New AI and Blood Tests Transform Endometrial Cancer Detection

New diagnostic developments are expanding the ways clinicians can detect endometrial cancer, with a focus on reducing the need for invasive procedures through the use of blood tests, vaginal swabs, and artificial intelligence.

Endometrial cancer, also known as womb cancer, begins in the endometrium, which is the lining of the uterus. In the United Kingdom, It’s currently the fourth most common cancer in women, with approximately 9,800 diagnoses annually.

Advancements in Blood-Based Detection

Gynaecological cancer experts at the University of Leicester and University Hospitals of Leicester NHS Trust have developed a pioneering blood test known as the ECctDNA test. This test identifies fragments of cancer within a patient’s blood.

The ECctDNA test is designed to make it easier and less invasive to determine if cancer has recurred. By using this method, patients may avoid the need for physical examinations, scans, and potentially uncomfortable biopsies.

The development of the test took place over eight years as part of a study involving more than 85 women with endometrial cancer. The research received funding from the National Institute for Health and Care Research (NIHR) Leicester Biomedical Research Centre, Hope Against Cancer, and the Medical Research Council, with results published in Precision Medicine.

We have been able to develop a blood test that can not only diagnose womb cancer recurrence more quickly but can avoid the need for confirmatory invasive biopsies. It can also give important information to the clinical team on the genetic changes that are driving the cancer to recur, which could be used to guide patients’ further treatment

Dr Esther Moss, Consultant Gynaecological Oncologist at the University Hospitals of Leicester NHS Trust and Associate Professor in Gynaecological Oncology at the University of Leicester

The Role of Artificial Intelligence in Diagnosis

Artificial intelligence is being integrated into various diagnostic pathways to improve precision and early detection. Researchers are investigating AI as a tool for the non-invasive detection of ovarian cancer and for the analysis of histopathological images to predict the molecular subtypes of endometrial tumors.

Beyond image analysis, AI is being used to identify high-risk forms of endometrial cancer and develop corresponding tests to transform how the disease is diagnosed, and treated.

Additional developments include the use of AI in conjunction with vaginal swab tests to accurately detect endometrial cancer. This approach aims to provide a simpler, less invasive alternative to traditional diagnostic methods.

Clinical Impact and Future Outlook

The shift toward non-invasive testing aims to address the challenges associated with traditional diagnostic tools. The ability to detect cancer recurrence or identify high-risk subtypes through blood or swabs can lead to faster clinical decision-making.

By broadening the scope of AI applications, there is potential to enhance diagnostic precision and improve outcomes across the spectrum of gynecologic cancers.

These emerging tools—ranging from the ECctDNA blood test to AI-augmented histopathology—represent a move toward more personalized and less burdensome monitoring for patients living with endometrial cancer.