Comparison of 3D two-point Dixon and standard 2D dual-echo breath-hold sequences for detection and quantification of fat content in renal angiomyolipoma

Is there enough evidence supporting the clinical adoption of clear cell likelihood score (ccLS)? An updated systematic review and meta-analysis

OBJECTIVE

To review the evidence for clinical adoption of clear cell likelihood score (ccLS) for identifying clear cell renal cell carcinoma (ccRCC) from small renal masses (SRMs).

METHODS

We distinguished the literature on ccLS for identifying ccRCC via systematic search using PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and Wanfang Data until 31 March, 2024. The risk of bias and concern on application was assessed using the modified quality assessment of diagnostic accuracy studies (QUADAS-2) tool. The level of evidence supporting the clinical adoption of ccLS for identifying ccRCC was determined based on meta-analyses.

RESULTS

Eight MRI studies and three CT studies were included. The risk of bias and application were mainly related to the index test and flow and timing, due to incomplete imaging protocol, unclear rating process, and inappropriate interval between imaging and surgery. The diagnostic odds ratios (95% confidence intervals) of MRI and CT ccLS were 14.69 (9.71-22.22; 6 studies, 1429 SRM, 869 ccRCC), and 5.64 (3.34-9.54; 3 studies, 296 SRM, 147 ccRCC), respectively, for identifying ccRCC from SRM. The evidence level for clinical adoption of MRI and CT ccLS were both rated as weak. MRI ccLS version 2.0 potentially has better diagnostic performance than version 1.0 (1 study, 700 SRM, 509 ccRCC). Both T2-weighted-imaging with or without fat suppression might be suitable for MRI ccLS version 2.0 (1 study, 111 SRM, 82 ccRCC).

CONCLUSION

ccLS shows promising diagnostic performance for identifying ccRCC from SRM, but the evidence for its adoption in clinical routine remains weak.

CRITICAL RELEVANCE STATEMENT

Although clear cell likelihood score (ccLS) demonstrates promising performance for detecting clear cell renal cell carcinoma, additional evidence is crucial to support its routine use as a tool for both initial diagnosis and active surveillance of small renal masses.

KEY POINTS

Clear cell likelihood score is designed for the evaluation of small renal masses. Both CT and MRI clear cell likelihood scores are accurate and efficient. More evidence is necessary for the clinical adoption of a clear cell likelihood score.

In Vivo Renal Lipid Quantification by Accelerated Magnetic Resonance Spectroscopic Imaging at 3T: Feasibility and Reliability Study

A reliable and practical renal-lipid quantification and imaging method is needed. Here, the feasibility of an accelerated MRSI method to map renal fat fractions (FF) at 3T and its repeatability were investigated. A 2D density-weighted concentric-ring-trajectory MRSI was used for accelerating the acquisition of 48 × 48 voxels (each of 0.25 mL spatial resolution) without respiratory navigation implementations. The data were collected over 512 complex-FID timepoints with a 1250 Hz spectral bandwidth. The MRSI sequence was designed with a metabolite-cycling technique for lipid–water separation. The in vivo repeatability performance of the sequence was assessed by conducting a test–reposition–retest study within healthy subjects. The coefficient of variation (CV) in the estimated FF from the test–retest measurements showed a high degree of repeatability of MRSI-FF (CV = 4.3 ± 2.5%). Additionally, the matching level of the spectral signature within the same anatomical region was also investigated, and their intrasubject repeatability was also high, with a small standard deviation (8.1 ± 6.4%). The MRSI acquisition duration was ~3 min only. The proposed MRSI technique can be a reliable technique to quantify and map renal metabolites within a clinically acceptable scan time at 3T that supports the future application of this technique for the non-invasive characterization of heterogeneous renal diseases and tumors.

How We Do It: Managing the Indeterminate Renal Mass with the MRI Clear Cell Likelihood Score

The widespread use of cross-sectional imaging has led to a continuous increase in the number of incidentally detected indeterminate renal masses. Frequently, these clinical scenarios involve an older patient with comorbidities and a small renal mass (≤4 cm). Despite aggressive treatment in early stages of the disease, a clear positive effect in reducing kidney cancer-specific mortality is lacking, indicating that many renal cancers exhibit an indolent oncologic behavior. Furthermore, in general, one in five small renal masses is histologically benign and may not benefit from aggressive treatment. Although active surveillance is increasingly recognized as a management option for some patients, the absence of reliable clinical and imaging predictive biologic markers of aggressiveness can contribute to patient anxiety and limit its use in clinical practice. A standardized approach to the image interpretation of solid renal masses has not been broadly implemented. The clear cell likelihood score (ccLS) derived from multiparametric MRI is useful in noninvasively identifying the clear cell subtype, the most common and aggressive form of kidney cancer. Herein, a review of the ccLS is presented, including a step-by-step guide for image interpretation and additional guidance for its implementation in clinical practice.

Protocol Optimization for Renal Mass Detection and Characterization

Renal masses increasingly are found incidentally, largely due to the frequent use of medical imaging. Computed tomography (CT) and MR imaging are mainstays for renal mass characterization, presurgical planning of renal tumors, and surveillance after surgery or systemic therapy for advanced renal cell carcinomas. CT protocols should be tailored to different clinical indications, balancing diagnostic accuracy and radiation exposure. MR imaging protocols should take advantage of the improved soft tissue contrast for renal tumor diagnosis and staging. Optimized imaging protocols enable analysis of imaging features that help narrow the differential diagnoses and guide management in patients with renal masses.

New MRI series for kidney evaluation: Saving time and money

OBJECTIVES

This study investigates the diagnostic performance of a new T1 imaging series, generated by the digital subtraction of the opposed phase from in phase T ₁ weighted images, in MRI for renal angiomyolipoma (AML) evaluation.

METHODS

This retrospective study involved 96 patients, 63 (65.6%) with at least one renal AML and 33 (34.4%) healthy patients. Two radiologists having different experience retrospectively reviewed two MR imaging series, starting with in and out-phase T ₁ weighted images and then the new subtracted T1 images, in which AML appeared white on black background. The presence, number, location, and dimensions of the AMLs, and reading time were collected separately for the two kidneys. Statistical analysis was carried out using the appropriate tests.

RESULTS

The number of lesions identified and the evaluation of lesion dimension did not statistically differ between the different MR imaging series evaluated, without interobserver variability. Both percentage agreement of the total number of observations and the κ coefficient showed very good agreement between the radiologists. The median time for the diagnosis was statistically lower when using the subtracted T1 imaging series for both observers with a median gain from 6.5 to 15 s per identified lesion, resulting in a total time-saving of more than half (52.9%), in both patients with and without AMLs, and in patients with a single or with more than one AML (p < 0.001).

CONCLUSIONS

The new subtracted T1 imaging series proved to be reliable in identifying fat-containing renal lesions, by both expert and non-expert radiologists, resulting in a saving of both time and money. Moreover, this new subtracted T1 imaging series could be an effective tool in non-dedicated kidney examinations in which a faster reading is advisable.

ADVANCES IN KNOWLEDGE

The opportunity of using a single set of MRI images in kidney evaluation for identifying fat-containing lesions, considerably reducing reading time, resulting in cost-effectiveness.

Renal and adrenal masses containing fat at MRI: Proposed nomenclature by the society of abdominal radiology disease-focused panel on renal cell carcinoma

This article proposes a consensus nomenclature for fat-containing renal and adrenal masses at MRI to reduce variability, improve understanding, and enhance communication when describing imaging findings. The MRI appearance of "macroscopic fat" occurs due to a sufficient number of aggregated adipocytes and results in one or more of: 1) intratumoral signal intensity (SI) loss using fat-suppression techniques, or 2) chemical shift artifact of the second kind causing linear or curvilinear India-ink (etching) artifact within or at the periphery of a mass at macroscopic fat-water interfaces. "Macroscopic fat" is most commonly observed in adrenal myelolipoma and renal angiomyolipoma (AML) and only rarely encountered in other adrenal cortical tumors and renal cell carcinomas (RCC). Nonlinear noncurvilinear signal intensity loss on opposed-phase (OP) compared with in-phase (IP) chemical shift MRI (CSI) may be referred to as "microscopic fat" and is due to: a) an insufficient amount of adipocytes, or b) the presence of fat within tumor cells. Determining whether the signal intensity loss observed on CSI is due to insufficient adipocytes or fat within tumor cells cannot be accomplished using CSI alone; however, it can be inferred when other imaging features strongly suggest a particular diagnosis. Fat-poor AML are homogeneously hypointense on T₂ -weighted (T₂ W) imaging and avidly enhancing; signal intensity loss at OP CSI is uncommon, but when present is usually focal and is caused by an insufficient number of adipocytes within adjacent voxels. Conversely, clear-cell RCC are heterogeneously hyperintense on T₂ W imaging and avidly enhancing, with the signal intensity loss observed on OP CSI being typically diffuse and due to fat within tumor cells. Adrenal adenomas, adrenal cortical carcinoma, and adrenal metastases from fat-containing primary malignancies also show signal intensity loss on OP CSI due to fat within tumor cells and not from intratumoral adipocytes. Level of Evidence: 5 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019;49:917-926.

Determination of an Optimized Weighting Factor of Liver Parenchyma for Six-point Interference Dixon Fat Percentage Imaging Accuracy in Nonalcoholic Fatty Liver Disease Rat Model

RATIONALE AND OBJECTIVES

The aim of this study was to determine the optimal weighting factor (WF) for precise quantification using six-point interference Dixon fat percentage imaging by analyzing changes in WFs of fatty acid metabolites (FMs) in high-fat-induced fatty liver disease rat model.

MATERIALS AND METHODS

Individual FM-related WFs were calculated based on concentration ratios of integrated areas of seven peak FMs with four phantom series. Ten 8-week-old male Sprague-Dawley rats were used for baseline quantification of fat in liver magnetic resonance imaging or magnetic resonance spectroscopy data. These seven lipid metabolites were then quantitatively analyzed. Spearman test was used for correlation analysis of different lipid proton concentrations. The most accurate WF for six-point interference Dixon fat percentage imaging was then determined.

RESULTS

The seven lipid resonance WF values obtained from magnetic resonance spectroscopy data for three different oils (oleic, linoleic, and soybean) were different from each other. In lipid phantoms, except for the phantom containing oleic acid, changes in FP values were significantly different when WFs were changed in six-point interference Dixon fat percentage image. The seven lipid resonance WF values for the nonalcoholic fatty liver animal model were different from human subcutaneous adipose tissue lipid WF values.

CONCLUSIONS

WF affected the calculation of six-point interference Dixon-based fat percentage imaging value in phantom experiment. If WF of liver parenchyma FM which is specific to each liver disease is applied, the accuracy of six-point interference Dixon fat percentage imaging can be further increased.

Efficacy of 3D VIBE Dixon fat quantification for differentiating clear-cell from non-clear-cell renal cell carcinoma

AIM

To assess the efficacy of three-dimensional (3D) volumetric interpolated breath-hold examination (VIBE) magnetic resonance imaging (MRI) with Dixon quantification for differentiating clear-cell from non-clear-cell types of renal cell carcinoma (RCC).

MATERIALS AND METHODS

The 3D VIBE Dixon renal MRI examinations of 44 patients with 45 histologically confirmed RCCs was analysed. The fat fractions and signal intensity indexes (SI_index) of the solid portions of clear-cell and non-clear-cell RCCs were measured and compared using Student's t-test and receiver operating characteristic (ROC) curves. The agreement of measurements among observers was evaluated by the intraclass correlation coefficient (ICC), and Bland-Altman plots.

RESULTS

The mean values of fat fraction (13.16±7.16%) and SI_index (22.64±15.7%) in clear-cell RCCs were significantly higher than that in non-clear-cell RCCs (7.7±2% and 7.9±4.8%; p<0.001, respectively). With the area under the ROC curve (AUC) of the fat fraction at 0.811, 75% (95% CI: 55.1-89.43%) sensitivity and 76.5% (95% CI: 50.1-93.2%) specificity for diagnosing clear-cell RCC were obtained at a cut-off fat fraction value of 8.9%. With a cut-off value of 8.89%, the diagnostic sensitivity and specificity were 85.7% (95% CI: 67.3-96%) and 70.6% (95% CI: 44-89.7%), respectively. The AUC of the SI_index was 0.870 (0.766-0.973). ICC and Bland-Altman plots show excellent agreement of the tumour fat fraction and SI_index measurement between the two observers.

CONCLUSION

Intracellular lipid content analysis using the 3D Dixon technique can help to differentiate clear-cell from non-clear-cell RCCs.

Fat status detection and histotypes differentiation in solid renal masses using Dixon technique

PURPOSE

To detect fat status and differentiate histotypes of renal masses by using Dixon technique.

MATERIALS AND METHODS

This study included 134 solid renal masses. Signal intensity index (SII) and fat fraction (FF) in different histotypes were compared.

RESULTS

Only angiomyolipoma (AML), clear cell renal cell carcinoma (RCC), and papillary RCC were confirmed to contain fat. The FF of 16.8% can effectively differentiate AML from clear cell RCC, so did the SII of 9.2% can differentiate clear cell RCC from non-clear cell RCC and rare benign histotypes.

CONCLUSION

Dixon technique successfully evaluated the fat status and histotypes of renal masses.

Imaging and Screening of Kidney Cancer

Renal cell carcinoma (RCC) exhibits a diverse and heterogeneous disease spectrum, but insight into its molecular biology has provided an improved understanding of potential risk factors, oncologic behavior, and imaging features. Computed tomography (CT) and MR imaging may allow the identification and preoperative subtyping of RCC and assessment of a response to various therapies. Active surveillance is a viable management option in some patients and has provided further insight into the natural history of RCC, including the favorable prognosis of cystic neoplasms. This article reviews CT and MR imaging in RCC and the role of screening in selected high-risk populations.

Advances in T1-weighted and T2-weighted imaging in the abdomen and pelvis

Utilization of abdominopelvic MR imaging continues to increase in volume and gain widespread clinical acceptance. Many factors such as diaphragmatic respiratory motion, bulk patient motion, and the need for large volumetric coverage while maintaining clinically feasible scan times have proven challenging for body applications of MRI. However, many advances in MR acquisition, including non-Cartesian T1-weighted and T2-weighted acquisitions, advanced Dixon sequences, and 3-dimensional volumetric T2-weighted imaging have helped to mitigate some of the issues which have hampered abdominopelvic MR. This article will summarize these advances in T1-weighted and T2-weighted imaging, with an emphasis on clinical applications and implementation.

MRI phenotype in renal cancer: is it clinically relevant?

Renal cell carcinoma (RCC) is most commonly diagnosed as an incidental finding on cross-sectional imaging and represents a significant clinical challenge. Although most patients have a surgically curable lesion at the time of diagnosis, the variability in the biologic behavior of the different histologic subtypes and tumor grade of RCC, together with the increasing array of management options, creates uncertainty for the optimal clinical approach to individual patients. State-of-the-art magnetic resonance imaging (MRI) provides a comprehensive assessment of renal lesions that includes multiple forms of tissue contrast as well as functional parameters, which in turn provides information that helps to address this dilemma. In this article, we review this evolving and increasingly comprehensive role of MRI in the detection, characterization, perioperative evaluation, and assessment of the treatment response of renal neoplasms. We emphasize the ability of the imaging "phenotype" of renal masses on MRI to help predict the histologic subtype, grade, and clinical behavior of RCC.

Renal relevant radiology: renal functional magnetic resonance imaging

Because of its noninvasive nature and provision of quantitative measures of a wide variety of physiologic parameters, functional magnetic resonance imaging (MRI) shows great potential for research and clinical applications. Over the past decade, application of functional MRI extended beyond detection of cerebral activity, and techniques for abdominal functional MRI evolved. Assessment of renal perfusion, glomerular filtration, interstitial diffusion, and parenchymal oxygenation turned this modality into an essential research and potentially diagnostic tool. Variations in many renal physiologic markers can be detected using functional MRI before morphologic changes become evident in anatomic magnetic resonance images. Moreover, the framework of functional MRI opened a window of opportunity to develop novel pathophysiologic markers. This article reviews applications of some well validated functional MRI techniques, including perfusion, diffusion-weighted imaging, and blood oxygen level-dependent MRI, as well as some emerging new techniques such as magnetic resonance elastography, which might evolve into clinically useful tools.