Ultrasound Guidance for Epidural Anesthesia

93 Pages·2013·1.85 MB·English

Ultrasound Guidance for Epidural Anesthesia
by
Hussam Al-Deen Ashab
MSc,BiomedicalEngineering,DukeUniversity,2010
A THESIS SUBMITTED IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
Master of Applied Science
in
THE FACULTY OF GRADUATE STUDIES
(ElectricalandComputerEngineering)
The University Of British Columbia
(Vancouver)
April 2013
(cid:13)c Hussam Al-Deen Ashab, 2013
Abstract
We propose an augmented reality system to automatically identify lumbar verte-
brallevelsandthelaminaregioninultrasound-guidedepiduralanesthesia. Spinal
needle insertion procedures require careful placement of a needle, both to en-
sure effective therapy delivery and to avoid damaging sensitive tissue such as the
spinal cord. An important step in such procedures is the accurate identification
of the vertebral levels, which is currently performed using manual palpation with
a reported success rate of only 30%. In this thesis, we propose a system using a
trinocular camerawhich tracks an ultrasound transducer during theacquisition of
a sequence of B-mode images. The system generates a panorama ultrasound im-
ageofthelumbarspine,automaticallyidentifiesthelumbarlevelsinthepanorama
image, and overlays the identified levels on a live camera view of the patient’s
back. Severalexperimentswereperformedtotesttheaccuracyofvertebralheight
in panorama images, the accuracy of vertebral levels identification in panorama
images, the accuracy of vertebral levels identification on the skin, and the impact
on accuracy with spine arching. The results from 17 subjects demonstrate the
feasibility of the approach and capability of achieving an error within a clinically
acceptablerangeforepiduralanesthesia.
The overlaid marks on the screen are used to assist locating needle puncture
site. Then, an automated slice selection algorithm is used to guide the operator
positioninga3Dtransducersuchthatthebestviewofthetargetanatomyisvisible
in a predefined re-slice of the 3D ultrasound volume. This re-slice is used to ob-
serve,inrealtime,thetrajectoryofaneedleattachedtothe3Dtransducer,towards
ii
the target. The method is based on Haar-like features and AdaBoost learning al-
gorithm. We have evaluated the method on a set of 32 volumes acquired from
volunteersubjectsbyplacingthe3DtransduceronL1-L2,L2-L3,L3-L4andL4-
L5 interspinous gaps on each side of the lumbar spine. Results show that the
needle insertion plane can be identified with a root mean square error of 5.4 mm,
accuracyof99.6%,andprecisionof78.7%.
iii
Preface
This thesis was prepared under the supervision of Dr. Purang Abolmaesumi
and Dr. Robert Rohling. They introduced the research topic of generating a
panorama image of the lumbar spine, automatically identifying the lumbar lev-
els in the panorama image, overlay the identified levels on a live camera view
of the patient’s back, and the idea of identifying lamina region from the lumbar
spineultrasoundvolumestoassistinneedleinsertion. Moreover,theyrevisedthe
manuscriptsofaconferencepaper,journalpaperandthisthesis.
AversionofChapter2hasbeenpublishedattheIEEEEngineeringinMedicine
andBiologySociety(EMBS)conference, under thetitle“AREA:AnAugmented
RealitySystemforEpiduralAnaesthesia”andintheIEEETransactionsonBiomed-
ical Engineering, under the title “An Augmented Reality System for Epidural
Anaesthesia (AREA): Pre-Puncture Identification of Vertebrae”. The work was
co-authored by Victoria A. Lessoway, Siavash Khallaghi, Alexis Cheng, Robert
Rohling and Purang Abolmaesumi [6]. Part of the code used for the system was
originally written by Alexis Cheng and Siavash Khallaghi. The author modified
and re-wrote these parts, and added to the code in order to develop a complete
working system. Moreover, the author was responsible for testing the system and
doingalltheanalysis.
DatafromsubjectswereacquiredbyVictoriaA.Lessoway(BritishColumbia
WomensHospitalandHealthCentre,DepartmentofUltrasound). Ethicsapproval
for this study was obtained from the UBC Research Ethics Board with certificate
number: H07-0691forthestudyinChapters2,andChapter3.
iv
Table of Contents
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
TableofContents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
ListofTables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
ListofFigures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x
ListofAlgorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiv
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 ThesisObjectives . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 ThesisOutline . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.1 LumbarSpineAnatomy . . . . . . . . . . . . . . . . . . 5
1.4.2 RegionalAnalgesiaandAnesthesia . . . . . . . . . . . . 7
1.5 UltrasoundGuidanceforEpiduralAnalgesiaandAnesthesia . . . 9
1.5.1 UltrasoundImageRegistrationandTrackingMethods . . . 9
1.5.2 AugmentedReality . . . . . . . . . . . . . . . . . . . . . 11
v
1.5.3 UltrasoundImageFilteringandVertebralLevelIdentifica-
tion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.5.4 AutomaticSliceSelection . . . . . . . . . . . . . . . . . 13
1.5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2 LumbarLevelIdentification . . . . . . . . . . . . . . . . . . . . . . 15
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2 UltrasoundImageCalibration . . . . . . . . . . . . . . . . . . . . 17
2.3 ImageAcquisition . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.4 PanoramaGeneration . . . . . . . . . . . . . . . . . . . . . . . . 23
2.5 VertebralIdentification . . . . . . . . . . . . . . . . . . . . . . . 25
2.6 Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.7 ExperimentsandResults . . . . . . . . . . . . . . . . . . . . . . 30
2.7.1 AccuracyofVertebralHeightinPanoramaImage . . . . . 33
2.7.2 Accuracy of Vertebral Level Identification in Panorama
Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.7.3 AccuracyofVertebralLevelIdentificationontheSkin . . 35
2.7.4 AccuracyofSpineArching . . . . . . . . . . . . . . . . . 36
2.8 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
2.8.1 AccuracyofVertebraeHeightinPanoramaImages . . . . 37
2.8.2 Accuracy of Vertebral Levels Identification in Panorama
Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
2.8.3 AccuracyofVertebralLevelsIdentificationontheSkin . . 40
2.8.4 AccuracyofSpineArching . . . . . . . . . . . . . . . . . 40
3 InsertionSliceDetection . . . . . . . . . . . . . . . . . . . . . . . . . 42
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
3.2 DataAcquisition . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.3 FeatureExtractionandConstructionofWeakClassifier . . . . . . 45
3.4 LearningClassifiers . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.4.1 TrainingCascadeClassifiers . . . . . . . . . . . . . . . . 51
vi
3.5 SliceSelection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.6 ExperimentsandResults . . . . . . . . . . . . . . . . . . . . . . 54
3.7 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
4 ConclusionandFutureWork . . . . . . . . . . . . . . . . . . . . . . 62
4.1 SummaryofContributions . . . . . . . . . . . . . . . . . . . . . 63
4.2 FutureWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
A AdditionalResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
vii
List of Tables
Table2.1 Typesofexperimentsperformed,goldstandardused,andmea-
surements/labelsthathavebeendefinedinthispaper. Numbers
used in the table refer to the measurements defined within the
text. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
Table2.2 Mean±standarddeviationofCurvilinearvertebralheight,Panorama
vertebralheight,andtheabsoluteerrorcalculatedasthediffer-
ence between those two measurements. Units are in millime-
tres;N=17. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Table2.3 Mean of the absolute error between AREA and Panorama ver-
tebral levels, and between Kerby and Panorama vertebral lev-
els. Unitsaremillimetres,N=17. . . . . . . . . . . . . . . . . 31
Table2.4 Number of false AREA and Kerby vertebral counts (N = 82).
Usingthelineartransducer,thesonographercouldnotidentify
three of the vertebrae because they were fused with a neigh-
bouringvertebra. . . . . . . . . . . . . . . . . . . . . . . . . . 34
Table2.5 Actual vertebral count, AREA vertebral count and Kerby ver-
tebral count (N = 82). For the actual vertebral count, the sono-
grapher could not identify three of the vertebrae because they
werefusedwithaneighbouringvertebra. . . . . . . . . . . . . 35
viii
Table2.6 Mean and standard deviation of the absolute difference be-
tweenAREAactualvertebraelabelsattherestingpositionand
actualvertebraelabelsattherestingpositionmeasuredonsub-
ject’sback. Unitsaremillimetres,N=17. . . . . . . . . . . . . 35
Table2.7 Comparison of the absolute error of AREA for different spine
archingangels. Unitsaremillimetres,N=17. . . . . . . . . . . 37
Table3.1 ThedistancebetweenSpinousprocess-FacetandFacet-Transverse
process measured from statistical shape model of the spine.
Unitsareinmillimetres. . . . . . . . . . . . . . . . . . . . . . 56
Table3.2 The RMS error of selecting optimal slice from ultrasound vol-
ume. Error was calculated as the distance between optimal
slice the sonographer chose and the algorithm optimal slice.
Unitsareinmillimetres. . . . . . . . . . . . . . . . . . . . . . 58
Table3.3 Theperformanceofthemethodinselectingoptimalslicefrom
ultrasoundvolume. . . . . . . . . . . . . . . . . . . . . . . . . 58
ix
List of Figures
Figure1.1 Anatomical structure of the lumbar spine showing vertebral
levels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Figure1.2 Needleinsertionintolumbarregionofthespine. . . . . . . . 8
Figure2.1 Markersusedforthecalibrationofultrasoundtransducer. . . . 17
Figure2.2 StylusCalibration. . . . . . . . . . . . . . . . . . . . . . . . 18
Figure2.3 PhantomRegistration. . . . . . . . . . . . . . . . . . . . . . 19
Figure2.4 SegmentationParameterModule. . . . . . . . . . . . . . . . . 20
Figure2.5 FreehandCalibration. . . . . . . . . . . . . . . . . . . . . . . 21
Figure2.6 WorkflowofAREA. . . . . . . . . . . . . . . . . . . . . . . 22
Figure2.7 Ultrasound B-modeimages areacquired by placingthe trans-
ducer in the parasagittal plane 10 mm from the midline. The
solid line shows the vertebral level the system identifies and
thedashedlineshowstheimagingplaneacquiredbythesono-
grapher. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Figure2.8 Example of two ultrasound panorama images. (a) Panorama
obtained in the parasagittal plane, showing L1, L2, L3, L4,
L5 and S1 from left to right. (b) The same panorama image
showingtheautomaticallyidentifiedlevelsL1,L2,L3,L4and
L5fromlefttoright. . . . . . . . . . . . . . . . . . . . . . . 26
x