```\nsource ./install.sh\n```\nWait...then open the Jupyter notebook in the `RadDBS-QSMenv` environment\n```\njupyter notebook ./src/jupyter/main.ipynb\n```\n\n## Notes\n* This tool was developed for use with [QSM](https://mriquestions.com/quantitative-susceptibility.html), but can be used with other contrasts.\n* If the QSM has not been reconstructed, [this repository](https://github.com/agr78/mSMV?tab=readme-ov-file#summary) provides code to obtain the whole brain susceptibility.\n* If manual region-of-interest masks are not available, [this repository](https://github.com/agr78/mSMV/blob/atlas/README.md) provides bash scripts to create a sample atlas and register individual cases.\n\n\n\n## Publications\nIf this code is used, please cite the following:\n\u003e [Neurosurgery Article](https://doi.org/10.1227/neu.0000000000003721): A. G. Roberts et al., \"Technical Feasibility of Quantitative Susceptibility Mapping Radiomics for Predicting Deep Brain Stimulation Outcomes in Parkinson’s Disease, 2025, DOI: 10.1227/neu.0000000000003721\n\u003e \n\n## BibTex\n\n```bibtex\n@article{Roberts_RadDBS-QSM_2025,\n  title    = \"Technical feasibility of quantitative susceptibility mapping\n              radiomics for predicting deep brain stimulation outcomes in\n              Parkinson disease\",\n  author   = \"Roberts, Alexandra G and Zhang, Jinwei and Tozlu, Ceren and\n              Romano, Dominick and Akkus, Sema and Kim, Heejong and Sabuncu,\n              Mert R and Spincemaille, Pascal and Li, Jianqi and Wang, Yi and\n              Wu, Xi and Kopell, Brian H\",\n  journal  = \"Neurosurgery\",\n  month    =  sep,\n  year     =  2025,\n  keywords = \"Deep brain stimulation; Machine learning; Parkinson disease;\n              Quantitative susceptibility mapping; Radiomics; Regression\",\n  language = \"en\"\n}\n```\n\n## Contact\nPlease direct questions to [Alexandra G. Roberts](https://github.com/agr78) at agr78@cornell.edu.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fagr78%2Fraddbs-qsm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fagr78%2Fraddbs-qsm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fagr78%2Fraddbs-qsm/lists"}