Evidence map›Paper›PMID 40689982›Full record

ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2025

Fully automated pedicle screw manufacturer identification in plain radiograph with deep learning methods.

Rattapoom Waranusast, Panomkhawn Riyamongkol, Santi Weerakul, Nattharut Chaibhuddanugul, Artit Laoruengthana, Akaworn Mahatthanatrakul

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Article in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Rattapoom WaranusastDepartment of Electrical and Computer Engineering, Faculty of Engineering, Naresuan University, Phitsanulok, Thailand.
Panomkhawn RiyamongkolDepartment of Electrical and Computer Engineering, Faculty of Engineering, Naresuan University, Phitsanulok, Thailand.
Santi WeerakulDepartment of Orthopaedics,Faculty of Medicine, Naresuan University, Phitsanulok, Thailand.
Nattharut ChaibhuddanugulDepartment of Orthopaedics,Faculty of Medicine, Naresuan University, Phitsanulok, Thailand.
Artit LaoruengthanaDepartment of Orthopaedics,Faculty of Medicine, Naresuan University, Phitsanulok, Thailand.
Akaworn MahatthanatrakulDepartment of Orthopaedics,Faculty of Medicine, Naresuan University, Phitsanulok, Thailand. akawornm@nu.ac.th.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPedicle screw manufacturer identification is crucial for revision surgery planning; however, this information is occasionally unavailable. We developed a deep learning-based algorithm to identify the pedicle screw manufacturer from plain radiographs.

methodsWe collected anteroposterior (AP) and lateral radiographs from 276 patients who had thoracolumbar spine surgery with pedicle screws from three international manufacturers. The samples were randomly assigned to training sets (178), validation sets (40), and test sets (58). The algorithm incorporated a convolutional neural network (CNN) model to classify the radiograph as AP and lateral, followed by YOLO object detection to locate the pedicle screw. Another CNN classifier model then identified the manufacturer of each pedicle screw in AP and lateral views. The voting scheme determined the final classification. For comparison, two spine surgeons independently evaluated the same test set, and the accuracy was compared.

resultsThe mean age of the patients was 59.5 years, with 1,887 pedicle screws included. The algorithm achieved a perfect accuracy of 100% for the AP radiograph, 98.9% for the lateral radiograph, and 100% when both views were considered. By comparison, the spine surgeons achieved 97.1% accuracy. Statistical analysis revealed near-perfect agreement between the algorithm and the surgeons.

conclusionWe have successfully developed an algorithm for pedicle screw manufacturer identification, which demonstrated excellent accuracy and was comparable to experienced spine surgeons.

Indexed as

Deep LearningLumbar VertebraePedicle ScrewsRadiographySpinal FusionThoracic VertebraeAdultAgedAlgorithmsFemaleHumansMaleMiddle AgedNeural Networks, ComputerComputer-Assisted radiographic image interpretationDeep learningMachine learningPedicle screw

Identifiers

PMID40689982

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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.