DICOM Metadata Indexation Analysis
The DICOM metadata indexation processes, related to the medical imaging exams in the PACS of three different healthcare institutions, made possible to identify the routine head TC, thorax CR and thorax DX exams that were performed. This information was achieved without constraint and independently of the equipment manufacturers. The information presented in Table 1 show a significant number of images produced by the CT modality and its repercussion on the indexing processes time.
Since it is possible to determine each modality IOD, the indexing processes allow the identification of the number of DICOM attributes available to characterize the respective healthcare institution. In this context, it is evident the discrepancy of the number of attributes …show more content…
when accessing medical imaging exams stored in media such as CD-ROM or during information migration processes between PACS).
In terms of population studies, the quality of the stored information and the variability associated with the usage of the DICOM attributes may limit the analyses that may be performed. This situation may entail data standardization processes and, consequently, the use of automatic tools to access, process and analyze DICOM metadata, namely within research initiatives. A possible example is the routine head CT population study, as might be observed in Figures 2 and Figure 3. These results may also be compared with other routine head CT population studies, such as the results of the Dose Datamed2 …show more content…
In Figure 5 it is also possible to verify that the average number of exams increases as the age of the patients increases, except for the age group from 0 to 4 years in HCI_03, a healthcare institution with a pediatric department.
The differences identified in the three healthcare institutions should be interpreted taking into account factors such as the time period covered or the healthcare delivery profile of each one (e.g. population being served, existing medical services or respective timelines).
For example, it is evident the number of thorax CR and DX exams per patient in each age group of HCI_02 is greater than the other two healthcare institutions (Figure 5). This aspect may influence the number of medical imaging exams performed by a patient, since the greater the time interval, the greater the likelihood of a patient performing medical imaging exams, particularly in older
Since it is possible to determine each modality IOD, the indexing processes allow the identification of the number of DICOM attributes available to characterize the respective healthcare institution. In this context, it is evident the discrepancy of the number of attributes …show more content…
when accessing medical imaging exams stored in media such as CD-ROM or during information migration processes between PACS).
In terms of population studies, the quality of the stored information and the variability associated with the usage of the DICOM attributes may limit the analyses that may be performed. This situation may entail data standardization processes and, consequently, the use of automatic tools to access, process and analyze DICOM metadata, namely within research initiatives. A possible example is the routine head CT population study, as might be observed in Figures 2 and Figure 3. These results may also be compared with other routine head CT population studies, such as the results of the Dose Datamed2 …show more content…
In Figure 5 it is also possible to verify that the average number of exams increases as the age of the patients increases, except for the age group from 0 to 4 years in HCI_03, a healthcare institution with a pediatric department.
The differences identified in the three healthcare institutions should be interpreted taking into account factors such as the time period covered or the healthcare delivery profile of each one (e.g. population being served, existing medical services or respective timelines).
For example, it is evident the number of thorax CR and DX exams per patient in each age group of HCI_02 is greater than the other two healthcare institutions (Figure 5). This aspect may influence the number of medical imaging exams performed by a patient, since the greater the time interval, the greater the likelihood of a patient performing medical imaging exams, particularly in older