Integrated multivariate optimization of bone grinding parameters minimizing iatrogenic trauma and maximizing postoperative osteoregenerative efficacy

Integrated multivariate optimization of bone grinding parameters minimizing iatrogenic trauma and maximizing postoperative osteoregenerative efficacy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Integrated multivariate optimization of bone grinding parameters minimizing iatrogenic trauma and maximizing postoperative osteoregenerative efficacy Ali Akhondi, Vahid Tahmasbi, Mahdi Qasemi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7726368/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Bone grinding represents a technically demanding and clinically sensitive procedure integral to neurosurgical and spinal interventions, particularly in the context of lumbar disc decompression. The thermo-mechanical stresses incurred during this operation pose substantial risks to adjacent neurovascular and osseous tissues, with surface topography especially roughness playing a critical role in post-operative healing kinetics and tissue integration. This investigation employed Response Surface Methodology (RSM) via Minitab to rigorously evaluate the compounded effects of four machining parameters rotational speed, feed rate, depth of cut, and tool diameter on thermal generation, grinding force, and surface microgeometry. The thermometric analysis indicated a predominant influence of spindle speed, feed trajectory, and axial depth on temperature escalation, with the optimal thermal condition (29.40°C) achieved at 3000 rpm, 20 mm/min feed, 0.1 mm cutting depth, and 8 mm tool diameter. Grinding force exhibited multidimensional sensitivity, with a nadir of 0.54 N observed under 5000 rpm in a transverse cutting configuration relative to osteonal microarchitecture. Surface roughness was largely dictated by tool diameter, engagement depth, and anatomical cutting orientation, with an optimal Ra value of 0.57 µm attained under parallel osteonal alignment. Collectively, the results delineate a high-fidelity parametric framework for minimizing deleterious thermal loads and mechanical disruptions during bone grinding. This framework advances precision surgery protocols and promotes biomechanically favorable outcomes in osseous tissue manipulation. osseous abrasive machining thermomechanical load cutting force dynamics topographical surface integrity cortical skeletal substrate Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 16 Nov, 2025 Reviews received at journal 14 Nov, 2025 Reviews received at journal 09 Nov, 2025 Reviewers agreed at journal 05 Nov, 2025 Reviewers agreed at journal 03 Nov, 2025 Reviewers invited by journal 03 Nov, 2025 Editor assigned by journal 30 Sep, 2025 Submission checks completed at journal 30 Sep, 2025 First submitted to journal 27 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7726368","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":544006595,"identity":"d738f63d-f6ad-489d-981e-f29b70d4ab53","order_by":0,"name":"Ali Akhondi","email":"","orcid":"","institution":"Arak University Of Technology","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Akhondi","suffix":""},{"id":544006596,"identity":"49d2449e-3a4c-4fc6-8f24-2fa47e589e24","order_by":1,"name":"Vahid Tahmasbi","email":"","orcid":"","institution":"Arak University Of 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