The basis of Doppler ultrasound sensing is that as an object emitting sound moves, the wavelength of the perceived sound is compressed and its frequency is increased in the forward direction. In the receding direction, the perceived wavelength would be expanded and frequency decreased. Doppler ultrasound probes have the ability to detect velocity or flow of material based on this measured increase or decrease of sound frequency. The delay in wave sensing between the primary and secondary reflected waves depends on the depth and the speed of the sound waves in various tissues [15]. Several LUS probes today have Doppler ultrasound capability, which allows for differentiation of blood vessels or highly vascularized masses compared to normal parenchymal tissue.

Recently, a sterile, disposable laparoscopic drop-in Doppler ultrasound (LDU) probe has been introduced for robotic procedures (Fig. 9.5) (VTI Vascular Technology Inc., Nashua, NH). The system includes a Doppler transceiver (8 or 20 MHz) with flexible disposable probes that emit ultrasound waves and sense reflected echo from blood flow. The 8 MHz is used to detect larger vessels such as the renal artery and vein. The 20 MHz probe is used to detect smaller vessels (1 mm or less) for microsurgical procedures (such as the testicular artery). This system provides an auditory pulse signal to identify blood flow allowing clear differentiation of arteries and veins [16].

Both extirpative and reconstructive robotic renal procedures are performed routinely with the da Vinci robotic platform such as radical and partial nephrectomy, nephroureterectomy, living-donor nephrectomy, pyeloplasty, and renovascular surgery [17]. Surgical maneuvers with robotic instruments around the renal hilum can in some cases be intimidating because of the lack of tactile feedback, scarring from prior surgeries and due to variations in renal vascular anatomy. A preoperative imaging study using helical CT angiography looked at 102 living donors. It revealed the presence of multiple renal arteries (31 % on the left, 20 % on the right) and multiple renal veins (5 % on the left, 20 % on the right) [18]. Although advanced preoperative imaging techniques such as multi-detector helical CT or MR-angiography are reasonably accurate in showing renal vascular anatomy, accessory vessels can be missed by imaging techniques [19, 20]. Even though this occurs in a small number patients, it can lead to surgical complexity and result in open conversion due to bleeding from unexpected vessel trauma [21]. Additionally, patient positioning, pneumoperitoneum, and intraoperative mobilization during robotic renal surgery can change the anatomical relationship between the renal hilum and other landmarks compared to preoperative imaging studies [22]. Recently, an analysis of 886 robotic partial nephrectomy procedures revealed that perioperative hemorrhage occurred in 0.5 % of the patients (two due to renal vein injury and two due to a missed unclamped renal artery) [23]. Lee et al. also described iatrogenic injury of the posterior segmental branch of renal artery during robot-assisted partial nephrectomy [8]. Unfortunately, these injuries can result in renal parenchymal loss, excessive blood loss, and longer operative times. Robotic pyeloplasty procedures can become a challenge due to obesity, a large floppy liver, redundant colon, crossing vessels, large calculi, and previous surgery [24].

For all the reasons mentioned above, IODU provides surgeons with an adjunctive tool to assist in identifying vessels and tissue perfusion during complex and challenging robotic renal procedures.