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Relationship between spinal alignment and functional disability after thoracolumbar spinal fractures: A systematic review 脊柱对齐与胸腰椎骨折后功能障碍之间的关系:系统回顾
Q3 Medicine Pub Date : 2024-07-18 DOI: 10.1016/j.xnsj.2024.100529
Romulo Augusto Andrade de Almeida MD , Francisco Call-Orellana MD , Andrei Fernandes Joaquim MD, PhD

Background

Thoracolumbar spinal fractures (TLSF) can cause pain, neurological deficits, and functional disability. Operative treatments aim to preserve neurological function, improve functional status, and restore spinal alignment and stability. In this review, we evaluate the relationship between spinal alignment and functional impairment in patients with TLSF.

Methods

We performed a systematic review in accordance with the PRISMA guidelines to identify full-text articles that evaluate the correlation between spinal alignment and functional outcomes of TLSF. The artificial intelligence software Rayyan assisted the screening process. Functional outcomes referred to activity/disability, quality of life, and pain scores, as well as return to work metrics. Radiological assessments included were vertebral compression angle, Cobb and Gardner angles, sagittal vertical axis, pelvic incidence, and pelvic tilt. Statistical analyses were performed for the data provided by articles using the SPSS v24.

Results

Of 1,616 articles reviewed, 6 were included for final analysis. Only 1 study primarily addressed the effects of spinopelvic parameters and functional outcomes. Four studies correlated Cobb angles with functional outcome, while 3 others compared vertebral compression angles with functional outcomes. Outcomes were assessed using work status or a combination of VAS pain and spine score, ODI, SF-36, and RMDQ-24. Neither the analysis done within the articles, nor the one made with the raw data provided by them, showed a significant correlation between the radiological measurements assessed at time of injury and final functional outcomes.

Conclusions

A correlation between the assessed spinal radiological measurements assessed with the functional outcomes of TLSF was not found in this review. Further well-designed prospective studies are necessary to evaluate spinal alignment measurements in TLSF with functional outcomes.

背景胸腰椎骨折(TLSF)可导致疼痛、神经功能缺损和功能障碍。手术治疗的目的是保护神经功能、改善功能状态、恢复脊柱对齐和稳定性。在这篇综述中,我们评估了 TLSF 患者脊柱排列与功能障碍之间的关系。方法我们根据 PRISMA 指南进行了系统性综述,以确定评估脊柱排列与 TLSF 功能结果之间相关性的全文文章。人工智能软件 Rayyan 为筛选过程提供了帮助。功能结果是指活动/残疾、生活质量、疼痛评分以及重返工作的指标。放射学评估包括椎体压缩角、Cobb 角和 Gardner 角、矢状纵轴、骨盆入射角和骨盆倾斜。我们使用 SPSS v24 对文章提供的数据进行了统计分析。只有一项研究主要探讨了脊柱骨盆参数和功能结果的影响。有 4 项研究将 Cobb 角与功能结果相关联,另有 3 项研究将椎体压缩角与功能结果进行了比较。研究结果采用工作状态或 VAS 疼痛和脊柱评分、ODI、SF-36 和 RMDQ-24 的组合进行评估。无论是在文章内部进行的分析,还是根据文章提供的原始数据进行的分析,均未显示受伤时评估的放射学测量值与最终功能结果之间存在显著相关性。有必要进一步开展精心设计的前瞻性研究,以评估 TLSF 的脊柱排列测量值与功能结果之间的关系。
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引用次数: 0
Twelve-month results from a randomized controlled trial comparing differential target multiplexed spinal cord stimulation and conventional spinal cord stimulation in subjects with chronic refractory axial low back pain not eligible for spine surgery 在不符合脊柱手术条件的慢性难治性轴性腰痛患者中比较差异化目标多路复用脊髓刺激和传统脊髓刺激的随机对照试验的 12 个月结果。
Q3 Medicine Pub Date : 2024-07-17 DOI: 10.1016/j.xnsj.2024.100528
Thomas White MD , Rafael Justiz MD , Wilson Almonte MD , Velimir Micovic MD , Binit Shah MD , Eric Anderson MD , Leonardo Kapural MD, PhD , Harold Cordner MD , Amr El-Naggar MD , Michael Fishman MD, MBA , Yashar Eshraghi MD , Philip Kim MD , Alaa Abd-Elsayed MD , Krishnan Chakravarthy , Yoann Millet MD , Mahendra Sanapati MD , Nathan Harrison MD , Brandon Goff DO , Mayank Gupta MD , Prabhdeep Grewal MD , Ricardo Vallejo MD, PhD

Background

Successful treatments for intractable chronic low back pain (CLBP) in patients who are not eligible for surgical interventions are scarce. The superior efficacy of differential target multiplexed spinal cord stimulation (DTM SCS) to conventional SCS (Conv-SCS) on the treatment of CLBP in patients with persistent spinal pain syndrome (PSPS) who have failed surgical interventions (PSPS-T2) motivated the evaluation of DTM SCS versus Conv-SCS on PSPS patients who are non-surgical candidates (PSPS-T1).

Methods

This is a prospective, open label, crossover, post-market randomized controlled trial in 20 centers across the United States. Eligible patients were randomized to either DTM SCS or Conv-SCS in a 1:1 ratio. Primary endpoint was CLBP responder rate (percentage of subjects with ≥50% CLBP relief) at 3-month in randomized subjects who completed trialing (modified intention-to-treat population). Patients were followed up to 12 months. Secondary endpoints included change of CLBP and leg pain, responder rates, changes in disability, quality of life, patient satisfaction and global impression of change, and safety profile. An optional crossover was available at 6-month to all patients.

Results

About 121 PSPS-T1 subjects with CLBP and leg pain mostly associated with degenerative disc disease and radiculopathy and who were not eligible for spine surgery were randomized. CLBP responder rate with DTM SCS (93.5%) was superior to Conv-SCS (36.4%) at the primary endpoint. Superior CLBP responder rates (88.1%–90.5%) were obtained with DTM SCS at all other timepoints. Mean CLBP reduction with DTM SCS (6.52 cm) was superior to that with Conv-SCS (3.01 cm) at the primary endpoint. Similar CLBP reductions (6.23–6.43 cm) were obtained with DTM SCS at other timepoints. DTM SCS provided significantly better leg pain reduction and responder rate, improvement of disability and quality of life, and better patient satisfaction and global impression of change. 90.9% of Conv-SCS subjects who crossed over were CLBP responders at completion of the study. Similar safety profiles were observed between the two groups.

Conclusion

DTM SCS for chronic CLBP in nonsurgical candidates is superior to Conv-SCS. Improvements were sustained and provided significant benefits on the management of these patients.

背景对于不符合手术治疗条件的顽固性慢性腰背痛(CLBP)患者,成功的治疗方法很少。在治疗手术干预失败的顽固性脊柱疼痛综合征(PSPS)患者(PSPS-T2)的慢性腰背痛(CLBP)方面,差异靶点多路脊髓刺激(DTM SCS)比传统的脊髓刺激(Conv-SCS)具有更优越的疗效,这促使我们对不适合手术的 PSPS 患者(PSPS-T1)进行 DTM SCS 与 Conv-SCS 的对比评估。符合条件的患者按 1:1 的比例随机接受 DTM SCS 或 Conv-SCS。主要终点是完成试验的随机受试者 3 个月后的 CLBP 回复率(CLBP 缓解率≥50% 的受试者百分比)(修正的意向治疗人群)。对患者的随访时间长达 12 个月。次要终点包括CLBP和腿痛的变化、应答率、残疾变化、生活质量、患者满意度和总体变化印象以及安全性。结果约有121名患有CLBP和腿痛的PSPS-T1受试者接受了随机治疗,这些患者大多伴有椎间盘退行性病变和根性病变,且不符合脊柱手术条件。在主要终点上,DTM SCS的CLBP应答率(93.5%)优于Conv-SCS(36.4%)。在所有其他时间点,DTM SCS 的 CLBP 应答率(88.1%-90.5%)均优于 Conv-SCS。在主要终点,DTM SCS 的平均 CLBP 减少量(6.52 厘米)优于 Conv-SCS(3.01 厘米)。在其他时间点,DTM SCS 的 CLBP 减少量(6.23-6.43 厘米)与 Conv-SCS 相似。DTM SCS 在减轻腿痛和应答率、改善残疾状况和生活质量、提高患者满意度和总体变化印象方面均有明显改善。研究结束时,90.9% 的 Conv-SCS 受试者对 CLBP 有反应。结论DTM SCS治疗非手术治疗慢性CLBP优于Conv-SCS。改善是持续性的,为这些患者的治疗带来了显著的益处。
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引用次数: 0
Prediction models for risk assessment of surgical site infection after spinal surgery: A systematic review 脊柱手术后手术部位感染风险评估的预测模型:系统回顾
Q3 Medicine Pub Date : 2024-07-10 DOI: 10.1016/j.xnsj.2024.100518
Alexa R. Lauinger BS , Samuel Blake BS , Alan Fullenkamp BS , Gregory Polites MD , Jonathan N. Grauer MD , Paul M. Arnold MD

Background

Spinal surgeries are a common procedure, but there is significant risk of adverse events following these operations. While the rate of adverse events ranges from 8% to 18%, surgical site infections (SSIs) alone occur in between 1% and 4% of spinal surgeries.

Methods

We completed a systematic review addressing factors that contribute to surgical site infection after spinal surgery. From the included studies, we separated the articles into groups based on whether they propose a clinical predictive tool or model. We then compared the prediction variables, model development, model validation, and model performance.

Results

About 47 articles were included in this study: 10 proposed a model and 5 validated a model. The models were developed from 7,720 participants in total and 210 participants with SSI. Only one of the proposed models was externally validated by an independent group. The other 4 validation papers examined the performance of the ACS NSQIP surgical risk calculator.

Conclusions

While some preoperative risk models have been validated, and even successfully implemented clinically, the significance of postoperative SSIs and the unique susceptibility of spine surgery patients merits the development of a spine-specific preoperative risk model. Additionally, comprehensive and stratified risk modeling for SSI would be of invaluable clinical utility and greatly improve the field of spine surgery.

背景脊柱手术是一种常见手术,但手术后发生不良事件的风险很大。不良事件的发生率在 8% 到 18% 之间,仅手术部位感染 (SSI) 就发生在 1% 到 4% 的脊柱手术中。在纳入的研究中,我们根据文章是否提出了临床预测工具或模型将其分为几组。然后,我们对预测变量、模型开发、模型验证和模型性能进行了比较:10篇文章提出了一个模型,5篇文章验证了一个模型。这些模型是从总共 7,720 名参与者和 210 名 SSI 参与者中开发出来的。只有一篇提出的模型经过了独立小组的外部验证。结论虽然一些术前风险模型已经过验证,甚至在临床上成功实施,但术后 SSI 的重要性和脊柱手术患者的独特易感性值得开发脊柱特异性术前风险模型。此外,全面、分层的 SSI 风险模型将在临床上发挥宝贵的作用,并极大地改进脊柱手术领域。
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引用次数: 0
Circumferential correction of spinal deformity and instability secondary to bacterial spondylodiscitis 细菌性脊柱盘炎继发脊柱畸形和不稳定的环形矫正
Q3 Medicine Pub Date : 2024-07-09 DOI: 10.1016/j.xnsj.2024.100517
Azeem A. Rehman MD, Ziev B. Moses MD, Mazda K. Turel MD, Ravi S. Nunna MD, Mena G. Kerolus MD, Samuel J. Meza MD, Ricardo B.V. Fontes MD, PhD

Background

Spinal deformity as a sequela of nontuberculous spondylodiscitis is a rarely discussed clinical entity. Sagittal plane deformity, segmental instability, and persistently active infection overlap in these patients resulting in severe restriction in activity and quality of life. The presence of multiple medical co-morbidities restricts surgical options but nonoperative care may be ineffective and result in persistent, refractory discitis for years. We describe our experience with vertebrectomy and long-segment fixation for patients with postinfectious thoracic or lumbar deformity.

Methods

A retrospective chart review of 23 consecutive patients who underwent vertebrectomy and long-segment fixation for thoracic or lumbar deformity secondary to nontuberculous bacterial spondylodiscitis was performed. Pre, peri- and postoperative data is compiled and analyzed with a focus on the perioperative management algorithm to safely perform an extensive reconstruction in this very sick patient population.

Results

Extremely low preoperative quality of life was evident with 87% (20/23) of patients bedridden primarily due to pain despite 70% (16/23) of patients being strong enough to ambulate (Frankel D or E). Most patients (87%) already had an identified infection under adequate treatment either through blood cultures, prior biopsy or decompressive surgery. A single-stage posterior-only was the primary surgical approach utilized in the majority (83%) of cases. Complications were present in 100% of patients, most commonly perioperative anemia and hypotension requiring vasopressor support and aggressive blood product replacement. One in-hospital mortality occurred secondarily to pulmonary embolism. Mean preoperative segmental angle was 18±10 degrees of kyphosis which was corrected to 1±9 degrees of lordosis (p=.001). The mean correction of the segmental angle was 19 degrees (standard deviation 23 degrees). Visual analogue scale scores improved from a preoperative value of 8.8±0.9 to a postoperative value of 2.5±1.4 (p<.001), which was obtained at the last outpatient follow-up (mean 631 days after surgery). Full self-care including ambulation was achieved in 18/23 (78%) patients, and the infection was successfully treated in 22/23 (96%) patients after long-term antibiotics.

Conclusions

Patients with refractory spondylodiscitis on appropriate care and antibiotics are typically considered extremely poor surgical candidates despite nonoperative care often being ineffective. Postinfectious deformity may also be so severe as to preclude a limited surgical treatment strategy. This study suggests that extensive circumferential reconstruction for deformity secondary to bacterial spondylodiscitis can be effective in restoring these extremely sick patients to self-care and ambulatory status.

背景非结核性脊椎盘炎的后遗症脊柱畸形是一种很少被讨论的临床实体。矢状面畸形、节段不稳定性和持续的活动性感染在这些患者中交织在一起,严重限制了患者的活动能力和生活质量。多种并发症的存在限制了手术治疗的选择,但非手术治疗可能效果不佳,导致椎间盘炎多年难愈。我们描述了对感染后胸椎或腰椎畸形患者进行椎体切除术和长节段固定术的经验。方法对连续 23 例因非结核性细菌性脊椎盘炎继发胸椎或腰椎畸形而接受椎体切除术和长节段固定术的患者进行回顾性病历审查。结果术前生活质量极低,87%(20/23)的患者主要因疼痛而卧床不起,尽管70%(16/23)的患者有足够的体力行走(Frankel D或E)。大多数患者(87%)已经通过血液培养、活检或减压手术确定了感染,并接受了适当的治疗。大多数病例(83%)采用的主要手术方法是单期后路手术。100%的患者都出现了并发症,最常见的是围手术期贫血和低血压,需要血管加压支持和积极补充血制品。一名患者因肺栓塞导致院内死亡。术前平均脊柱后凸角度为18±10度,术后矫正为1±9度(p=.001)。节段角度的平均矫正幅度为 19 度(标准偏差为 23 度)。视觉模拟量表评分从术前的 8.8±0.9 分提高到术后的 2.5±1.4 分(p<.001),这是最后一次门诊随访(平均术后 631 天)得出的结果。18/23(78%)例患者实现了完全自理,包括下地行走,22/23(96%)例患者经过长期抗生素治疗后成功治愈了感染。感染后畸形也可能非常严重,以至于无法采用有限的手术治疗策略。这项研究表明,针对继发于细菌性脊盘炎的畸形进行广泛的周缘重建可以有效地恢复这些重症患者的生活自理能力和活动能力。
{"title":"Circumferential correction of spinal deformity and instability secondary to bacterial spondylodiscitis","authors":"Azeem A. Rehman MD,&nbsp;Ziev B. Moses MD,&nbsp;Mazda K. Turel MD,&nbsp;Ravi S. Nunna MD,&nbsp;Mena G. Kerolus MD,&nbsp;Samuel J. Meza MD,&nbsp;Ricardo B.V. Fontes MD, PhD","doi":"10.1016/j.xnsj.2024.100517","DOIUrl":"10.1016/j.xnsj.2024.100517","url":null,"abstract":"<div><h3>Background</h3><p>Spinal deformity as a sequela of nontuberculous spondylodiscitis is a rarely discussed clinical entity. Sagittal plane deformity, segmental instability, and persistently active infection overlap in these patients resulting in severe restriction in activity and quality of life. The presence of multiple medical co-morbidities restricts surgical options but nonoperative care may be ineffective and result in persistent, refractory discitis for years. We describe our experience with vertebrectomy and long-segment fixation for patients with postinfectious thoracic or lumbar deformity.</p></div><div><h3>Methods</h3><p>A retrospective chart review of 23 consecutive patients who underwent vertebrectomy and long-segment fixation for thoracic or lumbar deformity secondary to nontuberculous bacterial spondylodiscitis was performed. Pre, peri- and postoperative data is compiled and analyzed with a focus on the perioperative management algorithm to safely perform an extensive reconstruction in this very sick patient population.</p></div><div><h3>Results</h3><p>Extremely low preoperative quality of life was evident with 87% (20/23) of patients bedridden primarily due to pain despite 70% (16/23) of patients being strong enough to ambulate (Frankel D or E). Most patients (87%) already had an identified infection under adequate treatment either through blood cultures, prior biopsy or decompressive surgery. A single-stage posterior-only was the primary surgical approach utilized in the majority (83%) of cases. Complications were present in 100% of patients, most commonly perioperative anemia and hypotension requiring vasopressor support and aggressive blood product replacement. One in-hospital mortality occurred secondarily to pulmonary embolism. Mean preoperative segmental angle was 18±10 degrees of kyphosis which was corrected to 1±9 degrees of lordosis (p=.001). The mean correction of the segmental angle was 19 degrees (standard deviation 23 degrees). Visual analogue scale scores improved from a preoperative value of 8.8±0.9 to a postoperative value of 2.5±1.4 (p&lt;.001), which was obtained at the last outpatient follow-up (mean 631 days after surgery). Full self-care including ambulation was achieved in 18/23 (78%) patients, and the infection was successfully treated in 22/23 (96%) patients after long-term antibiotics.</p></div><div><h3>Conclusions</h3><p>Patients with refractory spondylodiscitis on appropriate care and antibiotics are typically considered extremely poor surgical candidates despite nonoperative care often being ineffective. Postinfectious deformity may also be so severe as to preclude a limited surgical treatment strategy. This study suggests that extensive circumferential reconstruction for deformity secondary to bacterial spondylodiscitis can be effective in restoring these extremely sick patients to self-care and ambulatory status.</p></div>","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"19 ","pages":"Article 100517"},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424002105/pdfft?md5=2dd0196f5ba6de0e54c5f906e02b019a&pid=1-s2.0-S2666548424002105-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141714179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Sagittal spinal alignment measurements and evaluation: Historical perspective 脊柱矢状位对齐测量与评估:历史视角。
Q3 Medicine Pub Date : 2024-07-06 DOI: 10.1016/j.xnsj.2024.100519
Ashley Knebel BA, Mohammad Daher BS, Manjot Singh BS, Lauren Fisher BS, Alan H. Daniels MD, Bassel G. Diebo MD

Spinal alignment analysis play an important role in evaluating patients and planning surgical corrections for adult spinal deformity. The history of these parameters is relatively short with the first parameter, the Cobb angle, introduced in 1948 as part of an effort to improve scoliosis evaluation. New developments in the field were limited for nearly 30 years before better imaging technology encouraged new theories and later data about spinal alignment and the relationship between the spine and pelvis. These efforts would ultimately contribute to the creation of foundational spinal alignment parameters, including pelvic incidence, pelvic tilt, and sacral slope. By the 1990s, spinal alignment had become a sustained area of investigation for spinal surgeons and researchers. Novel alignment parameters have since been introduced as our knowledge has evolved and has allowed for valuable research that demonstrates the clinical and surgical value of alignment measurement. This manuscript will explore the history of spinal alignment analysis over the decades.

脊柱排列分析在成人脊柱畸形患者的评估和手术矫正计划中发挥着重要作用。这些参数的历史相对较短,第一个参数--科布角于1948年推出,是改善脊柱侧弯评估工作的一部分。在近 30 年的时间里,该领域的新发展一直受到限制,直到更好的成像技术促进了有关脊柱排列和脊柱与骨盆之间关系的新理论和新数据的出现。这些努力最终促成了基本脊柱排列参数的诞生,包括骨盆入射角、骨盆倾斜和骶骨斜度。到 20 世纪 90 年代,脊柱排列已成为脊柱外科医生和研究人员持续研究的领域。随着我们的知识不断发展,新的对齐参数也随之问世,这些有价值的研究证明了对齐测量的临床和手术价值。本手稿将探讨数十年来脊柱排列分析的历史。
{"title":"Sagittal spinal alignment measurements and evaluation: Historical perspective","authors":"Ashley Knebel BA,&nbsp;Mohammad Daher BS,&nbsp;Manjot Singh BS,&nbsp;Lauren Fisher BS,&nbsp;Alan H. Daniels MD,&nbsp;Bassel G. Diebo MD","doi":"10.1016/j.xnsj.2024.100519","DOIUrl":"10.1016/j.xnsj.2024.100519","url":null,"abstract":"<div><p>Spinal alignment analysis play an important role in evaluating patients and planning surgical corrections for adult spinal deformity. The history of these parameters is relatively short with the first parameter, the Cobb angle, introduced in 1948 as part of an effort to improve scoliosis evaluation. New developments in the field were limited for nearly 30 years before better imaging technology encouraged new theories and later data about spinal alignment and the relationship between the spine and pelvis. These efforts would ultimately contribute to the creation of foundational spinal alignment parameters, including pelvic incidence, pelvic tilt, and sacral slope. By the 1990s, spinal alignment had become a sustained area of investigation for spinal surgeons and researchers. Novel alignment parameters have since been introduced as our knowledge has evolved and has allowed for valuable research that demonstrates the clinical and surgical value of alignment measurement. This manuscript will explore the history of spinal alignment analysis over the decades.</p></div>","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"19 ","pages":"Article 100519"},"PeriodicalIF":0.0,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424002129/pdfft?md5=899717a59a2349c53a4d1c1e9b7374a9&pid=1-s2.0-S2666548424002129-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141841463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Lumbar pedicle subtraction osteotomy: techniques and outcomes 腰椎椎弓根减压截骨术:技术与疗效
Q3 Medicine Pub Date : 2024-07-06 DOI: 10.1016/j.xnsj.2024.100516
Anouar Bourghli MD , Louis Boissiere MD , Ibrahim Obeid MD

Pedicle subtraction osteotomy has been thoroughly described and studied over the past 2 decades, being applied mainly in the lumbar spine, followed by the thoracic spine. Our better understanding of alignment biomechanics, and the progressive refinements of the surgical technique over time made it a very efficient procedure for the management of fixed sagittal malalignment. However, a long learning curve is mandatory to mitigate the associated risks particularly neurological deficits and achieve satisfactory clinical and radiological outcomes with an acceptable rate of complications.

在过去的二十年中,对椎弓根减压截骨术进行了深入的描述和研究,主要应用于腰椎,其次是胸椎。随着时间的推移,我们对对位生物力学有了更深入的了解,手术技术也在逐步完善,使其成为治疗固定性矢状位错位的一种非常有效的手术方法。然而,要降低相关风险,尤其是神经功能缺损,并在可接受的并发症发生率下获得令人满意的临床和放射学效果,还需要很长的学习曲线。
{"title":"Lumbar pedicle subtraction osteotomy: techniques and outcomes","authors":"Anouar Bourghli MD ,&nbsp;Louis Boissiere MD ,&nbsp;Ibrahim Obeid MD","doi":"10.1016/j.xnsj.2024.100516","DOIUrl":"10.1016/j.xnsj.2024.100516","url":null,"abstract":"<div><p>Pedicle subtraction osteotomy has been thoroughly described and studied over the past 2 decades, being applied mainly in the lumbar spine, followed by the thoracic spine. Our better understanding of alignment biomechanics, and the progressive refinements of the surgical technique over time made it a very efficient procedure for the management of fixed sagittal malalignment. However, a long learning curve is mandatory to mitigate the associated risks particularly neurological deficits and achieve satisfactory clinical and radiological outcomes with an acceptable rate of complications.</p></div>","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"19 ","pages":"Article 100516"},"PeriodicalIF":0.0,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424002099/pdfft?md5=cc627705b747febabd53ce85ed9bf696&pid=1-s2.0-S2666548424002099-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141714659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Osteoporotic vertebral compression fracture (OVCF) detection using artificial neural networks model based on the AO spine-DGOU osteoporotic fracture classification system 基于 AO Spine-DGOU 骨质疏松性骨折分类系统的人工神经网络模型检测骨质疏松性椎体压缩性骨折 (OVCF)
Q3 Medicine Pub Date : 2024-07-04 DOI: 10.1016/j.xnsj.2024.100515
Wongthawat Liawrungrueang MD , Sung Tan Cho MD , Vit Kotheeranurak MD , Khanathip Jitpakdee MD , Pyeoungkee Kim PhD , Peem Sarasombath MD

Background

Osteoporotic Vertebral Compression Fracture (OVCF) substantially reduces a person's health-related quality of life. Computer Tomography (CT) scan is currently the standard for diagnosis of OVCF. The aim of this paper was to evaluate the OVCF detection potential of artificial neural networks (ANN).

Methods

Models of artificial intelligence based on deep learning hold promise for quickly and automatically identifying and visualizing OVCF. This study investigated the detection, classification, and grading of OVCF using deep artificial neural networks (ANN). Techniques: Annotation techniques were used to segregate the sagittal images of 1,050 OVCF CT pictures with symptomatic low back pain into 934 CT images for a training dataset (89%) and 116 CT images for a test dataset (11%). A radiologist tagged, cleaned, and annotated the training dataset. Disc deterioration was assessed in all lumbar discs using the AO Spine-DGOU Osteoporotic Fracture Classification System. The detection and grading of OVCF were trained using the deep learning ANN model. By putting an automatic model to the test for dataset grading, the outcomes of the ANN model training were confirmed.

Results

The sagittal lumbar CT training dataset included 5,010 OVCF from OF1, 1942 from OF2, 522 from OF3, 336 from OF4, and none from OF5. With overall 96.04% accuracy, the deep ANN model was able to identify and categorize lumbar OVCF.

Conclusions

The ANN model offers a rapid and effective way to classify lumbar OVCF by automatically and consistently evaluating routine CT scans using AO Spine-DGOU osteoporotic fracture classification system.

背景骨质疏松性椎体压缩骨折(OVCF)会大大降低患者与健康相关的生活质量。计算机断层扫描(CT)是目前诊断 OVCF 的标准。本文旨在评估人工神经网络(ANN)的 OVCF 检测潜力。方法基于深度学习的人工智能模型有望快速自动识别和可视化 OVCF。本研究利用深度人工神经网络(ANN)对 OVCF 的检测、分类和分级进行了研究。技术:使用注释技术将 1,050 张有症状腰痛的 OVCF CT 图像的矢状面图像分离成 934 张 CT 图像作为训练数据集(89%),116 张 CT 图像作为测试数据集(11%)。放射科医生对训练数据集进行标记、清理和注释。使用 AO Spine-DGOU 骨质疏松性骨折分类系统对所有腰椎间盘进行评估。使用深度学习 ANN 模型对 OVCF 的检测和分级进行了训练。结果矢状腰椎 CT 训练数据集包括 OF1 的 5010 个 OVCF、OF2 的 1942 个 OVCF、OF3 的 522 个 OVCF、OF4 的 336 个 OVCF 和 OF5 的 0 个 OVCF。结论通过使用 AO Spine-DGOU 骨质疏松性骨折分类系统自动、一致地评估常规 CT 扫描,ANN 模型为腰椎 OVCF 的分类提供了一种快速、有效的方法。
{"title":"Osteoporotic vertebral compression fracture (OVCF) detection using artificial neural networks model based on the AO spine-DGOU osteoporotic fracture classification system","authors":"Wongthawat Liawrungrueang MD ,&nbsp;Sung Tan Cho MD ,&nbsp;Vit Kotheeranurak MD ,&nbsp;Khanathip Jitpakdee MD ,&nbsp;Pyeoungkee Kim PhD ,&nbsp;Peem Sarasombath MD","doi":"10.1016/j.xnsj.2024.100515","DOIUrl":"10.1016/j.xnsj.2024.100515","url":null,"abstract":"<div><h3>Background</h3><p>Osteoporotic Vertebral Compression Fracture (OVCF) substantially reduces a person's health-related quality of life. Computer Tomography (CT) scan is currently the standard for diagnosis of OVCF. The aim of this paper was to evaluate the OVCF detection potential of artificial neural networks (ANN).</p></div><div><h3>Methods</h3><p>Models of artificial intelligence based on deep learning hold promise for quickly and automatically identifying and visualizing OVCF. This study investigated the detection, classification, and grading of OVCF using deep artificial neural networks (ANN). Techniques: Annotation techniques were used to segregate the sagittal images of 1,050 OVCF CT pictures with symptomatic low back pain into 934 CT images for a training dataset (89%) and 116 CT images for a test dataset (11%). A radiologist tagged, cleaned, and annotated the training dataset. Disc deterioration was assessed in all lumbar discs using the AO Spine-DGOU Osteoporotic Fracture Classification System. The detection and grading of OVCF were trained using the deep learning ANN model. By putting an automatic model to the test for dataset grading, the outcomes of the ANN model training were confirmed.</p></div><div><h3>Results</h3><p>The sagittal lumbar CT training dataset included 5,010 OVCF from OF1, 1942 from OF2, 522 from OF3, 336 from OF4, and none from OF5. With overall 96.04% accuracy, the deep ANN model was able to identify and categorize lumbar OVCF.</p></div><div><h3>Conclusions</h3><p>The ANN model offers a rapid and effective way to classify lumbar OVCF by automatically and consistently evaluating routine CT scans using AO Spine-DGOU osteoporotic fracture classification system.</p></div>","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"19 ","pages":"Article 100515"},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424002087/pdfft?md5=f7f1b7d64cc4de795abdd991aca59bd4&pid=1-s2.0-S2666548424002087-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141689227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Development of a natural language processing algorithm for the detection of spinal metastasis based on magnetic resonance imaging reports 根据核磁共振成像报告开发用于检测脊柱转移的自然语言处理算法
Q3 Medicine Pub Date : 2024-07-03 DOI: 10.1016/j.xnsj.2024.100513
Evan Mostafa MD , Aaron Hui BS , Boudewijn Aasman BS , Kamlesh Chowdary BS , Kyle Mani BS , Edward Mardakhaev MD , Richard Zampolin MD , Einat Blumfield MD , Jesse Berman MD , Rafael De La Garza Ramos MD , Mitchell Fourman MD , Reza Yassari MD , Ananth Eleswarapu MD , Parsa Mirhaji PhD

Background

Metastasis to the spinal column is a common complication of malignancy, potentially causing pain and neurologic injury. An automated system to identify and refer patients with spinal metastases can help overcome barriers to timely treatment. We describe the training, optimization and validation of a natural language processing algorithm to identify the presence of vertebral metastasis and metastatic epidural cord compression (MECC) from radiology reports of spinal MRIs.

Methods

Reports from patients with spine MRI studies performed between January 1, 2008 and April 14, 2019 were reviewed by a team of radiologists to assess for the presence of cancer and generate a labeled dataset for model training. Using regular expression, impression sections were extracted from the reports and converted to all lower-case letters with all nonalphabetic characters removed. The reports were then tokenized and vectorized using the doc2vec algorithm. These were then used to train a neural network to predict the likelihood of spinal tumor or MECC. For each report, the model provided a number from 0 to 1 corresponding to its impression. We then obtained 111 MRI reports from outside the test set, 92 manually labeled negative and 19 with MECC to test the model's performance.

Results

About 37,579 radiology reports were reviewed. About 36,676 were labeled negative, and 903 with MECC. We chose a cutoff of 0.02 as a positive result to optimize for a low false negative rate. At this threshold we found a 100% sensitivity rate with a low false positive rate of 2.2%.

Conclusions

The NLP model described predicts the presence of spinal tumor and MECC in spine MRI reports with high accuracy. We plan to implement the algorithm into our EMR to allow for faster referral of these patients to appropriate specialists, allowing for reduced morbidity and increased survival.

背景脊柱转移是恶性肿瘤的常见并发症,可能导致疼痛和神经损伤。一个用于识别和转诊脊柱转移患者的自动化系统有助于克服及时治疗的障碍。我们介绍了一种自然语言处理算法的训练、优化和验证过程,该算法可从脊柱核磁共振成像的放射学报告中识别出是否存在椎体转移和转移性硬膜外脊髓压迫(MECC)。方法放射科医生团队对2008年1月1日至2019年4月14日期间进行脊柱核磁共振成像检查的患者报告进行了审查,以评估是否存在癌症,并生成用于模型训练的标记数据集。使用正则表达式,从报告中提取印象部分,并转换为所有小写字母,去除所有非字母字符。然后使用 doc2vec 算法对报告进行标记化和矢量化。然后利用这些信息训练神经网络,预测脊柱肿瘤或 MECC 的可能性。对于每份报告,该模型都会提供一个从 0 到 1 的数字,与其印象相对应。然后,我们从测试集之外获取了 111 份 MRI 报告,其中 92 份手动标记为阴性,19 份标记为 MECC,以测试模型的性能。其中约 36,676 份标注为阴性,903 份标注为 MECC。我们选择 0.02 作为阳性结果的临界值,以优化低假阴性率。结论所述的 NLP 模型能准确预测脊柱 MRI 报告中是否存在脊柱肿瘤和 MECC。我们计划将该算法应用到我们的电子病历中,以便更快地将这些患者转诊给合适的专科医生,从而降低发病率,提高生存率。
{"title":"Development of a natural language processing algorithm for the detection of spinal metastasis based on magnetic resonance imaging reports","authors":"Evan Mostafa MD ,&nbsp;Aaron Hui BS ,&nbsp;Boudewijn Aasman BS ,&nbsp;Kamlesh Chowdary BS ,&nbsp;Kyle Mani BS ,&nbsp;Edward Mardakhaev MD ,&nbsp;Richard Zampolin MD ,&nbsp;Einat Blumfield MD ,&nbsp;Jesse Berman MD ,&nbsp;Rafael De La Garza Ramos MD ,&nbsp;Mitchell Fourman MD ,&nbsp;Reza Yassari MD ,&nbsp;Ananth Eleswarapu MD ,&nbsp;Parsa Mirhaji PhD","doi":"10.1016/j.xnsj.2024.100513","DOIUrl":"10.1016/j.xnsj.2024.100513","url":null,"abstract":"<div><h3>Background</h3><p>Metastasis to the spinal column is a common complication of malignancy, potentially causing pain and neurologic injury. An automated system to identify and refer patients with spinal metastases can help overcome barriers to timely treatment. We describe the training, optimization and validation of a natural language processing algorithm to identify the presence of vertebral metastasis and metastatic epidural cord compression (MECC) from radiology reports of spinal MRIs.</p></div><div><h3>Methods</h3><p>Reports from patients with spine MRI studies performed between January 1, 2008 and April 14, 2019 were reviewed by a team of radiologists to assess for the presence of cancer and generate a labeled dataset for model training. Using regular expression, impression sections were extracted from the reports and converted to all lower-case letters with all nonalphabetic characters removed. The reports were then tokenized and vectorized using the doc2vec algorithm. These were then used to train a neural network to predict the likelihood of spinal tumor or MECC. For each report, the model provided a number from 0 to 1 corresponding to its impression. We then obtained 111 MRI reports from outside the test set, 92 manually labeled negative and 19 with MECC to test the model's performance.</p></div><div><h3>Results</h3><p>About 37,579 radiology reports were reviewed. About 36,676 were labeled negative, and 903 with MECC. We chose a cutoff of 0.02 as a positive result to optimize for a low false negative rate. At this threshold we found a 100% sensitivity rate with a low false positive rate of 2.2%.</p></div><div><h3>Conclusions</h3><p>The NLP model described predicts the presence of spinal tumor and MECC in spine MRI reports with high accuracy. We plan to implement the algorithm into our EMR to allow for faster referral of these patients to appropriate specialists, allowing for reduced morbidity and increased survival.</p></div>","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"19 ","pages":"Article 100513"},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424002063/pdfft?md5=01450dbc60198665e1ef96ae67a4c9a2&pid=1-s2.0-S2666548424002063-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141700355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
37. Early versus late decompression for lumbar spinal nerve injury: a propensity score matched analysis 37.腰椎神经损伤早期减压与晚期减压:倾向得分匹配分析
Q3 Medicine Pub Date : 2024-07-01 DOI: 10.1016/j.xnsj.2024.100375
Sam Jiang BS , Zayed A Almadidy MD , Morteza Sadeh MD, PhD , Dario Marotta DO , Ankit Indravadan Mehta MD
<div><h3>BACKGROUND CONTEXT</h3><p>Traumatic lumbar spinal injury often necessitates surgical decompression of the thecal sac, nerve roots, or peripheral nerves. While there is some evidence in the literature to suggest a benefit to early surgery within 24 hours, there has yet to be a consensus and society recommendations for the timing of decompressive surgery for lumbar spine injuries.</p></div><div><h3>PURPOSE</h3><p>To evaluate the effect of early versus late decompressive surgery on inpatient outcomes at a nationwide level in the United States.</p></div><div><h3>STUDY DESIGN/SETTING</h3><p>Retrospective cohort database study.</p></div><div><h3>PATIENT SAMPLE</h3><p>Patients from the American College of Surgeons National Trauma Data Bank (NTDB) from 2017-2021.</p></div><div><h3>OUTCOME MEASURES</h3><p>The primary outcome measures are all-cause mortality and overall hospital length of stay (LOS). Secondary outcome measures entail hospital complications such as pressure ulcers and acute kidney injury (AKI) and discharge disposition such as routine discharge to home and discharge to skilled nursing.</p></div><div><h3>METHODS</h3><p>The NTDB was queried from 2017-2021 for all patients with a lumbar spinal cord or nerve injury matching the ICD-10-CM code S34. Patients younger than 18 years, who did not undergo surgical decompression, or who were missing outcome data were excluded. Patients were divided in the early surgery group if they underwent decompression within 24 hours and in the late surgery group if they underwent decompression at or after 24 hours. Propensity score matching was performed using the k-nearest neighbors algorithm based on patient age, sex, race, ethnicity, comorbidities, Glasgow Coma Scale, and insurance type. Equal post-match balance was evaluated using a standard mean difference threshold of 0.1. Early and late patients were compared using Student's t-tests and Pearson's chi-square tests.</p></div><div><h3>RESULTS</h3><p>A total of 1499 patients matching the inclusion and exclusion criteria were identified, of which 905 had early surgery and 591 had late surgery. Following propensity score matching, 591 matching patients in the late surgery group were identified. Post-match, the early surgery group had a lower mortality rate (0.17% vs 1.69%, p<0.01) and shorter overall length of stay (2.47 vs 3.79 days, p<0.01), as well as lower rates of unplanned intubation (1.02% vs 2.88%, p=0.02), AKI (0.17% vs 1.35%, p=0.02, stroke (0% vs 0.68%, p=0.045), pressure ulcer (0.68% vs 2.2%, p=0.03), unplanned intensive care unit admission (1.02% vs 4.06%, p<0.01), and ventilator-associated pneumonia (0.34% vs 1.69%, p=0.02) compared to the late surgery group. Additionally, the early surgery group was more likely to be discharged to inpatient rehabilitation (53.64% vs 40.61%, p<0.01) but less likely to be discharged routinely to home (26.73% vs 34.52%, p<0.01) or a skilled nursing facility (4.74% vs 7.61%, p=0.04).</p></div><
背景 CONTEXTT 外伤性腰椎损伤通常需要对椎囊、神经根或周围神经进行手术减压。虽然文献中有一些证据表明在 24 小时内尽早手术有好处,但对于腰椎损伤减压手术的时机尚未达成共识,也没有社会建议。研究设计/设置回顾性队列数据库研究。患者样本来自美国外科学院国家创伤数据库(NTDB)2017-2021年的患者。结果测量主要结果测量为全因死亡率和总住院时间(LOS)。次要结局指标包括压疮和急性肾损伤(AKI)等住院并发症,以及常规出院回家和出院接受专业护理等出院处置。方法:查询2017-2021年NTDB中所有符合ICD-10-CM代码S34的腰部脊髓或神经损伤患者。排除了年龄小于 18 岁、未接受手术减压或结果数据缺失的患者。如果患者在 24 小时内接受了减压手术,则将其分为早期手术组;如果患者在 24 小时内或 24 小时后接受了减压手术,则将其分为晚期手术组。根据患者的年龄、性别、种族、民族、合并症、格拉斯哥昏迷量表和保险类型,使用 k 近邻算法进行倾向评分匹配。采用 0.1 的标准平均差阈值评估匹配后的平衡。结果共确定了 1499 名符合纳入和排除标准的患者,其中 905 人接受了早期手术,591 人接受了晚期手术。经过倾向评分匹配,确定了晚期手术组中的 591 名匹配患者。匹配后,早期手术组的死亡率较低(0.17% vs 1.69%,p<0.01),总住院时间较短(2.47 vs 3.79 天,p<0.01),意外插管率(1.02% vs 2.88%,p=0.02)、AKI(0.17% vs 1.35%,p=0.02)、中风(0% vs 0.68%,p=0.045)、压疮(0.68% vs 2.2%,p=0.03)、非计划入住重症监护室(1.02% vs 4.06%,p<0.01)和呼吸机相关肺炎(0.34% vs 1.69%,p=0.02)的发生率均低于晚期手术组。此外,早期手术组更有可能出院接受住院康复治疗(53.64% vs 40.61%,p<0.01),但更不可能出院回家(26.73% vs 34.52%,p<0.01)或接受专业护理(4.74% vs 7.61%,p=0.04)。此外,它还与更高的康复出院率有关,这表明长期功能恢复的潜力更大。这项研究是这些课题中规模最大的研究之一,为早期减压的益处提供了更多证据。作为对费林斯、巴迪瓦拉等人现有文献的补充,这项工作有助于为腰椎神经损伤减压手术的时机制定更多指南。
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引用次数: 0
P28. Deep learning-based detection of lumbar spinal canal stenosis using convolutional neural networks P28.利用卷积神经网络进行基于深度学习的腰椎管狭窄症检测
Q3 Medicine Pub Date : 2024-07-01 DOI: 10.1016/j.xnsj.2024.100432
Hisataka Suzuki MD , Katsuhisa Yamada MD, PhD , Terufumi Kokabu MD , Yoko Ishikawa MD , Akito Yabu MD , Takahiko Hyakumachi MD
<div><h3>Background Context</h3><p>Lumbar spinal canal stenosis (LSCS) is the most common spinal degenerative disease in elderly people and usually first seen by primary care physicians or orthopedic surgeons who are not spine surgery specialists. Magnetic resonance imaging (MRI) is useful in the diagnosis of LSCS, but the equipment is often not available or difficult to read. LCSC patients with progressive neurologic deficits have difficulty with recovery if surgical treatment is delayed. So, early diagnosis and determination of appropriate surgical indications are crucial in the treatment of LCSC. Convolutional neural networks (CNNs), a type of deep learning, offers significant advantages for image recognition and classification, and work well with radiographs, which can be easily taken at any facility.</p></div><div><h3>Purpose</h3><p>Our purpose was to develop an algorithm to diagnose the presence or absence of LSCS requiring surgery from plain radiographs using CNNs.</p></div><div><h3>Study Design/Setting</h3><p>This study is a cross-sectional study.</p></div><div><h3>Patient Sample</h3><p>One hundred patients who underwent the surgery for LSCS including degenerative spondylolisthesis from January 2022 to May 2022 at a single institution were enrolled.</p></div><div><h3>Outcome Measures</h3><p>In annotation 1, the area under the curve (AUC) computed from the receiver operating characteristic (ROC) curve, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated. In annotation 2, correlation coefficients were used.</p></div><div><h3>Methods</h3><p>Four intervertebral levels from L1/2 to L4/5 were extracted as region of interest from lateral plain lumbar spine radiographs and totally 400 images were obtained. Based on the date of surgery, the 300 images derived from the first 75 cases were used for internal validation and 100 images from the second 25 cases for external validation. In annotation 1, binary classification of operative and nonoperative levels was used, and in annotation 2, the spinal canal area rate was calculated by dividing each disc level area measured on the MRI axial image by L1/2 level area. For internal validation, 300 images were divided into each 5 datasets on per-patient basis and 5-fold cross-validation was performed. Five trained models were registered in the external validation prediction performance. Grad-CAM was used to visualize area with the high features extracted by CNNs.</p></div><div><h3>Results</h3><p>In internal validation, the range of AUC and accuracy were 0.80 to 0.96 and 75% to 93% for the annotation 1 and correlation coefficients of 0.60 to 0.72 (All p<.01) for the annotation 2. In external validation, the AUC and accuracy were 0.93 and 86% in annotation 1, and correlation coefficient was 0.69 in annotation 2 using 5 trained CNN models. Grad-CAM showed high feature density
背景腰椎管狭窄症(LSCS)是老年人最常见的脊柱退行性疾病,通常由非脊柱外科专家的初级保健医生或骨科医生首诊。磁共振成像(MRI)对 LSCS 的诊断很有帮助,但往往没有设备或难以读取。如果延迟手术治疗,患有进行性神经功能缺损的 LCSC 患者将很难康复。因此,早期诊断和确定适当的手术指征对于治疗 LCSC 至关重要。卷积神经网络(CNN)是深度学习的一种,它在图像识别和分类方面具有显著优势,而且能很好地处理在任何机构都能轻松拍摄的放射照片。目的我们的目的是开发一种算法,利用 CNN 从普通放射照片诊断是否存在需要手术的 LSCS。结果测量在注释1中,计算了根据接收者操作特征曲线(ROC)计算出的曲线下面积(AUC)、敏感性、特异性、阳性预测值(PPV)、阴性预测值(NPV)、准确性、阳性似然比(PLR)和阴性似然比(NLR)。方法从腰椎侧位平片中提取 L1/2 至 L4/5 四个椎间水平作为感兴趣区,共获得 400 张图像。根据手术日期,前 75 个病例的 300 张图像用于内部验证,后 25 个病例的 100 张图像用于外部验证。在注释 1 中,使用了手术和非手术水平的二进制分类;在注释 2 中,通过将核磁共振轴向图像上测量的每个椎间盘水平面积除以 L1/2 水平面积,计算出椎管面积率。内部验证时,按每个病人将 300 张图像分成 5 个数据集,并进行 5 倍交叉验证。五个训练有素的模型被登记为外部验证预测性能。结果在内部验证中,注释 1 的 AUC 和准确率范围分别为 0.80 至 0.96 和 75% 至 93%,注释 2 的相关系数为 0.60 至 0.72(All p<.01)。在外部验证中,使用 5 个训练有素的 CNN 模型,注释 1 的 AUC 和准确率分别为 0.93 和 86%,注释 2 的相关系数为 0.69。Grad-CAM 在椎间关节和后椎间盘中显示出较高的特征密度。结论该技术可从普通腰椎X光片中自动检测 LSCS,使没有 MRI 或非专科医生的医疗机构也能诊断 LSCS,这表明有可能消除需要早期治疗的 LSCS 诊断和治疗中的延误。FDA 设备/药物状态本摘要未讨论或包含任何适用的设备或药物。
{"title":"P28. Deep learning-based detection of lumbar spinal canal stenosis using convolutional neural networks","authors":"Hisataka Suzuki MD ,&nbsp;Katsuhisa Yamada MD, PhD ,&nbsp;Terufumi Kokabu MD ,&nbsp;Yoko Ishikawa MD ,&nbsp;Akito Yabu MD ,&nbsp;Takahiko Hyakumachi MD","doi":"10.1016/j.xnsj.2024.100432","DOIUrl":"10.1016/j.xnsj.2024.100432","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Background Context&lt;/h3&gt;&lt;p&gt;Lumbar spinal canal stenosis (LSCS) is the most common spinal degenerative disease in elderly people and usually first seen by primary care physicians or orthopedic surgeons who are not spine surgery specialists. Magnetic resonance imaging (MRI) is useful in the diagnosis of LSCS, but the equipment is often not available or difficult to read. LCSC patients with progressive neurologic deficits have difficulty with recovery if surgical treatment is delayed. So, early diagnosis and determination of appropriate surgical indications are crucial in the treatment of LCSC. Convolutional neural networks (CNNs), a type of deep learning, offers significant advantages for image recognition and classification, and work well with radiographs, which can be easily taken at any facility.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Purpose&lt;/h3&gt;&lt;p&gt;Our purpose was to develop an algorithm to diagnose the presence or absence of LSCS requiring surgery from plain radiographs using CNNs.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Study Design/Setting&lt;/h3&gt;&lt;p&gt;This study is a cross-sectional study.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Patient Sample&lt;/h3&gt;&lt;p&gt;One hundred patients who underwent the surgery for LSCS including degenerative spondylolisthesis from January 2022 to May 2022 at a single institution were enrolled.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Outcome Measures&lt;/h3&gt;&lt;p&gt;In annotation 1, the area under the curve (AUC) computed from the receiver operating characteristic (ROC) curve, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated. In annotation 2, correlation coefficients were used.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;p&gt;Four intervertebral levels from L1/2 to L4/5 were extracted as region of interest from lateral plain lumbar spine radiographs and totally 400 images were obtained. Based on the date of surgery, the 300 images derived from the first 75 cases were used for internal validation and 100 images from the second 25 cases for external validation. In annotation 1, binary classification of operative and nonoperative levels was used, and in annotation 2, the spinal canal area rate was calculated by dividing each disc level area measured on the MRI axial image by L1/2 level area. For internal validation, 300 images were divided into each 5 datasets on per-patient basis and 5-fold cross-validation was performed. Five trained models were registered in the external validation prediction performance. Grad-CAM was used to visualize area with the high features extracted by CNNs.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;p&gt;In internal validation, the range of AUC and accuracy were 0.80 to 0.96 and 75% to 93% for the annotation 1 and correlation coefficients of 0.60 to 0.72 (All p&lt;.01) for the annotation 2. In external validation, the AUC and accuracy were 0.93 and 86% in annotation 1, and correlation coefficient was 0.69 in annotation 2 using 5 trained CNN models. Grad-CAM showed high feature density","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"18 ","pages":"Article 100432"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424001252/pdfft?md5=a318965fbd961106a972e510c95fa677&pid=1-s2.0-S2666548424001252-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141847361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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North American Spine Society Journal
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