According to Elisabeth Epstein, a professor in obstetrics and gynaecology at Karolinska Institutet, ovarian tumours are common and are often detected by chance.
“There is a serious shortage of ultrasound experts in many parts of the world, which has raised concerns of unnecessary interventions and delayed cancer diagnoses,” Prof Epstein said in a statement. “We therefore wanted to find out if AI can complement human experts.”
The researchers have developed and validated neural network models able to differentiate between benign and malignant ovarian lesions, having trained and tested the AI on over 17,000 ultrasound images from 3,652 patients across 20 hospitals in eight countries. They then compared the models’ diagnostic capacity with a large group of experts and less experienced ultrasound examiners.
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The results showed that the AI models outperformed expert and non-expert examiners at identifying ovarian cancer, achieving an accuracy rate of 86.3 per cent, compared to 82.6 per cent and 77.7 per cent for the expert and non-expert examiners respectively.
“This suggests that neural network models can offer valuable support in the diagnosis of ovarian cancer, especially in difficult-to-diagnose cases and in settings where there’s a shortage of ultrasound experts,” said Prof Epstein.
According to the team, the AI models can also reduce the need for expert referrals, which was demonstrated in a simulated triage situation where AI support cut the number of referrals by 63 per cent and the misdiagnosis rate by 18 per cent.
The researchers caution that more studies are needed before the full potential of the neural network models and their clinical limitations are fully understood.
“With continued research and development, AI-based tools can be an integral part of tomorrow’s healthcare, relieving experts and optimising hospital resources, but we need to make sure that they can be adapted to different clinical environments and patient groups,” said Filip Christiansen, doctoral student in Professor Epstein’s research group at Karolinska Institutet and joint first author with Emir Konuk at the KTH Royal Institute of Technology.
The researchers are now conducting prospective clinical studies at Södersjukhuset to evaluate the clinical safety and usefulness of the AI tool. Future research will also include a randomised multicentre study to examine its effect on patient management and healthcare costs.
The international team’s study is published in Nature Medicine.
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