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.

In this study, a 3 × 3 blue micro-LED array with a pixel size of 10 × 10 μm2 and a pitch of 15 μm was fabricated on an epilayer grown on a sapphire substrate using metalorganic chemical vapor deposition technology. The fabrication process involved photolithography, wet and dry etching, E-beam evaporation, and ion implantation technology. Arsenic multi-energy implantation was utilized to replace the mesa etching for electrical isolation, where the implantation depth increased with the average energy. Different ion depth profiles had varying effects on electrical properties, such as forward current and leakage currents, potentially causing damage to the n-GaN layer and increasing the series resistance of the LEDs. As the implantation depth increased, the light output power and peak external quantum efficiency of the LEDs also increased, improving from 5.33 to 9.82%. However, the efficiency droop also increased from 46.3 to 48.6%.

Determining the correct magnified pixel size of single-particle cryoEM micrographs is necessary to maximize resolution and enable accurate model building. Here we describe a simple and rapid procedure for determining the absolute magnification in an electron cryomicroscope to a precision of <0.5%. We show how to use the atomic lattice spacings of crystals of thin and readily available test specimens, such as gold, as an absolute reference to determine magnification for both room temperature and cryogenic imaging. We compare this method to other commonly used methods, and show that it provides comparable accuracy in spite of its simplicity. This magnification calibration method provides a definitive reference quantity for data analysis and processing, simplifies the combination of multiple datasets from different microscopes and detectors, and improves the accuracy with which the contrast transfer function of the microscope can be determined. We also provide an open source program, magCalEM, which can be used to accurately estimate the magnified pixel size of a cryoEM dataset ex post facto.

Aim. Flat panel detectors with small pixel sizes general can potentially improve imaging performance in radiography applications requiring fine detail resolution. This study evaluated the imaging performance of seven detectors, covering a wide range of pixel sizes, in the frame of orthopaedic applications.Material and methods. Pixel sizes ranged from 175 (detector A175) to 76μm (detector G76). Modulation transfer function (MTF) and detective quantum efficiency (DQE) were measured using International Electrotechnical Commission (IEC) RQA3 beam quality. Threshold contrast (CT) and a detectability index (d\') were measured at three air kerma/image levels. Rabbit shoulder images acquired at 60 kV, over five air kerma levels, were evaluated in a visual grading study for anatomical sharpness, image noise and overall diagnostic image quality by four radiologists. The detectors were compared to detector E124.Results. The 10% point of the MTF ranged from 3.21 to 4.80 mm-1, in going from detector A175to detector G76. DQE(0.5 mm-1) measured at 2.38μGy/image was 0.50 ± 0.05 for six detectors, but was higher for F100at 0.62. High frequency DQE was superior for the smaller pixel detectors, howeverCTfor 0.25 mm discs correlated best with DQE(0.5 mm-1). Correlation betweenCTand the detectability model was good (R2= 0.964).CTfor 0.25 mm diameter discs was significantly higher for D150and F100compared to E124. The visual grading data revealed higher image quality ratings for detectors D125and F100compared to E124. An increase in air kerma was associated with improved perceived sharpness and overall quality score, independent of detector. Detectors B150, D125, F100and G76, performed well in specific tests, however only F100consistently outperformed the reference detector.Conclusion. Pixel size alone was not a reliable predictor of small detail detectability or even perceived sharpness in a visual grading analysis study.

OBJECTIVE: Myocardial blood flow (MBF) and myocardial flow reserve (MFR) are measurable by 13N-NH3 positron emission tomography (PET). MFR, which is the ratio of MBF under adenosine stress to MBF at rest, is prognostically valuable. The ASNC imaging guidelines/SNMMI procedure standards recommend using 2-3 mm pixels, and pixel size does differ between institutions. We sought to evaluate the effects of pixel sizes on the quantitative values calculated from 13N-NH3 PET images.
METHODS: Thirty consecutive patients with ischemic heart disease who underwent 13N-NH3 PET were retrospectively enrolled. Dynamic images were quantified using PMOD\'s cardiac PET analysis tool (pixel sizes: 3.18, 2.03, and 1.59 mm). MBF under adenosine stress, MBF at rest, and MFR for the right coronary artery (RCA) region, left anterior descending artery region, and left circumflex coronary artery branch region innervation regions were calculated at each pixel size and compared.
RESULTS: Quantitative values did not significantly differ according to pixel size in any of the regions. However, MFR values for the RCA fluctuated the most. Ischemic and non-ischemic regions remained visually discernible in qualitative images, with no variation in quantitative values, regardless of pixel size.
CONCLUSIONS: Quantitative values were not significantly affected by pixel sizes within the recommended range of 2-3 mm. Values for the RCA region may have been overestimated, but this was true for all pixel sizes.

OBJECTIVE: Small photon beams used in radiotherapy techniques have inherent characteristics of charge particle disequilibrium and high-dose gradient making accurate dosimetry for such fields very challenging. By means of a 3D manufacturing technique, it is possible to create arrays of pixels with a very small sensitive volume for radiotherapy dosimetry. We investigate the impact of 3D pixels size on absorbed dose sensitivity, linearity of response with dose rate, reproducibility and beam profile measurements.
METHODS: Diamond detectors with different pixel sizes have been produced in the 3DOSE experiment framework. To investigate the pixels size impact, they were tested using an Elekta Synergy LINAC. Dose rate dependence, absorbed dose sensitivity, reproducibility and beam profile measurement accuracy have been investigated and compared with PTW 60019 and IBA SFD reference dosimeters.
RESULTS: All of the 3D pixels had a linear and reproducible response to the dose rate. The sensitivity of a pixel decreases with its size, although even the smallest pixel has a high absorbed dose sensitivity (15 nC/Gy). The penumbra width measured with the smallest pixel size was consistent with the PTW microDiamond and differed by 0.2 mm from the IBA SFD diode.
CONCLUSIONS: The study demonstrates that variation in pixel size do not affect the linearity of response with dose rate and the reproducibility of response. Due to the 3D geometry, the absorbed dose sensitivity of the detector remains high even for the smallest pixel, furthermore the pixel size was demonstrated to be of fundamental importance in the measurement of beam profiles.

To investigate the effects of the pixel sizes and the electrode structures on the performance of Ge-based terahertz (THz) photoconductive detectors, vertical structure Ge:Ga detectors with different structure parameters were fabricated. The characteristics of the detectors were investigated at 4.2 K, including the spectral response, blackbody response (Rbb), dark current density-voltage characters, and noise equivalent power (NEP). The detector with the pixel radius of 400 μm and the top electrode of the ring structure showed the best performance. The spectral response band of this detector was about 20-180 μm. The Rbb of this detector reached as high as 0.92 A/W, and the NEP reached 5.4 × 10-13 W/Hz at 0.5 V. Compared with the detector with a pixel radius of 1000 μm and the top electrode of the spot structure, the Rbb increased nearly six times, and the NEP decreased nearly 12 times. This is due to the fact that the optimized parameters increased the equivalent electric field of the detector. This work provides a route for future research into large-scale array Ge-based THz detectors.

BACKGROUND: Small peripheral nerve tractography is challenging because of the trade-off among resolution, image acquisition time, and signal-to-noise ratio.
OBJECTIVE: To optimize pixel size and slice thickness parameters for fiber tractography and diffusion tensor imaging (DTI) of the ulnar nerve at the cubital tunnel using 3T magnetic resonance imaging (MRI).
METHODS: Fifteen healthy volunteers (mean age 30 ± 6.8 years) were recruited prospectively. Axial T2-weighted and DTI scans were acquired, covering the cubital tunnel, using different pixel sizes and slice thicknesses. Three-dimensional (3D) nerve tractography was evaluated for the median number and length of the reconstructed fiber tracts and visual score from 0 to 5. Two-dimensional (2D) cross-sectional DTI was evaluated for fractional anisotropy (FA) values throughout the length of the ulnar nerve.
RESULTS: A pixel size of 1.3 mm2 revealed the highest number of reconstructed nerve fibers compared to that of 1.1 mm2 (P = 0.048), with a good visual score. A slice thickness of 4 mm had the highest number of reconstructed nerve fibers and visual score compared with other thicknesses (all P < 0.05). In 2D cross-sectional images, the median FA values were in the range of 0.40-0.63 at the proximal, central, and distal portions of the cubital tunnel. Inter-observer agreement for all parameters was good to excellent.
CONCLUSIONS: For fiber tractography and DTI of the ulnar nerve at the cubital tunnel, optimal image quality was obtained using a 1.3-mm2 pixel size and 4-mm slice thickness under MR parameters of this study at 3T.

We recently reported (Sobhani et al., 2020) that when a confocal Raman microscope imaged a nanoplastic with the diameter of 100 nm, the imaging lateral size was 300-400 nm, due to the diffraction limit of the laser spot. In this study, we examine the lateral intensity distribution of the Raman signal emitted by nanoplastics (diameters ranging ∼30-600 nm) within the excitation laser spot. We find that the Raman emission intensity, similar to the excitation power density distributed within a laser spot, also follows a lateral Gaussian distribution. To image and visualise individual nanoplastics, we (i) decrease the mapping pixel size, in a hope to generate an image with high-resolution and simultaneously to pick up items from the \"blind point\". We can then either (ii) offset the colour to intentionally image only the high-intensity portion of the Raman signal (emitted from the centre of the laser spot), to localise the exact position of the nanoplastic; or (iii) categorise the imaged nanoplastics to different groups via their Raman intensity, to simultaneously and separately visualise large nanoplastics/strong Raman signals, medium nanoplastics and small nanoplastics, in an effort to avoid the shielding and overlooking of weak signals. We (iv) also cross-check multi-images simultaneously mapped at two or three characteristic peaks via either a logic-OR or a logic-AND algorithm. Thus the imaging uncertainty can be significantly reduced from a statistical point of view.

The acquisition of high-quality, anatomic images is essential for the accurate delineation of tumor volumes and critical structures used for stereotactic radiosurgery (SRS) treatment planning. This study investigates the effect of CT slice thickness and field of view (FOV), i.e., longitudinal and axial CT resolution, on volume delineation and treatment planning in SRS and suggests optimal CT acquisition parameters for brain SRS simulation. Optimization of such parameters will maximize clinical efficacy, alter data storage requirements, reduce dosimetric uncertainties, and may ultimately facilitate more favorable clinical outcomes. Changes in the extent, shape and the absolute volume of the GTV were recorded when the longitudinal and axial CT resolution were modified. These changes ultimately impacted the PTV dose coverage. Reducing CT slice thickness from 2mm to 1mm resulted in an average decrease of 8.6%±13.9% (max=52.2%) and 3.0 %±4.3% (max=13.1%) in PTV Dmin and PTV D95, respectively. Increasing CT slice thickness from 2mm to 3mm resulted in an average decrease of 10%±9.9% (max=26.8%) and 5.8%±5.8% (max=17.4%) in PTV Dmin and PTV D95, respectively. Similarly, on average, PTV coverage decreased when FOV decreased. The average decrease in PTV Dmin and PTV D95 for a 350cm FOV was 5.2%±7.2% (max=21.4%) and 1.9%±3.2% (max=7.5%), respectively. Decreasing FOV to 250cm yielded similar results with the average decrease of 5.6%±5.0% (max=13.2%) and 1.6%±2.6% (max=6.3%) in PTV Dmin and PTV D95, respectively. These results suggest that the slice thickness and FOV of CT images affect target delineation and may potentially compromise the quality of the target coverage.