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

Quantitative Measurement on Contrast-Enhanced CT Distinguishes Small Clear Cell Renal Cell Carcinoma From Benign Renal Tumors: A Multicenter Study

RATIONALE AND OBJECTIVES

To evaluate the potential of quantitative measurements on contrast-enhanced CT (CECT) in differentiating small (≤4 cm) clear cell renal cell carcinoma (ccRCC) from benign renal tumors, including fat-poor angiomyolipoma (fpAML) and renal oncocytoma (RO).

MATERIALS AND METHODS

244 patients with pathologically confirmed ccRCC (n = 184) and benign renal tumors (fpAML, n = 50; RO, n = 10) were randomly assigned into training cohort (n = 193) and test cohort 1 (n = 51), while external test cohort 2 (n = 50) was from another hospital. Quantitative parameters were obtained from CECT (unenhanced phase, UP; corticomedullary phase, CMP; nephrographic phase, NP; excretory phase, EP) by measuring attenuation of renal mass and cortex and subsequently calculated. Univariable and multivariable logistic regression analyses were performed to evaluate the association between these parameters and ccRCC. Finally, the constructed models were compared with radiologists' diagnoses.

RESULTS

In univariable analysis, UP-related parameters, particularly UPC-T (cortex minus tumor attenuation on UP), demonstrated AUC of 0.766 in training cohort, 0.901 in test cohort 1, 0.805 in test cohort 2. The heterogeneity-related parameter SD (standard deviation) showed AUC of 0.781, 0.834, and 0.875 respectively. In multivariable analysis, model 1 incorporating UPC-T, NPC-T (cortex minus tumor attenuation on NP), CMPT-UPT (tumor attenuation on CMP minus UP), and SD yielded AUC of 0.866, 0.923, and 0.949 respectively. When compared with radiologists, multivariate models demonstrated higher accuracy (0.800-0.860) and sensitivity (0.794-0.971) than radiologists' assessments (accuracy: 0.700-0.720, sensitivity: 0.588-0.706).

CONCLUSION

Quantitative measurements on CECT, particularly UP- and heterogeneity-related parameters, have potential to discriminate ccRCC and benign renal tumors (fpAML, RO).

The Value of Amide Proton Transfer MRI in the Diagnosis of Malignant and Benign Urinary Bladder Lesions: Comparison With Diffusion-Weighted Imaging

BACKGROUND

Conventional magnetic resonance imaging (MRI) has certain limitations in distinguishing between malignant and benign urinary bladder (UB) lesions. Amide proton transfer (APT) imaging may provide more diagnostic information than diffusion-weighted imaging (DWI) to distinguish between malignant and benign UB.

PURPOSE

To investigate the potential of APT imaging in the diagnosis of malignant and benign UB lesions and to compare its diagnostic efficacy with that of conventional DWI.

STUDY TYPE

Prospective.

SUBJECTS

Eighty patients with UB lesions.

FIELD STRENGTH/SEQUENCE

A 3.0 T/turbo spin echo (TSE) T1-weighted and T2-weighted imaging, single-shot echo planar DWI, and three-dimensional TSE APT imaging.

ASSESSMENT

Patients underwent radical cystectomy or transurethral resection of the bladder lesions within 2 weeks after CT urography and MRI examination. APT signal intensity in UB lesions was quantified by the asymmetric magnetization transfer ratio (MTRasym ). MTRasym and apparent diffusion coefficient (ADC) values were measured and compared between malignant and benign UB lesions.

STATISTICAL TESTS

Kolmogorov-Smirnov test, Student's t test or Mann-Whitney U test, Spearman rank correlation coefficient, area under the receiver operating characteristic (ROC) curve (AUC), Delong test, and intraclass correlation coefficient (ICC). The significance threshold was set at P < 0.05.

RESULTS

Thirty-two patients had pathologically confirmed benign UB lesions, including 2 bladder leiomyomas, 1 submucosal amyloidosis, 1 inflammatory myofibroblastic tumor, and 28 inflammatory lesions, and 48 patients had pathologically confirmed urothelial carcinoma. Urothelial carcinomas showed significantly higher MTRasym values (1.53% [0.74%] vs. 0.85% [0.23%]) and significantly lower ADC values (1.24 ± 0.34 × 10-3  mm2 /s vs. 1.43 ± 0.22 × 10-3  mm2 /s) than benign UB lesions. The MTRasym value (AUC = 0.928) was significantly better in differentiating urothelial carcinoma from benign UB lesions than the ADC value (AUC = 0.722).

DATA CONCLUSION

APT imaging may have value in discriminating malignant from benign UB lesions and has better diagnostic performance than DWI.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Differentiating renal cell carcinoma and oncocytoma with volumetric MRI histogram analysis

OBJECTIVE

In this study, the utility of histogram parameters derived from diffusion-weighted imaging for differentiate renal cell carcinoma (RCC) from oncocytoma was investigated.

METHODS

This research tracked 126 individuals who were diagnosed with RCC and oncocytoma through histopathological analysis, using magnetic resonance imaging (MRI) assessments from 2015 to 2023. We observed various attributes of these patients, including demographic details, surgical records, pre-surgery MRI results, MRI apparent diffusion coefficient (ADC) histogram analysis, and post-surgery histopathological outcomes. Calculations of ADC measurements such as mean, minimum, and maximum in conjunction with the 5th, 10th, 25th, 50th, 75th, 90th, and 95th quantile points were made. In addition, we also noted the skewness, kurtosis, and variance of these data points.

RESULTS

The focus group for this investigation consisted of 75 male and 51 female patients. Out of these, 82 were diagnosed with RCC and 44 with oncocytoma. All ADC parameters including ADCmin, ADCmedian, ADCmean, and ADCmax, including the 5th, 10th, 25th, 50th, 75th, 90th, and 95th quantile divisions among the oncocytoma cohort were observed to be higher than the corresponding ones in the RCC group. A statistically meaningful difference was discovered between the minimum ADC value along with the 5th ranking of ADC measurements (p<0.001), in addition to mean of ADC (p=0.050), and the 10th (p=0.002) and 25th (p=0.015) quantiles of ADC data. When considering the region below the curve (AUC) in ROC analysis, the value of ADCmin was recorded as 0.739, with a sensitivity of 75.0%, and specificity of 68.2%.

CONCLUSION

To distinguish oncocytoma from RCC, it may be useful to conduct a whole-tumor histogram and textural analysis of ADC values.

Bosniak classification of cystic renal masses, version 2019: Is it helpful to incorporate the diffusion weighted imaging characteristic of lesions into the guideline?

Objective

To improve understanding of diffusion weighted imaging (DWI) characteristic of MRI and clinical variables, further optimize the Bosniak classification for diagnosis of cystic renal masses (CRMs).

Methods

This study retrospectively analyzed 130 CRMs in 125 patients with CT or MRI, including 87 patients with DWI (b = 600, 1000 s/mm2). Clinical variables and histopathological results were recorded. Two radiologists in consensus analyzed images of each lesion for the size, thickness of wall, number of septum, enhancement of wall/septum, wall nodule, signal intensity on DWI, calcification, and cyst content. Clinical variables, CT and MRI image characteristics were compared with pathology or follow-up results to evaluate the diagnostic performance for CRMs.

Results

Of the 130 lesions in 125 patients, histological analysis reported that 36 were malignant, 38 were benign, and no change was found in 56 followed-up lesions (mean follow-up of 24 months). The incidences of cystic wall thickened, more septa, measurable enhancement of wall/septum, nodule(s) on CT/MRI, and high signal intensity on DWI were significantly higher in malignant than in benign CRMs (CT: p = 0.005, p < 0.001, p < 0.001, p < 0.001, p < 0.001; MRI: p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001). Combination of MRI including DWI features with CT findings showed the highest area under ROC curve (0.973) in distinguishing benign and malignant CRMs.

Conclusions

Incorporating DWI characteristic of CRMs into Bosniak classification helps to improve diagnostic efficiency.

MRI-Based Radiomics and Urine Creatinine for the Differentiation of Renal Angiomyolipoma With Minimal Fat From Renal Cell Carcinoma: A Preliminary Study

Objectives

Standard magnetic resonance imaging (MRI) techniques are different to distinguish minimal fat angiomyolipoma (mf-AML) with minimal fat from renal cell carcinoma (RCC). Here we aimed to evaluate the diagnostic performance of MRI-based radiomics in the differentiation of fat-poor AMLs from other renal neoplasms.

Methods

A total of 69 patients with solid renal tumors without macroscopic fat and with a pathologic diagnosis of RCC (n=50) or mf-AML (n=19) who underwent conventional MRI and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) were included. Clinical data including age, sex, tumor location, urine creatinine, and urea nitrogen were collected from medical records. The apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were measured from renal tumors. We used the ITK-SNAP software to manually delineate the regions of interest on T2-weighted imaging (T2WI) and IVIM-DWI from the largest cross-sectional area of the tumor. We extracted 396 radiomics features by the Analysis Kit software for each MR sequence. The hand-crafted features were selected by using the Pearson correlation analysis and least absolute shrinkage and selection operator (LASSO). Diagnostic models were built by logistic regression analysis. Receiver operating characteristic curve analysis was performed using five-fold cross-validation and the mean area under the curve (AUC) values were calculated and compared between the models to obtain the optimal model for the differentiation of mf-AML and RCC. Decision curve analysis (DCA) was used to evaluate the clinical utility of the models.

Results

Clinical model based on urine creatinine achieved an AUC of 0.802 (95%CI: 0.761-0.843). IVIM-based model based on f value achieved an AUC of 0.692 (95%CI: 0.627-0.757). T2WI-radiomics model achieved an AUC of 0.883 (95%CI: 0.852-0.914). IVIM-radiomics model achieved an AUC of 0.874 (95%CI: 0.841-0.907). Combined radiomics model achieved an AUC of 0.919 (95%CI: 0.894-0.944). Clinical-radiomics model yielded the best performance, with an AUC of 0.931 (95%CI: 0.907-0.955). The calibration curve and DCA confirmed that the clinical-radiomics model had a good consistency and clinical usefulness.

Conclusion

The clinical-radiomics model may be served as a noninvasive diagnostic tool to differentiate mf-AML with RCC, which might facilitate the clinical decision-making process.

Utility of radiomics features of diffusion-weighted magnetic resonance imaging for differentiation of fat-poor angiomyolipoma from clear cell renal cell carcinoma: model development and external validation

PURPOSE

To investigate the utility of radiomics features of diffusion-weighted magnetic resonance imaging (DW-MRI) to differentiate fat-poor angiomyolipoma (fpAML) from clear cell renal cell carcinoma (ccRCC).

MATERIALS AND METHODS

This multi-institutional study included two cohorts with pathologically confirmed renal tumors: 65 patients with ccRCC and 18 with fpAML in the model development cohort, and 17 with ccRCC and 13 with fpAML in the external validation cohort. All patients underwent magnetic resonance imaging (MRI) including DW-MRI. Radiomics analysis was used to extract 39 imaging features from the apparent diffusion coefficient (ADC) map. The radiomics features were analyzed with unsupervised hierarchical cluster analysis. A random forest (RF) model was used to identify radiomics features important for differentiating fpAML from ccRCC in the development cohort. The diagnostic performance of the RF model was evaluated in the development and validation cohorts.

RESULTS

The cases in the developmental cohort were classified into three groups with different frequencies of fpAML by cluster analysis of radiomics features. RF analysis of the development cohort showed that the mean ADC value was important for differentiating fpAML from ccRCC, as well as higher-texture features including gray-level run length matrix (GLRLM)_long-run low gray-level enhancement (LRLGE), and GLRLM_low gray-level run emphasis (LGRE). The area under the curve values of the development [0.90, 95% confidence interval (CI) 0.80-1.00] and validation cohorts (0.87, 95% CI 0.74-1.00) were similar (P = 0.91).

CONCLUSION

The radiomics features of ADC maps are useful for differentiating fpAML from ccRCC.

Application of different methods used to measure the apparent diffusion coefficient of renal cell carcinoma on the same lesion and its correlation with ISUP nuclear grading

PURPOSE

To determine the most frequently used different apparent diffusion coefficient (ADC) measurement methods in renal cell carcinoma (RCC), and their correlation with the International Society of Urological Pathology (ISUP) histologic grading system.

METHODS

A total of 99 patients who underwent diffusion-weighted imaging and whose pathologic diagnosis of RCC was confirmed were included in the study. As a result of a literature review, region of interest (ROI) selection and measurement methods were determined in five ways. These included a small ROI (ADC1) on the solid part of the lesion showing the most restriction; a large ROI (ADC2) on the solid part of the lesion showing restriction; ROI (ADC3) that covered the lesion in the cross-section with the largest diameter, which was obtained by placing ROIs (ADC4) covering the lesion on all sections of the lesion; three small ROIs (ADC5) on solid parts of the lesion showing the most restriction. Then, ADC measurements were made from the contralateral normal kidney parenchyma. Tumors were pathologically subdivided [71 clear cell RCCs (ccRCC), 17 chromophobe RCCs (chRCC), 11 papillary RCCs (pRCC)], and graded according to the ISUP nuclear grading system (42 high-grade, 57 low-grade). Data were analyzed statistically.

RESULTS

In all measurement methods, ADC values of RCCs were statistically significantly lower than normal kidney ADC values. There were no differences between the ADC3 and ADC4 measurements of RCCs (p = 0.999). There was a statistical difference in other measurement methods (p < 0.001). There were differences between ccRCCs and pRCCs and chRCCs in all measurement methods. In all measurement methods, pRCC and chRCC ADC values ​​were lower than ccRCC ADC values. When ISUP nuclear grading and ADC values ​​were compared, there was a statistically inverse correlation between all ADC measurements. The strongest correlation was found in the ADC1 and ADC5 measurements. When the ADC values ​​of ISUP low and high-grade groups were compared, a significant difference was found in the ADC5 measurement method (p = 0.046).

CONCLUSION

According to the findings of the study, ADC5 is the measurement method that shows the best correlation with the ISUP histologic grading system. Therefore, we think that ADC5 can be the primary measurement method for determining the ADC value of RCCs.

Radiomics improves the utility of ADC for differentiation between renal oncocytoma and chromophobe renal cell carcinoma: Preliminary findings

OBJECTIVE

Differentiation between renal oncocytoma (RON) and chromophobe renal cell carcinoma (chRCC) remains challenging. We aimed to assess the accurate apparent diffusion coefficient (ADC) radiomics features in differentiating these tumors.

MATERIALS AND METHODS

This single-center retrospective study included 14 patients with histopathologically proven RON (n = 6) and chRCC (n = 8) who underwent magnetic resonance imaging. Features were extracted from ADC maps. Features with an intraclass correlation coefficient >0.90, an intergroup p < 0.01 and interrater differences with normal distribution underwent agreement and receiver operating characteristic curve analyses.

RESULTS

Overall, 6 features qualified for further analysis and Bland-Altman plots revealed acceptable agreement for all. Only 1 first order feature and 5 high order texture features successfully predicted RON with more than 90% sensitivities and specificities more than 80%.

CONCLUSION

Squared mean ADC and certain gray level run length matrix features extracted by radiomics of ADC mapping provide quite high diagnostic precision in terms of distinguishing between RON and chRCC.

Diffusion-Weighted MRI in the Genitourinary System

Diffusion weighted imaging (DWI) constitutes a major functional parameter performed in Magnetic Resonance Imaging (MRI). The DW sequence is performed by acquiring a set of native images described by their b-values, each b-value representing the strength of the diffusion MR gradients specific to that sequence. By fitting the data with models describing the motion of water in tissue, an apparent diffusion coefficient (ADC) map is built and allows the assessment of water mobility inside the tissue. The high cellularity of tumors restricts the water diffusion and decreases the value of ADC within tumors, which makes them appear hypointense on ADC maps. The role of this sequence now largely exceeds its first clinical apparitions in neuroimaging, whereby the method helped diagnose the early phases of cerebral ischemic stroke. The applications extend to whole-body imaging for both neoplastic and non-neoplastic diseases. This review emphasizes the integration of DWI in the genitourinary system imaging by outlining the sequence's usage in female pelvis, prostate, bladder, penis, testis and kidney MRI. In gynecologic imaging, DWI is an essential sequence for the characterization of cervix tumors and endometrial carcinomas, as well as to differentiate between leiomyosarcoma and benign leiomyoma of the uterus. In ovarian epithelial neoplasms, DWI provides key information for the characterization of solid components in heterogeneous complex ovarian masses. In prostate imaging, DWI became an essential part of multi-parametric Magnetic Resonance Imaging (mpMRI) to detect prostate cancer. The Prostate Imaging-Reporting and Data System (PI-RADS) scoring the probability of significant prostate tumors has significantly contributed to this success. Its contribution has established mpMRI as a mandatory examination for the planning of prostate biopsies and radical prostatectomy. Following a similar approach, DWI was included in multiparametric protocols for the bladder and the testis. In renal imaging, DWI is not able to robustly differentiate between malignant and benign renal tumors but may be helpful to characterize tumor subtypes, including clear-cell and non-clear-cell renal carcinomas or low-fat angiomyolipomas. One of the most promising developments of renal DWI is the estimation of renal fibrosis in chronic kidney disease (CKD) patients. In conclusion, DWI constitutes a major advancement in genitourinary imaging with a central role in decision algorithms in the female pelvis and prostate cancer, now allowing promising applications in renal imaging or in the bladder and testicular mpMRI.

Renal Cell Carcinoma or Oncocytoma? The Contribution of Diffusion-Weighted Magnetic Resonance Imaging to the Differential Diagnosis of Renal Masses

Background and Objectives: Renal Cell Carcinoma (RCC) accounts for 85% and oncocytomas constitute 3–7% of solid renal masses. Oncocytomas can be confused, especially with hypovascular RCC. The purpose of this research was to evaluate the contribution of diffusion-weighted imaging (DWI) and contrast-enhanced MRI sequences in the differential diagnosis of RCC and oncocytoma Materials and Methods: 465 patients with the diagnosis of RCC and 45 patients diagnosed with oncocytoma were retrospectively reviewed between 2009 to 2020. All MRI acquisitions were handled by a 1.5 T device (Achieva, Philips Healthcare, Best, The Netherlands) and all images were evaluated by the consensus of two radiologists with 10–15 years’ experience. The SPSS package program version 15.0 software was used for statistical analysis of the study. Chi-square test, Mann–Whitney U test or the Kruskal–Wallis tests were used in the statistical analysis. A receiver operating characteristic (ROC) curve was used to calculate the cut-off values Results: The results were evaluated with a 95% confidence interval and a significance threshold of p < 0.05. ADC values (p < 0.001) and enhancement index (p < 0.01) were significantly lower in the RCC group than the oncocytoma group. Conclusion: DWI might become an alternative technique to the contrast-enhanced MRI in patients with contrast agent nephropathy or with a high risk of nephrogenic systemic fibrosis, calculation of CI of the oncocytoma and RCCs in the contrast-enhanced acquisitions would contribute to the differential diagnosis.

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 imaging in the management of renal masses

The wide availability of cross-sectional imaging is responsible for the increased detection of small, usually asymptomatic renal masses. More than 50 % of renal cell carcinomas (RCCs) represent incidental findings on noninvasive imaging. Multimodality imaging, including conventional US, contrast-enhanced US (CEUS), CT and multiparametric MRI (mpMRI) is pivotal in diagnosing and characterizing a renal mass, but also provides information regarding its prognosis, therapeutic management, and follow-up. In this review, imaging data for renal masses that urologists need for accurate treatment planning will be discussed. The role of US, CEUS, CT and mpMRI in the detection and characterization of renal masses, RCC staging and follow-up of surgically treated or untreated localized RCC will be presented. The role of percutaneous image-guided ablation in the management of RCC will be also reviewed.

CT and MR imaging findings of bilateral ovarian metastasis from renal cell carcinoma: a case report

Secondary ovarian involvement by renal cell carcinoma rarely occurs. Here, we describe the computed tomography and magnetic resonance imaging findings of bilateral ovarian metastases from renal cell carcinoma that demonstrated heterogeneous strong contrast enhancing tumors with flow voids around and within the tumors. In addition, the apparent diffusion coefficients of the malignant tumors were high. These findings were similar to those of renal cell carcinomas at primary and other metastatic sites.

Imaging Characterization of Renal Masses

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

Repeatability and reproducibility of ADC measurements: a prospective multicenter whole-body-MRI study

OBJECTIVES

Multicenter oncology trials increasingly include MRI examinations with apparent diffusion coefficient (ADC) quantification for lesion characterization and follow-up. However, the repeatability and reproducibility (R&R) limits above which a true change in ADC can be considered relevant are poorly defined. This study assessed these limits in a standardized whole-body (WB)-MRI protocol.

METHODS

A prospective, multicenter study was performed at three centers equipped with the same 3.0-T scanners to test a WB-MRI protocol including diffusion-weighted imaging (DWI). Eight healthy volunteers per center were enrolled to undergo test and retest examinations in the same center and a third examination in another center. ADC variability was assessed in multiple organs by two readers using two-way mixed ANOVA, Bland-Altman plots, coefficient of variation (CoV), and the upper limit of the 95% CI on repeatability (RC) and reproducibility (RDC) coefficients.

RESULTS

CoV of ADC was not influenced by other factors (center, reader) than the organ. Based on the upper limit of the 95% CI on RC and RDC (from both readers), a change in ADC in an individual patient must be superior to 12% (cerebrum white matter), 16% (paraspinal muscle), 22% (renal cortex), 26% (central and peripheral zones of the prostate), 29% (renal medulla), 35% (liver), 45% (spleen), 50% (posterior iliac crest), 66% (L5 vertebra), 68% (femur), and 94% (acetabulum) to be significant.

CONCLUSIONS

This study proposes R&R limits above which ADC changes can be considered as a reliable quantitative endpoint to assess disease or treatment-related changes in the tissue microstructure in the setting of multicenter WB-MRI trials.

KEY POINTS

• The present study showed the range of R&R of ADC in WB-MRI that may be achieved in a multicenter framework when a standardized protocol is deployed. • R&R was not influenced by the site of acquisition of DW images. • Clinically significant changes in ADC measured in a multicenter WB-MRI protocol performed with the same type of MRI scanner must be superior to 12% (cerebrum white matter), 16% (paraspinal muscle), 22% (renal cortex), 26% (central zone and peripheral zone of prostate), 29% (renal medulla), 35% (liver), 45% (spleen), 50% (posterior iliac crest), 66% (L5 vertebra), 68% (femur), and 94% (acetabulum) to be detected with a 95% confidence level.