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This phantom study presents a thorough characterization of the physical image quality of a clinical whole-body photon-counting computed tomography (PCCT) scanner. Multiple quality metrics—noise, noise power spectrum (NPS), task transfer function (TTF), and detectability index (d′)—were analyzed across a range of reconstruction algorithms (filtered back projection, FBP, and Quantum Iterative Reconstruction, QIR, with strength levels Q1–Q4), and varying reconstruction kernels (Br40/Br60/Br76/Br98). Both standard (STD, 0.4 mm slice thickness) and high-resolution (HR, 0.2 mm slice thickness) reconstruction modes were assessed. QIR significantly reduced image noise (60–95%) compared to FBP, particularly with sharper kernels. Spatial resolution improved with increasing QIR strength level for smoother kernels and was further enhanced using HR mode with sharp kernels. HR mode exhibited better noise performance than STD with sharper reconstructions, due to the small pixel effect. While STD mode showed higher d′ values for larger objects, HR mode outperformed it for smaller objects and sharper kernels. Compared to a conventional energy-integrating computed tomography system, the PCCT scanner showed superior d′ values under similar settings. Overall, this study highlights the complex interplay between acquisition and reconstruction parameters on image quality, confirms the potential of PCCT technology, and underscores the need for further clinical validation.

Nowadays, given the technological advance in CT imaging and increasing heterogeneity in characteristics of CT scanners, a number of CT scanners with different manufacturers/technologies are often installed in a hospital centre and used by various departments. In this phantom study, a comprehensive assessment of image quality of 5 scanners (from 3 manufacturers and with different models) for head CT imaging, as clinically used at a single hospital centre, was hence carried out. Helical and/or sequential acquisitions of the Catphan-504 phantom were performed, using the scanning protocols (CTDI vol range: 54.7–57.5 mGy) employed by the staff of various Radiology/Neuroradiology departments of our institution for routine head examinations. CT image quality for each scanner/acquisition protocol was assessed through noise level, noise power spectrum (NPS), contrast-to-noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD) and non-uniformity index analyses. Noise values ranged from 3.5 HU to 5.7 HU across scanners/acquisition protocols. NPS curves differed in terms of peak position (range: 0.21–0.30 mm -1 ). A substantial variation of CNR values with scanner/acquisition protocol was observed for different contrast inserts. The coefficient of variation (standard deviation divided by mean value) of CNR values across scanners/acquisition protocols was 18.3%, 31.4%, 34.2%, 30.4% and 30% for teflon, delrin, LDPE, polystyrene and acrylic insert, respectively. An appreciable difference in MTF curves across scanners/acquisition protocols was revealed, with a coefficient of variation of f 50% /f 10% of MTF curves across scanners/acquisition protocols of 10.1%/7.4%. A relevant difference in LCD performance of different scanners/acquisition protocols was found. The range of contrast threshold for a typical object size of 3 mm was 3.7–5.8 HU. Moreover, appreciable differences in terms of NUI values (range: 4.1%-8.3%) were found. The analysis of several quality indices showed a non-negligible variability in head CT imaging capabilities across different scanners/acquisition protocols. This highlights the importance of a physical in-depth characterization of image quality for each CT scanner as clinically used, in order to optimize CT imaging procedures.

Background Photon-counting detector (PCD) technology has the potential to reduce noise in computed tomography (CT). This study aimed to carry out a voxelwise noise characterization for a clinical PCD-CT scanner with a model-based iterative reconstruction algorithm (QIR). Methods Forty repeated axial acquisitions (tube voltage 120 kV, tube load 200 mAs, slice thickness 0.4 mm) of a homogeneous water phantom and CTP404 module (Catphan-504) were performed. Water phantom acquisitions were also performed on a conventional energy-integrating detector (EID) scanner with a sinogram/image-based iterative reconstruction algorithm, using similar acquisition/reconstruction parameters. For smooth/sharp kernels, filtered back projection (FBP)- and iterative-reconstructed images were obtained. Noise maps, non-uniformity index (NUI) of noise maps, image noise histograms, and noise power spectrum (NPS) curves were computed. Results For FBP-reconstructed images of water phantom, mean noise was (smooth/sharp kernel) 11.7 HU/51.1 HU and 18.3 HU/80.1 HU for PCD-scanner and EID-scanner, respectively, with NUI values for PCD-scanner less than half those for EID-scanner. Percentage noise reduction increased with increasing iterative power, up to (smooth/sharp kernel) 57.7%/72.5% and 56.3%/70.1% for PCD-scanner and EID-scanner, respectively. For PCD-scanner, FBP- and QIR-reconstructed images featured an almost Gaussian distribution of noise values, whose shape did not appreciably vary with iterative power. Noise maps of CTP404 module showed increased NUI values with increasing iterative power, up to (smooth/sharp kernel) 15.7%/9.2%. QIR-reconstructed images showed limited low-frequency shift of NPS peak frequency. Conclusion PCD-CT allowed appreciably reducing image noise while improving its spatial uniformity. QIR algorithm decreases image noise without modifying its histogram distribution shape, and partly preserving noise texture. Relevance statement This phantom study corroborates the capability of photon-counting detector technology in appreciably reducing CT imaging noise and improving spatial uniformity of noise values, yielding a potential reduction of radiation exposure, though this needs to be assessed in more detail. Key Points First voxelwise characterization of noise for a clinical CT scanner with photon-counting detector technology. Photon-counting detector technology has the capability to appreciably reduce CT imaging noise and improve spatial uniformity of noise values. In photon-counting CT, a model-based iterative reconstruction algorithm (QIR) allows decreasing effectively image noise. This is done without modifying noise histogram distribution shape, while limiting the low-frequency shift of noise power spectrum peak frequency. Graphical Abstract

Digital breast tomosynthesis (DBT) has recently gained interest both for breast cancer screening and diagnosis. Its employment has increased also in conjunction with digital mammography (DM), to improve cancer detection and reduce false positive recall rate. Synthetic mammograms (SMs) reconstructed from DBT data have been introduced to replace DM in the DBT + DM approach, for preserving the benefits of the dual-acquisition modality whilst reducing radiation dose and compression time. Therefore, different DBT models have been commercialized and the effective potential of each system has been investigated. In particular, wide-angle DBT was shown to provide better depth resolution than narrow-angle DBT, while narrow-angle DBT allows better identification of microcalcifications compared to wide-angle DBT. Given the increasing employment of SMs as supplement to DBT, a comparison of image quality between SMs obtained in narrow-angle and wide-angle DBT is of practical interest. Therefore, the aim of this phantom study was to evaluate and compare the image quality of SMs reconstructed from 15° (SM15) and 40° (SM40) DBT in a commercial system. Spatial resolution, noise and contrast properties were evaluated through the modulation transfer function (MTF), noise power spectrum, maps of signal-to-noise ratio (SNR), image contrast, contrast-to-noise ratio (CNR) and contrast-detail (CD) thresholds. SM40 expressed higher MTF than SM15, but also lower SNR and CNR levels. SM15 and SM40 were characterized by slight different texture, and a different behavior in terms of contrast was found. SM15 provided better CD performances than SM40. These results suggest that the employment of wide/narrow-angle DBT + SM images should be optimized based on the specific image task.

Quantitative analyses in nuclear medicine are increasingly used, both for diagnostic and therapeutic purposes. The Partial Volume Effect (PVE) is the most important factor of loss of quantification in Nuclear Medicine, especially for evaluation in Region of Interest (ROI) smaller than the Full Width at Half Maximum (FWHM) of the PSF. The aim of this work is to present a new approach for the correction of PVE, using a post-reconstruction process starting from a mathematical expression, which only requires the knowledge of the FWHM of the final PSF of the imaging system used. After the presentation of the theoretical derivation, the experimental evaluation of this method is performed using a PET/CT hybrid system and acquiring the IEC NEMA phantom with six spherical “hot” ROIs (with diameters of 10, 13, 17, 22, 28, and 37 mm) and a homogeneous “colder” background. In order to evaluate the recovery of quantitative data, the effect of statistical noise (different acquisition times), tomographic reconstruction algorithm with and without time-of-flight (TOF) and different signal-to-background activity concentration ratio (3:1 and 10:1) was studied. The application of the corrective method allows recovering the loss of quantification due to PVE for all sizes of spheres acquired, with a final accuracy less than 17%, for lesion dimensions larger than two FWHM and for acquisition times equal to or greater than two minutes.

Given the inherent characteristics of nonlinearity and nonstationarity of iterative reconstruction algorithms in computed tomography (CT) imaging, this study aimed to perform, for the first time, a voxel-based characterization of noise properties in CT imaging with the ASiR-V and ASiR algorithms as compared with conventional filtered back projection (FBP). Multiple repeated scans of the Catphan-504 phantom were carried out. CT images were reconstructed using FBP and ASiR/ASiR-V with different blending levels of reconstruction (20%, 40%, 60%, 80%, 100%). Noise maps and their nonuniformity index (NUI) were obtained according to the approach proposed by the report of AAPM TG-233. For the homogeneous CTP486 module, ASiR-V/ASiR allowed a noise reduction of up to 63.7%/52.9% relative to FBP. While the noise reduction values of ASiR-V-/ASiR-reconstructed images ranged up to 33.8%/39.9% and 31.2%/35.5% for air and Teflon contrast objects, respectively, these values were approximately 60%/50% for other contrast objects (PMP, LDPE, polystyrene, acrylic, Delrin). Moreover, for all contrast objects but air and Teflon, ASiR-V showed a greater noise reduction potential than ASiR when the blending level was ≥40%. While noise maps of the homogenous CTP486 module showed only a slight spatial variation of noise (NUI < 5.2%) for all reconstruction algorithms, the NUI values of iterative-reconstructed images of the nonhomogeneous CTP404 module increased nonlinearly with blending level and were 19%/15% and 6.7% for pure ASiR-V/ASiR and FBP, respectively. Overall, these results confirm the potential of ASiR-V and ASiR in reducing noise as compared with conventional FBP, suggesting, however, that the use of pure ASiR-V or ASiR might be suboptimal for specific clinical applications.

Background To propose a practical and simple method to individually evaluate the average absorbed dose for digital breast tomosynthesis. Methods The method is based on the estimate of incident air kerma ( k a,i ) on the breast surface. An analytical model was developed to calculate the k a,i from the tube voltage, tube load, breast thickness, x-ray tube yield, and anode-filter combination. A homogeneous phantom was employed to simulate the breast in experimental measurements and to assess the dose-depth relationship. The k a,i values were employed to calculate the “average absorbed breast dose” (2ABD) index. Four mammographic units were used to develop and test our method under many conditions close to clinical settings. The average glandular dose (AGD) calculated following the method described by Dance et al., and the 2ABD computed through our method ( i.e., from the exposure parameters) were compared in a number of conditions. Results A good agreement was obtained between the k a,i computed through our model and that measured under different clinical conditions: discrepancies < 6% were found in all conditions. 2ABD matches with a good accuracy the AGD for a 100% glandular-breast: the minimum, maximum, and mean differences were < 0.1%, 7%, and 2.4%, respectively; the discrepancies increase with decreasing breast glandularity. Conclusions The proposed model, based on only few exposure parameters, represents a simple way to individually calculate an index, 2ABD, which can be interpreted as the average absorbed dose in a homogeneous phantom, approximating a 100% glandular breast. The method could be easily implemented in any mammographic device performing DBT.

The purpose of this study was to investigate the effect of image preprocessing on radiomic features estimation from computed tomography (CT) imaging of locally advanced rectal cancer (LARC). CT images of 20 patients with LARC were used to estimate 105 radiomic features of 7 classes (shape, first-order, GLCM, GLDM, GLRLM, GLSZM, and NGTDM). Radiomic features were estimated for 6 different isotropic resampling voxel sizes, using 10 interpolation algorithms (at fixed bin width) and 6 different bin widths (at fixed interpolation algorithm). The intraclass correlation coefficient (ICC) and the coefficient of variation (CV) were calculated to assess the variability in radiomic features estimation due to preprocessing. A repeated measures correlation analysis was performed to assess any linear correlation between radiomic feature estimate and resampling voxel size or bin width. Reproducibility of radiomic feature estimate, when assessed through ICC analysis, was nominally excellent (ICC>0.9) for shape features, good (0.75

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