Lipid in renal clear cell carcinoma: detection on opposed-phase gradient-echo MR images

Scientific Status Quo of Small Renal Lesions: Diagnostic Assessment and Radiomics

Background: Small renal masses (SRMs) are defined as contrast-enhanced renal lesions less than or equal to 4 cm in maximal diameter, which can be compatible with stage T1a renal cell carcinomas (RCCs). Currently, 50-61% of all renal tumors are found incidentally. Methods: The characteristics of the lesion influence the choice of the type of management, which include several methods SRM of management, including nephrectomy, partial nephrectomy, ablation, observation, and also stereotactic body radiotherapy. Typical imaging methods available for differentiating benign from malignant renal lesions include ultrasound (US), contrast-enhanced ultrasound (CEUS), computed tomography (CT), and magnetic resonance imaging (MRI). Results: Although ultrasound is the first imaging technique used to detect small renal lesions, it has several limitations. CT is the main and most widely used imaging technique for SRM characterization. The main advantages of MRI compared to CT are the better contrast resolution and tissue characterization, the use of functional imaging sequences, the possibility of performing the examination in patients allergic to iodine-containing contrast medium, and the absence of exposure to ionizing radiation. For a correct evaluation during imaging follow-up, it is necessary to use a reliable method for the assessment of renal lesions, represented by the Bosniak classification system. This classification was initially developed based on contrast-enhanced CT imaging findings, and the 2019 revision proposed the inclusion of MRI features; however, the latest classification has not yet received widespread validation. Conclusions: The use of radiomics in the evaluation of renal masses is an emerging and increasingly central field with several applications such as characterizing renal masses, distinguishing RCC subtypes, monitoring response to targeted therapeutic agents, and prognosis in a metastatic context.

Assessment of Imaging Findings of Renal Carcinoma Subtypes with 3.0T MRI

BACKGROUND

The prevalence of renal masses has escalated as a result of the augmented utilization of cross-sectional imaging techniques. The approach to managing renal masses may exhibit variability contingent upon the subtype of renal cell carcinoma (RCC).

AIM

This research aimed to distinguish between clear cell and papillary RCCs, utilizing dynamic contrast magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI).

MATERIALS AND METHODS

The study assessed the MR images of 112 patients with RCC. Two radiologists independently analyzed tumor size, vascular involvement, signal characteristics in T1- and T2-weighted sequences, the presence of hemosiderin, both microscopic and macroscopic fat content, enhancement patterns, and apparent diffusion coefficient (ADC) values derived from b-values of 1000 s/mm².

RESULTS

Seventy patients had clear cell RCC, and 42 had papillary. In the clear cell RCC, microscopic fat content was significantly higher than the papillary RCC (P < 0.001). However, in papillary RCC, hemosiderin content was substantially greater (P = 0.001). On T2-weighted MR images, clear cell RCCs were usually hyperintense, while papillary RCCs were hypointense (P < 0.001). Even though the rapid enhancement pattern was observed in clear cell RCCs, the progressive enhancement pattern was more prevalent in papillary RCCs (P < 0.001).

CONCLUSION

Hyperintensity on T2-weighted images, microscopic fat content, and rapid enhancement pattern may be indicative of clear cell RCC, whereas hypointensity on T2-weighted images, hemosiderin content, and a progressive contrast pattern may be diagnostic for papillary RCC.

Differentiation of renal masses with multi-parametric MRI: the de Silva St George classification scheme

Purpose

To develop a system for multi-parametric MRI to differentiate benign from malignant solid renal masses and assess its accuracy compared to the gold standard of histopathological diagnosis.

Methods

This is a retrospective analysis of patients who underwent 3 Tesla mpMRI for further assessment of small renal tumours with specific scanning and reporting protocol incorporating T2 HASTE signal intensity, contrast enhancement ratios, apparent diffusion coefficient and presence of microscopic/macroscopic fat. All MRIs were reported prior to comparison with histopathologic diagnosis and a reporting scheme was developed. 2 × 2 contingency table analysis (sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV)), Fisher Exact test were used to assess the association between suspicion of malignancy on mpMRI and histopathology, and descriptive statistics were performed.

Results

67 patients were included over a 5-year period with a total of 75 renal masses. 70 masses were confirmed on histopathology (five had pathognomonic findings for angiomyolipomas; biopsy was therefore considered unethical, so these were included without histopathology). Three patients were excluded due to a non-diagnostic result, non-standardised imaging and one found to be an organising haematoma rather than a mass. Therefore 72 cases were included in analysis (in 64 patients, with seven patients having multiple tumours). Unless otherwise specified, all further statistics refer to individual tumours rather than patients. 52 (72.2%) were deemed ‘suspicious or malignant’ and 20 (27.8%) were deemed ‘benign’ on mpMRI. 51 cases (70.8%) had renal cell carcinoma confirmed. The sensitivity, NPV, specificity and PPV for MRI for detecting malignancy were 96.1%, 90%, 85.7% and 94.2% respectively, Fisher’s exact test demonstrated p < 0.0001 for the association between suspicion of malignancy on MRI and histopathology.

Conclusion

The de Silva St George classification scheme performed well in differentiating benign from malignant solid renal masses, and may be useful in predicting the likelihood of malignancy to determine the need for biopsy/excision. Further validation is required before this reporting system can  be recommended for clinical use.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12894-022-01082-9.

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.

ACR Appropriateness Criteria® Adrenal Mass Evaluation: 2021 Update

The appropriate evaluation of adrenal masses is strongly dependent on the clinical circumstances in which it is discovered. Adrenal incidentalomas are masses that are discovered on imaging studies that have been obtained for purposes other than adrenal disease. Although the vast majority of adrenal incidentalomas are benign, further radiological and biochemical evaluation of these lesions is important to arrive at a specific diagnosis. Patients with a history of malignancy or symptoms of excess hormone require different imaging evaluations than patients with incidentalomas. This document reviews imaging approaches to adrenal masses and the various modalities utilized in evaluation of adrenal lesions. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Solid renal masses in adults

With the ever increasing trend of using cross-section imaging in today's era, incidental detection of small solid renal masses has dramatically multiplied. Coincidentally, the number of asymptomatic benign lesions being detected has also increased. The role of radiologists is not only to identify these lesions, but also go a one step further and accurately characterize various renal masses. Earlier detection of small renal cell carcinomas means identifying at the initial stage which has an impact on prognosis, patient management and healthcare costs. In this review article we share our experience with the typical and atypical solid renal masses encountered in adults in routine daily practice.

[Adrenal imaging: anatomy and pathology (literature review)]

This literature review focuses on the normal adrenal gland anatomy and typical imaging features necessary to evaluate benign and malignant lesions. In particular, adenoma, pheochromocytoma, metastases and adrenocortical carcinoma were discussed as some of the most common lesions. For this purpose, a review of relevant local and international literature sources up to January 2021 was conducted.In many cases, adrenal incidentalomas have distinctive features allowing characterization using noninvasive methods. It is possible to suspect a malignant nature and promptly refer the patient for the necessary invasive examinations in some cases. -Computed tomography, especially with intravenous contrast enhancement, is the primary imaging modality because it enables differential diagnosis. Magnetic resonance tomography remains a sensitive method in lesion detection and follow-up but is not very specific for determining the malignant potential. Positron emission computed tomography also remains an additional method and is used mainly for differential diagnosis of malignant tumors, detecting metastases and recurrences after surgical treatment. Ultrasound has a limited role but is nevertheless of great importance in the pediatric population, especially newborns. Promising techniques such as radiomics and dual-energy CT can expand imaging capabilities and improve diagnostic accuracy.Because adrenal lesions are often incidentally detected by imaging performed for other reasons, it is vital to interpret such findings correctly. This review should give the reader a broad overview of how different imaging modalities can evaluate adrenal pathology and guide radiologists and clinicians.

The Incidental Renal Mass- Update on Characterization and Management

Renal masses are commonly encountered on cross-sectional imaging examinations performed for nonrenal indications. Although most can be dismissed as benign cysts, a subset will be either indeterminate or suspicious; in many cases, imaging cannot be used to reliably differentiate between benign and malignant masses. On-going research in defining characteristics of common renal masses on advanced imaging shows promise in offering solutions to this issue. A recent update of the Bosniak classification (used to categorize cystic renal masses) was proposed with the goals of decreasing imaging follow-up in likely benign cystic masses, and therefore avoiding unnecessary surgical resection of such masses.

A convention-radiomics CT nomogram for differentiating fat-poor angiomyolipoma from clear cell renal cell carcinoma

This study aimed to construct convention-radiomics CT nomogram containing conventional CT characteristics and radiomics signature for distinguishing fat-poor angiomyolipoma (fp-AML) from clear-cell renal cell carcinoma (ccRCC). 29 fp-AML and 110 ccRCC patients were enrolled and underwent CT examinations in this study. The radiomics-only logistic model was constructed with selected radiomics features by the analysis of variance (ANOVA)/Mann–Whitney (MW), correlation analysis, and Least Absolute Shrinkage and Selection Operator (LASSO), and the radiomics score (rad-score) was computed. The convention-radiomics logistic model based on independent conventional CT risk factors and rad-score was constructed for differentiating. Then the relevant nomogram was developed. Receiver operation characteristic (ROC) curves were calculated to quantify the accuracy for distinguishing. The rad-score of ccRCC was smaller than that of fp-AML. The convention-radioimics logistic model was constructed containing variables of enhancement pattern, V_UP, and rad-score. To the entire cohort, the area under the curve (AUC) of convention-radiomics model (0.968 [95% CI 0.923–0.990]) was higher than that of radiomics-only model (0.958 [95% CI 0.910–0.985]). Our study indicated that convention-radiomics CT nomogram including conventional CT risk factors and radiomics signature exhibited better performance in distinguishing fp-AML from ccRCC.

Pulmonary hamartoma: Feasibility of dual-energy CT detection of intranodular fat

We have reported 2 cases of pulmonary hamartoma focusing on detecting intranodular fat, which is one of CT features suggestive of pulmonary hamartoma, using dual-energy CT analyses. For patient 1, a 73-year-old man was pointed out to have a nodular opacity on chest radiograph of pretreatment workup for retinal detachment. In patient 2, a 66-year-old woman with uterine carcinoma admitted for preoperative assessment. Both patients underwent dual-energy CT examination and the pulmonary lesions exhibited a downward-sloping curve at lower X-ray energies on attenuation curve of virtual monochromatic images, which suggested fatty tissue. Dual-energy CT analysis can help diagnose pulmonary hamartoma with detection of intralesional fatty tissue.

Imaging Characterization of Renal Masses

The detection of a renal mass is a relatively frequent occurrence in the daily practice of any Radiology Department. The diagnostic approaches depend on whether the lesion is cystic or solid. Cystic lesions can be managed using the Bosniak classification, while management of solid lesions depends on whether the lesion is well-defined or infiltrative. The approach to well-defined lesions focuses mainly on the differentiation between renal cancer and benign tumors such as angiomyolipoma (AML) and oncocytoma. Differential diagnosis of infiltrative lesions is wider, including primary and secondary malignancies and inflammatory disease, and knowledge of the patient history is essential. Radiologists may establish a possible differential diagnosis based on the imaging features of the renal masses and the clinical history. The aim of this review is to present the contribution of the different imaging techniques and image guided biopsies in the diagnostic management of cystic and solid renal lesions.

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.

Chemical shift imaging in the identification of those renal tumours that contain microscopic fat and the utility of multiparametric MRI in their differentiation

INTRODUCTION

The aim of this study was to assess the qualitative and MRI findings of renal tumours, to determine which lesions contain microscopic fat, one of the potential differentiating factors between tumour types.

METHODS

73 patients who underwent 3 Tesla MRI including chemical shift imaging, with subsequent biopsy or excision for histopathological diagnosis, were included in the study. The images were reviewed for a decrease in signal intensity (SI) on the opposed phase compared with the in-phase gradient echo T1 images, indicating the presence of microscopic fat. The chemical shift index was then calculated as a percentage of SI change and compared with the pathological diagnosis.

RESULTS

In total, 38 (52%) of lesions demonstrated a decrease in SI, consistent with microscopic fat. Microscopic fat was found in 28 (80%) clear cell renal cell carcinomas (RCCs), 6 (66.7%) angiomyolipomas, 2 (20%) papillary RCCs, 1 (20%) chromophobe RCC and 1 (9.1%) oncocytoma. Pairwise comparison of means indicated that the amount of microscopic fat was significantly larger only for angiomyolipomas compared with clear cell RCCs (P < 0.001) and other renal lesions (P < 0.001).

CONCLUSIONS

A decrease in SI on opposed phase compared with in-phase chemical shift imaging favours the diagnosis of either clear cell RCC or an angiomyolipoma. When combined with other parameters in mpMRI, this may aid differentiation of benign from malignant tumours and differentiation of aggressive from indolent RCC subtypes. This may be of value where biopsy is non-diagnostic, not feasible due to location or in high-risk patients.

Multiparametric MR for Solid Renal Mass Characterization

Multiparametric MR provides a noninvasive means for improved differentiation between benign and malignant solid renal masses. Although most large, heterogeneous renal masses are due to renal cell carcinoma, smaller "indeterminate" renal masses are being identified on cross-sectional imaging. Although definitive diagnosis of a solid renal mass may not always be possible by MR imaging, integrated evaluation of multiple MR imaging parameters can result in concise differential diagnosis. Multiparametric MR should be considered a critical step in the triage of patients with a solid renal mass for whom treatment options are being considered in the context of morbidity, prognosis, and mortality.

Diagnostic accuracy of signal loss in in-phase gradient-echo images for differentiation between small renal cell carcinoma and lipid-poor angiomyolipomas

OBJECTIVES

To assess the diagnostic accuracy of signal loss on in-phase (IP) gradient-echo (GRE) images for differentiation between renal cell carcinomas (RCCs) and lipid-poor angiomyolipomas (lpAMLs).

METHODS

We retrospectively searched our institutional database for histologically proven small RCCs (<5.0 cm) and AMLs without visible macroscopic fat (lpAMLs). Two experienced radiologists assessed MRIs qualitatively, to depict signal loss foci on IP GRE images. A third radiologist drew regions of interest (ROIs) on the same lesions, on IP and out-of-phase (OP) images to calculate the ratio of signal loss. Diagnostic accuracy parameters were calculated for both techniques and the inter-reader agreement for the qualitative analysis was evaluated using the κ test.

RESULTS

15 (38.4%) RCCs lost their signal on IP images, with a sensitivity of 38.5% (95% CI = 23.4-55.4), a specificity of 100% (71.1-100), a positive predictive value (PPV) of 100% (73.4-100), a negative predictive value (NPV) of 31.4% (26.3-37.0), and an overall accuracy of 52% (37.4-66.3%). In terms of the quantitative analysis, the signal intensity index (SII= [(SI_IP - SI_OP) / SI_OP] x 100) for RCCs was -0.132 ± 0.05, while for AMLs it was -0.031 ± 0.02, p = 0.26. The AUC was 0.414 ± -0.09 (0.237-0.592). Using 19% of signal loss as the threshold, sensitivity was 16% and specificity was 100%. The κappa value for subjective analysis was 0.63.

CONCLUSION

Signal loss in "IP" images, assessed subjectively, was highly specific for distinction between RCCs and lpAMLs, although with low sensitivity. The findings can be used to improve the preoperative diagnostic accuracy of MRI for renal masses.

ADVANCES IN KNOWLEDGE

Signal loss on "IP" GRE images is a reliable sign for differentiation between RCC and lpAMLs.

Characterization of clear cell renal cell carcinoma and other renal tumors: evaluation of dual-energy CT using material-specific iodine and fat imaging

OBJECTIVE

This study aimed to assess material-specific iodine and fat images for diagnosis of clear cell renal cell carcinoma (cc-RCC) compared to papillary RCC (p-RCC) and other renal masses.

MATERIALS AND METHODS

With IRB approval, we identified histologically confirmed solid renal masses that underwent rapid-kVp-switch DECT between 2016 and 2018: 25 cc-RCC (7 low grade versus 18 high grade), 11 p-RCC, and 6 other tumors (2 clear cell papillary RCC, 2 chromophobe RCC, 1 oncocytoma, 1 renal angiomyomatous tumor). A blinded radiologist measured iodine and fat concentration on material-specific iodine-water and fat-water basis pair images. Comparisons were performed between groups using univariate analysis and diagnostic accuracy calculated by ROC.

RESULTS

Iodine concentration was higher in cc-RCC (6.14 ± 1.79 mg/mL) compared to p-RCC (1.40 ± 0.54 mg/mL, p < 0.001), but not compared to other tumors (5.0 ± 2.2 mg/mL, p = 0.370). Intratumoral fat was seen in 36.0% (9/25) cc-RCC (309.6 ± 234.3 mg/mL [71.1-762.3 ng/mL]), 9.1% (1/11) papillary RCC (97.11 mg/mL), and no other tumors (p = 0.036). Iodine concentration ≥ 3.99 mg/mL achieved AUC and sensitivity/specificity of 0.88 (CI 0.76-1.00) and 92.31%/82.40% to diagnose cc-RCC. To diagnose p-RCC, iodine concentration ≤ 2.5 mg/mL achieved AUC and sensitivity/specificity of 0.99 (0.98-1.00) and 100%/100%. The presence of intratumoral fat had AUC 0.64 (CI 0.53-0.75) and sensitivity/specificity of 34.6%/93.8% to diagnose cc-RCC. A logistic regression model combining iodine concentration and presence of fat increased AUC to 0.91 (CI 0.81-1.0) with sensitivity/specificity of 80.8%/93.8% to diagnose cc-RCC.

CONCLUSION

Iodine concentration values are highly accurate to differentiate clear cell RCC from papillary RCC; however, they overlap with other tumors. Fat-specific images may improve differentiation of clear cell RCC from other avidly enhancing tumors.

KEY POINTS

• Clear cell renal cell carcinoma (RCC) has significantly higher iodine concentration than papillary RCC, but there is an overlap in values comparing clear cell RCC to other renal tumors. • Iodine concentration ≤ 2.5 mg/mL is highly accurate to differentiate papillary RCC from clear cell RCC and other renal tumors. • The presence of microscopic fat on material-specific fat images was specific for clear cell RCC, helping to differentiate clear cell RCC from other avidly enhancing renal tumors.

Can MRI be used to diagnose histologic grade in T1a (< 4 cm) clear cell renal cell carcinomas?

OBJECTIVE

To assess whether MRI can differentiate low-grade from high-grade T1a cc-RCC.

MATERIALS AND METHODS

With IRB approval, 49 consecutive solid < 4 cm cc-RCC (low grade [Grade 1 or 2] N = 38, high grade [Grade 3] N = 11) with pre-operative MRI before nephrectomy were identified between 2013 and 2018. Tumor size, apparent diffusion coefficient (ADC) histogram analysis, enhancement wash-in and wash-out rates, and chemical shift signal intensity index (SI index) were assessed by a blinded radiologist. Subjectively, two blinded Radiologists also assessed for (1) microscopic fat, (2) homogeneity (5-point Likert scale), and (3) ADC signal (relative to renal cortex); discrepancies were resolved by consensus. Outcomes were studied using Chi square, multivariate analysis, logistic regression modeling, and ROC. Inter-observer agreement was assessed using Cohen's kappa.

RESULTS

Tumor size was 24 ± 7 (13-39) mm with no association to grade (p = 0.45). Among quantitative features studied, corticomedullary phase wash-in index (p = 0.015), SI index (p = 0.137), and tenth-centile ADC (p = 0.049) were higher in low-grade tumors. 36.8% (14/38) low-grade tumors versus zero high-grade tumors demonstrated microscopic fat (p = 0.015; Kappa = 0.67). Microscopic fat was specific for low-grade disease (100.0% [71.5-100.0]) with low sensitivity (36.8% [21.8-54.6]). Other subjective features did not differ between groups (p > 0.05). A logistic regression model combining microscopic fat + wash-in index + tenth-centile-ADC yielded area under ROC curve 0.98 (Confidence Intervals 0.94-1.0) with sensitivity/specificity 87.5%/100%.

CONCLUSION

The combination of microscopic fat, higher corticomedullary phase wash-in and higher tenth-centile ADC is highly accurate for diagnosis of low-grade disease among T1a clear cell RCC.

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.

Renal Angiomyolipoma Based on New Classification: How to Differentiate It From Renal Cell Carcinoma

OBJECTIVE

The purpose of this article is to describe useful imaging features for differentiating angiomyolipoma (AML) subtypes from renal cell carcinoma subtypes.

CONCLUSION

A newer radiologic classification of renal AML consists of fat-rich AML (≤ -10 HU), fat-poor AML (> -10 HU; tumor-to-spleen ratio < 0.71; signal intensity index, > 16.5%), and fat-invisible AML (> -10 HU; tumor-to-spleen ratio, > 0.71; signal intensity index, < 16.5%). Each subtype must be differentiated from the renal cell carcinoma subtype because of overlapping imaging features.

Quantitative multiparametric MR analysis of small renal lesions: correlation with surgical pathology

PURPOSE

The purpose of the study is to evaluate the utility of apparent diffusion coefficient (ADC), chemical shift signal intensity index (SII), and contrast enhancement in distinguishing between benign lesions and renal cell carcinoma (RCC) and between subtypes of renal lesions.

METHODS

This retrospective study included 98 renal lesions (≤ 3 cm) on MRI with correlative surgical pathology. Scanner field strength, lesion location, and size were recorded. Two readers blinded to surgical pathology independently measured ADC ratio (ADC lesion/ADC non-lesion kidney), SII, and absolute/relative enhancement in the corticomedullary and nephrographic phases of contrast.

RESULTS

There were 76 malignant and 22 benign lesions. 42 RCC were clear cell (ccRCC), 19 papillary (pRCC), 5 chromophobe (cbRCC). Benign lesions included both solid and cystic lesions. Interreader agreement for all variables was good-excellent (ICC 0.70-0.91). There was no difference in ADC or SII between benign and malignant lesions. There was greater absolute corticomedullary enhancement of benign versus malignant lesions (150.0 ± 111.5 vs. 81.1 ± 74.8, p = 0.0115), which did not persist when excluding pRCC. For lesion subtype differentiation, ADC_ratio for pRCC was lower than benign lesions (0.74 ± 0.35 vs. 1.03 ± 0.46, p = 0.0246). ccRCC demonstrated greater SII than other RCC (0.09 ± 0.22 vs. 0.001 ± 0.26, p = 0.0412). Oncocytomas and angiomyolipoma (AML) showed greater absolute corticomedullary enhancement than ccRCC and pRCC (145.6 ± 65.2 vs. 107.2 ± 85.3, p = 0.043 and 186.2 ± 93.9 vs. 37.6 ± 35.3, p = 0.0108), respectively.

CONCLUSIONS

While corticomedullary-phase enhancement was a differentiating feature, quantitative metrics from diffusion and chemical shift imaging cannot reliably differentiate benign from malignant lesions. Quantitative assessment may be useful in differentiating some benign and malignant lesion subtypes.

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.

Imaging of Solid Renal Masses

The increase in serendipitous detection of solid renal masses on imaging has not resulted in a reduction in mortality from renal cell carcinoma. Consequently, efforts for improved lesion characterization have been pursued and incorporated into management algorithms for distinguishing clinically significant tumors from those with favorable histology or benign conditions. Although diagnostic imaging strategies have evolved for optimized lesion detection, distinction between benign tumors and both indolent and aggressive malignant neoplasms remain an important diagnostic challenge. Recent advances in cross-sectional imaging have expanded the role of these tests in the noninvasive characterization of solid renal tumors.

CT and MRI of small renal masses

Small renal masses are increasingly detected incidentally at imaging. They vary widely in histology and aggressiveness, and include benign renal tumors and renal cell carcinomas that can be either indolent or aggressive. Imaging plays a key role in the characterization of these small renal masses. While a confident diagnosis can be made in many cases, some renal masses are indeterminate at imaging and can present as diagnostic dilemmas for both the radiologists and the referring clinicians. This article will summarize the current evidence of imaging features that correlate with the biology of small solid renal masses, and discuss key approaches in imaging characterization of these masses using CT and MRI.

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.

Chemical shift magnetic resonance imaging for distinguishing minimal-fat renal angiomyolipoma from renal cell carcinoma: a meta-analysis

OBJECTIVES

To determine the performance of chemical shift signal intensity index (CS-SII) values for distinguishing minimal-fat renal angiomyolipoma (mfAML) from renal cell carcinoma (RCC) and to assess RCC subtype characterisation.

METHODS

We identified eligible studies on CS magnetic resonance imaging (CS-MRI) of focal renal lesions via PubMed, Embase, and the Cochrane Library. CS-SII values were extracted by lesion type and evaluated using linear mixed model-based meta-regression. RCC subtypes were analysed. Two-sided p value <0.05 indicated statistical significance. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool.

RESULTS

Eleven articles involving 850 patients were included. Minimal-fat AML had significantly higher CS-SII value than RCC (p < 0.05); there were no significant differences between mfAML and clear cell RCC (cc-RCC) (p = 0.112). Clear cell RCC had a significantly higher CS-SII value than papillary RCC (p-RCC) (p < 0.001) and chromophobe RCC (ch-RCC) (p = 0.045). The methodological quality was relatively high, and Begg's test data points indicated no obvious publication bias.

CONCLUSIONS

The CS-SII value for differentiating mfAML from cc-RCC remains unproven, but is a promising method for differentiating cc-RCC from p-RCC and ch-RCC.

KEY POINTS

• RCC CS-SII values are significantly lower than those of mfAML overall. • CS-SII values cannot aid differentiation between mfAML and cc-RCC. • CS-SII values might help characterise RCC subtypes.

Renal angiomyolipoma without visible fat: Can we make the diagnosis using CT and MRI?

Renal angiomyolipomas without visible fat (AML.wovf) are benign masses that are incidentally discovered mainly in women. AML.wovf are typically homogeneously hyperdense on unenhanced CT without calcification or haemorrhage. Unenhanced CT pixel analysis is not useful for diagnosis. AML.wovf are characteristically homogeneously hypointense on T2-weighted (T2W)-MRI and apparent diffusion coefficient (ADC) maps. Despite early reports, only a minority of AML.wovf show signal intensity drop on chemical-shift MRI due to microscopic fat. AML.wovf most commonly show avid early enhancement with washout kinetics at contrast-enhanced CT and MRI. The combination of homogeneously low T2W and/or ADC signal intensity with avid early enhancement and washout is highly accurate for diagnosis of AML.wovf.

KEY POINTS

• AML.wovf are small incidental benign renal masses occurring mainly in women. • AML.wovf are homogeneously hyperdense with low signal on T2W-MRI and ADC map. • AML.wovf typically show avid early enhancement with washout kinetics. • Combining features on CT/MRI is accurate for diagnosis of AML.wovf.

Renal Angiomyolipoma: Radiologic Classification and Imaging Features According to the Amount of Fat

OBJECTIVE

The purposes of this article are to introduce the radiologic classifications of renal angiomyolipoma (AML) and the clinical implications, to show the imaging features of each type of AML, and to describe which types of AML should be biopsied.

CONCLUSION

Renal AML can be classified according to amount of fat as fat rich, fat poor, or fat invisible. To detect fat, one needs to thoroughly evaluate the entire AML by controlling the size and shape of the ROI. Fat-invisible AML should be biopsied, and fat-poor AML requires further investigation to determine whether biopsy is necessary to differentiate it from renal cell carcinoma. If differentiation between AML and renal cell carcinoma is not clear with CT and MRI, percutaneous biopsy may be performed.

Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging to Identify Clear Cell Renal Cell Carcinoma in cT1a Renal Masses

PURPOSE

The detection of small renal masses is increasing with the use of cross-sectional imaging, although many incidental lesions have negligible metastatic potential. Among malignant masses clear cell renal cell carcinoma is the most prevalent and aggressive subtype. A method to identify such histology would aid in risk stratification. Our goal was to evaluate a likelihood scale for multiparametric magnetic resonance imaging in the diagnosis of clear cell histology.

MATERIALS AND METHODS

We retrospectively reviewed the records of patients with cT1a masses who underwent magnetic resonance imaging and partial or radical nephrectomy from December 2011 to July 2015. Seven radiologists with different levels of experience who were blinded to final pathology findings independently reviewed studies based on a predefined algorithm. They applied a clear cell likelihood score, including 1-definitely not, 2-probably not, 3-equivocal, 4-probably and 5-definitely. Binary classification was used to determine the accuracy of clear cell vs all other histologies. Interobserver agreement was calculated with the weighted κ statistic.

RESULTS

A total of 110 patients with 121 masses were identified. Mean tumor size was 2.4 cm and 50% of the lesions were clear cell. Defining clear cell as scores of 4 or greater demonstrated 78% sensitivity and 80% specificity while scores of 3 or greater showed 95% sensitivity and 58% specificity. Interobserver agreement was moderate to good with a mean κ of 0.53.

CONCLUSIONS

A clear cell likelihood score used with magnetic resonance imaging can reasonably identify clear cell histology in small renal masses and may decrease the number of diagnostic renal mass biopsies. Standardization of imaging protocols and reporting criteria is needed to improve interobserver reliability.

Reporting standards for the imaging-based diagnosis of renal masses on CT and MRI: a national survey of academic abdominal radiologists and urologists

PURPOSE

To define important elements of a structured radiology report of a CT or MRI performed to evaluate an indeterminate renal mass.

METHODS

IRB approval was waived for this multi-site prospective quality improvement study. A 35-question survey investigating elements of a CT or MRI report describing a renal mass was created through an iterative process by the Society of Abdominal Radiology Disease-Focused Panel on renal cell carcinoma. Surveys were distributed to consenting abdominal radiologists and urologists at nine academic institutions. Consensus within and between specialties was defined as ≥70% agreement. Respondent rates were compared with Chi Square test.

RESULTS

The response rate was 68% (117/171; 55% [39/71] urologists, 78% [78/100] radiologists). Inter-specialty consensus was that the following were essential: mass size with comparison to prior imaging, mass type (cystic vs. solid), presence of fat, presence of enhancement, and radiologic stage. Urologists were more likely to prefer the Nephrometry score (75% [27/36] vs. 22% [17/76], p < 0.0001), quantitative reporting of enhancement on CT (85% [32/38] vs. 46% [36/77], p < 0.0001), and mass position with respect to the renal polar lines (67% [24/36] vs. 36% [27/76], p = 0.002). There was inter-specialty consensus that the Bosniak classification for cystic masses was preferred. Most urologists (60% [21/35]) preferred management recommendations be omitted for solid masses or Bosniak III-IV cystic masses.

CONCLUSIONS

Important elements to include in a CT or MRI report of an indeterminate renal mass are critical diagnostic features, the Bosniak classification if relevant, and the most likely specific diagnosis when feasible; including management recommendations is controversial.

Associations between Tumor Vascularity, Vascular Endothelial Growth Factor Expression and PET/MRI Radiomic Signatures in Primary Clear-Cell-Renal-Cell-Carcinoma: Proof-of-Concept Study

Studies have shown that tumor angiogenesis is an essential process for tumor growth, proliferation and metastasis. Also, tumor angiogenesis is an important prognostic factor of clear cell renal cell carcinoma (ccRCC), as well as a factor in guiding treatment with antiangiogenic agents. Here, we attempted to find the associations between tumor angiogenesis and radiomic imaging features from PET/MRI. Specifically, sparse canonical correlation analysis was conducted on 3 feature datasets (i.e., radiomic imaging features, tumor microvascular density (MVD), and vascular endothelial growth factor (VEGF) expression) from 9 patients with primary ccRCC. In order to overcome the potential bias of intratumoral heterogeneity of angiogenesis, this study investigated the relationship between regional expressions of angiogenesis and VEGF, and localized radiomic features from different parts within the tumors. Our study highlighted the significant strong correlations between radiomic features and MVD, and also demonstrated that the spatiotemporal features extracted from DCE-MRI provided stronger radiomic correlation to MVD than the textural features extracted from Dixon sequences and FDG PET. Furthermore, PET/MRI, which takes advantage of the combined functional and structural information, had higher radiomics correlation to MVD than solely utilizing PET or MRI alone.

Imaging of Solid Renal Masses

Detection of solid renal masses has increased, although it has not resulted in significant mortality reduction from renal cell carcinoma. Efforts for improved lesion characterization have been pursued and incorporated in management algorithms, in order to distinguish clinically significant tumors from favorable or benign conditions. Concurrently, imaging methods have produced evidence supporting their role as useful tools not only in lesion detection but also characterization. In addition, newer modalities, such as contrast-enhanced ultrasonography, and advanced applications of MR imaging, are being investigated. This article reviews the current role of different imaging methods in the characterization of solid renal masses.

Correlating Preoperative Imaging with Histologic Subtypes of Renal Cell Carcinoma and Common Mimickers

Renal cell carcinoma (RCC) consists of distinct subtypes that have unique pathologic and imaging features as well as specific cytogenetic and molecular characteristics. As the prognosis and therapeutic strategies may differ for each subtype, correlation of the preoperative imaging with the pathologic findings is of great clinical relevance. In addition, differentiation of RCC from benign entities is ideal in order to prevent overtreatment. However, a noninvasive diagnosis with imaging alone is not always straightforward due to the overlapping appearance of RCC with benign lesions such as fat-poor angiomyolipoma and oncocytoma. With new imaging modalities, there have been significant improvements in correlating preoperative imaging with pathologic characteristics. These new discoveries are able to aid in a more specific, noninvasive, diagnosis that in turn helps direct patient management.

Small (< 4 cm) Renal Tumors With Predominantly Low Signal Intensity on T2-Weighted Images: Differentiation of Minimal-Fat Angiomyolipoma From Renal Cell Carcinoma

OBJECTIVE

The purpose of this study was to retrospectively investigate the utility of multiparametric MRI in differentiating minimal-fat angiomyolipoma (AML) from renal cell carcinoma (RCC) in small renal tumors with predominantly low signal intensity on T2-weighted MR images.

MATERIALS AND METHODS

Fifty-six patients with pathologically identified renal tumors (1-4 cm) with predominantly low signal intensity on T2-weighted images without visible fat on unenhanced CT images were enrolled. Clinical and MRI variables (tumor-to-renal cortex signal intensity [SI] ratio on T2-weighted images [T2 ratio], apparent diffusion coefficient [ADC], and SI index) on chemical-shift images were evaluated.

RESULTS

The ADC was significantly lower in RCC than in minimal-fat AML (p = 0.001). The T2 ratio and signal intensity index were not significantly different between RCC (p = 0.31) and minimal-fat AML (p = 0.74). Multivariate analysis showed that ADC (odds ratio [OR], 0.01; p = 0.02) and male sex (OR, 46.7; p < 0.001) were the independent predictors of RCC. For differentiating minimal-fat AML from RCC, the ROC AUC of ADC was 0.781. When ADC and sex were combined, the AUC significantly increased to 0.937 with a cutoff value of 1.129 × 10^-3 mm²/s. For making the diagnosis of minimal-fat AML if the ADC was greater than the threshold, sensitivity was 89.7% and specificity was 88.2% (p = 0.02).

CONCLUSION

In small renal tumors with predominantly low SI on T2-weighted images, ADC is useful for differentiating minimal-fat AML from RCC. Combining ADC with male sex increases the accuracy of RCC prediction.

Diagnosis of Renal Angiomyolipomas: Classic, Fat-Poor, and Epithelioid Types

With the increasing discovery of small renal masses with cross-sectional imaging, there has been the concomitant rise in their treatment. With the intent of early curative surgery for a presumed renal cell carcinoma, many renal masses are being resected at surgery without a confirmed diagnosis. Many of them are benign, and some are angiomyolipomas. The diagnosis of renal angiomyolipoma using imaging is, therefore, is as important as ever. Although most, if not all angiomyolipomas with abundant fat are diagnosed readily, some have too little fat to be detected with imaging. This article reviews the current classification, imaging pitfalls, and diagnosis of angiomyolipoma with an emphasis on the fat-poor types. Proper imaging technique, a thorough search for fat, and the appropriate use of percutanoeus biopsy are all needed to eliminate the unnecessary treatment of these benign neoplasms.

Review of renal cell carcinoma and its common subtypes in radiology

Representing 2%-3% of adult cancers, renal cell carcinoma (RCC) accounts for 90% of renal malignancies and is the most lethal neoplasm of the urologic system. Over the last 65 years, the incidence of RCC has increased at a rate of 2% per year. The increased incidence is at least partly due to improved tumor detection secondary to greater availability of high-resolution cross-sectional imaging modalities over the last few decades. Most RCCs are asymptomatic at discovery and are detected as unexpected findings on imaging performed for unrelated clinical indications. The 2004 World Health Organization Classification of adult renal tumors stratifies RCC into several distinct histologic subtypes of which clear cell, papillary and chromophobe tumors account for 70%, 10%-15%, and 5%, respectively. Knowledge of the RCC subtype is important because the various subtypes are associated with different biologic behavior, prognosis and treatment options. Furthermore, the common RCC subtypes can often be discriminated non-invasively based on gross morphologic imaging appearances, signal intensity on T2-weighted magnetic resonance images, and the degree of tumor enhancement on dynamic contrast-enhanced computed tomography or magnetic resonance imaging examinations. In this article, we review the incidence and survival data, risk factors, clinical and biochemical findings, imaging findings, staging, differential diagnosis, management options and post-treatment follow-up of RCC, with attention focused on the common subtypes.

Intracellular lipid in clear cell renal cell carcinoma tumor thrombus and metastases detected by chemical shift (in and opposed phase) MRI: radiologic-pathologic correlation

BACKGROUND

Clear cell renal cell carcinoma (RRC) characteristically contain intracellular lipid which is also detectable in tumor thrombus and metastases.

PURPOSE

To assess the incidence of intracellular lipid in clear cell RCC metastases and tumor thrombus using chemical shift MRI.

MATERIAL AND METHODS

With REB approval, 33 consecutive patients with clear cell RCC and tumor thrombus/metastatic disease underwent magnetic resonance imaging (MRI) over a 10-year period. Diagnosis was established by histopathology for tumor thrombi (n = 25) and metastases (n = 15) or growth for metastases (n = 14). Two blinded radiologists independently assessed for a signal intensity (SI) drop at chemical shift MRI (indicative of intracellular lipid) and a third radiologist established consensus. Chemical shift SI (CS-SI) index ([SItumorIP - SItumorOP]/SITumorIP x 100) was calculated. Inter-observer agreement was assessed using intra-class correlation (ICC) and tests of association were performed using the Chi-square test and Spearman correlation.

RESULTS

Using CS-MRI, intracellular lipid was detected in 36.4% of clear cell RCC, with moderate agreement, (ICC = 0.5). Intracellular lipid was detected in 20% of tumor thrombi and 20% of metastases with strong agreement (ICC = 0.73). Intracellular lipid within tumor thrombi/metastases was not associated with lipid within the primary tumor (P = 0.09). There was a correlation in CS-SI index between primary tumor and thrombi/metastases when lipid was detected in both lesions (r = 0.91, P = 0.005); however, there was no correlation when lipid was not detected in both lesions (r = -0.09, P = 0.72).

CONCLUSION

The presence of intracellular lipid in tumor thrombus and metastases from clear cell RCC is uncommon and, is not necessarily associated with lipid within the primary tumor at chemical shift MRI.

[Managing focal incidental renal lesions]

Incidental renal lesions are relatively common in daily radiological practice. It is important to know the different diagnostic possibilities for incidentally detected lesions, depending on whether they are cystic or solid. The management of cystic lesions is guided by the Bosniak classification. In solid lesions, the goal is to differentiate between renal cancer and benign tumors such as fat-poor angiomyolipoma and oncocytoma. Radiologists need to know the recommendations for the management of these lesions and the usefulness of the different imaging techniques and interventional procedures in function of the characteristics of the incidental lesion and the patient's life expectancy.

Novel application of chemical shift gradient echo in- and opposed-phase sequences in 3 T MRI for the detection of H-MRS visible lipids and grading of glioma

Objectives

We evaluated the feasibility of using chemical shift gradient-echo (GE) in- and opposed-phase (IOP) imaging to grade glioma.

Methods

A phantom study was performed to investigate the correlation of ¹H MRS-visible lipids with the signal loss ratio (SLR) obtained using IOP imaging. A cross-sectional study approved by the institutional review board was carried out in 22 patients with different glioma grades. The patients underwent scanning using IOP imaging and single-voxel spectroscopy (SVS) using 3T MRI. The brain spectra acquisitions from solid and cystic components were obtained and correlated with the SLR for different grades.

Results

The phantom study showed a positive linear correlation between lipid quantification at 0.9 parts per million (ppm) and 1.3 ppm with SLR (r = 0.79–0.99, p < 0.05). In the clinical study, we found that SLR at the solid portions was the best measure for differentiating glioma grades using optimal cut-points of 0.064 and 0.086 with classification probabilities for grade II (S_II = 1), grade III (S_III = 0.50) and grade IV (S_IV = 0.89).

Conclusions

The results underscore the lipid quantification differences in grades of glioma and provide a more comprehensive characterization by using SLR in chemical shift GE IOP imaging. SLR in IOP sequence demonstrates good performance in glioma grading.

Key Points

• Strong correlation was seen between lipid concentration and SLR obtained using IOP

• IOP sequence demonstrates significant differences in signal loss within the glioma grades

• SLR at solid tumour portions was the best measure for differentiation

• This sequence is applicable in a research capacity for glioma staging armamentarium

Predictive Value of Chemical-Shift MRI in Distinguishing Clear Cell Renal Cell Carcinoma From Non-Clear Cell Renal Cell Carcinoma and Minimal-Fat Angiomyolipoma

OBJECTIVE

The purpose of this study was to evaluate the diagnostic performance of chemical-shift MRI in the differentiation of clear cell renal cell carcinoma (RCC) from minimal-fat angiomyolipoma (AML) and non-clear cell RCC.

MATERIALS AND METHODS

In this retrospective study, 97 patients with solid renal tumors without macroscopic fat and with a pathologic diagnosis of clear cell RCC (n = 40), non-clear cell RCC (n = 31), or minimal-fat AML (n = 26) who had undergone renal chemical-shift MRI were included. Size, location, morphology, and signal intensity (SI) of the tumors and the contralateral normal kidneys on T2-weighted and in-phase and opposed-phase images were recorded by readers blinded to the pathology. Percentage tumor-to-renal parenchymal SI drop (percentage SI drop) was calculated and correlated to tumor histology. The statistical analysis was done using Kruskal-Wallis, one-way ANOVA, chi-square, and Fisher exact tests.

RESULTS

The percentage SI drop was significantly higher in clear cell RCC compared with non-clear cell RCC and minimal-fat AML (p < 0.001). Percentage SI drop of greater than 20% had 57.5% sensitivity, 96.5% specificity, and 92% positive predictive value (PPV); and percentage SI drop greater than 29% had 40% sensitivity and 100% specificity for diagnosis of clear cell RCC within the cohort of clear cell RCC, minimal-fat AML, and non-clear cell RCC. A significant proportion of minimal-fat AML (46.2%) displayed homogeneous low T2-weighted SI as opposed to clear cell RCC (5%) and non-clear cell RCC (29%) (p < 0.001).

CONCLUSION

The percentage SI drop on chemical-shift MRI had high specificity and moderate sensitivity in predicting clear cell RCC over non-clear cell RCC and minimal-fat AML. A percentage SI drop greater than 20% in a renal mass without macroscopically visible fat has high PPV for clear cell RCC over minimal-fat AML and non-clear cell RCC. Among morphologic features, homogeneous low T2 SI favors minimal-fat AML over RCC.

Renal cell carcinoma: histological classification and correlation with imaging findings

Renal cell carcinoma (RCC) is the seventh most common histological type of cancer in the Western world and has shown a sustained increase in its prevalence. The histological classification of RCCs is of utmost importance, considering the significant prognostic and therapeutic implications of its histological subtypes. Imaging methods play an outstanding role in the diagnosis, staging and follow-up of RCC. Clear cell, papillary and chromophobe are the most common histological subtypes of RCC, and their preoperative radiological characterization, either followed or not by confirmatory percutaneous biopsy, may be particularly useful in cases of poor surgical condition, metastatic disease, central mass in a solitary kidney, and in patients eligible for molecular targeted therapy. New strategies recently developed for treating renal cancer, such as cryo and radiofrequency ablation, molecularly targeted therapy and active surveillance also require appropriate preoperative characterization of renal masses. Less common histological types, although sharing nonspecific imaging features, may be suspected on the basis of clinical and epidemiological data. The present study is aimed at reviewing the main clinical and imaging findings of histological RCC subtypes.

Interactive Feature Space Explorer© for multi-modal magnetic resonance imaging

Wider information content of multi-modal biomedical imaging is advantageous for detection, diagnosis and prognosis of various pathologies. However, the necessity to evaluate a large number images might hinder these advantages and reduce the efficiency. Herein, a new computer aided approach based on the utilization of feature space (FS) with reduced reliance on multiple image evaluations is proposed for research and routine clinical use. The method introduces the physician experience into the discovery process of FS biomarkers for addressing biological complexity, e.g., disease heterogeneity. This, in turn, elucidates relevant biophysical information which would not be available when automated algorithms are utilized. Accordingly, the prototype platform was designed and built for interactively investigating the features and their corresponding anatomic loci in order to identify pathologic FS regions. While the platform might be potentially beneficial in decision support generally and specifically for evaluating outlier cases, it is also potentially suitable for accurate ground truth determination in FS for algorithm development. Initial assessments conducted on two different pathologies from two different institutions provided valuable biophysical perspective. Investigations of the prostate magnetic resonance imaging data resulted in locating a potential aggressiveness biomarker in prostate cancer. Preliminary findings on renal cell carcinoma imaging data demonstrated potential for characterization of disease subtypes in the FS.