Head

1
Head Cup Simulator

• Why do we use simulator?
• To verify the accuracy of new methods.
• When we invent a new measuring method,
  it is important to verify its accuracy and
  reliability. Many methods have been published,
  including using a special machine (see left
  picture, Fig. 1) 1, in which anteversion,
  inclination, and three directions wearing can be
  adjusted manually. Another method is to fabricate
  a cup inside plastic material with fixed
  orientation and wearing parameters. All these
  published methods are good but expensive. We
  propose an automatic, cheaper, and more accurate
  computer method to do the same thing.
• To simulate every control condition.
• For mechanical devices, to accurately
  adjust the orientation and wearing parameters is
  difficult. It is also hard to prove it. With
  computer, every condition is easy to simulate.
• To reduce noise in early development of new
  methods.
• In reality, noise is inevitable, but
  in simulated situation, noise is removable. In
  the early stage of developing a method, noise
  will always bother us. With the use of simulator,
  noise is removed, and we can focus more on the
  real measurement, thus facilitating the
  development.

Fig. 1. A mechanical device for
simulating wearing of every anteversion and
abduction from JBJS 1.
2

• How does the simulator work?
• Line tracing method
• We simulate every X-ray beam
  traveling from source to the film. The simulated
  prosthesis projection will be calculated. The
  total thickness of metal is estimated and then we
  translate to gray level of the simulated X-ray.
• Why not using OpenGL or DirectX?
• DirectX is the 3D tool of Windows. The OpenGL
  is the open source version of 3D tool. They are
  useful and effective in virtual reality. They
  are good in drawing non-transparent object. In
  our case, the X-ray beam is a highly penetrating
  radiation. We are drawing a semi-transparent
  object. It is hard to use OpenGL or DirectX,
  although they are quite good in performance.
• Absorption law
• The X-ray is a kind of radiation beam with
  high energy. It follows the general rule of
  absorption.
• Beer-Lambert law
•                          -kbcPenetration
  ek molar absorbability
  (a)
• b path length
• c concentration
  (b)
• It is hard for us to use it on our simulator.
• Absorption example (Fig. 2)
• Lookup table method
• The simulated X-ray was analyzed. We build a
  table with known thickness, in which we can
  deduce its photo-density on X-ray. We then look
  up the table, interpolate the data and then get
  the result of photo-density.

Fig. 2. (a) A metal model made of titanium with
1, 2, , 5mm thickness. (b) Its X-ray image.
3
PE Wear Meter

• What did we do before?
• In the past, we measured PE wear manually. A
  well accepted method is Livermores method (Fig.
  3) 2. He finds the center of femoral head,
  measures the thinnest PE, and then reads the
  wear.
• Whats new?
• Fig. 4a. Hardinges method
  Fig. 4b. Shavers method (need to point out
  p1, p2, p3)

Fig. 3c. Then measure it.
Fig. 3b. Find the thinnest polyethylene.
Fig. 3a. Livermores method, find head center.
4

• Our method
• Find head-neck junction by cross-correlation
• Fig. 5. Make a template and mark corresponding
  head-neck junction and the indicated place.
• At first, we make an ordinary X-ray with
  template. Then we mark the important landmark and
  pointout the indication from it. The program will
  use cross-correlation method, find the
  corresponding landmark on the other X-rays, and
  then find the indicated place. This procedure is
  the most time-consuming procedure and costs about
  60 seconds (Pentium 500MHz computer). This is
  also our original contribution to this method.
• Project 200 lines from indicated place to upper
  right side with about 135 degrees span.
• Detect edges with vector edge detector.
• Using vector edge detector subroutine, we
  detect the shell edges. These edges are rechecked
  again and again in order to remove noise such as
  screw or others. We consider currently published
  edge detectors unsuitable, so we invent a new
  one. It detects vectory edges, so we called it
  vector edge detector.

5

• Our method (cont.)
• Find center from the 200 detected edges.
• The center of the 40 edges are found by
  calculus. Then the program will exclude the
  extremes and find center again and again, until
  there are no extremes.
• Project 240 lines from the new center with 270
  degrees span. The lower left part is excluded.
• Find head edges with the same vector edge
  detector.
• Find the head center
• Again, the center of femoral head is found with
  exclusion of extremes.
• Check centers by Hill-Climbcing Search 7
• Compare the two centers, and find the
  displacement vector.

• .

6
Materials Methods

• Simulated data
• 64 simulated X-rays with 2 different anteversion
  angles, 2 different abduction angles, 4 different
  superior wears, and 4 different medial wears.
• We measure these simulated X-rays automatically
  by our Auto PE Wear Meter program.
• The results are compared.
• Real X-rays
• We digitized 88 total hip arthroplasty X-rays
  using Sony S70 digital camera size (20481680).
• The camera was set with the same distance and
  same zoom.

7

• Real X-rays (Cont.)
• There is no exclusion criteria of digitization.
• Results classification
• Wrong detection on cross-correlation
• Wrong detection of acetabulum
• Wrong detection of head
• Minor error on acetabular center estimation
• Minor error on head center estimation
• Unmeasurable X-ray by Livermores method
• Partially measurable X-ray, which can be measured
  by other method
• Measurable X-ray by Livermores method

8
Results

• Simulated data
• -Our program can detect 61 of 64 simulated X-rays
  without misdetection (Fig. 6).
• -The three mis-detected X-rays images were due to
  misdetection of acetabulum (Fig. 7).
• The error on measuring medial directional wear
  using our program is -0.0230.176mm.
• The error on measuring upper wear using our
  program is
• -0.1520.315mm.

Fig. 6. Four examples of successful detection
Fig. 7. The three misdetections.
9

• Real X-rays
• 47 excellent detections
• 2 unknown errors
• 3 wrong detections on cross-correlation (Fig. 8)
• 23 wrong detections of acetabulum (Fig. 9)
• 3 wrong detections of head (Fig.10)
• 10 minor errors on acetabular center estimation
  (Fig. 11)
• 0 error on head center estimation
• 19 unmeasurable X-rays by Livermores method
  (Fig. 12)
• 49 partially measurable X-rays, which can be
  measured with instrument (Fig. 13)
• 21 measurable X-rays by Livermores method (Fig.
  14)

Fig. 8. Wrong detection due to cross correlation.
Fig. 9. Wrong detection on finding acetabulum.
Fig. 10. Wrong detection on finding head.
Fig. 11. Minor error on fitting the circle with
acetabulum edges.
Fig. 12. Head-acetabulum edges are too unclear
to use Livermores method.
Fig. 13. With instrument, the thinnest edges can
be detected by other edges.
Fig. 14. Measurable by Livermores method.
10

• 2 X-rays measurable by program but unmeasurable
  manually
• 27 X-rays measurable by program but unmeasurable
  by Livermores method
• 24 X-rays measurable manually but unmeasurable by
  program
• 8 X-rays measurable by Livermores method but
  unmeasurable by program

Fig. 15a. Head edges are unclear to be detect
manually.
Fig. 15b. Our program can detect the edges and
find the best fitting circle.
Fig. 16a. Unmeasurable by Livermores method.
Fig. 16b. The program can measure it.
Fig. 17a. Measurable manually.
Fig. 17b. Misdetection by our program.
Fig. 18b Misdetection by our program.
Fig. 18a. Measurable by Livermores method.
11
Discussion

• In the simulated data, error in medial wear is
  -0.0230.176mm and error in upper wear is
  -0.1520.315mm.
• Compared with literature 16, in which the
  error listed was 0.1mm, our method is as good as
  other computer-assisted methods.
• Our program is the first fully automatic program
  in which no human intervention is needed for
  detection.
• Detection rate
• Our program 54.5 (40/88).If we accept minor
  error, the rate becomes 65.9 (58/88).
• Livermores method 23.9 (21/88)
• Others 78.4 (69/88)

12

• Reasons of misdetection
• Low kv
• As we know, the kv of X-rays will change the
  penetration power. When the kv is low, the
  penetration power is low. On the other hand, when
  the kv is high, the penetration power is high. If
  the kv is too low, the bone and prosthesis will
  be saturated as white. If the kv is adjusted
  high, the prosthesis will be whiter. That makes
  detection easy.
• Screw noise
• The screws of acetabulum are located just above
  it. That is the place where our program detects
  edges for estimating acetabulum center.
  Sometimes, the screws cause noises and
  misdetections.
• Bone noise
• The edges of bone will cause white lines on
  X-rays. If the white lines intersect the
  prosthesis edges, they may cause misdetection.
• Distortion
• X-ray filming
• When the X-rays pass through body to film,
  there are grids between body and film to filtrate
  scattering. The grids may cause torsions and make
  circles became ellipses.
• Digitizing
• There are several devices for digitizing
  X-rays. The digital cameras take pictures through
  lens. The lens will cause distortion.
• Validation
• Currently, we have not tested our program on
  revision hip arthroplasty, which is to measure
  wears after removal of polyethylene and compare
  it with preoperative X-rays. This should be our
  future work.

13
Conclusions

• We designed a program which can automatically
  measure polyethylene wear. We have tested it on
  simulated X-rays and the result is encouraging.
  Clinical validation is needed in future work.

14
Authors

• Liaw Chen-Kun, MD, Visiting Staff, Department of
  Orthopaedic Surgery, En Chu Kong Hospital
• Wu Tai-Yin, MD, Fellow, Department of Family
  Medicine, Jen-Ai General Hospital
• Hou Sheng-Mou, MD, Professor, Department of
  Orthopaedic Surgery, National Taiwan University
  Hospital
• Yang Rong-Sen, MD, Professor, Department of
  Orthopaedic Surgery, National Taiwan University
  Hospital
• Fuh Chiou-Shann, PhD., Professor, Department of
  Computer Science and Information Engineering,
  National Taiwan University
• Liaw Shong-Hon, MD, Resident, Department of
  Emergency, Sin-Lau Christial Hospital
• Wu Chang-Chin , MD, Visiting Staff, Department of
  Orthopaedic Surgery, En Chu Kong Hospital
• Tai Han-Cheng , MD, Visiting Staff, Department of
  Orthopaedic Surgery, En Chu Kong Hospital
• Liu Dah-Hsiang , MD, Visiting Staff, Department
  of Orthopaedic Surgery, En Chu Kong Hospital

15
Institutions

• En Chu Kong Hospital
• National Taiwan University Hospital
• Department of Computer Science and Information
  Engineering, National Taiwan University

16
Reference

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