DISCUSSION
First of all we would like to mention the grea-
test drawback to our study: Inaccuracy due to
magnification effects taking radiographs and
inaccuracy of defining the points of measure-
ments and measurement itself. We think we
could avoid the magnification effect by com-
paring the fibula length pre and postoperative-
ly (Table 2). We did not see big differences
here. As we believe this is the result of stan-
dardised methods and an experienced staff
taking the radiographs.
Calculating the average leg out of our measu-
rements gives us a triangle with the side a
being 36.3 cm and side b being 44.9 cm long.
In a model we can now calculate side c_pre.
Choosing the angle 195° or 165° we can cal-
culate side c_pre being 80.5 cm. Now we can
calculate c_predictive (
γ
now being 180°) the
result is a leg length of 81.2 cm. In this model
calculation of an average leg we will achieve a
leg lengthening of 0.7 cm by correcting the
angel. This gives us an idea of the estimated
lengthening after angle correction of 15°. This
value lies also in the range of the mean leng-
thening after TKA of 0.54 cm calculated out of
our data (Table 1). (Mean(total)c_post81.28cm
– mean(total)c_pre80.7cm=0.54cm.)
By calculating all the differences between the
predicted and postoperative leg lengths we
could define a mean error of 0.55 cm between
predicted leg lengths and measured leg lengths
after TKA. This lies below the mean error of
0.7 cm calculated by Kessler 2 for length
changes in tibial osteotomy with angular cor-
rection. This higher accuracy may be the result
of calculating c_predictive with angle
γ
post-
operative rather than just adding a_pre and
b_pre together. This is of course a result of our
retrospective study in which we used
γ
postop
to calculate the predictive leg length. Applying
our method preoperatively one would have to
choose
γ
180° to calculate the predictive leg
length and so one would receive more often
higher values for the difference between c_pre
and c_predictive. Our study shows, that the
bigger the deformity is the greater leg lengthe-
ning will be predicted. This is also represented
in the mean difference between c_pre and
c_post. In the valgus group this value is 1.2
cm, in the varus group 1.0 cm whereas this
value is only 0.3 cm in the normal group where
nearly no angular correction occurred.
We took the value of up to 0.5 cm difference
between (value just beneath mean error of
0.55 cm) c_post and c_predictiv to say that leg
length was predicted correctly. Values diver-
ging over 0.5 cm we analysed more exactly.
Here we could see that each value diverging
more than 0.5 cm could be satisfyingly explai-
ned by lengthening or shortening of femur
and/or tibia.
Using our method preoperatively will not pre-
vent leg lengthening because correction of the
deformity must stay a central point in TKA7-
11 to achieve good results. But this study
shows the tendency of lengthening above the
predicted length due to angular correction in
the varus and valgus groups, and there again
mainly on the tibial side (Table 4). We think it
could be helpful during operation to know the
estimated leg length. Maybe this method can
be combined with computer assisted surgery
(CAS). In this way the positioning of the
implant, the alignment [12, 13] and the resul-
ting leg length can be simulated. Starting from
the healthy condyle or tibial plateau side as
reference for our joint line we then may
achieve a greater accuracy in positioning our
implant in respect of the joint line [11].
CONCLUSION
We belief, that knowing the predicted leg
length can help to position the implant with
more accuracy. Of course in case of flexum
our method is not applicable but in these cases
a correction factor to calculate the true length
[1] may be helpful. Or the combination with
CAS could calculate the leg length and the
predicted leg length in real time on the opera-
ting table. By simulation of implant positio-
ning in combination of alignment we may so
increase accuracy and reproducibility in TKA.
14
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