Designing a Structured System for Mammography Reporting

Sedigheh Emadi; Sina Kardeh; Sepideh Sefidbakht; Alireza Shakibafard; Omid Pournik; Roxana Sharifian

doi:10.5812/iranjradiol.99152

IJ Radiology

An Innovative Journal in the Field of Radiology

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https://doi.org/10.5812/iranjradiol.99152

Designing a Structured System for Mammography Reporting

Author(s):

Sedigheh Emadi¹,

Sina Kardeh¹,

Sepideh Sefidbakht

²,

Alireza Shakibafard²,

Omid Pournik

³,

Roxana Sharifian

^1,*

1Department of Management and Medical Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran

2Department of Radiology, Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

3Department of Community Medicine, School of Medicine, Iran University of Medical Sciences, Shiraz, Iran

IJ Radiology:Vol. 16, issue Special Issue; e99152

Published online:Dec 08, 2019

Article type:Abstract

Received:Oct 26, 2019

Accepted:Dec 08, 2019

How to Cite:Sedigheh EmadiSina KardehSepideh SefidbakhtAlireza ShakibafardOmid PournikRoxana Sharifianet al.Designing a Structured System for Mammography Reporting.I J Radiol.2019;16(Special Issue):e99152.https://doi.org/10.5812/iranjradiol.99152.

Abstract

Background:

Breast cancer is among the top causes of cancer-related mortality among females in both developed and developing countries. Screening for breast cancer plays a crucial role in the prevention of disease burden. Among various imaging modalities, mammography is currently considered the first step for the detection of breast lesions. The mammography data of breast cancer patients encompass a wide array of texts related to specific visual findings. Accordingly, unorganized mammography documents usually impede physicians’ efforts to fully review the previous information in follow-up visits; hence, this not only affects clinical judgment and treatment planning adversely, but also adds to the financial burdens and workload imposed on the healthcare system. This further highlights the great potential of structured mammography reporting in the management of breast cancer patients.

Methods:

In the first step, an expert panel consisting of two attending radiologists and a health informatician (all affiliated to the Shiraz University of Medical Sciences, Shiraz, Iran) reviewed related guidelines to determine the appropriate items, ontologies, and standard formats for data entry. These included radiology textbooks and the systematized nomenclature of medicine (SNOMED). In addition, 100 mammography reports were completely examined for data extraction and the creation of a template report. In the next step, the structure of the data registry was discussed among a group of radiologists and breast cancer surgeons during several sessions using Delphi technique.

Results:

Overall, 119 fields were selected for data entry. Our survey showed that all of the contributing physicians believed that a structured reporting system for mammography can help standardize and reduce reporting time and errors. Following the completion of the template, a user interface was developed by the expert panel for integration in the cloud software workflow, which will be deployed and assessed in the next phase of the project.

Conclusion:

Structured mammography reporting helps radiologists and surgeons to efficiently and confidently track the management course of their patients. In addition, with the advancement of artificial intelligence, especially deep learning for image classification, clean and labeled image databases can be used for designing computer-assisted decision support systems without significant data preprocessing.

Keywords

Artificial Intelligence

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Search Relations

Author(s):

Sedigheh Emadi:[PubMed][Scholar]
Sina Kardeh:[PubMed][Scholar]
Sepideh Sefidbakht:[PubMed][Scholar]
Alireza Shakibafard:[PubMed][Scholar]
Omid Pournik:[PubMed][Scholar]
Roxana Sharifian:[PubMed][Scholar]