Reproducibility of native T1 mapping for renal tissue characterization at 3T

Native T1 mapping for non-invasive quantitative evaluation of renal function and renal fibrosis in patients with chronic kidney disease

Background

To investigate the role of native T1 mapping in the non-invasive quantitative assessment of renal function and renal fibrosis (RF) in chronic kidney disease (CKD) patients.

Methods

A prospective analysis of 71 consecutive patients [no RF (0%): 9 cases; mild RF (<25%): 36 cases; moderate RF (25-50%): 17 cases; severe RF (>50%): 9 cases] who were clinically diagnosed with CKD that was pathologically confirmed and who underwent magnetic resonance imaging (MRI) examination between October 2021 and September 2022 was performed. T1-C (mean cortical T1 value), T1-M (mean medullary T1 value), ΔT1 (mean corticomedullary difference) and T1% (mean corticomedullary ratio) values were compared. Correlations between T1 parameters and clinical and histopathological values were analyzed. Regression analysis was performed to determine independent predictors of RF. The areas under the receiver operating characteristic curve (AUC) were calculated to assess the diagnostic value of RF.

Results

The T1-C, ΔT1 and T1% values (P<0.05) were significantly different in the CKD group, but T1-M was not (P>0.05). The ΔT1 and T1% values showed significant differences in pairwise comparisons among CKD subgroups (P<0.05) except for CKD 2 and 3. ΔT1 and T1% were moderately correlated with the estimated glomerular filtration rate (ΔT1: rs=-0.561; T1%: r=-0.602), serum creatinine (ΔT1: rs=0.591; T1%: rs=0.563), blood urea nitrogen (ΔT1: rs=0.433; T1%: rs=0.435) and histopathological score (ΔT1: rs=0.630; T1%: rs=0.658). ΔT1 and T1%, but not T1-C, were independent predictors of RF (P<0.05). ΔT1 and T1% were set as -410.07 ms and 0.8222 with great specificity [ΔT1: 91.7% (77.5-98.2%); T1%: 97.2% (85.5-99.9%)] to identify mild RF and moderate-severe RF. The optimal cutoff values for differentiating severe RF from mild-moderate RF were -343.81 ms (ΔT1) and 0.8359 (T1%) with high sensitivity [both 100% (66.4-100%)] and specificity [ΔT1: 90.6% (79.3-96.9%); T1%: 94.3% (84.3-98.8%)].

Conclusions

ΔT1 and T1% overwhelm T1-C for assessment of renal function and RF in CKD patients. ΔT1 and T1% identify patients with <25% and >50% fibrosis, which can guide clinical decision-making and help to avoid biopsy-related bleeding.

Renal Assessment in Acute Cardiorenal Syndrome

Cardiorenal syndrome (CRS) is a complex, heterogeneous spectrum of symptoms that has kept cardiologists awake for decades. The heart failure (HF) population being burdened with multimorbidity poses diagnostic and therapeutic challenges even for experienced clinicians. Adding deteriorated renal function to the equation, which is one of the strongest predictors of adverse outcome, we measure ourselves against possibly the biggest problem in modern cardiology. With the rapid development of new renal assessment methods, we can treat CRS more effectively than ever. The presented review focuses on explaining the pathophysiology, recent advances and current practices of monitoring renal function in patients with acute CRS. Understanding the dynamic interaction between the heart and the kidney may improve patient care and support the selection of an effective and nephroprotective treatment strategy.

Native T1 Mapping and Magnetization Transfer Imaging in Grading Bowel Fibrosis in Crohn's Disease: A Comparative Animal Study

In this study, we investigated the utility of native T₁ mapping in differentiating between various grades of fibrosis and compared its diagnostic accuracy to magnetization transfer imaging (MTI) in a rat model of CD. Bowel specimens (64) from 46 CD model rats undergoing native T₁ mapping and MTI were enrolled. The longitudinal relaxation time (T₁ value) and normalized magnetization transfer ratio (MTR) were compared between none-to-mild and moderate-to-severe fibrotic bowel walls confirmed by pathological assessments. The results showed that the correlation between the T₁ value and fibrosis (r = 0.438, p < 0.001) was lower than that between the normalized MTR and fibrosis (r = 0.623, p < 0.001). Overall, the T₁ values (t = −3.066, p = 0.004) and normalized MTRs (z = 0.081, p < 0.001) in none-to-mild fibrotic bowel walls were lower than those in moderate-to-severe fibrotic bowel walls. The area under the curve (AUC) of the T₁ value (AUC = 0.716, p = 0.004) was significantly lower than that of the normalized MTR (AUC = 0.881, p < 0.001) in differentiating moderate-to-severe fibrosis from none-to-mild fibrosis (z = −2.037, p = 0.042). Our results support the view that the T₁ value could be a promising imaging biomarker in grading the fibrosis severity of CD. However, the diagnostic performance of native T₁ mapping was not superior to MTI.

Cardiorenal Syndrome: Emerging Role of Medical Imaging for Clinical Diagnosis and Management

Cardiorenal syndrome (CRS) concerns the interconnection between heart and kidneys in which the dysfunction of one organ leads to abnormalities of the other. The main clinical challenges associated with cardiorenal syndrome are the lack of tools for early diagnosis, prognosis, and evaluation of therapeutic effects. Ultrasound, computed tomography, nuclear medicine, and magnetic resonance imaging are increasingly used for clinical management of cardiovascular and renal diseases. In the last decade, rapid development of imaging techniques provides a number of promising biomarkers for functional evaluation and tissue characterization. This review summarizes the applicability as well as the future technological potential of each imaging modality in the assessment of CRS. Furthermore, opportunities for a comprehensive imaging approach for the evaluation of CRS are defined.

B1 -Corrected T1 Mapping in Lung Cancer: Repeatability, Reproducibility, and Identification of Histological Types

BACKGROUND

T1 mapping can potentially quantitatively assess the intrinsic properties of tumors. B₁ correction can reduce the magnetic field inhomogeneity.

PURPOSE

To assess the repeatability and reproducibility of B₁ -corrected T1 mapping for lung cancer and the ability to identify pathological types.

STUDY TYPE

Prospective reproducibility study.

POPULATION

Sixty lung cancer patients (22 with emphysema) with a total of 60 lesions (adenocarcinoma [n = 23], squamous cell carcinoma [n = 19], and small-cell lung cancer [SCLC] [n = 18]).

FIELD STRENGTH/SEQUENCE

A 3 T/B₁ -corrected 3D variable flip angle T1 mapping and free-breathing diffusion-weighted imaging.

ASSESSMENT

Intraobserver, interobserver, and test-retest reproducibility of minimum, maximum, mean, and SD of lung tumor T1 values were assessed. The correlation between mean T1 and apparent diffusion coefficient (ADC) and differences between different histological types of lung cancer were evaluated.

STATISTICAL TESTS

Intraclass correlation coefficients (ICCs), within-subject coefficients of variation (WCVs), Bland-Altman plots, Pearson's correlation coefficient (r), and analysis of variance (ANOVA). A P value <0.05 was considered to be statistically significant.

RESULTS

No significant differences were found in minimum, maximum, mean, and SD T1 values for repeated measurements (intraobserver and interobserver) and repeated examinations (P = 0.103-0.979). All parameters showed good intraobserver, interobserver and test-retest reproducibility (ICC, 0.780-0.978), except the maximum T1 value (ICC, 0.645-0.922). The mean T1 exhibited the best reproducibility and repeatability, with an average difference <6% for repeated measurements, <8% for repeated scans in lung cancer patients, and<10% for repeated scans in those with emphysema. The mean T1 correlated moderately with ADC (r = -0.580, -0.516, and -0.511 for observers A, B, and C). Both mean T1 and mean ADC were significantly different in SCLC patients compared with those in adenocarcinoma and squamous cell carcinoma patients.

DATA CONCLUSION

The mean T1 from B₁ -corrected T1 mapping is a repeatable parameter with the potential to identify histological types of lung cancer and thus may be a promising imaging biomarker for characterizing lung cancer.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Rapid B1-Insensitive MR Fingerprinting for Quantitative Kidney Imaging

Background MR fingerprinting (MRF) provides rapid and simultaneous quantification of multiple tissue parameters in a single scan. Purpose To evaluate a rapid kidney MRF technique at 3.0 T in phantoms, healthy volunteers, and patients. Materials and Methods A 15-second kidney MRF acquisition was designed with 12 acquisition segments, a range of low flip angles (5°-12°), multiple magnetization preparation schema (T1, T2, and fat suppression), and an undersampled spiral trajectory. This technique was first validated in vitro using standardized T1 and T2 phantoms. Kidney T1 and T2 maps were then obtained for 10 healthy adult volunteers (mean age ± standard deviation, 35 years ± 13; six men) and three pediatric patients with autosomal recessive polycystic kidney disease (ARPKD) (mean age, 10 years ± 3; two boys) between August 2019 and October 2020 to evaluate the method in vivo. Results Results in nine phantoms showed good agreement with spin-echo-based T1 and T2 values (R² > 0.99). In vivo MRF kidney T1 and T2 assessments in healthy adult volunteers (cortex: T1, 1362 msec ± 5; T2, 64 msec ± 5; medulla: T1, 1827 msec ± 94; T2, 69 msec ± 3) were consistent with values in the literature but with improved precision in comparison with prior MRF implementations. In vivo MRF-based kidney T1 and T2 values with and without B₁ correction were in good agreement (R² > 0.96, P < .001), demonstrating limited sensitivity to B₁ field inhomogeneities. Additional MRF reconstructions using the first nine segments of the MRF profiles (11-second acquisition time) were in good agreement with the reconstructions using 12 segments (15-second acquisition time) (R² > 0.87, P < .001). Repeat kidney MRF scans for the three patients with ARPKD on successive days also demonstrated good reproducibility (T1 and T2: <3% difference). Conclusion A kidney MR fingerprinting method provided in vivo kidney T1 and T2 maps at 3.0 T in a single breath hold with improved precision and no need for B₁ correction. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Laustsen in this issue.

Advanced non-invasive diagnostic techniques for visualization and estimation of kidney fibrosis

Kidney fibrosis is marked by excessive extracellular matrix deposition during disease progression. Unfortunately, existing kidney function parameters do not predict the extent of kidney fibrosis. Moreover, the traditional histology methods for the assessment of kidney fibrosis require liquid and imaging biomarkers as well as needle-based biopsies, which are invasive and often associated with kidney injury. The repetitive analyses required to monitor the disease progression are therefore difficult. Hence, there is an unmet medical need for non-invasive and informative diagnostic approaches to monitor kidney fibrosis during the progression of chronic kidney disease. Here, we summarize the modern advances in diagnostic imaging techniques that have shown promise for non-invasive estimation of kidney fibrosis in pre-clinical and clinical studies.

Recent advances in medical image processing for the evaluation of chronic kidney disease

Assessment of renal function and structure accurately remains essential in the diagnosis and prognosis of Chronic Kidney Disease (CKD). Advanced imaging, including Magnetic Resonance Imaging (MRI), Ultrasound Elastography (UE), Computed Tomography (CT) and scintigraphy (PET, SPECT) offers the opportunity to non-invasively retrieve structural, functional and molecular information that could detect changes in renal tissue properties and functionality. Currently, the ability of artificial intelligence to turn conventional medical imaging into a full-automated diagnostic tool is widely investigated. In addition to the qualitative analysis performed on renal medical imaging, texture analysis was integrated with machine learning techniques as a quantification of renal tissue heterogeneity, providing a promising complementary tool in renal function decline prediction. Interestingly, deep learning holds the ability to be a novel approach of renal function diagnosis. This paper proposes a survey that covers both qualitative and quantitative analysis applied to novel medical imaging techniques to monitor the decline of renal function. First, we summarize the use of different medical imaging modalities to monitor CKD and then, we show the ability of Artificial Intelligence (AI) to guide renal function evaluation from segmentation to disease prediction, discussing how texture analysis and machine learning techniques have emerged in recent clinical researches in order to improve renal dysfunction monitoring and prediction. The paper gives a summary about the role of AI in renal segmentation.

Multiparametric Renal MRI: An Intrasubject Test-Retest Repeatability Study

Background

Renal multiparametric magnetic resonance imaging (MRI) is a promising tool for diagnosis, prognosis, and treatment monitoring in kidney disease.

Purpose

To determine intrasubject test–retest repeatability of renal MRI measurements.

Study Type

Prospective.

Population

Nineteen healthy subjects aged over 40 years.

Field Strength/Sequences

T₁ and T₂ mapping, R₂* mapping or blood oxygenation level‐dependent (BOLD) MRI, diffusion tensor imaging (DTI), and intravoxel incoherent motion (IVIM) diffusion‐weighted imaging (DWI), 2D phase contrast, arterial spin labelling (ASL), dynamic contrast enhanced (DCE) MRI, and quantitative Dixon for fat quantification at 3T.

Assessment

Subjects were scanned twice with ~1 week between visits. Total scan time was ~1 hour. Postprocessing included motion correction, semiautomated segmentation of cortex and medulla, and fitting of the appropriate signal model.

Statistical Test

To assess the repeatability, a Bland–Altman analysis was performed and coefficients of variation (CoVs), repeatability coefficients, and intraclass correlation coefficients were calculated.

Results

CoVs for relaxometry (T₁, T₂, R₂*/BOLD) were below 6.1%, with the lowest CoVs for T₂ maps and highest for R₂*/BOLD. CoVs for all diffusion analyses were below 7.2%, except for perfusion fraction (F_P), with CoVs ranging from 18–24%. The CoV for renal sinus fat volume and percentage were both around 9%. Perfusion measurements were most repeatable with ASL (cortical perfusion only) and 2D phase contrast with CoVs of 10% and 13%, respectively. DCE perfusion had a CoV of 16%, while single kidney glomerular filtration rate (GFR) had a CoV of 13%. Repeatability coefficients (RCs) ranged from 7.7–87% (lowest/highest values for medullary mean diffusivity and cortical F_P, respectively) and intraclass correlation coefficients (ICCs) ranged from −0.01 to 0.98 (lowest/highest values for cortical F_P and renal sinus fat volume, respectively).

Data Conclusion

CoVs of most MRI measures of renal function and structure (with the exception of F_P and perfusion as measured by DCE) were below 13%, which is comparable to standard clinical tests in nephrology.

Level of Evidence

2

Technical Efficacy

Stage 1

Consensus-based technical recommendations for clinical translation of renal T1 and T2 mapping MRI

To develop technical recommendations on the acquisition and post-processing of renal longitudinal (T1) and transverse (T2) relaxation time mapping. A multidisciplinary panel consisting of 18 experts in the field of renal T1 and T2 mapping participated in a consensus project, which was initiated by the European Cooperation in Science and Technology Action PARENCHIMA CA16103. Consensus recommendations were formulated using a two-step modified Delphi method. The first survey consisted of 56 items on T1 mapping, of which 4 reached the pre-defined consensus threshold of 75% or higher. The second survey was expanded to include both T1 and T2 mapping, and consisted of 54 items of which 32 reached consensus. Recommendations based were formulated on hardware, patient preparation, acquisition, analysis and reporting. Consensus-based technical recommendations for renal T1 and T2 mapping were formulated. However, there was considerable lack of consensus for renal T1 and particularly renal T2 mapping, to some extent surprising considering the long history of relaxometry in MRI, highlighting key knowledge gaps that require further work. This paper should be regarded as a first step in a long-term evidence-based iterative process towards ever increasing harmonization of scan protocols across sites, to ultimately facilitate clinical implementation.

Consensus-based technical recommendations for clinical translation of renal T1 and T2 mapping MRI

To develop technical recommendations on the acquisition and post-processing of renal longitudinal (T1) and transverse (T2) relaxation time mapping. A multidisciplinary panel consisting of 18 experts in the field of renal T1 and T2 mapping participated in a consensus project, which was initiated by the European Cooperation in Science and Technology Action PARENCHIMA CA16103. Consensus recommendations were formulated using a two-step modified Delphi method. The first survey consisted of 56 items on T1 mapping, of which 4 reached the pre-defined consensus threshold of 75% or higher. The second survey was expanded to include both T1 and T2 mapping, and consisted of 54 items of which 32 reached consensus. Recommendations based were formulated on hardware, patient preparation, acquisition, analysis and reporting. Consensus-based technical recommendations for renal T1 and T2 mapping were formulated. However, there was considerable lack of consensus for renal T1 and particularly renal T2 mapping, to some extent surprising considering the long history of relaxometry in MRI, highlighting key knowledge gaps that require further work. This paper should be regarded as a first step in a long-term evidence-based iterative process towards ever increasing harmonization of scan protocols across sites, to ultimately facilitate clinical implementation.

Clinical application and technical considerations of T1 & T2(*) mapping in cardiac, liver, and renal imaging

Pathological tissue alterations due to disease processes such as fibrosis, edema and infiltrative disease can be non-invasively visualized and quantified by MRI using T₁ and T₂ relaxation properties. Pixel-wise mapping of T₁ and T₂ image sequences enable direct quantification of T₁, T₂(*), and extracellular volume values of the target organ of interest. Tissue characterization based on T₁ and T₂(*) mapping is currently making the transition from a research tool to a clinical modality, as clinical usefulness has been established for several diseases such as myocarditis, amyloidosis, Anderson-Fabry and iron deposition. Other potential clinical applications besides the heart include, quantification of steatosis, cirrhosis, hepatic siderosis and renal fibrosis. Here, we provide an overview of potential clinical applications of T₁ andT₂(*) mapping for imaging of cardiac, liver and renal disease. Furthermore, we give an overview of important technical considerations necessary for clinical implementation of quantitative parametric imaging, involving data acquisition, data analysis, quality assessment, and interpretation. In order to achieve clinical implementation of these techniques, standardization of T₁ and T₂(*) mapping methodology and validation of impact on clinical decision making is needed.