Unsupervised Bayesian generation of synthetic CT from CBCT using patient-specific score-based prior.

Background: Cone-beam computed tomography (CBCT) scans, performed fractionally (e.g., daily or weekly), are widely utilized for patient alignment in the image-guided radiotherapy (IGRT) process, thereby making it a potential imaging modality for the implementation of adaptive radiotherapy (ART) protocols.

Primary lung tumour stereotactic body radiotherapy followed by concurrent mediastinal chemoradiotherapy and adjuvant immunotherapy for locally advanced non-small-cell lung cancer: a multicentre, single-arm, phase 2 trial.

Background: Patients with locally advanced non-small-cell lung cancer (NSCLC) who undergo concurrent chemotherapy and radiotherapy often experience synergistic toxicity, and local regional control rates remain poor. We assessed the activity and safety outcomes of primary tumour stereotactic body radiotherapy (SBRT) followed by conventional chemoradiotherapy to the lymph nodes and consolidation immunotherapy in patients with unresectable locally advanced NSCLC.

Methods: In this multicentre, single-arm, phase 2 trial, patients aged 18 years and older were enrolled at eight regional cancer centres in North Carolina and South Carolina, USA.

Dosimetric comparison between laterality-specific and general knowledge-based planning models for nonsmall cell lung cancer.

To investigate the dosimetric impact of laterality-specific RapidPlan models for nonsmall cell lung cancer. Three RapidPlan models were developed and validated for Right, Left, and General conventional lung radiotherapy. Each model was trained using 50 plans.

Metabolic modulation of melanoma enhances the therapeutic potential of immune checkpoint inhibitors.

Introduction: Lactate is a pivotal molecule with diverse functions in the metabolic reprogramming of cancer cells. Beyond its role in metabolism, lactate exerts a modulatory effect within the tumor microenvironment; it is utilized by stromal cells and has been implicated in the suppression of the immune response against the tumor.

Methods: Using assays (including flow cytometry, live-cell imaging and metabolic analyses), the impact of lactate dehydrogenase inhibitors (LDHIs) on melanoma cells were assessed.

Pre-operative stereotactic radiosurgery and peri-operative dexamethasone for resectable brain metastases: a two-arm pilot study evaluating clinical outcomes and immunological correlates.

Enhancing the efficacy of immunotherapy in brain metastases (BrM) requires an improved understanding of the immune composition of BrM and how this is affected by radiation and dexamethasone. Our two-arm pilot study (NCT04895592) allocated 26 patients with BrM to either low (Arm A) or high (Arm B) dose peri-operative dexamethasone followed by pre-operative stereotactic radiosurgery (pSRS) and resection (n= 13 per arm). The primary endpoint, a safety analysis at 4 months, was met.

Lung SBRT: Dose gradient optimization based on target size.

This study investigated optimization settings that steepen the dose gradient as a function of target size for lung stereotactic body radiation therapy (SBRT). Sixty-eight lung SBRT patients with planning target volumes (PTVs) ranging from 2-203 cc were categorized into small (<20 cc), medium (20-50 cc), and large (>50 cc) groups. VMAT plans were generated using the normal tissue objective (NTO) to penalize the dose gradient at progressively steeper NTO fall-off values (0.

A lung SBRT treatment planning technique to focus high dose on gross disease.

This study investigated a straightforward treatment planning technique for definitive stereotactic body radiation therapy (SBRT) for patients with early-stage lung cancer aimed at increasing dose to gross disease by strategically penalizing the normal tissue objective (NTO) in the Eclipse treatment planning system. Twenty-five SBRT cases were replanned to 50 Gy in 5 fractions using static and dynamic NTO methods (50 plans total). The NTO had a start dose of 100% at the target border, end dose of 20%, fall-off rate of 0.

CBCT-based synthetic CT image generation using a diffusion model for CBCT-guided lung radiotherapy.

Background: Although cone beam computed tomography (CBCT) has lower resolution compared to planning CTs (pCT), its lower dose, higher high-contrast resolution, and shorter scanning time support its widespread use in clinical applications, especially in ensuring accurate patient positioning during the image-guided radiation therapy (IGRT) process.

Purpose: While CBCT is critical to IGRT, CBCT image quality can be compromised by severe stripe and scattering artifacts. Tumor movement secondary to respiratory motion also decreases CBCT resolution.

Unsupervised Bayesian Generation of Synthetic CT from CBCT Using Patient-Specific Score-Based Prior.

Background: Cone-beam computed tomography (CBCT) scans, performed fractionally (e.g., daily or weekly), are widely utilized for patient alignment in the image-guided radiotherapy (IGRT) process, thereby making it a potential imaging modality for the implementation of adaptive radiotherapy (ART) protocols.

Immune System Dose With Proton Versus Photon Radiotherapy for Treatment of Locally Advanced NSCLC.

Purpose: Emerging data have illuminated the impact of effective radiation dose to immune cells (EDIC) on outcomes in patients with locally advanced, unresectable non-small cell lung cancer (NSCLC) treated with intensity-modulated radiotherapy (IMRT). Hypothesizing that intensity-modulated proton therapy (IMPT) may reduce EDIC versus IMRT, we conducted a dosimetric analysis of patients treated at our institution.

Materials And Methods: Data were retrospectively collected for 12 patients with locally advanced, unresectable NSCLC diagnosed between 2019 and 2021 who had physician-approved IMRT and IMPT plans.

Cardiac MRI segmentation using shifted-window multilayer perceptron mixer networks.

. In this work, we proposed a deep-learning segmentation algorithm for cardiac magnetic resonance imaging to aid in contouring of the left ventricle, right ventricle, and Myocardium (Myo).We proposed a shifted window multilayer perceptron (Swin-MLP) mixer network which is built upon a 3D U-shaped symmetric encoder-decoder structure.

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).

Deformable lung 4DCT image registration via landmark-driven cycle network.

Background: An automated, accurate, and efficient lung four-dimensional computed tomography (4DCT) image registration method is clinically important to quantify respiratory motion for optimal motion management.

Purpose: The purpose of this work is to develop a weakly supervised deep learning method for 4DCT lung deformable image registration (DIR).

Methods: The landmark-driven cycle network is proposed as a deep learning platform that performs DIR of individual phase datasets in a simulation 4DCT.

Safety and efficacy of durvalumab after concurrent chemoradiation in Black patients with locally advanced non-small cell lung cancer.

Background: The PACIFIC trial established consolidative durvalumab after concurrent chemoradiation as standard-of-care in patients with stage III or unresectable non-small cell lung cancer (NSCLC). Black patients, however, comprised just 2% (n = 14) of randomized patients in this trial, warranting real-world evaluation of the PACIFIC regimen in these patients.

Methods: This single-institution, multi-site study included 105 patients with unresectable stage II/III NSCLC treated with concurrent chemoradiation followed by durvalumab between 2017 and 2021.

Deep learning-based fast volumetric imaging using kV and MV projection images for lung cancer radiotherapy: A feasibility study.

Purpose: The long acquisition time of CBCT discourages repeat verification imaging, therefore increasing treatment uncertainty. In this study, we present a fast volumetric imaging method for lung cancer radiation therapy using an orthogonal 2D kV/MV image pair.

Methods: The proposed model is a combination of 2D and 3D networks.

The mitochondrial pyruvate carrier complex potentiates the efficacy of proteasome inhibitors in multiple myeloma.

Multiple myeloma (MM) is a hematological malignancy that emerges from antibody-producing plasma B cells. Proteasome inhibitors, including the US Food and Drug Administration-approved bortezomib (BTZ) and carfilzomib (CFZ), are frequently used for the treatment of patients with MM. Nevertheless, a significant proportion of patients with MM are refractory or develop resistance to this class of inhibitors, which represents a significant challenge in the clinic.

Definitive intensity modulated proton re-irradiation for lung cancer in the immunotherapy era.

Introduction: As immunotherapy has improved distant metastasis-free survival (DMFS) in Non-Small Cell Lung Cancer (NSCLC), isolated locoregional recurrences have increased. However, management of locoregional recurrences can be challenging. We report our institutional experience with definitive intent re-irradiation using Intensity Modulated Proton Therapy (IMPT).

Compact portable sources of high-LET radiation: Validation and potential application for galactic cosmic radiation countermeasure discovery.

Implementation of a systematic program for galactic cosmic radiation (GCR) countermeasure discovery will require convenient access to ground-based space radiation analogs. The current gold standard approach for GCR simulation is to use a particle accelerator for sequential irradiation with ion beams representing different GCR components. This has limitations, particularly for studies of non-acute responses, strategies that require robotic instrumentation, or implementation of complex in vitro models that are emerging as alternatives to animal experimentation.

Automated lung tumor delineation on positron emission tomography/computed tomography via a hybrid regional network.

Background: Multimodality positron emission tomography/computed tomography (PET/CT) imaging combines the anatomical information of CT with the functional information of PET. In the diagnosis and treatment of many cancers, such as non-small cell lung cancer (NSCLC), PET/CT imaging allows more accurate delineation of tumor or involved lymph nodes for radiation planning.

Purpose: In this paper, we propose a hybrid regional network method of automatically segmenting lung tumors from PET/CT images.

Impact of radiation dose to the immune cells in unresectable or stage III non-small cell lung cancer in the durvalumab era.

Background/purpose: Higher estimated radiation doses to immune cells (EDIC) have correlated with worse overall survival (OS) in patients with locally-advanced non-small cell lung cancer (NSCLC) prior to the PACIFIC trial, which established consolidative durvalumab as standard-of-care. Here, we examine the prognostic impact of EDIC in the durvalumab era.

Materials/methods: This single-institution, multi-center study included patients with unresectable stage II/III NSCLC treated with chemoradiation followed by durvalumab.

Race, Ethnicity, and Sex Among Senior Faculty in Radiation Oncology From 2000 to 2019.

This cross-sectional study investigates intersections among race, ethnicity, and sex from 2000 to 2019 among senior faculty in radiation oncology.

Metabolic response to radiation therapy in cancer.

Tumor metabolism has emerged as a hallmark of cancer and is involved in carcinogenesis and tumor growth. Reprogramming of tumor metabolism is necessary for cancer cells to sustain high proliferation rates and enhanced demands for nutrients. Recent studies suggest that metabolic plasticity in cancer cells can decrease the efficacy of anticancer therapies by enhancing antioxidant defenses and DNA repair mechanisms.

Deep learning-based thoracic CBCT correction with histogram matching.

Kilovoltage cone-beam computed tomography (CBCT)-based image-guided radiation therapy (IGRT) is used for daily delivery of radiation therapy, especially for stereotactic body radiation therapy (SBRT), which imposes particularly high demands for setup accuracy. The clinical applications of CBCTs are constrained, however, by poor soft tissue contrast, image artifacts, and instability of Hounsfield unit (HU) values. Here, we propose a new deep learning-based method to generate synthetic CTs (sCT) from thoracic CBCTs.