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6. Pölcher M, Matz S, Braun M, Brambs C, Beer M, Hamann M.Sentinel lymph node mapping with indocyanine green compared to blue dye tracer in gynecologic malignancies-a single center experience of 218 patients. J Surg Oncol. 2021;123(4):1092–8. https://doi.org/10.1002/jso.26338.

7. Bodurtha Smith AJ, Fader AN, Tanner EJ.Sentinel lymph node assessment in endometrial cancer: a systematic review and meta-analysis. Am J Obstet Gynecol. 2017;216(5):459–476.e410. https://doi.org/10.1016/j.

ajog.2016.11.1033.

8. Abu-Rustum NR, Yashar CM, Bradley K, Campos SM, Chino J, Chon HS, Chu C, Cohn D, Crispens MA, Damast S, etal. NCCN guidelines® insights: uterine neoplasms, version 3.2021. J Natl Compr Cancer Netw. 2021;19(8):888–95. https://doi.org/10.6004/jnccn.2021.0038. From NLM.

9. Peone AM, Casadio P, Formelli G, Levorato M, Ghi T, Costa S, Meriggiola MC, Pelusi G. Cervical and hysteroscopic injection for identication of sentinel lymph node in endometrial cancer. Gynecol Oncol. 2008;111(1):62–7. https://doi.org/10.1016/j.ygyno.2008.05.032.

10. Rocha A, Domínguez AM, Lécuru F, Bourdel N.Indocyanine green and infrared uorescence in detection of sentinel lymph nodes in endometrial and cervical cancer staging—a systematic review. Eur J Obstet Gynecol Reprod Biol. 2016;206:213–9. https://doi.org/10.1016/j.

ejogrb.2016.09.027.

11. Ruscito I, Gaspai ML, Braicu EI, Bellati F, Raio L, Sehouli J, Mueller MD, Panici PB, Papadia A.Sentinel node mapping in cervical and endometrial cancer: Indocyanine green versus other conventional dyes-a metaanalysis. Ann Surg Oncol. 2016;23(11):3749–56. https://doi.org/10.1245/

s10434- 016- 5236- x.

12. Ulain Q, Han L, Wu Q, Zhao L, Wang Q, Tuo X, Wang Y, Wang Q, Ma S, Sun C, et al. Indocyanine green can stand alone in detecting sentinel lymph nodes in cervical cancer. J Int Med Res. 2018;46(12):4885–97.

https://doi.org/10.1177/0300060518803041.

13. Levinson KL, Mahdi H, Escobar PF.Feasibility and optimal dosage of indocyanine green uorescence for sentinel lymph node detection using robotic single-site instrumentation: preclinical study. J Minim Invasive Gynecol. 2013;20(5):691–6. https://doi.org/10.1016/j.jmig.2013.03.013.

14. Vahrmeijer AL, Hutteman M, van der Vorst JR, van de Velde CJ, Frangioni JV. Image-guided cancer surgery using near-infrared uorescence. Nat Rev Clin Oncol. 2013;10(9):507–18. https://doi.org/10.1038/nrcli-

nonc.2013.123.

15. Naldini A, Vizzielli G, Peone E, Gallotta V, Scambia G.Robotic video endoscopic inguinal lymphadenectomy (R-VEIL) for vulvar cancer with sentinel node mapping using indocyanine green and near-infrared uorescence imaging technology. Gynecol Oncol. 2018;150(1):203–4.

https://doi.org/10.1016/j.ygyno.2018.04.568.

16. Kleppe M, Wang T, Van Gorp T, Slangen BF, Kruse AJ, Kruitwagen RF. Lymph node metastasis in stages I and II ovarian cancer: a review.

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Gynecol Oncol. 2011;123(3):610–4. https://doi.org/10.1016/j.

ygyno.2011.09.013.

17. Lago V, Bello P, Montero B, Matute L, Padilla-Iserte P, Lopez S, Marina T, Agudelo M, Domingo S.Sentinel lymph node technique in early-stage ovarian cancer (SENTOV): a phase II clinical trial. Int J Gynecol Cancer. 2020;30(9):1390–6. https://doi.org/10.1136/ijgc- 2020- 001289.

18. Uccella S, Nero C, Vizza E, Vargiu V, Coado G, Bizzai N, Ghezzi F, Cosentino F, Turco LC, Fagotti A, etal. Sentinel-node biopsy in earlystage ovarian cancer: preliminary results of a prospective multicentre study (SELLY). Am J Obstet Gynecol. 2019;221(4):324.e321–10. https://

doi.org/10.1016/j.ajog.2019.05.005.

19. Nguyen-Xuan HT, Montero Macias R, Bonsang-Kitzis H, Deloménie M, Ngô C, Koual M, Bats AS, Hivelin M, Lécuru F, Balaya V.Use of uorescence to guide surgical resection in vulvo-vaginal neoplasia: two case reports. J Gynecol Obstet Hum Reprod. 2021;50(6):101768. https://doi.

org/10.1016/j.jogoh.2020.101768.

20. Degett TH, Andersen HS, Gögenur I.Indocyanine green uorescence angiography for intraoperative assessment of gastrointestinal anastomotic perfusion: a systematic review of clinical trials. Langenbeck's Arch Surg. 2016;401(6):767–75. https://doi.org/10.1007/s00423- 016- 1400- 9.

21. Bizzai N, Foschi N, Loveo M, Tortorella L, Santullo F, Rosati A, Gueli Alletti S, Costantini B, Gallotta V, Feandina G, etal. Indocyanine green to assess vascularity of ileal conduit anastomosis during pelvic exenteration for recuent/persistent gynecological cancer: a pilot study. Front Oncologia. 2021;11:727725. https://doi.org/10.3389/fonc.2021.727725.

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0282(97)00191- x.

23. De Neef A, Cadière GB, Bourgeois P, Barbieux R, Dapri G, Fastrez M.Fluorescence of deep inltrating endometriosis during laparoscopic surgery: a preliminary report on 6 cases. Surg Innov. 2018;25(5):450–4.

https://doi.org/10.1177/1553350618785486.

24. Bar-Shavit Y, Jaillet L, Chauvet P, Canis M, Bourdel N.Use of indocyanine green in endometriosis surgery. Fertil Steril. 2018;109(6):1136–7.

https://doi.org/10.1016/j.fertnstert.2018.02.113.

25. Raimondo D, Mastronardi M, Mabrouk M, Cafagna G, Salucci P, Arena A, Iodice R, Borghese G, Casadio P, Del Forno S, etal. Rectosigmoid endometriosis vascular patterns at intraoperative Indocyanine green angiography and their coelation with clinicopathological data. Surg Innov. 2020;27(5):474–80. https://doi.org/10.1177/1553350620930147.

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29. Fuchs Weizman N, Einarsson JI, Wang KC, Vitonis AF, Cohen SL.Vaginal cuff dehiscence: risk factors and associated morbidities. JSLS. 2015;19(2):1. https://doi.org/10.4293/jsls.2013.00351. From NLM.

30. Beran BD, Shockley M, Arnolds K, Escobar P, Zimberg S, Sprague ML. Laser angiography with Indocyanine green to assess vaginal cuff perfusion during total laparoscopic hysterectomy: a pilot study. J Minim Invasive Gynecol. 2017;24(3):432–7. https://doi.org/10.1016/j.

jmig.2016.12.021. From NLM.

31. Nicholson K, Urh A, Demertzis K, Holubyeva A, LaPier Z, CisnerosCamacho A, Goldberg GL, Schwartz B.Intraoperative Indocyanine green dye use in ovarian torsion: a feasibility study. J Minim Invasive Gynecol. 2022;29(6):738–42. https://doi.org/10.1016/j.jmig.2022.01.008. From NLM.

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35. Saidi MH, Sadler RK, Vancaillie TG, Akright BD, Farhart SA, White AJ. Diagnosis and management of serious urinary complications after major operative laparoscopy. Obstet Gynecol. 1996;87(2):272–6. https://

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36. Redan JA, McCarus SD.Protect the ureters. JSLS. 2009;13(2):139–41. From NLM.

37. Huh WK, Johnson JL, Elliott E, Boone JD, Leath CA 3rd, Kovar JL, Kim KH.Fluorescence imaging of the ureter in minimally invasive pelvic surgery. J Minim Invasive Gynecol. 2021;28(2):332–341.e314. https://doi.

org/10.1016/j.jmig.2020.06.022.

38. Fujita H, Kikuchi I, Nakagawa R, Katano M, Nakano E, Kitayama R, Tanaka Y.Use of a novel uorescent catheter to locate the ureters during Total laparoscopic hysterectomy. J Minim Invasive Gynecol. 2021;28(7):1420–4. https://doi.org/10.1016/j.jmig.2021.04.004.

39. Ris F, Liot E, Buchs NC, Kraus R, Ismael G, Belfontali V, Douissard J, Cunningham C, Lindsey I, Guy R, etal. Multicentre phase II trial of nearinfrared imaging in elective colorectal surgery. Br J Surg. 2018;105(10):1359–67. https://doi.org/10.1002/bjs.10844.

L. Lipetskaia et al.

Future Directions

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inFluorescence-and

Image- Guided Surgery

GeneYang

Introduction

Fluorescence- and image-guided surgery are rapidly growing elds of research with a wide range of potential applications to bridge the gap between preoperative imaging and the operative environment. Fluorescence guidance systems have been utilized in many clinical applications across several disciplines to improve surgical outcomes, including tumor localization, anatomy identication, perfusion assessment, and lymphatic mapping [1]. Since the development of near-infrared uorescent agents indocyanine green (ICG) and methylene blue, several additional uorophores with varying uorescence properties have been developed and validated for use in uorescence guided surgery [2]. More recently, molecular and activatable uorophores have emerged as alternatives to traditional uorophores to expand the translation of this technology to additional surgical indications [3, 4].

Novel applications of several imaging technologies have provided additional methods for surgeons to make intraoperative image-based decision-making. A promising example is laser

G. Yang (*) Department of Surgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA e-mail: geneyang@buffalo.edu

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speckle contrast imaging. Laser speckle contrast imaging (LSCI) is a noninvasive, real-time imaging technique that allows for perfusion assessment. This technology has been applied in the elds of cardiology, neurology, and dermatology. Validation studies have demonstrated LSCI as a potential valuable tool for perfusion assessment in laparoscopic surgery [5].

Augmented reality (AR) is another technology that is demonstrating increasing utility in image-guided surgery. AR can aid surgeons in the rapid identication of subsurface targets and structures, reduce surgeon’s cognitive load from mentally matching preoperative imaging to the operative environment, and guide resections with overlay of a virtual model onto the patient [6]. The purpose of this review is to provide an overview of the technology and recent developments in targeted uorophores, LSCI, and AR.

G. Yang

Fluorescence-Guided Surgery

Fluorescence-guided surgery (FGS) has developed into a validated method to augment surgeon’s ability to identify anatomic landmarks, localize tumors, and assess perfusion. Since the initial use of uorescein in 1948 to localize intracranial neoplasms during neurosurgery, several additional uorescent agents have been used for a variety of surgical applications. ICG initially used for quantitative measurement of hepatic and cardiac function has demonstrated clinical applications for perfusion assessment, cholangiography, lymphography, and tumor imaging. Methylene blue has been evaluated for ureter, thyroid, and neuroendocrine tumor assessment [7]. Five-Aminolevulinic acid and its derivative are clinically approved for imaging of malignant gliomas and bladder cancer with randomized controlled phase 3 trials demonstrating improved resection margin and increased progression-free survival for patients in these applications [8].

Recent focus has shifted from structural and functional uorescence to molecular uorescence, with subsequent developments resulting in uorophores with increased specicity. In this method, tumor-specic ligands are conjugated to uorescent dye, taking

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advantage of proven molecular probes and well-developed molecular pathology to aid in lesion detection and margin assessment during surgery and enable molecular targeted therapy with drug and photo-absorber conjugates [9].

Several therapeutic monoclonal antibodies have been repurposed for FGS by uorescence conjugation. Bevacizumab conjugated with the uorophore IRDye800CW has been applied in clinical feasibility studies to target tumors that overexpress vascular endothelial growth factor. The use of bevacizumabIRDye800CW during cytoreductive surgery for peritoneal carcinomatosis of colorectal origin demonstrated additional detection of malignant lesions [10]. Application in breast surgery has demonstrated the ability of bevacizumab-IRDye800CW to assess tumor-positive margin during back-table assessment after breast conserving surgery [11]. Similar applications in head and neck surgery have demonstrated the ability of cetuximabIRDye800CW to assess positive tumor margins on exvivo backtable imaging, and panitumumab-IRDye800CW demonstrated feasibility in performing both in situ tumor imaging and exvivo tumor margin assessment [12, 13].

An alternative approach is the use of activatable uorescent probes. Activatable uorescent probes seek to limit background signal by activating uorescence after engaging the target. Compared to traditional uorescent probes, activatable probes typically yield higher uorescent signal and higher tumor-tobackground uorescence ratio. A promising example of an activatable uorescent probe is LUM015. LUM015, a PEGylated cathepsin-activated uorescent imaging probe, is currently being investigated for detection of breast, gastrointestinal, brain, and prostate cancers. Initial studies demonstrated feasibility in tumorspecic uorescence of sarcoma and breast cancer during exvivo imaging and intraoperative detection of residual breast cancer [14]. Subsequent phase 2 study demonstrated improvement in nal margin status sensitivity over standard pathology assessment of lumpectomy specimen. This was associated with reduced need for second surgery in patients who underwent intraoperative excision of uorescence guided shaves [15].

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G. Yang

Limitations toClinical Translation

Molecular uorescence imaging can provide additional information that augments the ability of a surgeon to see and treat pathology, but this technology remains in the early stages of development. Clinical studies consist mostly of early-phase trials conducted to evaluate the safety and optimal dosing of uorescent agents and feasibility of intraoperative lesion detection. Further large, multicenter, randomized controlled trials are required to evaluate the diagnostic accuracy of uorescence molecular imaging and impact on surgical outcomes. As the eld of intraoperative molecular imaging matures, concurrent development of universal protocol for calibration and benchmarking of imaging devices to standardize the development and comparison of novel uorescent agents will be essential [16, 17].

Laser Speckle Contrast Imaging

LSCI has developed into a promising technology for imageguided surgery with current emphasis on intraoperative perfusion assessment. LSCI is based on the concept that tissue illuminated with coherent laser light backscatters in a random interference pattern, known as speckle pattern, onto a detector. When the speckle pattern is captured over an exposure time, movement of particles inside the tissue causes speckle pattern uctuations resulting in changes in the speckle image. Fluctuations in tissue images due to movement of red blood cells allow for the assessment of tissue perfusion. The rst invivo application of LSCI on visceral organ perfusion in open surgery was reported by Eriksson etal., demonstrating the feasibility of LSCI to measure hepatic microcirculation [18]. Subsequent studies with applications in porcine gastrointestinal tract and microvascular perfusion measurements of gastric conduit during esophagectomy further demonstrate the feasibility of using LSCI during gastrointestinal surgery [19, 20].

17 Future Directions inFluorescence-and Image-Guided Surgery

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More recent studies apply LSCI to the laparoscopic setting. Heeman etal. demonstrated feasibility of a laparoscopic laser speckle contrast imaging setup to measure tissue perfusion during colon resection [21]. Comparison study of LSCI to ICG uorescence imaging in intraoperative perfusion assessment during laparoscopic vascular occlusion of porcine intestine, stomach, and kidney demonstrated precise and accurate identication of demarcation between perfused and non-perfused tissue with both LSCI and ICG imaging. LSCI demonstrated an advantage over ICG with time-dependent perfusion assessment. Discordance in demarcation identication was noted in the ICG imaging group when images were assessed after 5 min from ICG administration [22].

Other novel developments in FGS include Activ Surgical, a company pioneering digital surgery imaging who has developed ActivSight, a modular imaging device which integrates with standard laparoscopic visualization systems to provide multimodal advanced visual intelligence. ActivSight enables visualization of ICG via its ActivICG module, as well as LCSI visualization via is ActivPerfusion module [23, 24].

491

Limitations toClinic Translation

Several limitations remain obstacles to the clinical use of LSCI.Initially introduced, LSCI was a qualitative method of perfusion assessment. Technical advancements such as introduction of multi-exposure speckle imaging now allow for quantitative assessments [25, 26]. LSCI is sensitive to motion as unwanted motion can be incorporated into the measured signal. In particular applications, such as intra-abdominal organ perfusion assessment, creating the required highly controlled environment is not always easily amenable. Recent studies have been published on motion artifact correction, but the need for a universal, real-time motion correction algorithm remains [5].

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G. Yang

Augmented Reality

AR is a technology that superimposes computer-generated objects onto real images and video in real time, often described on a virtuality continuum between real environment (direct view of real environment) and virtual reality (immersion in a fully digital environment). Recent denitions of AR platforms require the combination of real and virtual environments to be interactive in real time and registered in 3D [27]. The application of AR to medical imaging data offers several advantages. Compared to the traditional method of viewing imaging data on a separate monitor, AR visualization eliminates the need for physicians to mentally transform imaging data onto a patient. This has broad applications within medicine but further profound implications for imageguided interventions. By using AR-guided surgery, the proceduralist’s attention is not divided between navigation method and the patient resulting in improved hand-eye coordination, accuracy, and time efciency [28]. In addition, AR platforms enable stereoscopic/3D visualization of volumetric data to improve physician perception of imaging data to support the clinical decisionmaking process. Following is a review of current implementation of AR technology in surgery, as well as a brief description of the key technologies involved in developing AR platforms: medical imaging segmentation and modeling, tracking, registration, and visualization.

AR systems are currently best implemented during surgery when there is little to no movement of the real environment and when tissue deformation is minimal, as these use cases require less tracking and processing power as compared to applications on mobile organs where tracking and display are signicantly more complicated. Thus, clinical application of AR systems has been successfully implemented in the elds of neurosurgery, orthopedics, and otolaryngology, including for bone dissection, clipping of cerebral aneurysms, microvascular decompression, and placement of pedicle screws [29, 30]. AR systems have demonstrated accurate registration (0.2–3mm), but increased

17 Future Directions inFluorescence-and Image-Guided Surgery

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operative time and potential associated nancial costs have been reported with the use of AR systems for intraoperative guidance [31].

AR has been difcult to apply to abdominal surgery due to the amount of organ movement. Successful use cases have been reported for liver and pancreatic surgery, where AR has been used to compare the reconstructed virtual model with intraoperative ultrasound to identify lesions for resection [32]. Successful superimposed 3D representation of the patient’s hepatobiliary structures over the surgeon’s eld of view has been studied during open liver surgery [33]. Intraoperative AR has been used to accurately detect sentinel lymph node using preoperative SPECT/CT scan [34]. Recently, RSIP Vision, a company specializing in image analysis and articial intelligence for medical imaging, has developed RSIP Neph, an intraoperative AR tool that assists surgeons during partial nephrectomy to accurately locate and resect intracapsular renal lesions [35].

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Image Segmentation

The datasets presented from medical imaging are large, making them challenging to manipulate in real time. Image segmentation is the processing of medical imaging to isolate regions of interest and generate a model to interactively visualize the area. Identifying the relevant anatomy has traditionally been achieved by marking structures either manually or semi-autonomously within each individual image. Although several open-source packages are available to facilitate this process, image segmentation remains a limiting factor to clinical application of AR surgical guidance. Signicant research efforts are underway to develop generalizable autonomous image segmentation; however, a proven and clinically accepted method is yet to be established because of similar contrast intensity between neighboring tissue, unclear lesion/target boundary, and variation in lesion/target shape [36].

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