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Three-dimensional virtual models assistance predicts higher rates of “successful” minimally invasive partial nephrectomy: an Institutional analysis across the available trifecta definitions

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Abstract

Purpose

3D virtual models (3DVMs) are nowadays under scrutiny to improve partial nephrectomy (PN) outcomes. Five different Trifecta definitions have been proposed to optimize the framing of “success” in the PN field. Our aim is to analyze if the use of 3DVMs could impact the success rate of minimally invasive PN (mi-PN), according to the currently available definitions of Trifecta.

Materials and methods

At our Institution 250 cT1-2N0M0 renal masses patients treated with mi-PN were prospectively enrolled. Inclusion criteria were the availability of contrast-enhanced CT, baseline and postoperative serum creatinine, and eGFR. These patients were then compared with a control group of 710 patients who underwent mi-PN with the same renal function assessments, but without 3DVMs. Multivariable logistic regression (MLR) models were used to predict the trifecta achievement according to the different trifecta definitions.

Results

Among the definitions, Trifecta rates ranged between 70.8% to 97.4% in the 3DVM group vs. 56.8% to 92.8% in the control group (all p values < 0.05). 3DVMs showed better postoperative outcomes in terms of ΔeGFR, ( – 16.6% vs.  – 2.7%, p = 0.03), postoperative complications (15%, vs 22.9%, p = 0.002) and major complications (Clavien Dindo > 3, 2.8% vs 5.6%, p = 0.03). At MLR 3DVMs assistance independently predicted higher rates of successful PN across all the available definitions of Trifecta (OR: 2.7 p < 0.001, OR:2.0 p = 0.0008, OR:2.8 p = 0.02, OR 2.0 p = 0.003).

Conclusions

The 3DVMs availability was found to be the constant predictive factor of successful PN, with a twofold higher probability of achieving Trifecta regardless of the different definitions available in Literature.

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Data availability

The data that support the findings of this study are available from the corresponding author, [A.P.], upon reasonable request.

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Funding

No funding was received to assist with the preparation of this manuscript. No funding was received for conducting this study. No funds, grants, or other support was received.

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Authors and Affiliations

  1. Division of Urology, Department of Oncology, School of Medicine, University of Turin, San Luigi Gonzaga Hospital, Orbassano (Turin), Italy

    Angela Pecoraro, Daniele Amparore, Enrico Checcucci, Federico Piramide, Beatrice Carbonaro, Sabrina De Cillis, Stefano Granato, Michele Sica, Cristian Fiori & Francesco Porpiglia

  2. European Association of Urology (EAU) Young Academic Urologists (YAU) Renal Cancer Working Group, Arnhem, Netherlands

    Angela Pecoraro, Daniele Amparore & Riccardo Campi

  3. Department of Urology, Careggi Hospital, University of Florence, Florence, Italy

    Riccardo Campi

Authors
  1. Angela Pecoraro
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  2. Daniele Amparore
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  3. Enrico Checcucci
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  4. Federico Piramide
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  5. Beatrice Carbonaro
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  6. Sabrina De Cillis
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  7. Stefano Granato
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  8. Michele Sica
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  9. Riccardo Campi
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  10. Cristian Fiori
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  11. Francesco Porpiglia
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Contributions

Protocol/project development: AP, DA, CF, FP. Data collection or management: BC, AP, DA, EC, FP, SDC, SG, MS, RC. Data analysis: AP, DA. Manuscript writing/editing AP, DA, EC, FP, BC, SC, SG, MS, RC, CF, FP.

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Correspondence to Angela Pecoraro.

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Pecoraro, A., Amparore, D., Checcucci, E. et al. Three-dimensional virtual models assistance predicts higher rates of “successful” minimally invasive partial nephrectomy: an Institutional analysis across the available trifecta definitions. World J Urol 41, 1093–1100 (2023). https://doi.org/10.1007/s00345-023-04310-5

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