Abstract
Background/Aim: The need for instant histological evaluation of fresh tissue, especially in cancer treatment, remains paramount. The conventional frozen section technique has inherent limitations, prompting the exploration of alternative methods. A recently developed confocal laser endomicroscopic system provides real-time imaging of the tissue without the need for glass slide preparation. Herein, we evaluated its applicability in the histologic evaluation of gastric cancer tissues. Materials and Methods: A confocal laser endomicroscopic system (CLES) with a Lissajous pattern laser scanning, was developed. Fourteen fresh gastric cancer tissues and the same number of normal gastric tissues were obtained from advanced gastric cancer patients. Fluorescein sodium was used for staining. Five pathologists interpreted 100 endomicroscopic images and decided their histologic location and the presence of cancer. Following the review of matched hematoxylin and eosin (H&E) slides, their performance was evaluated with another 100 images. Results: CLES images mirrored gastric tissue histology. Pathologists were able to detect the histologic location of the images with 65.7% accuracy and differentiate cancer tissue from normal with 74.7% accuracy. The sensitivity and specificity of cancer detection were 71.9% and 76.1%. Following the review of matched H&E images, the accuracy of identifying the histologic location was increased to 92.8% (p<0.0001), and that of detecting cancer tissue was also increased to 90.9% (p<0.001). The sensitivity and specificity of cancer detection were enhanced to 89.1% and 93.2% (p<0.0001). Conclusion: High-quality histological images were immediately acquired by the CLES. The operator training enabled the accurate detection of cancer and histologic location raising its potential applicability as a real-time tissue imaging modality.
Instant histological evaluation of fresh tissue is crucial for effective cancer treatment, involving detection of tumor cells and ensuring resection with clear margins. However, the conventional frozen section technique, currently employed for this purpose, presents inherent limitations, such as processing time and suboptimal slide quality, due to preparation artifacts (1). Despite efforts to address these limitations, alternative methods have not gained widespread adoption in clinical practice. One such attempt involves magnifying narrow-band imaging, utilizing dual-wavelength light to distinguish cancerous and normal gastric tissue based on distinct emission patterns of microvasculature and mucosa (2). Nevertheless, challenges remain, particularly in accurately identifying pale-colored lesions with superficial flat morphology and histologically undifferentiated cancer.
Confocal microscopy, a laser scanning optical microscopy variant, allows real-time, high-resolution visualization of living tissue microstructures at the cellular level. However, its application for in vivo tissue imaging is hampered by issues like light transmission to tissue and the requirement of large objective lenses (3). A recent innovation aimed at mitigating these drawbacks is the minimized laser scanning microscope, known as the confocal laser endomicroscopic system (CLES). The CLES comprises a handheld endomicroscopic probe, a confocal microscope body unit, and an image signal processor, enabling real-time imaging of fresh tissue both ex vivo and in vivo without the need for biopsy (4). A pivotal component of this system is a pencil-like endomicroscopic probe utilizing a piezoelectric tube (PZT) for compact packaging and high mechanical stability. Additionally, it integrates a high definition and high frame rate (HDHF) Lissajous fiber scanner, ensuring uniform scanning density and speed (5, 6). Application of CLES to in vivo and ex vivo assessments of lung cancer (7) and brain tumor tissues (5) demonstrated successful discrimination between cancerous and normal tissues. Furthermore, the system exhibited efficacy in analyzing small tissue fragments, including biopsy specimens (8, 9), underlining its potential as an alternative to the frozen section technique.
In the context of gastric cancer, a previous study highlighted the clinical feasibility of cancer detection using CLES based on the vascular pattern of the lesion (10). While this study revealed characteristic vascular alterations in gastric cancer useful for distinguishing cancer from normal tissue, the lack of sophisticated characterization of cancer cells limited its diagnostic value, potentially resulting in false positive or false negative detections. Additionally, the study did not investigate whether the acquired images could be accurately interpreted by anonymous pathologists.
In this study, we comprehensively evaluated CLES-generated images of gastric cancer and normal gastric tissue using a system we previously developed (6). Our thorough validation confirmed that the system is non-invasive to gastric tissue, causing no tissue damage. Moreover, pathologists demonstrated highly accurate and reproducible interpretation of CLES images, establishing its significance as a real-time imaging platform for cancer detection.
Materials and Methods
Dataset. Fourteen fresh tissue samples from advanced gastric cancer patients were collected, along with an equal number of normal gastric tissue samples. All tumors were pathologically diagnosed as stage T3, indicating cancer extension from the mucosa to the subserosa. The tumor samples comprised well differentiated (n=3), moderately differentiated (n=3), and poorly differentiated tubular adenocarcinoma (n=3), as well as poorly cohesive carcinoma (n=5). Tissue fragments were cut to dimensions of 1.0′1.0′0.5 cm and subjected to imaging using the CLES. The Institutional Review Board (IRB) at the Ajou University Medical Center granted approval for this study under protocol AJIRB-BMR-KSP-22-070. Informed consent was waived by the IRB due to the utilization of anonymized clinical data for the analysis. The study adhered to the principles outlined in the Declaration of Helsinki.
Confocal laser endomicroscopic system. The mechanical configuration of the utilized CLES device in this study has been previously outlined in our earlier work (6) (Figure 1A). In summary, the microscopic head and probe, having a diameter of 4 mm (Figure 1B), are positioned in close proximity to the tissue. A 488 nm light emitted from the light source (cCeLL-A 488, VPIX Medical, Daejeon, Republic of Korea) is transmitted through an optical fiber to the tissue. The fluorescent dye, pre-applied to the tissue, absorbs this light, gets activated, and emits longer-wavelength light (500-560 nm). This emitted light is then transmitted back to the main unit through optical fibers present in the probe. The optical fibers utilize the principle of employing glass fibers with varying densities and refractive indices inside and outside the fiber. This causes light entering at a specific angle to undergo total internal reflection and propagate through the fiber. The optical signal returning to the main unit through the optical fibers is detected as an electrical signal by the optical detector within the main unit. Subsequently, the detected electrical signal is converted into a digital signal through a converter housed in the main unit. This digital signal undergoes processing through specialized software and is displayed as an image on the monitor. To ensure stability and precise movement, an automated stage holding the probe was employed during image capture (Figure 1C). As previously detailed, tissue scanning was performed using a Lissajou laser-scanning pattern, enabling image acquisition up to a thickness of 100μm from the tissue surface (5, 6).
Hardware of the confocal laser endomicroscopic system using 488 nm light source for fluorescein imaging. (A) The entire system consisting of the microscopic head probe, a confocal microscope body unit, an image signal processor, and a display monitor. (B) Details of the system attachable ultra-compact microscope head probe. (C) An automated stage for precise control of the microscope head.
Fluorescein sodium staining. For tissue staining, fluorescein sodium (FNa; Sigma-Aldrich, St. Louis, MO, USA) was dissolved in 30% ethanol to attain a concentration of 0.5 mg/ml. The FNa solution was carefully administered to the tissue sample drop by drop (Figure 2A). Following this, the samples were incubated for 1 minute and subsequently rinsed three times with phosphate-buffered saline (PBS). To eliminate any dye aggregates, the samples were delicately cleaned using a tissue wiper.
Evaluation of the effect of fluorescein sodium (FNa) on the fresh gastric tissue. (A) The procedure of FNa staining to tissue. (B) The effect of FNa in DNA and RNA quality in terms of A260/280. PBS, Phosphate-buffered saline. (C) The effect of FNa in hematoxylin and eosin-stained image quality of gastric cancer tissue. Scale bar, 200 μm; inset scale bar, 100 μm.
Nucleic acid extraction from the tissue. To assess the impact of the FNa dye on tissue quality, fragments of gastric cancer tissue from three patients and normal gastric tissue from five patients were separately prepared. These tissue fragments were incubated with PBS, a 0.5 mg/ml FNa solution, and a 5mg/ml FNa solution for comparative analysis. Subsequently, DNA extraction from the tissue was carried out using the QIAamp DNA Mini Kit (cat. No. 51306; Qiagen, Hilden, Germany), and RNA extraction was performed using the RNeasy Mini Kit (cat. No. 74104; Qiagen). The quantification of DNA and RNA in the tissue samples was determined using the A260/280 ratio measured by the NanoDrop 2000 Spectrophotometer (cat. No. ND-2000; Thermo Scientific, Waltham, MA, USA).
Image acquisition. Utilizing the CLES imaging technique, dynamic grayscale images of 1,024 × 1,024 pixels were vividly captured, providing a field of view measuring 500 μm × 500 μm. Both gastric cancer tissue and normal gastric tissue were meticulously scanned using the probe, starting from the mucosal surface, and progressing vertically through the submucosa to the proper muscle layer. After scanning a specific vertical plane, the probe shifted laterally to scan the subsequent vertical plane, ensuring comprehensive coverage from the mucosal layer to the proper muscle layer. This scanning process was meticulously managed with an automated stage to prevent any oversight. On average, a single tissue piece yielded approximately 200 to 300 images, contributing to a comprehensive representation of the tissue under examination.
Hematoxylin and eosin staining of the tissue and evaluation. Post-imaging, the tissues underwent fixation in 10% formalin, followed by the creation of formalin-fixed, paraffin-embedded (FFPE) blocks. Subsequently, 4μm-thick FFPE sections were obtained and stained with hematoxylin and eosin (H&E). The H&E-stained slides were then prepared and subjected to scanning using the Aperio AT2 digital whole slide scanner (Leica Biosystems Imaging, Buffalo Grove, IL, USA) at a magnification of 40×. The resulting scanned slide images were directly compared with the stitched vertical images obtained through CLES, enabling a comprehensive histological analysis and comparison.
Image evaluation by pathologists. A total of 100 CLES images from normal gastric tissue were selected, comprising images captured from the mucosa (n=33), submucosa (n=34), and proper muscle (n=35). These images were randomly presented to five board-certified pathologists (H.B., H.C., J.C., S.C., and S.K.) to identify the histological location accurately. Additionally, another set of 100 images was chosen, half of which included tumor cells (n=50) and the other half contained only normal tissue (n=50). These images were also presented to the pathologists to determine the presence of cancer cells. Following the initial assessment, the corresponding H&E images matching the CLES test set were provided to the pathologists for comparison and training. Subsequently, the pathologists’ performance in interpreting CLES images was re-evaluated. This assessment encompassed an additional set of 100 images of normal tissue for histological location detection and another 100 images (comprising both cancer and normal images) for cancer cell detection.
Statistical analysis. All data are expressed as mean±standard deviation based on the independent experiments. Statistical comparisons among the different treatment groups were conducted by unpaired t-tests using GraphPad Prism 9.3.1 (GraphPad Inc., San Diego, CA, USA). Statistical significance was defined as p<0.05.
Results
Validation of fluorescent dye impact on tissue integrity. To validate the safety and non-deleterious impact of FNa fluorescent dye used for tissue staining, we conducted experiments on fresh gastric cancer and normal gastric tissues. These tissues were exposed to FNa as a pretreatment for CLES imaging. After a one-minute incubation period with FNa, both tumor and normal tissues exhibited no alterations in DNA and RNA purity (Figure 2B). Notably, both the standard FNa concentration of 0.5 mg/ml, typically used in CLES imaging, and a concentration ten times higher (5 mg/ml) showed no statistically significant differences in DNA and RNA quality. Additionally, examination of the FFPE slides, following FNa washout, revealed no residual dye or adverse effects on tissue integrity and staining quality (Figure 2C). Consequently, we can affirm that FNa has no discernible impact on the standard histological procedures that follow CLES imaging.
Identification of normal gastric tissue features using confocal laser endomicroscopic imaging. The CLES images acquired from normal gastric tissue displayed patterns closely resembling those observed in the corresponding H&E images. The stitched CLES image, capturing the vertical plane from the mucosa to the submucosa and the proper muscle layer, showcased distinct layer morphologies similar to those depicted in the H&E image (Figure 3, left). More specifically, within the mucosa image, well-defined, tightly packed rolling structures resembling glandular configurations were easily discernible (Figure 3, right upper). In the submucosal layer image, a loose fibrous tissue pattern stood out with a distinctive dark gray color and an irregular density (Figure 3, right middle). Lastly, in the proper muscle layer image, the arrangement of muscle fibers was prominently featured, presenting as bright and curled structures (Figure 3, right lower).
Representative confocal laser endomicroscopic images and corresponding hematoxylin and eosin (H&E) images of normal gastric tissue. (Left) Entire gastric wall vertical image. Scale bar, 1 mm. (Right) Representative images of mucosa, submucosa, and proper muscle layer. Scale bar, 200 μm.
Identification of gastric cancer tissue features using confocal laser endomicroscopic imaging. Gastric cancer cells were distinctly observable in the CLES images. The vertical plane imaging from the mucosa to the proper muscle layer, encompassing gastric tissue with cancer cells, presented numerous bright, ovoid structures set against the backdrop of non-neoplastic gastric tissue displaying typical layer-dependent morphology (Figure 4, left). The well-to-moderately differentiated tubular adenocarcinoma exhibited a distinct white, glistening, glandular architecture disrupting the normal gastric tissue (Figure 4, right upper). Conversely, poorly cohesive carcinoma appeared as small scattered bright spots amidst normal gastric tissue (Figure 4, right lower). Further magnification provided a detailed view of cancer cell morphology, characterized by bright and irregular shapes and distributions, contrasting starkly with the normal gastric tissue image (Figure 5).
Representative confocal laser endomicroscopic images and corresponding hematoxylin and eosin (H&E) images of the gastric cancer tissue. (Left) Entire gastric wall vertical image infiltrated by cancer glands. Scale bar, 1mm. (Right) Representative images of moderately differentiated adenocarcinoma and poorly cohesive carcinoma. Scale bar, 200 μm.
Representative magnified confocal laser endoscopic images of normal gastric submucosa (left), moderately differentiated adenocarcinoma in submucosa (middle), and poorly cohesive carcinoma in submucosa (right). Scale bar, 100 μm.
Interpretation of confocal laser endomicroscopic image by pathologists. To assess the potential of CLES as a reproducibly interpretable histological imaging modality, we engaged five pathologists to detect the histologic location and presence of cancer cells in 100 randomly selected CLES images (Figure 6A). Initially, the pathologists, lacking prior CLES image interpretation experience, achieved an average accuracy of 65.7% in identifying the histologic location (Figure 6B) and an average accuracy of 74.7% in distinguishing cancer tissue from normal tissue (Figure 6C). The average sensitivity and specificity for cancer tissue detection were 71.9% and 76.1%, respectively (Figure 6D), and the average reading time per image was 12.0 seconds (Figure 6E). Following training with matched H&E images, the pathologists demonstrated significant improvement in performance. They achieved an average accuracy of 92.8% in identifying the histologic location (p<0.0001) (Figure 6B) and an average accuracy of 90.9% in detecting cancer tissue (p<0.001) (Figure 6C). The average sensitivity and specificity for cancer tissue detection notably increased to 89.1% and 93.2%, respectively (p<0.0001) (Figure 6D), and the average reading time per image decreased significantly to 5.3 seconds (p<0.01) (Figure 6E).
Evaluation of the confocal laser endoscopic images by pathologists. (A) Schematic flow of the initial interpretation, training, and post-training evaluation by pathologists. (B) The accuracy of detecting histologic location before and after the training. (C) The accuracy of detecting cancer cells in the images before and after the training. (D) The sensitivity and specificity for cancer detection before and after the training. (E) The interpretation time per image before and after the training. **p<0.01, ***p<0.001, ****p<0.0001.
Discussion
In this study, we demonstrated the feasibility of real-time CLES imaging for gastric cancer tissue with comprehensive validation. The short incubation period with FNa proved effective in staining the tissue without causing damage, resulting in clear and high-quality images. These acquired images accurately captured microscopic features characteristic of gastric tissue histology, allowing pathologists to quickly familiarize themselves through brief comparisons with H&E images.
Despite the consistent demand for real-time imaging of fresh tissue, the conventional frozen section technique remains the predominant method in practical use. This is due to the stringent criteria that an alternative modality must meet, including instant image acquisition, preservation of tissue integrity, high image quality, versatility across various tissue types, and reproducibility of interpretation. Developing an imaging modality that fulfills all these conditions is a complex undertaking. For instance, touch imprint cytology, a recently proposed technique, offers rapid sample preparation with high diagnostic accuracy compared to frozen section diagnosis. However, its applicability to a wide array of tissue types remains a subject for further investigation (11).
Confocal microscopic imaging using laser light source has long been recognized as a valuable real-time imaging method (12, 13). However, to optimize high-quality human tissue imaging, especially in an in vivo setting, overcoming various technical challenges was imperative. The development of a miniaturized handheld probe necessitated the incorporation of a scanning fiber actuated by a PZT to achieve compact packaging and ensure high mechanical stability (14). Additionally, employing Lissajous scanning, resonating at two distinct high scanning frequencies due to high spring constants for both orthogonal axes, resulted in more uniform figures within the central area and enhanced mechanical stability (15). To address the trade-off between scanning speed and scanning density, we applied HDHF Lissajous scanning in our CLES (16). Lastly, the integration of an automated stage was crucial to mitigate potential focusing issues along the z-axis and enable precise movement to avoid missing any focal points on the sample.
While utilizing a fluorescent dye for tissue staining in CLES imaging is essential, concerns regarding potential tissue damage resulting from the dye have been raised but never thoroughly investigated. In this study, we conducted a one-minute incubation of the tissue with FNa, followed by a washout procedure that visibly eliminated the yellow coloration associated with the dye. We not only validated that FNa incubation did not adversely impact the quality of subsequent H&E staining but also conducted a quantitative assessment of DNA and RNA quality. The quality of nucleic acids is particularly critical in the era of precision medicine, where next-generation sequencing is frequently employed for molecular-based diagnoses and identification of potential therapeutic targets. Moreover, in addition to the standard working concentration of FNa, we demonstrated that a 10-fold concentration of the dye did not compromise tissue quality.
Tumor cells exhibited distinctive features on the CLES images, appearing as bright shining objects. This increased brightness may be attributed to the higher abundance of cytoplasmic protein contents in cancer cells compared to normal cells (17). Supporting this hypothesis, CLES images of normal gastric tissue with localized inflammation revealed sporadic bright spots resembling those found in poorly cohesive carcinoma (data not shown). However, the degree of brightness in inflammatory cells was lesser, and the distribution pattern of the cells could aid in distinguishing between tumor cells and inflammatory cells. Quantitative analysis of signal intensity through image analysis in these cases could further enhance the precise detection of tumor cells.
Given that CLES images accurately mirror the histological features of gastric tissue, the pathologists were able to gain some familiarity with the grayscale images even without specific training. Initial misinterpretations were predominantly associated with submucosal layer images for histologic location detection experiments and poorly cohesive carcinoma images for cancer cell detection tasks. However, subsequent training with matched H&E images, particularly highlighting how loose connective tissue appears in CLES images, enabled the pathologists to accurately identify the submucosal layer. Detection of poorly cohesive carcinoma remained challenging even after training, constituting the majority of false-positive cases in post-training sessions. Particularly in cases where the tumor cell volume was small, CLES images containing poorly cohesive carcinoma lacked overt distinguishable features. Notably, training with H&E images led to a reduction in the interpretation time for CLES, confirming that the pathologists had indeed acquired the skills to interpret the images. These analyses collectively emphasize that CLES images can be objectively interpreted by pathologists, highlighting its reproducibility as a real-time imaging platform. Furthermore, the integration of artificial intelligence, training algorithms using CLES images to detect the presence of tumor cells, has the potential to further enhance the capabilities of this modality (18).
CLES imaging of gastric tissue holds significant potential across various applications. One key application lies in evaluating the resection margins of gastrectomy, providing a non-invasive, real-time method to aid in the detection of cancer cells. While the frozen section technique already achieves over 98% accuracy in intraoperative margin assessment (19), incorporating CLES imaging can further enhance margin evaluation by revealing tumor cells distinctly as bright objects. Moreover, it serves as a valuable alternative when the frozen section technique is not readily available. CLES imaging ability to clearly visualize tumor cells, even when H&E morphology is ambiguous, makes it invaluable for determining cell nature in challenging scenarios, such as detecting metastatic tumor cells in the omentum to guide decisions on curative surgery. This is particularly crucial when determining whether atypical cells are cancer cells or lymphoid cells, especially when the number of cells is sparse and frozen artifacts are present. Significantly, CLES imaging can be instrumental in margin diagnosis for gastric endoscopic submucosal dissection (ESD) specimens (20). In routine ESD procedures, margin evaluation is often not performed due to practical limitations, such as the workload in the pathology department and the small size of the specimen. While a recent prospective study has shown the applicability of frozen section biopsies for ESD specimens (21), the integration of this technique into routine practice remains uncertain. The non-invasive nature of CLES imaging offers a promising solution, enabling instant histologic evaluation of ESD margins to identify the extension of cancer cells. Moreover, the high-resolution CLES images have the potential to facilitate precise discrimination of crypt architecture. This discrimination extends beyond distinguishing between cancerous and normal glands, encompassing the ability to differentiate between crypt architecture in non-neoplastic diseases and normal crypt structures. Such capabilities enhance the broader applicability of CLES imaging, making it a valuable tool for the detailed assessment of various tissue conditions and histological features (22).
The current version of CLES system exhibits certain limitations that warrant improvement. Firstly, while CLES provides high-resolution imaging capabilities, its limited depth of tissue penetration restricts its ability to visualize deeper tissue layers. Consequently, its utility is constrained to detecting cancer in the most superficial layer of specimens, making it well-suited for evaluating the margin status of ESD or gastrectomy specimens. To broaden its scope, hardware development is necessary to enable imaging of deeper tissue layers, thereby facilitating the assessment of full-thickness specimens. Furthermore, while this study demonstrates the safety of FNa for ex vivo tissue use, concerns may persist regarding its in vivo application. Thus, further examination is warranted to assess the safety of FNa in vivo, including investigations into its concentration and mode of application. Additionally, alternative dyes that have already been established as safe for in vivo use, such as indocyanine green (ICG), should be evaluated for their applicability within the CLES system (23). These enhancements will be pivotal in advancing the capabilities and safety of CLES for broader clinical utilization.
Study limitations. Firstly, the sample size in this study was designed to investigate the feasibility of CLES imaging in fresh gastric cancer tissue, and it may not be sufficient to draw definitive conclusions. A larger, more comprehensive cohort study is warranted to validate and further extend the findings of this study. Additionally, a multi-centered study design could enhance the generalizability and applicability of the results. Secondly, involving a larger number of pathologists and investigating the false-positive and false-negative interpretations of CLES images could provide a more comprehensive understanding of the system’s performance and potential areas for improvement. Lastly, the development of an automated CLES image analysis system, employing algorithmic advancements, holds promise for achieving a comprehensive, standalone, real-time tissue imaging and interpretation platform. Further research in this direction is crucial for maximizing the potential of CLES imaging in clinical applications.
Conclusion
In conclusion, we explored the potential of the confocal laser endomicroscopic system (CLES) for real-time imaging of fresh gastric tissue in the context of cancer diagnosis and treatment. Our findings demonstrated that CLES can generate high-quality images without causing tissue damage. Pathologists, after receiving training with matched H&E images, exhibited a significant improvement in their ability to identify histologic locations and detect cancer cells within CLES images. Further enhancement can broaden its utility as a valuable tool for real-time tissue evaluation in clinical practice.
Acknowledgements
We thank the Tiniakos family for granting us the ‘George Tiniakos Award’ for the best oral presentation in gastrointestinal, liver and pancreas pathology at the 35th European Congress of Pathology 2023 with this study. This work was supported by the Korea Medical Device Development Fund grant funded by the Korea government (the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health & Welfare, the Ministry of Food and Drug Safety) (Project Number: RS-2022-00140721) and by the new faculty research fund of Ajou University School of Medicine.
Footnotes
Authors’ Contributions
K.H., K.K., and S.K. conceptualized the study. Y.J. and S.M.H. performed the data curation. H.B., H.C., J.C., S.C., and S.K conducted formal analysis. K.H. and S.K. contributed to the funding acquisition. H.B., H.C., Y.J., S.M.H., J.C, S.C., K.K. and S.K. contributed to the investigation and methodology. Y.J., K.H., and K.K prepared resources and software. H.B. and S.K. performed supervision and validation. S.K. wrote the original draft. All Authors reviewed, edited, and approved the final version of the manuscript.
Conflicts of Interest
Y.J., K.H. and K.K. are employed by VPIX Medical Inc. Other authors have no conflicts of interest in relation to this study.
- Received September 25, 2023.
- Revision received October 31, 2023.
- Accepted November 15, 2023.
- Copyright © 2024 The Author(s). Published by the International Institute of Anticancer Research.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).
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