Radiation Therapy for Colorectal Liver Metastasis: The Effect of Radiation Therapy Dose and Chemotherapy on Local Control and Survival.

Purpose: Colorectal liver metastases (CLMs) represent a radioresistant histology. We aimed to investigate CLM radiation therapy (RT) outcomes and explore the association with treatment parameters.

Methods And Materials: This retrospective analysis of CLM treated with RT at Memorial Sloan Kettering Cancer Center used Kaplan-Meier analysis to estimate freedom from local progression (FFLP), hepatic progression-free, progression-free, and overall survival (OS).

Simulating the Potential of Model-Based Individualized Prescriptions for Ultracentral Lung Tumors.

Purpose: The use of stereotactic body radiation therapy for ultracentral lung tumors is limited by increased toxicity. We hypothesized that using published normal tissue complication probability (NTCP) and tumor control probability (TCP) models could improve the therapeutic ratio between tumor control and toxicity. A proposed model-based approach was applied to virtually replan early-stage non-small cell lung cancer (NSCLC) tumors.

ROE (Radiotherapy Outcomes Estimator): An open-source tool for optimizing radiotherapy prescriptions.

Background And Objectives: Radiotherapy prescriptions currently derive from population-wide guidelines established through large clinical trials. We provide an open-source software tool for patient-specific prescription determination using personalized dose-response curves.

Methods: We developed ROE, a plugin to the Computational Environment for Radiotherapy Research to visualize predicted tumor control and normal tissue complication simultaneously, as a function of prescription dose.

External validation of pulmonary radiotherapy toxicity models for ultracentral lung tumors.

Introduction: Pulmonary toxicity is dose-limiting in stereotactic body radiation therapy (SBRT) for tumors that abut the proximal bronchial tree (PBT), esophagus, or other mediastinal structures. In this work we explored published models of pulmonary toxicity following SBRT for such ultracentral tumors in an independent cohort of patients.

Methods: The PubMed database was searched for pulmonary toxicity models.

Radiomics artificial intelligence modelling for prediction of local control for colorectal liver metastases treated with radiotherapy.

Background And Purpose: Prognostic assessment of local therapies for colorectal liver metastases (CLM) is essential for guiding management in radiation oncology. Computed tomography (CT) contains liver texture information which may be predictive of metastatic environments. To investigate the feasibility of analyzing CT texture, we sought to build an automated model to predict progression-free survival using CT radiomics and artificial intelligence (AI).

Deep cross-modality (MR-CT) educed distillation learning for cone beam CT lung tumor segmentation.

Purpose: Despite the widespread availability of in-treatment room cone beam computed tomography (CBCT) imaging, due to the lack of reliable segmentation methods, CBCT is only used for gross set up corrections in lung radiotherapies. Accurate and reliable auto-segmentation tools could potentiate volumetric response assessment and geometry-guided adaptive radiation therapies. Therefore, we developed a new deep learning CBCT lung tumor segmentation method.

Salvage of locally recurrent breast cancer with repeat breast conservation using 45 Gy hyperfractionated partial breast re-irradiation.

Purpose: Mastectomy has long been the preferred approach for local salvage of recurrent breast cancer following breast-conservation therapy (BCT). Growing interest in avoiding mastectomy prompted RTOG 1014, a landmark phase two study demonstrating the feasibility of repeat BCT using a novel radiotherapy (RT) regimen (i.e.

Early Prediction of Acute Esophagitis for Adaptive Radiation Therapy.

Purpose: Acute esophagitis (AE) is a common dose-limiting toxicity in radiation therapy of locally advanced non-small cell lung cancer (LA-NSCLC). We developed an early AE prediction model from weekly accumulated esophagus dose and its associated local volumetric change.

Methods And Materials: Fifty-one patients with LA-NSCLC underwent treatment with intensity modulated radiation therapy to 60 Gy in 2-Gy fractions with concurrent chemotherapy and weekly cone beam computed tomography (CBCT).

Management of ipsilateral breast tumor recurrence following breast conservation surgery: a comparative study of re-conservation vs mastectomy.

Background: Breast conservation therapy (BCT) is well established for the management of primary operable breast cancer, with oncologic outcomes comparable to those of mastectomy. It remains unclear whether re-conservation therapy (RCT) is suitable for those patients who develop ipsilateral breast tumor recurrence (IBTR), for whom mastectomy is generally recommended.

Methods: We identified women who underwent BCT for invasive or ductal carcinoma in situ and developed IBTR as a first event, comparing the pattern of subsequent events and survival for those treated by RCT versus mastectomy.

Assessment of the treatment approach and survival outcomes in a modern cohort of patients with atypical teratoid rhabdoid tumors using the National Cancer Database.

Background: Atypical teratoid rhabdoid tumors (ATRTs) are rare brain tumors that occur primarily in children under the age of 3 years. This report evaluates the treatment approach and survival outcomes in a large cohort of patients treated in the United States.

Methods: Using the National Cancer Database, the analysis included all ATRT patients aged 0 to 18 years who were diagnosed between 2004 and 2012 and had complete treatment data.

Disparity in Outcomes for Adolescent and Young Adult Patients Diagnosed With Pediatric Solid Tumors Across 4 Decades.

Objective: Cancer mortality is a leading cause of disease-related death in the adolescent and young adult (AYA) population. Compared with older and younger patients, AYA patients often experience worse cancer-specific outcomes. Here, we compare AYA and pediatric overall survival (OS) in the most common pediatric extracranial solid tumors.

Concurrent Ramsay Hunt syndrome and disseminated herpes zoster in a patient with relapsed chronic lymphocytic leukemia.

Ramsay Hunt Syndrome (RHS) is a rare complication of latent varicella-zoster virus (VZV) infection that can occur in immunocompetent host. It usually involves ipsilateral facial paralysis, ear pain and facial vesicles. Disseminated herpes zoster is another complication of VZV infection typically seen in immunocompromised hosts.

Clinical evaluation of a model-updated image-guidance approach to brain shift compensation: experience in 16 cases.

Purpose: Brain shift during neurosurgical procedures must be corrected for in order to reestablish accurate alignment for successful image-guided tumor resection. Sparse-data-driven biomechanical models that predict physiological brain shift by accounting for typical deformation-inducing events such as cerebrospinal fluid drainage, hyperosmotic drugs, swelling, retraction, resection, and tumor cavity collapse are an inexpensive solution. This study evaluated the robustness and accuracy of a biomechanical model-based brain shift correction system to assist with tumor resection surgery in 16 clinical cases.

A CDC20-APC/SOX2 Signaling Axis Regulates Human Glioblastoma Stem-like Cells.

Glioblastoma harbors a dynamic subpopulation of glioblastoma stem-like cells (GSCs) that can propagate tumors in vivo and is resistant to standard chemoradiation. Identification of the cell-intrinsic mechanisms governing this clinically important cell state may lead to the discovery of therapeutic strategies for this challenging malignancy. Here, we demonstrate that the mitotic E3 ubiquitin ligase CDC20-anaphase-promoting complex (CDC20-APC) drives invasiveness and self-renewal in patient tumor-derived GSCs.

Integrating Retraction Modeling Into an Atlas-Based Framework for Brain Shift Prediction.

In recent work, an atlas-based statistical model for brain shift prediction, which accounts for uncertainty in the intraoperative environment, has been proposed. Previous work reported in the literature using this technique did not account for local deformation caused by surgical retraction. It is challenging to precisely localize the retractor location prior to surgery and the retractor is often moved in the course of the procedure.

Intraoperative brain shift compensation: accounting for dural septa.

Biomechanical models that describe soft tissue deformation provide a relatively inexpensive way to correct registration errors in image-guided neurosurgical systems caused by nonrigid brain shift. Quantifying the factors that cause this deformation to sufficient precision is a challenging task. To circumvent this difficulty, atlas-based methods have been developed recently that allow for uncertainty, yet still capture the first-order effects associated with deformation.