Tractography-based targeting of ventral intermediate nucleus: A comparison between conventional stereotactic targeting and diffusion tensor imaging-based targeting Article Swipe
Anupa A. Vijayakumari
,
Drew Parker
,
Andrew I. Yang
,
Ashwin G. Ramayya
,
Ronald L. Wolf
,
Darien Aunapu
,
Gordon H. Baltuch
,
Ragini Verma
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1101/2021.04.29.441001
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1101/2021.04.29.441001
Background The ventral intermediate (VIM) nucleus of the thalamus is the main target for lesioning using magnetic resonance imaging (MRI) guided focused ultrasound (MRgFUS) or deep brain stimulation (DBS). Targeting of VIM still depends on standard stereotactic coordinates, which do not account for inter-individual variability. Several approaches have been proposed including visualization of dentato-rubro-thalamic tract (DRTT) using diffusion tensor imaging tractography. Objective To compare probabilistic tracking of DRTT with deterministic tracking of DRTT and stereotactic coordinates to identify the most appropriate approach to target VIM. Methods In this retrospective study, we assessed the VIM targeted using stereotactic coordinates, deterministic and probabilistic tracking of DRTT in 19 patients with essential tremor who underwent DBS with VIM targeted using microelectrode recordings. We subsequently determined the positions of VIM derived from these three approaches and compared with that of DBS lead position using paired sample t -tests. Results The probabilistic tracking of DRTT was significantly anterior to the lead (1.45 ± 1.61 mm ( P < 0.0001)), but not in the medial/lateral position (−0.29±2.42 mm ( P =0.50)). Deterministic tracking of DRTT was significantly lateral (2.16 ± 1.94 mm ( P < 0.0001)) and anterior to the lead (1.66 ± 2.1 mm ( P < 0.0001)). The stereotactic coordinates were significantly lateral (2.41 ± 1.41 mm ( P < 0.0001)) and anterior (1.23 ± 0.89 mm ( P < 0.0001)) to the lead. Conclusion Probabilistic tracking of DRTT was found to be superior in targeting VIM compared to deterministic tracking and stereotactic coordinates.
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2021.04.29.441001
- https://www.biorxiv.org/content/biorxiv/early/2021/04/30/2021.04.29.441001.full.pdf
- OA Status
- green
- References
- 42
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3159601904
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3159601904Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/2021.04.29.441001Digital Object Identifier
- Title
-
Tractography-based targeting of ventral intermediate nucleus: A comparison between conventional stereotactic targeting and diffusion tensor imaging-based targetingWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-04-30Full publication date if available
- Authors
-
Anupa A. Vijayakumari, Drew Parker, Andrew I. Yang, Ashwin G. Ramayya, Ronald L. Wolf, Darien Aunapu, Gordon H. Baltuch, Ragini VermaList of authors in order
- Landing page
-
https://doi.org/10.1101/2021.04.29.441001Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2021/04/30/2021.04.29.441001.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.biorxiv.org/content/biorxiv/early/2021/04/30/2021.04.29.441001.full.pdfDirect OA link when available
- Concepts
-
Diffusion MRI, Magnetic resonance imaging, Thalamus, Tractography, Deep brain stimulation, Probabilistic logic, Medicine, Stereotactic surgery, Neuroscience, Nuclear medicine, Computer science, Artificial intelligence, Psychology, Radiology, Pathology, Parkinson's disease, DiseaseTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
42Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3159601904 |
|---|---|
| doi | https://doi.org/10.1101/2021.04.29.441001 |
| ids.doi | https://doi.org/10.1101/2021.04.29.441001 |
| ids.mag | 3159601904 |
| ids.openalex | https://openalex.org/W3159601904 |
| fwci | 0.0 |
| type | preprint |
| title | Tractography-based targeting of ventral intermediate nucleus: A comparison between conventional stereotactic targeting and diffusion tensor imaging-based targeting |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10919 |
| topics[0].field.id | https://openalex.org/fields/27 |
| topics[0].field.display_name | Medicine |
| topics[0].score | 1.0 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2728 |
| topics[0].subfield.display_name | Neurology |
| topics[0].display_name | Neurological disorders and treatments |
| topics[1].id | https://openalex.org/T11304 |
| topics[1].field.id | https://openalex.org/fields/27 |
| topics[1].field.display_name | Medicine |
| topics[1].score | 1.0 |
| topics[1].domain.id | https://openalex.org/domains/4 |
| topics[1].domain.display_name | Health Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2741 |
| topics[1].subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| topics[1].display_name | Advanced Neuroimaging Techniques and Applications |
| topics[2].id | https://openalex.org/T12552 |
| topics[2].field.id | https://openalex.org/fields/27 |
| topics[2].field.display_name | Medicine |
| topics[2].score | 0.9987000226974487 |
| topics[2].domain.id | https://openalex.org/domains/4 |
| topics[2].domain.display_name | Health Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2735 |
| topics[2].subfield.display_name | Pediatrics, Perinatology and Child Health |
| topics[2].display_name | Fetal and Pediatric Neurological Disorders |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C149550507 |
| concepts[0].level | 3 |
| concepts[0].score | 0.700531005859375 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q899360 |
| concepts[0].display_name | Diffusion MRI |
| concepts[1].id | https://openalex.org/C143409427 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6178686618804932 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q161238 |
| concepts[1].display_name | Magnetic resonance imaging |
| concepts[2].id | https://openalex.org/C2779246727 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5307669043540955 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q184215 |
| concepts[2].display_name | Thalamus |
| concepts[3].id | https://openalex.org/C84787856 |
| concepts[3].level | 4 |
| concepts[3].score | 0.5286759734153748 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q3076659 |
| concepts[3].display_name | Tractography |
| concepts[4].id | https://openalex.org/C2778542668 |
| concepts[4].level | 4 |
| concepts[4].score | 0.5083271861076355 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q618076 |
| concepts[4].display_name | Deep brain stimulation |
| concepts[5].id | https://openalex.org/C49937458 |
| concepts[5].level | 2 |
| concepts[5].score | 0.48591795563697815 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q2599292 |
| concepts[5].display_name | Probabilistic logic |
| concepts[6].id | https://openalex.org/C71924100 |
| concepts[6].level | 0 |
| concepts[6].score | 0.4158300757408142 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[6].display_name | Medicine |
| concepts[7].id | https://openalex.org/C2779634917 |
| concepts[7].level | 2 |
| concepts[7].score | 0.4124712347984314 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q1931968 |
| concepts[7].display_name | Stereotactic surgery |
| concepts[8].id | https://openalex.org/C169760540 |
| concepts[8].level | 1 |
| concepts[8].score | 0.40747615694999695 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q207011 |
| concepts[8].display_name | Neuroscience |
| concepts[9].id | https://openalex.org/C2989005 |
| concepts[9].level | 1 |
| concepts[9].score | 0.3629233241081238 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q214963 |
| concepts[9].display_name | Nuclear medicine |
| concepts[10].id | https://openalex.org/C41008148 |
| concepts[10].level | 0 |
| concepts[10].score | 0.2533600330352783 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[10].display_name | Computer science |
| concepts[11].id | https://openalex.org/C154945302 |
| concepts[11].level | 1 |
| concepts[11].score | 0.20931211113929749 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[11].display_name | Artificial intelligence |
| concepts[12].id | https://openalex.org/C15744967 |
| concepts[12].level | 0 |
| concepts[12].score | 0.18671131134033203 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q9418 |
| concepts[12].display_name | Psychology |
| concepts[13].id | https://openalex.org/C126838900 |
| concepts[13].level | 1 |
| concepts[13].score | 0.1830289363861084 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q77604 |
| concepts[13].display_name | Radiology |
| concepts[14].id | https://openalex.org/C142724271 |
| concepts[14].level | 1 |
| concepts[14].score | 0.16368693113327026 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q7208 |
| concepts[14].display_name | Pathology |
| concepts[15].id | https://openalex.org/C2779734285 |
| concepts[15].level | 3 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q11085 |
| concepts[15].display_name | Parkinson's disease |
| concepts[16].id | https://openalex.org/C2779134260 |
| concepts[16].level | 2 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q12136 |
| concepts[16].display_name | Disease |
| keywords[0].id | https://openalex.org/keywords/diffusion-mri |
| keywords[0].score | 0.700531005859375 |
| keywords[0].display_name | Diffusion MRI |
| keywords[1].id | https://openalex.org/keywords/magnetic-resonance-imaging |
| keywords[1].score | 0.6178686618804932 |
| keywords[1].display_name | Magnetic resonance imaging |
| keywords[2].id | https://openalex.org/keywords/thalamus |
| keywords[2].score | 0.5307669043540955 |
| keywords[2].display_name | Thalamus |
| keywords[3].id | https://openalex.org/keywords/tractography |
| keywords[3].score | 0.5286759734153748 |
| keywords[3].display_name | Tractography |
| keywords[4].id | https://openalex.org/keywords/deep-brain-stimulation |
| keywords[4].score | 0.5083271861076355 |
| keywords[4].display_name | Deep brain stimulation |
| keywords[5].id | https://openalex.org/keywords/probabilistic-logic |
| keywords[5].score | 0.48591795563697815 |
| keywords[5].display_name | Probabilistic logic |
| keywords[6].id | https://openalex.org/keywords/medicine |
| keywords[6].score | 0.4158300757408142 |
| keywords[6].display_name | Medicine |
| keywords[7].id | https://openalex.org/keywords/stereotactic-surgery |
| keywords[7].score | 0.4124712347984314 |
| keywords[7].display_name | Stereotactic surgery |
| keywords[8].id | https://openalex.org/keywords/neuroscience |
| keywords[8].score | 0.40747615694999695 |
| keywords[8].display_name | Neuroscience |
| keywords[9].id | https://openalex.org/keywords/nuclear-medicine |
| keywords[9].score | 0.3629233241081238 |
| keywords[9].display_name | Nuclear medicine |
| keywords[10].id | https://openalex.org/keywords/computer-science |
| keywords[10].score | 0.2533600330352783 |
| keywords[10].display_name | Computer science |
| keywords[11].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[11].score | 0.20931211113929749 |
| keywords[11].display_name | Artificial intelligence |
| keywords[12].id | https://openalex.org/keywords/psychology |
| keywords[12].score | 0.18671131134033203 |
| keywords[12].display_name | Psychology |
| keywords[13].id | https://openalex.org/keywords/radiology |
| keywords[13].score | 0.1830289363861084 |
| keywords[13].display_name | Radiology |
| keywords[14].id | https://openalex.org/keywords/pathology |
| keywords[14].score | 0.16368693113327026 |
| keywords[14].display_name | Pathology |
| language | en |
| locations[0].id | doi:10.1101/2021.04.29.441001 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306402567 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| locations[0].source.host_organization | https://openalex.org/I2750212522 |
| locations[0].source.host_organization_name | Cold Spring Harbor Laboratory |
| locations[0].source.host_organization_lineage | https://openalex.org/I2750212522 |
| locations[0].license | cc-by-nc-nd |
| locations[0].pdf_url | https://www.biorxiv.org/content/biorxiv/early/2021/04/30/2021.04.29.441001.full.pdf |
| locations[0].version | acceptedVersion |
| locations[0].raw_type | posted-content |
| locations[0].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[0].is_accepted | True |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.1101/2021.04.29.441001 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5054241852 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-7041-9454 |
| authorships[0].author.display_name | Anupa A. Vijayakumari |
| authorships[0].countries | US |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I79576946 |
| authorships[0].affiliations[0].raw_affiliation_string | DiCIPHR (Diffusion and Connectomics in Precision Healthcare Research) Lab, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[0].institutions[0].id | https://openalex.org/I79576946 |
| authorships[0].institutions[0].ror | https://ror.org/00b30xv10 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I79576946 |
| authorships[0].institutions[0].country_code | US |
| authorships[0].institutions[0].display_name | University of Pennsylvania |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Anupa A. Vijayakumari |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | DiCIPHR (Diffusion and Connectomics in Precision Healthcare Research) Lab, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[1].author.id | https://openalex.org/A5112588875 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Drew Parker |
| authorships[1].countries | US |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I79576946 |
| authorships[1].affiliations[0].raw_affiliation_string | DiCIPHR (Diffusion and Connectomics in Precision Healthcare Research) Lab, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[1].institutions[0].id | https://openalex.org/I79576946 |
| authorships[1].institutions[0].ror | https://ror.org/00b30xv10 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I79576946 |
| authorships[1].institutions[0].country_code | US |
| authorships[1].institutions[0].display_name | University of Pennsylvania |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Drew Parker |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | DiCIPHR (Diffusion and Connectomics in Precision Healthcare Research) Lab, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[2].author.id | https://openalex.org/A5111853702 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Andrew I. Yang |
| authorships[2].countries | US |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I79576946 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[2].institutions[0].id | https://openalex.org/I79576946 |
| authorships[2].institutions[0].ror | https://ror.org/00b30xv10 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I79576946 |
| authorships[2].institutions[0].country_code | US |
| authorships[2].institutions[0].display_name | University of Pennsylvania |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Andrew I Yang |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[3].author.id | https://openalex.org/A5087648695 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-4444-0433 |
| authorships[3].author.display_name | Ashwin G. Ramayya |
| authorships[3].countries | US |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I79576946 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[3].institutions[0].id | https://openalex.org/I79576946 |
| authorships[3].institutions[0].ror | https://ror.org/00b30xv10 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I79576946 |
| authorships[3].institutions[0].country_code | US |
| authorships[3].institutions[0].display_name | University of Pennsylvania |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Ashwin G. Ramayya |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[4].author.id | https://openalex.org/A5015402223 |
| authorships[4].author.orcid | https://orcid.org/0000-0003-1887-3697 |
| authorships[4].author.display_name | Ronald L. Wolf |
| authorships[4].countries | US |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I79576946 |
| authorships[4].affiliations[0].raw_affiliation_string | Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[4].institutions[0].id | https://openalex.org/I79576946 |
| authorships[4].institutions[0].ror | https://ror.org/00b30xv10 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I79576946 |
| authorships[4].institutions[0].country_code | US |
| authorships[4].institutions[0].display_name | University of Pennsylvania |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Ronald L. Wolf |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[5].author.id | https://openalex.org/A5083866973 |
| authorships[5].author.orcid | |
| authorships[5].author.display_name | Darien Aunapu |
| authorships[5].countries | US |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I79576946 |
| authorships[5].affiliations[0].raw_affiliation_string | DiCIPHR (Diffusion and Connectomics in Precision Healthcare Research) Lab, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[5].institutions[0].id | https://openalex.org/I79576946 |
| authorships[5].institutions[0].ror | https://ror.org/00b30xv10 |
| authorships[5].institutions[0].type | education |
| authorships[5].institutions[0].lineage | https://openalex.org/I79576946 |
| authorships[5].institutions[0].country_code | US |
| authorships[5].institutions[0].display_name | University of Pennsylvania |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Darien Aunapu |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | DiCIPHR (Diffusion and Connectomics in Precision Healthcare Research) Lab, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[6].author.id | https://openalex.org/A5019389906 |
| authorships[6].author.orcid | |
| authorships[6].author.display_name | Gordon H. Baltuch |
| authorships[6].countries | US |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I79576946 |
| authorships[6].affiliations[0].raw_affiliation_string | Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[6].institutions[0].id | https://openalex.org/I79576946 |
| authorships[6].institutions[0].ror | https://ror.org/00b30xv10 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I79576946 |
| authorships[6].institutions[0].country_code | US |
| authorships[6].institutions[0].display_name | University of Pennsylvania |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Gordon H. Baltuch |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[7].author.id | https://openalex.org/A5083518354 |
| authorships[7].author.orcid | https://orcid.org/0000-0002-7479-1007 |
| authorships[7].author.display_name | Ragini Verma |
| authorships[7].countries | US |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I79576946 |
| authorships[7].affiliations[0].raw_affiliation_string | Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[7].affiliations[1].institution_ids | https://openalex.org/I79576946 |
| authorships[7].affiliations[1].raw_affiliation_string | Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[7].affiliations[2].institution_ids | https://openalex.org/I79576946 |
| authorships[7].affiliations[2].raw_affiliation_string | DiCIPHR (Diffusion and Connectomics in Precision Healthcare Research) Lab, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| authorships[7].institutions[0].id | https://openalex.org/I79576946 |
| authorships[7].institutions[0].ror | https://ror.org/00b30xv10 |
| authorships[7].institutions[0].type | education |
| authorships[7].institutions[0].lineage | https://openalex.org/I79576946 |
| authorships[7].institutions[0].country_code | US |
| authorships[7].institutions[0].display_name | University of Pennsylvania |
| authorships[7].author_position | last |
| authorships[7].raw_author_name | Ragini Verma |
| authorships[7].is_corresponding | True |
| authorships[7].raw_affiliation_strings | Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA, DiCIPHR (Diffusion and Connectomics in Precision Healthcare Research) Lab, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.biorxiv.org/content/biorxiv/early/2021/04/30/2021.04.29.441001.full.pdf |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Tractography-based targeting of ventral intermediate nucleus: A comparison between conventional stereotactic targeting and diffusion tensor imaging-based targeting |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10919 |
| primary_topic.field.id | https://openalex.org/fields/27 |
| primary_topic.field.display_name | Medicine |
| primary_topic.score | 1.0 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2728 |
| primary_topic.subfield.display_name | Neurology |
| primary_topic.display_name | Neurological disorders and treatments |
| related_works | https://openalex.org/W1974052986, https://openalex.org/W4400359433, https://openalex.org/W2488984732, https://openalex.org/W2528560501, https://openalex.org/W363907200, https://openalex.org/W2526824703, https://openalex.org/W177321449, https://openalex.org/W4242489200, https://openalex.org/W2000834694, https://openalex.org/W2124285946 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1101/2021.04.29.441001 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306402567 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| best_oa_location.source.host_organization | https://openalex.org/I2750212522 |
| best_oa_location.source.host_organization_name | Cold Spring Harbor Laboratory |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I2750212522 |
| best_oa_location.license | cc-by-nc-nd |
| best_oa_location.pdf_url | https://www.biorxiv.org/content/biorxiv/early/2021/04/30/2021.04.29.441001.full.pdf |
| best_oa_location.version | acceptedVersion |
| best_oa_location.raw_type | posted-content |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.1101/2021.04.29.441001 |
| primary_location.id | doi:10.1101/2021.04.29.441001 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306402567 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| primary_location.source.host_organization | https://openalex.org/I2750212522 |
| primary_location.source.host_organization_name | Cold Spring Harbor Laboratory |
| primary_location.source.host_organization_lineage | https://openalex.org/I2750212522 |
| primary_location.license | cc-by-nc-nd |
| primary_location.pdf_url | https://www.biorxiv.org/content/biorxiv/early/2021/04/30/2021.04.29.441001.full.pdf |
| primary_location.version | acceptedVersion |
| primary_location.raw_type | posted-content |
| primary_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| primary_location.is_accepted | True |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.1101/2021.04.29.441001 |
| publication_date | 2021-04-30 |
| publication_year | 2021 |
| referenced_works | https://openalex.org/W2062865989, https://openalex.org/W1960657214, https://openalex.org/W2038901759, https://openalex.org/W2740917306, https://openalex.org/W2999039138, https://openalex.org/W2968798979, https://openalex.org/W3003567086, https://openalex.org/W1972545529, https://openalex.org/W2160034651, https://openalex.org/W2766790529, https://openalex.org/W2005218321, https://openalex.org/W1975044929, https://openalex.org/W2039861760, https://openalex.org/W2078088488, https://openalex.org/W1866054690, https://openalex.org/W1935352187, https://openalex.org/W2079329115, https://openalex.org/W1963781350, https://openalex.org/W2789641575, https://openalex.org/W2790291981, https://openalex.org/W2481958177, https://openalex.org/W2900565808, https://openalex.org/W2035801035, https://openalex.org/W2025162361, https://openalex.org/W2397657821, https://openalex.org/W3009092965, https://openalex.org/W2593773276, https://openalex.org/W2790731589, https://openalex.org/W2604621060, https://openalex.org/W2016987995, https://openalex.org/W2069494733, https://openalex.org/W2127309075, https://openalex.org/W2006096283, https://openalex.org/W2196038229, https://openalex.org/W2149092213, https://openalex.org/W2151130155, https://openalex.org/W2127890285, https://openalex.org/W2019132393, https://openalex.org/W2139484893, https://openalex.org/W3025243928, https://openalex.org/W2972180470, https://openalex.org/W2019307288 |
| referenced_works_count | 42 |
| abstract_inverted_index.( | 161, 173, 187, 200, 214, 224 |
| abstract_inverted_index.P | 162, 174, 188, 201, 215, 225 |
| abstract_inverted_index.t | 143 |
| abstract_inverted_index.19 | 106 |
| abstract_inverted_index.In | 87 |
| abstract_inverted_index.To | 63 |
| abstract_inverted_index.We | 120 |
| abstract_inverted_index.be | 239 |
| abstract_inverted_index.do | 40 |
| abstract_inverted_index.in | 105, 167, 241 |
| abstract_inverted_index.is | 10 |
| abstract_inverted_index.mm | 160, 172, 186, 199, 213, 223 |
| abstract_inverted_index.of | 7, 31, 53, 67, 72, 103, 125, 136, 149, 178, 234 |
| abstract_inverted_index.on | 35 |
| abstract_inverted_index.or | 25 |
| abstract_inverted_index.to | 77, 83, 154, 193, 228, 238, 245 |
| abstract_inverted_index.we | 91 |
| abstract_inverted_index.± | 158, 184, 197, 211, 221 |
| abstract_inverted_index.2.1 | 198 |
| abstract_inverted_index.DBS | 113, 137 |
| abstract_inverted_index.The | 2, 146, 204 |
| abstract_inverted_index.VIM | 32, 94, 115, 126, 243 |
| abstract_inverted_index.and | 74, 100, 132, 191, 218, 248 |
| abstract_inverted_index.but | 165 |
| abstract_inverted_index.for | 14, 43 |
| abstract_inverted_index.not | 41, 166 |
| abstract_inverted_index.the | 8, 11, 79, 93, 123, 155, 168, 194, 229 |
| abstract_inverted_index.was | 151, 180, 236 |
| abstract_inverted_index.who | 111 |
| abstract_inverted_index.< | 163, 189, 202, 216, 226 |
| abstract_inverted_index.0.89 | 222 |
| abstract_inverted_index.1.41 | 212 |
| abstract_inverted_index.1.61 | 159 |
| abstract_inverted_index.1.94 | 185 |
| abstract_inverted_index.DRTT | 68, 73, 104, 150, 179, 235 |
| abstract_inverted_index.VIM. | 85 |
| abstract_inverted_index.been | 49 |
| abstract_inverted_index.deep | 26 |
| abstract_inverted_index.from | 128 |
| abstract_inverted_index.have | 48 |
| abstract_inverted_index.lead | 138, 156, 195 |
| abstract_inverted_index.main | 12 |
| abstract_inverted_index.most | 80 |
| abstract_inverted_index.that | 135 |
| abstract_inverted_index.this | 88 |
| abstract_inverted_index.were | 207 |
| abstract_inverted_index.with | 69, 108, 114, 134 |
| abstract_inverted_index.(1.23 | 220 |
| abstract_inverted_index.(1.45 | 157 |
| abstract_inverted_index.(1.66 | 196 |
| abstract_inverted_index.(2.16 | 183 |
| abstract_inverted_index.(2.41 | 210 |
| abstract_inverted_index.(MRI) | 20 |
| abstract_inverted_index.(VIM) | 5 |
| abstract_inverted_index.brain | 27 |
| abstract_inverted_index.found | 237 |
| abstract_inverted_index.lead. | 230 |
| abstract_inverted_index.still | 33 |
| abstract_inverted_index.these | 129 |
| abstract_inverted_index.three | 130 |
| abstract_inverted_index.tract | 55 |
| abstract_inverted_index.using | 16, 57, 96, 117, 140 |
| abstract_inverted_index.which | 39 |
| abstract_inverted_index.(DBS). | 29 |
| abstract_inverted_index.(DRTT) | 56 |
| abstract_inverted_index.guided | 21 |
| abstract_inverted_index.paired | 141 |
| abstract_inverted_index.sample | 142 |
| abstract_inverted_index.study, | 90 |
| abstract_inverted_index.target | 13, 84 |
| abstract_inverted_index.tensor | 59 |
| abstract_inverted_index.tremor | 110 |
| abstract_inverted_index.-tests. | 144 |
| abstract_inverted_index.Methods | 86 |
| abstract_inverted_index.Results | 145 |
| abstract_inverted_index.Several | 46 |
| abstract_inverted_index.account | 42 |
| abstract_inverted_index.compare | 64 |
| abstract_inverted_index.depends | 34 |
| abstract_inverted_index.derived | 127 |
| abstract_inverted_index.focused | 22 |
| abstract_inverted_index.imaging | 19, 60 |
| abstract_inverted_index.lateral | 182, 209 |
| abstract_inverted_index.nucleus | 6 |
| abstract_inverted_index.ventral | 3 |
| abstract_inverted_index.(MRgFUS) | 24 |
| abstract_inverted_index.0.0001)) | 190, 217, 227 |
| abstract_inverted_index.=0.50)). | 175 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.anterior | 153, 192, 219 |
| abstract_inverted_index.approach | 82 |
| abstract_inverted_index.assessed | 92 |
| abstract_inverted_index.compared | 133, 244 |
| abstract_inverted_index.identify | 78 |
| abstract_inverted_index.magnetic | 17 |
| abstract_inverted_index.patients | 107 |
| abstract_inverted_index.position | 139, 170 |
| abstract_inverted_index.proposed | 50 |
| abstract_inverted_index.standard | 36 |
| abstract_inverted_index.superior | 240 |
| abstract_inverted_index.targeted | 95, 116 |
| abstract_inverted_index.thalamus | 9 |
| abstract_inverted_index.tracking | 66, 71, 102, 148, 177, 233, 247 |
| abstract_inverted_index.0.0001)), | 164 |
| abstract_inverted_index.0.0001)). | 203 |
| abstract_inverted_index.Objective | 62 |
| abstract_inverted_index.Targeting | 30 |
| abstract_inverted_index.diffusion | 58 |
| abstract_inverted_index.essential | 109 |
| abstract_inverted_index.including | 51 |
| abstract_inverted_index.lesioning | 15 |
| abstract_inverted_index.positions | 124 |
| abstract_inverted_index.resonance | 18 |
| abstract_inverted_index.targeting | 242 |
| abstract_inverted_index.underwent | 112 |
| abstract_inverted_index.Background | 1 |
| abstract_inverted_index.Conclusion | 231 |
| abstract_inverted_index.approaches | 47, 131 |
| abstract_inverted_index.determined | 122 |
| abstract_inverted_index.ultrasound | 23 |
| abstract_inverted_index.appropriate | 81 |
| abstract_inverted_index.coordinates | 76, 206 |
| abstract_inverted_index.recordings. | 119 |
| abstract_inverted_index.stimulation | 28 |
| abstract_inverted_index.coordinates, | 38, 98 |
| abstract_inverted_index.coordinates. | 250 |
| abstract_inverted_index.intermediate | 4 |
| abstract_inverted_index.stereotactic | 37, 75, 97, 205, 249 |
| abstract_inverted_index.subsequently | 121 |
| abstract_inverted_index.variability. | 45 |
| abstract_inverted_index.Deterministic | 176 |
| abstract_inverted_index.Probabilistic | 232 |
| abstract_inverted_index.deterministic | 70, 99, 246 |
| abstract_inverted_index.probabilistic | 65, 101, 147 |
| abstract_inverted_index.retrospective | 89 |
| abstract_inverted_index.significantly | 152, 181, 208 |
| abstract_inverted_index.tractography. | 61 |
| abstract_inverted_index.visualization | 52 |
| abstract_inverted_index.(−0.29±2.42 | 171 |
| abstract_inverted_index.medial/lateral | 169 |
| abstract_inverted_index.microelectrode | 118 |
| abstract_inverted_index.inter-individual | 44 |
| abstract_inverted_index.dentato-rubro-thalamic | 54 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5083518354 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 8 |
| corresponding_institution_ids | https://openalex.org/I79576946 |
| citation_normalized_percentile.value | 0.0659587 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |