The AIRO(®) system is an easy-to-use and versatile iCT for navigated spinal instrumentation and provides high pedicle screw accuracy rates. Although the authors' experience suggests that the learning curve associated with AIRO(®)-based spinal navigation is steep, a systematic user-based approach to the technology is required.

The majority of the patients showed little differences in NTCPs between the different delineation guidelines. However, large NTCP differences >10% were found in 7% of the patients. For correct use of NTCP models in individual patients, uniform delineation guidelines are of great importance.

Background: We aimed at reviewing design and realisation of perfusion/flow phantoms for validating quantitative perfusion imaging (PI) applications to encourage best practices. Methods: A systematic search was performed on the Scopus database for "perfusion", "flow", and "phantom", limited to articles written in English published between January 1999 and December 2018. Information on phantom design, used PI and phantom applications was extracted. Results: Of 463 retrieved articles, 397 were rejected after abstract screening and 32 after full-text reading. The 37 accepted articles resulted to address PI simulation in brain (n = 11), myocardial (n = 8), liver (n = 2), tumour (n = 1), finger (n = 1), and non-specific tissue (n = 14), with diverse modalities: ultrasound (n = 11), computed tomography (n = 11), magnetic resonance imaging (n = 17), and positron emission tomography (n = 2). Three phantom designs were described: basic (n = 6), aligned capillary (n = 22), and tissue-filled (n = 12). Microvasculature and tissue perfusion were combined in one compartment (n = 23) or in two separated compartments (n = 17). With the only exception of one study, inter-compartmental fluid exchange could not be controlled. Nine studies compared phantom results with human or animal perfusion data. Only one commercially available perfusion phantom was identified. Conclusion: We provided insights into contemporary phantom approaches to PI, which can be used for ground truth evaluation of quantitative PI applications. Investigators are recommended to verify and validate whether assumptions underlying PI phantom modelling are justified for their intended phantom application.

Objective: Exercise-induced bronchoconstriction (EIB) is a specific morbidity of childhood asthma and a sign of insufficient disease control. EIB is diagnosed and monitored based on lung function changes after a standardized exercise challenge test (ECT). In daily practice however, EIB is often evaluated with self-reported respiratory symptoms and spirometry. We aimed to study the capacity of pediatricians to predict EIB based on information routinely available during an outpatient clinic visit. Methods: A clinical assessment was performed in 20 asthmatic children (mean age 11.6 years) from the outpatient clinic of the MST hospital from May 2015 to July 2015. During this assessment, video images were made. EIB was measured with a standardized ECT performed in cold, dry air. Twenty pediatricians (mean years of experience 14.4 years) each evaluated five children, providing 100 evaluations, and predicted EIB severity based on their medical history, physical examination, and video images. EIB severity was predicted again after additionally providing baseline spirometry results. Results: Nine children showed no EIB, four showed mild EIB, two showed moderate, and five showed severe EIB. Based on clinical information and spirometry results, pediatricians detected EIB with a sensitivity of 84% (95% CI 72–91%) and a specificity of 24% (95% CI 14–39%).The agreement between predicted EIB severity classifications and the validated classifications after the ECT was slight [Kappa = 0.05 (95% CI 0.00–0.17)]. This agreement still remained slight when baseline spirometry results were provided [Kappa = 0.19 (95% CI 0.06–0.32)]. Conclusion: Pediatricians' prediction of EIB occurrence was sensitive, but poorly specific. The prediction of EIB severity was poor. Pediatricians should be aware of this in order to prevent misjudgement of EIB severity and disease control.

Background Absolute myocardial perfusion imaging (MPI) is beneficial in the diagnosis and prognosis of patients with suspected or known coronary artery disease. However, validation and standardization of perfusion estimates across centers is needed to ensure safe and adequate integration into the clinical workflow. Physical myocardial perfusion models can contribute to this clinical need as these can provide ground-truth validation of perfusion estimates in a simplified, though controlled setup. This work presents the design and realization of such a myocardial perfusion phantom and highlights initial performance testing of the overall phantom setup using dynamic single photon emission computed tomography. Results Due to anatomical and (patho-)physiological representation in the 3D printed myocardial perfusion phantom, we were able to acquire 22 dynamic MPI datasets in which 99mTc-labelled tracer kinetics was measured and analyzed using clinical MPI software. After phantom setup optimization, time activity curve analysis was executed for measurements with normal myocardial perfusion settings (1.5 mL/g/min) and with settings containing a regional or global perfusion deficit (0.8 mL/g/min). In these measurements, a specific amount of activated carbon was used to adsorb radiotracer in the simulated myocardial tissue. Such mimicking of myocardial tracer uptake and retention over time satisfactorily matched patient tracer kinetics. For normal perfusion levels, the absolute mean error between computed myocardial blood flow and ground-truth flow settings ranged between 0.1 and 0.4 mL/g/min. Conclusion The presented myocardial perfusion phantom is a first step toward ground-truth validation of multimodal, absolute MPI applications in the clinical setting. Its dedicated and 3D printed design enables tracer kinetic measurement, including time activity curve and potentially compartmental myocardial blood flow analysis.

We aim to facilitate phantom-based (ground truth) evaluation of dynamic, quantitative myocardial perfusion imaging (MPI) applications. Current MPI phantoms are static representations or lack clinical hard- and software evaluation capabilities. This proof-of-concept study demonstrates the design, realisation and testing of a dedicated cardiac flow phantom. The 3D printed phantom mimics flow through a left ventricular cavity (LVC) and three myocardial segments. In the accompanying fluid circuit, tap water is pumped through the LVC and thereafter partially directed to the segments using adjustable resistances. Regulation hereof mimics perfusion deficit, whereby flow sensors serve as reference standard. Seven phantom measurements were performed while varying injected activity of 99mTc-tetrofosmin (330–550 MBq), cardiac output (1.5–3.0 L/min) and myocardial segmental flows (50–150 mL/min). Image data from dynamic single photon emission computed tomography was analysed with clinical software. Derived time activity curves were reproducible, showing logical trends regarding selected input variables. A promising correlation was found between software computed myocardial flows and its reference ($$\rho$$ ρ = − 0.98; p = 0.003). This proof-of-concept paper demonstrates we have successfully measured first-pass LV flow and myocardial perfusion in SPECT-MPI using a novel, dedicated, myocardial perfusion phantom. Graphical abstract This proof-of-concept study focuses on the development of a novel, dedicated myocardial perfusion phantom, ultimately aiming to contribute to the evaluation of quantitative myocardial perfusion imaging applications.

Institutional diagnostic workflows regarding coronary artery disease (CAD) may differ greatly. Myocardial perfusion imaging (MPI) is a commonly used diagnostic method in CAD, whereby multiple modalities are deployed to assess relative or absolute myocardial blood flow (MBF) (e.g. with SPECT, PET, MR, CT, or combinations). In line with proper clinical decision-making, it is essential to assess institutional MPI test validity by confronting MBF assessment to a ground truth. Our research focuses on developing such validation instrument/method for MPI by means of simulating controlled myocardial perfusion in a phantom flow setup. A first step was made in the process of method development and validation by specifying basic requirements for the phantom flow setup. First tests in CT-MPI were aimed to gain experience in clinical testing, to verify to which extent the set requirements are met, and to evaluate the steps needed to further improve accuracy and reproducibility of measurements. The myocardium was simulated as a static cylinder and placed in a controllable pulsatile flow circuit whereby using flow sensors as reference. First flow experiments were performed for different stroke volumes (20-35 mL/stroke). After contrast injection, dynamic MPI-CT scans (SOMATOM Force, Siemens) were obtained to investigate the relation between first-pass measured and computed flow. We observed a moderate correlation; hence, the required accuracy and reproducibility levels were not met. However, we have gained new insights in factors regarding the measurement setup and MBF computation process that might affect instrument validation, which we will incorporate in future flow setup design and testing.

This proof-of-concept study explores the multimodal application of a dedicated cardiac flow phantom for ground truth contrast measurements in dynamic myocardial perfusion imaging with CT, PET/CT, and MRI. A 3D-printed cardiac flow phantom and flow circuit mimics the shape of the left ventricular cavity (LVC) and three myocardial regions. The regions are filled with tissue-mimicking materials and the flow circuit regulates and measures contrast flow through LVC and myocardial regions. Normal tissue perfusion and perfusion deficits were simulated. Phantom measurements in PET/CT, CT, and MRI were evaluated with clinically used hardware and software. The reference arterial input flow was 4.0 L/min and myocardial flow 80 mL/min, corresponding to myocardial blood flow (MBF) of 1.6 mL/g/min. The phantom demonstrated successful completion of all processes involved in quantitative, multimodal myocardial perfusion imaging (MPI) applications. Contrast kinetics in time intensity curves were in line with expectations for a mimicked perfusion deficit (38 s vs. 32 s in normal tissue). Derived MBF in PET/CT and CT led to under- and overestimation of reference flow of 0.9 mL/g/min and 4.5 mL/g/min, respectively. Simulated perfusion deficit (0.8 mL/g/min) in CT resulted in MBF of 2.8 mL/g/min. We successfully performed initial, quantitative perfusion measurements with a dedicated phantom setup utilizing clinical hardware and software. These results showcase the multimodal phantom’s potential.