Tumor Volume Growth Rates and Doubling Times during Active Surveillance of IDH-mutant Low-Grade Glioma.

PURPOSE: Isocitrate dehydrogenase-mutant (IDH-mt) gliomas are incurable primary brain tumors characterized by a slow-growing phase over several years followed by a rapid-growing malignant phase. We hypothesized that tumor volume growth rate (TVGR) on MRI may act as an earlier measure of clinical benefit during the active surveillance period. EXPERIMENTAL DESIGN: We integrated three-dimensional volumetric measurements with clinical, radiologic, and molecular data in a retrospective cohort of IDH-mt gliomas that were observed after surgical resection in order to understand tumor growth kinetics and the impact of molecular genetics. RESULTS: Using log-linear mixed modeling, the entire cohort (n = 128) had a continuous %TVGR per 6 months of 10.46% [95% confidence interval (CI), 9.11%-11.83%] and a doubling time of 3.5 years (95% CI, 3.10-3.98). High molecular grade IDH-mt gliomas, defined by the presence of homozygous deletion of CDKN2A/B, had %TVGR per 6 months of 19.17% (95% CI, 15.57%-22.89%) which was significantly different from low molecular grade IDH-mt gliomas with a growth rate per 6 months of 9.54% (95% CI, 7.32%-11.80%; P < 0.0001). Using joint modeling to comodel the longitudinal course of TVGR and overall survival, we found each one natural logarithm tumor volume increase resulted in more than a 3-fold increase in risk of death (HR = 3.83; 95% CI, 2.32-6.30; P < 0.0001). CONCLUSIONS: TVGR may be used as an earlier measure of clinical benefit and correlates well with the WHO 2021 molecular classification of gliomas and survival. Incorporation of TVGR as a surrogate endpoint into future prospective studies of IDH-mt gliomas may accelerate drug development.

Advances in diffuse glial tumors diagnosis.

In recent decades, there have been significant advances in the diagnosis of diffuse gliomas, driven by the integration of novel technologies. These advancements have deepened our understanding of tumor oncogenesis, enabling a more refined stratification of the biological behavior of these neoplasms. This progress culminated in the fifth edition of the WHO classification of central nervous system (CNS) tumors in 2021. This comprehensive review article aims to elucidate these advances within a multidisciplinary framework, contextualized within the backdrop of the new classification. This article will explore morphologic pathology and molecular/genetics techniques (immunohistochemistry, genetic sequencing, and methylation profiling), which are pivotal in diagnosis, besides the correlation of structural neuroimaging radiophenotypes to pathology and genetics. It briefly reviews the usefulness of tractography and functional neuroimaging in surgical planning. Additionally, the article addresses the value of other functional imaging techniques such as perfusion MRI, spectroscopy, and nuclear medicine in distinguishing tumor progression from treatment-related changes. Furthermore, it discusses the advantages of evolving diagnostic techniques in classifying these tumors, as well as their limitations in terms of availability and utilization. Moreover, the expanding domains of data processing, artificial intelligence, radiomics, and radiogenomics hold great promise and may soon exert a substantial influence on glioma diagnosis. These innovative technologies have the potential to revolutionize our approach to these tumors. Ultimately, this review underscores the fundamental importance of multidisciplinary collaboration in employing recent diagnostic advancements, thereby hoping to translate them into improved quality of life and extended survival for glioma patients.

Nas últimas décadas, houve avanços significativos no diagnóstico de gliomas difusos, impulsionados pela integração de novas tecnologias. Esses avanços aprofundaram nossa compreensão da oncogênese tumoral, permitindo uma estratificação mais refinada do comportamento biológico dessas neoplasias. Esse progresso culminou na quinta edição da classificação da OMS de tumores do sistema nervoso central (SNC) em 2021. Esta revisão abrangente tem como objetivo elucidar esses avanços de forma multidisciplinar, no contexto da nova classificação. Este artigo irá explorar a patologia morfológica e as técnicas moleculares/genéticas (imuno-histoquímica, sequenciamento genético e perfil de metilação), que são fundamentais no diagnóstico, além da correlação dos radiofenótipos da neuroimagem estrutural com a patologia e a genética. Aborda sucintamente a utilidade da tractografia e da neuroimagem funcional no planejamento cirúrgico. Destacaremos o valor de outras técnicas de imagem funcional, como ressonância magnética de perfusão, espectroscopia e medicina nuclear, na distinção entre a progressão do tumor e as alterações relacionadas ao tratamento. Discutiremos as vantagens das diferentes técnicas de diagnóstico na classificação desses tumores, bem como suas limitações em termos de disponibilidade e utilização. Além disso, os crescentes avanços no processamento de dados, inteligência artificial, radiômica e radiogenômica têm grande potencial e podem em breve exercer uma influência substancial no diagnóstico de gliomas. Essas tecnologias inovadoras têm o potencial de revolucionar nossa abordagem a esses tumores. Em última análise, esta revisão destaca a importância fundamental da colaboração multidisciplinar na utilização dos recentes avanços diagnósticos, com a esperança de traduzi-los em uma melhor qualidade de vida e uma maior sobrevida.

Intracranial Outcomes of De Novo Brain Metastases Treated With Osimertinib Alone in Patients With Newly Diagnosed EGFR-Mutant NSCLC.

Introduction: Patients with EGFR-mutant NSCLC have a high incidence of brain metastases. The EGFR-directed tyrosine kinase inhibitor osimertinib has intracranial activity, making the role of local central nervous system (CNS)-directed therapies, such as radiation and surgery, less clear. Methods: Patients with EGFR-mutant NSCLC and brain metastases who received osimertinib as initial therapy after brain metastasis diagnosis were included. Individual lesion responses were assessed using adapted RANO-BM criteria. CNS progression and local progression of brain metastasis from osimertinib start were analyzed using cumulative incidence treating death as a competing risk. Overall survival was estimated using Kaplan-Meier methodology. Results: There were 36 patients who had a median interval from brain metastasis diagnosis to first-line osimertinib initiation of 25 days. In total, 136 previously untreated brain metastases were tracked from baseline. Overall, 105 lesions (77.2%) had complete response and 31 had partial response reflecting best objective response of 100%. Best response occurred at a median of 96 days (range: 28-1113 d) from baseline magnetic resonance imaging. This reflects a best objective response rate of 100%. Two-year overall survival was 80%. CNS progression rates at 1-, 2-, and 3-years post-osimertinib were 21%, 32%, and 41%, respectively. Lesion-level local failure was estimated to be 0.7% and 4.7% at 1- and 2-years post-osimertinib, respectively. No clinicodemographic factors including brain metastasis number were associated with post-osimertinib progression. Conclusions: Intracranial response to osimertinib is excellent for patients with EGFR-mutant NSCLC with de novo, previously untreated brain metastases. Very low local failure rates support a strategy of upfront osimertinib alone in selected patients.

Advances in diffuse glial tumors diagnosis / Avanços no diagnóstico dos gliomas difusos

Abstract In recent decades, there have been significant advances in the diagnosis of diffuse gliomas, driven by the integration of novel technologies. These advancements have deepened our understanding of tumor oncogenesis, enabling a more refined stratification of the biological behavior of these neoplasms. This progress culminated in the fifth edition of the WHO classification of central nervous system (CNS) tumors in 2021. This comprehensive review article aims to elucidate these advances within a multidisciplinary framework, contextualized within the backdrop of the new classification. This article will explore morphologic pathology and molecular/genetics techniques (immunohistochemistry, genetic sequencing, and methylation profiling), which are pivotal in diagnosis, besides the correlation of structural neuroimaging radiophenotypes to pathology and genetics. It briefly reviews the usefulness of tractography and functional neuroimaging in surgical planning. Additionally, the article addresses the value of other functional imaging techniques such as perfusion MRI, spectroscopy, and nuclear medicine in distinguishing tumor progression from treatment-related changes. Furthermore, it discusses the advantages of evolving diagnostic techniques in classifying these tumors, as well as their limitations in terms of availability and utilization. Moreover, the expanding domains of data processing, artificial intelligence, radiomics, and radiogenomics hold great promise and may soon exert a substantial influence on glioma diagnosis. These innovative technologies have the potential to revolutionize our approach to these tumors. Ultimately, this review underscores the fundamental importance of multidisciplinary collaboration in employing recent diagnostic advancements, thereby hoping to translate them into improved quality of life and extended survival for glioma patients.

Resumo Nas últimas décadas, houve avanços significativos no diagnóstico de gliomas difusos, impulsionados pela integração de novas tecnologias. Esses avanços aprofundaram nossa compreensão da oncogênese tumoral, permitindo uma estratificação mais refinada do comportamento biológico dessas neoplasias. Esse progresso culminou na quinta edição da classificação da OMS de tumores do sistema nervoso central (SNC) em 2021. Esta revisão abrangente tem como objetivo elucidar esses avanços de forma multidisciplinar, no contexto da nova classificação. Este artigo irá explorar a patologia morfológica e as técnicas moleculares/genéticas (imuno-histoquímica, sequenciamento genético e perfil de metilação), que são fundamentais no diagnóstico, além da correlação dos radiofenótipos da neuroimagem estrutural com a patologia e a genética. Aborda sucintamente a utilidade da tractografia e da neuroimagem funcional no planejamento cirúrgico. Destacaremos o valor de outras técnicas de imagem funcional, como ressonância magnética de perfusão, espectroscopia e medicina nuclear, na distinção entre a progressão do tumor e as alterações relacionadas ao tratamento. Discutiremos as vantagens das diferentes técnicas de diagnóstico na classificação desses tumores, bem como suas limitações em termos de disponibilidade e utilização. Além disso, os crescentes avanços no processamento de dados, inteligência artificial, radiômica e radiogenômica têm grande potencial e podem em breve exercer uma influência substancial no diagnóstico de gliomas. Essas tecnologias inovadoras têm o potencial de revolucionar nossa abordagem a esses tumores. Em última análise, esta revisão destaca a importância fundamental da colaboração multidisciplinar na utilização dos recentes avanços diagnósticos, com a esperança de traduzi-los em uma melhor qualidade de vida e uma maior sobrevida.

Outcomes Following Early Postoperative Adjuvant Radiosurgery for Brain Metastases.

Importance: Adjuvant stereotactic radiosurgery (SRS) enhances the local control of resected brain metastases (BrM). However, the risks of local failure (LF) and potential for posttreatment adverse radiation effects (PTRE) after early postoperative adjuvant SRS have not yet been established. Objective: To evaluate whether adjuvant SRS delivered within a median of 14 days after surgery is associated with improved LF without a concomitant increase in PTRE. Design, Setting, and Participants: This prospective cohort study examines a clinical workflow (RapidRT) that was implemented from 2019 to 2022 to deliver SRS to surgical patients within a median of 14 days, ensuring all patients were treated within 30 days postoperatively. This prospective cohort was compared with a historical cohort (StanRT) of patients with BrM resected between 2013 and 2019 to assess the association of the RapidRT workflow with LF and PTRE. The 2 cohorts were combined to identify optimal SRS timing, with a median follow-up of 3.3 years for survivors. Exposure: Timing of adjuvant SRS (14, 21, and 30 days postoperatively). Main Outcomes and Measures: LF and PTRE, according to modified Response Assessment in Neuro-Oncology Brain Metastases criteria. Results: There were 438 patients (265 [60.5%] female patients; 23 [5.3%] Asian, 27 [6.2%] Black, and 364 [83.1%] White patients) with a mean (SD) age of 62 (13) years; 377 were in the StanRT cohort and 61 in the RapidRT cohort. LF and PTRE rates at 1 year were not significantly different between RapidRT and StanRT cohorts. Timing of SRS was associated with radiographic PTRE. Patients receiving radiation within 14 days had the highest 1-year PTRE rate (18.08%; 95% CI, 8.31%-30.86%), and patients receiving radiation between 22 and 30 days had the lowest 1-year PTRE rate (4.10%; 95% CI, 1.52%-8.73%; P = .03). LF rates were highest for patients receiving radiation more than 30 days from surgery (10.65%; 95% CI, 6.90%-15.32%) but comparable for patients receiving radiation within 14 days, between 15 and 21 days, and between 22 and 30 days (≤14 days: 5.12%; 95% CI, 0.86%-15.60%; 15 to ≤21 days: 3.21%; 95% CI, 0.59%-9.99%; 22 to ≤30 days: 6.58%; 95% CI, 3.06%-11.94%; P = .20). Conclusions and Relevance: In this cohort study of adjuvant SRS timing following surgical resection of BrM, the optimal timing for adjuvant SRS appears to be within 22 to 30 days following surgery. The findings of this study suggest that this timing allows for a balanced approach that minimizes the risks associated with LF and PTRE.

The treatment of aggressive prolactinomas with everolimus.

INTRODUCTION: Aggressive prolactinomas are life-limiting tumors without a standard of care treatment option after the oral alkylator, temozolomide, fails to provide tumor control. METHODS: We reviewed an institutional database of pituitary tumors for patients with aggressive prolactinomas who progressed following treatment with a dopamine receptor agonist, radiotherapy and temozolomide. Within this cohort, we identified four patients who were treated with everolimus and we report their response to this therapy. Treatment response was determined by a neuroradiologist, who manually performed volumetric assessment and determined treatment response by Response Assessments in Neuro-Oncology (RANO) criteria. RESULTS: Three of four patients who were treated with everolimus had a biochemical response to therapy and all patients derived a clinically meaningful benefit based upon suppression of tumor growth. While the best overall response as assessed by RANO criteria was stable disease for the four patients, a minor regression in tumor size was appreciated in two of the four patients. CONCLUSION: Everolimus is an active agent in the treatment of prolactinomas that warrants further investigation.

Dabrafenib as a diagnostic and therapeutic strategy for the non-surgical management of papillary craniopharyngioma.

PURPOSE: Papillary craniopharyngiomas can cause considerable morbidity due to mass effect and potential surgical complications. These tumors are known to harbor BRAF V600 mutations, which make them exquisitely sensitive to BRAF inhibitors. METHODS: The patient is a 59 year old man with a progressive suprasellar lesion that was radiographically consistent with a papillary craniopharyngioma. He was consented to an Institution Review Board-approved protocol, which permits sequencing of cell free DNA in plasma and the collection and reporting of clinical data. RESULTS: The patient declined surgical resection and was empirically treated with dabrafenib at 150 mg twice daily. Treatment response was demonstrated after 19 days, confirming the diagnosis. After achieving a near complete response after 6.5 months on drug, a decision was made to deescalate treatment to dabrafenib 75 mg twice daily with subsequent tumor stability for 2.5 months. CONCLUSION: Patients with a suspected papillary craniopharyngioma can be challenged with dabrafenib as a potentially effective diagnostic and therapeutic strategy, given that rapid regression with dabrafenib is only observed in tumors harboring a BRAF V600 mutation. Further work is needed to explore the optimal regimen and dose of the targeted therapy.

Magnetic resonance relaxometry in quantitative imaging of brain gliomas: A literature review.

Magnetic resonance (MR) relaxometry is a quantitative imaging method that measures tissue relaxation properties. This review discusses the state of the art of clinical proton MR relaxometry for glial brain tumors. Current MR relaxometry technology also includes MR fingerprinting and synthetic MRI, which solve the inefficiencies and challenges of earlier techniques. Despite mixed results regarding its capability for brain tumor differential diagnosis, there is growing evidence that MR relaxometry can differentiate between gliomas and metastases and between glioma grades. Studies of the peritumoral zones have demonstrated their heterogeneity and possible directions of tumor infiltration. In addition, relaxometry offers T2* mapping that can define areas of tissue hypoxia not discriminated by perfusion assessment. Studies of tumor therapy response have demonstrated an association between survival and progression terms and dynamics of native and contrast-enhanced tumor relaxometric profiles. In conclusion, MR relaxometry is a promising technique for glial tumor diagnosis, particularly in association with neuropathological studies and other imaging techniques.

Fast, light, and scalable: harnessing data-mined line annotations for automated tumor segmentation on brain MRI.

OBJECTIVES: While fully supervised learning can yield high-performing segmentation models, the effort required to manually segment large training sets limits practical utility. We investigate whether data mined line annotations can facilitate brain MRI tumor segmentation model development without requiring manually segmented training data. METHODS: In this retrospective study, a tumor detection model trained using clinical line annotations mined from PACS was leveraged with unsupervised segmentation to generate pseudo-masks of enhancing tumors on T1-weighted post-contrast images (9911 image slices; 3449 adult patients). Baseline segmentation models were trained and employed within a semi-supervised learning (SSL) framework to refine the pseudo-masks. Following each self-refinement cycle, a new model was trained and tested on a held-out set of 319 manually segmented image slices (93 adult patients), with the SSL cycles continuing until Dice score coefficient (DSC) peaked. DSCs were compared using bootstrap resampling. Utilizing the best-performing models, two inference methods were compared: (1) conventional full-image segmentation, and (2) a hybrid method augmenting full-image segmentation with detection plus image patch segmentation. RESULTS: Baseline segmentation models achieved DSC of 0.768 (U-Net), 0.831 (Mask R-CNN), and 0.838 (HRNet), improving with self-refinement to 0.798, 0.871, and 0.873 (each p < 0.001), respectively. Hybrid inference outperformed full image segmentation alone: DSC 0.884 (Mask R-CNN) vs. 0.873 (HRNet), p < 0.001. CONCLUSIONS: Line annotations mined from PACS can be harnessed within an automated pipeline to produce accurate brain MRI tumor segmentation models without manually segmented training data, providing a mechanism to rapidly establish tumor segmentation capabilities across radiology modalities. KEY POINTS: • A brain MRI tumor detection model trained using clinical line measurement annotations mined from PACS was leveraged to automatically generate tumor segmentation pseudo-masks. • An iterative self-refinement process automatically improved pseudo-mask quality, with the best-performing segmentation pipeline achieving a Dice score of 0.884 on a held-out test set. • Tumor line measurement annotations generated in routine clinical radiology practice can be harnessed to develop high-performing segmentation models without manually segmented training data, providing a mechanism to rapidly establish tumor segmentation capabilities across radiology modalities.

Postradiosurgery cystic degeneration in brain metastases causing delayed and potentially severe sequelae: systematic review and illustrative cases.

BACKGROUND: Cystic postradiation degeneration has previously been described in the literature as a rare but potentially severe complication after central nervous system (CNS) irradiation for vascular malformations. Limited cases have been reported in the setting of brain metastases. OBSERVATIONS: Thirty-six total cases, including three reported here, of cystic postradiation degeneration are identified. Of 35 cases with complete clinical information, 34 (97.25%) of 35 were symptomatic from cystic changes at diagnosis. The average time between initial radiation dose and cyst development was 7.61 years (range 2-31 years). Although most patients were initially treated conservatively with medication, including steroids, 32 (88.9%) of 36 ultimately required surgical intervention. The most common interventions were craniotomy for cyst fenestration or resection (25 of 36; 69.4%) and Ommaya placement (8 of 36). After intervention, clinical improvement was seen in 10 (67%) of 15 cases, with persistent or worsening deficit or death seen in 5 (33%) of 15. Cysts were decompressed or obliterated on postoperative imaging in 20 (83.3%) of 24 cases, and recurrence was seen in 4 (16.7%) of 24. LESSONS: Cystic degeneration is a rare and delayed sequela after radiation for brain metastases. This entity has the potential to cause significant and permanent neurological deficit if not properly recognized and addressed. Durable control can be achieved with a variety of surgical treatments, including cyst fenestration and Ommaya placement.

Radiomic Analysis to Predict Histopathologically Confirmed Pseudoprogression in Glioblastoma Patients.

Purpose: Pseudoprogression mimicking recurrent glioblastoma remains a diagnostic challenge that may adversely confound or delay appropriate treatment or clinical trial enrollment. We sought to build a radiomic classifier to predict pseudoprogression in patients with primary isocitrate dehydrogenase wild type glioblastoma. Methods and Materials: We retrospectively examined a training cohort of 74 patients with isocitrate dehydrogenase wild type glioblastomas with brain magnetic resonance imaging including dynamic contrast enhanced T1 perfusion before resection of an enhancing lesion indeterminate for recurrent tumor or pseudoprogression. A recursive feature elimination random forest classifier was built using nested cross-validation without and with O6-methylguanine-DNA methyltransferase status to predict pseudoprogression. Results: A classifier constructed with cross-validation on the training cohort achieved an area under the receiver operating curve of 81% for predicting pseudoprogression. This was further improved to 89% with the addition of O6-methylguanine-DNA methyltransferase status into the classifier. Conclusions: Our results suggest that radiomic analysis of contrast T1-weighted images and magnetic resonance imaging perfusion images can assist the prompt diagnosis of pseudoprogression. Validation on external and independent data sets is necessary to verify these advanced analyses, which can be performed on routinely acquired clinical images and may help inform clinical treatment decisions.

Direct Evaluation of Treatment Response in Brain Metastatic Disease with Deep Neuroevolution.

Cancer centers have an urgent and unmet clinical and research need for AI that can guide patient management. A core component of advancing cancer treatment research is assessing response to therapy. Doing so by hand, for example, as per RECIST or RANO criteria, is tedious and time-consuming, and can miss important tumor response information. Most notably, the prevalent response criteria often exclude lesions, the non-target lesions, altogether. We wish to assess change in a holistic fashion that includes all lesions, obtaining simple, informative, and automated assessments of tumor progression or regression. Because genetic sub-types of cancer can be fairly specific and patient enrollment in therapy trials is often limited in number and accrual rate, we wish to make response assessments with small training sets. Deep neuroevolution (DNE) is a novel radiology artificial intelligence (AI) optimization approach that performs well on small training sets. Here, we use a DNE parameter search to optimize a convolutional neural network (CNN) that predicts progression versus regression of metastatic brain disease. We analyzed 50 pairs of MRI contrast-enhanced images as our training set. Half of these pairs, separated in time, qualified as disease progression, while the other 25 image pairs constituted regression. We trained the parameters of a CNN via "mutations" that consisted of random CNN weight adjustments and evaluated mutation "fitness" as summed training set accuracy. We then incorporated the best mutations into the next generation's CNN, repeating this process for approximately 50,000 generations. We applied the CNNs to our training set, as well as a separate testing set with the same class balance of 25 progression and 25 regression cases. DNE achieved monotonic convergence to 100% training set accuracy. DNE also converged monotonically to 100% testing set accuracy. We have thus shown that DNE can accurately classify brain metastatic disease progression versus regression. Future work will extend the input from 2D image slices to full 3D volumes, and include the category of "no change." We believe that an approach such as ours can ultimately provide a useful and informative complement to RANO/RECIST assessment and volumetric AI analysis.

CEST MR fingerprinting (CEST-MRF) for brain tumor quantification using EPI readout and deep learning reconstruction.

PURPOSE: To develop a clinical CEST MR fingerprinting (CEST-MRF) method for brain tumor quantification using EPI acquisition and deep learning reconstruction. METHODS: A CEST-MRF pulse sequence originally designed for animal imaging was modified to conform to hardware limits on clinical scanners while keeping scan time under 2 min. Quantitative MRF reconstruction was performed using a deep reconstruction network (DRONE) to yield the water relaxation and chemical exchange parameters. The feasibility of the six parameter DRONE reconstruction was tested in simulations using a digital brain phantom. A healthy subject was scanned with the CEST-MRF sequence, conventional MRF and CEST sequences for comparison. Reproducibility was assessed via test-retest experiments and the concordance correlation coefficient calculated for white matter and gray matter. The clinical utility of CEST-MRF was demonstrated on four patients with brain metastases in comparison to standard clinical imaging sequences. Tumors were segmented into edema, solid core, and necrotic core regions and the CEST-MRF values compared to the contra-lateral side. RESULTS: DRONE reconstruction of the digital phantom yielded a normalized RMS error of ≤7% for all parameters. The CEST-MRF parameters were in good agreement with those from conventional MRF and CEST sequences and previous studies. The mean concordance correlation coefficient for all six parameters was 0.98 ± 0.01 in white matter and 0.98 ± 0.02 in gray matter. The CEST-MRF values in nearly all tumor regions were significantly different (P = 0.05) from each other and the contra-lateral side. CONCLUSION: Combination of EPI readout and deep learning reconstruction enabled fast, accurate and reproducible CEST-MRF in brain tumors.

Salvage resection plus cesium-131 brachytherapy durably controls post-SRS recurrent brain metastases.

BACKGROUND: Salvage of recurrent previously irradiated brain metastases (rBrM) is a significant challenge. Resection without adjuvant re-irradiation is associated with a high local failure rate, while reirradiation only partially reduces failure but is associated with greater radiation necrosis risk. Salvage resection plus Cs131 brachytherapy may offer dosimetric and biologic advantages including improved local control versus observation, with reduced normal brain dose versus re-irradiation, however data are limited. METHODS: A prospective registry of consecutive patients with post-stereotactic radiosurgery (SRS) rBrM undergoing resection plus implantation of collagen-matrix embedded Cs131 seeds (GammaTile, GT Medical Technologies) prescribed to 60 Gy at 5 mm from the cavity was analyzed. RESULTS: Twenty patients underwent 24 operations with Cs131 implantation in 25 tumor cavities. Median maximum preoperative diameter was 3.0 cm (range 1.1-6.3). Gross- or near-total resection was achieved in 80% of lesions. A median of 16 Cs131 seeds (range 6-30), with a median air-kerma strength of 3.5 U/seed were implanted. There was one postoperative wound dehiscence. With median follow-up of 1.6 years for survivors, two tumors recurred (one in-field, one marginal) resulting in 8.4% 1-year progression incidence (95%CI = 0.0-19.9). Radiographic seed settling was identified in 7/25 cavities (28%) 1.9-11.7 months post-implantation, with 1 case of distant migration (4%), without clinical sequelae. There were 8 cases of radiation necrosis, of which 4 were symptomatic. CONCLUSIONS: With > 1.5 years of follow-up, intraoperative brachytherapy with commercially available Cs131 implants was associated with favorable local control and toxicity profiles. Weak correlation between preoperative tumor geometry and implanted tiles highlights a need to optimize planning criteria.

Randomized Phase II Trial of Proton Craniospinal Irradiation Versus Photon Involved-Field Radiotherapy for Patients With Solid Tumor Leptomeningeal Metastasis.

PURPOSE: Photon involved-field radiotherapy (IFRT) is the standard-of-care radiotherapy for patients with leptomeningeal metastasis (LM) from solid tumors. We tested whether proton craniospinal irradiation (pCSI) encompassing the entire CNS would result in superior CNS progression-free survival (PFS) compared with IFRT. PATIENTS AND METHODS: We conducted a randomized, phase II trial of pCSI versus IFRT in patients with non-small-cell lung cancer and breast cancers with LM. We enrolled patients with other solid tumors to an exploratory pCSI group. For the randomized groups, patients were assigned (2:1), stratified by histology and systemic disease status, to pCSI or IFRT. The primary end point was CNS PFS. Secondary end points included overall survival (OS) and treatment-related adverse events (TAEs). RESULTS: Between April 16, 2020, and October 11, 2021, 42 and 21 patients were randomly assigned to pCSI and IFRT, respectively. At planned interim analysis, a significant benefit in CNS PFS was observed with pCSI (median 7.5 months; 95% CI, 6.6 months to not reached) compared with IFRT (2.3 months; 95% CI, 1.2 to 5.8 months; P < .001). We also observed OS benefit with pCSI (9.9 months; 95% CI, 7.5 months to not reached) versus IFRT (6.0 months; 95% CI, 3.9 months to not reached; P = .029). There was no difference in the rate of grade 3 and 4 TAEs (P = .19). In the exploratory pCSI group, 35 patients enrolled, the median CNS PFS was 5.8 months (95% CI, 4.4 to 9.1 months) and OS was 6.6 months (95% CI, 5.4 to 11 months). CONCLUSION: Compared with photon IFRT, we found pCSI improved CNS PFS and OS for patients with non-small-cell lung cancer and breast cancer with LM with no increase in serious TAEs.

Brain radiotherapy, tremelimumab-mediated CTLA-4-directed blockade +/- trastuzumab in patients with breast cancer brain metastases.

Breast cancer brain metastases (BCBM) are a common and devastating complication of metastatic breast cancer with conventional systemic therapies demonstrating limited effectiveness. Consequently, radiotherapy (RT) ± surgery remains the cornerstone of BCBM management. Because preclinical and clinical evidence indicate that immune checkpoint blockade (ICB) may synergize with RT to promote systemic tumor regression, we explored the safety and efficacy of RT and concurrent tremelimumab-mediated cytotoxic T-lymphocyte associated protein 4 (CTLA-4) ICB with tremelimumab ± HER2-directed therapy with trastuzumab for BCBM. Eligible patients had BCBM indicated for brain RT. A Simon two-stage design was adopted to evaluate the efficacy of tremelimumab and RT in 20 patients with human epidermal growth factor receptor normal (HER2-) BCBM. The safety of concurrent RT, tremelimumab, and trastuzumab was evaluated in a cohort of 6 HER2+ patients. The primary endpoint was 12-week non-central nervous system (CNS) disease control rate (DCR). Secondary endpoints included safety, survival, and CNS response. Exploratory correlatives included characterization of peripheral blood immune responses among exceptional responders. Tremelimumab plus RT ± trastuzumab was tolerated with no treatment-related grade 4 adverse events reported. The 12-week non-CNS DCR was 10% (2/20) in the HER2- cohort and 33% (2/6) in the HER2+ cohort. One patient with HER2+ disease experienced a durable partial response with evidence of peripheral T-cell activation. Thus, tremelimumab and RT ± trastuzumab was tolerated. Although modest clinical activity was observed in the HER2- efficacy cohort, encouraging responses were observed in the HER2+ safety cohort. Consequently, a trial to determine efficacy in HER2+ BCBM is planned.Clinical Trial Registration Number: NCT02563925.