RESUMEN

We compared the computed tomography (CT) numbers from monochromatic images obtained using the first-generation (Discovery CT750 HD: GE Healthcare, Milwaukee, WI) and second-generation (Revolution CT: GE HealthCare) dual-energy CT (first and second DECT) scanners in phantom and clinical studies. In a polypropylene phantom, eight polypropylene tubes containing iodine at various concentrations (0.5, 1, 2, 5, 10, 12, 20, 30 mg I per ml) were arranged in an outer circle. The iodine densities and CT numbers obtained after imaging with different-generation DECT scanners were analyzed. The CT numbers from images obtained from 61 consecutive patients with aortic disease who underwent CT with different-generation DECT scanners were compared during the arterial and delayed phases. The iodine concentration obtained from second DECT was more accurate than that from the first DECT in the phantom study. A significantly higher contrast enhancement was observed with the second DECT compared with the first DECT during the arterial phase in the clinical study. Contrast enhancement was higher with the second DECT than with the first DECT, and the second DECT was effective in minimizing the use of contrast materials.

Asunto(s)

RESUMEN

OBJECTIVES: During computed tomography (CT), a large amount of ionizing radiation is emitted to ensure high quality of the obtained radiological image. This study measured the dose distribution around the CT scanner and the exposure of people staying near the CT scanner during the examination. MATERIAL AND METHODS: The measurements used an anthropomorphic phantom to assess human exposure to ionizing radiation. The probability of inducing leukemia and other cancers as a result of absorbing doses recorded around the CT device was also calculated. RESULTS: The highest exposure to scattered radiation in the proximity of the CT scanner is recorded at the gantry of the tomograph, i.e., 55.7 µGy, and the lowest, below lower detection limit of 6 µGy at the end of the diagnostic table. The whole-body detector placed on the anthropomorphic phantom located at the diagnostic table right next to the CT gantry recorded 59.5 µSv and at the end of the table 1.5 µSv. The average doses to the lenses in these locations were: 32.1 µSv and 2.9 µSv, respectively. CONCLUSIONS: The probability of induction of leukemia or other types of cancer is low, but the need for people to stay in the examination room during a CT examination should be limited to the necessary minimum. Int J Occup Med Environ Health. 2024;37(3):326-34.

Asunto(s)

RESUMEN

BACKGROUND: This study investigated whether the Combat compensation method can remove the variability of radiomic features extracted from different scanners, while also examining its impact on the subsequent predictive performance of machine learning models. MATERIALS AND METHODS: 135 CT images of Credence Cartridge Radiomic phantoms were collected and screened from three scanners manufactured by Siemens, Philips, and GE. 100 radiomic features were extracted and 20 radiomic features were screened according to the Lasso regression method. The radiomic features extracted from the rubber and resin-filled regions in the cartridges were labeled into different categories for evaluating the performance of the machine learning model. Radiomics features were divided into three groups based on the different scanner manufacturers. The radiomic features were randomly divided into training and test sets with a ratio of 8:2. Five machine learning models (lasso, logistic regression, random forest, support vector machine, neural network) were employed to evaluate the impact of Combat on radiomic features. The variability among radiomic features were assessed using analysis of variance (ANOVA) and principal component analysis (PCA). Accuracy, precision, recall, and area under the receiver curve (AUC) were used as evaluation metrics for model classification. RESULTS: The principal component and ANOVA analysis results show that the variability of different scanner manufacturers in radiomic features was removed (P˃0.05). After harmonization with the Combat algorithm, the distributions of radiomic features were aligned in terms of location and scale. The performance of machine learning models for classification improved, with the Random Forest model showing the most significant enhancement. The AUC value increased from 0.88 to 0.92. CONCLUSIONS: The Combat algorithm has reduced variability in radiomic features from different scanners. In the phantom CT dataset, it appears that the machine learning model's classification performance may have improved after Combat harmonization. However, further investigation and validation are required to fully comprehend Combat's impact on radiomic features in medical imaging.

Asunto(s)

RESUMEN

PURPOSE: To evaluate the efficiency of organ-based tube current modulation (OBTCM) in head Computed Tomography (CT) for different radiology departments and manufacturers. MATERIALS AND METHODS: Five CT scanners from four radiology departments were evaluated in this study. All scans were performed using a standard and a routine head protocol. A scintillating fiber optic detector was placed directly on the gantry to measure the tube exit kerma. Image quality was quantified on a 16-cm HEAD phantom by measuring the signal-to-noise ratio (SNR) and the standard deviation of the Hounsfield units (HU) of circular regions of interest placed in the phantom. The Noise Power Spectrum (NPS) was also studied. Measured values were compared on images with and without OBTCM. RESULTS: The reduction rates in tube exit kerma, on the anterior part, vary between 11 % and 74 % depending on the CT scanner and the protocol used. The tube exit kerma on the posterior part remains unchanged in GE and Canon CT scanners. On the contrary, the tube exit kerma to the posterior part increases by up to 39 % in Siemens CT scanner. Image noise and SNR increase by up to 10 % in the five CT scanners. Nonetheless, the differences in noise and SNR are statistically significant (p-value < 0.05).The analysis of the NPS indicates that the noise texture remains unchanged. CONCLUSION: OBTCM reduces the tube exit kerma to the anterior part of the gantry without reducing substantially image quality for head protocols.

Asunto(s)

RESUMEN

PURPOSE: A computational method based on Monte-Carlo calculations is presented and used to calculate isodose curves for a new upright and tilting CT scanner useful for radiation protection purposes. METHODS: The TOPAS code platform with imported CAD files for key components was used to construct a calculation space for the scanner. A sphere of water acts as the patient would by creating scatter out of the bore. Maximum intensity dose maps are calculated for various possible tilt angles to make sure radiation protection for site planning uses the maximum possible dose everywhere. RESULTS: The resulting maximum intensity isodose lines are more rounded than ones for just a single tilt angle and so closer to isotropic. These maximum intensity curves are closer to the isotropic assumption used in CTDI or DLP based methods of site planning and radiation protection. The isodose lines are similar to those of a standard CT scanner, just tilted upwards. There is more metal above the beam that lessens the dose above versus below isocenter. CONCLUSION: Aside from the orientation, this upright scanner is very similar to a typical CT scanner, and nothing different for shielding needs to be done for this new upright tilting CT scanner, because an isotropic scatter source is often assumed for any CT scanner.

Asunto(s)

RESUMEN

The OligoMetastatic Esophagogastric Cancer (OMEC) project aims to provide clinical practice guidelines for the definition, diagnosis, and treatment of esophagogastric oligometastatic disease (OMD). Guidelines were developed according to AGREE II and GRADE principles. Guidelines were based on a systematic review (OMEC-1), clinical case discussions (OMEC-2), and a Delphi consensus study (OMEC-3) by 49 European expert centers for esophagogastric cancer. OMEC identified patients for whom the term OMD is considered or could be considered. Disease-free interval (DFI) was defined as the time between primary tumor treatment and detection of OMD. Moderate to high quality of evidence was found (i.e. 1 randomized and 4 non-randomized phase II trials) resulting in moderate recommendations. OMD is considered in esophagogastric cancer patients with 1 organ with ≤ 3 metastases or 1 involved extra-regional lymph node station. In addition, OMD continues to be considered in patients with OMD without progression in number of metastases after systemic therapy. 18F-FDG PET/CT imaging is recommended for baseline staging and for restaging after systemic therapy when local treatment is considered. For patients with synchronous OMD or metachronous OMD and a DFI ≤ 2 years, recommended treatment consists of systemic therapy followed by restaging to assess suitability for local treatment. For patients with metachronous OMD and DFI > 2 years, upfront local treatment is additionally recommended. These multidisciplinary European clinical practice guidelines for the uniform definition, diagnosis and treatment of esophagogastric OMD can be used to standardize inclusion criteria in future clinical trials and to reduce variation in treatment.

Asunto(s)

RESUMEN

PURPOSE: To investigate the operation principles of the automatic tube current modulation (ATCM) of a modern GE healthcare CT scanner, and the impact of related settings on image quality and patient dose. MATERIAL & METHODS: A dedicated phantom (Mercury 4.0) was scanned using two of the most frequently used clinical scanning protocols (chest and abdomen-pelvis). The preset protocol settings were used as starting points (reference conditions). Scan direction, scan mode (helical vs. axial), total beam width, tube potential (kVp), and ATCM settings were then modified individually to understand their impact on radiation dose and image quality. Regarding the ATCM settings, the SmartmA minimum and maximum mA limits, and the noise index (NI) values were varied. As surrogates of patient dose, the CTDIvol and DLP values of each scan were used. As surrogates of image quality were used the image noise and the detectability index (d') of five different materials (air, solid water, polystyrene, iodine, and bone) embedded in the Mercury phantom calculated with the ImQuest software. RESULTS: The scanning direction did not have any effect on ATCM curves, unlike what has been observed in CT scanners from other manufacturers. Total beam width does matter, however, the SmartmA limit settings and kVp selection had the greatest impact on image quality and dose. It was seen that improper minimum mA limit settings practically invalidated the ATCM operation. In contrast, when full modulation was allowed without restrictions, noise standard deviation, and detectability index became much more consistent across the wide range of phantom diameters. For lower kVp settings an impressive dose reduction was observed that requires further investigation. CONCLUSION: SmartmA is a tool that if not properly used may increase the patient doses considerably. Therefore, its settings should be carefully adjusted for each preset different clinical protocol.

Asunto(s)

RESUMEN

CT protocol management is an arduous task that requires expertise from a variety of radiology professionals, including technologists, radiologists, radiology IT professionals, and medical physicists. Each CT vendor has unique, proprietary protocol file structures, some of which may vary by scanner model, making it difficult to develop a universal framework for distilling technical parameters to a human-readable file format. An ideal solution for CT protocol management is to minimize the work required for parameter extraction by introducing a data format into the workflow that is universal to all CT scanners. In this paper, we report a framework for CT protocol management that converts raw protocol files to an intermediary format before outputting them in a human-readable format for a variety of practical clinical applications, including routine protocol review, protocol version tracking, and cross-protocol comparisons. The framework was developed in Python 3. Technical parameters of interest were determined via collaborative effort between medical physicists and lead technologists. Protocol files were extracted and analyzed from a variety of scanners across our hospital-wide CT fleet, including various systems from Siemens and GE. Protocols were subcategorized based on relevant technical parameters into regular, dual-energy, and cardiac CT protocols. Backend code for technical parameter extraction from raw protocol files to a JavaScript Object Notation (JSON) format was performed on a per-system basis. Conversion from JSON to a readable output format (MS Excel) was performed identically for all scanners using the universal framework developed and presented in this work. Example results for Siemens and GE scanners are shown, including side-by-side comparisons for protocols with similar clinical indications. In conclusion, our CT protocol management framework may be deployed on any CT system to improve clinical efficiency in protocol review and upkeep.

Asunto(s)

RESUMEN

In this study, an evaluation of the compliance test data from 684 computed tomography (CT)-scanners in Indonesia for the 2019-22 test period was carried out. The study was aimed to describe the performance profile of CT-scanners in Indonesia and evaluate the testing protocol. A total of 87.8% of the CT-scanners unconditionally passed the tests, 8.8% passed the tests with conditions and 3.4% failed the tests. Of the devices conditionally passed the tests, the top two causes were water CT number accuracy (45.2%) and laser position accuracy (41.9%). Meanwhile, 75.0% of the failed devices were due to failing to meet the patient dose test criteria. The failure of the test for the water CT number accuracy parameter was caused by variations in the type of phantom used in the test, where several types of phantoms did not use water as material of the homogeneity module. Failures in laser position accuracy test were caused by the passing criteria that adjust to the minimum slice thickness, so that modern CT-scanner with small detector sizes and collimations tend not to pass. On the other hand, the failure on dose aspects was due to the frequent unavailability of baseline values for comparison. Of these top three failure causes, two of them, namely the CT number and dose test parameters, have been accommodated in the latest regulation (BAPETEN Regulation No. 2/2022) with a change in the evaluation method, while for the laser position accuracy test it is recommended to alter the passing criteria to an absolute value, namely 1 mm.

Asunto(s)

RESUMEN

Computed tomography (CT) arthrography is a quickly available imaging modality to investigate elbow disorders. Its excellent spatial resolution enables the detection of subtle pathologic changes of intra-articular structures, which makes this technique extremely valuable in a joint with very tiny chondral layers and complex anatomy of articular capsule and ligaments. Radiation exposure has been widely decreased with the novel CT scanners, thereby increasing the indications of this examination. The main applications of CT arthrography of the elbow are the evaluation of capsule, ligaments, and osteochondral lesions in both the settings of acute trauma, degenerative changes, and chronic injury due to repeated microtrauma and overuse. In this review, we discuss the normal anatomic findings, technical tips for injection and image acquisition, and pathologic findings that can be encountered in CT arthrography of the elbow, shedding light on its role in the diagnosis and management of different orthopedic conditions. We aspire to offer a roadmap for the integration of elbow CT arthrography into routine clinical practice, fostering improved patient outcomes and a deeper understanding of elbow pathologies.

Asunto(s)

RESUMEN

BACKGROUND AND PURPOSE: This work introduces the first assessment of CT calibration following the ESTRO's consensus guidelines and validating the HLUT through the irradiation of biological material. METHODS: Two electron density phantoms were scanned with two CT scanners using two CT scan energies. The stopping power ratio (SPR) and mass density (MD) HLUTs for different CT scan energies were derived using Schneider's and ESTRO's methods. The comparison metric in this work is based on the Water-Equivalent Thickness (WET) difference between the treatment planning system and biological irradiation measurement. The SPR HLUTs were compared between the two calibration methods. To assess the accuracy of using MD HLUT for dose calculation in the treatment planning system, MD vs SPR HLUT was compared. Lastly, the feasibility of using a single SPR HLUT to replace two different energy CT scans was explored. RESULTS: The results show a WET difference of less than 3.5% except for the result in the Bone region between Schneider's and ESTRO's methods. Comparing MD and SPR HLUT, the results from MD HLUT show less than a 3.5% difference except for the Bone region. However, the SPR HLUT shows a lower mean absolute percentage difference as compared to MD HLUT between the measured and calculated WET difference. Lastly, it is possible to use a single SPR HLUT for two different CT scan energies since both WET differences are within 3.5%. CONCLUSION: This is the first report on calibrating an HLUT following the ESTRO's guidelines. While our result shows incremental improvement in range uncertainty using the ESTRO's guideline, the prescriptional approach of the guideline does promote harmonization of CT calibration protocols between different centres.

Asunto(s)

RESUMEN

The use of mobile head CT scanners in the neurointensive care unit (NICU) saves time for patients and NICU staff and can reduce transport-related mishaps, but the reduced image quality of previous mobile scanners has prevented their widespread clinical use. This study compares the image quality of SOMATOM On.Site (Siemens Healthineers, Erlangen, Germany), a state-of-the-art mobile head CT scanner, and a conventional 64-slice stationary CT scanner. The study included 40 patients who underwent head scans with both mobile and stationary scanners. Gray and white matter signal and noise were measured at predefined locations on axial slices, and signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) were calculated. Artifacts below the cranial calvaria and in the posterior fossa were also measured. In addition, image quality was subjectively assessed by two radiologists in terms of corticomedullary differentiation, subcalvarial space, skull artifacts, and image noise. Quantitative measurements showed significantly higher image quality of the stationary CT scanner in terms of noise, SNR and CNR of gray and white matter. Artifacts measured in the posterior fossa were higher with the mobile CT scanner, but subcalvarial artifacts were comparable. Subjective image quality was rated similarly by two radiologists for both scanners in all domains except image noise, which was better for stationary CT scans. The image quality of the SOMATOM On.Site for brain scans is inferior to that of the conventional stationary scanner, but appears to be adequate for daily use in a clinical setting based on subjective ratings.

Asunto(s)

RESUMEN

OBJECTIVE: This study identifies key characteristics to help build a physical liver computed tomography (CT) phantom for radiomics harmonization; particularly, the higher-order texture metrics. MATERIALS AND METHODS: CT scans of a radiomics phantom comprising of 18 novel 3D printed inserts with varying size, shape, and material combinations were acquired on a 64-slice CT scanner (Brilliance 64, Philips Healthcare). The images were acquired at 120 kV, 250 mAs, CTDIvol of 16.36 mGy, 2 mm slice thickness, and iterative noise-reduction reconstruction (iDose, Philips Healthcare, Andover, MA). Radiomics analysis was performed using the Cancer Imaging Phenomics Toolkit (CaPTk), following automated segmentation of 3D regions of interest (ROI) of the 18 inserts. The findings were compared to three additional ROI obtained of an anthropomorphic liver phantom, a patient liver CT scan, and a water phantom, at comparable imaging settings. Percentage difference in radiomic metrics values between phantom and tissue was used to assess the biological equivalency and <10% was used to claim equivalent. RESULTS: The HU for all 18 ROI from the phantom ranged from -30 to 120 which is within clinically observed HU range of the liver, showing that our phantom material (T3-6B) is representative of biological CT tissue densities (liver) with >50% radiomic features having <10% difference from liver tissue. Based on the assessment of the Neighborhood Gray Tone Difference Matrix (NGTDM) metrics it is evident that the water phantom ROI show extreme values compared to the ROIs from the phantom. This result may further reinforce the difference between a structureless quantity such as water HU values and tissue HU values found in liver. CONCLUSION: The 3-D printed patterns of the constructed radiomics phantom cover a wide span of liver tissue textures seen in CT images. Using our results, texture metrics can be selectively harmonized to establish clinically relevant and reliable radiomics panels.

Asunto(s)

RESUMEN

AIM: To report on the performance characteristics of the 5-ring GE Discovery MI PET/CT systems using the AAPM TG-126 report and compare these results to NEMA NU 2-2012 where applicable. MATERIALS AND METHODS: TG-126 testing was performed on two GE 5-Rings Discovery MI scanners. Tests performed included spatial resolution, PET/CT image-registration accuracy, sensitivity, count rate performance, accuracy of corrections, image contrast, scatter/attenuation correction, and image uniformity. All acquired data were analyzed using scanner console or free software tools as described by TG-126 and the results were then compared to published NEMA NU 2-2012 values. RESULTS: Both scanners gave similar resolution results for TG-126 and NEMA NU 2-2012 and were within manufacturer specifications. Image-registration accuracy between PET and CT using our clinical protocol showed excellent results with values ≤1 mm. Sensitivity using TG-126 was 19.43 cps/kBq while for NEMA the value was 20.73 cps/kBq. The peak noise-equivalent counting rate was 2174 kcps at 63.1 kBq/mL and is not comparable to NEMA NU 2-2012 due to differences in phantoms and methods used to measure and calculate this parameter. The accuracy of corrections for count losses for TG-126 were expressed in SUV values and found to be within 10% of the expected SUV measurement of 1. Image contrast and scatter/attenuation correction using the TG-126 method gave acceptable results. Image uniformity assessment resulted in values within the recommended ± 5% limits. CONCLUSION: These results show that the 5-ring GE Discovery MI PET/CT scanner testing using TG-126 is reproducible and has similar results to NEMA NU 2-2012 tests where applicable. We hope these results start to form the basis to compare PET/CT systems using TG-126.

Asunto(s)

RESUMEN

BACKGROUND: Standards for image quality evaluation in multi-detector CT (MDCT) and cone-beam CT (CBCT) are evolving to keep pace with technological advances. A clear need is emerging for methods that facilitate rigorous quality assurance (QA) with up-to-date metrology and streamlined workflow suitable to a range of MDCT and CBCT systems. PURPOSE: To evaluate the feasibility and workflow associated with image quality (IQ) assessment in longitudinal studies for MDCT and CBCT with a single test phantom and semiautomated analysis of objective, quantitative IQ metrology. METHODS: A test phantom (CorgiTM Phantom, The Phantom Lab, Greenwich, New York, USA) was used in monthly IQ testing over the course of 1 year for three MDCT scanners (one of which presented helical and volumetric scan modes) and four CBCT scanners. Semiautomated software analyzed image uniformity, linearity, contrast, noise, contrast-to-noise ratio (CNR), 3D noise-power spectrum (NPS), modulation transfer function (MTF) in axial and oblique directions, and cone-beam artifact magnitude. The workflow was evaluated using methods adapted from systems/industrial engineering, including value stream process modeling (VSPM), standard work layout (SWL), and standard work control charts (SWCT) to quantify and optimize test methodology in routine practice. The completeness and consistency of DICOM data from each system was also evaluated. RESULTS: Quantitative IQ metrology provided valuable insight in longitudinal quality assurance (QA), with metrics such as NPS and MTF providing insight on root cause for various forms of system failure-for example, detector calibration and geometric calibration. Monthly constancy testing showed variations in IQ test metrics owing to system performance as well as phantom setup and provided initial estimates of upper and lower control limits appropriate to QA action levels. Rigorous evaluation of QA workflow identified methods to reduce total cycle time to ∼10 min for each system-viz., use of a single phantom configuration appropriate to all scanners and Head or Body scan protocols. Numerous gaps in the completeness and consistency of DICOM data were observed for CBCT systems. CONCLUSION: An IQ phantom and test methodology was found to be suitable to QA of MDCT and CBCT systems with streamlined workflow appropriate to busy clinical settings.

Asunto(s)

RESUMEN

Objective. In this study, nonlinearly frequency-modulated (NLFM) ultrasound was applied to magneto-acousto-electrical tomography (MAET) to increase the dynamic range of detection.Approach. Generation of NLFM signals using window function method-based on the principle of stationary phase-and piecewise linear frequency modulation method-based on the genetic algorithm-was discussed. The MAET experiment systems using spike, linearly frequency-modulated (LFM), or NLFM pulse stimulation were constructed, and three groups of MAET experiments on saline agar phantom samples were carried out to verify the performance-respectively the sensitivity, the dynamic range, and the longitudinal resolution of detection-of MAET using NLFM ultrasound in comparison to that using LFM ultrasound. Based on the above experiments, a pork sample was imaged by ultrasound imaging method, spike MAET method, LFM MAET method, and NLFM MAET method, to compare the imaging accuracy.Main results. The experiment results showed that, through sacrificing very little main-lobe width of pulse compression or equivalently the longitudinal resolution, the MAET using NLFM ultrasound achieved higher signal-to-interference ratio (and therefore higher detection sensitivity), lower side-lobe levels of pulse compression (and therefore larger dynamic range of detection), and large anti-interference capability, compared to the MAET using LFM ultrasound.Significance. The applicability of the MAET using NLFM ultrasound was proved in circumferences where sensitivity and dynamic range of detection were mostly important and slightly lower longitudinal resolution of detection was acceptable. The study furthered the scheme of using coded ultrasound excitation toward the clinical application of MAET.

Asunto(s)

Asunto(s)

RESUMEN

Recent advancements in diagnostic CT detector technology have made it possible to resolve anatomical features smaller than 20 LP/cm, referred to as ultra-high-resolution (UHR) CT. Subtle biological motions that did not affect standard-resolution (SR) CT may not be neglected in UHR. This study aimed to quantify the cardiac-induced motion of the pancreas and simulate its impact on the image quality of UHR-CT. We measured the displacement of the head of the pancreas in three healthy volunteers using Displacement Encoding with Stimulated Echoes (DENSE) MRI. The results were used to simulate SR- and UHR-CT acquisitions affected by pancreatic motion.We found pancreatic displacement in the 0.24-1.59 mm range during one cardiac cycle across the subjects. The greatest displacement was observed in the anterior-posterior direction. The time to peak displacement varied across subjects. Both SR and UHR images showed reduced image quality, as measured by radial modulation transfer function, due to cardiac-induced motion, but the motion artifacts caused more severe degradation in UHR acquisitions. Our investigation of cardiac-induced pancreatic displacement reveals its potential to degrade both standard and UHR-CT scans. To fully utilize the improvement in spatial resolution offered by UHR-CT, the effects of cardiac-induced motion in the abdomen need to be understood and corrected.Relevance statement Advancements in CT detector technology have enhanced CT scanner spatial resolution to approximately 100 µm. Consequently, previously ignored biological motions such as the cardiac-induced motion of the pancreas now demand attention to fully utilize this improved resolution.

Asunto(s)

RESUMEN

INTRODUCTION: Mobile Imaging Trailers enable moving diagnostic imaging equipment between locations requiring very little setup and configuration, example given CT-scanners and MRI-scanners. However, despite the apparent benefits of utilising these imaging capabilities, very little research on the subject exists. This study aims at gaining an overview of the current state of the literature, using the scoping review methodology. METHODS: The systematic literature search was conducted in three databases: Scopus, Embase and PubMed. Included sources were extracted based on the objectives of the scoping review, and inspired by the by PRISMA-ScR. RESULTS: 29 papers were included. CONCLUSION: The results of the review showed that three general categories of research on this subject exist - trailers used in research, trailers as the object of research and trailers as an element or tool of the research. Of these, the most prevalent one used is the latter - trailers used as an element or tool of the research. This; however, is an issue for the use of trailers in a clinical setting, as very little research has been conducted on how they might be used and how they compare to fixed installations. As seen during the recent COVID-19 pandemic, the potentials for the use of MITs are immense; however, with the current lack of knowledge and understanding, the full potential has not been realised, suggesting further research should be focused in this area. IMPLICATIONS FOR PRACTICE: This study has shown that the limited research in the area does point towards a few benefits of MITs; however, there is a clear lack of sufficient research on the field to say this with confidence.

Asunto(s)

RESUMEN

BACKGROUND: Multislice spiral computed tomography (MSCT) requires an interpolation between adjacent detector rows during backprojection. Not satisfying the Nyquist sampling condition along the z-axis results in aliasing effects, also known as windmill artifacts. These image distortions are characterized by bright streaks diverging from high contrast structures. PURPOSE: The z-flying focal spot (zFFS) is a well-established hardware-based solution that aims to double the sampling rate in longitudinal direction and therefore reduce aliasing artifacts. However, given the technical complexity of the zFFS, this work proposes a deep learning-based approach as an alternative solution. METHODS: We propose a supervised learning approach to perform a mapping between input projections and the corresponding rows required for double sampling in the z-direction. We present a comprehensive evaluation using both a clinical dataset obtained using raw data from 40 real patient scans acquired with zFFS and a synthetic dataset consisting of 100 simulated spiral scans using a phantom specifically designed for our problem. For the clinical dataset, we utilized 32 scans as training set and 8 scans as validation set, whereas for the synthetic dataset, we used 80 scans for training and 20 scans for validation purposes. Both qualitative and quantitative assessments are conducted on a test set consisting of nine real patient scans and six phantom measurements to validate the performance of our approach. A simulation study was performed to investigate the robustness against different scan configurations in terms of detector collimation and pitch value. RESULTS: In the quantitative comparison based on clinical patient scans from the test set, all network configurations show an improvement in the root mean square error (RMSE) of approximately 20% compared to neglecting the doubled longitudinal sampling by the zFFS. The results of the qualitative analysis indicate that both clinical and synthetic training data can reduce windmill artifacts through the application of a correspondingly trained network. Together with the qualitative results from the test set phantom measurements it is emphasized that a training of our method with synthetic data resulted in superior performance in windmill artifact reduction. CONCLUSIONS: Deep learning-based raw data interpolation has the potential to enhance the sampling in z-direction and thus minimize aliasing effects, as it is the case with the zFFS. Especially a training with synthetic data showed promising results. While it may not outperform zFFS, our method represents a beneficial solution for CT scanners lacking the necessary hardware components for zFFS.

Asunto(s)