One of the main challenges of utilizing spot-scanning proton arc therapy (SPArc) in routine clinics is treatment delivery efficiency. Spot reduction, which relies on spot sparsity optimization (SSO), is crucial for achieving high delivery efficiency in SPArc.

Pneumonia, a major infectious cause of morbidity and mortality among children worldwide, is typically diagnosed using low-dose pediatric chest X-ray [CXR (chest radiography)]. In pediatric CXR images, bone occlusion leads to a risk of missed diagnosis. Deep learning-based bone-suppression networks relying on training data have enabled considerable progress to be achieved in bone suppression in adult CXR images; however, these networks have poor generalizability to pediatric CXR images because of the lack of labeled pediatric CXR images (i.e., bone images vs. soft-tissue images). Dual-energy subtraction imaging approaches are capable of producing labeled adult CXR images; however, their application is limited because they require specialized equipment, and they are infrequently employed in pediatric settings. Traditional image processing-based models can be used to label pediatric CXR images, but they are semiautomatic and have suboptimal performance.

Respiratory motion management is essential in order to achieve high-precision radiotherapy. Markerless motion tracking of tumor can provide a non-invasive way to manage respiratory motion, thereby enhancing treatment accuracy. However, the low contrast in real-time x-ray images for image guidance limits the application of markerless tracking.

Radiation therapy often requires the accumulation of doses from multiple treatment fractions or courses for plan evaluation and treatment response assessment. However, due to underlying mass changes, the accumulated dose may not accurately reflect the total deposited energy, leading to potential inaccuracies in characterizing the treatment input.

Automatic primary gross tumor volume (GTVp) segmentation for nasopharyngeal carcinoma (NPC) is a quite challenging task because of the existence of similar visual characteristics between tumors and their surroundings, especially on computed tomography (CT) images with severe low contrast resolution. Therefore, most recently proposed methods based on radiomics or deep learning (DL) is difficult to achieve good results on CT datasets.

PET/CT and planning CT are commonly used medical images in radiotherapy for esophageal and nasopharyngeal cancer. However, repeated scans will expose patients to additional radiation doses and also introduce registration errors. This multimodal treatment approach is expected to be further improved.

Coronary artery disease is the most common form of cardiovascular disease. It is caused by excess plaque along the arterial wall, blocking blood flow to the heart (stenosis). A percutaneous coronary intervention widens the arterial wall with the inflation of a balloon inside the lesion area and leaves behind a metal stent to prevent re-narrowing of the artery (restenosis). However, in-stent restenosis may occur due to damage to the arterial wall tissue, triggering neointimal hyperplasia, producing fibrotic and calcified plaques and narrowing the artery again. Drug-eluting stents, which slowly release medication to inhibit neointimal hyperplasia, are used to prevent in-stent restenosis but fail up to 20% of cases. Coronary intravascular brachytherapy (IVBT), which uses -emitting radionuclides to prevent in-stent restenosis, is used in these failed cases to prevent in-stent restenosis. However, current clinical dosimetry for IVBT is water-based, and heterogeneities such as the guidewire of the IVBT device, fibrotic and calcified plaques and stents are not considered.

A fundamental obstacle for the preclinical development of ultrasound-(US) mediated cardiac imaging remains cardiac motion, which limits interframe correlation during extended acquisition periods.

In clinical proton radiotherapy, a constant relative biological effectiveness (RBE) of 1.1 is typically applied. Due to abundant evidence of variable RBE effects from in vitro data, multiple variable RBE models have been suggested, typically by describing the and parameters in the linear quadratic (LQ) model as a function of dose averaged linear energy transfer ( ).

The increasing use of nuclear medicine and PET imaging has intensified scrutiny of radiotracer extravasation. To our knowledge, this topic is understudied but holds great potential for enhancing our understanding of extravasation in clinical PET imaging.

Accurate fiber orientation distribution (FOD) is crucial for resolving complex neural fiber structures. However, existing reconstruction methods often fail to integrate both global and local FOD information, as well as the directional information of fixels, which limits reconstruction accuracy. Additionally, these methods overlook the spatial positional relationships between voxels, resulting in extracted features that lack continuity. In regions with signal distortion, many methods also exhibit issues with reconstruction artifacts.

Mammographic imaging is essential for breast cancer detection and diagnosis. In addition to masses, calcifications are of concern and the early detection of breast cancer also heavily relies on the correct interpretation of suspicious microcalcification clusters. Even with advances in imaging and the introduction of novel techniques such as digital breast tomosynthesis and contrast-enhanced mammography, a correct interpretation can still be challenging given the subtle nature and large variety of calcifications.

The permitted input power density of rotating anode x-ray sources is limited by the performance of available target materials. The commonly used simplified formulas for the focal spot surface temperature ignore the tube voltage despite its variation in clinical practice. Improved modeling of electron transport and target erosion, as proposed in this work, improves the prediction of x-ray output degradation by target erosion, the absolute x-ray dose output and the quality of diagnostic imaging and orthovolt cancer therapy for a wide range of technique factors.

Physical vascular phantoms are instrumental in studying intracranial aneurysms and testing relevant imaging tools and training systems to provide improved clinical care. Current vascular phantom production methods have major limitations in capturing the biophysical and morphological characteristics of intracranial aneurysms with good fidelity and multi-modal imaging capacity. With stereolithography (SLA) 3D printing technology becoming more accessible, newer flexible and transparent printing materials with higher precision controls open the door for improving the efficiency and quality of producing anthropomorphic vascular phantoms but have rarely been explored for the application.

Multi-material decomposition is an interesting topic in dual-energy CT (DECT) imaging; however, the accuracy and performance may be limited using the conventional algorithms.

Task Group (TG) 314 of the American Association of Physicists in Medicine (AAPM) was charged to develop guidance for recovering from fault states in radiation therapy, specifically regarding the delivery of photon or electron beams using a linear accelerator (linac) including ancillary systems. The fault conditions addressed may involve software, hardware, or a combination of causes. The report provides detailed recommendations for the proactive steps to be taken before a fault, the actions to be taken at the time of a fault, and the safety steps before returning a linac to clinical service, as well as the activities that device manufacturers and standard organizations can do to prevent and resolve the faults. A user-maintained log of prior faults; establishment of remote access by the vendor; and user training in emergency gantry, couch, and door motions are all useful proactive steps. At the moment of downtime and after ensuring the safety of the patient, the report stresses the importance of capturing fault information, prompt contact with the service engineer after the initial assessment, and considerations for communicating the estimated duration before the linac is returned to service. The medical physicist has a critical responsibility to assess the impact of the fault on patient care. Before resuming clinical use, the medical physicist must both determine the level of testing required to ensure safe operation of the linac and ensure any partially or totally delivered treatments have been correctly saved for accurate completion of the treatment fraction. The report stresses the roles of the radiation therapist, medical physicist, and service engineer to efficiently and safely address linac downtime. The appendices contain a description of the efforts of several organizations regarding linac safety: Integrating the Healthcare Enterprise-Radiation Oncology, International Standards Organization/International Electrotechnical Commission, Radiation Oncology Safety Stakeholder Initiative, and the AAPM Vendor Relations and Product Usability Subcommittee. Disclaimer: The recommendations of this TG should not be used to establish regulations. These recommendations are guidelines for Qualified Medical Physicists and others to use and appropriately interpret for their institution and clinical setting. Each institution may have site-specific or state-mandated needs and requirements which may modify their usage of these recommendations.

The conventional lying down position for radiation therapy can be challenging for patients due to pain, swallowing or breathing issues. To provide an alternative upright treatment position for these patients, we have developed a portable rotating radiation therapy platform which integrates with conventional photon treatment machines. The device enables cone-beam computed tomography (CBCT) imaging of patients in an upright position, and the future delivery of therapeutic radiation.

Four-dimensional computed tomography (4DCT) is an es sential tool in radiation therapy. However, the 4D acquisition process may cause motion artifacts which can obscure anatomy and distort functional measurements from CT scans.

Dosimetric equipment in particle therapy (PT) is associated with high costs. There is a lack of versatile, tissue-equivalent detectors suitable for in-vivo dosimetry. Faraday-cup (FC) type detectors are sensitive to stopped protons, that is, to track-ends (TEs). They experience a renaissance in PT as they can cope with high dose rates. Owing to their simple functional principle, production of FC could benefit from the dynamic technological developments in additive manufacturing of sensors.

Many thyroid nodules are detected incidentally with the widespread use of sensitive imaging techniques; however, only a fraction of these nodules are malignant, resulting in unnecessary medical expenditures and anxiety. The major challenge is to differentiate benign thyroid nodules from malignant ones. The application of dual-energy computed tomography (DECT) and radiomics provides a new diagnostic approach. Studies applying radiomics from primary tumours on iodine maps to differentiate malignant from benign thyroid nodules are still lacking.

Tumor assessment through imaging is crucial for diagnosing and treating cancer. Lesions in the liver, a common site for metastatic disease, are particularly challenging to accurately detect and segment. This labor-intensive task is subject to individual variation, which drives interest in automation using artificial intelligence (AI).