Vit Kotheeranurak, Jin-Sung Kim, Inbo Han, Hyeun-Sung Kim, Thanapol Ultarnpatumros, Chinati Puinongpo, Javier Quillo-Olvera, Lei Jiang, Christoph Siepe, Worawat Limthongkul, Weerasak Singhatanadgige, Surachat Jaroenwareekul
Neurospine 2026;23(3):605-624. Published online July 31, 2026
Objective Endoscopic spine surgery (ESS) has expanded rapidly, but existing spine registries do not consistently capture ESS-specific technical variables, ultra-early recovery trajectories, selective imaging validation, or dissemination-related learning-curve effects. This review synthesizes established spine registry models, contemporary consensus initiatives, and digital follow-up approaches to propose a candidate ESS-specific registry framework and preliminary Minimum Data Set (MDS) for future validation.
Methods A structured narrative review was conducted on national and multinational spine registries, relevant consensus initiatives, and digital follow-up models. Sources were reviewed with emphasis on governance, data architecture, workflow design, patient-reported outcome measures (PROMs) integration, follow-up structure, data linkage, validation strategies, and implementation feasibility.
Results Established registries provide a methodological foundation for benchmarking, complication surveillance, longitudinal PROM capture, and real-world evidence generation. However, ESS requires modular augmentation of existing registry infrastructures to capture approach-specific operative details, early recovery, selective imaging phenotypes, and governance-controlled maturity indicators. The proposed candidate MDS is organized into 4 domains: (1) baseline case-mix and phenotyping, (2) procedure-specific technical and perioperative variables, (3) selective quantitative imaging and morphometric validation, and (4) structured longitudinal outcome surveillance. The framework prioritizes an essential core dataset while separating recommended, optional, research-oriented, and governance-controlled modules, including digitally enabled early follow-up, opioid-related outcomes, radiation exposure, advanced imaging, and learning-curve variables.
Conclusion A candidate ESS-specific registry framework may support harmonized data capture, real-world evidence generation, quality feedback, and future registry-based research. Formal Delphi consensus, multicenter feasibility testing, and staged integration into existing spine registry infrastructures are required before broader implementation.
This study aimed to elucidate the efficacy and safety of mesenchymal stromal cell (MSC) therapy for chronic discogenic low back pain (LBP). A systematic literature search was conducted on PubMed/Medline, Scopus, Cochrane, and ClinicalTrials.gov following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) guidelines. Eligible studies included published and ongoing clinical trials assessing intradiscal MSC injections in patients with chronic discogenic LBP unresponsive to conservative treatment. Risk-of-bias (RoB) assessment was performed through MINORS (Methodological Index for Non-randomized Studies) and RoB 2 tools. Within- and between-group differences were expressed as means and 95% confidence intervals. Effect sizes were calculated through Cohen d and g. Data from 10 published clinical studies (n=736; 470 in treatment and 266 in control groups) revealed a mean age of 41.5 years and an average follow-up of 21.6 (range, 6–72) months. Various MSC sources were employed, including autologous and allogeneic bone marrow-derived MSCs and adipose-derived MSCs, with doses ranging from 6×10⁶ to over 50×10⁶ cells/disc. Visual analogue scale, Oswestry Disability Index, and quality-of-life questionnaires indicated modest improvements in pain, disability, and functional status. Additionally, magnetic resonance imaging assessments occasionally demonstrated increased disc hydration and stabilization or improvement of Pfirrmann grade. Data from 8 ongoing trials (n=498 participants; 276 treatment, 222 control) with follow-up periods ranging 6–24 months further corroborate the feasibility and safety of MSC-based interventions. MSC therapy is a biologically-driven approach for managing chronic discogenic LBP. While preliminary data support its potential to alleviate pain and improve disc integrity, further high-quality, standardized trials are necessary to optimize treatment protocols and confirm long-term clinical benefits.
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Objective To develop and evaluate a technique using convolutional neural networks (CNNs) for the computer-assisted diagnosis of cervical spine fractures from radiographic x-ray images. By leveraging deep learning techniques, the study might potentially lead to improved patient outcomes and clinical decision-making.
Methods This study obtained 500 lateral radiographic cervical spine x-ray images from standard open-source dataset repositories to develop a classification model using CNNs. All the images contained diagnostic information, including normal cervical radiographic images (n=250) and fracture images of the cervical spine fracture (n=250). The model would classify whether the patient had a cervical spine fracture or not. Seventy percent of the images were training data sets used for model training, and 30% were for testing. Konstanz Information Miner (KNIME)’s graphic user interface-based programming enabled class label annotation, data preprocessing, CNNs model training, and performance evaluation.
Results The performance evaluation of a model for detecting cervical spine fractures presents compelling results across various metrics. This model exhibits high sensitivity (recall) values of 0.886 for fractures and 0.957 for normal cases, indicating its proficiency in identifying true positives. Precision values of 0.954 for fractures and 0.893 for normal cases highlight the model’s ability to minimize false positives. With specificity values of 0.957 for fractures and 0.886 for normal cases, the model effectively identifies true negatives. The overall accuracy of 92.14% highlights its reliability in correctly classifying cases by the area under the receiver operating characteristic curve.
Conclusion We successfully used deep learning models for computer-assisted diagnosis of cervical spine fractures from radiographic x-ray images. This approach can assist the radiologist in screening, detecting, and diagnosing cervical spine fractures.
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Objective We aimed to comprehensively compare surgical methods for osteoporotic vertebral compression fracture (OVCF) using systematic review and network meta-analysis to understand their effectiveness and outcomes, as current research provides limited overviews.
Methods We followed PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines, preregistering our protocol with PROSPERO. We analyzed Englishpublished randomized controlled trials (RCTs) on adults with OVCFs that evaluated pain intensity or functionality using tools like visual analogue scale (VAS) or Oswestry Disability Index (ODI). Exclusions included non-RCTs, malignancy-related fractures, and certain interventions. Using the RoB 2 tool, we assessed bias and visualized results with Robvis. Our primary outcome was pain intensity, with secondary outcomes including disability, new fractures, and cement leakage. Results were synthesized using Stata/MP.
Results Thirty-four RCTs from 10 countries, totaling 4,384 patients, were analyzed. Shortterm VAS indicated kyphoplasty with facet joint injection (KIJ) as the top treatment at 87.7%, while unipedicular kyphoplasty (UKP) led to long-term at 74.9%. Short-term ODI favored vertebroplasty with facet joint injection (VIJ) at 98.4%, with kyphoplasty (KP) leading longterm at 66.0%. All surgical techniques were superior to conservative treatment. Vertebral augmentation devices reported the fewest new fractures and curved vertebroplasty had the least cement leakage. SUCRA (surface under the cumulative ranking) analyses suggested UKP and VIJ as top choices for postoperative pain relief, with VIJ excelling in postoperative disability improvement.
Conclusion Our analysis evaluates 12 OVCF interventions, underscoring KIJ for short-term pain relief and VIJ and UKP for long-term efficacy. Notably, VIJ stands out in disability outcomes, emphasizing the need for comprehensive OVCF management.
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