Motor Pathways Reorganization following Surgical Decompression for Degenerative Cervical Myelopathy: A Combined Navigated Transcranial Magnetic Stimulation and Clinical Outcome Study.

(1) Background: Degenerative cervical myelopathy is one of the main causes of disability in the elderly. The treatment of choice in patients with clear symptomatology and radiological correlation is surgical decompression. The application of navigated transcranial magnetic stimulation (nTMS) techniques has the potential to provide additional insights into the cortical and corticospinal behavior of the myelopathic cord and to better characterize the possible extent of clinical recovery. The objective of our study was to use nTMS to evaluate the effect of surgical decompression on neurophysiological properties at the cortical and corticospinal level and to better characterize the extent of possible clinical recovery. (2) Methods: We conducted a longitudinal study in which we assessed and compared nTMS neurophysiological indexes and clinical parameters (modified Japanese Orthopedic Association score and nine-hole pegboard test) before surgery, at 6 months, and at 12 months' follow-up in a population of 15 patients. (3) Results: We found a significant reduction in resting motor threshold (RMT; average 7%), cortical silent period (CSP; average 15%), and motor area (average 25%) at both 6 months and 12 months. A statistically significant linear correlation emerged between recruitment curve (RC) values obtained at follow-up appointments and at baseline (r = 0.95 at 6 months, r = 0.98 at 12 months). A concomitant improvement in the mJOA score and in the nine-hole pegboard task was observed after surgery. (4) Conclusions: Our results suggest that surgical decompression of the myelopathic spinal cord improves the neurophysiological balance at the cortical and corticospinal level, resulting in clinically significant recovery. Such findings contribute to the existing evidence characterizing the brain and the spinal cord as a dynamic system capable of functional and reversible plasticity and provide useful clinical insights to be used for patient counseling.

The Roof of the 4th Ventricle Seen From Inside: Endoscopic Anatomic Illustration-A Case Series.

BACKGROUND: The anatomy of the roof of the fourth ventricle has been illustrated in many laboratory investigations, but in vivo reports of the roof anatomy and its variants are still lacking. OBJECTIVE: To describe the topographical anatomy of the roof of the fourth ventricle explored through a transaqueductal approach that overcomes cerebrospinal fluid depletion, displaying in vivo anatomic images possibly quite close to normal physiological conditions. METHODS: We critically reviewed the intraoperative video recordings of our 838 neuroendoscopic procedures, selecting 27 cases of transaqueductal navigation that provided good quality image details of the anatomy of the roof of the fourth ventricle. Twenty-six patients affected by different forms of hydrocephalus were therefore categorized into three groups: Group A: blockage of the aqueduct-aqueductoplasty, Group B: communicating hydrocephalus, and Group C: tetraventricular obstructive hydrocephalus. RESULTS: Group A has shown what the roof of a normal fourth ventricle really looks like albeit the structures seemed overcrowded because of the narrow space. Images from groups B and C paradoxically allowed a more distinct identification of the roof structures flattened by ventricular dilation, making them more comparable with the topography traced on the laboratory microsurgical studies. CONCLUSION: Endoscopic in vivo videos and images provided a novel anatomic view and an in vivo redefinition of the real topography of the roof of the fourth ventricle. The relevant role of cerebrospinal fluid was defined and outlined, as well as the effects of hydrocephalic dilation on some structures on the roof of the fourth ventricle.

Hyperosmolar therapies for neurological deterioration in mild and moderate traumatic brain injury: A scoping review.

OBJECTIVE: To explore the available evidence on hyperosmolar therapies(HT) in mild and moderate traumatic brain injury(TBI) and to evaluate the effects on outcomes.A scoping review was conducted according to the Joanna Briggs Institute methodology. Inclusion criteria: (a)randomized controlled trials(RCTs), prospective and retrospective cohort studies and case-control studies; (b)all-ages mild and moderate TBIs; (c)HT administration; (d)functional outcomes recorded; (e)comparator group. RESULTS: From 4424 records, only 3 respected the inclusion criteria. In a retrospective cohort study of adult moderate TBIs, the Glasgow Coma Scale(GCS) remained the same at 48 hours in those treated with hypertonic saline(HTS) while it worsened in the non-treated. A trend toward increased pulmonary infections and length of stay was found. In an RCT of adult severe and moderate TBIs, moderate TBIs treated with HTS showed a trend toward better secondary outcomes than standard care alone, with similar odds of adverse effects. An RCT enrolling children with mild TBI found a significant improvement in concussive pain immediately after HTS administration and after 2-3 days. No adverse events occurred. CONCLUSIONS: A gap in the literature about HTs' role in mild and moderate TBI was found. Some benefits may exist with limited side effects and further studies are desirable.

Deep neural networks allow expert-level brain meningioma segmentation and present potential for improvement of clinical practice.

Accurate brain meningioma segmentation and volumetric assessment are critical for serial patient follow-up, surgical planning and monitoring response to treatment. Current gold standard of manual labeling is a time-consuming process, subject to inter-user variability. Fully-automated algorithms for meningioma segmentation have the potential to bring volumetric analysis into clinical and research workflows by increasing accuracy and efficiency, reducing inter-user variability and saving time. Previous research has focused solely on segmentation tasks without assessment of impact and usability of deep learning solutions in clinical practice. Herein, we demonstrate a three-dimensional convolutional neural network (3D-CNN) that performs expert-level, automated meningioma segmentation and volume estimation on MRI scans. A 3D-CNN was initially trained by segmenting entire brain volumes using a dataset of 10,099 healthy brain MRIs. Using transfer learning, the network was then specifically trained on meningioma segmentation using 806 expert-labeled MRIs. The final model achieved a median performance of 88.2% reaching the spectrum of current inter-expert variability (82.6-91.6%). We demonstrate in a simulated clinical scenario that a deep learning approach to meningioma segmentation is feasible, highly accurate and has the potential to improve current clinical practice.

Surgery vs. Biopsy in the Treatment of Butterfly Glioblastoma: A Systematic Review and Meta-Analysis.

Butterfly glioblastomas (bGBM) are grade IV gliomas that spread to bilateral hemispheres by infiltrating the corpus callosum. Data on the effect of surgery are limited to small case series. The aim of this meta-analysis was to compare resection vs. biopsy in terms of survival outcomes and postoperative complications. A systematic review of the literature was conducted using PubMed, EMBASE, and Cochrane databases through March 2021 in accordance with the PRISMA checklist. Pooled hazard ratios were calculated and meta-analyzed in a random-effects model including assessment of heterogeneity. Out of 3367 articles, seven studies were included with 293 patients. Surgical resection was significantly associated with longer overall survival (HR 0.39, 95%CI 0.2-0.55) than biopsy. Low heterogeneity was observed (I2: 0%). In further analysis, the effect persisted in extent of resection subgroups of both ≥80% and <80%. No statistically significant difference between surgery and biopsy was detected in terms of postoperative complications, although these were numerically larger for surgery. In patients with bGBM, surgical resection was associated with longer survival prospects compared with biopsy.

Efficacy and safety of flexible versus rigid endoscopic third ventriculostomy in pediatric and adult populations: a systematic review and meta-analysis.

Endoscopic third ventriculostomy (ETV) is a well-established surgical procedure for hydrocephalus treatment, but there is sparse evidence on the optimal choice between flexible and rigid approaches. A meta-analysis was conducted to compare efficacy and safety profiles of both techniques in pediatrics and adults. A comprehensive search was conducted on PubMED, EMBASE, and Cochrane until 11/10/2019. Efficacy was evaluated comparing incidence of ETV failure, while safety was defined by the incidence of perioperative complications, intraoperative bleedings, and deaths. Random-effects models were used to pool the incidence. Out of 1365 studies, 46 case series were meta-analyzed, yielding 821 patients who underwent flexible ETV and 2918 who underwent rigid ETV, with an age range of [5 days-87 years]. Although flexible ETV had a higher incidence of failure in adults (flexible: 54%, 95%CI: 22-82% vs rigid: 20%, 95%CI: 22-82%) possibly due to confounding due to etiology in adults treated with flexible, a smaller difference was seen in pediatrics (flexible: 36%, pediatric: 32%). Safety profiles were acceptable for both techniques, with a certain degree of variability for complications (flexible 2%, rigid 18%) and death (flexible 1%, rigid 3%) in pediatrics as well as complications (rigid 9%, flexible 13%), death (flexible 4%, rigid 6%) and intra-operative bleeding events (rigid 6%, flexible 8%) in adults. No clear superiority in efficacy could be depicted between flexible and rigid ETV for hydrocephalus treatment. Safety profiles varied by age but were acceptable for both techniques. Well-designed comparative studies are needed to assess the optimal endoscopic treatment option for hydrocephalus.

Spinal hemangioblastomas: analysis of surgical outcome and prognostic factors.

The prognostic factors for surgically removed spinal hemangioblastomas, the impact of VHL disease on outcome, and the role of intraoperative neuromonitoring are still not completely clear. The aim of this study was to review our experience with spinal hemangioblastomas in order to assess potential predictors of neurological outcome after surgery. All cases of spinal hemangioblastomas removed at two Italian academic institutions from 1985 to 2020 were reviewed. Data about clinical presentation and symptom duration, diagnosis of VHL, surgical approach, use of IONM, duration of hospital stay, follow-up, and modified McCormick grade before and after surgery were extracted. Sixty-one patients (31 F, 30 M) underwent 69 surgeries to remove 74 spinal hemangioblastomas (37 cervical, 32 thoracic, 5 lumbar). Improvement was found in 32.3% of cases, neurological condition remained stable in 51.6% of cases, and deteriorated in 16.1% of patients. A worsening trend in VHL patients and an improvement trend in non-VHL patients were detected, despite the lack of statistical significance. Laminotomy and use of IONM were found to be associated with better outcome, although no association was found between surgery without IONM and worse outcome. In most cases, patients affected by spinal hemangioblastomas can expect a good long-term outcome. In our experience, laminotomy seems to be associated with better outcome compared to laminectomy. While its absence is not associated with worse outcome, IONM seems to be associated with a better neurological outcome. Our study suggests that the more impaired the preoperative neurological condition, the worse the outcome.

Mobile health and neurocognitive domains evaluation through smartphones: A meta-analysis.

BACKGROUND: Mobile health (mHealth) have significantly advanced evaluating neurocognitive functions; but, few reports have documented whether they validate neurocognitive impairments as well as paper-and-pencil neuropsychological tests. OBJECTIVE: To meta-analyze the correlation between mobile applications for neuropsychological tests and validated paper-and-pencil neuropsychological tests for evaluating neurocognitive impairments. METHOD: We used PubMed, Embase, Cochrane, Web of Science, and IEEE Explorer through January 2020 to identify studies that compared mobile applications for neuropsychological tests vs. paper-and-pencil neurophysiological tests. We used random-effects models via the DerSimonian and Laird method to extract pooled Pearson's correlation coefficients and we stratified by study design. RESULT: Nine out of 4639 screened articles (one RCT and eight prospective longitudinal case series) were included. For the observational studies, there was a statistically significant strong and direct correlation between mobile applications for neuropsychological test scores and validated paper-and-pencil neuropsychological assessment scores (r = 0.70; 95% CI 0.59, 0.79; I2 = 74.5%; p- heterogeneity <0.001). Stronger results were seen for the RCT (r = 0.92; 95% CI 0.77, 0.97). CONCLUSION: This meta-analysis showed a statistically significant correlation between mobile applications and the validated paper-and-pencil neuropsychological assessments analyzed for the evaluation of neurocognitive impairments.

Deep Learning for Adjacent Segment Disease at Preoperative MRI for Cervical Radiculopathy.

Background Patients who undergo surgery for cervical radiculopathy are at risk for developing adjacent segment disease (ASD). Identifying patients who will develop ASD remains challenging for clinicians. Purpose To develop and validate a deep learning algorithm capable of predicting ASD by using only preoperative cervical MRI in patients undergoing single-level anterior cervical diskectomy and fusion (ACDF). Materials and Methods In this Health Insurance Portability and Accountability Act-compliant study, retrospective chart review was performed for 1244 patients undergoing single-level ACDF in two tertiary care centers. After application of inclusion and exclusion criteria, 344 patients were included, of whom 60% (n = 208) were used for training and 40% for validation (n = 43) and testing (n = 93). A deep learning-based prediction model with 48 convolutional layers was designed and trained by using preoperative T2-sagittal cervical MRI. To validate model performance, a neuroradiologist and neurosurgeon independently provided ASD predictions for the test set. Validation metrics included accuracy, areas under the curve, and F1 scores. The difference in proportion of wrongful predictions between the model and clinician was statistically tested by using the McNemar test. Results A total of 344 patients (median age, 48 years; interquartile range, 41-58 years; 182 women) were evaluated. The model predicted ASD on the 93 test images with an accuracy of 88 of 93 (95%; 95% CI: 90, 99), sensitivity of 12 of 15 (80%; 95% CI: 60, 100), and specificity of 76 of 78 (97%; 95% CI: 94, 100). The neuroradiologist and neurosurgeon provided predictions with lower accuracy (54 of 93; 58%; 95% CI: 48, 68), sensitivity (nine of 15; 60%; 95% CI: 35, 85), and specificity (45 of 78; 58%; 95% CI: 56, 77) compared with the algorithm. The McNemar test on the contingency table demonstrated that the proportion of wrongful predictions was significantly lower by the model (test statistic, 2.000; P < .001). Conclusion A deep learning algorithm that used only preoperative cervical T2-weighted MRI outperformed clinical experts at predicting adjacent segment disease in patients undergoing surgery for cervical radiculopathy. © RSNA, 2021 An earlier incorrect version appeared online. This article was corrected on September 22, 2021.

The Impact of Age and Severity on Dementia After Traumatic Brain Injury: A Comparison Study.

BACKGROUND: Growing evidence associates traumatic brain injury (TBI) with increased risk of dementia, but few studies have evaluated associations in patients younger than 55 yr using non-TBI orthopedic trauma (NTOT) patients as controls to investigate the influence of age and TBI severity, and to identify predictors of dementia after trauma. OBJECTIVE: To investigate the relationship between TBI and dementia in an institutional group. METHODS: Retrospective cohort study (2000-2018) of TBI patients aged 45 to 100 yr vs NTOT controls. Primary outcome was dementia after TBI (followed ≤10 yr). Cox proportional hazards models were used to assess risk of dementia; logistic regression models assessed predictors of dementia. RESULTS: Among 24 846 patients, TBI patients developed dementia (7.5% vs 4.6%) at a younger age (78.6 vs 82.7 yr) and demonstrated higher 10-yr mortality than controls (27% vs 14%; P < .001). Mild TBI patients had higher incidence of dementia (9%) than moderate/severe TBI (5.4%), with lower 10-yr mortality (20% vs 31%; P < .001). Risk of dementia was significant in all mild TBI age groups, even 45 to 54 yr (hazard ratio 4.1, 95% CI 2.7-7.8). A total of 10-yr cumulative incidence was higher in mild TBI (14.4%) than moderate/severe TBI (11.3%) and controls (6.8%) (P < .001). Predictors of dementia include TBI, sex, age, hypertension, hyperlipidemia, stroke, depression, anxiety, and Injury Severity Score. CONCLUSION: Mild and moderate/severe TBI patients experienced higher incidence of dementia, even in the youngest group (45-54 yr old), than NTOT controls. All TBI patients, especially middle-aged adults with minor injury who are more likely to be overlooked, should be monitored for dementia.

Smartphone GPS signatures of patients undergoing spine surgery correlate with mobility and current gold standard outcome measures.

OBJECTIVE: Patient-reported outcome measures (PROMs) are currently the gold standard to evaluate patient physical performance and ability to recover after spine surgery. However, PROMs have significant limitations due to the qualitative and subjective nature of the information reported as well as the impossibility of using this method in a continuous manner. The smartphone global positioning system (GPS) can be used to provide continuous, quantitative, and objective information on patient mobility. The aim of this study was to use daily mobility features derived from the smartphone GPS to characterize the perioperative period of patients undergoing spine surgery and to compare these objective measurements to PROMs, the current gold standard. METHODS: Eight daily mobility features were derived from smartphone GPS data in a population of 39 patients undergoing spine surgery for a period of 2 months starting 3weeks before surgery. In parallel, three different PROMs for pain (visual analog scale [VAS]), disability (Oswestry Disability Index [ODI]) and functional status (Patient-Reported Outcomes Measurement Information System [PROMIS]) were serially measured. Segmented linear regression analysis was used to assess trends before and after surgery. The Student paired t-test was used to compare pre- and postoperative PROM scores. Pearson's correlation was calculated between the daily average of each GPS-based mobility feature and the daily average of each PROM score during the recovery period. RESULTS: Smartphone GPS features provided data documenting a reduction in mobility during the immediate postoperative period, followed by a progressive and steady increase with a return to baseline mobility values 1 month after surgery. PROMs measuring pain, physical performance, and disability were significantly different 1 month after surgery compared to the 2 immediate preoperative weeks. The GPS-based features presented moderate to strong linear correlation with pain VAS and PROMIS physical score during the recovery period (Pearson r > 0.7), whereas the ODI and PROMIS mental scores presented a weak correlation (Pearson r approximately 0.4). CONCLUSIONS: Smartphone-derived GPS features were shown to accurately characterize perioperative mobility trends in patients undergoing surgery for spine-related diseases. Features related to time (rather than distance) were better at describing patient physical and performance status. Smartphone GPS has the potential to be used for the development of accurate, noninvasive and personalized tools for patient mobility monitoring after surgery.

The use of Grauer classification in the management of type II odontoid fracture in elderly: Prognostic factors and outcome analysis in a single centre patient series.

OBJECTIVE: To evaluate the results of Type II odontoid fractures management in the elderly, according to the Grauer classification. METHODS: Consecutive patients with type II odontoid fracture, age > 65 years and follow-up longer than 3 months were included. Fracture management was proposed according to Grauer classification. Peri-surgical risk factors, NDI, VAS and rate of fusion were evaluated according to the treatment modality and compared between conservative and surgical groups. RESULTS: Thirty-four patients were considered eligible for the study; 2 patients showed a Type IIa fracture, 30 patients a type IIb, and 2 patients a type IIc. Type IIa patients underwent conservative treatment that resulted in failure. A conservative management was adopted in 9 cases with type IIb due to patient preference or anaesthesiologic reasons with a treatment success at 6 months of 11%. Trans-odontoid stabilization was adopted in 21 type IIb cases with an evidence of bony or fibrous union at 6 months of 95% and a median NDI of 20%. A posterior approach was reserved for 2 type IIc fracture patients and in 6 cases as rescue surgery (bony union at 6 months of 100%; median NDI 37%). Higher Lakshmanan grade, gap and displacement of the fracture were found as significant risk factor for fracture non-union (p < 0.05). CONCLUSIONS: The surgical group presented better clinical and radiological outcome and the anterior approach proved to achieve the best results in type IIb fractures. The presence of osteoporosis and fracture spatial features should be duly considered in the decision-making process.

Improved outcomes associated with maximal extent of resection for butterfly glioblastoma: insights from institutional and national data.

BACKGROUND: Butterfly glioblastomas (bGBMs) are grade IV gliomas that infiltrate the corpus callosum and spread to bilateral cerebral hemispheres. Due to the rarity of cases, there is a dearth of information in existing literature. Herein, we evaluate clinical and genetic characteristics, associated predictors, and survival outcomes in an institutional series and compare them to a national cohort. METHODS: We identified all adult patients with bGBM treated at Brigham & Women's Hospital (2008-2018). The National Cancer Database (NCDB) was also queried for bGBM patients. Survival was analyzed with Kaplan-Meier methods, and Cox models were built to assess for predictive factors. RESULTS: Of 993 glioblastoma patients, 62 cases (6.2%) of bGBM were identified. Craniotomy for resection was attempted in 26 patients (41.9%), with a median volumetric extent of resection (vEOR) of 72.3% (95% confidence interval [95%CI] 58.3-82.1). The IDH1 R132H mutation was detected in two patients (3.2%), and MGMT promoter was methylated in 55.5% of the assessed cases. In multivariable regression, factors predictive of longer OS were increased vEOR, MGMT promoter methylation, and receipt of adjuvant therapy. Median OS for the resected cases was 11.5 months (95%CI 7.7-18.8) vs. 6.3 (95%CI 5.1-8.9) for the biopsied. Of 21,353 GBMs, 719 (3.37%) bGBM patients were identified in the NCDB. Resection was more likely to be pursued in recent years, and GTR was independently associated with prolonged OS (p < 0.01). CONCLUSION: Surgical resection followed by adjuvant chemoradiation is associated with significant survival gains and should be pursued in carefully selected bGBM patients.

A National Surgical Quality Improvement Program Analysis of Postoperative Major and Minor Complications in Patients with Spinal Metastatic Disease.

BACKGROUND: Major complications after spine metastasis surgery are prioritized in the literature with little consideration of the more frequent minor events such as pneumonia or urinary tract infection. We analyzed incidence and risk factors of postsurgical complications in patients with spinal metastasis extracted from the National Surgical Quality Improvement Program (NSQIP). We also developed a useful predictive model to estimate the probability of occurrence of complications. METHODS: A total of 1176 patients diagnosed with spinal metastasis were extracted from NSQIP. Variables screened included age, sex, tumor location, patient's functional status, comorbidities, laboratory values, and case urgency. Two multivariate logistic regression models were designed to evaluate risk factors and likelihood of event occurrence. RESULTS: Minor events occurred twice as frequently compared with major complications (36% vs. 18% of patients). The most common major event was death (10%); the most frequent minor event was need for postoperative transfusion (29.4%). In the multivariate analysis, elderly age, emergency case, preoperative leukocytosis, and smoking status retained significance for major complications; American Society of Anesthesiologists classes 4-5, low hematocrit levels, and intradural extramedullary location of the tumor retained significance for minor complications. The predictive models designed explained 72% of the variability in major complications occurrence and 67% for minor events. CONCLUSIONS: Smoking status and emergent surgery were found to be the strongest independent predictors of major complications, whereas higher American Society of Anesthesiologists class showed a greater association with minor events. The predictive models produced can be a useful aid for surgeons to identify those patients who are at greater risk of developing postoperative adverse events.

Tapentadol prolonged release for managing moderate to severe chronic neck pain with or without a neuropathic component.

Background: Despite the high prevalence of neck pain, few studies have addressed the pharmacological treatment of this condition.Purpose: We evaluated the effectiveness of tapentadol prolonged-release (PR) in patients with or without a neuropathic pain component, with a focus on functional movements, disability and Quality of Life (QoL).Study design/setting: Observational, retrospective study.Patient sample: Ninety-four adult patients with severe neck pain not responsive to opioid step III treatment.Outcome measures: The primary endpoint was a ≥ 30% improvement of pain intensity at 4 weeks (W4). Several secondary outcomes were evaluated, including neck disability index (NDI), range of motion (ROM), and QoL.Methods: Patients received tapentadol PR at the starting dose of 100 mg/day. Dose titration was allowed in 50 mg increments, up to 500 mg daily.Results: At W4, the primary endpoint of ≥30% improvement of pain was reported in 70% (n = 35; 95% confidence interval [CI]: 55-82%) of patients with a neuropathic pain component and in 69% (n = 20; 95% CI: 49-85%) of those without a neuropathic component. The percentage of patients reporting a neuropathic pain component significantly decreased from baseline (64.2%) to W4 (27.8%). NDI significantly improved in both groups at W12. ROM significantly improved in all three planes of motion (p < .01), with no difference between the two groups. Interference of pain with sleep and QoL also improved.Conclusions: The reduction in pain provided by tapentadol is associated with functional recovery, which may in turn be linked to an improvement in QoL.

The subependymal microvascular network revealed by endoscopic fluorescence angiography.

BACKGROUND: The subependymal vascularization of the cerebral ventricles has been described in anatomical studies on human specimens. Its identification in vivo during neuroendoscopic navigation could have anatomical interest and may lead to a safer ventricular navigation, also avoiding unexpected bleeding. The traditional endoscopic visualization allows the certain identification of only the main vessels. In this study we describe the features of the subependymal vascular network (SEVN) enhanced by sodium fluorescein (SF) angiography. We compare these findings with the vascular patterns visible under white light to evaluate the sensitivity of this technique in unveiling the most distant branches of the SEVN. METHODS: We reviewed the video records of 39 fluorescein-assisted neuroendoscopic procedures. Steerable fiberscopes equipped with a dual observation mode for both white light and fluorescence were used. After preliminary inspection of the ventricular cavities, the camera was switched to the blue light fluorescent mode. Identical portion of ventricular walls observed in both modalities were compared and analyzed to enhance potential differences of the vascular features. RESULTS: The main veins were positive (fluorescein enhanced) in 10 patients (25.6%), vessels of smaller diameter visible also under white light presented a detectable fluorescence in 27 patients (69.2%), the micro SEVN, not visible under with light, was revealed by SF in 21 patients (53.8%). CONCLUSIONS: Fluorescein-guided neuroendoscopy deserves closer investigation since it allows detection of small vessels, not otherwise visible, in the ventricle walls. This method could be applied to ameliorate the knowledge of the environment the surgeon is working on, leading as a result to a safer navigation, also by avoiding minor bleedings.

Contemporary assessment of extent of resection in molecularly defined categories of diffuse low-grade glioma: a volumetric analysis.

OBJECTIVE: While the effect of increased extent of resection (EOR) on survival in diffuse infiltrating low-grade glioma (LGG) patients is well established, there is still uncertainty about the influence of the new WHO molecular subtypes. The authors designed a retrospective analysis to assess the interplay between EOR and molecular classes. METHODS: The authors retrospectively reviewed the records of 326 patients treated surgically for hemispheric WHO grade II LGG at Brigham and Women's Hospital and Massachusetts General Hospital (2000-2017). EOR was calculated volumetrically and Cox proportional hazards models were built to assess for predictive factors of overall survival (OS), progression-free survival (PFS), and malignant progression-free survival (MPFS). RESULTS: There were 43 deaths (13.2%; median follow-up 5.4 years) among 326 LGG patients. Median preoperative tumor volume was 31.2 cm3 (IQR 12.9-66.0), and median postoperative residual tumor volume was 5.8 cm3 (IQR 1.1-20.5). On multivariable Cox regression, increasing postoperative volume was associated with worse OS (HR 1.02 per cm3; 95% CI 1.00-1.03; p = 0.016), PFS (HR 1.01 per cm3; 95% CI 1.00-1.02; p = 0.001), and MPFS (HR 1.01 per cm3; 95% CI 1.00-1.02; p = 0.035). This result was more pronounced in the worse prognosis subtypes of IDH-mutant and IDH-wildtype astrocytoma, for which differences in survival manifested in cases with residual tumor volume of only 1 cm3. In oligodendroglioma patients, postoperative residuals impacted survival when exceeding 8 cm3. Other significant predictors of OS were age at diagnosis, IDH-mutant and IDH-wildtype astrocytoma classes, adjuvant radiotherapy, and increasing preoperative volume. CONCLUSIONS: The results corroborate the role of EOR in survival and malignant transformation across all molecular subtypes of diffuse LGG. IDH-mutant and IDH-wildtype astrocytomas are affected even by minimal postoperative residuals and patients could potentially benefit from a more aggressive surgical approach.

Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement.

BACKGROUND: Longitudinal measurement of glioma burden with MRI is the basis for treatment response assessment. In this study, we developed a deep learning algorithm that automatically segments abnormal fluid attenuated inversion recovery (FLAIR) hyperintensity and contrast-enhancing tumor, quantitating tumor volumes as well as the product of maximum bidimensional diameters according to the Response Assessment in Neuro-Oncology (RANO) criteria (AutoRANO). METHODS: Two cohorts of patients were used for this study. One consisted of 843 preoperative MRIs from 843 patients with low- or high-grade gliomas from 4 institutions and the second consisted of 713 longitudinal postoperative MRI visits from 54 patients with newly diagnosed glioblastomas (each with 2 pretreatment "baseline" MRIs) from 1 institution. RESULTS: The automatically generated FLAIR hyperintensity volume, contrast-enhancing tumor volume, and AutoRANO were highly repeatable for the double-baseline visits, with an intraclass correlation coefficient (ICC) of 0.986, 0.991, and 0.977, respectively, on the cohort of postoperative GBM patients. Furthermore, there was high agreement between manually and automatically measured tumor volumes, with ICC values of 0.915, 0.924, and 0.965 for preoperative FLAIR hyperintensity, postoperative FLAIR hyperintensity, and postoperative contrast-enhancing tumor volumes, respectively. Lastly, the ICCs for comparing manually and automatically derived longitudinal changes in tumor burden were 0.917, 0.966, and 0.850 for FLAIR hyperintensity volume, contrast-enhancing tumor volume, and RANO measures, respectively. CONCLUSIONS: Our automated algorithm demonstrates potential utility for evaluating tumor burden in complex posttreatment settings, although further validation in multicenter clinical trials will be needed prior to widespread implementation.

Machine learning reveals multimodal MRI patterns predictive of isocitrate dehydrogenase and 1p/19q status in diffuse low- and high-grade gliomas.

PURPOSE: Isocitrate dehydrogenase (IDH) and 1p19q codeletion status are importantin providing prognostic information as well as prediction of treatment response in gliomas. Accurate determination of the IDH mutation status and 1p19q co-deletion prior to surgery may complement invasive tissue sampling and guide treatment decisions. METHODS: Preoperative MRIs of 538 glioma patients from three institutions were used as a training cohort. Histogram, shape, and texture features were extracted from preoperative MRIs of T1 contrast enhanced and T2-FLAIR sequences. The extracted features were then integrated with age using a random forest algorithm to generate a model predictive of IDH mutation status and 1p19q codeletion. The model was then validated using MRIs from glioma patients in the Cancer Imaging Archive. RESULTS: Our model predictive of IDH achieved an area under the receiver operating characteristic curve (AUC) of 0.921 in the training cohort and 0.919 in the validation cohort. Age offered the highest predictive value, followed by shape features. Based on the top 15 features, the AUC was 0.917 and 0.916 for the training and validation cohort, respectively. The overall accuracy for 3 group prediction (IDH-wild type, IDH-mutant and 1p19q co-deletion, IDH-mutant and 1p19q non-codeletion) was 78.2% (155 correctly predicted out of 198). CONCLUSION: Using machine-learning algorithms, high accuracy was achieved in the prediction of IDH genotype in gliomas and moderate accuracy in a three-group prediction including IDH genotype and 1p19q codeletion.