Entirely noninvasive outcome prediction in central nervous system lymphomas using circulating tumor DNA.

ABSTRACT: State-of-the-art response assessment of central nervous system lymphoma (CNSL) by magnetic resonance imaging is challenging and an insufficient predictor of treatment outcomes. Accordingly, the development of novel risk stratification strategies in CNSL is a high unmet medical need. We applied ultrasensitive circulating tumor DNA (ctDNA) sequencing to 146 plasma and cerebrospinal fluid (CSF) samples from 67 patients, aiming to develop an entirely noninvasive dynamic risk model considering clinical and molecular features of CNSL. Our ultrasensitive method allowed for the detection of CNSL-derived mutations in plasma ctDNA with high concordance to CSF and tumor tissue. Undetectable plasma ctDNA at baseline was associated with favorable outcomes. We tracked tumor-specific mutations in plasma-derived ctDNA over time and developed a novel CNSL biomarker based on this information: peripheral residual disease (PRD). Persistence of PRD after treatment was highly predictive of relapse. Integrating established baseline clinical risk factors with assessment of radiographic response and PRD during treatment resulted in the development and independent validation of a novel tool for risk stratification: molecular prognostic index for CNSL (MOP-C). MOP-C proved to be highly predictive of outcomes in patients with CNSL (failure-free survival hazard ratio per risk group of 6.60; 95% confidence interval, 3.12-13.97; P < .0001) and is publicly available at www.mop-c.com. Our results highlight the role of ctDNA sequencing in CNSL. MOP-C has the potential to improve the current standard of clinical risk stratification and radiographic response assessment in patients with CNSL, ultimately paving the way toward individualized treatment.

Stereotactic radiosurgery and radiotherapy for brainstem metastases: An international multicenter analysis.

Brainstem metastases (BSM) present a significant neuro-oncological challenge, resulting in profound neurological deficits and poor survival outcomes. Stereotactic radiosurgery (SRS) and fractionated stereotactic radiotherapy (FSRT) offer promising therapeutic avenues for BSM despite their precarious location. This international multicenter study investigates the efficacy and safety of SRS and FSRT in 136 patients with 144 BSM treated at nine institutions from 2005 to 2022. The median radiographic and clinical follow-up periods were 6.8 and 9.4 months, respectively. Predominantly, patients with BSM were managed with SRS (69.4%). The median prescription dose and isodose line for SRS were 18 Gy and 65%, respectively, while for FSRT, the median prescription dose was 21 Gy with a median isodose line of 70%. The 12-, 24-, and 36-month local control (LC) rates were 82.9%, 71.4%, and 61.2%, respectively. Corresponding overall survival rates at these time points were 61.1%, 34.7%, and 19.3%. In the multivariable Cox regression analysis for LC, only the minimum biologically effective dose was significantly associated with LC, favoring higher doses for improved control (in Gy, hazard ratio [HR]: 0.86, p < .01). Regarding overall survival, good performance status (Karnofsky performance status, ≥90%; HR: 0.43, p < .01) and prior whole brain radiotherapy (HR: 2.52, p < .01) emerged as associated factors. In 14 BSM (9.7%), treatment-related adverse events were noted, with a total of five (3.4%) radiation necrosis. SRS and FSRT for BSM exhibit efficacy and safety, making them suitable treatment options for affected patients.

Quality requirements for MRI simulation in cranial stereotactic radiotherapy: a guideline from the German Taskforce "Imaging in Stereotactic Radiotherapy".

Accurate Magnetic Resonance Imaging (MRI) simulation is fundamental for high-precision stereotactic radiosurgery and fractionated stereotactic radiotherapy, collectively referred to as stereotactic radiotherapy (SRT), to deliver doses of high biological effectiveness to well-defined cranial targets. Multiple MRI hardware related factors as well as scanner configuration and sequence protocol parameters can affect the imaging accuracy and need to be optimized for the special purpose of radiotherapy treatment planning. MRI simulation for SRT is possible for different organizational environments including patient referral for imaging as well as dedicated MRI simulation in the radiotherapy department but require radiotherapy-optimized MRI protocols and defined quality standards to ensure geometrically accurate images that form an impeccable foundation for treatment planning. For this guideline, an interdisciplinary panel including experts from the working group for radiosurgery and stereotactic radiotherapy of the German Society for Radiation Oncology (DEGRO), the working group for physics and technology in stereotactic radiotherapy of the German Society for Medical Physics (DGMP), the German Society of Neurosurgery (DGNC), the German Society of Neuroradiology (DGNR) and the German Chapter of the International Society for Magnetic Resonance in Medicine (DS-ISMRM) have defined minimum MRI quality requirements as well as advanced MRI simulation options for cranial SRT.

The impact of brain lesions on health-related quality of life in patients with WHO CNS grade 3 or 4 glioma: a lesion-function and resting-state fMRI analysis.

PURPOSE: In glioma patients, tumor development and multimodality therapy are associated with changes in health-related quality of life (HRQoL). It is largely unknown how different types and locations of tumor- and treatment-related brain lesions, as well as their relationship to white matter tracts and functional brain networks, affect HRQoL. METHODS: In 121 patients with pretreated gliomas of WHO CNS grades 3 or 4, structural MRI, O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET, resting-state functional MRI (rs-fMRI) and self-reported HRQoL questionnaires (EORTC QLQ-C30/BN20) were obtained. Resection cavities, T1-enhancing lesions, T2/FLAIR hyperintensities, and lesions with pathologically increased FET uptake were delineated. Effects of tumor lateralization, involvement of white matter tracts or resting-state network nodes by different types of lesions and within-network rs-fMRI connectivity were analyzed in terms of their interaction with HRQoL scores. RESULTS: Right hemisphere gliomas were associated with significantly less favorable outcomes in physical, role, emotional and social functioning, compared with left-sided tumors. Most functional HRQoL scores correlated significantly with right-sided white-matter tracts involvement by T2/FLAIR hyperintensities and with loss of within-network functional connectivity of right-sided nodes. Tumors of the left hemisphere caused significantly more communication deficits. CONCLUSION: In pretreated high-grade gliomas, right hemisphere lesions are associated with reduced HRQoL scores in most functional domains except communication ability, compared to tumors of the left hemisphere. These relationships are mainly observed for T2/FLAIR lesions involving structural and functional networks in the right hemisphere. The data suggest that sparing the right hemisphere from treatment-related tissue damage may improve HRQoL in glioma patients.

Radiomics for the non-invasive prediction of PD-L1 expression in patients with brain metastases secondary to non-small cell lung cancer.

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.

Primary Central Nervous System Lymphoma: Clinical Evaluation of Automated Segmentation on Multiparametric MRI Using Deep Learning.

BACKGROUND: Precise volumetric assessment of brain tumors is relevant for treatment planning and monitoring. However, manual segmentations are time-consuming and impeded by intra- and interrater variabilities. PURPOSE: To investigate the performance of a deep-learning model (DLM) to automatically detect and segment primary central nervous system lymphoma (PCNSL) on clinical MRI. STUDY TYPE: Retrospective. POPULATION: Sixty-nine scans (at initial and/or follow-up imaging) from 43 patients with PCNSL referred for clinical MRI tumor assessment. FIELD STRENGTH/SEQUENCE: T1 -/T2 -weighted, T1 -weighted contrast-enhanced (T1 CE), and FLAIR at 1.0, 1.5, and 3.0T from different vendors and study centers. ASSESSMENT: Fully automated voxelwise segmentation of tumor components was performed using a 3D convolutional neural network (DeepMedic) trained on gliomas (n = 220). DLM segmentations were compared to manual segmentations performed in a 3D voxelwise manner by two readers (radiologist and neurosurgeon; consensus reading) from T1 CE and FLAIR, which served as the reference standard. STATISTICAL TESTS: Dice similarity coefficient (DSC) for comparison of spatial overlap with the reference standard, Pearson's correlation coefficient (r) to assess the relationship between volumetric measurements of segmentations, and Wilcoxon rank-sum test for comparison of DSCs obtained in initial and follow-up imaging. RESULTS: The DLM detected 66 of 69 PCNSL, representing a sensitivity of 95.7%. Compared to the reference standard, DLM achieved good spatial overlap for total tumor volume (TTV, union of tumor volume in T1 CE and FLAIR; average size 77.16 ± 62.4 cm3 , median DSC: 0.76) and tumor core (contrast enhancing tumor in T1 CE; average size: 11.67 ± 13.88 cm3 , median DSC: 0.73). High volumetric correlation between automated and manual segmentations was observed (TTV: r = 0.88, P < 0.0001; core: r = 0.86, P < 0.0001). Performance of automated segmentations was comparable between pretreatment and follow-up scans without significant differences (TTV: P = 0.242, core: P = 0.177). DATA CONCLUSION: In clinical MRI scans, a DLM initially trained on gliomas provides segmentation of PCNSL comparable to manual segmentation, despite its complex and multifaceted appearance. Segmentation performance was high in both initial and follow-up scans, suggesting its potential for application in longitudinal tumor imaging. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Applications of radiomics and machine learning for radiotherapy of malignant brain tumors.

BACKGROUND: Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can be analyzed by machine learning algorithms and radiomics for the use of radiotherapy in patients with malignant brain tumors. METHODS: This study is based on comprehensive literature research on machine learning and radiomics analyses in neuroimaging and their potential application for radiotherapy in patients with malignant glioma or brain metastases. RESULTS: Feature-based radiomics and deep learning-based machine learning methods can be used to improve brain tumor diagnostics and automate various steps of radiotherapy planning. In glioma patients, important applications are the determination of WHO grade and molecular markers for integrated diagnosis in patients not eligible for biopsy or resection, automatic image segmentation for target volume planning, prediction of the location of tumor recurrence, and differentiation of pseudoprogression from actual tumor progression. In patients with brain metastases, radiomics is applied for additional detection of smaller brain metastases, accurate segmentation of multiple larger metastases, prediction of local response after radiosurgery, and differentiation of radiation injury from local brain metastasis relapse. Importantly, high diagnostic accuracies of 80-90% can be achieved by most approaches, despite a large variety in terms of applied imaging techniques and computational methods. CONCLUSION: Clinical application of automated image analyses based on radiomics and artificial intelligence has a great potential for improving radiotherapy in patients with malignant brain tumors. However, a common problem associated with these techniques is the large variability and the lack of standardization of the methods applied.

Observation after surgery for low grade glioma: long-term outcome in the light of the 2016 WHO classification.

PURPOSE: To provide detailed long-term data after initial observation for patients after histological confirmation of low grade (WHO II) gliomas according to molecular stratification. METHODS: A series of 110 patients with watchful waiting strategy after initial surgery for LGG and re-surgery at tumor progression were analyzed. Progression-free survival, time to malignant transformation, post-recurrence survival, and overall survival were estimated with the Kaplan-Meier method. Prognostic factors were identified by the Log Rank test and Cox multivariate proportional hazards model. RESULTS: The cohort comprised 18 IDH wild type (IDHwt) and 53 IDH mutated (IDHmut) astrocytomas, and 39 IDH mutated and 1p 19q co-deleted (IDHmut/codel) patients. The median follow-up was 126 (95% CI 109-143) months. Surgery was gross total resection in 58, subtotal resection in 28, and biopsy in 24 patients. Progression-free survival rates at 5, 10 and 15 years was 38% 18% and 1%. The corresponding malignant transformation rates were 17%, 39% and 71%. The initial extent of resection influenced progression-free survival, time to malignant transformation and overall survival. Molecular subtype IDHmut/codel was the strongest prognostic factor for overall survival and for time to malignant transformation. CONCLUSION: The strongest determinant of the patients' course after initial watchful waiting was the molecular tumor status. Extensive resection may increase time to progression and malignant transformation. Observation may be justified in selected patients.

Frame-based stereotactic biopsy of deep-seated and midline structures in 511 procedures: feasibility, risk profile, and diagnostic yield.

OBJECTIVES: We evaluated the feasibility, safety, and diagnostic yield of frame-based stereotactic biopsies (SB) in lesions located in deep-seated and midline structures of the brain to analyze these parameters in comparison to other brain areas. PATIENTS AND METHODS: In a retrospective, tertiary care single-center analysis, we identified all patients who received SB for lesions localized in deep-seated and midline structures (corpus callosum, basal ganglia, pineal region, sella, thalamus, and brainstem) between January 1996 and June 2015. Study participants were between 1 and 82 years. We evaluated the feasibility, procedural complications (mortality, transient and permanent morbidity), and diagnostic yield. We further performed a risk analysis of factors influencing the latter parameters. Chi-square test, Student t test, and Mann-Whitney rank-sum test were used for statistical analysis. RESULTS: Four hundred eighty-nine patients receiving 511 SB procedures (median age 48.5 years, range 1-82; median Karnofsky Performance Score 80%, range 50-100%, 43.8% female/56.2% male) were identified. Lesions were localized in the corpus callosum (29.5%), basal ganglia (17.0%), pineal region (11.5%), sella (7.8%), thalamus (4.3%), brainstem (28.8%), and others (1.1%). Procedure-related mortality was 0%, and permanent morbidity was 0.4%. Transient morbidity was 9.6%. Histological diagnosis was possible in 99.2% (low-grade gliomas 16.2%, high-grade gliomas 40.3%, other tumors in 27.8%, no neoplastic lesions 14.5%, no definitive histological diagnosis 0.8%). Only the pons location correlated significantly with transient morbidity (p < 0.001). CONCLUSION: In experienced centers, frame-based stereotactic biopsy is a safe diagnostic tool with a high diagnostic yield also for deep-seated and midline lesions.

Robotic Stereotactic Radiosurgery in Melanoma Patients with Brain Metastases under Simultaneous Anti-PD-1 Treatment.

Combination concepts of radiotherapy and immune checkpoint inhibition are currently of high interest. We examined imaging findings, acute toxicity, and local control in patients with melanoma brain metastases receiving programmed death 1 (PD-1) inhibitors and/or robotic stereotactic radiosurgery (SRS). Twenty-six patients treated with SRS alone (n = 13; 20 lesions) or in combination with anti-PD-1 therapy (n = 13; 28 lesions) were analyzed. Lesion size was evaluated three and six months after SRS using a volumetric assessment based on cranial magnetic resonance imaging (cMRI) and acute toxicity after 12 weeks according to the Common Terminology Criteria for Adverse Events (CTCAE). Local control after six months was comparable (86%, SRS + anti-PD-1, and 80%, SRS). All toxicities reported were less than or equal to grade 2. One metastasis (5%) in the SRS group and six (21%) in the SRS + anti-PD-1 group increased after three months, whereas four (14%) of the six regressed during further follow-ups. This was rated as pseudoprogression (PsP). Three patients (23%) in the SRS + anti-PD-1 group showed characteristics of PsP. Treatment with SRS and anti-PD-1 antibodies can be combined safely in melanoma patients with cerebral metastases. Early volumetric progression of lesions under simultaneous treatment may be related to PsP; thus, the evaluation of combined radioimmunotherapy remains challenging and requires experienced teams.

Stereotactic biopsy in elderly patients: risk assessment and impact on treatment decision.

To evaluate risk profile, diagnostic yield and impact on treatment decision of stereotactic biopsy (SB) in elderly patients with unclear cerebral lesions. In this single center retrospective analysis we identified all patients aged ≥70 years receiving SB between January 2005 and December 2015. Demographic data, Karnofsky Performance Status (KPS), histology, comorbidity (by CHA2DS2-VASc Score) and use of anticoagulation were retrieved. We scrutinized diagnostic yield, procedural complications (mortality, transient and permanent morbidity), hospitalization time and therapeutic consequence. For correlation analysis Chi-Square, Mann-Whitney rank sum test and binary regression were used. Two hundred and thirty patients were included. In 229 patients SB was technically successful. Median age was 74 (70-87) years, 56.1% of patients were male and median preoperative KPS was 80% (30-100). Median CHA2DS2-VASc Score was 4 (1-9), with 29.6% receiving anticoagulation. Median hospital stay was 8 (2-29) days. Pathological diagnosis was conclusive in 97% revealing neoplastic lesions in 91.7% (high-grade glioma 62.6%, lymphoma 18.3%, metastasis 4.8%, low-grade glioma 3.0% and other tumors 3.0%) and non-neoplastic lesions in 5.3% of cases. Procedure-related mortality was 0.4%, transient and permanent morbidity occurred in 19 patients (8.3%) and eight patients (3.5%). Complication rate was not associated with any of the above-mentioned parameters. Adjuvant therapy was initiated in 171 (74.3%) patients. Decision against disease-specific therapy was only influenced by preoperative KPS (p < 0.001). SB in elderly patients is characterized by a favorable risk profile and high diagnostic yield, allowing tissue based therapeutic consequences even in patients with high comorbidity and anticoagulant medication.

Feasibility, Risk Profile and Diagnostic Yield of Stereotactic Biopsy in Children and Young Adults with Brain Lesions.

Objective To evaluate the feasibility, safety, and diagnostic yield of stereotactic biopsy (SB) in children and adolescents with cerebral lesions. Methods We performed a systematic review of the literature and a retrospective analysis of all pediatric and adolescent patients who underwent SB for unclear brain lesions at our center. We collected patient and lesion-associated parameters, analysed the rate of procedural complications and diagnostic yield. Results Our institutional series consisted of 285 SBs in 269 children and young adults between 1989 and 2016 (median age, 9 (range 1-18) years). There was no procedure-related mortality. Permanent and transient morbidity was 0.7% and 5.8%, respectively. Lesions were located in brain lobes (26.3%) and in midline structures (73.7%). The diagnostic yield was 97.5% and histology consisted low-grade gliomas (44.2%), high-grade gliomas (15.1%), non-glial tumors (22.8%), and non-neoplastic disease (15.4%). Morbidity was not associated with tumor location, age, histology or intraoperative position of the patient. In order to compare our findings with previous reports, we reviewed 25 studies with 1 109 children and young adults which had underwent SB. The diagnostic yield ranged between 83% and 100%. The reported morbidity and mortality rates range from 0-27% and 0-3.3%, respectively. Conclusions SB in this particular patient population is a safe and a high-yield diagnostic procedure and indicates therefore its importance in the light of personalized medicine with the development of individual molecular treatment strategies.

Diagnosis of pseudoprogression in patients with glioblastoma using O-(2-[18F]fluoroethyl)-L-tyrosine PET.

PURPOSE: The follow-up of glioblastoma patients after radiochemotherapy with conventional MRI can be difficult since reactive alterations to the blood-brain barrier with contrast enhancement may mimic tumour progression (i.e. pseudoprogression, PsP). The aim of this study was to assess the clinical value of O-(2-(18)F-fluoroethyl)-L-tyrosine ((18)F-FET) PET in the differentiation of PsP and early tumour progression (EP) after radiochemotherapy of glioblastoma. METHODS: A group of 22 glioblastoma patients with new contrast-enhancing lesions or lesions showing increased enhancement (>25 %) on standard MRI within the first 12 weeks after completion of radiochemotherapy with concomitant temozolomide (median 7 weeks) were additionally examined using amino acid PET with (18)F-FET. Maximum and mean tumour-to-brain ratios (TBRmax, TBRmean) were determined. (18)F-FET uptake kinetic parameters (i.e. patterns of time-activity curves, TAC) were also evaluated. Classification as PsP or EP was based on the clinical course (no treatment change at least for 6 months), follow-up MR imaging and/or histopathological findings. Imaging results were also related to overall survival (OS). RESULTS: PsP was confirmed in 11 of the 22 patients. In patients with PsP, (18)F-FET uptake was significantly lower than in patients with EP (TBRmax 1.9 ± 0.4 vs. 2.8 ± 0.5, TBRmean 1.8 ± 0.2 vs. 2.3 ± 0.3; both P < 0.001) and presence of MGMT promoter methylation was significantly more frequent (P = 0.05). Furthermore, a TAC type II or III was more frequently present in patients with EP (P = 0.04). Receiver operating characteristic analysis showed that the optimal (18)F-FET TBRmax cut-off value for identifying PsP was 2.3 (sensitivity 100 %, specificity 91 %, accuracy 96 %, AUC 0.94 ± 0.06; P < 0.001). Univariate survival analysis showed that a TBRmax <2.3 predicted a significantly longer OS (median OS 23 vs. 12 months; P = 0.046). CONCLUSION: (18)F-FET PET may facilitate the diagnosis of PsP following radiochemotherapy of glioblastoma.

Long-term Functional Recovery and Quality of Life after Surgical Treatment of Putaminal Hemorrhages.

BACKGROUND: To evaluate the long-term functional recovery and health-related quality of life (HRQOL) in patients after surgically treated putaminal hemorrhages. Surgery for putaminal hemorrhages remains a controversial issue. Although numerous reports describe conflictive results regarding short-term outcome of surgically treated patients, very little is known about their long-term recovery and their HRQOL. METHODS: In this monocentric, retrospective study we analyzed mortality, long-term functional outcome, activity of daily life status, and HRQOL undergoing craniotomy for hematoma evacuation between December 2004 and January 2011. RESULTS: Forty-nine consecutive patients were identified with 8 (16.3%) patients dying during acute care. Forty-one patients surviving acute phase were transferred to neurologic rehabilitation hospitals. One patient was lost to follow-up. Median follow-up was 52.9 (17-101) months. At follow-up, 24 of 40 (60%) patients still were alive with 16 of 40 (40%) patients living with major disability (modified Rankin Scale [mRS], 4 or 5). Seven patients (17.5%) showed a mRS lesser than or equal to 3 with only 3 (7.5%) of those living functionally independent (mRS, 0-2). HRQOL in survivors was reduced with a median DEMQOL/DEMQOL (a patient/caregiver reported outcome measure designed to assess health-related quality of life of people with dementia) proxy score of 92 and 93, respectively. All patients showed severe impairment in activities of daily life. CONCLUSIONS: This is the first long-term follow-up analysis for patients with surgically treated putaminal hemorrhages. Survivors show only marginal recovery despite intensive neurologic rehabilitation; most remain dependent with a reduced HRQOL and significantly impaired activities of daily life status.

Low-dose rate stereotactic iodine-125 brachytherapy for the treatment of inoperable primary and recurrent glioblastoma: single-center experience with 201 cases.

Treatment options for inoperable glioblastoma are limited. Low-dose-rate stereotactic iodine-125 brachytherapy (SBT) has been reported as an effective and low-risk treatment option for circumscribed low-grade gliomas and brain metastases. The present study evaluates this treatment approach for patients with inoperable glioblastoma. Between 1990 and 2012, 201 patients with histologically proven glioblastoma were treated with SBT (iodine-125 seeds; median cumulative surface dose, 60 Gy; median dose-rate, 6 cGy/h; median gross-tumor-volume, 17 ml) either as primary treatment (n = 103) or at recurrence (n = 98). In addition to SBT, 90.3 % of patients in the primary treatment group received external boost radiotherapy (median dose, 25.2 Gy). Adjuvant chemotherapy was added for 30.8 % of patients following SBT and consisted of temozolomide for the majority of cases (88.7 %). Procedure-related complications, clinical outcome, progression-free and overall survival (PFS, OS) were evaluated. Median follow-up was 9.8 months. The procedure-related mortality was zero. During follow-up, transient and permanent procedure-related morbidity was observed in 7.5 and 2.0 %, respectively. Calculated from the time of SBT, median OS and PFS rates were 10.5 and 6.2 months, with no significant differences among primary and recurrent tumors (11.1 vs.10.4 months for OS and 6.2 vs. 5.9 months for PFS). For OS, multivariate analysis revealed Karnofsky performance score, age, and adjuvant chemotherapy as independent prognostic factors (all p < 0.01). Low-dose-rate SBT is a relatively safe and potentially effective local treatment option for patients with circumscribed inoperable glioblastoma initially or at recurrence. It deserves prospective validation since it may improve the outcome for a subset of patients with inoperable GBM.

Accuracy of robotic radiosurgery in renal cell carcinoma.

PURPOSE: Although emerging clinical evidence supports robotic radiosurgery as a highly effective treatment option for renal cell carcinoma (RCC) less than 4 cm in diameter, delivery uncertainties and associated target volume margins have not been studied in detail. We assess intrafraction tumor motion patterns and accuracy of robotic radiosurgery in renal tumors with real-time respiratory tracking to optimize treatment margins. METHODS: Delivery log files from 165 consecutive treatments of RCC were retrospectively analyzed. Five components were considered for planning target volume (PTV) margin estimation: (a) The model error from the correlation model between patient breath and tumor motion, (b) the prediction error from an algorithm predicting the patient breathing pattern, (c) the targeting error from the treatment robot, (d) the inherent total accuracy of the system for respiratory motion tracking, and (e) the margin required to cover potential target rotation, simulated with PTV rotations up to 10°. RESULTS: The median tumor motion was 10.5 mm, 2.4 mm and 4.4 mm in the superior-inferior, left-right, and anterior-posterior directions, respectively. The root of the sum of squares of all contributions to the system's inaccuracy results in a minimum PTV margin of 4.3 mm, 2.6 mm and 3.0 mm in the superior-inferior, left-right and anterior-posterior directions, respectively, assuming optimal fiducial position and neglecting target deformation. CONCLUSIONS: We have assessed kidney motion and derived PTV margins for the treatment of RCC with robotic radiosurgery, which helps to deliver renal treatments in a more consistent manner and potentially further improve outcomes.

Streamlined Intraoperative Brain Tumor Classification and Molecular Subtyping in Stereotactic Biopsies Using Stimulated Raman Histology and Deep Learning.

PURPOSE: Recent artificial intelligence 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 using a portable fiber laser Raman scattering microscope. Three deep learning models were tested to (i) identify tumorous/nontumorous tissue as qualitative biopsy control; (ii) subclassify into high-grade glioma (central nervous system World Health Organization grade 4), diffuse low-grade glioma (central nervous system World Health Organization grades 2-3), metastases, lymphoma, or gliosis; and (iii) molecularly subtype IDH and 1p/19q statuses of adult-type diffuse gliomas. Model predictions were evaluated against frozen section analysis and final neuropathologic diagnoses. RESULTS: The first model identified tumorous/nontumorous 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 images being smaller than hematoxylin and eosin images (4.1 ± 2.5 mm2 vs. 16.7 ± 8.2 mm2, P < 0.001). SRH images with more than 140 high-quality patches and a mean squeezed sample of 5.26 mm2 yielded 89.5% accuracy in subclassification and 93.9% in molecular subtyping of adult-type diffuse gliomas. CONCLUSIONS: Artificial intelligence-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; however, refinement is needed for long-term application.

Structural connectome-based predictive modeling of cognitive deficits in treated glioma patients.

Background: In glioma patients, tumor growth and subsequent treatments are associated with various types of brain lesions. We hypothesized that cognitive functioning in these patients critically depends on the maintained structural connectivity of multiple brain networks. Methods: The study included 121 glioma patients (median age, 52 years; median Eastern Cooperative Oncology Group performance score 1; CNS-WHO Grade 3 or 4) after multimodal therapy. Cognitive performance was assessed by 10 tests in 5 cognitive domains at a median of 14 months after treatment initiation. Hybrid amino acid PET/MRI using the tracer O-(2-[18F]fluoroethyl)-L-tyrosine, a network-based cortical parcellation, and advanced tractography were used to generate whole-brain fiber count-weighted connectivity matrices. The matrices were applied to a cross-validated machine-learning model to identify predictive fiber connections (edges), critical cortical regions (nodes), and the networks underlying cognitive performance. Results: Compared to healthy controls (n = 121), patients' cognitive scores were significantly lower in 9 cognitive tests. The models predicted the scores of 7/10 tests (median correlation coefficient, 0.47; range, 0.39-0.57) from 0.6% to 5.4% of the matrix entries; 84% of the predictive edges were between nodes of different networks. Critically involved cortical regions (≥10 adjacent edges) included predominantly left-sided nodes of the visual, somatomotor, dorsal/ventral attention, and default mode networks. Highly critical nodes (≥15 edges) included the default mode network's left temporal and bilateral posterior cingulate cortex. Conclusions: These results suggest that the cognitive performance of pretreated glioma patients is strongly related to structural connectivity between multiple brain networks and depends on the integrity of known network hubs also involved in other neurological disorders.

Fast intraoperative detection of primary CNS lymphoma and differentiation from common CNS tumors using stimulated Raman histology and deep learning.

Accurate intraoperative diagnosis is crucial for differentiating between primary CNS lymphoma (PCNSL) and other CNS entities, guiding surgical decision-making, but represents significant challenges due to overlapping histomorphological features, time constraints, and differing treatment strategies. We combined stimulated Raman histology (SRH) with deep learning to address this challenge. We imaged unprocessed, label-free tissue samples intraoperatively using a portable Raman scattering microscope, generating virtual H&E-like images within less than three minutes. We developed a deep learning pipeline called RapidLymphoma based on a self-supervised learning strategy to (1) detect PCNSL, (2) differentiate from other CNS entities, and (3) test the diagnostic performance in a prospective international multicenter cohort and two additional independent test cohorts. We trained on 54,000 SRH patch images sourced from surgical resections and stereotactic-guided biopsies, including various CNS tumor/non-tumor lesions. Training and test data were collected from four tertiary international medical centers. The final histopathological diagnosis served as ground-truth. In the prospective test cohort of PCNSL and non-PCNSL entities (n=160), RapidLymphoma achieved an overall balanced accuracy of 97.81% ±0.91, non-inferior to frozen section analysis in detecting PCNSL (100% vs. 78.94%). The additional test cohorts (n=420, n=59) reached balanced accuracy rates of 95.44% ±0.74 and 95.57% ±2.47 in differentiating IDH-wildtype diffuse gliomas and various brain metastasis from PCNSL. Visual heatmaps revealed RapidLymphoma's capabilities to detect class-specific histomorphological key features. RapidLymphoma is valid and reliable in detecting PCNSL and differentiating from other CNS entities within three minutes, as well as visual feedback in an intraoperative setting. This leads to fast clinical decision-making and further treatment strategy planning.

Development and validation of a clinical risk model for postoperative outcome in newly diagnosed glioblastoma: a report of the RANO resect group.

BACKGROUND: Following surgery, patients with newly diagnosed glioblastoma frequently enter clinical trials. Nuanced risk assessment is warranted to reduce imbalances between study arms. Here, we aimed (I) to analyze the interactive effects of residual tumor with clinical and molecular factors on outcome and (II) to define a postoperative risk assessment tool. METHODS: The RANO resect group retrospectively compiled an international, seven-center training cohort of patients with newly diagnosed glioblastoma. The combined associations of residual tumor with molecular or clinical factors and survival were analyzed, and recursive partitioning analysis was performed for risk modeling. The resulting model was prognostically verified in a separate external validation cohort. RESULTS: Our training cohort compromised 1003 patients with newly diagnosed isocitrate dehydrogenase-wildtype glioblastoma. Residual tumor, O6-methylguanine DNA methyltransferase (MGMT) promotor methylation status, age, and postoperative KPS were prognostic for survival and incorporated into regression tree analysis. By individually weighting the prognostic factors, an additive score (range, 0-9 points) integrating these four variables distinguished patients with low (0-2 points), intermediate (3-5 points), and high risk (6-9 points) for inferior survival. The prognostic value of our risk model was retained in treatment-based subgroups and confirmed in an external validation cohort of 258 patients with glioblastoma. Compared to previously postulated models, goodness-of-fit measurements were superior for our model. CONCLUSIONS: The novel RANO risk model serves as an easy-to-use, yet highly prognostic tool for postoperative patient stratification prior to further therapy. The model may serve to guide patient management and reduce imbalances between study arms in prospective trials.