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Shimizu H, Koide Y, Haimoto S, Aoyama T, Tachibana H, Hashimoto S, Iwata T, Kitagawa T, Kodaira T. Frequency of and risk factors associated with local recurrence after spinal stereotactic body radiation therapy without surgery. J Neurooncol 2024:10.1007/s11060-024-04755-7. [PMID: 39046598 DOI: 10.1007/s11060-024-04755-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Accepted: 06/20/2024] [Indexed: 07/25/2024]
Abstract
PURPOSE This study aimed to identify factors associated with local recurrence after spinal stereotactic body radiation therapy (SBRT), focusing on patient movement during treatment and tumor characteristics. METHODS A total of 48 patients who underwent spinal SBRT alone without surgery from August 2017 to October 2022 were evaluated. Logistic regression analysis was conducted to identify factors associated with local recurrence, including patient movement and tumor characteristics such as soft tissue involvement and tumor volume. Patient movement during treatment was measured using cone beam computed tomography before and after irradiation. RESULTS Among the included cases, 68.7% and 42.6% had soft tissue involvement and movement exceeding 1 mm, respectively. The median follow-up duration for local recurrence was 11.6 (range: 0.7-44.9) months, whereas the median duration to local recurrence was 6.3 months. Within 12 months, 29.3% of the patients experienced local recurrence, among whom 43.9% moved ≥ 1 mm during treatment, whereas 15.8% did not move. Univariable analysis found that both soft tissue involvement (OR = 10.3, 1.21-87.9; p = 0.033) and patient movement ≥ 1 mm (OR = 5.75, 1.45-22.8; p = 0.013) were associated with local recurrence. Multivariable analysis identified patient movement as an independent prognostic factor for local recurrence (OR = 5.15, 1.06-25.0; p = 0.042). CONCLUSION Our results suggest that patient movement during spinal SBRT was associated with local recurrence, emphasizing the need for better immobilization techniques and shorter delivery times to improve tumor control.
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Affiliation(s)
- Hidetoshi Shimizu
- Department of Radiation Oncology, Aichi Cancer Center Hospital, Nagoya, Japan.
| | - Yutaro Koide
- Department of Radiation Oncology, Aichi Cancer Center Hospital, Nagoya, Japan
| | - Shoichi Haimoto
- Department of Neurosurgery, Aichi Cancer Center Hospital, Nagoya, Japan
| | - Takahiro Aoyama
- Department of Radiation Oncology, Aichi Cancer Center Hospital, Nagoya, Japan
| | - Hiroyuki Tachibana
- Department of Radiation Oncology, Aichi Cancer Center Hospital, Nagoya, Japan
| | - Shingo Hashimoto
- Department of Radiation Oncology, Aichi Cancer Center Hospital, Nagoya, Japan
| | - Tohru Iwata
- Department of Radiation Oncology, Aichi Cancer Center Hospital, Nagoya, Japan
| | - Tomoki Kitagawa
- Department of Radiation Oncology, Aichi Cancer Center Hospital, Nagoya, Japan
| | - Takeshi Kodaira
- Department of Radiation Oncology, Aichi Cancer Center Hospital, Nagoya, Japan
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Kowalchuk RO, Mullikin TC, Spears GM, Johnson-Tesch BA, Rose PS, Siontis BL, Kun Kim D, Costello BA, Morris JM, Gao RW, Shiraishi S, Lucido JJ, Olivier KR, Owen D, Stish BJ, Waddle MR, Laack NN, Park SS, Brown PD, Merrell KW. Assessment of minimum target dose as a predictor of local failure after spine SBRT. Radiother Oncol 2024; 195:110260. [PMID: 38548114 DOI: 10.1016/j.radonc.2024.110260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 02/23/2024] [Accepted: 03/21/2024] [Indexed: 04/02/2024]
Abstract
OBJECTIVES Metastasis-directed stereotactic body radiation therapy (SBRT) has demonstrated robust clinical benefits in carefully selected patients, improving local control and even overall survival (OS). We assess a large database to determine clinical and dosimetric predictors of local failure after spine SBRT. METHODS Spine SBRT treatments with imaging follow-up were identified. Patients were treated with a simultaneous integrated boost technique using 1 or 3 fractions, delivering 20-24 Gy in 1 fraction to the gross tumor volume (GTV) and 16 Gy to the low dose volume (or 27-36 Gy and 21-24 Gy for 3 fraction treatments). Exclusions included: lack of imaging follow-up, proton therapy, and benign primary histologies. RESULTS 522 eligible spine SBRT treatments (68 % single fraction) were identified in 377 unique patients. Patients had a median OS of 43.7 months (95 % confidence interval: 34.3-54.4). The cumulative incidence of local failure was 10.5 % (7.4-13.4) at 1 year and 16.3 % (12.6-19.9) at 2 years. Local control was maximized at 15.3 Gy minimum dose for single-fraction treatment (HR = 0.31, 95 % CI: 0.17 - 0.56, p < 0.0001) and confirmed via multivariable analyses. Cumulative incidence of local failure was 6.1 % (2.6-9.4) vs. 14.2 % (8.3-19.8) at 1 year using this cut-off, with comparable findings for minimum 14 Gy. Additionally, epidural and soft tissue involvement were predictive of local failure (HR = 1.77 and 2.30). CONCLUSIONS Spine SBRT offers favorable local control; however, minimum dose to the GTV has a strong association with local control. Achieving GTV minimum dose of 14-15.3 Gy with single fraction SBRT is recommended whenever possible.
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Affiliation(s)
- Roman O Kowalchuk
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States
| | - Trey C Mullikin
- Duke University, Department of Radiation Oncology, Durham, NC 27710, United States
| | - Grant M Spears
- Mayo Clinic, Department of Statistics, Rochester, MN 55905, United States
| | | | - Peter S Rose
- Mayo Clinic, Department of Orthopedic Surgery, Rochester, MN 55905, United States
| | - Brittany L Siontis
- Mayo Clinic, Department of Medical Oncology, Rochester, MN 55905, United States
| | - Dong Kun Kim
- Mayo Clinic, Department of Radiology, Rochester, MN 55905, United States
| | - Brian A Costello
- Mayo Clinic, Department of Medical Oncology, Rochester, MN 55905, United States
| | - Jonathan M Morris
- Mayo Clinic, Department of Radiology, Rochester, MN 55905, United States
| | - Robert W Gao
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States
| | - Satomi Shiraishi
- Mayo Clinic, Department of Medical Physics, Rochester, MN 55905, United States
| | - John J Lucido
- Mayo Clinic, Department of Medical Physics, Rochester, MN 55905, United States
| | - Kenneth R Olivier
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States
| | - Dawn Owen
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States
| | - Bradley J Stish
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States
| | - Mark R Waddle
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States
| | - Nadia N Laack
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States
| | - Sean S Park
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States
| | - Paul D Brown
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States
| | - Kenneth W Merrell
- Mayo Clinic, Department of Radiation Oncology, Rochester, MN 55905, United States.
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Patel PP, Cao Y, Chen X, LeCompte MC, Kleinberg L, Khan M, McNutt T, Bydon A, Kebaish K, Theodore N, Larry Lo SF, Lee SH, Lubelski D, Redmond KJ. Oncologic and Functional Outcomes After Stereotactic Body Radiation Therapy for High-Grade Malignant Spinal Cord Compression. Adv Radiat Oncol 2024; 9:101327. [PMID: 38260225 PMCID: PMC10801652 DOI: 10.1016/j.adro.2023.101327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 07/21/2023] [Indexed: 01/24/2024] Open
Abstract
Purpose Although surgical decompression is the gold standard for metastatic epidural spinal cord compression (MESCC) from solid tumors, not all patients are candidates or undergo successful surgical Bilsky downgrading. We report oncologic and functional outcomes for patients treated with stereotactic body radiation therapy (SBRT) to high-grade MESCC. Methods and Materials Patients with Bilsky grade 2 to 3 MESCC from solid tumor metastases treated with SBRT at a single institution from 2009 to 2020 were retrospectively reviewed. Patients who received upfront surgery before SBRT were included only if postsurgical Bilsky grade remained ≥2. Neurologic examinations, magnetic resonance imaging, pain assessments, and analgesic usage were assessed every 3 to 4 months post-SBRT. Cumulative incidence of local recurrence was calculated with death as a competing risk, and overall survival was estimated by Kaplan-Meier. Results One hundred forty-three patients were included. The cumulative incidence of local recurrence was 5.1%, 7.5%, and 14.1% at 6, 12, and 24 months, respectively. At first post-SBRT imaging, 16.2% of patients with initial Bilsky grade 2 improved to grade 1, and 53.8% of patients were stable. Five of 13 patients (38.4%) with initial Bilsky grade 3 improved to grade 1 to 2. Pain response at 3 and 6 months post-SBRT was complete in 45.4% and 55.7%, partial in 26.9% and 13.1%, stable in 24.1% and 27.9%, and worse in 3.7% and 3.3% of patients, respectively. At 3 and 6 months after SBRT, 17.8% and 25.0% of patients had improved ambulatory status and 79.7% and 72.4% had stable status. Conclusions We report the largest series to date of patients with high-grade MESCC treated with SBRT. The excellent local control and functional outcomes suggest SBRT is a reasonable approach in inoperable patients or cases unable to be successfully surgically downgraded.
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Affiliation(s)
- Palak P. Patel
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Yilin Cao
- Department of Radiation Oncology, Dana-Farber/Brigham and Women's Cancer Center, Boston, Massachusetts
| | - Xuguang Chen
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Michael C. LeCompte
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Lawrence Kleinberg
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Majid Khan
- Department of Radiology, Thomas Jefferson University Sidney Kimmel Medical College, Philadelphia, Pennsylvania
| | - Todd McNutt
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland
| | | | - Khaled Kebaish
- Orthopedic Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland
| | | | - Sheng-fu Larry Lo
- Department of Neurosurgery, Zucker School of Medicine at Hoftstra, Manhasset, New York
| | - Sang H. Lee
- Orthopedic Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland
| | | | - Kristin J. Redmond
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland
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Guninski RS, Cuccia F, Alongi F, Andratschke N, Belka C, Bellut D, Dahele M, Josipovic M, Kroese TE, Mancosu P, Minniti G, Niyazi M, Ricardi U, Munck Af Rosenschold P, Sahgal A, Tsang Y, Verbakel WFAR, Guckenberger M. Efficacy and safety of SBRT for spine metastases: A systematic review and meta-analysis for preparation of an ESTRO practice guideline. Radiother Oncol 2024; 190:109969. [PMID: 37922993 DOI: 10.1016/j.radonc.2023.109969] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 10/18/2023] [Indexed: 11/07/2023]
Abstract
BACKGROUND AND PURPOSE Advances in characterizing cancer biology and the growing availability of novel targeted agents and immune therapeutics have significantly changed the prognosis of many patients with metastatic disease. Palliative radiotherapy needs to adapt to these developments. In this study, we summarize the available evidence for stereotactic body radiotherapy (SBRT) in the treatment of spinal metastases. MATERIALS AND METHODS A systematic review and meta-analysis was performed using PRISMA methodology, including publications from January 2005 to September 2021, with the exception of the randomized phase III trial RTOG-0631 which was added in April 2023. Re-irradiation was excluded. For meta-analysis, a random-effects model was used to pool the data. Heterogeneity was assessed with the I2-test, assuming substantial and considerable as I2 > 50 % and I2 > 75 %, respectively. A p-value < 0.05 was considered statistically significant. RESULTS A total of 69 studies assessing the outcomes of 7236 metastases in 5736 patients were analyzed. SBRT for spine metastases showed high efficacy, with a pooled overall pain response rate of 83 % (95 % confidence interval [CI] 68 %-94 %), pooled complete pain response of 36 % (95 % CI: 20 %-53 %), and 1-year local control rate of 94 % (95 % CI: 86 %-99 %), although with high levels of heterogeneity among studies (I2 = 93 %, I2 = 86 %, and 86 %, respectively). Furthermore, SBRT was safe, with a pooled vertebral fracture rate of 9 % (95 % CI: 4 %-16 %), pooled radiation induced myelopathy rate of 0 % (95 % CI 0-2 %), and pooled pain flare rate of 6 % (95 % CI: 3 %-17 %), although with mixed levels of heterogeneity among the studies (I2 = 92 %, I2 = 0 %, and 95 %, respectively). Only 1.7 % of vertebral fractures required surgical stabilization. CONCLUSION Spine SBRT is characterized by a favorable efficacy and safety profile, providing durable results for pain control and disease control, which is particularly relevant for oligometastatic patients.
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Affiliation(s)
- R S Guninski
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - F Cuccia
- ARNAS Civico Hospital, Radiation Oncology Unit, Palermo, Italy
| | - F Alongi
- Advanced Radiation Department, IRCCS Ospedale Sacro Cuore Don Calabria, Negrar-Verona, Italy. University of Brescia, Italy
| | - N Andratschke
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - C Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany. German Cancer Consortium (DKTK), partner site Munich, Munich, Germany. Bavarian Cancer Research Center (BZKF), Munich, Germany
| | - D Bellut
- University Hospital Zurich, University of Zurich, Department of Neurosurgery. Zurich, Switzerland
| | - M Dahele
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Radiation Oncology and Cancer Center Amsterdam, de Boelelaan 1117, Amsterdam, The Netherlands
| | - M Josipovic
- Department of Oncology, Centre for Cancer and Organ Diseases, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen, Denmark; Department of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen, Denmark
| | - T E Kroese
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - P Mancosu
- IRCCS Humanitas Research Hospital, Medical Physics Unit, Radiation Oncology department, via Manzoni 56, I-20089 Rozzano, Milan, Italy
| | - G Minniti
- Department of Radiological Sciences, Oncology and Anatomical PathologySapienza University of Rome, Rome; IRCCS Neuromed, Pozzilli, IS, Italy
| | - M Niyazi
- Department of Radiation Oncology, University hospital Tübingen, Tübingen, Germany
| | - U Ricardi
- University of Turin, Department of Oncology, Turin, Italy
| | - P Munck Af Rosenschold
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden; Medical Radiation Physics, Lund University, Lund, Sweden
| | - A Sahgal
- Odette Cancer Center of the Sunnybrook Health Sciences Center, Department of Radiation Oncology, Toronto, Canada
| | - Y Tsang
- Princess Margaret Cancer Centre, Radiation Medicine Program, Toronto, Canada
| | - W F A R Verbakel
- Amsterdam University Medical Center, Department of Radiation Oncology, Amsterdam, The Netherlands
| | - M Guckenberger
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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Chen Y, Qin S, Zhao W, Wang Q, Liu K, Xin P, Yuan H, Zhuang H, Lang N. MRI feature-based radiomics models to predict treatment outcome after stereotactic body radiotherapy for spinal metastases. Insights Imaging 2023; 14:169. [PMID: 37817044 PMCID: PMC10564690 DOI: 10.1186/s13244-023-01523-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 09/06/2023] [Indexed: 10/12/2023] Open
Abstract
OBJECTIVE This study aimed to extract radiomics features from MRI using machine learning (ML) algorithms and integrate them with clinical features to build response prediction models for patients with spinal metastases undergoing stereotactic body radiotherapy (SBRT). METHODS Patients with spinal metastases who were treated using SBRT at our hospital between July 2018 and April 2023 were recruited. We assessed their response to treatment using the revised Response Evaluation Criteria in Solid Tumors (version 1.1). The lesions were categorized into progressive disease (PD) and non-PD groups. Radiomics features were extracted from T1-weighted image (T1WI), T2-weighted image (T2WI), and fat-suppression T2WI sequences. Feature selection involved intraclass correlation coefficients, minimal-redundancy-maximal-relevance, and least absolute shrinkage and selection operator methods. Thirteen ML algorithms were employed to construct the radiomics prediction models. Clinical, conventional imaging, and radiomics features were integrated to develop combined models. Model performance was evaluated using receiver operating characteristic (ROC) curve analysis, and the clinical value was assessed using decision curve analysis. RESULTS We included 194 patients with 142 (73.2%) lesions in the non-PD group and 52 (26.8%) in the PD group. Each region of interest generated 2264 features. The clinical model exhibited a moderate predictive value (area under the ROC curve, AUC = 0.733), while the radiomics models demonstrated better performance (AUC = 0.745-0.825). The combined model achieved the best performance (AUC = 0.828). CONCLUSION The MRI-based radiomics models exhibited valuable predictive capability for treatment outcomes in patients with spinal metastases undergoing SBRT. CRITICAL RELEVANCE STATEMENT Radiomics prediction models have the potential to contribute to clinical decision-making and improve the prognosis of patients with spinal metastases undergoing SBRT. KEY POINTS • Stereotactic body radiotherapy effectively delivers high doses of radiation to treat spinal metastases. • Accurate prediction of treatment outcomes has crucial clinical significance. • MRI-based radiomics models demonstrated good performance to predict treatment outcomes.
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Affiliation(s)
- Yongye Chen
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Siyuan Qin
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Weili Zhao
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Qizheng Wang
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Ke Liu
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Peijin Xin
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Hongqing Zhuang
- Department of radiotherapy, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Ning Lang
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China.
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Predictive model based on DCE-MRI and clinical features for the evaluation of pain response after stereotactic body radiotherapy in patients with spinal metastases. Eur Radiol 2023:10.1007/s00330-023-09437-y. [PMID: 36735042 DOI: 10.1007/s00330-023-09437-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 12/12/2022] [Accepted: 01/09/2023] [Indexed: 02/04/2023]
Abstract
OBJECTIVE To investigate the correlation of conventional MRI, DCE-MRI and clinical features with pain response after stereotactic body radiotherapy (SBRT) in patients with spinal metastases and establish a pain response prediction model. METHODS Patients with spinal metastases who received SBRT in our hospital from July 2018 to April 2022 consecutively were enrolled. All patients underwent conventional MRI and DCE-MRI before treatment. Pain was assessed before treatment and in the third month after treatment, and the patients were divided into pain-response and no-pain-response groups. A multivariate logistic regression model was constructed to obtain the odds ratio and 95% confidence interval (CI) for each variable. C-index was used to evaluate the model's discrimination performance. RESULTS Overall, 112 independent spinal lesions in 89 patients were included. There were 73 (65.2%) and 39 (34.8%) lesions in the pain-response and no-pain-response groups, respectively. Multivariate analysis showed that the number of treated lesions, pretreatment pain score, Karnofsky performance status score, Bilsky grade, and the DCE-MRI quantitative parameter Ktrans were independent predictors of post-SBRT pain response in patients with spinal metastases. The discrimination performance of the prediction model was good; the C index was 0.806 (95% CI: 0.721-0.891), and the corrected C-index was 0.754. CONCLUSION Some imaging and clinical features correlated with post-SBRT pain response in patients with spinal metastases. The model based on these characteristics has a good predictive value and can provide valuable information for clinical decision-making. KEY POINTS • SBRT can accurately irradiate spinal metastases with ablative doses. • Predicting the post-SBRT pain response has important clinical implications. • The prediction models established based on clinical and MRI features have good performance.
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Amadasu E, Panther E, Lucke-Wold B. Characterization and Treatment of Spinal Tumors. INTENSIVE CARE RESEARCH 2022; 2:76-95. [PMID: 36741203 PMCID: PMC9893847 DOI: 10.1007/s44231-022-00014-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 09/03/2022] [Indexed: 02/07/2023]
Abstract
The prevalence of spinal tumors is rare in comparison to brain tumors which encompass most central nervous system tumors. Tumors of the spine can be divided into primary and metastatic tumors with the latter being the most common presentation. Primary tumors are subdivided based on their location on the spinal column and in the spinal cord into intramedullary, intradural extramedullary, and primary bone tumors. Back pain is a common presentation in spine cancer patients; however, other radicular pain may be present. Magnetic resonance imaging (MRI) is the imaging modality of choice for intradural extramedullary and intramedullary tumors. Plain radiographs are used in the initial diagnosis of primary bone tumors while Computed tomography (CT) and MRI may often be necessary for further characterization. Complete surgical resection is the treatment of choice for spinal tumors and may be curative for well circumscribed lesions. However, intralesional resection along with adjuvant radiation and chemotherapy can be indicated for patients that would experience increased morbidity from damage to nearby neurological structures caused by resection with wide margins. Even with the current treatment options, the prognosis for aggressive spinal cancer remains poor. Advances in novel treatments including molecular targeting, immunotherapy and stem cell therapy provide the potential for greater control of malignant and metastatic tumors of the spine.
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Affiliation(s)
- Efosa Amadasu
- School of Medicine, University of South Florida, Tampa, USA
| | - Eric Panther
- Department of Neurosurgery, University of Florida, Gainesville, USA
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Development and internal validation of an RPA-based model predictive of pain flare incidence after spine SBRT. Pract Radiat Oncol 2022; 12:e269-e277. [DOI: 10.1016/j.prro.2022.01.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 01/10/2022] [Accepted: 01/24/2022] [Indexed: 12/14/2022]
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Soltys SG, Grimm J, Milano MT, Xue J, Sahgal A, Yorke E, Yamada Y, Ding GX, Li XA, Lovelock DM, Jackson A, Ma L, El Naqa I, Gibbs IC, Marks LB, Benedict S. Stereotactic Body Radiation Therapy for Spinal Metastases: Tumor Control Probability Analyses and Recommended Reporting Standards. Int J Radiat Oncol Biol Phys 2021; 110:112-123. [PMID: 33516580 DOI: 10.1016/j.ijrobp.2020.11.021] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 11/02/2020] [Accepted: 11/09/2020] [Indexed: 01/07/2023]
Abstract
PURPOSE We sought to investigate the tumor control probability (TCP) of spinal metastases treated with stereotactic body radiation therapy (SBRT) in 1 to 5 fractions. METHODS AND MATERIALS PubMed-indexed articles from 1995 to 2018 were eligible for data extraction if they contained SBRT dosimetric details correlated with actuarial 2-year local tumor control rates. Logistic dose-response models of collected data were compared in terms of physical dose and 3-fraction equivalent dose. RESULTS Data were extracted from 24 articles with 2619 spinal metastases. Physical dose TCP modeling of 2-year local tumor control from the single-fraction data were compared with data from 2 to 5 fractions, resulting in an estimated α/β = 6 Gy, and this was used to pool data. Acknowledging the uncertainty intrinsic to the data extraction and modeling process, the 90% TCP corresponded to 20 Gy in 1 fraction, 28 Gy in 2 fractions, 33 Gy in 3 fractions, and (with extrapolation) 40 Gy in 5 fractions. The estimated TCP for common fractionation schemes was 82% at 18 Gy, 90% for 20 Gy, and 96% for 24 Gy in a single fraction, 82% for 24 Gy in 2 fractions, and 78% for 27 Gy in 3 fractions. CONCLUSIONS Spinal SBRT with the most common fractionation schemes yields 2-year estimates of local control of 82% to 96%. Given the heterogeneity in the tumor control estimates extracted from the literature, with variability in reporting of dosimetry data and the definition of and statistical methods of reporting tumor control, care should be taken interpreting the resultant model-based estimates. Depending on the clinical intent, the improved TCP with higher dose regimens should be weighed against the potential risks for greater toxicity. We encourage future reports to provide full dosimetric data correlated with tumor local control to allow future efforts of modeling pooled data.
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Affiliation(s)
- Scott G Soltys
- Department of Radiation Oncology, Stanford University, Stanford, California.
| | - Jimm Grimm
- Department of Radiation Oncology, Geisinger Health System, Danville, Pennsylvania; Department of Medical Imaging and Radiation Sciences, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Michael T Milano
- Department of Radiation Oncology, University of Rochester, Rochester, New York
| | - Jinyu Xue
- Department of Radiation Oncology, NYU Langone Medical Center, New York, New York
| | - Arjun Sahgal
- Department of Radiation Oncology, Odette Cancer Center, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON, Canada
| | - Ellen Yorke
- Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Yoshiya Yamada
- Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - George X Ding
- Department of Radiation Oncology, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - X Allen Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - D Michael Lovelock
- Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Andrew Jackson
- Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Lijun Ma
- Department of Radiation Oncology, University of California, San Francisco, San Francisco, California
| | - Issam El Naqa
- Machine Learning Department, Moffitt Cancer Center, Tampa, Florida
| | - Iris C Gibbs
- Department of Radiation Oncology, Stanford University, Stanford, California
| | - Lawrence B Marks
- Department of Radiation Oncology, University of North Carolina, Lineberger Cancer Center, Chapel Hill, North Carolina
| | - Stanley Benedict
- Department of Radiation Oncology, University of California at Davis, Sacramento, California
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