Subscribe to RSS
DOI: 10.1055/s-0029-1186109
© Georg Thieme Verlag KG Stuttgart · New York
Eine neue objektivierte und validierte Methode zur Quantifizierung der Knochenneubildung in Tiermodellen auf Basis eines frei verfügbaren Bildbearbeitungsprogramms
Novel Software-Based and Validated Evaluation Method for Objective Quantification of Bone Regeneration in Experimental Bone DefectsPublication History
Publication Date:
19 October 2009 (online)
Zusammenfassung
Studienziel: Die Quantifizierung neu gebildeten Knochens im experimentellen Knochendefektmodell ist ein häufiges Problem bei experimentellen Studien. Die meisten in der Literatur beschriebenen Methoden quantifizieren den Anteil des regenerierten Gewebes semiquantitativ, mithilfe eines Scoresystems. Dieses hängt oftmals stark von der Einschätzung des jeweiligen Untersuchers ab. Das Ziel der vorliegenden Arbeit ist die Einführung einer neuen Auswertemethode zur genauen Quantifizierung von Knochenregeneration anhand digitaler Röntgenbilder mithilfe einer frei verfügbaren Bildbearbeitungssoftware (GIMP, GNU General Public Licence) und deren Evaluation, bezogen auf die Parameter Objektivität und Reliabilität. Methoden: Die Auswertemethode umfasst 5 Schritte: Standardisierung der Bilder, Definition der „Region of Interest“ (ROI), Definition des „Interval of Interest“ (IOI), Pixelanalyse und Quantifizierung der Verknöcherung mittels Histogramm, ähnlich dem Houndsfield-Index. Um die Methode bezüglich der Objektivität und Reliabilität zu validieren, wurde sie mit 2 semiquantitativen Auswertemethoden verglichen. Dafür wurden 16 Röntgenbilder zweier verschiedener Tiermodelle (Radiusdefekt am Kaninchen [A] und Tibiadefekt am Schaf [B] von 6 Untersuchern bewertet. Zur Beurteilung der Reliabilität wurde die Auswertung nach 4 Wochen unter gleichen Bedingungen wiederholt. Ergebnisse: Die Objektivität war bei der Auswertung durch die neue Methode bei beiden Tiermodellen höher als bei den Kontrollmethoden. Als Maß wurde für jede Methode der Blant-Altman-Koeffizient gebildet (Modell A: GIMP: 0,095, Kontrolle 1: 0,272, Kontrolle 2: 0,283; Modell B: GIMP: 0,098, Kontrolle 1 : 0,658, Kontrolle 2: 0,668). Ähnliche Resultate wurden für die Reliabilität ermittelt (Modell A: GIMP: 0,086, Kontrolle 1: 0,221, Kontrolle 2: 0,385; Modell B: GIMP: 0,102, Kontrolle 1: 0,339, Kontrolle 2: 0,623). Schlussfolgerung: Die vorgestellte Quantifizierungsmethode hat sich als objektives und einfach zu bedienendes Werkzeug bei der Quantifizierung von Knochenneubildungen in 2 unterschiedlichen Tierexperimenten bewährt. Es zeichnet sich durch detaillierte und genaue Messergebnisse und eine hohe Objektivität und Reliabilität unabhängig vom Tiermodell aus.
Abstract
Aim: The quantification of newly formed bone in experimental defect models is a problem in various experimental set-ups. Several methods have been described to evaluate and quantify the regeneration of newly formed bone in various animal models. Most methods only describe the amount of regenerated tissue on a semi-quantitative level, the results significantly depend on the subjective rating of the observer and such evaluation methods have not been validated in terms of objectivity and reliability. The aim of the present study was to introduce a novel evaluation method for the accurate quantification of bone regeneration on digital X‐ray images using a freely available digital image software analysis programme (GIMP, GNU General Public Licence). Methods: The method introduced here contains 5 steps: standardisation of size and colour, determination of range of interest (ROI), defining different qualities of mineralisation, pixel analysis with histogram function, similar to the Hondsfield index, and quantification. In order to evaluate the objectivity and reliability, the quantification method was compared to semi-quantitative scores described by Mosheiff and Werntz for inter- and intraobserver variability. Six observers were asked to determine bone regeneration in 16 X‐ray images of 2 different animal models. In order to describe intraobserver variability, the evaluation was repeated after a period of 4 weeks. Statistical analysis including determination of intra- and interobserver variability (Bland-Altman coefficient of reproduction) was performed using SAS software. Results: For both experimental set-ups analysed in this project (rabbit and sheep bone defects), the objectivity was significantly higher in the GIMP-based evaluation compared to the evaluation according to Mosheiff and Werntz using the Bland-Altman coefficient (rabbit: GIMP: 0.095, Mosheiff: 0.272, Werntz: 0.283; sheep: GIMP: 0.098, Mosheiff: 0.658, Werntz: 0.668). Analogous results were obtained for reliability (rabbit: GIMP: 0.086, Mosheiff: 0.221, Werntz: 0.385; sheep: GIMP: 0.102, Mosheiff: 0.339, Werntz: 0.623). Conclusion: This quantification method introduced here has proved to be a reliable and “easy-to-use” tool in order to perform objective quantification of bone regeneration in 2 different experimental set-ups. It offers a more detailed and quantitative way for precise determination of regenerated tissue and is characterised by higher objectivity and reliability compared to other semi-quantitative evaluation methods. The objectivity seems to be independent of the animal model to which the method is applied.
Schlüsselwörter
Knochenregeneration - Knochendefekt - Tiermodelle - Tissue Engineering
Key words
bone regeneration - bone defect - bone quantification - animal model - tissue engineering
Literatur
- 1 Service R F. Tissue engineers build new bone. Science. 2000; 289 1498-1500
- 2 Bauer T W, Muschler G F. Bone graft materials. An overview of the basic science. Clin Orthop Relat Res. 2000; 371 10-27
- 3 Banwart J C, Asher M A, Hassanein R S. Iliac crest bone graft harvest donor site morbidity. A statistical evaluation. Spine. 1995; 20 1055-1060
- 4 Arrington E D, Smith W J, Chambers H G et al. Complications of iliac crest bone graft harvesting. Clin Orthop Relat Res. 1996; 329 300-309
- 5 Younger E M, Chapman M W. Morbidity at bone graft donor sites. J Orthop Trauma. 1989; 3 192-195
- 6 Cancedda R, Dozin B, Giannoni P et al. Tissue engineering and cell therapy of cartilage and bone. Matrix Biol. 2003; 22 81-91
- 7 Laurencin C T, Ambrosio A M, Borden M D et al. Tissue engineering: orthopedic applications. Annu Rev Biomed Eng. 1999; 1 19-46
- 8 Werntz J R, Lane J M, Burstein A H et al. Qualitative and quantitative analysis of orthotopic bone regeneration by marrow. J Orthop Res. 1996; 14 85-93
- 9 Mosheiff R, Friedman A, Friedman M et al. Quantification of guided regeneration of weight-bearing bones. Orthopedics. 2003; 26 789-794
- 10 Oberholzer M, Ostreicher M, Christen H et al. Methods in quantitative image analysis. Histochem Cell Biol. 1996; 105 333-355
- 11 Park C H, Abramson Z R, Taba Jr M et al. Three-dimensional micro-computed tomographic imaging of alveolar bone in experimental bone loss or repair. J Periodontol. 2007; 78 273-281
- 12 Gauthier O, Muller R, von Stechow D et al. In vivo bone regeneration with injectable calcium phosphate biomaterial: a three-dimensional micro-computed tomographic, biomechanical and SEM study. Biomaterials. 2005; 26 5444-5453
- 13 Geiger F, Bertram H, Berger I et al. Vascular endothelial growth factor gene-activated matrix (VEGF165-GAM) enhances osteogenesis and angiogenesis in large segmental bone defects. J Bone Miner Res. 2005; 20 2028-2035
- 14 Louisia S, Stromboni M, Meunier A et al. Coral grafting supplemented with bone marrow. J Bone Joint Surg [Br]. 1999; 81 719-724
- 15 Niemeyer P, Vohrer J, Klöppel H et al. HLA – independent transplantation of mesenchymal stem cells for regeneration of bone: preliminary results of a critical size defect study in the sheep tibia. Europ Cell Mat. 2008; 14 (Suppl. 1) 14
- 16 Norton M R, Gamble C. Bone classification: an objective scale of bone density using the computerized tomography scan. Clin Oral Implants Res. 2001; 12 79-84
- 17 Hangartner T N, Short D F. Accurate quantification of width and density of bone structures by computed tomography. Med Phys. 2007; 34 3777-3784
- 18 Whyne C, Hardisty M, Wu F et al. Quantitative characterization of metastatic disease in the spine. Part II. Histogram-based analyses. Med Phys. 2007; 34 3279-3285
- 19 Byng J W, Yaffe M J, Lockwood G A et al. Automated analysis of mammographic densities and breast carcinoma risk. Cancer. 1997; 80 66-74
- 20 Glide-Hurst C K, Duric N, Littrup P. A new method for quantitative analysis of mammographic density. Med Phys. 2007; 34 4491-4498
- 21 Helvie M A, Hadjiiski L, Makariou E et al. Sensitivity of noncommercial computer-aided detection system for mammographic breast cancer detection: pilot clinical trial. Radiology. 2004; 231 208-214
- 22 Rybak L D, Rosenthal D I. Radiological imaging for the diagnosis of bone metastases. Q J Nucl Med. 2001; 45 53-64
- 23 Kallergi M, Carney G M, Gaviria J. Evaluating the performance of detection algorithms in digital mammography. Med Phys. 1999; 26 267-275
- 24 Bae K T, Slone R M, Gierada D S et al. Patients with emphysema: quantitative CT analysis before and after lung volume reduction surgery. Work in Progress Radiol. 1997; 203 705-714
- 25 Muller N L, Staples C A, Miller R R et al. “Density mask”. An objective method to quantitate emphysema using computed tomography. Chest. 1988; 94 782-787
- 26 Valvassori G E. CT densitometry in otosclerosis. Adv Otorhinolaryngol. 1987; 37 47-49
- 27 Zhou C, Chan H P, Petrick N et al. Computerized image analysis: estimation of breast density on mammograms. Med Phys. 2001; 28 1056-1069
Dr. Philipp Niemeyer
Department für Orthopädie und Traumatologie
Universitätsklinikum Freiburg
Hugstetter Straße 55
79098 Freiburg
Phone: 07 61/2 70 28 64
Fax: 07 61/2 70 25 20
Email: philipp.niemeyer@uniklinik-freiburg.de