Can artificial intelligence support or even replace physicians in measuring sagittal balance? A validation study on preoperative and postoperative full spine images of 170 patients

Grover, Priyanka; Siebenwirth, Jakob; Caspari, Christina; Drange, Steffen; Dreischarf, Marcel; Huec, Jean-Charles Le; Putzier, Michael; Franke, Jörg

doi:10.1007/s00586-022-07309-5

Cited by 13 publications

(8 citation statements)

References 24 publications

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“…It is able to calculate spinopelvic parameters and automatically segment vertebrae for its end users [32]. These measurements have excellent reliability and accuracy compared to expert human measurements [33][34][35][36]. Because AI is able to analyze advanced imaging on a pixel level, it can make granular assumptions about the data and modify the original image.…”

Section: Artificial Intelligencementioning

confidence: 99%

Emerging Technologies within Spine Surgery

Foley,

Hardacker,

McCarthy

2023

Life

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New innovations within spine surgery continue to propel the field forward. These technologies improve surgeons’ understanding of their patients and allow them to optimize treatment planning both in the operating room and clinic. Additionally, changes in the implants and surgeon practice habits continue to evolve secondary to emerging biomaterials and device design. With ongoing advancements, patients can expect enhanced preoperative decision-making, improved patient outcomes, and better intraoperative execution. Additionally, these changes may decrease many of the most common complications following spine surgery in order to reduce morbidity, mortality, and the need for reoperation. This article reviews some of these technological advancements and how they are projected to impact the field. As the field continues to advance, it is vital that practitioners remain knowledgeable of these changes in order to provide the most effective treatment possible.

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Section: Artificial Intelligencementioning

confidence: 99%

Emerging Technologies within Spine Surgery

Foley,

Hardacker,

McCarthy

2023

Life

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“…Many recent studies have been conducted on the development of AI-based software to automatically measure or assist in the numerical measurement of spine balance parameters to reduce the effort of manual measurements. [ 17 , 18 ] Considering this, our study may potentially provide the basis for such studies.…”

Section: Discussionmentioning

confidence: 95%

Analysis of sagittal parameters for easier and more accurate determination of cervical spine alignment

Oh,

Kim,

Lee

et al. 2023

Medicine

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Cross-sectional comparative study. This study aimed to analyze the role of cervical parameters, in terms of the perception process, when evaluating cervical sagittal balance on an X-ray image. Reports on the role of cervical parameters in the perception of cervical sagittal balance have not been made. The study included 4 board-certified neurosurgeons and 6 residents of a neurosurgical department. They were instructed to answer a total of 40 questions. The parameter that was the most helpful in deriving the answer was checked. The correct answer rate, dependency on the parameter, and correct answer contribution of the parameter were analyzed. Among the various parameters, 5 parameters [C2-7 angle (C2-7A), T1 slope minus cervical lordosis (T1s-CL), C2 slope (C2s), C7 slope (C7s), and C2-7 sagittal vertical axis) were selected. The simple parameter (C2s, C7s) has a higher dependency and correct answer contribution than the complex parameter (C2-7A, T1s-CL). The angular (C2-7A, T1s-CL, C2s, C7s) parameters have a higher dependency; however, both the length and angular parameters correct answer contribution were similar. The cervical parameters that have simpler properties were highly preferred and had a lower perception error.

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“…AI has also shown potential in imaging analysis. Grover et al [ 78 ] evaluated an AI-based algorithm for determining sagittal balance parameters in patients with and without spinal instrumentation. The algorithm demonstrated excellent agreement with human raters, particularly on preoperative images, suggesting its efficiency for large-scale imaging analysis.…”

Section: Artificial Intelligence In Predicting and Preventing Pjk/pjf...mentioning

confidence: 99%

Proximal Junctional Failure in Adult Spinal Deformity Surgery: An In-depth Review

Yagi,

Yamanouchi,

Fujita

et al. 2023

Neurospine

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Adult spinal deformity (ASD) surgery aims to correct abnormal spinal curvature in adults, leading to improved functionality and reduced pain. However, this surgery is associated with various complications, one of which is proximal junctional failure (PJF). PJF can have a significant impact on a patient’s quality of life, necessitating a comprehensive understanding of its causes and the development of effective management strategies. This review aims to provide an in-depth understanding of PJF in ASD surgery. PJF is a complex complication resulting from a multitude of factors including patient characteristics, surgical techniques, and postoperative management. Age, osteoporosis, overcorrection of sagittal alignment, and poor bone quality are identified as significant risk factors. The clinical implications of PJF are substantial, often requiring revision surgery and causing a considerable decrease in patients’ quality of life. Prevention strategies include careful preoperative planning, appropriate patient selection, and optimization of surgical techniques. Treatment often necessitates a multifaceted approach, including surgical intervention and the management of underlying risk factors. Predictive modeling is an emerging field that may offer a promising avenue for the risk stratification of patients and individualized preventive strategies. A thorough understanding of PJF’s pathogenesis, risk factors, and clinical implications is essential for surgeons involved in ASD surgery. Current preventive measures and treatment strategies aim to mitigate the risk and manage the complications of PJF, but the complication cannot be entirely prevented. Future research should focus on the development of more effective preventive and treatment strategies, and predictive models could be valuable in this pursuit.

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Can artificial intelligence support or even replace physicians in measuring sagittal balance? A validation study on preoperative and postoperative full spine images of 170 patients

Cited by 13 publications

References 24 publications

Emerging Technologies within Spine Surgery

Emerging Technologies within Spine Surgery

Analysis of sagittal parameters for easier and more accurate determination of cervical spine alignment

Proximal Junctional Failure in Adult Spinal Deformity Surgery: An In-depth Review

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