The RENAL Score in Partial Nephrectomy Planning

What the RENAL Score is

The RENAL nephrometry score is a standardized classification system introduced in 2009 by Kutikov and Uzzo at the Fox Chase Cancer Center (Temple University, Philadelphia) to describe the anatomical complexity of a renal mass. Published in the Journal of Urology, it quickly became the reference tool in partial nephrectomy planning.

The goal of the RENAL score is to translate the tumor's anatomical features — assessed on CT or MR images — into an objective numerical score that facilitates communication among surgeons, radiologists, and pathologists and helps stratify surgical risk.

The acronym R.E.N.A.L. corresponds to five anatomical parameters, each evaluated on preoperative imaging.

The five parameters in detail

R — Radius

The maximum size of the tumor mass, measured at its largest diameter:

• 1 point: ≤ 4 cm
• 2 points: > 4 cm and < 7 cm
• 3 points: ≥ 7 cm

Radius is the simplest parameter to measure and the least subject to inter-observer variability. However, a small mass can be technically more complex than a large one if it is endophytic or in a hilar location.

E — Exophytic/Endophytic

The percentage of the mass protruding beyond the renal profile:

• 1 point: ≥ 50% exophytic (the tumor protrudes from the kidney)
• 2 points: < 50% exophytic
• 3 points: entirely endophytic (the tumor lies completely within the parenchyma)

This parameter has a direct impact on surgical technique: an exophytic tumor is more easily enucleable, while an endophytic tumor requires a deeper resection with a greater risk of opening the collecting system.

The 2D evaluation problem: on a single axial CT slice, the exophytic percentage can easily be over- or under-estimated. Inter-observer variability for the E parameter is among the highest in the RENAL score.

N — Nearness (to the collecting system)

Distance of the mass from the collecting system or renal sinus:

• 1 point: ≥ 7 mm
• 2 points: > 4 mm and < 7 mm
• 3 points: ≤ 4 mm

Proximity to the collecting system predicts the risk of postoperative urinary complications (fistulas, urinomas). Tumors with N = 3 require suturing of the excretory apparatus during renal reconstruction.

The 2D evaluation problem: distance must be measured at the closest point, which may lie on a different plane from the one being viewed. Multi-planar analysis is essential but increases the time and complexity of evaluation.

A — Anterior/Posterior

The position of the mass relative to the kidney's coronal plane:

• a: anterior
• p: posterior
• x: cannot be determined (median or hilar mass)

The A descriptor influences the choice of surgical approach: transperitoneal for anterior tumors, retroperitoneal for posterior tumors. It does not contribute to the total numerical score but is essential for operative planning.

L — Location (relative to polar lines)

The position of the mass relative to the kidney's polar lines (the imaginary lines that delimit the upper and lower poles):

• 1 point: entirely above or below the polar line (upper or lower pole)
• 2 points: the mass crosses the polar line
• 3 points: > 50% of the mass crosses the polar line, or it lies entirely between the polar lines (mesorenal)

Mesorenal tumors (L = 3) are typically closer to the vascular hilum and the collecting system, making the procedure more complex.

Suffix h — Hilar contact

To these five parameters is added the suffix h if the mass is in contact with the main hilar vessel (renal artery or vein). The h suffix does not modify the numerical score but signals a significant additional vascular risk.

How to interpret the score

The total score is obtained by summing R + E + N + L (the A parameter is a position descriptor and does not contribute to the total):

| Score | Complexity | Surgical indication | | ----- | ---------- | ----------------------------------------------------- | | 4-6 | Low | Partial nephrectomy generally favored | | 7-9 | Moderate | Partial nephrectomy possible but more demanding | | 10-12 | High | Complex partial nephrectomy; weigh risks vs. benefits |

A low RENAL score does not guarantee a simple procedure (the h suffix or unexpected vascular variants can complicate the picture), and a high score does not necessarily imply that partial nephrectomy is contraindicated. The RENAL score is a stratification tool, not a decision tool.

The problem: inter-observer variability

One of the recognized limitations of the RENAL score is inter-observer variability when assessment is performed on two-dimensional CT images.

Published studies have analyzed agreement between different observers for each parameter:

| Parameter | Inter-observer agreement | | ---------------------- | ---------------------------------- | | R (Radius) | ~94% — high, objective measurement | | E (Exophytic) | ~76% — moderate | | N (Nearness) | ~66% — low | | A (Anterior/Posterior) | ~80% — good | | L (Polar lines) | ~54% — the lowest |

The L parameter (location relative to polar lines) shows the lowest agreement because polar lines are not visible anatomical structures — they are imaginary lines that the observer must mentally trace. On axial CT slices, identifying the position of a mass relative to these lines requires three-dimensional mental reconstruction.

The overall intraclass correlation coefficient (ICC) for the RENAL score has been reported as 0.660 in comparative studies — a value that indicates moderate but not optimal agreement for a tool intended to provide a standardized common language.

The role of 3D models in RENAL score calculation

Traditional RENAL score evaluation is performed on two-dimensional CT images, with all the variability limits described above. 3D models address this problem by transforming a process of mental reconstruction into one of direct visual exploration.

A specific study on the topic compared the RENAL score calculated on traditional 2D images (RENAL-2D) with that calculated on virtual 3D reconstructions (RENAL-3D), highlighting significant findings:

• Inter-observer agreement: rs = 0.85 with 3D models versus rs = 0.65 with 2D imaging
• Predictive accuracy: RENAL-3D showed a significantly better correlation with postoperative complications than RENAL-2D
• Evaluation time: assessment with 3D models proved faster thanks to the immediate visualization of spatial relationships

The parameters that benefit most from 3D visualization are precisely those with the greatest variability in 2D:

• The exophytic percentage (E) is immediately appreciable by rotating the model and observing the mass from different angles
• The distance from the collecting system (N) is measurable directly in three-dimensional space, without having to correlate sections on different planes
• The position relative to polar lines (L) is evident from the coronal view of the model, where the renal profile and the mass are visible simultaneously
• The relationship with hilar vessels (h suffix) is appreciated by toggling anatomical layers (arteries, veins) on and off and adjusting parenchymal opacity

A practical example

Consider a real case from our series with a RENAL score of 7 (2-1-1-p-3-h):

• R = 2: mass between 4 and 7 cm
• E = 1: predominantly exophytic (> 50%)
• N = 1: far from the collecting system (≥ 7 mm)
• A = p: posterior position
• L = 3: mesorenal mass (crosses or lies between polar lines)
• h: contact with the hilar vessel

Despite an overall score of moderate complexity (7), the h suffix signals a critical element: proximity to the hilar vessels. On a conventional CT scan, confidently determining the h suffix requires careful multi-planar analysis and solid experience in reading vascular images.

With a 3D model, the surgeon can:

1. Make the renal arteries visible and adjust parenchymal opacity
2. Rotate the model to visualize the course of segmental vessels
3. Verify whether the tumor is actually in contact with a main arterial or venous branch
4. Plan the selective clamping strategy based on the vascular territories involved

This evaluation, which on 2D images requires experience and time, becomes immediate and shareable with the three-dimensional model.

Beyond RENAL: other scoring systems

RENAL is not the only system for classifying renal mass complexity. Other systems used in clinical practice include:

• PADUA score: an alternative system developed at the University of Padua, with partially overlapping parameters
• C-Index: measures the distance of the center of the mass from the center of the kidney
• ABC score (Arterial Based Complexity): a more recent system that integrates arterial anatomy into the complexity assessment

Each of these systems benefits similarly from 3D-model evaluation versus 2D imaging, with documented improvements in inter-observer agreement and predictive capability.

Conclusions

The RENAL score remains a fundamental tool for communication among specialists and for surgical risk stratification in partial nephrectomy. However, its application on two-dimensional CT images introduces a non-negligible inter-observer variability, especially for the E, N, and L parameters.

3D models do not replace the RENAL score — they make it more accurate, reproducible, and faster to calculate, reducing inter-operator variability and improving correlation with surgical outcomes. For the surgeon, this means more reliable preoperative information. For the patient, more precise planning.

References

1. Kutikov A, Uzzo RG. The R.E.N.A.L. nephrometry score: a comprehensive standardized system for quantitating renal tumor size, location and depth. J Urol. 2009 Sep;182(3):844-853. DOI: 10.1016/j.juro.2009.05.035 — PubMed

2. Bianchi L, et al. Improving Accuracy, Reliability, and Efficiency of the RENAL Nephrometry Score With 3D Reconstructed Virtual Imaging. Clin Genitourin Cancer. 2022. PubMed

3. Porpiglia F, et al. Three-dimensional virtual imaging of renal tumours: a new tool to improve the accuracy of nephrometry scores. BJU Int. 2019. PubMed

4. Spaliviero M, et al. Interobserver variability of R.E.N.A.L., PADUA, and centrality index nephrometry score systems. World J Urol. 2015. PubMed

5. Amparore D, et al. Interpreting nephrometry scores with three-dimensional virtual modelling for better planning of robotic partial nephrectomy and predicting complications. Minerva Urol Nephrol. 2022. PubMed