Partial nephrectomy (PN) is the therapy of choice for localized renal cell carcinoma (RCC) whenever technically feasible [1]. Surgical excellence is essential for the successful treatment of RCC to avoid long-term consequences such as tumor recurrence or chronic kidney disease with the necessity of dialysis. The aim is to accomplish oncological safety, while preserving kidney function [2]. The latter is achieved by reducing the ischemic kidney injury and preserving healthy renal parenchyma. The duration of warm ischemia remains a controversy among urologists [3]. Recent advances to improve the surgical technique of PN include early unclamping, zero-ischemia PN, or selective clamping of segmental renal arteries [4].

Furthermore, PN is a challenging procedure with a steep learning curve. Substantial risks associated with PN comprise bleeding, formation of arteriovenous fistula, urine leakage, and postoperative deterioration of kidney function [4]. This is true especially among less experienced surgeons [5]. The critical steps during PN include tumor localization, identification of target structures (vessels and ureter), tissue differentiation (tumor vs healthy parenchyma), and surgical margin assessment. Oftentimes, the surgeon needs to rely on his or her experience and subjective assessment in order to perform this procedure safely. Hence, surgical real-time guidance is required to assist the surgeon during the procedure. A promising tool to address this need is biophotonic imaging (BI).

Biophotonics is an interdisciplinary field that combines the principles of biology, physics, and engineering to study the interactions between light and living systems. It includes a wide range of imaging modalities, such as fluorescence [6], spectral imaging [7], and optical coherence tomography (OCT) [8]. Biophotonics aims to enhance our understanding of biological processes and develop new technologies for medical diagnosis, therapy, and research [9].

In the context of intraoperative guidance, BI offers real-time monitoring and navigation during surgical procedures and aids in surgical decision-making [10]. This is achieved by providing more information than perceptible with the human eye. BI techniques can discriminate target structures from its surroundings, differentiate between various types of tissue, characterize tissue in terms of its biochemical properties (eg, oxygenation and hemoglobin, water, or lipid content), and visualize perfusion patterns [10], [11]. Intraoperative BI is still an emerging technology, but has the potential to improve the accuracy, precision, and patient safety in different fields of surgical procedures [6], [7].

Accordingly, PN represents an ideal scenario in which intraoperative guidance may enhance surgical performance and patient-specific outcomes. The objective of this systematic review was to provide a comprehensive analysis of biophotonics used for intraoperative guidance during PN.