Subtype differentiation of renal cell carcinoma using diffusion-weighted and blood oxygenation level-dependent MRI. AJR Am J Roentgenol. 2014;203:W78-W84. [PMID: 24951231 DOI: 10.2214/ajr.13.11551]

Deep learning using contrast-enhanced ultrasound images to predict the nuclear grade of clear cell renal cell carcinoma

PURPOSE

To assess the effectiveness of a deep learning model using contrastenhanced ultrasound (CEUS) images in distinguishing between low-grade (grade I and II) and high-grade (grade III and IV) clear cell renal cell carcinoma (ccRCC).

METHODS

A retrospective study was conducted using CEUS images of 177 Fuhrmangraded ccRCCs (93 low-grade and 84 high-grade) from May 2017 to December 2020. A total of 6412 CEUS images were captured from the videos and normalized for subsequent analysis. A deep learning model using the RepVGG architecture was proposed to differentiate between low-grade and high-grade ccRCC. The model's performance was evaluated based on sensitivity, specificity, positive predictive value, negative predictive value and area under the receiver operating characteristic curve (AUC). Class activation mapping (CAM) was used to visualize the specific areas that contribute to the model's predictions.

RESULTS

For discriminating high-grade ccRCC from low-grade, the deep learning model achieved a sensitivity of 74.8%, specificity of 79.1%, accuracy of 77.0%, and an AUC of 0.852 in the test set.

CONCLUSION

The deep learning model based on CEUS images can accurately differentiate between low-grade and high-grade ccRCC in a non-invasive manner.

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.

Multiparametric MRI of Solid Renal Masses: Principles and Applications of Advanced Quantitative and Functional Methods for Tumor Diagnosis and Characterization

Solid renal masses (SRMs) are increasingly detected and encompass both benign and malignant masses, with renal cell carcinoma (RCC) being the most common malignant SRM. Most patients with SRMs will undergo management without a priori pathologic confirmation. There is an unmet need to noninvasively diagnose and characterize RCCs, as significant variability in clinical behavior is observed and a wide range of differing management options exist. Cross-sectional imaging modalities, including magnetic resonance imaging (MRI), are increasingly used for SRM characterization. Multiparametric (mp) MRI techniques can provide insight into tumor biology by probing different physiologic/pathophysiologic processes noninvasively. These include sequences that probe tissue microstructure, including intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and T₁ relaxometry; oxygen metabolism (blood oxygen level dependent [BOLD-MRI]); as well as vascular flow and perfusion (dynamic contrast-enhanced MRI [DCE-MRI] and arterial spin labeling [ASL]). In this review, we will discuss each mpMRI method in terms of its principles, roles, and discuss the results of human studies for SRM assessment. Future validation of these methods may help to enable a personalized management approach for patients with SRM in the emerging era of precision medicine. EVIDENCE LEVEL: 5. TECHNICAL EFFICACY: 2.

The relationship of apparent diffusion coefficient values of renal cell carcinoma before and after cryotherapy ablation

INTRODUCTION

The diagnosis of renal cell carcinoma (RCC) is increasing due to incidental findings with more frequent use of cross-sectional imaging. Therefore improvements to diagnostic and follow up imaging techniques is necessary. MRI diffusion weighted imaging (DWI) is a recognised method of measuring the diffusion of water within lesions using the apparent diffusion coefficient (ADC), and may have a role in monitoring the efficacy of cryotherapy ablation of RCC.

METHODS

A retrospective cohort study of 50 patients was approved to investigate if the ADC value can determine the success of cryotherapy ablation treatment for RCC. DWI was performed at a single centre using 1.5 T MRI before and after cryotherapy ablation to the RCC. The control group was considered as the unaffected kidney. The ADC value of the RCC tumour and normal kidney tissue prior to and after cryotherapy ablation was measured, and compared to the result of the MRI.

RESULTS

A statistically significant change in the ADC values was observed, pre ablation (1.562 × 10¯mm²/sec) to the post ablation (1.126 × 10¯³mm²/sec), p < 0.0005. There was no statistical significance in any of the other outcomes measured.

CONCLUSION

Although a change of ADC value occurred this is likely due to cryotherapy ablation causing coagulative necrosis at the site, and does not determine the success of the cryotherapy ablation. This can be considered a feasibility study for future research.

IMPLICATIONS FOR PRACTICE

DWI is a quick addition to routine protocols, does not require intravenous gadolinium based contrast agent, and provides qualitative and quantitative data. Further research is required to establish the role of ADC for treatment monitoring.

Evaluation of renal space occupying lesions with multiparametric MRI and its correlation with histopathology findings- an observational study

The term multiparametric MRI, is a useful tool in reference to an approach that takes advantage of the added value of different MR imaging acquisitions to yield anatomic and pathophysiologic information about renal space occupying lesions and to evaluate patients with different tumors, including genitourinary malignancies. The role of multiparametric MRI is continuously growing because of its ability to detect and characterize renal space occupying lesions as well as to assess response to treatment. An observational study was carried out in 50 patients who presented with renal mass, based on clinical suspicion and prior imaging diagnosis of neoplastic renal space occupying lesion. Total renal space occupying lesions were 50, of which, 38 were males & 12 were females. The age range of the study population was 30-80 years. In our study, Agreement analysis between mpMRI diagnosis and HPE diagnosis of different RCC subtypes was statistically significant. So, multiparametric MRI had a role in differentiating the subtypes of RCC which had fair agreement with HPE. The present study results state that the renal mass lesions has different ADC values for different lesions because of the change in tissue contents and there was a statistically significant difference in ADC values between low and high-stage RCCs. Histologic and radiologic profiles of renal space occupying lesions and diverse subtypes of RCC can be used as biologic indicators of clinical behavior, response to treatment, and prognosis.

Quantitative 3-tesla multiparametric MRI in differentiation between renal cell carcinoma subtypes

Background

MRI provides several distinct quantitative parameters that may better differentiate renal cell carcinoma (RCC) subtypes. The purpose of the study is to evaluate the diagnostic accuracy of apparent diffusion coefficient (ADC), chemical shift signal intensity index (SII), and contrast enhancement in differentiation between different subtypes of renal cell carcinoma.

Results

There were 63 RCC as regard surgical histopathological analysis: 43 clear cell (ccRCC), 12 papillary (pRCC), and 8 chromophobe (cbRCC). The mean ADC ratio for ccRCC (0.75 ± 0.13) was significantly higher than that of pRCC (0.46 ± 0.12, P < 0.001) and cbRCC (0.41 ± 0.15, P < 0.001). The mean ADC value for ccRCC (1.56 ± 0.27 × 10−3 mm2/s) was significantly higher than that of pRCC (0.96 ± 0.25 × 10−3 mm2/s, P < 0.001) and cbRCC (0.89 ± 0.29 × 10−3 mm2/s, P < 0.001). The mean SII of pRCC (1.49 ± 0.04) was significantly higher than that of ccRCC (0.93 ± 0.01, P < 0.001) and cbRCC (1.01 ± 0.16, P < 0.001). The ccRCC absolute corticomedullary enhancement (196.7 ± 81.6) was significantly greater than that of cbRCC (177.8 ± 77.7, P < 0.001) and pRCC (164.3 ± 84.6, P < 0.001).

Conclusion

Our study demonstrated that multiparametric MRI is able to afford some quantitative features such as ADC ratio, SII, and absolute corticomedullary enhancement which can be used to accurately distinguish different subtypes of renal cell carcinoma.

Cross-sectional imaging assessment of renal masses with emphasis on MRI

Magnetic resonance imaging (MRI) is a useful complementary imaging tool for the diagnosis and characterization of renal masses, as it provides both morphologic and functional information. A core MRI protocol for renal imaging should include a T1-weighted sequence with in- and opposed-phase images (or, alternatively with DIXON technique), T2-weighted and diffusion-weighted images as well as a dynamic contrast-enhanced sequence with subtraction images, followed by a delayed post-contrast T1-weighted sequence. The main advantages of MRI over computed tomography include increased sensitivity for contrast enhancement, less sensitivity for detection of calcifications, absence of pseudoenhancement, and lack of radiation exposure. MRI may be applied for renal cystic lesion characterization, differentiation of renal cell carcinoma (RCC) from benign solid renal tumors, RCC histologic grading, staging, post-treatment follow-up, and active surveillance of patients with treated or untreated RCC.

The role of diffusion-weighted MRI and contrast-enhanced MRI for differentiation between solid renal masses and renal cell carcinoma subtypes

PURPOSE

To assess the value of diffusion-weighted magnetic resonance imaging (DW-MRI) and contrast-enhanced MRI (CE-MRI) for differentiation between benign and malignant solid renal masses, renal cell carcinoma (RCC) subtypes, oncocytomas, and lipid-poor angiomyolipomas (LP-AML).

METHODS

Minimum or lowest 'apparent diffusion coefficient' (ADC₁) and representative ADC values (ADC₂) of 112 renal masses (n: 46 benign renal mass, n: 66 malignant renal mass) were measured on DW-MRI images (b 50, 400, 800 s/mm²). Signal intensity (SI) measurements were performed in normal renal parenchyma and most avid enhanced area of the renal masses at precontrast, corticomedullary, and nephrographic phases on CE-MRI. Contrast enhancement rate (CER) and contrast enhancement index (CEI) values of renal masses were compared between benign-malignant renal masses and RCC subtypes, oncocytomas, and LP-AMLs.

RESULTS

There was no significant difference between ADC₁, ADC₂ values, and SI of benign and malignant renal masses (p = 0.721, p = 0.255, p = 0.872). Mean ADC₁ and ADC₂ values of clear cell RCCs were significantly higher than nonclear cell RCCs (p = 0.005 p = 0.002). Mean CER value of clear cell RCCs was significantly higher than nonclear cell RCCs in nephrographic phase (p = 0.003). Mean CEI values of clear cell RCCs were significantly higher than nonclear cell RCCs in the corticomedullary and nephrographic phase (p = 0.027 vs. 0.008). LP-AMLs were differentiated from other renal masses with wash-out phenomenon.

CONCLUSION

Combined usage of ADC, SI, CER, and CEI values may be useful for discrimination between RCC subtypes, oncocytomas, and lipid-poor AMLs.

Predicting common solid renal tumors using machine learning models of classification of radiologist-assessed magnetic resonance characteristics

PURPOSE

Solid renal masses (SRM) are difficult to differentiate based on standard MR features. The purpose of this study was to assess MR imaging features of SRM to evaluate performance of ensemble methods of classifying SRM subtypes.

MATERIALS AND METHODS

MR images of SRM (n = 330) were retrospectively evaluated for standard and multiparametric (mp) features. Models of MR features for predicting malignant and benign lesions as well as subtyping SRM were developed using a training dataset and performance was evaluated in a test data-set using recursive partitioning (RP), gradient booting machine (GBM), and random forest (RF) methods.

RESULTS

In the test dataset, GBM and RF models demonstrated an accuracy of 86% (95% CI 75% to 93%) for predicting benign versus malignant SRM compared to 83% (95% CI 71% to 91%) for the RP model. RF had the greatest accuracy in predicting SRM subtypes, 81.2% (95% CI 69.5% to 89.9%) compared with GBM 73.4% (95% CI 60.9% to 83.7%) or RP 70.3% (95% CI 57.6% to 81.1%). Marginal homogeneity was reduced by the RF model compared with the RP model (P < 0.001), but not the GBM model (P = 0.135). All models had high sensitivity and specificity for clear cell and papillary renal cell carcinomas (RCC), but performed less well in differentiating chromophobe RCC, oncocytomas, and fat-poor angiomyolipomas.

CONCLUSION

Ensemble methods for prediction of SRM from radiologist-assessed image characteristics have high accuracy for distinguishing benign and malignant lesions. SRM subtype classification is limited by the ability to categorize chromophobe RCCs, oncocytomas, and fat-poor angiomyolipomas.

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 test accuracy of ADC values for identification of clear cell renal cell carcinoma: systematic review and meta-analysis

OBJECTIVES

To perform a systematic review on apparent diffusion coefficient (ADC) values of renal tumor subtypes and meta-analysis on the diagnostic performance of ADC for differentiation of localized clear cell renal cell carcinoma (ccRCC) from other renal tumor types.

METHODS

Medline, Embase, and the Cochrane Library databases were searched for studies published until May 1, 2019, that reported ADC values of renal tumors. Methodological quality was evaluated. For the meta-analysis on diagnostic test accuracy of ADC for differentiation of ccRCC from other renal lesions, we applied a bivariate random-effects model and compared two subgroups of ADC measurement with vs. without cystic and necrotic areas.

RESULTS

We included 48 studies (2588 lesions) in the systematic review and 13 studies (1126 lesions) in the meta-analysis. There was no significant difference in ADC of renal parenchyma using b values of 0-800 vs. 0-1000 (p = 0.08). ADC measured on selected portions (sADC) excluding cystic and necrotic areas differed significantly from whole-lesion ADC (wADC) (p = 0.002). Compared to ccRCC, minimal-fat angiomyolipoma, papillary RCC, and chromophobe RCC showed significantly lower sADC while oncocytoma exhibited higher sADC. Summary estimates of sensitivity and specificity to differentiate ccRCC from other tumors were 80% (95% CI, 0.76-0.88) and 78% (95% CI, 0.64-0.89), respectively, for sADC and 77% (95% CI, 0.59-0.90) and 77% (95% CI, 0.69-0.86) for wADC. sADC offered a higher area under the receiver operating characteristic curve than wADC (0.852 vs. 0.785, p = 0.02).

CONCLUSIONS

ADC values of kidney tumors that exclude cystic or necrotic areas more accurately differentiate ccRCC from other renal tumor types than whole-lesion ADC values.

KEY POINTS

• Selective ADC of renal tumors, excluding cystic and necrotic areas, provides better discriminatory ability than whole-lesion ADC to differentiate clear cell RCC from other renal lesions, with area under the receiver operating characteristic curve (AUC) of 0.852 vs. 0.785, respectively (p = 0.02). • Selective ADC of renal masses provides moderate sensitivity and specificity of 80% and 78%, respectively, for differentiation of clear cell renal cell carcinoma (RCC) from papillary RCC, chromophobe RCC, oncocytoma, and minimal-fat angiomyolipoma. • Selective ADC excluding cystic and necrotic areas are preferable to whole-lesion ADC as an additional tool to multiphasic MRI to differentiate clear cell RCC from other renal lesions whether the highest b value is 800 or 1000.

Predictive Value of In Vivo MR Spectroscopy With Semilocalization by Adiabatic Selective Refocusing in Differentiating Clear Cell Renal Cell Carcinoma From Other Subtypes

OBJECTIVE. The purpose of this study is to evaluate the diagnostic value of in vivo MR spectroscopy (MRS) with semilocalization by adiabatic selective refocusing (semi-LASER MRS) in differentiating clear cell renal cell carcinoma (RCC) from the non-clear cell subtype. SUBJECTS AND METHODS. Sixteen patients with biopsy-proven RCC or masses highly suspicious for RCC were prospectively recruited to participate in the study. Single-voxel ¹H spectra were acquired using a 3-T MRI system, with a semi-LASER sequence acquired for renal tumors in 14 patients and for healthy renal tissue (control tissue) in 12 patients. Offline processing of the MR spectra was performed. MRI and spectra analysis were performed independently by radiologists who were blinded to the reference histopathologic findings. RESULTS. Semi-LASER MRS was diagnostic for nine of 11 patients (82%) with histopathologically proven clear cell RCC, showing a strong lipid peak in seven patients and a weaker lipid resonance in two others, whereas control spectra showed weakly positive findings in only one patient. MRS findings were negative for lipid resonance in two of three patients (67%) with non-clear cell tumors and were weakly positive in another patient. Semi-LASER MRS had a high sensitivity and positive predictive value of 82% and 90%, respectively, in addition to a specificity of 67%, a negative predictive value of 50%, and overall accuracy of 79% for the detection of clear cell RCC. Lipid resonance was detected by MRS for four of six clear cell RCCs with no intravoxel fat on chemical-shift MRI. CONCLUSION. The preliminary results of the present study show that semi-LASER MRS is promising for the noninvasive discrimination of clear cell RCC from non-clear cell RCC on the basis of detection of lipid resonance and that it provides an incremental yield compared with chemical-shift MRI.

Assessment of apparent diffusion coefficient value as prognostic factor for renal cell carcinoma aggressiveness

Background

Assurance of prognostic elements is important for the management of renal cell carcinoma (RCC). Our goal was to check the relation between apparent diffusion coefficient (ADC) values and parameters predicting prognosis of RCC. Fifty pathologically confirmed RCC underwent diffusion-weighted (DW) MRI. ADC values were calculated using b factor (800 s/mm2). The correlation between ADC values and tumor size, cystic/necrotic feature, growth pattern, unenhanced T1, histological grade, clinical stage, and distant metastasis were analyzed.

Results

The optimal ADC threshold for prognosis of RCC appeared to be 1.4 × 10−3 mm2/s. There was a significant inverse correlation between ADC values and growth pattern (R = − 0, P = 0.05), unenhanced T1(R = − 0.41, P = 0.01), cystic/necrotic feature (R = − 0.4, P = 0.01), histological grade (R = − 0.37, P = 0.02), clinical stage (r = − 0.4, P = 0.01), and distant metastasis (R = − 0.33, P = 0.04), and significant linear correlation with tumor size (R = 0.39, P < 0.02).

Conclusion

The performance of ADC value as a newly proposed prognostic parameter follows with the degree of tumor differentiation and that may recognize extremely aggressive RCC. RCC with low ADC values should be inspected extensively for the risk of high pathological grade, high clinical stage, and distant metastasis.

Texture analysis of small renal cell carcinomas at MDCT for predicting relevant histologic and protein biomarkers

PURPOSE

To assess CT texture features of small renal cell carcinomas (≤ 4cm) for association with key pathologic features including protein biomarkers.

METHODS

Quantitative CT texture analysis (CTTA) of small renal cancers (≤ 4cm) was performed on non-contrast and portal venous phase abdominal MDCT scans with an ROI drawn at the largest cross-sectional diameter of the tumor using commercially available software. Texture parameters including mean pixel attenuation, the standard deviation (SD) of the pixel distribution histogram, entropy, the mean of positive pixels, the skewness (i.e., asymmetry) of the pixel histogram, kurtosis (i.e., peakness) of the pixel histogram, and the percentage of positive pixels were correlated with pathologic data from surgical resection, including histology and nuclear grade, as well as microarray analysis in a subset (n = 40) including Ki67 index, CRP, and neovascularization (CD105/CD31).

RESULTS

Portal venous phase images were available in 249 patients (105 women, 144 men; mean age, 56.7 years) with tumors ≤ 4cm (mean, median, range, ± SD; 2.66, 2.60, 0.3-4.0 ± 0.85 cm). CT texture features of standard deviation, mean of the positive pixels, and entropy of the pixel histogram were significantly associated with histologic cell type (clear vs. non-clear; p < 0.001). Entropy and mean of the positive pixels also showed an association with nuclear grade, although not statistically significant. In the microarray analysis subset, kurtosis of the pixel histogram was associated with CD105/CD31 (p = 0.05). SD also showed some association with CD 105 positivity (p = 0.02) and CAIX expression (p = 0.01). Non-contrast CT images were available in 174 patients (72 women, 102 men; mean age, 57.5 years). Although the association with histology was not as strong as on the portal venous phase, in the subset of patients with microarray data, SD was found to correlate with CRP (p = 0.08), kurtosis with CRP (p = 0.004), CD105/CD31 (p = 0.002), and with Ki 67 index (p < 0.001).

CONCLUSION

CT texture features were significantly associated with important histopathologic features in small renal cancers. These non-invasive measures can be performed retrospectively and may provide useful information when determining follow-up and treatment of small renal cancers.

Role of Virtual Biopsy in the Management of Renal Masses

OBJECTIVE. Renal masses comprise a heterogeneous group of pathologic conditions, including benign and indolent diseases and aggressive malignancies, complicating management. In this article, we explore the emerging role of imaging to provide a comprehensive noninvasive characterization of a renal mass-so-called "virtual biopsy"-and its potential use in the management of patients with renal tumors. CONCLUSION. Percutaneous renal mass biopsy (RMB) remains a valuable method to provide a presurgical histopathologic diagnosis of renal masses, but it is an invasive procedure and is not always feasible. Accumulating data support the use of imaging features to predict histopathology of renal masses. Imaging may help address some of the inherent limitations of RMB, and in certain settings, a multimodal clinical approach may allow decreasing the need for RMB.

Subtype Differentiation of Small (≤ 4 cm) Solid Renal Mass Using Volumetric Histogram Analysis of DWI at 3-T MRI

OBJECTIVE

The purpose of this article is to evaluate the utility of volumetric histogram analysis of apparent diffusion coefficient (ADC) derived from reduced-FOV DWI for small (≤ 4 cm) solid renal mass subtypes at 3-T MRI.

MATERIALS AND METHODS

This retrospective study included 38 clear cell renal cell carcinomas (RCCs), 16 papillary RCCs, 18 chromophobe RCCs, 13 minimal fat angiomyolipomas (AMLs), and seven oncocytomas evaluated with preoperative MRI. Volumetric ADC maps were generated using all slices of the reduced-FOV DW images to obtain histogram parameters, including mean, median, 10th percentile, 25th percentile, 75th percentile, 90th percentile, and SD ADC values, as well as skewness, kurtosis, and entropy. Comparisons of these parameters were made by one-way ANOVA, t test, and ROC curves analysis.

RESULTS

ADC histogram parameters differentiated eight of 10 pairs of renal tumors. Three subtype pairs (clear cell RCC vs papillary RCC, clear cell RCC vs chromophobe RCC, and clear cell RCC vs minimal fat AML) were differentiated by mean ADC. However, five other subtype pairs (clear cell RCC vs oncocytoma, papillary RCC vs minimal fat AML, papillary RCC vs oncocytoma, chromophobe RCC vs minimal fat AML, and chromophobe RCC vs oncocytoma) were differentiated by histogram distribution parameters exclusively (all p < 0.05). Mean ADC, median ADC, 75th and 90th percentile ADC, SD ADC, and entropy of malignant tumors were significantly higher than those of benign tumors (all p < 0.05). Combination of mean ADC with histogram parameters yielded the highest AUC (0.851; sensitivity, 80.0%; specificity, 86.1%).

CONCLUSION

Quantitative volumetric ADC histogram analysis may help differentiate various subtypes of small solid renal tumors, including benign and malignant lesions.

Novel imaging in renal cell carcinoma

PURPOSE OF REVIEW

Renal cell carcinoma is a heterogeneous disease with a spectrum of subtypes and clinical behavior. Quantitative and qualitative imaging biomarkers are sought to correlate with genetic and histologic features and complement pathologic analysis.

RECENT FINDINGS

Texture analysis, radiogenomics, and modality-specific advancements have yielded an array of renal cell carcinoma imaging biomarkers in the research domain. Although many techniques are promising, standardization and validation of these procedures are needed prior to implementation into clinical practice.

SUMMARY

We introduce novel imaging techniques and analytic methods which have been shown to contribute to characterization of renal cell carcinoma and its subtypes, aggressiveness, and responsiveness to therapy, including associated advantages and limitations.

Simultaneous Multislice Diffusion-Weighted Imaging of the Kidney: A Systematic Analysis of Image Quality

OBJECTIVES

The aims of this study were to implement a protocol for simultaneous multislice (SMS) accelerated diffusion-weighted imaging (DWI) of the kidneys and to perform a systematic analysis of image quality of the data sets.

MATERIALS AND METHODS

Ten healthy subjects and 5 patients with renal masses underwent DWI of the kidney in this prospective institutional review board-approved study on a 3 T magnetic resonance scanner. Simultaneous multislice DWI echo-planar sequences (acceleration factors [AFs] 2 and 3) were compared with conventional echo-planar DWI as reference standard for each acquisition scheme. The following 3 acquisition schemes were applied: comparison A, with increased number of acquisitions at constant scan time; comparison B, with reduction of acquisition time; and comparison C, with increased slice resolution (constant acquisition time, increasing number of slices). Interreader reliability was analyzed by calculating the intraclass correlation coefficient (ICC). Qualitative image quality features were evaluated by 2 independent radiologists on a 5-point Likert scale. Quantification accuracy of the apparent diffusion coefficients (ADCs) and signal-to-noise ratios (SNRs) were assessed by region of interest analysis. Furthermore, lesion conspicuity in the 5 patients was assessed using a 5-point Likert scale by 2 independent radiologists.

RESULTS

Interreader agreement was substantial with an ICC of 0.68 for the overall image quality and an ICC of 0.73 for the analysis of artifacts. In comparison A, AF2 resulted in increased SNR (P < 0.05) by 21% at stable image quality scores (image quality: P = 0.76, artifacts: P = 0.21). In comparison B, applying AF2, the scan time could be reduced by 46% without significant reduction in qualitative image quality scores (P = 0.059) or SNR (P = 0.126). In comparison C, slice resolution could be improved by 28% using AF2 with stable image quality scores and SNR. In general, AF3 resulted in reduced image quality and SNR. Significantly reduced ADC values were observed for AF3 in comparison C (cortex: P = 0.003; medulla: P = 0.001) compared with the standard echo-planar imaging sequence. The conventional DWI and the SMS DWI with AF2 showed stable lesion conspicuity ([AF1/AF2]: reader 1 [1.8/1.4] and reader 2 [1.8/1.4]). The lesion conspicuity was lower using AF3 (reader 1: 2.2 and reader 2: 1.8).

CONCLUSIONS

In conclusion, SMS DWI of the kidney is a potential tool to substantially reduce scan time without negative effects on SNR, ADC quantification accuracy, and image quality if an AF2 is used. Although AF3 results in even higher scan time reduction, a negative impact on image quality, SNR, ADC quantification accuracy, and lesion conspicuity must be considered.

Renal clear cell carcinoma: diffusion tensor imaging diagnostic accuracy and correlations with clinical and histopathological factors

AIM

To investigate whether diffusion tensor imaging (DTI) can be used to assess renal clinical histopathology, including the nuclear grade (NG), cell density (CD), and the presence of ki-67.

MATERIALS AND METHODS

Thirty patients were enrolled in the study and were confirmed at surgical histopathology to have clear cell renal cell carcinoma (CCRCC). For DTI, a coronal echo-planar imaging sequence was performed (1400 ms repetition time, 76 ms echo time, diffusion direction=6, number of excitations=4; b=0 and 800 s/mm², 6 mm section thickness with no intersection gap). CD and the presence of ki-67 were compared between the different NGs. Correlations between apparent diffusion coefficients (ADCs), E1, fractional anisotropy (FA), CD, and ki-67 were evaluated.

RESULTS

ADC, E1, and FA values are important tools used to identify NG. The cut-off values were 1.003×10^-3 mm²/s, 1.277×10^-3 mm²/s, and 0.218 mm²/s, respectively. The difference between high- and low-grade CD was significant (t=-4.50, p<0.05). Similarly, a significant difference between high and low grade was also found in ki-67 (t=-4.03, p<0.05). ADC, E1, and FA values were decreased with increased CD; a significant negative correlation was found (r=-0.796, -0.865, and -0.996, respectively). Significant negative correlations between ADC, E1, and FA values, and ki-67 were found (r=-0.739, -0.826, and -0.876, respectively).

CONCLUSIONS

DTI can be used to non-invasively assess CCRCC.

Diffusion-Weighted Genitourinary Imaging

This review article aims to provide an overview on of diffusion-weighted MR imaging (DW-MR imaging) in the urogenital tract. Compared with conventional cross-sectional imaging methods, the additional value of DW-MR imaging in the detection and further characterization of benign and malignant lesions of the kidneys, bladder, prostate, and pelvic lymph nodes is discussed as well as the role of DW-MR imaging in the evaluation of treatment response.

Challenges of advanced hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is an aggressive malignancy, resulting as the third cause of death by cancer each year. The management of patients with HCC is complex, as both the tumour stage and any underlying liver disease must be considered conjointly. Although surveillance by imaging, clinical and biochemical parameters is routinely performed, a lot of patients suffering from cirrhosis have an advanced stage HCC at the first diagnosis. Advanced stage HCC includes heterogeneous groups of patients with different clinical condition and radiological features and sorafenib is the only approved treatment according to Barcelona Clinic Liver Cancer. Since the introduction of sorafenib in clinical practice, several phase III clinical trials have failed to demonstrate any superiority over sorafenib in the frontline setting. Loco-regional therapies have also been tested as first line treatment, but their role in advanced HCC is still matter of debate. No single agent or combination therapies have been shown to impact outcomes after sorafenib failure. Therefore this review will focus on the range of experimental therapeutics for patients with advanced HCC and highlights the successes and failures of these treatments as well as areas for future development. Specifics such as dose limiting toxicity and safety profile in patients with liver dysfunction related to the underlying chronic liver disease should be considered when developing therapies in HCC. Finally, robust validated and reproducible surrogate end-points as well as predictive biomarkers should be defined in future randomized trials.

Role of Multiparametric MR Imaging in Malignancies of the Urogenital Tract

Multiparametric MR imaging (mpMRI) combine different sequences that, properly tailored, can provide qualitative and quantitative information about the tumor microenvironment beyond traditional tumor size measures and/or morphologic assessments. This article focuses on mpMRI in the evaluation of urogenital tract malignancies by first reviewing technical aspects and then discussing its potential clinical role. This includes insight into histologic subtyping and grading of renal cell carcinoma and assessment of tumor response to targeted therapies. The clinical utility of mpMRI in the staging and grading of ureteral and bladder tumors is presented. Finally, the evolving role of mpMRI in prostate cancer is discussed.

The spectrum of renal cell carcinoma in adults

The spectrum of renal cell carcinoma (RCC) includes many neoplasms with distinct cytogenetics, biologic behaviors, and imaging appearances. The advent of molecular therapies targeting different tumor types, new insights into the relative roles of biopsy and surveillance for small incidental tumors, and a growing array of nephron-sparing interventions have altered management of RCC. Similarly, the role of the radiologist is changing, and it is becoming increasingly important for radiologists to familiarize themselves with the various types of RCC. This article introduces the reader to the common and uncommon recognized types of renal cell carcinoma and discusses how these neoplasms differ in imaging appearance and behavior.

Diagnostic value of strain elastography for differentiation between renal cell carcinoma and transitional cell carcinoma of kidney

PURPOSE

The objective of our study was to prospectively evaluate the diagnostic performance of strain elastography for differentiation between renal cell carcinomas (RCCs) and transitional cell carcinomas (TCCs) of kidney.

METHODS

A total of 99 consecutive patients who were referred to our hospital because of a newly diagnosed solid renal mass suspicious for malignancy on radiological screenings were evaluated with sonography, including strain elastography. Strain elastography was used to compare the stiffness of the renal masses and renal cortex. The ratio of strain in a renal mass and nearby renal cortex was defined as the strain index value. Mean strain index values for RCCs and TCCs were compared, and mean strain index values between histological subtypes of RCC were also compared.

RESULTS

Although TCCs were smaller than RCCs (p < 0.001), there were no significant differences in gender distribution and mean age of the patients, and mean probe-tumor distance between RCC and TCC. The mean strain index value ±SD for TCC (5.18 ± 1.12) was significantly higher than the value for RCC (4.04 ± 0.72; p < 0.001). Mean strain index value for papillary cell carcinomas (4.09 ± 0.45) was slightly higher than that for clear cell carcinomas (3.85 ± 0.78): however, the difference was not statistically significant (p = 0.51).

CONCLUSIONS

Strain elastography can be used as a valuable imaging technique for preoperative differentiation between RCC and TCC of kidney.

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.

CT Textural Analysis of Large Primary Renal Cell Carcinomas: Pretreatment Tumor Heterogeneity Correlates With Histologic Findings and Clinical Outcomes

OBJECTIVE

The purpose of the present study is to determine whether CT texture features of newly diagnosed primary renal cell carcinomas (RCCs) correlate with pathologic features and oncologic outcomes.

MATERIALS AND METHODS

CT texture analysis was performed on large (> 7 cm; mean size, 9.9 cm) untreated RCCs in 157 patients (52 women and 105 men; mean age, 60.3 years). Measures of tumor heterogeneity, including entropy, kurtosis, skewness, mean, mean of positive pixels, and SD of pixel distribution histogram were derived from multiphasic CT using various filter settings: unfiltered (spatial scaling factor, 0), fine (spatial scaling factor, 2), medium (spatial scaling factor, 3-4), or coarse (spatial scaling factor, 5-6). Texture values were correlated with histologic subtype, nuclear grade, pathologic stage, and clinical outcome.

RESULTS

When a coarse filter setting (spatial scaling factor, 6) was used, entropy on portal venous phase CT images was positively associated with clear cell histologic findings (odds ratio [OR], 134; 95% CI, 16-1110; p < 0.001) and was negatively associated with non-clear cell subtype findings (papillary spatial scale factor, 6; OR, 0.016; 95% CI, 0.002-0.132; p < 0.001). ROC curve analysis for entropy (on portal venous phase images obtained with a spatial scaling factor of 6) revealed an AUC of 0.943 (95% CI, 0.892-0.993) for clear cell histologic findings, with similar values noted for non-clear cell histologic findings. The mean of positive pixels and the SD of the pixel distribution histogram were statistically significantly associated with histologic cell type in a similar fashion. Entropy, the SD of the pixel distribution histogram, and the mean of positive pixels were associated with nuclear grade, most prominently when fine or medium texture filters were used (p < 0.05). There was a statistically significant association of texture features noted on unenhanced CT, including the SD of the pixel distribution histogram, the mean of positive pixels, and entropy, with the time to disease recurrence and death due to disease (e.g., for entropy noted on unenhanced CT images obtained with a spatial scaling factor of 6, the hazard ratio was 3.49 [95% CI, 1.55-7.84]; p = 0.002).

CONCLUSION

CT texture features (in particular, entropy, the mean of positive pixels, and the SD of the pixel distribution histogram) are associated with tumor histologic findings, nuclear grade, and outcome measures. The contrast phase does seem to affect heterogeneity measures.

Fifty Years of Technological Innovation: Potential and Limitations of Current Technologies in Abdominal Magnetic Resonance Imaging and Computed Tomography

Magnetic resonance imaging (MRI) has become an important modality for the diagnosis of intra-abdominal pathology. Hardware and pulse sequence developments have made it possible to derive not only morphologic but also functional information related to organ perfusion (dynamic contrast-enhanced MRI), oxygen saturation (blood oxygen level dependent), tissue cellularity (diffusion-weighted imaging), and tissue composition (spectroscopy). These techniques enable a more specific assessment of pathologic lesions and organ functionality. Magnetic resonance imaging has thus transitioned from a purely morphologic examination to a modality from which image-based disease biomarkers can be derived. This fits well with several emerging trends in radiology, such as the need to accurately assess response to costly treatment strategies and the need to improve lesion characterization to potentially avoid biopsy. Meanwhile, the cost-effectiveness, availability, and robustness of computed tomography (CT) ensure its place as the current workhorse for clinical imaging. Although the lower soft tissue contrast of CT relative to MRI is a long-standing limitation, other disadvantages such as ionizing radiation exposure have become a matter of public concern. Nevertheless, recent technical developments such as dual-energy CT or dynamic volume perfusion CT also provide more functional imaging beyond morphology.The aim of this article was to review and discuss the most important recent technical developments in abdominal MRI and state-of-the-art CT, with an eye toward the future, providing examples of their clinical utility for the evaluation of hepatic and renal pathologies.

Bench to bedside molecular functional imaging in translational cancer medicine: to image or to imagine?

Ongoing research on malignant and normal cell biology has substantially enhanced the understanding of the biology of cancer and carcinogenesis. This has led to the development of methods to image the evolution of cancer, target specific biological molecules, and study the anti-tumour effects of novel therapeutic agents. At the same time, there has been a paradigm shift in the field of oncological imaging from purely structural or functional imaging to combined multimodal structure-function approaches that enable the assessment of malignancy from all aspects (including molecular and functional level) in a single examination. The evolving molecular functional imaging using specific molecular targets (especially with combined positron-emission tomography [PET] computed tomography [CT] using 2- [(18)F]-fluoro-2-deoxy-D-glucose [FDG] and other novel PET tracers) has great potential in translational research, giving specific quantitative information with regard to tumour activity, and has been of pivotal importance in diagnoses and therapy tailoring. Furthermore, molecular functional imaging has taken a key place in the present era of translational cancer research, producing an important tool to study and evolve newer receptor-targeted therapies, gene therapies, and in cancer stem cell research, which could form the basis to translate these agents into clinical practice, popularly termed "theranostics". Targeted molecular imaging needs to be developed in close association with biotechnology, information technology, and basic translational scientists for its best utility. This article reviews the current role of molecular functional imaging as one of the main pillars of translational research.

Is low b-factors-based apparent diffusion coefficient helpful in assessing renal dysfunction?

PURPOSE

To investigate whether low b-factors-based apparent diffusion coefficient (ADC) is helpful in assessing renal dysfunction.

MATERIALS AND METHODS

Forty-four subjects were recruited, and classified as having severe renal injury group (sRI) or not (non-sRI) according to a threshold of estimated glomerular filtration rate (eGFR) = 30 ml/min/1.73 m(2). A free-breathing DWI with 7 b-factors (0, 20, 40, 80, 200, 400, and 800 s/mm(2)) was performed. After choosing an anatomical section that covered the largest part of right kidney, the regions of interest covered the renal parenchyma. For each subject, two apparent diffusion coefficients based on all b-factors less than 400 s/mm(2) (ADC0-400) and 800 s/mm(2) (ADC0-800) were calculated by fitting the signal intensity at different b-factors to a mono-exponential decay, respectively. It was found that the examination time of the free-breathing DWI sequence in this study can be reduced from 3.27 to 2.55 min if the b-factor (800 s/mm(2)) is removed.

RESULTS

ADC0-400 was larger than ADC0-800 in each group (P < 0.05). Both ADC0-400 and ADC0-800 were smaller in the sRI group than those in the non-sRI group (P < 0.01), and they were linearly related with eGFR (P < 0.05). While a significant difference was not found between the two coefficients to differentiate sRI from non-sRI participants (P > 0.05), a strong correlation was present between ADC0-400 and ADC0-800 (r = 0.856, P < 0.001).

CONCLUSION

The low b-factors-based ADC was an economical option for reducing the examination time without sacrificing its diagnostic performance.

Diffusion-weighted MRI of kidneys in healthy volunteers and living kidney donors

AIM

To establish the normal apparent diffusion coefficient (ADC) values in healthy kidneys, comparing them with the literature, and assessing the correlation between ADC values, creatinine blood level, and glomerular filtration rate (GFR).

MATERIALS AND METHODS

Twenty-four healthy volunteers and 26 living kidney donors were examined on a 1.5 T magnetic resonance imaging (MRI) unit. Two diffusion-weighted imaging (DWI) sequences were included in the study protocol (protocol 1 with 16 b-values, protocol 2 with 10 b-values) before the examination blood and urine samples were collected. The GFR was calculated using Cockcroft & Gault and MDRD (Modification of Diet In Renal Disease) formulas and the ADC values were measured separately for the cortex and medulla of each kidney by two independent observers. All statistical analyses were performed using the STATISTICA (version 10.0) software package. Data were analysed using an unpaired t-test; p < 0.05 indicated a statistically significant difference.

RESULTS

The average ADC value for protocol 1 for the cortex was 2.26 × 10(-3) mm(2)/s, for the medulla 2.21 × 10(-3) mm(2)/s. In protocol 2, the respective values were 2.13 × 10(-3) mm(2)/s and 2.06 × 10(-3) mm(2)/s. Neither statistically significant interobserver differences nor correlation between ADC values, GFR, and creatinine serum level were observed.

CONCLUSION

The reference ADC values were established. The measurements show high interobserver consistency. The differences in ADC values reported in the literature suggest dependence on the equipment and methodology and point to the necessity of obtaining ADC norms for each MRI unit.

The value of blood oxygenation level-dependent (BOLD) MR imaging in differentiation of renal solid mass and grading of renal cell carcinoma (RCC): analysis based on the largest cross-sectional area versus the entire whole tumour

Objectives

To study the value of assessing renal masses using different methods in parameter approaches and to determine whether BOLD MRI is helpful in differentiating RCC from benign renal masses, differentiating clear-cell RCC from renal masses other than clear-cell RCC and determining the tumour grade.

Methods

Ninety-five patients with 139 renal masses (93 malignant and 46 benign) who underwent abdominal BOLD MRI were enrolled. R2* values were derived from the largest cross-section (R2*_largest) and from the whole tumour (R2*_whole). Intra-observer and inter-observer agreements were analysed based on two measurements by the same observer and the first measurement from each observer, respectively, and these agreements are reported with intra-class correlation coefficients and 95% confidence intervals. The diagnostic value of the R2* value in the evaluation was assessed with receiver-operating characteristic analysis.

Results

The intra-observer agreement was very good for R2*_largest and R2*_whole (all > 0.8). The inter-observer agreement of R2*_whole (0.75, 95% confidence interval: 0.69~0.79) was good and was significantly improved compared with the R2*_largest (0.61, 95% confidence interval: 0.52~0.68), as there was no overlap in the 95% confidence interval of the intra-class correlation coefficients. The diagnostic value in differentiating renal cell carcinoma from benign lesions with R2*_whole (AUC=0.79/0.78[observer1/observer2]) and R2*_largest (AUC=0.75[observer1]) was good and significantly higher (p=0.01 for R2*_largest[observer2] vs R2*_whole[observer2], p<0.01 for R2*_whole[observer1] vs R2*_largest[observer2]) than R2*_largest for observer 2 (AUC=0.64). For the grading of clear-cell RCC, both R2*_whole and R2*_largest were good (all > 0.7) and were not significantly different (p=0.89/0.93 for R2*largest vs R2*whole[observer1/observer2], 0.96 for R2*whole[observer1] vs R2*largest[observer2] and 0.96 for R2*whole [observer2] vs R2*largest[observer1]).

Conclusions

BOLD MRI could provide a feasible parameter for differentiating renal cell carcinoma from benign renal masses and for predicting clear-cell renal cell carcinoma grading. Compared with the largest cross-section, assessing the whole tumour provides better inter-observer agreement in parameter measurement for differentiating renal cell carcinoma from benign renal masses.