Purpose: Intraoperative fluorescence imaging (FI) is a promising technique that could potentially guide oncologic surgeons toward more radical resections and thus improve clinical outcome. Despite the increase in the number of clinical trials, fluorescent agents and imaging systems for intraoperative FI, a standardized approach for imaging system performance assessment and post-acquisition image analysis is currently unavailable. Procedures: We conducted a systematic, controlled comparison between two commercially available imaging systems using a novel calibration device for FI systems and various fluorescent agents. In addition, we analyzed fluorescence images from previous studies to evaluate signal-to-background ratio (SBR) and determinants of SBR. Results: Using the calibration device, imaging system performance could be quantified and compared, exposing relevant differences in sensitivity. Image analysis demonstrated a profound influence of background noise and the selection of the background on SBR. Conclusions: In this article, we suggest clear approaches for the quantification of imaging system performance assessment and post-acquisition image analysis, attempting to set new standards in the field of FI. Key words: Fluorescence, Optical imaging, Quantification, Image analysis, Signal-to-noise ratio, Phantom surgical decision-making . Fluorescence imaging (FI) is Introduction ideal for intraoperative applications due to fast acquisition Image-guided surgery (IGS) is a relatively new and emerging times (milliseconds), flexibility in application, and portability platform, in which imaging techniques are applied intraoper- . Various tumor-targeted near-infrared (NIR) fluorescence atively. The goal of IGS is to provide the surgeon with real- agents have been successfully studied in clinical trials [3–6]. time information on tissue in the surgical field, aiding in Moreover, there is great potential for a broad range of clinical applications besides oncology, such as infectious and inflam- Charlotte Hoogstins and Jan Jaap Burggraaf contributed equally to this matory diseases . Consequently, new study groups, industry work. as well as hospitals are increasingly interested to explore and implement this technology in clinical care. Correspondence to: Jacobus Burggraaf; e-mail: email@example.com Hoogstins C. et al.: Standards in Fluorescence-Guided Surgery As NIR light (wavelength 600–900 nm) is invisible to contrast between target and background and suggest an the human eye, dedicated imaging systems are needed to alternative measure, the contrast-to-noise ratio (CNR): detect the fluorescence signal and to form a two- dimensional (2D) image demarking its tissue distribution. ðÞ mean signal tumor−mean signal background The intraoperative detection of an imaging agent depends CNR ¼ on various biological and optical factors (Table 1). The standard deviation background considerable increase in the number of clinical trials in the FI field has led to the development of a variety of FI Although it is theoretically plausible that CNR may of systems . However, as the imaging system represents added value, this read-out has not yet been applied in daily the last link in the chain, sensitivity (i.e., detection limit) practice. Thus, a comparison between TBR and CNR of of the imaging system is crucial . It is therefore in vivo obtained images is needed. important to ascertain if an imaging system is sensitive Intraoperative FI holds great promise to revolutionize enough for the application of interest. Phantoms that surgery, but the ability to quantify FI, for reasons of mimic relevant concentrations of a fluorescent agent in comparison between centers and the imaging systems, will scattering and absorption media can aid in the quantifi- be a critical factor for successful application of the imaging cation of the imaging system performance. However, technique. Just as the field is in the process of gathering the guidance or standard documents describing sensitivity evidence through well-designed phase II/III clinical trials assessment for imaging systems, whether or not includ- necessary for routine clinical application, standards are ing phantoms, is currently lacking [10, 11]. needed to assure standardization and to assess if imaging The interplay between biological and optical factors systems are adequately sensitive and fluorescence images ultimately results in a fluorescence image, in which the can be accurately quantified [11, 13, 14]. Therefore, we fluorescence signal in both the target and background can be conducted a systematic, controlled in vitro comparison semi-quantified. Using ImageJ (National Institute of Health, between two commercially available, state-of-the-art Bethesda, USA, a public domain image processing and clinical imaging systems using a novel designed calibra- analysis program) or proprietary software provided with the tion device for FI systems and various fluorescent agents imaging system software, area and pixel value statistics in to evaluate important performance characteristics of user-defined selections, known as a region of interest (ROI), fluorescence imaging. In addition, we evaluated the can be analyzed. Standardized methods for selection of ROIs effect of ROI selection and background noise on SBR are not available, making this procedure prone to selection calculation by analyzing 271 fluorescence images from bias. Using the measured fluorescence signal in the ROIs of previous studies [3, 15–20].Basedontheseresults,we target and background, the signal-to-background ratio (SBR, propose an easily applicable, standardized approach to also reported as target or tumor-to-background ratio [TBR]) quantify and report imaging device performance and is calculated as: fluorescence image analysis. mean signal tumor Methods SBR ¼ mean signal background Imaging System Performance The SBR is the key determinant of sensitivity and detectability in FI and is frequently reported as a relevant The CalibrationDisk™ (SurgVision,‘t Harde, the Netherlands) is endpoint in (pre-)clinical studies. Tichauer et al. advocate a calibration device for FI systems. The disk can hold eight clear that noise originating from the background can influence the polypropylene tubes of 0.65 ml (Catalog # 15160, Sorenson, Table 1. Factors of influence on the signal to background ratio Concentration probe to reach tumor Imaging Tumor qualification for scientific reporting Specific delivery of a tracer to tumor Imaging settings (exposure time, camera Software (image format, program (i.e., vascularization of the tumor, distance, gain, darkness of room) settings) enhanced permeability and retention [EPR]) Tumor-specific receptor-ligand kinetics Optical qualities (scattering, absorption, Background and tumor selection (receptor availability, binding, and autofluorescence, depth of penetration) dissociation constants) Clearance Camera system Radiating underlying tissue Dosing Noise TBR or CNR Hoogstins C. et al.: Standards in Fluorescence-Guided Surgery BioScience, Inc., Murray, USA) (Fig. 1). Thedeviceconsistsof exposure time. Imaging was done in a dark room under two parts: an upper disk which holds the tubes in place and a base identical conditions, including an identical working distance of on which the upper disk can rotate. The upper disk has round 20 cm. System A provides high quality and resolution 16-bits windows that allow measurement of signal intensity in each tube. TIFF images. For system B, images were subtracted from By rotating the disk, different concentrations of a tracer can be videos (.qifs format) in the corresponding software suite, imaged at the same position and under the same excitation resulting in 8-bits TIFF images. Images were exported to conditions providing assessment of homogeneity in illumination ImageJ for gray value intensity analyses. Sensitivity was of the field of view. We performed the experiment with two defined as the lowest concentration detectable at maximal different commercially available imaging systems with distinctly settings (high gain, high exposure time). To mimic SBR in the different modes of operation: imaging system A and imaging clinical setting, we determined at what concentration a SBR 9 2 system B. Both systems are state-of-the-art clinical systems between the pertaining vial and background vial was achieved. optimized for intraoperative NIR imaging providing real-time For a fair comparison of different bits size images, fluorescence fluorescence images and white light overlays. System A, a cooled intensity values were indexed for maximal imaging system system, has two cameras, one for white-light image acquisition value and plotted on log10 fluorophore concentration versus and one for fluorescence image acquisition of a single NIR log10 fluorescence signal graphs. Linearity was defined as the channel (825 to 850 nm). System B uses a single camera for slopes of linear fits to the log–log data. An optimal imaging imaging two fluorescence channels (far red 700 to 830 nm and system provides a doubling in signal strength for every twofold NIR 830 to 1100 nm) and a white-light channel. Four different increase in concentration, resulting in a fitted linear slope of 1 NIR fluorescent agents including two dyes (indocyanine green in this logX–logY plot). (ICG) [Pulsion Medical Systems Munich, Germany] and IRDye As a reference, the performance of the two intraoperative 800CW[LI-COR Biosciences, Lincoln, NE, USA]) and two FI systems was compared to the Pearl Impulse preclinical molecularly targeting fluorescent tracers (bevacuzimab- imager (LI-COR Biosciences, Lincoln, NE, USA). This IRDye800CW  and a folate-NIR fluorophore (OTL-38) system contains an ambient-light-free chamber and can be ) were used to make dilution series in Intralipid 2 %. All used as a standard of the maximal linearity and sensitivity dilution series consisted of 21 concentrations, starting at achievable. Analysis of images obtained with the Pearl 10,000 nM and, following one on one dilution with Intralipid imaging system was done using the software suite provided 2 %, ending at 10 pM. Vials containing the 21 different with the device. concentrations were divided into three sets of seven (low, medium, and high concentration). A background or B0-vial^ containing Intralipid 2 % without a fluorescent agent was added Fluorescence Image Analysis to each set (Fig. 1). Each set was stacked into the CalibrationDisk™ and imaged at We evaluated 271 images available from previous studies to three different exposure times (low, medium, high) and three evaluate the effect of ROI selection and background noise on different gain settings (low, medium, high) with both imaging SBR. We randomly selected a representative sample of systems. Low, medium, and high settings of gain and intraoperative and ex vivo images from both animal and exposure time were used rather than absolute values, as human studies in different tumor types using different both imaging systems had a different maximum gain and fluorescent agents and imaging systems (Table 2). Fig. 1. The CalibrationDisk™ (SurgVision,‘t Harde, the Netherlands) loaded with eight clear polypropylene tubes of 0.65 ml (Catalog # 15160, Sorenson, BioScience, Inc., Murray, USA). Hoogstins C. et al.: Standards in Fluorescence-Guided Surgery Table 2. Specifications of the images used for fluorescence image analysis Results Imaging system Probe Tumor type Imaging System Performance Animal Pearl Trastuzumab-DTPA[ in] Breast By assessing the lowest concentration visible with an cRGD-ZW800-1 Colorectal imaging system, sensitivity of the system can be determined. Human Artemis Flare ICG Liver Using the CalibrationDisk™, the lowest detectable Pancreas concentration can easily be assessed for each agent and Vulvar SLN Rectal imaging system (Fig. 3). We found, irrespective of the OTL38 Ovarian fluorescent agent used, that system A is superior to EC17 Ovarian system B in terms of sensitivity. The lowest detectable concentration with system A is 1 nM, for system B this On these images, we drew a ROI around the (histolog- is 500 nM. For comparison, the Pearl Impulse detects ically confirmed) tumor. To evaluate the effect of ROI concentrations as low as 0.05 nM. Gain and exposure time selection, we drew two different ROIs of similar area size in settings influenced sensitivity of the system, with high settings the background: the darkest region adjacent to the tumor leading to maximal sensitivity for both systems, nevertheless ROI and the lightest region adjacent to the tumor. Lastly, we these settings did not affect the mutual differences between drew a ROI using our preferred method selecting the region systems A and B. surrounding the tumor ROI remaining within the anatomical Moreover, SBR values 9 2 (compared to the background structure in which the tumor is present. This can be done in vial) could be achieved from the low concentration set ImageJ by subtracting the tumor ROI from the overlapping (0.61 nM) using system A, while system B could only background, using the ROI manager menu and selecting the achieve a SBR 9 2 at concentrations exceeding 312.5 nM. BMore^ button followed by the BXOR^ button. Figure 2 Thus, in vitro performance of system A was superior to displays a representative example of ROI selection. Mean system B in terms of SBR. gray values and the standard deviation of the pixels within Analysis of the linearity of imaging systems A and B one ROI were assessed using ImageJ. To evaluate the effect reveals striking differences, with system A being superior, of background noise, we applied both SBR and CNR approaching the linearity of the Pearl Impulse. For the low equation on the values obtained with ImageJ. and medium concentrations, the detection limit of the system Fig. 2. a The influence of background selection on CNR and TBR. b A schematic example of different background selections. c Intraoperative image of a fluorescent metastatic lymph node with different background selections. Hoogstins C. et al.: Standards in Fluorescence-Guided Surgery Obviously, selection of a darker background will increase the SBR. As Fig. 2 effectively displays, a sufficient SBR (9 2) can be achieved by adapting background ROI selection. In addition, the area size of the background ROI influences the CNR. As the selection of a small area as background results in a small standard deviation, CNR is higher when smaller ROIs are selected. Discussion Quantitative ability of a FI system will play a crucial role in the clinical adoption of intraoperative FI. Despite repeated calls from the FI community, guidelines or standards for quantification of the performance of imaging systems or the analysis of fluorescence images are still lacking [11, 13, 14]. As clinical trials are expanding, the need of a performance test was regarded highly urgent and as such we propose a simple and low-cost imaging system performance test that can be applied to every fluorescent agent and imaging system. We demonstrate how this test can be performed and Fig. 3. Fluorescence imaging of the CalibrationDisk™ con- how data can be interpreted. In addition, we evaluated a taining seven vials with ascending concentrations of a representative sample of 271 fluorescence images. Based on fluorescent agent diluted in Intralipid 2 % and at 12 o’clock the effect of ROI selection and background noise on SBR position a background or B0-vial^ containing Intralipid 2 % calculation, we also propose a routine procedure for without a fluorescent agent. quantification of fluorescence images. was reached; therefore, signals measured by system B Imaging System Performance remain in the same range resulting in a horizontal line on the log10 graph. However, for the high concentrations, Sensitivity of two different imaging systems for intraop- system B does display a linear gradient similar to system A erative use was assessed. The goal of our experiment and the Pearl Impulse (Fig. 4). was not to quantify performance of an individual imaging systems, but to demonstrate how to compare different imaging systems and predict clinical perfor- Fluorescence Image Analysis mance in an experimental setting. Hence, we decided to select systems with a distinct mechanism of action and The method applied for ROI selection had a profound anonymize both systems. For the imaging system influence on both SBR and CNR. Figure 2 shows the assessment, we used the CalibrationDisk™ and tubes influence of background selection on CNR and TBR. filled with descending concentrations of different Fig. 4. Analysis of the linearity of imaging systems A and B compared to the Pearl Imager. An optimal imaging system provides a doubling in signal strength for every twofold increase in concentration, resulting in a slope of 1 (linear fit with 45° angle in logX–logY plot). Hoogstins C. et al.: Standards in Fluorescence-Guided Surgery fluorescent agents. Various types of other phantoms are Fluorescence Image Analysis described in literature. The use of solid polyurethane phantoms, with TiO2 particles mimicking scattering and The basic principle for FI is the excitation of fluorophores using quantum dots mimicking different concentrations of a a light source and the subsequent detection of photons emitted fluorophore, is suggested by Zhu et al. . Benefit of by the excited fluorophore using the imaging system. The these solid phantoms is their longer shelf life that allows detection of emitted photons is influenced by tissue optical repeated measurements over time. Disadvantages are that properties like absorption and scattering (including reflection). these phantoms are difficult to construct. More impor- Absorption of photons is a consequence of tissue specific tantly, however, is that while quantum dots mimic the absorption properties, of which in humans blood is the main fluorescence of the agent, it does not use the actual absorber . Scattering is the change of the direction of a fluorescent tracer that will be used in humans and thus photon in tissue. Scattering events can cause decreased signal provides only a distal proxy of the crucial information. strength and source localization, as occurs with fatty tissue. The Others have suggested the use of more tissue-like effect of these phenomena is increased when a photon has to phantoms made from gelatin [22, 23]. The fluorescent travel through more tissue, thus with greater tissue depths. inclusions, used to mimic tumors, are prepared using a Reflection seen at the surface of tissues causes diffusion of the custom-made silicone mold, which is filled with agarose mixture signal and consequently reduced detection. Besides the targeted containing a relevant concentration of the fluorescent agent. fluorophore, excitation can cause endogenous fluorophores Alternatively, hydroxyapatite (HA) crystals loaded with within the tissue to fluoresce as well (e.g., autofluorescence). Pam78, a fluorescent derivative of the bisphosphonate Noise is the sum of autofluorescence, scattering and reflection pamidronate, calibrated against the relevant concentration events and can make it difficult to discern the actual fluorescence of the fluorescent agent can be used. Background tissue signal. A SBR 9 2 is generally considered adequate to is made from gelatin to which various ingredients can be differentiate target from background . Nevertheless, there addedtomimicabsorption(hemoglobinorpinkIndia are clinical trials in which SBR values below 2 are described as ink),scattering(usingIntralipidormilkpowder), and sufficient for intraoperative FI . Despite routine use in optical autofluorescence (ICG). The fluorescent inclusions can imaging, including nuclear medicine, the cut-of value of 2 seems be incorporated at various depths in the gelatin base. to be based on marginal evidence and the clinical relevance of Although close to the clinical setting, the manufacturing this cut-of seems at least questionable. CNR is the ratio of the of these tissue-like phantoms is laborious and the shelf- absolute difference between background and tumor signal and life is limited. For training purposes, these phantoms are the standard deviation of the background. Rewriting the CNR probably superior, but for sensitivity and comparability formula shows that the CNR is strongly dependent on the SBR: testing of imaging systems most features seem superflu- ous. The use of the CalibrationDisk™ allowed determi- mean signal background nation of the lowest concentration detectable and the CNR ¼ðÞ SBR−1 standard deviation background ability to quantify concentrations. This data can be used to compare imaging systems or to predict clinical performance and can consequently simplify the task of selecting the right system for a certain application. The use of CNR is theoretically favorable over SBR to However, users of imaging systems should be aware quantitate in vivo obtained (patient) imaging data as it is more that the generated in vitro data is a simplification of the comprehensive measure and thus provides extra information. in vivo reality. In vivo optical tissue properties influence Following the three-sigma-rule, an empirical statistic rule often the ability to discriminate the signal from its background, used in descriptive statistics, a CNR of 3 or higher indicates sufficient knowledge and careful consideration of these that the average tumor signal is present only in approximately limitations remains of the utmost importance. Moreover, 0.135 % of the background selection . It could therefore be various other factors besides sensitivity may play a role argued that the CNR has a more evidence-based cut-off value. in the selection process. Dsouza et al. suggest six key However, this does not instantaneously mean that the CNR features for imaging systems : (1) real-time overlay can be declared superior to SBR, as both quantitative measures of white-light reflectance and fluorescence images; (2) are critically dependent on the ROI selection. Background ROI fluorescence-mode operation with ambient room lighting selection has an important influence on the mean background present; (3) high sensitivity to tracer of interest; (4) signal (SBR and CNR) and its standard deviation (CNR), ability to quantify fluorophores in situ; (5) ability to rendering CNR is equally prone to selection bias as SBR. To image multiple fluorophores simultaneously; and (6) increase reproducibility in FI research ROI selection process maximized ergonomic use. should be standardized and described more in detail in Although we focused on the sensitivity point, the other scientific articles. We suggest a ROI selection procedure that points are equally relevant when deciding on the optimal is representative and least prone to selection bias. However, as imaging system for a certain application. In addition, the selection is done manually, bias cannot be excluded costs should also be taken into account. Hoogstins C. et al.: Standards in Fluorescence-Guided Surgery Ntziachristos V, van Dam GM (2016) Molecular fluorescence-guided completely. The gold standard remains performance of surgery of peritoneal carcinomatosis of colorectal origin: a single- biodistribution studies describing the percentage of the dose centre feasibility study. Lancet Gastroenterol Hepatol 1:283–290 per gram of tumor and background tissue. 7. Tipirneni KE, Rosenthal EL, Moore LS, Haskins AD, Udayakumar N, Jani AH, Carroll WR, Morlandt AB, Bogyo M, Rao J, Warram JM (2017) Fluorescence imaging for cancer screening and surveillance. Mol Imaging Biol 19:645–655 Conclusion 8. Zhang RR, Schroeder AB, Grudzinski JJ, Rosenthal EL, Warram JM, Pinchuk AN, Eliceiri KW, Kuo JS, Weichert JP (2017) Beyond the In conclusion, assessing the sensitivity in terms of the detection margins: real-time detection of cancer using targeted fluorophores. Nat limit of an imaging system is easy and yields relevant data. Data Rev Clin Oncol 14:347–364 9. Zhu B, Rasmussen JC, Sevick-Muraca EM (2014) A matter of can be used to compare imaging systems or to predict clinical collection and detection for intraoperative and noninvasive near- performance, which allows selecting the right system for a certain infrared fluorescence molecular imaging: to see or not to see? 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