Principles and Applications of Dual-Layer Spectral CT in Gastrointestinal Imaging.

The advance in technology allows for the development of different CT scanners in the field of dual-energy computed tomography (DECT). In particular, a recently developed detector-based technology can collect data from different energy levels, thanks to its layers. The use of this system is suited for material decomposition with perfect spatial and temporal registration.

Computed tomography semi-automated lung volume quantification in SARS-CoV-2-related pneumonia.

Objectives: To evaluate a semi-automated segmentation and ventilated lung quantification on chest computed tomography (CT) to assess lung involvement in patients affected by SARS-CoV-2. Results were compared with clinical and functional parameters and outcomes.

Methods: All images underwent quantitative analyses with a dedicated workstation using a semi-automatic lung segmentation software to compute ventilated lung volume (VLV), Ground-glass opacity (GGO) volume (GGO-V), and consolidation volume (CONS-V) as absolute volume and as a percentage of total lung volume (TLV).

Anthropomorphic phantom for deformable lung and liver CT and MR imaging for radiotherapy.

In this study, a functioning and ventilated anthropomorphic phantom was further enhanced for the purpose of CT and MR imaging of the lung and liver. A deformable lung, including respiratory tract was 3D printed. Within the lung's inner structures is a solid region shaped from a patient's lung tumour and six nitro-glycerine capsules as reference landmarks.

Practice patterns of image guided particle therapy in Europe: A 2016 survey of the European Particle Therapy Network (EPTN).

Background And Purpose: Image guidance is critical in achieving accurate and precise radiation delivery in particle therapy, even more than in photon therapy. However, equipment, quality assurance procedures and clinical workflows for image-guided particle therapy (IGPT) may vary substantially between centres due to a lack of standardization. A survey was conducted to evaluate the current practice of IGPT in European particle therapy centres.

Monitoring of breathing motion in image-guided PBS proton therapy: comparative analysis of optical and electromagnetic technologies.

Background: Motion monitoring is essential when treating non-static tumours with pencil beam scanned protons. 4D medical imaging typically relies on the detected body surface displacement, considered as a surrogate of the patient's anatomical changes, a concept similarly applied by most motion mitigation techniques. In this study, we investigate benefits and pitfalls of optical and electromagnetic tracking, key technologies for non-invasive surface motion monitoring, in the specific environment of image-guided, gantry-based proton therapy.

Respiratory motion-management in stereotactic body radiation therapy for lung cancer - A dosimetric comparison in an anthropomorphic lung phantom (LuCa).

Background And Purpose: The objective of this study was to compare the latest respiratory motion-management strategies, namely the internal-target-volume (ITV) concept, the mid-ventilation (MidV) principle, respiratory gating and dynamic couch tracking.

Materials And Methods: An anthropomorphic, deformable and dynamic lung phantom was used for the dosimetric validation of these techniques. Stereotactic treatments were adapted to match the techniques and five distinct respiration patterns, and delivered to the phantom while radiographic film measurements were taken inside the tumor.

Four-Dimensional Dose Reconstruction for Scanned Proton Therapy Using Liver 4DCT-MRI.

Purpose: Four-dimensional computed tomography-magnetic resonance imaging (4DCT-MRI) is an image-processing technique for simulating many 4DCT data sets from a static reference CT and motions extracted from 4DMRI studies performed using either volunteers or patients. In this work, different motion extraction approaches were tested using 6 liver cases, and a detailed comparison between 4DCT-MRI and 4DCT was performed.

Methods And Materials: 4DCT-MRI has been generated using 2 approaches.

Automatic segmentation of head and neck CT images for radiotherapy treatment planning using multiple atlases, statistical appearance models, and geodesic active contours.

Purpose: Accurate delineation of organs at risk (OARs) is a precondition for intensity modulated radiation therapy. However, manual delineation of OARs is time consuming and prone to high interobserver variability. Because of image artifacts and low image contrast between different structures, however, the number of available approaches for autosegmentation of structures in the head-neck area is still rather low.

Vision 20/20: perspectives on automated image segmentation for radiotherapy.

Due to rapid advances in radiation therapy (RT), especially image guidance and treatment adaptation, a fast and accurate segmentation of medical images is a very important part of the treatment. Manual delineation of target volumes and organs at risk is still the standard routine for most clinics, even though it is time consuming and prone to intra- and interobserver variations. Automated segmentation methods seek to reduce delineation workload and unify the organ boundary definition.

Quantification of organ motion based on an adaptive image-based scale invariant feature method.

Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.

Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition.

Scale invariant feature transform in adaptive radiation therapy: a tool for deformable image registration assessment and re-planning indication.

Adaptive radiation therapy (ART) aims at compensating for anatomic and pathological changes to improve delivery along a treatment fraction sequence. Current ART protocols require time-consuming manual updating of all volumes of interest on the images acquired during treatment. Deformable image registration (DIR) and contour propagation stand as a state of the ART method to automate the process, but the lack of DIR quality control methods hinder an introduction into clinical practice.

Automatic segmentation and online virtualCT in head-and-neck adaptive radiation therapy.

Purpose: The purpose of this work was to develop and validate an efficient and automatic strategy to generate online virtual computed tomography (CT) scans for adaptive radiation therapy (ART) in head-and-neck (HN) cancer treatment.

Method: We retrospectively analyzed 20 patients, treated with intensity modulated radiation therapy (IMRT), for an HN malignancy. Different anatomical structures were considered: mandible, parotid glands, and nodal gross tumor volume (nGTV).

Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge.

EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intrapatient thoracic CT image pairs. Evaluation of nonrigid registration techniques is a nontrivial task. This is compounded by the fact that researchers typically test only on their own data, which varies widely.

Uncertainties in lung motion prediction relying on external surrogate: a 4DCT study in regular vs. irregular breathers.

This paper examines the uncertainty in estimating lung motion from external surrogates for lung cancer patients with regular and irregular breathing. 4DCT data sets were analyzed using a template matching algorithm to track the spatial movement of vessel bifurcations in 12 patients. The detected internal movement of features in 3D was retrospectively synchronized with the RPM surrogate signal, and the correlation index R(2) and the prediction error were computed.