Validation of BoneXpert in India
Dr Anuradha V. Khadilkar’s research group in Pune, India, has published a study of BoneXpert bone age, reporting its accuracy and presenting reference curves for Indian children.
External validation of commercial AI products
Kicky van Leeuwen and the AIR Working Group of Radboud University (Nijmegen, the Netherlands) have performed an external validation of commercial AI systems for bone age and lung nodules.
Swiss study compares two bone age algorithms
The accuracy of bone age determination by BoneXpert and Panda in 188 images was reported at ECR.
Federica Zanca from Leuven, together with four co-authors from Switzerland, presented a study comparing two bone age algorithms, BoneXpert from Visiana and Panda (based on deep learning) from ImageBiopsyLab. The study included 188 images taken under real-world conditions across 11 centres in Switzerland. The ground truth was provided by an exceptionally reliable manual rater. BoneXpert’s intended use includes autonomous use, while Panda’s is intended to only assist the radiologist. However, in this study, both algorithms were used without human interference.
The mean absolute deviation between the algorithm and the ground truth was 0.36 y for BoneXpert and 0.42 y for Panda, and this difference was significant with p=0.01.
In the Bland Altman plots below one can clearly see that the agreement is better with BoneXpert.
Figure 1: BoneXpert versus radiologist
Figure 2: Panda versus radiologist
The plots reveal that there are markedly fewer large deviations with BoneXpert.
So what is the clinical signficance of the different performance? The authors adressed this by defining the clinically acceptable limit of agreement to be ±1 year, and they found twice as many such significant deviations for Panda.
The table below summarises all the findings.
The poster is available though myESR (requiring log in)
Table: The deviation between the bone age algorithm and the radiologist
| BoneXpert | Panda | |
| Mean Absolute Deviation | 0.36 y | 0.42 y |
| Root Mean Square Deviation | 0.47 y | 0.55 y |
| Number of deviations > 1 y | 7 | 14 |
| Largest deviation | 1.2 y | 1.9 y |
BoneXpert knows its own limitation
A new paper documents BoneXpert’s accuracy and self-validation Read more “BoneXpert knows its own limitation”
BoneXpert is accurate in Moroccan children
A study from Queen Fabiola Children’s University Hospital in Brussels on the accuracy of bone age has been published.
New bone age reference curves from Taiwan
A new independent study has been published with bone age reference curves for healthy Taiwanese children.
New bone age reference curves from Mexico
A new independent study has been published with bone age reference curves for healthy Mexican children
RSNA challenge boosts automated bone age ratings
RNSA (The Radiological Society of North America) organized a machine learning challenge in bone age rating in 2017. This article reviews the challenge and explains its crucial role in boosting performance of BoneXpert in terms of bone age ratings.
Read more “RSNA challenge boosts automated bone age ratings”
