Digital Imaging Protocols for Pediatric Echo

"Because."

This was the explanation I was given, very early in my introduction to "digital echo", about why we record These Views in This Order. At the time, I was coming from a lab that did things proper: starting with the subcostal views. The only sense this new "parasternal images 1st" protocol made was that it supposedly made reading the studies easier.
How convenient.

For you.

Who is this protocol for anyhow?

I insist that the marriage of the image acquisition protocol with the ordered reviewing of said images is a potential liability. Always starting with the parasternal view is fine for most hearts— most hearts are nearly normal. The problem, in my opinion, with starting with the parasternal view is: it presumes that things are normal, or are nearly normal, or that I can at least make something up to look passably normal.

If things are not normal (this is what we're supposed to be particularly good with in Peds, isn't it?) this type of protocol presumes too much: that I already know enough about the heart to make some sense of the parasternal views. Try this on: what is the PLAX view for a patient with dextrocardia, DORV, and pulmonary atresia supposed to look like? How about HLHS? In order to record meaningful parasternal long axis views of these types of abnormal hearts, the sonographer has to either:

• immediately recognize the pathology from this one clip
• spend time scanning from subcostals and apicals first (in order to sort it out) then return to the "starting point"- the parasternal views.

The first option is not a fair predicament for most sonographers (including physicians), and the second- grossly inefficient.

The Images are for Physicians

Certainly, I appreciate that in order to report the anatomy, arrangement, size, and function of the examined heart some considerable structure is required. There must be images that support and document our conclusions. And, as we are increasingly moving towards structured reporting, the structure of the underlying, supporting images must also evolve. I have no problem with this, in fact, I embrace it. It's the "absence of evidence is not evidence of absence" philosophy, taken to it's logical conclusion. We don't want anyone to report anything that our images can't substantiate. The fact that physicians will determine and require a certain, precise collection of images is undisputed. They may choose and prefer to review them in any particular order. Bully for them.
Our obligation is to provide these images.

I simply prefer to do it in a manner that is most efficient for me.

The Protocol is for Sonographers

What is really needed to improve our exam consistency is a system that allows for the flexible acquisition of any prescribed (minimum) set of images. On a small scale, we are already doing this with stress echo, particularly with exercise stress echo: you grab what you can, when you can, and sort it out later. The order of collection is irrelevant, but the presentation of the images, in order, is everything. I can't tell you how many fetal echos I have done that would have been greatly improved by the ability to collect the images as I saw them, and then sort them into a logical arrangement later. Not to mention every "new blue" dextrocardia-aortic-atresia-single-ventricle-goat-wreck (Goat Rodeo + Train Wreck, contracted form), I have done since the inception of the current "parasternals 1st" protocol.

I am eager to see what the new Philips iE33's SmartExams are all about.

• Philips' SmartExams announcement
• SmartExams introduced to cardiology by way of new iE33
• Philips appearing to work harder on this front than anyone else

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Lately, I have been tinkering about with a collection of image acquisition protocols suitable for pediatric echo.
In addition to providing a basis for building our own structured, protocol-driven exams, I believe these could also turn into a fairly useful teaching tool (I still need more descriptions/images though).

Line Fitting for Pediatric Cardiology (and everyone else)

Described as "one of the fundamental tasks of scientific inquiry", model selection could consume the better part of an afternoon and an important part of one's budgeted time with a statistician.

Enter ZunZun.com.

If you're looking for quality curve fitting and surface fitting, this is the site for you!

The power law applied by Sable et al. in their description of coronary artery reference values caught my attention. Particularly, the scaling exponents for the individual coronary arteries are all different, and not what I would have intuitively guessed them to be, based on the principle of geometric similarity. So, I wanted to test a theory: perhaps the coronary arteries scale well with something besides BSA.

Consider this small data set of 10 hypothetical patients:

Ht (cm)	WT (kg)	BSA (Haycock)
57	6.1	0.3187
61	7	0.3525
83	12.6	0.5464
98	14.2	0.6223
104	16.6	0.6930
120	20.5	0.8215
148	41	1.2961
172	88.6	2.0820
176	58	1.6729
178	65.5	1.7940

From this I predicted the diameter of the LAD and height-based LV mass for each hypothetical subject.
I then constructed a second table of super hypothetical data:

LV Mass (g)	LAD (mm)
16.86	1.38
19.19	1.44
34.42	1.72
45.69	1.82
50.17	1.90
63.28	2.04
99.64	2.46
149.46	2.99
158.99	2.73
163.79	2.81

Then I did some line fitting:

The model fitted is:

y = a * x^b

The reported coefficients are:

a =  5.2619076425282296E-01
b =  3.3269001508780827E-01

The "b" term is the scaling exponent: 0.333.
That is to say, in this small sample of hypothetical data, the LAD (a linear measure) scales with LV mass (a volumetric measure) to the 1/3 power.
Maybe that is just random.
Or, maybe that is just… cool.

 

Of course, selection of the best model depends on numerous factors some of which are the regression "fit" statistics and things like the "Bayesian information criterion". Excel won't report these bits, but ZunZun.com throws a bunch at you.

It's free, by the way- unlike the statistician's time.

2D Area-Length LV Mass Calculator

I much prefer the 'ellipse tool' to the default method of tracing borders with the trackball. Plus, it is quick, pretty, and is more consistent with the principle behind the calculation.

Height (cm):
Epicardial Area (cm2):
Endocardial Area (cm2):
LV Long Axis (cm):
LV Mass (g):
Z-Score:

Notes:

• Measure at end diastole (End diastole can be defined at the onset of the QRS, but is preferably defined as the frame after mitral valve closure or the frame in the cardiac cycle in which the cardiac dimension is largest.)
• Measure areas at the midventricular short axis view, at the level of the papillary muscle tips- generally the widest short axis diameter.
• Measure the LV length from apex to plane of MV annulus, in A4C or A2C (largest) It is recommended that the basal border of the LV cavity area be delineated by a straight line connecting the mitral valve insertions.
• Z-Scores are 'off label' (source article used M-Mode derived LV mass)

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Recommendations for Chamber Quantification, JASE, December 2005

Recommendations for Quantification of the Left Ventricle by Two-Dimensional Echocardiography, JASE, 1989

A novel method of expressing left ventricular mass relative to body size in children.

Foster BJ, Mackie AS, Mitsnefes M, Ali H, Mamber S, Colan SD.

Circulation. 2008 May 27;117(21):2769-75.

New Coronary Artery Z-Score Calculator

The folks over at Children's National Medical Center, Washington, D.C. (CNMC) have fired up their digital echo database: in a four month period, they sorted through over 400 eligible normal echos, and served up the largest analysis of normal coronary artery dimensions to date.

Their approach to the data analysis included explorations of the independent variables of BSA and height (and height, raised to the 2.7 power). Analysis of the varying independent measures and relationships demonstrated that the "best fit" model was the exponential model using BSA, or what is also known as the allometric model. Landing on this manner of analysis is not just fortuitous happenstance- numerous other investigations have come to the same conclusion regarding the scaling of cardiovascular structures. It is interesting to note that other recently published z-score data landed on a unique and quite different model (nonlinear polynomial fit).

Considering their allometric model, the scaling exponents of each of the coronary arteries calculated in this analysis are quite similar, but are not identical. Also, the scaling exponents are all very near 0.4-- not 0.5 as might be predicted by the theory of dimensional consistency (linear measurement of the coronary artery scaled to body surface area, i.e., cm vs. cm²). Actually, this comes as no surprise, given that the true nature of the relationship is (probably) a complex cascade between lean body mass, cardiac output, wall tension, and LV mass. Imperfect estimations of BSA are only peripherally related to some of these factors. It makes me wonder what the relationship would look like if we scaled/standardized the coronary artery diameters to LV mass instead of BSA.

Comparing this data to prior work, the authors note a very close correlation with the data from Boston, and they very politely admit some similarities to the data from Singapore (although, to be fair to the Singapore analysis it should be noted that they sought to make an internally standardized reference- indexing to the aorta- and thus their treatment of the relationship to BSA is not very robust). The authors have already done their own "smackdown" and their graphic comparison of the CNMC and Boston data is unsurprising. Moreover, the models and scaling exponents are remarkably similar. Here are the two LMCA prediction equations:

CNMC*:

 

Boston:

  

 

* note: the CNMC equation is the alternate/equivalent form of their published equation: ln(M) = beta₁ + beta₂ x  ln(BSA)

If we discount the Boston y-intercept of -0.02887, as being so small as to be very nearly zero ( or, "not significantly different from zero"), the equations become all the more similar. We are then left with the primary difference between the z-score predictions being: the manner in which they deal with variance. The Boston group attempts to predict the standard deviation by a second regression equation, and the CNMC group takes the approach, now currently in vogue, of substituting the regression RMSE as the SD. The validity of either approach could(should?) probably be debated…

In the words of the authors:

Having a readily available Z-score calculator will be invaluable

Give it a go at ParameterZ.com.

I admit to taking a few liberties with this calculator: I convert the measurements to mm; I use the Haycock BSA formula rather than DuBois & DuBois (can't we just agree to do this already?); I use the 5th and 95th percentiles (± 1.65 SD's) for the limits on the range of normal values.

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Coronary Artery Z Score Regression Equations and Calculators Derived From a Large Heterogeneous Population of Children Undergoing Echocardiography.

Laura Olivieri, Bob Arling, Mark Friberg, Craig Sable. Journal of the American Society of Echocardiography December 2008 (Article in Press DOI: 10.1016/j.echo.2008.11.003)

Theoretical and empirical derivation of cardiovascular allometric relationships in children.

Sluysmans T, Colan SD. J Appl Physiol. 2005 Aug;99(2):445-57. Epub 2004 Nov 19.

Allometric analysis of the association between cardiac dimensions and body size variables in 464 junior athletes.

George K, Sharma S, Batterham A, Whyte G, McKenna W. Clin Sci (Lond). 2001 Jan;100(1):47-54.

Derivation of a size-independent variable for scaling of cardiac dimensions in a normal adult population.

Neilan TG, Pradhan AD, Weyman AE. J Am Soc Echocardiogr. 2008 Jul;21(7):779-85. Epub 2008 Mar 10.

Does size matter? Clinical applications of scaling cardiac size and function for body size.

Dewey FE, Rosenthal D, Murphy DJ Jr, Froelicher VF, Ashley EA. Circulation. 2008 Apr 29;117(17):2279-87. Review.

Regression Equations for Calculation of Z Scores of Cardiac Structures in a Large Cohort of Healthy Infants, Children, and Adolescents: An Echocardiographic Study.

Pettersen MD, Du W, Skeens ME, Humes RA. J Am Soc Echocardiogr. 2008 Aug;21(8):922-34. Epub 2008 Apr 11.

A Novel Method of Expressing Left Ventricular Mass Relative to Body Size in Children.

Foster BJ, Mackie AS, Mitsnefes M, Ali H, Mamber S, Colan SD. Circulation. 2008 May 27;117(21):2769-75. Epub 2008 May 19.

Coronary artery involvement in children with Kawasaki disease: risk factors from analysis of serial normalized measurements.

McCrindle BW, Li JS, Minich LL, Colan SD, Atz AM, Takahashi M, Vetter VL, Gersony WM, Mitchell PD, Newburger JW; Pediatric Heart Network Investigators.
Circulation. 2007 Jul 10;116(2):174-9. Epub 2007 Jun 18.

Coronary normograms and the coronary-aorta index: objective determinants of coronary artery dilatation.

Tan TH, Wong KY, Cheng TK, Heng JT. Pediatr Cardiol. 2003 Jul-Aug;24(4):328-35. Epub 2002 Sep 25.

Ascending Aorta Z-Score Calculator

A z-score calculator for the ascending aorta (AAO), based on this article, is now available at ParameterZ.

The source article is relatively recent (2006) and confirms my own experience: z-score data for the ascending aorta are hard to find.

We provide for the first time a published regression equation for calculation based on BSA of the expected size of the ascending aorta in children, which allows calculation of z scores.

Their data is based on a sample of 88 normal patients- the sample size was chosen to match their group of patients with bicuspid aortic valve. Technically speaking, this sample size is too small to be used to construct reference values. The demographic data describing the reference population is not provided.

The manner of z-score prediction was modeled after Daubeney et al., for "consistency with the prediction equations... used for other structures in our echocardiographic laboratory". Personally, I think that the "transform both sides" technique (regressing the log of both the BSA and the AAO measurements) is perfectly reasonable for modeling this relationship. However, I continue to have misgivings about the patent substitution of the regression root mean square error for the sample standard deviation- particularly for the purpose of calculating a z-score.

In the absence of any other AAO z-score equations, I used the following two manners to cross-check the Halifax data:

1. The "internally standardized" approach of Sheil et al., using the observed consistent ratio between the size of the AAO and the aortic annulus: 1.16. I used the Boston aortic valve z-score data in combination with their ratiometric approach- I call these the Derived AAO values.
2. Data from UCLA was used to generate z-scores for an exploration of dilated aortic root in children with bicuspid aortic valves. Their published data provide us with a formula for predicting a height-based mean value for the AAO.

Height (cm):
Weight (kg):
BSA:
Method	AOV Mean	AAO Mean	Range	AAO/AOV
Halifax :
Derived :
UCLA:

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Dilatation of the ascending aorta in paediatric patients with bicuspid aortic valve: frequency, rate of progression and risk factors.

Warren AE, Boyd ML, O'Connell C, Dodds L. Heart. 2006 Oct;92(10):1496-500. Epub 2006Mar 17.

Echocardiographic assessment of aortic root dimensions in normal children based on measurement of a new ratio of aortic size independent of growth.

Sheil ML, Jenkins O, Sholler GF. Am J Cardiol. 1995 Apr 1;75(10):711-5.

Validation and re-evaluation of a discriminant model predicting anatomic suitability for biventricular repair in neonates with aortic stenosis.

Colan SD, McElhinney DB, Crawford EC, Keane JF, Lock JE. J Am Coll Cardiol. 2006 May2;47(9):1858-65. Epub 2006 Apr 17.

Frequency of aortic root dilation in children with a bicuspid aortic valve.

Gurvitz M, Chang RK, Drant S, Allada V. Am J Cardiol. 2004 Nov15;94(10):1337-40.

Two-dimensional echocardiographic aortic root dimensions in normal children and adults.

Roman MJ, Devereux RB, Kramer-Fox R, O'Loughlin J. Am J Cardiol. 1989 Sep1;64(8):507-12.

Interpretation of echocardiographic measurements: a call for standardization.

Vasan RS, Levy D, Larson MG, Benjamin EJ. Am Heart J. 2000 Mar;139(3):412-22.

Relationship of the dimension of cardiac structures to body size: an echocardiographic study in normal infants and children.

Daubeney PE, Blackstone EH, Weintraub RG, Slavik Z, Scanlon J, Webber SA. CardiolYoung. 1999 Jul;9(4):402-10.