Stereotactic radiosurgery for intracranial and spinal adenoid cystic carcinoma: systematic review and illustrative case presentation.

Purpose: Adenoid cystic carcinoma (ACC) is a rare, aggressive malignancy with a predilection for perineural spread and distant metastases. Given the limited but emerging evidence on the role of stereotactic radiosurgery (SRS) in managing intracranial and spinal ACC, a systematic review was deemed necessary to synthesize relevant parameters related to clinical features and management of ACC patients, SRS treatment characteristics, and clinical outcomes across published studies.

Methods: This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

A Comprehensive Review of Arachnoid Cysts.

Arachnoid cysts are cerebrospinal fluid (CSF)-filled sacs that develop within the arachnoid membrane surrounding the brain or spinal cord, often remaining asymptomatic but occasionally causing neurological symptoms due to mass effect or CSF flow obstruction. The optimal management of these cysts remains debated, balancing conservative observation with surgical intervention. This review analyzes the epidemiology, pathophysiology, clinical presentation, diagnostic strategies, treatment options, and future management directions for arachnoid cysts.

Parametric response mapping of co-registered intravoxel incoherent motion magnetic resonance imaging and positron emission tomography in locally advanced cervical cancer undergoing concurrent chemoradiation therapy.

Background And Purpose: Intravoxel-incoherent-motion (IVIM) magnetic-resonance-imaging (MRI) and positron-emission-tomography (PET) have been investigated independently but not voxel-wise to evaluate tumor microenvironment in cervical carcinoma patients. Whether regionally combined information of IVIM and PET offers additional predictive benefit over each modality independently has not been explored. Here, we investigated parametric-response-mapping (PRM) of co-registered PET and IVIM in cervical cancer patients to identify sub-volumes that may predict tumor shrinkage to concurrent-chemoradiation-therapy (CCRT).

Where Does Auto-Segmentation for Brain Metastases Radiosurgery Stand Today?

Detection and segmentation of brain metastases (BMs) play a pivotal role in diagnosis, treatment planning, and follow-up evaluations for effective BM management. Given the rising prevalence of BM cases and its predominantly multiple onsets, automated segmentation is becoming necessary in stereotactic radiosurgery. It not only alleviates the clinician's manual workload and improves clinical workflow efficiency but also ensures treatment safety, ultimately improving patient care.

Automated contouring, treatment planning, and quality assurance for VMAT craniospinal irradiation (VMAT-CSI).

Purpose: Create a comprehensive automated solution for pediatric and adult VMAT-CSI including contouring, planning, and plan check to reduce planning time and improve plan quality.

Methods: Seventy-seven previously treated CSI patients (age, 2-67 years) were used for creation of an auto-contouring model to segment 25 organs at risk (OARs). The auto-contoured OARs were evaluated using the Dice Similarity Coefficient (DSC), 95% Hausdorff Distance (HD95), and a qualitative ranking by one physician and one physicist (scale: 1-acceptable, 2-minor edits, 3-major edits).

Automating the Treatment Planning Process for Volumetric Modulated Arc Therapy Craniospinal Irradiation.

Purpose: The purpose of this work is to develop a method to automate the treatment planning process of craniospinal irradiation (CSI) using volumetric modulated arc therapy.

Methods And Materials: Two scripts were developed using the Eclipse Scripting Application Programming Interface to perform auto-plan preparation and optimization. Ten patients (age, 5-44 years) previously treated at our institution with low dose volumetric modulated arc therapy CSI (prescription of 12 Gy) before total body irradiation were selected to evaluate the efficacy of the proposed auto-planning process.

Biology-guided deep learning predicts prognosis and cancer immunotherapy response.

Substantial progress has been made in using deep learning for cancer detection and diagnosis in medical images. Yet, there is limited success on prediction of treatment response and outcomes, which has important implications for personalized treatment strategies. A significant hurdle for clinical translation of current data-driven deep learning models is lack of interpretability, often attributable to a disconnect from the underlying pathobiology.

Non-invasive tumor microenvironment evaluation and treatment response prediction in gastric cancer using deep learning radiomics.

The tumor microenvironment (TME) plays a critical role in disease progression and is a key determinant of therapeutic response in cancer patients. Here, we propose a noninvasive approach to predict the TME status from radiological images by combining radiomics and deep learning analyses. Using multi-institution cohorts of 2,686 patients with gastric cancer, we show that the radiological model accurately predicted the TME status and is an independent prognostic factor beyond clinicopathologic variables.

Adaptive Region-Specific Loss for Improved Medical Image Segmentation.

Defining the loss function is an important part of neural network design and critically determines the success of deep learning modeling. A significant shortcoming of the conventional loss functions is that they weight all regions in the input image volume equally, despite the fact that the system is known to be heterogeneous (i.e.

Learning image representations for content-based image retrieval of radiotherapy treatment plans.

In this work, we propose a content-based image retrieval (CBIR) method for retrieving dose distributions of previously planned patients based on anatomical similarity. Retrieved dose distributions from this method can be incorporated into automated treatment planning workflows in order to streamline the iterative planning process. As CBIR has not yet been applied to treatment planning, our work seeks to understand which current machine learning models are most viable in this context.

Stratified assessment of an FDA-cleared deep learning algorithm for automated detection and contouring of metastatic brain tumors in stereotactic radiosurgery.

Purpose: Artificial intelligence-based tools can be leveraged to improve detection and segmentation of brain metastases for stereotactic radiosurgery (SRS). VBrain by Vysioneer Inc. is a deep learning algorithm with recent FDA clearance to assist in brain tumor contouring.

Leveraging data-driven self-consistency for high-fidelity gene expression recovery.

Single cell RNA sequencing is a promising technique to determine the states of individual cells and classify novel cell subtypes. In current sequence data analysis, however, genes with low expressions are omitted, which leads to inaccurate gene counts and hinders downstream analysis. Recovering these omitted expression values presents a challenge because of the large size of the data.

Local control of brain metastases with osimertinib alone in patients with EGFR-mutant non-small cell lung cancer.

Purpose: Although osimertinib has excellent intracranial activity in metastatic non-small cell lung cancer (NSCLC) with exon 19 deletion or L858R EGFR alterations, measures of local control of brain metastases are less well-reported. We describe lesion-level outcomes of brain metastases treated with osimertinib alone.

Methods: We retrospectively reviewed patients with EGFR-mutant NSCLC with untreated brain metastasis measuring ≥ 5 mm at the time of initiating osimertinib.

Genotype/Phenotype Interactions and First Steps Toward Targeted Therapy for Sphingosine Phosphate Lyase Insufficiency Syndrome.

Sphingosine-1-phosphate lyase insufficiency syndrome (SPLIS) is a rare metabolic disorder caused by a deficiency in sphingosine-1-phosphate lyase (SPL), the final enzyme in the sphingolipid degradative pathway. Inactivating mutations of SGPL1-the gene encoding SPL-lead to a deficiency of its downstream products, and buildup of sphingolipid intermediates, including its bioactive substrate, sphingosine-1-phosphate (S1P), the latter causing lymphopenia, a hallmark of the disease. Other manifestations of SPLIS include nephrotic syndrome, neuronal defects, and adrenal insufficiency, but their pathogenesis remains unknown.

Efficacy of AAV9-mediated SGPL1 gene transfer in a mouse model of S1P lyase insufficiency syndrome.

Sphingosine-1-phosphate lyase insufficiency syndrome (SPLIS) is a rare metabolic disorder caused by inactivating mutations in sphingosine-1-phosphate lyase 1 (SGPL1), which is required for the final step of sphingolipid metabolism. SPLIS features include steroid-resistant nephrotic syndrome and impairment of neurological, endocrine, and hematopoietic systems. Many affected individuals die within the first 2 years.

Postsynaptic Y654 dephosphorylation of β-catenin modulates presynaptic vesicle turnover through increased n-cadherin-mediated transsynaptic signaling.

Synaptic adhesion molecules, which coordinately control structural and functional changes at both sides of synapses, are important for synaptogenesis and synaptic plasticity. Because they physically form homophilic or heterophilic adhesions across synaptic junctions, these molecules can initiate transsynaptic communication in both anterograde and retrograde directions. Using optical imaging approaches, we investigated whether an increase in postsynaptic N-cadherin could correspondingly alter the function of connected presynaptic terminals.

N-Cadherin Regulates Cell Migration Through a Rab5-Dependent Temporal Control of Macropinocytosis.

Macropinocytosis is a clathrin-independent endocytic pathway implicated in fluid uptake, pathogen invasion and cell migration. During collective cell migration, macropinocytosis occurs primarily at membrane ruffles arising from the leading edges of migrating cells. We report here that N-cadherin (Ncad) regulates the tempo of macropinocytosis and thereby influences wound-induced collective cell migration.

Autographa californica multiple nucleopolyhedrovirus LEF-2 is a capsid protein required for amplification but not initiation of viral DNA replication.

The late expression factor 2 gene (lef-2) of baculovirus Autographa californica multiple nucleopolyhedrovirus (AcMNPV) has been identified as one of the factors essential for origin-dependent DNA replication in transient expression assays and has been shown to be involved in late/very late gene expression. To study the function of lef-2 in the life cycle of AcMNPV, lef-2 knockout and repair bacmids were generated by homologous recombination in Escherichia coli. Growth curve analysis showed that lef-2 was essential for virus production.

A functional genomics approach to identify and characterize oxidation resistance genes.

In order to develop a more complete understanding of the genes required for resistance to oxidative DNA damage, we devised methods to identify genes that can prevent or repair oxidative DNA damage. These methods use the oxidative mutator phenotype of a repair deficient E. coli strain to measure the antimutator effect resulting from the expression of human cDNAs.

Identification of baculoviral factors required for the activation of enhancer-like polyhedrin upstream (pu) sequence.

Previously, we identified a novel enhancer-like element, the polyhedrin upstream (pu) sequence, in the genome of the baculovirus Autographa californica multiple nucleopolyhedrovirus (AcMNPV), which activates several early promoters. The activation requires co-infection of AcMNPV, suggesting that viral gene products are needed for pu-mediated promoter activation. DNA replication assay showed that the pu sequence did not assist in DNA replication and suggested its involvement in activated transcription from target promoters.

The single-strand DNA binding activity of human PC4 prevents mutagenesis and killing by oxidative DNA damage.

Human positive cofactor 4 (PC4) is a transcriptional coactivator with a highly conserved single-strand DNA (ssDNA) binding domain of unknown function. We identified PC4 as a suppressor of the oxidative mutator phenotype of the Escherichia coli fpg mutY mutant and demonstrate that this suppression requires its ssDNA binding activity. Saccharomyces cerevisiae mutants lacking their PC4 ortholog Sub1 are sensitive to hydrogen peroxide and exhibit spontaneous and peroxide-induced hypermutability.