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PURPOSE: The COVID-19 pandemic has led to changes in global health care. Medical societies had to update guidelines and enhance new services such as video consultations. Cancer treatment had to be modified. The aim of this study is to ensure optimal care for cancer patients with the help of high-quality training even in times of crisis. We therefore conducted a nationwide survey of physicians in training in oncological disciplines during the pandemic to assess the impact on their education. METHODS: The survey was sent to tumour centres, hospitals, specialist societies, and working and junior research groups and distributed via newsletters and homepages. Interim results and a call for participation were published as a poster (DEGRO) [26] and in the German Cancer Society (DKG) journal FORUM [42]. The survey contained 53 questions on conditions of education and training and on clinical and scientific work. Statistics were carried out with LimeSurvey and SPSS (IBM Corp., Armonk, NY, USA). RESULTS: Between February and November 2022, 450 participants answered the survey, with radio-oncologists being the largest group (28%). Most colleagues (63%) had access to digital training methods. Virtual sessions were rated as a good alternative, especially as multidisciplinary meetings (54%) as well as in-house and external training programs (48%, 47%). The time spent by training supervisors on education was rated as less than before the pandemic by 57%. Half of all participants perceived communication (54%), motivation (44%) and atmosphere (50%) in the team as bad. The participants felt strongly burdened by extra work (55%) and by a changed team atmosphere (49%). One third felt a change in the quality of training during the pandemic and rated it as negative (35%). According to 37% of the participants, this had little influence on their own quality of work. Additional subgroup analyses revealed significant differences in gender, specialty and education level. CONCLUSION: In order to improve oncology training in times of crisis, access to digital training options and meetings should be ensured. Participants wish for regular team meetings in person to enable good team spirit, compensation for overtime work and sufficient time for training supervisors for discussion and feedback.
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COVID-19 , Neoplasias , Humanos , COVID-19/epidemiologia , Pandemias , Escolaridade , Neoplasias/epidemiologia , Neoplasias/radioterapiaRESUMO
BACKGROUND: The expression level of the programmed cell death ligand 1 (PD-L1) appears to be a predictor for response to immunotherapy using checkpoint inhibitors in patients with non-small cell lung cancer (NSCLC). As differences in terms of PD-L1 expression levels in the extracranial primary tumor and the brain metastases may occur, a reliable method for the non-invasive assessment of the intracranial PD-L1 expression is, therefore of clinical value. Here, we evaluated the potential of radiomics for a non-invasive prediction of PD-L1 expression in patients with brain metastases secondary to NSCLC. PATIENTS AND METHODS: Fifty-three NSCLC patients with brain metastases from two academic neuro-oncological centers (group 1, n = 36 patients; group 2, n = 17 patients) underwent tumor resection with a subsequent immunohistochemical evaluation of the PD-L1 expression. Brain metastases were manually segmented on preoperative T1-weighted contrast-enhanced MRI. Group 1 was used for model training and validation, group 2 for model testing. After image pre-processing and radiomics feature extraction, a test-retest analysis was performed to identify robust features prior to feature selection. The radiomics model was trained and validated using random stratified cross-validation. Finally, the best-performing radiomics model was applied to the test data. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analyses. RESULTS: An intracranial PD-L1 expression (i.e., staining of at least 1% or more of tumor cells) was present in 18 of 36 patients (50%) in group 1, and 7 of 17 patients (41%) in group 2. Univariate analysis identified the contrast-enhancing tumor volume as a significant predictor for PD-L1 expression (area under the ROC curve (AUC), 0.77). A random forest classifier using a four-parameter radiomics signature, including tumor volume, yielded an AUC of 0.83 ± 0.18 in the training data (group 1), and an AUC of 0.84 in the external test data (group 2). CONCLUSION: The developed radiomics classifiers allows for a non-invasive assessment of the intracranial PD-L1 expression in patients with brain metastases secondary to NSCLC with high accuracy.
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Neoplasias Encefálicas , Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Humanos , Antígeno B7-H1 , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/secundário , Carcinoma Pulmonar de Células não Pequenas/diagnóstico por imagem , Carcinoma Pulmonar de Células não Pequenas/patologia , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/patologia , Estudos Retrospectivos , Curva ROCRESUMO
BACKGROUND: Treatment decision for recurrent symptomatic brain metastases (BM) is challenging with scarce data regarding surgical resection. We therefore evaluated the efficacy of surgery for pretreated, recurrent BM in a comprehensive multidisciplinary treatment setting. METHODS: In a retrospective single center study, patients were analyzed, who underwent surgical resection of recurrent BM between 2007 and 2019. Intracranial event-free survival (EFS) and overall survival (OS) were evaluated by Kaplan-Maier and Cox regression analysis. RESULTS: We included 107 patients with different primary tumor entities and individual previous treatment for BM. Primary tumors comprised non-small cell lung cancer (NSCLC) (37.4%), breast cancer (19.6%), melanoma (13.1%), gastro-intestinal cancer (10.3%) and other, rare entities (19.6%). The number of previous treatments of BM ranged from one to four; the adjuvant treatment modalities comprised: none, focal or whole brain radiotherapy, brachytherapy and radiosurgery. The median pre-operative Karnofsky Performance Score (KPS) was 70% (range 40-100) and improved to 80% (range 0-100) after surgery. The complication rate was 26.2% and two patients died during the perioperative period. Sixty-seven (62.6%) patients received postoperative local radio-oncologic and/or systemic therapy. Median postoperative EFS and OS were 7.1 (95%CI 5.8-8.2) and 11.1 (95%CI 8.4-13.6) months, respectively. The clinical status (postoperative KPS ≥ 70 (HR 0.27 95%CI 0.16-0.46; p < 0.001) remained the only independent factor for survival in multivariate analysis. CONCLUSIONS: Surgical resection of recurrent BM may improve the clinical status and thus OS but is associated with a high complication rate; therefore a very careful patient selection is crucial.
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Neoplasias Encefálicas , Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Radiocirurgia , Neoplasias Encefálicas/secundário , Carcinoma Pulmonar de Células não Pequenas/patologia , Humanos , Neoplasias Pulmonares/patologia , Estudos RetrospectivosRESUMO
BACKGROUND: In brain tumor surgery a personalized surgical approach is crucial to achieve a maximum safe tumor resection. The extent of resection decisively depends on the histological diagnosis. Stimulated Raman histology (SRH), a fiber laser-based optical imaging method, offers the possibility for evaluation of an intraoperative diagnosis in a few minutes. OBJECTIVE: To provide an overview on the applications of SRH in neurosurgery and transference of the technique to other surgical disciplines. METHODS: Description of the technique and review of the current literature on SRH. RESULTS: The SRH technique was successfully used in multiple neuro-oncological tumor entities. Initial pilot projects showed the potential for analysis of extracranial tumors. CONCLUSION: The use of SRH provides a near real-time diagnosis with high diagnostic accuracy and provides further developmental potential to improve personalized tumor surgery.
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Neoplasias Encefálicas , Neurocirurgia , Humanos , Procedimentos Neurocirúrgicos/métodos , Imagem Óptica , Técnicas Histológicas , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/cirurgiaRESUMO
PURPOSE: Recent artificial intelligence (AI) algorithms aided intraoperative decision-making via stimulated Raman histology (SRH) during craniotomy. This study assesses deep-learning algorithms for rapid intraoperative diagnosis from SRH images in small stereotactic-guided brain biopsies. It defines a minimum tissue sample size threshold to ensure diagnostic accuracy. EXPERIMENTAL DESIGN: A prospective single-center study examined 121 SRH images from 84 patients with unclear intracranial lesions undergoing stereotactic brain biopsy. Unprocessed, label-free samples were imaged with a portable fiber-laser Raman scattering microscope. Three deep-learning models were tested to (I) identify tumorous/non-tumorous tissue as qualitative biopsy control, (II) subclassify into high-grade glioma (CNS WHO grade 4), diffuse low-grade glioma (CNS WHO grade 2-3), metastases, lymphoma, or gliosis, and (III) molecularly subtype IDH- and 1p/19q-status of adult-type diffuse gliomas. Model predictions were evaluated against frozen section analysis and final neuropathological diagnoses. RESULTS: The first model identified tumorous/non-tumorous tissue with 91.7% accuracy. Sample size on slides impacted accuracy in brain tumor subclassification (81.6%, κ=0.72 frozen section; 73.9%, κ=0.61 second model), with SRH being smaller than H&E (4.1±2.5mm² vs 16.7±8.2mm², p<0.001). SRH images with over 140 high-quality patches and a mean squeezed sample of 5.26mm² yielded 89.5% accuracy in subclassification and 93.9% in molecular subtyping of adult-type diffuse gliomas. CONCLUSIONS: AI-based SRH image analysis is non-inferior to frozen section analysis in detecting and subclassifying brain tumors during small stereotactic-guided biopsies once a critical squeezed sample size is reached. Beyond frozen section analysis, it enables valid molecular glioma subtyping, allowing faster treatment decisions in the future. Refinement is needed for long-term application.
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Contrast-enhanced MRI is the method of choice for brain tumor diagnostics, despite its low specificity for tumor tissue. This study compared the contribution of MR spectroscopic imaging (MRSI) and amino acid PET to improve the detection of tumor tissue. Methods: In 30 untreated patients with suspected glioma, O-(2-[18F]fluoroethyl)-l-tyrosine (18F-FET) PET; 3-T MRSI with a short echo time; and fluid-attenuated inversion recovery, T2-weighted, and contrast-enhanced T1-weighted MRI were performed for stereotactic biopsy planning. Serial samples were taken along the needle trajectory, and their masks were projected to the preoperative imaging data. Each sample was individually evaluated neuropathologically. 18F-FET uptake and the MRSI signals choline (Cho), N-acetyl-aspartate (NAA), creatine, myoinositol, and derived ratios were evaluated for each sample and classified using logistic regression. The diagnostic accuracy was evaluated by receiver operating characteristic analysis. Results: On the basis of the neuropathologic evaluation of tissue from 88 stereotactic biopsies, supplemented with 18F-FET PET and MRSI metrics from 20 areas on the healthy-appearing contralateral hemisphere to balance the glioma/nonglioma groups, 18F-FET PET identified glioma with the highest accuracy (area under the receiver operating characteristic curve, 0.89; 95% CI, 0.81-0.93; threshold, 1.4 × background uptake). Among the MR spectroscopic metabolites, Cho/NAA normalized to normal brain tissue showed the highest diagnostic accuracy (area under the receiver operating characteristic curve, 0.81; 95% CI, 0.71-0.88; threshold, 2.2). The combination of 18F-FET PET and normalized Cho/NAA did not improve the diagnostic performance. Conclusion: MRI-based delineation of gliomas should preferably be supplemented by 18F-FET PET.
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Neoplasias Encefálicas , Glioma , Humanos , Imageamento por Ressonância Magnética/métodos , Glioma/diagnóstico por imagem , Glioma/metabolismo , Espectroscopia de Ressonância Magnética , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/patologia , Tomografia por Emissão de Pósitrons/métodos , Tirosina , BiópsiaRESUMO
Introduction: The intrinsic autofluorescence of biological tissues interferes with the detection of fluorophores administered for fluorescence guidance, an emerging auxiliary technique in oncological surgery. Yet, autofluorescence of the human brain and its neoplasia is sparsely examined. This study aims to assess autofluorescence of the brain and its neoplasia on a microscopic level by stimulated Raman histology (SRH) combined with two-photon fluorescence. Methods: With this experimentally established label-free microscopy technique unprocessed tissue can be imaged and analyzed within minutes and the process is easily incorporated in the surgical workflow. In a prospective observational study, we analyzed 397 SRH and corresponding autofluorescence images of 162 samples from 81 consecutive patients that underwent brain tumor surgery. Small tissue samples were squashed on a slide for imaging. SRH and fluorescence images were acquired with a dual wavelength laser (790 nm and 1020 nm) for excitation. In these images tumor and non-tumor regions were identified by a convolutional neural network that reliably differentiates between tumor, healthy brain tissue and low quality SRH images. The identified areas were used to define regions.of- interests (ROIs) and the mean fluorescence intensity was measured. Results: In healthy brain tissue, we found an increased mean autofluorescence signal in the gray (11.86, SD 2.61, n=29) compared to the white matter (5.99, SD 5.14, n=11, p<0.01) and in the cerebrum (11.83, SD 3.29, n=33) versus the cerebellum (2.82, SD 0.93, n=7, p<0.001), respectively. The signal of carcinoma metastases, meningiomas, gliomas and pituitary adenomas was significantly lower (each p<0.05) compared to the autofluorescence in the cerebrum and dura, and significantly higher (each p<0.05) compared to the cerebellum. Melanoma metastases were found to have a higher fluorescent signal (p<0.01) compared to cerebrum and cerebellum. Discussion: In conclusion we found that autofluorescence in the brain varies depending on the tissue type and localization and differs significantly among various brain tumors. This needs to be considered for interpreting photon signal during fluorescence-guided brain tumor surgery.
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OBJECTIVE: Current guidelines primarily suggest resection of brain metastases (BMs) in patients with limited lesions. With a growing number of highly effective local and systemic treatment options, this view may be challenged. The purpose of this study was to evaluate the role of metastasectomy, disregarding BM count, in a comprehensive treatment setting. METHODS: In this monocentric retrospective analysis, the authors included patients who underwent resection for at least 1 BM and collected demographic, clinical, and tumor-associated parameters. Prognostic factors for local control and overall survival (OS) were analyzed with the log-rank test and Cox proportional hazards analysis. RESULTS: The authors analyzed 216 patients. One hundred twenty-nine (59.7%) patients were diagnosed with a single/solitary BM, whereas 64 (29.6%) patients had 2-3 BMs and the remaining 23 (10.6%) had more than 3 BMs. With resection of symptomatic BMs, a significant improvement in Karnofsky Performance Scale (KPS) was achieved (p < 0.001), thereby enabling adjuvant radiotherapy for 199 (92.1%) patients and systemic treatment for 119 (55.1%) patients. During follow-up, 83 (38.4%) patients experienced local recurrence. BM count did not significantly influence local control rates. By the time of analysis, 120 (55.6%) patients had died; the leading cause of death was systemic tumor progression. The mean (range) OS after surgery was 12.7 (0-88) months. In univariate analysis, the BM count did not influence OS (p = 0.844), but age < 65 years (p = 0.007), preoperative and postoperative KPS ≥ 70 (p = 0.002 and p = 0.005, respectively), systemic metastases other than BM (p = 0.004), adjuvant radiation therapy (p < 0.001), and adjuvant systemic treatment (p < 0.001) were prognostic factors. In regression analysis, the presence of extracranial metastases (HR 2.30, 95% CI 1.53-3.48, p < 0.001), adjuvant radiation therapy (HR 0.97, 95% CI 0.23-0.86, p = 0.016), and adjuvant systemic treatment (HR 0.37, 95% CI 0.25-0.55, p < 0.001) remained as independent factors for survival. CONCLUSIONS: Surgery for symptomatic BM from non-small cell lung cancer may be indicated even for patients with multiple lesions in order to alleviate their neurological symptoms and to consequently facilitate further treatment.
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Currently, contrast-enhanced MRI is the method of choice for treatment planning and follow-up in patients with meningioma. However, positron emission tomography (PET) imaging of somatostatin receptor subtype 2 (SSTR2) expression using 68Ga-DOTATATE may provide a higher sensitivity for meningioma detection, especially in cases with complex anatomy or in the recurrent setting. Here, we report on a patient with a multilocal recurrent atypical meningioma, in which 68Ga-DOTATATE PET was considerably helpful for treatment guidance and decision-making.
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BACKGROUND: The BRAF V600E mutation is present in approximately 50% of patients with melanoma brain metastases and an important prerequisite for response to targeted therapies, particularly BRAF inhibitors. As heterogeneity in terms of BRAF mutation status may occur in melanoma patients, a wild-type extracranial primary tumor does not necessarily rule out a targetable mutation in brain metastases using BRAF inhibitors. We evaluated the potential of MRI radiomics for a noninvasive prediction of the intracranial BRAF mutation status. METHODS: Fifty-nine patients with melanoma brain metastases from two university brain tumor centers (group 1, 45 patients; group 2, 14 patients) underwent tumor resection with subsequent genetic analysis of the intracranial BRAF mutation status. Preoperative contrast-enhanced MRI was manually segmented and analyzed. Group 1 was used for model training and validation, group 2 for model testing. After radiomics feature extraction, a test-retest analysis was performed to identify robust features prior to feature selection. Finally, the best performing radiomics model was applied to the test data. Diagnostic performances were evaluated using receiver operating characteristic (ROC) analyses. RESULTS: Twenty-two of 45 patients (49%) in group 1, and 8 of 14 patients (57%) in group 2 had an intracranial BRAF V600E mutation. A linear support vector machine classifier using a six-parameter radiomics signature yielded an area under the ROC curve of 0.92 (sensitivity, 83%; specificity, 88%) in the test data. CONCLUSIONS: The developed radiomics classifier allows a noninvasive prediction of the intracranial BRAF V600E mutation status in patients with melanoma brain metastases with high diagnostic performance.
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Neoplasias Encefálicas , Melanoma , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/secundário , Humanos , Imageamento por Ressonância Magnética , Melanoma/genética , Melanoma/patologia , Mutação , Proteínas Proto-Oncogênicas B-raf/genética , Estudos RetrospectivosRESUMO
While immune checkpoint inhibitors (ICIs) in combination with radiotherapy (RT) are widely used for patients with brain metastasis (BM), markers that predict treatment response for combined RT and ICI (RT-ICI) and their optimal dosing and sequence for the best immunogenic effects are still under investigation. The aim of this study was to evaluate prognostic factors for therapeutic outcome and to compare effects of concurrent and non-concurrent RT-ICI. We retrospectively analyzed data of 93 patients with 319 BMs of different cancer types who received PD-1 inhibitors and RT at the University Hospital Cologne between September/2014 and November/2020. Primary study endpoints were overall survival (OS), progression-free survival (PFS), and local control (LC). We included 66.7% melanoma, 22.8% lung, and 5.5% other cancer types with a mean follow-up time of 23.8 months. Median OS time was 12.19 months. LC at 6 months was 95.3% (concurrent) vs. 69.2% (non-concurrent; p = 0.008). Univariate Cox regression analysis detected following prognostic factors for OS: neutrophil-to-lymphocyte ratio NLR favoring <3 (low; HR 2.037 (1.184−3.506), p = 0.010), lactate dehydrogenase (LDH) favoring ≤ULN (HR 1.853 (1.059−3.241), p = 0.031), absence of neurological symptoms (HR 2.114 (1.285−3.478), p = 0.003), RT concept favoring SRS (HR 1.985 (1.112−3.543), p = 0.019), RT dose favoring ≥60 Gy (HR 0.519 (0.309−0.871), p = 0.013), and prior anti-CTLA4 treatment (HR 0.498 (0.271−0.914), p = 0.024). Independent prognostic factors for OS were concurrent RT-ICI application (HR 0.539 (0.299−0.971), p = 0.024) with a median OS of 17.61 vs. 6.83 months (non-concurrent), ECOG performance status favoring 0 (HR 7.756 (1.253−6.061), p = 0.012), cancer type favoring melanoma (HR 0.516 (0.288−0.926), p = 0.026), BM volume (PTV) favoring ≤3 cm3 (HR 1.947 (1.007−3.763), p = 0.048). Subgroups with the following factors showed significantly longer OS when being treated concurrently: RT dose <60 Gy (p = 0.014), PTV > 3 cm3 (p = 0.007), other cancer types than melanoma (p = 0.006), anti-CTLA4-naïve patients (p < 0.001), low NLR (p = 0.039), steroid intake ≤4 mg (p = 0.042). Specific immune responses, such as abscopal effects (AbEs), pseudoprogression (PsP), or immune-related adverse events (IrAEs), occurred more frequently with concurrent RT-ICI and resulted in better OS. Other toxicities, including radionecrosis, were not statistically different in both groups. The concurrent application of RT and ICI, the ECOG-PS, cancer type, and PTV had an independently prognostic impact on OS. In concurrently treated patients, treatment response (LC) was delayed and specific immune responses (AbE, PsP, IrAE) occurred more frequently with longer OS rates. Our results suggest that concurrent RT-ICI application is more beneficial than sequential treatment in patients with low pretreatment inflammatory status, more and larger BMs, and with other cancer types than melanoma.
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OBJECTIVE: The treatment of symptomatic, progressive or recurrent acquired intracerebral cysts is challenging, especially when they are localized in eloquent structures. In addition to resection, endoscopic fenestration, or stereotactic puncture, the implantation of a cystoventricular shunt by stereotactic guidance (SCVS) has been reported as a minimally invasive procedure; however, only scarce data are available regarding its feasibility and efficacy. Here, the authors evaluated the feasibility and efficacy of frame-based SCVS in patients with acquired intracranial cysts. METHODS: In this single-center retrospective analysis, the authors included all patients with acquired intracerebral cysts treated by SCVS following a standardized prospective protocol between 2012 and 2020. They analyzed clinical symptoms, complications, and radiological outcome with regard to cyst volume reduction by 3D volumetry. RESULTS: Thirty-four patients (17 females and 17 males; median age 44 years, range 5-77 years) were identified. The median initial cyst volume was 11.5 cm3 (range 1.6-71.6 cm3), and the mean follow-up was 20 months (range 1-82 months). At the last follow-up, 27 of 34 patients (79%) showed a cyst volume reduction of more than 50%. Initial symptoms improved or resolved in 74% (n = 25) and remained stable in 24% (n = 8). No permanent clinical deterioration after treatment was observed. The total complication rate was 5.9%, comprising transient neurological deterioration (n = 1) and ventriculitis (n = 1). There were no deaths. The overall recurrence rate was 11.8%. CONCLUSIONS: In this study, SCVS proved to be a safe, minimally invasive, and effective treatment with reliable long-term volume reduction, resulting in clinical improvement and a minor complication rate.
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Radiomics allows the extraction of quantitative features from medical images such as CT, MRI, or PET, thereby providing additional, potentially relevant diagnostic information for clinical decision-making. Because the computation of these features is performed highly automated on medical images acquired during routine follow-up, radiomics offers this information at low cost. Further, the radiomics features can be used alone or combined with other clinical or histomolecular parameters to generate predictive or prognostic mathematical models. These models can then be applied for various important diagnostic indications in neuro-oncology, for example, to noninvasively predict relevant biomarkers in glioma patients, to differentiate between treatment-related changes and local brain tumor relapse, or to predict treatment response. In recent years, amino acid PET has become an important diagnostic tool in patients with brain tumors. Therefore, the number of studies in patients with brain tumors investigating the potential of PET radiomics or combined PET/MRI radiomics is steadily increasing. This review summarizes current research regarding feature-based PET as well as combined PET/MRI radiomics in neuro-oncology.