Advanced approaches in Pediatric Epilepsy surgery.

While recent technological advancements are reshaping the landscape of surgical epilepsy management, the established techniques of resective and disconnective surgeries guided by electrographic monitoring remain the workhorse interventions for the management of refractory seizures and have the highest likelihood of achieving complete seizure resolution. Here we discuss examples of recent developments in surgical approaches and techniques for resective and disconnective surgeries with discussion of their indications and potential advantages.

Understanding metric-related pitfalls in image analysis validation.

Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence research and its translation into practice. However, increasing evidence shows that, particularly in image analysis, metrics are often chosen inadequately. Although taking into account the individual strengths, weaknesses and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multistage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides a reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Although focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation.

Metrics reloaded: recommendations for image analysis validation.

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. In biomedical image analysis, chosen performance metrics often do not reflect the domain interest, and thus fail to adequately measure scientific progress and hinder translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Developed by a large international consortium in a multistage Delphi process, it is based on the novel concept of a problem fingerprint-a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), dataset and algorithm output. On the basis of the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as classification tasks at image, object or pixel level, namely image-level classification, object detection, semantic segmentation and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases.

Burr Hole Hemispherotomy-Modification of Trans-Sylvian Peri-Insular Technique: 2-Dimensional Operative Video.

Trans-sylvian peri-insular hemispherotomy represents a functional hemispherectomy with minimal brain removal used for treatment of refractory hemispheric epilepsy.1 Exposure for this procedure is achieved by craniotomy. Refinement in the hemispherotomy technique, including trends toward minimizing cortical resection, has contributed to a substantial drop in complication rates.2 We present a refinement of this technique, allowing for complete hemispheric disconnection through a single burr hole. In this instance, this technique was applied in the case of a 4-year-old girl who presented with medically refractory epilepsy, which had developed on the first day of life due to a perinatal incomplete left middle cerebral artery stroke. Postoperatively, the patient experienced no worsening of her preexisting right-sided hemiparesis and remains seizure-free 18 months postoperatively, now off medication. While the trans-sylvian peri-insular hemispherotomy represents an established surgical technique, this is the first report of this procedure performed in a minimally invasive fashion through a single burr hole. Beyond the minimal incision and small aperture in the skull, seldom appreciated nuances of hemispheric disconnection are described and demonstrated, including amygdala disconnection, hippocampal tail disconnection directly into splenium disconnection, concomitant intermediate disconnection and callosotomy, and frontobasal disconnection landmarks. Consent was obtained from the patient's parents for the surgical procedure, use of outcome videos, and for publication of this video and associated materials. The participants and patient's parents consented to publication of their images and that of the patient.

Understanding metric-related pitfalls in image analysis validation.

Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately in relation to the underlying research problem. This could be attributed to a lack of accessibility of metric-related knowledge: While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Focusing on biomedical image analysis but with the potential of transfer to other fields, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. To facilitate comprehension, illustrations and specific examples accompany each pitfall. As a structured body of information accessible to researchers of all levels of expertise, this work enhances global comprehension of a key topic in image analysis validation.

Systematic review and cumulative analysis of clinical properties of BRAF V600E mutations in PLNTY histological samples.

PURPOSE: Polymorphous low-grade neuroepithelial tumors of the young (PLNTY) represent a rare pediatric-type tumor that most commonly presents as medically refractory epilepsy. PLNTY has only recently been recognized as a distinct clinical entity, having been first described in 2016 and added to the World Health Organization classification of CNS tumors in 2021. Molecular studies have determined that PLNTY is uniformly driven by aberrant MAPK pathway activation, with most tumors carrying either a BRAF V600E mutation or activating FGFR2 or FGFR3 fusion protein. Although it is known that these driver mutations are mutually exclusive, little is known about differences in clinical presentation or treatment outcomes between PLNTY cases driven by these distinct mutations. METHODS: We performed a systematic review and cumulative analysis of PLNTY cases to assess whether or not PLNTY tumors carrying the BRAF V600E mutation exhibit different clinical behaviors. By searching the literature for all cases of PLNTY wherein BRAF V600E status was characterized, we compiled a dataset of 62 unique patient instances. Using a logistic regression-based approach, we assessed a primary outcome of what factors of a clinical presentation were associated with BRAF V600E mutations and a secondary outcome of what factors predicted total seizure freedom post-surgical resection. RESULTS: PLNTY cases carrying BRAF V600E mutations in the literature were strongly positively associated with adult patients (p = 0.0055, OR = 6.556; 95% Conf. Int. = 1.737-24.742). BRAF V600E status was also positively associated with tumor involvement of the temporal lobe (p = 0.0046, OR = 11.036; 95% Conf. Int. = 2.100-58.006). Male sex was also positively associated with BRAF V600E status, but the result did not quite achieve statistical significance (p = 0.0731). BRAF V600E status was not found to be associated with post-operative seizure freedom. CONCLUSIONS: These findings indicate that BRAF V600E-positive PLNTY exhibit characteristic clinical presentations but are not necessarily different in treatment responsiveness. Non-BRAF V600E tumors are more commonly associated with young patients.

Addressing image misalignments in multi-parametric prostate MRI for enhanced computer-aided diagnosis of prostate cancer.

Prostate cancer (PCa) diagnosis on multi-parametric magnetic resonance images (MRI) requires radiologists with a high level of expertise. Misalignments between the MRI sequences can be caused by patient movement, elastic soft-tissue deformations, and imaging artifacts. They further increase the complexity of the task prompting radiologists to interpret the images. Recently, computer-aided diagnosis (CAD) tools have demonstrated potential for PCa diagnosis typically relying on complex co-registration of the input modalities. However, there is no consensus among research groups on whether CAD systems profit from using registration. Furthermore, alternative strategies to handle multi-modal misalignments have not been explored so far. Our study introduces and compares different strategies to cope with image misalignments and evaluates them regarding to their direct effect on diagnostic accuracy of PCa. In addition to established registration algorithms, we propose 'misalignment augmentation' as a concept to increase CAD robustness. As the results demonstrate, misalignment augmentations can not only compensate for a complete lack of registration, but if used in conjunction with registration, also improve the overall performance on an independent test set.

Bone marrow fibrosis is associated with non-response to CD19 CAR T-cell therapy in B-acute lymphoblastic leukemia.

CD19 directed CAR T-cell therapy is used to treat relapsed/refractory B-cell acute lymphoblastic leukemia. The role of the pre-CAR bone marrow (BM) stromal microenvironment in determining response to CAR T-cell therapy has been understudied. We performed whole transcriptome analysis, reticulin fibrosis assessment and CD3 T-cell infiltration on BM core biopsies from pre- and post-CAR timepoints for 61 patients, as well as on a cohort of 54 primary B-ALL samples. Pathways of fibrosis, extracellular matrix development, and associated transcription factors AP1 and TGF-ß3, were enriched and upregulated in nonresponders (NR) even prior to CAR T cell therapy. NR showed significantly higher levels of BM fibrosis compared to complete responders by both clinical reticulin assessment and AI-assisted digital image scoring. CD3+ T cells showed a trend toward lower infiltration in NR. NR had significantly higher levels of pre-CAR fibrosis compared to primary B-ALL. High levels of fibrosis were associated with lower overall survival after CAR T-cell therapy. In conclusion, BM fibrosis is a novel mechanism mediating nonresponse to CD19-directed CAR T-cell therapy in B-ALL. A widely used clinically assay for quantitating myelofibrosis can be repurposed to determine patients at high risk of non-response. Genes and pathways associated with BM fibrosis are a potential target to improve response.

Palliation for catastrophic nonlocalizing epilepsy: a retrospective case series of complete corpus callosotomy at a single institution.

OBJECTIVE: In this study, the authors describe their 10-year single-institution experience with single-step complete corpus callosotomy (CCC) for seizure management in pediatric and adult patients with catastrophic, medically refractory, nonlocalizing epilepsy at Advent Health Orlando. METHODS: The authors conducted a retrospective observational study of patients aged 6 months to 49 years who underwent clinically indicated CCC for drug-resistant nonlocalizing epilepsy at Advent Health Orlando between July 2011 and July 2021. Follow-up ranged from 12 months to 10 years. RESULTS: Of the 101 patients (57% of whom were male) who met eligibility criteria, 81 were pediatric patients and 20 were ≥ 18 years. All patients had seizures that appeared poorly lateralized on both electroencephalograms and clinical semiological studies. Of 54 patients with drop seizures before CCC, 29 (54%) achieved stable freedom from drop seizures after CCC. Of the 101 patients, 14 (13.9%) experienced stable resolution of all types of clinical seizures (International League Against Epilepsy classes 1 and 2). The most common postoperative neurological complication was a transient disconnection syndrome, observed in 50% of patients; of those patients, 73% experienced syndrome resolution within 2 months after surgery, and all resolved by the 2-year follow-up. Formal neuropsychological test results were stable in 13 patients assessed after CCC. CONCLUSIONS: CCC is an effective and well-tolerated palliative surgical technique. In this study, drop attacks were reduced after CCC but could recur for the first time as late as 44 months after surgery. Other seizure types were also reduced postoperatively but could recur for the first time as late as 28 months after surgery. Nearly 14% of patients achieved stable and complete freedom from seizures after CCC. Re-evaluation after CCC can reveal lateralized seizure onset in some patients.

Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke.

Swift diagnosis and treatment play a decisive role in the clinical outcome of patients with acute ischemic stroke (AIS), and computer-aided diagnosis (CAD) systems can accelerate the underlying diagnostic processes. Here, we developed an artificial neural network (ANN) which allows automated detection of abnormal vessel findings without any a-priori restrictions and in <2 minutes. Pseudo-prospective external validation was performed in consecutive patients with suspected AIS from 4 different hospitals during a 6-month timeframe and demonstrated high sensitivity (≥87%) and negative predictive value (≥93%). Benchmarking against two CE- and FDA-approved software solutions showed significantly higher performance for our ANN with improvements of 25-45% for sensitivity and 4-11% for NPV (p ≤ 0.003 each). We provide an imaging platform ( https://stroke.neuroAI-HD.org ) for online processing of medical imaging data with the developed ANN, including provisions for data crowdsourcing, which will allow continuous refinements and serve as a blueprint to build robust and generalizable AI algorithms.

The PECAn image and statistical analysis pipeline identifies Minute cell competition genes and features.

Investigating organ biology often requires methodologies to induce genetically distinct clones within a living tissue. However, the 3D nature of clones makes sample image analysis challenging and slow, limiting the amount of information that can be extracted manually. Here we develop PECAn, a pipeline for image processing and statistical data analysis of complex multi-genotype 3D images. PECAn includes data handling, machine-learning-enabled segmentation, multivariant statistical analysis, and graph generation. This enables researchers to perform rigorous analyses rapidly and at scale, without requiring programming skills. We demonstrate the power of this pipeline by applying it to the study of Minute cell competition. We find an unappreciated sexual dimorphism in Minute cell growth in competing wing discs and identify, by statistical regression analysis, tissue parameters that model and correlate with competitive death. Furthermore, using PECAn, we identify several genes with a role in cell competition by conducting an RNAi-based screen.

Configurational Causal Modeling and Logic Regression.

Configurational comparative methods (CCMs) and logic regression methods (LRMs) are two families of exploratory methods that employ very different techniques to analyze data generated by causal structures featuring conjunctural causation and equifinality. Aiming for the same by different means carries a substantive synergy potential, which, however, remains untapped so far because representatives of the two frameworks know little of each other. The purpose of this article is to change that. We first level the field for readers from both backgrounds by providing brief introductions to the basic ideas behind CCMs and LRMs. Then, we carve out the strengths and weaknesses of the two method families by benchmarking their performance when applied to binary data under a variety of different discovery contexts. It turns out that CCMs and LRMs have complementary strengths and weaknesses. This creates various promising avenues for cross-validation.

AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine.

Automated image analysis plays an increasing role in radiology in detecting and quantifying image features outside of the perception of human eyes. Common AI-based approaches address a single medical problem, although patients often present with multiple interacting, frequently subclinical medical conditions. A holistic imaging diagnostics tool based on artificial intelligence (AI) has the potential of providing an overview of multi-system comorbidities within a single workflow. An interdisciplinary, multicentric team of medical experts and computer scientists designed a pipeline, comprising AI-based tools for the automated detection, quantification and characterization of the most common pulmonary, metabolic, cardiovascular and musculoskeletal comorbidities in chest computed tomography (CT). To provide a comprehensive evaluation of each patient, a multidimensional workflow was established with algorithms operating synchronously on a decentralized Joined Imaging Platform (JIP). The results of each patient are transferred to a dedicated database and summarized as a structured report with reference to available reference values and annotated sample images of detected pathologies. Hence, this tool allows for the comprehensive, large-scale analysis of imaging-biomarkers of comorbidities in chest CT, first in science and then in clinical routine. Moreover, this tool accommodates the quantitative analysis and classification of each pathology, providing integral diagnostic and prognostic value, and subsequently leading to improved preventive patient care and further possibilities for future studies.

Biosignature stability in space enables their use for life detection on Mars.

Two rover missions to Mars aim to detect biomolecules as a sign of extinct or extant life with, among other instruments, Raman spectrometers. However, there are many unknowns about the stability of Raman-detectable biomolecules in the martian environment, clouding the interpretation of the results. To quantify Raman-detectable biomolecule stability, we exposed seven biomolecules for 469 days to a simulated martian environment outside the International Space Station. Ultraviolet radiation (UVR) strongly changed the Raman spectra signals, but only minor change was observed when samples were shielded from UVR. These findings provide support for Mars mission operations searching for biosignatures in the subsurface. This experiment demonstrates the detectability of biomolecules by Raman spectroscopy in Mars regolith analogs after space exposure and lays the groundwork for a consolidated space-proven database of spectroscopy biosignatures in targeted environments.

The Gr64 cluster of gustatory receptors promotes survival and proteostasis of epithelial cells in Drosophila.

Gustatory Receptor 64 (Gr64) genes are a cluster of 6 neuronally expressed receptors involved in sweet taste sensation in Drosophila melanogaster. Gr64s modulate calcium signalling and excitatory responses to several different sugars. Here, we discover an unexpected nonneuronal function of Gr64 receptors and show that they promote proteostasis in epithelial cells affected by proteotoxic stress. Using heterozygous mutations in ribosome proteins (Rp), which have recently been shown to induce proteotoxic stress and protein aggregates in cells, we show that Rp/+ cells in Drosophila imaginal discs up-regulate expression of the entire Gr64 cluster and depend on these receptors for survival. We further show that loss of Gr64 in Rp/+ cells exacerbates stress pathway activation and proteotoxic stress by negatively affecting autophagy and proteasome function. This work identifies a noncanonical role in proteostasis maintenance for a family of gustatory receptors known for their function in neuronal sensation.

Qualitative Comparative Analysis and robust sufficiency.

Some methodologists take the search target of Qualitative Comparative Analysis (QCA) to be causal INUS-conditions, others contend that QCA should instead be used to search for some form of sufficiency that is more substantive than mere Boolean sufficiency. While the notion of an INUS-condition has a long and uncontroversial definitional history, Adrian Dusa, in a recent paper, is the first to explicitly define a notion of substantive sufficiency, which he labels robust sufficiency. Dusa's definition, however, is vacuous in real-life research contexts. As an alternative, the first part of this paper non-vacuously defines robust sufficiency and supplies a corresponding notion of minimality, which-I argue-captures Dusa's conceptual intentions. In the second part, I then report and discuss the results of a series of simulation experiments benchmarking the performance of the different QCA solution types in recovering robust sufficiency and minimality. Supplementary Information: The online version contains supplementary material available at 10.1007/s11135-021-01157-z.

Xrp1 and Irbp18 trigger a feed-forward loop of proteotoxic stress to induce the loser status.

Cell competition induces the elimination of less-fit "loser" cells by fitter "winner" cells. In Drosophila, cells heterozygous mutant in ribosome genes, Rp/+, known as Minutes, are outcompeted by wild-type cells. Rp/+ cells display proteotoxic stress and the oxidative stress response, which drive the loser status. Minute cell competition also requires the transcription factors Irbp18 and Xrp1, but how these contribute to the loser status is partially understood. Here we provide evidence that initial proteotoxic stress in RpS3/+ cells is Xrp1-independent. However, Xrp1 is sufficient to induce proteotoxic stress in otherwise wild-type cells and is necessary for the high levels of proteotoxic stress found in RpS3/+ cells. Surprisingly, Xrp1 is also induced downstream of proteotoxic stress, and is required for the competitive elimination of cells suffering from proteotoxic stress or overexpressing Nrf2. Our data suggests that a feed-forward loop between Xrp1, proteotoxic stress, and Nrf2 drives Minute cells to become losers.

Incidental finding of renal cell carcinoma in an asymptomatic patient on low-dose computed tomography screening for lung cancer.

INTRODUCTION In 2013, the United States Preventive Services Task Force recommended annual low-dose computed tomography (CT) screening for lung cancer in high-risk adults with a significant smoking history. These screenings result in large numbers of incidental findings, and although most of these do not warrant further investigation, there have been reported cases of incidental findings identified on CT screening that led to successful treatment of a previously undiagnosed comorbidity. CASE HISTORY Here, we report a case of papillary renal cell carcinoma that was detected incidentally on low-dose CT in an asymptomatic individual, a rare diagnosis considering that renal neoplasms account for <1% of incidental findings on these screenings. CONCLUSION This case highlights the value of investigating these incidental findings, with the goal of detecting underlying disease in some cases before it would have presented symptomatically.

Mechanical cell competition in human pluripotent stem cell cultures.

Human induced pluripotent stem cells (hIPSCs) are an important tool, but challenges remain in optimizing their use. hIPSC cultures frequently become contaminated and overrun with cells containing genetic aberrations. In this issue of Developmental Cell, Price et al. establish that this results from cell competition between wild-type and variant cells.