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Husarova, T.; Maccuaig, W.M.; Dennahy, I.S.; Sanderson, E.J.; Edil, B.H.; Jain, A.; Bonds, M.M.; Mcnally, M.W.; Menclova, K.; Pudil, J.; et al. Intraoperative Imaging in Hepatopancreatobiliary Surgery. Encyclopedia. Available online: https://encyclopedia.pub/entry/50608 (accessed on 22 February 2024).
Husarova T, Maccuaig WM, Dennahy IS, Sanderson EJ, Edil BH, Jain A, et al. Intraoperative Imaging in Hepatopancreatobiliary Surgery. Encyclopedia. Available at: https://encyclopedia.pub/entry/50608. Accessed February 22, 2024.
Husarova, Tereza, William M. Maccuaig, Isabel S. Dennahy, Emma J. Sanderson, Barish H. Edil, Ajay Jain, Morgan M. Bonds, Molly W. Mcnally, Katerina Menclova, Jiri Pudil, et al. "Intraoperative Imaging in Hepatopancreatobiliary Surgery" Encyclopedia, https://encyclopedia.pub/entry/50608 (accessed February 22, 2024).
Husarova, T., Maccuaig, W.M., Dennahy, I.S., Sanderson, E.J., Edil, B.H., Jain, A., Bonds, M.M., Mcnally, M.W., Menclova, K., Pudil, J., Zaruba, P., Pohnan, R., Henson, C.E., Grizzle, W.E., & Mcnally, L.R. (2023, October 20). Intraoperative Imaging in Hepatopancreatobiliary Surgery. In Encyclopedia. https://encyclopedia.pub/entry/50608
Husarova, Tereza, et al. "Intraoperative Imaging in Hepatopancreatobiliary Surgery." Encyclopedia. Web. 20 October, 2023.
Intraoperative Imaging in Hepatopancreatobiliary Surgery
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Hepatopancreatobiliary surgery belongs to one of the most complex fields of general surgery. An intricate and vital anatomy is accompanied by difficult distinctions of tumors from fibrosis and inflammation; the identification of precise tumor margins; or small, even disappearing, lesions on currently available imaging. The routine implementation of ultrasound use shifted the possibilities in the operating room, yet more precision is necessary to achieve negative resection margins. Modalities utilizing fluorescent-compatible dyes have proven their role in hepatopancreatobiliary surgery, although this is not yet a routine practice, as there are many limitations. Modalities, such as photoacoustic imaging or 3D holograms, are emerging but are mostly limited to preclinical settings. There is a need to identify and develop an ideal contrast agent capable of differentiating between malignant and benign tissue and to report on the prognostic benefits of implemented intraoperative imaging in order to navigate clinical translation.

intraoperative imaging hepatopancreatobiliary surgery targeted imaging

1. Introduction

The current practice of perioperative imaging in hepatopancreatobiliary (HPB) surgery relies on a combination of imaging modalities including computed tomography (CT), magnetic resonance (MR), ultrasound (US), and positron emission tomography CT (PET/CT). Preoperative diagnostics have been improved by using organ-specific protocols [1][2][3][4], higher resolutions, complementary endoscopic imaging [5], and diagnostic biopsies. Even with these advances, the inability to differentiate peritumoral or chemotherapy-induced inflammation and fibrosis from the tumor itself persists; the detection of early stages of dissemination or determination of the extent of malignancy close to the dense vasculature of the upper gastrointestinal tract remains challenging. Often, small satellite lesions and microscopic margins are not evident with available imaging modalities, secondary to alterations in tissue composition due to other disease processes, examples being pancreatitis, steatosis of the liver, and cirrhosis. Intraoperatively, the surgeon’s only tools to navigate these difficulties are US, fresh frozen sectioning (FFS), and experience. FFS is the standard of care for intraoperative guidance, but there are numerous limitations to this method. These are mainly the length of the process, analysis limited to small amounts of tissues, analysis of small operative areas, and a notable discrepancy between FFS and definitive histopathology of up to 12.9% [6][7]. Importantly, if the FFS margins were positive, the tumor is not resected in-block. Obtaining additional margins in HPB surgery is often not possible, as further resection may require the resection of vital vasculatures such as the superior mesenteric artery in pancreas surgery, the portal triad, or hepatic venous structures, which would result in a too-small future liver remnant in the liver resection.

2. Ultrasound

US is used transabdominally and endoscopically (EUS); it is also the only routinely used intraoperative imaging modality in HPB surgery (IOUS). Techniques such as contrast enhancement (CEUS), doppler mode, or elastography have also been implemented [8]. US became a standard of care in any surgical facility performing liver surgery in order to image complex and individually variable areas of liver anatomy and to improve tumor detection in real time; ablative liver therapies are not feasible without the use of IOUS [9]. The profound benefits and advances made with the use of IOUS in liver surgery are well documented [10][11][12]; the “radical but conservative” strategy of G. Torzilli et al. in performing more complex resections using IOUS led to a shift from major liver resections to more precise and complex parenchyma-sparing surgeries [13]. Even today, in the era of high-resolution MR and CT, IOUS, or more precisely, contrast-enhanced intraoperative ultrasound (CEIOUS), have superior qualities [12][14], and their accuracy has a fundamental effect on surgical strategies in liver surgery [15][16]. Nevertheless, the intra-operative use of US requires expertise, with a notable learning curve of 40 pancreatic and 50 liver cases [17]. Other potential problems include a lack of precise visibility in subcapsular areas and lesions less than 5 mm [18][19]. Image quality is limited in the setting of liver disease and in the area where ablative therapy was previously used. Also, there is currently an insufficient amount of data on the outcomes of US use in laparoscopic surgery [20].

3. Optical Imaging with Fluorescent Agents

A well-studied method in HPB surgery uses optical imaging with near-infrared fluorescence (NIR) agents [21][22][23]. Infrared light has a better tissue penetration, of up to 1 cm, compared with visible light, and the minimal autofluorescence of tissues in the NIR spectrum improves the target-to-background ratio (TBR) [24]. As multispectral cameras with a fusion of RGB and NIR imaging are widely available, imaging is fast and includes no damaging radiation. NIR imaging was initially used to determine cardiac output and hepatic function [25][26]. At present, its spectrum of use includes the assessment of tissue perfusion, ophthalmic angiography, sentinel lymph node evaluation, ureter visualization, and tumor mapping.
The only FDA- and European Medicines Agency-approved fluorescent dyes are indocyanine green [27] and methylene blue (MB) [28]. Both dyes have been implemented in HPB surgery as perfusion agents. MB is often used as a visible stain as it is rapidly recognizable to the naked eye. However, with an excitation peak of around 700 nm, background tissue shows more autofluorescence in fluorescent images. The potential use of MB in HPB surgery is based on the ability to mark anatomic liver parenchymal resection margins [29] and detect bile leaks after liver resections [30].
The use of ICG is more widespread because it has an excitation peak of approximately 800 nm. This peak allows for superior visualization compared with MB because of the elimination of background autofluorescence, although it is difficult to detect with the eye alone, in contrast to MB [31]. Consensus guidelines for the use of fluorescence imaging in hepatobiliary surgery were published in 2021 by a group of Asia-Pacific experts [32] focusing on ICG use in liver and biliary surgery. ICG can be injected directly into the biliary system or intravenously, which could be considered a safer route. After intravenous application and binding to plasma proteins, ICG is taken up by hepatocytes and then fully eliminated via bile. These kinetics make it effective for imaging the extrahepatic biliary anatomy [33][34][35], a particularly beneficial trait in cases with anomalous or intricate biliary anatomies. Despite the notable benefits, ICG is unable to visualize the intrahepatic biliary tree because of limited tissue penetration or precisely identify common bile duct stones, probably because of the high concentrations of dye in bile.
In tumor imaging, ICG has a sensitivity of up to 99% in identifying hepatocellular carcinoma (HCC) lesions [36], which has led to a more widespread use primarily in eastern countries, where the incidence of HCC is high. Yet, the average rate of false positivity is 10.5% [37]. Colorectal liver metastases (CRLM) tend to display a rim pattern of fluorescence; this may be due to the extensive central necrosis that is common in CRLM, or possibly, it may be due to distorted biliary extraction in immature hepatocytes surrounding the tumor tissue that, conversely, do not uptake the dye [38]. A newly published study on imaging superficial CRLM using ICG identified the ability to detect “disappearing lesions” after downstaging chemotherapy in 15 patients [39]. While the depth of the visualization is the main limit of ICG imaging, combining fluorescence and IOUS has proven to be superior to preoperative CT or IOUS alone in the detection of CRLMs ≤ 3 mm [19]. “Positive” and “negative” staining techniques have been described to help guide anatomic resection margins [40].
The use of nonspecific dyes in pancreatic surgery has many limitations, and only a few reports exist. Healthy pancreases show a similar ICG uptake to tumor tissue, which creates ineffective tumor-to-background ratios (TBR) in carcinomas [41]. The way to potentially improve TBR with nonspecific dyes is using a second window technique (high-dose ICG injected intravenously 24 h prior to surgery). Given its enhanced permeability and retention effect (EPR), a TBR of 4.42 was achieved in 20 patients with malignant lesions enrolled in an open-label clinical trial [42][43]; three out of eight benign lesions were fluorescent as well.
Shirata et al. used intravenous ICG injected intraoperatively to image pancreatic ductal adenocarcinoma (PDAC), pancreatic NETs, and cystic neoplasms in 23 consecutive patients, proving the proposed hypothesis of visualization based on the hypovascularization (cystic lesions) or hypervascularization of lesions [44]. The reported TBR of the NETs was 1.99, with all the lesions successfully visualized intraoperatively (100% sensitivity). Cystic neoplasms showed lower fluorescent signals and a TBR of 0.54, with fair-to-poor visualization. The TBR of PDAC was of no statistical significance. These data are in line with other presented case reports; the COLPAN study reported 100% sensitivity in the laparoscopic ICG imaging of pancreatic NETs with a mean TBR of 7.7, peaking at 20 min after intravenous application [45]. Hutteman et al. reported no clear visualization of pancreatic carcinoma using intraoperative ICG, with a mean TBR of 1.22 ± 0.39 [41]. A recently published meta-analysis of ICG use in pancreatic surgery found six papers with a total of 64 lesions reported [46]; the overall sensitivity for all pancreatic lesions was 75% and a mean TBR of 1.22. The authors correctly pointed out the unknown effect of neoadjuvant therapy on visualization and the unknown effects of ICG use on recurrence-free and overall survival in pancreatic surgery.
While recommendations on ICG dosage and the timing of administration in liver and biliary surgery exist [32], there is a large inter-institutional discrepancy between dosages, ranging from a bolus of 2.5 mg to 5 mg/kg, and the timing of ICG administration in pancreatic tumor imaging [41][42]. Perhaps one of the main challenges is the fact that, while liver metastasis and the primary tumor site may benefit from the second window technique, peritoneal metastases are likely to be missed at the time of exploration and could require intraoperative ICG applications [47]. In contrast, the administration of ICG intraoperatively leads to unavoidable background fluorescence in the liver and biliary tract. As the current papers suggest, different pancreatic neoplasms will probably require different ICG administration timing. The timing of administration is currently being studied in a Japanese trial: jRCT1051180076.
Pancreatic surgery is burdened with high rates of R1 resections in up to 80% of cases [48][49] and difficulty in staging patients after neoadjuvant therapy, especially in evaluating the degree of treatment response within the tumor. The high rate of R1 resections is partially influenced by vascular invasion and a previous lack of widespread adoption of standardized pathologist protocols [50]. R0 resection is, however, an independent prognostic factor of survival after pancreatic resection [48], therefore, the ability to precisely image pancreatic tumors in the operating room would be an important milestone in pancreatic surgery. The era of minimally invasive surgery, where tactile feedback is omitted, calls for even more precise intraoperative imaging. New methods emerge with the aim of improving fluorescent imaging, e.g., the second near-infrared wavelength window NIR-II (1000–1700 nm), which suggests a higher sensitivity and detection of up to 8mm deep [51]. More studies evaluating the impact of fluorescence on intraoperative decision making are needed. Reporting was suggested by Lauwerends et al. [52].

4. Optoacoustic-Based Imaging

Optoacoustic (OA), or photoacoustic imaging, is another emerging method with significant potential. The principle of “light-in, sound-out” is utilized [53]; the absorption of near-infrared light generates acoustic waves via the thermoelastic expansion of tissues that are detected using a computerized transducer. In biological tissues, sound scatters 1000 times slower than light, circumventing the resolution/imaging depth tradeoff that hinders the application of optical imaging [54]. In addition, as biological tissue is largely transparent to near-infrared light, imaging depths of approximately 5 cm are achievable with no sacrifices in resolution [55][56]. While optical imaging agents, i.e., ICG, methylene blue, and IR-800-CW dyes, are detectable using both optical imaging and optoacoustic imaging, these agents are optimized to generate the largest fluorescence signal and represent suboptimal optoacoustic agents. Optical imaging with agents such as ICG requires a path length double of that of optoacoustic imaging while also utilizing higher-energy light, which is more susceptible to photon absorption and scatter in biological tissue.
Both endogenous and exogenous contrast agents can be detected with optoacoustic imaging. While endogenous contrast agents eliminate the problems of utilizing dyes in tissues, they are usually weak reporters with non-unique spectra [57]. However, there is a current lack of contrast agents that are developed and optimized for optoacoustic imaging [57][58][59][60][61]. The unique optical properties, e.g., optical absorption as a function of wavelength, of different contrast agents lead to the ability of “unmixing” images to determine the location and concentration of each unique agent simultaneously. This unmixing capability in the context of optoacoustic imaging is called multispectral optoacoustic tomography (MSOT). Specifically, multiwavelength illumination is used to identify the absorption and emission spectra for every contrast agent in an area to differentiate between background and individual contrast agent signals in a murine model. This capability could be utilized to provide information about a tumor’s molecular features and/or structure’s metabolism within tissues [62][63][64][65][66][67][68]. For example, a response to oxyhemoglobin may outline an artery in the vicinity of angiogenesis as a symptom of tumor progression. The development of OA agents can significantly improve the capabilities of in vivo imaging, such as identifying deep tumors following the administration of an OA agent in a murine model. This is a major advantage when aiming to distinguish tumors from peri-tumoral fibrosis, necrosis, and inflammation. For example, benign and malignant gallbladder polyps were shown to have different OA signal intensities [69].
The visualization of molecules within 200 uM blood vessels can be achieved without the artifacts associated with vascularly dense tissues or the vessels themselves with NIR [70][71][72]. In contrast, ICG loses fluorescence intensity after binding to proteins in blood vessels when visualized with NIR [73], therefore limiting use in highly vascular tissues, which is often the case in HPB surgery. Furthermore, the ICG signal may be hindered further by blood pooling within the surgical field secondary to blood loss, which is not uncommon in hepatobiliary surgery [74]. Of importance, hemoglobin is one of the few strong endogenous contrast agents that allow for the identification of microvascular changes and tissue oxygenation using MSOT [53][75], and it has been successfully used to monitor tumor responses to antiangiogenic agents in mouse models [76]. Exogenous contrast agents used for OA imaging in preclinical mouse studies include organic dyes, such as ICG, and nanoparticles, such as gold, silver, tungsten, iron oxide, and carbon nanotubes [57][65][66]. OAI showed a 3.7 TBR in the resected specimens of patients with PDAC when targeted with cetuximab-IRDye800, a NIR fluorescent agent that binds to the epidermal growth factor receptor [77].

5. Photodynamic Imaging

The concept of photodynamic diagnosis, or photodynamic imaging (PDD), utilizes the application of photosensitizers that accumulate in targeted tissues that can then be imaged upon excitation using specific infrared (IR) wavelengths. The photodynamic effects of ICG and similar molecules are expected upon excitation with an infrared laser (805 nm) during the surgical procedure.
Most of the data on photodynamic imaging are in preclinical proof-of-concept studies in small case series in various proposed areas of HPB surgery, notably in the successful imaging of HCC using ALA [78][79] and the determination of tumor margins for cholangiocarcinoma in a mouse model [80]. Another study tested laparoscopic photodynamic imaging to detect carcinomatosis in a staging laparoscopy for pancreatic cancer. Staging laparoscopies are a common practice for high-risk patients with HPB malignancy because of a lack of ability in preoperative imaging to precisely determine the early stages of peritoneal dissemination; however, this is currently solely dependent on the surgeon’s experience. Indicating an area that needs more improvement, the study reported an increased rate of laparoscopic detection of peritoneal dissemination with fluorescence and even higher rates with spectrophotometry compared with white light in mouse models. Perhaps the greatest limitation of PDD in laparoscopy, especially for ALA, which has emission peaks in the spectrum of red-to-near-infrared light, is the low concentrations of fluorophores not limited to superficial layers. The study used spectrophotometry to overcome this limitation. The rate of ex vivo detection in human specimens using spectrophotometry was 63% [81]. New photosensitizing agents and nanocarriers are being tested [82][83]. There is also an interest in finding adjuvant agents to accelerate protoporphyrin accumulation in tumors, e.g., the currently active clinical trial NCT03467789, which is evaluating the effect of vitamin D.

6. Intraoperative 3D Imaging

Creating a three-dimensional image is a natural next step in today’s digital era [84]. Three-dimensional modeling and its derived volumetric calculations are not uncommon in liver and biliary surgery. Data proving more precise preoperative planning in liver resection for HCC in 3D vs. 2D were recently published [85]. The idea of supporting intraoperative orientation led to the creation of 3D holograms, or 3D modeling, which faced the challenge of changing organ shapes during intraoperative manipulation. Today, “last-minute simulation” is mostly reported rather than intraoperative navigation, necessitating more research [86][87].

References

  1. Fukukura, Y.; Kumagae, Y.; Fujisaki, Y.; Yamagishi, R.; Nakamura, S.; Kamizono, J.; Nakajo, M.; Kamimura, K.; Nagano, H.; Takumi, K.; et al. Adding Delayed Phase Images to Dual-Phase Contrast-Enhanced CT Increases Sensitivity for Small Pancreatic Ductal Adenocarcinoma. AJR Am. J. Roentgenol. 2021, 217, 888–897.
  2. Donato, H.; Franca, M.; Candelaria, I.; Caseiro-Alves, F. Liver MRI: From basic protocol to advanced techniques. Eur. J. Radiol. 2017, 93, 30–39.
  3. Choi, J.Y.; Lee, J.M.; Sirlin, C.B. CT and MR imaging diagnosis and staging of hepatocellular carcinoma: Part I. Development, growth, and spread: Key pathologic and imaging aspects. Radiology 2014, 272, 635–654.
  4. Choi, J.Y.; Lee, J.M.; Sirlin, C.B. CT and MR imaging diagnosis and staging of hepatocellular carcinoma: Part II. Extracellular agents, hepatobiliary agents, and ancillary imaging features. Radiology 2014, 273, 30–50.
  5. Gonzalo-Marin, J.; Vila, J.J.; Perez-Miranda, M. Role of endoscopic ultrasound in the diagnosis of pancreatic cancer. World J. Gastrointest. Oncol. 2014, 6, 360–368.
  6. Voskuil, F.J.; Vonk, J.; van der Vegt, B.; Kruijff, S.; Ntziachristos, V.; van der Zaag, P.J.; Witjes, M.J.H.; van Dam, G.M. Intraoperative imaging in pathology-assisted surgery. Nat. Biomed. Eng. 2022, 6, 503–514.
  7. Nelson, D.W.; Blanchard, T.H.; Causey, M.W.; Homann, J.F.; Brown, T.A. Examining the accuracy and clinical usefulness of intraoperative frozen section analysis in the management of pancreatic lesions. Am. J. Surg. 2013, 205, 613–617.
  8. Bartos, A.; Iancu, I.; Ciobanu, L.; Badea, R.; Sparchez, Z.; Bartos, D.M. Intraoperative ultrasound in liver and pancreatic surgery. Med. Ultrason. 2021, 23, 319–328.
  9. Lee, J.Y.; Kim, Y.H.; Roh, Y.H.; Roh, K.B.; Kim, K.W.; Kang, S.H.; Baek, Y.H.; Lee, S.W.; Han, S.Y.; Kwon, H.J.; et al. Intraoperative radiofrequency ablation for hepatocellular carcinoma in 112 patients with cirrhosis: A surgeon’s view. Ann. Surg. Treat. Res. 2016, 90, 147–156.
  10. Torzilli, G.; Leoni, P.; Gendarini, A.; Calliada, F.; Olivari, N.; Makuuchi, M. Ultrasound-guided liver resections for hepatocellular carcinoma. Hepatogastroenterology 2002, 49, 21–27.
  11. Sietses, C.; Meijerink, M.R.; Meijer, S.; van den Tol, M.P. The impact of intraoperative ultrasonography on the surgical treatment of patients with colorectal liver metastases. Surg. Endosc. 2010, 24, 1917–1922.
  12. Hoch, G.; Croise-Laurent, V.; Germain, A.; Brunaud, L.; Bresler, L.; Ayav, A. Is intraoperative ultrasound still useful for the detection of colorectal cancer liver metastases? HPB 2015, 17, 514–519.
  13. Torzilli, G.; Montorsi, M.; Donadon, M.; Palmisano, A.; Del Fabbro, D.; Gambetti, A.; Olivari, N.; Makuuchi, M. “Radical but conservative” is the main goal for ultrasonography-guided liver resection: Prospective validation of this approach. J. Am. Coll. Surg. 2005, 201, 517–528.
  14. Sahani, D.V.; Kalva, S.P.; Tanabe, K.K.; Hayat, S.M.; O’Neill, M.J.; Halpern, E.F.; Saini, S.; Mueller, P.R. Intraoperative US in patients undergoing surgery for liver neoplasms: Comparison with MR imaging. Radiology 2004, 232, 810–814.
  15. Torzilli, G.; Del Fabbro, D.; Palmisano, A.; Donadon, M.; Bianchi, P.; Roncalli, M.; Balzarini, L.; Montorsi, M. Contrast-enhanced intraoperative ultrasonography during hepatectomies for colorectal cancer liver metastases. J. Gastrointest. Surg. 2005, 9, 1148–1153; discussion 1153–1144.
  16. Shah, A.J.; Callaway, M.; Thomas, M.G.; Finch-Jones, M.D. Contrast-enhanced intraoperative ultrasound improves detection of liver metastases during surgery for primary colorectal cancer. HPB 2010, 12, 181–187.
  17. Parks, K.R.; Hagopian, E.J. Introduction: The Importance of Ultrasound in a Surgical Practice. In Abdominal Ultrasound for Surgeons; Hagopian, E.J., Machi, J., Eds.; Springer: New York, NY, USA, 2014; pp. 3–6.
  18. Claudon, M.; Dietrich, C.F.; Choi, B.I.; Cosgrove, D.O.; Kudo, M.; Nolsoe, C.P.; Piscaglia, F.; Wilson, S.R.; Barr, R.G.; Chammas, M.C.; et al. Guidelines and good clinical practice recommendations for contrast enhanced ultrasound (CEUS) in the liver--update 2012: A WFUMB-EFSUMB initiative in cooperation with representatives of AFSUMB, AIUM, ASUM, FLAUS and ICUS. Ultraschall Med. 2013, 34, 11–29.
  19. Peloso, A.; Franchi, E.; Canepa, M.C.; Barbieri, L.; Briani, L.; Ferrario, J.; Bianco, C.; Quaretti, P.; Brugnatelli, S.; Dionigi, P.; et al. Combined use of intraoperative ultrasound and indocyanine green fluorescence imaging to detect liver metastases from colorectal cancer. HPB 2013, 15, 928–934.
  20. van der Steen, K.; Bosscha, K.; Lips, D.J. The value of laparoscopic intraoperative ultrasound of the liver by the surgeon. Ann. Laparosc. Endosc. Surg. 2021, 6, 17.
  21. Ishizawa, T.; Bandai, Y.; Ijichi, M.; Kaneko, J.; Hasegawa, K.; Kokudo, N. Fluorescent cholangiography illuminating the biliary tree during laparoscopic cholecystectomy. Br. J. Surg. 2010, 97, 1369–1377.
  22. Ashitate, Y.; Stockdale, A.; Choi, H.S.; Laurence, R.G.; Frangioni, J.V. Real-time simultaneous near-infrared fluorescence imaging of bile duct and arterial anatomy. J. Surg. Res. 2012, 176, 7–13.
  23. Aoki, T.; Murakami, M.; Yasuda, D.; Shimizu, Y.; Kusano, T.; Matsuda, K.; Niiya, T.; Kato, H.; Murai, N.; Otsuka, K.; et al. Intraoperative fluorescent imaging using indocyanine green for liver mapping and cholangiography. J. Hepatobiliary Pancreat. Sci. 2010, 17, 590–594.
  24. van Manen, L.; Handgraaf, H.J.M.; Diana, M.; Dijkstra, J.; Ishizawa, T.; Vahrmeijer, A.L.; Mieog, J.S.D. A practical guide for the use of indocyanine green and methylene blue in fluorescence-guided abdominal surgery. J. Surg. Oncol. 2018, 118, 283–300.
  25. Detter, C.; Wipper, S.; Russ, D.; Iffland, A.; Burdorf, L.; Thein, E.; Wegscheider, K.; Reichenspurner, H.; Reichart, B. Fluorescent cardiac imaging: A novel intraoperative method for quantitative assessment of myocardial perfusion during graded coronary artery stenosis. Circulation 2007, 116, 1007–1014.
  26. Dorshow, R.B.; Bugaj, J.E.; Burleigh, B.D.; Duncan, J.R.; Johnson, M.A.; Jones, W.B. Noninvasive fluorescence detection of hepatic and renal function. J. Biomed. Opt. 1998, 3, 340–345.
  27. Alexandrov, L.B.; Nik-Zainal, S.; Wedge, D.C.; Aparicio, S.A.; Behjati, S.; Biankin, A.V.; Bignell, G.R.; Bolli, N.; Borg, A.; Borresen-Dale, A.L.; et al. Signatures of mutational processes in human cancer. Nature 2013, 500, 415–421.
  28. Debie, P.; Hernot, S. Emerging Fluorescent Molecular Tracers to Guide Intra-Operative Surgical Decision-Making. Front. Pharmacol. 2019, 10, 510.
  29. Cai, S.; Yang, S.; Lv, W.; Geng, C.; Gu, W.; Duan, W.; Wang, W.; Huang, Z.; Dong, J. Sustained methylene blue staining to guide anatomic hepatectomy for hepatocellular carcinoma: Initial experience and technical details. Surgery 2015, 158, 121–127.
  30. Tuysuz, U.; Aktas, H.; Bati, I.B.; Emiroglu, R. The role of Intraoperative cholangiography (IOC) and methylene blue tests in reducing bile leakage after living donor hepatectomy. Asian J. Surg. 2021, 44, 147–152.
  31. Van Keulen, S.; Hom, M.; White, H.; Rosenthal, E.L.; Baik, F.M. The Evolution of Fluorescence-Guided Surgery. Mol. Imaging Biol. 2023, 25, 36–45.
  32. Wang, X.; Teh, C.S.C.; Ishizawa, T.; Aoki, T.; Cavallucci, D.; Lee, S.Y.; Panganiban, K.M.; Perini, M.V.; Shah, S.R.; Wang, H.; et al. Consensus Guidelines for the Use of Fluorescence Imaging in Hepatobiliary Surgery. Ann. Surg. 2021, 274, 97–106.
  33. Ishizawa, T.; Bandai, Y.; Kokudo, N. Fluorescent cholangiography using indocyanine green for laparoscopic cholecystectomy: An initial experience. Arch. Surg. 2009, 144, 381–382.
  34. Pesce, A.; Piccolo, G.; La Greca, G.; Puleo, S. Utility of fluorescent cholangiography during laparoscopic cholecystectomy: A systematic review. World J. Gastroenterol. 2015, 21, 7877–7883.
  35. Gene Skrabec, C.; Pardo Aranda, F.; Espin, F.; Cremades, M.; Navines, J.; Zarate, A.; Cugat, E. Fluorescent cholangiography with direct injection of indocyanine green (ICG) into the gallbladder: A safety method to outline biliary anatomy. Langenbecks Arch. Surg. 2020, 405, 827–832.
  36. Ishizawa, T.; Masuda, K.; Urano, Y.; Kawaguchi, Y.; Satou, S.; Kaneko, J.; Hasegawa, K.; Shibahara, J.; Fukayama, M.; Tsuji, S.; et al. Mechanistic background and clinical applications of indocyanine green fluorescence imaging of hepatocellular carcinoma. Ann. Surg. Oncol. 2014, 21, 440–448.
  37. Wakabayashi, T.; Cacciaguerra, A.B.; Abe, Y.; Bona, E.D.; Nicolini, D.; Mocchegiani, F.; Kabeshima, Y.; Vivarelli, M.; Wakabayashi, G.; Kitagawa, Y. Indocyanine Green Fluorescence Navigation in Liver Surgery: A Systematic Review on Dose and Timing of Administration. Ann. Surg. 2022, 275, 1025–1034.
  38. van der Vorst, J.R.; Schaafsma, B.E.; Hutteman, M.; Verbeek, F.P.R.; Liefers, G.J.; Hartgrink, H.H.; Smit, V.T.H.B.M.; Lowik, C.W.G.M.; van de Velde, C.J.H.; Frangioni, J.V.; et al. Near-infrared fluorescence-guided resection of colorectal liver metastases. Cancer 2013, 119, 3411–3418.
  39. Patel, I.; Bartlett, D.; Dasari, B.V.; Chatzizacharias, N.; Isaac, J.; Marudanayagam, R.; Mirza, D.F.; Roberts, J.K.; Sutcliffe, R.P. Detection of Colorectal Liver Metastases Using Near-Infrared Fluorescence Imaging During Hepatectomy: Prospective Single Centre UK Study. J. Gastrointest. Cancer 2022.
  40. Ishizawa, T.; Zuker, N.B.; Kokudo, N.; Gayet, B. Positive and negative staining of hepatic segments by use of fluorescent imaging techniques during laparoscopic hepatectomy. Arch Surg. 2012, 147, 393–394.
  41. Hutteman, M.; van der Vorst, J.R.; Mieog, J.S.; Bonsing, B.A.; Hartgrink, H.H.; Kuppen, P.J.; Lowik, C.W.; Frangioni, J.V.; van de Velde, C.J.; Vahrmeijer, A.L. Near-infrared fluorescence imaging in patients undergoing pancreaticoduodenectomy. Eur. Surg. Res. 2011, 47, 90–97.
  42. Newton, A.D.; Predina, J.D.; Shin, M.H.; Frenzel-Sulyok, L.G.; Vollmer, C.M.; Drebin, J.A.; Singhal, S.; Lee, M.K.T. Intraoperative Near-infrared Imaging Can Identify Neoplasms and Aid in Real-time Margin Assessment During Pancreatic Resection. Ann. Surg. 2019, 270, 12–20.
  43. Lohman, R.F.; Ozturk, C.N.; Ozturk, C.; Jayaprakash, V.; Djohan, R. An Analysis of Current Techniques Used for Intraoperative Flap Evaluation. Ann. Plast. Surg. 2015, 75, 679–685.
  44. Shirata, C.; Kawaguchi, Y.; Kobayashi, K.; Kobayashi, Y.; Arita, J.; Akamatsu, N.; Kaneko, J.; Sakamoto, Y.; Kokudo, N.; Hasegawa, K. Usefulness of indocyanine green-fluorescence imaging for real-time visualization of pancreas neuroendocrine tumor and cystic neoplasm. J. Surg. Oncol. 2018, 118, 1012–1020.
  45. Paiella, S.; De Pastena, M.; Landoni, L.; Esposito, A.; Casetti, L.; Miotto, M.; Ramera, M.; Salvia, R.; Secchettin, E.; Bonamini, D.; et al. Is there a role for near-infrared technology in laparoscopic resection of pancreatic neuroendocrine tumors? Results of the COLPAN “colour-and-resect the pancreas” study. Surg. Endosc. 2017, 31, 4478–4484.
  46. Rompianesi, G.; Montalti, R.; Giglio, M.C.; Ceresa, C.D.L.; Nasto, R.A.; De Simone, G.; Troisi, R.I. Systematic review, meta-analysis and single-centre experience of the diagnostic accuracy of intraoperative near-infrared indocyanine green-fluorescence in detecting pancreatic tumours. HPB 2022, 24, 1823–1831.
  47. Liberale, G.; Vankerckhove, S.; Caldon, M.G.; Ahmed, B.; Moreau, M.; Nakadi, I.E.; Larsimont, D.; Donckier, V.; Bourgeois, P.; Group, R.; et al. Fluorescence Imaging After Indocyanine Green Injection for Detection of Peritoneal Metastases in Patients Undergoing Cytoreductive Surgery for Peritoneal Carcinomatosis from Colorectal Cancer: A Pilot Study. Ann. Surg. 2016, 264, 1110–1115.
  48. Leonhardt, C.S.; Niesen, W.; Kalkum, E.; Klotz, R.; Hank, T.; Buchler, M.W.; Strobel, O.; Probst, P. Prognostic relevance of the revised R status definition in pancreatic cancer: Meta-analysis. BJS Open 2022, 6, zrac010.
  49. Verbeke, C.S.; Menon, K.V. Redefining resection margin status in pancreatic cancer. HPB 2009, 11, 282–289.
  50. Strobel, O.; Hank, T.; Hinz, U.; Bergmann, F.; Schneider, L.; Springfeld, C.; Jager, D.; Schirmacher, P.; Hackert, T.; Buchler, M.W. Pancreatic Cancer Surgery: The New R-status Counts. Ann. Surg. 2017, 265, 565–573.
  51. Hu, Z.; Fang, C.; Li, B.; Zhang, Z.; Cao, C.; Cai, M.; Su, S.; Sun, X.; Shi, X.; Li, C.; et al. First-in-human liver-tumour surgery guided by multispectral fluorescence imaging in the visible and near-infrared-I/II windows. Nat. Biomed. Eng. 2020, 4, 259–271.
  52. Lauwerends, L.J.; van Driel, P.; Baatenburg de Jong, R.J.; Hardillo, J.A.U.; Koljenovic, S.; Puppels, G.; Mezzanotte, L.; Lowik, C.; Rosenthal, E.L.; Vahrmeijer, A.L.; et al. Real-time fluorescence imaging in intraoperative decision making for cancer surgery. Lancet Oncol. 2021, 22, e186–e195.
  53. McNally, L.R.; Mezera, M.; Morgan, D.E.; Frederick, P.J.; Yang, E.S.; Eltoum, I.E.; Grizzle, W.E. Current and Emerging Clinical Applications of Multispectral Optoacoustic Tomography (MSOT) in Oncology. Clin. Cancer Res. 2016, 22, 3432–3439.
  54. Attia, A.B.E.; Balasundaram, G.; Moothanchery, M.; Dinish, U.S.; Bi, R.; Ntziachristos, V.; Olivo, M. A review of clinical photoacoustic imaging: Current and future trends. Photoacoustics 2019, 16, 100144.
  55. Wang, L.V.; Hu, S. Photoacoustic tomography: In vivo imaging from organelles to organs. Science 2012, 335, 1458–1462.
  56. Hudson, S.V.; Huang, J.S.; Yin, W.; Albeituni, S.; Rush, J.; Khanal, A.; Yan, J.; Ceresa, B.P.; Frieboes, H.B.; McNally, L.R. Targeted noninvasive imaging of EGFR-expressing orthotopic pancreatic cancer using multispectral optoacoustic tomography. Cancer Res. 2014, 74, 6271–6279.
  57. MacCuaig, W.M.; Jones, M.A.; Abeyakoon, O.; McNally, L.R. Development of Multispectral Optoacoustic Tomography as a Clinically Translatable Modality for Cancer Imaging. Radiol. Imaging Cancer 2020, 2, e200066.
  58. Chen, Z.; Dean-Ben, X.L.; Gottschalk, S.; Razansky, D. Performance of optoacoustic and fluorescence imaging in detecting deep-seated fluorescent agents. Biomed. Opt. Express 2018, 9, 2229–2239.
  59. Bhutiani, N.; Kimbrough, C.W.; Burton, N.C.; Morscher, S.; Egger, M.; McMasters, K.; Woloszynska-Read, A.; El-Baz, A.; McNally, L.R. Detection of microspheres in vivo using multispectral optoacoustic tomography. Biotech. Histochem. 2017, 92, 1–6.
  60. Bagley, A.F.; Ludmir, E.B.; Maitra, A.; Minsky, B.D.; Li Smith, G.; Das, P.; Koong, A.C.; Holliday, E.B.; Taniguchi, C.M.; Katz, M.H.G.; et al. NBTXR3, a first-in-class radioenhancer for pancreatic ductal adenocarcinoma: Report of first patient experience. Clin. Transl. Radiat. Oncol. 2022, 33, 66–69.
  61. Dennahy, I.S.; Han, Z.; MacCuaig, W.M.; Chalfant, H.M.; Condacse, A.; Hagood, J.M.; Claros-Sorto, J.C.; Razaq, W.; Holter-Chakrabarty, J.; Squires, R.; et al. Nanotheranostics for Image-Guided Cancer Treatment. Pharmaceutics 2022, 14, 917.
  62. Herzog, E.; Taruttis, A.; Beziere, N.; Lutich, A.A.; Razansky, D.; Ntziachristos, V. Optical imaging of cancer heterogeneity with multispectral optoacoustic tomography. Radiology 2012, 263, 461–468.
  63. Gargiulo, S.; Albanese, S.; Mancini, M. State-of-the-Art Preclinical Photoacoustic Imaging in Oncology: Recent Advances in Cancer Theranostics. Contrast Media Mol. Imaging 2019, 2019, 5080267.
  64. Ntziachristos, V.; Pleitez, M.A.; Aime, S.; Brindle, K.M. Emerging Technologies to Image Tissue Metabolism. Cell Metab. 2019, 29, 518–538.
  65. Laramie, M.D.; Fouts, B.L.; MacCuaig, W.M.; Buabeng, E.; Jones, M.A.; Mukherjee, P.; Behkam, B.; McNally, L.R.; Henary, M. Improved pentamethine cyanine nanosensors for optoacoustic imaging of pancreatic cancer. Sci. Rep. 2021, 11, 4366.
  66. MacCuaig, W.M.; Fouts, B.L.; McNally, M.W.; Grizzle, W.E.; Chuong, P.; Samykutty, A.; Mukherjee, P.; Li, M.; Jasinski, J.B.; Behkam, B.; et al. Active Targeting Significantly Outperforms Nanoparticle Size in Facilitating Tumor-Specific Uptake in Orthotopic Pancreatic Cancer. ACS Appl. Mater. Interfaces 2021, 13, 49614–49630.
  67. Cao, R.; Kilroy, J.P.; Ning, B.; Wang, T.; Hossack, J.A.; Hu, S. Multispectral photoacoustic microscopy based on an optical-acoustic objective. Photoacoustics 2015, 3, 55–59.
  68. Samykutty, A.; Thomas, K.N.; McNally, M.; Hagood, J.; Chiba, A.; Thomas, A.; McWilliams, L.; Behkam, B.; Zhan, Y.; Council-Troche, M.; et al. Simultaneous Detection of Multiple Tumor-targeted Gold Nanoparticles in HER2-Positive Breast Tumors Using Optoacoustic Imaging. Radiol. Imaging Cancer 2023, 5, e220180.
  69. Chae, H.D.; Lee, J.Y.; Jang, J.Y.; Chang, J.H.; Kang, J.; Kang, M.J.; Han, J.K. Photoacoustic Imaging for Differential Diagnosis of Benign Polyps versus Malignant Polyps of the Gallbladder: A Preliminary Study. Korean J. Radiol. 2017, 18, 821–827.
  70. Kimbrough, C.W.; Hudson, S.; Khanal, A.; Egger, M.E.; McNally, L.R. Orthotopic pancreatic tumors detected by optoacoustic tomography using Syndecan-1. J. Surg. Res. 2015, 193, 246–254.
  71. Bhutiani, N.; Grizzle, W.E.; Galandiuk, S.; Otali, D.; Dryden, G.W.; Egilmez, N.K.; McNally, L.R. Noninvasive Imaging of Colitis Using Multispectral Optoacoustic Tomography. J. Nucl. Med. 2017, 58, 1009–1012.
  72. Harold, K.M.; MacCuaig, W.M.; Holter-Charkabarty, J.; Williams, K.; Hill, K.; Arreola, A.X.; Sekhri, M.; Carter, S.; Gomez-Gutierrez, J.; Salem, G.; et al. Advances in Imaging of Inflammation, Fibrosis, and Cancer in the Gastrointestinal Tract. Int. J. Mol. Sci. 2022, 23, 16109.
  73. Ogawa, M.; Kosaka, N.; Choyke, P.L.; Kobayashi, H. In vivo molecular imaging of cancer with a quenching near-infrared fluorescent probe using conjugates of monoclonal antibodies and indocyanine green. Cancer Res. 2009, 69, 1268–1272.
  74. Chalfant, H.; Bonds, M.; Scott, K.; Condacse, A.; Dennahy, I.S.; Martin, W.T.; Little, C.; Edil, B.H.; McNally, L.R.; Jain, A. Innovative Imaging Techniques Used to Evaluate Borderline-Resectable Pancreatic Adenocarcinoma. J. Surg. Res. 2023, 284, 42–53.
  75. Han, Z.; MacCuaig, W.M.; Gurcan, M.N.; Claros-Sorto, J.; Garwe, T.; Henson, C.; Holter-Chakrabarty, J.; Hannafon, B.; Chandra, V.; Wellberg, E.; et al. Dynamic 2-deoxy-D-glucose-enhanced multispectral optoacoustic tomography for assessing metabolism and vascular hemodynamics of breast cancer. Photoacoustics 2023, 32, 100531.
  76. Bohndiek, S.E.; Sasportas, L.S.; Machtaler, S.; Jokerst, J.V.; Hori, S.; Gambhir, S.S. Photoacoustic Tomography Detects Early Vessel Regression and Normalization During Ovarian Tumor Response to the Antiangiogenic Therapy Trebananib. J. Nucl. Med. 2015, 56, 1942–1947.
  77. Tummers, W.S.; Miller, S.E.; Teraphongphom, N.T.; Gomez, A.; Steinberg, I.; Huland, D.M.; Hong, S.; Kothapalli, S.R.; Hasan, A.; Ertsey, R.; et al. Intraoperative Pancreatic Cancer Detection using Tumor-Specific Multimodality Molecular Imaging. Ann. Surg. Oncol. 2018, 25, 1880–1888.
  78. Nishimura, M.; Murayama, Y.; Harada, K.; Kamada, Y.; Morimura, R.; Ikoma, H.; Ichikawa, D.; Fujiwara, H.; Okamoto, K.; Otsuji, E. Photodynamic Diagnosis of Hepatocellular Carcinoma Using 5-Aminolevulinic Acid. Anticancer Res. 2016, 36, 4569–4574.
  79. Inoue, Y.; Tanaka, R.; Komeda, K.; Hirokawa, F.; Hayashi, M.; Uchiyama, K. Fluorescence detection of malignant liver tumors using 5-aminolevulinic acid-mediated photodynamic diagnosis: Principles, technique, and clinical experience. World J. Surg. 2014, 38, 1786–1794.
  80. Fujiwara, H.; Takahara, N.; Tateishi, K.; Tanaka, M.; Kanai, S.; Kato, H.; Nakatsuka, T.; Yamamoto, K.; Kogure, H.; Arita, J.; et al. 5-Aminolevulinic acid-mediated photodynamic activity in patient-derived cholangiocarcinoma organoids. Surg. Oncol. 2020, 35, 484–490.
  81. Saito, T.; Ebihara, Y.; Li, L.; Shirosaki, T.; Iijima, H.; Tanaka, K.; Nakanishi, Y.; Asano, T.; Noji, T.; Kurashima, Y.; et al. A novel laparoscopic near-infrared fluorescence spectrum system for photodynamic diagnosis of peritoneal dissemination in pancreatic cancer. Photodiagn. Photodyn. Ther. 2021, 33, 102157.
  82. Abrahamse, H.; Hamblin, M.R. New photosensitizers for photodynamic therapy. Biochem. J. 2016, 473, 347–364.
  83. Alsaab, H.O.; Alghamdi, M.S.; Alotaibi, A.S.; Alzhrani, R.; Alwuthaynani, F.; Althobaiti, Y.S.; Almalki, A.H.; Sau, S.; Iyer, A.K. Progress in Clinical Trials of Photodynamic Therapy for Solid Tumors and the Role of Nanomedicine. Cancers 2020, 12, 2793.
  84. Fang, C.; Zhang, P.; Qi, X. Digital and intelligent liver surgery in the new era: Prospects and dilemmas. EBioMedicine 2019, 41, 693–701.
  85. Felli, E.; Boleslawski, E.; Sommacale, D.; Scatton, O.; Brustia, R.; Schwarz, L.; Cherqui, D.; Zacharias, T.; Laurent, A.; Mabrut, J.Y.; et al. Paradigm shift: Should preoperative 3D reconstruction models become mandatory before hepatectomy for hepatocellular carcinoma (HCC)? Results of a multicenter prospective trial. HPB 2023, 25, 293–300.
  86. Saito, Y.; Sugimoto, M.; Imura, S.; Morine, Y.; Ikemoto, T.; Iwahashi, S.; Yamada, S.; Shimada, M. Intraoperative 3D Hologram Support with Mixed Reality Techniques in Liver Surgery. Ann. Surg. 2020, 271, e4–e7.
  87. Liu, J.P.; Lerut, J.; Yang, Z.; Li, Z.K.; Zheng, S.S. Three-dimensional modeling in complex liver surgery and liver transplantation. Hepatobiliary Pancreat. Dis. Int. 2022, 21, 318–324.
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