Interventions for the treatment of metastatic extradural spinal cord compression in adults.
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ABSTRACT:
SUBMITTER: George R
PROVIDER: S-EPMC6513178 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:RATIONALE:Rosai-Dorfman disease (RDD) is a rare benign histiocytic disease that is commonly characterized by massive painless cervical lymphadenopathy and systemic manifestations. Isolated extranodal involvement, especially spinal involvement, is extremely rare. PATIENT CONCERNS:A 28-year-old man presented with intermittent dorsodynia and bilateral lower-limb weakness and numbness. A magnetic resonance scan (MRI) showed an extradural lesion of the T6-T9 thoracic spine that lead to cord compression. DIAGNOSES:Histopathological findings showed distinctive emperipolesis and immunohistochemistry results that were positive for cluster of differentiation CD68 and S100. Therefore, we diagnosed the Rosai-Dorfman disease. INTERVENTIONS:we performed a nearly total surgical resection and a limited T6-T9 laminectomy. OUTCOMES:Postoperatively, the patient's symptoms were partially relieved and experienced no recurrence during the 6-month follow-up. The preoperative diagnosis of isolated spinal RDD still remains challenging. LESSONS:Thus, we should consider RDD in the differential diagnosis of the central nervous system. Besides surgical resection, the treatment also included radiation, chemotherapy or monoclonal antibodies. However, the optimal treatment remains controversial. Therefore, we should exert all our energies on the exploration of etiology and adjuvant therapy for this disease.
| S-EPMC6200482 | biostudies-other
Project description:Prostate cancer is the second common etiology of cord compression after lung cancer. Its slow natural history justifies an aggressive treatment. The fact that the metastatic lesion precedes the primary tumor remains rare. We report the case of a 86 year-old man who was admitted for heaviness of both lower limbs responsible for gait disorder. He had flaccid paraplegia. Spinal MRI showed an epidural lesion. Histology after surgery was compatible for a metastasis of prostatic adenocarcinoma. Spinal cord compression due to prostate cancer is correlated with poor prognosis. The fact that the metastatic lesion precedes the primary tumor remains rare.
| S-EPMC6562330 | biostudies-literature
Project description:Background and purpose - Metastatic spinal cord compression (MSCC) as the initial manifestation of malignancy (IMM) limits the time for diagnostic workup; most often, treatment is required before the final primary tumor diagnosis. We evaluated neurological outcome, complications, survival, and the manner of diagnosing the primary tumor in patients who were operated for MSCC as the IMM. Patients and methods - Records of 69 consecutive patients (51 men) who underwent surgery for MSCC as the IMM were reviewed. The patients had no history of cancer when they presented with pain (n = 2) and/or neurological symptoms (n = 67). Results - The primary tumor was identified in 59 patients. In 10 patients, no specific diagnosis could be established, and they were therefore defined as having cancer of unknown primary tumor (CUP). At the end of the study, 16 patients were still alive (median follow-up 2.5 years). The overall survival time was 20 months. Patients with CUP had the shortest survival (3.5 months) whereas patients with prostate cancer (6 years) and myeloma (5 years) had the longest survival. 20 of the 39 patients who were non-ambulatory preoperatively regained walking ability, and 29 of the 30 ambulatory patients preoperatively retained their walking ability 1 month postoperatively. 15 of the 69 patients suffered from a total of 20 complications within 1 month postoperatively. Interpretation - Postoperative survival with MSCC as the IMM depends on the type of primary tumor. Surgery in these patients maintains and improves ambulatory function.
| S-EPMC5499341 | biostudies-literature
Project description:Introduction:The new concept of separation surgery has changed the surgical paradigms for the treatment of metastatic epidural spinal cord compression (MESCC), shifting from aggressive cytoreductive surgery towards less invasive surgery with the aim to achieve circumferential separation of the spinal cord and create a safe target for high dose Stereotactic Body Radiation Therapy (SBRT), which turned out to be the real game-changer for disease's local control. Discussion:In this review a qualitative analysis of the English literature has been performed according to the rating of evidence, with the aim to underline the increasingly role of the concept of separation surgery in MESCC treatment. A review of the main steps in the evolution of both radiotherapy and surgery fields have been described, highlighting the important results deriving from their integration. Conclusion:Compared with more aggressive surgical approaches, the concept of separation surgery together with the advancements of radiotherapy and the use of SBRT for the treatment of MESCC showed promising results in order to achieve a valuable local control while reducing surgical related morbidities and complications.
| S-EPMC7559860 | biostudies-literature
Project description: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.
| S-EPMC9265325 | biostudies-literature
Project description:BackgroundMetastatic 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.PurposeTo develop a DL model for automated classification of MESCC on MRI.Materials and methodsPatients 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.ResultsOverall, 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.ConclusionA 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.
| S-EPMC9114468 | biostudies-literature
Project description:BackgroundFluid homeostasis in the central nervous system (CNS) is essential for normal neurological function. Cerebrospinal fluid (CSF) in the subarachnoid space and interstitial fluid circulation in the CNS parenchyma clears metabolites and neurotransmitters and removes pathogens and excess proteins. A thorough understanding of the normal physiology is required in order to understand CNS fluid disorders, including post-traumatic syringomyelia. The aim of this project was to compare fluid transport, using quantitative imaging of tracers, in the spinal cord from animals with normal and obstructed spinal subarachnoid spaces.MethodsA modified extradural constriction model was used to obstruct CSF flow in the subarachnoid space at the cervicothoracic junction (C7-T1) in Sprague-Dawley rats. Alexa-Fluor 647 Ovalbumin conjugate was injected into the cisterna magna at either 1 or 6 weeks post-surgery. Macroscopic and microscopic fluorescent imaging were performed in animals sacrificed at 10 or 20 min post-injection. Tracer fluorescence intensity was compared at cervical and thoracic spinal cord levels between control and constriction animals at each post-surgery and post-injection time point. The distribution of tracer around arterioles, venules and capillaries was also compared.ResultsMacroscopically, the fluorescence intensity of CSF tracer was significantly greater in spinal cords from animals with a constricted subarachnoid space compared to controls, except at 1 week post-surgery and 10 min post-injection. CSF tracer fluorescence intensity from microscopic images was significantly higher in the white matter of constriction animals 1 week post surgery and 10 min post-injection. At 6 weeks post-constriction surgery, fluorescence intensity in both gray and white matter was significantly increased in animals sacrificed 10 min post-injection. At 20 min post-injection this difference was significant only in the white matter and was less prominent. CSF tracer was found predominantly in the perivascular spaces of arterioles and venules, as well as the basement membrane of capillaries, highlighting the importance of perivascular pathways in the transport of fluid and solutes in the spinal cord.ConclusionsThe presence of a subarachnoid space obstruction may lead to an increase in fluid flow within the spinal cord tissue, presenting as increased flow in the perivascular spaces of arterioles and venules, and the basement membranes of capillaries. Increased fluid retention in the spinal cord in the presence of an obstructed subarachnoid space may be a critical step in the development of post-traumatic syringomyelia.
| S-EPMC6434898 | biostudies-literature
Project description:Simple Summary Metastatic epidural spinal cord compression (MESCC) is a disastrous complication of advanced malignancy, and early diagnosis is important to prevent irreversible neurological injury. MRI is the mainstay of diagnosis for MESCC, but it is expensive, and routine screening of asymptomatic patients is not feasible. Staging CT studies are performed routinely as part of the cancer diagnosis and represent an opportunity for earlier diagnosis and treatment planning. In this study, we trained deep learning models for automatic MESCC classification on staging CT studies using spine MRI and manual radiologist labels as the reference standard. On a test set, the DL models showed almost-perfect interobserver agreement for the classification of CT spine images into normal, low, and high-grade MESCC, with kappas ranging from 0.873–0.911 (p < 0.001). The DL models (lowest κ = 0.873, 95% CI 0.858–0.887) also showed superior interobserver agreement compared to two radiologists, including a specialist (κ = 0.820, 95% CI 0.803–0.837) and general radiologist (κ = 0.726, 95% CI 0.706–0.747), both p < 0.001. Abstract Background: Metastatic epidural spinal cord compression (MESCC) is a disastrous complication of advanced malignancy. Deep learning (DL) models for automatic MESCC classification on staging CT were developed to aid earlier diagnosis. Methods: This retrospective study included 444 CT staging studies from 185 patients with suspected MESCC who underwent MRI spine studies within 60 days of the CT studies. The DL model training/validation dataset consisted of 316/358 (88%) and the test set of 42/358 (12%) CT studies. Training/validation and test datasets were labeled in consensus by two subspecialized radiologists (6 and 11-years-experience) using the MRI studies as the reference standard. Test sets were labeled by the developed DL models and four radiologists (2–7 years of experience) for comparison. Results: DL models showed almost-perfect interobserver agreement for classification of CT spine images into normal, low, and high-grade MESCC, with kappas ranging from 0.873–0.911 (p < 0.001). The DL models (lowest κ = 0.873, 95% CI 0.858–0.887) also showed superior interobserver agreement compared to two of the four radiologists for three-class classification, including a specialist (κ = 0.820, 95% CI 0.803–0.837) and general radiologist (κ = 0.726, 95% CI 0.706–0.747), both p < 0.001. Conclusion: DL models for the MESCC classification on a CT showed comparable to superior interobserver agreement to radiologists and could be used to aid earlier diagnosis.
| S-EPMC9264856 | biostudies-literature
Project description:BackgroundMetastatic spinal cord compression (MSCC) treatment depends on life expectancies. Data regarding palliative decompression outcomes is scarce. We demonstrate that surgical timing has a significant impact on survival in MSCC patients treated with palliative decompression.MethodsEighty-nine consecutive MSCC patients at a tertiary referral medical center were enrolled between January 2012 and February 2016. Wide laminectomy was performed for tumors invading the vertebral body. Debulking surgery was done for tumors damaging the posterior column of the spine. Patient records were retrospectively analyzed.ResultsBetter survival was observed in patients with preoperative intact motor function (Group A, n = 37) than in those with motor deficit (Group B, n = 52, p = 0.0031). In Group B, survival was better in those who underwent surgery within 7 days of motor deficit onset than in those who underwent surgery 7 days after onset (p = 0.0444) and in postoperative ambulant patients than in nonambulant patients (p = 0.0120). In Group B, Frankel grade improved in patients who underwent surgery within 48 h than in those who underwent surgery after 48 h (p = 0.0992). Group A patients had a shorter hospital stay and higher revised Tokuhashi score than Group B patients. Overall survival was better in patients with a lower Tomita score (?5, p = 0.0012), higher revised Tokuhashi score (?9, p = 0.0009), better preoperative Frankel grade (p < 0.0001), and younger age (?55 years, p = 0.0179). There were no significant differences in age, sex, tumor type, involved vertebrae level, Tomita score, intraoperative blood loss, operation time, incidence of infection, and postoperative complications between groups.ConclusionWe can improve the survival of MSCC patients with palliative decompression before motor deficits occur. After motor deficit onset, survival can still be improved with surgery within 7 days. Overall survival was better in patients aged ?55 years.
| S-EPMC5747484 | biostudies-literature
Project description:BackgroundDegenerative cervical spinal cord compression is becoming increasingly prevalent, yet the MRI criteria that define compression are vague, and vary between studies. This contribution addresses the detection of compression by means of the Spinal Cord Toolbox (SCT) and assesses the variability of the morphometric parameters extracted with it.MethodsProspective cross-sectional study. Two types of MRI examination, 3 and 1.5 T, were performed on 66 healthy controls and 118 participants with cervical spinal cord compression. Morphometric parameters from 3T MRI obtained by Spinal Cord Toolbox (cross-sectional area, solidity, compressive ratio, torsion) were combined in multivariate logistic regression models with the outcome (binary dependent variable) being the presence of compression determined by two radiologists. Inter-trial (between 3 and 1.5 T) and inter-rater (three expert raters and SCT) variability of morphometric parameters were assessed in a subset of 35 controls and 30 participants with compression.ResultsThe logistic model combining compressive ratio, cross-sectional area, solidity, torsion and one binary indicator, whether or not the compression was set at level C6/7, demonstrated outstanding compression detection (area under curve =0.947). The single best cut-off for predicted probability calculated using a multiple regression equation was 0.451, with a sensitivity of 87.3% and a specificity of 90.2%. The inter-trial variability was better in Spinal Cord Toolbox (intraclass correlation coefficient was 0.858 for compressive ratio and 0.735 for cross-sectional area) compared to expert raters (mean coefficient for three expert raters was 0.722 for compressive ratio and 0.486 for cross-sectional area). The analysis of inter-rater variability demonstrated general agreement between SCT and three expert raters, as the correlations between SCT and raters were generally similar to those of the raters between one another.ConclusionsThis study demonstrates successful semi-automated compression detection based on four parameters. The inter-trial variability of parameters established through two MRI examinations was conclusively better for Spinal Cord Toolbox compared with that of three experts' manual ratings.
| S-EPMC8923862 | biostudies-literature