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A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Clinical Neurology".

Deadline for manuscript submissions: 25 November 2025 | Viewed by 7031

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Dr. Jae Hwan Cho

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Department of Orthopedic Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Republic of Korea
Interests: thoracolumbar degenerative spine; adult spinal deformity; spinal tumor

Special Issue Information

Dear Colleagues,

This Special Issue provides a comprehensive overview of the latest advancements in the field of spine tumor diagnosis and treatment. Highlighting critical developments in spinal tumor management, the issue explores innovative approaches to diagnosing and treating spinal metastases, pathologic fractures, and cord compression. It delves into the evolving role of the surgeon, the integration of radiotherapy, and the importance of interdisciplinary collaboration between surgeons, medical oncologists, and radiologic oncologists. Additionally, the issue addresses the psychological aspects and pain management strategies essential for improving patient outcomes. Through cutting-edge research and expert insights, this edition aims to enhance understanding and foster advancements in spine tumor care.

Dr. Jae Hwan Cho
Guest Editor

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Keywords

spine tumor
spinal metastasis
pathologic fracture
cord compression
separation surgery
radiotherapy
interdisciplinary collaboration
surgeon’s role
medical oncologist
radiologic oncologist
psychological aspects
pain management
innovative approaches
patient outcomes
diagnostic advancements

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Published Papers (7 papers)

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13 pages, 1367 KB

Open AccessArticle

Instrumentation-Related Complications Following Nonfusion Posterior Fixation in Patients with Metastatic Spinal Tumors: Incidence and Risk Factors

by Yunjin Nam, Jin-Sung Park, Dong-Ho Kang, Chong-Suh Lee, Seung Woo Suh and Se-Jun Park

J. Clin. Med. 2025, 14(13), 4629; https://doi.org/10.3390/jcm14134629 - 30 Jun 2025

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Abstract

Background/Objectives: Previous studies have reported satisfactory outcomes and low rates of instrumentation-related complications (IRCs) following nonfusion posterior fixation in patients with metastatic spinal tumors (MSTs). However, to adequately assess the longevity and durability of nonfusion instrumentation in patients with longer life expectancy, an extended follow-up period is essential. This study aims to evaluate the incidence of and risk factors for IRCs in patients with MSTs who underwent nonfusion posterior fixation and had radiographic follow-up data available for at least one year postoperatively. Methods: Consecutive data were collected from patients who underwent pedicle screw-based posterior fixation without fusion for MSTs in the thoracic and/or lumbar region from 2005 to 2018. The IRCs included screw loosening, screw pull-out, and metal breakage. The IRC-free survival and related factors were analyzed by Kaplan–Meier survivorship analysis with the log-rank test within a minimum follow-up period of one year. A multivariate analysis was performed using a Cox proportional-hazards regression model. Results: In total, 61 patients were included. The mean follow-up period was 28.3 months (range: 12.0–102.6 months). There were 27 cases (44.2%) of IRCs, including 22 cases of screw loosening, four cases of screw pull-out, and one case of rod breakage, at an average of 9.6 months (range: 1.0–38.1 months). The median IRC-free survival was 38.1 months (range: 1.0–102.6 months). Only three patients experienced pain aggravation with IRCs. No revision surgery was performed. A multivariate analysis identified that fixation length was a risk factor for IRCs (odds ratio: 0.358, 95% confidence interval: 0.114–0.888; p = 0.027). Conclusions: IRCs are frequent but mostly asymptomatic after nonfusion posterior fixation in patients with MSTs followed up for at least one year. Overall, the IRC-free survival was long enough considering the patient survival. Fixation length was a significant risk factor for IRCs regardless of MST location. Full article

(This article belongs to the Special Issue Recent Advances in Spine Tumor Diagnosis and Treatment)

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11 pages, 3399 KB

Open AccessArticle

BioGlue^® Induced Mass Formation Aggravating Spinal Canal Invasion After Intradural Tumor Surgery

by Sun Woo Jang, Sang Hyub Lee, Hong Kyung Shin, Sang Ryong Jeon, Danbi Park, Chongman Kim and Jin Hoon Park

J. Clin. Med. 2025, 14(13), 4540; https://doi.org/10.3390/jcm14134540 - 26 Jun 2025

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Abstract

Background/Objectives: The aim of this study was to evaluate whether the use of BioGlue^® increases the risk of postoperative mass formation and subsequent spinal canal invasion after intradural spinal tumor surgery. Methods: After retrospectively reviewing patients who underwent intradural tumor surgery from 2018 to 2023, we evaluated mass formation as detected in postoperative MRI according to the Epidural Spinal Cord Compression (ESCC) grade. Patients were divided into two groups based on the use of BioGlue^®, and we analyzed MRI postoperatively to compare the differences in ESCC grades and the incidence of symptomatic spinal canal invasion between the two groups. Additionally, we performed a logistic regression analysis to identify risk factors associated with mass formation and to explore their relationship with BioGlue^®. Results: This study included a total of 153 patients, 87 in the BioGlue^® and 66 in the non-BioGlue^® groups. In the BioGlue^® group, 18 patients had ESCC grade 2, and 11 had grade 3. Conversely, in the non-BioGlue^® group, only 8 patients had ESCC grade 2, and none had grade 3 (p = 0.001). Among the cases of symptomatic spinal canal invasion, all five cases were identified in the BioGlue^® group (p = 0.001). Both univariate and multivariate analyses showed that BioGlue^® was a significant risk factor for spinal canal invasion (univariate: OR = 3.931, p = 0.005, multivariate: OR = 3.812, p = 0.003). Conclusions: Our findings indicated that BioGlue^® was a significant risk factor for mass formation aggravating spinal canal invasion after intradural tumor surgery. Full article

(This article belongs to the Special Issue Recent Advances in Spine Tumor Diagnosis and Treatment)

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12 pages, 733 KB

Open AccessArticle

Clinical Significance of Prognostic Nutritional Index in Patients Who Underwent Palliative Surgery for Spine Metastasis

by Young-Hoon Kim, Kee-Yong Ha, Hyung-Youl Park, Kihyun Kwon, Yunseong Kim, Hyun W. Bae and Sang-Il Kim

J. Clin. Med. 2025, 14(12), 4372; https://doi.org/10.3390/jcm14124372 - 19 Jun 2025

Cited by 1 | Viewed by 589

Abstract

Background/Objectives: Malnutrition is common in patients with metastatic spine tumors (MSTs) and may adversely affect surgical outcomes. The Prognostic Nutritional Index (PNI) reflects both nutritional and immune status, but its role in palliative MST surgery is not well defined. The aim of this study was to investigate the association between preoperative the PNI and postoperative outcomes, including functional recovery and survival, in patients undergoing palliative surgery for MSTs. Methods: A brief description of the main methods or treatments applied. This can include any relevant preregistration or specimen information. Results: Patients with a higher PNI (≥42.8) demonstrated significantly better postoperative ambulation and longer overall survival compared to those with a lower PNI (<42.8). The higher PNI group showed earlier ambulation (p = 0.017) and longer median survival (30.7 vs. 7.0 months; p = 0.002). Multivariate analysis confirmed that a PNI ≥ 42.8 was an independent predictor of early ambulation (HR = 1.516; 95% CI: 1.010–2.277; p = 0.045) and prolonged survival (HR = 0.955; 95% CI: 0.927–0.985; p = 0.003). No significant association was found between the PNI and postoperative infections. Conclusions: The PNI is a simple and effective predictor of postoperative functional recovery and survival in patients undergoing palliative surgery for MSTs. Its routine preoperative assessment may help stratify surgical risk, guide nutritional interventions, and optimize clinical outcomes in this vulnerable population. Full article

(This article belongs to the Special Issue Recent Advances in Spine Tumor Diagnosis and Treatment)

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12 pages, 768 KB

Open AccessArticle

Impact of the Spinal Instability Neoplastic Score on Postoperative Prognosis in Patients with Metastatic Cancer of the Cervical Spine

by Dong-Ho Kang, Kyunghun Jung, Jin-Sung Park, Minwook Kang, Chong-Suh Lee and Se-Jun Park

J. Clin. Med. 2024, 13(24), 7860; https://doi.org/10.3390/jcm13247860 - 23 Dec 2024

Cited by 1 | Viewed by 1710

Abstract

Background: Although the Spinal Instability Neoplastic Score (SINS) is widely utilized to evaluate spinal instability, its prognostic value for survival in patients with cervical spinal metastases remains unclear. This study investigated the association between the SINS and survival outcomes in patients with metastatic cervical spine cancer. Methods: This retrospective cohort study included 106 patients who underwent surgery for metastatic cervical spine cancer at a single institution between 1995 and 2023. Patients were divided into two groups: high SINS (≥13) and low-to-moderate SINS (0–12). Overall survival (OS) was the primary outcome and was analyzed using Kaplan–Meier estimates and Cox regression. Secondary outcomes included changes in Eastern Cooperative Oncology Group Performance Status (ECOG-PS), operation time, estimated blood loss, and postoperative complications. Results: The median OS was significantly shorter in the high SINS group compared to the low-to-moderate SINS group (5.3 months versus 8.6 months; p = 0.023). A high SINS was independently associated with increased mortality risk (hazard ratio [HR], 1.959; 95% CI, 1.221–3.143; p = 0.005). Lung cancer (HR, 4.004; 95% CI, 1.878–8.535; p < 0.001) and rectal cancer (HR, 3.293; 95% CI, 1.126–9.632; p = 0.029) were predictive of worse survival, whereas postoperative chemotherapy (HR, 0.591; 95% CI, 0.381–0.917; p = 0.019) and radiotherapy (HR, 0.531; 95% CI, 0.340–0.827; p = 0.005) were associated with improved survival. Changes in the ECOG-PS and postoperative complication rates were not significantly different between the groups. Conclusions: A high SINS was associated with significantly shorter survival in patients with metastatic cervical spine cancer, reflecting both mechanical instability and tumor aggressiveness. Full article

(This article belongs to the Special Issue Recent Advances in Spine Tumor Diagnosis and Treatment)

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14 pages, 2079 KB

Open AccessArticle

Can Preoperative Hounsfield Unit Measurement Help Predict Mechanical Failure in Metastatic Spinal Tumor Surgery?

by Hyung Rae Lee, Jae Hwan Cho, Sang Yun Seok, San Kim, Dae Wi Cho and Jae Hyuk Yang

J. Clin. Med. 2024, 13(23), 7017; https://doi.org/10.3390/jcm13237017 - 21 Nov 2024

Cited by 1 | Viewed by 1188

Abstract

Background/Objectives: This study aimed to identify risk factors associated with mechanical failure in patients undergoing spinal instrumentation without fusion for metastatic spinal tumors. Methods: We retrospectively evaluated data from 220 patients with spinal tumors who underwent instrumentation without fusion. Propensity scores were used to match preoperative variables, resulting in the inclusion of 24 patients in the failure group (F group) and 72 in the non-failure group (non-F group). Demographic, surgical, and radiological characteristics were compared between the two groups. Logistic regression and Kaplan–Meier survival analyses were conducted to identify predictors of mechanical failure. Results: Propensity score matching resulted in a balanced distribution of covariates. Lower Hounsfield unit (HU) values at the lowest instrumented vertebra (LIV) were the only independent predictor of implant failure (p = 0.037). A cutoff value of 127.273 HUs was determined to predict mechanical failure, with a sensitivity of 59.1%, specificity of 73.4%, and area under the curve of 0.655 (95% confidence interval: 0.49–0.79). A significant difference in survival was observed between the groups with HU values above and below the cutoff (p = 0.0057). Cement-augmented screws were underutilized, with an average of only 0.2 screws per patient in the F group. Conclusions: Preoperative LIV HU values < 127.273 were strongly associated with an increased risk of mechanical failure following spinal instrumentation without fusion. Alternative surgical strategies including the use of cement-augmented screws are recommended for patients with low HU values. Full article

(This article belongs to the Special Issue Recent Advances in Spine Tumor Diagnosis and Treatment)

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14 pages, 3644 KB

Open AccessSystematic Review

Artificial Intelligence Models for Predicting Outcomes in Spinal Metastasis: A Systematic Review and Meta-Analysis

by Vivek Sanker, Prachi Dawer, Alexander Thaller, Zhikai Li, Philip Heesen, Srinath Hariharan, Emil O. R. Nordin, Maria Jose Cavagnaro, John Ratliff and Atman Desai

J. Clin. Med. 2025, 14(16), 5885; https://doi.org/10.3390/jcm14165885 - 20 Aug 2025

Viewed by 786

Abstract

Background: Spinal metastases can cause significant impairment of neurological function and quality of life. Hence, personalized clinical decision-making based on prognosis and likely outcome is desirable. The effectiveness of AI in predicting complications and treatment outcomes for patients with spinal metastases is assessed. Methods: A thorough search was carried out through the PubMed, Scopus, Web of Science, Embase, and Cochrane databases up until 27 January 2025. Included were studies that used AI-based models to predict outcomes for adult patients with spinal metastases. Three reviewers independently extracted the data, and screening was conducted in accordance with PRISMA principles. AUC results were pooled using a random-effects model, and the PROBAST program was used to evaluate the study’s quality. Results: Included were 47 articles totaling 25,790 patients. For training, internal validation, and external validation, the weighted average AUCs were 0.762, 0.876, and 0.810, respectively. The Skeletal Oncology Research Group machine learning algorithms (SORG-MLAs) were the ones externally validated the most, continuously producing AUCs > 0.84 for 90-day and 1-year mortality. Models based on radiomics showed promise in preoperative planning, especially for outcomes of radiation and concealed blood loss. Most research concentrated on breast, lung, and prostate malignancies, which limited its applicability to less common tumors. Conclusions: AI models have shown reasonable accuracy in predicting mortality, ambulatory status, blood loss, and surgical complications in patients with spinal metastases. Wider implementation necessitates additional validation, data standardization, and ethical and regulatory framework evaluation. Future work should concentrate on creating multimodal, hybrid models and assessing their practical applications. Full article

(This article belongs to the Special Issue Recent Advances in Spine Tumor Diagnosis and Treatment)

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15 pages, 1125 KB

Open AccessSystematic Review

Applications and Performance of Artificial Intelligence in Spinal Metastasis Imaging: A Systematic Review

by Vivek Sanker, Poorvikha Gowda, Alexander Thaller, Zhikai Li, Philip Heesen, Zekai Qiang, Srinath Hariharan, Emil O. R. Nordin, Maria Jose Cavagnaro, John Ratliff and Atman Desai

J. Clin. Med. 2025, 14(16), 5877; https://doi.org/10.3390/jcm14165877 - 20 Aug 2025

Viewed by 994

Abstract

Background: Spinal metastasis is the third most common site for metastatic localization, following the lung and liver. Manual detection through imaging modalities such as CT, MRI, PET, and bone scintigraphy can be costly and inefficient. Preliminary artificial intelligence (AI) techniques and computer-aided detection (CAD) systems have attempted to improve lesion detection, segmentation, and treatment response in oncological imaging. The objective of this review is to evaluate the current applications of AI across multimodal imaging techniques in the diagnosis of spinal metastasis. Methods: Databases like PubMed, Scopus, Web of Science Advance, Cochrane, and Embase (Ovid) were searched using specific keywords like ‘spine metastases’, ‘artificial intelligence’, ‘machine learning’, ‘deep learning’, and ‘diagnosis’. The screening of studies adhered to the PRISMA guidelines. Relevant variables were extracted from each of the included articles such as the primary tumor type, cohort size, and prediction model performance metrics: area under the receiver operating curve (AUC), accuracy, sensitivity, specificity, internal validation and external validation. A random-effects meta-analysis model was used to account for variability between the studies. Quality assessment was performed using the PROBAST tool. Results: This review included 39 studies published between 2007 and 2024, encompassing a total of 6267 patients. The three most common primary tumors were lung cancer (56.4%), breast cancer (51.3%), and prostate cancer (41.0%). Four studies reported AUC values for model training, 16 for internal validation, and five for external validation. The weighted average AUCs were 0.971 (training), 0.947 (internal validation), and 0.819 (external validation). The risk of bias was the highest in the analysis domain, with 22 studies (56%) rated high risk, primarily due to inadequate external validation and overfitting. Conclusions: AI-based approaches show promise for enhancing the detection, segmentation, and characterization of spinal metastatic lesions across multiple imaging modalities. Future research should focus on developing more generalizable models through larger and more diverse training datasets, integrating clinical and imaging data, and conducting prospective validation studies to demonstrate meaningful clinical impact. Full article

(This article belongs to the Special Issue Recent Advances in Spine Tumor Diagnosis and Treatment)

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