Evidence map›Paper›PMID 36247716›Full record

ArticleNeurophotonics2022

Using near-infrared spectroscopy and a random forest regressor to estimate intracranial pressure.

Filip A J Relander, Alexander Ruesch, Jason Yang, Deepshikha Acharya, Bradley Scammon, Samantha Schmitt, Emily C Crane, Matthew A Smith, Jana M Kainerstorfer

Open access · goldAbstract read
In one paragraph

Article in Neurophotonics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

10 citing papers in PubMed, 31 citations in OpenAlex.

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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

9 authors at 1 institution in 1 country.

Filip A J RelanderCarnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States.
Alexander RueschCarnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States.
Jason YangCarnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States.ORCID https://orcid.org/0000-0002-9970-3333
Deepshikha AcharyaCarnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States.ORCID https://orcid.org/0000-0002-5933-0528
Bradley ScammonCarnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States.
Samantha SchmittCarnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States.
Emily C CraneCarnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States.ORCID https://orcid.org/0000-0002-6207-3163
Matthew A SmithCarnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States.ORCID https://orcid.org/0000-0003-1192-9942
Jana M KainerstorferCarnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States.ORCID https://orcid.org/0000-0002-9481-8377
Carnegie Mellon University · US

Funding

Non-invasive Intracranial Pressure Sensing with Near Infrared Light for Monitoring the Healthy and Diseased BrainR21EB024675 · NIBIB · CARNEGIE-MELLON UNIVERSITY · PI KAINERSTORFER, JANA MARIA · 2018 to 2020
$591k
NIBIB NIH HHS R21 EB024675
6 · The paper itself

Abstract

Significance: Intracranial pressure (ICP) measurements are important for patient treatment but are invasive and prone to complications. Noninvasive ICP monitoring methods exist, but they suffer from poor accuracy, lack of generalizability, or high cost. Aim: We previously showed that cerebral blood flow (CBF) cardiac waveforms measured with diffuse correlation spectroscopy can be used for noninvasive ICP monitoring. Here we extend the approach to cardiac waveforms measured with near-infrared spectroscopy (NIRS). Approach: Changes in hemoglobin concentrations were measured in eight nonhuman primates, in addition to invasive ICP, arterial blood pressure, and CBF changes. Features of average cardiac waveforms in hemoglobin and CBF signals were used to train a random forest (RF) regressor. Results: The RF regressor achieves a cross-validated ICP estimation of Conclusions: This study provides a proof of concept for the use of NIRS in noninvasive ICP estimation.

Indexed as

biophotonicsintracranial pressuremachine learningnear-infrared spectroscopy

Identifiers

PMID36247716
PMCPMC9552940
OpenAlexW4304196011

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.