Proceedings Virtual Imaging Trials in Medicine 2024.

This submission comprises the proceedings of the 1st Virtual Imaging Trials in Medicine conference, organized by Duke University on April 22-24, 2024. The listed authors serve as the program directors for this conference. The VITM conference is a pioneering summit uniting experts from academia, industry and government in the fields of medical imaging and therapy to explore the transformative potential of in silico virtual trials and digital twins in revolutionizing healthcare. The proceedings are categorized by the respective days of the conference: Monday presentations, Tuesday presentations, Wednesday presentations, followed by the abstracts for the posters presented on Monday and Tuesday.

Absolute ground truth-based validation of computer-aided nodule detection and volumetry in low-dose CT imaging.

PURPOSE: To validate the performance of computer-aided detection (CAD) and volumetry software using an anthropomorphic phantom with a ground truth (GT) set of 3D-printed nodules. METHODS: The Kyoto Kaguku Lungman phantom, containing 3D-printed solid nodules including six diameters (4 to 9 mm) and three morphologies (smooth, lobulated, spiculated), was scanned at varying CTDIvol levels (6.04, 1.54 and 0.20 mGy). Combinations of reconstruction algorithms (iterative and deep learning image reconstruction) and kernels (soft and hard) were applied. Detection, volumetry and density results recorded by a commercially available AI-based algorithm (AVIEW LCS + ) were compared to the absolute GT, which was determined through µCT scanning at 50 µm resolution. The associations between image acquisition parameters or nodule characteristics and accuracy of nodule detection and characterization were analyzed with chi square tests and multiple linear regression. RESULTS: High levels of detection sensitivity and precision (minimal 83 % and 91 % respectively) were observed across all acquisitions. Neither reconstruction algorithm nor radiation dose showed significant associations with detection. Nodule diameter however showed a highly significant association with detection (p < 0.0001). Volumetric measurements for nodules > 6 mm were accurate within 10 % absolute range from volumeGT, regardless of dose and reconstruction. Nodule diameter and morphology are major determinants of volumetric accuracy (p < 0.001). Density assignment was not significantly influenced by any parameters. CONCLUSIONS: Our study confirms the software's accurate performance in nodule volumetry, detection and density characterization with robustness for variations in CT imaging protocols. This study suggests the incorporation of similar phantom setups in quality assurance of CAD tools.

Optimized signal of calcifications in wide-angle digital breast tomosynthesis: a virtual imaging trial.

OBJECTIVES: Evaluate microcalcification detectability in digital breast tomosynthesis (DBT) and synthetic 2D mammography (SM) for different acquisition setups using a virtual imaging trial (VIT) approach. MATERIALS AND METHODS: Medio-lateral oblique (MLO) DBT acquisitions on eight patients were performed at twice the automatic exposure controlled (AEC) dose. The noise was added to the projections to simulate a given dose trajectory. Virtual microcalcification models were added to a given projection set using an in-house VIT framework. Three setups were evaluated: (1) standard acquisition with 25 projections at AEC dose, (2) 25 projections with a convex dose distribution, and (3) sparse setup with 13 projections, every second one over the angular range. The total scan dose and angular range remained constant. DBT volume reconstruction and synthetic mammography image generation were performed using a Siemens prototype algorithm. Lesion detectability was assessed through a Jackknife-alternative free-response receiver operating characteristic (JAFROC) study with six observers. RESULTS: For DBT, the area under the curve (AUC) was 0.97 ± 0.01 for the standard, 0.95 ± 0.02 for the convex, and 0.89 ± 0.03 for the sparse setup. There was no significant difference between standard and convex dose distributions (p = 0.309). Sparse projections significantly reduced detectability (p = 0.001). Synthetic images had a higher AUC with the convex setup, though not significantly (p = 0.435). DBT required four times more reading time than synthetic mammography. DISCUSSION: A convex setup did not significantly improve detectability in DBT compared to the standard setup. Synthetic images exhibited a non-significant increase in detectability with the convex setup. Sparse setup significantly reduced detectability in both DBT and synthetic mammography. CLINICAL RELEVANCE STATEMENT: This virtual imaging trial study allowed the design and efficient testing of different dose distribution trajectories with real mammography images, using a dose-neutral protocol. KEY POINTS: • In DBT, a convex dose distribution did not increase the detectability of microcalcifications compared to the current standard setup but increased detectability for the SM images. • A sparse setup decreased microcalcification detectability in both DBT and SM images compared to the convex and current clinical setups. • Optimal microcalcification cluster detection in the system studied was achieved using either the standard or convex dose setting, with the default number of projections.

A combined analytical and Monte Carlo method for detailed simulations of antiscatter grids in x-ray medical imaging: implementing scatter within the grid.

Objective. To implement a hybrid method, which combines analytical tracking and interaction simulation using Monte Carlo (MC) techniques, in order to model photon transport inside antiscatter grids (ASG) for x-ray imaging.Approach. A new tally was developed for PENELOPE (v.2018) and penEasy (v. 2020) MC code to simulate photon transmission through ASGs. Two established analytical algorithms from the literature were implemented in this tally. In addition, a new hybrid method was introduced by extending one of the analytical algorithms to include photon-interactions inside the grid, while preserving the imaged grid structure. Calculations of primary(TP),scatter(TS),and total(TT)grid transmissions in addition to theQfactor (Q=TP2/TT) were performed. The new tally was validated for a quadric geometry ASG, and experimental measurements with a PMMA phantom of several thicknesses. In addition, the contribution of the scatter inside the grid was studied for three interspace materials, and a high resolution image of the grid was simulated.Main results. An excellent agreement was found between the two analytical models compared with the quadric grid without scatter, and the hybrid method with the geometrical grid with scatter. Average deviations of 0.2% and 1.4% were found betweenTPandTSfor the hybrid method and quadric grid, while for the hybrid method and experimental measurements these values were 1% and 20%. Antiscatter grids with aluminium as interspace material had the highest amount of scatter from inside the grid to the final image, followed up by paper fibre and air. The high resolution image of the grid was equivalent using the quadric geometry or the hybrid mode.Significance. The hybrid method provides a means of studying scattered radiation from the antiscatter grid with the advantage of higher performance, with results that are consistent with a full quadric geometry simulation of the ASG.

A spiculated mass target model for clinical image quality control in digital mammography.

OBJECTIVES: Quality assurance of breast imaging has a long history of using test objects to optimize and follow up imaging devices. In particular, the evaluation of new techniques benefits from suitable test objects. The applicability of a phantom consisting of spiculated masses to assess image quality and its dependence on dose in flat field digital mammography (FFDM) and digital breast tomosynthesis systems (DBT) is investigated. METHODS: Two spiculated masses in five different sizes each were created from a database of clinical tumour models. The masses were produced using 3D printing and embedded into a cuboid phantom. Image quality is determined by the number of spicules identified by human observers. RESULTS: The results suggest that the effect of dose on spicule detection is limited especially in cases with smaller objects and probably hidden by the inter-reader variability. Here, an average relative inter-reader variation of the counted number of 31% was found (maximum 83%). The mean relative intra-reader variability was found to be 17%. In DBT, sufficiently good results were obtained only for the largest masses. CONCLUSIONS: It is possible to integrate spiculated masses into a cuboid phantom. It is easy to print and should allow a direct and prompt evaluation of the quality status of the device by counting visible spicules. Human readout presented the major uncertainty in this study, indicating that automated readout may improve the reproducibility and consistency of the results considerably. ADVANCES IN KNOWLEDGE: A cuboid phantom including clinical objects as spiculated lesion models for visual assessing the image quality in FFDM and DBT was developed and is introduced in this work. The evaluation of image quality works best with the two larger masses with 21 spicules.

Survey on fan-beam computed tomography for radiotherapy: Current implementation and future perspectives of motion management and surface guidance devices.

Background and purpose: This work reports on the results of a survey performed on the use of computed tomography (CT) imaging for motion management, surface guidance devices, and their quality assurance (QA). Additionally, it details the collected user insights regarding professional needs in CT for radiotherapy. The purpose of the survey is to understand current practice, professional needs and future directions in the field of fan-beam CT in radiation therapy (RT). Materials and methods: An online institutional survey was conducted between 1-Sep-2022 and 10-Oct-2022 among medical physics experts at Belgian and Dutch radiotherapy institutions, to assess the current status, challenges, and future directions of motion management and surface image-guided radiotherapy. The survey consisted of a maximum of 143 questions, with the exact number depending on participants' responses. Results: The response rate was 66 % (31/47). Respiratory management was reported as standard practice in all but one institution; surface imaging during CT-simulation was reported in ten institutions. QA procedures are applied with varying frequencies and methodologies, primarily with commercial anatomy-like phantoms. Surface guidance users report employing commercial static and dynamic phantoms. Four main subjects are considered clinically important by the respondents: surface guidance, CT protocol optimisation, implementing gated imaging (4DCT, breath-hold), and a tattoo-less workflow. Conclusions: The survey highlights the scattered pattern of QA procedures for respiratory motion management, indicating the need for well-defined, unambiguous, and practicable guidelines. Surface guidance is considered one of the most important techniques that should be implemented in the clinical radiotherapy simulation workflow.

Impact of ultra-high-resolution imaging of the lungs on perceived diagnostic image quality using photon-counting CT.

OBJECTIVES: To compare clinical image quality and perceived impact on diagnostic interpretation of chest CT findings between ultra-high-resolution photon-counting CT (UHR-PCCT) and conventional high-resolution energy-integrating-detector CT (HR-EIDCT) using visual grading analysis (VGA) scores. MATERIALS AND METHODS: Fifty patients who underwent a UHR-PCCT (matrix 512 × 512, 768 × 768, or 1024 × 1024; FOV average 275 × 376 mm, 120 × 0.2 mm; focal spot size 0.6 × 0.7 mm) between November 2021 and February 2022 and with a previous HR-EIDCT within the last 14 months were included. Four readers evaluated central and peripheral airways, lung vasculature, nodules, ground glass opacities, inter- and intralobular lines, emphysema, fissures, bullae/cysts, and air trapping on PCCT (0.4 mm) and conventional EIDCT (1 mm) via side-by-side reference scoring using a 5-point diagnostic quality score. The median VGA scores were compared and tested using one-sample Wilcoxon signed rank tests with hypothesized median values of 0 (same visibility) and 2 (better visibility on PCCT with impact on diagnostic interpretation) at a 2.5% significance level. RESULTS: Almost all lung structures had significantly better visibility on PCCT compared to EIDCT (p < 0.025; exception for ground glass nodules (N = 2/50 patients, p = 0.157)), with the highest scores seen for peripheral airways, micronodules, inter- and intralobular lines, and centrilobular emphysema (mean VGA > 1). Although better visibility, a perceived difference in diagnostic interpretation could not be demonstrated, since the median VGA was significantly different from 2. CONCLUSION: UHR-PCCT showed superior visibility compared to HR-EIDCT for central and peripheral airways, lung vasculature, fissures, ground glass opacities, macro- and micronodules, inter- and intralobular lines, paraseptal and centrilobular emphysema, bullae/cysts, and air trapping. CLINICAL RELEVANCE STATEMENT: UHR-PCCT has emerged as a promising technique for thoracic imaging, offering improved spatial resolution and lower radiation dose. Implementing PCCT into daily practice may allow better visibility of multiple lung structures and optimization of scan protocols for specific pathology. KEY POINTS: • The aim of this study was to verify if the higher spatial resolution of UHR-PCCT would improve the visibility and detection of certain lung structures and abnormalities. • UHR-PCCT was judged to have superior clinical image quality compared to conventional HR-EIDCT in the evaluation of the lungs. UHR-PCCT showed better visibility for almost all tested lung structures (except for ground glass nodules). • Despite superior image quality, the readers perceived no significant impact on the diagnostic interpretation of the studied lung structures and abnormalities.

Joint AAPM Task Group 282/EFOMP Working Group Report: Breast dosimetry for standard and contrast-enhanced mammography and breast tomosynthesis.

Currently, there are multiple breast dosimetry estimation methods for mammography and its variants in use throughout the world. This fact alone introduces uncertainty, since it is often impossible to distinguish which model is internally used by a specific imaging system. In addition, all current models are hampered by various limitations, in terms of overly simplified models of the breast and its composition, as well as simplistic models of the imaging system. Many of these simplifications were necessary, for the most part, due to the need to limit the computational cost of obtaining the required dose conversion coefficients decades ago, when these models were first implemented. With the advancements in computational power, and to address most of the known limitations of previous breast dosimetry methods, a new breast dosimetry method, based on new breast models, has been developed, implemented, and tested. This model, developed jointly by the American Association of Physicists in Medicine and the European Federation for Organizations of Medical Physics, is applicable to standard mammography, digital breast tomosynthesis, and their contrast-enhanced variants. In addition, it includes models of the breast in both the cranio-caudal and the medio-lateral oblique views. Special emphasis was placed on the breast and system models used being based on evidence, either by analysis of large sets of patient data or by performing measurements on imaging devices from a range of manufacturers. Due to the vast number of dose conversion coefficients resulting from the developed model, and the relative complexity of the calculations needed to apply it, a software program has been made available for download or online use, free of charge, to apply the developed breast dosimetry method. The program is available for download or it can be used directly online. A separate User's Guide is provided with the software.

Survey on fan-beam computed tomography for radiotherapy: Imaging for dose calculation and delineation.

Background and purpose: To obtain an understanding of current practice, professional needs and future directions in the field of fan-beam CT in RT, a survey was conducted. This work presents the collected information regarding the use of CT imaging for dose calculation and structure delineation. Materials and methods: An online institutional survey was distributed to medical physics experts employed at Belgian and Dutch radiotherapy institutions to assess the status, challenges, and future directions of QA practices for fan-beam CT. A maximum of 143 questions covered topics such as CT scanner availability, CT scanner specifications, QA protocols, treatment simulation workflow, and radiotherapy dose calculation. Answer forms were collected between 1-Sep-2022 and 10-Oct-2022. Results: A 66 % response rate was achieved, yielding data on a total of 58 CT scanners. For MV photon therapy, all single-energy CT scans are reconstructed in Hounsfield Units for delineation or dose calculation, and a direct- or stoichiometric method was used to convert CT numbers for dose calculation. Limited use of dual-energy CT is reported for photon (N = 3) and proton dose calculations (N = 1). For brachytherapy, most institutions adopt water-based dose calculation, while approximately 26 % of the institutions take tissue heterogeneity into account. Commissioning and regular QA include eleven tasks, which are performed by two or more professions (29/31) with varying frequencies. Conclusions: Dual usage of a planning CT limits protocol optimization for both tissue characterization and delineation. DECT has been implemented only gradually. A variation of QA testing frequencies and tests are reported.

Special Section Guest Editorial: Introduction to the JMI Special Issue on Advances in Breast Imaging.

The editorial introduces the JMI Special Issue on Advances in Breast Imaging.

Development and validation of a 3D anthropomorphic phantom for dental CBCT imaging research.

BACKGROUND: Optimization of dental cone beam computed tomography (CBCT) imaging is still in a preliminary stage and should be addressed using task-based methods. Dedicated models containing relevant clinical tasks for image quality studies have yet to be developed. PURPOSE: To present a methodology to develop and validate a virtual adult anthropomorphic voxel phantom for use in task-based image quality optimization studies in dental CBCT imaging research, focusing on root fracture (RF) detection tasks in the presence of metal artefacts. METHODS: The phantom was developed from a CBCT scan with an isotropic voxel size of 0.2 mm, from which the main dental structures, mandible and maxilla were segmented. The missing large anatomical structures, including the spine, skull and remaining soft tissues, were segmented from a lower resolution full skull scan. Anatomical abnormalities were absent in the areas of interest. Fine detailed dental structures, that could not be segmented due to the limited resolution and noise in the clinical data, were modelled using a-priori anatomical knowledge. Model resolution of the teeth was therefore increased to 0.05 mm. Models of RFs as well as dental restorations to create the artefacts, were developed, and could be inserted in the phantom in any desired configuration. Simulated CBCT images of the models were generated using a newly developed multi-resolution simulation framework that incorporated the geometry, beam quality, noise and spatial resolution characteristics of a real dental CBCT scanner. Ray-tracing and Monte Carlo techniques were used to create the projection images, which were reconstructed using the classical FDK algorithm. Validation of the models was assessed by measurements of different tooth lengths, the pulp volume and the mandible, and comparison with reference values. Additionally, the simulated images were used in a reader study in which two oral radiologists had to score the realism level of the model's normal anatomy, as well as the modelled RFs and restorations. RESULTS: A model of an adult head, as well as models of RFs and different types of dental restorations were created. Anatomical measurements were consistent with ranges reported in literature. For the tooth length measurements, the deviations from the mean reference values were less than 20%. In 77% of all the measurements, the deviations were within 10.1%. The pulp volumes, and mandible measurements were within one standard deviation of the reference values. Regarding the normal anatomy, both readers considered the realism level of the dental structures to be good. Background structures received a lower realism score due to the lack of detailed enough trabecular bone structure, which was expected but not the focus of this study. All modelled RFs were scored at least adequate by at least one of the readers, both in appearance and position. The realism level of the modelled restorations was considered to be good. CONCLUSIONS: A methodology was proposed to develop and validate an anthropomorphic voxel phantom for image quality optimization studies in dental CBCT imaging, with a main focus on RF detection tasks. The methodology can be extended further to create more models representative of the clinical population.

Photon-counting CT allows better visualization of temporal bone structures in comparison with current generation multi-detector CT.

PURPOSE: To compare photon-counting CT (PCCT) and multi-detector CT (MDCT) for visualization of temporal bone anatomic structures. METHODS: Thirty-six exams of temporal bones without pathology were collected from consecutive patients on a MDCT, and another 35 exams on a PCCT scanner. Two radiologists independently scored visibility of 14 structures for the MDCT and PCCT dataset, using a 5-point Likert scale, with a 2-month wash-out period. For MDCT, the acquisition parameters were: 110 kV, 64 × 0.6 mm (slice thickness reconstructed to 0.4 mm), pitch 0.85, quality ref. mAs 150, and 1 s rotation time; for PCCT: 120 kV, 144 × 0.2 mm, pitch 0.35, IQ level 75, and 0.5 s rotation time. Patient doses were reported as dose length product values (DLP). Statistical analysis was done using the Mann-Whitney U test, visual grading characteristic (VGC) analysis, and ordinal regression. RESULTS: Substantial agreement was found between readers (intraclass correlation coefficient 0.63 and 0.52 for MDCT and PCCT, resp.). All structures were scored higher for PCCT (p < 0.0001), except for Arnold's canal (p = 0.12). The area under the VGC curve was 0.76 (95% CI, 0.73-0.79), indicating a significantly better visualization on PCCT. Ordinal regression showed the odds for better visualization are 354 times higher (95% CI, 75-1673) in PCCT (p < 0.0001). Average (range) of DLP was 95 (79-127) mGy*cm for MDCT and 74 (50-95) mGy*cm for PCCT (p < 0.001). CONCLUSION: PCCT provides a better depiction of temporal bone anatomy than MDCT, at a lower radiation dose. CRITICAL RELEVANCE STATEMENT: PCCT provides a better depiction of temporal bone anatomy than MDCT, at a lower radiation dose. KEY POINTS: 1. PCCT allows high-resolution imaging of temporal bone structures. 2. Compared to MDCT, the visibility of normal temporal bone structures is scored better with PCCT. 3. PCCT allows to obtain high-quality CT images of the temporal bones at lower radiation doses than MDCT.

Technical note: Realization and uncertainty analysis for an adjustable 3D structured breast phantom in digital breast tomosynthesis.

BACKGROUND: Projection imaging phantoms are often optimized for 2-dimensional image characteristics in homogeneous backgrounds. Therefore, evaluation of image quality in tomosynthesis (DBT) lacks accepted and established phantoms. PURPOSE: We describe a 3D breast phantom with a structured, variable background. The phantom is an adaptable and advanced version of the L1 phantom by Cockmartin et al. Phantom design and its use for quality assurance measurements for DBT devices are described. Four phantoms were compared to assess the objectivity. METHODS: The container size was increased to a diameter of 24 cm and a total height of 53.5 mm. Spiculated masses were replaced by five additional non-spiculated masses for higher granularity in threshold diameter resolution. These patterns are adjustable to the imaging device. The masses were printed in one session with a base layer using two-component 3D printing. New materials compared to the L1 phantom improved the attenuation difference between the lesion models and the background. Four phantoms were built and intra-human observer, inter-human observer and inter-phantom variations were determined. The latter assess the reproducibility of the phantom production. Coefficients of variance (V) were calculated for all three variations. RESULTS: The difference of the attenuation coefficients between the lesion models and the background was 0.20 cm-1 (with W/Al at 32 kV, equivalent to 19-20 keV effective energy) compared to 0.21 cm-1 for 50/50 glandular/adipose breast tissue and cancerous lesions. PMMA equivalent thickness of the phantom was 47.0 mm for the Siemens Mammomat Revelation. For the masses, the V i n t r a $V_{intra}$ for the intra-observer variation was 0.248, the averaged inter-observer variation, V ¯ i n t e r $\overline{V}_{inter}$ was 0.383. V p h a n t o m $V_{phantom}$ for phantom variance was 0.321. For the micro-calcifications, V i n t r a $V_{intra}$ was 0.0429, V ¯ i n t e r = $\overline{V}_{inter}=$ 0.0731 and V p h a n t o m = $V_{phantom}=$ 0.0759. CONCLUSIONS: Position, orientation and shape of the masses are reproducible and attenuation differences appropriate. The phantom presented proved to be a candidate test object for quality control.

Uncertainty estimation for deep learning-based pectoral muscle segmentation via Monte Carlo dropout.

Objective. Deep Learning models are often susceptible to failures after deployment. Knowing when your model is producing inadequate predictions is crucial. In this work, we investigate the utility of Monte Carlo (MC) dropout and the efficacy of the proposed uncertainty metric (UM) for flagging of unacceptable pectoral muscle segmentations in mammograms.Approach. Segmentation of pectoral muscle was performed with modified ResNet18 convolutional neural network. MC dropout layers were kept unlocked at inference time. For each mammogram, 50 pectoral muscle segmentations were generated. The mean was used to produce the final segmentation and the standard deviation was applied for the estimation of uncertainty. From each pectoral muscle uncertainty map, the overall UM was calculated. To validate the UM, a correlation between the dice similarity coefficient (DSC) and UM was used. The UM was first validated in a training set (200 mammograms) and finally tested in an independent dataset (300 mammograms). ROC-AUC analysis was performed to test the discriminatory power of the proposed UM for flagging unacceptable segmentations.Main results. The introduction of dropout layers in the model improved segmentation performance (DSC = 0.95 ± 0.07 versus DSC = 0.93 ± 0.10). Strong anti-correlation (r= -0.76,p< 0.001) between the proposed UM and DSC was observed. A high AUC of 0.98 (97% specificity at 100% sensitivity) was obtained for the discrimination of unacceptable segmentations. Qualitative inspection by the radiologist revealed that images with high UM are difficult to segment.Significance. The use of MC dropout at inference time in combination with the proposed UM enables flagging of unacceptable pectoral muscle segmentations from mammograms with excellent discriminatory power.

Monitoring cone-beam CT radiation dose levels in a University Hospital.

OBJECTIVE: To present patient dose levels for different CBCT scanners, acquired by a dose monitoring tool in a University Hospital, as a function of field of view (FOV), operation mode, and patient age. METHODS: An integrated dose monitoring tool was used to collect radiation exposure data [type of CBCT unit, dose-area product (DAP), FOV size, and operation mode] and patient demographic information (age, referral department) performed on a 3D Accuitomo 170 and a Newtom VGI EVO unit. Effective dose conversion factors were calculated and implemented into the dose monitoring system. For each CBCT unit, the frequency of examinations, clinical indications, and effective dose levels were obtained for different age and FOV groups, and operation modes. RESULTS: A total of 5163 CBCT examinations were analyzed. Surgical planning and follow-up were the most frequent clinical indications. For the standard operation mode, effective doses ranged from 35.1 to 300 µSv and 9.26-117 µSv using 3D Accuitomo 170 and Newtom VGI EVO, respectively. In general, effective doses decreased with increasing age and FOV size reduction. CONCLUSIONS: Effective dose levels varied notably between systems and operation modes.Operation mode selection and FOV size were indication-oriented, with larger FOV sizes election serving surgical planning and follow-up. Seeing the influence of FOV size on effective dose levels, manufacturers could be advised to move toward patient-specific collimation and dynamic FOV selection. Systematically monitoring patient doses could be recommended for steering future CBCT optimization.

Development, Construction, and Evaluation of an Alternative Dosimetry Phantom for Computed Tomography.

This article aims to present the development, construction, and evaluation of an alternative computed tomography dose index (CTDI) phantom. Epoxy resin was mixed with an iodine-based contrast agent to produce radiological characteristics resembling polymethyl methacrylate (PMMA) as a standard CTDI phantom. As a preliminary study, testing was carried out using computed tomography images (80 and 120 kVp) on 12 variations of epoxy-iodine resin mixtures to obtain relative electron density (ρe) values and effective atomic numbers (Zeff) of the samples. The alternative CTDI phantoms were then constructed with a resin-iodine mixture using iodine concentrations that yield on closest ρe and Zeff values to those of PMMA. The evaluation was carried out by comparing dose measurement results at various energies between the alternative phantom and the International Electrotechnical Commission-standard CTDI phantom. At a concentration of 0.46%, the epoxy resin has ρe and Zeff with a deviation against PMMA of 0.12% and 1.58%, respectively, so that composition was chosen for the alternative CTDI phantom construction. The average dose discrepancy values were 5% and 1%, respectively, for the head and body phantoms in the tested tube voltages of 80 kVp, 100 kVp, 120 kVp, and 135 kVp. The Student's t-test result between the alternative and the standard phantoms also showed P < 0.05, indicating the comparability of the alternative CTDI phantom with the standard CTDI phantom.

CTContour: An open-source Python pipeline for automatic contouring and calculation of mean SSDE along the abdomino-pelvic region for CT images; validation on fifteen systems.

PURPOSE: Calculation of the Size Specific Dose Estimate (SSDE) requires accurate delineation of the skin boundary of patient CT slices. The AAPM recommendation for SSDE evaluation at every CT slice is too time intensive for manual contouring, prohibiting real-time or bulk processing; an automated approach is therefore desirable. Previous automated delineation studies either did not fully disclose the steps of the algorithm or did not always manage to fully isolate the patient. The purpose of this study was to develop a validated, freely available, fast, vendor-independent open-source tool to automatically and accurately contour and calculate the SSDE for the abdomino-pelvic region for entire studies in real-time, including flagging of patient-truncated images. METHODS: The Python tool, CTContour, consists of a sequence of morphological steps and scales over multiple cores for speed. Tool validation was achieved on 700 randomly selected slices from abdominal and abdomino-pelvic studies from public datasets. Contouring accuracy was assessed visually by four medical physicists using a 1-5 Likert scale (5 indicating perfect contouring). Mean SSDE values were validated via manual calculation. RESULTS: Contour accuracy validation produced a score of four of five for 98.5 % of the images. A 300 slice exam was contoured and truncation flagged in 6.3 s on a six-core laptop. CONCLUSIONS: The algorithm was accurate even for complex clinical scenarios and when artefacts were present. Fast execution makes it possible to automate the calculation of SSDE in real time. The tool has been published on GitHub under the GNU-GPLv3 license.

Quality assurance of dose management systems.

BACKGROUND AND AIM: Dose management systems (DMS's) have been widely used for radiation dose data collection and analysis, and have been proven useful for optimization. Although DMS's are used for patient dosimetry, a quality assurance (QA) program has not yet been developed. The aim of this work was to propose vendor neutral quality tests and discuss how QA can be established for DMS's to ensure robustness and quality of patient dose data. MATERIALS & METHODS: Different DMS's functions were organized in three groups according to their complexity. As basic functions, we defined those that depend on simple data collection and require data verification. Intermediate functions provide calculations such as effective dose or higher dose alerts, while the advanced group aims to address complicated analyses, such as peak skin dose calculations. RESULTS: An Excel file was developed that includes quality tests on basic and intermediate functions for different modalities (radiography, interventional radiology, CT and mammography) and is provided as Annex. For advanced functionalities, tests are discussed to guide medical physics experts to design their QA program as appropriate. CONCLUSIONS: The QA program is intended to ensure the trustworthy functioning for applications in normal circumstances and patient outliers. As DMS's are systems with regular upgrades, the associated QA program should be a dynamic process that takes into account the functionalities of the DMS and its application in the clinics. Medical physics experts should ensure the safety and accuracy of DMS's, as an essential component in patient dosimetry - part of their mission.

Detection of pulmonary nodules with scoutless fixed-dose ultra-low-dose CT: a prospective study.

OBJECTIVES: To determine the accuracy of scoutless, fixed-dose ultra-low-dose (ULD) CT compared to standard-dose (SD) CT for pulmonary nodule detection and semi-automated nodule measurement, across different patient sizes. METHODS: Sixty-three patients underwent ULD and SD CT. Two readers examined all studies visually and with computer-aided detection (CAD). Nodules detected on SD CT were included in the reference standard by consensus and stratified into 4 categories (nodule category, NODCAT) from the Dutch-Belgian Lung Cancer Screening trial (NELSON). Effects of NODCAT and patient size on nodule detection were determined. For each nodule, volume and diameter were compared between both scans. RESULTS: The reference standard comprised 173 nodules. For both readers, detection rates on ULD versus SD CT were not significantly different for NODCAT 3 and 4 nodules > 50 mm3 (reader 1: 93% versus 89% (p = 0.257); reader 2: 96% versus 98% (p = 0.317)). For NODCAT 1 and 2 nodules < 50 mm3, detection rates on ULD versus SD CT dropped significantly (reader 1: 66% versus 80% (p = 0.023); reader 2: 77% versus 87% (p = 0.039)). Body mass index and chest circumference did not influence nodule detectability (p = 0.229 and p = 0.362, respectively). Calculated volumes and diameters were smaller on ULD CT (p < 0.0001), without altering NODCAT (84% agreement). CONCLUSIONS: Scoutless ULD CT reliably detects solid lung nodules with a clinically relevant volume (> 50 mm3) in lung cancer screening, irrespective of patient size. Since detection rates were lower compared to SD CT for nodules < 50 mm3, its use for lung metastasis detection should be considered on a case-by-case basis. KEY POINTS: • Detection rates of pulmonary nodules > 50 mm3are not significantly different between scoutless ULD and SD CT (i.e. volumes clinically relevant in lung cancer screening based on the NELSON trial), but were different for the detection of nodules < 50 mm3(i.e. volumes still potentially relevant in lung metastasis screening). • Calculated nodule volumes were on average 0.03 mL or 9% smaller on ULD CT, which is below the 20-25% interscan variability previously reported with software-based volumetry. • Even though a scoutless, fixed-dose ULD CT protocol was used (CTDIvol0.15 mGy), pulmonary nodule detection was not influenced by patient size.

PURSUING OPTIMAL RADIATION DOSE IN PEDIATRIC CARDIAC CT: A REPORT FROM UNIVERSITY HOSPITAL LEUVEN.

BACKGROUND: Computed tomography (CT) balances between high resolution and low radiation dose. Given the greater radiosensitivity of children, it is appropriate to use child-friendly CT-protocols that reduce radiation dose at acceptable image quality.This article states the radiation dose in pediatric cardiac CT-examinations at university hospital Leuven (Belgium) and compares with findings published by similar medical centers. The diagnostic accuracy was simultaneously compared, as it correlates with radiation dose. MATERIAL AND METHODS: his retrospective observational study analyzed 58 CT-scans of 52 patients. The radiation dose was calculated in effective dose. The image quality was scored qualitatively with a 5-point scale. The diagnostic accuracy, a derivative representation of the image quality, was checked with findings from surgery or conventional angiography. RESULTS: The mean effective dose in our study population was 1.3 ± 0.4 mSv. The qualitative image quality was on average 'good', elaborated with a score of 4.0 ± 0.2. The diagnostic accuracy was 92%. Comparative literature study provides a mean effective dose of 1.5 mSv and the reported diagnostic accuracy from other centers reaches ≥90%. CONCLUSIONS: At our center pediatric cardiac CT-scans are obtained with good-to-excellent image quality and high diagnostic accuracy at low radiation doses. These results meet the radiation dose and diagnostic accuracy as published by comparable medical centers.