The impact of diabetes mellitus on foot perfusion pre- and post-revascularisation measured by near-infrared fluorescence imaging

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Peul, Mo W. Kruiswijk, Floris P. Tange, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6905400/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 Introduction: Diabetes Mellitus (DM) contributes to the complexity of lower extremity arterial disease (LEAD), inducing peripheral neuropathy and increasing susceptibility to severe ischemia, foot ulceration, and amputation. Perfusion differences in LEAD patients with and without DM may advocate a more individualised revascularisation strategy than the current WIfI classification for risk prediction. This study aims to utilise near-infrared (NIR) fluorescence imaging with Indocyanine Green (ICG) to assess perfusion parameters before and after revascularisation in DM and non-DM patients and explore their relationship with clinical outcome. Methods ICG NIR fluorescence imaging was performed pre- and post-revascularisation in LEAD patients with and without DM. Three time-related perfusion parameters were analysed to assess differences in perfusion patterns. Clinical improvement (CI) after revascularisation was analysed in chronic limb-threatening ischemia (CLTI) patients with- and without DM. Results Successful revascularisation and ICG NIR fluorescence measurements were conducted in 128 patients (144 limbs), with 42 (48 limbs) DM patients. Two out of three revascularisation parameters post-operatively improved significantly in the DM group, compared to three out of three in the non-DM group. Additionally, in the sub-analyses of the CLTI group, no parameters in the DM CI group showed significant enhancement, compared to significant improvements in all parameters in the non-DM CI group (p = 0.003 - <0.001). A trend towards a lower likelihood of CI was observed in DM CLTI patients, though not statistically significant (86% vs 66%, p = 0.073). Conclusion This study demonstrates the capability of ICG NIR fluorescence to map disparities in the dynamic tissue perfusion between DM and non-DM LEAD patients undergoing revascularisation. In general, ICG NIR fluorescence findings appear to correlate with postoperative outcomes, with CLTI DM patients showing reduced responsiveness to therapy. These findings may pave the way for a more personalised approaches in CLTI revascularisation. Diabetes Lower extremity arterial disease Perfusion NIRF-imaging Indocyanine green Revascularisation Clinical outcome Figures Figure 1 Figure 2 1. Introduction Patients with diabetes mellitus (DM) form a heterogeneous group with a considerable but variable risk of developing diabetic complications, such as a diabetic foot ulcer (DFU), peripheral neuropathy and microvascular disease. ( 1 ) Additional risk factors, including infection, structural foot deformities, and impaired metabolic regulation, further influence the high risk of limb loss and mortality in these patients. ( 2 ) Patients with combined lower extremity arterial disease (LEAD) and DM are disproportionately affected by critical limb-threatening ischaemia (CLTI), the most severe form of LEAD. Up to 25% of individuals with DM will develop a DFU during their lifetime, often associated with CLTI. CLTI in DM patients carries a 14–24% risk of major amputation and a five-year post-amputation mortality rate increasing 50%. ( 2 – 5 ) Revascularisation remains the cornerstone of CLTI treatment, aiming to improve blood flow, promote ulcer healing, and prevent limb loss. ( 6 ) However, DM patients face disproportionately worse outcomes compared to non-DM patients, including higher rates of restenosis (HR 1.73), total occlusion (HR 1.74), major amputation (HR 1.5-4), and mortality (HR 1.2-2). ( 7 – 11 ) The Society for Vascular Surgery’s WIfI classification system, is commonly used to guide treatment and predict outcomes in CLTI patients. ( 5 , 6 , 12 ) The WIfI system incorporates parameters for wound severity, ischaemia, and foot infection. However, the perfusion assessment, typically measured by ankle-brachial index (ABI), toe pressure (TP), toe-brachial index (TBI), or transcutaneous oxygen pressure (TcPO₂), is often unreliable in DM patients. For instance, to predict LEAD, ABI has a sensitivity of only 35%, TP 82%, and TcPO₂ 72%. ( 13 – 15 ) TBI, in particular, has a limited specificity of 66%.( 16 ) These metrics fail to adequately account for the diabetic vascular dysfunction and impaired tissue perfusion pre- and postoperative, and may explain the inferior outcomes observed in DM patients following revascularisation. ( 13 , 14 , 17 , 18 ) Understanding the differences in outcomes following revascularisation between DM and non-DM patients is important, as variations in foot perfusion may partly explain these differences.( 19 , 20 ) Near-infrared (NIR) fluorescence imaging with indocyanine green (ICG) enables real-time, quantitative perfusion assessment, unaffected by arterial calcification or neuropathy, making it ideal for DM patients. It detects microvascular differences between DM and non-DM patients, offering insights into DM-related foot complications.( 21 ) Moreover, ICG-based assessments can potentially improve clinical decision-making and postoperative outcomes by guiding individualised treatment strategies. ( 21 – 25 ) This study aims to examine perfusion changes before and after revascularisation in LEAD patients with and without DM using ICG NIR fluorescence imaging and explore the relationship between these perfusion parameters and clinical outcomes. 2. Methods 2.1 Patients This retrospective cohort study included all LEAD patients treated at the Leiden University Medical Center (LUMC) between July 2019 and August 2024 who underwent a technically successful revascularization. The presence and severity of LEAD was diagnosed by the treating physician based on clinical presentation, maximal systolic acceleration (ACCmax), duplex ultrasound, and CT angiography.( 26 , 27 ) Patients with DM were defined as individuals with a clinical diagnosis of either type 1 or type 2 diabetes, according to the American Diabetes Association (ADA) criteria. ( 28 ) In cases of bilateral treatment, data from both feet were included. 2.2 Measurements Perfusion parameters were assessed to compare the DM and non-DM groups before and after revascularization. Additionally, patients were stratified according to the Fontaine classification, as recommended by the European Society for Vascular Surgery, to account for different stages of vascular disease.( 6 ) In patients with CLTI (Fontaine stage 3 and 4), further distinction was made between those with and without clinical improvement (CI). Only CLTI patients were included in this analyses, being the highest risk group with the most severe (diabetic) vascular damage. CI was defined by the treating physician as a resolution of rest or nocturnal pain, improvement of walking distance, or noticeable progress in wound or ulcer healing. ICG NIR fluorescence imaging was performed following a predefined protocol.( 23 ) Trained personnel conducted ICG NIR measurements pre- and post-revascularization, initially within the study framework and later as part of routine clinical practice. 2.3 Measurement setup Pre- and post-revascularisation, all patients received a bolus of 0.1 mg/kg of ICG (Verdye 25mg, Diagnostic Green HmbH) through the IV placed in the cubital vein. A 5-minute ICG NIR recording was made utilising the Quest Spectrum Platform® (Quest Medical Imaging, Wieringerwerf, The Netherlands) positioning it at 50cm perpendicular to the dorsum of the foot. This imaging system is equipped with a dual light source comprising an LED for visible light and a NIR source operating within the 700–820 nm wavelength range. 2.4 Quantification The Quest Research Framework® (Quest Medical Imaging, Wieringerwerf, the Netherlands) software was used to post-operatively quantify the NIR fluorescence signals. This application measures the ICG signal within a designated region of interest (ROI) and produces time-intensity curves. The entire dorsum of the foot was selected as a ROI. Supplemental Fig. 1 displays a time-intensity curve depicting the in- and outflow of the ICG signal generated by the software. These curves provide extractable perfusion parameters, of which three time-related and normalised parameters were analysed.( 29 , 30 ) The 3 time-related parameters used in this study included the time till maximum intensity (Tmax), the normalized maximum ingress slope (norm max ingress slope), and the area under the curve 180 seconds after Tmax (Egress-180). Extraction of the perfusion parameters was performed for all measurements pre- and post-revascularisation. In this study, the dorsum of the interventional foot was selected as the ROI. The software's integrated motion tracker corrected for movement during the ICG NIR fluorescence measurements. All parameters except the normalized maximum ingress slope were extracted from the absolute curves. 2.5 Statistical analyses The Wilcoxon signed-rank test was utilised to analyse pre- and post-revascularisation parameter differences within the DM and non-DM groups. Normality was assessed using the Kolmogorov-Smirnov-test. Parameters with non-normal distributions necessitated the utilisation of medians instead of means. A chi-square test was performed to analyse the difference in CI between the DM and non-DM CLTI groups. IBM SPSS Statistics 25 (IBM Corp., 2017) was used for statistical analyses. 2.6 Ethical considerations This study (G21.087) received approval from the Medical Research and Ethics Committee of the LUMC. It was conducted in accordance with the Declaration of Helsinki and institutional guidelines. Informed consent was obtained from all enrolled patients. 3. Results 3.1 Patient characteristics Successful ICG NIR measurements were performed in 128 LEAD patients (144 limbs) of which 42 patients (48 limbs) suffered from DM. Table 1 provides a complete description of the study population. The group consisted of 49 women, whereof 12 had DM. No significant difference was observed in Fontaine classification between the DM and non-DM group (p = 0.639). Revascularisation levels varied significantly between groups (p = 0.019), with DM patients more frequently undergoing crural (16,6% vs 3,2%) and aortoiliac (39,6% vs 30,2%) procedures, while non-DM patients had a higher incidence of femoral-popliteal revascularisations (66,6% vs 43,8%). Revascularisation type displayed a significant difference as well, predominantly performing percutaneous transluminal angioplasty (PTA) in DM patients (72,9% vs 59,4%) and bypass surgery in non-DM patients (20,8% vs 8,3%). 3.2 Outcomes Pre- versus Post-revascularisation Table 2 displays the extracted pre- and post-revascularisation parameters of all LEAD patients categorised by DM. Pre-revascularisation, all parameters in the DM group showed a faster in- and outflow compared to the non-DM group. Post-revascularisation, all parameters in both groups improved in value. All parameters improved significantly in the non-DM group (p-values <0.001) compared to 2 out of 3 in the DM group (p-values between 0.03 - <.001). Egress-180 was found to be insignificantly improved (∆ %=4,4, p=0.104). When comparing the revascularisation effect (∆%) between the groups, a consistently larger improvement is observed in all parameters of the non-DM group. 3.3 Clinical improvement Table 3 outlines the perfusion parameters for the CI groups. Post-revascularisation, 14 out of 23 DM patients with CLTI demonstrated CI. In the non-DM CLTI group, 32 out of 37 patients showed CI (66% vs 86%, p=0.073). The mean follow-up time was 36,43±20,14 days. None of the parameters significantly improved in the DM CLTI CI group (p values between 0.433–0.056), whereas 3 out of 3 parameters significantly improved in the non-DM CLTI CI group (p-values ranging from 0.003 to < 0.001). Table 4 presents the no-CI data of both the DM and non-DM group. In the DM CLTI no-CI group, none of the parameters showed significant improvement. Conversely, 2 out of 3 parameters displayed higher post-revascularisation values. In contrast, none of the parameters in the non-DM CLTI no-CI group showed significant improvement, with all parameters demonstrating a post-revascularisation signal decrease. Figure 1 displays the percentual difference in perfusion values between the DM and non-DM CI groups, whereas Fig. 2 displays this for the no-CI groups. 4. Discussion This study demonstrated significant differences in foot perfusion following revascularisation in LEAD patients with DM compared to non-DM patients. Pre-revascularisation, DM patients exhibited a different perfusion pattern compared to non-DM patients, with faster in- and outflow. Furthermore, post-revascularisation, DM patients were less likely to experience clinical improvement, particularly those with CLTI. Thirdly, non-DM patients demonstrated broader and more significant improvements in perfusion parameters, underscoring reduced therapy responsiveness in DM patients. This study builds on prior research where ICG NIR fluorescence imaging has proven its potential in analysing blood flow in LEAD patients. ( 21 , 23 – 25 , 31 – 36 ) These studies displayed the ability of NIRF imaging to predict post-revascularisation treatment success in terms of clinical improvement such as wound healing or long-term limb salvage. However, few studies have focused on DM-specific outcomes. ( 21 , 34 ) Unlike previous studies, which primarily reported blood flow differences across various disease stages, this study evaluates the direct impact of revascularisation on perfusion parameters and clinical outcomes in LEAD patients with and without DM. The apparently diminished response to therapy in DM patients aligns with the pathophysiology of DM-induced (micro)vascular dysfunction, where disrupted vascular tone and open shunts result in paradoxical perfusion patterns ( 17 , 37 – 39 ). Additionally, studies comparing ankle and toe pressures between DM and non-DM patients finds the methods challenging for reliable perfusion assessment in DM due to medial arterial calcification, ulceration and toe-amputations.( 13 , 38 ) These limitations emphasize the need for alternative perfusion assessment methods, such as ICG NIR fluorescence imaging, which can provide a more precise and dynamic evaluation of tissue perfusion in DM patients. LEAD patients with DM face worse outcomes following revascularisation, with higher risks of restenosis, occlusion, and major amputation. ( 7 – 11 ) In this study, DM patients exhibited five times more crural pathology than non-DM patients, one-third of DM CLTI patients experienced poor outcomes post-revascularisation, and limited improvement in perfusion parameters was detected in all DM CLTI patients. The observed differences in perfusion response can possibly be attributed to several factors. First, DM patients frequently present with complex crural disease, leading to a higher proportion of distal revascularisations, which may yield less robust improvements in tissue perfusion. Second, wound healing is inherently multifactorial, influenced by not only ischemia but also neuropathy, inflammation, and impaired cellular repair mechanisms. Third, microvascular dysfunction in DM patients plays a critical role, as hyperglycaemia-induced endothelial damage and capillary dropout limit the efficacy of macrovascular revascularisation. ( 34 ) This is supported by the finding that DM patients without CI exhibited higher pre-revascularisation perfusion indices than those with CI, suggesting that ischemia alone does not fully explain poor outcomes, but additional factors beyond microvascular dysfunction may play a role in wound healing failure. This highlights the need for further investigation into alternative mechanisms, such as neuropathy, persistent inflammation, or local tissue factors, that may influence post-revascularization healing outcomes.( 4 , 15 ) While this study provides new insights, several limitations must be acknowledged. The retrospective nature and heterogeneous patient population introduce variability. Furthermore, the determination of clinical improvement was rather subjective, relying either on the patient's symptoms or the treating physicians assessment. Additionally, a procedural imbalance was noted, with DM patients predominantly undergoing PTA while non-DM patients more often received bypass surgery. This real-world discrepancy may have influenced outcomes, given the differences in patency and effectiveness of these procedures. Another limitation is the small size of the sub analysis groups used to evaluate clinical improvement following revascularization. Due to the limited number of patients in these subgroups, no definitive conclusions can be drawn. However, if performed in a larger cohort, these findings may provide more robust evidence regarding the relationship between perfusion changes and clinical outcomes. Despite the limitations, these findings align with the understanding that DFU formation is multifactorial and its treatment is less responsive to revascularisation. ICG NIR fluorescence imaging has proven capable of distinguishing these perfusion differences, and may therefore serve guiding treatment of CLTI patients with diabetes. Future prospective studies should focus on validating these findings in larger, cohorts with a focus on prospective risk stratification of CLTI patients Conclusion This study demonstrates the capability of ICG NIR fluorescence to map disparities in the dynamic tissue perfusion between DM and non-DM LEAD patients undergoing revascularisation. In general, ICG NIR fluorescence findings appear to correlate with postoperative outcomes, with CLTI DM patients showing reduced responsiveness to therapy. These findings may pave the way for a more personalised approaches in CLTI revascularisation. Abbreviations ABI Ankle-Brachial Index ACCmax Maximal Systolic Acceleration ADA American Diabetes Association AUC Area Under the Curve BYP Bypass (Surgery) CI Clinical Improvement CLTI Chronic Limb-Threatening Ischemia CT Computed Tomography DFU Diabetic Foot Ulcer DM Diabetes Mellitus eGFR Estimated Glomerular Filtration Rate HR Hazard Ratio ICG Indocyanine Green IWGDF International Working Group on the Diabetic Foot LED Light-Emitting Diode LEAD Lower Extremity Arterial Disease LUMC Leiden University Medical Center NIRF Near-Infrared Fluorescence PTA Percutaneous Transluminal Angioplasty ROI Region of Interest SVS Society for Vascular Surgery TBI Toe-Brachial Index TcPO₂ Transcutaneous Oxygen Pressure TEA Thrombendarteriectomy Tmax Time to Maximum Intensity TP Toe Pressure WIfI Wound, Ischemia, and foot Infection (classification system) Declarations Ethics approval and consent to participate This study (G21.087) received approval from the Medical Research and Ethics Committee of the LUMC. It was conducted in accordance with the Declaration of Helsinki and institutional guidelines. Informed consent was obtained from all enrolled patients. Consent for publication Not applicable Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests Funding This project is co-funded by the PPP Allowance made available by Health~Holland regarding the RULER and IMPULSE-project. Top Sector Life Sciences & Health, to stimulate public-private partnerships. Together with the RETINA-project receiving funding from the European Union’s Horizon Europe research and innovation program under grant agreement number 101135529. Authors' contributions Stefan Koning: Writing – original draft, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Roderick C. Peul: Writing – review & editing, Data curation. Investigation. Mo W. Kruiswijk: Writing – review & editing, Data curation, Investigation. Floris P. Tange: Writing – review & editing, Investigation, Data curation. Jan van Schaik: Writing – review & editing. Abbey Schepers: Writing – review & editing. Jeroen J.W.M. Brouwers: Writing – review & editing. Carla S.P. van Rijswijk: Writing – review & editing, data curation. Koen E.A. van der Bogt: Writing – review & editing. Jonas P. Eiberg: Writing – review & editing. Alexander L. Vahrmeijer: Writing – review & editing, Supervision, Resources. Jaap F. Hamming: Writing – review & editing, Supervision. Pim van den Hoven: Writing – review & editing, Supervision, Methodology, Conceptualization. Joost R. van der Vorst: Writing – review & editing, Supervision, Methodology, Conceptualization. Acknowledgements Not applicable References Rümenapf G, Abilmona N, Morbach S, Sigl M. 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Peul","email":"","orcid":"","institution":"Leiden University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Roderick","middleName":"C.","lastName":"Peul","suffix":""},{"id":473664686,"identity":"60b25243-983a-4a65-9f8d-51a7aada3e70","order_by":2,"name":"Mo W. Kruiswijk","email":"","orcid":"","institution":"Leiden University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Mo","middleName":"W.","lastName":"Kruiswijk","suffix":""},{"id":473664687,"identity":"38330197-2a74-4731-bc83-eda1474e3e09","order_by":3,"name":"Floris P. Tange","email":"","orcid":"","institution":"Leiden University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Floris","middleName":"P.","lastName":"Tange","suffix":""},{"id":473664688,"identity":"509cd37f-acec-475c-92d3-fb0d45e508a4","order_by":4,"name":"Jan van Schaik","email":"","orcid":"","institution":"Leiden University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Jan","middleName":"van","lastName":"Schaik","suffix":""},{"id":473664689,"identity":"a900ea25-40ca-49dc-acef-734b9eb585c0","order_by":5,"name":"Abbey Schepers","email":"","orcid":"","institution":"Leiden University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Abbey","middleName":"","lastName":"Schepers","suffix":""},{"id":473664690,"identity":"2e7ba0ca-9329-4acd-bb39-e2ce3e7a0f01","order_by":6,"name":"Jeroen J.W.M. Brouwers","email":"","orcid":"","institution":"Leiden University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Jeroen","middleName":"J.W.M.","lastName":"Brouwers","suffix":""},{"id":473664691,"identity":"6eb612c5-d3cb-4858-81f9-7d29b37e5601","order_by":7,"name":"Carla S.P. Rijswijk","email":"","orcid":"","institution":"Leiden University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Carla","middleName":"S.P.","lastName":"Rijswijk","suffix":""},{"id":473664692,"identity":"a536dbcd-df20-4fbb-9827-a1d7b5fa9c1d","order_by":8,"name":"Koen E.A. Bogt","email":"","orcid":"","institution":"Haaglanden Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Koen","middleName":"E.A.","lastName":"Bogt","suffix":""},{"id":473664693,"identity":"395e0a13-b0ee-4fb7-b4c4-0e85c22375b7","order_by":9,"name":"Jonas P. Eiberg","email":"","orcid":"","institution":"University Hospital - Rigshospitalet","correspondingAuthor":false,"prefix":"","firstName":"Jonas","middleName":"P.","lastName":"Eiberg","suffix":""},{"id":473664694,"identity":"4c9f32c9-b06c-4131-886d-485f34e687db","order_by":10,"name":"Alexander L. Vahrmeijer","email":"","orcid":"","institution":"Leiden University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"L.","lastName":"Vahrmeijer","suffix":""},{"id":473664695,"identity":"a80194f5-bb53-4fc5-a677-65fb3e619235","order_by":11,"name":"Jaap F. Hamming","email":"","orcid":"","institution":"Leiden University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Jaap","middleName":"F.","lastName":"Hamming","suffix":""},{"id":473664696,"identity":"7dd7cadf-c6e7-4a4b-9ab9-d4e7d4bf60f4","order_by":12,"name":"Pim van den Hoven","email":"","orcid":"","institution":"Leiden University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Pim","middleName":"van den","lastName":"Hoven","suffix":""},{"id":473664697,"identity":"37b310ff-4cf1-4940-9792-ce7a86a2157b","order_by":13,"name":"Joost R. van der Vorst","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYBACxgYY6wCMwd4MEeMjWgsPz0GIGBtB++BaJBLxa2Fu4H3AzFNzh4HveC+QUXHP3l7yYZvUjRqGPFxaGBvYDZh5jj1jkDxzHMg4U5zYI53YJp1zjKEYtxY2BsYZbIcZDG6kMTDObEtI4AFpyW1gSGzDq+UfUMv9Z2At9jySBwlrYfjYBrIFzEhg7JFgJKClmY3hwMe+w0C/pDEwfDiTkNhzJrHZOueYBE4thu1tjA8Svh0GhtgxBoaEigR79vbDB2/n1Ngk9uPS0gyJkfoGYLT/QJKQwKGBgUEep8woGAWjYBSMAhgAALqJUUrOh2FXAAAAAElFTkSuQmCC","orcid":"","institution":"Leiden University Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Joost","middleName":"R. van der","lastName":"Vorst","suffix":""}],"badges":[],"createdAt":"2025-06-16 12:08:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6905400/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6905400/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85389693,"identity":"eea9ac58-45ad-47e7-b1f4-f7101ccf5213","added_by":"auto","created_at":"2025-06-25 10:22:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":59855,"visible":true,"origin":"","legend":"\u003cp\u003ePercentual difference in perfusion parameter improvement in the CI-groups. In red DM and in blue non-DM. Boxplot depicted as medians with interquartile range. Whiskers display min-max range.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6905400/v1/f035fd75ce6d8f8f6bdc9006.png"},{"id":85389696,"identity":"d22100e8-961e-4e68-a4e0-6c3822e6f66f","added_by":"auto","created_at":"2025-06-25 10:22:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":55182,"visible":true,"origin":"","legend":"\u003cp\u003ePercentual difference in perfusion parameter improvement in the no-CI groups. In red DM and in blue non-DM. Boxplot depicted as medians with interquartile range. Whiskers display min-max range.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6905400/v1/1b53bdd6e3366efb498d202b.png"},{"id":86029655,"identity":"29e5d07e-59d9-4a80-a06d-4fd5fb935c00","added_by":"auto","created_at":"2025-07-04 14:01:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":817539,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6905400/v1/8c4a886b-f99e-4821-8a9e-0b71914fb917.pdf"},{"id":85389694,"identity":"3fc143cb-3964-473d-95a6-a20243ecd529","added_by":"auto","created_at":"2025-06-25 10:22:45","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":64053,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementalfigure.docx","url":"https://assets-eu.researchsquare.com/files/rs-6905400/v1/fb189cde90b9542403dd3494.docx"},{"id":85389697,"identity":"fd8a7487-6805-43c8-8c7f-0222c48eb824","added_by":"auto","created_at":"2025-06-25 10:22:45","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":28840,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-6905400/v1/495bd17b317c746b92109807.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The impact of diabetes mellitus on foot perfusion pre- and post-revascularisation measured by near-infrared fluorescence imaging","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePatients with diabetes mellitus (DM) form a heterogeneous group with a considerable but variable risk of developing diabetic complications, such as a diabetic foot ulcer (DFU), peripheral neuropathy and microvascular disease. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Additional risk factors, including infection, structural foot deformities, and impaired metabolic regulation, further influence the high risk of limb loss and mortality in these patients. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Patients with combined lower extremity arterial disease (LEAD) and DM are disproportionately affected by critical limb-threatening ischaemia (CLTI), the most severe form of LEAD. Up to 25% of individuals with DM will develop a DFU during their lifetime, often associated with CLTI. CLTI in DM patients carries a 14\u0026ndash;24% risk of major amputation and a five-year post-amputation mortality rate increasing 50%. (\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eRevascularisation remains the cornerstone of CLTI treatment, aiming to improve blood flow, promote ulcer healing, and prevent limb loss. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) However, DM patients face disproportionately worse outcomes compared to non-DM patients, including higher rates of restenosis (HR 1.73), total occlusion (HR 1.74), major amputation (HR 1.5-4), and mortality (HR 1.2-2). (\u003cspan additionalcitationids=\"CR8 CR9 CR10\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe Society for Vascular Surgery\u0026rsquo;s WIfI classification system, is commonly used to guide treatment and predict outcomes in CLTI patients. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) The WIfI system incorporates parameters for wound severity, ischaemia, and foot infection. However, the perfusion assessment, typically measured by ankle-brachial index (ABI), toe pressure (TP), toe-brachial index (TBI), or transcutaneous oxygen pressure (TcPO₂), is often unreliable in DM patients. For instance, to predict LEAD, ABI has a sensitivity of only 35%, TP 82%, and TcPO₂ 72%. (\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) TBI, in particular, has a limited specificity of 66%.(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) These metrics fail to adequately account for the diabetic vascular dysfunction and impaired tissue perfusion pre- and postoperative, and may explain the inferior outcomes observed in DM patients following revascularisation. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) Understanding the differences in outcomes following revascularisation between DM and non-DM patients is important, as variations in foot perfusion may partly explain these differences.(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eNear-infrared (NIR) fluorescence imaging with indocyanine green (ICG) enables real-time, quantitative perfusion assessment, unaffected by arterial calcification or neuropathy, making it ideal for DM patients. It detects microvascular differences between DM and non-DM patients, offering insights into DM-related foot complications.(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) Moreover, ICG-based assessments can potentially improve clinical decision-making and postoperative outcomes by guiding individualised treatment strategies. (\u003cspan additionalcitationids=\"CR22 CR23 CR24\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThis study aims to examine perfusion changes before and after revascularisation in LEAD patients with and without DM using ICG NIR fluorescence imaging and explore the relationship between these perfusion parameters and clinical outcomes.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Patients\u003c/h2\u003e \u003cp\u003eThis retrospective cohort study included all LEAD patients treated at the Leiden University Medical Center (LUMC) between July 2019 and August 2024 who underwent a technically successful revascularization. The presence and severity of LEAD was diagnosed by the treating physician based on clinical presentation, maximal systolic acceleration (ACCmax), duplex ultrasound, and CT angiography.(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) Patients with DM were defined as individuals with a clinical diagnosis of either type 1 or type 2 diabetes, according to the American Diabetes Association (ADA) criteria. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) In cases of bilateral treatment, data from both feet were included.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Measurements\u003c/h2\u003e \u003cp\u003ePerfusion parameters were assessed to compare the DM and non-DM groups before and after revascularization. Additionally, patients were stratified according to the Fontaine classification, as recommended by the European Society for Vascular Surgery, to account for different stages of vascular disease.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) In patients with CLTI (Fontaine stage 3 and 4), further distinction was made between those with and without clinical improvement (CI). Only CLTI patients were included in this analyses, being the highest risk group with the most severe (diabetic) vascular damage. CI was defined by the treating physician as a resolution of rest or nocturnal pain, improvement of walking distance, or noticeable progress in wound or ulcer healing. ICG NIR fluorescence imaging was performed following a predefined protocol.(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) Trained personnel conducted ICG NIR measurements pre- and post-revascularization, initially within the study framework and later as part of routine clinical practice.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Measurement setup\u003c/h2\u003e \u003cp\u003ePre- and post-revascularisation, all patients received a bolus of 0.1 mg/kg of ICG (Verdye 25mg, Diagnostic Green HmbH) through the IV placed in the cubital vein. A 5-minute ICG NIR recording was made utilising the Quest Spectrum Platform\u0026reg; (Quest Medical Imaging, Wieringerwerf, The Netherlands) positioning it at 50cm perpendicular to the dorsum of the foot. This imaging system is equipped with a dual light source comprising an LED for visible light and a NIR source operating within the 700\u0026ndash;820 nm wavelength range.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Quantification\u003c/h2\u003e \u003cp\u003eThe Quest Research Framework\u0026reg; (Quest Medical Imaging, Wieringerwerf, the Netherlands) software was used to post-operatively quantify the NIR fluorescence signals. This application measures the ICG signal within a designated region of interest (ROI) and produces time-intensity curves. The entire dorsum of the foot was selected as a ROI. \u003cb\u003eSupplemental Fig.\u0026nbsp;1\u003c/b\u003e displays a time-intensity curve depicting the in- and outflow of the ICG signal generated by the software. These curves provide extractable perfusion parameters, of which three time-related and normalised parameters were analysed.(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) The 3 time-related parameters used in this study included the time till maximum intensity (Tmax), the normalized maximum ingress slope (norm max ingress slope), and the area under the curve 180 seconds after Tmax (Egress-180). Extraction of the perfusion parameters was performed for all measurements pre- and post-revascularisation. In this study, the dorsum of the interventional foot was selected as the ROI. The software's integrated motion tracker corrected for movement during the ICG NIR fluorescence measurements. All parameters except the normalized maximum ingress slope were extracted from the absolute curves.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical analyses\u003c/h2\u003e \u003cp\u003eThe Wilcoxon signed-rank test was utilised to analyse pre- and post-revascularisation parameter differences within the DM and non-DM groups. Normality was assessed using the Kolmogorov-Smirnov-test. Parameters with non-normal distributions necessitated the utilisation of medians instead of means. A chi-square test was performed to analyse the difference in CI between the DM and non-DM CLTI groups. IBM SPSS Statistics 25 (IBM Corp., 2017) was used for statistical analyses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Ethical considerations\u003c/h2\u003e \u003cp\u003eThis study (G21.087) received approval from the Medical Research and Ethics Committee of the LUMC. It was conducted in accordance with the Declaration of Helsinki and institutional guidelines. Informed consent was obtained from all enrolled patients.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003e3.1 Patient characteristics\u003c/h2\u003e\n \u003cp\u003eSuccessful ICG NIR measurements were performed in 128 LEAD patients (144 limbs) of which 42 patients (48 limbs) suffered from DM. Table 1 provides a complete description of the study population. The group consisted of 49 women, whereof 12 had DM. No significant difference was observed in Fontaine classification between the DM and non-DM group (p\u0026thinsp;=\u0026thinsp;0.639). Revascularisation levels varied significantly between groups (p\u0026thinsp;=\u0026thinsp;0.019), with DM patients more frequently undergoing crural (16,6% vs 3,2%) and aortoiliac (39,6% vs 30,2%) procedures, while non-DM patients had a higher incidence of femoral-popliteal revascularisations (66,6% vs 43,8%). Revascularisation type displayed a significant difference as well, predominantly performing percutaneous transluminal angioplasty (PTA) in DM patients (72,9% vs 59,4%) and bypass surgery in non-DM patients (20,8% vs 8,3%).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003e3.2 Outcomes Pre- versus Post-revascularisation\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cdiv align=\"left\"\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e displays the extracted pre- and post-revascularisation parameters of all LEAD patients categorised by DM. Pre-revascularisation, all parameters in the DM group showed a faster in- and outflow compared to the non-DM group. Post-revascularisation, all parameters in both groups improved in value. All parameters improved significantly in the non-DM group (p-values \u0026lt;0.001) compared to 2 out of 3 in the DM group (p-values between 0.03 - \u0026lt;.001). Egress-180 was found to be insignificantly improved (∆ %=4,4, p=0.104). When comparing the revascularisation effect (∆%) between the groups, a consistently larger improvement is observed in all parameters of the non-DM group.\u0026nbsp;\u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003e3.3 Clinical improvement\u003c/h2\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e outlines the perfusion parameters for the CI groups. Post-revascularisation, 14 out of 23 DM patients with CLTI demonstrated CI. In the non-DM CLTI group, 32 out of 37 patients showed CI (66% vs 86%, p=0.073). The mean follow-up time was 36,43\u0026plusmn;20,14 days.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNone of the parameters significantly improved in the DM CLTI CI group (p values between 0.433\u0026ndash;0.056), whereas 3 out of 3 parameters significantly improved in the non-DM CLTI CI group (p-values ranging from 0.003 to \u0026lt;\u0026thinsp;0.001). Table 4 presents the no-CI data of both the DM and non-DM group. In the DM CLTI no-CI group, none of the parameters showed significant improvement. Conversely, 2 out of 3 parameters displayed higher post-revascularisation values. In contrast, none of the parameters in the non-DM CLTI no-CI group showed significant improvement, with all parameters demonstrating a post-revascularisation signal decrease. Figure 1 displays the percentual difference in perfusion values between the DM and non-DM CI groups, whereas Fig. 2 displays this for the no-CI groups.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study demonstrated significant differences in foot perfusion following revascularisation in LEAD patients with DM compared to non-DM patients. Pre-revascularisation, DM patients exhibited a different perfusion pattern compared to non-DM patients, with faster in- and outflow. Furthermore, post-revascularisation, DM patients were less likely to experience clinical improvement, particularly those with CLTI. Thirdly, non-DM patients demonstrated broader and more significant improvements in perfusion parameters, underscoring reduced therapy responsiveness in DM patients.\u003c/p\u003e \u003cp\u003eThis study builds on prior research where ICG NIR fluorescence imaging has proven its potential in analysing blood flow in LEAD patients. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e–\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan additionalcitationids=\"CR32 CR33 CR34 CR35\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e–\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) These studies displayed the ability of NIRF imaging to predict post-revascularisation treatment success in terms of clinical improvement such as wound healing or long-term limb salvage. However, few studies have focused on DM-specific outcomes. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) Unlike previous studies, which primarily reported blood flow differences across various disease stages, this study evaluates the direct impact of revascularisation on perfusion parameters and clinical outcomes in LEAD patients with and without DM. The apparently diminished response to therapy in DM patients aligns with the pathophysiology of DM-induced (micro)vascular dysfunction, where disrupted vascular tone and open shunts result in paradoxical perfusion patterns (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e–\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Additionally, studies comparing ankle and toe pressures between DM and non-DM patients finds the methods challenging for reliable perfusion assessment in DM due to medial arterial calcification, ulceration and toe-amputations.(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) These limitations emphasize the need for alternative perfusion assessment methods, such as ICG NIR fluorescence imaging, which can provide a more precise and dynamic evaluation of tissue perfusion in DM patients.\u003c/p\u003e \u003cp\u003eLEAD patients with DM face worse outcomes following revascularisation, with higher risks of restenosis, occlusion, and major amputation. (\u003cspan additionalcitationids=\"CR8 CR9 CR10\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e–\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) In this study, DM patients exhibited five times more crural pathology than non-DM patients, one-third of DM CLTI patients experienced poor outcomes post-revascularisation, and limited improvement in perfusion parameters was detected in all DM CLTI patients. The observed differences in perfusion response can possibly be attributed to several factors. First, DM patients frequently present with complex crural disease, leading to a higher proportion of distal revascularisations, which may yield less robust improvements in tissue perfusion. Second, wound healing is inherently multifactorial, influenced by not only ischemia but also neuropathy, inflammation, and impaired cellular repair mechanisms. Third, microvascular dysfunction in DM patients plays a critical role, as hyperglycaemia-induced endothelial damage and capillary dropout limit the efficacy of macrovascular revascularisation. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) This is supported by the finding that DM patients without CI exhibited higher pre-revascularisation perfusion indices than those with CI, suggesting that ischemia alone does not fully explain poor outcomes, but additional factors beyond microvascular dysfunction may play a role in wound healing failure. This highlights the need for further investigation into alternative mechanisms, such as neuropathy, persistent inflammation, or local tissue factors, that may influence post-revascularization healing outcomes.(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eWhile this study provides new insights, several limitations must be acknowledged. The retrospective nature and heterogeneous patient population introduce variability. Furthermore, the determination of clinical improvement was rather subjective, relying either on the patient's symptoms or the treating physicians assessment. Additionally, a procedural imbalance was noted, with DM patients predominantly undergoing PTA while non-DM patients more often received bypass surgery. This real-world discrepancy may have influenced outcomes, given the differences in patency and effectiveness of these procedures. Another limitation is the small size of the sub analysis groups used to evaluate clinical improvement following revascularization. Due to the limited number of patients in these subgroups, no definitive conclusions can be drawn. However, if performed in a larger cohort, these findings may provide more robust evidence regarding the relationship between perfusion changes and clinical outcomes.\u003c/p\u003e \u003cp\u003eDespite the limitations, these findings align with the understanding that DFU formation is multifactorial and its treatment is less responsive to revascularisation. ICG NIR fluorescence imaging has proven capable of distinguishing these perfusion differences, and may therefore serve guiding treatment of CLTI patients with diabetes. Future prospective studies should focus on validating these findings in larger, cohorts with a focus on prospective risk stratification of CLTI patients\u003c/p\u003e "},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates the capability of ICG NIR fluorescence to map disparities in the dynamic tissue perfusion between DM and non-DM LEAD patients undergoing revascularisation. In general, ICG NIR fluorescence findings appear to correlate with postoperative outcomes, with CLTI DM patients showing reduced responsiveness to therapy. These findings may pave the way for a more personalised approaches in CLTI revascularisation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eABI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAnkle-Brachial Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eACCmax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMaximal Systolic Acceleration\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eADA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAmerican Diabetes Association\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eArea Under the Curve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBYP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eBypass (Surgery)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eClinical Improvement\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCLTI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eChronic Limb-Threatening Ischemia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eComputed Tomography\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDFU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDiabetic Foot Ulcer\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDiabetes Mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eeGFR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEstimated Glomerular Filtration Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHazard Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eICG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eIndocyanine Green\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eIWGDF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInternational Working Group on the Diabetic Foot\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLED\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLight-Emitting Diode\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLEAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLower Extremity Arterial Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLUMC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLeiden University Medical Center\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNIRF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNear-Infrared Fluorescence\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePercutaneous Transluminal Angioplasty\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eROI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRegion of Interest\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSVS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSociety for Vascular Surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTBI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eToe-Brachial Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTcPO₂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTranscutaneous Oxygen Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eThrombendarteriectomy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTmax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTime to Maximum Intensity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eToe Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWIfI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eWound, Ischemia, and foot Infection (classification system)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study (G21.087) received approval from the Medical Research and Ethics Committee of the LUMC. It was conducted in accordance with the Declaration of Helsinki and institutional guidelines. Informed consent was obtained from all enrolled patients.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis project is co-funded by the PPP Allowance made available by Health~Holland regarding the RULER and IMPULSE-project. Top Sector Life Sciences \u0026amp; Health, to stimulate public-private partnerships. Together with the RETINA-project receiving funding from the European Union\u0026rsquo;s Horizon Europe research and innovation program under grant agreement number 101135529.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors\u0026apos; contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStefan Koning:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; original draft, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.\u003cstrong\u003e\u0026nbsp;Roderick C. Peul:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, Data curation. Investigation. \u003cstrong\u003eMo W. Kruiswijk:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, Data curation, Investigation. \u003cstrong\u003eFloris P. Tange:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, Investigation, Data curation. \u003cstrong\u003eJan van Schaik:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing. \u003cstrong\u003eAbbey Schepers:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing. \u003cstrong\u003eJeroen J.W.M. Brouwers:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing.\u003cstrong\u003e\u0026nbsp;Carla S.P. van Rijswijk:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, data curation.\u003cstrong\u003e\u0026nbsp;Koen E.A. van der Bogt:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing. \u003cstrong\u003eJonas P. Eiberg:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing. \u003cstrong\u003eAlexander L. Vahrmeijer:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, Supervision, Resources. \u003cstrong\u003eJaap F. Hamming:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, Supervision. \u003cstrong\u003ePim van den Hoven:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, Supervision, Methodology, Conceptualization. \u003cstrong\u003eJoost R. van der Vorst:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, Supervision, Methodology, Conceptualization.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eR\u0026uuml;menapf G, Abilmona N, Morbach S, Sigl M. Peripheral Arterial Disease and the Diabetic Foot Syndrome: Neuropathy Makes the Difference! A Narrative Review. Journal of Clinical Medicine. 2024;13(7):2141.\u003c/li\u003e\n\u003cli\u003eMcDermott K, Fang M, Boulton AJM, Selvin E, Hicks CW. Etiology, Epidemiology, and Disparities in the Burden of Diabetic Foot Ulcers. Diabetes Care. 2022;46(1):209-21.\u003c/li\u003e\n\u003cli\u003eSch\u0026ouml;nborn M, Gregorczyk-Maga I, Batko K, Maga M, Bogucka K, Gawlik K, et al. Angiogenic and Microvascular Status Alterations after Endovascular Revascularization of Lower Limb Arteries among Patients with Diabetic Foot Syndrome: A Prospective 12-Month Follow-Up Study. J Clin Med. 2023;12(17).\u003c/li\u003e\n\u003cli\u003eBurgess JL, Wyant WA, Abdo Abujamra B, Kirsner RS, Jozic I. Diabetic Wound-Healing Science. Medicina (Kaunas). 2021;57(10).\u003c/li\u003e\n\u003cli\u003eFitridge R, Chuter V, Mills J, Hinchliffe R, Azuma N, Behrendt C-A, et al. The intersocietal IWGDF, ESVS, SVS guidelines on peripheral artery disease in people with diabetes and a foot ulcer. 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J Vasc Surg. 2016;63(2 Suppl):29S-36S.e1-2.\u003c/li\u003e\n\u003cli\u003eNormahani P, Mustafa C, Shalhoub J, Davies AH, Norrie J, Sounderajah V, et al. A systematic review and meta-analysis of the diagnostic accuracy of point-of-care tests used to establish the presence of peripheral arterial disease in people with diabetes. J Vasc Surg. 2021;73(5):1811-20.\u003c/li\u003e\n\u003cli\u003eWilliams DT, Pugh ND, Coleman DP, Harding KG, Price P. Review: The laboratory evaluation of lower limb perfusion in diabetes mellitus. A clinical review. The British Journal of Diabetes \u0026amp; Vascular Disease. 2005;5(2):64-70.\u003c/li\u003e\n\u003cli\u003eFejfarov\u0026aacute; V, Matu\u0026scaron;ka J, Jude E, Piťhov\u0026aacute; P, Flekač M, Roztočil K, et al. Stimulation TcPO2 Testing Improves Diagnosis of Peripheral Arterial Disease in Patients With Diabetic Foot. Front Endocrinol (Lausanne). 2021;12:744195.\u003c/li\u003e\n\u003cli\u003eFitridge R, Pena G, Mills JL. The patient presenting with chronic limb-threatening ischaemia. Does diabetes influence presentation, limb outcomes and survival? Diabetes Metab Res Rev. 2020;36 Suppl 1:e3242.\u003c/li\u003e\n\u003cli\u003eJ\u0026ouml;rneskog G. Why Critical Limb Ischemia Criteria are Not Applicable to Diabetic Foot and What the Consequences are. Scandinavian Journal of Surgery. 2012;101(2):114-8.\u003c/li\u003e\n\u003cli\u003eKoning S, van Kersen J, Tange FP, Kruiswijk MW, Peul RC, van Schaik J, et al. The impact of diabetes mellitus on foot perfusion measured by ICG NIR fluorescence imaging. Diabetes Res Clin Pract. 2024;214:111772.\u003c/li\u003e\n\u003cli\u003eTange FP, Verduijn PS, Sibinga Mulder BG, van Capelle L, Koning S, Driessen C, et al. Near-infrared fluorescence angiography with indocyanine green for perfusion assessment of DIEP and msTRAM flaps: A Dutch multicenter randomized controlled trial. Contemp Clin Trials Commun. 2023;33:101128.\u003c/li\u003e\n\u003cli\u003eVan den Hoven P, S Weller F, Van De Bent M, Goncalves LN, Ruig M, D Van Den Berg S, et al. Near-infrared fluorescence imaging with indocyanine green for quantification of changes in tissue perfusion following revascularization. Vascular. 2022;30(5):867-73.\u003c/li\u003e\n\u003cli\u003eTange FP, van den Hoven P, van Schaik J, Schepers A, van der Bogt KEA, van Rijswijk CSP, et al. Near-Infrared Fluorescence Imaging With Indocyanine Green to Predict Clinical Outcome After Revascularization in Lower Extremity Arterial Disease. Angiology. 2023:33197231186096.\u003c/li\u003e\n\u003cli\u003eIgari K, Kudo T, Toyofuku T, Jibiki M, Inoue Y, Kawano T. Quantitative evaluation of the outcomes of revascularization procedures for peripheral arterial disease using indocyanine green angiography. Eur J Vasc Endovasc Surg. 2013;46(4):460-5.\u003c/li\u003e\n\u003cli\u003eBrouwers JJWM, van Doorn LP, Pronk L, van Wissen RC, Putter H, Schepers A, et al. Doppler Ultrasonography Derived Maximal Systolic Acceleration: Value Determination With Artificially Induced Stenosis. Vascular and Endovascular Surgery. 2022;56(5):472-9.\u003c/li\u003e\n\u003cli\u003eWillems SA, Dolfing SG, van Wissen RC, van der Vorst JR, van Schaik J, Schepers A, et al. Diagnostic accuracy of the maximal systolic acceleration to detect peripheral arterial disease. J Vasc Surg. 2024;79(2):405-11.\u003c/li\u003e\n\u003cli\u003eCommittee ADAPP. 2. Diagnosis and Classification of Diabetes: Standards of Care in Diabetes\u0026mdash;2025. Diabetes Care. 2024;48(Supplement_1):S27-S49.\u003c/li\u003e\n\u003cli\u003eIgari K, Kudo T, Uchiyama H, Toyofuku T, Inoue Y. Indocyanine green angiography for the diagnosis of peripheral arterial disease with isolated infrapopliteal lesions. Ann Vasc Surg. 2014;28(6):1479-84.\u003c/li\u003e\n\u003cli\u003eVan Den Hoven P, Tange F, Van Der Valk J, Nerup N, Putter H, Van Rijswijk C, et al. Normalization of Time-Intensity Curves for Quantification of Foot Perfusion Using Near-Infrared Fluorescence Imaging With Indocyanine Green. J Endovasc Ther. 2023;30(3):364-71.\u003c/li\u003e\n\u003cli\u003eBraun JD, Trinidad-Hernandez M, Perry D, Armstrong DG, Mills JL, Sr. Early quantitative evaluation of indocyanine green angiography in patients with critical limb ischemia. J Vasc Surg. 2013;57(5):1213-8.\u003c/li\u003e\n\u003cli\u003eColvard B, Itoga NK, Hitchner E, Sun Q, Long B, Lee G, et al. SPY technology as an adjunctive measure for lower extremity perfusion. J Vasc Surg. 2016;64(1):195-201.\u003c/li\u003e\n\u003cli\u003eSettembre N, Kauhanen P, Alb\u0026auml;ck A, Spillerova K, Venermo M. Quality Control of the Foot Revascularization Using Indocyanine Green Fluorescence Imaging. World J Surg. 2017;41(7):1919-26.\u003c/li\u003e\n\u003cli\u003eAn Y, Kang Y, Lee J, Ahn C, Kwon K, Choi C. Blood flow characteristics of diabetic patients with complications detected by optical measurement. Biomed Eng Online. 2018;17(1):25.\u003c/li\u003e\n\u003cli\u003eRie\u0026szlig; HC, Dupr\u0026eacute;e A, Behrendt CA, K\u0026ouml;lbel T, Debus ES, Larena-Avellaneda A, et al. Initial experience with a new quantitative assessment tool for fluorescent imaging in peripheral artery disease. Vasa. 2017;46(5):383-8.\u003c/li\u003e\n\u003cli\u003evan den Hoven P, Ooms S, van Manen L, van der Bogt KEA, van Schaik J, Hamming JF, et al. A systematic review of the use of near-infrared fluorescence imaging in patients with peripheral artery disease. J Vasc Surg. 2019;70(1):286-97.e1.\u003c/li\u003e\n\u003cli\u003eFowler MJ. Microvascular and Macrovascular Complications of Diabetes. Clinical Diabetes. 2008;26(2):77-82.\u003c/li\u003e\n\u003cli\u003eWilliams DT, Harding KG, Price P. An evaluation of the efficacy of methods used in screening for lower-limb arterial disease in diabetes. Diabetes Care. 2005;28(9):2206-10.\u003c/li\u003e\n\u003cli\u003eFlynn MD, Tooke JE. Diabetic neuropathy and the microcirculation. Diabet Med. 1995;12(4):298-301.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables are available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","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":"Diabetes, Lower extremity arterial disease, Perfusion, NIRF-imaging, Indocyanine green, Revascularisation, Clinical outcome","lastPublishedDoi":"10.21203/rs.3.rs-6905400/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6905400/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eDiabetes Mellitus (DM) contributes to the complexity of lower extremity arterial disease (LEAD), inducing peripheral neuropathy and increasing susceptibility to severe ischemia, foot ulceration, and amputation. Perfusion differences in LEAD patients with and without DM may advocate a more individualised revascularisation strategy than the current WIfI classification for risk prediction. This study aims to utilise near-infrared (NIR) fluorescence imaging with Indocyanine Green (ICG) to assess perfusion parameters before and after revascularisation in DM and non-DM patients and explore their relationship with clinical outcome.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eICG NIR fluorescence imaging was performed pre- and post-revascularisation in LEAD patients with and without DM. Three time-related perfusion parameters were analysed to assess differences in perfusion patterns. Clinical improvement (CI) after revascularisation was analysed in chronic limb-threatening ischemia (CLTI) patients with- and without DM.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSuccessful revascularisation and ICG NIR fluorescence measurements were conducted in 128 patients (144 limbs), with 42 (48 limbs) DM patients. Two out of three revascularisation parameters post-operatively improved significantly in the DM group, compared to three out of three in the non-DM group. Additionally, in the sub-analyses of the CLTI group, no parameters in the DM CI group showed significant enhancement, compared to significant improvements in all parameters in the non-DM CI group (p\u0026thinsp;=\u0026thinsp;0.003 - \u0026lt;0.001). A trend towards a lower likelihood of CI was observed in DM CLTI patients, though not statistically significant (86% vs 66%, p\u0026thinsp;=\u0026thinsp;0.073).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study demonstrates the capability of ICG NIR fluorescence to map disparities in the dynamic tissue perfusion between DM and non-DM LEAD patients undergoing revascularisation. In general, ICG NIR fluorescence findings appear to correlate with postoperative outcomes, with CLTI DM patients showing reduced responsiveness to therapy. These findings may pave the way for a more personalised approaches in CLTI revascularisation.\u003c/p\u003e","manuscriptTitle":"The impact of diabetes mellitus on foot perfusion pre- and post-revascularisation measured by near-infrared fluorescence imaging","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-25 10:22:40","doi":"10.21203/rs.3.rs-6905400/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":"d5febd76-7fa6-4e87-a759-c7a98a78e491","owner":[],"postedDate":"June 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-04T13:53:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-25 10:22:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6905400","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6905400","identity":"rs-6905400","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}