NCT06418243

Brief Summary

This study's purpose is the comparison of the automatically segmented 3D model to the reference manual segmentation, based on the Dice precision index. It is implemented by making parents' patients, surgeons and surgical helpers answer specific questions comparing 3D images to usual 2D images of the patient's tumor.

Trial Health

77
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
60

participants targeted

Target at P25-P50 for all trials

Timeline
4mo left

Started Sep 2024

Geographic Reach
1 country

1 active site

Status
recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Progress84%
Sep 2024Sep 2026

First Submitted

Initial submission to the registry

May 13, 2024

Completed
4 days until next milestone

First Posted

Study publicly available on registry

May 17, 2024

Completed
4 months until next milestone

Study Start

First participant enrolled

September 16, 2024

Completed
1.9 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

August 1, 2026

Expected
1 month until next milestone

Study Completion

Last participant's last visit for all outcomes

September 1, 2026

Last Updated

March 23, 2026

Status Verified

March 1, 2026

Enrollment Period

1.9 years

First QC Date

May 13, 2024

Last Update Submit

March 19, 2026

Conditions

Keywords

Surgery3D-ImagingMRICT ScanPaediatric surgeryTumor

Outcome Measures

Primary Outcomes (1)

  • Segmentation comparison

    Comparison of the automatically segmented 3D model to the reference manual segmentation, based on the Dice precision index

    1 month

Secondary Outcomes (11)

  • Distance comparison

    1 month

  • Anatomical structure recognition comparison

    Day 0

  • Pre-operative planning contribution

    Day 0

  • Added value evaluation

    Day 0

  • Surgeons' support evaluation in pre-operative routine

    Day 0

  • +6 more secondary outcomes

Study Arms (1)

Children planned to get an MRI or CT scan

Children with a pelvic or retroperitoneal tumor requiring an MRI or CT scan for a possible surgical intervention

Eligibility Criteria

Age3 Months - 17 Years
Sexall
Age GroupsChild (0-17)
Sampling MethodNon-Probability Sample
Study Population

Children with a pelvic or retroperitoneal tumor requiring an MRI or CT scan for a possible surgical intervention coming at the hospital for a consultation as part of their standard care.

You may qualify if:

  • Children:
  • Children between 3 months and less than 18 years old
  • Children with a pelvic tumor requiring an MRI for a possible surgical intervention
  • Children with a retroperitoneal tumor requiring a CT scan or MRI with a view to surgical intervention
  • Children with no contraindication for a CT scan and/or 3T MRI
  • Children whose parents do not object to their participation in the study
  • Other participants:
  • Operating surgeon agreeing to participate in the study
  • Caregiver agreeing to participate in the study
  • External surgeon agreeing to participate in the study

You may not qualify if:

  • Children :
  • Contraindication to MRI: metallic ocular foreign body, pacemaker, mechanical heart valve, old vascular clips on cerebral aneurysm
  • Need for an MRI under general anaesthesia
  • Contraindication for a CT scan with injection: renal failure, allergy to iodinated contrast products
  • Emergency situation

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Hôpital Necker Enfants Malades

Paris, 75015, France

RECRUITING

Related Publications (10)

  • Wake N, Wysock JS, Bjurlin MA, Chandarana H, Huang WC. "Pin the Tumor on the Kidney:" An Evaluation of How Surgeons Translate CT and MRI Data to 3D Models. Urology. 2019 Sep;131:255-261. doi: 10.1016/j.urology.2019.06.016. Epub 2019 Jun 22.

    PMID: 31233814BACKGROUND
  • Talanki VR, Peng Q, Shamir SB, Baete SH, Duong TQ, Wake N. Three-Dimensional Printed Anatomic Models Derived From Magnetic Resonance Imaging Data: Current State and Image Acquisition Recommendations for Appropriate Clinical Scenarios. J Magn Reson Imaging. 2022 Apr;55(4):1060-1081. doi: 10.1002/jmri.27744. Epub 2021 May 27.

    PMID: 34046959BACKGROUND
  • Ibrahim I, Skoch A, Herynek V, Jiru F, Tintera J. Magnetic resonance tractography of the lumbosacral plexus: Step-by-step. Medicine (Baltimore). 2021 Feb 12;100(6):e24646. doi: 10.1097/MD.0000000000024646.

    PMID: 33578590BACKGROUND
  • van der Zee JM, Fitski M, Simonis FFJ, van de Ven CP, Klijn AJ, Wijnen MHWA, van der Steeg AFW. Virtual Resection: A New Tool for Preparing for Nephron-Sparing Surgery in Wilms Tumor Patients. Curr Oncol. 2022 Feb 1;29(2):777-784. doi: 10.3390/curroncol29020066.

    PMID: 35200565BACKGROUND
  • Bertrand MM, Macri F, Mazars R, Droupy S, Beregi JP, Prudhomme M. MRI-based 3D pelvic autonomous innervation: a first step towards image-guided pelvic surgery. Eur Radiol. 2014 Aug;24(8):1989-97. doi: 10.1007/s00330-014-3211-0. Epub 2014 May 17.

    PMID: 24838739BACKGROUND
  • Simons DC, Buser MAD, Fitski M, van de Ven CP, Ten Haken B, Wijnen MHWA, Tan CO, van der Steeg AFW. Multi-modal 3-Dimensional Visualization of Pediatric Neuroblastoma: Aiding Surgical Planning Beyond Anatomical Information. J Pediatr Surg. 2024 Aug;59(8):1575-1581. doi: 10.1016/j.jpedsurg.2024.02.025. Epub 2024 Feb 24.

    PMID: 38461108BACKGROUND
  • Valls-Esteve A, Adell-Gomez N, Pasten A, Barber I, Munuera J, Krauel L. Exploring the Potential of Three-Dimensional Imaging, Printing, and Modeling in Pediatric Surgical Oncology: A New Era of Precision Surgery. Children (Basel). 2023 May 3;10(5):832. doi: 10.3390/children10050832.

    PMID: 37238380BACKGROUND
  • Hampshire J, Dicken BJ, Uruththirakodeeswaran T, Punithakumar K, Noga M. Pediatric patient-specific three-dimensional virtual models for surgical decision making in resection of hepatic and retroperitoneal tumors. Int J Comput Assist Radiol Surg. 2023 Oct;18(10):1941-1949. doi: 10.1007/s11548-023-02852-y. Epub 2023 Mar 11.

    PMID: 36905500BACKGROUND
  • Bernhard JC, Isotani S, Matsugasumi T, Duddalwar V, Hung AJ, Suer E, Baco E, Satkunasivam R, Djaladat H, Metcalfe C, Hu B, Wong K, Park D, Nguyen M, Hwang D, Bazargani ST, de Castro Abreu AL, Aron M, Ukimura O, Gill IS. Personalized 3D printed model of kidney and tumor anatomy: a useful tool for patient education. World J Urol. 2016 Mar;34(3):337-45. doi: 10.1007/s00345-015-1632-2. Epub 2015 Jul 11.

    PMID: 26162845BACKGROUND
  • Youn JK, Park SJ, Choi YH, Han JW, Ko D, Byun J, Yang HB, Kim HY. Application of 3D printing technology for pre-operative evaluation, education and informed consent in pediatric retroperitoneal tumors. Sci Rep. 2023 Jan 30;13(1):1671. doi: 10.1038/s41598-023-28423-4.

    PMID: 36717595BACKGROUND

MeSH Terms

Conditions

Pelvic NeoplasmsNeoplasms

Condition Hierarchy (Ancestors)

Neoplasms by Site

Study Officials

  • Sabine SARNACKI, MD

    Assistance Publique - Hôpitaux de Paris

    STUDY CHAIR

Central Study Contacts

Study Design

Study Type
observational
Observational Model
CASE ONLY
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

May 13, 2024

First Posted

May 17, 2024

Study Start

September 16, 2024

Primary Completion (Estimated)

August 1, 2026

Study Completion (Estimated)

September 1, 2026

Last Updated

March 23, 2026

Record last verified: 2026-03

Data Sharing

IPD Sharing
Will not share

Locations