Implementation of a personal identification system using alveolar bone images.

OBJECTIVE: In recent years, personal identification has been performed using antemortem panoramic X-ray images and postmortem-CT images. Using these, we have developed a personal identification method that focuses on the alveolar bone. This study examined the effectiveness of this method and aimed to implement a reproducible system. MATERIALS AND METHODS: For personal identification, a total of 633 CT images and panoramic X-ray images belonging to three groups with different conditions were used.　These images were 160 sets in the same person group and 96,820 in the other groups. The similarity of alveolar bone images was calculated using the landmark method of Procrustes analysis. The processes were system implemented and the methodology was validated. RESULTS: The ability to identify between the same person group and other person groups showed 0.9769 as the area under the curve (AUC: ROC curve). At the cutoff value of 4.978, there was no false rejection rate, but false acceptance rate was slightly higher. CONCLUSION: This method was useful as a screening method for personal identification. In addition, system implementation was efficient and reduced human error. In the future, we aim to realize a more efficient personal identification method using distortion-corrected images and including auto-detective landmarks using deep learning.

Whole brain analysis of postmortem density changes of grey and white matter on computed tomography by statistical parametric mapping.

OBJECTIVES: This study examined the usefulness of statistical parametric mapping (SPM) for investigating postmortem changes on brain computed tomography (CT). METHODS: This retrospective study included 128 patients (23 - 100 years old) without cerebral abnormalities who underwent unenhanced brain CT before and after death. The antemortem CT (AMCT) scans and postmortem CT (PMCT) scans were spatially normalized using our original brain CT template, and postmortem changes of CT values (in Hounsfield units; HU) were analysed by the SPM technique. RESULTS: Compared with AMCT scans, 58.6 % and 98.4 % of PMCT scans showed loss of the cerebral sulci and an unclear grey matter (GM)-white matter (WM) interface, respectively. SPM analysis revealed a significant decrease in cortical GM density within 70 min after death on PMCT scans, suggesting cytotoxic brain oedema. Furthermore, there was a significant increase in the density of the WM, lenticular nucleus and thalamus more than 120 min after death. CONCLUSIONS: The SPM technique demonstrated typical postmortem changes on brain CT scans, and revealed that the unclear GM-WM interface on early PMCT scans is caused by a rapid decrease in cortical GM density combined with a delayed increase in WM density. SPM may be useful for assessment of whole brain postmortem changes. KEY POINTS: • The original brain CT template achieved successful normalization of brain morphology. • Postmortem changes in the brain were independent of sex. • Cortical GM density decreased rapidly after death. • WM and deep GM densities increased following cortical GM density change. • SPM could be useful for assessment of whole brain postmortem changes.

Effect of the forward-projected model-based iterative reconstruction solution algorithm on image quality and radiation dose in pediatric cardiac computed tomography.

BACKGROUND: Some iterative reconstruction algorithms are useful for reducing the radiation dose in pediatric cardiac CT. A new iterative reconstruction algorithm (forward-projected model-based iterative reconstruction solution) has been developed, but its usefulness for radiation dose reduction in pediatric cardiac CT is unknown. OBJECTIVE: To investigate the effect of the new algorithm on CT image quality and on radiation dose in pediatric cardiac CT. MATERIALS AND METHODS: We obtained phantom data at six dose levels, as well as pediatric cardiac CT data, and reconstructed CT images using filtered back projection, adaptive iterative dose reduction 3-D (AIDR 3-D) and the new algorithm. We evaluated phantom image quality using physical assessment. Four radiologists performed visual evaluation of cardiac CT image quality. RESULTS: In the phantom study, the new algorithm effectively suppressed noise in the low-dose range and moderately generated modulation transfer function, yielding a higher signal-to-noise ratio compared with filtered back projection or AIDR 3-D. When clinical cardiac CT was performed, images obtained by the new method had less perceived image noise and better tissue contrast at similar resolution compared with AIDR 3-D images. CONCLUSION: The new algorithm reduced image noise at moderate resolution in low-dose CT scans and improved the perceived quality of cardiac CT images to some extent. This new algorithm might be superior to AIDR 3-D for radiation dose reduction in pediatric cardiac CT.

[Usefulness of Iterative Reconstruction Method in the Field of Acute Cerebral Infarction Computed Tomography Examination].

We evaluated clinical images to investigate the usefulness of adaptive iterative dose reduction algorithm (AIDR) in the field of acute cerebral infarction. We did receiver operating characteristic (ROC) analysis by 4 radiologists using 50 clinical images (abnormal case=24, normal case=26) which were reconstructed by AIDR and filtered back projection (FBP). The area under the curve (AUC) value from average ROC curve of observers were 0.79 with the FBP and 0.87 with the AIDR (P=0.31). The standard deviation of AUC was 0.06 with the FBP and 0.03 with the AIDR. More in detail, the AUC value of Expert group (over 10 years of experience) increased to 0.06 by using AIDR compared with FBP method. On the other hand, in Beginner group (less than 10 years of experience) there was 0.09 increase. Therefore, there was some possibility to reduce the variation of diagnostic accuracy among observer and the diagnostic accuracy improvement of the doctor in a few Experience group, by using AIDR for acute cerebral infarction computed tomography (CT) examination.