Author Interviews, Neurological Disorders, Neurology, Personalized Medicine, Radiology, Surgical Research / 13.07.2018
Multimodal Imaging Can Personalize and Predict Therapeutic Needs
MedicalResearch.com Interview with:
[caption id="attachment_43125" align="alignleft" width="139"]
Dr. turria-Medina[/caption]
Yasser Iturria-Medina, PhD
Primary Investigator, Ludmer Centre for Neuroinformatics & Mental Health
Assistant Professor, Department of Neurology and Neurosurgery
Faculty of Medicine
McGill University
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: There are millions of patients following therapeutic interventions that will not benefit them. In this study, we aimed to illustrate that it is possible to identify the most beneficial intervention for each patient, in correspondence with the principles of the personalized medicine (PM). Our results show that using multimodal imaging and computational models it is possible to predict individualized therapeutic needs. The predictions are in correspondence with the individual molecular properties, which validate our findings and the used computational techniques.
The results highly also the imprecision of the traditional clinical evaluations and categories for understanding the individual therapeutic needs, evidencing the positive impact that would have to use multimodal data and data-driven techniques in the clinic, in addition to the medical doctor's criterion/evaluations.
Dr. turria-Medina[/caption]
Yasser Iturria-Medina, PhD
Primary Investigator, Ludmer Centre for Neuroinformatics & Mental Health
Assistant Professor, Department of Neurology and Neurosurgery
Faculty of Medicine
McGill University
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: There are millions of patients following therapeutic interventions that will not benefit them. In this study, we aimed to illustrate that it is possible to identify the most beneficial intervention for each patient, in correspondence with the principles of the personalized medicine (PM). Our results show that using multimodal imaging and computational models it is possible to predict individualized therapeutic needs. The predictions are in correspondence with the individual molecular properties, which validate our findings and the used computational techniques.
The results highly also the imprecision of the traditional clinical evaluations and categories for understanding the individual therapeutic needs, evidencing the positive impact that would have to use multimodal data and data-driven techniques in the clinic, in addition to the medical doctor's criterion/evaluations.
Dr. Ishida[/caption]
Dr. Julie H. Ishida MD
Department of Medicine, Division of Nephrology
University of California, San Francisco and
San Francisco Veterans Affairs Medical Center
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: Gabapentin and pregabalin are used for the management of symptoms such as neuropathic pain, itching, and restless leg syndrome in patients receiving hemodialysis. However, hemodialysis patients may be particularly vulnerable to adverse events related to these agents, which are cleared by the kidney, but there is limited data evaluating their risk in this population.
Gabapentin and pregabalin use were associated with risk for altered mental status, fall, and fracture, and in some cases, even at doses that would be considered safe for use in this population. 

















