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    RENAL Nephrometry Score

    Categorizes renal masses by complexity for surgical decision-making.
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    INSTRUCTIONS

    Use cross-sectional imaging (CT or MRI, not ultrasound).

    When to Use
    Pearls/Pitfalls
    Why Use

    Patients with renal mass on cross-sectional imaging (CT or MRI).

    The RENAL Nephrometry Score was developed as a standardized system to objectify reporting of critical anatomical features of a renal mass.  

    • Provides a quantifiable and reproducible method to classify renal masses according to anatomic complexity.
    • Stratifies masses into low, medium, and high complexity, with increasing complexity correlating with more aggressive tumor biology, more challenging resectability via nephron sparing surgery, and clinical outcomes.
    • Can be used in preoperative evaluation, planning, and standardized literature reporting.
    • Does not engender specific management strategies.
    • Does not preclude the need to view imaging directly in surgical planning and prior to operation.

    Tips on assessing individual variables: 

    • R: Assess coronal and sagittal views, not just axial.
    • E: Not all masses are symmetrical. Use the most predominant feature in any axis. Measure from where normal parenchymal edge should be if no tumor were present (masses often distort normal renal parenchymal contour). Compare distance from normal parenchymal edge location to most endophytic and most exophytic portions of the tumor.
    • N: Measure from deepest portion of the tumor (in any plane) to renal sinus or collecting system.
    • A: Assess in axial view. Draw a line paralleling renal hilar structures bisecting the kidney (see Facts & Figures). Assign A if primarily anterior to line, P if primarily posterior. Assign X if mass on tip of poles or otherwise cannot be assigned A or P designation. Apply as suffix (e.g. 10-A).
    • L: Assess in axial view. Polar lines are defined as plane above or below which the medial lip of parenchyma intersects renal sinus fat, vessels, or collecting system (see Facts & Figures). Renal axial midline is the point halfway between polar lines.
    • H: Apply as suffix (e.g. 10-A-H).
    • Standardizes reporting of renal tumor size, depth, and location.
    • Informs surgical decision-making and effectively compares masses in practice and in the literature.
    • Allows for accurate communication regarding complexity of masses (e.g. when consulting with specialists before images are sent).
    • Validated to predict likelihood of surgical complications, perioperative clinical outcomes, high grade pathology, and case selection (partial versus radical nephrectomy)—see Management for details.
    • The most consistently used and extensively validated score in the urologic literature.
    Content Contributors
    • Andrew G. McIntosh, MD

    Result:

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    Next Steps
    Evidence
    Creator Insights

    Advice

    Consider competing risks of morbidity and mortality, oncologic prognosis, and patient preference to inform decision-making and to risk-stratify management strategies.

    Management

    Management of small renal masses:

    • Management strategies typically include:
      1. Surgical intervention.
        • Partial nephrectomy (PN).
          • Minimally invasive surgery (MIS) vs. open surgery.
        • Radical nephrectomy (RN).
          • MIS vs. open.
      2. Ablative intervention.
        • Cryoablation.
        • Radiofrequency ablation.
      3. Active surveillance (structured expectant management)
    • Impact of RENAL score on surgical decision-making:
      1. PN vs. RN: Higher complexity score more likely to undergo RN.
      2. MIS vs. open: High complexity scores more likely to undergo open surgical approaches.
      3. Active surveillance vs. intervention: High complexity score more likely to undergo surgical intervention.

    Critical Actions

    Not to be used with ultrasound imaging—requires cross-sectional imaging (i.e., CT or MRI).

    Formula

     

    Addition of selected points, plus suffixes as applicable:

     

    1 point

    2 points

    3 points

    Radius

    Measure largest cross-sectional (MRI/CT) diameter in any single plane.

    ≤4 cm

    >4 cm and <7 cm

    ≥7 cm

    Exophytic/endophytic

    Assess % mass exophytic (protruding out from renal parenchyma) vs. endophytic (contained within renal parenchyma).

    ≥50% exophytic

    <50% exophytic

    Entirely endophytic

    Nearness to renal sinus or collecting system

    Measure shortest distance.

    ≤4 mm

    >4 mm and <7 mm

    ≥7 mm

    Anterior vs. posterior

    Suffix applied for primary location of tumor relative to coronal plane at level of hilar vessels.

    (add suffix)

    A: Anterior to hilar vessels

    (add suffix)

    P: Posterior to hilar vessels

    (add suffix)

    X: Neither

    Polar lines

    Determine location of tumor relative to polar lines (see figure for details)

    Entirely above or below polar lines

    Crosses a polar line

    >50% diameter across polar line, contained entirely within polar lines, or crosses renal axial midline

    Hilar tumor

    (add suffix)

    H: If touching renal artery or vein

       

    Facts & Figures

    RENAL Nephrometry Score

    Complexity

    Complication Rate*

    4–6

    Low

    6.4%

    7–9

    Intermediate

    11.1%

    10–12

    High

    21.9%

    *Major complications as defined by Clavien-Dindo classification 3–5 (requiring intervention, requiring ICU admission, or death), from Simhan 2011.

    RENAL Nephrometry: Coronal CT images for "L" scoring

    Figure 1. Scoring of L component. Polar lines (solid lines) and axial renal midline (broken line) are depicted on each sagittal view of kidney. Numbers 1 to 3 represent points attributed to each category of tumor.

    RENAL Nephrometry: CT images for "E" scoring

    Figure 2. Scoring of E component. Broken line demonstrates how expected renal contour is estimated.

    RENAL Nephrometry: CT images for "L" scoring

    Figure 3. A, scoring of L component, determined in relation to upper or lower polar line. B, polar lines defined as portion of kidney where concentric rim of renal parenchyma is interrupted by renal hilar vessels, pelvis or fat on axial imaging. Axial cut is shown between polar lines, and medial renal parenchyma is interrupted by sinus fat and renal vessels. Line drawn over right kidney divides kidney into anterior and posterior components. C, axial cut is shown below lower polar line and concentric rim of renal parenchyma in both kidneys surrounds sinus fat. Line drawn to divide kidney for anterior and posterior designations.

    Figures from Kutikov 2009.

    Evidence Appraisal

    The RENAL Nephrometry Score was initially introduced in 2009 by Kutikov et al to quantify the characteristics of renal masses on cross-sectional imaging. It was applied to 50 consecutive masses resected at Fox Chase Cancer Center and accurately classified their complexity in a reproducible, standardized fashion. It was introduced to allow standardized reporting of renal masses, assist with objective discussions of risks with patients, and contribute to decision making.

    RENAL Nephrometry has since been validated in dozens of peer-reviewed publications to objectify and predict complications, predict pathology, assist with case selection of patients to operative pathways, and predict various other clinical perioperative outcomes.

    Specifically, RENAL Nephrometry has been found to stratify increasing complication rates after partial nephrectomy as score increases (6.4% vs. 11.1% vs. 21.9%) (Simhan 2011). Further, Rosevear et al found that RENAL Scores were higher among patients who underwent partial nephrectomy who developed complications than those who did not develop complications (6.9 vs. 6.0, p=0.02).

    Several studies have validated RENAL Nephrometry as useful in case selection and triage of patients into various management modalities.  Canter at al (2011) evaluated the relationship between RENAL Scores and treatment approach, noting that patients with higher scores were more likely to undergo radical nephrectomy and open partial nephrectomy (p <0.0001) as opposed to minimally invasive partial nephrectomy.  Patients with lower (anatomically “simple”) scores have also been found to be more likely to enter active surveillance protocols than those with higher scores (Tomaszewski 2014).

    The RENAL Nephrometry Score has also been validated in predicting high grade pathology as part of a preoperative nomogram (Kutikov 2011).  This nomogram was further validated to show that higher complexity tumors are more likely to exhibit high grade pathology (Wang 2012), and increasingly likely to be upstaged from cT1 to pT3a postoperatively (Gorin 2013).

    Literature

    Validation

    Research PaperCanter D, Kutikov A, Manley B, et al. Utility of the R.E.N.A.L.-Nephrometry Scoring System in Objectifying Treatment Decision-Making of the Enhancing Renal Mass Urology. 2011;78(5):1089-1094. doi:10.1016/j.urology.2011.04.035.Research PaperSimhan J, Smaldone MC, Tsai KJ, et al. Objective measures of renal mass anatomic complexity predict rates of major complications following partial nephrectomy. Eur Urol. 2011;60(4):724-30.Research PaperRosevear HM, Gellhaus PT, Lightfoot AJ, Kresowik TP, Joudi FN, Tracy CR. Utility of the RENAL nephrometry scoring system in the real world: predicting surgeon operative preference and complication risk. BJU Int. 2012;109(5):700-5.Research PaperKutikov A, Smaldone MC, Egleston BL, et al. Anatomic features of enhancing renal masses predict malignant and high-grade pathology: a preoperative nomogram using the RENAL Nephrometry score. Eur Urol. 2011;60(2):241-8.Research PaperWang HK, Zhu Y, Yao XD, et al. External validation of a nomogram using RENAL nephrometry score to predict high grade renal cell carcinoma. J Urol. 2012;187(5):1555-60.Research PaperGorin MA, Ball MW, Pierorazio PM, et al. Outcomes and predictors of clinical T1 to pathological T3a tumor up-staging after robotic partial nephrectomy: a multi-institutional analysis. J Urol. 2013;190(5):1907-11.
    Dr. Alexander Kutikov

    From the Creator

    (transcribed from telephone interview)

    Why did you develop the RENAL Nephrometry Score? Was there a clinical experience or a patient encounter that inspired you to create it?
    There was a lot of literature comparing series of nephron-sparing surgeries from different institutions, and complication rates and surgeon experience varied. It became obvious that what somebody considered a tumor amenable to partial nephrectomy at one institution might be considered unresectable via nephron-sparing surgery at another institution. There was no meaningful way to compare series or standardize reporting, so Rob Uzzo and I sat down (I was a fellow at the time) and created this score that we thought would be a simple and effective way of standardizing reporting in the literature. It really got a lot of traction quite quickly.

    How does the RENAL Nephrometry Score compare to other similar grading systems such as PADUA and C-Index?
    The PADUA score came out around the same time, about a few months later, and those investigators wrote that they had been working on a similar system, and they saw ours and decided to publish theirs. They’re very, very similar; it’s hard to know if one is superior because they’re almost identical.

    The C-Index is from the Cleveland Clinic and is meant to quantify anatomic complexities in a slightly different way. Again, it’s hard to say whether it’s better or worse, but what we tried to do is make a very simple score. I think it has the most references out there of any other anatomic grading system, and I think the simplicity of it is what really caught on.

    The tools that you have on your website, where you’ve operationalized them to be used at the point of care, are very important. We’ve done a little bit of that at Fox Chase Cancer Center with cancernomograms.com as well. It helps to objectify some of the decision-making instead of only using clinical gestalt. You can use these predictive models as a sort of jumping-off point for some hard decisions.

    The important thing to know in interpreting these tools is that none of them have perfect predictive ability. A lot of them are in the 70th percentile or lower. 50th percentile is a coin flip, so being halfway between a coin flip and a perfect prediction is still not something that you can completely rely on in a clinical setting. Again, the number you get is a jumping-off point. At an extreme, it’s very useful. Obviously when they’re not externally validated, they have to be used with caution, and a lot of times you’ll see a patient who is very different from the patients used to derive the predictive model, so I think all those little nuances are really important in these models.

    Do you know of any cases where the RENAL Nephrometry Score has been misused or misapplied?
    You know, I think most clinicians realize that these are just a general guide. There are some patients that ask, “What are my chances?” These are useful to show them what we do know and what the predictive abilities are, but they’re not perfect, and in the absence of a perfect predictive model, you still have to rely on clinical judgment and mutual decision-making. It’s important to make the patient an active participant in their care, and to understand that there’s some uncertainty involved. Communication is important, so whatever path they choose, they should understand that there are potential pitfalls on that path.

    There’s a nomogram you developed that incorporates the score and predicts the likelihood of high-grade malignancy. How do you use that clinically?
    The score was meant to be a standardized descriptor of these masses, and to communicate the relationship of the tumor to the rest of the kidney, we and other groups explored what other information the score communicates. One thing that has been described in the past is that the deeper the tumor is, the more central it is, the closer to the collecting system it is, and the more likely it is to be high grade. We created that nomogram to harness the anatomic complexity score (the RENAL Nephrometry Score), to see its predictive ability in predicting a high grade tumor.

    It’s not perfect, and you can question whether it’s clinically always important, but it does have significant predictive ability in differentiating high grade and low grade tumors. The closer it is to the business end of renal structures, the more likely it is to be aggressive. Sometimes you can hang some important clinical decisions on that.

    It must be useful to have that number to tell the patient.
    There’s another paper from our group showing that the higher the complexity of the tumor, the higher the complication rate. That really plays a role in clinical practice when you see a high-complexity tumor. Especially in an elderly frail patient who may not be able to tolerate any sort of complication—you can choose a radical nephrectomy, which is a simpler operation, where you don’t expose the patient to these higher complication rates. And especially for patients who have a normal contralateral kidney, the decision to do a radical versus a partial nephrectomy is really painted by the anatomic complexity and the score, the function of the contralateral kidney, and the frailty of the patient. It seems obvious, but when you put numbers on it, it sort of drives the point home. The more complex the mass, the higher complication rate, and you can use that in making decisions.

    It seems like the score has a few different potential uses: a reporting system like BIRADS, an evidence-based aid for shared decisionmaking, a component of research protocols like RECIST, a tool for surgical planning. What do you think are the most useful applications of the score?

    It depends on your practice and what kind of patients you’re selecting for, what kind of surgery and complications, but it’s the common denominator. It really normalizes all the other data to understand beyond what’s happening in one’s practice, and that’s number one. In reality, when I look at a tumor, my review of the films tells me everything I need to know. But when I’m on the phone with a referring physician and I don’t see the images but they tell me the Nephrometry Score, that gives me a lot of information. It’s really first and foremost a communication tool. It’s hard to say I go by the numbers every time. One has to realize that especially with the Nephrometry sum, it only communicates a certain amount of information, because you can have a score of 7 several different ways, and the complexity of various 7s is very different. But each component tells you a part of the story. Not as much as the imaging does, but it can tell you what the tumor is doing, how it’s sitting on the kidney, and where it sits in relation to other structures. So especially with a good data set, it helps to be able to quantitate this.

    About the Creator

    Alexander Kutikov, MD, is an attending surgeon and professor of urologic oncology at Fox Chase Cancer Center in Philadelphia. He is an active investigator in kidney, prostate, bladder, and adrenal disease. Dr. Kutikov is a co-founder of VisibleHealth, Inc., a digital health company with flagship products that include the app suite drawMD and Ureteral/Endoscopic Stent Trackers.

    To view Dr. Alexander Kutikov's publications, visit PubMed

    Dr. Robert Uzzo

    About the Creator

    Robert Uzzo, MD, is chair of surgical oncology at Fox Chase Cancer Center in Philadephia and professor of surgery at Temple University Health System. His clinical interests include minimally invasive urological oncology and renal malignancies. Dr. Uzzo has has authored over 300 peer-reviewed articles and chapters that have been cited over 3,500 times.

    To view Dr. Robert Uzzo's publications, visit PubMed

    Content Contributors
    • Andrew G. McIntosh, MD