Objective To establish a method of quick three-dimensional (3D) reconstruction of pubic symphysis based on magnetic resonance imaging. Methods The pelvis images of adult male were generated on a 3.0 T scanner using a T1 Gradient Echo FLASH-3D (T1- FL3D) sequence and imported the images into medical image control system. Segmentation of binaryzation threshold was conducted and pelvic soft tissue image was extracted by regional growth, 3D structure model of pubic symphysis was obtained by Boolean operation. The 3D structure model of pubic symphysis was established by the noise reduction of reverse engineering software. And compared with the 3D reconstruction model pubic bone CT scan. Results The morphological characters of the MRI pubic symphysis 3D model, such as the ridges and furrows on the symphysial surface, lower extremity, dorsal margin (beveling), margin (beveling) and pubic tubercle, were highly consistent with the morphological characters of the 3D model established by CT scan. Conclusion MRI scan can be used to reconstruct the 3D structure of pubic symphysis quickly and effectively, and it can provide a safe radiation-free 3D visualization imaging technique for forensic age estimation for the living.

Objective To investigate the correlation between ADC value and glioma IDH-1/1p19q genotype. Methods The MRI features and molecular pathological results of 69 patients with pathologically confirmed diagnosis of WHO grade Ⅱ/Ⅲ glioma between March 2013 and December 2020 were retrospectively analyzed. The diagnostic performance of ADC values on glioma genotypes (IDH-1, 1p19q) was evaluated using the ROC curve of the subjects' working characteristics. Results The ADCmean, ADC_min, rADC_mean, and rADC_min in the IDH-1 mutation group were significantly higher than those in the IDH-1 wild group (P < 0.05, P < 0.01, P < 0.05, P < 0.01). The use of the rADC_min threshold (0.979×10³mm²/s) had the highest efficacy (AUC=0.770) for diagnosis of IDH-1 mutant and IDH-1 wild-type gliomas as well as sensitivity and specificity of 84.61% and 59.09%, respectively. Conclusion ADC can be used as an imaging biomarker for noninvasive prediction of IDH-1 mutant and wild-type Ⅱ /Ⅲ gliomas.