Post-mortem interval estimation of human skeletal remains by micro-computed tomography, mid-infrared microscopic imaging and energy dispersive X-ray mapping.
Post-mortem interval estimation of human skeletal remains by micro-computed tomography, mid-infrared microscopic imaging and energy dispersive X-ray mapping.
复制标题
DOI：
10.1039/c4ay02943g
复制
发表时间：
2015-04-07
期刊：
影响因子：
--
通讯作者：
Pallua JD
中科院分区：
文献类型：
--
作者：
Longato S;Wöss C;Hatzer-Grubwieser P;Bauer C;Parson W;Unterberger SH;Kuhn V;Pemberger N;Pallua AK;Recheis W;Lackner R;Stalder R;Pallua JD
在这项研究中，不同的国家的最先进的可视化方法进行了评估，以研究人类骨骼遗骸的确定死后间隔（PMI）。在这项研究中，不同的国家的最先进的可视化方法，如微型计算机断层扫描（micro-CT），中红外（MIR）显微成像和能量色散X射线（EDS）映射进行了评估，以研究人类骨骼遗骸的确定死后时间（PMI）。通过重叠分子成像数据和由放射技术产生的形态组织结构以及从共聚焦显微镜（Infinite Focus（IFM））获得的显微图像来识别和可视化PMI特异性特征。通过这种方式，实现了关于PMI期间的过程的更清晰的画面以及PMI的更现实的近似。可以证明，所获得的结果结合多变量数据分析可以用于预测钙/碳比值和骨体积（BV）占总体积（TV）的PMI估计。本研究的统计局限性在于样本量小，未来的工作将基于更多的标本，基于这种多维方法的结果开发PMI的筛选工具。
In this study different state-of-the-art visualization methods were evaluated to study human skeletal remains for the determination of the post-mortem interval (PMI). In this study different state-of-the-art visualization methods such as micro-computed tomography (micro-CT), mid-infrared (MIR) microscopic imaging and energy dispersive X-ray (EDS) mapping were evaluated to study human skeletal remains for the determination of the post-mortem interval (PMI). PMI specific features were identified and visualized by overlaying molecular imaging data and morphological tissue structures generated by radiological techniques and microscopic images gained from confocal microscopy (Infinite Focus (IFM)). In this way, a more distinct picture concerning processes during the PMI as well as a more realistic approximation of the PMI were achieved. It could be demonstrated that the gained result in combination with multivariate data analysis can be used to predict the Ca/C ratio and bone volume (BV) over total volume (TV) for PMI estimation. Statistical limitation of this study is the small sample size, and future work will be based on more specimens to develop a screening tool for PMI based on the outcome of this multidimensional approach.
登录
查看更多内容
影响因子：
6.2
作者：
Gourion-Arsiquaud, Samuel;Faibish, Dan;Boskey, Adele L.
通讯作者：
Boskey, Adele L.
影响因子：
1.5
作者：
KNIGHT, B;LAUDER, I
通讯作者：
LAUDER, I
影响因子：
2.2
作者：
MACLAUGHLINBLACK, SM;HERD, RJM;WEST, IE
通讯作者：
WEST, IE
影响因子：
4.3
作者：
Koehler, Milena;Machill, Susanne;Krafft, Christoph
通讯作者：
Krafft, Christoph
影响因子：
4.1
作者：
Chibnall, AC;Rees, MW;Williams, EF
通讯作者：
Williams, EF