Algorithm to diagnose ovarian cancer faster

Every year approximately 7,600 Dutch women are diagnosed with an ovarian tumor. 1,400 of them are actually diagnosed with ovarian cancer, the rest are benign tumours. Little progress has been made in the treatment of ovarian cancer over the past 30 years, according to the Catharina Kanker Instituut. 40 percent of women with such a malignant tumor still die within five years.

In addition, the treatment process is very difficult. For example, patients have to undergo major surgery to remove the uterus, ovaries and fallopian tubes, among other things. In addition, it is not easy to recognize ovarian cancer prior to surgery.

Faster Diagnosis

Enough reasons for researchers Anna Koch and Caroline Muntinga to make a ‘faster’ diagnosis of ovarian cancer together with gynecologist oncologist Dr Jurgen Piek. to want to developWomen with a benign tumor of the ovary can be treated in a non-oncology center, Muntinga says. However, it is very important that women with ovarian cancer are treated in a center of expertise. The sooner it becomes clear whether a tumor on the ovary is malignant, the faster patients can be referred to such a specialized oncology center.

In the current study, the focus is on better distinguishing between the two patient groups using a computer model. Currently, only tissue research can determine whether a tumor is benign or malignant. If ovarian cancer is suspected, the tumor cannot be pricked because of the risk of cancer cells spreading in the abdominal cavity.

Missed a quarter of cases

Therefore, prior to surgery, a distinction is made between benign and malignant ovarian tumors by means of an ultrasound model. However, a quarter of cancer cases are missed as a result, says Koch, which means that it takes much longer before these women are referred to a center of expertise. “It is still too common for women with a malignant tumor to undergo a second operation in the oncology hospital,” Muntinga adds.

Conversely, in about 1 in 20 cases, women have a benign tumor and are therefore incorrectly referred to an oncology hospital for extensive abdominal surgery to determine the stage of the disease. This causes a lot of tension and fear for this patient group and an increase in healthcare costs for the hospital.

Better separating groups

The purpose of the computer model is to better separate the two different patient groups. so that women with a malignant tumor can be referred to the right expertise center more quickly. This should improve care for these women because they are treated faster in the right place.

Koch explains that an algorithm has been developed in collaboration with TU/e ​​that uses CT scans and clinical data to predict whether an ovary tumor is benign or malignant before patients undergo surgery. This model is intended to be more precise than the currently used echo model. Over the next two years, the researchers hope that their algorithm will become better than the method currently used.

Technology for women

Last March, a multidisciplinary research group from the University of Twente outwards that it is committed to developing technology especially for women. Women regularly deal with different diseases than men, such as cervical and ovarian cancer. By developing new data strategies and technology especially for women, the research group wants to focus on prevention, realize more customized care and promote women’s well-being. Central to the university’s research is developing technology that can be used in the prevention, diagnosis and treatment of diseases that primarily affect women.

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