Analysis of Wrist Morphology Through Hamate and Lunate Bone Variations in Anatolian Population Using Plain Radiography

Abstract

The present study aimed to evaluate wrist (lunate) anatomy in terms of the incidence of lunatum morphology on plain-radiographs among the Anatolian (Turkey) population, accompanied by demographic analysis. We obtained all the patients' data regarding demographical features, diagnosis, and posteroanterior (PA) X-ray imaging. Two radiograph-reviewers repeated the analysis twice, one month later, blinded to their findings before the previous review. The lunatum structure was determined as Type-1 (n:293) and Type-2 (n:207) for each radiograph. Most of the 500 wrists' radiographs [n:293 (58.6 %)] were type-I lunate. The mean age was 36.7±13.3 (range:18-90) years. Sex distribution was as follows: 185 (63.1 %) males to 108 (36.9 %) females. Type-2 lunate was seen in 207 participants (41.4 %). The mean age for type-2 was 41.6±15.2 (18-88) years. 142 (68.6 %) participants were male sex, while 65 (31.4 %) were females. The mean age of subjects with type-I showed a difference with type-II (p=0.007). There was no relationship in terms of sex (p=0.206) between the groups. In the Anatolian region, type-1 lunate was dominant compared to type-2. The incidence rate of lunate type in Anatolian population was similar to the Arab population.

Application of Cognitive Information Systems in Medical Image Semantic Analysis

“…Research conducted by other researchers usually concerns selected aspects of such analysis, e.g., preprocessing of hand images [10], or morphological analysis of individual bones. For example, the works [17,18] describe approaches for the analysis of selected morphometric parameters of the bones of the hand and wrist, which was carried out using simple methods of calculating distances and shape coefficients, achieving an efficiency of just over 60%. The conclusion is that the analysis of multi-object bone structures is extremely difficult, and the cognitive systems presented in this work offer a holistic approach that significantly improves the effectiveness of the analysis of hand images.…”