Royal Philips announced new innovations that will help improve cancer care across the patient journey at the American Society for Radiation Oncology (ASTRO) annual meeting. During the event, the company will debut its Multimodality RT Simulation Workspace, a new precision medicine application that provides a vendor-agnostic single space for simulation, multimodality image fusion and contouring. New MR and CT imaging systems tailored for the needs of radiation therapy will also be showcased, delivering breakthroughs in imaging and treatment planning. The company will also highlight its deepened strategic partnership with Elekta to support the ambition of providing clear care pathways and predictable outcomes for every cancer patient. Bringing clarity in therapy planning close to the point of care with Multimodality RT Simulation Workspace: with images and data often siloed in different systems, the complexity of image fusion and contouring can lengthen patient time to treatment. Integrating seamlessly into the simulation workflow, Multimodality RT Simulation Workspace, a new precision medicine application, is designed to help physicians define tumor volume and surrounding organs-at-risk through a versatile multimodality image platform which connects to both Philips and non-Philips imaging devices or a Picture Archiving and Communication System (PACS) to access image datasets such as CT, MR, PET, Spectral CT and Cone Beam CT. These capabilities provide better access to a task-centered, vendor neutral solution that efficiently utilizes all available images and data in one central location. Innovations in MR and CT simulation deliver advances in imaging and treatment planning: the next-generation Philips MR ? Ingenia RT XD ?? MR simulation platform has been designed around the needs of radiation oncology, combining ease-of-use, streamlined integration and versatility. The platform can be easily adapted for different procedures, including external beam radiation therapy (EBRT), proton therapy and brachytherapy planning. The new Couch Top RT XD with Unity indexing further extends the compatibility between the Philips MR ? Ingenia RT XD ? and Elekta Unity, supporting great consistency in both image quality and imaging and positioning workflows that enhance reproducibility, help accelerate learning curves and drive continuity across the care path. The recently-introduced Spectral CT 7500 system delivers high quality spectral images for every patient on every scan 100% of the time to help improve disease characterization, and reduce rescans and follow-ups, all at the same dose levels as conventional scans. Unlocking the clinical value of dual-energy CT for radiation oncology applications, Spectral CT allows for optimization of lesions that may represent cancer. By capturing additional information such as electron density and effective atomic number, Spectral CT enables physicians to quantify physiological processes such as perfusion and ventilation, enhancing treatment planning. The company is collaborating with MIM Software to integrate its Contour Prot?g?AI next-generation deep learning segmentation on its CT ? Big Bore RT ? platform, providing automatically segmented Organ at Risk segmentation immediately after the simulation exam. Also being introduced at ASTRO, Multidisciplinary Team Orchestrator virtually connects and securely integrates multi-disciplinary teams and data across the patient cancer journey. Together with Multimodality RT Simulation Workspace, applications already available from the company that advance precision oncology through integrated care, pathway orchestration, and clinical decision support, include: lung cancer orchestrator, a proactive patient management system for lung cancer screening and incidental findings and the orchestration of lung cancer care; oncology pathways that are created by oncologists for oncologists, covering both medical and the newly-introduced radiation oncology pathways. customers become collaborators, providing input into the ever-evolving pathways; and genomics workspace, bringing genomic data alongside disease histology and patient phenotype for a comprehensive biomarker-informed diagnostic and therapeutic picture.