Can the introduction of a 12-lead ECG help reduce mortality in those presenting with foot ulceration to multidisciplinary diabetic foot clinics? An observational evaluation of a real-world implementation pilot in England.

AIMS/HYPOTHESIS: The risk of dying within 2 years of presentation with diabetic foot ulceration is over six times the risk of amputation, with CVD the major contributor. Using an observational evaluation of a real-world implementation pilot, we aimed to assess whether for those presenting with diabetic foot ulceration in England, introducing a 12-lead ECG into routine care followed by appropriate clinical action was associated with reduced mortality. METHODS: Between July 2014 and December 2017, ten multidisciplinary diabetic foot services in England participated in a pilot project introducing 12-lead ECGs for new attendees with foot ulceration. Inception coincided with launch of the National Diabetes Footcare Audit (NDFA), whereby all diabetic footcare services in England were invited to enter data on new attendees with foot ulceration. Poisson regression models assessed the mortality RR at 2 and 5 years following first assessment of those receiving care in a participating pilot unit vs those receiving care in any other unit in England, adjusting for age, sex, ethnicity, deprivation, type and duration of diabetes, ulcer severity, and morbidity in the year prior to first assessment. RESULTS: Of the 3110 people recorded in the NDFA at a participating unit during the pilot, 33% (1015) were recorded as having received an ECG. A further 25,195 people recorded in the NDFA had attended another English footcare service. Unadjusted mortality in the pilot units was 16.3% (165) at 2 years and 37.4% (380) at 5 years for those who received an ECG, and 20.5% (430) and 45.2% (950), respectively, for those who did not receive an ECG. For people included in the NDFA at other units, unadjusted mortality was 20.1% (5075) and 42.6% (10,745), respectively. In the fully adjusted model, mortality was not significantly lower for those attending participating units at 2 (RR 0.93 [95% CI 0.85, 1.01]) or 5 years (RR 0.95 [95% CI 0.90, 1.01]). At participating units, mortality in those who received an ECG vs those who did not was lower at 5 years (RR 0.86 [95% CI 0.76, 0.97]), but not at 2 years (RR 0.87 [95% CI 0.72, 1.04]). Comparing just those that received an ECG with attendees at all other centres in England, mortality was lower at 5 years (RR 0.87 [95% CI 0.78, 0.96]), but not at 2 years (RR 0.86 [95% CI 0.74, 1.01]). CONCLUSIONS/INTERPRETATION: The evaluation confirms the high mortality seen in those presenting with diabetic foot ulceration. Overall mortality at the participating units was not significantly reduced at 2 or 5 years, with confidence intervals just crossing parity. Implementation of the 12-lead ECG into the routine care pathway proved challenging for clinical teams-overall a third of attendees had one, although some units delivered the intervention to over 60% of attendees-and the evaluation was therefore underpowered. Nonetheless, the signals of potential mortality benefit among those who had an ECG suggest that units in a position to operationalise implementation may wish to consider this. DATA AVAILABILITY: Data from the National Diabetes Audit can be requested through the National Health Service Digital Data Access Request Service process at: https://digital.nhs.uk/services/data-access-request-service-dars/dars-products-and-services/data-set-catalogue/national-diabetes-audit-nda.

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.

Directed evolution of biomass intensive CHO cells by adaptation to sub-physiological temperature.

We report a simple and effective means to increase the biosynthetic capacity of host CHO cells. Lonza proprietary CHOK1SV® cells were evolved by serial sub-culture for over 150 generations at 32 °C. During this period the specific proliferation rate of hypothermic cells gradually recovered to become comparable to that of cells routinely maintained at 37 °C. Cold-adapted cell populations exhibited (1) a significantly increased volume and biomass content (exemplified by total RNA and protein), (2) increased mitochondrial function, (3) an increased antioxidant capacity, (4) altered central metabolism, (5) increased transient and stable productivity of a model IgG4 monoclonal antibody and Fc-fusion protein, and (6) unaffected recombinant protein N-glycan processing. This phenotypic transformation was associated with significant genome-scale changes in both karyotype and the relative abundance of thousands of cellular mRNAs across numerous functional groups. Taken together, these observations provide evidence of coordinated cellular adaptations to sub-physiological temperature. These data reveal the extreme genomic/functional plasticity of CHO cells, and that directed evolution is a viable genome-scale cell engineering strategy that can be exploited to create host cells with an increased cellular capacity for recombinant protein production.

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.

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.

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.

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.

Structure-Guided Design and Synthesis of a Pyridazinone Series of Trypanosoma cruzi Proteasome Inhibitors.

There is an urgent need for new treatments for Chagas disease, a parasitic infection which mostly impacts South and Central America. We previously reported on the discovery of GSK3494245/DDD01305143, a preclinical candidate for visceral leishmaniasis which acted through inhibition of the Leishmania proteasome. A related analogue, active against Trypanosoma cruzi, showed suboptimal efficacy in an animal model of Chagas disease, so alternative proteasome inhibitors were investigated. Screening a library of phenotypically active analogues against the T. cruzi proteasome identified an active, selective pyridazinone, the development of which is described herein. We obtained a cryo-EM co-structure of proteasome and a key inhibitor and used this to drive optimization of the compounds. Alongside this, optimization of the absorption, distribution, metabolism, and excretion (ADME) properties afforded a suitable compound for mouse efficacy studies. The outcome of these studies is discussed, alongside future plans to further understand the series and its potential to deliver a new treatment for Chagas disease.

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.

Today's drug discovery and the shadow of the rule of 5.

INTRODUCTION: The rule of 5 developed by Lipinski et al., a landmark and prescient piece of scholarship, focused the minds of drug hunters by systematically characterizing the physical make-up of drug molecules for the first time, noting many sub-optimal compounds identified by high-throughput screening practices. Its profound influence on thinking and practices, whilst providing benefit, perhaps etched the guidelines too strongly in the minds of some drug hunters who applied the bounds too literally without understanding the implications of the underlying statistics. AREAS COVERED: This opinion is based on recent key developments that take thinking, measurements, and standards beyond those first set out, particularly the influences of molecular weight and the understanding, measurement, and calculation of lipophilicity. EXPERT OPINION: Techniques and technologies for physicochemical estimations set new standards. It is timely to celebrate the significance and influence of the rule of 5, whilst taking thinking to new levels with better characterizations. The shadow of the rule of 5 may be long, but it is not dark, as new measurements, predictions and principles emerge as guiding lights in the design and prioritization of higher-quality molecules redefining the meaning of beyond the rule of 5.

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.

Production of Graphene/Inorganic Matrix Composites through the Sintering of Graphene Oxide Flakes Decorated with CuWO4·2H2O Nanoparticles.

There is growing interest in graphene-reinforced inorganic matrix composites, but progress in this field is far behind that of polymer matrices due to difficulties in the processing of carbon materials in aggressive sintering environments, including oxidation and solubility in the host matrix. Copper-tungsten matrices are of particular interest in the power switching field but are difficult to produce due to the mutual insolubility of metals and poor wetting. Herein, composites were produced by decorating graphene oxide flakes with 8 nm diameter CuWO4·2H2O nanoparticles and then sintering them to form the final shape. The oxide nanoparticles were found to self-assemble into platelets on the surfaces of graphene flakes. Upon sintering, the presence of graphene was found to change the grain morphology from elongated needles to a polyhedral shape. It was found that, despite the nanosize of the CuWO4·2H2O particles used, the sintering conditions did not reduce the matrix to a pure metal; the sintered composites were found to be of mixed phase with copper tungstate and copper oxide present. Raman spectroscopy indicated that the graphene oxide became hydrogenated during the sintering process as a result of the reducing hydrogen atmosphere used.

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.