Impact of signal-to-noise ratio and contrast definition on the sensitivity assessment and benchmarking of fluorescence molecular imaging systems.

Significance: Standardization of fluorescence molecular imaging (FMI) is critical for ensuring quality control in guiding surgical procedures. To accurately evaluate system performance, two metrics, the signal-to-noise ratio (SNR) and contrast, are widely employed. However, there is currently no consensus on how these metrics can be computed. Aim: We aim to examine the impact of SNR and contrast definitions on the performance assessment of FMI systems. Approach: We quantified the SNR and contrast of six near-infrared FMI systems by imaging a multi-parametric phantom. Based on approaches commonly used in the literature, we quantified seven SNRs and four contrast values considering different background regions and/or formulas. Then, we calculated benchmarking (BM) scores and respective rank values for each system. Results: We show that the performance assessment of an FMI system changes depending on the background locations and the applied quantification method. For a single system, the different metrics can vary up to ∼ 35 dB (SNR), ∼ 8.65 a . u . (contrast), and ∼ 0.67 a . u . (BM score). Conclusions: The definition of precise guidelines for FMI performance assessment is imperative to ensure successful clinical translation of the technology. Such guidelines can also enable quality control for the already clinically approved indocyanine green-based fluorescence image-guided surgery.

The effect of elimination of gibbs ringing, noise and systematic errors on the DTI metrics and tractography in a rat brain.

Diffusion tensor imaging (DTI) metrics and tractography can be biased due to low signal-to-noise ratio (SNR) and systematic errors resulting from image artifacts and imperfections in magnetic field gradients. The imperfections include non-uniformity and nonlinearity, effects caused by eddy currents, and the influence of background and imaging gradients. We investigated the impact of systematic errors on DTI metrics of an isotropic phantom and DTI metrics and tractography of a rat brain measured at high resolution. We tested denoising and Gibbs ringing removal methods combined with the B matrix spatial distribution (BSD) method for magnetic field gradient calibration. The results showed that the performance of the BSD method depends on whether Gibbs ringing is removed and the effectiveness of stochastic error removal. Region of interest (ROI)-based analysis of the DTI metrics showed that, depending on the size of the ROI and its location in space, correction methods can remove systematic bias to varying degrees. The preprocessing pipeline proposed and dedicated to this type of data together with the BSD method resulted in an even - 90% decrease in fractional anisotropy (FA) (globally and locally) in the isotropic phantom and - 45% in the rat brain. The largest global changes in the rat brain tractogram compared to the standard method without preprocessing (sDTI) were noticed after denoising. The direction of the first eigenvector obtained from DTI after denoising, Gibbs ringing removal and BSD differed by an average of 56 and 10 degrees in the ROI from sDTI and from sDTI after denoising and Gibbs ringing removal, respectively. The latter can be identified with the amount of improvement in tractography due to the elimination of systematic errors related to imperfect magnetic field gradients. Based on the results, the systematic bias for high resolution data mainly depended on SNR, but the influence of non-uniform gradients could also be seen. After denoising, the BSD method was able to further correct both the metrics and tractography of the diffusion tensor in the rat brain by taking into account the actual distribution of magnetic field gradients independent of the examined object and uniquely dependent on the scanner and sequence. This means that in vivo studies are also subject to this type of errors, which should be taken into account when processing such data.

An in-vivo treatment monitoring system for ion-beam radiotherapy based on 28 Timepix3 detectors.

Ion-beam radiotherapy is an advanced cancer treatment modality offering steep dose gradients and a high biological effectiveness. These gradients make the therapy vulnerable to patient-setup and anatomical changes between treatment fractions, which may go unnoticed. Charged fragments from nuclear interactions of the ion beam with the patient tissue may carry information about the treatment quality. Currently, the fragments escape the patient undetected. Inter-fractional in-vivo treatment monitoring based on these charged nuclear fragments could make ion-beam therapy safer and more efficient. We developed an ion-beam monitoring system based on 28 hybrid silicon pixel detectors (Timepix3) to measure the distribution of fragment origins in three dimensions. The system design choices as well as the ion-beam monitoring performance measurements are presented in this manuscript. A spatial resolution of 4 mm along the beam axis was achieved for the measurement of individual fragment origins. Beam-range shifts of 1.5 mm were identified in a clinically realistic treatment scenario with an anthropomorphic head phantom. The monitoring system is currently being used in a prospective clinical trial at the Heidelberg Ion Beam Therapy Centre for head-and-neck as well as central nervous system cancer patients.

Verification of the effect of data-driven brain motion correction on PET imaging.

INTRODUCTION: Brain positron emission tomography/computed tomography (PET/CT) scans are useful for identifying the cause of dementia by evaluating glucose metabolism in the brain with F-18-fluorodeoxyglucose or Aß deposition with F-18-florbetaben. However, since imaging time ranges from 10 to 30 minutes, movements during the examination might result in image artifacts, which interfere with diagnosis. To solve this problem, data-driven brain motion correction (DDBMC) techniques are capable of performing motion corrected reconstruction using highly accurate motion estimates with high temporal resolution. In this study, we investigated the effectiveness of DDBMC techniques on PET/CT images using a Hoffman phantom, involving continuous rotational and tilting motion, each expanded up to approximately 20 degrees. MATERIALS AND METHODS: Listmode imaging was performed using a Hoffman phantom that reproduced rotational and tilting motions of the head. Brain motion correction processing was performed on the obtained data. Reconstructed images with and without brain motion correction processing were compared. Visual evaluations by a nuclear medicine specialist and quantitative parameters of images with correction and reference still images were compared. RESULTS: Normalized Mean Squared Error (NMSE) results demonstrated the effectiveness of DDBMC in compensating for rotational and tilting motions during PET imaging. In Cases 1 and 2 involving rotational motion, NMSE decreased from 0.15-0.2 to approximately 0.01 with DDBMC, indicating a substantial reduction in differences from the reference image across various brain regions. In the Structural Similarity Index (SSIM), DDBMC improved it to above 0.96 Contrast assessment revealed notable improvements with DDBMC. In continuous rotational motion, % contrast increased from 42.4% to 73.5%, In tilting motion, % contrast increased from 52.3% to 64.5%, eliminating significant differences from the static reference image. These findings underscore the efficacy of DDBMC in enhancing image contrast and minimizing motion induced variations across different motion scenarios. CONCLUSIONS: DDBMC processing can effectively compensate for continuous rotational and tilting motion of the head during PET, with motion angles of approximately 20 degrees. However, a significant limitation of this study is the exclusive validation of the proposed method using a Hoffman phantom; its applicability to the human brain has not been investigated. Further research involving human subjects is necessary to assess the generalizability and reliability of the presented motion correction technique in real clinical scenarios.

Non-contact elasticity contrast imaging using photon counting.

Significance: Tissues' biomechanical properties, such as elasticity, are related to tissue health. Optical coherence elastography produces images of tissues based on their elasticity, but its performance is constrained by the laser power used, working distance, and excitation methods. Aim: We develop a new method to reconstruct the elasticity contrast image over a long working distance, with only low-intensity illumination, and by non-contact acoustic wave excitation. Approach: We combine single-photon vibrometry and quantum parametric mode sorting (QPMS) to measure the oscillating backscattered signals at a single-photon level and derive the phantoms' relative elasticity. Results: We test our system on tissue-mimicking phantoms consisting of contrast sections with different concentrations and thus stiffness. Our results show that as the driving acoustic frequency is swept, the phantoms' vibrational responses are mapped onto the photon-counting histograms from which their mechanical properties-including elasticity-can be derived. Through lateral and longitudinal laser scanning at a fixed frequency, a contrast image based on samples' elasticity can be reliably reconstructed upon photon level signals. Conclusions: We demonstrated the reliability of QPMS-based elasticity contrast imaging of agar phantoms in a long working distance, low-intensity environment. This technique has the potential for in-depth images of real biological tissue and provides a new approach to elastography research and applications.

Magnetic resonance thermometry for hyperthermia in the oropharynx region.

Magnetic resonance thermometry (MRT) can measure in-vivo 3D-temperature changes in real-time and noninvasively. However, for the oropharynx region and the entire head and neck, motion potentially introduces large artifacts. Considering long treatment times of 60-90 min, this study aims to evaluate whether MRT around the oropharynx is clinically feasible for hyperthermia treatments and quantify the effects of breathing and swallowing on MRT performance. A 3D-ME-FGRE sequence was used in a phantom cooling down and around the oropharynx of five volunteers over ∼75 min. The imaging protocol consisted of imaging with acceleration (ARC = 2), number of image averages (NEX = 1,2 and 3). For volunteers, the acquisitions included a breath-hold scan and scans with deliberate swallowing. MRT performance was quantified in neck muscle, spinal cord and masseter muscle, using mean average error (MAE), mean error (ME) and spatial standard deviation (SD). In phantom, an increase in NEX leads to a significant decrease in SD, but MAE and ME were unchanged. No significant difference was found in volunteers between the different scans. There was a significant difference between the regions evaluated: neck muscle had the best MAE (=1.96 °C) and SD (=0.82 °C), followed by spinal cord (MAE = 3.17 °C, SD = 0.92 °C) and masseter muscle (MAE = 4.53 °C, SD = 1.16 °C). Concerning the ME, spinal cord did best, then neck muscle and masseter muscle, with values of -0.64 °C, 1.15 °C and -3.05 °C respectively. Breathing, swallowing, and different ways of imaging (acceleration and NEX) do not significantly influence the MRT performance in the oropharynx region. The ROI selected however, leads to significant differences.

Using torsional wave elastography to evaluate spring pot parameters in skin tumor mimicking phantoms.

Estimating the tissue parameters of skin tumors is crucial for diagnosis and effective therapy in dermatology and related fields. However, identifying the most sensitive biomarkers require an optimal rheological model for simulating skin behavior this remains an ongoing research endeavor. Additionally, the multi-layered structure of the skin introduces further complexity to this task. In order to surmount these challenges, an inverse problem methodology, in conjunction with signal analysis techniques, is being employed. In this study, a fractional rheological model is presented to enhance the precision of skin tissue parameter estimation from the acquired signal from torsional wave elastography technique (TWE) on skin tumor-mimicking phantoms for lab validation and the estimation of the thickness of the cancerous layer. An exhaustive analysis of the spring-pot model (SP) solved by the finite difference time domain (FDTD) is conducted. The results of experiments performed using a TWE probe designed and prototyped in the laboratory were validated against ultrafast imaging carried out by the Verasonics Research System. Twelve tissue-mimicking phantoms, which precisely simulated the characteristics of skin tissue, were prepared for our experimental setting. The experimental data from these bi-layer phantoms were measured using a TWE probe, and the parameters of the skin tissue were estimated using inverse problem-solving. The agreement between the two datasets was evaluated by comparing the experimental data obtained from the TWE technique with simulated data from the SP- FDTD model using Pearson correlation, dynamic time warping (DTW), and time-frequency representation. Our findings show that the SP-FDTD model and TWE are capable of determining the mechanical properties of both layers in a bilayer phantom, using a single signal and an inverse problem approach. The ultrafast imaging and the validation of TWE results further demonstrate the robustness and reliability of our technology for a realistic range of phantoms. This fusion of the SP-FDTD model and TWE, as well as inverse problem-solving methods has the potential to have a considerable impact on diagnoses and treatments in dermatology and related fields.

Electric field and SAR reduction in high-impedance RF arrays by using high permittivity materials for 7T MR imaging.

In the field of ultra-high field MR imaging, the challenges associated with higher frequencies and shorter wavelengths necessitate rigorous attention to multichannel array design. While the need for such arrays remains, and efforts to increase channel counts continue, a persistent impediment-inter-element coupling-constantly hinders development. This coupling degrades current and field distribution, introduces noise correlation between channels, and alters the frequency of array elements, affecting image quality and overall performance. The goal of optimizing ultra-high field MRI goes beyond resolving inter-element coupling and includes significant safety considerations related to the design changes required to achieve high-impedance coils. Although these coils provide excellent isolation, the higher impedance needs special design changes. However, such changes pose a significant safety risk in the form of strong electric fields across low-capacitance lumped components. This process may raise Specific Absorption Rate (SAR) values in the imaging subject, increasing power deposition and, as a result, the risk of tissue heating-related injury. To balance the requirement of inter-element decoupling with the critical need for safety, we suggest a new solution. Our method uses high-dielectric materials to efficiently reduce electric fields and SAR values in the imaging sample. This intervention tries to maintain B1 efficiency and inter-element decoupling within the existing array design, which includes high-impedance coils. Our method aims to promote the full potential of ultra-high field MRI by alleviating this critical safety concern with minimal changes to the existing array setup.

Optical tuning of copolymer-in-oil tissue-mimicking materials for multispectral photoacoustic imaging.

Objective. The availability of tissue-mimicking materials (TMMs) for manufacturing high-quality phantoms is crucial for standardization, evaluating novel quantitative approaches, and clinically translating new imaging modalities, such as photoacoustic imaging (PAI). Recently, a gel comprising the copolymer styrene-ethylene/butylene-styrene (SEBS) in mineral oil has shown significant potential as TMM due to its optical and acoustic properties akin to soft tissue. We propose using artists' oil-based inks dissolved and diluted in balsam turpentine to tune the optical properties.Approach. A TMM was fabricated by mixing a SEBS copolymer and mineral oil, supplemented with additives to tune its optical absorption and scattering properties independently. A systematic investigation of the tuning accuracies and relationships between concentrations of oil-based pigments and optical absorption properties of the TMM across visible and near-infrared wavelengths using collimated transmission spectroscopy was conducted. The photoacoustic spectrum of various oil-based inks was studied to analyze the effect of increasing concentration and depth.Main results. Artists' oil-based inks dissolved in turpentine proved effective as additives to tune the optical absorption properties of mineral oil SEBS-gel with high accuracy. The TMMs demonstrated long-term stability and suitability for producing phantoms with desired optical absorption properties for PAI studies.Significance. The findings, including tuning of optical absorption and spectral shape, suggest that this TMM facilitates the development of more sophisticated phantoms of arbitrary shapes. This approach holds promise for advancing the development of PAI, including investigation of the spectral coloring effect. In addition, it can potentially aid in the development and clinical translation of ultrasound optical tomography.

Pulse generators for enhanced magnetomotive ultrasound: Toward a cost-effective imaging for tissue characterization.

Magnetomotive ultrasound (MMUS) stands out as a promising and effective ultrasound-based method for detecting magnetic nanoparticles (MNPs) within tissues. This innovative technique relies on the precise estimation of micrometric displacements induced by the interaction of an external magnetic field with MNPs. Pulsed MMUS has emerged as a strategic alternative to address limitations associated with harmonic excitation, such as heat generation in amplifiers and coils, frequency-dependent tissue mechanical responses, and prolonged magnetic field rise times. Despite the growing interest in MMUS, the devices conventionally employed to excite the coil are not specifically tailored to generate intense magnetic fields while minimizing interference with the transient behavior of induced displacements. To bridge this gap, our work introduces the design and fabrication of two pulse generators: one based on a capacitor-discharge circuit and the other on a resonant-inverter circuit. We evaluated the performance of these pulse generators by considering parameters such as the magnetic field generated, rise and fall times, and their ability to supply sustained current for varied pulse widths across different pulse repetition frequencies. Furthermore, we carried out a practical MMUS implementation using tissue-mimicking phantoms, demonstrating the capability of both devices to achieve magnetic fields of up to 1 T and average displacements of 25 µm within the phantom. In addition, we estimated the shear wave velocity, effective shear modulus, and their temperature-dependent variations. Our findings highlight the versatility and efficacy of the proposed pulse generators and emphasize their potential as low-cost platforms for theranostic applications, enabling the assessment of targeted entities within biological tissues.

Deep learning-enabled high-speed, multi-parameter diffuse optical tomography.

Significance: Frequency-domain diffuse optical tomography (FD-DOT) could enhance clinical breast tumor characterization. However, conventional diffuse optical tomography (DOT) image reconstruction algorithms require case-by-case expert tuning and are too computationally intensive to provide feedback during a scan. Deep learning (DL) algorithms front-load computational and tuning costs, enabling high-speed, high-fidelity FD-DOT. Aim: We aim to demonstrate a simultaneous reconstruction of three-dimensional absorption and reduced scattering coefficients using DL-FD-DOT, with a view toward real-time imaging with a handheld probe. Approach: A DL model was trained to solve the DOT inverse problem using a realistically simulated FD-DOT dataset emulating a handheld probe for human breast imaging and tested using both synthetic and experimental data. Results: Over a test set of 300 simulated tissue phantoms for absorption and scattering reconstructions, the DL-DOT model reduced the root mean square error by 12 % ± 40 % and 23 % ± 40 % , increased the spatial similarity by 17 % ± 17 % and 9 % ± 15 % , increased the anomaly contrast accuracy by 9 % ± 9 % ( µ a ), and reduced the crosstalk by 5 % ± 18 % and 7 % ± 11 % , respectively, compared with model-based tomography. The average reconstruction time was reduced from 3.8 min to 0.02 s for a single reconstruction. The model was successfully verified using two tumor-emulating optical phantoms. Conclusions: There is clinical potential for real-time functional imaging of human breast tissue using DL and FD-DOT.

TEMPy: a toolkit for the modeling of weighted tissue equivalent material in diagnostic imaging.

Objective.Accurate simulation of human tissues is imperative for advancements in diagnostic imaging, particularly in the fields of dosimetry and image quality evaluation. Developing Tissue Equivalent Materials (TEMs) with radiological characteristics akin to those of human tissues is essential for ensuring the reliability and relevance of imaging studies. This study presents the development of a mathematical model and a new toolkit (TEMPy) for obtaining the best composition of materials that mimic the radiological characteristics of human tissues. The model and the toolkit are described, along with an example showcasing its application to obtain desired TEMs.Approach.The methodology consisted of fitting volume fractions of the components of TEM in order to determine its linear attenuation coefficient as close as possible to the linear attenuation coefficient of the reference material. The fitting procedure adopted a modified Least Square Method including a weight function. This function reflects the contribution of the x-ray spectra in the suitable energy range of interest. TEMPy can also be used to estimate the effective atomic number and electron density of the resulting TEM.Main results.TEMPy was used to obtain the chemical composition of materials equivalent to water and soft tissue, in the energy range used in x-ray imaging (10 -150 keV) and for breast tissue using the energy range (5-40 keV). The maximum relative difference between the linear attenuation coefficients of the developed and reference materials was ±5% in the considered energy ranges.Significance.TEMPy facilitates the formulation of TEMs with radiological properties closely mimicking those of real tissues, aiding in the preparation of physical anthropomorphic or geometric phantoms for various applications. The toolkit is freely available to interested readers.

One-step inverse generation network for sparse-view dual-energy CT reconstruction and material imaging.

Objective.Sparse-view dual-energy spectral computed tomography (DECT) imaging is a challenging inverse problem. Due to the incompleteness of the collected data, the presence of streak artifacts can result in the degradation of reconstructed spectral images. The subsequent material decomposition task in DECT can further lead to the amplification of artifacts and noise.Approach.To address this problem, we propose a novel one-step inverse generation network (OIGN) for sparse-view dual-energy CT imaging, which can achieve simultaneous imaging of spectral images and materials. The entire OIGN consists of five sub-networks that form four modules, including the pre-reconstruction module, the pre-decomposition module, and the following residual filtering module and residual decomposition module. The residual feedback mechanism is introduced to synchronize the optimization of spectral CT images and materials.Main results.Numerical simulation experiments show that the OIGN has better performance on both reconstruction and material decomposition than other state-of-the-art spectral CT imaging algorithms. OIGN also demonstrates high imaging efficiency by completing two high-quality imaging tasks in just 50 seconds. Additionally, anti-noise testing is conducted to evaluate the robustness of OIGN.Significance.These findings have great potential in high-quality multi-task spectral CT imaging in clinical diagnosis.

[A dual-domain cone beam computed tomography reconstruction framework with improved differentiable domain transform for cone-angle artifact correction].

OBJECTIVE: We propose a dual-domain cone beam computed tomography (CBCT) reconstruction framework DualCBR-Net based on improved differentiable domain transform for cone-angle artifact correction. METHODS: The proposed CBCT dual-domain reconstruction framework DualCBR-Net consists of 3 individual modules: projection preprocessing, differentiable domain transform, and image post-processing. The projection preprocessing module first extends the original projection data in the row direction to ensure full coverage of the scanned object by X-ray. The differentiable domain transform introduces the FDK reconstruction and forward projection operators to complete the forward and gradient backpropagation processes, where the geometric parameters correspond to the extended data dimension to provide crucial prior information in the forward pass of the network and ensure the accuracy in the gradient backpropagation, thus enabling precise learning of cone-beam region data. The image post-processing module further fine-tunes the domain-transformed image to remove residual artifacts and noises. RESULTS: The results of validation experiments conducted on Mayo's public chest dataset showed that the proposed DualCBR-Net framework was superior to other comparison methods in terms of artifact removal and structural detail preservation. Compared with the latest methods, the DualCBR-Net framework improved the PSNR and SSIM by 0.6479 and 0.0074, respectively. CONCLUSION: The proposed DualCBR-Net framework for cone-angle artifact correction allows effective joint training of the CBCT dual-domain network and is especially effective for large cone-angle region.

A nonparametric measure of contrast in x-ray images.

Objective.We propose a nonparametric figure of merit, the contrast equivalent distance CED, to measure contrast directly from clinical images.Approach.A relative brightness distanceδis calculated by making use of the order statistic of the pixel values. By multiplyingδwith the grey value rangeR, the mean brightness distance MBD is obtained. From the MBD, the CED and the distance-to-noise ratio DNR can be derived. The latter is the ratio of the MBD and a previously suggested nonparametric measureτfor the noise. Since the order statistic is independent of the spatial arrangement of the pixel values, the measures can be obtained directly from clinical images. We apply the new measures to mammography images of an anthropomorphic phantom and of a phantom with a step wedge as well as to CT images of a head phantom.Main results.For low-noise images of a step wedge, the MBD is equivalent to the conventional grey value distance. While this measure permits the evaluation of clinical images, it is sensitive to noise. Therefore, noise has to be quantified at the same time. When the ratioσ/τof the noise standard deviationσtoτis available, validity limits for the CED as a measure of contrast can be established. The new figures of merit can be calculated for entire images as well as on regions of interest (ROI) with an edge length not smaller than 32 px.Significance.The new figures of merit are suited to quantify the quality of clinical images without relying on the assumption of a linear, shift-invariant system. They can be used for any kind of greyscale image, provided the ratioσ/τcan be estimated. This will hopefully help to achieve the optimisation of image quality vs dose required by radioprotection laws.

Design and experimental validation of a metamaterial-based sensor for microwave imaging in breast, lung, and brain cancer detection.

This study proposes an innovative geometry of a microstrip sensor for high-resolution microwave imaging (MWI). The main intended application of the sensor is early detection of breast, lung, and brain cancer. The proposed design consists of a microstrip patch antenna fed by a coplanar waveguide with a metamaterial (MTM) layer-based lens implemented on the back side, and an artificial magnetic conductor (AMC) realized on as a separate layer. The analysis of the AMC's permeability and permittivity demonstrate that the structure exhibits negative epsilon (ENG) qualities near the antenna resonance point. In addition, reflectivity, transmittance, and absorption are also studied. The sensor prototype has been manufactures using the FR4 laminate. Excellent electrical and field characteristics of the structure are confirmed through experimental validation. At the resonance frequency of 4.56 GHz, the realized gain reaches 8.5 dBi, with 3.8 dBi gain enhancement contributed by the AMC. The suitability of the presented sensor for detecting brain tumors, lung cancer, and breast cancer has been corroborated through extensive simulation-based experiments performed using the MWI system model, which employs four copies of the proposed sensor, as well as the breast, lung, and brain phantoms. As demonstrated, the directional radiation pattern and enhanced gain of the sensor enable precise tumor size discrimination. The proposed sensor offers competitive performance in comparison the state-of-the-art sensors described in the recent literature, especially with respect to as gain, pattern directivity, and impedance matching, all being critical for MWI.

Evaluation of low-dose pediatric chest CT examination using in-house developed various age-size pediatric chest phantoms.

PURPOSE: This study aims to develop Various Age-size Pediatric Chest Phantoms (VAPC) to evaluate low-dose protocol that approximates clinical conditions achieved by low organ-specific doses and optimal image quality among the challenges of pediatric size variations. METHODS: Three original pediatric data aged 1, 4, and 7 years were used as a reference for developing VAPC phantoms. Six protocols, namely standard dose (STD) and low dose (low mA and low kV) reconstructed using Filtered Back Projection (FBP) and iterative reconstruction (IR) algorithms, were investigated. This study directly measured the lungs, heart, and spinal cord dose using LD-V1 film. Linearity, Modulation Transfer Function (MTF), Contrast to Noise Ratio (CNR), and Noise Power Spectrum (NPS) were evaluated to assess the CT image quality of the VAPC phantom. RESULTS: This study found that the mean organ-specific dose was higher than CTDIvol. A Comparison of mean lung doses showed VAPC phantom 1 (y.o.) received 74.8% and 137.2% more doses than 4 (y.o.) and 7 (y.o.), respectively. Low kV produces a lower organ dose than low mA. The linearity of CT numbers is not biased at low doses. Differences in age measures significantly influenced organ-specific dose, MTF, CNR, and NPS. CONCLUSION: Smaller pediatrics are still exposed to higher doses at low-dose examinations, whereas larger pediatrics have lower contrast resolution and increased image noise. CT number linearity is unbiased. The combination of low kV with FBP produces higher spatial resolution, while low mA with IR effectively reduces noise to detect low-contrast objects better.

Pterional vs. lateral supraorbital approach in the management of middle cerebral artery aneurysms: insights from a phantom model study.

The pterional approach has traditionally been employed for managing middle cerebral artery (MCA) aneurysms. With potential benefits like reduced surgical morbidity and improved postoperative recovery, the lateral supraorbital approach (LSO) should be considered individually based on aneurysm morphology, location and patient-specific variations of the MCA anatomy, which requires considerable technical expertise traditionally acquired through years of experience. The goal of this study was the development and evaluation of a novel phantom simulator in the context of clinical decision-making in the managmement of MCA aneurysms. For this purpose, high-fidelity simulators inclusive of MCA models with identical M1- and bifurcation aneurysms were manufactured employing 3D reconstruction techniques, additive manufacturing and rheological testings. Medical students, neurosurgical residents, and seasoned neurosurgeons (n = 22) tested and evaluated both approaches. Participants' performances and progress over time were assessed based on objective metrics. The simulator received positive ratings in face and content validity, with mean scores of 4.9 out of 5, respectively. Objective evaluation demonstrated the model's efficacy as a practical training tool, particularly among inexperienced participants. While requiring more technical expertise, results of the comparative analysis suggest that the LSO approach can improve clipping precision and outcome particularly in patients with shorter than average M1-segments. In conclusion, the employed methodology allowed a direct comparison of the pterional and LSO approaches, revealing comparable success rates via the LSO approach while reducing operation time and complication rate. Future research should aim to establish simulators in the context of clinical decision making.

Improved Detection of Small and Low-Density Plaques in Virtual Noncontrast Imaging-based Calcium Scoring at Photon-Counting Detector CT.

Purpose To investigate the impact of plaque size and density on virtual noncontrast (VNC)-based coronary artery calcium scoring (CACS) using photon-counting detector CT and to provide safety net reconstructions for improved detection of subtle plaques in patients whose VNC-based CACS would otherwise be erroneously zero when compared with true noncontrast (TNC)-based CACS. Materials and Methods In this prospective study, CACS was evaluated in a phantom containing calcifications with different diameters (5, 3, and 1 mm) and densities (800, 400, and 200 mg/cm3) and in participants who underwent TNC and contrast-enhanced cardiac photon-counting detector CT (July 2021-March 2022). VNC images were reconstructed at different virtual monoenergetic imaging (55-80 keV) and quantum iterative reconstruction (QIR) levels (QIR,1-4). TNC scans at 70 keV with QIR off served as the reference standard. In vitro CACS was analyzed using standard settings (3.0-mm sections, kernel Qr36, 130-HU threshold). Calcification detectability and CACS of small and low-density plaques were also evaluated using 1.0-mm sections, kernel Qr44, and 120- or 110-HU thresholds. Safety net reconstructions were defined based on background Agatston scores and evaluated in vivo in TNC plaques initially nondetectable using standard VNC reconstructions. Results The in vivo cohort included 63 participants (57.8 years ± 15.5 [SD]; 37 [59%] male, 26 [41%] female). Correlation and agreement between standard CACSVNC and CACSTNC were higher in large- and medium-sized and high- and medium-density than in low-density plaques (in vitro: intraclass correlation coefficient [ICC] ≥ 0.90; r > 0.9 vs ICC = 0.20-0.48; r = 0.5-0.6). Small plaques were not detectable using standard VNC reconstructions. Calcification detectability was highest using 1.0-mm sections, kernel Qr44, 120- and 110-HU thresholds, and QIR level of 2 or less VNC reconstructions. Compared with standard VNC, using safety net reconstructions (55 keV, QIR 2, 110-HU threshold) for in vivo subtle plaque detection led to higher detection (increased by 89% [50 of 56]) and improved correlation and agreement of CACSVNC with CACSTNC (in vivo: ICC = 0.51-0.61; r = 0.6). Conclusion Compared with TNC-based calcium scoring, VNC-based calcium scoring was limited for small and low-density plaques but improved using safety net reconstructions, which may be particularly useful in patients with low calcium scores who would otherwise be treated based on potentially false-negative results. Keywords: Coronary Artery Calcium CT, Photon-Counting Detector CT, Virtual Noncontrast, Plaque Size, Plaque Density Supplemental material is available for this article. © RSNA, 2024.

A prospective study on the effect of tumor shrinkage on exit fluence gamma pass rate in high precision radiotherapy and influence of phantom setup error in patient-specific quality assurance.

PURPOSE: Objective parameters for decision on adaptive radiotherapy depend on patient, tumor and treatment related factors. Present study reports geometric uncertainties occurring during high precision radiotherapy, beam fluence analysis and serial exit dose measurement as a patient-specific tool for adaptive radiotherapy. MATERIALS AND METHODS: Serial exit dose fluence of 24 patients (at baseline and mid-treatment) undergoing IMRT/VMAT treatment were measured. Baseline and midtreatment exit dose evaluation was done using gafchromic films in predefined region of interest. Difference of volume of GTV at baseline (from simulation CT scan) and midtreatment CBCT scan was calculated (ΔGTV). RESULTS: Population based systematic errors (mm) were 4.15, 2.26, 0.88 and random errors (mm) were 2.56, 3.69, and 2.03 in mediolateral (ML), craniocaudal (CC) and anteroposterior (AP) directions respectively. Gamma pass rate reduced with incremental shift. For a 5 mm shift, maximum deviation was found in anteroposterior axis (22.16 ± 7.50) and lowest in mediolateral axis (12.85 ± 4.95). On serial measurement of exit dose fluence, tumor shrinkage significantly influenced gamma pass rate. The mean gamma pass rate was significantly different between groups with 50% shrinkage of tumor volume (86.36 vs 96.24, P = 0.008, on multivariate analysis P = 0.026). CONCLUSION: Rapid fall of gamma pass rate was observed for set up error of ≥3 mm. Serial measurement of exit dose fluence by radiochromic film is a feasible method of exit dose comparison in IMRT/VMAT, where EPID dosimetry is not available with linear accelerator configuration. Our study suggests that there is a significant difference between gamma pass rates of baseline and mid treatment exit dose fluence with greater than 50% tumor shrinkage.