A TPS integrated machine learning tool for predicting patient-specific quality assurance outcomes in volumetric-modulated arc therapy.

PURPOSE: Machine learning (ML) models have been demonstrated to be beneficial for optimizing the workload of patient-specific quality assurance (PSQA). Implementing them in clinical routine frequently requires third-party applications beyond the treatment planning system (TPS), slowing down the workflow. To address this issue, a PSQA outcomes predictive model was carefully selected and validated before being fully integrated into the TPS. MATERIALS AND METHODS: Nine ML algorithms were evaluated using cross-validation. The learning database was built by calculating complexity metrics (CM) and binarizing PSQA results into "pass"/"fail" classes for 1767 VMAT arcs. The predictive performance was evaluated using area under the ROC curve (AUROC), sensitivity, and specificity. The ML model was integrated into the TPS via a C# script. Script-guided reoptimization impact on PSQA and dosimetric results was evaluated on ten VMAT plans with "fail"-predicted arcs. Workload reduction potential was also assessed. RESULTS: The selected model exhibited an AUROC of 0.88, with a sensitivity and specificity exceeding 50 % and 90 %, respectively. The script-guided reoptimization of the ten evaluated plans led to an average improvement of 1.4 ± 0.9 percentage points in PSQA results, while preserving the quality of the dose distribution. A yearly savings of about 140 h with the use of the script was estimated. CONCLUSIONS: The proposed script is a valuable complementary tool for PSQA measurement. It was efficiently integrated into the clinical workflow to enhance PSQA outcomes and reduce PSQA workload by decreasing the risk of failing QA and thereby, the need for repeated replanning and measurements.

Repurposing of the multiciliation gene regulatory network in fate specification of Cajal-Retzius neurons.

Cajal-Retzius cells (CRs) are key players in cerebral cortex development, and they display a unique transcriptomic identity. Here, we use scRNA-seq to reconstruct the differentiation trajectory of mouse hem-derived CRs, and we unravel the transient expression of a complete gene module previously known to control multiciliogenesis. However, CRs do not undergo centriole amplification or multiciliation. Upon deletion of Gmnc, the master regulator of multiciliogenesis, CRs are initially produced but fail to reach their normal identity resulting in their massive apoptosis. We further dissect the contribution of multiciliation effector genes and identify Trp73 as a key determinant. Finally, we use in utero electroporation to demonstrate that the intrinsic competence of hem progenitors as well as the heterochronic expression of Gmnc prevent centriole amplification in the CR lineage. Our work exemplifies how the co-option of a complete gene module, repurposed to control a distinct process, may contribute to the emergence of novel cell identities.

Diversity within olfactory sensory derivatives revealed by the contribution of Dbx1 lineages.

In vertebrates, the embryonic olfactory epithelium contains progenitors that will give rise to distinct classes of neurons, including olfactory sensory neurons (OSNs; involved in odor detection), vomeronasal sensory neurons (VSNs; responsible for pheromone sensing), and gonadotropin-releasing hormone (GnRH) neurons that control the hypothalamic-pituitary-gonadal axis. Currently, these three neuronal lineages are usually believed to emerge from uniform pools of progenitors. Here, we found that the homeodomain transcription factor Dbx1 is expressed by neurogenic progenitors in the developing and adult mouse olfactory epithelium. We demonstrate that Dbx1 itself is dispensable for neuronal fate specification and global organization of the olfactory sensory system. Using lineage tracing, we characterize the contribution of Dbx1 lineages to OSN, VSN, and GnRH neuron populations and reveal an unexpected degree of diversity. Furthermore, we demonstrate that Dbx1-expressing progenitors remain neurogenic in the absence of the proneural gene Ascl1. Our work therefore points to the existence of distinct neurogenic programs in Dbx1-derived and other olfactory lineages.

p53/p21 pathway activation contributes to the ependymal fate decision downstream of GemC1.

Multiciliated ependymal cells and adult neural stem cells are components of the adult neurogenic niche, essential for brain homeostasis. These cells share a common glial cell lineage regulated by the Geminin family members Geminin and GemC1/Mcidas. Ependymal precursors require GemC1/Mcidas expression to massively amplify centrioles and become multiciliated cells. Here, we show that GemC1-dependent differentiation is initiated in actively cycling radial glial cells, in which a DNA damage response, including DNA replication-associated damage and dysfunctional telomeres, is induced, without affecting cell survival. Genotoxic stress is not sufficient by itself to induce ependymal cell differentiation, although the absence of p53 or p21 in progenitors hinders differentiation by maintaining cell division. Activation of the p53-p21 pathway downstream of GemC1 leads to cell-cycle slowdown/arrest, which permits timely onset of ependymal cell differentiation in progenitor cells.

Implementation of volumetric-modulated arc therapy for locally advanced breast cancer patients: Dosimetric comparison with deliverability consideration of planning techniques and predictions of patient-specific QA results via supervised machine learning.

PURPOSE: The aim of this study was to implement a clinically deliverable VMAT planning technique dedicated to advanced breast cancer, and to predict failed QA using a machine learning (ML) model to optimize the QA workload. METHODS: For three planning methods (2A: 2-partial arc, 2AS: 2-partial arc with splitting, 4A: 4-partial arc), dosimetric results were compared with patient-specific QA performed with the electronic portal imaging device of the linac. A dataset was built with the pass/fail status of the plans and complexity metrics. It was divided into training and testing sets. An ML metamodel combining predictions from six base classifiers was trained on the training set to predict plans as 'pass' or 'fail'. The predictive performances were evaluated using the unseen data of the testing set. RESULTS: The dosimetric comparison highlighted that 4A was the highest dosimetric performant method but also the poorest performant in the QA process. 2AS spared the best heart, but provided the highest dose to the contralateral breast and lowest node coverage. 2A provides a dosimetric compromise between organ at risk sparing and PTV coverage with satisfactory QA results. The metamodel had a median predictive sensitivity of 73% and a median specificity of 91%. CONCLUSIONS: The 2A method was selected to calculate clinically deliverable VMAT plans; however, the 2AS method was maintained when the heart was of particular importance and breath-hold techniques were not applicable. The metamodel provides promising predictive performance, and it is intended to be improved as a larger dataset becomes available.

Astrocytes close the mouse critical period for visual plasticity.

Brain postnatal development is characterized by critical periods of experience-dependent remodeling of neuronal circuits. Failure to end these periods results in neurodevelopmental disorders. The cellular processes defining critical-period timing remain unclear. Here, we show that in the mouse visual cortex, astrocytes control critical-period closure. We uncover the underlying pathway, which involves astrocytic regulation of the extracellular matrix, allowing interneuron maturation. Unconventional astrocyte connexin signaling hinders expression of extracellular matrix-degrading enzyme matrix metalloproteinase 9 (MMP9) through RhoA-guanosine triphosphatase activation. Thus, astrocytes not only influence the activity of single synapses but also are key elements in the experience-dependent wiring of brain circuits.

Single-cell transcriptomics of the early developing mouse cerebral cortex disentangle the spatial and temporal components of neuronal fate acquisition.

In the developing cerebral cortex, how progenitors that seemingly display limited diversity end up producing a vast array of neurons remains a puzzling question. The prevailing model suggests that temporal maturation of progenitors is a key driver in the diversification of the neuronal output. However, temporal constraints are unlikely to account for all diversity, especially in the ventral and lateral pallium where neuronal types significantly differ from their dorsal neocortical counterparts born at the same time. In this study, we implemented single-cell RNAseq to sample the diversity of progenitors and neurons along the dorso-ventral axis of the early developing pallium. We first identified neuronal types, mapped them on the tissue and determined their origin through genetic tracing. We characterised progenitor diversity and disentangled the gene modules underlying temporal versus spatial regulations of neuronal specification. Finally, we reconstructed the developmental trajectories followed by ventral and dorsal pallial neurons to identify lineage-specific gene waves. Our data suggest a model by which discrete neuronal fate acquisition from a continuous gradient of progenitors results from the superimposition of spatial information and temporal maturation.

The multiple facets of Cajal-Retzius neurons.

Cajal-Retzius neurons (CRs) are among the first-born neurons in the developing cortex of reptiles, birds and mammals, including humans. The peculiarity of CRs lies in the fact they are initially embedded into the immature neuronal network before being almost completely eliminated by cell death at the end of cortical development. CRs are best known for controlling the migration of glutamatergic neurons and the formation of cortical layers through the secretion of the glycoprotein reelin. However, they have been shown to play numerous additional key roles at many steps of cortical development, spanning from patterning and sizing functional areas to synaptogenesis. The use of genetic lineage tracing has allowed the discovery of their multiple ontogenetic origins, migratory routes, expression of molecular markers and death dynamics. Nowadays, single-cell technologies enable us to appreciate the molecular heterogeneity of CRs with an unprecedented resolution. In this Review, we discuss the morphological, electrophysiological, molecular and genetic criteria allowing the identification of CRs. We further expose the various sources, migration trajectories, developmental functions and death dynamics of CRs. Finally, we demonstrate how the analysis of public transcriptomic datasets allows extraction of the molecular signature of CRs throughout their transient life and consider their heterogeneity within and across species.

A GATE/Geant4 Monte Carlo toolkit for surface dose calculation in VMAT breast cancer radiotherapy.

The accuracy of superficial dose calculations for breast cancer treatments with Volumetric Modulated Arc Therapy (VMAT) is of major importance. For target volumes close to the surface, the inverse dosimetric planning can lead to very high fluences in the build-up region to properly cover the volume to be treated. Various radiotherapy modalities are currently used in parallel with additional protocols to enable a better control on the dose delivery (bolus, target volume margins). One of the difficulties currently facing medical physicists is the lack of available tools to test the impact of these different solutions on the superficial dose distribution. We present a new open source toolkit to assist medical physicists in evaluating the 3D distributions of superficial dose in VMAT breast cancer treatments. This tool is based on the GATE Monte Carlo software, a Geant4 application dedicated to medical physics. A set of macros has been developed to simulate in an easy way a full VMAT plan from the information available in the DICOM-RT files (image, plan, structure and dose). The toolkit has been tested on a 6 MV Varian NovalisTx™ accelerator. The paper presents a precise comparison of 3D surface dose distributions from experimental measurements (EBT3 films), TPS (Varian Eclipse) and Monte Carlo simulation (GATE). The comparison made it possible to highlight both the TPS biases for the surface dose calculation and the good performances of the developed toolkit. The simulation of surface dose distributions on a real patient has also been performed to illustrate the potential clinical applications.

18F-FDOPA PET/CT Combined with MRI for Gross Tumor Volume Delineation in Patients with Skull Base Paraganglioma.

In this simulation study, we assessed differences in gross tumor volume (GTV) in a series of skull base paragangliomas (SBPGLs) using magnetic resonance imaging (MRI), 18F-dihydroxyphenylalanine (18F-FDOPA) combined positron emission tomography/computed tomography (PET/CT), and 18F-FDOPA PET/MRI images obtained by rigid alignment of PET and MRI. GTV was delineated in 16 patients with SBPGLs on MRI (GTVMRI), 18F-FDOPA PET/CT (GTVPET), and combined PET/MRI (GTVPET/MRI). GTVPET/MRI was the union of GTVMRI and GTVPET after visual adjustment. Three observers delineated GTVMRI and GTVPET/MRI independently. Excellent interobserver reproducibility was found for both GTVMRI and GTVPET/MRI. GTVPET and GTVMRI were not significantly different. However, there was some spatial difference between the locations of GTVMRI, GTVPET, and GTVPET/MRI. The Dice similarity coefficient median value was 0.4 between PET/CT and MRI, and 0.8 between MRI and PET/MRI. The combined use of PET/MRI produced a larger GTV than MRI alone. Nevertheless, both the target-delivered dose and organs-at-risk conservancy were respected when treatment was planned on the PET/MRI-matched data set. Future integration of 18F-FDOPA PET/CT into clinical practice will be necessary to evaluate the influence of this diagnostic modality on SBPGL therapeutic management. If the clinical utility of 18F-FDOPA PET/CT and/or PET/MRI is confirmed, GTVPET/MRI should be considered for tailored radiotherapy planning in patients with SBPGL.

Comparative analysis of sequence covariation methods to mine evolutionary hubs: examples from selected GPCR families.

Covariation between positions in a multiple sequence alignment may reflect structural, functional, and/or phylogenetic constraints and can be analyzed by a wide variety of methods. We explored several of these methods for their ability to identify covarying positions related to the divergence of a protein family at different hierarchical levels. Specifically, we compared seven methods on a model system composed of three nested sets of G-protein-coupled receptors (GPCRs) in which a divergence event occurred. The covariation methods analyzed were based on: χ2 test, mutual information, substitution matrices, and perturbation methods. We first analyzed the dependence of the covariation scores on residue conservation (measured by sequence entropy), and then we analyzed the networking structure of the top pairs. Two methods out of seven--OMES (Observed minus Expected Squared) and ELSC (Explicit Likelihood of Subset Covariation)--favored pairs with intermediate entropy and a networking structure with a central residue involved in several high-scoring pairs. This networking structure was observed for the three sequence sets. In each case, the central residue corresponded to a residue known to be crucial for the evolution of the GPCR family and the subfamily specificity. These central residues can be viewed as evolutionary hubs, in relation with an epistasis-based mechanism of functional divergence within a protein family.

Multidimensional scaling reveals the main evolutionary pathways of class A G-protein-coupled receptors.

Class A G-protein-coupled receptors (GPCRs) constitute the largest family of transmembrane receptors in the human genome. Understanding the mechanisms which drove the evolution of such a large family would help understand the specificity of each GPCR sub-family with applications to drug design. To gain evolutionary information on class A GPCRs, we explored their sequence space by metric multidimensional scaling analysis (MDS). Three-dimensional mapping of human sequences shows a non-uniform distribution of GPCRs, organized in clusters that lay along four privileged directions. To interpret these directions, we projected supplementary sequences from different species onto the human space used as a reference. With this technique, we can easily monitor the evolutionary drift of several GPCR sub-families from cnidarians to humans. Results support a model of radiative evolution of class A GPCRs from a central node formed by peptide receptors. The privileged directions obtained from the MDS analysis are interpretable in terms of three main evolutionary pathways related to specific sequence determinants. The first pathway was initiated by a deletion in transmembrane helix 2 (TM2) and led to three sub-families by divergent evolution. The second pathway corresponds to the differentiation of the amine receptors. The third pathway corresponds to parallel evolution of several sub-families in relation with a covarion process involving proline residues in TM2 and TM5. As exemplified with GPCRs, the MDS projection technique is an important tool to compare orthologous sequence sets and to help decipher the mutational events that drove the evolution of protein families.