Differential diagnosis of the small renal masses: role of the apparent diffusion coefficient of the diffusion-weighted MRI

Differentiation of solid and friable tumour thrombus in patients with renal cell carcinoma: The role of MRI apparent diffusion coefficient

PURPOSE

Inferior vena cava (IVC) involvement by renal cell carcinoma (RCC) is associated with a higher disease stage and is considered a risk factor for poor prognosis. This study aimed to investigate the role of the apparent diffusion coefficient (ADC) of MRI 3D texture analysis in the differentiation of solid and friable tumour thrombus in patients with RCC.

MATERIALS AND METHODS

The study involved 27 patients with RCC with tumour thrombus in the renal vein or IVC, surgically treated with nephrectomy and thrombectomy and in whom preoperatively abdominal MRI including the DWI sequence was conducted. For 3D texture analysis, the ADC map was used, and the first-order radiomic features were calculated from the whole volume of the thrombus. All tumour thrombi were histologically classified as solid or friable.

RESULTS

The solid and friable thrombus was detected in 51.9 ​% and 48.1 ​% of patients, respectively. No differences in mean values of range, 90th percentile, interquartile range, kurtosis, uniformity and variance were found between groups. Equal sensitivity and specificity (93 ​% and 69 ​%, respectively) of ADC mean, median and entropy in differentiation between solid and friable tumour thrombus, with the highest AUC for entropy (0.808), were observed. Applying the skewness threshold value of 0.09 allowed us to achieve a sensitivity of 86 ​% and a specificity of 92 ​%.

CONCLUSIONS

In patients with RCC and tumour thrombus in the renal vein or IVC, the 3D texture analysis based on ADC-map allows for precise differentiation of a solid from a friable thrombus.

Evaluation of contrast-enhanced ultrasound for predicting tumor grade in small (≤4 cm) clear cell renal cell carcinoma: Qualitative and quantitative analysis

OBJECTIVE

The study aimed to evaluate the utility of qualitative and quantitative analysis employing contrast-enhanced ultrasound (CEUS) in predicting the WHO/ISUP grade of small (≤4 cm) clear cell renal cell carcinoma (ccRCCs).

METHODS

Patients with small ccRCCs, confirmed by histological examination, underwent preoperative CEUS and were classified into low- (grade I/II) and high-grade (grade III/IV) groups. Qualitative and quantitative assessments of CEUS were conducted and compared between the two groups. Diagnostic performance was assessed using receiver operating characteristic curves.

RESULTS

A total of 72 patients were diagnosed with small ccRCCs, comprising 23 individuals in the high-grade group and 49 in the low-grade group. The low-grade group exhibited a significantly greater percentage of hyper-enhancement compared to the high-grade group (79.6% VS 39.1%, P < 0.05). The low-grade group showed significantly higher relative index values for peak enhancement, wash-in area under the curve, wash-in rate, wash-in perfusion index, and wash-out rate compared to the high-grade group (all P < 0.05). The AUC values for qualitative and quantitative parameters in predicting the WHO/ISUP grade of small ccRCCs ranged from 0.676 to 0.756.

CONCLUSIONS

Both qualitative and quantitative CEUS analysis could help to distinguish the high- from low-grade small ccRCCs.

To characterize small renal cell carcinoma using diffusion relaxation correlation spectroscopic imaging and apparent diffusion coefficient based histogram analysis: a preliminary study

PURPOSE

To study the capability of diffusion-relaxation correlation spectroscopic imaging (DR-CSI) on subtype classification and grade differentiation for small renal cell carcinoma (RCC). Histogram analysis for apparent diffusion coefficient (ADC) was studied for comparison.

MATERIALS AND METHODS

A total of 61 patients with small RCC (< 4 cm) were included in the retrospective study. MRI data were reviewed, including a multi-b (0-1500 s/mm2) multi-TE (51-200 ms) diffusion weighted imaging (DWI) sequence. Region of interest (ROI) was delineated manually on DWI to include solid tumor. For each patient, a D-T2 spectrum was fitted and segmented into 5 compartments, and the volume fractions VA, VB, VC, VD, VE were obtained. ADC mapping was calculated, and histogram parameters ADC 90th, 10th, median, standard deviation, skewness and kurtosis were obtained. All MRI metrices were compared between clear cell RCC (ccRCC) and non-ccRCC group, and between high-grade and low-grade group. Receiver operator curve analysis was used to assess the corresponding diagnostic performance.

RESULTS

Significantly higher ADC 90th, ADC 10th and ADC median, and significantly lower DR-CSI VB was found for ccRCC compared to non-ccRCC. Significantly lower ADC 90th, ADC median and significantly higher VB was found for high-grade RCC compared to low-grade. For identifying ccRCC from non-ccRCC, VB showed the highest area under curve (AUC, 0.861) and specificity (0.882). For differentiating high- from low-grade, ADC 90th showed the highest AUC (0.726) and specificity (0.786), while VB also displayed a moderate AUC (0.715).

CONCLUSION

DR-CSI may offer improved accuracy in subtype identification for small RCC, while do not show better performance for small RCC grading compared to ADC histogram.

Comparison of conventional diffusion-weighted imaging and intravoxel incoherent motion in differentiating between chromophobe renal cell carcinoma and renal oncocytoma: a preliminary study

OBJECTIVE

Quantitative comparison of the diagnostic efficacy of conventional diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) in differentiating between chromophobe renal cell carcinoma (ChRCC) from renal oncocytoma (RO).

METHODS

A total of 48 patients with renal tumours who had undergone DWI and IVIM were divided into two groups-ChRCC (n = 28) and RO (n = 20) groups, and the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f) and their diagnostic efficacy were compared between the two groups.

RESULTS

The D* values were higher in the ChRCCs group compared to the RO groups (0.019 ± 0.003 mm2/s vs 0.008 ± 0.002 mm2/s, P < .05). Moreover, the ADC, D and f values were higher in ROs compared to ChRCCs (0.61 ± 0.08 × 10-3 mm2/s vs 0.51 ± 0.06 × 10-3 mm2/s, 1.02 ± 0.15 × 10-3 mm2/s vs 0.86 ± 0.07 × 10-3 mm2/s, 0.41 ± 0.05 vs 0.28 ± 0.02, P < .05). The areas of the ADC, D, D* and f values under the ROC curves in differentiating ChRCCs from ROs were 0.713, 0.839, 0.856 and 0.906, respectively. The cut-off values of ADC, D, D* and f were 0.54, 0.91, 0.013 and 0.31, respectively. The AUC, sensitivity, specificity and accuracy of the f values were 0.906, 89.3%, 80.0% and 89.6%, respectively. For pairwise comparisons of ROC curves and diagnostic efficacy, IVIM parameters, that is, D, D* and f offered better diagnostic accuracy than ADC in differentiating ChRCCs from ROs (P = .013, .016, and .008) with f having the highest diagnostic accuracy.

CONCLUSION

IVIM parameters presented better performance than ADC in differentiating ChRCCs from ROs.

ADVANCES IN KNOWLEDGE

(1) D* values of ChRCCs were higher, while ADC, D and f values were lower than those of RO tumours. (2) f values had the highest diagnostic efficacy in differentiating ChRCC from RO. (3) IVIM parameters, that is, D, D* and f offered better diagnostic accuracy than ADC in differentiating ChRCC from RO (P=.013, .016, and .008).

Diagnostic performance of diffusion-weighted imaging and intravoxel incoherent motion for renal lesions: a meta-analysis

AIM

To compare the diagnostic performance of diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) parameters, specifically true diffusion coefficient (D), pseudo diffusion coefficient (D∗), and perfusion fraction (f) for quantitatively differentiating benign and malignant renal lesions.

MATERIALS AND METHODS

A comprehensive search was conducted in the EMBASE and PubMed databases before September 2022 to identify studies in English investigating the diagnostic accuracy of DWI and IVIM in renal lesions. The quality of the included studies was assessed using the QUADAS-2 tool. Pooled sensitivity, specificity, and area under the curve (AUC) values were estimated for each parameter.

RESULTS

A total of 19 studies involving 1,860 renal lesions (1,160 malignant and 700 benign), met the inclusion criteria. Among these studies, 15 assessed the apparent diffusion coefficient (ADC), four assessed IVIM, and three evaluated both ADC and IVIM. The pooled sensitivity, specificity, and AUC for ADC were 0.84 (95% confidence interval [Cl], 0.79-0.88), 0.82 (95% Cl, 0.72-0.89), and 0.89 (95% Cl, 0.86-0.92), respectively. The IVIM parameter with the highest diagnostic accuracy was D, with a pooled sensitivity, specificity, and AUC of 0.89 (95% Cl, 0.74-0.96), 0.96 (95% Cl, 0.85-0.99), and 0.98 (95% Cl, 0.96-0.99), respectively. The pooled sensitivity, specificity and AUC for f were 0.67 (95% Cl, 0.55-0.77), 0.81 (95% Cl, 0.30-0.98), and 0.73 (95% Cl, 0.69-0.77), respectively. The pooled sensitivity, specificity, and AUC for D∗ were 0.87 (95% Cl, 0.81-0.91), 0.59 (95% Cl, 0.48-0.70), and 0.82 (95% Cl, 0.78-0.85), respectively.

CONCLUSION

This meta-analysis indicated that both IVIM and DWI had moderate to high diagnostic accuracy for differentiating benign and malignant renal lesions. Among the IVIM parameter, D exhibited the highest diagnostic accuracy, demonstrating higher sensitivity and specificity than ADC, D∗, and f.

MRI for the detection of small malignant renal masses: a systematic review and meta-analysis

Objective

We aimed to review the available evidence on the diagnostic performance of magnetic resonance imaging in differentiating malignant from benign small renal masses.

Methods

An electronic literature search of Web of Science, MEDLINE (Ovid and PubMed), Cochrane Library, EMBASE, and Google Scholar was performed to identify relevant articles up to 31 January 2023. We included studies that reported the diagnostic accuracy of using magnetic resonance imaging to differentiate small (≤4 cm) malignant from benign renal masses. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated using the bivariate model and the hierarchical summary receiver operating characteristic model. The study quality evaluation was performed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

Results

A total of 10 studies with 860 small renal masses (815 patients) were included in the current meta-analysis. The pooled sensitivity and specificity of the studies for the detection of malignant masses were 0.85 (95% CI 0.79-0.90) and 0.83 (95% CI 0.67-0.92), respectively.

Conclusions

MRI had a moderate diagnostic performance in differentiating small malignant renal masses from benign ones. Substantial heterogeneity was observed between studies for both sensitivity and specificity.

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.

Local recurrence of renal cell carcinoma after partial nephrectomy: applicability of the apparent diffusion coefficient of MRI as an imaging marker - a multicentre study

Purpose

The goal of the study was an assessment of the diagnostic performance of diffusion-weighted images (DWI) and apparent diffusion coefficient (ADC) of magnetic resonance imaging (MRI) in distinguishing local recurrence (LR) of renal cell carcinoma (RCC) from benign conditions after partial nephrectomy.

Material and methods

Thirty-nine patients after partial nephrectomy for solid RCC were enrolled in the study. Patients were followed up using MRI, which included DWI sequence (b = 800 s/mm²). All patients with MRI features of LR were included in the main group (n = 14) and patients without such features – into the group of comparison (n = 25). Apparent diffusion coefficient (ADC) values of suspicious lesions were recorded. In all patients with signs of locally recurrent RCC, surgical treatment was performed followed by pathologic analysis.

Results

The mean ADC values of recurrent RCC demonstrated significantly higher numbers compared to benign fibrous tissues and were 1.64 ± 0.15 × 10^-3 mm²/s vs. 1.02 ± 0.26 × 10^-3 mm²/s (p < 0.001). The mean ADC values of RCCs’ LR and benign post-op changes in renal scar substantially differed from mean ADC values of healthy kidneys’ parenchyma; the latter was 2.58 ± 0.05 × 10^-3 mm²/s (p < 0.001). In ROC analysis, the use of ADC with a threshold value of 1.28 × 10^-3 mm²/s allowed us to differentiate local recurrence of RCC from benign postoperative changes with 100% sensitivity, 80% specificity, and accuracy: AUC = 0.980 (p < 0.001).

Conclusions

The apparent diffusion coefficient of DWI of MRI can be used as a potential imaging marker for the diagnosis of local recurrence of RCC.

THE ROLE OF THE APPARENT DIFFUSION COEFFICIENT OF THE BIPARAMETRIC MRI AS AN IMAGING MARKER OF PROSTATE CANCER

Prostate cancer (PCa) is the most common malignancy in men. The role of the apparent diffusion coefficient (ADC)of biparametric MRI (biMRI) which is a study without the use of dynamic contrast enhancement (DCE), in detectionof PCa is still not comprehensively investigated.

OBJECTIVE

The goal of the study was to assess the role of ADC of biMRI as an imaging marker of clinically significant PCaMaterials and methods. The study involved 78 men suspected of having PCa. All patients underwent a comprehensive clinical examination, which included multiparametric MRI of the prostate, a component of which was biMRI. TheMRI data was evaluated according to the PIRADS system version 2.1.

RESULTS

The distribution of patients according to the PIRADS system was as follows: 1 point - 9 (11.54 %)patients, 2 points - 12 (15.38 %) patients, 3 points - 25 (32.05 %) patients, 4 points - 19 (24.36 %) patients and5 points - 13 (16.67 %) patients. In a subgroup of patients with 5 points, clinically significant PCa was detected in 100 % of cases. In the subgroup of patients with tumors of 4 points clinically significant PCa was diagnosed in 16of 19 (84.21 %) cases, and in 3 (15.79 %) patients - clinically insignificant tumor. In the subgroup of patients with3 points, clinically significant PCa was diagnosed in 11 of 25 (44.0 %) cases, in 8 (32.0 %) patients - clinicallyinsignificant tumor and in 6 (24.0 %) patients - benign prostatic hyperplasia. PCa with a score of 7 on the Gleasonscale showed significantly lower mean values of ADC of the diffusion weighted MRI images compared to tumors witha score of < 7 on the Gleason scale: (0.86 ± 0.07) x 103 mm2/s vs (1.08 ± 0.04) x 103 mm2/s (р < 0.05).

CONCLUSIONS

The obtained results testify to the high informativeness of biMRI in the diagnosis of prostate cancer.The use of ADC allowed to differentiate clinically significant and insignificant variants of the tumor, as well asbenign changes in prostate tissues and can be considered as a potential imaging marker of PCa.

Kidney tumor diffusion-weighted magnetic resonance imaging derived ADC histogram parameters combined with patient characteristics and tumor volume to discriminate oncocytoma from renal cell carcinoma

PURPOSE

To assess the ability to discriminate oncocytoma from RCC based on a model using whole tumor ADC histogram parameters with additional use of tumor volume and patient characteristics.

METHOD

In this prospective study, 39 patients (mean age 65 years, range 28-79; 9/39 (23%) female) with 39 renal tumors (32/39 (82%) RCC and 7/39 (18%) oncocytoma) underwent multiparametric MRI between November 2014 and June 2018. Two regions of interest (ROIs) were drawn to cover both the entire tumor volume and a part of healthy renal cortex. ROI ADC maps were calculated using a mono-exponential model and ADC histogram distribution parameters were calculated. A logistic regression model was created using ADC histogram parameters, radiographic and patient characteristics that were significantly different between oncocytoma and RCC. A ROC curve of the model was constructed and the AUC, sensitivity and specificity were calculated. Furthermore, differences in intra-patient ADC histogram parameters between renal tumor and healthy cortex were calculated. A separate ROC curve was constructed to differentiate oncocytoma from RCC using statistically significant intra-patient parameter differences.

RESULTS

ADC standard deviation (p = 0.008), entropy (p = 0.010), tumor volume (p = 0.012), and patient sex (p = 0.018) were significantly different between RCC and oncocytoma. The regression model of these parameters combined had an ROC-AUC of 0.91 with a sensitivity of 86% and specificity of 84%. Intra-patient difference in ADC 25th percentile (p < 0.01) and entropy (p = 0.030) combined had a ROC-AUC of 0.86 with a sensitivity and specificity of 86%, and 81%, respectively.

CONCLUSION

A model combining ADC standard deviation and entropy with tumor volume and patient sex has the highest diagnostic value for discrimination of oncocytoma. Although less accurate, intra-patient difference in ADC 25th percentile and entropy between renal tumor and healthy cortex can also be used. Although the results of this preliminary study do not yet justify clinical use of the model, it does stimulate further research using whole tumor ADC histogram parameters.

Functional magnetic resonance imaging for distinguishing type of papillary renal cell carcinoma: a preliminary study

OBJECTIVE

To investigate the feasibility of magnetic resonance diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) for distinguishing Type 1 and 2 of papillary renal cell carcinoma (PRCC).

METHODS

A total of Type 1 (n = 20) and Type 2 (n = 16) of PRCC were examined by pathology. For DKI and IVIM, mean diffusivity (MD), fractional anisotropy (FA), mean kurtosis (MK), kurtosis anisotropy (KA), radial kurtosis (RK), diffusivity (D), pseudodiffusivity (D*) and perfusion fraction (f) were performed in assessment of type of PRCC.

RESULTS

The mean SNRs of IVIM and DKI images at b = 1500 and 2000 s/mm² were 8.6 ± 0.8 and 7.8 ± 0.6. Statistically significant differences were observed in MD and D values (1.11 ± 0.23 vs 0.73 ± 0.13, 0.91 ± 0.24 vs 0.49 ± 0.13, p < 0.05) between Type 1 and Type 2 of PRCC, while comparable FA, RK, D* and f values were found between Type 1 and Type 2 of PRCC (p > 0.05). Statistically significant differences were observed in MK and KA values (1.23 ± 0.16 vs 1.91 ± 0.26, 1.49 ± 0.19 vs 2.36 ± 0.39, p < 0.05) between Type 1 and Type 2 of PRCC. Areas of MD, MK, KA and D values under ROC curves for differentiating Type 1 and Type 2 of PRCC were 0.836, 0.818, 0.881 and 0.766, respectively. Using MD, MK, KA and D values of 0.93, 1.64, 1.94, 0.68 as the threshold value for differentiating Type 1 from Type 2 of PRCC, the best result obtained had a sensitivity of 85.0%, 80.0%, 90.0%, 85.0%, a specificity 75.0%, 68.7%, 87.5%, 81.2%, and an accuracy of 83.3%, 80.5%, 88.9%, 86.1%, respectively.

CONCLUSION

DKI and IVIM are feasible techniques for distinguishing type of PRCC, given an adequate SNR of IVIM and DKI images.

ADVANCES IN KNOWLEDGE

1. MD and D values are higher for Type 1 of PRCC and lower for Type 2 of PRCC.2. MK and KA values are higher for Type 2 of PRCC and lower for Type 1 of PRCC.3. DKI and IVIM can be used as clinical biomarker for PRCC type's differential diagnosis, given an adequate SNR.

The diagnostic utility of diffusion weighted MRI imaging and ADC ratio to distinguish benign from malignant renal masses: sorting the kittens from the tigers

Background

MRI is playing an increasing role in risk stratification and non-invasive diagnosis of the undifferentiated small renal mass. This study was designed to assess the reliability of MRI in diagnostic evaluation of renal masses, specifically characterising lesions with diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) values.

Methods

This is a retrospective analysis of patients undergoing MRI as part of their clinical workup for a renal mass suspicious for renal cell carcinoma (RCC) on CT or ultrasound followed by biopsy and/or surgical excision. All cases were conducted on 3 Tesla MRI, with conventional breath-held sequences, DWI and dynamic contrast enhanced phases. Tumour regions of interest were evaluated on ADC maps and compared with T2 weighted and post-contrast images.

Results

Of the 66 renal tumours included, 33 (50.0%) were Clear Cell RCC, 11 (16.7%) were Oncocytoma, nine (13.6%) were Angiomyolipoma (AML), nine (13.6%) were Papillary RCC and four (6.1%) were Chromophobe RCC. Oncocytoma had the largest ADC values, significantly larger than AMLs and all RCC subtypes (p < 0.001). The average ADC value was also significantly larger in Clear Cell RCCs compared to AMLs, and other RCC subtypes (p < 0.001).

Conclusions

MRI with DWI/ADC imaging may aid the differentiation of oncocytomas from RCCs and stratify RCC subtypes, Further studies are required to validate these findings.

Trial registration: Not applicable/retrospective study.

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.

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.

Diagnostic accuracy of contrast-enhanced ultrasound in the detection of small renal masses: A protocol of systematic review and meta-analysis

BACKGROUND

The small renal masses (SRMs) were defined that the diameter of renal masses measured by enhanced image was ≤4 cm. The diagnostic accuracy of contrast-enhanced ultrasound (CEUS) for SRMs is apparently variable among previous studies. Hence, this study will evaluate the diagnostic accuracy of CEUS in the identification of benign and malignant SRMs.

METHODS

A comprehensive search using the databases of Cochrane Library, Embase, PubMed, WANGFANG, and China National Knowledge Infrastructure will be carried out to identify studies in which patients with SRMs are assessed by CEUS. Two investigators will independently screen the literature and extract the data. Any discrepancies will be resolved via discussion with the senior author. Study quality will be assessed by the Quality Assessment of Diagnostic Accuracy Studies 2 tool, and pooled sensitivity and specificity of various CEUS findings for the diagnosis of SRMs will be determined. Summary receiver operating characteristic curve will be used to assess the overall performance of CEUS.

RESULTS

This study will evaluate the diagnostic accuracy of CEUS for the diagnosis of SRMs through sensitivity, specificity, positive and negative likelihood ratio, and diagnostic odds ratio.

CONCLUSION

This study will summarize the most recent evidence that focusing on the diagnosis of CEUS for SRMs.

STUDY REGISTRATION

INPLASY202060040.

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.

Choosing The Right Animal Model for Renal Cancer Research

The increase in the life expectancy of patients with renal cell carcinoma (RCC) in the last decade is due to changes that have occurred in the area of preclinical studies. Understanding cancer pathophysiology and the emergence of new therapeutic options, including immunotherapy, would not be possible without proper research. Before new approaches to disease treatment are developed and introduced into clinical practice they must be preceded by preclinical tests, in which animal studies play a significant role. This review describes the progress in animal model development in kidney cancer research starting from the oldest syngeneic or chemically-induced models, through genetically modified mice, finally to xenograft, especially patient-derived, avatar and humanized mouse models. As there are a number of subtypes of RCC, our aim is to help to choose the right animal model for a particular kidney cancer subtype. The data on genetic backgrounds, biochemical parameters, histology, different stages of carcinogenesis and metastasis in various animal models of RCC as well as their translational relevance are summarized. Moreover, we shed some light on imaging methods, which can help define tumor microstructure, assist in the analysis of its metabolic changes and track metastasis development.

Systemic treatment of the metastatic renal cell carcinoma: usefulness of the apparent diffusion coefficient of diffusion-weighted MRI in prediction of early therapeutic response

Accurate prediction of early treatment response to systemic therapy (ST) with tyrosine kinase inhibitors (TKI) in patients with metastatic renal cell carcinoma (mRCC) could help avoid ineffective and expensive treatment with serious side effects. Neither RECIST v.1.1 nor Choi criteria successfully discriminate between patients with mRCC who received ST having a short or long time to progression (TTP). There is no biomarker, which is able to predict early therapeutic response to TKIs application in patients with mRCC. The goal of our study was to investigate the potential of apparent diffusion coefficient (ADC) of diffusion-weighted imaging (DWI) of MRI in prediction of early therapeutic response to ST with pazopanib in patients with mRCC. The retrospective study enrolled 32 adult patients with conventional mRCC who received pazopanib (mean duration-7.5 ± 3.45). The mean duration of follow-up was 11.85 ± 4.34 months. In all patients as baseline examination and 1 month after treatment, 1.5T MRI including DWI sequence was performed followed by ADC measurement of the main renal lesion. For assessment of the therapeutic response, RECIST 1.1 is used. Partial response (PR), stable disease (SD) and progressive disease (PD) were observed in 12 (37.50%), 10 (31.25%) and 10 (31.25%) cases with mean TTP of 10.33 ± 2.06 months (95% confidence interval, CI = 9.05-11.61), 7.40 ± 2.50 months (95% CI = 5.61-9.19) and 4.20 ± 1.99 months (95% CI = 2.78-5.62) accordingly (p < 0.05). There was no difference in change of main lesions' longest size 1 month after ST in patients with PR, SD and PD. Comparison of mean ADC values before and 1 month after systemic treatment showed significant decrease by 19.11 ± 10.64% (95% CI = 12.35-25.87) and by 7.66 ± 6.72% (95% CI = 2.86-12.47) in subgroups with PR and SD, respectively (p < 0.05). There was shorter TTP in patients with mRCC if ADC of the main renal lesion 1 month after the ST increased from the baseline less than 1.73% compared to patients with ADC levels above this threshold: 5.29 ± 3.45 versus 9.50 ± 2.04 months accordingly (p < 0.001). Overall, our findings highlighted the use of ADC as a predictive biomarker for early therapeutic response assessment. Use of ADC will be effective and useful for reliable prediction of responders and non-responders to systemic treatment with pazopanib.

Role of Interface Sign and Diffusion-Weighted Magnetic Resonance Imaging in Differential Diagnosis of Exophytic Renal Masses

PURPOSE

We aimed to investigate the role of interfaces of exophytic solid and cystic renal masses on magnetic resonance imaging (MRI) and the added value of diffusion-weighted imaging in differentiating benign from malignant lesions.

METHODS

The Institutional Review Board approved this retrospective study, and informed consent was waived. A total of 265 patients (109 [41%] women and 156 [59%] men) with a mean age of 57 ± 12 (standard deviation) years were enrolled in this study. Preoperative MRI (n = 238) examinations of patients with solid or cystic renal masses and MRI (n = 27) examinations of patients with Bosniak IIF cysts without progression were reviewed. Solid/cystic pattern, interface types and apparent diffusion coefficient (ADC) values were recorded by 2 radiologists. The diagnostic performance of combining normalized ADC values with interface sign were evaluated.

RESULTS

Among 265 renal lesions (109 cystic and 156 solid), all malignant lesions (n = 192) had a round interface. No malignant lesions showed an angular interface. For prediction of benignity in cystic lesions, sensitivity (82.86% vs 56.16%), negative predictive value (92.50% vs 85.71%), and accuracy (94.50% vs 87.92%) ratios of angular interface were higher compared to all (solid plus cystic) lesions. The best normalized ADC cutoff values for predicting malignancy in lesions with round interface were as follows: for all (solid plus cystic), ≤ 0.75 (AUROC = 0.804); solid, ≤ 0.6 (AUROC = 0.819); and cystic, ≤ 0.8 (AUROC = 0.936).

CONCLUSIONS

Angular interface can be a predictor of benignity for especially cystic renal masses. The evaluation of interface type with normalized ADC value can be an important clue in differential diagnosis especially in patients avoiding contrast.