Diffusion magnetic resonance imaging for kidney cyst volume quantification and non-cystic tissue characterisation in ADPKD
Creators
- 1. Clinical Research Center for Rare Diseases "Aldo & Cele Daccò", Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Via Camozzi 3, 24020, Bergamo, Ranica (Italy)
- 2. Department of Diagnostic Radiology, Azienda Socio-Sanitaria Territoriale Papa Giovanni XXIII, Bergamo (Italy)
- 3. Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield (United Kingdom)
- 4. School of Medicine, University of Milano-Bicocca, Milan (Italy)
- 5. Department of Management, Information and Production Engineering, University of Bergamo, Dalmine, BG (Italy)
Description
Beyond total kidney and cyst volume (TCV), non-cystic tissue plays an important role in autosomal dominant polycystic kidney disease (ADPKD) progression. This study aims at presenting and preliminarily validating a diffusion MRI (DWI)-based TCV quantification method and providing evidence of DWI potential in characterising non-cystic tissue microstructure. T2-weighted MRI and DWI scans (b = 0, 15, 50, 100, 200, 350, 500, 700, 1000; 3 directions) were acquired from 35 ADPKD patients with CKD stage 1 to 3a and 15 healthy volunteers on a 1.5 T scanner. ADPKD classification was performed using the Mayo model. DWI scans were processed by mono- and segmented bi-exponential models. TCV was quantified on T2-weighted MRI by the reference semi-automatic method and automatically computed by thresholding the pure diffusivity (D) histogram. The agreement between reference and DWI-based TCV values and the differences in DWI-based parameters between healthy and ADPKD tissue components were assessed. There was strong correlation between DWI-based and reference TCV (rho = 0.994, p < 0.001). Non-cystic ADPKD tissue had significantly higher D, and lower pseudo-diffusion and flowing fraction than healthy tissue (p < 0.001). Moreover, apparent diffusion coefficient and D values significantly differed by Mayo imaging class, both in the whole kidney (Wilcoxon p = 0.007 and p = 0.004) and non-cystic tissue (p = 0.024 and p = 0.007). DWI shows potential in ADPKD to quantify TCV and characterise non-cystic kidney tissue microstructure, indicating the presence of microcysts and peritubular interstitial fibrosis. DWI could complement existing biomarkers for non-invasively staging, monitoring, and predicting ADPKD progression and evaluating the impact of novel therapies, possibly targeting damaged non-cystic tissue besides cyst expansion. This study shows diffusion-weighted MRI (DWI) potential to quantify total cyst volume and characterise non-cystic kidney tissue microstructure in ADPKD. DWI could complement existing biomarkers for non-invasively staging, monitoring, and predicting ADPKD progression and evaluating the impact of novel therapies, possibly targeting damaged non-cystic tissue besides cyst expansion. Diffusion magnetic resonance imaging shows potential to quantify total cyst volume in ADPKD. Diffusion magnetic resonance imaging might allow to non-invasively characterise non-cystic kidney tissue microstructure. Diffusion magnetic resonance imaging-based biomarkers significantly differ by Mayo imaging class, suggesting their possible prognostic value.
Availability note (English)
Available from: http://dx.doi.org/10.1007/s00330-023-09601-4Additional details
Identifiers
Publishing Information
- Journal Title
- European Radiology (Internet)
- Journal Volume
- 33
- Journal Issue
- 9
- Journal Page Range
- p. 6009-6019
- ISSN
- 1432-1084
- CODEN
- EURAE3
INIS
- Country of Publication
- Germany
- Country of Input or Organization
- Germany
- INIS RN
- 54098060
- Subject category
- S62: RADIOLOGY AND NUCLEAR MEDICINE;
- Descriptors DEI
- AUTOMATION; BIOLOGICAL MARKERS; CLASSIFICATION; CORRELATIONS; CYSTS; DATA COMPILATION; DIFFUSION; FIBROSIS; IMAGE PROCESSING; KIDNEYS; MICROSTRUCTURE; NMR IMAGING; RELAXATION TIME; THERAPY; UROGENITAL SYSTEM DISEASES; VOLUME; WEIGHTING FUNCTIONS
- Descriptors DEC
- BODY; DATA; DATA PROCESSING; DIAGNOSTIC TECHNIQUES; DISEASES; FUNCTIONS; INFORMATION; MEDICINE; ORGANS; PATHOLOGICAL CHANGES; PROCESSING