Intraoperative pelvic neuromonitoring based on bioimpedance signals: a new method analyzed on 30 patients.

PURPOSE: Increasing importance has been attributed in recent years to the preservation of the pelvic autonomic nerves during rectal resection to achieve better functional results. In addition to improved surgical techniques, intraoperative neuromonitoring may be useful. METHODS: This single-arm prospective study included 30 patients who underwent rectal resection performed with intraoperative neuromonitoring by recording the change in the tissue impedance of the urinary bladder and rectum after stimulation of the pelvic autonomic nerves. The International Prostate Symptom Score, the post-void residual urine volume and the Low Anterior Resection Syndrome Score (LARS score) were assessed during the 12-month follow-up period. RESULTS: A stimulation-induced change in tissue impedance was observed in 28/30 patients (93.3%). In the presence of risk factors such as low anastomosis, neoadjuvant radiotherapy and a deviation stoma, an average increase of the LARS score by 9 points was observed 12 months after surgery (p = 0,04). The function of the urinary bladder remained unaffected in the first week (p = 0,7) as well as 12 months after the procedure (p = 0,93). CONCLUSION: The clinical feasibility of the new method for pelvic intraoperative neuromonitoring could be verified. The benefits of intraoperative pelvic neuromonitoring were particularly evident in difficult intraoperative situations with challenging visualization of the pelvic nerves.

Automatic muscle impedance and nerve analyzer (AMINA) as a novel approach for classifying bioimpedance signals in intraoperative pelvic neuromonitoring.

Frequent complications arising from low anterior resections include urinary and fecal incontinence, as well as sexual disorders, which are commonly associated with damage to the pelvic autonomic nerves during surgery. To assist the surgeon in preserving pelvic autonomic nerves, a novel approach for intraoperative pelvic neuromonitoring was investigated that is based on impedance measurements of the innervated organs. The objective of this work was to develop an algorithm called AMINA to classify the bioimpedance signals, with the goal of facilitating signal interpretation for the surgeon. Thirty patients included in a clinical investigation underwent nerve-preserving robotic rectal surgery using intraoperative pelvic neuromonitoring. Contraction of the urinary bladder and/or rectum, triggered by direct stimulation of the innervating nerves, resulted in a change in tissue impedance signal, allowing the nerves to be identified and preserved. Impedance signal characteristics in the time domain and the time-frequency domain were calculated and classified to develop the AMINA. Stimulation-induced positive impedance changes were statistically significantly different from negative stimulation responses by the percent amplitude of impedance change Amax in the time domain. Positive impedance changes and artifacts were distinguished by classifying wavelet scales resulting from peak detection in the continuous wavelet transform scalogram, which allowed implementation of a decision tree underlying the AMINA. The sensitivity of the software-based signal evaluation by the AMINA was 96.3%, whereas its specificity was 91.2%. This approach streamlines and automates the interpretation of impedance signals during intraoperative pelvic neuromonitoring.