Azienda Sanitaria Firenze 1

Stefano Michelagnoli MD, Emiliano Chisci, MD, Neri Alamanni, Phy.

Department of Surgery, Vascular and Endovascular Surgery Unit, “San Giovanni di Dio” Hospital, Florence, Italy.

Calculating risk of rupture of an AAA Milano December, 11 - 2014

www.anefix.com

Rationale..

We would like to find out a tool to grade the

individual patient risk of rupture of an AAA....

2

the estimated rupture rate for small AAAs is up as much 6% per annum

AAA Rupture Risk Indicators

Anatomic Indicators

(Diameter)

Structural Indicators

(PWS, RPI)

Haemodynamic Indicators

(Aneurysm Formation Index(AFI),Gradient Oscillating

Number (GON), Relative Residence Time (RRT),

Oscillatory Shear Index (OSI) etc.)

3

Fillinger MF, Marra SP, Raghavan ML, Kennedy FE. Prediction of rupture risk in abdominal aortic aneurysm during observation: wall stress versus diameter. J

Vasc Surg 2003;37:724–732.

Vande Geest JP, Di Martino ES, Bohra A, et al. A biomechanics-based rupture potential index for abdominal aortic aneurysm risk assessment: demonstrative application. Ann N Y

Acad Sci 2006;1085:11–21.

Gasser TC, Auer M, Labruto F, et al. Biomechanical Rupture Risk Assessment of Abdominal Aortic Aneurysm: Model Complexity versus Predicability of Finite Element

Simulations. Eur J Vasc Endovasc Surg 2010;40:176-185.

RPI: rupture potential index

The most used risk factor

PWS = Peak Stress in AAA wall

RPI is a Safety Factor i.e.:

RPI= PWS / Wall Strength

Varies between 0 and 1: 0 = No Risk, 1 = Risk of imminent rupture

PWS depends on

AAA shape,

Wall strength: = 71.9 − 37.9 × (ILT^1/2 − 0.81) − 15.6×(NORD −

2.46) − 21.3 × HIST+19.3 × SEX (1)

Where ILT= Thickness in cm of Intraluminal Thrombus; NORD= Ratio between

AAA max diameter and non-aneurysmatic aorta diameter; HIST=0.5 in case

of positive familiary history for AAA,-0.5 otherwise; SEX=0.5 for male patient,

-0,5 for female patient

4 (1) Van de Geest JP, Wang DHJ, Wisniewski SR, Makaroun SM, Vorp DA. Towards A Noninvasive Method for Determination of

Patient-Specific Wall Strength Distribution in Abdominal Aortic Aneurysms. Annals of Biomedical Engineering, Vol. 34, No. 7,

July 2006 ( C 2006) pp. 1098–1106

RPI how to calculate it

5

CT Scan

Image Segmentation

Geometric Model creation

F.E. Model creation

Model solution and index calculation

Good CT scan required

Expensive proprietary

software required

Dedicated hardware

required

Engineering skill

required to assess the

quality of the analysis

Off-line analysis:

(1 hr from CT to results)

Another Approach: based upon haemodynamic

indicators from 2d/3d models

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CDU

Geometry recognition

CFD, FSI mesh

Input (jpeg or Dicom)

Wss

Shear Rate

OSI

Risk factors

calculation,

evolutivity or CT

2D instead 3D models: rationale

7

CT scans required, or even a good US image

Only Open Source used (Gmsh or Netgen for meshing, CSC

Elmer for analysis)

Standard hardware required

Very short analysis time: from image to results (10 mins)

Cheap and affordable approach

Implementable even during a US routinary check

Haemodinamic risk indicators (WSS, OSI)

8

Wall Shear Stress (WSS) is the frictional force per unit area acting on the

inner vessel wall as a result of a flow of viscous blood.

Malek AM, Alper SA, Izumo S “Hemodynamic Shear Stress and Its Role in Atherosclerosis”

AMA. 1999;282(21):2035-2042.

OSI

Oscillatory Shear Index (OSI) is used to identify regions on the vessel

wall subjected to highly oscillating WSS values during the cardiac

cycle. These regions are usually associated with bifurcating flows and

vortex formation that are strictly related to atherosclerotic plaque

formation and fibrointimal hyperplasia.

• Low OSI values occur where flow disruption is minimal

• High OSI values (with a maximum of 0.5) highlight sites where the

instantaneous WSS deviates from the main flow direction in a large

fraction of the cardiac cycle,inducing perturbed endothelial alignment.

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Methods

CTA scans were coupled with computational fluid dynamics (CFD) evaluation performed using open source software

ElmerSolver, CSC Institute of Technology, Finland.

10

Results: 143 pts

11

2D

3D

rAAA rAAA rAAA

Distribution of the 2D-3D CFD parameters OSI (A), TAWSS (B) and RRT (C) vs. the presence of non aneurysmatic aorta, AAA, or ruptured AAA.

2D OSI

Results: 143 pts

12

2D

3D

rAAA rAAA rAAA

Distribution of the 2D-3D CFD parameters OSI (A), TAWSS (B) and RRT (C) vs. the presence of non aneurysmatic aorta, AAA, or ruptured AAA.

2D OSI

AAA Rupture RISK SCORE

multivariate analysis

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B Constant 1.746 OSI

<0.3 -0.804

0.3-0.48 -0.406

>0.48 0

AAA diameter <5.5 cm -0.552

5.5-7 cm -0.047

>7 cm 0 Diabetes -0.255

The Risk Score for AAA rupture

AAA I

LOW RISK - RR <0.5% per

annum

<2.3

AAA II

MODERATE RISK: RR 1% per

annum

2.3-6.5

AAA III

HIGH RISK: RR >50% per

annum

>6.5

AAA rupture risk score

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CLINICAL RELEVANCE

For small AAAs: Low risk patients (class AAA I) could be followed-up as reported by current guidelines (AAAs 3.0-4.0 cm in size require yearly ultrasound surveillance, with half-yearly follow-up if enlargement is noted to be greater than 10% per year; AAAs 4.0-5.5 cm in size require 6 monthly abdominal ultrasound).

Moderate AAA risk patients (AAA II) could be followed at 3-month intervals.

High AAA risk patients (AAA III) could be offered to undergo a repair operation even if the 5.5 cm threshold has not been reached yet according to our scoring system.

For large AAAs: A delayed repair for AAA>5.5 cm with a reduced risk of rupture in old patients with many comorbidities (AAA I class according to our study), could be hypothesized. Therefore, a

SCREENING: Another possible role of the score herein proposed is its possible combination with an AAA screening programme. In fact, our ongoing research is to combine 2D CDU images to CFD evaluation and give a quick risk of AAA rupture to each screened patient in order to offer an accurate follow-up or treatment.

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16

WSS at the systole

WSS at the diastole

Velocity

An example

17

An example An example

A ruptured AAA

OSI

18

WSS at the systole

WSS at the diastole

Velocity

An example

A ruptured AAA

OSI

19

A future prospective:

from ultrasound

38 patients with coupled 2D images and CT scan

2D vs 3D geometries

20

US Image

2D Model

3D Model

Results from structural analysis of the

3D model

21

Von Mises

Stress

RPI (or

PWRR) >

100%

Patient at

High Risk

(Wall

Strength

5.83 E5 Pa)

2D Risk evaluation: OSI Index

22

OSI Index

2D Risk evaluation: OSI Index

23

OSI Index distribution

calculated from a 2d model

is not incoherent with Von

Mises as calculated from a

3D model

Remarks

The use of 2d model, deduced from a US scan, allows

a risk assessment in this case comparable with the

one produced by a 3D analysis

In order to understand if the 2d approach is a feasible

approach we compared the results got from 18 patients

with 2d OSI indicator and 3D RPI indicator (8 pts with

no AAA and 10 with ruptured AAA)

If the use of 2d models is comparable with the use of

3d model, the healthy patients and the ruptured AAA

should be selected in the same way and should give

the same risk evaluation

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Comparing 2d OSI & 3D RPI

The RPI based risk indicator is:

If AAA diam > 4.5 cm && RPI > 50%

Risk presence

Else

No Risk

The OSI based risk indicator is:

If AAA diam > 4.5 cm && OSI > 0.3

Risk presence

Else

No Risk

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Comparison

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Pt. ID Age Sex Diam [cm.] Wall Strength [Pa] Von Mises Stres [Pa] RPI 3D OSI 2D Risk RPI Risk OSI

Pz1 77 F 1.938 1.05075E+06 1.73000e+05 16.46% 0.494 NO NO

Pz2 68 M 2.153 1.23186E+06 1.34726E+05 11.00% 0.106 NO NO

Pz3 77 F 2.243 1.031726E+06 1.95000E+05 18.90% 0.133 NO NO

Pz4 68 M 2.566 1.199602E+06 3.72000E+05 31.01% 0.140 NO NO

Pz53 69 F 2.681 1.020478E+06 1.77000E+05 17.34% 0.114 NO NO

Pz211 63 M 3.379 1.193518E+06 2.10213E+05 17.61% 0.166 NO NO

Pz213 81 M 3.001 1.216672E+06 5.76500E+05 47.38% 0.083 NO NO

Pz214 75 F 2.906 1.301486E+06 3.28100E+05 31.81% 0.135 NO NO

Pz128 63 M 7.502 1.91266E+05 1.640000E+06 857.45% 0.473 YES YES

Pz130 83 M 6.150 5.41050E+05 3.051000E+06 563.90% 0.497 YES YES

Pz131 82 M 6.470 5.16090E+05 7.08900E+06 137.36% 0.422 YES YES

Pz132 77 F 7.069 1.00000E+05 1.348000E+06 1348.00% 0.479 YES YES

Pz135 85 F 6.761 4.11399E+05 5.80000E+05 140.98% 0.497 YES YES

Pz136 81 M 9.424 1.00000E+05 1.380000E+06 1380.00% 0.5 YES YES

Pz137 90 M 8.515 1.00000E+05 6.70000E+05 331.11 0.499 YES YES

Pz143 65 M 4.570 6.57015E+05 1.360000E+06 207.00% 0.310 YES YES

Pz145 74 M 9.377 2.89383E+05 1.194000E+06 412.60% 0.499 YES YES

Pz216 84 M 6.749 3.52413E+05 7.91000E+05 224.45% 0.494 YES YES

Von Mises Stress is calculated using 3d models from CT Scan, with non linear HyperElastic Solver (Code Aster)

Wall Strentgh is calculated according to (1)

OSI index is calculated using 2d models created from 2d sections of a CT scan, using Elmer CSC CFD solver

(1) Vande Geest JP, Wang DHJ, Wisniewski SR, Makaroun SM, Vorp DA. Towards A Noninvasive Method for Determination of Patient-Specific Wall

Strength Distribution in Abdominal Aortic Aneurysms. Annals of Biomedical Engineering, Vol. 34, No. 7, July 2006 ( C 2006) pp. 1098–1106

Identical risk evaluation for 2d and 3d models

Comparison

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Pt. ID Age Sex Diam [cm.] Wall Strength [Pa] Von Mises Stres [Pa] RPI 3D OSI 2D Risk RPI Risk OSI

Pz1 77 F 1.938 1.05075E+06 1.73000e+05 16.46% 0.494 NO NO

Pz2 68 M 2.153 1.23186E+06 1.34726E+05 11.00% 0.106 NO NO

Pz3 77 F 2.243 1.031726E+06 1.95000E+05 18.90% 0.133 NO NO

Pz4 68 M 2.566 1.199602E+06 3.72000E+05 31.01% 0.140 NO NO

Pz53 69 F 2.681 1.020478E+06 1.77000E+05 17.34% 0.114 NO NO

Pz211 63 M 3.379 1.193518E+06 2.10213E+05 17.61% 0.166 NO NO

Pz213 81 M 3.001 1.216672E+06 5.76500E+05 47.38% 0.083 NO NO

Pz214 75 F 2.906 1.301486E+06 3.28100E+05 31.81% 0.135 NO NO

Pz128 63 M 7.502 1.91266E+05 1.640000E+06 857.45% 0.473 YES YES

Pz130 83 M 6.150 5.41050E+05 3.051000E+06 563.90% 0.497 YES YES

Pz131 82 M 6.470 5.16090E+05 7.08900E+06 137.36% 0.422 YES YES

Pz132 77 F 7.069 1.00000E+05 1.348000E+06 1348.00% 0.479 YES YES

Pz135 85 F 6.761 4.11399E+05 5.80000E+05 140.98% 0.497 YES YES

Pz136 81 M 9.424 1.00000E+05 1.380000E+06 1380.00% 0.5 YES YES

Pz137 90 M 8.515 1.00000E+05 6.70000E+05 331.11 0.499 YES YES

Pz143 65 M 4.570 6.57015E+05 1.360000E+06 207.00% 0.310 YES YES

Pz145 74 M 9.377 2.89383E+05 1.194000E+06 412.60% 0.499 YES YES

Pz216 84 M 6.749 3.52413E+05 7.91000E+05 224.45% 0.494 YES YES

Von Mises Stress is calculated using 3d models from CT Scan, with non linear HyperElastic Solver (Code Aster)

Wall Strentgh is calculated according to (1)

OSI index is calculated using 2d models created from 2d sections of a CT scan, using Elmer CSC CFD solver

(1) Vande Geest JP, Wang DHJ, Wisniewski SR, Makaroun SM, Vorp DA. Towards A Noninvasive Method for Determination of Patient-Specific Wall

Strength Distribution in Abdominal Aortic Aneurysms. Annals of Biomedical Engineering, Vol. 34, No. 7, July 2006 ( C 2006) pp. 1098–1106

Identical risk evaluation for 2d and 3d models

95 % coincidence in

risk evaluation using

RPI & OSI

Conclusions

The use of 2d models seems a promising alternative

approach to the conventional RPI calculations based upon

3d models derived from CT scan

In a near future it seems to be possible to use 2D

ultrasound images for calculating aneurysm rupture risk.

28

A potential selective treatment and follow-up could be offered to patients with either a small or a large AAA on the basis of the individual risk of AAA rupture.