{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T23:42:45Z","timestamp":1769470965413,"version":"3.49.0"},"reference-count":43,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T00:00:00Z","timestamp":1769385600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Children with rare tumours and malformations may benefit from innovative imaging, including patient-specific 3D models that can enhance communication and surgical planning. The primary aim was to evaluate the impact of patient-specific 3D models on communication with families. The secondary aims were to assess their influence on medical management and to establish an efficient post-processing workflow. From 2021 to 2024, we prospectively included patients aged 3 months to 18 years with rare tumours or malformations. Families completed questionnaires before and after the presentation of a 3D model generated from MRI sequences, including peripheral nerve tractography. Treating physicians completed a separate questionnaire before surgical planning. Analyses were performed in R. Among 21 patients, diagnoses included 11 tumours, 8 malformations, 1 trauma, and 1 pancreatic pseudo-cyst. Likert scale responses showed improved family understanding after viewing the 3D model (mean score 3.94 to 4.67) and a high overall evaluation (mean 4.61). Physicians also rated the models positively. An efficient image post-processing workflow was defined. Although manual 3D reconstruction remains time-consuming, these preliminary results show that colourful, patient-specific 3D models substantially improve family communication and support clinical decision-making. They also highlight the need for supporting the development of MRI-based automated segmentation softwares using deep neural networks, which are clinically approved and usable in routine practice.<\/jats:p>","DOI":"10.3390\/jimaging12020056","type":"journal-article","created":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T12:41:16Z","timestamp":1769431276000},"page":"56","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Use of Patient-Specific 3D Models in Paediatric Surgery: Effect on Communication and Surgical Management"],"prefix":"10.3390","volume":"12","author":[{"given":"C\u00e9cile O.","family":"Muller","sequence":"first","affiliation":[{"name":"Paediatric Surgery Department, Cantonal Hospital Aarau, Tellstrasse 25, 5001 Aarau, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lydia","family":"Helbling","sequence":"additional","affiliation":[{"name":"Paediatric Surgery Department, Cantonal Hospital Aarau, Tellstrasse 25, 5001 Aarau, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Theodoros","family":"Xydias","sequence":"additional","affiliation":[{"name":"Paediatric Radiology Department, Cantonal Hospital Aarau, Tellstrasse 25, 5001 Aarau, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeanette","family":"Greiner","sequence":"additional","affiliation":[{"name":"Paediatric Oncology Department, Cantonal Hospital Aarau, Tellstrasse 25, 5001 Aarau, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Val\u00e9rie","family":"Oesch","sequence":"additional","affiliation":[{"name":"Paediatric Surgery Department, Cantonal Hospital Aarau, Tellstrasse 25, 5001 Aarau, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3197-329X","authenticated-orcid":false,"given":"Henrik","family":"K\u00f6hler","sequence":"additional","affiliation":[{"name":"Paediatric Department, Cantonal Hospital Aarau, Tellstrasse 25, 5001 Aarau, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tim","family":"Ohletz","sequence":"additional","affiliation":[{"name":"Radiology Department and 3D Lab, Cantonal Hospital Aarau, Tellstrasse 25, 5001 Aarau, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6551-8308","authenticated-orcid":false,"given":"Jatta","family":"Berberat","sequence":"additional","affiliation":[{"name":"Neuroradiology Department, Cantonal Hospital Aarau, Tellstrasse 25, 5001 Aarau, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1038\/s41746-024-01413-0","article-title":"Digital Twin Assisted Surgery, Concept, Opportunities, and Challenges","volume":"8","author":"Asciak","year":"2025","journal-title":"NPJ Digit. 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