Citations

Context.— Artificial intelligence is a transforming technology for anatomic pathology. Involvement within the workforce will foster support for algorithm development and implementation. Objective.— To develop a supportive ecosystem that enables pathologists with variable expertise in artificial intelligence to create algorithms in a development environment with seamless transition to a production environment. Design.— Platform requirements included (1) approachable and intuitive user interface, (2) diverse algorithmic modeling options, (3) support capability for internal and external collaborations, (4) a seamless mechanism for discovery to clinical deployment transition, (5) the ability to meet minimum institutional requirements for information technology (IT) review, and (6) the ability to be scalable over time. The ecosystem required platform education, data science guidance, project management structure, and ongoing leadership. Results.— The development team considered internal development and vended solutions. Because of the extended timeline and resource requirements for internal development, a decision was made to use a vended solution. Vendor proposals were solicited and reviewed by pathologists, IT, and security groups. A vendor was selected and pipelines for development and production were established. Proposals for development were solicited from the pathology department. Eighty-four investigators were selected for the initial cohort, receiving training and access to dedicated subject matter experts. A total of 30 of 31 projects progressed through the model development process of annotating, training, and validation. Based on these projects, 15 abstracts were submitted to national meetings. Conclusions.— Democratizing artificial intelligence by creating an ecosystem to support pathologists with varying levels of expertise can break down entry barriers, reduce overall cost of algorithm development, improve algorithm quality, and enhance the speed of adoption.

AbstractUse of magnetic resonance (MR) imaging in radiation therapy has increased substantially in recent years as more radiotherapy centers are having MR simulators installed, requesting more time on clinical diagnostic MR systems, or even treating with combination MR linear accelerator (MR‐linac) systems. With this increased use, to ensure the most accurate integration of images into radiotherapy (RT), RT immobilization devices and accessories must be able to be used safely in the MR environment and produce minimal perturbations. The determination of the safety profile and considerations often falls to the medical physicist or other support staff members who at a minimum should be a Level 2 personnel as per the ACR. The purpose of this guidance document will be to help guide the user in making determinations on MR Safety labeling (i.e., MR Safe, Conditional, or Unsafe) including standard testing, and verification of image quality, when using RT immobilization devices and accessories in an MR environment.

Abstract Objective . Photon-counting detector (PCD) CT enables routine virtual-monoenergetic image (VMI) reconstruction. We evaluated the performance of an automatic VMI energy level (keV) selection tool on a clinical PCD-CT system in comparison to an automatic tube potential (kV) selection tool from an energy-integrating-detector (EID) CT system from the same manufacturer. Approach. Four torso-shaped phantoms (20–50 cm width) containing iodine (2, 5, and 10 mg cc −1 ) and calcium (100 mg cc −1 ) were scanned on PCD-CT and EID-CT. Dose optimization techniques, task-based VMI energy level and tube-potential selection on PCD-CT (CARE keV) and task-based tube potential selection on EID-CT (CARE kV), were enabled. CT numbers, image noise, and dose-normalized contrast-to-noise ratio (CNR d ) were compared. Main results . PCD-CT produced task-specific VMIs at 70, 65, 60, and 55 keV for non-contrast, bone, soft tissue with contrast, and vascular settings, respectively. A 120 kV tube potential was automatically selected on PCD-CT for all scans. In comparison, EID-CT used x-ray tube potentials from 80 to 150 kV based on imaging task and phantom size. PCD-CT achieved consistent dose reduction at 9%, 21% and 39% for bone, soft tissue with contrast, and vascular tasks relative to the non-contrast task, independent of phantom size. On EID-CT, dose reduction factor for contrast tasks relative to the non-contrast task ranged from a 65% decrease (vascular task, 70 kV, 20 cm phantom) to a 21% increase (soft tissue with contrast task, 150 kV, 50 cm phantom) due to size-specific tube potential adaptation. PCD-CT CNR d was equivalent to or higher than those of EID-CT for all tasks and phantom sizes, except for the vascular task with 20 cm phantom, where 70 kV EID-CT CNR d outperformed 55 keV PCD-CT images. Significance . PCD-CT produced more consistent CT numbers compared to EID-CT due to standardized VMI output, which greatly benefits standardization efforts and facilitates radiation dose reduction.

Abstract Spatially fractionated radiation therapy (SFRT) is a therapeutic approach with the potential to disrupt the classical paradigms of conventional radiation therapy. The high spatial dose modulation in SFRT activates distinct radiobiological mechanisms which lead to a remarkable increase in normal tissue tolerances. Several decades of clinical use and numerous preclinical experiments suggest that SFRT has the potential to increase the therapeutic index, especially in bulky and radioresistant tumors. To unleash the full potential of SFRT a deeper understanding of the underlying biology and its relationship with the complex dosimetry of SFRT is needed. This review provides a critical analysis of the field, discussing not only the main clinical and preclinical findings but also analyzing the main knowledge gaps in a holistic way.

Brain arteriovenous malformations (bAVMs) are complex, and rare arteriovenous shunts that present with a wide range of signs and symptoms, with intracerebral hemorrhage being the most severe. Despite prior societal position statements, there is no consensus on the management of these lesions. ARISE (Aneurysm/bAVM/cSDH Roundtable Discussion With Industry and Stroke Experts) was convened to discuss evidence-based approaches and enhance our understanding of these complex lesions. ARISE identified the need to develop scales to predict the risk of rupture of bAVMs, and the use of common data elements to perform prospective registries and clinical studies. Additionally, the group underscored the need for comprehensive patient management with specialized centers with expertise in cranial and spinal microsurgery, neurological endovascular surgery, and stereotactic radiosurgery. The collection of prospective multicenter data and gross specimens was deemed essential for improving bAVM characterization, genetic evaluation, and phenotyping. Finally, bAVMs should be managed within a multidisciplinary framework, with clinical studies and research conducted collaboratively across multiple centers, harnessing the collective expertise and centralization of resources.