Contrast-Free Functional MRI for Assessing Renal Involvement in Patients with ANCA-associated Vasculitis

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Current diagnostic standards, such as the measurement of serum creatinine, renal biopsy and urinary analyses have limitations due to delayed detection and lack of speficity. Functional renal MRI techniques (mpMRI), including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), arterial spin labeling (ASL) and blood oxygenation level dependent (BOLD) offer promising non-invasive alternatives for assessing renal function in AAV. Methods This study evaluated 7 patients and 10 healthy controls: patients with rapidly progressive glomerulonephritis (RPGN) due to AAV (n = 3), AAV patients without clinical signs of renal involvement (n = 4), and healthy controls (n = 10). All participants underwent renal mpMRI. Key parameters, including the apparent diffusion coefficient (ADC), fractional anisotropy (FA), and ASL-based renal perfusion and T2* parameter maps, were acquired and analyzed. Results The following differences in renal imaging parameters were observed between RPGN patients and healthy controls: RPGN patients showed reduced ADC values in the renal medulla and increased FA values compared to controls. Additionally, ASL values in the renal cortex were lower in RPGN patients. T2* values were lower in RPGN patients compared to the healthy control group in the cortex. Patients with AAV without confirmed renal involvement also showed alterations in ADC, T2* and FA values compared to healthy controls. Conclusion Our findings indicate that functional MRI parameter might detect renal alterations in AAV that precede clinical changes. Therefore, mpMRI might offer novel opportunities for non-invasive detection of disease-associated changes. vasculitis AAV fMRI kidney Figures Figure 1 Figure 2 Introduction/Background ANCA-associated vasculitis (AAV) is a group of rare, life-threatening autoimmune disorders characterized by necrotizing inflammation of small to medium blood vessels and the presence of anti-neutrophil cytoplasmic antibodies (ANCA) ( 1 ). The three principal subtypes are granulomatosis with polyangiitis (GPA), microscopic polyangiitis (MPA), and eosinophilic granulomatosis with polyangiitis (EGPA), each distinguished by clinical features such as granulomatous inflammation in GPA and eosinophil infiltration in EGPA ( 2 ). ANCAs against proteinase 3 (PR3-ANCA) are most commonly found in GPA, while myeloperoxidase ANCAs (MPO-ANCA) predominate in MPA and EGPA. Vasculitis encompass a range of complex illnesses that can affect any organ system, posing significant diagnostic and management challenges due to overlapping and varying symptoms. Vasculitis can also manifest as single-organ vasculitis (SOV), characterized by inflammation of blood vessels within a single organ, such as the kidney ( 1 ). In rare cases, with an incidence of 7 per 1,000,000, AAV can result in rapidly progressive glomerulonephritis (RPGN) ( 3 ). Typically, renal involvement becomes symptomatic through acute kidney injury with proteinuria and erythrocyturia. The gold standard to confirm a renal involvement remains the invasive renal biopsy ( 4 ). Given the risks associated with biopsy ( 5 ), an alternative method for diagnosing renal involvement in vasculitis is essential. Non-invasive functional MRI presents a promising option. Functional renal MRI have shown its potential to reflect renal involvement in different pathological conditions as diabetic kidney disease (DKD) and chronic kidney disease (CKD). The apparent diffusion coefficient (ADC) measures restricted water molecule motion in renal tissue, influenced by structural features like cell membranes and the interstitial matrix ( 6 ). Reduced eGFR and fibrosis in chronic renal dysfunction hinder water diffusion, leading to lower ADC values. Several studies have shown a positive correlation between ADC and GFR ( 7 ). To characterize tissue microarchitecture by quantifying anisotropy and spatial diffusion dependence, diffusion encoding in multiple directions is required. This is achieved with diffusion tensor imaging (DTI), which necessitates at least six distinct signal encoding directions. DTI enables the calculation of FA, reflecting tissue anisotropy ( 7 ). Studies have already demonstrated that FA alterations are possible in kidney diseases. Liu et al. reported that DTI is valuable for the noninvasive assessment of renal function and pathology in patients with CKD. A decrease in FA was associated with glomerular lesions, tubulointerstitial injuries, and eGFR decline ( 8 ). Approximately 25% of cardiac output circulates through the kidneys, making renal perfusion essential for nutrient and oxygen supply as well as glomerular filtration. Renal ischemia plays a critical role in acute kidney injury (AKI) and accelerates CKD progression ( 9 ). Early assessment of renal perfusion is crucial for predicting, slowing, or preventing further deterioration. Arterial spin labeling (ASL) is a non-invasive MRI technique that uses magnetically labeled arterial blood protons as an endogenous tracer to assess tissue perfusion without exogenous contrast agents ( 10 ). Many studies report reproducibility of renal perfusion by ASL and lower ASL values in CKD patients compared with healthy subjects, which correlates with eGFR ( 11 ). Blood oxygenation level dependent (BOLD) MRI utilizes changes in blood oxygenation to create contrast, as oxygen saturation alters the magnetic properties of hemoglobin (Hb). Fully oxygenated Hb is diamagnetic, while deoxygenated Hb is paramagnetic, affecting the transverse decay time (T2*) or the rate constant (R2*). Studies have also shown that R2* values are positively correlated with kidney function and inversely correlated with the eGFR ( 12 ). Also recent studies have reported that the evaluation of oxygenation in renal cortex by BOLD-MRI can predict the progression of renal function ( 13 ). This study aimed to evaluate the extent to which functional MRI parameters reflect renal parenchymal damage in patients with AAV with known rapid progressive glomerulonephritis (RPGN). Additionally, it investigated whether alterations in these parameters are detectable in patients without clinical manifestation of a renal involvement. Methods Study population The study was approved by the local ethics committee, and written informed consent was obtained from all study participants. Ten healthy volunteers (group 1) (mean age 63.2 ± 6,9 years; 6 women and 4 men) without any history of kidney disease, diabetes, vascular disease, previous renal surgery or any known systemic disease potentially involving the kidneys participated in the study. Furthermore, sevens patients (mean age 63,8 ± 11 years; 5 women and 2 men) were included in the study to assess the potential clinical relevance of functional renal MRI (Table 1 ). The group of patients included patients with biopsy proven rapidly progressive glomerulonephritis associated with vasculitis (group 2) (n = 3) and patients with diagnosed vasculitis without confirmed renal involvement (group 3) (n = 4). Table 1 Summary of Vasculitis Patients: Demographics and Clinical Parameters. Group Age (years) Sex AAV Subtype Proteinurie (mg/g) Hematuria (cells/µl) RPGN due to AAV 42 Female MPA 839 1204 62 Male GPA none none 81 Female GPA 798 1098 Vasculitis without clinical signs of renal involvement 65 Male EGPA none 15 59 Female EGPA none 48 61 Female GPA none 12 60 Female MPA 225 26 MR Imaging Multiparametric, functional MRI measurements were performed on a clinical 3T MRI scanner (Magnetom Prisma, Siemens AG, Healthineers, Erlangen, Germany) without the use of contrasting agents. Functional renal sequences were performed according to consensus-based recommendations for functional renal imaging by PARENCHIMA project ( 14 ). For each patient, MRI acquisition began with a T2-weighted HASTE (Half-Fourier Acquisition Single-Shot Turbo Spin-Echo) sequence, providing an anatomical overview of the kidneys. This was followed by diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) using a coronal echo-planar imaging (EPI) sequence. These techniques allowed for the assessment of water diffusion in renal tissue, enabling the calculation of the apparent diffusion coefficient (ADC) and fractional anisotropy (FA). The EPI sequence was acquired with 15 slices of 5 mm thickness, a field of view (FOV) of 400 × 400 mm, and TR/TE of 3000/78 ms, using b-values of 0, 50, 400, 800 s/mm² with 6 diffusion encoding directions. DWI data acquisition adhered to the recommendations outlined by Ljimani et al. ( 15 ). Renal perfusion was assessed using arterial spin labeling (ASL) with a paracoronal FAIR-TrueFISP sequence, employing the SSFSE technique with TR/TE of 5/2.5 ms, an inversion time (TI) of 1.2 ms, a slice thickness of 8 mm, and an FOV of 400 × 400 mm ( 10 ). Renal oxygenation was evaluated using blood oxygenation level-dependent (BOLD) MRI with a coronal T2*-weighted multi-echo gradient-echo (GRE) sequence. The sequence included 12–16 echoes, TR/TE ranging from 65 ms to 11.1–53.1 ms, and a flip angle of 40°. Images were acquired with a slice thickness of 5 mm, three slices with a 1 mm gap, a matrix of 256 × 256, and an FOV of 396 × 399 mm ( 14 ). Image and statistical analysis ROI (Region of Interest) based analysis were performed using the clinic's PACS (Picture Archiving and Communication System) for each acquired sequence. ROIs were drawn with a surface area of 40–70 mm², ensuring comparability, with one ROI placed in the cortex and medulla of each kidney. Due to the low number of patients included in this study, statistical analysis was only performed for healthy control compared to all patients and not individual patient groups. Analyses were performed using Wilcoxon-Mann-Whitney u-test. Furthermore, results of different patient groups were presented descriptively to illustrate observable differences between the groups. Results 1. Comparison of all patients with AAV and the healthy control group Figure 1 shows multiparametric renal MRI data comparing patients with ANCA-associated vasculitis (AAV) and healthy controls. Across the AAV cohort, changes were observed in diffusion (ADC), microstructural integrity (FA), perfusion (ASL), and tissue oxygenation (T2*). Figure 2 illustrates representative coronal renal MRI images and corresponding parametric maps for the different quantitative MRI techniques. ADC values were lower and FA values higher in AAV patients, particularly in the medulla, suggesting altered tissue architecture. Cortical perfusion was reduced, and T2* times were markedly shorter in both cortex and medulla, indicating impaired oxygenation. These findings highlight subclinical renal involvement in AAV, detectable by functional MRI even in the absence of overt RPGN. Table 2 summarizes the quantitative MRI parameters in healthy controls and AAV patients, stratified by renal cortex and medulla, including group sizes, mean values, standard deviations, and statistical significance. Parameter Region p-value Significance N Healthy N Disease Mean Healthy Mean Disease SD Healthy SD Disease ADC (10 ⁻6 mm 2 /s) Cortex 0.014 * 10 7 1980.9 1872.857 77.449 68.722 ADC (10 ⁻6 mm 2 /s) Medulla 0.019 * 10 7 1982.1 1733.286 101.259 213.564 ASL (ml/100g/s) Cortex 0.230 ns 10 7 285.5 235.500 58.464 62.794 ASL (ml/100g/s) Medulla 0.261 ns 10 7 306.7 332.357 75.013 88.103 FA (a.u.) Cortex 0.669 ns 10 7 0.21 0.199 0.032 0.035 FA (a.u.) Medulla 0.010 ** 10 7 0.21 0.291 0.027 0.071 T2* (ms) Cortex 0.001 *** 10 7 58 39.714 3.256 12.898 T2* (ms) Medulla 0.045 * 10 7 24.8 37.214 5.031 13.677 2. Comparison between patients RPGN due to AAV and healthy controls In the renal medulla, patients with biopsy proven RPGN due to AAV showed lower ADC values compared to the healthy volunteers (Table 3 ). For the FA parameter, higher values were measured in the renal medulla of patients with RPGN compared to healthy volunteers. For the ASL parameter, lower values were observed in the renal cortex of patients with RPGN compared to the healthy control group. No relevant differences were observed in the medulla. Cortical T2* values were also lower in patients with RPGN compared to the healthy control group. Table 3 Comparison of MRI parameters among the two groups (for all measurements, the mean value of the right and left kidney was calculated) ADC (10 ⁻6 mm 2 /s) FA (a.u.) ASL (ml/100g/s) T2* (ms) Cortex Medulla Cortex Medulla Cortex Medulla Cortex Medulla RPGN due to AAV 1907 +/-59 1588 +/- 260 0.18 +/-0.05 0.034 +/- 0.09 187 +/-48 275 +/- 131 28 +/- 12 30 +/-9 Healthy control group 1981 +/- 89 1982 +/- 109 0.21 +/-0.04 0.21 +/- 0.03 286 +/-62 307 +/-78 59 +/-5 25 +/-5 ( 1 ) Healthy subjects (n = 10), ( 2 ) Patients with rapidly progressive glomerulonephritis associated with vasculitis (n = 3). 3) Comparison between patients with AAV without clinical signs of renal involvement and healthy controls In patients with AAV without clinical signs of renal involvement such as proteinuria, erythrocyturia, or elevation of serum creatinine, lower ADC values were observed in the renal cortex and renal medulla compared to the healthy control group (Table 4 ). For the ASL parameter, values were comparable between both groups. For the FA parameter, higher values were observed in the renal medulla of patients with AAV without renal involvement compared to the healthy control group. Similar to patients with RPGN, cortical T2* values were also lower in patients without previously confirmed renal involvement. Table 4 Comparison of MRI parameters among the two groups (for all measurements, the mean value of the right and left kidney was calculated) ADC (10 ⁻6 mm 2 /s) FA (a.u.) ASL (ml/100g/s) T2* (ms) Cortex Medulla Cortex Medulla Cortex Medulla Cortex Medulla Patients with AAV without clinical signs of renal involvement 1847 +/-133 1785 +/- 184 0.22 +/-0.04 0.29 +/-0.05 272 +/-64 375 +/- 79 49 +/-5 37 +/-8 Healthy control group 1981 +/- 89 1982 +/- 109 0.21 +/-0.04 0.21 +/- 0.033 286 +/-62 307 +/-78 59 +/-5 25 +/-5 ( 1 ) Healthy subjects (n = 10), ( 2 ) patients with vasculitis without confirmed renal involvement (n = 4). Discussion This study highlights the potential of functional MRI to detect renal alterations in patients with AAV. The differences observed in ADC, FA, T2* and ASL values between RPGN patients and healthy controls suggest that these imaging biomarkers reflect structural and functional kidney impairment. Interestingly, alterations were also detected in AAV patients without clinical manifestation of renal involvement, pointing to the possibility of early kidney alterations. DWI is a non-invasive imaging technique that detects renal interstitial alterations, including fibrosis, inflammation, edema, and perfusion changes ( 7 ). Previous studies have shown that the ADC value is positively correlated with the glomerular filtration rate, suggesting its potential as a biomarker for assessing renal function ( 16 ). Acute and chronic renal failure also showed decreased ADC values compared with those of healthy volunteers ( 17 ). In this study, patients with RPGN exhibited lower ADC values in the renal medulla compared to the healthy control group, whereas no differences were observed in the renal cortex. Previous studies have confirmed that in AAV, not only the glomeruli but also the tubuli and the tubular basement membrane (BM) can be affected, potentially leading to tubulointerstitial inflammation ( 18 ). This could explain the reduced ADC values in the renal medulla. In patients with CKD, it has also been shown that ADC values decline more significantly in the renal medulla than in the cortex ( 7 ). Previous studies on functional renal MRI have generally shown that FA values significantly decrease in kidney diseases ( 8 ). In our study, higher medullary FA values were observed in patients with RPGN compared to the healthy control group. It is possible that during the acute inflammatory stage of vasculitis, tubular swelling in the medulla occurs, leading initially to an acceleration of fluid flow. A study also demonstrated that the Na⁺/H⁺ exchanger-3 is upregulated in glomerulonephritis, facilitating sodium uptake and proton secretion into the tubular system ( 19 ). This could explain the increased directional proton flux during inflammatory responses in the kidney, potentially contributing to the elevation of the FA parameter. Many studies report reproducibility of renal perfusion by ASL and lower ASL values in CKD patients compared with healthy subjects, which correlates with eGFR ( 20 ). This reproducibility seems to be lower in the medulla than the cortex ( 11 )( 21 ). This is also reflected in the study: ASL values in the cortex showed differences between patients with RPGN due to vasculitis and the healthy control group, with lower values in RPGN patients, whereas values in the medulla did not exhibit differences. Studies indicate that renal hypoxia may be a key prognostic factor for the progression of chronic kidney disease ( 22 ). BOLD-MRI has increasingly been utilized in recent years to evaluate alterations in renal oxygenation across various kidney diseases ( 12 ). In this study, patients with RPGN due to AAV exhibited lower cortical T2* values compared to the healthy control group. Patients with AAV but without clinical manifestation of renal involvement were also examined and compared to the healthy control group. Consistent with the findings in patients with confirmed RPGN, differences were observed in BOLD imaging cortical as well as in medullary FA and ADC values. These findings suggest that these parameters may have the potential to detect early, clinically silent kidney alterations in patients with AAV. The ASL values did not show differences, suggesting preserved renal perfusion. In patients without clinical signs of renal involvement such as proteinuria or erythrocyturia, biopsy data are unfortunately not available due to ethical reasons. Biopsies might confirm structural changes that are already visible on fMRI. Future studies should focus on longitudinal assessments to evaluate the potential of functional MRI for disease monitoring of AAV over time. Repeated measurements could provide insights into disease progression and treatment response. While MRI represents a cost factor, early detection of renal involvement could help prevent disease progression and reduce the need for more invasive or costly interventions. Delayed diagnosis may result in a prolonged disease course, leading to higher healthcare expenses due to extended hospital stays, more intensive treatments, or complications requiring dialysis. Therefore, implementing MRI as a non-invasive monitoring tool could potentially improve patient outcomes while optimizing healthcare resources. The low number of RPGN patients represents a limitation of this study. Given the incidence of RPGN of only 7 cases per 1,000,000 inhabitants, an increase in patient numbers would likely only be feasible through a multicenter study ( 3 ). Another limitation of this study is the relatively low number of b-values used for diffusion-weighted imaging. However, the MRI protocol was designed to be feasible within a clinically acceptable scanning time. Despite this constraint, the acquired diffusion-weighted sequences were still analyzable and provided valuable insights into renal function. In conclusion this study demonstrates that functional MRI can detect renal alterations in ANCA-associated vasculitis. Differences in ADC, FA, T2* and ASL values between RPGN patients and healthy controls suggest that these parameters reflect structural and functional kidney impairment. Notably, imaging markers were also altered in patients without confirmed renal involvement, indicating potential early kidney damage. These findings highlight the potential of multiparametric renal MRI as a non-invasive tool for assessing and monitoring vasculitis-related kidney disease. Declarations Ethics approval: The study was approved by the Ethics Committee of the Medical Faculty of Heinrich Heine University Düsseldorf (study number 5891R, approval date August 28, 2018). All patients who participated in the study signed an informed consent form. Consent for publication: Not applicable. Data availability statement : The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interest statement: The authors declare that they have no conflicts of interest. Acknowledgements: Böttger: funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation): 493659010 Ljimani is supported by an internal research grant of the local Research Committee of the Medical Faculty of Heinrich-Heine-University Düsseldorf (2020-65) Bechler is supported by an internal research grant of the local Research Committee of the Medical Faculty of Heinrich-Heine-University Düsseldorf (2024-07) Author Contributions: M.S.: study conception; data analysis and manuscript drafting; A.K.: study design and data interpretation; critical manuscript revision.; I.H.: data acquisition and analysis; manuscript preparation; S.B. manuscript revision; T.A.T.: manuscript manuscript revision; E.B.: manuscript revision; C.B.: manuscript manuscript revision; H.A.P.: manuscript revision; G.A.: manuscript revision; J.H.W.D.: manuscript revision; M.Sch.: manuscript revision; A.L.: study supervision and data interpretation; critical manuscript revision. 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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-8475989","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":572833665,"identity":"d661dbde-97af-45ac-9797-38f8e0d3c817","order_by":0,"name":"Marie Scheuer","email":"","orcid":"","institution":"University Dusseldorf, Medical Faculty","correspondingAuthor":false,"prefix":"","firstName":"Marie","middleName":"","lastName":"Scheuer","suffix":""},{"id":572833666,"identity":"cf11c709-483b-4140-98e3-717fd7d6f1a8","order_by":1,"name":"Anna Kernder","email":"data:image/png;base64,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","orcid":"","institution":"Ruhr University Bochum","correspondingAuthor":true,"prefix":"","firstName":"Anna","middleName":"","lastName":"Kernder","suffix":""},{"id":572833667,"identity":"2a20187b-ac3e-4afa-b116-cd7d2028ce98","order_by":2,"name":"Isabell Haase","email":"","orcid":"","institution":"University Medical Center Hamburg-Eppendorf","correspondingAuthor":false,"prefix":"","firstName":"Isabell","middleName":"","lastName":"Haase","suffix":""},{"id":572833668,"identity":"3cabafe0-08c3-489b-80ea-97dac3c2b76b","order_by":3,"name":"Sara Bokonjic","email":"","orcid":"","institution":"University Dusseldorf, Medical Faculty","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Bokonjic","suffix":""},{"id":572833669,"identity":"4bce7e06-ab54-4002-af2f-56807b982275","order_by":4,"name":"Thomas Andreas Thiel","email":"","orcid":"","institution":"University Dusseldorf, Medical Faculty","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"Andreas","lastName":"Thiel","suffix":""},{"id":572833670,"identity":"b47beb0a-bd6e-4f46-b367-ab0d78b7acf9","order_by":5,"name":"Eric Bechler","email":"","orcid":"","institution":"University Dusseldorf, Medical Faculty","correspondingAuthor":false,"prefix":"","firstName":"Eric","middleName":"","lastName":"Bechler","suffix":""},{"id":572833673,"identity":"669911ed-625f-4294-8eec-0faf4f10c5db","order_by":6,"name":"Charlotte Böttger","email":"","orcid":"","institution":"University Dusseldorf, Medical Faculty","correspondingAuthor":false,"prefix":"","firstName":"Charlotte","middleName":"","lastName":"Böttger","suffix":""},{"id":572833674,"identity":"563aa254-b035-494a-8800-e053386b83ad","order_by":7,"name":"Helena Anne Peters","email":"","orcid":"","institution":"University Dusseldorf, Medical Faculty","correspondingAuthor":false,"prefix":"","firstName":"Helena","middleName":"Anne","lastName":"Peters","suffix":""},{"id":572833676,"identity":"a663c645-f955-4673-90f8-671d4e427b7b","order_by":8,"name":"Gerald Antoch","email":"","orcid":"","institution":"University Dusseldorf, Medical Faculty","correspondingAuthor":false,"prefix":"","firstName":"Gerald","middleName":"","lastName":"Antoch","suffix":""},{"id":572833677,"identity":"c26d14e1-6e24-4d4a-809c-5ebe6041260e","order_by":9,"name":"Jörg H. 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W.","lastName":"Distler","suffix":""},{"id":572833678,"identity":"b46583db-d716-4cf5-870d-f1e5c1c7ee37","order_by":10,"name":"Matthias Schneider","email":"","orcid":"","institution":"Düsseldorf University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Matthias","middleName":"","lastName":"Schneider","suffix":""},{"id":572833680,"identity":"ad55b68a-bf3d-4290-8ec9-6f9ea23271a6","order_by":11,"name":"Alexandra Ljimani","email":"","orcid":"","institution":"University Dusseldorf, Medical Faculty","correspondingAuthor":false,"prefix":"","firstName":"Alexandra","middleName":"","lastName":"Ljimani","suffix":""}],"badges":[],"createdAt":"2025-12-29 22:08:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8475989/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8475989/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12882-026-04981-3","type":"published","date":"2026-04-30T15:57:57+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":100094120,"identity":"503d3fa3-f7b5-48e0-b3ff-0ef1fe86bb99","added_by":"auto","created_at":"2026-01-13 01:28:36","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":9555330,"visible":true,"origin":"","legend":"","description":"","filename":"fMRIVasculitisKidneyRev1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8475989/v1/833c19bddbb05947a4aae321.docx"},{"id":100094111,"identity":"3a2fe644-0105-4378-9ed3-cd899a9296d2","added_by":"auto","created_at":"2026-01-13 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07:53:30","extension":"xml","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":81639,"visible":true,"origin":"","legend":"","description":"","filename":"d0575c42e0154471904b0552cdf2a3af1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8475989/v1/bc2ba638c8f61580d6ef2922.xml"},{"id":100365918,"identity":"46db4c38-8413-4203-acc6-febb4b06fd63","added_by":"auto","created_at":"2026-01-16 07:55:44","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":91344,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8475989/v1/cc0e9f9462a2e0c6374ca0cb.html"},{"id":100094114,"identity":"8fad72e4-1f27-4a17-ba6f-79f1ddcdd653","added_by":"auto","created_at":"2026-01-13 01:28:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":585244,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMultiparametric MRI parameters in renal cortex and medulla across healthy controls (green), patients with AAV without RPGN (orange), and patients with RPGN due to AAV (blue).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8475989/v1/989b4868764662b7ae8e3d03.png"},{"id":100094117,"identity":"7811ed4b-01a4-48a9-a282-26f932ef1db4","added_by":"auto","created_at":"2026-01-13 01:28:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":8030065,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eRepresentative renal MRI parameter maps (ADC, FA, ASL and T2*\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e) in patients with ANCA-associated vasculitis and healthy controls:\u003c/strong\u003e\u003cem\u003e \u003cbr\u003e\n Cortical ADC values appeared markedly lower in both RPGN patients and those without confirmed renal involvement compared to healthy controls. \u003cbr\u003e\nCortical perfusion, as assessed by ASL, was also reduced in both patient groups.\u003c/em\u003e \u003cbr\u003e\n Medullary FA values were higher in both patient groups compared to healthy controls\u003cem\u003e. Additionally, cortical T2\u003c/em\u003e* values were lower than those observed in the healthy control group.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8475989/v1/393d092c7bd93eba10d7d0c7.png"},{"id":108438948,"identity":"591a3954-779f-47f4-900b-6c4553c2b3c4","added_by":"auto","created_at":"2026-05-04 16:11:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":12121750,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8475989/v1/544d4c22-adfb-4b6f-9423-58421a0f4e6c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Contrast-Free Functional MRI for Assessing Renal Involvement in Patients with ANCA-associated Vasculitis","fulltext":[{"header":"Introduction/Background","content":"\u003cp\u003eANCA-associated vasculitis (AAV) is a group of rare, life-threatening autoimmune disorders characterized by necrotizing inflammation of small to medium blood vessels and the presence of anti-neutrophil cytoplasmic antibodies (ANCA) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The three principal subtypes are granulomatosis with polyangiitis (GPA), microscopic polyangiitis (MPA), and eosinophilic granulomatosis with polyangiitis (EGPA), each distinguished by clinical features such as granulomatous inflammation in GPA and eosinophil infiltration in EGPA (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eANCAs against proteinase 3 (PR3-ANCA) are most commonly found in GPA, while myeloperoxidase ANCAs (MPO-ANCA) predominate in MPA and EGPA.\u003c/p\u003e \u003cp\u003eVasculitis encompass a range of complex illnesses that can affect any organ system, posing significant diagnostic and management challenges due to overlapping and varying symptoms. Vasculitis can also manifest as single-organ vasculitis (SOV), characterized by inflammation of blood vessels within a single organ, such as the kidney (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn rare cases, with an incidence of 7 per 1,000,000, AAV can result in rapidly progressive glomerulonephritis (RPGN) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTypically, renal involvement becomes symptomatic through acute kidney injury with proteinuria and erythrocyturia. The gold standard to confirm a renal involvement remains the invasive renal biopsy (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven the risks associated with biopsy (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), an alternative method for diagnosing renal involvement in vasculitis is essential. Non-invasive functional MRI presents a promising option. Functional renal MRI have shown its potential to reflect renal involvement in different pathological conditions as diabetic kidney disease (DKD) and chronic kidney disease (CKD).\u003c/p\u003e \u003cp\u003eThe apparent diffusion coefficient (ADC) measures restricted water molecule motion in renal tissue, influenced by structural features like cell membranes and the interstitial matrix (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Reduced eGFR and fibrosis in chronic renal dysfunction hinder water diffusion, leading to lower ADC values. Several studies have shown a positive correlation between ADC and GFR (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo characterize tissue microarchitecture by quantifying anisotropy and spatial diffusion dependence, diffusion encoding in multiple directions is required. This is achieved with diffusion tensor imaging (DTI), which necessitates at least six distinct signal encoding directions. DTI enables the calculation of FA, reflecting tissue anisotropy (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Studies have already demonstrated that FA alterations are possible in kidney diseases. Liu et al. reported that DTI is valuable for the noninvasive assessment of renal function and pathology in patients with CKD. A decrease in FA was associated with glomerular lesions, tubulointerstitial injuries, and eGFR decline (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eApproximately 25% of cardiac output circulates through the kidneys, making renal perfusion essential for nutrient and oxygen supply as well as glomerular filtration. Renal ischemia plays a critical role in acute kidney injury (AKI) and accelerates CKD progression (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Early assessment of renal perfusion is crucial for predicting, slowing, or preventing further deterioration. Arterial spin labeling (ASL) is a non-invasive MRI technique that uses magnetically labeled arterial blood protons as an endogenous tracer to assess tissue perfusion without exogenous contrast agents (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Many studies report reproducibility of renal perfusion by ASL and lower ASL values in CKD patients compared with healthy subjects, which correlates with eGFR (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBlood oxygenation level dependent (BOLD) MRI utilizes changes in blood oxygenation to create contrast, as oxygen saturation alters the magnetic properties of hemoglobin (Hb). Fully oxygenated Hb is diamagnetic, while deoxygenated Hb is paramagnetic, affecting the transverse decay time (T2*) or the rate constant (R2*). Studies have also shown that R2* values are positively correlated with kidney function and inversely correlated with the eGFR (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Also recent studies have reported that the evaluation of oxygenation in renal cortex by BOLD-MRI can predict the progression of renal function (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study aimed to evaluate the extent to which functional MRI parameters reflect renal parenchymal damage in patients with AAV with known rapid progressive glomerulonephritis (RPGN). Additionally, it investigated whether alterations in these parameters are detectable in patients without clinical manifestation of a renal involvement.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003e The study was approved by the local ethics committee, and written informed consent was obtained from all study participants. Ten healthy volunteers (group 1) (mean age 63.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6,9 years; 6 women and 4 men) without any history of kidney disease, diabetes, vascular disease, previous renal surgery or any known systemic disease potentially involving the kidneys participated in the study.\u003c/p\u003e \u003cp\u003eFurthermore, sevens patients (mean age 63,8\u0026thinsp;\u0026plusmn;\u0026thinsp;11 years; 5 women and 2 men) were included in the study to assess the potential clinical relevance of functional renal MRI (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The group of patients included patients with biopsy proven rapidly progressive glomerulonephritis associated with vasculitis (group 2) (n\u0026thinsp;=\u0026thinsp;3) and patients with diagnosed vasculitis without confirmed renal involvement (group 3) (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Vasculitis Patients: Demographics and Clinical Parameters.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge \u003c/p\u003e \u003cp\u003e(years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAAV Subtype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProteinurie \u003c/p\u003e \u003cp\u003e(mg/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHematuria \u003c/p\u003e \u003cp\u003e(cells/\u0026micro;l)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eRPGN due to AAV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003enone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003enone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eVasculitis without clinical signs of renal involvement\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEGPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003enone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEGPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003enone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003enone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMR Imaging\u003c/h3\u003e\n\u003cp\u003eMultiparametric, functional MRI measurements were performed on a clinical 3T MRI scanner (Magnetom Prisma, Siemens AG, Healthineers, Erlangen, Germany) without the use of contrasting agents.\u003c/p\u003e \u003cp\u003eFunctional renal sequences were performed according to consensus-based recommendations for functional renal imaging by PARENCHIMA project (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor each patient, MRI acquisition began with a T2-weighted HASTE (Half-Fourier Acquisition Single-Shot Turbo Spin-Echo) sequence, providing an anatomical overview of the kidneys.\u003c/p\u003e \u003cp\u003eThis was followed by diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) using a coronal echo-planar imaging (EPI) sequence. These techniques allowed for the assessment of water diffusion in renal tissue, enabling the calculation of the apparent diffusion coefficient (ADC) and fractional anisotropy (FA). The EPI sequence was acquired with 15 slices of 5 mm thickness, a field of view (FOV) of 400 \u0026times; 400 mm, and TR/TE of 3000/78 ms, using b-values of 0, 50, 400, 800 s/mm\u0026sup2; with 6 diffusion encoding directions. DWI data acquisition adhered to the recommendations outlined by Ljimani et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRenal perfusion was assessed using arterial spin labeling (ASL) with a paracoronal FAIR-TrueFISP sequence, employing the SSFSE technique with TR/TE of 5/2.5 ms, an inversion time (TI) of 1.2 ms, a slice thickness of 8 mm, and an FOV of 400 \u0026times; 400 mm (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRenal oxygenation was evaluated using blood oxygenation level-dependent (BOLD) MRI with a coronal T2*-weighted multi-echo gradient-echo (GRE) sequence. The sequence included 12\u0026ndash;16 echoes, TR/TE ranging from 65 ms to 11.1\u0026ndash;53.1 ms, and a flip angle of 40\u0026deg;. Images were acquired with a slice thickness of 5 mm, three slices with a 1 mm gap, a matrix of 256 \u0026times; 256, and an FOV of 396 \u0026times; 399 mm (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eImage and statistical analysis\u003c/h3\u003e\n\u003cp\u003eROI (Region of Interest) based analysis were performed using the clinic's PACS (Picture Archiving and Communication System) for each acquired sequence. ROIs were drawn with a surface area of 40\u0026ndash;70 mm\u0026sup2;, ensuring comparability, with one ROI placed in the cortex and medulla of each kidney.\u003c/p\u003e \u003cp\u003eDue to the low number of patients included in this study, statistical analysis was only performed for healthy control compared to all patients and not individual patient groups. Analyses were performed using Wilcoxon-Mann-Whitney u-test. Furthermore, results of different patient groups were presented descriptively to illustrate observable differences between the groups.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e1. Comparison of all patients with AAV and the healthy control group\u003c/p\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows multiparametric renal MRI data comparing patients with ANCA-associated vasculitis (AAV) and healthy controls. Across the AAV cohort, changes were observed in diffusion (ADC), microstructural integrity (FA), perfusion (ASL), and tissue oxygenation (T2*). Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates representative coronal renal MRI images and corresponding parametric maps for the different quantitative MRI techniques.\u003c/p\u003e\n\u003cp\u003eADC values were lower and FA values higher in AAV patients, particularly in the medulla, suggesting altered tissue architecture. Cortical perfusion was reduced, and T2* times were markedly shorter in both cortex and medulla, indicating impaired oxygenation. These findings highlight subclinical renal involvement in AAV, detectable by functional MRI even in the absence of overt RPGN.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003esummarizes the quantitative MRI parameters in healthy controls and AAV patients, stratified by renal cortex and medulla, including group sizes, mean values, standard deviations, and statistical significance.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSignificance\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN Healthy\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN Disease\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean Healthy\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean Disease\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSD Healthy\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSD Disease\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eADC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(10\u003csup\u003e⁻6\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1980.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1872.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e77.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e68.722\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eADC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(10\u003csup\u003e⁻6\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedulla\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1982.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1733.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e101.259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e213.564\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eASL\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(ml/100g/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e285.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e235.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58.464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62.794\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eASL\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(ml/100g/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedulla\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e306.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e332.357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e75.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88.103\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFA\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(a.u.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.669\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFA\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(a.u.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedulla\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eT2*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(ms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.898\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eT2*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(ms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedulla\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.677\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2. Comparison between patients RPGN due to AAV and healthy controls\u003c/p\u003e\n\u003cp\u003eIn the renal medulla, patients with biopsy proven RPGN due to AAV showed lower ADC values compared to the healthy volunteers (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eFor the FA parameter, higher values were measured in the renal medulla of patients with RPGN compared to healthy volunteers.\u003c/p\u003e\n\u003cp\u003eFor the ASL parameter, lower values were observed in the renal cortex of patients with RPGN compared to the healthy control group. No relevant differences were observed in the medulla.\u003c/p\u003e\n\u003cp\u003eCortical T2* values were also lower in patients with RPGN compared to the healthy control group.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of MRI parameters among the two groups (for all measurements, the mean value of the right and left kidney was calculated)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eADC\u003c/p\u003e\n \u003cp\u003e(10\u003csup\u003e⁻6\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eFA\u003c/p\u003e\n \u003cp\u003e(a.u.)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eASL\u003c/p\u003e\n \u003cp\u003e\u003cspan class=\"Underline\"\u003e(ml/100g/s)\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eT2*\u003c/p\u003e\n \u003cp\u003e(ms)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCortex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMedulla\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCortex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMedulla\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCortex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMedulla\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCortex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMedulla\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRPGN due to AAV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1907\u003c/p\u003e\n \u003cp\u003e+/-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1588\u003c/p\u003e\n \u003cp\u003e+/- 260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003cp\u003e+/-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003cp\u003e+/- 0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e187\u003c/p\u003e\n \u003cp\u003e+/-48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e275\u003c/p\u003e\n \u003cp\u003e+/- 131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003cp\u003e+/- 12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003cp\u003e+/-9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy control group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1981\u003c/p\u003e\n \u003cp\u003e+/- 89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1982\u003c/p\u003e\n \u003cp\u003e+/- 109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003cp\u003e+/-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003cp\u003e+/- 0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e286\u003c/p\u003e\n \u003cp\u003e+/-62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e307\u003c/p\u003e\n \u003cp\u003e+/-78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003cp\u003e+/-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003cp\u003e+/-5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e(\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e) Healthy subjects (n\u0026thinsp;=\u0026thinsp;10),\u003c/p\u003e\n\u003cp\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e) Patients with rapidly progressive glomerulonephritis associated with vasculitis (n\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e\n\u003cp\u003e3) Comparison between patients with AAV without clinical signs of renal involvement and healthy controls\u003c/p\u003e\n\u003cp\u003eIn patients with AAV without clinical signs of renal involvement such as proteinuria, erythrocyturia, or elevation of serum creatinine, lower ADC values were observed in the renal cortex and renal medulla compared to the healthy control group (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eFor the ASL parameter, values were comparable between both groups.\u003c/p\u003e\n\u003cp\u003eFor the FA parameter, higher values were observed in the renal medulla of patients with AAV without renal involvement compared to the healthy control group.\u003c/p\u003e\n\u003cp\u003eSimilar to patients with RPGN, cortical T2* values were also lower in patients without previously confirmed renal involvement.\u0026nbsp;\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of MRI parameters among the two groups (for all measurements, the mean value of the right and left kidney was calculated)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eADC\u003c/p\u003e\n \u003cp\u003e(10\u003csup\u003e⁻6\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eFA\u003c/p\u003e\n \u003cp\u003e(a.u.)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eASL\u003c/p\u003e\n \u003cp\u003e\u003cspan class=\"Underline\"\u003e(ml/100g/s)\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eT2*\u003c/p\u003e\n \u003cp\u003e(ms)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCortex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMedulla\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCortex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMedulla\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCortex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMedulla\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCortex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMedulla\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with AAV without clinical signs of renal involvement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1847\u003c/p\u003e\n \u003cp\u003e+/-133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1785\u003c/p\u003e\n \u003cp\u003e+/- 184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003cp\u003e+/-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003cp\u003e+/-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e272\u003c/p\u003e\n \u003cp\u003e+/-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e375\u003c/p\u003e\n \u003cp\u003e+/- 79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003cp\u003e+/-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003cp\u003e+/-8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy control group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1981\u003c/p\u003e\n \u003cp\u003e+/- 89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1982\u003c/p\u003e\n \u003cp\u003e+/- 109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003cp\u003e+/-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003cp\u003e+/- 0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e286\u003c/p\u003e\n \u003cp\u003e+/-62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e307\u003c/p\u003e\n \u003cp\u003e+/-78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003cp\u003e+/-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003cp\u003e+/-5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e(\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e) Healthy subjects (n\u0026thinsp;=\u0026thinsp;10),\u003c/p\u003e\n\u003cp\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e) patients with vasculitis without confirmed renal involvement (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study highlights the potential of functional MRI to detect renal alterations in patients with AAV. The differences observed in ADC, FA, T2* and ASL values between RPGN patients and healthy controls suggest that these imaging biomarkers reflect structural and functional kidney impairment. Interestingly, alterations were also detected in AAV patients without clinical manifestation of renal involvement, pointing to the possibility of early kidney alterations.\u003c/p\u003e \u003cp\u003eDWI is a non-invasive imaging technique that detects renal interstitial alterations, including fibrosis, inflammation, edema, and perfusion changes (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Previous studies have shown that the ADC value is positively correlated with the glomerular filtration rate, suggesting its potential as a biomarker for assessing renal function (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Acute and chronic renal failure also showed decreased ADC values compared with those of healthy volunteers (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). In this study, patients with RPGN exhibited lower ADC values in the renal medulla compared to the healthy control group, whereas no differences were observed in the renal cortex. Previous studies have confirmed that in AAV, not only the glomeruli but also the tubuli and the tubular basement membrane (BM) can be affected, potentially leading to tubulointerstitial inflammation (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). This could explain the reduced ADC values in the renal medulla. In patients with CKD, it has also been shown that ADC values decline more significantly in the renal medulla than in the cortex (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrevious studies on functional renal MRI have generally shown that FA values significantly decrease in kidney diseases (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In our study, higher medullary FA values were observed in patients with RPGN compared to the healthy control group. It is possible that during the acute inflammatory stage of vasculitis, tubular swelling in the medulla occurs, leading initially to an acceleration of fluid flow. A study also demonstrated that the Na⁺/H⁺ exchanger-3 is upregulated in glomerulonephritis, facilitating sodium uptake and proton secretion into the tubular system (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). This could explain the increased directional proton flux during inflammatory responses in the kidney, potentially contributing to the elevation of the FA parameter.\u003c/p\u003e \u003cp\u003eMany studies report reproducibility of renal perfusion by ASL and lower ASL values in CKD patients compared with healthy subjects, which correlates with eGFR (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). This reproducibility seems to be lower in the medulla than the cortex (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). This is also reflected in the study: ASL values in the cortex showed differences between patients with RPGN due to vasculitis and the healthy control group, with lower values in RPGN patients, whereas values in the medulla did not exhibit differences.\u003c/p\u003e \u003cp\u003eStudies indicate that renal hypoxia may be a key prognostic factor for the progression of chronic kidney disease (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). BOLD-MRI has increasingly been utilized in recent years to evaluate alterations in renal oxygenation across various kidney diseases (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In this study, patients with RPGN due to AAV exhibited lower cortical T2* values compared to the healthy control group.\u003c/p\u003e \u003cp\u003ePatients with AAV but without clinical manifestation of renal involvement were also examined and compared to the healthy control group. Consistent with the findings in patients with confirmed RPGN, differences were observed in BOLD imaging cortical as well as in medullary FA and ADC values. These findings suggest that these parameters may have the potential to detect early, clinically silent kidney alterations in patients with AAV. The ASL values did not show differences, suggesting preserved renal perfusion. In patients without clinical signs of renal involvement such as proteinuria or erythrocyturia, biopsy data are unfortunately not available due to ethical reasons. Biopsies might confirm structural changes that are already visible on fMRI.\u003c/p\u003e \u003cp\u003eFuture studies should focus on longitudinal assessments to evaluate the potential of functional MRI for disease monitoring of AAV over time. Repeated measurements could provide insights into disease progression and treatment response.\u003c/p\u003e \u003cp\u003eWhile MRI represents a cost factor, early detection of renal involvement could help prevent disease progression and reduce the need for more invasive or costly interventions. Delayed diagnosis may result in a prolonged disease course, leading to higher healthcare expenses due to extended hospital stays, more intensive treatments, or complications requiring dialysis. Therefore, implementing MRI as a non-invasive monitoring tool could potentially improve patient outcomes while optimizing healthcare resources.\u003c/p\u003e \u003cp\u003eThe low number of RPGN patients represents a limitation of this study. Given the incidence of RPGN of only 7 cases per 1,000,000 inhabitants, an increase in patient numbers would likely only be feasible through a multicenter study (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother limitation of this study is the relatively low number of b-values used for diffusion-weighted imaging. However, the MRI protocol was designed to be feasible within a clinically acceptable scanning time. Despite this constraint, the acquired diffusion-weighted sequences were still analyzable and provided valuable insights into renal function.\u003c/p\u003e \u003cp\u003eIn conclusion this study demonstrates that functional MRI can detect renal alterations in ANCA-associated vasculitis. Differences in ADC, FA, T2* and ASL values between RPGN patients and healthy controls suggest that these parameters reflect structural and functional kidney impairment. Notably, imaging markers were also altered in patients without confirmed renal involvement, indicating potential early kidney damage.\u003c/p\u003e \u003cp\u003eThese findings highlight the potential of multiparametric renal MRI as a non-invasive tool for assessing and monitoring vasculitis-related kidney disease.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval:\u0026nbsp;\u003c/strong\u003eThe study was approved by the Ethics Committee of the Medical Faculty of Heinrich Heine University Düsseldorf (study number 5891R, approval date August 28, 2018). All patients who participated in the study signed an informed consent form.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest statement:\u003c/strong\u003e The authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003cbr\u003e\u003c/strong\u003eBöttger: funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation): 493659010\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003eLjimani is supported by an internal research grant of the local Research Committee of the Medical Faculty of Heinrich-Heine-University Düsseldorf (2020-65)\u003c/p\u003e\n\u003cp\u003eBechler is supported by an internal research grant of the local Research Committee of the Medical Faculty of Heinrich-Heine-University Düsseldorf (2024-07)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003cbr\u003e\u003c/strong\u003eM.S.: study conception; data analysis and manuscript drafting; A.K.: study design and data interpretation; critical manuscript revision.; I.H.: data acquisition and analysis; manuscript preparation; S.B. manuscript revision; T.A.T.: manuscript manuscript revision; E.B.: manuscript revision; C.B.: manuscript manuscript revision; H.A.P.: manuscript revision; G.A.: manuscript revision; J.H.W.D.: manuscript revision; M.Sch.: manuscript revision; A.L.: study supervision and data interpretation; critical manuscript revision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research did not receive funding.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJennette JC. Oktober. Overview of the 2012 revised International Chapel Hill Consensus Conference nomenclature of vasculitides. Clin Exp Nephrol. 2013;17(5):603\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRathmann J, Mohammad AJ. Classification Criteria for ANCA Associated Vasculitis \u0026ndash; Ready for Prime Time? Curr Rheumatol Rep September. 2024;26(9):332\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCouser WG. Rapidly Progressive Glomerulonephritis: Classification, Pathogenetic Mechanisms, and Therapy. Am J Kidney Dis Juni. 1988;11(6):449\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJayne D. Vasculitis\u0026mdash;when can biopsy be avoided? Nephrol Dial Transpl 1 September. 2017;32(9):1454\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeumann T. Update Immunglobulin-A-Vaskulitis. Z F\u0026uuml;r Rheumatol Mai. 2022;81(4):305\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang JL, Rusinek H, Chandarana H, Lee VS. Functional MRI of the kidneys. J Magn Reson Imaging Februar. 2013;37(2):282\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaroli A, Schneider M, Friedli I, Ljimani A, De Seigneux S, Boor P. u. a. Diffusion-weighted magnetic resonance imaging to assess diffuse renal pathology: a systematic review and statement paper. Nephrol Dial Transpl. September 2018;1(suppl2):ii29\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Z, Xu Y, Zhang J, Zhen J, Wang R, Cai S. u. a. Chronic kidney disease: pathological and functional assessment with diffusion tensor imaging at 3T MR. Eur Radiol M\u0026auml;rz. 2015;25(3):652\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMao W, Ding Y, Ding X, Fu C, Cao B, Kuehn B. u. a. Capability of arterial spin labeling and intravoxel incoherent motion diffusion-weighted imaging to detect early kidney injury in chronic kidney disease. Eur Radiol 13 Dezember. 2022;33(5):3286\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNery F, Buchanan CE, Harteveld AA, Odudu A, Bane O, Cox EF. u. a. Consensus-based technical recommendations for clinical translation of renal ASL MRI. Magn Reson Mater Phys Biol Med Februar. 2020;33(1):141\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOdudu A, Nery F, Harteveld AA, Evans RG, Pendse D, Buchanan CE. u. a. Arterial spin labelling MRI to measure renal perfusion: a systematic review and statement paper. Nephrol Dial Transpl 1 September. 2018;33(suppl2):ii15\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen F, Yan H, Yang F, Cheng L, Zhang S, Li S. u. a. Evaluation of Renal Tissue Oxygenation Using Blood Oxygen Level-Dependent Magnetic Resonance Imaging in Chronic Kidney Disease. Kidney Blood Press Res. 2021;46(4):441\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePruijm M, Milani B, Pivin E, Podhajska A, Vogt B, Stuber M. u. a. Reduced cortical oxygenation predicts a progressive decline of renal function in patients with chronic kidney disease. Kidney Int April. 2018;93(4):932\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBane O, Mendichovszky IA, Milani B, Dekkers IA, Deux JF, Eckerbom P. u. a. Consensus-based technical recommendations for clinical translation of renal BOLD MRI. Magn Reson Mater Phys Biol Med Februar. 2020;33(1):199\u0026ndash;215.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLjimani A, Caroli A, Laustsen C, Francis S, Mendichovszky IA, Bane O. u. a. Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI. Magn Reson Mater Phys Biol Med Februar. 2020;33(1):177\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu Y, Wang X, Jiang X. Relationship between the renal apparent diffusion coefficient and glomerular filtration rate: Preliminary experience. J Magn Reson Imaging September. 2007;26(3):678\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNamimoto T, Yamashita Y, Mitsuzaki K, Nakayama Y, Tang Y, Takahashi M. Measurement of the apparent diffusion coefficient in diffuse renal disease by diffusion-weighted echo-planar MR imaging. J Magn Reson Imaging Juni. 1999;9(6):832\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGluhovschi C, Gadalean F, Velciov S, Nistor M, Petrica L. Three Diseases Mediated by Different Immunopathologic Mechanisms\u0026mdash;ANCA-Associated Vasculitis, Anti-Glomerular Basement Membrane Disease, and Immune Complex-Mediated Glomerulonephritis\u0026mdash;A Common Clinical and Histopathologic Picture: Rapidly Progressive Crescentic Glomerulonephritis. Biomedicines 6 November. 2023;11(11):2978.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGadau J, Peters H, Kastner C, K\u0026uuml;hn H, Nieminen-Kelh\u0026auml; M, Khadzhynov D. u. a. Mechanisms of tubular volume retention in immune-mediated glomerulonephritis. Kidney Int April. 2009;75(7):699\u0026ndash;710.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGillis KA, McComb C, Patel RK, Stevens KK, Schneider MP, Radjenovic A. u. a. Non-Contrast Renal Magnetic Resonance Imaging to Assess Perfusion and Corticomedullary Differentiation in Health and Chronic Kidney Disease. Nephron. 2016;133(3):183\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMora-Guti\u0026eacute;rrez JM, Garcia‐Fernandez N, Slon Roblero MF, P\u0026aacute;ramo JA, Escalada FJ. Wang DJj, u. a. Arterial spin labeling MRI is able to detect early hemodynamic changes in diabetic nephropathy. J Magn Reson Imaging Dezember. 2017;46(6):1810\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen F, Yan H, Yang F, Cheng L, Zhang S, Li S. u. a. Evaluation of Renal Tissue Oxygenation Using Blood Oxygen Level-Dependent Magnetic Resonance Imaging in Chronic Kidney Disease. Kidney Blood Press Res. 2021;46(4):441\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"vasculitis, AAV, fMRI, kidney","lastPublishedDoi":"10.21203/rs.3.rs-8475989/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8475989/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEarly detection of renal involvement in ANCA-associated vasculitis (AAV) is crucial, as functional changes often precede anatomical damage. Current diagnostic standards, such as the measurement of serum creatinine, renal biopsy and urinary analyses have limitations due to delayed detection and lack of speficity. Functional renal MRI techniques (mpMRI), including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), arterial spin labeling (ASL) and blood oxygenation level dependent (BOLD) offer promising non-invasive alternatives for assessing renal function in AAV.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study evaluated 7 patients and 10 healthy controls: patients with rapidly progressive glomerulonephritis (RPGN) due to AAV (n\u0026thinsp;=\u0026thinsp;3), AAV patients without clinical signs of renal involvement (n\u0026thinsp;=\u0026thinsp;4), and healthy controls (n\u0026thinsp;=\u0026thinsp;10). All participants underwent renal mpMRI. Key parameters, including the apparent diffusion coefficient (ADC), fractional anisotropy (FA), and ASL-based renal perfusion and T2* parameter maps, were acquired and analyzed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe following differences in renal imaging parameters were observed between RPGN patients and healthy controls: RPGN patients showed reduced ADC values in the renal medulla and increased FA values compared to controls. Additionally, ASL values in the renal cortex were lower in RPGN patients. T2* values were lower in RPGN patients compared to the healthy control group in the cortex. Patients with AAV without confirmed renal involvement also showed alterations in ADC, T2* and FA values compared to healthy controls.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur findings indicate that functional MRI parameter might detect renal alterations in AAV that precede clinical changes. Therefore, mpMRI might offer novel opportunities for non-invasive detection of disease-associated changes.\u003c/p\u003e","manuscriptTitle":"Contrast-Free Functional MRI for Assessing Renal Involvement in Patients with ANCA-associated Vasculitis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-13 01:28:31","doi":"10.21203/rs.3.rs-8475989/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-22T16:53:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-21T20:16:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-20T03:50:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-15T13:02:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-09T17:00:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"22010040207747402038851466626473860239","date":"2026-01-09T14:15:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"150618134770857866785707753777211604338","date":"2026-01-09T06:36:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"70659259515285161436040471822214897184","date":"2026-01-08T07:35:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303937564647209927951851329411598252238","date":"2026-01-07T22:51:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"19697075083362369253977342585580628923","date":"2026-01-07T07:52:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-06T19:30:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-06T11:10:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nephrology","date":"2026-01-06T10:51:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c60f9389-9892-4408-b5af-947fe7ca224d","owner":[],"postedDate":"January 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T16:11:38+00:00","versionOfRecord":{"articleIdentity":"rs-8475989","link":"https://doi.org/10.1186/s12882-026-04981-3","journal":{"identity":"bmc-nephrology","isVorOnly":false,"title":"BMC Nephrology"},"publishedOn":"2026-04-30 15:57:57","publishedOnDateReadable":"April 30th, 2026"},"versionCreatedAt":"2026-01-13 01:28:31","video":"","vorDoi":"10.1186/s12882-026-04981-3","vorDoiUrl":"https://doi.org/10.1186/s12882-026-04981-3","workflowStages":[]},"version":"v1","identity":"rs-8475989","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8475989","identity":"rs-8475989","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}