Imaging of Renal Cancer

Journal Pre-proof

Imaging of Renal Cancer Satheesh Krishna , Ashley Leckie , Ania Kielar , Robert Hartman , Ashish Khandelwal PII: DOI: Reference:

S0887-2171(19)30081-2 https://doi.org/10.1053/j.sult.2019.12.004 YSULT 901

To appear in:

Seminars in Ultrasound CT and MRI

Please cite this article as: Satheesh Krishna , Ashley Leckie , Ania Kielar , Robert Hartman , Ashish Khandelwal , Imaging of Renal Cancer, Seminars in Ultrasound CT and MRI (2019), doi: https://doi.org/10.1053/j.sult.2019.12.004

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Inc.

Imaging of Renal Cancer Authors- Satheesh Krishna1, Ashley Leckie1, Ania Kielar1, Robert Hartman2, Ashish Khandelwal2 Addresses of the institution1. Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital, Women's College Hospital, University of Toronto. 2. Mayo Clinic 200 First Street SW, Rochester, MN 55905 CorrespondenceAshish Khandelwal, MD Department of Radiology, Mayo Clinic 200 First Street SW, Rochester, MN 55905 Email: [email protected] Tel: 507-255-2015 Fax: 507-255-7872 Funding: None Disclosures-None

Abstract Cystic renal masses are common incidental findings on cross-sectional imaging. Accurate characterisation of cystic renal masses is essential to guide management. Renal mass protocol comprises of a good quality non-contrast, corticomedullary and nephrographic phases with each phase providing complementary information for diagnosis. Attenuation measurements in different phases are central to the ‘golden-rules’ in renal mass imaging in characterisation of cystic renal masses. Newer modalities like dual energy CT, can obviate need for repeat imaging by generation of iodine-overlay image and also help in eliminating artifactual pseudoenhancement which is problematic in small endophytic cysts. Contrast enhanced ultrasound (CEUS) is extremely sensitive in identification of enhancing components in cystic masses especially in the setting of renal failure as the microbubbles are not excreted via the renal route. The Bosniak classification for renal cystic masses has been revised in 2019 to standardise terminology and further improve upon the original version. The current version includes CT and MRI, although CEUS is yet to be included. Image guided biopsy of renal mass helps confirm the diagnosis and also gives information regarding the subtype and grading and is useful in avoiding overtreatment of benign entities, and in active surveillance. Multiparametric MRI can potentially help avoid needle biopsy in a subset of patients by accurate characterisation through previously validated algorithm. Keywords Renal nodule; Bosniak; Renal mass protocol; Dual-energy CT; MR algorithm

Introduction Cystic renal masses are common incidental findings on cross-sectional imaging. About 15% of patients undergoing CT have at least one incidental renal cystic renal mass >1cm [1]. The majority of these cystic renal masses are benign cortical cysts; however a small proportion are renal cell carcinomas (RCC). The most common types of RCC include: 1) clear cell 2) papillary and 3) chromophobe, with clear cell RCC having the worst prognosis. Currently, the most common clinical presentation of RCC is as an incidentally discovered renal lesion [2]. The incidence rates of RCC have been increasing, and it is currently the 6th most common cancer in men [3]. The cause of this increased incidence may partially be due to an increased imaging utilisation of CT. The first step in approaching a renal cystic renal mass is characterising the cystic mass as a benign cyst vs solid neoplasm and this is accomplished with either CT or MR. CT has a slightly higher rating for the initial characterisation of indeterminate renal masses by the American College of Radiology appropriateness criteria when compared to MR (ACR – Appropriateness Criteria® rating 9 for CT vs 8 for MRI) [4].

Renal mass protocol CT The standard “renal mass” protocol CT consists of a three-phase acquisition composed of: (1) non-enhanced CT (NECT), (2) corticomedullary (CM) phase and (3) nephrographic (NG) phase contrast-enhanced CT (CECT) [5]. A sample protocol is presented in Table 1. NECT identifies the baseline attenuation of a renal cystic mass before administration of iodinated contrast in order to detect and quantify post contrast enhancement. NECT is also important for detection of bulk fat and calcification, both of which may potentially be less discernible on CECT [6]. Presence of bulk fat (macroscopic/gross fat) in a renal mass is diagnostic of angiomyolipoma (AML). Reconstructions of NECT data to thin sections (1.5-3 mm) are necessary to confirm the presence of intralesional bulk fat because small amounts of fat may be obscured by volume averaging in thicker sections [7]. Correct identification of bulk fat helps in identifying AMLs which are benign neoplasms and unnecessary interventions/surgery can be avoided,

particularly when they are small. On the other hand, calcification in solid lesions is more common in RCCs and exceedingly rare in untreated AMLs [8]. The CM phase is timed when the contrast medium is present in the proximal convoluted tubules of the renal cortex and in the Columns of Bertin, at a time when there is maximum contrast separation between the renal cortex and medulla [9]. The timing is approximately 3040 seconds after contrast injection; this may be timed either empirically or by using bolustracking software depending on institutional preference and scanner type. The major use of the CM phase is categorizing the subtypes of RCC depending on their temporal enhancement characteristics. CM phase also clearly depicts the renal arterial vasculature (as a roadmap for embolization/surgery) and potential renal vein involvement by enhancing tumour thrombus [10]. CM phase best identifies vascular mimics of renal masses such as aneurysms or arterialvenous fistulas, which can simulate a solid enhancing renal masses on other phases, and thereby avoid a biopsy which could result in catastrophic complications. The NG phase is defined as the time when the contrast medium enters the loop of Henle and the collecting ducts. At this time, both the renal cortex and medulla are enhancing uniformly and homogeneously [9]. The timing is approximately 90 to 120 seconds after contrast injection. The NG phase is the key-phase of the renal mass CT protocol for two reasons: (1) NG phase is the most sensitive for detecting cystic renal masses (Figure 1), and (2) NG phase is also most sensitive for detecting internal enhancement of a renal cystic mass. Furthermore, the NG phase potentially depicts extent of tumour thrombus especially into the renal vein and inferior vena cava [11]. The technical parameters (such tube current, tube voltage, noise index levels, type of image reconstruction and iterative reconstruction levels) should be identical between the NECT, CM and NG phases [12]. This is necessary for consistent subjective assessment of the renal lesion. Higher noise levels from a lower dose technique can artifactually simulate lesion heterogeneity and contour irregularity [5, 13]. Also, attenuation values may be affected by differences in technique. Some institutions routinely use a fourth, urographic phase, which is performed at approximately 8 to 10 minutes after contrast injection. This phase is used to detect upper tract urothelial malignancies and for renal mass extension into the pelvi-calyceal

system[14]. However, data is lacking if routine use of the urographic phase adds a clear benefit in renal mass imaging and if its use can be justified against added radiation dose to patient.

Five golden rules in renal mass imaging Characterisation of cystic renal masses is guided by evidence based guidelines and algorithms. 1. A renal mass with low-density components that measures less than -10 HU should be considered diagnostic of AML. However, identification should be performed using small regions of interest of 19-24 mm2 [15] or identification of at least 20 pixels of attenuation less than -20 HU [16]. Using smaller regions of interest or identification of a single pixel using cross-hair should be avoided as it can result in erroneous sampling of stochastic noise (quantum mottle) which can result in false-positive fat detection, resulting in misclassifying an aggressive renal mass as an AML. 2. A renal cystic mass measuring between -10 and +20 HU (on both NECT and CECT) is consistent with water attenuation. However, in order to confidently diagnose a cyst, such cystic masses should also be homogeneous with a smooth imperceptible wall and internal homogeneity. A minority of solid clear-cell RCCs may measure between -10 and +20 HU, however they are heterogeneous with irregular margins [17] (Figure 2). On the other hand, while using the portal venous phase CT to measure the attenuation of an incidental renal cystic mass, studies have shown that very few masses with density of less than 40 HU turn out to be RCCs [18, 19]. It is considered safer to use a threshold of 30 HU or lower to diagnose benign cyst on portal venous phase CECT [20]. 3. A renal cystic mass measuring between 20 - 70 HU on NECT or >30 HU on a single phase CECT is considered indeterminate (due to overlap in attenuation with RCC). Further evaluation with renal mass protocol CT / MRI is required to detect the presence of internal enhancement in order to differentiate between a solid neoplasm versus a haemorrhagic/proteinaceous cyst. 4. A non-calcified homogeneous renal cystic mass with attenuation of 70 HU or greater on NECT is diagnostic of hemorrhagic proteinaceous cyst (HPC) [21].

5. An increase in attenuation by 20 HU or more on the CECT when compared with baseline attenuation on NECT is consistent with enhancement, whereas an attenuation difference of 10 HU or less is consistent with absence of enhancement [22]. Enhancement between 10 - 20 HU is considered indeterminate and usually requires further confirmation with a different cross-sectional modality. For purposes of identifying enhancement, measurement of attenuation should be done on the NG phase as some papillary tumors show slow progressive enhancement and may be mischaracterised as indeterminate or non-enhancing (attenuation difference less than 20 HU) if measurements are done on CM or portal venous phase CECT [23].

Dual energy CT Introduction of dual-energy CT (DECT) further expands the ability of CT to correctly diagnose and categorize cystic renal masses. The potential applications of DECT in renal mass imaging include: 1) derivation of a virtual NECT data set to determine baseline attenuation, when only a single phase CECT acquisition is performed, potentially replacing the true NECT dataset, 2) reconstruction of virtual mono-energetic/monochromatic data to eliminate artifactual pseudoenhancement and 3) subjective visual analysis of iodine overlay images or quantitative analysis of iodine concentration to confirm or quantify enhancement [24]. Eliminating routine acquisition of a true NECT, as part of the triphasic renal mass protocol, and replacing it with virtual NECT derived from either the CM or NG phase DECT acquisition may decrease radiation dose by up to 33%. However, there has been considerable heterogeneity across vendors in the method of implementation, prevalence of artifacts and the reliability of the results. The variation of the derived virtual NECT attenuation measurements with true NECT measurements in the setting of cystic renal masses and its potential impact on diagnosis of internal enhancement has not been adequately established. In phantom studies, the absolute difference between attenuation values measured using true and virtual NECT was >10 HU, in up to 25% of cases [25]. An error of 10 HU in establishing baseline attenuation would result in incorrectly diagnosing presence or absence of enhancement within a renal lesion. Due to these

reasons, most radiology departments continue to perform a true NECT a part of the routing renal mass protocol. Pseudo-enhancement is the artifactual increase in attenuation of a non-enhancing renal cystic mass following contrast medium administration, even after elimination of partial volume averaging. This phenomenon is due to inadequate algorithmic correction for beam-hardening artefacts from a polychromatic beam source [26]. Pseudo-enhancement is more common in small cystic renal masses and in endophytic cystic renal masses [27] (Figure 3). If the artifactual attenuation increase is more than 20HU, this artifactual increase may result in wrongly categorizing a non-enhancing cyst as RCC. More often than not, the artifactual increase is between 10 - 20 HU (in the indeterminate range) resulting in patient recall for further imaging with either ultrasound or MR for correct characterization. Dual-energy data sets can be reconstructed in virtual monoenergetic/monochromatic data sets using material decomposition, which enables more accurate beam-hardening correction, allowing for improved linearity of CT attenuation resulting thereby eliminating the problem of pseudoenhancement (which is caused by a polychromatic beam). This has been validated in multiple studies and would potentially result in more accurate characterization especially of smaller and endophytic cystic renal masses [28, 29]. Especially in rapid kilo-voltage switching DECT, a 70 keV monochromatic reconstruction yielded best correlation of attenuation and enhancement compared to conventional CECT [30]. Increasing imaging utilisation has resulted in higher incidence of detecting cystic renal masses: this includes those seen on a single phase CECT with attenuation in the indeterminate range (>30HU). Due to overlap in attenuation values between RCCs and HPCs patients end up being called back for further assessment. However presence of enhancement within a renal cystic mass can be diagnosed if the CT was done using a single-phase DECT acquisition, saving the patient time and anxiety [31] (Figure 4). In select patients, the monetary savings from abolishing additional imaging may reduce payer costs associated with use of DECT [32]. The use of material decomposition in DECT enables accurate identification of imaging voxels containing iodine. This information can then be superimposed onto the virtual non-contrast

image set to generate iodine overlay images with colour representations of pixels containing iodine. Subjective visual assessment of these iodine-overlay images generated from single phase DECT can be used to assess presence or absence of iodine (and thereby presence or absence of enhancement) [33]. In addition, the iodine concentration within a cystic mass can be quantified, and presence or absence of enhancement can be established comparing with previously established thresholds. Multiple published studies have shown reproducible results when using quantitative iodine content analysis with DECT for characterisation of enhancement (using either dsDECT or rsDECT technologies) [34-39]. However, the thresholds for diagnosis differ between different imaging platforms used and in the case of rsDECT, across different institutions using the same platform. For example, using dsDECT a threshold of 0.5mg/ml was identified by Chandarana et al. whereas when using rsDECT, both Kaza et al. and Zarzour et al. showed significantly higher threshold levels of iodine content needed to confirm enhancement [36, 37, 39]. Even when using the same technology, Kaza et al. (>2 mg/ml) and Zarzour et al. identified different thresholds, which also showed variation depending on the phase of acquisition (1.22 in CM phase versus 1.28 mg/ml in NG phase) [37, 39]. In a study by Sadoughi et al, the optimal threshold at rsDECT was confirmed to be 1.2mg/ml, while they also claim that using an attenuation difference of 15HU (as against 20HU) while using DECT increased sensitivity without pseudoenhancement [40]. Thus it is still unclear if the iodine concentration measurements vary significantly between DECT implementation in NG phase vs. CM phase and which is the optimal phase to implement. A sample protocol has been provided in Table 2. Despite these variations, iodine quantification has been shown to be at least comparable, if not better than, traditional standard enhancement measurements [34, 40, 41]. In addition to elimination of pseudoenhancement and enabling quantification of enhancement within a renal cystic mass, DECT has also been used in multiple other indications in renal mass imaging such as in diagnosis of minimal-fat-angiomyolipoma, subtyping clear-cell and papillary RCC and differentiating between low-versus high-grade clear-cell RCC [38, 42, 43]. However, the clinical utility and the iodine content thresholds across various DECT platforms and vendors are less well established in this setting and further work is required.

Ultrasound Incidental cystic renal masses are frequently identified on ultrasound. Comprehensive characterisation of cystic renal masses by ultrasound is limited both by contrast resolution as well as by impact of patient body habitus, patient’s ability to hold their breath and intersonographer variation regarding image quality. However, ultrasound is useful for evaluating indeterminate renal masses, specifically, homogeneous lesions with attenuation of 20–70 HU on unenhanced CT and > 20 HU on single phase contrast-enhanced CT (Figure 5). In these cases, visualisation of homogeneously anechoic, round or ovoid structure, with a sharply defined smooth, imperceptible wall and increased sonographic through-transmission with up to 2-3 nonmeasurable septa or tiny calcifications, is diagnostic of simple cyst [44]. Presence of internal echoes usually requires further evaluation with a “renal mass” protocol CT or MRI. Introduction of contrast-enhanced ultrasound (CEUS) has increased the contrast-resolution of ultrasound, expanding scope of this modality. The principal use of CEUS is to identify presence or absence of enhancing solid components in a renal cystic mass and CEUS has high sensitivity in this setting [45, 46]. CEUS is especially useful in patients with contraindication to CT or MR contrast agents and in patients with renal failure, since microbubbles are not excreted by kidney (Figure 6). It can also be used patients with prior renal transplant being evaluated for an indeterminate renal cystic mass in their native kidney [47, 48].

MRI MR is comparable to CT for evaluation of renal masses. Sample protocol provided in Table 3. Better contrast resolution enables better evaluation of internal architecture including being cystic versus solid, presence of septations and hemorrhage. T1 weighted opposed phase imaging is more sensitive for identifying small amounts of macroscopic/bulk fat within AML due to india-ink artifact on out-of-phase images or direct visualisation on fat-only reconstructions from Dixon-based acquisitions [49]. This increased accuracy for identifying benign angiomyolipomas translates into decrease in biopsy and other unnecessary intervention for benign AML. Subtraction imaging after intravenous gadolinium-based contrast agent

administration, is the gold-standard for detection of enhancement in a renal cystic mass (Figure 4). It is sensitive for identify a small focus of enhancement in an otherwise non-enhancing, heterogeneous cystic mass. However, many of these advantages are limited due to artefacts from respiratory motion resulting in misregistration artifacts which can either obscure or simulate enhancement (Figure 7). The same guiding principles for the ‘golden-rules for CT’ also apply for MR. Well-defined homogeneous cystic renal masses similar in signal intensity to cerebrospinal fluid at T2-weighted imaging are benign cysts (Figure 3). On unenhanced MR, a markedly hyperintense lesion on T1 weighted images (approximately 2.5 times the normal parenchymal signal intensity) is likely a HPCs [50, 51]. Measurable enhancement has been defined as a 15% or more increase in signal intensity on contrast enhanced MRI [52], however, qualitative assessment of subtraction imaging has been shown to be superior in assessment of enhancement in renal masses [53]. The role of functional imaging such as diffusion-weighted imaging (DWI) and perfusion analysis in routine clinical practice has not been fully established and requires further investigation.

Cystic renal masses and Revisions in Bosniak Classification 2019 Cystic RCC pose a unique diagnostic challenge because when compared with solid masses, they are more likely to be benign, and, when malignant, they tend to be less aggressive. They are almost certainly overdiagnosed and overtreated [54, 55]. For more than 30 years, the Bosniak classification has been used to risk-stratify and predict the likelihood of malignancy in cystic renal lesions. The original Bosniak classification had high interobserver variation because the descriptors pertaining to walls and septations (which form the basis for differentiating Bosniak classes) lack clear definitions (i.e. “thin”, “few”, “perceived enhancement”) [56]. This has resulted in wide variability in the reported malignancy rates for each Bosniak class. Also, the original Bosniak classification was designed for CT and does not formally incorporate MRI or US. The Bosniak classification has been recently revised in 2019 and endorsed by the Society of Abdominal Radiology to address these shortcomings (Table 4) [55]. This revised Bosniak classification, version 2019, considers a cystic mass to be one in which less than 25% of the

mass is composed of enhancing tissue. This value was chosen to prevent overlap with aggressive solid masses containing area of necrosis from being miscategorized as an indolent cystic mass. Terms such as ‘complicated/complex cyst’ should be avoided. Quantitative measurements of wall and septal thickening, <=2mm (thin), 3mm (minimally thickened) and >=4mm (thick) as well as quantitative measurements of the number of septations 1-3 (few) and >=4 (many), have replaced the previously more ambiguous subjective descriptors. Enhancement within walls and septations has been simplified into a binary ‘enhancing’ vs. ‘nonenhancing’ rather than the previous confusing terms which included ‘measurable enhancement’ vs ‘perceived enhancement’. Homogeneously hyperattenuating, nonenhancing renal masses, measuring larger than 3cm have been downgraded from Bosniak IIF to Bosniak II (Figure 5). Cystic renal masses with thick or nodular calcification have also been downgraded from Bosniak IIF to Bosniak II. The 2019 Bosniak II category now includes any type of calcification since it has been found that presence or change of calcification over time does not have high positive predictive value as an isolated feature [57]. MRI may be helpful in the setting of calcified renal lesion assessment, as streak artifact from abundant nodular calcification may obscure visualized of an enhancing solid component using CT. Homogeneous masses considered too small to characterize have also been classified into Bosniak II. In the revised classification, septations in renal lesions classified as Bosniak IIF must be enhancing and lesions with non-enhancing septations have been downgraded from Bosniak IIF to II (Figure 8). All the above changes have been proposed in order to increase the specificity, at the cost of sensitivity, to avoid overtreatment, given that most cystic renal neoplasms have an indolent course. A heterogeneous, non-enhancing mass on CT (defined as temporal attenuation difference of less than 20HU) is considered incompletely characterised and requires MR for assessment, due to superior contrast resolution of MRI. This is to avoid potentially miscategorising a papillary neoplasm as a Bosniak II cyst: up to 1/3 of papillary RCCs show temporal attenuation differences of <20HU, even on NG phase [58]. The definition of Bosniak IV renal cystic mass has been clarified as a focal, enhancing, convex protrusion, measuring 4 mm or more, if it has obtuse margins with the wall or septa. However, it can be any size if it has acute margins (Figure 7). The rates of malignancy in each of the updated Bosniak classification has been

estimated as follows: Class I - 0%, II - <1%, IIF – 10%, III – 50%, IV – 90% [59, 60]. The size of the mass or interval change in size on follow-up is not used in the current Bosniak classification. 10% of Bosniak IIF show migration to a higher Bosniak class (either Bosniak III or IV) at follow up imaging, and those with progression have an approximately 85% likelihood of being malignant [59]. Further research is required to validate this revised classification system in terms of interobserver agreement and rates of malignancy in each class. Potential incorporation of CEUS into the classification will also need to be investigated.

Image-guided renal mass biopsy Optimal treatment of renal masses depends on the size of the tumor (above or below 4cm), staging (which is usually accomplished by imaging), subtype of RCC, as well as the grading of RCC (low grade vs high grade). The most common sub-types include clear cell RCC (ccRCC; 7075%), papillary RCC (pRCC; 10–21%) and chromophobe RCC (chrRCC; 5%) [61]. In the past, any presumed RCC on cross-sectional imaging used to be treated with nephrectomy. However, oncocytomas and AMLs are common benign mimickers of RCC: up to 20% of small cT1a masses that undergo resection are determined at pathology to be benign, mainly oncocytoma and AML without detectable macroscopic fat (termed “fat-poor AML”) [54, 62]. Percutaneous, targeted renal mass biopsy can be used to potentially identify these benign mimickers and help avoid unnecessary interventions. A recent meta-analysis showed aggregate sensitivity and specificity of 99.1% and 99.7%, for renal biopsy, with 90.3% concordance between diagnoses established at biopsy and after surgery [63]. Renal mass biopsy can help avoiding surgery in up to 33% of cases initially considered to be malignant on imaging [64]. Underutilization of renal mass biopsy may contribute to 6000 unnecessary nephrectomies annually [65]. Underutilisation of biopsy has been traditionally due to fear of tumor seeding, which is currently recognized as an extremely rare complication and is not observed at any higher frequency than after biopsy of other malignancies in other organs, with published rates varying from 0.01- 1.0% [66-68]. Although the published rate of complications after renal biopsy is about 8%, the incidence of severe bleeding (Clavien-Dindo classification > grade 1 [i.e., bleeding requiring pharmacologic

treatment, intervention, or blood transfusion]) is extremely low, occurring in only 0.7% of cases [63]. Thus, biopsy is considered a safe procedure. Of note, bleeding is more common with biopsies of central hilar masses [69].

Emergence of ‘virtual biopsy’ Despite the above mentioned safety profile of renal mass biopsy, it is still an invasive test causing significant anxiety and concern to the patient. Accurate biopsy especially in small central masses may be technically challenging, especially in patients with high body mass index. The role of sampling in cystic renal masses has not been well established, due to concerns of tumor spillage, as well as difficulty in accurately targeting the small, solid component of these cystic masses. Final results of renal mass biopsy may non diagnostic in up to 14% [70]. Up to 37% of patients found to have either inadequate, nondiagnostic or negative sampling have malignant disease at time of surgical resection, despite an initial “negative” biopsy [68]. Specifically, oncocytomas have overlapping pathologic features with chromophobe RCC and the resultant report may not be more specific than “oncocytic neoplasm” [71, 72]. There has been a reported 1% increase in likelihood of upstaging renal masses from cT1a to pT3a (i.e., involvement of perirenal fat) in patients with RCC undergoing biopsy, potentially due to breach of the tumor’s capsule [73]. The accuracy of grading (low grade vs high grade) of RCC on renal mass biopsy is fairly low. Biopsy samples only a small portion or specific areas of a renal cystic mass, whereas up to 25% of RCCs can have intratumoral grade heterogeneity (meaning, that different areas have different tumor grades) [74]. Due to undersampling on renal mass biopsy, pathologic upgrading of low grade RCC to high grade RCC after surgery occurs in 20% of patients [75]. Moreover, some critical features including presence of a sarcomatoid component of RCC (which is associated with worse prognosis) is not identified in up to 90% of patients prior to surgery [76]. Lack of such crucial information due to limitations of tissue undersampling necessitates alternate strategies for more comprehensive evaluation. Attempts at non-invasive characterisation of the entirety of a renal mass using imaging (especially MR) has been termed ‘virtual biopsy’ [77].

Any attempt at ‘virtual biopsy’ of the renal mass using imaging should be able to correctly identify the histologic subtype of the renal mass and the tumor grade. An algorithmic approach to characterisation using multiparametric MRI has been presented (Table 5) [77, 78]. First step in this algorithm is to assess signal intensity of renal mass on T2-weighted images and determine whether mass is hyper-, iso-, or hypointense relative to renal cortex. ccRCC is usually hyperintense on T2W images while pRCC and AML (without visible fat) is usually hypointense. The second step is to establish the degree of enhancement on the CM phase as being intense, moderate or mild, depending on if the mass is enhancing more than the renal cortex, 50% of renal cortex or 25-30% of renal cortex respectively [79]. pRCC shows only mild enhancement which progressively increased on the subsequent NG phase. ccRCC and AML can both show intense enhancement and can mimic each other, especially when the ccRCC is hypointense on T2W. In such cases, calculation of ADER (arterial-delayed enhancement ratio) (Table 5) with a ratio of > 1.5 favors AML (along with diffusion restriction and homogeneity of the lesion) [80, 81] (Figure 9). For masses that are hyperintense on T2 weighted images, and which demonstrate intense post-gadolinium enhancement, the primary differential diagnosis is between oncocytoma and ccRCC. Although multiple studies have shown that it is difficult to reliably distinguish between these two entities, presence of considerable heterogeneity and microscopic fat (signal drop on opposed phase imaging) strongly favours ccRCC (Figure 10), while presence of SEI (segmental enhancement inversion) favors oncocytoma. SEI is defined as presence of both intensely enhancing and hypoenhancing components on the CM phase which reverses on the NG phase [82]. This is a controversial imaging finding with low reproducibility and low interobserver agreement that has been disputed by several studies [83]. chrRCC is usually isointense on T2W images with moderate enhancement. The above algorithm has been validated to produce a 5-point Likert score (ccLS – clear cell likelihood score) which conveys likelihood of ccRCC in cT1a renal masses. A score of 4 or greater had 79% accuracy for ccRCC and a score of 2 or less had 93% positive predictive value for nonccRCC neoplasms (including benign or malignant) [84] (Figure 10). Although these results are promising, the accuracy is still less than that of renal mass biopsy. Addition of other features (including presence of hemorrhage/T1 hyperintensity, presence of iron/loss of signal on in-

phase images in pRCC, diffusion-restriction in AML without visible fat as well as patient demographics, specifically middle aged women), all of which are not part of the current routine algorithm, may further improve accuracy but require rigorous validation [85-87]. The exact role of DWI in subtyping of RCC is less well established and has not been currently incorporated in this iteration of the algorithm. A meta-analysis of DWI studies did not show differences in ADC values among RCC subtypes [88]. However, a significant difference has been identified in ADCs of RCCs vs oncocytomas [89]. This information may potentially be useful, especially in patients in which renal mass biopsy result is non-specific and the pathology report only mentions ‘oncocytic neoplasm’ which can be the result of overlapping pathologic findings of oncocytoma with chrRCC [90]. Staging of RCC is according to the 8th edition TNM classification of American Joint Committee on Cancer (AJCC) as provided in Table 6. While T1 and T2 are purely based on the size, imaging is only moderately accurate in identification of T3a (renal sinus fat invasion, perinephric fat invasion, segmental renal vein invasion). While renal vein thrombus invasion beneath the diaphragm is staged as T3b, presence of invasion of wall of IVC upgrades the local stage to T3c. Although conventional subjective imaging is difficult to differentiate T3b from T3c, recently texture analysis has been shown to be useful in identifying IVC wall invasion [91]. The utility of imaging for grading renal neoplasms is less well established. Various strategies using diffusion restriction, tumor texture analysis, radiomics and machine-learning/artificial intelligence have been attempted with variable success [92, 93]. None has yet been validated for clinical use due to variability of results based on type of scanners used and imaging parameters. Thus non-invasive ‘virtual biopsy’ with multiparametric MR, although promising, requires further improvement in accuracy in successive iterations and validation in large prospective cohorts. Also, the current pathologic classification of renal masses has considerably expanded beyond the routine subtyping into ccRCC, pRCC and chrRCC and a detailed discussion of this is beyond the scope of this review and has been discussed elsewhere [94]. The syndromic associations of RCC have also been discussed elsewhere [95].

Treatment of RCC Surgical resection remains the only known curative treatment for localized RCC (partial nephrectomy for T1 disease and laparoscopic radical nephrectomy for T2 disease), and it also is used for palliation in metastatic disease. Focal ablation (radiofrequency or cryoablation) can be considered as an alternative for small lesions in carefully selected patients who are not candidates for surgery. Alternatively, active surveillance is being increasingly used in elderly and/or comorbid patients with small renal masses. Targeted therapy and immunomodulatory agents are considered standard of care in patients with metastatic disease [96].

Conclusion Increased imaging utilisation has led to increased detection of indeterminate cystic renal masses which can be accurately classified as benign cysts or enhancing neoplasms based on well-established guiding principles of imaging. Each commonly used imaging modality has its own strengths and weaknesses in characterisation of renal lesions and the information obtained from each of them is complementary towards achieving a final diagnosis. Image guided-renal mass biopsy has emerged as having a central role, especially in the era of increasing active surveillance of small renal masses. Non-invasive virtual biopsy using an algorithmic approach on MR has been validated, however requires further refinement on successive iterations to improve accuracy.

Figure legends: Figure 1: 63 year old female with left renal cell carcinoma (RCC). The renal cystic mass is difficult to appreciate on non-enhanced CT (NECT) (a) and corticomedullary (CM) phase (b) CT. However, the renal cystic mass is well identified (arrow) on the Nephrographic (NG) phase (c). NG phase is the most sensitive in detection of renal masses.

Figure 2: 80 year old male with renal mass. (a) NECT shows a renal cystic mass with attenuation <20HU (arrow). However, the cystic mass appears heterogeneous (b) on NECT with appropriate windowing. NG phase (c) and excretory phase (d) CT shows the cystic mass having enhancing solid components (arrows). The renal cystic mass was clear-cell type RCC on biopsy. RCCs can rarely have attenuation less than 20HU on NECT. A renal cystic mass should be diagnosed as a benign cyst only if it measures <20HU on NECT AND is uniformly homogenous. A heterogeneous renal cystic mass should not be misdiagnosed as a cyst based on attenuation and requires ‘renal-mass protocol’ CT for further evaluation. Figure 3: 23 year old female with an incidentally detected renal cystic mass. NG phase CECT (a) shows an incidental small renal cystic mass (arrow). Attenuation on NECT (b) is 16HU and attenuation on NG phase (c) is 40HU. The attenuation difference (40-16 HU) equals 24 HU which is greater than the 20HU threshold which is considered diagnostic of ‘enhancement’. MRI was performed due to suspicion for pseudoenhancement. T2W MRI (d) shows that the cystic mass is homogenous and thin-walled (arrow), with signal intensity similar to CSF. Subtraction imaging following gadolinium administration (e) shows no contrast uptake (arrow), which is diagnostic of simple cyst. Pseudoenhancement is artifactual increase in attenuation following iodinated contrast medium administration in benign cysts. Pseudoenhancement is more common in small and endophytic cysts. Figure 4: 48 year old female with incidentally detected renal cystic mass during evaluation for a pancreatic lesion. Axial CECT (a) shows an incidental left renal cystic mass (arrow) which has attenuation higher than expected (>30HU) for a simple renal cyst and is concerning for either a solid renal mass or a hemorrhagic/proteinaceous cyst (HPC). The CT was done with dual-energy CT technique and iodine-overlay images could be obtained. Iodine-overlay image (b) shows absence of iodine in the renal cystic mass (arrow). Subsequently MR was performed. Axial T1W sequence (c) shows the renal cystic mass as hyperintense on T1 (arrow). Axial post-gadolinium enhanced subtraction image (d) (which is considered the gold-standard in the detection of contrast enhancement) shows no enhancement within the renal cystic mass (arrow), thereby confirming the diagnosis of HPC. Greyscale ultrasound (e) depicts the HPC (arrow) as anechoic, with thin imperceptible wall without internal echogenic solid component.

Figure 5: 57 year old female with an incidental renal cystic mass. NECT (a) shows a homogeneous renal cystic mass (arrow) with attenuation in the indeterminate range (2070HU). The attenuation on CM phase (b) and NG phase (c) is 59 HU and 56 HU respectively, which confirms absence of enhancement because the temporal attenuation difference is less than 20HU. Absence of enhancement in a hyperattenuating renal cystic mass is in keeping with hemorrhagic/proteinaceous cyst. According to the original Bosniak classification cystic renal masses with similar characteristics measuring larger than 3cm were classified into Bosniak IIF whereas they have been re-classified into Bosniak II according to the revised Bosniak 2019 classification. Ultrasound (d) shows an anechoic cystic mass (arrow) with no solid component and no internal vascularity with thin imperceptible wall. Ultrasound is useful for evaluation of homogeneously hyperattenuating cystic renal masses identified on CT. Figure 6: 65 year old female with left renal cystic mass in a patient with renal failure. Grey-scale ultrasound (a) shows a homogenous anechoic cystic mass with thin imperceptible wall (arrows) which is the expected appearance of a simple cyst. NECT (b) shows the renal cystic mass (arrow) with an attenuation of 38HU which is higher than expected of a simple cyst. Contrast-enhanced ultrasound (CEUS) (c) shows solid enhancement (arrow) in the renal cystic mass. Subsequent biopsy confirmed papillary RCC and CT guided radiofrequency ablation (d) was performed (arrow). Figure 7: 72 year old female with renal mass. CECT (a) shows a heterogeneous renal mass (arrow) with attenuation in the indeterminate range (>30HU). T2W MR (b) confirms heterogeneous T2-hypointense renal cystic mass (arrow). Coronal T1W post-gadolinium enhanced subtraction image (c) is degraded by motion artefacts which makes it difficult to ascertain if the enhancement in the periphery of the lesion (arrow) is true enhancement in a solid component or artifactual due to respiratory motion. CEUS (d) clearly shows an enhancing renal cystic mass. Although the revised Bosniak classification currently does not apply to CEUS, presence of an enhancing protrusion within the cyst with an acute angle would classify the renal cystic mass as Bosniak IV (with a 90% chance of malignancy).

Figure 8: 57 year old female with left renal cyst. CECT (a) shows a left renal cyst without any solid component or septations (arrow). Ultrasound (b) however shows septations with thickening in its lower part (arrow). MR was performed for further characterisation as septal thickening and solid component on ultrasound is concerning for malignancy. Septations were once again identified on T2W MRI (arrow in c). However, following gadolinium administration (d) no enhancement of the solid component or septations was identified (arrow) and was thus classified as a Bosniak II cyst. Ultrasound and MRI and more sensitive than CT in identification of septations. According to the revised Bosniak classification, cysts with non-enhancing septations have been downgraded from Bosniak IIF to Bosniak II. Figure 9: 21 year old female with Tuberous sclerosis. MR was performed for right renal mass. T2W (a) image shows a right renal mass (arrow) which is hypointense on T2, which is the first step of the algorithm. The mass is intensely enhancing (arrow in b) on CM phase (b). No macroscopic or microscopic fat was identified within the mass (images not shown). Differential for a T2 hypointense but intensely enhancing mass is clear cell RCC and angiomyolipoma without visible fat. According to the algorithm, the next step is calculation of ADER (arterialdelayed enhancement ratio). It is the ratio of the CM phase signal intensity (SI) subtracted from the pre-contrast SI, divided by the delayed phase (3-min) SI subtracted from the pre-contrast SI. Axial pre-contrast T1 image (c) and 3-minute delayed post-gadolinium T1 image (d) are shown. As shown in the figures, precontrast SI (c) = 300 , CM phase SI (b) = 685, delayed phase SI (d) = 550. ADER = (685-300)/(550-300) = 1.54. An ADER of more than 1.5 is in keeping with angiomyolipoma. Biopsy and subsequent histopathology confirmed angiomyolipoma in this patient with tuberous sclerosis. Figure 10: 59 year old man with MRI for characterisation of left renal mass. The first step in the algorithm is to evaluate signal intensity on T2W image. On T2W (a) the left renal mass (arrow) is hyperintense. The second step is to evaluate the degree of enhancement on CM phase. On CM phase (B) the renal mass (arrow) is intensely enhancing. Following the algorithm, the next step is to evaluate for presence of central non-enhancing area and microscopic fat. The mass shows central non-enhancing areas (arrowhead in b). Axial T1W in‐phase (IP) (c) image shows T1 hyperintensity within the mass (arrow in c) with loss of signal (arrow in d) on the opposed‐

phase (OP) dual‐echo GRE image (d) indicating presence of microscopic fat. Presence of microscopic fat and central non-enhancing area in a T2 hyperintense renal mass which is intensely enhancing on CM phase is classified as ccLS 5 (clear cell likelihood score). ccLS 5 has the highest likelihood of the mass being a clear cell RCC. In this patient, subsequent partial nephrectomy and histopathology confirmed clear cell RCC.

References: 1.

O'Connor, S.D., et al., Incidental Finding of Renal Masses at Unenhanced CT: Prevalence and Analysis of Features for Guiding Management. American Journal of Roentgenology, 2011. 197(1): p. 139-145.

2.

Campbell, S.C., et al., Guideline for management of the clinical T1 renal mass. J Urol, 2009. 182(4): p. 1271-9.

3.

Siegel, R.L., K.D. Miller, and A. Jemal, Cancer statistics, 2019. CA Cancer J Clin, 2019. 69(1): p. 734.

4.

Heilbrun, M.E., et al., ACR Appropriateness Criteria indeterminate renal mass. J Am Coll Radiol, 2015. 12(4): p. 333-41.

5.

Krishna, S., et al., CT imaging of solid renal masses: pitfalls and solutions. Clin Radiol, 2017. 72(9): p. 708-721.

6.

Schieda, N., et al., Ten uncommon and unusual variants of renal angiomyolipoma (AML): radiologic-pathologic correlation. Clin Radiol, 2015. 70(2): p. 206-20.

7.

Jinzaki, M., et al., Renal angiomyolipoma: a radiological classification and update on recent developments in diagnosis and management. Abdom Imaging, 2014. 39(3): p. 588-604.

8.

Hakim, S.W., et al., Angiomyolipoma (AML) without visible fat: Ultrasound, CT and MR imaging features with pathological correlation. Eur Radiol, 2016. 26(2): p. 592-600.

9.

Yuh, B.I. and R.H. Cohan, Different phases of renal enhancement: role in detecting and characterizing renal masses during helical CT. AJR Am J Roentgenol, 1999. 173(3): p. 747-55.

10.

Welch, T.J. and A.J. LeRoy, Helical and electron beam CT scanning in the evaluation of renal vein involvement in patients with renal cell carcinoma. J Comput Assist Tomogr, 1997. 21(3): p. 46771.

11.

Shetty, C., et al., Dual-phase helical CT of kidney : Comparison of corticomedullary and nephrographic phases in detection and characterization of renal masses. Indian Journal of Radiology and Imaging, 2004. 14(3): p. 285-290.

12.

Birnbaum, B.A., et al., Multi-detector row CT attenuation measurements: assessment of intraand interscanner variability with an anthropomorphic body CT phantom. Radiology, 2007. 242(1): p. 109-19.

13.

Greffier, J., et al., Dose reduction with iterative reconstruction: Optimization of CT protocols in clinical practice. Diagn Interv Imaging, 2015. 96(5): p. 477-86.

14.

Silverman, S.G., J.R. Leyendecker, and E.S. Amis, Jr., What is the current role of CT urography and MR urography in the evaluation of the urinary tract? Radiology, 2009. 250(2): p. 309-23.

15.

Davenport, M.S., et al., Diagnosis of renal angiomyolipoma with hounsfield unit thresholds: effect of size of region of interest and nephrographic phase imaging. Radiology, 2011. 260(1): p. 158-65.

16.

Simpfendorfer, C., et al., Angiomyolipoma with minimal fat on MDCT: can counts of negativeattenuation pixels aid diagnosis? AJR Am J Roentgenol, 2009. 192(2): p. 438-43.

17.

Hodgdon, T., et al., Can Quantitative CT Texture Analysis be Used to Differentiate Fat-poor Renal Angiomyolipoma from Renal Cell Carcinoma on Unenhanced CT Images? Radiology, 2015. 276(3): p. 787-96.

18.

Corwin, M.T., et al., Prevalence of Solid Tumors in Incidentally Detected Homogeneous Renal Masses Measuring > 20 HU on Portal Venous Phase CT. AJR Am J Roentgenol, 2018. 211(3): p. W173-w177.

19.

Hu, E.M., et al., Expanding the Definition of a Benign Renal Cyst on Contrast-enhanced CT: Can Incidental Homogeneous Renal Masses Measuring 21-39 HU be Safely Ignored? Acad Radiol, 2018. 25(2): p. 209-212.

20.

Agochukwu, N., et al., Differentiating Renal Neoplasms From Simple Cysts on Contrast-Enhanced CT on the Basis of Attenuation and Homogeneity. AJR Am J Roentgenol, 2017. 208(4): p. 801804.

21.

Jonisch, A.I., et al., Can high-attenuation renal cysts be differentiated from renal cell carcinoma at unenhanced CT? Radiology, 2007. 243(2): p. 445-50.

22.

Israel, G.M. and M.A. Bosniak, How I do it: evaluating renal masses. Radiology, 2005. 236(2): p. 441-50.

23.

Dilauro, M., et al., Comparison of Contrast-Enhanced Multiphase Renal Protocol CT Versus MRI for Diagnosis of Papillary Renal Cell Carcinoma. AJR Am J Roentgenol, 2016. 206(2): p. 319-25.

24.

Mileto, A. and D. Marin, Dual-Energy Computed Tomography in Genitourinary Imaging. Radiol Clin North Am, 2017. 55(2): p. 373-391.

25.

Kaza, R.K., et al., Variability of CT Attenuation Measurements in Virtual Unenhanced Images Generated Using Multimaterial Decomposition from Fast Kilovoltage-switching Dual-energy CT. Acad Radiol, 2017. 24(3): p. 365-372.

26.

Maki, D.D., et al., Renal cyst pseudoenhancement: beam-hardening effects on CT numbers. Radiology, 1999. 213(2): p. 468-72.

27.

Tappouni, R., et al., Pseudoenhancement of renal cysts: influence of lesion size, lesion location, slice thickness, and number of MDCT detectors. AJR Am J Roentgenol, 2012. 198(1): p. 133-7.

28.

Mileto, A., et al., Impact of dual-energy multi-detector row CT with virtual monochromatic imaging on renal cyst pseudoenhancement: in vitro and in vivo study. Radiology, 2014. 272(3): p. 767-76.

29.

Yamada, Y., et al., Renal cyst pseudoenhancement: intraindividual comparison between virtual monochromatic spectral images and conventional polychromatic 120-kVp images obtained during the same CT examination and comparisons among images reconstructed using filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction. Medicine (Baltimore), 2015. 94(15): p. e754.

30.

Krishna, S., et al., Attenuation and Degree of Enhancement With Conventional 120-kVp Polychromatic CT and 70-keV Monochromatic Rapid Kilovoltage-Switching Dual-Energy CT in Cystic and Solid Renal Masses. AJR Am J Roentgenol, 2018. 211(4): p. 789-796.

31.

Mileto, A., et al., Dual-Energy MDCT for Imaging the Renal Mass. AJR Am J Roentgenol, 2015. 204(6): p. W640-7.

32.

Itani, M., et al., Clinical and Payer-Based Analysis of Value of Dual-Energy Computed Tomography for Workup of Incidental Abdominal Findings. J Comput Assist Tomogr, 2019. 43(4): p. 605-611.

33.

Song, K.D., et al., Utility of iodine overlay technique and virtual unenhanced images for the characterization of renal masses by dual-energy CT. AJR Am J Roentgenol, 2011. 197(6): p. W1076-82.

34.

Ascenti, G., et al., Distinguishing enhancing from nonenhancing renal masses with dual-source dual-energy CT: iodine quantification versus standard enhancement measurements. Eur Radiol, 2013. 23(8): p. 2288-95.

35.

Cha, D., et al., Evaluation of hyperdense renal lesions incidentally detected on single-phase postcontrast CT using dual-energy CT. Br J Radiol, 2016. 89(1062): p. 20150860.

36.

Chandarana, H., et al., Iodine quantification with dual-energy CT: phantom study and preliminary experience with renal masses. AJR Am J Roentgenol, 2011. 196(6): p. W693-700.

37.

Kaza, R.K., et al., Distinguishing enhancing from nonenhancing renal lesions with fast kilovoltageswitching dual-energy CT. AJR Am J Roentgenol, 2011. 197(6): p. 1375-81.

38.

Mileto, A., et al., Iodine quantification to distinguish clear cell from papillary renal cell carcinoma at dual-energy multidetector CT: a multireader diagnostic performance study. Radiology, 2014. 273(3): p. 813-20.

39.

Zarzour, J.G., et al., Quantitative iodine content threshold for discrimination of renal cell carcinomas using rapid kV-switching dual-energy CT. Abdom Radiol (NY), 2017. 42(3): p. 727734.

40.

Sadoughi, N., et al., Diagnostic Accuracy of Attenuation Difference and Iodine Concentration Thresholds at Rapid-Kilovoltage-Switching Dual-Energy CT for Detection of Enhancement in Renal Masses. AJR Am J Roentgenol, 2019: p. 1-7.

41.

Salameh, J.P., et al., Diagnostic Accuracy of Dual-Energy CT for Evaluation of Renal Masses: Systematic Review and Meta-Analysis. AJR Am J Roentgenol, 2019. 212(4): p. W100-W105.

42.

Wan, Y., et al., Gemstone spectral imaging dual-energy computed tomography for differentiation of renal cell carcinoma and minimal-fat renal angiomyolipoma. J Cancer Res Ther, 2018. 14(Supplement): p. S394-s399.

43.

Wei, J., et al., Analysis of dual energy spectral CT and pathological grading of clear cell renal cell carcinoma (ccRCC). 2018. 13(5): p. e0195699.

44.

Siddaiah, M., et al., Is Ultrasound Useful for Further Evaluation of Homogeneously Hyperattenuating Renal Lesions Detected on CT? AJR Am J Roentgenol, 2017. 209(3): p. 604-610.

45.

Zhang, F., et al., Value of Contrast-Enhanced Ultrasound in the Diagnosis of Renal Cancer and in Comparison With Contrast-Enhanced Computed Tomography: A Meta-analysis. J Ultrasound Med, 2019. 38(4): p. 903-914.

46.

Zhou, L., et al., Comparison of contrast-enhanced ultrasound with MRI in the diagnosis of complex cystic renal masses: a meta-analysis. Acta Radiol, 2018. 59(10): p. 1254-1263.

47.

Barr, R.G., C. Peterson, and A. Hindi, Evaluation of indeterminate renal masses with contrastenhanced US: a diagnostic performance study. Radiology, 2014. 271(1): p. 133-42.

48.

Harvey, C.J., et al., Role of US Contrast Agents in the Assessment of Indeterminate Solid and Cystic Lesions in Native and Transplant Kidneys. Radiographics, 2015. 35(5): p. 1419-30.

49.

Schieda, N., L. Avruch, and T.A. Flood, Small (<1 cm) incidental echogenic renal cortical nodules: chemical shift MRI outperforms CT for confirmatory diagnosis of angiomyolipoma (AML). Insights Imaging, 2014. 5(3): p. 295-9.

50.

Davarpanah, A.H., et al., Homogeneous T1 Hyperintense Renal Lesions with Smooth Borders: Is Contrast-enhanced MR Imaging Needed? Radiology, 2016. 280(1): p. 128-36.

51.

Kim, C.W., et al., Visual Assessment of the Intensity and Pattern of T1 Hyperintensity on MRI to Differentiate Hemorrhagic Renal Cysts From Renal Cell Carcinoma. AJR Am J Roentgenol, 2017. 208(2): p. 337-342.

52.

Ho, V.B., et al., Renal masses: quantitative assessment of enhancement with dynamic MR imaging. Radiology, 2002. 224(3): p. 695-700.

53.

Hecht, E.M., et al., Renal masses: quantitative analysis of enhancement with signal intensity measurements versus qualitative analysis of enhancement with image subtraction for diagnosing malignancy at MR imaging. Radiology, 2004. 232(2): p. 373-8.

54.

Johnson, D.C., et al., Preoperatively misclassified, surgically removed benign renal masses: a systematic review of surgical series and United States population level burden estimate. J Urol, 2015. 193(1): p. 30-5.

55.

Silverman, S.G., et al., Bosniak Classification of Cystic Renal Masses, Version 2019: An Update Proposal and Needs Assessment. Radiology, 2019. 292(2): p. 475-488.

56.

Bosniak, M.A., The current radiological approach to renal cysts. Radiology, 1986. 158(1): p. 1-10.

57.

Israel, G.M. and M.A. Bosniak, Calcification in cystic renal masses: is it important in diagnosis? Radiology, 2003. 226(1): p. 47-52.

58.

Egbert, N.D., et al., Differentiation of papillary renal cell carcinoma subtypes on CT and MRI. AJR Am J Roentgenol, 2013. 201(2): p. 347-55.

59.

Schoots, I.G., et al., Bosniak Classification for Complex Renal Cysts Reevaluated: A Systematic Review. J Urol, 2017. 198(1): p. 12-21.

60.

Smith, A.D., et al., Active Surveillance Versus Nephron-Sparing Surgery for a Bosniak IIF or III Renal Cyst: A Cost-Effectiveness Analysis. AJR Am J Roentgenol, 2019. 212(4): p. 830-838.

61.

Barata, P.C. and B.I. Rini, Treatment of renal cell carcinoma: Current status and future directions. CA Cancer J Clin, 2017. 67(6): p. 507-524.

62.

Frank, I., et al., Solid renal tumors: an analysis of pathological features related to tumor size. J Urol, 2003. 170(6 Pt 1): p. 2217-20.

63.

Marconi, L., et al., Systematic Review and Meta-analysis of Diagnostic Accuracy of Percutaneous Renal Tumour Biopsy. Eur Urol, 2016. 69(4): p. 660-673.

64.

Vasudevan, A., et al., Incidental renal tumours: the frequency of benign lesions and the role of preoperative core biopsy. BJU Int, 2006. 97(5): p. 946-9.

65.

Patel, R.M., et al., Pretreatment Diagnosis of the Small Renal Mass: Status of Renal Biopsy in the United States of America. J Endourol, 2018. 32(9): p. 884-890.

66.

Macklin, P.S., et al., Tumour Seeding in the Tract of Percutaneous Renal Tumour Biopsy: A Report on Seven Cases from a UK Tertiary Referral Centre. Eur Urol, 2019. 75(5): p. 861-867.

67.

Mullins, J.K. and R. Rodriguez, Renal cell carcinoma seeding of a percutaneous biopsy tract. Can Urol Assoc J, 2013. 7(3-4): p. E176-9.

68.

Patel, H.D., et al., Diagnostic Accuracy and Risks of Biopsy in the Diagnosis of a Renal Mass Suspicious for Localized Renal Cell Carcinoma: Systematic Review of the Literature. J Urol, 2016. 195(5): p. 1340-1347.

69.

Cooper, S., et al., Diagnostic Yield and Complication Rate in Percutaneous Needle Biopsy of Renal Hilar Masses With Comparison With Renal Cortical Mass Biopsies in a Cohort of 195 Patients. AJR Am J Roentgenol, 2019. 212(3): p. 570-575.

70.

Gellert, L.L., et al., The diagnostic accuracy of percutaneous renal needle core biopsy and its potential impact on the clinical management of renal cortical neoplasms. Arch Pathol Lab Med, 2014. 138(12): p. 1673-9.

71.

Williamson, S.R., et al., Diagnostic criteria for oncocytic renal neoplasms: a survey of urologic pathologists. Hum Pathol, 2017. 63: p. 149-156.

72.

Wobker, S.E. and S.R. Williamson, Modern Pathologic Diagnosis of Renal Oncocytoma. J Kidney Cancer VHL, 2017. 4(4): p. 1-12.

73.

Salmasi, A., et al., Association between renal mass biopsy and upstaging to perinephric fat involvement in a contemporary cohort of patients with clinical T1a renal cell carcinoma. Urol Oncol, 2018. 36(12): p. 527.e13-527.e19.

74.

Ball, M.W., et al., Grade heterogeneity in small renal masses: potential implications for renal mass biopsy. J Urol, 2015. 193(1): p. 36-40.

75.

Sanchez, A., A.S. Feldman, and A.A. Hakimi, Current Management of Small Renal Masses, Including Patient Selection, Renal Tumor Biopsy, Active Surveillance, and Thermal Ablation. J Clin Oncol, 2018: p. Jco2018792341.

76.

Abel, E.J., et al., Percutaneous biopsy of primary tumor in metastatic renal cell carcinoma to predict high risk pathological features: comparison with nephrectomy assessment. J Urol, 2010. 184(5): p. 1877-81.

77.

Diaz de Leon, A., et al., Role of Virtual Biopsy in the Management of Renal Masses. AJR Am J Roentgenol, 2019: p. 1-10.

78.

Kay, F.U. and I. Pedrosa, Imaging of Solid Renal Masses. Radiol Clin North Am, 2017. 55(2): p. 243-258.

79.

Sun, M.R., et al., Renal cell carcinoma: dynamic contrast-enhanced MR imaging for differentiation of tumor subtypes--correlation with pathologic findings. Radiology, 2009. 250(3): p. 793-802.

80.

Kay, F.U., et al., Diagnostic Performance and Interreader Agreement of a Standardized MR Imaging Approach in the Prediction of Small Renal Mass Histology. Radiology, 2018. 287(2): p. 543-553.

81.

Sasiwimonphan, K., et al., Small (<4 cm) Renal Mass: Differentiation of Angiomyolipoma without Visible Fat from Renal Cell Carcinoma Utilizing MR Imaging. Radiology, 2016. 280(2): p. 653.

82.

Kim, J.I., et al., Segmental enhancement inversion at biphasic multidetector CT: characteristic finding of small renal oncocytoma. Radiology, 2009. 252(2): p. 441-8.

83.

Schieda, N., M.D. McInnes, and L. Cao, Diagnostic accuracy of segmental enhancement inversion for diagnosis of renal oncocytoma at biphasic contrast enhanced CT: systematic review. Eur Radiol, 2014. 24(6): p. 1421-9.

84.

Canvasser, N.E., et al., Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging to Identify Clear Cell Renal Cell Carcinoma in cT1a Renal Masses. J Urol, 2017. 198(4): p. 780-786.

85.

Childs, D.D., et al., In-phase signal intensity loss in solid renal masses on dual-echo gradient-echo MRI: association with malignancy and pathologic classification. AJR Am J Roentgenol, 2014. 203(4): p. W421-8.

86.

Murray, C.A., et al., Evaluation of T1-Weighted MRI to Detect Intratumoral Hemorrhage Within Papillary Renal Cell Carcinoma as a Feature Differentiating From Angiomyolipoma Without Visible Fat. AJR Am J Roentgenol, 2016. 207(3): p. 585-91.

87.

Tanaka, H., et al., Diffusion-weighted magnetic resonance imaging in the differentiation of angiomyolipoma with minimal fat from clear cell renal cell carcinoma. Int J Urol, 2011. 18(10): p. 727-30.

88.

Kang, S.K., et al., DWI for Renal Mass Characterization: Systematic Review and Meta-Analysis of Diagnostic Test Performance. AJR Am J Roentgenol, 2015. 205(2): p. 317-24.

89.

Lassel, E.A., et al., Diffusion-weighted imaging of focal renal lesions: a meta-analysis. Eur Radiol, 2014. 24(1): p. 241-9.

90.

Cornelis, F., et al., Routinely performed multiparametric magnetic resonance imaging helps to differentiate common subtypes of renal tumours. Eur Radiol, 2014. 24(5): p. 1068-80.

91.

Alayed, A., et al., Diagnostic Accuracy of MRI for Detecting Inferior Vena Cava Wall Invasion in Renal Cell Carcinoma Tumor Thrombus Using Quantitative and Subjective Analysis. AJR Am J Roentgenol, 2019. 212(3): p. 562-569.

92.

Ding, J., et al., CT-based radiomic model predicts high grade of clear cell renal cell carcinoma. Eur J Radiol, 2018. 103: p. 51-56.

93.

Goyal, A., et al., Role of MR texture analysis in histological subtyping and grading of renal cell carcinoma: a preliminary study. Abdom Radiol (NY), 2019.

94.

Comperat, E. and J. Varinot, Classification of Adult Renal Tumors: An Update. Semin Ultrasound CT MR, 2017. 38(1): p. 2-9.

95.

Gaur, S., B. Turkbey, and P. Choyke, Hereditary Renal Tumor Syndromes: Update on Diagnosis and Management. Seminars in Ultrasound, CT and MRI, 2017. 38(1): p. 59-71.

96.

Ljungberg, B., et al., European Association of Urology Guidelines on Renal Cell Carcinoma: The 2019 Update. European Urology, 2019. 75(5): p. 799-810.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

PROTOCOL

RENAL MASS PROTOCOL

ORAL CONTRAST – None CONTRAST

I.V. CONTRAST – 90 –110ml

CT TECHNIQUE

Kidneys Without - 2.5mm

Without IV

NOISE INDEX 41.4

Contrast Scan

Recon thickness

kV

mA

Scan type Rotation time

12

150-450

Helical 0.8

Thickness

Scan

(mm)

mode

(mm)

1.25

0.984:1

39.37

Speed

Algorithm (mm)

2.5 AXIAL

STANDARD

2 CORONAL

0

2 SAGITTAL

CT TECHNIQUE

Kidneys ONLY - 2.5mm

With IV Contrast

CMP (Corticomedullary phase) - BOLUS TRACKING - 15 sec from 100 HU 3.2 ml/sec NOISE INDEX 41.4 Scan

Recon thickness

kV

mA

Scan type Rotation time

Thickness

Scan

(mm)

mode

Speed

Algorithm (mm)

(mm)

12

150-450

HELCIAL 0.8

1.25

0.984:1

39.37

2.5 AXIAL

STANDARD

2 CORONAL

0

2 SAGITTAL

Nephrographic Phase - Abdomen - 2.5mm BOLUS TRACKING- 80 sec from 100 HU Pelvis 2.5mm (if chosen by Radiologist) Scan

Recon thickness

kV

mA

Scan type Rotation time

Thickness

Scan

(mm)

mode

(mm)

1.25

0.984:1

39.37

Speed

Algorithm (mm)

ABDOMEN 12 0

150-450

HELCIAL 0.8

2.5 AXIAL

STANDARD

2 CORONAL 2 SAGITTAL

COMMENT

**Use same kV, mA, rotation speed, pitch, and noise index for W/O, CMP and NP phases. This is so reliable attenuation enhancement assessment can be made

CLINICAL

RENAL LESIONS (RCC, BOSNIAK CLASSIFICATION) Pre or Post RFA Kidney

INDICATION

PROTOCOL

RENAL MASS PROTOCOL WITH DECT

ORAL CONTRAST – None

CONTRAST I.V. CONTRAST – 90 –110ml

CT TECHNIQUE Without IV

Kidneys Without - 2.5mm

Contrast Scan

Recon thickness

kV

mA

Scan type Rotation time

120

300

Helical .6

Thickness

Scan

(mm)

mode

(mm)

1.25

0.984:1

39.37

Speed

Algorithm (mm)

2.5 AXIAL 2 CORONAL 2 SAGITTAL

STANDARD

CT TECHNQUE

Kidneys ONLY - 2.5mm

With IV Contrast

CMP (Corticomedullary phase) - BOLUS TRACKING -15 sec from 100 HU 3.2 ml/sec 70 keV monochromatic images, 2.5 mm iodine (water) maps

Scan

Recon thickness

kV

CTDI

Scan type Rotation time

GSI

GSI 1

(Gemstone

17.49

HELCIAL .5

Thickness

Scan

(mm)

mode

(mm)

1.25

0.984:1

39.37

Speed

Algorithm (mm)

2.5 AXIAL

STANDARD

2 CORONAL

Spectral

2 SAGITTAL

Imaging)

Nephrographic Phase-Abdomen - 2.5mm BOLUS TRACKING- 80 sec from 100 HU Pelvis 2.5mm(if chosen by Radiologist) Scan

Recon

Algorithm

thickness kV

mA

Scan type Rotation time

ABDOMEN

120

300

HELCIAL .6

Thickness

Scan

Speed

(mm)

mode

(mm)

1.25

0.984:1

39.37

(mm)

2.5 AXIAL

STANDARD

2 CORONAL 2 SAGITTAL

COMMENT

** Fixed mA and kV for NC and Nephrographic phase, GSI on CM phase Values may need to be adjusted according to pt size but always use same mA and kV for NC and Nephrographic phase.

Table 2: Sample Renal mass protocol using Dual energy CT in Corticomedullary phase

IMAGING SEQUENCE

TR

T

Fli

F

Slic

N

Voxel

Base

Fat

Paral Rece

(ms)

E

p

O

e

o.

Size

Reso Supp

lel

(

A

V

Thic

of

(mm)

lutio

ressi

Acqu Ban

m ng (

kne

Sli

n

on

isitio

dwid

s)

iver

le

m

ss

ce

n

th

(o)

m

(m

s

Tech

(Hz/

)

m)

niqu

pixel

e

)

Unenhanced Coronal T2-weighted

100

HASTE

0

181

15 40 5.0 0

40

0

1.6 x

320

None

2

460

320

SPAI

2

460

2

390,

1.3 x 5.0

Axial T2-weighted

791

HASTE/BLADE

0

92

15 34 6.0 0

30

0

1.1 x 1.1 x

R

6.0 Axial T1-weighted in-

174

and opposed-phase

2.2, 4.5

70 30 5.0

40

0

256

none

1.2 x

G RE DWI

1.3 x

400

5.0 530

68

0

90 38 6.0

30

0

2.5 x

192

2.0 x

SPAI

2

1628

Off

490

3

490

R

6.0 Axial T1-weighted 3D

3.2

GRE VIBE

9

1.2

12 33 5.0

44

0

2.1 x

256

1.3 x

SPAI R

5.0 Coronal T1-weighted

3.4

3D GRE VIBE

8

1.22

12 40 5.0 0

48

2.1 x 1.3 x 5.0

320

SPAI R

Contrast-enhanced Coronal T1-wei ghted

3.4

3D GRE VIBE

8

1.22

12 40 5.0

48

0

2.1 x

320

1.3 x

SPAI

3

490

Off

490

R

5.0 Axial T1-weighted 3D

3.2

GRE VIBE

9

1.2

12 33 5.0 0

44

2.1 x 1.3 x

256

SPAI R

5.0

FOOTNOTE: BLADE = proprietary variant of the PROPELLER sequence adapted by Siemens

Healthcare, GRE = gradient-recalled echo, VIBE = volumetric interpolated breath-hold, SPAIR = spectral attenuated inversion recovery. Table 3: Sample Renal MR protocol for 1.5 Tesla

*The Bosniak classification is intended for cystic renal masses after infectious, inflammatory, or vascular etiologies and necrotic solid masses are excluded. If a cystic mass has features described in more than one Bosniak class, the highest Bosniak class is assigned. In rare cases, a mass may have an unusual combination of features (undefined, not fitting a specific Bosniak class) that may warrant inclusion into Bosniak IIF. Other than for the diagnosis of Bosniak I simple cysts, the role of US with or without contrast material in assigning a Bosniak class is uncertain. †

Renal masses that at CT have abundant thick or nodular calcifications; are hyperattenuating,

homogeneous, nonenhancing, and larger than 3 cm; or are heterogeneous (including but not limited to many [four or more] nonenhancing septa or 3-mm or larger nonenhancing septa or wall) might best be visualized at MRI prior to the assignment of a Bosniak class to determine if there are occult enhancing elements that might affect classification.

Table 4: Proposed Update to the Bosniak Classification of Cystic Renal Masses (Reproduced with permission from Radiology from Silverman, S.G., et al., Bosniak Classification of Cystic Renal

Masses, Version 2019: An Update Proposal and Needs Assessment. Radiology, 2019. 292(2): p. 475-488.)

Table 5: Flowchart shows algorithm for characterization of solid renal masses by using imaging features on MRI and assigning clear cell likelihood score (ccLS)

ccLS is Likert score that conveys likelihood of clear cell renal cell carcinoma (ccRCC) and is defined as follows: 1, very unlikely; 2, unlikely; 3, equivocal; 4, likely; and 5, highly likely. First step in algorithm is to assess signal intensity of renal mass on T2-weighted images and determine whether mass is hyper-, iso-, or hypointense relative to renal cortex. Masses are then subdivided by degree of enhancement during corticomedullary phase imaging: intense, moderate, or mild. Additional features (e.g., presence of microscopic fat, segmental enhancement inversion [SEI], appearance on DWI) are then used to ultimately assign ccLS value. ADER = arterial-delayed enhancement ratio, AML = angiomyolipoma, AMLrare = angiomyolipoma (rare presentation), pRCC = papillary renal cell carcinoma, Onco = oncocytoma, chrRCC = chromophobe renal cell carcinoma, SIart = signal intensity on arterial phase images, SIpre = signal intensity on unenhanced images, SIdel = signal intensity on delayed phase images (illustration by Moore E).

(Adapted from Radiologic Clinics of North America, Vol. 55, Kay FU, Pedrosa I. “Imaging of Solid Renal Masses,” Pages 243–258, Copyright 2018 with permission from Elsevier)

Primary tumors (T) TX

Primary tumor cannot be assessed

T0

No evidence of primary tumor

T1

T1a

T1b

T2

T2a T2b

Tumor ≤7 cm in greatest dimension, limited to the kidney Tumor ≤4 cm in greatest dimension, limited to the kidney Tumor >4 cm but ≤7 cm in greatest dimension, limited to the kidney Tumor >7 cm in greatest dimension, limited to the kidney Tumor >7 cm but ≤10 cm in greatest dimension, limited to the kidney Tumor >10 cm, limited to the kidney Tumor extends into major veins or

T3

perinephric tissues but not into the ipsilateral adrenal gland and not beyond the Gerota fascia Tumor grossly extends into the renal vein or its segmental (muscle-containing)

T3a

branches, or tumor invades perirenal and/or renal sinus fat but not beyond the Gerota fascia

T3b

Tumor grossly extends into the vena cava below the diaphragm Tumor grossly extends into the vena

T3c

cava above the diaphragm or invades the wall of the vena cava

Tumor invades beyond the Gerota T4

fascia (including contiguous extension into the ipsilateral adrenal gland)

Regional lymph node (N) NX

Regional lymph nodes cannot be assessed

N0

No regional lymph node metastasis

N1

Metastasis in regional lymph node(s)

Distant metastasis (M) M0

No distant metastasis

M1

Distant metastasis

Table 6: TNM staging of renal cell carcinoma – 8th edition of American Joint Committee on Cancer (AJCC) from (Amin, M.B., Edge, S.B., Greene, F.L. et al, AJCC Cancer Staging Manual. ed. 8. Springer, Cham, Switzerland; 2017)