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1.
Curr Probl Diagn Radiol ; 53(3): 329-331, 2024.
Article in English | MEDLINE | ID: mdl-38246794

ABSTRACT

The inclusion of comparison studies within radiology reports is an important, standard practice. Despite this, we identified that after-hours preliminary reports rendered by trainees within our institution often omitted reference to comparison studies for pediatric inpatient portable radiographs. We addressed this issue through a quality improvement project targeting pediatric radiographs. Key interventions included modifying the structured reports by removing default text in the comparison field, designating the comparison field as mandatory, and restructuring the report templates to remove extraneous information. We also initiated a targeted educational campaign. 392 reports before and 267 reports after intervention (total 732 reports) were evaluated to determine the number of reports lacking comparison information when comparisons were available. Following the interventions, there was a statistically significant decrease in incomplete reports from 12.5% to 6%. This project highlights the success of utilizing structured reporting to improve the quality of trainee reports.


Subject(s)
Radiology Information Systems , Research Report , Child , Humans , Quality Improvement , Documentation
2.
Acad Radiol ; 31(6): 2281-2291, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38286723

ABSTRACT

Radiomics uses advanced mathematical analysis of pixel-level information from radiologic images to extract existing information in traditional imaging algorithms. It is intended to find imaging biomarkers related to the genomics of tumors or disease patterns that improve medical care by advanced detection of tumor response patterns in tumors and to assess prognosis. Radiomics expands the paradigm of medical imaging to help with diagnosis, management of diseases and prognostication, leveraging image features by extracting information that can be used as imaging biomarkers to predict prognosis and response to treatment. Radiogenomics is an emerging area in radiomics that investigates the association between imaging characteristics and gene expression profiles. There are an increasing number of research publications using different radiomics approaches without a clear consensus on which method works best. We aim to describe the workflow of radiomics along with a guide of what to expect when starting a radiomics-based research project.


Subject(s)
Imaging Genomics , Humans , Imaging Genomics/methods , Neoplasms/diagnostic imaging , Neoplasms/genetics , Algorithms , Diagnostic Imaging/methods , Genomics , Biomedical Research , Multiomics , Radiomics
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