Quantifying the Impact of Signal-to-background Ratios on Surgical Discrimination of Fluorescent Lesions

Abstract

Purpose Surgical fluorescence guidance has gained popularity in various settings, e.g., minimally invasive robot-assisted laparoscopic surgery. In pursuit of novel receptor-targeted tracers, the field of fluorescence-guided surgery is currently moving toward increasingly lower signal intensities. This highlights the importance of understanding the impact of low fluorescence intensities on clinical decision making. This study uses kinematics to investigate the impact of signal-to-background ratios (SBR) on surgical performance. Methods Using a custom grid exercise containing hidden fluorescent targets, a da Vinci Xi robot with Firefly fluorescence endoscope and ProGrasp and Maryland forceps instruments, we studied how the participants’ (N = 16) actions were influenced by the fluorescent SBR. To monitor the surgeon’s actions, the surgical instrument tip was tracked using a custom video-based tracking framework. The digitized instrument tracks were then subjected to multi-parametric kinematic analysis, allowing for the isolation of various metrics (e.g., velocity, jerkiness, tortuosity). These were incorporated in scores for dexterity (Dx), decision making (DM), overall performance (PS) and proficiency. All were related to the SBR values. Results Multi-parametric analysis showed that task completion time, time spent in fluorescence-imaging mode and total pathlength are metrics that are directly related to the SBR. Below SBR 1.5, these values substantially increased, and handling errors became more frequent. The difference in Dx and DM between the targets that gave SBR < 1.50 and SBR > 1.50, indicates that the latter group generally yields a 2.5-fold higher Dx value and a threefold higher DM value. As these values provide the basis for the PS score, proficiency could only be achieved at SBR > 1.55. Conclusion By tracking the surgical instruments we were able to, for the first time, quantitatively and objectively assess how the instrument positioning is impacted by fluorescent SBR. Our findings suggest that in ideal situations a minimum SBR of 1.5 is required to discriminate fluorescent lesions, a substantially lower value than the SBR 2 often reported in literature.

Artificial Intelligence‐Supported Video Analysis as a Means to Assess the Impact of DROP‐IN Image Guidance on Robotic Surgeons: Radioguided Sentinel Lymph Node versus PSMA‐Targeted Prostate Cancer Surgery

“…In line with Pearson correlation, these values were highly correlated to SBR values, whereby an SBR < 2 value resulted in inferior DM and Dx values (Figure 6B,E). [ 19 ] Relating the preoperative SPECT signal to DM and Dx revealed a similar but less strong trend (Figure 6C,F). The findings were not influenced by differences in the pelvic distribution of the lesions (Figure 2D,E) but prior surgery in the salvage cases could have negatively affected the patient anatomy.…”

“…To this end, marker‐based video tracking of da Vinci instruments has been exploited in the form of patterned‐ [ 13 ] and fluorescent markers. [ 14 ] There is a growing body of evidence suggesting that such approaches can be used to monitor instrument use, [ 15 ] to compare the performance difference between experts and novices, [ 16 ] to perform scoring during virtual simulation training, [ 17 ] to generate freehand scans, [13a,18] and to assess how image guidance technologies effect performance [14b,16a,19] . To make video‐based instrument tracking accessible for a global audience of robotic surgeons, markerless detection algorithms are needed that can automatically extract the required data out of endoscopic videostreams.…”

“…To understand how the different levels of image guidance impact surgical decision-making, computer-vision algorithms are used to extract the DROP-IN probe kinematic form clinical videos. 44 PCa patients undergo SLN (25) and PSMA-targeted (19) resections. PSMA-PET/CT and SPECT/CT create preoperative roadmaps, and intraoperative probe signal intensities are recorded.…”

Immunohistochemical Evaluation of Candidate Biomarkers for Fluorescence-Guided Surgery of Myxofibrosarcoma Using an Objective Scoring Method

“…Three important parameters define successful targeted FGS: the tumor-specific biomarker, the targeting moiety conjugated to a fluorophore (tracer), and the dedicated FGS camera system. While the ideal tumor-specific biomarker is strongly and diffusely expressed on tumor cells and absent on adjacent healthy tissue, a minimum of 1.5× overexpression of the tumor-specific biomarker on tumor cells compared to adjacent healthy tissue is already enough to guide surgeons in their actions [ 20 ]. The biomarker should preferably be located on the cell surface of malignant cells to permit direct targeting and have the possibility of internalization to facilitate a long-lasting fluorescence signal.…”

Value-assessment of computer-assisted navigation strategies during percutaneous needle placement

“…Such evaluations are generally based on total pathlength and procedural time [15][16][17][18]. However, a more multi-dimensional inclusion of kinematic metrics, has been posed to facilitate a more extensive analysis providing insight on procedural performance [19,20].…”