Optimization-based image reconstruction regularized with inter-spectral structural similarity for limited-angle dual-energy cone-beam CT.

. Limited-angle dual-energy (DE) cone-beam CT (CBCT) is considered as a potential solution to achieve fast and low-dose DE imaging on current CBCT scanners without hardware modification. However, its clinical implementations are hindered by the challenging image reconstruction from limited-angle projections.

MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shifting.

Magnetic resonance imaging (MRI) is essential in clinical and research contexts, providing exceptional soft-tissue contrast. However, prolonged acquisition times often lead to patient discomfort and motion artifacts. Diffusion-based deep learning super-resolution (SR) techniques reconstruct high-resolution (HR) images from low-resolution (LR) pairs, but they involve extensive sampling steps, limiting real-time application.

Combination radiation and αPD-L1 enhance tumor control by stimulating CD8+ PD-1+ TCF-1+ T cells in the tumor-draining lymph node.

Combination radiotherapy (RT) and αPD-L1 therapy has potential to enhance local and distant (abscopal) tumor control, however, clinical results in humans have been variable. Using murine melanoma models, we found RT + αPD-L1 increases intra-tumor progenitor CD8+ PD-1+ TCF-1+ T cells. This increase depends on trafficking of the PD-1+ TCF-1+ cells from the tumor-draining lymph node (TdLN) to the tumor.

Triad: Vision Foundation Model for 3D Magnetic Resonance Imaging.

Vision foundation models (VFMs) are pre-trained on extensive image datasets to learn general representations for diverse types of data. These models can subsequently be fine-tuned for specific downstream tasks, significantly boosting performance across a broad range of applications. However, existing vision foundation models that claim to be applicable to various clinical tasks are mostly pre-trained on 3D computed tomography (CT), which benefits from the availability of extensive 3D CT databases.

MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shifting.

Objective: Magnetic resonance imaging (MRI) is essential in clinical and research contexts, providing exceptional soft-tissue contrast. However, prolonged acquisition times often lead to patient discomfort and motion artifacts. Diffusion-based deep learning super-resolution (SR) techniques reconstruct high-resolution (HR) images from low-resolution (LR) pairs, but they involve extensive sampling steps, limiting real-time application.

A Physics-Informed Deep Learning Model for MRI Brain Motion Correction.

Background: Magnetic resonance imaging (MRI) is an essential brain imaging tool, but its long acquisition times make it highly susceptible to motion artifacts that can degrade diagnostic quality.

Purpose: This work aims to develop and evaluate a novel physics-informed motion correction network, termed PI-MoCoNet, which leverages complementary information from both the spatial and -space domains. The primary goal is to robustly remove motion artifacts from high-resolution brain MRI images without explicit motion parameter estimation, thereby preserving image fidelity and enhancing diagnostic reliability.

Automatic medical imaging segmentation via self-supervising large-scale convolutional neural networks.

Purpose: This study aims to develop a robust, large-scale deep learning model for medical image segmentation, leveraging self-supervised learning to overcome the limitations of supervised learning and data variability in clinical settings.

Methods And Materials: We curated a substantial multi-center CT dataset for self-supervised pre-training using masked image modeling with sparse submanifold convolution. We designed a series of Sparse Submanifold U-Nets (SS-UNets) of varying sizes and performed self-supervised pre-training.

Exploration of an adaptive proton therapy strategy using CBCT with the concept of digital twins.

This study aims to develop a digital twin (DT) framework to achieve adaptive proton prostate stereotactic body radiation therapy (SBRT) with fast treatment plan selection and patient-specific clinical target volume (CTV) setup uncertainty. Prostate SBRT has emerged as a leading option for external beam radiotherapy due to its effectiveness and reduced treatment duration. However, interfractional anatomy variations can impact treatment outcomes.

T1-contrast enhanced MRI generation from multi-parametric MRI for glioma patients with latent tumor conditioning.

Background: Gadolinium-based contrast agents (GBCAs) are commonly used in MRI scans of patients with gliomas to enhance brain tumor characterization using T1-weighted (T1W) MRI. However, there is growing concern about GBCA toxicity. This study develops a deep-learning framework to generate T1-postcontrast (T1C) from pre-contrast multiparametric MRI.

Loss of tet methyl cytosine dioxygenase 3 (TET3) enhances cardiac fibrosis via modulating the DNA damage repair response.

Background: Cardiac fibrosis is the hallmark of all forms of chronic heart disease. Activation and proliferation of cardiac fibroblasts are the prime mediators of cardiac fibrosis. Existing studies show that ROS and inflammatory cytokines produced during fibrosis not only signal proliferative stimuli but also contribute to DNA damage.

PD-L1 deglycosylation promotes its nuclear translocation and accelerates DNA double-strand-break repair in cancer.

Resistance to radiotherapy is a major barrier during cancer treatment. Here using genome-scale CRISPR/Cas9 screening, we identify CD274 gene, which encodes PD-L1, to confer lung cancer cell resistance to ionizing radiation (IR). Depletion of endogenous PD-L1 delays the repair of IR-induced DNA double-strand breaks (DSBs) and PD-L1 loss downregulates non-homologous end joining (NHEJ) while overexpression of PD-L1 upregulates NHEJ.

Adaptive Proton Therapy Using CBCT-Guided Digital Twins.

This study aims to develop a digital twin (DT) framework to enhance adaptive proton stereotactic body radiation therapy (SBRT) for prostate cancer. Prostate SBRT has emerged as a leading option for external beam radiotherapy due to its effectiveness and reduced treatment duration. However, interfractional anatomy variations can impact treatment outcomes.

Radiation and anti-PD-L1 synergize by stimulating a stem-like T cell population in the tumor-draining lymph node.

Radiotherapy (RT) and anti-PD-L1 synergize to enhance local and distant (abscopal) tumor control. However, clinical results in humans have been variable. With the goal of improving clinical outcomes, we investigated the underlying synergistic mechanism focusing on a CD8+ PD-1+ Tcf-1+ stem-like T cell subset in the tumor-draining lymph node (TdLN).

ATR signaling controls the bystander responses of human chondrosarcoma cells by promoting RAD51-dependent DNA repair.

Purpose: Radiation-induced bystander effect (RIBE) frequently is seen as DNA damage in unirradiated bystander cells, but the repair processes initiated in response to that DNA damage are not well understood. RIBE-mediated formation of micronuclei (MN), a biomarker of persistent DNA damage, was previously observed in bystander normal fibroblast (AG01522) cells, but not in bystander human chondrosarcoma (HTB94) cells. The molecular mechanisms causing this disparity are not clear.

SAMHD1 expression contributes to doxorubicin resistance and predicts survival outcomes in diffuse large B-cell lymphoma patients.

Diffuse large B-cell lymphoma (DLBCL) is a commonly diagnosed, aggressive non-Hodgkin's lymphoma. While R-CHOP chemoimmunotherapy is potentially curative, about 40% of DLBCL patients will fail, highlighting the need to identify biomarkers to optimize management. SAMHD1 has a dNTPase-independent role in promoting resection to facilitate DNA double-strand break (DSB) repair by homologous recombination.

A retrospective study on the investigation of potential dosimetric benefits of online adaptive proton therapy for head and neck cancer.

Purpose: Proton therapy is sensitive to anatomical changes, often occurring in head-and-neck (HN) cancer patients. Although multiple studies have proposed online adaptive proton therapy (APT), there is still a concern in the radiotherapy community about the necessity of online APT. We have performed a retrospective study to investigate the potential dosimetric benefits of online APT for HN patients relative to the current offline APT.

The putative RNA helicase DDX1 associates with the nuclear RNA exosome and modulates RNA/DNA hybrids (R-loops).

The RNA exosome is a ribonuclease complex that mediates both RNA processing and degradation. This complex is evolutionarily conserved, ubiquitously expressed, and required for fundamental cellular functions, including rRNA processing. The RNA exosome plays roles in regulating gene expression and protecting the genome, including modulating the accumulation of RNA-DNA hybrids (R-loops).

Streamlined pin-ridge-filter design for single-energy proton FLASH planning.

Background: FLASH radiotherapy (FLASH-RT) with ultra-high dose rate has yielded promising results in reducing normal tissue toxicity while maintaining tumor control. Planning with single-energy proton beams modulated by ridge filters (RFs) has been demonstrated feasible for FLASH-RT.

Purpose: This study explored the feasibility of a streamlined pin-shaped RF (pin-RF) design, characterized by coarse resolution and sparsely distributed ridge pins, for single-energy proton FLASH planning.

HELZ promotes R loop resolution to facilitate DNA double-strand break repair by homologous recombination.

R loops are RNA-DNA hybrid containing structures involved in diverse cellular processes, including DNA double-strand break (DSB) repair. R loop homeostasis involving the formation and resolution of R loops is critical for DSB repair, and its dysregulation leads to genome instability. Here we show that the HELZ helicase promotes R loop resolution to facilitate DSB repair by homologous recombination (HR).

Synthetic CT generation from MRI using 3D transformer-based denoising diffusion model.

Background And Purpose: Magnetic resonance imaging (MRI)-based synthetic computed tomography (sCT) simplifies radiation therapy treatment planning by eliminating the need for CT simulation and error-prone image registration, ultimately reducing patient radiation dose and setup uncertainty. In this work, we propose a MRI-to-CT transformer-based improved denoising diffusion probabilistic model (MC-IDDPM) to translate MRI into high-quality sCT to facilitate radiation treatment planning.

Methods: MC-IDDPM implements diffusion processes with a shifted-window transformer network to generate sCT from MRI.

Streamlined Pin-Ridge-Filter Design for Single-energy Proton FLASH Planning.

Purpose: This study explored the feasibility of a streamlined pin-shaped ridge filter (pin-RF) design for single-energy proton FLASH planning.

Methods: An inverse planning framework integrated within a TPS was established for FLASH planning. The framework involves generating a IMPT plan based on downstream energy modulation strategy (IMPT-DS), followed by a nested spot reduction process to iteratively reduce the total number of pencil beam directions (PBDs) and energy layers along each PBD for the IMPT-DS plan.

DNA-PK is activated by SIRT2 deacetylation to promote DNA double-strand break repair by non-homologous end joining.

DNA-dependent protein kinase (DNA-PK) plays a critical role in non-homologous end joining (NHEJ), the predominant pathway that repairs DNA double-strand breaks (DSB) in response to ionizing radiation (IR) to govern genome integrity. The interaction of the catalytic subunit of DNA-PK (DNA-PKcs) with the Ku70/Ku80 heterodimer on DSBs leads to DNA-PK activation; however, it is not known if upstream signaling events govern this activation. Here, we reveal a regulatory step governing DNA-PK activation by SIRT2 deacetylation, which facilitates DNA-PKcs localization to DSBs and interaction with Ku, thereby promoting DSB repair by NHEJ.