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Azadbakht J, Condos A, Haynor D, Gibbs WN, Jabehdar Maralani P, Sahgal A, Chao ST, Foote MC, Suh J, Chang EL, Guckenberger M, Mossa-Basha M, Lo SS. The Role of CT and MR Imaging in Stereotactic Body Radiotherapy of the Spine: From Patient Selection and Treatment Planning to Post-Treatment Monitoring. Cancers (Basel) 2024; 16:3692. [PMID: 39518130 PMCID: PMC11545634 DOI: 10.3390/cancers16213692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2024] [Accepted: 10/28/2024] [Indexed: 11/16/2024] Open
Abstract
Spine metastases (SMs) are common, arising in 70% of the cases of the most prevalent malignancies in males (prostate cancer) and females (breast cancer). Stereotactic body radiotherapy, or SBRT, has been incorporated into clinical treatment algorithms over the past decade. SBRT has shown promising rates of local control for oligometastatic spinal lesions with low radiation dose to adjacent critical tissues, particularly the spinal cord. Imaging is critically important in SBRT planning, guidance, and response monitoring. This paper reviews the roles of imaging in spine SBRT, including conventional and advanced imaging approaches for SM detection, treatment planning, and post-SBRT follow-up.
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Affiliation(s)
- Javid Azadbakht
- Department of Radiology, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Amy Condos
- Department of Radiology, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - David Haynor
- Department of Radiology, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Wende N. Gibbs
- Department of Radiology, Barrow Neurological Institute, Phoenix, AZ 85013, USA
| | - Pejman Jabehdar Maralani
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
| | - Samuel T. Chao
- Department of Radiation Oncology, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Matthew C. Foote
- Department of Radiation Oncology, Princess Alexandra Hospital, University of Queensland, Brisbane, QLD 4102, Australia
| | - John Suh
- Department of Radiation Oncology, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Eric L. Chang
- Department of Radiation Oncology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
| | - Matthias Guckenberger
- Department of Radiation Oncology, University Hospital Zürich and University of Zürich, 8091 Zürich, Switzerland
| | - Mahmud Mossa-Basha
- Department of Radiology, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Simon S. Lo
- Department of Radiation Oncology, University of Washington School of Medicine, Seattle, WA 98195, USA
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Mazurek MH, Abruzzo AR, King AH, Koranteng E, Rigney G, Lie W, Razak S, Gupta R, Mehan WA, Lev MH, Hirsch JA, Buch K, Succi MD. Implementation of a Survey Spine MR Imaging Protocol for Cord Compression in the Emergency Department: Experience at a Level 1 Trauma Center. AJNR Am J Neuroradiol 2024; 45:1378-1384. [PMID: 38702066 PMCID: PMC11392377 DOI: 10.3174/ajnr.a8326] [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: 01/28/2024] [Accepted: 04/22/2024] [Indexed: 05/06/2024]
Abstract
BACKGROUND AND PURPOSE Imaging stewardship in the emergency department (ED) is vital in ensuring patients receive optimized care. While suspected cord compression (CC) is a frequent indication for total spine MR imaging in the ED, the incidence of CC is low. Recently, our level 1 trauma center introduced a survey spine MR imaging protocol to evaluate for suspected CC while reducing examination time to avoid imaging overutilization. This study aims to evaluate the time savings, frequency of ordering patterns of the survey, and the symptoms and outcomes of patients undergoing the survey. MATERIALS AND METHODS This retrospective study examined patients who received a survey spine MR imaging in the ED at our institution between 2018 and 2022. All examinations were performed on a 1.5T GE Healthcare scanner by using our institutional CC survey protocol, which includes sagittal T2WI and STIR sequences through the cervical, thoracic, and lumbar spine. Examinations were read by a blinded, board-certified neuroradiologist. RESULTS A total of 2002 patients received a survey spine MR imaging protocol during the study period. Of these patients, 845 (42.2%, mean age 57 ± 19 years, 45% women) received survey spine MR imaging examinations for the suspicion of CC, and 120 patients (14.2% positivity rate) had radiographic CC. The survey spine MR imaging averaged 5 minutes and 50 seconds (79% faster than routine MR imaging). On multivariate analysis, trauma, back pain, lower extremity weakness, urinary or bowel incontinence, numbness, ataxia, and hyperreflexia were each independently associated with CC. Of the 120 patients with CC, 71 underwent emergent surgery, 20 underwent nonemergent surgery, and 29 were managed medically. CONCLUSIONS The survey spine protocol was positive for CC in 14% of patients in our cohort and acquired at a 79% faster rate compared with routine total spine. Understanding the positivity rate of CC, the clinical symptoms that are most associated with CC, and the subsequent care management for patients presenting with suspected cord compression who received the survey spine MR imaging may better inform the broad adoption and subsequent utilization of survey imaging protocols in emergency settings to increase throughput, improve allocation of resources, and provide efficient care for patients with suspected CC.
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Affiliation(s)
- Mercy H Mazurek
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Annie R Abruzzo
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Alexander H King
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Erica Koranteng
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Grant Rigney
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Winston Lie
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Shahaan Razak
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Rajiv Gupta
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
- Department of Radiology (R.G., W.A.M., M.H.L., J.A.H., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - William A Mehan
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
- Department of Radiology (R.G., W.A.M., M.H.L., J.A.H., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Michael H Lev
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
- Department of Radiology (R.G., W.A.M., M.H.L., J.A.H., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Joshua A Hirsch
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
- Department of Radiology (R.G., W.A.M., M.H.L., J.A.H., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Karen Buch
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
| | - Marc D Succi
- From the Harvard Medical School (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Boston, Massachusetts
- Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO) (M.H.M., A.R.A., A.H.K., E.K., G.R., W.L., S.R., R.G., W.A.M., M.H.L., J.A.H., K.B., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
- Department of Radiology (R.G., W.A.M., M.H.L., J.A.H., M.D.S.), Massachusetts General Hospital, Boston, Massachusetts
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Jiménez Mascuñán C, Martínez Martínez A, Ríos Pelegrina R, Láinez Ramos-Bossini AJ. Epidural angioleiomyoma: an extraordinary cause of compressive myelopathy-MRI findings with histopathological correlation. EUROPEAN SPINE JOURNAL : OFFICIAL PUBLICATION OF THE EUROPEAN SPINE SOCIETY, THE EUROPEAN SPINAL DEFORMITY SOCIETY, AND THE EUROPEAN SECTION OF THE CERVICAL SPINE RESEARCH SOCIETY 2024; 33:2892-2896. [PMID: 38647603 DOI: 10.1007/s00586-024-08265-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 02/15/2024] [Accepted: 04/07/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND Angioleiomyomas are benign mesenchymal tumors usually located in the limbs, with anecdotal reports in the spine. We present an atypical case of an epidural spine angioleiomyoma presenting with compressive myelopathy symptoms. The diagnosis was suggested based on MRI findings, and subsequently confirmed histopathologically. RESULTS This is the first known occurrence of pure spinal epidural angioleiomyoma as a source of compressive myelopathy. The imaging presentation, especially the 'dark reticular sign' on MRI, was crucial in suggesting the diagnosis despite the atypical location CONCLUSION: This report serves to raise awareness among clinicians and radiologists about including angioleiomyoma in differential diagnoses for spinal epidural lesions with indicative MRI features. The favorable outcome after surgical intervention underscores the necessity of swift and accurate diagnosis followed by appropriate treatment for such uncommon spinal tumors.
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Affiliation(s)
- Carlos Jiménez Mascuñán
- Department of Radiology, Hospital Universitario Virgen de Las Nieves, Avda. Fuerzas Armadas, 2, 18014, Granada, Spain
- Advanced Medical Imaging Group (TeCe22), Biosanitary Institute of Granada (Ibs.GRANADA), 18016, Granada, Spain
| | - Alberto Martínez Martínez
- Department of Radiology, Hospital Universitario Virgen de Las Nieves, Avda. Fuerzas Armadas, 2, 18014, Granada, Spain
- Advanced Medical Imaging Group (TeCe22), Biosanitary Institute of Granada (Ibs.GRANADA), 18016, Granada, Spain
| | - Rosa Ríos Pelegrina
- Department of Pathology, Hospital Universitario Virgen de Las Nieves, 18014, Granada, Spain
- Advanced Medical Imaging Group (TeCe22), Biosanitary Institute of Granada (Ibs.GRANADA), 18016, Granada, Spain
| | - Antonio Jesús Láinez Ramos-Bossini
- Department of Radiology, Hospital Universitario Virgen de Las Nieves, Avda. Fuerzas Armadas, 2, 18014, Granada, Spain.
- Advanced Medical Imaging Group (TeCe22), Biosanitary Institute of Granada (Ibs.GRANADA), 18016, Granada, Spain.
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Fournel J, Hermier M, Martin A, Gamondès D, Tommasino E, Broussolle T, Morgado A, Baassiri W, Cotton F, Berthezène Y, Bani-Sadr A. It Looks Like a Spinal Cord Tumor but It Is Not. Cancers (Basel) 2024; 16:1004. [PMID: 38473365 DOI: 10.3390/cancers16051004] [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: 02/07/2024] [Revised: 02/23/2024] [Accepted: 02/26/2024] [Indexed: 03/14/2024] Open
Abstract
Differentiating neoplastic from non-neoplastic spinal cord pathologies may be challenging due to overlapping clinical and radiological features. Spinal cord tumors, which comprise only 2-4% of central nervous system tumors, are rarer than non-tumoral myelopathies of inflammatory, vascular, or infectious origins. The risk of neurological deterioration and the high rate of false negatives or misdiagnoses associated with spinal cord biopsies require a cautious approach. Facing a spinal cord lesion, prioritizing more common non-surgical myelopathies in differential diagnoses is essential. A comprehensive radiological diagnostic approach is mandatory to identify spinal cord tumor mimics. The diagnostic process involves a multi-step approach: detecting lesions primarily using MRI techniques, precise localization of lesions, assessing lesion signal intensity characteristics, and searching for potentially associated anomalies at spinal cord and cerebral MRI. This review aims to delineate the radiological diagnostic approach for spinal cord lesions that may mimic tumors and briefly highlight the primary pathologies behind these lesions.
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Affiliation(s)
- Julien Fournel
- Department of Neuroradiology, East Group Hospital, Hospices Civils de Lyon, 59 Bd Pinel, 69500 Bron, France
| | - Marc Hermier
- Department of Neuroradiology, East Group Hospital, Hospices Civils de Lyon, 59 Bd Pinel, 69500 Bron, France
| | - Anna Martin
- Department of Neuroradiology, East Group Hospital, Hospices Civils de Lyon, 59 Bd Pinel, 69500 Bron, France
| | - Delphine Gamondès
- Department of Neuroradiology, East Group Hospital, Hospices Civils de Lyon, 59 Bd Pinel, 69500 Bron, France
| | - Emanuele Tommasino
- Department of Neuroradiology, East Group Hospital, Hospices Civils de Lyon, 59 Bd Pinel, 69500 Bron, France
| | - Théo Broussolle
- Department of Spine and Spinal Cord Neurosurgery, East Group Hospital, Hospices Civils de Lyon, 59 Bd Pinel, 69500 Bron, France
| | - Alexis Morgado
- Department of Spine and Spinal Cord Neurosurgery, East Group Hospital, Hospices Civils de Lyon, 59 Bd Pinel, 69500 Bron, France
| | - Wassim Baassiri
- Department of Spine and Spinal Cord Neurosurgery, East Group Hospital, Hospices Civils de Lyon, 59 Bd Pinel, 69500 Bron, France
| | - Francois Cotton
- CREATIS Laboratory, CNRS UMR 5220, INSERM U1294, Claude Bernard Lyon I University, 7 Avenue Jean Capelle, 69100 Villeurbanne, France
- Department of Radiology, South Lyon Hospital, Hospices Civils de Lyon, 165 Chemin du Grand Revoyet, 69495 Pierre-Bénite, France
| | - Yves Berthezène
- Department of Neuroradiology, East Group Hospital, Hospices Civils de Lyon, 59 Bd Pinel, 69500 Bron, France
- CREATIS Laboratory, CNRS UMR 5220, INSERM U1294, Claude Bernard Lyon I University, 7 Avenue Jean Capelle, 69100 Villeurbanne, France
| | - Alexandre Bani-Sadr
- Department of Neuroradiology, East Group Hospital, Hospices Civils de Lyon, 59 Bd Pinel, 69500 Bron, France
- CREATIS Laboratory, CNRS UMR 5220, INSERM U1294, Claude Bernard Lyon I University, 7 Avenue Jean Capelle, 69100 Villeurbanne, France
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Payne DL, Xu X, Faraji F, John K, Pradas KF, Bernard VV, Bangiyev L, Prasanna P. Automated Detection of Cervical Spinal Stenosis and Cord Compression via Vision Transformer and Rules-Based Classification. AJNR Am J Neuroradiol 2024; 45:ajnr.A8141. [PMID: 38360785 PMCID: PMC11288556 DOI: 10.3174/ajnr.a8141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 12/15/2023] [Indexed: 02/17/2024]
Abstract
BACKGROUND AND PURPOSE Cervical spinal cord compression, defined as spinal cord deformity and severe narrowing of the spinal canal in the cervical region, can lead to severe clinical consequences, including intractable pain, sensory disturbance, paralysis, and even death, and may require emergent intervention to prevent negative outcomes. Despite the critical nature of cord compression, no automated tool is available to alert clinical radiologists to the presence of such findings. This study aims to demonstrate the ability of a vision transformer (ViT) model for the accurate detection of cervical cord compression. MATERIALS AND METHODS A clinically diverse cohort of 142 cervical spine MRIs was identified, 34% of which were normal or had mild stenosis, 31% with moderate stenosis, and 35% with cord compression. Utilizing gradient-echo images, slices were labeled as no cord compression/mild stenosis, moderate stenosis, or severe stenosis/cord compression. Segmentation of the spinal canal was performed and confirmed by neuroradiology faculty. A pretrained ViT model was fine-tuned to predict section-level severity by using a train:validation:test split of 60:20:20. Each examination was assigned an overall severity based on the highest level of section severity, with an examination labeled as positive for cord compression if ≥1 section was predicted in the severe category. Additionally, 2 convolutional neural network (CNN) models (ResNet50, DenseNet121) were tested in the same manner. RESULTS The ViT model outperformed both CNN models at the section level, achieving section-level accuracy of 82%, compared with 72% and 78% for ResNet and DenseNet121, respectively. ViT patient-level classification achieved accuracy of 93%, sensitivity of 0.90, positive predictive value of 0.90, specificity of 0.95, and negative predictive value of 0.95. Receiver operating characteristic area under the curve was greater for ViT than either CNN. CONCLUSIONS This classification approach using a ViT model and rules-based classification accurately detects the presence of cervical spinal cord compression at the patient level. In this study, the ViT model outperformed both conventional CNN approaches at the section and patient levels. If implemented into the clinical setting, such a tool may streamline neuroradiology workflow, improving efficiency and consistency.
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Affiliation(s)
- David L Payne
- From the Department of Radiology (D.L.P., F.F., K.J., K.F.P., V.V.B., L.B.), Stony Brook University Hospital, Stony Brook, New York
- Department of Biomedical Informatics (D.L.P., X.X., F.F., K.J., P.P.), Stony Brook University, Stony Brook, New York
| | - Xuan Xu
- Department of Biomedical Informatics (D.L.P., X.X., F.F., K.J., P.P.), Stony Brook University, Stony Brook, New York
| | - Farshid Faraji
- From the Department of Radiology (D.L.P., F.F., K.J., K.F.P., V.V.B., L.B.), Stony Brook University Hospital, Stony Brook, New York
- Department of Biomedical Informatics (D.L.P., X.X., F.F., K.J., P.P.), Stony Brook University, Stony Brook, New York
| | - Kevin John
- From the Department of Radiology (D.L.P., F.F., K.J., K.F.P., V.V.B., L.B.), Stony Brook University Hospital, Stony Brook, New York
- Department of Biomedical Informatics (D.L.P., X.X., F.F., K.J., P.P.), Stony Brook University, Stony Brook, New York
| | - Katherine Ferra Pradas
- From the Department of Radiology (D.L.P., F.F., K.J., K.F.P., V.V.B., L.B.), Stony Brook University Hospital, Stony Brook, New York
| | - Vahni Vishala Bernard
- From the Department of Radiology (D.L.P., F.F., K.J., K.F.P., V.V.B., L.B.), Stony Brook University Hospital, Stony Brook, New York
| | - Lev Bangiyev
- From the Department of Radiology (D.L.P., F.F., K.J., K.F.P., V.V.B., L.B.), Stony Brook University Hospital, Stony Brook, New York
| | - Prateek Prasanna
- Department of Biomedical Informatics (D.L.P., X.X., F.F., K.J., P.P.), Stony Brook University, Stony Brook, New York
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Duan S, Cao G, Hua Y, Hu J, Zheng Y, Wu F, Xu S, Rong T, Liu B. Identification of Origin for Spinal Metastases from MR Images: Comparison Between Radiomics and Deep Learning Methods. World Neurosurg 2023; 175:e823-e831. [PMID: 37059360 DOI: 10.1016/j.wneu.2023.04.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 04/06/2023] [Accepted: 04/07/2023] [Indexed: 04/16/2023]
Abstract
OBJECTIVE To determine whether spinal metastatic lesions originated from lung cancer or from other cancers based on spinal contrast-enhanced T1 (CET1) magnetic resonance (MR) images analyzed using radiomics (RAD) and deep learning (DL) methods. METHODS We recruited and retrospectively reviewed 173 patients diagnosed with spinal metastases at two different centers between July 2018 and June 2021. Of these, 68 involved lung cancer and 105 were other types of cancer. They were assigned to an internal cohort of 149 patients, randomly divided into a training set and a validation set, and to an external cohort of 24 patients. All patients underwent CET1-MR imaging before surgery or biopsy. We developed two predictive algorithms: a DL model and a RAD model. We compared performance between models, and against human radiological assessment, via accuracy (ACC) and receiver operating characteristic (ROC) analyses. Furthermore, we analyzed the correlation between RAD and DL features. RESULTS The DL model outperformed RAD model across the board, with ACC/ area under the receiver operating characteristic curve (AUC) values of 0.93/0.94 (DL) versus 0.84/0.93 (RAD) when applied to the training set from the internal cohort, 0.74/0.76 versus 0.72/0.75 when applied to the validation set, and 0.72/0.76 versus 0.69/0.72 when applied to the external test cohort. For the validation set, it also outperformed expert radiological assessment (ACC: 0.65, AUC: 0.68). We only found weak correlations between DL and RAD features. CONCLUSION The DL algorithm successfully identified the origin of spinal metastases from pre-operative CET1-MR images, outperforming both RAD models and expert assessment by trained radiologists.
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Affiliation(s)
- Shuo Duan
- Department of Orthopaedic Surgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Guanmei Cao
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yichun Hua
- Department of Medical Oncology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Junnan Hu
- Department of Orthopaedic Surgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yali Zheng
- Department of Respiratory, Critical Care, and Sleep Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Fangfang Wu
- Department of Respiratory, Critical Care, and Sleep Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Shuai Xu
- Department of Spinal Surgery, Peking University People's Hospital, Peking University, Beijing, China
| | - Tianhua Rong
- Department of Orthopaedic Surgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Baoge Liu
- Department of Orthopaedic Surgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China.
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7
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Duan S, Hua Y, Cao G, Hu J, Cui W, Zhang D, Xu S, Rong T, Liu B. Differential diagnosis of benign and malignant vertebral compression fractures: Comparison and correlation of radiomics and deep learning frameworks based on spinal CT and clinical characteristics. Eur J Radiol 2023; 165:110899. [PMID: 37300935 DOI: 10.1016/j.ejrad.2023.110899] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 04/28/2023] [Accepted: 05/26/2023] [Indexed: 06/12/2023]
Abstract
PURPOSE Differentiating benign from malignant vertebral compression fractures (VCFs) is a diagnostic dilemma in clinical practice. To improve the accuracy and efficiency of diagnosis, we evaluated the performance of deep learning and radiomics methods based on computed tomography (CT) and clinical characteristics in differentiating between Osteoporosis VCFs (OVCFs) and malignant VCFs (MVCFs). METHODS We enrolled a total of 280 patients (155 with OVCFs and 125 with MVCFs) and randomly divided them into a training set (80%, n = 224) and a validation set (20%, n = 56). We developed three predictive models: a deep learning (DL) model, a radiomics (Rad) model, and a combined DL_Rad model, using CT and clinical characteristics data. The Inception_V3 served as the backbone of the DL model. The input data for the DL_Rad model consisted of the combined features of Rad and DCNN features. We calculated the receiver operating characteristic curve, area under the curve (AUC), and accuracy (ACC) to assess the performance of the models. Additionally, we calculated the correlation between Rad features and DCNN features. RESULTS For the training set, the DL_Rad model achieved the best results, with an AUC of 0.99 and ACC of 0.99, followed by the Rad model (AUC: 0.99, ACC: 0.97) and DL model (AUC: 0.99, ACC: 0.94). For the validation set, the DL_Rad model (with an AUC of 0.97 and ACC of 0.93) outperformed the Rad model (with an AUC: 0.93 and ACC: 0.91) and the DL model (with an AUC: 0.89 and ACC: 0.88). Rad features achieved better classifier performance than the DCNN features, and their general correlations were weak. CONCLUSIONS The Deep learnig model, Radiomics model, and Deep learning Radiomics model achieved promising results in discriminating MVCFs from OVCFs, and the DL_Rad model performed the best.
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Affiliation(s)
- Shuo Duan
- Department of Orthopaedic Surgery, Beijing Tiantan Hospital, Capital Medical University, China
| | - Yichun Hua
- Department of Medical Oncology, Beijing Tiantan Hospital, Capital Medical University, China
| | - Guanmei Cao
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, China
| | - Junnan Hu
- Department of Orthopaedic Surgery, Beijing Tiantan Hospital, Capital Medical University, China
| | - Wei Cui
- Department of Orthopaedic Surgery, Beijing Tiantan Hospital, Capital Medical University, China
| | - Duo Zhang
- Department of Orthopaedic Surgery, Beijing Tiantan Hospital, Capital Medical University, China
| | - Shuai Xu
- Department of Spinal Surgery, Peking University People's Hospital, Peking University, China
| | - Tianhua Rong
- Department of Orthopaedic Surgery, Beijing Tiantan Hospital, Capital Medical University, China
| | - Baoge Liu
- Department of Orthopaedic Surgery, Beijing Tiantan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing, China.
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8
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Mohammed HJ, Hammady MM, Abbas FN. A Comparison Between Somatosensory Evoked Potentials and Spine MRI in the Diagnosis of Non-compressive Myelopathy: Which Is More Accurate? Cureus 2023; 15:e38051. [PMID: 37228549 PMCID: PMC10207993 DOI: 10.7759/cureus.38051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 04/23/2023] [Indexed: 05/27/2023] Open
Abstract
INTRODUCTION Non-compressive myelopathy is a neurological disorder due to pathological processes affecting the spinal cord in the absence of clinical and radiological evidence of spinal cord compression. Two commonly used diagnostic tools for non-compressive myelopathy are somatosensory evoked potentials (SSEPs) and magnetic resonance imaging (MRI). SSEPs are a neurophysiological tool used to assess the functional integrity of the spinal cord. MRI, on the other hand, is the mainstay imaging modality used for identifying compressive lesions and other structural abnormalities in the spinal cord. The aim of this study was to test the diagnostic accuracy of SSEPs versus spine MRI in the diagnosis and assessment of the severity of non-compressive myelopathy using the Modified Japanese Orthopaedic Association (mJOA) clinical severity score. METHODS Our study included 63 subjects. Whole spine MRI and SSEPs (median and tibial SSEP bilaterally) were done for all subjects; their results were compared according to their relation to the mJOA score and classified into mild, moderate, and severe. The control group was examined to establish normative data for SSEP results and compared with cases. Blood investigations such as complete blood count, thyroid function test, A1C, HIV tests, venereal disease research laboratory test, erythrocyte sedimentation rate, C-reactive protein, and antinuclear antibody tests were done. Blood tests for vitamin B12 levels were done for patients who were suspected of sub-acute combined degeneration of the spinal cord; cerebrospinal fluid (CSF) analysis was done for patients suspected of multiple sclerosis (MS), acute transverse myelitis (ATM), or other inflammatory/infectious diseases. CSF was analyzed for cell count, cytology, protein, and oligoclonal bands (if indicated). RESULTS No mild categories were registered in this study; 30% of patients were moderate and 70% were severe. Causes for non-compressive myelopathy in this study were hereditary degenerative ataxias in 12 (38.71%), ATM in 8 (25.81%), and MS in 5 (16.13%); other causes included vitamin B12 deficiency in 2 (6.45%), ischemia in 2 (6.45%), and an unknown cause in 2 (6.45%). SSEPs showed abnormal results in all patients (31; 100%) whereas MRI showed abnormality in only seven patients (22.6%). SSEP sensitivity for detecting severe cases was around 63.6% while that for MRI was 27.3%. CONCLUSION The study concluded that SSEPs were more reliable for the detection of non-compressive myelopathies rather than MRI and correlated better with clinical severity. Performing SSEPs is recommended for all patients with non-compressive myelopathy, especially those with negative imaging.
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Affiliation(s)
| | - Mazin M Hammady
- Department of Internal Medicine, College of Medicine, University of Basrah, Basrah, IRQ
| | - Farah N Abbas
- Department of Physiology, College of Medicine, University of Babylon, Babylon, IRQ
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9
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Ornelas-Dorian C, Jhun P. A Case Report of a Man with Burning Arm and Leg Weakness. JOURNAL OF EDUCATION & TEACHING IN EMERGENCY MEDICINE 2022; 7:V4-V6. [PMID: 37465137 PMCID: PMC10332663 DOI: 10.21980/j8v659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Figures] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 08/16/2022] [Indexed: 07/20/2023]
Abstract
A 44-year-old male presented with sudden onset of severe left arm burning dysesthesia and bilateral leg numbness and weakness for several hours. He denied any recent illnesses or trauma and was previously healthy. His exam showed decreased strength to his left upper extremity, decreased light touch sensation to bilateral lower extremities, and urinary retention. Computed tomography (CT) and magnetic resonance imaging (MRI) of the cervical spine were performed, which demonstrated acute cervical myelopathy due to congenital cervical stenosis, a less common finding. Congenital cervical stenosis is the narrowing of the cervical spinal canal that is not due to structural, infectious, vascular, or malignant causes. This is an important diagnosis to consider in patients who present with neurologic symptoms without risk factors for common myelopathy causes (eg, degenerative changes). Early diagnosis and treatment are essential to prevent long term neurologic deficits. Topics Neurosurgery, cervical myelopathy, acute neurologic deficits.
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Affiliation(s)
- Carolina Ornelas-Dorian
- University of California, San Francisco, Department of Emergency Medicine, San Francisco, CA
| | - Paul Jhun
- University of California, San Francisco, Department of Emergency Medicine, San Francisco, CA
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10
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Bahouth SM, Yeboa DN, Ghia AJ, Tatsui CE, Alvarez-Breckenridge CA, Beckham TH, Bishio AJ, Li J, McAleer MF, North RY, Rhines LD, Swanson TA, Chenyang W, Amini B. Multidisciplinary management of spinal metastases: what the radiologist needs to know. Br J Radiol 2022; 95:20220266. [PMID: 35856792 PMCID: PMC9815745 DOI: 10.1259/bjr.20220266] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 06/17/2022] [Accepted: 07/11/2022] [Indexed: 01/13/2023] Open
Abstract
The modern management of spinal metastases requires a multidisciplinary approach that includes radiation oncologists, surgeons, medical oncologists, and diagnostic and interventional radiologists. The diagnostic radiologist can play an important role in the multidisciplinary team and help guide assessment of disease and selection of appropriate therapy. The assessment of spine metastases is best performed on MRI, but imaging from other modalities is often needed. We provide a review of the clinical and imaging features that are needed by the multidisciplinary team caring for patients with spine metastases and stress the importance of the spine radiologist taking responsibility for synthesizing imaging features across multiple modalities to provide a report that advances patient care.
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Affiliation(s)
- Sarah M Bahouth
- Musculoskeletal Imaging and Intervention Department, Brigham and Women’s Hospital, Boston MA, USA
| | - Debra N Yeboa
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Amol J Ghia
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Claudio E Tatsui
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Thomas H Beckham
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Andrew J Bishio
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jing Li
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Mary Frances McAleer
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Robert Y North
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Laurence D Rhines
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Todd A Swanson
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Wang Chenyang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Behrang Amini
- Department of Musculoskeletal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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11
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Hallinan JTPD, Ge S, Zhu L, Zhang W, Lim YT, Thian YL, Jagmohan P, Kuah T, Lim DSW, Low XZ, Teo EC, Barr Kumarakulasinghe N, Yap QV, Chan YH, Tan JH, Kumar N, Vellayappan BA, Ooi BC, Quek ST, Makmur A. Diagnostic Accuracy of CT for Metastatic Epidural Spinal Cord Compression. Cancers (Basel) 2022; 14:cancers14174231. [PMID: 36077767 PMCID: PMC9454807 DOI: 10.3390/cancers14174231] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 08/23/2022] [Accepted: 08/25/2022] [Indexed: 11/16/2022] Open
Abstract
Background: Early diagnosis of metastatic epidural spinal cord compression (MESCC) is vital to expedite therapy and prevent paralysis. Staging CT is performed routinely in cancer patients and presents an opportunity for earlier diagnosis. Methods: This retrospective study included 123 CT scans from 101 patients who underwent spine MRI within 30 days, excluding 549 CT scans from 216 patients due to CT performed post-MRI, non-contrast CT, or a gap greater than 30 days between modalities. Reference standard MESCC gradings on CT were provided in consensus via two spine radiologists (11 and 7 years of experience) analyzing the MRI scans. CT scans were labeled using the original reports and by three radiologists (3, 13, and 14 years of experience) using dedicated CT windowing. Results: For normal/none versus low/high-grade MESCC per CT scan, all radiologists demonstrated almost perfect agreement with kappa values ranging from 0.866 (95% CI 0.787–0.945) to 0.947 (95% CI 0.899–0.995), compared to slight agreement for the reports (kappa = 0.095, 95%CI −0.098–0.287). Radiologists also showed high sensitivities ranging from 91.51 (95% CI 84.49–96.04) to 98.11 (95% CI 93.35–99.77), compared to 44.34 (95% CI 34.69–54.31) for the reports. Conclusion: Dedicated radiologist review for MESCC on CT showed high interobserver agreement and sensitivity compared to the current standard of care.
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Affiliation(s)
- James Thomas Patrick Decourcy Hallinan
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
- Correspondence:
| | - Shuliang Ge
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Lei Zhu
- Department of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore
| | - Wenqiao Zhang
- Department of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore
| | - Yi Ting Lim
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Yee Liang Thian
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Pooja Jagmohan
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Tricia Kuah
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
| | - Desmond Shi Wei Lim
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
| | - Xi Zhen Low
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
| | - Ee Chin Teo
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
| | - Nesaretnam Barr Kumarakulasinghe
- National University Cancer Institute, NUH Medical Centre (NUHMC), Levels 8–10, 5 Lower Kent Ridge Road, Singapore 119074, Singapore
| | - Qai Ven Yap
- Biostatistics Unit, Yong Loo Lin School of Medicine, 10 Medical Drive, Singapore 117597, Singapore
| | - Yiong Huak Chan
- Biostatistics Unit, Yong Loo Lin School of Medicine, 10 Medical Drive, Singapore 117597, Singapore
| | - Jiong Hao Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, Singapore 119228, Singapore
| | - Naresh Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E, Lower Kent Ridge Road, Singapore 119228, Singapore
| | - Balamurugan A. Vellayappan
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore 119074, Singapore
| | - Beng Chin Ooi
- Department of Computer Science, School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore
| | - Swee Tian Quek
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Andrew Makmur
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
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12
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Bai J, Grant K, Hussien A, Kawakyu-O'Connor D. Imaging of metastatic epidural spinal cord compression. FRONTIERS IN RADIOLOGY 2022; 2:962797. [PMID: 37492671 PMCID: PMC10365281 DOI: 10.3389/fradi.2022.962797] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 07/18/2022] [Indexed: 07/27/2023]
Abstract
Metastatic epidural spinal cord compression develops in 5-10% of patients with cancer and is becoming more common as advancement in cancer treatment prolongs survival in patients with cancer (1-3). It represents an oncological emergency as metastatic epidural compression in adjacent neural structures, including the spinal cord and cauda equina, and exiting nerve roots may result in irreversible neurological deficits, pain, and spinal instability. Although management of metastatic epidural spinal cord compression remains palliative, early diagnosis and intervention may improve outcomes by preserving neurological function, stabilizing the vertebral column, and achieving localized tumor and pain control. Imaging serves an essential role in early diagnosis of metastatic epidural spinal cord compression, evaluation of the degree of spinal cord compression and extent of tumor burden, and preoperative planning. This review focuses on imaging features and techniques for diagnosing metastatic epidural spinal cord compression, differential diagnosis, and management guidelines.
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13
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Analysis of the Curative Effect and Prognostic Factors of Anterior Cervical Surgery for Spinal Cord Injury without Radiographic Abnormalities. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2022; 2022:6836966. [PMID: 35979000 PMCID: PMC9377897 DOI: 10.1155/2022/6836966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 06/14/2022] [Indexed: 12/02/2022]
Abstract
Objective The study aimed to investigate the effect of anterior cervical surgery in the treatment of spinal cord injury without radiographic abnormalities (SCIWORAs) and analyze the related factors affecting the prognosis of patients. Methods A total of 86 patients with SCIWORA who were admitted to our hospital from June 2018 to March 2021 were selected as the research subjects. According to the different treatment methods selected by the patients, they were divided into the control group (n = 38) and the observation group (n = 48). The control group was treated with conservative therapy, and the observation group was treated with anterior cervical total laminectomy decompression, internal fixation, and bone graft fusion. The efficacy of the treatment was assessed preoperatively and 6 months after surgery using the Japanese Orthopedics Association (JOA) functional evaluation criteria for cervical spinal cord injury. The improvement rate of the JOA score at the last follow-up visit was calculated according to the Hirabayashi formula to evaluate the prognosis of patients. Results The JOA score of the observation group six months after surgery was (14.98 ± 2.75) that was higher than that of the control group (12.16 ± 2.54) (P < 0.05). After surgery, the improvement rate of the JOA score in the observation group was higher than that in the control group (P < 0.05). After surgery, the scores of health condition, physiological function, and role physical in the observation group were (23.18 ± 1.09), (22.75 ± 1.54), and (22.64 ± 1.46), which were higher than those in the control groups (20.94 ± 1.65), (20.26 ± 1.78), and (19.56 ± 1.82) (P < 0.05). The results of univariate analysis showed that the ASIA classification of cervical spinal cord injury, the type of MRI cervical spinal cord injury, the scope of cervical spinal cord injury, lumbar disc herniation, and the time from injury to treatment were all related to the prognosis of the patients (P < 0.05). Multivariate analysis showed that the ASIA classification of cervical spinal cord injury, the type of MRI cervical spinal cord injury, the scope of cervical spinal cord injury, and the time from injury to treatment were the independent factors affecting the prognosis of patients (P < 0.05). Conclusion For patients with SCIWORA, anterior total lamina decompression and internal fixation with bone grafting and fusion can effectively promote the recovery of cervical spinal cord function and improve the prognosis and quality of life of patients. The ASIA classification of cervical spinal cord injury, the type of MRI cervical spinal cord injury, the scope of cervical spinal cord injury, and the time from injury to treatment were the independent prognostic factors for patients.
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14
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Kuah T, Vellayappan BA, Makmur A, Nair S, Song J, Tan JH, Kumar N, Quek ST, Hallinan JTPD. State-of-the-Art Imaging Techniques in Metastatic Spinal Cord Compression. Cancers (Basel) 2022; 14:3289. [PMID: 35805059 PMCID: PMC9265325 DOI: 10.3390/cancers14133289] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 06/24/2022] [Accepted: 06/28/2022] [Indexed: 12/23/2022] Open
Abstract
Metastatic Spinal Cord Compression (MSCC) is a debilitating complication in oncology patients. This narrative review discusses the strengths and limitations of various imaging modalities in diagnosing MSCC, the role of imaging in stereotactic body radiotherapy (SBRT) for MSCC treatment, and recent advances in deep learning (DL) tools for MSCC diagnosis. PubMed and Google Scholar databases were searched using targeted keywords. Studies were reviewed in consensus among the co-authors for their suitability before inclusion. MRI is the gold standard of imaging to diagnose MSCC with reported sensitivity and specificity of 93% and 97% respectively. CT Myelogram appears to have comparable sensitivity and specificity to contrast-enhanced MRI. Conventional CT has a lower diagnostic accuracy than MRI in MSCC diagnosis, but is helpful in emergent situations with limited access to MRI. Metal artifact reduction techniques for MRI and CT are continually being researched for patients with spinal implants. Imaging is crucial for SBRT treatment planning and three-dimensional positional verification of the treatment isocentre prior to SBRT delivery. Structural and functional MRI may be helpful in post-treatment surveillance. DL tools may improve detection of vertebral metastasis and reduce time to MSCC diagnosis. This enables earlier institution of definitive therapy for better outcomes.
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Affiliation(s)
- Tricia Kuah
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (A.M.); (S.N.); (J.S.); (S.T.Q.); (J.T.P.D.H.)
| | - Balamurugan A. Vellayappan
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore 119074, Singapore;
| | - Andrew Makmur
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (A.M.); (S.N.); (J.S.); (S.T.Q.); (J.T.P.D.H.)
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - Shalini Nair
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (A.M.); (S.N.); (J.S.); (S.T.Q.); (J.T.P.D.H.)
| | - Junda Song
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (A.M.); (S.N.); (J.S.); (S.T.Q.); (J.T.P.D.H.)
| | - Jiong Hao Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E Lower Kent Ridge Road, Singapore 119228, Singapore; (J.H.T.); (N.K.)
| | - Naresh Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, 1E Lower Kent Ridge Road, Singapore 119228, Singapore; (J.H.T.); (N.K.)
| | - Swee Tian Quek
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (A.M.); (S.N.); (J.S.); (S.T.Q.); (J.T.P.D.H.)
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
| | - James Thomas Patrick Decourcy Hallinan
- Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore; (A.M.); (S.N.); (J.S.); (S.T.Q.); (J.T.P.D.H.)
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
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15
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Hallinan JTPD, Zhu L, Zhang W, Lim DSW, Baskar S, Low XZ, Yeong KY, Teo EC, Kumarakulasinghe NB, Yap QV, Chan YH, Lin S, Tan JH, Kumar N, Vellayappan BA, Ooi BC, Quek ST, Makmur A. Deep Learning Model for Classifying Metastatic Epidural Spinal Cord Compression on MRI. Front Oncol 2022; 12:849447. [PMID: 35600347 PMCID: PMC9114468 DOI: 10.3389/fonc.2022.849447] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/18/2022] [Indexed: 11/13/2022] Open
Abstract
Background Metastatic epidural spinal cord compression (MESCC) is a devastating complication of advanced cancer. A deep learning (DL) model for automated MESCC classification on MRI could aid earlier diagnosis and referral. Purpose To develop a DL model for automated classification of MESCC on MRI. Materials and Methods Patients with known MESCC diagnosed on MRI between September 2007 and September 2017 were eligible. MRI studies with instrumentation, suboptimal image quality, and non-thoracic regions were excluded. Axial T2-weighted images were utilized. The internal dataset split was 82% and 18% for training/validation and test sets, respectively. External testing was also performed. Internal training/validation data were labeled using the Bilsky MESCC classification by a musculoskeletal radiologist (10-year experience) and a neuroradiologist (5-year experience). These labels were used to train a DL model utilizing a prototypical convolutional neural network. Internal and external test sets were labeled by the musculoskeletal radiologist as the reference standard. For assessment of DL model performance and interobserver variability, test sets were labeled independently by the neuroradiologist (5-year experience), a spine surgeon (5-year experience), and a radiation oncologist (11-year experience). Inter-rater agreement (Gwet’s kappa) and sensitivity/specificity were calculated. Results Overall, 215 MRI spine studies were analyzed [164 patients, mean age = 62 ± 12(SD)] with 177 (82%) for training/validation and 38 (18%) for internal testing. For internal testing, the DL model and specialists all showed almost perfect agreement (kappas = 0.92–0.98, p < 0.001) for dichotomous Bilsky classification (low versus high grade) compared to the reference standard. Similar performance was seen for external testing on a set of 32 MRI spines with the DL model and specialists all showing almost perfect agreement (kappas = 0.94–0.95, p < 0.001) compared to the reference standard. Conclusion A DL model showed comparable agreement to a subspecialist radiologist and clinical specialists for the classification of malignant epidural spinal cord compression and could optimize earlier diagnosis and surgical referral.
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Affiliation(s)
- James Thomas Patrick Decourcy Hallinan
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore.,Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Lei Zhu
- NUS Graduate School, Integrative Sciences and Engineering Programme, National University of Singapore, Singapore, Singapore
| | - Wenqiao Zhang
- Department of Computer Science, School of Computing, National University of Singapore, Singapore, Singapore
| | - Desmond Shi Wei Lim
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore.,Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Sangeetha Baskar
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
| | - Xi Zhen Low
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore.,Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Kuan Yuen Yeong
- Department of Radiology, Ng Teng Fong General Hospital, Singapore, Singapore
| | - Ee Chin Teo
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore
| | | | - Qai Ven Yap
- Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore, Singapore
| | - Yiong Huak Chan
- Biostatistics Unit, Yong Loo Lin School of Medicine, Singapore, Singapore
| | - Shuxun Lin
- Division of Spine Surgery, Department of Orthopaedic Surgery, Ng Teng Fong General Hospital, Singapore, Singapore
| | - Jiong Hao Tan
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore, Singapore
| | - Naresh Kumar
- University Spine Centre, Department of Orthopaedic Surgery, National University Health System, Singapore, Singapore
| | - Balamurugan A Vellayappan
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore, Singapore
| | - Beng Chin Ooi
- Department of Computer Science, School of Computing, National University of Singapore, Singapore, Singapore
| | - Swee Tian Quek
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore.,Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Andrew Makmur
- Department of Diagnostic Imaging, National University Hospital, Singapore, Singapore.,Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
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CHAN CH, DESAI SR, HWANG NC. Cerebrospinal Fluid Drains: Risks in Contemporary Practice. J Cardiothorac Vasc Anesth 2022; 36:2685-2699. [DOI: 10.1053/j.jvca.2022.01.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 01/03/2022] [Accepted: 01/12/2022] [Indexed: 11/11/2022]
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Popp D, Kerschbaum M, Mahr D, Thiedemann C, Ernstberger A, Wiesinger I, Bäumler W, Alt V, Schicho A. Necessity of Immediate MRI Imaging in the Acute Care of Severely Injured Patients. MEDICINA-LITHUANIA 2021; 57:medicina57090982. [PMID: 34577905 PMCID: PMC8470916 DOI: 10.3390/medicina57090982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 09/08/2021] [Accepted: 09/15/2021] [Indexed: 11/16/2022]
Abstract
Background and Objectives: The standard diagnostic procedure for a patient with a suspected polytrauma injury is computed tomography (CT). In individual cases, however, extended acute imaging using magnetic resonance imaging (MRI) can provide valuable and therapy-relevant information. The aim of our cohort study was to find such cases and to describe their characteristics in order to be able to give possible recommendations for MRI application in acute trauma situations. Materials and Methods: In the study period from 2015-2019, an evaluation of the imaging performed on polytrauma patients was carried out. The specific diagnostic and therapeutic criteria of the MRI group were further defined. Results: In total, 580 patients with an ISS ≥16 (injury severity score) were included in the study. Of these 580 patients, 568 patients received a CT scan and 12 patients an MRI scan as part of the initial diagnostic. Altogether, 66.67% of the MRIs took place outside of regular service hours. The main findings for MRI indications were neurological abnormalities with a focus on myelon injuries. Further MRI examinations were performed to rule out vascular injuries. All in all, 58.3% of the MRIs performed resulted in modified therapeutic strategies afterward. Conclusions: MRI in the context of acute diagnostic of a severely injured patient will likely remain reserved for special indications in the future. However, maximum care hospitals with a high flow of severely injured patients should provide 24/7 MR imaging to ensure the best possible care, especially in neurological and blunt vascular injuries.
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Affiliation(s)
- Daniel Popp
- Department of Trauma Surgery, University Medical Centre Regensburg, 93053 Regensburg, Germany; (M.K.); (D.M.); (C.T.); (V.A.)
- Correspondence: ; Tel.: +49-944-6805; Fax: +49-944-6806
| | - Maximilian Kerschbaum
- Department of Trauma Surgery, University Medical Centre Regensburg, 93053 Regensburg, Germany; (M.K.); (D.M.); (C.T.); (V.A.)
| | - Daniel Mahr
- Department of Trauma Surgery, University Medical Centre Regensburg, 93053 Regensburg, Germany; (M.K.); (D.M.); (C.T.); (V.A.)
| | - Claudius Thiedemann
- Department of Trauma Surgery, University Medical Centre Regensburg, 93053 Regensburg, Germany; (M.K.); (D.M.); (C.T.); (V.A.)
| | | | - Isabel Wiesinger
- Institute of Neuroradiology, Medbo Bezirksklinikum Regensburg, 93053 Regensburg, Germany;
| | - Wolf Bäumler
- Department of Radiology, University Medical Centre Regensburg, 93053 Regensburg, Germany; (W.B.); (A.S.)
| | - Volker Alt
- Department of Trauma Surgery, University Medical Centre Regensburg, 93053 Regensburg, Germany; (M.K.); (D.M.); (C.T.); (V.A.)
| | - Andreas Schicho
- Department of Radiology, University Medical Centre Regensburg, 93053 Regensburg, Germany; (W.B.); (A.S.)
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Acute paraplegia with or without coronavirus disease 2019 infection: Decision-making algorithm. J Vasc Surg 2021; 74:1047-1048. [PMID: 34425946 PMCID: PMC8376821 DOI: 10.1016/j.jvs.2021.05.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 05/11/2021] [Indexed: 11/30/2022]
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Winn A, Martin A, Castellon I, Sanchez A, Lavi ES, Munera F, Nunez D. Spine MRI: A Review of Commonly Encountered Emergent Conditions. Top Magn Reson Imaging 2021; 29:291-320. [PMID: 33264271 DOI: 10.1097/rmr.0000000000000261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Over the last 2 decades, the proliferation of magnetic resonance imaging (MRI) availability and continuous improvements in acquisition speeds have led to significantly increased MRI utilization across the health care system, and MRI studies are increasingly ordered in the emergent setting. Depending on the clinical presentation, MRI can yield vital diagnostic information not detectable with other imaging modalities. The aim of this text is to report on the up-to-date indications for MRI of the spine in the ED, and review the various MRI appearances of commonly encountered acute spine pathology, including traumatic injuries, acute non traumatic myelopathy, infection, neoplasia, degenerative disc disease, and postoperative complications. Imaging review will focus on the aspects of the disease process that are not readily resolved with other modalities.
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Affiliation(s)
- Aaron Winn
- University of Miami, Jackson Memorial Hospital, Miami, FL
| | - Adam Martin
- University of Miami, Jackson Memorial Hospital, Miami, FL
| | - Ivan Castellon
- University of Miami, Jackson Memorial Hospital, Miami, FL
| | - Allen Sanchez
- University of Miami, Jackson Memorial Hospital, Miami, FL
| | | | - Felipe Munera
- University of Miami, Jackson Memorial Hospital, Miami, FL
| | - Diego Nunez
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA
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Abstract
PURPOSE OF REVIEW This article reviews the neuroimaging of disorders of the spinal cord and cauda equina, with a focus on MRI. An anatomic approach is used; diseases of the extradural, intradural-extramedullary, and intramedullary (parenchymal) compartments are considered, and both neoplastic and non-neoplastic conditions are covered. Differentiating imaging features are highlighted. RECENT FINDINGS Although T2-hyperintense signal abnormality of the spinal cord can have myriad etiologies, neuroimaging can provide specific diagnoses or considerably narrow the differential diagnosis in many cases. Intradural-extramedullary lesions compressing the spinal cord have a limited differential diagnosis and are usually benign; meningiomas and schwannomas are most common. Extradural lesions can often be specifically diagnosed. Disk herniations are the most commonly encountered mass of the epidural space. Cervical spondylotic myelopathy can cause a characteristic pattern of enhancement, which may be mistaken for an intrinsic myelopathy. A do-not-miss diagnosis of the extradural compartment is idiopathic spinal cord herniation, the appearance of which can overlap with arachnoid cysts and webs. Regarding intrinsic causes of myelopathy, the lesions of multiple sclerosis are characteristically short segment but can be confluent when multiple. Postcontrast MRI can be particularly helpful, including when attempting to differentiate the long-segment myelopathy of neurosarcoidosis and aquaporin-4 (AQP4)-IgG-seropositive neuromyelitis optica spectrum disorder (NMOSD) and when characterizing spinal cord tumors such as primary neoplasms and metastases. Spinal dural arteriovenous fistula is another do-not-miss diagnosis, with characteristic MRI features both precontrast and postcontrast. Tract-specific white matter involvement can be a clue for diseases such as subacute combined degeneration, paraneoplastic myelopathy, and radiation myelitis, whereas gray matter-specific involvement can suggest conditions such as cord infarct, viral myelitis, or myelin oligodendrocyte glycoprotein (MOG)-IgG associated disorder. SUMMARY Knowledge of the neuroimaging findings of the many causes of spinal cord and cauda equina dysfunction is critical for both neurologists and neuroradiologists. A structured approach to lesion compartmental location and imaging feature characterization is recommended.
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The practice of emergency radiology throughout Europe: a survey from the European Society of Emergency Radiology on volume, staffing, equipment, and scheduling. Eur Radiol 2020; 31:2994-3001. [PMID: 33151392 DOI: 10.1007/s00330-020-07436-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 10/02/2020] [Accepted: 10/15/2020] [Indexed: 10/23/2022]
Abstract
OBJECTIVES To obtain information from radiology departments throughout Europe regarding the practice of emergency radiology METHODS: A survey which comprised of 24 questions was developed and made available online. The questionnaire was sent to 1097 chairs of radiology departments throughout Europe using the ESR database. All data were collected and analyzed using IBM SPSS Statistics software, version 20 (IBM). RESULTS A total of 1097 radiologists were asked to participate, 109 responded to our survey. The response rate was 10%. From our survey, 71.6% of the hospitals had more than 500 beds. Ninety-eight percent of hospitals have an active teaching affiliation. In large trauma centers, emergency radiology was considered a dedicated section. Fifty-three percent of institutions have dedicated emergency radiology sections. Less than 30% had all imaging modalities available. Seventy-nine percent of institutions have 24/7 coverage by staff radiologists. Emergency radiologists interpret cross-sectional body imaging, US scans, and basic CT/MRI neuroimaging in more than 50% of responding institutions. Cardiac imaging examinations/procedures are usually performed by cardiologist in 53% of institutions, while non-cardiac vascular procedures are largely performed and interpreted by interventional radiologists. Most people consider the European Diploma in Emergency Radiology an essential tool to advance the education and the dissemination of information within the specialty of emergency radiology. CONCLUSION Emergency radiologists have an active role in the emergency medical team. Indeed, based upon our survey, they have to interact with emergency physicians and surgeons in the management of critically ill patients. A broad skillset from ultrasonography and basic neuroimaging is required. KEY POINTS • At most major trauma centers in Europe, emergency imaging is currently performed by all radiologists in specific units who are designated in the emergency department. • Radiologists in the emergency section at present have a broad skillset, which includes cross-sectional body imaging, ultrasonography, and basic neuroimaging of the brain and spine. • A dedicated curriculum that certifies a subspecialty in emergency radiology with a diploma offered by the European Society of Emergency Radiology demonstrates a great interest by the vast majority of the respondents.
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