Remote metastasis detection by video thermometry: A promissing preclinical study

Remote metastasis detection by video thermometry: A promissing preclinical study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Remote metastasis detection by video thermometry: A promissing preclinical study Paula Gebe Abreu Cabral, Silvia Marcela Ruiz Cadena, Scarlath Ohana Penna dos Santos, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3115452/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The thermometric video image (VTM) can guide the search for distant metastases, once the vascular architecture is known, identifying, by segmentation, the tumor thermal impression and a similar pattern at a distance. Thus, suspicious areas can be better investigated, improving the postoperative prognosis. In this study, it was possible to observe the assertive capacity of video thermometry in identifying distant metastases and breast tumors in female dogs, not palpable or visible to the naked eye, in relation to conventionally used techniques. It was also possible to identify textures with anatomical limits, from emboli to early formations of carcinomas, adenocarcinomas and adenomyoepithelioma. It was also possible to find non-neoplastic changes such as dermatitis, lipoma, hyperplasia and breast cysts. it can be concluded that the video thermometry (VTM) technique was capable of identifying distant metastases from the primary tumor and other benign alterations with great precision. However, for this to be possible, it is essential that the processing be carried out by SaMD (Software as a Medical Device), with tools capable of identifying patterns and thermal signatures, just like the algorithm, thus increasing the efficacy of the technique. breast cancer diagnostic imaging video thermometry infrared imaging SaMD Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. INTRODUCTION Approximately 25% of female dogs develop new nodules following surgical removal, which have the potential to be malignant despite the initial tumor being benign 1 . The process of metastasis is selective for the few cells that lose their adhesion and manage to penetrate vessel walls, eventually forming emboli in distant capillary beds. If the immune system fails to eliminate these cells, metastasis can occur 2 . Angiogenesis, hypervascularity, and hyperthermia are frequent and early alterations observed in breast tumors 3,4,5 , small with only 100 cells 6 . Furthermore, the extracellular space in most tumors is slightly acidic due to the excessive production of lactic acid (aerobic glycolysis - chronic activation of hypoxia-inducible factor-1 / HIF-1) and the H + transport through the plasma membrane mediated by V-ATPases 7,8 . This acidity creates a favorable tumor microenvironment, promoting angiogenesis and influencing its invasive capabilities 9 . However, the hypervascularity and microvessel density around the tumor correlate with the central temperature of the tumor 10 , and this heat is a result of different metabolic intensities 11 It can be detected by infrared sensors 12,13 . In 1957, a milestone in the detection of breast cancer occurred when Lawson used, for the first time, a thermal camera for this purpose. He identified temperature differences between the tumor and the surrounding healthy area. In 1963, researchers such as Lausanne and Ghatmati published studies that associated increased skin temperature with breast cancer, highlighting the importance of venous convection in this process. In 1982, the Food and Drug Administration (FDA) approval thermometry as a diagnostic aid to detect breast cancer came . In 1996, a comparative study between thermal imaging and radiography showed that thermal imaging was able to detect the disease in a patient, while radiography was not able to identify it. 14 . Subsequently, in 2003, the FDA approved real-time digital thermometry as a classifier for assisted neural networks. Different tissues have different emissivity at infrared wavelengths, emitting signals 15 ,16 . Objects naturally emit thermal signals in the range of infrared electromagnetic radiation, and the type of signal emitted or radiated at a certain temperature depends on both the characteristics of the object and its surrounding environment 17 , just like the technology that captures these signals and transforms them into images 18 , Therefore, infrared measurement devices acquire the radiation emitted by the object and convert it into an electronic signal 19,20 . When a cell performs a biological task ATP hydrolysis takes place resulting in the loss of energy in the form of heat 21 . Only with the advancements in thermodynamics was the mechanical theory of heat established, with heat being recognized as dynamic energy in motion, derived from molecular motion based on the degree of freedom of each molecule 22 , which can be measured on a varying scale of degrees that we refer to as temperature 23 . The heat from infrared radiation is based on thermodynamics and the transfer of bioheat 24 . The Stefan-Boltzmann law can be used to understand the relationship between the energy emitted by an object and its temperature, while the Penne’s bioheat equation can effectively measure the heat produced by cancer cells. 25 . In breast carcinomas, increased cellular activity leads to changes in local temperature 26 As a result, the heat generated from metabolism can vary in intensity, leading to thermal asymmetries 27 . Infrared electromagnetic radiation lies outside the human visual range and, therefore, is capable of recording non-visible occurrences 28 . On the other hand, the sensitivity of infrared sensors has significantly improved from 0.5°C in the 1960s to less than 0.02°C in modern sensors, allowing them to accurately capture the subtle temperature variations of the breast 29 . The dynamic cooling-assisted video image capture monitors the temperature of each pixel over time, thereby increasing specificity 30 , furthermore, with computational resources, artificial intelligence can be utilized to extract more features from this technology 31 . Although, the use of thermography has been recognized as a potential mechanism for the diagnosis and monitoring of cancers, particularly skin and breast cancers, thermography is linked to portable cameras and industrial software that limits video and processing functionalities dedicated to homeotherms beings, harming its application for diagnostic purposes. Video thermometry together with a SaMD with mechanisms of artificial intelligence and machine learning, has the potential to emerge as a significant tool for cancer detection, even being used during surgical procedures to provide real-time visualization of tumor margins to the medical team. However, its utilization is still limited, due to emerging technology. The dynamic images in this study were referred to as video thermometric or video thermometry images. Based on this, the objective of this study was to detect distant metastases in canine mammary neoplasms. 2. MATERIALS AND METHODS 2.1. Sampling method Twenty-one female dogs with palpable mammary nodules underwent total unilateral mastectomy. This study was approved by the animal ethics committee ID 432171-CEUA/UENF. As the inclusion criteria, female dog in reproductive phase, without weight or age restrictions, with one or more evident masses of adenomas, carcinomas, or their mixed variants were included in this study. These surgeries were combined with real-time, non-contact video thermometry examination, and the image capture was performed in a temperature-controlled surgical center maintained at 22±2°C. All visible tumor masses were sent for histopathological diagnosis, and twenty-five presumptive samples, guided by VTM, were collected for histopathological study. In three surgeries, multiple presumptive samples were collected, as shown in Table 1. 2.2. Anesthetic Procedure After trichotomy, the animal was taken to the operating room, where it was positioned, sedated, and anesthetized. Induction was performed by intravenous administration of propofol at a dose of 3 mg/kg -1 , and anesthesia maintenance was achieved with 100% oxygen and isoflurane via a semi-closed inhalation anesthesia circuit (Baraka system) for animals weighing up to 7 kg, and a semi-closed circuit for animals weighing over 7 kg. Intraoperative pain control was achieved through continuous infusion of morphine sulfate at a rate of 1.66 μg/kg-1/min, lidocaine hydrochloride at 30 μg/kg -1 /min, and ketamine hydrochloride at 15 μg/kg -1 /min, initially administered as bolus doses and subsequently maintained using an infusion pump at a dosage of 0.4 mg/kg of morphine, 1 mg/kg of lidocaine, and 1 mg/kg of ketamine. Heart rate (HR), respiratory rate (RR), peripheral oxygen hemoglobin saturation (SpO 2 ), electrocardiographic tracing, plethysmography, end-tidal carbon dioxide concentration (EtCO 2 ), and non-invasive blood pressure were monitored. The animals remained under spontaneous ventilation throughout the operation. Postoperative analgesia was achieved through a combination of oral tramadol hydrochloride at a dose of 4 mg/kg-1 every 12 hours, oral carprofen at a dose of 2.2 mg/kg -1 every 12 hours, and dipyrone at a dose of 25 mg/kg -1 every 12 hours, all administered for a duration of 5 days. Patient selection was based on clinical assessment and complementary exams (medical history, physical examination, laboratory tests, imaging exams, prescription of supportive care, and surgical referral), as well as postoperative care (hospitalization, monitoring, antibiotic therapy, and pain management). 2.3. Transoperative Video Thermometric Evaluation The examination was performed using the MART (Metabolic Activity in Real-Time) station designed for surgical center and/or educational purposes, utilizing the Mart v2.0 software for video thermometric image processing and enhancement. The operator of the station was positioned outside the sterile environment, avoiding interference with the surgical routine, while the thermic sensor was positioned above the surgical field at a variable height ranging from 1 to 1.20 meters. After sedation, a 15 minutes period was performed for the patient's thermal acclimatization with room temperature of 22±2°C before starting the inspection protocol. Subsequently, a provocative test was performed with 0.5% chlorhexidine alcoholic solution. This procedure helps to mark the main tumor irrigation and the direction of blood flow in the mammary chains, axillary and inguinal lymph nodes to confirm, later, if images of similarity are found in the direction of the verified flow. As the skin generates heat, thermal discrepancies between nearby pixels call attention to dysfunction, perforating arteries, hot or cold regions for another reason and artifacts which must be differentiated during the exam. 2.4. Analysis of Video thermometric Images In this experiment, in the pre-operative inspection, the “Merlin” tool, shows several small images with different color gradients, where the operator chooses the screen that shows the best image and transfer it to the processing area. In this sense, the operator processed the image following the MART protocol with the following routine: 1) assessment of symmetry; 2) vascular inspection; 3) analysis of thermal discrepancy in nearby pixels in areas suspected of abnormalities. 4) identification of textures and anatomical delimitation; 5) search for similarities of thermal patterns; when the operator marks a breast cancer known area and activate the “Similarity” tool, automatically identifies areas with the same thermal signature, thus enabling the identification of possible areas to be inspected by the surgeon during the surgical procedure. The operator suggest which presumptive samples should be collected in the preoperative. In this study, the images were recorded on video, in real time, from the acclimatization period until the beginning of the surgery 32,33 . 3. RESULTS In this study 21 unilateral total mastectomy surgeries were performed, and during these procedures, 23 presumptive samples of remote alterations were collected (Table 1). Table 1. Identification of the number of surgeries and number of presumptive samples collected, histopathological diagnosis of the primary tumor, and remote presumptive samples in mammary tumors in female dogs. PRIMARY TUMOR PRESUMPTIVE RESULT 01 Carcinoma sólido Breast Carcinoma Embolus and Vascular Hamartoma 02 Adenocarcinoma with Solid and Tubular Areas Neoplastic Embolus in Vessel, Mammary Duct with Cellular Proliferation 03 Multicentric Tubular Carcinoma Tubular Carcinoma 04 Solid Tubular Carcinoma Tubular Carcinoma 05 Tubular Breast Adenocarcinoma Tubular Breast Adenocarcinoma 06 Complex Adenomyoepithelioma Malignant Grade II Adenomyoepithelioma 07 Complex Adenomyoepithelioma Basal Cell Carcinoma, well-differentiated with clear surgical margins. Dermatitis. 08 Complex Adenocarcinoma with Differentiated Cystic and Papillary Areas Mammary Cysts and Hyperplasia Mammary Hyperplasia 09 Tubular Carcinoma in Mixed Tumor Lipoma Dermatitis 10 Solid Carcinoma Dermatitis 11 Breast Adenoma Breast Hyperplasia 12 Solid Carcinoma No abnormalities detected 13 Suppurated Grade I Ductal Adenocarcinoma No abnormalities detected 14 Complex Adenomyoepithelioma No abnormalities detected 15 Cystadenocarcinoma in Mixed Tumor, Grade I and II No abnormalities detected 16 Ulcerated Carcinosarcoma No abnormalities detected 17 Papillary Adenocarcinoma No abnormalities detected 18 Cystic and Papillary Adenocarcinoma with Abundant Squamous Differentiation No abnormalities detected 19 Solid Adenocarcinoma No abnormalities detected 20 Carcinoma in Mixed Tumor No abnormalities detected 21 Tubular Carcinoma No abnormalities detected Of the collected samples, 07 neoplastic alterations and 06 non-neoplastic alterations were found. 10 samples had no alteration (Table 1). Among the altered samples, proven through histopathology, 44% were not detected by the conventional identification method, and 56% were not visible or palpable. All altered samples were found by video thermometry (Figure 3). Of the total number of lesions identified, the evaluation performed using videotermometria was 62% more accurate than the conventional method (Figure 4). In figure 5, it is possible to observe the demarcation of two known tumor masses, which are visible and palpable in the female dog abdominal and caudal breast. it is also possible to observe the thermal signature identification tool of the algorithm, which it was able to identify the two predominant temperatures, and similar ones, of the tumor masses already identified by the conventional method. However, the algorithm was also able to identify a cranial image with thermal impression similar to known masses, along the vascular pathways of the left mammary chain, with temperature discrepancy of the surrounding areas. This image, although very small, had the same thermal signature as the already known masses and, through histopathological examination, the presumed sample resulted in a neoplastic embolus. In figure 6, it is possible to observe the visible tumor mass of the breast female dog, showing the previous left total mastectomy scar. In the video thermometry exam, it was possible to observe the textures of the tumor architecture, as well as the predominant vascular supply (black). Through the similarity analysis of the thermal signature, it was possible to identify an image in the right cranial abdominal mammary region, compatible with the vascular pathways and showing a thermal impression similar to the known mass, after the analysis and verification of the thermal discrepancies (red arrow). Through histopathological examination, the presumptive sample resulted in a neoplastic embolus compatible with carcinoma and vascular hamartoma. In Figure 7A, it was possible to observe a visible solid tumor mass of adenocarcinoma in the right caudal abdominal breast. Next to it, the right inguinal mammary gland appears enlarged in relation to the contralateral gland, but on palpation, its elastic and deformable appearance suggests a lipoma. Figure 7B shows the intraoperative view of the right total mastectomy, where the tubular images become apparent. Images 8C, 8D and 8E are from the intraoperative phase in which it is possible to observe the surgeon's hand over the tumor mass on the left. In the area marked with a red circle, three sequential moments were captured by VTM, revealing the ability of the technique, together with the algorithm, to highlight textures and tubular structures. Upon histopathological examination, the findings resulted in mammary hyperplasia and cysts. 4. DISCUSSION Thermometry is an image generated by convert infrared radiation emitted from the body into electrical impulses (radiometric image) that are displayed on a monitor in various colors 34 . The spectrum of colors based on a degrees scale indicates an increase or decrease in the infrared radiation or temperature being emitted from the body surface. An abnormality detected by thermal image indicates an area of temperature asymmetry in the body. Based on patterns of heat and blood flow on or near the surface of the body, thermometry has been utilized in an effort to detect, characterize, and monitor multiple diseases processes. Although thermography has already been demonstrated as a potential breast cancer detection mechanism 35,36,37 , VTM can become an important tool during image processing, through an AI system capable of detecting benign alterations and distant metastases, tumor textures and delimitation, tumor vascular supply, as demonstrated by the data of this study. Presumptive samples without abnormalities may be artifacts, vascular changes, or initial pathological changes not found on histopathological examination. This image reflects a different generation of heat from the surroundings, demonstrating that the composition of matter in this location generates a molecular movement that differs from the surrounding region. According to Jiang et al., (2010), the dynamic state of the breast exhibits distinct patterns, which makes it difficult to identify thermal signatures to identify tumors and metastases in the tissue 38 . A study by Jawzal (2018) indicates that thermography reflects, mainly, a heat map under the skin, but does not exactly locate the tumor for surgical purposes, and may cause confusion during the procedure, when the metabolic intensity of some tumors decreases. The results found in this study, with the advancement of technology, are in contrast to those found by Jiang et al., (2010) and Jawzal (2018), since, among all the samples with alteration that were verified in the study, 62% were alterations neoplastic lesions distant from the primary tumor (Figure 4). This result is promising, as benign and malignant lesions that would not be detected by the conventional method were identified by VTM. It is noteworthy that the identification of distant metastases was made through the use of thermal signatures of the tumor tissue. This data shows the efficiency not only of the VTM, but also the algorithm, which was able to identify the thermal signatures of the lesion and detect the same signature, enabling the detection of distant metastases from the primary tumor, even at a very early stage. Another factor that may explain the success rate of the technique in this study was reported by Vardasca et al., (2018), in which it was demonstrated that temperature differences between the areas of lesions and the surrounding tissue can be used to differentiate neoplasms. In the case of benign neoplasms of the skin, if dynamic thermal imaging (DTI) and application of cold stress are used, sensitivity and specificity values of 95% and 83%, respectively, were observed. 39 . According to Sadeghi et al., (2019), both stationary and dynamic infrared images can detect a superficial tumor, but in dynamic exams they can considerably increase efficiency, due to their increased contrast and thermal events, providing greater specificity and allowing analyze different tumor depths, after cold provocative tests 40 . These data corroborate those found in this study. The potential of invisible thermal radiation is far from being fully exploited, as small variations in temperature distribution may go undetected and minimal discrepancies may be masked and remain undetected, due to two factors: low efficiency of thermal image capture sensors and thermal image treatment software 41 . It is known that computing is no longer a limitation in the processing of large volumes of data and algorithms for image segmentation have been the object of attention. The infrared systems developed in the 1970s and 80s are excellent for industrial or military purposes, but may not meet the needs of medical imaging applications, because for these high-precision images to reach their potential, minimum hardware requirements are required needed in the clinical environment 42 . James et al., (2014) demonstrated that the integration between hardware and software ends up being a limiting factor for the processing and storage of the infrared image in real-time 43 , Singh et al., (2019), point out in their study that existing intelligent systems need to improve the commercially viable interface to serve users and validate the diagnosis. In this sense, it can be noted that the results found in this study are based on the efficiency between the algorithm interaction with the operator experience (Figure 5 and 6). Therefore, despite being in constant evolution, the efficiency of the AI in detecting similar thermal signatures indicates a great step forward for the use of video thermometry in the detection of tumors and distant metastases, making possible the formation of a database (Machine Learning) for the identification of lesions and artifacts, possibly being this one of the main differentials of the results found in this study, in relation to the others. According to Hodorowicz et al., (2020), the use of thermography for the purpose of early detection of breast cancer showed higher efficiency than those found in other commonly used techniques, even when combined 44 . These same researchers show that despite the encouraging results found, there is still a long way to go, especially in the use of intelligent software for detecting the thermal variations emitted by tumors. These data corroborate those found in this study (Figure 5, 6, 7 and 8). It is known that VTM inspection looks for textures, vascular formations, known tumor thermal impression and similar areas in relation to the surroundings indicative of dysfunction. We also know that heat comes from molecular movement, respecting the degree of freedom of each molecule, tissue, organ, fluid and, since each compound has its own emissivity, then, the logic, applied to homeotherms, should be better understood. Different metabolic intensities in nearby pixels, or thermal impressions similar to tumors at a distance, in a thermally controlled environment, are not a natural condition and, as homeotherms do not tend towards thermal equilibrium as materials do, both heat production and heat loss have the purpose of keeping the temperature stable, since most of the enzymes responsible for metabolic functioning act effectively at this temperature 45 . Most natural surfaces form repetitive patterns of texture that can be recognized and differentiated by the human eye through characteristics such as smoothness, roughness and regularity 46 . Furthermore, a universal algorithm for image segmentation certainly does not exist 47 , but texture and shape can show organs, tissues and anomalies, which in most cases have specific textures and shapes 48 , therefore, software and algorithms can guide us in the range of the invisible and, if we consider that the occurrences are happening, we can say that the information is available and it is up to us to find ways to access it. Based on this, it is important to emphasize that this study was able to detect textures and thermal signatures (Figure 7 and 8). Despite an initial study, the data demonstrate an evolution between the thermometric data and the generated image, reducing the dependence on exclusive thermal analysis, since the image starts to bring more visual information and a big step towards understanding heat signatures for medical use. 5. CONCLUSION In this study, it was possible to observe the VTM assertive capacity in identifying distant metastases and breast tumors in female dogs, in relation to conventionally used techniques. It was also possible to identify textures with anatomical limits, emboli to early formations of carcinomas, adenocarcinomas and adenomyoepithelioma. It was also possible to find non-neoplastic changes such as dermatitis, lipoma, hyperplasia and breast cysts. It can be seen that these lesions would not be identified in conventional surgical planning, as the presumptive samples were not visible or palpable, being video guided exclusively by VTM. This result is promising, as benign and malignant lesions that would not be detected by the conventional method were identified by VTM, initiating the identification of lesions and artifacts for the formation of a database (Machine Learning) in order to increase accuracy. It can be concluded that the videothermometry exam is a promising technology in the preoperative evaluation of breast cancer and surgical planning, having the potential to be a routine exam and increase its applicability. Declarations ACKNOWLEDGEMENTS Ao Department of Clinical Surgery Veterinary Hospital of Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF) and to all professionals involved in this department. To Galzu Institute, Rio de Janeiro, Brazil, for the assignment of the MART station. CONFLICT OF INTEREST All of the authors claim that no conflict of interest exists. References Kristiansen, V. M., Nødtvedt, A., Breen, A. M., Langeland, M., Teige, J., Goldschmidt, M., & Sørenmo, K. (2014). 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Annual Review Of Biomedical Engineering, V. 2, N. 1, P. 315-337, 2000. Balan, Agr Et Al. Fractal Analysis Of Image Textures For Indexing And Retrieval By Content. In: Computer-Based Medical Systems, 2005. Proceedings. 18th IEEE Symposium On. IEEE, 2005. P. 581-586. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3115452","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":213644697,"identity":"83e2311b-4fd7-4e03-b2e5-b4fdf365866d","order_by":0,"name":"Paula Gebe Abreu 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Brazil","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Raul","middleName":"Ferraz","lastName":"Arruda","suffix":""},{"id":213778532,"identity":"b9a01a5e-97d9-4653-9cef-431ec5178a2e","order_by":10,"name":"Sheila Passos de Figueiredo Cabral","email":"","orcid":"","institution":"Galzu Institute, Santa Casa de Misericórdia de Campos Hospital, 115 pelinca avenue, Campos dos Goytacazes, Rio de Janeiro, Brazil","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sheila","middleName":"Passos de Figueiredo","lastName":"Cabral","suffix":""},{"id":213778533,"identity":"7e8265b3-2fc9-4524-965f-d04a16d7e913","order_by":11,"name":"Fernanda Antunes","email":"","orcid":"","institution":"Department of anaesthesiology and pharmacology, UENF, 2000 Alberto Lamego avenue, Campos dos Goytacazes, Rio de Janeiro, Brazil","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fernanda","middleName":"","lastName":"Antunes","suffix":""},{"id":213778534,"identity":"b61ff8da-2094-4ce5-89bb-3aa8299aa6dd","order_by":12,"name":"André Lacerda de Abreu Oliveira","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYBACPjDJBiKYDzAwFCC4OAEbnGRjS2BgMCBNC48BkVrYDz98XFFml9gv3/NN4oMBgzy/2AG2xxX4tPCkGRueOZecOLONd5vkDAMGw5mzE9gNz+B1WA6bZGMbs7HBMd5t0kC3JRjcTmCTbMCnhf8N+8/Gtnpj+2M8z4jUIpHDxtjYdljOgI2HjVgtz4wlG84dl5M4lmZsOcNAAuiXxHZDfFr4+ZMffmwoq+bhbz788MaHCht5funkYw/xaUEHEkDMSIqGUTAKRsEoGAXYAACsID5vL6cvwAAAAABJRU5ErkJggg==","orcid":"","institution":"Coordinator of Animal Experimental Unit, Department of Clinical Surgery Veterinary Hospital, North Fluminense Estatal University (UENF), 2000 Alberto Lamego avenue, Rio de Janeiro, Campos dos Goytacazes, Brazil","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"André","middleName":"Lacerda de Abreu","lastName":"Oliveira","suffix":""}],"badges":[],"createdAt":"2023-06-27 11:48:22","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true,"coiExplicitlySet":false},"doi":"10.21203/rs.3.rs-3115452/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3115452/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":39251314,"identity":"650757a6-c295-484e-8b59-c46d01fefbb4","added_by":"auto","created_at":"2023-06-28 18:30:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":60412,"visible":true,"origin":"","legend":"\u003cp\u003eParticipation flowchart.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3115452/v1/2342ca3e371eb8824a5bb623.png"},{"id":39252151,"identity":"cc37c7d4-c655-4a13-b087-c3c8dfba3c88","added_by":"auto","created_at":"2023-06-28 18:38:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":65209,"visible":true,"origin":"","legend":"\u003cp\u003eFemale dog\u003cstrong\u003e \u003c/strong\u003ebreast thermometry\u003cstrong\u003e \u003c/strong\u003eprocedure.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3115452/v1/8295bce521b77b6e9b6e3235.png"},{"id":39251316,"identity":"127c0597-3942-4815-89a8-8df2c9cd0516","added_by":"auto","created_at":"2023-06-28 18:30:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":201396,"visible":true,"origin":"","legend":"\u003cp\u003eA) Total number of presumptive samples collected and analyzed. B) Percentage of samples detected by the VTM technique in relation to the traditional method.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3115452/v1/a099d0a4621afc80e21d164d.png"},{"id":39251315,"identity":"5f7c6bed-c4d0-4237-a5ee-071f4fcac270","added_by":"auto","created_at":"2023-06-28 18:30:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":15209,"visible":true,"origin":"","legend":"\u003cp\u003eTotal number of tumor samples successfully identified by the techniques used.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3115452/v1/b99c48550609ba0a5e74879c.png"},{"id":39251321,"identity":"64eb1106-b50c-449a-908d-f116e5e0d94a","added_by":"auto","created_at":"2023-06-28 18:30:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":245410,"visible":true,"origin":"","legend":"\u003cp\u003eDemarcation of tumor mass and identification of non-visible or palpable distant metastasis, identified by VTM (red and green markings).\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-3115452/v1/fe436e7aed6bea5d4819c61d.png"},{"id":39251319,"identity":"cae6e8a5-30f3-408e-8e9a-96eb83c6a59f","added_by":"auto","created_at":"2023-06-28 18:30:02","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":228867,"visible":true,"origin":"","legend":"\u003cp\u003eDemarcation of tumor mass and identification of non-visible or palpable distant metastasis, identified by VTM (red markings).\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-3115452/v1/49a8d54c405475e880038a9e.png"},{"id":39251320,"identity":"f3ae37ba-d5af-4304-8302-8405fba7b1bb","added_by":"auto","created_at":"2023-06-28 18:30:02","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":104455,"visible":true,"origin":"","legend":"\u003cp\u003eMammary tumor in a female dog. In image A, we observe the real image of a visible solid tumor mass of adenocarcinoma in the right caudal abdominal mammary gland.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-3115452/v1/87db0ab96445eccfc0074595.png"},{"id":39252152,"identity":"cec41a4e-f004-4dac-a07f-fa3a453309aa","added_by":"auto","created_at":"2023-06-28 18:38:02","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":218715,"visible":true,"origin":"","legend":"\u003cp\u003eImages C, D, and E demonstrate sequential moments were captured by VTM, revealing textures that highlight tubular structures.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-3115452/v1/3f59bdb3278d3afec50912c5.png"},{"id":39252153,"identity":"0c7ffc87-658c-4026-9ba2-4f76ee2e9c6d","added_by":"auto","created_at":"2023-06-28 18:38:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1630087,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3115452/v1/ab291b5c-220f-4ec5-8384-275a1381c624.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003e\u003cstrong\u003eRemote metastasis detection by video thermometry: A promissing preclinical study\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eApproximately 25% of female dogs develop new nodules following surgical removal, which have the potential to be malignant despite the initial tumor being benign\u003csup\u003e1\u003c/sup\u003e. The process of metastasis is selective for the few cells that lose their adhesion and manage to penetrate vessel walls, eventually forming emboli in distant capillary beds. If the immune system fails to eliminate these cells, metastasis can occur\u003csup\u003e2\u003c/sup\u003e. Angiogenesis, hypervascularity, and hyperthermia are frequent and early alterations observed in breast tumors\u003csup\u003e3,4,5\u003c/sup\u003e,\u0026nbsp;small with only 100 cells\u003csup\u003e6\u003c/sup\u003e.\u0026nbsp;Furthermore, the extracellular space in most tumors is slightly acidic due to the excessive production of lactic acid (aerobic glycolysis - chronic activation of hypoxia-inducible factor-1 / HIF-1) and the H\u003csup\u003e+\u003c/sup\u003e transport through the plasma membrane mediated by V-ATPases\u003csup\u003e7,8\u003c/sup\u003e. This acidity creates a favorable tumor microenvironment, promoting angiogenesis and influencing its invasive capabilities\u003csup\u003e9\u003c/sup\u003e. However, the hypervascularity and microvessel density around the tumor correlate with the central temperature of the tumor\u003csup\u003e10\u003c/sup\u003e, and this heat is a result of different metabolic intensities\u003csup\u003e11\u003c/sup\u003e It can be detected by infrared sensors\u003csup\u003e12,13\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn 1957, a milestone in the detection of breast cancer occurred when Lawson used, for the first time, a thermal camera for this purpose. He identified temperature differences between the tumor and the surrounding healthy area. In 1963, researchers such as Lausanne and Ghatmati published studies that associated increased skin temperature with breast cancer, highlighting the importance of venous convection in this process. In 1982, the Food and Drug Administration (FDA) approval\u0026nbsp;thermometry\u0026nbsp;as a diagnostic aid to detect breast cancer \u003cs\u003ecame\u003c/s\u003e. In 1996, a comparative study between thermal imaging and radiography showed that thermal imaging was able to detect the disease in a patient, while radiography was not able to identify it.\u003csup\u003e14\u003c/sup\u003e.\u0026nbsp;Subsequently, in 2003, the FDA approved real-time digital thermometry as a classifier for assisted neural networks.\u003c/p\u003e\n\u003cp\u003eDifferent tissues have different emissivity at infrared wavelengths, emitting signals\u003csup\u003e15\u003c/sup\u003e\u003csup\u003e,16\u003c/sup\u003e.\u0026nbsp;Objects naturally emit thermal signals\u0026nbsp;in the range of infrared electromagnetic radiation,\u0026nbsp;and the type of signal emitted or radiated at a certain temperature depends on both the characteristics of the object and its surrounding environment\u003csup\u003e17\u003c/sup\u003e, just like the technology that captures these signals and transforms them into images\u003csup\u003e18\u003c/sup\u003e,\u0026nbsp;Therefore, infrared measurement devices acquire the radiation emitted by the object and convert it into an electronic signal\u003csup\u003e19,20\u003c/sup\u003e.\u0026nbsp;When\u0026nbsp;a cell performs a biological task ATP hydrolysis takes place resulting in the loss of energy in the form of heat\u003csup\u003e21\u003c/sup\u003e.\u0026nbsp;Only with the advancements in thermodynamics was the mechanical theory of heat established, with heat being recognized as dynamic energy in motion,\u0026nbsp;derived from molecular motion based on the degree of freedom of each molecule\u003csup\u003e22\u003c/sup\u003e,\u0026nbsp;which can be measured on a varying scale of degrees that we refer to as temperature\u003csup\u003e23\u003c/sup\u003e.\u0026nbsp;The heat from infrared radiation\u0026nbsp;is based on thermodynamics and the transfer of bioheat\u003csup\u003e24\u003c/sup\u003e. The Stefan-Boltzmann law can be used to understand the relationship between the energy emitted by an object and its temperature, while the Penne\u0026rsquo;s bioheat equation can effectively measure the heat produced by cancer cells.\u003csup\u003e25\u003c/sup\u003e. In breast carcinomas, increased cellular activity leads to changes in local temperature\u003csup\u003e26\u003c/sup\u003e As a result, the heat generated from metabolism can vary in intensity, leading to thermal asymmetries\u003csup\u003e27\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInfrared electromagnetic radiation lies outside the human visual range and, therefore, is capable of recording non-visible occurrences\u003csup\u003e28\u003c/sup\u003e.\u0026nbsp;On the other hand,\u0026nbsp;the sensitivity of infrared sensors has significantly improved from 0.5\u0026deg;C in the 1960s to less than 0.02\u0026deg;C in modern sensors, allowing them to accurately capture the subtle temperature variations of the breast\u003csup\u003e29\u003c/sup\u003e. The dynamic cooling-assisted video image capture monitors the temperature of each pixel over time, thereby increasing specificity\u003csup\u003e30\u003c/sup\u003e, furthermore, with computational resources, artificial intelligence can be utilized to extract more features from this technology\u003csup\u003e31\u003c/sup\u003e. Although, the use of thermography has been recognized as a potential mechanism for the diagnosis and monitoring of cancers, particularly skin and breast cancers, thermography is linked to portable cameras and industrial software that limits video and processing functionalities dedicated to homeotherms\u0026nbsp;beings,\u0026nbsp;harming its application for diagnostic purposes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVideo thermometry\u003c/strong\u003e together with a SaMD with mechanisms of artificial intelligence and machine learning, has the potential to emerge as a significant tool for cancer detection, even being used during surgical procedures to provide real-time visualization of tumor margins to the medical team. However, its utilization is still limited,\u0026nbsp;due to emerging technology.\u003c/p\u003e\n\u003cp\u003eThe dynamic images in this study were referred to as video thermometric or video thermometry images. Based on this, the objective of this study was to detect distant metastases in canine mammary neoplasms.\u003c/p\u003e"},{"header":"2. MATERIALS AND METHODS","content":"\u003cp\u003e\u003cstrong\u003e2.1. Sampling method\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwenty-one female dogs with palpable mammary nodules underwent total unilateral mastectomy. This study was approved by the animal ethics committee ID 432171-CEUA/UENF. As the inclusion criteria, female dog in reproductive phase, without weight or age restrictions, with one or more evident masses of adenomas, carcinomas, or their mixed variants were included in this study. These surgeries were combined with real-time, non-contact video thermometry examination, and the image capture was performed in a temperature-controlled surgical center maintained at 22\u0026plusmn;2\u0026deg;C. All visible tumor masses were sent for histopathological diagnosis, and twenty-five presumptive samples, guided by VTM, were collected for histopathological study. In three surgeries, multiple presumptive samples were collected, as shown in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. Anesthetic Procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter trichotomy, the animal was taken to the operating room, where it was positioned, sedated, and anesthetized. Induction was performed by intravenous administration of propofol at a dose of 3 mg/kg\u003csup\u003e-1\u003c/sup\u003e, and anesthesia maintenance was achieved with 100% oxygen and isoflurane via a semi-closed inhalation anesthesia circuit (Baraka system) for animals weighing up to 7 kg, and a semi-closed circuit for animals weighing over 7 kg. Intraoperative pain control was achieved through continuous infusion of morphine sulfate at a rate of 1.66\u0026nbsp;\u0026mu;g/kg-1/min, lidocaine hydrochloride at 30\u0026nbsp;\u0026mu;g/kg\u003csup\u003e-1\u003c/sup\u003e/min, and ketamine hydrochloride at 15\u0026nbsp;\u0026mu;g/kg\u003csup\u003e-1\u003c/sup\u003e/min, initially administered as bolus doses and subsequently maintained using an infusion pump at a dosage of 0.4 mg/kg of morphine, 1 mg/kg of lidocaine, and 1 mg/kg of ketamine. Heart rate (HR), respiratory rate (RR), peripheral oxygen hemoglobin saturation (SpO\u003csub\u003e2\u003c/sub\u003e), electrocardiographic tracing, plethysmography, end-tidal carbon dioxide concentration (EtCO\u003csub\u003e2\u003c/sub\u003e), and non-invasive blood pressure were monitored. The animals remained under spontaneous ventilation throughout the operation. Postoperative analgesia was achieved through a combination of oral tramadol hydrochloride at a dose of 4 mg/kg-1 every 12 hours, oral carprofen at a dose of 2.2 mg/kg\u003csup\u003e-1\u003c/sup\u003e every 12 hours, and dipyrone at a dose of 25 mg/kg\u003csup\u003e-1\u003c/sup\u003e every 12 hours, all administered for a duration of 5 days. Patient selection was based on clinical assessment and complementary exams (medical history, physical examination, laboratory tests, imaging exams, prescription of supportive care, and surgical referral), as well as postoperative care (hospitalization, monitoring, antibiotic therapy, and pain management).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. Transoperative Video Thermometric\u0026nbsp;Evaluation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe examination was performed using the MART (Metabolic Activity in Real-Time) station designed for surgical center and/or educational purposes, utilizing the Mart v2.0 software for video thermometric image processing and enhancement. The operator of the station was positioned outside the sterile environment, avoiding interference with the surgical routine, while the thermic sensor was positioned above the surgical field at a variable height ranging from 1 to 1.20 meters.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter sedation, a 15 minutes period was performed for the patient\u0026apos;s thermal acclimatization with room temperature of 22\u0026plusmn;2\u0026deg;C before starting the inspection protocol. Subsequently, a provocative test was performed with 0.5% chlorhexidine alcoholic solution. This procedure helps to mark the main tumor irrigation and the direction of blood flow in the mammary chains, axillary and inguinal lymph nodes to confirm, later, if images of similarity are found in the direction of the verified flow. As the skin generates heat, thermal discrepancies between nearby pixels call attention to dysfunction, perforating arteries, hot or cold regions for another reason and artifacts which must be differentiated during the exam.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4. Analysis of Video\u0026nbsp;thermometric\u0026nbsp;Images\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this experiment, in the pre-operative inspection, the \u0026ldquo;Merlin\u0026rdquo; tool, shows several small images with different color gradients, where the operator chooses the screen that shows the best image and transfer it to the processing area. In this sense, the operator processed the image following the MART protocol with the following routine: 1) assessment of symmetry; 2) vascular inspection; 3) analysis of thermal discrepancy in nearby pixels in areas suspected of abnormalities. 4) identification of textures and anatomical delimitation; 5) search for similarities of thermal patterns; when the operator marks a breast cancer known area and activate the \u0026ldquo;Similarity\u0026rdquo; tool, automatically identifies areas with the same thermal signature, thus enabling the identification of possible areas to be inspected by the surgeon during the surgical procedure. The operator suggest which presumptive samples should be collected in the preoperative. In this study, the images were recorded on video, in real time, from the acclimatization period until the beginning of the surgery\u003csup\u003e32,33\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003eIn this study 21 unilateral total mastectomy surgeries were performed, and during these procedures, 23 presumptive samples of remote alterations were collected (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Identification of the number of surgeries and number of presumptive samples collected, histopathological diagnosis of the primary tumor, and remote presumptive samples in mammary tumors in female dogs.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.67548500881834%\" colspan=\"2\"\u003e\n \u003cp\u003ePRIMARY TUMOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\"\u003e\n \u003cp\u003ePRESUMPTIVE RESULT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eCarcinoma s\u0026oacute;lido\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eBreast Carcinoma Embolus and Vascular Hamartoma\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eAdenocarcinoma with Solid and Tubular Areas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eNeoplastic Embolus in Vessel, Mammary\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDuct with Cellular Proliferation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eMulticentric Tubular Carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eTubular Carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eSolid Tubular Carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eTubular Carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eTubular Breast Adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eTubular Breast Adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eComplex Adenomyoepithelioma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eMalignant Grade II Adenomyoepithelioma\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eComplex Adenomyoepithelioma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eBasal Cell Carcinoma, well-differentiated with clear surgical margins.\u003c/p\u003e\n \u003cp\u003eDermatitis.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eComplex Adenocarcinoma with Differentiated Cystic and Papillary Areas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eMammary Cysts and Hyperplasia\u003c/p\u003e\n \u003cp\u003eMammary Hyperplasia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eTubular Carcinoma in Mixed Tumor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eLipoma\u003c/p\u003e\n \u003cp\u003eDermatitis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eSolid Carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eDermatitis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eBreast Adenoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eBreast Hyperplasia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eSolid Carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eNo abnormalities detected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eSuppurated Grade I Ductal Adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eNo abnormalities detected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eComplex Adenomyoepithelioma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eNo abnormalities detected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\" valign=\"top\"\u003e\n \u003cp\u003eCystadenocarcinoma in Mixed Tumor, Grade I and II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eNo abnormalities detected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\"\u003e\n \u003cp\u003eUlcerated Carcinosarcoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eNo abnormalities detected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\"\u003e\n \u003cp\u003ePapillary Adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eNo abnormalities detected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\"\u003e\n \u003cp\u003eCystic and Papillary Adenocarcinoma with Abundant Squamous Differentiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eNo abnormalities detected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\"\u003e\n \u003cp\u003eSolid Adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eNo abnormalities detected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\"\u003e\n \u003cp\u003eCarcinoma in Mixed Tumor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eNo abnormalities detected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.054673721340388%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.620811287477956%\"\u003e\n \u003cp\u003eTubular Carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.32451499118166%\" valign=\"top\"\u003e\n \u003cp\u003eNo abnormalities detected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eOf the collected samples, 07 neoplastic alterations and 06 non-neoplastic alterations were found. 10 samples had no alteration (Table 1). Among the altered samples, proven through histopathology, 44% were not detected by the conventional identification method, and 56% were not visible or palpable. All altered samples were found by video thermometry (Figure 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOf the total number of lesions identified, the evaluation performed using videotermometria was 62% more accurate than the conventional method (Figure 4).\u003c/p\u003e\n\u003cp\u003eIn figure 5, it is possible to observe the demarcation of two known tumor masses, which are visible and palpable in the female dog abdominal and caudal breast. it is also possible to observe the thermal signature identification tool of the algorithm, which it was able to identify the two predominant temperatures, and similar ones, of the tumor masses already identified by the conventional method. However, the algorithm was also able to identify a cranial image with thermal impression similar to known masses, along the vascular pathways of the left mammary chain, with temperature discrepancy of the surrounding areas. This image, although very small, had the same thermal signature as the already known masses and, through histopathological examination, the presumed sample resulted in a neoplastic embolus.\u003c/p\u003e\n\u003cp\u003eIn figure 6, it is possible to observe the visible tumor mass of the breast female dog, showing the previous left total mastectomy scar. In the video thermometry exam, it was possible to observe the textures of the tumor architecture, as well as the predominant vascular supply (black). Through the similarity analysis of the thermal signature, it was possible to identify an image in the right cranial abdominal mammary region, compatible with the vascular pathways and showing a thermal impression similar to the known mass, after the analysis and verification of the thermal discrepancies (red arrow). Through histopathological examination, the presumptive sample resulted in a neoplastic embolus compatible with carcinoma and vascular hamartoma.\u003c/p\u003e\n\u003cp\u003eIn Figure 7A, it was possible to observe a visible solid tumor mass of adenocarcinoma in the right caudal abdominal breast. Next to it, the right inguinal mammary gland appears enlarged in relation to the contralateral gland, but on palpation, its elastic and deformable appearance suggests a lipoma. Figure 7B shows the intraoperative view of the right total mastectomy, where the tubular images become apparent.\u003c/p\u003e\n\u003cp\u003eImages 8C, 8D and 8E are from the intraoperative phase in which it is possible to observe the surgeon\u0026apos;s hand over the tumor mass on the left. In the area marked with a red circle, three sequential moments were captured by VTM, revealing the ability of the technique, together with the algorithm, to highlight textures and tubular structures. Upon histopathological examination, the findings resulted in mammary hyperplasia and cysts.\u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThermometry\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eis an image generated by convert infrared radiation emitted from the body into electrical impulses (radiometric image) that are displayed on a monitor in various colors\u003csup\u003e34\u003c/sup\u003e. The spectrum of colors\u0026nbsp;based on a degrees scale\u0026nbsp;indicates an increase or decrease in the infrared radiation or temperature being emitted from the body surface. An abnormality detected by thermal image\u0026nbsp;indicates an area of temperature asymmetry in the body. Based on patterns of heat and blood flow on or near the surface of the body, thermometry\u0026nbsp;has been utilized in an effort to detect, characterize, and monitor multiple diseases processes. Although thermography\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ehas already been demonstrated as a potential breast cancer detection mechanism\u003csup\u003e35,36,37\u003c/sup\u003e, VTM can become an important tool during image processing, through an AI system capable of detecting benign alterations and distant metastases, tumor textures and delimitation, tumor vascular supply, as demonstrated by the data of this study.\u003c/p\u003e\n\u003cp\u003ePresumptive\u0026nbsp;samples\u0026nbsp;without abnormalities may be artifacts, vascular changes, or initial pathological changes not found on histopathological examination. This image reflects a different generation of heat from the surroundings, demonstrating that the composition of matter in this location generates a molecular movement that differs from the surrounding\u0026nbsp;region.\u003c/p\u003e\n\u003cp\u003eAccording to Jiang et al., (2010), the dynamic state of the breast exhibits distinct patterns, which makes it difficult to identify thermal signatures to identify tumors and metastases in the tissue\u003csup\u003e38\u003c/sup\u003e. A study by Jawzal (2018) indicates that thermography reflects, mainly, a heat map under the skin, but does not exactly locate the tumor for surgical purposes, and may cause confusion during the procedure, when the metabolic intensity of some tumors decreases.\u003c/p\u003e\n\u003cp\u003eThe results found in this study, with the advancement of technology, \u003cs\u003eare in\u003c/s\u003e contrast to those found by Jiang et al., (2010) and Jawzal (2018), since, among all the samples with alteration that were verified in the study,\u0026nbsp;62% were alterations neoplastic lesions distant from the primary tumor (Figure 4). This result is promising, as benign and malignant lesions that would not be detected by the conventional method were identified by VTM.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIt is noteworthy that the identification of distant metastases was made through the use of thermal signatures of the tumor tissue. This data shows the efficiency not only of the VTM, but also the algorithm, which was able to identify the thermal signatures of the lesion and detect the same signature, enabling the detection of distant metastases from the primary tumor, even at a very early stage.\u003c/p\u003e\n\u003cp\u003eAnother factor that may explain the success rate of the technique in this study was reported by Vardasca et al., (2018), in which it was demonstrated that temperature differences between the areas of lesions and the surrounding tissue can be used to differentiate neoplasms. In the case of benign neoplasms of the skin, if dynamic thermal imaging (DTI) and application of cold stress are used, sensitivity and specificity values of 95% and 83%, respectively, were observed.\u003csup\u003e39\u003c/sup\u003e. According to Sadeghi et al., (2019), both stationary and dynamic infrared images can detect a superficial tumor, but in dynamic exams they can considerably increase efficiency, due to their increased contrast and thermal events, providing greater specificity and allowing analyze different tumor depths, after cold provocative tests\u003csup\u003e40\u003c/sup\u003e. These data corroborate those found in this study.\u003c/p\u003e\n\u003cp\u003eThe potential of invisible thermal radiation is far from being fully exploited, as small variations in temperature distribution may go undetected and minimal discrepancies may be masked and remain undetected, due to two factors: low efficiency of thermal image capture sensors and thermal image treatment software\u003csup\u003e41\u003c/sup\u003e.\u0026nbsp;It is known that computing is no longer a limitation in the processing of large volumes of data and algorithms for image segmentation have been the object of attention. The infrared systems developed in the 1970s and 80s are excellent for industrial or military purposes, but may not meet the needs of medical imaging applications, because for these high-precision images to reach their potential, minimum hardware requirements are required needed in the clinical environment\u003csup\u003e42\u003c/sup\u003e.\u0026nbsp;James et al., (2014) demonstrated that the integration between hardware and software ends up being a limiting factor for the processing and storage of the infrared image in real-time\u0026nbsp;\u003csup\u003e43\u003c/sup\u003e, Singh et al., (2019), point out in their study that existing intelligent systems need to improve the commercially viable interface to serve users and validate the diagnosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this sense, it can be noted that the results found in this study are based on the efficiency between the algorithm interaction with the operator experience\u0026nbsp;(Figure 5 and 6). Therefore, despite being in constant evolution, the efficiency of the AI in detecting similar\u0026nbsp;thermal signatures indicates a great step forward for the use of video thermometry in the detection of tumors and distant metastases, making possible the formation of a database (Machine Learning) for the identification of lesions and artifacts, possibly being this one of the main differentials of the results found in this study, in relation to the others.\u003c/p\u003e\n\u003cp\u003eAccording to Hodorowicz et al., (2020), the use of thermography for the purpose of early detection of breast cancer showed higher efficiency than those found in other commonly used techniques, even when combined\u003csup\u003e44\u003c/sup\u003e. These same researchers show that despite the encouraging results found, there is still a long way to go, especially in the use of intelligent software for detecting the thermal variations emitted by tumors. These data corroborate those found in this study (Figure 5, 6, 7 and 8).\u003c/p\u003e\n\u003cp\u003eIt is known that VTM inspection looks for textures, vascular formations, known tumor thermal impression and similar areas in relation to the surroundings indicative of dysfunction. We also know\u0026nbsp;that heat comes from molecular movement, respecting the degree of freedom of each molecule, tissue, organ, fluid and, since each compound has its own emissivity, then, the logic, applied to homeotherms, should be better understood. Different metabolic intensities in nearby pixels, or thermal impressions similar to tumors at a distance, in a thermally controlled environment, are not a natural condition and, as homeotherms do not tend towards thermal equilibrium as materials do, both heat production and heat loss have the purpose of keeping the temperature stable, since most of the enzymes responsible for metabolic functioning act effectively at this temperature\u003csup\u003e45\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eMost natural surfaces form repetitive patterns of texture that can be recognized and differentiated by the human eye through characteristics such as smoothness, roughness and regularity\u003csup\u003e46\u003c/sup\u003e. Furthermore, a universal algorithm for image segmentation certainly does not exist\u003csup\u003e47\u003c/sup\u003e, but texture and shape can show\u0026nbsp;organs, tissues and anomalies, which in most cases have specific textures and shapes\u003csup\u003e48\u003c/sup\u003e, therefore, software and algorithms can guide us in the range of the invisible and, if we consider that the occurrences are happening, we can say that the information is available and it is up to us to find ways to access it. Based on this, it is important to emphasize that this study was able to detect textures and thermal signatures (Figure 7 and 8). Despite an initial study, the data demonstrate an evolution between the thermometric data and the generated image, reducing the dependence on exclusive thermal analysis, since the image starts to bring more visual information and a big step towards understanding heat signatures for medical use.\u003c/p\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eIn this study, it was possible to observe the VTM assertive capacity in identifying distant metastases and breast tumors in female dogs, in relation to conventionally used techniques. It was also possible to identify textures with anatomical limits, emboli to early formations of carcinomas, adenocarcinomas and adenomyoepithelioma. It was also possible to find non-neoplastic changes such as dermatitis, lipoma, hyperplasia and breast cysts. It can be seen that these lesions would not be identified in conventional surgical planning, as the presumptive samples were not visible or palpable, being video guided exclusively by VTM. This result is promising, as benign and malignant lesions that would not be detected by the conventional method were identified by VTM, initiating the identification of lesions and artifacts for the formation of a database (Machine Learning) in order to increase accuracy. It can be concluded that the videothermometry exam is a promising technology in the preoperative evaluation of breast cancer and surgical planning, having the potential to be a routine exam and increase its applicability.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAo Department of Clinical Surgery Veterinary Hospital of Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF) and to all professionals involved in this department.\u003c/p\u003e\n\u003cp\u003eTo Galzu Institute, Rio de Janeiro, Brazil, for the assignment of the MART station.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONFLICT OF INTEREST\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll of the authors claim that no conflict of interest exists.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKristiansen, V. M., N\u0026oslash;dtvedt, A., Breen, A. 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P. 581-586.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Universidade Estadual do Norte Fluminense Darcy Ribeiro","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"breast cancer, diagnostic imaging, video thermometry, infrared imaging, SaMD","lastPublishedDoi":"10.21203/rs.3.rs-3115452/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3115452/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe thermometric video image (VTM) can guide the search for distant metastases, once the vascular architecture is known, identifying, by segmentation, the tumor thermal impression and a similar pattern at a distance. Thus, suspicious areas can be better investigated, improving the postoperative prognosis. In this study, it was possible to observe the assertive capacity of video thermometry in identifying distant metastases and breast tumors in female dogs, not palpable or visible to the naked eye, in relation to conventionally used techniques. It was also possible to identify textures with anatomical limits, from emboli to early formations of carcinomas, adenocarcinomas and adenomyoepithelioma. It was also possible to find non-neoplastic changes such as dermatitis, lipoma, hyperplasia and breast cysts. it can be concluded that the video thermometry (VTM) technique was capable of identifying distant metastases from the primary tumor and other benign alterations with great precision. However, for this to be possible, it is essential that the processing be carried out by SaMD (Software as a Medical Device), with tools capable of identifying patterns and thermal signatures, just like the algorithm, thus increasing the efficacy of the technique.\u003c/p\u003e","manuscriptTitle":"Remote metastasis detection by video thermometry: A promissing preclinical study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-06-28 18:29:57","doi":"10.21203/rs.3.rs-3115452/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ace44646-e53a-42ea-b723-d08403f56010","owner":[],"postedDate":"June 28th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-06-28T18:29:57+00:00","versionOfRecord":[],"versionCreatedAt":"2023-06-28 18:29:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3115452","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3115452","identity":"rs-3115452","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}