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Zhao W, Qin S, Wang Q, Chen Y, Liu K, Xin P, Lang N. Assessment of Hidden Blood Loss in Spinal Metastasis Surgery: A Comprehensive Approach with MRI-Based Radiomics Models. J Magn Reson Imaging 2024; 59:2023-2032. [PMID: 37578031 DOI: 10.1002/jmri.28954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 08/01/2023] [Accepted: 08/01/2023] [Indexed: 08/15/2023] Open
Abstract
BACKGROUND Patients undergoing surgery for spinal metastasis are predisposed to hidden blood loss (HBL), which is associated with poor surgical outcomes but unpredictable. PURPOSE To evaluate the role of MRI-based radiomics models for assess the risk of HBL in patients undergoing spinal metastasis surgery. STUDY TYPE Retrospective. SUBJECTS 202 patients (42.6% female) operated on for spinal metastasis with a mean age of 58 ± 11 years were divided into a training (n = 162) and a validation cohort (n = 40). FIELD STRENGTH/SEQUENCE 1.5T or 3.0T scanners. Sagittal T1-weighted and fat-suppressed T2-weighted imaging sequences. ASSESSMENT HBL was calculated using the Gross formula. Patients were classified as low and high HBL group, with 1000 mL as the threshold. Radiomics models were constructed with radiomics features. The radiomics score (Radscore) was obtained from the optimal radiomics model. Clinical variables were accessed using univariate and multivariate logistic regression analyses. Independent risk variables were used to build a clinical model. Clinical variables combined with Radscore were used to establish a combined model. STATISTICAL TESTS Predictive performance was evaluated using area under the curve (AUC), accuracy, sensitivity, specificity, and F1 score. Calibration curves and decision curves analyses were produced to evaluate the accuracy and clinical utility. RESULTS Among the radiomics models, the fusion (T1WI + FS-T2WI) model demonstrated the highest predictive efficacy (AUC: 0.744, 95% confidence interval [CI]: 0.576-0.914). The Radscore model (AUC: 0.809, 95% CI: 0.664-0.954) performs slightly better than the clinical model (AUC: 0.721, 95% CI: 0.524-0.918; P = 0.418) and the combined model (AUC: 0.752, 95% CI: 0.593-0.911; P = 0.178). DATA CONCLUSION A radiomics model may serve as a promising assessment tool for the risk of HBL in patients undergoing spinal metastasis surgery, and guide perioperative planning to improve surgical outcomes. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Weili Zhao
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Siyuan Qin
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Qizheng Wang
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Yongye Chen
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Ke Liu
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Peijin Xin
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Ning Lang
- Department of Radiology, Peking University Third Hospital, Beijing, China
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Creze M, Ghaouche J, Missenard G, Lazure T, Cluzel G, Devilder M, Briand S, Soubeyrand M, Meyrignac O, Carlier RY, Court C, Bouthors C. Understanding a mass in the paraspinal region: an anatomical approach. Insights Imaging 2023; 14:128. [PMID: 37466751 DOI: 10.1186/s13244-023-01462-1] [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: 05/09/2023] [Accepted: 06/10/2023] [Indexed: 07/20/2023] Open
Abstract
The paraspinal region encompasses all tissues around the spine. The regional anatomy is complex and includes the paraspinal muscles, spinal nerves, sympathetic chains, Batson's venous plexus and a rich arterial network. A wide variety of pathologies can occur in the paraspinal region, originating either from paraspinal soft tissues or the vertebral column. The most common paraspinal benign neoplasms include lipomas, fibroblastic tumours and benign peripheral nerve sheath tumours. Tumour-like masses such as haematomas, extramedullary haematopoiesis or abscesses should be considered in patients with suggestive medical histories. Malignant neoplasms are less frequent than benign processes and include liposarcomas and undifferentiated sarcomas. Secondary and primary spinal tumours may present as midline expansile soft tissue masses invading the adjacent paraspinal region. Knowledge of the anatomy of the paraspinal region is of major importance since it allows understanding of the complex locoregional tumour spread that can occur via many adipose corridors, haematogenous pathways and direct contact. Paraspinal tumours can extend into other anatomical regions, such as the retroperitoneum, pleura, posterior mediastinum, intercostal space or extradural neural axis compartment. Imaging plays a crucial role in formulating a hypothesis regarding the aetiology of the mass and tumour staging, which informs preoperative planning. Understanding the complex relationship between the different elements and the imaging features of common paraspinal masses is fundamental to achieving a correct diagnosis and adequate patient management. This review gives an overview of the anatomy of the paraspinal region and describes imaging features of the main tumours and tumour-like lesions that occur in the region.
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Affiliation(s)
- Maud Creze
- Department of Radiology, Assistance Publique des Hôpitaux de Paris, GH Université Paris- Saclay, DMU Smart Imaging, Bicêtre Teaching Hospital, Le Kremlin-Bicêtre, France.
- BioMaps, Université Paris-Saclay, Hôpital Kremlin-Bicêtre, 78 rue du Général Leclerc, 94270, Le Kremlin-Bicêtre, France.
| | - Jessica Ghaouche
- Department of Radiology, Assistance Publique des Hôpitaux de Paris, GH Université Paris- Saclay, DMU Smart Imaging, Bicêtre Teaching Hospital, Le Kremlin-Bicêtre, France
| | - Gilles Missenard
- Department of Orthopedic Surgery, Assistance Publique des Hôpitaux de Paris, GH Université Paris-Saclay, DMU de Chirurgie Traumatologie Orthopédique-Chirurgie Plastique- Reconstruction, Bicêtre Teaching Hospital, Le Kremlin-Bicêtre, France
| | - Thierry Lazure
- Department of Pathology, Assistance Publique des Hôpitaux de Paris, GH Université Paris-Saclay, DMU Smart Imaging, Bicêtre hospital, Le Kremlin Bicêtre, France
| | - Guillaume Cluzel
- Department of Radiology, Assistance Publique des Hôpitaux de Paris, GH Université Paris- Saclay, DMU Smart Imaging, Bicêtre Teaching Hospital, Le Kremlin-Bicêtre, France
| | - Matthieu Devilder
- Department of Radiology, Assistance Publique des Hôpitaux de Paris, GH Université Paris- Saclay, DMU Smart Imaging, Bicêtre Teaching Hospital, Le Kremlin-Bicêtre, France
| | - Sylvain Briand
- Department of Orthopedic Surgery, Assistance Publique des Hôpitaux de Paris, GH Université Paris-Saclay, DMU de Chirurgie Traumatologie Orthopédique-Chirurgie Plastique- Reconstruction, Bicêtre Teaching Hospital, Le Kremlin-Bicêtre, France
| | | | - Olivier Meyrignac
- Department of Radiology, Assistance Publique des Hôpitaux de Paris, GH Université Paris- Saclay, DMU Smart Imaging, Bicêtre Teaching Hospital, Le Kremlin-Bicêtre, France
- BioMaps, Université Paris-Saclay, Hôpital Kremlin-Bicêtre, 78 rue du Général Leclerc, 94270, Le Kremlin-Bicêtre, France
| | - Robert-Yves Carlier
- Department of Radiology, Assistance Publique des Hôpitaux de Paris, GH Université Paris- Saclay, DMU Smart Imaging, Garches Teaching Hospital, Le Kremlin-Bicêtre, France
| | - Charles Court
- Department of Orthopedic Surgery, Assistance Publique des Hôpitaux de Paris, GH Université Paris-Saclay, DMU de Chirurgie Traumatologie Orthopédique-Chirurgie Plastique- Reconstruction, Bicêtre Teaching Hospital, Le Kremlin-Bicêtre, France
| | - Charlie Bouthors
- Department of Orthopedic Surgery, Assistance Publique des Hôpitaux de Paris, GH Université Paris-Saclay, DMU de Chirurgie Traumatologie Orthopédique-Chirurgie Plastique- Reconstruction, Bicêtre Teaching Hospital, Le Kremlin-Bicêtre, France
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Deboever N, Mitchell KG, Feldman HA, Cascone T, Sepesi B. Current Surgical Indications for Non-Small-Cell Lung Cancer. Cancers (Basel) 2022; 14:1263. [PMID: 35267572 PMCID: PMC8909782 DOI: 10.3390/cancers14051263] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 02/05/2022] [Accepted: 02/24/2022] [Indexed: 02/01/2023] Open
Abstract
With recent strides made within the field of thoracic oncology, the management of NSCLC is evolving rapidly. Careful patient selection and timing of multi-modality therapy to permit the optimization of therapeutic benefit must be pursued. While chemotherapy and radiotherapy continue to have a role in the management of lung cancer, surgical therapy remains an essential component of lung cancer treatment in early, locally and regionally advanced, as well as in selected, cases of metastatic disease. Recent and most impactful advances in the treatment of lung cancer relate to the advent of immunotherapy and targeted therapy, molecular profiling, and predictive biomarker discovery. Many of these systemic therapies are a part of the standard of care in metastatic NSCLC, and their indications are expanding towards surgically operable lung cancer to improve survival outcomes. Numerous completed and ongoing clinical trials in the surgically operable NSCLC speak to the interest and importance of the multi-modality therapy even in earlier stages of NSCLC. In this review, we focus on the current standard of care indications for surgical therapy in stage I-IV NSCLC as well as on the anticipated future direction of multi-disciplinary lung cancer therapy.
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Affiliation(s)
- Nathaniel Deboever
- Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (N.D.); (K.G.M.); (H.A.F.)
| | - Kyle G. Mitchell
- Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (N.D.); (K.G.M.); (H.A.F.)
| | - Hope A. Feldman
- Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (N.D.); (K.G.M.); (H.A.F.)
| | - Tina Cascone
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA;
| | - Boris Sepesi
- Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (N.D.); (K.G.M.); (H.A.F.)
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