Does volumetric measurement serve as an imaging biomarker for tumor aggressiveness of ameloblastomas?

Safi, Ali-Farid; Kauke, Martin; Timmer, Marco; Grandoch, Andrea; Nickenig, Hans-Joachim; Gültekin, Elif; Büttner, Reinhard; Kreppel, Matthias; Zöller, Joachim E.

doi:10.1016/j.oraloncology.2018.01.002

Cited by 5 publications

(6 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The three most commonly surgically treated odontogenic tumours are ameloblastoma, the keratocystic odontogenic tumour and OM. 5,7,23 For diagnostics and therapeutic planning, a method that reliably delineates the extent of an osteolytic jaw lesions and simultaneously allows for the relative visualization of surrounding healthy tissue is indispensable for guidance of the managing craniomaxillofacial surgeon. This is of utmost importance in the context of pre-surgical planning of osseous reconstructive procedures.…”

Section: Discussionmentioning

confidence: 99%

“…Hence, we considered patients who have been diagnosed with either one of the two most common odontogenic cysts (periapical and dentigerous) or with one of the three most common potentially infiltrative odontogenic tumours [ameloblastoma, keratocystic odontogenic tumour, odontogenic myxoma (OM)] by histopathological, radiological and clinical means. 4,5,7,15 Each individual received pre-operative diagnostics according to a standardized imaging protocol as well as therapeutic assessment between 2007 and 2017. Due to the retrospective nature of this study, it was granted an exemption in writing by the University Hospital IRB.…”

Section: Patientsmentioning

confidence: 99%

“…10 Multiple consecutive studies confirmed these results. [4][5][6][7][16][17][18][19][20] Maximum tumour diameter and formula-based volume approximation With the help of ITK-SNAP, we manually measured the three maximum orthogonal tumour diameters in centimeters (cm) in anteroposterior, mediolateral and craniocaudal direction. The measurement was automatically indicated by the program in millimeters.…”

Section: Image Segmentationmentioning

confidence: 99%

“…The size is frequently taken as a surrogate for the aggressiveness and respectively the growth potential of a lesion, thereby constituting an imaging biomarker. [4][5][6][7] Importantly, in the context of pharmaceutically targeted therapy of neoplasms in general, radiological size delineation is important in order to quantify the therapeutic success as judged by neoplastic disease regression. Pharmaceutically targeted therapy of ameloblastomas, the most prevalent neoplastic odontogenic tumour, with BRAF-inhibitors has made it to clinical trials.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Image segmentation-based volume approximation—volume as a factor in the clinical management of osteolytic jaw lesions

Kauke

Safi

Grandoch

et al. 2019

Dentomaxillofacial Radiology

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Patientsmentioning

confidence: 99%

Section: Image Segmentationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Image segmentation-based volume approximation—volume as a factor in the clinical management of osteolytic jaw lesions

Kauke

Safi

Grandoch

et al. 2019

Dentomaxillofacial Radiology

Self Cite

View full text Add to dashboard Cite

show abstract

“…Nevertheless, only relying on these features is insufficient to obtain a strong differential diagnosis. Previous studies have sought more instrumental radiographic findings, such as the width-to-length ratio, volumetric measurement, and assessment of the Hounsfield unit, to distinguish these two lesions (9)(10)(11). However, these studies have the same limitation in that they only focused on low-level and limited features.…”

Section: Introductionmentioning

confidence: 99%

Improved Diagnostic Accuracy of Ameloblastoma and Odontogenic Keratocyst on Cone-Beam CT by Artificial Intelligence

et al. 2022

View full text Add to dashboard Cite

ObjectiveThe purpose of this study was to utilize a convolutional neural network (CNN) to make preoperative differential diagnoses between ameloblastoma (AME) and odontogenic keratocyst (OKC) on cone-beam CT (CBCT).MethodsThe CBCT images of 178 AMEs and 172 OKCs were retrospectively retrieved from the Hospital of Stomatology, Wuhan University. The datasets were randomly split into a training dataset of 272 cases and a testing dataset of 78 cases. Slices comprising lesions were retained and then cropped to suitable patches for training. The Inception v3 deep learning algorithm was utilized, and its diagnostic performance was compared with that of oral and maxillofacial surgeons.ResultsThe sensitivity, specificity, accuracy, and F1 score were 87.2%, 82.1%, 84.6%, and 85.0%, respectively. Furthermore, the average scores of the same indexes for 7 senior oral and maxillofacial surgeons were 60.0%, 71.4%, 65.7%, and 63.6%, respectively, and those of 30 junior oral and maxillofacial surgeons were 63.9%, 53.2%, 58.5%, and 60.7%, respectively.ConclusionThe deep learning model was able to differentiate these two lesions with better diagnostic accuracy than clinical surgeons. The results indicate that the CNN may provide assistance for clinical diagnosis, especially for inexperienced surgeons.

show abstract

Accuracy of formula-based volume and image segmentation-based volume in calculation of preoperative cystic jaw lesions’ volume

El-beblawy,

Bakry,

Mohamed

2023

Oral Radiol

View full text Add to dashboard Cite

Objective The aim of this study was to assess the accuracy of formula-based volume measurements and the 3D volume analysis with different software packages in the calculation of preoperative cystic jaw lesions’ volume. The secondary aim was to assess the reliability and the accuracy of 3 imaging software programs for measuring the cystic jaw lesions' volume in CBCT images. Materials and methods This study consisted of two parts: an in vitro part using 2 dry human mandibles that were used to create simulated osteolytic lesions to assess the accuracy of the volumetric analysis and formula-based volume. As a gold standard, the volume of each bone defect was determined by taking an impression using rapid soft silicone (Vinylight) and then quantifying the volume of the replica. Afterward, each tooth socket was scanned using a high-resolution CBCT. A retrospective part using archived CBCT radiographs that were taken from the database of the outpatient clinic of the oral and maxillofacial radiology department, Faculty of Dentistry, Minia University to assess the reliability of the 3 software packages. The volumetric data set was exported for volume quantification using the 3 software packages (MIMICS-OnDemand and InVesalius software). Also, the three greatest orthogonal diameters of the lesions were calculated, and the volume was assessed using the ellipsoid formula. Dunn’s test was used for pair-wise comparisons when Friedman’s test was significant. The inter-examiner agreement was assessed using Cronbach’s alpha reliability coefficient and intra-class correlation coefficient. Results Regarding the results of the retrospective part, there was a statistically significant difference between volumetric measurements by equation and different software (P value < 0.001, Effect size = 0.513). The inter-observer reliability of the measurements of the cystic lesions using the different software packages was very good. The highest inter-examiner agreement for volume measurement was found with InVesalius (Cronbach’s alpha = 0.992). On the other hand, there was a statistically significant difference between dry mandible volumetric measurements and Gold Standard. All software showed statistically significantly lower dry mandible volumetric measurements than the gold standard. Conclusion Computer-aided assessment of cystic lesion volume using InVesalius, OnDemand, and MIMICS is a readily available, easy to use, non-invasive option. It confers an advantage over formula-based volume as it gives the exact morphology of the lesion so that potential problems can be detected before surgery. Volume analysis with InVesalius software was accurate in determining the volume of simulated periapical defects in a human cadaver mandible as compared to true volume. InVesalius software proved that open-source software can be robust yet user-friendly with the advantage of minimal cost to use.

show abstract

Does volumetric measurement serve as an imaging biomarker for tumor aggressiveness of ameloblastomas?

Cited by 5 publications

References 19 publications

Image segmentation-based volume approximation—volume as a factor in the clinical management of osteolytic jaw lesions

Image segmentation-based volume approximation—volume as a factor in the clinical management of osteolytic jaw lesions

Improved Diagnostic Accuracy of Ameloblastoma and Odontogenic Keratocyst on Cone-Beam CT by Artificial Intelligence

Accuracy of formula-based volume and image segmentation-based volume in calculation of preoperative cystic jaw lesions’ volume

Contact Info

Product

Resources

About