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Inter and intra‐operator reliability of Lekholm and Zarb classification and proposal of a novel radiomic data‐driven clustering for qualitative assessment of edentulous alveolar ridges

Giuseppe Troiano
•
Antonio Rapani
•
Francesco Fanelli
altro
Claudio Stacchi
2024
  • journal article

Periodico
CLINICAL ORAL IMPLANTS RESEARCH
Abstract
Objectives: The present study was conducted to evaluate the reproducibility of Lekholm and Zarb classification system (L&Z) for bone quality assessment of edentulous alveolar ridges and to investigate the potential of a data-driven approach for bone quality classification. Materials and methods: Twenty-six expert clinicians were asked to classify 110 CBCT cross-sections according to L&Z classification (T0). The same evaluation was repeated after one month with the images put in a different order (T1). Intra- and inter-examiner agreement analyses were performed using Cohen's kappa coefficient (CK) and Fleiss' kappa coefficient (FK), respectively. Additionally, radiomic features extraction was performed from 3D edentulous ridge blocks derived from the same 110 CBCTs, and unsupervised clustering using 3 different clustering methods was used to identify patterns in the obtained data. Results: Intra-examiner agreement between T0 and T1 was weak (CK 0.515). Inter-examiner agreement at both time points was minimal (FK at T0: 0.273; FK at T1: 0.243). The three different unsupervised clustering methods based on radiomic features aggregated the 110 CBCTs in three groups in the same way. Conclusions: The results showed low agreement among clinicians when using L&Z classification, indicating that the system may not be as reliable as previously thought. The present study suggests the possible application of a reproducible data-driven approach based on radiomics for the classification of edentulous alveolar ridges, with potential implications for improving clinical outcomes. Further research is needed to determine the clinical significance of these findings and to develop more standardized and accurate methods for assessing bone quality of edentulous alveolar ridges.
DOI
10.1111/clr.14271
WOS
WOS:001204032700001
Archivio
https://hdl.handle.net/11368/3073059
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85190954718
https://onlinelibrary.wiley.com/doi/10.1111/clr.14271
Diritti
open access
license:creative commons
license uri:http://creativecommons.org/licenses/by-nc/4.0/
FVG url
https://arts.units.it/bitstream/11368/3073059/3/Clinical Oral Implants Res - 2024 - Troiano - Inter and intraâ operator reliability of Lekholm and Zarb classification and.pdf
Soggetti
  • artificial intelligen...

  • big data

  • bone

  • clustering

  • data mining

  • dental implant

  • osseointegration

  • radiomics

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