30 s sit-to-stand power is positively associated with chest muscle thickness in COVID-19 survivors.

INTRODUCTION: After hospitalization, early detection of musculoskeletal sequelae might help healthcare professionals to improve and individualize treatment, accelerating recovery after COVID-19. The objective was to determine the association between the 30s sit-to-stand muscle power (30s-STS) and cross-sectional area of the chest muscles (pectoralis) in COVID-19 survivors. METHOD: This cross-sectional study collected routine data from COVID-19 survivors one month after hospitalization: 1) a chest computed tomography (CT) scan and 2) a functional capacity test (30s-STS). The pectoralis muscle area (PMA) was measured from axial CT images. For each gender, patients were categorized into tertiles based on PMA. The 30s-STS was performed to determine the leg extension power. The allometric and relative STS power were calculated as absolute 30s-STS power normalized to height squared and body mass. The two-way ANOVA was used to compare the gender-stratified tertiles of 30s-STS power variants. RESULTS: Fifty-eight COVID-19 survivors were included (mean age 61.2 ± 12.9 years, 30/28 (51.7%/48.3%) men/women). The two-way ANOVA showed significant differences between the PMA tertiles in absolute STS power (p = .002) and allometric STS power (p = .001). There were no significant gender x PMA tertile interactions (all variables p > .05). The high tertile of PMA showed a higher allometric STS power compared to the low and middle tertile, p = .002 and p = .004, respectively. Absolute STS power and allometric STS power had a moderate correlation with the PMA, r = 0.519 (p < .001) and r = 0.458 (p < .001) respectively. CONCLUSION: The 30s-STS power is associated with pectoralis muscle thickness in both male and female COVID-19 survivors. Thus, this test may indicate global muscle-wasting and may be used as a screening tool for lower extremity functional capacity in the early stages of rehabilitation planning in COVID-19 survivors.

Usefulness of ultrasound in dermatofibrosarcoma protuberans and correlation with histopathological findings: A series of 30 cases.

BACKGROUND: Small series of ultrasound findings in dermatofibrosarcoma protuberans (DFSP) have been published, but the usefulness of this technique as a preoperative planning tool for tumor resection has not been studied. MATERIALS AND METHODS: We retrospectively reviewed patients with DFSP at our hospital that underwent ultrasound examination. Depth of invasion was evaluated by ultrasound and histopathology. Accuracy of ultrasound for assessing depth of tumor invasion was estimated. RESULTS: Thirty histopathologically confirmed DFSPs were studied. Classic finger-like projections were observed in 73.3% of cases. A posterior hyperechoic area extending deep into the subcutaneous tissue correlated with the honeycomb DFSP pattern and was observed in 53.3% of patients. Concordance between ultrasound and histopathologic depth measurements was excellent. Lateral tumor extension and Doppler activity were not evaluated in our series. CONCLUSION: Ultrasound showed excellent prediction of depth of invasion. Further studies are required to define the usefulness of ultrasound for determining lateral tumor extension.

Administration of iodinated contrast: What is the risk in cancer patients?

OBJECTIVE: Despite the association between intravenous contrast and kidney injury, few studies exist in oncology. Our objective was to estimate kidney outcomes following iodinated contrast-enhanced computed tomography (CECT) in cancer patients, and to evaluate whether self-assessment questionnaires can identify kidney injury risk factors. METHODS: This prospective observational study included 289 patients who underwent a CECT scan between March and May 2017 in a hospital setting. All patients completed the modified European Society of Urogenital Radiology (ESUR) questionnaire and had an estimated glomerular filtration rate (eGFR) >30 ml/min/1.73 m2 on the day of the examination. Outcomes were followed for 4 months. Univariate and logistic regression analyses were carried out. RESULTS: In the logistic regression analysis, the only variables statistically associated with deterioration in the eGFR were age, (odds ratio (OR) = 1.091, p = 0.003), female sex, (OR 0.22, p = 0.020) and arterial hypertension (AH), (OR = 3.57, p = 0.019). Regarding exitus, only the group with a worse eGFR was close to predictive statistical significance (OR = 2.48, p = 0.09). CONCLUSIONS: The administration of iodinated contrast in cancer patients was not associated with an increase in kidney outcomes. Risk factors in these patients were age, sex and AH.

Metastatic Versus Osteoporotic Vertebral Fractures on MRI: A Blinded, Multicenter, and Multispecialty Observer Agreement Evaluation.

BACKGROUND: MRI is assumed to be valid for distinguishing metastatic vertebral fractures (MVFs) from osteoporotic vertebral fractures (OVFs). This study assessed (1) concordance between the image-based diagnosis of MVF versus OVF and the reference (biopsy or follow-up of >6 months), (2) interobserver and intraobserver agreement on key imaging findings and the diagnosis of MVF versus OVF, and (3) whether disclosing a patient's history of cancer leads to variations in diagnosis, concordance, or agreement. PATIENTS AND METHODS: This retrospective cohort study included clinical data and imaging from 203 patients with confirmed MVF or OVF provided to 25 clinicians (neurosurgeons, radiologists, orthopedic surgeons, and radiation oncologists). From January 2018 through October 2018, the clinicians interpreted images in conditions as close as possible to routine practice. Each specialist assessed data twice, with a minimum 6-week interval, blinded to assessments made by other clinicians and to their own previous assessments. The kappa statistic was used to assess interobserver and intraobserver agreement on key imaging findings, diagnosis (MVF vs OVF), and concordance with the reference. Subgroup analyses were based on clinicians' specialty, years of experience, and complexity of the hospital where they worked. RESULTS: For diagnosis of MVF versus OVF, interobserver agreement was fair, whereas intraobserver agreement was substantial. Only the latter improved to almost perfect when a patient's history of cancer was disclosed. Interobserver agreement for key imaging findings was fair or moderate, whereas intraobserver agreement on key imaging findings was moderate or substantial. Concordance between the diagnosis of MVF versus OVF and the reference was moderate. Results were similar regardless of clinicians' specialty, experience, and hospital category. CONCLUSIONS: When MRI is used to distinguish MVF versus OVF, interobserver agreement and concordance with the reference were moderate. These results cast doubt on the reliability of basing such a diagnosis on MRI in routine practice.

Morphological MRI-based features provide pretreatment survival prediction in glioblastoma.

OBJECTIVES: We wished to determine whether tumor morphology descriptors obtained from pretreatment magnetic resonance images and clinical variables could predict survival for glioblastoma patients. METHODS: A cohort of 404 glioblastoma patients (311 discoveries and 93 validations) was used in the study. Pretreatment volumetric postcontrast T1-weighted magnetic resonance images were segmented to obtain the relevant morphological measures. Kaplan-Meier, Cox proportional hazards, correlations, and Harrell's concordance indexes (c-indexes) were used for the statistical analysis. RESULTS: A linear prognostic model based on the outstanding variables (age, contrast-enhanced (CE) rim width, and surface regularity) identified a group of patients with significantly better survival (p < 0.001, HR = 2.57) with high accuracy (discovery c-index = 0.74; validation c-index = 0.77). A similar model applied to totally resected patients was also able to predict survival (p < 0.001, HR = 3.43) with high predictive value (discovery c-index = 0.81; validation c-index = 0.92). Biopsied patients with better survival were well identified (p < 0.001, HR = 7.25) by a model including age and CE volume (c-index = 0.87). CONCLUSIONS: Simple linear models based on small sets of meaningful MRI-based pretreatment morphological features and age predicted survival of glioblastoma patients to a high degree of accuracy. The partition of the population using the extent of resection improved the prognostic value of those measures. KEY POINTS: • A combination of two MRI-based morphological features (CE rim width and surface regularity) and patients' age outperformed previous prognosis scores for glioblastoma. • Prognosis models for homogeneous surgical procedure groups led to even more accurate survival prediction based on Kaplan-Meier analysis and concordance indexes.

Correction to: Morphological MRI-based features provide pretreatment survival prediction in glioblastoma.

The original version of this article, published on 15 October 2018, unfortunately contained a mistake. The following correction has therefore been made in the original: The name of Mariano Amo-Salas and the affiliation of Ismael Herruzo were presented incorrectly.

Tumor Surface Regularity at MR Imaging Predicts Survival and Response to Surgery in Patients with Glioblastoma.

Purpose To evaluate the prognostic and predictive value of surface-derived imaging biomarkers obtained from contrast material-enhanced volumetric T1-weighted pretreatment magnetic resonance (MR) imaging sequences in patients with glioblastoma multiforme. Materials and Methods A discovery cohort from five local institutions (165 patients; mean age, 62 years ± 12 [standard deviation]; 43% women and 57% men) and an independent validation cohort (51 patients; mean age, 60 years ± 12; 39% women and 61% men) from The Cancer Imaging Archive with volumetric T1-weighted pretreatment contrast-enhanced MR imaging sequences were included in the study. Clinical variables such as age, treatment, and survival were collected. After tumor segmentation and image processing, tumor surface regularity, measuring how much the tumor surface deviates from a sphere of the same volume, was obtained. Kaplan-Meier, Cox proportional hazards, correlations, and concordance indexes were used to compare variables and patient subgroups. Results Surface regularity was a powerful predictor of survival in the discovery (P = .005, hazard ratio [HR] = 1.61) and validation groups (P = .05, HR = 1.84). Multivariate analysis selected age and surface regularity as significant variables in a combined prognostic model (P < .001, HR = 3.05). The model achieved concordance indexes of 0.76 and 0.74 for the discovery and validation cohorts, respectively. Tumor surface regularity was a predictor of survival for patients who underwent complete resection (P = .01, HR = 1.90). Tumors with irregular surfaces did not benefit from total over subtotal resections (P = .57, HR = 1.17), but those with regular surfaces did (P = .004, HR = 2.07). Conclusion The surface regularity obtained from high-resolution contrast-enhanced pretreatment volumetric T1-weighted MR images is a predictor of survival in patients with glioblastoma. It may help in classifying patients for surgery.

Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study.

OBJECTIVE: To examine the capability of MRI texture analysis to differentiate the primary site of origin of brain metastases following a radiomics approach. METHODS: Sixty-seven untreated brain metastases (BM) were found in 3D T1-weighted MRI of 38 patients with cancer: 27 from lung cancer, 23 from melanoma and 17 from breast cancer. These lesions were segmented in 2D and 3D to compare the discriminative power of 2D and 3D texture features. The images were quantized using different number of gray-levels to test the influence of quantization. Forty-three rotation-invariant texture features were examined. Feature selection and random forest classification were implemented within a nested cross-validation structure. Classification was evaluated with the area under receiver operating characteristic curve (AUC) considering two strategies: multiclass and one-versus-one. RESULTS: In the multiclass approach, 3D texture features were more discriminative than 2D features. The best results were achieved for images quantized with 32 gray-levels (AUC = 0.873 ± 0.064) using the top four features provided by the feature selection method based on the p-value. In the one-versus-one approach, high accuracy was obtained when differentiating lung cancer BM from breast cancer BM (four features, AUC = 0.963 ± 0.054) and melanoma BM (eight features, AUC = 0.936 ± 0.070) using the optimal dataset (3D features, 32 gray-levels). Classification of breast cancer and melanoma BM was unsatisfactory (AUC = 0.607 ± 0.180). CONCLUSION: Volumetric MRI texture features can be useful to differentiate brain metastases from different primary cancers after quantizing the images with the proper number of gray-levels. KEY POINTS: • Texture analysis is a promising source of biomarkers for classifying brain neoplasms. • MRI texture features of brain metastases could help identifying the primary cancer. • Volumetric texture features are more discriminative than traditional 2D texture features.

2D and 3D texture analysis to differentiate brain metastases on MR images: proceed with caution.

OBJECTIVE: To find structural differences between brain metastases of lung and breast cancer, computing their heterogeneity parameters by means of both 2D and 3D texture analysis (TA). MATERIALS AND METHODS: Patients with 58 brain metastases from breast (26) and lung cancer (32) were examined by MR imaging. Brain lesions were manually delineated by 2D ROIs on the slices of contrast-enhanced T1-weighted (CET1) images, and local binary patterns (LBP) maps were created from each region. Histogram-based (minimum, maximum, mean, standard deviation, and variance), and co-occurrence matrix-based (contrast, correlation, energy, entropy, and homogeneity) 2D, weighted average of the 2D slices, and true 3D TA were obtained on the CET1 images and LBP maps. RESULTS: For LBP maps and 2D TA contrast, correlation, energy, and homogeneity were identified as statistically different heterogeneity parameters (SDHPs) between lung and breast metastasis. The weighted 3D TA identified entropy as an additional SDHP. Only two texture indexes (TI) were significantly different with true 3D TA: entropy and energy. All these TIs discriminated between the two tumor types significantly by ROC analysis. For the CET1 images there was no SDHP at all by 3D TA. CONCLUSION: Our results indicate that the used textural analysis methods may help with discriminating between brain metastases of different primary tumors.

A critical appraisal of the quality of low back pain practice guidelines using the AGREE II tool and comparison with previous evaluations: a EuroAIM initiative.

PURPOSE: To assess the methodologic quality of guidelines for the management of low back pain (LBP) and compare their recommendations. METHODS: No ethics committee approval was needed for this systematic review. In March 2017, a systematic search was performed using MEDLINE, EMBASE, National Guideline Clearinghouse, and National Institute for Health and Clinical Excellence to find practice guidelines of assessment and management of LBP. The evaluation of guidelines quality was performed independently by four authors using the AGREE II tool, and the results were compared with previous appraisals performed in 2004 and 2009. RESULTS: Of 114 retrieved guidelines, eight were appraised. All except one reached the level of "acceptable" in overall result, with two of them reaching the highest scores. Only two guidelines reached a level of "acceptable" in every domain; the others had at least one domain with low scores. The guidelines had the higher scores (range = 63-94%) on "Scope and purpose" and "Clarity of presentation" (47-89%). "Stakeholder Involvement" has the highest variability between the guidelines results (40-96%). "Rigor of Development" reached an intermediate mean result (34-90%), "Applicability" (42-70%), and "Editorial Independence" (38-85%). Only three guidelines had a radiologist among authors and reached higher scores compared to guidelines without a radiologist among the authors. Compared to previous assessments, low-level guidelines were 53% in 2004, 36% in 2009, and 13% in 2017. CONCLUSIONS: Considering all guidelines, only one had a "low" overall score, while half of them were rated as of "high" quality. Future guidelines might take this into account to improve clinical applicability.

Opportunistic screening for osteoporosis by routine CT in Southern Europe.

Feasibility evaluation of early detection of osteoporosis in oncologic patients by bone mineral density (BMD) on abdominal computed tomography (CT) scans performed for other clinical indications, by using dual-energy X-ray absorptiometry (DXA) as reference. Abdominal CT images can identify patients with osteoporosis BMD without additional radiation exposure or cost. INTRODUCTION: The purpose of the study is to evaluate the feasibility of early detection of osteoporosis by bone mineral density (BMD) on abdominal computed tomography (CT) scans performed in oncologic patients, comparing calibrated and uncalibrated measurements by using dual-energy X-ray absorptiometry (DXA) as reference. We also performed an external validation of a threshold of 160 Hounsfield units (HU), proposed as highly sensitive. METHODS: Cohort comprised CT-DXA pairs within a 6-month period performed for any indication on 326 consecutive adults, aged 62.4 ± 12.38 years (mean ± standard deviation). CT attenuation of trabecular bone in HU was measured at the axial cross sections of L1, L2, L3, and L4 vertebrae. Vertebral compression fractures were assessed by sagittal reconstruction view. Diagnostic performance measures and the area under the receiver operator characteristic curve (AUC) for diagnosing osteoporosis were calculated. RESULTS: BMD values were statistical significantly lower at any vertebral level from L1 to L4 for patients with osteoporosis defined by DXA (p < 0.001). Calibrated and uncalibrated BMD values were significantly correlated (R 2 = 0.833, p < 0.01). An uncalibrated L1 CT attenuation threshold of 160 HU was more than 90 % sensitive, and a threshold of 73 HU was more than 90 % specific for distinguishing osteoporosis BMD. Fifty-nine percent of patients with vertebral compression fracture had non-osteoporotic DXA T-scores. CONCLUSIONS: Abdominal CT images obtained for other reasons can identify patients with osteoporosis BMD without additional radiation exposure or cost. Uncalibrated values at L1 can detect more osteoporosis patients with spinal compression fractures than DXA in oncologic patients.

Glioblastoma: does the pre-treatment geometry matter? A postcontrast T1 MRI-based study.

BACKGROUND: The potential of a tumour's volumetric measures obtained from pretreatment MRI sequences of glioblastoma (GBM) patients as predictors of clinical outcome has been controversial. Mathematical models of GBM growth have suggested a relation between a tumour's geometry and its aggressiveness. METHODS: A multicenter retrospective clinical study was designed to study volumetric and geometrical measures on pretreatment postcontrast T1 MRIs of 117 GBM patients. Clinical variables were collected, tumours segmented, and measures computed including: contrast enhancing (CE), necrotic, and total volumes; maximal tumour diameter; equivalent spherical CE width and several geometric measures of the CE "rim". The significance of the measures was studied using proportional hazards analysis and Kaplan-Meier curves. RESULTS: Kaplan-Meier and univariate Cox survival analysis showed that total volume [p = 0.034, Hazard ratio (HR) = 1.574], CE volume (p = 0.017, HR = 1.659), spherical rim width (p = 0.007, HR = 1.749), and geometric heterogeneity (p = 0.015, HR = 1.646) were significant parameters in terms of overall survival (OS). Multivariable Cox analysis for OS provided the later two parameters as age-adjusted predictors of OS (p = 0.043, HR = 1.536 and p = 0.032, HR = 1.570, respectively). CONCLUSION: Patients with tumours having small geometric heterogeneity and/or spherical rim widths had significantly better prognosis. These novel imaging biomarkers have a strong individual and combined prognostic value for GBM patients. KEY POINTS: • Three-dimensional segmentation on magnetic resonance images allows the study of geometric measures. • Patients with small width of contrast enhancing areas have better prognosis. • The irregularity of contrast enhancing areas predicts survival in glioblastoma patients.

Brain metastases detection on MR by means of three-dimensional tumor-appearance template matching.

PURPOSE: To develop and evaluate a method for an automatic detection of brain metastases in MR images. MATERIALS AND METHODS: Nineteen patients were scanned using a 1.5 Tesla MR scanner. Two radiologists and a radiation oncologist marked the location of the brain metastases. The training group consisted of eight patients harboring 20 metastases. First, three-dimensional (3D) tumor-appearance templates were cross-correlated with MR brain images to evaluate their similarity, and a correlation threshold was established for metastasis candidates. Afterward, a method to reduce false positive rate (FPR) was applied: each detected object was segmented and its degree of anisotropy (DA) was obtained, removing the elongated structures with a DA above the optimal value from the receiver operating characteristic curve. Finally, the method was statistically validated in two groups: 11 patients with 42 brain metastases and 11 patients without metastases. RESULTS: The method led to a sensitivity of 80% and an FPR per slice of 0.023 and 2.75 per patient in the training group. In the first validation group, a sensitivity of 88.10% and an FPR per slice of 0.05 corresponding to 6.91 false positives per patient were obtained. DA implementation decreased 3.5 times FPR compared with templates alone. It improved the radiologist's performance in metastases less than 10 mm from 89-93% to 100%. In the second validation group the FPR was 0.04 per slice and 5.18 per patient. CONCLUSION: This method demonstrates that 3D template matching applying DA technique has high sensitivity and low FPR for detecting brain metastases in MR images. J. Magn. Reson. Imaging 2016;44:642-652.

Agreement in Metastatic Spinal Cord Compression.

BACKGROUND: Metastatic epidural spinal cord compression (ESCC) is a devastating medical emergency. The purpose of this study was to determine the reliability of the 6-point ESCC scoring system and the identification of the spinal level presenting ESCC. METHODS: Clinical data and imaging from 90 patients with biopsy-proven spinal metastases were provided to 83 specialists from 44 hospitals. The spinal levels presenting metastases and the ESCC scores for each case were calculated twice by each clinician, with a minimum of 6 weeks' interval. Clinicians were blinded to assessments made by other specialists and their own previous assessment. Fleiss kappa (κ) statistic was used to assess intraobserver and interobserver agreement. Subgroup analyses were performed according to clinicians' specialty (medical oncology, neurosurgery, radiology, orthopedic surgery, and radiation oncology), years of experience, and type of hospital. RESULTS: Intraobserver and interobserver agreement on the location of ESCC was substantial (κ>0.61). Intraobserver agreement on the ESCC score was "excellent" (κ=0.82), whereas interobserver agreement was substantial (κ=0.64). Overall agreement with the tumor board classification was substantial (κ=0.71). Results were similar across specialties, years of experience and hospital category. CONCLUSIONS: The ESCC score can help improve communication among clinicians involved in oncology care.

Support vector machine classification of brain metastasis and radiation necrosis based on texture analysis in MRI.

PURPOSE: To develop a classification model using texture features and support vector machine in contrast-enhanced T1-weighted images to differentiate between brain metastasis and radiation necrosis. METHODS: Texture features were extracted from 115 lesions: 32 of them previously diagnosed as radiation necrosis, 23 as radiation-treated metastasis and 60 untreated metastases; including a total of 179 features derived from six texture analysis methods. A feature selection technique based on support vector machine was used to obtain a subset of features that provide optimal performance. RESULTS: The highest classification accuracy evaluated over test sets was achieved with a subset of ten features when the untreated metastases were not considered; and with a subset of seven features when the classifier was trained with untreated metastases and tested on treated ones. Receiver operating characteristic curves provided area-under-the-curve (mean ± standard deviation) of 0.94 ± 0.07 in the first case, and 0.93 ± 0.02 in the second. CONCLUSION: High classification accuracy (AUC > 0.9) was obtained using texture features and a support vector machine classifier in an approach based on conventional MRI to differentiate between brain metastasis and radiation necrosis.

Disc degeneration and chronic low back pain: an association which becomes nonsignificant when endplate changes and disc contour are taken into account.

INTRODUCTION: The objective of this study was to assess the association between severe disc degeneration (DD) and low back pain (LBP). METHODS: A case-control study was conducted with 304 subjects, aged 35-50, recruited in routine clinical practice across six hospitals; 240 cases (chronic LBP patients with a median pain duration of 46 months) and 64 controls (asymptomatic subjects without any lifetime history of significant LBP). The following variables were assessed once, using previously validated methods: gender, age, body mass index (BMI), lifetime smoking exposure, degree of physical activity, severity of LBP, disability, and findings on magnetic resonance (MRI) (disc degeneration, Modic changes (MC), disc protrusion/hernia, annular tears, spinal stenosis, and spondylolisthesis). Radiologists who interpreted MRI were blinded to the subjects' characteristics. A multivariate logistic regression model assessed the association between severe DD and chronic LBP, adjusting for gender, age, BMI, physical activity, MC, disc protrusion/hernia, and spinal stenosis. RESULTS: Severe DD at ≥1 level was found in 46.9 % of the controls and 65.8 % of the cases. Crude odds ratio (95 % CI), for suffering chronic LBP when having severe DD, was 2.06 (1.05; 4.06). After adjusting for "MC" and "disc protrusion/hernia," it was 1.81 (0.81; 4.05). CONCLUSIONS: The association between severe DD and LBP ceases to be significant when adjusted for MC and disc protrusion/hernia. These results do not support that DD as a major cause of chronic LBP.

Volumetric analysis: Rethinking brain metastases response assessment.

Background: The Response Assessment in Neuro-Oncology for Brain Metastases (RANO-BM) criteria are the gold standard for assessing brain metastases (BMs) treatment response. However, they are limited by their reliance on 1D, despite the routine use of high-resolution T1-weighted MRI scans for BMs, which allows for 3D measurements. Our study aimed to investigate whether volumetric measurements could improve the response assessment in patients with BMs. Methods: We retrospectively evaluated a dataset comprising 783 BMs and analyzed the response of 185 of them from 132 patients who underwent stereotactic radiotherapy between 2007 and 2021 at 5 hospitals. We used T1-weighted MRIs to compute the volume of the lesions. For the volumetric criteria, progressive disease was defined as at least a 30% increase in volume, and partial response was characterized by a 20% volume reduction. Results: Our study showed that the proposed volumetric criteria outperformed the RANO-BM criteria in several aspects: (1) Evaluating every lesion, while RANO-BM failed to evaluate 9.2% of them. (2) Classifying response effectively in 140 lesions, compared to only 72 lesions classified by RANO-BM. (3) Identifying BM recurrences a median of 3.3 months earlier than RANO-BM criteria. Conclusions: Our study demonstrates the superiority of volumetric criteria in improving the response assessment of BMs compared to the RANO-BM criteria. Our proposed criteria allow for evaluation of every lesion, regardless of its size or shape, better classification, and enable earlier identification of progressive disease. Volumetric criteria provide a standardized, reliable, and objective tool for assessing treatment response.

The Management of Metastatic Spinal Cord Compression in Routine Clinical Practice.

(1) Background: Whether clinical management of spinal metastatic disease (SMD) matches evidence-based recommendations is largely unknown. (2) Patients and Methods: A questionnaire was distributed through Spanish Medical Societies, exploring routine practice, interpretation of the SINS and ESCC scores and agreement with items in the Tokuhashi and SINS scales, and NICE guideline recommendations. Questionnaires were completed voluntarily and anonymously, without compensation. (3) Results: Eighty specialists participated in the study. A protocol for patients with SMD existed in 33.7% of the hospitals, a specific multidisciplinary board in 33.7%, 40% of radiological reports included the ESCC score, and a prognostic scoring method was used in 73.7%. While 77.5% of the participants were familiar with SINS, only 60% used it. The different SINS and ESCC scores were interpreted correctly by 57.5-70.0% and 30.0-37.5% of the participants, respectively. Over 70% agreed with the items included in the SINS and Tokuhashi scores and with the recommendations from the NICE guideline. Differences were found across private/public sectors, hospital complexity, number of years of experience, number of patients with SMD seen annually and especially across specialties. (4) Conclusions: Most specialists know and agree with features defining the gold standard treatment for patients with SCC, but many do not apply them.