UNASSIGNED: The current study provides insights into the challenges of safely operating a magnetic resonance imaging (MRI)-guided focused ultrasound (MRgFUS) robotic system in a high-field MRI scanner in terms of robotic motion accuracy.
UNASSIGNED: Grid sonications were carried out in phantoms and excised porcine tissue in a 3T MRI scanner using an existing MRgFUS robotic system. Fast low-angle shot-based magnetic resonance thermometry was employed for the intraprocedural monitoring of thermal distribution.
UNASSIGNED: Strong shifting of the heated spots from the intended points was observed owing to electromagnetic interference (EMI)-induced malfunctions in system\'s operation. Increasing the slice thickness of the thermometry sequence to at least 8 mm was proven an efficient method for preserving the robotic motion accuracy.
UNASSIGNED: These findings raise awareness about EMI effects on the motion accuracy of MRgFUS robotic devices and how they can be mitigated by employing suitable thermometry parameters.

BACKGROUND: Computer-aided modeling and design (CAM/CAD) of patient anatomy from computed tomography (CT) imaging and 3D printing technology enable the creation of tangible, patient-specific anatomic models that can be used for surgical guidance. These models have been associated with better patient outcomes; however, a lack of CT imaging guidelines risks the capture of unsuitable imaging for patient-specific modeling. This study aims to investigate how CT image pixel size (X-Y) and slice thickness (Z) impact the accuracy of mandibular models.
METHODS: Six cadaver heads were CT scanned at varying slice thicknesses and pixel sizes and turned into CAD models of the mandible for each scan. The cadaveric mandibles were then dissected and surface scanned, producing a CAD model of the true anatomy to be used as the gold standard for digital comparison. The root mean square (RMS) value of these comparisons, and the percentage of points that deviated from the true cadaveric anatomy by over 2.00 mm were used to evaluate accuracy. Two-way ANOVA and Tukey-Kramer post-hoc tests were used to determine significant differences in accuracy.
RESULTS: Two-way ANOVA demonstrated significant difference in RMS for slice thickness but not pixel size while post-hoc testing showed a significant difference in pixel size only between pixels of 0.32 mm and 1.32 mm. For slice thickness, post-hoc testing revealed significantly smaller RMS values for scans with slice thicknesses of 0.67 mm, 1.25 mm, and 3.00 mm compared to those with a slice thickness of 5.00 mm. No significant differences were found between 0.67 mm, 1.25 mm, and 3.00 mm slice thicknesses. Results for the percentage of points deviating from cadaveric anatomy greater than 2.00 mm agreed with those for RMS except when comparing pixel sizes of 0.75 mm and 0.818 mm against 1.32 mm in post-hoc testing, which showed a significant difference as well.
CONCLUSIONS: This study suggests that slice thickness has a more significant impact on 3D model accuracy than pixel size, providing objective validation for guidelines favoring rigorous standards for slice thickness while recommending isotropic voxels. Additionally, our results indicate that CT scans up to 3.00 mm in slice thickness may provide an adequate 3D model for facial bony anatomy, such as the mandible, depending on the clinical indication.

BACKGROUND: Thinner slices are more susceptible in detecting small lesions but suffer from higher statistical fluctuation. This work aimed to reduce image noise in multiphase contrast-enhanced CT reconstructed with slice thickness thinner than the clinical setting (i.e., 5 mm) using convolutional neural network (CNN) for enabling better detection of hypo-vascular liver metastasis.
METHODS: A DenseNet model was used to generate noise map for multiphase CT reconstructed with slice thickness of 2.5 mm and 1.25 mm. Image denoising was conducted by subtracting the CNN-generated noise map from CT images with reduced photon flux due to thinner slice thickness. The performance of DenseNet was evaluated on CT scans of electron density phantoms and patients with hypovascular liver metastases less than 1.5 cm in terms of Hounsfield Unit (HU) variation, statistical fluctuation, and contrast-to-noise ratio (CNR).
RESULTS: The phantom study demonstrated that the CNN-based denoising method was able to reduce statistical fluctuation in CT images reconstructed with slice thickness of 2.5 mm and 1.25 mm without causing significant edge blurring or variation in HU values. With regards to patient study, it was found that the denoised 2.5-mm and 1.25-mm slices had higher CNR than the conventional 5-mm slices for hypo-vascular liver metastases in all 4 phases of multiphase CT.
CONCLUSIONS: Our results demonstrated that the detection of hypo-vascular liver metastases in multiphase contrast-enhanced CT with slice thickness less than 5 mm could be improved by using the CNN-based denoising method.
CONCLUSIONS: Reconstruction slice thickness has a strong influence on the image quality of CT imaging. A CNN-based denoising method was used in this work to reduce the image noise in multiphase contrast-enhanced CT reconstructed with slice thickness less than 5 mm.

UNASSIGNED: Radiomics posits that quantified characteristics from radiographic images reflect underlying pathophysiology. Lung cancer (LC) is one of the prevalent forms of cancer, causing mortality. Slice thickness (ST) of computed tomography (CT) images is a crucial factor influencing the generalizability of radiomic features (RF) in oncology. There is scarcity of research that how ST affects variability of RF in LC. The present study helps in identifying the specific RF categories affected by variations in ST and provides valuable insights for researchers and clinicians working with RF in the field of LC.Hence, aim of the study is to evaluate influence of ST on reproducibility of CT-RF for lung tumors.
UNASSIGNED: This is a prospective study, 32 patients with confirmed histopathological diagnosis of lung tumors were included. Contrast Enhanced CT (CECT) thorax was performed using a 128- Incisive CT (Philips Health Care). The image acquisition was performed with 5-mm and 2 mm STwas reconstructed retrospectively. RF were extracted from the CECT thorax images of both ST. We conducted a paired t-test to evaluate the disparity in RF between the two thicknesses. Lin\'s Concordance Correlation Coefficient (CCC) was performed to identify the reproducibility of RF between the two thicknesses.
UNASSIGNED: Out of 107 RF, 66 (61.6%) exhibited a statistically significant distinction (p<0.05) when comparing two ST and while 41 (38.3%) RF did not show significant distinction (p>0.05) between the two ST measurements. 29 features (CCC ≥ 0.90) showed excellent to moderate reproducibility, and 78 features (CCC ≤ 0.90) showed poor reproducibility. Among the 7 RF categories, the shape-based features (57.1%) showed the maximum reproducibility whereas NGTDM-based features showed negligible reproducibility.
UNASSIGNED: The ST had a notable impact on the majority of CT-RF of lung tumors. Shape based features (57.1%). First order (44.4%) features showed highest reproducibility compared to other RF categories.

OBJECTIVE: Several studies present the unsuitability of the tilted-wire method for slice sensitivity profile (SSP) in helical scan. We compared the accuracy for SSP by the tilted-wire averaging method using multiple wire profiles and by the conventional micro-coin method.
METHODS: A micro-coin phantom positioned at the center or the off-center was scanned using a 64-detector row CT scanner in different positions where an X-ray tube starts scanning. In the same way, tilted-wire averaging phantoms, approximately 70 mm in diameter, in the shape of a donut, 8 wires tilted from the circumference toward the center, were scanned. Images were reconstructed with a slice thickness of 0.5 mm.
RESULTS: The relative errors of full width at half maximum (FWHM) by the tilted-wire averaging method were -0.015 mm to -0.004 mm (-1.98% to -0.56%) at the center compared to those by the micro-coin method, and it is almost the same value regardless of the number of wires. Relative errors were 0.001 mm to 0.029 mm (0.11% to 3.74%) at the upper 8 cm from the center, and 0.014 mm to 0.078 mm (1.86% to 10.25%) at the upper 16 cm, and the value of relative errors increased as it got farther from the center and as the number of wires went fewer.
CONCLUSIONS: This study indicated that accurate measurement of SSP may be achieved by using 4 (arranged every 90 degrees) or more averaging wires.

Purpose. The use of the Hough transform for angle detection is quite accurate for relatively wide slice thickness. However, the Hough transform fails to accurately detect the angle for thin slice thickness. This study proposes a method for automatically measuring the thickness of thin slices on images of a Catphan phantom.Methods. In the proposed method, the angle of the phantom\'s orientation was determined based on the relative coordinates of the four hole objects in the phantom. After the angles of the wires were determined, the profiles of pixel values across the wire objects were constructed. Finally, their full widths at half maximum (FWHMs) were determined and multiplied bytan23° to obtain the slice thicknesses of the images. The results of the proposed method were compared to a previous method, which used the Hough transform to obtain the phantom\'s orientation. We used slice thicknesses ranging from 0.8 mm to 5.0 mm, and phantom angles from 0° to 10°.Results. Our proposed method detected the angle of the phantom accurately for thin slices, whereas a previous method did not accurately detect the angle. The results of the slice thickness using this current method were slightly higher (within 7.9%) compared to the previous method. However, the results of the two methods did not differ significantly (p-value > 0.05). Using different angles, the current method detected all the angles more accurately. Again, the slice thicknesses were not significantly different from the previous method (p-value > 0.05).Conclusion. The proposed method for measuring the thickness of thin slices in an image of a Catphan phantom, based on the relative coordinates of the four hole objects in the phantom, outperformed a previous method based on the Hough transform.

Photon-counting detector computed tomography (PCD-CT) yields improved spatial resolution. The combined use of PCD-CT and a modern iterative reconstruction method, known as quantum iterative reconstruction (QIR), has the potential to significantly improve the quality of lung CT images. In this study, we aimed to analyze the impacts of different slice thicknesses and QIR levels on low-dose ultra-high-resolution (UHR) PCD-CT imaging of the lungs. Our study included 51 patients with different lung diseases who underwent unenhanced UHR-PCD-CT scans. Images were reconstructed using three different slice thicknesses (0.2, 0.4, and 1.0 mm) and three QIR levels (2-4). Noise levels were determined in all reconstructions. Three raters evaluated the delineation of anatomical structures and conspicuity of various pulmonary pathologies in the images compared to the clinical reference reconstruction (1.0 mm, QIR-3). The highest QIR level (QIR-4) yielded the best image quality. Reducing the slice thickness to 0.4 mm improved the delineation and conspicuity of pathologies. The 0.2 mm reconstructions exhibited lower image quality due to high image noise. In conclusion, the optimal reconstruction protocol for low-dose UHR-PCD-CT of the lungs includes a slice thickness of 0.4 mm, with the highest QIR level. This optimized protocol might improve the diagnostic accuracy and confidence of lung imaging.

Left atrial catheter ablation is well established in patients with symptomatic atrial fibrillation (AF) but associated with risk of embolism to the brain. The present analysis aims to assess the impact of diffusion-weighted imaging (DWI) slice thickness on the rate of magnetic resonance imaging (MRI)-detected ischaemic brain lesions after ablation.
AXAFA-AFNET 5 trial (NCT02227550) participants underwent MRI using high-resolution (hr) DWI (slice thickness: 2.5-3 mm) and standard DWI (slice thickness: 5-6 mm) within 3-48 h after ablation. In 321 patients with analysable brain MRI (mean age 64 years, 33% female, median CHA2DS2-VASc 2), hrDWI detected at least one acute brain lesion in 84 (26.2%) patients and standard DWI in 60 (18.7%; P < 0.01) patients. High-resolution diffusion-weighted imaging detected more lesions compared to standard DWI (165 vs. 104; P < 0.01). The degree of agreement for lesion confirmation using hrDWI vs. standard DWI was substantial (κ = 0769). Comparing the proportion of DWI-detected lesions, lesion distribution, and total lesion volume per patient, there was no difference in the cohort of participants undergoing MRI at 1.5 T (n = 52) vs. 3 T (n = 269).
The pre-specified AXAFA-AFNET 5 sub-analysis revealed significantly increased rates of MRI-detected acute brain lesions using hrDWI instead of standard DWI in AF patients undergoing ablation. In comparison to DWI slice thickness, MRI field strength had a no significant impact in the trial. Comparing the varying rates of ablation-related MRI-detected brain lesions across previous studies has to consider these technical parameters. Future studies should use hrDWI, as feasibility was demonstrated in the multicentre AXAFA-AFNET 5 trial.

This study aimed to investigate the effect of using slice partial Fourier (SPF), phase partial Fourier (PPF), and radial scan (Elliptical scanning) methods on image quality. Changes in signal-to-noise ratio (SNR), effective slice thickness, and in-plane resolution were measured in 3D-gradient echo when SPF, PPF, and radial scan were used. Effective slice thickness increased and SNR increased when SPF was used; in-plane resolution decreased and SNR decreased when PPF was used; effective slice thickness did not change, in-plane resolution decreased, and SNR increased when the radial scan method was used. The radial scan method reduces image quality and imaging time compared to those in the SPF and PPF methods.

High-quality and detailed CT scan images are crucial for accurate diagnosis. Factors such as image noise and slice thickness affect image quality. This study aimed to determine the optimal slice thickness that minimized image noise while maintaining sufficient diagnostic information using the single-source computed tomography head protocol. Single-source CT images were examined using the Linux Operating system Ge Revolution 64-slice CT scanner, and a combination of statical analysis and DICOM CT image analysis was employed. The single-source energy head CT protocol was used to investigate the effect of slice thickness on noise and visibility in images. Different values of slice thickness 0.625, 1.25, 2.5, 3.75, 5, 7.5, and 10 were prepared, and then quantitative analysis was performed. Thinner slice thickness decreased image noise, increased visibility, and improved detection. Therefore, the balance between changing the thickness of the slice with the diagnostic content and image noise must be considered. Maximum slice thickness enhances CT image detail and structure despite more noise. Based on the results, a slice thickness of 1.25mm was identified as the optimal choice for reducing image noise and achieving better and more accurate detection using the single-source computed tomography head protocol. The study revealed that image noise tends to increase with greater slice thickness according to the Linux operating system. These findings can serve as a valuable guide for quality control methods in CT centers, emphasizing the need to determine the appropriate slice thickness to ensure an accurate diagnosis.