How to evaluate perfusion imaging in post-treatment glioma: a comparison of three different analysis methods.

INTRODUCTION: Dynamic susceptibility contrast (DSC) perfusion weighted (PW)-MRI can aid in differentiating treatment related abnormalities (TRA) from tumor progression (TP) in post-treatment glioma patients. Common methods, like the 'hot spot', or visual approach suffer from oversimplification and subjectivity. Using perfusion of the complete lesion potentially offers an objective and accurate alternative. This study aims to compare the diagnostic value and assess the subjectivity of these techniques. METHODS: 50 Glioma patients with enhancing lesions post-surgery and chemo-radiotherapy were retrospectively included. Outcome was determined by clinical/radiological follow-up or biopsy. Imaging analysis used the 'hot spot', volume of interest (VOI) and visual approach. Diagnostic accuracy was compared using receiving operator characteristics (ROC) curves for the VOI and 'hot spot' approach, visual assessment was analysed with contingency tables. Inter-operator agreement was determined with Cohens kappa and intra-class coefficient (ICC). RESULTS: 29 Patients suffered from TP, 21 had TRA. The visual assessment showed poor to substantial inter-operator agreement (κ = -0.72 - 0.68). Reliability of the 'hot spot' placement was excellent (ICC = 0.89), while reference placement was variable (ICC = 0.54). The area under the ROC (AUROC) of the mean- and maximum relative cerebral blood volume (rCBV) (VOI-analysis) were 0.82 and 0.72, while the rCBV-ratio ('hot spot' analysis) was 0.69. The VOI-analysis had a more balanced sensitivity and specificity compared to visual assessment. CONCLUSIONS: VOI analysis of DSC PW-MRI data holds greater diagnostic accuracy in single-moment differentiation of TP and TRA than 'hot spot' or visual analysis. This study underlines the subjectivity of visual placement and assessment.

Quantification of perineural satellitosis in pretreatment glioblastoma with structural MRI and a diffusion tensor imaging template.

Background: Survival outcomes for glioblastoma (GBM) patients remain unfavorable, and tumor recurrence is often observed. Understanding the radiological growth patterns of GBM could aid in improving outcomes. This study aimed to examine the relationship between contrast-enhancing tumor growth direction and white matter, using an image registration and deformation strategy. Methods: In GBM patients 2 pretreatment scans (diagnostic and neuronavigation) were gathered retrospectively, and coregistered to a template and diffusion tensor imaging (DTI) atlas. The GBM lesions were segmented and coregistered to the same space. Growth vectors were derived and divided into vector populations parallel (Φ = 0-20°) and perpendicular (Φ = 70-90°) to white matter. To test for statistical significance between parallel and perpendicular groups, a paired samples Student's t-test was performed. O6-methylguanine-DNA methyltransferase (MGMT) methylation status and its correlation to growth rate were also tested using a one-way ANOVA test. Results: For 78 GBM patients (mean age 61 years ±â€…13 SD, 32 men), the included GBM lesions showed a predominant preference for perineural satellitosis (P < .001), with a mean percentile growth of 30.8% (95% CI: 29.6-32.0%) parallel (0°â€…< |Φ| < 20°) to white matter. Perpendicular tumor growth with respect to white matter microstructure (70°â€…< |Φ| < 90°) showed to be 22.7% (95% CI: 21.3-24.1%) of total tumor growth direction. Conclusions: The presented strategy showed that tumor growth direction in pretreatment GBM patients correlated with white matter architecture. Future studies with patient-specific DTI data are required to verify the accuracy of this method prospectively to identify its usefulness as a clinical metric in pre and posttreatment settings.

The Predicted Outcome of Spinal Cord Stimulation in Patients With a Psychopathological Disorder and Persistent Spinal Pain Syndrome Type 2: A Systematic Review From 2009 to 2021.

OBJECTIVES: Psychologic screening is often included as a mandatory component of evaluation of the impact of psychopathology disorders on the predicted outcome of spinal cord stimulation (SCS) for patients with chronic pain due to persistent spinal pain syndrome type 2 (PSPS type 2). The conclusion of such screenings can influence the decision to offer SCS therapy to a patient. However, evidence on the impact of psychopathology on SCS outcomes is still scarce. MATERIALS AND METHODS: To address this knowledge gap, we systematically reviewed the literature from 2009 to 2021 to explore the correlation between the presence of a psychopathological disorder and the predicted outcome of SCS in patients with PSPS type 2. The literature search was conducted using various online data bases with "failed back surgery syndrome," "psychopathology," and "spinal cord stimulation" used as essential keywords. The identified studies were organized in a Rayyan AI data base, and the quality was analyzed with the Critical Appraisal Skills Program tool. RESULTS: Our search generated the identification of 468 original articles, of which two prospective and four retrospective studies met our inclusion criteria. These studies reported pain relief, a reduction of symptoms of anxiety and depression, and an improvement in rumination on the Pain Catastrophizing Scale in patients with PSPS type 2 after SCS therapy. The studies also found contradictory outcomes measured using the Oswestry Disability Index, and in terms of the impact of psychopathological disorder on the clinical outcome and revision rate of the SCS system. CONCLUSION: In this systematic review, we found no convincing evidence that the presence of a psychopathological disorder affects the predicted outcome of SCS therapy in patients with PSPS type 2.

Microstructural Changes in the Spinothalamic Tract of CPSS Patients: Preliminary Results from a Single-Center Diffusion-Weighted Magnetic Resonance Imaging Study.

INTRODUCTION: Chronic pain after spinal surgery (CPSS), formerly known as failed back surgery syndrome, encompasses a variety of highly incapacitating chronic pain syndromes emerging after spinal surgery. The intractability of CPSS makes objective parameters that could aid classification and treatment essential. In this study, we investigated the use of cerebral diffusion-weighted magnetic resonance imaging. METHODS: Cerebral 3T diffusion-weighted (DW-) MRI data from adult CPSS patients were assessed and compared with those of healthy controls matched by age and gender. Only imaging data without relevant artefacts or significant pathologies were included. Apparent diffusion coefficient (ADC) maps were calculated from the b0 and b1000 values using nonlinear regression. After skull stripping and affine registration of all imaging data, ADC values for fifteen anatomical regions were calculated and analyzed with independent samples T-tests. RESULTS: A total of 32 subjects were included (sixteen CPSS patients and sixteen controls). The mean ADC value of the spinothalamic tract was found to be significantly higher in CPSS patients compared with in healthy controls (p = 0.013). The other anatomical regions did not show statistically different ADC values between the two groups. CONCLUSION: Our results suggest that patients suffering from CPSS are subject to microstructural changes, predominantly within the cerebral spinothalamic tract. Additional research could possibly lead to imaging biomarkers derived from ADC values in CPSS patients.

Apparent Diffusion Coefficient Metrics to Differentiate between Treatment-Related Abnormalities and Tumor Progression in Post-Treatment Glioblastoma Patients: A Retrospective Study.

Distinguishing treatment-related abnormalities (TRA) from tumor progression (TP) in glioblastoma patients is a diagnostic imaging challenge due to the identical morphology of conventional MR imaging sequences. Diffusion-weighted imaging (DWI) and its derived images of the apparent diffusion coefficient (ADC) have been suggested as diagnostic tools for this problem. The aim of this study is to determine the diagnostic accuracy of different cut-off values of the ADC to differentiate between TP and TRA. In total, 76 post-treatment glioblastoma patients with new contrast-enhancing lesions were selected. Lesions were segmented using a T1-weighted, contrast-enhanced scan. The mean ADC values of the segmentations were compared between TRA and TP groups. Diagnostic accuracy was compared by use of the area under the curve (AUC) and the derived sensitivity and specificity values from cutoff points. Although ADC values in TP (mean = 1.32 × 10-3 mm2/s; SD = 0.31 × 10-3 mm2/s) were significantly different compared to TRA (mean = 1.53 × 10-3 mm2/s; SD = 0.28 × 10-3 mm2/s) (p = 0.003), considerable overlap in their distributions exists. The AUC of ADC values to distinguish TP from TRA was 0.71, with a sensitivity and specificity of 65% and 70%, respectively, at an ADC value of 1.47 × 10-3 mm2/s. These findings therefore indicate that ADC maps should not be used in discerning between TP and TRA at a certain timepoint without information on temporal evolution.

Spinal Cord Stimulation for Failed Back Surgery Syndrome: to Trial or Not to Trial?

Spinal cord stimulation (SCS) is a recommended therapy to treat failed back surgery syndrome (FBSS). A trial period is practiced to enhance patient selection. However, its fundamental evidence is limited, especially concerning long-term benefit and therapy safety. We compared the long-term (5.3 ± 4.0 years) clinical outcome and therapy safety of a trialed and nontrialed implantation strategy, including multidimensional variables and pain intensity fluctuations over time. A multicenter cohort analysis was performed in 2 comparable groups of FBSS patients. Regarding eligibility, patients had to be treated with SCS for at least 3 months. While the Trial group comprised patients who underwent an SCS implantation after a successful trial, the No-Trial group encompassed patients who underwent complete implantation within 1 session. The primary outcome measures were pain intensity scores and complications. The Trial and No-Trial groups consisted of 194 and 376 patients (N = 570), respectively. A statistically but not clinically significant difference in pain intensity (P = .003; effect = 0.506 (.172-.839)) was found in favor of the Trial group. No interaction between a time dependency effect and pain intensity was noted. Whereas trialed SCS patients were more likely to cease opioid usage (P = .003; OR = .509 (.326-.792)), patients in the No-Trial group endured fewer infections (P = .006; proportion difference = .43 (.007-.083)). Although the clinical relevance of our findings should be proven in future studies, this long-term real-world data study indicates that patient-centered assessments on whether an SCS trial should be performed have to be investigated. According to the current ambiguous evidence, SCS trials should be considered on a case-by-case basis. PERSPECTIVE: The currently available comparative evidence, together with our results, remains ambiguous on which SCS implantation strategy might be deemed superior. An SCS trial should be considered on a case-by-case basis, for which further investigation of its clinical utility in certain patient populations or character traits is warranted.

A magnetic resonance imaging based radiomics model to predict mitosis cycles in intracranial meningioma.

The aim of this study was to develop a magnetic resonance imaging (MRI) based radiomics model to predict mitosis cycles in intracranial meningioma grading prior to surgery. Preoperative contrast-enhanced T1-weighted (T1CE) cerebral MRI data of 167 meningioma patients between 2015 and 2020 were obtained, preprocessed and segmented using the 3D Slicer software and the PyRadiomics plugin. In total 145 radiomics features of the T1CE MRI images were computed. The criterion on the basis of which the feature selection was made is whether the number of mitoses per 10 high power field (HPF) is greater than or equal to zero. Our analyses show that machine learning algorithms can be used to make accurate predictions about whether the number of mitoses per 10 HPF is greater than or equal to zero. We obtained our best model using Ridge regression for feature pre-selection, followed by stepwise logistic regression for final model construction. Using independent test data, this model resulted in an AUC (Area under the Curve) of 0.8523, an accuracy of 0.7941, a sensitivity of 0.8182, a specificity of 0.7500 and a Cohen's Kappa of 0.5576. We analyzed the performance of this model as a function of the number of mitoses per 10 HPF. The model performs well for cases with zero mitoses as well as for cases with more than one mitosis per 10 HPF. The worst model performance (accuracy = 0.6250) is obtained for cases with one mitosis per 10 HPF. Our results show that MRI-based radiomics may be a promising approach to predict the mitosis cycles in intracranial meningioma prior to surgery. Specifically, our approach may offer a non-invasive means of detecting the early stages of a malignant process in meningiomas prior to the onset of clinical symptoms.

Radiomics for pseudoprogression prediction in high grade gliomas: added value of MR contrast agent.

Objective: Our aim is to define the capabilities of radiomics in predicting pseudoprogression from pre-treatment MR images in patients diagnosed with high-grade gliomas using T1 non-contrast-enhanced and contrast-enhanced images. Material & methods: In this retrospective IRB-approved study, image segmentation of high-grade gliomas was semi-automatically performed using 3D Slicer. Non-contrast-enhanced T1-weighted images and contrast-enhanced T1-weighted images were used prior to surgical therapy or radio-chemotherapy. Imaging data was split into a training sample and an independent test sample at random. We extracted 107 radiomic features by use of PyRadiomics. Feature selection and model construction were performed using Generalized Boosted Regression Models (GBM). Results: Our cohort included 124 patients (female: n = 53), diagnosed with progressive (n = 61) and pseudoprogressive disease (n = 63) of primary high-grade gliomas. Based on non-contrast-enhanced T1-weighted images of the independent test sample, the mean area under the curve (AUC), mean sensitivity, mean specificity and mean accuracy of our model were 0.651 [0.576, 0.761], 0.616 [0.417, 0.833], 0.578 [0.417, 0.750] and 0.597 [0.500, 0.708] to predict the development of pseudoprogression. In comparison, the independent test data of contrast-enhanced T1-weighted images yielded significantly higher values of AUC = 0.819 [0.760, 0.872], sensitivity = 0.817 [0.750, 0.833], specificity = 0.723 [0.583, 0.833] and accuracy = 0.770 [0.687, 0.833]. Conclusion: Our findings show that it is possible to predict pseudoprogression of high-grade gliomas with a Radiomics model using contrast-enhanced T1-weighted images with comparatively good discriminatory power. The use of a contrast agent results in a clear added value.

Assessing preoperative risk of STR in skull meningiomas using MR radiomics and machine learning.

Our aim is to predict possible gross total and subtotal resections of skull meningiomas from pre-treatment T1 post contrast MR-images using radiomics and machine learning in a representative patient cohort. We analyse the accuracy of our model predictions depending on the tumor location within the skull and the postoperative tumor volume. In this retrospective, IRB-approved study, image segmentation of the contrast enhancing parts of the tumor was semi-automatically performed using the 3D Slicer open-source software platform. Imaging data were split into training data and independent test data at random. We extracted a total of 107 radiomic features by hand-delineated regions of interest on T1 post contrast MR images. Feature preselection and model construction were performed with eight different machine learning algorithms. Each model was estimated 100 times on new training data and then tested on a previously unknown, independent test data set to avoid possible overfitting. Our cohort included 138 patients. A gross total resection of the meningioma was performed in 107 cases and a subtotal resection in the remaining 31 cases. Using the training data, the mean area under the curve (AUC), mean accuracy, mean kappa, mean sensitivity and mean specificity were 0.901, 0.875, 0.629, 0.675 and 0.933 respectively. We obtained very similar results with the independent test data: mean AUC = 0.900, mean accuracy = 0.881, mean kappa = 0.644, mean sensitivity = 0.692 and mean specificity = 0.936. Thus, our model exposes good and stable predictive performance with both training and test data. Our radiomics approach shows that with machine learning algorithms and comparatively few explanatory factors such as the location of the tumor within the skull as well as its shape, it is possible to make accurate predictions about whether a meningioma can be completely resected by surgery. Complete resections and resections with larger postoperative tumor volumes can be predicted with very high accuracy. However, cases with very small postoperative tumor volumes are comparatively difficult to predict correctly.

The current role and future directions of imaging in failed back surgery syndrome patients: an educational review.

BACKGROUND: Failed back surgery syndrome (FBSS) is an umbrella term referring to painful sensations experienced by patients after spinal surgery, mostly of neuropathic nature. Adequate treatment of FBSS is challenging, as its etiology is believed to be multifactorial and still not fully clarified. Accurate identification of the source of pain is difficult but pivotal to establish the most appropriate treatment strategy. Although the clinical utility of imaging in FBSS patients is still contentious, objective parameters are highly warranted to map different phenotypes of FBSS and tailor each subsequent therapy. MAIN BODY: Since technological developments have weakened the applicability of prior research, this educational review outlined the recent evidence (i.e., from January 2005 onwards) after a systematic literature search. The state of the art on multiple imaging modalities in FBSS patients was reviewed. Future directions related to functional MRI and the development of imaging biomarkers have also been discussed. CONCLUSION: Besides the fact that more imaging studies correlated with symptomatology in the postoperative setting are warranted, the current educational review outlined that contrast-enhanced MRI and MR neurography have been suggested as valuable imaging protocols to assess alterations in the spine of FBSS patients. The use of imaging biomarkers to study correlations between imaging features and symptomatology might hold future potential; however, more research is required before any promising hypotheses can be drawn.

Pseudoprogression prediction in high grade primary CNS tumors by use of radiomics.

Our aim is to define the capabilities of radiomics and machine learning in predicting pseudoprogression development from pre-treatment MR images in a patient cohort diagnosed with high grade gliomas. In this retrospective analysis, we analysed 131 patients with high grade gliomas. Segmentation of the contrast enhancing parts of the tumor before administration of radio-chemotherapy was semi-automatically performed using the 3D Slicer open-source software platform (version 4.10) on T1 post contrast MR images. Imaging data was split into training data, test data and an independent validation sample at random. We extracted a total of 107 radiomic features by hand-delineated regions of interest (ROI). Feature selection and model construction were performed using Generalized Boosted Regression Models (GBM). 131 patients were included, of which 64 patients had a histopathologically proven progressive disease and 67 were diagnosed with mixed or pure pseudoprogression after initial treatment. Our Radiomics approach is able to predict the occurrence of pseudoprogression with an AUC, mean sensitivity, mean specificity and mean accuracy of 91.49% [86.27%, 95.89%], 79.92% [73.08%, 87.55%], 88.61% [85.19%, 94.44%] and 84.35% [80.19%, 90.57%] in the full development group, 78.51% [75.27%, 82.46%], 66.26% [57.95%, 73.02%], 78.31% [70.48%, 84.19%] and 72.40% [68.06%, 76.85%] in the testing group and finally 72.87% [70.18%, 76.28%], 71.75% [62.29%, 75.00%], 80.00% [69.23%, 84.62%] and 76.04% [69.90%, 80.00%] in the independent validation sample, respectively. Our results indicate that radiomics is a promising tool to predict pseudo-progression, thus potentially allowing to reduce the use of biopsies and invasive histopathology.

Surgical Paddle Electrode Implantation as a Rescue Therapy to Failed Percutaneous Leads in Failed Back Surgery Syndrome Patients.

INTRODUCTION: Spinal cord stimulation (SCS) to treat failed back surgery syndrome (FBSS) can be provided with either percutaneously or surgically implanted electrodes. Percutaneous electrodes are considered the first choice in many pain practices, but surgical paddle electrodes can also be indicated if a percutaneous electrode fails to retain sufficient pain relief or if percutaneous implantation is considered unachievable. Although the current efficacy of surgical paddle electrodes has been based mainly upon pain intensity scores, the evidence on surgical paddle electrodes as a rescue to failed percutaneous electrodes remains even more scarce. OBJECTIVE: This study aimed to evaluate the safety and clinical effectiveness of rescue surgical paddle electrodes in FBSS patients, multidimensionally. MATERIALS AND METHODS: The occurrence of complications, pain intensity scores, psychosocial-related questionnaires, and medication intake were collected. Subsequently, a Quality-of-Life Index (QLI) was calculated. A clinically relevant effect was obtained if the minimal clinically important difference regarding pain intensity was reached. RESULTS: A total of 25 patients were included in the study. The pain intensity scores were significantly reduced (p < 0.001), and clinically relevant reductions occurred during short-term (0-6 months), mid-term (1-3 years), and long-term follow-up (≥4 years). The structural morphine usage and QLI were significantly decreased at short-term follow-up (p = 0.038 and p = 0.036, respectively). Six complications occurred in five patients, of which, four concerned hardware-related problems and two were of biological origin. CONCLUSION: SCS utilizing a surgical paddle electrode as a salvage treatment to failed conventional percutaneous cylindrical lead SCS can be practiced safely and effectively to treat FBSS. Because of potentially improved clinical effectiveness and cost-effectiveness resulting from fewer reoperations, a SCS treatment algorithm may benefit from expediting surgical paddle electrodes.

Accuracy of Machine Learning Algorithms for the Classification of Molecular Features of Gliomas on MRI: A Systematic Literature Review and Meta-Analysis.

Treatment planning and prognosis in glioma treatment are based on the classification into low- and high-grade oligodendroglioma or astrocytoma, which is mainly based on molecular characteristics (IDH1/2- and 1p/19q codeletion status). It would be of great value if this classification could be made reliably before surgery, without biopsy. Machine learning algorithms (MLAs) could play a role in achieving this by enabling glioma characterization on magnetic resonance imaging (MRI) data without invasive tissue sampling. The aim of this study is to provide a performance evaluation and meta-analysis of various MLAs for glioma characterization. Systematic literature search and meta-analysis were performed on the aggregated data, after which subgroup analyses for several target conditions were conducted. This study is registered with PROSPERO, CRD42020191033. We identified 724 studies; 60 and 17 studies were eligible to be included in the systematic review and meta-analysis, respectively. Meta-analysis showed excellent accuracy for all subgroups, with the classification of 1p/19q codeletion status scoring significantly poorer than other subgroups (AUC: 0.748, p = 0.132). There was considerable heterogeneity among some of the included studies. Although promising results were found with regard to the ability of MLA-tools to be used for the non-invasive classification of gliomas, large-scale, prospective trials with external validation are warranted in the future.

Experiences From the Patient Perspective on Spinal Cord Stimulation for Failed Back Surgery Syndrome: A Qualitatively Driven Mixed Method Analysis.

INTRODUCTION: When neither pharmacological therapies nor alternative interventions provide sufficient pain relief, spinal cord stimulation (SCS) can be used to treat Failed Back Surgery Syndrome (FBSS). Although it seems reasonable that quality of life (QoL)- and psychosocial-related factors contribute to the outcome of SCS since pain is a multidimensional experience, few qualitative studies have explored the expectations of SCS and experiences on SCS to treat FBSS from the patient perspective. OBJECTIVES: The aim of this study was to qualitatively and quantitatively map the FBSS patients' experiences with SCS and the effects of SCS on low back pain caused by FBSS. MATERIALS AND METHODS: A qualitative study with in-depth semi-structured interviews, assisted by the Brief Pain Inventory (BPI)-questionnaire. RESULTS: Seven themes regarding patients' experiences, subdivided into 15 categories, were identified, including an understudied theme within this field of research, Spiritual Well-Being. "Acceptance" and "coping" emerged as pre-eminent motifs throughout these themes. Moreover, the realization of patients' expectations were variable throughout the presented themes. According to the BPI Questionnaire, four out of 13 patients (31%) had significant pain relief (≥50%). Seven out of 13 (54%) reported a ≥50% increase regarding enjoyment of life. CONCLUSION: Multiple QoL- and psychosocial-related themes are related to SCS-outcomes. In order to improve SCS-outcomes for both short- and long-term, these themes should be implemented as a multidimensional approach, both prior to implantation as during follow-up.

Views of patients suffering from Failed Back Surgery Syndrome on their health and their ability to adapt to daily life and self-management: A qualitative exploration.

BACKGROUND: The clinical outcomes of Spinal Cord Stimulation (SCS) therapy in patients with a Failed Back Surgery Syndrome (FBSS) is mostly done by standardized pain and quality of life measurements instruments and hardly account for personal feelings and needs as a basis for a patient-centred approach and shared decision making. OBJECTIVES: The objective of this study is to explore perspectives on personal health and quality of life (QoL) in FBSS patients concerning their physical-, psychological and spiritual well-being prior to receiving an SCS system. METHODS: We performed face-to-face, semi-structured, in-depth interviews to obtain descriptive and detailed data on personal health, guided by the Web diagram of Positive Health (Huber et al.) and a topic list. The following main topics were assessed qualitatively: 1) Bodily functioning, 2) Mental function and perception 3) Spiritual dimension, 4) Quality of life, 5) Social and societal participation and 6) Daily functioning. RESULTS: Seventeen FBSS patients (eight male, nine female) were included from April-November 2019 at the department of pain medicine in the Albert Schweitzer Hospital in the Netherlands. Median age 49 years; range 28 to 67 years, and patients underwent between one and five lumbar surgical operations. The duration of their chronic pain was between four and 22 years. After analyzing the interviews, three themes emerged: 1) dealing with chronic pain, 2) the current situation regarding aspects of positive health, and 3) future perspectives on health and quality of life. These themes arose from eleven categories and a hundred ninety codes. CONCLUSION: This qualitative study explored FBSS patients 'views on their health and the ability to adapt to daily life having complex chronic pain, and showed that patients experienced shortcomings in daily life within the six dimensions of the Web diagram of Positive Health before the SCS implant.

Systematic Review and Neural Network Analysis to Define Predictive Variables in Implantable Motor Cortex Stimulation to Treat Chronic Intractable Pain.

Implantable motor cortex stimulation (iMCS) has been performed for >25 years to treat various intractable pain syndromes. Its effectiveness is highly variable and, although various studies revealed predictive variables, none of these were found repeatedly. This study uses neural network analysis (NNA) to identify predictive factors of iMCS treatment for intractable pain. A systematic review provided a database of patient data on an individual level of patients who underwent iMCS to treat refractory pain between 1991 and 2017. Responders were defined as patients with a pain relief of >40% as measured by a numerical rating scale (NRS) score. NNA was carried out to predict the outcome of iMCS and to identify predictive factors that impacted the outcome of iMCS. The outcome prediction value of the NNA was expressed as the mean accuracy, sensitivity, and specificity. The NNA furthermore provided the mean weight of predictive variables, which shows the impact of the predictive variable on the prediction. The mean weight was converted into the mean relative influence (M), a value that varies between 0 and 100%. A total of 358 patients were included (202 males [56.4%]; mean age, 54.2 ±13.3 years), 201 of whom were responders to iMCS. NNA had a mean accuracy of 66.3% and a sensitivity and specificity of 69.8% and 69.4%, respectively. NNA further identified 6 predictive variables that had a relatively high M: 1) the sex of the patient (M = 19.7%); 2) the origin of the lesion (M = 15.1%); 3) the preoperative numerical rating scale score (M = 9.2%); 4) preoperative use of repetitive transcranial magnetic stimulation (M = 7.3%); 5) preoperative intake of opioids (M = 7.1%); and 6) the follow-up period (M = 13.1%). The results from the present study show that these 6 predictive variables influence the outcome of iMCS and that, based on these variables, a fair prediction model can be built to predict outcome after iMCS surgery. PERSPECTIVE: The presented NNA analyzed the functioning of computational models and modeled nonlinear statistical data. Based on this NNA, 6 predictive variables were identified that are suggested to be of importance in the improvement of future iMCS to treat chronic pain.

Patients' Expectations on Spinal Cord Stimulation for Failed Back Surgery Syndrome: A Qualitative Exploration.

BACKGROUND: Spinal cord stimulation (SCS) is an effective therapy to reduce pain in patients who suffer from failed back surgery syndrome (FBSS). In order to inform patients optimally prior to this therapy, knowing their expectations is crucial. METHODS: Thirteen patients suffering from FBSS and scheduled for SCS were interviewed using a semistructured protocol. Patients were interviewed either at home or at their treating hospital. Data from these interviews were analyzed using directed content analysis. In addition to the qualitative interviews, an adjusted Brief Pain Inventory questionnaire was used to quantify expectations. RESULTS: The expectations of patients with regard to SCS could be subdivided into 13 categories, which could be grouped into 6 general themes: (1) physical well-being, (2) social well-being, (3) material well-being, (4) emotional well-being, (5) development and activity, and (6) constraints of the procedure of SCS. These findings confirm patients' expectations about the improvement of their quality of life by SCS for FBSS. This indicates that assessing pain relief is not enough to adequately evaluate the effects of SCS. The small diversity within the studied population and the lack of patient-to-patient education are 2 possible limitations of this study. CONCLUSIONS: To improve education for patients prior to SCS surgery and to evaluate the effects of SCS, a multidimensional approach needs to be implemented. Possible disadvantages of SCS need to be discussed prior to the treatment.