Point-of-care diagnoses occur when a doctor can quickly diagnose a patient during an examination without sending biological samples to a laboratory or consulting with other specialists. The stress and anxiety that can come with waiting for the results of medical testing, and the cost associated with in-depth laboratory testing, make point-of-care testing a gold standard. However, point-of-care diagnostics remain rare in oncology.
Research shows that women suspected of endometrial cancer experience stress and anxiety while waiting for a confirmed diagnosis. While the procedures and waiting time associated with endometrial cancer diagnoses vary, endometrial biopsies can take weeks to return results. Of added concern, since most endometrial cancers require surgical intervention, usually a hysterectomy, delays in diagnosis lead to delays in treatment. Indeed, these surgical delays can negatively impact survival. Thus, rapid endometrial cancer diagnostic strategies would significantly improve patient care.
To address the need for new, more efficient endometrial cancer diagnostics, a group of researchers initiated a study to assess the ability of an intelligent knife (iKnife) to identify malignancy in endometrial tissue biopsies. The researchers published the results of the study in the journal Cancers.
The iKnife takes advantage of electrosurgical techniques to produce aerosols from the biopsied tissue. Electrosurgical procedures, commonly used in dermatology, utilize alternating electric currents to produce heat to cauterize tissue following a surgical incision. The aerosols, which appear like smoke rising from the tissue, occur when the tissue is healing from the incision. The iKnife also includes a mass spectrometer to analyze the aerosols generated by the procedure. The researchers tested whether the results of this analysis could differentiate between malignant and non-malignant tissue.
The study analyzed biopsy samples from 150 women. Among the samples, 59 came from patients with endometrial cancer. The iKnife technology garnered a diagnostic accuracy of 89%, and the sensitivity and specificity of the iKnife diagnostic remained high at 85% and 93%, respectively. Further, the study produced positive and negative predictive values that support the use of iKnife for this application. The analysis revealed the positive predictive value, the probability that a patient with a malignant result has endometrial cancer, at 94%. The negative predictive value of 85% indicated that 15% of patients received a false negative and did have endometrial cancer, given the negative result.
The study shows that the iKnife has the potential to provide point-of-care diagnostics for endometrial cancer. Further improvements to the diagnostic performance of the iKnife will increase the efficacy of this technology.
In addition to the study presented here, other studies have shown the ability of the iKnife to support surgeons in detecting tumor margins during surgery, including surgical resection for breast cancer.
Sources: Psycho-Oncol, Am J Obs Gynecol, Cancers, Science, Br Cancer Res
