Presentation of microstructural diffusion components by color schemes in abdominal organs.

PURPOSE: Development of a color scheme representation to facilitate the interpretation of tri-exponential DWI data from abdominal organs, where multi-exponential behavior is more pronounced. METHODS: Multi-exponential analysis of DWI data provides information about the microstructure of the tissue under study. The tri-exponential signal analysis generates numerous parameter images that are difficult to analyze individually. Summarized color images can simplify at-a-glance analysis. A color scheme was developed in which the slow, intermediate, and fast diffusion components were each assigned to a different red, green, and blue color channel. To improve the appearance of the image, histogram equalization, gamma correction, and white balance were used, and the processing parameters were adjusted. Examples of the resulting color maps of the diffusion fractions of healthy and pathological kidney and prostate are shown. RESULTS: The color maps obtained by the presented method show the merged information of the slow, intermediate, and fast diffusion components in a single view. A differentiation of the different fractions becomes clearly visible. Fast diffusion regimes, such as in the renal hilus, can be clearly distinguished from slow fractions, such as in dense tumor tissue. CONCLUSION: Combining the diffusion information from tri-exponential DWI analysis into a single color image allows for simplified interpretation of the diffusion fractions. In the future, such color images may provide additional information about the microstructural nature of the tissue under study.

Disease Course and Pulmonary Involvement of COVID-19 during the Delta Variant Period in Germany: A Comparative Study of Vaccinated and Unvaccinated Patients at a Tertiary Hospital.

Background: Despite the availability of vaccines, there is an increasing number of SARS-CoV-2-breakthrough-infections. OBJECTIVE: The aim of this study was to determine whether there is a radiological difference in lung parenchymal involvement between infected vaccinated and unvaccinated patients. Additionally, we aimed to investigate whether vaccination has an impact on the course of illness and the need for intensive care. METHODS: This study includes all patients undergoing chest computed tomography (CT) or x-ray imaging in case of a proven SARS-CoV-2 infection between September and November 2021. Anonymized CT and x-ray images were reviewed retrospectively and in consensus by two radiologists, applying an internal severity score scheme for CT and x-ray as well as CARE and BRIXIA scores for x-ray. Radiological findings were compared to vaccination status, comorbidities, inpatient course of the patient's illness and the subjective onset of symptoms. RESULTS: In total, 38 patients with acute SARS-CoV-2 infection underwent a CT scan, and 168 patients underwent an x-ray examination during the study period. Of these, 32% were vaccinated in the CT group, and 45% in the x-ray group. For the latter, vaccinated patients exhibited significantly more comorbidities (cardiovascular (p=0.002), haemato-oncological diseases (p=0.016), immunosuppression (p=0.004)), and a higher age (p<0.001). Vaccinated groups showed significantly lower extent of lung involvement (severity scores in CT cohort and x-ray cohort both p≤0.020; ARDS 42% in unvaccinated CT cohort vs. 8% in vaccinated CT cohort). Furthermore, vaccinated patients in the CT cohort had significantly less need for intensive care treatment (p=0.040). CONCLUSION: Our data suggest that vaccination, in the case of breakthrough infection, favours a milder course of illness concerning lung parenchymal involvement and the need for intensive care, despite negative predictors, such as immunosuppression or other pre-existing conditions.

Probing Renal Microstructure and Function with Advanced Diffusion MRI: Concepts, Applications, Challenges, and Future Directions.

Diffusion measurements in the kidney are affected not only by renal microstructure but also by physiological processes (i.e., glomerular filtration, water reabsorption, and urine formation). Because of the superposition of passive tissue diffusion, blood perfusion, and tubular pre-urine flow, the limitations of the monoexponential apparent diffusion coefficient (ADC) model in assessing pathophysiological changes in renal tissue are becoming apparent and motivate the development of more advanced diffusion-weighted imaging (DWI) variants. These approaches take advantage of the fact that the length scale probed in DWI measurements can be adjusted by experimental parameters, including diffusion-weighting, diffusion gradient directions and diffusion time. This forms the basis by which advanced DWI models can be used to capture not only passive diffusion effects, but also microcirculation, compartmentalization, tissue anisotropy. In this review, we provide a comprehensive overview of the recent advancements in the field of renal DWI. Following a short introduction on renal structure and physiology, we present the key methodological approaches for the acquisition and analysis of renal DWI data, including intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), non-Gaussian diffusion, and hybrid IVIM-DTI. We then briefly summarize the applications of these methods in chronic kidney disease and renal allograft dysfunction. Finally, we discuss the challenges and potential avenues for further development of renal DWI. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Influence of tube and patient positioning in thoracoabdominal CT examinations on radiation exposure-towards a better patient positioning.

Although iso-centric patient positioning is enormously important in computed tomography (CT), it is complicated in thoracoabdominal imaging by the varying dimensions of the body. Patient positioning can affect the appearance of the patient on the localiser. Positioned too close to the x-ray tube, a patient appears considerably more voluminous. The goal of this study is to assess the difference in radiation exposure of combined chest and abdomen CT scans between scans with prior 0°- and 180°-localisers in conjunction with patient positioning. In this IRB-approved retrospective study, patients who had two routine thoracoabdominal CT scans on the same CT scanner, one with a prior 0°- and one with a prior 180°-localiser, were included. To evaluate the radiation exposure of the thoracoabdominal CT examination regarding the tube position during the localiser, volumetric computed tomography dose index (CTDIvol), size-specific dose estimate (SSDE), patient diameter and positioning within the iso-centre for three positions (heart, abdomen, femur level) were compared with regard to the tube position during the prior localiser. CT examinations of 114 patients were included. Despite similar patient weight and diameter between the two examinations, SSDE and CTDIvolwas significantly larger (up to 73%) with 180°-localisers. Patient offset from the iso-centre ranged between -9 mm at the centre slice (abdomen level) to -43 mm at the most caudal slice at the pelvis (femur level), causing a significant magnification (p < 0.001) on 180°-localisers with a subsequent increase of the apparent attenuation. The results of this study emphasise the use of 0°-localisers in thoracoabdominal CTs, since 180°-localisers caused patient magnification with subsequent increase in radiation exposure. The advantage of 180°-localisers, namely reducing the dose in thyroid and breast, is eliminated if the dose of the CT scan increases significantly in the abdomen and pelvis.

calf - Software for CEST Analysis with Lorentzian Fitting.

Analysis of chemical exchange saturation transfer (CEST) MRI data requires sophisticated methods to obtain reliable results about metabolites in the tissue under study. CEST generates z-spectra with multiple components, each originating from individual molecular groups. The individual lines with Lorentzian line shape are mostly overlapping and disturbed by various effects. We present an elaborate method based on an adaptive nonlinear least squares algorithm that provides robust quantification of z-spectra and incorporates prior knowledge in the fitting process. To disseminate CEST to the research community, we developed software as part of this study that runs on the Microsoft Windows operating system and will be made freely available to the community. Special attention has been paid to establish a low entrance threshold and high usability, so that even less experienced users can successfully analyze CEST data.

J-difference GABA-edited MRS reveals altered cerebello-thalamo-cortical metabolism in patients with hepatic encephalopathy.

Hepatic encephalopathy (HE) is a common neurological manifestation of liver cirrhosis and is characterized by an increase of ammonia in the brain accompanied by a disrupted neurotransmitter balance, including the GABAergic and glutamatergic systems. The aim of this study is to investigate metabolic abnormalities in the cerebello-thalamo-cortical system of HE patients using GABA-edited MRS and links between metabolite levels, disease severity, critical flicker frequency (CFF), motor performance scores, and blood ammonia levels. GABA-edited MRS was performed in 35 participants (16 controls, 19 HE patients) on a clinical 3 T MRI system. MRS voxels were placed in the right cerebellum, left thalamus, and left motor cortex. Levels of GABA+ and of other metabolites of interest (glutamine, glutamate, myo-inositol, glutathione, total choline, total NAA, and total creatine) were assessed. Group differences in metabolite levels and associations with clinical metrics were tested. GABA+ levels were significantly increased in the cerebellum of patients with HE. GABA+ levels in the motor cortex were significantly decreased in HE patients, and correlated with the CFF (r = 0.73; p < .05) and motor performance scores (r = -0.65; p < .05). Well-established HE-typical metabolite patterns (increased glutamine, decreased myo-inositol and total choline) were confirmed in all three regions and were closely linked to clinical metrics. In summary, our findings provide further evidence for alterations in the GABAergic system in the cerebellum and motor cortex in HE. These changes were accompanied by characteristic patterns of osmolytes and oxidative stress markers in the cerebello-thalamo-cortical system. These metabolic disturbances are a likely contributor to HE motor symptoms in HE. In patients with hepatic encephalopathy, GABA+ levels in the cerebello-thalamo-cortical loop are significantly increased in the cerebellum and significantly decreased in the motor cortex. GABA+ levels in the motor cortex strongly correlate with critical flicker frequency (CFF) and motor performance score (pegboard test tPEG), but not blood ammonia levels (NH3).

Image downsampling expedited adaptive least-squares (IDEAL) fitting improves intravoxel incoherent motion (IVIM) analysis in the human kidney.

PURPOSE: To improve the reliability of intravoxel incoherent motion (IVIM) model parameter estimation for the DWI in the kidney using a novel image downsampling expedited adaptive least-squares (IDEAL) approach. METHODS: The robustness of IDEAL was investigated using simulated DW-MRI data corrupted with different levels of Rician noise. Subsequently, the performance of the proposed method was tested by fitting bi- and triexponential IVIM model to in vivo renal DWI data acquired on a clinical 3 Tesla MRI scanner and compared to conventional approaches (fixed D* and segmented fitting). RESULTS: The numerical simulations demonstrated that the IDEAL algorithm provides robust estimates of the IVIM parameters in the presence of noise (SNR of 20) as indicated by relatively low absolute percentage bias (maximal sMdPB <20%) and normalized RMSE (maximal RMSE <28%). The analysis of the in vivo data showed that the IDEAL-based IVIM parameter maps were less noisy and more visually appealing than those obtained using the fixed D* and segmented methods. Further, coefficients of variation for nearly all IVIM parameters were significantly reduced in cortex and medulla for IDEAL-based biexponential (coefficients of variation: 4%-50%) and triexponential (coefficients of variation: 7.5%-75%) IVIM modelling compared to the segmented (coefficients of variation: 4%-120%) and fixed D* (coefficients of variation: 17%-174%) methods, reflecting greater accuracy of this method. CONCLUSION: The proposed fitting algorithm yields more robust IVIM parameter estimates and is less susceptible to poor SNR than the conventional fitting approaches. Thus, the IDEAL approach has the potential to improve the reliability of renal DW-MRI analysis for clinical applications.

Influence of a Deep Learning Noise Reduction on the CT Values, Image Noise and Characterization of Kidney and Ureter Stones.

Deep-learning (DL) noise reduction techniques in computed tomography (CT) are expected to reduce the image noise while maintaining the clinically relevant information in reduced dose acquisitions. This study aimed to assess the size, attenuation, and objective image quality of reno-ureteric stones denoised using DL-software in comparison to traditionally reconstructed low-dose abdominal CT-images and evaluated its clinical impact. In this institutional review-board-approved retrospective study, 45 patients with renal and/or ureteral stones were included. All patients had undergone abdominal CT between August 2019 and October 2019. CT-images were reconstructed using the following three methods: filtered back-projection, iterative reconstruction, and PixelShine (DL-software) with both sharp and soft kernels. Stone size, CT attenuation, and objective image quality (signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)) were evaluated and compared using Bonferroni-corrected Friedman tests. Objective image quality was measured in six regions-of-interest. Stone size ranged between 4.4 × 3.1−4.4 × 3.2 mm (sharp kernel) and 5.1 × 3.8−5.6 × 4.2 mm (soft kernel). Mean attenuation ranged between 704−717 Hounsfield Units (HU) (soft kernel) and 915−1047 HU (sharp kernel). Differences in measured stone sizes were ≤1.3 mm. DL-processed images resulted in significantly higher CNR and SNR values (p < 0.001) by decreasing image noise significantly (p < 0.001). DL-software significantly improved objective image quality while maintaining both correct stone size and CT-attenuation values. Therefore, the clinical impact of stone assessment in denoised image data sets remains unchanged. Through the relevant noise suppression, the software additionally offers the potential to further reduce radiation exposure.

Chemical Exchange Saturation Transfer for Lactate-Weighted Imaging at 3 T MRI: Comprehensive In Silico, In Vitro, In Situ, and In Vivo Evaluations.

Based on in silico, in vitro, in situ, and in vivo evaluations, this study aims to establish and optimize the chemical exchange saturation transfer (CEST) imaging of lactate (Lactate-CEST­LATEST). To this end, we optimized LATEST sequences using Bloch−McConnell simulations for optimal detection of lactate with a clinical 3 T MRI scanner. The optimized sequences were used to image variable lactate concentrations in vitro (using phantom measurements), in situ (using nine human cadaveric lower leg specimens), and in vivo (using four healthy volunteers after exertional exercise) that were then statistically analyzed using the non-parametric Friedman test and Kendall Tau-b rank correlation. Within the simulated Bloch−McConnell equations framework, the magnetization transfer ratio asymmetry (MTRasym) value was quantified as 0.4% in the lactate-specific range of 0.5−1 ppm, both in vitro and in situ, and served as the imaging surrogate of the lactate level. In situ, significant differences (p < 0.001) and strong correlations (τ = 0.67) were observed between the MTRasym values and standardized intra-muscular lactate concentrations. In vivo, a temporary increase in the MTRasym values was detected after exertional exercise. In this bench-to-bedside comprehensive feasibility study, different lactate concentrations were detected using an optimized LATEST imaging protocol in vitro, in situ, and in vivo at 3 T, which prospectively paves the way towards non-invasive quantification and monitoring of lactate levels across a broad spectrum of diseases.

CT Findings in Patients with COVID-19-Compatible Symptoms but Initially Negative qPCR Test.

PURPOSE: To assess whether it is possible to reliably detect patients with strong suspicion of COVID-19 despite initially negative quantitative polymerase-chain-reaction (qPCR) tests by means of computed tomography (CT). MATERIALS AND METHODS: 437 patients with suspected COVID-19 but initially negative qPCR and subsequent chest CT between March 13 and November 30, 2020 were included in this retrospective study. CT findings were compared to results of successive qPCR tests (minimum of 3 qPCR tests if CT suggested infection) to determine the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of CT for diagnosing COVID-19. RESULTS: COVID-19 was diagnosed correctly with a sensitivity of 100 % [95 % confidence interval (CI): 65-100] and a specificity of 88 % [95 % CI: 84-90]. A PPV of 12 % [95 % CI: 6-22] and an NPV of 100 % [95 % CI: 99-100] were determined. CONCLUSION: CT is able to detect COVID-19 before qPCR in initially negative patients in this special study setting. Similar CT findings in COVID-19 and other atypical pneumonias can lead to high numbers of false-positive patients, reducing the specificity of CT. KEY POINTS: · Low-dose chest CT is able to diagnose COVID-19 in symptomatic patients even in cases of an initially negative quantitative PCR result and therefore is a fast support method to detect COVID-19, especially in early disease.. · Low-dose chest CT can reliably exclude COVID-19 in a pandemic setting.. · CT does not always ensure a reliable differentiation from other viral diseases.. CITATION FORMAT: · Valentin B, Steuwe A, Wienemann T, et al. CT Findings in Patients with COVID-19-Compatible Symptoms but Initially Negative qPCR Test. Fortschr Röntgenstr 2022; 194: 1110 - 1118.

Two point Dixon-based chemical exchange saturation transfer (CEST) MRI in renal transplant patients on 3 T.

PURPOSE: To assess the performance of two point (2-pt) Dixon-based chemical exchange saturation transfer (CEST) imaging for fat suppression in renal transplant patients. METHODS: The 2-pt Dixon-based CEST MRI was validated in an egg-phantom and in fourteen renal transplant recipients (5 females and 9 males; age range: 23-78 years; mean age: 51 ± 16.8). All CEST experiments were performed on a 3 T clinical MRI scanner using a dual-echo CEST sequence. The 2-pt Dixon technique was applied to generate water-only CEST images at different frequency offsets, which were further used to calculate the z-spectra. The magnetization transfer ratio asymmetry (MTRasym) values in the frequency ranges of hydroxyl, amine and amide protons were estimated in the renal cortex and medulla. RESULTS: Results of the in vitro experiments suggest that the 2-pt Dixon technique enables effective fat peak removal and does not introduce additional asymmetries to the z-spectrum. Accordingly, our results in vivo show that the fat-corrected amide proton transfer (APT) effect in the kidney is significantly higher compared to that obtained from the CEST data acquired close to the in-phase condition both in the renal cortex (-0.1 [0.7] vs. -0.7 [1.2], P = 0.029) and medulla (0.3 [0.8] vs. 0.01 [1.3], P = 0.049), indicating that the 2-pt Dixon-based CEST method increases the specificity of the APT contrast by correcting the fat-induced artifacts. CONCLUSION: Combination of the dual-echo CEST acquisition with Dixon post-processing provides effective water-fat separation, allowing more accurate quantification of the APT CEST effect in the transplanted kidney.

Applicability of CO-RADS in an Anonymized Cohort Including Early and Advanced Stages of COVID-19 in Comparison to the Recommendations of the German Radiological Society and Radiological Society of North America.

PURPOSE: Classifications were created to facilitate radiological evaluation of the novel coronavirus disease 2019 (COVID-19) on computed tomography (CT) images. The categorical CT assessment scheme (CO-RADS) categorizes lung parenchymal changes according to their likelihood of being caused by SARS-CoV-2 infection. This study investigates the diagnostic accuracy of diagnosing COVID-19 with CO-RADS compared to the Thoracic Imaging Section of the German Radiological Society (DRG) classification and Radiological Society of North America (RSNA) classification in an anonymized patient cohort. To mimic advanced disease stages, follow-up examinations were included as well. METHOD: This study includes all patients undergoing chest CT in the case of a suspected SARS-CoV-2 infection or an already confirmed infection between March 13 and November 30, 2020. During the study period, two regional lockdowns occurred due to high incidence values, increasing the pre-test probability of COVID-19. Anonymized CT images were reviewed retrospectively and in consensus by two radiologists applying CO-RADS, DRG, and RSNA classification. Afterwards, CT findings were compared to results of sequential real-time reverse transcriptase polymerase chain reaction (qPCR) test performed during hospitalization to determine statistical analysis for diagnosing COVID-19. RESULTS: 536 CT examinations were included. CO-RADS, DRG and RSNA achieved an NPV of 96 %/94 %/95 % (CO-RADS/DRG/RSNA), PPV of 83 %/80 %/88 %, sensitivity of 86 %/76 %/80 %, and specificity of 96 %/95 %/97 %. The disease prevalence was 20 %. CONCLUSION: All applied classifications can reliably exclude a SARS-CoV-2 infection even in an anonymous setting. Nevertheless, pre-test probability was high in our study setting and has a great influence on the classifications. Therefore, the applicability of the individual classifications will become apparent in the future with lower prevalence and incidence of COVID-19. KEY POINTS: · CO-RADS, DRG, and RSNA classifications help to reliably detect infected patients in an anonymized setting. · Pre-test probability has a great influence on the individual classifications. · Difficulties in an anonymized study setting are severe pulmonary changes and residuals.. CITATION FORMAT: · Valentin B, Steuwe A, Wienemann T et al. Applicability of CO-RADS in an Anonymized Cohort Including Early and Advanced Stages of COVID-19 in Comparison to the Recommendations of the German Radiological Society and Radiological Society of North America. Fortschr Röntgenstr 2022; 194: 862 - 872.

Evaluation of Radiographic Contrast-Induced Nephropathy by Functional Diffusion Weighted Imaging.

Contrast-induced nephropathy (CIN) resembles an important complication of radiographic contrast medium (XCM) displayed by a rise in creatinine levels 48-72 h after XCM administration. The purpose of the current study was to evaluate microstructural renal changes due to CIN in high-risk patients by diffusion weighted (DWI) and diffusion tensor imaging (DTI). Fifteen patients (five CIN and ten non-CIN) scheduled for cardiological intervention were included in the study. All patients were investigated pre- and post-intervention on a clinical 3T scanner. After anatomical imaging, renal DWI was performed by a paracoronal echo-planar-imaging sequence. Renal clinical routine serum parameters and advanced urinary injury markers were determined to monitor renal function. We observed a drop in cortical and medullar apparent diffusion coefficient (ADC) and fractional anisotropy (FA) before and after XCM administration in the CIN group. In contrast, the non-CIN group differed only in medullary ADC. The decrease of ADC and FA was apparent even before serum parameters of the kidney changed. In conclusion, DWI/DTI may be a useful tool for monitoring high-risk CIN patients as part of multi-modality based clinical protocol. Further studies, including advanced analysis of the diffusion signal, may improve the identification of patients at risk for CIN.

Renal Diffusion-Weighted Imaging (DWI) for Apparent Diffusion Coefficient (ADC), Intravoxel Incoherent Motion (IVIM), and Diffusion Tensor Imaging (DTI): Basic Concepts.

The specialized function of the kidney is reflected in its unique structure, characterized by juxtaposition of disorganized and ordered elements, including renal glomerula, capillaries, and tubules. The key role of the kidney in blood filtration, and changes in filtration rate and blood flow associated with pathological conditions, make it possible to investigate kidney function using the motion of water molecules in renal tissue. Diffusion-weighted imaging (DWI) is a versatile modality that sensitizes observable signal to water motion, and can inform on the complexity of the tissue microstructure. Several DWI acquisition strategies are available, as are different analysis strategies, and models that attempt to capture not only simple diffusion effects, but also perfusion, compartmentalization, and anisotropy. This chapter introduces the basic concepts of DWI alongside common acquisition schemes and models, and gives an overview of specific DWI applications for animal models of renal disease.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.

Spectral diffusion analysis of kidney intravoxel incoherent motion MRI in healthy volunteers and patients with renal pathologies.

PURPOSE: To assess the feasibility of measuring tubular and vascular signal fractions in the human kidney using nonnegative least-square (NNLS) analysis of intravoxel incoherent motion data collected in healthy volunteers and patients with renal pathologies. METHODS: MR imaging was performed at 3 Tesla in 12 healthy subjects and 3 patients with various kidney pathologies (fibrotic kidney disease, failed renal graft, and renal masses). Relative signal fractions f and mean diffusivities of the diffusion components in the cortex, medulla, and renal lesions were obtained using the regularized NNLS fitting of the intravoxel incoherent motion data. Test-retest repeatability of the NNLS approach was tested in 5 volunteers scanned twice. RESULTS: In the healthy kidneys, the NNLS method yielded diffusion spectra with 3 distinguishable components that may be linked to the slow tissue water diffusion, intermediate tubular and vascular flow, and fast blood flow in larger vessels with the relative signal fractions, fslow , finterm and ffast , respectively. In the pathological kidneys, the diffusion spectra varied substantially from those acquired in the healthy kidneys. Overall, the renal cyst showed substantially higher finterm and lower fslow , whereas the fibrotic kidney, failed renal graft, and renal cell carcinoma demonstrated the opposite trend. CONCLUSION: NNLS-based intravoxel incoherent motion could potentially become a valuable tool in assessing changes in tubular and vascular volume fractions under pathophysiological conditions.

Detection of early cartilage degeneration in the tibiotalar joint using 3 T gagCEST imaging: a feasibility study.

OBJECTIVE: To establish and optimize a stable 3 Tesla (T) glycosaminoglycan chemical exchange saturation transfer (gagCEST) imaging protocol for assessing the articular cartilage of the tibiotalar joint in healthy volunteers and patients after a sustained injury to the ankle. METHODS: Using Bloch-McConnell simulations, we optimized the sequence protocol for a 3 T MRI scanner for maximum gagCEST effect size within a clinically feasible time frame of less than 07:30 min. This protocol was then used to analyze the gagCEST effect of the articular cartilage of the tibiotalar joint of 17 healthy volunteers and five patients with osteochondral lesions of the talus following ankle trauma. Reproducibility was tested with the intraclass correlation coefficient. RESULTS: The mean magnetization transfer ratio asymmetry (MTRasym), i.e., the gagCEST effect size, was significantly lower in patients than in healthy volunteers (0.34 ± 1.9% vs. 1.49 ± 0.11%; p < 0.001 [linear mixed model]). Intra- and inter-rater reproducibility was excellent with an average measure intraclass correlation coefficient (ICC) of 0.97 and a single measure ICC of 0.91 (p < 0.01). DISCUSSION: In this feasibility study, pre-morphological tibiotalar joint cartilage damage was quantitatively assessable on the basis of the optimized 3 T gagCEST imaging protocol that allowed stable quantification gagCEST effect sizes across a wide range of health and disease in clinically feasible acquisition times.