Patient dose management solution directly integrated in the RIS: "Gray Detector" software.
J Digit Imaging
; 27(6): 786-93, 2014 Dec.
Article
em En
| MEDLINE
| ID: mdl-24965275
On X-ray modalities, the information concerning the dose delivered to the patient is usually available in image headers or in structured reports stored in the picture archiving and communication system (PACS). Sometimes this information is sent in the Modality Performed Procedure Step message. By saving the information inside the Radiological Information System, it can be linked to the patient and to his/her episode/request. A software, "Gray Detector," implementing different and complementary extraction methods was developed. Query/retrieve on images header, Modality Performed Procedure Step message analysis, or the combination of the two methods were used. In order to avoid erroneous dose-protocol association, every accession number is linked to its unique report code, allowing multiple-protocols exam recognition. The adoption of different methods to extract dosimetric information makes it possible to integrate any kind of modality in a vendor/version neutral way. Linking the dosimetric information received from a modality to the patient and to the unique report code solves, for example, common problems in computed tomography exams, where the dosimetric value related to multiple segments/studies on the modality can be associated by the technician who performs the exam only to one accession number corresponding to a single study/segment. Analyses of dosimetric indexes' dependence on modality type, patient age, technician, and radiologist were performed. Linking dosimetric information to radiological information system data allows a contextualization of the former and helps to optimize the image-quality/dose ratio, thereby making it possible to take a clinical decision that is "patient-centered."
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Doses de Radiação
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Software
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Sistemas de Informação em Radiologia
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Integração de Sistemas
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Registros Eletrônicos de Saúde
Tipo de estudo:
Guideline
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2014
Tipo de documento:
Article