Insights to enhance the examination of tool marks in human cartilage

Publikationen: Beitrag in FachzeitschriftZeitschriftenaufsätzeForschungBegutachtung




This work deals with the examination of tool marks in human cartilage. We compared the effectiveness of several cleaning methods on cut marks in porcine cartilage. The method cleaning by multiple casts achieved the significantly highest scores (P = 0.02). Furthermore, we examined the grain-like elevations (dots) located on casts of cut cartilage. The results of this study suggest that the casting material forms these dots when penetrating cartilage cavities, which are areas where the strong collagen fibres leave space for the chondrocytes. We performed fixation experiments to avoid this, without success. In addition, 31 casting materials were compared regarding contrast under light-microscope and 3D tool marks scanner. Under the light-microscope, brown materials achieved significantly higher values than grey (P = 0.02) or black (P = 0.00) whereas under the 3D scanner, black materials reached higher contrast values than grey (P = 0.04) or brown (P = 0.047). To compare the accuracy and reproducibility of 6 test materials for cartilage, we used 10 knives to create cut marks that were subsequently scanned. During the alignment of the individual signals of each mark, the cross-correlation coefficients (Xmax) and lags (LXmax) were calculated. The signals of the marks in agarose were aligned with significantly fewer lags and achieved significantly higher cross-correlation coefficients compared to all tested materials (both P = 0.00). Moreover, we determined the cross-correlation coefficients (XC) for known-matches (KM) per material. Agarose achieved significantly higher values than AccuTrans®, Clear Ballistics™, and gelatine (all P = 0.00). The results of this work provide valuable insights for the forensic investigation of marks in human costal cartilage.

PublikationsstatusElektronische Veröffentlichung vor Drucklegung. - 2021

Bibliographische Notiz

Ahead of print.

ID: 5997417


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