Evidence map›Paper›PMID 40036517›Full record

ArticleIEEE transactions on bio-medical engineering2025

Comparison of Complex Open Domain Electrical Impedance Tomography Methods.

Allaire F Doussan, Ethan K Murphy, Sophie A Lloyd, Ryan J Halter

Abstract readComparative Study
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Allaire F Doussan
Ethan K Murphy
Sophie A Lloyd
Ryan J Halter

Funding

Microendoscopic Electrical Impedance Sensing for Real-time Intraoperative Surgical Margin AssessmentR01CA237654 · NCI · DARTMOUTH COLLEGE · PI HALTER, RYAN JOSEPH · 2020 to 2024
$2.4M
Classifying Oral Lesions with Chip-on-tip Electrical Impedance SensingR21DE031095 · NIDCR · DARTMOUTH COLLEGE · PI HALTER, RYAN JOSEPH · 2021 to 2022
$436k
NCI NIH HHS R01 CA237654NIDCR NIH HHS R21 DE031095
6 · The paper itself

Abstract

objectiveThis study evaluates the potential of complex 3D Electrical Impedance Tomography (EIT) for intraoperative surgical margin assessment (SMA) using an ex vivo bovine model.

methodsA custom electrode array was used to collect impedance data across multiple frequencies (100 Hz-1 MHz) from 57 tissue samples. An optimal pressure range was identified to ensure proper electrode contact with minimal tissue deformation (2 kPa to 5 kPa) and a saline calibration was used to minimize model-data mismatch. A novel best fit factor, β, was introduced to scale the reference data of difference EIT and initial guess for absolute EIT to eliminate inversions in permittivity. The accuracy of complex EIT reconstructions were investigated using pixel-based tissue classification.

resultsExperimental difference EIT, particularly for conductivity (σ) at 100 Hz, achieved high sensitivity (0.92) and specificity (0.90) with fast reconstruction speeds of 1.67 seconds. While absolute EIT performed slightly better in quantitative metrics for σ imaging (AUC = 0.90, Accuracy = 0.86), difference EIT was found to be more suitable for real-time applications due to its faster processing time. Simulations suggested that permittivity (ϵ) has sufficient contrast for classifying muscle and adipose tissue. However, experimental ϵ reconstructions exhibited lower performance, suggesting the need for hardware improvements.

conclusionDifference EIT is the most promising method for real-time applications, balancing high accuracy with reconstruction speeds. Absolute EIT, while slightly more accurate, is less feasible due to longer processing times (150.6 seconds). SIGNIFICANCE: This study advances the potential for real-time intraoperative SMA using a novel complex EIT reconstruction method.

Indexed as

Electric ImpedanceImaging, Three-DimensionalTomographyAnimalsCattle

Identifiers

PMID40036517
PMCPMC12885056

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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.