Evidence map›Paper›PMID 28282026›Full record

ArticlePhysiological measurement2017

Comparative study of separation between ex vivo prostatic malignant and benign tissue using electrical impedance spectroscopy and electrical impedance tomography.

Ethan K Murphy, Aditya Mahara, Shadab Khan, Elias S Hyams, Alan R Schned, Jason Pettus, Ryan J Halter

Abstract readComparative Study
In one paragraph

Article in Physiological measurement, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Comparison of Complex Open Domain Electrical Impedance Tomography Methods.IEEE transactions on bio-medical engineering · 2025
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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

7 authors.

Ethan K MurphyThayer School of Engineering, Dartmouth College, 14 Engineering Drive, Hanover, NH 03755, United States of America.
Aditya MaharaThayer School of Engineering, Dartmouth College, 14 Engineering Drive, Hanover, NH 03755, United States of America.
Shadab KhanBoston Children's Hospital, Boston, MA 02115, United States of America.
Elias S HyamsDartmouth-Hitchcock Medical Center, Lebanon, NH 03766, United States of America.
Alan R SchnedDartmouth-Hitchcock Medical Center, Lebanon, NH 03766, United States of America.
Jason PettusDartmouth-Hitchcock Medical Center, Lebanon, NH 03766, United States of America.
Ryan J HalterThayer School of Engineering, Dartmouth College, 14 Engineering Drive, Hanover, NH 03755, United States of America.

Funding

Intraoperative Surgical Margin Assessment with Electrical Impedance SpectroscopyR01CA143020 · NCI · DARTMOUTH COLLEGE · PI HALTER, RYAN JOSEPH · 2011 to 2014
$1.2M
NCI NIH HHS R01 CA143020
6 · The paper itself

Abstract

objectiveCurrently no efficient and reliable technique exists to routinely assess surgical margins during a radical prostatectomy. Electrical impedance spectroscopy (EIS) has been reported as a potential technique to provide surgeons with real-time intraoperative margin assessment. In addition to providing a quantified measure of margin status, a co-registered electrical impedance tomography (EIT) image presented on a surgeon's workstation could add value to the margin assessment process. APPROACH: To investigate this, we conducted a comparative study between EIS and EIT to evaluate the potential these technologies might have for margin assessment. EIS and EIT data was acquired from ex vivo human prostates using a multi-electrode endoscopic impedance acquisition probe. MAIN

resultsEIS and EIT show good predictive performance with a 0.76 and 0.80 area-under-curve (AUC), respectively, when considering discrete frequencies only. A machine learning (ML) algorithm is implemented to combine features, which improves the AUCs of EIS and EIT to 0.84 and 0.85, respectively. Single-step EIT takes significantly less time to reconstruct than multi-step EIT, yet provides similarly accurate classification results, making the single-step approach a potential candidate for real-time margin assessment. While the ML-based approach clearly exhibits benefits as compared to the single feature assessment, the decision to use EIS versus EIT is unclear since each approach performs better for different subsets of tissue classifications. SIGNIFICANCE: The results presented in this paper corroborate our previous studies and present the strongest evidence yet that an intraoperative-capable impedance probe can be used to distinguish benign from malignant prostate tissues. An in vivo study with a large cohort will be necessary to definitively determine the preferred approach and to show the clinical effectiveness of using this technology for margin assessment.

Indexed as

Electric ImpedanceTomographyDielectric SpectroscopyHumansImage Processing, Computer-AssistedMachine LearningMaleProstateProstatic Neoplasms

Identifiers

PMID28282026
PMCPMC5757237

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Registered trials

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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.