ArticleInternational journal of computer assisted radiology and surgery2026
Standardizing ACL tunnel placement: an automated method for knee quadrant computation.
Article in International journal of computer assisted radiology and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
purposeAnatomical tunnel placement in the anterior cruciate ligament (ACL) reconstruction is essential for better functional recovery and reduced complications. However, subjective factors and ambiguous definitions reduce the accuracy and efficiency of quantifying ACL position on 3D models. This study aims to develop and validate a fully automated framework for standardized 3D quadrant coordinate computation of femoral and tibial ACL footprints, enabling objective preoperative planning and postoperative evaluation.
methodsAn nnUNet-based foundation network was fine-tuned to reconstruct distal femur and proximal tibia 3D models from CT or MRI data. Automated template registration and morphological analysis were used to determine anatomical planes and generate individualized quadrant coordinate systems. The pipeline was validated on both CT and MRI datasets, comparing location accuracy, calculation repeatability, and time efficiency against manual methods.
resultsThe 3D distances between the actual and automatic predicted centroids were 1.72 ± 0.94 mm and 1.47 ± 1.06 mm for femur and tibia, respectively, while the errors of manual method were 1.89 ± 1.42 mm and 2.11 ± 1.27 mm. The method achieved an average repeatability of 0.992 in quadrant calculations with different initializations, while the ICCs of two manual annotation were 0.961 (A), 0.946 (B), and 0.882 (A&B). The processing time for generating quadrant coordinate systems was significantly reduced to an average of 4.7 ± 1.3 s, compared to 8.5 ± 2.1 min for manual annotation.
conclusionThis study presented the first fully automated, modality-independent method for 3D quadrant coordinate computation in knee surgery. The proposed framework delivers robust and standardized ACL anatomical locations across both CT and MRI data, enhancing the clinical efficiency of the preoperative planning and postoperative assessment of ACL reconstruction.
Indexed as
Identifiers
41739356What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.