RSIP Vision spinoff XPlan.ai is highlighting a new milestone for its x-ray-based 3D bone modeling system with the publication of a peer-reviewed clinical study published in the Journal of Clinical Medicine.
The study, led by a consortium of orthopedic surgeons, found that XPlan.ai offers a promising alternative to conventional CT scans. XPlan.ai uses AI to produce 3D bone models from two standard x-ray images. Together with XPlan's automated planning technologies, this model can be used for surgical planning and navigation during orthopedic procedures such as total knee replacement.
The company highlighted that the accuracy of the tool was proven in the study by comparing the 3D models to the ground truth patient anatomy given in a corresponding CT scan. The accuracy was measured in multiple areas used for actual surgical planning, including bony landmarks and anatomical axes, and it was found to be equivalent to CT-based measurements at a sub-mm level.
XPlan.ai said it plans to apply for clearance of its knee reconstruction product by the U.S. Food and Drug Administration (FDA). It is also developing applications for additional anatomies, with initial results indicating wide applicability of XPlan's unique technology.
![Representative example of a 16-year-old male patient with underlying X-linked adrenoleukodystrophy. (A, B) Paired anteroposterior (AP) chest radiograph and dual-energy x-ray absorptiometry (DXA) report shows lumbar spine (L1 through L4) areal bone mineral density (BMD). The DXA report was reformatted for anonymization and improved readability. The patient had low BMD (Z score ≤ −2.0). (C) Model (chest radiography [CXR]–BMD) output shows the predicted raw BMD and Z score in comparison with the DXA reference standard, together with interpretability analyses using Shapley additive explanations (SHAP) and gradient-weighted class activation maps. The patient was classified as having low BMD, consistent with the reference standard. AM = age-matched, DEXA = dual-energy x-ray absorptiometry, RM2 = room 2, SNUH = Seoul National University Hospital, YA = young adult.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/04/ai-children-bone-density.0snnf2EJjr.jpg?auto=format%2Ccompress&fit=crop&h=100&q=70&w=100)
![Representative example of a 16-year-old male patient with underlying X-linked adrenoleukodystrophy. (A, B) Paired anteroposterior (AP) chest radiograph and dual-energy x-ray absorptiometry (DXA) report shows lumbar spine (L1 through L4) areal bone mineral density (BMD). The DXA report was reformatted for anonymization and improved readability. The patient had low BMD (Z score ≤ −2.0). (C) Model (chest radiography [CXR]–BMD) output shows the predicted raw BMD and Z score in comparison with the DXA reference standard, together with interpretability analyses using Shapley additive explanations (SHAP) and gradient-weighted class activation maps. The patient was classified as having low BMD, consistent with the reference standard. AM = age-matched, DEXA = dual-energy x-ray absorptiometry, RM2 = room 2, SNUH = Seoul National University Hospital, YA = young adult.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/04/ai-children-bone-density.0snnf2EJjr.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
