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PURPOSE: Registration and segmentation of magnetic resonance (MR) and ultrasound (US) images could play an essential role in surgical planning and resectioning brain tumors. However, validating these techniques is challenging due to the scarcity of publicly accessible sources with high-quality ground truth information. To this end, we propose a unique set of segmentations (RESECT-SEG) of cerebral structures from the previously published RESECT dataset to encourage a more rigorous development and assessment of image-processing techniques for neurosurgery. ACQUISITION AND VALIDATION METHODS: The RESECT database consists of MR and intraoperative US (iUS) images of 23 patients who underwent brain tumor resection surgeries. The proposed RESECT-SEG dataset contains segmentations of tumor tissues, sulci, falx cerebri, and resection cavity of the RESECT iUS images. Two highly experienced neurosurgeons validated the quality of the segmentations. DATA FORMAT AND USAGE NOTES: Segmentations are provided in 3D NIFTI format in the OSF open-science platform: https://osf.io/jv8bk. POTENTIAL APPLICATIONS: The proposed RESECT-SEG dataset includes segmentations of real-world clinical US brain images that could be used to develop and evaluate segmentation and registration methods. Eventually, this dataset could further improve the quality of image guidance in neurosurgery.
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BACKGROUND: Gliomas have a heterogeneous nature, and identifying the most aggressive parts of the tumor and defining tumor borders are important for histomolecular diagnosis, surgical resection, and radiation therapy planning. This study evaluated [18F]-FACBC PET for glioma tissue classification. METHODS: Pre-surgical [18F]-FACBC PET/MR images were used during surgery and image-localized biopsy sampling in patients with high- and low-grade glioma. TBR was compared to histomolecular results to determine optimal threshold values, sensitivity, specificity, and AUC values for the classification of tumor tissue. Additionally, PET volumes were determined in patients with glioblastoma based on the optimal threshold. [18F]-FACBC PET volumes and diagnostic accuracy were compared to ce-T1 MRI. In total, 48 biopsies from 17 patients were analyzed. RESULTS: [18F]-FACBC had low uptake in non-glioblastoma tumors, but overall higher sensitivity and specificity for the classification of tumor tissue (0.63 and 0.57) than ce-T1 MRI (0.24 and 0.43). Additionally, [18F]-FACBC TBR was an excellent classifier for IDH1-wildtype tumor tissue (AUC: 0.83, 95% CI: 0.71-0.96). In glioblastoma patients, PET tumor volumes were on average eight times larger than ce-T1 MRI volumes and included 87.5% of tumor-positive biopsies compared to 31.5% for ce-T1 MRI. CONCLUSION: The addition of [18F]-FACBC PET to conventional MRI could improve tumor classification and volume delineation.
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Standard treatment of patients with glioblastoma includes surgical resection of the tumor. The extent of resection (EOR) achieved during surgery significantly impacts prognosis and is used to stratify patients in clinical trials. In this study, we developed a U-Net-based deep-learning model to segment contrast-enhancing tumor on post-operative MRI exams taken within 72â h of resection surgery and used these segmentations to classify the EOR as either maximal or submaximal. The model was trained on 122 multiparametric MRI scans from our institution and achieved a mean Dice score of 0.52 ± 0.03 on an external dataset (n = 248), a performance -on par with the interrater agreement between expert annotators as reported in literature. We obtained an EOR classification precision/recall of 0.72/0.78 on the internal test dataset (n = 462) and 0.90/0.87 on the external dataset. Furthermore, Kaplan-Meier curves were used to compare the overall survival between patients with maximal and submaximal resection in the internal test dataset, as determined by either clinicians or the model. There was no significant difference between the survival predictions using the model's and clinical EOR classification. We find that the proposed segmentation model is capable of reliably classifying the EOR of glioblastoma tumors on early post-operative MRI scans. Moreover, we show that stratification of patients based on the model's predictions offers at least the same prognostic value as when done by clinicians.
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Introduction: Postoperative hematomas that require reoperation are a serious, but uncommon complication to glioma surgery. However, smaller blood volumes are frequently observed, but their clinical significance is less known. Research question: What are the incidence rates, risk factors, and patient-reported outcomes of all measurable blood in or near the resection cavity on postoperative MRI in diffuse glioma patients? Material and methods: We manually segmented intradural and extradural blood from early postoperative MRI of 292 diffuse glioma resections. Potential associations between blood volume and tumor characteristics, demographics, and perioperative factors were explored using non-parametric methods. The assessed outcomes were generic and disease-specific patient-reported HRQoL. Results: Out of the 292 MRI scans included, 184 (63%) had intradural blood, and 212 (73%) had extradural blood in or near the resection cavity. The median blood volumes were 0.4 mL and 3.0 mL, respectively. Intradural blood volume was associated with tumor volume, intraoperative blood loss, and EOR. Extradural blood volume was associated with age and tumor volume. Greater intradural blood volume was associated with less headache and cognitive improvement, but not after adjustments for tumor volume. Discussion and conclusions: Postoperative blood on early postoperative MRI is common. Intradural blood volumes tend to be larger in patients with larger tumors, more intraoperative blood loss, or undergoing subtotal resections. Extradural blood volumes tend to be larger in younger patients with larger tumors. Postoperative blood in or near the resection cavity that does not require reoperation does not seem to affect HRQoL in diffuse glioma patients.
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Traumatic axonal injury (TAI) is a common finding on magnetic resonance imaging (MRI) in patients with moderate-severe traumatic brain injury (TBI), and the burden of TAI is associated with outcome in this patient group. Lesion mapping offers a way to combine imaging findings from numerous individual patients into common lesion maps where the findings from a whole patient cohort can be assessed. The aim of this study was to evaluate the spatial distribution of TAI lesions on different MRI sequences and its associations to outcome with use of lesion mapping. Included prospectively were 269 patients (8-70 years) with moderate or severe TBI and MRI within six weeks after injury. The TAI lesions were evaluated and manually segmented on fluid-attenuated inversed recovery (FLAIR), diffusion weighted imaging (DWI), and either T2* gradient echo (T2*GRE) or susceptibility weighted imaging (SWI). The segmentations were registered to the Montreal Neurological Institute space and combined to lesion frequency distribution maps. Outcome was assessed with Glasgow Outcome Scale Extended (GOSE) score at 12 months. The frequency and distribution of TAI was assessed qualitatively by visual reading. Univariable associations to outcome were assessed qualitatively by visual reading and also quantitatively with use of voxel-based lesion-symptom mapping (VLSM). The highest frequency of TAI was found in the posterior half of corpus callosum. The frequency of TAI was higher in the frontal and temporal lobes than in the parietal and occipital lobes, and in the upper parts of the brainstem than in the lower. At the group level, all voxels in mesencephalon had TAI on FLAIR. The patients with poorest outcome (GOSE scores ≤4) had higher frequencies of TAI. On VLSM, poor outcome was associated with TAI lesions bilaterally in the splenium, the right side of tectum, tegmental mesencephalon, and pons. In conclusion, we found higher frequency of TAI in posterior corpus callosum, and TAI in splenium, mesencephalon, and pons were associated with poor outcome. If lesion frequency distribution maps containing outcome information based on imaging findings from numerous patients in the future can be compared with the imaging findings from individual patients, it would offer a new tool in the clinical workup and outcome prediction of the patient with TBI.
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Lesões Encefálicas Traumáticas , Lesão Axonal Difusa , Imageamento por Ressonância Magnética , Humanos , Adulto , Masculino , Feminino , Pessoa de Meia-Idade , Adolescente , Adulto Jovem , Lesões Encefálicas Traumáticas/diagnóstico por imagem , Idoso , Imageamento por Ressonância Magnética/métodos , Criança , Lesão Axonal Difusa/diagnóstico por imagem , Estudos ProspectivosRESUMO
BACKGROUND: Surveillance of incidence and survival of central nervous system tumors is essential to monitor disease burden and epidemiological changes, and to allocate health care resources. Here, we describe glioma incidence and survival trends by histopathology group, age, and sex in the Norwegian population. MATERIAL AND METHODS: We included patients with a histologically verified glioma reported to the Cancer Registry of Norway from 2002 to 2021 (N = 7,048). Population size and expected mortality were obtained from Statistics Norway. Cases were followed from diagnosis until death, emigration, or 31 December 2022, whichever came first. We calculated age-standardized incidence rates (ASIR) per 100,000 person-years and age-standardized relative survival (RS). Results: The ASIR for histologically verified gliomas was 7.4 (95% CI: 7.3-7.6) and was higher for males (8.8; 95% CI: 8.5-9.1) than females (6.1; 95% CI: 5.9-6.4). Overall incidence was stable over time. Glioblastoma was the most frequent tumor entity (ASIR = 4.2; 95% CI: 4.1-4.4). Overall, glioma patients had a 1-year RS of 63.6% (95% CI: 62.5-64.8%), and a 5-year RS of 32.8% (95% CI: 31.6-33.9%). Females had slightly better survival than males. For most entities, 1- and 5-year RS improved over time (5-year RS for all gliomas 29.0% (2006) and 33.1% (2021), p < 0.001). Across all tumor types, the RS declined with increasing age at diagnosis. INTERPRETATION: The incidence of gliomas has been stable while patient survival has increased over the past 20 years in Norway. As gliomas represent a heterogeneous group of primary CNS tumors, regular reporting from cancer registries at the histopathology group level is important to monitor disease burden and allocate health care resources in a population.
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Glioma , Masculino , Feminino , Humanos , Incidência , Estudos de Coortes , Glioma/epidemiologia , Sistema de Registros , Noruega/epidemiologiaRESUMO
BACKGROUND: Postoperative drainage systems have become a standard treatment for chronic subdural hematoma (CSDH). We previously compared treatment results from three Scandinavian centers using three different postoperative drainage systems and concluded that the active subgaleal drainage was associated with lower recurrence and complication rates than the passive subdural drainage. We consequently changed clinical practice from using the passive subdural drainage to the active subgaleal drainage. OBJECTIVE: The aim of the present study was to assess a potential change in reoperation rates for CSDH after conversion to the active subgaleal drainage. METHODS: This single-center cohort study compared the reoperation rates for recurrent same-sided CSDH and postoperative complication rates between patients treated during two study periods (passive subdural drainage cohort versus active subgaleal drainage cohort). RESULTS: In total, 594 patients were included in the study. We found no significant difference in reoperation rates between the passive subdural drain group and the active subgaleal drain group (21.6%, 95% CI 17.5-26.4% vs. 18.0%, 95% CI 13.8-23.2%; p = 0.275). There was no statistical difference in the rate of serious complications between the groups. The operating time was significantly shorter for patients operated with the active subgaleal drain than patients with the passive subdural drain (32.8 min, 95% CI 31.2-34.5 min vs. 47.6 min, 95% CI 44.7-50.4 min; p < 0.001). CONCLUSIONS: Conversion from the passive subdural to the active subgaleal drainage did not result in a clear reduction of reoperation rates for CSDH in our center.
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Hematoma Subdural Crônico , Humanos , Seguimentos , Estudos de Coortes , Estudos Retrospectivos , Hematoma Subdural Crônico/cirurgia , ReoperaçãoRESUMO
Background: Knowledge about meningioma growth characteristics is needed for developing biologically rational follow-up routines. In this study of untreated meningiomas followed with repeated magnetic resonance imaging (MRI) scans, we studied growth dynamics and explored potential factors associated with tumor growth. Methods: In a single-center cohort study, we included 235 adult patients with radiologically suspected intracranial meningioma and at least 3 MRI scans during follow-up. Tumors were segmented using an automatic algorithm from contrast-enhanced T1 series, and, if needed, manually corrected. Potential meningioma growth curves were statistically compared: linear, exponential, linear radial, or Gompertzian. Factors associated with growth were explored. Results: In 235 patients, 1394 MRI scans were carried out in the median 5-year observational period. Of the models tested, a Gompertzian growth curve best described growth dynamics of meningiomas on group level. 59% of the tumors grew, 27% remained stable, and 14% shrunk. Only 13 patients (5%) underwent surgery during the observational period and were excluded after surgery. Tumor size at the time of diagnosis, multifocality, and length of follow-up were associated with tumor growth, whereas age, sex, presence of peritumoral edema, and hyperintense T2-signal were not significant factors. Conclusions: Untreated meningiomas follow a Gompertzian growth curve, indicating that increasing and potentially doubling subsequent follow-up intervals between MRIs seems biologically reasonable, instead of fixed time intervals. Tumor size at diagnosis is the strongest predictor of future growth, indicating a potential for longer follow-up intervals for smaller tumors. Although most untreated meningiomas grow, few require surgery.
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PURPOSE: The primary aim was to evaluate whether anti-3-[18F]FACBC PET combined with conventional MRI correlated better with histomolecular diagnosis (reference standard) than MRI alone in glioma diagnostics. The ability of anti-3-[18F]FACBC to differentiate between molecular and histopathological entities in gliomas was also evaluated. METHODS: In this prospective study, patients with suspected primary or recurrent gliomas were recruited from two sites in Norway and examined with PET/MRI prior to surgery. Anti-3-[18F]FACBC uptake (TBRpeak) was compared to histomolecular features in 36 patients. PET results were then added to clinical MRI readings (performed by two neuroradiologists, blinded for histomolecular results and PET data) to assess the predicted tumor characteristics with and without PET. RESULTS: Histomolecular analyses revealed two CNS WHO grade 1, nine grade 2, eight grade 3, and 17 grade 4 gliomas. All tumors were visible on MRI FLAIR. The sensitivity of contrast-enhanced MRI and anti-3-[18F]FACBC PET was 61% (95%CI [45, 77]) and 72% (95%CI [58, 87]), respectively, in the detection of gliomas. Median TBRpeak was 7.1 (range: 1.4-19.2) for PET positive tumors. All CNS WHO grade 1 pilocytic astrocytomas/gangliogliomas, grade 3 oligodendrogliomas, and grade 4 glioblastomas/astrocytomas were PET positive, while 25% of grade 2-3 astrocytomas and 56% of grade 2-3 oligodendrogliomas were PET positive. Generally, TBRpeak increased with malignancy grade for diffuse gliomas. A significant difference in PET uptake between CNS WHO grade 2 and 4 gliomas (p < 0.001) and between grade 3 and 4 gliomas (p = 0.002) was observed. Diffuse IDH wildtype gliomas had significantly higher TBRpeak compared to IDH1/2 mutated gliomas (p < 0.001). Adding anti-3-[18F]FACBC PET to MRI improved the accuracy of predicted glioma grades, types, and IDH status, and yielded 13.9 and 16.7 percentage point improvement in the overall diagnoses for both readers, respectively. CONCLUSION: Anti-3-[18F]FACBC PET demonstrated high uptake in the majority of gliomas, especially in IDH wildtype gliomas, and improved the accuracy of preoperatively predicted glioma diagnoses. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT04111588, URL: https://clinicaltrials.gov/study/NCT04111588.
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Neoplasias Encefálicas , Glioblastoma , Glioma , Oligodendroglioma , Humanos , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/patologia , Estudos Prospectivos , Recidiva Local de Neoplasia , Glioma/diagnóstico por imagem , Glioma/patologia , Tomografia por Emissão de Pósitrons/métodos , Imageamento por Ressonância MagnéticaRESUMO
Extent of resection after surgery is one of the main prognostic factors for patients diagnosed with glioblastoma. To achieve this, accurate segmentation and classification of residual tumor from post-operative MR images is essential. The current standard method for estimating it is subject to high inter- and intra-rater variability, and an automated method for segmentation of residual tumor in early post-operative MRI could lead to a more accurate estimation of extent of resection. In this study, two state-of-the-art neural network architectures for pre-operative segmentation were trained for the task. The models were extensively validated on a multicenter dataset with nearly 1000 patients, from 12 hospitals in Europe and the United States. The best performance achieved was a 61% Dice score, and the best classification performance was about 80% balanced accuracy, with a demonstrated ability to generalize across hospitals. In addition, the segmentation performance of the best models was on par with human expert raters. The predicted segmentations can be used to accurately classify the patients into those with residual tumor, and those with gross total resection.
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Glioblastoma , Humanos , Europa (Continente) , Glioblastoma/diagnóstico por imagem , Glioblastoma/cirurgia , Glioblastoma/patologia , Processamento de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética/métodos , Neoplasia Residual/diagnóstico por imagem , Redes Neurais de Computação , Estudos Multicêntricos como Assunto , Conjuntos de Dados como AssuntoRESUMO
PURPOSE: The aim of this study was to study the use of brain scanning, and the subsequent findings of presumed incidental meningioma in two time periods, and to study differences in follow-up, treatment, and outcome. METHODS: Records of all performed CT and MRI of the brain during two time periods were retrospectively reviewed in search of patients with presumed incidental meningioma. These patients were further analyzed using medical health records, with the purpose to study clinical handling and outcome during a 3 year follow up. RESULTS: An identical number of unique patients underwent brain imaging during the two time periods (n = 22 259 vs. 22 013). In 2018-2019, 25% more incidental meningiomas were diagnosed compared to 2008-2009 (n = 161 vs. 129, p = 0.052). MRI was used more often in 2018-2019 (26.1 vs. 12.4%, p = 0.004), and the use of contrast enhancement, irrespective of modality, also increased (26.8 vs. 12.2%, p < 0.001). In the most recent cohort, patients were older (median 79 years vs. 73 years, p = 0.03). Indications showed a significant increase of cancer without known metastases among scanned patients. 29.5 and 35.4% of patients in the cohorts were deceased 3 years after diagnosis for causes unrelated to their meningioma. CONCLUSIONS: Despite the same number of unique patients undergoing brain scans in the time periods, there was a trend towards more patients diagnosed with an incidental asymptomatic meningioma in the more recent years. This difference may be attributed to more contrast enhanced scans and more scans among the elderly but needs to be further studied. Patients in the cohort from 2018 to 2019 more often had non-metastatic cancer, with their cause of scan screening for metastases. There was no significant difference in management decision at diagnosis, but within 3 years of follow up significantly more patients in the latter cohort had been re-scanned. Almost a third of all patients were deceased within 3 years after diagnosis, due to causes other than their meningioma.
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Neoplasias Meníngeas , Meningioma , Humanos , Idoso , Meningioma/diagnóstico por imagem , Meningioma/epidemiologia , Meningioma/terapia , Estudos Retrospectivos , Incidência , Encéfalo/patologia , Neoplasias Meníngeas/diagnóstico por imagem , Neoplasias Meníngeas/epidemiologia , Neoplasias Meníngeas/terapiaRESUMO
Objective cognitive function in patients with glioblastoma may depend on tumor location. Less is known about the potential impact of tumor location on cognitive function from the patients' perspective. This study aimed to investigate the association between patient-reported cognitive function and the location of glioblastoma using voxel-based lesion-symptom mapping. Patient-reported cognitive function was assessed with the European Organisation for Research and Treatment (EORTC) QLQ-C30 cognitive function subscale preoperatively and 1 month postoperatively. Semi-automatic tumor segmentations from preoperative MRI images with the corresponding EORTC QLQ-C30 cognitive function score were registered to a standardized brain template. Student's pooled-variance t-test was used to compare mean patient-reported cognitive function scores between those with and without tumors in each voxel. Both preoperative brain maps (n = 162) and postoperative maps of changes (n = 99) were developed. Glioblastomas around the superior part of the left lateral ventricle, the left lateral part of the thalamus, the left caudate nucleus, and a portion of the left internal capsule were significantly associated with reduced preoperative patient-reported cognitive function. However, no voxels were significantly associated with postoperative change in patient-reported cognitive function assessed 1 month postoperatively. There seems to be an anatomical relation between tumor location and patient-reported cognitive function before surgery, with the left hemisphere being the dominant from the patients' perspective.
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Glioblastoma , Humanos , Glioblastoma/cirurgia , Encéfalo , Imageamento por Ressonância Magnética/métodos , Cognição , Medidas de Resultados Relatados pelo Paciente , Qualidade de Vida , Inquéritos e QuestionáriosRESUMO
For patients suffering from central nervous system tumors, prognosis estimation, treatment decisions, and postoperative assessments are made from the analysis of a set of magnetic resonance (MR) scans. Currently, the lack of open tools for standardized and automatic tumor segmentation and generation of clinical reports, incorporating relevant tumor characteristics, leads to potential risks from inherent decisions' subjectivity. To tackle this problem, the proposed Raidionics open-source software has been developed, offering both a user-friendly graphical user interface and stable processing backend. The software includes preoperative segmentation models for each of the most common tumor types (i.e., glioblastomas, lower grade gliomas, meningiomas, and metastases), together with one early postoperative glioblastoma segmentation model. Preoperative segmentation performances were quite homogeneous across the four different brain tumor types, with an average Dice around 85% and patient-wise recall and precision around 95%. Postoperatively, performances were lower with an average Dice of 41%. Overall, the generation of a standardized clinical report, including the tumor segmentation and features computation, requires about ten minutes on a regular laptop. The proposed Raidionics software is the first open solution enabling an easy use of state-of-the-art segmentation models for all major tumor types, including preoperative and postsurgical standardized reports.
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Neoplasias Encefálicas , Neoplasias do Sistema Nervoso Central , Glioblastoma , Neoplasias Meníngeas , Meningioma , Humanos , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/cirurgia , Glioblastoma/diagnóstico por imagem , Glioblastoma/cirurgia , SoftwareRESUMO
PURPOSE: Since the introduction of the molecular definition of oligodendrogliomas based on isocitrate dehydrogenase (IDH)-status and the 1p19q-codeletion, it has become increasingly evident how this glioma entity differs much from other diffuse lower grade gliomas and stands out with longer survival and often better responsiveness to adjuvant therapy. Therefore, apart from using a molecular oligodendroglioma definition, an extended follow-up time is necessary to understand the nature of this slow growing, yet malignant condition. The aim of this study was to describe the long-term course of the oligodendroglioma disease in a population-based setting and to determine which factors affect outcome in terms of survival. METHODS: All adults with WHO-grade 2 oligodendrogliomas with known 1p19q-codeletion from five Scandinavian neurosurgical centers and with a follow-up time exceeding 5 years, were analyzed regarding survival and factors potentially affecting survival. RESULTS: 126 patients diagnosed between 1998 and 2016 were identified. The median follow-up was 12.0 years, and the median survival was 17.8 years (95% CI 16.0-19.6). Factors associated with shorter survival in multivariable analysis were age (HR 1.05 per year; CI 1.02-1.08, p < 0.001), tumor diameter (HR 1.05 per millimeter; CI 1.02-1.08, p < 0.001) and poor preoperative functional status (KPS < 80) (HR 4.47; CI 1.70-11.78, p = 0.002). In our material, surgical strategy was not associated with survival. CONCLUSION: Individuals with molecularly defined oligodendrogliomas demonstrate long survival, also in a population-based setting. This is important to consider for optimal timing of therapies that may cause long-term side effects. Advanced age, large tumors and poor function before surgery are predictors of shorter survival.
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Glioma , Oligodendroglioma , Adulto , Humanos , Oligodendroglioma/genética , Oligodendroglioma/terapia , Seguimentos , Terapia Combinada , Organização Mundial da SaúdeRESUMO
BACKGROUND: Brain metastases (BM) are common in cancer patients and are associated with high morbidity and mortality. Surgery is an option, but the optimal selection of patients for surgery is challenging and controversial. Current prognostication tools are not ideal for preoperative prognostication. By using a reference population (derivation data set) and two external populations (validation data set) of patients who underwent surgery for BM, we aimed to create and validate a preoperative prognostic index. METHODS: The derivation data set consists of 590 patients who underwent surgery for BM (2011-2018) at Oslo University Hospital. We identified variables associated with survival and created a preoperative prognostic index with four prognostic groups, which was validated on patients who underwent surgery for BM at Karolinska University Hospital and St. Olavs University Hospital during the same time period. To reduce over-fitting, we adjusted the index in accordance with our findings. RESULTS: 438 patients were included in the validation data set. The preoperative prognostic index correctly divided patients into four true prognostic groups. The two prognostic groups with the poorest survival outcomes overlapped, and these were merged to create the adjusted preoperative prognostic index. CONCLUSION: We created a prognostic index for patients with BM that predicts overall survival preoperatively. This index might be valuable in supporting informed choice when considering surgery for BM.
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This follow-up study examines back painrelated disability at 6 months following a randomized trial of spinal cord burst stimulation for chronic radicular pain after lumbar spine surgery.
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Procedimentos Neurocirúrgicos , Radiculopatia , Estimulação da Medula Espinal , Humanos , Pessoas com Deficiência , Seguimentos , Dor/etiologia , Medula Espinal , Terapia por Estimulação Elétrica/métodos , Estimulação da Medula Espinal/métodos , Efeito Placebo , Radiculopatia/etiologia , Radiculopatia/terapia , Vértebras Lombares/cirurgia , Procedimentos Neurocirúrgicos/efeitos adversos , Procedimentos Neurocirúrgicos/métodosRESUMO
Meningioma is the most frequent brain tumor, and the incidence is ever-increasing. Though often benign and slow growth, recurrence rates are substantial and today's surgical and radiation-based treatment are not without complications. No drugs specific for meningiomas are hitherto approved and patients with inoperable or recurrent meningioma are left with few treatment options. Somatostatin receptors are previously detected in meningiomas and may inhibit growth when stimulated by somatostatin. Hence, somatostatin analogs could provide a targeted drug therapy. The aim of this study was to compile the current insights of somatostatin analogs for patients with meningioma. This paper adheres to the PRISMA extension for Scoping Reviews. A systematic search was conducted in the search databases PubMed, Embase via Ovid, and Web of Science. Seventeen papers adhered to the inclusion and exclusion criteria, and critical appraisal was conducted. The overall quality of evidence is low, as none of the studies were randomized or controlled. Various efficacy of somatostatin analogs is reported, and adverse effects are sparse. Due to the beneficial effects reported by some studies, somatostatin analogs may offer a novel last-option treatment for severely ill-patients. Nonetheless, only a controlled study, preferably a randomized clinical trial, could clarify the efficacy of somatostatin analogs.
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Neoplasias Meníngeas , Meningioma , Somatostatina , Humanos , Neoplasias Meníngeas/patologia , Meningioma/patologia , Recidiva Local de Neoplasia/tratamento farmacológico , Octreotida/uso terapêutico , Ensaios Clínicos Controlados Aleatórios como Assunto , Receptores de Somatostatina , Somatostatina/análogos & derivadosRESUMO
INTRODUCTION: Meningioma has a prevalence around 1% in the population, and with the increasing use and availability of diagnostic imaging modalities, incidental meningiomas are increasingly detected. There is no clear consensus on their management, although several guidelines suggest firsthand active monitoring if no aggravating factors emerge. However, no collective guidelines on follow-up interval exist. AREAS COVERED: This narrative review covers the epidemiology, diagnosis, growth prediction, and management strategies of incidental meningioma. EXPERT OPINION: Overdiagnosis and excessive follow-up are potential pitfalls in the management of incidental meningioma. An MRI after 6-12 months could be reasonable to rule out rapid growth and differential diagnoses. Using the available prognostic models, one might later suggest more active monitoring for certain patient groups harboring specific radiological features predictive of growth. However, detecting growth may not necessarily be clinically significant as all larger non-growing meningiomas have at one point been small. Too much follow-up may place an unnecessary burden on patients and the health-care system and could be a driver toward overtreatment. It must be contemplated whether growth is an acceptable primary outcome measure or if there are other factors more relevant to consider in this often benign tumor entity.
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Neoplasias Meníngeas , Meningioma , Humanos , Meningioma/diagnóstico por imagem , Meningioma/terapia , Neoplasias Meníngeas/diagnóstico por imagem , Neoplasias Meníngeas/terapia , Achados Incidentais , Imageamento por Ressonância Magnética , Prognóstico , Estudos RetrospectivosRESUMO
The globally accepted surgical strategy in glioblastomas is removing the enhancing tumor. However, the peritumoral region harbors infiltration areas responsible for future tumor recurrence. This study aimed to evaluate a predictive model that identifies areas of future recurrence using a voxel-based radiomics analysis of magnetic resonance imaging (MRI) data. This multi-institutional study included a retrospective analysis of patients diagnosed with glioblastoma who underwent surgery with complete resection of the enhancing tumor. Fifty-five patients met the selection criteria. The study sample was split into training (N = 40) and testing (N = 15) datasets. Follow-up MRI was used for ground truth definition, and postoperative structural multiparametric MRI was used to extract voxel-based radiomic features. Deformable coregistration was used to register the MRI sequences for each patient, followed by segmentation of the peritumoral region in the postoperative scan and the enhancing tumor in the follow-up scan. Peritumoral voxels overlapping with enhancing tumor voxels were labeled as recurrence, while non-overlapping voxels were labeled as nonrecurrence. Voxel-based radiomic features were extracted from the peritumoral region. Four machine learning-based classifiers were trained for recurrence prediction. A region-based evaluation approach was used for model evaluation. The Categorical Boosting (CatBoost) classifier obtained the best performance on the testing dataset with an average area under the curve (AUC) of 0.81 ± 0.09 and an accuracy of 0.84 ± 0.06, using region-based evaluation. There was a clear visual correspondence between predicted and actual recurrence regions. We have developed a method that accurately predicts the region of future tumor recurrence in MRI scans of glioblastoma patients. This could enable the adaptation of surgical and radiotherapy treatment to these areas to potentially prolong the survival of these patients.
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Importance: Disulfiram has demonstrated broad antitumoral effect in several preclinical studies. One of the proposed indications is for the treatment of glioblastoma. Objective: To evaluate the efficacy and safety of disulfiram and copper as add-on to alkylating chemotherapy in patients with recurrent glioblastoma. Design, Setting, and Participants: This was a multicenter, open-label, randomized phase II/III clinical trial with parallel group design. Patients were recruited at 7 study sites in Sweden and 2 sites in Norway between January 2017 and November 2020. Eligible patients were 18 years or older, had a first recurrence of glioblastoma, and indication for treatment with alkylating chemotherapy. Patients were followed up until death or a maximum of 24 months. The date of final follow-up was January 15, 2021. Data analysis was performed from February to September 2022. Interventions: Patients were randomized 1:1 to receive either standard-of-care (SOC) alkylating chemotherapy alone, or SOC with the addition of disulfiram (400 mg daily) and copper (2.5 mg daily). Main Outcomes and Measures: The primary end point was survival at 6 months. Secondary end points included overall survival, progression-free survival, adverse events, and patient-reported quality of life. Results: Among the 88 patients randomized to either SOC (n = 45) or SOC plus disulfiram and copper (n = 43), 63 (72%) were male; the mean (SD) age was 55.4 (11.5) years. There was no significant difference between the study groups (SOC vs SOC plus disulfiram and copper) in 6 months survival (62% [26 of 42] vs 44% [19 of 43]; P = .10). Median overall survival was 8.2 months (95% CI, 5.4-10.2 months) with SOC and 5.5 months (95% CI, 3.9-9.3 months) with SOC plus disulfiram and copper, and median progression-free survival was 2.6 months (95% CI, 2.4-4.6 months) vs 2.3 months (95% CI, 1.7-2.6 months), respectively. More patients in the SOC plus disulfiram and copper group had adverse events grade 3 or higher (34% [14 of 41] vs 11% [5 of 44]; P = .02) and serious adverse events (41% [17 of 41] vs 16% [7 of 44]; P = .02), and 10 patients (24%) discontinued disulfiram treatment because of adverse effects. Conclusions and Relevance: This randomized clinical trial found that among patients with recurrent glioblastoma, the addition of disulfiram and copper to chemotherapy, compared with chemotherapy alone, resulted in significantly increased toxic effects, but no significant difference in survival. These findings suggest that disulfiram and copper is without benefit in patients with recurrent glioblastoma. Trial Registration: ClinicalTrials.gov Identifier: NCT02678975; EUDRACT Identifier: 2016-000167-16.