Artificial Intelligence and Robotics in Spine Surgery

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Study Design:

Narrative review.

Objectives:

Artificial intelligence (AI) and machine learning (ML) have emerged as disruptive technologies with the potential to drastically affect clinical decision making in spine surgery. AI can enhance the delivery of spine care in several arenas: (1) preoperative patient workup, patient selection, and outcome prediction; (2) quality and reproducibility of spine research; (3) perioperative surgical assistance and data tracking optimization; and (4) intraoperative surgical performance. The purpose of this narrative review is to concisely assemble, analyze, and discuss current trends and applications of AI and ML in conventional and robotic-assisted spine surgery.

Methods:

We conducted a comprehensive PubMed search of peer-reviewed articles that were published between 2006 and 2019 examining AI, ML, and robotics in spine surgery. Key findings were then compiled and summarized in this review.

Results:

The majority of the published AI literature in spine surgery has focused on predictive analytics and supervised image recognition for radiographic diagnosis. Several investigators have studied the use of AI/ML in the perioperative setting in small patient cohorts; pivotal trials are still pending.

Conclusions:

Artificial intelligence has tremendous potential in revolutionizing comprehensive spine care. Evidence-based, predictive analytics can help surgeons improve preoperative patient selection, surgical indications, and individualized postoperative care. Robotic-assisted surgery, while still in early stages of development, has the potential to reduce surgeon fatigue and improve technical precision.

Related collections

Most cited references 61

Record: found
Abstract: found
Article: not found

Magnetic resonance classification of lumbar intervertebral disc degeneration.

C Pfirrmann, A Metzdorf, M. Zanetti … (2001)

A reliability study was conducted. To develop a classification system for lumbar disc degeneration based on routine magnetic resonance imaging, to investigate the applicability of a simple algorithm, and to assess the reliability of this classification system. A standardized nomenclature in the assessment of disc abnormalities is a prerequisite for a comparison of data from different investigations. The reliability of the assessment has a crucial influence on the validity of the data. Grading systems of disc degeneration based on state of the art magnetic resonance imaging and corresponding reproducibility studies currently are sparse. A grading system for lumbar disc degeneration was developed on the basis of the literature. An algorithm to assess the grading was developed and optimized by reviewing lumbar magnetic resonance examinations. The reliability of the algorithm in depicting intervertebral disc alterations was tested on the magnetic resonance images of 300 lumbar intervertebral discs in 60 patients (33 men and 27 women) with a mean age of 40 years (range, 10-83 years). All scans were analyzed independently by three observers. Intra- and interobserver reliabilities were assessed by calculating kappa statistics. There were 14 Grade I, 82 Grade II, 72 Grade III, 68 Grade IV, and 64 Grade V discs. The kappa coefficients for intra- and interobserver agreement were substantial to excellent: intraobserver (kappa range, 0.84-0.90) and interobserver (kappa range, 0.69-0.81). Complete agreement was obtained, on the average, in 83.8% of all the discs. A difference of one grade occurred in 15.9% and a difference of two or more grades in 1.3% of all the cases. Disc degeneration can be graded reliably on routine T2-weighted magnetic resonance images using the grading system and algorithm presented in this investigation.

0 comments Cited 596 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Using and Reporting the Delphi Method for Selecting Healthcare Quality Indicators: A Systematic Review

Rym Boulkedid, Hendy Abdoul, Marine Loustau … (2011)

Objective Delphi technique is a structured process commonly used to developed healthcare quality indicators, but there is a little recommendation for researchers who wish to use it. This study aimed 1) to describe reporting of the Delphi method to develop quality indicators, 2) to discuss specific methodological skills for quality indicators selection 3) to give guidance about this practice. Methodology and Main Finding Three electronic data bases were searched over a 30 years period (1978–2009). All articles that used the Delphi method to select quality indicators were identified. A standardized data extraction form was developed. Four domains (questionnaire preparation, expert panel, progress of the survey and Delphi results) were assessed. Of 80 included studies, quality of reporting varied significantly between items (9% for year's number of experience of the experts to 98% for the type of Delphi used). Reporting of methodological aspects needed to evaluate the reliability of the survey was insufficient: only 39% (31/80) of studies reported response rates for all rounds, 60% (48/80) that feedback was given between rounds, 77% (62/80) the method used to achieve consensus and 57% (48/80) listed quality indicators selected at the end of the survey. A modified Delphi procedure was used in 49/78 (63%) with a physical meeting of the panel members, usually between Delphi rounds. Median number of panel members was 17(Q1:11; Q3:31). In 40/70 (57%) studies, the panel included multiple stakeholders, who were healthcare professionals in 95% (38/40) of cases. Among 75 studies describing criteria to select quality indicators, 28 (37%) used validity and 17(23%) feasibility. Conclusion The use and reporting of the Delphi method for quality indicators selection need to be improved. We provide some guidance to the investigators to improve the using and reporting of the method in future surveys.

0 comments Cited 371 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Trends, major medical complications, and charges associated with surgery for lumbar spinal stenosis in older adults.

Richard A Deyo (2010)

In recent decades, the fastest growth in lumbar surgery occurred in older patients with spinal stenosis. Trials indicate that for selected patients, decompressive surgery offers an advantage over nonoperative treatment, but surgeons often recommend more invasive fusion procedures. Comorbidity is common in older patients, so benefits and risks must be carefully weighed in the choice of surgical procedure. To examine trends in use of different types of stenosis operations and the association of complications and resource use with surgical complexity. Retrospective cohort analysis of Medicare claims for 2002-2007, focusing on 2007 to assess complications and resource use in US hospitals. Operations for Medicare recipients undergoing surgery for lumbar stenosis (n = 32,152 in the first 11 months of 2007) were grouped into 3 gradations of invasiveness: decompression alone, simple fusion (1 or 2 disk levels, single surgical approach), or complex fusion (more than 2 disk levels or combined anterior and posterior approach). Rates of the 3 types of surgery, major complications, postoperative mortality, and resource use. Overall, surgical rates declined slightly from 2002-2007, but the rate of complex fusion procedures increased 15-fold, from 1.3 to 19.9 per 100,000 beneficiaries. Life-threatening complications increased with increasing surgical invasiveness, from 2.3% among patients having decompression alone to 5.6% among those having complex fusions. After adjustment for age, comorbidity, previous spine surgery, and other features, the odds ratio (OR) of life-threatening complications for complex fusion compared with decompression alone was 2.95 (95% confidence interval [CI], 2.50-3.49). A similar pattern was observed for rehospitalization within 30 days, which occurred for 7.8% of patients undergoing decompression and 13.0% having a complex fusion (adjusted OR, 1.94; 95% CI, 1.74-2.17). Adjusted mean hospital charges for complex fusion procedures were US $80,888 compared with US $23,724 for decompression alone. Among Medicare recipients, between 2002 and 2007, the frequency of complex fusion procedures for spinal stenosis increased while the frequency of decompression surgery and simple fusions decreased. In 2007, compared with decompression, simple fusion and complex fusion were associated with increased risk of major complications, 30-day mortality, and resource use.

0 comments Cited 157 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Journal ID (nlm-ta): Global Spine J

Journal ID (iso-abbrev): Global Spine J

Journal ID (publisher-id): GSJ

Journal ID (hwp): spgsj

Title: Global Spine Journal

Publisher: SAGE Publications (Sage CA: Los Angeles, CA )

ISSN (Print): 2192-5682

ISSN (Electronic): 2192-5690

Publication date (Electronic): 1 April 2020

Publication date (Print): May 2021

Volume: 11

Issue: 4

Pages: 556-564

Affiliations

[1 ]Ringgold 2569, universityCleveland Clinic; , Cleveland, OH, USA

[2 ]Ringgold 5925, universityIcahn School of Medicine at Mount Sinai; , New York, NY, USA

[3 ]Ringgold 384840, universityMayo Clinic Scottsdale; , Scottsdale, AZ, USA

Author notes

[*]Jonathan J. Rasouli, Cleveland Clinic, Center for Spine Health, Desk S40, Cleveland, OH 44195, USA. Email: rasoulj@ 123456ccf.org

Author information

Jonathan J. Rasouli https://orcid.org/0000-0002-5085-8422

Article

Publisher ID: 10.1177_2192568220915718

DOI: 10.1177/2192568220915718

PMC ID: 8119909

PubMed ID: 32875928

SO-VID: ce35b568-7aec-4dc8-9523-9f00c51c05e4

License:

This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License ( https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits non-commercial use, reproduction and distribution of the work as published without adaptation or alteration, without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

History

Custom metadata

typesetter ts3

Keywords: artificial intelligence,machine learning,spine surgery,robotic spine surgery,radiology,review

Data availability:

Keywords: artificial intelligence, machine learning, spine surgery, robotic spine surgery, radiology, review

Artificial Intelligence and Robotics in Spine Surgery

Read this article at

Abstract

Study Design:

Objectives:

Methods:

Results:

Conclusions:

Related collections

Annual Reviews AI, Machine Learning, and Society

Most cited references 61

Magnetic resonance classification of lumbar intervertebral disc degeneration.

Using and Reporting the Delphi Method for Selecting Healthcare Quality Indicators: A Systematic Review

Trends, major medical complications, and charges associated with surgery for lumbar spinal stenosis in older adults.

Author and article information

Journal

Affiliations

Author notes

Author information

Article

History

Categories

Custom metadata

Comments

Comment on this article

Similar content 215

Cited by 22

Most referenced authors 617