AI-driven spine-focused musculoskeletal management

Helen Gharaei , Pranshul Gupta , Ziba Bagherian , Sonal Mahalwar

Exploration of Musculoskeletal Diseases ›› 2026, Vol. 4 ›› Issue (1) : 1007126

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Exploration of Musculoskeletal Diseases ›› 2026, Vol. 4 ›› Issue (1) :1007126 DOI: 10.37349/emd.2026.1007126
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AI-driven spine-focused musculoskeletal management
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Abstract

Precision Spine Care integrates individualized diagnostics and interventions tailored to the unique anatomical and clinical characteristics of each patient. Recent advances in artificial intelligence (AI) and machine learning are addressing these challenges by enabling automated image interpretation, tissue segmentation, quantitative analysis of muscular and fascial features, and longitudinal tracking of structural and functional changes. These AI-driven capabilities support objective assessment, early detection of pathology, personalized rehabilitation planning, and continuous monitoring of treatment response. This approach becomes increasingly complex when incorporating advanced interventional techniques such as ultrasound-guided pain injections and AI tools. AI facilitates automated image interpretation, tissue characterization, and structure recognition, improving efficiency and diagnostic consistency. Augmented reality (AR) and mixed reality (MR) technologies enhance spatial orientation, procedural guidance, and anatomy education, while tele-ultrasound expands access to expert consultation, imaging support, and training in underserved regions. Although ultrasound remains operator dependent and AI outputs require ongoing physician oversight, the integration of ultrasound with AI, AR/MR, and telemedicine represents a significant advancement in spine care. These technologies complement traditional anatomical and clinical approaches, improving diagnostic accuracy, procedural precision, and personalized rehabilitation strategies. As healthcare systems face increasing demand and workforce constraints, technology-assisted ultrasound is positioned to play a pivotal role in advancing spine assessment, education, and comprehensive spine-focused musculoskeletal management. Ultimately, AI, ultrasound, and telemedicine serve to augment, not replace clinicians, enabling precision spine care that is safe, effective, and patient-centered.

Keywords

artificial intelligence / tele-ultrasound / spine / musculoskeletal

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Helen Gharaei, Pranshul Gupta, Ziba Bagherian, Sonal Mahalwar. AI-driven spine-focused musculoskeletal management. Exploration of Musculoskeletal Diseases, 2026, 4 (1) : 1007126 DOI:10.37349/emd.2026.1007126

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References

[1]

Seymour CW, Gomez H, Chang CH, Clermont G, Kellum JA, Kennedy J, et al. Precision medicine for all? Challenges and opportunities for a precision medicine approach to critical illness. Crit Care. 2017; 21: 257.

[2]

Pregelj L, Hwang TJ, Hine DC, Siegel EB, Barnard RT, Darrow JJ, et al. Precision Medicines Have Faster Approvals Based On Fewer And Smaller Trials Than Other Medicines. Health Aff. 2018; 37: 724-31.

[3]

Ashley EA. The Precision Medicine Initiative. JAMA. 2015; 313: 2119-20.

[4]

Samartzis D, Alini M, An HS, Karppinen J, Rajasekaran S, Vialle L, et al. Precision Spine Care: A New Era of Discovery, Innovation, and Global Impact. Glob Spine J. 2018; 8: 321-2.

[5]

Lian Y, Shi Y, Shang H, Zhan H. Predicting Treatment Outcomes in Patients with Low Back Pain Using Gene Signature-Based Machine Learning Models. Pain Ther. 2024; 14: 359-73.

[6]

Peng P, Soneji N. Ultrasound-Guided Intervention for Pain Management. Pain Manag. 2013; 4: 13-5.

[7]

Ergönenç T, Stockman J. New ultrasound-guided techniques in chronic pain management: an update. Curr Opin Anaesthesiol. 2021; 34: 634-40.

[8]

Rodríguez-Sanz J, Borrella-Andrés S, Pérez-Bellmunt A, Fernández-de-Las-Peñas C, Albarova-Corral I, López-de-Celis C, et al. Accuracy of Ultrasound-Guided Needle Placement on the L5 Lumbar Nerve Root. Am J Phys Med Rehabil. 2023; 102: 1091-6.

[9]

Li X, Zhang H, Zhang S, Wu M, Wang S, Tang Z, et al. Musculoskeletal ultrasound-guided needle knife therapy in the treatment of refractory nonspecific low back pain: A single-blind, randomized controlled trial. Medicine. 2024; 103: e41066.

[10]

Wang B, Sun Y, Zhang J, Meng H, Zhang H, Shan L. Ultrasound-guided versus fluoroscopy-guided lumbar selective nerve root block: a retrospective comparative study. Sci Rep. 2024; 14: 3235.

[11]

Gharaei H. Atlas of ultrasound guided Interfascial plane hydrodissection. Tehran: Arya Teb; 2024.

[12]

Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019; 25: 44-56.

[13]

Weiner EB, Dankwa-Mullan I, Nelson WA, Hassanpour S. Ethical challenges and evolving strategies in the integration of artificial intelligence into clinical practice. PLOS Digit Health. 2025; 4: e0000810.

[14]

Hallweaver M, McBeth C, Stolz L, Struder A, Schick M. Ultrasound in the Limited-Resource Setting: A Systematic Qualitative Review. Curr Radiol Rep. 2019; 7: e7.

[15]

Lai T, Stafinski T, Beach J, Menon D. Is remotely supervised ultrasound (tele-ultrasound) inferior to the traditional service model of ultrasound with an in-person imaging specialist? A systematic review. Ultrasound J. 2025; 17: 34.

[16]

Britton N, Miller MA, Safadi S, Siegel A, Levine AR, McCurdy MT. Tele-Ultrasound in Resource-Limited Settings: A Systematic Review. Front Public Health. 2019; 7: 244.

[17]

El-Tallawy SN, Pergolizzi JV, Vasiliu-Feltes I, Ahmed RS, LeQuang JK, El-Tallawy HN, et al. Incorporation of “Artificial Intelligence” for Objective Pain Assessment: A Comprehensive Review. Pain Ther. 2024; 13: 293-317.

[18]

Gunasekeran DV. Regulations for the development of deep technology applications in healthcare urgently needed to prevent abuse of vulnerable patients. BMJ Innov. 2018; 4: 111-2.

[19]

Ivanusic J, Cowie B, Barrington M. Undergraduate student perceptions of the use of ultrasonography in the study of “living anatomy”. Anat Sci Educ. 2010; 3: 318-22.

[20]

Rabie NZ, Sandlin AT, Barber KA, Ounpraseuth S, Nembhard W, Magann EF, et al. Teleultrasound: How Accurate Are We? J Ultrasound Med. 2017; 36: 2329-35.

[21]

Poland S, Frey JA, Khobrani A, Ondrejka JE, Ruhlin MU, George RL, et al. Telepresent Focused Assessment With Sonography for Trauma Examination Training Versus Traditional Training for Medical Students: A Simulation-Based Pilot Study. J Ultrasound Med. 2018; 37: 1985-92.

[22]

Drake AE, Hy J, MacDougall GA, Holmes B, Icken L, Schrock JW, et al. Innovations with tele-ultrasound in education sonography: the use of tele-ultrasound to train novice scanners. Ultrasound J. 2021; 13: 6.

[23]

Zhou YJ, Guo LH, Bo XW, Sun LP, Zhang YF, Chai HH, et al. Tele-Mentored Handheld Ultrasound System for General Practitioners: A Prospective, Descriptive Study in Remote and Rural Communities. Diagnostics. 2023; 13: 2932.

[24]

Eadie L, Mulhern J, Regan L, Mort A, Shannon H, Macaden A, et al. Remotely supported prehospital ultrasound: A feasibility study of real-time image transmission and expert guidance to aid diagnosis in remote and rural communities. J Telemed Telecare. 2017; 24: 616-22.

[25]

Cal EM, Gunnell E, Olinger K, Benefield T, Nelson J, Maggioncalda E, et al. Utility of tele-guidance for point-of-care ultrasound: a single center prospective diagnostic study. J Ultrasound. 2024; 27: 519-25.

[26]

Martinelli T, Bosson JL, Bressollette L, Pelissier F, Boidard E, Troccaz J, et al. Robot-Based Tele-Echography. J Ultrasound Med. 2007; 26: 1611-6.

[27]

Narouze S, Peng PW. Ultrasound-guided interventional procedures in pain medicine: a review of anatomy, sonoanatomy, and procedures. Part II: axial structures. Reg Anesth Pain Med. 2010; 35: 386-96.

[28]

Dinescu SC, Stoica D, Bita CE, Nicoara AI, Cirstei M, Staiculesc MA, et al. Applications of artificial intelligence in musculoskeletal ultrasound: narrative review. Front Med. 2023; 10: 1286085.

[29]

Hui X, Rajendran P, Ling T, Dai X, Xing L, Pramanik M. Ultrasound-guided needle tracking with deep learning: A novel approach with photoacoustic ground truth. Photoacoustics. 2023; 34: 100575.

[30]

Beigi P, Salcudean SE, Ng GC, Rohling R. Enhancement of needle visualization and localization in ultrasound. Int J Comput Assist Radiol Surg. 2021; 16: 169-78.

[31]

Esteva A, Robicquet A, Ramsundar B, Kuleshov V, DePristo M, Chou K, et al. A guide to deep learning in healthcare. Nat Med. 2019; 25: 24-9.

[32]

Saccenti L, Bessy H, Ben Jedidia B, Longere B, Tortolano L, Derbel H, et al. Performance Comparison of Augmented Reality Versus Ultrasound Guidance for Puncture: A Phantom Study. CardioVasc Interv Radiol. 2024; 47: 993-9.

[33]

Liao SC, Shao SC, Gao SY, Lai EC. Augmented reality visualization for ultrasound-guided interventions: a pilot randomized crossover trial to assess trainee performance and cognitive load. BMC Med Educ. 2024; 24: 1058.

[34]

Chien C, Lee K, Lau V. Real-time Ultrasound Fusion Imaging-Guided Interventions: a Review. Hong Kong J Radiol. 2021; 24: 116-24.

[35]

Borde T, Saccenti L, Li M, Varble NA, Hazen LA, Kassin MT, et al. Smart goggles augmented reality CT-US fusion compared to conventional fusion navigation for percutaneous needle insertion. Int J Comput Assist Radiol Surg. 2024; 20: 107-15.

[36]

Li F, Bi Y, Huang D, Jiang Z, Navab N. Robotic CBCT meets robotic ultrasound. Int J Comput Assist Radiol Surg. 2025; 20: 1049-57.

[37]

Holtz B, Mitchell K, Adams R, Grier C, Wright J. Enhancing comprehension of online informed consent: the impact of interactive elements and presentation formats. Ethics Behav. 2024; 35: 153-66.

[38]

Morley J, Machado CCV, Burr C, Cowls J, Joshi I, Taddeo M, et al. The ethics of AI in health care: A mapping review. Soc Sci Med. 2020; 260: 113172.

[39]

Banerjee S. A Framework for Designing Compassionate and Ethical Artificial Intelligence and Artificial Consciousness. Interdiscip Descr Complex Syst. 2020; 18: 85-95.

[40]

Ahmed L, Constantinidou A, Chatzittofis A. Patients’ perspectives related to ethical issues and risks in precision medicine: a systematic review. Front Med. 2023; 10: 1215663.

[41]

Banerjee A, Kamboj P, Gupta S. Framework for developing and evaluating ethical collaboration between expert and machine. arXiv:2411.10983 [Preprint]. 2024 [cited 2026 Mar 12]. Available from: https://doi.org/10.48550/arXiv.2411.10983

[42]

Haji-Hassan M, Călinici T, Drugan T, Bolboacă SD. Effectiveness of Ultrasound Cardiovascular Images in Teaching Anatomy: A Pilot Study of an Eight-Hour Training Exposure. Int J Environ Res Public Health. 2022; 19: 3033.

[43]

Tauben DJ, Langford DJ, Sturgeon JA, Rundell SD, Towle C, Bockman C, et al. Optimizing telehealth pain care after COVID-19. Pain. 2020; 161: 2437-45.

[44]

El-Tallawy SN, Perglozzi JV, Ahmed RS, Kaki AM, Nagiub MS, LeQuang JK, et al. Pain Management in the Post-COVID Era-An Update: A Narrative Review. Pain Ther. 2023; 12: 423-48.

[45]

Ghai B, Malhotra N, Bajwa SJS. Telemedicine for chronic pain management during COVID-19 pandemic. Indian J Anaesth. 2020; 64: 456-62.

[46]

Telemedicine for Pain Management: Where Does it Stand as We Head into 2023? [Internet]. HealthCentral LLC; c2022 [cited 2026 Mar 14]. Available from: https://www.medcentral.com/telemedicine/telemedicine-for-pain-management-where-does-it-stand-as-we-head-into-2023

[47]

Johnson CD, Davison L, Graham EC, Sweeney EM. Ultrasound technology as a tool to teach basic concepts of physiology and anatomy in undergraduate and graduate courses: a systematic review. Adv Physiol Educ. 2025; 49: 11-26.

[48]

Huang Y, Wee TC, Loh KJ, Tan YL. Use of Ultrasound to Enhance Musculoskeletal Palpation Skills of the Upper and Lower Limbs Anatomy: A Scoping Review. J Med Ultrasound. 2025; 34: 75-84.

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