Evidence map›Paper›PMID 29868451›Full record

ArticleNeuroImage. Clinical2018

Convergence Analysis of Micro-Lesions (CAML): An approach to mapping of diffuse lesions from carotid revascularization.

Allyson C Rosen, Salil Soman, Jyoti Bhat, Angela R Laird, Jeffrey Stephens, Simon B Eickhoff, P Mickle Fox, Becky Long, David Dinishak, Mario Ortega and 4 more

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 97% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 8 institutions in 2 countries.

Allyson C RosenPalo Alto Veterans Affairs Health Care System, Palo Alto, CA 94304, United States; Department of Psychiatry, Stanford University, Stanford, CA 94305, United States. Electronic address: rosena@stanford.edu.
Salil SomanPalo Alto Veterans Affairs Health Care System, Palo Alto, CA 94304, United States; Harvard Medical School, Beth Israel Deaconess Medical Center, Department of Radiology, Boston, MA 00215, United States.
Jyoti BhatPalo Alto Veterans Affairs Health Care System, Palo Alto, CA 94304, United States; Palo Alto Veterans Institute for Research, Palo Alto, CA 94304, United States.
Angela R LairdDepartment of Physics, School of Integrated Science and Humanity, Florida International University, Miami, FL 33199, United States.
Jeffrey StephensPalo Alto Veterans Affairs Health Care System, Palo Alto, CA 94304, United States.
Simon B EickhoffInstitute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
P Mickle FoxResearch Imaging Institute, The University of Texas Health Science Center at San Antonio, TX 78229, United States.
Becky LongDepartment of Surgery, Stanford University, Stanford, CA 94305, United States; Department of Surgery, Texas Tech University Health Science Center El Paso, TX 79905, United States.
David DinishakPalo Alto University, Redwood City, CA 94063, United States.
Mario OrtegaDepartment of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States.
Barton LanePalo Alto Veterans Affairs Health Care System, Palo Alto, CA 94304, United States; Department of Radiology, Stanford University, Stanford, CA 94305, United States.
Max WintermarkPalo Alto Veterans Affairs Health Care System, Palo Alto, CA 94304, United States; Department of Radiology, Stanford University, Stanford, CA 94305, United States.
Elizabeth HitchnerPalo Alto Veterans Affairs Health Care System, Palo Alto, CA 94304, United States; Department of Vascular Surgery, Stanford University, Stanford, CA 94305, United States.
Wei ZhouPalo Alto Veterans Affairs Health Care System, Palo Alto, CA 94304, United States; Department of Vascular Surgery, Stanford University, Stanford, CA 94305, United States; Department of Surgery, Tucson, AZ 85724-5066, United States.
VA Palo Alto Health Care System · USBeth Israel Deaconess Medical Center · USFlorida International University · USHeinrich Heine University Düsseldorf · DEPalo Alto University · USTexas Tech University · USThe University of Texas Health Science Center at San Antonio · USWashington University in St. Louis · US

Funding

Meta-anaylsis in human brain mappingR01MH074457 · NIMH · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI FOX, PETER THORNTON · 2006 to 2024
$10.5M
BIOMEDICAL RESEARCH TRAINING IN DRUG ABUSET32DA007261 · NIDA · WASHINGTON UNIVERSITY · PI ARPANA AGRAWAL, Jose A Moron-Concepcion · 1991 to 2026
$8.8M
FMRI and TMS Analysis of Frontal Lobes in AgingK01AG025157 · NIA · STANFORD UNIVERSITY · PI ROSEN, ALLYSON C · 2005 to 2009
$637k
NIDA NIH HHS T32 DA007261NIH HHS K01AG025157NIMH NIH HHS R01 MH074457
6 · The paper itself

Abstract

Carotid revascularization (endarterectomy, stenting) prevents stroke; however, procedure-related embolization is common and results in small brain lesions easily identified by diffusion weighted magnetic resonance imaging (DWI). A crucial barrier to understanding the clinical significance of these lesions has been the lack of a statistical approach to identify vulnerable brain areas. The problem is that the lesions are small, numerous, and non-overlapping. Here we address this problem with a new method, the Convergence Analysis of Micro-Lesions (CAML) technique, an extension of the Anatomic Likelihood Analysis (ALE). The method combines manual lesion tracing, constraints based on known lesion patterns, and convergence analysis to represent regions vulnerable to lesions as probabilistic brain atlases. Two studies were conducted over the course of 12 years in an active, vascular surgery clinic. An analysis in an initial group of 126 patients at 1.5 T MRI was cross-validated in a second group of 80 patients at 3T MRI. In CAML, lesions were manually defined and center points identified. Brains were aligned according to side of surgery since this factor powerfully determines lesion distribution. A convergence based analysis, was performed on each of these groups. Results indicated the most consistent region of vulnerability was in motor and premotor cortex regions. Smaller regions common to both groups included the dorsolateral prefrontal cortex and medial parietal regions. Vulnerability of motor cortex is consistent with previous work showing changes in hand dexterity associated with these procedures. The consistency of CAML also demonstrates the feasibility of this new approach to characterize small, diffuse, non-overlapping lesions in patients with multifocal pathologies.

Indexed as

Cerebral RevascularizationBrainBrain MappingCarotid StenosisEndarterectomyHumansMagnetic Resonance ImagingStentsALEDWIEmbolization

Identifiers

PMID29868451
PMCPMC5984594
OpenAlexW2792332803

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.