[PPT] - Optimal PEEP selection in Mechanical Ventilation using EIT Ravi B. PowerPoint Presentation

SLIDE 1

Optimal PEEP selection in Mechanical Ventilation using EIT

Ravi B. Bhanabhai

Carleton University - 2009/11 M.A.Sc

January 20, 2012

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 1 / 28

SLIDE 2

Outline

1

Introduction The Problem How to solve the problem?

2

Contributions IP Calculation Fuzzy Logic System

3

Results Sigmoid vs. Linear Linear vs. Visual Optimal PEEP

4

References

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 2 / 28

SLIDE 3

Introduction

This is a presentation outlining the work done within Ravi Bhanabhai M.A.Sc thesis. Purpose: Investigate the use of Electrical Impedance Tomography (EIT) within mechanical ventilation.

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 3 / 28

SLIDE 4

Introduction

This is a presentation outlining the work done within Ravi Bhanabhai M.A.Sc thesis. Purpose: Investigate the use of Electrical Impedance Tomography (EIT) within mechanical ventilation. Mathematical Tools:

1

Linear and Non-Linear curve fitting techniques

2

Fuzzy Logic.

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 3 / 28

SLIDE 5

Introduction

This is a presentation outlining the work done within Ravi Bhanabhai M.A.Sc thesis. Purpose: Investigate the use of Electrical Impedance Tomography (EIT) within mechanical ventilation. Mathematical Tools:

1

Linear and Non-Linear curve fitting techniques

2

Fuzzy Logic.

Contribtions:

1

Summarize scholarly papers on ALI.

2

Inflection Point (IP) location on EIT and pressure data.

3

Creation of Fuzzy Logic System using IP.

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 3 / 28

SLIDE 6

Introduction

This is a presentation outlining the work done within Ravi Bhanabhai M.A.Sc thesis. Purpose: Investigate the use of Electrical Impedance Tomography (EIT) within mechanical ventilation. Mathematical Tools:

1

Linear and Non-Linear curve fitting techniques

2

Fuzzy Logic.

Contribtions:

1

Summarize scholarly papers on ALI.

2

Inflection Point (IP) location on EIT and pressure data.

3

Creation of Fuzzy Logic System using IP.

Novel Aspects:

1

Use of short recruitment maneuever (≤ 2min)

2

Regional Inflection Points used

3

Use of Inflection Points within an automated classification system

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 3 / 28

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Introduction The Problem

ALI & VILI Respiratory Failure

Oxygenation Failure (hypoxemia) Ventilatory Failure (hypercapnia) + more oxygen related conditions

Acute Lung Injury (ALI)

Ventilator Induce Lung Injury (VILI)

* Cyclic opening and closing * overdistension PEEP

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 4 / 28

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Introduction How to solve the problem?

Respiratory Function Models

Pao = V C + ˙ V R + ¨ V I − Pmus (1)

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 5 / 28

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Introduction How to solve the problem?

Respiratory Function Models

Pao = V C + ˙ V R + ¨ V I − Pmus (1) Interested in V

C only.

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 5 / 28

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Introduction How to solve the problem?

Respiratory Function Models

Pao = V C + ˙ V R + ¨ V I − Pmus (1) Interested in V

C only.

To remove other components this thesis data did two things:

1

Slow Constant Flow

2

Antheysia

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 5 / 28

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Introduction How to solve the problem?

Pressure-Volume Curves

Used to help guide ventilation strategies by locating points of compliance change.

5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Inflation Original Sigmoid Fitted Inflection Points 5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Deflation Original Sigmoid Fitted Inflection Points

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 6 / 28

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Introduction How to solve the problem?

Pressure-Volume Curves

Used to help guide ventilation strategies by locating points of compliance change. Points are Lower Inflection Point (LIP) and Upper Inflection Point (UIP)

5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Inflation Original Sigmoid Fitted Inflection Points 5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Deflation Original Sigmoid Fitted Inflection Points

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 6 / 28

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Introduction How to solve the problem?

Pressure-Volume Curves

Used to help guide ventilation strategies by locating points of compliance change. Points are Lower Inflection Point (LIP) and Upper Inflection Point (UIP)

5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Inflation Original Sigmoid Fitted Inflection Points 5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Deflation Original Sigmoid Fitted Inflection Points

(e) Linear Fit of PI data

−20 −10 10 20 30 0.2 0.4 0.6 0.8 1 Time Alignment global EIT Pressure

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 6 / 28

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Introduction How to solve the problem?

Data used

Data used: 26 patients low constant flow maneuver (4 L/min) start 0 mbar → 35 mbar / 2L

20 40 60 80 100 120 140 160 180 200 5 10 15 20 Pressure [mbar] Pressure Maneuver 20 40 60 80 100 120 140 160 180 200 500 1000 1500 Volume [ml] Volume Maneuver 20 40 60 80 100 120 140 160 180 200 −20 20 40 Flow [L/min] Flow Maneuver Time [sec]

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 7 / 28

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Introduction How to solve the problem?

Electrical Impedance Tomography (EIT)

EIT is real-time impedance tomography, it can be used to accuratly measure air distrubtion within the thorax.

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 8 / 28

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Introduction How to solve the problem?

Electrical Impedance Tomography (EIT)

EIT is real-time impedance tomography, it can be used to accuratly measure air distrubtion within the thorax.

(a) Start of Inflation (b) Max Pressure (c) End of Deflation Figure: Example reconstruction using the GREIT methods of a healthy lung patient (patient 7).

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 8 / 28

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Contributions

Automated IP calculation

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 9 / 28

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Contributions

Automated IP calculation Rule-base Fuzzy Logic Classifier

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 9 / 28

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Contributions IP Calculation

IP Calculation

Three Types of IP location methods were used:

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 10 / 28

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Contributions IP Calculation

IP Calculation

Three Types of IP location methods were used:

1 Sigmoid method Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 10 / 28

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Contributions IP Calculation

IP Calculation

Three Types of IP location methods were used:

1 Sigmoid method 2 Visual heuristics Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 10 / 28

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Contributions IP Calculation

IP Calculation

Three Types of IP location methods were used:

1 Sigmoid method 2 Visual heuristics 3 3-piece linear spline method Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 10 / 28

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Contributions IP Calculation

IP Calculation

Three Types of IP location methods were used:

1 Sigmoid method 2 Visual heuristics 3 3-piece linear spline method

Multiple methods were implemented for comparison reasons.

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 10 / 28

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Contributions IP Calculation

Sigmoid Method

5 10 15 20 25 30 35 200 400 600 800 1000 1200 pressure − mbar volume − ml Sigmoid Method a= 12ml b= 1173 ml Plip =c - 2d =11.1 Plip =c +2d =22.9 c= 17 cm H20 Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 11 / 28

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Contributions IP Calculation

Visual Heuristics

Clinicians used this method to locate Inflection Points from global PV curves. Multiple methods exist:

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 12 / 28

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Contributions IP Calculation

Visual Heuristics

Clinicians used this method to locate Inflection Points from global PV curves. Multiple methods exist:

1

Find location where PV curve has linear compliance

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 12 / 28

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Contributions IP Calculation

Visual Heuristics

Clinicians used this method to locate Inflection Points from global PV curves. Multiple methods exist:

1

Find location where PV curve has linear compliance

2

Pressure where rapid increase in compliance occurs

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 12 / 28

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Contributions IP Calculation

Visual Heuristics

Clinicians used this method to locate Inflection Points from global PV curves. Multiple methods exist:

1

Find location where PV curve has linear compliance

2

Pressure where rapid increase in compliance occurs

3

Place two line. 1) Along low compliance. 2) Along High compliance. Locate Intersection.

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 12 / 28

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Contributions IP Calculation

Visual Heuristics

Clinicians used this method to locate Inflection Points from global PV curves. Multiple methods exist:

1

Find location where PV curve has linear compliance

2

Pressure where rapid increase in compliance occurs

3

Place two line. 1) Along low compliance. 2) Along High compliance. Locate Intersection.

This thesis:

1

5 participants

2

Fit in linear manner to get closest to all the data points

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 12 / 28

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Contributions IP Calculation

Visual Heuristic

5 10 15 20 25 30 35 −0.4 −0.2 0.2 0.4 0.6 0.8 1 Pressure (mbar) EIT Conductivity Trial3/ 4 − Deflation One chance only, be carefull 5 10 15 20 25 30 35 −0.1 0.1 0.2 0.3 0.4 0.5 0.6 Pressure (mbar) EIT Conductivity Trial1/ 4 − Deflation One chance only, be carefull

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 13 / 28

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Contributions IP Calculation

3-piece Linear Spline Method

Similar to visual methods

5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Inflation Original Sigmoid Fitted Inflection Points 5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Deflation Original Sigmoid Fitted Inflection Points

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 14 / 28

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Contributions IP Calculation

3-piece Linear Spline Method

Similar to visual methods Fits to 3 lines with Inflection Points being located at intersection

5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Inflation Original Sigmoid Fitted Inflection Points 5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Deflation Original Sigmoid Fitted Inflection Points

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 14 / 28

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Contributions IP Calculation

3-piece Linear Spline Method

Similar to visual methods Fits to 3 lines with Inflection Points being located at intersection This Thesis: No Constraints on fitting other then minimization of criteria

5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Inflation Original Sigmoid Fitted Inflection Points 5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Deflation Original Sigmoid Fitted Inflection Points

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 14 / 28

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Contributions IP Calculation

3-piece Linear Spline Method

Similar to visual methods Fits to 3 lines with Inflection Points being located at intersection This Thesis: No Constraints on fitting other then minimization of criteria

5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Inflation Original Sigmoid Fitted Inflection Points 5 10 15 20 25 30 35 −2 2 4 6 Pressure (mbar) EIT Conductivity Linear Fit − Deflation Original Sigmoid Fitted Inflection Points

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 14 / 28

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Contributions Fuzzy Logic System

Introduction

The Fuzzy System is designed into 4 sections:

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 15 / 28

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Contributions Fuzzy Logic System

Introduction

The Fuzzy System is designed into 4 sections:

1 Location of IP Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 15 / 28

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Contributions Fuzzy Logic System

Introduction

The Fuzzy System is designed into 4 sections:

1 Location of IP 2 Fuzzification Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 15 / 28

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Contributions Fuzzy Logic System

Introduction

The Fuzzy System is designed into 4 sections:

1 Location of IP 2 Fuzzification 3 Premise Calculation (Application of IF-THEN) 4 Defuzzification and Optimization Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 15 / 28

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Contributions Fuzzy Logic System

Introduction

5 10 15 20 25 30 35 40 −1 1 2 3 Pressure (mbar) EIT Conductivity Linear Fit − Inflation Original Sigmoid Fitted Inflection Points 5 10 15 20 25 30 35 40 −1 1 2 3 Pressure (mbar) EIT Conductivity Linear Fit − Deflation Original Sigmoid Fitted Inflection Points 5 10 15 20 25 30 35 40 −0.5 0.5 1 1.5 2 Pressure (mbar) EIT Conductivity Linear Fit − Inflation Original Sigmoid Fitted Inflection Points 5 10 15 20 25 30 35 40 −1 1 2 Pressure (mbar) EIT Conductivity Linear Fit − Deflation Original Sigmoid Fitted Inflection Points

5 10 15 20 25 30 35 0.2 0.4 0.6 0.8 1 Pressure Membership Value Pressure based Membership Graph − Inflation Below In Between Above 5 10 15 20 25 30 35 0.2 0.4 0.6 0.8 1 Pressure Membership Value Pressure based Membership Graph − Deflation Below In Between Above 5 10 15 20 25 30 35 0.2 0.4 0.6 0.8 1 Pressure Membership Value Pressure based Membership Graph − Inflation Below In Between Above 5 10 15 20 25 30 35 0.2 0.4 0.6 0.8 1 Pressure Membership Value Pressure based Membership Graph − Deflation Below In Between Above 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 0.2 0.4 0.6 0.8 1 EIT Membership Value LIP UIP EIT based Membership Graph − Inflation Below In Between Above −0.5 0.5 1 1.5 0.2 0.4 0.6 0.8 1 EIT Membership Value LIP UIP EIT based Membership Graph − Deflation Below In Between Above 0.5 1 1.5 2 0.2 0.4 0.6 0.8 1 EIT Membership Value LIP UIP EIT based Membership Graph − Inflation Below In Between Above 0.5 1 1.5 2 0.2 0.4 0.6 0.8 1 EIT Membership Value LIP UIP EIT based Membership Graph − Deflation Below In Between Above 5 10 15 20 25 30 35 0.2 0.4 0.6 0.8 1 Pressure Magnitude Pressure based Optimal Pressure Graph − Inflation Good States Bad States 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 0.2 0.4 0.6 0.8 1 EIT Magnitude EIT based Optimal Pressure Graph − Inflation Good States Bad States 5 10 15 20 25 30 35 0.2 0.4 0.6 0.8 1 Pressure Magnitude Pressure based Optimal Pressure Graph − Deflation Good States Bad States −0.5 0.5 1 1.5 0.2 0.4 0.6 0.8 1 EIT Magnitude EIT based Optimal Pressure Graph − Deflation Good States Bad States 5 10 15 20 25 30 35 0.2 0.4 0.6 0.8 1 Pressure Magnitude Pressure based Optimal Pressure Graph − Inflation Good States Bad States 0.5 1 1.5 2 0.2 0.4 0.6 0.8 1 EIT Magnitude EIT based Optimal Pressure Graph − Inflation Good States Bad States 5 10 15 20 25 30 35 0.2 0.4 0.6 0.8 1 Pressure Magnitude Pressure based Optimal Pressure Graph − Deflation Good States Bad States 0.5 1 1.5 2 0.2 0.4 0.6 0.8 1 EIT Magnitude EIT based Optimal Pressure Graph − Deflation Good States Bad States

Average over all pixels Calculate Optimal PEEP IF P re ssure /E I T THEN State Be low Collpase d I n Be twe e n Normal Ab

ve

Ove rdiste nde d

Inflection Points Fuzzification Premise Calculation Optimization Rule Base

50 100 150 200 250 300 350 400 450 50 100 150 200 250 300 Good vs Bad states − Pressure based system Pressure Index Mantiude ← Optimal PEEP ← Optimal PEEP 50 100 150 200 250 300 350 400 50 100 150 200 250 300 Good vs Bad states − Pressure based system Pressure Index Mantiude ← Optimal PEEP 50 100 150 200 250 300 350 400 450 50 100 150 200 250 300 Good vs Bad states − EIT based system Pressure Index Mantiude ← Optimal PEEP 50 100 150 200 250 300 350 400 50 100 150 200 250 300 350 Good vs Bad states − EIT based system Pressure Index Mantiude ← Optimal PEEP

Pressure - Inflation Pressure - Deflation EIT - Inflation EIT - Deflation

Inference and Defuzzification Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 16 / 28

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Contributions Fuzzy Logic System

IP and Fuzzification

IP were taken from the 3-piece linear optimization portion and used in the creation of the fuzzification graphs.

0.25 0.5 0.75 1 a b c d

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Contributions Fuzzy Logic System

IP and Fuzzification

IP were taken from the 3-piece linear optimization portion and used in the creation of the fuzzification graphs.

Membership Input 1 (mbar) Input 2 (mbar) Input 3 (mbar) Input 4 (mbar) Below min(p) min(p)

2+LIP

LIP In Between

2+LIP

LIP UIP 2+UIP Above UIP 2+UIP max(p) max(p)

Table: Details on creating the trapezoidal based fuzzy membership functions

0.25 0.5 0.75 1 a b c d

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 17 / 28

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Contributions Fuzzy Logic System

IP and Fuzzification

IP were taken from the 3-piece linear optimization portion and used in the creation of the fuzzification graphs.

Membership Input 1 (mbar) Input 2 (mbar) Input 3 (mbar) Input 4 (mbar) Below min(p) min(p)

2+LIP

LIP In Between

2+LIP

LIP UIP 2+UIP Above UIP 2+UIP max(p) max(p)

Table: Details on creating the trapezoidal based fuzzy membership functions

0.25 0.5 0.75 1 a b c d

Figure: Trapezoidal Fuzzy Membership graph

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 17 / 28

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Contributions Fuzzy Logic System

Inference and Defuzzification

The Inference is conducted using the Rule base. With key relations to previous papers:

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 18 / 28

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Contributions Fuzzy Logic System

Inference and Defuzzification

The Inference is conducted using the Rule base. With key relations to previous papers:

1 Pressure below the LIP is considered collapsed 2 Pressure above the UIP is considered overdistended Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 18 / 28

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Contributions Fuzzy Logic System

Inference and Defuzzification

The Inference is conducted using the Rule base. With key relations to previous papers:

1 Pressure below the LIP is considered collapsed 2 Pressure above the UIP is considered overdistended

Defuzzification was done by breaking the output states into two classifications:

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 18 / 28

SLIDE 46

Contributions Fuzzy Logic System

Inference and Defuzzification

The Inference is conducted using the Rule base. With key relations to previous papers:

1 Pressure below the LIP is considered collapsed 2 Pressure above the UIP is considered overdistended

Defuzzification was done by breaking the output states into two classifications:

1 ‘Good’ = Normal states 2 ‘Bad’ = Collpased + Overdistended states Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 18 / 28

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Contributions Fuzzy Logic System

Inference and Defuzzification

The Inference is conducted using the Rule base. With key relations to previous papers:

1 Pressure below the LIP is considered collapsed 2 Pressure above the UIP is considered overdistended

Defuzzification was done by breaking the output states into two classifications:

1 ‘Good’ = Normal states 2 ‘Bad’ = Collpased + Overdistended states

Upon averaging over lung region MAX value between the difference of ‘Good’ and ‘Bad’ states is performed to locate the PEEP.

Fuzzy Logic Schematic Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 18 / 28

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Results Sigmoid vs. Linear

Sigmoid vs. Linear

5 10 15 20 x 10

−3

LIP−Inf UIP−Inf LIP−Def UIP−Def Linear Method % not found 0.2 0.4 0.6 0.8 1 LIP−Inf UIP−Inf LIP−Def UIP−Def Sigmoid Method % not found

Figure: How frequent each sigmoid and linear method are not able to find IP.

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 19 / 28

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Results Sigmoid vs. Linear

Sigmoid vs. Linear

5 10 15 20 x 10

−3

LIP−Inf UIP−Inf LIP−Def UIP−Def Linear Method % not found 0.2 0.4 0.6 0.8 1 LIP−Inf UIP−Inf LIP−Def UIP−Def Sigmoid Method % not found

Figure: How frequent each sigmoid and linear method are not able to find IP.

Mean Std Median LIP - Inflation 1.47 3.02 1.50 UIP - Inflation

6.80

2.54

6.82

LIP - Deflation 4.07 1.84 4.07 UIP - Deflation

2.37

2.24

2.78

Table: Difference between Sigmoid and Linear Method

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 19 / 28

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Results Linear vs. Visual

Linear vs. Visual Heuristics

Difference = Linear IP − Visual Heuristic IP

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Results Linear vs. Visual

Linear vs. Visual Heuristics

Difference = Linear IP − Visual Heuristic IP −0.6247mbar for LIP −0.4662mbar for UIP

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 20 / 28

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Results Linear vs. Visual

Linear vs. Visual Heuristics

Difference = Linear IP − Visual Heuristic IP −0.6247mbar for LIP −0.4662mbar for UIP best average = 0.016mbar worst average = −1.507mbar

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 20 / 28

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Results Linear vs. Visual

Linear vs. Visual Heuristics

Difference = Linear IP − Visual Heuristic IP −0.6247mbar for LIP −0.4662mbar for UIP best average = 0.016mbar worst average = −1.507mbar Provides insight to accuracy of linear method

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 20 / 28

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Results Optimal PEEP

Hetergenaity

Figure: Progressive change of lung state with pressure

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 21 / 28

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Results Optimal PEEP

LIP+2 vs FLS

5 10 15 20 25 30 35 −0.5 0.5 1 1.5 2 Pressure [mbar] EIT Linear Fit graph with LIP+2 mbar PEEP ← LIP+2cm = 9.4837 mbar 5 10 15 20 25 30 35 −1 −0.5 0.5 1 Pressure [mbar] Membership Optimal Selection graph with Optimal PEEP ← FLS = 17.2 mbar PI Linear Fit Lower IP Upper IP Bad Good Difference

(a) Patient 12

−10 10 20 30 40 −0.5 0.5 1 1.5 Pressure [mbar] EIT Linear Fit graph with LIP+2 mbar PEEP ← LIP+2cm = 2.1 mbar 10 20 30 40 −1 −0.5 0.5 1 Pressure [mbar] Membership Optimal Selection graph with Optimal PEEP ← FLS = 16.8 mbar PI Linear Fit Lower IP Upper IP Bad Good Difference

(b) Patient 16

5 10 15 20 −1 1 2 3 4 5 Pressure [mbar] EIT Linear Fit graph with LIP+2 mbar PEEP ← LIP+2cm = 8.5263 mbar PI Linear Fit Lower IP Upper IP 5 10 15 20 −1 −0.5 0.5 1 Pressure [mbar] Membership Optimal Selection graph with Optimal PEEP ← FLS = 8.6 mbar Bad Good Difference

(c) Patient 8

5 10 15 20 25 −1 1 2 3 4 Pressure [mbar] EIT Linear Fit graph with LIP+2 mbar PEEP ← LIP+2cm = 9.628 mbar 5 10 15 20 25 −1 −0.5 0.5 1 Pressure [mbar] Membership Optimal Selection graph with Optimal PEEP ← FLS = 10.3 mbar PI Linear Fit Lower IP Upper IP Bad Good Difference

(d) Patient 17 Figure: Global PI curve with LIP, UIP, and the LIP+2 mbar pressure and the Fuzzy optimal selection with according FLS based pressure.

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 22 / 28

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References I

Adler, A., Amato, M., Arnold, J., Bayford, R., Bodenstein, M., B¨

hm,

S., Brown, B., Frerichs, I., Stenqvist, O., Weiler, N., and Wolf, G. (2012). Whither lung EIT: where are we, where do we want to go, and what do we need to get there? Submitted for publication to Journal of Applied Physiology. EIDORS (2011). EIDORS: Electrical impedance tomography and diffuse optical tomography reconstruction software. http://eidors3d.sourceforge.net/. Graham, B. M. (2007). Enhancements in Electrical Impedance Tomography (EIT) Image Reconstruction for 3D Lung Imaging. PhD thesis, Carleton University.

SLIDE 57

References

References II

Grychtol, B., Wolf, G. K., Adler, A., and Arnold, J. H. (2010). Towards lung EIT image segmentation: automatic classification of lung tissue state from analysis of EIT monitored recruitment manoeuvres. Physiological Measurement, 31(8):S31. Grychtol, B., Wolf, G. K., and Arnold, J. H. (2009). Differences in regional pulmonary pressure impedance curves before and after lung injury assessed with a novel algorithm. Physiological Measurement, 30(6):S137. Holder, D. (2004). Electrical Impedance Tomography: Methods, History, Applications. Institute of Physics Publishing.

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 24 / 28

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References

References III

Luepschen, H., Meier, T., Grossherr, M., Leibecke, T., Karsten, J., and Leonhardt, S. (2007). Protective ventilation using electrical impedance tomography. Physiological Measurement, 28(7):S247. Mendel, J. M. (2001). Uncertain rule-based fuzzy logic system: introduction and new directions. Prentice-Hall PTR, 1st edition. Pulletz, S., Adler, A., Kott, M., Elke, B., Hawelczyk, B., Sch¨ adler, D., Zick, G., Weiler, N., and Frerichs, I. (2011). Regional lung opening and closing pressures in patients with acute lung injury. Journal of Critical Care, 0000(0000):0000.

Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 25 / 28

SLIDE 59

References

References IV

Victorino, J. A., Borges, J. B., Okamoto, V. N., Matos, G. F. J., Tucci, M. R., Caramez, M. P. R., Tanaka, H., Sipmann, F. S., Santos,

D. C. B., Barbas, C. S. V., Carvalho, C. R. R., and Amato, M. B. P.

(2004). Imbalances in regional lung ventilation: A validation study on electrical impedance tomography.

Am. J. Respir. Crit. Care Med., 169(7):791–800.

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Fuzzy Logic Schematic Ravi B. Bhanabhai (Carleton U) Safe Keeping Ventilation Patients 01/20/2012 28 / 28