Susceptibility weighted imaging (SWI) of the kidney at 3T--initial results

Quantitative susceptibility mapping for detection of kidney stones, hemorrhage differentiation, and cyst classification in ADPKD

BACKGROUND AND PURPOSE

The objective is to demonstrate feasibility of quantitative susceptibility mapping (QSM) in autosomal dominant polycystic kidney disease (ADPKD) patients and to compare imaging findings with traditional T1/T2w magnetic resonance imaging (MRI).

METHODS

Thirty-three consecutive patients (11 male, 22 female) diagnosed with ADPKD were initially selected. QSM images were reconstructed from the multiecho gradient echo data and compared to co-registered T2w, T1w, and CT images. Complex cysts were identified and classified into distinct subclasses based on their imaging features. Prevalence of each subclass was estimated.

RESULTS

QSM visualized two renal calcifications measuring 9 and 10 mm and three pelvic phleboliths measuring 2 mm but missed 24 calcifications measuring 1 mm or less and 1 larger calcification at the edge of the field of view. A total of 121 complex T1 hyperintense/T2 hypointense renal cysts were detected. 52 (43%) Cysts appeared hyperintense on QSM consistent with hemorrhage; 60 (49%) cysts were isointense with respect to simple cysts and normal kidney parenchyma, while the remaining 9 (7%) were hypointense. The presentation of the latter two complex cyst subtypes is likely indicative of proteinaceous composition without hemorrhage.

CONCLUSION

Our results indicate that QSM of ADPKD kidneys is possible and uniquely suited to detect large renal calculi without ionizing radiation and able to identify properties of complex cysts unattainable with traditional approaches.

The value of functional magnetic resonance imaging in the evaluation of diabetic kidney disease: a systematic review and meta-analysis

Background

The diversity of clinical trajectories in diabetic kidney disease (DKD) has made blood and biochemical urine markers less precise, while renal puncture, the gold standard, is almost impossible in the assessment of diabetic kidney disease, and the value of functional magnetic resonance imaging in the evaluation of diabetic pathological alterations is increasingly recognized.

Methods

The literature on functional magnetic resonance imaging (fMRI) for the assessment of renal alterations in diabetic kidney disease was searched in PubMed, Web of Science, Cochrane Library, and Embase databases. The search time limit is from database creation to March 10, 2023. RevMan was used to perform a meta-analysis of the main parameters of fMRIs extracted from DKD patients and healthy volunteers (HV).

Results

24 publications (1550 subjects) were included in this study, using five functional MRIs with seven different parameters. The renal blood flow (RBF) values on Arterial spin labeling magnetic resonance imaging (ASL-MRI) was significantly lower in the DKD group than in the HV group. The [WMD=-99.03, 95% CI (-135.8,-62.27), P<0.00001]; Diffusion tensor imaging magnetic resonance imaging (DTI-MRI) showed that the fractional anisotropy (FA) values in the DKD group were significantly lower than that in HV group [WMD=-0.02, 95%CI (-0.03,-0.01), P<0.0001]. And there were no statistically significant differences in the relevant parameters in Blood oxygen level-dependent magnetic resonance imaging (BOLD-MRI) or Intro-voxel incoherent movement magnetic resonance imaging (IVIM-DWI).

Discussion

ASL and DWI can identify the differences between DKD and HV. DTI has a significant advantage in assessing renal cortical changes; IVIM has some value in determining early diabetic kidney disease from the cortex or medulla. We recommend combining multiple fMRI parameters to assess structural or functional changes in the kidney to make the assessment more comprehensive. We did not observe a significant risk of bias in the present study.

Systematic review registration

https://www.crd.york.ac.uk, identifier CRD42023409249.

The role of MRI texture analysis based on susceptibility-weighted imaging in predicting Fuhrman grade of clear cell renal cell carcinoma

BACKGROUND

The Fuhrman nuclear grade system is one of the most important independent indicators in patients with clear cell renal cell carcinoma (ccRCC) for aggressiveness and prognosis. Preoperative assessment of tumor aggressiveness is important for surgical decision-making.

PURPOSE

To explore the role of magnetic resonance imaging (MRI) texture analysis based on susceptibility-weighted imaging (SWI) in predicting Fuhrman grade of ccRCC.

MATERIAL AND METHODS

A total of 45 patients with SWI and surgically proven ccRCC were divided into two groups: the low-grade group (Fuhrman I/II, n = 29) and the high-grade group (Fuhrman III/IV, n = 16). Texture features were extracted from SWI images. Feature selection was performed, and multivariable logistic regression analysis was performed to develop the SWI-based texture model for grading ccRCCs. Receiver operating characteristic (ROC) curve analysis and leave-group-out cross-validation (LGOCV) were performed to test the reliability of the model.

RESULTS

A total of 396 SWI-based texture features were extracted from each SWI image. The SWI-based texture model developed by multivariable logistic regression analysis was: SWIscore = -0.59 + 1.60 * ZonePercentage. The area under the ROC curve of the SWI-based texture model for differentiating high-grade ccRCC from low-grade ccRCC was 0.81 (95% confidence interval 0.67-0.94), with 80% accuracy, 56.25% sensitivity, and 93.10% specificity. After 100 LGOCVs, the mean accuracy, sensitivity, and specificity were 90.91%, 91.83%, and 89.89% for the training sets, and 77.29%, 80.52%, and 71.44% for the test sets, respectively.

CONCLUSION

SWI-based texture analysis might be a reliable quantitative approach for differentiating high-grade ccRCC from low-grade ccRCC.

Susceptibility weighted imaging (SWI) for evaluating renal dysfunction in type 2 diabetes mellitus: a preliminary study using SWI parameters and SWI-based texture features

Background

Susceptibility weighted imaging (SWI) could reflect tissue blood oxygen levels, and then whether it could be used to evaluate renal injury remains to be further studied. This study aimed to examine the performance of SWI parameters and SWI-based texture features in evaluating renal dysfunction of type 2 diabetes mellitus (T2DM).

Methods

Forty-five patients with T2DM were included. With the estimated glomerular filtration rate (eGFR), the patients were divided into non-moderate-severe renal injured group (non-msRI, eGFR >60 mL/min/1.73 m²) and moderate-severe renal injured group (msRI, eGFR ≤60 mL/min/1.73 m²). The 3 SWI parameters and 16 SWI-based texture features between non-msRI and msRI were compared. The correlation between the parameters and BUN, Scr was analyzed.

Results

The signal intensity ratio of the medulla to psoas muscle (MPswi) was significantly lower than the signal intensity ratio of the cortex to psoas muscle (CPswi) in non-msRI and msRI group (t=8.619, 3.483, respectively, P<0.05). MPswi was higher, and the signal intensity ratio of the cortex to the medulla (CMswi), Skewness, Correlation were lower in msRI than in non-msRI (P<0.05). These parameters showed similar diagnostic efficacies for msRI (P>0.05), and AUCs were 0.703–0.854. CMswi was an independent protective factor for msRI (OR =0.026, P=0.003). MPswi and CMswi were correlated with BUN (r=0.416, −0.545, P<0.05). CMswi and Correlation were correlated with Scr (r=−0.645, −0.411, P<0.05).

Conclusions

SWI was valuable for assessing renal dysfunction, which may be helpful for the evaluation of moderate-severe renal injured patients with T2DM.

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.

Assessment of delayed graft function using susceptibility-weighted imaging in the early period after kidney transplantation: a feasibility study

PURPOSE

This study aimed to explore the feasibility of susceptibility-weighted imaging (SWI) for evaluating delayed graft function (DGF) during the early posttransplantation period.

METHODS

Sixty-nine recipients who accepted allograft renal transplantation underwent SWI during the second posttransplantation week. Renal allograft function was estimated via the glomerular filtration rate. Recipients with and without DGF were identified. For each transplanted kidney, the presence of abnormal signal intensity lesions (ASILs), excluding benign lesions, on SWI was assessed. Renal allograft function was compared between the recipients with and without ASILs. The correlation between ASILs and renal allograft function was tested by Spearman's rank correlation analysis.

RESULTS

Thirty-four recipients were diagnosed with DGF, while 35 recipients showed no DGF. In the DGF group, 16 recipients had low-intensity ASILs, primarily at the corticomedullary junction of transplanted kidneys on SWI, and no ASILs were found in 18 recipients. In the non-DGF group, none of the recipients showed ASILs on SWI. In the DGF group, the renal allograft function among the 16 recipients with low-intensity ASILs was significantly lower than that among the other 18 recipients (8.5 ± 4.2 vs. 19.7 ± 9.7 mL/min, P < 0.001). The presence of low-intensity ASILs on SWI showed a moderate negative correlation with renal allograft function in recipients with DGF (r = - 0.553, P = 0.001).

CONCLUSION

SWI can be used to evaluate DGF in the early post-kidney transplantation period.

Evaluation of renal dysfunction using texture analysis based on DWI, BOLD, and susceptibility-weighted imaging

OBJECTIVE

To explore the value of texture analysis based on diffusion-weighted imaging (DWI), blood oxygen level-dependent MRI (BOLD), and susceptibility-weighted imaging (SWI) in evaluating renal dysfunction.

METHODS

Seventy-two patients (mean age 53.72 ± 13.46 years) underwent MRI consisting of DWI, BOLD, and SWI. According to their estimated glomerular filtration rate (eGFR), the patients were classified into either severe renal function impairment (sRI, eGFR < 30 mL/min/1.73 m²), non-severe renal function impairment (non-sRI, eGFR ≥ 30 mL/min/1.73 m², and < 80 mL/min/1.73 m²), or control (CG, eGFR ≥ 80 mL/min/1.73 m²) groups. Thirteen texture features were extracted and then were analyzed to select the most valuable for discerning the three groups with each imaging method. A ROC curve was performed to compare the capacities of the features to differentiate non-sRI from sRI or CG.

RESULTS

Six features proved to be the most valuable for assessing renal dysfunction: 0.25Quantile_DWI, 0.5Quantile_DWI, Homogeneity_DWI, Entropy_BOLD, Skewness_SWI, and Correlation_SWI. Three features derived from DWI (0.25Quantile_DWI, 0.5Quantile_DWI, and Homogeneity_DWI) were smaller in sRI than in non-sRI; Entropy_BOLD and Correlation_SWI were smaller in non-sRI than in CG (p < 0.05). 0.25Quantile_DWI, 0.5Quantile_DWI, and Homogeneity_DWI showed similar capacities for differentiating sRI from non-sRI. Similarly, Entropy_BOLD and Correlation_SWI showed equal capacities for differentiating non-sRI from CG.

CONCLUSION

Texture analysis based on DWI, BOLD, and SWI can assist in assessing renal dysfunction, and texture features based on BOLD and SWI may be suitable for assessing renal dysfunction during early stages.

KEY POINTS

• Texture analysis based on MRI techniques allowed for assessing renal dysfunction. • Texture features based on BOLD and SWI, but not DWI, may be suitable for assessing renal function impairment during early stages. • SWI exhibited a similar capacity to BOLD for assessing renal dysfunction.

Susceptibility-weighted imaging: current status and future directions

Susceptibility-weighted imaging (SWI) is a method that uses the intrinsic nature of local magnetic fields to enhance image contrast in order to improve the visibility of various susceptibility sources and to facilitate diagnostic interpretation. It is also the precursor to the concept of the use of phase for quantitative susceptibility mapping (QSM). Nowadays, SWI has become a widely used clinical tool to image deoxyhemoglobin in veins, iron deposition in the brain, hemorrhages, microbleeds and calcification. In this article, we review the basics of SWI, including data acquisition, data reconstruction and post-processing. In particular, the source of cusp artifacts in phase images is investigated in detail and an improved multi-channel phase data combination algorithm is provided. In addition, we show a few clinical applications of SWI for the imaging of stroke, traumatic brain injury, carotid vessel wall, siderotic nodules in cirrhotic liver, prostate cancer, prostatic calcification, spinal cord injury and intervertebral disc degeneration. As the clinical applications of SWI continue to expand both in and outside the brain, the improvement of SWI in conjunction with QSM is an important future direction of this technology. Copyright © 2016 John Wiley & Sons, Ltd.

Improving detection of siderotic nodules in patients with liver disease using 2D ESWAN technique

RATIONALE AND OBJECTIVES

To conduct a preliminary evaluation of the use of two-dimensional (2D) enhanced multiecho T2*-weighted angiography (ESWAN) sequence for detection and quantification of siderotic nodules (SNs) in patients with liver disease.

MATERIALS AND METHODS

Seventy-four patients with liver cirrhosis SNs confirmed by pathology were imaged using conventional T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), T2*-weighted imaging (T2*WI), and 2D ESWAN. The signal intensity ratio (SIR) and the lesion-to-liver contrast-to-noise ratio (CNR) were calculated. The quality of SNs identification of the ESWAN images was evaluated.

RESULTS

The SIR of SNs on ESWAN was lower than those in any other sequence, whereas the CNR of SNs on ESWAN was significantly greater than those in the other sequences (P < .05). The conspicuity of SNs was shown to be significantly different between every pair of techniques (P < .05). The nodules had the better conspicuity in ESWAN images than in the T1WI, T2WI, and T2*WI. Almost all (97.3%, 72 of 74) patients were considered to have excellent grade 3 conspicuity on ESWAN imaging, compared to 40.5% (30 of 74) for T2*WI. The signal intensity of small hepatic cancer on ESWAN was greater than those of SNs.

CONCLUSIONS

The detection and conspicuity of SNs is substantially improved using breath-hold 2D ESWAN. Therefore, 2D ESWAN imaging may be an alternative for the accurate detection of hepatic SNs in the future.

Susceptibility-weighted imaging for the noncontrast evaluation of hepatocellular carcinoma: a prospective study with histopathologic correlation

BACKGROUND

Specific morphologic features of hepatocellular carcinoma (HCC) on imaging have identifiable pathologic correlates as well as implications for altering surgical management and defining prognosis. In this study, we compared susceptibility-weighted imaging (SWI) to conventional techniques and correlated our findings with histopathology to determine the role of SWI in assessing morphologic features of HCC without using a contrast agent.

METHODS

86 consecutive patients with suspected HCC were imaged with MRI (including T1, T2, T2*, and SWI) and subsequently CT. 59 histologically-proven HCC lesions were identified in 53 patients. Each lesion on each imaging sequence was evaluated by two radiologists, and classified with respect to lesion morphology, signal intensity relative to surrounding hepatic parenchyma, presence of a pseudocapsule, presence of venous invasion, and internal homogeneity.

RESULTS

Histopathology confirmed pseudocapsules in 41/59 lesions. SWI was able to detect a pseudocapsule in 34/41 lesions; compared to conventional T1/T2 imaging (12/41) and T2* (27/41). Mosaic pattern was identified in 25/59 lesions by histopathology; SWI confirmed this in all 25 lesions, compared to T1/T2 imaging (13/25) or T2* (18/25). Hemorrhage was confirmed by histopathology in 43/59 lesions, and visible on SWI in 41/43 lesions, compared to T1/T2 (7/43) and T2* (38/43). Venous invasion was confirmed by histopathology in 31/59 patients; SWI demonstrated invasion in 28/31 patients, compared to T1/T2 (7/31) and T2* (24/31).

CONCLUSIONS

SWI is better at identifying certain morphologic features such as pseudocapsule and hemorrhage than conventional MRI without using a contrast agent in HCC patients.

Characterizing venous vasculatures of hepatocellular carcinoma using a multi-breath-hold two-dimensional susceptibility weighted imaging

The aim of our study is to characterize the venous vasculatures of hepatocellular carcinoma (HCC) using a multi-breath-hold two-dimensional (2D) susceptibility weighted imaging (SWI) in comparison with conventional Magnetic Resonance Imaging (MRI) sequences. Twenty-nine patients with pathologically confirmed HCC underwent MR examination at a 3.0 T scanner. The number of venous vascularity in or around the lesion was counted and the image quality was subjectively evaluated by two experienced radiologists independently based on four image sets: 1) SWI, 2) T1-weighted sequence, 3) T2-weighted sequence, and 4) T1-weighted dynamic contrast-enhanced (DCE) sequence. Of the 29 patients, a total of 33 liver lesions were detected by both SWI and conventional MR sequences. In the evaluation of the conspicuity of venous vascularity, a mean of 10.7 tumor venous vessels per mass was detected by the SWI and 3.9 tumor vasculatures were detected by T1-weighted DCE (P<0.0001), while none was detected by T1-, T2-weighted sequences. The Pearson correlation coefficients between the lesion sizes and the number of tumor vasculatures detected by T1-weighted DCE was 0.708 (P<0.001), and 0.883 by SWI (P<0.001). Our data suggest that SWI appears to be a more sensitive tool compared to T1-weighted DCE sequence to characterize venous vasculature in liver lesions.

Comparing anisotropic diffusion filters for the enhancement of sodium magnetic resonance images

The anisotropic diffusion (AND) filter, an image processing technique derived from physics, was applied to low-resolution sodium magnetic resonance imaging (MRI) to examine the possibilities of image enhancement by postprocessing. We compared six different variants of AND filters. Besides the qualitative good results on phantom measurements, quantitative analyses on MRI of human kidney yielded major improvements in noise reduction and other quality measures: the noise (i.e., the standard deviation in the image background) could be reduced to 1%-2% of its original value, while linear filters (Gaussian, Fermi, Hamming) achieved a reduction to 42%-64%. Besides that, less than 5% of structures and intensities are lost when using AND filters. Comparing the different variants, the two-dimensional and the three-dimensional AND filter outperformed the histogram-of-gradient and tensor-based AND filter. We envision that by using these AND filters, quantitative analysis of sodium MRI of kidney could be improved.