Human Electrical-Impedance-Tomography Reconstruction Models

Assessment of CT-derived Thoracic Electrical-Impedance-Tomography Finite Element Models

Current EIT analyses are based on the assumption of a circular thorax-shape and do not provide any information on lung borders. The aim is to obtain the body and lung border contours of male subjects by multi-detector computed tomography (MDCT) in defined thresholds of anthropometric data (gender = male; height; weight) for calibration of more realistic EIT reconstruction models.

Study Overview

• Status: Unknown
• Conditions: Respiratory Monitoring
• Intervention / Treatment: Device: "electrical impedance tomography"

Detailed Description

A major drawback of EIT is its relatively poor spatial resolution and its limitation in measuring changes in bioimpedance as compared to a reference state (and not absolute quantities). Therefore, the technique cannot differentiate between extrapulmonary structures (muscles, thorax, heart, large vessels, spine, etc.) and non-aerated lung tissues - which is a major limitation for the clinical use of information derived from EIT-imaging. Moreover, current EIT-reconstruction algorithms are based on the consideration of a complete circular thoracic shape and do not take into account the body contours and lung borders.

The investigators are convinced that EIT-derived dynamic bedside lung imaging can be advanced by morphing computed tomography (CT) scans of the respective thoracic levels with concomitant EIT images - thus enhancing EIT-image information with CT-data. Integrating the anatomy of thoracic shape and lung borders provided by high-spatial resolution multi detector CT-scans (MDCT) with high-temporal resolution EIT has the potential to improve image quality considerably. This data can be used to compute mean EIT-reconstruction models that further offer the possibility to develop novel and clinically meaningful EIT parameters.

Therefore, the investigators hypothesize that by integration of CT-scan information of body and lung contours (and by computing different EIT reconstruction models) the current methodological limitations of EIT technology can be overcome.

• Study Type: Interventional
• Enrollment (Anticipated): 160
• Phase: Phase 3

Contacts and Locations

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: Male

Description

Inclusion Criteria:

• spontaneous breathing male subjects
• age > 18,
• clinical indication for thoracic CT scanning,
• matching of weight and height to the predefined model-thresholds

Exclusion Criteria:

• pre-existing chronic pulmonary disease
• skin lesions / wounds in the thoracic plane where the EIT SensorBelt will be attached
• known allergy against any ingredient of the used ContactAgent
• abnormalities in thoracic shape as defined by the radiologist in charge (e.g. extreme kyphosis, funnel chest, pigeon breast, multiple rip fractures)
• pneumothorax
• pace maker (external and internal)
• other implanted electrical devices
• other methods measuring bioimpedance

Study Plan

How is the study designed?

Design Details

• Primary Purpose: DIAGNOSTIC
• Allocation: NA
• Interventional Model: SINGLE_GROUP
• Masking: NONE

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
EXPERIMENTAL: Study cohort 1; "electrical impedance tomography"	Device: "electrical impedance tomography"; One continous electrical impedance tomography (EIT) measurement per subject of approximately 5 minutes duration (2 min prior to MDCT scanning, during end-inspiratory MDCT acquisition and 2 min after MDCT scanning)

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Electrical Impedance Tomography Finite Element Model	Based on CT-derived thorax, lung and heart contours we propose to calculate human finite element models (FEM) for EIT analysis	approximately 1 year through study completion

Secondary Outcome Measures

Outcome Measure	Time Frame
height	at the time-point of inclusion
weight	at the time-point of inclusion
gender	at the time-point of inclusion

Collaborators and Investigators

• Sponsor: Medical University of Vienna
• Investigators: Principal Investigator: Stefan Boehme, MD, Department of General Anesthesia, Intensive Care Medicine and Pain Management, Medical University of Vienna, Austria

Study record dates

Study Major Dates

• Study Start: May 1, 2016
• Primary Completion (ANTICIPATED): November 1, 2016
• Study Completion (ANTICIPATED): June 1, 2017

Study Registration Dates

• First Submitted: May 9, 2016
• First Submitted That Met QC Criteria: May 11, 2016
• First Posted (ESTIMATE): May 16, 2016

Study Record Updates

• Last Update Posted (ESTIMATE): May 16, 2016
• Last Update Submitted That Met QC Criteria: May 11, 2016
• Last Verified: May 1, 2016

More Information

Terms related to this study

• Keywords: respiration; monitoring, physiologic; diagnostic techniques, respiratory system
• Other Study ID Numbers: 1917/2015

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO