Apparent Diffusion Coefficient Distinguishes Malignancy in T1-Hyperintense Small Renal Masses

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.

Multiparametric magnetic resonance imaging for characterizing renal tumors: A validation study of the algorithm presented by Cornelis et al

Objectives

In the last decade, the incidence of renal cell carcinoma (RCC) has been rising, with the greatest increase observed for solid tumors. Magnetic resonance imaging (MRI) protocols and algorithms have recently been available for classifying RCC subtypes and benign subtypes. The objective of this study was to prospectively validate the MRI algorithm presented by Cornelis et al. for RCC classification.

Material and Methods

Over a 7-month period, 38 patients with 44 renal tumors were prospectively included in the study and received an MRI examination in addition to the conventional investigation program. The MRI sequences were: T2-weighted, dual chemical shift MRI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced T1-weighted in wash-in and wash-out phases. The images were evaluated according to the algorithm by two experienced, blinded radiologists, and the histopathological diagnosis served as the gold standard.

Results

Of 44 tumors in 38 patients, only 8 tumors (18.2%) received the same MRI diagnosis according to the algorithm as the histopathological diagnosis. MRI diagnosed 16 angiomyolipoma, 14 clear cell RCC (ccRCC), 12 chromophobe RCC (chRCC), and two papillary RCC (pRCC), while histopathological examination diagnosed 24 ccRCC, four pRCC, one chRCC, and one mixed tumor of both pRCC and chRCC. Malignant tumors were statistically significantly larger than the benign (3.16 ± 1.34 cm vs. 2.00 ± 1.04 cm, P = 0.006).

Conclusion

This prospective study could not reproduce Cornelis et al.'s results and does not support differentiating renal masses using multiparametric MRI without percutaneous biopsy in the future. The MRI algorithm showed few promising results to categorize renal tumors, indicating histopathology for clinical decisions and follow-up regimes of renal masses are still required.

DWI and ADC value versus ADC ratio in the characterization of solid renal masses: radiologic-pathologic correlation

Background

Renal masses are becoming an increasingly common finding on cross-sectional images. Characterization of the nature of the lesion either neoplastic or not, benign or malignant as well as further subtype characterization is becoming an important factor in determining management plan. The purpose of our study with to assess the sensitivity and specificity of both ADC mean value and ADC ratio in such characterization along with the calculation of different cutoff values to differentiate between different varieties, using pathological data as the main gold standard for diagnosis.

Results

Our study included 50 patients with a total of 72 masses. A final diagnosis was reached in 69 masses by pathological examination and three masses had clinical and laboratory signs of infection. We had a total of 49 malignant lesions (68%) and 23 benign lesions (32%). The ADC value of ccRCC (1.4 × 10−3 mm2/s) was significantly higher than all other renal masses. A cutoff ADC value of > 1.1 and a cutoff ADC ratio of > 0.56 can be used to differentiate between clear cell renal cell carcinoma and other lesions and an ADC value of < 0.8 and an ADC ratio of ≤ 0.56 to differentiate papillary renal cell carcinoma from other masses. There was no statistically significant ADC value to differentiate between benign and malignant lesions but a statistically significant ADC ratio (> 0.52) was reached.

Conclusion

ADC value and ADC ratio can be used as an adjunct tool in the characterization of different renal masses, with ADC ratio having a higher sensitivity, which can affect the prognosis and management of the patient.

[Dignity of Small Renal Masses: Implications for Diagnostics and Therapy]

Dignity of Small Renal Masses: Implications for Diagnostics and Therapy Abstract. The ubiquitous availability of radiological imaging has increased the diagnosis of renal incidentalomas with a diameter ≤4 cm. If malignancy is suspected, these are often treated surgically without prior biopsy. However, several studies demonstrate a relevant proportion of benign tumors, equating to a degree of overtreatment. There are no Swiss data available. Renal tumors resected in our center between 2006 and 2014 (n = 404) were retrospectively examined for size on cross-sectional imaging and their respective histology, identifying 221 (54.7 %) small renal masses with a diameter ≤4 cm. Of these, 62 (28 %) were benign and three (1.4 %) were of unclear or low malignant potential. Among the remaining 156 malignancies, 116 (74.4 %) were classified as prognostically favorable, allowing for active surveillance, if the patient's clinical context allows.