Three‐dimensional virtual imaging of renal tumours: a new tool to improve the accuracy of nephrometry scores

Abstract

ObjectivesTo apply the standard PADUA and RENAL nephrometry score variables to three-dimensional (3D) virtual models (VMs) produced from standard bi-dimensional imaging, thereby creating three-dimensional (3D)-based (PADUA and RENAL) nephrometry scores/categories for the reclassification of the surgical complexity of renal masses, and to compare the new 3D nephrometry score/category with the standard 2D-based nephrometry score/category, in order to evaluate their predictive role for postoperative complications. Materials and MethodsAll patients with localized renal tumours scheduled for minimally invasive partial nephrectomy (PN) between September 2016 and September 2018 underwent 3D and 2D nephrometry score/category assessments preoperatively. After nephrometry score/category evaluation, all the patients underwent surgery. Chi-squared tests were used to evaluate the individual patients' grouping on the basis of the imaging tool (3D VMs and 2D imaging) used to assess the nephrometry score/category, while Cohen's j coefficient was used to test the concordance between classifications. Receiver-operating characteristic curves were produced to evaluate the sensitivity and specificity of the 3D nephrometry score/category vs the 2D nephrometry score/ category in predicting the occurrence of postoperative complications. A general linear model was used to perform multivariable analyses to identify predictors of overall and major postoperative complications. ConclusionsIn the present study, we showed that 3D VMs were more precise than 2D standard imaging in evaluating the surgical complexity of renal masses according to nephrometry score/ category. This was attributable to a better perception of tumour depth and its relationships with intrarenal structures using the 3D VM, as confirmed by the higher accuracy of the 3D VM in predicting postoperative complications.Additional Supporting Information may be found in the online version of this article: Table S1. Multivariable analysis identifying the preoperative independent predictors of overall complication and major complications for PADUA and RENAL score. 954

Three‐dimensional virtual reconstruction with DocDo, a novel interactive tool to score renal mass complexity

“…Our analysis confirmed the finding of Porpiglia et al [1] that the lowest level of agreement between the 2D and the 3D scores was between the variables related to the protrusion of the mass and its relationship with the hilum (Fig. 1B); thus, the 3D scoring system may potentially provide more of an advantage when assessing these features; a prospective comparative study is currently ongoing, as are technological improvements such as the inclusion of a ruler within the tool.…”

“…Preoperative knowledge of the complexity of a renal mass is the cornerstone for planning a partial nephrectomy (PN) [1]. Given the multiple variables characterizing it – size, length of protrusion from renal parenchyma, longitudinal and coronal location, proximity to the hilum – several nephrometric scoring systems have been proposed during the last decade [2,3]; the RENAL and PADUA classifications are the most widely used of these [4‐6].…”

“…Such systems are based, however, on conventional two‐dimensional (2D) imaging rendered as greyscale, which requires a type of cognitive three‐dimensional (3D) reconstruction of a complex structure such as the kidney. Porpiglia et al [1] address this issue by scoring PADUA and RENAL systems with 3D virtual models developed by MEDICS. As expected, 3D nephrometric scoring performed better than the conventional 2D‐based method in predicting postoperative complications.…”

“…As stated by Porpiglia et al [1], a novel era is about to begin with the use of 3D imaging reconstruction; with growing evidence favouring a conservative approach, and attempts to expand indications for PN and to select increasingly tricky cases, 3D models may overcome the complexity associated with 2D evaluation and standardize surgical reporting overall [7].…”

Will three‐dimensional models change the way nephrometric scoring is carried out?

“…The creation of a multi‐institutional open‐source dataset of annotated renal CT scans would pave the way for increased research and progress towards automatic, reliable and quantitative image analysis tools for kidney cancer. In particular, research on 3D nephrometric scoring , image‐based volumetry (segmentation) and tracking of tumours to assess the response of therapy , and CT volumetry to predict 6‐month postoperative estimated GFR could be developed into fully automatic and robust software that finds its way into clinical practice.…”