Brain connectivity atlas for personalized functional neurosurgery targeting and brain stimulation programming

1. A system for identifying a patient-specific neurosurgery target location, the system comprising:

a processor programmed to:

receive brain imaging data for a patient that includes tracts and networks in the patient brain;

access a quantitative connectome atlas comprising population-based, disease-specific structural and functional connectivity maps comprising a pattern of tracts and networks associated with an optimal target area (OTA) identified from a population of patients; and

define the patient-specific neurosurgery target location based on a comparison between a pattern of the tracts and networks from the brain imaging data for the patient and the pattern of tracts and networks associated with the OTA identified from the population of patients in the quantitative connectome atlas.

2. The system of claim 1 , wherein in defining the patient-specific neurosurgery target location, the processor is programmed to match the pattern of tracts and networks in the patient brain imaging data to the pattern of tracts and networks associated with the OTA identified from the population of patients in the quantitative connectome atlas, and to generate a probabilistic map.

3. The system of claim 2 , wherein the processer is further programmed to select the best match from the probabilistic map to identify the patient-specific neurosurgery target location.

4. The system of claim 3 , wherein the processor is further programmed to determine an optimal set of deep brain stimulation (DBS) parameters to be used for patient treatment at the patient-specific neurosurgery target location.

5. The system of claim 4 , wherein in determining the optimal set of DBS parameters, the processor is programmed to identify an optimal combination of signal voltage, signal frequency, signal pulse-width, and an activated electrode contact.

6. The system of claim 1 , wherein the quantitative connectome atlas comprises data on a population of patients having previously undergone functional neurosurgical treatment and data on a healthy control population, the data comprising patient brain imaging data, parameters of a stimulation used during the functional neurosurgical treatment, and clinical outcomes for the population of patients, for each of a plurality of diseases.

7. The system of claim 6 , wherein the functional neurosurgical treatment comprises a lesioning procedure or stimulation procedure, and wherein the quantitative connectome atlas further comprises data on a location of an ablative treatment or a location of one or more electrodes implanted in the patient for stimulation.

8. The system of claim 7 wherein, the processor is further programmed to generate the quantitative connectome atlas by:

identifying, for each patient in the population, a treatment area derived from the brain imaging data, the treatment area comprising a lesion location or electrode location and corresponding volume of tissue activated (VTA);

weighting the treatment area for each patient based on one or more of symptom improvement and side-effect minimization resulting from the functional neurosurgical treatment; and

averaging the weighted treatment area across the population of patients to identify the OTA; and

determining structural and functional connectivity maps for the OTA using data from the population of patients and the healthy control population.

9. The system of claim 8 , wherein generation of quantitative connectome atlas further comprises averaging structural and functional connectivity maps obtained for the treatment area of each patient in the population.

10. The system of claim 1 , wherein the brain imaging data comprises magnetic resonance imaging (MRI) data.

11. The system of claim 1 , wherein the neurosurgery target location in the patient is disease-specific and functional neurosurgery technique-specific, with the pattern of tracts and networks associated with an OTA differing between diseases and functional neurosurgery techniques.

12. A computer-based method for deriving a disease-specific, population-based quantitative connectome atlas, the method comprising:

accessing a database comprising data on a population of patients having previously undergone functional neurosurgical treatment and on a healthy control population of patients, the data comprising structural and/or functional brain imaging data, and clinical outcomes for the population of patients, for each of a plurality of diseases;

identifying a treatment area for each patient in the population, the treatment area comprising a lesion location when the functional neurosurgical treatment is an ablative procedure or an electrode location, and corresponding volume of tissue activated (VTA) when the functional neurosurgical treatment is deep brain stimulation (DBS);

weighting the treatment area for each patient based on symptom improvement resulting from the functional neurosurgical treatment; and

averaging the weighted treatment areas across the population of patients to identify an optimal target area (OTA) associated with a maximal clinical improvement in each of a number of disease cohorts in the population of patients.

13. The computer-based method of claim 12 further comprising performing a step of localizing the treatment area.

14. The computer-based method of claim 12 further comprising determining structural and functional connectivity maps for the OTAs using disease-specific functional brain imaging data or data from the healthy control population of patients, the connectivity maps establishing a pattern of optimal tracts and networks associated with the OTAs.

15. The computer-based method of claim 12 wherein, in identifying the OTA for a disease cohort, the method further comprises:

averaging non-weighted treatment areas across the population of patients; and

identifying the OTA for the disease cohort via one of normalizing a product of the weighted and non-weighted treatment areas, using average maps masked by frequency, or using maps made of voxel-wise statistics.

16. A computer-based method for identifying a patient-specific neurosurgery target location, the method comprising:

accessing a population-based, disease-specific brain connectivity atlas derived from a population of patients having previously undergone functional neurosurgical treatment, with data collected on each of the patients comprising brain imaging data and clinical outcomes for the patient, for each of a plurality of diseases; and

identifying from the brain connectivity atlas, one or more optimal neurosurgery target locations associated with optimal treatment of the patient; and

further comprising:

receiving brain imaging data for the patient comprising tracts and networks in the patient brain;

comparing the tracts and networks in the patient brain to an optimal target area (OTA) derived from the brain connectivity atlas and to an optimal pattern of tracts and networks associated with the OTA; and

identifying a patient OTA that best matches with the OTA from the brain connectivity atlas to identify the one or more optimal neurosurgery target locations.

17. The computer-based method of claim 16 , wherein the brain imaging data for the patient comprises magnetic resonance imaging (MRI) data.

18. A computer-based method for identifying a patient-specific neurosurgery target location, the method comprising:

accessing a population-based, disease-specific brain connectivity atlas derived from a population of patients having previously undergone functional neurosurgical treatment, with data collected on each of the patients comprising brain imaging data and clinical outcomes for the patient, for each of a plurality of diseases; and

identifying from the brain connectivity atlas, one or more optimal neurosurgery target locations associated with optimal treatment of the patient; and

further comprising:

identifying an optimal target area (OTA) from the brain connectivity atlas and an optimal pattern of tracts and networks associated therewith; and

deforming the OTA and associated optimal pattern of tracts and networks to the brain of the patient to identify the one or more optimal neurosurgery target locations.

19. The computer-based method of claim 18 further comprising determining an optimal set of DBS parameters to be used for patient treatment at the neurosurgery target location that achieves the optimal treatment of the patient.

20. A computer-based method for identifying a patient-specific neurosurgery target location, the method comprising:

accessing a population-based, disease-specific brain connectivity atlas derived from a population of patients having previously undergone functional neurosurgical treatment, with data collected on each of the patients comprising brain imaging data and clinical outcomes for the patient, for each of a plurality of diseases; and

identifying from the brain connectivity atlas, one or more optimal neurosurgery target locations associated with optimal treatment of the patient;

wherein the functional neurosurgery to be performed on the patient comprises deep brain stimulation (DBS) treatment, and wherein the quantitative connectome atlas comprises data on a location of one or more DBS electrodes implanted in the patient and parameters of a DBS used during the functional DBS treatment.