# Image Guided Robotic Nephron-Sparing Surgery

> **NIH NIH R01** · VANDERBILT UNIVERSITY · 2020 · $353,250

## Abstract

Project Summary
The importance of preserving renal function during surgical interventions through nephron-sparing (“partial
nephrectomy”) surgical techniques has garnered considerable and growing recent recognition. Total kidney
removal (“radical nephrectomy”) permanently compromises renal function and leads to increased morbidity and
mortality, with substantial negative impact on long-term patient quality of life. In contrast, partial nephrectomy
improves long-term outcomes by sparing a maximal amount of healthy kidney tissue. However, minimally
invasive partial nephrectomy is rarely attempted because it is extremely challenging to accomplish. The
surgeon must make critical intraoperative decisions (which can mean life or death for the patient), based on
imprecisely mentally inferred and registered three-dimensional anatomical relationships. The surgeon must
view a series of 2D preoperative images and build a mental 3D model of patient anatomy. He/she must then
intraoperatively guess how this remembered anatomical map should be registered to the patient. The inherent
inaccuracies in this process prevent many surgeons from attempting minimally invasive partial nephrectomy,
since positive margins (or inadvertent damage to internal kidney structures) are disastrous outcomes, while
taking a large negative margin defeats the purpose of the partial nephrectomy procedure.
 Our overall goal is to create an image-guided surgical system that makes localization, dissection, and
isolation of critical vascular and organ structures, as well as correct margin selection, easier and more accurate
for the surgeon (and thus the procedure safer and more effective for the patient), thereby increasing the
number of surgeons and hospitals able to adopt nephron sparing techniques. Toward this goal, our specific
objective in this proposal is to test the hypothesis that image guidance can increase the accuracy and/or time-
efficiency of the surgery. To test this hypothesis, we propose three Specific Aims: Aim 1 implements image
guidance on the da Vinci surgical robot platform. Aim 2 addresses extensive phantom validation studies using
anatomically accurate synthetic organs with realistic material properties. Aim 3 consists of an in vivo human
subject pilot study we call a “bystander study” because it can be achieved with essentially zero risk to human
subjects. The endpoint of this R01 will be a fully validated system, and the necessary experimental data to
power a large-scale clinical comparative efficacy study. This study will be able to take place soon after the
conclusion of this R01, due to the wide availability of the da Vinci robot, and the fact that all a surgeon or
hospital must have to participate is the robot itself – no additional pieces of equipment or infrastructural
changes will be necessary.

## Key facts

- **NIH application ID:** 9942420
- **Project number:** 5R01EB023717-04
- **Recipient organization:** VANDERBILT UNIVERSITY
- **Principal Investigator:** Stanley Duke Herrell
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $353,250
- **Award type:** 5
- **Project period:** 2017-09-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9942420

## Citation

> US National Institutes of Health, RePORTER application 9942420, Image Guided Robotic Nephron-Sparing Surgery (5R01EB023717-04). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9942420. Licensed CC0.

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