RadDeploy: A framework for integrating in-house developed software and artificial intelligence models seamlessly into radiotherapy workflows.

The use of and research in automation and artificial intelligence (AI) in radiotherapy is moving with incredible pace. Many innovations do, however, not make it into the clinic. One technical reason for this may be the lack of a platform to deploy such software into clinical practice.

Geometric distortions in clinical MRI sequences for radiotherapy: insights gained from a multicenter investigation.

Background: As magnetic resonance imaging (MRI) becomes increasingly integrated into radiotherapy (RT) for enhanced treatment planning and adaptation, the inherent geometric distortion in acquired MR images pose a potential challenge to treatment accuracy. This study aimed to evaluate the geometric distortion levels in the clinical MRI protocols used across Danish RT centers and discuss influence of specific sequence parameters. Based on the variety in geometric performance across centers, we assess if harmonization of MRI sequences is a relevant measure.

Multi-parametric PET/MRI for enhanced tumor characterization of patients with cervical cancer.

Aim: The concept of personalized medicine has brought increased awareness to the importance of inter- and intra-tumor heterogeneity for cancer treatment. The aim of this study was to explore simultaneous multi-parametric PET/MRI prior to chemoradiotherapy for cervical cancer for characterization of tumors and tumor heterogeneity.

Methods: Ten patients with histologically proven primary cervical cancer were examined with multi-parametric Ga-NODAGA-E[c(RGDyK)]-PET/MRI for radiation treatment planning after diagnostic F-FDG-PET/CT.

A national study on the inter-observer variability in the delineation of organs at risk in the brain.

Background: The Danish Neuro Oncology Group (DNOG) has established national consensus guidelines for the delineation of organs at risk (OAR) structures based on published literature. This study was conducted to finalise these guidelines and evaluate the inter-observer variability of the delineated OAR structures by expert observers.

Material And Methods: The DNOG delineation guidelines were formed by participants from all Danish centres that treat brain tumours with radiotherapy.

Cognitive impairment following radiation to hippocampus and other brain structures in adults with primary brain tumours.

Background: Radiation therapy (RT) to the brain may result in cognitive impairment. The primary objective of the present study was to examine the relationship between RT dose to the hippocampus and learning and memory functions. Secondary objective was to examine relationships between doses to other brain structures and specific cognitive functions.

Diffusion-weighted magnetic resonance imaging during radiotherapy of locally advanced cervical cancer--treatment response assessment using different segmentation methods.

Background: Diffusion-weighted magnetic resonance imaging (DW-MRI) and the derived apparent diffusion coefficient (ADC) value has potential for monitoring tumor response to radiotherapy (RT). Method used for segmentation of volumes with reduced diffusion will influence both volume size and observed distribution of ADC values. This study evaluates: 1) different segmentation methods; and 2) how they affect assessment of tumor ADC value during RT.

An adaptive radiotherapy planning strategy for bladder cancer using deformation vector fields.

Purpose: Adaptive radiotherapy (ART) has considerable potential in treatment of bladder cancer due to large inter-fractional changes in shape and size of the target. The aim of this study was to compare our clinically applied method for plan library creation that involves manual bladder delineations (Clin-ART) with a method using the deformation vector fields (DVFs) resulting from intensity-based deformable image registrations (DVF-based ART).

Materials And Methods: The study included thirteen patients with urinary bladder cancer who had daily cone beam CTs (CBCTs) acquired for set-up.

Tracer kinetic model selection for dynamic contrast-enhanced magnetic resonance imaging of locally advanced cervical cancer.

Background: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) offers a unique capability to probe tumour microvasculature. Different analysis of the acquired data will possibly lead to different conclusions. Therefore, the objective of this study was to investigate under which conditions the Tofts (TM), extended Tofts (ETM), compartmental tissue uptake model (C-TU) and 2-compartment exchange model (2CXM) were the optimal tracer kinetic models (TKMs) for the analysis of DCE-MRI in patients with cervical cancer.

Apparent Diffusion Coefficient (ADC) as a quantitative parameter in diffusion weighted MR imaging in gynecologic cancer: Dependence on b-values used.

Background: Diffusion weighted imaging (DWI) has gained interest as an imaging modality for assessment of tumor extension and response to cancer treatment. The purpose of this study is to assess the impact of the choice of b-values on the calculation of the Apparent Diffusion Coefficient (ADC) for locally advanced gynecological cancer and to estimate a stable interval of diffusion gradients that allows for best comparison of the ADC between patients and institutions.

Material And Methods: Six patients underwent a high resolution single shot EPI based DWI scan with 16 different diffusion gradients on a 3 Tesla Philips Achieva MR-scanner.