Impact of size of region-of-interest on differentiation of renal cell carcinoma and renal cysts on multi-phase CT: preliminary findings

World Health Organization (WHO) 2022 Classification Update: Radiologic and Pathologic Features of Papillary Renal Cell Carcinomas

RATIONALE AND OBJECTIVES

To describe imaging and pathology features of newly defined papillary renal cell carcinoma (pRCC) based on the WHO 2022 update.

MATERIALS AND METHODS

This retrospective study included 87 patients with 93 pathologically proven papillary renal cell carcinomas who underwent pre-treatment renal mass protocol CT or MRI. Baseline and post-treatment follow-up imaging was evaluated by two radiologists systematically based on established lexicon.

RESULTS

At pathology, 63 (68%) were grade 1-2, 29 (31%) were grade 3-4, and 1 (%) was unreported. At surgical pathology, 84 (90%) were localized (≤pT2b), 5 (5%) were pT3a, and none were ≥pT3b; 4 (4%) had unknown pT stage (core biopsies). 33 (35%) had necrosis and 39 (41%) had hemorrhage. None had sarcomatoid or rhabdoid differentiation. At imaging, 73 (83%) were solid and 16 (17%) were cystic. Of 16 cystic masses, four were Bosniak class IIF (three were heterogeneously T1 hyperintense) and 12 were class IV. All were well-circumscribed. 92 (99%) were hypovascular. Median follow-up for 74 patients was 30 months (IQR 12-56). One untreated patient had non-regional nodal metastasis at presentation, and one patient had metastasis to lymph nodes and bones after surgery, but the patient had unresected renal masses elsewhere without pathology. Otherwise, no recurrence or metastases were detected.

CONCLUSION

Most pRCCs present as a hypovascular, circumscribed, solid renal mass. A few pRCCs present as the newly defined Bosniak class IIF subtype. Our results can form the basis of a non-invasive, likelihood score to identify this relatively indolent pathology in the era of virtual biopsy and active surveillance.

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

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

Risk of malignancy in T1-hyperintense Bosniak version 2019 class II and IIF cystic renal masses

BACKGROUND

Bosniak classification version 2019 includes cystic masses in class II and IIF based partly on their hyperintense appearance at T1-weighted MRI. The prevalence of malignancy in non-enhancing heterogeneously T1-hyperintense masses is unknown, nor whether the pattern of T1 hyperintensity affects malignancy likelihood.

PURPOSE

To determine the malignancy proportion among six patterns of T1 hyperintensity within non-enhancing cystic renal masses.

METHODS

This retrospective, single-institution study included 72 Bosniak class II and IIF, non-enhancing, T1-hyperintense cystic renal masses. Diagnosis was confirmed by histopathology or by follow-up imaging demonstrating 5-year size and morphologic stability, decreased in size by ≥ 30%, resolution, or Bosniak down-classification. Six patterns of T1 hyperintensity were pre-defined: homogeneous (pattern A), fluid-fluid level (pattern B), peripherally markedly T1-hyperintense (pattern C), containing a T1-hyperintense non-enhancing nodule (pattern D), peripherally T1-hypointense (pattern E), and heterogeneously T1-hyperintense without a distinct pattern (pattern F). Three readers independently assigned each mass to a pattern. Individual and mean malignancy proportion were determined. Mann-Whitney test and Fischer's exact test compared the likelihood of malignancy between patterns. Inter-reader agreement was analyzed with Gwet's agreement coefficient (AC).

RESULTS

Among 72 masses, the mean number of masses assigned was 11 (15%) to pattern A, 21 (29%) to pattern B, 6 (8%) to pattern C, 7 (10%) to pattern D, 5 (7%) to pattern E, and 22 (31%) to pattern F. Five of 72 masses (7%) were malignant; none was assigned pattern A, B, or D. Mean malignancy proportion was 5% (0/9, 1/6, and 0/4) for pattern C, 13% (0/4, 1/3, and 1/7) for pattern E, and 18% (5/20, 3/21, and 4/25) for pattern F. Malignant masses were more likely assigned to pattern E or F (p = 0.003-0.039). Inter-reader agreement was substantial (Gwet's AC: 0.68).

CONCLUSION

Bosniak version 2019 class IIF masses that are non-enhancing and heterogeneously T1-hyperintense with a fluid-fluid level are likely benign. Those that are non-enhancing and heterogeneously T1-hyperintense without a distinct pattern have a malignancy proportion up to 25% (5/20).

Differentiation of renal angiomyolipoma without visible fat from small clear cell renal cell carcinoma by using specific region of interest on contrast-enhanced CT: a new combination of quantitative tools

Background

To investigate the value of using specific region of interest (ROI) on contrast-enhanced CT for differentiating renal angiomyolipoma without visible fat (AML.wovf) from small clear cell renal cell carcinoma (ccRCC).

Methods

Four-phase (pre-contrast phase [PCP], corticomedullary phase [CMP], nephrographic phase [NP], and excretory phase [EP]) contrast-enhanced CT images of AML.wovf (n = 31) and ccRCC (n = 74) confirmed by histopathology were retrospectively analyzed. The CT attenuation value of tumor (AVT), net enhancement value (NEV), relative enhancement ratio (RER), heterogeneous degree of tumor (HDT) and standardized heterogeneous ratio (SHR) were obtained by using different ROIs [small: ROI (1), smaller: ROI (2), large: ROI (3)], and the differences of these quantitative data between AML.wovf and ccRCC were statistically analyzed. Multivariate regression was used to screen the main factors for differentiation in each scanning phase, and the prediction models were established and evaluated.

Results

Among the quantitative parameters determined by different ROIs, the degree of enhancement measured by ROI (2) and the enhanced heterogeneity measured by ROI (3) performed better than ROI (1) in distinguishing AML.wovf from ccRCC. The receiver operating characteristic (ROC) curves showed that the area under the curve (AUC) of RER_CMP (2), RER_NP (2) measured by ROI (2) and HDT_CMP and SHR_CMP measured by ROI (3) were higher (AUC = 0.876, 0.849, 0.837 and 0.800). Prediction models that incorporated demographic data, morphological features and quantitative data derived from the enhanced phase were superior to quantitative data derived from the pre-contrast phase in differentiating between AML.wovf and ccRCC. Among them, the model in CMP was the best prediction model with the highest AUC (AUC = 0.986).

Conclusion

The combination of quantitative data obtained by specific ROI in CMP can be used as a simple quantitative tool to distinguish AML.wovf from ccRCC, which has a high diagnostic value after combining demographic data and morphological features.

Bosniak classification of cystic renal masses, version 2019: interpretation pitfalls and recommendations to avoid misclassification

The purpose of this review is to describe the potential sources of variability or discrepancy in interpretation of cystic renal masses under the Bosniak v2019 classification system. Strategies to avoid these pitfalls and clinical examples of diagnostic approaches are also presented. Potential pitfalls in the application of Bosniak v2019 are divided into three categories: interpretative, technical, and mass related. An organized, comprehensive review of possible discrepancies in interpreting Bosniak v2019 cystic masses is presented with pictorial examples of difficult clinical cases and proposed solutions. The scheme provided can guide readers to consistent, precise application of the classification system. Radiologists should be aware of the possible sources of misinterpretation of cystic renal masses when applying Bosniak v2019. Knowing which features and types of cystic masses are prone to interpretive errors, in addition to the inherent trade-offs between the CT and MR techniques used to characterize them, can help radiologists avoid these pitfalls.

Comparison of Different Machine Models Based on Contrast-Enhanced Computed Tomography Radiomic Features to Differentiate High From Low Grade Clear Cell Renal Cell Carcinomas

Purpose

This study was to investigate the role of different radiomics models with enhanced computed tomography (CT) scan in differentiating low from high grade renal clear cell carcinomas.

Materials and Methods

CT data of 190 cases with pathologically confirmed renal cell carcinomas were collected and divided into the training set and testing set according to different time periods, with 122 cases in the training set and 68 cases in the testing set. The region of interest (ROI) was delineated layer by layer.

Results

A total of 402 radiomics features were extracted for analysis. Six of the radiomic parameters were deemed very valuable by univariate analysis, rank sum test, LASSO cross validation and correlation analysis. From these six features, multivariate logistic regression model, support vector machine (SVM), and decision tree model were established for analysis. The performance of each model was evaluated by AUC value on the ROC curve and decision curve analysis (DCA). Among the three prediction models, the SVM model showed a high predictive efficiency. The AUC values of the training set and the testing set were 0.84 and 0.83, respectively, which were significantly higher than those of the decision tree model and the multivariate logistic regression model. The DCA revealed a better predictive performance in the SVM model that possessed the highest degree of coincidence.

Conclusion

Radiomics analysis using the SVM radiomics model has highly efficiency in discriminating high- and low-grade clear cell renal cell carcinomas.

Bosniak Classification of Cystic Renal Masses, Version 2019: A Pictorial Guide to Clinical Use

Cystic renal masses are commonly encountered in clinical practice. In 2019, the Bosniak classification of cystic renal masses, originally developed for CT, underwent a major revision to incorporate MRI and is referred to as the Bosniak Classification, version 2019. The proposed changes attempt to (a) define renal masses (ie, cystic tumors with less than 25% enhancing tissue) to which the classification should be applied; (b) emphasize specificity for diagnosis of cystic renal cancers, thereby decreasing the number of benign and indolent cystic masses that are unnecessarily treated or imaged further; (c) improve interobserver agreement by defining imaging features, terms, and classes of cystic renal masses; (d) reduce variation in reported malignancy rates for each of the Bosniak classes; (e) incorporate MRI and to some extent US; and (f) be applicable to all cystic renal masses encountered in clinical practice, including those that had been considered indeterminate with the original classification. The authors instruct how, using CT, MRI, and to some extent US, the revised classification can be applied, with representative clinical examples and images. Practical tips, pitfalls to avoid, and decision tree rules are included to help radiologists and other physicians apply the Bosniak Classification, version 2019 and better manage cystic renal masses. An online resource and mobile application are also available for clinical assistance. An invited commentary by Siegel and Cohan is available online. ^©RSNA, 2021.

Update on MRI of Cystic Renal Masses Including Bosniak Version 2019

Incidental cystic renal masses are common, usually benign, and almost always indolent. Since 1986, the Bosniak classification has been used to express the risk of malignancy in a cystic renal mass detected at imaging. Historically, magnetic resonance imaging (MRI) was not included in that classification. The proposed Bosniak v.2019 update has formally incorporated MRI, included definitions of imaging terms designed to improve interobserver agreement and specificity for malignancy, and incorporated a variety of masses that were incompletely defined or not included in the original classification. For example, at unenhanced MRI, homogeneous masses markedly hyperintense at T₂ -weighted imaging (similar to cerebrospinal fluid) and homogeneous masses markedly hyperintense at fat suppressed T₁ -weighted imaging (approximately ≥2.5 times more intense than adjacent renal parenchyma) are classified as Bosniak II and may be safely ignored, even when they have not been imaged with a complete renal mass MRI protocol. MRI has specific advantages and is recommended to evaluate masses that at computed tomography (CT) 1) have abundant thick or nodular calcifications; 2) are homogeneous, hyperattenuating, ≥3 cm, and nonenhancing; or 3) are heterogeneous and nonenhancing. Although MRI is generally excellent for characterizing cystic renal masses, there are unique weaknesses of MRI that bear consideration. These details and others related to MRI of cystic renal masses are described in this review, with an emphasis on Bosniak v.2019. A website (https://bosniak-calculator.herokuapp.com/) and mobile phone apps named "Bosniak Calculator" have been developed for ease of assignment of Bosniak classes. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.

Mimics and Pitfalls in Renal Imaging

There are several potential pitfalls that radiologists face when interpreting images of the kidneys. Some result from image acquisition and can arise from the imaging equipment or imaging technique, whereas others are patient related. Another category of pitfalls relates to image interpretation. Some difficulties stem from methods to detect enhancement after contrast administration, whereas others are benign entities that can mimic a renal tumor. Finally, interpretation and diagnosis of fat-containing renal masses may be tricky due to the complexities discerning the pattern of fat within a mass and how that translates to an accurate diagnosis.

Bosniak Classification of Cystic Renal Masses, Version 2019: An Update Proposal and Needs Assessment

Cystic renal cell carcinoma (RCC) is almost certainly overdiagnosed and overtreated. Efforts to diagnose and treat RCC at a curable stage result in many benign neoplasms and indolent cancers being resected without clear benefit. This is especially true for cystic masses, which compared with solid masses are more likely to be benign and, when malignant, less aggressive. For more than 30 years, the Bosniak classification has been used to stratify the risk of malignancy in cystic renal masses. Although it is widely used and still effective, the classification does not formally incorporate masses identified at MRI or US or masses that are incompletely characterized but are highly likely to be benign, and it is affected by interreader variability and variable reported malignancy rates. The Bosniak classification system cannot fully differentiate aggressive from indolent cancers and results in many benign masses being resected. This proposed update to the Bosniak classification addresses some of these shortcomings. The primary modifications incorporate MRI, establish definitions for previously vague imaging terms, and enable a greater proportion of masses to enter lower-risk classes. Although the update will require validation, it aims to expand the number of cystic masses to which the Bosniak classification can be applied while improving its precision and accuracy for the likelihood of cancer in each class.

Clear cell renal cell carcinoma: identifying PTEN expression on multiphasic MDCT

PURPOSE

To investigate whether multiphasic MDCT enhancement profiles can help to identify PTEN expression in clear cell renal cell carcinomas (ccRCCs). Lack of PTEN expression is associated with worsened overall survival, a more advanced Fuhrman grade, and a greater likelihood of lymph mode metastasis.

METHODS

With IRB approval for this retrospective study, we derived a cohort of 103 histologically proven ccRCCs with preoperative 4-phase renal mass MDCT from 2001-2013. Following manual segmentation, a computer-assisted detection algorithm selected a 0.5-cm-diameter region of maximal attenuation within each lesion in each phase; a 0.5-cm-diameter region of interest was manually placed on uninvolved renal cortex in each phase. The relative attenuation of each lesion was calculated as [(Maximal lesion attenuation - cortex attenuation)/cortex attenuation] × 100. Absolute and relative attenuation in each phase were compared using t tests. The performance of multiphasic enhancement in identifying PTEN expression was assessed with logistic regression analysis.

RESULTS

PTEN-positive and PTEN-negative ccRCCs both exhibited peak enhancement in the corticomedullary phase. Relative corticomedullary phase attenuation was significantly greater for PTEN-negative ccRCCs in comparison to PTEN-positive ccRCCs (33.7 vs. 9.5, p = 0.03). After controlling for lesion stage and size, relative corticomedullary phase attenuation had an accuracy of 84% (86/103), specificity of 100% (84/84), sensitivity of 11% (2/19), positive predictive value of 100% (2/2), and negative predictive value of 83% (84/101) in identifying PTEN expression.

CONCLUSION

Relative corticomedullary phase attenuation may help to identify PTEN expression in ccRCCs, if validated prospectively.

Utility of multiphasic multidetector computed tomography in discriminating between clear cell renal cell carcinomas with high and low carbonic anhydrase-IX expression

PURPOSE

To investigate if multiphasic multidetector computed tomography (MDCT) enhancement profiles can distinguish clear cell renal cell carcinomas (ccRCCs) with high carbonic anhydrase-IX (CA-IX) expression from ccRCCs with low CA-IX expression.

METHODS

With IRB approval for this retrospective study, we derived a cohort of 105 histologically proven ccRCCs with preoperative 4-phase renal mass MDCT from 2001 to 2013. Following manual segmentation, the computer-assisted detection algorithm selected a 0.5-cm-diameter region of maximal attenuation within each lesion in each phase. CA-IX expression level was determined by immunohistochemical staining of tumor specimens. In the high and low CA-IX expression subgroups, the magnitude of enhancement and washout were compared using t tests; the performance of contrast washout in differentiating between subgroups was assessed with logistic regression analysis.

RESULTS

ccRCCs with high and low CA-IX expression both exhibited peak enhancement in the corticomedullary phase. ccRCCs with high CA-IX expression demonstrated significantly greater relative nephrographic washout than those with low CA-IX expression (18.4% vs. 7.8%, p = 0.03). ccRCCs with high CA-IX expression had greater relative excretory washout than ccRCCs with low CA-IX expression with a trend toward significance (33.4% vs. 25.2%, p = 0.05). After controlling for tumor size and stage, for distinguishing ccRCCs with high and low CA-IX expression, relative excretory washout had a sensitivity, negative predictive value, accuracy, and positive predictive value of 99% (65/66), 88% (7/8), 69% (72/105), and 67% (65/97), respectively.

CONCLUSION

Relative nephrographic and excretory washout may have the potential to help distinguish ccRCCs with high and low CA-IX expression, but this requires further validation.

Renal cell carcinoma attenuation values on unenhanced CT: importance of multiple, small region-of-interest measurements

OBJECTIVE

Since it has been suggested that benign renal cysts can be diagnosed at unenhanced CT on the basis of homogeneity and attenuations of 20 HU or less, we determined the prevalence of renal cell carcinomas (RCCs) with these characteristics using two different methods of measuring attenuation.

MATERIALS AND METHODS

After IRB approval, two radiologists obtained unenhanced attenuation values of 104 RCCs (mean size 5.6 cm) using a single, large region of interest (ROI), two-thirds the size of the mass. They were then determined if the masses appeared heterogeneous. Of RCCs measuring 20 HU or less, those which appeared homogeneous were re-measured with multiple (6 or more), small (0.6 cm² or smaller) ROIs dispersed throughout the lesion. Masses with attenuations 20 HU or less were compared to those with masses with HU greater than 20 for any differences in demographic data.

RESULTS

Of 104 RCCS, 24 RCC had HU less than 20 using a large ROI. Of these, 21 appeared heterogeneous and 3 appeared homogeneous. Using multiple small ROIs, these three RCCs revealed maximum attenuation values above 20 HU (Range: 26-32 HU). A greater portion of RCCs measuring 20 HU or less using a large ROI were clear cell sub-type. There were no other differences.

CONCLUSIONS

Renal cell carcinoma can measure 20 HU or less at unenhanced CT when a single large ROI is used. While most appear heterogeneous, some may appear homogeneous, but will likely reveal attenuations greater than 20 HU when multiple, small ROIs are used. This knowledge may prevent some RCCs from being misdiagnosed as cysts on unenhanced CT.

Imaging features of solid renal masses

The widespread use of abdominal imaging techniques has increased the detection of solid renal masses over the past years. Imaging plays a crucial role in the management and surveillance and in determining which lesions need treatment. The "classical angiomyolipoma" is the only benign solid renal mass that can be characterized with confidence by imaging through the detection of a fat-containing lesion without calcifications. There is a large overlap of imaging features between benign and malignant renal masses that often makes difficult a correct characterization of these lesions. In this review, we discuss the imaging features of the main solid renal masses that may suggest a likely benign diagnosis.

Quantitative computer-aided diagnostic algorithm for automated detection of peak lesion attenuation in differentiating clear cell from papillary and chromophobe renal cell carcinoma, oncocytoma, and fat-poor angiomyolipoma on multiphasic multidetector computed tomography

OBJECTIVE

To evaluate the performance of a novel, quantitative computer-aided diagnostic (CAD) algorithm on four-phase multidetector computed tomography (MDCT) to detect peak lesion attenuation to enable differentiation of clear cell renal cell carcinoma (ccRCC) from chromophobe RCC (chRCC), papillary RCC (pRCC), oncocytoma, and fat-poor angiomyolipoma (fp-AML).

MATERIALS AND METHODS

We queried our clinical databases to obtain a cohort of histologically proven renal masses with preoperative MDCT with four phases [unenhanced (U), corticomedullary (CM), nephrographic (NP), and excretory (E)]. A whole lesion 3D contour was obtained in all four phases. The CAD algorithm determined a region of interest (ROI) of peak lesion attenuation within the 3D lesion contour. For comparison, a manual ROI was separately placed in the most enhancing portion of the lesion by visual inspection for a reference standard, and in uninvolved renal cortex. Relative lesion attenuation for both CAD and manual methods was obtained by normalizing the CAD peak lesion attenuation ROI (and the reference standard manually placed ROI) to uninvolved renal cortex with the formula [(peak lesion attenuation ROI - cortex ROI)/cortex ROI] × 100%. ROC analysis and area under the curve (AUC) were used to assess diagnostic performance. Bland-Altman analysis was used to compare peak ROI between CAD and manual method.

RESULTS

The study cohort comprised 200 patients with 200 unique renal masses: 106 (53%) ccRCC, 32 (16%) oncocytomas, 18 (9%) chRCCs, 34 (17%) pRCCs, and 10 (5%) fp-AMLs. In the CM phase, CAD-derived ROI enabled characterization of ccRCC from chRCC, pRCC, oncocytoma, and fp-AML with AUCs of 0.850 (95% CI 0.732-0.968), 0.959 (95% CI 0.930-0.989), 0.792 (95% CI 0.716-0.869), and 0.825 (95% CI 0.703-0.948), respectively. On Bland-Altman analysis, there was excellent agreement of CAD and manual methods with mean differences between 14 and 26 HU in each phase.

CONCLUSION

A novel, quantitative CAD algorithm enabled robust peak HU lesion detection and discrimination of ccRCC from other renal lesions with similar performance compared to the manual method.

Type 1 papillary renal cell carcinoma: differentiation from Type 2 papillary RCC on multiphasic MDCT

PURPOSE

To investigate whether multiphasic MDCT enhancement can help differentiate type 1 papillary renal cell carcinoma (RCC) from type 2 papillary RCC.

METHODS

With IRB approval for this HIPAA-compliant retrospective study, we derived a cohort of 36 type 1 papillary RCCs and 33 type 2 papillary RCCs with preoperative multiphasic MDCT with up to four phases (unenhanced, corticomedullary, nephrographic, and excretory) from 2000 to 2013. Following segmentation, a computer-assisted detection (CAD) algorithm selected a 0.5 cm-diameter region of maximal attenuation within each lesion in each phase; a 0.5 cm-diameter region of interest was manually placed on uninvolved renal cortex in each phase. The relative attenuation of each lesion was calculated as [(Lesion attenuation-cortex attenuation)/cortex attenuation] × 100. Absolute and relative attenuation values were compared using Mann-Whitney tests with Bonferroni correction for multiple comparisons.

RESULTS

Relative excretory phase attenuation of type 2 papillary RCCs was significantly greater than that of type 1 papillary RCCs (2.0 vs. -18.3, p = 0.005). Relative excretory phase attenuation differentiated type 1 papillary RCCs from type 2 papillary RCCs with an accuracy of 73% (36/49), sensitivity of 87% (26/30), positive predictive value of 74% (26/35), and negative predictive value of 71% (10/14).

CONCLUSION

Multiphasic MDCT enhancement may assist in differentiating type 1 papillary RCCs from type 2 papillary RCCs, if prospectively validated.

Clear Cell Renal Cell Carcinoma: Identifying the Loss of the Y Chromosome on Multiphasic MDCT

OBJECTIVE

The objective of our study was to investigate whether multiphasic MDCT enhancement can help identify clear cell renal cell carcinomas (RCCs) with the loss of the Y chromosome.

MATERIALS AND METHODS

We derived a cohort of 43 clear cell RCCs in men who underwent preoperative four-phase renal mass MDCT from October 2000 to August 2013. Each lesion was segmented in its entirety on axial images. A computer-assisted detection algorithm selected a 0.5-cm-diameter region of maximal attenuation within each lesion in each phase. A 0.5-cm-diameter ROI was manually placed on uninvolved renal cortex in each phase. The relative attenuation of each lesion was calculated as follows: [(maximal lesion attenuation - cortex attenuation) / cortex attenuation] × 100. Absolute attenuation and relative attenuation in each phase were compared using t tests.

RESULTS

Both clear cell RCCs with the loss of the Y chromosome and clear cell RCCs without the loss of the Y chromosome exhibited peak enhancement in the corticomedullary phase. However, relative nephrographic attenuation of clear cell RCCs with the loss of Y was significantly less than that of clear cell RCCs without the loss of Y (mean, -8.9 vs 8.4 respectively; p = 0.013). A relative nephrographic attenuation threshold of -1.6 identified the loss of Y with an accuracy of 70% (30/43), sensitivity of 73% (16/22), and specificity of 67% (14/21).

CONCLUSION

Multiphasic MDCT enhancement may assist in identifying the loss of the Y chromosome in clear cell RCCs; this result should be validated in a large prospective trial.

Diagnostic Imaging of Autosomal Dominant Polycystic Kidney Disease

Autosomal dominant polycystic kidney disease (ADPKD) is one of the most common genetic disorders caused by a single gene mutation. The disease usually manifests itself at the age of 30-40 years and is characterized by formation of renal cysts along with the enlargement of kidneys and deterioration of their function, eventually leading to renal insufficiency. Imaging studies (sonography, computed tomography, magnetic resonance imaging) play an important role in the diagnostics of the disease, the monitoring of its progression, and the detection of complications. Imaging is also helpful in detecting extrarenal manifestations of ADPKD, most significant of which include intracranial aneurysms and cystic liver diseases.

MRI features of renal cell carcinoma that predict favorable clinicopathologic outcomes

OBJECTIVE

The purpose of this article is to determine whether MRI features of renal cell carcinoma (RCC), such as enhancing solid component and T1 signal intensity, are associated with clinicopathologic outcomes.

MATERIALS AND METHODS

This retrospective study included 241 RCCs in 230 patients who underwent preoperative MRI, had pathologic analysis results available, and were monitored for at least 3 months. A radiologist assessed tumor features on MRI, including unenhanced T1 signal relative to renal cortex and the percentage of solid enhancing components. The electronic medical record or follow-up images were reviewed to assess for the development of local recurrence or metastases. Statistical analysis was performed to correlate imaging features at MRI with pathologic and clinical outcome.

RESULTS

The following tumor features were observed: predominantly cystic morphologic features (defined as solid component≤25%, n=33), solid component greater than 25% (n=208), T1 hypointensity (n=97), and T1 intermediate intensity or hyperintensity (n=144). Local recurrence or metastases were observed in 14 patients. Compared with T1-intermediate or -hyperintense lesions, T1-hypointense RCCs were more likely to be low stage (90.7% vs 74.3%; p=0.001) and low grade (78.9% vs 41.8%; p<0.001) and had a lower rate of recurrence or metastases (3.3% vs 8%; p=0.167). Compared with lesions with greater than 25% solid enhancement, predominantly cystic RCCs were more likely to be lower stage (93.9% vs 78.8%; p=0.053) and lower grade (94.7 vs 56.5%; p<0.001) and to have no incidence of recurrence or metastasis (0% vs 6.9%; p=0.227). RCCs that were both cystic and T1 hypointense (n=14) were lower stage (100% vs 79.6%; p=0.047) and lower grade (92.9% vs 58.1%; p=0.01) and had no recurrence or metastases on follow-up.

CONCLUSION

Cystic and T1-hypointense RCC show less-aggressive pathologic features and favorable clinical behavior.

Clinical utility of quantitative imaging

Quantitative imaging (QI) is increasingly applied in modern radiology practice, assisting in the clinical assessment of many patients and providing a source of biomarkers for a spectrum of diseases. QI is commonly used to inform patient diagnosis or prognosis, determine the choice of therapy, or monitor therapy response. Because most radiologists will likely implement some QI tools to meet the patient care needs of their referring clinicians, it is important for all radiologists to become familiar with the strengths and limitations of QI. The Association of University Radiologists Radiology Research Alliance Quantitative Imaging Task Force has explored the clinical application of QI and summarizes its work in this review. We provide an overview of the clinical use of QI by discussing QI tools that are currently used in clinical practice, clinical applications of these tools, approaches to reporting of QI, and challenges to implementing QI. It is hoped that these insights will help radiologists recognize the tangible benefits of QI to their patients, their referring clinicians, and their own radiology practice.