Klinische Evaluierung algorithmisch-semi-automatischer Open Source Software Segmentierung des Unterkiefers
Organizational Data
- DRKS-ID:
- DRKS00014337
- Recruitment Status:
- Recruiting complete, study complete
- Date of registration in DRKS:
- 2018-05-04
- Last update in DRKS:
- 2024-02-15
- Registration type:
- Retrospective
Acronym/abbreviation of the study
enFaced
URL of the study
https://www.tugraz.at/index.php?id=26448
Brief summary in lay language
Computer-assistierte Technologien wie die bild-basierte automatische Segmentierung spielen eine wichtige Rolle in der Unterstützung der Diagnosestellung und Therapieplanung im Fachbereich der Mund-, Kiefer- und Gesichtschirurgie. Obwohl zahlreiche derartige bild-basierte Segmentierungsmethoden existieren, ist deren klinische Anwendung oft auf Grund von technischen, humanen oder finanziellen Ressourcen stark limitiert. Dies gilt speziell für frei-zugängliche und lizenzfreie Segmentierungsmethoden in Bezug auf eine systematische Evaluierung. Das Ziel dieser Studie ist daher die Beurteilung der tatsächlichen Segmentierungsqualität einer gewöhnlich-verfügbaren und lizenzfreien automatischen Segmentierungsmethode im Unterkiefer. Die Beurteilung erfolgt anhand eines Vergleiches zwischen segmentierten CT-Bilddaten des Unterkiefers. Segmentierte patienten-spezifische klinische Bilddaten erstellt von einem automatischen Segmentierungsalgorithmus werden mit manuellen Ground Truth Segmentierungen erstellt von klinischen Experten verglichen. Beurteilungsparameter sind unter anderem der Dice Score Coefficient (DSC, %) und die Hausdorff Distance (HD, Voxel). Diese Studie ist ein systematischer Vergleich einer lizenzfreien, frei-zugänglichen Segmentierungsmethode im Unterkiefer auf Basis von klinischen CT-Daten zur Verbesserung von Segmentierungsalgorithmen und einer potentiellen klinischen Anwendung im Bereich der patienten-individualisierten Medizin im Fachgebiet der Mund-, Kiefer- und Gesischtschirugie. Des Weiteren, sind die Ergebnisse dieser Studie reproduzierbar für andere und können sowohl für klinische, als auch wissenschaftliche Zwecke verwendet werden.
Brief summary in scientific language
Computer-assisted technologies such as image-based segmentation play an important in the diagnosis and treatment support in oral- and maxillofacial surgery. However, although many image-based segmentation approaches exist, their clinical in-house use is often strongly limited due to technical, human or financial resources. Especially in open-source based segmentation, systematic evaluations of segmentation approaches are lacking. Therefore, the aim of this study is to assess the real segmentation quality of a commonly available and license-free segmentation method in the mandible. The assessment is done in a comparison between segmented CT-image data of the mandible. Segmented patient-specific clinical image data performed by an automatic segmentation algorithm are compared with the manual ground truth segmentations performed by clinical experts. Assessment parameters are amongst others the Dice Score Coefficient (DSC, %) and the Hausdorff Distance (HD, voxel). This study is a systematic comparison that evaluates a license-free, open-source segmentation approach in the mandible based on clinical CT-data for the improvement of segmentation algorithms and a potential clinical use in patient-individualized medicine in the field of oral and maxillofacial surgery. Further, the results presented are reproducible by others and can be used for both clinical and research purposes.
Health condition or problem studied
- Free text:
- bone fracture, bone defect
- Healthy volunteers:
- No Entry
Interventions, Observational Groups
- Arm 1:
- Establishment of a CT database of the mandible with datasets from the clinical routine for the evaluation of an image-based computer program.
Endpoints
- Primary outcome:
- Comparison image based segmentation of lower jaw CT-data between automatic (algorithm) vs. manual (clinical experts) at measurement point T by Hausdorff Distance (HD, voxel) and Dice Similarity Score (DSC, %).
- Secondary outcome:
- Comparison image based segmentation of lower jaw CT-data between automatic (algorithm) vs. manual (clinical experts) at measurement point T by Volume (V, mm3), Voxel (Vx, Number), time (t, min., sec.).
Study Design
- Purpose:
- Basic research/physiological study
- Retrospective/prospective:
- No Entry
- Study type:
- Non-interventional
- Longitudinal/cross-sectional:
- No Entry
- Study type non-interventional:
- No Entry
Recruitment
- Recruitment Status:
- Recruiting complete, study complete
- Reason if recruiting stopped or withdrawn:
- No Entry
Recruitment Locations
- Recruitment countries:
-
- Austria
- Number of study centers:
- Monocenter study
- Recruitment location(s):
-
- Medical center Medizinische Universität Graz Graz
Recruitment period and number of participants
- Planned study start date:
- 2018-07-01
- Actual study start date:
- 2017-04-01
- Planned study completion date:
- No Entry
- Actual Study Completion Date:
- 2019-05-06
- Target Sample Size:
- 10
- Final Sample Size:
- 10
Inclusion Criteria
- Sex:
- All
- Minimum Age:
- 18 Years
- Maximum Age:
- 99 Years
- Additional Inclusion Criteria:
- • Physiologically functional, complete lower jawbones • Age ≥18 Years • Age <99 Years • Data due to the medical indication in the clinical diagnostic at the department of Oral and maxillofacial surgery
Exclusion Criteria
• Implants or osteosynthesis material • Age <18 Years • Lower jawbone necrosis or pathologic-cystic changes of the bones
Addresses
Primary Sponsor
- Address:
- Medizinische Universität GrazDDDr. Jürgen WallnerAuenbrugger Platz 18036 GrazAustria
- Telephone:
- 004331638530193
- Fax:
- No Entry
- Contact per E-Mail:
- Contact per E-Mail
- URL:
- http://www.lkh-graz.at; www.medunigraz.at
- Investigator Sponsored/Initiated Trial (IST/IIT):
- Yes
Contact for Scientific Queries
- Address:
- Medizinische Universität GrazDDDr. Jürgen WallnerAuenbruggerplatz 5/18036 GrazAustria
- Telephone:
- +43/316/385-12428
- Fax:
- No Entry
- Contact per E-Mail:
- Contact per E-Mail
- URL:
- https://www.medunigraz.at/en/
Contact for Public Queries
- Address:
- Medizinische Universität GrazDDDr. Jürgen WallnerAuenbruggerplatz 5/18036 GrazAustria
- Telephone:
- +43/316/385-12428
- Fax:
- No Entry
- Contact per E-Mail:
- Contact per E-Mail
- URL:
- https://www.medunigraz.at/en/
Principal Investigator
- Address:
- Medizinische Universität GrazDDDr. Jürgen WallnerAuenbruggerplatz 5/18036 GrazAustria
- Telephone:
- +43/316/385-12428
- Fax:
- No Entry
- Contact per E-Mail:
- Contact per E-Mail
- URL:
- https://www.medunigraz.at/en/
Sources of Monetary or Material Support
Public funding institutions financed by tax money/Government funding body (German Research Foundation (DFG), Federal Ministry of Education and Research (BMBF), etc.)
- Address:
- Austrian Science Fund (FWF) KLI 678-B31: “enFaced: Virtual and Augmented Reality Training and Navigation Module for 3D-Printed Facial Defect Reconstructions” (PIs: Jürgen Wallner and Jan Egger)1090 WienAustria
- Telephone:
- No Entry
- Fax:
- No Entry
- Contact per E-Mail:
- Contact per E-Mail
- URL:
- No Entry
Public funding institutions financed by tax money/Government funding body (German Research Foundation (DFG), Federal Ministry of Education and Research (BMBF), etc.)
- Address:
- Fonds zur Förderung der wissenschaftlichen Forschung (FWF)Sensengasse 11090 WienAustria
- Telephone:
- No Entry
- Fax:
- No Entry
- Contact per E-Mail:
- Contact per E-Mail
- URL:
- https://www.fwf.ac.at/
Ethics Committee
Address Ethics Committee
- Address:
- Ethikkommission der Medizinischen Universität GrazAuenbruggerplatz 28036 GrazGermany
- Telephone:
- (+43)316-38513928
- Fax:
- (+43)316-38514348
- Contact per E-Mail:
- Contact per E-Mail
- URL:
- No Entry
Vote of leading Ethics Committee
- Vote of leading Ethics Committee
- Date of ethics committee application:
- 2016-11-29
- Ethics committee number:
- EK-29-143 ex 16/17
- Vote of the Ethics Committee:
- Approved
- Date of the vote:
- 2017-02-03
Further identification numbers
- Other primary registry ID:
- No Entry
- EudraCT Number:
- No Entry
IPD - Individual Participant Data
- Do you plan to make participant-related data (IPD) available to other researchers in an anonymized form?:
- Yes
- IPD Sharing Plan:
- Data obtained through this study may be provided to qualified researchers with academic interest to this study. Data or samples shared will be anonymized and shared according to the internal review board approval of this study.
Study protocol and other study documents
- Study protocols:
- No Entry
- Study abstract:
- No Entry
- Other study documents:
- No Entry
- Background literature:
- No Entry
- Related DRKS studies:
- No Entry
Publication of study results
- Planned publication:
- 2018
- Publikationen/Studienergebnisse:
- Wallner J, Hochegger K, Chen X, Mischak I, Reinbacher K, Pau M, Zrnc T, Schwenzer-Zimmerer K, Zemann W, Schmalstieg D, Egger J. Clinical evaluation of semi-automatic open-source algorithmic software segmentation of the mandibular bone: Practical feasibility and assessment of a new course of action. PLoS One. 2018 May 10;13(5):e0196378. doi: 10.1371/journal.pone.0196378. PMID: 29746490; PMCID: PMC5944980.
- Date of first publication of study results:
- 2018-05-02
- DRKS entry published for the first time with results:
- 2024-02-05
Basic reporting
- Basic Reporting / Results tables:
- Jürgen Wallner, Plos One, 2018
- Brief summary of results:
- No Entry