# Effects of a personalized or generic three-dimensional tumoral kidney model on patient experience and caregiver-patient interactions, before and after partial nephrectomy, a randomized trial (Rein 3D Print Personalize-UroCCR 114)

Maxime Pattou, Sarah Masanet, Marthe-Aline Jutand, Hélène Hoarau, Joffrey Sarrazin, Alice Pitout, Laura Richert, Hugo Larribere, Federico Rubat
Baleuri, Manon Jaffredo, et al.

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## To cite this version:

Maxime Pattou, Sarah Masanet, Marthe-Aline Jutand, Hélène Hoarau, Joffrey Sarrazin, et al. Ef-fects of a personalized or generic three-dimensional tumoral kidney model on patient experience and caregiver-patient interactions, before and after partial nephrectomy, a randomized trial (Rein 3D Print Personalize-UroCCR 114). PLoS ONE, 2025, 20 (8), pp.e0323515. 10.1371/journal.pone.0323515. hal-05229557

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STUDY PROTOCOL

# Effects of a personalized or generic three-dimensional tumoral kidney model on patient experience and caregiver-patient interactions, before and after partial nephrectomy, a randomized trial (Rein 3D Print Personalize—UroCCR 114)

Maxime Pattou<sup>1,2,*</sup>, Sarah Masanet<sup>3,°</sup>, Marthe-Aline Jutand<sup>3</sup>, Hélène Hoarau<sup>4</sup>,
Joffrey Sarrazin<sup>5</sup>, Alice Pitout<sup>1,2</sup>, Laura Richert<sup>6</sup>, Hugo Larribere<sup>5</sup>,
Federico Rubat Baleuri<sup>1,2</sup>, Manon Jaffredo<sup>1,2</sup>, Solène Ricard<sup>1,2</sup>, Matthieu Faessel<sup>5</sup>,
Jocelyn Sabatier<sup>5</sup>, Jean-Christophe Bernhard<sup>1,2</sup>, Gaëlle Margue<sup>1,2</sup>

1 Department of Urology, University Hospital, Bordeaux, France, 2 I.CaRe (Integrated Research & Innovation Program for Kidney Cancer)—Inserm, UMR1312, BRIC, Bordeaux Institute of Oncology, Bordeaux University, Bordeaux, France, 3 Culture et Diffusion des Savoirs UR-7440, Bordeaux University, Bordeaux, France, 4 Teaching Hospital of Bordeaux (CHU- URISH), Culture et Diffusion des Savoirs EA-7440, University of Bordeaux, Bordeaux, France, 5 Department of Additive Fabrication Engineering, TechnoShop Coh@bit, Bordeaux University Technological Institute, Gradignan, France, 6 Medical Information Department, Bordeaux University Hospital, Bordeaux Cedex, France

© These authors contributed equally to this work as co-first authors.

* maxime.pattou@gmail.com

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OPEN ACCESS

**Citation:** Pattou M, Masanet S, Jutand M-A, Hoarau H, Sarrazin J, Pitout A, et al. (2025) Effects of a personalized or generic three-dimensional tumoral kidney model on patient experience and caregiver-patient interactions, before and after partial nephrectomy, a randomized trial (Rein 3D Print Personalize—UroCCR 114). PLoS One 20(8): e0323515.
https://doi.org/10.1371/journal.pone.0323515

**Editor:** Yudai Ishiyama, Tokyo Women's Medical University, JAPAN

**Received:** April 9, 2025

**Accepted:** July 18, 2025

**Published:** August 18, 2025

**Copyright:** © 2025 Pattou et al. This is an open access article distributed under the terms of the [Creative Commons Attribution License](https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

**Data availability statement:** No data will be made available. At the completion of the study, the data will be archived on the Université de Bordeaux network (CIRRUS system).

## Abstract

### Introduction

Personalized 3D-printed kidney models could serve as valuable educational tools for patients undergoing robot-assisted partial nephrectomy (RAPN). These models facilitate patients’ understanding of their pathology, surgical procedure, and anatomy. However, the costs associated with ‘personalized’ printing remain a barrier to their use. This study aims to thoroughly investigate the benefits of using a personalized 3D-printed kidney model as opposed to a generic 3D-printed kidney model as an educational tool for patients and as a communication tool for healthcare professionals.

### Methods and analysis

In this prospective single center study, 60 patients undergoing RAPN will be randomized to receive information based on their personalized 3D-printed tumoral kidney model or a generic 3D-printed tumoral kidney model. These models will accompany patients throughout their care pathway, from pre-operative consultations to the post-operative visit. The impact of these models on the management approaches of
**Funding:** This clinical trial has benefited from a french public grant. JC.B benefited from the national RHU5 grant on the 10th of September December, as part of the 3rd "Investissement d'Avenir" program by the French National Research Agency. website: https://anr.fr/ The sponsors or funders did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

**Competing interests:** I have read the journal's policy and the authors of this manuscript have the following competing interests: Pr Jean-Christophe Bernhard has benefited from a french public grant by l'Agence nationale de la Recherche for this trial (French National Research Agency) as a part of the 3rd "Investissement d'Avenir" program. Award Number: RHU5 on the 10th of December 2021.

**Abbreviations:** RAPN, Robotic Assisted Partial Nephrectomy; R3DP-P, Rein 3D Print – Personalize; HSS, Humanities and Social Sciences; 3D, Three Dimension; T0 to T6, consultation Timepoints

various healthcare professionals will also be examined. The data will be collected and analyzed using a mixed method, combining interviews (with patients and caregivers), observations during the presentation of the models and questionnaires (understanding of their pathology and the surgical procedure, Health-literacy, satisfaction).

## Discussion

Three dimensional kidney models have the potential to play a central role in the pre-operative information process and serve as an effective educational tool during the patient's social interactions with relatives and healthcare professionals. This study will evaluate the potential advantages of personalized 3D models of tumoral kidneys compared to their generic counterparts.

## Trial registration

The PERSONALIZE study was registered on [ClinicalTrials.gov (NCT06379698)](https://ClinicalTrials.gov) on the 5th of September 2023.

## Introduction

Educational mediation tools to reduce anxiety and improve patient comprehension remains underexploited in modern surgical practice. A pilot study from 2015 demonstrated the benefits of personalized 3D-printed kidney models as educational tools during pre-operative consultations for patients undergoing robot-assisted partial nephrectomy (RAPN) [1] for kidney cancer. This approach enhanced patients' understanding of their pathology and the surgical procedure, resulting in higher satisfaction levels [2]. In the context of personalized medicine, it is crucial to acknowledge the heterogeneity of patients' cultural and social backgrounds to optimize the doctor-patient relationship [3]. Patients with lower literacy levels often exhibit more preoperative anxiety [4,5] and poorer post-operative recovery outcomes [6]. Numerous studies have aimed to enhance the health literacy of cancer patients and improve doctor-patient communication [7–9].

Patients diagnosed with renal tumors interact with multiple healthcare professionals, and the nature of their interactions can be influenced by various factors. These include patient-related characteristics (such as clinical setting, context, age, gender, occupation, and literacy levels) as well as healthcare professional-related perceptions, like viewing patients as active participants in their care, which can alter relations and expectations [10].

Patient care is evolving to incorporate machine learning nomograms to better predict oncological pathways [11,12] as well as new digital technologies that improve patient safety [13]. Three dimensional printed kidney models enhance patients' understanding of their pathology and anatomy, as well as the communication with their family and healthcare professionals [14,15]. Most recent studies on 3D kidney models are descriptive, lack validated patient-oriented questionnaires and only one
randomized controlled trial was published, though it was not solely focused on kidney cancer [16]. Printing costs and time remain a significant barrier to the widespread use of personalized 3D-printed kidneys, generic models could represent a more affordable option [17]. Directly comparing the effect of personalized 3D-printed kidney tumor models with generic models on the patient care pathway in terms of understanding, participation, and interaction with all stakeholders through a comprehensive approach will make it possible to assess the significant differences between generic and personalized models. The results could therefore have important clinical and economic implications.

# Materials and methods

## Aim

The aim of this study is to investigate the benefits of using a personalized 3D-printed model of the tumoral kidney versus a generic 3D-printed tumoral kidney model as an educational tool throughout the care pathway, on patient's experience and their interactions with caregivers

## Trial design

We are conducting a prospective, unblinded, randomized trial with two parallel groups (1:1 ratio). Participants will be assigned to either use of a personalized 3D-printed model or a generic 3D-printed model as information and communication support throughout their care journey. The SPIRIT schedule of enrollment, interventions and assessments is presented in Fig 1 while the study's design is presented in Fig 2.

## Study population

Patients enrollment will take place during standard diagnostic consultations for kidney tumor prior to being scheduled for RAPN at a high-volume academic hospital. Recruitment started in May 2024, inclusion and exclusion criteria are outlined in Table 1 – inclusion and exclusion criteria. Eligible participants will include patients aged 18 or older who are scheduled for RAPN for a unilateral renal tumor, or first surgery for bilateral tumors, and who are affiliated to the French social security system. Patients will be excluded if they are contraindicated to a four-phase preoperative CT scan required to produce the 3D model, have a solitary kidney, a history of other cancers, or metastatic disease at inclusion, are under trusteeship, curatorship, or legal guardianship, or if they refuse to give consent in either the UroCCR project or this trial. All patients and surgical data will be stored in the database of the French research network on kidney cancer UroCCR (NCT03293563). This prospectively maintained database is IRB-approved and obtained the CNIL authorization number DR-2013-206 and EDS authorization DT-2024-027. It has been labeled by the French National Cancer Institute (INCa), the French High Authority of Health (HAS), the French Scientific Interest Group on Biology, Health and Agronomy (GIS-IBISA) and the French National Research Agency (ANR).

Healthcare professionals involved in patient care will be invited to participate in the study. Participants will include junior and senior urologists, residents, nurses from the urology ward, operating theatre nurses, auxiliary nurses, nurse anesthetists and anesthesiologists. We will ensure diversity in terms of profession and seniority to better represent professional heterogeneity and diversity of experience. An initial interview will take place before the introduction of 3D models in the department, and a second interview will be conducted one year after the study begins.

## Study setting

In this study, patients scheduled for RAPN will be randomized into two groups: one informed using a personalized 3D-printed model of their tumoral kidney and the other a generic 3D-printed model. Consecutive patients who meet the eligibility criteria during the inclusion period will be offered to participate in the study. All participants and health professionals will provide written informed consent prior to their inclusion in both UroCCR and in the Rein 3D print – Personalize
<table><caption>**Fig 1.** SPIRIT schedule of enrolment, interventions, and assessment. Abbreviations: T0 to T5 = timepoints 1 to 5, D0 = day of surgery. HLSEU-Q16 = European Health Literacy Survey Questionnaire.</caption><thead><tr><th rowspan="3"></th><th rowspan="3">Timepoint</th><th colspan="7">STUDY PERIOD</th></tr><tr><th>Enrolment</th><th>Allocation</th><th colspan="4">Post-allocation</th><th>Close-out</th><th></th></tr><tr><th>T0<br>(First<br>consultation)</th><th>T1<br>(T0 + 1 day)</th><th>(T1 + 15<br>days)</th><th>T2<br>(30 to 7 days<br>before D0)</th><th>T3<br>(T2 + 15<br>days)</th><th>T4<br>(D0)</th><th>T5<br>(T4 + 15 to<br>+45 days)</th><th>T6<br>T5+15 days</th></tr></thead><tbody><tr><td rowspan="3">ENROLEMENT</td><td>Eligibility screen</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Informed consent</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Allocation</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="5">INTERVENTION</td><td>Modeling virtual 3D-<br>model (according to<br>randomized arm)</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td>Printing 3D-model<br>(according to<br>randomized arm)</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td>Preoperative<br>information according<br>to randomized arm</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td>Surgery</td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td></tr><tr><td>Postoperative<br>consultation</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td></tr><tr><td rowspan="4">ASSESSMENTS</td><td>HLSEU-Q16<br>questionnaire (health<br>literacy)</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>X</td></tr><tr><td>Questionnaire<br>(knowledge of disease<br>and planned surgery)</td><td></td><td>X</td><td></td><td></td><td>X</td><td></td><td>X</td></tr><tr><td>Questionnaire of<br>satisfaction</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td></tr><tr><td>Semi-directive<br>interview</td><td></td><td>X</td><td></td><td></td><td>X</td><td></td><td>X</td></tr></tbody></table>

https://doi.org/10.1371/journal.pone.0323515.g001

(R3DP-P) study. The study received a favorable opinion by the French Ethics Committee for the Protection of Individuals South-East IV gave a on the 24th of April 2024 (Approval number: 24.00621.000226). After inclusion, patients' data will be anonymized and collected in the UroCCR database. Source data from observations (notebook) and interviews (using digital audio recording) will be transcribed, entered, and coded exclusively by the HSS (humanities and social sciences) research team. The transcribed data will be documented directly into the Nvivo Pro 13® qualitative analysis software, and subsequently analyzed using Nvivo Pro 13®.

Randomization and blinding

Randomization between the two groups is balanced 1:1, without stratification. The randomization list is established by a statistician at Bordeaux University Hospital's Clinical Epidemiology Unit before the onset of the study and is implemented in the electronic UroCCR platform. Randomization will be carried out on the UroCCR platform, immediately following the inclusion visit. Upon confirming a patient's eligibility, the investigator accesses the UroCCR website using secure credentials. The platform then instantly provides the investigator with a unique participant identifier and the result of the
<figure><img src="image_5.png" /><figcaption>**Fig 2.** Study design. Abbreviations: T0 to T5 = timepoints 1 to 5. D is for days.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0323515.g002

<table><caption>**Table 1.** Inclusion and exclusion criteria.</caption><thead><tr><td>Inclusion criteria</td><td>Exclusion criteria</td></tr></thead><tbody><tr><td>Male and female aged of 18 and over</td><td>Language difficulties in French</td></tr><tr><td>Scheduled for a first robotic-assisted partial nephrectomy for a unilateral renal tumor, or first surgery for a bilateral tumor</td><td>Contraindication to a four-phase preoperative CT scan required to produce the 3D model</td></tr><tr><td>Affiliation to or beneficiary of the French social security</td><td>Person under trusteeship, curatorship, or legal guardianship</td></tr><tr><td>Free, informed, and written consent signed by the patient and the investigating physician (at the latest on the day of inclusion and before any examination required by the research)</td><td>Refusal of consent or participation in the UroCCR project and the R3DP-P ancillary trial</td></tr></tbody></table>

R3DP-P: Rein 3D – Personalize.

https://doi.org/10.1371/journal.pone.0323515.t001

randomization process. Although the study is designed as unblinded, patients will remain unaware of their assigned randomization group until their designated follow-up visit.

## Procedure

Each patient will be randomly assigned to one of the two parallel groups (1:1 ratio) at inclusion, corresponding to the information mediation tool used throughout the care pathway. All patients will undergo a high quality, four-phase preoperative abdominal CT scan.
* Personalized 3D-printed model group: CT scans are segmented by a urologist using Synapse 3D® software (Fujifilm) to generate a comprehensive virtual 3D model of the tumoral kidney, its vascularization and excretory tract. Our workflow is in accordance with high quality 3D model recommendations [18]. The models are then printed using high-resolution, multi-material 3D printing technology (Stratasys J750® 3D printer) (Fig 3), model accurateness was previously published by our team [19]. The personalized three-dimensional printed physical model of the patient's tumoral kidney will be used as an educational tool.

* Generic 3D-printed model group: a three-dimensional printed physical model of a tumoral kidney selected from a set of eight models that best matches the patient's condition will be used as an educational tool. These models were created from the CT-scans of previously operated patients and were selected to represent the full spectrum of kidney cancer presentations. Fig 4 shows the eight kidney models and corresponding RENAL nephrometry scores and TNM staging [20]. Three of the models represented anterior tumors of low to intermediate complexity (Renal scores 5a, 8a and 9a, all cT1a), two other models were upper and lower posterior tumors of low to intermediate complexity (Renal scores 8p and 5p, cT1b and cT1a), two hilar endophytic and exophytic models (Renal scores 10xh and 11xh, cT1b and cT1a) and one large inferior tumor model (Renal scores 10x, cT2b).

A surgical consultation using the 3D-model from the patient's allocated group will take place between 30 and 7 days before the surgery. This consultation serves to inform the patient about their medical situation and the planned operation, using the 3D model as an educational tool. It allows patients to ask any questions, express doubts or clarify

<figure><img src="image_6.png" /><figcaption>**Fig 3.** 3D printed model workflow. A. CT-scan. B. 3D model rendering. C. 3D printing.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0323515.g003

<figure><img src="image_7.png" /><figcaption>**Fig 4.** Generic kidney models set. Renal scores [20] according to each kidney: A.8a B.9a C.5a D.10x E.10xh F.11xh G.8p H.5p.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0323515.g004
misunderstandings they may have. Importantly, the explanations provided during this consultation are not standardized and follow routine clinical practice, allowing for natural dialogue and variation across interactions. The 3D model then accompanies the patient throughout their care pathway to serve as a tool for communication and education.

## Outcomes measures

All patients will complete questionnaires assessing their health literacy, knowledge of kidney-tumor anatomy, and satisfaction with the use of 3D-printed kidney models as educational tools. Patients' experience and their interactions with caregivers will be analyzed during semi-structured interviews conducted by a team of humanities researchers at three different times: after the first consultation with the surgeon and before the preoperative education consultation, between this second consultation and the surgery, and after the post-operative consultation. The impact of these 3D models on healthcare professionals and the changes induced in their practice will be assessed through two interviews: one interview before the start of the study, i.e., the introduction of 3D models into the care pathways, and a second interview one year after the introduction of the models.

**Primary outcomes.** Qualitative evaluation of patients' experience using a personalized 3D-printed kidney model versus a generic 3D-printed kidney model as an education tool throughout the care pathway, focusing on patient experiences and their interactions with healthcare professionals before and after partial nephrectomy. These experiences will be analyzed in conjunction with clinical and demographic data from the UroCCR database.

## Secondary outcomes.

* Detailed description of interactions between caregivers and patients, including the context, environment, practice, vocabulary, and discourse content used throughout the care process.

* Comparison of speech and terminology differences when using the different models during interactions between patients, caregivers, and patients' families, through systematic analysis of interviews.

* Investigation of the 3D-printed kidney model's use from the initial consultation to the post-operative visit, documenting its role throughout the entire care process.

* Comparison of patient's understanding of kidney and tumor anatomy, as well as surgical strategy and risk of complications based on the type of model used (personalized vs generic) before and after the surgery (S6 and S7 Files).

* Comparison of health literacy levels between the two groups at various times, analyzing changes in the average score on the Health literacy Survey Questionnaire (HLSEU-Q16: European Health Literacy Survey Questionnaire [21], French version [22]) (S5 File).

* Evaluation of Healthcare professionals' adoption of the 3D tool and perception of patient management following the integration of 3D models, by qualitatively assessing changes in practices throughout the care process.

All questionnaires will be distributed using the UroConnect® application (Resilience) [23], a telemonitoring tool routinely used in our nurse-led pathways (enhanced rehabilitation after surgery and ambulatory) or in paper format for patients without internet access. The application will notify participants at designated times to complete the appropriate questionnaire.

## Anthropology-driven approach

We will employ a comprehensive health anthropology-driven [24] approach to examine the information and educational interactions between healthcare professionals and patients. The following interactions will be investigated by two educational experts:

* The way caregivers provide information to patients, exploring patient experiences, and assessing health education and literacy [25].
* The informational context that occurs within the patient care pathway, describing the process of knowledge dissemination and construction of various participants, and examining the adaptation work performed by professionals during interactions with patients.

Additionally, a quantitative approach will complement our comprehensive and didactic exploration, allowing us to question the impact of integrating the model on patients' understanding of their pathology and their level of health literacy through the HLSEU-Q16 literacy questionnaire (S5 File). Understanding of kidney anatomy, tumor localization, surgical planning and surgical procedure as well as knowledge of postoperative complications will be assessed using multiple validated questionnaires: the pathology understanding questionnaire (S6 File) [1] and a satisfaction questionnaire (S7 File) [16]. This study will employ a mixed-method design, combining qualitative and quantitative elements. It is a single-center study based on observations (interaction situations), interviews (with professionals and patients), and questionnaires (completed by patients).

## Pre- and post-operative follow-up

Study participation begins with an inclusion consultation (T0), aligning with standard management practices as depicted in the timeline in Fig 2. Following this consultation, patients are randomized into one of two groups, allowing the surgical team to create a personalized 3D printed model of patients' tumoral kidney for those included in the personalized group.

Subsequently, an interview with the HSS researcher is conducted either at the hospital or at home (T1), according to the patient's preferences, within 15 days after the inclusion visit. This face-to-face meeting explores the patient's experience from the initial onset of symptoms to seeking urological care. It also gathers socio-demographic data and insights into the patient's interactions with family and peers regarding the disease. During this visit, patients will complete questionnaires via the UroConnect platform, focusing on HLSEU-Q16 literacy, and their understanding of renal anatomy and surgical issues considerations.

Fifteen days after the "3D model introduction" consultation (T2), patients will participate in another interview (T3), either at the hospital or at home. This session gathers insights about their experience since the previous interview and their interactions with healthcare professionals, family, and friends related to the disease. At this point, both questionnaires will be completed again. The surgery will then be performed, 7-30 days after the T2 consultation, without altering the surgeon's standard practice.

The collection of research data will conclude within 15 days after the one-month post-operative consultation. A final interview will be conducted either at home or the hospital, depending on the patient's preference. This meeting will explore the patient's experience since the prior interview and their communications with relatives about the disease. Participants will also complete one last time the questionnaires via the UroConnect platform, addressing HLSEU-Q16 literacy, their understanding of renal anatomy and surgical issues, and their overall satisfaction.

## Statistical analysis

**Sample size.** The study was designed to include 60 patients, divided into two randomized groups of 30 each. This number allows for cross-analysis of data collected from the same population—through interviews as well as questionnaires and falls within the upper range generally recommended for qualitative studies [26,27]. No statistical power calculation was performed, as the primary aim of this study is not to detect a specific measurement difference, but rather to explore the overall impact on the patient's experience. Should any patients be lost to follow-up, it may be decided to recruit new participants without exceeding 68 inclusions. Furthermore, interviews will be conducted with 30 healthcare professionals who meet the inclusion criteria.

**Ethics statement and participants consent.** The study received a favorable opinion by the French Ethics Committee for the Protection of Individuals South-East IV gave a on the 24th of April 2024 (Approval number: 24.00621.000226). All
participants and health professionals will provide written informed consent prior to their inclusion in both UroCCR and in
the Rein 3D print - Personalize (R3DP-P) study.

**Data analysis.** A mixed-methods analysis will be employed using a triangulation approach [28]. Data from patients' questionnaires will undergo descriptive analysis, detailing the score distribution for the HLS-EU16 literacy questionnaire at baseline and study conclusion, as well as patient satisfaction and Knowledge of kidney and tumor anatomy questionnaires. Quantitative variables will be described with mean, standard deviation, median, and interquartiles. They will be compared between groups using the Student *t* test or the Wilcoxon test, depending on normality. Qualitative variables will be described using frequencies and percentages, and will be compared using Fisher's exact test.

**Interview content analysis.** Changes in understanding of the disease and surgical process will be further examined through a complementary analysis of the contents from cross-sectional interviews, conducted by humanities researchers. The purpose of this analytical approach is to identify recurring themes and salient points of the discourse in the interviews. In the initial phase, this will facilitate the establishment of patient profiles, incorporating elements such as the patient's life history, their treatment trajectory and their psychological state at the end of the first consultation with the surgeon. The data from the second interview will be studied in light of these profiles. The care pathway will be analyzed longitudinally by looking at the evolution across the three interviews, and the third interview will provide feedback on the use of these 3D models in the care pathway. In addition, the content of the interviews with healthcare professionals collected at the end of the study will be used to study the place of models in care and the changes perceived following the integration of printed 3D models into the care pathway.

**Trial status**

The protocol number is ID-RCB 2023-A00146-39, version no. 1 from 27/10/2023. Recruitment began in May 2024.
Inclusion deadline is scheduled September 2025. Trial is registered with the reference NCT06379698 [ClinicalTrials.gov] [registered on 5 September 2023]. UroCCR network is registered with the reference NCT03293563.

**Discussion**

We hypothesize that both 3D tumoral kidney models will serve as a crucial educational tool during the patient's interac-
tions with relatives and healthcare professionals: they are intended to empower the patient by integrating it as a part of
their healthcare process. The personalized 3D printed model may facilitate tailored discussions about the patient's specific
condition while enhancing the understanding of their illness. Thus, the introduction of these 3D models could have an
impact on the relationship that professionals have with patients.

We furthermore assume that patients' ability to visually and physically interact with the 3D representation of "their" kidney will significantly enhance their comprehension of their pathology throughout their care pathway. This hypothesis is driven by the belief that tangible, personalized representations can aid in demystifying complex medical conditions for patients. This study is the first to directly compare personalized 3D-printed tumoral kidney models to generic models, its findings may have important clinical and economic implications.

**Supporting information**

**S1 File. Letter of acceptance ANR.**
(PDF)

**S2 File. Jury ANR.**
(PDF)

**S3 File. ANR presentation.**
(PDF)
**S4 File. SPIRIT Checklist.**

(PDF)

**S5 File. HLSEU16-French-2020.**

(PDF)

**S6 File. Knowledge questionnaire.**

(PDF)

**S7 File. Satisfaction questionnaire.**

(PDF)

**S8 File. UroCCR_Information and consent document.**

(PDF)

**S9 File. Ethical committee favorable opinion.**

(PDF)

**S10 File. English personalize protocol.**

(PDF)

**S11 File. Protocol_in_French.**

(PDF)

**Author contributions**

**Conceptualization:** Marthe-Aline Jutand, Hélène Hoarau, Joffrey Sarrazin, Laura Richert, Hugo Larribere, Manon Jaffredo, Solène Ricard, Matthieu Faessel, Jean-Christophe Bernhard, Gaëlle Margue.

**Data curation:** Sarah Masanet, Hélène Hoarau, Alice Pitout, Laura Richert, Gaëlle Margue.

**Formal analysis:** Gaëlle margue.

**Funding acquisition:** Jean-Christophe Bernhard.

**Investigation:** Maxime Pattou, Sarah Masanet, Alice Pitout, Federico Rubat Baleuri, Jocelyn Sabatier, Jean-Christophe Bernhard.

**Methodology:** Manon Jaffredo, Jean-Christophe Bernhard.

**Project administration:** Alice Pitout, Jean-Christophe Bernhard, Gaëlle Margue.

**Resources:** Joffrey Sarrazin, Hugo Larribere, Gaëlle Margue.

**Software:** Joffrey Sarrazin, Matthieu Faessel, Jocelyn Sabatier.

**Supervision:** Manon Jaffredo, Solène Ricard, Jean-Christophe Bernhard.

**Validation:** Jean-Christophe Bernhard.

**Writing – original draft:** Maxime Pattou, Sarah Masanet, Marthe-Aline Jutand, Jean-Christophe Bernhard, Gaëlle Margue.

**Writing – review & editing:** Maxime Pattou, Sarah Masanet, Marthe-Aline Jutand, Jean-Christophe Bernhard, Gaëlle Margue.

**References**

1. Bernhard J-C, Isotani S, Matsugasumi T, Duddalwar V, Hung AJ, Suer E, et al. Personalized 3D printed model of kidney and tumor anatomy: a useful tool for patient education. World J Urol. 2016;34(3):337–45. https://doi.org/10.1007/s00345-015-1632-2 PMID: 26162845
2. Travaline JM, Ruchinskas R, D'Alonzo GE Jr. Patient-physician communication: why and how. J Am Osteopath Assoc. 2005;105(1):13-8. PMID: 15710660

3. Curchod C. Identifier les facteurs de détérioration de la relation. In: Relations soignants-soignés. Elsevier; 2009. p. 13-28. https://doi.org/10.1016/
b978-2-294-70537-3.50001-7

4. Stephanie C-J, Mathieu A, Aurore M, Monique MR-T. Outpatients' perception of their preoperative information regarding their health literacy skills and their preoperative anxiety level: Protocol for a prospective multicenter cross-sectional study. Medicine (Baltimore). 2021;100(20):e26018.
https://doi.org/10.1097/MD.00000000000026018 PMID: 34011104

5. Köhler H, Dorozhkina R, Gruner-Labitzke K, de Zwaan M. Specific Health Knowledge and Health Literacy of Patients before and after Bariatric Surgery: A Cross-Sectional Study. Obes Facts. 2020;13(2):166-78. https://doi.org/10.1159/000505837 PMID: 32208386

6. Hälleberg Nyman M, Nilsson U, Dahlberg K, Jaensson M. Association Between Functional Health Literacy and Postoperative Recovery, Health Care Contacts, and Health-Related Quality of Life Among Patients Undergoing Day Surgery: Secondary Analysis of a Randomized Clinical Trial. JAMA Surg. 2018;153(8):738-45. https://doi.org/10.1001/jamasurg.2018.0672 PMID: 29710226

7. Shen H-N, Lin C-C, Hoffmann T, Tsai C-Y, Hou W-H, Kuo KN. The relationship between health literacy and perceived shared decision making in patients with breast cancer. Patient Educ Couns. 2019;102(2):360-6. https://doi.org/10.1016/j.pec.2018.09.017 PMID: 30270171

8. Pieterse AH, Gulbrandsen P, Ofstad EH, Menichetti J. What does shared decision making ask from doctors? Uncovering suppressed qualities that could improve person-centered care. Patient Educ Couns. 2023;114:107801. https://doi.org/10.1016/j.pec.2023.107801 PMID: 37230040

9. Luckenbaugh AN, Moses KA. The impact of health literacy on urologic oncology care. Urol Oncol. 2022;40(4):117-9. https://doi.org/10.1016/j.
urolonc.2019.06.016 PMID: 31324457

10. Marche H. Au-delà de l'autonomie du patient: l' « esprit de soin » dans les trajectoires de cancer avancé. Anthropologie et Santé. 2015;10:Art. no. 10. https://doi.org/10.4000/anthropologiesante.1595

11. Margue G, Ferrer L, Etchepare G, Bigot P, Bensalah K, Mejean A, et al. UroPredict: Machine learning model on real-world data for prediction of kidney cancer recurrence (UroCCR-120). NPJ Precis Oncol. 2024;8(1):45. https://doi.org/10.1038/s41698-024-00532-x PMID: 38396089

12. Boulenger de Hauteclocque A, Ferrer L, Ambrosetti D, Ricard S, Bigot P, Bensalah K, et al. Machine-learning approach for prediction of pT3a upstaging and outcomes of localized renal cell carcinoma (UroCCR-15). BJU Int. 2023;132(2):160-9. https://doi.org/10.1111/bju.15959 PMID: 36648124

13. Canfell OJ, Meshkat Y, Kodiyattu Z, Engstrom T, Chan W, Mifsud J, et al. Understanding the Digital Disruption of Health Care: An Ethno- graphic Study of Real-Time Multidisciplinary Clinical Behavior in a New Digital Hospital. Appl Clin Inform. 2022;13(5):1079-91. https://doi. org/10.1055/s-0042-1758482 PMID: 36351558

14. Yuan X, Liu X, Jing Q, Liu F, Zhang X. The application of full-size three-dimensional individual printed model combined with three-dimensional digital demonstration can facilitate patient's preoperative comprehension to robotic-assisted laparoscopic partial nephrectomy. Perioper Med (Lond). 2022;11(1):22. https://doi.org/10.1186/s13741-022-00256-1 PMID: 35761307

15. Scott ER, Singh A, Quinn AM, Morano S, Karp A, Boyd K, et al. The use of individualized 3D-printed models on trainee and patient education, and surgical planning for robotic partial nephrectomies. J Robot Surg. 2023;17(2):465-72. https://doi.org/10.1007/s11701-022-01441-6 PMID: 35781195

16. Wake N, Rosenkrantz AB, Huang R, Park KU, Wysock JS, Taneja SS, et al. Patient-specific 3D printed and augmented reality kidney and prostate cancer models: impact on patient education. 3D Print Med. 2019;5(1):4. https://doi.org/10.1186/s41205-019-0041-3 PMID: 30783869

17. Scott ER, Singh A, Quinn A, Boyd K, Lallas CD. How I Do It: Cost-effective 3D printed models for renal masses. Can J Urol. 2021;28(5):10874-7. PMID: 34657662

18. Checcucci E, Piazza P, Micali S, Ghazi A, Mottrie A, Porpiglia F, et al. Three-dimensional Model Reconstruction: The Need for Standardization to Drive Tailored Surgery. Eur Urol. 2022;81(2):129-31. https://doi.org/10.1016/j.eururo.2021.11.010 PMID: 34862098

19. Michiels C, Jambon E, Bernhard JC. Measurement of the Accuracy of 3D-Printed Medical Models to Be Used for Robot-Assisted Partial Nephrectomy. AJR Am J Roentgenol. 2019;213(3):626-31. https://doi.org/10.2214/AJR.18.21048 PMID: 31063426

20. 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;182(3):844-53. https://doi.org/10.1016/j.juro.2009.05.035 PMID: 19616235

21. Sørensen K, Van den Broucke S, Pelikan JM, Fullam J, Doyle G, Slonska Z, et al. Measuring health literacy in populations: illuminating the design and development process of the European Health Literacy Survey Questionnaire (HLS-EU-Q). BMC Public Health. 2013;13:948. https://doi. org/10.1186/1471-2458-13-948 PMID: 24112855

22. Rouquette A, Nadot T, Labitrie P, Van den Broucke S, Mancini J, Rigal L, et al. Validity and measurement invariance across sex, age, and edu- cation level of the French short versions of the European Health Literacy Survey Questionnaire. PLoS One. 2018;13(12):e0208091. https://doi. org/10.1371/journal.pone.0208091 PMID: 30521552

23. Margue G, Callede E, Ricard S, Picard F, Dubernet C, Robert G, et al. Digitalisation de la coordination infirmière des parcours périopératoires de chirurgie rénale en réhabilitation améliorée et ambulatoire par l'application UroConnect*. Prog Urol. 2022;32(13):888-92. https://doi.org/10.1016/j. purol.2022.08.015 PMID: 36055902

24. Mercan A. Sylvie Fainzang, La relation médecins-malades: information et mensonges. Amades. 2007;69. https://doi.org/10.4000/amades.394
25. Pierron J-P. Une nouvelle figure du patient ? Les transformations contemporaines de la relation de soins. Sosan. 2007;25(2):43-66. https://doi.org/10.3406/sosan.2007.1858

26. Ahmed SK. Sample size for saturation in qualitative research: Debates, definitions, and strategies. J Med Surg Public Health. 2025;5:100171. https://doi.org/10.1016/j.glmedi.2024.100171

27. Hamad AA, Ahmed SK. Understanding the Lower and Upper Limits of Sample Sizes in Clinical Research. Cureus. 2025;17(1):e76724. https://doi.org/10.7759/cureus.76724 PMID: 39897306

28. Nagels M. Enquêter dans les métiers de l'humain. In: Enquêter dans les métiers de l'humain. Éditions Raison et Passions; 2022. p. 396-411. https://doi.org/10.3917/rp.alber.2022.01.0396