Objective: This project aimed at aiding the radiologist in the early detection of Breast Cancer by analyzing mammograms using AI thereby saving the patient’s life and reducing the costs associated with treatment of cancer. In addition, because there are fewer qualified experts in this field in MOH, Oman, this also would aid in processing more no. of patients than currently possible.
Results Achieved: The radiologists were able to process many more patients and focus their attention on the patients where AI reported positive findings while reliving the patients with negative findings. They were also able to detect with higher degree of accuracy the cases, which were in Early Stages of Cancer thereby reducing the cost of the treatment.
The following Impact generated as follow:
a. Reducing the turnaround time of reporting especially of positive cases.
b. Reduction in the need of multiple qualified experts to report.
c. Reduction in False Positives
d. Less Errors due to human fatigue
e. Early Detection means less impact on the person and their family
f. Reduction in healthcare costs

https://www.moh.gov.om/en/home

• Oman

• Women

Both public and private fixed medical centers and mobile screening centers producing Digital Mammograms can all replicate this process. Digital mammography machines follow the international open standard of DICOM for producing and transferring these mammograms. The applications deployed to read, transfer, receive these DICOM files and log them into databases are either open source or made using open source software like java. The applications deployed on open source LINUX platforms. This project can be deployed even in virtual machines thus saving on the cost of multiple physical hardware. The communication can happen on any kind of networks both LAN (Local Area Network), WAN (Wide Area Network) and even the Internet provided they meet certain specific security guidelines.

Since the workflow envisages, sending from any kind of mammography machine to any kind of AI software reports back the report to a centralized reading system and since many of the standards, protocols and software used are open source or made with open source, this workflow can be replicated across any public/private fixed/mobile center, for any AI Solution.

Sustainability of a project is the ability of the project to continue into the future. One of the main category to decide its sustainability would be financial. Let us examine this side.
All the software like PACS, DICOM, JAVA etc., used for this project are open source and hence entail no cost of purchasing. The HIS/RIS used for the project for displaying the worklist with the score and integrating to the AI Viewer and the PACS Viewer is AlShifa, an in-house developed project of the Ministry Of Health in Oman and which holds the source code rights of the project.

The cost entailed for the project is only the cost of procuring the license of an AI software and the cost of acquiring any physical servers for the project. Even the deployment of the AI Software was on LINUX an open source Operating System. The rest of the software used entailed no cost.

A full treatment of a patient diagnosed in the third stage, by some estimates, could cost anywhere between 65,000 USD to 130,000 USD. Treatment of a patient diagnosed in the first stage, by estimates, could cost anywhere between 13,000 USD to 26,000 USD. Even if we take the lower figure that is a saving of 80% which is a huge reduction. If we have 5000 cases at this rate, the savings could be in the tune of 100 m (One Hundred million) or thereabouts. AI would help us in diagnosing early thus giving us this huge reduction in costs both to the center and to the patient and their family. On top of this is the Mental, Physical, Financial and Social cost the patient and family has to bear is unaccounted for and if we add that for all the families, we can easily add another half million or even more.

If we compare this cost of purchase to the financial cost of treating breast cancer patients, especially in the latter stages of cancer, the cost benefits are tremendous as long as AI is able to perform at a level similar to a trained radiologist or even better. This proves that the project is sustainable.

This project reflects the following WSIS values: - Gender equality: The Ministry of Health (MoH) provides services in early detection of breast cancer for women who are at risk of developing it. - Inclusion: this service is available for all women in the Sultanate with plans for expansions to more locations. - Early disease detection.