Expanding the medical physicist curricular and professional programme to include Artificial Intelligence.

PURPOSE: To provide a guideline curriculum related to Artificial Intelligence (AI), for the education and training of European Medical Physicists (MPs). MATERIALS AND METHODS: The proposed curriculum consists of two levels: Basic (introducing MPs to the pillars of knowledge, development and applications of AI, in the context of medical imaging and radiation therapy) and Advanced. Both are common to the subspecialties (diagnostic and interventional radiology, nuclear medicine, and radiation oncology). The learning outcomes of the training are presented as knowledge, skills and competences (KSC approach). RESULTS: For the Basic section, KSCs were stratified in four subsections: (1) Medical imaging analysis and AI Basics; (2) Implementation of AI applications in clinical practice; (3) Big data and enterprise imaging, and (4) Quality, Regulatory and Ethical Issues of AI processes. For the Advanced section instead, a common block was proposed to be further elaborated by each subspecialty core curriculum. The learning outcomes were also translated into a syllabus of a more traditional format, including practical applications. CONCLUSIONS: This AI curriculum is the first attempt to create a guideline expanding the current educational framework for Medical Physicists in Europe. It should be considered as a document to top the sub-specialties' curriculums and adapted by national training and regulatory bodies. The proposed educational program can be implemented via the European School of Medical Physics Expert (ESMPE) course modules and - to some extent - also by the national competent EFOMP organizations, to reach widely the medical physicist community in Europe.

RDI[Formula: see text]a regression detectability index for quality assurance in: x-ray imaging.

Novel iterative image reconstruction methods can help reduce the required radiation dose in x-ray diagnostics such as computed tomography (CT), while maintaining sufficient image quality. Since some of the established image quality measures are not appropriate for reliably judging the quality of images derived by iterative methods, alternative approaches such as task-specific quality assessment would be highly desirable for acceptance or constancy testing. Task-based image quality methods are also closer to tasks performed by the radiologists, such as lesion detection. However, this approach is usually hampered by a huge workload, since hundreds of images are usually required for its application. It is demonstrated that the proposed approach works reliably on the basis of significantly fewer images, and that it correlates well with results obtained from human observers.

MULTICENTRE COMPARISON OF IMAGE QUALITY FOR LOW-CONTRAST OBJECTS AND MICROCATHETER TIPS IN X-RAY-GUIDED TREATMENT OF ARTERIOVENOUS MALFORMATION IN THE BRAIN.

The treatment of brain arteriovenous malformations (AVMs) can be performed as a minimally invasive X-ray-guided procedure using a microcatheter for navigation to reach the target site. The performance of the interventional vascular surgery devices used for AVM was compared in four hospitals. The relation between image quality and the entrance surface air kerma (ESAK) was assessed for the default protocols for digital subtraction angiography (DSA) and fluoroscopy. A custom phantom, built with PMMA and aluminium plates was used to mimic the attenuation properties of the patient head. Image quality was assessed using low-contrast objects and catheters embedded in two phantoms. Differences were found in the ESAK values, especially for the fluoroscopy, whereas for DSA, the ESAK values were similar. The differences in image quality can be related to acquisition parameters, such as kV and filtration, and post-processing. The proposed method can be used to optimise the existing AVM protocols.

Low contrast detectability performance of model observers based on CT phantom images: kVp influence.

This paper studies low contrast detectability (LCD) performance of two model observers in CT phantom images acquired at different kVp levels and compares the results with humans in a 2-alternative forced choice experiment (2-AFC). Images of the Catphan phantom with objects of different contrasts (0.5 and 1%) and diameters (2-15 mm) were acquired in an Aquilion ONE 320-detector row CT (Toshiba Medical Systems, Tokyo, Japan), in two experiments, selecting (80-100-120-135 kV) with fixed mAs and varying the mAs to keep the dose constant, respectively. Four human observers evaluated the objects visibility obtaining a proportion correct (PC) for each case. LCD was also analyzed with two model observers (non-prewhitening matched filter with an eye filter, NPWE, and channelized Hotelling observer with Gabor channels, CHO). Object contrast was affected by kV, with differences up to 17% between the lowest and highest kV. Both models overestimated human performance and were corrected by efficiency and internal noise factors. The NPWE model reproduced better the human PC values trends showing Pearson's correlation coefficients ≥0.976 (0.954-0.987, 95% CI) for both experiments, whereas for CHO they were ≥0.706 (0.493-0.839). Bland-Altman plots showed better agreement between NPWE and humans being the average difference Δ and the range of the differences Δ±2σ (σ, standard deviation) of Δ=-0.3%, Δ±2σ = [-4.0%,4.5%]. For CHO, Δ=-1.2%, Δ± 2σ= [-10.7%,8.3%]. The NPWE model can be a useful tool to predict human performance in CT low contrast detection tasks in a standard phantom and be potentially used in protocol optimization based on kV selection.

Comparison between human and model observer performance in low-contrast detection tasks in CT images: application to images reconstructed with filtered back projection and iterative algorithms.

OBJECTIVE: To compare low-contrast detectability (LCDet) performance between a model [non-pre-whitening matched filter with an eye filter (NPWE)] and human observers in CT images reconstructed with filtered back projection (FBP) and iterative [adaptive iterative dose reduction three-dimensional (AIDR 3D; Toshiba Medical Systems, Zoetermeer, Netherlands)] algorithms. METHODS: Images of the Catphan® phantom (Phantom Laboratories, New York, NY) were acquired with Aquilion ONE™ 320-detector row CT (Toshiba Medical Systems, Tokyo, Japan) at five tube current levels (20-500 mA range) and reconstructed with FBP and AIDR 3D. Samples containing either low-contrast objects (diameters, 2-15 mm) or background were extracted and analysed by the NPWE model and four human observers in a two-alternative forced choice detection task study. Proportion correct (PC) values were obtained for each analysed object and used to compare human and model observer performances. An efficiency factor (η) was calculated to normalize NPWE to human results. RESULTS: Human and NPWE model PC values (normalized by the efficiency, η = 0.44) were highly correlated for the whole dose range. The Pearson's product-moment correlation coefficients (95% confidence interval) between human and NPWE were 0.984 (0.972-0.991) for AIDR 3D and 0.984 (0.971-0.991) for FBP, respectively. Bland-Altman plots based on PC results showed excellent agreement between human and NPWE [mean absolute difference 0.5 ± 0.4%; range of differences (-4.7%, 5.6%)]. CONCLUSION: The NPWE model observer can predict human performance in LCDet tasks in phantom CT images reconstructed with FBP and AIDR 3D algorithms at different dose levels. ADVANCES IN KNOWLEDGE: Quantitative assessment of LCDet in CT can accurately be performed using software based on a model observer.

[State of the art and future trends in technology for computed tomography dose reduction]. / Estado actual y tendencia en el desarrollo tecnológico para la reducción de dosis en los equipos de tomografía computarizada.

The introduction of helical and multislice acquisitions in CT scanners together with decreased image reconstruction times has had a tremendous impact on radiological practice. Technological developments in the last 10 to 12 years have enabled very high quality images to be obtained in a very short time. Improved image quality has led to an increase in the number of indications for CT. In parallel to this development, radiation exposure in patients has increased considerably. Concern about the potential health risks posed by CT imaging, reflected in diverse initiatives and actions by official organs and scientific societies, has prompted the search for ways to reduce radiation exposure in patients without compromising diagnostic efficacy. To this end, good practice guidelines have been established, special applications have been developed for scanners, and research has been undertaken to optimize the clinical use of CT. Noteworthy technical developments incorporated in scanners include the different modes of X-ray tube current modulation, automatic selection of voltage settings, selective organ protection, adaptive collimation, and iterative reconstruction. The appropriate use of these tools to reduce radiation doses requires thorough knowledge of how they work.

Dosimetry of a cone beam CT device for oral and maxillofacial radiology using Monte Carlo techniques and ICRP adult reference computational phantoms.

OBJECTIVES: The aim of this study was to calculate organ and effective doses for a range of available protocols in a particular cone beam CT (CBCT) scanner dedicated to dentistry and to derive effective dose conversion factors. METHODS: Monte Carlo simulations were used to calculate organ and effective doses using the International Commission on Radiological Protection voxel adult male and female reference phantoms (AM and AF) in an i-CAT CBCT. Nine different fields of view (FOVs) were simulated considering full- and half-rotation modes, and also a high-resolution acquisition for a particular protocol. Dose-area product (DAP) was measured. RESULTS: Dose to organs varied for the different FOVs, usually being higher in the AF phantom. For 360°, effective doses were in the range of 25-66 µSv, and 46 µSv for full head. Higher contributions to the effective dose corresponded to the remainder (31%; 27-36 range), salivary glands (23%; 20-29%), thyroid (13%; 8-17%), red bone marrow (10%; 9-11%) and oesophagus (7%; 4-10%). The high-resolution protocol doubled the standard resolution doses. DAP values were between 181 mGy cm(2) and 556 mGy cm(2) for 360°. For 180° protocols, dose to organs, effective dose and DAP were approximately 40% lower. A conversion factor (DAP to effective dose) of 0.130 ± 0.006 µSv mGy(-1) cm(-2) was derived for all the protocols, excluding full head. A wide variation in dose to eye lens and thyroid was found when shifting the FOV in the AF phantom. CONCLUSIONS: Organ and effective doses varied according to field size, acquisition angle and positioning of the beam relative to radiosensitive organs. Good positive correlation between calculated effective dose and measured DAP was found.

Validation of a Monte Carlo simulation for dose assessment in dental cone beam CT examinations.

A Monte Carlo (MC) simulation for calculating absorbed dose has been developed and applied for dental applications with an i-CAT cone beam CT (CBCT) system. To validate the method a comparison was made between calculated and measured dose values for two different clinical protocols. Measurements with a pencil CT chamber were performed free-in-air and in a CT dose head phantom; measurements were also performed with a transmission ionization chamber. In addition for each protocol a total number of 58 thermoluminescence dosemeters (TLD) were packed in groups and placed at 16 representative anatomical locations of an anthropomorphic phantom (Remab system) to assess absorbed doses. To simulate X-ray exposure, a software application based on the EGS4 package was applied. Dose quantities were calculated for different voxelized models representing the CT ionization and transmission chambers, the TLDs, and the phantoms as well. The dose quantities evaluated in the comparison were the accumulated dose averaged along the rotation axis (D(i)), the volume average dose,D(vol) for the dosimetric phantom, the dose area product (DAP) and the absorbed dose for the TLDs. Absolute differences between measured and simulated outcomes were ≤ 2.1% for free-in-air doses; ≤ 6.2% in the 5 cavities of the CT dose head phantom; ≤ 13% for TLDs inside the primary beam. Such differences were considered acceptable in all cases and confirmed the validity of the MC program for different geometries. In conclusion, the devised MC simulation program can be a robust tool to optimize protocols and estimate patient doses for CBCT units in dental, oral and maxillofacial radiology.

Automated assessment of low contrast sensitivity for CT systems using a model observer.

PURPOSE: Low contrast sensitivity of CT scanners is regularly assessed by subjective scoring of low contrast detectability within phantom CT images. Since in these phantoms low contrast objects are arranged in known fixed patterns, subjective rating of low contrast visibility might be biased. The purpose of this study was to develop and validate a software for automated objective low contrast detectability based on a model observer. METHODS: Images of the low contrast module of the Catphan 600 phantom were used for the evaluation of the software. This module contains two subregions: the supraslice region with three groups of low contrast objects (each consisting of nine circular objects with diameter 2-15 mm and contrast 0.3, 0.5, and 1.0%, respectively) and the subslice region with three groups of four circular objects each (diameter 3-9 mm; contrast 1.0%). The software method offered automated determination of low contrast detectability using a NPWE (nonprewhitening matched filter with an eye filter) model observer for the supraslice region. The model observer correlated templates of the low contrast objects with the acquired images of the Catphan phantom and a discrimination index d' was calculated. This index was transformed into a proportion correct (PC) value. In the two-alternative forced choice (2-AFC) experiments used in this study, a PC ≥ 75% was proposed as a threshold to decide whether objects were visible. As a proof of concept, influence of kVp (between 80 and 135 kV), mAs (25-200 mAs range) and reconstruction filter (four filters, two soft and two sharp) on low contrast detectability was investigated. To validate the outcome of the software in a qualitative way, a human observer study was performed. RESULTS: The expected influence of kV, mAs and reconstruction filter on image quality are consistent with the results of the proposed automated model. Higher values for d' (or PC) are found with increasing mAs or kV values and for the soft reconstruction filters. For the highest contrast group (1%), PC values were fairly above 75% for all object diameters >2 mm, for all conditions. For the 0.5% contrast group, the same behavior was observed for object diameters >3 mm for all conditions. For the 0.3% contrast group, PC values were higher than 75% for object diameters >6 mm except for the series acquired at the lowest dose (25 mAs), which gave lower PC values. In the human observer study similar trends were found. CONCLUSIONS: We have developed an automated method to objectively investigate image quality using the NPWE model in combination with images of the Catphan phantom low contrast module. As a first step, low contrast detectability as a function of both acquisition and reconstruction parameter settings was successfully investigated with the software. In future work, this method could play a role in image reconstruction algorithms evaluation, dose reduction strategies or novel CT technologies, and other model observers may be implemented as well.

Performance of data acceptance criteria over 50 months from an automatic real-time environmental radiation surveillance network.

The automatic real-time environmental radiation surveillance network of Catalonia (Spain) comprises two subnetworks; one with 9 aerosol monitors and the other with 8 Geiger monitors together with 2 water monitors located in the Ebre river. Since September 2006, several improvements were implemented in order to get better quality and quantity of data, allowing a more accurate data analysis. However, several causes (natural causes, equipment failure, artificial external causes and incidents in nuclear power plants) may produce radiological measured values mismatched with the own station background, whether spurious without significance or true radiological values. Thus, data analysis for a 50-month period was made and allowed to establish an easily implementable statistical criterion to find those values that require special attention. This criterion proved a very useful tool for creating a properly debugged database and to give a quick response to equipment failures or possible radiological incidents. This paper presents the results obtained from the criterion application, including the figures for the expected, raw and debugged data, percentages of missing data grouped by causes and radiological measurements from the networks. Finally, based on the discussed information, recommendations for the improvement of the network are identified to obtain better radiological information and analysis capabilities.