Comparison of Vendor-Pretrained and Custom-Trained Deep Learning Segmentation Models for Head-and-Neck, Breast, and Prostate Cancers.

Background/objectives: We assessed the influence of local patients and clinical characteristics on the performance of commercial deep learning (DL) segmentation models for head-and-neck (HN), breast, and prostate cancers.

Methods: Clinical computed tomography (CT) scans and clinically approved contours of 210 patients (53 HN, 49 left breast, 55 right breast, and 53 prostate cancer) were used to train and validate segmentation models integrated within a vendor-supplied DL training toolkit and to assess the performance of both vendor-pretrained and custom-trained models. Four custom models (HN, left breast, right breast, and prostate) were trained and validated with 30 (training)/5 (validation) HN, 34/5 left breast, 39/5 right breast, and 30/5 prostate patients to auto-segment a total of 24 organs at risk (OARs).

Effects of Multiple Factors on the Compressive Strength of Porous Ceramsite Prepared from Secondary Aluminum Dross.

Aluminum is one of the most in-demand nonferrous metals in the world. The secondary aluminum dross (SAD) produced during aluminum smelting is a type of solid waste that urgently requires disposal. SAD, municipal solid waste incineration fly ash, and bottom slag were used as raw materials to prepare porous ceramsite in a laboratory in this study.

Upper Urinary Tract Stereotactic Body Radiotherapy Using a 1.5 Tesla Magnetic Resonance Imaging-Guided Linear Accelerator: Workflow and Physics Considerations.

Advancements in radiotherapy technology now enable the delivery of ablative doses to targets in the upper urinary tract, including primary renal cell carcinoma (RCC) or upper tract urothelial carcinomas (UTUC), and secondary involvement by other histologies. Magnetic resonance imaging-guided linear accelerators (MR-Linacs) have shown promise to further improve the precision and adaptability of stereotactic body radiotherapy (SBRT). This single-institution retrospective study analyzed 34 patients (31 with upper urinary tract non-metastatic primaries [RCC or UTUC] and 3 with metastases of non-genitourinary histology) who received SBRT from August 2020 through September 2024 using a 1.

TG-FTIR-Py-GCMS analysis and catalytic pyrolysis mechanism of textile waste by red mud catalyst for liquid fuel production.

The substantial generation of textile waste (TW) and red mud (RM) has resulted in significant resource wastage and environmental challenges. Co-utilization technology of solid waste is an effective approach to improve waste utilization efficiency. In this study, RM catalytic pyrolysis experiments of TW were conducted using TG-FTIR and Py-GC-MS for liquid fuel production, and TW and RM were recycled simultaneously.

Coronary artery segmentation in CCTA images based on multi-scale feature learning.

Background: Coronary artery segmentation is a prerequisite in computer-aided diagnosis of Coronary Artery Disease (CAD). However, segmentation of coronary arteries in Coronary Computed Tomography Angiography (CCTA) images faces several challenges. The current segmentation approaches are unable to effectively address these challenges and existing problems such as the need for manual interaction or low segmentation accuracy.

Multi-modal segmentation with missing image data for automatic delineation of gross tumor volumes in head and neck cancers.

Background: Head and neck (HN) gross tumor volume (GTV) auto-segmentation is challenging due to the morphological complexity and low image contrast of targets. Multi-modality images, including computed tomography (CT) and positron emission tomography (PET), are used in the routine clinic to assist radiation oncologists for accurate GTV delineation. However, the availability of PET imaging may not always be guaranteed.

A multi-institutional comparison of retrospective deformable dose accumulation for online adaptive magnetic resonance-guided radiotherapy.

Background And Purpose: Application of different deformable dose accumulation (DDA) solutions makes institutional comparisons after online-adaptive magnetic resonance-guided radiotherapy (OA-MRgRT) challenging. The aim of this multi-institutional study was to analyze accuracy and agreement of DDA-implementations in OA-MRgRT.

Material And Methods: One gold standard (GS) case deformed with a biomechanical-model and five clinical cases consisting of prostate (2x), cervix, liver, and lymph node cancer, treated with OA-MRgRT, were analyzed.

MR-guided stereotactic radiation therapy for head and neck cancers.

Purpose: MR-guided radiotherapy (MRgRT) has the advantage of utilizing high soft tissue contrast imaging to track daily changes in target and critical organs throughout the entire radiation treatment course. Head and neck (HN) stereotactic body radiation therapy (SBRT) has been increasingly used to treat localized lesions within a shorter timeframe. The purpose of this study is to examine the dosimetric difference between the step-and-shot intensity modulated radiation therapy (IMRT) plans on Elekta Unity and our clinical volumetric modulated arc therapy (VMAT) plans on Varian TrueBeam for HN SBRT.

SC-GAN: Structure-completion generative adversarial network for synthetic CT generation from MR images with truncated anatomy.

Creating synthetic CT (sCT) from magnetic resonance (MR) images enables MR-based treatment planning in radiation therapy. However, the MR images used for MR-guided adaptive planning are often truncated in the boundary regions due to the limited field of view and the need for sequence optimization. Consequently, the sCT generated from these truncated MR images lacks complete anatomic information, leading to dose calculation error for MR-based adaptive planning.

A look-up-table development to facilitate CT simulation of MR-Linac treatment.

While current MR-Linac (MRL) treatment workflows utilize a large table overlay during CT simulation to convert indexing between the two machines, we developed a look-up-table (LUT) as an alternative approach. After populating the LUT, index conversion factors were verified at three separate table locations. The resultant root-mean-square isocenter shifts on the MRL were 0.

Thermal utilization techniques and strategies for secondary aluminum dross: A review.

Secondary aluminum ash (SAD) disposal is challenging, particularly in developing countries, and presents severe eco-environmental risks. This paper presents the treatment techniques, mechanisms, and effects of SAD at the current technical-economic level based on aluminum ash's resource utilization and environmental properties. Five recovery techniques were summarized based on aluminum's recoverability in SAD.

Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources.

Access to radiotherapy worldwide is limited. The Radiation Planning Assistant (RPA) is a fully automated, web-based tool that is being developed to offer fully automated radiotherapy treatment planning tools to clinics with limited resources. The goal is to help clinical teams scale their efforts, thus reaching more patients with cancer.

Characteristics of solid waste from common generation source in nonferrous smelting industry reveal a new classification method.

Solid waste produced by the nonferrous smelting industry has a significant number of notable differences. The lack of recognition of solid waste characteristics is the main factor restricting its disposal and utilization. In this study, we analyzed the main production processes of the nonferrous smelting industry; identified the key production nodes of solid waste; and clarified the characteristics, including the physical, chemical, and pollution characteristics of solid wastes, through a large sample statistical analysis.

A real-time contouring feedback tool for consensus-based contour training.

Purpose: Variability in contouring structures of interest for radiotherapy continues to be challenging. Although training can reduce such variability, having radiation oncologists provide feedback can be impractical. We developed a contour training tool to provide real-time feedback to trainees, thereby reducing variability in contouring.

Free radical formation via BDE-209 thermolysis in the precalciner of a cement kiln: Simulation and DFT study.

To deeply understand the formation mechanism of polybrominated dibenzo-p-dioxins/furans (PBDD/Fs) in the thermal disposal process of polybrominated diphenyl ether (PBDE)-containing waste, this paper studied the formation pathways of key intermediates (free radicals, FRs) in the formation process of PBDD/Fs. BDE-209, the most common PBDE in the environment, was selected as the object of study to analyze FR formation by simulating the key conditions such as temperature (850 °C) and Fe-based materials when PBDE-containing waste entering cement kiln precalciner. Electron paramagnetic resonance (EPR) spectroscopy and density functional theory (DFT) calculations were used to study the reaction.

Multi-constraint point set registration with redundant point removal for the registration of coronary arteries.

Background: Coronary artery disease (CAD) is the leading cause of death worldwide. The registration of the coronary artery at different phases can help radiologists explore the motion patterns of the coronary artery and assist in the diagnosis of CAD. However, there is no automatic and easy-to-execute method to solve the missing data problem that occurs at the endpoints of the coronary artery tree.

Identifying the optimal deep learning architecture and parameters for automatic beam aperture definition in 3D radiotherapy.

Purpose: Two-dimensional radiotherapy is often used to treat cervical cancer in low- and middle-income countries, but treatment planning can be challenging and time-consuming. Neural networks offer the potential to greatly decrease planning time through automation, but the impact of the wide range of hyperparameters to be set during training on model accuracy has not been exhaustively investigated. In the current study, we evaluated the effect of several convolutional neural network architectures and hyperparameters on 2D radiotherapy treatment field delineation.

Severe Lymphopenia During Chemoradiation Therapy for Esophageal Cancer: Comprehensive Analysis of Randomized Phase 2B Trial of Proton Beam Therapy Versus Intensity Modulated Radiation Therapy.

Purpose: Lymphocytes play an important role in antitumor immunity; however, they are also especially vulnerable to depletion during chemoradiation therapy (CRT). The purpose of this study was to compare the incidence of grade 4 lymphopenia (G4L) between proton beam therapy (PBT) and intensity modulated photon radiation therapy (IMRT) in patients with esophageal cancer treated with CRT in a completed randomized trial and to ascertain patient heterogeneity to G4L risk based on treatment and established prognostic factors.

Methods And Materials: Between April 2012 and March 2019, a single-institution, open-label, nonblinded, phase 2 randomized trial (NCT01512589) was conducted at the University of Texas MD Anderson Cancer Center.